From c8dbef2c0f96786feab808ba5946083de023335e Mon Sep 17 00:00:00 2001 From: "Ishan S. Patel" Date: Mon, 30 Jun 2025 14:19:58 -0400 Subject: [PATCH] YACWC --- compare.py | 25 +- deepstream_obj_det_pre_queue.py | 21 +- dump.json | 2 +- min_repro.py | 336 + ml_run.py | 334 + orin.png | Bin 0 -> 294912 bytes report_dynamo_export.sarif | 95638 ++++++++++++++++++++++++++++++ saved.png | Bin 0 -> 265671 bytes short.npz | Bin 0 -> 4713 bytes try_decode.py | 75 +- 10 files changed, 96383 insertions(+), 48 deletions(-) create mode 100644 min_repro.py create mode 100644 ml_run.py create mode 100644 orin.png create mode 100644 report_dynamo_export.sarif create mode 100644 saved.png create mode 100755 short.npz diff --git a/compare.py b/compare.py index 3da58e7..91de438 100644 --- a/compare.py +++ b/compare.py @@ -1,6 +1,9 @@ -import numpy as np import json -datum = np.load('dump.npz.npy') + +import numpy as np + +#datum = np.load('dump.npz.npy') +datum = np.load('dump_so400m.npy') with open('dump.json','r') as rr: @@ -29,25 +32,15 @@ def cosine_sim(emb_in_1, emb_in_2): arr_in_deepstream = np.asarray([y for _,y in emb_dict.items()]) - normed = np.divide(datum.T, np.linalg.norm(datum, axis=1)).T print('_________________________') + +print(len(emb_dict)) +print(len(datum)) for fr, emb in emb_dict.items(): emb1 = np.linalg.norm(emb) emb2 = np.linalg.norm(datum[fr]) -# print( cosine_sim(emb, datum[fr])) + print( cosine_sim(emb, datum[fr])) -print('Deepstream and Actual norm') -print(np.max(np.dot(arr_in_deepstream, normed.T),axis=1)) - -print('_________________________') -for dat in datum: -# print(cosine_sim(dat, datum[0])) - pass - - -#print(cosine_sim(datum[fr], datum[fr+1])) - -#print(cosine_sim(emb_dict[fr], emb_dict[fr+1])) diff --git a/deepstream_obj_det_pre_queue.py b/deepstream_obj_det_pre_queue.py index 4fa53ea..ae72082 100755 --- a/deepstream_obj_det_pre_queue.py +++ b/deepstream_obj_det_pre_queue.py @@ -178,7 +178,7 @@ def embed_results_probe(pad, info, u_data, list_add, frame_num=0): if True: for i in range(tensor_meta.num_output_layers): layer = pyds.get_nvds_LayerInfo(tensor_meta, i) - if layer.layerName == "embedding": + if layer.layerName == "output": ptr = ctypes.cast( pyds.get_ptr(layer.buffer), ctypes.POINTER(ctypes.c_float) @@ -395,8 +395,8 @@ if True: streammux_embed.set_property("width", target_width_embed) streammux_embed.set_property("height", target_height_embed) streammux_embed.set_property("batched-push-timeout", MUXER_BATCH_TIMEOUT_USEC) - streammux_embed.set_property("enable-padding", 1) - streammux_embed.set_property("batch-size", 4) + streammux_embed.set_property("enable-padding", 0) + streammux_embed.set_property("batch-size", 1) nugget_embed = Gst.ElementFactory.make("nvinfer", "primary-inference") nugget_embed.set_property( @@ -426,7 +426,7 @@ if True: # capsfilter.link(tee) nvvidconv.link(tee) - if True: + if False: pipeline.add(queue_detect) pipeline.add(streammux_detect) pipeline.add(nugget_detector) @@ -442,7 +442,7 @@ if True: os.environ["GST_DEBUG_DUMP_DOT_DIR"] = "/tmp" os.putenv("GST_DEBUG_DUMP_DIR_DIR", "/tmp") - if False: + if True: pipeline.add(queue_embed) pipeline.add(streammux_embed) @@ -522,7 +522,13 @@ if True: pass # cleanup pipeline.set_state(Gst.State.NULL) -# return detector_list, embed_list + + # return detector_list, embed_list\\ + out = [detector_list, embed_list ] + import json + with open("dump.json", "w") as ff: + json.dump([out[0], out[1]], ff) + sys.exit() if __name__ == "__main__": @@ -537,6 +543,3 @@ if __name__ == "__main__": import json - with open("dump.json", "w") as ff: - json.dump([out[0], out[1]], ff) - sys.exit() diff --git a/dump.json b/dump.json index e6f9476..bfa346c 100644 --- a/dump.json +++ b/dump.json @@ -1 +1 @@ -[[], []] \ No newline at end of file +[[], [{"frame_number": 0, "vector": [-0.144287109375, 0.34619140625, 0.00439453125, -0.173828125, -0.5966796875, 0.309814453125, 0.01568603515625, -0.481201171875, -0.0948486328125, 0.0217132568359375, -0.122314453125, 0.006591796875, 0.27587890625, 0.19482421875, 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super().__init__() + self.num_heads = num_heads + head_dim = dim // num_heads + if attn_head_dim is not None: + head_dim = attn_head_dim + all_head_dim = head_dim * self.num_heads + self.scale = qk_scale or head_dim**-0.5 + + self.qkv = nn.Linear(dim, all_head_dim * 3, bias=False) + if qkv_bias: + self.q_bias = nn.Parameter(torch.zeros(all_head_dim)) + self.v_bias = nn.Parameter(torch.zeros(all_head_dim)) + else: + self.q_bias = None + self.v_bias = None + + self.attn_drop = nn.Dropout(attn_drop) + self.proj = nn.Linear(all_head_dim, dim) + self.proj_drop = nn.Dropout(proj_drop) + + def forward(self, x): + B, N, C = x.shape + qkv_bias = None + if self.q_bias is not None: + qkv_bias = torch.cat( + ( + self.q_bias, + torch.zeros_like(self.v_bias, requires_grad=False), + self.v_bias, + ) + ) + qkv = F.linear(input=x, weight=self.qkv.weight, bias=qkv_bias) + qkv = qkv.reshape(B, N, 3, self.num_heads, -1).permute(2, 0, 3, 1, 4) + q, k, v = qkv.unbind(0) + + x = F.scaled_dot_product_attention( + q, + k, + v, + dropout_p=self.attn_drop.p if self.training else 0.0, + scale=self.scale, + ) + + x = x.transpose(1, 2).reshape(B, N, -1) + + x = self.proj(x) + x = self.proj_drop(x) + return x + + +class ExplicitAttention(nn.Module): + """ + The explicit, original version of the Attention layer from the VideoMAEv2 codebase. + """ + + def __init__( + self, + dim, + num_heads=8, + qkv_bias=False, + qk_scale=None, + attn_drop=0.0, + proj_drop=0.0, + attn_head_dim=None, + ): + super().__init__() + self.num_heads = num_heads + head_dim = dim // num_heads + if attn_head_dim is not None: + head_dim = attn_head_dim + all_head_dim = head_dim * self.num_heads + self.scale = qk_scale or head_dim**-0.5 + + self.qkv = nn.Linear(dim, all_head_dim * 3, bias=False) + if qkv_bias: + self.q_bias = nn.Parameter(torch.zeros(all_head_dim)) + self.v_bias = nn.Parameter(torch.zeros(all_head_dim)) + else: + self.q_bias = None + self.v_bias = None + + self.attn_drop = nn.Dropout(attn_drop) + self.proj = nn.Linear(all_head_dim, dim) + self.proj_drop = nn.Dropout(proj_drop) + + def forward(self, x): + B, N, C = x.shape + qkv_bias = None + if self.q_bias is not None: + qkv_bias = torch.cat( + ( + self.q_bias, + torch.zeros_like(self.v_bias, requires_grad=False), + self.v_bias, + ) + ) + qkv = F.linear(input=x, weight=self.qkv.weight, bias=qkv_bias) + qkv = qkv.reshape(B, N, 3, self.num_heads, -1).permute(2, 0, 3, 1, 4) + q, k, v = qkv.unbind(0) + + q = q * self.scale + attn = q @ k.transpose(-2, -1) + + attn = attn.softmax(dim=-1) + attn = self.attn_drop(attn) + + x = (attn @ v).transpose(1, 2).reshape(B, N, -1) + + x = self.proj(x) + x = self.proj_drop(x) + + return x + + +class AttentionUsingMHAForward(nn.Module): + def __init__( + self, + dim, + num_heads=8, + qkv_bias=False, + qk_scale=None, + attn_drop=0.0, + proj_drop=0.0, + attn_head_dim=None, + ): + super().__init__() + self.num_heads = num_heads + head_dim = dim // num_heads + if attn_head_dim is not None: + head_dim = attn_head_dim + all_head_dim = head_dim * self.num_heads + self.scale = qk_scale or head_dim**-0.5 + + self.qkv = nn.Linear(dim, all_head_dim * 3, bias=False) + if qkv_bias: + self.q_bias = nn.Parameter(torch.zeros(all_head_dim)) + self.v_bias = nn.Parameter(torch.zeros(all_head_dim)) + else: + self.q_bias = None + self.v_bias = None + + self.attn_drop = nn.Dropout(attn_drop) + self.proj = nn.Linear(all_head_dim, dim) + self.proj_drop = nn.Dropout(proj_drop) + + def forward(self, x): + B, N, C = x.shape + qkv_bias = None + if self.q_bias is not None: + qkv_bias = torch.cat( + ( + self.q_bias, + torch.zeros_like(self.v_bias, requires_grad=False), + self.v_bias, + ) + ) + qkv = F.linear(input=x, weight=self.qkv.weight, bias=qkv_bias) + qkv = qkv.reshape(B, N, 3, self.num_heads, -1).permute(2, 0, 3, 1, 4) + q, k, v = qkv.unbind(0) + + # MHA expects [sequence, batch, embed_dim]. + x_t = x.transpose(0, 1) # => [N, B, C] + + attn_out, _ = F.multi_head_attention_forward( + x_t, + x_t, + x_t, + embed_dim_to_check=C, + num_heads=self.num_heads, + # Since use_separate_proj_weight=False (default), then according to the docs: + # "in_proj_weight will be used, which is a combination of q_proj_weight, k_proj_weight, v_proj_weight." + in_proj_weight=self.qkv.weight, + in_proj_bias=qkv_bias, + bias_k=None, + bias_v=None, + add_zero_attn=False, + dropout_p=self.attn_drop.p, + out_proj_weight=self.proj.weight, + out_proj_bias=self.proj.bias, + training=self.training, + key_padding_mask=None, + need_weights=False, + attn_mask=None, + ) + + # Transpose back to [B, N, C]. + x = attn_out.transpose(0, 1) + + return x + + +def onnx_to_trt(onnx_bytes: bytes) -> bytes: + TRT_LOGGER = trt.Logger(trt.Logger.INFO) + builder = trt.Builder(TRT_LOGGER) + + network = builder.create_network() + parser = trt.OnnxParser(network, TRT_LOGGER) + + parser.parse(onnx_bytes) + + config = builder.create_builder_config() + config.builder_optimization_level = 0 + + engine = builder.build_serialized_network(network, config) + + return engine + + +def build_trt_module(model, x): + onnx_bytes = io.BytesIO() + + torch.onnx.export( + model, + (x,), + onnx_bytes, + export_params=True, + opset_version=17, + do_constant_folding=True, + input_names=["x"], + output_names=["y"], + ) + + trt_engine = onnx_to_trt(onnx_bytes.getvalue()) + return trt_engine + + + +#@torch.inference_mode() +#def main(): +with torch.no_grad(): + torch.manual_seed(0) + + EMB_DIM = 384 + x = torch.rand((6, 1568, EMB_DIM)) + + explicit_attention = ExplicitAttention(EMB_DIM) + sdpa = AttentionUsingScaledDotProduct(EMB_DIM) + mha_fwd = AttentionUsingMHAForward(EMB_DIM) + + # Use the same params for all. + sdpa.load_state_dict(explicit_attention.state_dict()) + mha_fwd.load_state_dict(explicit_attention.state_dict()) + + sdpa_torch_y = sdpa(x) + explicit_attention_torch_y = explicit_attention(x) + mha_fwd_torch_y = mha_fwd(x) + + print( + "Torch: [explicit<->sdpa] Is allclose?", + sdpa_torch_y.allclose(explicit_attention_torch_y, atol=0.0001), + ) + print( + "Torch: [explicit<->mha_fwd] Is allclose?", + mha_fwd_torch_y.allclose(explicit_attention_torch_y, atol=0.0001), + ) + print( + "Torch: [explicit<->sdpa] Total difference:", + (sdpa_torch_y - explicit_attention_torch_y).abs().sum(), + ) + print( + "Torch: [explicit<->mha_fwd] Total difference:", + (mha_fwd_torch_y - explicit_attention_torch_y).abs().sum(), + ) + assert sdpa_torch_y.allclose(explicit_attention_torch_y, atol=0.0001), "Precheck" + assert mha_fwd_torch_y.allclose(explicit_attention_torch_y, atol=0.0001), "Precheck" +# %% + + explicit_attention_trt = build_trt_module(explicit_attention, x) + with open('explicit_attention_trt.trt','wb') as ea: + ea.write(explicit_attention_trt) + + sdpa_trt_model = build_trt_module(sdpa, x) + with open('sdpa_trt.trt','wb') as ea: + ea.write(sdpa_trt_model) + + mha_fwd_trt_model = build_trt_module(mha_fwd, x) + with open('mha_trt.trt','wb') as ea: + ea.write(mha_fwd_trt_model) +# %% + + + +# %% + explicit_attention_y = explicit_attention_trt(x.cuda()) + sdpa_y = sdpa_trt_model(x.cuda()) + mha_fwd_y = mha_fwd_trt_model(x.cuda()) + + print( + "TRT: [explicit<->sdpa] Is allclose?", + sdpa_y.allclose(explicit_attention_y, atol=0.0001), + ) + print( + "TRT: [explicit<->sdpa] Total difference:", + (sdpa_y - explicit_attention_y).abs().sum(), + ) + + print( + "TRT: [explicit<->mha_fwd] Is allclose?", + mha_fwd_y.allclose(explicit_attention_y, atol=0.0001), + ) + print( + "TRT: [explicit<->mha_fwd] Total difference:", + (mha_fwd_y - explicit_attention_y).abs().sum(), + ) + + print("TRT: Explicit Attention:", explicit_attention_y[0, 0, :32]) + print("TRT: Scaled Dot Product Attention:", sdpa_y[0, 0, :32]) + print("TRT: MHA Forward:", mha_fwd_y[0, 0, :32]) + + +if __name__ == "__main__": + main() diff --git a/ml_run.py b/ml_run.py new file mode 100644 index 0000000..62e76dc --- /dev/null +++ b/ml_run.py @@ -0,0 +1,334 @@ +import sys + +sys.path.insert(0, "/home/thebears/source/models/yolov7") +import time +from datetime import datetime +import cv2 +import numpy as np +from pymediainfo import MediaInfo +import inspect +import open_clip +import sys +import torch +import yaml +from models.experimental import attempt_load +from utils.general import check_img_size, non_max_suppression +from torchvision import transforms + +device = torch.device("cuda") + +pretrained_name = "webli" +#model_name = "ViT-SO400M-16-SigLIP2-512" +#model_name = 'ViT-SO400M-14-SigLIP-384' + +clip_model, _, clip_preprocess_og = open_clip.create_model_and_transforms( + model_name, pretrained=pretrained_name +) +tokenizer = open_clip.get_tokenizer('hf-hub:timm/'+model_name) +labels_list = ["A bird with a brown head and black body", "A bird with a black head and black body"] +text = tokenizer(labels_list, context_length=clip_model.context_length) + +import torch.nn.functional as F +with torch.no_grad(): + text_features = clip_model.encode_text(text).detach().cpu() + text_features = F.normalize(text_features, dim=-1).detach().cpu() +# %% + +clip_model = clip_model.half().to(device) +clip_dtype = next(clip_model.parameters()).dtype +clip_img_size = clip_preprocess_og.transforms[0].size +_ = clip_model.encode_image( + torch.rand(1, 3, *clip_img_size, dtype=clip_dtype, device=device) +) +clip_preprocess = transforms.Compose([clip_preprocess_og.transforms[x] for x in [0, 3]]) + +det_root_path = "/home/thebears/source/model_weights" +det_model_weights_root = os.path.join(det_root_path, "yolov7") +det_model_weights_path = os.path.join(det_model_weights_root, "best.pt") +det_data_yaml_path = os.path.join(det_model_weights_root, "inaturalist.yaml") +det_model = attempt_load(det_model_weights_path, map_location=device) +det_model = det_model.half().to(device) + +det_dtype = next(det_model.parameters()).dtype +det_imgsz = 1280 +det_stride = int(det_model.stride.max()) +det_imgsz = check_img_size(det_imgsz, s=det_stride) +_ = det_model(torch.zeros(1, 3, det_imgsz, det_imgsz, dtype=det_dtype).to(device)) + +with open(det_data_yaml_path, "r") as ff: + det_model_info = yaml.safe_load(ff) + det_labels = det_model_info["names"] + + + + +array_score = clip_array +frame_numbers = [x[0] for x in array_score] +frame_values = [x[1] for x in array_score] +frame_as_tensor = ( + torch.from_numpy(np.stack(frame_values)[:, :, :, 0:3]) + .to(torch.float16) + .to(device) + .permute([0, 3, 1, 2]) +) +def score_frames_det(array_score): + frame_numbers = [x[0] for x in array_score] + frame_values = [x[1] for x in array_score] + frame_as_tensor = ( + torch.from_numpy(np.stack(frame_values)[:, :, :, 0:3]) + .to(torch.float16) + .to(device) + .permute([0, 3, 1, 2]) + ) + + with torch.no_grad(): + frame_for_model = det_vid_preprocess(frame_as_tensor).div(255)[:,[2,1,0],:,:] + det_preds = det_model(frame_for_model)[0] + det_pred_post_nms = non_max_suppression(det_preds,0.25, 0.5) + det_cpu_pred = [x.detach().cpu().numpy() for x in det_pred_post_nms] + +# frame_for_clip = clip_preprocess(frame_as_tensor[:,[0,1,2],:,:]) +# clip_pred = clip_model.encode_image(frame_for_clip).detach().cpu().numpy() + + return {"det": det_cpu_pred, "fr#": frame_numbers} + +def score_frames_clip(array_score): + frame_numbers = [x[0] for x in array_score] + frame_values = [x[1] for x in array_score] + frame_as_tensor = ( + torch.from_numpy(np.stack(frame_values)[:, :, :, 0:3]) + .to(torch.float16) + .to(device) + .permute([0, 3, 1, 2]) + ) + + with torch.no_grad(): +# frame_for_model = det_vid_preprocess(frame_as_tensor).div(255)[:,[2,1,0],:,:] +# det_preds = det_model(frame_for_model)[0] +# det_pred_post_nms = non_max_suppression(det_preds,0.25, 0.5) +# det_cpu_pred = [x.detach().cpu().numpy() for x in det_pred_post_nms] + + frame_for_clip = clip_preprocess(frame_as_tensor[:,[0,1,2],:,:]) + clip_pred = clip_model.encode_image(frame_for_clip).detach().cpu().numpy() + + + return {"clip": clip_pred, "fr#": frame_numbers} + + + + + +with torch.no_grad(): + frame_for_model = det_vid_preprocess(frame_as_tensor).div(255)[:,[2,1,0],:,:] + det_preds = det_model(frame_for_model)[0] + det_pred_post_nms = non_max_suppression(det_preds,0.25, 0.5) + det_cpu_pred = [x.detach().cpu().numpy() for x in det_pred_post_nms] + frame_for_clip = frame_as_tensor.div(255) + + frame_for_clip = clip_preprocess(frame_for_clip[:,(2,1,0),:,:]) + clip_pred = clip_model.encode_image(frame_for_clip).detach().cpu().numpy() + +score_result = {"det": det_cpu_pred, "clip": clip_pred, "fr#": frame_numbers} + + +clip_orin = F.normalize(torch.from_numpy(score_result['clip'])) +clip_tree = F.normalize(torch.from_numpy(saved_emb)) +print(np.dot(clip_tree, clip_orin.T)) + + +mvo = mean_vec_out[0] +ooo = frame_for_clip[0].cpu().numpy() + +plt.close('all') +fig = plt.figure() + +ax1 = fig.add_subplot(3,2,1) +ax1.imshow(mvo[0]) +ax2 = fig.add_subplot(3,2,2) +ax2.imshow(ooo[0]) +ax3 = fig.add_subplot(3,2,3) +ax3.imshow(mvo[1]) +ax4 = fig.add_subplot(3,2,4) +ax4.imshow(ooo[1]) +ax5 = fig.add_subplot(3,2,5) +ax5.imshow(mvo[2]) +ax6 = fig.add_subplot(3,2,6) +ax6.imshow(ooo[2]) +fig.show() + +# %% + + +raw_vec_out +mean_vec_out + +# %% +file_to_score = "/home/thebears/source/ml_code/short.mp4" +vec_file = '/home/thebears/source/ml_code/short.npz' +out = np.load(vec_file) + +mean_vec_path = '/home/thebears/source/ml_code/as_np_mean.npy' +mean_vec_out = np.load(mean_vec_path) + +raw_vec_path = '/home/thebears/source/ml_code/as_np_raw.npy' +raw_vec_out = np.load(raw_vec_path) + +saved_fr = list(out['frame_numbers']) +saved_emb = out['embeds'] +import numpy as np + + + +def get_video_info(file_path): + file_info = MediaInfo.parse(file_path) + video_info = None + frame_count = 0 + if len(file_info.video_tracks) > 0: video_info = file_info.video_tracks[0] + + video_info.frame_count = int(video_info.frame_count) + return video_info + + +video_info = get_video_info(file_to_score) +vid_decoder = "h264parse" +if video_info.format.lower() == "HEVC".lower(): + vid_decoder = "h265parse" + + +gst_cmd = "filesrc location={file_to_score} ! qtdemux name=demux demux.video_0 ! queue ! {vid_decoder} ! nvv4l2decoder ! nvvidconv ! videoscale method=1 add-borders=false ! video/x-raw,width=1280,height=1280 ! appsink sync=false".format( + file_to_score=file_to_score, vid_decoder=vid_decoder +) + +# gst_cmd = "filesrc location={file_to_score} ! qtdemux name=demux demux.video_0 ! queue ! {vid_decoder} ! nvv4l2decoder ! nvvidconv ! videoscale method=1 add-borders=false ! appsink sync=false".format(file_to_score=file_to_score, vid_decoder=vid_decoder) + +cap_handle = cv2.VideoCapture(gst_cmd, cv2.CAP_GSTREAMER) + +target_max = det_imgsz +vid_h = video_info.height +vid_w = video_info.width + +if vid_h > vid_w: + target_h = target_max + target_w = target_max * vid_w / vid_h +elif vid_h == vid_w: + target_h = target_max + target_w = target_max +elif vid_h < vid_w: + target_h = target_max * vid_h / vid_w + target_w = target_max + +target_h = int(target_h) +target_w = int(target_w) + +pad_amt = [None, None, None, None] +if target_w % det_stride != 0: + off = det_stride - target_w % det_stride + new_w = target_w + off + pad_diff = new_w - target_w + pad_left = round(pad_diff / 2) + pad_right = pad_diff - pad_left + pad_amt[0] = pad_left + pad_amt[2] = pad_right +else: + pad_amt[0] = 0 + pad_amt[2] = 0 + +if target_h % det_stride != 0: + off = det_stride - target_h % det_stride + new_h = target_h + off + pad_diff = new_h - target_h + pad_up = round(pad_diff / 2) + pad_down = pad_diff - pad_up + pad_amt[1] = pad_up + pad_amt[3] = pad_down +else: + pad_amt[1] = 0 + pad_amt[3] = 0 + + +det_vid_preprocess = transforms.Compose( + [transforms.Resize((target_h, target_w)), transforms.Pad(pad_amt, fill=127)] +) + +batch_size = 6 +clip_interval = 10 +array_score = list() +final_output = dict() +final_output["start_score_time"] = time.time() +final_output["num_frames"] = video_info.frame_count +st = time.time() +frame_numbers = list() +det_results = list() +clip_results = list() + +clip_array = list() + +for i in range(video_info.frame_count): + success, frame_matrix = cap_handle.read() + + clip_array.append((i, frame_matrix)) + + if not success: + break + + + array_score.append((i, frame_matrix)) + + if len(array_score) >= batch_size: + score_result = score_frames(array_score) + + + det_results.extend(score_result["det"]) + clip_results.extend(score_result["clip"]) + frame_numbers.extend(score_result["fr#"]) + array_score = list() + + if not (i % clip_interval): + print('do_clip') + +if len(array_score) > 0: + score_result = score_frames(array_score) + det_results.extend(score_result["det"]) + clip_results.extend(score_result["clip"]) + frame_numbers.extend(score_result["fr#"]) + +cap_handle.release() +et = time.time() + +final_output["end_score_time"] = time.time() +final_output["video"] = { + "w": vid_w, + "h": vid_h, + "path": file_to_score, + "target_w": target_w, + "target_h": target_h, + "pad_amt": pad_amt, +} + +try: + final_output['scoring_fps'] = final_output['num_frames']/ (final_output['end_score_time'] - final_output['start_score_time']) +except Exception as e: + pass + +final_output['scores'] = list() + +for frame_number, frame in zip(frame_numbers, det_results): + cframe_dict = dict() + cframe_dict['frame'] = frame_number + cframe_dict['score_number'] = frame_number + cframe_dict['detections'] = list() + + for det in frame: + data = dict() + data['coords'] = [float(x) for x in list(det[0:4])] + data['score'] = float(det[4]) + data['idx'] = int(det[5]) + + try: + data['name'] = det_labels[data['idx']] + except: + data['name'] = 'Code failed' + + cframe_dict['detections'].append(data) + + final_output['scores'].append(cframe_dict) diff --git a/orin.png b/orin.png new file mode 100644 index 0000000000000000000000000000000000000000..a5334b8e4951ae17445d8f6e1efa1f780732efd0 GIT binary patch literal 294912 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"kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":1625 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0015", + "stacks":[] + }, + { + "message":{ + "markdown":"Skipped p_trunk_attn_pool_latent: not a call_function.\n\n## Additional Message:\n\n## Function Signature\n### Function Signature _TypePromotionInterpreter.run_node\n- self: \n- node: fx.Node(p_trunk_attn_pool_latent)[placeholder]:Tensor(f32[1, 1, 1024])\n## Return values\nTensor(f32[1, 1, 1024])", + "text":"Skipped p_trunk_attn_pool_latent: not a call_function." + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":1625 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0015", + "stacks":[] + }, + { + "message":{ + "markdown":"Skipped p_trunk_patch_embed_proj_weight: not a call_function.\n\n## Additional Message:\n\n## Function Signature\n### Function Signature _TypePromotionInterpreter.run_node\n- self: \n- node: fx.Node(p_trunk_patch_embed_proj_weight)[placeholder]:Tensor(f32[1024, 3, 16, 16])\n## Return values\nTensor(f32[1024, 3, 16, 16])", + "text":"Skipped p_trunk_patch_embed_proj_weight: not a call_function." + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":1625 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0015", + "stacks":[] + }, + { + "message":{ + "markdown":"Skipped p_trunk_patch_embed_proj_bias: not a call_function.\n\n## Additional Message:\n\n## Function Signature\n### Function Signature _TypePromotionInterpreter.run_node\n- self: \n- node: fx.Node(p_trunk_patch_embed_proj_bias)[placeholder]:Tensor(f32[1024])\n## Return values\nTensor(f32[1024])", + "text":"Skipped p_trunk_patch_embed_proj_bias: not a call_function." + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":1625 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0015", + "stacks":[] + }, + { + "message":{ + "markdown":"Skipped p_getattr_l__self___trunk_blocks___0___norm1_weight: not a call_function.\n\n## Additional Message:\n\n## Function Signature\n### Function Signature _TypePromotionInterpreter.run_node\n- self: \n- node: fx.Node(p_getattr_l__self___trunk_blocks___0___norm1_weight)[placeholder]:Tensor(f32[1024])\n## Return values\nTensor(f32[1024])", + "text":"Skipped p_getattr_l__self___trunk_blocks___0___norm1_weight: not a call_function." + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":1625 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0015", + "stacks":[] + }, + { + "message":{ + "markdown":"Skipped p_getattr_l__self___trunk_blocks___0___norm1_bias: not a call_function.\n\n## Additional Message:\n\n## Function Signature\n### Function Signature _TypePromotionInterpreter.run_node\n- self: \n- node: fx.Node(p_getattr_l__self___trunk_blocks___0___norm1_bias)[placeholder]:Tensor(f32[1024])\n## Return values\nTensor(f32[1024])", + "text":"Skipped p_getattr_l__self___trunk_blocks___0___norm1_bias: not a call_function." + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":1625 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0015", + "stacks":[] + }, + { + "message":{ + "markdown":"Skipped p_getattr_l__self___trunk_blocks___0___attn_qkv_weight: not a call_function.\n\n## Additional Message:\n\n## Function Signature\n### Function Signature _TypePromotionInterpreter.run_node\n- self: \n- node: fx.Node(p_getattr_l__self___trunk_blocks___0___attn_qkv_weight)[placeholder]:Tensor(f32[3072, 1024])\n## Return values\nTensor(f32[3072, 1024])", + "text":"Skipped p_getattr_l__self___trunk_blocks___0___attn_qkv_weight: not a call_function." + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":1625 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0015", + "stacks":[] + }, + { + "message":{ + "markdown":"Skipped p_getattr_l__self___trunk_blocks___0___attn_qkv_bias: not a call_function.\n\n## Additional Message:\n\n## Function Signature\n### Function Signature _TypePromotionInterpreter.run_node\n- self: \n- node: fx.Node(p_getattr_l__self___trunk_blocks___0___attn_qkv_bias)[placeholder]:Tensor(f32[3072])\n## Return values\nTensor(f32[3072])", + "text":"Skipped p_getattr_l__self___trunk_blocks___0___attn_qkv_bias: not a call_function." + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":1625 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0015", + "stacks":[] + }, + { + "message":{ + "markdown":"Skipped p_getattr_l__self___trunk_blocks___0___attn_proj_weight: not a call_function.\n\n## Additional Message:\n\n## Function Signature\n### Function Signature _TypePromotionInterpreter.run_node\n- self: \n- node: fx.Node(p_getattr_l__self___trunk_blocks___0___attn_proj_weight)[placeholder]:Tensor(f32[1024, 1024])\n## Return values\nTensor(f32[1024, 1024])", + "text":"Skipped p_getattr_l__self___trunk_blocks___0___attn_proj_weight: not a call_function." + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":1625 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0015", + "stacks":[] + }, + { + "message":{ + "markdown":"Skipped p_getattr_l__self___trunk_blocks___0___attn_proj_bias: not a call_function.\n\n## Additional Message:\n\n## Function Signature\n### Function Signature _TypePromotionInterpreter.run_node\n- self: \n- node: fx.Node(p_getattr_l__self___trunk_blocks___0___attn_proj_bias)[placeholder]:Tensor(f32[1024])\n## Return values\nTensor(f32[1024])", + "text":"Skipped p_getattr_l__self___trunk_blocks___0___attn_proj_bias: not a call_function." + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":1625 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0015", + "stacks":[] + }, + { + "message":{ + "markdown":"Skipped p_getattr_l__self___trunk_blocks___0___norm2_weight: not a call_function.\n\n## Additional Message:\n\n## Function Signature\n### Function Signature _TypePromotionInterpreter.run_node\n- self: \n- node: fx.Node(p_getattr_l__self___trunk_blocks___0___norm2_weight)[placeholder]:Tensor(f32[1024])\n## Return values\nTensor(f32[1024])", + "text":"Skipped p_getattr_l__self___trunk_blocks___0___norm2_weight: not a call_function." + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":1625 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0015", + "stacks":[] + }, + { + "message":{ + "markdown":"Skipped p_getattr_l__self___trunk_blocks___0___norm2_bias: not a call_function.\n\n## Additional Message:\n\n## Function Signature\n### Function Signature _TypePromotionInterpreter.run_node\n- self: \n- node: fx.Node(p_getattr_l__self___trunk_blocks___0___norm2_bias)[placeholder]:Tensor(f32[1024])\n## Return values\nTensor(f32[1024])", + "text":"Skipped p_getattr_l__self___trunk_blocks___0___norm2_bias: not a call_function." + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":1625 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0015", + "stacks":[] + }, + { + "message":{ + "markdown":"Skipped p_getattr_l__self___trunk_blocks___0___mlp_fc1_weight: not a call_function.\n\n## Additional Message:\n\n## Function Signature\n### Function Signature _TypePromotionInterpreter.run_node\n- self: \n- node: fx.Node(p_getattr_l__self___trunk_blocks___0___mlp_fc1_weight)[placeholder]:Tensor(f32[4096, 1024])\n## Return values\nTensor(f32[4096, 1024])", + "text":"Skipped p_getattr_l__self___trunk_blocks___0___mlp_fc1_weight: not a call_function." + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":1625 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0015", + "stacks":[] + }, + { + "message":{ + "markdown":"Skipped p_getattr_l__self___trunk_blocks___0___mlp_fc1_bias: not a call_function.\n\n## Additional Message:\n\n## Function Signature\n### Function Signature _TypePromotionInterpreter.run_node\n- self: \n- node: fx.Node(p_getattr_l__self___trunk_blocks___0___mlp_fc1_bias)[placeholder]:Tensor(f32[4096])\n## Return values\nTensor(f32[4096])", + "text":"Skipped p_getattr_l__self___trunk_blocks___0___mlp_fc1_bias: not a call_function." + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":1625 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0015", + "stacks":[] + }, + { + "message":{ + "markdown":"Skipped p_getattr_l__self___trunk_blocks___0___mlp_fc2_weight: not a call_function.\n\n## Additional Message:\n\n## Function Signature\n### Function Signature _TypePromotionInterpreter.run_node\n- self: \n- node: fx.Node(p_getattr_l__self___trunk_blocks___0___mlp_fc2_weight)[placeholder]:Tensor(f32[1024, 4096])\n## Return values\nTensor(f32[1024, 4096])", + "text":"Skipped p_getattr_l__self___trunk_blocks___0___mlp_fc2_weight: not a call_function." + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":1625 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0015", + "stacks":[] + }, + { + "message":{ + "markdown":"Skipped p_getattr_l__self___trunk_blocks___0___mlp_fc2_bias: not a call_function.\n\n## Additional Message:\n\n## Function Signature\n### Function Signature _TypePromotionInterpreter.run_node\n- self: \n- node: fx.Node(p_getattr_l__self___trunk_blocks___0___mlp_fc2_bias)[placeholder]:Tensor(f32[1024])\n## Return values\nTensor(f32[1024])", + "text":"Skipped p_getattr_l__self___trunk_blocks___0___mlp_fc2_bias: not a call_function." + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":1625 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0015", + "stacks":[] + }, + { + "message":{ + "markdown":"Skipped p_getattr_l__self___trunk_blocks___1___norm1_weight: not a call_function.\n\n## Additional Message:\n\n## Function Signature\n### Function Signature _TypePromotionInterpreter.run_node\n- self: \n- node: fx.Node(p_getattr_l__self___trunk_blocks___1___norm1_weight)[placeholder]:Tensor(f32[1024])\n## Return values\nTensor(f32[1024])", + "text":"Skipped p_getattr_l__self___trunk_blocks___1___norm1_weight: not a call_function." + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":1625 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0015", + "stacks":[] + }, + { + "message":{ + "markdown":"Skipped p_getattr_l__self___trunk_blocks___1___norm1_bias: not a call_function.\n\n## Additional Message:\n\n## Function Signature\n### Function Signature _TypePromotionInterpreter.run_node\n- self: \n- node: fx.Node(p_getattr_l__self___trunk_blocks___1___norm1_bias)[placeholder]:Tensor(f32[1024])\n## Return values\nTensor(f32[1024])", + "text":"Skipped p_getattr_l__self___trunk_blocks___1___norm1_bias: not a call_function." + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + 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"uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":1625 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0015", + "stacks":[] + }, + { + "message":{ + "markdown":"Skipped p_getattr_l__self___trunk_blocks___1___attn_qkv_bias: not a call_function.\n\n## Additional Message:\n\n## Function Signature\n### Function Signature _TypePromotionInterpreter.run_node\n- self: \n- node: fx.Node(p_getattr_l__self___trunk_blocks___1___attn_qkv_bias)[placeholder]:Tensor(f32[3072])\n## Return values\nTensor(f32[3072])", + "text":"Skipped p_getattr_l__self___trunk_blocks___1___attn_qkv_bias: not a call_function." + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":1625 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0015", + "stacks":[] + }, + { + "message":{ + "markdown":"Skipped p_getattr_l__self___trunk_blocks___1___attn_proj_weight: not a call_function.\n\n## Additional Message:\n\n## Function Signature\n### Function Signature _TypePromotionInterpreter.run_node\n- self: \n- node: fx.Node(p_getattr_l__self___trunk_blocks___1___attn_proj_weight)[placeholder]:Tensor(f32[1024, 1024])\n## Return values\nTensor(f32[1024, 1024])", + "text":"Skipped p_getattr_l__self___trunk_blocks___1___attn_proj_weight: not a call_function." + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":1625 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0015", + "stacks":[] + }, + { + "message":{ + "markdown":"Skipped p_getattr_l__self___trunk_blocks___1___attn_proj_bias: not a call_function.\n\n## Additional Message:\n\n## Function Signature\n### Function Signature _TypePromotionInterpreter.run_node\n- self: \n- node: fx.Node(p_getattr_l__self___trunk_blocks___1___attn_proj_bias)[placeholder]:Tensor(f32[1024])\n## Return values\nTensor(f32[1024])", + "text":"Skipped p_getattr_l__self___trunk_blocks___1___attn_proj_bias: not a call_function." + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":1625 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0015", + "stacks":[] + }, + { + "message":{ + "markdown":"Skipped p_getattr_l__self___trunk_blocks___1___norm2_weight: not a call_function.\n\n## Additional Message:\n\n## Function Signature\n### Function Signature _TypePromotionInterpreter.run_node\n- self: \n- node: fx.Node(p_getattr_l__self___trunk_blocks___1___norm2_weight)[placeholder]:Tensor(f32[1024])\n## Return values\nTensor(f32[1024])", + "text":"Skipped p_getattr_l__self___trunk_blocks___1___norm2_weight: not a call_function." + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":1625 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0015", + "stacks":[] + }, + { + "message":{ + "markdown":"Skipped p_getattr_l__self___trunk_blocks___1___norm2_bias: not a call_function.\n\n## Additional Message:\n\n## Function Signature\n### Function Signature _TypePromotionInterpreter.run_node\n- self: \n- node: fx.Node(p_getattr_l__self___trunk_blocks___1___norm2_bias)[placeholder]:Tensor(f32[1024])\n## Return values\nTensor(f32[1024])", + "text":"Skipped p_getattr_l__self___trunk_blocks___1___norm2_bias: not a call_function." + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":1625 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0015", + "stacks":[] + }, + { + "message":{ + "markdown":"Skipped p_getattr_l__self___trunk_blocks___1___mlp_fc1_weight: not a call_function.\n\n## Additional Message:\n\n## Function Signature\n### Function Signature _TypePromotionInterpreter.run_node\n- self: \n- node: fx.Node(p_getattr_l__self___trunk_blocks___1___mlp_fc1_weight)[placeholder]:Tensor(f32[4096, 1024])\n## Return values\nTensor(f32[4096, 1024])", + "text":"Skipped p_getattr_l__self___trunk_blocks___1___mlp_fc1_weight: not a call_function." + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":1625 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0015", + "stacks":[] + }, + { + "message":{ + "markdown":"Skipped p_getattr_l__self___trunk_blocks___1___mlp_fc1_bias: not a call_function.\n\n## Additional Message:\n\n## Function Signature\n### Function Signature _TypePromotionInterpreter.run_node\n- self: \n- node: fx.Node(p_getattr_l__self___trunk_blocks___1___mlp_fc1_bias)[placeholder]:Tensor(f32[4096])\n## Return values\nTensor(f32[4096])", + "text":"Skipped p_getattr_l__self___trunk_blocks___1___mlp_fc1_bias: not a call_function." + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":1625 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0015", + "stacks":[] + }, + { + "message":{ + "markdown":"Skipped p_getattr_l__self___trunk_blocks___1___mlp_fc2_weight: not a call_function.\n\n## Additional Message:\n\n## Function Signature\n### Function Signature _TypePromotionInterpreter.run_node\n- self: \n- node: fx.Node(p_getattr_l__self___trunk_blocks___1___mlp_fc2_weight)[placeholder]:Tensor(f32[1024, 4096])\n## Return values\nTensor(f32[1024, 4096])", + "text":"Skipped p_getattr_l__self___trunk_blocks___1___mlp_fc2_weight: not a call_function." + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":1625 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0015", + "stacks":[] + }, + { + "message":{ + "markdown":"Skipped p_getattr_l__self___trunk_blocks___1___mlp_fc2_bias: not a call_function.\n\n## Additional Message:\n\n## Function Signature\n### Function Signature _TypePromotionInterpreter.run_node\n- self: \n- node: fx.Node(p_getattr_l__self___trunk_blocks___1___mlp_fc2_bias)[placeholder]:Tensor(f32[1024])\n## Return values\nTensor(f32[1024])", + "text":"Skipped p_getattr_l__self___trunk_blocks___1___mlp_fc2_bias: not a call_function." + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":1625 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0015", + "stacks":[] + }, + { + "message":{ + "markdown":"Skipped p_getattr_l__self___trunk_blocks___2___norm1_weight: not a call_function.\n\n## Additional Message:\n\n## Function Signature\n### Function Signature _TypePromotionInterpreter.run_node\n- self: \n- node: fx.Node(p_getattr_l__self___trunk_blocks___2___norm1_weight)[placeholder]:Tensor(f32[1024])\n## Return values\nTensor(f32[1024])", + "text":"Skipped p_getattr_l__self___trunk_blocks___2___norm1_weight: not a call_function." + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":1625 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0015", + "stacks":[] + }, + { + "message":{ + "markdown":"Skipped p_getattr_l__self___trunk_blocks___2___norm1_bias: not a call_function.\n\n## Additional Message:\n\n## Function Signature\n### Function Signature _TypePromotionInterpreter.run_node\n- self: \n- node: fx.Node(p_getattr_l__self___trunk_blocks___2___norm1_bias)[placeholder]:Tensor(f32[1024])\n## Return values\nTensor(f32[1024])", + "text":"Skipped p_getattr_l__self___trunk_blocks___2___norm1_bias: not a call_function." + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":1625 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0015", + "stacks":[] + }, + { + "message":{ + "markdown":"Skipped p_getattr_l__self___trunk_blocks___2___attn_qkv_weight: not a call_function.\n\n## Additional Message:\n\n## Function Signature\n### Function Signature _TypePromotionInterpreter.run_node\n- self: \n- node: fx.Node(p_getattr_l__self___trunk_blocks___2___attn_qkv_weight)[placeholder]:Tensor(f32[3072, 1024])\n## Return values\nTensor(f32[3072, 1024])", + "text":"Skipped p_getattr_l__self___trunk_blocks___2___attn_qkv_weight: not a call_function." + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":1625 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0015", + "stacks":[] + }, + { + "message":{ + "markdown":"Skipped p_getattr_l__self___trunk_blocks___2___attn_qkv_bias: not a call_function.\n\n## Additional Message:\n\n## Function Signature\n### Function Signature _TypePromotionInterpreter.run_node\n- self: \n- node: fx.Node(p_getattr_l__self___trunk_blocks___2___attn_qkv_bias)[placeholder]:Tensor(f32[3072])\n## Return values\nTensor(f32[3072])", + "text":"Skipped p_getattr_l__self___trunk_blocks___2___attn_qkv_bias: not a call_function." + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":1625 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0015", + "stacks":[] + }, + { + "message":{ + "markdown":"Skipped p_getattr_l__self___trunk_blocks___2___attn_proj_weight: not a call_function.\n\n## Additional Message:\n\n## Function Signature\n### Function Signature _TypePromotionInterpreter.run_node\n- self: \n- node: fx.Node(p_getattr_l__self___trunk_blocks___2___attn_proj_weight)[placeholder]:Tensor(f32[1024, 1024])\n## Return values\nTensor(f32[1024, 1024])", + "text":"Skipped p_getattr_l__self___trunk_blocks___2___attn_proj_weight: not a call_function." + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":1625 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0015", + "stacks":[] + }, + { + "message":{ + "markdown":"Skipped p_getattr_l__self___trunk_blocks___2___attn_proj_bias: not a call_function.\n\n## Additional Message:\n\n## Function Signature\n### Function Signature _TypePromotionInterpreter.run_node\n- self: \n- node: fx.Node(p_getattr_l__self___trunk_blocks___2___attn_proj_bias)[placeholder]:Tensor(f32[1024])\n## Return values\nTensor(f32[1024])", + "text":"Skipped p_getattr_l__self___trunk_blocks___2___attn_proj_bias: not a call_function." + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + 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] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":1625 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0015", + "stacks":[] + }, + { + "message":{ + "markdown":"Skipped p_getattr_l__self___trunk_blocks___3___attn_qkv_weight: not a call_function.\n\n## Additional Message:\n\n## Function Signature\n### Function Signature _TypePromotionInterpreter.run_node\n- self: \n- node: fx.Node(p_getattr_l__self___trunk_blocks___3___attn_qkv_weight)[placeholder]:Tensor(f32[3072, 1024])\n## Return values\nTensor(f32[3072, 1024])", + "text":"Skipped p_getattr_l__self___trunk_blocks___3___attn_qkv_weight: not a call_function." + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":1625 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0015", + "stacks":[] + }, + { + "message":{ + "markdown":"Skipped p_getattr_l__self___trunk_blocks___3___attn_qkv_bias: not a call_function.\n\n## Additional Message:\n\n## Function Signature\n### Function Signature _TypePromotionInterpreter.run_node\n- self: \n- node: fx.Node(p_getattr_l__self___trunk_blocks___3___attn_qkv_bias)[placeholder]:Tensor(f32[3072])\n## Return values\nTensor(f32[3072])", + "text":"Skipped p_getattr_l__self___trunk_blocks___3___attn_qkv_bias: not a call_function." + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":1625 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0015", + "stacks":[] + }, + { + "message":{ + "markdown":"Skipped p_getattr_l__self___trunk_blocks___3___attn_proj_weight: not a call_function.\n\n## Additional Message:\n\n## Function Signature\n### Function Signature _TypePromotionInterpreter.run_node\n- self: \n- node: fx.Node(p_getattr_l__self___trunk_blocks___3___attn_proj_weight)[placeholder]:Tensor(f32[1024, 1024])\n## 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fx.Node(p_getattr_l__self___trunk_blocks___3___attn_proj_bias)[placeholder]:Tensor(f32[1024])\n## Return values\nTensor(f32[1024])", + "text":"Skipped p_getattr_l__self___trunk_blocks___3___attn_proj_bias: not a call_function." + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":1625 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0015", + "stacks":[] + }, + { + "message":{ + "markdown":"Skipped p_getattr_l__self___trunk_blocks___3___norm2_weight: not a call_function.\n\n## Additional Message:\n\n## Function Signature\n### Function Signature _TypePromotionInterpreter.run_node\n- self: \n- node: fx.Node(p_getattr_l__self___trunk_blocks___3___norm2_weight)[placeholder]:Tensor(f32[1024])\n## Return values\nTensor(f32[1024])", + "text":"Skipped p_getattr_l__self___trunk_blocks___3___norm2_weight: not a call_function." + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":1625 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0015", + "stacks":[] + }, + { + "message":{ + "markdown":"Skipped p_getattr_l__self___trunk_blocks___3___norm2_bias: not a call_function.\n\n## Additional Message:\n\n## Function 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Additional Message:\n\n## Function Signature\n### Function Signature _TypePromotionInterpreter.run_node\n- self: \n- node: fx.Node(p_getattr_l__self___trunk_blocks___3___mlp_fc1_weight)[placeholder]:Tensor(f32[4096, 1024])\n## Return values\nTensor(f32[4096, 1024])", + "text":"Skipped p_getattr_l__self___trunk_blocks___3___mlp_fc1_weight: not a call_function." + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":1625 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0015", + "stacks":[] + }, + { + "message":{ + "markdown":"Skipped p_getattr_l__self___trunk_blocks___3___mlp_fc1_bias: not a call_function.\n\n## Additional Message:\n\n## Function Signature\n### Function Signature _TypePromotionInterpreter.run_node\n- self: \n- node: fx.Node(p_getattr_l__self___trunk_blocks___3___mlp_fc1_bias)[placeholder]:Tensor(f32[4096])\n## Return values\nTensor(f32[4096])", + "text":"Skipped p_getattr_l__self___trunk_blocks___3___mlp_fc1_bias: not a call_function." + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":1625 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0015", + "stacks":[] + }, + { + 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call_function." + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":1625 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0015", + "stacks":[] + }, + { + "message":{ + "markdown":"Skipped p_getattr_l__self___trunk_blocks___4___mlp_fc1_bias: not a call_function.\n\n## Additional Message:\n\n## Function Signature\n### Function Signature _TypePromotionInterpreter.run_node\n- self: \n- node: fx.Node(p_getattr_l__self___trunk_blocks___4___mlp_fc1_bias)[placeholder]:Tensor(f32[4096])\n## Return values\nTensor(f32[4096])", + "text":"Skipped 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fx.Node(p_getattr_l__self___trunk_blocks___4___mlp_fc2_bias)[placeholder]:Tensor(f32[1024])\n## Return values\nTensor(f32[1024])", + "text":"Skipped p_getattr_l__self___trunk_blocks___4___mlp_fc2_bias: not a call_function." + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":1625 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0015", + "stacks":[] + }, + { + "message":{ + "markdown":"Skipped p_getattr_l__self___trunk_blocks___5___norm1_weight: not a call_function.\n\n## Additional Message:\n\n## Function Signature\n### Function Signature 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"codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":1625 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0015", + "stacks":[] + }, + { + "message":{ + "markdown":"Skipped p_getattr_l__self___trunk_blocks___6___attn_qkv_bias: not a call_function.\n\n## Additional Message:\n\n## Function Signature\n### Function Signature _TypePromotionInterpreter.run_node\n- self: \n- node: fx.Node(p_getattr_l__self___trunk_blocks___6___attn_qkv_bias)[placeholder]:Tensor(f32[3072])\n## Return values\nTensor(f32[3072])", + "text":"Skipped p_getattr_l__self___trunk_blocks___6___attn_qkv_bias: not a call_function." + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":1625 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0015", + "stacks":[] + }, + { + "message":{ + "markdown":"Skipped p_getattr_l__self___trunk_blocks___6___attn_proj_weight: not a call_function.\n\n## Additional Message:\n\n## Function Signature\n### Function Signature _TypePromotionInterpreter.run_node\n- self: \n- node: fx.Node(p_getattr_l__self___trunk_blocks___6___attn_proj_weight)[placeholder]:Tensor(f32[1024, 1024])\n## 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fx.Node(p_getattr_l__self___trunk_blocks___6___attn_proj_bias)[placeholder]:Tensor(f32[1024])\n## Return values\nTensor(f32[1024])", + "text":"Skipped p_getattr_l__self___trunk_blocks___6___attn_proj_bias: not a call_function." + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":1625 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0015", + "stacks":[] + }, + { + "message":{ + "markdown":"Skipped p_getattr_l__self___trunk_blocks___6___norm2_weight: not a call_function.\n\n## Additional Message:\n\n## Function Signature\n### Function Signature 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Additional Message:\n\n## Function Signature\n### Function Signature _TypePromotionInterpreter.run_node\n- self: \n- node: fx.Node(p_getattr_l__self___trunk_blocks___6___mlp_fc1_weight)[placeholder]:Tensor(f32[4096, 1024])\n## Return values\nTensor(f32[4096, 1024])", + "text":"Skipped p_getattr_l__self___trunk_blocks___6___mlp_fc1_weight: not a call_function." + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":1625 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0015", + "stacks":[] + }, + { + "message":{ + "markdown":"Skipped p_getattr_l__self___trunk_blocks___6___mlp_fc1_bias: not a call_function.\n\n## Additional Message:\n\n## Function Signature\n### Function Signature _TypePromotionInterpreter.run_node\n- self: \n- node: fx.Node(p_getattr_l__self___trunk_blocks___6___mlp_fc1_bias)[placeholder]:Tensor(f32[4096])\n## Return values\nTensor(f32[4096])", + "text":"Skipped p_getattr_l__self___trunk_blocks___6___mlp_fc1_bias: not a call_function." + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":1625 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0015", + "stacks":[] + }, + { + "message":{ + "markdown":"Skipped p_getattr_l__self___trunk_blocks___6___mlp_fc2_weight: not a call_function.\n\n## Additional Message:\n\n## Function Signature\n### Function Signature _TypePromotionInterpreter.run_node\n- self: \n- node: fx.Node(p_getattr_l__self___trunk_blocks___6___mlp_fc2_weight)[placeholder]:Tensor(f32[1024, 4096])\n## Return values\nTensor(f32[1024, 4096])", + "text":"Skipped p_getattr_l__self___trunk_blocks___6___mlp_fc2_weight: not a call_function." + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":1625 + } + } + } + ], + "properties":{ + "tags":[] 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call_function." + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":1625 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0015", + "stacks":[] + }, + { + "message":{ + "markdown":"Skipped p_getattr_l__self___trunk_blocks___7___mlp_fc1_bias: not a call_function.\n\n## Additional Message:\n\n## Function Signature\n### Function Signature _TypePromotionInterpreter.run_node\n- self: \n- node: fx.Node(p_getattr_l__self___trunk_blocks___7___mlp_fc1_bias)[placeholder]:Tensor(f32[4096])\n## Return values\nTensor(f32[4096])", + "text":"Skipped 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values\nTensor(f32[1024, 4096])", + "text":"Skipped p_getattr_l__self___trunk_blocks___7___mlp_fc2_weight: not a call_function." + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":1625 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0015", + "stacks":[] + }, + { + "message":{ + "markdown":"Skipped p_getattr_l__self___trunk_blocks___7___mlp_fc2_bias: not a call_function.\n\n## Additional Message:\n\n## Function Signature\n### Function Signature _TypePromotionInterpreter.run_node\n- self: \n- node: fx.Node(p_getattr_l__self___trunk_blocks___7___mlp_fc2_bias)[placeholder]:Tensor(f32[1024])\n## Return values\nTensor(f32[1024])", + "text":"Skipped p_getattr_l__self___trunk_blocks___7___mlp_fc2_bias: not a call_function." + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":1625 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0015", + "stacks":[] + }, + { + "message":{ + "markdown":"Skipped p_getattr_l__self___trunk_blocks___8___norm1_weight: not a call_function.\n\n## Additional Message:\n\n## Function Signature\n### Function Signature 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Additional Message:\n\n## Function Signature\n### Function Signature _TypePromotionInterpreter.run_node\n- self: \n- node: fx.Node(p_getattr_l__self___trunk_blocks___8___attn_qkv_weight)[placeholder]:Tensor(f32[3072, 1024])\n## Return values\nTensor(f32[3072, 1024])", + "text":"Skipped p_getattr_l__self___trunk_blocks___8___attn_qkv_weight: not a call_function." + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":1625 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0015", + "stacks":[] + }, + { + "message":{ + "markdown":"Skipped p_getattr_l__self___trunk_blocks___8___attn_qkv_bias: not a call_function.\n\n## Additional Message:\n\n## Function Signature\n### Function Signature _TypePromotionInterpreter.run_node\n- self: \n- node: fx.Node(p_getattr_l__self___trunk_blocks___8___attn_qkv_bias)[placeholder]:Tensor(f32[3072])\n## Return values\nTensor(f32[3072])", + "text":"Skipped p_getattr_l__self___trunk_blocks___8___attn_qkv_bias: not a call_function." + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":1625 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0015", + "stacks":[] + }, + 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"codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":1625 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0015", + "stacks":[] + }, + { + "message":{ + "markdown":"Skipped p_getattr_l__self___trunk_blocks___9___attn_qkv_bias: not a call_function.\n\n## Additional Message:\n\n## Function Signature\n### Function Signature _TypePromotionInterpreter.run_node\n- self: \n- node: fx.Node(p_getattr_l__self___trunk_blocks___9___attn_qkv_bias)[placeholder]:Tensor(f32[3072])\n## Return values\nTensor(f32[3072])", + "text":"Skipped p_getattr_l__self___trunk_blocks___9___attn_qkv_bias: not a call_function." + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":1625 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0015", + "stacks":[] + }, + { + "message":{ + "markdown":"Skipped p_getattr_l__self___trunk_blocks___9___attn_proj_weight: not a call_function.\n\n## Additional Message:\n\n## Function Signature\n### Function Signature _TypePromotionInterpreter.run_node\n- self: \n- node: fx.Node(p_getattr_l__self___trunk_blocks___9___attn_proj_weight)[placeholder]:Tensor(f32[1024, 1024])\n## Return values\nTensor(f32[1024, 1024])", + "text":"Skipped p_getattr_l__self___trunk_blocks___9___attn_proj_weight: not a call_function." + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":1625 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0015", + "stacks":[] + }, + { + "message":{ + "markdown":"Skipped p_getattr_l__self___trunk_blocks___9___attn_proj_bias: not a call_function.\n\n## Additional Message:\n\n## Function Signature\n### Function Signature _TypePromotionInterpreter.run_node\n- self: \n- node: fx.Node(p_getattr_l__self___trunk_blocks___9___attn_proj_bias)[placeholder]:Tensor(f32[1024])\n## Return values\nTensor(f32[1024])", + "text":"Skipped p_getattr_l__self___trunk_blocks___9___attn_proj_bias: not a call_function." + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":1625 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0015", + "stacks":[] + }, + { + "message":{ + "markdown":"Skipped p_getattr_l__self___trunk_blocks___9___norm2_weight: not a call_function.\n\n## Additional Message:\n\n## Function Signature\n### Function Signature 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Additional Message:\n\n## Function Signature\n### Function Signature _TypePromotionInterpreter.run_node\n- self: \n- node: fx.Node(p_getattr_l__self___trunk_blocks___9___mlp_fc1_weight)[placeholder]:Tensor(f32[4096, 1024])\n## Return values\nTensor(f32[4096, 1024])", + "text":"Skipped p_getattr_l__self___trunk_blocks___9___mlp_fc1_weight: not a call_function." + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":1625 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0015", + "stacks":[] + }, + { + "message":{ + "markdown":"Skipped p_getattr_l__self___trunk_blocks___9___mlp_fc1_bias: not a call_function.\n\n## Additional Message:\n\n## Function Signature\n### Function Signature _TypePromotionInterpreter.run_node\n- self: \n- node: fx.Node(p_getattr_l__self___trunk_blocks___9___mlp_fc1_bias)[placeholder]:Tensor(f32[4096])\n## Return values\nTensor(f32[4096])", + "text":"Skipped p_getattr_l__self___trunk_blocks___9___mlp_fc1_bias: not a call_function." + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":1625 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0015", + "stacks":[] + }, + { + "message":{ + "markdown":"Skipped p_getattr_l__self___trunk_blocks___9___mlp_fc2_weight: not a call_function.\n\n## Additional Message:\n\n## Function Signature\n### Function Signature _TypePromotionInterpreter.run_node\n- self: \n- node: fx.Node(p_getattr_l__self___trunk_blocks___9___mlp_fc2_weight)[placeholder]:Tensor(f32[1024, 4096])\n## Return values\nTensor(f32[1024, 4096])", + "text":"Skipped p_getattr_l__self___trunk_blocks___9___mlp_fc2_weight: not a call_function." + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":1625 + } + } + } + ], + "properties":{ + "tags":[] 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"message":{ + "text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":1625 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0015", + "stacks":[] + }, + { + "message":{ + "markdown":"Skipped p_getattr_l__self___trunk_blocks___10___attn_proj_bias: not a call_function.\n\n## Additional Message:\n\n## Function Signature\n### Function Signature _TypePromotionInterpreter.run_node\n- self: \n- node: fx.Node(p_getattr_l__self___trunk_blocks___10___attn_proj_bias)[placeholder]:Tensor(f32[1024])\n## Return values\nTensor(f32[1024])", + "text":"Skipped p_getattr_l__self___trunk_blocks___10___attn_proj_bias: not a call_function." + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + 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"locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":1625 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0015", + "stacks":[] + }, + { + "message":{ + "markdown":"Skipped p_getattr_l__self___trunk_blocks___10___norm2_bias: not a call_function.\n\n## Additional Message:\n\n## Function Signature\n### Function Signature _TypePromotionInterpreter.run_node\n- self: \n- node: fx.Node(p_getattr_l__self___trunk_blocks___10___norm2_bias)[placeholder]:Tensor(f32[1024])\n## Return values\nTensor(f32[1024])", + "text":"Skipped p_getattr_l__self___trunk_blocks___10___norm2_bias: not a call_function." + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":1625 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0015", + "stacks":[] + }, + { + "message":{ + "markdown":"Skipped p_getattr_l__self___trunk_blocks___10___mlp_fc1_weight: not a call_function.\n\n## Additional Message:\n\n## Function Signature\n### Function Signature _TypePromotionInterpreter.run_node\n- self: \n- node: fx.Node(p_getattr_l__self___trunk_blocks___10___mlp_fc1_weight)[placeholder]:Tensor(f32[4096, 1024])\n## Return values\nTensor(f32[4096, 1024])", + "text":"Skipped p_getattr_l__self___trunk_blocks___10___mlp_fc1_weight: not a call_function." + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":1625 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0015", + "stacks":[] + }, + { + "message":{ + "markdown":"Skipped p_getattr_l__self___trunk_blocks___10___mlp_fc1_bias: not a call_function.\n\n## Additional Message:\n\n## Function Signature\n### Function Signature _TypePromotionInterpreter.run_node\n- self: \n- node: fx.Node(p_getattr_l__self___trunk_blocks___10___mlp_fc1_bias)[placeholder]:Tensor(f32[4096])\n## Return values\nTensor(f32[4096])", + "text":"Skipped p_getattr_l__self___trunk_blocks___10___mlp_fc1_bias: not a call_function." + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":1625 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0015", + "stacks":[] + }, + { + "message":{ + "markdown":"Skipped p_getattr_l__self___trunk_blocks___10___mlp_fc2_weight: not a call_function.\n\n## Additional Message:\n\n## Function Signature\n### Function Signature _TypePromotionInterpreter.run_node\n- self: \n- node: fx.Node(p_getattr_l__self___trunk_blocks___10___mlp_fc2_weight)[placeholder]:Tensor(f32[1024, 4096])\n## Return values\nTensor(f32[1024, 4096])", + "text":"Skipped p_getattr_l__self___trunk_blocks___10___mlp_fc2_weight: not a call_function." + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":1625 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0015", + "stacks":[] + }, + { + "message":{ + "markdown":"Skipped p_getattr_l__self___trunk_blocks___10___mlp_fc2_bias: not a call_function.\n\n## Additional Message:\n\n## Function Signature\n### Function Signature _TypePromotionInterpreter.run_node\n- self: \n- node: fx.Node(p_getattr_l__self___trunk_blocks___10___mlp_fc2_bias)[placeholder]:Tensor(f32[1024])\n## Return values\nTensor(f32[1024])", + "text":"Skipped p_getattr_l__self___trunk_blocks___10___mlp_fc2_bias: not a call_function." + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":1625 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0015", + "stacks":[] + }, + { + "message":{ + "markdown":"Skipped p_getattr_l__self___trunk_blocks___11___norm1_weight: not a call_function.\n\n## Additional Message:\n\n## 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call_function.\n\n## Additional Message:\n\n## Function Signature\n### Function Signature _TypePromotionInterpreter.run_node\n- self: \n- node: fx.Node(p_getattr_l__self___trunk_blocks___11___norm1_bias)[placeholder]:Tensor(f32[1024])\n## Return values\nTensor(f32[1024])", + "text":"Skipped p_getattr_l__self___trunk_blocks___11___norm1_bias: not a call_function." + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":1625 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0015", + "stacks":[] + }, + { + "message":{ + "markdown":"Skipped p_getattr_l__self___trunk_blocks___11___attn_qkv_weight: not a call_function.\n\n## Additional Message:\n\n## Function Signature\n### Function Signature _TypePromotionInterpreter.run_node\n- self: \n- node: fx.Node(p_getattr_l__self___trunk_blocks___11___attn_qkv_weight)[placeholder]:Tensor(f32[3072, 1024])\n## Return values\nTensor(f32[3072, 1024])", + "text":"Skipped p_getattr_l__self___trunk_blocks___11___attn_qkv_weight: not a call_function." + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":1625 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0015", 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"properties":{ + "tags":[] + }, + "ruleId":"FXE0015", + "stacks":[] + }, + { + "message":{ + "markdown":"Skipped p_getattr_l__self___trunk_blocks___11___attn_proj_weight: not a call_function.\n\n## Additional Message:\n\n## Function Signature\n### Function Signature _TypePromotionInterpreter.run_node\n- self: \n- node: fx.Node(p_getattr_l__self___trunk_blocks___11___attn_proj_weight)[placeholder]:Tensor(f32[1024, 1024])\n## Return values\nTensor(f32[1024, 1024])", + "text":"Skipped p_getattr_l__self___trunk_blocks___11___attn_proj_weight: not a call_function." + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + 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"physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":1625 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0015", + "stacks":[] + }, + { + "message":{ + "markdown":"Skipped p_getattr_l__self___trunk_blocks___11___norm2_bias: not a call_function.\n\n## Additional Message:\n\n## Function Signature\n### Function Signature _TypePromotionInterpreter.run_node\n- self: \n- node: fx.Node(p_getattr_l__self___trunk_blocks___11___norm2_bias)[placeholder]:Tensor(f32[1024])\n## Return values\nTensor(f32[1024])", + "text":"Skipped p_getattr_l__self___trunk_blocks___11___norm2_bias: not a call_function." + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":1625 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0015", + "stacks":[] + }, + { + "message":{ + "markdown":"Skipped p_getattr_l__self___trunk_blocks___11___mlp_fc1_weight: not a call_function.\n\n## Additional Message:\n\n## Function Signature\n### Function Signature _TypePromotionInterpreter.run_node\n- self: \n- node: fx.Node(p_getattr_l__self___trunk_blocks___11___mlp_fc1_weight)[placeholder]:Tensor(f32[4096, 1024])\n## Return values\nTensor(f32[4096, 1024])", + "text":"Skipped p_getattr_l__self___trunk_blocks___11___mlp_fc1_weight: not a call_function." + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + 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"locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":1625 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0015", + "stacks":[] + }, + { + "message":{ + "markdown":"Skipped p_getattr_l__self___trunk_blocks___11___mlp_fc2_weight: not a call_function.\n\n## Additional Message:\n\n## Function Signature\n### Function Signature _TypePromotionInterpreter.run_node\n- self: \n- node: fx.Node(p_getattr_l__self___trunk_blocks___11___mlp_fc2_weight)[placeholder]:Tensor(f32[1024, 4096])\n## Return values\nTensor(f32[1024, 4096])", + "text":"Skipped p_getattr_l__self___trunk_blocks___11___mlp_fc2_weight: not a call_function." + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":1625 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0015", + "stacks":[] + }, + { + "message":{ + "markdown":"Skipped p_getattr_l__self___trunk_blocks___11___mlp_fc2_bias: not a call_function.\n\n## Additional Message:\n\n## Function Signature\n### Function Signature _TypePromotionInterpreter.run_node\n- self: \n- node: fx.Node(p_getattr_l__self___trunk_blocks___11___mlp_fc2_bias)[placeholder]:Tensor(f32[1024])\n## Return values\nTensor(f32[1024])", + "text":"Skipped p_getattr_l__self___trunk_blocks___11___mlp_fc2_bias: not a call_function." + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":1625 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0015", + "stacks":[] + }, + { + "message":{ + "markdown":"Skipped p_getattr_l__self___trunk_blocks___12___norm1_weight: not a call_function.\n\n## Additional Message:\n\n## Function Signature\n### Function Signature _TypePromotionInterpreter.run_node\n- self: \n- node: fx.Node(p_getattr_l__self___trunk_blocks___12___norm1_weight)[placeholder]:Tensor(f32[1024])\n## Return values\nTensor(f32[1024])", + "text":"Skipped p_getattr_l__self___trunk_blocks___12___norm1_weight: not a call_function." + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":1625 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0015", + "stacks":[] + }, + { + "message":{ + "markdown":"Skipped p_getattr_l__self___trunk_blocks___12___norm1_bias: not a call_function.\n\n## Additional Message:\n\n## Function Signature\n### Function Signature _TypePromotionInterpreter.run_node\n- self: \n- node: 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p_getattr_l__self___trunk_blocks___12___attn_proj_weight: not a call_function.\n\n## Additional Message:\n\n## Function Signature\n### Function Signature _TypePromotionInterpreter.run_node\n- self: \n- node: fx.Node(p_getattr_l__self___trunk_blocks___12___attn_proj_weight)[placeholder]:Tensor(f32[1024, 1024])\n## Return values\nTensor(f32[1024, 1024])", + "text":"Skipped p_getattr_l__self___trunk_blocks___12___attn_proj_weight: not a call_function." + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":1625 + } + } + } + ], + "properties":{ + "tags":[] + }, + 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call_function." + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":1625 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0015", + "stacks":[] + }, + { + "message":{ + "markdown":"Skipped p_getattr_l__self___trunk_blocks___13___attn_qkv_bias: not a call_function.\n\n## Additional Message:\n\n## Function Signature\n### Function Signature _TypePromotionInterpreter.run_node\n- self: \n- node: fx.Node(p_getattr_l__self___trunk_blocks___13___attn_qkv_bias)[placeholder]:Tensor(f32[3072])\n## Return values\nTensor(f32[3072])", + "text":"Skipped 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call_function." + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":1625 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0015", + "stacks":[] + }, + { + "message":{ + "markdown":"Skipped p_getattr_l__self___trunk_blocks___15___mlp_fc2_bias: not a call_function.\n\n## Additional Message:\n\n## Function Signature\n### Function Signature _TypePromotionInterpreter.run_node\n- self: \n- node: fx.Node(p_getattr_l__self___trunk_blocks___15___mlp_fc2_bias)[placeholder]:Tensor(f32[1024])\n## Return values\nTensor(f32[1024])", + "text":"Skipped 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values\nTensor(f32[1024])", + "text":"Skipped p_getattr_l__self___trunk_blocks___16___norm1_weight: not a call_function." + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":1625 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0015", + "stacks":[] + }, + { + "message":{ + "markdown":"Skipped p_getattr_l__self___trunk_blocks___16___norm1_bias: not a call_function.\n\n## Additional Message:\n\n## Function Signature\n### Function Signature _TypePromotionInterpreter.run_node\n- self: \n- node: 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p_getattr_l__self___trunk_blocks___16___attn_proj_weight: not a call_function.\n\n## Additional Message:\n\n## Function Signature\n### Function Signature _TypePromotionInterpreter.run_node\n- self: \n- node: fx.Node(p_getattr_l__self___trunk_blocks___16___attn_proj_weight)[placeholder]:Tensor(f32[1024, 1024])\n## Return values\nTensor(f32[1024, 1024])", + "text":"Skipped p_getattr_l__self___trunk_blocks___16___attn_proj_weight: not a call_function." + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":1625 + } + } + } + ], + "properties":{ + "tags":[] + }, + 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"locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":1625 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0015", + "stacks":[] + }, + { + "message":{ + "markdown":"Skipped p_getattr_l__self___trunk_blocks___17___attn_qkv_weight: not a call_function.\n\n## Additional Message:\n\n## Function Signature\n### Function Signature _TypePromotionInterpreter.run_node\n- self: \n- node: fx.Node(p_getattr_l__self___trunk_blocks___17___attn_qkv_weight)[placeholder]:Tensor(f32[3072, 1024])\n## Return values\nTensor(f32[3072, 1024])", + "text":"Skipped p_getattr_l__self___trunk_blocks___17___attn_qkv_weight: not a call_function." + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":1625 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0015", + "stacks":[] + }, + { + "message":{ + "markdown":"Skipped p_getattr_l__self___trunk_blocks___17___attn_qkv_bias: not a call_function.\n\n## Additional Message:\n\n## Function Signature\n### Function Signature _TypePromotionInterpreter.run_node\n- self: \n- node: fx.Node(p_getattr_l__self___trunk_blocks___17___attn_qkv_bias)[placeholder]:Tensor(f32[3072])\n## Return values\nTensor(f32[3072])", + "text":"Skipped 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fx.Node(p_getattr_l__self___trunk_blocks___17___attn_proj_bias)[placeholder]:Tensor(f32[1024])\n## Return values\nTensor(f32[1024])", + "text":"Skipped p_getattr_l__self___trunk_blocks___17___attn_proj_bias: not a call_function." + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":1625 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0015", + "stacks":[] + }, + { + "message":{ + "markdown":"Skipped p_getattr_l__self___trunk_blocks___17___norm2_weight: not a call_function.\n\n## Additional Message:\n\n## Function Signature\n### Function Signature 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p_getattr_l__self___trunk_blocks___17___mlp_fc1_bias: not a call_function.\n\n## Additional Message:\n\n## Function Signature\n### Function Signature _TypePromotionInterpreter.run_node\n- self: \n- node: fx.Node(p_getattr_l__self___trunk_blocks___17___mlp_fc1_bias)[placeholder]:Tensor(f32[4096])\n## Return values\nTensor(f32[4096])", + "text":"Skipped p_getattr_l__self___trunk_blocks___17___mlp_fc1_bias: not a call_function." + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":1625 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0015", + "stacks":[] + }, + 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"tags":[] + }, + "ruleId":"FXE0015", + "stacks":[] + }, + { + "message":{ + "markdown":"Skipped p_getattr_l__self___trunk_blocks___17___mlp_fc2_bias: not a call_function.\n\n## Additional Message:\n\n## Function Signature\n### Function Signature _TypePromotionInterpreter.run_node\n- self: \n- node: fx.Node(p_getattr_l__self___trunk_blocks___17___mlp_fc2_bias)[placeholder]:Tensor(f32[1024])\n## Return values\nTensor(f32[1024])", + "text":"Skipped p_getattr_l__self___trunk_blocks___17___mlp_fc2_bias: not a call_function." + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":1625 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0015", + "stacks":[] + }, + { + "message":{ + "markdown":"Skipped p_getattr_l__self___trunk_blocks___18___norm1_weight: not a call_function.\n\n## Additional Message:\n\n## Function Signature\n### Function Signature _TypePromotionInterpreter.run_node\n- self: \n- node: fx.Node(p_getattr_l__self___trunk_blocks___18___norm1_weight)[placeholder]:Tensor(f32[1024])\n## Return values\nTensor(f32[1024])", + "text":"Skipped p_getattr_l__self___trunk_blocks___18___norm1_weight: not a call_function." + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + 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"uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":1625 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0015", + "stacks":[] + }, + { + "message":{ + "markdown":"Skipped p_getattr_l__self___trunk_blocks___18___attn_qkv_bias: not a call_function.\n\n## Additional Message:\n\n## Function Signature\n### Function Signature _TypePromotionInterpreter.run_node\n- self: \n- node: fx.Node(p_getattr_l__self___trunk_blocks___18___attn_qkv_bias)[placeholder]:Tensor(f32[3072])\n## Return values\nTensor(f32[3072])", + "text":"Skipped p_getattr_l__self___trunk_blocks___18___attn_qkv_bias: not a call_function." + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"_TypePromotionInterpreter.run_node" + }, + 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"message":{ + "text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":1625 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0015", + "stacks":[] + }, + { + "message":{ + "markdown":"Skipped p_getattr_l__self___trunk_blocks___18___attn_proj_bias: not a call_function.\n\n## Additional Message:\n\n## Function Signature\n### Function Signature _TypePromotionInterpreter.run_node\n- self: \n- node: fx.Node(p_getattr_l__self___trunk_blocks___18___attn_proj_bias)[placeholder]:Tensor(f32[1024])\n## Return values\nTensor(f32[1024])", + "text":"Skipped p_getattr_l__self___trunk_blocks___18___attn_proj_bias: not a call_function." + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + 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"codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":1625 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0015", + "stacks":[] + }, + { + "message":{ + "markdown":"Skipped p_getattr_l__self___trunk_blocks___18___mlp_fc1_weight: not a call_function.\n\n## Additional Message:\n\n## Function Signature\n### Function Signature _TypePromotionInterpreter.run_node\n- self: \n- node: fx.Node(p_getattr_l__self___trunk_blocks___18___mlp_fc1_weight)[placeholder]:Tensor(f32[4096, 1024])\n## Return values\nTensor(f32[4096, 1024])", + "text":"Skipped p_getattr_l__self___trunk_blocks___18___mlp_fc1_weight: not a call_function." + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":1625 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0015", + "stacks":[] + }, + { + "message":{ + "markdown":"Skipped p_getattr_l__self___trunk_blocks___18___mlp_fc1_bias: not a call_function.\n\n## Additional Message:\n\n## Function Signature\n### Function Signature _TypePromotionInterpreter.run_node\n- self: \n- node: fx.Node(p_getattr_l__self___trunk_blocks___18___mlp_fc1_bias)[placeholder]:Tensor(f32[4096])\n## Return values\nTensor(f32[4096])", + "text":"Skipped p_getattr_l__self___trunk_blocks___18___mlp_fc1_bias: not a call_function." + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":1625 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0015", + "stacks":[] + }, + { + "message":{ + "markdown":"Skipped p_getattr_l__self___trunk_blocks___18___mlp_fc2_weight: not a call_function.\n\n## Additional Message:\n\n## Function Signature\n### Function Signature _TypePromotionInterpreter.run_node\n- self: \n- node: fx.Node(p_getattr_l__self___trunk_blocks___18___mlp_fc2_weight)[placeholder]:Tensor(f32[1024, 4096])\n## Return values\nTensor(f32[1024, 4096])", + "text":"Skipped p_getattr_l__self___trunk_blocks___18___mlp_fc2_weight: not a call_function." + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":1625 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0015", + "stacks":[] + }, + { + "message":{ + "markdown":"Skipped p_getattr_l__self___trunk_blocks___18___mlp_fc2_bias: not a call_function.\n\n## Additional Message:\n\n## Function Signature\n### Function Signature _TypePromotionInterpreter.run_node\n- self: \n- node: fx.Node(p_getattr_l__self___trunk_blocks___18___mlp_fc2_bias)[placeholder]:Tensor(f32[1024])\n## Return values\nTensor(f32[1024])", + "text":"Skipped p_getattr_l__self___trunk_blocks___18___mlp_fc2_bias: not a call_function." + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":1625 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0015", + "stacks":[] + }, + { + "message":{ + "markdown":"Skipped p_getattr_l__self___trunk_blocks___19___norm1_weight: not a call_function.\n\n## Additional Message:\n\n## Function Signature\n### Function Signature _TypePromotionInterpreter.run_node\n- self: \n- node: fx.Node(p_getattr_l__self___trunk_blocks___19___norm1_weight)[placeholder]:Tensor(f32[1024])\n## Return values\nTensor(f32[1024])", + "text":"Skipped p_getattr_l__self___trunk_blocks___19___norm1_weight: not a call_function." + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":1625 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0015", + "stacks":[] + }, + { + "message":{ + "markdown":"Skipped p_getattr_l__self___trunk_blocks___19___norm1_bias: not a call_function.\n\n## Additional Message:\n\n## Function Signature\n### Function Signature _TypePromotionInterpreter.run_node\n- self: \n- node: fx.Node(p_getattr_l__self___trunk_blocks___19___norm1_bias)[placeholder]:Tensor(f32[1024])\n## Return values\nTensor(f32[1024])", + "text":"Skipped p_getattr_l__self___trunk_blocks___19___norm1_bias: not a call_function." + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":1625 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0015", + "stacks":[] + }, + { + "message":{ + "markdown":"Skipped p_getattr_l__self___trunk_blocks___19___attn_qkv_weight: not a call_function.\n\n## Additional Message:\n\n## Function Signature\n### Function Signature _TypePromotionInterpreter.run_node\n- self: \n- node: fx.Node(p_getattr_l__self___trunk_blocks___19___attn_qkv_weight)[placeholder]:Tensor(f32[3072, 1024])\n## Return values\nTensor(f32[3072, 1024])", + "text":"Skipped p_getattr_l__self___trunk_blocks___19___attn_qkv_weight: not a call_function." + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":1625 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0015", 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"text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":1625 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0015", + "stacks":[] + }, + { + "message":{ + "markdown":"Skipped p_getattr_l__self___trunk_blocks___19___mlp_fc1_weight: not a call_function.\n\n## Additional Message:\n\n## Function Signature\n### Function Signature _TypePromotionInterpreter.run_node\n- self: \n- node: fx.Node(p_getattr_l__self___trunk_blocks___19___mlp_fc1_weight)[placeholder]:Tensor(f32[4096, 1024])\n## Return values\nTensor(f32[4096, 1024])", + "text":"Skipped p_getattr_l__self___trunk_blocks___19___mlp_fc1_weight: not a call_function." + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + 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"locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":1625 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0015", + "stacks":[] + }, + { + "message":{ + "markdown":"Skipped p_getattr_l__self___trunk_blocks___19___mlp_fc2_weight: not a call_function.\n\n## Additional Message:\n\n## Function Signature\n### Function Signature _TypePromotionInterpreter.run_node\n- self: \n- node: fx.Node(p_getattr_l__self___trunk_blocks___19___mlp_fc2_weight)[placeholder]:Tensor(f32[1024, 4096])\n## Return values\nTensor(f32[1024, 4096])", + "text":"Skipped p_getattr_l__self___trunk_blocks___19___mlp_fc2_weight: not a call_function." + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":1625 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0015", + "stacks":[] + }, + { + "message":{ + "markdown":"Skipped p_getattr_l__self___trunk_blocks___19___mlp_fc2_bias: not a call_function.\n\n## Additional Message:\n\n## Function Signature\n### Function Signature _TypePromotionInterpreter.run_node\n- self: \n- node: fx.Node(p_getattr_l__self___trunk_blocks___19___mlp_fc2_bias)[placeholder]:Tensor(f32[1024])\n## Return values\nTensor(f32[1024])", + "text":"Skipped p_getattr_l__self___trunk_blocks___19___mlp_fc2_bias: not a call_function." + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":1625 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0015", + "stacks":[] + }, + { + "message":{ + "markdown":"Skipped p_getattr_l__self___trunk_blocks___20___norm1_weight: not a call_function.\n\n## Additional Message:\n\n## Function Signature\n### Function Signature _TypePromotionInterpreter.run_node\n- self: \n- node: fx.Node(p_getattr_l__self___trunk_blocks___20___norm1_weight)[placeholder]:Tensor(f32[1024])\n## Return values\nTensor(f32[1024])", + "text":"Skipped p_getattr_l__self___trunk_blocks___20___norm1_weight: not a call_function." + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":1625 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0015", + "stacks":[] + }, + { + "message":{ + "markdown":"Skipped p_getattr_l__self___trunk_blocks___20___norm1_bias: not a call_function.\n\n## Additional Message:\n\n## Function Signature\n### Function Signature _TypePromotionInterpreter.run_node\n- self: \n- node: fx.Node(p_getattr_l__self___trunk_blocks___20___norm1_bias)[placeholder]:Tensor(f32[1024])\n## Return values\nTensor(f32[1024])", + "text":"Skipped p_getattr_l__self___trunk_blocks___20___norm1_bias: not a call_function." + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":1625 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0015", + "stacks":[] + }, + { + "message":{ + "markdown":"Skipped p_getattr_l__self___trunk_blocks___20___attn_qkv_weight: not a call_function.\n\n## Additional Message:\n\n## Function Signature\n### Function Signature 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p_getattr_l__self___trunk_blocks___20___attn_proj_weight: not a call_function.\n\n## Additional Message:\n\n## Function Signature\n### Function Signature _TypePromotionInterpreter.run_node\n- self: \n- node: fx.Node(p_getattr_l__self___trunk_blocks___20___attn_proj_weight)[placeholder]:Tensor(f32[1024, 1024])\n## Return values\nTensor(f32[1024, 1024])", + "text":"Skipped p_getattr_l__self___trunk_blocks___20___attn_proj_weight: not a call_function." + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":1625 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0015", + "stacks":[] + }, + { + "message":{ + "markdown":"Skipped p_getattr_l__self___trunk_blocks___20___attn_proj_bias: not a call_function.\n\n## Additional Message:\n\n## Function Signature\n### Function Signature _TypePromotionInterpreter.run_node\n- self: \n- node: fx.Node(p_getattr_l__self___trunk_blocks___20___attn_proj_bias)[placeholder]:Tensor(f32[1024])\n## Return values\nTensor(f32[1024])", + "text":"Skipped p_getattr_l__self___trunk_blocks___20___attn_proj_bias: not a call_function." + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":1625 + } + } + 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call_function." + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":1625 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0015", + "stacks":[] + }, + { + "message":{ + "markdown":"Skipped p_getattr_l__self___trunk_blocks___21___attn_qkv_bias: not a call_function.\n\n## Additional Message:\n\n## Function Signature\n### Function Signature _TypePromotionInterpreter.run_node\n- self: \n- node: fx.Node(p_getattr_l__self___trunk_blocks___21___attn_qkv_bias)[placeholder]:Tensor(f32[3072])\n## Return values\nTensor(f32[3072])", + "text":"Skipped 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"codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":1625 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0015", + "stacks":[] + }, + { + "message":{ + "markdown":"Skipped p_getattr_l__self___trunk_blocks___22___mlp_fc1_weight: not a call_function.\n\n## Additional Message:\n\n## Function Signature\n### Function Signature _TypePromotionInterpreter.run_node\n- self: \n- node: fx.Node(p_getattr_l__self___trunk_blocks___22___mlp_fc1_weight)[placeholder]:Tensor(f32[4096, 1024])\n## Return values\nTensor(f32[4096, 1024])", + "text":"Skipped p_getattr_l__self___trunk_blocks___22___mlp_fc1_weight: not a call_function." + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":1625 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0015", + "stacks":[] + }, + { + "message":{ + "markdown":"Skipped p_getattr_l__self___trunk_blocks___22___mlp_fc1_bias: not a call_function.\n\n## Additional Message:\n\n## Function Signature\n### Function Signature _TypePromotionInterpreter.run_node\n- self: \n- node: fx.Node(p_getattr_l__self___trunk_blocks___22___mlp_fc1_bias)[placeholder]:Tensor(f32[4096])\n## Return values\nTensor(f32[4096])", + "text":"Skipped p_getattr_l__self___trunk_blocks___22___mlp_fc1_bias: not a call_function." + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":1625 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0015", + "stacks":[] + }, + { + "message":{ + "markdown":"Skipped p_getattr_l__self___trunk_blocks___22___mlp_fc2_weight: not a call_function.\n\n## Additional Message:\n\n## Function Signature\n### Function Signature _TypePromotionInterpreter.run_node\n- self: \n- node: 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call_function.\n\n## Additional Message:\n\n## Function Signature\n### Function Signature _TypePromotionInterpreter.run_node\n- self: \n- node: fx.Node(p_getattr_l__self___trunk_blocks___23___norm1_bias)[placeholder]:Tensor(f32[1024])\n## Return values\nTensor(f32[1024])", + "text":"Skipped p_getattr_l__self___trunk_blocks___23___norm1_bias: not a call_function." + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":1625 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0015", + "stacks":[] + }, + { + "message":{ + "markdown":"Skipped p_getattr_l__self___trunk_blocks___23___attn_qkv_weight: not a call_function.\n\n## Additional Message:\n\n## Function Signature\n### Function Signature _TypePromotionInterpreter.run_node\n- self: \n- node: fx.Node(p_getattr_l__self___trunk_blocks___23___attn_qkv_weight)[placeholder]:Tensor(f32[3072, 1024])\n## Return values\nTensor(f32[3072, 1024])", + "text":"Skipped p_getattr_l__self___trunk_blocks___23___attn_qkv_weight: not a call_function." + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":1625 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0015", 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"text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":1625 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0015", + "stacks":[] + }, + { + "message":{ + "markdown":"Skipped p_getattr_l__self___trunk_blocks___23___mlp_fc1_weight: not a call_function.\n\n## Additional Message:\n\n## Function Signature\n### Function Signature _TypePromotionInterpreter.run_node\n- self: \n- node: fx.Node(p_getattr_l__self___trunk_blocks___23___mlp_fc1_weight)[placeholder]:Tensor(f32[4096, 1024])\n## Return values\nTensor(f32[4096, 1024])", + "text":"Skipped p_getattr_l__self___trunk_blocks___23___mlp_fc1_weight: not a call_function." + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + 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"locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":1625 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0015", + "stacks":[] + }, + { + "message":{ + "markdown":"Skipped p_getattr_l__self___trunk_blocks___23___mlp_fc2_weight: not a call_function.\n\n## Additional Message:\n\n## Function Signature\n### Function Signature _TypePromotionInterpreter.run_node\n- self: \n- node: fx.Node(p_getattr_l__self___trunk_blocks___23___mlp_fc2_weight)[placeholder]:Tensor(f32[1024, 4096])\n## Return values\nTensor(f32[1024, 4096])", + "text":"Skipped p_getattr_l__self___trunk_blocks___23___mlp_fc2_weight: not a call_function." + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":1625 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0015", + "stacks":[] + }, + { + "message":{ + "markdown":"Skipped p_getattr_l__self___trunk_blocks___23___mlp_fc2_bias: not a call_function.\n\n## Additional Message:\n\n## Function Signature\n### Function Signature _TypePromotionInterpreter.run_node\n- self: \n- node: fx.Node(p_getattr_l__self___trunk_blocks___23___mlp_fc2_bias)[placeholder]:Tensor(f32[1024])\n## Return values\nTensor(f32[1024])", + "text":"Skipped p_getattr_l__self___trunk_blocks___23___mlp_fc2_bias: not a call_function." + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":1625 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0015", + "stacks":[] + }, + { + "message":{ + "markdown":"Skipped p_trunk_norm_weight: not a call_function.\n\n## Additional Message:\n\n## Function Signature\n### Function Signature _TypePromotionInterpreter.run_node\n- self: \n- node: fx.Node(p_trunk_norm_weight)[placeholder]:Tensor(f32[1024])\n## Return values\nTensor(f32[1024])", + "text":"Skipped p_trunk_norm_weight: not a call_function." + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":1625 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0015", + "stacks":[] + }, + { + "message":{ + "markdown":"Skipped p_trunk_norm_bias: not a call_function.\n\n## Additional Message:\n\n## Function Signature\n### Function Signature _TypePromotionInterpreter.run_node\n- self: \n- node: fx.Node(p_trunk_norm_bias)[placeholder]:Tensor(f32[1024])\n## Return values\nTensor(f32[1024])", + "text":"Skipped p_trunk_norm_bias: not a call_function." + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":1625 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0015", + "stacks":[] + }, + { + "message":{ + "markdown":"Skipped p_trunk_attn_pool_q_weight: not a call_function.\n\n## Additional Message:\n\n## Function Signature\n### Function Signature _TypePromotionInterpreter.run_node\n- self: \n- node: fx.Node(p_trunk_attn_pool_q_weight)[placeholder]:Tensor(f32[1024, 1024])\n## Return values\nTensor(f32[1024, 1024])", + "text":"Skipped p_trunk_attn_pool_q_weight: not a call_function." + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":1625 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0015", + "stacks":[] + }, + { + "message":{ + "markdown":"Skipped p_trunk_attn_pool_q_bias: not a call_function.\n\n## Additional Message:\n\n## Function Signature\n### Function Signature _TypePromotionInterpreter.run_node\n- self: \n- node: fx.Node(p_trunk_attn_pool_q_bias)[placeholder]:Tensor(f32[1024])\n## Return values\nTensor(f32[1024])", + "text":"Skipped p_trunk_attn_pool_q_bias: not a call_function." + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":1625 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0015", + "stacks":[] + }, + { + "message":{ + "markdown":"Skipped p_trunk_attn_pool_kv_weight: not a call_function.\n\n## Additional Message:\n\n## Function Signature\n### Function Signature _TypePromotionInterpreter.run_node\n- self: \n- node: fx.Node(p_trunk_attn_pool_kv_weight)[placeholder]:Tensor(f32[2048, 1024])\n## Return values\nTensor(f32[2048, 1024])", + "text":"Skipped p_trunk_attn_pool_kv_weight: not a call_function." + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":1625 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0015", + "stacks":[] + }, + { + "message":{ + "markdown":"Skipped p_trunk_attn_pool_kv_bias: not a call_function.\n\n## Additional Message:\n\n## Function Signature\n### Function Signature _TypePromotionInterpreter.run_node\n- self: \n- node: fx.Node(p_trunk_attn_pool_kv_bias)[placeholder]:Tensor(f32[2048])\n## Return values\nTensor(f32[2048])", + "text":"Skipped p_trunk_attn_pool_kv_bias: not a call_function." + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":1625 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0015", + "stacks":[] + }, + { + "message":{ + "markdown":"Skipped p_trunk_attn_pool_proj_weight: not a call_function.\n\n## Additional Message:\n\n## Function Signature\n### Function Signature _TypePromotionInterpreter.run_node\n- self: \n- node: fx.Node(p_trunk_attn_pool_proj_weight)[placeholder]:Tensor(f32[1024, 1024])\n## Return values\nTensor(f32[1024, 1024])", + "text":"Skipped p_trunk_attn_pool_proj_weight: not a call_function." + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":1625 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0015", + "stacks":[] + }, + { + "message":{ + "markdown":"Skipped p_trunk_attn_pool_proj_bias: not a call_function.\n\n## Additional Message:\n\n## Function Signature\n### Function Signature _TypePromotionInterpreter.run_node\n- self: \n- node: fx.Node(p_trunk_attn_pool_proj_bias)[placeholder]:Tensor(f32[1024])\n## Return values\nTensor(f32[1024])", + "text":"Skipped p_trunk_attn_pool_proj_bias: not a call_function." + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":1625 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0015", + "stacks":[] + }, + { + "message":{ + "markdown":"Skipped p_trunk_attn_pool_norm_weight: not a call_function.\n\n## Additional Message:\n\n## Function Signature\n### Function Signature _TypePromotionInterpreter.run_node\n- self: \n- node: fx.Node(p_trunk_attn_pool_norm_weight)[placeholder]:Tensor(f32[1024])\n## Return values\nTensor(f32[1024])", + "text":"Skipped p_trunk_attn_pool_norm_weight: not a call_function." + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":1625 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0015", + "stacks":[] + }, + { + "message":{ + "markdown":"Skipped p_trunk_attn_pool_norm_bias: not a call_function.\n\n## Additional Message:\n\n## Function Signature\n### Function Signature _TypePromotionInterpreter.run_node\n- self: \n- node: fx.Node(p_trunk_attn_pool_norm_bias)[placeholder]:Tensor(f32[1024])\n## Return values\nTensor(f32[1024])", + "text":"Skipped p_trunk_attn_pool_norm_bias: not a call_function." + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":1625 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0015", + "stacks":[] + }, + { + "message":{ + "markdown":"Skipped p_trunk_attn_pool_mlp_fc1_weight: not a call_function.\n\n## Additional Message:\n\n## Function Signature\n### Function Signature _TypePromotionInterpreter.run_node\n- self: \n- node: fx.Node(p_trunk_attn_pool_mlp_fc1_weight)[placeholder]:Tensor(f32[4096, 1024])\n## Return values\nTensor(f32[4096, 1024])", + "text":"Skipped p_trunk_attn_pool_mlp_fc1_weight: not a call_function." + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":1625 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0015", + "stacks":[] + }, + { + "message":{ + "markdown":"Skipped p_trunk_attn_pool_mlp_fc1_bias: not a call_function.\n\n## Additional Message:\n\n## Function Signature\n### Function Signature _TypePromotionInterpreter.run_node\n- self: \n- node: fx.Node(p_trunk_attn_pool_mlp_fc1_bias)[placeholder]:Tensor(f32[4096])\n## Return values\nTensor(f32[4096])", + "text":"Skipped p_trunk_attn_pool_mlp_fc1_bias: not a call_function." + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":1625 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0015", + "stacks":[] + }, + { + "message":{ + "markdown":"Skipped p_trunk_attn_pool_mlp_fc2_weight: not a call_function.\n\n## Additional Message:\n\n## Function Signature\n### Function Signature _TypePromotionInterpreter.run_node\n- self: \n- node: fx.Node(p_trunk_attn_pool_mlp_fc2_weight)[placeholder]:Tensor(f32[1024, 4096])\n## Return values\nTensor(f32[1024, 4096])", + "text":"Skipped p_trunk_attn_pool_mlp_fc2_weight: not a call_function." + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":1625 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0015", + "stacks":[] + }, + { + "message":{ + "markdown":"Skipped p_trunk_attn_pool_mlp_fc2_bias: not a call_function.\n\n## Additional Message:\n\n## Function Signature\n### Function Signature _TypePromotionInterpreter.run_node\n- self: \n- node: fx.Node(p_trunk_attn_pool_mlp_fc2_bias)[placeholder]:Tensor(f32[1024])\n## Return values\nTensor(f32[1024])", + "text":"Skipped p_trunk_attn_pool_mlp_fc2_bias: not a call_function." + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":1625 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0015", + "stacks":[] + }, + { + "message":{ + "markdown":"Skipped x: not a call_function.\n\n## Additional Message:\n\n## Function Signature\n### Function Signature _TypePromotionInterpreter.run_node\n- self: \n- node: fx.Node(x)[placeholder]:Tensor(f32[4, 3, 512, 512])\n## Return values\nTensor(f32[4, 3, 512, 512])", + "text":"Skipped x: not a call_function." + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":1625 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0015", + "stacks":[] + }, + { + "message":{ + "markdown":"Skipped for fx.Node(aten.convolution.default)[call_function]:Tensor(f32[4, 1024, 32, 32]): Cannot find type promotion rule for op: aten.convolution.default\n\n## Additional Message:\n\n## Function Signature\n### Function Signature _TypePromotionInterpreter.run_node\n- self: \n- node: fx.Node(aten.convolution.default)[call_function]:Tensor(f32[4, 1024, 32, 32])\n## Return values\nTensor(f32[4, 1024, 32, 32])", + "text":"Skipped for fx.Node(aten.convolution.default)[call_function]:Tensor(f32[4, 1024, 32, 32]): Cannot find type promotion rule for op: aten.convolution.default" + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":1625 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0015", + "stacks":[] + }, + { + "message":{ + "markdown":"Skipped for fx.Node(aten.view.default)[call_function]:Tensor(f32[4, 1024, 1024]): Cannot find type promotion rule for op: aten.view.default\n\n## Additional Message:\n\n## Function Signature\n### Function Signature _TypePromotionInterpreter.run_node\n- self: \n- node: fx.Node(aten.view.default)[call_function]:Tensor(f32[4, 1024, 1024])\n## Return values\nTensor(f32[4, 1024, 1024])", + "text":"Skipped for fx.Node(aten.view.default)[call_function]:Tensor(f32[4, 1024, 1024]): Cannot find type promotion rule for op: aten.view.default" + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":1625 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0015", + "stacks":[] + }, + { + "message":{ + "markdown":"Skipped for fx.Node(aten.transpose.int)[call_function]:Tensor(f32[4, 1024, 1024]): Cannot find type promotion rule for op: aten.transpose.int\n\n## Additional Message:\n\n## Function Signature\n### Function Signature _TypePromotionInterpreter.run_node\n- self: \n- node: fx.Node(aten.transpose.int)[call_function]:Tensor(f32[4, 1024, 1024])\n## Return values\nTensor(f32[4, 1024, 1024])", + "text":"Skipped for fx.Node(aten.transpose.int)[call_function]:Tensor(f32[4, 1024, 1024]): Cannot find type promotion rule for op: aten.transpose.int" + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":1625 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0015", + "stacks":[] + }, + { + "message":{ + "markdown":"Type promotion not needed for add. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature _TypePromotionInterpreter.run_node\n- self: \n- node: fx.Node(aten.add.Tensor)[call_function]:Tensor(f32[4, 1024, 1024])\nFound type promotion rule: ElementwiseTypePromotionRule('aten', 'add', [0, 1], [], ELEMENTWISE_TYPE_PROMOTION_KIND.DEFAULT)\nArgument transpose is not promoted. Already torch.float32.\nArgument p_trunk_pos_embed is not promoted. Already torch.float32.\n## Return values\nTensor(f32[4, 1024, 1024])", + "text":"Type promotion not needed for add. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":1625 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0015", + "stacks":[] + }, + { + "message":{ + "markdown":"Skipped for fx.Node(aten.clone.default)[call_function]:Tensor(f32[4, 1024, 1024]): Cannot find type promotion rule for op: aten.clone.default\n\n## Additional Message:\n\n## Function Signature\n### Function Signature _TypePromotionInterpreter.run_node\n- self: \n- node: fx.Node(aten.clone.default)[call_function]:Tensor(f32[4, 1024, 1024])\n## Return values\nTensor(f32[4, 1024, 1024])", + "text":"Skipped for fx.Node(aten.clone.default)[call_function]:Tensor(f32[4, 1024, 1024]): Cannot find type promotion rule for op: aten.clone.default" + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":1625 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0015", + "stacks":[] + }, + { + "message":{ + "markdown":"Skipped for fx.Node(aten.native_layer_norm.default)[call_function]:Tuple[length=3](\nTensor(f32[4, 1024, 1024]),\nTensor(f32[4, 1024, 1]),\nTensor(f32[4, 1024, 1]),\n): Cannot find type promotion rule for op: aten.native_layer_norm.default\n\n## Additional Message:\n\n## Function Signature\n### Function Signature _TypePromotionInterpreter.run_node\n- self: \n- node: fx.Node(aten.native_layer_norm.default)[call_function]:Tuple[length=3](\nTensor(f32[4, 1024, 1024]),\nTensor(f32[4, 1024, 1]),\nTensor(f32[4, 1024, 1]),\n)\n## Return values\nTuple[length=3](\nTensor(f32[4, 1024, 1024]),\nTensor(f32[4, 1024, 1]),\nTensor(f32[4, 1024, 1]),\n)", + "text":"Skipped for fx.Node(aten.native_layer_norm.default)[call_function]:Tuple[length=3](\nTensor(f32[4, 1024, 1024]),\nTensor(f32[4, 1024, 1]),\nTensor(f32[4, 1024, 1]),\n): Cannot find type promotion rule for op: aten.native_layer_norm.default" + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":1625 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0015", + "stacks":[] + }, + { + "message":{ + "markdown":"Skipped for fx.Node()[call_function]:Tensor(f32[4, 1024, 1024]): node.target is not OpOverload. Got type: \n\n## Additional Message:\n\n## Function Signature\n### Function Signature _TypePromotionInterpreter.run_node\n- self: \n- node: fx.Node()[call_function]:Tensor(f32[4, 1024, 1024])\n## Return values\nTensor(f32[4, 1024, 1024])", + "text":"Skipped for fx.Node()[call_function]:Tensor(f32[4, 1024, 1024]): node.target is not OpOverload. Got type: " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":1625 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0015", + "stacks":[] + }, + { + "message":{ + "markdown":"Skipped for fx.Node(aten.view.default)[call_function]:Tensor(f32[4096, 1024]): Cannot find type promotion rule for op: aten.view.default\n\n## Additional Message:\n\n## Function Signature\n### Function Signature _TypePromotionInterpreter.run_node\n- self: \n- node: fx.Node(aten.view.default)[call_function]:Tensor(f32[4096, 1024])\n## Return values\nTensor(f32[4096, 1024])", + "text":"Skipped for fx.Node(aten.view.default)[call_function]:Tensor(f32[4096, 1024]): Cannot find type promotion rule for op: aten.view.default" + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":1625 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0015", + "stacks":[] + }, + { + "message":{ + "markdown":"Skipped for fx.Node(aten.t.default)[call_function]:Tensor(f32[1024, 3072]): Cannot find type promotion rule for op: aten.t.default\n\n## Additional Message:\n\n## Function Signature\n### Function Signature _TypePromotionInterpreter.run_node\n- self: \n- node: fx.Node(aten.t.default)[call_function]:Tensor(f32[1024, 3072])\n## Return values\nTensor(f32[1024, 3072])", + "text":"Skipped for fx.Node(aten.t.default)[call_function]:Tensor(f32[1024, 3072]): Cannot find type promotion rule for op: aten.t.default" + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":1625 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0015", + "stacks":[] + }, + { + "message":{ + "markdown":"Skipped for fx.Node(aten.addmm.default)[call_function]:Tensor(f32[4096, 3072]): Cannot find type promotion rule for op: aten.addmm.default\n\n## Additional Message:\n\n## Function Signature\n### Function Signature _TypePromotionInterpreter.run_node\n- self: \n- node: fx.Node(aten.addmm.default)[call_function]:Tensor(f32[4096, 3072])\n## Return values\nTensor(f32[4096, 3072])", + "text":"Skipped for fx.Node(aten.addmm.default)[call_function]:Tensor(f32[4096, 3072]): Cannot find type promotion rule for op: aten.addmm.default" + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":1625 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0015", + "stacks":[] + }, + { + "message":{ + "markdown":"Skipped for fx.Node(aten.view.default)[call_function]:Tensor(f32[4, 1024, 3072]): Cannot find type promotion rule for op: aten.view.default\n\n## Additional Message:\n\n## Function Signature\n### Function Signature _TypePromotionInterpreter.run_node\n- self: \n- node: fx.Node(aten.view.default)[call_function]:Tensor(f32[4, 1024, 3072])\n## Return values\nTensor(f32[4, 1024, 3072])", + "text":"Skipped for fx.Node(aten.view.default)[call_function]:Tensor(f32[4, 1024, 3072]): Cannot find type promotion rule for op: aten.view.default" + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":1625 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0015", + "stacks":[] + }, + { + "message":{ + "markdown":"Skipped for fx.Node(aten.view.default)[call_function]:Tensor(f32[4, 1024, 3, 16, 64]): Cannot find type promotion rule for op: aten.view.default\n\n## Additional Message:\n\n## Function Signature\n### Function Signature _TypePromotionInterpreter.run_node\n- self: \n- node: fx.Node(aten.view.default)[call_function]:Tensor(f32[4, 1024, 3, 16, 64])\n## Return values\nTensor(f32[4, 1024, 3, 16, 64])", + "text":"Skipped for fx.Node(aten.view.default)[call_function]:Tensor(f32[4, 1024, 3, 16, 64]): Cannot find type promotion rule for op: aten.view.default" + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":1625 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0015", + "stacks":[] + }, + { + "message":{ + "markdown":"Skipped for fx.Node(aten.permute.default)[call_function]:Tensor(f32[3, 4, 16, 1024, 64]): Cannot find type promotion rule for op: aten.permute.default\n\n## Additional Message:\n\n## Function Signature\n### Function Signature _TypePromotionInterpreter.run_node\n- self: \n- node: fx.Node(aten.permute.default)[call_function]:Tensor(f32[3, 4, 16, 1024, 64])\n## Return values\nTensor(f32[3, 4, 16, 1024, 64])", + "text":"Skipped for fx.Node(aten.permute.default)[call_function]:Tensor(f32[3, 4, 16, 1024, 64]): Cannot find type promotion rule for op: aten.permute.default" + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":1625 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0015", + "stacks":[] + }, + { + "message":{ + "markdown":"Skipped for fx.Node(aten.unbind.int)[call_function]:List[length=3](\nTensor(f32[4, 16, 1024, 64]),\nTensor(f32[4, 16, 1024, 64]),\nTensor(f32[4, 16, 1024, 64]),\n): Cannot find type promotion rule for op: aten.unbind.int\n\n## Additional Message:\n\n## Function Signature\n### Function Signature _TypePromotionInterpreter.run_node\n- self: \n- node: fx.Node(aten.unbind.int)[call_function]:List[length=3](\nTensor(f32[4, 16, 1024, 64]),\nTensor(f32[4, 16, 1024, 64]),\nTensor(f32[4, 16, 1024, 64]),\n)\n## Return values\nList[length=3](\nTensor(f32[4, 16, 1024, 64]),\nTensor(f32[4, 16, 1024, 64]),\nTensor(f32[4, 16, 1024, 64]),\n)", + "text":"Skipped for fx.Node(aten.unbind.int)[call_function]:List[length=3](\nTensor(f32[4, 16, 1024, 64]),\nTensor(f32[4, 16, 1024, 64]),\nTensor(f32[4, 16, 1024, 64]),\n): Cannot find type promotion rule for op: aten.unbind.int" + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":1625 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0015", + "stacks":[] + }, + { + "message":{ + "markdown":"Skipped for fx.Node()[call_function]:Tensor(f32[4, 16, 1024, 64]): node.target is not OpOverload. Got type: \n\n## Additional Message:\n\n## Function Signature\n### Function Signature _TypePromotionInterpreter.run_node\n- self: \n- node: fx.Node()[call_function]:Tensor(f32[4, 16, 1024, 64])\n## Return values\nTensor(f32[4, 16, 1024, 64])", + "text":"Skipped for fx.Node()[call_function]:Tensor(f32[4, 16, 1024, 64]): node.target is not OpOverload. Got type: " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":1625 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0015", + "stacks":[] + }, + { + "message":{ + "markdown":"Skipped for fx.Node()[call_function]:Tensor(f32[4, 16, 1024, 64]): node.target is not OpOverload. Got type: \n\n## Additional Message:\n\n## Function Signature\n### Function Signature _TypePromotionInterpreter.run_node\n- self: \n- node: fx.Node()[call_function]:Tensor(f32[4, 16, 1024, 64])\n## Return values\nTensor(f32[4, 16, 1024, 64])", + "text":"Skipped for fx.Node()[call_function]:Tensor(f32[4, 16, 1024, 64]): node.target is not OpOverload. Got type: " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":1625 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0015", + "stacks":[] + }, + { + "message":{ + "markdown":"Skipped for fx.Node()[call_function]:Tensor(f32[4, 16, 1024, 64]): node.target is not OpOverload. Got type: \n\n## Additional Message:\n\n## Function Signature\n### Function Signature _TypePromotionInterpreter.run_node\n- self: \n- node: fx.Node()[call_function]:Tensor(f32[4, 16, 1024, 64])\n## Return values\nTensor(f32[4, 16, 1024, 64])", + "text":"Skipped for fx.Node()[call_function]:Tensor(f32[4, 16, 1024, 64]): node.target is not OpOverload. Got type: " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":1625 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0015", + "stacks":[] + }, + { + "message":{ + "markdown":"Skipped for fx.Node(aten._scaled_dot_product_efficient_attention.default)[call_function]:Tuple[length=4](\nTensor(f32[4, 16, 1024, 64]),\nTensor(f32[4, 16, 0]),\nTensor(i64[]),\nTensor(i64[]),\n): Cannot find type promotion rule for op: aten._scaled_dot_product_efficient_attention.default\n\n## Additional Message:\n\n## Function Signature\n### Function Signature _TypePromotionInterpreter.run_node\n- self: \n- node: fx.Node(aten._scaled_dot_product_efficient_attention.default)[call_function]:Tuple[length=4](\nTensor(f32[4, 16, 1024, 64]),\nTensor(f32[4, 16, 0]),\nTensor(i64[]),\nTensor(i64[]),\n)\n## Return values\nTuple[length=4](\nTensor(f32[4, 16, 1024, 64]),\nTensor(f32[4, 16, 0]),\nTensor(i64[]),\nTensor(i64[]),\n)", + "text":"Skipped for fx.Node(aten._scaled_dot_product_efficient_attention.default)[call_function]:Tuple[length=4](\nTensor(f32[4, 16, 1024, 64]),\nTensor(f32[4, 16, 0]),\nTensor(i64[]),\nTensor(i64[]),\n): Cannot find type promotion rule for op: aten._scaled_dot_product_efficient_attention.default" + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":1625 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0015", + "stacks":[] + }, + { + "message":{ + "markdown":"Skipped for fx.Node()[call_function]:Tensor(f32[4, 16, 1024, 64]): node.target is not OpOverload. Got type: \n\n## Additional Message:\n\n## Function Signature\n### Function Signature _TypePromotionInterpreter.run_node\n- self: \n- node: fx.Node()[call_function]:Tensor(f32[4, 16, 1024, 64])\n## Return values\nTensor(f32[4, 16, 1024, 64])", + "text":"Skipped for fx.Node()[call_function]:Tensor(f32[4, 16, 1024, 64]): node.target is not OpOverload. Got type: " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":1625 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0015", + "stacks":[] + }, + { + "message":{ + "markdown":"Skipped for fx.Node(aten.transpose.int)[call_function]:Tensor(f32[4, 1024, 16, 64]): Cannot find type promotion rule for op: aten.transpose.int\n\n## Additional Message:\n\n## Function Signature\n### Function Signature _TypePromotionInterpreter.run_node\n- self: \n- node: fx.Node(aten.transpose.int)[call_function]:Tensor(f32[4, 1024, 16, 64])\n## Return values\nTensor(f32[4, 1024, 16, 64])", + "text":"Skipped for fx.Node(aten.transpose.int)[call_function]:Tensor(f32[4, 1024, 16, 64]): Cannot find type promotion rule for op: aten.transpose.int" + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":1625 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0015", + "stacks":[] + }, + { + "message":{ + "markdown":"Skipped for fx.Node(aten.view.default)[call_function]:Tensor(f32[4, 1024, 1024]): Cannot find type promotion rule for op: aten.view.default\n\n## Additional Message:\n\n## Function Signature\n### Function Signature _TypePromotionInterpreter.run_node\n- self: \n- node: fx.Node(aten.view.default)[call_function]:Tensor(f32[4, 1024, 1024])\n## Return values\nTensor(f32[4, 1024, 1024])", + "text":"Skipped for fx.Node(aten.view.default)[call_function]:Tensor(f32[4, 1024, 1024]): Cannot find type promotion rule for op: aten.view.default" + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":1625 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0015", + "stacks":[] + }, + { + "message":{ + "markdown":"Skipped for fx.Node(aten.view.default)[call_function]:Tensor(f32[4096, 1024]): Cannot find type promotion rule for op: aten.view.default\n\n## Additional Message:\n\n## Function Signature\n### Function Signature _TypePromotionInterpreter.run_node\n- self: \n- node: fx.Node(aten.view.default)[call_function]:Tensor(f32[4096, 1024])\n## Return values\nTensor(f32[4096, 1024])", + "text":"Skipped for fx.Node(aten.view.default)[call_function]:Tensor(f32[4096, 1024]): Cannot find type promotion rule for op: aten.view.default" + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":1625 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0015", + "stacks":[] + }, + { + "message":{ + "markdown":"Skipped for fx.Node(aten.t.default)[call_function]:Tensor(f32[1024, 1024]): Cannot find type promotion rule for op: aten.t.default\n\n## Additional Message:\n\n## Function Signature\n### Function Signature _TypePromotionInterpreter.run_node\n- self: \n- node: fx.Node(aten.t.default)[call_function]:Tensor(f32[1024, 1024])\n## Return values\nTensor(f32[1024, 1024])", + "text":"Skipped for fx.Node(aten.t.default)[call_function]:Tensor(f32[1024, 1024]): Cannot find type promotion rule for op: aten.t.default" + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":1625 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0015", + "stacks":[] + }, + { + "message":{ + "markdown":"Skipped for fx.Node(aten.addmm.default)[call_function]:Tensor(f32[4096, 1024]): Cannot find type promotion rule for op: aten.addmm.default\n\n## Additional Message:\n\n## Function Signature\n### Function Signature _TypePromotionInterpreter.run_node\n- self: \n- node: fx.Node(aten.addmm.default)[call_function]:Tensor(f32[4096, 1024])\n## Return values\nTensor(f32[4096, 1024])", + "text":"Skipped for fx.Node(aten.addmm.default)[call_function]:Tensor(f32[4096, 1024]): Cannot find type promotion rule for op: aten.addmm.default" + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":1625 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0015", + "stacks":[] + }, + { + "message":{ + "markdown":"Skipped for fx.Node(aten.view.default)[call_function]:Tensor(f32[4, 1024, 1024]): Cannot find type promotion rule for op: aten.view.default\n\n## Additional Message:\n\n## Function Signature\n### Function Signature _TypePromotionInterpreter.run_node\n- self: \n- node: fx.Node(aten.view.default)[call_function]:Tensor(f32[4, 1024, 1024])\n## Return values\nTensor(f32[4, 1024, 1024])", + "text":"Skipped for fx.Node(aten.view.default)[call_function]:Tensor(f32[4, 1024, 1024]): Cannot find type promotion rule for op: aten.view.default" + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":1625 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0015", + "stacks":[] + }, + { + "message":{ + "markdown":"Skipped for fx.Node(aten.clone.default)[call_function]:Tensor(f32[4, 1024, 1024]): Cannot find type promotion rule for op: aten.clone.default\n\n## Additional Message:\n\n## Function Signature\n### Function Signature _TypePromotionInterpreter.run_node\n- self: \n- node: fx.Node(aten.clone.default)[call_function]:Tensor(f32[4, 1024, 1024])\n## Return values\nTensor(f32[4, 1024, 1024])", + "text":"Skipped for fx.Node(aten.clone.default)[call_function]:Tensor(f32[4, 1024, 1024]): Cannot find type promotion rule for op: aten.clone.default" + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":1625 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0015", + "stacks":[] + }, + { + "message":{ + "markdown":"Type promotion not needed for add_1. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature _TypePromotionInterpreter.run_node\n- self: \n- node: fx.Node(aten.add.Tensor)[call_function]:Tensor(f32[4, 1024, 1024])\nFound type promotion rule: ElementwiseTypePromotionRule('aten', 'add', [0, 1], [], ELEMENTWISE_TYPE_PROMOTION_KIND.DEFAULT)\nArgument clone is not promoted. Already torch.float32.\nArgument clone_1 is not promoted. Already torch.float32.\n## Return values\nTensor(f32[4, 1024, 1024])", + "text":"Type promotion not needed for add_1. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":1625 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0015", + "stacks":[] + }, + { + "message":{ + "markdown":"Skipped for fx.Node(aten.native_layer_norm.default)[call_function]:Tuple[length=3](\nTensor(f32[4, 1024, 1024]),\nTensor(f32[4, 1024, 1]),\nTensor(f32[4, 1024, 1]),\n): Cannot find type promotion rule for op: aten.native_layer_norm.default\n\n## Additional Message:\n\n## Function Signature\n### Function Signature _TypePromotionInterpreter.run_node\n- self: \n- node: fx.Node(aten.native_layer_norm.default)[call_function]:Tuple[length=3](\nTensor(f32[4, 1024, 1024]),\nTensor(f32[4, 1024, 1]),\nTensor(f32[4, 1024, 1]),\n)\n## Return values\nTuple[length=3](\nTensor(f32[4, 1024, 1024]),\nTensor(f32[4, 1024, 1]),\nTensor(f32[4, 1024, 1]),\n)", + "text":"Skipped for fx.Node(aten.native_layer_norm.default)[call_function]:Tuple[length=3](\nTensor(f32[4, 1024, 1024]),\nTensor(f32[4, 1024, 1]),\nTensor(f32[4, 1024, 1]),\n): Cannot find type promotion rule for op: aten.native_layer_norm.default" + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":1625 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0015", + "stacks":[] + }, + { + "message":{ + "markdown":"Skipped for fx.Node()[call_function]:Tensor(f32[4, 1024, 1024]): node.target is not OpOverload. Got type: \n\n## Additional Message:\n\n## Function Signature\n### Function Signature _TypePromotionInterpreter.run_node\n- self: \n- node: fx.Node()[call_function]:Tensor(f32[4, 1024, 1024])\n## Return values\nTensor(f32[4, 1024, 1024])", + "text":"Skipped for fx.Node()[call_function]:Tensor(f32[4, 1024, 1024]): node.target is not OpOverload. Got type: " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":1625 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0015", + "stacks":[] + }, + { + "message":{ + "markdown":"Skipped for fx.Node(aten.view.default)[call_function]:Tensor(f32[4096, 1024]): Cannot find type promotion rule for op: aten.view.default\n\n## Additional Message:\n\n## Function Signature\n### Function Signature _TypePromotionInterpreter.run_node\n- self: \n- node: fx.Node(aten.view.default)[call_function]:Tensor(f32[4096, 1024])\n## Return values\nTensor(f32[4096, 1024])", + "text":"Skipped for fx.Node(aten.view.default)[call_function]:Tensor(f32[4096, 1024]): Cannot find type promotion rule for op: aten.view.default" + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":1625 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0015", + "stacks":[] + }, + { + "message":{ + "markdown":"Skipped for fx.Node(aten.t.default)[call_function]:Tensor(f32[1024, 4096]): Cannot find type promotion rule for op: aten.t.default\n\n## Additional Message:\n\n## Function Signature\n### Function Signature _TypePromotionInterpreter.run_node\n- self: \n- node: fx.Node(aten.t.default)[call_function]:Tensor(f32[1024, 4096])\n## Return values\nTensor(f32[1024, 4096])", + "text":"Skipped for fx.Node(aten.t.default)[call_function]:Tensor(f32[1024, 4096]): Cannot find type promotion rule for op: aten.t.default" + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":1625 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0015", + "stacks":[] + }, + { + "message":{ + "markdown":"Skipped for fx.Node(aten.addmm.default)[call_function]:Tensor(f32[4096, 4096]): Cannot find type promotion rule for op: aten.addmm.default\n\n## Additional Message:\n\n## Function Signature\n### Function Signature _TypePromotionInterpreter.run_node\n- self: \n- node: fx.Node(aten.addmm.default)[call_function]:Tensor(f32[4096, 4096])\n## Return values\nTensor(f32[4096, 4096])", + "text":"Skipped for fx.Node(aten.addmm.default)[call_function]:Tensor(f32[4096, 4096]): Cannot find type promotion rule for op: aten.addmm.default" + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":1625 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0015", + "stacks":[] + }, + { + "message":{ + "markdown":"Skipped for fx.Node(aten.view.default)[call_function]:Tensor(f32[4, 1024, 4096]): Cannot find type promotion rule for op: aten.view.default\n\n## Additional Message:\n\n## Function Signature\n### Function Signature _TypePromotionInterpreter.run_node\n- self: \n- node: fx.Node(aten.view.default)[call_function]:Tensor(f32[4, 1024, 4096])\n## Return values\nTensor(f32[4, 1024, 4096])", + "text":"Skipped for fx.Node(aten.view.default)[call_function]:Tensor(f32[4, 1024, 4096]): Cannot find type promotion rule for op: aten.view.default" + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":1625 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0015", + "stacks":[] + }, + { + "message":{ + "markdown":"Type promotion not needed for gelu. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature _TypePromotionInterpreter.run_node\n- self: \n- node: fx.Node(aten.gelu.default)[call_function]:Tensor(f32[4, 1024, 4096])\nFound type promotion rule: ElementwiseTypePromotionRule('aten', 'gelu', [0], [], ELEMENTWISE_TYPE_PROMOTION_KIND.DEFAULT)\nArgument view_8 is not promoted. Already torch.float32.\nArgument tanh is not promoted. Not mentioned by type promotion rule.\n## Return values\nTensor(f32[4, 1024, 4096])", + "text":"Type promotion not needed for gelu. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":1625 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0015", + "stacks":[] + }, + { + "message":{ + "markdown":"Skipped for fx.Node(aten.clone.default)[call_function]:Tensor(f32[4, 1024, 4096]): Cannot find type promotion rule for op: aten.clone.default\n\n## Additional Message:\n\n## Function Signature\n### Function Signature _TypePromotionInterpreter.run_node\n- self: \n- node: fx.Node(aten.clone.default)[call_function]:Tensor(f32[4, 1024, 4096])\n## Return values\nTensor(f32[4, 1024, 4096])", + "text":"Skipped for fx.Node(aten.clone.default)[call_function]:Tensor(f32[4, 1024, 4096]): Cannot find type promotion rule for op: aten.clone.default" + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":1625 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0015", + "stacks":[] + }, + { + "message":{ + "markdown":"Skipped for fx.Node(aten.view.default)[call_function]:Tensor(f32[4096, 4096]): Cannot find type promotion rule for op: aten.view.default\n\n## Additional Message:\n\n## Function Signature\n### Function Signature _TypePromotionInterpreter.run_node\n- self: \n- node: fx.Node(aten.view.default)[call_function]:Tensor(f32[4096, 4096])\n## Return values\nTensor(f32[4096, 4096])", + "text":"Skipped for fx.Node(aten.view.default)[call_function]:Tensor(f32[4096, 4096]): Cannot find type promotion rule for op: aten.view.default" + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":1625 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0015", + "stacks":[] + }, + { + "message":{ + "markdown":"Skipped for fx.Node(aten.t.default)[call_function]:Tensor(f32[4096, 1024]): Cannot find type promotion rule for op: aten.t.default\n\n## Additional Message:\n\n## Function Signature\n### Function Signature _TypePromotionInterpreter.run_node\n- self: \n- node: fx.Node(aten.t.default)[call_function]:Tensor(f32[4096, 1024])\n## Return values\nTensor(f32[4096, 1024])", + "text":"Skipped for fx.Node(aten.t.default)[call_function]:Tensor(f32[4096, 1024]): Cannot find type promotion rule for op: aten.t.default" + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":1625 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0015", + "stacks":[] + }, + { + "message":{ + "markdown":"Skipped for fx.Node(aten.addmm.default)[call_function]:Tensor(f32[4096, 1024]): Cannot find type promotion rule for op: aten.addmm.default\n\n## Additional Message:\n\n## Function Signature\n### Function Signature _TypePromotionInterpreter.run_node\n- self: \n- node: fx.Node(aten.addmm.default)[call_function]:Tensor(f32[4096, 1024])\n## Return values\nTensor(f32[4096, 1024])", + "text":"Skipped for fx.Node(aten.addmm.default)[call_function]:Tensor(f32[4096, 1024]): Cannot find type promotion rule for op: aten.addmm.default" + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":1625 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0015", + "stacks":[] + }, + { + "message":{ + "markdown":"Skipped for fx.Node(aten.view.default)[call_function]:Tensor(f32[4, 1024, 1024]): Cannot find type promotion rule for op: aten.view.default\n\n## Additional Message:\n\n## Function Signature\n### Function Signature _TypePromotionInterpreter.run_node\n- self: \n- node: fx.Node(aten.view.default)[call_function]:Tensor(f32[4, 1024, 1024])\n## Return values\nTensor(f32[4, 1024, 1024])", + "text":"Skipped for fx.Node(aten.view.default)[call_function]:Tensor(f32[4, 1024, 1024]): Cannot find type promotion rule for op: aten.view.default" + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":1625 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0015", + "stacks":[] + }, + { + "message":{ + "markdown":"Skipped for fx.Node(aten.clone.default)[call_function]:Tensor(f32[4, 1024, 1024]): Cannot find type promotion rule for op: aten.clone.default\n\n## Additional Message:\n\n## Function Signature\n### Function Signature _TypePromotionInterpreter.run_node\n- self: \n- node: fx.Node(aten.clone.default)[call_function]:Tensor(f32[4, 1024, 1024])\n## Return values\nTensor(f32[4, 1024, 1024])", + "text":"Skipped for fx.Node(aten.clone.default)[call_function]:Tensor(f32[4, 1024, 1024]): Cannot find type promotion rule for op: aten.clone.default" + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":1625 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0015", + "stacks":[] + }, + { + "message":{ + "markdown":"Type promotion not needed for add_2. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature _TypePromotionInterpreter.run_node\n- self: \n- node: fx.Node(aten.add.Tensor)[call_function]:Tensor(f32[4, 1024, 1024])\nFound type promotion rule: ElementwiseTypePromotionRule('aten', 'add', [0, 1], [], ELEMENTWISE_TYPE_PROMOTION_KIND.DEFAULT)\nArgument add_1 is not promoted. Already torch.float32.\nArgument clone_3 is not promoted. Already torch.float32.\n## Return values\nTensor(f32[4, 1024, 1024])", + "text":"Type promotion not needed for add_2. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":1625 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0015", + "stacks":[] + }, + { + "message":{ + "markdown":"Skipped for fx.Node(aten.native_layer_norm.default)[call_function]:Tuple[length=3](\nTensor(f32[4, 1024, 1024]),\nTensor(f32[4, 1024, 1]),\nTensor(f32[4, 1024, 1]),\n): Cannot find type promotion rule for op: aten.native_layer_norm.default\n\n## Additional Message:\n\n## Function Signature\n### Function Signature _TypePromotionInterpreter.run_node\n- self: \n- node: fx.Node(aten.native_layer_norm.default)[call_function]:Tuple[length=3](\nTensor(f32[4, 1024, 1024]),\nTensor(f32[4, 1024, 1]),\nTensor(f32[4, 1024, 1]),\n)\n## Return values\nTuple[length=3](\nTensor(f32[4, 1024, 1024]),\nTensor(f32[4, 1024, 1]),\nTensor(f32[4, 1024, 1]),\n)", + "text":"Skipped for fx.Node(aten.native_layer_norm.default)[call_function]:Tuple[length=3](\nTensor(f32[4, 1024, 1024]),\nTensor(f32[4, 1024, 1]),\nTensor(f32[4, 1024, 1]),\n): Cannot find type promotion rule for op: aten.native_layer_norm.default" + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":1625 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0015", + "stacks":[] + }, + { + "message":{ + "markdown":"Skipped for fx.Node()[call_function]:Tensor(f32[4, 1024, 1024]): node.target is not OpOverload. Got type: \n\n## Additional Message:\n\n## Function Signature\n### Function Signature _TypePromotionInterpreter.run_node\n- self: \n- node: fx.Node()[call_function]:Tensor(f32[4, 1024, 1024])\n## Return values\nTensor(f32[4, 1024, 1024])", + "text":"Skipped for fx.Node()[call_function]:Tensor(f32[4, 1024, 1024]): node.target is not OpOverload. Got type: " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":1625 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0015", + "stacks":[] + }, + { + "message":{ + "markdown":"Skipped for fx.Node(aten.view.default)[call_function]:Tensor(f32[4096, 1024]): Cannot find type promotion rule for op: aten.view.default\n\n## Additional Message:\n\n## Function Signature\n### Function Signature _TypePromotionInterpreter.run_node\n- self: \n- node: fx.Node(aten.view.default)[call_function]:Tensor(f32[4096, 1024])\n## Return values\nTensor(f32[4096, 1024])", + "text":"Skipped for fx.Node(aten.view.default)[call_function]:Tensor(f32[4096, 1024]): Cannot find type promotion rule for op: aten.view.default" + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":1625 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0015", + "stacks":[] + }, + { + "message":{ + "markdown":"Skipped for fx.Node(aten.t.default)[call_function]:Tensor(f32[1024, 3072]): Cannot find type promotion rule for op: aten.t.default\n\n## Additional Message:\n\n## Function Signature\n### Function Signature _TypePromotionInterpreter.run_node\n- self: \n- node: fx.Node(aten.t.default)[call_function]:Tensor(f32[1024, 3072])\n## Return values\nTensor(f32[1024, 3072])", + "text":"Skipped for fx.Node(aten.t.default)[call_function]:Tensor(f32[1024, 3072]): Cannot find type promotion rule for op: aten.t.default" + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":1625 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0015", + "stacks":[] + }, + { + "message":{ + "markdown":"Skipped for fx.Node(aten.addmm.default)[call_function]:Tensor(f32[4096, 3072]): Cannot find type promotion rule for op: aten.addmm.default\n\n## Additional Message:\n\n## Function Signature\n### Function Signature _TypePromotionInterpreter.run_node\n- self: \n- node: fx.Node(aten.addmm.default)[call_function]:Tensor(f32[4096, 3072])\n## Return values\nTensor(f32[4096, 3072])", + "text":"Skipped for fx.Node(aten.addmm.default)[call_function]:Tensor(f32[4096, 3072]): Cannot find type promotion rule for op: aten.addmm.default" + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":1625 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0015", + "stacks":[] + }, + { + "message":{ + "markdown":"Skipped for fx.Node(aten.view.default)[call_function]:Tensor(f32[4, 1024, 3072]): Cannot find type promotion rule for op: aten.view.default\n\n## Additional Message:\n\n## Function Signature\n### Function Signature _TypePromotionInterpreter.run_node\n- self: \n- node: fx.Node(aten.view.default)[call_function]:Tensor(f32[4, 1024, 3072])\n## Return values\nTensor(f32[4, 1024, 3072])", + "text":"Skipped for fx.Node(aten.view.default)[call_function]:Tensor(f32[4, 1024, 3072]): Cannot find type promotion rule for op: aten.view.default" + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":1625 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0015", + "stacks":[] + }, + { + "message":{ + "markdown":"Skipped for fx.Node(aten.view.default)[call_function]:Tensor(f32[4, 1024, 3, 16, 64]): Cannot find type promotion rule for op: aten.view.default\n\n## Additional Message:\n\n## Function Signature\n### Function Signature _TypePromotionInterpreter.run_node\n- self: \n- node: fx.Node(aten.view.default)[call_function]:Tensor(f32[4, 1024, 3, 16, 64])\n## Return values\nTensor(f32[4, 1024, 3, 16, 64])", + "text":"Skipped for fx.Node(aten.view.default)[call_function]:Tensor(f32[4, 1024, 3, 16, 64]): Cannot find type promotion rule for op: aten.view.default" + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":1625 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0015", + "stacks":[] + }, + { + "message":{ + "markdown":"Skipped for fx.Node(aten.permute.default)[call_function]:Tensor(f32[3, 4, 16, 1024, 64]): Cannot find type promotion rule for op: aten.permute.default\n\n## Additional Message:\n\n## Function Signature\n### Function Signature _TypePromotionInterpreter.run_node\n- self: \n- node: fx.Node(aten.permute.default)[call_function]:Tensor(f32[3, 4, 16, 1024, 64])\n## Return values\nTensor(f32[3, 4, 16, 1024, 64])", + "text":"Skipped for fx.Node(aten.permute.default)[call_function]:Tensor(f32[3, 4, 16, 1024, 64]): Cannot find type promotion rule for op: aten.permute.default" + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":1625 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0015", + "stacks":[] + }, + { + "message":{ + "markdown":"Skipped for fx.Node(aten.unbind.int)[call_function]:List[length=3](\nTensor(f32[4, 16, 1024, 64]),\nTensor(f32[4, 16, 1024, 64]),\nTensor(f32[4, 16, 1024, 64]),\n): Cannot find type promotion rule for op: aten.unbind.int\n\n## Additional Message:\n\n## Function Signature\n### Function Signature _TypePromotionInterpreter.run_node\n- self: \n- node: fx.Node(aten.unbind.int)[call_function]:List[length=3](\nTensor(f32[4, 16, 1024, 64]),\nTensor(f32[4, 16, 1024, 64]),\nTensor(f32[4, 16, 1024, 64]),\n)\n## Return values\nList[length=3](\nTensor(f32[4, 16, 1024, 64]),\nTensor(f32[4, 16, 1024, 64]),\nTensor(f32[4, 16, 1024, 64]),\n)", + "text":"Skipped for fx.Node(aten.unbind.int)[call_function]:List[length=3](\nTensor(f32[4, 16, 1024, 64]),\nTensor(f32[4, 16, 1024, 64]),\nTensor(f32[4, 16, 1024, 64]),\n): Cannot find type promotion rule for op: aten.unbind.int" + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":1625 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0015", + "stacks":[] + }, + { + "message":{ + "markdown":"Skipped for fx.Node()[call_function]:Tensor(f32[4, 16, 1024, 64]): node.target is not OpOverload. Got type: \n\n## Additional Message:\n\n## Function Signature\n### Function Signature _TypePromotionInterpreter.run_node\n- self: \n- node: fx.Node()[call_function]:Tensor(f32[4, 16, 1024, 64])\n## Return values\nTensor(f32[4, 16, 1024, 64])", + "text":"Skipped for fx.Node()[call_function]:Tensor(f32[4, 16, 1024, 64]): node.target is not OpOverload. Got type: " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":1625 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0015", + "stacks":[] + }, + { + "message":{ + "markdown":"Skipped for fx.Node()[call_function]:Tensor(f32[4, 16, 1024, 64]): node.target is not OpOverload. Got type: \n\n## Additional Message:\n\n## Function Signature\n### Function Signature _TypePromotionInterpreter.run_node\n- self: \n- node: fx.Node()[call_function]:Tensor(f32[4, 16, 1024, 64])\n## Return values\nTensor(f32[4, 16, 1024, 64])", + "text":"Skipped for fx.Node()[call_function]:Tensor(f32[4, 16, 1024, 64]): node.target is not OpOverload. Got type: " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":1625 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0015", + "stacks":[] + }, + { + "message":{ + "markdown":"Skipped for fx.Node()[call_function]:Tensor(f32[4, 16, 1024, 64]): node.target is not OpOverload. Got type: \n\n## Additional Message:\n\n## Function Signature\n### Function Signature _TypePromotionInterpreter.run_node\n- self: \n- node: fx.Node()[call_function]:Tensor(f32[4, 16, 1024, 64])\n## Return values\nTensor(f32[4, 16, 1024, 64])", + "text":"Skipped for fx.Node()[call_function]:Tensor(f32[4, 16, 1024, 64]): node.target is not OpOverload. Got type: " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":1625 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0015", + "stacks":[] + }, + { + "message":{ + "markdown":"Skipped for fx.Node(aten._scaled_dot_product_efficient_attention.default)[call_function]:Tuple[length=4](\nTensor(f32[4, 16, 1024, 64]),\nTensor(f32[4, 16, 0]),\nTensor(i64[]),\nTensor(i64[]),\n): Cannot find type promotion rule for op: aten._scaled_dot_product_efficient_attention.default\n\n## Additional Message:\n\n## Function Signature\n### Function Signature _TypePromotionInterpreter.run_node\n- self: \n- node: fx.Node(aten._scaled_dot_product_efficient_attention.default)[call_function]:Tuple[length=4](\nTensor(f32[4, 16, 1024, 64]),\nTensor(f32[4, 16, 0]),\nTensor(i64[]),\nTensor(i64[]),\n)\n## Return values\nTuple[length=4](\nTensor(f32[4, 16, 1024, 64]),\nTensor(f32[4, 16, 0]),\nTensor(i64[]),\nTensor(i64[]),\n)", + "text":"Skipped for fx.Node(aten._scaled_dot_product_efficient_attention.default)[call_function]:Tuple[length=4](\nTensor(f32[4, 16, 1024, 64]),\nTensor(f32[4, 16, 0]),\nTensor(i64[]),\nTensor(i64[]),\n): Cannot find type promotion rule for op: aten._scaled_dot_product_efficient_attention.default" + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":1625 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0015", + "stacks":[] + }, + { + "message":{ + "markdown":"Skipped for fx.Node()[call_function]:Tensor(f32[4, 16, 1024, 64]): node.target is not OpOverload. Got type: \n\n## Additional Message:\n\n## Function Signature\n### Function Signature _TypePromotionInterpreter.run_node\n- self: \n- node: fx.Node()[call_function]:Tensor(f32[4, 16, 1024, 64])\n## Return values\nTensor(f32[4, 16, 1024, 64])", + "text":"Skipped for fx.Node()[call_function]:Tensor(f32[4, 16, 1024, 64]): node.target is not OpOverload. Got type: " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":1625 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0015", + "stacks":[] + }, + { + "message":{ + "markdown":"Skipped for fx.Node(aten.transpose.int)[call_function]:Tensor(f32[4, 1024, 16, 64]): Cannot find type promotion rule for op: aten.transpose.int\n\n## Additional Message:\n\n## Function Signature\n### Function Signature _TypePromotionInterpreter.run_node\n- self: \n- node: fx.Node(aten.transpose.int)[call_function]:Tensor(f32[4, 1024, 16, 64])\n## Return values\nTensor(f32[4, 1024, 16, 64])", + "text":"Skipped for fx.Node(aten.transpose.int)[call_function]:Tensor(f32[4, 1024, 16, 64]): Cannot find type promotion rule for op: aten.transpose.int" + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":1625 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0015", + "stacks":[] + }, + { + "message":{ + "markdown":"Skipped for fx.Node(aten.view.default)[call_function]:Tensor(f32[4, 1024, 1024]): Cannot find type promotion rule for op: aten.view.default\n\n## Additional Message:\n\n## Function Signature\n### Function Signature _TypePromotionInterpreter.run_node\n- self: \n- node: fx.Node(aten.view.default)[call_function]:Tensor(f32[4, 1024, 1024])\n## Return values\nTensor(f32[4, 1024, 1024])", + "text":"Skipped for fx.Node(aten.view.default)[call_function]:Tensor(f32[4, 1024, 1024]): Cannot find type promotion rule for op: aten.view.default" + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":1625 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0015", + "stacks":[] + }, + { + "message":{ + "markdown":"Skipped for fx.Node(aten.view.default)[call_function]:Tensor(f32[4096, 1024]): Cannot find type promotion rule for op: aten.view.default\n\n## Additional Message:\n\n## Function Signature\n### Function Signature _TypePromotionInterpreter.run_node\n- self: \n- node: fx.Node(aten.view.default)[call_function]:Tensor(f32[4096, 1024])\n## Return values\nTensor(f32[4096, 1024])", + "text":"Skipped for fx.Node(aten.view.default)[call_function]:Tensor(f32[4096, 1024]): Cannot find type promotion rule for op: aten.view.default" + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":1625 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0015", + "stacks":[] + }, + { + "message":{ + "markdown":"Skipped for fx.Node(aten.t.default)[call_function]:Tensor(f32[1024, 1024]): Cannot find type promotion rule for op: aten.t.default\n\n## Additional Message:\n\n## Function Signature\n### Function Signature _TypePromotionInterpreter.run_node\n- self: \n- node: fx.Node(aten.t.default)[call_function]:Tensor(f32[1024, 1024])\n## Return values\nTensor(f32[1024, 1024])", + "text":"Skipped for fx.Node(aten.t.default)[call_function]:Tensor(f32[1024, 1024]): Cannot find type promotion rule for op: aten.t.default" + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":1625 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0015", + "stacks":[] + }, + { + "message":{ + "markdown":"Skipped for fx.Node(aten.addmm.default)[call_function]:Tensor(f32[4096, 1024]): Cannot find type promotion rule for op: aten.addmm.default\n\n## Additional Message:\n\n## Function Signature\n### Function Signature _TypePromotionInterpreter.run_node\n- self: \n- node: fx.Node(aten.addmm.default)[call_function]:Tensor(f32[4096, 1024])\n## Return values\nTensor(f32[4096, 1024])", + "text":"Skipped for fx.Node(aten.addmm.default)[call_function]:Tensor(f32[4096, 1024]): Cannot find type promotion rule for op: aten.addmm.default" + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":1625 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0015", + "stacks":[] + }, + { + "message":{ + "markdown":"Skipped for fx.Node(aten.view.default)[call_function]:Tensor(f32[4, 1024, 1024]): Cannot find type promotion rule for op: aten.view.default\n\n## Additional Message:\n\n## Function Signature\n### Function Signature _TypePromotionInterpreter.run_node\n- self: \n- node: fx.Node(aten.view.default)[call_function]:Tensor(f32[4, 1024, 1024])\n## Return values\nTensor(f32[4, 1024, 1024])", + "text":"Skipped for fx.Node(aten.view.default)[call_function]:Tensor(f32[4, 1024, 1024]): Cannot find type promotion rule for op: aten.view.default" + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":1625 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0015", + "stacks":[] + }, + { + "message":{ + "markdown":"Skipped for fx.Node(aten.clone.default)[call_function]:Tensor(f32[4, 1024, 1024]): Cannot find type promotion rule for op: aten.clone.default\n\n## Additional Message:\n\n## Function Signature\n### Function Signature _TypePromotionInterpreter.run_node\n- self: \n- node: fx.Node(aten.clone.default)[call_function]:Tensor(f32[4, 1024, 1024])\n## Return values\nTensor(f32[4, 1024, 1024])", + "text":"Skipped for fx.Node(aten.clone.default)[call_function]:Tensor(f32[4, 1024, 1024]): Cannot find type promotion rule for op: aten.clone.default" + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":1625 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0015", + "stacks":[] + }, + { + "message":{ + "markdown":"Type promotion not needed for add_3. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature _TypePromotionInterpreter.run_node\n- self: \n- node: fx.Node(aten.add.Tensor)[call_function]:Tensor(f32[4, 1024, 1024])\nFound type promotion rule: ElementwiseTypePromotionRule('aten', 'add', [0, 1], [], ELEMENTWISE_TYPE_PROMOTION_KIND.DEFAULT)\nArgument add_2 is not promoted. Already torch.float32.\nArgument clone_4 is not promoted. Already torch.float32.\n## Return values\nTensor(f32[4, 1024, 1024])", + "text":"Type promotion not needed for add_3. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":1625 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0015", + "stacks":[] + }, + { + "message":{ + "markdown":"Skipped for fx.Node(aten.native_layer_norm.default)[call_function]:Tuple[length=3](\nTensor(f32[4, 1024, 1024]),\nTensor(f32[4, 1024, 1]),\nTensor(f32[4, 1024, 1]),\n): Cannot find type promotion rule for op: aten.native_layer_norm.default\n\n## Additional Message:\n\n## Function Signature\n### Function Signature _TypePromotionInterpreter.run_node\n- self: \n- node: fx.Node(aten.native_layer_norm.default)[call_function]:Tuple[length=3](\nTensor(f32[4, 1024, 1024]),\nTensor(f32[4, 1024, 1]),\nTensor(f32[4, 1024, 1]),\n)\n## Return values\nTuple[length=3](\nTensor(f32[4, 1024, 1024]),\nTensor(f32[4, 1024, 1]),\nTensor(f32[4, 1024, 1]),\n)", + "text":"Skipped for fx.Node(aten.native_layer_norm.default)[call_function]:Tuple[length=3](\nTensor(f32[4, 1024, 1024]),\nTensor(f32[4, 1024, 1]),\nTensor(f32[4, 1024, 1]),\n): Cannot find type promotion rule for op: aten.native_layer_norm.default" + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":1625 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0015", + "stacks":[] + }, + { + "message":{ + "markdown":"Skipped for fx.Node()[call_function]:Tensor(f32[4, 1024, 1024]): node.target is not OpOverload. Got type: \n\n## Additional Message:\n\n## Function Signature\n### Function Signature _TypePromotionInterpreter.run_node\n- self: \n- node: fx.Node()[call_function]:Tensor(f32[4, 1024, 1024])\n## Return values\nTensor(f32[4, 1024, 1024])", + "text":"Skipped for fx.Node()[call_function]:Tensor(f32[4, 1024, 1024]): node.target is not OpOverload. Got type: " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":1625 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0015", + "stacks":[] + }, + { + "message":{ + "markdown":"Skipped for fx.Node(aten.view.default)[call_function]:Tensor(f32[4096, 1024]): Cannot find type promotion rule for op: aten.view.default\n\n## Additional Message:\n\n## Function Signature\n### Function Signature _TypePromotionInterpreter.run_node\n- self: \n- node: fx.Node(aten.view.default)[call_function]:Tensor(f32[4096, 1024])\n## Return values\nTensor(f32[4096, 1024])", + "text":"Skipped for fx.Node(aten.view.default)[call_function]:Tensor(f32[4096, 1024]): Cannot find type promotion rule for op: aten.view.default" + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":1625 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0015", + "stacks":[] + }, + { + "message":{ + "markdown":"Skipped for fx.Node(aten.t.default)[call_function]:Tensor(f32[1024, 4096]): Cannot find type promotion rule for op: aten.t.default\n\n## Additional Message:\n\n## Function Signature\n### Function Signature _TypePromotionInterpreter.run_node\n- self: \n- node: fx.Node(aten.t.default)[call_function]:Tensor(f32[1024, 4096])\n## Return values\nTensor(f32[1024, 4096])", + "text":"Skipped for fx.Node(aten.t.default)[call_function]:Tensor(f32[1024, 4096]): Cannot find type promotion rule for op: aten.t.default" + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":1625 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0015", + "stacks":[] + }, + { + "message":{ + "markdown":"Skipped for fx.Node(aten.addmm.default)[call_function]:Tensor(f32[4096, 4096]): Cannot find type promotion rule for op: aten.addmm.default\n\n## Additional Message:\n\n## Function Signature\n### Function Signature _TypePromotionInterpreter.run_node\n- self: \n- node: fx.Node(aten.addmm.default)[call_function]:Tensor(f32[4096, 4096])\n## Return values\nTensor(f32[4096, 4096])", + "text":"Skipped for fx.Node(aten.addmm.default)[call_function]:Tensor(f32[4096, 4096]): Cannot find type promotion rule for op: aten.addmm.default" + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":1625 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0015", + "stacks":[] + }, + { + "message":{ + "markdown":"Skipped for fx.Node(aten.view.default)[call_function]:Tensor(f32[4, 1024, 4096]): Cannot find type promotion rule for op: aten.view.default\n\n## Additional Message:\n\n## Function Signature\n### Function Signature _TypePromotionInterpreter.run_node\n- self: \n- node: fx.Node(aten.view.default)[call_function]:Tensor(f32[4, 1024, 4096])\n## Return values\nTensor(f32[4, 1024, 4096])", + "text":"Skipped for fx.Node(aten.view.default)[call_function]:Tensor(f32[4, 1024, 4096]): Cannot find type promotion rule for op: aten.view.default" + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":1625 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0015", + "stacks":[] + }, + { + "message":{ + "markdown":"Type promotion not needed for gelu_1. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature _TypePromotionInterpreter.run_node\n- self: \n- node: fx.Node(aten.gelu.default)[call_function]:Tensor(f32[4, 1024, 4096])\nFound type promotion rule: ElementwiseTypePromotionRule('aten', 'gelu', [0], [], ELEMENTWISE_TYPE_PROMOTION_KIND.DEFAULT)\nArgument view_18 is not promoted. Already torch.float32.\nArgument tanh is not promoted. Not mentioned by type promotion rule.\n## Return values\nTensor(f32[4, 1024, 4096])", + "text":"Type promotion not needed for gelu_1. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":1625 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0015", + "stacks":[] + }, + { + "message":{ + "markdown":"Skipped for fx.Node(aten.clone.default)[call_function]:Tensor(f32[4, 1024, 4096]): Cannot find type promotion rule for op: aten.clone.default\n\n## Additional Message:\n\n## Function Signature\n### Function Signature _TypePromotionInterpreter.run_node\n- self: \n- node: fx.Node(aten.clone.default)[call_function]:Tensor(f32[4, 1024, 4096])\n## Return values\nTensor(f32[4, 1024, 4096])", + "text":"Skipped for fx.Node(aten.clone.default)[call_function]:Tensor(f32[4, 1024, 4096]): Cannot find type promotion rule for op: aten.clone.default" + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":1625 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0015", + "stacks":[] + }, + { + "message":{ + "markdown":"Skipped for fx.Node(aten.view.default)[call_function]:Tensor(f32[4096, 4096]): Cannot find type promotion rule for op: aten.view.default\n\n## Additional Message:\n\n## Function Signature\n### Function Signature _TypePromotionInterpreter.run_node\n- self: \n- node: fx.Node(aten.view.default)[call_function]:Tensor(f32[4096, 4096])\n## Return values\nTensor(f32[4096, 4096])", + "text":"Skipped for fx.Node(aten.view.default)[call_function]:Tensor(f32[4096, 4096]): Cannot find type promotion rule for op: aten.view.default" + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":1625 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0015", + "stacks":[] + }, + { + "message":{ + "markdown":"Skipped for fx.Node(aten.t.default)[call_function]:Tensor(f32[4096, 1024]): Cannot find type promotion rule for op: aten.t.default\n\n## Additional Message:\n\n## Function Signature\n### Function Signature _TypePromotionInterpreter.run_node\n- self: \n- node: fx.Node(aten.t.default)[call_function]:Tensor(f32[4096, 1024])\n## Return values\nTensor(f32[4096, 1024])", + "text":"Skipped for fx.Node(aten.t.default)[call_function]:Tensor(f32[4096, 1024]): Cannot find type promotion rule for op: aten.t.default" + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":1625 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0015", + "stacks":[] + }, + { + "message":{ + "markdown":"Skipped for fx.Node(aten.addmm.default)[call_function]:Tensor(f32[4096, 1024]): Cannot find type promotion rule for op: aten.addmm.default\n\n## Additional Message:\n\n## Function Signature\n### Function Signature _TypePromotionInterpreter.run_node\n- self: \n- node: fx.Node(aten.addmm.default)[call_function]:Tensor(f32[4096, 1024])\n## Return values\nTensor(f32[4096, 1024])", + "text":"Skipped for fx.Node(aten.addmm.default)[call_function]:Tensor(f32[4096, 1024]): Cannot find type promotion rule for op: aten.addmm.default" + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":1625 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0015", + "stacks":[] + }, + { + "message":{ + "markdown":"Skipped for fx.Node(aten.view.default)[call_function]:Tensor(f32[4, 1024, 1024]): Cannot find type promotion rule for op: aten.view.default\n\n## Additional Message:\n\n## Function Signature\n### Function Signature _TypePromotionInterpreter.run_node\n- self: \n- node: fx.Node(aten.view.default)[call_function]:Tensor(f32[4, 1024, 1024])\n## Return values\nTensor(f32[4, 1024, 1024])", + "text":"Skipped for fx.Node(aten.view.default)[call_function]:Tensor(f32[4, 1024, 1024]): Cannot find type promotion rule for op: aten.view.default" + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":1625 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0015", + "stacks":[] + }, + { + "message":{ + "markdown":"Skipped for fx.Node(aten.clone.default)[call_function]:Tensor(f32[4, 1024, 1024]): Cannot find type promotion rule for op: aten.clone.default\n\n## Additional Message:\n\n## Function Signature\n### Function Signature _TypePromotionInterpreter.run_node\n- self: \n- node: fx.Node(aten.clone.default)[call_function]:Tensor(f32[4, 1024, 1024])\n## Return values\nTensor(f32[4, 1024, 1024])", + "text":"Skipped for fx.Node(aten.clone.default)[call_function]:Tensor(f32[4, 1024, 1024]): Cannot find type promotion rule for op: aten.clone.default" + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":1625 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0015", + "stacks":[] + }, + { + "message":{ + "markdown":"Type promotion not needed for add_4. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature _TypePromotionInterpreter.run_node\n- self: \n- node: fx.Node(aten.add.Tensor)[call_function]:Tensor(f32[4, 1024, 1024])\nFound type promotion rule: ElementwiseTypePromotionRule('aten', 'add', [0, 1], [], ELEMENTWISE_TYPE_PROMOTION_KIND.DEFAULT)\nArgument add_3 is not promoted. Already torch.float32.\nArgument clone_6 is not promoted. Already torch.float32.\n## Return values\nTensor(f32[4, 1024, 1024])", + "text":"Type promotion not needed for add_4. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":1625 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0015", + "stacks":[] + }, + { + "message":{ + "markdown":"Skipped for fx.Node(aten.native_layer_norm.default)[call_function]:Tuple[length=3](\nTensor(f32[4, 1024, 1024]),\nTensor(f32[4, 1024, 1]),\nTensor(f32[4, 1024, 1]),\n): Cannot find type promotion rule for op: aten.native_layer_norm.default\n\n## Additional Message:\n\n## Function Signature\n### Function Signature _TypePromotionInterpreter.run_node\n- self: \n- node: fx.Node(aten.native_layer_norm.default)[call_function]:Tuple[length=3](\nTensor(f32[4, 1024, 1024]),\nTensor(f32[4, 1024, 1]),\nTensor(f32[4, 1024, 1]),\n)\n## Return values\nTuple[length=3](\nTensor(f32[4, 1024, 1024]),\nTensor(f32[4, 1024, 1]),\nTensor(f32[4, 1024, 1]),\n)", + "text":"Skipped for fx.Node(aten.native_layer_norm.default)[call_function]:Tuple[length=3](\nTensor(f32[4, 1024, 1024]),\nTensor(f32[4, 1024, 1]),\nTensor(f32[4, 1024, 1]),\n): Cannot find type promotion rule for op: aten.native_layer_norm.default" + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":1625 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0015", + "stacks":[] + }, + { + "message":{ + "markdown":"Skipped for fx.Node()[call_function]:Tensor(f32[4, 1024, 1024]): node.target is not OpOverload. Got type: \n\n## Additional Message:\n\n## Function Signature\n### Function Signature _TypePromotionInterpreter.run_node\n- self: \n- node: fx.Node()[call_function]:Tensor(f32[4, 1024, 1024])\n## Return values\nTensor(f32[4, 1024, 1024])", + "text":"Skipped for fx.Node()[call_function]:Tensor(f32[4, 1024, 1024]): node.target is not OpOverload. Got type: " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":1625 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0015", + "stacks":[] + }, + { + "message":{ + "markdown":"Skipped for fx.Node(aten.view.default)[call_function]:Tensor(f32[4096, 1024]): Cannot find type promotion rule for op: aten.view.default\n\n## Additional Message:\n\n## Function Signature\n### Function Signature _TypePromotionInterpreter.run_node\n- self: \n- node: fx.Node(aten.view.default)[call_function]:Tensor(f32[4096, 1024])\n## Return values\nTensor(f32[4096, 1024])", + "text":"Skipped for fx.Node(aten.view.default)[call_function]:Tensor(f32[4096, 1024]): Cannot find type promotion rule for op: aten.view.default" + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":1625 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0015", + "stacks":[] + }, + { + "message":{ + "markdown":"Skipped for fx.Node(aten.t.default)[call_function]:Tensor(f32[1024, 3072]): Cannot find type promotion rule for op: aten.t.default\n\n## Additional Message:\n\n## Function Signature\n### Function Signature _TypePromotionInterpreter.run_node\n- self: \n- node: fx.Node(aten.t.default)[call_function]:Tensor(f32[1024, 3072])\n## Return values\nTensor(f32[1024, 3072])", + "text":"Skipped for fx.Node(aten.t.default)[call_function]:Tensor(f32[1024, 3072]): Cannot find type promotion rule for op: aten.t.default" + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":1625 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0015", + "stacks":[] + }, + { + "message":{ + "markdown":"Skipped for fx.Node(aten.addmm.default)[call_function]:Tensor(f32[4096, 3072]): Cannot find type promotion rule for op: aten.addmm.default\n\n## Additional Message:\n\n## Function Signature\n### Function Signature _TypePromotionInterpreter.run_node\n- self: \n- node: fx.Node(aten.addmm.default)[call_function]:Tensor(f32[4096, 3072])\n## Return values\nTensor(f32[4096, 3072])", + "text":"Skipped for fx.Node(aten.addmm.default)[call_function]:Tensor(f32[4096, 3072]): Cannot find type promotion rule for op: aten.addmm.default" + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":1625 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0015", + "stacks":[] + }, + { + "message":{ + "markdown":"Skipped for fx.Node(aten.view.default)[call_function]:Tensor(f32[4, 1024, 3072]): Cannot find type promotion rule for op: aten.view.default\n\n## Additional Message:\n\n## Function Signature\n### Function Signature _TypePromotionInterpreter.run_node\n- self: \n- node: fx.Node(aten.view.default)[call_function]:Tensor(f32[4, 1024, 3072])\n## Return values\nTensor(f32[4, 1024, 3072])", + "text":"Skipped for fx.Node(aten.view.default)[call_function]:Tensor(f32[4, 1024, 3072]): Cannot find type promotion rule for op: aten.view.default" + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":1625 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0015", + "stacks":[] + }, + { + "message":{ + "markdown":"Skipped for fx.Node(aten.view.default)[call_function]:Tensor(f32[4, 1024, 3, 16, 64]): Cannot find type promotion rule for op: aten.view.default\n\n## Additional Message:\n\n## Function Signature\n### Function Signature _TypePromotionInterpreter.run_node\n- self: \n- node: fx.Node(aten.view.default)[call_function]:Tensor(f32[4, 1024, 3, 16, 64])\n## Return values\nTensor(f32[4, 1024, 3, 16, 64])", + "text":"Skipped for fx.Node(aten.view.default)[call_function]:Tensor(f32[4, 1024, 3, 16, 64]): Cannot find type promotion rule for op: aten.view.default" + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":1625 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0015", + "stacks":[] + }, + { + "message":{ + "markdown":"Skipped for fx.Node(aten.permute.default)[call_function]:Tensor(f32[3, 4, 16, 1024, 64]): Cannot find type promotion rule for op: aten.permute.default\n\n## Additional Message:\n\n## Function Signature\n### Function Signature _TypePromotionInterpreter.run_node\n- self: \n- node: fx.Node(aten.permute.default)[call_function]:Tensor(f32[3, 4, 16, 1024, 64])\n## Return values\nTensor(f32[3, 4, 16, 1024, 64])", + "text":"Skipped for fx.Node(aten.permute.default)[call_function]:Tensor(f32[3, 4, 16, 1024, 64]): Cannot find type promotion rule for op: aten.permute.default" + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":1625 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0015", + "stacks":[] + }, + { + "message":{ + "markdown":"Skipped for fx.Node(aten.unbind.int)[call_function]:List[length=3](\nTensor(f32[4, 16, 1024, 64]),\nTensor(f32[4, 16, 1024, 64]),\nTensor(f32[4, 16, 1024, 64]),\n): Cannot find type promotion rule for op: aten.unbind.int\n\n## Additional Message:\n\n## Function Signature\n### Function Signature _TypePromotionInterpreter.run_node\n- self: \n- node: fx.Node(aten.unbind.int)[call_function]:List[length=3](\nTensor(f32[4, 16, 1024, 64]),\nTensor(f32[4, 16, 1024, 64]),\nTensor(f32[4, 16, 1024, 64]),\n)\n## Return values\nList[length=3](\nTensor(f32[4, 16, 1024, 64]),\nTensor(f32[4, 16, 1024, 64]),\nTensor(f32[4, 16, 1024, 64]),\n)", + "text":"Skipped for fx.Node(aten.unbind.int)[call_function]:List[length=3](\nTensor(f32[4, 16, 1024, 64]),\nTensor(f32[4, 16, 1024, 64]),\nTensor(f32[4, 16, 1024, 64]),\n): Cannot find type promotion rule for op: aten.unbind.int" + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":1625 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0015", + "stacks":[] + }, + { + "message":{ + "markdown":"Skipped for fx.Node()[call_function]:Tensor(f32[4, 16, 1024, 64]): node.target is not OpOverload. Got type: \n\n## Additional Message:\n\n## Function Signature\n### Function Signature _TypePromotionInterpreter.run_node\n- self: \n- node: fx.Node()[call_function]:Tensor(f32[4, 16, 1024, 64])\n## Return values\nTensor(f32[4, 16, 1024, 64])", + "text":"Skipped for fx.Node()[call_function]:Tensor(f32[4, 16, 1024, 64]): node.target is not OpOverload. Got type: " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":1625 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0015", + "stacks":[] + }, + { + "message":{ + "markdown":"Skipped for fx.Node()[call_function]:Tensor(f32[4, 16, 1024, 64]): node.target is not OpOverload. Got type: \n\n## Additional Message:\n\n## Function Signature\n### Function Signature _TypePromotionInterpreter.run_node\n- self: \n- node: fx.Node()[call_function]:Tensor(f32[4, 16, 1024, 64])\n## Return values\nTensor(f32[4, 16, 1024, 64])", + "text":"Skipped for fx.Node()[call_function]:Tensor(f32[4, 16, 1024, 64]): node.target is not OpOverload. Got type: " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":1625 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0015", + "stacks":[] + }, + { + "message":{ + "markdown":"Skipped for fx.Node()[call_function]:Tensor(f32[4, 16, 1024, 64]): node.target is not OpOverload. Got type: \n\n## Additional Message:\n\n## Function Signature\n### Function Signature _TypePromotionInterpreter.run_node\n- self: \n- node: fx.Node()[call_function]:Tensor(f32[4, 16, 1024, 64])\n## Return values\nTensor(f32[4, 16, 1024, 64])", + "text":"Skipped for fx.Node()[call_function]:Tensor(f32[4, 16, 1024, 64]): node.target is not OpOverload. Got type: " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":1625 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0015", + "stacks":[] + }, + { + "message":{ + "markdown":"Skipped for fx.Node(aten._scaled_dot_product_efficient_attention.default)[call_function]:Tuple[length=4](\nTensor(f32[4, 16, 1024, 64]),\nTensor(f32[4, 16, 0]),\nTensor(i64[]),\nTensor(i64[]),\n): Cannot find type promotion rule for op: aten._scaled_dot_product_efficient_attention.default\n\n## Additional Message:\n\n## Function Signature\n### Function Signature _TypePromotionInterpreter.run_node\n- self: \n- node: fx.Node(aten._scaled_dot_product_efficient_attention.default)[call_function]:Tuple[length=4](\nTensor(f32[4, 16, 1024, 64]),\nTensor(f32[4, 16, 0]),\nTensor(i64[]),\nTensor(i64[]),\n)\n## Return values\nTuple[length=4](\nTensor(f32[4, 16, 1024, 64]),\nTensor(f32[4, 16, 0]),\nTensor(i64[]),\nTensor(i64[]),\n)", + "text":"Skipped for fx.Node(aten._scaled_dot_product_efficient_attention.default)[call_function]:Tuple[length=4](\nTensor(f32[4, 16, 1024, 64]),\nTensor(f32[4, 16, 0]),\nTensor(i64[]),\nTensor(i64[]),\n): Cannot find type promotion rule for op: aten._scaled_dot_product_efficient_attention.default" + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":1625 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0015", + "stacks":[] + }, + { + "message":{ + "markdown":"Skipped for fx.Node()[call_function]:Tensor(f32[4, 16, 1024, 64]): node.target is not OpOverload. Got type: \n\n## Additional Message:\n\n## Function Signature\n### Function Signature _TypePromotionInterpreter.run_node\n- self: \n- node: fx.Node()[call_function]:Tensor(f32[4, 16, 1024, 64])\n## Return values\nTensor(f32[4, 16, 1024, 64])", + "text":"Skipped for fx.Node()[call_function]:Tensor(f32[4, 16, 1024, 64]): node.target is not OpOverload. Got type: " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":1625 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0015", + "stacks":[] + }, + { + "message":{ + "markdown":"Skipped for fx.Node(aten.transpose.int)[call_function]:Tensor(f32[4, 1024, 16, 64]): Cannot find type promotion rule for op: aten.transpose.int\n\n## Additional Message:\n\n## Function Signature\n### Function Signature _TypePromotionInterpreter.run_node\n- self: \n- node: fx.Node(aten.transpose.int)[call_function]:Tensor(f32[4, 1024, 16, 64])\n## Return values\nTensor(f32[4, 1024, 16, 64])", + "text":"Skipped for fx.Node(aten.transpose.int)[call_function]:Tensor(f32[4, 1024, 16, 64]): Cannot find type promotion rule for op: aten.transpose.int" + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":1625 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0015", + "stacks":[] + }, + { + "message":{ + "markdown":"Skipped for fx.Node(aten.view.default)[call_function]:Tensor(f32[4, 1024, 1024]): Cannot find type promotion rule for op: aten.view.default\n\n## Additional Message:\n\n## Function Signature\n### Function Signature _TypePromotionInterpreter.run_node\n- self: \n- node: fx.Node(aten.view.default)[call_function]:Tensor(f32[4, 1024, 1024])\n## Return values\nTensor(f32[4, 1024, 1024])", + "text":"Skipped for fx.Node(aten.view.default)[call_function]:Tensor(f32[4, 1024, 1024]): Cannot find type promotion rule for op: aten.view.default" + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":1625 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0015", + "stacks":[] + }, + { + "message":{ + "markdown":"Skipped for fx.Node(aten.view.default)[call_function]:Tensor(f32[4096, 1024]): Cannot find type promotion rule for op: aten.view.default\n\n## Additional Message:\n\n## Function Signature\n### Function Signature _TypePromotionInterpreter.run_node\n- self: \n- node: fx.Node(aten.view.default)[call_function]:Tensor(f32[4096, 1024])\n## Return values\nTensor(f32[4096, 1024])", + "text":"Skipped for fx.Node(aten.view.default)[call_function]:Tensor(f32[4096, 1024]): Cannot find type promotion rule for op: aten.view.default" + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":1625 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0015", + "stacks":[] + }, + { + "message":{ + "markdown":"Skipped for fx.Node(aten.t.default)[call_function]:Tensor(f32[1024, 1024]): Cannot find type promotion rule for op: aten.t.default\n\n## Additional Message:\n\n## Function Signature\n### Function Signature _TypePromotionInterpreter.run_node\n- self: \n- node: fx.Node(aten.t.default)[call_function]:Tensor(f32[1024, 1024])\n## Return values\nTensor(f32[1024, 1024])", + "text":"Skipped for fx.Node(aten.t.default)[call_function]:Tensor(f32[1024, 1024]): Cannot find type promotion rule for op: aten.t.default" + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":1625 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0015", + "stacks":[] + }, + { + "message":{ + "markdown":"Skipped for fx.Node(aten.addmm.default)[call_function]:Tensor(f32[4096, 1024]): Cannot find type promotion rule for op: aten.addmm.default\n\n## Additional Message:\n\n## Function Signature\n### Function Signature _TypePromotionInterpreter.run_node\n- self: \n- node: fx.Node(aten.addmm.default)[call_function]:Tensor(f32[4096, 1024])\n## Return values\nTensor(f32[4096, 1024])", + "text":"Skipped for fx.Node(aten.addmm.default)[call_function]:Tensor(f32[4096, 1024]): Cannot find type promotion rule for op: aten.addmm.default" + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":1625 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0015", + "stacks":[] + }, + { + "message":{ + "markdown":"Skipped for fx.Node(aten.view.default)[call_function]:Tensor(f32[4, 1024, 1024]): Cannot find type promotion rule for op: aten.view.default\n\n## Additional Message:\n\n## Function Signature\n### Function Signature _TypePromotionInterpreter.run_node\n- self: \n- node: fx.Node(aten.view.default)[call_function]:Tensor(f32[4, 1024, 1024])\n## Return values\nTensor(f32[4, 1024, 1024])", + "text":"Skipped for fx.Node(aten.view.default)[call_function]:Tensor(f32[4, 1024, 1024]): Cannot find type promotion rule for op: aten.view.default" + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":1625 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0015", + "stacks":[] + }, + { + "message":{ + "markdown":"Skipped for fx.Node(aten.clone.default)[call_function]:Tensor(f32[4, 1024, 1024]): Cannot find type promotion rule for op: aten.clone.default\n\n## Additional Message:\n\n## Function Signature\n### Function Signature _TypePromotionInterpreter.run_node\n- self: \n- node: fx.Node(aten.clone.default)[call_function]:Tensor(f32[4, 1024, 1024])\n## Return values\nTensor(f32[4, 1024, 1024])", + "text":"Skipped for fx.Node(aten.clone.default)[call_function]:Tensor(f32[4, 1024, 1024]): Cannot find type promotion rule for op: aten.clone.default" + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":1625 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0015", + "stacks":[] + }, + { + "message":{ + "markdown":"Type promotion not needed for add_5. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature _TypePromotionInterpreter.run_node\n- self: \n- node: fx.Node(aten.add.Tensor)[call_function]:Tensor(f32[4, 1024, 1024])\nFound type promotion rule: ElementwiseTypePromotionRule('aten', 'add', [0, 1], [], ELEMENTWISE_TYPE_PROMOTION_KIND.DEFAULT)\nArgument add_4 is not promoted. Already torch.float32.\nArgument clone_7 is not promoted. Already torch.float32.\n## Return values\nTensor(f32[4, 1024, 1024])", + "text":"Type promotion not needed for add_5. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":1625 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0015", + "stacks":[] + }, + { + "message":{ + "markdown":"Skipped for fx.Node(aten.native_layer_norm.default)[call_function]:Tuple[length=3](\nTensor(f32[4, 1024, 1024]),\nTensor(f32[4, 1024, 1]),\nTensor(f32[4, 1024, 1]),\n): Cannot find type promotion rule for op: aten.native_layer_norm.default\n\n## Additional Message:\n\n## Function Signature\n### Function Signature _TypePromotionInterpreter.run_node\n- self: \n- node: fx.Node(aten.native_layer_norm.default)[call_function]:Tuple[length=3](\nTensor(f32[4, 1024, 1024]),\nTensor(f32[4, 1024, 1]),\nTensor(f32[4, 1024, 1]),\n)\n## Return values\nTuple[length=3](\nTensor(f32[4, 1024, 1024]),\nTensor(f32[4, 1024, 1]),\nTensor(f32[4, 1024, 1]),\n)", + "text":"Skipped for fx.Node(aten.native_layer_norm.default)[call_function]:Tuple[length=3](\nTensor(f32[4, 1024, 1024]),\nTensor(f32[4, 1024, 1]),\nTensor(f32[4, 1024, 1]),\n): Cannot find type promotion rule for op: aten.native_layer_norm.default" + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":1625 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0015", + "stacks":[] + }, + { + "message":{ + "markdown":"Skipped for fx.Node()[call_function]:Tensor(f32[4, 1024, 1024]): node.target is not OpOverload. Got type: \n\n## Additional Message:\n\n## Function Signature\n### Function Signature _TypePromotionInterpreter.run_node\n- self: \n- node: fx.Node()[call_function]:Tensor(f32[4, 1024, 1024])\n## Return values\nTensor(f32[4, 1024, 1024])", + "text":"Skipped for fx.Node()[call_function]:Tensor(f32[4, 1024, 1024]): node.target is not OpOverload. Got type: " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":1625 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0015", + "stacks":[] + }, + { + "message":{ + "markdown":"Skipped for fx.Node(aten.view.default)[call_function]:Tensor(f32[4096, 1024]): Cannot find type promotion rule for op: aten.view.default\n\n## Additional Message:\n\n## Function Signature\n### Function Signature _TypePromotionInterpreter.run_node\n- self: \n- node: fx.Node(aten.view.default)[call_function]:Tensor(f32[4096, 1024])\n## Return values\nTensor(f32[4096, 1024])", + "text":"Skipped for fx.Node(aten.view.default)[call_function]:Tensor(f32[4096, 1024]): Cannot find type promotion rule for op: aten.view.default" + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":1625 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0015", + "stacks":[] + }, + { + "message":{ + "markdown":"Skipped for fx.Node(aten.t.default)[call_function]:Tensor(f32[1024, 4096]): Cannot find type promotion rule for op: aten.t.default\n\n## Additional Message:\n\n## Function Signature\n### Function Signature _TypePromotionInterpreter.run_node\n- self: \n- node: fx.Node(aten.t.default)[call_function]:Tensor(f32[1024, 4096])\n## Return values\nTensor(f32[1024, 4096])", + "text":"Skipped for fx.Node(aten.t.default)[call_function]:Tensor(f32[1024, 4096]): Cannot find type promotion rule for op: aten.t.default" + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":1625 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0015", + "stacks":[] + }, + { + "message":{ + "markdown":"Skipped for fx.Node(aten.addmm.default)[call_function]:Tensor(f32[4096, 4096]): Cannot find type promotion rule for op: aten.addmm.default\n\n## Additional Message:\n\n## Function Signature\n### Function Signature _TypePromotionInterpreter.run_node\n- self: \n- node: fx.Node(aten.addmm.default)[call_function]:Tensor(f32[4096, 4096])\n## Return values\nTensor(f32[4096, 4096])", + "text":"Skipped for fx.Node(aten.addmm.default)[call_function]:Tensor(f32[4096, 4096]): Cannot find type promotion rule for op: aten.addmm.default" + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":1625 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0015", + "stacks":[] + }, + { + "message":{ + "markdown":"Skipped for fx.Node(aten.view.default)[call_function]:Tensor(f32[4, 1024, 4096]): Cannot find type promotion rule for op: aten.view.default\n\n## Additional Message:\n\n## Function Signature\n### Function Signature _TypePromotionInterpreter.run_node\n- self: \n- node: fx.Node(aten.view.default)[call_function]:Tensor(f32[4, 1024, 4096])\n## Return values\nTensor(f32[4, 1024, 4096])", + "text":"Skipped for fx.Node(aten.view.default)[call_function]:Tensor(f32[4, 1024, 4096]): Cannot find type promotion rule for op: aten.view.default" + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":1625 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0015", + "stacks":[] + }, + { + "message":{ + "markdown":"Type promotion not needed for gelu_2. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature _TypePromotionInterpreter.run_node\n- self: \n- node: fx.Node(aten.gelu.default)[call_function]:Tensor(f32[4, 1024, 4096])\nFound type promotion rule: ElementwiseTypePromotionRule('aten', 'gelu', [0], [], ELEMENTWISE_TYPE_PROMOTION_KIND.DEFAULT)\nArgument view_28 is not promoted. Already torch.float32.\nArgument tanh is not promoted. Not mentioned by type promotion rule.\n## Return values\nTensor(f32[4, 1024, 4096])", + "text":"Type promotion not needed for gelu_2. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":1625 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0015", + "stacks":[] + }, + { + "message":{ + "markdown":"Skipped for fx.Node(aten.clone.default)[call_function]:Tensor(f32[4, 1024, 4096]): Cannot find type promotion rule for op: aten.clone.default\n\n## Additional Message:\n\n## Function Signature\n### Function Signature _TypePromotionInterpreter.run_node\n- self: \n- node: fx.Node(aten.clone.default)[call_function]:Tensor(f32[4, 1024, 4096])\n## Return values\nTensor(f32[4, 1024, 4096])", + "text":"Skipped for fx.Node(aten.clone.default)[call_function]:Tensor(f32[4, 1024, 4096]): Cannot find type promotion rule for op: aten.clone.default" + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":1625 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0015", + "stacks":[] + }, + { + "message":{ + "markdown":"Skipped for fx.Node(aten.view.default)[call_function]:Tensor(f32[4096, 4096]): Cannot find type promotion rule for op: aten.view.default\n\n## Additional Message:\n\n## Function Signature\n### Function Signature _TypePromotionInterpreter.run_node\n- self: \n- node: fx.Node(aten.view.default)[call_function]:Tensor(f32[4096, 4096])\n## Return values\nTensor(f32[4096, 4096])", + "text":"Skipped for fx.Node(aten.view.default)[call_function]:Tensor(f32[4096, 4096]): Cannot find type promotion rule for op: aten.view.default" + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":1625 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0015", + "stacks":[] + }, + { + "message":{ + "markdown":"Skipped for fx.Node(aten.t.default)[call_function]:Tensor(f32[4096, 1024]): Cannot find type promotion rule for op: aten.t.default\n\n## Additional Message:\n\n## Function Signature\n### Function Signature _TypePromotionInterpreter.run_node\n- self: \n- node: fx.Node(aten.t.default)[call_function]:Tensor(f32[4096, 1024])\n## Return values\nTensor(f32[4096, 1024])", + "text":"Skipped for fx.Node(aten.t.default)[call_function]:Tensor(f32[4096, 1024]): Cannot find type promotion rule for op: aten.t.default" + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":1625 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0015", + "stacks":[] + }, + { + "message":{ + "markdown":"Skipped for fx.Node(aten.addmm.default)[call_function]:Tensor(f32[4096, 1024]): Cannot find type promotion rule for op: aten.addmm.default\n\n## Additional Message:\n\n## Function Signature\n### Function Signature _TypePromotionInterpreter.run_node\n- self: \n- node: fx.Node(aten.addmm.default)[call_function]:Tensor(f32[4096, 1024])\n## Return values\nTensor(f32[4096, 1024])", + "text":"Skipped for fx.Node(aten.addmm.default)[call_function]:Tensor(f32[4096, 1024]): Cannot find type promotion rule for op: aten.addmm.default" + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":1625 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0015", + "stacks":[] + }, + { + "message":{ + "markdown":"Skipped for fx.Node(aten.view.default)[call_function]:Tensor(f32[4, 1024, 1024]): Cannot find type promotion rule for op: aten.view.default\n\n## Additional Message:\n\n## Function Signature\n### Function Signature _TypePromotionInterpreter.run_node\n- self: \n- node: fx.Node(aten.view.default)[call_function]:Tensor(f32[4, 1024, 1024])\n## Return values\nTensor(f32[4, 1024, 1024])", + "text":"Skipped for fx.Node(aten.view.default)[call_function]:Tensor(f32[4, 1024, 1024]): Cannot find type promotion rule for op: aten.view.default" + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":1625 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0015", + "stacks":[] + }, + { + "message":{ + "markdown":"Skipped for fx.Node(aten.clone.default)[call_function]:Tensor(f32[4, 1024, 1024]): Cannot find type promotion rule for op: aten.clone.default\n\n## Additional Message:\n\n## Function Signature\n### Function Signature _TypePromotionInterpreter.run_node\n- self: \n- node: fx.Node(aten.clone.default)[call_function]:Tensor(f32[4, 1024, 1024])\n## Return values\nTensor(f32[4, 1024, 1024])", + "text":"Skipped for fx.Node(aten.clone.default)[call_function]:Tensor(f32[4, 1024, 1024]): Cannot find type promotion rule for op: aten.clone.default" + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":1625 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0015", + "stacks":[] + }, + { + "message":{ + "markdown":"Type promotion not needed for add_6. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature _TypePromotionInterpreter.run_node\n- self: \n- node: fx.Node(aten.add.Tensor)[call_function]:Tensor(f32[4, 1024, 1024])\nFound type promotion rule: ElementwiseTypePromotionRule('aten', 'add', [0, 1], [], ELEMENTWISE_TYPE_PROMOTION_KIND.DEFAULT)\nArgument add_5 is not promoted. Already torch.float32.\nArgument clone_9 is not promoted. Already torch.float32.\n## Return values\nTensor(f32[4, 1024, 1024])", + "text":"Type promotion not needed for add_6. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":1625 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0015", + "stacks":[] + }, + { + "message":{ + "markdown":"Skipped for fx.Node(aten.native_layer_norm.default)[call_function]:Tuple[length=3](\nTensor(f32[4, 1024, 1024]),\nTensor(f32[4, 1024, 1]),\nTensor(f32[4, 1024, 1]),\n): Cannot find type promotion rule for op: aten.native_layer_norm.default\n\n## Additional Message:\n\n## Function Signature\n### Function Signature _TypePromotionInterpreter.run_node\n- self: \n- node: fx.Node(aten.native_layer_norm.default)[call_function]:Tuple[length=3](\nTensor(f32[4, 1024, 1024]),\nTensor(f32[4, 1024, 1]),\nTensor(f32[4, 1024, 1]),\n)\n## Return values\nTuple[length=3](\nTensor(f32[4, 1024, 1024]),\nTensor(f32[4, 1024, 1]),\nTensor(f32[4, 1024, 1]),\n)", + "text":"Skipped for fx.Node(aten.native_layer_norm.default)[call_function]:Tuple[length=3](\nTensor(f32[4, 1024, 1024]),\nTensor(f32[4, 1024, 1]),\nTensor(f32[4, 1024, 1]),\n): Cannot find type promotion rule for op: aten.native_layer_norm.default" + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":1625 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0015", + "stacks":[] + }, + { + "message":{ + "markdown":"Skipped for fx.Node()[call_function]:Tensor(f32[4, 1024, 1024]): node.target is not OpOverload. Got type: \n\n## Additional Message:\n\n## Function Signature\n### Function Signature _TypePromotionInterpreter.run_node\n- self: \n- node: fx.Node()[call_function]:Tensor(f32[4, 1024, 1024])\n## Return values\nTensor(f32[4, 1024, 1024])", + "text":"Skipped for fx.Node()[call_function]:Tensor(f32[4, 1024, 1024]): node.target is not OpOverload. Got type: " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":1625 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0015", + "stacks":[] + }, + { + "message":{ + "markdown":"Skipped for fx.Node(aten.view.default)[call_function]:Tensor(f32[4096, 1024]): Cannot find type promotion rule for op: aten.view.default\n\n## Additional Message:\n\n## Function Signature\n### Function Signature _TypePromotionInterpreter.run_node\n- self: \n- node: fx.Node(aten.view.default)[call_function]:Tensor(f32[4096, 1024])\n## Return values\nTensor(f32[4096, 1024])", + "text":"Skipped for fx.Node(aten.view.default)[call_function]:Tensor(f32[4096, 1024]): Cannot find type promotion rule for op: aten.view.default" + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":1625 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0015", + "stacks":[] + }, + { + "message":{ + "markdown":"Skipped for fx.Node(aten.t.default)[call_function]:Tensor(f32[1024, 3072]): Cannot find type promotion rule for op: aten.t.default\n\n## Additional Message:\n\n## Function Signature\n### Function Signature _TypePromotionInterpreter.run_node\n- self: \n- node: fx.Node(aten.t.default)[call_function]:Tensor(f32[1024, 3072])\n## Return values\nTensor(f32[1024, 3072])", + "text":"Skipped for fx.Node(aten.t.default)[call_function]:Tensor(f32[1024, 3072]): Cannot find type promotion rule for op: aten.t.default" + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":1625 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0015", + "stacks":[] + }, + { + "message":{ + "markdown":"Skipped for fx.Node(aten.addmm.default)[call_function]:Tensor(f32[4096, 3072]): Cannot find type promotion rule for op: aten.addmm.default\n\n## Additional Message:\n\n## Function Signature\n### Function Signature _TypePromotionInterpreter.run_node\n- self: \n- node: fx.Node(aten.addmm.default)[call_function]:Tensor(f32[4096, 3072])\n## Return values\nTensor(f32[4096, 3072])", + "text":"Skipped for fx.Node(aten.addmm.default)[call_function]:Tensor(f32[4096, 3072]): Cannot find type promotion rule for op: aten.addmm.default" + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":1625 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0015", + "stacks":[] + }, + { + "message":{ + "markdown":"Skipped for fx.Node(aten.view.default)[call_function]:Tensor(f32[4, 1024, 3072]): Cannot find type promotion rule for op: aten.view.default\n\n## Additional Message:\n\n## Function Signature\n### Function Signature _TypePromotionInterpreter.run_node\n- self: \n- node: fx.Node(aten.view.default)[call_function]:Tensor(f32[4, 1024, 3072])\n## Return values\nTensor(f32[4, 1024, 3072])", + "text":"Skipped for fx.Node(aten.view.default)[call_function]:Tensor(f32[4, 1024, 3072]): Cannot find type promotion rule for op: aten.view.default" + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":1625 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0015", + "stacks":[] + }, + { + "message":{ + "markdown":"Skipped for fx.Node(aten.view.default)[call_function]:Tensor(f32[4, 1024, 3, 16, 64]): Cannot find type promotion rule for op: aten.view.default\n\n## Additional Message:\n\n## Function Signature\n### Function Signature _TypePromotionInterpreter.run_node\n- self: \n- node: fx.Node(aten.view.default)[call_function]:Tensor(f32[4, 1024, 3, 16, 64])\n## Return values\nTensor(f32[4, 1024, 3, 16, 64])", + "text":"Skipped for fx.Node(aten.view.default)[call_function]:Tensor(f32[4, 1024, 3, 16, 64]): Cannot find type promotion rule for op: aten.view.default" + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":1625 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0015", + "stacks":[] + }, + { + "message":{ + "markdown":"Skipped for fx.Node(aten.permute.default)[call_function]:Tensor(f32[3, 4, 16, 1024, 64]): Cannot find type promotion rule for op: aten.permute.default\n\n## Additional Message:\n\n## Function Signature\n### Function Signature _TypePromotionInterpreter.run_node\n- self: \n- node: fx.Node(aten.permute.default)[call_function]:Tensor(f32[3, 4, 16, 1024, 64])\n## Return values\nTensor(f32[3, 4, 16, 1024, 64])", + "text":"Skipped for fx.Node(aten.permute.default)[call_function]:Tensor(f32[3, 4, 16, 1024, 64]): Cannot find type promotion rule for op: aten.permute.default" + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":1625 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0015", + "stacks":[] + }, + { + "message":{ + "markdown":"Skipped for fx.Node(aten.unbind.int)[call_function]:List[length=3](\nTensor(f32[4, 16, 1024, 64]),\nTensor(f32[4, 16, 1024, 64]),\nTensor(f32[4, 16, 1024, 64]),\n): Cannot find type promotion rule for op: aten.unbind.int\n\n## Additional Message:\n\n## Function Signature\n### Function Signature _TypePromotionInterpreter.run_node\n- self: \n- node: fx.Node(aten.unbind.int)[call_function]:List[length=3](\nTensor(f32[4, 16, 1024, 64]),\nTensor(f32[4, 16, 1024, 64]),\nTensor(f32[4, 16, 1024, 64]),\n)\n## Return values\nList[length=3](\nTensor(f32[4, 16, 1024, 64]),\nTensor(f32[4, 16, 1024, 64]),\nTensor(f32[4, 16, 1024, 64]),\n)", + "text":"Skipped for fx.Node(aten.unbind.int)[call_function]:List[length=3](\nTensor(f32[4, 16, 1024, 64]),\nTensor(f32[4, 16, 1024, 64]),\nTensor(f32[4, 16, 1024, 64]),\n): Cannot find type promotion rule for op: aten.unbind.int" + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":1625 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0015", + "stacks":[] + }, + { + "message":{ + "markdown":"Skipped for fx.Node()[call_function]:Tensor(f32[4, 16, 1024, 64]): node.target is not OpOverload. Got type: \n\n## Additional Message:\n\n## Function Signature\n### Function Signature _TypePromotionInterpreter.run_node\n- self: \n- node: fx.Node()[call_function]:Tensor(f32[4, 16, 1024, 64])\n## Return values\nTensor(f32[4, 16, 1024, 64])", + "text":"Skipped for fx.Node()[call_function]:Tensor(f32[4, 16, 1024, 64]): node.target is not OpOverload. Got type: " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":1625 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0015", + "stacks":[] + }, + { + "message":{ + "markdown":"Skipped for fx.Node()[call_function]:Tensor(f32[4, 16, 1024, 64]): node.target is not OpOverload. Got type: \n\n## Additional Message:\n\n## Function Signature\n### Function Signature _TypePromotionInterpreter.run_node\n- self: \n- node: fx.Node()[call_function]:Tensor(f32[4, 16, 1024, 64])\n## Return values\nTensor(f32[4, 16, 1024, 64])", + "text":"Skipped for fx.Node()[call_function]:Tensor(f32[4, 16, 1024, 64]): node.target is not OpOverload. Got type: " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":1625 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0015", + "stacks":[] + }, + { + "message":{ + "markdown":"Skipped for fx.Node()[call_function]:Tensor(f32[4, 16, 1024, 64]): node.target is not OpOverload. Got type: \n\n## Additional Message:\n\n## Function Signature\n### Function Signature _TypePromotionInterpreter.run_node\n- self: \n- node: fx.Node()[call_function]:Tensor(f32[4, 16, 1024, 64])\n## Return values\nTensor(f32[4, 16, 1024, 64])", + "text":"Skipped for fx.Node()[call_function]:Tensor(f32[4, 16, 1024, 64]): node.target is not OpOverload. Got type: " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":1625 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0015", + "stacks":[] + }, + { + "message":{ + "markdown":"Skipped for fx.Node(aten._scaled_dot_product_efficient_attention.default)[call_function]:Tuple[length=4](\nTensor(f32[4, 16, 1024, 64]),\nTensor(f32[4, 16, 0]),\nTensor(i64[]),\nTensor(i64[]),\n): Cannot find type promotion rule for op: aten._scaled_dot_product_efficient_attention.default\n\n## Additional Message:\n\n## Function Signature\n### Function Signature _TypePromotionInterpreter.run_node\n- self: \n- node: fx.Node(aten._scaled_dot_product_efficient_attention.default)[call_function]:Tuple[length=4](\nTensor(f32[4, 16, 1024, 64]),\nTensor(f32[4, 16, 0]),\nTensor(i64[]),\nTensor(i64[]),\n)\n## Return values\nTuple[length=4](\nTensor(f32[4, 16, 1024, 64]),\nTensor(f32[4, 16, 0]),\nTensor(i64[]),\nTensor(i64[]),\n)", + "text":"Skipped for fx.Node(aten._scaled_dot_product_efficient_attention.default)[call_function]:Tuple[length=4](\nTensor(f32[4, 16, 1024, 64]),\nTensor(f32[4, 16, 0]),\nTensor(i64[]),\nTensor(i64[]),\n): Cannot find type promotion rule for op: aten._scaled_dot_product_efficient_attention.default" + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":1625 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0015", + "stacks":[] + }, + { + "message":{ + "markdown":"Skipped for fx.Node()[call_function]:Tensor(f32[4, 16, 1024, 64]): node.target is not OpOverload. Got type: \n\n## Additional Message:\n\n## Function Signature\n### Function Signature _TypePromotionInterpreter.run_node\n- self: \n- node: fx.Node()[call_function]:Tensor(f32[4, 16, 1024, 64])\n## Return values\nTensor(f32[4, 16, 1024, 64])", + "text":"Skipped for fx.Node()[call_function]:Tensor(f32[4, 16, 1024, 64]): node.target is not OpOverload. Got type: " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":1625 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0015", + "stacks":[] + }, + { + "message":{ + "markdown":"Skipped for fx.Node(aten.transpose.int)[call_function]:Tensor(f32[4, 1024, 16, 64]): Cannot find type promotion rule for op: aten.transpose.int\n\n## Additional Message:\n\n## Function Signature\n### Function Signature _TypePromotionInterpreter.run_node\n- self: \n- node: fx.Node(aten.transpose.int)[call_function]:Tensor(f32[4, 1024, 16, 64])\n## Return values\nTensor(f32[4, 1024, 16, 64])", + "text":"Skipped for fx.Node(aten.transpose.int)[call_function]:Tensor(f32[4, 1024, 16, 64]): Cannot find type promotion rule for op: aten.transpose.int" + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":1625 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0015", + "stacks":[] + }, + { + "message":{ + "markdown":"Skipped for fx.Node(aten.view.default)[call_function]:Tensor(f32[4, 1024, 1024]): Cannot find type promotion rule for op: aten.view.default\n\n## Additional Message:\n\n## Function Signature\n### Function Signature _TypePromotionInterpreter.run_node\n- self: \n- node: fx.Node(aten.view.default)[call_function]:Tensor(f32[4, 1024, 1024])\n## Return values\nTensor(f32[4, 1024, 1024])", + "text":"Skipped for fx.Node(aten.view.default)[call_function]:Tensor(f32[4, 1024, 1024]): Cannot find type promotion rule for op: aten.view.default" + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":1625 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0015", + "stacks":[] + }, + { + "message":{ + "markdown":"Skipped for fx.Node(aten.view.default)[call_function]:Tensor(f32[4096, 1024]): Cannot find type promotion rule for op: aten.view.default\n\n## Additional Message:\n\n## Function Signature\n### Function Signature _TypePromotionInterpreter.run_node\n- self: \n- node: fx.Node(aten.view.default)[call_function]:Tensor(f32[4096, 1024])\n## Return values\nTensor(f32[4096, 1024])", + "text":"Skipped for fx.Node(aten.view.default)[call_function]:Tensor(f32[4096, 1024]): Cannot find type promotion rule for op: aten.view.default" + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":1625 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0015", + "stacks":[] + }, + { + "message":{ + "markdown":"Skipped for fx.Node(aten.t.default)[call_function]:Tensor(f32[1024, 1024]): Cannot find type promotion rule for op: aten.t.default\n\n## Additional Message:\n\n## Function Signature\n### Function Signature _TypePromotionInterpreter.run_node\n- self: \n- node: fx.Node(aten.t.default)[call_function]:Tensor(f32[1024, 1024])\n## Return values\nTensor(f32[1024, 1024])", + "text":"Skipped for fx.Node(aten.t.default)[call_function]:Tensor(f32[1024, 1024]): Cannot find type promotion rule for op: aten.t.default" + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":1625 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0015", + "stacks":[] + }, + { + "message":{ + "markdown":"Skipped for fx.Node(aten.addmm.default)[call_function]:Tensor(f32[4096, 1024]): Cannot find type promotion rule for op: aten.addmm.default\n\n## Additional Message:\n\n## Function Signature\n### Function Signature _TypePromotionInterpreter.run_node\n- self: \n- node: fx.Node(aten.addmm.default)[call_function]:Tensor(f32[4096, 1024])\n## Return values\nTensor(f32[4096, 1024])", + "text":"Skipped for fx.Node(aten.addmm.default)[call_function]:Tensor(f32[4096, 1024]): Cannot find type promotion rule for op: aten.addmm.default" + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":1625 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0015", + "stacks":[] + }, + { + "message":{ + "markdown":"Skipped for fx.Node(aten.view.default)[call_function]:Tensor(f32[4, 1024, 1024]): Cannot find type promotion rule for op: aten.view.default\n\n## Additional Message:\n\n## Function Signature\n### Function Signature _TypePromotionInterpreter.run_node\n- self: \n- node: fx.Node(aten.view.default)[call_function]:Tensor(f32[4, 1024, 1024])\n## Return values\nTensor(f32[4, 1024, 1024])", + "text":"Skipped for fx.Node(aten.view.default)[call_function]:Tensor(f32[4, 1024, 1024]): Cannot find type promotion rule for op: aten.view.default" + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":1625 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0015", + "stacks":[] + }, + { + "message":{ + "markdown":"Skipped for fx.Node(aten.clone.default)[call_function]:Tensor(f32[4, 1024, 1024]): Cannot find type promotion rule for op: aten.clone.default\n\n## Additional Message:\n\n## Function Signature\n### Function Signature _TypePromotionInterpreter.run_node\n- self: \n- node: fx.Node(aten.clone.default)[call_function]:Tensor(f32[4, 1024, 1024])\n## Return values\nTensor(f32[4, 1024, 1024])", + "text":"Skipped for fx.Node(aten.clone.default)[call_function]:Tensor(f32[4, 1024, 1024]): Cannot find type promotion rule for op: aten.clone.default" + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":1625 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0015", + "stacks":[] + }, + { + "message":{ + "markdown":"Type promotion not needed for add_7. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature _TypePromotionInterpreter.run_node\n- self: \n- node: fx.Node(aten.add.Tensor)[call_function]:Tensor(f32[4, 1024, 1024])\nFound type promotion rule: ElementwiseTypePromotionRule('aten', 'add', [0, 1], [], ELEMENTWISE_TYPE_PROMOTION_KIND.DEFAULT)\nArgument add_6 is not promoted. Already torch.float32.\nArgument clone_10 is not promoted. Already torch.float32.\n## Return values\nTensor(f32[4, 1024, 1024])", + "text":"Type promotion not needed for add_7. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":1625 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0015", + "stacks":[] + }, + { + "message":{ + "markdown":"Skipped for fx.Node(aten.native_layer_norm.default)[call_function]:Tuple[length=3](\nTensor(f32[4, 1024, 1024]),\nTensor(f32[4, 1024, 1]),\nTensor(f32[4, 1024, 1]),\n): Cannot find type promotion rule for op: aten.native_layer_norm.default\n\n## Additional Message:\n\n## Function Signature\n### Function Signature _TypePromotionInterpreter.run_node\n- self: \n- node: fx.Node(aten.native_layer_norm.default)[call_function]:Tuple[length=3](\nTensor(f32[4, 1024, 1024]),\nTensor(f32[4, 1024, 1]),\nTensor(f32[4, 1024, 1]),\n)\n## Return values\nTuple[length=3](\nTensor(f32[4, 1024, 1024]),\nTensor(f32[4, 1024, 1]),\nTensor(f32[4, 1024, 1]),\n)", + "text":"Skipped for fx.Node(aten.native_layer_norm.default)[call_function]:Tuple[length=3](\nTensor(f32[4, 1024, 1024]),\nTensor(f32[4, 1024, 1]),\nTensor(f32[4, 1024, 1]),\n): Cannot find type promotion rule for op: aten.native_layer_norm.default" + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":1625 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0015", + "stacks":[] + }, + { + "message":{ + "markdown":"Skipped for fx.Node()[call_function]:Tensor(f32[4, 1024, 1024]): node.target is not OpOverload. Got type: \n\n## Additional Message:\n\n## Function Signature\n### Function Signature _TypePromotionInterpreter.run_node\n- self: \n- node: fx.Node()[call_function]:Tensor(f32[4, 1024, 1024])\n## Return values\nTensor(f32[4, 1024, 1024])", + "text":"Skipped for fx.Node()[call_function]:Tensor(f32[4, 1024, 1024]): node.target is not OpOverload. Got type: " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":1625 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0015", + "stacks":[] + }, + { + "message":{ + "markdown":"Skipped for fx.Node(aten.view.default)[call_function]:Tensor(f32[4096, 1024]): Cannot find type promotion rule for op: aten.view.default\n\n## Additional Message:\n\n## Function Signature\n### Function Signature _TypePromotionInterpreter.run_node\n- self: \n- node: fx.Node(aten.view.default)[call_function]:Tensor(f32[4096, 1024])\n## Return values\nTensor(f32[4096, 1024])", + "text":"Skipped for fx.Node(aten.view.default)[call_function]:Tensor(f32[4096, 1024]): Cannot find type promotion rule for op: aten.view.default" + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":1625 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0015", + "stacks":[] + }, + { + "message":{ + "markdown":"Skipped for fx.Node(aten.t.default)[call_function]:Tensor(f32[1024, 4096]): Cannot find type promotion rule for op: aten.t.default\n\n## Additional Message:\n\n## Function Signature\n### Function Signature _TypePromotionInterpreter.run_node\n- self: \n- node: fx.Node(aten.t.default)[call_function]:Tensor(f32[1024, 4096])\n## Return values\nTensor(f32[1024, 4096])", + "text":"Skipped for fx.Node(aten.t.default)[call_function]:Tensor(f32[1024, 4096]): Cannot find type promotion rule for op: aten.t.default" + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":1625 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0015", + "stacks":[] + }, + { + "message":{ + "markdown":"Skipped for fx.Node(aten.addmm.default)[call_function]:Tensor(f32[4096, 4096]): Cannot find type promotion rule for op: aten.addmm.default\n\n## Additional Message:\n\n## Function Signature\n### Function Signature _TypePromotionInterpreter.run_node\n- self: \n- node: fx.Node(aten.addmm.default)[call_function]:Tensor(f32[4096, 4096])\n## Return values\nTensor(f32[4096, 4096])", + "text":"Skipped for fx.Node(aten.addmm.default)[call_function]:Tensor(f32[4096, 4096]): Cannot find type promotion rule for op: aten.addmm.default" + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":1625 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0015", + "stacks":[] + }, + { + "message":{ + "markdown":"Skipped for fx.Node(aten.view.default)[call_function]:Tensor(f32[4, 1024, 4096]): Cannot find type promotion rule for op: aten.view.default\n\n## Additional Message:\n\n## Function Signature\n### Function Signature _TypePromotionInterpreter.run_node\n- self: \n- node: fx.Node(aten.view.default)[call_function]:Tensor(f32[4, 1024, 4096])\n## Return values\nTensor(f32[4, 1024, 4096])", + "text":"Skipped for fx.Node(aten.view.default)[call_function]:Tensor(f32[4, 1024, 4096]): Cannot find type promotion rule for op: aten.view.default" + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":1625 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0015", + "stacks":[] + }, + { + "message":{ + "markdown":"Type promotion not needed for gelu_3. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature _TypePromotionInterpreter.run_node\n- self: \n- node: fx.Node(aten.gelu.default)[call_function]:Tensor(f32[4, 1024, 4096])\nFound type promotion rule: ElementwiseTypePromotionRule('aten', 'gelu', [0], [], ELEMENTWISE_TYPE_PROMOTION_KIND.DEFAULT)\nArgument view_38 is not promoted. Already torch.float32.\nArgument tanh is not promoted. Not mentioned by type promotion rule.\n## Return values\nTensor(f32[4, 1024, 4096])", + "text":"Type promotion not needed for gelu_3. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":1625 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0015", + "stacks":[] + }, + { + "message":{ + "markdown":"Skipped for fx.Node(aten.clone.default)[call_function]:Tensor(f32[4, 1024, 4096]): Cannot find type promotion rule for op: aten.clone.default\n\n## Additional Message:\n\n## Function Signature\n### Function Signature _TypePromotionInterpreter.run_node\n- self: \n- node: fx.Node(aten.clone.default)[call_function]:Tensor(f32[4, 1024, 4096])\n## Return values\nTensor(f32[4, 1024, 4096])", + "text":"Skipped for fx.Node(aten.clone.default)[call_function]:Tensor(f32[4, 1024, 4096]): Cannot find type promotion rule for op: aten.clone.default" + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":1625 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0015", + "stacks":[] + }, + { + "message":{ + "markdown":"Skipped for fx.Node(aten.view.default)[call_function]:Tensor(f32[4096, 4096]): Cannot find type promotion rule for op: aten.view.default\n\n## Additional Message:\n\n## Function Signature\n### Function Signature _TypePromotionInterpreter.run_node\n- self: \n- node: fx.Node(aten.view.default)[call_function]:Tensor(f32[4096, 4096])\n## Return values\nTensor(f32[4096, 4096])", + "text":"Skipped for fx.Node(aten.view.default)[call_function]:Tensor(f32[4096, 4096]): Cannot find type promotion rule for op: aten.view.default" + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":1625 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0015", + "stacks":[] + }, + { + "message":{ + "markdown":"Skipped for fx.Node(aten.t.default)[call_function]:Tensor(f32[4096, 1024]): Cannot find type promotion rule for op: aten.t.default\n\n## Additional Message:\n\n## Function Signature\n### Function Signature _TypePromotionInterpreter.run_node\n- self: \n- node: fx.Node(aten.t.default)[call_function]:Tensor(f32[4096, 1024])\n## Return values\nTensor(f32[4096, 1024])", + "text":"Skipped for fx.Node(aten.t.default)[call_function]:Tensor(f32[4096, 1024]): Cannot find type promotion rule for op: aten.t.default" + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":1625 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0015", + "stacks":[] + }, + { + "message":{ + "markdown":"Skipped for fx.Node(aten.addmm.default)[call_function]:Tensor(f32[4096, 1024]): Cannot find type promotion rule for op: aten.addmm.default\n\n## Additional Message:\n\n## Function Signature\n### Function Signature _TypePromotionInterpreter.run_node\n- self: \n- node: fx.Node(aten.addmm.default)[call_function]:Tensor(f32[4096, 1024])\n## Return values\nTensor(f32[4096, 1024])", + "text":"Skipped for fx.Node(aten.addmm.default)[call_function]:Tensor(f32[4096, 1024]): Cannot find type promotion rule for op: aten.addmm.default" + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":1625 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0015", + "stacks":[] + }, + { + "message":{ + "markdown":"Skipped for fx.Node(aten.view.default)[call_function]:Tensor(f32[4, 1024, 1024]): Cannot find type promotion rule for op: aten.view.default\n\n## Additional Message:\n\n## Function Signature\n### Function Signature _TypePromotionInterpreter.run_node\n- self: \n- node: fx.Node(aten.view.default)[call_function]:Tensor(f32[4, 1024, 1024])\n## Return values\nTensor(f32[4, 1024, 1024])", + "text":"Skipped for fx.Node(aten.view.default)[call_function]:Tensor(f32[4, 1024, 1024]): Cannot find type promotion rule for op: aten.view.default" + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":1625 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0015", + "stacks":[] + }, + { + "message":{ + "markdown":"Skipped for fx.Node(aten.clone.default)[call_function]:Tensor(f32[4, 1024, 1024]): Cannot find type promotion rule for op: aten.clone.default\n\n## Additional Message:\n\n## Function Signature\n### Function Signature _TypePromotionInterpreter.run_node\n- self: \n- node: fx.Node(aten.clone.default)[call_function]:Tensor(f32[4, 1024, 1024])\n## Return values\nTensor(f32[4, 1024, 1024])", + "text":"Skipped for fx.Node(aten.clone.default)[call_function]:Tensor(f32[4, 1024, 1024]): Cannot find type promotion rule for op: aten.clone.default" + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":1625 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0015", + "stacks":[] + }, + { + "message":{ + "markdown":"Type promotion not needed for add_8. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature _TypePromotionInterpreter.run_node\n- self: \n- node: fx.Node(aten.add.Tensor)[call_function]:Tensor(f32[4, 1024, 1024])\nFound type promotion rule: ElementwiseTypePromotionRule('aten', 'add', [0, 1], [], ELEMENTWISE_TYPE_PROMOTION_KIND.DEFAULT)\nArgument add_7 is not promoted. Already torch.float32.\nArgument clone_12 is not promoted. Already torch.float32.\n## Return values\nTensor(f32[4, 1024, 1024])", + "text":"Type promotion not needed for add_8. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":1625 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0015", + "stacks":[] + }, + { + "message":{ + "markdown":"Skipped for fx.Node(aten.native_layer_norm.default)[call_function]:Tuple[length=3](\nTensor(f32[4, 1024, 1024]),\nTensor(f32[4, 1024, 1]),\nTensor(f32[4, 1024, 1]),\n): Cannot find type promotion rule for op: aten.native_layer_norm.default\n\n## Additional Message:\n\n## Function Signature\n### Function Signature _TypePromotionInterpreter.run_node\n- self: \n- node: fx.Node(aten.native_layer_norm.default)[call_function]:Tuple[length=3](\nTensor(f32[4, 1024, 1024]),\nTensor(f32[4, 1024, 1]),\nTensor(f32[4, 1024, 1]),\n)\n## Return values\nTuple[length=3](\nTensor(f32[4, 1024, 1024]),\nTensor(f32[4, 1024, 1]),\nTensor(f32[4, 1024, 1]),\n)", + "text":"Skipped for fx.Node(aten.native_layer_norm.default)[call_function]:Tuple[length=3](\nTensor(f32[4, 1024, 1024]),\nTensor(f32[4, 1024, 1]),\nTensor(f32[4, 1024, 1]),\n): Cannot find type promotion rule for op: aten.native_layer_norm.default" + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":1625 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0015", + "stacks":[] + }, + { + "message":{ + "markdown":"Skipped for fx.Node()[call_function]:Tensor(f32[4, 1024, 1024]): node.target is not OpOverload. Got type: \n\n## Additional Message:\n\n## Function Signature\n### Function Signature _TypePromotionInterpreter.run_node\n- self: \n- node: fx.Node()[call_function]:Tensor(f32[4, 1024, 1024])\n## Return values\nTensor(f32[4, 1024, 1024])", + "text":"Skipped for fx.Node()[call_function]:Tensor(f32[4, 1024, 1024]): node.target is not OpOverload. Got type: " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":1625 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0015", + "stacks":[] + }, + { + "message":{ + "markdown":"Skipped for fx.Node(aten.view.default)[call_function]:Tensor(f32[4096, 1024]): Cannot find type promotion rule for op: aten.view.default\n\n## Additional Message:\n\n## Function Signature\n### Function Signature _TypePromotionInterpreter.run_node\n- self: \n- node: fx.Node(aten.view.default)[call_function]:Tensor(f32[4096, 1024])\n## Return values\nTensor(f32[4096, 1024])", + "text":"Skipped for fx.Node(aten.view.default)[call_function]:Tensor(f32[4096, 1024]): Cannot find type promotion rule for op: aten.view.default" + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":1625 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0015", + "stacks":[] + }, + { + "message":{ + "markdown":"Skipped for fx.Node(aten.t.default)[call_function]:Tensor(f32[1024, 3072]): Cannot find type promotion rule for op: aten.t.default\n\n## Additional Message:\n\n## Function Signature\n### Function Signature _TypePromotionInterpreter.run_node\n- self: \n- node: fx.Node(aten.t.default)[call_function]:Tensor(f32[1024, 3072])\n## Return values\nTensor(f32[1024, 3072])", + "text":"Skipped for fx.Node(aten.t.default)[call_function]:Tensor(f32[1024, 3072]): Cannot find type promotion rule for op: aten.t.default" + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":1625 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0015", + "stacks":[] + }, + { + "message":{ + "markdown":"Skipped for fx.Node(aten.addmm.default)[call_function]:Tensor(f32[4096, 3072]): Cannot find type promotion rule for op: aten.addmm.default\n\n## Additional Message:\n\n## Function Signature\n### Function Signature _TypePromotionInterpreter.run_node\n- self: \n- node: fx.Node(aten.addmm.default)[call_function]:Tensor(f32[4096, 3072])\n## Return values\nTensor(f32[4096, 3072])", + "text":"Skipped for fx.Node(aten.addmm.default)[call_function]:Tensor(f32[4096, 3072]): Cannot find type promotion rule for op: aten.addmm.default" + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":1625 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0015", + "stacks":[] + }, + { + "message":{ + "markdown":"Skipped for fx.Node(aten.view.default)[call_function]:Tensor(f32[4, 1024, 3072]): Cannot find type promotion rule for op: aten.view.default\n\n## Additional Message:\n\n## Function Signature\n### Function Signature _TypePromotionInterpreter.run_node\n- self: \n- node: fx.Node(aten.view.default)[call_function]:Tensor(f32[4, 1024, 3072])\n## Return values\nTensor(f32[4, 1024, 3072])", + "text":"Skipped for fx.Node(aten.view.default)[call_function]:Tensor(f32[4, 1024, 3072]): Cannot find type promotion rule for op: aten.view.default" + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":1625 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0015", + "stacks":[] + }, + { + "message":{ + "markdown":"Skipped for fx.Node(aten.view.default)[call_function]:Tensor(f32[4, 1024, 3, 16, 64]): Cannot find type promotion rule for op: aten.view.default\n\n## Additional Message:\n\n## Function Signature\n### Function Signature _TypePromotionInterpreter.run_node\n- self: \n- node: fx.Node(aten.view.default)[call_function]:Tensor(f32[4, 1024, 3, 16, 64])\n## Return values\nTensor(f32[4, 1024, 3, 16, 64])", + "text":"Skipped for fx.Node(aten.view.default)[call_function]:Tensor(f32[4, 1024, 3, 16, 64]): Cannot find type promotion rule for op: aten.view.default" + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":1625 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0015", + "stacks":[] + }, + { + "message":{ + "markdown":"Skipped for fx.Node(aten.permute.default)[call_function]:Tensor(f32[3, 4, 16, 1024, 64]): Cannot find type promotion rule for op: aten.permute.default\n\n## Additional Message:\n\n## Function Signature\n### Function Signature _TypePromotionInterpreter.run_node\n- self: \n- node: fx.Node(aten.permute.default)[call_function]:Tensor(f32[3, 4, 16, 1024, 64])\n## Return values\nTensor(f32[3, 4, 16, 1024, 64])", + "text":"Skipped for fx.Node(aten.permute.default)[call_function]:Tensor(f32[3, 4, 16, 1024, 64]): Cannot find type promotion rule for op: aten.permute.default" + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":1625 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0015", + "stacks":[] + }, + { + "message":{ + "markdown":"Skipped for fx.Node(aten.unbind.int)[call_function]:List[length=3](\nTensor(f32[4, 16, 1024, 64]),\nTensor(f32[4, 16, 1024, 64]),\nTensor(f32[4, 16, 1024, 64]),\n): Cannot find type promotion rule for op: aten.unbind.int\n\n## Additional Message:\n\n## Function Signature\n### Function Signature _TypePromotionInterpreter.run_node\n- self: \n- node: fx.Node(aten.unbind.int)[call_function]:List[length=3](\nTensor(f32[4, 16, 1024, 64]),\nTensor(f32[4, 16, 1024, 64]),\nTensor(f32[4, 16, 1024, 64]),\n)\n## Return values\nList[length=3](\nTensor(f32[4, 16, 1024, 64]),\nTensor(f32[4, 16, 1024, 64]),\nTensor(f32[4, 16, 1024, 64]),\n)", + "text":"Skipped for fx.Node(aten.unbind.int)[call_function]:List[length=3](\nTensor(f32[4, 16, 1024, 64]),\nTensor(f32[4, 16, 1024, 64]),\nTensor(f32[4, 16, 1024, 64]),\n): Cannot find type promotion rule for op: aten.unbind.int" + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":1625 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0015", + "stacks":[] + }, + { + "message":{ + "markdown":"Skipped for fx.Node()[call_function]:Tensor(f32[4, 16, 1024, 64]): node.target is not OpOverload. Got type: \n\n## Additional Message:\n\n## Function Signature\n### Function Signature _TypePromotionInterpreter.run_node\n- self: \n- node: fx.Node()[call_function]:Tensor(f32[4, 16, 1024, 64])\n## Return values\nTensor(f32[4, 16, 1024, 64])", + "text":"Skipped for fx.Node()[call_function]:Tensor(f32[4, 16, 1024, 64]): node.target is not OpOverload. Got type: " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":1625 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0015", + "stacks":[] + }, + { + "message":{ + "markdown":"Skipped for fx.Node()[call_function]:Tensor(f32[4, 16, 1024, 64]): node.target is not OpOverload. Got type: \n\n## Additional Message:\n\n## Function Signature\n### Function Signature _TypePromotionInterpreter.run_node\n- self: \n- node: fx.Node()[call_function]:Tensor(f32[4, 16, 1024, 64])\n## Return values\nTensor(f32[4, 16, 1024, 64])", + "text":"Skipped for fx.Node()[call_function]:Tensor(f32[4, 16, 1024, 64]): node.target is not OpOverload. Got type: " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":1625 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0015", + "stacks":[] + }, + { + "message":{ + "markdown":"Skipped for fx.Node()[call_function]:Tensor(f32[4, 16, 1024, 64]): node.target is not OpOverload. Got type: \n\n## Additional Message:\n\n## Function Signature\n### Function Signature _TypePromotionInterpreter.run_node\n- self: \n- node: fx.Node()[call_function]:Tensor(f32[4, 16, 1024, 64])\n## Return values\nTensor(f32[4, 16, 1024, 64])", + "text":"Skipped for fx.Node()[call_function]:Tensor(f32[4, 16, 1024, 64]): node.target is not OpOverload. Got type: " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":1625 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0015", + "stacks":[] + }, + { + "message":{ + "markdown":"Skipped for fx.Node(aten._scaled_dot_product_efficient_attention.default)[call_function]:Tuple[length=4](\nTensor(f32[4, 16, 1024, 64]),\nTensor(f32[4, 16, 0]),\nTensor(i64[]),\nTensor(i64[]),\n): Cannot find type promotion rule for op: aten._scaled_dot_product_efficient_attention.default\n\n## Additional Message:\n\n## Function Signature\n### Function Signature _TypePromotionInterpreter.run_node\n- self: \n- node: fx.Node(aten._scaled_dot_product_efficient_attention.default)[call_function]:Tuple[length=4](\nTensor(f32[4, 16, 1024, 64]),\nTensor(f32[4, 16, 0]),\nTensor(i64[]),\nTensor(i64[]),\n)\n## Return values\nTuple[length=4](\nTensor(f32[4, 16, 1024, 64]),\nTensor(f32[4, 16, 0]),\nTensor(i64[]),\nTensor(i64[]),\n)", + "text":"Skipped for fx.Node(aten._scaled_dot_product_efficient_attention.default)[call_function]:Tuple[length=4](\nTensor(f32[4, 16, 1024, 64]),\nTensor(f32[4, 16, 0]),\nTensor(i64[]),\nTensor(i64[]),\n): Cannot find type promotion rule for op: aten._scaled_dot_product_efficient_attention.default" + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":1625 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0015", + "stacks":[] + }, + { + "message":{ + "markdown":"Skipped for fx.Node()[call_function]:Tensor(f32[4, 16, 1024, 64]): node.target is not OpOverload. Got type: \n\n## Additional Message:\n\n## Function Signature\n### Function Signature _TypePromotionInterpreter.run_node\n- self: \n- node: fx.Node()[call_function]:Tensor(f32[4, 16, 1024, 64])\n## Return values\nTensor(f32[4, 16, 1024, 64])", + "text":"Skipped for fx.Node()[call_function]:Tensor(f32[4, 16, 1024, 64]): node.target is not OpOverload. Got type: " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":1625 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0015", + "stacks":[] + }, + { + "message":{ + "markdown":"Skipped for fx.Node(aten.transpose.int)[call_function]:Tensor(f32[4, 1024, 16, 64]): Cannot find type promotion rule for op: aten.transpose.int\n\n## Additional Message:\n\n## Function Signature\n### Function Signature _TypePromotionInterpreter.run_node\n- self: \n- node: fx.Node(aten.transpose.int)[call_function]:Tensor(f32[4, 1024, 16, 64])\n## Return values\nTensor(f32[4, 1024, 16, 64])", + "text":"Skipped for fx.Node(aten.transpose.int)[call_function]:Tensor(f32[4, 1024, 16, 64]): Cannot find type promotion rule for op: aten.transpose.int" + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":1625 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0015", + "stacks":[] + }, + { + "message":{ + "markdown":"Skipped for fx.Node(aten.view.default)[call_function]:Tensor(f32[4, 1024, 1024]): Cannot find type promotion rule for op: aten.view.default\n\n## Additional Message:\n\n## Function Signature\n### Function Signature _TypePromotionInterpreter.run_node\n- self: \n- node: fx.Node(aten.view.default)[call_function]:Tensor(f32[4, 1024, 1024])\n## Return values\nTensor(f32[4, 1024, 1024])", + "text":"Skipped for fx.Node(aten.view.default)[call_function]:Tensor(f32[4, 1024, 1024]): Cannot find type promotion rule for op: aten.view.default" + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":1625 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0015", + "stacks":[] + }, + { + "message":{ + "markdown":"Skipped for fx.Node(aten.view.default)[call_function]:Tensor(f32[4096, 1024]): Cannot find type promotion rule for op: aten.view.default\n\n## Additional Message:\n\n## Function Signature\n### Function Signature _TypePromotionInterpreter.run_node\n- self: \n- node: fx.Node(aten.view.default)[call_function]:Tensor(f32[4096, 1024])\n## Return values\nTensor(f32[4096, 1024])", + "text":"Skipped for fx.Node(aten.view.default)[call_function]:Tensor(f32[4096, 1024]): Cannot find type promotion rule for op: aten.view.default" + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":1625 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0015", + "stacks":[] + }, + { + "message":{ + "markdown":"Skipped for fx.Node(aten.t.default)[call_function]:Tensor(f32[1024, 1024]): Cannot find type promotion rule for op: aten.t.default\n\n## Additional Message:\n\n## Function Signature\n### Function Signature _TypePromotionInterpreter.run_node\n- self: \n- node: fx.Node(aten.t.default)[call_function]:Tensor(f32[1024, 1024])\n## Return values\nTensor(f32[1024, 1024])", + "text":"Skipped for fx.Node(aten.t.default)[call_function]:Tensor(f32[1024, 1024]): Cannot find type promotion rule for op: aten.t.default" + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":1625 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0015", + "stacks":[] + }, + { + "message":{ + "markdown":"Skipped for fx.Node(aten.addmm.default)[call_function]:Tensor(f32[4096, 1024]): Cannot find type promotion rule for op: aten.addmm.default\n\n## Additional Message:\n\n## Function Signature\n### Function Signature _TypePromotionInterpreter.run_node\n- self: \n- node: fx.Node(aten.addmm.default)[call_function]:Tensor(f32[4096, 1024])\n## Return values\nTensor(f32[4096, 1024])", + "text":"Skipped for fx.Node(aten.addmm.default)[call_function]:Tensor(f32[4096, 1024]): Cannot find type promotion rule for op: aten.addmm.default" + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":1625 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0015", + "stacks":[] + }, + { + "message":{ + "markdown":"Skipped for fx.Node(aten.view.default)[call_function]:Tensor(f32[4, 1024, 1024]): Cannot find type promotion rule for op: aten.view.default\n\n## Additional Message:\n\n## Function Signature\n### Function Signature _TypePromotionInterpreter.run_node\n- self: \n- node: fx.Node(aten.view.default)[call_function]:Tensor(f32[4, 1024, 1024])\n## Return values\nTensor(f32[4, 1024, 1024])", + "text":"Skipped for fx.Node(aten.view.default)[call_function]:Tensor(f32[4, 1024, 1024]): Cannot find type promotion rule for op: aten.view.default" + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":1625 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0015", + "stacks":[] + }, + { + "message":{ + "markdown":"Skipped for fx.Node(aten.clone.default)[call_function]:Tensor(f32[4, 1024, 1024]): Cannot find type promotion rule for op: aten.clone.default\n\n## Additional Message:\n\n## Function Signature\n### Function Signature _TypePromotionInterpreter.run_node\n- self: \n- node: fx.Node(aten.clone.default)[call_function]:Tensor(f32[4, 1024, 1024])\n## Return values\nTensor(f32[4, 1024, 1024])", + "text":"Skipped for fx.Node(aten.clone.default)[call_function]:Tensor(f32[4, 1024, 1024]): Cannot find type promotion rule for op: aten.clone.default" + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":1625 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0015", + "stacks":[] + }, + { + "message":{ + "markdown":"Type promotion not needed for add_9. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature _TypePromotionInterpreter.run_node\n- self: \n- node: fx.Node(aten.add.Tensor)[call_function]:Tensor(f32[4, 1024, 1024])\nFound type promotion rule: ElementwiseTypePromotionRule('aten', 'add', [0, 1], [], ELEMENTWISE_TYPE_PROMOTION_KIND.DEFAULT)\nArgument add_8 is not promoted. Already torch.float32.\nArgument clone_13 is not promoted. Already torch.float32.\n## Return values\nTensor(f32[4, 1024, 1024])", + "text":"Type promotion not needed for add_9. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":1625 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0015", + "stacks":[] + }, + { + "message":{ + "markdown":"Skipped for fx.Node(aten.native_layer_norm.default)[call_function]:Tuple[length=3](\nTensor(f32[4, 1024, 1024]),\nTensor(f32[4, 1024, 1]),\nTensor(f32[4, 1024, 1]),\n): Cannot find type promotion rule for op: aten.native_layer_norm.default\n\n## Additional Message:\n\n## Function Signature\n### Function Signature _TypePromotionInterpreter.run_node\n- self: \n- node: fx.Node(aten.native_layer_norm.default)[call_function]:Tuple[length=3](\nTensor(f32[4, 1024, 1024]),\nTensor(f32[4, 1024, 1]),\nTensor(f32[4, 1024, 1]),\n)\n## Return values\nTuple[length=3](\nTensor(f32[4, 1024, 1024]),\nTensor(f32[4, 1024, 1]),\nTensor(f32[4, 1024, 1]),\n)", + "text":"Skipped for fx.Node(aten.native_layer_norm.default)[call_function]:Tuple[length=3](\nTensor(f32[4, 1024, 1024]),\nTensor(f32[4, 1024, 1]),\nTensor(f32[4, 1024, 1]),\n): Cannot find type promotion rule for op: aten.native_layer_norm.default" + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":1625 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0015", + "stacks":[] + }, + { + "message":{ + "markdown":"Skipped for fx.Node()[call_function]:Tensor(f32[4, 1024, 1024]): node.target is not OpOverload. Got type: \n\n## Additional Message:\n\n## Function Signature\n### Function Signature _TypePromotionInterpreter.run_node\n- self: \n- node: fx.Node()[call_function]:Tensor(f32[4, 1024, 1024])\n## Return values\nTensor(f32[4, 1024, 1024])", + "text":"Skipped for fx.Node()[call_function]:Tensor(f32[4, 1024, 1024]): node.target is not OpOverload. Got type: " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":1625 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0015", + "stacks":[] + }, + { + "message":{ + "markdown":"Skipped for fx.Node(aten.view.default)[call_function]:Tensor(f32[4096, 1024]): Cannot find type promotion rule for op: aten.view.default\n\n## Additional Message:\n\n## Function Signature\n### Function Signature _TypePromotionInterpreter.run_node\n- self: \n- node: fx.Node(aten.view.default)[call_function]:Tensor(f32[4096, 1024])\n## Return values\nTensor(f32[4096, 1024])", + "text":"Skipped for fx.Node(aten.view.default)[call_function]:Tensor(f32[4096, 1024]): Cannot find type promotion rule for op: aten.view.default" + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":1625 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0015", + "stacks":[] + }, + { + "message":{ + "markdown":"Skipped for fx.Node(aten.t.default)[call_function]:Tensor(f32[1024, 4096]): Cannot find type promotion rule for op: aten.t.default\n\n## Additional Message:\n\n## Function Signature\n### Function Signature _TypePromotionInterpreter.run_node\n- self: \n- node: fx.Node(aten.t.default)[call_function]:Tensor(f32[1024, 4096])\n## Return values\nTensor(f32[1024, 4096])", + "text":"Skipped for fx.Node(aten.t.default)[call_function]:Tensor(f32[1024, 4096]): Cannot find type promotion rule for op: aten.t.default" + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":1625 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0015", + "stacks":[] + }, + { + "message":{ + "markdown":"Skipped for fx.Node(aten.addmm.default)[call_function]:Tensor(f32[4096, 4096]): Cannot find type promotion rule for op: aten.addmm.default\n\n## Additional Message:\n\n## Function Signature\n### Function Signature _TypePromotionInterpreter.run_node\n- self: \n- node: fx.Node(aten.addmm.default)[call_function]:Tensor(f32[4096, 4096])\n## Return values\nTensor(f32[4096, 4096])", + "text":"Skipped for fx.Node(aten.addmm.default)[call_function]:Tensor(f32[4096, 4096]): Cannot find type promotion rule for op: aten.addmm.default" + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":1625 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0015", + "stacks":[] + }, + { + "message":{ + "markdown":"Skipped for fx.Node(aten.view.default)[call_function]:Tensor(f32[4, 1024, 4096]): Cannot find type promotion rule for op: aten.view.default\n\n## Additional Message:\n\n## Function Signature\n### Function Signature _TypePromotionInterpreter.run_node\n- self: \n- node: fx.Node(aten.view.default)[call_function]:Tensor(f32[4, 1024, 4096])\n## Return values\nTensor(f32[4, 1024, 4096])", + "text":"Skipped for fx.Node(aten.view.default)[call_function]:Tensor(f32[4, 1024, 4096]): Cannot find type promotion rule for op: aten.view.default" + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":1625 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0015", + "stacks":[] + }, + { + "message":{ + "markdown":"Type promotion not needed for gelu_4. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature _TypePromotionInterpreter.run_node\n- self: \n- node: fx.Node(aten.gelu.default)[call_function]:Tensor(f32[4, 1024, 4096])\nFound type promotion rule: ElementwiseTypePromotionRule('aten', 'gelu', [0], [], ELEMENTWISE_TYPE_PROMOTION_KIND.DEFAULT)\nArgument view_48 is not promoted. Already torch.float32.\nArgument tanh is not promoted. Not mentioned by type promotion rule.\n## Return values\nTensor(f32[4, 1024, 4096])", + "text":"Type promotion not needed for gelu_4. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":1625 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0015", + "stacks":[] + }, + { + "message":{ + "markdown":"Skipped for fx.Node(aten.clone.default)[call_function]:Tensor(f32[4, 1024, 4096]): Cannot find type promotion rule for op: aten.clone.default\n\n## Additional Message:\n\n## Function Signature\n### Function Signature _TypePromotionInterpreter.run_node\n- self: \n- node: fx.Node(aten.clone.default)[call_function]:Tensor(f32[4, 1024, 4096])\n## Return values\nTensor(f32[4, 1024, 4096])", + "text":"Skipped for fx.Node(aten.clone.default)[call_function]:Tensor(f32[4, 1024, 4096]): Cannot find type promotion rule for op: aten.clone.default" + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":1625 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0015", + "stacks":[] + }, + { + "message":{ + "markdown":"Skipped for fx.Node(aten.view.default)[call_function]:Tensor(f32[4096, 4096]): Cannot find type promotion rule for op: aten.view.default\n\n## Additional Message:\n\n## Function Signature\n### Function Signature _TypePromotionInterpreter.run_node\n- self: \n- node: fx.Node(aten.view.default)[call_function]:Tensor(f32[4096, 4096])\n## Return values\nTensor(f32[4096, 4096])", + "text":"Skipped for fx.Node(aten.view.default)[call_function]:Tensor(f32[4096, 4096]): Cannot find type promotion rule for op: aten.view.default" + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":1625 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0015", + "stacks":[] + }, + { + "message":{ + "markdown":"Skipped for fx.Node(aten.t.default)[call_function]:Tensor(f32[4096, 1024]): Cannot find type promotion rule for op: aten.t.default\n\n## Additional Message:\n\n## Function Signature\n### Function Signature _TypePromotionInterpreter.run_node\n- self: \n- node: fx.Node(aten.t.default)[call_function]:Tensor(f32[4096, 1024])\n## Return values\nTensor(f32[4096, 1024])", + "text":"Skipped for fx.Node(aten.t.default)[call_function]:Tensor(f32[4096, 1024]): Cannot find type promotion rule for op: aten.t.default" + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":1625 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0015", + "stacks":[] + }, + { + "message":{ + "markdown":"Skipped for fx.Node(aten.addmm.default)[call_function]:Tensor(f32[4096, 1024]): Cannot find type promotion rule for op: aten.addmm.default\n\n## Additional Message:\n\n## Function Signature\n### Function Signature _TypePromotionInterpreter.run_node\n- self: \n- node: fx.Node(aten.addmm.default)[call_function]:Tensor(f32[4096, 1024])\n## Return values\nTensor(f32[4096, 1024])", + "text":"Skipped for fx.Node(aten.addmm.default)[call_function]:Tensor(f32[4096, 1024]): Cannot find type promotion rule for op: aten.addmm.default" + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":1625 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0015", + "stacks":[] + }, + { + "message":{ + "markdown":"Skipped for fx.Node(aten.view.default)[call_function]:Tensor(f32[4, 1024, 1024]): Cannot find type promotion rule for op: aten.view.default\n\n## Additional Message:\n\n## Function Signature\n### Function Signature _TypePromotionInterpreter.run_node\n- self: \n- node: fx.Node(aten.view.default)[call_function]:Tensor(f32[4, 1024, 1024])\n## Return values\nTensor(f32[4, 1024, 1024])", + "text":"Skipped for fx.Node(aten.view.default)[call_function]:Tensor(f32[4, 1024, 1024]): Cannot find type promotion rule for op: aten.view.default" + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":1625 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0015", + "stacks":[] + }, + { + "message":{ + "markdown":"Skipped for fx.Node(aten.clone.default)[call_function]:Tensor(f32[4, 1024, 1024]): Cannot find type promotion rule for op: aten.clone.default\n\n## Additional Message:\n\n## Function Signature\n### Function Signature _TypePromotionInterpreter.run_node\n- self: \n- node: fx.Node(aten.clone.default)[call_function]:Tensor(f32[4, 1024, 1024])\n## Return values\nTensor(f32[4, 1024, 1024])", + "text":"Skipped for fx.Node(aten.clone.default)[call_function]:Tensor(f32[4, 1024, 1024]): Cannot find type promotion rule for op: aten.clone.default" + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":1625 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0015", + "stacks":[] + }, + { + "message":{ + "markdown":"Type promotion not needed for add_10. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature _TypePromotionInterpreter.run_node\n- self: \n- node: fx.Node(aten.add.Tensor)[call_function]:Tensor(f32[4, 1024, 1024])\nFound type promotion rule: ElementwiseTypePromotionRule('aten', 'add', [0, 1], [], ELEMENTWISE_TYPE_PROMOTION_KIND.DEFAULT)\nArgument add_9 is not promoted. Already torch.float32.\nArgument clone_15 is not promoted. Already torch.float32.\n## Return values\nTensor(f32[4, 1024, 1024])", + "text":"Type promotion not needed for add_10. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":1625 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0015", + "stacks":[] + }, + { + "message":{ + "markdown":"Skipped for fx.Node(aten.native_layer_norm.default)[call_function]:Tuple[length=3](\nTensor(f32[4, 1024, 1024]),\nTensor(f32[4, 1024, 1]),\nTensor(f32[4, 1024, 1]),\n): Cannot find type promotion rule for op: aten.native_layer_norm.default\n\n## Additional Message:\n\n## Function Signature\n### Function Signature _TypePromotionInterpreter.run_node\n- self: \n- node: fx.Node(aten.native_layer_norm.default)[call_function]:Tuple[length=3](\nTensor(f32[4, 1024, 1024]),\nTensor(f32[4, 1024, 1]),\nTensor(f32[4, 1024, 1]),\n)\n## Return values\nTuple[length=3](\nTensor(f32[4, 1024, 1024]),\nTensor(f32[4, 1024, 1]),\nTensor(f32[4, 1024, 1]),\n)", + "text":"Skipped for fx.Node(aten.native_layer_norm.default)[call_function]:Tuple[length=3](\nTensor(f32[4, 1024, 1024]),\nTensor(f32[4, 1024, 1]),\nTensor(f32[4, 1024, 1]),\n): Cannot find type promotion rule for op: aten.native_layer_norm.default" + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":1625 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0015", + "stacks":[] + }, + { + "message":{ + "markdown":"Skipped for fx.Node()[call_function]:Tensor(f32[4, 1024, 1024]): node.target is not OpOverload. Got type: \n\n## Additional Message:\n\n## Function Signature\n### Function Signature _TypePromotionInterpreter.run_node\n- self: \n- node: fx.Node()[call_function]:Tensor(f32[4, 1024, 1024])\n## Return values\nTensor(f32[4, 1024, 1024])", + "text":"Skipped for fx.Node()[call_function]:Tensor(f32[4, 1024, 1024]): node.target is not OpOverload. Got type: " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":1625 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0015", + "stacks":[] + }, + { + "message":{ + "markdown":"Skipped for fx.Node(aten.view.default)[call_function]:Tensor(f32[4096, 1024]): Cannot find type promotion rule for op: aten.view.default\n\n## Additional Message:\n\n## Function Signature\n### Function Signature _TypePromotionInterpreter.run_node\n- self: \n- node: fx.Node(aten.view.default)[call_function]:Tensor(f32[4096, 1024])\n## Return values\nTensor(f32[4096, 1024])", + "text":"Skipped for fx.Node(aten.view.default)[call_function]:Tensor(f32[4096, 1024]): Cannot find type promotion rule for op: aten.view.default" + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":1625 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0015", + "stacks":[] + }, + { + "message":{ + "markdown":"Skipped for fx.Node(aten.t.default)[call_function]:Tensor(f32[1024, 3072]): Cannot find type promotion rule for op: aten.t.default\n\n## Additional Message:\n\n## Function Signature\n### Function Signature _TypePromotionInterpreter.run_node\n- self: \n- node: fx.Node(aten.t.default)[call_function]:Tensor(f32[1024, 3072])\n## Return values\nTensor(f32[1024, 3072])", + "text":"Skipped for fx.Node(aten.t.default)[call_function]:Tensor(f32[1024, 3072]): Cannot find type promotion rule for op: aten.t.default" + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":1625 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0015", + "stacks":[] + }, + { + "message":{ + "markdown":"Skipped for fx.Node(aten.addmm.default)[call_function]:Tensor(f32[4096, 3072]): Cannot find type promotion rule for op: aten.addmm.default\n\n## Additional Message:\n\n## Function Signature\n### Function Signature _TypePromotionInterpreter.run_node\n- self: \n- node: fx.Node(aten.addmm.default)[call_function]:Tensor(f32[4096, 3072])\n## Return values\nTensor(f32[4096, 3072])", + "text":"Skipped for fx.Node(aten.addmm.default)[call_function]:Tensor(f32[4096, 3072]): Cannot find type promotion rule for op: aten.addmm.default" + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":1625 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0015", + "stacks":[] + }, + { + "message":{ + "markdown":"Skipped for fx.Node(aten.view.default)[call_function]:Tensor(f32[4, 1024, 3072]): Cannot find type promotion rule for op: aten.view.default\n\n## Additional Message:\n\n## Function Signature\n### Function Signature _TypePromotionInterpreter.run_node\n- self: \n- node: fx.Node(aten.view.default)[call_function]:Tensor(f32[4, 1024, 3072])\n## Return values\nTensor(f32[4, 1024, 3072])", + "text":"Skipped for fx.Node(aten.view.default)[call_function]:Tensor(f32[4, 1024, 3072]): Cannot find type promotion rule for op: aten.view.default" + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":1625 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0015", + "stacks":[] + }, + { + "message":{ + "markdown":"Skipped for fx.Node(aten.view.default)[call_function]:Tensor(f32[4, 1024, 3, 16, 64]): Cannot find type promotion rule for op: aten.view.default\n\n## Additional Message:\n\n## Function Signature\n### Function Signature _TypePromotionInterpreter.run_node\n- self: \n- node: fx.Node(aten.view.default)[call_function]:Tensor(f32[4, 1024, 3, 16, 64])\n## Return values\nTensor(f32[4, 1024, 3, 16, 64])", + "text":"Skipped for fx.Node(aten.view.default)[call_function]:Tensor(f32[4, 1024, 3, 16, 64]): Cannot find type promotion rule for op: aten.view.default" + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":1625 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0015", + "stacks":[] + }, + { + "message":{ + "markdown":"Skipped for fx.Node(aten.permute.default)[call_function]:Tensor(f32[3, 4, 16, 1024, 64]): Cannot find type promotion rule for op: aten.permute.default\n\n## Additional Message:\n\n## Function Signature\n### Function Signature _TypePromotionInterpreter.run_node\n- self: \n- node: fx.Node(aten.permute.default)[call_function]:Tensor(f32[3, 4, 16, 1024, 64])\n## Return values\nTensor(f32[3, 4, 16, 1024, 64])", + "text":"Skipped for fx.Node(aten.permute.default)[call_function]:Tensor(f32[3, 4, 16, 1024, 64]): Cannot find type promotion rule for op: aten.permute.default" + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":1625 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0015", + "stacks":[] + }, + { + "message":{ + "markdown":"Skipped for fx.Node(aten.unbind.int)[call_function]:List[length=3](\nTensor(f32[4, 16, 1024, 64]),\nTensor(f32[4, 16, 1024, 64]),\nTensor(f32[4, 16, 1024, 64]),\n): Cannot find type promotion rule for op: aten.unbind.int\n\n## Additional Message:\n\n## Function Signature\n### Function Signature _TypePromotionInterpreter.run_node\n- self: \n- node: fx.Node(aten.unbind.int)[call_function]:List[length=3](\nTensor(f32[4, 16, 1024, 64]),\nTensor(f32[4, 16, 1024, 64]),\nTensor(f32[4, 16, 1024, 64]),\n)\n## Return values\nList[length=3](\nTensor(f32[4, 16, 1024, 64]),\nTensor(f32[4, 16, 1024, 64]),\nTensor(f32[4, 16, 1024, 64]),\n)", + "text":"Skipped for fx.Node(aten.unbind.int)[call_function]:List[length=3](\nTensor(f32[4, 16, 1024, 64]),\nTensor(f32[4, 16, 1024, 64]),\nTensor(f32[4, 16, 1024, 64]),\n): Cannot find type promotion rule for op: aten.unbind.int" + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":1625 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0015", + "stacks":[] + }, + { + "message":{ + "markdown":"Skipped for fx.Node()[call_function]:Tensor(f32[4, 16, 1024, 64]): node.target is not OpOverload. Got type: \n\n## Additional Message:\n\n## Function Signature\n### Function Signature _TypePromotionInterpreter.run_node\n- self: \n- node: fx.Node()[call_function]:Tensor(f32[4, 16, 1024, 64])\n## Return values\nTensor(f32[4, 16, 1024, 64])", + "text":"Skipped for fx.Node()[call_function]:Tensor(f32[4, 16, 1024, 64]): node.target is not OpOverload. Got type: " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":1625 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0015", + "stacks":[] + }, + { + "message":{ + "markdown":"Skipped for fx.Node()[call_function]:Tensor(f32[4, 16, 1024, 64]): node.target is not OpOverload. Got type: \n\n## Additional Message:\n\n## Function Signature\n### Function Signature _TypePromotionInterpreter.run_node\n- self: \n- node: fx.Node()[call_function]:Tensor(f32[4, 16, 1024, 64])\n## Return values\nTensor(f32[4, 16, 1024, 64])", + "text":"Skipped for fx.Node()[call_function]:Tensor(f32[4, 16, 1024, 64]): node.target is not OpOverload. Got type: " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":1625 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0015", + "stacks":[] + }, + { + "message":{ + "markdown":"Skipped for fx.Node()[call_function]:Tensor(f32[4, 16, 1024, 64]): node.target is not OpOverload. Got type: \n\n## Additional Message:\n\n## Function Signature\n### Function Signature _TypePromotionInterpreter.run_node\n- self: \n- node: fx.Node()[call_function]:Tensor(f32[4, 16, 1024, 64])\n## Return values\nTensor(f32[4, 16, 1024, 64])", + "text":"Skipped for fx.Node()[call_function]:Tensor(f32[4, 16, 1024, 64]): node.target is not OpOverload. Got type: " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":1625 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0015", + "stacks":[] + }, + { + "message":{ + "markdown":"Skipped for fx.Node(aten._scaled_dot_product_efficient_attention.default)[call_function]:Tuple[length=4](\nTensor(f32[4, 16, 1024, 64]),\nTensor(f32[4, 16, 0]),\nTensor(i64[]),\nTensor(i64[]),\n): Cannot find type promotion rule for op: aten._scaled_dot_product_efficient_attention.default\n\n## Additional Message:\n\n## Function Signature\n### Function Signature _TypePromotionInterpreter.run_node\n- self: \n- node: fx.Node(aten._scaled_dot_product_efficient_attention.default)[call_function]:Tuple[length=4](\nTensor(f32[4, 16, 1024, 64]),\nTensor(f32[4, 16, 0]),\nTensor(i64[]),\nTensor(i64[]),\n)\n## Return values\nTuple[length=4](\nTensor(f32[4, 16, 1024, 64]),\nTensor(f32[4, 16, 0]),\nTensor(i64[]),\nTensor(i64[]),\n)", + "text":"Skipped for fx.Node(aten._scaled_dot_product_efficient_attention.default)[call_function]:Tuple[length=4](\nTensor(f32[4, 16, 1024, 64]),\nTensor(f32[4, 16, 0]),\nTensor(i64[]),\nTensor(i64[]),\n): Cannot find type promotion rule for op: aten._scaled_dot_product_efficient_attention.default" + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":1625 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0015", + "stacks":[] + }, + { + "message":{ + "markdown":"Skipped for fx.Node()[call_function]:Tensor(f32[4, 16, 1024, 64]): node.target is not OpOverload. Got type: \n\n## Additional Message:\n\n## Function Signature\n### Function Signature _TypePromotionInterpreter.run_node\n- self: \n- node: fx.Node()[call_function]:Tensor(f32[4, 16, 1024, 64])\n## Return values\nTensor(f32[4, 16, 1024, 64])", + "text":"Skipped for fx.Node()[call_function]:Tensor(f32[4, 16, 1024, 64]): node.target is not OpOverload. Got type: " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":1625 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0015", + "stacks":[] + }, + { + "message":{ + "markdown":"Skipped for fx.Node(aten.transpose.int)[call_function]:Tensor(f32[4, 1024, 16, 64]): Cannot find type promotion rule for op: aten.transpose.int\n\n## Additional Message:\n\n## Function Signature\n### Function Signature _TypePromotionInterpreter.run_node\n- self: \n- node: fx.Node(aten.transpose.int)[call_function]:Tensor(f32[4, 1024, 16, 64])\n## Return values\nTensor(f32[4, 1024, 16, 64])", + "text":"Skipped for fx.Node(aten.transpose.int)[call_function]:Tensor(f32[4, 1024, 16, 64]): Cannot find type promotion rule for op: aten.transpose.int" + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":1625 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0015", + "stacks":[] + }, + { + "message":{ + "markdown":"Skipped for fx.Node(aten.view.default)[call_function]:Tensor(f32[4, 1024, 1024]): Cannot find type promotion rule for op: aten.view.default\n\n## Additional Message:\n\n## Function Signature\n### Function Signature _TypePromotionInterpreter.run_node\n- self: \n- node: fx.Node(aten.view.default)[call_function]:Tensor(f32[4, 1024, 1024])\n## Return values\nTensor(f32[4, 1024, 1024])", + "text":"Skipped for fx.Node(aten.view.default)[call_function]:Tensor(f32[4, 1024, 1024]): Cannot find type promotion rule for op: aten.view.default" + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":1625 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0015", + "stacks":[] + }, + { + "message":{ + "markdown":"Skipped for fx.Node(aten.view.default)[call_function]:Tensor(f32[4096, 1024]): Cannot find type promotion rule for op: aten.view.default\n\n## Additional Message:\n\n## Function Signature\n### Function Signature _TypePromotionInterpreter.run_node\n- self: \n- node: fx.Node(aten.view.default)[call_function]:Tensor(f32[4096, 1024])\n## Return values\nTensor(f32[4096, 1024])", + "text":"Skipped for fx.Node(aten.view.default)[call_function]:Tensor(f32[4096, 1024]): Cannot find type promotion rule for op: aten.view.default" + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":1625 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0015", + "stacks":[] + }, + { + "message":{ + "markdown":"Skipped for fx.Node(aten.t.default)[call_function]:Tensor(f32[1024, 1024]): Cannot find type promotion rule for op: aten.t.default\n\n## Additional Message:\n\n## Function Signature\n### Function Signature _TypePromotionInterpreter.run_node\n- self: \n- node: fx.Node(aten.t.default)[call_function]:Tensor(f32[1024, 1024])\n## Return values\nTensor(f32[1024, 1024])", + "text":"Skipped for fx.Node(aten.t.default)[call_function]:Tensor(f32[1024, 1024]): Cannot find type promotion rule for op: aten.t.default" + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":1625 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0015", + "stacks":[] + }, + { + "message":{ + "markdown":"Skipped for fx.Node(aten.addmm.default)[call_function]:Tensor(f32[4096, 1024]): Cannot find type promotion rule for op: aten.addmm.default\n\n## Additional Message:\n\n## Function Signature\n### Function Signature _TypePromotionInterpreter.run_node\n- self: \n- node: fx.Node(aten.addmm.default)[call_function]:Tensor(f32[4096, 1024])\n## Return values\nTensor(f32[4096, 1024])", + "text":"Skipped for fx.Node(aten.addmm.default)[call_function]:Tensor(f32[4096, 1024]): Cannot find type promotion rule for op: aten.addmm.default" + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":1625 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0015", + "stacks":[] + }, + { + "message":{ + "markdown":"Skipped for fx.Node(aten.view.default)[call_function]:Tensor(f32[4, 1024, 1024]): Cannot find type promotion rule for op: aten.view.default\n\n## Additional Message:\n\n## Function Signature\n### Function Signature _TypePromotionInterpreter.run_node\n- self: \n- node: fx.Node(aten.view.default)[call_function]:Tensor(f32[4, 1024, 1024])\n## Return values\nTensor(f32[4, 1024, 1024])", + "text":"Skipped for fx.Node(aten.view.default)[call_function]:Tensor(f32[4, 1024, 1024]): Cannot find type promotion rule for op: aten.view.default" + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":1625 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0015", + "stacks":[] + }, + { + "message":{ + "markdown":"Skipped for fx.Node(aten.clone.default)[call_function]:Tensor(f32[4, 1024, 1024]): Cannot find type promotion rule for op: aten.clone.default\n\n## Additional Message:\n\n## Function Signature\n### Function Signature _TypePromotionInterpreter.run_node\n- self: \n- node: fx.Node(aten.clone.default)[call_function]:Tensor(f32[4, 1024, 1024])\n## Return values\nTensor(f32[4, 1024, 1024])", + "text":"Skipped for fx.Node(aten.clone.default)[call_function]:Tensor(f32[4, 1024, 1024]): Cannot find type promotion rule for op: aten.clone.default" + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":1625 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0015", + "stacks":[] + }, + { + "message":{ + "markdown":"Type promotion not needed for add_11. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature _TypePromotionInterpreter.run_node\n- self: \n- node: fx.Node(aten.add.Tensor)[call_function]:Tensor(f32[4, 1024, 1024])\nFound type promotion rule: ElementwiseTypePromotionRule('aten', 'add', [0, 1], [], ELEMENTWISE_TYPE_PROMOTION_KIND.DEFAULT)\nArgument add_10 is not promoted. Already torch.float32.\nArgument clone_16 is not promoted. Already torch.float32.\n## Return values\nTensor(f32[4, 1024, 1024])", + "text":"Type promotion not needed for add_11. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":1625 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0015", + "stacks":[] + }, + { + "message":{ + "markdown":"Skipped for fx.Node(aten.native_layer_norm.default)[call_function]:Tuple[length=3](\nTensor(f32[4, 1024, 1024]),\nTensor(f32[4, 1024, 1]),\nTensor(f32[4, 1024, 1]),\n): Cannot find type promotion rule for op: aten.native_layer_norm.default\n\n## Additional Message:\n\n## Function Signature\n### Function Signature _TypePromotionInterpreter.run_node\n- self: \n- node: fx.Node(aten.native_layer_norm.default)[call_function]:Tuple[length=3](\nTensor(f32[4, 1024, 1024]),\nTensor(f32[4, 1024, 1]),\nTensor(f32[4, 1024, 1]),\n)\n## Return values\nTuple[length=3](\nTensor(f32[4, 1024, 1024]),\nTensor(f32[4, 1024, 1]),\nTensor(f32[4, 1024, 1]),\n)", + "text":"Skipped for fx.Node(aten.native_layer_norm.default)[call_function]:Tuple[length=3](\nTensor(f32[4, 1024, 1024]),\nTensor(f32[4, 1024, 1]),\nTensor(f32[4, 1024, 1]),\n): Cannot find type promotion rule for op: aten.native_layer_norm.default" + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":1625 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0015", + "stacks":[] + }, + { + "message":{ + "markdown":"Skipped for fx.Node()[call_function]:Tensor(f32[4, 1024, 1024]): node.target is not OpOverload. Got type: \n\n## Additional Message:\n\n## Function Signature\n### Function Signature _TypePromotionInterpreter.run_node\n- self: \n- node: fx.Node()[call_function]:Tensor(f32[4, 1024, 1024])\n## Return values\nTensor(f32[4, 1024, 1024])", + "text":"Skipped for fx.Node()[call_function]:Tensor(f32[4, 1024, 1024]): node.target is not OpOverload. Got type: " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":1625 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0015", + "stacks":[] + }, + { + "message":{ + "markdown":"Skipped for fx.Node(aten.view.default)[call_function]:Tensor(f32[4096, 1024]): Cannot find type promotion rule for op: aten.view.default\n\n## Additional Message:\n\n## Function Signature\n### Function Signature _TypePromotionInterpreter.run_node\n- self: \n- node: fx.Node(aten.view.default)[call_function]:Tensor(f32[4096, 1024])\n## Return values\nTensor(f32[4096, 1024])", + "text":"Skipped for fx.Node(aten.view.default)[call_function]:Tensor(f32[4096, 1024]): Cannot find type promotion rule for op: aten.view.default" + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":1625 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0015", + "stacks":[] + }, + { + "message":{ + "markdown":"Skipped for fx.Node(aten.t.default)[call_function]:Tensor(f32[1024, 4096]): Cannot find type promotion rule for op: aten.t.default\n\n## Additional Message:\n\n## Function Signature\n### Function Signature _TypePromotionInterpreter.run_node\n- self: \n- node: fx.Node(aten.t.default)[call_function]:Tensor(f32[1024, 4096])\n## Return values\nTensor(f32[1024, 4096])", + "text":"Skipped for fx.Node(aten.t.default)[call_function]:Tensor(f32[1024, 4096]): Cannot find type promotion rule for op: aten.t.default" + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":1625 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0015", + "stacks":[] + }, + { + "message":{ + "markdown":"Skipped for fx.Node(aten.addmm.default)[call_function]:Tensor(f32[4096, 4096]): Cannot find type promotion rule for op: aten.addmm.default\n\n## Additional Message:\n\n## Function Signature\n### Function Signature _TypePromotionInterpreter.run_node\n- self: \n- node: fx.Node(aten.addmm.default)[call_function]:Tensor(f32[4096, 4096])\n## Return values\nTensor(f32[4096, 4096])", + "text":"Skipped for fx.Node(aten.addmm.default)[call_function]:Tensor(f32[4096, 4096]): Cannot find type promotion rule for op: aten.addmm.default" + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":1625 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0015", + "stacks":[] + }, + { + "message":{ + "markdown":"Skipped for fx.Node(aten.view.default)[call_function]:Tensor(f32[4, 1024, 4096]): Cannot find type promotion rule for op: aten.view.default\n\n## Additional Message:\n\n## Function Signature\n### Function Signature _TypePromotionInterpreter.run_node\n- self: \n- node: fx.Node(aten.view.default)[call_function]:Tensor(f32[4, 1024, 4096])\n## Return values\nTensor(f32[4, 1024, 4096])", + "text":"Skipped for fx.Node(aten.view.default)[call_function]:Tensor(f32[4, 1024, 4096]): Cannot find type promotion rule for op: aten.view.default" + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":1625 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0015", + "stacks":[] + }, + { + "message":{ + "markdown":"Type promotion not needed for gelu_5. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature _TypePromotionInterpreter.run_node\n- self: \n- node: fx.Node(aten.gelu.default)[call_function]:Tensor(f32[4, 1024, 4096])\nFound type promotion rule: ElementwiseTypePromotionRule('aten', 'gelu', [0], [], ELEMENTWISE_TYPE_PROMOTION_KIND.DEFAULT)\nArgument view_58 is not promoted. Already torch.float32.\nArgument tanh is not promoted. Not mentioned by type promotion rule.\n## Return values\nTensor(f32[4, 1024, 4096])", + "text":"Type promotion not needed for gelu_5. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":1625 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0015", + "stacks":[] + }, + { + "message":{ + "markdown":"Skipped for fx.Node(aten.clone.default)[call_function]:Tensor(f32[4, 1024, 4096]): Cannot find type promotion rule for op: aten.clone.default\n\n## Additional Message:\n\n## Function Signature\n### Function Signature _TypePromotionInterpreter.run_node\n- self: \n- node: fx.Node(aten.clone.default)[call_function]:Tensor(f32[4, 1024, 4096])\n## Return values\nTensor(f32[4, 1024, 4096])", + "text":"Skipped for fx.Node(aten.clone.default)[call_function]:Tensor(f32[4, 1024, 4096]): Cannot find type promotion rule for op: aten.clone.default" + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":1625 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0015", + "stacks":[] + }, + { + "message":{ + "markdown":"Skipped for fx.Node(aten.view.default)[call_function]:Tensor(f32[4096, 4096]): Cannot find type promotion rule for op: aten.view.default\n\n## Additional Message:\n\n## Function Signature\n### Function Signature _TypePromotionInterpreter.run_node\n- self: \n- node: fx.Node(aten.view.default)[call_function]:Tensor(f32[4096, 4096])\n## Return values\nTensor(f32[4096, 4096])", + "text":"Skipped for fx.Node(aten.view.default)[call_function]:Tensor(f32[4096, 4096]): Cannot find type promotion rule for op: aten.view.default" + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":1625 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0015", + "stacks":[] + }, + { + "message":{ + "markdown":"Skipped for fx.Node(aten.t.default)[call_function]:Tensor(f32[4096, 1024]): Cannot find type promotion rule for op: aten.t.default\n\n## Additional Message:\n\n## Function Signature\n### Function Signature _TypePromotionInterpreter.run_node\n- self: \n- node: fx.Node(aten.t.default)[call_function]:Tensor(f32[4096, 1024])\n## Return values\nTensor(f32[4096, 1024])", + "text":"Skipped for fx.Node(aten.t.default)[call_function]:Tensor(f32[4096, 1024]): Cannot find type promotion rule for op: aten.t.default" + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":1625 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0015", + "stacks":[] + }, + { + "message":{ + "markdown":"Skipped for fx.Node(aten.addmm.default)[call_function]:Tensor(f32[4096, 1024]): Cannot find type promotion rule for op: aten.addmm.default\n\n## Additional Message:\n\n## Function Signature\n### Function Signature _TypePromotionInterpreter.run_node\n- self: \n- node: fx.Node(aten.addmm.default)[call_function]:Tensor(f32[4096, 1024])\n## Return values\nTensor(f32[4096, 1024])", + "text":"Skipped for fx.Node(aten.addmm.default)[call_function]:Tensor(f32[4096, 1024]): Cannot find type promotion rule for op: aten.addmm.default" + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":1625 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0015", + "stacks":[] + }, + { + "message":{ + "markdown":"Skipped for fx.Node(aten.view.default)[call_function]:Tensor(f32[4, 1024, 1024]): Cannot find type promotion rule for op: aten.view.default\n\n## Additional Message:\n\n## Function Signature\n### Function Signature _TypePromotionInterpreter.run_node\n- self: \n- node: fx.Node(aten.view.default)[call_function]:Tensor(f32[4, 1024, 1024])\n## Return values\nTensor(f32[4, 1024, 1024])", + "text":"Skipped for fx.Node(aten.view.default)[call_function]:Tensor(f32[4, 1024, 1024]): Cannot find type promotion rule for op: aten.view.default" + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":1625 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0015", + "stacks":[] + }, + { + "message":{ + "markdown":"Skipped for fx.Node(aten.clone.default)[call_function]:Tensor(f32[4, 1024, 1024]): Cannot find type promotion rule for op: aten.clone.default\n\n## Additional Message:\n\n## Function Signature\n### Function Signature _TypePromotionInterpreter.run_node\n- self: \n- node: fx.Node(aten.clone.default)[call_function]:Tensor(f32[4, 1024, 1024])\n## Return values\nTensor(f32[4, 1024, 1024])", + "text":"Skipped for fx.Node(aten.clone.default)[call_function]:Tensor(f32[4, 1024, 1024]): Cannot find type promotion rule for op: aten.clone.default" + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":1625 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0015", + "stacks":[] + }, + { + "message":{ + "markdown":"Type promotion not needed for add_12. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature _TypePromotionInterpreter.run_node\n- self: \n- node: fx.Node(aten.add.Tensor)[call_function]:Tensor(f32[4, 1024, 1024])\nFound type promotion rule: ElementwiseTypePromotionRule('aten', 'add', [0, 1], [], ELEMENTWISE_TYPE_PROMOTION_KIND.DEFAULT)\nArgument add_11 is not promoted. Already torch.float32.\nArgument clone_18 is not promoted. Already torch.float32.\n## Return values\nTensor(f32[4, 1024, 1024])", + "text":"Type promotion not needed for add_12. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":1625 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0015", + "stacks":[] + }, + { + "message":{ + "markdown":"Skipped for fx.Node(aten.native_layer_norm.default)[call_function]:Tuple[length=3](\nTensor(f32[4, 1024, 1024]),\nTensor(f32[4, 1024, 1]),\nTensor(f32[4, 1024, 1]),\n): Cannot find type promotion rule for op: aten.native_layer_norm.default\n\n## Additional Message:\n\n## Function Signature\n### Function Signature _TypePromotionInterpreter.run_node\n- self: \n- node: fx.Node(aten.native_layer_norm.default)[call_function]:Tuple[length=3](\nTensor(f32[4, 1024, 1024]),\nTensor(f32[4, 1024, 1]),\nTensor(f32[4, 1024, 1]),\n)\n## Return values\nTuple[length=3](\nTensor(f32[4, 1024, 1024]),\nTensor(f32[4, 1024, 1]),\nTensor(f32[4, 1024, 1]),\n)", + "text":"Skipped for fx.Node(aten.native_layer_norm.default)[call_function]:Tuple[length=3](\nTensor(f32[4, 1024, 1024]),\nTensor(f32[4, 1024, 1]),\nTensor(f32[4, 1024, 1]),\n): Cannot find type promotion rule for op: aten.native_layer_norm.default" + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":1625 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0015", + "stacks":[] + }, + { + "message":{ + "markdown":"Skipped for fx.Node()[call_function]:Tensor(f32[4, 1024, 1024]): node.target is not OpOverload. Got type: \n\n## Additional Message:\n\n## Function Signature\n### Function Signature _TypePromotionInterpreter.run_node\n- self: \n- node: fx.Node()[call_function]:Tensor(f32[4, 1024, 1024])\n## Return values\nTensor(f32[4, 1024, 1024])", + "text":"Skipped for fx.Node()[call_function]:Tensor(f32[4, 1024, 1024]): node.target is not OpOverload. Got type: " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":1625 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0015", + "stacks":[] + }, + { + "message":{ + "markdown":"Skipped for fx.Node(aten.view.default)[call_function]:Tensor(f32[4096, 1024]): Cannot find type promotion rule for op: aten.view.default\n\n## Additional Message:\n\n## Function Signature\n### Function Signature _TypePromotionInterpreter.run_node\n- self: \n- node: fx.Node(aten.view.default)[call_function]:Tensor(f32[4096, 1024])\n## Return values\nTensor(f32[4096, 1024])", + "text":"Skipped for fx.Node(aten.view.default)[call_function]:Tensor(f32[4096, 1024]): Cannot find type promotion rule for op: aten.view.default" + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":1625 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0015", + "stacks":[] + }, + { + "message":{ + "markdown":"Skipped for fx.Node(aten.t.default)[call_function]:Tensor(f32[1024, 3072]): Cannot find type promotion rule for op: aten.t.default\n\n## Additional Message:\n\n## Function Signature\n### Function Signature _TypePromotionInterpreter.run_node\n- self: \n- node: fx.Node(aten.t.default)[call_function]:Tensor(f32[1024, 3072])\n## Return values\nTensor(f32[1024, 3072])", + "text":"Skipped for fx.Node(aten.t.default)[call_function]:Tensor(f32[1024, 3072]): Cannot find type promotion rule for op: aten.t.default" + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":1625 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0015", + "stacks":[] + }, + { + "message":{ + "markdown":"Skipped for fx.Node(aten.addmm.default)[call_function]:Tensor(f32[4096, 3072]): Cannot find type promotion rule for op: aten.addmm.default\n\n## Additional Message:\n\n## Function Signature\n### Function Signature _TypePromotionInterpreter.run_node\n- self: \n- node: fx.Node(aten.addmm.default)[call_function]:Tensor(f32[4096, 3072])\n## Return values\nTensor(f32[4096, 3072])", + "text":"Skipped for fx.Node(aten.addmm.default)[call_function]:Tensor(f32[4096, 3072]): Cannot find type promotion rule for op: aten.addmm.default" + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":1625 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0015", + "stacks":[] + }, + { + "message":{ + "markdown":"Skipped for fx.Node(aten.view.default)[call_function]:Tensor(f32[4, 1024, 3072]): Cannot find type promotion rule for op: aten.view.default\n\n## Additional Message:\n\n## Function Signature\n### Function Signature _TypePromotionInterpreter.run_node\n- self: \n- node: fx.Node(aten.view.default)[call_function]:Tensor(f32[4, 1024, 3072])\n## Return values\nTensor(f32[4, 1024, 3072])", + "text":"Skipped for fx.Node(aten.view.default)[call_function]:Tensor(f32[4, 1024, 3072]): Cannot find type promotion rule for op: aten.view.default" + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":1625 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0015", + "stacks":[] + }, + { + "message":{ + "markdown":"Skipped for fx.Node(aten.view.default)[call_function]:Tensor(f32[4, 1024, 3, 16, 64]): Cannot find type promotion rule for op: aten.view.default\n\n## Additional Message:\n\n## Function Signature\n### Function Signature _TypePromotionInterpreter.run_node\n- self: \n- node: fx.Node(aten.view.default)[call_function]:Tensor(f32[4, 1024, 3, 16, 64])\n## Return values\nTensor(f32[4, 1024, 3, 16, 64])", + "text":"Skipped for fx.Node(aten.view.default)[call_function]:Tensor(f32[4, 1024, 3, 16, 64]): Cannot find type promotion rule for op: aten.view.default" + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":1625 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0015", + "stacks":[] + }, + { + "message":{ + "markdown":"Skipped for fx.Node(aten.permute.default)[call_function]:Tensor(f32[3, 4, 16, 1024, 64]): Cannot find type promotion rule for op: aten.permute.default\n\n## Additional Message:\n\n## Function Signature\n### Function Signature _TypePromotionInterpreter.run_node\n- self: \n- node: fx.Node(aten.permute.default)[call_function]:Tensor(f32[3, 4, 16, 1024, 64])\n## Return values\nTensor(f32[3, 4, 16, 1024, 64])", + "text":"Skipped for fx.Node(aten.permute.default)[call_function]:Tensor(f32[3, 4, 16, 1024, 64]): Cannot find type promotion rule for op: aten.permute.default" + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":1625 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0015", + "stacks":[] + }, + { + "message":{ + "markdown":"Skipped for fx.Node(aten.unbind.int)[call_function]:List[length=3](\nTensor(f32[4, 16, 1024, 64]),\nTensor(f32[4, 16, 1024, 64]),\nTensor(f32[4, 16, 1024, 64]),\n): Cannot find type promotion rule for op: aten.unbind.int\n\n## Additional Message:\n\n## Function Signature\n### Function Signature _TypePromotionInterpreter.run_node\n- self: \n- node: fx.Node(aten.unbind.int)[call_function]:List[length=3](\nTensor(f32[4, 16, 1024, 64]),\nTensor(f32[4, 16, 1024, 64]),\nTensor(f32[4, 16, 1024, 64]),\n)\n## Return values\nList[length=3](\nTensor(f32[4, 16, 1024, 64]),\nTensor(f32[4, 16, 1024, 64]),\nTensor(f32[4, 16, 1024, 64]),\n)", + "text":"Skipped for fx.Node(aten.unbind.int)[call_function]:List[length=3](\nTensor(f32[4, 16, 1024, 64]),\nTensor(f32[4, 16, 1024, 64]),\nTensor(f32[4, 16, 1024, 64]),\n): Cannot find type promotion rule for op: aten.unbind.int" + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":1625 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0015", + "stacks":[] + }, + { + "message":{ + "markdown":"Skipped for fx.Node()[call_function]:Tensor(f32[4, 16, 1024, 64]): node.target is not OpOverload. Got type: \n\n## Additional Message:\n\n## Function Signature\n### Function Signature _TypePromotionInterpreter.run_node\n- self: \n- node: fx.Node()[call_function]:Tensor(f32[4, 16, 1024, 64])\n## Return values\nTensor(f32[4, 16, 1024, 64])", + "text":"Skipped for fx.Node()[call_function]:Tensor(f32[4, 16, 1024, 64]): node.target is not OpOverload. Got type: " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":1625 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0015", + "stacks":[] + }, + { + "message":{ + "markdown":"Skipped for fx.Node()[call_function]:Tensor(f32[4, 16, 1024, 64]): node.target is not OpOverload. Got type: \n\n## Additional Message:\n\n## Function Signature\n### Function Signature _TypePromotionInterpreter.run_node\n- self: \n- node: fx.Node()[call_function]:Tensor(f32[4, 16, 1024, 64])\n## Return values\nTensor(f32[4, 16, 1024, 64])", + "text":"Skipped for fx.Node()[call_function]:Tensor(f32[4, 16, 1024, 64]): node.target is not OpOverload. Got type: " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":1625 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0015", + "stacks":[] + }, + { + "message":{ + "markdown":"Skipped for fx.Node()[call_function]:Tensor(f32[4, 16, 1024, 64]): node.target is not OpOverload. Got type: \n\n## Additional Message:\n\n## Function Signature\n### Function Signature _TypePromotionInterpreter.run_node\n- self: \n- node: fx.Node()[call_function]:Tensor(f32[4, 16, 1024, 64])\n## Return values\nTensor(f32[4, 16, 1024, 64])", + "text":"Skipped for fx.Node()[call_function]:Tensor(f32[4, 16, 1024, 64]): node.target is not OpOverload. Got type: " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":1625 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0015", + "stacks":[] + }, + { + "message":{ + "markdown":"Skipped for fx.Node(aten._scaled_dot_product_efficient_attention.default)[call_function]:Tuple[length=4](\nTensor(f32[4, 16, 1024, 64]),\nTensor(f32[4, 16, 0]),\nTensor(i64[]),\nTensor(i64[]),\n): Cannot find type promotion rule for op: aten._scaled_dot_product_efficient_attention.default\n\n## Additional Message:\n\n## Function Signature\n### Function Signature _TypePromotionInterpreter.run_node\n- self: \n- node: fx.Node(aten._scaled_dot_product_efficient_attention.default)[call_function]:Tuple[length=4](\nTensor(f32[4, 16, 1024, 64]),\nTensor(f32[4, 16, 0]),\nTensor(i64[]),\nTensor(i64[]),\n)\n## Return values\nTuple[length=4](\nTensor(f32[4, 16, 1024, 64]),\nTensor(f32[4, 16, 0]),\nTensor(i64[]),\nTensor(i64[]),\n)", + "text":"Skipped for fx.Node(aten._scaled_dot_product_efficient_attention.default)[call_function]:Tuple[length=4](\nTensor(f32[4, 16, 1024, 64]),\nTensor(f32[4, 16, 0]),\nTensor(i64[]),\nTensor(i64[]),\n): Cannot find type promotion rule for op: aten._scaled_dot_product_efficient_attention.default" + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":1625 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0015", + "stacks":[] + }, + { + "message":{ + "markdown":"Skipped for fx.Node()[call_function]:Tensor(f32[4, 16, 1024, 64]): node.target is not OpOverload. Got type: \n\n## Additional Message:\n\n## Function Signature\n### Function Signature _TypePromotionInterpreter.run_node\n- self: \n- node: fx.Node()[call_function]:Tensor(f32[4, 16, 1024, 64])\n## Return values\nTensor(f32[4, 16, 1024, 64])", + "text":"Skipped for fx.Node()[call_function]:Tensor(f32[4, 16, 1024, 64]): node.target is not OpOverload. Got type: " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":1625 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0015", + "stacks":[] + }, + { + "message":{ + "markdown":"Skipped for fx.Node(aten.transpose.int)[call_function]:Tensor(f32[4, 1024, 16, 64]): Cannot find type promotion rule for op: aten.transpose.int\n\n## Additional Message:\n\n## Function Signature\n### Function Signature _TypePromotionInterpreter.run_node\n- self: \n- node: fx.Node(aten.transpose.int)[call_function]:Tensor(f32[4, 1024, 16, 64])\n## Return values\nTensor(f32[4, 1024, 16, 64])", + "text":"Skipped for fx.Node(aten.transpose.int)[call_function]:Tensor(f32[4, 1024, 16, 64]): Cannot find type promotion rule for op: aten.transpose.int" + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":1625 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0015", + "stacks":[] + }, + { + "message":{ + "markdown":"Skipped for fx.Node(aten.view.default)[call_function]:Tensor(f32[4, 1024, 1024]): Cannot find type promotion rule for op: aten.view.default\n\n## Additional Message:\n\n## Function Signature\n### Function Signature _TypePromotionInterpreter.run_node\n- self: \n- node: fx.Node(aten.view.default)[call_function]:Tensor(f32[4, 1024, 1024])\n## Return values\nTensor(f32[4, 1024, 1024])", + "text":"Skipped for fx.Node(aten.view.default)[call_function]:Tensor(f32[4, 1024, 1024]): Cannot find type promotion rule for op: aten.view.default" + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":1625 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0015", + "stacks":[] + }, + { + "message":{ + "markdown":"Skipped for fx.Node(aten.view.default)[call_function]:Tensor(f32[4096, 1024]): Cannot find type promotion rule for op: aten.view.default\n\n## Additional Message:\n\n## Function Signature\n### Function Signature _TypePromotionInterpreter.run_node\n- self: \n- node: fx.Node(aten.view.default)[call_function]:Tensor(f32[4096, 1024])\n## Return values\nTensor(f32[4096, 1024])", + "text":"Skipped for fx.Node(aten.view.default)[call_function]:Tensor(f32[4096, 1024]): Cannot find type promotion rule for op: aten.view.default" + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":1625 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0015", + "stacks":[] + }, + { + "message":{ + "markdown":"Skipped for fx.Node(aten.t.default)[call_function]:Tensor(f32[1024, 1024]): Cannot find type promotion rule for op: aten.t.default\n\n## Additional Message:\n\n## Function Signature\n### Function Signature _TypePromotionInterpreter.run_node\n- self: \n- node: fx.Node(aten.t.default)[call_function]:Tensor(f32[1024, 1024])\n## Return values\nTensor(f32[1024, 1024])", + "text":"Skipped for fx.Node(aten.t.default)[call_function]:Tensor(f32[1024, 1024]): Cannot find type promotion rule for op: aten.t.default" + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":1625 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0015", + "stacks":[] + }, + { + "message":{ + "markdown":"Skipped for fx.Node(aten.addmm.default)[call_function]:Tensor(f32[4096, 1024]): Cannot find type promotion rule for op: aten.addmm.default\n\n## Additional Message:\n\n## Function Signature\n### Function Signature _TypePromotionInterpreter.run_node\n- self: \n- node: fx.Node(aten.addmm.default)[call_function]:Tensor(f32[4096, 1024])\n## Return values\nTensor(f32[4096, 1024])", + "text":"Skipped for fx.Node(aten.addmm.default)[call_function]:Tensor(f32[4096, 1024]): Cannot find type promotion rule for op: aten.addmm.default" + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":1625 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0015", + "stacks":[] + }, + { + "message":{ + "markdown":"Skipped for fx.Node(aten.view.default)[call_function]:Tensor(f32[4, 1024, 1024]): Cannot find type promotion rule for op: aten.view.default\n\n## Additional Message:\n\n## Function Signature\n### Function Signature _TypePromotionInterpreter.run_node\n- self: \n- node: fx.Node(aten.view.default)[call_function]:Tensor(f32[4, 1024, 1024])\n## Return values\nTensor(f32[4, 1024, 1024])", + "text":"Skipped for fx.Node(aten.view.default)[call_function]:Tensor(f32[4, 1024, 1024]): Cannot find type promotion rule for op: aten.view.default" + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":1625 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0015", + "stacks":[] + }, + { + "message":{ + "markdown":"Skipped for fx.Node(aten.clone.default)[call_function]:Tensor(f32[4, 1024, 1024]): Cannot find type promotion rule for op: aten.clone.default\n\n## Additional Message:\n\n## Function Signature\n### Function Signature _TypePromotionInterpreter.run_node\n- self: \n- node: fx.Node(aten.clone.default)[call_function]:Tensor(f32[4, 1024, 1024])\n## Return values\nTensor(f32[4, 1024, 1024])", + "text":"Skipped for fx.Node(aten.clone.default)[call_function]:Tensor(f32[4, 1024, 1024]): Cannot find type promotion rule for op: aten.clone.default" + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":1625 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0015", + "stacks":[] + }, + { + "message":{ + "markdown":"Type promotion not needed for add_13. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature _TypePromotionInterpreter.run_node\n- self: \n- node: fx.Node(aten.add.Tensor)[call_function]:Tensor(f32[4, 1024, 1024])\nFound type promotion rule: ElementwiseTypePromotionRule('aten', 'add', [0, 1], [], ELEMENTWISE_TYPE_PROMOTION_KIND.DEFAULT)\nArgument add_12 is not promoted. Already torch.float32.\nArgument clone_19 is not promoted. Already torch.float32.\n## Return values\nTensor(f32[4, 1024, 1024])", + "text":"Type promotion not needed for add_13. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":1625 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0015", + "stacks":[] + }, + { + "message":{ + "markdown":"Skipped for fx.Node(aten.native_layer_norm.default)[call_function]:Tuple[length=3](\nTensor(f32[4, 1024, 1024]),\nTensor(f32[4, 1024, 1]),\nTensor(f32[4, 1024, 1]),\n): Cannot find type promotion rule for op: aten.native_layer_norm.default\n\n## Additional Message:\n\n## Function Signature\n### Function Signature _TypePromotionInterpreter.run_node\n- self: \n- node: fx.Node(aten.native_layer_norm.default)[call_function]:Tuple[length=3](\nTensor(f32[4, 1024, 1024]),\nTensor(f32[4, 1024, 1]),\nTensor(f32[4, 1024, 1]),\n)\n## Return values\nTuple[length=3](\nTensor(f32[4, 1024, 1024]),\nTensor(f32[4, 1024, 1]),\nTensor(f32[4, 1024, 1]),\n)", + "text":"Skipped for fx.Node(aten.native_layer_norm.default)[call_function]:Tuple[length=3](\nTensor(f32[4, 1024, 1024]),\nTensor(f32[4, 1024, 1]),\nTensor(f32[4, 1024, 1]),\n): Cannot find type promotion rule for op: aten.native_layer_norm.default" + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":1625 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0015", + "stacks":[] + }, + { + "message":{ + "markdown":"Skipped for fx.Node()[call_function]:Tensor(f32[4, 1024, 1024]): node.target is not OpOverload. Got type: \n\n## Additional Message:\n\n## Function Signature\n### Function Signature _TypePromotionInterpreter.run_node\n- self: \n- node: fx.Node()[call_function]:Tensor(f32[4, 1024, 1024])\n## Return values\nTensor(f32[4, 1024, 1024])", + "text":"Skipped for fx.Node()[call_function]:Tensor(f32[4, 1024, 1024]): node.target is not OpOverload. Got type: " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":1625 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0015", + "stacks":[] + }, + { + "message":{ + "markdown":"Skipped for fx.Node(aten.view.default)[call_function]:Tensor(f32[4096, 1024]): Cannot find type promotion rule for op: aten.view.default\n\n## Additional Message:\n\n## Function Signature\n### Function Signature _TypePromotionInterpreter.run_node\n- self: \n- node: fx.Node(aten.view.default)[call_function]:Tensor(f32[4096, 1024])\n## Return values\nTensor(f32[4096, 1024])", + "text":"Skipped for fx.Node(aten.view.default)[call_function]:Tensor(f32[4096, 1024]): Cannot find type promotion rule for op: aten.view.default" + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":1625 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0015", + "stacks":[] + }, + { + "message":{ + "markdown":"Skipped for fx.Node(aten.t.default)[call_function]:Tensor(f32[1024, 4096]): Cannot find type promotion rule for op: aten.t.default\n\n## Additional Message:\n\n## Function Signature\n### Function Signature _TypePromotionInterpreter.run_node\n- self: \n- node: fx.Node(aten.t.default)[call_function]:Tensor(f32[1024, 4096])\n## Return values\nTensor(f32[1024, 4096])", + "text":"Skipped for fx.Node(aten.t.default)[call_function]:Tensor(f32[1024, 4096]): Cannot find type promotion rule for op: aten.t.default" + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":1625 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0015", + "stacks":[] + }, + { + "message":{ + "markdown":"Skipped for fx.Node(aten.addmm.default)[call_function]:Tensor(f32[4096, 4096]): Cannot find type promotion rule for op: aten.addmm.default\n\n## Additional Message:\n\n## Function Signature\n### Function Signature _TypePromotionInterpreter.run_node\n- self: \n- node: fx.Node(aten.addmm.default)[call_function]:Tensor(f32[4096, 4096])\n## Return values\nTensor(f32[4096, 4096])", + "text":"Skipped for fx.Node(aten.addmm.default)[call_function]:Tensor(f32[4096, 4096]): Cannot find type promotion rule for op: aten.addmm.default" + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":1625 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0015", + "stacks":[] + }, + { + "message":{ + "markdown":"Skipped for fx.Node(aten.view.default)[call_function]:Tensor(f32[4, 1024, 4096]): Cannot find type promotion rule for op: aten.view.default\n\n## Additional Message:\n\n## Function Signature\n### Function Signature _TypePromotionInterpreter.run_node\n- self: \n- node: fx.Node(aten.view.default)[call_function]:Tensor(f32[4, 1024, 4096])\n## Return values\nTensor(f32[4, 1024, 4096])", + "text":"Skipped for fx.Node(aten.view.default)[call_function]:Tensor(f32[4, 1024, 4096]): Cannot find type promotion rule for op: aten.view.default" + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":1625 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0015", + "stacks":[] + }, + { + "message":{ + "markdown":"Type promotion not needed for gelu_6. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature _TypePromotionInterpreter.run_node\n- self: \n- node: fx.Node(aten.gelu.default)[call_function]:Tensor(f32[4, 1024, 4096])\nFound type promotion rule: ElementwiseTypePromotionRule('aten', 'gelu', [0], [], ELEMENTWISE_TYPE_PROMOTION_KIND.DEFAULT)\nArgument view_68 is not promoted. Already torch.float32.\nArgument tanh is not promoted. Not mentioned by type promotion rule.\n## Return values\nTensor(f32[4, 1024, 4096])", + "text":"Type promotion not needed for gelu_6. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":1625 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0015", + "stacks":[] + }, + { + "message":{ + "markdown":"Skipped for fx.Node(aten.clone.default)[call_function]:Tensor(f32[4, 1024, 4096]): Cannot find type promotion rule for op: aten.clone.default\n\n## Additional Message:\n\n## Function Signature\n### Function Signature _TypePromotionInterpreter.run_node\n- self: \n- node: fx.Node(aten.clone.default)[call_function]:Tensor(f32[4, 1024, 4096])\n## Return values\nTensor(f32[4, 1024, 4096])", + "text":"Skipped for fx.Node(aten.clone.default)[call_function]:Tensor(f32[4, 1024, 4096]): Cannot find type promotion rule for op: aten.clone.default" + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":1625 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0015", + "stacks":[] + }, + { + "message":{ + "markdown":"Skipped for fx.Node(aten.view.default)[call_function]:Tensor(f32[4096, 4096]): Cannot find type promotion rule for op: aten.view.default\n\n## Additional Message:\n\n## Function Signature\n### Function Signature _TypePromotionInterpreter.run_node\n- self: \n- node: fx.Node(aten.view.default)[call_function]:Tensor(f32[4096, 4096])\n## Return values\nTensor(f32[4096, 4096])", + "text":"Skipped for fx.Node(aten.view.default)[call_function]:Tensor(f32[4096, 4096]): Cannot find type promotion rule for op: aten.view.default" + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":1625 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0015", + "stacks":[] + }, + { + "message":{ + "markdown":"Skipped for fx.Node(aten.t.default)[call_function]:Tensor(f32[4096, 1024]): Cannot find type promotion rule for op: aten.t.default\n\n## Additional Message:\n\n## Function Signature\n### Function Signature _TypePromotionInterpreter.run_node\n- self: \n- node: fx.Node(aten.t.default)[call_function]:Tensor(f32[4096, 1024])\n## Return values\nTensor(f32[4096, 1024])", + "text":"Skipped for fx.Node(aten.t.default)[call_function]:Tensor(f32[4096, 1024]): Cannot find type promotion rule for op: aten.t.default" + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":1625 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0015", + "stacks":[] + }, + { + "message":{ + "markdown":"Skipped for fx.Node(aten.addmm.default)[call_function]:Tensor(f32[4096, 1024]): Cannot find type promotion rule for op: aten.addmm.default\n\n## Additional Message:\n\n## Function Signature\n### Function Signature _TypePromotionInterpreter.run_node\n- self: \n- node: fx.Node(aten.addmm.default)[call_function]:Tensor(f32[4096, 1024])\n## Return values\nTensor(f32[4096, 1024])", + "text":"Skipped for fx.Node(aten.addmm.default)[call_function]:Tensor(f32[4096, 1024]): Cannot find type promotion rule for op: aten.addmm.default" + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":1625 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0015", + "stacks":[] + }, + { + "message":{ + "markdown":"Skipped for fx.Node(aten.view.default)[call_function]:Tensor(f32[4, 1024, 1024]): Cannot find type promotion rule for op: aten.view.default\n\n## Additional Message:\n\n## Function Signature\n### Function Signature _TypePromotionInterpreter.run_node\n- self: \n- node: fx.Node(aten.view.default)[call_function]:Tensor(f32[4, 1024, 1024])\n## Return values\nTensor(f32[4, 1024, 1024])", + "text":"Skipped for fx.Node(aten.view.default)[call_function]:Tensor(f32[4, 1024, 1024]): Cannot find type promotion rule for op: aten.view.default" + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":1625 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0015", + "stacks":[] + }, + { + "message":{ + "markdown":"Skipped for fx.Node(aten.clone.default)[call_function]:Tensor(f32[4, 1024, 1024]): Cannot find type promotion rule for op: aten.clone.default\n\n## Additional Message:\n\n## Function Signature\n### Function Signature _TypePromotionInterpreter.run_node\n- self: \n- node: fx.Node(aten.clone.default)[call_function]:Tensor(f32[4, 1024, 1024])\n## Return values\nTensor(f32[4, 1024, 1024])", + "text":"Skipped for fx.Node(aten.clone.default)[call_function]:Tensor(f32[4, 1024, 1024]): Cannot find type promotion rule for op: aten.clone.default" + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":1625 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0015", + "stacks":[] + }, + { + "message":{ + "markdown":"Type promotion not needed for add_14. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature _TypePromotionInterpreter.run_node\n- self: \n- node: fx.Node(aten.add.Tensor)[call_function]:Tensor(f32[4, 1024, 1024])\nFound type promotion rule: ElementwiseTypePromotionRule('aten', 'add', [0, 1], [], ELEMENTWISE_TYPE_PROMOTION_KIND.DEFAULT)\nArgument add_13 is not promoted. Already torch.float32.\nArgument clone_21 is not promoted. Already torch.float32.\n## Return values\nTensor(f32[4, 1024, 1024])", + "text":"Type promotion not needed for add_14. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":1625 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0015", + "stacks":[] + }, + { + "message":{ + "markdown":"Skipped for fx.Node(aten.native_layer_norm.default)[call_function]:Tuple[length=3](\nTensor(f32[4, 1024, 1024]),\nTensor(f32[4, 1024, 1]),\nTensor(f32[4, 1024, 1]),\n): Cannot find type promotion rule for op: aten.native_layer_norm.default\n\n## Additional Message:\n\n## Function Signature\n### Function Signature _TypePromotionInterpreter.run_node\n- self: \n- node: fx.Node(aten.native_layer_norm.default)[call_function]:Tuple[length=3](\nTensor(f32[4, 1024, 1024]),\nTensor(f32[4, 1024, 1]),\nTensor(f32[4, 1024, 1]),\n)\n## Return values\nTuple[length=3](\nTensor(f32[4, 1024, 1024]),\nTensor(f32[4, 1024, 1]),\nTensor(f32[4, 1024, 1]),\n)", + "text":"Skipped for fx.Node(aten.native_layer_norm.default)[call_function]:Tuple[length=3](\nTensor(f32[4, 1024, 1024]),\nTensor(f32[4, 1024, 1]),\nTensor(f32[4, 1024, 1]),\n): Cannot find type promotion rule for op: aten.native_layer_norm.default" + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":1625 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0015", + "stacks":[] + }, + { + "message":{ + "markdown":"Skipped for fx.Node()[call_function]:Tensor(f32[4, 1024, 1024]): node.target is not OpOverload. Got type: \n\n## Additional Message:\n\n## Function Signature\n### Function Signature _TypePromotionInterpreter.run_node\n- self: \n- node: fx.Node()[call_function]:Tensor(f32[4, 1024, 1024])\n## Return values\nTensor(f32[4, 1024, 1024])", + "text":"Skipped for fx.Node()[call_function]:Tensor(f32[4, 1024, 1024]): node.target is not OpOverload. Got type: " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":1625 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0015", + "stacks":[] + }, + { + "message":{ + "markdown":"Skipped for fx.Node(aten.view.default)[call_function]:Tensor(f32[4096, 1024]): Cannot find type promotion rule for op: aten.view.default\n\n## Additional Message:\n\n## Function Signature\n### Function Signature _TypePromotionInterpreter.run_node\n- self: \n- node: fx.Node(aten.view.default)[call_function]:Tensor(f32[4096, 1024])\n## Return values\nTensor(f32[4096, 1024])", + "text":"Skipped for fx.Node(aten.view.default)[call_function]:Tensor(f32[4096, 1024]): Cannot find type promotion rule for op: aten.view.default" + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":1625 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0015", + "stacks":[] + }, + { + "message":{ + "markdown":"Skipped for fx.Node(aten.t.default)[call_function]:Tensor(f32[1024, 3072]): Cannot find type promotion rule for op: aten.t.default\n\n## Additional Message:\n\n## Function Signature\n### Function Signature _TypePromotionInterpreter.run_node\n- self: \n- node: fx.Node(aten.t.default)[call_function]:Tensor(f32[1024, 3072])\n## Return values\nTensor(f32[1024, 3072])", + "text":"Skipped for fx.Node(aten.t.default)[call_function]:Tensor(f32[1024, 3072]): Cannot find type promotion rule for op: aten.t.default" + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":1625 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0015", + "stacks":[] + }, + { + "message":{ + "markdown":"Skipped for fx.Node(aten.addmm.default)[call_function]:Tensor(f32[4096, 3072]): Cannot find type promotion rule for op: aten.addmm.default\n\n## Additional Message:\n\n## Function Signature\n### Function Signature _TypePromotionInterpreter.run_node\n- self: \n- node: fx.Node(aten.addmm.default)[call_function]:Tensor(f32[4096, 3072])\n## Return values\nTensor(f32[4096, 3072])", + "text":"Skipped for fx.Node(aten.addmm.default)[call_function]:Tensor(f32[4096, 3072]): Cannot find type promotion rule for op: aten.addmm.default" + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":1625 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0015", + "stacks":[] + }, + { + "message":{ + "markdown":"Skipped for fx.Node(aten.view.default)[call_function]:Tensor(f32[4, 1024, 3072]): Cannot find type promotion rule for op: aten.view.default\n\n## Additional Message:\n\n## Function Signature\n### Function Signature _TypePromotionInterpreter.run_node\n- self: \n- node: fx.Node(aten.view.default)[call_function]:Tensor(f32[4, 1024, 3072])\n## Return values\nTensor(f32[4, 1024, 3072])", + "text":"Skipped for fx.Node(aten.view.default)[call_function]:Tensor(f32[4, 1024, 3072]): Cannot find type promotion rule for op: aten.view.default" + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":1625 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0015", + "stacks":[] + }, + { + "message":{ + "markdown":"Skipped for fx.Node(aten.view.default)[call_function]:Tensor(f32[4, 1024, 3, 16, 64]): Cannot find type promotion rule for op: aten.view.default\n\n## Additional Message:\n\n## Function Signature\n### Function Signature _TypePromotionInterpreter.run_node\n- self: \n- node: fx.Node(aten.view.default)[call_function]:Tensor(f32[4, 1024, 3, 16, 64])\n## Return values\nTensor(f32[4, 1024, 3, 16, 64])", + "text":"Skipped for fx.Node(aten.view.default)[call_function]:Tensor(f32[4, 1024, 3, 16, 64]): Cannot find type promotion rule for op: aten.view.default" + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":1625 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0015", + "stacks":[] + }, + { + "message":{ + "markdown":"Skipped for fx.Node(aten.permute.default)[call_function]:Tensor(f32[3, 4, 16, 1024, 64]): Cannot find type promotion rule for op: aten.permute.default\n\n## Additional Message:\n\n## Function Signature\n### Function Signature _TypePromotionInterpreter.run_node\n- self: \n- node: fx.Node(aten.permute.default)[call_function]:Tensor(f32[3, 4, 16, 1024, 64])\n## Return values\nTensor(f32[3, 4, 16, 1024, 64])", + "text":"Skipped for fx.Node(aten.permute.default)[call_function]:Tensor(f32[3, 4, 16, 1024, 64]): Cannot find type promotion rule for op: aten.permute.default" + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":1625 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0015", + "stacks":[] + }, + { + "message":{ + "markdown":"Skipped for fx.Node(aten.unbind.int)[call_function]:List[length=3](\nTensor(f32[4, 16, 1024, 64]),\nTensor(f32[4, 16, 1024, 64]),\nTensor(f32[4, 16, 1024, 64]),\n): Cannot find type promotion rule for op: aten.unbind.int\n\n## Additional Message:\n\n## Function Signature\n### Function Signature _TypePromotionInterpreter.run_node\n- self: \n- node: fx.Node(aten.unbind.int)[call_function]:List[length=3](\nTensor(f32[4, 16, 1024, 64]),\nTensor(f32[4, 16, 1024, 64]),\nTensor(f32[4, 16, 1024, 64]),\n)\n## Return values\nList[length=3](\nTensor(f32[4, 16, 1024, 64]),\nTensor(f32[4, 16, 1024, 64]),\nTensor(f32[4, 16, 1024, 64]),\n)", + "text":"Skipped for fx.Node(aten.unbind.int)[call_function]:List[length=3](\nTensor(f32[4, 16, 1024, 64]),\nTensor(f32[4, 16, 1024, 64]),\nTensor(f32[4, 16, 1024, 64]),\n): Cannot find type promotion rule for op: aten.unbind.int" + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":1625 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0015", + "stacks":[] + }, + { + "message":{ + "markdown":"Skipped for fx.Node()[call_function]:Tensor(f32[4, 16, 1024, 64]): node.target is not OpOverload. Got type: \n\n## Additional Message:\n\n## Function Signature\n### Function Signature _TypePromotionInterpreter.run_node\n- self: \n- node: fx.Node()[call_function]:Tensor(f32[4, 16, 1024, 64])\n## Return values\nTensor(f32[4, 16, 1024, 64])", + "text":"Skipped for fx.Node()[call_function]:Tensor(f32[4, 16, 1024, 64]): node.target is not OpOverload. Got type: " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":1625 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0015", + "stacks":[] + }, + { + "message":{ + "markdown":"Skipped for fx.Node()[call_function]:Tensor(f32[4, 16, 1024, 64]): node.target is not OpOverload. Got type: \n\n## Additional Message:\n\n## Function Signature\n### Function Signature _TypePromotionInterpreter.run_node\n- self: \n- node: fx.Node()[call_function]:Tensor(f32[4, 16, 1024, 64])\n## Return values\nTensor(f32[4, 16, 1024, 64])", + "text":"Skipped for fx.Node()[call_function]:Tensor(f32[4, 16, 1024, 64]): node.target is not OpOverload. Got type: " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":1625 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0015", + "stacks":[] + }, + { + "message":{ + "markdown":"Skipped for fx.Node()[call_function]:Tensor(f32[4, 16, 1024, 64]): node.target is not OpOverload. Got type: \n\n## Additional Message:\n\n## Function Signature\n### Function Signature _TypePromotionInterpreter.run_node\n- self: \n- node: fx.Node()[call_function]:Tensor(f32[4, 16, 1024, 64])\n## Return values\nTensor(f32[4, 16, 1024, 64])", + "text":"Skipped for fx.Node()[call_function]:Tensor(f32[4, 16, 1024, 64]): node.target is not OpOverload. Got type: " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":1625 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0015", + "stacks":[] + }, + { + "message":{ + "markdown":"Skipped for fx.Node(aten._scaled_dot_product_efficient_attention.default)[call_function]:Tuple[length=4](\nTensor(f32[4, 16, 1024, 64]),\nTensor(f32[4, 16, 0]),\nTensor(i64[]),\nTensor(i64[]),\n): Cannot find type promotion rule for op: aten._scaled_dot_product_efficient_attention.default\n\n## Additional Message:\n\n## Function Signature\n### Function Signature _TypePromotionInterpreter.run_node\n- self: \n- node: fx.Node(aten._scaled_dot_product_efficient_attention.default)[call_function]:Tuple[length=4](\nTensor(f32[4, 16, 1024, 64]),\nTensor(f32[4, 16, 0]),\nTensor(i64[]),\nTensor(i64[]),\n)\n## Return values\nTuple[length=4](\nTensor(f32[4, 16, 1024, 64]),\nTensor(f32[4, 16, 0]),\nTensor(i64[]),\nTensor(i64[]),\n)", + "text":"Skipped for fx.Node(aten._scaled_dot_product_efficient_attention.default)[call_function]:Tuple[length=4](\nTensor(f32[4, 16, 1024, 64]),\nTensor(f32[4, 16, 0]),\nTensor(i64[]),\nTensor(i64[]),\n): Cannot find type promotion rule for op: aten._scaled_dot_product_efficient_attention.default" + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":1625 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0015", + "stacks":[] + }, + { + "message":{ + "markdown":"Skipped for fx.Node()[call_function]:Tensor(f32[4, 16, 1024, 64]): node.target is not OpOverload. Got type: \n\n## Additional Message:\n\n## Function Signature\n### Function Signature _TypePromotionInterpreter.run_node\n- self: \n- node: fx.Node()[call_function]:Tensor(f32[4, 16, 1024, 64])\n## Return values\nTensor(f32[4, 16, 1024, 64])", + "text":"Skipped for fx.Node()[call_function]:Tensor(f32[4, 16, 1024, 64]): node.target is not OpOverload. Got type: " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":1625 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0015", + "stacks":[] + }, + { + "message":{ + "markdown":"Skipped for fx.Node(aten.transpose.int)[call_function]:Tensor(f32[4, 1024, 16, 64]): Cannot find type promotion rule for op: aten.transpose.int\n\n## Additional Message:\n\n## Function Signature\n### Function Signature _TypePromotionInterpreter.run_node\n- self: \n- node: fx.Node(aten.transpose.int)[call_function]:Tensor(f32[4, 1024, 16, 64])\n## Return values\nTensor(f32[4, 1024, 16, 64])", + "text":"Skipped for fx.Node(aten.transpose.int)[call_function]:Tensor(f32[4, 1024, 16, 64]): Cannot find type promotion rule for op: aten.transpose.int" + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":1625 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0015", + "stacks":[] + }, + { + "message":{ + "markdown":"Skipped for fx.Node(aten.view.default)[call_function]:Tensor(f32[4, 1024, 1024]): Cannot find type promotion rule for op: aten.view.default\n\n## Additional Message:\n\n## Function Signature\n### Function Signature _TypePromotionInterpreter.run_node\n- self: \n- node: fx.Node(aten.view.default)[call_function]:Tensor(f32[4, 1024, 1024])\n## Return values\nTensor(f32[4, 1024, 1024])", + "text":"Skipped for fx.Node(aten.view.default)[call_function]:Tensor(f32[4, 1024, 1024]): Cannot find type promotion rule for op: aten.view.default" + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":1625 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0015", + "stacks":[] + }, + { + "message":{ + "markdown":"Skipped for fx.Node(aten.view.default)[call_function]:Tensor(f32[4096, 1024]): Cannot find type promotion rule for op: aten.view.default\n\n## Additional Message:\n\n## Function Signature\n### Function Signature _TypePromotionInterpreter.run_node\n- self: \n- node: fx.Node(aten.view.default)[call_function]:Tensor(f32[4096, 1024])\n## Return values\nTensor(f32[4096, 1024])", + "text":"Skipped for fx.Node(aten.view.default)[call_function]:Tensor(f32[4096, 1024]): Cannot find type promotion rule for op: aten.view.default" + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":1625 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0015", + "stacks":[] + }, + { + "message":{ + "markdown":"Skipped for fx.Node(aten.t.default)[call_function]:Tensor(f32[1024, 1024]): Cannot find type promotion rule for op: aten.t.default\n\n## Additional Message:\n\n## Function Signature\n### Function Signature _TypePromotionInterpreter.run_node\n- self: \n- node: fx.Node(aten.t.default)[call_function]:Tensor(f32[1024, 1024])\n## Return values\nTensor(f32[1024, 1024])", + "text":"Skipped for fx.Node(aten.t.default)[call_function]:Tensor(f32[1024, 1024]): Cannot find type promotion rule for op: aten.t.default" + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":1625 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0015", + "stacks":[] + }, + { + "message":{ + "markdown":"Skipped for fx.Node(aten.addmm.default)[call_function]:Tensor(f32[4096, 1024]): Cannot find type promotion rule for op: aten.addmm.default\n\n## Additional Message:\n\n## Function Signature\n### Function Signature _TypePromotionInterpreter.run_node\n- self: \n- node: fx.Node(aten.addmm.default)[call_function]:Tensor(f32[4096, 1024])\n## Return values\nTensor(f32[4096, 1024])", + "text":"Skipped for fx.Node(aten.addmm.default)[call_function]:Tensor(f32[4096, 1024]): Cannot find type promotion rule for op: aten.addmm.default" + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":1625 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0015", + "stacks":[] + }, + { + "message":{ + "markdown":"Skipped for fx.Node(aten.view.default)[call_function]:Tensor(f32[4, 1024, 1024]): Cannot find type promotion rule for op: aten.view.default\n\n## Additional Message:\n\n## Function Signature\n### Function Signature _TypePromotionInterpreter.run_node\n- self: \n- node: fx.Node(aten.view.default)[call_function]:Tensor(f32[4, 1024, 1024])\n## Return values\nTensor(f32[4, 1024, 1024])", + "text":"Skipped for fx.Node(aten.view.default)[call_function]:Tensor(f32[4, 1024, 1024]): Cannot find type promotion rule for op: aten.view.default" + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":1625 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0015", + "stacks":[] + }, + { + "message":{ + "markdown":"Skipped for fx.Node(aten.clone.default)[call_function]:Tensor(f32[4, 1024, 1024]): Cannot find type promotion rule for op: aten.clone.default\n\n## Additional Message:\n\n## Function Signature\n### Function Signature _TypePromotionInterpreter.run_node\n- self: \n- node: fx.Node(aten.clone.default)[call_function]:Tensor(f32[4, 1024, 1024])\n## Return values\nTensor(f32[4, 1024, 1024])", + "text":"Skipped for fx.Node(aten.clone.default)[call_function]:Tensor(f32[4, 1024, 1024]): Cannot find type promotion rule for op: aten.clone.default" + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":1625 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0015", + "stacks":[] + }, + { + "message":{ + "markdown":"Type promotion not needed for add_15. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature _TypePromotionInterpreter.run_node\n- self: \n- node: fx.Node(aten.add.Tensor)[call_function]:Tensor(f32[4, 1024, 1024])\nFound type promotion rule: ElementwiseTypePromotionRule('aten', 'add', [0, 1], [], ELEMENTWISE_TYPE_PROMOTION_KIND.DEFAULT)\nArgument add_14 is not promoted. Already torch.float32.\nArgument clone_22 is not promoted. Already torch.float32.\n## Return values\nTensor(f32[4, 1024, 1024])", + "text":"Type promotion not needed for add_15. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":1625 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0015", + "stacks":[] + }, + { + "message":{ + "markdown":"Skipped for fx.Node(aten.native_layer_norm.default)[call_function]:Tuple[length=3](\nTensor(f32[4, 1024, 1024]),\nTensor(f32[4, 1024, 1]),\nTensor(f32[4, 1024, 1]),\n): Cannot find type promotion rule for op: aten.native_layer_norm.default\n\n## Additional Message:\n\n## Function Signature\n### Function Signature _TypePromotionInterpreter.run_node\n- self: \n- node: fx.Node(aten.native_layer_norm.default)[call_function]:Tuple[length=3](\nTensor(f32[4, 1024, 1024]),\nTensor(f32[4, 1024, 1]),\nTensor(f32[4, 1024, 1]),\n)\n## Return values\nTuple[length=3](\nTensor(f32[4, 1024, 1024]),\nTensor(f32[4, 1024, 1]),\nTensor(f32[4, 1024, 1]),\n)", + "text":"Skipped for fx.Node(aten.native_layer_norm.default)[call_function]:Tuple[length=3](\nTensor(f32[4, 1024, 1024]),\nTensor(f32[4, 1024, 1]),\nTensor(f32[4, 1024, 1]),\n): Cannot find type promotion rule for op: aten.native_layer_norm.default" + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":1625 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0015", + "stacks":[] + }, + { + "message":{ + "markdown":"Skipped for fx.Node()[call_function]:Tensor(f32[4, 1024, 1024]): node.target is not OpOverload. Got type: \n\n## Additional Message:\n\n## Function Signature\n### Function Signature _TypePromotionInterpreter.run_node\n- self: \n- node: fx.Node()[call_function]:Tensor(f32[4, 1024, 1024])\n## Return values\nTensor(f32[4, 1024, 1024])", + "text":"Skipped for fx.Node()[call_function]:Tensor(f32[4, 1024, 1024]): node.target is not OpOverload. Got type: " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":1625 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0015", + "stacks":[] + }, + { + "message":{ + "markdown":"Skipped for fx.Node(aten.view.default)[call_function]:Tensor(f32[4096, 1024]): Cannot find type promotion rule for op: aten.view.default\n\n## Additional Message:\n\n## Function Signature\n### Function Signature _TypePromotionInterpreter.run_node\n- self: \n- node: fx.Node(aten.view.default)[call_function]:Tensor(f32[4096, 1024])\n## Return values\nTensor(f32[4096, 1024])", + "text":"Skipped for fx.Node(aten.view.default)[call_function]:Tensor(f32[4096, 1024]): Cannot find type promotion rule for op: aten.view.default" + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":1625 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0015", + "stacks":[] + }, + { + "message":{ + "markdown":"Skipped for fx.Node(aten.t.default)[call_function]:Tensor(f32[1024, 4096]): Cannot find type promotion rule for op: aten.t.default\n\n## Additional Message:\n\n## Function Signature\n### Function Signature _TypePromotionInterpreter.run_node\n- self: \n- node: fx.Node(aten.t.default)[call_function]:Tensor(f32[1024, 4096])\n## Return values\nTensor(f32[1024, 4096])", + "text":"Skipped for fx.Node(aten.t.default)[call_function]:Tensor(f32[1024, 4096]): Cannot find type promotion rule for op: aten.t.default" + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":1625 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0015", + "stacks":[] + }, + { + "message":{ + "markdown":"Skipped for fx.Node(aten.addmm.default)[call_function]:Tensor(f32[4096, 4096]): Cannot find type promotion rule for op: aten.addmm.default\n\n## Additional Message:\n\n## Function Signature\n### Function Signature _TypePromotionInterpreter.run_node\n- self: \n- node: fx.Node(aten.addmm.default)[call_function]:Tensor(f32[4096, 4096])\n## Return values\nTensor(f32[4096, 4096])", + "text":"Skipped for fx.Node(aten.addmm.default)[call_function]:Tensor(f32[4096, 4096]): Cannot find type promotion rule for op: aten.addmm.default" + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":1625 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0015", + "stacks":[] + }, + { + "message":{ + "markdown":"Skipped for fx.Node(aten.view.default)[call_function]:Tensor(f32[4, 1024, 4096]): Cannot find type promotion rule for op: aten.view.default\n\n## Additional Message:\n\n## Function Signature\n### Function Signature _TypePromotionInterpreter.run_node\n- self: \n- node: fx.Node(aten.view.default)[call_function]:Tensor(f32[4, 1024, 4096])\n## Return values\nTensor(f32[4, 1024, 4096])", + "text":"Skipped for fx.Node(aten.view.default)[call_function]:Tensor(f32[4, 1024, 4096]): Cannot find type promotion rule for op: aten.view.default" + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":1625 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0015", + "stacks":[] + }, + { + "message":{ + "markdown":"Type promotion not needed for gelu_7. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature _TypePromotionInterpreter.run_node\n- self: \n- node: fx.Node(aten.gelu.default)[call_function]:Tensor(f32[4, 1024, 4096])\nFound type promotion rule: ElementwiseTypePromotionRule('aten', 'gelu', [0], [], ELEMENTWISE_TYPE_PROMOTION_KIND.DEFAULT)\nArgument view_78 is not promoted. Already torch.float32.\nArgument tanh is not promoted. Not mentioned by type promotion rule.\n## Return values\nTensor(f32[4, 1024, 4096])", + "text":"Type promotion not needed for gelu_7. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":1625 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0015", + "stacks":[] + }, + { + "message":{ + "markdown":"Skipped for fx.Node(aten.clone.default)[call_function]:Tensor(f32[4, 1024, 4096]): Cannot find type promotion rule for op: aten.clone.default\n\n## Additional Message:\n\n## Function Signature\n### Function Signature _TypePromotionInterpreter.run_node\n- self: \n- node: fx.Node(aten.clone.default)[call_function]:Tensor(f32[4, 1024, 4096])\n## Return values\nTensor(f32[4, 1024, 4096])", + "text":"Skipped for fx.Node(aten.clone.default)[call_function]:Tensor(f32[4, 1024, 4096]): Cannot find type promotion rule for op: aten.clone.default" + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":1625 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0015", + "stacks":[] + }, + { + "message":{ + "markdown":"Skipped for fx.Node(aten.view.default)[call_function]:Tensor(f32[4096, 4096]): Cannot find type promotion rule for op: aten.view.default\n\n## Additional Message:\n\n## Function Signature\n### Function Signature _TypePromotionInterpreter.run_node\n- self: \n- node: fx.Node(aten.view.default)[call_function]:Tensor(f32[4096, 4096])\n## Return values\nTensor(f32[4096, 4096])", + "text":"Skipped for fx.Node(aten.view.default)[call_function]:Tensor(f32[4096, 4096]): Cannot find type promotion rule for op: aten.view.default" + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":1625 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0015", + "stacks":[] + }, + { + "message":{ + "markdown":"Skipped for fx.Node(aten.t.default)[call_function]:Tensor(f32[4096, 1024]): Cannot find type promotion rule for op: aten.t.default\n\n## Additional Message:\n\n## Function Signature\n### Function Signature _TypePromotionInterpreter.run_node\n- self: \n- node: fx.Node(aten.t.default)[call_function]:Tensor(f32[4096, 1024])\n## Return values\nTensor(f32[4096, 1024])", + "text":"Skipped for fx.Node(aten.t.default)[call_function]:Tensor(f32[4096, 1024]): Cannot find type promotion rule for op: aten.t.default" + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":1625 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0015", + "stacks":[] + }, + { + "message":{ + "markdown":"Skipped for fx.Node(aten.addmm.default)[call_function]:Tensor(f32[4096, 1024]): Cannot find type promotion rule for op: aten.addmm.default\n\n## Additional Message:\n\n## Function Signature\n### Function Signature _TypePromotionInterpreter.run_node\n- self: \n- node: fx.Node(aten.addmm.default)[call_function]:Tensor(f32[4096, 1024])\n## Return values\nTensor(f32[4096, 1024])", + "text":"Skipped for fx.Node(aten.addmm.default)[call_function]:Tensor(f32[4096, 1024]): Cannot find type promotion rule for op: aten.addmm.default" + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":1625 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0015", + "stacks":[] + }, + { + "message":{ + "markdown":"Skipped for fx.Node(aten.view.default)[call_function]:Tensor(f32[4, 1024, 1024]): Cannot find type promotion rule for op: aten.view.default\n\n## Additional Message:\n\n## Function Signature\n### Function Signature _TypePromotionInterpreter.run_node\n- self: \n- node: fx.Node(aten.view.default)[call_function]:Tensor(f32[4, 1024, 1024])\n## Return values\nTensor(f32[4, 1024, 1024])", + "text":"Skipped for fx.Node(aten.view.default)[call_function]:Tensor(f32[4, 1024, 1024]): Cannot find type promotion rule for op: aten.view.default" + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":1625 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0015", + "stacks":[] + }, + { + "message":{ + "markdown":"Skipped for fx.Node(aten.clone.default)[call_function]:Tensor(f32[4, 1024, 1024]): Cannot find type promotion rule for op: aten.clone.default\n\n## Additional Message:\n\n## Function Signature\n### Function Signature _TypePromotionInterpreter.run_node\n- self: \n- node: fx.Node(aten.clone.default)[call_function]:Tensor(f32[4, 1024, 1024])\n## Return values\nTensor(f32[4, 1024, 1024])", + "text":"Skipped for fx.Node(aten.clone.default)[call_function]:Tensor(f32[4, 1024, 1024]): Cannot find type promotion rule for op: aten.clone.default" + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":1625 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0015", + "stacks":[] + }, + { + "message":{ + "markdown":"Type promotion not needed for add_16. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature _TypePromotionInterpreter.run_node\n- self: \n- node: fx.Node(aten.add.Tensor)[call_function]:Tensor(f32[4, 1024, 1024])\nFound type promotion rule: ElementwiseTypePromotionRule('aten', 'add', [0, 1], [], ELEMENTWISE_TYPE_PROMOTION_KIND.DEFAULT)\nArgument add_15 is not promoted. Already torch.float32.\nArgument clone_24 is not promoted. Already torch.float32.\n## Return values\nTensor(f32[4, 1024, 1024])", + "text":"Type promotion not needed for add_16. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":1625 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0015", + "stacks":[] + }, + { + "message":{ + "markdown":"Skipped for fx.Node(aten.native_layer_norm.default)[call_function]:Tuple[length=3](\nTensor(f32[4, 1024, 1024]),\nTensor(f32[4, 1024, 1]),\nTensor(f32[4, 1024, 1]),\n): Cannot find type promotion rule for op: aten.native_layer_norm.default\n\n## Additional Message:\n\n## Function Signature\n### Function Signature _TypePromotionInterpreter.run_node\n- self: \n- node: fx.Node(aten.native_layer_norm.default)[call_function]:Tuple[length=3](\nTensor(f32[4, 1024, 1024]),\nTensor(f32[4, 1024, 1]),\nTensor(f32[4, 1024, 1]),\n)\n## Return values\nTuple[length=3](\nTensor(f32[4, 1024, 1024]),\nTensor(f32[4, 1024, 1]),\nTensor(f32[4, 1024, 1]),\n)", + "text":"Skipped for fx.Node(aten.native_layer_norm.default)[call_function]:Tuple[length=3](\nTensor(f32[4, 1024, 1024]),\nTensor(f32[4, 1024, 1]),\nTensor(f32[4, 1024, 1]),\n): Cannot find type promotion rule for op: aten.native_layer_norm.default" + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":1625 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0015", + "stacks":[] + }, + { + "message":{ + "markdown":"Skipped for fx.Node()[call_function]:Tensor(f32[4, 1024, 1024]): node.target is not OpOverload. Got type: \n\n## Additional Message:\n\n## Function Signature\n### Function Signature _TypePromotionInterpreter.run_node\n- self: \n- node: fx.Node()[call_function]:Tensor(f32[4, 1024, 1024])\n## Return values\nTensor(f32[4, 1024, 1024])", + "text":"Skipped for fx.Node()[call_function]:Tensor(f32[4, 1024, 1024]): node.target is not OpOverload. Got type: " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":1625 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0015", + "stacks":[] + }, + { + "message":{ + "markdown":"Skipped for fx.Node(aten.view.default)[call_function]:Tensor(f32[4096, 1024]): Cannot find type promotion rule for op: aten.view.default\n\n## Additional Message:\n\n## Function Signature\n### Function Signature _TypePromotionInterpreter.run_node\n- self: \n- node: fx.Node(aten.view.default)[call_function]:Tensor(f32[4096, 1024])\n## Return values\nTensor(f32[4096, 1024])", + "text":"Skipped for fx.Node(aten.view.default)[call_function]:Tensor(f32[4096, 1024]): Cannot find type promotion rule for op: aten.view.default" + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":1625 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0015", + "stacks":[] + }, + { + "message":{ + "markdown":"Skipped for fx.Node(aten.t.default)[call_function]:Tensor(f32[1024, 3072]): Cannot find type promotion rule for op: aten.t.default\n\n## Additional Message:\n\n## Function Signature\n### Function Signature _TypePromotionInterpreter.run_node\n- self: \n- node: fx.Node(aten.t.default)[call_function]:Tensor(f32[1024, 3072])\n## Return values\nTensor(f32[1024, 3072])", + "text":"Skipped for fx.Node(aten.t.default)[call_function]:Tensor(f32[1024, 3072]): Cannot find type promotion rule for op: aten.t.default" + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":1625 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0015", + "stacks":[] + }, + { + "message":{ + "markdown":"Skipped for fx.Node(aten.addmm.default)[call_function]:Tensor(f32[4096, 3072]): Cannot find type promotion rule for op: aten.addmm.default\n\n## Additional Message:\n\n## Function Signature\n### Function Signature _TypePromotionInterpreter.run_node\n- self: \n- node: fx.Node(aten.addmm.default)[call_function]:Tensor(f32[4096, 3072])\n## Return values\nTensor(f32[4096, 3072])", + "text":"Skipped for fx.Node(aten.addmm.default)[call_function]:Tensor(f32[4096, 3072]): Cannot find type promotion rule for op: aten.addmm.default" + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":1625 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0015", + "stacks":[] + }, + { + "message":{ + "markdown":"Skipped for fx.Node(aten.view.default)[call_function]:Tensor(f32[4, 1024, 3072]): Cannot find type promotion rule for op: aten.view.default\n\n## Additional Message:\n\n## Function Signature\n### Function Signature _TypePromotionInterpreter.run_node\n- self: \n- node: fx.Node(aten.view.default)[call_function]:Tensor(f32[4, 1024, 3072])\n## Return values\nTensor(f32[4, 1024, 3072])", + "text":"Skipped for fx.Node(aten.view.default)[call_function]:Tensor(f32[4, 1024, 3072]): Cannot find type promotion rule for op: aten.view.default" + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":1625 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0015", + "stacks":[] + }, + { + "message":{ + "markdown":"Skipped for fx.Node(aten.view.default)[call_function]:Tensor(f32[4, 1024, 3, 16, 64]): Cannot find type promotion rule for op: aten.view.default\n\n## Additional Message:\n\n## Function Signature\n### Function Signature _TypePromotionInterpreter.run_node\n- self: \n- node: fx.Node(aten.view.default)[call_function]:Tensor(f32[4, 1024, 3, 16, 64])\n## Return values\nTensor(f32[4, 1024, 3, 16, 64])", + "text":"Skipped for fx.Node(aten.view.default)[call_function]:Tensor(f32[4, 1024, 3, 16, 64]): Cannot find type promotion rule for op: aten.view.default" + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":1625 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0015", + "stacks":[] + }, + { + "message":{ + "markdown":"Skipped for fx.Node(aten.permute.default)[call_function]:Tensor(f32[3, 4, 16, 1024, 64]): Cannot find type promotion rule for op: aten.permute.default\n\n## Additional Message:\n\n## Function Signature\n### Function Signature _TypePromotionInterpreter.run_node\n- self: \n- node: fx.Node(aten.permute.default)[call_function]:Tensor(f32[3, 4, 16, 1024, 64])\n## Return values\nTensor(f32[3, 4, 16, 1024, 64])", + "text":"Skipped for fx.Node(aten.permute.default)[call_function]:Tensor(f32[3, 4, 16, 1024, 64]): Cannot find type promotion rule for op: aten.permute.default" + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":1625 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0015", + "stacks":[] + }, + { + "message":{ + "markdown":"Skipped for fx.Node(aten.unbind.int)[call_function]:List[length=3](\nTensor(f32[4, 16, 1024, 64]),\nTensor(f32[4, 16, 1024, 64]),\nTensor(f32[4, 16, 1024, 64]),\n): Cannot find type promotion rule for op: aten.unbind.int\n\n## Additional Message:\n\n## Function Signature\n### Function Signature _TypePromotionInterpreter.run_node\n- self: \n- node: fx.Node(aten.unbind.int)[call_function]:List[length=3](\nTensor(f32[4, 16, 1024, 64]),\nTensor(f32[4, 16, 1024, 64]),\nTensor(f32[4, 16, 1024, 64]),\n)\n## Return values\nList[length=3](\nTensor(f32[4, 16, 1024, 64]),\nTensor(f32[4, 16, 1024, 64]),\nTensor(f32[4, 16, 1024, 64]),\n)", + "text":"Skipped for fx.Node(aten.unbind.int)[call_function]:List[length=3](\nTensor(f32[4, 16, 1024, 64]),\nTensor(f32[4, 16, 1024, 64]),\nTensor(f32[4, 16, 1024, 64]),\n): Cannot find type promotion rule for op: aten.unbind.int" + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":1625 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0015", + "stacks":[] + }, + { + "message":{ + "markdown":"Skipped for fx.Node()[call_function]:Tensor(f32[4, 16, 1024, 64]): node.target is not OpOverload. Got type: \n\n## Additional Message:\n\n## Function Signature\n### Function Signature _TypePromotionInterpreter.run_node\n- self: \n- node: fx.Node()[call_function]:Tensor(f32[4, 16, 1024, 64])\n## Return values\nTensor(f32[4, 16, 1024, 64])", + "text":"Skipped for fx.Node()[call_function]:Tensor(f32[4, 16, 1024, 64]): node.target is not OpOverload. Got type: " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":1625 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0015", + "stacks":[] + }, + { + "message":{ + "markdown":"Skipped for fx.Node()[call_function]:Tensor(f32[4, 16, 1024, 64]): node.target is not OpOverload. Got type: \n\n## Additional Message:\n\n## Function Signature\n### Function Signature _TypePromotionInterpreter.run_node\n- self: \n- node: fx.Node()[call_function]:Tensor(f32[4, 16, 1024, 64])\n## Return values\nTensor(f32[4, 16, 1024, 64])", + "text":"Skipped for fx.Node()[call_function]:Tensor(f32[4, 16, 1024, 64]): node.target is not OpOverload. Got type: " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":1625 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0015", + "stacks":[] + }, + { + "message":{ + "markdown":"Skipped for fx.Node()[call_function]:Tensor(f32[4, 16, 1024, 64]): node.target is not OpOverload. Got type: \n\n## Additional Message:\n\n## Function Signature\n### Function Signature _TypePromotionInterpreter.run_node\n- self: \n- node: fx.Node()[call_function]:Tensor(f32[4, 16, 1024, 64])\n## Return values\nTensor(f32[4, 16, 1024, 64])", + "text":"Skipped for fx.Node()[call_function]:Tensor(f32[4, 16, 1024, 64]): node.target is not OpOverload. Got type: " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":1625 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0015", + "stacks":[] + }, + { + "message":{ + "markdown":"Skipped for fx.Node(aten._scaled_dot_product_efficient_attention.default)[call_function]:Tuple[length=4](\nTensor(f32[4, 16, 1024, 64]),\nTensor(f32[4, 16, 0]),\nTensor(i64[]),\nTensor(i64[]),\n): Cannot find type promotion rule for op: aten._scaled_dot_product_efficient_attention.default\n\n## Additional Message:\n\n## Function Signature\n### Function Signature _TypePromotionInterpreter.run_node\n- self: \n- node: fx.Node(aten._scaled_dot_product_efficient_attention.default)[call_function]:Tuple[length=4](\nTensor(f32[4, 16, 1024, 64]),\nTensor(f32[4, 16, 0]),\nTensor(i64[]),\nTensor(i64[]),\n)\n## Return values\nTuple[length=4](\nTensor(f32[4, 16, 1024, 64]),\nTensor(f32[4, 16, 0]),\nTensor(i64[]),\nTensor(i64[]),\n)", + "text":"Skipped for fx.Node(aten._scaled_dot_product_efficient_attention.default)[call_function]:Tuple[length=4](\nTensor(f32[4, 16, 1024, 64]),\nTensor(f32[4, 16, 0]),\nTensor(i64[]),\nTensor(i64[]),\n): Cannot find type promotion rule for op: aten._scaled_dot_product_efficient_attention.default" + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":1625 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0015", + "stacks":[] + }, + { + "message":{ + "markdown":"Skipped for fx.Node()[call_function]:Tensor(f32[4, 16, 1024, 64]): node.target is not OpOverload. Got type: \n\n## Additional Message:\n\n## Function Signature\n### Function Signature _TypePromotionInterpreter.run_node\n- self: \n- node: fx.Node()[call_function]:Tensor(f32[4, 16, 1024, 64])\n## Return values\nTensor(f32[4, 16, 1024, 64])", + "text":"Skipped for fx.Node()[call_function]:Tensor(f32[4, 16, 1024, 64]): node.target is not OpOverload. Got type: " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":1625 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0015", + "stacks":[] + }, + { + "message":{ + "markdown":"Skipped for fx.Node(aten.transpose.int)[call_function]:Tensor(f32[4, 1024, 16, 64]): Cannot find type promotion rule for op: aten.transpose.int\n\n## Additional Message:\n\n## Function Signature\n### Function Signature _TypePromotionInterpreter.run_node\n- self: \n- node: fx.Node(aten.transpose.int)[call_function]:Tensor(f32[4, 1024, 16, 64])\n## Return values\nTensor(f32[4, 1024, 16, 64])", + "text":"Skipped for fx.Node(aten.transpose.int)[call_function]:Tensor(f32[4, 1024, 16, 64]): Cannot find type promotion rule for op: aten.transpose.int" + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":1625 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0015", + "stacks":[] + }, + { + "message":{ + "markdown":"Skipped for fx.Node(aten.view.default)[call_function]:Tensor(f32[4, 1024, 1024]): Cannot find type promotion rule for op: aten.view.default\n\n## Additional Message:\n\n## Function Signature\n### Function Signature _TypePromotionInterpreter.run_node\n- self: \n- node: fx.Node(aten.view.default)[call_function]:Tensor(f32[4, 1024, 1024])\n## Return values\nTensor(f32[4, 1024, 1024])", + "text":"Skipped for fx.Node(aten.view.default)[call_function]:Tensor(f32[4, 1024, 1024]): Cannot find type promotion rule for op: aten.view.default" + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":1625 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0015", + "stacks":[] + }, + { + "message":{ + "markdown":"Skipped for fx.Node(aten.view.default)[call_function]:Tensor(f32[4096, 1024]): Cannot find type promotion rule for op: aten.view.default\n\n## Additional Message:\n\n## Function Signature\n### Function Signature _TypePromotionInterpreter.run_node\n- self: \n- node: fx.Node(aten.view.default)[call_function]:Tensor(f32[4096, 1024])\n## Return values\nTensor(f32[4096, 1024])", + "text":"Skipped for fx.Node(aten.view.default)[call_function]:Tensor(f32[4096, 1024]): Cannot find type promotion rule for op: aten.view.default" + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":1625 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0015", + "stacks":[] + }, + { + "message":{ + "markdown":"Skipped for fx.Node(aten.t.default)[call_function]:Tensor(f32[1024, 1024]): Cannot find type promotion rule for op: aten.t.default\n\n## Additional Message:\n\n## Function Signature\n### Function Signature _TypePromotionInterpreter.run_node\n- self: \n- node: fx.Node(aten.t.default)[call_function]:Tensor(f32[1024, 1024])\n## Return values\nTensor(f32[1024, 1024])", + "text":"Skipped for fx.Node(aten.t.default)[call_function]:Tensor(f32[1024, 1024]): Cannot find type promotion rule for op: aten.t.default" + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":1625 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0015", + "stacks":[] + }, + { + "message":{ + "markdown":"Skipped for fx.Node(aten.addmm.default)[call_function]:Tensor(f32[4096, 1024]): Cannot find type promotion rule for op: aten.addmm.default\n\n## Additional Message:\n\n## Function Signature\n### Function Signature _TypePromotionInterpreter.run_node\n- self: \n- node: fx.Node(aten.addmm.default)[call_function]:Tensor(f32[4096, 1024])\n## Return values\nTensor(f32[4096, 1024])", + "text":"Skipped for fx.Node(aten.addmm.default)[call_function]:Tensor(f32[4096, 1024]): Cannot find type promotion rule for op: aten.addmm.default" + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":1625 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0015", + "stacks":[] + }, + { + "message":{ + "markdown":"Skipped for fx.Node(aten.view.default)[call_function]:Tensor(f32[4, 1024, 1024]): Cannot find type promotion rule for op: aten.view.default\n\n## Additional Message:\n\n## Function Signature\n### Function Signature _TypePromotionInterpreter.run_node\n- self: \n- node: fx.Node(aten.view.default)[call_function]:Tensor(f32[4, 1024, 1024])\n## Return values\nTensor(f32[4, 1024, 1024])", + "text":"Skipped for fx.Node(aten.view.default)[call_function]:Tensor(f32[4, 1024, 1024]): Cannot find type promotion rule for op: aten.view.default" + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":1625 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0015", + "stacks":[] + }, + { + "message":{ + "markdown":"Skipped for fx.Node(aten.clone.default)[call_function]:Tensor(f32[4, 1024, 1024]): Cannot find type promotion rule for op: aten.clone.default\n\n## Additional Message:\n\n## Function Signature\n### Function Signature _TypePromotionInterpreter.run_node\n- self: \n- node: fx.Node(aten.clone.default)[call_function]:Tensor(f32[4, 1024, 1024])\n## Return values\nTensor(f32[4, 1024, 1024])", + "text":"Skipped for fx.Node(aten.clone.default)[call_function]:Tensor(f32[4, 1024, 1024]): Cannot find type promotion rule for op: aten.clone.default" + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":1625 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0015", + "stacks":[] + }, + { + "message":{ + "markdown":"Type promotion not needed for add_17. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature _TypePromotionInterpreter.run_node\n- self: \n- node: fx.Node(aten.add.Tensor)[call_function]:Tensor(f32[4, 1024, 1024])\nFound type promotion rule: ElementwiseTypePromotionRule('aten', 'add', [0, 1], [], ELEMENTWISE_TYPE_PROMOTION_KIND.DEFAULT)\nArgument add_16 is not promoted. Already torch.float32.\nArgument clone_25 is not promoted. Already torch.float32.\n## Return values\nTensor(f32[4, 1024, 1024])", + "text":"Type promotion not needed for add_17. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":1625 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0015", + "stacks":[] + }, + { + "message":{ + "markdown":"Skipped for fx.Node(aten.native_layer_norm.default)[call_function]:Tuple[length=3](\nTensor(f32[4, 1024, 1024]),\nTensor(f32[4, 1024, 1]),\nTensor(f32[4, 1024, 1]),\n): Cannot find type promotion rule for op: aten.native_layer_norm.default\n\n## Additional Message:\n\n## Function Signature\n### Function Signature _TypePromotionInterpreter.run_node\n- self: \n- node: fx.Node(aten.native_layer_norm.default)[call_function]:Tuple[length=3](\nTensor(f32[4, 1024, 1024]),\nTensor(f32[4, 1024, 1]),\nTensor(f32[4, 1024, 1]),\n)\n## Return values\nTuple[length=3](\nTensor(f32[4, 1024, 1024]),\nTensor(f32[4, 1024, 1]),\nTensor(f32[4, 1024, 1]),\n)", + "text":"Skipped for fx.Node(aten.native_layer_norm.default)[call_function]:Tuple[length=3](\nTensor(f32[4, 1024, 1024]),\nTensor(f32[4, 1024, 1]),\nTensor(f32[4, 1024, 1]),\n): Cannot find type promotion rule for op: aten.native_layer_norm.default" + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":1625 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0015", + "stacks":[] + }, + { + "message":{ + "markdown":"Skipped for fx.Node()[call_function]:Tensor(f32[4, 1024, 1024]): node.target is not OpOverload. Got type: \n\n## Additional Message:\n\n## Function Signature\n### Function Signature _TypePromotionInterpreter.run_node\n- self: \n- node: fx.Node()[call_function]:Tensor(f32[4, 1024, 1024])\n## Return values\nTensor(f32[4, 1024, 1024])", + "text":"Skipped for fx.Node()[call_function]:Tensor(f32[4, 1024, 1024]): node.target is not OpOverload. Got type: " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":1625 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0015", + "stacks":[] + }, + { + "message":{ + "markdown":"Skipped for fx.Node(aten.view.default)[call_function]:Tensor(f32[4096, 1024]): Cannot find type promotion rule for op: aten.view.default\n\n## Additional Message:\n\n## Function Signature\n### Function Signature _TypePromotionInterpreter.run_node\n- self: \n- node: fx.Node(aten.view.default)[call_function]:Tensor(f32[4096, 1024])\n## Return values\nTensor(f32[4096, 1024])", + "text":"Skipped for fx.Node(aten.view.default)[call_function]:Tensor(f32[4096, 1024]): Cannot find type promotion rule for op: aten.view.default" + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":1625 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0015", + "stacks":[] + }, + { + "message":{ + "markdown":"Skipped for fx.Node(aten.t.default)[call_function]:Tensor(f32[1024, 4096]): Cannot find type promotion rule for op: aten.t.default\n\n## Additional Message:\n\n## Function Signature\n### Function Signature _TypePromotionInterpreter.run_node\n- self: \n- node: fx.Node(aten.t.default)[call_function]:Tensor(f32[1024, 4096])\n## Return values\nTensor(f32[1024, 4096])", + "text":"Skipped for fx.Node(aten.t.default)[call_function]:Tensor(f32[1024, 4096]): Cannot find type promotion rule for op: aten.t.default" + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":1625 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0015", + "stacks":[] + }, + { + "message":{ + "markdown":"Skipped for fx.Node(aten.addmm.default)[call_function]:Tensor(f32[4096, 4096]): Cannot find type promotion rule for op: aten.addmm.default\n\n## Additional Message:\n\n## Function Signature\n### Function Signature _TypePromotionInterpreter.run_node\n- self: \n- node: fx.Node(aten.addmm.default)[call_function]:Tensor(f32[4096, 4096])\n## Return values\nTensor(f32[4096, 4096])", + "text":"Skipped for fx.Node(aten.addmm.default)[call_function]:Tensor(f32[4096, 4096]): Cannot find type promotion rule for op: aten.addmm.default" + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":1625 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0015", + "stacks":[] + }, + { + "message":{ + "markdown":"Skipped for fx.Node(aten.view.default)[call_function]:Tensor(f32[4, 1024, 4096]): Cannot find type promotion rule for op: aten.view.default\n\n## Additional Message:\n\n## Function Signature\n### Function Signature _TypePromotionInterpreter.run_node\n- self: \n- node: fx.Node(aten.view.default)[call_function]:Tensor(f32[4, 1024, 4096])\n## Return values\nTensor(f32[4, 1024, 4096])", + "text":"Skipped for fx.Node(aten.view.default)[call_function]:Tensor(f32[4, 1024, 4096]): Cannot find type promotion rule for op: aten.view.default" + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":1625 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0015", + "stacks":[] + }, + { + "message":{ + "markdown":"Type promotion not needed for gelu_8. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature _TypePromotionInterpreter.run_node\n- self: \n- node: fx.Node(aten.gelu.default)[call_function]:Tensor(f32[4, 1024, 4096])\nFound type promotion rule: ElementwiseTypePromotionRule('aten', 'gelu', [0], [], ELEMENTWISE_TYPE_PROMOTION_KIND.DEFAULT)\nArgument view_88 is not promoted. Already torch.float32.\nArgument tanh is not promoted. Not mentioned by type promotion rule.\n## Return values\nTensor(f32[4, 1024, 4096])", + "text":"Type promotion not needed for gelu_8. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":1625 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0015", + "stacks":[] + }, + { + "message":{ + "markdown":"Skipped for fx.Node(aten.clone.default)[call_function]:Tensor(f32[4, 1024, 4096]): Cannot find type promotion rule for op: aten.clone.default\n\n## Additional Message:\n\n## Function Signature\n### Function Signature _TypePromotionInterpreter.run_node\n- self: \n- node: fx.Node(aten.clone.default)[call_function]:Tensor(f32[4, 1024, 4096])\n## Return values\nTensor(f32[4, 1024, 4096])", + "text":"Skipped for fx.Node(aten.clone.default)[call_function]:Tensor(f32[4, 1024, 4096]): Cannot find type promotion rule for op: aten.clone.default" + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":1625 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0015", + "stacks":[] + }, + { + "message":{ + "markdown":"Skipped for fx.Node(aten.view.default)[call_function]:Tensor(f32[4096, 4096]): Cannot find type promotion rule for op: aten.view.default\n\n## Additional Message:\n\n## Function Signature\n### Function Signature _TypePromotionInterpreter.run_node\n- self: \n- node: fx.Node(aten.view.default)[call_function]:Tensor(f32[4096, 4096])\n## Return values\nTensor(f32[4096, 4096])", + "text":"Skipped for fx.Node(aten.view.default)[call_function]:Tensor(f32[4096, 4096]): Cannot find type promotion rule for op: aten.view.default" + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":1625 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0015", + "stacks":[] + }, + { + "message":{ + "markdown":"Skipped for fx.Node(aten.t.default)[call_function]:Tensor(f32[4096, 1024]): Cannot find type promotion rule for op: aten.t.default\n\n## Additional Message:\n\n## Function Signature\n### Function Signature _TypePromotionInterpreter.run_node\n- self: \n- node: fx.Node(aten.t.default)[call_function]:Tensor(f32[4096, 1024])\n## Return values\nTensor(f32[4096, 1024])", + "text":"Skipped for fx.Node(aten.t.default)[call_function]:Tensor(f32[4096, 1024]): Cannot find type promotion rule for op: aten.t.default" + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":1625 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0015", + "stacks":[] + }, + { + "message":{ + "markdown":"Skipped for fx.Node(aten.addmm.default)[call_function]:Tensor(f32[4096, 1024]): Cannot find type promotion rule for op: aten.addmm.default\n\n## Additional Message:\n\n## Function Signature\n### Function Signature _TypePromotionInterpreter.run_node\n- self: \n- node: fx.Node(aten.addmm.default)[call_function]:Tensor(f32[4096, 1024])\n## Return values\nTensor(f32[4096, 1024])", + "text":"Skipped for fx.Node(aten.addmm.default)[call_function]:Tensor(f32[4096, 1024]): Cannot find type promotion rule for op: aten.addmm.default" + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":1625 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0015", + "stacks":[] + }, + { + "message":{ + "markdown":"Skipped for fx.Node(aten.view.default)[call_function]:Tensor(f32[4, 1024, 1024]): Cannot find type promotion rule for op: aten.view.default\n\n## Additional Message:\n\n## Function Signature\n### Function Signature _TypePromotionInterpreter.run_node\n- self: \n- node: fx.Node(aten.view.default)[call_function]:Tensor(f32[4, 1024, 1024])\n## Return values\nTensor(f32[4, 1024, 1024])", + "text":"Skipped for fx.Node(aten.view.default)[call_function]:Tensor(f32[4, 1024, 1024]): Cannot find type promotion rule for op: aten.view.default" + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":1625 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0015", + "stacks":[] + }, + { + "message":{ + "markdown":"Skipped for fx.Node(aten.clone.default)[call_function]:Tensor(f32[4, 1024, 1024]): Cannot find type promotion rule for op: aten.clone.default\n\n## Additional Message:\n\n## Function Signature\n### Function Signature _TypePromotionInterpreter.run_node\n- self: \n- node: fx.Node(aten.clone.default)[call_function]:Tensor(f32[4, 1024, 1024])\n## Return values\nTensor(f32[4, 1024, 1024])", + "text":"Skipped for fx.Node(aten.clone.default)[call_function]:Tensor(f32[4, 1024, 1024]): Cannot find type promotion rule for op: aten.clone.default" + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":1625 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0015", + "stacks":[] + }, + { + "message":{ + "markdown":"Type promotion not needed for add_18. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature _TypePromotionInterpreter.run_node\n- self: \n- node: fx.Node(aten.add.Tensor)[call_function]:Tensor(f32[4, 1024, 1024])\nFound type promotion rule: ElementwiseTypePromotionRule('aten', 'add', [0, 1], [], ELEMENTWISE_TYPE_PROMOTION_KIND.DEFAULT)\nArgument add_17 is not promoted. Already torch.float32.\nArgument clone_27 is not promoted. Already torch.float32.\n## Return values\nTensor(f32[4, 1024, 1024])", + "text":"Type promotion not needed for add_18. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":1625 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0015", + "stacks":[] + }, + { + "message":{ + "markdown":"Skipped for fx.Node(aten.native_layer_norm.default)[call_function]:Tuple[length=3](\nTensor(f32[4, 1024, 1024]),\nTensor(f32[4, 1024, 1]),\nTensor(f32[4, 1024, 1]),\n): Cannot find type promotion rule for op: aten.native_layer_norm.default\n\n## Additional Message:\n\n## Function Signature\n### Function Signature _TypePromotionInterpreter.run_node\n- self: \n- node: fx.Node(aten.native_layer_norm.default)[call_function]:Tuple[length=3](\nTensor(f32[4, 1024, 1024]),\nTensor(f32[4, 1024, 1]),\nTensor(f32[4, 1024, 1]),\n)\n## Return values\nTuple[length=3](\nTensor(f32[4, 1024, 1024]),\nTensor(f32[4, 1024, 1]),\nTensor(f32[4, 1024, 1]),\n)", + "text":"Skipped for fx.Node(aten.native_layer_norm.default)[call_function]:Tuple[length=3](\nTensor(f32[4, 1024, 1024]),\nTensor(f32[4, 1024, 1]),\nTensor(f32[4, 1024, 1]),\n): Cannot find type promotion rule for op: aten.native_layer_norm.default" + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":1625 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0015", + "stacks":[] + }, + { + "message":{ + "markdown":"Skipped for fx.Node()[call_function]:Tensor(f32[4, 1024, 1024]): node.target is not OpOverload. Got type: \n\n## Additional Message:\n\n## Function Signature\n### Function Signature _TypePromotionInterpreter.run_node\n- self: \n- node: fx.Node()[call_function]:Tensor(f32[4, 1024, 1024])\n## Return values\nTensor(f32[4, 1024, 1024])", + "text":"Skipped for fx.Node()[call_function]:Tensor(f32[4, 1024, 1024]): node.target is not OpOverload. Got type: " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":1625 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0015", + "stacks":[] + }, + { + "message":{ + "markdown":"Skipped for fx.Node(aten.view.default)[call_function]:Tensor(f32[4096, 1024]): Cannot find type promotion rule for op: aten.view.default\n\n## Additional Message:\n\n## Function Signature\n### Function Signature _TypePromotionInterpreter.run_node\n- self: \n- node: fx.Node(aten.view.default)[call_function]:Tensor(f32[4096, 1024])\n## Return values\nTensor(f32[4096, 1024])", + "text":"Skipped for fx.Node(aten.view.default)[call_function]:Tensor(f32[4096, 1024]): Cannot find type promotion rule for op: aten.view.default" + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":1625 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0015", + "stacks":[] + }, + { + "message":{ + "markdown":"Skipped for fx.Node(aten.t.default)[call_function]:Tensor(f32[1024, 3072]): Cannot find type promotion rule for op: aten.t.default\n\n## Additional Message:\n\n## Function Signature\n### Function Signature _TypePromotionInterpreter.run_node\n- self: \n- node: fx.Node(aten.t.default)[call_function]:Tensor(f32[1024, 3072])\n## Return values\nTensor(f32[1024, 3072])", + "text":"Skipped for fx.Node(aten.t.default)[call_function]:Tensor(f32[1024, 3072]): Cannot find type promotion rule for op: aten.t.default" + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":1625 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0015", + "stacks":[] + }, + { + "message":{ + "markdown":"Skipped for fx.Node(aten.addmm.default)[call_function]:Tensor(f32[4096, 3072]): Cannot find type promotion rule for op: aten.addmm.default\n\n## Additional Message:\n\n## Function Signature\n### Function Signature _TypePromotionInterpreter.run_node\n- self: \n- node: fx.Node(aten.addmm.default)[call_function]:Tensor(f32[4096, 3072])\n## Return values\nTensor(f32[4096, 3072])", + "text":"Skipped for fx.Node(aten.addmm.default)[call_function]:Tensor(f32[4096, 3072]): Cannot find type promotion rule for op: aten.addmm.default" + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":1625 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0015", + "stacks":[] + }, + { + "message":{ + "markdown":"Skipped for fx.Node(aten.view.default)[call_function]:Tensor(f32[4, 1024, 3072]): Cannot find type promotion rule for op: aten.view.default\n\n## Additional Message:\n\n## Function Signature\n### Function Signature _TypePromotionInterpreter.run_node\n- self: \n- node: fx.Node(aten.view.default)[call_function]:Tensor(f32[4, 1024, 3072])\n## Return values\nTensor(f32[4, 1024, 3072])", + "text":"Skipped for fx.Node(aten.view.default)[call_function]:Tensor(f32[4, 1024, 3072]): Cannot find type promotion rule for op: aten.view.default" + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":1625 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0015", + "stacks":[] + }, + { + "message":{ + "markdown":"Skipped for fx.Node(aten.view.default)[call_function]:Tensor(f32[4, 1024, 3, 16, 64]): Cannot find type promotion rule for op: aten.view.default\n\n## Additional Message:\n\n## Function Signature\n### Function Signature _TypePromotionInterpreter.run_node\n- self: \n- node: fx.Node(aten.view.default)[call_function]:Tensor(f32[4, 1024, 3, 16, 64])\n## Return values\nTensor(f32[4, 1024, 3, 16, 64])", + "text":"Skipped for fx.Node(aten.view.default)[call_function]:Tensor(f32[4, 1024, 3, 16, 64]): Cannot find type promotion rule for op: aten.view.default" + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":1625 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0015", + "stacks":[] + }, + { + "message":{ + "markdown":"Skipped for fx.Node(aten.permute.default)[call_function]:Tensor(f32[3, 4, 16, 1024, 64]): Cannot find type promotion rule for op: aten.permute.default\n\n## Additional Message:\n\n## Function Signature\n### Function Signature _TypePromotionInterpreter.run_node\n- self: \n- node: fx.Node(aten.permute.default)[call_function]:Tensor(f32[3, 4, 16, 1024, 64])\n## Return values\nTensor(f32[3, 4, 16, 1024, 64])", + "text":"Skipped for fx.Node(aten.permute.default)[call_function]:Tensor(f32[3, 4, 16, 1024, 64]): Cannot find type promotion rule for op: aten.permute.default" + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":1625 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0015", + "stacks":[] + }, + { + "message":{ + "markdown":"Skipped for fx.Node(aten.unbind.int)[call_function]:List[length=3](\nTensor(f32[4, 16, 1024, 64]),\nTensor(f32[4, 16, 1024, 64]),\nTensor(f32[4, 16, 1024, 64]),\n): Cannot find type promotion rule for op: aten.unbind.int\n\n## Additional Message:\n\n## Function Signature\n### Function Signature _TypePromotionInterpreter.run_node\n- self: \n- node: fx.Node(aten.unbind.int)[call_function]:List[length=3](\nTensor(f32[4, 16, 1024, 64]),\nTensor(f32[4, 16, 1024, 64]),\nTensor(f32[4, 16, 1024, 64]),\n)\n## Return values\nList[length=3](\nTensor(f32[4, 16, 1024, 64]),\nTensor(f32[4, 16, 1024, 64]),\nTensor(f32[4, 16, 1024, 64]),\n)", + "text":"Skipped for fx.Node(aten.unbind.int)[call_function]:List[length=3](\nTensor(f32[4, 16, 1024, 64]),\nTensor(f32[4, 16, 1024, 64]),\nTensor(f32[4, 16, 1024, 64]),\n): Cannot find type promotion rule for op: aten.unbind.int" + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":1625 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0015", + "stacks":[] + }, + { + "message":{ + "markdown":"Skipped for fx.Node()[call_function]:Tensor(f32[4, 16, 1024, 64]): node.target is not OpOverload. Got type: \n\n## Additional Message:\n\n## Function Signature\n### Function Signature _TypePromotionInterpreter.run_node\n- self: \n- node: fx.Node()[call_function]:Tensor(f32[4, 16, 1024, 64])\n## Return values\nTensor(f32[4, 16, 1024, 64])", + "text":"Skipped for fx.Node()[call_function]:Tensor(f32[4, 16, 1024, 64]): node.target is not OpOverload. Got type: " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":1625 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0015", + "stacks":[] + }, + { + "message":{ + "markdown":"Skipped for fx.Node()[call_function]:Tensor(f32[4, 16, 1024, 64]): node.target is not OpOverload. Got type: \n\n## Additional Message:\n\n## Function Signature\n### Function Signature _TypePromotionInterpreter.run_node\n- self: \n- node: fx.Node()[call_function]:Tensor(f32[4, 16, 1024, 64])\n## Return values\nTensor(f32[4, 16, 1024, 64])", + "text":"Skipped for fx.Node()[call_function]:Tensor(f32[4, 16, 1024, 64]): node.target is not OpOverload. Got type: " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":1625 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0015", + "stacks":[] + }, + { + "message":{ + "markdown":"Skipped for fx.Node()[call_function]:Tensor(f32[4, 16, 1024, 64]): node.target is not OpOverload. Got type: \n\n## Additional Message:\n\n## Function Signature\n### Function Signature _TypePromotionInterpreter.run_node\n- self: \n- node: fx.Node()[call_function]:Tensor(f32[4, 16, 1024, 64])\n## Return values\nTensor(f32[4, 16, 1024, 64])", + "text":"Skipped for fx.Node()[call_function]:Tensor(f32[4, 16, 1024, 64]): node.target is not OpOverload. Got type: " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":1625 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0015", + "stacks":[] + }, + { + "message":{ + "markdown":"Skipped for fx.Node(aten._scaled_dot_product_efficient_attention.default)[call_function]:Tuple[length=4](\nTensor(f32[4, 16, 1024, 64]),\nTensor(f32[4, 16, 0]),\nTensor(i64[]),\nTensor(i64[]),\n): Cannot find type promotion rule for op: aten._scaled_dot_product_efficient_attention.default\n\n## Additional Message:\n\n## Function Signature\n### Function Signature _TypePromotionInterpreter.run_node\n- self: \n- node: fx.Node(aten._scaled_dot_product_efficient_attention.default)[call_function]:Tuple[length=4](\nTensor(f32[4, 16, 1024, 64]),\nTensor(f32[4, 16, 0]),\nTensor(i64[]),\nTensor(i64[]),\n)\n## Return values\nTuple[length=4](\nTensor(f32[4, 16, 1024, 64]),\nTensor(f32[4, 16, 0]),\nTensor(i64[]),\nTensor(i64[]),\n)", + "text":"Skipped for fx.Node(aten._scaled_dot_product_efficient_attention.default)[call_function]:Tuple[length=4](\nTensor(f32[4, 16, 1024, 64]),\nTensor(f32[4, 16, 0]),\nTensor(i64[]),\nTensor(i64[]),\n): Cannot find type promotion rule for op: aten._scaled_dot_product_efficient_attention.default" + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":1625 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0015", + "stacks":[] + }, + { + "message":{ + "markdown":"Skipped for fx.Node()[call_function]:Tensor(f32[4, 16, 1024, 64]): node.target is not OpOverload. Got type: \n\n## Additional Message:\n\n## Function Signature\n### Function Signature _TypePromotionInterpreter.run_node\n- self: \n- node: fx.Node()[call_function]:Tensor(f32[4, 16, 1024, 64])\n## Return values\nTensor(f32[4, 16, 1024, 64])", + "text":"Skipped for fx.Node()[call_function]:Tensor(f32[4, 16, 1024, 64]): node.target is not OpOverload. Got type: " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":1625 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0015", + "stacks":[] + }, + { + "message":{ + "markdown":"Skipped for fx.Node(aten.transpose.int)[call_function]:Tensor(f32[4, 1024, 16, 64]): Cannot find type promotion rule for op: aten.transpose.int\n\n## Additional Message:\n\n## Function Signature\n### Function Signature _TypePromotionInterpreter.run_node\n- self: \n- node: fx.Node(aten.transpose.int)[call_function]:Tensor(f32[4, 1024, 16, 64])\n## Return values\nTensor(f32[4, 1024, 16, 64])", + "text":"Skipped for fx.Node(aten.transpose.int)[call_function]:Tensor(f32[4, 1024, 16, 64]): Cannot find type promotion rule for op: aten.transpose.int" + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":1625 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0015", + "stacks":[] + }, + { + "message":{ + "markdown":"Skipped for fx.Node(aten.view.default)[call_function]:Tensor(f32[4, 1024, 1024]): Cannot find type promotion rule for op: aten.view.default\n\n## Additional Message:\n\n## Function Signature\n### Function Signature _TypePromotionInterpreter.run_node\n- self: \n- node: fx.Node(aten.view.default)[call_function]:Tensor(f32[4, 1024, 1024])\n## Return values\nTensor(f32[4, 1024, 1024])", + "text":"Skipped for fx.Node(aten.view.default)[call_function]:Tensor(f32[4, 1024, 1024]): Cannot find type promotion rule for op: aten.view.default" + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":1625 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0015", + "stacks":[] + }, + { + "message":{ + "markdown":"Skipped for fx.Node(aten.view.default)[call_function]:Tensor(f32[4096, 1024]): Cannot find type promotion rule for op: aten.view.default\n\n## Additional Message:\n\n## Function Signature\n### Function Signature _TypePromotionInterpreter.run_node\n- self: \n- node: fx.Node(aten.view.default)[call_function]:Tensor(f32[4096, 1024])\n## Return values\nTensor(f32[4096, 1024])", + "text":"Skipped for fx.Node(aten.view.default)[call_function]:Tensor(f32[4096, 1024]): Cannot find type promotion rule for op: aten.view.default" + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":1625 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0015", + "stacks":[] + }, + { + "message":{ + "markdown":"Skipped for fx.Node(aten.t.default)[call_function]:Tensor(f32[1024, 1024]): Cannot find type promotion rule for op: aten.t.default\n\n## Additional Message:\n\n## Function Signature\n### Function Signature _TypePromotionInterpreter.run_node\n- self: \n- node: fx.Node(aten.t.default)[call_function]:Tensor(f32[1024, 1024])\n## Return values\nTensor(f32[1024, 1024])", + "text":"Skipped for fx.Node(aten.t.default)[call_function]:Tensor(f32[1024, 1024]): Cannot find type promotion rule for op: aten.t.default" + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":1625 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0015", + "stacks":[] + }, + { + "message":{ + "markdown":"Skipped for fx.Node(aten.addmm.default)[call_function]:Tensor(f32[4096, 1024]): Cannot find type promotion rule for op: aten.addmm.default\n\n## Additional Message:\n\n## Function Signature\n### Function Signature _TypePromotionInterpreter.run_node\n- self: \n- node: fx.Node(aten.addmm.default)[call_function]:Tensor(f32[4096, 1024])\n## Return values\nTensor(f32[4096, 1024])", + "text":"Skipped for fx.Node(aten.addmm.default)[call_function]:Tensor(f32[4096, 1024]): Cannot find type promotion rule for op: aten.addmm.default" + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":1625 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0015", + "stacks":[] + }, + { + "message":{ + "markdown":"Skipped for fx.Node(aten.view.default)[call_function]:Tensor(f32[4, 1024, 1024]): Cannot find type promotion rule for op: aten.view.default\n\n## Additional Message:\n\n## Function Signature\n### Function Signature _TypePromotionInterpreter.run_node\n- self: \n- node: fx.Node(aten.view.default)[call_function]:Tensor(f32[4, 1024, 1024])\n## Return values\nTensor(f32[4, 1024, 1024])", + "text":"Skipped for fx.Node(aten.view.default)[call_function]:Tensor(f32[4, 1024, 1024]): Cannot find type promotion rule for op: aten.view.default" + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":1625 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0015", + "stacks":[] + }, + { + "message":{ + "markdown":"Skipped for fx.Node(aten.clone.default)[call_function]:Tensor(f32[4, 1024, 1024]): Cannot find type promotion rule for op: aten.clone.default\n\n## Additional Message:\n\n## Function Signature\n### Function Signature _TypePromotionInterpreter.run_node\n- self: \n- node: fx.Node(aten.clone.default)[call_function]:Tensor(f32[4, 1024, 1024])\n## Return values\nTensor(f32[4, 1024, 1024])", + "text":"Skipped for fx.Node(aten.clone.default)[call_function]:Tensor(f32[4, 1024, 1024]): Cannot find type promotion rule for op: aten.clone.default" + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":1625 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0015", + "stacks":[] + }, + { + "message":{ + "markdown":"Type promotion not needed for add_19. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature _TypePromotionInterpreter.run_node\n- self: \n- node: fx.Node(aten.add.Tensor)[call_function]:Tensor(f32[4, 1024, 1024])\nFound type promotion rule: ElementwiseTypePromotionRule('aten', 'add', [0, 1], [], ELEMENTWISE_TYPE_PROMOTION_KIND.DEFAULT)\nArgument add_18 is not promoted. Already torch.float32.\nArgument clone_28 is not promoted. Already torch.float32.\n## Return values\nTensor(f32[4, 1024, 1024])", + "text":"Type promotion not needed for add_19. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":1625 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0015", + "stacks":[] + }, + { + "message":{ + "markdown":"Skipped for fx.Node(aten.native_layer_norm.default)[call_function]:Tuple[length=3](\nTensor(f32[4, 1024, 1024]),\nTensor(f32[4, 1024, 1]),\nTensor(f32[4, 1024, 1]),\n): Cannot find type promotion rule for op: aten.native_layer_norm.default\n\n## Additional Message:\n\n## Function Signature\n### Function Signature _TypePromotionInterpreter.run_node\n- self: \n- node: fx.Node(aten.native_layer_norm.default)[call_function]:Tuple[length=3](\nTensor(f32[4, 1024, 1024]),\nTensor(f32[4, 1024, 1]),\nTensor(f32[4, 1024, 1]),\n)\n## Return values\nTuple[length=3](\nTensor(f32[4, 1024, 1024]),\nTensor(f32[4, 1024, 1]),\nTensor(f32[4, 1024, 1]),\n)", + "text":"Skipped for fx.Node(aten.native_layer_norm.default)[call_function]:Tuple[length=3](\nTensor(f32[4, 1024, 1024]),\nTensor(f32[4, 1024, 1]),\nTensor(f32[4, 1024, 1]),\n): Cannot find type promotion rule for op: aten.native_layer_norm.default" + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":1625 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0015", + "stacks":[] + }, + { + "message":{ + "markdown":"Skipped for fx.Node()[call_function]:Tensor(f32[4, 1024, 1024]): node.target is not OpOverload. Got type: \n\n## Additional Message:\n\n## Function Signature\n### Function Signature _TypePromotionInterpreter.run_node\n- self: \n- node: fx.Node()[call_function]:Tensor(f32[4, 1024, 1024])\n## Return values\nTensor(f32[4, 1024, 1024])", + "text":"Skipped for fx.Node()[call_function]:Tensor(f32[4, 1024, 1024]): node.target is not OpOverload. Got type: " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":1625 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0015", + "stacks":[] + }, + { + "message":{ + "markdown":"Skipped for fx.Node(aten.view.default)[call_function]:Tensor(f32[4096, 1024]): Cannot find type promotion rule for op: aten.view.default\n\n## Additional Message:\n\n## Function Signature\n### Function Signature _TypePromotionInterpreter.run_node\n- self: \n- node: fx.Node(aten.view.default)[call_function]:Tensor(f32[4096, 1024])\n## Return values\nTensor(f32[4096, 1024])", + "text":"Skipped for fx.Node(aten.view.default)[call_function]:Tensor(f32[4096, 1024]): Cannot find type promotion rule for op: aten.view.default" + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":1625 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0015", + "stacks":[] + }, + { + "message":{ + "markdown":"Skipped for fx.Node(aten.t.default)[call_function]:Tensor(f32[1024, 4096]): Cannot find type promotion rule for op: aten.t.default\n\n## Additional Message:\n\n## Function Signature\n### Function Signature _TypePromotionInterpreter.run_node\n- self: \n- node: fx.Node(aten.t.default)[call_function]:Tensor(f32[1024, 4096])\n## Return values\nTensor(f32[1024, 4096])", + "text":"Skipped for fx.Node(aten.t.default)[call_function]:Tensor(f32[1024, 4096]): Cannot find type promotion rule for op: aten.t.default" + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":1625 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0015", + "stacks":[] + }, + { + "message":{ + "markdown":"Skipped for fx.Node(aten.addmm.default)[call_function]:Tensor(f32[4096, 4096]): Cannot find type promotion rule for op: aten.addmm.default\n\n## Additional Message:\n\n## Function Signature\n### Function Signature _TypePromotionInterpreter.run_node\n- self: \n- node: fx.Node(aten.addmm.default)[call_function]:Tensor(f32[4096, 4096])\n## Return values\nTensor(f32[4096, 4096])", + "text":"Skipped for fx.Node(aten.addmm.default)[call_function]:Tensor(f32[4096, 4096]): Cannot find type promotion rule for op: aten.addmm.default" + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":1625 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0015", + "stacks":[] + }, + { + "message":{ + "markdown":"Skipped for fx.Node(aten.view.default)[call_function]:Tensor(f32[4, 1024, 4096]): Cannot find type promotion rule for op: aten.view.default\n\n## Additional Message:\n\n## Function Signature\n### Function Signature _TypePromotionInterpreter.run_node\n- self: \n- node: fx.Node(aten.view.default)[call_function]:Tensor(f32[4, 1024, 4096])\n## Return values\nTensor(f32[4, 1024, 4096])", + "text":"Skipped for fx.Node(aten.view.default)[call_function]:Tensor(f32[4, 1024, 4096]): Cannot find type promotion rule for op: aten.view.default" + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":1625 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0015", + "stacks":[] + }, + { + "message":{ + "markdown":"Type promotion not needed for gelu_9. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature _TypePromotionInterpreter.run_node\n- self: \n- node: fx.Node(aten.gelu.default)[call_function]:Tensor(f32[4, 1024, 4096])\nFound type promotion rule: ElementwiseTypePromotionRule('aten', 'gelu', [0], [], ELEMENTWISE_TYPE_PROMOTION_KIND.DEFAULT)\nArgument view_98 is not promoted. Already torch.float32.\nArgument tanh is not promoted. Not mentioned by type promotion rule.\n## Return values\nTensor(f32[4, 1024, 4096])", + "text":"Type promotion not needed for gelu_9. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":1625 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0015", + "stacks":[] + }, + { + "message":{ + "markdown":"Skipped for fx.Node(aten.clone.default)[call_function]:Tensor(f32[4, 1024, 4096]): Cannot find type promotion rule for op: aten.clone.default\n\n## Additional Message:\n\n## Function Signature\n### Function Signature _TypePromotionInterpreter.run_node\n- self: \n- node: fx.Node(aten.clone.default)[call_function]:Tensor(f32[4, 1024, 4096])\n## Return values\nTensor(f32[4, 1024, 4096])", + "text":"Skipped for fx.Node(aten.clone.default)[call_function]:Tensor(f32[4, 1024, 4096]): Cannot find type promotion rule for op: aten.clone.default" + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":1625 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0015", + "stacks":[] + }, + { + "message":{ + "markdown":"Skipped for fx.Node(aten.view.default)[call_function]:Tensor(f32[4096, 4096]): Cannot find type promotion rule for op: aten.view.default\n\n## Additional Message:\n\n## Function Signature\n### Function Signature _TypePromotionInterpreter.run_node\n- self: \n- node: fx.Node(aten.view.default)[call_function]:Tensor(f32[4096, 4096])\n## Return values\nTensor(f32[4096, 4096])", + "text":"Skipped for fx.Node(aten.view.default)[call_function]:Tensor(f32[4096, 4096]): Cannot find type promotion rule for op: aten.view.default" + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":1625 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0015", + "stacks":[] + }, + { + "message":{ + "markdown":"Skipped for fx.Node(aten.t.default)[call_function]:Tensor(f32[4096, 1024]): Cannot find type promotion rule for op: aten.t.default\n\n## Additional Message:\n\n## Function Signature\n### Function Signature _TypePromotionInterpreter.run_node\n- self: \n- node: fx.Node(aten.t.default)[call_function]:Tensor(f32[4096, 1024])\n## Return values\nTensor(f32[4096, 1024])", + "text":"Skipped for fx.Node(aten.t.default)[call_function]:Tensor(f32[4096, 1024]): Cannot find type promotion rule for op: aten.t.default" + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":1625 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0015", + "stacks":[] + }, + { + "message":{ + "markdown":"Skipped for fx.Node(aten.addmm.default)[call_function]:Tensor(f32[4096, 1024]): Cannot find type promotion rule for op: aten.addmm.default\n\n## Additional Message:\n\n## Function Signature\n### Function Signature _TypePromotionInterpreter.run_node\n- self: \n- node: fx.Node(aten.addmm.default)[call_function]:Tensor(f32[4096, 1024])\n## Return values\nTensor(f32[4096, 1024])", + "text":"Skipped for fx.Node(aten.addmm.default)[call_function]:Tensor(f32[4096, 1024]): Cannot find type promotion rule for op: aten.addmm.default" + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":1625 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0015", + "stacks":[] + }, + { + "message":{ + "markdown":"Skipped for fx.Node(aten.view.default)[call_function]:Tensor(f32[4, 1024, 1024]): Cannot find type promotion rule for op: aten.view.default\n\n## Additional Message:\n\n## Function Signature\n### Function Signature _TypePromotionInterpreter.run_node\n- self: \n- node: fx.Node(aten.view.default)[call_function]:Tensor(f32[4, 1024, 1024])\n## Return values\nTensor(f32[4, 1024, 1024])", + "text":"Skipped for fx.Node(aten.view.default)[call_function]:Tensor(f32[4, 1024, 1024]): Cannot find type promotion rule for op: aten.view.default" + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":1625 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0015", + "stacks":[] + }, + { + "message":{ + "markdown":"Skipped for fx.Node(aten.clone.default)[call_function]:Tensor(f32[4, 1024, 1024]): Cannot find type promotion rule for op: aten.clone.default\n\n## Additional Message:\n\n## Function Signature\n### Function Signature _TypePromotionInterpreter.run_node\n- self: \n- node: fx.Node(aten.clone.default)[call_function]:Tensor(f32[4, 1024, 1024])\n## Return values\nTensor(f32[4, 1024, 1024])", + "text":"Skipped for fx.Node(aten.clone.default)[call_function]:Tensor(f32[4, 1024, 1024]): Cannot find type promotion rule for op: aten.clone.default" + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":1625 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0015", + "stacks":[] + }, + { + "message":{ + "markdown":"Type promotion not needed for add_20. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature _TypePromotionInterpreter.run_node\n- self: \n- node: fx.Node(aten.add.Tensor)[call_function]:Tensor(f32[4, 1024, 1024])\nFound type promotion rule: ElementwiseTypePromotionRule('aten', 'add', [0, 1], [], ELEMENTWISE_TYPE_PROMOTION_KIND.DEFAULT)\nArgument add_19 is not promoted. Already torch.float32.\nArgument clone_30 is not promoted. Already torch.float32.\n## Return values\nTensor(f32[4, 1024, 1024])", + "text":"Type promotion not needed for add_20. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":1625 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0015", + "stacks":[] + }, + { + "message":{ + "markdown":"Skipped for fx.Node(aten.native_layer_norm.default)[call_function]:Tuple[length=3](\nTensor(f32[4, 1024, 1024]),\nTensor(f32[4, 1024, 1]),\nTensor(f32[4, 1024, 1]),\n): Cannot find type promotion rule for op: aten.native_layer_norm.default\n\n## Additional Message:\n\n## Function Signature\n### Function Signature _TypePromotionInterpreter.run_node\n- self: \n- node: fx.Node(aten.native_layer_norm.default)[call_function]:Tuple[length=3](\nTensor(f32[4, 1024, 1024]),\nTensor(f32[4, 1024, 1]),\nTensor(f32[4, 1024, 1]),\n)\n## Return values\nTuple[length=3](\nTensor(f32[4, 1024, 1024]),\nTensor(f32[4, 1024, 1]),\nTensor(f32[4, 1024, 1]),\n)", + "text":"Skipped for fx.Node(aten.native_layer_norm.default)[call_function]:Tuple[length=3](\nTensor(f32[4, 1024, 1024]),\nTensor(f32[4, 1024, 1]),\nTensor(f32[4, 1024, 1]),\n): Cannot find type promotion rule for op: aten.native_layer_norm.default" + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":1625 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0015", + "stacks":[] + }, + { + "message":{ + "markdown":"Skipped for fx.Node()[call_function]:Tensor(f32[4, 1024, 1024]): node.target is not OpOverload. Got type: \n\n## Additional Message:\n\n## Function Signature\n### Function Signature _TypePromotionInterpreter.run_node\n- self: \n- node: fx.Node()[call_function]:Tensor(f32[4, 1024, 1024])\n## Return values\nTensor(f32[4, 1024, 1024])", + "text":"Skipped for fx.Node()[call_function]:Tensor(f32[4, 1024, 1024]): node.target is not OpOverload. Got type: " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":1625 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0015", + "stacks":[] + }, + { + "message":{ + "markdown":"Skipped for fx.Node(aten.view.default)[call_function]:Tensor(f32[4096, 1024]): Cannot find type promotion rule for op: aten.view.default\n\n## Additional Message:\n\n## Function Signature\n### Function Signature _TypePromotionInterpreter.run_node\n- self: \n- node: fx.Node(aten.view.default)[call_function]:Tensor(f32[4096, 1024])\n## Return values\nTensor(f32[4096, 1024])", + "text":"Skipped for fx.Node(aten.view.default)[call_function]:Tensor(f32[4096, 1024]): Cannot find type promotion rule for op: aten.view.default" + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":1625 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0015", + "stacks":[] + }, + { + "message":{ + "markdown":"Skipped for fx.Node(aten.t.default)[call_function]:Tensor(f32[1024, 3072]): Cannot find type promotion rule for op: aten.t.default\n\n## Additional Message:\n\n## Function Signature\n### Function Signature _TypePromotionInterpreter.run_node\n- self: \n- node: fx.Node(aten.t.default)[call_function]:Tensor(f32[1024, 3072])\n## Return values\nTensor(f32[1024, 3072])", + "text":"Skipped for fx.Node(aten.t.default)[call_function]:Tensor(f32[1024, 3072]): Cannot find type promotion rule for op: aten.t.default" + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":1625 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0015", + "stacks":[] + }, + { + "message":{ + "markdown":"Skipped for fx.Node(aten.addmm.default)[call_function]:Tensor(f32[4096, 3072]): Cannot find type promotion rule for op: aten.addmm.default\n\n## Additional Message:\n\n## Function Signature\n### Function Signature _TypePromotionInterpreter.run_node\n- self: \n- node: fx.Node(aten.addmm.default)[call_function]:Tensor(f32[4096, 3072])\n## Return values\nTensor(f32[4096, 3072])", + "text":"Skipped for fx.Node(aten.addmm.default)[call_function]:Tensor(f32[4096, 3072]): Cannot find type promotion rule for op: aten.addmm.default" + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":1625 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0015", + "stacks":[] + }, + { + "message":{ + "markdown":"Skipped for fx.Node(aten.view.default)[call_function]:Tensor(f32[4, 1024, 3072]): Cannot find type promotion rule for op: aten.view.default\n\n## Additional Message:\n\n## Function Signature\n### Function Signature _TypePromotionInterpreter.run_node\n- self: \n- node: fx.Node(aten.view.default)[call_function]:Tensor(f32[4, 1024, 3072])\n## Return values\nTensor(f32[4, 1024, 3072])", + "text":"Skipped for fx.Node(aten.view.default)[call_function]:Tensor(f32[4, 1024, 3072]): Cannot find type promotion rule for op: aten.view.default" + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":1625 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0015", + "stacks":[] + }, + { + "message":{ + "markdown":"Skipped for fx.Node(aten.view.default)[call_function]:Tensor(f32[4, 1024, 3, 16, 64]): Cannot find type promotion rule for op: aten.view.default\n\n## Additional Message:\n\n## Function Signature\n### Function Signature _TypePromotionInterpreter.run_node\n- self: \n- node: fx.Node(aten.view.default)[call_function]:Tensor(f32[4, 1024, 3, 16, 64])\n## Return values\nTensor(f32[4, 1024, 3, 16, 64])", + "text":"Skipped for fx.Node(aten.view.default)[call_function]:Tensor(f32[4, 1024, 3, 16, 64]): Cannot find type promotion rule for op: aten.view.default" + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":1625 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0015", + "stacks":[] + }, + { + "message":{ + "markdown":"Skipped for fx.Node(aten.permute.default)[call_function]:Tensor(f32[3, 4, 16, 1024, 64]): Cannot find type promotion rule for op: aten.permute.default\n\n## Additional Message:\n\n## Function Signature\n### Function Signature _TypePromotionInterpreter.run_node\n- self: \n- node: fx.Node(aten.permute.default)[call_function]:Tensor(f32[3, 4, 16, 1024, 64])\n## Return values\nTensor(f32[3, 4, 16, 1024, 64])", + "text":"Skipped for fx.Node(aten.permute.default)[call_function]:Tensor(f32[3, 4, 16, 1024, 64]): Cannot find type promotion rule for op: aten.permute.default" + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":1625 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0015", + "stacks":[] + }, + { + "message":{ + "markdown":"Skipped for fx.Node(aten.unbind.int)[call_function]:List[length=3](\nTensor(f32[4, 16, 1024, 64]),\nTensor(f32[4, 16, 1024, 64]),\nTensor(f32[4, 16, 1024, 64]),\n): Cannot find type promotion rule for op: aten.unbind.int\n\n## Additional Message:\n\n## Function Signature\n### Function Signature _TypePromotionInterpreter.run_node\n- self: \n- node: fx.Node(aten.unbind.int)[call_function]:List[length=3](\nTensor(f32[4, 16, 1024, 64]),\nTensor(f32[4, 16, 1024, 64]),\nTensor(f32[4, 16, 1024, 64]),\n)\n## Return values\nList[length=3](\nTensor(f32[4, 16, 1024, 64]),\nTensor(f32[4, 16, 1024, 64]),\nTensor(f32[4, 16, 1024, 64]),\n)", + "text":"Skipped for fx.Node(aten.unbind.int)[call_function]:List[length=3](\nTensor(f32[4, 16, 1024, 64]),\nTensor(f32[4, 16, 1024, 64]),\nTensor(f32[4, 16, 1024, 64]),\n): Cannot find type promotion rule for op: aten.unbind.int" + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":1625 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0015", + "stacks":[] + }, + { + "message":{ + "markdown":"Skipped for fx.Node()[call_function]:Tensor(f32[4, 16, 1024, 64]): node.target is not OpOverload. Got type: \n\n## Additional Message:\n\n## Function Signature\n### Function Signature _TypePromotionInterpreter.run_node\n- self: \n- node: fx.Node()[call_function]:Tensor(f32[4, 16, 1024, 64])\n## Return values\nTensor(f32[4, 16, 1024, 64])", + "text":"Skipped for fx.Node()[call_function]:Tensor(f32[4, 16, 1024, 64]): node.target is not OpOverload. Got type: " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":1625 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0015", + "stacks":[] + }, + { + "message":{ + "markdown":"Skipped for fx.Node()[call_function]:Tensor(f32[4, 16, 1024, 64]): node.target is not OpOverload. Got type: \n\n## Additional Message:\n\n## Function Signature\n### Function Signature _TypePromotionInterpreter.run_node\n- self: \n- node: fx.Node()[call_function]:Tensor(f32[4, 16, 1024, 64])\n## Return values\nTensor(f32[4, 16, 1024, 64])", + "text":"Skipped for fx.Node()[call_function]:Tensor(f32[4, 16, 1024, 64]): node.target is not OpOverload. Got type: " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":1625 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0015", + "stacks":[] + }, + { + "message":{ + "markdown":"Skipped for fx.Node()[call_function]:Tensor(f32[4, 16, 1024, 64]): node.target is not OpOverload. Got type: \n\n## Additional Message:\n\n## Function Signature\n### Function Signature _TypePromotionInterpreter.run_node\n- self: \n- node: fx.Node()[call_function]:Tensor(f32[4, 16, 1024, 64])\n## Return values\nTensor(f32[4, 16, 1024, 64])", + "text":"Skipped for fx.Node()[call_function]:Tensor(f32[4, 16, 1024, 64]): node.target is not OpOverload. Got type: " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":1625 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0015", + "stacks":[] + }, + { + "message":{ + "markdown":"Skipped for fx.Node(aten._scaled_dot_product_efficient_attention.default)[call_function]:Tuple[length=4](\nTensor(f32[4, 16, 1024, 64]),\nTensor(f32[4, 16, 0]),\nTensor(i64[]),\nTensor(i64[]),\n): Cannot find type promotion rule for op: aten._scaled_dot_product_efficient_attention.default\n\n## Additional Message:\n\n## Function Signature\n### Function Signature _TypePromotionInterpreter.run_node\n- self: \n- node: fx.Node(aten._scaled_dot_product_efficient_attention.default)[call_function]:Tuple[length=4](\nTensor(f32[4, 16, 1024, 64]),\nTensor(f32[4, 16, 0]),\nTensor(i64[]),\nTensor(i64[]),\n)\n## Return values\nTuple[length=4](\nTensor(f32[4, 16, 1024, 64]),\nTensor(f32[4, 16, 0]),\nTensor(i64[]),\nTensor(i64[]),\n)", + "text":"Skipped for fx.Node(aten._scaled_dot_product_efficient_attention.default)[call_function]:Tuple[length=4](\nTensor(f32[4, 16, 1024, 64]),\nTensor(f32[4, 16, 0]),\nTensor(i64[]),\nTensor(i64[]),\n): Cannot find type promotion rule for op: aten._scaled_dot_product_efficient_attention.default" + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":1625 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0015", + "stacks":[] + }, + { + "message":{ + "markdown":"Skipped for fx.Node()[call_function]:Tensor(f32[4, 16, 1024, 64]): node.target is not OpOverload. Got type: \n\n## Additional Message:\n\n## Function Signature\n### Function Signature _TypePromotionInterpreter.run_node\n- self: \n- node: fx.Node()[call_function]:Tensor(f32[4, 16, 1024, 64])\n## Return values\nTensor(f32[4, 16, 1024, 64])", + "text":"Skipped for fx.Node()[call_function]:Tensor(f32[4, 16, 1024, 64]): node.target is not OpOverload. Got type: " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":1625 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0015", + "stacks":[] + }, + { + "message":{ + "markdown":"Skipped for fx.Node(aten.transpose.int)[call_function]:Tensor(f32[4, 1024, 16, 64]): Cannot find type promotion rule for op: aten.transpose.int\n\n## Additional Message:\n\n## Function Signature\n### Function Signature _TypePromotionInterpreter.run_node\n- self: \n- node: fx.Node(aten.transpose.int)[call_function]:Tensor(f32[4, 1024, 16, 64])\n## Return values\nTensor(f32[4, 1024, 16, 64])", + "text":"Skipped for fx.Node(aten.transpose.int)[call_function]:Tensor(f32[4, 1024, 16, 64]): Cannot find type promotion rule for op: aten.transpose.int" + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":1625 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0015", + "stacks":[] + }, + { + "message":{ + "markdown":"Skipped for fx.Node(aten.view.default)[call_function]:Tensor(f32[4, 1024, 1024]): Cannot find type promotion rule for op: aten.view.default\n\n## Additional Message:\n\n## Function Signature\n### Function Signature _TypePromotionInterpreter.run_node\n- self: \n- node: fx.Node(aten.view.default)[call_function]:Tensor(f32[4, 1024, 1024])\n## Return values\nTensor(f32[4, 1024, 1024])", + "text":"Skipped for fx.Node(aten.view.default)[call_function]:Tensor(f32[4, 1024, 1024]): Cannot find type promotion rule for op: aten.view.default" + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":1625 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0015", + "stacks":[] + }, + { + "message":{ + "markdown":"Skipped for fx.Node(aten.view.default)[call_function]:Tensor(f32[4096, 1024]): Cannot find type promotion rule for op: aten.view.default\n\n## Additional Message:\n\n## Function Signature\n### Function Signature _TypePromotionInterpreter.run_node\n- self: \n- node: fx.Node(aten.view.default)[call_function]:Tensor(f32[4096, 1024])\n## Return values\nTensor(f32[4096, 1024])", + "text":"Skipped for fx.Node(aten.view.default)[call_function]:Tensor(f32[4096, 1024]): Cannot find type promotion rule for op: aten.view.default" + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":1625 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0015", + "stacks":[] + }, + { + "message":{ + "markdown":"Skipped for fx.Node(aten.t.default)[call_function]:Tensor(f32[1024, 1024]): Cannot find type promotion rule for op: aten.t.default\n\n## Additional Message:\n\n## Function Signature\n### Function Signature _TypePromotionInterpreter.run_node\n- self: \n- node: fx.Node(aten.t.default)[call_function]:Tensor(f32[1024, 1024])\n## Return values\nTensor(f32[1024, 1024])", + "text":"Skipped for fx.Node(aten.t.default)[call_function]:Tensor(f32[1024, 1024]): Cannot find type promotion rule for op: aten.t.default" + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":1625 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0015", + "stacks":[] + }, + { + "message":{ + "markdown":"Skipped for fx.Node(aten.addmm.default)[call_function]:Tensor(f32[4096, 1024]): Cannot find type promotion rule for op: aten.addmm.default\n\n## Additional Message:\n\n## Function Signature\n### Function Signature _TypePromotionInterpreter.run_node\n- self: \n- node: fx.Node(aten.addmm.default)[call_function]:Tensor(f32[4096, 1024])\n## Return values\nTensor(f32[4096, 1024])", + "text":"Skipped for fx.Node(aten.addmm.default)[call_function]:Tensor(f32[4096, 1024]): Cannot find type promotion rule for op: aten.addmm.default" + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":1625 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0015", + "stacks":[] + }, + { + "message":{ + "markdown":"Skipped for fx.Node(aten.view.default)[call_function]:Tensor(f32[4, 1024, 1024]): Cannot find type promotion rule for op: aten.view.default\n\n## Additional Message:\n\n## Function Signature\n### Function Signature _TypePromotionInterpreter.run_node\n- self: \n- node: fx.Node(aten.view.default)[call_function]:Tensor(f32[4, 1024, 1024])\n## Return values\nTensor(f32[4, 1024, 1024])", + "text":"Skipped for fx.Node(aten.view.default)[call_function]:Tensor(f32[4, 1024, 1024]): Cannot find type promotion rule for op: aten.view.default" + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":1625 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0015", + "stacks":[] + }, + { + "message":{ + "markdown":"Skipped for fx.Node(aten.clone.default)[call_function]:Tensor(f32[4, 1024, 1024]): Cannot find type promotion rule for op: aten.clone.default\n\n## Additional Message:\n\n## Function Signature\n### Function Signature _TypePromotionInterpreter.run_node\n- self: \n- node: fx.Node(aten.clone.default)[call_function]:Tensor(f32[4, 1024, 1024])\n## Return values\nTensor(f32[4, 1024, 1024])", + "text":"Skipped for fx.Node(aten.clone.default)[call_function]:Tensor(f32[4, 1024, 1024]): Cannot find type promotion rule for op: aten.clone.default" + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":1625 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0015", + "stacks":[] + }, + { + "message":{ + "markdown":"Type promotion not needed for add_21. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature _TypePromotionInterpreter.run_node\n- self: \n- node: fx.Node(aten.add.Tensor)[call_function]:Tensor(f32[4, 1024, 1024])\nFound type promotion rule: ElementwiseTypePromotionRule('aten', 'add', [0, 1], [], ELEMENTWISE_TYPE_PROMOTION_KIND.DEFAULT)\nArgument add_20 is not promoted. Already torch.float32.\nArgument clone_31 is not promoted. Already torch.float32.\n## Return values\nTensor(f32[4, 1024, 1024])", + "text":"Type promotion not needed for add_21. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":1625 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0015", + "stacks":[] + }, + { + "message":{ + "markdown":"Skipped for fx.Node(aten.native_layer_norm.default)[call_function]:Tuple[length=3](\nTensor(f32[4, 1024, 1024]),\nTensor(f32[4, 1024, 1]),\nTensor(f32[4, 1024, 1]),\n): Cannot find type promotion rule for op: aten.native_layer_norm.default\n\n## Additional Message:\n\n## Function Signature\n### Function Signature _TypePromotionInterpreter.run_node\n- self: \n- node: fx.Node(aten.native_layer_norm.default)[call_function]:Tuple[length=3](\nTensor(f32[4, 1024, 1024]),\nTensor(f32[4, 1024, 1]),\nTensor(f32[4, 1024, 1]),\n)\n## Return values\nTuple[length=3](\nTensor(f32[4, 1024, 1024]),\nTensor(f32[4, 1024, 1]),\nTensor(f32[4, 1024, 1]),\n)", + "text":"Skipped for fx.Node(aten.native_layer_norm.default)[call_function]:Tuple[length=3](\nTensor(f32[4, 1024, 1024]),\nTensor(f32[4, 1024, 1]),\nTensor(f32[4, 1024, 1]),\n): Cannot find type promotion rule for op: aten.native_layer_norm.default" + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":1625 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0015", + "stacks":[] + }, + { + "message":{ + "markdown":"Skipped for fx.Node()[call_function]:Tensor(f32[4, 1024, 1024]): node.target is not OpOverload. Got type: \n\n## Additional Message:\n\n## Function Signature\n### Function Signature _TypePromotionInterpreter.run_node\n- self: \n- node: fx.Node()[call_function]:Tensor(f32[4, 1024, 1024])\n## Return values\nTensor(f32[4, 1024, 1024])", + "text":"Skipped for fx.Node()[call_function]:Tensor(f32[4, 1024, 1024]): node.target is not OpOverload. Got type: " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":1625 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0015", + "stacks":[] + }, + { + "message":{ + "markdown":"Skipped for fx.Node(aten.view.default)[call_function]:Tensor(f32[4096, 1024]): Cannot find type promotion rule for op: aten.view.default\n\n## Additional Message:\n\n## Function Signature\n### Function Signature _TypePromotionInterpreter.run_node\n- self: \n- node: fx.Node(aten.view.default)[call_function]:Tensor(f32[4096, 1024])\n## Return values\nTensor(f32[4096, 1024])", + "text":"Skipped for fx.Node(aten.view.default)[call_function]:Tensor(f32[4096, 1024]): Cannot find type promotion rule for op: aten.view.default" + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":1625 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0015", + "stacks":[] + }, + { + "message":{ + "markdown":"Skipped for fx.Node(aten.t.default)[call_function]:Tensor(f32[1024, 4096]): Cannot find type promotion rule for op: aten.t.default\n\n## Additional Message:\n\n## Function Signature\n### Function Signature _TypePromotionInterpreter.run_node\n- self: \n- node: fx.Node(aten.t.default)[call_function]:Tensor(f32[1024, 4096])\n## Return values\nTensor(f32[1024, 4096])", + "text":"Skipped for fx.Node(aten.t.default)[call_function]:Tensor(f32[1024, 4096]): Cannot find type promotion rule for op: aten.t.default" + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":1625 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0015", + "stacks":[] + }, + { + "message":{ + "markdown":"Skipped for fx.Node(aten.addmm.default)[call_function]:Tensor(f32[4096, 4096]): Cannot find type promotion rule for op: aten.addmm.default\n\n## Additional Message:\n\n## Function Signature\n### Function Signature _TypePromotionInterpreter.run_node\n- self: \n- node: fx.Node(aten.addmm.default)[call_function]:Tensor(f32[4096, 4096])\n## Return values\nTensor(f32[4096, 4096])", + "text":"Skipped for fx.Node(aten.addmm.default)[call_function]:Tensor(f32[4096, 4096]): Cannot find type promotion rule for op: aten.addmm.default" + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":1625 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0015", + "stacks":[] + }, + { + "message":{ + "markdown":"Skipped for fx.Node(aten.view.default)[call_function]:Tensor(f32[4, 1024, 4096]): Cannot find type promotion rule for op: aten.view.default\n\n## Additional Message:\n\n## Function Signature\n### Function Signature _TypePromotionInterpreter.run_node\n- self: \n- node: fx.Node(aten.view.default)[call_function]:Tensor(f32[4, 1024, 4096])\n## Return values\nTensor(f32[4, 1024, 4096])", + "text":"Skipped for fx.Node(aten.view.default)[call_function]:Tensor(f32[4, 1024, 4096]): Cannot find type promotion rule for op: aten.view.default" + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":1625 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0015", + "stacks":[] + }, + { + "message":{ + "markdown":"Type promotion not needed for gelu_10. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature _TypePromotionInterpreter.run_node\n- self: \n- node: fx.Node(aten.gelu.default)[call_function]:Tensor(f32[4, 1024, 4096])\nFound type promotion rule: ElementwiseTypePromotionRule('aten', 'gelu', [0], [], ELEMENTWISE_TYPE_PROMOTION_KIND.DEFAULT)\nArgument view_108 is not promoted. Already torch.float32.\nArgument tanh is not promoted. Not mentioned by type promotion rule.\n## Return values\nTensor(f32[4, 1024, 4096])", + "text":"Type promotion not needed for gelu_10. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":1625 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0015", + "stacks":[] + }, + { + "message":{ + "markdown":"Skipped for fx.Node(aten.clone.default)[call_function]:Tensor(f32[4, 1024, 4096]): Cannot find type promotion rule for op: aten.clone.default\n\n## Additional Message:\n\n## Function Signature\n### Function Signature _TypePromotionInterpreter.run_node\n- self: \n- node: fx.Node(aten.clone.default)[call_function]:Tensor(f32[4, 1024, 4096])\n## Return values\nTensor(f32[4, 1024, 4096])", + "text":"Skipped for fx.Node(aten.clone.default)[call_function]:Tensor(f32[4, 1024, 4096]): Cannot find type promotion rule for op: aten.clone.default" + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":1625 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0015", + "stacks":[] + }, + { + "message":{ + "markdown":"Skipped for fx.Node(aten.view.default)[call_function]:Tensor(f32[4096, 4096]): Cannot find type promotion rule for op: aten.view.default\n\n## Additional Message:\n\n## Function Signature\n### Function Signature _TypePromotionInterpreter.run_node\n- self: \n- node: fx.Node(aten.view.default)[call_function]:Tensor(f32[4096, 4096])\n## Return values\nTensor(f32[4096, 4096])", + "text":"Skipped for fx.Node(aten.view.default)[call_function]:Tensor(f32[4096, 4096]): Cannot find type promotion rule for op: aten.view.default" + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":1625 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0015", + "stacks":[] + }, + { + "message":{ + "markdown":"Skipped for fx.Node(aten.t.default)[call_function]:Tensor(f32[4096, 1024]): Cannot find type promotion rule for op: aten.t.default\n\n## Additional Message:\n\n## Function Signature\n### Function Signature _TypePromotionInterpreter.run_node\n- self: \n- node: fx.Node(aten.t.default)[call_function]:Tensor(f32[4096, 1024])\n## Return values\nTensor(f32[4096, 1024])", + "text":"Skipped for fx.Node(aten.t.default)[call_function]:Tensor(f32[4096, 1024]): Cannot find type promotion rule for op: aten.t.default" + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":1625 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0015", + "stacks":[] + }, + { + "message":{ + "markdown":"Skipped for fx.Node(aten.addmm.default)[call_function]:Tensor(f32[4096, 1024]): Cannot find type promotion rule for op: aten.addmm.default\n\n## Additional Message:\n\n## Function Signature\n### Function Signature _TypePromotionInterpreter.run_node\n- self: \n- node: fx.Node(aten.addmm.default)[call_function]:Tensor(f32[4096, 1024])\n## Return values\nTensor(f32[4096, 1024])", + "text":"Skipped for fx.Node(aten.addmm.default)[call_function]:Tensor(f32[4096, 1024]): Cannot find type promotion rule for op: aten.addmm.default" + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":1625 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0015", + "stacks":[] + }, + { + "message":{ + "markdown":"Skipped for fx.Node(aten.view.default)[call_function]:Tensor(f32[4, 1024, 1024]): Cannot find type promotion rule for op: aten.view.default\n\n## Additional Message:\n\n## Function Signature\n### Function Signature _TypePromotionInterpreter.run_node\n- self: \n- node: fx.Node(aten.view.default)[call_function]:Tensor(f32[4, 1024, 1024])\n## Return values\nTensor(f32[4, 1024, 1024])", + "text":"Skipped for fx.Node(aten.view.default)[call_function]:Tensor(f32[4, 1024, 1024]): Cannot find type promotion rule for op: aten.view.default" + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":1625 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0015", + "stacks":[] + }, + { + "message":{ + "markdown":"Skipped for fx.Node(aten.clone.default)[call_function]:Tensor(f32[4, 1024, 1024]): Cannot find type promotion rule for op: aten.clone.default\n\n## Additional Message:\n\n## Function Signature\n### Function Signature _TypePromotionInterpreter.run_node\n- self: \n- node: fx.Node(aten.clone.default)[call_function]:Tensor(f32[4, 1024, 1024])\n## Return values\nTensor(f32[4, 1024, 1024])", + "text":"Skipped for fx.Node(aten.clone.default)[call_function]:Tensor(f32[4, 1024, 1024]): Cannot find type promotion rule for op: aten.clone.default" + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":1625 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0015", + "stacks":[] + }, + { + "message":{ + "markdown":"Type promotion not needed for add_22. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature _TypePromotionInterpreter.run_node\n- self: \n- node: fx.Node(aten.add.Tensor)[call_function]:Tensor(f32[4, 1024, 1024])\nFound type promotion rule: ElementwiseTypePromotionRule('aten', 'add', [0, 1], [], ELEMENTWISE_TYPE_PROMOTION_KIND.DEFAULT)\nArgument add_21 is not promoted. Already torch.float32.\nArgument clone_33 is not promoted. Already torch.float32.\n## Return values\nTensor(f32[4, 1024, 1024])", + "text":"Type promotion not needed for add_22. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":1625 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0015", + "stacks":[] + }, + { + "message":{ + "markdown":"Skipped for fx.Node(aten.native_layer_norm.default)[call_function]:Tuple[length=3](\nTensor(f32[4, 1024, 1024]),\nTensor(f32[4, 1024, 1]),\nTensor(f32[4, 1024, 1]),\n): Cannot find type promotion rule for op: aten.native_layer_norm.default\n\n## Additional Message:\n\n## Function Signature\n### Function Signature _TypePromotionInterpreter.run_node\n- self: \n- node: fx.Node(aten.native_layer_norm.default)[call_function]:Tuple[length=3](\nTensor(f32[4, 1024, 1024]),\nTensor(f32[4, 1024, 1]),\nTensor(f32[4, 1024, 1]),\n)\n## Return values\nTuple[length=3](\nTensor(f32[4, 1024, 1024]),\nTensor(f32[4, 1024, 1]),\nTensor(f32[4, 1024, 1]),\n)", + "text":"Skipped for fx.Node(aten.native_layer_norm.default)[call_function]:Tuple[length=3](\nTensor(f32[4, 1024, 1024]),\nTensor(f32[4, 1024, 1]),\nTensor(f32[4, 1024, 1]),\n): Cannot find type promotion rule for op: aten.native_layer_norm.default" + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":1625 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0015", + "stacks":[] + }, + { + "message":{ + "markdown":"Skipped for fx.Node()[call_function]:Tensor(f32[4, 1024, 1024]): node.target is not OpOverload. Got type: \n\n## Additional Message:\n\n## Function Signature\n### Function Signature _TypePromotionInterpreter.run_node\n- self: \n- node: fx.Node()[call_function]:Tensor(f32[4, 1024, 1024])\n## Return values\nTensor(f32[4, 1024, 1024])", + "text":"Skipped for fx.Node()[call_function]:Tensor(f32[4, 1024, 1024]): node.target is not OpOverload. Got type: " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":1625 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0015", + "stacks":[] + }, + { + "message":{ + "markdown":"Skipped for fx.Node(aten.view.default)[call_function]:Tensor(f32[4096, 1024]): Cannot find type promotion rule for op: aten.view.default\n\n## Additional Message:\n\n## Function Signature\n### Function Signature _TypePromotionInterpreter.run_node\n- self: \n- node: fx.Node(aten.view.default)[call_function]:Tensor(f32[4096, 1024])\n## Return values\nTensor(f32[4096, 1024])", + "text":"Skipped for fx.Node(aten.view.default)[call_function]:Tensor(f32[4096, 1024]): Cannot find type promotion rule for op: aten.view.default" + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":1625 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0015", + "stacks":[] + }, + { + "message":{ + "markdown":"Skipped for fx.Node(aten.t.default)[call_function]:Tensor(f32[1024, 3072]): Cannot find type promotion rule for op: aten.t.default\n\n## Additional Message:\n\n## Function Signature\n### Function Signature _TypePromotionInterpreter.run_node\n- self: \n- node: fx.Node(aten.t.default)[call_function]:Tensor(f32[1024, 3072])\n## Return values\nTensor(f32[1024, 3072])", + "text":"Skipped for fx.Node(aten.t.default)[call_function]:Tensor(f32[1024, 3072]): Cannot find type promotion rule for op: aten.t.default" + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":1625 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0015", + "stacks":[] + }, + { + "message":{ + "markdown":"Skipped for fx.Node(aten.addmm.default)[call_function]:Tensor(f32[4096, 3072]): Cannot find type promotion rule for op: aten.addmm.default\n\n## Additional Message:\n\n## Function Signature\n### Function Signature _TypePromotionInterpreter.run_node\n- self: \n- node: fx.Node(aten.addmm.default)[call_function]:Tensor(f32[4096, 3072])\n## Return values\nTensor(f32[4096, 3072])", + "text":"Skipped for fx.Node(aten.addmm.default)[call_function]:Tensor(f32[4096, 3072]): Cannot find type promotion rule for op: aten.addmm.default" + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":1625 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0015", + "stacks":[] + }, + { + "message":{ + "markdown":"Skipped for fx.Node(aten.view.default)[call_function]:Tensor(f32[4, 1024, 3072]): Cannot find type promotion rule for op: aten.view.default\n\n## Additional Message:\n\n## Function Signature\n### Function Signature _TypePromotionInterpreter.run_node\n- self: \n- node: fx.Node(aten.view.default)[call_function]:Tensor(f32[4, 1024, 3072])\n## Return values\nTensor(f32[4, 1024, 3072])", + "text":"Skipped for fx.Node(aten.view.default)[call_function]:Tensor(f32[4, 1024, 3072]): Cannot find type promotion rule for op: aten.view.default" + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":1625 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0015", + "stacks":[] + }, + { + "message":{ + "markdown":"Skipped for fx.Node(aten.view.default)[call_function]:Tensor(f32[4, 1024, 3, 16, 64]): Cannot find type promotion rule for op: aten.view.default\n\n## Additional Message:\n\n## Function Signature\n### Function Signature _TypePromotionInterpreter.run_node\n- self: \n- node: fx.Node(aten.view.default)[call_function]:Tensor(f32[4, 1024, 3, 16, 64])\n## Return values\nTensor(f32[4, 1024, 3, 16, 64])", + "text":"Skipped for fx.Node(aten.view.default)[call_function]:Tensor(f32[4, 1024, 3, 16, 64]): Cannot find type promotion rule for op: aten.view.default" + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":1625 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0015", + "stacks":[] + }, + { + "message":{ + "markdown":"Skipped for fx.Node(aten.permute.default)[call_function]:Tensor(f32[3, 4, 16, 1024, 64]): Cannot find type promotion rule for op: aten.permute.default\n\n## Additional Message:\n\n## Function Signature\n### Function Signature _TypePromotionInterpreter.run_node\n- self: \n- node: fx.Node(aten.permute.default)[call_function]:Tensor(f32[3, 4, 16, 1024, 64])\n## Return values\nTensor(f32[3, 4, 16, 1024, 64])", + "text":"Skipped for fx.Node(aten.permute.default)[call_function]:Tensor(f32[3, 4, 16, 1024, 64]): Cannot find type promotion rule for op: aten.permute.default" + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":1625 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0015", + "stacks":[] + }, + { + "message":{ + "markdown":"Skipped for fx.Node(aten.unbind.int)[call_function]:List[length=3](\nTensor(f32[4, 16, 1024, 64]),\nTensor(f32[4, 16, 1024, 64]),\nTensor(f32[4, 16, 1024, 64]),\n): Cannot find type promotion rule for op: aten.unbind.int\n\n## Additional Message:\n\n## Function Signature\n### Function Signature _TypePromotionInterpreter.run_node\n- self: \n- node: fx.Node(aten.unbind.int)[call_function]:List[length=3](\nTensor(f32[4, 16, 1024, 64]),\nTensor(f32[4, 16, 1024, 64]),\nTensor(f32[4, 16, 1024, 64]),\n)\n## Return values\nList[length=3](\nTensor(f32[4, 16, 1024, 64]),\nTensor(f32[4, 16, 1024, 64]),\nTensor(f32[4, 16, 1024, 64]),\n)", + "text":"Skipped for fx.Node(aten.unbind.int)[call_function]:List[length=3](\nTensor(f32[4, 16, 1024, 64]),\nTensor(f32[4, 16, 1024, 64]),\nTensor(f32[4, 16, 1024, 64]),\n): Cannot find type promotion rule for op: aten.unbind.int" + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":1625 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0015", + "stacks":[] + }, + { + "message":{ + "markdown":"Skipped for fx.Node()[call_function]:Tensor(f32[4, 16, 1024, 64]): node.target is not OpOverload. Got type: \n\n## Additional Message:\n\n## Function Signature\n### Function Signature _TypePromotionInterpreter.run_node\n- self: \n- node: fx.Node()[call_function]:Tensor(f32[4, 16, 1024, 64])\n## Return values\nTensor(f32[4, 16, 1024, 64])", + "text":"Skipped for fx.Node()[call_function]:Tensor(f32[4, 16, 1024, 64]): node.target is not OpOverload. Got type: " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":1625 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0015", + "stacks":[] + }, + { + "message":{ + "markdown":"Skipped for fx.Node()[call_function]:Tensor(f32[4, 16, 1024, 64]): node.target is not OpOverload. Got type: \n\n## Additional Message:\n\n## Function Signature\n### Function Signature _TypePromotionInterpreter.run_node\n- self: \n- node: fx.Node()[call_function]:Tensor(f32[4, 16, 1024, 64])\n## Return values\nTensor(f32[4, 16, 1024, 64])", + "text":"Skipped for fx.Node()[call_function]:Tensor(f32[4, 16, 1024, 64]): node.target is not OpOverload. Got type: " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":1625 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0015", + "stacks":[] + }, + { + "message":{ + "markdown":"Skipped for fx.Node()[call_function]:Tensor(f32[4, 16, 1024, 64]): node.target is not OpOverload. Got type: \n\n## Additional Message:\n\n## Function Signature\n### Function Signature _TypePromotionInterpreter.run_node\n- self: \n- node: fx.Node()[call_function]:Tensor(f32[4, 16, 1024, 64])\n## Return values\nTensor(f32[4, 16, 1024, 64])", + "text":"Skipped for fx.Node()[call_function]:Tensor(f32[4, 16, 1024, 64]): node.target is not OpOverload. Got type: " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":1625 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0015", + "stacks":[] + }, + { + "message":{ + "markdown":"Skipped for fx.Node(aten._scaled_dot_product_efficient_attention.default)[call_function]:Tuple[length=4](\nTensor(f32[4, 16, 1024, 64]),\nTensor(f32[4, 16, 0]),\nTensor(i64[]),\nTensor(i64[]),\n): Cannot find type promotion rule for op: aten._scaled_dot_product_efficient_attention.default\n\n## Additional Message:\n\n## Function Signature\n### Function Signature _TypePromotionInterpreter.run_node\n- self: \n- node: fx.Node(aten._scaled_dot_product_efficient_attention.default)[call_function]:Tuple[length=4](\nTensor(f32[4, 16, 1024, 64]),\nTensor(f32[4, 16, 0]),\nTensor(i64[]),\nTensor(i64[]),\n)\n## Return values\nTuple[length=4](\nTensor(f32[4, 16, 1024, 64]),\nTensor(f32[4, 16, 0]),\nTensor(i64[]),\nTensor(i64[]),\n)", + "text":"Skipped for fx.Node(aten._scaled_dot_product_efficient_attention.default)[call_function]:Tuple[length=4](\nTensor(f32[4, 16, 1024, 64]),\nTensor(f32[4, 16, 0]),\nTensor(i64[]),\nTensor(i64[]),\n): Cannot find type promotion rule for op: aten._scaled_dot_product_efficient_attention.default" + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":1625 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0015", + "stacks":[] + }, + { + "message":{ + "markdown":"Skipped for fx.Node()[call_function]:Tensor(f32[4, 16, 1024, 64]): node.target is not OpOverload. Got type: \n\n## Additional Message:\n\n## Function Signature\n### Function Signature _TypePromotionInterpreter.run_node\n- self: \n- node: fx.Node()[call_function]:Tensor(f32[4, 16, 1024, 64])\n## Return values\nTensor(f32[4, 16, 1024, 64])", + "text":"Skipped for fx.Node()[call_function]:Tensor(f32[4, 16, 1024, 64]): node.target is not OpOverload. Got type: " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":1625 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0015", + "stacks":[] + }, + { + "message":{ + "markdown":"Skipped for fx.Node(aten.transpose.int)[call_function]:Tensor(f32[4, 1024, 16, 64]): Cannot find type promotion rule for op: aten.transpose.int\n\n## Additional Message:\n\n## Function Signature\n### Function Signature _TypePromotionInterpreter.run_node\n- self: \n- node: fx.Node(aten.transpose.int)[call_function]:Tensor(f32[4, 1024, 16, 64])\n## Return values\nTensor(f32[4, 1024, 16, 64])", + "text":"Skipped for fx.Node(aten.transpose.int)[call_function]:Tensor(f32[4, 1024, 16, 64]): Cannot find type promotion rule for op: aten.transpose.int" + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":1625 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0015", + "stacks":[] + }, + { + "message":{ + "markdown":"Skipped for fx.Node(aten.view.default)[call_function]:Tensor(f32[4, 1024, 1024]): Cannot find type promotion rule for op: aten.view.default\n\n## Additional Message:\n\n## Function Signature\n### Function Signature _TypePromotionInterpreter.run_node\n- self: \n- node: fx.Node(aten.view.default)[call_function]:Tensor(f32[4, 1024, 1024])\n## Return values\nTensor(f32[4, 1024, 1024])", + "text":"Skipped for fx.Node(aten.view.default)[call_function]:Tensor(f32[4, 1024, 1024]): Cannot find type promotion rule for op: aten.view.default" + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":1625 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0015", + "stacks":[] + }, + { + "message":{ + "markdown":"Skipped for fx.Node(aten.view.default)[call_function]:Tensor(f32[4096, 1024]): Cannot find type promotion rule for op: aten.view.default\n\n## Additional Message:\n\n## Function Signature\n### Function Signature _TypePromotionInterpreter.run_node\n- self: \n- node: fx.Node(aten.view.default)[call_function]:Tensor(f32[4096, 1024])\n## Return values\nTensor(f32[4096, 1024])", + "text":"Skipped for fx.Node(aten.view.default)[call_function]:Tensor(f32[4096, 1024]): Cannot find type promotion rule for op: aten.view.default" + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":1625 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0015", + "stacks":[] + }, + { + "message":{ + "markdown":"Skipped for fx.Node(aten.t.default)[call_function]:Tensor(f32[1024, 1024]): Cannot find type promotion rule for op: aten.t.default\n\n## Additional Message:\n\n## Function Signature\n### Function Signature _TypePromotionInterpreter.run_node\n- self: \n- node: fx.Node(aten.t.default)[call_function]:Tensor(f32[1024, 1024])\n## Return values\nTensor(f32[1024, 1024])", + "text":"Skipped for fx.Node(aten.t.default)[call_function]:Tensor(f32[1024, 1024]): Cannot find type promotion rule for op: aten.t.default" + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":1625 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0015", + "stacks":[] + }, + { + "message":{ + "markdown":"Skipped for fx.Node(aten.addmm.default)[call_function]:Tensor(f32[4096, 1024]): Cannot find type promotion rule for op: aten.addmm.default\n\n## Additional Message:\n\n## Function Signature\n### Function Signature _TypePromotionInterpreter.run_node\n- self: \n- node: fx.Node(aten.addmm.default)[call_function]:Tensor(f32[4096, 1024])\n## Return values\nTensor(f32[4096, 1024])", + "text":"Skipped for fx.Node(aten.addmm.default)[call_function]:Tensor(f32[4096, 1024]): Cannot find type promotion rule for op: aten.addmm.default" + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":1625 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0015", + "stacks":[] + }, + { + "message":{ + "markdown":"Skipped for fx.Node(aten.view.default)[call_function]:Tensor(f32[4, 1024, 1024]): Cannot find type promotion rule for op: aten.view.default\n\n## Additional Message:\n\n## Function Signature\n### Function Signature _TypePromotionInterpreter.run_node\n- self: \n- node: fx.Node(aten.view.default)[call_function]:Tensor(f32[4, 1024, 1024])\n## Return values\nTensor(f32[4, 1024, 1024])", + "text":"Skipped for fx.Node(aten.view.default)[call_function]:Tensor(f32[4, 1024, 1024]): Cannot find type promotion rule for op: aten.view.default" + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":1625 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0015", + "stacks":[] + }, + { + "message":{ + "markdown":"Skipped for fx.Node(aten.clone.default)[call_function]:Tensor(f32[4, 1024, 1024]): Cannot find type promotion rule for op: aten.clone.default\n\n## Additional Message:\n\n## Function Signature\n### Function Signature _TypePromotionInterpreter.run_node\n- self: \n- node: fx.Node(aten.clone.default)[call_function]:Tensor(f32[4, 1024, 1024])\n## Return values\nTensor(f32[4, 1024, 1024])", + "text":"Skipped for fx.Node(aten.clone.default)[call_function]:Tensor(f32[4, 1024, 1024]): Cannot find type promotion rule for op: aten.clone.default" + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":1625 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0015", + "stacks":[] + }, + { + "message":{ + "markdown":"Type promotion not needed for add_23. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature _TypePromotionInterpreter.run_node\n- self: \n- node: fx.Node(aten.add.Tensor)[call_function]:Tensor(f32[4, 1024, 1024])\nFound type promotion rule: ElementwiseTypePromotionRule('aten', 'add', [0, 1], [], ELEMENTWISE_TYPE_PROMOTION_KIND.DEFAULT)\nArgument add_22 is not promoted. Already torch.float32.\nArgument clone_34 is not promoted. Already torch.float32.\n## Return values\nTensor(f32[4, 1024, 1024])", + "text":"Type promotion not needed for add_23. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":1625 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0015", + "stacks":[] + }, + { + "message":{ + "markdown":"Skipped for fx.Node(aten.native_layer_norm.default)[call_function]:Tuple[length=3](\nTensor(f32[4, 1024, 1024]),\nTensor(f32[4, 1024, 1]),\nTensor(f32[4, 1024, 1]),\n): Cannot find type promotion rule for op: aten.native_layer_norm.default\n\n## Additional Message:\n\n## Function Signature\n### Function Signature _TypePromotionInterpreter.run_node\n- self: \n- node: fx.Node(aten.native_layer_norm.default)[call_function]:Tuple[length=3](\nTensor(f32[4, 1024, 1024]),\nTensor(f32[4, 1024, 1]),\nTensor(f32[4, 1024, 1]),\n)\n## Return values\nTuple[length=3](\nTensor(f32[4, 1024, 1024]),\nTensor(f32[4, 1024, 1]),\nTensor(f32[4, 1024, 1]),\n)", + "text":"Skipped for fx.Node(aten.native_layer_norm.default)[call_function]:Tuple[length=3](\nTensor(f32[4, 1024, 1024]),\nTensor(f32[4, 1024, 1]),\nTensor(f32[4, 1024, 1]),\n): Cannot find type promotion rule for op: aten.native_layer_norm.default" + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":1625 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0015", + "stacks":[] + }, + { + "message":{ + "markdown":"Skipped for fx.Node()[call_function]:Tensor(f32[4, 1024, 1024]): node.target is not OpOverload. Got type: \n\n## Additional Message:\n\n## Function Signature\n### Function Signature _TypePromotionInterpreter.run_node\n- self: \n- node: fx.Node()[call_function]:Tensor(f32[4, 1024, 1024])\n## Return values\nTensor(f32[4, 1024, 1024])", + "text":"Skipped for fx.Node()[call_function]:Tensor(f32[4, 1024, 1024]): node.target is not OpOverload. Got type: " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":1625 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0015", + "stacks":[] + }, + { + "message":{ + "markdown":"Skipped for fx.Node(aten.view.default)[call_function]:Tensor(f32[4096, 1024]): Cannot find type promotion rule for op: aten.view.default\n\n## Additional Message:\n\n## Function Signature\n### Function Signature _TypePromotionInterpreter.run_node\n- self: \n- node: fx.Node(aten.view.default)[call_function]:Tensor(f32[4096, 1024])\n## Return values\nTensor(f32[4096, 1024])", + "text":"Skipped for fx.Node(aten.view.default)[call_function]:Tensor(f32[4096, 1024]): Cannot find type promotion rule for op: aten.view.default" + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":1625 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0015", + "stacks":[] + }, + { + "message":{ + "markdown":"Skipped for fx.Node(aten.t.default)[call_function]:Tensor(f32[1024, 4096]): Cannot find type promotion rule for op: aten.t.default\n\n## Additional Message:\n\n## Function Signature\n### Function Signature _TypePromotionInterpreter.run_node\n- self: \n- node: fx.Node(aten.t.default)[call_function]:Tensor(f32[1024, 4096])\n## Return values\nTensor(f32[1024, 4096])", + "text":"Skipped for fx.Node(aten.t.default)[call_function]:Tensor(f32[1024, 4096]): Cannot find type promotion rule for op: aten.t.default" + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":1625 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0015", + "stacks":[] + }, + { + "message":{ + "markdown":"Skipped for fx.Node(aten.addmm.default)[call_function]:Tensor(f32[4096, 4096]): Cannot find type promotion rule for op: aten.addmm.default\n\n## Additional Message:\n\n## Function Signature\n### Function Signature _TypePromotionInterpreter.run_node\n- self: \n- node: fx.Node(aten.addmm.default)[call_function]:Tensor(f32[4096, 4096])\n## Return values\nTensor(f32[4096, 4096])", + "text":"Skipped for fx.Node(aten.addmm.default)[call_function]:Tensor(f32[4096, 4096]): Cannot find type promotion rule for op: aten.addmm.default" + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":1625 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0015", + "stacks":[] + }, + { + "message":{ + "markdown":"Skipped for fx.Node(aten.view.default)[call_function]:Tensor(f32[4, 1024, 4096]): Cannot find type promotion rule for op: aten.view.default\n\n## Additional Message:\n\n## Function Signature\n### Function Signature _TypePromotionInterpreter.run_node\n- self: \n- node: fx.Node(aten.view.default)[call_function]:Tensor(f32[4, 1024, 4096])\n## Return values\nTensor(f32[4, 1024, 4096])", + "text":"Skipped for fx.Node(aten.view.default)[call_function]:Tensor(f32[4, 1024, 4096]): Cannot find type promotion rule for op: aten.view.default" + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":1625 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0015", + "stacks":[] + }, + { + "message":{ + "markdown":"Type promotion not needed for gelu_11. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature _TypePromotionInterpreter.run_node\n- self: \n- node: fx.Node(aten.gelu.default)[call_function]:Tensor(f32[4, 1024, 4096])\nFound type promotion rule: ElementwiseTypePromotionRule('aten', 'gelu', [0], [], ELEMENTWISE_TYPE_PROMOTION_KIND.DEFAULT)\nArgument view_118 is not promoted. Already torch.float32.\nArgument tanh is not promoted. Not mentioned by type promotion rule.\n## Return values\nTensor(f32[4, 1024, 4096])", + "text":"Type promotion not needed for gelu_11. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":1625 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0015", + "stacks":[] + }, + { + "message":{ + "markdown":"Skipped for fx.Node(aten.clone.default)[call_function]:Tensor(f32[4, 1024, 4096]): Cannot find type promotion rule for op: aten.clone.default\n\n## Additional Message:\n\n## Function Signature\n### Function Signature _TypePromotionInterpreter.run_node\n- self: \n- node: fx.Node(aten.clone.default)[call_function]:Tensor(f32[4, 1024, 4096])\n## Return values\nTensor(f32[4, 1024, 4096])", + "text":"Skipped for fx.Node(aten.clone.default)[call_function]:Tensor(f32[4, 1024, 4096]): Cannot find type promotion rule for op: aten.clone.default" + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":1625 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0015", + "stacks":[] + }, + { + "message":{ + "markdown":"Skipped for fx.Node(aten.view.default)[call_function]:Tensor(f32[4096, 4096]): Cannot find type promotion rule for op: aten.view.default\n\n## Additional Message:\n\n## Function Signature\n### Function Signature _TypePromotionInterpreter.run_node\n- self: \n- node: fx.Node(aten.view.default)[call_function]:Tensor(f32[4096, 4096])\n## Return values\nTensor(f32[4096, 4096])", + "text":"Skipped for fx.Node(aten.view.default)[call_function]:Tensor(f32[4096, 4096]): Cannot find type promotion rule for op: aten.view.default" + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":1625 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0015", + "stacks":[] + }, + { + "message":{ + "markdown":"Skipped for fx.Node(aten.t.default)[call_function]:Tensor(f32[4096, 1024]): Cannot find type promotion rule for op: aten.t.default\n\n## Additional Message:\n\n## Function Signature\n### Function Signature _TypePromotionInterpreter.run_node\n- self: \n- node: fx.Node(aten.t.default)[call_function]:Tensor(f32[4096, 1024])\n## Return values\nTensor(f32[4096, 1024])", + "text":"Skipped for fx.Node(aten.t.default)[call_function]:Tensor(f32[4096, 1024]): Cannot find type promotion rule for op: aten.t.default" + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":1625 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0015", + "stacks":[] + }, + { + "message":{ + "markdown":"Skipped for fx.Node(aten.addmm.default)[call_function]:Tensor(f32[4096, 1024]): Cannot find type promotion rule for op: aten.addmm.default\n\n## Additional Message:\n\n## Function Signature\n### Function Signature _TypePromotionInterpreter.run_node\n- self: \n- node: fx.Node(aten.addmm.default)[call_function]:Tensor(f32[4096, 1024])\n## Return values\nTensor(f32[4096, 1024])", + "text":"Skipped for fx.Node(aten.addmm.default)[call_function]:Tensor(f32[4096, 1024]): Cannot find type promotion rule for op: aten.addmm.default" + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":1625 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0015", + "stacks":[] + }, + { + "message":{ + "markdown":"Skipped for fx.Node(aten.view.default)[call_function]:Tensor(f32[4, 1024, 1024]): Cannot find type promotion rule for op: aten.view.default\n\n## Additional Message:\n\n## Function Signature\n### Function Signature _TypePromotionInterpreter.run_node\n- self: \n- node: fx.Node(aten.view.default)[call_function]:Tensor(f32[4, 1024, 1024])\n## Return values\nTensor(f32[4, 1024, 1024])", + "text":"Skipped for fx.Node(aten.view.default)[call_function]:Tensor(f32[4, 1024, 1024]): Cannot find type promotion rule for op: aten.view.default" + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":1625 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0015", + "stacks":[] + }, + { + "message":{ + "markdown":"Skipped for fx.Node(aten.clone.default)[call_function]:Tensor(f32[4, 1024, 1024]): Cannot find type promotion rule for op: aten.clone.default\n\n## Additional Message:\n\n## Function Signature\n### Function Signature _TypePromotionInterpreter.run_node\n- self: \n- node: fx.Node(aten.clone.default)[call_function]:Tensor(f32[4, 1024, 1024])\n## Return values\nTensor(f32[4, 1024, 1024])", + "text":"Skipped for fx.Node(aten.clone.default)[call_function]:Tensor(f32[4, 1024, 1024]): Cannot find type promotion rule for op: aten.clone.default" + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":1625 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0015", + "stacks":[] + }, + { + "message":{ + "markdown":"Type promotion not needed for add_24. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature _TypePromotionInterpreter.run_node\n- self: \n- node: fx.Node(aten.add.Tensor)[call_function]:Tensor(f32[4, 1024, 1024])\nFound type promotion rule: ElementwiseTypePromotionRule('aten', 'add', [0, 1], [], ELEMENTWISE_TYPE_PROMOTION_KIND.DEFAULT)\nArgument add_23 is not promoted. Already torch.float32.\nArgument clone_36 is not promoted. Already torch.float32.\n## Return values\nTensor(f32[4, 1024, 1024])", + "text":"Type promotion not needed for add_24. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":1625 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0015", + "stacks":[] + }, + { + "message":{ + "markdown":"Skipped for fx.Node(aten.native_layer_norm.default)[call_function]:Tuple[length=3](\nTensor(f32[4, 1024, 1024]),\nTensor(f32[4, 1024, 1]),\nTensor(f32[4, 1024, 1]),\n): Cannot find type promotion rule for op: aten.native_layer_norm.default\n\n## Additional Message:\n\n## Function Signature\n### Function Signature _TypePromotionInterpreter.run_node\n- self: \n- node: fx.Node(aten.native_layer_norm.default)[call_function]:Tuple[length=3](\nTensor(f32[4, 1024, 1024]),\nTensor(f32[4, 1024, 1]),\nTensor(f32[4, 1024, 1]),\n)\n## Return values\nTuple[length=3](\nTensor(f32[4, 1024, 1024]),\nTensor(f32[4, 1024, 1]),\nTensor(f32[4, 1024, 1]),\n)", + "text":"Skipped for fx.Node(aten.native_layer_norm.default)[call_function]:Tuple[length=3](\nTensor(f32[4, 1024, 1024]),\nTensor(f32[4, 1024, 1]),\nTensor(f32[4, 1024, 1]),\n): Cannot find type promotion rule for op: aten.native_layer_norm.default" + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":1625 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0015", + "stacks":[] + }, + { + "message":{ + "markdown":"Skipped for fx.Node()[call_function]:Tensor(f32[4, 1024, 1024]): node.target is not OpOverload. Got type: \n\n## Additional Message:\n\n## Function Signature\n### Function Signature _TypePromotionInterpreter.run_node\n- self: \n- node: fx.Node()[call_function]:Tensor(f32[4, 1024, 1024])\n## Return values\nTensor(f32[4, 1024, 1024])", + "text":"Skipped for fx.Node()[call_function]:Tensor(f32[4, 1024, 1024]): node.target is not OpOverload. Got type: " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":1625 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0015", + "stacks":[] + }, + { + "message":{ + "markdown":"Skipped for fx.Node(aten.view.default)[call_function]:Tensor(f32[4096, 1024]): Cannot find type promotion rule for op: aten.view.default\n\n## Additional Message:\n\n## Function Signature\n### Function Signature _TypePromotionInterpreter.run_node\n- self: \n- node: fx.Node(aten.view.default)[call_function]:Tensor(f32[4096, 1024])\n## Return values\nTensor(f32[4096, 1024])", + "text":"Skipped for fx.Node(aten.view.default)[call_function]:Tensor(f32[4096, 1024]): Cannot find type promotion rule for op: aten.view.default" + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":1625 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0015", + "stacks":[] + }, + { + "message":{ + "markdown":"Skipped for fx.Node(aten.t.default)[call_function]:Tensor(f32[1024, 3072]): Cannot find type promotion rule for op: aten.t.default\n\n## Additional Message:\n\n## Function Signature\n### Function Signature _TypePromotionInterpreter.run_node\n- self: \n- node: fx.Node(aten.t.default)[call_function]:Tensor(f32[1024, 3072])\n## Return values\nTensor(f32[1024, 3072])", + "text":"Skipped for fx.Node(aten.t.default)[call_function]:Tensor(f32[1024, 3072]): Cannot find type promotion rule for op: aten.t.default" + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":1625 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0015", + "stacks":[] + }, + { + "message":{ + "markdown":"Skipped for fx.Node(aten.addmm.default)[call_function]:Tensor(f32[4096, 3072]): Cannot find type promotion rule for op: aten.addmm.default\n\n## Additional Message:\n\n## Function Signature\n### Function Signature _TypePromotionInterpreter.run_node\n- self: \n- node: fx.Node(aten.addmm.default)[call_function]:Tensor(f32[4096, 3072])\n## Return values\nTensor(f32[4096, 3072])", + "text":"Skipped for fx.Node(aten.addmm.default)[call_function]:Tensor(f32[4096, 3072]): Cannot find type promotion rule for op: aten.addmm.default" + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":1625 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0015", + "stacks":[] + }, + { + "message":{ + "markdown":"Skipped for fx.Node(aten.view.default)[call_function]:Tensor(f32[4, 1024, 3072]): Cannot find type promotion rule for op: aten.view.default\n\n## Additional Message:\n\n## Function Signature\n### Function Signature _TypePromotionInterpreter.run_node\n- self: \n- node: fx.Node(aten.view.default)[call_function]:Tensor(f32[4, 1024, 3072])\n## Return values\nTensor(f32[4, 1024, 3072])", + "text":"Skipped for fx.Node(aten.view.default)[call_function]:Tensor(f32[4, 1024, 3072]): Cannot find type promotion rule for op: aten.view.default" + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":1625 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0015", + "stacks":[] + }, + { + "message":{ + "markdown":"Skipped for fx.Node(aten.view.default)[call_function]:Tensor(f32[4, 1024, 3, 16, 64]): Cannot find type promotion rule for op: aten.view.default\n\n## Additional Message:\n\n## Function Signature\n### Function Signature _TypePromotionInterpreter.run_node\n- self: \n- node: fx.Node(aten.view.default)[call_function]:Tensor(f32[4, 1024, 3, 16, 64])\n## Return values\nTensor(f32[4, 1024, 3, 16, 64])", + "text":"Skipped for fx.Node(aten.view.default)[call_function]:Tensor(f32[4, 1024, 3, 16, 64]): Cannot find type promotion rule for op: aten.view.default" + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":1625 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0015", + "stacks":[] + }, + { + "message":{ + "markdown":"Skipped for fx.Node(aten.permute.default)[call_function]:Tensor(f32[3, 4, 16, 1024, 64]): Cannot find type promotion rule for op: aten.permute.default\n\n## Additional Message:\n\n## Function Signature\n### Function Signature _TypePromotionInterpreter.run_node\n- self: \n- node: fx.Node(aten.permute.default)[call_function]:Tensor(f32[3, 4, 16, 1024, 64])\n## Return values\nTensor(f32[3, 4, 16, 1024, 64])", + "text":"Skipped for fx.Node(aten.permute.default)[call_function]:Tensor(f32[3, 4, 16, 1024, 64]): Cannot find type promotion rule for op: aten.permute.default" + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":1625 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0015", + "stacks":[] + }, + { + "message":{ + "markdown":"Skipped for fx.Node(aten.unbind.int)[call_function]:List[length=3](\nTensor(f32[4, 16, 1024, 64]),\nTensor(f32[4, 16, 1024, 64]),\nTensor(f32[4, 16, 1024, 64]),\n): Cannot find type promotion rule for op: aten.unbind.int\n\n## Additional Message:\n\n## Function Signature\n### Function Signature _TypePromotionInterpreter.run_node\n- self: \n- node: fx.Node(aten.unbind.int)[call_function]:List[length=3](\nTensor(f32[4, 16, 1024, 64]),\nTensor(f32[4, 16, 1024, 64]),\nTensor(f32[4, 16, 1024, 64]),\n)\n## Return values\nList[length=3](\nTensor(f32[4, 16, 1024, 64]),\nTensor(f32[4, 16, 1024, 64]),\nTensor(f32[4, 16, 1024, 64]),\n)", + "text":"Skipped for fx.Node(aten.unbind.int)[call_function]:List[length=3](\nTensor(f32[4, 16, 1024, 64]),\nTensor(f32[4, 16, 1024, 64]),\nTensor(f32[4, 16, 1024, 64]),\n): Cannot find type promotion rule for op: aten.unbind.int" + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":1625 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0015", + "stacks":[] + }, + { + "message":{ + "markdown":"Skipped for fx.Node()[call_function]:Tensor(f32[4, 16, 1024, 64]): node.target is not OpOverload. Got type: \n\n## Additional Message:\n\n## Function Signature\n### Function Signature _TypePromotionInterpreter.run_node\n- self: \n- node: fx.Node()[call_function]:Tensor(f32[4, 16, 1024, 64])\n## Return values\nTensor(f32[4, 16, 1024, 64])", + "text":"Skipped for fx.Node()[call_function]:Tensor(f32[4, 16, 1024, 64]): node.target is not OpOverload. Got type: " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":1625 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0015", + "stacks":[] + }, + { + "message":{ + "markdown":"Skipped for fx.Node()[call_function]:Tensor(f32[4, 16, 1024, 64]): node.target is not OpOverload. Got type: \n\n## Additional Message:\n\n## Function Signature\n### Function Signature _TypePromotionInterpreter.run_node\n- self: \n- node: fx.Node()[call_function]:Tensor(f32[4, 16, 1024, 64])\n## Return values\nTensor(f32[4, 16, 1024, 64])", + "text":"Skipped for fx.Node()[call_function]:Tensor(f32[4, 16, 1024, 64]): node.target is not OpOverload. Got type: " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":1625 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0015", + "stacks":[] + }, + { + "message":{ + "markdown":"Skipped for fx.Node()[call_function]:Tensor(f32[4, 16, 1024, 64]): node.target is not OpOverload. Got type: \n\n## Additional Message:\n\n## Function Signature\n### Function Signature _TypePromotionInterpreter.run_node\n- self: \n- node: fx.Node()[call_function]:Tensor(f32[4, 16, 1024, 64])\n## Return values\nTensor(f32[4, 16, 1024, 64])", + "text":"Skipped for fx.Node()[call_function]:Tensor(f32[4, 16, 1024, 64]): node.target is not OpOverload. Got type: " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":1625 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0015", + "stacks":[] + }, + { + "message":{ + "markdown":"Skipped for fx.Node(aten._scaled_dot_product_efficient_attention.default)[call_function]:Tuple[length=4](\nTensor(f32[4, 16, 1024, 64]),\nTensor(f32[4, 16, 0]),\nTensor(i64[]),\nTensor(i64[]),\n): Cannot find type promotion rule for op: aten._scaled_dot_product_efficient_attention.default\n\n## Additional Message:\n\n## Function Signature\n### Function Signature _TypePromotionInterpreter.run_node\n- self: \n- node: fx.Node(aten._scaled_dot_product_efficient_attention.default)[call_function]:Tuple[length=4](\nTensor(f32[4, 16, 1024, 64]),\nTensor(f32[4, 16, 0]),\nTensor(i64[]),\nTensor(i64[]),\n)\n## Return values\nTuple[length=4](\nTensor(f32[4, 16, 1024, 64]),\nTensor(f32[4, 16, 0]),\nTensor(i64[]),\nTensor(i64[]),\n)", + "text":"Skipped for fx.Node(aten._scaled_dot_product_efficient_attention.default)[call_function]:Tuple[length=4](\nTensor(f32[4, 16, 1024, 64]),\nTensor(f32[4, 16, 0]),\nTensor(i64[]),\nTensor(i64[]),\n): Cannot find type promotion rule for op: aten._scaled_dot_product_efficient_attention.default" + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":1625 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0015", + "stacks":[] + }, + { + "message":{ + "markdown":"Skipped for fx.Node()[call_function]:Tensor(f32[4, 16, 1024, 64]): node.target is not OpOverload. Got type: \n\n## Additional Message:\n\n## Function Signature\n### Function Signature _TypePromotionInterpreter.run_node\n- self: \n- node: fx.Node()[call_function]:Tensor(f32[4, 16, 1024, 64])\n## Return values\nTensor(f32[4, 16, 1024, 64])", + "text":"Skipped for fx.Node()[call_function]:Tensor(f32[4, 16, 1024, 64]): node.target is not OpOverload. Got type: " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":1625 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0015", + "stacks":[] + }, + { + "message":{ + "markdown":"Skipped for fx.Node(aten.transpose.int)[call_function]:Tensor(f32[4, 1024, 16, 64]): Cannot find type promotion rule for op: aten.transpose.int\n\n## Additional Message:\n\n## Function Signature\n### Function Signature _TypePromotionInterpreter.run_node\n- self: \n- node: fx.Node(aten.transpose.int)[call_function]:Tensor(f32[4, 1024, 16, 64])\n## Return values\nTensor(f32[4, 1024, 16, 64])", + "text":"Skipped for fx.Node(aten.transpose.int)[call_function]:Tensor(f32[4, 1024, 16, 64]): Cannot find type promotion rule for op: aten.transpose.int" + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":1625 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0015", + "stacks":[] + }, + { + "message":{ + "markdown":"Skipped for fx.Node(aten.view.default)[call_function]:Tensor(f32[4, 1024, 1024]): Cannot find type promotion rule for op: aten.view.default\n\n## Additional Message:\n\n## Function Signature\n### Function Signature _TypePromotionInterpreter.run_node\n- self: \n- node: fx.Node(aten.view.default)[call_function]:Tensor(f32[4, 1024, 1024])\n## Return values\nTensor(f32[4, 1024, 1024])", + "text":"Skipped for fx.Node(aten.view.default)[call_function]:Tensor(f32[4, 1024, 1024]): Cannot find type promotion rule for op: aten.view.default" + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":1625 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0015", + "stacks":[] + }, + { + "message":{ + "markdown":"Skipped for fx.Node(aten.view.default)[call_function]:Tensor(f32[4096, 1024]): Cannot find type promotion rule for op: aten.view.default\n\n## Additional Message:\n\n## Function Signature\n### Function Signature _TypePromotionInterpreter.run_node\n- self: \n- node: fx.Node(aten.view.default)[call_function]:Tensor(f32[4096, 1024])\n## Return values\nTensor(f32[4096, 1024])", + "text":"Skipped for fx.Node(aten.view.default)[call_function]:Tensor(f32[4096, 1024]): Cannot find type promotion rule for op: aten.view.default" + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":1625 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0015", + "stacks":[] + }, + { + "message":{ + "markdown":"Skipped for fx.Node(aten.t.default)[call_function]:Tensor(f32[1024, 1024]): Cannot find type promotion rule for op: aten.t.default\n\n## Additional Message:\n\n## Function Signature\n### Function Signature _TypePromotionInterpreter.run_node\n- self: \n- node: fx.Node(aten.t.default)[call_function]:Tensor(f32[1024, 1024])\n## Return values\nTensor(f32[1024, 1024])", + "text":"Skipped for fx.Node(aten.t.default)[call_function]:Tensor(f32[1024, 1024]): Cannot find type promotion rule for op: aten.t.default" + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":1625 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0015", + "stacks":[] + }, + { + "message":{ + "markdown":"Skipped for fx.Node(aten.addmm.default)[call_function]:Tensor(f32[4096, 1024]): Cannot find type promotion rule for op: aten.addmm.default\n\n## Additional Message:\n\n## Function Signature\n### Function Signature _TypePromotionInterpreter.run_node\n- self: \n- node: fx.Node(aten.addmm.default)[call_function]:Tensor(f32[4096, 1024])\n## Return values\nTensor(f32[4096, 1024])", + "text":"Skipped for fx.Node(aten.addmm.default)[call_function]:Tensor(f32[4096, 1024]): Cannot find type promotion rule for op: aten.addmm.default" + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":1625 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0015", + "stacks":[] + }, + { + "message":{ + "markdown":"Skipped for fx.Node(aten.view.default)[call_function]:Tensor(f32[4, 1024, 1024]): Cannot find type promotion rule for op: aten.view.default\n\n## Additional Message:\n\n## Function Signature\n### Function Signature _TypePromotionInterpreter.run_node\n- self: \n- node: fx.Node(aten.view.default)[call_function]:Tensor(f32[4, 1024, 1024])\n## Return values\nTensor(f32[4, 1024, 1024])", + "text":"Skipped for fx.Node(aten.view.default)[call_function]:Tensor(f32[4, 1024, 1024]): Cannot find type promotion rule for op: aten.view.default" + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":1625 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0015", + "stacks":[] + }, + { + "message":{ + "markdown":"Skipped for fx.Node(aten.clone.default)[call_function]:Tensor(f32[4, 1024, 1024]): Cannot find type promotion rule for op: aten.clone.default\n\n## Additional Message:\n\n## Function Signature\n### Function Signature _TypePromotionInterpreter.run_node\n- self: \n- node: fx.Node(aten.clone.default)[call_function]:Tensor(f32[4, 1024, 1024])\n## Return values\nTensor(f32[4, 1024, 1024])", + "text":"Skipped for fx.Node(aten.clone.default)[call_function]:Tensor(f32[4, 1024, 1024]): Cannot find type promotion rule for op: aten.clone.default" + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":1625 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0015", + "stacks":[] + }, + { + "message":{ + "markdown":"Type promotion not needed for add_25. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature _TypePromotionInterpreter.run_node\n- self: \n- node: fx.Node(aten.add.Tensor)[call_function]:Tensor(f32[4, 1024, 1024])\nFound type promotion rule: ElementwiseTypePromotionRule('aten', 'add', [0, 1], [], ELEMENTWISE_TYPE_PROMOTION_KIND.DEFAULT)\nArgument add_24 is not promoted. Already torch.float32.\nArgument clone_37 is not promoted. Already torch.float32.\n## Return values\nTensor(f32[4, 1024, 1024])", + "text":"Type promotion not needed for add_25. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":1625 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0015", + "stacks":[] + }, + { + "message":{ + "markdown":"Skipped for fx.Node(aten.native_layer_norm.default)[call_function]:Tuple[length=3](\nTensor(f32[4, 1024, 1024]),\nTensor(f32[4, 1024, 1]),\nTensor(f32[4, 1024, 1]),\n): Cannot find type promotion rule for op: aten.native_layer_norm.default\n\n## Additional Message:\n\n## Function Signature\n### Function Signature _TypePromotionInterpreter.run_node\n- self: \n- node: fx.Node(aten.native_layer_norm.default)[call_function]:Tuple[length=3](\nTensor(f32[4, 1024, 1024]),\nTensor(f32[4, 1024, 1]),\nTensor(f32[4, 1024, 1]),\n)\n## Return values\nTuple[length=3](\nTensor(f32[4, 1024, 1024]),\nTensor(f32[4, 1024, 1]),\nTensor(f32[4, 1024, 1]),\n)", + "text":"Skipped for fx.Node(aten.native_layer_norm.default)[call_function]:Tuple[length=3](\nTensor(f32[4, 1024, 1024]),\nTensor(f32[4, 1024, 1]),\nTensor(f32[4, 1024, 1]),\n): Cannot find type promotion rule for op: aten.native_layer_norm.default" + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":1625 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0015", + "stacks":[] + }, + { + "message":{ + "markdown":"Skipped for fx.Node()[call_function]:Tensor(f32[4, 1024, 1024]): node.target is not OpOverload. Got type: \n\n## Additional Message:\n\n## Function Signature\n### Function Signature _TypePromotionInterpreter.run_node\n- self: \n- node: fx.Node()[call_function]:Tensor(f32[4, 1024, 1024])\n## Return values\nTensor(f32[4, 1024, 1024])", + "text":"Skipped for fx.Node()[call_function]:Tensor(f32[4, 1024, 1024]): node.target is not OpOverload. Got type: " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":1625 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0015", + "stacks":[] + }, + { + "message":{ + "markdown":"Skipped for fx.Node(aten.view.default)[call_function]:Tensor(f32[4096, 1024]): Cannot find type promotion rule for op: aten.view.default\n\n## Additional Message:\n\n## Function Signature\n### Function Signature _TypePromotionInterpreter.run_node\n- self: \n- node: fx.Node(aten.view.default)[call_function]:Tensor(f32[4096, 1024])\n## Return values\nTensor(f32[4096, 1024])", + "text":"Skipped for fx.Node(aten.view.default)[call_function]:Tensor(f32[4096, 1024]): Cannot find type promotion rule for op: aten.view.default" + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":1625 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0015", + "stacks":[] + }, + { + "message":{ + "markdown":"Skipped for fx.Node(aten.t.default)[call_function]:Tensor(f32[1024, 4096]): Cannot find type promotion rule for op: aten.t.default\n\n## Additional Message:\n\n## Function Signature\n### Function Signature _TypePromotionInterpreter.run_node\n- self: \n- node: fx.Node(aten.t.default)[call_function]:Tensor(f32[1024, 4096])\n## Return values\nTensor(f32[1024, 4096])", + "text":"Skipped for fx.Node(aten.t.default)[call_function]:Tensor(f32[1024, 4096]): Cannot find type promotion rule for op: aten.t.default" + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":1625 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0015", + "stacks":[] + }, + { + "message":{ + "markdown":"Skipped for fx.Node(aten.addmm.default)[call_function]:Tensor(f32[4096, 4096]): Cannot find type promotion rule for op: aten.addmm.default\n\n## Additional Message:\n\n## Function Signature\n### Function Signature _TypePromotionInterpreter.run_node\n- self: \n- node: fx.Node(aten.addmm.default)[call_function]:Tensor(f32[4096, 4096])\n## Return values\nTensor(f32[4096, 4096])", + "text":"Skipped for fx.Node(aten.addmm.default)[call_function]:Tensor(f32[4096, 4096]): Cannot find type promotion rule for op: aten.addmm.default" + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":1625 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0015", + "stacks":[] + }, + { + "message":{ + "markdown":"Skipped for fx.Node(aten.view.default)[call_function]:Tensor(f32[4, 1024, 4096]): Cannot find type promotion rule for op: aten.view.default\n\n## Additional Message:\n\n## Function Signature\n### Function Signature _TypePromotionInterpreter.run_node\n- self: \n- node: fx.Node(aten.view.default)[call_function]:Tensor(f32[4, 1024, 4096])\n## Return values\nTensor(f32[4, 1024, 4096])", + "text":"Skipped for fx.Node(aten.view.default)[call_function]:Tensor(f32[4, 1024, 4096]): Cannot find type promotion rule for op: aten.view.default" + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":1625 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0015", + "stacks":[] + }, + { + "message":{ + "markdown":"Type promotion not needed for gelu_12. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature _TypePromotionInterpreter.run_node\n- self: \n- node: fx.Node(aten.gelu.default)[call_function]:Tensor(f32[4, 1024, 4096])\nFound type promotion rule: ElementwiseTypePromotionRule('aten', 'gelu', [0], [], ELEMENTWISE_TYPE_PROMOTION_KIND.DEFAULT)\nArgument view_128 is not promoted. Already torch.float32.\nArgument tanh is not promoted. Not mentioned by type promotion rule.\n## Return values\nTensor(f32[4, 1024, 4096])", + "text":"Type promotion not needed for gelu_12. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":1625 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0015", + "stacks":[] + }, + { + "message":{ + "markdown":"Skipped for fx.Node(aten.clone.default)[call_function]:Tensor(f32[4, 1024, 4096]): Cannot find type promotion rule for op: aten.clone.default\n\n## Additional Message:\n\n## Function Signature\n### Function Signature _TypePromotionInterpreter.run_node\n- self: \n- node: fx.Node(aten.clone.default)[call_function]:Tensor(f32[4, 1024, 4096])\n## Return values\nTensor(f32[4, 1024, 4096])", + "text":"Skipped for fx.Node(aten.clone.default)[call_function]:Tensor(f32[4, 1024, 4096]): Cannot find type promotion rule for op: aten.clone.default" + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":1625 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0015", + "stacks":[] + }, + { + "message":{ + "markdown":"Skipped for fx.Node(aten.view.default)[call_function]:Tensor(f32[4096, 4096]): Cannot find type promotion rule for op: aten.view.default\n\n## Additional Message:\n\n## Function Signature\n### Function Signature _TypePromotionInterpreter.run_node\n- self: \n- node: fx.Node(aten.view.default)[call_function]:Tensor(f32[4096, 4096])\n## Return values\nTensor(f32[4096, 4096])", + "text":"Skipped for fx.Node(aten.view.default)[call_function]:Tensor(f32[4096, 4096]): Cannot find type promotion rule for op: aten.view.default" + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":1625 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0015", + "stacks":[] + }, + { + "message":{ + "markdown":"Skipped for fx.Node(aten.t.default)[call_function]:Tensor(f32[4096, 1024]): Cannot find type promotion rule for op: aten.t.default\n\n## Additional Message:\n\n## Function Signature\n### Function Signature _TypePromotionInterpreter.run_node\n- self: \n- node: fx.Node(aten.t.default)[call_function]:Tensor(f32[4096, 1024])\n## Return values\nTensor(f32[4096, 1024])", + "text":"Skipped for fx.Node(aten.t.default)[call_function]:Tensor(f32[4096, 1024]): Cannot find type promotion rule for op: aten.t.default" + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":1625 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0015", + "stacks":[] + }, + { + "message":{ + "markdown":"Skipped for fx.Node(aten.addmm.default)[call_function]:Tensor(f32[4096, 1024]): Cannot find type promotion rule for op: aten.addmm.default\n\n## Additional Message:\n\n## Function Signature\n### Function Signature _TypePromotionInterpreter.run_node\n- self: \n- node: fx.Node(aten.addmm.default)[call_function]:Tensor(f32[4096, 1024])\n## Return values\nTensor(f32[4096, 1024])", + "text":"Skipped for fx.Node(aten.addmm.default)[call_function]:Tensor(f32[4096, 1024]): Cannot find type promotion rule for op: aten.addmm.default" + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":1625 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0015", + "stacks":[] + }, + { + "message":{ + "markdown":"Skipped for fx.Node(aten.view.default)[call_function]:Tensor(f32[4, 1024, 1024]): Cannot find type promotion rule for op: aten.view.default\n\n## Additional Message:\n\n## Function Signature\n### Function Signature _TypePromotionInterpreter.run_node\n- self: \n- node: fx.Node(aten.view.default)[call_function]:Tensor(f32[4, 1024, 1024])\n## Return values\nTensor(f32[4, 1024, 1024])", + "text":"Skipped for fx.Node(aten.view.default)[call_function]:Tensor(f32[4, 1024, 1024]): Cannot find type promotion rule for op: aten.view.default" + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":1625 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0015", + "stacks":[] + }, + { + "message":{ + "markdown":"Skipped for fx.Node(aten.clone.default)[call_function]:Tensor(f32[4, 1024, 1024]): Cannot find type promotion rule for op: aten.clone.default\n\n## Additional Message:\n\n## Function Signature\n### Function Signature _TypePromotionInterpreter.run_node\n- self: \n- node: fx.Node(aten.clone.default)[call_function]:Tensor(f32[4, 1024, 1024])\n## Return values\nTensor(f32[4, 1024, 1024])", + "text":"Skipped for fx.Node(aten.clone.default)[call_function]:Tensor(f32[4, 1024, 1024]): Cannot find type promotion rule for op: aten.clone.default" + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":1625 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0015", + "stacks":[] + }, + { + "message":{ + "markdown":"Type promotion not needed for add_26. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature _TypePromotionInterpreter.run_node\n- self: \n- node: fx.Node(aten.add.Tensor)[call_function]:Tensor(f32[4, 1024, 1024])\nFound type promotion rule: ElementwiseTypePromotionRule('aten', 'add', [0, 1], [], ELEMENTWISE_TYPE_PROMOTION_KIND.DEFAULT)\nArgument add_25 is not promoted. Already torch.float32.\nArgument clone_39 is not promoted. Already torch.float32.\n## Return values\nTensor(f32[4, 1024, 1024])", + "text":"Type promotion not needed for add_26. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":1625 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0015", + "stacks":[] + }, + { + "message":{ + "markdown":"Skipped for fx.Node(aten.native_layer_norm.default)[call_function]:Tuple[length=3](\nTensor(f32[4, 1024, 1024]),\nTensor(f32[4, 1024, 1]),\nTensor(f32[4, 1024, 1]),\n): Cannot find type promotion rule for op: aten.native_layer_norm.default\n\n## Additional Message:\n\n## Function Signature\n### Function Signature _TypePromotionInterpreter.run_node\n- self: \n- node: fx.Node(aten.native_layer_norm.default)[call_function]:Tuple[length=3](\nTensor(f32[4, 1024, 1024]),\nTensor(f32[4, 1024, 1]),\nTensor(f32[4, 1024, 1]),\n)\n## Return values\nTuple[length=3](\nTensor(f32[4, 1024, 1024]),\nTensor(f32[4, 1024, 1]),\nTensor(f32[4, 1024, 1]),\n)", + "text":"Skipped for fx.Node(aten.native_layer_norm.default)[call_function]:Tuple[length=3](\nTensor(f32[4, 1024, 1024]),\nTensor(f32[4, 1024, 1]),\nTensor(f32[4, 1024, 1]),\n): Cannot find type promotion rule for op: aten.native_layer_norm.default" + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":1625 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0015", + "stacks":[] + }, + { + "message":{ + "markdown":"Skipped for fx.Node()[call_function]:Tensor(f32[4, 1024, 1024]): node.target is not OpOverload. Got type: \n\n## Additional Message:\n\n## Function Signature\n### Function Signature _TypePromotionInterpreter.run_node\n- self: \n- node: fx.Node()[call_function]:Tensor(f32[4, 1024, 1024])\n## Return values\nTensor(f32[4, 1024, 1024])", + "text":"Skipped for fx.Node()[call_function]:Tensor(f32[4, 1024, 1024]): node.target is not OpOverload. Got type: " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":1625 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0015", + "stacks":[] + }, + { + "message":{ + "markdown":"Skipped for fx.Node(aten.view.default)[call_function]:Tensor(f32[4096, 1024]): Cannot find type promotion rule for op: aten.view.default\n\n## Additional Message:\n\n## Function Signature\n### Function Signature _TypePromotionInterpreter.run_node\n- self: \n- node: fx.Node(aten.view.default)[call_function]:Tensor(f32[4096, 1024])\n## Return values\nTensor(f32[4096, 1024])", + "text":"Skipped for fx.Node(aten.view.default)[call_function]:Tensor(f32[4096, 1024]): Cannot find type promotion rule for op: aten.view.default" + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":1625 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0015", + "stacks":[] + }, + { + "message":{ + "markdown":"Skipped for fx.Node(aten.t.default)[call_function]:Tensor(f32[1024, 3072]): Cannot find type promotion rule for op: aten.t.default\n\n## Additional Message:\n\n## Function Signature\n### Function Signature _TypePromotionInterpreter.run_node\n- self: \n- node: fx.Node(aten.t.default)[call_function]:Tensor(f32[1024, 3072])\n## Return values\nTensor(f32[1024, 3072])", + "text":"Skipped for fx.Node(aten.t.default)[call_function]:Tensor(f32[1024, 3072]): Cannot find type promotion rule for op: aten.t.default" + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":1625 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0015", + "stacks":[] + }, + { + "message":{ + "markdown":"Skipped for fx.Node(aten.addmm.default)[call_function]:Tensor(f32[4096, 3072]): Cannot find type promotion rule for op: aten.addmm.default\n\n## Additional Message:\n\n## Function Signature\n### Function Signature _TypePromotionInterpreter.run_node\n- self: \n- node: fx.Node(aten.addmm.default)[call_function]:Tensor(f32[4096, 3072])\n## Return values\nTensor(f32[4096, 3072])", + "text":"Skipped for fx.Node(aten.addmm.default)[call_function]:Tensor(f32[4096, 3072]): Cannot find type promotion rule for op: aten.addmm.default" + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":1625 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0015", + "stacks":[] + }, + { + "message":{ + "markdown":"Skipped for fx.Node(aten.view.default)[call_function]:Tensor(f32[4, 1024, 3072]): Cannot find type promotion rule for op: aten.view.default\n\n## Additional Message:\n\n## Function Signature\n### Function Signature _TypePromotionInterpreter.run_node\n- self: \n- node: fx.Node(aten.view.default)[call_function]:Tensor(f32[4, 1024, 3072])\n## Return values\nTensor(f32[4, 1024, 3072])", + "text":"Skipped for fx.Node(aten.view.default)[call_function]:Tensor(f32[4, 1024, 3072]): Cannot find type promotion rule for op: aten.view.default" + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":1625 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0015", + "stacks":[] + }, + { + "message":{ + "markdown":"Skipped for fx.Node(aten.view.default)[call_function]:Tensor(f32[4, 1024, 3, 16, 64]): Cannot find type promotion rule for op: aten.view.default\n\n## Additional Message:\n\n## Function Signature\n### Function Signature _TypePromotionInterpreter.run_node\n- self: \n- node: fx.Node(aten.view.default)[call_function]:Tensor(f32[4, 1024, 3, 16, 64])\n## Return values\nTensor(f32[4, 1024, 3, 16, 64])", + "text":"Skipped for fx.Node(aten.view.default)[call_function]:Tensor(f32[4, 1024, 3, 16, 64]): Cannot find type promotion rule for op: aten.view.default" + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":1625 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0015", + "stacks":[] + }, + { + "message":{ + "markdown":"Skipped for fx.Node(aten.permute.default)[call_function]:Tensor(f32[3, 4, 16, 1024, 64]): Cannot find type promotion rule for op: aten.permute.default\n\n## Additional Message:\n\n## Function Signature\n### Function Signature _TypePromotionInterpreter.run_node\n- self: \n- node: fx.Node(aten.permute.default)[call_function]:Tensor(f32[3, 4, 16, 1024, 64])\n## Return values\nTensor(f32[3, 4, 16, 1024, 64])", + "text":"Skipped for fx.Node(aten.permute.default)[call_function]:Tensor(f32[3, 4, 16, 1024, 64]): Cannot find type promotion rule for op: aten.permute.default" + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":1625 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0015", + "stacks":[] + }, + { + "message":{ + "markdown":"Skipped for fx.Node(aten.unbind.int)[call_function]:List[length=3](\nTensor(f32[4, 16, 1024, 64]),\nTensor(f32[4, 16, 1024, 64]),\nTensor(f32[4, 16, 1024, 64]),\n): Cannot find type promotion rule for op: aten.unbind.int\n\n## Additional Message:\n\n## Function Signature\n### Function Signature _TypePromotionInterpreter.run_node\n- self: \n- node: fx.Node(aten.unbind.int)[call_function]:List[length=3](\nTensor(f32[4, 16, 1024, 64]),\nTensor(f32[4, 16, 1024, 64]),\nTensor(f32[4, 16, 1024, 64]),\n)\n## Return values\nList[length=3](\nTensor(f32[4, 16, 1024, 64]),\nTensor(f32[4, 16, 1024, 64]),\nTensor(f32[4, 16, 1024, 64]),\n)", + "text":"Skipped for fx.Node(aten.unbind.int)[call_function]:List[length=3](\nTensor(f32[4, 16, 1024, 64]),\nTensor(f32[4, 16, 1024, 64]),\nTensor(f32[4, 16, 1024, 64]),\n): Cannot find type promotion rule for op: aten.unbind.int" + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":1625 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0015", + "stacks":[] + }, + { + "message":{ + "markdown":"Skipped for fx.Node()[call_function]:Tensor(f32[4, 16, 1024, 64]): node.target is not OpOverload. Got type: \n\n## Additional Message:\n\n## Function Signature\n### Function Signature _TypePromotionInterpreter.run_node\n- self: \n- node: fx.Node()[call_function]:Tensor(f32[4, 16, 1024, 64])\n## Return values\nTensor(f32[4, 16, 1024, 64])", + "text":"Skipped for fx.Node()[call_function]:Tensor(f32[4, 16, 1024, 64]): node.target is not OpOverload. Got type: " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":1625 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0015", + "stacks":[] + }, + { + "message":{ + "markdown":"Skipped for fx.Node()[call_function]:Tensor(f32[4, 16, 1024, 64]): node.target is not OpOverload. Got type: \n\n## Additional Message:\n\n## Function Signature\n### Function Signature _TypePromotionInterpreter.run_node\n- self: \n- node: fx.Node()[call_function]:Tensor(f32[4, 16, 1024, 64])\n## Return values\nTensor(f32[4, 16, 1024, 64])", + "text":"Skipped for fx.Node()[call_function]:Tensor(f32[4, 16, 1024, 64]): node.target is not OpOverload. Got type: " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":1625 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0015", + "stacks":[] + }, + { + "message":{ + "markdown":"Skipped for fx.Node()[call_function]:Tensor(f32[4, 16, 1024, 64]): node.target is not OpOverload. Got type: \n\n## Additional Message:\n\n## Function Signature\n### Function Signature _TypePromotionInterpreter.run_node\n- self: \n- node: fx.Node()[call_function]:Tensor(f32[4, 16, 1024, 64])\n## Return values\nTensor(f32[4, 16, 1024, 64])", + "text":"Skipped for fx.Node()[call_function]:Tensor(f32[4, 16, 1024, 64]): node.target is not OpOverload. Got type: " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":1625 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0015", + "stacks":[] + }, + { + "message":{ + "markdown":"Skipped for fx.Node(aten._scaled_dot_product_efficient_attention.default)[call_function]:Tuple[length=4](\nTensor(f32[4, 16, 1024, 64]),\nTensor(f32[4, 16, 0]),\nTensor(i64[]),\nTensor(i64[]),\n): Cannot find type promotion rule for op: aten._scaled_dot_product_efficient_attention.default\n\n## Additional Message:\n\n## Function Signature\n### Function Signature _TypePromotionInterpreter.run_node\n- self: \n- node: fx.Node(aten._scaled_dot_product_efficient_attention.default)[call_function]:Tuple[length=4](\nTensor(f32[4, 16, 1024, 64]),\nTensor(f32[4, 16, 0]),\nTensor(i64[]),\nTensor(i64[]),\n)\n## Return values\nTuple[length=4](\nTensor(f32[4, 16, 1024, 64]),\nTensor(f32[4, 16, 0]),\nTensor(i64[]),\nTensor(i64[]),\n)", + "text":"Skipped for fx.Node(aten._scaled_dot_product_efficient_attention.default)[call_function]:Tuple[length=4](\nTensor(f32[4, 16, 1024, 64]),\nTensor(f32[4, 16, 0]),\nTensor(i64[]),\nTensor(i64[]),\n): Cannot find type promotion rule for op: aten._scaled_dot_product_efficient_attention.default" + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":1625 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0015", + "stacks":[] + }, + { + "message":{ + "markdown":"Skipped for fx.Node()[call_function]:Tensor(f32[4, 16, 1024, 64]): node.target is not OpOverload. Got type: \n\n## Additional Message:\n\n## Function Signature\n### Function Signature _TypePromotionInterpreter.run_node\n- self: \n- node: fx.Node()[call_function]:Tensor(f32[4, 16, 1024, 64])\n## Return values\nTensor(f32[4, 16, 1024, 64])", + "text":"Skipped for fx.Node()[call_function]:Tensor(f32[4, 16, 1024, 64]): node.target is not OpOverload. Got type: " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":1625 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0015", + "stacks":[] + }, + { + "message":{ + "markdown":"Skipped for fx.Node(aten.transpose.int)[call_function]:Tensor(f32[4, 1024, 16, 64]): Cannot find type promotion rule for op: aten.transpose.int\n\n## Additional Message:\n\n## Function Signature\n### Function Signature _TypePromotionInterpreter.run_node\n- self: \n- node: fx.Node(aten.transpose.int)[call_function]:Tensor(f32[4, 1024, 16, 64])\n## Return values\nTensor(f32[4, 1024, 16, 64])", + "text":"Skipped for fx.Node(aten.transpose.int)[call_function]:Tensor(f32[4, 1024, 16, 64]): Cannot find type promotion rule for op: aten.transpose.int" + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":1625 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0015", + "stacks":[] + }, + { + "message":{ + "markdown":"Skipped for fx.Node(aten.view.default)[call_function]:Tensor(f32[4, 1024, 1024]): Cannot find type promotion rule for op: aten.view.default\n\n## Additional Message:\n\n## Function Signature\n### Function Signature _TypePromotionInterpreter.run_node\n- self: \n- node: fx.Node(aten.view.default)[call_function]:Tensor(f32[4, 1024, 1024])\n## Return values\nTensor(f32[4, 1024, 1024])", + "text":"Skipped for fx.Node(aten.view.default)[call_function]:Tensor(f32[4, 1024, 1024]): Cannot find type promotion rule for op: aten.view.default" + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":1625 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0015", + "stacks":[] + }, + { + "message":{ + "markdown":"Skipped for fx.Node(aten.view.default)[call_function]:Tensor(f32[4096, 1024]): Cannot find type promotion rule for op: aten.view.default\n\n## Additional Message:\n\n## Function Signature\n### Function Signature _TypePromotionInterpreter.run_node\n- self: \n- node: fx.Node(aten.view.default)[call_function]:Tensor(f32[4096, 1024])\n## Return values\nTensor(f32[4096, 1024])", + "text":"Skipped for fx.Node(aten.view.default)[call_function]:Tensor(f32[4096, 1024]): Cannot find type promotion rule for op: aten.view.default" + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":1625 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0015", + "stacks":[] + }, + { + "message":{ + "markdown":"Skipped for fx.Node(aten.t.default)[call_function]:Tensor(f32[1024, 1024]): Cannot find type promotion rule for op: aten.t.default\n\n## Additional Message:\n\n## Function Signature\n### Function Signature _TypePromotionInterpreter.run_node\n- self: \n- node: fx.Node(aten.t.default)[call_function]:Tensor(f32[1024, 1024])\n## Return values\nTensor(f32[1024, 1024])", + "text":"Skipped for fx.Node(aten.t.default)[call_function]:Tensor(f32[1024, 1024]): Cannot find type promotion rule for op: aten.t.default" + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":1625 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0015", + "stacks":[] + }, + { + "message":{ + "markdown":"Skipped for fx.Node(aten.addmm.default)[call_function]:Tensor(f32[4096, 1024]): Cannot find type promotion rule for op: aten.addmm.default\n\n## Additional Message:\n\n## Function Signature\n### Function Signature _TypePromotionInterpreter.run_node\n- self: \n- node: fx.Node(aten.addmm.default)[call_function]:Tensor(f32[4096, 1024])\n## Return values\nTensor(f32[4096, 1024])", + "text":"Skipped for fx.Node(aten.addmm.default)[call_function]:Tensor(f32[4096, 1024]): Cannot find type promotion rule for op: aten.addmm.default" + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":1625 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0015", + "stacks":[] + }, + { + "message":{ + "markdown":"Skipped for fx.Node(aten.view.default)[call_function]:Tensor(f32[4, 1024, 1024]): Cannot find type promotion rule for op: aten.view.default\n\n## Additional Message:\n\n## Function Signature\n### Function Signature _TypePromotionInterpreter.run_node\n- self: \n- node: fx.Node(aten.view.default)[call_function]:Tensor(f32[4, 1024, 1024])\n## Return values\nTensor(f32[4, 1024, 1024])", + "text":"Skipped for fx.Node(aten.view.default)[call_function]:Tensor(f32[4, 1024, 1024]): Cannot find type promotion rule for op: aten.view.default" + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":1625 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0015", + "stacks":[] + }, + { + "message":{ + "markdown":"Skipped for fx.Node(aten.clone.default)[call_function]:Tensor(f32[4, 1024, 1024]): Cannot find type promotion rule for op: aten.clone.default\n\n## Additional Message:\n\n## Function Signature\n### Function Signature _TypePromotionInterpreter.run_node\n- self: \n- node: fx.Node(aten.clone.default)[call_function]:Tensor(f32[4, 1024, 1024])\n## Return values\nTensor(f32[4, 1024, 1024])", + "text":"Skipped for fx.Node(aten.clone.default)[call_function]:Tensor(f32[4, 1024, 1024]): Cannot find type promotion rule for op: aten.clone.default" + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":1625 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0015", + "stacks":[] + }, + { + "message":{ + "markdown":"Type promotion not needed for add_27. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature _TypePromotionInterpreter.run_node\n- self: \n- node: fx.Node(aten.add.Tensor)[call_function]:Tensor(f32[4, 1024, 1024])\nFound type promotion rule: ElementwiseTypePromotionRule('aten', 'add', [0, 1], [], ELEMENTWISE_TYPE_PROMOTION_KIND.DEFAULT)\nArgument add_26 is not promoted. Already torch.float32.\nArgument clone_40 is not promoted. Already torch.float32.\n## Return values\nTensor(f32[4, 1024, 1024])", + "text":"Type promotion not needed for add_27. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":1625 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0015", + "stacks":[] + }, + { + "message":{ + "markdown":"Skipped for fx.Node(aten.native_layer_norm.default)[call_function]:Tuple[length=3](\nTensor(f32[4, 1024, 1024]),\nTensor(f32[4, 1024, 1]),\nTensor(f32[4, 1024, 1]),\n): Cannot find type promotion rule for op: aten.native_layer_norm.default\n\n## Additional Message:\n\n## Function Signature\n### Function Signature _TypePromotionInterpreter.run_node\n- self: \n- node: fx.Node(aten.native_layer_norm.default)[call_function]:Tuple[length=3](\nTensor(f32[4, 1024, 1024]),\nTensor(f32[4, 1024, 1]),\nTensor(f32[4, 1024, 1]),\n)\n## Return values\nTuple[length=3](\nTensor(f32[4, 1024, 1024]),\nTensor(f32[4, 1024, 1]),\nTensor(f32[4, 1024, 1]),\n)", + "text":"Skipped for fx.Node(aten.native_layer_norm.default)[call_function]:Tuple[length=3](\nTensor(f32[4, 1024, 1024]),\nTensor(f32[4, 1024, 1]),\nTensor(f32[4, 1024, 1]),\n): Cannot find type promotion rule for op: aten.native_layer_norm.default" + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":1625 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0015", + "stacks":[] + }, + { + "message":{ + "markdown":"Skipped for fx.Node()[call_function]:Tensor(f32[4, 1024, 1024]): node.target is not OpOverload. Got type: \n\n## Additional Message:\n\n## Function Signature\n### Function Signature _TypePromotionInterpreter.run_node\n- self: \n- node: fx.Node()[call_function]:Tensor(f32[4, 1024, 1024])\n## Return values\nTensor(f32[4, 1024, 1024])", + "text":"Skipped for fx.Node()[call_function]:Tensor(f32[4, 1024, 1024]): node.target is not OpOverload. Got type: " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":1625 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0015", + "stacks":[] + }, + { + "message":{ + "markdown":"Skipped for fx.Node(aten.view.default)[call_function]:Tensor(f32[4096, 1024]): Cannot find type promotion rule for op: aten.view.default\n\n## Additional Message:\n\n## Function Signature\n### Function Signature _TypePromotionInterpreter.run_node\n- self: \n- node: fx.Node(aten.view.default)[call_function]:Tensor(f32[4096, 1024])\n## Return values\nTensor(f32[4096, 1024])", + "text":"Skipped for fx.Node(aten.view.default)[call_function]:Tensor(f32[4096, 1024]): Cannot find type promotion rule for op: aten.view.default" + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":1625 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0015", + "stacks":[] + }, + { + "message":{ + "markdown":"Skipped for fx.Node(aten.t.default)[call_function]:Tensor(f32[1024, 4096]): Cannot find type promotion rule for op: aten.t.default\n\n## Additional Message:\n\n## Function Signature\n### Function Signature _TypePromotionInterpreter.run_node\n- self: \n- node: fx.Node(aten.t.default)[call_function]:Tensor(f32[1024, 4096])\n## Return values\nTensor(f32[1024, 4096])", + "text":"Skipped for fx.Node(aten.t.default)[call_function]:Tensor(f32[1024, 4096]): Cannot find type promotion rule for op: aten.t.default" + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":1625 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0015", + "stacks":[] + }, + { + "message":{ + "markdown":"Skipped for fx.Node(aten.addmm.default)[call_function]:Tensor(f32[4096, 4096]): Cannot find type promotion rule for op: aten.addmm.default\n\n## Additional Message:\n\n## Function Signature\n### Function Signature _TypePromotionInterpreter.run_node\n- self: \n- node: fx.Node(aten.addmm.default)[call_function]:Tensor(f32[4096, 4096])\n## Return values\nTensor(f32[4096, 4096])", + "text":"Skipped for fx.Node(aten.addmm.default)[call_function]:Tensor(f32[4096, 4096]): Cannot find type promotion rule for op: aten.addmm.default" + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":1625 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0015", + "stacks":[] + }, + { + "message":{ + "markdown":"Skipped for fx.Node(aten.view.default)[call_function]:Tensor(f32[4, 1024, 4096]): Cannot find type promotion rule for op: aten.view.default\n\n## Additional Message:\n\n## Function Signature\n### Function Signature _TypePromotionInterpreter.run_node\n- self: \n- node: fx.Node(aten.view.default)[call_function]:Tensor(f32[4, 1024, 4096])\n## Return values\nTensor(f32[4, 1024, 4096])", + "text":"Skipped for fx.Node(aten.view.default)[call_function]:Tensor(f32[4, 1024, 4096]): Cannot find type promotion rule for op: aten.view.default" + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":1625 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0015", + "stacks":[] + }, + { + "message":{ + "markdown":"Type promotion not needed for gelu_13. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature _TypePromotionInterpreter.run_node\n- self: \n- node: fx.Node(aten.gelu.default)[call_function]:Tensor(f32[4, 1024, 4096])\nFound type promotion rule: ElementwiseTypePromotionRule('aten', 'gelu', [0], [], ELEMENTWISE_TYPE_PROMOTION_KIND.DEFAULT)\nArgument view_138 is not promoted. Already torch.float32.\nArgument tanh is not promoted. Not mentioned by type promotion rule.\n## Return values\nTensor(f32[4, 1024, 4096])", + "text":"Type promotion not needed for gelu_13. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":1625 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0015", + "stacks":[] + }, + { + "message":{ + "markdown":"Skipped for fx.Node(aten.clone.default)[call_function]:Tensor(f32[4, 1024, 4096]): Cannot find type promotion rule for op: aten.clone.default\n\n## Additional Message:\n\n## Function Signature\n### Function Signature _TypePromotionInterpreter.run_node\n- self: \n- node: fx.Node(aten.clone.default)[call_function]:Tensor(f32[4, 1024, 4096])\n## Return values\nTensor(f32[4, 1024, 4096])", + "text":"Skipped for fx.Node(aten.clone.default)[call_function]:Tensor(f32[4, 1024, 4096]): Cannot find type promotion rule for op: aten.clone.default" + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":1625 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0015", + "stacks":[] + }, + { + "message":{ + "markdown":"Skipped for fx.Node(aten.view.default)[call_function]:Tensor(f32[4096, 4096]): Cannot find type promotion rule for op: aten.view.default\n\n## Additional Message:\n\n## Function Signature\n### Function Signature _TypePromotionInterpreter.run_node\n- self: \n- node: fx.Node(aten.view.default)[call_function]:Tensor(f32[4096, 4096])\n## Return values\nTensor(f32[4096, 4096])", + "text":"Skipped for fx.Node(aten.view.default)[call_function]:Tensor(f32[4096, 4096]): Cannot find type promotion rule for op: aten.view.default" + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":1625 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0015", + "stacks":[] + }, + { + "message":{ + "markdown":"Skipped for fx.Node(aten.t.default)[call_function]:Tensor(f32[4096, 1024]): Cannot find type promotion rule for op: aten.t.default\n\n## Additional Message:\n\n## Function Signature\n### Function Signature _TypePromotionInterpreter.run_node\n- self: \n- node: fx.Node(aten.t.default)[call_function]:Tensor(f32[4096, 1024])\n## Return values\nTensor(f32[4096, 1024])", + "text":"Skipped for fx.Node(aten.t.default)[call_function]:Tensor(f32[4096, 1024]): Cannot find type promotion rule for op: aten.t.default" + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":1625 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0015", + "stacks":[] + }, + { + "message":{ + "markdown":"Skipped for fx.Node(aten.addmm.default)[call_function]:Tensor(f32[4096, 1024]): Cannot find type promotion rule for op: aten.addmm.default\n\n## Additional Message:\n\n## Function Signature\n### Function Signature _TypePromotionInterpreter.run_node\n- self: \n- node: fx.Node(aten.addmm.default)[call_function]:Tensor(f32[4096, 1024])\n## Return values\nTensor(f32[4096, 1024])", + "text":"Skipped for fx.Node(aten.addmm.default)[call_function]:Tensor(f32[4096, 1024]): Cannot find type promotion rule for op: aten.addmm.default" + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":1625 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0015", + "stacks":[] + }, + { + "message":{ + "markdown":"Skipped for fx.Node(aten.view.default)[call_function]:Tensor(f32[4, 1024, 1024]): Cannot find type promotion rule for op: aten.view.default\n\n## Additional Message:\n\n## Function Signature\n### Function Signature _TypePromotionInterpreter.run_node\n- self: \n- node: fx.Node(aten.view.default)[call_function]:Tensor(f32[4, 1024, 1024])\n## Return values\nTensor(f32[4, 1024, 1024])", + "text":"Skipped for fx.Node(aten.view.default)[call_function]:Tensor(f32[4, 1024, 1024]): Cannot find type promotion rule for op: aten.view.default" + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":1625 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0015", + "stacks":[] + }, + { + "message":{ + "markdown":"Skipped for fx.Node(aten.clone.default)[call_function]:Tensor(f32[4, 1024, 1024]): Cannot find type promotion rule for op: aten.clone.default\n\n## Additional Message:\n\n## Function Signature\n### Function Signature _TypePromotionInterpreter.run_node\n- self: \n- node: fx.Node(aten.clone.default)[call_function]:Tensor(f32[4, 1024, 1024])\n## Return values\nTensor(f32[4, 1024, 1024])", + "text":"Skipped for fx.Node(aten.clone.default)[call_function]:Tensor(f32[4, 1024, 1024]): Cannot find type promotion rule for op: aten.clone.default" + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":1625 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0015", + "stacks":[] + }, + { + "message":{ + "markdown":"Type promotion not needed for add_28. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature _TypePromotionInterpreter.run_node\n- self: \n- node: fx.Node(aten.add.Tensor)[call_function]:Tensor(f32[4, 1024, 1024])\nFound type promotion rule: ElementwiseTypePromotionRule('aten', 'add', [0, 1], [], ELEMENTWISE_TYPE_PROMOTION_KIND.DEFAULT)\nArgument add_27 is not promoted. Already torch.float32.\nArgument clone_42 is not promoted. Already torch.float32.\n## Return values\nTensor(f32[4, 1024, 1024])", + "text":"Type promotion not needed for add_28. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":1625 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0015", + "stacks":[] + }, + { + "message":{ + "markdown":"Skipped for fx.Node(aten.native_layer_norm.default)[call_function]:Tuple[length=3](\nTensor(f32[4, 1024, 1024]),\nTensor(f32[4, 1024, 1]),\nTensor(f32[4, 1024, 1]),\n): Cannot find type promotion rule for op: aten.native_layer_norm.default\n\n## Additional Message:\n\n## Function Signature\n### Function Signature _TypePromotionInterpreter.run_node\n- self: \n- node: fx.Node(aten.native_layer_norm.default)[call_function]:Tuple[length=3](\nTensor(f32[4, 1024, 1024]),\nTensor(f32[4, 1024, 1]),\nTensor(f32[4, 1024, 1]),\n)\n## Return values\nTuple[length=3](\nTensor(f32[4, 1024, 1024]),\nTensor(f32[4, 1024, 1]),\nTensor(f32[4, 1024, 1]),\n)", + "text":"Skipped for fx.Node(aten.native_layer_norm.default)[call_function]:Tuple[length=3](\nTensor(f32[4, 1024, 1024]),\nTensor(f32[4, 1024, 1]),\nTensor(f32[4, 1024, 1]),\n): Cannot find type promotion rule for op: aten.native_layer_norm.default" + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":1625 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0015", + "stacks":[] + }, + { + "message":{ + "markdown":"Skipped for fx.Node()[call_function]:Tensor(f32[4, 1024, 1024]): node.target is not OpOverload. Got type: \n\n## Additional Message:\n\n## Function Signature\n### Function Signature _TypePromotionInterpreter.run_node\n- self: \n- node: fx.Node()[call_function]:Tensor(f32[4, 1024, 1024])\n## Return values\nTensor(f32[4, 1024, 1024])", + "text":"Skipped for fx.Node()[call_function]:Tensor(f32[4, 1024, 1024]): node.target is not OpOverload. Got type: " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":1625 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0015", + "stacks":[] + }, + { + "message":{ + "markdown":"Skipped for fx.Node(aten.view.default)[call_function]:Tensor(f32[4096, 1024]): Cannot find type promotion rule for op: aten.view.default\n\n## Additional Message:\n\n## Function Signature\n### Function Signature _TypePromotionInterpreter.run_node\n- self: \n- node: fx.Node(aten.view.default)[call_function]:Tensor(f32[4096, 1024])\n## Return values\nTensor(f32[4096, 1024])", + "text":"Skipped for fx.Node(aten.view.default)[call_function]:Tensor(f32[4096, 1024]): Cannot find type promotion rule for op: aten.view.default" + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":1625 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0015", + "stacks":[] + }, + { + "message":{ + "markdown":"Skipped for fx.Node(aten.t.default)[call_function]:Tensor(f32[1024, 3072]): Cannot find type promotion rule for op: aten.t.default\n\n## Additional Message:\n\n## Function Signature\n### Function Signature _TypePromotionInterpreter.run_node\n- self: \n- node: fx.Node(aten.t.default)[call_function]:Tensor(f32[1024, 3072])\n## Return values\nTensor(f32[1024, 3072])", + "text":"Skipped for fx.Node(aten.t.default)[call_function]:Tensor(f32[1024, 3072]): Cannot find type promotion rule for op: aten.t.default" + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":1625 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0015", + "stacks":[] + }, + { + "message":{ + "markdown":"Skipped for fx.Node(aten.addmm.default)[call_function]:Tensor(f32[4096, 3072]): Cannot find type promotion rule for op: aten.addmm.default\n\n## Additional Message:\n\n## Function Signature\n### Function Signature _TypePromotionInterpreter.run_node\n- self: \n- node: fx.Node(aten.addmm.default)[call_function]:Tensor(f32[4096, 3072])\n## Return values\nTensor(f32[4096, 3072])", + "text":"Skipped for fx.Node(aten.addmm.default)[call_function]:Tensor(f32[4096, 3072]): Cannot find type promotion rule for op: aten.addmm.default" + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":1625 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0015", + "stacks":[] + }, + { + "message":{ + "markdown":"Skipped for fx.Node(aten.view.default)[call_function]:Tensor(f32[4, 1024, 3072]): Cannot find type promotion rule for op: aten.view.default\n\n## Additional Message:\n\n## Function Signature\n### Function Signature _TypePromotionInterpreter.run_node\n- self: \n- node: fx.Node(aten.view.default)[call_function]:Tensor(f32[4, 1024, 3072])\n## Return values\nTensor(f32[4, 1024, 3072])", + "text":"Skipped for fx.Node(aten.view.default)[call_function]:Tensor(f32[4, 1024, 3072]): Cannot find type promotion rule for op: aten.view.default" + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":1625 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0015", + "stacks":[] + }, + { + "message":{ + "markdown":"Skipped for fx.Node(aten.view.default)[call_function]:Tensor(f32[4, 1024, 3, 16, 64]): Cannot find type promotion rule for op: aten.view.default\n\n## Additional Message:\n\n## Function Signature\n### Function Signature _TypePromotionInterpreter.run_node\n- self: \n- node: fx.Node(aten.view.default)[call_function]:Tensor(f32[4, 1024, 3, 16, 64])\n## Return values\nTensor(f32[4, 1024, 3, 16, 64])", + "text":"Skipped for fx.Node(aten.view.default)[call_function]:Tensor(f32[4, 1024, 3, 16, 64]): Cannot find type promotion rule for op: aten.view.default" + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":1625 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0015", + "stacks":[] + }, + { + "message":{ + "markdown":"Skipped for fx.Node(aten.permute.default)[call_function]:Tensor(f32[3, 4, 16, 1024, 64]): Cannot find type promotion rule for op: aten.permute.default\n\n## Additional Message:\n\n## Function Signature\n### Function Signature _TypePromotionInterpreter.run_node\n- self: \n- node: fx.Node(aten.permute.default)[call_function]:Tensor(f32[3, 4, 16, 1024, 64])\n## Return values\nTensor(f32[3, 4, 16, 1024, 64])", + "text":"Skipped for fx.Node(aten.permute.default)[call_function]:Tensor(f32[3, 4, 16, 1024, 64]): Cannot find type promotion rule for op: aten.permute.default" + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":1625 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0015", + "stacks":[] + }, + { + "message":{ + "markdown":"Skipped for fx.Node(aten.unbind.int)[call_function]:List[length=3](\nTensor(f32[4, 16, 1024, 64]),\nTensor(f32[4, 16, 1024, 64]),\nTensor(f32[4, 16, 1024, 64]),\n): Cannot find type promotion rule for op: aten.unbind.int\n\n## Additional Message:\n\n## Function Signature\n### Function Signature _TypePromotionInterpreter.run_node\n- self: \n- node: fx.Node(aten.unbind.int)[call_function]:List[length=3](\nTensor(f32[4, 16, 1024, 64]),\nTensor(f32[4, 16, 1024, 64]),\nTensor(f32[4, 16, 1024, 64]),\n)\n## Return values\nList[length=3](\nTensor(f32[4, 16, 1024, 64]),\nTensor(f32[4, 16, 1024, 64]),\nTensor(f32[4, 16, 1024, 64]),\n)", + "text":"Skipped for fx.Node(aten.unbind.int)[call_function]:List[length=3](\nTensor(f32[4, 16, 1024, 64]),\nTensor(f32[4, 16, 1024, 64]),\nTensor(f32[4, 16, 1024, 64]),\n): Cannot find type promotion rule for op: aten.unbind.int" + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":1625 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0015", + "stacks":[] + }, + { + "message":{ + "markdown":"Skipped for fx.Node()[call_function]:Tensor(f32[4, 16, 1024, 64]): node.target is not OpOverload. Got type: \n\n## Additional Message:\n\n## Function Signature\n### Function Signature _TypePromotionInterpreter.run_node\n- self: \n- node: fx.Node()[call_function]:Tensor(f32[4, 16, 1024, 64])\n## Return values\nTensor(f32[4, 16, 1024, 64])", + "text":"Skipped for fx.Node()[call_function]:Tensor(f32[4, 16, 1024, 64]): node.target is not OpOverload. Got type: " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":1625 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0015", + "stacks":[] + }, + { + "message":{ + "markdown":"Skipped for fx.Node()[call_function]:Tensor(f32[4, 16, 1024, 64]): node.target is not OpOverload. Got type: \n\n## Additional Message:\n\n## Function Signature\n### Function Signature _TypePromotionInterpreter.run_node\n- self: \n- node: fx.Node()[call_function]:Tensor(f32[4, 16, 1024, 64])\n## Return values\nTensor(f32[4, 16, 1024, 64])", + "text":"Skipped for fx.Node()[call_function]:Tensor(f32[4, 16, 1024, 64]): node.target is not OpOverload. Got type: " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":1625 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0015", + "stacks":[] + }, + { + "message":{ + "markdown":"Skipped for fx.Node()[call_function]:Tensor(f32[4, 16, 1024, 64]): node.target is not OpOverload. Got type: \n\n## Additional Message:\n\n## Function Signature\n### Function Signature _TypePromotionInterpreter.run_node\n- self: \n- node: fx.Node()[call_function]:Tensor(f32[4, 16, 1024, 64])\n## Return values\nTensor(f32[4, 16, 1024, 64])", + "text":"Skipped for fx.Node()[call_function]:Tensor(f32[4, 16, 1024, 64]): node.target is not OpOverload. Got type: " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":1625 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0015", + "stacks":[] + }, + { + "message":{ + "markdown":"Skipped for fx.Node(aten._scaled_dot_product_efficient_attention.default)[call_function]:Tuple[length=4](\nTensor(f32[4, 16, 1024, 64]),\nTensor(f32[4, 16, 0]),\nTensor(i64[]),\nTensor(i64[]),\n): Cannot find type promotion rule for op: aten._scaled_dot_product_efficient_attention.default\n\n## Additional Message:\n\n## Function Signature\n### Function Signature _TypePromotionInterpreter.run_node\n- self: \n- node: fx.Node(aten._scaled_dot_product_efficient_attention.default)[call_function]:Tuple[length=4](\nTensor(f32[4, 16, 1024, 64]),\nTensor(f32[4, 16, 0]),\nTensor(i64[]),\nTensor(i64[]),\n)\n## Return values\nTuple[length=4](\nTensor(f32[4, 16, 1024, 64]),\nTensor(f32[4, 16, 0]),\nTensor(i64[]),\nTensor(i64[]),\n)", + "text":"Skipped for fx.Node(aten._scaled_dot_product_efficient_attention.default)[call_function]:Tuple[length=4](\nTensor(f32[4, 16, 1024, 64]),\nTensor(f32[4, 16, 0]),\nTensor(i64[]),\nTensor(i64[]),\n): Cannot find type promotion rule for op: aten._scaled_dot_product_efficient_attention.default" + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":1625 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0015", + "stacks":[] + }, + { + "message":{ + "markdown":"Skipped for fx.Node()[call_function]:Tensor(f32[4, 16, 1024, 64]): node.target is not OpOverload. Got type: \n\n## Additional Message:\n\n## Function Signature\n### Function Signature _TypePromotionInterpreter.run_node\n- self: \n- node: fx.Node()[call_function]:Tensor(f32[4, 16, 1024, 64])\n## Return values\nTensor(f32[4, 16, 1024, 64])", + "text":"Skipped for fx.Node()[call_function]:Tensor(f32[4, 16, 1024, 64]): node.target is not OpOverload. Got type: " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":1625 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0015", + "stacks":[] + }, + { + "message":{ + "markdown":"Skipped for fx.Node(aten.transpose.int)[call_function]:Tensor(f32[4, 1024, 16, 64]): Cannot find type promotion rule for op: aten.transpose.int\n\n## Additional Message:\n\n## Function Signature\n### Function Signature _TypePromotionInterpreter.run_node\n- self: \n- node: fx.Node(aten.transpose.int)[call_function]:Tensor(f32[4, 1024, 16, 64])\n## Return values\nTensor(f32[4, 1024, 16, 64])", + "text":"Skipped for fx.Node(aten.transpose.int)[call_function]:Tensor(f32[4, 1024, 16, 64]): Cannot find type promotion rule for op: aten.transpose.int" + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":1625 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0015", + "stacks":[] + }, + { + "message":{ + "markdown":"Skipped for fx.Node(aten.view.default)[call_function]:Tensor(f32[4, 1024, 1024]): Cannot find type promotion rule for op: aten.view.default\n\n## Additional Message:\n\n## Function Signature\n### Function Signature _TypePromotionInterpreter.run_node\n- self: \n- node: fx.Node(aten.view.default)[call_function]:Tensor(f32[4, 1024, 1024])\n## Return values\nTensor(f32[4, 1024, 1024])", + "text":"Skipped for fx.Node(aten.view.default)[call_function]:Tensor(f32[4, 1024, 1024]): Cannot find type promotion rule for op: aten.view.default" + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":1625 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0015", + "stacks":[] + }, + { + "message":{ + "markdown":"Skipped for fx.Node(aten.view.default)[call_function]:Tensor(f32[4096, 1024]): Cannot find type promotion rule for op: aten.view.default\n\n## Additional Message:\n\n## Function Signature\n### Function Signature _TypePromotionInterpreter.run_node\n- self: \n- node: fx.Node(aten.view.default)[call_function]:Tensor(f32[4096, 1024])\n## Return values\nTensor(f32[4096, 1024])", + "text":"Skipped for fx.Node(aten.view.default)[call_function]:Tensor(f32[4096, 1024]): Cannot find type promotion rule for op: aten.view.default" + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":1625 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0015", + "stacks":[] + }, + { + "message":{ + "markdown":"Skipped for fx.Node(aten.t.default)[call_function]:Tensor(f32[1024, 1024]): Cannot find type promotion rule for op: aten.t.default\n\n## Additional Message:\n\n## Function Signature\n### Function Signature _TypePromotionInterpreter.run_node\n- self: \n- node: fx.Node(aten.t.default)[call_function]:Tensor(f32[1024, 1024])\n## Return values\nTensor(f32[1024, 1024])", + "text":"Skipped for fx.Node(aten.t.default)[call_function]:Tensor(f32[1024, 1024]): Cannot find type promotion rule for op: aten.t.default" + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":1625 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0015", + "stacks":[] + }, + { + "message":{ + "markdown":"Skipped for fx.Node(aten.addmm.default)[call_function]:Tensor(f32[4096, 1024]): Cannot find type promotion rule for op: aten.addmm.default\n\n## Additional Message:\n\n## Function Signature\n### Function Signature _TypePromotionInterpreter.run_node\n- self: \n- node: fx.Node(aten.addmm.default)[call_function]:Tensor(f32[4096, 1024])\n## Return values\nTensor(f32[4096, 1024])", + "text":"Skipped for fx.Node(aten.addmm.default)[call_function]:Tensor(f32[4096, 1024]): Cannot find type promotion rule for op: aten.addmm.default" + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":1625 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0015", + "stacks":[] + }, + { + "message":{ + "markdown":"Skipped for fx.Node(aten.view.default)[call_function]:Tensor(f32[4, 1024, 1024]): Cannot find type promotion rule for op: aten.view.default\n\n## Additional Message:\n\n## Function Signature\n### Function Signature _TypePromotionInterpreter.run_node\n- self: \n- node: fx.Node(aten.view.default)[call_function]:Tensor(f32[4, 1024, 1024])\n## Return values\nTensor(f32[4, 1024, 1024])", + "text":"Skipped for fx.Node(aten.view.default)[call_function]:Tensor(f32[4, 1024, 1024]): Cannot find type promotion rule for op: aten.view.default" + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":1625 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0015", + "stacks":[] + }, + { + "message":{ + "markdown":"Skipped for fx.Node(aten.clone.default)[call_function]:Tensor(f32[4, 1024, 1024]): Cannot find type promotion rule for op: aten.clone.default\n\n## Additional Message:\n\n## Function Signature\n### Function Signature _TypePromotionInterpreter.run_node\n- self: \n- node: fx.Node(aten.clone.default)[call_function]:Tensor(f32[4, 1024, 1024])\n## Return values\nTensor(f32[4, 1024, 1024])", + "text":"Skipped for fx.Node(aten.clone.default)[call_function]:Tensor(f32[4, 1024, 1024]): Cannot find type promotion rule for op: aten.clone.default" + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":1625 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0015", + "stacks":[] + }, + { + "message":{ + "markdown":"Type promotion not needed for add_29. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature _TypePromotionInterpreter.run_node\n- self: \n- node: fx.Node(aten.add.Tensor)[call_function]:Tensor(f32[4, 1024, 1024])\nFound type promotion rule: ElementwiseTypePromotionRule('aten', 'add', [0, 1], [], ELEMENTWISE_TYPE_PROMOTION_KIND.DEFAULT)\nArgument add_28 is not promoted. Already torch.float32.\nArgument clone_43 is not promoted. Already torch.float32.\n## Return values\nTensor(f32[4, 1024, 1024])", + "text":"Type promotion not needed for add_29. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":1625 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0015", + "stacks":[] + }, + { + "message":{ + "markdown":"Skipped for fx.Node(aten.native_layer_norm.default)[call_function]:Tuple[length=3](\nTensor(f32[4, 1024, 1024]),\nTensor(f32[4, 1024, 1]),\nTensor(f32[4, 1024, 1]),\n): Cannot find type promotion rule for op: aten.native_layer_norm.default\n\n## Additional Message:\n\n## Function Signature\n### Function Signature _TypePromotionInterpreter.run_node\n- self: \n- node: fx.Node(aten.native_layer_norm.default)[call_function]:Tuple[length=3](\nTensor(f32[4, 1024, 1024]),\nTensor(f32[4, 1024, 1]),\nTensor(f32[4, 1024, 1]),\n)\n## Return values\nTuple[length=3](\nTensor(f32[4, 1024, 1024]),\nTensor(f32[4, 1024, 1]),\nTensor(f32[4, 1024, 1]),\n)", + "text":"Skipped for fx.Node(aten.native_layer_norm.default)[call_function]:Tuple[length=3](\nTensor(f32[4, 1024, 1024]),\nTensor(f32[4, 1024, 1]),\nTensor(f32[4, 1024, 1]),\n): Cannot find type promotion rule for op: aten.native_layer_norm.default" + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":1625 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0015", + "stacks":[] + }, + { + "message":{ + "markdown":"Skipped for fx.Node()[call_function]:Tensor(f32[4, 1024, 1024]): node.target is not OpOverload. Got type: \n\n## Additional Message:\n\n## Function Signature\n### Function Signature _TypePromotionInterpreter.run_node\n- self: \n- node: fx.Node()[call_function]:Tensor(f32[4, 1024, 1024])\n## Return values\nTensor(f32[4, 1024, 1024])", + "text":"Skipped for fx.Node()[call_function]:Tensor(f32[4, 1024, 1024]): node.target is not OpOverload. Got type: " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":1625 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0015", + "stacks":[] + }, + { + "message":{ + "markdown":"Skipped for fx.Node(aten.view.default)[call_function]:Tensor(f32[4096, 1024]): Cannot find type promotion rule for op: aten.view.default\n\n## Additional Message:\n\n## Function Signature\n### Function Signature _TypePromotionInterpreter.run_node\n- self: \n- node: fx.Node(aten.view.default)[call_function]:Tensor(f32[4096, 1024])\n## Return values\nTensor(f32[4096, 1024])", + "text":"Skipped for fx.Node(aten.view.default)[call_function]:Tensor(f32[4096, 1024]): Cannot find type promotion rule for op: aten.view.default" + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":1625 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0015", + "stacks":[] + }, + { + "message":{ + "markdown":"Skipped for fx.Node(aten.t.default)[call_function]:Tensor(f32[1024, 4096]): Cannot find type promotion rule for op: aten.t.default\n\n## Additional Message:\n\n## Function Signature\n### Function Signature _TypePromotionInterpreter.run_node\n- self: \n- node: fx.Node(aten.t.default)[call_function]:Tensor(f32[1024, 4096])\n## Return values\nTensor(f32[1024, 4096])", + "text":"Skipped for fx.Node(aten.t.default)[call_function]:Tensor(f32[1024, 4096]): Cannot find type promotion rule for op: aten.t.default" + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":1625 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0015", + "stacks":[] + }, + { + "message":{ + "markdown":"Skipped for fx.Node(aten.addmm.default)[call_function]:Tensor(f32[4096, 4096]): Cannot find type promotion rule for op: aten.addmm.default\n\n## Additional Message:\n\n## Function Signature\n### Function Signature _TypePromotionInterpreter.run_node\n- self: \n- node: fx.Node(aten.addmm.default)[call_function]:Tensor(f32[4096, 4096])\n## Return values\nTensor(f32[4096, 4096])", + "text":"Skipped for fx.Node(aten.addmm.default)[call_function]:Tensor(f32[4096, 4096]): Cannot find type promotion rule for op: aten.addmm.default" + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":1625 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0015", + "stacks":[] + }, + { + "message":{ + "markdown":"Skipped for fx.Node(aten.view.default)[call_function]:Tensor(f32[4, 1024, 4096]): Cannot find type promotion rule for op: aten.view.default\n\n## Additional Message:\n\n## Function Signature\n### Function Signature _TypePromotionInterpreter.run_node\n- self: \n- node: fx.Node(aten.view.default)[call_function]:Tensor(f32[4, 1024, 4096])\n## Return values\nTensor(f32[4, 1024, 4096])", + "text":"Skipped for fx.Node(aten.view.default)[call_function]:Tensor(f32[4, 1024, 4096]): Cannot find type promotion rule for op: aten.view.default" + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":1625 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0015", + "stacks":[] + }, + { + "message":{ + "markdown":"Type promotion not needed for gelu_14. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature _TypePromotionInterpreter.run_node\n- self: \n- node: fx.Node(aten.gelu.default)[call_function]:Tensor(f32[4, 1024, 4096])\nFound type promotion rule: ElementwiseTypePromotionRule('aten', 'gelu', [0], [], ELEMENTWISE_TYPE_PROMOTION_KIND.DEFAULT)\nArgument view_148 is not promoted. Already torch.float32.\nArgument tanh is not promoted. Not mentioned by type promotion rule.\n## Return values\nTensor(f32[4, 1024, 4096])", + "text":"Type promotion not needed for gelu_14. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":1625 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0015", + "stacks":[] + }, + { + "message":{ + "markdown":"Skipped for fx.Node(aten.clone.default)[call_function]:Tensor(f32[4, 1024, 4096]): Cannot find type promotion rule for op: aten.clone.default\n\n## Additional Message:\n\n## Function Signature\n### Function Signature _TypePromotionInterpreter.run_node\n- self: \n- node: fx.Node(aten.clone.default)[call_function]:Tensor(f32[4, 1024, 4096])\n## Return values\nTensor(f32[4, 1024, 4096])", + "text":"Skipped for fx.Node(aten.clone.default)[call_function]:Tensor(f32[4, 1024, 4096]): Cannot find type promotion rule for op: aten.clone.default" + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":1625 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0015", + "stacks":[] + }, + { + "message":{ + "markdown":"Skipped for fx.Node(aten.view.default)[call_function]:Tensor(f32[4096, 4096]): Cannot find type promotion rule for op: aten.view.default\n\n## Additional Message:\n\n## Function Signature\n### Function Signature _TypePromotionInterpreter.run_node\n- self: \n- node: fx.Node(aten.view.default)[call_function]:Tensor(f32[4096, 4096])\n## Return values\nTensor(f32[4096, 4096])", + "text":"Skipped for fx.Node(aten.view.default)[call_function]:Tensor(f32[4096, 4096]): Cannot find type promotion rule for op: aten.view.default" + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":1625 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0015", + "stacks":[] + }, + { + "message":{ + "markdown":"Skipped for fx.Node(aten.t.default)[call_function]:Tensor(f32[4096, 1024]): Cannot find type promotion rule for op: aten.t.default\n\n## Additional Message:\n\n## Function Signature\n### Function Signature _TypePromotionInterpreter.run_node\n- self: \n- node: fx.Node(aten.t.default)[call_function]:Tensor(f32[4096, 1024])\n## Return values\nTensor(f32[4096, 1024])", + "text":"Skipped for fx.Node(aten.t.default)[call_function]:Tensor(f32[4096, 1024]): Cannot find type promotion rule for op: aten.t.default" + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":1625 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0015", + "stacks":[] + }, + { + "message":{ + "markdown":"Skipped for fx.Node(aten.addmm.default)[call_function]:Tensor(f32[4096, 1024]): Cannot find type promotion rule for op: aten.addmm.default\n\n## Additional Message:\n\n## Function Signature\n### Function Signature _TypePromotionInterpreter.run_node\n- self: \n- node: fx.Node(aten.addmm.default)[call_function]:Tensor(f32[4096, 1024])\n## Return values\nTensor(f32[4096, 1024])", + "text":"Skipped for fx.Node(aten.addmm.default)[call_function]:Tensor(f32[4096, 1024]): Cannot find type promotion rule for op: aten.addmm.default" + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":1625 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0015", + "stacks":[] + }, + { + "message":{ + "markdown":"Skipped for fx.Node(aten.view.default)[call_function]:Tensor(f32[4, 1024, 1024]): Cannot find type promotion rule for op: aten.view.default\n\n## Additional Message:\n\n## Function Signature\n### Function Signature _TypePromotionInterpreter.run_node\n- self: \n- node: fx.Node(aten.view.default)[call_function]:Tensor(f32[4, 1024, 1024])\n## Return values\nTensor(f32[4, 1024, 1024])", + "text":"Skipped for fx.Node(aten.view.default)[call_function]:Tensor(f32[4, 1024, 1024]): Cannot find type promotion rule for op: aten.view.default" + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":1625 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0015", + "stacks":[] + }, + { + "message":{ + "markdown":"Skipped for fx.Node(aten.clone.default)[call_function]:Tensor(f32[4, 1024, 1024]): Cannot find type promotion rule for op: aten.clone.default\n\n## Additional Message:\n\n## Function Signature\n### Function Signature _TypePromotionInterpreter.run_node\n- self: \n- node: fx.Node(aten.clone.default)[call_function]:Tensor(f32[4, 1024, 1024])\n## Return values\nTensor(f32[4, 1024, 1024])", + "text":"Skipped for fx.Node(aten.clone.default)[call_function]:Tensor(f32[4, 1024, 1024]): Cannot find type promotion rule for op: aten.clone.default" + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":1625 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0015", + "stacks":[] + }, + { + "message":{ + "markdown":"Type promotion not needed for add_30. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature _TypePromotionInterpreter.run_node\n- self: \n- node: fx.Node(aten.add.Tensor)[call_function]:Tensor(f32[4, 1024, 1024])\nFound type promotion rule: ElementwiseTypePromotionRule('aten', 'add', [0, 1], [], ELEMENTWISE_TYPE_PROMOTION_KIND.DEFAULT)\nArgument add_29 is not promoted. Already torch.float32.\nArgument clone_45 is not promoted. Already torch.float32.\n## Return values\nTensor(f32[4, 1024, 1024])", + "text":"Type promotion not needed for add_30. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":1625 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0015", + "stacks":[] + }, + { + "message":{ + "markdown":"Skipped for fx.Node(aten.native_layer_norm.default)[call_function]:Tuple[length=3](\nTensor(f32[4, 1024, 1024]),\nTensor(f32[4, 1024, 1]),\nTensor(f32[4, 1024, 1]),\n): Cannot find type promotion rule for op: aten.native_layer_norm.default\n\n## Additional Message:\n\n## Function Signature\n### Function Signature _TypePromotionInterpreter.run_node\n- self: \n- node: fx.Node(aten.native_layer_norm.default)[call_function]:Tuple[length=3](\nTensor(f32[4, 1024, 1024]),\nTensor(f32[4, 1024, 1]),\nTensor(f32[4, 1024, 1]),\n)\n## Return values\nTuple[length=3](\nTensor(f32[4, 1024, 1024]),\nTensor(f32[4, 1024, 1]),\nTensor(f32[4, 1024, 1]),\n)", + "text":"Skipped for fx.Node(aten.native_layer_norm.default)[call_function]:Tuple[length=3](\nTensor(f32[4, 1024, 1024]),\nTensor(f32[4, 1024, 1]),\nTensor(f32[4, 1024, 1]),\n): Cannot find type promotion rule for op: aten.native_layer_norm.default" + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":1625 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0015", + "stacks":[] + }, + { + "message":{ + "markdown":"Skipped for fx.Node()[call_function]:Tensor(f32[4, 1024, 1024]): node.target is not OpOverload. Got type: \n\n## Additional Message:\n\n## Function Signature\n### Function Signature _TypePromotionInterpreter.run_node\n- self: \n- node: fx.Node()[call_function]:Tensor(f32[4, 1024, 1024])\n## Return values\nTensor(f32[4, 1024, 1024])", + "text":"Skipped for fx.Node()[call_function]:Tensor(f32[4, 1024, 1024]): node.target is not OpOverload. Got type: " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":1625 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0015", + "stacks":[] + }, + { + "message":{ + "markdown":"Skipped for fx.Node(aten.view.default)[call_function]:Tensor(f32[4096, 1024]): Cannot find type promotion rule for op: aten.view.default\n\n## Additional Message:\n\n## Function Signature\n### Function Signature _TypePromotionInterpreter.run_node\n- self: \n- node: fx.Node(aten.view.default)[call_function]:Tensor(f32[4096, 1024])\n## Return values\nTensor(f32[4096, 1024])", + "text":"Skipped for fx.Node(aten.view.default)[call_function]:Tensor(f32[4096, 1024]): Cannot find type promotion rule for op: aten.view.default" + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":1625 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0015", + "stacks":[] + }, + { + "message":{ + "markdown":"Skipped for fx.Node(aten.t.default)[call_function]:Tensor(f32[1024, 3072]): Cannot find type promotion rule for op: aten.t.default\n\n## Additional Message:\n\n## Function Signature\n### Function Signature _TypePromotionInterpreter.run_node\n- self: \n- node: fx.Node(aten.t.default)[call_function]:Tensor(f32[1024, 3072])\n## Return values\nTensor(f32[1024, 3072])", + "text":"Skipped for fx.Node(aten.t.default)[call_function]:Tensor(f32[1024, 3072]): Cannot find type promotion rule for op: aten.t.default" + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":1625 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0015", + "stacks":[] + }, + { + "message":{ + "markdown":"Skipped for fx.Node(aten.addmm.default)[call_function]:Tensor(f32[4096, 3072]): Cannot find type promotion rule for op: aten.addmm.default\n\n## Additional Message:\n\n## Function Signature\n### Function Signature _TypePromotionInterpreter.run_node\n- self: \n- node: fx.Node(aten.addmm.default)[call_function]:Tensor(f32[4096, 3072])\n## Return values\nTensor(f32[4096, 3072])", + "text":"Skipped for fx.Node(aten.addmm.default)[call_function]:Tensor(f32[4096, 3072]): Cannot find type promotion rule for op: aten.addmm.default" + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":1625 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0015", + "stacks":[] + }, + { + "message":{ + "markdown":"Skipped for fx.Node(aten.view.default)[call_function]:Tensor(f32[4, 1024, 3072]): Cannot find type promotion rule for op: aten.view.default\n\n## Additional Message:\n\n## Function Signature\n### Function Signature _TypePromotionInterpreter.run_node\n- self: \n- node: fx.Node(aten.view.default)[call_function]:Tensor(f32[4, 1024, 3072])\n## Return values\nTensor(f32[4, 1024, 3072])", + "text":"Skipped for fx.Node(aten.view.default)[call_function]:Tensor(f32[4, 1024, 3072]): Cannot find type promotion rule for op: aten.view.default" + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":1625 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0015", + "stacks":[] + }, + { + "message":{ + "markdown":"Skipped for fx.Node(aten.view.default)[call_function]:Tensor(f32[4, 1024, 3, 16, 64]): Cannot find type promotion rule for op: aten.view.default\n\n## Additional Message:\n\n## Function Signature\n### Function Signature _TypePromotionInterpreter.run_node\n- self: \n- node: fx.Node(aten.view.default)[call_function]:Tensor(f32[4, 1024, 3, 16, 64])\n## Return values\nTensor(f32[4, 1024, 3, 16, 64])", + "text":"Skipped for fx.Node(aten.view.default)[call_function]:Tensor(f32[4, 1024, 3, 16, 64]): Cannot find type promotion rule for op: aten.view.default" + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":1625 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0015", + "stacks":[] + }, + { + "message":{ + "markdown":"Skipped for fx.Node(aten.permute.default)[call_function]:Tensor(f32[3, 4, 16, 1024, 64]): Cannot find type promotion rule for op: aten.permute.default\n\n## Additional Message:\n\n## Function Signature\n### Function Signature _TypePromotionInterpreter.run_node\n- self: \n- node: fx.Node(aten.permute.default)[call_function]:Tensor(f32[3, 4, 16, 1024, 64])\n## Return values\nTensor(f32[3, 4, 16, 1024, 64])", + "text":"Skipped for fx.Node(aten.permute.default)[call_function]:Tensor(f32[3, 4, 16, 1024, 64]): Cannot find type promotion rule for op: aten.permute.default" + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":1625 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0015", + "stacks":[] + }, + { + "message":{ + "markdown":"Skipped for fx.Node(aten.unbind.int)[call_function]:List[length=3](\nTensor(f32[4, 16, 1024, 64]),\nTensor(f32[4, 16, 1024, 64]),\nTensor(f32[4, 16, 1024, 64]),\n): Cannot find type promotion rule for op: aten.unbind.int\n\n## Additional Message:\n\n## Function Signature\n### Function Signature _TypePromotionInterpreter.run_node\n- self: \n- node: fx.Node(aten.unbind.int)[call_function]:List[length=3](\nTensor(f32[4, 16, 1024, 64]),\nTensor(f32[4, 16, 1024, 64]),\nTensor(f32[4, 16, 1024, 64]),\n)\n## Return values\nList[length=3](\nTensor(f32[4, 16, 1024, 64]),\nTensor(f32[4, 16, 1024, 64]),\nTensor(f32[4, 16, 1024, 64]),\n)", + "text":"Skipped for fx.Node(aten.unbind.int)[call_function]:List[length=3](\nTensor(f32[4, 16, 1024, 64]),\nTensor(f32[4, 16, 1024, 64]),\nTensor(f32[4, 16, 1024, 64]),\n): Cannot find type promotion rule for op: aten.unbind.int" + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":1625 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0015", + "stacks":[] + }, + { + "message":{ + "markdown":"Skipped for fx.Node()[call_function]:Tensor(f32[4, 16, 1024, 64]): node.target is not OpOverload. Got type: \n\n## Additional Message:\n\n## Function Signature\n### Function Signature _TypePromotionInterpreter.run_node\n- self: \n- node: fx.Node()[call_function]:Tensor(f32[4, 16, 1024, 64])\n## Return values\nTensor(f32[4, 16, 1024, 64])", + "text":"Skipped for fx.Node()[call_function]:Tensor(f32[4, 16, 1024, 64]): node.target is not OpOverload. Got type: " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":1625 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0015", + "stacks":[] + }, + { + "message":{ + "markdown":"Skipped for fx.Node()[call_function]:Tensor(f32[4, 16, 1024, 64]): node.target is not OpOverload. Got type: \n\n## Additional Message:\n\n## Function Signature\n### Function Signature _TypePromotionInterpreter.run_node\n- self: \n- node: fx.Node()[call_function]:Tensor(f32[4, 16, 1024, 64])\n## Return values\nTensor(f32[4, 16, 1024, 64])", + "text":"Skipped for fx.Node()[call_function]:Tensor(f32[4, 16, 1024, 64]): node.target is not OpOverload. Got type: " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":1625 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0015", + "stacks":[] + }, + { + "message":{ + "markdown":"Skipped for fx.Node()[call_function]:Tensor(f32[4, 16, 1024, 64]): node.target is not OpOverload. Got type: \n\n## Additional Message:\n\n## Function Signature\n### Function Signature _TypePromotionInterpreter.run_node\n- self: \n- node: fx.Node()[call_function]:Tensor(f32[4, 16, 1024, 64])\n## Return values\nTensor(f32[4, 16, 1024, 64])", + "text":"Skipped for fx.Node()[call_function]:Tensor(f32[4, 16, 1024, 64]): node.target is not OpOverload. Got type: " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":1625 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0015", + "stacks":[] + }, + { + "message":{ + "markdown":"Skipped for fx.Node(aten._scaled_dot_product_efficient_attention.default)[call_function]:Tuple[length=4](\nTensor(f32[4, 16, 1024, 64]),\nTensor(f32[4, 16, 0]),\nTensor(i64[]),\nTensor(i64[]),\n): Cannot find type promotion rule for op: aten._scaled_dot_product_efficient_attention.default\n\n## Additional Message:\n\n## Function Signature\n### Function Signature _TypePromotionInterpreter.run_node\n- self: \n- node: fx.Node(aten._scaled_dot_product_efficient_attention.default)[call_function]:Tuple[length=4](\nTensor(f32[4, 16, 1024, 64]),\nTensor(f32[4, 16, 0]),\nTensor(i64[]),\nTensor(i64[]),\n)\n## Return values\nTuple[length=4](\nTensor(f32[4, 16, 1024, 64]),\nTensor(f32[4, 16, 0]),\nTensor(i64[]),\nTensor(i64[]),\n)", + "text":"Skipped for fx.Node(aten._scaled_dot_product_efficient_attention.default)[call_function]:Tuple[length=4](\nTensor(f32[4, 16, 1024, 64]),\nTensor(f32[4, 16, 0]),\nTensor(i64[]),\nTensor(i64[]),\n): Cannot find type promotion rule for op: aten._scaled_dot_product_efficient_attention.default" + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":1625 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0015", + "stacks":[] + }, + { + "message":{ + "markdown":"Skipped for fx.Node()[call_function]:Tensor(f32[4, 16, 1024, 64]): node.target is not OpOverload. Got type: \n\n## Additional Message:\n\n## Function Signature\n### Function Signature _TypePromotionInterpreter.run_node\n- self: \n- node: fx.Node()[call_function]:Tensor(f32[4, 16, 1024, 64])\n## Return values\nTensor(f32[4, 16, 1024, 64])", + "text":"Skipped for fx.Node()[call_function]:Tensor(f32[4, 16, 1024, 64]): node.target is not OpOverload. Got type: " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":1625 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0015", + "stacks":[] + }, + { + "message":{ + "markdown":"Skipped for fx.Node(aten.transpose.int)[call_function]:Tensor(f32[4, 1024, 16, 64]): Cannot find type promotion rule for op: aten.transpose.int\n\n## Additional Message:\n\n## Function Signature\n### Function Signature _TypePromotionInterpreter.run_node\n- self: \n- node: fx.Node(aten.transpose.int)[call_function]:Tensor(f32[4, 1024, 16, 64])\n## Return values\nTensor(f32[4, 1024, 16, 64])", + "text":"Skipped for fx.Node(aten.transpose.int)[call_function]:Tensor(f32[4, 1024, 16, 64]): Cannot find type promotion rule for op: aten.transpose.int" + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":1625 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0015", + "stacks":[] + }, + { + "message":{ + "markdown":"Skipped for fx.Node(aten.view.default)[call_function]:Tensor(f32[4, 1024, 1024]): Cannot find type promotion rule for op: aten.view.default\n\n## Additional Message:\n\n## Function Signature\n### Function Signature _TypePromotionInterpreter.run_node\n- self: \n- node: fx.Node(aten.view.default)[call_function]:Tensor(f32[4, 1024, 1024])\n## Return values\nTensor(f32[4, 1024, 1024])", + "text":"Skipped for fx.Node(aten.view.default)[call_function]:Tensor(f32[4, 1024, 1024]): Cannot find type promotion rule for op: aten.view.default" + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":1625 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0015", + "stacks":[] + }, + { + "message":{ + "markdown":"Skipped for fx.Node(aten.view.default)[call_function]:Tensor(f32[4096, 1024]): Cannot find type promotion rule for op: aten.view.default\n\n## Additional Message:\n\n## Function Signature\n### Function Signature _TypePromotionInterpreter.run_node\n- self: \n- node: fx.Node(aten.view.default)[call_function]:Tensor(f32[4096, 1024])\n## Return values\nTensor(f32[4096, 1024])", + "text":"Skipped for fx.Node(aten.view.default)[call_function]:Tensor(f32[4096, 1024]): Cannot find type promotion rule for op: aten.view.default" + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":1625 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0015", + "stacks":[] + }, + { + "message":{ + "markdown":"Skipped for fx.Node(aten.t.default)[call_function]:Tensor(f32[1024, 1024]): Cannot find type promotion rule for op: aten.t.default\n\n## Additional Message:\n\n## Function Signature\n### Function Signature _TypePromotionInterpreter.run_node\n- self: \n- node: fx.Node(aten.t.default)[call_function]:Tensor(f32[1024, 1024])\n## Return values\nTensor(f32[1024, 1024])", + "text":"Skipped for fx.Node(aten.t.default)[call_function]:Tensor(f32[1024, 1024]): Cannot find type promotion rule for op: aten.t.default" + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":1625 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0015", + "stacks":[] + }, + { + "message":{ + "markdown":"Skipped for fx.Node(aten.addmm.default)[call_function]:Tensor(f32[4096, 1024]): Cannot find type promotion rule for op: aten.addmm.default\n\n## Additional Message:\n\n## Function Signature\n### Function Signature _TypePromotionInterpreter.run_node\n- self: \n- node: fx.Node(aten.addmm.default)[call_function]:Tensor(f32[4096, 1024])\n## Return values\nTensor(f32[4096, 1024])", + "text":"Skipped for fx.Node(aten.addmm.default)[call_function]:Tensor(f32[4096, 1024]): Cannot find type promotion rule for op: aten.addmm.default" + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":1625 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0015", + "stacks":[] + }, + { + "message":{ + "markdown":"Skipped for fx.Node(aten.view.default)[call_function]:Tensor(f32[4, 1024, 1024]): Cannot find type promotion rule for op: aten.view.default\n\n## Additional Message:\n\n## Function Signature\n### Function Signature _TypePromotionInterpreter.run_node\n- self: \n- node: fx.Node(aten.view.default)[call_function]:Tensor(f32[4, 1024, 1024])\n## Return values\nTensor(f32[4, 1024, 1024])", + "text":"Skipped for fx.Node(aten.view.default)[call_function]:Tensor(f32[4, 1024, 1024]): Cannot find type promotion rule for op: aten.view.default" + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":1625 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0015", + "stacks":[] + }, + { + "message":{ + "markdown":"Skipped for fx.Node(aten.clone.default)[call_function]:Tensor(f32[4, 1024, 1024]): Cannot find type promotion rule for op: aten.clone.default\n\n## Additional Message:\n\n## Function Signature\n### Function Signature _TypePromotionInterpreter.run_node\n- self: \n- node: fx.Node(aten.clone.default)[call_function]:Tensor(f32[4, 1024, 1024])\n## Return values\nTensor(f32[4, 1024, 1024])", + "text":"Skipped for fx.Node(aten.clone.default)[call_function]:Tensor(f32[4, 1024, 1024]): Cannot find type promotion rule for op: aten.clone.default" + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":1625 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0015", + "stacks":[] + }, + { + "message":{ + "markdown":"Type promotion not needed for add_31. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature _TypePromotionInterpreter.run_node\n- self: \n- node: fx.Node(aten.add.Tensor)[call_function]:Tensor(f32[4, 1024, 1024])\nFound type promotion rule: ElementwiseTypePromotionRule('aten', 'add', [0, 1], [], ELEMENTWISE_TYPE_PROMOTION_KIND.DEFAULT)\nArgument add_30 is not promoted. Already torch.float32.\nArgument clone_46 is not promoted. Already torch.float32.\n## Return values\nTensor(f32[4, 1024, 1024])", + "text":"Type promotion not needed for add_31. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":1625 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0015", + "stacks":[] + }, + { + "message":{ + "markdown":"Skipped for fx.Node(aten.native_layer_norm.default)[call_function]:Tuple[length=3](\nTensor(f32[4, 1024, 1024]),\nTensor(f32[4, 1024, 1]),\nTensor(f32[4, 1024, 1]),\n): Cannot find type promotion rule for op: aten.native_layer_norm.default\n\n## Additional Message:\n\n## Function Signature\n### Function Signature _TypePromotionInterpreter.run_node\n- self: \n- node: fx.Node(aten.native_layer_norm.default)[call_function]:Tuple[length=3](\nTensor(f32[4, 1024, 1024]),\nTensor(f32[4, 1024, 1]),\nTensor(f32[4, 1024, 1]),\n)\n## Return values\nTuple[length=3](\nTensor(f32[4, 1024, 1024]),\nTensor(f32[4, 1024, 1]),\nTensor(f32[4, 1024, 1]),\n)", + "text":"Skipped for fx.Node(aten.native_layer_norm.default)[call_function]:Tuple[length=3](\nTensor(f32[4, 1024, 1024]),\nTensor(f32[4, 1024, 1]),\nTensor(f32[4, 1024, 1]),\n): Cannot find type promotion rule for op: aten.native_layer_norm.default" + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":1625 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0015", + "stacks":[] + }, + { + "message":{ + "markdown":"Skipped for fx.Node()[call_function]:Tensor(f32[4, 1024, 1024]): node.target is not OpOverload. Got type: \n\n## Additional Message:\n\n## Function Signature\n### Function Signature _TypePromotionInterpreter.run_node\n- self: \n- node: fx.Node()[call_function]:Tensor(f32[4, 1024, 1024])\n## Return values\nTensor(f32[4, 1024, 1024])", + "text":"Skipped for fx.Node()[call_function]:Tensor(f32[4, 1024, 1024]): node.target is not OpOverload. Got type: " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":1625 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0015", + "stacks":[] + }, + { + "message":{ + "markdown":"Skipped for fx.Node(aten.view.default)[call_function]:Tensor(f32[4096, 1024]): Cannot find type promotion rule for op: aten.view.default\n\n## Additional Message:\n\n## Function Signature\n### Function Signature _TypePromotionInterpreter.run_node\n- self: \n- node: fx.Node(aten.view.default)[call_function]:Tensor(f32[4096, 1024])\n## Return values\nTensor(f32[4096, 1024])", + "text":"Skipped for fx.Node(aten.view.default)[call_function]:Tensor(f32[4096, 1024]): Cannot find type promotion rule for op: aten.view.default" + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":1625 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0015", + "stacks":[] + }, + { + "message":{ + "markdown":"Skipped for fx.Node(aten.t.default)[call_function]:Tensor(f32[1024, 4096]): Cannot find type promotion rule for op: aten.t.default\n\n## Additional Message:\n\n## Function Signature\n### Function Signature _TypePromotionInterpreter.run_node\n- self: \n- node: fx.Node(aten.t.default)[call_function]:Tensor(f32[1024, 4096])\n## Return values\nTensor(f32[1024, 4096])", + "text":"Skipped for fx.Node(aten.t.default)[call_function]:Tensor(f32[1024, 4096]): Cannot find type promotion rule for op: aten.t.default" + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":1625 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0015", + "stacks":[] + }, + { + "message":{ + "markdown":"Skipped for fx.Node(aten.addmm.default)[call_function]:Tensor(f32[4096, 4096]): Cannot find type promotion rule for op: aten.addmm.default\n\n## Additional Message:\n\n## Function Signature\n### Function Signature _TypePromotionInterpreter.run_node\n- self: \n- node: fx.Node(aten.addmm.default)[call_function]:Tensor(f32[4096, 4096])\n## Return values\nTensor(f32[4096, 4096])", + "text":"Skipped for fx.Node(aten.addmm.default)[call_function]:Tensor(f32[4096, 4096]): Cannot find type promotion rule for op: aten.addmm.default" + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":1625 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0015", + "stacks":[] + }, + { + "message":{ + "markdown":"Skipped for fx.Node(aten.view.default)[call_function]:Tensor(f32[4, 1024, 4096]): Cannot find type promotion rule for op: aten.view.default\n\n## Additional Message:\n\n## Function Signature\n### Function Signature _TypePromotionInterpreter.run_node\n- self: \n- node: fx.Node(aten.view.default)[call_function]:Tensor(f32[4, 1024, 4096])\n## Return values\nTensor(f32[4, 1024, 4096])", + "text":"Skipped for fx.Node(aten.view.default)[call_function]:Tensor(f32[4, 1024, 4096]): Cannot find type promotion rule for op: aten.view.default" + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":1625 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0015", + "stacks":[] + }, + { + "message":{ + "markdown":"Type promotion not needed for gelu_15. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature _TypePromotionInterpreter.run_node\n- self: \n- node: fx.Node(aten.gelu.default)[call_function]:Tensor(f32[4, 1024, 4096])\nFound type promotion rule: ElementwiseTypePromotionRule('aten', 'gelu', [0], [], ELEMENTWISE_TYPE_PROMOTION_KIND.DEFAULT)\nArgument view_158 is not promoted. Already torch.float32.\nArgument tanh is not promoted. Not mentioned by type promotion rule.\n## Return values\nTensor(f32[4, 1024, 4096])", + "text":"Type promotion not needed for gelu_15. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":1625 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0015", + "stacks":[] + }, + { + "message":{ + "markdown":"Skipped for fx.Node(aten.clone.default)[call_function]:Tensor(f32[4, 1024, 4096]): Cannot find type promotion rule for op: aten.clone.default\n\n## Additional Message:\n\n## Function Signature\n### Function Signature _TypePromotionInterpreter.run_node\n- self: \n- node: fx.Node(aten.clone.default)[call_function]:Tensor(f32[4, 1024, 4096])\n## Return values\nTensor(f32[4, 1024, 4096])", + "text":"Skipped for fx.Node(aten.clone.default)[call_function]:Tensor(f32[4, 1024, 4096]): Cannot find type promotion rule for op: aten.clone.default" + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":1625 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0015", + "stacks":[] + }, + { + "message":{ + "markdown":"Skipped for fx.Node(aten.view.default)[call_function]:Tensor(f32[4096, 4096]): Cannot find type promotion rule for op: aten.view.default\n\n## Additional Message:\n\n## Function Signature\n### Function Signature _TypePromotionInterpreter.run_node\n- self: \n- node: fx.Node(aten.view.default)[call_function]:Tensor(f32[4096, 4096])\n## Return values\nTensor(f32[4096, 4096])", + "text":"Skipped for fx.Node(aten.view.default)[call_function]:Tensor(f32[4096, 4096]): Cannot find type promotion rule for op: aten.view.default" + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":1625 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0015", + "stacks":[] + }, + { + "message":{ + "markdown":"Skipped for fx.Node(aten.t.default)[call_function]:Tensor(f32[4096, 1024]): Cannot find type promotion rule for op: aten.t.default\n\n## Additional Message:\n\n## Function Signature\n### Function Signature _TypePromotionInterpreter.run_node\n- self: \n- node: fx.Node(aten.t.default)[call_function]:Tensor(f32[4096, 1024])\n## Return values\nTensor(f32[4096, 1024])", + "text":"Skipped for fx.Node(aten.t.default)[call_function]:Tensor(f32[4096, 1024]): Cannot find type promotion rule for op: aten.t.default" + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":1625 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0015", + "stacks":[] + }, + { + "message":{ + "markdown":"Skipped for fx.Node(aten.addmm.default)[call_function]:Tensor(f32[4096, 1024]): Cannot find type promotion rule for op: aten.addmm.default\n\n## Additional Message:\n\n## Function Signature\n### Function Signature _TypePromotionInterpreter.run_node\n- self: \n- node: fx.Node(aten.addmm.default)[call_function]:Tensor(f32[4096, 1024])\n## Return values\nTensor(f32[4096, 1024])", + "text":"Skipped for fx.Node(aten.addmm.default)[call_function]:Tensor(f32[4096, 1024]): Cannot find type promotion rule for op: aten.addmm.default" + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":1625 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0015", + "stacks":[] + }, + { + "message":{ + "markdown":"Skipped for fx.Node(aten.view.default)[call_function]:Tensor(f32[4, 1024, 1024]): Cannot find type promotion rule for op: aten.view.default\n\n## Additional Message:\n\n## Function Signature\n### Function Signature _TypePromotionInterpreter.run_node\n- self: \n- node: fx.Node(aten.view.default)[call_function]:Tensor(f32[4, 1024, 1024])\n## Return values\nTensor(f32[4, 1024, 1024])", + "text":"Skipped for fx.Node(aten.view.default)[call_function]:Tensor(f32[4, 1024, 1024]): Cannot find type promotion rule for op: aten.view.default" + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":1625 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0015", + "stacks":[] + }, + { + "message":{ + "markdown":"Skipped for fx.Node(aten.clone.default)[call_function]:Tensor(f32[4, 1024, 1024]): Cannot find type promotion rule for op: aten.clone.default\n\n## Additional Message:\n\n## Function Signature\n### Function Signature _TypePromotionInterpreter.run_node\n- self: \n- node: fx.Node(aten.clone.default)[call_function]:Tensor(f32[4, 1024, 1024])\n## Return values\nTensor(f32[4, 1024, 1024])", + "text":"Skipped for fx.Node(aten.clone.default)[call_function]:Tensor(f32[4, 1024, 1024]): Cannot find type promotion rule for op: aten.clone.default" + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":1625 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0015", + "stacks":[] + }, + { + "message":{ + "markdown":"Type promotion not needed for add_32. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature _TypePromotionInterpreter.run_node\n- self: \n- node: fx.Node(aten.add.Tensor)[call_function]:Tensor(f32[4, 1024, 1024])\nFound type promotion rule: ElementwiseTypePromotionRule('aten', 'add', [0, 1], [], ELEMENTWISE_TYPE_PROMOTION_KIND.DEFAULT)\nArgument add_31 is not promoted. Already torch.float32.\nArgument clone_48 is not promoted. Already torch.float32.\n## Return values\nTensor(f32[4, 1024, 1024])", + "text":"Type promotion not needed for add_32. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":1625 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0015", + "stacks":[] + }, + { + "message":{ + "markdown":"Skipped for fx.Node(aten.native_layer_norm.default)[call_function]:Tuple[length=3](\nTensor(f32[4, 1024, 1024]),\nTensor(f32[4, 1024, 1]),\nTensor(f32[4, 1024, 1]),\n): Cannot find type promotion rule for op: aten.native_layer_norm.default\n\n## Additional Message:\n\n## Function Signature\n### Function Signature _TypePromotionInterpreter.run_node\n- self: \n- node: fx.Node(aten.native_layer_norm.default)[call_function]:Tuple[length=3](\nTensor(f32[4, 1024, 1024]),\nTensor(f32[4, 1024, 1]),\nTensor(f32[4, 1024, 1]),\n)\n## Return values\nTuple[length=3](\nTensor(f32[4, 1024, 1024]),\nTensor(f32[4, 1024, 1]),\nTensor(f32[4, 1024, 1]),\n)", + "text":"Skipped for fx.Node(aten.native_layer_norm.default)[call_function]:Tuple[length=3](\nTensor(f32[4, 1024, 1024]),\nTensor(f32[4, 1024, 1]),\nTensor(f32[4, 1024, 1]),\n): Cannot find type promotion rule for op: aten.native_layer_norm.default" + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":1625 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0015", + "stacks":[] + }, + { + "message":{ + "markdown":"Skipped for fx.Node()[call_function]:Tensor(f32[4, 1024, 1024]): node.target is not OpOverload. Got type: \n\n## Additional Message:\n\n## Function Signature\n### Function Signature _TypePromotionInterpreter.run_node\n- self: \n- node: fx.Node()[call_function]:Tensor(f32[4, 1024, 1024])\n## Return values\nTensor(f32[4, 1024, 1024])", + "text":"Skipped for fx.Node()[call_function]:Tensor(f32[4, 1024, 1024]): node.target is not OpOverload. Got type: " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":1625 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0015", + "stacks":[] + }, + { + "message":{ + "markdown":"Skipped for fx.Node(aten.view.default)[call_function]:Tensor(f32[4096, 1024]): Cannot find type promotion rule for op: aten.view.default\n\n## Additional Message:\n\n## Function Signature\n### Function Signature _TypePromotionInterpreter.run_node\n- self: \n- node: fx.Node(aten.view.default)[call_function]:Tensor(f32[4096, 1024])\n## Return values\nTensor(f32[4096, 1024])", + "text":"Skipped for fx.Node(aten.view.default)[call_function]:Tensor(f32[4096, 1024]): Cannot find type promotion rule for op: aten.view.default" + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":1625 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0015", + "stacks":[] + }, + { + "message":{ + "markdown":"Skipped for fx.Node(aten.t.default)[call_function]:Tensor(f32[1024, 3072]): Cannot find type promotion rule for op: aten.t.default\n\n## Additional Message:\n\n## Function Signature\n### Function Signature _TypePromotionInterpreter.run_node\n- self: \n- node: fx.Node(aten.t.default)[call_function]:Tensor(f32[1024, 3072])\n## Return values\nTensor(f32[1024, 3072])", + "text":"Skipped for fx.Node(aten.t.default)[call_function]:Tensor(f32[1024, 3072]): Cannot find type promotion rule for op: aten.t.default" + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":1625 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0015", + "stacks":[] + }, + { + "message":{ + "markdown":"Skipped for fx.Node(aten.addmm.default)[call_function]:Tensor(f32[4096, 3072]): Cannot find type promotion rule for op: aten.addmm.default\n\n## Additional Message:\n\n## Function Signature\n### Function Signature _TypePromotionInterpreter.run_node\n- self: \n- node: fx.Node(aten.addmm.default)[call_function]:Tensor(f32[4096, 3072])\n## Return values\nTensor(f32[4096, 3072])", + "text":"Skipped for fx.Node(aten.addmm.default)[call_function]:Tensor(f32[4096, 3072]): Cannot find type promotion rule for op: aten.addmm.default" + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":1625 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0015", + "stacks":[] + }, + { + "message":{ + "markdown":"Skipped for fx.Node(aten.view.default)[call_function]:Tensor(f32[4, 1024, 3072]): Cannot find type promotion rule for op: aten.view.default\n\n## Additional Message:\n\n## Function Signature\n### Function Signature _TypePromotionInterpreter.run_node\n- self: \n- node: fx.Node(aten.view.default)[call_function]:Tensor(f32[4, 1024, 3072])\n## Return values\nTensor(f32[4, 1024, 3072])", + "text":"Skipped for fx.Node(aten.view.default)[call_function]:Tensor(f32[4, 1024, 3072]): Cannot find type promotion rule for op: aten.view.default" + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":1625 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0015", + "stacks":[] + }, + { + "message":{ + "markdown":"Skipped for fx.Node(aten.view.default)[call_function]:Tensor(f32[4, 1024, 3, 16, 64]): Cannot find type promotion rule for op: aten.view.default\n\n## Additional Message:\n\n## Function Signature\n### Function Signature _TypePromotionInterpreter.run_node\n- self: \n- node: fx.Node(aten.view.default)[call_function]:Tensor(f32[4, 1024, 3, 16, 64])\n## Return values\nTensor(f32[4, 1024, 3, 16, 64])", + "text":"Skipped for fx.Node(aten.view.default)[call_function]:Tensor(f32[4, 1024, 3, 16, 64]): Cannot find type promotion rule for op: aten.view.default" + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":1625 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0015", + "stacks":[] + }, + { + "message":{ + "markdown":"Skipped for fx.Node(aten.permute.default)[call_function]:Tensor(f32[3, 4, 16, 1024, 64]): Cannot find type promotion rule for op: aten.permute.default\n\n## Additional Message:\n\n## Function Signature\n### Function Signature _TypePromotionInterpreter.run_node\n- self: \n- node: fx.Node(aten.permute.default)[call_function]:Tensor(f32[3, 4, 16, 1024, 64])\n## Return values\nTensor(f32[3, 4, 16, 1024, 64])", + "text":"Skipped for fx.Node(aten.permute.default)[call_function]:Tensor(f32[3, 4, 16, 1024, 64]): Cannot find type promotion rule for op: aten.permute.default" + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":1625 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0015", + "stacks":[] + }, + { + "message":{ + "markdown":"Skipped for fx.Node(aten.unbind.int)[call_function]:List[length=3](\nTensor(f32[4, 16, 1024, 64]),\nTensor(f32[4, 16, 1024, 64]),\nTensor(f32[4, 16, 1024, 64]),\n): Cannot find type promotion rule for op: aten.unbind.int\n\n## Additional Message:\n\n## Function Signature\n### Function Signature _TypePromotionInterpreter.run_node\n- self: \n- node: fx.Node(aten.unbind.int)[call_function]:List[length=3](\nTensor(f32[4, 16, 1024, 64]),\nTensor(f32[4, 16, 1024, 64]),\nTensor(f32[4, 16, 1024, 64]),\n)\n## Return values\nList[length=3](\nTensor(f32[4, 16, 1024, 64]),\nTensor(f32[4, 16, 1024, 64]),\nTensor(f32[4, 16, 1024, 64]),\n)", + "text":"Skipped for fx.Node(aten.unbind.int)[call_function]:List[length=3](\nTensor(f32[4, 16, 1024, 64]),\nTensor(f32[4, 16, 1024, 64]),\nTensor(f32[4, 16, 1024, 64]),\n): Cannot find type promotion rule for op: aten.unbind.int" + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":1625 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0015", + "stacks":[] + }, + { + "message":{ + "markdown":"Skipped for fx.Node()[call_function]:Tensor(f32[4, 16, 1024, 64]): node.target is not OpOverload. Got type: \n\n## Additional Message:\n\n## Function Signature\n### Function Signature _TypePromotionInterpreter.run_node\n- self: \n- node: fx.Node()[call_function]:Tensor(f32[4, 16, 1024, 64])\n## Return values\nTensor(f32[4, 16, 1024, 64])", + "text":"Skipped for fx.Node()[call_function]:Tensor(f32[4, 16, 1024, 64]): node.target is not OpOverload. Got type: " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":1625 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0015", + "stacks":[] + }, + { + "message":{ + "markdown":"Skipped for fx.Node()[call_function]:Tensor(f32[4, 16, 1024, 64]): node.target is not OpOverload. Got type: \n\n## Additional Message:\n\n## Function Signature\n### Function Signature _TypePromotionInterpreter.run_node\n- self: \n- node: fx.Node()[call_function]:Tensor(f32[4, 16, 1024, 64])\n## Return values\nTensor(f32[4, 16, 1024, 64])", + "text":"Skipped for fx.Node()[call_function]:Tensor(f32[4, 16, 1024, 64]): node.target is not OpOverload. Got type: " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":1625 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0015", + "stacks":[] + }, + { + "message":{ + "markdown":"Skipped for fx.Node()[call_function]:Tensor(f32[4, 16, 1024, 64]): node.target is not OpOverload. Got type: \n\n## Additional Message:\n\n## Function Signature\n### Function Signature _TypePromotionInterpreter.run_node\n- self: \n- node: fx.Node()[call_function]:Tensor(f32[4, 16, 1024, 64])\n## Return values\nTensor(f32[4, 16, 1024, 64])", + "text":"Skipped for fx.Node()[call_function]:Tensor(f32[4, 16, 1024, 64]): node.target is not OpOverload. Got type: " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":1625 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0015", + "stacks":[] + }, + { + "message":{ + "markdown":"Skipped for fx.Node(aten._scaled_dot_product_efficient_attention.default)[call_function]:Tuple[length=4](\nTensor(f32[4, 16, 1024, 64]),\nTensor(f32[4, 16, 0]),\nTensor(i64[]),\nTensor(i64[]),\n): Cannot find type promotion rule for op: aten._scaled_dot_product_efficient_attention.default\n\n## Additional Message:\n\n## Function Signature\n### Function Signature _TypePromotionInterpreter.run_node\n- self: \n- node: fx.Node(aten._scaled_dot_product_efficient_attention.default)[call_function]:Tuple[length=4](\nTensor(f32[4, 16, 1024, 64]),\nTensor(f32[4, 16, 0]),\nTensor(i64[]),\nTensor(i64[]),\n)\n## Return values\nTuple[length=4](\nTensor(f32[4, 16, 1024, 64]),\nTensor(f32[4, 16, 0]),\nTensor(i64[]),\nTensor(i64[]),\n)", + "text":"Skipped for fx.Node(aten._scaled_dot_product_efficient_attention.default)[call_function]:Tuple[length=4](\nTensor(f32[4, 16, 1024, 64]),\nTensor(f32[4, 16, 0]),\nTensor(i64[]),\nTensor(i64[]),\n): Cannot find type promotion rule for op: aten._scaled_dot_product_efficient_attention.default" + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":1625 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0015", + "stacks":[] + }, + { + "message":{ + "markdown":"Skipped for fx.Node()[call_function]:Tensor(f32[4, 16, 1024, 64]): node.target is not OpOverload. Got type: \n\n## Additional Message:\n\n## Function Signature\n### Function Signature _TypePromotionInterpreter.run_node\n- self: \n- node: fx.Node()[call_function]:Tensor(f32[4, 16, 1024, 64])\n## Return values\nTensor(f32[4, 16, 1024, 64])", + "text":"Skipped for fx.Node()[call_function]:Tensor(f32[4, 16, 1024, 64]): node.target is not OpOverload. Got type: " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":1625 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0015", + "stacks":[] + }, + { + "message":{ + "markdown":"Skipped for fx.Node(aten.transpose.int)[call_function]:Tensor(f32[4, 1024, 16, 64]): Cannot find type promotion rule for op: aten.transpose.int\n\n## Additional Message:\n\n## Function Signature\n### Function Signature _TypePromotionInterpreter.run_node\n- self: \n- node: fx.Node(aten.transpose.int)[call_function]:Tensor(f32[4, 1024, 16, 64])\n## Return values\nTensor(f32[4, 1024, 16, 64])", + "text":"Skipped for fx.Node(aten.transpose.int)[call_function]:Tensor(f32[4, 1024, 16, 64]): Cannot find type promotion rule for op: aten.transpose.int" + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":1625 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0015", + "stacks":[] + }, + { + "message":{ + "markdown":"Skipped for fx.Node(aten.view.default)[call_function]:Tensor(f32[4, 1024, 1024]): Cannot find type promotion rule for op: aten.view.default\n\n## Additional Message:\n\n## Function Signature\n### Function Signature _TypePromotionInterpreter.run_node\n- self: \n- node: fx.Node(aten.view.default)[call_function]:Tensor(f32[4, 1024, 1024])\n## Return values\nTensor(f32[4, 1024, 1024])", + "text":"Skipped for fx.Node(aten.view.default)[call_function]:Tensor(f32[4, 1024, 1024]): Cannot find type promotion rule for op: aten.view.default" + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":1625 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0015", + "stacks":[] + }, + { + "message":{ + "markdown":"Skipped for fx.Node(aten.view.default)[call_function]:Tensor(f32[4096, 1024]): Cannot find type promotion rule for op: aten.view.default\n\n## Additional Message:\n\n## Function Signature\n### Function Signature _TypePromotionInterpreter.run_node\n- self: \n- node: fx.Node(aten.view.default)[call_function]:Tensor(f32[4096, 1024])\n## Return values\nTensor(f32[4096, 1024])", + "text":"Skipped for fx.Node(aten.view.default)[call_function]:Tensor(f32[4096, 1024]): Cannot find type promotion rule for op: aten.view.default" + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":1625 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0015", + "stacks":[] + }, + { + "message":{ + "markdown":"Skipped for fx.Node(aten.t.default)[call_function]:Tensor(f32[1024, 1024]): Cannot find type promotion rule for op: aten.t.default\n\n## Additional Message:\n\n## Function Signature\n### Function Signature _TypePromotionInterpreter.run_node\n- self: \n- node: fx.Node(aten.t.default)[call_function]:Tensor(f32[1024, 1024])\n## Return values\nTensor(f32[1024, 1024])", + "text":"Skipped for fx.Node(aten.t.default)[call_function]:Tensor(f32[1024, 1024]): Cannot find type promotion rule for op: aten.t.default" + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":1625 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0015", + "stacks":[] + }, + { + "message":{ + "markdown":"Skipped for fx.Node(aten.addmm.default)[call_function]:Tensor(f32[4096, 1024]): Cannot find type promotion rule for op: aten.addmm.default\n\n## Additional Message:\n\n## Function Signature\n### Function Signature _TypePromotionInterpreter.run_node\n- self: \n- node: fx.Node(aten.addmm.default)[call_function]:Tensor(f32[4096, 1024])\n## Return values\nTensor(f32[4096, 1024])", + "text":"Skipped for fx.Node(aten.addmm.default)[call_function]:Tensor(f32[4096, 1024]): Cannot find type promotion rule for op: aten.addmm.default" + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":1625 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0015", + "stacks":[] + }, + { + "message":{ + "markdown":"Skipped for fx.Node(aten.view.default)[call_function]:Tensor(f32[4, 1024, 1024]): Cannot find type promotion rule for op: aten.view.default\n\n## Additional Message:\n\n## Function Signature\n### Function Signature _TypePromotionInterpreter.run_node\n- self: \n- node: fx.Node(aten.view.default)[call_function]:Tensor(f32[4, 1024, 1024])\n## Return values\nTensor(f32[4, 1024, 1024])", + "text":"Skipped for fx.Node(aten.view.default)[call_function]:Tensor(f32[4, 1024, 1024]): Cannot find type promotion rule for op: aten.view.default" + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":1625 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0015", + "stacks":[] + }, + { + "message":{ + "markdown":"Skipped for fx.Node(aten.clone.default)[call_function]:Tensor(f32[4, 1024, 1024]): Cannot find type promotion rule for op: aten.clone.default\n\n## Additional Message:\n\n## Function Signature\n### Function Signature _TypePromotionInterpreter.run_node\n- self: \n- node: fx.Node(aten.clone.default)[call_function]:Tensor(f32[4, 1024, 1024])\n## Return values\nTensor(f32[4, 1024, 1024])", + "text":"Skipped for fx.Node(aten.clone.default)[call_function]:Tensor(f32[4, 1024, 1024]): Cannot find type promotion rule for op: aten.clone.default" + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":1625 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0015", + "stacks":[] + }, + { + "message":{ + "markdown":"Type promotion not needed for add_33. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature _TypePromotionInterpreter.run_node\n- self: \n- node: fx.Node(aten.add.Tensor)[call_function]:Tensor(f32[4, 1024, 1024])\nFound type promotion rule: ElementwiseTypePromotionRule('aten', 'add', [0, 1], [], ELEMENTWISE_TYPE_PROMOTION_KIND.DEFAULT)\nArgument add_32 is not promoted. Already torch.float32.\nArgument clone_49 is not promoted. Already torch.float32.\n## Return values\nTensor(f32[4, 1024, 1024])", + "text":"Type promotion not needed for add_33. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":1625 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0015", + "stacks":[] + }, + { + "message":{ + "markdown":"Skipped for fx.Node(aten.native_layer_norm.default)[call_function]:Tuple[length=3](\nTensor(f32[4, 1024, 1024]),\nTensor(f32[4, 1024, 1]),\nTensor(f32[4, 1024, 1]),\n): Cannot find type promotion rule for op: aten.native_layer_norm.default\n\n## Additional Message:\n\n## Function Signature\n### Function Signature _TypePromotionInterpreter.run_node\n- self: \n- node: fx.Node(aten.native_layer_norm.default)[call_function]:Tuple[length=3](\nTensor(f32[4, 1024, 1024]),\nTensor(f32[4, 1024, 1]),\nTensor(f32[4, 1024, 1]),\n)\n## Return values\nTuple[length=3](\nTensor(f32[4, 1024, 1024]),\nTensor(f32[4, 1024, 1]),\nTensor(f32[4, 1024, 1]),\n)", + "text":"Skipped for fx.Node(aten.native_layer_norm.default)[call_function]:Tuple[length=3](\nTensor(f32[4, 1024, 1024]),\nTensor(f32[4, 1024, 1]),\nTensor(f32[4, 1024, 1]),\n): Cannot find type promotion rule for op: aten.native_layer_norm.default" + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":1625 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0015", + "stacks":[] + }, + { + "message":{ + "markdown":"Skipped for fx.Node()[call_function]:Tensor(f32[4, 1024, 1024]): node.target is not OpOverload. Got type: \n\n## Additional Message:\n\n## Function Signature\n### Function Signature _TypePromotionInterpreter.run_node\n- self: \n- node: fx.Node()[call_function]:Tensor(f32[4, 1024, 1024])\n## Return values\nTensor(f32[4, 1024, 1024])", + "text":"Skipped for fx.Node()[call_function]:Tensor(f32[4, 1024, 1024]): node.target is not OpOverload. Got type: " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":1625 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0015", + "stacks":[] + }, + { + "message":{ + "markdown":"Skipped for fx.Node(aten.view.default)[call_function]:Tensor(f32[4096, 1024]): Cannot find type promotion rule for op: aten.view.default\n\n## Additional Message:\n\n## Function Signature\n### Function Signature _TypePromotionInterpreter.run_node\n- self: \n- node: fx.Node(aten.view.default)[call_function]:Tensor(f32[4096, 1024])\n## Return values\nTensor(f32[4096, 1024])", + "text":"Skipped for fx.Node(aten.view.default)[call_function]:Tensor(f32[4096, 1024]): Cannot find type promotion rule for op: aten.view.default" + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":1625 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0015", + "stacks":[] + }, + { + "message":{ + "markdown":"Skipped for fx.Node(aten.t.default)[call_function]:Tensor(f32[1024, 4096]): Cannot find type promotion rule for op: aten.t.default\n\n## Additional Message:\n\n## Function Signature\n### Function Signature _TypePromotionInterpreter.run_node\n- self: \n- node: fx.Node(aten.t.default)[call_function]:Tensor(f32[1024, 4096])\n## Return values\nTensor(f32[1024, 4096])", + "text":"Skipped for fx.Node(aten.t.default)[call_function]:Tensor(f32[1024, 4096]): Cannot find type promotion rule for op: aten.t.default" + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":1625 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0015", + "stacks":[] + }, + { + "message":{ + "markdown":"Skipped for fx.Node(aten.addmm.default)[call_function]:Tensor(f32[4096, 4096]): Cannot find type promotion rule for op: aten.addmm.default\n\n## Additional Message:\n\n## Function Signature\n### Function Signature _TypePromotionInterpreter.run_node\n- self: \n- node: fx.Node(aten.addmm.default)[call_function]:Tensor(f32[4096, 4096])\n## Return values\nTensor(f32[4096, 4096])", + "text":"Skipped for fx.Node(aten.addmm.default)[call_function]:Tensor(f32[4096, 4096]): Cannot find type promotion rule for op: aten.addmm.default" + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":1625 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0015", + "stacks":[] + }, + { + "message":{ + "markdown":"Skipped for fx.Node(aten.view.default)[call_function]:Tensor(f32[4, 1024, 4096]): Cannot find type promotion rule for op: aten.view.default\n\n## Additional Message:\n\n## Function Signature\n### Function Signature _TypePromotionInterpreter.run_node\n- self: \n- node: fx.Node(aten.view.default)[call_function]:Tensor(f32[4, 1024, 4096])\n## Return values\nTensor(f32[4, 1024, 4096])", + "text":"Skipped for fx.Node(aten.view.default)[call_function]:Tensor(f32[4, 1024, 4096]): Cannot find type promotion rule for op: aten.view.default" + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":1625 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0015", + "stacks":[] + }, + { + "message":{ + "markdown":"Type promotion not needed for gelu_16. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature _TypePromotionInterpreter.run_node\n- self: \n- node: fx.Node(aten.gelu.default)[call_function]:Tensor(f32[4, 1024, 4096])\nFound type promotion rule: ElementwiseTypePromotionRule('aten', 'gelu', [0], [], ELEMENTWISE_TYPE_PROMOTION_KIND.DEFAULT)\nArgument view_168 is not promoted. Already torch.float32.\nArgument tanh is not promoted. Not mentioned by type promotion rule.\n## Return values\nTensor(f32[4, 1024, 4096])", + "text":"Type promotion not needed for gelu_16. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":1625 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0015", + "stacks":[] + }, + { + "message":{ + "markdown":"Skipped for fx.Node(aten.clone.default)[call_function]:Tensor(f32[4, 1024, 4096]): Cannot find type promotion rule for op: aten.clone.default\n\n## Additional Message:\n\n## Function Signature\n### Function Signature _TypePromotionInterpreter.run_node\n- self: \n- node: fx.Node(aten.clone.default)[call_function]:Tensor(f32[4, 1024, 4096])\n## Return values\nTensor(f32[4, 1024, 4096])", + "text":"Skipped for fx.Node(aten.clone.default)[call_function]:Tensor(f32[4, 1024, 4096]): Cannot find type promotion rule for op: aten.clone.default" + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":1625 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0015", + "stacks":[] + }, + { + "message":{ + "markdown":"Skipped for fx.Node(aten.view.default)[call_function]:Tensor(f32[4096, 4096]): Cannot find type promotion rule for op: aten.view.default\n\n## Additional Message:\n\n## Function Signature\n### Function Signature _TypePromotionInterpreter.run_node\n- self: \n- node: fx.Node(aten.view.default)[call_function]:Tensor(f32[4096, 4096])\n## Return values\nTensor(f32[4096, 4096])", + "text":"Skipped for fx.Node(aten.view.default)[call_function]:Tensor(f32[4096, 4096]): Cannot find type promotion rule for op: aten.view.default" + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":1625 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0015", + "stacks":[] + }, + { + "message":{ + "markdown":"Skipped for fx.Node(aten.t.default)[call_function]:Tensor(f32[4096, 1024]): Cannot find type promotion rule for op: aten.t.default\n\n## Additional Message:\n\n## Function Signature\n### Function Signature _TypePromotionInterpreter.run_node\n- self: \n- node: fx.Node(aten.t.default)[call_function]:Tensor(f32[4096, 1024])\n## Return values\nTensor(f32[4096, 1024])", + "text":"Skipped for fx.Node(aten.t.default)[call_function]:Tensor(f32[4096, 1024]): Cannot find type promotion rule for op: aten.t.default" + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":1625 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0015", + "stacks":[] + }, + { + "message":{ + "markdown":"Skipped for fx.Node(aten.addmm.default)[call_function]:Tensor(f32[4096, 1024]): Cannot find type promotion rule for op: aten.addmm.default\n\n## Additional Message:\n\n## Function Signature\n### Function Signature _TypePromotionInterpreter.run_node\n- self: \n- node: fx.Node(aten.addmm.default)[call_function]:Tensor(f32[4096, 1024])\n## Return values\nTensor(f32[4096, 1024])", + "text":"Skipped for fx.Node(aten.addmm.default)[call_function]:Tensor(f32[4096, 1024]): Cannot find type promotion rule for op: aten.addmm.default" + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":1625 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0015", + "stacks":[] + }, + { + "message":{ + "markdown":"Skipped for fx.Node(aten.view.default)[call_function]:Tensor(f32[4, 1024, 1024]): Cannot find type promotion rule for op: aten.view.default\n\n## Additional Message:\n\n## Function Signature\n### Function Signature _TypePromotionInterpreter.run_node\n- self: \n- node: fx.Node(aten.view.default)[call_function]:Tensor(f32[4, 1024, 1024])\n## Return values\nTensor(f32[4, 1024, 1024])", + "text":"Skipped for fx.Node(aten.view.default)[call_function]:Tensor(f32[4, 1024, 1024]): Cannot find type promotion rule for op: aten.view.default" + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":1625 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0015", + "stacks":[] + }, + { + "message":{ + "markdown":"Skipped for fx.Node(aten.clone.default)[call_function]:Tensor(f32[4, 1024, 1024]): Cannot find type promotion rule for op: aten.clone.default\n\n## Additional Message:\n\n## Function Signature\n### Function Signature _TypePromotionInterpreter.run_node\n- self: \n- node: fx.Node(aten.clone.default)[call_function]:Tensor(f32[4, 1024, 1024])\n## Return values\nTensor(f32[4, 1024, 1024])", + "text":"Skipped for fx.Node(aten.clone.default)[call_function]:Tensor(f32[4, 1024, 1024]): Cannot find type promotion rule for op: aten.clone.default" + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":1625 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0015", + "stacks":[] + }, + { + "message":{ + "markdown":"Type promotion not needed for add_34. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature _TypePromotionInterpreter.run_node\n- self: \n- node: fx.Node(aten.add.Tensor)[call_function]:Tensor(f32[4, 1024, 1024])\nFound type promotion rule: ElementwiseTypePromotionRule('aten', 'add', [0, 1], [], ELEMENTWISE_TYPE_PROMOTION_KIND.DEFAULT)\nArgument add_33 is not promoted. Already torch.float32.\nArgument clone_51 is not promoted. Already torch.float32.\n## Return values\nTensor(f32[4, 1024, 1024])", + "text":"Type promotion not needed for add_34. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":1625 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0015", + "stacks":[] + }, + { + "message":{ + "markdown":"Skipped for fx.Node(aten.native_layer_norm.default)[call_function]:Tuple[length=3](\nTensor(f32[4, 1024, 1024]),\nTensor(f32[4, 1024, 1]),\nTensor(f32[4, 1024, 1]),\n): Cannot find type promotion rule for op: aten.native_layer_norm.default\n\n## Additional Message:\n\n## Function Signature\n### Function Signature _TypePromotionInterpreter.run_node\n- self: \n- node: fx.Node(aten.native_layer_norm.default)[call_function]:Tuple[length=3](\nTensor(f32[4, 1024, 1024]),\nTensor(f32[4, 1024, 1]),\nTensor(f32[4, 1024, 1]),\n)\n## Return values\nTuple[length=3](\nTensor(f32[4, 1024, 1024]),\nTensor(f32[4, 1024, 1]),\nTensor(f32[4, 1024, 1]),\n)", + "text":"Skipped for fx.Node(aten.native_layer_norm.default)[call_function]:Tuple[length=3](\nTensor(f32[4, 1024, 1024]),\nTensor(f32[4, 1024, 1]),\nTensor(f32[4, 1024, 1]),\n): Cannot find type promotion rule for op: aten.native_layer_norm.default" + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":1625 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0015", + "stacks":[] + }, + { + "message":{ + "markdown":"Skipped for fx.Node()[call_function]:Tensor(f32[4, 1024, 1024]): node.target is not OpOverload. Got type: \n\n## Additional Message:\n\n## Function Signature\n### Function Signature _TypePromotionInterpreter.run_node\n- self: \n- node: fx.Node()[call_function]:Tensor(f32[4, 1024, 1024])\n## Return values\nTensor(f32[4, 1024, 1024])", + "text":"Skipped for fx.Node()[call_function]:Tensor(f32[4, 1024, 1024]): node.target is not OpOverload. Got type: " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":1625 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0015", + "stacks":[] + }, + { + "message":{ + "markdown":"Skipped for fx.Node(aten.view.default)[call_function]:Tensor(f32[4096, 1024]): Cannot find type promotion rule for op: aten.view.default\n\n## Additional Message:\n\n## Function Signature\n### Function Signature _TypePromotionInterpreter.run_node\n- self: \n- node: fx.Node(aten.view.default)[call_function]:Tensor(f32[4096, 1024])\n## Return values\nTensor(f32[4096, 1024])", + "text":"Skipped for fx.Node(aten.view.default)[call_function]:Tensor(f32[4096, 1024]): Cannot find type promotion rule for op: aten.view.default" + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":1625 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0015", + "stacks":[] + }, + { + "message":{ + "markdown":"Skipped for fx.Node(aten.t.default)[call_function]:Tensor(f32[1024, 3072]): Cannot find type promotion rule for op: aten.t.default\n\n## Additional Message:\n\n## Function Signature\n### Function Signature _TypePromotionInterpreter.run_node\n- self: \n- node: fx.Node(aten.t.default)[call_function]:Tensor(f32[1024, 3072])\n## Return values\nTensor(f32[1024, 3072])", + "text":"Skipped for fx.Node(aten.t.default)[call_function]:Tensor(f32[1024, 3072]): Cannot find type promotion rule for op: aten.t.default" + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":1625 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0015", + "stacks":[] + }, + { + "message":{ + "markdown":"Skipped for fx.Node(aten.addmm.default)[call_function]:Tensor(f32[4096, 3072]): Cannot find type promotion rule for op: aten.addmm.default\n\n## Additional Message:\n\n## Function Signature\n### Function Signature _TypePromotionInterpreter.run_node\n- self: \n- node: fx.Node(aten.addmm.default)[call_function]:Tensor(f32[4096, 3072])\n## Return values\nTensor(f32[4096, 3072])", + "text":"Skipped for fx.Node(aten.addmm.default)[call_function]:Tensor(f32[4096, 3072]): Cannot find type promotion rule for op: aten.addmm.default" + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":1625 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0015", + "stacks":[] + }, + { + "message":{ + "markdown":"Skipped for fx.Node(aten.view.default)[call_function]:Tensor(f32[4, 1024, 3072]): Cannot find type promotion rule for op: aten.view.default\n\n## Additional Message:\n\n## Function Signature\n### Function Signature _TypePromotionInterpreter.run_node\n- self: \n- node: fx.Node(aten.view.default)[call_function]:Tensor(f32[4, 1024, 3072])\n## Return values\nTensor(f32[4, 1024, 3072])", + "text":"Skipped for fx.Node(aten.view.default)[call_function]:Tensor(f32[4, 1024, 3072]): Cannot find type promotion rule for op: aten.view.default" + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":1625 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0015", + "stacks":[] + }, + { + "message":{ + "markdown":"Skipped for fx.Node(aten.view.default)[call_function]:Tensor(f32[4, 1024, 3, 16, 64]): Cannot find type promotion rule for op: aten.view.default\n\n## Additional Message:\n\n## Function Signature\n### Function Signature _TypePromotionInterpreter.run_node\n- self: \n- node: fx.Node(aten.view.default)[call_function]:Tensor(f32[4, 1024, 3, 16, 64])\n## Return values\nTensor(f32[4, 1024, 3, 16, 64])", + "text":"Skipped for fx.Node(aten.view.default)[call_function]:Tensor(f32[4, 1024, 3, 16, 64]): Cannot find type promotion rule for op: aten.view.default" + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":1625 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0015", + "stacks":[] + }, + { + "message":{ + "markdown":"Skipped for fx.Node(aten.permute.default)[call_function]:Tensor(f32[3, 4, 16, 1024, 64]): Cannot find type promotion rule for op: aten.permute.default\n\n## Additional Message:\n\n## Function Signature\n### Function Signature _TypePromotionInterpreter.run_node\n- self: \n- node: fx.Node(aten.permute.default)[call_function]:Tensor(f32[3, 4, 16, 1024, 64])\n## Return values\nTensor(f32[3, 4, 16, 1024, 64])", + "text":"Skipped for fx.Node(aten.permute.default)[call_function]:Tensor(f32[3, 4, 16, 1024, 64]): Cannot find type promotion rule for op: aten.permute.default" + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":1625 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0015", + "stacks":[] + }, + { + "message":{ + "markdown":"Skipped for fx.Node(aten.unbind.int)[call_function]:List[length=3](\nTensor(f32[4, 16, 1024, 64]),\nTensor(f32[4, 16, 1024, 64]),\nTensor(f32[4, 16, 1024, 64]),\n): Cannot find type promotion rule for op: aten.unbind.int\n\n## Additional Message:\n\n## Function Signature\n### Function Signature _TypePromotionInterpreter.run_node\n- self: \n- node: fx.Node(aten.unbind.int)[call_function]:List[length=3](\nTensor(f32[4, 16, 1024, 64]),\nTensor(f32[4, 16, 1024, 64]),\nTensor(f32[4, 16, 1024, 64]),\n)\n## Return values\nList[length=3](\nTensor(f32[4, 16, 1024, 64]),\nTensor(f32[4, 16, 1024, 64]),\nTensor(f32[4, 16, 1024, 64]),\n)", + "text":"Skipped for fx.Node(aten.unbind.int)[call_function]:List[length=3](\nTensor(f32[4, 16, 1024, 64]),\nTensor(f32[4, 16, 1024, 64]),\nTensor(f32[4, 16, 1024, 64]),\n): Cannot find type promotion rule for op: aten.unbind.int" + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":1625 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0015", + "stacks":[] + }, + { + "message":{ + "markdown":"Skipped for fx.Node()[call_function]:Tensor(f32[4, 16, 1024, 64]): node.target is not OpOverload. Got type: \n\n## Additional Message:\n\n## Function Signature\n### Function Signature _TypePromotionInterpreter.run_node\n- self: \n- node: fx.Node()[call_function]:Tensor(f32[4, 16, 1024, 64])\n## Return values\nTensor(f32[4, 16, 1024, 64])", + "text":"Skipped for fx.Node()[call_function]:Tensor(f32[4, 16, 1024, 64]): node.target is not OpOverload. Got type: " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":1625 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0015", + "stacks":[] + }, + { + "message":{ + "markdown":"Skipped for fx.Node()[call_function]:Tensor(f32[4, 16, 1024, 64]): node.target is not OpOverload. Got type: \n\n## Additional Message:\n\n## Function Signature\n### Function Signature _TypePromotionInterpreter.run_node\n- self: \n- node: fx.Node()[call_function]:Tensor(f32[4, 16, 1024, 64])\n## Return values\nTensor(f32[4, 16, 1024, 64])", + "text":"Skipped for fx.Node()[call_function]:Tensor(f32[4, 16, 1024, 64]): node.target is not OpOverload. Got type: " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":1625 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0015", + "stacks":[] + }, + { + "message":{ + "markdown":"Skipped for fx.Node()[call_function]:Tensor(f32[4, 16, 1024, 64]): node.target is not OpOverload. Got type: \n\n## Additional Message:\n\n## Function Signature\n### Function Signature _TypePromotionInterpreter.run_node\n- self: \n- node: fx.Node()[call_function]:Tensor(f32[4, 16, 1024, 64])\n## Return values\nTensor(f32[4, 16, 1024, 64])", + "text":"Skipped for fx.Node()[call_function]:Tensor(f32[4, 16, 1024, 64]): node.target is not OpOverload. Got type: " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":1625 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0015", + "stacks":[] + }, + { + "message":{ + "markdown":"Skipped for fx.Node(aten._scaled_dot_product_efficient_attention.default)[call_function]:Tuple[length=4](\nTensor(f32[4, 16, 1024, 64]),\nTensor(f32[4, 16, 0]),\nTensor(i64[]),\nTensor(i64[]),\n): Cannot find type promotion rule for op: aten._scaled_dot_product_efficient_attention.default\n\n## Additional Message:\n\n## Function Signature\n### Function Signature _TypePromotionInterpreter.run_node\n- self: \n- node: fx.Node(aten._scaled_dot_product_efficient_attention.default)[call_function]:Tuple[length=4](\nTensor(f32[4, 16, 1024, 64]),\nTensor(f32[4, 16, 0]),\nTensor(i64[]),\nTensor(i64[]),\n)\n## Return values\nTuple[length=4](\nTensor(f32[4, 16, 1024, 64]),\nTensor(f32[4, 16, 0]),\nTensor(i64[]),\nTensor(i64[]),\n)", + "text":"Skipped for fx.Node(aten._scaled_dot_product_efficient_attention.default)[call_function]:Tuple[length=4](\nTensor(f32[4, 16, 1024, 64]),\nTensor(f32[4, 16, 0]),\nTensor(i64[]),\nTensor(i64[]),\n): Cannot find type promotion rule for op: aten._scaled_dot_product_efficient_attention.default" + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":1625 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0015", + "stacks":[] + }, + { + "message":{ + "markdown":"Skipped for fx.Node()[call_function]:Tensor(f32[4, 16, 1024, 64]): node.target is not OpOverload. Got type: \n\n## Additional Message:\n\n## Function Signature\n### Function Signature _TypePromotionInterpreter.run_node\n- self: \n- node: fx.Node()[call_function]:Tensor(f32[4, 16, 1024, 64])\n## Return values\nTensor(f32[4, 16, 1024, 64])", + "text":"Skipped for fx.Node()[call_function]:Tensor(f32[4, 16, 1024, 64]): node.target is not OpOverload. Got type: " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":1625 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0015", + "stacks":[] + }, + { + "message":{ + "markdown":"Skipped for fx.Node(aten.transpose.int)[call_function]:Tensor(f32[4, 1024, 16, 64]): Cannot find type promotion rule for op: aten.transpose.int\n\n## Additional Message:\n\n## Function Signature\n### Function Signature _TypePromotionInterpreter.run_node\n- self: \n- node: fx.Node(aten.transpose.int)[call_function]:Tensor(f32[4, 1024, 16, 64])\n## Return values\nTensor(f32[4, 1024, 16, 64])", + "text":"Skipped for fx.Node(aten.transpose.int)[call_function]:Tensor(f32[4, 1024, 16, 64]): Cannot find type promotion rule for op: aten.transpose.int" + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":1625 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0015", + "stacks":[] + }, + { + "message":{ + "markdown":"Skipped for fx.Node(aten.view.default)[call_function]:Tensor(f32[4, 1024, 1024]): Cannot find type promotion rule for op: aten.view.default\n\n## Additional Message:\n\n## Function Signature\n### Function Signature _TypePromotionInterpreter.run_node\n- self: \n- node: fx.Node(aten.view.default)[call_function]:Tensor(f32[4, 1024, 1024])\n## Return values\nTensor(f32[4, 1024, 1024])", + "text":"Skipped for fx.Node(aten.view.default)[call_function]:Tensor(f32[4, 1024, 1024]): Cannot find type promotion rule for op: aten.view.default" + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":1625 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0015", + "stacks":[] + }, + { + "message":{ + "markdown":"Skipped for fx.Node(aten.view.default)[call_function]:Tensor(f32[4096, 1024]): Cannot find type promotion rule for op: aten.view.default\n\n## Additional Message:\n\n## Function Signature\n### Function Signature _TypePromotionInterpreter.run_node\n- self: \n- node: fx.Node(aten.view.default)[call_function]:Tensor(f32[4096, 1024])\n## Return values\nTensor(f32[4096, 1024])", + "text":"Skipped for fx.Node(aten.view.default)[call_function]:Tensor(f32[4096, 1024]): Cannot find type promotion rule for op: aten.view.default" + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":1625 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0015", + "stacks":[] + }, + { + "message":{ + "markdown":"Skipped for fx.Node(aten.t.default)[call_function]:Tensor(f32[1024, 1024]): Cannot find type promotion rule for op: aten.t.default\n\n## Additional Message:\n\n## Function Signature\n### Function Signature _TypePromotionInterpreter.run_node\n- self: \n- node: fx.Node(aten.t.default)[call_function]:Tensor(f32[1024, 1024])\n## Return values\nTensor(f32[1024, 1024])", + "text":"Skipped for fx.Node(aten.t.default)[call_function]:Tensor(f32[1024, 1024]): Cannot find type promotion rule for op: aten.t.default" + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":1625 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0015", + "stacks":[] + }, + { + "message":{ + "markdown":"Skipped for fx.Node(aten.addmm.default)[call_function]:Tensor(f32[4096, 1024]): Cannot find type promotion rule for op: aten.addmm.default\n\n## Additional Message:\n\n## Function Signature\n### Function Signature _TypePromotionInterpreter.run_node\n- self: \n- node: fx.Node(aten.addmm.default)[call_function]:Tensor(f32[4096, 1024])\n## Return values\nTensor(f32[4096, 1024])", + "text":"Skipped for fx.Node(aten.addmm.default)[call_function]:Tensor(f32[4096, 1024]): Cannot find type promotion rule for op: aten.addmm.default" + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":1625 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0015", + "stacks":[] + }, + { + "message":{ + "markdown":"Skipped for fx.Node(aten.view.default)[call_function]:Tensor(f32[4, 1024, 1024]): Cannot find type promotion rule for op: aten.view.default\n\n## Additional Message:\n\n## Function Signature\n### Function Signature _TypePromotionInterpreter.run_node\n- self: \n- node: fx.Node(aten.view.default)[call_function]:Tensor(f32[4, 1024, 1024])\n## Return values\nTensor(f32[4, 1024, 1024])", + "text":"Skipped for fx.Node(aten.view.default)[call_function]:Tensor(f32[4, 1024, 1024]): Cannot find type promotion rule for op: aten.view.default" + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":1625 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0015", + "stacks":[] + }, + { + "message":{ + "markdown":"Skipped for fx.Node(aten.clone.default)[call_function]:Tensor(f32[4, 1024, 1024]): Cannot find type promotion rule for op: aten.clone.default\n\n## Additional Message:\n\n## Function Signature\n### Function Signature _TypePromotionInterpreter.run_node\n- self: \n- node: fx.Node(aten.clone.default)[call_function]:Tensor(f32[4, 1024, 1024])\n## Return values\nTensor(f32[4, 1024, 1024])", + "text":"Skipped for fx.Node(aten.clone.default)[call_function]:Tensor(f32[4, 1024, 1024]): Cannot find type promotion rule for op: aten.clone.default" + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":1625 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0015", + "stacks":[] + }, + { + "message":{ + "markdown":"Type promotion not needed for add_35. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature _TypePromotionInterpreter.run_node\n- self: \n- node: fx.Node(aten.add.Tensor)[call_function]:Tensor(f32[4, 1024, 1024])\nFound type promotion rule: ElementwiseTypePromotionRule('aten', 'add', [0, 1], [], ELEMENTWISE_TYPE_PROMOTION_KIND.DEFAULT)\nArgument add_34 is not promoted. Already torch.float32.\nArgument clone_52 is not promoted. Already torch.float32.\n## Return values\nTensor(f32[4, 1024, 1024])", + "text":"Type promotion not needed for add_35. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":1625 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0015", + "stacks":[] + }, + { + "message":{ + "markdown":"Skipped for fx.Node(aten.native_layer_norm.default)[call_function]:Tuple[length=3](\nTensor(f32[4, 1024, 1024]),\nTensor(f32[4, 1024, 1]),\nTensor(f32[4, 1024, 1]),\n): Cannot find type promotion rule for op: aten.native_layer_norm.default\n\n## Additional Message:\n\n## Function Signature\n### Function Signature _TypePromotionInterpreter.run_node\n- self: \n- node: fx.Node(aten.native_layer_norm.default)[call_function]:Tuple[length=3](\nTensor(f32[4, 1024, 1024]),\nTensor(f32[4, 1024, 1]),\nTensor(f32[4, 1024, 1]),\n)\n## Return values\nTuple[length=3](\nTensor(f32[4, 1024, 1024]),\nTensor(f32[4, 1024, 1]),\nTensor(f32[4, 1024, 1]),\n)", + "text":"Skipped for fx.Node(aten.native_layer_norm.default)[call_function]:Tuple[length=3](\nTensor(f32[4, 1024, 1024]),\nTensor(f32[4, 1024, 1]),\nTensor(f32[4, 1024, 1]),\n): Cannot find type promotion rule for op: aten.native_layer_norm.default" + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":1625 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0015", + "stacks":[] + }, + { + "message":{ + "markdown":"Skipped for fx.Node()[call_function]:Tensor(f32[4, 1024, 1024]): node.target is not OpOverload. Got type: \n\n## Additional Message:\n\n## Function Signature\n### Function Signature _TypePromotionInterpreter.run_node\n- self: \n- node: fx.Node()[call_function]:Tensor(f32[4, 1024, 1024])\n## Return values\nTensor(f32[4, 1024, 1024])", + "text":"Skipped for fx.Node()[call_function]:Tensor(f32[4, 1024, 1024]): node.target is not OpOverload. Got type: " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":1625 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0015", + "stacks":[] + }, + { + "message":{ + "markdown":"Skipped for fx.Node(aten.view.default)[call_function]:Tensor(f32[4096, 1024]): Cannot find type promotion rule for op: aten.view.default\n\n## Additional Message:\n\n## Function Signature\n### Function Signature _TypePromotionInterpreter.run_node\n- self: \n- node: fx.Node(aten.view.default)[call_function]:Tensor(f32[4096, 1024])\n## Return values\nTensor(f32[4096, 1024])", + "text":"Skipped for fx.Node(aten.view.default)[call_function]:Tensor(f32[4096, 1024]): Cannot find type promotion rule for op: aten.view.default" + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":1625 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0015", + "stacks":[] + }, + { + "message":{ + "markdown":"Skipped for fx.Node(aten.t.default)[call_function]:Tensor(f32[1024, 4096]): Cannot find type promotion rule for op: aten.t.default\n\n## Additional Message:\n\n## Function Signature\n### Function Signature _TypePromotionInterpreter.run_node\n- self: \n- node: fx.Node(aten.t.default)[call_function]:Tensor(f32[1024, 4096])\n## Return values\nTensor(f32[1024, 4096])", + "text":"Skipped for fx.Node(aten.t.default)[call_function]:Tensor(f32[1024, 4096]): Cannot find type promotion rule for op: aten.t.default" + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":1625 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0015", + "stacks":[] + }, + { + "message":{ + "markdown":"Skipped for fx.Node(aten.addmm.default)[call_function]:Tensor(f32[4096, 4096]): Cannot find type promotion rule for op: aten.addmm.default\n\n## Additional Message:\n\n## Function Signature\n### Function Signature _TypePromotionInterpreter.run_node\n- self: \n- node: fx.Node(aten.addmm.default)[call_function]:Tensor(f32[4096, 4096])\n## Return values\nTensor(f32[4096, 4096])", + "text":"Skipped for fx.Node(aten.addmm.default)[call_function]:Tensor(f32[4096, 4096]): Cannot find type promotion rule for op: aten.addmm.default" + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":1625 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0015", + "stacks":[] + }, + { + "message":{ + "markdown":"Skipped for fx.Node(aten.view.default)[call_function]:Tensor(f32[4, 1024, 4096]): Cannot find type promotion rule for op: aten.view.default\n\n## Additional Message:\n\n## Function Signature\n### Function Signature _TypePromotionInterpreter.run_node\n- self: \n- node: fx.Node(aten.view.default)[call_function]:Tensor(f32[4, 1024, 4096])\n## Return values\nTensor(f32[4, 1024, 4096])", + "text":"Skipped for fx.Node(aten.view.default)[call_function]:Tensor(f32[4, 1024, 4096]): Cannot find type promotion rule for op: aten.view.default" + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":1625 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0015", + "stacks":[] + }, + { + "message":{ + "markdown":"Type promotion not needed for gelu_17. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature _TypePromotionInterpreter.run_node\n- self: \n- node: fx.Node(aten.gelu.default)[call_function]:Tensor(f32[4, 1024, 4096])\nFound type promotion rule: ElementwiseTypePromotionRule('aten', 'gelu', [0], [], ELEMENTWISE_TYPE_PROMOTION_KIND.DEFAULT)\nArgument view_178 is not promoted. Already torch.float32.\nArgument tanh is not promoted. Not mentioned by type promotion rule.\n## Return values\nTensor(f32[4, 1024, 4096])", + "text":"Type promotion not needed for gelu_17. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":1625 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0015", + "stacks":[] + }, + { + "message":{ + "markdown":"Skipped for fx.Node(aten.clone.default)[call_function]:Tensor(f32[4, 1024, 4096]): Cannot find type promotion rule for op: aten.clone.default\n\n## Additional Message:\n\n## Function Signature\n### Function Signature _TypePromotionInterpreter.run_node\n- self: \n- node: fx.Node(aten.clone.default)[call_function]:Tensor(f32[4, 1024, 4096])\n## Return values\nTensor(f32[4, 1024, 4096])", + "text":"Skipped for fx.Node(aten.clone.default)[call_function]:Tensor(f32[4, 1024, 4096]): Cannot find type promotion rule for op: aten.clone.default" + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":1625 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0015", + "stacks":[] + }, + { + "message":{ + "markdown":"Skipped for fx.Node(aten.view.default)[call_function]:Tensor(f32[4096, 4096]): Cannot find type promotion rule for op: aten.view.default\n\n## Additional Message:\n\n## Function Signature\n### Function Signature _TypePromotionInterpreter.run_node\n- self: \n- node: fx.Node(aten.view.default)[call_function]:Tensor(f32[4096, 4096])\n## Return values\nTensor(f32[4096, 4096])", + "text":"Skipped for fx.Node(aten.view.default)[call_function]:Tensor(f32[4096, 4096]): Cannot find type promotion rule for op: aten.view.default" + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":1625 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0015", + "stacks":[] + }, + { + "message":{ + "markdown":"Skipped for fx.Node(aten.t.default)[call_function]:Tensor(f32[4096, 1024]): Cannot find type promotion rule for op: aten.t.default\n\n## Additional Message:\n\n## Function Signature\n### Function Signature _TypePromotionInterpreter.run_node\n- self: \n- node: fx.Node(aten.t.default)[call_function]:Tensor(f32[4096, 1024])\n## Return values\nTensor(f32[4096, 1024])", + "text":"Skipped for fx.Node(aten.t.default)[call_function]:Tensor(f32[4096, 1024]): Cannot find type promotion rule for op: aten.t.default" + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":1625 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0015", + "stacks":[] + }, + { + "message":{ + "markdown":"Skipped for fx.Node(aten.addmm.default)[call_function]:Tensor(f32[4096, 1024]): Cannot find type promotion rule for op: aten.addmm.default\n\n## Additional Message:\n\n## Function Signature\n### Function Signature _TypePromotionInterpreter.run_node\n- self: \n- node: fx.Node(aten.addmm.default)[call_function]:Tensor(f32[4096, 1024])\n## Return values\nTensor(f32[4096, 1024])", + "text":"Skipped for fx.Node(aten.addmm.default)[call_function]:Tensor(f32[4096, 1024]): Cannot find type promotion rule for op: aten.addmm.default" + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":1625 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0015", + "stacks":[] + }, + { + "message":{ + "markdown":"Skipped for fx.Node(aten.view.default)[call_function]:Tensor(f32[4, 1024, 1024]): Cannot find type promotion rule for op: aten.view.default\n\n## Additional Message:\n\n## Function Signature\n### Function Signature _TypePromotionInterpreter.run_node\n- self: \n- node: fx.Node(aten.view.default)[call_function]:Tensor(f32[4, 1024, 1024])\n## Return values\nTensor(f32[4, 1024, 1024])", + "text":"Skipped for fx.Node(aten.view.default)[call_function]:Tensor(f32[4, 1024, 1024]): Cannot find type promotion rule for op: aten.view.default" + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":1625 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0015", + "stacks":[] + }, + { + "message":{ + "markdown":"Skipped for fx.Node(aten.clone.default)[call_function]:Tensor(f32[4, 1024, 1024]): Cannot find type promotion rule for op: aten.clone.default\n\n## Additional Message:\n\n## Function Signature\n### Function Signature _TypePromotionInterpreter.run_node\n- self: \n- node: fx.Node(aten.clone.default)[call_function]:Tensor(f32[4, 1024, 1024])\n## Return values\nTensor(f32[4, 1024, 1024])", + "text":"Skipped for fx.Node(aten.clone.default)[call_function]:Tensor(f32[4, 1024, 1024]): Cannot find type promotion rule for op: aten.clone.default" + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":1625 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0015", + "stacks":[] + }, + { + "message":{ + "markdown":"Type promotion not needed for add_36. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature _TypePromotionInterpreter.run_node\n- self: \n- node: fx.Node(aten.add.Tensor)[call_function]:Tensor(f32[4, 1024, 1024])\nFound type promotion rule: ElementwiseTypePromotionRule('aten', 'add', [0, 1], [], ELEMENTWISE_TYPE_PROMOTION_KIND.DEFAULT)\nArgument add_35 is not promoted. Already torch.float32.\nArgument clone_54 is not promoted. Already torch.float32.\n## Return values\nTensor(f32[4, 1024, 1024])", + "text":"Type promotion not needed for add_36. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":1625 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0015", + "stacks":[] + }, + { + "message":{ + "markdown":"Skipped for fx.Node(aten.native_layer_norm.default)[call_function]:Tuple[length=3](\nTensor(f32[4, 1024, 1024]),\nTensor(f32[4, 1024, 1]),\nTensor(f32[4, 1024, 1]),\n): Cannot find type promotion rule for op: aten.native_layer_norm.default\n\n## Additional Message:\n\n## Function Signature\n### Function Signature _TypePromotionInterpreter.run_node\n- self: \n- node: fx.Node(aten.native_layer_norm.default)[call_function]:Tuple[length=3](\nTensor(f32[4, 1024, 1024]),\nTensor(f32[4, 1024, 1]),\nTensor(f32[4, 1024, 1]),\n)\n## Return values\nTuple[length=3](\nTensor(f32[4, 1024, 1024]),\nTensor(f32[4, 1024, 1]),\nTensor(f32[4, 1024, 1]),\n)", + "text":"Skipped for fx.Node(aten.native_layer_norm.default)[call_function]:Tuple[length=3](\nTensor(f32[4, 1024, 1024]),\nTensor(f32[4, 1024, 1]),\nTensor(f32[4, 1024, 1]),\n): Cannot find type promotion rule for op: aten.native_layer_norm.default" + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":1625 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0015", + "stacks":[] + }, + { + "message":{ + "markdown":"Skipped for fx.Node()[call_function]:Tensor(f32[4, 1024, 1024]): node.target is not OpOverload. Got type: \n\n## Additional Message:\n\n## Function Signature\n### Function Signature _TypePromotionInterpreter.run_node\n- self: \n- node: fx.Node()[call_function]:Tensor(f32[4, 1024, 1024])\n## Return values\nTensor(f32[4, 1024, 1024])", + "text":"Skipped for fx.Node()[call_function]:Tensor(f32[4, 1024, 1024]): node.target is not OpOverload. Got type: " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":1625 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0015", + "stacks":[] + }, + { + "message":{ + "markdown":"Skipped for fx.Node(aten.view.default)[call_function]:Tensor(f32[4096, 1024]): Cannot find type promotion rule for op: aten.view.default\n\n## Additional Message:\n\n## Function Signature\n### Function Signature _TypePromotionInterpreter.run_node\n- self: \n- node: fx.Node(aten.view.default)[call_function]:Tensor(f32[4096, 1024])\n## Return values\nTensor(f32[4096, 1024])", + "text":"Skipped for fx.Node(aten.view.default)[call_function]:Tensor(f32[4096, 1024]): Cannot find type promotion rule for op: aten.view.default" + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":1625 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0015", + "stacks":[] + }, + { + "message":{ + "markdown":"Skipped for fx.Node(aten.t.default)[call_function]:Tensor(f32[1024, 3072]): Cannot find type promotion rule for op: aten.t.default\n\n## Additional Message:\n\n## Function Signature\n### Function Signature _TypePromotionInterpreter.run_node\n- self: \n- node: fx.Node(aten.t.default)[call_function]:Tensor(f32[1024, 3072])\n## Return values\nTensor(f32[1024, 3072])", + "text":"Skipped for fx.Node(aten.t.default)[call_function]:Tensor(f32[1024, 3072]): Cannot find type promotion rule for op: aten.t.default" + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":1625 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0015", + "stacks":[] + }, + { + "message":{ + "markdown":"Skipped for fx.Node(aten.addmm.default)[call_function]:Tensor(f32[4096, 3072]): Cannot find type promotion rule for op: aten.addmm.default\n\n## Additional Message:\n\n## Function Signature\n### Function Signature _TypePromotionInterpreter.run_node\n- self: \n- node: fx.Node(aten.addmm.default)[call_function]:Tensor(f32[4096, 3072])\n## Return values\nTensor(f32[4096, 3072])", + "text":"Skipped for fx.Node(aten.addmm.default)[call_function]:Tensor(f32[4096, 3072]): Cannot find type promotion rule for op: aten.addmm.default" + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":1625 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0015", + "stacks":[] + }, + { + "message":{ + "markdown":"Skipped for fx.Node(aten.view.default)[call_function]:Tensor(f32[4, 1024, 3072]): Cannot find type promotion rule for op: aten.view.default\n\n## Additional Message:\n\n## Function Signature\n### Function Signature _TypePromotionInterpreter.run_node\n- self: \n- node: fx.Node(aten.view.default)[call_function]:Tensor(f32[4, 1024, 3072])\n## Return values\nTensor(f32[4, 1024, 3072])", + "text":"Skipped for fx.Node(aten.view.default)[call_function]:Tensor(f32[4, 1024, 3072]): Cannot find type promotion rule for op: aten.view.default" + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":1625 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0015", + "stacks":[] + }, + { + "message":{ + "markdown":"Skipped for fx.Node(aten.view.default)[call_function]:Tensor(f32[4, 1024, 3, 16, 64]): Cannot find type promotion rule for op: aten.view.default\n\n## Additional Message:\n\n## Function Signature\n### Function Signature _TypePromotionInterpreter.run_node\n- self: \n- node: fx.Node(aten.view.default)[call_function]:Tensor(f32[4, 1024, 3, 16, 64])\n## Return values\nTensor(f32[4, 1024, 3, 16, 64])", + "text":"Skipped for fx.Node(aten.view.default)[call_function]:Tensor(f32[4, 1024, 3, 16, 64]): Cannot find type promotion rule for op: aten.view.default" + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":1625 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0015", + "stacks":[] + }, + { + "message":{ + "markdown":"Skipped for fx.Node(aten.permute.default)[call_function]:Tensor(f32[3, 4, 16, 1024, 64]): Cannot find type promotion rule for op: aten.permute.default\n\n## Additional Message:\n\n## Function Signature\n### Function Signature _TypePromotionInterpreter.run_node\n- self: \n- node: fx.Node(aten.permute.default)[call_function]:Tensor(f32[3, 4, 16, 1024, 64])\n## Return values\nTensor(f32[3, 4, 16, 1024, 64])", + "text":"Skipped for fx.Node(aten.permute.default)[call_function]:Tensor(f32[3, 4, 16, 1024, 64]): Cannot find type promotion rule for op: aten.permute.default" + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":1625 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0015", + "stacks":[] + }, + { + "message":{ + "markdown":"Skipped for fx.Node(aten.unbind.int)[call_function]:List[length=3](\nTensor(f32[4, 16, 1024, 64]),\nTensor(f32[4, 16, 1024, 64]),\nTensor(f32[4, 16, 1024, 64]),\n): Cannot find type promotion rule for op: aten.unbind.int\n\n## Additional Message:\n\n## Function Signature\n### Function Signature _TypePromotionInterpreter.run_node\n- self: \n- node: fx.Node(aten.unbind.int)[call_function]:List[length=3](\nTensor(f32[4, 16, 1024, 64]),\nTensor(f32[4, 16, 1024, 64]),\nTensor(f32[4, 16, 1024, 64]),\n)\n## Return values\nList[length=3](\nTensor(f32[4, 16, 1024, 64]),\nTensor(f32[4, 16, 1024, 64]),\nTensor(f32[4, 16, 1024, 64]),\n)", + "text":"Skipped for fx.Node(aten.unbind.int)[call_function]:List[length=3](\nTensor(f32[4, 16, 1024, 64]),\nTensor(f32[4, 16, 1024, 64]),\nTensor(f32[4, 16, 1024, 64]),\n): Cannot find type promotion rule for op: aten.unbind.int" + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":1625 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0015", + "stacks":[] + }, + { + "message":{ + "markdown":"Skipped for fx.Node()[call_function]:Tensor(f32[4, 16, 1024, 64]): node.target is not OpOverload. Got type: \n\n## Additional Message:\n\n## Function Signature\n### Function Signature _TypePromotionInterpreter.run_node\n- self: \n- node: fx.Node()[call_function]:Tensor(f32[4, 16, 1024, 64])\n## Return values\nTensor(f32[4, 16, 1024, 64])", + "text":"Skipped for fx.Node()[call_function]:Tensor(f32[4, 16, 1024, 64]): node.target is not OpOverload. Got type: " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":1625 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0015", + "stacks":[] + }, + { + "message":{ + "markdown":"Skipped for fx.Node()[call_function]:Tensor(f32[4, 16, 1024, 64]): node.target is not OpOverload. Got type: \n\n## Additional Message:\n\n## Function Signature\n### Function Signature _TypePromotionInterpreter.run_node\n- self: \n- node: fx.Node()[call_function]:Tensor(f32[4, 16, 1024, 64])\n## Return values\nTensor(f32[4, 16, 1024, 64])", + "text":"Skipped for fx.Node()[call_function]:Tensor(f32[4, 16, 1024, 64]): node.target is not OpOverload. Got type: " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":1625 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0015", + "stacks":[] + }, + { + "message":{ + "markdown":"Skipped for fx.Node()[call_function]:Tensor(f32[4, 16, 1024, 64]): node.target is not OpOverload. Got type: \n\n## Additional Message:\n\n## Function Signature\n### Function Signature _TypePromotionInterpreter.run_node\n- self: \n- node: fx.Node()[call_function]:Tensor(f32[4, 16, 1024, 64])\n## Return values\nTensor(f32[4, 16, 1024, 64])", + "text":"Skipped for fx.Node()[call_function]:Tensor(f32[4, 16, 1024, 64]): node.target is not OpOverload. Got type: " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":1625 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0015", + "stacks":[] + }, + { + "message":{ + "markdown":"Skipped for fx.Node(aten._scaled_dot_product_efficient_attention.default)[call_function]:Tuple[length=4](\nTensor(f32[4, 16, 1024, 64]),\nTensor(f32[4, 16, 0]),\nTensor(i64[]),\nTensor(i64[]),\n): Cannot find type promotion rule for op: aten._scaled_dot_product_efficient_attention.default\n\n## Additional Message:\n\n## Function Signature\n### Function Signature _TypePromotionInterpreter.run_node\n- self: \n- node: fx.Node(aten._scaled_dot_product_efficient_attention.default)[call_function]:Tuple[length=4](\nTensor(f32[4, 16, 1024, 64]),\nTensor(f32[4, 16, 0]),\nTensor(i64[]),\nTensor(i64[]),\n)\n## Return values\nTuple[length=4](\nTensor(f32[4, 16, 1024, 64]),\nTensor(f32[4, 16, 0]),\nTensor(i64[]),\nTensor(i64[]),\n)", + "text":"Skipped for fx.Node(aten._scaled_dot_product_efficient_attention.default)[call_function]:Tuple[length=4](\nTensor(f32[4, 16, 1024, 64]),\nTensor(f32[4, 16, 0]),\nTensor(i64[]),\nTensor(i64[]),\n): Cannot find type promotion rule for op: aten._scaled_dot_product_efficient_attention.default" + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":1625 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0015", + "stacks":[] + }, + { + "message":{ + "markdown":"Skipped for fx.Node()[call_function]:Tensor(f32[4, 16, 1024, 64]): node.target is not OpOverload. Got type: \n\n## Additional Message:\n\n## Function Signature\n### Function Signature _TypePromotionInterpreter.run_node\n- self: \n- node: fx.Node()[call_function]:Tensor(f32[4, 16, 1024, 64])\n## Return values\nTensor(f32[4, 16, 1024, 64])", + "text":"Skipped for fx.Node()[call_function]:Tensor(f32[4, 16, 1024, 64]): node.target is not OpOverload. Got type: " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":1625 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0015", + "stacks":[] + }, + { + "message":{ + "markdown":"Skipped for fx.Node(aten.transpose.int)[call_function]:Tensor(f32[4, 1024, 16, 64]): Cannot find type promotion rule for op: aten.transpose.int\n\n## Additional Message:\n\n## Function Signature\n### Function Signature _TypePromotionInterpreter.run_node\n- self: \n- node: fx.Node(aten.transpose.int)[call_function]:Tensor(f32[4, 1024, 16, 64])\n## Return values\nTensor(f32[4, 1024, 16, 64])", + "text":"Skipped for fx.Node(aten.transpose.int)[call_function]:Tensor(f32[4, 1024, 16, 64]): Cannot find type promotion rule for op: aten.transpose.int" + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":1625 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0015", + "stacks":[] + }, + { + "message":{ + "markdown":"Skipped for fx.Node(aten.view.default)[call_function]:Tensor(f32[4, 1024, 1024]): Cannot find type promotion rule for op: aten.view.default\n\n## Additional Message:\n\n## Function Signature\n### Function Signature _TypePromotionInterpreter.run_node\n- self: \n- node: fx.Node(aten.view.default)[call_function]:Tensor(f32[4, 1024, 1024])\n## Return values\nTensor(f32[4, 1024, 1024])", + "text":"Skipped for fx.Node(aten.view.default)[call_function]:Tensor(f32[4, 1024, 1024]): Cannot find type promotion rule for op: aten.view.default" + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":1625 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0015", + "stacks":[] + }, + { + "message":{ + "markdown":"Skipped for fx.Node(aten.view.default)[call_function]:Tensor(f32[4096, 1024]): Cannot find type promotion rule for op: aten.view.default\n\n## Additional Message:\n\n## Function Signature\n### Function Signature _TypePromotionInterpreter.run_node\n- self: \n- node: fx.Node(aten.view.default)[call_function]:Tensor(f32[4096, 1024])\n## Return values\nTensor(f32[4096, 1024])", + "text":"Skipped for fx.Node(aten.view.default)[call_function]:Tensor(f32[4096, 1024]): Cannot find type promotion rule for op: aten.view.default" + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":1625 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0015", + "stacks":[] + }, + { + "message":{ + "markdown":"Skipped for fx.Node(aten.t.default)[call_function]:Tensor(f32[1024, 1024]): Cannot find type promotion rule for op: aten.t.default\n\n## Additional Message:\n\n## Function Signature\n### Function Signature _TypePromotionInterpreter.run_node\n- self: \n- node: fx.Node(aten.t.default)[call_function]:Tensor(f32[1024, 1024])\n## Return values\nTensor(f32[1024, 1024])", + "text":"Skipped for fx.Node(aten.t.default)[call_function]:Tensor(f32[1024, 1024]): Cannot find type promotion rule for op: aten.t.default" + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":1625 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0015", + "stacks":[] + }, + { + "message":{ + "markdown":"Skipped for fx.Node(aten.addmm.default)[call_function]:Tensor(f32[4096, 1024]): Cannot find type promotion rule for op: aten.addmm.default\n\n## Additional Message:\n\n## Function Signature\n### Function Signature _TypePromotionInterpreter.run_node\n- self: \n- node: fx.Node(aten.addmm.default)[call_function]:Tensor(f32[4096, 1024])\n## Return values\nTensor(f32[4096, 1024])", + "text":"Skipped for fx.Node(aten.addmm.default)[call_function]:Tensor(f32[4096, 1024]): Cannot find type promotion rule for op: aten.addmm.default" + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":1625 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0015", + "stacks":[] + }, + { + "message":{ + "markdown":"Skipped for fx.Node(aten.view.default)[call_function]:Tensor(f32[4, 1024, 1024]): Cannot find type promotion rule for op: aten.view.default\n\n## Additional Message:\n\n## Function Signature\n### Function Signature _TypePromotionInterpreter.run_node\n- self: \n- node: fx.Node(aten.view.default)[call_function]:Tensor(f32[4, 1024, 1024])\n## Return values\nTensor(f32[4, 1024, 1024])", + "text":"Skipped for fx.Node(aten.view.default)[call_function]:Tensor(f32[4, 1024, 1024]): Cannot find type promotion rule for op: aten.view.default" + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":1625 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0015", + "stacks":[] + }, + { + "message":{ + "markdown":"Skipped for fx.Node(aten.clone.default)[call_function]:Tensor(f32[4, 1024, 1024]): Cannot find type promotion rule for op: aten.clone.default\n\n## Additional Message:\n\n## Function Signature\n### Function Signature _TypePromotionInterpreter.run_node\n- self: \n- node: fx.Node(aten.clone.default)[call_function]:Tensor(f32[4, 1024, 1024])\n## Return values\nTensor(f32[4, 1024, 1024])", + "text":"Skipped for fx.Node(aten.clone.default)[call_function]:Tensor(f32[4, 1024, 1024]): Cannot find type promotion rule for op: aten.clone.default" + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":1625 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0015", + "stacks":[] + }, + { + "message":{ + "markdown":"Type promotion not needed for add_37. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature _TypePromotionInterpreter.run_node\n- self: \n- node: fx.Node(aten.add.Tensor)[call_function]:Tensor(f32[4, 1024, 1024])\nFound type promotion rule: ElementwiseTypePromotionRule('aten', 'add', [0, 1], [], ELEMENTWISE_TYPE_PROMOTION_KIND.DEFAULT)\nArgument add_36 is not promoted. Already torch.float32.\nArgument clone_55 is not promoted. Already torch.float32.\n## Return values\nTensor(f32[4, 1024, 1024])", + "text":"Type promotion not needed for add_37. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":1625 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0015", + "stacks":[] + }, + { + "message":{ + "markdown":"Skipped for fx.Node(aten.native_layer_norm.default)[call_function]:Tuple[length=3](\nTensor(f32[4, 1024, 1024]),\nTensor(f32[4, 1024, 1]),\nTensor(f32[4, 1024, 1]),\n): Cannot find type promotion rule for op: aten.native_layer_norm.default\n\n## Additional Message:\n\n## Function Signature\n### Function Signature _TypePromotionInterpreter.run_node\n- self: \n- node: fx.Node(aten.native_layer_norm.default)[call_function]:Tuple[length=3](\nTensor(f32[4, 1024, 1024]),\nTensor(f32[4, 1024, 1]),\nTensor(f32[4, 1024, 1]),\n)\n## Return values\nTuple[length=3](\nTensor(f32[4, 1024, 1024]),\nTensor(f32[4, 1024, 1]),\nTensor(f32[4, 1024, 1]),\n)", + "text":"Skipped for fx.Node(aten.native_layer_norm.default)[call_function]:Tuple[length=3](\nTensor(f32[4, 1024, 1024]),\nTensor(f32[4, 1024, 1]),\nTensor(f32[4, 1024, 1]),\n): Cannot find type promotion rule for op: aten.native_layer_norm.default" + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":1625 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0015", + "stacks":[] + }, + { + "message":{ + "markdown":"Skipped for fx.Node()[call_function]:Tensor(f32[4, 1024, 1024]): node.target is not OpOverload. Got type: \n\n## Additional Message:\n\n## Function Signature\n### Function Signature _TypePromotionInterpreter.run_node\n- self: \n- node: fx.Node()[call_function]:Tensor(f32[4, 1024, 1024])\n## Return values\nTensor(f32[4, 1024, 1024])", + "text":"Skipped for fx.Node()[call_function]:Tensor(f32[4, 1024, 1024]): node.target is not OpOverload. Got type: " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":1625 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0015", + "stacks":[] + }, + { + "message":{ + "markdown":"Skipped for fx.Node(aten.view.default)[call_function]:Tensor(f32[4096, 1024]): Cannot find type promotion rule for op: aten.view.default\n\n## Additional Message:\n\n## Function Signature\n### Function Signature _TypePromotionInterpreter.run_node\n- self: \n- node: fx.Node(aten.view.default)[call_function]:Tensor(f32[4096, 1024])\n## Return values\nTensor(f32[4096, 1024])", + "text":"Skipped for fx.Node(aten.view.default)[call_function]:Tensor(f32[4096, 1024]): Cannot find type promotion rule for op: aten.view.default" + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":1625 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0015", + "stacks":[] + }, + { + "message":{ + "markdown":"Skipped for fx.Node(aten.t.default)[call_function]:Tensor(f32[1024, 4096]): Cannot find type promotion rule for op: aten.t.default\n\n## Additional Message:\n\n## Function Signature\n### Function Signature _TypePromotionInterpreter.run_node\n- self: \n- node: fx.Node(aten.t.default)[call_function]:Tensor(f32[1024, 4096])\n## Return values\nTensor(f32[1024, 4096])", + "text":"Skipped for fx.Node(aten.t.default)[call_function]:Tensor(f32[1024, 4096]): Cannot find type promotion rule for op: aten.t.default" + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":1625 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0015", + "stacks":[] + }, + { + "message":{ + "markdown":"Skipped for fx.Node(aten.addmm.default)[call_function]:Tensor(f32[4096, 4096]): Cannot find type promotion rule for op: aten.addmm.default\n\n## Additional Message:\n\n## Function Signature\n### Function Signature _TypePromotionInterpreter.run_node\n- self: \n- node: fx.Node(aten.addmm.default)[call_function]:Tensor(f32[4096, 4096])\n## Return values\nTensor(f32[4096, 4096])", + "text":"Skipped for fx.Node(aten.addmm.default)[call_function]:Tensor(f32[4096, 4096]): Cannot find type promotion rule for op: aten.addmm.default" + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":1625 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0015", + "stacks":[] + }, + { + "message":{ + "markdown":"Skipped for fx.Node(aten.view.default)[call_function]:Tensor(f32[4, 1024, 4096]): Cannot find type promotion rule for op: aten.view.default\n\n## Additional Message:\n\n## Function Signature\n### Function Signature _TypePromotionInterpreter.run_node\n- self: \n- node: fx.Node(aten.view.default)[call_function]:Tensor(f32[4, 1024, 4096])\n## Return values\nTensor(f32[4, 1024, 4096])", + "text":"Skipped for fx.Node(aten.view.default)[call_function]:Tensor(f32[4, 1024, 4096]): Cannot find type promotion rule for op: aten.view.default" + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":1625 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0015", + "stacks":[] + }, + { + "message":{ + "markdown":"Type promotion not needed for gelu_18. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature _TypePromotionInterpreter.run_node\n- self: \n- node: fx.Node(aten.gelu.default)[call_function]:Tensor(f32[4, 1024, 4096])\nFound type promotion rule: ElementwiseTypePromotionRule('aten', 'gelu', [0], [], ELEMENTWISE_TYPE_PROMOTION_KIND.DEFAULT)\nArgument view_188 is not promoted. Already torch.float32.\nArgument tanh is not promoted. Not mentioned by type promotion rule.\n## Return values\nTensor(f32[4, 1024, 4096])", + "text":"Type promotion not needed for gelu_18. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":1625 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0015", + "stacks":[] + }, + { + "message":{ + "markdown":"Skipped for fx.Node(aten.clone.default)[call_function]:Tensor(f32[4, 1024, 4096]): Cannot find type promotion rule for op: aten.clone.default\n\n## Additional Message:\n\n## Function Signature\n### Function Signature _TypePromotionInterpreter.run_node\n- self: \n- node: fx.Node(aten.clone.default)[call_function]:Tensor(f32[4, 1024, 4096])\n## Return values\nTensor(f32[4, 1024, 4096])", + "text":"Skipped for fx.Node(aten.clone.default)[call_function]:Tensor(f32[4, 1024, 4096]): Cannot find type promotion rule for op: aten.clone.default" + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":1625 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0015", + "stacks":[] + }, + { + "message":{ + "markdown":"Skipped for fx.Node(aten.view.default)[call_function]:Tensor(f32[4096, 4096]): Cannot find type promotion rule for op: aten.view.default\n\n## Additional Message:\n\n## Function Signature\n### Function Signature _TypePromotionInterpreter.run_node\n- self: \n- node: fx.Node(aten.view.default)[call_function]:Tensor(f32[4096, 4096])\n## Return values\nTensor(f32[4096, 4096])", + "text":"Skipped for fx.Node(aten.view.default)[call_function]:Tensor(f32[4096, 4096]): Cannot find type promotion rule for op: aten.view.default" + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":1625 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0015", + "stacks":[] + }, + { + "message":{ + "markdown":"Skipped for fx.Node(aten.t.default)[call_function]:Tensor(f32[4096, 1024]): Cannot find type promotion rule for op: aten.t.default\n\n## Additional Message:\n\n## Function Signature\n### Function Signature _TypePromotionInterpreter.run_node\n- self: \n- node: fx.Node(aten.t.default)[call_function]:Tensor(f32[4096, 1024])\n## Return values\nTensor(f32[4096, 1024])", + "text":"Skipped for fx.Node(aten.t.default)[call_function]:Tensor(f32[4096, 1024]): Cannot find type promotion rule for op: aten.t.default" + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":1625 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0015", + "stacks":[] + }, + { + "message":{ + "markdown":"Skipped for fx.Node(aten.addmm.default)[call_function]:Tensor(f32[4096, 1024]): Cannot find type promotion rule for op: aten.addmm.default\n\n## Additional Message:\n\n## Function Signature\n### Function Signature _TypePromotionInterpreter.run_node\n- self: \n- node: fx.Node(aten.addmm.default)[call_function]:Tensor(f32[4096, 1024])\n## Return values\nTensor(f32[4096, 1024])", + "text":"Skipped for fx.Node(aten.addmm.default)[call_function]:Tensor(f32[4096, 1024]): Cannot find type promotion rule for op: aten.addmm.default" + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":1625 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0015", + "stacks":[] + }, + { + "message":{ + "markdown":"Skipped for fx.Node(aten.view.default)[call_function]:Tensor(f32[4, 1024, 1024]): Cannot find type promotion rule for op: aten.view.default\n\n## Additional Message:\n\n## Function Signature\n### Function Signature _TypePromotionInterpreter.run_node\n- self: \n- node: fx.Node(aten.view.default)[call_function]:Tensor(f32[4, 1024, 1024])\n## Return values\nTensor(f32[4, 1024, 1024])", + "text":"Skipped for fx.Node(aten.view.default)[call_function]:Tensor(f32[4, 1024, 1024]): Cannot find type promotion rule for op: aten.view.default" + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":1625 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0015", + "stacks":[] + }, + { + "message":{ + "markdown":"Skipped for fx.Node(aten.clone.default)[call_function]:Tensor(f32[4, 1024, 1024]): Cannot find type promotion rule for op: aten.clone.default\n\n## Additional Message:\n\n## Function Signature\n### Function Signature _TypePromotionInterpreter.run_node\n- self: \n- node: fx.Node(aten.clone.default)[call_function]:Tensor(f32[4, 1024, 1024])\n## Return values\nTensor(f32[4, 1024, 1024])", + "text":"Skipped for fx.Node(aten.clone.default)[call_function]:Tensor(f32[4, 1024, 1024]): Cannot find type promotion rule for op: aten.clone.default" + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":1625 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0015", + "stacks":[] + }, + { + "message":{ + "markdown":"Type promotion not needed for add_38. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature _TypePromotionInterpreter.run_node\n- self: \n- node: fx.Node(aten.add.Tensor)[call_function]:Tensor(f32[4, 1024, 1024])\nFound type promotion rule: ElementwiseTypePromotionRule('aten', 'add', [0, 1], [], ELEMENTWISE_TYPE_PROMOTION_KIND.DEFAULT)\nArgument add_37 is not promoted. Already torch.float32.\nArgument clone_57 is not promoted. Already torch.float32.\n## Return values\nTensor(f32[4, 1024, 1024])", + "text":"Type promotion not needed for add_38. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":1625 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0015", + "stacks":[] + }, + { + "message":{ + "markdown":"Skipped for fx.Node(aten.native_layer_norm.default)[call_function]:Tuple[length=3](\nTensor(f32[4, 1024, 1024]),\nTensor(f32[4, 1024, 1]),\nTensor(f32[4, 1024, 1]),\n): Cannot find type promotion rule for op: aten.native_layer_norm.default\n\n## Additional Message:\n\n## Function Signature\n### Function Signature _TypePromotionInterpreter.run_node\n- self: \n- node: fx.Node(aten.native_layer_norm.default)[call_function]:Tuple[length=3](\nTensor(f32[4, 1024, 1024]),\nTensor(f32[4, 1024, 1]),\nTensor(f32[4, 1024, 1]),\n)\n## Return values\nTuple[length=3](\nTensor(f32[4, 1024, 1024]),\nTensor(f32[4, 1024, 1]),\nTensor(f32[4, 1024, 1]),\n)", + "text":"Skipped for fx.Node(aten.native_layer_norm.default)[call_function]:Tuple[length=3](\nTensor(f32[4, 1024, 1024]),\nTensor(f32[4, 1024, 1]),\nTensor(f32[4, 1024, 1]),\n): Cannot find type promotion rule for op: aten.native_layer_norm.default" + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":1625 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0015", + "stacks":[] + }, + { + "message":{ + "markdown":"Skipped for fx.Node()[call_function]:Tensor(f32[4, 1024, 1024]): node.target is not OpOverload. Got type: \n\n## Additional Message:\n\n## Function Signature\n### Function Signature _TypePromotionInterpreter.run_node\n- self: \n- node: fx.Node()[call_function]:Tensor(f32[4, 1024, 1024])\n## Return values\nTensor(f32[4, 1024, 1024])", + "text":"Skipped for fx.Node()[call_function]:Tensor(f32[4, 1024, 1024]): node.target is not OpOverload. Got type: " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":1625 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0015", + "stacks":[] + }, + { + "message":{ + "markdown":"Skipped for fx.Node(aten.view.default)[call_function]:Tensor(f32[4096, 1024]): Cannot find type promotion rule for op: aten.view.default\n\n## Additional Message:\n\n## Function Signature\n### Function Signature _TypePromotionInterpreter.run_node\n- self: \n- node: fx.Node(aten.view.default)[call_function]:Tensor(f32[4096, 1024])\n## Return values\nTensor(f32[4096, 1024])", + "text":"Skipped for fx.Node(aten.view.default)[call_function]:Tensor(f32[4096, 1024]): Cannot find type promotion rule for op: aten.view.default" + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":1625 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0015", + "stacks":[] + }, + { + "message":{ + "markdown":"Skipped for fx.Node(aten.t.default)[call_function]:Tensor(f32[1024, 3072]): Cannot find type promotion rule for op: aten.t.default\n\n## Additional Message:\n\n## Function Signature\n### Function Signature _TypePromotionInterpreter.run_node\n- self: \n- node: fx.Node(aten.t.default)[call_function]:Tensor(f32[1024, 3072])\n## Return values\nTensor(f32[1024, 3072])", + "text":"Skipped for fx.Node(aten.t.default)[call_function]:Tensor(f32[1024, 3072]): Cannot find type promotion rule for op: aten.t.default" + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":1625 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0015", + "stacks":[] + }, + { + "message":{ + "markdown":"Skipped for fx.Node(aten.addmm.default)[call_function]:Tensor(f32[4096, 3072]): Cannot find type promotion rule for op: aten.addmm.default\n\n## Additional Message:\n\n## Function Signature\n### Function Signature _TypePromotionInterpreter.run_node\n- self: \n- node: fx.Node(aten.addmm.default)[call_function]:Tensor(f32[4096, 3072])\n## Return values\nTensor(f32[4096, 3072])", + "text":"Skipped for fx.Node(aten.addmm.default)[call_function]:Tensor(f32[4096, 3072]): Cannot find type promotion rule for op: aten.addmm.default" + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":1625 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0015", + "stacks":[] + }, + { + "message":{ + "markdown":"Skipped for fx.Node(aten.view.default)[call_function]:Tensor(f32[4, 1024, 3072]): Cannot find type promotion rule for op: aten.view.default\n\n## Additional Message:\n\n## Function Signature\n### Function Signature _TypePromotionInterpreter.run_node\n- self: \n- node: fx.Node(aten.view.default)[call_function]:Tensor(f32[4, 1024, 3072])\n## Return values\nTensor(f32[4, 1024, 3072])", + "text":"Skipped for fx.Node(aten.view.default)[call_function]:Tensor(f32[4, 1024, 3072]): Cannot find type promotion rule for op: aten.view.default" + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":1625 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0015", + "stacks":[] + }, + { + "message":{ + "markdown":"Skipped for fx.Node(aten.view.default)[call_function]:Tensor(f32[4, 1024, 3, 16, 64]): Cannot find type promotion rule for op: aten.view.default\n\n## Additional Message:\n\n## Function Signature\n### Function Signature _TypePromotionInterpreter.run_node\n- self: \n- node: fx.Node(aten.view.default)[call_function]:Tensor(f32[4, 1024, 3, 16, 64])\n## Return values\nTensor(f32[4, 1024, 3, 16, 64])", + "text":"Skipped for fx.Node(aten.view.default)[call_function]:Tensor(f32[4, 1024, 3, 16, 64]): Cannot find type promotion rule for op: aten.view.default" + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":1625 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0015", + "stacks":[] + }, + { + "message":{ + "markdown":"Skipped for fx.Node(aten.permute.default)[call_function]:Tensor(f32[3, 4, 16, 1024, 64]): Cannot find type promotion rule for op: aten.permute.default\n\n## Additional Message:\n\n## Function Signature\n### Function Signature _TypePromotionInterpreter.run_node\n- self: \n- node: fx.Node(aten.permute.default)[call_function]:Tensor(f32[3, 4, 16, 1024, 64])\n## Return values\nTensor(f32[3, 4, 16, 1024, 64])", + "text":"Skipped for fx.Node(aten.permute.default)[call_function]:Tensor(f32[3, 4, 16, 1024, 64]): Cannot find type promotion rule for op: aten.permute.default" + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":1625 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0015", + "stacks":[] + }, + { + "message":{ + "markdown":"Skipped for fx.Node(aten.unbind.int)[call_function]:List[length=3](\nTensor(f32[4, 16, 1024, 64]),\nTensor(f32[4, 16, 1024, 64]),\nTensor(f32[4, 16, 1024, 64]),\n): Cannot find type promotion rule for op: aten.unbind.int\n\n## Additional Message:\n\n## Function Signature\n### Function Signature _TypePromotionInterpreter.run_node\n- self: \n- node: fx.Node(aten.unbind.int)[call_function]:List[length=3](\nTensor(f32[4, 16, 1024, 64]),\nTensor(f32[4, 16, 1024, 64]),\nTensor(f32[4, 16, 1024, 64]),\n)\n## Return values\nList[length=3](\nTensor(f32[4, 16, 1024, 64]),\nTensor(f32[4, 16, 1024, 64]),\nTensor(f32[4, 16, 1024, 64]),\n)", + "text":"Skipped for fx.Node(aten.unbind.int)[call_function]:List[length=3](\nTensor(f32[4, 16, 1024, 64]),\nTensor(f32[4, 16, 1024, 64]),\nTensor(f32[4, 16, 1024, 64]),\n): Cannot find type promotion rule for op: aten.unbind.int" + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":1625 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0015", + "stacks":[] + }, + { + "message":{ + "markdown":"Skipped for fx.Node()[call_function]:Tensor(f32[4, 16, 1024, 64]): node.target is not OpOverload. Got type: \n\n## Additional Message:\n\n## Function Signature\n### Function Signature _TypePromotionInterpreter.run_node\n- self: \n- node: fx.Node()[call_function]:Tensor(f32[4, 16, 1024, 64])\n## Return values\nTensor(f32[4, 16, 1024, 64])", + "text":"Skipped for fx.Node()[call_function]:Tensor(f32[4, 16, 1024, 64]): node.target is not OpOverload. Got type: " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":1625 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0015", + "stacks":[] + }, + { + "message":{ + "markdown":"Skipped for fx.Node()[call_function]:Tensor(f32[4, 16, 1024, 64]): node.target is not OpOverload. Got type: \n\n## Additional Message:\n\n## Function Signature\n### Function Signature _TypePromotionInterpreter.run_node\n- self: \n- node: fx.Node()[call_function]:Tensor(f32[4, 16, 1024, 64])\n## Return values\nTensor(f32[4, 16, 1024, 64])", + "text":"Skipped for fx.Node()[call_function]:Tensor(f32[4, 16, 1024, 64]): node.target is not OpOverload. Got type: " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":1625 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0015", + "stacks":[] + }, + { + "message":{ + "markdown":"Skipped for fx.Node()[call_function]:Tensor(f32[4, 16, 1024, 64]): node.target is not OpOverload. Got type: \n\n## Additional Message:\n\n## Function Signature\n### Function Signature _TypePromotionInterpreter.run_node\n- self: \n- node: fx.Node()[call_function]:Tensor(f32[4, 16, 1024, 64])\n## Return values\nTensor(f32[4, 16, 1024, 64])", + "text":"Skipped for fx.Node()[call_function]:Tensor(f32[4, 16, 1024, 64]): node.target is not OpOverload. Got type: " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":1625 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0015", + "stacks":[] + }, + { + "message":{ + "markdown":"Skipped for fx.Node(aten._scaled_dot_product_efficient_attention.default)[call_function]:Tuple[length=4](\nTensor(f32[4, 16, 1024, 64]),\nTensor(f32[4, 16, 0]),\nTensor(i64[]),\nTensor(i64[]),\n): Cannot find type promotion rule for op: aten._scaled_dot_product_efficient_attention.default\n\n## Additional Message:\n\n## Function Signature\n### Function Signature _TypePromotionInterpreter.run_node\n- self: \n- node: fx.Node(aten._scaled_dot_product_efficient_attention.default)[call_function]:Tuple[length=4](\nTensor(f32[4, 16, 1024, 64]),\nTensor(f32[4, 16, 0]),\nTensor(i64[]),\nTensor(i64[]),\n)\n## Return values\nTuple[length=4](\nTensor(f32[4, 16, 1024, 64]),\nTensor(f32[4, 16, 0]),\nTensor(i64[]),\nTensor(i64[]),\n)", + "text":"Skipped for fx.Node(aten._scaled_dot_product_efficient_attention.default)[call_function]:Tuple[length=4](\nTensor(f32[4, 16, 1024, 64]),\nTensor(f32[4, 16, 0]),\nTensor(i64[]),\nTensor(i64[]),\n): Cannot find type promotion rule for op: aten._scaled_dot_product_efficient_attention.default" + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":1625 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0015", + "stacks":[] + }, + { + "message":{ + "markdown":"Skipped for fx.Node()[call_function]:Tensor(f32[4, 16, 1024, 64]): node.target is not OpOverload. Got type: \n\n## Additional Message:\n\n## Function Signature\n### Function Signature _TypePromotionInterpreter.run_node\n- self: \n- node: fx.Node()[call_function]:Tensor(f32[4, 16, 1024, 64])\n## Return values\nTensor(f32[4, 16, 1024, 64])", + "text":"Skipped for fx.Node()[call_function]:Tensor(f32[4, 16, 1024, 64]): node.target is not OpOverload. Got type: " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":1625 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0015", + "stacks":[] + }, + { + "message":{ + "markdown":"Skipped for fx.Node(aten.transpose.int)[call_function]:Tensor(f32[4, 1024, 16, 64]): Cannot find type promotion rule for op: aten.transpose.int\n\n## Additional Message:\n\n## Function Signature\n### Function Signature _TypePromotionInterpreter.run_node\n- self: \n- node: fx.Node(aten.transpose.int)[call_function]:Tensor(f32[4, 1024, 16, 64])\n## Return values\nTensor(f32[4, 1024, 16, 64])", + "text":"Skipped for fx.Node(aten.transpose.int)[call_function]:Tensor(f32[4, 1024, 16, 64]): Cannot find type promotion rule for op: aten.transpose.int" + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":1625 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0015", + "stacks":[] + }, + { + "message":{ + "markdown":"Skipped for fx.Node(aten.view.default)[call_function]:Tensor(f32[4, 1024, 1024]): Cannot find type promotion rule for op: aten.view.default\n\n## Additional Message:\n\n## Function Signature\n### Function Signature _TypePromotionInterpreter.run_node\n- self: \n- node: fx.Node(aten.view.default)[call_function]:Tensor(f32[4, 1024, 1024])\n## Return values\nTensor(f32[4, 1024, 1024])", + "text":"Skipped for fx.Node(aten.view.default)[call_function]:Tensor(f32[4, 1024, 1024]): Cannot find type promotion rule for op: aten.view.default" + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":1625 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0015", + "stacks":[] + }, + { + "message":{ + "markdown":"Skipped for fx.Node(aten.view.default)[call_function]:Tensor(f32[4096, 1024]): Cannot find type promotion rule for op: aten.view.default\n\n## Additional Message:\n\n## Function Signature\n### Function Signature _TypePromotionInterpreter.run_node\n- self: \n- node: fx.Node(aten.view.default)[call_function]:Tensor(f32[4096, 1024])\n## Return values\nTensor(f32[4096, 1024])", + "text":"Skipped for fx.Node(aten.view.default)[call_function]:Tensor(f32[4096, 1024]): Cannot find type promotion rule for op: aten.view.default" + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":1625 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0015", + "stacks":[] + }, + { + "message":{ + "markdown":"Skipped for fx.Node(aten.t.default)[call_function]:Tensor(f32[1024, 1024]): Cannot find type promotion rule for op: aten.t.default\n\n## Additional Message:\n\n## Function Signature\n### Function Signature _TypePromotionInterpreter.run_node\n- self: \n- node: fx.Node(aten.t.default)[call_function]:Tensor(f32[1024, 1024])\n## Return values\nTensor(f32[1024, 1024])", + "text":"Skipped for fx.Node(aten.t.default)[call_function]:Tensor(f32[1024, 1024]): Cannot find type promotion rule for op: aten.t.default" + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":1625 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0015", + "stacks":[] + }, + { + "message":{ + "markdown":"Skipped for fx.Node(aten.addmm.default)[call_function]:Tensor(f32[4096, 1024]): Cannot find type promotion rule for op: aten.addmm.default\n\n## Additional Message:\n\n## Function Signature\n### Function Signature _TypePromotionInterpreter.run_node\n- self: \n- node: fx.Node(aten.addmm.default)[call_function]:Tensor(f32[4096, 1024])\n## Return values\nTensor(f32[4096, 1024])", + "text":"Skipped for fx.Node(aten.addmm.default)[call_function]:Tensor(f32[4096, 1024]): Cannot find type promotion rule for op: aten.addmm.default" + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":1625 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0015", + "stacks":[] + }, + { + "message":{ + "markdown":"Skipped for fx.Node(aten.view.default)[call_function]:Tensor(f32[4, 1024, 1024]): Cannot find type promotion rule for op: aten.view.default\n\n## Additional Message:\n\n## Function Signature\n### Function Signature _TypePromotionInterpreter.run_node\n- self: \n- node: fx.Node(aten.view.default)[call_function]:Tensor(f32[4, 1024, 1024])\n## Return values\nTensor(f32[4, 1024, 1024])", + "text":"Skipped for fx.Node(aten.view.default)[call_function]:Tensor(f32[4, 1024, 1024]): Cannot find type promotion rule for op: aten.view.default" + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":1625 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0015", + "stacks":[] + }, + { + "message":{ + "markdown":"Skipped for fx.Node(aten.clone.default)[call_function]:Tensor(f32[4, 1024, 1024]): Cannot find type promotion rule for op: aten.clone.default\n\n## Additional Message:\n\n## Function Signature\n### Function Signature _TypePromotionInterpreter.run_node\n- self: \n- node: fx.Node(aten.clone.default)[call_function]:Tensor(f32[4, 1024, 1024])\n## Return values\nTensor(f32[4, 1024, 1024])", + "text":"Skipped for fx.Node(aten.clone.default)[call_function]:Tensor(f32[4, 1024, 1024]): Cannot find type promotion rule for op: aten.clone.default" + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":1625 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0015", + "stacks":[] + }, + { + "message":{ + "markdown":"Type promotion not needed for add_39. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature _TypePromotionInterpreter.run_node\n- self: \n- node: fx.Node(aten.add.Tensor)[call_function]:Tensor(f32[4, 1024, 1024])\nFound type promotion rule: ElementwiseTypePromotionRule('aten', 'add', [0, 1], [], ELEMENTWISE_TYPE_PROMOTION_KIND.DEFAULT)\nArgument add_38 is not promoted. Already torch.float32.\nArgument clone_58 is not promoted. Already torch.float32.\n## Return values\nTensor(f32[4, 1024, 1024])", + "text":"Type promotion not needed for add_39. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":1625 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0015", + "stacks":[] + }, + { + "message":{ + "markdown":"Skipped for fx.Node(aten.native_layer_norm.default)[call_function]:Tuple[length=3](\nTensor(f32[4, 1024, 1024]),\nTensor(f32[4, 1024, 1]),\nTensor(f32[4, 1024, 1]),\n): Cannot find type promotion rule for op: aten.native_layer_norm.default\n\n## Additional Message:\n\n## Function Signature\n### Function Signature _TypePromotionInterpreter.run_node\n- self: \n- node: fx.Node(aten.native_layer_norm.default)[call_function]:Tuple[length=3](\nTensor(f32[4, 1024, 1024]),\nTensor(f32[4, 1024, 1]),\nTensor(f32[4, 1024, 1]),\n)\n## Return values\nTuple[length=3](\nTensor(f32[4, 1024, 1024]),\nTensor(f32[4, 1024, 1]),\nTensor(f32[4, 1024, 1]),\n)", + "text":"Skipped for fx.Node(aten.native_layer_norm.default)[call_function]:Tuple[length=3](\nTensor(f32[4, 1024, 1024]),\nTensor(f32[4, 1024, 1]),\nTensor(f32[4, 1024, 1]),\n): Cannot find type promotion rule for op: aten.native_layer_norm.default" + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":1625 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0015", + "stacks":[] + }, + { + "message":{ + "markdown":"Skipped for fx.Node()[call_function]:Tensor(f32[4, 1024, 1024]): node.target is not OpOverload. Got type: \n\n## Additional Message:\n\n## Function Signature\n### Function Signature _TypePromotionInterpreter.run_node\n- self: \n- node: fx.Node()[call_function]:Tensor(f32[4, 1024, 1024])\n## Return values\nTensor(f32[4, 1024, 1024])", + "text":"Skipped for fx.Node()[call_function]:Tensor(f32[4, 1024, 1024]): node.target is not OpOverload. Got type: " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":1625 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0015", + "stacks":[] + }, + { + "message":{ + "markdown":"Skipped for fx.Node(aten.view.default)[call_function]:Tensor(f32[4096, 1024]): Cannot find type promotion rule for op: aten.view.default\n\n## Additional Message:\n\n## Function Signature\n### Function Signature _TypePromotionInterpreter.run_node\n- self: \n- node: fx.Node(aten.view.default)[call_function]:Tensor(f32[4096, 1024])\n## Return values\nTensor(f32[4096, 1024])", + "text":"Skipped for fx.Node(aten.view.default)[call_function]:Tensor(f32[4096, 1024]): Cannot find type promotion rule for op: aten.view.default" + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":1625 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0015", + "stacks":[] + }, + { + "message":{ + "markdown":"Skipped for fx.Node(aten.t.default)[call_function]:Tensor(f32[1024, 4096]): Cannot find type promotion rule for op: aten.t.default\n\n## Additional Message:\n\n## Function Signature\n### Function Signature _TypePromotionInterpreter.run_node\n- self: \n- node: fx.Node(aten.t.default)[call_function]:Tensor(f32[1024, 4096])\n## Return values\nTensor(f32[1024, 4096])", + "text":"Skipped for fx.Node(aten.t.default)[call_function]:Tensor(f32[1024, 4096]): Cannot find type promotion rule for op: aten.t.default" + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":1625 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0015", + "stacks":[] + }, + { + "message":{ + "markdown":"Skipped for fx.Node(aten.addmm.default)[call_function]:Tensor(f32[4096, 4096]): Cannot find type promotion rule for op: aten.addmm.default\n\n## Additional Message:\n\n## Function Signature\n### Function Signature _TypePromotionInterpreter.run_node\n- self: \n- node: fx.Node(aten.addmm.default)[call_function]:Tensor(f32[4096, 4096])\n## Return values\nTensor(f32[4096, 4096])", + "text":"Skipped for fx.Node(aten.addmm.default)[call_function]:Tensor(f32[4096, 4096]): Cannot find type promotion rule for op: aten.addmm.default" + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":1625 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0015", + "stacks":[] + }, + { + "message":{ + "markdown":"Skipped for fx.Node(aten.view.default)[call_function]:Tensor(f32[4, 1024, 4096]): Cannot find type promotion rule for op: aten.view.default\n\n## Additional Message:\n\n## Function Signature\n### Function Signature _TypePromotionInterpreter.run_node\n- self: \n- node: fx.Node(aten.view.default)[call_function]:Tensor(f32[4, 1024, 4096])\n## Return values\nTensor(f32[4, 1024, 4096])", + "text":"Skipped for fx.Node(aten.view.default)[call_function]:Tensor(f32[4, 1024, 4096]): Cannot find type promotion rule for op: aten.view.default" + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":1625 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0015", + "stacks":[] + }, + { + "message":{ + "markdown":"Type promotion not needed for gelu_19. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature _TypePromotionInterpreter.run_node\n- self: \n- node: fx.Node(aten.gelu.default)[call_function]:Tensor(f32[4, 1024, 4096])\nFound type promotion rule: ElementwiseTypePromotionRule('aten', 'gelu', [0], [], ELEMENTWISE_TYPE_PROMOTION_KIND.DEFAULT)\nArgument view_198 is not promoted. Already torch.float32.\nArgument tanh is not promoted. Not mentioned by type promotion rule.\n## Return values\nTensor(f32[4, 1024, 4096])", + "text":"Type promotion not needed for gelu_19. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":1625 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0015", + "stacks":[] + }, + { + "message":{ + "markdown":"Skipped for fx.Node(aten.clone.default)[call_function]:Tensor(f32[4, 1024, 4096]): Cannot find type promotion rule for op: aten.clone.default\n\n## Additional Message:\n\n## Function Signature\n### Function Signature _TypePromotionInterpreter.run_node\n- self: \n- node: fx.Node(aten.clone.default)[call_function]:Tensor(f32[4, 1024, 4096])\n## Return values\nTensor(f32[4, 1024, 4096])", + "text":"Skipped for fx.Node(aten.clone.default)[call_function]:Tensor(f32[4, 1024, 4096]): Cannot find type promotion rule for op: aten.clone.default" + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":1625 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0015", + "stacks":[] + }, + { + "message":{ + "markdown":"Skipped for fx.Node(aten.view.default)[call_function]:Tensor(f32[4096, 4096]): Cannot find type promotion rule for op: aten.view.default\n\n## Additional Message:\n\n## Function Signature\n### Function Signature _TypePromotionInterpreter.run_node\n- self: \n- node: fx.Node(aten.view.default)[call_function]:Tensor(f32[4096, 4096])\n## Return values\nTensor(f32[4096, 4096])", + "text":"Skipped for fx.Node(aten.view.default)[call_function]:Tensor(f32[4096, 4096]): Cannot find type promotion rule for op: aten.view.default" + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":1625 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0015", + "stacks":[] + }, + { + "message":{ + "markdown":"Skipped for fx.Node(aten.t.default)[call_function]:Tensor(f32[4096, 1024]): Cannot find type promotion rule for op: aten.t.default\n\n## Additional Message:\n\n## Function Signature\n### Function Signature _TypePromotionInterpreter.run_node\n- self: \n- node: fx.Node(aten.t.default)[call_function]:Tensor(f32[4096, 1024])\n## Return values\nTensor(f32[4096, 1024])", + "text":"Skipped for fx.Node(aten.t.default)[call_function]:Tensor(f32[4096, 1024]): Cannot find type promotion rule for op: aten.t.default" + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":1625 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0015", + "stacks":[] + }, + { + "message":{ + "markdown":"Skipped for fx.Node(aten.addmm.default)[call_function]:Tensor(f32[4096, 1024]): Cannot find type promotion rule for op: aten.addmm.default\n\n## Additional Message:\n\n## Function Signature\n### Function Signature _TypePromotionInterpreter.run_node\n- self: \n- node: fx.Node(aten.addmm.default)[call_function]:Tensor(f32[4096, 1024])\n## Return values\nTensor(f32[4096, 1024])", + "text":"Skipped for fx.Node(aten.addmm.default)[call_function]:Tensor(f32[4096, 1024]): Cannot find type promotion rule for op: aten.addmm.default" + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":1625 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0015", + "stacks":[] + }, + { + "message":{ + "markdown":"Skipped for fx.Node(aten.view.default)[call_function]:Tensor(f32[4, 1024, 1024]): Cannot find type promotion rule for op: aten.view.default\n\n## Additional Message:\n\n## Function Signature\n### Function Signature _TypePromotionInterpreter.run_node\n- self: \n- node: fx.Node(aten.view.default)[call_function]:Tensor(f32[4, 1024, 1024])\n## Return values\nTensor(f32[4, 1024, 1024])", + "text":"Skipped for fx.Node(aten.view.default)[call_function]:Tensor(f32[4, 1024, 1024]): Cannot find type promotion rule for op: aten.view.default" + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":1625 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0015", + "stacks":[] + }, + { + "message":{ + "markdown":"Skipped for fx.Node(aten.clone.default)[call_function]:Tensor(f32[4, 1024, 1024]): Cannot find type promotion rule for op: aten.clone.default\n\n## Additional Message:\n\n## Function Signature\n### Function Signature _TypePromotionInterpreter.run_node\n- self: \n- node: fx.Node(aten.clone.default)[call_function]:Tensor(f32[4, 1024, 1024])\n## Return values\nTensor(f32[4, 1024, 1024])", + "text":"Skipped for fx.Node(aten.clone.default)[call_function]:Tensor(f32[4, 1024, 1024]): Cannot find type promotion rule for op: aten.clone.default" + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":1625 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0015", + "stacks":[] + }, + { + "message":{ + "markdown":"Type promotion not needed for add_40. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature _TypePromotionInterpreter.run_node\n- self: \n- node: fx.Node(aten.add.Tensor)[call_function]:Tensor(f32[4, 1024, 1024])\nFound type promotion rule: ElementwiseTypePromotionRule('aten', 'add', [0, 1], [], ELEMENTWISE_TYPE_PROMOTION_KIND.DEFAULT)\nArgument add_39 is not promoted. Already torch.float32.\nArgument clone_60 is not promoted. Already torch.float32.\n## Return values\nTensor(f32[4, 1024, 1024])", + "text":"Type promotion not needed for add_40. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":1625 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0015", + "stacks":[] + }, + { + "message":{ + "markdown":"Skipped for fx.Node(aten.native_layer_norm.default)[call_function]:Tuple[length=3](\nTensor(f32[4, 1024, 1024]),\nTensor(f32[4, 1024, 1]),\nTensor(f32[4, 1024, 1]),\n): Cannot find type promotion rule for op: aten.native_layer_norm.default\n\n## Additional Message:\n\n## Function Signature\n### Function Signature _TypePromotionInterpreter.run_node\n- self: \n- node: fx.Node(aten.native_layer_norm.default)[call_function]:Tuple[length=3](\nTensor(f32[4, 1024, 1024]),\nTensor(f32[4, 1024, 1]),\nTensor(f32[4, 1024, 1]),\n)\n## Return values\nTuple[length=3](\nTensor(f32[4, 1024, 1024]),\nTensor(f32[4, 1024, 1]),\nTensor(f32[4, 1024, 1]),\n)", + "text":"Skipped for fx.Node(aten.native_layer_norm.default)[call_function]:Tuple[length=3](\nTensor(f32[4, 1024, 1024]),\nTensor(f32[4, 1024, 1]),\nTensor(f32[4, 1024, 1]),\n): Cannot find type promotion rule for op: aten.native_layer_norm.default" + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":1625 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0015", + "stacks":[] + }, + { + "message":{ + "markdown":"Skipped for fx.Node()[call_function]:Tensor(f32[4, 1024, 1024]): node.target is not OpOverload. Got type: \n\n## Additional Message:\n\n## Function Signature\n### Function Signature _TypePromotionInterpreter.run_node\n- self: \n- node: fx.Node()[call_function]:Tensor(f32[4, 1024, 1024])\n## Return values\nTensor(f32[4, 1024, 1024])", + "text":"Skipped for fx.Node()[call_function]:Tensor(f32[4, 1024, 1024]): node.target is not OpOverload. Got type: " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":1625 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0015", + "stacks":[] + }, + { + "message":{ + "markdown":"Skipped for fx.Node(aten.view.default)[call_function]:Tensor(f32[4096, 1024]): Cannot find type promotion rule for op: aten.view.default\n\n## Additional Message:\n\n## Function Signature\n### Function Signature _TypePromotionInterpreter.run_node\n- self: \n- node: fx.Node(aten.view.default)[call_function]:Tensor(f32[4096, 1024])\n## Return values\nTensor(f32[4096, 1024])", + "text":"Skipped for fx.Node(aten.view.default)[call_function]:Tensor(f32[4096, 1024]): Cannot find type promotion rule for op: aten.view.default" + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":1625 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0015", + "stacks":[] + }, + { + "message":{ + "markdown":"Skipped for fx.Node(aten.t.default)[call_function]:Tensor(f32[1024, 3072]): Cannot find type promotion rule for op: aten.t.default\n\n## Additional Message:\n\n## Function Signature\n### Function Signature _TypePromotionInterpreter.run_node\n- self: \n- node: fx.Node(aten.t.default)[call_function]:Tensor(f32[1024, 3072])\n## Return values\nTensor(f32[1024, 3072])", + "text":"Skipped for fx.Node(aten.t.default)[call_function]:Tensor(f32[1024, 3072]): Cannot find type promotion rule for op: aten.t.default" + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":1625 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0015", + "stacks":[] + }, + { + "message":{ + "markdown":"Skipped for fx.Node(aten.addmm.default)[call_function]:Tensor(f32[4096, 3072]): Cannot find type promotion rule for op: aten.addmm.default\n\n## Additional Message:\n\n## Function Signature\n### Function Signature _TypePromotionInterpreter.run_node\n- self: \n- node: fx.Node(aten.addmm.default)[call_function]:Tensor(f32[4096, 3072])\n## Return values\nTensor(f32[4096, 3072])", + "text":"Skipped for fx.Node(aten.addmm.default)[call_function]:Tensor(f32[4096, 3072]): Cannot find type promotion rule for op: aten.addmm.default" + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":1625 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0015", + "stacks":[] + }, + { + "message":{ + "markdown":"Skipped for fx.Node(aten.view.default)[call_function]:Tensor(f32[4, 1024, 3072]): Cannot find type promotion rule for op: aten.view.default\n\n## Additional Message:\n\n## Function Signature\n### Function Signature _TypePromotionInterpreter.run_node\n- self: \n- node: fx.Node(aten.view.default)[call_function]:Tensor(f32[4, 1024, 3072])\n## Return values\nTensor(f32[4, 1024, 3072])", + "text":"Skipped for fx.Node(aten.view.default)[call_function]:Tensor(f32[4, 1024, 3072]): Cannot find type promotion rule for op: aten.view.default" + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":1625 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0015", + "stacks":[] + }, + { + "message":{ + "markdown":"Skipped for fx.Node(aten.view.default)[call_function]:Tensor(f32[4, 1024, 3, 16, 64]): Cannot find type promotion rule for op: aten.view.default\n\n## Additional Message:\n\n## Function Signature\n### Function Signature _TypePromotionInterpreter.run_node\n- self: \n- node: fx.Node(aten.view.default)[call_function]:Tensor(f32[4, 1024, 3, 16, 64])\n## Return values\nTensor(f32[4, 1024, 3, 16, 64])", + "text":"Skipped for fx.Node(aten.view.default)[call_function]:Tensor(f32[4, 1024, 3, 16, 64]): Cannot find type promotion rule for op: aten.view.default" + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":1625 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0015", + "stacks":[] + }, + { + "message":{ + "markdown":"Skipped for fx.Node(aten.permute.default)[call_function]:Tensor(f32[3, 4, 16, 1024, 64]): Cannot find type promotion rule for op: aten.permute.default\n\n## Additional Message:\n\n## Function Signature\n### Function Signature _TypePromotionInterpreter.run_node\n- self: \n- node: fx.Node(aten.permute.default)[call_function]:Tensor(f32[3, 4, 16, 1024, 64])\n## Return values\nTensor(f32[3, 4, 16, 1024, 64])", + "text":"Skipped for fx.Node(aten.permute.default)[call_function]:Tensor(f32[3, 4, 16, 1024, 64]): Cannot find type promotion rule for op: aten.permute.default" + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":1625 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0015", + "stacks":[] + }, + { + "message":{ + "markdown":"Skipped for fx.Node(aten.unbind.int)[call_function]:List[length=3](\nTensor(f32[4, 16, 1024, 64]),\nTensor(f32[4, 16, 1024, 64]),\nTensor(f32[4, 16, 1024, 64]),\n): Cannot find type promotion rule for op: aten.unbind.int\n\n## Additional Message:\n\n## Function Signature\n### Function Signature _TypePromotionInterpreter.run_node\n- self: \n- node: fx.Node(aten.unbind.int)[call_function]:List[length=3](\nTensor(f32[4, 16, 1024, 64]),\nTensor(f32[4, 16, 1024, 64]),\nTensor(f32[4, 16, 1024, 64]),\n)\n## Return values\nList[length=3](\nTensor(f32[4, 16, 1024, 64]),\nTensor(f32[4, 16, 1024, 64]),\nTensor(f32[4, 16, 1024, 64]),\n)", + "text":"Skipped for fx.Node(aten.unbind.int)[call_function]:List[length=3](\nTensor(f32[4, 16, 1024, 64]),\nTensor(f32[4, 16, 1024, 64]),\nTensor(f32[4, 16, 1024, 64]),\n): Cannot find type promotion rule for op: aten.unbind.int" + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":1625 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0015", + "stacks":[] + }, + { + "message":{ + "markdown":"Skipped for fx.Node()[call_function]:Tensor(f32[4, 16, 1024, 64]): node.target is not OpOverload. Got type: \n\n## Additional Message:\n\n## Function Signature\n### Function Signature _TypePromotionInterpreter.run_node\n- self: \n- node: fx.Node()[call_function]:Tensor(f32[4, 16, 1024, 64])\n## Return values\nTensor(f32[4, 16, 1024, 64])", + "text":"Skipped for fx.Node()[call_function]:Tensor(f32[4, 16, 1024, 64]): node.target is not OpOverload. Got type: " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":1625 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0015", + "stacks":[] + }, + { + "message":{ + "markdown":"Skipped for fx.Node()[call_function]:Tensor(f32[4, 16, 1024, 64]): node.target is not OpOverload. Got type: \n\n## Additional Message:\n\n## Function Signature\n### Function Signature _TypePromotionInterpreter.run_node\n- self: \n- node: fx.Node()[call_function]:Tensor(f32[4, 16, 1024, 64])\n## Return values\nTensor(f32[4, 16, 1024, 64])", + "text":"Skipped for fx.Node()[call_function]:Tensor(f32[4, 16, 1024, 64]): node.target is not OpOverload. Got type: " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":1625 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0015", + "stacks":[] + }, + { + "message":{ + "markdown":"Skipped for fx.Node()[call_function]:Tensor(f32[4, 16, 1024, 64]): node.target is not OpOverload. Got type: \n\n## Additional Message:\n\n## Function Signature\n### Function Signature _TypePromotionInterpreter.run_node\n- self: \n- node: fx.Node()[call_function]:Tensor(f32[4, 16, 1024, 64])\n## Return values\nTensor(f32[4, 16, 1024, 64])", + "text":"Skipped for fx.Node()[call_function]:Tensor(f32[4, 16, 1024, 64]): node.target is not OpOverload. Got type: " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":1625 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0015", + "stacks":[] + }, + { + "message":{ + "markdown":"Skipped for fx.Node(aten._scaled_dot_product_efficient_attention.default)[call_function]:Tuple[length=4](\nTensor(f32[4, 16, 1024, 64]),\nTensor(f32[4, 16, 0]),\nTensor(i64[]),\nTensor(i64[]),\n): Cannot find type promotion rule for op: aten._scaled_dot_product_efficient_attention.default\n\n## Additional Message:\n\n## Function Signature\n### Function Signature _TypePromotionInterpreter.run_node\n- self: \n- node: fx.Node(aten._scaled_dot_product_efficient_attention.default)[call_function]:Tuple[length=4](\nTensor(f32[4, 16, 1024, 64]),\nTensor(f32[4, 16, 0]),\nTensor(i64[]),\nTensor(i64[]),\n)\n## Return values\nTuple[length=4](\nTensor(f32[4, 16, 1024, 64]),\nTensor(f32[4, 16, 0]),\nTensor(i64[]),\nTensor(i64[]),\n)", + "text":"Skipped for fx.Node(aten._scaled_dot_product_efficient_attention.default)[call_function]:Tuple[length=4](\nTensor(f32[4, 16, 1024, 64]),\nTensor(f32[4, 16, 0]),\nTensor(i64[]),\nTensor(i64[]),\n): Cannot find type promotion rule for op: aten._scaled_dot_product_efficient_attention.default" + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":1625 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0015", + "stacks":[] + }, + { + "message":{ + "markdown":"Skipped for fx.Node()[call_function]:Tensor(f32[4, 16, 1024, 64]): node.target is not OpOverload. Got type: \n\n## Additional Message:\n\n## Function Signature\n### Function Signature _TypePromotionInterpreter.run_node\n- self: \n- node: fx.Node()[call_function]:Tensor(f32[4, 16, 1024, 64])\n## Return values\nTensor(f32[4, 16, 1024, 64])", + "text":"Skipped for fx.Node()[call_function]:Tensor(f32[4, 16, 1024, 64]): node.target is not OpOverload. Got type: " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":1625 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0015", + "stacks":[] + }, + { + "message":{ + "markdown":"Skipped for fx.Node(aten.transpose.int)[call_function]:Tensor(f32[4, 1024, 16, 64]): Cannot find type promotion rule for op: aten.transpose.int\n\n## Additional Message:\n\n## Function Signature\n### Function Signature _TypePromotionInterpreter.run_node\n- self: \n- node: fx.Node(aten.transpose.int)[call_function]:Tensor(f32[4, 1024, 16, 64])\n## Return values\nTensor(f32[4, 1024, 16, 64])", + "text":"Skipped for fx.Node(aten.transpose.int)[call_function]:Tensor(f32[4, 1024, 16, 64]): Cannot find type promotion rule for op: aten.transpose.int" + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":1625 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0015", + "stacks":[] + }, + { + "message":{ + "markdown":"Skipped for fx.Node(aten.view.default)[call_function]:Tensor(f32[4, 1024, 1024]): Cannot find type promotion rule for op: aten.view.default\n\n## Additional Message:\n\n## Function Signature\n### Function Signature _TypePromotionInterpreter.run_node\n- self: \n- node: fx.Node(aten.view.default)[call_function]:Tensor(f32[4, 1024, 1024])\n## Return values\nTensor(f32[4, 1024, 1024])", + "text":"Skipped for fx.Node(aten.view.default)[call_function]:Tensor(f32[4, 1024, 1024]): Cannot find type promotion rule for op: aten.view.default" + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":1625 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0015", + "stacks":[] + }, + { + "message":{ + "markdown":"Skipped for fx.Node(aten.view.default)[call_function]:Tensor(f32[4096, 1024]): Cannot find type promotion rule for op: aten.view.default\n\n## Additional Message:\n\n## Function Signature\n### Function Signature _TypePromotionInterpreter.run_node\n- self: \n- node: fx.Node(aten.view.default)[call_function]:Tensor(f32[4096, 1024])\n## Return values\nTensor(f32[4096, 1024])", + "text":"Skipped for fx.Node(aten.view.default)[call_function]:Tensor(f32[4096, 1024]): Cannot find type promotion rule for op: aten.view.default" + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":1625 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0015", + "stacks":[] + }, + { + "message":{ + "markdown":"Skipped for fx.Node(aten.t.default)[call_function]:Tensor(f32[1024, 1024]): Cannot find type promotion rule for op: aten.t.default\n\n## Additional Message:\n\n## Function Signature\n### Function Signature _TypePromotionInterpreter.run_node\n- self: \n- node: fx.Node(aten.t.default)[call_function]:Tensor(f32[1024, 1024])\n## Return values\nTensor(f32[1024, 1024])", + "text":"Skipped for fx.Node(aten.t.default)[call_function]:Tensor(f32[1024, 1024]): Cannot find type promotion rule for op: aten.t.default" + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":1625 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0015", + "stacks":[] + }, + { + "message":{ + "markdown":"Skipped for fx.Node(aten.addmm.default)[call_function]:Tensor(f32[4096, 1024]): Cannot find type promotion rule for op: aten.addmm.default\n\n## Additional Message:\n\n## Function Signature\n### Function Signature _TypePromotionInterpreter.run_node\n- self: \n- node: fx.Node(aten.addmm.default)[call_function]:Tensor(f32[4096, 1024])\n## Return values\nTensor(f32[4096, 1024])", + "text":"Skipped for fx.Node(aten.addmm.default)[call_function]:Tensor(f32[4096, 1024]): Cannot find type promotion rule for op: aten.addmm.default" + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":1625 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0015", + "stacks":[] + }, + { + "message":{ + "markdown":"Skipped for fx.Node(aten.view.default)[call_function]:Tensor(f32[4, 1024, 1024]): Cannot find type promotion rule for op: aten.view.default\n\n## Additional Message:\n\n## Function Signature\n### Function Signature _TypePromotionInterpreter.run_node\n- self: \n- node: fx.Node(aten.view.default)[call_function]:Tensor(f32[4, 1024, 1024])\n## Return values\nTensor(f32[4, 1024, 1024])", + "text":"Skipped for fx.Node(aten.view.default)[call_function]:Tensor(f32[4, 1024, 1024]): Cannot find type promotion rule for op: aten.view.default" + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":1625 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0015", + "stacks":[] + }, + { + "message":{ + "markdown":"Skipped for fx.Node(aten.clone.default)[call_function]:Tensor(f32[4, 1024, 1024]): Cannot find type promotion rule for op: aten.clone.default\n\n## Additional Message:\n\n## Function Signature\n### Function Signature _TypePromotionInterpreter.run_node\n- self: \n- node: fx.Node(aten.clone.default)[call_function]:Tensor(f32[4, 1024, 1024])\n## Return values\nTensor(f32[4, 1024, 1024])", + "text":"Skipped for fx.Node(aten.clone.default)[call_function]:Tensor(f32[4, 1024, 1024]): Cannot find type promotion rule for op: aten.clone.default" + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":1625 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0015", + "stacks":[] + }, + { + "message":{ + "markdown":"Type promotion not needed for add_41. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature _TypePromotionInterpreter.run_node\n- self: \n- node: fx.Node(aten.add.Tensor)[call_function]:Tensor(f32[4, 1024, 1024])\nFound type promotion rule: ElementwiseTypePromotionRule('aten', 'add', [0, 1], [], ELEMENTWISE_TYPE_PROMOTION_KIND.DEFAULT)\nArgument add_40 is not promoted. Already torch.float32.\nArgument clone_61 is not promoted. Already torch.float32.\n## Return values\nTensor(f32[4, 1024, 1024])", + "text":"Type promotion not needed for add_41. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":1625 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0015", + "stacks":[] + }, + { + "message":{ + "markdown":"Skipped for fx.Node(aten.native_layer_norm.default)[call_function]:Tuple[length=3](\nTensor(f32[4, 1024, 1024]),\nTensor(f32[4, 1024, 1]),\nTensor(f32[4, 1024, 1]),\n): Cannot find type promotion rule for op: aten.native_layer_norm.default\n\n## Additional Message:\n\n## Function Signature\n### Function Signature _TypePromotionInterpreter.run_node\n- self: \n- node: fx.Node(aten.native_layer_norm.default)[call_function]:Tuple[length=3](\nTensor(f32[4, 1024, 1024]),\nTensor(f32[4, 1024, 1]),\nTensor(f32[4, 1024, 1]),\n)\n## Return values\nTuple[length=3](\nTensor(f32[4, 1024, 1024]),\nTensor(f32[4, 1024, 1]),\nTensor(f32[4, 1024, 1]),\n)", + "text":"Skipped for fx.Node(aten.native_layer_norm.default)[call_function]:Tuple[length=3](\nTensor(f32[4, 1024, 1024]),\nTensor(f32[4, 1024, 1]),\nTensor(f32[4, 1024, 1]),\n): Cannot find type promotion rule for op: aten.native_layer_norm.default" + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":1625 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0015", + "stacks":[] + }, + { + "message":{ + "markdown":"Skipped for fx.Node()[call_function]:Tensor(f32[4, 1024, 1024]): node.target is not OpOverload. Got type: \n\n## Additional Message:\n\n## Function Signature\n### Function Signature _TypePromotionInterpreter.run_node\n- self: \n- node: fx.Node()[call_function]:Tensor(f32[4, 1024, 1024])\n## Return values\nTensor(f32[4, 1024, 1024])", + "text":"Skipped for fx.Node()[call_function]:Tensor(f32[4, 1024, 1024]): node.target is not OpOverload. Got type: " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":1625 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0015", + "stacks":[] + }, + { + "message":{ + "markdown":"Skipped for fx.Node(aten.view.default)[call_function]:Tensor(f32[4096, 1024]): Cannot find type promotion rule for op: aten.view.default\n\n## Additional Message:\n\n## Function Signature\n### Function Signature _TypePromotionInterpreter.run_node\n- self: \n- node: fx.Node(aten.view.default)[call_function]:Tensor(f32[4096, 1024])\n## Return values\nTensor(f32[4096, 1024])", + "text":"Skipped for fx.Node(aten.view.default)[call_function]:Tensor(f32[4096, 1024]): Cannot find type promotion rule for op: aten.view.default" + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":1625 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0015", + "stacks":[] + }, + { + "message":{ + "markdown":"Skipped for fx.Node(aten.t.default)[call_function]:Tensor(f32[1024, 4096]): Cannot find type promotion rule for op: aten.t.default\n\n## Additional Message:\n\n## Function Signature\n### Function Signature _TypePromotionInterpreter.run_node\n- self: \n- node: fx.Node(aten.t.default)[call_function]:Tensor(f32[1024, 4096])\n## Return values\nTensor(f32[1024, 4096])", + "text":"Skipped for fx.Node(aten.t.default)[call_function]:Tensor(f32[1024, 4096]): Cannot find type promotion rule for op: aten.t.default" + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":1625 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0015", + "stacks":[] + }, + { + "message":{ + "markdown":"Skipped for fx.Node(aten.addmm.default)[call_function]:Tensor(f32[4096, 4096]): Cannot find type promotion rule for op: aten.addmm.default\n\n## Additional Message:\n\n## Function Signature\n### Function Signature _TypePromotionInterpreter.run_node\n- self: \n- node: fx.Node(aten.addmm.default)[call_function]:Tensor(f32[4096, 4096])\n## Return values\nTensor(f32[4096, 4096])", + "text":"Skipped for fx.Node(aten.addmm.default)[call_function]:Tensor(f32[4096, 4096]): Cannot find type promotion rule for op: aten.addmm.default" + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":1625 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0015", + "stacks":[] + }, + { + "message":{ + "markdown":"Skipped for fx.Node(aten.view.default)[call_function]:Tensor(f32[4, 1024, 4096]): Cannot find type promotion rule for op: aten.view.default\n\n## Additional Message:\n\n## Function Signature\n### Function Signature _TypePromotionInterpreter.run_node\n- self: \n- node: fx.Node(aten.view.default)[call_function]:Tensor(f32[4, 1024, 4096])\n## Return values\nTensor(f32[4, 1024, 4096])", + "text":"Skipped for fx.Node(aten.view.default)[call_function]:Tensor(f32[4, 1024, 4096]): Cannot find type promotion rule for op: aten.view.default" + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":1625 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0015", + "stacks":[] + }, + { + "message":{ + "markdown":"Type promotion not needed for gelu_20. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature _TypePromotionInterpreter.run_node\n- self: \n- node: fx.Node(aten.gelu.default)[call_function]:Tensor(f32[4, 1024, 4096])\nFound type promotion rule: ElementwiseTypePromotionRule('aten', 'gelu', [0], [], ELEMENTWISE_TYPE_PROMOTION_KIND.DEFAULT)\nArgument view_208 is not promoted. Already torch.float32.\nArgument tanh is not promoted. Not mentioned by type promotion rule.\n## Return values\nTensor(f32[4, 1024, 4096])", + "text":"Type promotion not needed for gelu_20. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":1625 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0015", + "stacks":[] + }, + { + "message":{ + "markdown":"Skipped for fx.Node(aten.clone.default)[call_function]:Tensor(f32[4, 1024, 4096]): Cannot find type promotion rule for op: aten.clone.default\n\n## Additional Message:\n\n## Function Signature\n### Function Signature _TypePromotionInterpreter.run_node\n- self: \n- node: fx.Node(aten.clone.default)[call_function]:Tensor(f32[4, 1024, 4096])\n## Return values\nTensor(f32[4, 1024, 4096])", + "text":"Skipped for fx.Node(aten.clone.default)[call_function]:Tensor(f32[4, 1024, 4096]): Cannot find type promotion rule for op: aten.clone.default" + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":1625 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0015", + "stacks":[] + }, + { + "message":{ + "markdown":"Skipped for fx.Node(aten.view.default)[call_function]:Tensor(f32[4096, 4096]): Cannot find type promotion rule for op: aten.view.default\n\n## Additional Message:\n\n## Function Signature\n### Function Signature _TypePromotionInterpreter.run_node\n- self: \n- node: fx.Node(aten.view.default)[call_function]:Tensor(f32[4096, 4096])\n## Return values\nTensor(f32[4096, 4096])", + "text":"Skipped for fx.Node(aten.view.default)[call_function]:Tensor(f32[4096, 4096]): Cannot find type promotion rule for op: aten.view.default" + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":1625 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0015", + "stacks":[] + }, + { + "message":{ + "markdown":"Skipped for fx.Node(aten.t.default)[call_function]:Tensor(f32[4096, 1024]): Cannot find type promotion rule for op: aten.t.default\n\n## Additional Message:\n\n## Function Signature\n### Function Signature _TypePromotionInterpreter.run_node\n- self: \n- node: fx.Node(aten.t.default)[call_function]:Tensor(f32[4096, 1024])\n## Return values\nTensor(f32[4096, 1024])", + "text":"Skipped for fx.Node(aten.t.default)[call_function]:Tensor(f32[4096, 1024]): Cannot find type promotion rule for op: aten.t.default" + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":1625 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0015", + "stacks":[] + }, + { + "message":{ + "markdown":"Skipped for fx.Node(aten.addmm.default)[call_function]:Tensor(f32[4096, 1024]): Cannot find type promotion rule for op: aten.addmm.default\n\n## Additional Message:\n\n## Function Signature\n### Function Signature _TypePromotionInterpreter.run_node\n- self: \n- node: fx.Node(aten.addmm.default)[call_function]:Tensor(f32[4096, 1024])\n## Return values\nTensor(f32[4096, 1024])", + "text":"Skipped for fx.Node(aten.addmm.default)[call_function]:Tensor(f32[4096, 1024]): Cannot find type promotion rule for op: aten.addmm.default" + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":1625 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0015", + "stacks":[] + }, + { + "message":{ + "markdown":"Skipped for fx.Node(aten.view.default)[call_function]:Tensor(f32[4, 1024, 1024]): Cannot find type promotion rule for op: aten.view.default\n\n## Additional Message:\n\n## Function Signature\n### Function Signature _TypePromotionInterpreter.run_node\n- self: \n- node: fx.Node(aten.view.default)[call_function]:Tensor(f32[4, 1024, 1024])\n## Return values\nTensor(f32[4, 1024, 1024])", + "text":"Skipped for fx.Node(aten.view.default)[call_function]:Tensor(f32[4, 1024, 1024]): Cannot find type promotion rule for op: aten.view.default" + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":1625 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0015", + "stacks":[] + }, + { + "message":{ + "markdown":"Skipped for fx.Node(aten.clone.default)[call_function]:Tensor(f32[4, 1024, 1024]): Cannot find type promotion rule for op: aten.clone.default\n\n## Additional Message:\n\n## Function Signature\n### Function Signature _TypePromotionInterpreter.run_node\n- self: \n- node: fx.Node(aten.clone.default)[call_function]:Tensor(f32[4, 1024, 1024])\n## Return values\nTensor(f32[4, 1024, 1024])", + "text":"Skipped for fx.Node(aten.clone.default)[call_function]:Tensor(f32[4, 1024, 1024]): Cannot find type promotion rule for op: aten.clone.default" + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":1625 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0015", + "stacks":[] + }, + { + "message":{ + "markdown":"Type promotion not needed for add_42. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature _TypePromotionInterpreter.run_node\n- self: \n- node: fx.Node(aten.add.Tensor)[call_function]:Tensor(f32[4, 1024, 1024])\nFound type promotion rule: ElementwiseTypePromotionRule('aten', 'add', [0, 1], [], ELEMENTWISE_TYPE_PROMOTION_KIND.DEFAULT)\nArgument add_41 is not promoted. Already torch.float32.\nArgument clone_63 is not promoted. Already torch.float32.\n## Return values\nTensor(f32[4, 1024, 1024])", + "text":"Type promotion not needed for add_42. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":1625 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0015", + "stacks":[] + }, + { + "message":{ + "markdown":"Skipped for fx.Node(aten.native_layer_norm.default)[call_function]:Tuple[length=3](\nTensor(f32[4, 1024, 1024]),\nTensor(f32[4, 1024, 1]),\nTensor(f32[4, 1024, 1]),\n): Cannot find type promotion rule for op: aten.native_layer_norm.default\n\n## Additional Message:\n\n## Function Signature\n### Function Signature _TypePromotionInterpreter.run_node\n- self: \n- node: fx.Node(aten.native_layer_norm.default)[call_function]:Tuple[length=3](\nTensor(f32[4, 1024, 1024]),\nTensor(f32[4, 1024, 1]),\nTensor(f32[4, 1024, 1]),\n)\n## Return values\nTuple[length=3](\nTensor(f32[4, 1024, 1024]),\nTensor(f32[4, 1024, 1]),\nTensor(f32[4, 1024, 1]),\n)", + "text":"Skipped for fx.Node(aten.native_layer_norm.default)[call_function]:Tuple[length=3](\nTensor(f32[4, 1024, 1024]),\nTensor(f32[4, 1024, 1]),\nTensor(f32[4, 1024, 1]),\n): Cannot find type promotion rule for op: aten.native_layer_norm.default" + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":1625 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0015", + "stacks":[] + }, + { + "message":{ + "markdown":"Skipped for fx.Node()[call_function]:Tensor(f32[4, 1024, 1024]): node.target is not OpOverload. Got type: \n\n## Additional Message:\n\n## Function Signature\n### Function Signature _TypePromotionInterpreter.run_node\n- self: \n- node: fx.Node()[call_function]:Tensor(f32[4, 1024, 1024])\n## Return values\nTensor(f32[4, 1024, 1024])", + "text":"Skipped for fx.Node()[call_function]:Tensor(f32[4, 1024, 1024]): node.target is not OpOverload. Got type: " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":1625 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0015", + "stacks":[] + }, + { + "message":{ + "markdown":"Skipped for fx.Node(aten.view.default)[call_function]:Tensor(f32[4096, 1024]): Cannot find type promotion rule for op: aten.view.default\n\n## Additional Message:\n\n## Function Signature\n### Function Signature _TypePromotionInterpreter.run_node\n- self: \n- node: fx.Node(aten.view.default)[call_function]:Tensor(f32[4096, 1024])\n## Return values\nTensor(f32[4096, 1024])", + "text":"Skipped for fx.Node(aten.view.default)[call_function]:Tensor(f32[4096, 1024]): Cannot find type promotion rule for op: aten.view.default" + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":1625 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0015", + "stacks":[] + }, + { + "message":{ + "markdown":"Skipped for fx.Node(aten.t.default)[call_function]:Tensor(f32[1024, 3072]): Cannot find type promotion rule for op: aten.t.default\n\n## Additional Message:\n\n## Function Signature\n### Function Signature _TypePromotionInterpreter.run_node\n- self: \n- node: fx.Node(aten.t.default)[call_function]:Tensor(f32[1024, 3072])\n## Return values\nTensor(f32[1024, 3072])", + "text":"Skipped for fx.Node(aten.t.default)[call_function]:Tensor(f32[1024, 3072]): Cannot find type promotion rule for op: aten.t.default" + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":1625 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0015", + "stacks":[] + }, + { + "message":{ + "markdown":"Skipped for fx.Node(aten.addmm.default)[call_function]:Tensor(f32[4096, 3072]): Cannot find type promotion rule for op: aten.addmm.default\n\n## Additional Message:\n\n## Function Signature\n### Function Signature _TypePromotionInterpreter.run_node\n- self: \n- node: fx.Node(aten.addmm.default)[call_function]:Tensor(f32[4096, 3072])\n## Return values\nTensor(f32[4096, 3072])", + "text":"Skipped for fx.Node(aten.addmm.default)[call_function]:Tensor(f32[4096, 3072]): Cannot find type promotion rule for op: aten.addmm.default" + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":1625 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0015", + "stacks":[] + }, + { + "message":{ + "markdown":"Skipped for fx.Node(aten.view.default)[call_function]:Tensor(f32[4, 1024, 3072]): Cannot find type promotion rule for op: aten.view.default\n\n## Additional Message:\n\n## Function Signature\n### Function Signature _TypePromotionInterpreter.run_node\n- self: \n- node: fx.Node(aten.view.default)[call_function]:Tensor(f32[4, 1024, 3072])\n## Return values\nTensor(f32[4, 1024, 3072])", + "text":"Skipped for fx.Node(aten.view.default)[call_function]:Tensor(f32[4, 1024, 3072]): Cannot find type promotion rule for op: aten.view.default" + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":1625 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0015", + "stacks":[] + }, + { + "message":{ + "markdown":"Skipped for fx.Node(aten.view.default)[call_function]:Tensor(f32[4, 1024, 3, 16, 64]): Cannot find type promotion rule for op: aten.view.default\n\n## Additional Message:\n\n## Function Signature\n### Function Signature _TypePromotionInterpreter.run_node\n- self: \n- node: fx.Node(aten.view.default)[call_function]:Tensor(f32[4, 1024, 3, 16, 64])\n## Return values\nTensor(f32[4, 1024, 3, 16, 64])", + "text":"Skipped for fx.Node(aten.view.default)[call_function]:Tensor(f32[4, 1024, 3, 16, 64]): Cannot find type promotion rule for op: aten.view.default" + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":1625 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0015", + "stacks":[] + }, + { + "message":{ + "markdown":"Skipped for fx.Node(aten.permute.default)[call_function]:Tensor(f32[3, 4, 16, 1024, 64]): Cannot find type promotion rule for op: aten.permute.default\n\n## Additional Message:\n\n## Function Signature\n### Function Signature _TypePromotionInterpreter.run_node\n- self: \n- node: fx.Node(aten.permute.default)[call_function]:Tensor(f32[3, 4, 16, 1024, 64])\n## Return values\nTensor(f32[3, 4, 16, 1024, 64])", + "text":"Skipped for fx.Node(aten.permute.default)[call_function]:Tensor(f32[3, 4, 16, 1024, 64]): Cannot find type promotion rule for op: aten.permute.default" + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":1625 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0015", + "stacks":[] + }, + { + "message":{ + "markdown":"Skipped for fx.Node(aten.unbind.int)[call_function]:List[length=3](\nTensor(f32[4, 16, 1024, 64]),\nTensor(f32[4, 16, 1024, 64]),\nTensor(f32[4, 16, 1024, 64]),\n): Cannot find type promotion rule for op: aten.unbind.int\n\n## Additional Message:\n\n## Function Signature\n### Function Signature _TypePromotionInterpreter.run_node\n- self: \n- node: fx.Node(aten.unbind.int)[call_function]:List[length=3](\nTensor(f32[4, 16, 1024, 64]),\nTensor(f32[4, 16, 1024, 64]),\nTensor(f32[4, 16, 1024, 64]),\n)\n## Return values\nList[length=3](\nTensor(f32[4, 16, 1024, 64]),\nTensor(f32[4, 16, 1024, 64]),\nTensor(f32[4, 16, 1024, 64]),\n)", + "text":"Skipped for fx.Node(aten.unbind.int)[call_function]:List[length=3](\nTensor(f32[4, 16, 1024, 64]),\nTensor(f32[4, 16, 1024, 64]),\nTensor(f32[4, 16, 1024, 64]),\n): Cannot find type promotion rule for op: aten.unbind.int" + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":1625 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0015", + "stacks":[] + }, + { + "message":{ + "markdown":"Skipped for fx.Node()[call_function]:Tensor(f32[4, 16, 1024, 64]): node.target is not OpOverload. Got type: \n\n## Additional Message:\n\n## Function Signature\n### Function Signature _TypePromotionInterpreter.run_node\n- self: \n- node: fx.Node()[call_function]:Tensor(f32[4, 16, 1024, 64])\n## Return values\nTensor(f32[4, 16, 1024, 64])", + "text":"Skipped for fx.Node()[call_function]:Tensor(f32[4, 16, 1024, 64]): node.target is not OpOverload. Got type: " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":1625 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0015", + "stacks":[] + }, + { + "message":{ + "markdown":"Skipped for fx.Node()[call_function]:Tensor(f32[4, 16, 1024, 64]): node.target is not OpOverload. Got type: \n\n## Additional Message:\n\n## Function Signature\n### Function Signature _TypePromotionInterpreter.run_node\n- self: \n- node: fx.Node()[call_function]:Tensor(f32[4, 16, 1024, 64])\n## Return values\nTensor(f32[4, 16, 1024, 64])", + "text":"Skipped for fx.Node()[call_function]:Tensor(f32[4, 16, 1024, 64]): node.target is not OpOverload. Got type: " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":1625 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0015", + "stacks":[] + }, + { + "message":{ + "markdown":"Skipped for fx.Node()[call_function]:Tensor(f32[4, 16, 1024, 64]): node.target is not OpOverload. Got type: \n\n## Additional Message:\n\n## Function Signature\n### Function Signature _TypePromotionInterpreter.run_node\n- self: \n- node: fx.Node()[call_function]:Tensor(f32[4, 16, 1024, 64])\n## Return values\nTensor(f32[4, 16, 1024, 64])", + "text":"Skipped for fx.Node()[call_function]:Tensor(f32[4, 16, 1024, 64]): node.target is not OpOverload. Got type: " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":1625 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0015", + "stacks":[] + }, + { + "message":{ + "markdown":"Skipped for fx.Node(aten._scaled_dot_product_efficient_attention.default)[call_function]:Tuple[length=4](\nTensor(f32[4, 16, 1024, 64]),\nTensor(f32[4, 16, 0]),\nTensor(i64[]),\nTensor(i64[]),\n): Cannot find type promotion rule for op: aten._scaled_dot_product_efficient_attention.default\n\n## Additional Message:\n\n## Function Signature\n### Function Signature _TypePromotionInterpreter.run_node\n- self: \n- node: fx.Node(aten._scaled_dot_product_efficient_attention.default)[call_function]:Tuple[length=4](\nTensor(f32[4, 16, 1024, 64]),\nTensor(f32[4, 16, 0]),\nTensor(i64[]),\nTensor(i64[]),\n)\n## Return values\nTuple[length=4](\nTensor(f32[4, 16, 1024, 64]),\nTensor(f32[4, 16, 0]),\nTensor(i64[]),\nTensor(i64[]),\n)", + "text":"Skipped for fx.Node(aten._scaled_dot_product_efficient_attention.default)[call_function]:Tuple[length=4](\nTensor(f32[4, 16, 1024, 64]),\nTensor(f32[4, 16, 0]),\nTensor(i64[]),\nTensor(i64[]),\n): Cannot find type promotion rule for op: aten._scaled_dot_product_efficient_attention.default" + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":1625 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0015", + "stacks":[] + }, + { + "message":{ + "markdown":"Skipped for fx.Node()[call_function]:Tensor(f32[4, 16, 1024, 64]): node.target is not OpOverload. Got type: \n\n## Additional Message:\n\n## Function Signature\n### Function Signature _TypePromotionInterpreter.run_node\n- self: \n- node: fx.Node()[call_function]:Tensor(f32[4, 16, 1024, 64])\n## Return values\nTensor(f32[4, 16, 1024, 64])", + "text":"Skipped for fx.Node()[call_function]:Tensor(f32[4, 16, 1024, 64]): node.target is not OpOverload. Got type: " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":1625 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0015", + "stacks":[] + }, + { + "message":{ + "markdown":"Skipped for fx.Node(aten.transpose.int)[call_function]:Tensor(f32[4, 1024, 16, 64]): Cannot find type promotion rule for op: aten.transpose.int\n\n## Additional Message:\n\n## Function Signature\n### Function Signature _TypePromotionInterpreter.run_node\n- self: \n- node: fx.Node(aten.transpose.int)[call_function]:Tensor(f32[4, 1024, 16, 64])\n## Return values\nTensor(f32[4, 1024, 16, 64])", + "text":"Skipped for fx.Node(aten.transpose.int)[call_function]:Tensor(f32[4, 1024, 16, 64]): Cannot find type promotion rule for op: aten.transpose.int" + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":1625 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0015", + "stacks":[] + }, + { + "message":{ + "markdown":"Skipped for fx.Node(aten.view.default)[call_function]:Tensor(f32[4, 1024, 1024]): Cannot find type promotion rule for op: aten.view.default\n\n## Additional Message:\n\n## Function Signature\n### Function Signature _TypePromotionInterpreter.run_node\n- self: \n- node: fx.Node(aten.view.default)[call_function]:Tensor(f32[4, 1024, 1024])\n## Return values\nTensor(f32[4, 1024, 1024])", + "text":"Skipped for fx.Node(aten.view.default)[call_function]:Tensor(f32[4, 1024, 1024]): Cannot find type promotion rule for op: aten.view.default" + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":1625 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0015", + "stacks":[] + }, + { + "message":{ + "markdown":"Skipped for fx.Node(aten.view.default)[call_function]:Tensor(f32[4096, 1024]): Cannot find type promotion rule for op: aten.view.default\n\n## Additional Message:\n\n## Function Signature\n### Function Signature _TypePromotionInterpreter.run_node\n- self: \n- node: fx.Node(aten.view.default)[call_function]:Tensor(f32[4096, 1024])\n## Return values\nTensor(f32[4096, 1024])", + "text":"Skipped for fx.Node(aten.view.default)[call_function]:Tensor(f32[4096, 1024]): Cannot find type promotion rule for op: aten.view.default" + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":1625 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0015", + "stacks":[] + }, + { + "message":{ + "markdown":"Skipped for fx.Node(aten.t.default)[call_function]:Tensor(f32[1024, 1024]): Cannot find type promotion rule for op: aten.t.default\n\n## Additional Message:\n\n## Function Signature\n### Function Signature _TypePromotionInterpreter.run_node\n- self: \n- node: fx.Node(aten.t.default)[call_function]:Tensor(f32[1024, 1024])\n## Return values\nTensor(f32[1024, 1024])", + "text":"Skipped for fx.Node(aten.t.default)[call_function]:Tensor(f32[1024, 1024]): Cannot find type promotion rule for op: aten.t.default" + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":1625 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0015", + "stacks":[] + }, + { + "message":{ + "markdown":"Skipped for fx.Node(aten.addmm.default)[call_function]:Tensor(f32[4096, 1024]): Cannot find type promotion rule for op: aten.addmm.default\n\n## Additional Message:\n\n## Function Signature\n### Function Signature _TypePromotionInterpreter.run_node\n- self: \n- node: fx.Node(aten.addmm.default)[call_function]:Tensor(f32[4096, 1024])\n## Return values\nTensor(f32[4096, 1024])", + "text":"Skipped for fx.Node(aten.addmm.default)[call_function]:Tensor(f32[4096, 1024]): Cannot find type promotion rule for op: aten.addmm.default" + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":1625 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0015", + "stacks":[] + }, + { + "message":{ + "markdown":"Skipped for fx.Node(aten.view.default)[call_function]:Tensor(f32[4, 1024, 1024]): Cannot find type promotion rule for op: aten.view.default\n\n## Additional Message:\n\n## Function Signature\n### Function Signature _TypePromotionInterpreter.run_node\n- self: \n- node: fx.Node(aten.view.default)[call_function]:Tensor(f32[4, 1024, 1024])\n## Return values\nTensor(f32[4, 1024, 1024])", + "text":"Skipped for fx.Node(aten.view.default)[call_function]:Tensor(f32[4, 1024, 1024]): Cannot find type promotion rule for op: aten.view.default" + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":1625 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0015", + "stacks":[] + }, + { + "message":{ + "markdown":"Skipped for fx.Node(aten.clone.default)[call_function]:Tensor(f32[4, 1024, 1024]): Cannot find type promotion rule for op: aten.clone.default\n\n## Additional Message:\n\n## Function Signature\n### Function Signature _TypePromotionInterpreter.run_node\n- self: \n- node: fx.Node(aten.clone.default)[call_function]:Tensor(f32[4, 1024, 1024])\n## Return values\nTensor(f32[4, 1024, 1024])", + "text":"Skipped for fx.Node(aten.clone.default)[call_function]:Tensor(f32[4, 1024, 1024]): Cannot find type promotion rule for op: aten.clone.default" + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":1625 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0015", + "stacks":[] + }, + { + "message":{ + "markdown":"Type promotion not needed for add_43. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature _TypePromotionInterpreter.run_node\n- self: \n- node: fx.Node(aten.add.Tensor)[call_function]:Tensor(f32[4, 1024, 1024])\nFound type promotion rule: ElementwiseTypePromotionRule('aten', 'add', [0, 1], [], ELEMENTWISE_TYPE_PROMOTION_KIND.DEFAULT)\nArgument add_42 is not promoted. Already torch.float32.\nArgument clone_64 is not promoted. Already torch.float32.\n## Return values\nTensor(f32[4, 1024, 1024])", + "text":"Type promotion not needed for add_43. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":1625 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0015", + "stacks":[] + }, + { + "message":{ + "markdown":"Skipped for fx.Node(aten.native_layer_norm.default)[call_function]:Tuple[length=3](\nTensor(f32[4, 1024, 1024]),\nTensor(f32[4, 1024, 1]),\nTensor(f32[4, 1024, 1]),\n): Cannot find type promotion rule for op: aten.native_layer_norm.default\n\n## Additional Message:\n\n## Function Signature\n### Function Signature _TypePromotionInterpreter.run_node\n- self: \n- node: fx.Node(aten.native_layer_norm.default)[call_function]:Tuple[length=3](\nTensor(f32[4, 1024, 1024]),\nTensor(f32[4, 1024, 1]),\nTensor(f32[4, 1024, 1]),\n)\n## Return values\nTuple[length=3](\nTensor(f32[4, 1024, 1024]),\nTensor(f32[4, 1024, 1]),\nTensor(f32[4, 1024, 1]),\n)", + "text":"Skipped for fx.Node(aten.native_layer_norm.default)[call_function]:Tuple[length=3](\nTensor(f32[4, 1024, 1024]),\nTensor(f32[4, 1024, 1]),\nTensor(f32[4, 1024, 1]),\n): Cannot find type promotion rule for op: aten.native_layer_norm.default" + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":1625 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0015", + "stacks":[] + }, + { + "message":{ + "markdown":"Skipped for fx.Node()[call_function]:Tensor(f32[4, 1024, 1024]): node.target is not OpOverload. Got type: \n\n## Additional Message:\n\n## Function Signature\n### Function Signature _TypePromotionInterpreter.run_node\n- self: \n- node: fx.Node()[call_function]:Tensor(f32[4, 1024, 1024])\n## Return values\nTensor(f32[4, 1024, 1024])", + "text":"Skipped for fx.Node()[call_function]:Tensor(f32[4, 1024, 1024]): node.target is not OpOverload. Got type: " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":1625 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0015", + "stacks":[] + }, + { + "message":{ + "markdown":"Skipped for fx.Node(aten.view.default)[call_function]:Tensor(f32[4096, 1024]): Cannot find type promotion rule for op: aten.view.default\n\n## Additional Message:\n\n## Function Signature\n### Function Signature _TypePromotionInterpreter.run_node\n- self: \n- node: fx.Node(aten.view.default)[call_function]:Tensor(f32[4096, 1024])\n## Return values\nTensor(f32[4096, 1024])", + "text":"Skipped for fx.Node(aten.view.default)[call_function]:Tensor(f32[4096, 1024]): Cannot find type promotion rule for op: aten.view.default" + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":1625 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0015", + "stacks":[] + }, + { + "message":{ + "markdown":"Skipped for fx.Node(aten.t.default)[call_function]:Tensor(f32[1024, 4096]): Cannot find type promotion rule for op: aten.t.default\n\n## Additional Message:\n\n## Function Signature\n### Function Signature _TypePromotionInterpreter.run_node\n- self: \n- node: fx.Node(aten.t.default)[call_function]:Tensor(f32[1024, 4096])\n## Return values\nTensor(f32[1024, 4096])", + "text":"Skipped for fx.Node(aten.t.default)[call_function]:Tensor(f32[1024, 4096]): Cannot find type promotion rule for op: aten.t.default" + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":1625 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0015", + "stacks":[] + }, + { + "message":{ + "markdown":"Skipped for fx.Node(aten.addmm.default)[call_function]:Tensor(f32[4096, 4096]): Cannot find type promotion rule for op: aten.addmm.default\n\n## Additional Message:\n\n## Function Signature\n### Function Signature _TypePromotionInterpreter.run_node\n- self: \n- node: fx.Node(aten.addmm.default)[call_function]:Tensor(f32[4096, 4096])\n## Return values\nTensor(f32[4096, 4096])", + "text":"Skipped for fx.Node(aten.addmm.default)[call_function]:Tensor(f32[4096, 4096]): Cannot find type promotion rule for op: aten.addmm.default" + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":1625 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0015", + "stacks":[] + }, + { + "message":{ + "markdown":"Skipped for fx.Node(aten.view.default)[call_function]:Tensor(f32[4, 1024, 4096]): Cannot find type promotion rule for op: aten.view.default\n\n## Additional Message:\n\n## Function Signature\n### Function Signature _TypePromotionInterpreter.run_node\n- self: \n- node: fx.Node(aten.view.default)[call_function]:Tensor(f32[4, 1024, 4096])\n## Return values\nTensor(f32[4, 1024, 4096])", + "text":"Skipped for fx.Node(aten.view.default)[call_function]:Tensor(f32[4, 1024, 4096]): Cannot find type promotion rule for op: aten.view.default" + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":1625 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0015", + "stacks":[] + }, + { + "message":{ + "markdown":"Type promotion not needed for gelu_21. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature _TypePromotionInterpreter.run_node\n- self: \n- node: fx.Node(aten.gelu.default)[call_function]:Tensor(f32[4, 1024, 4096])\nFound type promotion rule: ElementwiseTypePromotionRule('aten', 'gelu', [0], [], ELEMENTWISE_TYPE_PROMOTION_KIND.DEFAULT)\nArgument view_218 is not promoted. Already torch.float32.\nArgument tanh is not promoted. Not mentioned by type promotion rule.\n## Return values\nTensor(f32[4, 1024, 4096])", + "text":"Type promotion not needed for gelu_21. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":1625 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0015", + "stacks":[] + }, + { + "message":{ + "markdown":"Skipped for fx.Node(aten.clone.default)[call_function]:Tensor(f32[4, 1024, 4096]): Cannot find type promotion rule for op: aten.clone.default\n\n## Additional Message:\n\n## Function Signature\n### Function Signature _TypePromotionInterpreter.run_node\n- self: \n- node: fx.Node(aten.clone.default)[call_function]:Tensor(f32[4, 1024, 4096])\n## Return values\nTensor(f32[4, 1024, 4096])", + "text":"Skipped for fx.Node(aten.clone.default)[call_function]:Tensor(f32[4, 1024, 4096]): Cannot find type promotion rule for op: aten.clone.default" + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":1625 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0015", + "stacks":[] + }, + { + "message":{ + "markdown":"Skipped for fx.Node(aten.view.default)[call_function]:Tensor(f32[4096, 4096]): Cannot find type promotion rule for op: aten.view.default\n\n## Additional Message:\n\n## Function Signature\n### Function Signature _TypePromotionInterpreter.run_node\n- self: \n- node: fx.Node(aten.view.default)[call_function]:Tensor(f32[4096, 4096])\n## Return values\nTensor(f32[4096, 4096])", + "text":"Skipped for fx.Node(aten.view.default)[call_function]:Tensor(f32[4096, 4096]): Cannot find type promotion rule for op: aten.view.default" + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":1625 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0015", + "stacks":[] + }, + { + "message":{ + "markdown":"Skipped for fx.Node(aten.t.default)[call_function]:Tensor(f32[4096, 1024]): Cannot find type promotion rule for op: aten.t.default\n\n## Additional Message:\n\n## Function Signature\n### Function Signature _TypePromotionInterpreter.run_node\n- self: \n- node: fx.Node(aten.t.default)[call_function]:Tensor(f32[4096, 1024])\n## Return values\nTensor(f32[4096, 1024])", + "text":"Skipped for fx.Node(aten.t.default)[call_function]:Tensor(f32[4096, 1024]): Cannot find type promotion rule for op: aten.t.default" + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":1625 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0015", + "stacks":[] + }, + { + "message":{ + "markdown":"Skipped for fx.Node(aten.addmm.default)[call_function]:Tensor(f32[4096, 1024]): Cannot find type promotion rule for op: aten.addmm.default\n\n## Additional Message:\n\n## Function Signature\n### Function Signature _TypePromotionInterpreter.run_node\n- self: \n- node: fx.Node(aten.addmm.default)[call_function]:Tensor(f32[4096, 1024])\n## Return values\nTensor(f32[4096, 1024])", + "text":"Skipped for fx.Node(aten.addmm.default)[call_function]:Tensor(f32[4096, 1024]): Cannot find type promotion rule for op: aten.addmm.default" + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":1625 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0015", + "stacks":[] + }, + { + "message":{ + "markdown":"Skipped for fx.Node(aten.view.default)[call_function]:Tensor(f32[4, 1024, 1024]): Cannot find type promotion rule for op: aten.view.default\n\n## Additional Message:\n\n## Function Signature\n### Function Signature _TypePromotionInterpreter.run_node\n- self: \n- node: fx.Node(aten.view.default)[call_function]:Tensor(f32[4, 1024, 1024])\n## Return values\nTensor(f32[4, 1024, 1024])", + "text":"Skipped for fx.Node(aten.view.default)[call_function]:Tensor(f32[4, 1024, 1024]): Cannot find type promotion rule for op: aten.view.default" + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":1625 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0015", + "stacks":[] + }, + { + "message":{ + "markdown":"Skipped for fx.Node(aten.clone.default)[call_function]:Tensor(f32[4, 1024, 1024]): Cannot find type promotion rule for op: aten.clone.default\n\n## Additional Message:\n\n## Function Signature\n### Function Signature _TypePromotionInterpreter.run_node\n- self: \n- node: fx.Node(aten.clone.default)[call_function]:Tensor(f32[4, 1024, 1024])\n## Return values\nTensor(f32[4, 1024, 1024])", + "text":"Skipped for fx.Node(aten.clone.default)[call_function]:Tensor(f32[4, 1024, 1024]): Cannot find type promotion rule for op: aten.clone.default" + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":1625 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0015", + "stacks":[] + }, + { + "message":{ + "markdown":"Type promotion not needed for add_44. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature _TypePromotionInterpreter.run_node\n- self: \n- node: fx.Node(aten.add.Tensor)[call_function]:Tensor(f32[4, 1024, 1024])\nFound type promotion rule: ElementwiseTypePromotionRule('aten', 'add', [0, 1], [], ELEMENTWISE_TYPE_PROMOTION_KIND.DEFAULT)\nArgument add_43 is not promoted. Already torch.float32.\nArgument clone_66 is not promoted. Already torch.float32.\n## Return values\nTensor(f32[4, 1024, 1024])", + "text":"Type promotion not needed for add_44. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":1625 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0015", + "stacks":[] + }, + { + "message":{ + "markdown":"Skipped for fx.Node(aten.native_layer_norm.default)[call_function]:Tuple[length=3](\nTensor(f32[4, 1024, 1024]),\nTensor(f32[4, 1024, 1]),\nTensor(f32[4, 1024, 1]),\n): Cannot find type promotion rule for op: aten.native_layer_norm.default\n\n## Additional Message:\n\n## Function Signature\n### Function Signature _TypePromotionInterpreter.run_node\n- self: \n- node: fx.Node(aten.native_layer_norm.default)[call_function]:Tuple[length=3](\nTensor(f32[4, 1024, 1024]),\nTensor(f32[4, 1024, 1]),\nTensor(f32[4, 1024, 1]),\n)\n## Return values\nTuple[length=3](\nTensor(f32[4, 1024, 1024]),\nTensor(f32[4, 1024, 1]),\nTensor(f32[4, 1024, 1]),\n)", + "text":"Skipped for fx.Node(aten.native_layer_norm.default)[call_function]:Tuple[length=3](\nTensor(f32[4, 1024, 1024]),\nTensor(f32[4, 1024, 1]),\nTensor(f32[4, 1024, 1]),\n): Cannot find type promotion rule for op: aten.native_layer_norm.default" + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":1625 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0015", + "stacks":[] + }, + { + "message":{ + "markdown":"Skipped for fx.Node()[call_function]:Tensor(f32[4, 1024, 1024]): node.target is not OpOverload. Got type: \n\n## Additional Message:\n\n## Function Signature\n### Function Signature _TypePromotionInterpreter.run_node\n- self: \n- node: fx.Node()[call_function]:Tensor(f32[4, 1024, 1024])\n## Return values\nTensor(f32[4, 1024, 1024])", + "text":"Skipped for fx.Node()[call_function]:Tensor(f32[4, 1024, 1024]): node.target is not OpOverload. Got type: " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":1625 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0015", + "stacks":[] + }, + { + "message":{ + "markdown":"Skipped for fx.Node(aten.view.default)[call_function]:Tensor(f32[4096, 1024]): Cannot find type promotion rule for op: aten.view.default\n\n## Additional Message:\n\n## Function Signature\n### Function Signature _TypePromotionInterpreter.run_node\n- self: \n- node: fx.Node(aten.view.default)[call_function]:Tensor(f32[4096, 1024])\n## Return values\nTensor(f32[4096, 1024])", + "text":"Skipped for fx.Node(aten.view.default)[call_function]:Tensor(f32[4096, 1024]): Cannot find type promotion rule for op: aten.view.default" + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":1625 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0015", + "stacks":[] + }, + { + "message":{ + "markdown":"Skipped for fx.Node(aten.t.default)[call_function]:Tensor(f32[1024, 3072]): Cannot find type promotion rule for op: aten.t.default\n\n## Additional Message:\n\n## Function Signature\n### Function Signature _TypePromotionInterpreter.run_node\n- self: \n- node: fx.Node(aten.t.default)[call_function]:Tensor(f32[1024, 3072])\n## Return values\nTensor(f32[1024, 3072])", + "text":"Skipped for fx.Node(aten.t.default)[call_function]:Tensor(f32[1024, 3072]): Cannot find type promotion rule for op: aten.t.default" + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":1625 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0015", + "stacks":[] + }, + { + "message":{ + "markdown":"Skipped for fx.Node(aten.addmm.default)[call_function]:Tensor(f32[4096, 3072]): Cannot find type promotion rule for op: aten.addmm.default\n\n## Additional Message:\n\n## Function Signature\n### Function Signature _TypePromotionInterpreter.run_node\n- self: \n- node: fx.Node(aten.addmm.default)[call_function]:Tensor(f32[4096, 3072])\n## Return values\nTensor(f32[4096, 3072])", + "text":"Skipped for fx.Node(aten.addmm.default)[call_function]:Tensor(f32[4096, 3072]): Cannot find type promotion rule for op: aten.addmm.default" + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":1625 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0015", + "stacks":[] + }, + { + "message":{ + "markdown":"Skipped for fx.Node(aten.view.default)[call_function]:Tensor(f32[4, 1024, 3072]): Cannot find type promotion rule for op: aten.view.default\n\n## Additional Message:\n\n## Function Signature\n### Function Signature _TypePromotionInterpreter.run_node\n- self: \n- node: fx.Node(aten.view.default)[call_function]:Tensor(f32[4, 1024, 3072])\n## Return values\nTensor(f32[4, 1024, 3072])", + "text":"Skipped for fx.Node(aten.view.default)[call_function]:Tensor(f32[4, 1024, 3072]): Cannot find type promotion rule for op: aten.view.default" + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":1625 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0015", + "stacks":[] + }, + { + "message":{ + "markdown":"Skipped for fx.Node(aten.view.default)[call_function]:Tensor(f32[4, 1024, 3, 16, 64]): Cannot find type promotion rule for op: aten.view.default\n\n## Additional Message:\n\n## Function Signature\n### Function Signature _TypePromotionInterpreter.run_node\n- self: \n- node: fx.Node(aten.view.default)[call_function]:Tensor(f32[4, 1024, 3, 16, 64])\n## Return values\nTensor(f32[4, 1024, 3, 16, 64])", + "text":"Skipped for fx.Node(aten.view.default)[call_function]:Tensor(f32[4, 1024, 3, 16, 64]): Cannot find type promotion rule for op: aten.view.default" + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":1625 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0015", + "stacks":[] + }, + { + "message":{ + "markdown":"Skipped for fx.Node(aten.permute.default)[call_function]:Tensor(f32[3, 4, 16, 1024, 64]): Cannot find type promotion rule for op: aten.permute.default\n\n## Additional Message:\n\n## Function Signature\n### Function Signature _TypePromotionInterpreter.run_node\n- self: \n- node: fx.Node(aten.permute.default)[call_function]:Tensor(f32[3, 4, 16, 1024, 64])\n## Return values\nTensor(f32[3, 4, 16, 1024, 64])", + "text":"Skipped for fx.Node(aten.permute.default)[call_function]:Tensor(f32[3, 4, 16, 1024, 64]): Cannot find type promotion rule for op: aten.permute.default" + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":1625 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0015", + "stacks":[] + }, + { + "message":{ + "markdown":"Skipped for fx.Node(aten.unbind.int)[call_function]:List[length=3](\nTensor(f32[4, 16, 1024, 64]),\nTensor(f32[4, 16, 1024, 64]),\nTensor(f32[4, 16, 1024, 64]),\n): Cannot find type promotion rule for op: aten.unbind.int\n\n## Additional Message:\n\n## Function Signature\n### Function Signature _TypePromotionInterpreter.run_node\n- self: \n- node: fx.Node(aten.unbind.int)[call_function]:List[length=3](\nTensor(f32[4, 16, 1024, 64]),\nTensor(f32[4, 16, 1024, 64]),\nTensor(f32[4, 16, 1024, 64]),\n)\n## Return values\nList[length=3](\nTensor(f32[4, 16, 1024, 64]),\nTensor(f32[4, 16, 1024, 64]),\nTensor(f32[4, 16, 1024, 64]),\n)", + "text":"Skipped for fx.Node(aten.unbind.int)[call_function]:List[length=3](\nTensor(f32[4, 16, 1024, 64]),\nTensor(f32[4, 16, 1024, 64]),\nTensor(f32[4, 16, 1024, 64]),\n): Cannot find type promotion rule for op: aten.unbind.int" + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":1625 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0015", + "stacks":[] + }, + { + "message":{ + "markdown":"Skipped for fx.Node()[call_function]:Tensor(f32[4, 16, 1024, 64]): node.target is not OpOverload. Got type: \n\n## Additional Message:\n\n## Function Signature\n### Function Signature _TypePromotionInterpreter.run_node\n- self: \n- node: fx.Node()[call_function]:Tensor(f32[4, 16, 1024, 64])\n## Return values\nTensor(f32[4, 16, 1024, 64])", + "text":"Skipped for fx.Node()[call_function]:Tensor(f32[4, 16, 1024, 64]): node.target is not OpOverload. Got type: " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":1625 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0015", + "stacks":[] + }, + { + "message":{ + "markdown":"Skipped for fx.Node()[call_function]:Tensor(f32[4, 16, 1024, 64]): node.target is not OpOverload. Got type: \n\n## Additional Message:\n\n## Function Signature\n### Function Signature _TypePromotionInterpreter.run_node\n- self: \n- node: fx.Node()[call_function]:Tensor(f32[4, 16, 1024, 64])\n## Return values\nTensor(f32[4, 16, 1024, 64])", + "text":"Skipped for fx.Node()[call_function]:Tensor(f32[4, 16, 1024, 64]): node.target is not OpOverload. Got type: " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":1625 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0015", + "stacks":[] + }, + { + "message":{ + "markdown":"Skipped for fx.Node()[call_function]:Tensor(f32[4, 16, 1024, 64]): node.target is not OpOverload. Got type: \n\n## Additional Message:\n\n## Function Signature\n### Function Signature _TypePromotionInterpreter.run_node\n- self: \n- node: fx.Node()[call_function]:Tensor(f32[4, 16, 1024, 64])\n## Return values\nTensor(f32[4, 16, 1024, 64])", + "text":"Skipped for fx.Node()[call_function]:Tensor(f32[4, 16, 1024, 64]): node.target is not OpOverload. Got type: " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":1625 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0015", + "stacks":[] + }, + { + "message":{ + "markdown":"Skipped for fx.Node(aten._scaled_dot_product_efficient_attention.default)[call_function]:Tuple[length=4](\nTensor(f32[4, 16, 1024, 64]),\nTensor(f32[4, 16, 0]),\nTensor(i64[]),\nTensor(i64[]),\n): Cannot find type promotion rule for op: aten._scaled_dot_product_efficient_attention.default\n\n## Additional Message:\n\n## Function Signature\n### Function Signature _TypePromotionInterpreter.run_node\n- self: \n- node: fx.Node(aten._scaled_dot_product_efficient_attention.default)[call_function]:Tuple[length=4](\nTensor(f32[4, 16, 1024, 64]),\nTensor(f32[4, 16, 0]),\nTensor(i64[]),\nTensor(i64[]),\n)\n## Return values\nTuple[length=4](\nTensor(f32[4, 16, 1024, 64]),\nTensor(f32[4, 16, 0]),\nTensor(i64[]),\nTensor(i64[]),\n)", + "text":"Skipped for fx.Node(aten._scaled_dot_product_efficient_attention.default)[call_function]:Tuple[length=4](\nTensor(f32[4, 16, 1024, 64]),\nTensor(f32[4, 16, 0]),\nTensor(i64[]),\nTensor(i64[]),\n): Cannot find type promotion rule for op: aten._scaled_dot_product_efficient_attention.default" + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":1625 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0015", + "stacks":[] + }, + { + "message":{ + "markdown":"Skipped for fx.Node()[call_function]:Tensor(f32[4, 16, 1024, 64]): node.target is not OpOverload. Got type: \n\n## Additional Message:\n\n## Function Signature\n### Function Signature _TypePromotionInterpreter.run_node\n- self: \n- node: fx.Node()[call_function]:Tensor(f32[4, 16, 1024, 64])\n## Return values\nTensor(f32[4, 16, 1024, 64])", + "text":"Skipped for fx.Node()[call_function]:Tensor(f32[4, 16, 1024, 64]): node.target is not OpOverload. Got type: " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":1625 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0015", + "stacks":[] + }, + { + "message":{ + "markdown":"Skipped for fx.Node(aten.transpose.int)[call_function]:Tensor(f32[4, 1024, 16, 64]): Cannot find type promotion rule for op: aten.transpose.int\n\n## Additional Message:\n\n## Function Signature\n### Function Signature _TypePromotionInterpreter.run_node\n- self: \n- node: fx.Node(aten.transpose.int)[call_function]:Tensor(f32[4, 1024, 16, 64])\n## Return values\nTensor(f32[4, 1024, 16, 64])", + "text":"Skipped for fx.Node(aten.transpose.int)[call_function]:Tensor(f32[4, 1024, 16, 64]): Cannot find type promotion rule for op: aten.transpose.int" + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":1625 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0015", + "stacks":[] + }, + { + "message":{ + "markdown":"Skipped for fx.Node(aten.view.default)[call_function]:Tensor(f32[4, 1024, 1024]): Cannot find type promotion rule for op: aten.view.default\n\n## Additional Message:\n\n## Function Signature\n### Function Signature _TypePromotionInterpreter.run_node\n- self: \n- node: fx.Node(aten.view.default)[call_function]:Tensor(f32[4, 1024, 1024])\n## Return values\nTensor(f32[4, 1024, 1024])", + "text":"Skipped for fx.Node(aten.view.default)[call_function]:Tensor(f32[4, 1024, 1024]): Cannot find type promotion rule for op: aten.view.default" + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":1625 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0015", + "stacks":[] + }, + { + "message":{ + "markdown":"Skipped for fx.Node(aten.view.default)[call_function]:Tensor(f32[4096, 1024]): Cannot find type promotion rule for op: aten.view.default\n\n## Additional Message:\n\n## Function Signature\n### Function Signature _TypePromotionInterpreter.run_node\n- self: \n- node: fx.Node(aten.view.default)[call_function]:Tensor(f32[4096, 1024])\n## Return values\nTensor(f32[4096, 1024])", + "text":"Skipped for fx.Node(aten.view.default)[call_function]:Tensor(f32[4096, 1024]): Cannot find type promotion rule for op: aten.view.default" + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":1625 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0015", + "stacks":[] + }, + { + "message":{ + "markdown":"Skipped for fx.Node(aten.t.default)[call_function]:Tensor(f32[1024, 1024]): Cannot find type promotion rule for op: aten.t.default\n\n## Additional Message:\n\n## Function Signature\n### Function Signature _TypePromotionInterpreter.run_node\n- self: \n- node: fx.Node(aten.t.default)[call_function]:Tensor(f32[1024, 1024])\n## Return values\nTensor(f32[1024, 1024])", + "text":"Skipped for fx.Node(aten.t.default)[call_function]:Tensor(f32[1024, 1024]): Cannot find type promotion rule for op: aten.t.default" + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":1625 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0015", + "stacks":[] + }, + { + "message":{ + "markdown":"Skipped for fx.Node(aten.addmm.default)[call_function]:Tensor(f32[4096, 1024]): Cannot find type promotion rule for op: aten.addmm.default\n\n## Additional Message:\n\n## Function Signature\n### Function Signature _TypePromotionInterpreter.run_node\n- self: \n- node: fx.Node(aten.addmm.default)[call_function]:Tensor(f32[4096, 1024])\n## Return values\nTensor(f32[4096, 1024])", + "text":"Skipped for fx.Node(aten.addmm.default)[call_function]:Tensor(f32[4096, 1024]): Cannot find type promotion rule for op: aten.addmm.default" + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":1625 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0015", + "stacks":[] + }, + { + "message":{ + "markdown":"Skipped for fx.Node(aten.view.default)[call_function]:Tensor(f32[4, 1024, 1024]): Cannot find type promotion rule for op: aten.view.default\n\n## Additional Message:\n\n## Function Signature\n### Function Signature _TypePromotionInterpreter.run_node\n- self: \n- node: fx.Node(aten.view.default)[call_function]:Tensor(f32[4, 1024, 1024])\n## Return values\nTensor(f32[4, 1024, 1024])", + "text":"Skipped for fx.Node(aten.view.default)[call_function]:Tensor(f32[4, 1024, 1024]): Cannot find type promotion rule for op: aten.view.default" + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":1625 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0015", + "stacks":[] + }, + { + "message":{ + "markdown":"Skipped for fx.Node(aten.clone.default)[call_function]:Tensor(f32[4, 1024, 1024]): Cannot find type promotion rule for op: aten.clone.default\n\n## Additional Message:\n\n## Function Signature\n### Function Signature _TypePromotionInterpreter.run_node\n- self: \n- node: fx.Node(aten.clone.default)[call_function]:Tensor(f32[4, 1024, 1024])\n## Return values\nTensor(f32[4, 1024, 1024])", + "text":"Skipped for fx.Node(aten.clone.default)[call_function]:Tensor(f32[4, 1024, 1024]): Cannot find type promotion rule for op: aten.clone.default" + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":1625 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0015", + "stacks":[] + }, + { + "message":{ + "markdown":"Type promotion not needed for add_45. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature _TypePromotionInterpreter.run_node\n- self: \n- node: fx.Node(aten.add.Tensor)[call_function]:Tensor(f32[4, 1024, 1024])\nFound type promotion rule: ElementwiseTypePromotionRule('aten', 'add', [0, 1], [], ELEMENTWISE_TYPE_PROMOTION_KIND.DEFAULT)\nArgument add_44 is not promoted. Already torch.float32.\nArgument clone_67 is not promoted. Already torch.float32.\n## Return values\nTensor(f32[4, 1024, 1024])", + "text":"Type promotion not needed for add_45. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":1625 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0015", + "stacks":[] + }, + { + "message":{ + "markdown":"Skipped for fx.Node(aten.native_layer_norm.default)[call_function]:Tuple[length=3](\nTensor(f32[4, 1024, 1024]),\nTensor(f32[4, 1024, 1]),\nTensor(f32[4, 1024, 1]),\n): Cannot find type promotion rule for op: aten.native_layer_norm.default\n\n## Additional Message:\n\n## Function Signature\n### Function Signature _TypePromotionInterpreter.run_node\n- self: \n- node: fx.Node(aten.native_layer_norm.default)[call_function]:Tuple[length=3](\nTensor(f32[4, 1024, 1024]),\nTensor(f32[4, 1024, 1]),\nTensor(f32[4, 1024, 1]),\n)\n## Return values\nTuple[length=3](\nTensor(f32[4, 1024, 1024]),\nTensor(f32[4, 1024, 1]),\nTensor(f32[4, 1024, 1]),\n)", + "text":"Skipped for fx.Node(aten.native_layer_norm.default)[call_function]:Tuple[length=3](\nTensor(f32[4, 1024, 1024]),\nTensor(f32[4, 1024, 1]),\nTensor(f32[4, 1024, 1]),\n): Cannot find type promotion rule for op: aten.native_layer_norm.default" + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":1625 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0015", + "stacks":[] + }, + { + "message":{ + "markdown":"Skipped for fx.Node()[call_function]:Tensor(f32[4, 1024, 1024]): node.target is not OpOverload. Got type: \n\n## Additional Message:\n\n## Function Signature\n### Function Signature _TypePromotionInterpreter.run_node\n- self: \n- node: fx.Node()[call_function]:Tensor(f32[4, 1024, 1024])\n## Return values\nTensor(f32[4, 1024, 1024])", + "text":"Skipped for fx.Node()[call_function]:Tensor(f32[4, 1024, 1024]): node.target is not OpOverload. Got type: " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":1625 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0015", + "stacks":[] + }, + { + "message":{ + "markdown":"Skipped for fx.Node(aten.view.default)[call_function]:Tensor(f32[4096, 1024]): Cannot find type promotion rule for op: aten.view.default\n\n## Additional Message:\n\n## Function Signature\n### Function Signature _TypePromotionInterpreter.run_node\n- self: \n- node: fx.Node(aten.view.default)[call_function]:Tensor(f32[4096, 1024])\n## Return values\nTensor(f32[4096, 1024])", + "text":"Skipped for fx.Node(aten.view.default)[call_function]:Tensor(f32[4096, 1024]): Cannot find type promotion rule for op: aten.view.default" + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":1625 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0015", + "stacks":[] + }, + { + "message":{ + "markdown":"Skipped for fx.Node(aten.t.default)[call_function]:Tensor(f32[1024, 4096]): Cannot find type promotion rule for op: aten.t.default\n\n## Additional Message:\n\n## Function Signature\n### Function Signature _TypePromotionInterpreter.run_node\n- self: \n- node: fx.Node(aten.t.default)[call_function]:Tensor(f32[1024, 4096])\n## Return values\nTensor(f32[1024, 4096])", + "text":"Skipped for fx.Node(aten.t.default)[call_function]:Tensor(f32[1024, 4096]): Cannot find type promotion rule for op: aten.t.default" + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":1625 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0015", + "stacks":[] + }, + { + "message":{ + "markdown":"Skipped for fx.Node(aten.addmm.default)[call_function]:Tensor(f32[4096, 4096]): Cannot find type promotion rule for op: aten.addmm.default\n\n## Additional Message:\n\n## Function Signature\n### Function Signature _TypePromotionInterpreter.run_node\n- self: \n- node: fx.Node(aten.addmm.default)[call_function]:Tensor(f32[4096, 4096])\n## Return values\nTensor(f32[4096, 4096])", + "text":"Skipped for fx.Node(aten.addmm.default)[call_function]:Tensor(f32[4096, 4096]): Cannot find type promotion rule for op: aten.addmm.default" + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":1625 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0015", + "stacks":[] + }, + { + "message":{ + "markdown":"Skipped for fx.Node(aten.view.default)[call_function]:Tensor(f32[4, 1024, 4096]): Cannot find type promotion rule for op: aten.view.default\n\n## Additional Message:\n\n## Function Signature\n### Function Signature _TypePromotionInterpreter.run_node\n- self: \n- node: fx.Node(aten.view.default)[call_function]:Tensor(f32[4, 1024, 4096])\n## Return values\nTensor(f32[4, 1024, 4096])", + "text":"Skipped for fx.Node(aten.view.default)[call_function]:Tensor(f32[4, 1024, 4096]): Cannot find type promotion rule for op: aten.view.default" + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":1625 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0015", + "stacks":[] + }, + { + "message":{ + "markdown":"Type promotion not needed for gelu_22. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature _TypePromotionInterpreter.run_node\n- self: \n- node: fx.Node(aten.gelu.default)[call_function]:Tensor(f32[4, 1024, 4096])\nFound type promotion rule: ElementwiseTypePromotionRule('aten', 'gelu', [0], [], ELEMENTWISE_TYPE_PROMOTION_KIND.DEFAULT)\nArgument view_228 is not promoted. Already torch.float32.\nArgument tanh is not promoted. Not mentioned by type promotion rule.\n## Return values\nTensor(f32[4, 1024, 4096])", + "text":"Type promotion not needed for gelu_22. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":1625 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0015", + "stacks":[] + }, + { + "message":{ + "markdown":"Skipped for fx.Node(aten.clone.default)[call_function]:Tensor(f32[4, 1024, 4096]): Cannot find type promotion rule for op: aten.clone.default\n\n## Additional Message:\n\n## Function Signature\n### Function Signature _TypePromotionInterpreter.run_node\n- self: \n- node: fx.Node(aten.clone.default)[call_function]:Tensor(f32[4, 1024, 4096])\n## Return values\nTensor(f32[4, 1024, 4096])", + "text":"Skipped for fx.Node(aten.clone.default)[call_function]:Tensor(f32[4, 1024, 4096]): Cannot find type promotion rule for op: aten.clone.default" + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":1625 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0015", + "stacks":[] + }, + { + "message":{ + "markdown":"Skipped for fx.Node(aten.view.default)[call_function]:Tensor(f32[4096, 4096]): Cannot find type promotion rule for op: aten.view.default\n\n## Additional Message:\n\n## Function Signature\n### Function Signature _TypePromotionInterpreter.run_node\n- self: \n- node: fx.Node(aten.view.default)[call_function]:Tensor(f32[4096, 4096])\n## Return values\nTensor(f32[4096, 4096])", + "text":"Skipped for fx.Node(aten.view.default)[call_function]:Tensor(f32[4096, 4096]): Cannot find type promotion rule for op: aten.view.default" + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":1625 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0015", + "stacks":[] + }, + { + "message":{ + "markdown":"Skipped for fx.Node(aten.t.default)[call_function]:Tensor(f32[4096, 1024]): Cannot find type promotion rule for op: aten.t.default\n\n## Additional Message:\n\n## Function Signature\n### Function Signature _TypePromotionInterpreter.run_node\n- self: \n- node: fx.Node(aten.t.default)[call_function]:Tensor(f32[4096, 1024])\n## Return values\nTensor(f32[4096, 1024])", + "text":"Skipped for fx.Node(aten.t.default)[call_function]:Tensor(f32[4096, 1024]): Cannot find type promotion rule for op: aten.t.default" + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":1625 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0015", + "stacks":[] + }, + { + "message":{ + "markdown":"Skipped for fx.Node(aten.addmm.default)[call_function]:Tensor(f32[4096, 1024]): Cannot find type promotion rule for op: aten.addmm.default\n\n## Additional Message:\n\n## Function Signature\n### Function Signature _TypePromotionInterpreter.run_node\n- self: \n- node: fx.Node(aten.addmm.default)[call_function]:Tensor(f32[4096, 1024])\n## Return values\nTensor(f32[4096, 1024])", + "text":"Skipped for fx.Node(aten.addmm.default)[call_function]:Tensor(f32[4096, 1024]): Cannot find type promotion rule for op: aten.addmm.default" + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":1625 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0015", + "stacks":[] + }, + { + "message":{ + "markdown":"Skipped for fx.Node(aten.view.default)[call_function]:Tensor(f32[4, 1024, 1024]): Cannot find type promotion rule for op: aten.view.default\n\n## Additional Message:\n\n## Function Signature\n### Function Signature _TypePromotionInterpreter.run_node\n- self: \n- node: fx.Node(aten.view.default)[call_function]:Tensor(f32[4, 1024, 1024])\n## Return values\nTensor(f32[4, 1024, 1024])", + "text":"Skipped for fx.Node(aten.view.default)[call_function]:Tensor(f32[4, 1024, 1024]): Cannot find type promotion rule for op: aten.view.default" + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":1625 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0015", + "stacks":[] + }, + { + "message":{ + "markdown":"Skipped for fx.Node(aten.clone.default)[call_function]:Tensor(f32[4, 1024, 1024]): Cannot find type promotion rule for op: aten.clone.default\n\n## Additional Message:\n\n## Function Signature\n### Function Signature _TypePromotionInterpreter.run_node\n- self: \n- node: fx.Node(aten.clone.default)[call_function]:Tensor(f32[4, 1024, 1024])\n## Return values\nTensor(f32[4, 1024, 1024])", + "text":"Skipped for fx.Node(aten.clone.default)[call_function]:Tensor(f32[4, 1024, 1024]): Cannot find type promotion rule for op: aten.clone.default" + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":1625 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0015", + "stacks":[] + }, + { + "message":{ + "markdown":"Type promotion not needed for add_46. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature _TypePromotionInterpreter.run_node\n- self: \n- node: fx.Node(aten.add.Tensor)[call_function]:Tensor(f32[4, 1024, 1024])\nFound type promotion rule: ElementwiseTypePromotionRule('aten', 'add', [0, 1], [], ELEMENTWISE_TYPE_PROMOTION_KIND.DEFAULT)\nArgument add_45 is not promoted. Already torch.float32.\nArgument clone_69 is not promoted. Already torch.float32.\n## Return values\nTensor(f32[4, 1024, 1024])", + "text":"Type promotion not needed for add_46. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":1625 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0015", + "stacks":[] + }, + { + "message":{ + "markdown":"Skipped for fx.Node(aten.native_layer_norm.default)[call_function]:Tuple[length=3](\nTensor(f32[4, 1024, 1024]),\nTensor(f32[4, 1024, 1]),\nTensor(f32[4, 1024, 1]),\n): Cannot find type promotion rule for op: aten.native_layer_norm.default\n\n## Additional Message:\n\n## Function Signature\n### Function Signature _TypePromotionInterpreter.run_node\n- self: \n- node: fx.Node(aten.native_layer_norm.default)[call_function]:Tuple[length=3](\nTensor(f32[4, 1024, 1024]),\nTensor(f32[4, 1024, 1]),\nTensor(f32[4, 1024, 1]),\n)\n## Return values\nTuple[length=3](\nTensor(f32[4, 1024, 1024]),\nTensor(f32[4, 1024, 1]),\nTensor(f32[4, 1024, 1]),\n)", + "text":"Skipped for fx.Node(aten.native_layer_norm.default)[call_function]:Tuple[length=3](\nTensor(f32[4, 1024, 1024]),\nTensor(f32[4, 1024, 1]),\nTensor(f32[4, 1024, 1]),\n): Cannot find type promotion rule for op: aten.native_layer_norm.default" + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":1625 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0015", + "stacks":[] + }, + { + "message":{ + "markdown":"Skipped for fx.Node()[call_function]:Tensor(f32[4, 1024, 1024]): node.target is not OpOverload. Got type: \n\n## Additional Message:\n\n## Function Signature\n### Function Signature _TypePromotionInterpreter.run_node\n- self: \n- node: fx.Node()[call_function]:Tensor(f32[4, 1024, 1024])\n## Return values\nTensor(f32[4, 1024, 1024])", + "text":"Skipped for fx.Node()[call_function]:Tensor(f32[4, 1024, 1024]): node.target is not OpOverload. Got type: " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":1625 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0015", + "stacks":[] + }, + { + "message":{ + "markdown":"Skipped for fx.Node(aten.view.default)[call_function]:Tensor(f32[4096, 1024]): Cannot find type promotion rule for op: aten.view.default\n\n## Additional Message:\n\n## Function Signature\n### Function Signature _TypePromotionInterpreter.run_node\n- self: \n- node: fx.Node(aten.view.default)[call_function]:Tensor(f32[4096, 1024])\n## Return values\nTensor(f32[4096, 1024])", + "text":"Skipped for fx.Node(aten.view.default)[call_function]:Tensor(f32[4096, 1024]): Cannot find type promotion rule for op: aten.view.default" + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":1625 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0015", + "stacks":[] + }, + { + "message":{ + "markdown":"Skipped for fx.Node(aten.t.default)[call_function]:Tensor(f32[1024, 3072]): Cannot find type promotion rule for op: aten.t.default\n\n## Additional Message:\n\n## Function Signature\n### Function Signature _TypePromotionInterpreter.run_node\n- self: \n- node: fx.Node(aten.t.default)[call_function]:Tensor(f32[1024, 3072])\n## Return values\nTensor(f32[1024, 3072])", + "text":"Skipped for fx.Node(aten.t.default)[call_function]:Tensor(f32[1024, 3072]): Cannot find type promotion rule for op: aten.t.default" + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":1625 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0015", + "stacks":[] + }, + { + "message":{ + "markdown":"Skipped for fx.Node(aten.addmm.default)[call_function]:Tensor(f32[4096, 3072]): Cannot find type promotion rule for op: aten.addmm.default\n\n## Additional Message:\n\n## Function Signature\n### Function Signature _TypePromotionInterpreter.run_node\n- self: \n- node: fx.Node(aten.addmm.default)[call_function]:Tensor(f32[4096, 3072])\n## Return values\nTensor(f32[4096, 3072])", + "text":"Skipped for fx.Node(aten.addmm.default)[call_function]:Tensor(f32[4096, 3072]): Cannot find type promotion rule for op: aten.addmm.default" + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":1625 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0015", + "stacks":[] + }, + { + "message":{ + "markdown":"Skipped for fx.Node(aten.view.default)[call_function]:Tensor(f32[4, 1024, 3072]): Cannot find type promotion rule for op: aten.view.default\n\n## Additional Message:\n\n## Function Signature\n### Function Signature _TypePromotionInterpreter.run_node\n- self: \n- node: fx.Node(aten.view.default)[call_function]:Tensor(f32[4, 1024, 3072])\n## Return values\nTensor(f32[4, 1024, 3072])", + "text":"Skipped for fx.Node(aten.view.default)[call_function]:Tensor(f32[4, 1024, 3072]): Cannot find type promotion rule for op: aten.view.default" + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":1625 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0015", + "stacks":[] + }, + { + "message":{ + "markdown":"Skipped for fx.Node(aten.view.default)[call_function]:Tensor(f32[4, 1024, 3, 16, 64]): Cannot find type promotion rule for op: aten.view.default\n\n## Additional Message:\n\n## Function Signature\n### Function Signature _TypePromotionInterpreter.run_node\n- self: \n- node: fx.Node(aten.view.default)[call_function]:Tensor(f32[4, 1024, 3, 16, 64])\n## Return values\nTensor(f32[4, 1024, 3, 16, 64])", + "text":"Skipped for fx.Node(aten.view.default)[call_function]:Tensor(f32[4, 1024, 3, 16, 64]): Cannot find type promotion rule for op: aten.view.default" + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":1625 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0015", + "stacks":[] + }, + { + "message":{ + "markdown":"Skipped for fx.Node(aten.permute.default)[call_function]:Tensor(f32[3, 4, 16, 1024, 64]): Cannot find type promotion rule for op: aten.permute.default\n\n## Additional Message:\n\n## Function Signature\n### Function Signature _TypePromotionInterpreter.run_node\n- self: \n- node: fx.Node(aten.permute.default)[call_function]:Tensor(f32[3, 4, 16, 1024, 64])\n## Return values\nTensor(f32[3, 4, 16, 1024, 64])", + "text":"Skipped for fx.Node(aten.permute.default)[call_function]:Tensor(f32[3, 4, 16, 1024, 64]): Cannot find type promotion rule for op: aten.permute.default" + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":1625 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0015", + "stacks":[] + }, + { + "message":{ + "markdown":"Skipped for fx.Node(aten.unbind.int)[call_function]:List[length=3](\nTensor(f32[4, 16, 1024, 64]),\nTensor(f32[4, 16, 1024, 64]),\nTensor(f32[4, 16, 1024, 64]),\n): Cannot find type promotion rule for op: aten.unbind.int\n\n## Additional Message:\n\n## Function Signature\n### Function Signature _TypePromotionInterpreter.run_node\n- self: \n- node: fx.Node(aten.unbind.int)[call_function]:List[length=3](\nTensor(f32[4, 16, 1024, 64]),\nTensor(f32[4, 16, 1024, 64]),\nTensor(f32[4, 16, 1024, 64]),\n)\n## Return values\nList[length=3](\nTensor(f32[4, 16, 1024, 64]),\nTensor(f32[4, 16, 1024, 64]),\nTensor(f32[4, 16, 1024, 64]),\n)", + "text":"Skipped for fx.Node(aten.unbind.int)[call_function]:List[length=3](\nTensor(f32[4, 16, 1024, 64]),\nTensor(f32[4, 16, 1024, 64]),\nTensor(f32[4, 16, 1024, 64]),\n): Cannot find type promotion rule for op: aten.unbind.int" + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":1625 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0015", + "stacks":[] + }, + { + "message":{ + "markdown":"Skipped for fx.Node()[call_function]:Tensor(f32[4, 16, 1024, 64]): node.target is not OpOverload. Got type: \n\n## Additional Message:\n\n## Function Signature\n### Function Signature _TypePromotionInterpreter.run_node\n- self: \n- node: fx.Node()[call_function]:Tensor(f32[4, 16, 1024, 64])\n## Return values\nTensor(f32[4, 16, 1024, 64])", + "text":"Skipped for fx.Node()[call_function]:Tensor(f32[4, 16, 1024, 64]): node.target is not OpOverload. Got type: " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":1625 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0015", + "stacks":[] + }, + { + "message":{ + "markdown":"Skipped for fx.Node()[call_function]:Tensor(f32[4, 16, 1024, 64]): node.target is not OpOverload. Got type: \n\n## Additional Message:\n\n## Function Signature\n### Function Signature _TypePromotionInterpreter.run_node\n- self: \n- node: fx.Node()[call_function]:Tensor(f32[4, 16, 1024, 64])\n## Return values\nTensor(f32[4, 16, 1024, 64])", + "text":"Skipped for fx.Node()[call_function]:Tensor(f32[4, 16, 1024, 64]): node.target is not OpOverload. Got type: " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":1625 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0015", + "stacks":[] + }, + { + "message":{ + "markdown":"Skipped for fx.Node()[call_function]:Tensor(f32[4, 16, 1024, 64]): node.target is not OpOverload. Got type: \n\n## Additional Message:\n\n## Function Signature\n### Function Signature _TypePromotionInterpreter.run_node\n- self: \n- node: fx.Node()[call_function]:Tensor(f32[4, 16, 1024, 64])\n## Return values\nTensor(f32[4, 16, 1024, 64])", + "text":"Skipped for fx.Node()[call_function]:Tensor(f32[4, 16, 1024, 64]): node.target is not OpOverload. Got type: " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":1625 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0015", + "stacks":[] + }, + { + "message":{ + "markdown":"Skipped for fx.Node(aten._scaled_dot_product_efficient_attention.default)[call_function]:Tuple[length=4](\nTensor(f32[4, 16, 1024, 64]),\nTensor(f32[4, 16, 0]),\nTensor(i64[]),\nTensor(i64[]),\n): Cannot find type promotion rule for op: aten._scaled_dot_product_efficient_attention.default\n\n## Additional Message:\n\n## Function Signature\n### Function Signature _TypePromotionInterpreter.run_node\n- self: \n- node: fx.Node(aten._scaled_dot_product_efficient_attention.default)[call_function]:Tuple[length=4](\nTensor(f32[4, 16, 1024, 64]),\nTensor(f32[4, 16, 0]),\nTensor(i64[]),\nTensor(i64[]),\n)\n## Return values\nTuple[length=4](\nTensor(f32[4, 16, 1024, 64]),\nTensor(f32[4, 16, 0]),\nTensor(i64[]),\nTensor(i64[]),\n)", + "text":"Skipped for fx.Node(aten._scaled_dot_product_efficient_attention.default)[call_function]:Tuple[length=4](\nTensor(f32[4, 16, 1024, 64]),\nTensor(f32[4, 16, 0]),\nTensor(i64[]),\nTensor(i64[]),\n): Cannot find type promotion rule for op: aten._scaled_dot_product_efficient_attention.default" + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":1625 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0015", + "stacks":[] + }, + { + "message":{ + "markdown":"Skipped for fx.Node()[call_function]:Tensor(f32[4, 16, 1024, 64]): node.target is not OpOverload. Got type: \n\n## Additional Message:\n\n## Function Signature\n### Function Signature _TypePromotionInterpreter.run_node\n- self: \n- node: fx.Node()[call_function]:Tensor(f32[4, 16, 1024, 64])\n## Return values\nTensor(f32[4, 16, 1024, 64])", + "text":"Skipped for fx.Node()[call_function]:Tensor(f32[4, 16, 1024, 64]): node.target is not OpOverload. Got type: " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":1625 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0015", + "stacks":[] + }, + { + "message":{ + "markdown":"Skipped for fx.Node(aten.transpose.int)[call_function]:Tensor(f32[4, 1024, 16, 64]): Cannot find type promotion rule for op: aten.transpose.int\n\n## Additional Message:\n\n## Function Signature\n### Function Signature _TypePromotionInterpreter.run_node\n- self: \n- node: fx.Node(aten.transpose.int)[call_function]:Tensor(f32[4, 1024, 16, 64])\n## Return values\nTensor(f32[4, 1024, 16, 64])", + "text":"Skipped for fx.Node(aten.transpose.int)[call_function]:Tensor(f32[4, 1024, 16, 64]): Cannot find type promotion rule for op: aten.transpose.int" + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":1625 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0015", + "stacks":[] + }, + { + "message":{ + "markdown":"Skipped for fx.Node(aten.view.default)[call_function]:Tensor(f32[4, 1024, 1024]): Cannot find type promotion rule for op: aten.view.default\n\n## Additional Message:\n\n## Function Signature\n### Function Signature _TypePromotionInterpreter.run_node\n- self: \n- node: fx.Node(aten.view.default)[call_function]:Tensor(f32[4, 1024, 1024])\n## Return values\nTensor(f32[4, 1024, 1024])", + "text":"Skipped for fx.Node(aten.view.default)[call_function]:Tensor(f32[4, 1024, 1024]): Cannot find type promotion rule for op: aten.view.default" + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":1625 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0015", + "stacks":[] + }, + { + "message":{ + "markdown":"Skipped for fx.Node(aten.view.default)[call_function]:Tensor(f32[4096, 1024]): Cannot find type promotion rule for op: aten.view.default\n\n## Additional Message:\n\n## Function Signature\n### Function Signature _TypePromotionInterpreter.run_node\n- self: \n- node: fx.Node(aten.view.default)[call_function]:Tensor(f32[4096, 1024])\n## Return values\nTensor(f32[4096, 1024])", + "text":"Skipped for fx.Node(aten.view.default)[call_function]:Tensor(f32[4096, 1024]): Cannot find type promotion rule for op: aten.view.default" + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":1625 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0015", + "stacks":[] + }, + { + "message":{ + "markdown":"Skipped for fx.Node(aten.t.default)[call_function]:Tensor(f32[1024, 1024]): Cannot find type promotion rule for op: aten.t.default\n\n## Additional Message:\n\n## Function Signature\n### Function Signature _TypePromotionInterpreter.run_node\n- self: \n- node: fx.Node(aten.t.default)[call_function]:Tensor(f32[1024, 1024])\n## Return values\nTensor(f32[1024, 1024])", + "text":"Skipped for fx.Node(aten.t.default)[call_function]:Tensor(f32[1024, 1024]): Cannot find type promotion rule for op: aten.t.default" + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":1625 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0015", + "stacks":[] + }, + { + "message":{ + "markdown":"Skipped for fx.Node(aten.addmm.default)[call_function]:Tensor(f32[4096, 1024]): Cannot find type promotion rule for op: aten.addmm.default\n\n## Additional Message:\n\n## Function Signature\n### Function Signature _TypePromotionInterpreter.run_node\n- self: \n- node: fx.Node(aten.addmm.default)[call_function]:Tensor(f32[4096, 1024])\n## Return values\nTensor(f32[4096, 1024])", + "text":"Skipped for fx.Node(aten.addmm.default)[call_function]:Tensor(f32[4096, 1024]): Cannot find type promotion rule for op: aten.addmm.default" + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":1625 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0015", + "stacks":[] + }, + { + "message":{ + "markdown":"Skipped for fx.Node(aten.view.default)[call_function]:Tensor(f32[4, 1024, 1024]): Cannot find type promotion rule for op: aten.view.default\n\n## Additional Message:\n\n## Function Signature\n### Function Signature _TypePromotionInterpreter.run_node\n- self: \n- node: fx.Node(aten.view.default)[call_function]:Tensor(f32[4, 1024, 1024])\n## Return values\nTensor(f32[4, 1024, 1024])", + "text":"Skipped for fx.Node(aten.view.default)[call_function]:Tensor(f32[4, 1024, 1024]): Cannot find type promotion rule for op: aten.view.default" + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":1625 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0015", + "stacks":[] + }, + { + "message":{ + "markdown":"Skipped for fx.Node(aten.clone.default)[call_function]:Tensor(f32[4, 1024, 1024]): Cannot find type promotion rule for op: aten.clone.default\n\n## Additional Message:\n\n## Function Signature\n### Function Signature _TypePromotionInterpreter.run_node\n- self: \n- node: fx.Node(aten.clone.default)[call_function]:Tensor(f32[4, 1024, 1024])\n## Return values\nTensor(f32[4, 1024, 1024])", + "text":"Skipped for fx.Node(aten.clone.default)[call_function]:Tensor(f32[4, 1024, 1024]): Cannot find type promotion rule for op: aten.clone.default" + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":1625 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0015", + "stacks":[] + }, + { + "message":{ + "markdown":"Type promotion not needed for add_47. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature _TypePromotionInterpreter.run_node\n- self: \n- node: fx.Node(aten.add.Tensor)[call_function]:Tensor(f32[4, 1024, 1024])\nFound type promotion rule: ElementwiseTypePromotionRule('aten', 'add', [0, 1], [], ELEMENTWISE_TYPE_PROMOTION_KIND.DEFAULT)\nArgument add_46 is not promoted. Already torch.float32.\nArgument clone_70 is not promoted. Already torch.float32.\n## Return values\nTensor(f32[4, 1024, 1024])", + "text":"Type promotion not needed for add_47. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":1625 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0015", + "stacks":[] + }, + { + "message":{ + "markdown":"Skipped for fx.Node(aten.native_layer_norm.default)[call_function]:Tuple[length=3](\nTensor(f32[4, 1024, 1024]),\nTensor(f32[4, 1024, 1]),\nTensor(f32[4, 1024, 1]),\n): Cannot find type promotion rule for op: aten.native_layer_norm.default\n\n## Additional Message:\n\n## Function Signature\n### Function Signature _TypePromotionInterpreter.run_node\n- self: \n- node: fx.Node(aten.native_layer_norm.default)[call_function]:Tuple[length=3](\nTensor(f32[4, 1024, 1024]),\nTensor(f32[4, 1024, 1]),\nTensor(f32[4, 1024, 1]),\n)\n## Return values\nTuple[length=3](\nTensor(f32[4, 1024, 1024]),\nTensor(f32[4, 1024, 1]),\nTensor(f32[4, 1024, 1]),\n)", + "text":"Skipped for fx.Node(aten.native_layer_norm.default)[call_function]:Tuple[length=3](\nTensor(f32[4, 1024, 1024]),\nTensor(f32[4, 1024, 1]),\nTensor(f32[4, 1024, 1]),\n): Cannot find type promotion rule for op: aten.native_layer_norm.default" + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":1625 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0015", + "stacks":[] + }, + { + "message":{ + "markdown":"Skipped for fx.Node()[call_function]:Tensor(f32[4, 1024, 1024]): node.target is not OpOverload. Got type: \n\n## Additional Message:\n\n## Function Signature\n### Function Signature _TypePromotionInterpreter.run_node\n- self: \n- node: fx.Node()[call_function]:Tensor(f32[4, 1024, 1024])\n## Return values\nTensor(f32[4, 1024, 1024])", + "text":"Skipped for fx.Node()[call_function]:Tensor(f32[4, 1024, 1024]): node.target is not OpOverload. Got type: " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":1625 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0015", + "stacks":[] + }, + { + "message":{ + "markdown":"Skipped for fx.Node(aten.view.default)[call_function]:Tensor(f32[4096, 1024]): Cannot find type promotion rule for op: aten.view.default\n\n## Additional Message:\n\n## Function Signature\n### Function Signature _TypePromotionInterpreter.run_node\n- self: \n- node: fx.Node(aten.view.default)[call_function]:Tensor(f32[4096, 1024])\n## Return values\nTensor(f32[4096, 1024])", + "text":"Skipped for fx.Node(aten.view.default)[call_function]:Tensor(f32[4096, 1024]): Cannot find type promotion rule for op: aten.view.default" + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":1625 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0015", + "stacks":[] + }, + { + "message":{ + "markdown":"Skipped for fx.Node(aten.t.default)[call_function]:Tensor(f32[1024, 4096]): Cannot find type promotion rule for op: aten.t.default\n\n## Additional Message:\n\n## Function Signature\n### Function Signature _TypePromotionInterpreter.run_node\n- self: \n- node: fx.Node(aten.t.default)[call_function]:Tensor(f32[1024, 4096])\n## Return values\nTensor(f32[1024, 4096])", + "text":"Skipped for fx.Node(aten.t.default)[call_function]:Tensor(f32[1024, 4096]): Cannot find type promotion rule for op: aten.t.default" + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":1625 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0015", + "stacks":[] + }, + { + "message":{ + "markdown":"Skipped for fx.Node(aten.addmm.default)[call_function]:Tensor(f32[4096, 4096]): Cannot find type promotion rule for op: aten.addmm.default\n\n## Additional Message:\n\n## Function Signature\n### Function Signature _TypePromotionInterpreter.run_node\n- self: \n- node: fx.Node(aten.addmm.default)[call_function]:Tensor(f32[4096, 4096])\n## Return values\nTensor(f32[4096, 4096])", + "text":"Skipped for fx.Node(aten.addmm.default)[call_function]:Tensor(f32[4096, 4096]): Cannot find type promotion rule for op: aten.addmm.default" + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":1625 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0015", + "stacks":[] + }, + { + "message":{ + "markdown":"Skipped for fx.Node(aten.view.default)[call_function]:Tensor(f32[4, 1024, 4096]): Cannot find type promotion rule for op: aten.view.default\n\n## Additional Message:\n\n## Function Signature\n### Function Signature _TypePromotionInterpreter.run_node\n- self: \n- node: fx.Node(aten.view.default)[call_function]:Tensor(f32[4, 1024, 4096])\n## Return values\nTensor(f32[4, 1024, 4096])", + "text":"Skipped for fx.Node(aten.view.default)[call_function]:Tensor(f32[4, 1024, 4096]): Cannot find type promotion rule for op: aten.view.default" + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":1625 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0015", + "stacks":[] + }, + { + "message":{ + "markdown":"Type promotion not needed for gelu_23. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature _TypePromotionInterpreter.run_node\n- self: \n- node: fx.Node(aten.gelu.default)[call_function]:Tensor(f32[4, 1024, 4096])\nFound type promotion rule: ElementwiseTypePromotionRule('aten', 'gelu', [0], [], ELEMENTWISE_TYPE_PROMOTION_KIND.DEFAULT)\nArgument view_238 is not promoted. Already torch.float32.\nArgument tanh is not promoted. Not mentioned by type promotion rule.\n## Return values\nTensor(f32[4, 1024, 4096])", + "text":"Type promotion not needed for gelu_23. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":1625 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0015", + "stacks":[] + }, + { + "message":{ + "markdown":"Skipped for fx.Node(aten.clone.default)[call_function]:Tensor(f32[4, 1024, 4096]): Cannot find type promotion rule for op: aten.clone.default\n\n## Additional Message:\n\n## Function Signature\n### Function Signature _TypePromotionInterpreter.run_node\n- self: \n- node: fx.Node(aten.clone.default)[call_function]:Tensor(f32[4, 1024, 4096])\n## Return values\nTensor(f32[4, 1024, 4096])", + "text":"Skipped for fx.Node(aten.clone.default)[call_function]:Tensor(f32[4, 1024, 4096]): Cannot find type promotion rule for op: aten.clone.default" + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":1625 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0015", + "stacks":[] + }, + { + "message":{ + "markdown":"Skipped for fx.Node(aten.view.default)[call_function]:Tensor(f32[4096, 4096]): Cannot find type promotion rule for op: aten.view.default\n\n## Additional Message:\n\n## Function Signature\n### Function Signature _TypePromotionInterpreter.run_node\n- self: \n- node: fx.Node(aten.view.default)[call_function]:Tensor(f32[4096, 4096])\n## Return values\nTensor(f32[4096, 4096])", + "text":"Skipped for fx.Node(aten.view.default)[call_function]:Tensor(f32[4096, 4096]): Cannot find type promotion rule for op: aten.view.default" + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":1625 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0015", + "stacks":[] + }, + { + "message":{ + "markdown":"Skipped for fx.Node(aten.t.default)[call_function]:Tensor(f32[4096, 1024]): Cannot find type promotion rule for op: aten.t.default\n\n## Additional Message:\n\n## Function Signature\n### Function Signature _TypePromotionInterpreter.run_node\n- self: \n- node: fx.Node(aten.t.default)[call_function]:Tensor(f32[4096, 1024])\n## Return values\nTensor(f32[4096, 1024])", + "text":"Skipped for fx.Node(aten.t.default)[call_function]:Tensor(f32[4096, 1024]): Cannot find type promotion rule for op: aten.t.default" + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":1625 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0015", + "stacks":[] + }, + { + "message":{ + "markdown":"Skipped for fx.Node(aten.addmm.default)[call_function]:Tensor(f32[4096, 1024]): Cannot find type promotion rule for op: aten.addmm.default\n\n## Additional Message:\n\n## Function Signature\n### Function Signature _TypePromotionInterpreter.run_node\n- self: \n- node: fx.Node(aten.addmm.default)[call_function]:Tensor(f32[4096, 1024])\n## Return values\nTensor(f32[4096, 1024])", + "text":"Skipped for fx.Node(aten.addmm.default)[call_function]:Tensor(f32[4096, 1024]): Cannot find type promotion rule for op: aten.addmm.default" + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":1625 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0015", + "stacks":[] + }, + { + "message":{ + "markdown":"Skipped for fx.Node(aten.view.default)[call_function]:Tensor(f32[4, 1024, 1024]): Cannot find type promotion rule for op: aten.view.default\n\n## Additional Message:\n\n## Function Signature\n### Function Signature _TypePromotionInterpreter.run_node\n- self: \n- node: fx.Node(aten.view.default)[call_function]:Tensor(f32[4, 1024, 1024])\n## Return values\nTensor(f32[4, 1024, 1024])", + "text":"Skipped for fx.Node(aten.view.default)[call_function]:Tensor(f32[4, 1024, 1024]): Cannot find type promotion rule for op: aten.view.default" + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":1625 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0015", + "stacks":[] + }, + { + "message":{ + "markdown":"Skipped for fx.Node(aten.clone.default)[call_function]:Tensor(f32[4, 1024, 1024]): Cannot find type promotion rule for op: aten.clone.default\n\n## Additional Message:\n\n## Function Signature\n### Function Signature _TypePromotionInterpreter.run_node\n- self: \n- node: fx.Node(aten.clone.default)[call_function]:Tensor(f32[4, 1024, 1024])\n## Return values\nTensor(f32[4, 1024, 1024])", + "text":"Skipped for fx.Node(aten.clone.default)[call_function]:Tensor(f32[4, 1024, 1024]): Cannot find type promotion rule for op: aten.clone.default" + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":1625 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0015", + "stacks":[] + }, + { + "message":{ + "markdown":"Type promotion not needed for add_48. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature _TypePromotionInterpreter.run_node\n- self: \n- node: fx.Node(aten.add.Tensor)[call_function]:Tensor(f32[4, 1024, 1024])\nFound type promotion rule: ElementwiseTypePromotionRule('aten', 'add', [0, 1], [], ELEMENTWISE_TYPE_PROMOTION_KIND.DEFAULT)\nArgument add_47 is not promoted. Already torch.float32.\nArgument clone_72 is not promoted. Already torch.float32.\n## Return values\nTensor(f32[4, 1024, 1024])", + "text":"Type promotion not needed for add_48. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":1625 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0015", + "stacks":[] + }, + { + "message":{ + "markdown":"Skipped for fx.Node(aten.native_layer_norm.default)[call_function]:Tuple[length=3](\nTensor(f32[4, 1024, 1024]),\nTensor(f32[4, 1024, 1]),\nTensor(f32[4, 1024, 1]),\n): Cannot find type promotion rule for op: aten.native_layer_norm.default\n\n## Additional Message:\n\n## Function Signature\n### Function Signature _TypePromotionInterpreter.run_node\n- self: \n- node: fx.Node(aten.native_layer_norm.default)[call_function]:Tuple[length=3](\nTensor(f32[4, 1024, 1024]),\nTensor(f32[4, 1024, 1]),\nTensor(f32[4, 1024, 1]),\n)\n## Return values\nTuple[length=3](\nTensor(f32[4, 1024, 1024]),\nTensor(f32[4, 1024, 1]),\nTensor(f32[4, 1024, 1]),\n)", + "text":"Skipped for fx.Node(aten.native_layer_norm.default)[call_function]:Tuple[length=3](\nTensor(f32[4, 1024, 1024]),\nTensor(f32[4, 1024, 1]),\nTensor(f32[4, 1024, 1]),\n): Cannot find type promotion rule for op: aten.native_layer_norm.default" + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":1625 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0015", + "stacks":[] + }, + { + "message":{ + "markdown":"Skipped for fx.Node()[call_function]:Tensor(f32[4, 1024, 1024]): node.target is not OpOverload. Got type: \n\n## Additional Message:\n\n## Function Signature\n### Function Signature _TypePromotionInterpreter.run_node\n- self: \n- node: fx.Node()[call_function]:Tensor(f32[4, 1024, 1024])\n## Return values\nTensor(f32[4, 1024, 1024])", + "text":"Skipped for fx.Node()[call_function]:Tensor(f32[4, 1024, 1024]): node.target is not OpOverload. Got type: " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":1625 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0015", + "stacks":[] + }, + { + "message":{ + "markdown":"Skipped for fx.Node(aten.expand.default)[call_function]:Tensor(f32[4, 1, 1024]): Cannot find type promotion rule for op: aten.expand.default\n\n## Additional Message:\n\n## Function Signature\n### Function Signature _TypePromotionInterpreter.run_node\n- self: \n- node: fx.Node(aten.expand.default)[call_function]:Tensor(f32[4, 1, 1024])\n## Return values\nTensor(f32[4, 1, 1024])", + "text":"Skipped for fx.Node(aten.expand.default)[call_function]:Tensor(f32[4, 1, 1024]): Cannot find type promotion rule for op: aten.expand.default" + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":1625 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0015", + "stacks":[] + }, + { + "message":{ + "markdown":"Skipped for fx.Node(aten.t.default)[call_function]:Tensor(f32[1024, 1024]): Cannot find type promotion rule for op: aten.t.default\n\n## Additional Message:\n\n## Function Signature\n### Function Signature _TypePromotionInterpreter.run_node\n- self: \n- node: fx.Node(aten.t.default)[call_function]:Tensor(f32[1024, 1024])\n## Return values\nTensor(f32[1024, 1024])", + "text":"Skipped for fx.Node(aten.t.default)[call_function]:Tensor(f32[1024, 1024]): Cannot find type promotion rule for op: aten.t.default" + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":1625 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0015", + "stacks":[] + }, + { + "message":{ + "markdown":"Skipped for fx.Node(aten.view.default)[call_function]:Tensor(f32[4, 1024]): Cannot find type promotion rule for op: aten.view.default\n\n## Additional Message:\n\n## Function Signature\n### Function Signature _TypePromotionInterpreter.run_node\n- self: \n- node: fx.Node(aten.view.default)[call_function]:Tensor(f32[4, 1024])\n## Return values\nTensor(f32[4, 1024])", + "text":"Skipped for fx.Node(aten.view.default)[call_function]:Tensor(f32[4, 1024]): Cannot find type promotion rule for op: aten.view.default" + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":1625 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0015", + "stacks":[] + }, + { + "message":{ + "markdown":"Skipped for fx.Node(aten.mm.default)[call_function]:Tensor(f32[4, 1024]): Cannot find type promotion rule for op: aten.mm.default\n\n## Additional Message:\n\n## Function Signature\n### Function Signature _TypePromotionInterpreter.run_node\n- self: \n- node: fx.Node(aten.mm.default)[call_function]:Tensor(f32[4, 1024])\n## Return values\nTensor(f32[4, 1024])", + "text":"Skipped for fx.Node(aten.mm.default)[call_function]:Tensor(f32[4, 1024]): Cannot find type promotion rule for op: aten.mm.default" + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":1625 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0015", + "stacks":[] + }, + { + "message":{ + "markdown":"Skipped for fx.Node(aten.view.default)[call_function]:Tensor(f32[4, 1, 1024]): Cannot find type promotion rule for op: aten.view.default\n\n## Additional Message:\n\n## Function Signature\n### Function Signature _TypePromotionInterpreter.run_node\n- self: \n- node: fx.Node(aten.view.default)[call_function]:Tensor(f32[4, 1, 1024])\n## Return values\nTensor(f32[4, 1, 1024])", + "text":"Skipped for fx.Node(aten.view.default)[call_function]:Tensor(f32[4, 1, 1024]): Cannot find type promotion rule for op: aten.view.default" + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":1625 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0015", + "stacks":[] + }, + { + "message":{ + "markdown":"Type promotion not needed for add_49. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature _TypePromotionInterpreter.run_node\n- self: \n- node: fx.Node(aten.add.Tensor)[call_function]:Tensor(f32[4, 1, 1024])\nFound type promotion rule: ElementwiseTypePromotionRule('aten', 'add', [0, 1], [], ELEMENTWISE_TYPE_PROMOTION_KIND.DEFAULT)\nArgument view_242 is not promoted. Already torch.float32.\nArgument p_trunk_attn_pool_q_bias is not promoted. Already torch.float32.\n## Return values\nTensor(f32[4, 1, 1024])", + "text":"Type promotion not needed for add_49. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":1625 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0015", + "stacks":[] + }, + { + "message":{ + "markdown":"Skipped for fx.Node(aten.view.default)[call_function]:Tensor(f32[4, 1, 16, 64]): Cannot find type promotion rule for op: aten.view.default\n\n## Additional Message:\n\n## Function Signature\n### Function Signature _TypePromotionInterpreter.run_node\n- self: \n- node: fx.Node(aten.view.default)[call_function]:Tensor(f32[4, 1, 16, 64])\n## Return values\nTensor(f32[4, 1, 16, 64])", + "text":"Skipped for fx.Node(aten.view.default)[call_function]:Tensor(f32[4, 1, 16, 64]): Cannot find type promotion rule for op: aten.view.default" + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":1625 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0015", + "stacks":[] + }, + { + "message":{ + "markdown":"Skipped for fx.Node(aten.transpose.int)[call_function]:Tensor(f32[4, 16, 1, 64]): Cannot find type promotion rule for op: aten.transpose.int\n\n## Additional Message:\n\n## Function Signature\n### Function Signature _TypePromotionInterpreter.run_node\n- self: \n- node: fx.Node(aten.transpose.int)[call_function]:Tensor(f32[4, 16, 1, 64])\n## Return values\nTensor(f32[4, 16, 1, 64])", + "text":"Skipped for fx.Node(aten.transpose.int)[call_function]:Tensor(f32[4, 16, 1, 64]): Cannot find type promotion rule for op: aten.transpose.int" + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":1625 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0015", + "stacks":[] + }, + { + "message":{ + "markdown":"Skipped for fx.Node(aten.view.default)[call_function]:Tensor(f32[4096, 1024]): Cannot find type promotion rule for op: aten.view.default\n\n## Additional Message:\n\n## Function Signature\n### Function Signature _TypePromotionInterpreter.run_node\n- self: \n- node: fx.Node(aten.view.default)[call_function]:Tensor(f32[4096, 1024])\n## Return values\nTensor(f32[4096, 1024])", + "text":"Skipped for fx.Node(aten.view.default)[call_function]:Tensor(f32[4096, 1024]): Cannot find type promotion rule for op: aten.view.default" + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":1625 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0015", + "stacks":[] + }, + { + "message":{ + "markdown":"Skipped for fx.Node(aten.t.default)[call_function]:Tensor(f32[1024, 2048]): Cannot find type promotion rule for op: aten.t.default\n\n## Additional Message:\n\n## Function Signature\n### Function Signature _TypePromotionInterpreter.run_node\n- self: \n- node: fx.Node(aten.t.default)[call_function]:Tensor(f32[1024, 2048])\n## Return values\nTensor(f32[1024, 2048])", + "text":"Skipped for fx.Node(aten.t.default)[call_function]:Tensor(f32[1024, 2048]): Cannot find type promotion rule for op: aten.t.default" + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":1625 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0015", + "stacks":[] + }, + { + "message":{ + "markdown":"Skipped for fx.Node(aten.addmm.default)[call_function]:Tensor(f32[4096, 2048]): Cannot find type promotion rule for op: aten.addmm.default\n\n## Additional Message:\n\n## Function Signature\n### Function Signature _TypePromotionInterpreter.run_node\n- self: \n- node: fx.Node(aten.addmm.default)[call_function]:Tensor(f32[4096, 2048])\n## Return values\nTensor(f32[4096, 2048])", + "text":"Skipped for fx.Node(aten.addmm.default)[call_function]:Tensor(f32[4096, 2048]): Cannot find type promotion rule for op: aten.addmm.default" + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":1625 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0015", + "stacks":[] + }, + { + "message":{ + "markdown":"Skipped for fx.Node(aten.view.default)[call_function]:Tensor(f32[4, 1024, 2048]): Cannot find type promotion rule for op: aten.view.default\n\n## Additional Message:\n\n## Function Signature\n### Function Signature _TypePromotionInterpreter.run_node\n- self: \n- node: fx.Node(aten.view.default)[call_function]:Tensor(f32[4, 1024, 2048])\n## Return values\nTensor(f32[4, 1024, 2048])", + "text":"Skipped for fx.Node(aten.view.default)[call_function]:Tensor(f32[4, 1024, 2048]): Cannot find type promotion rule for op: aten.view.default" + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":1625 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0015", + "stacks":[] + }, + { + "message":{ + "markdown":"Skipped for fx.Node(aten.view.default)[call_function]:Tensor(f32[4, 1024, 2, 16, 64]): Cannot find type promotion rule for op: aten.view.default\n\n## Additional Message:\n\n## Function Signature\n### Function Signature _TypePromotionInterpreter.run_node\n- self: \n- node: fx.Node(aten.view.default)[call_function]:Tensor(f32[4, 1024, 2, 16, 64])\n## Return values\nTensor(f32[4, 1024, 2, 16, 64])", + "text":"Skipped for fx.Node(aten.view.default)[call_function]:Tensor(f32[4, 1024, 2, 16, 64]): Cannot find type promotion rule for op: aten.view.default" + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":1625 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0015", + "stacks":[] + }, + { + "message":{ + "markdown":"Skipped for fx.Node(aten.permute.default)[call_function]:Tensor(f32[2, 4, 16, 1024, 64]): Cannot find type promotion rule for op: aten.permute.default\n\n## Additional Message:\n\n## Function Signature\n### Function Signature _TypePromotionInterpreter.run_node\n- self: \n- node: fx.Node(aten.permute.default)[call_function]:Tensor(f32[2, 4, 16, 1024, 64])\n## Return values\nTensor(f32[2, 4, 16, 1024, 64])", + "text":"Skipped for fx.Node(aten.permute.default)[call_function]:Tensor(f32[2, 4, 16, 1024, 64]): Cannot find type promotion rule for op: aten.permute.default" + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":1625 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0015", + "stacks":[] + }, + { + "message":{ + "markdown":"Skipped for fx.Node(aten.unbind.int)[call_function]:List[length=2](\nTensor(f32[4, 16, 1024, 64]),\nTensor(f32[4, 16, 1024, 64]),\n): Cannot find type promotion rule for op: aten.unbind.int\n\n## Additional Message:\n\n## Function Signature\n### Function Signature _TypePromotionInterpreter.run_node\n- self: \n- node: fx.Node(aten.unbind.int)[call_function]:List[length=2](\nTensor(f32[4, 16, 1024, 64]),\nTensor(f32[4, 16, 1024, 64]),\n)\n## Return values\nList[length=2](\nTensor(f32[4, 16, 1024, 64]),\nTensor(f32[4, 16, 1024, 64]),\n)", + "text":"Skipped for fx.Node(aten.unbind.int)[call_function]:List[length=2](\nTensor(f32[4, 16, 1024, 64]),\nTensor(f32[4, 16, 1024, 64]),\n): Cannot find type promotion rule for op: aten.unbind.int" + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":1625 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0015", + "stacks":[] + }, + { + "message":{ + "markdown":"Skipped for fx.Node()[call_function]:Tensor(f32[4, 16, 1024, 64]): node.target is not OpOverload. Got type: \n\n## Additional Message:\n\n## Function Signature\n### Function Signature _TypePromotionInterpreter.run_node\n- self: \n- node: fx.Node()[call_function]:Tensor(f32[4, 16, 1024, 64])\n## Return values\nTensor(f32[4, 16, 1024, 64])", + "text":"Skipped for fx.Node()[call_function]:Tensor(f32[4, 16, 1024, 64]): node.target is not OpOverload. Got type: " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":1625 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0015", + "stacks":[] + }, + { + "message":{ + "markdown":"Skipped for fx.Node()[call_function]:Tensor(f32[4, 16, 1024, 64]): node.target is not OpOverload. Got type: \n\n## Additional Message:\n\n## Function Signature\n### Function Signature _TypePromotionInterpreter.run_node\n- self: \n- node: fx.Node()[call_function]:Tensor(f32[4, 16, 1024, 64])\n## Return values\nTensor(f32[4, 16, 1024, 64])", + "text":"Skipped for fx.Node()[call_function]:Tensor(f32[4, 16, 1024, 64]): node.target is not OpOverload. Got type: " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":1625 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0015", + "stacks":[] + }, + { + "message":{ + "markdown":"Skipped for fx.Node(aten._scaled_dot_product_efficient_attention.default)[call_function]:Tuple[length=4](\nTensor(f32[4, 16, 1, 64]),\nTensor(f32[4, 16, 0]),\nTensor(i64[]),\nTensor(i64[]),\n): Cannot find type promotion rule for op: aten._scaled_dot_product_efficient_attention.default\n\n## Additional Message:\n\n## Function Signature\n### Function Signature _TypePromotionInterpreter.run_node\n- self: \n- node: fx.Node(aten._scaled_dot_product_efficient_attention.default)[call_function]:Tuple[length=4](\nTensor(f32[4, 16, 1, 64]),\nTensor(f32[4, 16, 0]),\nTensor(i64[]),\nTensor(i64[]),\n)\n## Return values\nTuple[length=4](\nTensor(f32[4, 16, 1, 64]),\nTensor(f32[4, 16, 0]),\nTensor(i64[]),\nTensor(i64[]),\n)", + "text":"Skipped for fx.Node(aten._scaled_dot_product_efficient_attention.default)[call_function]:Tuple[length=4](\nTensor(f32[4, 16, 1, 64]),\nTensor(f32[4, 16, 0]),\nTensor(i64[]),\nTensor(i64[]),\n): Cannot find type promotion rule for op: aten._scaled_dot_product_efficient_attention.default" + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":1625 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0015", + "stacks":[] + }, + { + "message":{ + "markdown":"Skipped for fx.Node()[call_function]:Tensor(f32[4, 16, 1, 64]): node.target is not OpOverload. Got type: \n\n## Additional Message:\n\n## Function Signature\n### Function Signature _TypePromotionInterpreter.run_node\n- self: \n- node: fx.Node()[call_function]:Tensor(f32[4, 16, 1, 64])\n## Return values\nTensor(f32[4, 16, 1, 64])", + "text":"Skipped for fx.Node()[call_function]:Tensor(f32[4, 16, 1, 64]): node.target is not OpOverload. Got type: " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":1625 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0015", + "stacks":[] + }, + { + "message":{ + "markdown":"Skipped for fx.Node(aten.transpose.int)[call_function]:Tensor(f32[4, 1, 16, 64]): Cannot find type promotion rule for op: aten.transpose.int\n\n## Additional Message:\n\n## Function Signature\n### Function Signature _TypePromotionInterpreter.run_node\n- self: \n- node: fx.Node(aten.transpose.int)[call_function]:Tensor(f32[4, 1, 16, 64])\n## Return values\nTensor(f32[4, 1, 16, 64])", + "text":"Skipped for fx.Node(aten.transpose.int)[call_function]:Tensor(f32[4, 1, 16, 64]): Cannot find type promotion rule for op: aten.transpose.int" + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":1625 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0015", + "stacks":[] + }, + { + "message":{ + "markdown":"Skipped for fx.Node(aten.view.default)[call_function]:Tensor(f32[4, 1, 1024]): Cannot find type promotion rule for op: aten.view.default\n\n## Additional Message:\n\n## Function Signature\n### Function Signature _TypePromotionInterpreter.run_node\n- self: \n- node: fx.Node(aten.view.default)[call_function]:Tensor(f32[4, 1, 1024])\n## Return values\nTensor(f32[4, 1, 1024])", + "text":"Skipped for fx.Node(aten.view.default)[call_function]:Tensor(f32[4, 1, 1024]): Cannot find type promotion rule for op: aten.view.default" + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":1625 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0015", + "stacks":[] + }, + { + "message":{ + "markdown":"Skipped for fx.Node(aten.view.default)[call_function]:Tensor(f32[4, 1024]): Cannot find type promotion rule for op: aten.view.default\n\n## Additional Message:\n\n## Function Signature\n### Function Signature _TypePromotionInterpreter.run_node\n- self: \n- node: fx.Node(aten.view.default)[call_function]:Tensor(f32[4, 1024])\n## Return values\nTensor(f32[4, 1024])", + "text":"Skipped for fx.Node(aten.view.default)[call_function]:Tensor(f32[4, 1024]): Cannot find type promotion rule for op: aten.view.default" + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":1625 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0015", + "stacks":[] + }, + { + "message":{ + "markdown":"Skipped for fx.Node(aten.t.default)[call_function]:Tensor(f32[1024, 1024]): Cannot find type promotion rule for op: aten.t.default\n\n## Additional Message:\n\n## Function Signature\n### Function Signature _TypePromotionInterpreter.run_node\n- self: \n- node: fx.Node(aten.t.default)[call_function]:Tensor(f32[1024, 1024])\n## Return values\nTensor(f32[1024, 1024])", + "text":"Skipped for fx.Node(aten.t.default)[call_function]:Tensor(f32[1024, 1024]): Cannot find type promotion rule for op: aten.t.default" + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":1625 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0015", + "stacks":[] + }, + { + "message":{ + "markdown":"Skipped for fx.Node(aten.addmm.default)[call_function]:Tensor(f32[4, 1024]): Cannot find type promotion rule for op: aten.addmm.default\n\n## Additional Message:\n\n## Function Signature\n### Function Signature _TypePromotionInterpreter.run_node\n- self: \n- node: fx.Node(aten.addmm.default)[call_function]:Tensor(f32[4, 1024])\n## Return values\nTensor(f32[4, 1024])", + "text":"Skipped for fx.Node(aten.addmm.default)[call_function]:Tensor(f32[4, 1024]): Cannot find type promotion rule for op: aten.addmm.default" + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":1625 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0015", + "stacks":[] + }, + { + "message":{ + "markdown":"Skipped for fx.Node(aten.view.default)[call_function]:Tensor(f32[4, 1, 1024]): Cannot find type promotion rule for op: aten.view.default\n\n## Additional Message:\n\n## Function Signature\n### Function Signature _TypePromotionInterpreter.run_node\n- self: \n- node: fx.Node(aten.view.default)[call_function]:Tensor(f32[4, 1, 1024])\n## Return values\nTensor(f32[4, 1, 1024])", + "text":"Skipped for fx.Node(aten.view.default)[call_function]:Tensor(f32[4, 1, 1024]): Cannot find type promotion rule for op: aten.view.default" + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":1625 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0015", + "stacks":[] + }, + { + "message":{ + "markdown":"Skipped for fx.Node(aten.clone.default)[call_function]:Tensor(f32[4, 1, 1024]): Cannot find type promotion rule for op: aten.clone.default\n\n## Additional Message:\n\n## Function Signature\n### Function Signature _TypePromotionInterpreter.run_node\n- self: \n- node: fx.Node(aten.clone.default)[call_function]:Tensor(f32[4, 1, 1024])\n## Return values\nTensor(f32[4, 1, 1024])", + "text":"Skipped for fx.Node(aten.clone.default)[call_function]:Tensor(f32[4, 1, 1024]): Cannot find type promotion rule for op: aten.clone.default" + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":1625 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0015", + "stacks":[] + }, + { + "message":{ + "markdown":"Skipped for fx.Node(aten.native_layer_norm.default)[call_function]:Tuple[length=3](\nTensor(f32[4, 1, 1024]),\nTensor(f32[4, 1, 1]),\nTensor(f32[4, 1, 1]),\n): Cannot find type promotion rule for op: aten.native_layer_norm.default\n\n## Additional Message:\n\n## Function Signature\n### Function Signature _TypePromotionInterpreter.run_node\n- self: \n- node: fx.Node(aten.native_layer_norm.default)[call_function]:Tuple[length=3](\nTensor(f32[4, 1, 1024]),\nTensor(f32[4, 1, 1]),\nTensor(f32[4, 1, 1]),\n)\n## Return values\nTuple[length=3](\nTensor(f32[4, 1, 1024]),\nTensor(f32[4, 1, 1]),\nTensor(f32[4, 1, 1]),\n)", + "text":"Skipped for fx.Node(aten.native_layer_norm.default)[call_function]:Tuple[length=3](\nTensor(f32[4, 1, 1024]),\nTensor(f32[4, 1, 1]),\nTensor(f32[4, 1, 1]),\n): Cannot find type promotion rule for op: aten.native_layer_norm.default" + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":1625 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0015", + "stacks":[] + }, + { + "message":{ + "markdown":"Skipped for fx.Node()[call_function]:Tensor(f32[4, 1, 1024]): node.target is not OpOverload. Got type: \n\n## Additional Message:\n\n## Function Signature\n### Function Signature _TypePromotionInterpreter.run_node\n- self: \n- node: fx.Node()[call_function]:Tensor(f32[4, 1, 1024])\n## Return values\nTensor(f32[4, 1, 1024])", + "text":"Skipped for fx.Node()[call_function]:Tensor(f32[4, 1, 1024]): node.target is not OpOverload. Got type: " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":1625 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0015", + "stacks":[] + }, + { + "message":{ + "markdown":"Skipped for fx.Node(aten.view.default)[call_function]:Tensor(f32[4, 1024]): Cannot find type promotion rule for op: aten.view.default\n\n## Additional Message:\n\n## Function Signature\n### Function Signature _TypePromotionInterpreter.run_node\n- self: \n- node: fx.Node(aten.view.default)[call_function]:Tensor(f32[4, 1024])\n## Return values\nTensor(f32[4, 1024])", + "text":"Skipped for fx.Node(aten.view.default)[call_function]:Tensor(f32[4, 1024]): Cannot find type promotion rule for op: aten.view.default" + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":1625 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0015", + "stacks":[] + }, + { + "message":{ + "markdown":"Skipped for fx.Node(aten.t.default)[call_function]:Tensor(f32[1024, 4096]): Cannot find type promotion rule for op: aten.t.default\n\n## Additional Message:\n\n## Function Signature\n### Function Signature _TypePromotionInterpreter.run_node\n- self: \n- node: fx.Node(aten.t.default)[call_function]:Tensor(f32[1024, 4096])\n## Return values\nTensor(f32[1024, 4096])", + "text":"Skipped for fx.Node(aten.t.default)[call_function]:Tensor(f32[1024, 4096]): Cannot find type promotion rule for op: aten.t.default" + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":1625 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0015", + "stacks":[] + }, + { + "message":{ + "markdown":"Skipped for fx.Node(aten.addmm.default)[call_function]:Tensor(f32[4, 4096]): Cannot find type promotion rule for op: aten.addmm.default\n\n## Additional Message:\n\n## Function Signature\n### Function Signature _TypePromotionInterpreter.run_node\n- self: \n- node: fx.Node(aten.addmm.default)[call_function]:Tensor(f32[4, 4096])\n## Return values\nTensor(f32[4, 4096])", + "text":"Skipped for fx.Node(aten.addmm.default)[call_function]:Tensor(f32[4, 4096]): Cannot find type promotion rule for op: aten.addmm.default" + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":1625 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0015", + "stacks":[] + }, + { + "message":{ + "markdown":"Skipped for fx.Node(aten.view.default)[call_function]:Tensor(f32[4, 1, 4096]): Cannot find type promotion rule for op: aten.view.default\n\n## Additional Message:\n\n## Function Signature\n### Function Signature _TypePromotionInterpreter.run_node\n- self: \n- node: fx.Node(aten.view.default)[call_function]:Tensor(f32[4, 1, 4096])\n## Return values\nTensor(f32[4, 1, 4096])", + "text":"Skipped for fx.Node(aten.view.default)[call_function]:Tensor(f32[4, 1, 4096]): Cannot find type promotion rule for op: aten.view.default" + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":1625 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0015", + "stacks":[] + }, + { + "message":{ + "markdown":"Type promotion not needed for gelu_24. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature _TypePromotionInterpreter.run_node\n- self: \n- node: fx.Node(aten.gelu.default)[call_function]:Tensor(f32[4, 1, 4096])\nFound type promotion rule: ElementwiseTypePromotionRule('aten', 'gelu', [0], [], ELEMENTWISE_TYPE_PROMOTION_KIND.DEFAULT)\nArgument view_251 is not promoted. Already torch.float32.\nArgument tanh is not promoted. Not mentioned by type promotion rule.\n## Return values\nTensor(f32[4, 1, 4096])", + "text":"Type promotion not needed for gelu_24. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":1625 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0015", + "stacks":[] + }, + { + "message":{ + "markdown":"Skipped for fx.Node(aten.clone.default)[call_function]:Tensor(f32[4, 1, 4096]): Cannot find type promotion rule for op: aten.clone.default\n\n## Additional Message:\n\n## Function Signature\n### Function Signature _TypePromotionInterpreter.run_node\n- self: \n- node: fx.Node(aten.clone.default)[call_function]:Tensor(f32[4, 1, 4096])\n## Return values\nTensor(f32[4, 1, 4096])", + "text":"Skipped for fx.Node(aten.clone.default)[call_function]:Tensor(f32[4, 1, 4096]): Cannot find type promotion rule for op: aten.clone.default" + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":1625 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0015", + "stacks":[] + }, + { + "message":{ + "markdown":"Skipped for fx.Node(aten.view.default)[call_function]:Tensor(f32[4, 4096]): Cannot find type promotion rule for op: aten.view.default\n\n## Additional Message:\n\n## Function Signature\n### Function Signature _TypePromotionInterpreter.run_node\n- self: \n- node: fx.Node(aten.view.default)[call_function]:Tensor(f32[4, 4096])\n## Return values\nTensor(f32[4, 4096])", + "text":"Skipped for fx.Node(aten.view.default)[call_function]:Tensor(f32[4, 4096]): Cannot find type promotion rule for op: aten.view.default" + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":1625 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0015", + "stacks":[] + }, + { + "message":{ + "markdown":"Skipped for fx.Node(aten.t.default)[call_function]:Tensor(f32[4096, 1024]): Cannot find type promotion rule for op: aten.t.default\n\n## Additional Message:\n\n## Function Signature\n### Function Signature _TypePromotionInterpreter.run_node\n- self: \n- node: fx.Node(aten.t.default)[call_function]:Tensor(f32[4096, 1024])\n## Return values\nTensor(f32[4096, 1024])", + "text":"Skipped for fx.Node(aten.t.default)[call_function]:Tensor(f32[4096, 1024]): Cannot find type promotion rule for op: aten.t.default" + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":1625 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0015", + "stacks":[] + }, + { + "message":{ + "markdown":"Skipped for fx.Node(aten.addmm.default)[call_function]:Tensor(f32[4, 1024]): Cannot find type promotion rule for op: aten.addmm.default\n\n## Additional Message:\n\n## Function Signature\n### Function Signature _TypePromotionInterpreter.run_node\n- self: \n- node: fx.Node(aten.addmm.default)[call_function]:Tensor(f32[4, 1024])\n## Return values\nTensor(f32[4, 1024])", + "text":"Skipped for fx.Node(aten.addmm.default)[call_function]:Tensor(f32[4, 1024]): Cannot find type promotion rule for op: aten.addmm.default" + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":1625 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0015", + "stacks":[] + }, + { + "message":{ + "markdown":"Skipped for fx.Node(aten.view.default)[call_function]:Tensor(f32[4, 1, 1024]): Cannot find type promotion rule for op: aten.view.default\n\n## Additional Message:\n\n## Function Signature\n### Function Signature _TypePromotionInterpreter.run_node\n- self: \n- node: fx.Node(aten.view.default)[call_function]:Tensor(f32[4, 1, 1024])\n## Return values\nTensor(f32[4, 1, 1024])", + "text":"Skipped for fx.Node(aten.view.default)[call_function]:Tensor(f32[4, 1, 1024]): Cannot find type promotion rule for op: aten.view.default" + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":1625 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0015", + "stacks":[] + }, + { + "message":{ + "markdown":"Skipped for fx.Node(aten.clone.default)[call_function]:Tensor(f32[4, 1, 1024]): Cannot find type promotion rule for op: aten.clone.default\n\n## Additional Message:\n\n## Function Signature\n### Function Signature _TypePromotionInterpreter.run_node\n- self: \n- node: fx.Node(aten.clone.default)[call_function]:Tensor(f32[4, 1, 1024])\n## Return values\nTensor(f32[4, 1, 1024])", + "text":"Skipped for fx.Node(aten.clone.default)[call_function]:Tensor(f32[4, 1, 1024]): Cannot find type promotion rule for op: aten.clone.default" + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":1625 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0015", + "stacks":[] + }, + { + "message":{ + "markdown":"Type promotion not needed for add_50. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature _TypePromotionInterpreter.run_node\n- self: \n- node: fx.Node(aten.add.Tensor)[call_function]:Tensor(f32[4, 1, 1024])\nFound type promotion rule: ElementwiseTypePromotionRule('aten', 'add', [0, 1], [], ELEMENTWISE_TYPE_PROMOTION_KIND.DEFAULT)\nArgument clone_73 is not promoted. Already torch.float32.\nArgument clone_75 is not promoted. Already torch.float32.\n## Return values\nTensor(f32[4, 1, 1024])", + "text":"Type promotion not needed for add_50. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":1625 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0015", + "stacks":[] + }, + { + "message":{ + "markdown":"Skipped for fx.Node(aten.slice.Tensor)[call_function]:Tensor(f32[4, 1, 1024]): Cannot find type promotion rule for op: aten.slice.Tensor\n\n## Additional Message:\n\n## Function Signature\n### Function Signature _TypePromotionInterpreter.run_node\n- self: \n- node: fx.Node(aten.slice.Tensor)[call_function]:Tensor(f32[4, 1, 1024])\n## Return values\nTensor(f32[4, 1, 1024])", + "text":"Skipped for fx.Node(aten.slice.Tensor)[call_function]:Tensor(f32[4, 1, 1024]): Cannot find type promotion rule for op: aten.slice.Tensor" + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":1625 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0015", + "stacks":[] + }, + { + "message":{ + "markdown":"Skipped for fx.Node(aten.select.int)[call_function]:Tensor(f32[4, 1024]): Cannot find type promotion rule for op: aten.select.int\n\n## Additional Message:\n\n## Function Signature\n### Function Signature _TypePromotionInterpreter.run_node\n- self: \n- node: fx.Node(aten.select.int)[call_function]:Tensor(f32[4, 1024])\n## Return values\nTensor(f32[4, 1024])", + "text":"Skipped for fx.Node(aten.select.int)[call_function]:Tensor(f32[4, 1024]): Cannot find type promotion rule for op: aten.select.int" + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":1625 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0015", + "stacks":[] + }, + { + "message":{ + "markdown":"Skipped for fx.Node(aten.clone.default)[call_function]:Tensor(f32[4, 1024]): Cannot find type promotion rule for op: aten.clone.default\n\n## Additional Message:\n\n## Function Signature\n### Function Signature _TypePromotionInterpreter.run_node\n- self: \n- node: fx.Node(aten.clone.default)[call_function]:Tensor(f32[4, 1024])\n## Return values\nTensor(f32[4, 1024])", + "text":"Skipped for fx.Node(aten.clone.default)[call_function]:Tensor(f32[4, 1024]): Cannot find type promotion rule for op: aten.clone.default" + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":1625 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0015", + "stacks":[] + }, + { + "message":{ + "markdown":"Skipped output: not a call_function.\n\n## Additional Message:\n\n## Function Signature\n### Function Signature _TypePromotionInterpreter.run_node\n- self: \n- node: fx.Node(output)[output]:None\n## Return values\nTuple[length=1](\nTensor(f32[4, 1024]),\n)", + "text":"Skipped output: not a call_function." + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"_TypePromotionInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/passes/type_promotion.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":1625 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0015", + "stacks":[] + }, + { + "message":{ + "markdown":"Running InsertTypePromotion pass. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature Transform.run\n- self: \nFor detailed logging of graph modifications by this pass, either set `DiagnosticOptions.verbosity_level` to `logging.DEBUG` or use the environment variable `TORCH_LOGS='onnx_diagnostics'`.\n## Return values\ntorch.fx.GraphModule(GraphModule)", + "text":"Running InsertTypePromotion pass. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"Transform.run" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/_pass.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":243 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0010", + "stacks":[] + }, + { + "message":{ + "markdown":"Running Modularize pass. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature Transform.run\n- self: \nFor detailed logging of graph modifications by this pass, either set `DiagnosticOptions.verbosity_level` to `logging.DEBUG` or use the environment variable `TORCH_LOGS='onnx_diagnostics'`.\n## Return values\ntorch.fx.GraphModule()", + "text":"Running Modularize pass. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"Transform.run" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/_pass.py" + }, + "region":{ + "snippet":{ + "text":"@diagnostics.diagnose_call(" + }, + "startLine":243 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0010", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Node: placeholder:p_trunk_pos_embed[name=p_trunk_pos_embed]. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature FxOnnxInterpreter.run_node\n- self: \n- node: fx.Node(p_trunk_pos_embed)[placeholder]:Tensor(f32[1, 1024, 1024])\n- fx_graph_module: torch.fx.GraphModule()\n- onnxfunction_dispatcher: \n- op_level_debug: False\n- onnxscript_graph: \n- onnxscript_tracer: \n- fx_name_to_onnxscript_value: Dict[length=0](\nNone)\n## Return values\n", + "text":"FX Node: placeholder:p_trunk_pos_embed[name=p_trunk_pos_embed]. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"FxOnnxInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":414 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0008", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Node: placeholder:p_trunk_attn_pool_latent[name=p_trunk_attn_pool_latent]. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature FxOnnxInterpreter.run_node\n- self: \n- node: fx.Node(p_trunk_attn_pool_latent)[placeholder]:Tensor(f32[1, 1, 1024])\n- fx_graph_module: torch.fx.GraphModule()\n- onnxfunction_dispatcher: \n- op_level_debug: False\n- onnxscript_graph: \n- onnxscript_tracer: \n- fx_name_to_onnxscript_value: Dict[length=1](\np_trunk_pos_embed: `TorchScriptTensor(f32[1, 1024, 1024])`,\n)\n## Return values\n", + "text":"FX Node: placeholder:p_trunk_attn_pool_latent[name=p_trunk_attn_pool_latent]. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"FxOnnxInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":414 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0008", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Node: placeholder:p_trunk_patch_embed_proj_weight[name=p_trunk_patch_embed_proj_weight]. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature FxOnnxInterpreter.run_node\n- self: \n- node: fx.Node(p_trunk_patch_embed_proj_weight)[placeholder]:Tensor(f32[1024, 3, 16, 16])\n- fx_graph_module: torch.fx.GraphModule()\n- onnxfunction_dispatcher: \n- op_level_debug: False\n- onnxscript_graph: \n- onnxscript_tracer: \n- fx_name_to_onnxscript_value: Dict[length=2](\np_trunk_pos_embed: `TorchScriptTensor(f32[1, 1024, 1024])`,\np_trunk_attn_pool_latent: `TorchScriptTensor(f32[1, 1, 1024])`,\n)\n## Return values\n", + "text":"FX Node: placeholder:p_trunk_patch_embed_proj_weight[name=p_trunk_patch_embed_proj_weight]. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"FxOnnxInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":414 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0008", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Node: placeholder:p_trunk_patch_embed_proj_bias[name=p_trunk_patch_embed_proj_bias]. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature FxOnnxInterpreter.run_node\n- self: \n- node: fx.Node(p_trunk_patch_embed_proj_bias)[placeholder]:Tensor(f32[1024])\n- fx_graph_module: torch.fx.GraphModule()\n- onnxfunction_dispatcher: \n- op_level_debug: False\n- onnxscript_graph: \n- onnxscript_tracer: \n- fx_name_to_onnxscript_value: Dict[length=3](\np_trunk_pos_embed: `TorchScriptTensor(f32[1, 1024, 1024])`,\np_trunk_attn_pool_latent: `TorchScriptTensor(f32[1, 1, 1024])`,\np_trunk_patch_embed_proj_weight: `TorchScriptTensor(f32[1024, 3, 16, 16])`,\n)\n## Return values\n", + "text":"FX Node: placeholder:p_trunk_patch_embed_proj_bias[name=p_trunk_patch_embed_proj_bias]. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"FxOnnxInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":414 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0008", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___0___norm1_weight[name=p_getattr_l__self___trunk_blocks___0___norm1_weight]. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature FxOnnxInterpreter.run_node\n- self: \n- node: fx.Node(p_getattr_l__self___trunk_blocks___0___norm1_weight)[placeholder]:Tensor(f32[1024])\n- fx_graph_module: torch.fx.GraphModule()\n- onnxfunction_dispatcher: \n- op_level_debug: False\n- onnxscript_graph: \n- onnxscript_tracer: \n- fx_name_to_onnxscript_value: Dict[length=4](\np_trunk_pos_embed: `TorchScriptTensor(f32[1, 1024, 1024])`,\np_trunk_attn_pool_latent: `TorchScriptTensor(f32[1, 1, 1024])`,\np_trunk_patch_embed_proj_weight: `TorchScriptTensor(f32[1024, 3, 16, 16])`,\np_trunk_patch_embed_proj_bias: `TorchScriptTensor(f32[1024])`,\n)\n## Return values\n", + "text":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___0___norm1_weight[name=p_getattr_l__self___trunk_blocks___0___norm1_weight]. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"FxOnnxInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":414 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0008", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___0___norm1_bias[name=p_getattr_l__self___trunk_blocks___0___norm1_bias]. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature FxOnnxInterpreter.run_node\n- self: \n- node: fx.Node(p_getattr_l__self___trunk_blocks___0___norm1_bias)[placeholder]:Tensor(f32[1024])\n- fx_graph_module: torch.fx.GraphModule()\n- onnxfunction_dispatcher: \n- op_level_debug: False\n- onnxscript_graph: \n- onnxscript_tracer: \n- fx_name_to_onnxscript_value: Dict[length=5](\np_trunk_pos_embed: `TorchScriptTensor(f32[1, 1024, 1024])`,\np_trunk_attn_pool_latent: `TorchScriptTensor(f32[1, 1, 1024])`,\np_trunk_patch_embed_proj_weight: `TorchScriptTensor(f32[1024, 3, 16, 16])`,\np_trunk_patch_embed_proj_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_weight: `TorchScriptTensor(f32[1024])`,\n)\n## Return values\n", + "text":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___0___norm1_bias[name=p_getattr_l__self___trunk_blocks___0___norm1_bias]. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"FxOnnxInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":414 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0008", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___0___attn_qkv_weight[name=p_getattr_l__self___trunk_blocks___0___attn_qkv_weight]. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature FxOnnxInterpreter.run_node\n- self: \n- node: fx.Node(p_getattr_l__self___trunk_blocks___0___attn_qkv_weight)[placeholder]:Tensor(f32[3072, 1024])\n- fx_graph_module: torch.fx.GraphModule()\n- onnxfunction_dispatcher: \n- op_level_debug: False\n- onnxscript_graph: \n- onnxscript_tracer: \n- fx_name_to_onnxscript_value: Dict[length=6](\np_trunk_pos_embed: `TorchScriptTensor(f32[1, 1024, 1024])`,\np_trunk_attn_pool_latent: `TorchScriptTensor(f32[1, 1, 1024])`,\np_trunk_patch_embed_proj_weight: `TorchScriptTensor(f32[1024, 3, 16, 16])`,\np_trunk_patch_embed_proj_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_bias: `TorchScriptTensor(f32[1024])`,\n)\n## Return values\n", + "text":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___0___attn_qkv_weight[name=p_getattr_l__self___trunk_blocks___0___attn_qkv_weight]. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"FxOnnxInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":414 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0008", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___0___attn_qkv_bias[name=p_getattr_l__self___trunk_blocks___0___attn_qkv_bias]. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature FxOnnxInterpreter.run_node\n- self: \n- node: fx.Node(p_getattr_l__self___trunk_blocks___0___attn_qkv_bias)[placeholder]:Tensor(f32[3072])\n- fx_graph_module: torch.fx.GraphModule()\n- onnxfunction_dispatcher: \n- op_level_debug: False\n- onnxscript_graph: \n- onnxscript_tracer: \n- fx_name_to_onnxscript_value: Dict[length=7](\np_trunk_pos_embed: `TorchScriptTensor(f32[1, 1024, 1024])`,\np_trunk_attn_pool_latent: `TorchScriptTensor(f32[1, 1, 1024])`,\np_trunk_patch_embed_proj_weight: `TorchScriptTensor(f32[1024, 3, 16, 16])`,\np_trunk_patch_embed_proj_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_weight: `TorchScriptTensor(f32[3072, 1024])`,\n)\n## Return values\n", + "text":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___0___attn_qkv_bias[name=p_getattr_l__self___trunk_blocks___0___attn_qkv_bias]. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"FxOnnxInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":414 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0008", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___0___attn_proj_weight[name=p_getattr_l__self___trunk_blocks___0___attn_proj_weight]. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature FxOnnxInterpreter.run_node\n- self: \n- node: fx.Node(p_getattr_l__self___trunk_blocks___0___attn_proj_weight)[placeholder]:Tensor(f32[1024, 1024])\n- fx_graph_module: torch.fx.GraphModule()\n- onnxfunction_dispatcher: \n- op_level_debug: False\n- onnxscript_graph: \n- onnxscript_tracer: \n- fx_name_to_onnxscript_value: Dict[length=8](\np_trunk_pos_embed: `TorchScriptTensor(f32[1, 1024, 1024])`,\np_trunk_attn_pool_latent: `TorchScriptTensor(f32[1, 1, 1024])`,\np_trunk_patch_embed_proj_weight: `TorchScriptTensor(f32[1024, 3, 16, 16])`,\np_trunk_patch_embed_proj_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_weight: `TorchScriptTensor(f32[3072, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_bias: `TorchScriptTensor(f32[3072])`,\n)\n## Return values\n", + "text":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___0___attn_proj_weight[name=p_getattr_l__self___trunk_blocks___0___attn_proj_weight]. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"FxOnnxInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":414 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0008", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___0___attn_proj_bias[name=p_getattr_l__self___trunk_blocks___0___attn_proj_bias]. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature FxOnnxInterpreter.run_node\n- self: \n- node: fx.Node(p_getattr_l__self___trunk_blocks___0___attn_proj_bias)[placeholder]:Tensor(f32[1024])\n- fx_graph_module: torch.fx.GraphModule()\n- onnxfunction_dispatcher: \n- op_level_debug: False\n- onnxscript_graph: \n- onnxscript_tracer: \n- fx_name_to_onnxscript_value: Dict[length=9](\np_trunk_pos_embed: `TorchScriptTensor(f32[1, 1024, 1024])`,\np_trunk_attn_pool_latent: `TorchScriptTensor(f32[1, 1, 1024])`,\np_trunk_patch_embed_proj_weight: `TorchScriptTensor(f32[1024, 3, 16, 16])`,\np_trunk_patch_embed_proj_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_weight: `TorchScriptTensor(f32[3072, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_bias: `TorchScriptTensor(f32[3072])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_weight: `TorchScriptTensor(f32[1024, 1024])`,\n)\n## Return values\n", + "text":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___0___attn_proj_bias[name=p_getattr_l__self___trunk_blocks___0___attn_proj_bias]. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"FxOnnxInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":414 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0008", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___0___norm2_weight[name=p_getattr_l__self___trunk_blocks___0___norm2_weight]. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature FxOnnxInterpreter.run_node\n- self: \n- node: fx.Node(p_getattr_l__self___trunk_blocks___0___norm2_weight)[placeholder]:Tensor(f32[1024])\n- fx_graph_module: torch.fx.GraphModule()\n- onnxfunction_dispatcher: \n- op_level_debug: False\n- onnxscript_graph: \n- onnxscript_tracer: \n- fx_name_to_onnxscript_value: Dict[length=10](\np_trunk_pos_embed: `TorchScriptTensor(f32[1, 1024, 1024])`,\np_trunk_attn_pool_latent: `TorchScriptTensor(f32[1, 1, 1024])`,\np_trunk_patch_embed_proj_weight: `TorchScriptTensor(f32[1024, 3, 16, 16])`,\np_trunk_patch_embed_proj_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_weight: `TorchScriptTensor(f32[3072, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_bias: `TorchScriptTensor(f32[3072])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_weight: `TorchScriptTensor(f32[1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_bias: `TorchScriptTensor(f32[1024])`,\n)\n## Return values\n", + "text":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___0___norm2_weight[name=p_getattr_l__self___trunk_blocks___0___norm2_weight]. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"FxOnnxInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":414 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0008", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___0___norm2_bias[name=p_getattr_l__self___trunk_blocks___0___norm2_bias]. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature FxOnnxInterpreter.run_node\n- self: \n- node: fx.Node(p_getattr_l__self___trunk_blocks___0___norm2_bias)[placeholder]:Tensor(f32[1024])\n- fx_graph_module: torch.fx.GraphModule()\n- onnxfunction_dispatcher: \n- op_level_debug: False\n- onnxscript_graph: \n- onnxscript_tracer: \n- fx_name_to_onnxscript_value: Dict[length=11](\np_trunk_pos_embed: `TorchScriptTensor(f32[1, 1024, 1024])`,\np_trunk_attn_pool_latent: `TorchScriptTensor(f32[1, 1, 1024])`,\np_trunk_patch_embed_proj_weight: `TorchScriptTensor(f32[1024, 3, 16, 16])`,\np_trunk_patch_embed_proj_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_weight: `TorchScriptTensor(f32[3072, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_bias: `TorchScriptTensor(f32[3072])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_weight: `TorchScriptTensor(f32[1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_bias: `TorchScriptTensor(f32[1024])`,\n...\n)\n## Return values\n", + "text":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___0___norm2_bias[name=p_getattr_l__self___trunk_blocks___0___norm2_bias]. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"FxOnnxInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":414 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0008", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___0___mlp_fc1_weight[name=p_getattr_l__self___trunk_blocks___0___mlp_fc1_weight]. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature FxOnnxInterpreter.run_node\n- self: \n- node: fx.Node(p_getattr_l__self___trunk_blocks___0___mlp_fc1_weight)[placeholder]:Tensor(f32[4096, 1024])\n- fx_graph_module: torch.fx.GraphModule()\n- onnxfunction_dispatcher: \n- op_level_debug: False\n- onnxscript_graph: \n- onnxscript_tracer: \n- fx_name_to_onnxscript_value: Dict[length=12](\np_trunk_pos_embed: `TorchScriptTensor(f32[1, 1024, 1024])`,\np_trunk_attn_pool_latent: `TorchScriptTensor(f32[1, 1, 1024])`,\np_trunk_patch_embed_proj_weight: `TorchScriptTensor(f32[1024, 3, 16, 16])`,\np_trunk_patch_embed_proj_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_weight: `TorchScriptTensor(f32[3072, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_bias: `TorchScriptTensor(f32[3072])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_weight: `TorchScriptTensor(f32[1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_bias: `TorchScriptTensor(f32[1024])`,\n...\n)\n## Return values\n", + "text":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___0___mlp_fc1_weight[name=p_getattr_l__self___trunk_blocks___0___mlp_fc1_weight]. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"FxOnnxInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":414 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0008", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___0___mlp_fc1_bias[name=p_getattr_l__self___trunk_blocks___0___mlp_fc1_bias]. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature FxOnnxInterpreter.run_node\n- self: \n- node: fx.Node(p_getattr_l__self___trunk_blocks___0___mlp_fc1_bias)[placeholder]:Tensor(f32[4096])\n- fx_graph_module: torch.fx.GraphModule()\n- onnxfunction_dispatcher: \n- op_level_debug: False\n- onnxscript_graph: \n- onnxscript_tracer: \n- fx_name_to_onnxscript_value: Dict[length=13](\np_trunk_pos_embed: `TorchScriptTensor(f32[1, 1024, 1024])`,\np_trunk_attn_pool_latent: `TorchScriptTensor(f32[1, 1, 1024])`,\np_trunk_patch_embed_proj_weight: `TorchScriptTensor(f32[1024, 3, 16, 16])`,\np_trunk_patch_embed_proj_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_weight: `TorchScriptTensor(f32[3072, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_bias: `TorchScriptTensor(f32[3072])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_weight: `TorchScriptTensor(f32[1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_bias: `TorchScriptTensor(f32[1024])`,\n...\n)\n## Return values\n", + "text":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___0___mlp_fc1_bias[name=p_getattr_l__self___trunk_blocks___0___mlp_fc1_bias]. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"FxOnnxInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":414 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0008", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___0___mlp_fc2_weight[name=p_getattr_l__self___trunk_blocks___0___mlp_fc2_weight]. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature FxOnnxInterpreter.run_node\n- self: \n- node: fx.Node(p_getattr_l__self___trunk_blocks___0___mlp_fc2_weight)[placeholder]:Tensor(f32[1024, 4096])\n- fx_graph_module: torch.fx.GraphModule()\n- onnxfunction_dispatcher: \n- op_level_debug: False\n- onnxscript_graph: \n- onnxscript_tracer: \n- fx_name_to_onnxscript_value: Dict[length=14](\np_trunk_pos_embed: `TorchScriptTensor(f32[1, 1024, 1024])`,\np_trunk_attn_pool_latent: `TorchScriptTensor(f32[1, 1, 1024])`,\np_trunk_patch_embed_proj_weight: `TorchScriptTensor(f32[1024, 3, 16, 16])`,\np_trunk_patch_embed_proj_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_weight: `TorchScriptTensor(f32[3072, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_bias: `TorchScriptTensor(f32[3072])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_weight: `TorchScriptTensor(f32[1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_bias: `TorchScriptTensor(f32[1024])`,\n...\n)\n## Return values\n", + "text":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___0___mlp_fc2_weight[name=p_getattr_l__self___trunk_blocks___0___mlp_fc2_weight]. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"FxOnnxInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":414 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0008", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___0___mlp_fc2_bias[name=p_getattr_l__self___trunk_blocks___0___mlp_fc2_bias]. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature FxOnnxInterpreter.run_node\n- self: \n- node: fx.Node(p_getattr_l__self___trunk_blocks___0___mlp_fc2_bias)[placeholder]:Tensor(f32[1024])\n- fx_graph_module: torch.fx.GraphModule()\n- onnxfunction_dispatcher: \n- op_level_debug: False\n- onnxscript_graph: \n- onnxscript_tracer: \n- fx_name_to_onnxscript_value: Dict[length=15](\np_trunk_pos_embed: `TorchScriptTensor(f32[1, 1024, 1024])`,\np_trunk_attn_pool_latent: `TorchScriptTensor(f32[1, 1, 1024])`,\np_trunk_patch_embed_proj_weight: `TorchScriptTensor(f32[1024, 3, 16, 16])`,\np_trunk_patch_embed_proj_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_weight: `TorchScriptTensor(f32[3072, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_bias: `TorchScriptTensor(f32[3072])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_weight: `TorchScriptTensor(f32[1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_bias: `TorchScriptTensor(f32[1024])`,\n...\n)\n## Return values\n", + "text":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___0___mlp_fc2_bias[name=p_getattr_l__self___trunk_blocks___0___mlp_fc2_bias]. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"FxOnnxInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":414 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0008", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___1___norm1_weight[name=p_getattr_l__self___trunk_blocks___1___norm1_weight]. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature FxOnnxInterpreter.run_node\n- self: \n- node: fx.Node(p_getattr_l__self___trunk_blocks___1___norm1_weight)[placeholder]:Tensor(f32[1024])\n- fx_graph_module: torch.fx.GraphModule()\n- onnxfunction_dispatcher: \n- op_level_debug: False\n- onnxscript_graph: \n- onnxscript_tracer: \n- fx_name_to_onnxscript_value: Dict[length=16](\np_trunk_pos_embed: `TorchScriptTensor(f32[1, 1024, 1024])`,\np_trunk_attn_pool_latent: `TorchScriptTensor(f32[1, 1, 1024])`,\np_trunk_patch_embed_proj_weight: `TorchScriptTensor(f32[1024, 3, 16, 16])`,\np_trunk_patch_embed_proj_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_weight: `TorchScriptTensor(f32[3072, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_bias: `TorchScriptTensor(f32[3072])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_weight: `TorchScriptTensor(f32[1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_bias: `TorchScriptTensor(f32[1024])`,\n...\n)\n## Return values\n", + "text":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___1___norm1_weight[name=p_getattr_l__self___trunk_blocks___1___norm1_weight]. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"FxOnnxInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":414 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0008", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___1___norm1_bias[name=p_getattr_l__self___trunk_blocks___1___norm1_bias]. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature FxOnnxInterpreter.run_node\n- self: \n- node: fx.Node(p_getattr_l__self___trunk_blocks___1___norm1_bias)[placeholder]:Tensor(f32[1024])\n- fx_graph_module: torch.fx.GraphModule()\n- onnxfunction_dispatcher: \n- op_level_debug: False\n- onnxscript_graph: \n- onnxscript_tracer: \n- fx_name_to_onnxscript_value: Dict[length=17](\np_trunk_pos_embed: `TorchScriptTensor(f32[1, 1024, 1024])`,\np_trunk_attn_pool_latent: `TorchScriptTensor(f32[1, 1, 1024])`,\np_trunk_patch_embed_proj_weight: `TorchScriptTensor(f32[1024, 3, 16, 16])`,\np_trunk_patch_embed_proj_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_weight: `TorchScriptTensor(f32[3072, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_bias: `TorchScriptTensor(f32[3072])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_weight: `TorchScriptTensor(f32[1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_bias: `TorchScriptTensor(f32[1024])`,\n...\n)\n## Return values\n", + "text":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___1___norm1_bias[name=p_getattr_l__self___trunk_blocks___1___norm1_bias]. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"FxOnnxInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":414 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0008", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___1___attn_qkv_weight[name=p_getattr_l__self___trunk_blocks___1___attn_qkv_weight]. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature FxOnnxInterpreter.run_node\n- self: \n- node: fx.Node(p_getattr_l__self___trunk_blocks___1___attn_qkv_weight)[placeholder]:Tensor(f32[3072, 1024])\n- fx_graph_module: torch.fx.GraphModule()\n- onnxfunction_dispatcher: \n- op_level_debug: False\n- onnxscript_graph: \n- onnxscript_tracer: \n- fx_name_to_onnxscript_value: Dict[length=18](\np_trunk_pos_embed: `TorchScriptTensor(f32[1, 1024, 1024])`,\np_trunk_attn_pool_latent: `TorchScriptTensor(f32[1, 1, 1024])`,\np_trunk_patch_embed_proj_weight: `TorchScriptTensor(f32[1024, 3, 16, 16])`,\np_trunk_patch_embed_proj_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_weight: `TorchScriptTensor(f32[3072, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_bias: `TorchScriptTensor(f32[3072])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_weight: `TorchScriptTensor(f32[1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_bias: `TorchScriptTensor(f32[1024])`,\n...\n)\n## Return values\n", + "text":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___1___attn_qkv_weight[name=p_getattr_l__self___trunk_blocks___1___attn_qkv_weight]. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"FxOnnxInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":414 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0008", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___1___attn_qkv_bias[name=p_getattr_l__self___trunk_blocks___1___attn_qkv_bias]. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature FxOnnxInterpreter.run_node\n- self: \n- node: fx.Node(p_getattr_l__self___trunk_blocks___1___attn_qkv_bias)[placeholder]:Tensor(f32[3072])\n- fx_graph_module: torch.fx.GraphModule()\n- onnxfunction_dispatcher: \n- op_level_debug: False\n- onnxscript_graph: \n- onnxscript_tracer: \n- fx_name_to_onnxscript_value: Dict[length=19](\np_trunk_pos_embed: `TorchScriptTensor(f32[1, 1024, 1024])`,\np_trunk_attn_pool_latent: `TorchScriptTensor(f32[1, 1, 1024])`,\np_trunk_patch_embed_proj_weight: `TorchScriptTensor(f32[1024, 3, 16, 16])`,\np_trunk_patch_embed_proj_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_weight: `TorchScriptTensor(f32[3072, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_bias: `TorchScriptTensor(f32[3072])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_weight: `TorchScriptTensor(f32[1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_bias: `TorchScriptTensor(f32[1024])`,\n...\n)\n## Return values\n", + "text":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___1___attn_qkv_bias[name=p_getattr_l__self___trunk_blocks___1___attn_qkv_bias]. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"FxOnnxInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":414 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0008", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___1___attn_proj_weight[name=p_getattr_l__self___trunk_blocks___1___attn_proj_weight]. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature FxOnnxInterpreter.run_node\n- self: \n- node: fx.Node(p_getattr_l__self___trunk_blocks___1___attn_proj_weight)[placeholder]:Tensor(f32[1024, 1024])\n- fx_graph_module: torch.fx.GraphModule()\n- onnxfunction_dispatcher: \n- op_level_debug: False\n- onnxscript_graph: \n- onnxscript_tracer: \n- fx_name_to_onnxscript_value: Dict[length=20](\np_trunk_pos_embed: `TorchScriptTensor(f32[1, 1024, 1024])`,\np_trunk_attn_pool_latent: `TorchScriptTensor(f32[1, 1, 1024])`,\np_trunk_patch_embed_proj_weight: `TorchScriptTensor(f32[1024, 3, 16, 16])`,\np_trunk_patch_embed_proj_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_weight: `TorchScriptTensor(f32[3072, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_bias: `TorchScriptTensor(f32[3072])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_weight: `TorchScriptTensor(f32[1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_bias: `TorchScriptTensor(f32[1024])`,\n...\n)\n## Return values\n", + "text":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___1___attn_proj_weight[name=p_getattr_l__self___trunk_blocks___1___attn_proj_weight]. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"FxOnnxInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":414 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0008", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___1___attn_proj_bias[name=p_getattr_l__self___trunk_blocks___1___attn_proj_bias]. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature FxOnnxInterpreter.run_node\n- self: \n- node: fx.Node(p_getattr_l__self___trunk_blocks___1___attn_proj_bias)[placeholder]:Tensor(f32[1024])\n- fx_graph_module: torch.fx.GraphModule()\n- onnxfunction_dispatcher: \n- op_level_debug: False\n- onnxscript_graph: \n- onnxscript_tracer: \n- fx_name_to_onnxscript_value: Dict[length=21](\np_trunk_pos_embed: `TorchScriptTensor(f32[1, 1024, 1024])`,\np_trunk_attn_pool_latent: `TorchScriptTensor(f32[1, 1, 1024])`,\np_trunk_patch_embed_proj_weight: `TorchScriptTensor(f32[1024, 3, 16, 16])`,\np_trunk_patch_embed_proj_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_weight: `TorchScriptTensor(f32[3072, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_bias: `TorchScriptTensor(f32[3072])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_weight: `TorchScriptTensor(f32[1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_bias: `TorchScriptTensor(f32[1024])`,\n...\n)\n## Return values\n", + "text":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___1___attn_proj_bias[name=p_getattr_l__self___trunk_blocks___1___attn_proj_bias]. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"FxOnnxInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":414 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0008", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___1___norm2_weight[name=p_getattr_l__self___trunk_blocks___1___norm2_weight]. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature FxOnnxInterpreter.run_node\n- self: \n- node: fx.Node(p_getattr_l__self___trunk_blocks___1___norm2_weight)[placeholder]:Tensor(f32[1024])\n- fx_graph_module: torch.fx.GraphModule()\n- onnxfunction_dispatcher: \n- op_level_debug: False\n- onnxscript_graph: \n- onnxscript_tracer: \n- fx_name_to_onnxscript_value: Dict[length=22](\np_trunk_pos_embed: `TorchScriptTensor(f32[1, 1024, 1024])`,\np_trunk_attn_pool_latent: `TorchScriptTensor(f32[1, 1, 1024])`,\np_trunk_patch_embed_proj_weight: `TorchScriptTensor(f32[1024, 3, 16, 16])`,\np_trunk_patch_embed_proj_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_weight: `TorchScriptTensor(f32[3072, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_bias: `TorchScriptTensor(f32[3072])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_weight: `TorchScriptTensor(f32[1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_bias: `TorchScriptTensor(f32[1024])`,\n...\n)\n## Return values\n", + "text":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___1___norm2_weight[name=p_getattr_l__self___trunk_blocks___1___norm2_weight]. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"FxOnnxInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":414 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0008", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___1___norm2_bias[name=p_getattr_l__self___trunk_blocks___1___norm2_bias]. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature FxOnnxInterpreter.run_node\n- self: \n- node: fx.Node(p_getattr_l__self___trunk_blocks___1___norm2_bias)[placeholder]:Tensor(f32[1024])\n- fx_graph_module: torch.fx.GraphModule()\n- onnxfunction_dispatcher: \n- op_level_debug: False\n- onnxscript_graph: \n- onnxscript_tracer: \n- fx_name_to_onnxscript_value: Dict[length=23](\np_trunk_pos_embed: `TorchScriptTensor(f32[1, 1024, 1024])`,\np_trunk_attn_pool_latent: `TorchScriptTensor(f32[1, 1, 1024])`,\np_trunk_patch_embed_proj_weight: `TorchScriptTensor(f32[1024, 3, 16, 16])`,\np_trunk_patch_embed_proj_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_weight: `TorchScriptTensor(f32[3072, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_bias: `TorchScriptTensor(f32[3072])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_weight: `TorchScriptTensor(f32[1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_bias: `TorchScriptTensor(f32[1024])`,\n...\n)\n## Return values\n", + "text":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___1___norm2_bias[name=p_getattr_l__self___trunk_blocks___1___norm2_bias]. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"FxOnnxInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":414 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0008", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___1___mlp_fc1_weight[name=p_getattr_l__self___trunk_blocks___1___mlp_fc1_weight]. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature FxOnnxInterpreter.run_node\n- self: \n- node: fx.Node(p_getattr_l__self___trunk_blocks___1___mlp_fc1_weight)[placeholder]:Tensor(f32[4096, 1024])\n- fx_graph_module: torch.fx.GraphModule()\n- onnxfunction_dispatcher: \n- op_level_debug: False\n- onnxscript_graph: \n- onnxscript_tracer: \n- fx_name_to_onnxscript_value: Dict[length=24](\np_trunk_pos_embed: `TorchScriptTensor(f32[1, 1024, 1024])`,\np_trunk_attn_pool_latent: `TorchScriptTensor(f32[1, 1, 1024])`,\np_trunk_patch_embed_proj_weight: `TorchScriptTensor(f32[1024, 3, 16, 16])`,\np_trunk_patch_embed_proj_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_weight: `TorchScriptTensor(f32[3072, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_bias: `TorchScriptTensor(f32[3072])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_weight: `TorchScriptTensor(f32[1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_bias: `TorchScriptTensor(f32[1024])`,\n...\n)\n## Return values\n", + "text":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___1___mlp_fc1_weight[name=p_getattr_l__self___trunk_blocks___1___mlp_fc1_weight]. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"FxOnnxInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":414 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0008", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___1___mlp_fc1_bias[name=p_getattr_l__self___trunk_blocks___1___mlp_fc1_bias]. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature FxOnnxInterpreter.run_node\n- self: \n- node: fx.Node(p_getattr_l__self___trunk_blocks___1___mlp_fc1_bias)[placeholder]:Tensor(f32[4096])\n- fx_graph_module: torch.fx.GraphModule()\n- onnxfunction_dispatcher: \n- op_level_debug: False\n- onnxscript_graph: \n- onnxscript_tracer: \n- fx_name_to_onnxscript_value: Dict[length=25](\np_trunk_pos_embed: `TorchScriptTensor(f32[1, 1024, 1024])`,\np_trunk_attn_pool_latent: `TorchScriptTensor(f32[1, 1, 1024])`,\np_trunk_patch_embed_proj_weight: `TorchScriptTensor(f32[1024, 3, 16, 16])`,\np_trunk_patch_embed_proj_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_weight: `TorchScriptTensor(f32[3072, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_bias: `TorchScriptTensor(f32[3072])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_weight: `TorchScriptTensor(f32[1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_bias: `TorchScriptTensor(f32[1024])`,\n...\n)\n## Return values\n", + "text":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___1___mlp_fc1_bias[name=p_getattr_l__self___trunk_blocks___1___mlp_fc1_bias]. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"FxOnnxInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":414 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0008", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___1___mlp_fc2_weight[name=p_getattr_l__self___trunk_blocks___1___mlp_fc2_weight]. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature FxOnnxInterpreter.run_node\n- self: \n- node: fx.Node(p_getattr_l__self___trunk_blocks___1___mlp_fc2_weight)[placeholder]:Tensor(f32[1024, 4096])\n- fx_graph_module: torch.fx.GraphModule()\n- onnxfunction_dispatcher: \n- op_level_debug: False\n- onnxscript_graph: \n- onnxscript_tracer: \n- fx_name_to_onnxscript_value: Dict[length=26](\np_trunk_pos_embed: `TorchScriptTensor(f32[1, 1024, 1024])`,\np_trunk_attn_pool_latent: `TorchScriptTensor(f32[1, 1, 1024])`,\np_trunk_patch_embed_proj_weight: `TorchScriptTensor(f32[1024, 3, 16, 16])`,\np_trunk_patch_embed_proj_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_weight: `TorchScriptTensor(f32[3072, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_bias: `TorchScriptTensor(f32[3072])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_weight: `TorchScriptTensor(f32[1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_bias: `TorchScriptTensor(f32[1024])`,\n...\n)\n## Return values\n", + "text":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___1___mlp_fc2_weight[name=p_getattr_l__self___trunk_blocks___1___mlp_fc2_weight]. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"FxOnnxInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":414 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0008", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___1___mlp_fc2_bias[name=p_getattr_l__self___trunk_blocks___1___mlp_fc2_bias]. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature FxOnnxInterpreter.run_node\n- self: \n- node: fx.Node(p_getattr_l__self___trunk_blocks___1___mlp_fc2_bias)[placeholder]:Tensor(f32[1024])\n- fx_graph_module: torch.fx.GraphModule()\n- onnxfunction_dispatcher: \n- op_level_debug: False\n- onnxscript_graph: \n- onnxscript_tracer: \n- fx_name_to_onnxscript_value: Dict[length=27](\np_trunk_pos_embed: `TorchScriptTensor(f32[1, 1024, 1024])`,\np_trunk_attn_pool_latent: `TorchScriptTensor(f32[1, 1, 1024])`,\np_trunk_patch_embed_proj_weight: `TorchScriptTensor(f32[1024, 3, 16, 16])`,\np_trunk_patch_embed_proj_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_weight: `TorchScriptTensor(f32[3072, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_bias: `TorchScriptTensor(f32[3072])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_weight: `TorchScriptTensor(f32[1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_bias: `TorchScriptTensor(f32[1024])`,\n...\n)\n## Return values\n", + "text":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___1___mlp_fc2_bias[name=p_getattr_l__self___trunk_blocks___1___mlp_fc2_bias]. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"FxOnnxInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":414 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0008", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___2___norm1_weight[name=p_getattr_l__self___trunk_blocks___2___norm1_weight]. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature FxOnnxInterpreter.run_node\n- self: \n- node: fx.Node(p_getattr_l__self___trunk_blocks___2___norm1_weight)[placeholder]:Tensor(f32[1024])\n- fx_graph_module: torch.fx.GraphModule()\n- onnxfunction_dispatcher: \n- op_level_debug: False\n- onnxscript_graph: \n- onnxscript_tracer: \n- fx_name_to_onnxscript_value: Dict[length=28](\np_trunk_pos_embed: `TorchScriptTensor(f32[1, 1024, 1024])`,\np_trunk_attn_pool_latent: `TorchScriptTensor(f32[1, 1, 1024])`,\np_trunk_patch_embed_proj_weight: `TorchScriptTensor(f32[1024, 3, 16, 16])`,\np_trunk_patch_embed_proj_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_weight: `TorchScriptTensor(f32[3072, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_bias: `TorchScriptTensor(f32[3072])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_weight: `TorchScriptTensor(f32[1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_bias: `TorchScriptTensor(f32[1024])`,\n...\n)\n## Return values\n", + "text":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___2___norm1_weight[name=p_getattr_l__self___trunk_blocks___2___norm1_weight]. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"FxOnnxInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":414 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0008", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___2___norm1_bias[name=p_getattr_l__self___trunk_blocks___2___norm1_bias]. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature FxOnnxInterpreter.run_node\n- self: \n- node: fx.Node(p_getattr_l__self___trunk_blocks___2___norm1_bias)[placeholder]:Tensor(f32[1024])\n- fx_graph_module: torch.fx.GraphModule()\n- onnxfunction_dispatcher: \n- op_level_debug: False\n- onnxscript_graph: \n- onnxscript_tracer: \n- fx_name_to_onnxscript_value: Dict[length=29](\np_trunk_pos_embed: `TorchScriptTensor(f32[1, 1024, 1024])`,\np_trunk_attn_pool_latent: `TorchScriptTensor(f32[1, 1, 1024])`,\np_trunk_patch_embed_proj_weight: `TorchScriptTensor(f32[1024, 3, 16, 16])`,\np_trunk_patch_embed_proj_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_weight: `TorchScriptTensor(f32[3072, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_bias: `TorchScriptTensor(f32[3072])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_weight: `TorchScriptTensor(f32[1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_bias: `TorchScriptTensor(f32[1024])`,\n...\n)\n## Return values\n", + "text":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___2___norm1_bias[name=p_getattr_l__self___trunk_blocks___2___norm1_bias]. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"FxOnnxInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":414 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0008", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___2___attn_qkv_weight[name=p_getattr_l__self___trunk_blocks___2___attn_qkv_weight]. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature FxOnnxInterpreter.run_node\n- self: \n- node: fx.Node(p_getattr_l__self___trunk_blocks___2___attn_qkv_weight)[placeholder]:Tensor(f32[3072, 1024])\n- fx_graph_module: torch.fx.GraphModule()\n- onnxfunction_dispatcher: \n- op_level_debug: False\n- onnxscript_graph: \n- onnxscript_tracer: \n- fx_name_to_onnxscript_value: Dict[length=30](\np_trunk_pos_embed: `TorchScriptTensor(f32[1, 1024, 1024])`,\np_trunk_attn_pool_latent: `TorchScriptTensor(f32[1, 1, 1024])`,\np_trunk_patch_embed_proj_weight: `TorchScriptTensor(f32[1024, 3, 16, 16])`,\np_trunk_patch_embed_proj_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_weight: `TorchScriptTensor(f32[3072, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_bias: `TorchScriptTensor(f32[3072])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_weight: `TorchScriptTensor(f32[1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_bias: `TorchScriptTensor(f32[1024])`,\n...\n)\n## Return values\n", + "text":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___2___attn_qkv_weight[name=p_getattr_l__self___trunk_blocks___2___attn_qkv_weight]. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"FxOnnxInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":414 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0008", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___2___attn_qkv_bias[name=p_getattr_l__self___trunk_blocks___2___attn_qkv_bias]. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature FxOnnxInterpreter.run_node\n- self: \n- node: fx.Node(p_getattr_l__self___trunk_blocks___2___attn_qkv_bias)[placeholder]:Tensor(f32[3072])\n- fx_graph_module: torch.fx.GraphModule()\n- onnxfunction_dispatcher: \n- op_level_debug: False\n- onnxscript_graph: \n- onnxscript_tracer: \n- fx_name_to_onnxscript_value: Dict[length=31](\np_trunk_pos_embed: `TorchScriptTensor(f32[1, 1024, 1024])`,\np_trunk_attn_pool_latent: `TorchScriptTensor(f32[1, 1, 1024])`,\np_trunk_patch_embed_proj_weight: `TorchScriptTensor(f32[1024, 3, 16, 16])`,\np_trunk_patch_embed_proj_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_weight: `TorchScriptTensor(f32[3072, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_bias: `TorchScriptTensor(f32[3072])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_weight: `TorchScriptTensor(f32[1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_bias: `TorchScriptTensor(f32[1024])`,\n...\n)\n## Return values\n", + "text":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___2___attn_qkv_bias[name=p_getattr_l__self___trunk_blocks___2___attn_qkv_bias]. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"FxOnnxInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":414 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0008", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___2___attn_proj_weight[name=p_getattr_l__self___trunk_blocks___2___attn_proj_weight]. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature FxOnnxInterpreter.run_node\n- self: \n- node: fx.Node(p_getattr_l__self___trunk_blocks___2___attn_proj_weight)[placeholder]:Tensor(f32[1024, 1024])\n- fx_graph_module: torch.fx.GraphModule()\n- onnxfunction_dispatcher: \n- op_level_debug: False\n- onnxscript_graph: \n- onnxscript_tracer: \n- fx_name_to_onnxscript_value: Dict[length=32](\np_trunk_pos_embed: `TorchScriptTensor(f32[1, 1024, 1024])`,\np_trunk_attn_pool_latent: `TorchScriptTensor(f32[1, 1, 1024])`,\np_trunk_patch_embed_proj_weight: `TorchScriptTensor(f32[1024, 3, 16, 16])`,\np_trunk_patch_embed_proj_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_weight: `TorchScriptTensor(f32[3072, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_bias: `TorchScriptTensor(f32[3072])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_weight: `TorchScriptTensor(f32[1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_bias: `TorchScriptTensor(f32[1024])`,\n...\n)\n## Return values\n", + "text":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___2___attn_proj_weight[name=p_getattr_l__self___trunk_blocks___2___attn_proj_weight]. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"FxOnnxInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":414 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0008", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___2___attn_proj_bias[name=p_getattr_l__self___trunk_blocks___2___attn_proj_bias]. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature FxOnnxInterpreter.run_node\n- self: \n- node: fx.Node(p_getattr_l__self___trunk_blocks___2___attn_proj_bias)[placeholder]:Tensor(f32[1024])\n- fx_graph_module: torch.fx.GraphModule()\n- onnxfunction_dispatcher: \n- op_level_debug: False\n- onnxscript_graph: \n- onnxscript_tracer: \n- fx_name_to_onnxscript_value: Dict[length=33](\np_trunk_pos_embed: `TorchScriptTensor(f32[1, 1024, 1024])`,\np_trunk_attn_pool_latent: `TorchScriptTensor(f32[1, 1, 1024])`,\np_trunk_patch_embed_proj_weight: `TorchScriptTensor(f32[1024, 3, 16, 16])`,\np_trunk_patch_embed_proj_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_weight: `TorchScriptTensor(f32[3072, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_bias: `TorchScriptTensor(f32[3072])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_weight: `TorchScriptTensor(f32[1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_bias: `TorchScriptTensor(f32[1024])`,\n...\n)\n## Return values\n", + "text":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___2___attn_proj_bias[name=p_getattr_l__self___trunk_blocks___2___attn_proj_bias]. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"FxOnnxInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":414 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0008", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___2___norm2_weight[name=p_getattr_l__self___trunk_blocks___2___norm2_weight]. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature FxOnnxInterpreter.run_node\n- self: \n- node: fx.Node(p_getattr_l__self___trunk_blocks___2___norm2_weight)[placeholder]:Tensor(f32[1024])\n- fx_graph_module: torch.fx.GraphModule()\n- onnxfunction_dispatcher: \n- op_level_debug: False\n- onnxscript_graph: \n- onnxscript_tracer: \n- fx_name_to_onnxscript_value: Dict[length=34](\np_trunk_pos_embed: `TorchScriptTensor(f32[1, 1024, 1024])`,\np_trunk_attn_pool_latent: `TorchScriptTensor(f32[1, 1, 1024])`,\np_trunk_patch_embed_proj_weight: `TorchScriptTensor(f32[1024, 3, 16, 16])`,\np_trunk_patch_embed_proj_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_weight: `TorchScriptTensor(f32[3072, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_bias: `TorchScriptTensor(f32[3072])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_weight: `TorchScriptTensor(f32[1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_bias: `TorchScriptTensor(f32[1024])`,\n...\n)\n## Return values\n", + "text":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___2___norm2_weight[name=p_getattr_l__self___trunk_blocks___2___norm2_weight]. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"FxOnnxInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":414 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0008", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___2___norm2_bias[name=p_getattr_l__self___trunk_blocks___2___norm2_bias]. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature FxOnnxInterpreter.run_node\n- self: \n- node: fx.Node(p_getattr_l__self___trunk_blocks___2___norm2_bias)[placeholder]:Tensor(f32[1024])\n- fx_graph_module: torch.fx.GraphModule()\n- onnxfunction_dispatcher: \n- op_level_debug: False\n- onnxscript_graph: \n- onnxscript_tracer: \n- fx_name_to_onnxscript_value: Dict[length=35](\np_trunk_pos_embed: `TorchScriptTensor(f32[1, 1024, 1024])`,\np_trunk_attn_pool_latent: `TorchScriptTensor(f32[1, 1, 1024])`,\np_trunk_patch_embed_proj_weight: `TorchScriptTensor(f32[1024, 3, 16, 16])`,\np_trunk_patch_embed_proj_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_weight: `TorchScriptTensor(f32[3072, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_bias: `TorchScriptTensor(f32[3072])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_weight: `TorchScriptTensor(f32[1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_bias: `TorchScriptTensor(f32[1024])`,\n...\n)\n## Return values\n", + "text":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___2___norm2_bias[name=p_getattr_l__self___trunk_blocks___2___norm2_bias]. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"FxOnnxInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":414 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0008", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___2___mlp_fc1_weight[name=p_getattr_l__self___trunk_blocks___2___mlp_fc1_weight]. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature FxOnnxInterpreter.run_node\n- self: \n- node: fx.Node(p_getattr_l__self___trunk_blocks___2___mlp_fc1_weight)[placeholder]:Tensor(f32[4096, 1024])\n- fx_graph_module: torch.fx.GraphModule()\n- onnxfunction_dispatcher: \n- op_level_debug: False\n- onnxscript_graph: \n- onnxscript_tracer: \n- fx_name_to_onnxscript_value: Dict[length=36](\np_trunk_pos_embed: `TorchScriptTensor(f32[1, 1024, 1024])`,\np_trunk_attn_pool_latent: `TorchScriptTensor(f32[1, 1, 1024])`,\np_trunk_patch_embed_proj_weight: `TorchScriptTensor(f32[1024, 3, 16, 16])`,\np_trunk_patch_embed_proj_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_weight: `TorchScriptTensor(f32[3072, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_bias: `TorchScriptTensor(f32[3072])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_weight: `TorchScriptTensor(f32[1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_bias: `TorchScriptTensor(f32[1024])`,\n...\n)\n## Return values\n", + "text":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___2___mlp_fc1_weight[name=p_getattr_l__self___trunk_blocks___2___mlp_fc1_weight]. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"FxOnnxInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":414 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0008", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___2___mlp_fc1_bias[name=p_getattr_l__self___trunk_blocks___2___mlp_fc1_bias]. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature FxOnnxInterpreter.run_node\n- self: \n- node: fx.Node(p_getattr_l__self___trunk_blocks___2___mlp_fc1_bias)[placeholder]:Tensor(f32[4096])\n- fx_graph_module: torch.fx.GraphModule()\n- onnxfunction_dispatcher: \n- op_level_debug: False\n- onnxscript_graph: \n- onnxscript_tracer: \n- fx_name_to_onnxscript_value: Dict[length=37](\np_trunk_pos_embed: `TorchScriptTensor(f32[1, 1024, 1024])`,\np_trunk_attn_pool_latent: `TorchScriptTensor(f32[1, 1, 1024])`,\np_trunk_patch_embed_proj_weight: `TorchScriptTensor(f32[1024, 3, 16, 16])`,\np_trunk_patch_embed_proj_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_weight: `TorchScriptTensor(f32[3072, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_bias: `TorchScriptTensor(f32[3072])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_weight: `TorchScriptTensor(f32[1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_bias: `TorchScriptTensor(f32[1024])`,\n...\n)\n## Return values\n", + "text":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___2___mlp_fc1_bias[name=p_getattr_l__self___trunk_blocks___2___mlp_fc1_bias]. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"FxOnnxInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":414 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0008", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___2___mlp_fc2_weight[name=p_getattr_l__self___trunk_blocks___2___mlp_fc2_weight]. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature FxOnnxInterpreter.run_node\n- self: \n- node: fx.Node(p_getattr_l__self___trunk_blocks___2___mlp_fc2_weight)[placeholder]:Tensor(f32[1024, 4096])\n- fx_graph_module: torch.fx.GraphModule()\n- onnxfunction_dispatcher: \n- op_level_debug: False\n- onnxscript_graph: \n- onnxscript_tracer: \n- fx_name_to_onnxscript_value: Dict[length=38](\np_trunk_pos_embed: `TorchScriptTensor(f32[1, 1024, 1024])`,\np_trunk_attn_pool_latent: `TorchScriptTensor(f32[1, 1, 1024])`,\np_trunk_patch_embed_proj_weight: `TorchScriptTensor(f32[1024, 3, 16, 16])`,\np_trunk_patch_embed_proj_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_weight: `TorchScriptTensor(f32[3072, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_bias: `TorchScriptTensor(f32[3072])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_weight: `TorchScriptTensor(f32[1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_bias: `TorchScriptTensor(f32[1024])`,\n...\n)\n## Return values\n", + "text":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___2___mlp_fc2_weight[name=p_getattr_l__self___trunk_blocks___2___mlp_fc2_weight]. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"FxOnnxInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":414 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0008", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___2___mlp_fc2_bias[name=p_getattr_l__self___trunk_blocks___2___mlp_fc2_bias]. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature FxOnnxInterpreter.run_node\n- self: \n- node: fx.Node(p_getattr_l__self___trunk_blocks___2___mlp_fc2_bias)[placeholder]:Tensor(f32[1024])\n- fx_graph_module: torch.fx.GraphModule()\n- onnxfunction_dispatcher: \n- op_level_debug: False\n- onnxscript_graph: \n- onnxscript_tracer: \n- fx_name_to_onnxscript_value: Dict[length=39](\np_trunk_pos_embed: `TorchScriptTensor(f32[1, 1024, 1024])`,\np_trunk_attn_pool_latent: `TorchScriptTensor(f32[1, 1, 1024])`,\np_trunk_patch_embed_proj_weight: `TorchScriptTensor(f32[1024, 3, 16, 16])`,\np_trunk_patch_embed_proj_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_weight: `TorchScriptTensor(f32[3072, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_bias: `TorchScriptTensor(f32[3072])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_weight: `TorchScriptTensor(f32[1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_bias: `TorchScriptTensor(f32[1024])`,\n...\n)\n## Return values\n", + "text":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___2___mlp_fc2_bias[name=p_getattr_l__self___trunk_blocks___2___mlp_fc2_bias]. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"FxOnnxInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":414 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0008", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___3___norm1_weight[name=p_getattr_l__self___trunk_blocks___3___norm1_weight]. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature FxOnnxInterpreter.run_node\n- self: \n- node: fx.Node(p_getattr_l__self___trunk_blocks___3___norm1_weight)[placeholder]:Tensor(f32[1024])\n- fx_graph_module: torch.fx.GraphModule()\n- onnxfunction_dispatcher: \n- op_level_debug: False\n- onnxscript_graph: \n- onnxscript_tracer: \n- fx_name_to_onnxscript_value: Dict[length=40](\np_trunk_pos_embed: `TorchScriptTensor(f32[1, 1024, 1024])`,\np_trunk_attn_pool_latent: `TorchScriptTensor(f32[1, 1, 1024])`,\np_trunk_patch_embed_proj_weight: `TorchScriptTensor(f32[1024, 3, 16, 16])`,\np_trunk_patch_embed_proj_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_weight: `TorchScriptTensor(f32[3072, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_bias: `TorchScriptTensor(f32[3072])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_weight: `TorchScriptTensor(f32[1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_bias: `TorchScriptTensor(f32[1024])`,\n...\n)\n## Return values\n", + "text":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___3___norm1_weight[name=p_getattr_l__self___trunk_blocks___3___norm1_weight]. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"FxOnnxInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":414 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0008", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___3___norm1_bias[name=p_getattr_l__self___trunk_blocks___3___norm1_bias]. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature FxOnnxInterpreter.run_node\n- self: \n- node: fx.Node(p_getattr_l__self___trunk_blocks___3___norm1_bias)[placeholder]:Tensor(f32[1024])\n- fx_graph_module: torch.fx.GraphModule()\n- onnxfunction_dispatcher: \n- op_level_debug: False\n- onnxscript_graph: \n- onnxscript_tracer: \n- fx_name_to_onnxscript_value: Dict[length=41](\np_trunk_pos_embed: `TorchScriptTensor(f32[1, 1024, 1024])`,\np_trunk_attn_pool_latent: `TorchScriptTensor(f32[1, 1, 1024])`,\np_trunk_patch_embed_proj_weight: `TorchScriptTensor(f32[1024, 3, 16, 16])`,\np_trunk_patch_embed_proj_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_weight: `TorchScriptTensor(f32[3072, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_bias: `TorchScriptTensor(f32[3072])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_weight: `TorchScriptTensor(f32[1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_bias: `TorchScriptTensor(f32[1024])`,\n...\n)\n## Return values\n", + "text":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___3___norm1_bias[name=p_getattr_l__self___trunk_blocks___3___norm1_bias]. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"FxOnnxInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":414 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0008", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___3___attn_qkv_weight[name=p_getattr_l__self___trunk_blocks___3___attn_qkv_weight]. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature FxOnnxInterpreter.run_node\n- self: \n- node: fx.Node(p_getattr_l__self___trunk_blocks___3___attn_qkv_weight)[placeholder]:Tensor(f32[3072, 1024])\n- fx_graph_module: torch.fx.GraphModule()\n- onnxfunction_dispatcher: \n- op_level_debug: False\n- onnxscript_graph: \n- onnxscript_tracer: \n- fx_name_to_onnxscript_value: Dict[length=42](\np_trunk_pos_embed: `TorchScriptTensor(f32[1, 1024, 1024])`,\np_trunk_attn_pool_latent: `TorchScriptTensor(f32[1, 1, 1024])`,\np_trunk_patch_embed_proj_weight: `TorchScriptTensor(f32[1024, 3, 16, 16])`,\np_trunk_patch_embed_proj_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_weight: `TorchScriptTensor(f32[3072, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_bias: `TorchScriptTensor(f32[3072])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_weight: `TorchScriptTensor(f32[1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_bias: `TorchScriptTensor(f32[1024])`,\n...\n)\n## Return values\n", + "text":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___3___attn_qkv_weight[name=p_getattr_l__self___trunk_blocks___3___attn_qkv_weight]. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"FxOnnxInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":414 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0008", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___3___attn_qkv_bias[name=p_getattr_l__self___trunk_blocks___3___attn_qkv_bias]. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature FxOnnxInterpreter.run_node\n- self: \n- node: fx.Node(p_getattr_l__self___trunk_blocks___3___attn_qkv_bias)[placeholder]:Tensor(f32[3072])\n- fx_graph_module: torch.fx.GraphModule()\n- onnxfunction_dispatcher: \n- op_level_debug: False\n- onnxscript_graph: \n- onnxscript_tracer: \n- fx_name_to_onnxscript_value: Dict[length=43](\np_trunk_pos_embed: `TorchScriptTensor(f32[1, 1024, 1024])`,\np_trunk_attn_pool_latent: `TorchScriptTensor(f32[1, 1, 1024])`,\np_trunk_patch_embed_proj_weight: `TorchScriptTensor(f32[1024, 3, 16, 16])`,\np_trunk_patch_embed_proj_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_weight: `TorchScriptTensor(f32[3072, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_bias: `TorchScriptTensor(f32[3072])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_weight: `TorchScriptTensor(f32[1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_bias: `TorchScriptTensor(f32[1024])`,\n...\n)\n## Return values\n", + "text":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___3___attn_qkv_bias[name=p_getattr_l__self___trunk_blocks___3___attn_qkv_bias]. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"FxOnnxInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":414 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0008", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___3___attn_proj_weight[name=p_getattr_l__self___trunk_blocks___3___attn_proj_weight]. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature FxOnnxInterpreter.run_node\n- self: \n- node: fx.Node(p_getattr_l__self___trunk_blocks___3___attn_proj_weight)[placeholder]:Tensor(f32[1024, 1024])\n- fx_graph_module: torch.fx.GraphModule()\n- onnxfunction_dispatcher: \n- op_level_debug: False\n- onnxscript_graph: \n- onnxscript_tracer: \n- fx_name_to_onnxscript_value: Dict[length=44](\np_trunk_pos_embed: `TorchScriptTensor(f32[1, 1024, 1024])`,\np_trunk_attn_pool_latent: `TorchScriptTensor(f32[1, 1, 1024])`,\np_trunk_patch_embed_proj_weight: `TorchScriptTensor(f32[1024, 3, 16, 16])`,\np_trunk_patch_embed_proj_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_weight: `TorchScriptTensor(f32[3072, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_bias: `TorchScriptTensor(f32[3072])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_weight: `TorchScriptTensor(f32[1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_bias: `TorchScriptTensor(f32[1024])`,\n...\n)\n## Return values\n", + "text":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___3___attn_proj_weight[name=p_getattr_l__self___trunk_blocks___3___attn_proj_weight]. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"FxOnnxInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":414 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0008", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___3___attn_proj_bias[name=p_getattr_l__self___trunk_blocks___3___attn_proj_bias]. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature FxOnnxInterpreter.run_node\n- self: \n- node: fx.Node(p_getattr_l__self___trunk_blocks___3___attn_proj_bias)[placeholder]:Tensor(f32[1024])\n- fx_graph_module: torch.fx.GraphModule()\n- onnxfunction_dispatcher: \n- op_level_debug: False\n- onnxscript_graph: \n- onnxscript_tracer: \n- fx_name_to_onnxscript_value: Dict[length=45](\np_trunk_pos_embed: `TorchScriptTensor(f32[1, 1024, 1024])`,\np_trunk_attn_pool_latent: `TorchScriptTensor(f32[1, 1, 1024])`,\np_trunk_patch_embed_proj_weight: `TorchScriptTensor(f32[1024, 3, 16, 16])`,\np_trunk_patch_embed_proj_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_weight: `TorchScriptTensor(f32[3072, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_bias: `TorchScriptTensor(f32[3072])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_weight: `TorchScriptTensor(f32[1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_bias: `TorchScriptTensor(f32[1024])`,\n...\n)\n## Return values\n", + "text":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___3___attn_proj_bias[name=p_getattr_l__self___trunk_blocks___3___attn_proj_bias]. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"FxOnnxInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":414 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0008", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___3___norm2_weight[name=p_getattr_l__self___trunk_blocks___3___norm2_weight]. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature FxOnnxInterpreter.run_node\n- self: \n- node: fx.Node(p_getattr_l__self___trunk_blocks___3___norm2_weight)[placeholder]:Tensor(f32[1024])\n- fx_graph_module: torch.fx.GraphModule()\n- onnxfunction_dispatcher: \n- op_level_debug: False\n- onnxscript_graph: \n- onnxscript_tracer: \n- fx_name_to_onnxscript_value: Dict[length=46](\np_trunk_pos_embed: `TorchScriptTensor(f32[1, 1024, 1024])`,\np_trunk_attn_pool_latent: `TorchScriptTensor(f32[1, 1, 1024])`,\np_trunk_patch_embed_proj_weight: `TorchScriptTensor(f32[1024, 3, 16, 16])`,\np_trunk_patch_embed_proj_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_weight: `TorchScriptTensor(f32[3072, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_bias: `TorchScriptTensor(f32[3072])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_weight: `TorchScriptTensor(f32[1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_bias: `TorchScriptTensor(f32[1024])`,\n...\n)\n## Return values\n", + "text":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___3___norm2_weight[name=p_getattr_l__self___trunk_blocks___3___norm2_weight]. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"FxOnnxInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":414 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0008", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___3___norm2_bias[name=p_getattr_l__self___trunk_blocks___3___norm2_bias]. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature FxOnnxInterpreter.run_node\n- self: \n- node: fx.Node(p_getattr_l__self___trunk_blocks___3___norm2_bias)[placeholder]:Tensor(f32[1024])\n- fx_graph_module: torch.fx.GraphModule()\n- onnxfunction_dispatcher: \n- op_level_debug: False\n- onnxscript_graph: \n- onnxscript_tracer: \n- fx_name_to_onnxscript_value: Dict[length=47](\np_trunk_pos_embed: `TorchScriptTensor(f32[1, 1024, 1024])`,\np_trunk_attn_pool_latent: `TorchScriptTensor(f32[1, 1, 1024])`,\np_trunk_patch_embed_proj_weight: `TorchScriptTensor(f32[1024, 3, 16, 16])`,\np_trunk_patch_embed_proj_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_weight: `TorchScriptTensor(f32[3072, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_bias: `TorchScriptTensor(f32[3072])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_weight: `TorchScriptTensor(f32[1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_bias: `TorchScriptTensor(f32[1024])`,\n...\n)\n## Return values\n", + "text":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___3___norm2_bias[name=p_getattr_l__self___trunk_blocks___3___norm2_bias]. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"FxOnnxInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":414 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0008", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___3___mlp_fc1_weight[name=p_getattr_l__self___trunk_blocks___3___mlp_fc1_weight]. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature FxOnnxInterpreter.run_node\n- self: \n- node: fx.Node(p_getattr_l__self___trunk_blocks___3___mlp_fc1_weight)[placeholder]:Tensor(f32[4096, 1024])\n- fx_graph_module: torch.fx.GraphModule()\n- onnxfunction_dispatcher: \n- op_level_debug: False\n- onnxscript_graph: \n- onnxscript_tracer: \n- fx_name_to_onnxscript_value: Dict[length=48](\np_trunk_pos_embed: `TorchScriptTensor(f32[1, 1024, 1024])`,\np_trunk_attn_pool_latent: `TorchScriptTensor(f32[1, 1, 1024])`,\np_trunk_patch_embed_proj_weight: `TorchScriptTensor(f32[1024, 3, 16, 16])`,\np_trunk_patch_embed_proj_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_weight: `TorchScriptTensor(f32[3072, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_bias: `TorchScriptTensor(f32[3072])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_weight: `TorchScriptTensor(f32[1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_bias: `TorchScriptTensor(f32[1024])`,\n...\n)\n## Return values\n", + "text":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___3___mlp_fc1_weight[name=p_getattr_l__self___trunk_blocks___3___mlp_fc1_weight]. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"FxOnnxInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":414 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0008", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___3___mlp_fc1_bias[name=p_getattr_l__self___trunk_blocks___3___mlp_fc1_bias]. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature FxOnnxInterpreter.run_node\n- self: \n- node: fx.Node(p_getattr_l__self___trunk_blocks___3___mlp_fc1_bias)[placeholder]:Tensor(f32[4096])\n- fx_graph_module: torch.fx.GraphModule()\n- onnxfunction_dispatcher: \n- op_level_debug: False\n- onnxscript_graph: \n- onnxscript_tracer: \n- fx_name_to_onnxscript_value: Dict[length=49](\np_trunk_pos_embed: `TorchScriptTensor(f32[1, 1024, 1024])`,\np_trunk_attn_pool_latent: `TorchScriptTensor(f32[1, 1, 1024])`,\np_trunk_patch_embed_proj_weight: `TorchScriptTensor(f32[1024, 3, 16, 16])`,\np_trunk_patch_embed_proj_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_weight: `TorchScriptTensor(f32[3072, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_bias: `TorchScriptTensor(f32[3072])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_weight: `TorchScriptTensor(f32[1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_bias: `TorchScriptTensor(f32[1024])`,\n...\n)\n## Return values\n", + "text":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___3___mlp_fc1_bias[name=p_getattr_l__self___trunk_blocks___3___mlp_fc1_bias]. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"FxOnnxInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":414 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0008", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___3___mlp_fc2_weight[name=p_getattr_l__self___trunk_blocks___3___mlp_fc2_weight]. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature FxOnnxInterpreter.run_node\n- self: \n- node: fx.Node(p_getattr_l__self___trunk_blocks___3___mlp_fc2_weight)[placeholder]:Tensor(f32[1024, 4096])\n- fx_graph_module: torch.fx.GraphModule()\n- onnxfunction_dispatcher: \n- op_level_debug: False\n- onnxscript_graph: \n- onnxscript_tracer: \n- fx_name_to_onnxscript_value: Dict[length=50](\np_trunk_pos_embed: `TorchScriptTensor(f32[1, 1024, 1024])`,\np_trunk_attn_pool_latent: `TorchScriptTensor(f32[1, 1, 1024])`,\np_trunk_patch_embed_proj_weight: `TorchScriptTensor(f32[1024, 3, 16, 16])`,\np_trunk_patch_embed_proj_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_weight: `TorchScriptTensor(f32[3072, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_bias: `TorchScriptTensor(f32[3072])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_weight: `TorchScriptTensor(f32[1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_bias: `TorchScriptTensor(f32[1024])`,\n...\n)\n## Return values\n", + "text":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___3___mlp_fc2_weight[name=p_getattr_l__self___trunk_blocks___3___mlp_fc2_weight]. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"FxOnnxInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":414 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0008", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___3___mlp_fc2_bias[name=p_getattr_l__self___trunk_blocks___3___mlp_fc2_bias]. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature FxOnnxInterpreter.run_node\n- self: \n- node: fx.Node(p_getattr_l__self___trunk_blocks___3___mlp_fc2_bias)[placeholder]:Tensor(f32[1024])\n- fx_graph_module: torch.fx.GraphModule()\n- onnxfunction_dispatcher: \n- op_level_debug: False\n- onnxscript_graph: \n- onnxscript_tracer: \n- fx_name_to_onnxscript_value: Dict[length=51](\np_trunk_pos_embed: `TorchScriptTensor(f32[1, 1024, 1024])`,\np_trunk_attn_pool_latent: `TorchScriptTensor(f32[1, 1, 1024])`,\np_trunk_patch_embed_proj_weight: `TorchScriptTensor(f32[1024, 3, 16, 16])`,\np_trunk_patch_embed_proj_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_weight: `TorchScriptTensor(f32[3072, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_bias: `TorchScriptTensor(f32[3072])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_weight: `TorchScriptTensor(f32[1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_bias: `TorchScriptTensor(f32[1024])`,\n...\n)\n## Return values\n", + "text":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___3___mlp_fc2_bias[name=p_getattr_l__self___trunk_blocks___3___mlp_fc2_bias]. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"FxOnnxInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":414 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0008", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___4___norm1_weight[name=p_getattr_l__self___trunk_blocks___4___norm1_weight]. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature FxOnnxInterpreter.run_node\n- self: \n- node: fx.Node(p_getattr_l__self___trunk_blocks___4___norm1_weight)[placeholder]:Tensor(f32[1024])\n- fx_graph_module: torch.fx.GraphModule()\n- onnxfunction_dispatcher: \n- op_level_debug: False\n- onnxscript_graph: \n- onnxscript_tracer: \n- fx_name_to_onnxscript_value: Dict[length=52](\np_trunk_pos_embed: `TorchScriptTensor(f32[1, 1024, 1024])`,\np_trunk_attn_pool_latent: `TorchScriptTensor(f32[1, 1, 1024])`,\np_trunk_patch_embed_proj_weight: `TorchScriptTensor(f32[1024, 3, 16, 16])`,\np_trunk_patch_embed_proj_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_weight: `TorchScriptTensor(f32[3072, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_bias: `TorchScriptTensor(f32[3072])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_weight: `TorchScriptTensor(f32[1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_bias: `TorchScriptTensor(f32[1024])`,\n...\n)\n## Return values\n", + "text":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___4___norm1_weight[name=p_getattr_l__self___trunk_blocks___4___norm1_weight]. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"FxOnnxInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":414 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0008", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___4___norm1_bias[name=p_getattr_l__self___trunk_blocks___4___norm1_bias]. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature FxOnnxInterpreter.run_node\n- self: \n- node: fx.Node(p_getattr_l__self___trunk_blocks___4___norm1_bias)[placeholder]:Tensor(f32[1024])\n- fx_graph_module: torch.fx.GraphModule()\n- onnxfunction_dispatcher: \n- op_level_debug: False\n- onnxscript_graph: \n- onnxscript_tracer: \n- fx_name_to_onnxscript_value: Dict[length=53](\np_trunk_pos_embed: `TorchScriptTensor(f32[1, 1024, 1024])`,\np_trunk_attn_pool_latent: `TorchScriptTensor(f32[1, 1, 1024])`,\np_trunk_patch_embed_proj_weight: `TorchScriptTensor(f32[1024, 3, 16, 16])`,\np_trunk_patch_embed_proj_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_weight: `TorchScriptTensor(f32[3072, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_bias: `TorchScriptTensor(f32[3072])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_weight: `TorchScriptTensor(f32[1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_bias: `TorchScriptTensor(f32[1024])`,\n...\n)\n## Return values\n", + "text":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___4___norm1_bias[name=p_getattr_l__self___trunk_blocks___4___norm1_bias]. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"FxOnnxInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":414 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0008", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___4___attn_qkv_weight[name=p_getattr_l__self___trunk_blocks___4___attn_qkv_weight]. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature FxOnnxInterpreter.run_node\n- self: \n- node: fx.Node(p_getattr_l__self___trunk_blocks___4___attn_qkv_weight)[placeholder]:Tensor(f32[3072, 1024])\n- fx_graph_module: torch.fx.GraphModule()\n- onnxfunction_dispatcher: \n- op_level_debug: False\n- onnxscript_graph: \n- onnxscript_tracer: \n- fx_name_to_onnxscript_value: Dict[length=54](\np_trunk_pos_embed: `TorchScriptTensor(f32[1, 1024, 1024])`,\np_trunk_attn_pool_latent: `TorchScriptTensor(f32[1, 1, 1024])`,\np_trunk_patch_embed_proj_weight: `TorchScriptTensor(f32[1024, 3, 16, 16])`,\np_trunk_patch_embed_proj_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_weight: `TorchScriptTensor(f32[3072, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_bias: `TorchScriptTensor(f32[3072])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_weight: `TorchScriptTensor(f32[1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_bias: `TorchScriptTensor(f32[1024])`,\n...\n)\n## Return values\n", + "text":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___4___attn_qkv_weight[name=p_getattr_l__self___trunk_blocks___4___attn_qkv_weight]. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"FxOnnxInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":414 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0008", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___4___attn_qkv_bias[name=p_getattr_l__self___trunk_blocks___4___attn_qkv_bias]. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature FxOnnxInterpreter.run_node\n- self: \n- node: fx.Node(p_getattr_l__self___trunk_blocks___4___attn_qkv_bias)[placeholder]:Tensor(f32[3072])\n- fx_graph_module: torch.fx.GraphModule()\n- onnxfunction_dispatcher: \n- op_level_debug: False\n- onnxscript_graph: \n- onnxscript_tracer: \n- fx_name_to_onnxscript_value: Dict[length=55](\np_trunk_pos_embed: `TorchScriptTensor(f32[1, 1024, 1024])`,\np_trunk_attn_pool_latent: `TorchScriptTensor(f32[1, 1, 1024])`,\np_trunk_patch_embed_proj_weight: `TorchScriptTensor(f32[1024, 3, 16, 16])`,\np_trunk_patch_embed_proj_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_weight: `TorchScriptTensor(f32[3072, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_bias: `TorchScriptTensor(f32[3072])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_weight: `TorchScriptTensor(f32[1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_bias: `TorchScriptTensor(f32[1024])`,\n...\n)\n## Return values\n", + "text":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___4___attn_qkv_bias[name=p_getattr_l__self___trunk_blocks___4___attn_qkv_bias]. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"FxOnnxInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":414 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0008", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___4___attn_proj_weight[name=p_getattr_l__self___trunk_blocks___4___attn_proj_weight]. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature FxOnnxInterpreter.run_node\n- self: \n- node: fx.Node(p_getattr_l__self___trunk_blocks___4___attn_proj_weight)[placeholder]:Tensor(f32[1024, 1024])\n- fx_graph_module: torch.fx.GraphModule()\n- onnxfunction_dispatcher: \n- op_level_debug: False\n- onnxscript_graph: \n- onnxscript_tracer: \n- fx_name_to_onnxscript_value: Dict[length=56](\np_trunk_pos_embed: `TorchScriptTensor(f32[1, 1024, 1024])`,\np_trunk_attn_pool_latent: `TorchScriptTensor(f32[1, 1, 1024])`,\np_trunk_patch_embed_proj_weight: `TorchScriptTensor(f32[1024, 3, 16, 16])`,\np_trunk_patch_embed_proj_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_weight: `TorchScriptTensor(f32[3072, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_bias: `TorchScriptTensor(f32[3072])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_weight: `TorchScriptTensor(f32[1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_bias: `TorchScriptTensor(f32[1024])`,\n...\n)\n## Return values\n", + "text":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___4___attn_proj_weight[name=p_getattr_l__self___trunk_blocks___4___attn_proj_weight]. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"FxOnnxInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":414 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0008", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___4___attn_proj_bias[name=p_getattr_l__self___trunk_blocks___4___attn_proj_bias]. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature FxOnnxInterpreter.run_node\n- self: \n- node: fx.Node(p_getattr_l__self___trunk_blocks___4___attn_proj_bias)[placeholder]:Tensor(f32[1024])\n- fx_graph_module: torch.fx.GraphModule()\n- onnxfunction_dispatcher: \n- op_level_debug: False\n- onnxscript_graph: \n- onnxscript_tracer: \n- fx_name_to_onnxscript_value: Dict[length=57](\np_trunk_pos_embed: `TorchScriptTensor(f32[1, 1024, 1024])`,\np_trunk_attn_pool_latent: `TorchScriptTensor(f32[1, 1, 1024])`,\np_trunk_patch_embed_proj_weight: `TorchScriptTensor(f32[1024, 3, 16, 16])`,\np_trunk_patch_embed_proj_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_weight: `TorchScriptTensor(f32[3072, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_bias: `TorchScriptTensor(f32[3072])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_weight: `TorchScriptTensor(f32[1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_bias: `TorchScriptTensor(f32[1024])`,\n...\n)\n## Return values\n", + "text":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___4___attn_proj_bias[name=p_getattr_l__self___trunk_blocks___4___attn_proj_bias]. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"FxOnnxInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":414 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0008", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___4___norm2_weight[name=p_getattr_l__self___trunk_blocks___4___norm2_weight]. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature FxOnnxInterpreter.run_node\n- self: \n- node: fx.Node(p_getattr_l__self___trunk_blocks___4___norm2_weight)[placeholder]:Tensor(f32[1024])\n- fx_graph_module: torch.fx.GraphModule()\n- onnxfunction_dispatcher: \n- op_level_debug: False\n- onnxscript_graph: \n- onnxscript_tracer: \n- fx_name_to_onnxscript_value: Dict[length=58](\np_trunk_pos_embed: `TorchScriptTensor(f32[1, 1024, 1024])`,\np_trunk_attn_pool_latent: `TorchScriptTensor(f32[1, 1, 1024])`,\np_trunk_patch_embed_proj_weight: `TorchScriptTensor(f32[1024, 3, 16, 16])`,\np_trunk_patch_embed_proj_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_weight: `TorchScriptTensor(f32[3072, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_bias: `TorchScriptTensor(f32[3072])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_weight: `TorchScriptTensor(f32[1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_bias: `TorchScriptTensor(f32[1024])`,\n...\n)\n## Return values\n", + "text":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___4___norm2_weight[name=p_getattr_l__self___trunk_blocks___4___norm2_weight]. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"FxOnnxInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":414 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0008", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___4___norm2_bias[name=p_getattr_l__self___trunk_blocks___4___norm2_bias]. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature FxOnnxInterpreter.run_node\n- self: \n- node: fx.Node(p_getattr_l__self___trunk_blocks___4___norm2_bias)[placeholder]:Tensor(f32[1024])\n- fx_graph_module: torch.fx.GraphModule()\n- onnxfunction_dispatcher: \n- op_level_debug: False\n- onnxscript_graph: \n- onnxscript_tracer: \n- fx_name_to_onnxscript_value: Dict[length=59](\np_trunk_pos_embed: `TorchScriptTensor(f32[1, 1024, 1024])`,\np_trunk_attn_pool_latent: `TorchScriptTensor(f32[1, 1, 1024])`,\np_trunk_patch_embed_proj_weight: `TorchScriptTensor(f32[1024, 3, 16, 16])`,\np_trunk_patch_embed_proj_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_weight: `TorchScriptTensor(f32[3072, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_bias: `TorchScriptTensor(f32[3072])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_weight: `TorchScriptTensor(f32[1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_bias: `TorchScriptTensor(f32[1024])`,\n...\n)\n## Return values\n", + "text":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___4___norm2_bias[name=p_getattr_l__self___trunk_blocks___4___norm2_bias]. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"FxOnnxInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":414 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0008", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___4___mlp_fc1_weight[name=p_getattr_l__self___trunk_blocks___4___mlp_fc1_weight]. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature FxOnnxInterpreter.run_node\n- self: \n- node: fx.Node(p_getattr_l__self___trunk_blocks___4___mlp_fc1_weight)[placeholder]:Tensor(f32[4096, 1024])\n- fx_graph_module: torch.fx.GraphModule()\n- onnxfunction_dispatcher: \n- op_level_debug: False\n- onnxscript_graph: \n- onnxscript_tracer: \n- fx_name_to_onnxscript_value: Dict[length=60](\np_trunk_pos_embed: `TorchScriptTensor(f32[1, 1024, 1024])`,\np_trunk_attn_pool_latent: `TorchScriptTensor(f32[1, 1, 1024])`,\np_trunk_patch_embed_proj_weight: `TorchScriptTensor(f32[1024, 3, 16, 16])`,\np_trunk_patch_embed_proj_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_weight: `TorchScriptTensor(f32[3072, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_bias: `TorchScriptTensor(f32[3072])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_weight: `TorchScriptTensor(f32[1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_bias: `TorchScriptTensor(f32[1024])`,\n...\n)\n## Return values\n", + "text":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___4___mlp_fc1_weight[name=p_getattr_l__self___trunk_blocks___4___mlp_fc1_weight]. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"FxOnnxInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":414 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0008", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___4___mlp_fc1_bias[name=p_getattr_l__self___trunk_blocks___4___mlp_fc1_bias]. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature FxOnnxInterpreter.run_node\n- self: \n- node: fx.Node(p_getattr_l__self___trunk_blocks___4___mlp_fc1_bias)[placeholder]:Tensor(f32[4096])\n- fx_graph_module: torch.fx.GraphModule()\n- onnxfunction_dispatcher: \n- op_level_debug: False\n- onnxscript_graph: \n- onnxscript_tracer: \n- fx_name_to_onnxscript_value: Dict[length=61](\np_trunk_pos_embed: `TorchScriptTensor(f32[1, 1024, 1024])`,\np_trunk_attn_pool_latent: `TorchScriptTensor(f32[1, 1, 1024])`,\np_trunk_patch_embed_proj_weight: `TorchScriptTensor(f32[1024, 3, 16, 16])`,\np_trunk_patch_embed_proj_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_weight: `TorchScriptTensor(f32[3072, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_bias: `TorchScriptTensor(f32[3072])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_weight: `TorchScriptTensor(f32[1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_bias: `TorchScriptTensor(f32[1024])`,\n...\n)\n## Return values\n", + "text":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___4___mlp_fc1_bias[name=p_getattr_l__self___trunk_blocks___4___mlp_fc1_bias]. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"FxOnnxInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":414 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0008", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___4___mlp_fc2_weight[name=p_getattr_l__self___trunk_blocks___4___mlp_fc2_weight]. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature FxOnnxInterpreter.run_node\n- self: \n- node: fx.Node(p_getattr_l__self___trunk_blocks___4___mlp_fc2_weight)[placeholder]:Tensor(f32[1024, 4096])\n- fx_graph_module: torch.fx.GraphModule()\n- onnxfunction_dispatcher: \n- op_level_debug: False\n- onnxscript_graph: \n- onnxscript_tracer: \n- fx_name_to_onnxscript_value: Dict[length=62](\np_trunk_pos_embed: `TorchScriptTensor(f32[1, 1024, 1024])`,\np_trunk_attn_pool_latent: `TorchScriptTensor(f32[1, 1, 1024])`,\np_trunk_patch_embed_proj_weight: `TorchScriptTensor(f32[1024, 3, 16, 16])`,\np_trunk_patch_embed_proj_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_weight: `TorchScriptTensor(f32[3072, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_bias: `TorchScriptTensor(f32[3072])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_weight: `TorchScriptTensor(f32[1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_bias: `TorchScriptTensor(f32[1024])`,\n...\n)\n## Return values\n", + "text":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___4___mlp_fc2_weight[name=p_getattr_l__self___trunk_blocks___4___mlp_fc2_weight]. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"FxOnnxInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":414 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0008", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___4___mlp_fc2_bias[name=p_getattr_l__self___trunk_blocks___4___mlp_fc2_bias]. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature FxOnnxInterpreter.run_node\n- self: \n- node: fx.Node(p_getattr_l__self___trunk_blocks___4___mlp_fc2_bias)[placeholder]:Tensor(f32[1024])\n- fx_graph_module: torch.fx.GraphModule()\n- onnxfunction_dispatcher: \n- op_level_debug: False\n- onnxscript_graph: \n- onnxscript_tracer: \n- fx_name_to_onnxscript_value: Dict[length=63](\np_trunk_pos_embed: `TorchScriptTensor(f32[1, 1024, 1024])`,\np_trunk_attn_pool_latent: `TorchScriptTensor(f32[1, 1, 1024])`,\np_trunk_patch_embed_proj_weight: `TorchScriptTensor(f32[1024, 3, 16, 16])`,\np_trunk_patch_embed_proj_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_weight: `TorchScriptTensor(f32[3072, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_bias: `TorchScriptTensor(f32[3072])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_weight: `TorchScriptTensor(f32[1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_bias: `TorchScriptTensor(f32[1024])`,\n...\n)\n## Return values\n", + "text":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___4___mlp_fc2_bias[name=p_getattr_l__self___trunk_blocks___4___mlp_fc2_bias]. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"FxOnnxInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":414 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0008", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___5___norm1_weight[name=p_getattr_l__self___trunk_blocks___5___norm1_weight]. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature FxOnnxInterpreter.run_node\n- self: \n- node: fx.Node(p_getattr_l__self___trunk_blocks___5___norm1_weight)[placeholder]:Tensor(f32[1024])\n- fx_graph_module: torch.fx.GraphModule()\n- onnxfunction_dispatcher: \n- op_level_debug: False\n- onnxscript_graph: \n- onnxscript_tracer: \n- fx_name_to_onnxscript_value: Dict[length=64](\np_trunk_pos_embed: `TorchScriptTensor(f32[1, 1024, 1024])`,\np_trunk_attn_pool_latent: `TorchScriptTensor(f32[1, 1, 1024])`,\np_trunk_patch_embed_proj_weight: `TorchScriptTensor(f32[1024, 3, 16, 16])`,\np_trunk_patch_embed_proj_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_weight: `TorchScriptTensor(f32[3072, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_bias: `TorchScriptTensor(f32[3072])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_weight: `TorchScriptTensor(f32[1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_bias: `TorchScriptTensor(f32[1024])`,\n...\n)\n## Return values\n", + "text":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___5___norm1_weight[name=p_getattr_l__self___trunk_blocks___5___norm1_weight]. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"FxOnnxInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":414 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0008", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___5___norm1_bias[name=p_getattr_l__self___trunk_blocks___5___norm1_bias]. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature FxOnnxInterpreter.run_node\n- self: \n- node: fx.Node(p_getattr_l__self___trunk_blocks___5___norm1_bias)[placeholder]:Tensor(f32[1024])\n- fx_graph_module: torch.fx.GraphModule()\n- onnxfunction_dispatcher: \n- op_level_debug: False\n- onnxscript_graph: \n- onnxscript_tracer: \n- fx_name_to_onnxscript_value: Dict[length=65](\np_trunk_pos_embed: `TorchScriptTensor(f32[1, 1024, 1024])`,\np_trunk_attn_pool_latent: `TorchScriptTensor(f32[1, 1, 1024])`,\np_trunk_patch_embed_proj_weight: `TorchScriptTensor(f32[1024, 3, 16, 16])`,\np_trunk_patch_embed_proj_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_weight: `TorchScriptTensor(f32[3072, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_bias: `TorchScriptTensor(f32[3072])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_weight: `TorchScriptTensor(f32[1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_bias: `TorchScriptTensor(f32[1024])`,\n...\n)\n## Return values\n", + "text":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___5___norm1_bias[name=p_getattr_l__self___trunk_blocks___5___norm1_bias]. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"FxOnnxInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":414 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0008", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___5___attn_qkv_weight[name=p_getattr_l__self___trunk_blocks___5___attn_qkv_weight]. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature FxOnnxInterpreter.run_node\n- self: \n- node: fx.Node(p_getattr_l__self___trunk_blocks___5___attn_qkv_weight)[placeholder]:Tensor(f32[3072, 1024])\n- fx_graph_module: torch.fx.GraphModule()\n- onnxfunction_dispatcher: \n- op_level_debug: False\n- onnxscript_graph: \n- onnxscript_tracer: \n- fx_name_to_onnxscript_value: Dict[length=66](\np_trunk_pos_embed: `TorchScriptTensor(f32[1, 1024, 1024])`,\np_trunk_attn_pool_latent: `TorchScriptTensor(f32[1, 1, 1024])`,\np_trunk_patch_embed_proj_weight: `TorchScriptTensor(f32[1024, 3, 16, 16])`,\np_trunk_patch_embed_proj_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_weight: `TorchScriptTensor(f32[3072, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_bias: `TorchScriptTensor(f32[3072])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_weight: `TorchScriptTensor(f32[1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_bias: `TorchScriptTensor(f32[1024])`,\n...\n)\n## Return values\n", + "text":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___5___attn_qkv_weight[name=p_getattr_l__self___trunk_blocks___5___attn_qkv_weight]. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"FxOnnxInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":414 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0008", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___5___attn_qkv_bias[name=p_getattr_l__self___trunk_blocks___5___attn_qkv_bias]. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature FxOnnxInterpreter.run_node\n- self: \n- node: fx.Node(p_getattr_l__self___trunk_blocks___5___attn_qkv_bias)[placeholder]:Tensor(f32[3072])\n- fx_graph_module: torch.fx.GraphModule()\n- onnxfunction_dispatcher: \n- op_level_debug: False\n- onnxscript_graph: \n- onnxscript_tracer: \n- fx_name_to_onnxscript_value: Dict[length=67](\np_trunk_pos_embed: `TorchScriptTensor(f32[1, 1024, 1024])`,\np_trunk_attn_pool_latent: `TorchScriptTensor(f32[1, 1, 1024])`,\np_trunk_patch_embed_proj_weight: `TorchScriptTensor(f32[1024, 3, 16, 16])`,\np_trunk_patch_embed_proj_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_weight: `TorchScriptTensor(f32[3072, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_bias: `TorchScriptTensor(f32[3072])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_weight: `TorchScriptTensor(f32[1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_bias: `TorchScriptTensor(f32[1024])`,\n...\n)\n## Return values\n", + "text":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___5___attn_qkv_bias[name=p_getattr_l__self___trunk_blocks___5___attn_qkv_bias]. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"FxOnnxInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":414 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0008", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___5___attn_proj_weight[name=p_getattr_l__self___trunk_blocks___5___attn_proj_weight]. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature FxOnnxInterpreter.run_node\n- self: \n- node: fx.Node(p_getattr_l__self___trunk_blocks___5___attn_proj_weight)[placeholder]:Tensor(f32[1024, 1024])\n- fx_graph_module: torch.fx.GraphModule()\n- onnxfunction_dispatcher: \n- op_level_debug: False\n- onnxscript_graph: \n- onnxscript_tracer: \n- fx_name_to_onnxscript_value: Dict[length=68](\np_trunk_pos_embed: `TorchScriptTensor(f32[1, 1024, 1024])`,\np_trunk_attn_pool_latent: `TorchScriptTensor(f32[1, 1, 1024])`,\np_trunk_patch_embed_proj_weight: `TorchScriptTensor(f32[1024, 3, 16, 16])`,\np_trunk_patch_embed_proj_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_weight: `TorchScriptTensor(f32[3072, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_bias: `TorchScriptTensor(f32[3072])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_weight: `TorchScriptTensor(f32[1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_bias: `TorchScriptTensor(f32[1024])`,\n...\n)\n## Return values\n", + "text":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___5___attn_proj_weight[name=p_getattr_l__self___trunk_blocks___5___attn_proj_weight]. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"FxOnnxInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":414 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0008", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___5___attn_proj_bias[name=p_getattr_l__self___trunk_blocks___5___attn_proj_bias]. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature FxOnnxInterpreter.run_node\n- self: \n- node: fx.Node(p_getattr_l__self___trunk_blocks___5___attn_proj_bias)[placeholder]:Tensor(f32[1024])\n- fx_graph_module: torch.fx.GraphModule()\n- onnxfunction_dispatcher: \n- op_level_debug: False\n- onnxscript_graph: \n- onnxscript_tracer: \n- fx_name_to_onnxscript_value: Dict[length=69](\np_trunk_pos_embed: `TorchScriptTensor(f32[1, 1024, 1024])`,\np_trunk_attn_pool_latent: `TorchScriptTensor(f32[1, 1, 1024])`,\np_trunk_patch_embed_proj_weight: `TorchScriptTensor(f32[1024, 3, 16, 16])`,\np_trunk_patch_embed_proj_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_weight: `TorchScriptTensor(f32[3072, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_bias: `TorchScriptTensor(f32[3072])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_weight: `TorchScriptTensor(f32[1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_bias: `TorchScriptTensor(f32[1024])`,\n...\n)\n## Return values\n", + "text":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___5___attn_proj_bias[name=p_getattr_l__self___trunk_blocks___5___attn_proj_bias]. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"FxOnnxInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":414 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0008", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___5___norm2_weight[name=p_getattr_l__self___trunk_blocks___5___norm2_weight]. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature FxOnnxInterpreter.run_node\n- self: \n- node: fx.Node(p_getattr_l__self___trunk_blocks___5___norm2_weight)[placeholder]:Tensor(f32[1024])\n- fx_graph_module: torch.fx.GraphModule()\n- onnxfunction_dispatcher: \n- op_level_debug: False\n- onnxscript_graph: \n- onnxscript_tracer: \n- fx_name_to_onnxscript_value: Dict[length=70](\np_trunk_pos_embed: `TorchScriptTensor(f32[1, 1024, 1024])`,\np_trunk_attn_pool_latent: `TorchScriptTensor(f32[1, 1, 1024])`,\np_trunk_patch_embed_proj_weight: `TorchScriptTensor(f32[1024, 3, 16, 16])`,\np_trunk_patch_embed_proj_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_weight: `TorchScriptTensor(f32[3072, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_bias: `TorchScriptTensor(f32[3072])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_weight: `TorchScriptTensor(f32[1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_bias: `TorchScriptTensor(f32[1024])`,\n...\n)\n## Return values\n", + "text":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___5___norm2_weight[name=p_getattr_l__self___trunk_blocks___5___norm2_weight]. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"FxOnnxInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":414 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0008", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___5___norm2_bias[name=p_getattr_l__self___trunk_blocks___5___norm2_bias]. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature FxOnnxInterpreter.run_node\n- self: \n- node: fx.Node(p_getattr_l__self___trunk_blocks___5___norm2_bias)[placeholder]:Tensor(f32[1024])\n- fx_graph_module: torch.fx.GraphModule()\n- onnxfunction_dispatcher: \n- op_level_debug: False\n- onnxscript_graph: \n- onnxscript_tracer: \n- fx_name_to_onnxscript_value: Dict[length=71](\np_trunk_pos_embed: `TorchScriptTensor(f32[1, 1024, 1024])`,\np_trunk_attn_pool_latent: `TorchScriptTensor(f32[1, 1, 1024])`,\np_trunk_patch_embed_proj_weight: `TorchScriptTensor(f32[1024, 3, 16, 16])`,\np_trunk_patch_embed_proj_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_weight: `TorchScriptTensor(f32[3072, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_bias: `TorchScriptTensor(f32[3072])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_weight: `TorchScriptTensor(f32[1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_bias: `TorchScriptTensor(f32[1024])`,\n...\n)\n## Return values\n", + "text":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___5___norm2_bias[name=p_getattr_l__self___trunk_blocks___5___norm2_bias]. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"FxOnnxInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":414 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0008", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___5___mlp_fc1_weight[name=p_getattr_l__self___trunk_blocks___5___mlp_fc1_weight]. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature FxOnnxInterpreter.run_node\n- self: \n- node: fx.Node(p_getattr_l__self___trunk_blocks___5___mlp_fc1_weight)[placeholder]:Tensor(f32[4096, 1024])\n- fx_graph_module: torch.fx.GraphModule()\n- onnxfunction_dispatcher: \n- op_level_debug: False\n- onnxscript_graph: \n- onnxscript_tracer: \n- fx_name_to_onnxscript_value: Dict[length=72](\np_trunk_pos_embed: `TorchScriptTensor(f32[1, 1024, 1024])`,\np_trunk_attn_pool_latent: `TorchScriptTensor(f32[1, 1, 1024])`,\np_trunk_patch_embed_proj_weight: `TorchScriptTensor(f32[1024, 3, 16, 16])`,\np_trunk_patch_embed_proj_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_weight: `TorchScriptTensor(f32[3072, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_bias: `TorchScriptTensor(f32[3072])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_weight: `TorchScriptTensor(f32[1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_bias: `TorchScriptTensor(f32[1024])`,\n...\n)\n## Return values\n", + "text":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___5___mlp_fc1_weight[name=p_getattr_l__self___trunk_blocks___5___mlp_fc1_weight]. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"FxOnnxInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":414 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0008", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___5___mlp_fc1_bias[name=p_getattr_l__self___trunk_blocks___5___mlp_fc1_bias]. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature FxOnnxInterpreter.run_node\n- self: \n- node: fx.Node(p_getattr_l__self___trunk_blocks___5___mlp_fc1_bias)[placeholder]:Tensor(f32[4096])\n- fx_graph_module: torch.fx.GraphModule()\n- onnxfunction_dispatcher: \n- op_level_debug: False\n- onnxscript_graph: \n- onnxscript_tracer: \n- fx_name_to_onnxscript_value: Dict[length=73](\np_trunk_pos_embed: `TorchScriptTensor(f32[1, 1024, 1024])`,\np_trunk_attn_pool_latent: `TorchScriptTensor(f32[1, 1, 1024])`,\np_trunk_patch_embed_proj_weight: `TorchScriptTensor(f32[1024, 3, 16, 16])`,\np_trunk_patch_embed_proj_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_weight: `TorchScriptTensor(f32[3072, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_bias: `TorchScriptTensor(f32[3072])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_weight: `TorchScriptTensor(f32[1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_bias: `TorchScriptTensor(f32[1024])`,\n...\n)\n## Return values\n", + "text":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___5___mlp_fc1_bias[name=p_getattr_l__self___trunk_blocks___5___mlp_fc1_bias]. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"FxOnnxInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":414 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0008", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___5___mlp_fc2_weight[name=p_getattr_l__self___trunk_blocks___5___mlp_fc2_weight]. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature FxOnnxInterpreter.run_node\n- self: \n- node: fx.Node(p_getattr_l__self___trunk_blocks___5___mlp_fc2_weight)[placeholder]:Tensor(f32[1024, 4096])\n- fx_graph_module: torch.fx.GraphModule()\n- onnxfunction_dispatcher: \n- op_level_debug: False\n- onnxscript_graph: \n- onnxscript_tracer: \n- fx_name_to_onnxscript_value: Dict[length=74](\np_trunk_pos_embed: `TorchScriptTensor(f32[1, 1024, 1024])`,\np_trunk_attn_pool_latent: `TorchScriptTensor(f32[1, 1, 1024])`,\np_trunk_patch_embed_proj_weight: `TorchScriptTensor(f32[1024, 3, 16, 16])`,\np_trunk_patch_embed_proj_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_weight: `TorchScriptTensor(f32[3072, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_bias: `TorchScriptTensor(f32[3072])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_weight: `TorchScriptTensor(f32[1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_bias: `TorchScriptTensor(f32[1024])`,\n...\n)\n## Return values\n", + "text":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___5___mlp_fc2_weight[name=p_getattr_l__self___trunk_blocks___5___mlp_fc2_weight]. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"FxOnnxInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":414 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0008", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___5___mlp_fc2_bias[name=p_getattr_l__self___trunk_blocks___5___mlp_fc2_bias]. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature FxOnnxInterpreter.run_node\n- self: \n- node: fx.Node(p_getattr_l__self___trunk_blocks___5___mlp_fc2_bias)[placeholder]:Tensor(f32[1024])\n- fx_graph_module: torch.fx.GraphModule()\n- onnxfunction_dispatcher: \n- op_level_debug: False\n- onnxscript_graph: \n- onnxscript_tracer: \n- fx_name_to_onnxscript_value: Dict[length=75](\np_trunk_pos_embed: `TorchScriptTensor(f32[1, 1024, 1024])`,\np_trunk_attn_pool_latent: `TorchScriptTensor(f32[1, 1, 1024])`,\np_trunk_patch_embed_proj_weight: `TorchScriptTensor(f32[1024, 3, 16, 16])`,\np_trunk_patch_embed_proj_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_weight: `TorchScriptTensor(f32[3072, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_bias: `TorchScriptTensor(f32[3072])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_weight: `TorchScriptTensor(f32[1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_bias: `TorchScriptTensor(f32[1024])`,\n...\n)\n## Return values\n", + "text":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___5___mlp_fc2_bias[name=p_getattr_l__self___trunk_blocks___5___mlp_fc2_bias]. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"FxOnnxInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":414 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0008", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___6___norm1_weight[name=p_getattr_l__self___trunk_blocks___6___norm1_weight]. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature FxOnnxInterpreter.run_node\n- self: \n- node: fx.Node(p_getattr_l__self___trunk_blocks___6___norm1_weight)[placeholder]:Tensor(f32[1024])\n- fx_graph_module: torch.fx.GraphModule()\n- onnxfunction_dispatcher: \n- op_level_debug: False\n- onnxscript_graph: \n- onnxscript_tracer: \n- fx_name_to_onnxscript_value: Dict[length=76](\np_trunk_pos_embed: `TorchScriptTensor(f32[1, 1024, 1024])`,\np_trunk_attn_pool_latent: `TorchScriptTensor(f32[1, 1, 1024])`,\np_trunk_patch_embed_proj_weight: `TorchScriptTensor(f32[1024, 3, 16, 16])`,\np_trunk_patch_embed_proj_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_weight: `TorchScriptTensor(f32[3072, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_bias: `TorchScriptTensor(f32[3072])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_weight: `TorchScriptTensor(f32[1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_bias: `TorchScriptTensor(f32[1024])`,\n...\n)\n## Return values\n", + "text":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___6___norm1_weight[name=p_getattr_l__self___trunk_blocks___6___norm1_weight]. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"FxOnnxInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":414 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0008", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___6___norm1_bias[name=p_getattr_l__self___trunk_blocks___6___norm1_bias]. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature FxOnnxInterpreter.run_node\n- self: \n- node: fx.Node(p_getattr_l__self___trunk_blocks___6___norm1_bias)[placeholder]:Tensor(f32[1024])\n- fx_graph_module: torch.fx.GraphModule()\n- onnxfunction_dispatcher: \n- op_level_debug: False\n- onnxscript_graph: \n- onnxscript_tracer: \n- fx_name_to_onnxscript_value: Dict[length=77](\np_trunk_pos_embed: `TorchScriptTensor(f32[1, 1024, 1024])`,\np_trunk_attn_pool_latent: `TorchScriptTensor(f32[1, 1, 1024])`,\np_trunk_patch_embed_proj_weight: `TorchScriptTensor(f32[1024, 3, 16, 16])`,\np_trunk_patch_embed_proj_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_weight: `TorchScriptTensor(f32[3072, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_bias: `TorchScriptTensor(f32[3072])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_weight: `TorchScriptTensor(f32[1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_bias: `TorchScriptTensor(f32[1024])`,\n...\n)\n## Return values\n", + "text":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___6___norm1_bias[name=p_getattr_l__self___trunk_blocks___6___norm1_bias]. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"FxOnnxInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":414 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0008", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___6___attn_qkv_weight[name=p_getattr_l__self___trunk_blocks___6___attn_qkv_weight]. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature FxOnnxInterpreter.run_node\n- self: \n- node: fx.Node(p_getattr_l__self___trunk_blocks___6___attn_qkv_weight)[placeholder]:Tensor(f32[3072, 1024])\n- fx_graph_module: torch.fx.GraphModule()\n- onnxfunction_dispatcher: \n- op_level_debug: False\n- onnxscript_graph: \n- onnxscript_tracer: \n- fx_name_to_onnxscript_value: Dict[length=78](\np_trunk_pos_embed: `TorchScriptTensor(f32[1, 1024, 1024])`,\np_trunk_attn_pool_latent: `TorchScriptTensor(f32[1, 1, 1024])`,\np_trunk_patch_embed_proj_weight: `TorchScriptTensor(f32[1024, 3, 16, 16])`,\np_trunk_patch_embed_proj_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_weight: `TorchScriptTensor(f32[3072, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_bias: `TorchScriptTensor(f32[3072])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_weight: `TorchScriptTensor(f32[1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_bias: `TorchScriptTensor(f32[1024])`,\n...\n)\n## Return values\n", + "text":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___6___attn_qkv_weight[name=p_getattr_l__self___trunk_blocks___6___attn_qkv_weight]. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"FxOnnxInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":414 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0008", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___6___attn_qkv_bias[name=p_getattr_l__self___trunk_blocks___6___attn_qkv_bias]. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature FxOnnxInterpreter.run_node\n- self: \n- node: fx.Node(p_getattr_l__self___trunk_blocks___6___attn_qkv_bias)[placeholder]:Tensor(f32[3072])\n- fx_graph_module: torch.fx.GraphModule()\n- onnxfunction_dispatcher: \n- op_level_debug: False\n- onnxscript_graph: \n- onnxscript_tracer: \n- fx_name_to_onnxscript_value: Dict[length=79](\np_trunk_pos_embed: `TorchScriptTensor(f32[1, 1024, 1024])`,\np_trunk_attn_pool_latent: `TorchScriptTensor(f32[1, 1, 1024])`,\np_trunk_patch_embed_proj_weight: `TorchScriptTensor(f32[1024, 3, 16, 16])`,\np_trunk_patch_embed_proj_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_weight: `TorchScriptTensor(f32[3072, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_bias: `TorchScriptTensor(f32[3072])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_weight: `TorchScriptTensor(f32[1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_bias: `TorchScriptTensor(f32[1024])`,\n...\n)\n## Return values\n", + "text":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___6___attn_qkv_bias[name=p_getattr_l__self___trunk_blocks___6___attn_qkv_bias]. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"FxOnnxInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":414 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0008", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___6___attn_proj_weight[name=p_getattr_l__self___trunk_blocks___6___attn_proj_weight]. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature FxOnnxInterpreter.run_node\n- self: \n- node: fx.Node(p_getattr_l__self___trunk_blocks___6___attn_proj_weight)[placeholder]:Tensor(f32[1024, 1024])\n- fx_graph_module: torch.fx.GraphModule()\n- onnxfunction_dispatcher: \n- op_level_debug: False\n- onnxscript_graph: \n- onnxscript_tracer: \n- fx_name_to_onnxscript_value: Dict[length=80](\np_trunk_pos_embed: `TorchScriptTensor(f32[1, 1024, 1024])`,\np_trunk_attn_pool_latent: `TorchScriptTensor(f32[1, 1, 1024])`,\np_trunk_patch_embed_proj_weight: `TorchScriptTensor(f32[1024, 3, 16, 16])`,\np_trunk_patch_embed_proj_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_weight: `TorchScriptTensor(f32[3072, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_bias: `TorchScriptTensor(f32[3072])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_weight: `TorchScriptTensor(f32[1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_bias: `TorchScriptTensor(f32[1024])`,\n...\n)\n## Return values\n", + "text":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___6___attn_proj_weight[name=p_getattr_l__self___trunk_blocks___6___attn_proj_weight]. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"FxOnnxInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":414 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0008", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___6___attn_proj_bias[name=p_getattr_l__self___trunk_blocks___6___attn_proj_bias]. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature FxOnnxInterpreter.run_node\n- self: \n- node: fx.Node(p_getattr_l__self___trunk_blocks___6___attn_proj_bias)[placeholder]:Tensor(f32[1024])\n- fx_graph_module: torch.fx.GraphModule()\n- onnxfunction_dispatcher: \n- op_level_debug: False\n- onnxscript_graph: \n- onnxscript_tracer: \n- fx_name_to_onnxscript_value: Dict[length=81](\np_trunk_pos_embed: `TorchScriptTensor(f32[1, 1024, 1024])`,\np_trunk_attn_pool_latent: `TorchScriptTensor(f32[1, 1, 1024])`,\np_trunk_patch_embed_proj_weight: `TorchScriptTensor(f32[1024, 3, 16, 16])`,\np_trunk_patch_embed_proj_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_weight: `TorchScriptTensor(f32[3072, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_bias: `TorchScriptTensor(f32[3072])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_weight: `TorchScriptTensor(f32[1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_bias: `TorchScriptTensor(f32[1024])`,\n...\n)\n## Return values\n", + "text":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___6___attn_proj_bias[name=p_getattr_l__self___trunk_blocks___6___attn_proj_bias]. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"FxOnnxInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":414 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0008", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___6___norm2_weight[name=p_getattr_l__self___trunk_blocks___6___norm2_weight]. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature FxOnnxInterpreter.run_node\n- self: \n- node: fx.Node(p_getattr_l__self___trunk_blocks___6___norm2_weight)[placeholder]:Tensor(f32[1024])\n- fx_graph_module: torch.fx.GraphModule()\n- onnxfunction_dispatcher: \n- op_level_debug: False\n- onnxscript_graph: \n- onnxscript_tracer: \n- fx_name_to_onnxscript_value: Dict[length=82](\np_trunk_pos_embed: `TorchScriptTensor(f32[1, 1024, 1024])`,\np_trunk_attn_pool_latent: `TorchScriptTensor(f32[1, 1, 1024])`,\np_trunk_patch_embed_proj_weight: `TorchScriptTensor(f32[1024, 3, 16, 16])`,\np_trunk_patch_embed_proj_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_weight: `TorchScriptTensor(f32[3072, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_bias: `TorchScriptTensor(f32[3072])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_weight: `TorchScriptTensor(f32[1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_bias: `TorchScriptTensor(f32[1024])`,\n...\n)\n## Return values\n", + "text":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___6___norm2_weight[name=p_getattr_l__self___trunk_blocks___6___norm2_weight]. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"FxOnnxInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":414 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0008", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___6___norm2_bias[name=p_getattr_l__self___trunk_blocks___6___norm2_bias]. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature FxOnnxInterpreter.run_node\n- self: \n- node: fx.Node(p_getattr_l__self___trunk_blocks___6___norm2_bias)[placeholder]:Tensor(f32[1024])\n- fx_graph_module: torch.fx.GraphModule()\n- onnxfunction_dispatcher: \n- op_level_debug: False\n- onnxscript_graph: \n- onnxscript_tracer: \n- fx_name_to_onnxscript_value: Dict[length=83](\np_trunk_pos_embed: `TorchScriptTensor(f32[1, 1024, 1024])`,\np_trunk_attn_pool_latent: `TorchScriptTensor(f32[1, 1, 1024])`,\np_trunk_patch_embed_proj_weight: `TorchScriptTensor(f32[1024, 3, 16, 16])`,\np_trunk_patch_embed_proj_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_weight: `TorchScriptTensor(f32[3072, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_bias: `TorchScriptTensor(f32[3072])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_weight: `TorchScriptTensor(f32[1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_bias: `TorchScriptTensor(f32[1024])`,\n...\n)\n## Return values\n", + "text":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___6___norm2_bias[name=p_getattr_l__self___trunk_blocks___6___norm2_bias]. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"FxOnnxInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":414 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0008", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___6___mlp_fc1_weight[name=p_getattr_l__self___trunk_blocks___6___mlp_fc1_weight]. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature FxOnnxInterpreter.run_node\n- self: \n- node: fx.Node(p_getattr_l__self___trunk_blocks___6___mlp_fc1_weight)[placeholder]:Tensor(f32[4096, 1024])\n- fx_graph_module: torch.fx.GraphModule()\n- onnxfunction_dispatcher: \n- op_level_debug: False\n- onnxscript_graph: \n- onnxscript_tracer: \n- fx_name_to_onnxscript_value: Dict[length=84](\np_trunk_pos_embed: `TorchScriptTensor(f32[1, 1024, 1024])`,\np_trunk_attn_pool_latent: `TorchScriptTensor(f32[1, 1, 1024])`,\np_trunk_patch_embed_proj_weight: `TorchScriptTensor(f32[1024, 3, 16, 16])`,\np_trunk_patch_embed_proj_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_weight: `TorchScriptTensor(f32[3072, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_bias: `TorchScriptTensor(f32[3072])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_weight: `TorchScriptTensor(f32[1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_bias: `TorchScriptTensor(f32[1024])`,\n...\n)\n## Return values\n", + "text":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___6___mlp_fc1_weight[name=p_getattr_l__self___trunk_blocks___6___mlp_fc1_weight]. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"FxOnnxInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":414 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0008", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___6___mlp_fc1_bias[name=p_getattr_l__self___trunk_blocks___6___mlp_fc1_bias]. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature FxOnnxInterpreter.run_node\n- self: \n- node: fx.Node(p_getattr_l__self___trunk_blocks___6___mlp_fc1_bias)[placeholder]:Tensor(f32[4096])\n- fx_graph_module: torch.fx.GraphModule()\n- onnxfunction_dispatcher: \n- op_level_debug: False\n- onnxscript_graph: \n- onnxscript_tracer: \n- fx_name_to_onnxscript_value: Dict[length=85](\np_trunk_pos_embed: `TorchScriptTensor(f32[1, 1024, 1024])`,\np_trunk_attn_pool_latent: `TorchScriptTensor(f32[1, 1, 1024])`,\np_trunk_patch_embed_proj_weight: `TorchScriptTensor(f32[1024, 3, 16, 16])`,\np_trunk_patch_embed_proj_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_weight: `TorchScriptTensor(f32[3072, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_bias: `TorchScriptTensor(f32[3072])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_weight: `TorchScriptTensor(f32[1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_bias: `TorchScriptTensor(f32[1024])`,\n...\n)\n## Return values\n", + "text":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___6___mlp_fc1_bias[name=p_getattr_l__self___trunk_blocks___6___mlp_fc1_bias]. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"FxOnnxInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":414 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0008", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___6___mlp_fc2_weight[name=p_getattr_l__self___trunk_blocks___6___mlp_fc2_weight]. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature FxOnnxInterpreter.run_node\n- self: \n- node: fx.Node(p_getattr_l__self___trunk_blocks___6___mlp_fc2_weight)[placeholder]:Tensor(f32[1024, 4096])\n- fx_graph_module: torch.fx.GraphModule()\n- onnxfunction_dispatcher: \n- op_level_debug: False\n- onnxscript_graph: \n- onnxscript_tracer: \n- fx_name_to_onnxscript_value: Dict[length=86](\np_trunk_pos_embed: `TorchScriptTensor(f32[1, 1024, 1024])`,\np_trunk_attn_pool_latent: `TorchScriptTensor(f32[1, 1, 1024])`,\np_trunk_patch_embed_proj_weight: `TorchScriptTensor(f32[1024, 3, 16, 16])`,\np_trunk_patch_embed_proj_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_weight: `TorchScriptTensor(f32[3072, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_bias: `TorchScriptTensor(f32[3072])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_weight: `TorchScriptTensor(f32[1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_bias: `TorchScriptTensor(f32[1024])`,\n...\n)\n## Return values\n", + "text":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___6___mlp_fc2_weight[name=p_getattr_l__self___trunk_blocks___6___mlp_fc2_weight]. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"FxOnnxInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":414 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0008", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___6___mlp_fc2_bias[name=p_getattr_l__self___trunk_blocks___6___mlp_fc2_bias]. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature FxOnnxInterpreter.run_node\n- self: \n- node: fx.Node(p_getattr_l__self___trunk_blocks___6___mlp_fc2_bias)[placeholder]:Tensor(f32[1024])\n- fx_graph_module: torch.fx.GraphModule()\n- onnxfunction_dispatcher: \n- op_level_debug: False\n- onnxscript_graph: \n- onnxscript_tracer: \n- fx_name_to_onnxscript_value: Dict[length=87](\np_trunk_pos_embed: `TorchScriptTensor(f32[1, 1024, 1024])`,\np_trunk_attn_pool_latent: `TorchScriptTensor(f32[1, 1, 1024])`,\np_trunk_patch_embed_proj_weight: `TorchScriptTensor(f32[1024, 3, 16, 16])`,\np_trunk_patch_embed_proj_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_weight: `TorchScriptTensor(f32[3072, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_bias: `TorchScriptTensor(f32[3072])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_weight: `TorchScriptTensor(f32[1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_bias: `TorchScriptTensor(f32[1024])`,\n...\n)\n## Return values\n", + "text":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___6___mlp_fc2_bias[name=p_getattr_l__self___trunk_blocks___6___mlp_fc2_bias]. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"FxOnnxInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":414 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0008", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___7___norm1_weight[name=p_getattr_l__self___trunk_blocks___7___norm1_weight]. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature FxOnnxInterpreter.run_node\n- self: \n- node: fx.Node(p_getattr_l__self___trunk_blocks___7___norm1_weight)[placeholder]:Tensor(f32[1024])\n- fx_graph_module: torch.fx.GraphModule()\n- onnxfunction_dispatcher: \n- op_level_debug: False\n- onnxscript_graph: \n- onnxscript_tracer: \n- fx_name_to_onnxscript_value: Dict[length=88](\np_trunk_pos_embed: `TorchScriptTensor(f32[1, 1024, 1024])`,\np_trunk_attn_pool_latent: `TorchScriptTensor(f32[1, 1, 1024])`,\np_trunk_patch_embed_proj_weight: `TorchScriptTensor(f32[1024, 3, 16, 16])`,\np_trunk_patch_embed_proj_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_weight: `TorchScriptTensor(f32[3072, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_bias: `TorchScriptTensor(f32[3072])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_weight: `TorchScriptTensor(f32[1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_bias: `TorchScriptTensor(f32[1024])`,\n...\n)\n## Return values\n", + "text":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___7___norm1_weight[name=p_getattr_l__self___trunk_blocks___7___norm1_weight]. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"FxOnnxInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":414 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0008", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___7___norm1_bias[name=p_getattr_l__self___trunk_blocks___7___norm1_bias]. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature FxOnnxInterpreter.run_node\n- self: \n- node: fx.Node(p_getattr_l__self___trunk_blocks___7___norm1_bias)[placeholder]:Tensor(f32[1024])\n- fx_graph_module: torch.fx.GraphModule()\n- onnxfunction_dispatcher: \n- op_level_debug: False\n- onnxscript_graph: \n- onnxscript_tracer: \n- fx_name_to_onnxscript_value: Dict[length=89](\np_trunk_pos_embed: `TorchScriptTensor(f32[1, 1024, 1024])`,\np_trunk_attn_pool_latent: `TorchScriptTensor(f32[1, 1, 1024])`,\np_trunk_patch_embed_proj_weight: `TorchScriptTensor(f32[1024, 3, 16, 16])`,\np_trunk_patch_embed_proj_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_weight: `TorchScriptTensor(f32[3072, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_bias: `TorchScriptTensor(f32[3072])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_weight: `TorchScriptTensor(f32[1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_bias: `TorchScriptTensor(f32[1024])`,\n...\n)\n## Return values\n", + "text":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___7___norm1_bias[name=p_getattr_l__self___trunk_blocks___7___norm1_bias]. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"FxOnnxInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":414 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0008", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___7___attn_qkv_weight[name=p_getattr_l__self___trunk_blocks___7___attn_qkv_weight]. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature FxOnnxInterpreter.run_node\n- self: \n- node: fx.Node(p_getattr_l__self___trunk_blocks___7___attn_qkv_weight)[placeholder]:Tensor(f32[3072, 1024])\n- fx_graph_module: torch.fx.GraphModule()\n- onnxfunction_dispatcher: \n- op_level_debug: False\n- onnxscript_graph: \n- onnxscript_tracer: \n- fx_name_to_onnxscript_value: Dict[length=90](\np_trunk_pos_embed: `TorchScriptTensor(f32[1, 1024, 1024])`,\np_trunk_attn_pool_latent: `TorchScriptTensor(f32[1, 1, 1024])`,\np_trunk_patch_embed_proj_weight: `TorchScriptTensor(f32[1024, 3, 16, 16])`,\np_trunk_patch_embed_proj_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_weight: `TorchScriptTensor(f32[3072, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_bias: `TorchScriptTensor(f32[3072])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_weight: `TorchScriptTensor(f32[1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_bias: `TorchScriptTensor(f32[1024])`,\n...\n)\n## Return values\n", + "text":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___7___attn_qkv_weight[name=p_getattr_l__self___trunk_blocks___7___attn_qkv_weight]. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"FxOnnxInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":414 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0008", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___7___attn_qkv_bias[name=p_getattr_l__self___trunk_blocks___7___attn_qkv_bias]. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature FxOnnxInterpreter.run_node\n- self: \n- node: fx.Node(p_getattr_l__self___trunk_blocks___7___attn_qkv_bias)[placeholder]:Tensor(f32[3072])\n- fx_graph_module: torch.fx.GraphModule()\n- onnxfunction_dispatcher: \n- op_level_debug: False\n- onnxscript_graph: \n- onnxscript_tracer: \n- fx_name_to_onnxscript_value: Dict[length=91](\np_trunk_pos_embed: `TorchScriptTensor(f32[1, 1024, 1024])`,\np_trunk_attn_pool_latent: `TorchScriptTensor(f32[1, 1, 1024])`,\np_trunk_patch_embed_proj_weight: `TorchScriptTensor(f32[1024, 3, 16, 16])`,\np_trunk_patch_embed_proj_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_weight: `TorchScriptTensor(f32[3072, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_bias: `TorchScriptTensor(f32[3072])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_weight: `TorchScriptTensor(f32[1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_bias: `TorchScriptTensor(f32[1024])`,\n...\n)\n## Return values\n", + "text":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___7___attn_qkv_bias[name=p_getattr_l__self___trunk_blocks___7___attn_qkv_bias]. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"FxOnnxInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":414 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0008", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___7___attn_proj_weight[name=p_getattr_l__self___trunk_blocks___7___attn_proj_weight]. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature FxOnnxInterpreter.run_node\n- self: \n- node: fx.Node(p_getattr_l__self___trunk_blocks___7___attn_proj_weight)[placeholder]:Tensor(f32[1024, 1024])\n- fx_graph_module: torch.fx.GraphModule()\n- onnxfunction_dispatcher: \n- op_level_debug: False\n- onnxscript_graph: \n- onnxscript_tracer: \n- fx_name_to_onnxscript_value: Dict[length=92](\np_trunk_pos_embed: `TorchScriptTensor(f32[1, 1024, 1024])`,\np_trunk_attn_pool_latent: `TorchScriptTensor(f32[1, 1, 1024])`,\np_trunk_patch_embed_proj_weight: `TorchScriptTensor(f32[1024, 3, 16, 16])`,\np_trunk_patch_embed_proj_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_weight: `TorchScriptTensor(f32[3072, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_bias: `TorchScriptTensor(f32[3072])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_weight: `TorchScriptTensor(f32[1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_bias: `TorchScriptTensor(f32[1024])`,\n...\n)\n## Return values\n", + "text":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___7___attn_proj_weight[name=p_getattr_l__self___trunk_blocks___7___attn_proj_weight]. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"FxOnnxInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":414 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0008", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___7___attn_proj_bias[name=p_getattr_l__self___trunk_blocks___7___attn_proj_bias]. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature FxOnnxInterpreter.run_node\n- self: \n- node: fx.Node(p_getattr_l__self___trunk_blocks___7___attn_proj_bias)[placeholder]:Tensor(f32[1024])\n- fx_graph_module: torch.fx.GraphModule()\n- onnxfunction_dispatcher: \n- op_level_debug: False\n- onnxscript_graph: \n- onnxscript_tracer: \n- fx_name_to_onnxscript_value: Dict[length=93](\np_trunk_pos_embed: `TorchScriptTensor(f32[1, 1024, 1024])`,\np_trunk_attn_pool_latent: `TorchScriptTensor(f32[1, 1, 1024])`,\np_trunk_patch_embed_proj_weight: `TorchScriptTensor(f32[1024, 3, 16, 16])`,\np_trunk_patch_embed_proj_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_weight: `TorchScriptTensor(f32[3072, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_bias: `TorchScriptTensor(f32[3072])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_weight: `TorchScriptTensor(f32[1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_bias: `TorchScriptTensor(f32[1024])`,\n...\n)\n## Return values\n", + "text":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___7___attn_proj_bias[name=p_getattr_l__self___trunk_blocks___7___attn_proj_bias]. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"FxOnnxInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":414 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0008", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___7___norm2_weight[name=p_getattr_l__self___trunk_blocks___7___norm2_weight]. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature FxOnnxInterpreter.run_node\n- self: \n- node: fx.Node(p_getattr_l__self___trunk_blocks___7___norm2_weight)[placeholder]:Tensor(f32[1024])\n- fx_graph_module: torch.fx.GraphModule()\n- onnxfunction_dispatcher: \n- op_level_debug: False\n- onnxscript_graph: \n- onnxscript_tracer: \n- fx_name_to_onnxscript_value: Dict[length=94](\np_trunk_pos_embed: `TorchScriptTensor(f32[1, 1024, 1024])`,\np_trunk_attn_pool_latent: `TorchScriptTensor(f32[1, 1, 1024])`,\np_trunk_patch_embed_proj_weight: `TorchScriptTensor(f32[1024, 3, 16, 16])`,\np_trunk_patch_embed_proj_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_weight: `TorchScriptTensor(f32[3072, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_bias: `TorchScriptTensor(f32[3072])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_weight: `TorchScriptTensor(f32[1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_bias: `TorchScriptTensor(f32[1024])`,\n...\n)\n## Return values\n", + "text":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___7___norm2_weight[name=p_getattr_l__self___trunk_blocks___7___norm2_weight]. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"FxOnnxInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":414 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0008", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___7___norm2_bias[name=p_getattr_l__self___trunk_blocks___7___norm2_bias]. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature FxOnnxInterpreter.run_node\n- self: \n- node: fx.Node(p_getattr_l__self___trunk_blocks___7___norm2_bias)[placeholder]:Tensor(f32[1024])\n- fx_graph_module: torch.fx.GraphModule()\n- onnxfunction_dispatcher: \n- op_level_debug: False\n- onnxscript_graph: \n- onnxscript_tracer: \n- fx_name_to_onnxscript_value: Dict[length=95](\np_trunk_pos_embed: `TorchScriptTensor(f32[1, 1024, 1024])`,\np_trunk_attn_pool_latent: `TorchScriptTensor(f32[1, 1, 1024])`,\np_trunk_patch_embed_proj_weight: `TorchScriptTensor(f32[1024, 3, 16, 16])`,\np_trunk_patch_embed_proj_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_weight: `TorchScriptTensor(f32[3072, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_bias: `TorchScriptTensor(f32[3072])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_weight: `TorchScriptTensor(f32[1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_bias: `TorchScriptTensor(f32[1024])`,\n...\n)\n## Return values\n", + "text":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___7___norm2_bias[name=p_getattr_l__self___trunk_blocks___7___norm2_bias]. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"FxOnnxInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":414 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0008", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___7___mlp_fc1_weight[name=p_getattr_l__self___trunk_blocks___7___mlp_fc1_weight]. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature FxOnnxInterpreter.run_node\n- self: \n- node: fx.Node(p_getattr_l__self___trunk_blocks___7___mlp_fc1_weight)[placeholder]:Tensor(f32[4096, 1024])\n- fx_graph_module: torch.fx.GraphModule()\n- onnxfunction_dispatcher: \n- op_level_debug: False\n- onnxscript_graph: \n- onnxscript_tracer: \n- fx_name_to_onnxscript_value: Dict[length=96](\np_trunk_pos_embed: `TorchScriptTensor(f32[1, 1024, 1024])`,\np_trunk_attn_pool_latent: `TorchScriptTensor(f32[1, 1, 1024])`,\np_trunk_patch_embed_proj_weight: `TorchScriptTensor(f32[1024, 3, 16, 16])`,\np_trunk_patch_embed_proj_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_weight: `TorchScriptTensor(f32[3072, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_bias: `TorchScriptTensor(f32[3072])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_weight: `TorchScriptTensor(f32[1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_bias: `TorchScriptTensor(f32[1024])`,\n...\n)\n## Return values\n", + "text":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___7___mlp_fc1_weight[name=p_getattr_l__self___trunk_blocks___7___mlp_fc1_weight]. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"FxOnnxInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":414 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0008", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___7___mlp_fc1_bias[name=p_getattr_l__self___trunk_blocks___7___mlp_fc1_bias]. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature FxOnnxInterpreter.run_node\n- self: \n- node: fx.Node(p_getattr_l__self___trunk_blocks___7___mlp_fc1_bias)[placeholder]:Tensor(f32[4096])\n- fx_graph_module: torch.fx.GraphModule()\n- onnxfunction_dispatcher: \n- op_level_debug: False\n- onnxscript_graph: \n- onnxscript_tracer: \n- fx_name_to_onnxscript_value: Dict[length=97](\np_trunk_pos_embed: `TorchScriptTensor(f32[1, 1024, 1024])`,\np_trunk_attn_pool_latent: `TorchScriptTensor(f32[1, 1, 1024])`,\np_trunk_patch_embed_proj_weight: `TorchScriptTensor(f32[1024, 3, 16, 16])`,\np_trunk_patch_embed_proj_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_weight: `TorchScriptTensor(f32[3072, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_bias: `TorchScriptTensor(f32[3072])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_weight: `TorchScriptTensor(f32[1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_bias: `TorchScriptTensor(f32[1024])`,\n...\n)\n## Return values\n", + "text":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___7___mlp_fc1_bias[name=p_getattr_l__self___trunk_blocks___7___mlp_fc1_bias]. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"FxOnnxInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":414 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0008", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___7___mlp_fc2_weight[name=p_getattr_l__self___trunk_blocks___7___mlp_fc2_weight]. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature FxOnnxInterpreter.run_node\n- self: \n- node: fx.Node(p_getattr_l__self___trunk_blocks___7___mlp_fc2_weight)[placeholder]:Tensor(f32[1024, 4096])\n- fx_graph_module: torch.fx.GraphModule()\n- onnxfunction_dispatcher: \n- op_level_debug: False\n- onnxscript_graph: \n- onnxscript_tracer: \n- fx_name_to_onnxscript_value: Dict[length=98](\np_trunk_pos_embed: `TorchScriptTensor(f32[1, 1024, 1024])`,\np_trunk_attn_pool_latent: `TorchScriptTensor(f32[1, 1, 1024])`,\np_trunk_patch_embed_proj_weight: `TorchScriptTensor(f32[1024, 3, 16, 16])`,\np_trunk_patch_embed_proj_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_weight: `TorchScriptTensor(f32[3072, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_bias: `TorchScriptTensor(f32[3072])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_weight: `TorchScriptTensor(f32[1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_bias: `TorchScriptTensor(f32[1024])`,\n...\n)\n## Return values\n", + "text":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___7___mlp_fc2_weight[name=p_getattr_l__self___trunk_blocks___7___mlp_fc2_weight]. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"FxOnnxInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":414 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0008", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___7___mlp_fc2_bias[name=p_getattr_l__self___trunk_blocks___7___mlp_fc2_bias]. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature FxOnnxInterpreter.run_node\n- self: \n- node: fx.Node(p_getattr_l__self___trunk_blocks___7___mlp_fc2_bias)[placeholder]:Tensor(f32[1024])\n- fx_graph_module: torch.fx.GraphModule()\n- onnxfunction_dispatcher: \n- op_level_debug: False\n- onnxscript_graph: \n- onnxscript_tracer: \n- fx_name_to_onnxscript_value: Dict[length=99](\np_trunk_pos_embed: `TorchScriptTensor(f32[1, 1024, 1024])`,\np_trunk_attn_pool_latent: `TorchScriptTensor(f32[1, 1, 1024])`,\np_trunk_patch_embed_proj_weight: `TorchScriptTensor(f32[1024, 3, 16, 16])`,\np_trunk_patch_embed_proj_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_weight: `TorchScriptTensor(f32[3072, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_bias: `TorchScriptTensor(f32[3072])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_weight: `TorchScriptTensor(f32[1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_bias: `TorchScriptTensor(f32[1024])`,\n...\n)\n## Return values\n", + "text":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___7___mlp_fc2_bias[name=p_getattr_l__self___trunk_blocks___7___mlp_fc2_bias]. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"FxOnnxInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":414 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0008", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___8___norm1_weight[name=p_getattr_l__self___trunk_blocks___8___norm1_weight]. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature FxOnnxInterpreter.run_node\n- self: \n- node: fx.Node(p_getattr_l__self___trunk_blocks___8___norm1_weight)[placeholder]:Tensor(f32[1024])\n- fx_graph_module: torch.fx.GraphModule()\n- onnxfunction_dispatcher: \n- op_level_debug: False\n- onnxscript_graph: \n- onnxscript_tracer: \n- fx_name_to_onnxscript_value: Dict[length=100](\np_trunk_pos_embed: `TorchScriptTensor(f32[1, 1024, 1024])`,\np_trunk_attn_pool_latent: `TorchScriptTensor(f32[1, 1, 1024])`,\np_trunk_patch_embed_proj_weight: `TorchScriptTensor(f32[1024, 3, 16, 16])`,\np_trunk_patch_embed_proj_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_weight: `TorchScriptTensor(f32[3072, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_bias: `TorchScriptTensor(f32[3072])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_weight: `TorchScriptTensor(f32[1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_bias: `TorchScriptTensor(f32[1024])`,\n...\n)\n## Return values\n", + "text":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___8___norm1_weight[name=p_getattr_l__self___trunk_blocks___8___norm1_weight]. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"FxOnnxInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":414 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0008", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___8___norm1_bias[name=p_getattr_l__self___trunk_blocks___8___norm1_bias]. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature FxOnnxInterpreter.run_node\n- self: \n- node: fx.Node(p_getattr_l__self___trunk_blocks___8___norm1_bias)[placeholder]:Tensor(f32[1024])\n- fx_graph_module: torch.fx.GraphModule()\n- onnxfunction_dispatcher: \n- op_level_debug: False\n- onnxscript_graph: \n- onnxscript_tracer: \n- fx_name_to_onnxscript_value: Dict[length=101](\np_trunk_pos_embed: `TorchScriptTensor(f32[1, 1024, 1024])`,\np_trunk_attn_pool_latent: `TorchScriptTensor(f32[1, 1, 1024])`,\np_trunk_patch_embed_proj_weight: `TorchScriptTensor(f32[1024, 3, 16, 16])`,\np_trunk_patch_embed_proj_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_weight: `TorchScriptTensor(f32[3072, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_bias: `TorchScriptTensor(f32[3072])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_weight: `TorchScriptTensor(f32[1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_bias: `TorchScriptTensor(f32[1024])`,\n...\n)\n## Return values\n", + "text":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___8___norm1_bias[name=p_getattr_l__self___trunk_blocks___8___norm1_bias]. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"FxOnnxInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":414 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0008", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___8___attn_qkv_weight[name=p_getattr_l__self___trunk_blocks___8___attn_qkv_weight]. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature FxOnnxInterpreter.run_node\n- self: \n- node: fx.Node(p_getattr_l__self___trunk_blocks___8___attn_qkv_weight)[placeholder]:Tensor(f32[3072, 1024])\n- fx_graph_module: torch.fx.GraphModule()\n- onnxfunction_dispatcher: \n- op_level_debug: False\n- onnxscript_graph: \n- onnxscript_tracer: \n- fx_name_to_onnxscript_value: Dict[length=102](\np_trunk_pos_embed: `TorchScriptTensor(f32[1, 1024, 1024])`,\np_trunk_attn_pool_latent: `TorchScriptTensor(f32[1, 1, 1024])`,\np_trunk_patch_embed_proj_weight: `TorchScriptTensor(f32[1024, 3, 16, 16])`,\np_trunk_patch_embed_proj_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_weight: `TorchScriptTensor(f32[3072, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_bias: `TorchScriptTensor(f32[3072])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_weight: `TorchScriptTensor(f32[1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_bias: `TorchScriptTensor(f32[1024])`,\n...\n)\n## Return values\n", + "text":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___8___attn_qkv_weight[name=p_getattr_l__self___trunk_blocks___8___attn_qkv_weight]. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"FxOnnxInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":414 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0008", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___8___attn_qkv_bias[name=p_getattr_l__self___trunk_blocks___8___attn_qkv_bias]. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature FxOnnxInterpreter.run_node\n- self: \n- node: fx.Node(p_getattr_l__self___trunk_blocks___8___attn_qkv_bias)[placeholder]:Tensor(f32[3072])\n- fx_graph_module: torch.fx.GraphModule()\n- onnxfunction_dispatcher: \n- op_level_debug: False\n- onnxscript_graph: \n- onnxscript_tracer: \n- fx_name_to_onnxscript_value: Dict[length=103](\np_trunk_pos_embed: `TorchScriptTensor(f32[1, 1024, 1024])`,\np_trunk_attn_pool_latent: `TorchScriptTensor(f32[1, 1, 1024])`,\np_trunk_patch_embed_proj_weight: `TorchScriptTensor(f32[1024, 3, 16, 16])`,\np_trunk_patch_embed_proj_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_weight: `TorchScriptTensor(f32[3072, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_bias: `TorchScriptTensor(f32[3072])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_weight: `TorchScriptTensor(f32[1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_bias: `TorchScriptTensor(f32[1024])`,\n...\n)\n## Return values\n", + "text":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___8___attn_qkv_bias[name=p_getattr_l__self___trunk_blocks___8___attn_qkv_bias]. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"FxOnnxInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":414 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0008", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___8___attn_proj_weight[name=p_getattr_l__self___trunk_blocks___8___attn_proj_weight]. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature FxOnnxInterpreter.run_node\n- self: \n- node: fx.Node(p_getattr_l__self___trunk_blocks___8___attn_proj_weight)[placeholder]:Tensor(f32[1024, 1024])\n- fx_graph_module: torch.fx.GraphModule()\n- onnxfunction_dispatcher: \n- op_level_debug: False\n- onnxscript_graph: \n- onnxscript_tracer: \n- fx_name_to_onnxscript_value: Dict[length=104](\np_trunk_pos_embed: `TorchScriptTensor(f32[1, 1024, 1024])`,\np_trunk_attn_pool_latent: `TorchScriptTensor(f32[1, 1, 1024])`,\np_trunk_patch_embed_proj_weight: `TorchScriptTensor(f32[1024, 3, 16, 16])`,\np_trunk_patch_embed_proj_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_weight: `TorchScriptTensor(f32[3072, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_bias: `TorchScriptTensor(f32[3072])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_weight: `TorchScriptTensor(f32[1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_bias: `TorchScriptTensor(f32[1024])`,\n...\n)\n## Return values\n", + "text":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___8___attn_proj_weight[name=p_getattr_l__self___trunk_blocks___8___attn_proj_weight]. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"FxOnnxInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":414 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0008", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___8___attn_proj_bias[name=p_getattr_l__self___trunk_blocks___8___attn_proj_bias]. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature FxOnnxInterpreter.run_node\n- self: \n- node: fx.Node(p_getattr_l__self___trunk_blocks___8___attn_proj_bias)[placeholder]:Tensor(f32[1024])\n- fx_graph_module: torch.fx.GraphModule()\n- onnxfunction_dispatcher: \n- op_level_debug: False\n- onnxscript_graph: \n- onnxscript_tracer: \n- fx_name_to_onnxscript_value: Dict[length=105](\np_trunk_pos_embed: `TorchScriptTensor(f32[1, 1024, 1024])`,\np_trunk_attn_pool_latent: `TorchScriptTensor(f32[1, 1, 1024])`,\np_trunk_patch_embed_proj_weight: `TorchScriptTensor(f32[1024, 3, 16, 16])`,\np_trunk_patch_embed_proj_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_weight: `TorchScriptTensor(f32[3072, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_bias: `TorchScriptTensor(f32[3072])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_weight: `TorchScriptTensor(f32[1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_bias: `TorchScriptTensor(f32[1024])`,\n...\n)\n## Return values\n", + "text":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___8___attn_proj_bias[name=p_getattr_l__self___trunk_blocks___8___attn_proj_bias]. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"FxOnnxInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":414 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0008", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___8___norm2_weight[name=p_getattr_l__self___trunk_blocks___8___norm2_weight]. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature FxOnnxInterpreter.run_node\n- self: \n- node: fx.Node(p_getattr_l__self___trunk_blocks___8___norm2_weight)[placeholder]:Tensor(f32[1024])\n- fx_graph_module: torch.fx.GraphModule()\n- onnxfunction_dispatcher: \n- op_level_debug: False\n- onnxscript_graph: \n- onnxscript_tracer: \n- fx_name_to_onnxscript_value: Dict[length=106](\np_trunk_pos_embed: `TorchScriptTensor(f32[1, 1024, 1024])`,\np_trunk_attn_pool_latent: `TorchScriptTensor(f32[1, 1, 1024])`,\np_trunk_patch_embed_proj_weight: `TorchScriptTensor(f32[1024, 3, 16, 16])`,\np_trunk_patch_embed_proj_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_weight: `TorchScriptTensor(f32[3072, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_bias: `TorchScriptTensor(f32[3072])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_weight: `TorchScriptTensor(f32[1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_bias: `TorchScriptTensor(f32[1024])`,\n...\n)\n## Return values\n", + "text":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___8___norm2_weight[name=p_getattr_l__self___trunk_blocks___8___norm2_weight]. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"FxOnnxInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":414 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0008", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___8___norm2_bias[name=p_getattr_l__self___trunk_blocks___8___norm2_bias]. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature FxOnnxInterpreter.run_node\n- self: \n- node: fx.Node(p_getattr_l__self___trunk_blocks___8___norm2_bias)[placeholder]:Tensor(f32[1024])\n- fx_graph_module: torch.fx.GraphModule()\n- onnxfunction_dispatcher: \n- op_level_debug: False\n- onnxscript_graph: \n- onnxscript_tracer: \n- fx_name_to_onnxscript_value: Dict[length=107](\np_trunk_pos_embed: `TorchScriptTensor(f32[1, 1024, 1024])`,\np_trunk_attn_pool_latent: `TorchScriptTensor(f32[1, 1, 1024])`,\np_trunk_patch_embed_proj_weight: `TorchScriptTensor(f32[1024, 3, 16, 16])`,\np_trunk_patch_embed_proj_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_weight: `TorchScriptTensor(f32[3072, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_bias: `TorchScriptTensor(f32[3072])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_weight: `TorchScriptTensor(f32[1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_bias: `TorchScriptTensor(f32[1024])`,\n...\n)\n## Return values\n", + "text":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___8___norm2_bias[name=p_getattr_l__self___trunk_blocks___8___norm2_bias]. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"FxOnnxInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":414 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0008", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___8___mlp_fc1_weight[name=p_getattr_l__self___trunk_blocks___8___mlp_fc1_weight]. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature FxOnnxInterpreter.run_node\n- self: \n- node: fx.Node(p_getattr_l__self___trunk_blocks___8___mlp_fc1_weight)[placeholder]:Tensor(f32[4096, 1024])\n- fx_graph_module: torch.fx.GraphModule()\n- onnxfunction_dispatcher: \n- op_level_debug: False\n- onnxscript_graph: \n- onnxscript_tracer: \n- fx_name_to_onnxscript_value: Dict[length=108](\np_trunk_pos_embed: `TorchScriptTensor(f32[1, 1024, 1024])`,\np_trunk_attn_pool_latent: `TorchScriptTensor(f32[1, 1, 1024])`,\np_trunk_patch_embed_proj_weight: `TorchScriptTensor(f32[1024, 3, 16, 16])`,\np_trunk_patch_embed_proj_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_weight: `TorchScriptTensor(f32[3072, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_bias: `TorchScriptTensor(f32[3072])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_weight: `TorchScriptTensor(f32[1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_bias: `TorchScriptTensor(f32[1024])`,\n...\n)\n## Return values\n", + "text":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___8___mlp_fc1_weight[name=p_getattr_l__self___trunk_blocks___8___mlp_fc1_weight]. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"FxOnnxInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":414 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0008", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___8___mlp_fc1_bias[name=p_getattr_l__self___trunk_blocks___8___mlp_fc1_bias]. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature FxOnnxInterpreter.run_node\n- self: \n- node: fx.Node(p_getattr_l__self___trunk_blocks___8___mlp_fc1_bias)[placeholder]:Tensor(f32[4096])\n- fx_graph_module: torch.fx.GraphModule()\n- onnxfunction_dispatcher: \n- op_level_debug: False\n- onnxscript_graph: \n- onnxscript_tracer: \n- fx_name_to_onnxscript_value: Dict[length=109](\np_trunk_pos_embed: `TorchScriptTensor(f32[1, 1024, 1024])`,\np_trunk_attn_pool_latent: `TorchScriptTensor(f32[1, 1, 1024])`,\np_trunk_patch_embed_proj_weight: `TorchScriptTensor(f32[1024, 3, 16, 16])`,\np_trunk_patch_embed_proj_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_weight: `TorchScriptTensor(f32[3072, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_bias: `TorchScriptTensor(f32[3072])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_weight: `TorchScriptTensor(f32[1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_bias: `TorchScriptTensor(f32[1024])`,\n...\n)\n## Return values\n", + "text":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___8___mlp_fc1_bias[name=p_getattr_l__self___trunk_blocks___8___mlp_fc1_bias]. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"FxOnnxInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":414 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0008", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___8___mlp_fc2_weight[name=p_getattr_l__self___trunk_blocks___8___mlp_fc2_weight]. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature FxOnnxInterpreter.run_node\n- self: \n- node: fx.Node(p_getattr_l__self___trunk_blocks___8___mlp_fc2_weight)[placeholder]:Tensor(f32[1024, 4096])\n- fx_graph_module: torch.fx.GraphModule()\n- onnxfunction_dispatcher: \n- op_level_debug: False\n- onnxscript_graph: \n- onnxscript_tracer: \n- fx_name_to_onnxscript_value: Dict[length=110](\np_trunk_pos_embed: `TorchScriptTensor(f32[1, 1024, 1024])`,\np_trunk_attn_pool_latent: `TorchScriptTensor(f32[1, 1, 1024])`,\np_trunk_patch_embed_proj_weight: `TorchScriptTensor(f32[1024, 3, 16, 16])`,\np_trunk_patch_embed_proj_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_weight: `TorchScriptTensor(f32[3072, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_bias: `TorchScriptTensor(f32[3072])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_weight: `TorchScriptTensor(f32[1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_bias: `TorchScriptTensor(f32[1024])`,\n...\n)\n## Return values\n", + "text":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___8___mlp_fc2_weight[name=p_getattr_l__self___trunk_blocks___8___mlp_fc2_weight]. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"FxOnnxInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":414 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0008", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___8___mlp_fc2_bias[name=p_getattr_l__self___trunk_blocks___8___mlp_fc2_bias]. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature FxOnnxInterpreter.run_node\n- self: \n- node: fx.Node(p_getattr_l__self___trunk_blocks___8___mlp_fc2_bias)[placeholder]:Tensor(f32[1024])\n- fx_graph_module: torch.fx.GraphModule()\n- onnxfunction_dispatcher: \n- op_level_debug: False\n- onnxscript_graph: \n- onnxscript_tracer: \n- fx_name_to_onnxscript_value: Dict[length=111](\np_trunk_pos_embed: `TorchScriptTensor(f32[1, 1024, 1024])`,\np_trunk_attn_pool_latent: `TorchScriptTensor(f32[1, 1, 1024])`,\np_trunk_patch_embed_proj_weight: `TorchScriptTensor(f32[1024, 3, 16, 16])`,\np_trunk_patch_embed_proj_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_weight: `TorchScriptTensor(f32[3072, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_bias: `TorchScriptTensor(f32[3072])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_weight: `TorchScriptTensor(f32[1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_bias: `TorchScriptTensor(f32[1024])`,\n...\n)\n## Return values\n", + "text":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___8___mlp_fc2_bias[name=p_getattr_l__self___trunk_blocks___8___mlp_fc2_bias]. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"FxOnnxInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":414 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0008", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___9___norm1_weight[name=p_getattr_l__self___trunk_blocks___9___norm1_weight]. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature FxOnnxInterpreter.run_node\n- self: \n- node: fx.Node(p_getattr_l__self___trunk_blocks___9___norm1_weight)[placeholder]:Tensor(f32[1024])\n- fx_graph_module: torch.fx.GraphModule()\n- onnxfunction_dispatcher: \n- op_level_debug: False\n- onnxscript_graph: \n- onnxscript_tracer: \n- fx_name_to_onnxscript_value: Dict[length=112](\np_trunk_pos_embed: `TorchScriptTensor(f32[1, 1024, 1024])`,\np_trunk_attn_pool_latent: `TorchScriptTensor(f32[1, 1, 1024])`,\np_trunk_patch_embed_proj_weight: `TorchScriptTensor(f32[1024, 3, 16, 16])`,\np_trunk_patch_embed_proj_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_weight: `TorchScriptTensor(f32[3072, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_bias: `TorchScriptTensor(f32[3072])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_weight: `TorchScriptTensor(f32[1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_bias: `TorchScriptTensor(f32[1024])`,\n...\n)\n## Return values\n", + "text":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___9___norm1_weight[name=p_getattr_l__self___trunk_blocks___9___norm1_weight]. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"FxOnnxInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":414 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0008", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___9___norm1_bias[name=p_getattr_l__self___trunk_blocks___9___norm1_bias]. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature FxOnnxInterpreter.run_node\n- self: \n- node: fx.Node(p_getattr_l__self___trunk_blocks___9___norm1_bias)[placeholder]:Tensor(f32[1024])\n- fx_graph_module: torch.fx.GraphModule()\n- onnxfunction_dispatcher: \n- op_level_debug: False\n- onnxscript_graph: \n- onnxscript_tracer: \n- fx_name_to_onnxscript_value: Dict[length=113](\np_trunk_pos_embed: `TorchScriptTensor(f32[1, 1024, 1024])`,\np_trunk_attn_pool_latent: `TorchScriptTensor(f32[1, 1, 1024])`,\np_trunk_patch_embed_proj_weight: `TorchScriptTensor(f32[1024, 3, 16, 16])`,\np_trunk_patch_embed_proj_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_weight: `TorchScriptTensor(f32[3072, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_bias: `TorchScriptTensor(f32[3072])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_weight: `TorchScriptTensor(f32[1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_bias: `TorchScriptTensor(f32[1024])`,\n...\n)\n## Return values\n", + "text":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___9___norm1_bias[name=p_getattr_l__self___trunk_blocks___9___norm1_bias]. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"FxOnnxInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":414 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0008", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___9___attn_qkv_weight[name=p_getattr_l__self___trunk_blocks___9___attn_qkv_weight]. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature FxOnnxInterpreter.run_node\n- self: \n- node: fx.Node(p_getattr_l__self___trunk_blocks___9___attn_qkv_weight)[placeholder]:Tensor(f32[3072, 1024])\n- fx_graph_module: torch.fx.GraphModule()\n- onnxfunction_dispatcher: \n- op_level_debug: False\n- onnxscript_graph: \n- onnxscript_tracer: \n- fx_name_to_onnxscript_value: Dict[length=114](\np_trunk_pos_embed: `TorchScriptTensor(f32[1, 1024, 1024])`,\np_trunk_attn_pool_latent: `TorchScriptTensor(f32[1, 1, 1024])`,\np_trunk_patch_embed_proj_weight: `TorchScriptTensor(f32[1024, 3, 16, 16])`,\np_trunk_patch_embed_proj_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_weight: `TorchScriptTensor(f32[3072, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_bias: `TorchScriptTensor(f32[3072])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_weight: `TorchScriptTensor(f32[1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_bias: `TorchScriptTensor(f32[1024])`,\n...\n)\n## Return values\n", + "text":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___9___attn_qkv_weight[name=p_getattr_l__self___trunk_blocks___9___attn_qkv_weight]. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"FxOnnxInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":414 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0008", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___9___attn_qkv_bias[name=p_getattr_l__self___trunk_blocks___9___attn_qkv_bias]. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature FxOnnxInterpreter.run_node\n- self: \n- node: fx.Node(p_getattr_l__self___trunk_blocks___9___attn_qkv_bias)[placeholder]:Tensor(f32[3072])\n- fx_graph_module: torch.fx.GraphModule()\n- onnxfunction_dispatcher: \n- op_level_debug: False\n- onnxscript_graph: \n- onnxscript_tracer: \n- fx_name_to_onnxscript_value: Dict[length=115](\np_trunk_pos_embed: `TorchScriptTensor(f32[1, 1024, 1024])`,\np_trunk_attn_pool_latent: `TorchScriptTensor(f32[1, 1, 1024])`,\np_trunk_patch_embed_proj_weight: `TorchScriptTensor(f32[1024, 3, 16, 16])`,\np_trunk_patch_embed_proj_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_weight: `TorchScriptTensor(f32[3072, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_bias: `TorchScriptTensor(f32[3072])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_weight: `TorchScriptTensor(f32[1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_bias: `TorchScriptTensor(f32[1024])`,\n...\n)\n## Return values\n", + "text":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___9___attn_qkv_bias[name=p_getattr_l__self___trunk_blocks___9___attn_qkv_bias]. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"FxOnnxInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":414 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0008", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___9___attn_proj_weight[name=p_getattr_l__self___trunk_blocks___9___attn_proj_weight]. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature FxOnnxInterpreter.run_node\n- self: \n- node: fx.Node(p_getattr_l__self___trunk_blocks___9___attn_proj_weight)[placeholder]:Tensor(f32[1024, 1024])\n- fx_graph_module: torch.fx.GraphModule()\n- onnxfunction_dispatcher: \n- op_level_debug: False\n- onnxscript_graph: \n- onnxscript_tracer: \n- fx_name_to_onnxscript_value: Dict[length=116](\np_trunk_pos_embed: `TorchScriptTensor(f32[1, 1024, 1024])`,\np_trunk_attn_pool_latent: `TorchScriptTensor(f32[1, 1, 1024])`,\np_trunk_patch_embed_proj_weight: `TorchScriptTensor(f32[1024, 3, 16, 16])`,\np_trunk_patch_embed_proj_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_weight: `TorchScriptTensor(f32[3072, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_bias: `TorchScriptTensor(f32[3072])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_weight: `TorchScriptTensor(f32[1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_bias: `TorchScriptTensor(f32[1024])`,\n...\n)\n## Return values\n", + "text":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___9___attn_proj_weight[name=p_getattr_l__self___trunk_blocks___9___attn_proj_weight]. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"FxOnnxInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":414 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0008", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___9___attn_proj_bias[name=p_getattr_l__self___trunk_blocks___9___attn_proj_bias]. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature FxOnnxInterpreter.run_node\n- self: \n- node: fx.Node(p_getattr_l__self___trunk_blocks___9___attn_proj_bias)[placeholder]:Tensor(f32[1024])\n- fx_graph_module: torch.fx.GraphModule()\n- onnxfunction_dispatcher: \n- op_level_debug: False\n- onnxscript_graph: \n- onnxscript_tracer: \n- fx_name_to_onnxscript_value: Dict[length=117](\np_trunk_pos_embed: `TorchScriptTensor(f32[1, 1024, 1024])`,\np_trunk_attn_pool_latent: `TorchScriptTensor(f32[1, 1, 1024])`,\np_trunk_patch_embed_proj_weight: `TorchScriptTensor(f32[1024, 3, 16, 16])`,\np_trunk_patch_embed_proj_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_weight: `TorchScriptTensor(f32[3072, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_bias: `TorchScriptTensor(f32[3072])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_weight: `TorchScriptTensor(f32[1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_bias: `TorchScriptTensor(f32[1024])`,\n...\n)\n## Return values\n", + "text":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___9___attn_proj_bias[name=p_getattr_l__self___trunk_blocks___9___attn_proj_bias]. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"FxOnnxInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":414 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0008", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___9___norm2_weight[name=p_getattr_l__self___trunk_blocks___9___norm2_weight]. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature FxOnnxInterpreter.run_node\n- self: \n- node: fx.Node(p_getattr_l__self___trunk_blocks___9___norm2_weight)[placeholder]:Tensor(f32[1024])\n- fx_graph_module: torch.fx.GraphModule()\n- onnxfunction_dispatcher: \n- op_level_debug: False\n- onnxscript_graph: \n- onnxscript_tracer: \n- fx_name_to_onnxscript_value: Dict[length=118](\np_trunk_pos_embed: `TorchScriptTensor(f32[1, 1024, 1024])`,\np_trunk_attn_pool_latent: `TorchScriptTensor(f32[1, 1, 1024])`,\np_trunk_patch_embed_proj_weight: `TorchScriptTensor(f32[1024, 3, 16, 16])`,\np_trunk_patch_embed_proj_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_weight: `TorchScriptTensor(f32[3072, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_bias: `TorchScriptTensor(f32[3072])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_weight: `TorchScriptTensor(f32[1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_bias: `TorchScriptTensor(f32[1024])`,\n...\n)\n## Return values\n", + "text":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___9___norm2_weight[name=p_getattr_l__self___trunk_blocks___9___norm2_weight]. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"FxOnnxInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":414 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0008", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___9___norm2_bias[name=p_getattr_l__self___trunk_blocks___9___norm2_bias]. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature FxOnnxInterpreter.run_node\n- self: \n- node: fx.Node(p_getattr_l__self___trunk_blocks___9___norm2_bias)[placeholder]:Tensor(f32[1024])\n- fx_graph_module: torch.fx.GraphModule()\n- onnxfunction_dispatcher: \n- op_level_debug: False\n- onnxscript_graph: \n- onnxscript_tracer: \n- fx_name_to_onnxscript_value: Dict[length=119](\np_trunk_pos_embed: `TorchScriptTensor(f32[1, 1024, 1024])`,\np_trunk_attn_pool_latent: `TorchScriptTensor(f32[1, 1, 1024])`,\np_trunk_patch_embed_proj_weight: `TorchScriptTensor(f32[1024, 3, 16, 16])`,\np_trunk_patch_embed_proj_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_weight: `TorchScriptTensor(f32[3072, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_bias: `TorchScriptTensor(f32[3072])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_weight: `TorchScriptTensor(f32[1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_bias: `TorchScriptTensor(f32[1024])`,\n...\n)\n## Return values\n", + "text":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___9___norm2_bias[name=p_getattr_l__self___trunk_blocks___9___norm2_bias]. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"FxOnnxInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":414 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0008", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___9___mlp_fc1_weight[name=p_getattr_l__self___trunk_blocks___9___mlp_fc1_weight]. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature FxOnnxInterpreter.run_node\n- self: \n- node: fx.Node(p_getattr_l__self___trunk_blocks___9___mlp_fc1_weight)[placeholder]:Tensor(f32[4096, 1024])\n- fx_graph_module: torch.fx.GraphModule()\n- onnxfunction_dispatcher: \n- op_level_debug: False\n- onnxscript_graph: \n- onnxscript_tracer: \n- fx_name_to_onnxscript_value: Dict[length=120](\np_trunk_pos_embed: `TorchScriptTensor(f32[1, 1024, 1024])`,\np_trunk_attn_pool_latent: `TorchScriptTensor(f32[1, 1, 1024])`,\np_trunk_patch_embed_proj_weight: `TorchScriptTensor(f32[1024, 3, 16, 16])`,\np_trunk_patch_embed_proj_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_weight: `TorchScriptTensor(f32[3072, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_bias: `TorchScriptTensor(f32[3072])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_weight: `TorchScriptTensor(f32[1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_bias: `TorchScriptTensor(f32[1024])`,\n...\n)\n## Return values\n", + "text":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___9___mlp_fc1_weight[name=p_getattr_l__self___trunk_blocks___9___mlp_fc1_weight]. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"FxOnnxInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":414 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0008", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___9___mlp_fc1_bias[name=p_getattr_l__self___trunk_blocks___9___mlp_fc1_bias]. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature FxOnnxInterpreter.run_node\n- self: \n- node: fx.Node(p_getattr_l__self___trunk_blocks___9___mlp_fc1_bias)[placeholder]:Tensor(f32[4096])\n- fx_graph_module: torch.fx.GraphModule()\n- onnxfunction_dispatcher: \n- op_level_debug: False\n- onnxscript_graph: \n- onnxscript_tracer: \n- fx_name_to_onnxscript_value: Dict[length=121](\np_trunk_pos_embed: `TorchScriptTensor(f32[1, 1024, 1024])`,\np_trunk_attn_pool_latent: `TorchScriptTensor(f32[1, 1, 1024])`,\np_trunk_patch_embed_proj_weight: `TorchScriptTensor(f32[1024, 3, 16, 16])`,\np_trunk_patch_embed_proj_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_weight: `TorchScriptTensor(f32[3072, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_bias: `TorchScriptTensor(f32[3072])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_weight: `TorchScriptTensor(f32[1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_bias: `TorchScriptTensor(f32[1024])`,\n...\n)\n## Return values\n", + "text":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___9___mlp_fc1_bias[name=p_getattr_l__self___trunk_blocks___9___mlp_fc1_bias]. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"FxOnnxInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":414 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0008", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___9___mlp_fc2_weight[name=p_getattr_l__self___trunk_blocks___9___mlp_fc2_weight]. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature FxOnnxInterpreter.run_node\n- self: \n- node: fx.Node(p_getattr_l__self___trunk_blocks___9___mlp_fc2_weight)[placeholder]:Tensor(f32[1024, 4096])\n- fx_graph_module: torch.fx.GraphModule()\n- onnxfunction_dispatcher: \n- op_level_debug: False\n- onnxscript_graph: \n- onnxscript_tracer: \n- fx_name_to_onnxscript_value: Dict[length=122](\np_trunk_pos_embed: `TorchScriptTensor(f32[1, 1024, 1024])`,\np_trunk_attn_pool_latent: `TorchScriptTensor(f32[1, 1, 1024])`,\np_trunk_patch_embed_proj_weight: `TorchScriptTensor(f32[1024, 3, 16, 16])`,\np_trunk_patch_embed_proj_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_weight: `TorchScriptTensor(f32[3072, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_bias: `TorchScriptTensor(f32[3072])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_weight: `TorchScriptTensor(f32[1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_bias: `TorchScriptTensor(f32[1024])`,\n...\n)\n## Return values\n", + "text":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___9___mlp_fc2_weight[name=p_getattr_l__self___trunk_blocks___9___mlp_fc2_weight]. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"FxOnnxInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":414 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0008", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___9___mlp_fc2_bias[name=p_getattr_l__self___trunk_blocks___9___mlp_fc2_bias]. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature FxOnnxInterpreter.run_node\n- self: \n- node: fx.Node(p_getattr_l__self___trunk_blocks___9___mlp_fc2_bias)[placeholder]:Tensor(f32[1024])\n- fx_graph_module: torch.fx.GraphModule()\n- onnxfunction_dispatcher: \n- op_level_debug: False\n- onnxscript_graph: \n- onnxscript_tracer: \n- fx_name_to_onnxscript_value: Dict[length=123](\np_trunk_pos_embed: `TorchScriptTensor(f32[1, 1024, 1024])`,\np_trunk_attn_pool_latent: `TorchScriptTensor(f32[1, 1, 1024])`,\np_trunk_patch_embed_proj_weight: `TorchScriptTensor(f32[1024, 3, 16, 16])`,\np_trunk_patch_embed_proj_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_weight: `TorchScriptTensor(f32[3072, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_bias: `TorchScriptTensor(f32[3072])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_weight: `TorchScriptTensor(f32[1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_bias: `TorchScriptTensor(f32[1024])`,\n...\n)\n## Return values\n", + "text":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___9___mlp_fc2_bias[name=p_getattr_l__self___trunk_blocks___9___mlp_fc2_bias]. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"FxOnnxInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":414 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0008", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___10___norm1_weight[name=p_getattr_l__self___trunk_blocks___10___norm1_weight]. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature FxOnnxInterpreter.run_node\n- self: \n- node: fx.Node(p_getattr_l__self___trunk_blocks___10___norm1_weight)[placeholder]:Tensor(f32[1024])\n- fx_graph_module: torch.fx.GraphModule()\n- onnxfunction_dispatcher: \n- op_level_debug: False\n- onnxscript_graph: \n- onnxscript_tracer: \n- fx_name_to_onnxscript_value: Dict[length=124](\np_trunk_pos_embed: `TorchScriptTensor(f32[1, 1024, 1024])`,\np_trunk_attn_pool_latent: `TorchScriptTensor(f32[1, 1, 1024])`,\np_trunk_patch_embed_proj_weight: `TorchScriptTensor(f32[1024, 3, 16, 16])`,\np_trunk_patch_embed_proj_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_weight: `TorchScriptTensor(f32[3072, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_bias: `TorchScriptTensor(f32[3072])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_weight: `TorchScriptTensor(f32[1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_bias: `TorchScriptTensor(f32[1024])`,\n...\n)\n## Return values\n", + "text":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___10___norm1_weight[name=p_getattr_l__self___trunk_blocks___10___norm1_weight]. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"FxOnnxInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":414 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0008", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___10___norm1_bias[name=p_getattr_l__self___trunk_blocks___10___norm1_bias]. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature FxOnnxInterpreter.run_node\n- self: \n- node: fx.Node(p_getattr_l__self___trunk_blocks___10___norm1_bias)[placeholder]:Tensor(f32[1024])\n- fx_graph_module: torch.fx.GraphModule()\n- onnxfunction_dispatcher: \n- op_level_debug: False\n- onnxscript_graph: \n- onnxscript_tracer: \n- fx_name_to_onnxscript_value: Dict[length=125](\np_trunk_pos_embed: `TorchScriptTensor(f32[1, 1024, 1024])`,\np_trunk_attn_pool_latent: `TorchScriptTensor(f32[1, 1, 1024])`,\np_trunk_patch_embed_proj_weight: `TorchScriptTensor(f32[1024, 3, 16, 16])`,\np_trunk_patch_embed_proj_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_weight: `TorchScriptTensor(f32[3072, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_bias: `TorchScriptTensor(f32[3072])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_weight: `TorchScriptTensor(f32[1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_bias: `TorchScriptTensor(f32[1024])`,\n...\n)\n## Return values\n", + "text":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___10___norm1_bias[name=p_getattr_l__self___trunk_blocks___10___norm1_bias]. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"FxOnnxInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":414 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0008", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___10___attn_qkv_weight[name=p_getattr_l__self___trunk_blocks___10___attn_qkv_weight]. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature FxOnnxInterpreter.run_node\n- self: \n- node: fx.Node(p_getattr_l__self___trunk_blocks___10___attn_qkv_weight)[placeholder]:Tensor(f32[3072, 1024])\n- fx_graph_module: torch.fx.GraphModule()\n- onnxfunction_dispatcher: \n- op_level_debug: False\n- onnxscript_graph: \n- onnxscript_tracer: \n- fx_name_to_onnxscript_value: Dict[length=126](\np_trunk_pos_embed: `TorchScriptTensor(f32[1, 1024, 1024])`,\np_trunk_attn_pool_latent: `TorchScriptTensor(f32[1, 1, 1024])`,\np_trunk_patch_embed_proj_weight: `TorchScriptTensor(f32[1024, 3, 16, 16])`,\np_trunk_patch_embed_proj_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_weight: `TorchScriptTensor(f32[3072, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_bias: `TorchScriptTensor(f32[3072])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_weight: `TorchScriptTensor(f32[1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_bias: `TorchScriptTensor(f32[1024])`,\n...\n)\n## Return values\n", + "text":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___10___attn_qkv_weight[name=p_getattr_l__self___trunk_blocks___10___attn_qkv_weight]. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"FxOnnxInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":414 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0008", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___10___attn_qkv_bias[name=p_getattr_l__self___trunk_blocks___10___attn_qkv_bias]. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature FxOnnxInterpreter.run_node\n- self: \n- node: fx.Node(p_getattr_l__self___trunk_blocks___10___attn_qkv_bias)[placeholder]:Tensor(f32[3072])\n- fx_graph_module: torch.fx.GraphModule()\n- onnxfunction_dispatcher: \n- op_level_debug: False\n- onnxscript_graph: \n- onnxscript_tracer: \n- fx_name_to_onnxscript_value: Dict[length=127](\np_trunk_pos_embed: `TorchScriptTensor(f32[1, 1024, 1024])`,\np_trunk_attn_pool_latent: `TorchScriptTensor(f32[1, 1, 1024])`,\np_trunk_patch_embed_proj_weight: `TorchScriptTensor(f32[1024, 3, 16, 16])`,\np_trunk_patch_embed_proj_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_weight: `TorchScriptTensor(f32[3072, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_bias: `TorchScriptTensor(f32[3072])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_weight: `TorchScriptTensor(f32[1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_bias: `TorchScriptTensor(f32[1024])`,\n...\n)\n## Return values\n", + "text":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___10___attn_qkv_bias[name=p_getattr_l__self___trunk_blocks___10___attn_qkv_bias]. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"FxOnnxInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":414 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0008", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___10___attn_proj_weight[name=p_getattr_l__self___trunk_blocks___10___attn_proj_weight]. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature FxOnnxInterpreter.run_node\n- self: \n- node: fx.Node(p_getattr_l__self___trunk_blocks___10___attn_proj_weight)[placeholder]:Tensor(f32[1024, 1024])\n- fx_graph_module: torch.fx.GraphModule()\n- onnxfunction_dispatcher: \n- op_level_debug: False\n- onnxscript_graph: \n- onnxscript_tracer: \n- fx_name_to_onnxscript_value: Dict[length=128](\np_trunk_pos_embed: `TorchScriptTensor(f32[1, 1024, 1024])`,\np_trunk_attn_pool_latent: `TorchScriptTensor(f32[1, 1, 1024])`,\np_trunk_patch_embed_proj_weight: `TorchScriptTensor(f32[1024, 3, 16, 16])`,\np_trunk_patch_embed_proj_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_weight: `TorchScriptTensor(f32[3072, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_bias: `TorchScriptTensor(f32[3072])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_weight: `TorchScriptTensor(f32[1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_bias: `TorchScriptTensor(f32[1024])`,\n...\n)\n## Return values\n", + "text":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___10___attn_proj_weight[name=p_getattr_l__self___trunk_blocks___10___attn_proj_weight]. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"FxOnnxInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":414 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0008", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___10___attn_proj_bias[name=p_getattr_l__self___trunk_blocks___10___attn_proj_bias]. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature FxOnnxInterpreter.run_node\n- self: \n- node: fx.Node(p_getattr_l__self___trunk_blocks___10___attn_proj_bias)[placeholder]:Tensor(f32[1024])\n- fx_graph_module: torch.fx.GraphModule()\n- onnxfunction_dispatcher: \n- op_level_debug: False\n- onnxscript_graph: \n- onnxscript_tracer: \n- fx_name_to_onnxscript_value: Dict[length=129](\np_trunk_pos_embed: `TorchScriptTensor(f32[1, 1024, 1024])`,\np_trunk_attn_pool_latent: `TorchScriptTensor(f32[1, 1, 1024])`,\np_trunk_patch_embed_proj_weight: `TorchScriptTensor(f32[1024, 3, 16, 16])`,\np_trunk_patch_embed_proj_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_weight: `TorchScriptTensor(f32[3072, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_bias: `TorchScriptTensor(f32[3072])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_weight: `TorchScriptTensor(f32[1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_bias: `TorchScriptTensor(f32[1024])`,\n...\n)\n## Return values\n", + "text":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___10___attn_proj_bias[name=p_getattr_l__self___trunk_blocks___10___attn_proj_bias]. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"FxOnnxInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":414 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0008", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___10___norm2_weight[name=p_getattr_l__self___trunk_blocks___10___norm2_weight]. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature FxOnnxInterpreter.run_node\n- self: \n- node: fx.Node(p_getattr_l__self___trunk_blocks___10___norm2_weight)[placeholder]:Tensor(f32[1024])\n- fx_graph_module: torch.fx.GraphModule()\n- onnxfunction_dispatcher: \n- op_level_debug: False\n- onnxscript_graph: \n- onnxscript_tracer: \n- fx_name_to_onnxscript_value: Dict[length=130](\np_trunk_pos_embed: `TorchScriptTensor(f32[1, 1024, 1024])`,\np_trunk_attn_pool_latent: `TorchScriptTensor(f32[1, 1, 1024])`,\np_trunk_patch_embed_proj_weight: `TorchScriptTensor(f32[1024, 3, 16, 16])`,\np_trunk_patch_embed_proj_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_weight: `TorchScriptTensor(f32[3072, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_bias: `TorchScriptTensor(f32[3072])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_weight: `TorchScriptTensor(f32[1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_bias: `TorchScriptTensor(f32[1024])`,\n...\n)\n## Return values\n", + "text":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___10___norm2_weight[name=p_getattr_l__self___trunk_blocks___10___norm2_weight]. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"FxOnnxInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":414 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0008", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___10___norm2_bias[name=p_getattr_l__self___trunk_blocks___10___norm2_bias]. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature FxOnnxInterpreter.run_node\n- self: \n- node: fx.Node(p_getattr_l__self___trunk_blocks___10___norm2_bias)[placeholder]:Tensor(f32[1024])\n- fx_graph_module: torch.fx.GraphModule()\n- onnxfunction_dispatcher: \n- op_level_debug: False\n- onnxscript_graph: \n- onnxscript_tracer: \n- fx_name_to_onnxscript_value: Dict[length=131](\np_trunk_pos_embed: `TorchScriptTensor(f32[1, 1024, 1024])`,\np_trunk_attn_pool_latent: `TorchScriptTensor(f32[1, 1, 1024])`,\np_trunk_patch_embed_proj_weight: `TorchScriptTensor(f32[1024, 3, 16, 16])`,\np_trunk_patch_embed_proj_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_weight: `TorchScriptTensor(f32[3072, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_bias: `TorchScriptTensor(f32[3072])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_weight: `TorchScriptTensor(f32[1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_bias: `TorchScriptTensor(f32[1024])`,\n...\n)\n## Return values\n", + "text":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___10___norm2_bias[name=p_getattr_l__self___trunk_blocks___10___norm2_bias]. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"FxOnnxInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":414 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0008", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___10___mlp_fc1_weight[name=p_getattr_l__self___trunk_blocks___10___mlp_fc1_weight]. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature FxOnnxInterpreter.run_node\n- self: \n- node: fx.Node(p_getattr_l__self___trunk_blocks___10___mlp_fc1_weight)[placeholder]:Tensor(f32[4096, 1024])\n- fx_graph_module: torch.fx.GraphModule()\n- onnxfunction_dispatcher: \n- op_level_debug: False\n- onnxscript_graph: \n- onnxscript_tracer: \n- fx_name_to_onnxscript_value: Dict[length=132](\np_trunk_pos_embed: `TorchScriptTensor(f32[1, 1024, 1024])`,\np_trunk_attn_pool_latent: `TorchScriptTensor(f32[1, 1, 1024])`,\np_trunk_patch_embed_proj_weight: `TorchScriptTensor(f32[1024, 3, 16, 16])`,\np_trunk_patch_embed_proj_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_weight: `TorchScriptTensor(f32[3072, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_bias: `TorchScriptTensor(f32[3072])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_weight: `TorchScriptTensor(f32[1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_bias: `TorchScriptTensor(f32[1024])`,\n...\n)\n## Return values\n", + "text":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___10___mlp_fc1_weight[name=p_getattr_l__self___trunk_blocks___10___mlp_fc1_weight]. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"FxOnnxInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":414 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0008", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___10___mlp_fc1_bias[name=p_getattr_l__self___trunk_blocks___10___mlp_fc1_bias]. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature FxOnnxInterpreter.run_node\n- self: \n- node: fx.Node(p_getattr_l__self___trunk_blocks___10___mlp_fc1_bias)[placeholder]:Tensor(f32[4096])\n- fx_graph_module: torch.fx.GraphModule()\n- onnxfunction_dispatcher: \n- op_level_debug: False\n- onnxscript_graph: \n- onnxscript_tracer: \n- fx_name_to_onnxscript_value: Dict[length=133](\np_trunk_pos_embed: `TorchScriptTensor(f32[1, 1024, 1024])`,\np_trunk_attn_pool_latent: `TorchScriptTensor(f32[1, 1, 1024])`,\np_trunk_patch_embed_proj_weight: `TorchScriptTensor(f32[1024, 3, 16, 16])`,\np_trunk_patch_embed_proj_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_weight: `TorchScriptTensor(f32[3072, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_bias: `TorchScriptTensor(f32[3072])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_weight: `TorchScriptTensor(f32[1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_bias: `TorchScriptTensor(f32[1024])`,\n...\n)\n## Return values\n", + "text":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___10___mlp_fc1_bias[name=p_getattr_l__self___trunk_blocks___10___mlp_fc1_bias]. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"FxOnnxInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":414 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0008", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___10___mlp_fc2_weight[name=p_getattr_l__self___trunk_blocks___10___mlp_fc2_weight]. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature FxOnnxInterpreter.run_node\n- self: \n- node: fx.Node(p_getattr_l__self___trunk_blocks___10___mlp_fc2_weight)[placeholder]:Tensor(f32[1024, 4096])\n- fx_graph_module: torch.fx.GraphModule()\n- onnxfunction_dispatcher: \n- op_level_debug: False\n- onnxscript_graph: \n- onnxscript_tracer: \n- fx_name_to_onnxscript_value: Dict[length=134](\np_trunk_pos_embed: `TorchScriptTensor(f32[1, 1024, 1024])`,\np_trunk_attn_pool_latent: `TorchScriptTensor(f32[1, 1, 1024])`,\np_trunk_patch_embed_proj_weight: `TorchScriptTensor(f32[1024, 3, 16, 16])`,\np_trunk_patch_embed_proj_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_weight: `TorchScriptTensor(f32[3072, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_bias: `TorchScriptTensor(f32[3072])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_weight: `TorchScriptTensor(f32[1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_bias: `TorchScriptTensor(f32[1024])`,\n...\n)\n## Return values\n", + "text":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___10___mlp_fc2_weight[name=p_getattr_l__self___trunk_blocks___10___mlp_fc2_weight]. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"FxOnnxInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":414 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0008", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___10___mlp_fc2_bias[name=p_getattr_l__self___trunk_blocks___10___mlp_fc2_bias]. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature FxOnnxInterpreter.run_node\n- self: \n- node: fx.Node(p_getattr_l__self___trunk_blocks___10___mlp_fc2_bias)[placeholder]:Tensor(f32[1024])\n- fx_graph_module: torch.fx.GraphModule()\n- onnxfunction_dispatcher: \n- op_level_debug: False\n- onnxscript_graph: \n- onnxscript_tracer: \n- fx_name_to_onnxscript_value: Dict[length=135](\np_trunk_pos_embed: `TorchScriptTensor(f32[1, 1024, 1024])`,\np_trunk_attn_pool_latent: `TorchScriptTensor(f32[1, 1, 1024])`,\np_trunk_patch_embed_proj_weight: `TorchScriptTensor(f32[1024, 3, 16, 16])`,\np_trunk_patch_embed_proj_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_weight: `TorchScriptTensor(f32[3072, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_bias: `TorchScriptTensor(f32[3072])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_weight: `TorchScriptTensor(f32[1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_bias: `TorchScriptTensor(f32[1024])`,\n...\n)\n## Return values\n", + "text":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___10___mlp_fc2_bias[name=p_getattr_l__self___trunk_blocks___10___mlp_fc2_bias]. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"FxOnnxInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":414 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0008", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___11___norm1_weight[name=p_getattr_l__self___trunk_blocks___11___norm1_weight]. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature FxOnnxInterpreter.run_node\n- self: \n- node: fx.Node(p_getattr_l__self___trunk_blocks___11___norm1_weight)[placeholder]:Tensor(f32[1024])\n- fx_graph_module: torch.fx.GraphModule()\n- onnxfunction_dispatcher: \n- op_level_debug: False\n- onnxscript_graph: \n- onnxscript_tracer: \n- fx_name_to_onnxscript_value: Dict[length=136](\np_trunk_pos_embed: `TorchScriptTensor(f32[1, 1024, 1024])`,\np_trunk_attn_pool_latent: `TorchScriptTensor(f32[1, 1, 1024])`,\np_trunk_patch_embed_proj_weight: `TorchScriptTensor(f32[1024, 3, 16, 16])`,\np_trunk_patch_embed_proj_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_weight: `TorchScriptTensor(f32[3072, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_bias: `TorchScriptTensor(f32[3072])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_weight: `TorchScriptTensor(f32[1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_bias: `TorchScriptTensor(f32[1024])`,\n...\n)\n## Return values\n", + "text":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___11___norm1_weight[name=p_getattr_l__self___trunk_blocks___11___norm1_weight]. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"FxOnnxInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":414 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0008", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___11___norm1_bias[name=p_getattr_l__self___trunk_blocks___11___norm1_bias]. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature FxOnnxInterpreter.run_node\n- self: \n- node: fx.Node(p_getattr_l__self___trunk_blocks___11___norm1_bias)[placeholder]:Tensor(f32[1024])\n- fx_graph_module: torch.fx.GraphModule()\n- onnxfunction_dispatcher: \n- op_level_debug: False\n- onnxscript_graph: \n- onnxscript_tracer: \n- fx_name_to_onnxscript_value: Dict[length=137](\np_trunk_pos_embed: `TorchScriptTensor(f32[1, 1024, 1024])`,\np_trunk_attn_pool_latent: `TorchScriptTensor(f32[1, 1, 1024])`,\np_trunk_patch_embed_proj_weight: `TorchScriptTensor(f32[1024, 3, 16, 16])`,\np_trunk_patch_embed_proj_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_weight: `TorchScriptTensor(f32[3072, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_bias: `TorchScriptTensor(f32[3072])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_weight: `TorchScriptTensor(f32[1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_bias: `TorchScriptTensor(f32[1024])`,\n...\n)\n## Return values\n", + "text":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___11___norm1_bias[name=p_getattr_l__self___trunk_blocks___11___norm1_bias]. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"FxOnnxInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":414 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0008", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___11___attn_qkv_weight[name=p_getattr_l__self___trunk_blocks___11___attn_qkv_weight]. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature FxOnnxInterpreter.run_node\n- self: \n- node: fx.Node(p_getattr_l__self___trunk_blocks___11___attn_qkv_weight)[placeholder]:Tensor(f32[3072, 1024])\n- fx_graph_module: torch.fx.GraphModule()\n- onnxfunction_dispatcher: \n- op_level_debug: False\n- onnxscript_graph: \n- onnxscript_tracer: \n- fx_name_to_onnxscript_value: Dict[length=138](\np_trunk_pos_embed: `TorchScriptTensor(f32[1, 1024, 1024])`,\np_trunk_attn_pool_latent: `TorchScriptTensor(f32[1, 1, 1024])`,\np_trunk_patch_embed_proj_weight: `TorchScriptTensor(f32[1024, 3, 16, 16])`,\np_trunk_patch_embed_proj_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_weight: `TorchScriptTensor(f32[3072, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_bias: `TorchScriptTensor(f32[3072])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_weight: `TorchScriptTensor(f32[1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_bias: `TorchScriptTensor(f32[1024])`,\n...\n)\n## Return values\n", + "text":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___11___attn_qkv_weight[name=p_getattr_l__self___trunk_blocks___11___attn_qkv_weight]. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"FxOnnxInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":414 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0008", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___11___attn_qkv_bias[name=p_getattr_l__self___trunk_blocks___11___attn_qkv_bias]. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature FxOnnxInterpreter.run_node\n- self: \n- node: fx.Node(p_getattr_l__self___trunk_blocks___11___attn_qkv_bias)[placeholder]:Tensor(f32[3072])\n- fx_graph_module: torch.fx.GraphModule()\n- onnxfunction_dispatcher: \n- op_level_debug: False\n- onnxscript_graph: \n- onnxscript_tracer: \n- fx_name_to_onnxscript_value: Dict[length=139](\np_trunk_pos_embed: `TorchScriptTensor(f32[1, 1024, 1024])`,\np_trunk_attn_pool_latent: `TorchScriptTensor(f32[1, 1, 1024])`,\np_trunk_patch_embed_proj_weight: `TorchScriptTensor(f32[1024, 3, 16, 16])`,\np_trunk_patch_embed_proj_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_weight: `TorchScriptTensor(f32[3072, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_bias: `TorchScriptTensor(f32[3072])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_weight: `TorchScriptTensor(f32[1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_bias: `TorchScriptTensor(f32[1024])`,\n...\n)\n## Return values\n", + "text":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___11___attn_qkv_bias[name=p_getattr_l__self___trunk_blocks___11___attn_qkv_bias]. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"FxOnnxInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":414 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0008", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___11___attn_proj_weight[name=p_getattr_l__self___trunk_blocks___11___attn_proj_weight]. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature FxOnnxInterpreter.run_node\n- self: \n- node: fx.Node(p_getattr_l__self___trunk_blocks___11___attn_proj_weight)[placeholder]:Tensor(f32[1024, 1024])\n- fx_graph_module: torch.fx.GraphModule()\n- onnxfunction_dispatcher: \n- op_level_debug: False\n- onnxscript_graph: \n- onnxscript_tracer: \n- fx_name_to_onnxscript_value: Dict[length=140](\np_trunk_pos_embed: `TorchScriptTensor(f32[1, 1024, 1024])`,\np_trunk_attn_pool_latent: `TorchScriptTensor(f32[1, 1, 1024])`,\np_trunk_patch_embed_proj_weight: `TorchScriptTensor(f32[1024, 3, 16, 16])`,\np_trunk_patch_embed_proj_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_weight: `TorchScriptTensor(f32[3072, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_bias: `TorchScriptTensor(f32[3072])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_weight: `TorchScriptTensor(f32[1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_bias: `TorchScriptTensor(f32[1024])`,\n...\n)\n## Return values\n", + "text":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___11___attn_proj_weight[name=p_getattr_l__self___trunk_blocks___11___attn_proj_weight]. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"FxOnnxInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":414 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0008", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___11___attn_proj_bias[name=p_getattr_l__self___trunk_blocks___11___attn_proj_bias]. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature FxOnnxInterpreter.run_node\n- self: \n- node: fx.Node(p_getattr_l__self___trunk_blocks___11___attn_proj_bias)[placeholder]:Tensor(f32[1024])\n- fx_graph_module: torch.fx.GraphModule()\n- onnxfunction_dispatcher: \n- op_level_debug: False\n- onnxscript_graph: \n- onnxscript_tracer: \n- fx_name_to_onnxscript_value: Dict[length=141](\np_trunk_pos_embed: `TorchScriptTensor(f32[1, 1024, 1024])`,\np_trunk_attn_pool_latent: `TorchScriptTensor(f32[1, 1, 1024])`,\np_trunk_patch_embed_proj_weight: `TorchScriptTensor(f32[1024, 3, 16, 16])`,\np_trunk_patch_embed_proj_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_weight: `TorchScriptTensor(f32[3072, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_bias: `TorchScriptTensor(f32[3072])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_weight: `TorchScriptTensor(f32[1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_bias: `TorchScriptTensor(f32[1024])`,\n...\n)\n## Return values\n", + "text":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___11___attn_proj_bias[name=p_getattr_l__self___trunk_blocks___11___attn_proj_bias]. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"FxOnnxInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":414 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0008", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___11___norm2_weight[name=p_getattr_l__self___trunk_blocks___11___norm2_weight]. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature FxOnnxInterpreter.run_node\n- self: \n- node: fx.Node(p_getattr_l__self___trunk_blocks___11___norm2_weight)[placeholder]:Tensor(f32[1024])\n- fx_graph_module: torch.fx.GraphModule()\n- onnxfunction_dispatcher: \n- op_level_debug: False\n- onnxscript_graph: \n- onnxscript_tracer: \n- fx_name_to_onnxscript_value: Dict[length=142](\np_trunk_pos_embed: `TorchScriptTensor(f32[1, 1024, 1024])`,\np_trunk_attn_pool_latent: `TorchScriptTensor(f32[1, 1, 1024])`,\np_trunk_patch_embed_proj_weight: `TorchScriptTensor(f32[1024, 3, 16, 16])`,\np_trunk_patch_embed_proj_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_weight: `TorchScriptTensor(f32[3072, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_bias: `TorchScriptTensor(f32[3072])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_weight: `TorchScriptTensor(f32[1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_bias: `TorchScriptTensor(f32[1024])`,\n...\n)\n## Return values\n", + "text":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___11___norm2_weight[name=p_getattr_l__self___trunk_blocks___11___norm2_weight]. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"FxOnnxInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":414 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0008", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___11___norm2_bias[name=p_getattr_l__self___trunk_blocks___11___norm2_bias]. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature FxOnnxInterpreter.run_node\n- self: \n- node: fx.Node(p_getattr_l__self___trunk_blocks___11___norm2_bias)[placeholder]:Tensor(f32[1024])\n- fx_graph_module: torch.fx.GraphModule()\n- onnxfunction_dispatcher: \n- op_level_debug: False\n- onnxscript_graph: \n- onnxscript_tracer: \n- fx_name_to_onnxscript_value: Dict[length=143](\np_trunk_pos_embed: `TorchScriptTensor(f32[1, 1024, 1024])`,\np_trunk_attn_pool_latent: `TorchScriptTensor(f32[1, 1, 1024])`,\np_trunk_patch_embed_proj_weight: `TorchScriptTensor(f32[1024, 3, 16, 16])`,\np_trunk_patch_embed_proj_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_weight: `TorchScriptTensor(f32[3072, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_bias: `TorchScriptTensor(f32[3072])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_weight: `TorchScriptTensor(f32[1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_bias: `TorchScriptTensor(f32[1024])`,\n...\n)\n## Return values\n", + "text":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___11___norm2_bias[name=p_getattr_l__self___trunk_blocks___11___norm2_bias]. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"FxOnnxInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":414 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0008", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___11___mlp_fc1_weight[name=p_getattr_l__self___trunk_blocks___11___mlp_fc1_weight]. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature FxOnnxInterpreter.run_node\n- self: \n- node: fx.Node(p_getattr_l__self___trunk_blocks___11___mlp_fc1_weight)[placeholder]:Tensor(f32[4096, 1024])\n- fx_graph_module: torch.fx.GraphModule()\n- onnxfunction_dispatcher: \n- op_level_debug: False\n- onnxscript_graph: \n- onnxscript_tracer: \n- fx_name_to_onnxscript_value: Dict[length=144](\np_trunk_pos_embed: `TorchScriptTensor(f32[1, 1024, 1024])`,\np_trunk_attn_pool_latent: `TorchScriptTensor(f32[1, 1, 1024])`,\np_trunk_patch_embed_proj_weight: `TorchScriptTensor(f32[1024, 3, 16, 16])`,\np_trunk_patch_embed_proj_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_weight: `TorchScriptTensor(f32[3072, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_bias: `TorchScriptTensor(f32[3072])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_weight: `TorchScriptTensor(f32[1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_bias: `TorchScriptTensor(f32[1024])`,\n...\n)\n## Return values\n", + "text":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___11___mlp_fc1_weight[name=p_getattr_l__self___trunk_blocks___11___mlp_fc1_weight]. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"FxOnnxInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":414 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0008", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___11___mlp_fc1_bias[name=p_getattr_l__self___trunk_blocks___11___mlp_fc1_bias]. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature FxOnnxInterpreter.run_node\n- self: \n- node: fx.Node(p_getattr_l__self___trunk_blocks___11___mlp_fc1_bias)[placeholder]:Tensor(f32[4096])\n- fx_graph_module: torch.fx.GraphModule()\n- onnxfunction_dispatcher: \n- op_level_debug: False\n- onnxscript_graph: \n- onnxscript_tracer: \n- fx_name_to_onnxscript_value: Dict[length=145](\np_trunk_pos_embed: `TorchScriptTensor(f32[1, 1024, 1024])`,\np_trunk_attn_pool_latent: `TorchScriptTensor(f32[1, 1, 1024])`,\np_trunk_patch_embed_proj_weight: `TorchScriptTensor(f32[1024, 3, 16, 16])`,\np_trunk_patch_embed_proj_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_weight: `TorchScriptTensor(f32[3072, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_bias: `TorchScriptTensor(f32[3072])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_weight: `TorchScriptTensor(f32[1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_bias: `TorchScriptTensor(f32[1024])`,\n...\n)\n## Return values\n", + "text":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___11___mlp_fc1_bias[name=p_getattr_l__self___trunk_blocks___11___mlp_fc1_bias]. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"FxOnnxInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":414 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0008", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___11___mlp_fc2_weight[name=p_getattr_l__self___trunk_blocks___11___mlp_fc2_weight]. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature FxOnnxInterpreter.run_node\n- self: \n- node: fx.Node(p_getattr_l__self___trunk_blocks___11___mlp_fc2_weight)[placeholder]:Tensor(f32[1024, 4096])\n- fx_graph_module: torch.fx.GraphModule()\n- onnxfunction_dispatcher: \n- op_level_debug: False\n- onnxscript_graph: \n- onnxscript_tracer: \n- fx_name_to_onnxscript_value: Dict[length=146](\np_trunk_pos_embed: `TorchScriptTensor(f32[1, 1024, 1024])`,\np_trunk_attn_pool_latent: `TorchScriptTensor(f32[1, 1, 1024])`,\np_trunk_patch_embed_proj_weight: `TorchScriptTensor(f32[1024, 3, 16, 16])`,\np_trunk_patch_embed_proj_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_weight: `TorchScriptTensor(f32[3072, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_bias: `TorchScriptTensor(f32[3072])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_weight: `TorchScriptTensor(f32[1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_bias: `TorchScriptTensor(f32[1024])`,\n...\n)\n## Return values\n", + "text":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___11___mlp_fc2_weight[name=p_getattr_l__self___trunk_blocks___11___mlp_fc2_weight]. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"FxOnnxInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":414 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0008", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___11___mlp_fc2_bias[name=p_getattr_l__self___trunk_blocks___11___mlp_fc2_bias]. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature FxOnnxInterpreter.run_node\n- self: \n- node: fx.Node(p_getattr_l__self___trunk_blocks___11___mlp_fc2_bias)[placeholder]:Tensor(f32[1024])\n- fx_graph_module: torch.fx.GraphModule()\n- onnxfunction_dispatcher: \n- op_level_debug: False\n- onnxscript_graph: \n- onnxscript_tracer: \n- fx_name_to_onnxscript_value: Dict[length=147](\np_trunk_pos_embed: `TorchScriptTensor(f32[1, 1024, 1024])`,\np_trunk_attn_pool_latent: `TorchScriptTensor(f32[1, 1, 1024])`,\np_trunk_patch_embed_proj_weight: `TorchScriptTensor(f32[1024, 3, 16, 16])`,\np_trunk_patch_embed_proj_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_weight: `TorchScriptTensor(f32[3072, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_bias: `TorchScriptTensor(f32[3072])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_weight: `TorchScriptTensor(f32[1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_bias: `TorchScriptTensor(f32[1024])`,\n...\n)\n## Return values\n", + "text":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___11___mlp_fc2_bias[name=p_getattr_l__self___trunk_blocks___11___mlp_fc2_bias]. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"FxOnnxInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":414 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0008", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___12___norm1_weight[name=p_getattr_l__self___trunk_blocks___12___norm1_weight]. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature FxOnnxInterpreter.run_node\n- self: \n- node: fx.Node(p_getattr_l__self___trunk_blocks___12___norm1_weight)[placeholder]:Tensor(f32[1024])\n- fx_graph_module: torch.fx.GraphModule()\n- onnxfunction_dispatcher: \n- op_level_debug: False\n- onnxscript_graph: \n- onnxscript_tracer: \n- fx_name_to_onnxscript_value: Dict[length=148](\np_trunk_pos_embed: `TorchScriptTensor(f32[1, 1024, 1024])`,\np_trunk_attn_pool_latent: `TorchScriptTensor(f32[1, 1, 1024])`,\np_trunk_patch_embed_proj_weight: `TorchScriptTensor(f32[1024, 3, 16, 16])`,\np_trunk_patch_embed_proj_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_weight: `TorchScriptTensor(f32[3072, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_bias: `TorchScriptTensor(f32[3072])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_weight: `TorchScriptTensor(f32[1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_bias: `TorchScriptTensor(f32[1024])`,\n...\n)\n## Return values\n", + "text":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___12___norm1_weight[name=p_getattr_l__self___trunk_blocks___12___norm1_weight]. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"FxOnnxInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":414 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0008", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___12___norm1_bias[name=p_getattr_l__self___trunk_blocks___12___norm1_bias]. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature FxOnnxInterpreter.run_node\n- self: \n- node: fx.Node(p_getattr_l__self___trunk_blocks___12___norm1_bias)[placeholder]:Tensor(f32[1024])\n- fx_graph_module: torch.fx.GraphModule()\n- onnxfunction_dispatcher: \n- op_level_debug: False\n- onnxscript_graph: \n- onnxscript_tracer: \n- fx_name_to_onnxscript_value: Dict[length=149](\np_trunk_pos_embed: `TorchScriptTensor(f32[1, 1024, 1024])`,\np_trunk_attn_pool_latent: `TorchScriptTensor(f32[1, 1, 1024])`,\np_trunk_patch_embed_proj_weight: `TorchScriptTensor(f32[1024, 3, 16, 16])`,\np_trunk_patch_embed_proj_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_weight: `TorchScriptTensor(f32[3072, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_bias: `TorchScriptTensor(f32[3072])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_weight: `TorchScriptTensor(f32[1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_bias: `TorchScriptTensor(f32[1024])`,\n...\n)\n## Return values\n", + "text":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___12___norm1_bias[name=p_getattr_l__self___trunk_blocks___12___norm1_bias]. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"FxOnnxInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":414 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0008", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___12___attn_qkv_weight[name=p_getattr_l__self___trunk_blocks___12___attn_qkv_weight]. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature FxOnnxInterpreter.run_node\n- self: \n- node: fx.Node(p_getattr_l__self___trunk_blocks___12___attn_qkv_weight)[placeholder]:Tensor(f32[3072, 1024])\n- fx_graph_module: torch.fx.GraphModule()\n- onnxfunction_dispatcher: \n- op_level_debug: False\n- onnxscript_graph: \n- onnxscript_tracer: \n- fx_name_to_onnxscript_value: Dict[length=150](\np_trunk_pos_embed: `TorchScriptTensor(f32[1, 1024, 1024])`,\np_trunk_attn_pool_latent: `TorchScriptTensor(f32[1, 1, 1024])`,\np_trunk_patch_embed_proj_weight: `TorchScriptTensor(f32[1024, 3, 16, 16])`,\np_trunk_patch_embed_proj_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_weight: `TorchScriptTensor(f32[3072, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_bias: `TorchScriptTensor(f32[3072])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_weight: `TorchScriptTensor(f32[1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_bias: `TorchScriptTensor(f32[1024])`,\n...\n)\n## Return values\n", + "text":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___12___attn_qkv_weight[name=p_getattr_l__self___trunk_blocks___12___attn_qkv_weight]. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"FxOnnxInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":414 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0008", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___12___attn_qkv_bias[name=p_getattr_l__self___trunk_blocks___12___attn_qkv_bias]. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature FxOnnxInterpreter.run_node\n- self: \n- node: fx.Node(p_getattr_l__self___trunk_blocks___12___attn_qkv_bias)[placeholder]:Tensor(f32[3072])\n- fx_graph_module: torch.fx.GraphModule()\n- onnxfunction_dispatcher: \n- op_level_debug: False\n- onnxscript_graph: \n- onnxscript_tracer: \n- fx_name_to_onnxscript_value: Dict[length=151](\np_trunk_pos_embed: `TorchScriptTensor(f32[1, 1024, 1024])`,\np_trunk_attn_pool_latent: `TorchScriptTensor(f32[1, 1, 1024])`,\np_trunk_patch_embed_proj_weight: `TorchScriptTensor(f32[1024, 3, 16, 16])`,\np_trunk_patch_embed_proj_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_weight: `TorchScriptTensor(f32[3072, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_bias: `TorchScriptTensor(f32[3072])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_weight: `TorchScriptTensor(f32[1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_bias: `TorchScriptTensor(f32[1024])`,\n...\n)\n## Return values\n", + "text":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___12___attn_qkv_bias[name=p_getattr_l__self___trunk_blocks___12___attn_qkv_bias]. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"FxOnnxInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":414 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0008", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___12___attn_proj_weight[name=p_getattr_l__self___trunk_blocks___12___attn_proj_weight]. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature FxOnnxInterpreter.run_node\n- self: \n- node: fx.Node(p_getattr_l__self___trunk_blocks___12___attn_proj_weight)[placeholder]:Tensor(f32[1024, 1024])\n- fx_graph_module: torch.fx.GraphModule()\n- onnxfunction_dispatcher: \n- op_level_debug: False\n- onnxscript_graph: \n- onnxscript_tracer: \n- fx_name_to_onnxscript_value: Dict[length=152](\np_trunk_pos_embed: `TorchScriptTensor(f32[1, 1024, 1024])`,\np_trunk_attn_pool_latent: `TorchScriptTensor(f32[1, 1, 1024])`,\np_trunk_patch_embed_proj_weight: `TorchScriptTensor(f32[1024, 3, 16, 16])`,\np_trunk_patch_embed_proj_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_weight: `TorchScriptTensor(f32[3072, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_bias: `TorchScriptTensor(f32[3072])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_weight: `TorchScriptTensor(f32[1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_bias: `TorchScriptTensor(f32[1024])`,\n...\n)\n## Return values\n", + "text":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___12___attn_proj_weight[name=p_getattr_l__self___trunk_blocks___12___attn_proj_weight]. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"FxOnnxInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":414 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0008", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___12___attn_proj_bias[name=p_getattr_l__self___trunk_blocks___12___attn_proj_bias]. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature FxOnnxInterpreter.run_node\n- self: \n- node: fx.Node(p_getattr_l__self___trunk_blocks___12___attn_proj_bias)[placeholder]:Tensor(f32[1024])\n- fx_graph_module: torch.fx.GraphModule()\n- onnxfunction_dispatcher: \n- op_level_debug: False\n- onnxscript_graph: \n- onnxscript_tracer: \n- fx_name_to_onnxscript_value: Dict[length=153](\np_trunk_pos_embed: `TorchScriptTensor(f32[1, 1024, 1024])`,\np_trunk_attn_pool_latent: `TorchScriptTensor(f32[1, 1, 1024])`,\np_trunk_patch_embed_proj_weight: `TorchScriptTensor(f32[1024, 3, 16, 16])`,\np_trunk_patch_embed_proj_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_weight: `TorchScriptTensor(f32[3072, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_bias: `TorchScriptTensor(f32[3072])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_weight: `TorchScriptTensor(f32[1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_bias: `TorchScriptTensor(f32[1024])`,\n...\n)\n## Return values\n", + "text":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___12___attn_proj_bias[name=p_getattr_l__self___trunk_blocks___12___attn_proj_bias]. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"FxOnnxInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":414 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0008", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___12___norm2_weight[name=p_getattr_l__self___trunk_blocks___12___norm2_weight]. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature FxOnnxInterpreter.run_node\n- self: \n- node: fx.Node(p_getattr_l__self___trunk_blocks___12___norm2_weight)[placeholder]:Tensor(f32[1024])\n- fx_graph_module: torch.fx.GraphModule()\n- onnxfunction_dispatcher: \n- op_level_debug: False\n- onnxscript_graph: \n- onnxscript_tracer: \n- fx_name_to_onnxscript_value: Dict[length=154](\np_trunk_pos_embed: `TorchScriptTensor(f32[1, 1024, 1024])`,\np_trunk_attn_pool_latent: `TorchScriptTensor(f32[1, 1, 1024])`,\np_trunk_patch_embed_proj_weight: `TorchScriptTensor(f32[1024, 3, 16, 16])`,\np_trunk_patch_embed_proj_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_weight: `TorchScriptTensor(f32[3072, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_bias: `TorchScriptTensor(f32[3072])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_weight: `TorchScriptTensor(f32[1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_bias: `TorchScriptTensor(f32[1024])`,\n...\n)\n## Return values\n", + "text":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___12___norm2_weight[name=p_getattr_l__self___trunk_blocks___12___norm2_weight]. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"FxOnnxInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":414 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0008", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___12___norm2_bias[name=p_getattr_l__self___trunk_blocks___12___norm2_bias]. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature FxOnnxInterpreter.run_node\n- self: \n- node: fx.Node(p_getattr_l__self___trunk_blocks___12___norm2_bias)[placeholder]:Tensor(f32[1024])\n- fx_graph_module: torch.fx.GraphModule()\n- onnxfunction_dispatcher: \n- op_level_debug: False\n- onnxscript_graph: \n- onnxscript_tracer: \n- fx_name_to_onnxscript_value: Dict[length=155](\np_trunk_pos_embed: `TorchScriptTensor(f32[1, 1024, 1024])`,\np_trunk_attn_pool_latent: `TorchScriptTensor(f32[1, 1, 1024])`,\np_trunk_patch_embed_proj_weight: `TorchScriptTensor(f32[1024, 3, 16, 16])`,\np_trunk_patch_embed_proj_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_weight: `TorchScriptTensor(f32[3072, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_bias: `TorchScriptTensor(f32[3072])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_weight: `TorchScriptTensor(f32[1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_bias: `TorchScriptTensor(f32[1024])`,\n...\n)\n## Return values\n", + "text":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___12___norm2_bias[name=p_getattr_l__self___trunk_blocks___12___norm2_bias]. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"FxOnnxInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":414 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0008", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___12___mlp_fc1_weight[name=p_getattr_l__self___trunk_blocks___12___mlp_fc1_weight]. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature FxOnnxInterpreter.run_node\n- self: \n- node: fx.Node(p_getattr_l__self___trunk_blocks___12___mlp_fc1_weight)[placeholder]:Tensor(f32[4096, 1024])\n- fx_graph_module: torch.fx.GraphModule()\n- onnxfunction_dispatcher: \n- op_level_debug: False\n- onnxscript_graph: \n- onnxscript_tracer: \n- fx_name_to_onnxscript_value: Dict[length=156](\np_trunk_pos_embed: `TorchScriptTensor(f32[1, 1024, 1024])`,\np_trunk_attn_pool_latent: `TorchScriptTensor(f32[1, 1, 1024])`,\np_trunk_patch_embed_proj_weight: `TorchScriptTensor(f32[1024, 3, 16, 16])`,\np_trunk_patch_embed_proj_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_weight: `TorchScriptTensor(f32[3072, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_bias: `TorchScriptTensor(f32[3072])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_weight: `TorchScriptTensor(f32[1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_bias: `TorchScriptTensor(f32[1024])`,\n...\n)\n## Return values\n", + "text":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___12___mlp_fc1_weight[name=p_getattr_l__self___trunk_blocks___12___mlp_fc1_weight]. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"FxOnnxInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":414 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0008", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___12___mlp_fc1_bias[name=p_getattr_l__self___trunk_blocks___12___mlp_fc1_bias]. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature FxOnnxInterpreter.run_node\n- self: \n- node: fx.Node(p_getattr_l__self___trunk_blocks___12___mlp_fc1_bias)[placeholder]:Tensor(f32[4096])\n- fx_graph_module: torch.fx.GraphModule()\n- onnxfunction_dispatcher: \n- op_level_debug: False\n- onnxscript_graph: \n- onnxscript_tracer: \n- fx_name_to_onnxscript_value: Dict[length=157](\np_trunk_pos_embed: `TorchScriptTensor(f32[1, 1024, 1024])`,\np_trunk_attn_pool_latent: `TorchScriptTensor(f32[1, 1, 1024])`,\np_trunk_patch_embed_proj_weight: `TorchScriptTensor(f32[1024, 3, 16, 16])`,\np_trunk_patch_embed_proj_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_weight: `TorchScriptTensor(f32[3072, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_bias: `TorchScriptTensor(f32[3072])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_weight: `TorchScriptTensor(f32[1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_bias: `TorchScriptTensor(f32[1024])`,\n...\n)\n## Return values\n", + "text":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___12___mlp_fc1_bias[name=p_getattr_l__self___trunk_blocks___12___mlp_fc1_bias]. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"FxOnnxInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":414 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0008", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___12___mlp_fc2_weight[name=p_getattr_l__self___trunk_blocks___12___mlp_fc2_weight]. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature FxOnnxInterpreter.run_node\n- self: \n- node: fx.Node(p_getattr_l__self___trunk_blocks___12___mlp_fc2_weight)[placeholder]:Tensor(f32[1024, 4096])\n- fx_graph_module: torch.fx.GraphModule()\n- onnxfunction_dispatcher: \n- op_level_debug: False\n- onnxscript_graph: \n- onnxscript_tracer: \n- fx_name_to_onnxscript_value: Dict[length=158](\np_trunk_pos_embed: `TorchScriptTensor(f32[1, 1024, 1024])`,\np_trunk_attn_pool_latent: `TorchScriptTensor(f32[1, 1, 1024])`,\np_trunk_patch_embed_proj_weight: `TorchScriptTensor(f32[1024, 3, 16, 16])`,\np_trunk_patch_embed_proj_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_weight: `TorchScriptTensor(f32[3072, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_bias: `TorchScriptTensor(f32[3072])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_weight: `TorchScriptTensor(f32[1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_bias: `TorchScriptTensor(f32[1024])`,\n...\n)\n## Return values\n", + "text":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___12___mlp_fc2_weight[name=p_getattr_l__self___trunk_blocks___12___mlp_fc2_weight]. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"FxOnnxInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":414 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0008", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___12___mlp_fc2_bias[name=p_getattr_l__self___trunk_blocks___12___mlp_fc2_bias]. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature FxOnnxInterpreter.run_node\n- self: \n- node: fx.Node(p_getattr_l__self___trunk_blocks___12___mlp_fc2_bias)[placeholder]:Tensor(f32[1024])\n- fx_graph_module: torch.fx.GraphModule()\n- onnxfunction_dispatcher: \n- op_level_debug: False\n- onnxscript_graph: \n- onnxscript_tracer: \n- fx_name_to_onnxscript_value: Dict[length=159](\np_trunk_pos_embed: `TorchScriptTensor(f32[1, 1024, 1024])`,\np_trunk_attn_pool_latent: `TorchScriptTensor(f32[1, 1, 1024])`,\np_trunk_patch_embed_proj_weight: `TorchScriptTensor(f32[1024, 3, 16, 16])`,\np_trunk_patch_embed_proj_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_weight: `TorchScriptTensor(f32[3072, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_bias: `TorchScriptTensor(f32[3072])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_weight: `TorchScriptTensor(f32[1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_bias: `TorchScriptTensor(f32[1024])`,\n...\n)\n## Return values\n", + "text":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___12___mlp_fc2_bias[name=p_getattr_l__self___trunk_blocks___12___mlp_fc2_bias]. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"FxOnnxInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":414 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0008", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___13___norm1_weight[name=p_getattr_l__self___trunk_blocks___13___norm1_weight]. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature FxOnnxInterpreter.run_node\n- self: \n- node: fx.Node(p_getattr_l__self___trunk_blocks___13___norm1_weight)[placeholder]:Tensor(f32[1024])\n- fx_graph_module: torch.fx.GraphModule()\n- onnxfunction_dispatcher: \n- op_level_debug: False\n- onnxscript_graph: \n- onnxscript_tracer: \n- fx_name_to_onnxscript_value: Dict[length=160](\np_trunk_pos_embed: `TorchScriptTensor(f32[1, 1024, 1024])`,\np_trunk_attn_pool_latent: `TorchScriptTensor(f32[1, 1, 1024])`,\np_trunk_patch_embed_proj_weight: `TorchScriptTensor(f32[1024, 3, 16, 16])`,\np_trunk_patch_embed_proj_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_weight: `TorchScriptTensor(f32[3072, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_bias: `TorchScriptTensor(f32[3072])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_weight: `TorchScriptTensor(f32[1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_bias: `TorchScriptTensor(f32[1024])`,\n...\n)\n## Return values\n", + "text":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___13___norm1_weight[name=p_getattr_l__self___trunk_blocks___13___norm1_weight]. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"FxOnnxInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":414 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0008", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___13___norm1_bias[name=p_getattr_l__self___trunk_blocks___13___norm1_bias]. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature FxOnnxInterpreter.run_node\n- self: \n- node: fx.Node(p_getattr_l__self___trunk_blocks___13___norm1_bias)[placeholder]:Tensor(f32[1024])\n- fx_graph_module: torch.fx.GraphModule()\n- onnxfunction_dispatcher: \n- op_level_debug: False\n- onnxscript_graph: \n- onnxscript_tracer: \n- fx_name_to_onnxscript_value: Dict[length=161](\np_trunk_pos_embed: `TorchScriptTensor(f32[1, 1024, 1024])`,\np_trunk_attn_pool_latent: `TorchScriptTensor(f32[1, 1, 1024])`,\np_trunk_patch_embed_proj_weight: `TorchScriptTensor(f32[1024, 3, 16, 16])`,\np_trunk_patch_embed_proj_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_weight: `TorchScriptTensor(f32[3072, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_bias: `TorchScriptTensor(f32[3072])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_weight: `TorchScriptTensor(f32[1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_bias: `TorchScriptTensor(f32[1024])`,\n...\n)\n## Return values\n", + "text":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___13___norm1_bias[name=p_getattr_l__self___trunk_blocks___13___norm1_bias]. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"FxOnnxInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":414 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0008", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___13___attn_qkv_weight[name=p_getattr_l__self___trunk_blocks___13___attn_qkv_weight]. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature FxOnnxInterpreter.run_node\n- self: \n- node: fx.Node(p_getattr_l__self___trunk_blocks___13___attn_qkv_weight)[placeholder]:Tensor(f32[3072, 1024])\n- fx_graph_module: torch.fx.GraphModule()\n- onnxfunction_dispatcher: \n- op_level_debug: False\n- onnxscript_graph: \n- onnxscript_tracer: \n- fx_name_to_onnxscript_value: Dict[length=162](\np_trunk_pos_embed: `TorchScriptTensor(f32[1, 1024, 1024])`,\np_trunk_attn_pool_latent: `TorchScriptTensor(f32[1, 1, 1024])`,\np_trunk_patch_embed_proj_weight: `TorchScriptTensor(f32[1024, 3, 16, 16])`,\np_trunk_patch_embed_proj_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_weight: `TorchScriptTensor(f32[3072, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_bias: `TorchScriptTensor(f32[3072])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_weight: `TorchScriptTensor(f32[1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_bias: `TorchScriptTensor(f32[1024])`,\n...\n)\n## Return values\n", + "text":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___13___attn_qkv_weight[name=p_getattr_l__self___trunk_blocks___13___attn_qkv_weight]. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"FxOnnxInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":414 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0008", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___13___attn_qkv_bias[name=p_getattr_l__self___trunk_blocks___13___attn_qkv_bias]. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature FxOnnxInterpreter.run_node\n- self: \n- node: fx.Node(p_getattr_l__self___trunk_blocks___13___attn_qkv_bias)[placeholder]:Tensor(f32[3072])\n- fx_graph_module: torch.fx.GraphModule()\n- onnxfunction_dispatcher: \n- op_level_debug: False\n- onnxscript_graph: \n- onnxscript_tracer: \n- fx_name_to_onnxscript_value: Dict[length=163](\np_trunk_pos_embed: `TorchScriptTensor(f32[1, 1024, 1024])`,\np_trunk_attn_pool_latent: `TorchScriptTensor(f32[1, 1, 1024])`,\np_trunk_patch_embed_proj_weight: `TorchScriptTensor(f32[1024, 3, 16, 16])`,\np_trunk_patch_embed_proj_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_weight: `TorchScriptTensor(f32[3072, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_bias: `TorchScriptTensor(f32[3072])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_weight: `TorchScriptTensor(f32[1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_bias: `TorchScriptTensor(f32[1024])`,\n...\n)\n## Return values\n", + "text":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___13___attn_qkv_bias[name=p_getattr_l__self___trunk_blocks___13___attn_qkv_bias]. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"FxOnnxInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":414 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0008", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___13___attn_proj_weight[name=p_getattr_l__self___trunk_blocks___13___attn_proj_weight]. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature FxOnnxInterpreter.run_node\n- self: \n- node: fx.Node(p_getattr_l__self___trunk_blocks___13___attn_proj_weight)[placeholder]:Tensor(f32[1024, 1024])\n- fx_graph_module: torch.fx.GraphModule()\n- onnxfunction_dispatcher: \n- op_level_debug: False\n- onnxscript_graph: \n- onnxscript_tracer: \n- fx_name_to_onnxscript_value: Dict[length=164](\np_trunk_pos_embed: `TorchScriptTensor(f32[1, 1024, 1024])`,\np_trunk_attn_pool_latent: `TorchScriptTensor(f32[1, 1, 1024])`,\np_trunk_patch_embed_proj_weight: `TorchScriptTensor(f32[1024, 3, 16, 16])`,\np_trunk_patch_embed_proj_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_weight: `TorchScriptTensor(f32[3072, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_bias: `TorchScriptTensor(f32[3072])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_weight: `TorchScriptTensor(f32[1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_bias: `TorchScriptTensor(f32[1024])`,\n...\n)\n## Return values\n", + "text":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___13___attn_proj_weight[name=p_getattr_l__self___trunk_blocks___13___attn_proj_weight]. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"FxOnnxInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":414 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0008", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___13___attn_proj_bias[name=p_getattr_l__self___trunk_blocks___13___attn_proj_bias]. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature FxOnnxInterpreter.run_node\n- self: \n- node: fx.Node(p_getattr_l__self___trunk_blocks___13___attn_proj_bias)[placeholder]:Tensor(f32[1024])\n- fx_graph_module: torch.fx.GraphModule()\n- onnxfunction_dispatcher: \n- op_level_debug: False\n- onnxscript_graph: \n- onnxscript_tracer: \n- fx_name_to_onnxscript_value: Dict[length=165](\np_trunk_pos_embed: `TorchScriptTensor(f32[1, 1024, 1024])`,\np_trunk_attn_pool_latent: `TorchScriptTensor(f32[1, 1, 1024])`,\np_trunk_patch_embed_proj_weight: `TorchScriptTensor(f32[1024, 3, 16, 16])`,\np_trunk_patch_embed_proj_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_weight: `TorchScriptTensor(f32[3072, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_bias: `TorchScriptTensor(f32[3072])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_weight: `TorchScriptTensor(f32[1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_bias: `TorchScriptTensor(f32[1024])`,\n...\n)\n## Return values\n", + "text":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___13___attn_proj_bias[name=p_getattr_l__self___trunk_blocks___13___attn_proj_bias]. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"FxOnnxInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":414 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0008", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___13___norm2_weight[name=p_getattr_l__self___trunk_blocks___13___norm2_weight]. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature FxOnnxInterpreter.run_node\n- self: \n- node: fx.Node(p_getattr_l__self___trunk_blocks___13___norm2_weight)[placeholder]:Tensor(f32[1024])\n- fx_graph_module: torch.fx.GraphModule()\n- onnxfunction_dispatcher: \n- op_level_debug: False\n- onnxscript_graph: \n- onnxscript_tracer: \n- fx_name_to_onnxscript_value: Dict[length=166](\np_trunk_pos_embed: `TorchScriptTensor(f32[1, 1024, 1024])`,\np_trunk_attn_pool_latent: `TorchScriptTensor(f32[1, 1, 1024])`,\np_trunk_patch_embed_proj_weight: `TorchScriptTensor(f32[1024, 3, 16, 16])`,\np_trunk_patch_embed_proj_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_weight: `TorchScriptTensor(f32[3072, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_bias: `TorchScriptTensor(f32[3072])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_weight: `TorchScriptTensor(f32[1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_bias: `TorchScriptTensor(f32[1024])`,\n...\n)\n## Return values\n", + "text":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___13___norm2_weight[name=p_getattr_l__self___trunk_blocks___13___norm2_weight]. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"FxOnnxInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":414 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0008", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___13___norm2_bias[name=p_getattr_l__self___trunk_blocks___13___norm2_bias]. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature FxOnnxInterpreter.run_node\n- self: \n- node: fx.Node(p_getattr_l__self___trunk_blocks___13___norm2_bias)[placeholder]:Tensor(f32[1024])\n- fx_graph_module: torch.fx.GraphModule()\n- onnxfunction_dispatcher: \n- op_level_debug: False\n- onnxscript_graph: \n- onnxscript_tracer: \n- fx_name_to_onnxscript_value: Dict[length=167](\np_trunk_pos_embed: `TorchScriptTensor(f32[1, 1024, 1024])`,\np_trunk_attn_pool_latent: `TorchScriptTensor(f32[1, 1, 1024])`,\np_trunk_patch_embed_proj_weight: `TorchScriptTensor(f32[1024, 3, 16, 16])`,\np_trunk_patch_embed_proj_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_weight: `TorchScriptTensor(f32[3072, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_bias: `TorchScriptTensor(f32[3072])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_weight: `TorchScriptTensor(f32[1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_bias: `TorchScriptTensor(f32[1024])`,\n...\n)\n## Return values\n", + "text":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___13___norm2_bias[name=p_getattr_l__self___trunk_blocks___13___norm2_bias]. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"FxOnnxInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":414 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0008", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___13___mlp_fc1_weight[name=p_getattr_l__self___trunk_blocks___13___mlp_fc1_weight]. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature FxOnnxInterpreter.run_node\n- self: \n- node: fx.Node(p_getattr_l__self___trunk_blocks___13___mlp_fc1_weight)[placeholder]:Tensor(f32[4096, 1024])\n- fx_graph_module: torch.fx.GraphModule()\n- onnxfunction_dispatcher: \n- op_level_debug: False\n- onnxscript_graph: \n- onnxscript_tracer: \n- fx_name_to_onnxscript_value: Dict[length=168](\np_trunk_pos_embed: `TorchScriptTensor(f32[1, 1024, 1024])`,\np_trunk_attn_pool_latent: `TorchScriptTensor(f32[1, 1, 1024])`,\np_trunk_patch_embed_proj_weight: `TorchScriptTensor(f32[1024, 3, 16, 16])`,\np_trunk_patch_embed_proj_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_weight: `TorchScriptTensor(f32[3072, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_bias: `TorchScriptTensor(f32[3072])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_weight: `TorchScriptTensor(f32[1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_bias: `TorchScriptTensor(f32[1024])`,\n...\n)\n## Return values\n", + "text":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___13___mlp_fc1_weight[name=p_getattr_l__self___trunk_blocks___13___mlp_fc1_weight]. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"FxOnnxInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":414 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0008", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___13___mlp_fc1_bias[name=p_getattr_l__self___trunk_blocks___13___mlp_fc1_bias]. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature FxOnnxInterpreter.run_node\n- self: \n- node: fx.Node(p_getattr_l__self___trunk_blocks___13___mlp_fc1_bias)[placeholder]:Tensor(f32[4096])\n- fx_graph_module: torch.fx.GraphModule()\n- onnxfunction_dispatcher: \n- op_level_debug: False\n- onnxscript_graph: \n- onnxscript_tracer: \n- fx_name_to_onnxscript_value: Dict[length=169](\np_trunk_pos_embed: `TorchScriptTensor(f32[1, 1024, 1024])`,\np_trunk_attn_pool_latent: `TorchScriptTensor(f32[1, 1, 1024])`,\np_trunk_patch_embed_proj_weight: `TorchScriptTensor(f32[1024, 3, 16, 16])`,\np_trunk_patch_embed_proj_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_weight: `TorchScriptTensor(f32[3072, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_bias: `TorchScriptTensor(f32[3072])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_weight: `TorchScriptTensor(f32[1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_bias: `TorchScriptTensor(f32[1024])`,\n...\n)\n## Return values\n", + "text":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___13___mlp_fc1_bias[name=p_getattr_l__self___trunk_blocks___13___mlp_fc1_bias]. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"FxOnnxInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":414 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0008", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___13___mlp_fc2_weight[name=p_getattr_l__self___trunk_blocks___13___mlp_fc2_weight]. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature FxOnnxInterpreter.run_node\n- self: \n- node: fx.Node(p_getattr_l__self___trunk_blocks___13___mlp_fc2_weight)[placeholder]:Tensor(f32[1024, 4096])\n- fx_graph_module: torch.fx.GraphModule()\n- onnxfunction_dispatcher: \n- op_level_debug: False\n- onnxscript_graph: \n- onnxscript_tracer: \n- fx_name_to_onnxscript_value: Dict[length=170](\np_trunk_pos_embed: `TorchScriptTensor(f32[1, 1024, 1024])`,\np_trunk_attn_pool_latent: `TorchScriptTensor(f32[1, 1, 1024])`,\np_trunk_patch_embed_proj_weight: `TorchScriptTensor(f32[1024, 3, 16, 16])`,\np_trunk_patch_embed_proj_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_weight: `TorchScriptTensor(f32[3072, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_bias: `TorchScriptTensor(f32[3072])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_weight: `TorchScriptTensor(f32[1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_bias: `TorchScriptTensor(f32[1024])`,\n...\n)\n## Return values\n", + "text":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___13___mlp_fc2_weight[name=p_getattr_l__self___trunk_blocks___13___mlp_fc2_weight]. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"FxOnnxInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":414 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0008", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___13___mlp_fc2_bias[name=p_getattr_l__self___trunk_blocks___13___mlp_fc2_bias]. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature FxOnnxInterpreter.run_node\n- self: \n- node: fx.Node(p_getattr_l__self___trunk_blocks___13___mlp_fc2_bias)[placeholder]:Tensor(f32[1024])\n- fx_graph_module: torch.fx.GraphModule()\n- onnxfunction_dispatcher: \n- op_level_debug: False\n- onnxscript_graph: \n- onnxscript_tracer: \n- fx_name_to_onnxscript_value: Dict[length=171](\np_trunk_pos_embed: `TorchScriptTensor(f32[1, 1024, 1024])`,\np_trunk_attn_pool_latent: `TorchScriptTensor(f32[1, 1, 1024])`,\np_trunk_patch_embed_proj_weight: `TorchScriptTensor(f32[1024, 3, 16, 16])`,\np_trunk_patch_embed_proj_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_weight: `TorchScriptTensor(f32[3072, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_bias: `TorchScriptTensor(f32[3072])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_weight: `TorchScriptTensor(f32[1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_bias: `TorchScriptTensor(f32[1024])`,\n...\n)\n## Return values\n", + "text":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___13___mlp_fc2_bias[name=p_getattr_l__self___trunk_blocks___13___mlp_fc2_bias]. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"FxOnnxInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":414 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0008", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___14___norm1_weight[name=p_getattr_l__self___trunk_blocks___14___norm1_weight]. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature FxOnnxInterpreter.run_node\n- self: \n- node: fx.Node(p_getattr_l__self___trunk_blocks___14___norm1_weight)[placeholder]:Tensor(f32[1024])\n- fx_graph_module: torch.fx.GraphModule()\n- onnxfunction_dispatcher: \n- op_level_debug: False\n- onnxscript_graph: \n- onnxscript_tracer: \n- fx_name_to_onnxscript_value: Dict[length=172](\np_trunk_pos_embed: `TorchScriptTensor(f32[1, 1024, 1024])`,\np_trunk_attn_pool_latent: `TorchScriptTensor(f32[1, 1, 1024])`,\np_trunk_patch_embed_proj_weight: `TorchScriptTensor(f32[1024, 3, 16, 16])`,\np_trunk_patch_embed_proj_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_weight: `TorchScriptTensor(f32[3072, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_bias: `TorchScriptTensor(f32[3072])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_weight: `TorchScriptTensor(f32[1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_bias: `TorchScriptTensor(f32[1024])`,\n...\n)\n## Return values\n", + "text":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___14___norm1_weight[name=p_getattr_l__self___trunk_blocks___14___norm1_weight]. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"FxOnnxInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":414 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0008", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___14___norm1_bias[name=p_getattr_l__self___trunk_blocks___14___norm1_bias]. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature FxOnnxInterpreter.run_node\n- self: \n- node: fx.Node(p_getattr_l__self___trunk_blocks___14___norm1_bias)[placeholder]:Tensor(f32[1024])\n- fx_graph_module: torch.fx.GraphModule()\n- onnxfunction_dispatcher: \n- op_level_debug: False\n- onnxscript_graph: \n- onnxscript_tracer: \n- fx_name_to_onnxscript_value: Dict[length=173](\np_trunk_pos_embed: `TorchScriptTensor(f32[1, 1024, 1024])`,\np_trunk_attn_pool_latent: `TorchScriptTensor(f32[1, 1, 1024])`,\np_trunk_patch_embed_proj_weight: `TorchScriptTensor(f32[1024, 3, 16, 16])`,\np_trunk_patch_embed_proj_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_weight: `TorchScriptTensor(f32[3072, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_bias: `TorchScriptTensor(f32[3072])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_weight: `TorchScriptTensor(f32[1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_bias: `TorchScriptTensor(f32[1024])`,\n...\n)\n## Return values\n", + "text":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___14___norm1_bias[name=p_getattr_l__self___trunk_blocks___14___norm1_bias]. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"FxOnnxInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":414 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0008", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___14___attn_qkv_weight[name=p_getattr_l__self___trunk_blocks___14___attn_qkv_weight]. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature FxOnnxInterpreter.run_node\n- self: \n- node: fx.Node(p_getattr_l__self___trunk_blocks___14___attn_qkv_weight)[placeholder]:Tensor(f32[3072, 1024])\n- fx_graph_module: torch.fx.GraphModule()\n- onnxfunction_dispatcher: \n- op_level_debug: False\n- onnxscript_graph: \n- onnxscript_tracer: \n- fx_name_to_onnxscript_value: Dict[length=174](\np_trunk_pos_embed: `TorchScriptTensor(f32[1, 1024, 1024])`,\np_trunk_attn_pool_latent: `TorchScriptTensor(f32[1, 1, 1024])`,\np_trunk_patch_embed_proj_weight: `TorchScriptTensor(f32[1024, 3, 16, 16])`,\np_trunk_patch_embed_proj_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_weight: `TorchScriptTensor(f32[3072, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_bias: `TorchScriptTensor(f32[3072])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_weight: `TorchScriptTensor(f32[1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_bias: `TorchScriptTensor(f32[1024])`,\n...\n)\n## Return values\n", + "text":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___14___attn_qkv_weight[name=p_getattr_l__self___trunk_blocks___14___attn_qkv_weight]. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"FxOnnxInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":414 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0008", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___14___attn_qkv_bias[name=p_getattr_l__self___trunk_blocks___14___attn_qkv_bias]. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature FxOnnxInterpreter.run_node\n- self: \n- node: fx.Node(p_getattr_l__self___trunk_blocks___14___attn_qkv_bias)[placeholder]:Tensor(f32[3072])\n- fx_graph_module: torch.fx.GraphModule()\n- onnxfunction_dispatcher: \n- op_level_debug: False\n- onnxscript_graph: \n- onnxscript_tracer: \n- fx_name_to_onnxscript_value: Dict[length=175](\np_trunk_pos_embed: `TorchScriptTensor(f32[1, 1024, 1024])`,\np_trunk_attn_pool_latent: `TorchScriptTensor(f32[1, 1, 1024])`,\np_trunk_patch_embed_proj_weight: `TorchScriptTensor(f32[1024, 3, 16, 16])`,\np_trunk_patch_embed_proj_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_weight: `TorchScriptTensor(f32[3072, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_bias: `TorchScriptTensor(f32[3072])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_weight: `TorchScriptTensor(f32[1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_bias: `TorchScriptTensor(f32[1024])`,\n...\n)\n## Return values\n", + "text":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___14___attn_qkv_bias[name=p_getattr_l__self___trunk_blocks___14___attn_qkv_bias]. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"FxOnnxInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":414 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0008", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___14___attn_proj_weight[name=p_getattr_l__self___trunk_blocks___14___attn_proj_weight]. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature FxOnnxInterpreter.run_node\n- self: \n- node: fx.Node(p_getattr_l__self___trunk_blocks___14___attn_proj_weight)[placeholder]:Tensor(f32[1024, 1024])\n- fx_graph_module: torch.fx.GraphModule()\n- onnxfunction_dispatcher: \n- op_level_debug: False\n- onnxscript_graph: \n- onnxscript_tracer: \n- fx_name_to_onnxscript_value: Dict[length=176](\np_trunk_pos_embed: `TorchScriptTensor(f32[1, 1024, 1024])`,\np_trunk_attn_pool_latent: `TorchScriptTensor(f32[1, 1, 1024])`,\np_trunk_patch_embed_proj_weight: `TorchScriptTensor(f32[1024, 3, 16, 16])`,\np_trunk_patch_embed_proj_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_weight: `TorchScriptTensor(f32[3072, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_bias: `TorchScriptTensor(f32[3072])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_weight: `TorchScriptTensor(f32[1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_bias: `TorchScriptTensor(f32[1024])`,\n...\n)\n## Return values\n", + "text":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___14___attn_proj_weight[name=p_getattr_l__self___trunk_blocks___14___attn_proj_weight]. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"FxOnnxInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":414 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0008", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___14___attn_proj_bias[name=p_getattr_l__self___trunk_blocks___14___attn_proj_bias]. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature FxOnnxInterpreter.run_node\n- self: \n- node: fx.Node(p_getattr_l__self___trunk_blocks___14___attn_proj_bias)[placeholder]:Tensor(f32[1024])\n- fx_graph_module: torch.fx.GraphModule()\n- onnxfunction_dispatcher: \n- op_level_debug: False\n- onnxscript_graph: \n- onnxscript_tracer: \n- fx_name_to_onnxscript_value: Dict[length=177](\np_trunk_pos_embed: `TorchScriptTensor(f32[1, 1024, 1024])`,\np_trunk_attn_pool_latent: `TorchScriptTensor(f32[1, 1, 1024])`,\np_trunk_patch_embed_proj_weight: `TorchScriptTensor(f32[1024, 3, 16, 16])`,\np_trunk_patch_embed_proj_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_weight: `TorchScriptTensor(f32[3072, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_bias: `TorchScriptTensor(f32[3072])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_weight: `TorchScriptTensor(f32[1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_bias: `TorchScriptTensor(f32[1024])`,\n...\n)\n## Return values\n", + "text":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___14___attn_proj_bias[name=p_getattr_l__self___trunk_blocks___14___attn_proj_bias]. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"FxOnnxInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":414 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0008", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___14___norm2_weight[name=p_getattr_l__self___trunk_blocks___14___norm2_weight]. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature FxOnnxInterpreter.run_node\n- self: \n- node: fx.Node(p_getattr_l__self___trunk_blocks___14___norm2_weight)[placeholder]:Tensor(f32[1024])\n- fx_graph_module: torch.fx.GraphModule()\n- onnxfunction_dispatcher: \n- op_level_debug: False\n- onnxscript_graph: \n- onnxscript_tracer: \n- fx_name_to_onnxscript_value: Dict[length=178](\np_trunk_pos_embed: `TorchScriptTensor(f32[1, 1024, 1024])`,\np_trunk_attn_pool_latent: `TorchScriptTensor(f32[1, 1, 1024])`,\np_trunk_patch_embed_proj_weight: `TorchScriptTensor(f32[1024, 3, 16, 16])`,\np_trunk_patch_embed_proj_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_weight: `TorchScriptTensor(f32[3072, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_bias: `TorchScriptTensor(f32[3072])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_weight: `TorchScriptTensor(f32[1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_bias: `TorchScriptTensor(f32[1024])`,\n...\n)\n## Return values\n", + "text":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___14___norm2_weight[name=p_getattr_l__self___trunk_blocks___14___norm2_weight]. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"FxOnnxInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":414 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0008", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___14___norm2_bias[name=p_getattr_l__self___trunk_blocks___14___norm2_bias]. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature FxOnnxInterpreter.run_node\n- self: \n- node: fx.Node(p_getattr_l__self___trunk_blocks___14___norm2_bias)[placeholder]:Tensor(f32[1024])\n- fx_graph_module: torch.fx.GraphModule()\n- onnxfunction_dispatcher: \n- op_level_debug: False\n- onnxscript_graph: \n- onnxscript_tracer: \n- fx_name_to_onnxscript_value: Dict[length=179](\np_trunk_pos_embed: `TorchScriptTensor(f32[1, 1024, 1024])`,\np_trunk_attn_pool_latent: `TorchScriptTensor(f32[1, 1, 1024])`,\np_trunk_patch_embed_proj_weight: `TorchScriptTensor(f32[1024, 3, 16, 16])`,\np_trunk_patch_embed_proj_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_weight: `TorchScriptTensor(f32[3072, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_bias: `TorchScriptTensor(f32[3072])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_weight: `TorchScriptTensor(f32[1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_bias: `TorchScriptTensor(f32[1024])`,\n...\n)\n## Return values\n", + "text":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___14___norm2_bias[name=p_getattr_l__self___trunk_blocks___14___norm2_bias]. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"FxOnnxInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":414 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0008", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___14___mlp_fc1_weight[name=p_getattr_l__self___trunk_blocks___14___mlp_fc1_weight]. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature FxOnnxInterpreter.run_node\n- self: \n- node: fx.Node(p_getattr_l__self___trunk_blocks___14___mlp_fc1_weight)[placeholder]:Tensor(f32[4096, 1024])\n- fx_graph_module: torch.fx.GraphModule()\n- onnxfunction_dispatcher: \n- op_level_debug: False\n- onnxscript_graph: \n- onnxscript_tracer: \n- fx_name_to_onnxscript_value: Dict[length=180](\np_trunk_pos_embed: `TorchScriptTensor(f32[1, 1024, 1024])`,\np_trunk_attn_pool_latent: `TorchScriptTensor(f32[1, 1, 1024])`,\np_trunk_patch_embed_proj_weight: `TorchScriptTensor(f32[1024, 3, 16, 16])`,\np_trunk_patch_embed_proj_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_weight: `TorchScriptTensor(f32[3072, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_bias: `TorchScriptTensor(f32[3072])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_weight: `TorchScriptTensor(f32[1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_bias: `TorchScriptTensor(f32[1024])`,\n...\n)\n## Return values\n", + "text":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___14___mlp_fc1_weight[name=p_getattr_l__self___trunk_blocks___14___mlp_fc1_weight]. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"FxOnnxInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":414 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0008", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___14___mlp_fc1_bias[name=p_getattr_l__self___trunk_blocks___14___mlp_fc1_bias]. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature FxOnnxInterpreter.run_node\n- self: \n- node: fx.Node(p_getattr_l__self___trunk_blocks___14___mlp_fc1_bias)[placeholder]:Tensor(f32[4096])\n- fx_graph_module: torch.fx.GraphModule()\n- onnxfunction_dispatcher: \n- op_level_debug: False\n- onnxscript_graph: \n- onnxscript_tracer: \n- fx_name_to_onnxscript_value: Dict[length=181](\np_trunk_pos_embed: `TorchScriptTensor(f32[1, 1024, 1024])`,\np_trunk_attn_pool_latent: `TorchScriptTensor(f32[1, 1, 1024])`,\np_trunk_patch_embed_proj_weight: `TorchScriptTensor(f32[1024, 3, 16, 16])`,\np_trunk_patch_embed_proj_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_weight: `TorchScriptTensor(f32[3072, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_bias: `TorchScriptTensor(f32[3072])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_weight: `TorchScriptTensor(f32[1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_bias: `TorchScriptTensor(f32[1024])`,\n...\n)\n## Return values\n", + "text":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___14___mlp_fc1_bias[name=p_getattr_l__self___trunk_blocks___14___mlp_fc1_bias]. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"FxOnnxInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":414 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0008", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___14___mlp_fc2_weight[name=p_getattr_l__self___trunk_blocks___14___mlp_fc2_weight]. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature FxOnnxInterpreter.run_node\n- self: \n- node: fx.Node(p_getattr_l__self___trunk_blocks___14___mlp_fc2_weight)[placeholder]:Tensor(f32[1024, 4096])\n- fx_graph_module: torch.fx.GraphModule()\n- onnxfunction_dispatcher: \n- op_level_debug: False\n- onnxscript_graph: \n- onnxscript_tracer: \n- fx_name_to_onnxscript_value: Dict[length=182](\np_trunk_pos_embed: `TorchScriptTensor(f32[1, 1024, 1024])`,\np_trunk_attn_pool_latent: `TorchScriptTensor(f32[1, 1, 1024])`,\np_trunk_patch_embed_proj_weight: `TorchScriptTensor(f32[1024, 3, 16, 16])`,\np_trunk_patch_embed_proj_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_weight: `TorchScriptTensor(f32[3072, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_bias: `TorchScriptTensor(f32[3072])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_weight: `TorchScriptTensor(f32[1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_bias: `TorchScriptTensor(f32[1024])`,\n...\n)\n## Return values\n", + "text":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___14___mlp_fc2_weight[name=p_getattr_l__self___trunk_blocks___14___mlp_fc2_weight]. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"FxOnnxInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":414 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0008", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___14___mlp_fc2_bias[name=p_getattr_l__self___trunk_blocks___14___mlp_fc2_bias]. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature FxOnnxInterpreter.run_node\n- self: \n- node: fx.Node(p_getattr_l__self___trunk_blocks___14___mlp_fc2_bias)[placeholder]:Tensor(f32[1024])\n- fx_graph_module: torch.fx.GraphModule()\n- onnxfunction_dispatcher: \n- op_level_debug: False\n- onnxscript_graph: \n- onnxscript_tracer: \n- fx_name_to_onnxscript_value: Dict[length=183](\np_trunk_pos_embed: `TorchScriptTensor(f32[1, 1024, 1024])`,\np_trunk_attn_pool_latent: `TorchScriptTensor(f32[1, 1, 1024])`,\np_trunk_patch_embed_proj_weight: `TorchScriptTensor(f32[1024, 3, 16, 16])`,\np_trunk_patch_embed_proj_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_weight: `TorchScriptTensor(f32[3072, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_bias: `TorchScriptTensor(f32[3072])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_weight: `TorchScriptTensor(f32[1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_bias: `TorchScriptTensor(f32[1024])`,\n...\n)\n## Return values\n", + "text":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___14___mlp_fc2_bias[name=p_getattr_l__self___trunk_blocks___14___mlp_fc2_bias]. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"FxOnnxInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":414 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0008", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___15___norm1_weight[name=p_getattr_l__self___trunk_blocks___15___norm1_weight]. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature FxOnnxInterpreter.run_node\n- self: \n- node: fx.Node(p_getattr_l__self___trunk_blocks___15___norm1_weight)[placeholder]:Tensor(f32[1024])\n- fx_graph_module: torch.fx.GraphModule()\n- onnxfunction_dispatcher: \n- op_level_debug: False\n- onnxscript_graph: \n- onnxscript_tracer: \n- fx_name_to_onnxscript_value: Dict[length=184](\np_trunk_pos_embed: `TorchScriptTensor(f32[1, 1024, 1024])`,\np_trunk_attn_pool_latent: `TorchScriptTensor(f32[1, 1, 1024])`,\np_trunk_patch_embed_proj_weight: `TorchScriptTensor(f32[1024, 3, 16, 16])`,\np_trunk_patch_embed_proj_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_weight: `TorchScriptTensor(f32[3072, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_bias: `TorchScriptTensor(f32[3072])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_weight: `TorchScriptTensor(f32[1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_bias: `TorchScriptTensor(f32[1024])`,\n...\n)\n## Return values\n", + "text":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___15___norm1_weight[name=p_getattr_l__self___trunk_blocks___15___norm1_weight]. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"FxOnnxInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":414 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0008", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___15___norm1_bias[name=p_getattr_l__self___trunk_blocks___15___norm1_bias]. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature FxOnnxInterpreter.run_node\n- self: \n- node: fx.Node(p_getattr_l__self___trunk_blocks___15___norm1_bias)[placeholder]:Tensor(f32[1024])\n- fx_graph_module: torch.fx.GraphModule()\n- onnxfunction_dispatcher: \n- op_level_debug: False\n- onnxscript_graph: \n- onnxscript_tracer: \n- fx_name_to_onnxscript_value: Dict[length=185](\np_trunk_pos_embed: `TorchScriptTensor(f32[1, 1024, 1024])`,\np_trunk_attn_pool_latent: `TorchScriptTensor(f32[1, 1, 1024])`,\np_trunk_patch_embed_proj_weight: `TorchScriptTensor(f32[1024, 3, 16, 16])`,\np_trunk_patch_embed_proj_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_weight: `TorchScriptTensor(f32[3072, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_bias: `TorchScriptTensor(f32[3072])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_weight: `TorchScriptTensor(f32[1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_bias: `TorchScriptTensor(f32[1024])`,\n...\n)\n## Return values\n", + "text":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___15___norm1_bias[name=p_getattr_l__self___trunk_blocks___15___norm1_bias]. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"FxOnnxInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":414 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0008", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___15___attn_qkv_weight[name=p_getattr_l__self___trunk_blocks___15___attn_qkv_weight]. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature FxOnnxInterpreter.run_node\n- self: \n- node: fx.Node(p_getattr_l__self___trunk_blocks___15___attn_qkv_weight)[placeholder]:Tensor(f32[3072, 1024])\n- fx_graph_module: torch.fx.GraphModule()\n- onnxfunction_dispatcher: \n- op_level_debug: False\n- onnxscript_graph: \n- onnxscript_tracer: \n- fx_name_to_onnxscript_value: Dict[length=186](\np_trunk_pos_embed: `TorchScriptTensor(f32[1, 1024, 1024])`,\np_trunk_attn_pool_latent: `TorchScriptTensor(f32[1, 1, 1024])`,\np_trunk_patch_embed_proj_weight: `TorchScriptTensor(f32[1024, 3, 16, 16])`,\np_trunk_patch_embed_proj_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_weight: `TorchScriptTensor(f32[3072, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_bias: `TorchScriptTensor(f32[3072])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_weight: `TorchScriptTensor(f32[1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_bias: `TorchScriptTensor(f32[1024])`,\n...\n)\n## Return values\n", + "text":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___15___attn_qkv_weight[name=p_getattr_l__self___trunk_blocks___15___attn_qkv_weight]. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"FxOnnxInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":414 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0008", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___15___attn_qkv_bias[name=p_getattr_l__self___trunk_blocks___15___attn_qkv_bias]. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature FxOnnxInterpreter.run_node\n- self: \n- node: fx.Node(p_getattr_l__self___trunk_blocks___15___attn_qkv_bias)[placeholder]:Tensor(f32[3072])\n- fx_graph_module: torch.fx.GraphModule()\n- onnxfunction_dispatcher: \n- op_level_debug: False\n- onnxscript_graph: \n- onnxscript_tracer: \n- fx_name_to_onnxscript_value: Dict[length=187](\np_trunk_pos_embed: `TorchScriptTensor(f32[1, 1024, 1024])`,\np_trunk_attn_pool_latent: `TorchScriptTensor(f32[1, 1, 1024])`,\np_trunk_patch_embed_proj_weight: `TorchScriptTensor(f32[1024, 3, 16, 16])`,\np_trunk_patch_embed_proj_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_weight: `TorchScriptTensor(f32[3072, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_bias: `TorchScriptTensor(f32[3072])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_weight: `TorchScriptTensor(f32[1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_bias: `TorchScriptTensor(f32[1024])`,\n...\n)\n## Return values\n", + "text":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___15___attn_qkv_bias[name=p_getattr_l__self___trunk_blocks___15___attn_qkv_bias]. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"FxOnnxInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":414 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0008", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___15___attn_proj_weight[name=p_getattr_l__self___trunk_blocks___15___attn_proj_weight]. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature FxOnnxInterpreter.run_node\n- self: \n- node: fx.Node(p_getattr_l__self___trunk_blocks___15___attn_proj_weight)[placeholder]:Tensor(f32[1024, 1024])\n- fx_graph_module: torch.fx.GraphModule()\n- onnxfunction_dispatcher: \n- op_level_debug: False\n- onnxscript_graph: \n- onnxscript_tracer: \n- fx_name_to_onnxscript_value: Dict[length=188](\np_trunk_pos_embed: `TorchScriptTensor(f32[1, 1024, 1024])`,\np_trunk_attn_pool_latent: `TorchScriptTensor(f32[1, 1, 1024])`,\np_trunk_patch_embed_proj_weight: `TorchScriptTensor(f32[1024, 3, 16, 16])`,\np_trunk_patch_embed_proj_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_weight: `TorchScriptTensor(f32[3072, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_bias: `TorchScriptTensor(f32[3072])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_weight: `TorchScriptTensor(f32[1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_bias: `TorchScriptTensor(f32[1024])`,\n...\n)\n## Return values\n", + "text":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___15___attn_proj_weight[name=p_getattr_l__self___trunk_blocks___15___attn_proj_weight]. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"FxOnnxInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":414 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0008", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___15___attn_proj_bias[name=p_getattr_l__self___trunk_blocks___15___attn_proj_bias]. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature FxOnnxInterpreter.run_node\n- self: \n- node: fx.Node(p_getattr_l__self___trunk_blocks___15___attn_proj_bias)[placeholder]:Tensor(f32[1024])\n- fx_graph_module: torch.fx.GraphModule()\n- onnxfunction_dispatcher: \n- op_level_debug: False\n- onnxscript_graph: \n- onnxscript_tracer: \n- fx_name_to_onnxscript_value: Dict[length=189](\np_trunk_pos_embed: `TorchScriptTensor(f32[1, 1024, 1024])`,\np_trunk_attn_pool_latent: `TorchScriptTensor(f32[1, 1, 1024])`,\np_trunk_patch_embed_proj_weight: `TorchScriptTensor(f32[1024, 3, 16, 16])`,\np_trunk_patch_embed_proj_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_weight: `TorchScriptTensor(f32[3072, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_bias: `TorchScriptTensor(f32[3072])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_weight: `TorchScriptTensor(f32[1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_bias: `TorchScriptTensor(f32[1024])`,\n...\n)\n## Return values\n", + "text":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___15___attn_proj_bias[name=p_getattr_l__self___trunk_blocks___15___attn_proj_bias]. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"FxOnnxInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":414 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0008", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___15___norm2_weight[name=p_getattr_l__self___trunk_blocks___15___norm2_weight]. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature FxOnnxInterpreter.run_node\n- self: \n- node: fx.Node(p_getattr_l__self___trunk_blocks___15___norm2_weight)[placeholder]:Tensor(f32[1024])\n- fx_graph_module: torch.fx.GraphModule()\n- onnxfunction_dispatcher: \n- op_level_debug: False\n- onnxscript_graph: \n- onnxscript_tracer: \n- fx_name_to_onnxscript_value: Dict[length=190](\np_trunk_pos_embed: `TorchScriptTensor(f32[1, 1024, 1024])`,\np_trunk_attn_pool_latent: `TorchScriptTensor(f32[1, 1, 1024])`,\np_trunk_patch_embed_proj_weight: `TorchScriptTensor(f32[1024, 3, 16, 16])`,\np_trunk_patch_embed_proj_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_weight: `TorchScriptTensor(f32[3072, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_bias: `TorchScriptTensor(f32[3072])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_weight: `TorchScriptTensor(f32[1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_bias: `TorchScriptTensor(f32[1024])`,\n...\n)\n## Return values\n", + "text":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___15___norm2_weight[name=p_getattr_l__self___trunk_blocks___15___norm2_weight]. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"FxOnnxInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":414 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0008", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___15___norm2_bias[name=p_getattr_l__self___trunk_blocks___15___norm2_bias]. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature FxOnnxInterpreter.run_node\n- self: \n- node: fx.Node(p_getattr_l__self___trunk_blocks___15___norm2_bias)[placeholder]:Tensor(f32[1024])\n- fx_graph_module: torch.fx.GraphModule()\n- onnxfunction_dispatcher: \n- op_level_debug: False\n- onnxscript_graph: \n- onnxscript_tracer: \n- fx_name_to_onnxscript_value: Dict[length=191](\np_trunk_pos_embed: `TorchScriptTensor(f32[1, 1024, 1024])`,\np_trunk_attn_pool_latent: `TorchScriptTensor(f32[1, 1, 1024])`,\np_trunk_patch_embed_proj_weight: `TorchScriptTensor(f32[1024, 3, 16, 16])`,\np_trunk_patch_embed_proj_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_weight: `TorchScriptTensor(f32[3072, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_bias: `TorchScriptTensor(f32[3072])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_weight: `TorchScriptTensor(f32[1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_bias: `TorchScriptTensor(f32[1024])`,\n...\n)\n## Return values\n", + "text":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___15___norm2_bias[name=p_getattr_l__self___trunk_blocks___15___norm2_bias]. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"FxOnnxInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":414 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0008", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___15___mlp_fc1_weight[name=p_getattr_l__self___trunk_blocks___15___mlp_fc1_weight]. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature FxOnnxInterpreter.run_node\n- self: \n- node: fx.Node(p_getattr_l__self___trunk_blocks___15___mlp_fc1_weight)[placeholder]:Tensor(f32[4096, 1024])\n- fx_graph_module: torch.fx.GraphModule()\n- onnxfunction_dispatcher: \n- op_level_debug: False\n- onnxscript_graph: \n- onnxscript_tracer: \n- fx_name_to_onnxscript_value: Dict[length=192](\np_trunk_pos_embed: `TorchScriptTensor(f32[1, 1024, 1024])`,\np_trunk_attn_pool_latent: `TorchScriptTensor(f32[1, 1, 1024])`,\np_trunk_patch_embed_proj_weight: `TorchScriptTensor(f32[1024, 3, 16, 16])`,\np_trunk_patch_embed_proj_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_weight: `TorchScriptTensor(f32[3072, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_bias: `TorchScriptTensor(f32[3072])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_weight: `TorchScriptTensor(f32[1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_bias: `TorchScriptTensor(f32[1024])`,\n...\n)\n## Return values\n", + "text":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___15___mlp_fc1_weight[name=p_getattr_l__self___trunk_blocks___15___mlp_fc1_weight]. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"FxOnnxInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":414 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0008", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___15___mlp_fc1_bias[name=p_getattr_l__self___trunk_blocks___15___mlp_fc1_bias]. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature FxOnnxInterpreter.run_node\n- self: \n- node: fx.Node(p_getattr_l__self___trunk_blocks___15___mlp_fc1_bias)[placeholder]:Tensor(f32[4096])\n- fx_graph_module: torch.fx.GraphModule()\n- onnxfunction_dispatcher: \n- op_level_debug: False\n- onnxscript_graph: \n- onnxscript_tracer: \n- fx_name_to_onnxscript_value: Dict[length=193](\np_trunk_pos_embed: `TorchScriptTensor(f32[1, 1024, 1024])`,\np_trunk_attn_pool_latent: `TorchScriptTensor(f32[1, 1, 1024])`,\np_trunk_patch_embed_proj_weight: `TorchScriptTensor(f32[1024, 3, 16, 16])`,\np_trunk_patch_embed_proj_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_weight: `TorchScriptTensor(f32[3072, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_bias: `TorchScriptTensor(f32[3072])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_weight: `TorchScriptTensor(f32[1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_bias: `TorchScriptTensor(f32[1024])`,\n...\n)\n## Return values\n", + "text":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___15___mlp_fc1_bias[name=p_getattr_l__self___trunk_blocks___15___mlp_fc1_bias]. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"FxOnnxInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":414 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0008", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___15___mlp_fc2_weight[name=p_getattr_l__self___trunk_blocks___15___mlp_fc2_weight]. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature FxOnnxInterpreter.run_node\n- self: \n- node: fx.Node(p_getattr_l__self___trunk_blocks___15___mlp_fc2_weight)[placeholder]:Tensor(f32[1024, 4096])\n- fx_graph_module: torch.fx.GraphModule()\n- onnxfunction_dispatcher: \n- op_level_debug: False\n- onnxscript_graph: \n- onnxscript_tracer: \n- fx_name_to_onnxscript_value: Dict[length=194](\np_trunk_pos_embed: `TorchScriptTensor(f32[1, 1024, 1024])`,\np_trunk_attn_pool_latent: `TorchScriptTensor(f32[1, 1, 1024])`,\np_trunk_patch_embed_proj_weight: `TorchScriptTensor(f32[1024, 3, 16, 16])`,\np_trunk_patch_embed_proj_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_weight: `TorchScriptTensor(f32[3072, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_bias: `TorchScriptTensor(f32[3072])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_weight: `TorchScriptTensor(f32[1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_bias: `TorchScriptTensor(f32[1024])`,\n...\n)\n## Return values\n", + "text":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___15___mlp_fc2_weight[name=p_getattr_l__self___trunk_blocks___15___mlp_fc2_weight]. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"FxOnnxInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":414 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0008", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___15___mlp_fc2_bias[name=p_getattr_l__self___trunk_blocks___15___mlp_fc2_bias]. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature FxOnnxInterpreter.run_node\n- self: \n- node: fx.Node(p_getattr_l__self___trunk_blocks___15___mlp_fc2_bias)[placeholder]:Tensor(f32[1024])\n- fx_graph_module: torch.fx.GraphModule()\n- onnxfunction_dispatcher: \n- op_level_debug: False\n- onnxscript_graph: \n- onnxscript_tracer: \n- fx_name_to_onnxscript_value: Dict[length=195](\np_trunk_pos_embed: `TorchScriptTensor(f32[1, 1024, 1024])`,\np_trunk_attn_pool_latent: `TorchScriptTensor(f32[1, 1, 1024])`,\np_trunk_patch_embed_proj_weight: `TorchScriptTensor(f32[1024, 3, 16, 16])`,\np_trunk_patch_embed_proj_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_weight: `TorchScriptTensor(f32[3072, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_bias: `TorchScriptTensor(f32[3072])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_weight: `TorchScriptTensor(f32[1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_bias: `TorchScriptTensor(f32[1024])`,\n...\n)\n## Return values\n", + "text":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___15___mlp_fc2_bias[name=p_getattr_l__self___trunk_blocks___15___mlp_fc2_bias]. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"FxOnnxInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":414 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0008", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___16___norm1_weight[name=p_getattr_l__self___trunk_blocks___16___norm1_weight]. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature FxOnnxInterpreter.run_node\n- self: \n- node: fx.Node(p_getattr_l__self___trunk_blocks___16___norm1_weight)[placeholder]:Tensor(f32[1024])\n- fx_graph_module: torch.fx.GraphModule()\n- onnxfunction_dispatcher: \n- op_level_debug: False\n- onnxscript_graph: \n- onnxscript_tracer: \n- fx_name_to_onnxscript_value: Dict[length=196](\np_trunk_pos_embed: `TorchScriptTensor(f32[1, 1024, 1024])`,\np_trunk_attn_pool_latent: `TorchScriptTensor(f32[1, 1, 1024])`,\np_trunk_patch_embed_proj_weight: `TorchScriptTensor(f32[1024, 3, 16, 16])`,\np_trunk_patch_embed_proj_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_weight: `TorchScriptTensor(f32[3072, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_bias: `TorchScriptTensor(f32[3072])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_weight: `TorchScriptTensor(f32[1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_bias: `TorchScriptTensor(f32[1024])`,\n...\n)\n## Return values\n", + "text":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___16___norm1_weight[name=p_getattr_l__self___trunk_blocks___16___norm1_weight]. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"FxOnnxInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":414 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0008", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___16___norm1_bias[name=p_getattr_l__self___trunk_blocks___16___norm1_bias]. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature FxOnnxInterpreter.run_node\n- self: \n- node: fx.Node(p_getattr_l__self___trunk_blocks___16___norm1_bias)[placeholder]:Tensor(f32[1024])\n- fx_graph_module: torch.fx.GraphModule()\n- onnxfunction_dispatcher: \n- op_level_debug: False\n- onnxscript_graph: \n- onnxscript_tracer: \n- fx_name_to_onnxscript_value: Dict[length=197](\np_trunk_pos_embed: `TorchScriptTensor(f32[1, 1024, 1024])`,\np_trunk_attn_pool_latent: `TorchScriptTensor(f32[1, 1, 1024])`,\np_trunk_patch_embed_proj_weight: `TorchScriptTensor(f32[1024, 3, 16, 16])`,\np_trunk_patch_embed_proj_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_weight: `TorchScriptTensor(f32[3072, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_bias: `TorchScriptTensor(f32[3072])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_weight: `TorchScriptTensor(f32[1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_bias: `TorchScriptTensor(f32[1024])`,\n...\n)\n## Return values\n", + "text":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___16___norm1_bias[name=p_getattr_l__self___trunk_blocks___16___norm1_bias]. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"FxOnnxInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":414 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0008", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___16___attn_qkv_weight[name=p_getattr_l__self___trunk_blocks___16___attn_qkv_weight]. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature FxOnnxInterpreter.run_node\n- self: \n- node: fx.Node(p_getattr_l__self___trunk_blocks___16___attn_qkv_weight)[placeholder]:Tensor(f32[3072, 1024])\n- fx_graph_module: torch.fx.GraphModule()\n- onnxfunction_dispatcher: \n- op_level_debug: False\n- onnxscript_graph: \n- onnxscript_tracer: \n- fx_name_to_onnxscript_value: Dict[length=198](\np_trunk_pos_embed: `TorchScriptTensor(f32[1, 1024, 1024])`,\np_trunk_attn_pool_latent: `TorchScriptTensor(f32[1, 1, 1024])`,\np_trunk_patch_embed_proj_weight: `TorchScriptTensor(f32[1024, 3, 16, 16])`,\np_trunk_patch_embed_proj_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_weight: `TorchScriptTensor(f32[3072, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_bias: `TorchScriptTensor(f32[3072])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_weight: `TorchScriptTensor(f32[1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_bias: `TorchScriptTensor(f32[1024])`,\n...\n)\n## Return values\n", + "text":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___16___attn_qkv_weight[name=p_getattr_l__self___trunk_blocks___16___attn_qkv_weight]. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"FxOnnxInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":414 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0008", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___16___attn_qkv_bias[name=p_getattr_l__self___trunk_blocks___16___attn_qkv_bias]. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature FxOnnxInterpreter.run_node\n- self: \n- node: fx.Node(p_getattr_l__self___trunk_blocks___16___attn_qkv_bias)[placeholder]:Tensor(f32[3072])\n- fx_graph_module: torch.fx.GraphModule()\n- onnxfunction_dispatcher: \n- op_level_debug: False\n- onnxscript_graph: \n- onnxscript_tracer: \n- fx_name_to_onnxscript_value: Dict[length=199](\np_trunk_pos_embed: `TorchScriptTensor(f32[1, 1024, 1024])`,\np_trunk_attn_pool_latent: `TorchScriptTensor(f32[1, 1, 1024])`,\np_trunk_patch_embed_proj_weight: `TorchScriptTensor(f32[1024, 3, 16, 16])`,\np_trunk_patch_embed_proj_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_weight: `TorchScriptTensor(f32[3072, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_bias: `TorchScriptTensor(f32[3072])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_weight: `TorchScriptTensor(f32[1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_bias: `TorchScriptTensor(f32[1024])`,\n...\n)\n## Return values\n", + "text":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___16___attn_qkv_bias[name=p_getattr_l__self___trunk_blocks___16___attn_qkv_bias]. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"FxOnnxInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":414 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0008", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___16___attn_proj_weight[name=p_getattr_l__self___trunk_blocks___16___attn_proj_weight]. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature FxOnnxInterpreter.run_node\n- self: \n- node: fx.Node(p_getattr_l__self___trunk_blocks___16___attn_proj_weight)[placeholder]:Tensor(f32[1024, 1024])\n- fx_graph_module: torch.fx.GraphModule()\n- onnxfunction_dispatcher: \n- op_level_debug: False\n- onnxscript_graph: \n- onnxscript_tracer: \n- fx_name_to_onnxscript_value: Dict[length=200](\np_trunk_pos_embed: `TorchScriptTensor(f32[1, 1024, 1024])`,\np_trunk_attn_pool_latent: `TorchScriptTensor(f32[1, 1, 1024])`,\np_trunk_patch_embed_proj_weight: `TorchScriptTensor(f32[1024, 3, 16, 16])`,\np_trunk_patch_embed_proj_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_weight: `TorchScriptTensor(f32[3072, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_bias: `TorchScriptTensor(f32[3072])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_weight: `TorchScriptTensor(f32[1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_bias: `TorchScriptTensor(f32[1024])`,\n...\n)\n## Return values\n", + "text":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___16___attn_proj_weight[name=p_getattr_l__self___trunk_blocks___16___attn_proj_weight]. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"FxOnnxInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":414 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0008", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___16___attn_proj_bias[name=p_getattr_l__self___trunk_blocks___16___attn_proj_bias]. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature FxOnnxInterpreter.run_node\n- self: \n- node: fx.Node(p_getattr_l__self___trunk_blocks___16___attn_proj_bias)[placeholder]:Tensor(f32[1024])\n- fx_graph_module: torch.fx.GraphModule()\n- onnxfunction_dispatcher: \n- op_level_debug: False\n- onnxscript_graph: \n- onnxscript_tracer: \n- fx_name_to_onnxscript_value: Dict[length=201](\np_trunk_pos_embed: `TorchScriptTensor(f32[1, 1024, 1024])`,\np_trunk_attn_pool_latent: `TorchScriptTensor(f32[1, 1, 1024])`,\np_trunk_patch_embed_proj_weight: `TorchScriptTensor(f32[1024, 3, 16, 16])`,\np_trunk_patch_embed_proj_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_weight: `TorchScriptTensor(f32[3072, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_bias: `TorchScriptTensor(f32[3072])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_weight: `TorchScriptTensor(f32[1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_bias: `TorchScriptTensor(f32[1024])`,\n...\n)\n## Return values\n", + "text":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___16___attn_proj_bias[name=p_getattr_l__self___trunk_blocks___16___attn_proj_bias]. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"FxOnnxInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":414 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0008", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___16___norm2_weight[name=p_getattr_l__self___trunk_blocks___16___norm2_weight]. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature FxOnnxInterpreter.run_node\n- self: \n- node: fx.Node(p_getattr_l__self___trunk_blocks___16___norm2_weight)[placeholder]:Tensor(f32[1024])\n- fx_graph_module: torch.fx.GraphModule()\n- onnxfunction_dispatcher: \n- op_level_debug: False\n- onnxscript_graph: \n- onnxscript_tracer: \n- fx_name_to_onnxscript_value: Dict[length=202](\np_trunk_pos_embed: `TorchScriptTensor(f32[1, 1024, 1024])`,\np_trunk_attn_pool_latent: `TorchScriptTensor(f32[1, 1, 1024])`,\np_trunk_patch_embed_proj_weight: `TorchScriptTensor(f32[1024, 3, 16, 16])`,\np_trunk_patch_embed_proj_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_weight: `TorchScriptTensor(f32[3072, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_bias: `TorchScriptTensor(f32[3072])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_weight: `TorchScriptTensor(f32[1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_bias: `TorchScriptTensor(f32[1024])`,\n...\n)\n## Return values\n", + "text":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___16___norm2_weight[name=p_getattr_l__self___trunk_blocks___16___norm2_weight]. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"FxOnnxInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":414 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0008", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___16___norm2_bias[name=p_getattr_l__self___trunk_blocks___16___norm2_bias]. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature FxOnnxInterpreter.run_node\n- self: \n- node: fx.Node(p_getattr_l__self___trunk_blocks___16___norm2_bias)[placeholder]:Tensor(f32[1024])\n- fx_graph_module: torch.fx.GraphModule()\n- onnxfunction_dispatcher: \n- op_level_debug: False\n- onnxscript_graph: \n- onnxscript_tracer: \n- fx_name_to_onnxscript_value: Dict[length=203](\np_trunk_pos_embed: `TorchScriptTensor(f32[1, 1024, 1024])`,\np_trunk_attn_pool_latent: `TorchScriptTensor(f32[1, 1, 1024])`,\np_trunk_patch_embed_proj_weight: `TorchScriptTensor(f32[1024, 3, 16, 16])`,\np_trunk_patch_embed_proj_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_weight: `TorchScriptTensor(f32[3072, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_bias: `TorchScriptTensor(f32[3072])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_weight: `TorchScriptTensor(f32[1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_bias: `TorchScriptTensor(f32[1024])`,\n...\n)\n## Return values\n", + "text":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___16___norm2_bias[name=p_getattr_l__self___trunk_blocks___16___norm2_bias]. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"FxOnnxInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":414 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0008", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___16___mlp_fc1_weight[name=p_getattr_l__self___trunk_blocks___16___mlp_fc1_weight]. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature FxOnnxInterpreter.run_node\n- self: \n- node: fx.Node(p_getattr_l__self___trunk_blocks___16___mlp_fc1_weight)[placeholder]:Tensor(f32[4096, 1024])\n- fx_graph_module: torch.fx.GraphModule()\n- onnxfunction_dispatcher: \n- op_level_debug: False\n- onnxscript_graph: \n- onnxscript_tracer: \n- fx_name_to_onnxscript_value: Dict[length=204](\np_trunk_pos_embed: `TorchScriptTensor(f32[1, 1024, 1024])`,\np_trunk_attn_pool_latent: `TorchScriptTensor(f32[1, 1, 1024])`,\np_trunk_patch_embed_proj_weight: `TorchScriptTensor(f32[1024, 3, 16, 16])`,\np_trunk_patch_embed_proj_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_weight: `TorchScriptTensor(f32[3072, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_bias: `TorchScriptTensor(f32[3072])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_weight: `TorchScriptTensor(f32[1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_bias: `TorchScriptTensor(f32[1024])`,\n...\n)\n## Return values\n", + "text":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___16___mlp_fc1_weight[name=p_getattr_l__self___trunk_blocks___16___mlp_fc1_weight]. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"FxOnnxInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":414 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0008", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___16___mlp_fc1_bias[name=p_getattr_l__self___trunk_blocks___16___mlp_fc1_bias]. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature FxOnnxInterpreter.run_node\n- self: \n- node: fx.Node(p_getattr_l__self___trunk_blocks___16___mlp_fc1_bias)[placeholder]:Tensor(f32[4096])\n- fx_graph_module: torch.fx.GraphModule()\n- onnxfunction_dispatcher: \n- op_level_debug: False\n- onnxscript_graph: \n- onnxscript_tracer: \n- fx_name_to_onnxscript_value: Dict[length=205](\np_trunk_pos_embed: `TorchScriptTensor(f32[1, 1024, 1024])`,\np_trunk_attn_pool_latent: `TorchScriptTensor(f32[1, 1, 1024])`,\np_trunk_patch_embed_proj_weight: `TorchScriptTensor(f32[1024, 3, 16, 16])`,\np_trunk_patch_embed_proj_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_weight: `TorchScriptTensor(f32[3072, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_bias: `TorchScriptTensor(f32[3072])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_weight: `TorchScriptTensor(f32[1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_bias: `TorchScriptTensor(f32[1024])`,\n...\n)\n## Return values\n", + "text":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___16___mlp_fc1_bias[name=p_getattr_l__self___trunk_blocks___16___mlp_fc1_bias]. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"FxOnnxInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":414 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0008", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___16___mlp_fc2_weight[name=p_getattr_l__self___trunk_blocks___16___mlp_fc2_weight]. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature FxOnnxInterpreter.run_node\n- self: \n- node: fx.Node(p_getattr_l__self___trunk_blocks___16___mlp_fc2_weight)[placeholder]:Tensor(f32[1024, 4096])\n- fx_graph_module: torch.fx.GraphModule()\n- onnxfunction_dispatcher: \n- op_level_debug: False\n- onnxscript_graph: \n- onnxscript_tracer: \n- fx_name_to_onnxscript_value: Dict[length=206](\np_trunk_pos_embed: `TorchScriptTensor(f32[1, 1024, 1024])`,\np_trunk_attn_pool_latent: `TorchScriptTensor(f32[1, 1, 1024])`,\np_trunk_patch_embed_proj_weight: `TorchScriptTensor(f32[1024, 3, 16, 16])`,\np_trunk_patch_embed_proj_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_weight: `TorchScriptTensor(f32[3072, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_bias: `TorchScriptTensor(f32[3072])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_weight: `TorchScriptTensor(f32[1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_bias: `TorchScriptTensor(f32[1024])`,\n...\n)\n## Return values\n", + "text":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___16___mlp_fc2_weight[name=p_getattr_l__self___trunk_blocks___16___mlp_fc2_weight]. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"FxOnnxInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":414 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0008", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___16___mlp_fc2_bias[name=p_getattr_l__self___trunk_blocks___16___mlp_fc2_bias]. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature FxOnnxInterpreter.run_node\n- self: \n- node: fx.Node(p_getattr_l__self___trunk_blocks___16___mlp_fc2_bias)[placeholder]:Tensor(f32[1024])\n- fx_graph_module: torch.fx.GraphModule()\n- onnxfunction_dispatcher: \n- op_level_debug: False\n- onnxscript_graph: \n- onnxscript_tracer: \n- fx_name_to_onnxscript_value: Dict[length=207](\np_trunk_pos_embed: `TorchScriptTensor(f32[1, 1024, 1024])`,\np_trunk_attn_pool_latent: `TorchScriptTensor(f32[1, 1, 1024])`,\np_trunk_patch_embed_proj_weight: `TorchScriptTensor(f32[1024, 3, 16, 16])`,\np_trunk_patch_embed_proj_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_weight: `TorchScriptTensor(f32[3072, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_bias: `TorchScriptTensor(f32[3072])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_weight: `TorchScriptTensor(f32[1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_bias: `TorchScriptTensor(f32[1024])`,\n...\n)\n## Return values\n", + "text":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___16___mlp_fc2_bias[name=p_getattr_l__self___trunk_blocks___16___mlp_fc2_bias]. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"FxOnnxInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":414 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0008", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___17___norm1_weight[name=p_getattr_l__self___trunk_blocks___17___norm1_weight]. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature FxOnnxInterpreter.run_node\n- self: \n- node: fx.Node(p_getattr_l__self___trunk_blocks___17___norm1_weight)[placeholder]:Tensor(f32[1024])\n- fx_graph_module: torch.fx.GraphModule()\n- onnxfunction_dispatcher: \n- op_level_debug: False\n- onnxscript_graph: \n- onnxscript_tracer: \n- fx_name_to_onnxscript_value: Dict[length=208](\np_trunk_pos_embed: `TorchScriptTensor(f32[1, 1024, 1024])`,\np_trunk_attn_pool_latent: `TorchScriptTensor(f32[1, 1, 1024])`,\np_trunk_patch_embed_proj_weight: `TorchScriptTensor(f32[1024, 3, 16, 16])`,\np_trunk_patch_embed_proj_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_weight: `TorchScriptTensor(f32[3072, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_bias: `TorchScriptTensor(f32[3072])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_weight: `TorchScriptTensor(f32[1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_bias: `TorchScriptTensor(f32[1024])`,\n...\n)\n## Return values\n", + "text":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___17___norm1_weight[name=p_getattr_l__self___trunk_blocks___17___norm1_weight]. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"FxOnnxInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":414 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0008", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___17___norm1_bias[name=p_getattr_l__self___trunk_blocks___17___norm1_bias]. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature FxOnnxInterpreter.run_node\n- self: \n- node: fx.Node(p_getattr_l__self___trunk_blocks___17___norm1_bias)[placeholder]:Tensor(f32[1024])\n- fx_graph_module: torch.fx.GraphModule()\n- onnxfunction_dispatcher: \n- op_level_debug: False\n- onnxscript_graph: \n- onnxscript_tracer: \n- fx_name_to_onnxscript_value: Dict[length=209](\np_trunk_pos_embed: `TorchScriptTensor(f32[1, 1024, 1024])`,\np_trunk_attn_pool_latent: `TorchScriptTensor(f32[1, 1, 1024])`,\np_trunk_patch_embed_proj_weight: `TorchScriptTensor(f32[1024, 3, 16, 16])`,\np_trunk_patch_embed_proj_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_weight: `TorchScriptTensor(f32[3072, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_bias: `TorchScriptTensor(f32[3072])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_weight: `TorchScriptTensor(f32[1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_bias: `TorchScriptTensor(f32[1024])`,\n...\n)\n## Return values\n", + "text":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___17___norm1_bias[name=p_getattr_l__self___trunk_blocks___17___norm1_bias]. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"FxOnnxInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":414 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0008", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___17___attn_qkv_weight[name=p_getattr_l__self___trunk_blocks___17___attn_qkv_weight]. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature FxOnnxInterpreter.run_node\n- self: \n- node: fx.Node(p_getattr_l__self___trunk_blocks___17___attn_qkv_weight)[placeholder]:Tensor(f32[3072, 1024])\n- fx_graph_module: torch.fx.GraphModule()\n- onnxfunction_dispatcher: \n- op_level_debug: False\n- onnxscript_graph: \n- onnxscript_tracer: \n- fx_name_to_onnxscript_value: Dict[length=210](\np_trunk_pos_embed: `TorchScriptTensor(f32[1, 1024, 1024])`,\np_trunk_attn_pool_latent: `TorchScriptTensor(f32[1, 1, 1024])`,\np_trunk_patch_embed_proj_weight: `TorchScriptTensor(f32[1024, 3, 16, 16])`,\np_trunk_patch_embed_proj_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_weight: `TorchScriptTensor(f32[3072, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_bias: `TorchScriptTensor(f32[3072])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_weight: `TorchScriptTensor(f32[1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_bias: `TorchScriptTensor(f32[1024])`,\n...\n)\n## Return values\n", + "text":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___17___attn_qkv_weight[name=p_getattr_l__self___trunk_blocks___17___attn_qkv_weight]. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"FxOnnxInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":414 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0008", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___17___attn_qkv_bias[name=p_getattr_l__self___trunk_blocks___17___attn_qkv_bias]. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature FxOnnxInterpreter.run_node\n- self: \n- node: fx.Node(p_getattr_l__self___trunk_blocks___17___attn_qkv_bias)[placeholder]:Tensor(f32[3072])\n- fx_graph_module: torch.fx.GraphModule()\n- onnxfunction_dispatcher: \n- op_level_debug: False\n- onnxscript_graph: \n- onnxscript_tracer: \n- fx_name_to_onnxscript_value: Dict[length=211](\np_trunk_pos_embed: `TorchScriptTensor(f32[1, 1024, 1024])`,\np_trunk_attn_pool_latent: `TorchScriptTensor(f32[1, 1, 1024])`,\np_trunk_patch_embed_proj_weight: `TorchScriptTensor(f32[1024, 3, 16, 16])`,\np_trunk_patch_embed_proj_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_weight: `TorchScriptTensor(f32[3072, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_bias: `TorchScriptTensor(f32[3072])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_weight: `TorchScriptTensor(f32[1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_bias: `TorchScriptTensor(f32[1024])`,\n...\n)\n## Return values\n", + "text":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___17___attn_qkv_bias[name=p_getattr_l__self___trunk_blocks___17___attn_qkv_bias]. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"FxOnnxInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":414 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0008", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___17___attn_proj_weight[name=p_getattr_l__self___trunk_blocks___17___attn_proj_weight]. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature FxOnnxInterpreter.run_node\n- self: \n- node: fx.Node(p_getattr_l__self___trunk_blocks___17___attn_proj_weight)[placeholder]:Tensor(f32[1024, 1024])\n- fx_graph_module: torch.fx.GraphModule()\n- onnxfunction_dispatcher: \n- op_level_debug: False\n- onnxscript_graph: \n- onnxscript_tracer: \n- fx_name_to_onnxscript_value: Dict[length=212](\np_trunk_pos_embed: `TorchScriptTensor(f32[1, 1024, 1024])`,\np_trunk_attn_pool_latent: `TorchScriptTensor(f32[1, 1, 1024])`,\np_trunk_patch_embed_proj_weight: `TorchScriptTensor(f32[1024, 3, 16, 16])`,\np_trunk_patch_embed_proj_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_weight: `TorchScriptTensor(f32[3072, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_bias: `TorchScriptTensor(f32[3072])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_weight: `TorchScriptTensor(f32[1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_bias: `TorchScriptTensor(f32[1024])`,\n...\n)\n## Return values\n", + "text":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___17___attn_proj_weight[name=p_getattr_l__self___trunk_blocks___17___attn_proj_weight]. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"FxOnnxInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":414 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0008", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___17___attn_proj_bias[name=p_getattr_l__self___trunk_blocks___17___attn_proj_bias]. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature FxOnnxInterpreter.run_node\n- self: \n- node: fx.Node(p_getattr_l__self___trunk_blocks___17___attn_proj_bias)[placeholder]:Tensor(f32[1024])\n- fx_graph_module: torch.fx.GraphModule()\n- onnxfunction_dispatcher: \n- op_level_debug: False\n- onnxscript_graph: \n- onnxscript_tracer: \n- fx_name_to_onnxscript_value: Dict[length=213](\np_trunk_pos_embed: `TorchScriptTensor(f32[1, 1024, 1024])`,\np_trunk_attn_pool_latent: `TorchScriptTensor(f32[1, 1, 1024])`,\np_trunk_patch_embed_proj_weight: `TorchScriptTensor(f32[1024, 3, 16, 16])`,\np_trunk_patch_embed_proj_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_weight: `TorchScriptTensor(f32[3072, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_bias: `TorchScriptTensor(f32[3072])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_weight: `TorchScriptTensor(f32[1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_bias: `TorchScriptTensor(f32[1024])`,\n...\n)\n## Return values\n", + "text":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___17___attn_proj_bias[name=p_getattr_l__self___trunk_blocks___17___attn_proj_bias]. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"FxOnnxInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":414 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0008", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___17___norm2_weight[name=p_getattr_l__self___trunk_blocks___17___norm2_weight]. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature FxOnnxInterpreter.run_node\n- self: \n- node: fx.Node(p_getattr_l__self___trunk_blocks___17___norm2_weight)[placeholder]:Tensor(f32[1024])\n- fx_graph_module: torch.fx.GraphModule()\n- onnxfunction_dispatcher: \n- op_level_debug: False\n- onnxscript_graph: \n- onnxscript_tracer: \n- fx_name_to_onnxscript_value: Dict[length=214](\np_trunk_pos_embed: `TorchScriptTensor(f32[1, 1024, 1024])`,\np_trunk_attn_pool_latent: `TorchScriptTensor(f32[1, 1, 1024])`,\np_trunk_patch_embed_proj_weight: `TorchScriptTensor(f32[1024, 3, 16, 16])`,\np_trunk_patch_embed_proj_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_weight: `TorchScriptTensor(f32[3072, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_bias: `TorchScriptTensor(f32[3072])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_weight: `TorchScriptTensor(f32[1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_bias: `TorchScriptTensor(f32[1024])`,\n...\n)\n## Return values\n", + "text":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___17___norm2_weight[name=p_getattr_l__self___trunk_blocks___17___norm2_weight]. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"FxOnnxInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":414 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0008", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___17___norm2_bias[name=p_getattr_l__self___trunk_blocks___17___norm2_bias]. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature FxOnnxInterpreter.run_node\n- self: \n- node: fx.Node(p_getattr_l__self___trunk_blocks___17___norm2_bias)[placeholder]:Tensor(f32[1024])\n- fx_graph_module: torch.fx.GraphModule()\n- onnxfunction_dispatcher: \n- op_level_debug: False\n- onnxscript_graph: \n- onnxscript_tracer: \n- fx_name_to_onnxscript_value: Dict[length=215](\np_trunk_pos_embed: `TorchScriptTensor(f32[1, 1024, 1024])`,\np_trunk_attn_pool_latent: `TorchScriptTensor(f32[1, 1, 1024])`,\np_trunk_patch_embed_proj_weight: `TorchScriptTensor(f32[1024, 3, 16, 16])`,\np_trunk_patch_embed_proj_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_weight: `TorchScriptTensor(f32[3072, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_bias: `TorchScriptTensor(f32[3072])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_weight: `TorchScriptTensor(f32[1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_bias: `TorchScriptTensor(f32[1024])`,\n...\n)\n## Return values\n", + "text":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___17___norm2_bias[name=p_getattr_l__self___trunk_blocks___17___norm2_bias]. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"FxOnnxInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":414 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0008", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___17___mlp_fc1_weight[name=p_getattr_l__self___trunk_blocks___17___mlp_fc1_weight]. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature FxOnnxInterpreter.run_node\n- self: \n- node: fx.Node(p_getattr_l__self___trunk_blocks___17___mlp_fc1_weight)[placeholder]:Tensor(f32[4096, 1024])\n- fx_graph_module: torch.fx.GraphModule()\n- onnxfunction_dispatcher: \n- op_level_debug: False\n- onnxscript_graph: \n- onnxscript_tracer: \n- fx_name_to_onnxscript_value: Dict[length=216](\np_trunk_pos_embed: `TorchScriptTensor(f32[1, 1024, 1024])`,\np_trunk_attn_pool_latent: `TorchScriptTensor(f32[1, 1, 1024])`,\np_trunk_patch_embed_proj_weight: `TorchScriptTensor(f32[1024, 3, 16, 16])`,\np_trunk_patch_embed_proj_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_weight: `TorchScriptTensor(f32[3072, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_bias: `TorchScriptTensor(f32[3072])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_weight: `TorchScriptTensor(f32[1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_bias: `TorchScriptTensor(f32[1024])`,\n...\n)\n## Return values\n", + "text":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___17___mlp_fc1_weight[name=p_getattr_l__self___trunk_blocks___17___mlp_fc1_weight]. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"FxOnnxInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":414 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0008", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___17___mlp_fc1_bias[name=p_getattr_l__self___trunk_blocks___17___mlp_fc1_bias]. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature FxOnnxInterpreter.run_node\n- self: \n- node: fx.Node(p_getattr_l__self___trunk_blocks___17___mlp_fc1_bias)[placeholder]:Tensor(f32[4096])\n- fx_graph_module: torch.fx.GraphModule()\n- onnxfunction_dispatcher: \n- op_level_debug: False\n- onnxscript_graph: \n- onnxscript_tracer: \n- fx_name_to_onnxscript_value: Dict[length=217](\np_trunk_pos_embed: `TorchScriptTensor(f32[1, 1024, 1024])`,\np_trunk_attn_pool_latent: `TorchScriptTensor(f32[1, 1, 1024])`,\np_trunk_patch_embed_proj_weight: `TorchScriptTensor(f32[1024, 3, 16, 16])`,\np_trunk_patch_embed_proj_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_weight: `TorchScriptTensor(f32[3072, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_bias: `TorchScriptTensor(f32[3072])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_weight: `TorchScriptTensor(f32[1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_bias: `TorchScriptTensor(f32[1024])`,\n...\n)\n## Return values\n", + "text":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___17___mlp_fc1_bias[name=p_getattr_l__self___trunk_blocks___17___mlp_fc1_bias]. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"FxOnnxInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":414 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0008", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___17___mlp_fc2_weight[name=p_getattr_l__self___trunk_blocks___17___mlp_fc2_weight]. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature FxOnnxInterpreter.run_node\n- self: \n- node: fx.Node(p_getattr_l__self___trunk_blocks___17___mlp_fc2_weight)[placeholder]:Tensor(f32[1024, 4096])\n- fx_graph_module: torch.fx.GraphModule()\n- onnxfunction_dispatcher: \n- op_level_debug: False\n- onnxscript_graph: \n- onnxscript_tracer: \n- fx_name_to_onnxscript_value: Dict[length=218](\np_trunk_pos_embed: `TorchScriptTensor(f32[1, 1024, 1024])`,\np_trunk_attn_pool_latent: `TorchScriptTensor(f32[1, 1, 1024])`,\np_trunk_patch_embed_proj_weight: `TorchScriptTensor(f32[1024, 3, 16, 16])`,\np_trunk_patch_embed_proj_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_weight: `TorchScriptTensor(f32[3072, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_bias: `TorchScriptTensor(f32[3072])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_weight: `TorchScriptTensor(f32[1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_bias: `TorchScriptTensor(f32[1024])`,\n...\n)\n## Return values\n", + "text":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___17___mlp_fc2_weight[name=p_getattr_l__self___trunk_blocks___17___mlp_fc2_weight]. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"FxOnnxInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":414 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0008", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___17___mlp_fc2_bias[name=p_getattr_l__self___trunk_blocks___17___mlp_fc2_bias]. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature FxOnnxInterpreter.run_node\n- self: \n- node: fx.Node(p_getattr_l__self___trunk_blocks___17___mlp_fc2_bias)[placeholder]:Tensor(f32[1024])\n- fx_graph_module: torch.fx.GraphModule()\n- onnxfunction_dispatcher: \n- op_level_debug: False\n- onnxscript_graph: \n- onnxscript_tracer: \n- fx_name_to_onnxscript_value: Dict[length=219](\np_trunk_pos_embed: `TorchScriptTensor(f32[1, 1024, 1024])`,\np_trunk_attn_pool_latent: `TorchScriptTensor(f32[1, 1, 1024])`,\np_trunk_patch_embed_proj_weight: `TorchScriptTensor(f32[1024, 3, 16, 16])`,\np_trunk_patch_embed_proj_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_weight: `TorchScriptTensor(f32[3072, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_bias: `TorchScriptTensor(f32[3072])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_weight: `TorchScriptTensor(f32[1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_bias: `TorchScriptTensor(f32[1024])`,\n...\n)\n## Return values\n", + "text":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___17___mlp_fc2_bias[name=p_getattr_l__self___trunk_blocks___17___mlp_fc2_bias]. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"FxOnnxInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":414 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0008", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___18___norm1_weight[name=p_getattr_l__self___trunk_blocks___18___norm1_weight]. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature FxOnnxInterpreter.run_node\n- self: \n- node: fx.Node(p_getattr_l__self___trunk_blocks___18___norm1_weight)[placeholder]:Tensor(f32[1024])\n- fx_graph_module: torch.fx.GraphModule()\n- onnxfunction_dispatcher: \n- op_level_debug: False\n- onnxscript_graph: \n- onnxscript_tracer: \n- fx_name_to_onnxscript_value: Dict[length=220](\np_trunk_pos_embed: `TorchScriptTensor(f32[1, 1024, 1024])`,\np_trunk_attn_pool_latent: `TorchScriptTensor(f32[1, 1, 1024])`,\np_trunk_patch_embed_proj_weight: `TorchScriptTensor(f32[1024, 3, 16, 16])`,\np_trunk_patch_embed_proj_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_weight: `TorchScriptTensor(f32[3072, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_bias: `TorchScriptTensor(f32[3072])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_weight: `TorchScriptTensor(f32[1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_bias: `TorchScriptTensor(f32[1024])`,\n...\n)\n## Return values\n", + "text":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___18___norm1_weight[name=p_getattr_l__self___trunk_blocks___18___norm1_weight]. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"FxOnnxInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":414 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0008", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___18___norm1_bias[name=p_getattr_l__self___trunk_blocks___18___norm1_bias]. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature FxOnnxInterpreter.run_node\n- self: \n- node: fx.Node(p_getattr_l__self___trunk_blocks___18___norm1_bias)[placeholder]:Tensor(f32[1024])\n- fx_graph_module: torch.fx.GraphModule()\n- onnxfunction_dispatcher: \n- op_level_debug: False\n- onnxscript_graph: \n- onnxscript_tracer: \n- fx_name_to_onnxscript_value: Dict[length=221](\np_trunk_pos_embed: `TorchScriptTensor(f32[1, 1024, 1024])`,\np_trunk_attn_pool_latent: `TorchScriptTensor(f32[1, 1, 1024])`,\np_trunk_patch_embed_proj_weight: `TorchScriptTensor(f32[1024, 3, 16, 16])`,\np_trunk_patch_embed_proj_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_weight: `TorchScriptTensor(f32[3072, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_bias: `TorchScriptTensor(f32[3072])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_weight: `TorchScriptTensor(f32[1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_bias: `TorchScriptTensor(f32[1024])`,\n...\n)\n## Return values\n", + "text":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___18___norm1_bias[name=p_getattr_l__self___trunk_blocks___18___norm1_bias]. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"FxOnnxInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":414 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0008", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___18___attn_qkv_weight[name=p_getattr_l__self___trunk_blocks___18___attn_qkv_weight]. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature FxOnnxInterpreter.run_node\n- self: \n- node: fx.Node(p_getattr_l__self___trunk_blocks___18___attn_qkv_weight)[placeholder]:Tensor(f32[3072, 1024])\n- fx_graph_module: torch.fx.GraphModule()\n- onnxfunction_dispatcher: \n- op_level_debug: False\n- onnxscript_graph: \n- onnxscript_tracer: \n- fx_name_to_onnxscript_value: Dict[length=222](\np_trunk_pos_embed: `TorchScriptTensor(f32[1, 1024, 1024])`,\np_trunk_attn_pool_latent: `TorchScriptTensor(f32[1, 1, 1024])`,\np_trunk_patch_embed_proj_weight: `TorchScriptTensor(f32[1024, 3, 16, 16])`,\np_trunk_patch_embed_proj_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_weight: `TorchScriptTensor(f32[3072, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_bias: `TorchScriptTensor(f32[3072])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_weight: `TorchScriptTensor(f32[1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_bias: `TorchScriptTensor(f32[1024])`,\n...\n)\n## Return values\n", + "text":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___18___attn_qkv_weight[name=p_getattr_l__self___trunk_blocks___18___attn_qkv_weight]. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"FxOnnxInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":414 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0008", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___18___attn_qkv_bias[name=p_getattr_l__self___trunk_blocks___18___attn_qkv_bias]. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature FxOnnxInterpreter.run_node\n- self: \n- node: fx.Node(p_getattr_l__self___trunk_blocks___18___attn_qkv_bias)[placeholder]:Tensor(f32[3072])\n- fx_graph_module: torch.fx.GraphModule()\n- onnxfunction_dispatcher: \n- op_level_debug: False\n- onnxscript_graph: \n- onnxscript_tracer: \n- fx_name_to_onnxscript_value: Dict[length=223](\np_trunk_pos_embed: `TorchScriptTensor(f32[1, 1024, 1024])`,\np_trunk_attn_pool_latent: `TorchScriptTensor(f32[1, 1, 1024])`,\np_trunk_patch_embed_proj_weight: `TorchScriptTensor(f32[1024, 3, 16, 16])`,\np_trunk_patch_embed_proj_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_weight: `TorchScriptTensor(f32[3072, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_bias: `TorchScriptTensor(f32[3072])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_weight: `TorchScriptTensor(f32[1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_bias: `TorchScriptTensor(f32[1024])`,\n...\n)\n## Return values\n", + "text":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___18___attn_qkv_bias[name=p_getattr_l__self___trunk_blocks___18___attn_qkv_bias]. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"FxOnnxInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":414 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0008", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___18___attn_proj_weight[name=p_getattr_l__self___trunk_blocks___18___attn_proj_weight]. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature FxOnnxInterpreter.run_node\n- self: \n- node: fx.Node(p_getattr_l__self___trunk_blocks___18___attn_proj_weight)[placeholder]:Tensor(f32[1024, 1024])\n- fx_graph_module: torch.fx.GraphModule()\n- onnxfunction_dispatcher: \n- op_level_debug: False\n- onnxscript_graph: \n- onnxscript_tracer: \n- fx_name_to_onnxscript_value: Dict[length=224](\np_trunk_pos_embed: `TorchScriptTensor(f32[1, 1024, 1024])`,\np_trunk_attn_pool_latent: `TorchScriptTensor(f32[1, 1, 1024])`,\np_trunk_patch_embed_proj_weight: `TorchScriptTensor(f32[1024, 3, 16, 16])`,\np_trunk_patch_embed_proj_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_weight: `TorchScriptTensor(f32[3072, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_bias: `TorchScriptTensor(f32[3072])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_weight: `TorchScriptTensor(f32[1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_bias: `TorchScriptTensor(f32[1024])`,\n...\n)\n## Return values\n", + "text":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___18___attn_proj_weight[name=p_getattr_l__self___trunk_blocks___18___attn_proj_weight]. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"FxOnnxInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":414 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0008", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___18___attn_proj_bias[name=p_getattr_l__self___trunk_blocks___18___attn_proj_bias]. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature FxOnnxInterpreter.run_node\n- self: \n- node: fx.Node(p_getattr_l__self___trunk_blocks___18___attn_proj_bias)[placeholder]:Tensor(f32[1024])\n- fx_graph_module: torch.fx.GraphModule()\n- onnxfunction_dispatcher: \n- op_level_debug: False\n- onnxscript_graph: \n- onnxscript_tracer: \n- fx_name_to_onnxscript_value: Dict[length=225](\np_trunk_pos_embed: `TorchScriptTensor(f32[1, 1024, 1024])`,\np_trunk_attn_pool_latent: `TorchScriptTensor(f32[1, 1, 1024])`,\np_trunk_patch_embed_proj_weight: `TorchScriptTensor(f32[1024, 3, 16, 16])`,\np_trunk_patch_embed_proj_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_weight: `TorchScriptTensor(f32[3072, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_bias: `TorchScriptTensor(f32[3072])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_weight: `TorchScriptTensor(f32[1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_bias: `TorchScriptTensor(f32[1024])`,\n...\n)\n## Return values\n", + "text":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___18___attn_proj_bias[name=p_getattr_l__self___trunk_blocks___18___attn_proj_bias]. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"FxOnnxInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":414 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0008", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___18___norm2_weight[name=p_getattr_l__self___trunk_blocks___18___norm2_weight]. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature FxOnnxInterpreter.run_node\n- self: \n- node: fx.Node(p_getattr_l__self___trunk_blocks___18___norm2_weight)[placeholder]:Tensor(f32[1024])\n- fx_graph_module: torch.fx.GraphModule()\n- onnxfunction_dispatcher: \n- op_level_debug: False\n- onnxscript_graph: \n- onnxscript_tracer: \n- fx_name_to_onnxscript_value: Dict[length=226](\np_trunk_pos_embed: `TorchScriptTensor(f32[1, 1024, 1024])`,\np_trunk_attn_pool_latent: `TorchScriptTensor(f32[1, 1, 1024])`,\np_trunk_patch_embed_proj_weight: `TorchScriptTensor(f32[1024, 3, 16, 16])`,\np_trunk_patch_embed_proj_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_weight: `TorchScriptTensor(f32[3072, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_bias: `TorchScriptTensor(f32[3072])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_weight: `TorchScriptTensor(f32[1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_bias: `TorchScriptTensor(f32[1024])`,\n...\n)\n## Return values\n", + "text":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___18___norm2_weight[name=p_getattr_l__self___trunk_blocks___18___norm2_weight]. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"FxOnnxInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":414 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0008", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___18___norm2_bias[name=p_getattr_l__self___trunk_blocks___18___norm2_bias]. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature FxOnnxInterpreter.run_node\n- self: \n- node: fx.Node(p_getattr_l__self___trunk_blocks___18___norm2_bias)[placeholder]:Tensor(f32[1024])\n- fx_graph_module: torch.fx.GraphModule()\n- onnxfunction_dispatcher: \n- op_level_debug: False\n- onnxscript_graph: \n- onnxscript_tracer: \n- fx_name_to_onnxscript_value: Dict[length=227](\np_trunk_pos_embed: `TorchScriptTensor(f32[1, 1024, 1024])`,\np_trunk_attn_pool_latent: `TorchScriptTensor(f32[1, 1, 1024])`,\np_trunk_patch_embed_proj_weight: `TorchScriptTensor(f32[1024, 3, 16, 16])`,\np_trunk_patch_embed_proj_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_weight: `TorchScriptTensor(f32[3072, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_bias: `TorchScriptTensor(f32[3072])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_weight: `TorchScriptTensor(f32[1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_bias: `TorchScriptTensor(f32[1024])`,\n...\n)\n## Return values\n", + "text":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___18___norm2_bias[name=p_getattr_l__self___trunk_blocks___18___norm2_bias]. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"FxOnnxInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":414 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0008", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___18___mlp_fc1_weight[name=p_getattr_l__self___trunk_blocks___18___mlp_fc1_weight]. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature FxOnnxInterpreter.run_node\n- self: \n- node: fx.Node(p_getattr_l__self___trunk_blocks___18___mlp_fc1_weight)[placeholder]:Tensor(f32[4096, 1024])\n- fx_graph_module: torch.fx.GraphModule()\n- onnxfunction_dispatcher: \n- op_level_debug: False\n- onnxscript_graph: \n- onnxscript_tracer: \n- fx_name_to_onnxscript_value: Dict[length=228](\np_trunk_pos_embed: `TorchScriptTensor(f32[1, 1024, 1024])`,\np_trunk_attn_pool_latent: `TorchScriptTensor(f32[1, 1, 1024])`,\np_trunk_patch_embed_proj_weight: `TorchScriptTensor(f32[1024, 3, 16, 16])`,\np_trunk_patch_embed_proj_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_weight: `TorchScriptTensor(f32[3072, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_bias: `TorchScriptTensor(f32[3072])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_weight: `TorchScriptTensor(f32[1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_bias: `TorchScriptTensor(f32[1024])`,\n...\n)\n## Return values\n", + "text":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___18___mlp_fc1_weight[name=p_getattr_l__self___trunk_blocks___18___mlp_fc1_weight]. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"FxOnnxInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":414 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0008", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___18___mlp_fc1_bias[name=p_getattr_l__self___trunk_blocks___18___mlp_fc1_bias]. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature FxOnnxInterpreter.run_node\n- self: \n- node: fx.Node(p_getattr_l__self___trunk_blocks___18___mlp_fc1_bias)[placeholder]:Tensor(f32[4096])\n- fx_graph_module: torch.fx.GraphModule()\n- onnxfunction_dispatcher: \n- op_level_debug: False\n- onnxscript_graph: \n- onnxscript_tracer: \n- fx_name_to_onnxscript_value: Dict[length=229](\np_trunk_pos_embed: `TorchScriptTensor(f32[1, 1024, 1024])`,\np_trunk_attn_pool_latent: `TorchScriptTensor(f32[1, 1, 1024])`,\np_trunk_patch_embed_proj_weight: `TorchScriptTensor(f32[1024, 3, 16, 16])`,\np_trunk_patch_embed_proj_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_weight: `TorchScriptTensor(f32[3072, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_bias: `TorchScriptTensor(f32[3072])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_weight: `TorchScriptTensor(f32[1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_bias: `TorchScriptTensor(f32[1024])`,\n...\n)\n## Return values\n", + "text":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___18___mlp_fc1_bias[name=p_getattr_l__self___trunk_blocks___18___mlp_fc1_bias]. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"FxOnnxInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":414 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0008", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___18___mlp_fc2_weight[name=p_getattr_l__self___trunk_blocks___18___mlp_fc2_weight]. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature FxOnnxInterpreter.run_node\n- self: \n- node: fx.Node(p_getattr_l__self___trunk_blocks___18___mlp_fc2_weight)[placeholder]:Tensor(f32[1024, 4096])\n- fx_graph_module: torch.fx.GraphModule()\n- onnxfunction_dispatcher: \n- op_level_debug: False\n- onnxscript_graph: \n- onnxscript_tracer: \n- fx_name_to_onnxscript_value: Dict[length=230](\np_trunk_pos_embed: `TorchScriptTensor(f32[1, 1024, 1024])`,\np_trunk_attn_pool_latent: `TorchScriptTensor(f32[1, 1, 1024])`,\np_trunk_patch_embed_proj_weight: `TorchScriptTensor(f32[1024, 3, 16, 16])`,\np_trunk_patch_embed_proj_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_weight: `TorchScriptTensor(f32[3072, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_bias: `TorchScriptTensor(f32[3072])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_weight: `TorchScriptTensor(f32[1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_bias: `TorchScriptTensor(f32[1024])`,\n...\n)\n## Return values\n", + "text":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___18___mlp_fc2_weight[name=p_getattr_l__self___trunk_blocks___18___mlp_fc2_weight]. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"FxOnnxInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":414 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0008", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___18___mlp_fc2_bias[name=p_getattr_l__self___trunk_blocks___18___mlp_fc2_bias]. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature FxOnnxInterpreter.run_node\n- self: \n- node: fx.Node(p_getattr_l__self___trunk_blocks___18___mlp_fc2_bias)[placeholder]:Tensor(f32[1024])\n- fx_graph_module: torch.fx.GraphModule()\n- onnxfunction_dispatcher: \n- op_level_debug: False\n- onnxscript_graph: \n- onnxscript_tracer: \n- fx_name_to_onnxscript_value: Dict[length=231](\np_trunk_pos_embed: `TorchScriptTensor(f32[1, 1024, 1024])`,\np_trunk_attn_pool_latent: `TorchScriptTensor(f32[1, 1, 1024])`,\np_trunk_patch_embed_proj_weight: `TorchScriptTensor(f32[1024, 3, 16, 16])`,\np_trunk_patch_embed_proj_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_weight: `TorchScriptTensor(f32[3072, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_bias: `TorchScriptTensor(f32[3072])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_weight: `TorchScriptTensor(f32[1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_bias: `TorchScriptTensor(f32[1024])`,\n...\n)\n## Return values\n", + "text":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___18___mlp_fc2_bias[name=p_getattr_l__self___trunk_blocks___18___mlp_fc2_bias]. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"FxOnnxInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":414 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0008", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___19___norm1_weight[name=p_getattr_l__self___trunk_blocks___19___norm1_weight]. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature FxOnnxInterpreter.run_node\n- self: \n- node: fx.Node(p_getattr_l__self___trunk_blocks___19___norm1_weight)[placeholder]:Tensor(f32[1024])\n- fx_graph_module: torch.fx.GraphModule()\n- onnxfunction_dispatcher: \n- op_level_debug: False\n- onnxscript_graph: \n- onnxscript_tracer: \n- fx_name_to_onnxscript_value: Dict[length=232](\np_trunk_pos_embed: `TorchScriptTensor(f32[1, 1024, 1024])`,\np_trunk_attn_pool_latent: `TorchScriptTensor(f32[1, 1, 1024])`,\np_trunk_patch_embed_proj_weight: `TorchScriptTensor(f32[1024, 3, 16, 16])`,\np_trunk_patch_embed_proj_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_weight: `TorchScriptTensor(f32[3072, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_bias: `TorchScriptTensor(f32[3072])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_weight: `TorchScriptTensor(f32[1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_bias: `TorchScriptTensor(f32[1024])`,\n...\n)\n## Return values\n", + "text":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___19___norm1_weight[name=p_getattr_l__self___trunk_blocks___19___norm1_weight]. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"FxOnnxInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":414 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0008", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___19___norm1_bias[name=p_getattr_l__self___trunk_blocks___19___norm1_bias]. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature FxOnnxInterpreter.run_node\n- self: \n- node: fx.Node(p_getattr_l__self___trunk_blocks___19___norm1_bias)[placeholder]:Tensor(f32[1024])\n- fx_graph_module: torch.fx.GraphModule()\n- onnxfunction_dispatcher: \n- op_level_debug: False\n- onnxscript_graph: \n- onnxscript_tracer: \n- fx_name_to_onnxscript_value: Dict[length=233](\np_trunk_pos_embed: `TorchScriptTensor(f32[1, 1024, 1024])`,\np_trunk_attn_pool_latent: `TorchScriptTensor(f32[1, 1, 1024])`,\np_trunk_patch_embed_proj_weight: `TorchScriptTensor(f32[1024, 3, 16, 16])`,\np_trunk_patch_embed_proj_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_weight: `TorchScriptTensor(f32[3072, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_bias: `TorchScriptTensor(f32[3072])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_weight: `TorchScriptTensor(f32[1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_bias: `TorchScriptTensor(f32[1024])`,\n...\n)\n## Return values\n", + "text":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___19___norm1_bias[name=p_getattr_l__self___trunk_blocks___19___norm1_bias]. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"FxOnnxInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":414 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0008", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___19___attn_qkv_weight[name=p_getattr_l__self___trunk_blocks___19___attn_qkv_weight]. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature FxOnnxInterpreter.run_node\n- self: \n- node: fx.Node(p_getattr_l__self___trunk_blocks___19___attn_qkv_weight)[placeholder]:Tensor(f32[3072, 1024])\n- fx_graph_module: torch.fx.GraphModule()\n- onnxfunction_dispatcher: \n- op_level_debug: False\n- onnxscript_graph: \n- onnxscript_tracer: \n- fx_name_to_onnxscript_value: Dict[length=234](\np_trunk_pos_embed: `TorchScriptTensor(f32[1, 1024, 1024])`,\np_trunk_attn_pool_latent: `TorchScriptTensor(f32[1, 1, 1024])`,\np_trunk_patch_embed_proj_weight: `TorchScriptTensor(f32[1024, 3, 16, 16])`,\np_trunk_patch_embed_proj_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_weight: `TorchScriptTensor(f32[3072, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_bias: `TorchScriptTensor(f32[3072])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_weight: `TorchScriptTensor(f32[1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_bias: `TorchScriptTensor(f32[1024])`,\n...\n)\n## Return values\n", + "text":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___19___attn_qkv_weight[name=p_getattr_l__self___trunk_blocks___19___attn_qkv_weight]. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"FxOnnxInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":414 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0008", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___19___attn_qkv_bias[name=p_getattr_l__self___trunk_blocks___19___attn_qkv_bias]. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature FxOnnxInterpreter.run_node\n- self: \n- node: fx.Node(p_getattr_l__self___trunk_blocks___19___attn_qkv_bias)[placeholder]:Tensor(f32[3072])\n- fx_graph_module: torch.fx.GraphModule()\n- onnxfunction_dispatcher: \n- op_level_debug: False\n- onnxscript_graph: \n- onnxscript_tracer: \n- fx_name_to_onnxscript_value: Dict[length=235](\np_trunk_pos_embed: `TorchScriptTensor(f32[1, 1024, 1024])`,\np_trunk_attn_pool_latent: `TorchScriptTensor(f32[1, 1, 1024])`,\np_trunk_patch_embed_proj_weight: `TorchScriptTensor(f32[1024, 3, 16, 16])`,\np_trunk_patch_embed_proj_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_weight: `TorchScriptTensor(f32[3072, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_bias: `TorchScriptTensor(f32[3072])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_weight: `TorchScriptTensor(f32[1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_bias: `TorchScriptTensor(f32[1024])`,\n...\n)\n## Return values\n", + "text":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___19___attn_qkv_bias[name=p_getattr_l__self___trunk_blocks___19___attn_qkv_bias]. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"FxOnnxInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":414 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0008", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___19___attn_proj_weight[name=p_getattr_l__self___trunk_blocks___19___attn_proj_weight]. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature FxOnnxInterpreter.run_node\n- self: \n- node: fx.Node(p_getattr_l__self___trunk_blocks___19___attn_proj_weight)[placeholder]:Tensor(f32[1024, 1024])\n- fx_graph_module: torch.fx.GraphModule()\n- onnxfunction_dispatcher: \n- op_level_debug: False\n- onnxscript_graph: \n- onnxscript_tracer: \n- fx_name_to_onnxscript_value: Dict[length=236](\np_trunk_pos_embed: `TorchScriptTensor(f32[1, 1024, 1024])`,\np_trunk_attn_pool_latent: `TorchScriptTensor(f32[1, 1, 1024])`,\np_trunk_patch_embed_proj_weight: `TorchScriptTensor(f32[1024, 3, 16, 16])`,\np_trunk_patch_embed_proj_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_weight: `TorchScriptTensor(f32[3072, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_bias: `TorchScriptTensor(f32[3072])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_weight: `TorchScriptTensor(f32[1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_bias: `TorchScriptTensor(f32[1024])`,\n...\n)\n## Return values\n", + "text":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___19___attn_proj_weight[name=p_getattr_l__self___trunk_blocks___19___attn_proj_weight]. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"FxOnnxInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":414 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0008", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___19___attn_proj_bias[name=p_getattr_l__self___trunk_blocks___19___attn_proj_bias]. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature FxOnnxInterpreter.run_node\n- self: \n- node: fx.Node(p_getattr_l__self___trunk_blocks___19___attn_proj_bias)[placeholder]:Tensor(f32[1024])\n- fx_graph_module: torch.fx.GraphModule()\n- onnxfunction_dispatcher: \n- op_level_debug: False\n- onnxscript_graph: \n- onnxscript_tracer: \n- fx_name_to_onnxscript_value: Dict[length=237](\np_trunk_pos_embed: `TorchScriptTensor(f32[1, 1024, 1024])`,\np_trunk_attn_pool_latent: `TorchScriptTensor(f32[1, 1, 1024])`,\np_trunk_patch_embed_proj_weight: `TorchScriptTensor(f32[1024, 3, 16, 16])`,\np_trunk_patch_embed_proj_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_weight: `TorchScriptTensor(f32[3072, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_bias: `TorchScriptTensor(f32[3072])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_weight: `TorchScriptTensor(f32[1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_bias: `TorchScriptTensor(f32[1024])`,\n...\n)\n## Return values\n", + "text":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___19___attn_proj_bias[name=p_getattr_l__self___trunk_blocks___19___attn_proj_bias]. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"FxOnnxInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":414 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0008", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___19___norm2_weight[name=p_getattr_l__self___trunk_blocks___19___norm2_weight]. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature FxOnnxInterpreter.run_node\n- self: \n- node: fx.Node(p_getattr_l__self___trunk_blocks___19___norm2_weight)[placeholder]:Tensor(f32[1024])\n- fx_graph_module: torch.fx.GraphModule()\n- onnxfunction_dispatcher: \n- op_level_debug: False\n- onnxscript_graph: \n- onnxscript_tracer: \n- fx_name_to_onnxscript_value: Dict[length=238](\np_trunk_pos_embed: `TorchScriptTensor(f32[1, 1024, 1024])`,\np_trunk_attn_pool_latent: `TorchScriptTensor(f32[1, 1, 1024])`,\np_trunk_patch_embed_proj_weight: `TorchScriptTensor(f32[1024, 3, 16, 16])`,\np_trunk_patch_embed_proj_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_weight: `TorchScriptTensor(f32[3072, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_bias: `TorchScriptTensor(f32[3072])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_weight: `TorchScriptTensor(f32[1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_bias: `TorchScriptTensor(f32[1024])`,\n...\n)\n## Return values\n", + "text":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___19___norm2_weight[name=p_getattr_l__self___trunk_blocks___19___norm2_weight]. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"FxOnnxInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":414 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0008", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___19___norm2_bias[name=p_getattr_l__self___trunk_blocks___19___norm2_bias]. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature FxOnnxInterpreter.run_node\n- self: \n- node: fx.Node(p_getattr_l__self___trunk_blocks___19___norm2_bias)[placeholder]:Tensor(f32[1024])\n- fx_graph_module: torch.fx.GraphModule()\n- onnxfunction_dispatcher: \n- op_level_debug: False\n- onnxscript_graph: \n- onnxscript_tracer: \n- fx_name_to_onnxscript_value: Dict[length=239](\np_trunk_pos_embed: `TorchScriptTensor(f32[1, 1024, 1024])`,\np_trunk_attn_pool_latent: `TorchScriptTensor(f32[1, 1, 1024])`,\np_trunk_patch_embed_proj_weight: `TorchScriptTensor(f32[1024, 3, 16, 16])`,\np_trunk_patch_embed_proj_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_weight: `TorchScriptTensor(f32[3072, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_bias: `TorchScriptTensor(f32[3072])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_weight: `TorchScriptTensor(f32[1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_bias: `TorchScriptTensor(f32[1024])`,\n...\n)\n## Return values\n", + "text":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___19___norm2_bias[name=p_getattr_l__self___trunk_blocks___19___norm2_bias]. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"FxOnnxInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":414 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0008", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___19___mlp_fc1_weight[name=p_getattr_l__self___trunk_blocks___19___mlp_fc1_weight]. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature FxOnnxInterpreter.run_node\n- self: \n- node: fx.Node(p_getattr_l__self___trunk_blocks___19___mlp_fc1_weight)[placeholder]:Tensor(f32[4096, 1024])\n- fx_graph_module: torch.fx.GraphModule()\n- onnxfunction_dispatcher: \n- op_level_debug: False\n- onnxscript_graph: \n- onnxscript_tracer: \n- fx_name_to_onnxscript_value: Dict[length=240](\np_trunk_pos_embed: `TorchScriptTensor(f32[1, 1024, 1024])`,\np_trunk_attn_pool_latent: `TorchScriptTensor(f32[1, 1, 1024])`,\np_trunk_patch_embed_proj_weight: `TorchScriptTensor(f32[1024, 3, 16, 16])`,\np_trunk_patch_embed_proj_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_weight: `TorchScriptTensor(f32[3072, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_bias: `TorchScriptTensor(f32[3072])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_weight: `TorchScriptTensor(f32[1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_bias: `TorchScriptTensor(f32[1024])`,\n...\n)\n## Return values\n", + "text":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___19___mlp_fc1_weight[name=p_getattr_l__self___trunk_blocks___19___mlp_fc1_weight]. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"FxOnnxInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":414 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0008", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___19___mlp_fc1_bias[name=p_getattr_l__self___trunk_blocks___19___mlp_fc1_bias]. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature FxOnnxInterpreter.run_node\n- self: \n- node: fx.Node(p_getattr_l__self___trunk_blocks___19___mlp_fc1_bias)[placeholder]:Tensor(f32[4096])\n- fx_graph_module: torch.fx.GraphModule()\n- onnxfunction_dispatcher: \n- op_level_debug: False\n- onnxscript_graph: \n- onnxscript_tracer: \n- fx_name_to_onnxscript_value: Dict[length=241](\np_trunk_pos_embed: `TorchScriptTensor(f32[1, 1024, 1024])`,\np_trunk_attn_pool_latent: `TorchScriptTensor(f32[1, 1, 1024])`,\np_trunk_patch_embed_proj_weight: `TorchScriptTensor(f32[1024, 3, 16, 16])`,\np_trunk_patch_embed_proj_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_weight: `TorchScriptTensor(f32[3072, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_bias: `TorchScriptTensor(f32[3072])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_weight: `TorchScriptTensor(f32[1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_bias: `TorchScriptTensor(f32[1024])`,\n...\n)\n## Return values\n", + "text":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___19___mlp_fc1_bias[name=p_getattr_l__self___trunk_blocks___19___mlp_fc1_bias]. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"FxOnnxInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":414 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0008", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___19___mlp_fc2_weight[name=p_getattr_l__self___trunk_blocks___19___mlp_fc2_weight]. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature FxOnnxInterpreter.run_node\n- self: \n- node: fx.Node(p_getattr_l__self___trunk_blocks___19___mlp_fc2_weight)[placeholder]:Tensor(f32[1024, 4096])\n- fx_graph_module: torch.fx.GraphModule()\n- onnxfunction_dispatcher: \n- op_level_debug: False\n- onnxscript_graph: \n- onnxscript_tracer: \n- fx_name_to_onnxscript_value: Dict[length=242](\np_trunk_pos_embed: `TorchScriptTensor(f32[1, 1024, 1024])`,\np_trunk_attn_pool_latent: `TorchScriptTensor(f32[1, 1, 1024])`,\np_trunk_patch_embed_proj_weight: `TorchScriptTensor(f32[1024, 3, 16, 16])`,\np_trunk_patch_embed_proj_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_weight: `TorchScriptTensor(f32[3072, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_bias: `TorchScriptTensor(f32[3072])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_weight: `TorchScriptTensor(f32[1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_bias: `TorchScriptTensor(f32[1024])`,\n...\n)\n## Return values\n", + "text":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___19___mlp_fc2_weight[name=p_getattr_l__self___trunk_blocks___19___mlp_fc2_weight]. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"FxOnnxInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":414 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0008", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___19___mlp_fc2_bias[name=p_getattr_l__self___trunk_blocks___19___mlp_fc2_bias]. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature FxOnnxInterpreter.run_node\n- self: \n- node: fx.Node(p_getattr_l__self___trunk_blocks___19___mlp_fc2_bias)[placeholder]:Tensor(f32[1024])\n- fx_graph_module: torch.fx.GraphModule()\n- onnxfunction_dispatcher: \n- op_level_debug: False\n- onnxscript_graph: \n- onnxscript_tracer: \n- fx_name_to_onnxscript_value: Dict[length=243](\np_trunk_pos_embed: `TorchScriptTensor(f32[1, 1024, 1024])`,\np_trunk_attn_pool_latent: `TorchScriptTensor(f32[1, 1, 1024])`,\np_trunk_patch_embed_proj_weight: `TorchScriptTensor(f32[1024, 3, 16, 16])`,\np_trunk_patch_embed_proj_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_weight: `TorchScriptTensor(f32[3072, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_bias: `TorchScriptTensor(f32[3072])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_weight: `TorchScriptTensor(f32[1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_bias: `TorchScriptTensor(f32[1024])`,\n...\n)\n## Return values\n", + "text":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___19___mlp_fc2_bias[name=p_getattr_l__self___trunk_blocks___19___mlp_fc2_bias]. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"FxOnnxInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":414 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0008", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___20___norm1_weight[name=p_getattr_l__self___trunk_blocks___20___norm1_weight]. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature FxOnnxInterpreter.run_node\n- self: \n- node: fx.Node(p_getattr_l__self___trunk_blocks___20___norm1_weight)[placeholder]:Tensor(f32[1024])\n- fx_graph_module: torch.fx.GraphModule()\n- onnxfunction_dispatcher: \n- op_level_debug: False\n- onnxscript_graph: \n- onnxscript_tracer: \n- fx_name_to_onnxscript_value: Dict[length=244](\np_trunk_pos_embed: `TorchScriptTensor(f32[1, 1024, 1024])`,\np_trunk_attn_pool_latent: `TorchScriptTensor(f32[1, 1, 1024])`,\np_trunk_patch_embed_proj_weight: `TorchScriptTensor(f32[1024, 3, 16, 16])`,\np_trunk_patch_embed_proj_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_weight: `TorchScriptTensor(f32[3072, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_bias: `TorchScriptTensor(f32[3072])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_weight: `TorchScriptTensor(f32[1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_bias: `TorchScriptTensor(f32[1024])`,\n...\n)\n## Return values\n", + "text":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___20___norm1_weight[name=p_getattr_l__self___trunk_blocks___20___norm1_weight]. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"FxOnnxInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":414 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0008", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___20___norm1_bias[name=p_getattr_l__self___trunk_blocks___20___norm1_bias]. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature FxOnnxInterpreter.run_node\n- self: \n- node: fx.Node(p_getattr_l__self___trunk_blocks___20___norm1_bias)[placeholder]:Tensor(f32[1024])\n- fx_graph_module: torch.fx.GraphModule()\n- onnxfunction_dispatcher: \n- op_level_debug: False\n- onnxscript_graph: \n- onnxscript_tracer: \n- fx_name_to_onnxscript_value: Dict[length=245](\np_trunk_pos_embed: `TorchScriptTensor(f32[1, 1024, 1024])`,\np_trunk_attn_pool_latent: `TorchScriptTensor(f32[1, 1, 1024])`,\np_trunk_patch_embed_proj_weight: `TorchScriptTensor(f32[1024, 3, 16, 16])`,\np_trunk_patch_embed_proj_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_weight: `TorchScriptTensor(f32[3072, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_bias: `TorchScriptTensor(f32[3072])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_weight: `TorchScriptTensor(f32[1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_bias: `TorchScriptTensor(f32[1024])`,\n...\n)\n## Return values\n", + "text":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___20___norm1_bias[name=p_getattr_l__self___trunk_blocks___20___norm1_bias]. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"FxOnnxInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":414 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0008", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___20___attn_qkv_weight[name=p_getattr_l__self___trunk_blocks___20___attn_qkv_weight]. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature FxOnnxInterpreter.run_node\n- self: \n- node: fx.Node(p_getattr_l__self___trunk_blocks___20___attn_qkv_weight)[placeholder]:Tensor(f32[3072, 1024])\n- fx_graph_module: torch.fx.GraphModule()\n- onnxfunction_dispatcher: \n- op_level_debug: False\n- onnxscript_graph: \n- onnxscript_tracer: \n- fx_name_to_onnxscript_value: Dict[length=246](\np_trunk_pos_embed: `TorchScriptTensor(f32[1, 1024, 1024])`,\np_trunk_attn_pool_latent: `TorchScriptTensor(f32[1, 1, 1024])`,\np_trunk_patch_embed_proj_weight: `TorchScriptTensor(f32[1024, 3, 16, 16])`,\np_trunk_patch_embed_proj_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_weight: `TorchScriptTensor(f32[3072, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_bias: `TorchScriptTensor(f32[3072])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_weight: `TorchScriptTensor(f32[1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_bias: `TorchScriptTensor(f32[1024])`,\n...\n)\n## Return values\n", + "text":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___20___attn_qkv_weight[name=p_getattr_l__self___trunk_blocks___20___attn_qkv_weight]. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"FxOnnxInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":414 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0008", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___20___attn_qkv_bias[name=p_getattr_l__self___trunk_blocks___20___attn_qkv_bias]. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature FxOnnxInterpreter.run_node\n- self: \n- node: fx.Node(p_getattr_l__self___trunk_blocks___20___attn_qkv_bias)[placeholder]:Tensor(f32[3072])\n- fx_graph_module: torch.fx.GraphModule()\n- onnxfunction_dispatcher: \n- op_level_debug: False\n- onnxscript_graph: \n- onnxscript_tracer: \n- fx_name_to_onnxscript_value: Dict[length=247](\np_trunk_pos_embed: `TorchScriptTensor(f32[1, 1024, 1024])`,\np_trunk_attn_pool_latent: `TorchScriptTensor(f32[1, 1, 1024])`,\np_trunk_patch_embed_proj_weight: `TorchScriptTensor(f32[1024, 3, 16, 16])`,\np_trunk_patch_embed_proj_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_weight: `TorchScriptTensor(f32[3072, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_bias: `TorchScriptTensor(f32[3072])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_weight: `TorchScriptTensor(f32[1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_bias: `TorchScriptTensor(f32[1024])`,\n...\n)\n## Return values\n", + "text":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___20___attn_qkv_bias[name=p_getattr_l__self___trunk_blocks___20___attn_qkv_bias]. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"FxOnnxInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":414 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0008", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___20___attn_proj_weight[name=p_getattr_l__self___trunk_blocks___20___attn_proj_weight]. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature FxOnnxInterpreter.run_node\n- self: \n- node: fx.Node(p_getattr_l__self___trunk_blocks___20___attn_proj_weight)[placeholder]:Tensor(f32[1024, 1024])\n- fx_graph_module: torch.fx.GraphModule()\n- onnxfunction_dispatcher: \n- op_level_debug: False\n- onnxscript_graph: \n- onnxscript_tracer: \n- fx_name_to_onnxscript_value: Dict[length=248](\np_trunk_pos_embed: `TorchScriptTensor(f32[1, 1024, 1024])`,\np_trunk_attn_pool_latent: `TorchScriptTensor(f32[1, 1, 1024])`,\np_trunk_patch_embed_proj_weight: `TorchScriptTensor(f32[1024, 3, 16, 16])`,\np_trunk_patch_embed_proj_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_weight: `TorchScriptTensor(f32[3072, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_bias: `TorchScriptTensor(f32[3072])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_weight: `TorchScriptTensor(f32[1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_bias: `TorchScriptTensor(f32[1024])`,\n...\n)\n## Return values\n", + "text":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___20___attn_proj_weight[name=p_getattr_l__self___trunk_blocks___20___attn_proj_weight]. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"FxOnnxInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":414 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0008", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___20___attn_proj_bias[name=p_getattr_l__self___trunk_blocks___20___attn_proj_bias]. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature FxOnnxInterpreter.run_node\n- self: \n- node: fx.Node(p_getattr_l__self___trunk_blocks___20___attn_proj_bias)[placeholder]:Tensor(f32[1024])\n- fx_graph_module: torch.fx.GraphModule()\n- onnxfunction_dispatcher: \n- op_level_debug: False\n- onnxscript_graph: \n- onnxscript_tracer: \n- fx_name_to_onnxscript_value: Dict[length=249](\np_trunk_pos_embed: `TorchScriptTensor(f32[1, 1024, 1024])`,\np_trunk_attn_pool_latent: `TorchScriptTensor(f32[1, 1, 1024])`,\np_trunk_patch_embed_proj_weight: `TorchScriptTensor(f32[1024, 3, 16, 16])`,\np_trunk_patch_embed_proj_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_weight: `TorchScriptTensor(f32[3072, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_bias: `TorchScriptTensor(f32[3072])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_weight: `TorchScriptTensor(f32[1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_bias: `TorchScriptTensor(f32[1024])`,\n...\n)\n## Return values\n", + "text":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___20___attn_proj_bias[name=p_getattr_l__self___trunk_blocks___20___attn_proj_bias]. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"FxOnnxInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":414 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0008", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___20___norm2_weight[name=p_getattr_l__self___trunk_blocks___20___norm2_weight]. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature FxOnnxInterpreter.run_node\n- self: \n- node: fx.Node(p_getattr_l__self___trunk_blocks___20___norm2_weight)[placeholder]:Tensor(f32[1024])\n- fx_graph_module: torch.fx.GraphModule()\n- onnxfunction_dispatcher: \n- op_level_debug: False\n- onnxscript_graph: \n- onnxscript_tracer: \n- fx_name_to_onnxscript_value: Dict[length=250](\np_trunk_pos_embed: `TorchScriptTensor(f32[1, 1024, 1024])`,\np_trunk_attn_pool_latent: `TorchScriptTensor(f32[1, 1, 1024])`,\np_trunk_patch_embed_proj_weight: `TorchScriptTensor(f32[1024, 3, 16, 16])`,\np_trunk_patch_embed_proj_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_weight: `TorchScriptTensor(f32[3072, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_bias: `TorchScriptTensor(f32[3072])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_weight: `TorchScriptTensor(f32[1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_bias: `TorchScriptTensor(f32[1024])`,\n...\n)\n## Return values\n", + "text":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___20___norm2_weight[name=p_getattr_l__self___trunk_blocks___20___norm2_weight]. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"FxOnnxInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":414 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0008", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___20___norm2_bias[name=p_getattr_l__self___trunk_blocks___20___norm2_bias]. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature FxOnnxInterpreter.run_node\n- self: \n- node: fx.Node(p_getattr_l__self___trunk_blocks___20___norm2_bias)[placeholder]:Tensor(f32[1024])\n- fx_graph_module: torch.fx.GraphModule()\n- onnxfunction_dispatcher: \n- op_level_debug: False\n- onnxscript_graph: \n- onnxscript_tracer: \n- fx_name_to_onnxscript_value: Dict[length=251](\np_trunk_pos_embed: `TorchScriptTensor(f32[1, 1024, 1024])`,\np_trunk_attn_pool_latent: `TorchScriptTensor(f32[1, 1, 1024])`,\np_trunk_patch_embed_proj_weight: `TorchScriptTensor(f32[1024, 3, 16, 16])`,\np_trunk_patch_embed_proj_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_weight: `TorchScriptTensor(f32[3072, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_bias: `TorchScriptTensor(f32[3072])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_weight: `TorchScriptTensor(f32[1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_bias: `TorchScriptTensor(f32[1024])`,\n...\n)\n## Return values\n", + "text":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___20___norm2_bias[name=p_getattr_l__self___trunk_blocks___20___norm2_bias]. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"FxOnnxInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":414 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0008", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___20___mlp_fc1_weight[name=p_getattr_l__self___trunk_blocks___20___mlp_fc1_weight]. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature FxOnnxInterpreter.run_node\n- self: \n- node: fx.Node(p_getattr_l__self___trunk_blocks___20___mlp_fc1_weight)[placeholder]:Tensor(f32[4096, 1024])\n- fx_graph_module: torch.fx.GraphModule()\n- onnxfunction_dispatcher: \n- op_level_debug: False\n- onnxscript_graph: \n- onnxscript_tracer: \n- fx_name_to_onnxscript_value: Dict[length=252](\np_trunk_pos_embed: `TorchScriptTensor(f32[1, 1024, 1024])`,\np_trunk_attn_pool_latent: `TorchScriptTensor(f32[1, 1, 1024])`,\np_trunk_patch_embed_proj_weight: `TorchScriptTensor(f32[1024, 3, 16, 16])`,\np_trunk_patch_embed_proj_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_weight: `TorchScriptTensor(f32[3072, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_bias: `TorchScriptTensor(f32[3072])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_weight: `TorchScriptTensor(f32[1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_bias: `TorchScriptTensor(f32[1024])`,\n...\n)\n## Return values\n", + "text":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___20___mlp_fc1_weight[name=p_getattr_l__self___trunk_blocks___20___mlp_fc1_weight]. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"FxOnnxInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":414 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0008", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___20___mlp_fc1_bias[name=p_getattr_l__self___trunk_blocks___20___mlp_fc1_bias]. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature FxOnnxInterpreter.run_node\n- self: \n- node: fx.Node(p_getattr_l__self___trunk_blocks___20___mlp_fc1_bias)[placeholder]:Tensor(f32[4096])\n- fx_graph_module: torch.fx.GraphModule()\n- onnxfunction_dispatcher: \n- op_level_debug: False\n- onnxscript_graph: \n- onnxscript_tracer: \n- fx_name_to_onnxscript_value: Dict[length=253](\np_trunk_pos_embed: `TorchScriptTensor(f32[1, 1024, 1024])`,\np_trunk_attn_pool_latent: `TorchScriptTensor(f32[1, 1, 1024])`,\np_trunk_patch_embed_proj_weight: `TorchScriptTensor(f32[1024, 3, 16, 16])`,\np_trunk_patch_embed_proj_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_weight: `TorchScriptTensor(f32[3072, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_bias: `TorchScriptTensor(f32[3072])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_weight: `TorchScriptTensor(f32[1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_bias: `TorchScriptTensor(f32[1024])`,\n...\n)\n## Return values\n", + "text":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___20___mlp_fc1_bias[name=p_getattr_l__self___trunk_blocks___20___mlp_fc1_bias]. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"FxOnnxInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":414 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0008", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___20___mlp_fc2_weight[name=p_getattr_l__self___trunk_blocks___20___mlp_fc2_weight]. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature FxOnnxInterpreter.run_node\n- self: \n- node: fx.Node(p_getattr_l__self___trunk_blocks___20___mlp_fc2_weight)[placeholder]:Tensor(f32[1024, 4096])\n- fx_graph_module: torch.fx.GraphModule()\n- onnxfunction_dispatcher: \n- op_level_debug: False\n- onnxscript_graph: \n- onnxscript_tracer: \n- fx_name_to_onnxscript_value: Dict[length=254](\np_trunk_pos_embed: `TorchScriptTensor(f32[1, 1024, 1024])`,\np_trunk_attn_pool_latent: `TorchScriptTensor(f32[1, 1, 1024])`,\np_trunk_patch_embed_proj_weight: `TorchScriptTensor(f32[1024, 3, 16, 16])`,\np_trunk_patch_embed_proj_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_weight: `TorchScriptTensor(f32[3072, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_bias: `TorchScriptTensor(f32[3072])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_weight: `TorchScriptTensor(f32[1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_bias: `TorchScriptTensor(f32[1024])`,\n...\n)\n## Return values\n", + "text":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___20___mlp_fc2_weight[name=p_getattr_l__self___trunk_blocks___20___mlp_fc2_weight]. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"FxOnnxInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":414 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0008", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___20___mlp_fc2_bias[name=p_getattr_l__self___trunk_blocks___20___mlp_fc2_bias]. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature FxOnnxInterpreter.run_node\n- self: \n- node: fx.Node(p_getattr_l__self___trunk_blocks___20___mlp_fc2_bias)[placeholder]:Tensor(f32[1024])\n- fx_graph_module: torch.fx.GraphModule()\n- onnxfunction_dispatcher: \n- op_level_debug: False\n- onnxscript_graph: \n- onnxscript_tracer: \n- fx_name_to_onnxscript_value: Dict[length=255](\np_trunk_pos_embed: `TorchScriptTensor(f32[1, 1024, 1024])`,\np_trunk_attn_pool_latent: `TorchScriptTensor(f32[1, 1, 1024])`,\np_trunk_patch_embed_proj_weight: `TorchScriptTensor(f32[1024, 3, 16, 16])`,\np_trunk_patch_embed_proj_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_weight: `TorchScriptTensor(f32[3072, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_bias: `TorchScriptTensor(f32[3072])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_weight: `TorchScriptTensor(f32[1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_bias: `TorchScriptTensor(f32[1024])`,\n...\n)\n## Return values\n", + "text":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___20___mlp_fc2_bias[name=p_getattr_l__self___trunk_blocks___20___mlp_fc2_bias]. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"FxOnnxInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":414 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0008", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___21___norm1_weight[name=p_getattr_l__self___trunk_blocks___21___norm1_weight]. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature FxOnnxInterpreter.run_node\n- self: \n- node: fx.Node(p_getattr_l__self___trunk_blocks___21___norm1_weight)[placeholder]:Tensor(f32[1024])\n- fx_graph_module: torch.fx.GraphModule()\n- onnxfunction_dispatcher: \n- op_level_debug: False\n- onnxscript_graph: \n- onnxscript_tracer: \n- fx_name_to_onnxscript_value: Dict[length=256](\np_trunk_pos_embed: `TorchScriptTensor(f32[1, 1024, 1024])`,\np_trunk_attn_pool_latent: `TorchScriptTensor(f32[1, 1, 1024])`,\np_trunk_patch_embed_proj_weight: `TorchScriptTensor(f32[1024, 3, 16, 16])`,\np_trunk_patch_embed_proj_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_weight: `TorchScriptTensor(f32[3072, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_bias: `TorchScriptTensor(f32[3072])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_weight: `TorchScriptTensor(f32[1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_bias: `TorchScriptTensor(f32[1024])`,\n...\n)\n## Return values\n", + "text":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___21___norm1_weight[name=p_getattr_l__self___trunk_blocks___21___norm1_weight]. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"FxOnnxInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":414 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0008", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___21___norm1_bias[name=p_getattr_l__self___trunk_blocks___21___norm1_bias]. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature FxOnnxInterpreter.run_node\n- self: \n- node: fx.Node(p_getattr_l__self___trunk_blocks___21___norm1_bias)[placeholder]:Tensor(f32[1024])\n- fx_graph_module: torch.fx.GraphModule()\n- onnxfunction_dispatcher: \n- op_level_debug: False\n- onnxscript_graph: \n- onnxscript_tracer: \n- fx_name_to_onnxscript_value: Dict[length=257](\np_trunk_pos_embed: `TorchScriptTensor(f32[1, 1024, 1024])`,\np_trunk_attn_pool_latent: `TorchScriptTensor(f32[1, 1, 1024])`,\np_trunk_patch_embed_proj_weight: `TorchScriptTensor(f32[1024, 3, 16, 16])`,\np_trunk_patch_embed_proj_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_weight: `TorchScriptTensor(f32[3072, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_bias: `TorchScriptTensor(f32[3072])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_weight: `TorchScriptTensor(f32[1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_bias: `TorchScriptTensor(f32[1024])`,\n...\n)\n## Return values\n", + "text":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___21___norm1_bias[name=p_getattr_l__self___trunk_blocks___21___norm1_bias]. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"FxOnnxInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":414 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0008", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___21___attn_qkv_weight[name=p_getattr_l__self___trunk_blocks___21___attn_qkv_weight]. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature FxOnnxInterpreter.run_node\n- self: \n- node: fx.Node(p_getattr_l__self___trunk_blocks___21___attn_qkv_weight)[placeholder]:Tensor(f32[3072, 1024])\n- fx_graph_module: torch.fx.GraphModule()\n- onnxfunction_dispatcher: \n- op_level_debug: False\n- onnxscript_graph: \n- onnxscript_tracer: \n- fx_name_to_onnxscript_value: Dict[length=258](\np_trunk_pos_embed: `TorchScriptTensor(f32[1, 1024, 1024])`,\np_trunk_attn_pool_latent: `TorchScriptTensor(f32[1, 1, 1024])`,\np_trunk_patch_embed_proj_weight: `TorchScriptTensor(f32[1024, 3, 16, 16])`,\np_trunk_patch_embed_proj_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_weight: `TorchScriptTensor(f32[3072, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_bias: `TorchScriptTensor(f32[3072])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_weight: `TorchScriptTensor(f32[1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_bias: `TorchScriptTensor(f32[1024])`,\n...\n)\n## Return values\n", + "text":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___21___attn_qkv_weight[name=p_getattr_l__self___trunk_blocks___21___attn_qkv_weight]. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"FxOnnxInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":414 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0008", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___21___attn_qkv_bias[name=p_getattr_l__self___trunk_blocks___21___attn_qkv_bias]. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature FxOnnxInterpreter.run_node\n- self: \n- node: fx.Node(p_getattr_l__self___trunk_blocks___21___attn_qkv_bias)[placeholder]:Tensor(f32[3072])\n- fx_graph_module: torch.fx.GraphModule()\n- onnxfunction_dispatcher: \n- op_level_debug: False\n- onnxscript_graph: \n- onnxscript_tracer: \n- fx_name_to_onnxscript_value: Dict[length=259](\np_trunk_pos_embed: `TorchScriptTensor(f32[1, 1024, 1024])`,\np_trunk_attn_pool_latent: `TorchScriptTensor(f32[1, 1, 1024])`,\np_trunk_patch_embed_proj_weight: `TorchScriptTensor(f32[1024, 3, 16, 16])`,\np_trunk_patch_embed_proj_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_weight: `TorchScriptTensor(f32[3072, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_bias: `TorchScriptTensor(f32[3072])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_weight: `TorchScriptTensor(f32[1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_bias: `TorchScriptTensor(f32[1024])`,\n...\n)\n## Return values\n", + "text":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___21___attn_qkv_bias[name=p_getattr_l__self___trunk_blocks___21___attn_qkv_bias]. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"FxOnnxInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":414 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0008", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___21___attn_proj_weight[name=p_getattr_l__self___trunk_blocks___21___attn_proj_weight]. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature FxOnnxInterpreter.run_node\n- self: \n- node: fx.Node(p_getattr_l__self___trunk_blocks___21___attn_proj_weight)[placeholder]:Tensor(f32[1024, 1024])\n- fx_graph_module: torch.fx.GraphModule()\n- onnxfunction_dispatcher: \n- op_level_debug: False\n- onnxscript_graph: \n- onnxscript_tracer: \n- fx_name_to_onnxscript_value: Dict[length=260](\np_trunk_pos_embed: `TorchScriptTensor(f32[1, 1024, 1024])`,\np_trunk_attn_pool_latent: `TorchScriptTensor(f32[1, 1, 1024])`,\np_trunk_patch_embed_proj_weight: `TorchScriptTensor(f32[1024, 3, 16, 16])`,\np_trunk_patch_embed_proj_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_weight: `TorchScriptTensor(f32[3072, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_bias: `TorchScriptTensor(f32[3072])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_weight: `TorchScriptTensor(f32[1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_bias: `TorchScriptTensor(f32[1024])`,\n...\n)\n## Return values\n", + "text":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___21___attn_proj_weight[name=p_getattr_l__self___trunk_blocks___21___attn_proj_weight]. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"FxOnnxInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":414 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0008", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___21___attn_proj_bias[name=p_getattr_l__self___trunk_blocks___21___attn_proj_bias]. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature FxOnnxInterpreter.run_node\n- self: \n- node: fx.Node(p_getattr_l__self___trunk_blocks___21___attn_proj_bias)[placeholder]:Tensor(f32[1024])\n- fx_graph_module: torch.fx.GraphModule()\n- onnxfunction_dispatcher: \n- op_level_debug: False\n- onnxscript_graph: \n- onnxscript_tracer: \n- fx_name_to_onnxscript_value: Dict[length=261](\np_trunk_pos_embed: `TorchScriptTensor(f32[1, 1024, 1024])`,\np_trunk_attn_pool_latent: `TorchScriptTensor(f32[1, 1, 1024])`,\np_trunk_patch_embed_proj_weight: `TorchScriptTensor(f32[1024, 3, 16, 16])`,\np_trunk_patch_embed_proj_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_weight: `TorchScriptTensor(f32[3072, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_bias: `TorchScriptTensor(f32[3072])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_weight: `TorchScriptTensor(f32[1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_bias: `TorchScriptTensor(f32[1024])`,\n...\n)\n## Return values\n", + "text":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___21___attn_proj_bias[name=p_getattr_l__self___trunk_blocks___21___attn_proj_bias]. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"FxOnnxInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":414 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0008", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___21___norm2_weight[name=p_getattr_l__self___trunk_blocks___21___norm2_weight]. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature FxOnnxInterpreter.run_node\n- self: \n- node: fx.Node(p_getattr_l__self___trunk_blocks___21___norm2_weight)[placeholder]:Tensor(f32[1024])\n- fx_graph_module: torch.fx.GraphModule()\n- onnxfunction_dispatcher: \n- op_level_debug: False\n- onnxscript_graph: \n- onnxscript_tracer: \n- fx_name_to_onnxscript_value: Dict[length=262](\np_trunk_pos_embed: `TorchScriptTensor(f32[1, 1024, 1024])`,\np_trunk_attn_pool_latent: `TorchScriptTensor(f32[1, 1, 1024])`,\np_trunk_patch_embed_proj_weight: `TorchScriptTensor(f32[1024, 3, 16, 16])`,\np_trunk_patch_embed_proj_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_weight: `TorchScriptTensor(f32[3072, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_bias: `TorchScriptTensor(f32[3072])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_weight: `TorchScriptTensor(f32[1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_bias: `TorchScriptTensor(f32[1024])`,\n...\n)\n## Return values\n", + "text":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___21___norm2_weight[name=p_getattr_l__self___trunk_blocks___21___norm2_weight]. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"FxOnnxInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":414 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0008", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___21___norm2_bias[name=p_getattr_l__self___trunk_blocks___21___norm2_bias]. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature FxOnnxInterpreter.run_node\n- self: \n- node: fx.Node(p_getattr_l__self___trunk_blocks___21___norm2_bias)[placeholder]:Tensor(f32[1024])\n- fx_graph_module: torch.fx.GraphModule()\n- onnxfunction_dispatcher: \n- op_level_debug: False\n- onnxscript_graph: \n- onnxscript_tracer: \n- fx_name_to_onnxscript_value: Dict[length=263](\np_trunk_pos_embed: `TorchScriptTensor(f32[1, 1024, 1024])`,\np_trunk_attn_pool_latent: `TorchScriptTensor(f32[1, 1, 1024])`,\np_trunk_patch_embed_proj_weight: `TorchScriptTensor(f32[1024, 3, 16, 16])`,\np_trunk_patch_embed_proj_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_weight: `TorchScriptTensor(f32[3072, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_bias: `TorchScriptTensor(f32[3072])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_weight: `TorchScriptTensor(f32[1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_bias: `TorchScriptTensor(f32[1024])`,\n...\n)\n## Return values\n", + "text":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___21___norm2_bias[name=p_getattr_l__self___trunk_blocks___21___norm2_bias]. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"FxOnnxInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":414 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0008", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___21___mlp_fc1_weight[name=p_getattr_l__self___trunk_blocks___21___mlp_fc1_weight]. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature FxOnnxInterpreter.run_node\n- self: \n- node: fx.Node(p_getattr_l__self___trunk_blocks___21___mlp_fc1_weight)[placeholder]:Tensor(f32[4096, 1024])\n- fx_graph_module: torch.fx.GraphModule()\n- onnxfunction_dispatcher: \n- op_level_debug: False\n- onnxscript_graph: \n- onnxscript_tracer: \n- fx_name_to_onnxscript_value: Dict[length=264](\np_trunk_pos_embed: `TorchScriptTensor(f32[1, 1024, 1024])`,\np_trunk_attn_pool_latent: `TorchScriptTensor(f32[1, 1, 1024])`,\np_trunk_patch_embed_proj_weight: `TorchScriptTensor(f32[1024, 3, 16, 16])`,\np_trunk_patch_embed_proj_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_weight: `TorchScriptTensor(f32[3072, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_bias: `TorchScriptTensor(f32[3072])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_weight: `TorchScriptTensor(f32[1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_bias: `TorchScriptTensor(f32[1024])`,\n...\n)\n## Return values\n", + "text":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___21___mlp_fc1_weight[name=p_getattr_l__self___trunk_blocks___21___mlp_fc1_weight]. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"FxOnnxInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":414 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0008", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___21___mlp_fc1_bias[name=p_getattr_l__self___trunk_blocks___21___mlp_fc1_bias]. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature FxOnnxInterpreter.run_node\n- self: \n- node: fx.Node(p_getattr_l__self___trunk_blocks___21___mlp_fc1_bias)[placeholder]:Tensor(f32[4096])\n- fx_graph_module: torch.fx.GraphModule()\n- onnxfunction_dispatcher: \n- op_level_debug: False\n- onnxscript_graph: \n- onnxscript_tracer: \n- fx_name_to_onnxscript_value: Dict[length=265](\np_trunk_pos_embed: `TorchScriptTensor(f32[1, 1024, 1024])`,\np_trunk_attn_pool_latent: `TorchScriptTensor(f32[1, 1, 1024])`,\np_trunk_patch_embed_proj_weight: `TorchScriptTensor(f32[1024, 3, 16, 16])`,\np_trunk_patch_embed_proj_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_weight: `TorchScriptTensor(f32[3072, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_bias: `TorchScriptTensor(f32[3072])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_weight: `TorchScriptTensor(f32[1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_bias: `TorchScriptTensor(f32[1024])`,\n...\n)\n## Return values\n", + "text":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___21___mlp_fc1_bias[name=p_getattr_l__self___trunk_blocks___21___mlp_fc1_bias]. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"FxOnnxInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":414 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0008", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___21___mlp_fc2_weight[name=p_getattr_l__self___trunk_blocks___21___mlp_fc2_weight]. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature FxOnnxInterpreter.run_node\n- self: \n- node: fx.Node(p_getattr_l__self___trunk_blocks___21___mlp_fc2_weight)[placeholder]:Tensor(f32[1024, 4096])\n- fx_graph_module: torch.fx.GraphModule()\n- onnxfunction_dispatcher: \n- op_level_debug: False\n- onnxscript_graph: \n- onnxscript_tracer: \n- fx_name_to_onnxscript_value: Dict[length=266](\np_trunk_pos_embed: `TorchScriptTensor(f32[1, 1024, 1024])`,\np_trunk_attn_pool_latent: `TorchScriptTensor(f32[1, 1, 1024])`,\np_trunk_patch_embed_proj_weight: `TorchScriptTensor(f32[1024, 3, 16, 16])`,\np_trunk_patch_embed_proj_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_weight: `TorchScriptTensor(f32[3072, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_bias: `TorchScriptTensor(f32[3072])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_weight: `TorchScriptTensor(f32[1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_bias: `TorchScriptTensor(f32[1024])`,\n...\n)\n## Return values\n", + "text":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___21___mlp_fc2_weight[name=p_getattr_l__self___trunk_blocks___21___mlp_fc2_weight]. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"FxOnnxInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":414 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0008", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___21___mlp_fc2_bias[name=p_getattr_l__self___trunk_blocks___21___mlp_fc2_bias]. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature FxOnnxInterpreter.run_node\n- self: \n- node: fx.Node(p_getattr_l__self___trunk_blocks___21___mlp_fc2_bias)[placeholder]:Tensor(f32[1024])\n- fx_graph_module: torch.fx.GraphModule()\n- onnxfunction_dispatcher: \n- op_level_debug: False\n- onnxscript_graph: \n- onnxscript_tracer: \n- fx_name_to_onnxscript_value: Dict[length=267](\np_trunk_pos_embed: `TorchScriptTensor(f32[1, 1024, 1024])`,\np_trunk_attn_pool_latent: `TorchScriptTensor(f32[1, 1, 1024])`,\np_trunk_patch_embed_proj_weight: `TorchScriptTensor(f32[1024, 3, 16, 16])`,\np_trunk_patch_embed_proj_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_weight: `TorchScriptTensor(f32[3072, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_bias: `TorchScriptTensor(f32[3072])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_weight: `TorchScriptTensor(f32[1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_bias: `TorchScriptTensor(f32[1024])`,\n...\n)\n## Return values\n", + "text":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___21___mlp_fc2_bias[name=p_getattr_l__self___trunk_blocks___21___mlp_fc2_bias]. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"FxOnnxInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":414 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0008", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___22___norm1_weight[name=p_getattr_l__self___trunk_blocks___22___norm1_weight]. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature FxOnnxInterpreter.run_node\n- self: \n- node: fx.Node(p_getattr_l__self___trunk_blocks___22___norm1_weight)[placeholder]:Tensor(f32[1024])\n- fx_graph_module: torch.fx.GraphModule()\n- onnxfunction_dispatcher: \n- op_level_debug: False\n- onnxscript_graph: \n- onnxscript_tracer: \n- fx_name_to_onnxscript_value: Dict[length=268](\np_trunk_pos_embed: `TorchScriptTensor(f32[1, 1024, 1024])`,\np_trunk_attn_pool_latent: `TorchScriptTensor(f32[1, 1, 1024])`,\np_trunk_patch_embed_proj_weight: `TorchScriptTensor(f32[1024, 3, 16, 16])`,\np_trunk_patch_embed_proj_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_weight: `TorchScriptTensor(f32[3072, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_bias: `TorchScriptTensor(f32[3072])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_weight: `TorchScriptTensor(f32[1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_bias: `TorchScriptTensor(f32[1024])`,\n...\n)\n## Return values\n", + "text":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___22___norm1_weight[name=p_getattr_l__self___trunk_blocks___22___norm1_weight]. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"FxOnnxInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":414 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0008", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___22___norm1_bias[name=p_getattr_l__self___trunk_blocks___22___norm1_bias]. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature FxOnnxInterpreter.run_node\n- self: \n- node: fx.Node(p_getattr_l__self___trunk_blocks___22___norm1_bias)[placeholder]:Tensor(f32[1024])\n- fx_graph_module: torch.fx.GraphModule()\n- onnxfunction_dispatcher: \n- op_level_debug: False\n- onnxscript_graph: \n- onnxscript_tracer: \n- fx_name_to_onnxscript_value: Dict[length=269](\np_trunk_pos_embed: `TorchScriptTensor(f32[1, 1024, 1024])`,\np_trunk_attn_pool_latent: `TorchScriptTensor(f32[1, 1, 1024])`,\np_trunk_patch_embed_proj_weight: `TorchScriptTensor(f32[1024, 3, 16, 16])`,\np_trunk_patch_embed_proj_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_weight: `TorchScriptTensor(f32[3072, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_bias: `TorchScriptTensor(f32[3072])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_weight: `TorchScriptTensor(f32[1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_bias: `TorchScriptTensor(f32[1024])`,\n...\n)\n## Return values\n", + "text":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___22___norm1_bias[name=p_getattr_l__self___trunk_blocks___22___norm1_bias]. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"FxOnnxInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":414 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0008", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___22___attn_qkv_weight[name=p_getattr_l__self___trunk_blocks___22___attn_qkv_weight]. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature FxOnnxInterpreter.run_node\n- self: \n- node: fx.Node(p_getattr_l__self___trunk_blocks___22___attn_qkv_weight)[placeholder]:Tensor(f32[3072, 1024])\n- fx_graph_module: torch.fx.GraphModule()\n- onnxfunction_dispatcher: \n- op_level_debug: False\n- onnxscript_graph: \n- onnxscript_tracer: \n- fx_name_to_onnxscript_value: Dict[length=270](\np_trunk_pos_embed: `TorchScriptTensor(f32[1, 1024, 1024])`,\np_trunk_attn_pool_latent: `TorchScriptTensor(f32[1, 1, 1024])`,\np_trunk_patch_embed_proj_weight: `TorchScriptTensor(f32[1024, 3, 16, 16])`,\np_trunk_patch_embed_proj_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_weight: `TorchScriptTensor(f32[3072, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_bias: `TorchScriptTensor(f32[3072])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_weight: `TorchScriptTensor(f32[1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_bias: `TorchScriptTensor(f32[1024])`,\n...\n)\n## Return values\n", + "text":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___22___attn_qkv_weight[name=p_getattr_l__self___trunk_blocks___22___attn_qkv_weight]. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"FxOnnxInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":414 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0008", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___22___attn_qkv_bias[name=p_getattr_l__self___trunk_blocks___22___attn_qkv_bias]. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature FxOnnxInterpreter.run_node\n- self: \n- node: fx.Node(p_getattr_l__self___trunk_blocks___22___attn_qkv_bias)[placeholder]:Tensor(f32[3072])\n- fx_graph_module: torch.fx.GraphModule()\n- onnxfunction_dispatcher: \n- op_level_debug: False\n- onnxscript_graph: \n- onnxscript_tracer: \n- fx_name_to_onnxscript_value: Dict[length=271](\np_trunk_pos_embed: `TorchScriptTensor(f32[1, 1024, 1024])`,\np_trunk_attn_pool_latent: `TorchScriptTensor(f32[1, 1, 1024])`,\np_trunk_patch_embed_proj_weight: `TorchScriptTensor(f32[1024, 3, 16, 16])`,\np_trunk_patch_embed_proj_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_weight: `TorchScriptTensor(f32[3072, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_bias: `TorchScriptTensor(f32[3072])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_weight: `TorchScriptTensor(f32[1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_bias: `TorchScriptTensor(f32[1024])`,\n...\n)\n## Return values\n", + "text":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___22___attn_qkv_bias[name=p_getattr_l__self___trunk_blocks___22___attn_qkv_bias]. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"FxOnnxInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":414 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0008", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___22___attn_proj_weight[name=p_getattr_l__self___trunk_blocks___22___attn_proj_weight]. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature FxOnnxInterpreter.run_node\n- self: \n- node: fx.Node(p_getattr_l__self___trunk_blocks___22___attn_proj_weight)[placeholder]:Tensor(f32[1024, 1024])\n- fx_graph_module: torch.fx.GraphModule()\n- onnxfunction_dispatcher: \n- op_level_debug: False\n- onnxscript_graph: \n- onnxscript_tracer: \n- fx_name_to_onnxscript_value: Dict[length=272](\np_trunk_pos_embed: `TorchScriptTensor(f32[1, 1024, 1024])`,\np_trunk_attn_pool_latent: `TorchScriptTensor(f32[1, 1, 1024])`,\np_trunk_patch_embed_proj_weight: `TorchScriptTensor(f32[1024, 3, 16, 16])`,\np_trunk_patch_embed_proj_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_weight: `TorchScriptTensor(f32[3072, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_bias: `TorchScriptTensor(f32[3072])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_weight: `TorchScriptTensor(f32[1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_bias: `TorchScriptTensor(f32[1024])`,\n...\n)\n## Return values\n", + "text":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___22___attn_proj_weight[name=p_getattr_l__self___trunk_blocks___22___attn_proj_weight]. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"FxOnnxInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":414 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0008", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___22___attn_proj_bias[name=p_getattr_l__self___trunk_blocks___22___attn_proj_bias]. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature FxOnnxInterpreter.run_node\n- self: \n- node: fx.Node(p_getattr_l__self___trunk_blocks___22___attn_proj_bias)[placeholder]:Tensor(f32[1024])\n- fx_graph_module: torch.fx.GraphModule()\n- onnxfunction_dispatcher: \n- op_level_debug: False\n- onnxscript_graph: \n- onnxscript_tracer: \n- fx_name_to_onnxscript_value: Dict[length=273](\np_trunk_pos_embed: `TorchScriptTensor(f32[1, 1024, 1024])`,\np_trunk_attn_pool_latent: `TorchScriptTensor(f32[1, 1, 1024])`,\np_trunk_patch_embed_proj_weight: `TorchScriptTensor(f32[1024, 3, 16, 16])`,\np_trunk_patch_embed_proj_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_weight: `TorchScriptTensor(f32[3072, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_bias: `TorchScriptTensor(f32[3072])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_weight: `TorchScriptTensor(f32[1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_bias: `TorchScriptTensor(f32[1024])`,\n...\n)\n## Return values\n", + "text":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___22___attn_proj_bias[name=p_getattr_l__self___trunk_blocks___22___attn_proj_bias]. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"FxOnnxInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":414 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0008", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___22___norm2_weight[name=p_getattr_l__self___trunk_blocks___22___norm2_weight]. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature FxOnnxInterpreter.run_node\n- self: \n- node: fx.Node(p_getattr_l__self___trunk_blocks___22___norm2_weight)[placeholder]:Tensor(f32[1024])\n- fx_graph_module: torch.fx.GraphModule()\n- onnxfunction_dispatcher: \n- op_level_debug: False\n- onnxscript_graph: \n- onnxscript_tracer: \n- fx_name_to_onnxscript_value: Dict[length=274](\np_trunk_pos_embed: `TorchScriptTensor(f32[1, 1024, 1024])`,\np_trunk_attn_pool_latent: `TorchScriptTensor(f32[1, 1, 1024])`,\np_trunk_patch_embed_proj_weight: `TorchScriptTensor(f32[1024, 3, 16, 16])`,\np_trunk_patch_embed_proj_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_weight: `TorchScriptTensor(f32[3072, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_bias: `TorchScriptTensor(f32[3072])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_weight: `TorchScriptTensor(f32[1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_bias: `TorchScriptTensor(f32[1024])`,\n...\n)\n## Return values\n", + "text":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___22___norm2_weight[name=p_getattr_l__self___trunk_blocks___22___norm2_weight]. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"FxOnnxInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":414 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0008", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___22___norm2_bias[name=p_getattr_l__self___trunk_blocks___22___norm2_bias]. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature FxOnnxInterpreter.run_node\n- self: \n- node: fx.Node(p_getattr_l__self___trunk_blocks___22___norm2_bias)[placeholder]:Tensor(f32[1024])\n- fx_graph_module: torch.fx.GraphModule()\n- onnxfunction_dispatcher: \n- op_level_debug: False\n- onnxscript_graph: \n- onnxscript_tracer: \n- fx_name_to_onnxscript_value: Dict[length=275](\np_trunk_pos_embed: `TorchScriptTensor(f32[1, 1024, 1024])`,\np_trunk_attn_pool_latent: `TorchScriptTensor(f32[1, 1, 1024])`,\np_trunk_patch_embed_proj_weight: `TorchScriptTensor(f32[1024, 3, 16, 16])`,\np_trunk_patch_embed_proj_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_weight: `TorchScriptTensor(f32[3072, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_bias: `TorchScriptTensor(f32[3072])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_weight: `TorchScriptTensor(f32[1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_bias: `TorchScriptTensor(f32[1024])`,\n...\n)\n## Return values\n", + "text":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___22___norm2_bias[name=p_getattr_l__self___trunk_blocks___22___norm2_bias]. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"FxOnnxInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":414 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0008", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___22___mlp_fc1_weight[name=p_getattr_l__self___trunk_blocks___22___mlp_fc1_weight]. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature FxOnnxInterpreter.run_node\n- self: \n- node: fx.Node(p_getattr_l__self___trunk_blocks___22___mlp_fc1_weight)[placeholder]:Tensor(f32[4096, 1024])\n- fx_graph_module: torch.fx.GraphModule()\n- onnxfunction_dispatcher: \n- op_level_debug: False\n- onnxscript_graph: \n- onnxscript_tracer: \n- fx_name_to_onnxscript_value: Dict[length=276](\np_trunk_pos_embed: `TorchScriptTensor(f32[1, 1024, 1024])`,\np_trunk_attn_pool_latent: `TorchScriptTensor(f32[1, 1, 1024])`,\np_trunk_patch_embed_proj_weight: `TorchScriptTensor(f32[1024, 3, 16, 16])`,\np_trunk_patch_embed_proj_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_weight: `TorchScriptTensor(f32[3072, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_bias: `TorchScriptTensor(f32[3072])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_weight: `TorchScriptTensor(f32[1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_bias: `TorchScriptTensor(f32[1024])`,\n...\n)\n## Return values\n", + "text":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___22___mlp_fc1_weight[name=p_getattr_l__self___trunk_blocks___22___mlp_fc1_weight]. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"FxOnnxInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":414 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0008", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___22___mlp_fc1_bias[name=p_getattr_l__self___trunk_blocks___22___mlp_fc1_bias]. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature FxOnnxInterpreter.run_node\n- self: \n- node: fx.Node(p_getattr_l__self___trunk_blocks___22___mlp_fc1_bias)[placeholder]:Tensor(f32[4096])\n- fx_graph_module: torch.fx.GraphModule()\n- onnxfunction_dispatcher: \n- op_level_debug: False\n- onnxscript_graph: \n- onnxscript_tracer: \n- fx_name_to_onnxscript_value: Dict[length=277](\np_trunk_pos_embed: `TorchScriptTensor(f32[1, 1024, 1024])`,\np_trunk_attn_pool_latent: `TorchScriptTensor(f32[1, 1, 1024])`,\np_trunk_patch_embed_proj_weight: `TorchScriptTensor(f32[1024, 3, 16, 16])`,\np_trunk_patch_embed_proj_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_weight: `TorchScriptTensor(f32[3072, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_bias: `TorchScriptTensor(f32[3072])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_weight: `TorchScriptTensor(f32[1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_bias: `TorchScriptTensor(f32[1024])`,\n...\n)\n## Return values\n", + "text":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___22___mlp_fc1_bias[name=p_getattr_l__self___trunk_blocks___22___mlp_fc1_bias]. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"FxOnnxInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":414 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0008", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___22___mlp_fc2_weight[name=p_getattr_l__self___trunk_blocks___22___mlp_fc2_weight]. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature FxOnnxInterpreter.run_node\n- self: \n- node: fx.Node(p_getattr_l__self___trunk_blocks___22___mlp_fc2_weight)[placeholder]:Tensor(f32[1024, 4096])\n- fx_graph_module: torch.fx.GraphModule()\n- onnxfunction_dispatcher: \n- op_level_debug: False\n- onnxscript_graph: \n- onnxscript_tracer: \n- fx_name_to_onnxscript_value: Dict[length=278](\np_trunk_pos_embed: `TorchScriptTensor(f32[1, 1024, 1024])`,\np_trunk_attn_pool_latent: `TorchScriptTensor(f32[1, 1, 1024])`,\np_trunk_patch_embed_proj_weight: `TorchScriptTensor(f32[1024, 3, 16, 16])`,\np_trunk_patch_embed_proj_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_weight: `TorchScriptTensor(f32[3072, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_bias: `TorchScriptTensor(f32[3072])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_weight: `TorchScriptTensor(f32[1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_bias: `TorchScriptTensor(f32[1024])`,\n...\n)\n## Return values\n", + "text":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___22___mlp_fc2_weight[name=p_getattr_l__self___trunk_blocks___22___mlp_fc2_weight]. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"FxOnnxInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":414 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0008", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___22___mlp_fc2_bias[name=p_getattr_l__self___trunk_blocks___22___mlp_fc2_bias]. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature FxOnnxInterpreter.run_node\n- self: \n- node: fx.Node(p_getattr_l__self___trunk_blocks___22___mlp_fc2_bias)[placeholder]:Tensor(f32[1024])\n- fx_graph_module: torch.fx.GraphModule()\n- onnxfunction_dispatcher: \n- op_level_debug: False\n- onnxscript_graph: \n- onnxscript_tracer: \n- fx_name_to_onnxscript_value: Dict[length=279](\np_trunk_pos_embed: `TorchScriptTensor(f32[1, 1024, 1024])`,\np_trunk_attn_pool_latent: `TorchScriptTensor(f32[1, 1, 1024])`,\np_trunk_patch_embed_proj_weight: `TorchScriptTensor(f32[1024, 3, 16, 16])`,\np_trunk_patch_embed_proj_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_weight: `TorchScriptTensor(f32[3072, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_bias: `TorchScriptTensor(f32[3072])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_weight: `TorchScriptTensor(f32[1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_bias: `TorchScriptTensor(f32[1024])`,\n...\n)\n## Return values\n", + "text":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___22___mlp_fc2_bias[name=p_getattr_l__self___trunk_blocks___22___mlp_fc2_bias]. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"FxOnnxInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":414 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0008", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___23___norm1_weight[name=p_getattr_l__self___trunk_blocks___23___norm1_weight]. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature FxOnnxInterpreter.run_node\n- self: \n- node: fx.Node(p_getattr_l__self___trunk_blocks___23___norm1_weight)[placeholder]:Tensor(f32[1024])\n- fx_graph_module: torch.fx.GraphModule()\n- onnxfunction_dispatcher: \n- op_level_debug: False\n- onnxscript_graph: \n- onnxscript_tracer: \n- fx_name_to_onnxscript_value: Dict[length=280](\np_trunk_pos_embed: `TorchScriptTensor(f32[1, 1024, 1024])`,\np_trunk_attn_pool_latent: `TorchScriptTensor(f32[1, 1, 1024])`,\np_trunk_patch_embed_proj_weight: `TorchScriptTensor(f32[1024, 3, 16, 16])`,\np_trunk_patch_embed_proj_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_weight: `TorchScriptTensor(f32[3072, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_bias: `TorchScriptTensor(f32[3072])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_weight: `TorchScriptTensor(f32[1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_bias: `TorchScriptTensor(f32[1024])`,\n...\n)\n## Return values\n", + "text":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___23___norm1_weight[name=p_getattr_l__self___trunk_blocks___23___norm1_weight]. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"FxOnnxInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":414 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0008", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___23___norm1_bias[name=p_getattr_l__self___trunk_blocks___23___norm1_bias]. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature FxOnnxInterpreter.run_node\n- self: \n- node: fx.Node(p_getattr_l__self___trunk_blocks___23___norm1_bias)[placeholder]:Tensor(f32[1024])\n- fx_graph_module: torch.fx.GraphModule()\n- onnxfunction_dispatcher: \n- op_level_debug: False\n- onnxscript_graph: \n- onnxscript_tracer: \n- fx_name_to_onnxscript_value: Dict[length=281](\np_trunk_pos_embed: `TorchScriptTensor(f32[1, 1024, 1024])`,\np_trunk_attn_pool_latent: `TorchScriptTensor(f32[1, 1, 1024])`,\np_trunk_patch_embed_proj_weight: `TorchScriptTensor(f32[1024, 3, 16, 16])`,\np_trunk_patch_embed_proj_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_weight: `TorchScriptTensor(f32[3072, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_bias: `TorchScriptTensor(f32[3072])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_weight: `TorchScriptTensor(f32[1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_bias: `TorchScriptTensor(f32[1024])`,\n...\n)\n## Return values\n", + "text":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___23___norm1_bias[name=p_getattr_l__self___trunk_blocks___23___norm1_bias]. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"FxOnnxInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":414 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0008", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___23___attn_qkv_weight[name=p_getattr_l__self___trunk_blocks___23___attn_qkv_weight]. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature FxOnnxInterpreter.run_node\n- self: \n- node: fx.Node(p_getattr_l__self___trunk_blocks___23___attn_qkv_weight)[placeholder]:Tensor(f32[3072, 1024])\n- fx_graph_module: torch.fx.GraphModule()\n- onnxfunction_dispatcher: \n- op_level_debug: False\n- onnxscript_graph: \n- onnxscript_tracer: \n- fx_name_to_onnxscript_value: Dict[length=282](\np_trunk_pos_embed: `TorchScriptTensor(f32[1, 1024, 1024])`,\np_trunk_attn_pool_latent: `TorchScriptTensor(f32[1, 1, 1024])`,\np_trunk_patch_embed_proj_weight: `TorchScriptTensor(f32[1024, 3, 16, 16])`,\np_trunk_patch_embed_proj_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_weight: `TorchScriptTensor(f32[3072, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_bias: `TorchScriptTensor(f32[3072])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_weight: `TorchScriptTensor(f32[1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_bias: `TorchScriptTensor(f32[1024])`,\n...\n)\n## Return values\n", + "text":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___23___attn_qkv_weight[name=p_getattr_l__self___trunk_blocks___23___attn_qkv_weight]. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"FxOnnxInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":414 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0008", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___23___attn_qkv_bias[name=p_getattr_l__self___trunk_blocks___23___attn_qkv_bias]. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature FxOnnxInterpreter.run_node\n- self: \n- node: fx.Node(p_getattr_l__self___trunk_blocks___23___attn_qkv_bias)[placeholder]:Tensor(f32[3072])\n- fx_graph_module: torch.fx.GraphModule()\n- onnxfunction_dispatcher: \n- op_level_debug: False\n- onnxscript_graph: \n- onnxscript_tracer: \n- fx_name_to_onnxscript_value: Dict[length=283](\np_trunk_pos_embed: `TorchScriptTensor(f32[1, 1024, 1024])`,\np_trunk_attn_pool_latent: `TorchScriptTensor(f32[1, 1, 1024])`,\np_trunk_patch_embed_proj_weight: `TorchScriptTensor(f32[1024, 3, 16, 16])`,\np_trunk_patch_embed_proj_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_weight: `TorchScriptTensor(f32[3072, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_bias: `TorchScriptTensor(f32[3072])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_weight: `TorchScriptTensor(f32[1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_bias: `TorchScriptTensor(f32[1024])`,\n...\n)\n## Return values\n", + "text":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___23___attn_qkv_bias[name=p_getattr_l__self___trunk_blocks___23___attn_qkv_bias]. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"FxOnnxInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":414 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0008", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___23___attn_proj_weight[name=p_getattr_l__self___trunk_blocks___23___attn_proj_weight]. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature FxOnnxInterpreter.run_node\n- self: \n- node: fx.Node(p_getattr_l__self___trunk_blocks___23___attn_proj_weight)[placeholder]:Tensor(f32[1024, 1024])\n- fx_graph_module: torch.fx.GraphModule()\n- onnxfunction_dispatcher: \n- op_level_debug: False\n- onnxscript_graph: \n- onnxscript_tracer: \n- fx_name_to_onnxscript_value: Dict[length=284](\np_trunk_pos_embed: `TorchScriptTensor(f32[1, 1024, 1024])`,\np_trunk_attn_pool_latent: `TorchScriptTensor(f32[1, 1, 1024])`,\np_trunk_patch_embed_proj_weight: `TorchScriptTensor(f32[1024, 3, 16, 16])`,\np_trunk_patch_embed_proj_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_weight: `TorchScriptTensor(f32[3072, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_bias: `TorchScriptTensor(f32[3072])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_weight: `TorchScriptTensor(f32[1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_bias: `TorchScriptTensor(f32[1024])`,\n...\n)\n## Return values\n", + "text":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___23___attn_proj_weight[name=p_getattr_l__self___trunk_blocks___23___attn_proj_weight]. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"FxOnnxInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":414 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0008", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___23___attn_proj_bias[name=p_getattr_l__self___trunk_blocks___23___attn_proj_bias]. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature FxOnnxInterpreter.run_node\n- self: \n- node: fx.Node(p_getattr_l__self___trunk_blocks___23___attn_proj_bias)[placeholder]:Tensor(f32[1024])\n- fx_graph_module: torch.fx.GraphModule()\n- onnxfunction_dispatcher: \n- op_level_debug: False\n- onnxscript_graph: \n- onnxscript_tracer: \n- fx_name_to_onnxscript_value: Dict[length=285](\np_trunk_pos_embed: `TorchScriptTensor(f32[1, 1024, 1024])`,\np_trunk_attn_pool_latent: `TorchScriptTensor(f32[1, 1, 1024])`,\np_trunk_patch_embed_proj_weight: `TorchScriptTensor(f32[1024, 3, 16, 16])`,\np_trunk_patch_embed_proj_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_weight: `TorchScriptTensor(f32[3072, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_bias: `TorchScriptTensor(f32[3072])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_weight: `TorchScriptTensor(f32[1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_bias: `TorchScriptTensor(f32[1024])`,\n...\n)\n## Return values\n", + "text":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___23___attn_proj_bias[name=p_getattr_l__self___trunk_blocks___23___attn_proj_bias]. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"FxOnnxInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":414 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0008", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___23___norm2_weight[name=p_getattr_l__self___trunk_blocks___23___norm2_weight]. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature FxOnnxInterpreter.run_node\n- self: \n- node: fx.Node(p_getattr_l__self___trunk_blocks___23___norm2_weight)[placeholder]:Tensor(f32[1024])\n- fx_graph_module: torch.fx.GraphModule()\n- onnxfunction_dispatcher: \n- op_level_debug: False\n- onnxscript_graph: \n- onnxscript_tracer: \n- fx_name_to_onnxscript_value: Dict[length=286](\np_trunk_pos_embed: `TorchScriptTensor(f32[1, 1024, 1024])`,\np_trunk_attn_pool_latent: `TorchScriptTensor(f32[1, 1, 1024])`,\np_trunk_patch_embed_proj_weight: `TorchScriptTensor(f32[1024, 3, 16, 16])`,\np_trunk_patch_embed_proj_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_weight: `TorchScriptTensor(f32[3072, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_bias: `TorchScriptTensor(f32[3072])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_weight: `TorchScriptTensor(f32[1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_bias: `TorchScriptTensor(f32[1024])`,\n...\n)\n## Return values\n", + "text":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___23___norm2_weight[name=p_getattr_l__self___trunk_blocks___23___norm2_weight]. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"FxOnnxInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":414 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0008", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___23___norm2_bias[name=p_getattr_l__self___trunk_blocks___23___norm2_bias]. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature FxOnnxInterpreter.run_node\n- self: \n- node: fx.Node(p_getattr_l__self___trunk_blocks___23___norm2_bias)[placeholder]:Tensor(f32[1024])\n- fx_graph_module: torch.fx.GraphModule()\n- onnxfunction_dispatcher: \n- op_level_debug: False\n- onnxscript_graph: \n- onnxscript_tracer: \n- fx_name_to_onnxscript_value: Dict[length=287](\np_trunk_pos_embed: `TorchScriptTensor(f32[1, 1024, 1024])`,\np_trunk_attn_pool_latent: `TorchScriptTensor(f32[1, 1, 1024])`,\np_trunk_patch_embed_proj_weight: `TorchScriptTensor(f32[1024, 3, 16, 16])`,\np_trunk_patch_embed_proj_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_weight: `TorchScriptTensor(f32[3072, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_bias: `TorchScriptTensor(f32[3072])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_weight: `TorchScriptTensor(f32[1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_bias: `TorchScriptTensor(f32[1024])`,\n...\n)\n## Return values\n", + "text":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___23___norm2_bias[name=p_getattr_l__self___trunk_blocks___23___norm2_bias]. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"FxOnnxInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":414 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0008", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___23___mlp_fc1_weight[name=p_getattr_l__self___trunk_blocks___23___mlp_fc1_weight]. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature FxOnnxInterpreter.run_node\n- self: \n- node: fx.Node(p_getattr_l__self___trunk_blocks___23___mlp_fc1_weight)[placeholder]:Tensor(f32[4096, 1024])\n- fx_graph_module: torch.fx.GraphModule()\n- onnxfunction_dispatcher: \n- op_level_debug: False\n- onnxscript_graph: \n- onnxscript_tracer: \n- fx_name_to_onnxscript_value: Dict[length=288](\np_trunk_pos_embed: `TorchScriptTensor(f32[1, 1024, 1024])`,\np_trunk_attn_pool_latent: `TorchScriptTensor(f32[1, 1, 1024])`,\np_trunk_patch_embed_proj_weight: `TorchScriptTensor(f32[1024, 3, 16, 16])`,\np_trunk_patch_embed_proj_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_weight: `TorchScriptTensor(f32[3072, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_bias: `TorchScriptTensor(f32[3072])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_weight: `TorchScriptTensor(f32[1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_bias: `TorchScriptTensor(f32[1024])`,\n...\n)\n## Return values\n", + "text":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___23___mlp_fc1_weight[name=p_getattr_l__self___trunk_blocks___23___mlp_fc1_weight]. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"FxOnnxInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":414 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0008", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___23___mlp_fc1_bias[name=p_getattr_l__self___trunk_blocks___23___mlp_fc1_bias]. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature FxOnnxInterpreter.run_node\n- self: \n- node: fx.Node(p_getattr_l__self___trunk_blocks___23___mlp_fc1_bias)[placeholder]:Tensor(f32[4096])\n- fx_graph_module: torch.fx.GraphModule()\n- onnxfunction_dispatcher: \n- op_level_debug: False\n- onnxscript_graph: \n- onnxscript_tracer: \n- fx_name_to_onnxscript_value: Dict[length=289](\np_trunk_pos_embed: `TorchScriptTensor(f32[1, 1024, 1024])`,\np_trunk_attn_pool_latent: `TorchScriptTensor(f32[1, 1, 1024])`,\np_trunk_patch_embed_proj_weight: `TorchScriptTensor(f32[1024, 3, 16, 16])`,\np_trunk_patch_embed_proj_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_weight: `TorchScriptTensor(f32[3072, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_bias: `TorchScriptTensor(f32[3072])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_weight: `TorchScriptTensor(f32[1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_bias: `TorchScriptTensor(f32[1024])`,\n...\n)\n## Return values\n", + "text":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___23___mlp_fc1_bias[name=p_getattr_l__self___trunk_blocks___23___mlp_fc1_bias]. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"FxOnnxInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":414 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0008", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___23___mlp_fc2_weight[name=p_getattr_l__self___trunk_blocks___23___mlp_fc2_weight]. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature FxOnnxInterpreter.run_node\n- self: \n- node: fx.Node(p_getattr_l__self___trunk_blocks___23___mlp_fc2_weight)[placeholder]:Tensor(f32[1024, 4096])\n- fx_graph_module: torch.fx.GraphModule()\n- onnxfunction_dispatcher: \n- op_level_debug: False\n- onnxscript_graph: \n- onnxscript_tracer: \n- fx_name_to_onnxscript_value: Dict[length=290](\np_trunk_pos_embed: `TorchScriptTensor(f32[1, 1024, 1024])`,\np_trunk_attn_pool_latent: `TorchScriptTensor(f32[1, 1, 1024])`,\np_trunk_patch_embed_proj_weight: `TorchScriptTensor(f32[1024, 3, 16, 16])`,\np_trunk_patch_embed_proj_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_weight: `TorchScriptTensor(f32[3072, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_bias: `TorchScriptTensor(f32[3072])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_weight: `TorchScriptTensor(f32[1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_bias: `TorchScriptTensor(f32[1024])`,\n...\n)\n## Return values\n", + "text":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___23___mlp_fc2_weight[name=p_getattr_l__self___trunk_blocks___23___mlp_fc2_weight]. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"FxOnnxInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":414 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0008", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___23___mlp_fc2_bias[name=p_getattr_l__self___trunk_blocks___23___mlp_fc2_bias]. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature FxOnnxInterpreter.run_node\n- self: \n- node: fx.Node(p_getattr_l__self___trunk_blocks___23___mlp_fc2_bias)[placeholder]:Tensor(f32[1024])\n- fx_graph_module: torch.fx.GraphModule()\n- onnxfunction_dispatcher: \n- op_level_debug: False\n- onnxscript_graph: \n- onnxscript_tracer: \n- fx_name_to_onnxscript_value: Dict[length=291](\np_trunk_pos_embed: `TorchScriptTensor(f32[1, 1024, 1024])`,\np_trunk_attn_pool_latent: `TorchScriptTensor(f32[1, 1, 1024])`,\np_trunk_patch_embed_proj_weight: `TorchScriptTensor(f32[1024, 3, 16, 16])`,\np_trunk_patch_embed_proj_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_weight: `TorchScriptTensor(f32[3072, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_bias: `TorchScriptTensor(f32[3072])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_weight: `TorchScriptTensor(f32[1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_bias: `TorchScriptTensor(f32[1024])`,\n...\n)\n## Return values\n", + "text":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___23___mlp_fc2_bias[name=p_getattr_l__self___trunk_blocks___23___mlp_fc2_bias]. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"FxOnnxInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":414 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0008", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Node: placeholder:p_trunk_norm_weight[name=p_trunk_norm_weight]. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature FxOnnxInterpreter.run_node\n- self: \n- node: fx.Node(p_trunk_norm_weight)[placeholder]:Tensor(f32[1024])\n- fx_graph_module: torch.fx.GraphModule()\n- onnxfunction_dispatcher: \n- op_level_debug: False\n- onnxscript_graph: \n- onnxscript_tracer: \n- fx_name_to_onnxscript_value: Dict[length=292](\np_trunk_pos_embed: `TorchScriptTensor(f32[1, 1024, 1024])`,\np_trunk_attn_pool_latent: `TorchScriptTensor(f32[1, 1, 1024])`,\np_trunk_patch_embed_proj_weight: `TorchScriptTensor(f32[1024, 3, 16, 16])`,\np_trunk_patch_embed_proj_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_weight: `TorchScriptTensor(f32[3072, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_bias: `TorchScriptTensor(f32[3072])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_weight: `TorchScriptTensor(f32[1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_bias: `TorchScriptTensor(f32[1024])`,\n...\n)\n## Return values\n", + "text":"FX Node: placeholder:p_trunk_norm_weight[name=p_trunk_norm_weight]. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"FxOnnxInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":414 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0008", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Node: placeholder:p_trunk_norm_bias[name=p_trunk_norm_bias]. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature FxOnnxInterpreter.run_node\n- self: \n- node: fx.Node(p_trunk_norm_bias)[placeholder]:Tensor(f32[1024])\n- fx_graph_module: torch.fx.GraphModule()\n- onnxfunction_dispatcher: \n- op_level_debug: False\n- onnxscript_graph: \n- onnxscript_tracer: \n- fx_name_to_onnxscript_value: Dict[length=293](\np_trunk_pos_embed: `TorchScriptTensor(f32[1, 1024, 1024])`,\np_trunk_attn_pool_latent: `TorchScriptTensor(f32[1, 1, 1024])`,\np_trunk_patch_embed_proj_weight: `TorchScriptTensor(f32[1024, 3, 16, 16])`,\np_trunk_patch_embed_proj_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_weight: `TorchScriptTensor(f32[3072, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_bias: `TorchScriptTensor(f32[3072])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_weight: `TorchScriptTensor(f32[1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_bias: `TorchScriptTensor(f32[1024])`,\n...\n)\n## Return values\n", + "text":"FX Node: placeholder:p_trunk_norm_bias[name=p_trunk_norm_bias]. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"FxOnnxInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":414 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0008", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Node: placeholder:p_trunk_attn_pool_q_weight[name=p_trunk_attn_pool_q_weight]. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature FxOnnxInterpreter.run_node\n- self: \n- node: fx.Node(p_trunk_attn_pool_q_weight)[placeholder]:Tensor(f32[1024, 1024])\n- fx_graph_module: torch.fx.GraphModule()\n- onnxfunction_dispatcher: \n- op_level_debug: False\n- onnxscript_graph: \n- onnxscript_tracer: \n- fx_name_to_onnxscript_value: Dict[length=294](\np_trunk_pos_embed: `TorchScriptTensor(f32[1, 1024, 1024])`,\np_trunk_attn_pool_latent: `TorchScriptTensor(f32[1, 1, 1024])`,\np_trunk_patch_embed_proj_weight: `TorchScriptTensor(f32[1024, 3, 16, 16])`,\np_trunk_patch_embed_proj_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_weight: `TorchScriptTensor(f32[3072, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_bias: `TorchScriptTensor(f32[3072])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_weight: `TorchScriptTensor(f32[1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_bias: `TorchScriptTensor(f32[1024])`,\n...\n)\n## Return values\n", + "text":"FX Node: placeholder:p_trunk_attn_pool_q_weight[name=p_trunk_attn_pool_q_weight]. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"FxOnnxInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":414 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0008", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Node: placeholder:p_trunk_attn_pool_q_bias[name=p_trunk_attn_pool_q_bias]. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature FxOnnxInterpreter.run_node\n- self: \n- node: fx.Node(p_trunk_attn_pool_q_bias)[placeholder]:Tensor(f32[1024])\n- fx_graph_module: torch.fx.GraphModule()\n- onnxfunction_dispatcher: \n- op_level_debug: False\n- onnxscript_graph: \n- onnxscript_tracer: \n- fx_name_to_onnxscript_value: Dict[length=295](\np_trunk_pos_embed: `TorchScriptTensor(f32[1, 1024, 1024])`,\np_trunk_attn_pool_latent: `TorchScriptTensor(f32[1, 1, 1024])`,\np_trunk_patch_embed_proj_weight: `TorchScriptTensor(f32[1024, 3, 16, 16])`,\np_trunk_patch_embed_proj_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_weight: `TorchScriptTensor(f32[3072, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_bias: `TorchScriptTensor(f32[3072])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_weight: `TorchScriptTensor(f32[1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_bias: `TorchScriptTensor(f32[1024])`,\n...\n)\n## Return values\n", + "text":"FX Node: placeholder:p_trunk_attn_pool_q_bias[name=p_trunk_attn_pool_q_bias]. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"FxOnnxInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":414 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0008", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Node: placeholder:p_trunk_attn_pool_kv_weight[name=p_trunk_attn_pool_kv_weight]. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature FxOnnxInterpreter.run_node\n- self: \n- node: fx.Node(p_trunk_attn_pool_kv_weight)[placeholder]:Tensor(f32[2048, 1024])\n- fx_graph_module: torch.fx.GraphModule()\n- onnxfunction_dispatcher: \n- op_level_debug: False\n- onnxscript_graph: \n- onnxscript_tracer: \n- fx_name_to_onnxscript_value: Dict[length=296](\np_trunk_pos_embed: `TorchScriptTensor(f32[1, 1024, 1024])`,\np_trunk_attn_pool_latent: `TorchScriptTensor(f32[1, 1, 1024])`,\np_trunk_patch_embed_proj_weight: `TorchScriptTensor(f32[1024, 3, 16, 16])`,\np_trunk_patch_embed_proj_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_weight: `TorchScriptTensor(f32[3072, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_bias: `TorchScriptTensor(f32[3072])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_weight: `TorchScriptTensor(f32[1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_bias: `TorchScriptTensor(f32[1024])`,\n...\n)\n## Return values\n", + "text":"FX Node: placeholder:p_trunk_attn_pool_kv_weight[name=p_trunk_attn_pool_kv_weight]. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"FxOnnxInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":414 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0008", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Node: placeholder:p_trunk_attn_pool_kv_bias[name=p_trunk_attn_pool_kv_bias]. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature FxOnnxInterpreter.run_node\n- self: \n- node: fx.Node(p_trunk_attn_pool_kv_bias)[placeholder]:Tensor(f32[2048])\n- fx_graph_module: torch.fx.GraphModule()\n- onnxfunction_dispatcher: \n- op_level_debug: False\n- onnxscript_graph: \n- onnxscript_tracer: \n- fx_name_to_onnxscript_value: Dict[length=297](\np_trunk_pos_embed: `TorchScriptTensor(f32[1, 1024, 1024])`,\np_trunk_attn_pool_latent: `TorchScriptTensor(f32[1, 1, 1024])`,\np_trunk_patch_embed_proj_weight: `TorchScriptTensor(f32[1024, 3, 16, 16])`,\np_trunk_patch_embed_proj_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_weight: `TorchScriptTensor(f32[3072, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_bias: `TorchScriptTensor(f32[3072])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_weight: `TorchScriptTensor(f32[1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_bias: `TorchScriptTensor(f32[1024])`,\n...\n)\n## Return values\n", + "text":"FX Node: placeholder:p_trunk_attn_pool_kv_bias[name=p_trunk_attn_pool_kv_bias]. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"FxOnnxInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":414 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0008", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Node: placeholder:p_trunk_attn_pool_proj_weight[name=p_trunk_attn_pool_proj_weight]. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature FxOnnxInterpreter.run_node\n- self: \n- node: fx.Node(p_trunk_attn_pool_proj_weight)[placeholder]:Tensor(f32[1024, 1024])\n- fx_graph_module: torch.fx.GraphModule()\n- onnxfunction_dispatcher: \n- op_level_debug: False\n- onnxscript_graph: \n- onnxscript_tracer: \n- fx_name_to_onnxscript_value: Dict[length=298](\np_trunk_pos_embed: `TorchScriptTensor(f32[1, 1024, 1024])`,\np_trunk_attn_pool_latent: `TorchScriptTensor(f32[1, 1, 1024])`,\np_trunk_patch_embed_proj_weight: `TorchScriptTensor(f32[1024, 3, 16, 16])`,\np_trunk_patch_embed_proj_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_weight: `TorchScriptTensor(f32[3072, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_bias: `TorchScriptTensor(f32[3072])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_weight: `TorchScriptTensor(f32[1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_bias: `TorchScriptTensor(f32[1024])`,\n...\n)\n## Return values\n", + "text":"FX Node: placeholder:p_trunk_attn_pool_proj_weight[name=p_trunk_attn_pool_proj_weight]. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"FxOnnxInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":414 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0008", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Node: placeholder:p_trunk_attn_pool_proj_bias[name=p_trunk_attn_pool_proj_bias]. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature FxOnnxInterpreter.run_node\n- self: \n- node: fx.Node(p_trunk_attn_pool_proj_bias)[placeholder]:Tensor(f32[1024])\n- fx_graph_module: torch.fx.GraphModule()\n- onnxfunction_dispatcher: \n- op_level_debug: False\n- onnxscript_graph: \n- onnxscript_tracer: \n- fx_name_to_onnxscript_value: Dict[length=299](\np_trunk_pos_embed: `TorchScriptTensor(f32[1, 1024, 1024])`,\np_trunk_attn_pool_latent: `TorchScriptTensor(f32[1, 1, 1024])`,\np_trunk_patch_embed_proj_weight: `TorchScriptTensor(f32[1024, 3, 16, 16])`,\np_trunk_patch_embed_proj_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_weight: `TorchScriptTensor(f32[3072, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_bias: `TorchScriptTensor(f32[3072])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_weight: `TorchScriptTensor(f32[1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_bias: `TorchScriptTensor(f32[1024])`,\n...\n)\n## Return values\n", + "text":"FX Node: placeholder:p_trunk_attn_pool_proj_bias[name=p_trunk_attn_pool_proj_bias]. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"FxOnnxInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":414 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0008", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Node: placeholder:p_trunk_attn_pool_norm_weight[name=p_trunk_attn_pool_norm_weight]. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature FxOnnxInterpreter.run_node\n- self: \n- node: fx.Node(p_trunk_attn_pool_norm_weight)[placeholder]:Tensor(f32[1024])\n- fx_graph_module: torch.fx.GraphModule()\n- onnxfunction_dispatcher: \n- op_level_debug: False\n- onnxscript_graph: \n- onnxscript_tracer: \n- fx_name_to_onnxscript_value: Dict[length=300](\np_trunk_pos_embed: `TorchScriptTensor(f32[1, 1024, 1024])`,\np_trunk_attn_pool_latent: `TorchScriptTensor(f32[1, 1, 1024])`,\np_trunk_patch_embed_proj_weight: `TorchScriptTensor(f32[1024, 3, 16, 16])`,\np_trunk_patch_embed_proj_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_weight: `TorchScriptTensor(f32[3072, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_bias: `TorchScriptTensor(f32[3072])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_weight: `TorchScriptTensor(f32[1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_bias: `TorchScriptTensor(f32[1024])`,\n...\n)\n## Return values\n", + "text":"FX Node: placeholder:p_trunk_attn_pool_norm_weight[name=p_trunk_attn_pool_norm_weight]. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"FxOnnxInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":414 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0008", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Node: placeholder:p_trunk_attn_pool_norm_bias[name=p_trunk_attn_pool_norm_bias]. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature FxOnnxInterpreter.run_node\n- self: \n- node: fx.Node(p_trunk_attn_pool_norm_bias)[placeholder]:Tensor(f32[1024])\n- fx_graph_module: torch.fx.GraphModule()\n- onnxfunction_dispatcher: \n- op_level_debug: False\n- onnxscript_graph: \n- onnxscript_tracer: \n- fx_name_to_onnxscript_value: Dict[length=301](\np_trunk_pos_embed: `TorchScriptTensor(f32[1, 1024, 1024])`,\np_trunk_attn_pool_latent: `TorchScriptTensor(f32[1, 1, 1024])`,\np_trunk_patch_embed_proj_weight: `TorchScriptTensor(f32[1024, 3, 16, 16])`,\np_trunk_patch_embed_proj_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_weight: `TorchScriptTensor(f32[3072, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_bias: `TorchScriptTensor(f32[3072])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_weight: `TorchScriptTensor(f32[1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_bias: `TorchScriptTensor(f32[1024])`,\n...\n)\n## Return values\n", + "text":"FX Node: placeholder:p_trunk_attn_pool_norm_bias[name=p_trunk_attn_pool_norm_bias]. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"FxOnnxInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":414 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0008", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Node: placeholder:p_trunk_attn_pool_mlp_fc1_weight[name=p_trunk_attn_pool_mlp_fc1_weight]. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature FxOnnxInterpreter.run_node\n- self: \n- node: fx.Node(p_trunk_attn_pool_mlp_fc1_weight)[placeholder]:Tensor(f32[4096, 1024])\n- fx_graph_module: torch.fx.GraphModule()\n- onnxfunction_dispatcher: \n- op_level_debug: False\n- onnxscript_graph: \n- onnxscript_tracer: \n- fx_name_to_onnxscript_value: Dict[length=302](\np_trunk_pos_embed: `TorchScriptTensor(f32[1, 1024, 1024])`,\np_trunk_attn_pool_latent: `TorchScriptTensor(f32[1, 1, 1024])`,\np_trunk_patch_embed_proj_weight: `TorchScriptTensor(f32[1024, 3, 16, 16])`,\np_trunk_patch_embed_proj_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_weight: `TorchScriptTensor(f32[3072, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_bias: `TorchScriptTensor(f32[3072])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_weight: `TorchScriptTensor(f32[1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_bias: `TorchScriptTensor(f32[1024])`,\n...\n)\n## Return values\n", + "text":"FX Node: placeholder:p_trunk_attn_pool_mlp_fc1_weight[name=p_trunk_attn_pool_mlp_fc1_weight]. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"FxOnnxInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":414 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0008", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Node: placeholder:p_trunk_attn_pool_mlp_fc1_bias[name=p_trunk_attn_pool_mlp_fc1_bias]. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature FxOnnxInterpreter.run_node\n- self: \n- node: fx.Node(p_trunk_attn_pool_mlp_fc1_bias)[placeholder]:Tensor(f32[4096])\n- fx_graph_module: torch.fx.GraphModule()\n- onnxfunction_dispatcher: \n- op_level_debug: False\n- onnxscript_graph: \n- onnxscript_tracer: \n- fx_name_to_onnxscript_value: Dict[length=303](\np_trunk_pos_embed: `TorchScriptTensor(f32[1, 1024, 1024])`,\np_trunk_attn_pool_latent: `TorchScriptTensor(f32[1, 1, 1024])`,\np_trunk_patch_embed_proj_weight: `TorchScriptTensor(f32[1024, 3, 16, 16])`,\np_trunk_patch_embed_proj_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_weight: `TorchScriptTensor(f32[3072, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_bias: `TorchScriptTensor(f32[3072])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_weight: `TorchScriptTensor(f32[1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_bias: `TorchScriptTensor(f32[1024])`,\n...\n)\n## Return values\n", + "text":"FX Node: placeholder:p_trunk_attn_pool_mlp_fc1_bias[name=p_trunk_attn_pool_mlp_fc1_bias]. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"FxOnnxInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":414 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0008", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Node: placeholder:p_trunk_attn_pool_mlp_fc2_weight[name=p_trunk_attn_pool_mlp_fc2_weight]. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature FxOnnxInterpreter.run_node\n- self: \n- node: fx.Node(p_trunk_attn_pool_mlp_fc2_weight)[placeholder]:Tensor(f32[1024, 4096])\n- fx_graph_module: torch.fx.GraphModule()\n- onnxfunction_dispatcher: \n- op_level_debug: False\n- onnxscript_graph: \n- onnxscript_tracer: \n- fx_name_to_onnxscript_value: Dict[length=304](\np_trunk_pos_embed: `TorchScriptTensor(f32[1, 1024, 1024])`,\np_trunk_attn_pool_latent: `TorchScriptTensor(f32[1, 1, 1024])`,\np_trunk_patch_embed_proj_weight: `TorchScriptTensor(f32[1024, 3, 16, 16])`,\np_trunk_patch_embed_proj_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_weight: `TorchScriptTensor(f32[3072, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_bias: `TorchScriptTensor(f32[3072])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_weight: `TorchScriptTensor(f32[1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_bias: `TorchScriptTensor(f32[1024])`,\n...\n)\n## Return values\n", + "text":"FX Node: placeholder:p_trunk_attn_pool_mlp_fc2_weight[name=p_trunk_attn_pool_mlp_fc2_weight]. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"FxOnnxInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":414 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0008", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Node: placeholder:p_trunk_attn_pool_mlp_fc2_bias[name=p_trunk_attn_pool_mlp_fc2_bias]. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature FxOnnxInterpreter.run_node\n- self: \n- node: fx.Node(p_trunk_attn_pool_mlp_fc2_bias)[placeholder]:Tensor(f32[1024])\n- fx_graph_module: torch.fx.GraphModule()\n- onnxfunction_dispatcher: \n- op_level_debug: False\n- onnxscript_graph: \n- onnxscript_tracer: \n- fx_name_to_onnxscript_value: Dict[length=305](\np_trunk_pos_embed: `TorchScriptTensor(f32[1, 1024, 1024])`,\np_trunk_attn_pool_latent: `TorchScriptTensor(f32[1, 1, 1024])`,\np_trunk_patch_embed_proj_weight: `TorchScriptTensor(f32[1024, 3, 16, 16])`,\np_trunk_patch_embed_proj_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_weight: `TorchScriptTensor(f32[3072, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_bias: `TorchScriptTensor(f32[3072])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_weight: `TorchScriptTensor(f32[1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_bias: `TorchScriptTensor(f32[1024])`,\n...\n)\n## Return values\n", + "text":"FX Node: placeholder:p_trunk_attn_pool_mlp_fc2_bias[name=p_trunk_attn_pool_mlp_fc2_bias]. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"FxOnnxInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":414 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0008", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Node: placeholder:x[name=x]. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature FxOnnxInterpreter.run_node\n- self: \n- node: fx.Node(x)[placeholder]:Tensor(f32[4, 3, 512, 512])\n- fx_graph_module: torch.fx.GraphModule()\n- onnxfunction_dispatcher: \n- op_level_debug: False\n- onnxscript_graph: \n- onnxscript_tracer: \n- fx_name_to_onnxscript_value: Dict[length=306](\np_trunk_pos_embed: `TorchScriptTensor(f32[1, 1024, 1024])`,\np_trunk_attn_pool_latent: `TorchScriptTensor(f32[1, 1, 1024])`,\np_trunk_patch_embed_proj_weight: `TorchScriptTensor(f32[1024, 3, 16, 16])`,\np_trunk_patch_embed_proj_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_weight: `TorchScriptTensor(f32[3072, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_bias: `TorchScriptTensor(f32[3072])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_weight: `TorchScriptTensor(f32[1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_bias: `TorchScriptTensor(f32[1024])`,\n...\n)\n## Return values\n", + "text":"FX Node: placeholder:x[name=x]. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"FxOnnxInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":414 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0008", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Node: placeholder:x[name=x]. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature FxOnnxInterpreter.run_node\n- self: \n- node: fx.Node(x)[placeholder]:Tensor(f32[4, 3, 512, 512])\n- fx_graph_module: torch.fx.GraphModule(timm_models_vision_transformer_VisionTransformer)\n- onnxfunction_dispatcher: \n- op_level_debug: False\n- onnxscript_graph: \n- onnxscript_tracer: \n- fx_name_to_onnxscript_value: Dict[length=0](\nNone)\n## Return values\n", + "text":"FX Node: placeholder:x[name=x]. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"FxOnnxInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":414 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0008", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Node: placeholder:p_trunk_patch_embed_proj_weight[name=p_trunk_patch_embed_proj_weight]. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature FxOnnxInterpreter.run_node\n- self: \n- node: fx.Node(p_trunk_patch_embed_proj_weight)[placeholder]:Tensor(f32[1024, 3, 16, 16])\n- fx_graph_module: torch.fx.GraphModule(timm_models_vision_transformer_VisionTransformer)\n- onnxfunction_dispatcher: \n- op_level_debug: False\n- onnxscript_graph: \n- onnxscript_tracer: \n- fx_name_to_onnxscript_value: Dict[length=1](\nx: `TorchScriptTensor(f32[4, 3, 512, 512])`,\n)\n## Return values\n", + "text":"FX Node: placeholder:p_trunk_patch_embed_proj_weight[name=p_trunk_patch_embed_proj_weight]. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"FxOnnxInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":414 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0008", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Node: placeholder:p_trunk_patch_embed_proj_bias[name=p_trunk_patch_embed_proj_bias]. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature FxOnnxInterpreter.run_node\n- self: \n- node: fx.Node(p_trunk_patch_embed_proj_bias)[placeholder]:Tensor(f32[1024])\n- fx_graph_module: torch.fx.GraphModule(timm_models_vision_transformer_VisionTransformer)\n- onnxfunction_dispatcher: \n- op_level_debug: False\n- onnxscript_graph: \n- onnxscript_tracer: \n- fx_name_to_onnxscript_value: Dict[length=2](\nx: `TorchScriptTensor(f32[4, 3, 512, 512])`,\np_trunk_patch_embed_proj_weight: `TorchScriptTensor(f32[1024, 3, 16, 16])`,\n)\n## Return values\n", + "text":"FX Node: placeholder:p_trunk_patch_embed_proj_bias[name=p_trunk_patch_embed_proj_bias]. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"FxOnnxInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":414 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0008", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Node: placeholder:p_trunk_pos_embed[name=p_trunk_pos_embed]. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature FxOnnxInterpreter.run_node\n- self: \n- node: fx.Node(p_trunk_pos_embed)[placeholder]:Tensor(f32[1, 1024, 1024])\n- fx_graph_module: torch.fx.GraphModule(timm_models_vision_transformer_VisionTransformer)\n- onnxfunction_dispatcher: \n- op_level_debug: False\n- onnxscript_graph: \n- onnxscript_tracer: \n- fx_name_to_onnxscript_value: Dict[length=3](\nx: `TorchScriptTensor(f32[4, 3, 512, 512])`,\np_trunk_patch_embed_proj_weight: `TorchScriptTensor(f32[1024, 3, 16, 16])`,\np_trunk_patch_embed_proj_bias: `TorchScriptTensor(f32[1024])`,\n)\n## Return values\n", + "text":"FX Node: placeholder:p_trunk_pos_embed[name=p_trunk_pos_embed]. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"FxOnnxInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":414 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0008", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___0___norm1_weight[name=p_getattr_l__self___trunk_blocks___0___norm1_weight]. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature FxOnnxInterpreter.run_node\n- self: \n- node: fx.Node(p_getattr_l__self___trunk_blocks___0___norm1_weight)[placeholder]:Tensor(f32[1024])\n- fx_graph_module: torch.fx.GraphModule(timm_models_vision_transformer_VisionTransformer)\n- onnxfunction_dispatcher: \n- op_level_debug: False\n- onnxscript_graph: \n- onnxscript_tracer: \n- fx_name_to_onnxscript_value: Dict[length=4](\nx: `TorchScriptTensor(f32[4, 3, 512, 512])`,\np_trunk_patch_embed_proj_weight: `TorchScriptTensor(f32[1024, 3, 16, 16])`,\np_trunk_patch_embed_proj_bias: `TorchScriptTensor(f32[1024])`,\np_trunk_pos_embed: `TorchScriptTensor(f32[1, 1024, 1024])`,\n)\n## Return values\n", + "text":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___0___norm1_weight[name=p_getattr_l__self___trunk_blocks___0___norm1_weight]. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"FxOnnxInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":414 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0008", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___0___norm1_bias[name=p_getattr_l__self___trunk_blocks___0___norm1_bias]. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature FxOnnxInterpreter.run_node\n- self: \n- node: fx.Node(p_getattr_l__self___trunk_blocks___0___norm1_bias)[placeholder]:Tensor(f32[1024])\n- fx_graph_module: torch.fx.GraphModule(timm_models_vision_transformer_VisionTransformer)\n- onnxfunction_dispatcher: \n- op_level_debug: False\n- onnxscript_graph: \n- onnxscript_tracer: \n- fx_name_to_onnxscript_value: Dict[length=5](\nx: `TorchScriptTensor(f32[4, 3, 512, 512])`,\np_trunk_patch_embed_proj_weight: `TorchScriptTensor(f32[1024, 3, 16, 16])`,\np_trunk_patch_embed_proj_bias: `TorchScriptTensor(f32[1024])`,\np_trunk_pos_embed: `TorchScriptTensor(f32[1, 1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_weight: `TorchScriptTensor(f32[1024])`,\n)\n## Return values\n", + "text":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___0___norm1_bias[name=p_getattr_l__self___trunk_blocks___0___norm1_bias]. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"FxOnnxInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":414 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0008", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___0___attn_qkv_weight[name=p_getattr_l__self___trunk_blocks___0___attn_qkv_weight]. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature FxOnnxInterpreter.run_node\n- self: \n- node: fx.Node(p_getattr_l__self___trunk_blocks___0___attn_qkv_weight)[placeholder]:Tensor(f32[3072, 1024])\n- fx_graph_module: torch.fx.GraphModule(timm_models_vision_transformer_VisionTransformer)\n- onnxfunction_dispatcher: \n- op_level_debug: False\n- onnxscript_graph: \n- onnxscript_tracer: \n- fx_name_to_onnxscript_value: Dict[length=6](\nx: `TorchScriptTensor(f32[4, 3, 512, 512])`,\np_trunk_patch_embed_proj_weight: `TorchScriptTensor(f32[1024, 3, 16, 16])`,\np_trunk_patch_embed_proj_bias: `TorchScriptTensor(f32[1024])`,\np_trunk_pos_embed: `TorchScriptTensor(f32[1, 1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_bias: `TorchScriptTensor(f32[1024])`,\n)\n## Return values\n", + "text":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___0___attn_qkv_weight[name=p_getattr_l__self___trunk_blocks___0___attn_qkv_weight]. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"FxOnnxInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":414 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0008", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___0___attn_qkv_bias[name=p_getattr_l__self___trunk_blocks___0___attn_qkv_bias]. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature FxOnnxInterpreter.run_node\n- self: \n- node: fx.Node(p_getattr_l__self___trunk_blocks___0___attn_qkv_bias)[placeholder]:Tensor(f32[3072])\n- fx_graph_module: torch.fx.GraphModule(timm_models_vision_transformer_VisionTransformer)\n- onnxfunction_dispatcher: \n- op_level_debug: False\n- onnxscript_graph: \n- onnxscript_tracer: \n- fx_name_to_onnxscript_value: Dict[length=7](\nx: `TorchScriptTensor(f32[4, 3, 512, 512])`,\np_trunk_patch_embed_proj_weight: `TorchScriptTensor(f32[1024, 3, 16, 16])`,\np_trunk_patch_embed_proj_bias: `TorchScriptTensor(f32[1024])`,\np_trunk_pos_embed: `TorchScriptTensor(f32[1, 1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_weight: `TorchScriptTensor(f32[3072, 1024])`,\n)\n## Return values\n", + "text":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___0___attn_qkv_bias[name=p_getattr_l__self___trunk_blocks___0___attn_qkv_bias]. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"FxOnnxInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":414 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0008", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___0___attn_proj_weight[name=p_getattr_l__self___trunk_blocks___0___attn_proj_weight]. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature FxOnnxInterpreter.run_node\n- self: \n- node: fx.Node(p_getattr_l__self___trunk_blocks___0___attn_proj_weight)[placeholder]:Tensor(f32[1024, 1024])\n- fx_graph_module: torch.fx.GraphModule(timm_models_vision_transformer_VisionTransformer)\n- onnxfunction_dispatcher: \n- op_level_debug: False\n- onnxscript_graph: \n- onnxscript_tracer: \n- fx_name_to_onnxscript_value: Dict[length=8](\nx: `TorchScriptTensor(f32[4, 3, 512, 512])`,\np_trunk_patch_embed_proj_weight: `TorchScriptTensor(f32[1024, 3, 16, 16])`,\np_trunk_patch_embed_proj_bias: `TorchScriptTensor(f32[1024])`,\np_trunk_pos_embed: `TorchScriptTensor(f32[1, 1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_weight: `TorchScriptTensor(f32[3072, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_bias: `TorchScriptTensor(f32[3072])`,\n)\n## Return values\n", + "text":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___0___attn_proj_weight[name=p_getattr_l__self___trunk_blocks___0___attn_proj_weight]. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"FxOnnxInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":414 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0008", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___0___attn_proj_bias[name=p_getattr_l__self___trunk_blocks___0___attn_proj_bias]. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature FxOnnxInterpreter.run_node\n- self: \n- node: fx.Node(p_getattr_l__self___trunk_blocks___0___attn_proj_bias)[placeholder]:Tensor(f32[1024])\n- fx_graph_module: torch.fx.GraphModule(timm_models_vision_transformer_VisionTransformer)\n- onnxfunction_dispatcher: \n- op_level_debug: False\n- onnxscript_graph: \n- onnxscript_tracer: \n- fx_name_to_onnxscript_value: Dict[length=9](\nx: `TorchScriptTensor(f32[4, 3, 512, 512])`,\np_trunk_patch_embed_proj_weight: `TorchScriptTensor(f32[1024, 3, 16, 16])`,\np_trunk_patch_embed_proj_bias: `TorchScriptTensor(f32[1024])`,\np_trunk_pos_embed: `TorchScriptTensor(f32[1, 1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_weight: `TorchScriptTensor(f32[3072, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_bias: `TorchScriptTensor(f32[3072])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_weight: `TorchScriptTensor(f32[1024, 1024])`,\n)\n## Return values\n", + "text":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___0___attn_proj_bias[name=p_getattr_l__self___trunk_blocks___0___attn_proj_bias]. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"FxOnnxInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":414 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0008", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___0___norm2_weight[name=p_getattr_l__self___trunk_blocks___0___norm2_weight]. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature FxOnnxInterpreter.run_node\n- self: \n- node: fx.Node(p_getattr_l__self___trunk_blocks___0___norm2_weight)[placeholder]:Tensor(f32[1024])\n- fx_graph_module: torch.fx.GraphModule(timm_models_vision_transformer_VisionTransformer)\n- onnxfunction_dispatcher: \n- op_level_debug: False\n- onnxscript_graph: \n- onnxscript_tracer: \n- fx_name_to_onnxscript_value: Dict[length=10](\nx: `TorchScriptTensor(f32[4, 3, 512, 512])`,\np_trunk_patch_embed_proj_weight: `TorchScriptTensor(f32[1024, 3, 16, 16])`,\np_trunk_patch_embed_proj_bias: `TorchScriptTensor(f32[1024])`,\np_trunk_pos_embed: `TorchScriptTensor(f32[1, 1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_weight: `TorchScriptTensor(f32[3072, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_bias: `TorchScriptTensor(f32[3072])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_weight: `TorchScriptTensor(f32[1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_bias: `TorchScriptTensor(f32[1024])`,\n)\n## Return values\n", + "text":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___0___norm2_weight[name=p_getattr_l__self___trunk_blocks___0___norm2_weight]. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"FxOnnxInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":414 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0008", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___0___norm2_bias[name=p_getattr_l__self___trunk_blocks___0___norm2_bias]. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature FxOnnxInterpreter.run_node\n- self: \n- node: fx.Node(p_getattr_l__self___trunk_blocks___0___norm2_bias)[placeholder]:Tensor(f32[1024])\n- fx_graph_module: torch.fx.GraphModule(timm_models_vision_transformer_VisionTransformer)\n- onnxfunction_dispatcher: \n- op_level_debug: False\n- onnxscript_graph: \n- onnxscript_tracer: \n- fx_name_to_onnxscript_value: Dict[length=11](\nx: `TorchScriptTensor(f32[4, 3, 512, 512])`,\np_trunk_patch_embed_proj_weight: `TorchScriptTensor(f32[1024, 3, 16, 16])`,\np_trunk_patch_embed_proj_bias: `TorchScriptTensor(f32[1024])`,\np_trunk_pos_embed: `TorchScriptTensor(f32[1, 1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_weight: `TorchScriptTensor(f32[3072, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_bias: `TorchScriptTensor(f32[3072])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_weight: `TorchScriptTensor(f32[1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_bias: `TorchScriptTensor(f32[1024])`,\n...\n)\n## Return values\n", + "text":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___0___norm2_bias[name=p_getattr_l__self___trunk_blocks___0___norm2_bias]. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"FxOnnxInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":414 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0008", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___0___mlp_fc1_weight[name=p_getattr_l__self___trunk_blocks___0___mlp_fc1_weight]. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature FxOnnxInterpreter.run_node\n- self: \n- node: fx.Node(p_getattr_l__self___trunk_blocks___0___mlp_fc1_weight)[placeholder]:Tensor(f32[4096, 1024])\n- fx_graph_module: torch.fx.GraphModule(timm_models_vision_transformer_VisionTransformer)\n- onnxfunction_dispatcher: \n- op_level_debug: False\n- onnxscript_graph: \n- onnxscript_tracer: \n- fx_name_to_onnxscript_value: Dict[length=12](\nx: `TorchScriptTensor(f32[4, 3, 512, 512])`,\np_trunk_patch_embed_proj_weight: `TorchScriptTensor(f32[1024, 3, 16, 16])`,\np_trunk_patch_embed_proj_bias: `TorchScriptTensor(f32[1024])`,\np_trunk_pos_embed: `TorchScriptTensor(f32[1, 1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_weight: `TorchScriptTensor(f32[3072, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_bias: `TorchScriptTensor(f32[3072])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_weight: `TorchScriptTensor(f32[1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_bias: `TorchScriptTensor(f32[1024])`,\n...\n)\n## Return values\n", + "text":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___0___mlp_fc1_weight[name=p_getattr_l__self___trunk_blocks___0___mlp_fc1_weight]. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"FxOnnxInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":414 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0008", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___0___mlp_fc1_bias[name=p_getattr_l__self___trunk_blocks___0___mlp_fc1_bias]. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature FxOnnxInterpreter.run_node\n- self: \n- node: fx.Node(p_getattr_l__self___trunk_blocks___0___mlp_fc1_bias)[placeholder]:Tensor(f32[4096])\n- fx_graph_module: torch.fx.GraphModule(timm_models_vision_transformer_VisionTransformer)\n- onnxfunction_dispatcher: \n- op_level_debug: False\n- onnxscript_graph: \n- onnxscript_tracer: \n- fx_name_to_onnxscript_value: Dict[length=13](\nx: `TorchScriptTensor(f32[4, 3, 512, 512])`,\np_trunk_patch_embed_proj_weight: `TorchScriptTensor(f32[1024, 3, 16, 16])`,\np_trunk_patch_embed_proj_bias: `TorchScriptTensor(f32[1024])`,\np_trunk_pos_embed: `TorchScriptTensor(f32[1, 1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_weight: `TorchScriptTensor(f32[3072, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_bias: `TorchScriptTensor(f32[3072])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_weight: `TorchScriptTensor(f32[1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_bias: `TorchScriptTensor(f32[1024])`,\n...\n)\n## Return values\n", + "text":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___0___mlp_fc1_bias[name=p_getattr_l__self___trunk_blocks___0___mlp_fc1_bias]. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"FxOnnxInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":414 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0008", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___0___mlp_fc2_weight[name=p_getattr_l__self___trunk_blocks___0___mlp_fc2_weight]. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature FxOnnxInterpreter.run_node\n- self: \n- node: fx.Node(p_getattr_l__self___trunk_blocks___0___mlp_fc2_weight)[placeholder]:Tensor(f32[1024, 4096])\n- fx_graph_module: torch.fx.GraphModule(timm_models_vision_transformer_VisionTransformer)\n- onnxfunction_dispatcher: \n- op_level_debug: False\n- onnxscript_graph: \n- onnxscript_tracer: \n- fx_name_to_onnxscript_value: Dict[length=14](\nx: `TorchScriptTensor(f32[4, 3, 512, 512])`,\np_trunk_patch_embed_proj_weight: `TorchScriptTensor(f32[1024, 3, 16, 16])`,\np_trunk_patch_embed_proj_bias: `TorchScriptTensor(f32[1024])`,\np_trunk_pos_embed: `TorchScriptTensor(f32[1, 1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_weight: `TorchScriptTensor(f32[3072, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_bias: `TorchScriptTensor(f32[3072])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_weight: `TorchScriptTensor(f32[1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_bias: `TorchScriptTensor(f32[1024])`,\n...\n)\n## Return values\n", + "text":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___0___mlp_fc2_weight[name=p_getattr_l__self___trunk_blocks___0___mlp_fc2_weight]. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"FxOnnxInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":414 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0008", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___0___mlp_fc2_bias[name=p_getattr_l__self___trunk_blocks___0___mlp_fc2_bias]. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature FxOnnxInterpreter.run_node\n- self: \n- node: fx.Node(p_getattr_l__self___trunk_blocks___0___mlp_fc2_bias)[placeholder]:Tensor(f32[1024])\n- fx_graph_module: torch.fx.GraphModule(timm_models_vision_transformer_VisionTransformer)\n- onnxfunction_dispatcher: \n- op_level_debug: False\n- onnxscript_graph: \n- onnxscript_tracer: \n- fx_name_to_onnxscript_value: Dict[length=15](\nx: `TorchScriptTensor(f32[4, 3, 512, 512])`,\np_trunk_patch_embed_proj_weight: `TorchScriptTensor(f32[1024, 3, 16, 16])`,\np_trunk_patch_embed_proj_bias: `TorchScriptTensor(f32[1024])`,\np_trunk_pos_embed: `TorchScriptTensor(f32[1, 1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_weight: `TorchScriptTensor(f32[3072, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_bias: `TorchScriptTensor(f32[3072])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_weight: `TorchScriptTensor(f32[1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_bias: `TorchScriptTensor(f32[1024])`,\n...\n)\n## Return values\n", + "text":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___0___mlp_fc2_bias[name=p_getattr_l__self___trunk_blocks___0___mlp_fc2_bias]. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"FxOnnxInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":414 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0008", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___1___norm1_weight[name=p_getattr_l__self___trunk_blocks___1___norm1_weight]. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature FxOnnxInterpreter.run_node\n- self: \n- node: fx.Node(p_getattr_l__self___trunk_blocks___1___norm1_weight)[placeholder]:Tensor(f32[1024])\n- fx_graph_module: torch.fx.GraphModule(timm_models_vision_transformer_VisionTransformer)\n- onnxfunction_dispatcher: \n- op_level_debug: False\n- onnxscript_graph: \n- onnxscript_tracer: \n- fx_name_to_onnxscript_value: Dict[length=16](\nx: `TorchScriptTensor(f32[4, 3, 512, 512])`,\np_trunk_patch_embed_proj_weight: `TorchScriptTensor(f32[1024, 3, 16, 16])`,\np_trunk_patch_embed_proj_bias: `TorchScriptTensor(f32[1024])`,\np_trunk_pos_embed: `TorchScriptTensor(f32[1, 1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_weight: `TorchScriptTensor(f32[3072, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_bias: `TorchScriptTensor(f32[3072])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_weight: `TorchScriptTensor(f32[1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_bias: `TorchScriptTensor(f32[1024])`,\n...\n)\n## Return values\n", + "text":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___1___norm1_weight[name=p_getattr_l__self___trunk_blocks___1___norm1_weight]. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"FxOnnxInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":414 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0008", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___1___norm1_bias[name=p_getattr_l__self___trunk_blocks___1___norm1_bias]. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature FxOnnxInterpreter.run_node\n- self: \n- node: fx.Node(p_getattr_l__self___trunk_blocks___1___norm1_bias)[placeholder]:Tensor(f32[1024])\n- fx_graph_module: torch.fx.GraphModule(timm_models_vision_transformer_VisionTransformer)\n- onnxfunction_dispatcher: \n- op_level_debug: False\n- onnxscript_graph: \n- onnxscript_tracer: \n- fx_name_to_onnxscript_value: Dict[length=17](\nx: `TorchScriptTensor(f32[4, 3, 512, 512])`,\np_trunk_patch_embed_proj_weight: `TorchScriptTensor(f32[1024, 3, 16, 16])`,\np_trunk_patch_embed_proj_bias: `TorchScriptTensor(f32[1024])`,\np_trunk_pos_embed: `TorchScriptTensor(f32[1, 1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_weight: `TorchScriptTensor(f32[3072, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_bias: `TorchScriptTensor(f32[3072])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_weight: `TorchScriptTensor(f32[1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_bias: `TorchScriptTensor(f32[1024])`,\n...\n)\n## Return values\n", + "text":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___1___norm1_bias[name=p_getattr_l__self___trunk_blocks___1___norm1_bias]. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"FxOnnxInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":414 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0008", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___1___attn_qkv_weight[name=p_getattr_l__self___trunk_blocks___1___attn_qkv_weight]. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature FxOnnxInterpreter.run_node\n- self: \n- node: fx.Node(p_getattr_l__self___trunk_blocks___1___attn_qkv_weight)[placeholder]:Tensor(f32[3072, 1024])\n- fx_graph_module: torch.fx.GraphModule(timm_models_vision_transformer_VisionTransformer)\n- onnxfunction_dispatcher: \n- op_level_debug: False\n- onnxscript_graph: \n- onnxscript_tracer: \n- fx_name_to_onnxscript_value: Dict[length=18](\nx: `TorchScriptTensor(f32[4, 3, 512, 512])`,\np_trunk_patch_embed_proj_weight: `TorchScriptTensor(f32[1024, 3, 16, 16])`,\np_trunk_patch_embed_proj_bias: `TorchScriptTensor(f32[1024])`,\np_trunk_pos_embed: `TorchScriptTensor(f32[1, 1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_weight: `TorchScriptTensor(f32[3072, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_bias: `TorchScriptTensor(f32[3072])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_weight: `TorchScriptTensor(f32[1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_bias: `TorchScriptTensor(f32[1024])`,\n...\n)\n## Return values\n", + "text":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___1___attn_qkv_weight[name=p_getattr_l__self___trunk_blocks___1___attn_qkv_weight]. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"FxOnnxInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":414 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0008", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___1___attn_qkv_bias[name=p_getattr_l__self___trunk_blocks___1___attn_qkv_bias]. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature FxOnnxInterpreter.run_node\n- self: \n- node: fx.Node(p_getattr_l__self___trunk_blocks___1___attn_qkv_bias)[placeholder]:Tensor(f32[3072])\n- fx_graph_module: torch.fx.GraphModule(timm_models_vision_transformer_VisionTransformer)\n- onnxfunction_dispatcher: \n- op_level_debug: False\n- onnxscript_graph: \n- onnxscript_tracer: \n- fx_name_to_onnxscript_value: Dict[length=19](\nx: `TorchScriptTensor(f32[4, 3, 512, 512])`,\np_trunk_patch_embed_proj_weight: `TorchScriptTensor(f32[1024, 3, 16, 16])`,\np_trunk_patch_embed_proj_bias: `TorchScriptTensor(f32[1024])`,\np_trunk_pos_embed: `TorchScriptTensor(f32[1, 1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_weight: `TorchScriptTensor(f32[3072, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_bias: `TorchScriptTensor(f32[3072])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_weight: `TorchScriptTensor(f32[1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_bias: `TorchScriptTensor(f32[1024])`,\n...\n)\n## Return values\n", + "text":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___1___attn_qkv_bias[name=p_getattr_l__self___trunk_blocks___1___attn_qkv_bias]. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"FxOnnxInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":414 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0008", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___1___attn_proj_weight[name=p_getattr_l__self___trunk_blocks___1___attn_proj_weight]. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature FxOnnxInterpreter.run_node\n- self: \n- node: fx.Node(p_getattr_l__self___trunk_blocks___1___attn_proj_weight)[placeholder]:Tensor(f32[1024, 1024])\n- fx_graph_module: torch.fx.GraphModule(timm_models_vision_transformer_VisionTransformer)\n- onnxfunction_dispatcher: \n- op_level_debug: False\n- onnxscript_graph: \n- onnxscript_tracer: \n- fx_name_to_onnxscript_value: Dict[length=20](\nx: `TorchScriptTensor(f32[4, 3, 512, 512])`,\np_trunk_patch_embed_proj_weight: `TorchScriptTensor(f32[1024, 3, 16, 16])`,\np_trunk_patch_embed_proj_bias: `TorchScriptTensor(f32[1024])`,\np_trunk_pos_embed: `TorchScriptTensor(f32[1, 1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_weight: `TorchScriptTensor(f32[3072, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_bias: `TorchScriptTensor(f32[3072])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_weight: `TorchScriptTensor(f32[1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_bias: `TorchScriptTensor(f32[1024])`,\n...\n)\n## Return values\n", + "text":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___1___attn_proj_weight[name=p_getattr_l__self___trunk_blocks___1___attn_proj_weight]. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"FxOnnxInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":414 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0008", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___1___attn_proj_bias[name=p_getattr_l__self___trunk_blocks___1___attn_proj_bias]. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature FxOnnxInterpreter.run_node\n- self: \n- node: fx.Node(p_getattr_l__self___trunk_blocks___1___attn_proj_bias)[placeholder]:Tensor(f32[1024])\n- fx_graph_module: torch.fx.GraphModule(timm_models_vision_transformer_VisionTransformer)\n- onnxfunction_dispatcher: \n- op_level_debug: False\n- onnxscript_graph: \n- onnxscript_tracer: \n- fx_name_to_onnxscript_value: Dict[length=21](\nx: `TorchScriptTensor(f32[4, 3, 512, 512])`,\np_trunk_patch_embed_proj_weight: `TorchScriptTensor(f32[1024, 3, 16, 16])`,\np_trunk_patch_embed_proj_bias: `TorchScriptTensor(f32[1024])`,\np_trunk_pos_embed: `TorchScriptTensor(f32[1, 1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_weight: `TorchScriptTensor(f32[3072, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_bias: `TorchScriptTensor(f32[3072])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_weight: `TorchScriptTensor(f32[1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_bias: `TorchScriptTensor(f32[1024])`,\n...\n)\n## Return values\n", + "text":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___1___attn_proj_bias[name=p_getattr_l__self___trunk_blocks___1___attn_proj_bias]. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"FxOnnxInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":414 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0008", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___1___norm2_weight[name=p_getattr_l__self___trunk_blocks___1___norm2_weight]. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature FxOnnxInterpreter.run_node\n- self: \n- node: fx.Node(p_getattr_l__self___trunk_blocks___1___norm2_weight)[placeholder]:Tensor(f32[1024])\n- fx_graph_module: torch.fx.GraphModule(timm_models_vision_transformer_VisionTransformer)\n- onnxfunction_dispatcher: \n- op_level_debug: False\n- onnxscript_graph: \n- onnxscript_tracer: \n- fx_name_to_onnxscript_value: Dict[length=22](\nx: `TorchScriptTensor(f32[4, 3, 512, 512])`,\np_trunk_patch_embed_proj_weight: `TorchScriptTensor(f32[1024, 3, 16, 16])`,\np_trunk_patch_embed_proj_bias: `TorchScriptTensor(f32[1024])`,\np_trunk_pos_embed: `TorchScriptTensor(f32[1, 1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_weight: `TorchScriptTensor(f32[3072, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_bias: `TorchScriptTensor(f32[3072])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_weight: `TorchScriptTensor(f32[1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_bias: `TorchScriptTensor(f32[1024])`,\n...\n)\n## Return values\n", + "text":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___1___norm2_weight[name=p_getattr_l__self___trunk_blocks___1___norm2_weight]. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"FxOnnxInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":414 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0008", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___1___norm2_bias[name=p_getattr_l__self___trunk_blocks___1___norm2_bias]. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature FxOnnxInterpreter.run_node\n- self: \n- node: fx.Node(p_getattr_l__self___trunk_blocks___1___norm2_bias)[placeholder]:Tensor(f32[1024])\n- fx_graph_module: torch.fx.GraphModule(timm_models_vision_transformer_VisionTransformer)\n- onnxfunction_dispatcher: \n- op_level_debug: False\n- onnxscript_graph: \n- onnxscript_tracer: \n- fx_name_to_onnxscript_value: Dict[length=23](\nx: `TorchScriptTensor(f32[4, 3, 512, 512])`,\np_trunk_patch_embed_proj_weight: `TorchScriptTensor(f32[1024, 3, 16, 16])`,\np_trunk_patch_embed_proj_bias: `TorchScriptTensor(f32[1024])`,\np_trunk_pos_embed: `TorchScriptTensor(f32[1, 1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_weight: `TorchScriptTensor(f32[3072, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_bias: `TorchScriptTensor(f32[3072])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_weight: `TorchScriptTensor(f32[1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_bias: `TorchScriptTensor(f32[1024])`,\n...\n)\n## Return values\n", + "text":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___1___norm2_bias[name=p_getattr_l__self___trunk_blocks___1___norm2_bias]. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"FxOnnxInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":414 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0008", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___1___mlp_fc1_weight[name=p_getattr_l__self___trunk_blocks___1___mlp_fc1_weight]. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature FxOnnxInterpreter.run_node\n- self: \n- node: fx.Node(p_getattr_l__self___trunk_blocks___1___mlp_fc1_weight)[placeholder]:Tensor(f32[4096, 1024])\n- fx_graph_module: torch.fx.GraphModule(timm_models_vision_transformer_VisionTransformer)\n- onnxfunction_dispatcher: \n- op_level_debug: False\n- onnxscript_graph: \n- onnxscript_tracer: \n- fx_name_to_onnxscript_value: Dict[length=24](\nx: `TorchScriptTensor(f32[4, 3, 512, 512])`,\np_trunk_patch_embed_proj_weight: `TorchScriptTensor(f32[1024, 3, 16, 16])`,\np_trunk_patch_embed_proj_bias: `TorchScriptTensor(f32[1024])`,\np_trunk_pos_embed: `TorchScriptTensor(f32[1, 1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_weight: `TorchScriptTensor(f32[3072, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_bias: `TorchScriptTensor(f32[3072])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_weight: `TorchScriptTensor(f32[1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_bias: `TorchScriptTensor(f32[1024])`,\n...\n)\n## Return values\n", + "text":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___1___mlp_fc1_weight[name=p_getattr_l__self___trunk_blocks___1___mlp_fc1_weight]. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"FxOnnxInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":414 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0008", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___1___mlp_fc1_bias[name=p_getattr_l__self___trunk_blocks___1___mlp_fc1_bias]. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature FxOnnxInterpreter.run_node\n- self: \n- node: fx.Node(p_getattr_l__self___trunk_blocks___1___mlp_fc1_bias)[placeholder]:Tensor(f32[4096])\n- fx_graph_module: torch.fx.GraphModule(timm_models_vision_transformer_VisionTransformer)\n- onnxfunction_dispatcher: \n- op_level_debug: False\n- onnxscript_graph: \n- onnxscript_tracer: \n- fx_name_to_onnxscript_value: Dict[length=25](\nx: `TorchScriptTensor(f32[4, 3, 512, 512])`,\np_trunk_patch_embed_proj_weight: `TorchScriptTensor(f32[1024, 3, 16, 16])`,\np_trunk_patch_embed_proj_bias: `TorchScriptTensor(f32[1024])`,\np_trunk_pos_embed: `TorchScriptTensor(f32[1, 1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_weight: `TorchScriptTensor(f32[3072, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_bias: `TorchScriptTensor(f32[3072])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_weight: `TorchScriptTensor(f32[1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_bias: `TorchScriptTensor(f32[1024])`,\n...\n)\n## Return values\n", + "text":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___1___mlp_fc1_bias[name=p_getattr_l__self___trunk_blocks___1___mlp_fc1_bias]. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"FxOnnxInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":414 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0008", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___1___mlp_fc2_weight[name=p_getattr_l__self___trunk_blocks___1___mlp_fc2_weight]. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature FxOnnxInterpreter.run_node\n- self: \n- node: fx.Node(p_getattr_l__self___trunk_blocks___1___mlp_fc2_weight)[placeholder]:Tensor(f32[1024, 4096])\n- fx_graph_module: torch.fx.GraphModule(timm_models_vision_transformer_VisionTransformer)\n- onnxfunction_dispatcher: \n- op_level_debug: False\n- onnxscript_graph: \n- onnxscript_tracer: \n- fx_name_to_onnxscript_value: Dict[length=26](\nx: `TorchScriptTensor(f32[4, 3, 512, 512])`,\np_trunk_patch_embed_proj_weight: `TorchScriptTensor(f32[1024, 3, 16, 16])`,\np_trunk_patch_embed_proj_bias: `TorchScriptTensor(f32[1024])`,\np_trunk_pos_embed: `TorchScriptTensor(f32[1, 1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_weight: `TorchScriptTensor(f32[3072, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_bias: `TorchScriptTensor(f32[3072])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_weight: `TorchScriptTensor(f32[1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_bias: `TorchScriptTensor(f32[1024])`,\n...\n)\n## Return values\n", + "text":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___1___mlp_fc2_weight[name=p_getattr_l__self___trunk_blocks___1___mlp_fc2_weight]. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"FxOnnxInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":414 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0008", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___1___mlp_fc2_bias[name=p_getattr_l__self___trunk_blocks___1___mlp_fc2_bias]. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature FxOnnxInterpreter.run_node\n- self: \n- node: fx.Node(p_getattr_l__self___trunk_blocks___1___mlp_fc2_bias)[placeholder]:Tensor(f32[1024])\n- fx_graph_module: torch.fx.GraphModule(timm_models_vision_transformer_VisionTransformer)\n- onnxfunction_dispatcher: \n- op_level_debug: False\n- onnxscript_graph: \n- onnxscript_tracer: \n- fx_name_to_onnxscript_value: Dict[length=27](\nx: `TorchScriptTensor(f32[4, 3, 512, 512])`,\np_trunk_patch_embed_proj_weight: `TorchScriptTensor(f32[1024, 3, 16, 16])`,\np_trunk_patch_embed_proj_bias: `TorchScriptTensor(f32[1024])`,\np_trunk_pos_embed: `TorchScriptTensor(f32[1, 1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_weight: `TorchScriptTensor(f32[3072, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_bias: `TorchScriptTensor(f32[3072])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_weight: `TorchScriptTensor(f32[1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_bias: `TorchScriptTensor(f32[1024])`,\n...\n)\n## Return values\n", + "text":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___1___mlp_fc2_bias[name=p_getattr_l__self___trunk_blocks___1___mlp_fc2_bias]. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"FxOnnxInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":414 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0008", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___2___norm1_weight[name=p_getattr_l__self___trunk_blocks___2___norm1_weight]. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature FxOnnxInterpreter.run_node\n- self: \n- node: fx.Node(p_getattr_l__self___trunk_blocks___2___norm1_weight)[placeholder]:Tensor(f32[1024])\n- fx_graph_module: torch.fx.GraphModule(timm_models_vision_transformer_VisionTransformer)\n- onnxfunction_dispatcher: \n- op_level_debug: False\n- onnxscript_graph: \n- onnxscript_tracer: \n- fx_name_to_onnxscript_value: Dict[length=28](\nx: `TorchScriptTensor(f32[4, 3, 512, 512])`,\np_trunk_patch_embed_proj_weight: `TorchScriptTensor(f32[1024, 3, 16, 16])`,\np_trunk_patch_embed_proj_bias: `TorchScriptTensor(f32[1024])`,\np_trunk_pos_embed: `TorchScriptTensor(f32[1, 1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_weight: `TorchScriptTensor(f32[3072, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_bias: `TorchScriptTensor(f32[3072])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_weight: `TorchScriptTensor(f32[1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_bias: `TorchScriptTensor(f32[1024])`,\n...\n)\n## Return values\n", + "text":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___2___norm1_weight[name=p_getattr_l__self___trunk_blocks___2___norm1_weight]. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"FxOnnxInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":414 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0008", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___2___norm1_bias[name=p_getattr_l__self___trunk_blocks___2___norm1_bias]. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature FxOnnxInterpreter.run_node\n- self: \n- node: fx.Node(p_getattr_l__self___trunk_blocks___2___norm1_bias)[placeholder]:Tensor(f32[1024])\n- fx_graph_module: torch.fx.GraphModule(timm_models_vision_transformer_VisionTransformer)\n- onnxfunction_dispatcher: \n- op_level_debug: False\n- onnxscript_graph: \n- onnxscript_tracer: \n- fx_name_to_onnxscript_value: Dict[length=29](\nx: `TorchScriptTensor(f32[4, 3, 512, 512])`,\np_trunk_patch_embed_proj_weight: `TorchScriptTensor(f32[1024, 3, 16, 16])`,\np_trunk_patch_embed_proj_bias: `TorchScriptTensor(f32[1024])`,\np_trunk_pos_embed: `TorchScriptTensor(f32[1, 1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_weight: `TorchScriptTensor(f32[3072, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_bias: `TorchScriptTensor(f32[3072])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_weight: `TorchScriptTensor(f32[1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_bias: `TorchScriptTensor(f32[1024])`,\n...\n)\n## Return values\n", + "text":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___2___norm1_bias[name=p_getattr_l__self___trunk_blocks___2___norm1_bias]. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"FxOnnxInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":414 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0008", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___2___attn_qkv_weight[name=p_getattr_l__self___trunk_blocks___2___attn_qkv_weight]. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature FxOnnxInterpreter.run_node\n- self: \n- node: fx.Node(p_getattr_l__self___trunk_blocks___2___attn_qkv_weight)[placeholder]:Tensor(f32[3072, 1024])\n- fx_graph_module: torch.fx.GraphModule(timm_models_vision_transformer_VisionTransformer)\n- onnxfunction_dispatcher: \n- op_level_debug: False\n- onnxscript_graph: \n- onnxscript_tracer: \n- fx_name_to_onnxscript_value: Dict[length=30](\nx: `TorchScriptTensor(f32[4, 3, 512, 512])`,\np_trunk_patch_embed_proj_weight: `TorchScriptTensor(f32[1024, 3, 16, 16])`,\np_trunk_patch_embed_proj_bias: `TorchScriptTensor(f32[1024])`,\np_trunk_pos_embed: `TorchScriptTensor(f32[1, 1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_weight: `TorchScriptTensor(f32[3072, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_bias: `TorchScriptTensor(f32[3072])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_weight: `TorchScriptTensor(f32[1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_bias: `TorchScriptTensor(f32[1024])`,\n...\n)\n## Return values\n", + "text":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___2___attn_qkv_weight[name=p_getattr_l__self___trunk_blocks___2___attn_qkv_weight]. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"FxOnnxInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":414 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0008", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___2___attn_qkv_bias[name=p_getattr_l__self___trunk_blocks___2___attn_qkv_bias]. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature FxOnnxInterpreter.run_node\n- self: \n- node: fx.Node(p_getattr_l__self___trunk_blocks___2___attn_qkv_bias)[placeholder]:Tensor(f32[3072])\n- fx_graph_module: torch.fx.GraphModule(timm_models_vision_transformer_VisionTransformer)\n- onnxfunction_dispatcher: \n- op_level_debug: False\n- onnxscript_graph: \n- onnxscript_tracer: \n- fx_name_to_onnxscript_value: Dict[length=31](\nx: `TorchScriptTensor(f32[4, 3, 512, 512])`,\np_trunk_patch_embed_proj_weight: `TorchScriptTensor(f32[1024, 3, 16, 16])`,\np_trunk_patch_embed_proj_bias: `TorchScriptTensor(f32[1024])`,\np_trunk_pos_embed: `TorchScriptTensor(f32[1, 1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_weight: `TorchScriptTensor(f32[3072, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_bias: `TorchScriptTensor(f32[3072])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_weight: `TorchScriptTensor(f32[1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_bias: `TorchScriptTensor(f32[1024])`,\n...\n)\n## Return values\n", + "text":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___2___attn_qkv_bias[name=p_getattr_l__self___trunk_blocks___2___attn_qkv_bias]. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"FxOnnxInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":414 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0008", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___2___attn_proj_weight[name=p_getattr_l__self___trunk_blocks___2___attn_proj_weight]. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature FxOnnxInterpreter.run_node\n- self: \n- node: fx.Node(p_getattr_l__self___trunk_blocks___2___attn_proj_weight)[placeholder]:Tensor(f32[1024, 1024])\n- fx_graph_module: torch.fx.GraphModule(timm_models_vision_transformer_VisionTransformer)\n- onnxfunction_dispatcher: \n- op_level_debug: False\n- onnxscript_graph: \n- onnxscript_tracer: \n- fx_name_to_onnxscript_value: Dict[length=32](\nx: `TorchScriptTensor(f32[4, 3, 512, 512])`,\np_trunk_patch_embed_proj_weight: `TorchScriptTensor(f32[1024, 3, 16, 16])`,\np_trunk_patch_embed_proj_bias: `TorchScriptTensor(f32[1024])`,\np_trunk_pos_embed: `TorchScriptTensor(f32[1, 1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_weight: `TorchScriptTensor(f32[3072, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_bias: `TorchScriptTensor(f32[3072])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_weight: `TorchScriptTensor(f32[1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_bias: `TorchScriptTensor(f32[1024])`,\n...\n)\n## Return values\n", + "text":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___2___attn_proj_weight[name=p_getattr_l__self___trunk_blocks___2___attn_proj_weight]. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"FxOnnxInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":414 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0008", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___2___attn_proj_bias[name=p_getattr_l__self___trunk_blocks___2___attn_proj_bias]. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature FxOnnxInterpreter.run_node\n- self: \n- node: fx.Node(p_getattr_l__self___trunk_blocks___2___attn_proj_bias)[placeholder]:Tensor(f32[1024])\n- fx_graph_module: torch.fx.GraphModule(timm_models_vision_transformer_VisionTransformer)\n- onnxfunction_dispatcher: \n- op_level_debug: False\n- onnxscript_graph: \n- onnxscript_tracer: \n- fx_name_to_onnxscript_value: Dict[length=33](\nx: `TorchScriptTensor(f32[4, 3, 512, 512])`,\np_trunk_patch_embed_proj_weight: `TorchScriptTensor(f32[1024, 3, 16, 16])`,\np_trunk_patch_embed_proj_bias: `TorchScriptTensor(f32[1024])`,\np_trunk_pos_embed: `TorchScriptTensor(f32[1, 1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_weight: `TorchScriptTensor(f32[3072, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_bias: `TorchScriptTensor(f32[3072])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_weight: `TorchScriptTensor(f32[1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_bias: `TorchScriptTensor(f32[1024])`,\n...\n)\n## Return values\n", + "text":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___2___attn_proj_bias[name=p_getattr_l__self___trunk_blocks___2___attn_proj_bias]. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"FxOnnxInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":414 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0008", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___2___norm2_weight[name=p_getattr_l__self___trunk_blocks___2___norm2_weight]. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature FxOnnxInterpreter.run_node\n- self: \n- node: fx.Node(p_getattr_l__self___trunk_blocks___2___norm2_weight)[placeholder]:Tensor(f32[1024])\n- fx_graph_module: torch.fx.GraphModule(timm_models_vision_transformer_VisionTransformer)\n- onnxfunction_dispatcher: \n- op_level_debug: False\n- onnxscript_graph: \n- onnxscript_tracer: \n- fx_name_to_onnxscript_value: Dict[length=34](\nx: `TorchScriptTensor(f32[4, 3, 512, 512])`,\np_trunk_patch_embed_proj_weight: `TorchScriptTensor(f32[1024, 3, 16, 16])`,\np_trunk_patch_embed_proj_bias: `TorchScriptTensor(f32[1024])`,\np_trunk_pos_embed: `TorchScriptTensor(f32[1, 1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_weight: `TorchScriptTensor(f32[3072, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_bias: `TorchScriptTensor(f32[3072])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_weight: `TorchScriptTensor(f32[1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_bias: `TorchScriptTensor(f32[1024])`,\n...\n)\n## Return values\n", + "text":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___2___norm2_weight[name=p_getattr_l__self___trunk_blocks___2___norm2_weight]. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"FxOnnxInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":414 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0008", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___2___norm2_bias[name=p_getattr_l__self___trunk_blocks___2___norm2_bias]. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature FxOnnxInterpreter.run_node\n- self: \n- node: fx.Node(p_getattr_l__self___trunk_blocks___2___norm2_bias)[placeholder]:Tensor(f32[1024])\n- fx_graph_module: torch.fx.GraphModule(timm_models_vision_transformer_VisionTransformer)\n- onnxfunction_dispatcher: \n- op_level_debug: False\n- onnxscript_graph: \n- onnxscript_tracer: \n- fx_name_to_onnxscript_value: Dict[length=35](\nx: `TorchScriptTensor(f32[4, 3, 512, 512])`,\np_trunk_patch_embed_proj_weight: `TorchScriptTensor(f32[1024, 3, 16, 16])`,\np_trunk_patch_embed_proj_bias: `TorchScriptTensor(f32[1024])`,\np_trunk_pos_embed: `TorchScriptTensor(f32[1, 1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_weight: `TorchScriptTensor(f32[3072, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_bias: `TorchScriptTensor(f32[3072])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_weight: `TorchScriptTensor(f32[1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_bias: `TorchScriptTensor(f32[1024])`,\n...\n)\n## Return values\n", + "text":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___2___norm2_bias[name=p_getattr_l__self___trunk_blocks___2___norm2_bias]. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"FxOnnxInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":414 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0008", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___2___mlp_fc1_weight[name=p_getattr_l__self___trunk_blocks___2___mlp_fc1_weight]. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature FxOnnxInterpreter.run_node\n- self: \n- node: fx.Node(p_getattr_l__self___trunk_blocks___2___mlp_fc1_weight)[placeholder]:Tensor(f32[4096, 1024])\n- fx_graph_module: torch.fx.GraphModule(timm_models_vision_transformer_VisionTransformer)\n- onnxfunction_dispatcher: \n- op_level_debug: False\n- onnxscript_graph: \n- onnxscript_tracer: \n- fx_name_to_onnxscript_value: Dict[length=36](\nx: `TorchScriptTensor(f32[4, 3, 512, 512])`,\np_trunk_patch_embed_proj_weight: `TorchScriptTensor(f32[1024, 3, 16, 16])`,\np_trunk_patch_embed_proj_bias: `TorchScriptTensor(f32[1024])`,\np_trunk_pos_embed: `TorchScriptTensor(f32[1, 1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_weight: `TorchScriptTensor(f32[3072, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_bias: `TorchScriptTensor(f32[3072])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_weight: `TorchScriptTensor(f32[1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_bias: `TorchScriptTensor(f32[1024])`,\n...\n)\n## Return values\n", + "text":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___2___mlp_fc1_weight[name=p_getattr_l__self___trunk_blocks___2___mlp_fc1_weight]. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"FxOnnxInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":414 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0008", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___2___mlp_fc1_bias[name=p_getattr_l__self___trunk_blocks___2___mlp_fc1_bias]. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature FxOnnxInterpreter.run_node\n- self: \n- node: fx.Node(p_getattr_l__self___trunk_blocks___2___mlp_fc1_bias)[placeholder]:Tensor(f32[4096])\n- fx_graph_module: torch.fx.GraphModule(timm_models_vision_transformer_VisionTransformer)\n- onnxfunction_dispatcher: \n- op_level_debug: False\n- onnxscript_graph: \n- onnxscript_tracer: \n- fx_name_to_onnxscript_value: Dict[length=37](\nx: `TorchScriptTensor(f32[4, 3, 512, 512])`,\np_trunk_patch_embed_proj_weight: `TorchScriptTensor(f32[1024, 3, 16, 16])`,\np_trunk_patch_embed_proj_bias: `TorchScriptTensor(f32[1024])`,\np_trunk_pos_embed: `TorchScriptTensor(f32[1, 1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_weight: `TorchScriptTensor(f32[3072, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_bias: `TorchScriptTensor(f32[3072])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_weight: `TorchScriptTensor(f32[1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_bias: `TorchScriptTensor(f32[1024])`,\n...\n)\n## Return values\n", + "text":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___2___mlp_fc1_bias[name=p_getattr_l__self___trunk_blocks___2___mlp_fc1_bias]. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"FxOnnxInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":414 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0008", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___2___mlp_fc2_weight[name=p_getattr_l__self___trunk_blocks___2___mlp_fc2_weight]. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature FxOnnxInterpreter.run_node\n- self: \n- node: fx.Node(p_getattr_l__self___trunk_blocks___2___mlp_fc2_weight)[placeholder]:Tensor(f32[1024, 4096])\n- fx_graph_module: torch.fx.GraphModule(timm_models_vision_transformer_VisionTransformer)\n- onnxfunction_dispatcher: \n- op_level_debug: False\n- onnxscript_graph: \n- onnxscript_tracer: \n- fx_name_to_onnxscript_value: Dict[length=38](\nx: `TorchScriptTensor(f32[4, 3, 512, 512])`,\np_trunk_patch_embed_proj_weight: `TorchScriptTensor(f32[1024, 3, 16, 16])`,\np_trunk_patch_embed_proj_bias: `TorchScriptTensor(f32[1024])`,\np_trunk_pos_embed: `TorchScriptTensor(f32[1, 1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_weight: `TorchScriptTensor(f32[3072, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_bias: `TorchScriptTensor(f32[3072])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_weight: `TorchScriptTensor(f32[1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_bias: `TorchScriptTensor(f32[1024])`,\n...\n)\n## Return values\n", + "text":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___2___mlp_fc2_weight[name=p_getattr_l__self___trunk_blocks___2___mlp_fc2_weight]. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"FxOnnxInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":414 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0008", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___2___mlp_fc2_bias[name=p_getattr_l__self___trunk_blocks___2___mlp_fc2_bias]. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature FxOnnxInterpreter.run_node\n- self: \n- node: fx.Node(p_getattr_l__self___trunk_blocks___2___mlp_fc2_bias)[placeholder]:Tensor(f32[1024])\n- fx_graph_module: torch.fx.GraphModule(timm_models_vision_transformer_VisionTransformer)\n- onnxfunction_dispatcher: \n- op_level_debug: False\n- onnxscript_graph: \n- onnxscript_tracer: \n- fx_name_to_onnxscript_value: Dict[length=39](\nx: `TorchScriptTensor(f32[4, 3, 512, 512])`,\np_trunk_patch_embed_proj_weight: `TorchScriptTensor(f32[1024, 3, 16, 16])`,\np_trunk_patch_embed_proj_bias: `TorchScriptTensor(f32[1024])`,\np_trunk_pos_embed: `TorchScriptTensor(f32[1, 1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_weight: `TorchScriptTensor(f32[3072, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_bias: `TorchScriptTensor(f32[3072])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_weight: `TorchScriptTensor(f32[1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_bias: `TorchScriptTensor(f32[1024])`,\n...\n)\n## Return values\n", + "text":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___2___mlp_fc2_bias[name=p_getattr_l__self___trunk_blocks___2___mlp_fc2_bias]. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"FxOnnxInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":414 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0008", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___3___norm1_weight[name=p_getattr_l__self___trunk_blocks___3___norm1_weight]. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature FxOnnxInterpreter.run_node\n- self: \n- node: fx.Node(p_getattr_l__self___trunk_blocks___3___norm1_weight)[placeholder]:Tensor(f32[1024])\n- fx_graph_module: torch.fx.GraphModule(timm_models_vision_transformer_VisionTransformer)\n- onnxfunction_dispatcher: \n- op_level_debug: False\n- onnxscript_graph: \n- onnxscript_tracer: \n- fx_name_to_onnxscript_value: Dict[length=40](\nx: `TorchScriptTensor(f32[4, 3, 512, 512])`,\np_trunk_patch_embed_proj_weight: `TorchScriptTensor(f32[1024, 3, 16, 16])`,\np_trunk_patch_embed_proj_bias: `TorchScriptTensor(f32[1024])`,\np_trunk_pos_embed: `TorchScriptTensor(f32[1, 1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_weight: `TorchScriptTensor(f32[3072, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_bias: `TorchScriptTensor(f32[3072])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_weight: `TorchScriptTensor(f32[1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_bias: `TorchScriptTensor(f32[1024])`,\n...\n)\n## Return values\n", + "text":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___3___norm1_weight[name=p_getattr_l__self___trunk_blocks___3___norm1_weight]. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"FxOnnxInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":414 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0008", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___3___norm1_bias[name=p_getattr_l__self___trunk_blocks___3___norm1_bias]. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature FxOnnxInterpreter.run_node\n- self: \n- node: fx.Node(p_getattr_l__self___trunk_blocks___3___norm1_bias)[placeholder]:Tensor(f32[1024])\n- fx_graph_module: torch.fx.GraphModule(timm_models_vision_transformer_VisionTransformer)\n- onnxfunction_dispatcher: \n- op_level_debug: False\n- onnxscript_graph: \n- onnxscript_tracer: \n- fx_name_to_onnxscript_value: Dict[length=41](\nx: `TorchScriptTensor(f32[4, 3, 512, 512])`,\np_trunk_patch_embed_proj_weight: `TorchScriptTensor(f32[1024, 3, 16, 16])`,\np_trunk_patch_embed_proj_bias: `TorchScriptTensor(f32[1024])`,\np_trunk_pos_embed: `TorchScriptTensor(f32[1, 1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_weight: `TorchScriptTensor(f32[3072, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_bias: `TorchScriptTensor(f32[3072])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_weight: `TorchScriptTensor(f32[1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_bias: `TorchScriptTensor(f32[1024])`,\n...\n)\n## Return values\n", + "text":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___3___norm1_bias[name=p_getattr_l__self___trunk_blocks___3___norm1_bias]. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"FxOnnxInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":414 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0008", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___3___attn_qkv_weight[name=p_getattr_l__self___trunk_blocks___3___attn_qkv_weight]. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature FxOnnxInterpreter.run_node\n- self: \n- node: fx.Node(p_getattr_l__self___trunk_blocks___3___attn_qkv_weight)[placeholder]:Tensor(f32[3072, 1024])\n- fx_graph_module: torch.fx.GraphModule(timm_models_vision_transformer_VisionTransformer)\n- onnxfunction_dispatcher: \n- op_level_debug: False\n- onnxscript_graph: \n- onnxscript_tracer: \n- fx_name_to_onnxscript_value: Dict[length=42](\nx: `TorchScriptTensor(f32[4, 3, 512, 512])`,\np_trunk_patch_embed_proj_weight: `TorchScriptTensor(f32[1024, 3, 16, 16])`,\np_trunk_patch_embed_proj_bias: `TorchScriptTensor(f32[1024])`,\np_trunk_pos_embed: `TorchScriptTensor(f32[1, 1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_weight: `TorchScriptTensor(f32[3072, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_bias: `TorchScriptTensor(f32[3072])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_weight: `TorchScriptTensor(f32[1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_bias: `TorchScriptTensor(f32[1024])`,\n...\n)\n## Return values\n", + "text":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___3___attn_qkv_weight[name=p_getattr_l__self___trunk_blocks___3___attn_qkv_weight]. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"FxOnnxInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":414 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0008", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___3___attn_qkv_bias[name=p_getattr_l__self___trunk_blocks___3___attn_qkv_bias]. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature FxOnnxInterpreter.run_node\n- self: \n- node: fx.Node(p_getattr_l__self___trunk_blocks___3___attn_qkv_bias)[placeholder]:Tensor(f32[3072])\n- fx_graph_module: torch.fx.GraphModule(timm_models_vision_transformer_VisionTransformer)\n- onnxfunction_dispatcher: \n- op_level_debug: False\n- onnxscript_graph: \n- onnxscript_tracer: \n- fx_name_to_onnxscript_value: Dict[length=43](\nx: `TorchScriptTensor(f32[4, 3, 512, 512])`,\np_trunk_patch_embed_proj_weight: `TorchScriptTensor(f32[1024, 3, 16, 16])`,\np_trunk_patch_embed_proj_bias: `TorchScriptTensor(f32[1024])`,\np_trunk_pos_embed: `TorchScriptTensor(f32[1, 1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_weight: `TorchScriptTensor(f32[3072, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_bias: `TorchScriptTensor(f32[3072])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_weight: `TorchScriptTensor(f32[1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_bias: `TorchScriptTensor(f32[1024])`,\n...\n)\n## Return values\n", + "text":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___3___attn_qkv_bias[name=p_getattr_l__self___trunk_blocks___3___attn_qkv_bias]. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"FxOnnxInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":414 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0008", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___3___attn_proj_weight[name=p_getattr_l__self___trunk_blocks___3___attn_proj_weight]. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature FxOnnxInterpreter.run_node\n- self: \n- node: fx.Node(p_getattr_l__self___trunk_blocks___3___attn_proj_weight)[placeholder]:Tensor(f32[1024, 1024])\n- fx_graph_module: torch.fx.GraphModule(timm_models_vision_transformer_VisionTransformer)\n- onnxfunction_dispatcher: \n- op_level_debug: False\n- onnxscript_graph: \n- onnxscript_tracer: \n- fx_name_to_onnxscript_value: Dict[length=44](\nx: `TorchScriptTensor(f32[4, 3, 512, 512])`,\np_trunk_patch_embed_proj_weight: `TorchScriptTensor(f32[1024, 3, 16, 16])`,\np_trunk_patch_embed_proj_bias: `TorchScriptTensor(f32[1024])`,\np_trunk_pos_embed: `TorchScriptTensor(f32[1, 1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_weight: `TorchScriptTensor(f32[3072, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_bias: `TorchScriptTensor(f32[3072])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_weight: `TorchScriptTensor(f32[1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_bias: `TorchScriptTensor(f32[1024])`,\n...\n)\n## Return values\n", + "text":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___3___attn_proj_weight[name=p_getattr_l__self___trunk_blocks___3___attn_proj_weight]. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"FxOnnxInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":414 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0008", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___3___attn_proj_bias[name=p_getattr_l__self___trunk_blocks___3___attn_proj_bias]. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature FxOnnxInterpreter.run_node\n- self: \n- node: fx.Node(p_getattr_l__self___trunk_blocks___3___attn_proj_bias)[placeholder]:Tensor(f32[1024])\n- fx_graph_module: torch.fx.GraphModule(timm_models_vision_transformer_VisionTransformer)\n- onnxfunction_dispatcher: \n- op_level_debug: False\n- onnxscript_graph: \n- onnxscript_tracer: \n- fx_name_to_onnxscript_value: Dict[length=45](\nx: `TorchScriptTensor(f32[4, 3, 512, 512])`,\np_trunk_patch_embed_proj_weight: `TorchScriptTensor(f32[1024, 3, 16, 16])`,\np_trunk_patch_embed_proj_bias: `TorchScriptTensor(f32[1024])`,\np_trunk_pos_embed: `TorchScriptTensor(f32[1, 1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_weight: `TorchScriptTensor(f32[3072, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_bias: `TorchScriptTensor(f32[3072])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_weight: `TorchScriptTensor(f32[1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_bias: `TorchScriptTensor(f32[1024])`,\n...\n)\n## Return values\n", + "text":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___3___attn_proj_bias[name=p_getattr_l__self___trunk_blocks___3___attn_proj_bias]. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"FxOnnxInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":414 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0008", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___3___norm2_weight[name=p_getattr_l__self___trunk_blocks___3___norm2_weight]. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature FxOnnxInterpreter.run_node\n- self: \n- node: fx.Node(p_getattr_l__self___trunk_blocks___3___norm2_weight)[placeholder]:Tensor(f32[1024])\n- fx_graph_module: torch.fx.GraphModule(timm_models_vision_transformer_VisionTransformer)\n- onnxfunction_dispatcher: \n- op_level_debug: False\n- onnxscript_graph: \n- onnxscript_tracer: \n- fx_name_to_onnxscript_value: Dict[length=46](\nx: `TorchScriptTensor(f32[4, 3, 512, 512])`,\np_trunk_patch_embed_proj_weight: `TorchScriptTensor(f32[1024, 3, 16, 16])`,\np_trunk_patch_embed_proj_bias: `TorchScriptTensor(f32[1024])`,\np_trunk_pos_embed: `TorchScriptTensor(f32[1, 1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_weight: `TorchScriptTensor(f32[3072, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_bias: `TorchScriptTensor(f32[3072])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_weight: `TorchScriptTensor(f32[1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_bias: `TorchScriptTensor(f32[1024])`,\n...\n)\n## Return values\n", + "text":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___3___norm2_weight[name=p_getattr_l__self___trunk_blocks___3___norm2_weight]. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"FxOnnxInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":414 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0008", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___3___norm2_bias[name=p_getattr_l__self___trunk_blocks___3___norm2_bias]. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature FxOnnxInterpreter.run_node\n- self: \n- node: fx.Node(p_getattr_l__self___trunk_blocks___3___norm2_bias)[placeholder]:Tensor(f32[1024])\n- fx_graph_module: torch.fx.GraphModule(timm_models_vision_transformer_VisionTransformer)\n- onnxfunction_dispatcher: \n- op_level_debug: False\n- onnxscript_graph: \n- onnxscript_tracer: \n- fx_name_to_onnxscript_value: Dict[length=47](\nx: `TorchScriptTensor(f32[4, 3, 512, 512])`,\np_trunk_patch_embed_proj_weight: `TorchScriptTensor(f32[1024, 3, 16, 16])`,\np_trunk_patch_embed_proj_bias: `TorchScriptTensor(f32[1024])`,\np_trunk_pos_embed: `TorchScriptTensor(f32[1, 1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_weight: `TorchScriptTensor(f32[3072, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_bias: `TorchScriptTensor(f32[3072])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_weight: `TorchScriptTensor(f32[1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_bias: `TorchScriptTensor(f32[1024])`,\n...\n)\n## Return values\n", + "text":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___3___norm2_bias[name=p_getattr_l__self___trunk_blocks___3___norm2_bias]. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"FxOnnxInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":414 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0008", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___3___mlp_fc1_weight[name=p_getattr_l__self___trunk_blocks___3___mlp_fc1_weight]. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature FxOnnxInterpreter.run_node\n- self: \n- node: fx.Node(p_getattr_l__self___trunk_blocks___3___mlp_fc1_weight)[placeholder]:Tensor(f32[4096, 1024])\n- fx_graph_module: torch.fx.GraphModule(timm_models_vision_transformer_VisionTransformer)\n- onnxfunction_dispatcher: \n- op_level_debug: False\n- onnxscript_graph: \n- onnxscript_tracer: \n- fx_name_to_onnxscript_value: Dict[length=48](\nx: `TorchScriptTensor(f32[4, 3, 512, 512])`,\np_trunk_patch_embed_proj_weight: `TorchScriptTensor(f32[1024, 3, 16, 16])`,\np_trunk_patch_embed_proj_bias: `TorchScriptTensor(f32[1024])`,\np_trunk_pos_embed: `TorchScriptTensor(f32[1, 1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_weight: `TorchScriptTensor(f32[3072, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_bias: `TorchScriptTensor(f32[3072])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_weight: `TorchScriptTensor(f32[1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_bias: `TorchScriptTensor(f32[1024])`,\n...\n)\n## Return values\n", + "text":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___3___mlp_fc1_weight[name=p_getattr_l__self___trunk_blocks___3___mlp_fc1_weight]. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"FxOnnxInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":414 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0008", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___3___mlp_fc1_bias[name=p_getattr_l__self___trunk_blocks___3___mlp_fc1_bias]. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature FxOnnxInterpreter.run_node\n- self: \n- node: fx.Node(p_getattr_l__self___trunk_blocks___3___mlp_fc1_bias)[placeholder]:Tensor(f32[4096])\n- fx_graph_module: torch.fx.GraphModule(timm_models_vision_transformer_VisionTransformer)\n- onnxfunction_dispatcher: \n- op_level_debug: False\n- onnxscript_graph: \n- onnxscript_tracer: \n- fx_name_to_onnxscript_value: Dict[length=49](\nx: `TorchScriptTensor(f32[4, 3, 512, 512])`,\np_trunk_patch_embed_proj_weight: `TorchScriptTensor(f32[1024, 3, 16, 16])`,\np_trunk_patch_embed_proj_bias: `TorchScriptTensor(f32[1024])`,\np_trunk_pos_embed: `TorchScriptTensor(f32[1, 1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_weight: `TorchScriptTensor(f32[3072, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_bias: `TorchScriptTensor(f32[3072])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_weight: `TorchScriptTensor(f32[1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_bias: `TorchScriptTensor(f32[1024])`,\n...\n)\n## Return values\n", + "text":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___3___mlp_fc1_bias[name=p_getattr_l__self___trunk_blocks___3___mlp_fc1_bias]. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"FxOnnxInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":414 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0008", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___3___mlp_fc2_weight[name=p_getattr_l__self___trunk_blocks___3___mlp_fc2_weight]. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature FxOnnxInterpreter.run_node\n- self: \n- node: fx.Node(p_getattr_l__self___trunk_blocks___3___mlp_fc2_weight)[placeholder]:Tensor(f32[1024, 4096])\n- fx_graph_module: torch.fx.GraphModule(timm_models_vision_transformer_VisionTransformer)\n- onnxfunction_dispatcher: \n- op_level_debug: False\n- onnxscript_graph: \n- onnxscript_tracer: \n- fx_name_to_onnxscript_value: Dict[length=50](\nx: `TorchScriptTensor(f32[4, 3, 512, 512])`,\np_trunk_patch_embed_proj_weight: `TorchScriptTensor(f32[1024, 3, 16, 16])`,\np_trunk_patch_embed_proj_bias: `TorchScriptTensor(f32[1024])`,\np_trunk_pos_embed: `TorchScriptTensor(f32[1, 1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_weight: `TorchScriptTensor(f32[3072, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_bias: `TorchScriptTensor(f32[3072])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_weight: `TorchScriptTensor(f32[1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_bias: `TorchScriptTensor(f32[1024])`,\n...\n)\n## Return values\n", + "text":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___3___mlp_fc2_weight[name=p_getattr_l__self___trunk_blocks___3___mlp_fc2_weight]. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"FxOnnxInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":414 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0008", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___3___mlp_fc2_bias[name=p_getattr_l__self___trunk_blocks___3___mlp_fc2_bias]. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature FxOnnxInterpreter.run_node\n- self: \n- node: fx.Node(p_getattr_l__self___trunk_blocks___3___mlp_fc2_bias)[placeholder]:Tensor(f32[1024])\n- fx_graph_module: torch.fx.GraphModule(timm_models_vision_transformer_VisionTransformer)\n- onnxfunction_dispatcher: \n- op_level_debug: False\n- onnxscript_graph: \n- onnxscript_tracer: \n- fx_name_to_onnxscript_value: Dict[length=51](\nx: `TorchScriptTensor(f32[4, 3, 512, 512])`,\np_trunk_patch_embed_proj_weight: `TorchScriptTensor(f32[1024, 3, 16, 16])`,\np_trunk_patch_embed_proj_bias: `TorchScriptTensor(f32[1024])`,\np_trunk_pos_embed: `TorchScriptTensor(f32[1, 1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_weight: `TorchScriptTensor(f32[3072, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_bias: `TorchScriptTensor(f32[3072])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_weight: `TorchScriptTensor(f32[1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_bias: `TorchScriptTensor(f32[1024])`,\n...\n)\n## Return values\n", + "text":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___3___mlp_fc2_bias[name=p_getattr_l__self___trunk_blocks___3___mlp_fc2_bias]. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"FxOnnxInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":414 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0008", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___4___norm1_weight[name=p_getattr_l__self___trunk_blocks___4___norm1_weight]. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature FxOnnxInterpreter.run_node\n- self: \n- node: fx.Node(p_getattr_l__self___trunk_blocks___4___norm1_weight)[placeholder]:Tensor(f32[1024])\n- fx_graph_module: torch.fx.GraphModule(timm_models_vision_transformer_VisionTransformer)\n- onnxfunction_dispatcher: \n- op_level_debug: False\n- onnxscript_graph: \n- onnxscript_tracer: \n- fx_name_to_onnxscript_value: Dict[length=52](\nx: `TorchScriptTensor(f32[4, 3, 512, 512])`,\np_trunk_patch_embed_proj_weight: `TorchScriptTensor(f32[1024, 3, 16, 16])`,\np_trunk_patch_embed_proj_bias: `TorchScriptTensor(f32[1024])`,\np_trunk_pos_embed: `TorchScriptTensor(f32[1, 1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_weight: `TorchScriptTensor(f32[3072, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_bias: `TorchScriptTensor(f32[3072])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_weight: `TorchScriptTensor(f32[1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_bias: `TorchScriptTensor(f32[1024])`,\n...\n)\n## Return values\n", + "text":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___4___norm1_weight[name=p_getattr_l__self___trunk_blocks___4___norm1_weight]. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"FxOnnxInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":414 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0008", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___4___norm1_bias[name=p_getattr_l__self___trunk_blocks___4___norm1_bias]. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature FxOnnxInterpreter.run_node\n- self: \n- node: fx.Node(p_getattr_l__self___trunk_blocks___4___norm1_bias)[placeholder]:Tensor(f32[1024])\n- fx_graph_module: torch.fx.GraphModule(timm_models_vision_transformer_VisionTransformer)\n- onnxfunction_dispatcher: \n- op_level_debug: False\n- onnxscript_graph: \n- onnxscript_tracer: \n- fx_name_to_onnxscript_value: Dict[length=53](\nx: `TorchScriptTensor(f32[4, 3, 512, 512])`,\np_trunk_patch_embed_proj_weight: `TorchScriptTensor(f32[1024, 3, 16, 16])`,\np_trunk_patch_embed_proj_bias: `TorchScriptTensor(f32[1024])`,\np_trunk_pos_embed: `TorchScriptTensor(f32[1, 1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_weight: `TorchScriptTensor(f32[3072, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_bias: `TorchScriptTensor(f32[3072])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_weight: `TorchScriptTensor(f32[1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_bias: `TorchScriptTensor(f32[1024])`,\n...\n)\n## Return values\n", + "text":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___4___norm1_bias[name=p_getattr_l__self___trunk_blocks___4___norm1_bias]. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"FxOnnxInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":414 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0008", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___4___attn_qkv_weight[name=p_getattr_l__self___trunk_blocks___4___attn_qkv_weight]. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature FxOnnxInterpreter.run_node\n- self: \n- node: fx.Node(p_getattr_l__self___trunk_blocks___4___attn_qkv_weight)[placeholder]:Tensor(f32[3072, 1024])\n- fx_graph_module: torch.fx.GraphModule(timm_models_vision_transformer_VisionTransformer)\n- onnxfunction_dispatcher: \n- op_level_debug: False\n- onnxscript_graph: \n- onnxscript_tracer: \n- fx_name_to_onnxscript_value: Dict[length=54](\nx: `TorchScriptTensor(f32[4, 3, 512, 512])`,\np_trunk_patch_embed_proj_weight: `TorchScriptTensor(f32[1024, 3, 16, 16])`,\np_trunk_patch_embed_proj_bias: `TorchScriptTensor(f32[1024])`,\np_trunk_pos_embed: `TorchScriptTensor(f32[1, 1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_weight: `TorchScriptTensor(f32[3072, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_bias: `TorchScriptTensor(f32[3072])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_weight: `TorchScriptTensor(f32[1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_bias: `TorchScriptTensor(f32[1024])`,\n...\n)\n## Return values\n", + "text":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___4___attn_qkv_weight[name=p_getattr_l__self___trunk_blocks___4___attn_qkv_weight]. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"FxOnnxInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":414 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0008", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___4___attn_qkv_bias[name=p_getattr_l__self___trunk_blocks___4___attn_qkv_bias]. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature FxOnnxInterpreter.run_node\n- self: \n- node: fx.Node(p_getattr_l__self___trunk_blocks___4___attn_qkv_bias)[placeholder]:Tensor(f32[3072])\n- fx_graph_module: torch.fx.GraphModule(timm_models_vision_transformer_VisionTransformer)\n- onnxfunction_dispatcher: \n- op_level_debug: False\n- onnxscript_graph: \n- onnxscript_tracer: \n- fx_name_to_onnxscript_value: Dict[length=55](\nx: `TorchScriptTensor(f32[4, 3, 512, 512])`,\np_trunk_patch_embed_proj_weight: `TorchScriptTensor(f32[1024, 3, 16, 16])`,\np_trunk_patch_embed_proj_bias: `TorchScriptTensor(f32[1024])`,\np_trunk_pos_embed: `TorchScriptTensor(f32[1, 1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_weight: `TorchScriptTensor(f32[3072, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_bias: `TorchScriptTensor(f32[3072])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_weight: `TorchScriptTensor(f32[1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_bias: `TorchScriptTensor(f32[1024])`,\n...\n)\n## Return values\n", + "text":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___4___attn_qkv_bias[name=p_getattr_l__self___trunk_blocks___4___attn_qkv_bias]. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"FxOnnxInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":414 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0008", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___4___attn_proj_weight[name=p_getattr_l__self___trunk_blocks___4___attn_proj_weight]. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature FxOnnxInterpreter.run_node\n- self: \n- node: fx.Node(p_getattr_l__self___trunk_blocks___4___attn_proj_weight)[placeholder]:Tensor(f32[1024, 1024])\n- fx_graph_module: torch.fx.GraphModule(timm_models_vision_transformer_VisionTransformer)\n- onnxfunction_dispatcher: \n- op_level_debug: False\n- onnxscript_graph: \n- onnxscript_tracer: \n- fx_name_to_onnxscript_value: Dict[length=56](\nx: `TorchScriptTensor(f32[4, 3, 512, 512])`,\np_trunk_patch_embed_proj_weight: `TorchScriptTensor(f32[1024, 3, 16, 16])`,\np_trunk_patch_embed_proj_bias: `TorchScriptTensor(f32[1024])`,\np_trunk_pos_embed: `TorchScriptTensor(f32[1, 1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_weight: `TorchScriptTensor(f32[3072, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_bias: `TorchScriptTensor(f32[3072])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_weight: `TorchScriptTensor(f32[1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_bias: `TorchScriptTensor(f32[1024])`,\n...\n)\n## Return values\n", + "text":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___4___attn_proj_weight[name=p_getattr_l__self___trunk_blocks___4___attn_proj_weight]. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"FxOnnxInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":414 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0008", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___4___attn_proj_bias[name=p_getattr_l__self___trunk_blocks___4___attn_proj_bias]. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature FxOnnxInterpreter.run_node\n- self: \n- node: fx.Node(p_getattr_l__self___trunk_blocks___4___attn_proj_bias)[placeholder]:Tensor(f32[1024])\n- fx_graph_module: torch.fx.GraphModule(timm_models_vision_transformer_VisionTransformer)\n- onnxfunction_dispatcher: \n- op_level_debug: False\n- onnxscript_graph: \n- onnxscript_tracer: \n- fx_name_to_onnxscript_value: Dict[length=57](\nx: `TorchScriptTensor(f32[4, 3, 512, 512])`,\np_trunk_patch_embed_proj_weight: `TorchScriptTensor(f32[1024, 3, 16, 16])`,\np_trunk_patch_embed_proj_bias: `TorchScriptTensor(f32[1024])`,\np_trunk_pos_embed: `TorchScriptTensor(f32[1, 1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_weight: `TorchScriptTensor(f32[3072, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_bias: `TorchScriptTensor(f32[3072])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_weight: `TorchScriptTensor(f32[1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_bias: `TorchScriptTensor(f32[1024])`,\n...\n)\n## Return values\n", + "text":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___4___attn_proj_bias[name=p_getattr_l__self___trunk_blocks___4___attn_proj_bias]. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"FxOnnxInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":414 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0008", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___4___norm2_weight[name=p_getattr_l__self___trunk_blocks___4___norm2_weight]. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature FxOnnxInterpreter.run_node\n- self: \n- node: fx.Node(p_getattr_l__self___trunk_blocks___4___norm2_weight)[placeholder]:Tensor(f32[1024])\n- fx_graph_module: torch.fx.GraphModule(timm_models_vision_transformer_VisionTransformer)\n- onnxfunction_dispatcher: \n- op_level_debug: False\n- onnxscript_graph: \n- onnxscript_tracer: \n- fx_name_to_onnxscript_value: Dict[length=58](\nx: `TorchScriptTensor(f32[4, 3, 512, 512])`,\np_trunk_patch_embed_proj_weight: `TorchScriptTensor(f32[1024, 3, 16, 16])`,\np_trunk_patch_embed_proj_bias: `TorchScriptTensor(f32[1024])`,\np_trunk_pos_embed: `TorchScriptTensor(f32[1, 1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_weight: `TorchScriptTensor(f32[3072, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_bias: `TorchScriptTensor(f32[3072])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_weight: `TorchScriptTensor(f32[1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_bias: `TorchScriptTensor(f32[1024])`,\n...\n)\n## Return values\n", + "text":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___4___norm2_weight[name=p_getattr_l__self___trunk_blocks___4___norm2_weight]. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"FxOnnxInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":414 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0008", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___4___norm2_bias[name=p_getattr_l__self___trunk_blocks___4___norm2_bias]. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature FxOnnxInterpreter.run_node\n- self: \n- node: fx.Node(p_getattr_l__self___trunk_blocks___4___norm2_bias)[placeholder]:Tensor(f32[1024])\n- fx_graph_module: torch.fx.GraphModule(timm_models_vision_transformer_VisionTransformer)\n- onnxfunction_dispatcher: \n- op_level_debug: False\n- onnxscript_graph: \n- onnxscript_tracer: \n- fx_name_to_onnxscript_value: Dict[length=59](\nx: `TorchScriptTensor(f32[4, 3, 512, 512])`,\np_trunk_patch_embed_proj_weight: `TorchScriptTensor(f32[1024, 3, 16, 16])`,\np_trunk_patch_embed_proj_bias: `TorchScriptTensor(f32[1024])`,\np_trunk_pos_embed: `TorchScriptTensor(f32[1, 1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_weight: `TorchScriptTensor(f32[3072, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_bias: `TorchScriptTensor(f32[3072])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_weight: `TorchScriptTensor(f32[1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_bias: `TorchScriptTensor(f32[1024])`,\n...\n)\n## Return values\n", + "text":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___4___norm2_bias[name=p_getattr_l__self___trunk_blocks___4___norm2_bias]. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"FxOnnxInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":414 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0008", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___4___mlp_fc1_weight[name=p_getattr_l__self___trunk_blocks___4___mlp_fc1_weight]. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature FxOnnxInterpreter.run_node\n- self: \n- node: fx.Node(p_getattr_l__self___trunk_blocks___4___mlp_fc1_weight)[placeholder]:Tensor(f32[4096, 1024])\n- fx_graph_module: torch.fx.GraphModule(timm_models_vision_transformer_VisionTransformer)\n- onnxfunction_dispatcher: \n- op_level_debug: False\n- onnxscript_graph: \n- onnxscript_tracer: \n- fx_name_to_onnxscript_value: Dict[length=60](\nx: `TorchScriptTensor(f32[4, 3, 512, 512])`,\np_trunk_patch_embed_proj_weight: `TorchScriptTensor(f32[1024, 3, 16, 16])`,\np_trunk_patch_embed_proj_bias: `TorchScriptTensor(f32[1024])`,\np_trunk_pos_embed: `TorchScriptTensor(f32[1, 1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_weight: `TorchScriptTensor(f32[3072, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_bias: `TorchScriptTensor(f32[3072])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_weight: `TorchScriptTensor(f32[1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_bias: `TorchScriptTensor(f32[1024])`,\n...\n)\n## Return values\n", + "text":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___4___mlp_fc1_weight[name=p_getattr_l__self___trunk_blocks___4___mlp_fc1_weight]. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"FxOnnxInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":414 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0008", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___4___mlp_fc1_bias[name=p_getattr_l__self___trunk_blocks___4___mlp_fc1_bias]. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature FxOnnxInterpreter.run_node\n- self: \n- node: fx.Node(p_getattr_l__self___trunk_blocks___4___mlp_fc1_bias)[placeholder]:Tensor(f32[4096])\n- fx_graph_module: torch.fx.GraphModule(timm_models_vision_transformer_VisionTransformer)\n- onnxfunction_dispatcher: \n- op_level_debug: False\n- onnxscript_graph: \n- onnxscript_tracer: \n- fx_name_to_onnxscript_value: Dict[length=61](\nx: `TorchScriptTensor(f32[4, 3, 512, 512])`,\np_trunk_patch_embed_proj_weight: `TorchScriptTensor(f32[1024, 3, 16, 16])`,\np_trunk_patch_embed_proj_bias: `TorchScriptTensor(f32[1024])`,\np_trunk_pos_embed: `TorchScriptTensor(f32[1, 1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_weight: `TorchScriptTensor(f32[3072, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_bias: `TorchScriptTensor(f32[3072])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_weight: `TorchScriptTensor(f32[1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_bias: `TorchScriptTensor(f32[1024])`,\n...\n)\n## Return values\n", + "text":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___4___mlp_fc1_bias[name=p_getattr_l__self___trunk_blocks___4___mlp_fc1_bias]. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"FxOnnxInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":414 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0008", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___4___mlp_fc2_weight[name=p_getattr_l__self___trunk_blocks___4___mlp_fc2_weight]. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature FxOnnxInterpreter.run_node\n- self: \n- node: fx.Node(p_getattr_l__self___trunk_blocks___4___mlp_fc2_weight)[placeholder]:Tensor(f32[1024, 4096])\n- fx_graph_module: torch.fx.GraphModule(timm_models_vision_transformer_VisionTransformer)\n- onnxfunction_dispatcher: \n- op_level_debug: False\n- onnxscript_graph: \n- onnxscript_tracer: \n- fx_name_to_onnxscript_value: Dict[length=62](\nx: `TorchScriptTensor(f32[4, 3, 512, 512])`,\np_trunk_patch_embed_proj_weight: `TorchScriptTensor(f32[1024, 3, 16, 16])`,\np_trunk_patch_embed_proj_bias: `TorchScriptTensor(f32[1024])`,\np_trunk_pos_embed: `TorchScriptTensor(f32[1, 1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_weight: `TorchScriptTensor(f32[3072, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_bias: `TorchScriptTensor(f32[3072])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_weight: `TorchScriptTensor(f32[1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_bias: `TorchScriptTensor(f32[1024])`,\n...\n)\n## Return values\n", + "text":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___4___mlp_fc2_weight[name=p_getattr_l__self___trunk_blocks___4___mlp_fc2_weight]. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"FxOnnxInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":414 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0008", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___4___mlp_fc2_bias[name=p_getattr_l__self___trunk_blocks___4___mlp_fc2_bias]. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature FxOnnxInterpreter.run_node\n- self: \n- node: fx.Node(p_getattr_l__self___trunk_blocks___4___mlp_fc2_bias)[placeholder]:Tensor(f32[1024])\n- fx_graph_module: torch.fx.GraphModule(timm_models_vision_transformer_VisionTransformer)\n- onnxfunction_dispatcher: \n- op_level_debug: False\n- onnxscript_graph: \n- onnxscript_tracer: \n- fx_name_to_onnxscript_value: Dict[length=63](\nx: `TorchScriptTensor(f32[4, 3, 512, 512])`,\np_trunk_patch_embed_proj_weight: `TorchScriptTensor(f32[1024, 3, 16, 16])`,\np_trunk_patch_embed_proj_bias: `TorchScriptTensor(f32[1024])`,\np_trunk_pos_embed: `TorchScriptTensor(f32[1, 1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_weight: `TorchScriptTensor(f32[3072, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_bias: `TorchScriptTensor(f32[3072])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_weight: `TorchScriptTensor(f32[1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_bias: `TorchScriptTensor(f32[1024])`,\n...\n)\n## Return values\n", + "text":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___4___mlp_fc2_bias[name=p_getattr_l__self___trunk_blocks___4___mlp_fc2_bias]. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"FxOnnxInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":414 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0008", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___5___norm1_weight[name=p_getattr_l__self___trunk_blocks___5___norm1_weight]. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature FxOnnxInterpreter.run_node\n- self: \n- node: fx.Node(p_getattr_l__self___trunk_blocks___5___norm1_weight)[placeholder]:Tensor(f32[1024])\n- fx_graph_module: torch.fx.GraphModule(timm_models_vision_transformer_VisionTransformer)\n- onnxfunction_dispatcher: \n- op_level_debug: False\n- onnxscript_graph: \n- onnxscript_tracer: \n- fx_name_to_onnxscript_value: Dict[length=64](\nx: `TorchScriptTensor(f32[4, 3, 512, 512])`,\np_trunk_patch_embed_proj_weight: `TorchScriptTensor(f32[1024, 3, 16, 16])`,\np_trunk_patch_embed_proj_bias: `TorchScriptTensor(f32[1024])`,\np_trunk_pos_embed: `TorchScriptTensor(f32[1, 1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_weight: `TorchScriptTensor(f32[3072, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_bias: `TorchScriptTensor(f32[3072])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_weight: `TorchScriptTensor(f32[1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_bias: `TorchScriptTensor(f32[1024])`,\n...\n)\n## Return values\n", + "text":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___5___norm1_weight[name=p_getattr_l__self___trunk_blocks___5___norm1_weight]. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"FxOnnxInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":414 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0008", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___5___norm1_bias[name=p_getattr_l__self___trunk_blocks___5___norm1_bias]. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature FxOnnxInterpreter.run_node\n- self: \n- node: fx.Node(p_getattr_l__self___trunk_blocks___5___norm1_bias)[placeholder]:Tensor(f32[1024])\n- fx_graph_module: torch.fx.GraphModule(timm_models_vision_transformer_VisionTransformer)\n- onnxfunction_dispatcher: \n- op_level_debug: False\n- onnxscript_graph: \n- onnxscript_tracer: \n- fx_name_to_onnxscript_value: Dict[length=65](\nx: `TorchScriptTensor(f32[4, 3, 512, 512])`,\np_trunk_patch_embed_proj_weight: `TorchScriptTensor(f32[1024, 3, 16, 16])`,\np_trunk_patch_embed_proj_bias: `TorchScriptTensor(f32[1024])`,\np_trunk_pos_embed: `TorchScriptTensor(f32[1, 1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_weight: `TorchScriptTensor(f32[3072, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_bias: `TorchScriptTensor(f32[3072])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_weight: `TorchScriptTensor(f32[1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_bias: `TorchScriptTensor(f32[1024])`,\n...\n)\n## Return values\n", + "text":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___5___norm1_bias[name=p_getattr_l__self___trunk_blocks___5___norm1_bias]. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"FxOnnxInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":414 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0008", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___5___attn_qkv_weight[name=p_getattr_l__self___trunk_blocks___5___attn_qkv_weight]. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature FxOnnxInterpreter.run_node\n- self: \n- node: fx.Node(p_getattr_l__self___trunk_blocks___5___attn_qkv_weight)[placeholder]:Tensor(f32[3072, 1024])\n- fx_graph_module: torch.fx.GraphModule(timm_models_vision_transformer_VisionTransformer)\n- onnxfunction_dispatcher: \n- op_level_debug: False\n- onnxscript_graph: \n- onnxscript_tracer: \n- fx_name_to_onnxscript_value: Dict[length=66](\nx: `TorchScriptTensor(f32[4, 3, 512, 512])`,\np_trunk_patch_embed_proj_weight: `TorchScriptTensor(f32[1024, 3, 16, 16])`,\np_trunk_patch_embed_proj_bias: `TorchScriptTensor(f32[1024])`,\np_trunk_pos_embed: `TorchScriptTensor(f32[1, 1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_weight: `TorchScriptTensor(f32[3072, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_bias: `TorchScriptTensor(f32[3072])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_weight: `TorchScriptTensor(f32[1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_bias: `TorchScriptTensor(f32[1024])`,\n...\n)\n## Return values\n", + "text":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___5___attn_qkv_weight[name=p_getattr_l__self___trunk_blocks___5___attn_qkv_weight]. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"FxOnnxInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":414 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0008", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___5___attn_qkv_bias[name=p_getattr_l__self___trunk_blocks___5___attn_qkv_bias]. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature FxOnnxInterpreter.run_node\n- self: \n- node: fx.Node(p_getattr_l__self___trunk_blocks___5___attn_qkv_bias)[placeholder]:Tensor(f32[3072])\n- fx_graph_module: torch.fx.GraphModule(timm_models_vision_transformer_VisionTransformer)\n- onnxfunction_dispatcher: \n- op_level_debug: False\n- onnxscript_graph: \n- onnxscript_tracer: \n- fx_name_to_onnxscript_value: Dict[length=67](\nx: `TorchScriptTensor(f32[4, 3, 512, 512])`,\np_trunk_patch_embed_proj_weight: `TorchScriptTensor(f32[1024, 3, 16, 16])`,\np_trunk_patch_embed_proj_bias: `TorchScriptTensor(f32[1024])`,\np_trunk_pos_embed: `TorchScriptTensor(f32[1, 1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_weight: `TorchScriptTensor(f32[3072, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_bias: `TorchScriptTensor(f32[3072])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_weight: `TorchScriptTensor(f32[1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_bias: `TorchScriptTensor(f32[1024])`,\n...\n)\n## Return values\n", + "text":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___5___attn_qkv_bias[name=p_getattr_l__self___trunk_blocks___5___attn_qkv_bias]. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"FxOnnxInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":414 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0008", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___5___attn_proj_weight[name=p_getattr_l__self___trunk_blocks___5___attn_proj_weight]. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature FxOnnxInterpreter.run_node\n- self: \n- node: fx.Node(p_getattr_l__self___trunk_blocks___5___attn_proj_weight)[placeholder]:Tensor(f32[1024, 1024])\n- fx_graph_module: torch.fx.GraphModule(timm_models_vision_transformer_VisionTransformer)\n- onnxfunction_dispatcher: \n- op_level_debug: False\n- onnxscript_graph: \n- onnxscript_tracer: \n- fx_name_to_onnxscript_value: Dict[length=68](\nx: `TorchScriptTensor(f32[4, 3, 512, 512])`,\np_trunk_patch_embed_proj_weight: `TorchScriptTensor(f32[1024, 3, 16, 16])`,\np_trunk_patch_embed_proj_bias: `TorchScriptTensor(f32[1024])`,\np_trunk_pos_embed: `TorchScriptTensor(f32[1, 1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_weight: `TorchScriptTensor(f32[3072, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_bias: `TorchScriptTensor(f32[3072])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_weight: `TorchScriptTensor(f32[1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_bias: `TorchScriptTensor(f32[1024])`,\n...\n)\n## Return values\n", + "text":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___5___attn_proj_weight[name=p_getattr_l__self___trunk_blocks___5___attn_proj_weight]. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"FxOnnxInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":414 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0008", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___5___attn_proj_bias[name=p_getattr_l__self___trunk_blocks___5___attn_proj_bias]. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature FxOnnxInterpreter.run_node\n- self: \n- node: fx.Node(p_getattr_l__self___trunk_blocks___5___attn_proj_bias)[placeholder]:Tensor(f32[1024])\n- fx_graph_module: torch.fx.GraphModule(timm_models_vision_transformer_VisionTransformer)\n- onnxfunction_dispatcher: \n- op_level_debug: False\n- onnxscript_graph: \n- onnxscript_tracer: \n- fx_name_to_onnxscript_value: Dict[length=69](\nx: `TorchScriptTensor(f32[4, 3, 512, 512])`,\np_trunk_patch_embed_proj_weight: `TorchScriptTensor(f32[1024, 3, 16, 16])`,\np_trunk_patch_embed_proj_bias: `TorchScriptTensor(f32[1024])`,\np_trunk_pos_embed: `TorchScriptTensor(f32[1, 1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_weight: `TorchScriptTensor(f32[3072, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_bias: `TorchScriptTensor(f32[3072])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_weight: `TorchScriptTensor(f32[1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_bias: `TorchScriptTensor(f32[1024])`,\n...\n)\n## Return values\n", + "text":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___5___attn_proj_bias[name=p_getattr_l__self___trunk_blocks___5___attn_proj_bias]. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"FxOnnxInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":414 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0008", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___5___norm2_weight[name=p_getattr_l__self___trunk_blocks___5___norm2_weight]. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature FxOnnxInterpreter.run_node\n- self: \n- node: fx.Node(p_getattr_l__self___trunk_blocks___5___norm2_weight)[placeholder]:Tensor(f32[1024])\n- fx_graph_module: torch.fx.GraphModule(timm_models_vision_transformer_VisionTransformer)\n- onnxfunction_dispatcher: \n- op_level_debug: False\n- onnxscript_graph: \n- onnxscript_tracer: \n- fx_name_to_onnxscript_value: Dict[length=70](\nx: `TorchScriptTensor(f32[4, 3, 512, 512])`,\np_trunk_patch_embed_proj_weight: `TorchScriptTensor(f32[1024, 3, 16, 16])`,\np_trunk_patch_embed_proj_bias: `TorchScriptTensor(f32[1024])`,\np_trunk_pos_embed: `TorchScriptTensor(f32[1, 1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_weight: `TorchScriptTensor(f32[3072, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_bias: `TorchScriptTensor(f32[3072])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_weight: `TorchScriptTensor(f32[1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_bias: `TorchScriptTensor(f32[1024])`,\n...\n)\n## Return values\n", + "text":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___5___norm2_weight[name=p_getattr_l__self___trunk_blocks___5___norm2_weight]. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"FxOnnxInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":414 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0008", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___5___norm2_bias[name=p_getattr_l__self___trunk_blocks___5___norm2_bias]. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature FxOnnxInterpreter.run_node\n- self: \n- node: fx.Node(p_getattr_l__self___trunk_blocks___5___norm2_bias)[placeholder]:Tensor(f32[1024])\n- fx_graph_module: torch.fx.GraphModule(timm_models_vision_transformer_VisionTransformer)\n- onnxfunction_dispatcher: \n- op_level_debug: False\n- onnxscript_graph: \n- onnxscript_tracer: \n- fx_name_to_onnxscript_value: Dict[length=71](\nx: `TorchScriptTensor(f32[4, 3, 512, 512])`,\np_trunk_patch_embed_proj_weight: `TorchScriptTensor(f32[1024, 3, 16, 16])`,\np_trunk_patch_embed_proj_bias: `TorchScriptTensor(f32[1024])`,\np_trunk_pos_embed: `TorchScriptTensor(f32[1, 1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_weight: `TorchScriptTensor(f32[3072, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_bias: `TorchScriptTensor(f32[3072])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_weight: `TorchScriptTensor(f32[1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_bias: `TorchScriptTensor(f32[1024])`,\n...\n)\n## Return values\n", + "text":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___5___norm2_bias[name=p_getattr_l__self___trunk_blocks___5___norm2_bias]. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"FxOnnxInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":414 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0008", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___5___mlp_fc1_weight[name=p_getattr_l__self___trunk_blocks___5___mlp_fc1_weight]. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature FxOnnxInterpreter.run_node\n- self: \n- node: fx.Node(p_getattr_l__self___trunk_blocks___5___mlp_fc1_weight)[placeholder]:Tensor(f32[4096, 1024])\n- fx_graph_module: torch.fx.GraphModule(timm_models_vision_transformer_VisionTransformer)\n- onnxfunction_dispatcher: \n- op_level_debug: False\n- onnxscript_graph: \n- onnxscript_tracer: \n- fx_name_to_onnxscript_value: Dict[length=72](\nx: `TorchScriptTensor(f32[4, 3, 512, 512])`,\np_trunk_patch_embed_proj_weight: `TorchScriptTensor(f32[1024, 3, 16, 16])`,\np_trunk_patch_embed_proj_bias: `TorchScriptTensor(f32[1024])`,\np_trunk_pos_embed: `TorchScriptTensor(f32[1, 1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_weight: `TorchScriptTensor(f32[3072, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_bias: `TorchScriptTensor(f32[3072])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_weight: `TorchScriptTensor(f32[1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_bias: `TorchScriptTensor(f32[1024])`,\n...\n)\n## Return values\n", + "text":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___5___mlp_fc1_weight[name=p_getattr_l__self___trunk_blocks___5___mlp_fc1_weight]. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"FxOnnxInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":414 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0008", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___5___mlp_fc1_bias[name=p_getattr_l__self___trunk_blocks___5___mlp_fc1_bias]. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature FxOnnxInterpreter.run_node\n- self: \n- node: fx.Node(p_getattr_l__self___trunk_blocks___5___mlp_fc1_bias)[placeholder]:Tensor(f32[4096])\n- fx_graph_module: torch.fx.GraphModule(timm_models_vision_transformer_VisionTransformer)\n- onnxfunction_dispatcher: \n- op_level_debug: False\n- onnxscript_graph: \n- onnxscript_tracer: \n- fx_name_to_onnxscript_value: Dict[length=73](\nx: `TorchScriptTensor(f32[4, 3, 512, 512])`,\np_trunk_patch_embed_proj_weight: `TorchScriptTensor(f32[1024, 3, 16, 16])`,\np_trunk_patch_embed_proj_bias: `TorchScriptTensor(f32[1024])`,\np_trunk_pos_embed: `TorchScriptTensor(f32[1, 1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_weight: `TorchScriptTensor(f32[3072, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_bias: `TorchScriptTensor(f32[3072])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_weight: `TorchScriptTensor(f32[1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_bias: `TorchScriptTensor(f32[1024])`,\n...\n)\n## Return values\n", + "text":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___5___mlp_fc1_bias[name=p_getattr_l__self___trunk_blocks___5___mlp_fc1_bias]. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"FxOnnxInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":414 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0008", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___5___mlp_fc2_weight[name=p_getattr_l__self___trunk_blocks___5___mlp_fc2_weight]. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature FxOnnxInterpreter.run_node\n- self: \n- node: fx.Node(p_getattr_l__self___trunk_blocks___5___mlp_fc2_weight)[placeholder]:Tensor(f32[1024, 4096])\n- fx_graph_module: torch.fx.GraphModule(timm_models_vision_transformer_VisionTransformer)\n- onnxfunction_dispatcher: \n- op_level_debug: False\n- onnxscript_graph: \n- onnxscript_tracer: \n- fx_name_to_onnxscript_value: Dict[length=74](\nx: `TorchScriptTensor(f32[4, 3, 512, 512])`,\np_trunk_patch_embed_proj_weight: `TorchScriptTensor(f32[1024, 3, 16, 16])`,\np_trunk_patch_embed_proj_bias: `TorchScriptTensor(f32[1024])`,\np_trunk_pos_embed: `TorchScriptTensor(f32[1, 1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_weight: `TorchScriptTensor(f32[3072, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_bias: `TorchScriptTensor(f32[3072])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_weight: `TorchScriptTensor(f32[1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_bias: `TorchScriptTensor(f32[1024])`,\n...\n)\n## Return values\n", + "text":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___5___mlp_fc2_weight[name=p_getattr_l__self___trunk_blocks___5___mlp_fc2_weight]. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"FxOnnxInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":414 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0008", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___5___mlp_fc2_bias[name=p_getattr_l__self___trunk_blocks___5___mlp_fc2_bias]. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature FxOnnxInterpreter.run_node\n- self: \n- node: fx.Node(p_getattr_l__self___trunk_blocks___5___mlp_fc2_bias)[placeholder]:Tensor(f32[1024])\n- fx_graph_module: torch.fx.GraphModule(timm_models_vision_transformer_VisionTransformer)\n- onnxfunction_dispatcher: \n- op_level_debug: False\n- onnxscript_graph: \n- onnxscript_tracer: \n- fx_name_to_onnxscript_value: Dict[length=75](\nx: `TorchScriptTensor(f32[4, 3, 512, 512])`,\np_trunk_patch_embed_proj_weight: `TorchScriptTensor(f32[1024, 3, 16, 16])`,\np_trunk_patch_embed_proj_bias: `TorchScriptTensor(f32[1024])`,\np_trunk_pos_embed: `TorchScriptTensor(f32[1, 1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_weight: `TorchScriptTensor(f32[3072, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_bias: `TorchScriptTensor(f32[3072])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_weight: `TorchScriptTensor(f32[1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_bias: `TorchScriptTensor(f32[1024])`,\n...\n)\n## Return values\n", + "text":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___5___mlp_fc2_bias[name=p_getattr_l__self___trunk_blocks___5___mlp_fc2_bias]. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"FxOnnxInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":414 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0008", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___6___norm1_weight[name=p_getattr_l__self___trunk_blocks___6___norm1_weight]. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature FxOnnxInterpreter.run_node\n- self: \n- node: fx.Node(p_getattr_l__self___trunk_blocks___6___norm1_weight)[placeholder]:Tensor(f32[1024])\n- fx_graph_module: torch.fx.GraphModule(timm_models_vision_transformer_VisionTransformer)\n- onnxfunction_dispatcher: \n- op_level_debug: False\n- onnxscript_graph: \n- onnxscript_tracer: \n- fx_name_to_onnxscript_value: Dict[length=76](\nx: `TorchScriptTensor(f32[4, 3, 512, 512])`,\np_trunk_patch_embed_proj_weight: `TorchScriptTensor(f32[1024, 3, 16, 16])`,\np_trunk_patch_embed_proj_bias: `TorchScriptTensor(f32[1024])`,\np_trunk_pos_embed: `TorchScriptTensor(f32[1, 1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_weight: `TorchScriptTensor(f32[3072, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_bias: `TorchScriptTensor(f32[3072])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_weight: `TorchScriptTensor(f32[1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_bias: `TorchScriptTensor(f32[1024])`,\n...\n)\n## Return values\n", + "text":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___6___norm1_weight[name=p_getattr_l__self___trunk_blocks___6___norm1_weight]. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"FxOnnxInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":414 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0008", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___6___norm1_bias[name=p_getattr_l__self___trunk_blocks___6___norm1_bias]. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature FxOnnxInterpreter.run_node\n- self: \n- node: fx.Node(p_getattr_l__self___trunk_blocks___6___norm1_bias)[placeholder]:Tensor(f32[1024])\n- fx_graph_module: torch.fx.GraphModule(timm_models_vision_transformer_VisionTransformer)\n- onnxfunction_dispatcher: \n- op_level_debug: False\n- onnxscript_graph: \n- onnxscript_tracer: \n- fx_name_to_onnxscript_value: Dict[length=77](\nx: `TorchScriptTensor(f32[4, 3, 512, 512])`,\np_trunk_patch_embed_proj_weight: `TorchScriptTensor(f32[1024, 3, 16, 16])`,\np_trunk_patch_embed_proj_bias: `TorchScriptTensor(f32[1024])`,\np_trunk_pos_embed: `TorchScriptTensor(f32[1, 1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_weight: `TorchScriptTensor(f32[3072, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_bias: `TorchScriptTensor(f32[3072])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_weight: `TorchScriptTensor(f32[1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_bias: `TorchScriptTensor(f32[1024])`,\n...\n)\n## Return values\n", + "text":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___6___norm1_bias[name=p_getattr_l__self___trunk_blocks___6___norm1_bias]. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"FxOnnxInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":414 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0008", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___6___attn_qkv_weight[name=p_getattr_l__self___trunk_blocks___6___attn_qkv_weight]. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature FxOnnxInterpreter.run_node\n- self: \n- node: fx.Node(p_getattr_l__self___trunk_blocks___6___attn_qkv_weight)[placeholder]:Tensor(f32[3072, 1024])\n- fx_graph_module: torch.fx.GraphModule(timm_models_vision_transformer_VisionTransformer)\n- onnxfunction_dispatcher: \n- op_level_debug: False\n- onnxscript_graph: \n- onnxscript_tracer: \n- fx_name_to_onnxscript_value: Dict[length=78](\nx: `TorchScriptTensor(f32[4, 3, 512, 512])`,\np_trunk_patch_embed_proj_weight: `TorchScriptTensor(f32[1024, 3, 16, 16])`,\np_trunk_patch_embed_proj_bias: `TorchScriptTensor(f32[1024])`,\np_trunk_pos_embed: `TorchScriptTensor(f32[1, 1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_weight: `TorchScriptTensor(f32[3072, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_bias: `TorchScriptTensor(f32[3072])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_weight: `TorchScriptTensor(f32[1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_bias: `TorchScriptTensor(f32[1024])`,\n...\n)\n## Return values\n", + "text":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___6___attn_qkv_weight[name=p_getattr_l__self___trunk_blocks___6___attn_qkv_weight]. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"FxOnnxInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":414 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0008", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___6___attn_qkv_bias[name=p_getattr_l__self___trunk_blocks___6___attn_qkv_bias]. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature FxOnnxInterpreter.run_node\n- self: \n- node: fx.Node(p_getattr_l__self___trunk_blocks___6___attn_qkv_bias)[placeholder]:Tensor(f32[3072])\n- fx_graph_module: torch.fx.GraphModule(timm_models_vision_transformer_VisionTransformer)\n- onnxfunction_dispatcher: \n- op_level_debug: False\n- onnxscript_graph: \n- onnxscript_tracer: \n- fx_name_to_onnxscript_value: Dict[length=79](\nx: `TorchScriptTensor(f32[4, 3, 512, 512])`,\np_trunk_patch_embed_proj_weight: `TorchScriptTensor(f32[1024, 3, 16, 16])`,\np_trunk_patch_embed_proj_bias: `TorchScriptTensor(f32[1024])`,\np_trunk_pos_embed: `TorchScriptTensor(f32[1, 1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_weight: `TorchScriptTensor(f32[3072, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_bias: `TorchScriptTensor(f32[3072])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_weight: `TorchScriptTensor(f32[1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_bias: `TorchScriptTensor(f32[1024])`,\n...\n)\n## Return values\n", + "text":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___6___attn_qkv_bias[name=p_getattr_l__self___trunk_blocks___6___attn_qkv_bias]. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"FxOnnxInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":414 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0008", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___6___attn_proj_weight[name=p_getattr_l__self___trunk_blocks___6___attn_proj_weight]. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature FxOnnxInterpreter.run_node\n- self: \n- node: fx.Node(p_getattr_l__self___trunk_blocks___6___attn_proj_weight)[placeholder]:Tensor(f32[1024, 1024])\n- fx_graph_module: torch.fx.GraphModule(timm_models_vision_transformer_VisionTransformer)\n- onnxfunction_dispatcher: \n- op_level_debug: False\n- onnxscript_graph: \n- onnxscript_tracer: \n- fx_name_to_onnxscript_value: Dict[length=80](\nx: `TorchScriptTensor(f32[4, 3, 512, 512])`,\np_trunk_patch_embed_proj_weight: `TorchScriptTensor(f32[1024, 3, 16, 16])`,\np_trunk_patch_embed_proj_bias: `TorchScriptTensor(f32[1024])`,\np_trunk_pos_embed: `TorchScriptTensor(f32[1, 1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_weight: `TorchScriptTensor(f32[3072, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_bias: `TorchScriptTensor(f32[3072])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_weight: `TorchScriptTensor(f32[1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_bias: `TorchScriptTensor(f32[1024])`,\n...\n)\n## Return values\n", + "text":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___6___attn_proj_weight[name=p_getattr_l__self___trunk_blocks___6___attn_proj_weight]. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"FxOnnxInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":414 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0008", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___6___attn_proj_bias[name=p_getattr_l__self___trunk_blocks___6___attn_proj_bias]. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature FxOnnxInterpreter.run_node\n- self: \n- node: fx.Node(p_getattr_l__self___trunk_blocks___6___attn_proj_bias)[placeholder]:Tensor(f32[1024])\n- fx_graph_module: torch.fx.GraphModule(timm_models_vision_transformer_VisionTransformer)\n- onnxfunction_dispatcher: \n- op_level_debug: False\n- onnxscript_graph: \n- onnxscript_tracer: \n- fx_name_to_onnxscript_value: Dict[length=81](\nx: `TorchScriptTensor(f32[4, 3, 512, 512])`,\np_trunk_patch_embed_proj_weight: `TorchScriptTensor(f32[1024, 3, 16, 16])`,\np_trunk_patch_embed_proj_bias: `TorchScriptTensor(f32[1024])`,\np_trunk_pos_embed: `TorchScriptTensor(f32[1, 1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_weight: `TorchScriptTensor(f32[3072, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_bias: `TorchScriptTensor(f32[3072])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_weight: `TorchScriptTensor(f32[1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_bias: `TorchScriptTensor(f32[1024])`,\n...\n)\n## Return values\n", + "text":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___6___attn_proj_bias[name=p_getattr_l__self___trunk_blocks___6___attn_proj_bias]. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"FxOnnxInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":414 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0008", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___6___norm2_weight[name=p_getattr_l__self___trunk_blocks___6___norm2_weight]. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature FxOnnxInterpreter.run_node\n- self: \n- node: fx.Node(p_getattr_l__self___trunk_blocks___6___norm2_weight)[placeholder]:Tensor(f32[1024])\n- fx_graph_module: torch.fx.GraphModule(timm_models_vision_transformer_VisionTransformer)\n- onnxfunction_dispatcher: \n- op_level_debug: False\n- onnxscript_graph: \n- onnxscript_tracer: \n- fx_name_to_onnxscript_value: Dict[length=82](\nx: `TorchScriptTensor(f32[4, 3, 512, 512])`,\np_trunk_patch_embed_proj_weight: `TorchScriptTensor(f32[1024, 3, 16, 16])`,\np_trunk_patch_embed_proj_bias: `TorchScriptTensor(f32[1024])`,\np_trunk_pos_embed: `TorchScriptTensor(f32[1, 1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_weight: `TorchScriptTensor(f32[3072, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_bias: `TorchScriptTensor(f32[3072])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_weight: `TorchScriptTensor(f32[1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_bias: `TorchScriptTensor(f32[1024])`,\n...\n)\n## Return values\n", + "text":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___6___norm2_weight[name=p_getattr_l__self___trunk_blocks___6___norm2_weight]. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"FxOnnxInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":414 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0008", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___6___norm2_bias[name=p_getattr_l__self___trunk_blocks___6___norm2_bias]. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature FxOnnxInterpreter.run_node\n- self: \n- node: fx.Node(p_getattr_l__self___trunk_blocks___6___norm2_bias)[placeholder]:Tensor(f32[1024])\n- fx_graph_module: torch.fx.GraphModule(timm_models_vision_transformer_VisionTransformer)\n- onnxfunction_dispatcher: \n- op_level_debug: False\n- onnxscript_graph: \n- onnxscript_tracer: \n- fx_name_to_onnxscript_value: Dict[length=83](\nx: `TorchScriptTensor(f32[4, 3, 512, 512])`,\np_trunk_patch_embed_proj_weight: `TorchScriptTensor(f32[1024, 3, 16, 16])`,\np_trunk_patch_embed_proj_bias: `TorchScriptTensor(f32[1024])`,\np_trunk_pos_embed: `TorchScriptTensor(f32[1, 1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_weight: `TorchScriptTensor(f32[3072, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_bias: `TorchScriptTensor(f32[3072])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_weight: `TorchScriptTensor(f32[1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_bias: `TorchScriptTensor(f32[1024])`,\n...\n)\n## Return values\n", + "text":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___6___norm2_bias[name=p_getattr_l__self___trunk_blocks___6___norm2_bias]. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"FxOnnxInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":414 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0008", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___6___mlp_fc1_weight[name=p_getattr_l__self___trunk_blocks___6___mlp_fc1_weight]. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature FxOnnxInterpreter.run_node\n- self: \n- node: fx.Node(p_getattr_l__self___trunk_blocks___6___mlp_fc1_weight)[placeholder]:Tensor(f32[4096, 1024])\n- fx_graph_module: torch.fx.GraphModule(timm_models_vision_transformer_VisionTransformer)\n- onnxfunction_dispatcher: \n- op_level_debug: False\n- onnxscript_graph: \n- onnxscript_tracer: \n- fx_name_to_onnxscript_value: Dict[length=84](\nx: `TorchScriptTensor(f32[4, 3, 512, 512])`,\np_trunk_patch_embed_proj_weight: `TorchScriptTensor(f32[1024, 3, 16, 16])`,\np_trunk_patch_embed_proj_bias: `TorchScriptTensor(f32[1024])`,\np_trunk_pos_embed: `TorchScriptTensor(f32[1, 1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_weight: `TorchScriptTensor(f32[3072, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_bias: `TorchScriptTensor(f32[3072])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_weight: `TorchScriptTensor(f32[1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_bias: `TorchScriptTensor(f32[1024])`,\n...\n)\n## Return values\n", + "text":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___6___mlp_fc1_weight[name=p_getattr_l__self___trunk_blocks___6___mlp_fc1_weight]. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"FxOnnxInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":414 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0008", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___6___mlp_fc1_bias[name=p_getattr_l__self___trunk_blocks___6___mlp_fc1_bias]. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature FxOnnxInterpreter.run_node\n- self: \n- node: fx.Node(p_getattr_l__self___trunk_blocks___6___mlp_fc1_bias)[placeholder]:Tensor(f32[4096])\n- fx_graph_module: torch.fx.GraphModule(timm_models_vision_transformer_VisionTransformer)\n- onnxfunction_dispatcher: \n- op_level_debug: False\n- onnxscript_graph: \n- onnxscript_tracer: \n- fx_name_to_onnxscript_value: Dict[length=85](\nx: `TorchScriptTensor(f32[4, 3, 512, 512])`,\np_trunk_patch_embed_proj_weight: `TorchScriptTensor(f32[1024, 3, 16, 16])`,\np_trunk_patch_embed_proj_bias: `TorchScriptTensor(f32[1024])`,\np_trunk_pos_embed: `TorchScriptTensor(f32[1, 1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_weight: `TorchScriptTensor(f32[3072, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_bias: `TorchScriptTensor(f32[3072])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_weight: `TorchScriptTensor(f32[1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_bias: `TorchScriptTensor(f32[1024])`,\n...\n)\n## Return values\n", + "text":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___6___mlp_fc1_bias[name=p_getattr_l__self___trunk_blocks___6___mlp_fc1_bias]. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"FxOnnxInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":414 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0008", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___6___mlp_fc2_weight[name=p_getattr_l__self___trunk_blocks___6___mlp_fc2_weight]. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature FxOnnxInterpreter.run_node\n- self: \n- node: fx.Node(p_getattr_l__self___trunk_blocks___6___mlp_fc2_weight)[placeholder]:Tensor(f32[1024, 4096])\n- fx_graph_module: torch.fx.GraphModule(timm_models_vision_transformer_VisionTransformer)\n- onnxfunction_dispatcher: \n- op_level_debug: False\n- onnxscript_graph: \n- onnxscript_tracer: \n- fx_name_to_onnxscript_value: Dict[length=86](\nx: `TorchScriptTensor(f32[4, 3, 512, 512])`,\np_trunk_patch_embed_proj_weight: `TorchScriptTensor(f32[1024, 3, 16, 16])`,\np_trunk_patch_embed_proj_bias: `TorchScriptTensor(f32[1024])`,\np_trunk_pos_embed: `TorchScriptTensor(f32[1, 1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_weight: `TorchScriptTensor(f32[3072, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_bias: `TorchScriptTensor(f32[3072])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_weight: `TorchScriptTensor(f32[1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_bias: `TorchScriptTensor(f32[1024])`,\n...\n)\n## Return values\n", + "text":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___6___mlp_fc2_weight[name=p_getattr_l__self___trunk_blocks___6___mlp_fc2_weight]. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"FxOnnxInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":414 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0008", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___6___mlp_fc2_bias[name=p_getattr_l__self___trunk_blocks___6___mlp_fc2_bias]. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature FxOnnxInterpreter.run_node\n- self: \n- node: fx.Node(p_getattr_l__self___trunk_blocks___6___mlp_fc2_bias)[placeholder]:Tensor(f32[1024])\n- fx_graph_module: torch.fx.GraphModule(timm_models_vision_transformer_VisionTransformer)\n- onnxfunction_dispatcher: \n- op_level_debug: False\n- onnxscript_graph: \n- onnxscript_tracer: \n- fx_name_to_onnxscript_value: Dict[length=87](\nx: `TorchScriptTensor(f32[4, 3, 512, 512])`,\np_trunk_patch_embed_proj_weight: `TorchScriptTensor(f32[1024, 3, 16, 16])`,\np_trunk_patch_embed_proj_bias: `TorchScriptTensor(f32[1024])`,\np_trunk_pos_embed: `TorchScriptTensor(f32[1, 1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_weight: `TorchScriptTensor(f32[3072, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_bias: `TorchScriptTensor(f32[3072])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_weight: `TorchScriptTensor(f32[1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_bias: `TorchScriptTensor(f32[1024])`,\n...\n)\n## Return values\n", + "text":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___6___mlp_fc2_bias[name=p_getattr_l__self___trunk_blocks___6___mlp_fc2_bias]. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"FxOnnxInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":414 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0008", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___7___norm1_weight[name=p_getattr_l__self___trunk_blocks___7___norm1_weight]. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature FxOnnxInterpreter.run_node\n- self: \n- node: fx.Node(p_getattr_l__self___trunk_blocks___7___norm1_weight)[placeholder]:Tensor(f32[1024])\n- fx_graph_module: torch.fx.GraphModule(timm_models_vision_transformer_VisionTransformer)\n- onnxfunction_dispatcher: \n- op_level_debug: False\n- onnxscript_graph: \n- onnxscript_tracer: \n- fx_name_to_onnxscript_value: Dict[length=88](\nx: `TorchScriptTensor(f32[4, 3, 512, 512])`,\np_trunk_patch_embed_proj_weight: `TorchScriptTensor(f32[1024, 3, 16, 16])`,\np_trunk_patch_embed_proj_bias: `TorchScriptTensor(f32[1024])`,\np_trunk_pos_embed: `TorchScriptTensor(f32[1, 1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_weight: `TorchScriptTensor(f32[3072, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_bias: `TorchScriptTensor(f32[3072])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_weight: `TorchScriptTensor(f32[1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_bias: `TorchScriptTensor(f32[1024])`,\n...\n)\n## Return values\n", + "text":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___7___norm1_weight[name=p_getattr_l__self___trunk_blocks___7___norm1_weight]. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"FxOnnxInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":414 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0008", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___7___norm1_bias[name=p_getattr_l__self___trunk_blocks___7___norm1_bias]. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature FxOnnxInterpreter.run_node\n- self: \n- node: fx.Node(p_getattr_l__self___trunk_blocks___7___norm1_bias)[placeholder]:Tensor(f32[1024])\n- fx_graph_module: torch.fx.GraphModule(timm_models_vision_transformer_VisionTransformer)\n- onnxfunction_dispatcher: \n- op_level_debug: False\n- onnxscript_graph: \n- onnxscript_tracer: \n- fx_name_to_onnxscript_value: Dict[length=89](\nx: `TorchScriptTensor(f32[4, 3, 512, 512])`,\np_trunk_patch_embed_proj_weight: `TorchScriptTensor(f32[1024, 3, 16, 16])`,\np_trunk_patch_embed_proj_bias: `TorchScriptTensor(f32[1024])`,\np_trunk_pos_embed: `TorchScriptTensor(f32[1, 1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_weight: `TorchScriptTensor(f32[3072, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_bias: `TorchScriptTensor(f32[3072])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_weight: `TorchScriptTensor(f32[1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_bias: `TorchScriptTensor(f32[1024])`,\n...\n)\n## Return values\n", + "text":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___7___norm1_bias[name=p_getattr_l__self___trunk_blocks___7___norm1_bias]. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"FxOnnxInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":414 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0008", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___7___attn_qkv_weight[name=p_getattr_l__self___trunk_blocks___7___attn_qkv_weight]. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature FxOnnxInterpreter.run_node\n- self: \n- node: fx.Node(p_getattr_l__self___trunk_blocks___7___attn_qkv_weight)[placeholder]:Tensor(f32[3072, 1024])\n- fx_graph_module: torch.fx.GraphModule(timm_models_vision_transformer_VisionTransformer)\n- onnxfunction_dispatcher: \n- op_level_debug: False\n- onnxscript_graph: \n- onnxscript_tracer: \n- fx_name_to_onnxscript_value: Dict[length=90](\nx: `TorchScriptTensor(f32[4, 3, 512, 512])`,\np_trunk_patch_embed_proj_weight: `TorchScriptTensor(f32[1024, 3, 16, 16])`,\np_trunk_patch_embed_proj_bias: `TorchScriptTensor(f32[1024])`,\np_trunk_pos_embed: `TorchScriptTensor(f32[1, 1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_weight: `TorchScriptTensor(f32[3072, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_bias: `TorchScriptTensor(f32[3072])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_weight: `TorchScriptTensor(f32[1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_bias: `TorchScriptTensor(f32[1024])`,\n...\n)\n## Return values\n", + "text":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___7___attn_qkv_weight[name=p_getattr_l__self___trunk_blocks___7___attn_qkv_weight]. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"FxOnnxInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":414 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0008", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___7___attn_qkv_bias[name=p_getattr_l__self___trunk_blocks___7___attn_qkv_bias]. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature FxOnnxInterpreter.run_node\n- self: \n- node: fx.Node(p_getattr_l__self___trunk_blocks___7___attn_qkv_bias)[placeholder]:Tensor(f32[3072])\n- fx_graph_module: torch.fx.GraphModule(timm_models_vision_transformer_VisionTransformer)\n- onnxfunction_dispatcher: \n- op_level_debug: False\n- onnxscript_graph: \n- onnxscript_tracer: \n- fx_name_to_onnxscript_value: Dict[length=91](\nx: `TorchScriptTensor(f32[4, 3, 512, 512])`,\np_trunk_patch_embed_proj_weight: `TorchScriptTensor(f32[1024, 3, 16, 16])`,\np_trunk_patch_embed_proj_bias: `TorchScriptTensor(f32[1024])`,\np_trunk_pos_embed: `TorchScriptTensor(f32[1, 1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_weight: `TorchScriptTensor(f32[3072, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_bias: `TorchScriptTensor(f32[3072])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_weight: `TorchScriptTensor(f32[1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_bias: `TorchScriptTensor(f32[1024])`,\n...\n)\n## Return values\n", + "text":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___7___attn_qkv_bias[name=p_getattr_l__self___trunk_blocks___7___attn_qkv_bias]. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"FxOnnxInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":414 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0008", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___7___attn_proj_weight[name=p_getattr_l__self___trunk_blocks___7___attn_proj_weight]. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature FxOnnxInterpreter.run_node\n- self: \n- node: fx.Node(p_getattr_l__self___trunk_blocks___7___attn_proj_weight)[placeholder]:Tensor(f32[1024, 1024])\n- fx_graph_module: torch.fx.GraphModule(timm_models_vision_transformer_VisionTransformer)\n- onnxfunction_dispatcher: \n- op_level_debug: False\n- onnxscript_graph: \n- onnxscript_tracer: \n- fx_name_to_onnxscript_value: Dict[length=92](\nx: `TorchScriptTensor(f32[4, 3, 512, 512])`,\np_trunk_patch_embed_proj_weight: `TorchScriptTensor(f32[1024, 3, 16, 16])`,\np_trunk_patch_embed_proj_bias: `TorchScriptTensor(f32[1024])`,\np_trunk_pos_embed: `TorchScriptTensor(f32[1, 1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_weight: `TorchScriptTensor(f32[3072, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_bias: `TorchScriptTensor(f32[3072])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_weight: `TorchScriptTensor(f32[1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_bias: `TorchScriptTensor(f32[1024])`,\n...\n)\n## Return values\n", + "text":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___7___attn_proj_weight[name=p_getattr_l__self___trunk_blocks___7___attn_proj_weight]. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"FxOnnxInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":414 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0008", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___7___attn_proj_bias[name=p_getattr_l__self___trunk_blocks___7___attn_proj_bias]. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature FxOnnxInterpreter.run_node\n- self: \n- node: fx.Node(p_getattr_l__self___trunk_blocks___7___attn_proj_bias)[placeholder]:Tensor(f32[1024])\n- fx_graph_module: torch.fx.GraphModule(timm_models_vision_transformer_VisionTransformer)\n- onnxfunction_dispatcher: \n- op_level_debug: False\n- onnxscript_graph: \n- onnxscript_tracer: \n- fx_name_to_onnxscript_value: Dict[length=93](\nx: `TorchScriptTensor(f32[4, 3, 512, 512])`,\np_trunk_patch_embed_proj_weight: `TorchScriptTensor(f32[1024, 3, 16, 16])`,\np_trunk_patch_embed_proj_bias: `TorchScriptTensor(f32[1024])`,\np_trunk_pos_embed: `TorchScriptTensor(f32[1, 1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_weight: `TorchScriptTensor(f32[3072, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_bias: `TorchScriptTensor(f32[3072])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_weight: `TorchScriptTensor(f32[1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_bias: `TorchScriptTensor(f32[1024])`,\n...\n)\n## Return values\n", + "text":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___7___attn_proj_bias[name=p_getattr_l__self___trunk_blocks___7___attn_proj_bias]. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"FxOnnxInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":414 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0008", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___7___norm2_weight[name=p_getattr_l__self___trunk_blocks___7___norm2_weight]. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature FxOnnxInterpreter.run_node\n- self: \n- node: fx.Node(p_getattr_l__self___trunk_blocks___7___norm2_weight)[placeholder]:Tensor(f32[1024])\n- fx_graph_module: torch.fx.GraphModule(timm_models_vision_transformer_VisionTransformer)\n- onnxfunction_dispatcher: \n- op_level_debug: False\n- onnxscript_graph: \n- onnxscript_tracer: \n- fx_name_to_onnxscript_value: Dict[length=94](\nx: `TorchScriptTensor(f32[4, 3, 512, 512])`,\np_trunk_patch_embed_proj_weight: `TorchScriptTensor(f32[1024, 3, 16, 16])`,\np_trunk_patch_embed_proj_bias: `TorchScriptTensor(f32[1024])`,\np_trunk_pos_embed: `TorchScriptTensor(f32[1, 1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_weight: `TorchScriptTensor(f32[3072, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_bias: `TorchScriptTensor(f32[3072])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_weight: `TorchScriptTensor(f32[1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_bias: `TorchScriptTensor(f32[1024])`,\n...\n)\n## Return values\n", + "text":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___7___norm2_weight[name=p_getattr_l__self___trunk_blocks___7___norm2_weight]. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"FxOnnxInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":414 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0008", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___7___norm2_bias[name=p_getattr_l__self___trunk_blocks___7___norm2_bias]. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature FxOnnxInterpreter.run_node\n- self: \n- node: fx.Node(p_getattr_l__self___trunk_blocks___7___norm2_bias)[placeholder]:Tensor(f32[1024])\n- fx_graph_module: torch.fx.GraphModule(timm_models_vision_transformer_VisionTransformer)\n- onnxfunction_dispatcher: \n- op_level_debug: False\n- onnxscript_graph: \n- onnxscript_tracer: \n- fx_name_to_onnxscript_value: Dict[length=95](\nx: `TorchScriptTensor(f32[4, 3, 512, 512])`,\np_trunk_patch_embed_proj_weight: `TorchScriptTensor(f32[1024, 3, 16, 16])`,\np_trunk_patch_embed_proj_bias: `TorchScriptTensor(f32[1024])`,\np_trunk_pos_embed: `TorchScriptTensor(f32[1, 1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_weight: `TorchScriptTensor(f32[3072, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_bias: `TorchScriptTensor(f32[3072])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_weight: `TorchScriptTensor(f32[1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_bias: `TorchScriptTensor(f32[1024])`,\n...\n)\n## Return values\n", + "text":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___7___norm2_bias[name=p_getattr_l__self___trunk_blocks___7___norm2_bias]. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"FxOnnxInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":414 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0008", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___7___mlp_fc1_weight[name=p_getattr_l__self___trunk_blocks___7___mlp_fc1_weight]. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature FxOnnxInterpreter.run_node\n- self: \n- node: fx.Node(p_getattr_l__self___trunk_blocks___7___mlp_fc1_weight)[placeholder]:Tensor(f32[4096, 1024])\n- fx_graph_module: torch.fx.GraphModule(timm_models_vision_transformer_VisionTransformer)\n- onnxfunction_dispatcher: \n- op_level_debug: False\n- onnxscript_graph: \n- onnxscript_tracer: \n- fx_name_to_onnxscript_value: Dict[length=96](\nx: `TorchScriptTensor(f32[4, 3, 512, 512])`,\np_trunk_patch_embed_proj_weight: `TorchScriptTensor(f32[1024, 3, 16, 16])`,\np_trunk_patch_embed_proj_bias: `TorchScriptTensor(f32[1024])`,\np_trunk_pos_embed: `TorchScriptTensor(f32[1, 1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_weight: `TorchScriptTensor(f32[3072, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_bias: `TorchScriptTensor(f32[3072])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_weight: `TorchScriptTensor(f32[1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_bias: `TorchScriptTensor(f32[1024])`,\n...\n)\n## Return values\n", + "text":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___7___mlp_fc1_weight[name=p_getattr_l__self___trunk_blocks___7___mlp_fc1_weight]. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"FxOnnxInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":414 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0008", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___7___mlp_fc1_bias[name=p_getattr_l__self___trunk_blocks___7___mlp_fc1_bias]. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature FxOnnxInterpreter.run_node\n- self: \n- node: fx.Node(p_getattr_l__self___trunk_blocks___7___mlp_fc1_bias)[placeholder]:Tensor(f32[4096])\n- fx_graph_module: torch.fx.GraphModule(timm_models_vision_transformer_VisionTransformer)\n- onnxfunction_dispatcher: \n- op_level_debug: False\n- onnxscript_graph: \n- onnxscript_tracer: \n- fx_name_to_onnxscript_value: Dict[length=97](\nx: `TorchScriptTensor(f32[4, 3, 512, 512])`,\np_trunk_patch_embed_proj_weight: `TorchScriptTensor(f32[1024, 3, 16, 16])`,\np_trunk_patch_embed_proj_bias: `TorchScriptTensor(f32[1024])`,\np_trunk_pos_embed: `TorchScriptTensor(f32[1, 1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_weight: `TorchScriptTensor(f32[3072, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_bias: `TorchScriptTensor(f32[3072])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_weight: `TorchScriptTensor(f32[1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_bias: `TorchScriptTensor(f32[1024])`,\n...\n)\n## Return values\n", + "text":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___7___mlp_fc1_bias[name=p_getattr_l__self___trunk_blocks___7___mlp_fc1_bias]. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"FxOnnxInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":414 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0008", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___7___mlp_fc2_weight[name=p_getattr_l__self___trunk_blocks___7___mlp_fc2_weight]. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature FxOnnxInterpreter.run_node\n- self: \n- node: fx.Node(p_getattr_l__self___trunk_blocks___7___mlp_fc2_weight)[placeholder]:Tensor(f32[1024, 4096])\n- fx_graph_module: torch.fx.GraphModule(timm_models_vision_transformer_VisionTransformer)\n- onnxfunction_dispatcher: \n- op_level_debug: False\n- onnxscript_graph: \n- onnxscript_tracer: \n- fx_name_to_onnxscript_value: Dict[length=98](\nx: `TorchScriptTensor(f32[4, 3, 512, 512])`,\np_trunk_patch_embed_proj_weight: `TorchScriptTensor(f32[1024, 3, 16, 16])`,\np_trunk_patch_embed_proj_bias: `TorchScriptTensor(f32[1024])`,\np_trunk_pos_embed: `TorchScriptTensor(f32[1, 1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_weight: `TorchScriptTensor(f32[3072, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_bias: `TorchScriptTensor(f32[3072])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_weight: `TorchScriptTensor(f32[1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_bias: `TorchScriptTensor(f32[1024])`,\n...\n)\n## Return values\n", + "text":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___7___mlp_fc2_weight[name=p_getattr_l__self___trunk_blocks___7___mlp_fc2_weight]. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"FxOnnxInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":414 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0008", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___7___mlp_fc2_bias[name=p_getattr_l__self___trunk_blocks___7___mlp_fc2_bias]. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature FxOnnxInterpreter.run_node\n- self: \n- node: fx.Node(p_getattr_l__self___trunk_blocks___7___mlp_fc2_bias)[placeholder]:Tensor(f32[1024])\n- fx_graph_module: torch.fx.GraphModule(timm_models_vision_transformer_VisionTransformer)\n- onnxfunction_dispatcher: \n- op_level_debug: False\n- onnxscript_graph: \n- onnxscript_tracer: \n- fx_name_to_onnxscript_value: Dict[length=99](\nx: `TorchScriptTensor(f32[4, 3, 512, 512])`,\np_trunk_patch_embed_proj_weight: `TorchScriptTensor(f32[1024, 3, 16, 16])`,\np_trunk_patch_embed_proj_bias: `TorchScriptTensor(f32[1024])`,\np_trunk_pos_embed: `TorchScriptTensor(f32[1, 1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_weight: `TorchScriptTensor(f32[3072, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_bias: `TorchScriptTensor(f32[3072])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_weight: `TorchScriptTensor(f32[1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_bias: `TorchScriptTensor(f32[1024])`,\n...\n)\n## Return values\n", + "text":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___7___mlp_fc2_bias[name=p_getattr_l__self___trunk_blocks___7___mlp_fc2_bias]. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"FxOnnxInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":414 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0008", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___8___norm1_weight[name=p_getattr_l__self___trunk_blocks___8___norm1_weight]. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature FxOnnxInterpreter.run_node\n- self: \n- node: fx.Node(p_getattr_l__self___trunk_blocks___8___norm1_weight)[placeholder]:Tensor(f32[1024])\n- fx_graph_module: torch.fx.GraphModule(timm_models_vision_transformer_VisionTransformer)\n- onnxfunction_dispatcher: \n- op_level_debug: False\n- onnxscript_graph: \n- onnxscript_tracer: \n- fx_name_to_onnxscript_value: Dict[length=100](\nx: `TorchScriptTensor(f32[4, 3, 512, 512])`,\np_trunk_patch_embed_proj_weight: `TorchScriptTensor(f32[1024, 3, 16, 16])`,\np_trunk_patch_embed_proj_bias: `TorchScriptTensor(f32[1024])`,\np_trunk_pos_embed: `TorchScriptTensor(f32[1, 1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_weight: `TorchScriptTensor(f32[3072, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_bias: `TorchScriptTensor(f32[3072])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_weight: `TorchScriptTensor(f32[1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_bias: `TorchScriptTensor(f32[1024])`,\n...\n)\n## Return values\n", + "text":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___8___norm1_weight[name=p_getattr_l__self___trunk_blocks___8___norm1_weight]. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"FxOnnxInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":414 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0008", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___8___norm1_bias[name=p_getattr_l__self___trunk_blocks___8___norm1_bias]. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature FxOnnxInterpreter.run_node\n- self: \n- node: fx.Node(p_getattr_l__self___trunk_blocks___8___norm1_bias)[placeholder]:Tensor(f32[1024])\n- fx_graph_module: torch.fx.GraphModule(timm_models_vision_transformer_VisionTransformer)\n- onnxfunction_dispatcher: \n- op_level_debug: False\n- onnxscript_graph: \n- onnxscript_tracer: \n- fx_name_to_onnxscript_value: Dict[length=101](\nx: `TorchScriptTensor(f32[4, 3, 512, 512])`,\np_trunk_patch_embed_proj_weight: `TorchScriptTensor(f32[1024, 3, 16, 16])`,\np_trunk_patch_embed_proj_bias: `TorchScriptTensor(f32[1024])`,\np_trunk_pos_embed: `TorchScriptTensor(f32[1, 1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_weight: `TorchScriptTensor(f32[3072, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_bias: `TorchScriptTensor(f32[3072])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_weight: `TorchScriptTensor(f32[1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_bias: `TorchScriptTensor(f32[1024])`,\n...\n)\n## Return values\n", + "text":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___8___norm1_bias[name=p_getattr_l__self___trunk_blocks___8___norm1_bias]. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"FxOnnxInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":414 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0008", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___8___attn_qkv_weight[name=p_getattr_l__self___trunk_blocks___8___attn_qkv_weight]. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature FxOnnxInterpreter.run_node\n- self: \n- node: fx.Node(p_getattr_l__self___trunk_blocks___8___attn_qkv_weight)[placeholder]:Tensor(f32[3072, 1024])\n- fx_graph_module: torch.fx.GraphModule(timm_models_vision_transformer_VisionTransformer)\n- onnxfunction_dispatcher: \n- op_level_debug: False\n- onnxscript_graph: \n- onnxscript_tracer: \n- fx_name_to_onnxscript_value: Dict[length=102](\nx: `TorchScriptTensor(f32[4, 3, 512, 512])`,\np_trunk_patch_embed_proj_weight: `TorchScriptTensor(f32[1024, 3, 16, 16])`,\np_trunk_patch_embed_proj_bias: `TorchScriptTensor(f32[1024])`,\np_trunk_pos_embed: `TorchScriptTensor(f32[1, 1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_weight: `TorchScriptTensor(f32[3072, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_bias: `TorchScriptTensor(f32[3072])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_weight: `TorchScriptTensor(f32[1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_bias: `TorchScriptTensor(f32[1024])`,\n...\n)\n## Return values\n", + "text":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___8___attn_qkv_weight[name=p_getattr_l__self___trunk_blocks___8___attn_qkv_weight]. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"FxOnnxInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":414 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0008", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___8___attn_qkv_bias[name=p_getattr_l__self___trunk_blocks___8___attn_qkv_bias]. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature FxOnnxInterpreter.run_node\n- self: \n- node: fx.Node(p_getattr_l__self___trunk_blocks___8___attn_qkv_bias)[placeholder]:Tensor(f32[3072])\n- fx_graph_module: torch.fx.GraphModule(timm_models_vision_transformer_VisionTransformer)\n- onnxfunction_dispatcher: \n- op_level_debug: False\n- onnxscript_graph: \n- onnxscript_tracer: \n- fx_name_to_onnxscript_value: Dict[length=103](\nx: `TorchScriptTensor(f32[4, 3, 512, 512])`,\np_trunk_patch_embed_proj_weight: `TorchScriptTensor(f32[1024, 3, 16, 16])`,\np_trunk_patch_embed_proj_bias: `TorchScriptTensor(f32[1024])`,\np_trunk_pos_embed: `TorchScriptTensor(f32[1, 1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_weight: `TorchScriptTensor(f32[3072, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_bias: `TorchScriptTensor(f32[3072])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_weight: `TorchScriptTensor(f32[1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_bias: `TorchScriptTensor(f32[1024])`,\n...\n)\n## Return values\n", + "text":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___8___attn_qkv_bias[name=p_getattr_l__self___trunk_blocks___8___attn_qkv_bias]. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"FxOnnxInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":414 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0008", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___8___attn_proj_weight[name=p_getattr_l__self___trunk_blocks___8___attn_proj_weight]. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature FxOnnxInterpreter.run_node\n- self: \n- node: fx.Node(p_getattr_l__self___trunk_blocks___8___attn_proj_weight)[placeholder]:Tensor(f32[1024, 1024])\n- fx_graph_module: torch.fx.GraphModule(timm_models_vision_transformer_VisionTransformer)\n- onnxfunction_dispatcher: \n- op_level_debug: False\n- onnxscript_graph: \n- onnxscript_tracer: \n- fx_name_to_onnxscript_value: Dict[length=104](\nx: `TorchScriptTensor(f32[4, 3, 512, 512])`,\np_trunk_patch_embed_proj_weight: `TorchScriptTensor(f32[1024, 3, 16, 16])`,\np_trunk_patch_embed_proj_bias: `TorchScriptTensor(f32[1024])`,\np_trunk_pos_embed: `TorchScriptTensor(f32[1, 1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_weight: `TorchScriptTensor(f32[3072, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_bias: `TorchScriptTensor(f32[3072])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_weight: `TorchScriptTensor(f32[1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_bias: `TorchScriptTensor(f32[1024])`,\n...\n)\n## Return values\n", + "text":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___8___attn_proj_weight[name=p_getattr_l__self___trunk_blocks___8___attn_proj_weight]. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"FxOnnxInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":414 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0008", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___8___attn_proj_bias[name=p_getattr_l__self___trunk_blocks___8___attn_proj_bias]. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature FxOnnxInterpreter.run_node\n- self: \n- node: fx.Node(p_getattr_l__self___trunk_blocks___8___attn_proj_bias)[placeholder]:Tensor(f32[1024])\n- fx_graph_module: torch.fx.GraphModule(timm_models_vision_transformer_VisionTransformer)\n- onnxfunction_dispatcher: \n- op_level_debug: False\n- onnxscript_graph: \n- onnxscript_tracer: \n- fx_name_to_onnxscript_value: Dict[length=105](\nx: `TorchScriptTensor(f32[4, 3, 512, 512])`,\np_trunk_patch_embed_proj_weight: `TorchScriptTensor(f32[1024, 3, 16, 16])`,\np_trunk_patch_embed_proj_bias: `TorchScriptTensor(f32[1024])`,\np_trunk_pos_embed: `TorchScriptTensor(f32[1, 1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_weight: `TorchScriptTensor(f32[3072, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_bias: `TorchScriptTensor(f32[3072])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_weight: `TorchScriptTensor(f32[1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_bias: `TorchScriptTensor(f32[1024])`,\n...\n)\n## Return values\n", + "text":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___8___attn_proj_bias[name=p_getattr_l__self___trunk_blocks___8___attn_proj_bias]. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"FxOnnxInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":414 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0008", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___8___norm2_weight[name=p_getattr_l__self___trunk_blocks___8___norm2_weight]. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature FxOnnxInterpreter.run_node\n- self: \n- node: fx.Node(p_getattr_l__self___trunk_blocks___8___norm2_weight)[placeholder]:Tensor(f32[1024])\n- fx_graph_module: torch.fx.GraphModule(timm_models_vision_transformer_VisionTransformer)\n- onnxfunction_dispatcher: \n- op_level_debug: False\n- onnxscript_graph: \n- onnxscript_tracer: \n- fx_name_to_onnxscript_value: Dict[length=106](\nx: `TorchScriptTensor(f32[4, 3, 512, 512])`,\np_trunk_patch_embed_proj_weight: `TorchScriptTensor(f32[1024, 3, 16, 16])`,\np_trunk_patch_embed_proj_bias: `TorchScriptTensor(f32[1024])`,\np_trunk_pos_embed: `TorchScriptTensor(f32[1, 1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_weight: `TorchScriptTensor(f32[3072, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_bias: `TorchScriptTensor(f32[3072])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_weight: `TorchScriptTensor(f32[1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_bias: `TorchScriptTensor(f32[1024])`,\n...\n)\n## Return values\n", + "text":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___8___norm2_weight[name=p_getattr_l__self___trunk_blocks___8___norm2_weight]. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"FxOnnxInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":414 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0008", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___8___norm2_bias[name=p_getattr_l__self___trunk_blocks___8___norm2_bias]. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature FxOnnxInterpreter.run_node\n- self: \n- node: fx.Node(p_getattr_l__self___trunk_blocks___8___norm2_bias)[placeholder]:Tensor(f32[1024])\n- fx_graph_module: torch.fx.GraphModule(timm_models_vision_transformer_VisionTransformer)\n- onnxfunction_dispatcher: \n- op_level_debug: False\n- onnxscript_graph: \n- onnxscript_tracer: \n- fx_name_to_onnxscript_value: Dict[length=107](\nx: `TorchScriptTensor(f32[4, 3, 512, 512])`,\np_trunk_patch_embed_proj_weight: `TorchScriptTensor(f32[1024, 3, 16, 16])`,\np_trunk_patch_embed_proj_bias: `TorchScriptTensor(f32[1024])`,\np_trunk_pos_embed: `TorchScriptTensor(f32[1, 1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_weight: `TorchScriptTensor(f32[3072, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_bias: `TorchScriptTensor(f32[3072])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_weight: `TorchScriptTensor(f32[1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_bias: `TorchScriptTensor(f32[1024])`,\n...\n)\n## Return values\n", + "text":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___8___norm2_bias[name=p_getattr_l__self___trunk_blocks___8___norm2_bias]. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"FxOnnxInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":414 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0008", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___8___mlp_fc1_weight[name=p_getattr_l__self___trunk_blocks___8___mlp_fc1_weight]. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature FxOnnxInterpreter.run_node\n- self: \n- node: fx.Node(p_getattr_l__self___trunk_blocks___8___mlp_fc1_weight)[placeholder]:Tensor(f32[4096, 1024])\n- fx_graph_module: torch.fx.GraphModule(timm_models_vision_transformer_VisionTransformer)\n- onnxfunction_dispatcher: \n- op_level_debug: False\n- onnxscript_graph: \n- onnxscript_tracer: \n- fx_name_to_onnxscript_value: Dict[length=108](\nx: `TorchScriptTensor(f32[4, 3, 512, 512])`,\np_trunk_patch_embed_proj_weight: `TorchScriptTensor(f32[1024, 3, 16, 16])`,\np_trunk_patch_embed_proj_bias: `TorchScriptTensor(f32[1024])`,\np_trunk_pos_embed: `TorchScriptTensor(f32[1, 1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_weight: `TorchScriptTensor(f32[3072, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_bias: `TorchScriptTensor(f32[3072])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_weight: `TorchScriptTensor(f32[1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_bias: `TorchScriptTensor(f32[1024])`,\n...\n)\n## Return values\n", + "text":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___8___mlp_fc1_weight[name=p_getattr_l__self___trunk_blocks___8___mlp_fc1_weight]. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"FxOnnxInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":414 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0008", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___8___mlp_fc1_bias[name=p_getattr_l__self___trunk_blocks___8___mlp_fc1_bias]. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature FxOnnxInterpreter.run_node\n- self: \n- node: fx.Node(p_getattr_l__self___trunk_blocks___8___mlp_fc1_bias)[placeholder]:Tensor(f32[4096])\n- fx_graph_module: torch.fx.GraphModule(timm_models_vision_transformer_VisionTransformer)\n- onnxfunction_dispatcher: \n- op_level_debug: False\n- onnxscript_graph: \n- onnxscript_tracer: \n- fx_name_to_onnxscript_value: Dict[length=109](\nx: `TorchScriptTensor(f32[4, 3, 512, 512])`,\np_trunk_patch_embed_proj_weight: `TorchScriptTensor(f32[1024, 3, 16, 16])`,\np_trunk_patch_embed_proj_bias: `TorchScriptTensor(f32[1024])`,\np_trunk_pos_embed: `TorchScriptTensor(f32[1, 1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_weight: `TorchScriptTensor(f32[3072, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_bias: `TorchScriptTensor(f32[3072])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_weight: `TorchScriptTensor(f32[1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_bias: `TorchScriptTensor(f32[1024])`,\n...\n)\n## Return values\n", + "text":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___8___mlp_fc1_bias[name=p_getattr_l__self___trunk_blocks___8___mlp_fc1_bias]. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"FxOnnxInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":414 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0008", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___8___mlp_fc2_weight[name=p_getattr_l__self___trunk_blocks___8___mlp_fc2_weight]. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature FxOnnxInterpreter.run_node\n- self: \n- node: fx.Node(p_getattr_l__self___trunk_blocks___8___mlp_fc2_weight)[placeholder]:Tensor(f32[1024, 4096])\n- fx_graph_module: torch.fx.GraphModule(timm_models_vision_transformer_VisionTransformer)\n- onnxfunction_dispatcher: \n- op_level_debug: False\n- onnxscript_graph: \n- onnxscript_tracer: \n- fx_name_to_onnxscript_value: Dict[length=110](\nx: `TorchScriptTensor(f32[4, 3, 512, 512])`,\np_trunk_patch_embed_proj_weight: `TorchScriptTensor(f32[1024, 3, 16, 16])`,\np_trunk_patch_embed_proj_bias: `TorchScriptTensor(f32[1024])`,\np_trunk_pos_embed: `TorchScriptTensor(f32[1, 1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_weight: `TorchScriptTensor(f32[3072, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_bias: `TorchScriptTensor(f32[3072])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_weight: `TorchScriptTensor(f32[1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_bias: `TorchScriptTensor(f32[1024])`,\n...\n)\n## Return values\n", + "text":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___8___mlp_fc2_weight[name=p_getattr_l__self___trunk_blocks___8___mlp_fc2_weight]. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"FxOnnxInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":414 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0008", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___8___mlp_fc2_bias[name=p_getattr_l__self___trunk_blocks___8___mlp_fc2_bias]. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature FxOnnxInterpreter.run_node\n- self: \n- node: fx.Node(p_getattr_l__self___trunk_blocks___8___mlp_fc2_bias)[placeholder]:Tensor(f32[1024])\n- fx_graph_module: torch.fx.GraphModule(timm_models_vision_transformer_VisionTransformer)\n- onnxfunction_dispatcher: \n- op_level_debug: False\n- onnxscript_graph: \n- onnxscript_tracer: \n- fx_name_to_onnxscript_value: Dict[length=111](\nx: `TorchScriptTensor(f32[4, 3, 512, 512])`,\np_trunk_patch_embed_proj_weight: `TorchScriptTensor(f32[1024, 3, 16, 16])`,\np_trunk_patch_embed_proj_bias: `TorchScriptTensor(f32[1024])`,\np_trunk_pos_embed: `TorchScriptTensor(f32[1, 1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_weight: `TorchScriptTensor(f32[3072, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_bias: `TorchScriptTensor(f32[3072])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_weight: `TorchScriptTensor(f32[1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_bias: `TorchScriptTensor(f32[1024])`,\n...\n)\n## Return values\n", + "text":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___8___mlp_fc2_bias[name=p_getattr_l__self___trunk_blocks___8___mlp_fc2_bias]. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"FxOnnxInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":414 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0008", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___9___norm1_weight[name=p_getattr_l__self___trunk_blocks___9___norm1_weight]. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature FxOnnxInterpreter.run_node\n- self: \n- node: fx.Node(p_getattr_l__self___trunk_blocks___9___norm1_weight)[placeholder]:Tensor(f32[1024])\n- fx_graph_module: torch.fx.GraphModule(timm_models_vision_transformer_VisionTransformer)\n- onnxfunction_dispatcher: \n- op_level_debug: False\n- onnxscript_graph: \n- onnxscript_tracer: \n- fx_name_to_onnxscript_value: Dict[length=112](\nx: `TorchScriptTensor(f32[4, 3, 512, 512])`,\np_trunk_patch_embed_proj_weight: `TorchScriptTensor(f32[1024, 3, 16, 16])`,\np_trunk_patch_embed_proj_bias: `TorchScriptTensor(f32[1024])`,\np_trunk_pos_embed: `TorchScriptTensor(f32[1, 1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_weight: `TorchScriptTensor(f32[3072, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_bias: `TorchScriptTensor(f32[3072])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_weight: `TorchScriptTensor(f32[1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_bias: `TorchScriptTensor(f32[1024])`,\n...\n)\n## Return values\n", + "text":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___9___norm1_weight[name=p_getattr_l__self___trunk_blocks___9___norm1_weight]. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"FxOnnxInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":414 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0008", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___9___norm1_bias[name=p_getattr_l__self___trunk_blocks___9___norm1_bias]. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature FxOnnxInterpreter.run_node\n- self: \n- node: fx.Node(p_getattr_l__self___trunk_blocks___9___norm1_bias)[placeholder]:Tensor(f32[1024])\n- fx_graph_module: torch.fx.GraphModule(timm_models_vision_transformer_VisionTransformer)\n- onnxfunction_dispatcher: \n- op_level_debug: False\n- onnxscript_graph: \n- onnxscript_tracer: \n- fx_name_to_onnxscript_value: Dict[length=113](\nx: `TorchScriptTensor(f32[4, 3, 512, 512])`,\np_trunk_patch_embed_proj_weight: `TorchScriptTensor(f32[1024, 3, 16, 16])`,\np_trunk_patch_embed_proj_bias: `TorchScriptTensor(f32[1024])`,\np_trunk_pos_embed: `TorchScriptTensor(f32[1, 1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_weight: `TorchScriptTensor(f32[3072, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_bias: `TorchScriptTensor(f32[3072])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_weight: `TorchScriptTensor(f32[1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_bias: `TorchScriptTensor(f32[1024])`,\n...\n)\n## Return values\n", + "text":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___9___norm1_bias[name=p_getattr_l__self___trunk_blocks___9___norm1_bias]. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"FxOnnxInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":414 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0008", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___9___attn_qkv_weight[name=p_getattr_l__self___trunk_blocks___9___attn_qkv_weight]. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature FxOnnxInterpreter.run_node\n- self: \n- node: fx.Node(p_getattr_l__self___trunk_blocks___9___attn_qkv_weight)[placeholder]:Tensor(f32[3072, 1024])\n- fx_graph_module: torch.fx.GraphModule(timm_models_vision_transformer_VisionTransformer)\n- onnxfunction_dispatcher: \n- op_level_debug: False\n- onnxscript_graph: \n- onnxscript_tracer: \n- fx_name_to_onnxscript_value: Dict[length=114](\nx: `TorchScriptTensor(f32[4, 3, 512, 512])`,\np_trunk_patch_embed_proj_weight: `TorchScriptTensor(f32[1024, 3, 16, 16])`,\np_trunk_patch_embed_proj_bias: `TorchScriptTensor(f32[1024])`,\np_trunk_pos_embed: `TorchScriptTensor(f32[1, 1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_weight: `TorchScriptTensor(f32[3072, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_bias: `TorchScriptTensor(f32[3072])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_weight: `TorchScriptTensor(f32[1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_bias: `TorchScriptTensor(f32[1024])`,\n...\n)\n## Return values\n", + "text":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___9___attn_qkv_weight[name=p_getattr_l__self___trunk_blocks___9___attn_qkv_weight]. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"FxOnnxInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":414 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0008", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___9___attn_qkv_bias[name=p_getattr_l__self___trunk_blocks___9___attn_qkv_bias]. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature FxOnnxInterpreter.run_node\n- self: \n- node: fx.Node(p_getattr_l__self___trunk_blocks___9___attn_qkv_bias)[placeholder]:Tensor(f32[3072])\n- fx_graph_module: torch.fx.GraphModule(timm_models_vision_transformer_VisionTransformer)\n- onnxfunction_dispatcher: \n- op_level_debug: False\n- onnxscript_graph: \n- onnxscript_tracer: \n- fx_name_to_onnxscript_value: Dict[length=115](\nx: `TorchScriptTensor(f32[4, 3, 512, 512])`,\np_trunk_patch_embed_proj_weight: `TorchScriptTensor(f32[1024, 3, 16, 16])`,\np_trunk_patch_embed_proj_bias: `TorchScriptTensor(f32[1024])`,\np_trunk_pos_embed: `TorchScriptTensor(f32[1, 1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_weight: `TorchScriptTensor(f32[3072, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_bias: `TorchScriptTensor(f32[3072])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_weight: `TorchScriptTensor(f32[1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_bias: `TorchScriptTensor(f32[1024])`,\n...\n)\n## Return values\n", + "text":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___9___attn_qkv_bias[name=p_getattr_l__self___trunk_blocks___9___attn_qkv_bias]. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"FxOnnxInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":414 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0008", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___9___attn_proj_weight[name=p_getattr_l__self___trunk_blocks___9___attn_proj_weight]. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature FxOnnxInterpreter.run_node\n- self: \n- node: fx.Node(p_getattr_l__self___trunk_blocks___9___attn_proj_weight)[placeholder]:Tensor(f32[1024, 1024])\n- fx_graph_module: torch.fx.GraphModule(timm_models_vision_transformer_VisionTransformer)\n- onnxfunction_dispatcher: \n- op_level_debug: False\n- onnxscript_graph: \n- onnxscript_tracer: \n- fx_name_to_onnxscript_value: Dict[length=116](\nx: `TorchScriptTensor(f32[4, 3, 512, 512])`,\np_trunk_patch_embed_proj_weight: `TorchScriptTensor(f32[1024, 3, 16, 16])`,\np_trunk_patch_embed_proj_bias: `TorchScriptTensor(f32[1024])`,\np_trunk_pos_embed: `TorchScriptTensor(f32[1, 1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_weight: `TorchScriptTensor(f32[3072, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_bias: `TorchScriptTensor(f32[3072])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_weight: `TorchScriptTensor(f32[1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_bias: `TorchScriptTensor(f32[1024])`,\n...\n)\n## Return values\n", + "text":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___9___attn_proj_weight[name=p_getattr_l__self___trunk_blocks___9___attn_proj_weight]. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"FxOnnxInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":414 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0008", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___9___attn_proj_bias[name=p_getattr_l__self___trunk_blocks___9___attn_proj_bias]. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature FxOnnxInterpreter.run_node\n- self: \n- node: fx.Node(p_getattr_l__self___trunk_blocks___9___attn_proj_bias)[placeholder]:Tensor(f32[1024])\n- fx_graph_module: torch.fx.GraphModule(timm_models_vision_transformer_VisionTransformer)\n- onnxfunction_dispatcher: \n- op_level_debug: False\n- onnxscript_graph: \n- onnxscript_tracer: \n- fx_name_to_onnxscript_value: Dict[length=117](\nx: `TorchScriptTensor(f32[4, 3, 512, 512])`,\np_trunk_patch_embed_proj_weight: `TorchScriptTensor(f32[1024, 3, 16, 16])`,\np_trunk_patch_embed_proj_bias: `TorchScriptTensor(f32[1024])`,\np_trunk_pos_embed: `TorchScriptTensor(f32[1, 1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_weight: `TorchScriptTensor(f32[3072, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_bias: `TorchScriptTensor(f32[3072])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_weight: `TorchScriptTensor(f32[1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_bias: `TorchScriptTensor(f32[1024])`,\n...\n)\n## Return values\n", + "text":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___9___attn_proj_bias[name=p_getattr_l__self___trunk_blocks___9___attn_proj_bias]. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"FxOnnxInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":414 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0008", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___9___norm2_weight[name=p_getattr_l__self___trunk_blocks___9___norm2_weight]. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature FxOnnxInterpreter.run_node\n- self: \n- node: fx.Node(p_getattr_l__self___trunk_blocks___9___norm2_weight)[placeholder]:Tensor(f32[1024])\n- fx_graph_module: torch.fx.GraphModule(timm_models_vision_transformer_VisionTransformer)\n- onnxfunction_dispatcher: \n- op_level_debug: False\n- onnxscript_graph: \n- onnxscript_tracer: \n- fx_name_to_onnxscript_value: Dict[length=118](\nx: `TorchScriptTensor(f32[4, 3, 512, 512])`,\np_trunk_patch_embed_proj_weight: `TorchScriptTensor(f32[1024, 3, 16, 16])`,\np_trunk_patch_embed_proj_bias: `TorchScriptTensor(f32[1024])`,\np_trunk_pos_embed: `TorchScriptTensor(f32[1, 1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_weight: `TorchScriptTensor(f32[3072, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_bias: `TorchScriptTensor(f32[3072])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_weight: `TorchScriptTensor(f32[1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_bias: `TorchScriptTensor(f32[1024])`,\n...\n)\n## Return values\n", + "text":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___9___norm2_weight[name=p_getattr_l__self___trunk_blocks___9___norm2_weight]. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"FxOnnxInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":414 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0008", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___9___norm2_bias[name=p_getattr_l__self___trunk_blocks___9___norm2_bias]. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature FxOnnxInterpreter.run_node\n- self: \n- node: fx.Node(p_getattr_l__self___trunk_blocks___9___norm2_bias)[placeholder]:Tensor(f32[1024])\n- fx_graph_module: torch.fx.GraphModule(timm_models_vision_transformer_VisionTransformer)\n- onnxfunction_dispatcher: \n- op_level_debug: False\n- onnxscript_graph: \n- onnxscript_tracer: \n- fx_name_to_onnxscript_value: Dict[length=119](\nx: `TorchScriptTensor(f32[4, 3, 512, 512])`,\np_trunk_patch_embed_proj_weight: `TorchScriptTensor(f32[1024, 3, 16, 16])`,\np_trunk_patch_embed_proj_bias: `TorchScriptTensor(f32[1024])`,\np_trunk_pos_embed: `TorchScriptTensor(f32[1, 1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_weight: `TorchScriptTensor(f32[3072, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_bias: `TorchScriptTensor(f32[3072])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_weight: `TorchScriptTensor(f32[1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_bias: `TorchScriptTensor(f32[1024])`,\n...\n)\n## Return values\n", + "text":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___9___norm2_bias[name=p_getattr_l__self___trunk_blocks___9___norm2_bias]. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"FxOnnxInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":414 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0008", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___9___mlp_fc1_weight[name=p_getattr_l__self___trunk_blocks___9___mlp_fc1_weight]. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature FxOnnxInterpreter.run_node\n- self: \n- node: fx.Node(p_getattr_l__self___trunk_blocks___9___mlp_fc1_weight)[placeholder]:Tensor(f32[4096, 1024])\n- fx_graph_module: torch.fx.GraphModule(timm_models_vision_transformer_VisionTransformer)\n- onnxfunction_dispatcher: \n- op_level_debug: False\n- onnxscript_graph: \n- onnxscript_tracer: \n- fx_name_to_onnxscript_value: Dict[length=120](\nx: `TorchScriptTensor(f32[4, 3, 512, 512])`,\np_trunk_patch_embed_proj_weight: `TorchScriptTensor(f32[1024, 3, 16, 16])`,\np_trunk_patch_embed_proj_bias: `TorchScriptTensor(f32[1024])`,\np_trunk_pos_embed: `TorchScriptTensor(f32[1, 1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_weight: `TorchScriptTensor(f32[3072, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_bias: `TorchScriptTensor(f32[3072])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_weight: `TorchScriptTensor(f32[1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_bias: `TorchScriptTensor(f32[1024])`,\n...\n)\n## Return values\n", + "text":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___9___mlp_fc1_weight[name=p_getattr_l__self___trunk_blocks___9___mlp_fc1_weight]. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"FxOnnxInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":414 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0008", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___9___mlp_fc1_bias[name=p_getattr_l__self___trunk_blocks___9___mlp_fc1_bias]. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature FxOnnxInterpreter.run_node\n- self: \n- node: fx.Node(p_getattr_l__self___trunk_blocks___9___mlp_fc1_bias)[placeholder]:Tensor(f32[4096])\n- fx_graph_module: torch.fx.GraphModule(timm_models_vision_transformer_VisionTransformer)\n- onnxfunction_dispatcher: \n- op_level_debug: False\n- onnxscript_graph: \n- onnxscript_tracer: \n- fx_name_to_onnxscript_value: Dict[length=121](\nx: `TorchScriptTensor(f32[4, 3, 512, 512])`,\np_trunk_patch_embed_proj_weight: `TorchScriptTensor(f32[1024, 3, 16, 16])`,\np_trunk_patch_embed_proj_bias: `TorchScriptTensor(f32[1024])`,\np_trunk_pos_embed: `TorchScriptTensor(f32[1, 1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_weight: `TorchScriptTensor(f32[3072, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_bias: `TorchScriptTensor(f32[3072])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_weight: `TorchScriptTensor(f32[1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_bias: `TorchScriptTensor(f32[1024])`,\n...\n)\n## Return values\n", + "text":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___9___mlp_fc1_bias[name=p_getattr_l__self___trunk_blocks___9___mlp_fc1_bias]. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"FxOnnxInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":414 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0008", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___9___mlp_fc2_weight[name=p_getattr_l__self___trunk_blocks___9___mlp_fc2_weight]. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature FxOnnxInterpreter.run_node\n- self: \n- node: fx.Node(p_getattr_l__self___trunk_blocks___9___mlp_fc2_weight)[placeholder]:Tensor(f32[1024, 4096])\n- fx_graph_module: torch.fx.GraphModule(timm_models_vision_transformer_VisionTransformer)\n- onnxfunction_dispatcher: \n- op_level_debug: False\n- onnxscript_graph: \n- onnxscript_tracer: \n- fx_name_to_onnxscript_value: Dict[length=122](\nx: `TorchScriptTensor(f32[4, 3, 512, 512])`,\np_trunk_patch_embed_proj_weight: `TorchScriptTensor(f32[1024, 3, 16, 16])`,\np_trunk_patch_embed_proj_bias: `TorchScriptTensor(f32[1024])`,\np_trunk_pos_embed: `TorchScriptTensor(f32[1, 1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_weight: `TorchScriptTensor(f32[3072, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_bias: `TorchScriptTensor(f32[3072])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_weight: `TorchScriptTensor(f32[1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_bias: `TorchScriptTensor(f32[1024])`,\n...\n)\n## Return values\n", + "text":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___9___mlp_fc2_weight[name=p_getattr_l__self___trunk_blocks___9___mlp_fc2_weight]. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"FxOnnxInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":414 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0008", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___9___mlp_fc2_bias[name=p_getattr_l__self___trunk_blocks___9___mlp_fc2_bias]. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature FxOnnxInterpreter.run_node\n- self: \n- node: fx.Node(p_getattr_l__self___trunk_blocks___9___mlp_fc2_bias)[placeholder]:Tensor(f32[1024])\n- fx_graph_module: torch.fx.GraphModule(timm_models_vision_transformer_VisionTransformer)\n- onnxfunction_dispatcher: \n- op_level_debug: False\n- onnxscript_graph: \n- onnxscript_tracer: \n- fx_name_to_onnxscript_value: Dict[length=123](\nx: `TorchScriptTensor(f32[4, 3, 512, 512])`,\np_trunk_patch_embed_proj_weight: `TorchScriptTensor(f32[1024, 3, 16, 16])`,\np_trunk_patch_embed_proj_bias: `TorchScriptTensor(f32[1024])`,\np_trunk_pos_embed: `TorchScriptTensor(f32[1, 1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_weight: `TorchScriptTensor(f32[3072, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_bias: `TorchScriptTensor(f32[3072])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_weight: `TorchScriptTensor(f32[1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_bias: `TorchScriptTensor(f32[1024])`,\n...\n)\n## Return values\n", + "text":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___9___mlp_fc2_bias[name=p_getattr_l__self___trunk_blocks___9___mlp_fc2_bias]. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"FxOnnxInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":414 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0008", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___10___norm1_weight[name=p_getattr_l__self___trunk_blocks___10___norm1_weight]. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature FxOnnxInterpreter.run_node\n- self: \n- node: fx.Node(p_getattr_l__self___trunk_blocks___10___norm1_weight)[placeholder]:Tensor(f32[1024])\n- fx_graph_module: torch.fx.GraphModule(timm_models_vision_transformer_VisionTransformer)\n- onnxfunction_dispatcher: \n- op_level_debug: False\n- onnxscript_graph: \n- onnxscript_tracer: \n- fx_name_to_onnxscript_value: Dict[length=124](\nx: `TorchScriptTensor(f32[4, 3, 512, 512])`,\np_trunk_patch_embed_proj_weight: `TorchScriptTensor(f32[1024, 3, 16, 16])`,\np_trunk_patch_embed_proj_bias: `TorchScriptTensor(f32[1024])`,\np_trunk_pos_embed: `TorchScriptTensor(f32[1, 1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_weight: `TorchScriptTensor(f32[3072, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_bias: `TorchScriptTensor(f32[3072])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_weight: `TorchScriptTensor(f32[1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_bias: `TorchScriptTensor(f32[1024])`,\n...\n)\n## Return values\n", + "text":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___10___norm1_weight[name=p_getattr_l__self___trunk_blocks___10___norm1_weight]. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"FxOnnxInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":414 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0008", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___10___norm1_bias[name=p_getattr_l__self___trunk_blocks___10___norm1_bias]. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature FxOnnxInterpreter.run_node\n- self: \n- node: fx.Node(p_getattr_l__self___trunk_blocks___10___norm1_bias)[placeholder]:Tensor(f32[1024])\n- fx_graph_module: torch.fx.GraphModule(timm_models_vision_transformer_VisionTransformer)\n- onnxfunction_dispatcher: \n- op_level_debug: False\n- onnxscript_graph: \n- onnxscript_tracer: \n- fx_name_to_onnxscript_value: Dict[length=125](\nx: `TorchScriptTensor(f32[4, 3, 512, 512])`,\np_trunk_patch_embed_proj_weight: `TorchScriptTensor(f32[1024, 3, 16, 16])`,\np_trunk_patch_embed_proj_bias: `TorchScriptTensor(f32[1024])`,\np_trunk_pos_embed: `TorchScriptTensor(f32[1, 1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_weight: `TorchScriptTensor(f32[3072, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_bias: `TorchScriptTensor(f32[3072])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_weight: `TorchScriptTensor(f32[1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_bias: `TorchScriptTensor(f32[1024])`,\n...\n)\n## Return values\n", + "text":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___10___norm1_bias[name=p_getattr_l__self___trunk_blocks___10___norm1_bias]. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"FxOnnxInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":414 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0008", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___10___attn_qkv_weight[name=p_getattr_l__self___trunk_blocks___10___attn_qkv_weight]. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature FxOnnxInterpreter.run_node\n- self: \n- node: fx.Node(p_getattr_l__self___trunk_blocks___10___attn_qkv_weight)[placeholder]:Tensor(f32[3072, 1024])\n- fx_graph_module: torch.fx.GraphModule(timm_models_vision_transformer_VisionTransformer)\n- onnxfunction_dispatcher: \n- op_level_debug: False\n- onnxscript_graph: \n- onnxscript_tracer: \n- fx_name_to_onnxscript_value: Dict[length=126](\nx: `TorchScriptTensor(f32[4, 3, 512, 512])`,\np_trunk_patch_embed_proj_weight: `TorchScriptTensor(f32[1024, 3, 16, 16])`,\np_trunk_patch_embed_proj_bias: `TorchScriptTensor(f32[1024])`,\np_trunk_pos_embed: `TorchScriptTensor(f32[1, 1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_weight: `TorchScriptTensor(f32[3072, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_bias: `TorchScriptTensor(f32[3072])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_weight: `TorchScriptTensor(f32[1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_bias: `TorchScriptTensor(f32[1024])`,\n...\n)\n## Return values\n", + "text":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___10___attn_qkv_weight[name=p_getattr_l__self___trunk_blocks___10___attn_qkv_weight]. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"FxOnnxInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":414 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0008", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___10___attn_qkv_bias[name=p_getattr_l__self___trunk_blocks___10___attn_qkv_bias]. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature FxOnnxInterpreter.run_node\n- self: \n- node: fx.Node(p_getattr_l__self___trunk_blocks___10___attn_qkv_bias)[placeholder]:Tensor(f32[3072])\n- fx_graph_module: torch.fx.GraphModule(timm_models_vision_transformer_VisionTransformer)\n- onnxfunction_dispatcher: \n- op_level_debug: False\n- onnxscript_graph: \n- onnxscript_tracer: \n- fx_name_to_onnxscript_value: Dict[length=127](\nx: `TorchScriptTensor(f32[4, 3, 512, 512])`,\np_trunk_patch_embed_proj_weight: `TorchScriptTensor(f32[1024, 3, 16, 16])`,\np_trunk_patch_embed_proj_bias: `TorchScriptTensor(f32[1024])`,\np_trunk_pos_embed: `TorchScriptTensor(f32[1, 1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_weight: `TorchScriptTensor(f32[3072, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_bias: `TorchScriptTensor(f32[3072])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_weight: `TorchScriptTensor(f32[1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_bias: `TorchScriptTensor(f32[1024])`,\n...\n)\n## Return values\n", + "text":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___10___attn_qkv_bias[name=p_getattr_l__self___trunk_blocks___10___attn_qkv_bias]. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"FxOnnxInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":414 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0008", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___10___attn_proj_weight[name=p_getattr_l__self___trunk_blocks___10___attn_proj_weight]. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature FxOnnxInterpreter.run_node\n- self: \n- node: fx.Node(p_getattr_l__self___trunk_blocks___10___attn_proj_weight)[placeholder]:Tensor(f32[1024, 1024])\n- fx_graph_module: torch.fx.GraphModule(timm_models_vision_transformer_VisionTransformer)\n- onnxfunction_dispatcher: \n- op_level_debug: False\n- onnxscript_graph: \n- onnxscript_tracer: \n- fx_name_to_onnxscript_value: Dict[length=128](\nx: `TorchScriptTensor(f32[4, 3, 512, 512])`,\np_trunk_patch_embed_proj_weight: `TorchScriptTensor(f32[1024, 3, 16, 16])`,\np_trunk_patch_embed_proj_bias: `TorchScriptTensor(f32[1024])`,\np_trunk_pos_embed: `TorchScriptTensor(f32[1, 1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_weight: `TorchScriptTensor(f32[3072, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_bias: `TorchScriptTensor(f32[3072])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_weight: `TorchScriptTensor(f32[1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_bias: `TorchScriptTensor(f32[1024])`,\n...\n)\n## Return values\n", + "text":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___10___attn_proj_weight[name=p_getattr_l__self___trunk_blocks___10___attn_proj_weight]. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"FxOnnxInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":414 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0008", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___10___attn_proj_bias[name=p_getattr_l__self___trunk_blocks___10___attn_proj_bias]. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature FxOnnxInterpreter.run_node\n- self: \n- node: fx.Node(p_getattr_l__self___trunk_blocks___10___attn_proj_bias)[placeholder]:Tensor(f32[1024])\n- fx_graph_module: torch.fx.GraphModule(timm_models_vision_transformer_VisionTransformer)\n- onnxfunction_dispatcher: \n- op_level_debug: False\n- onnxscript_graph: \n- onnxscript_tracer: \n- fx_name_to_onnxscript_value: Dict[length=129](\nx: `TorchScriptTensor(f32[4, 3, 512, 512])`,\np_trunk_patch_embed_proj_weight: `TorchScriptTensor(f32[1024, 3, 16, 16])`,\np_trunk_patch_embed_proj_bias: `TorchScriptTensor(f32[1024])`,\np_trunk_pos_embed: `TorchScriptTensor(f32[1, 1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_weight: `TorchScriptTensor(f32[3072, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_bias: `TorchScriptTensor(f32[3072])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_weight: `TorchScriptTensor(f32[1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_bias: `TorchScriptTensor(f32[1024])`,\n...\n)\n## Return values\n", + "text":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___10___attn_proj_bias[name=p_getattr_l__self___trunk_blocks___10___attn_proj_bias]. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"FxOnnxInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":414 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0008", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___10___norm2_weight[name=p_getattr_l__self___trunk_blocks___10___norm2_weight]. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature FxOnnxInterpreter.run_node\n- self: \n- node: fx.Node(p_getattr_l__self___trunk_blocks___10___norm2_weight)[placeholder]:Tensor(f32[1024])\n- fx_graph_module: torch.fx.GraphModule(timm_models_vision_transformer_VisionTransformer)\n- onnxfunction_dispatcher: \n- op_level_debug: False\n- onnxscript_graph: \n- onnxscript_tracer: \n- fx_name_to_onnxscript_value: Dict[length=130](\nx: `TorchScriptTensor(f32[4, 3, 512, 512])`,\np_trunk_patch_embed_proj_weight: `TorchScriptTensor(f32[1024, 3, 16, 16])`,\np_trunk_patch_embed_proj_bias: `TorchScriptTensor(f32[1024])`,\np_trunk_pos_embed: `TorchScriptTensor(f32[1, 1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_weight: `TorchScriptTensor(f32[3072, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_bias: `TorchScriptTensor(f32[3072])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_weight: `TorchScriptTensor(f32[1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_bias: `TorchScriptTensor(f32[1024])`,\n...\n)\n## Return values\n", + "text":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___10___norm2_weight[name=p_getattr_l__self___trunk_blocks___10___norm2_weight]. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"FxOnnxInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":414 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0008", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___10___norm2_bias[name=p_getattr_l__self___trunk_blocks___10___norm2_bias]. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature FxOnnxInterpreter.run_node\n- self: \n- node: fx.Node(p_getattr_l__self___trunk_blocks___10___norm2_bias)[placeholder]:Tensor(f32[1024])\n- fx_graph_module: torch.fx.GraphModule(timm_models_vision_transformer_VisionTransformer)\n- onnxfunction_dispatcher: \n- op_level_debug: False\n- onnxscript_graph: \n- onnxscript_tracer: \n- fx_name_to_onnxscript_value: Dict[length=131](\nx: `TorchScriptTensor(f32[4, 3, 512, 512])`,\np_trunk_patch_embed_proj_weight: `TorchScriptTensor(f32[1024, 3, 16, 16])`,\np_trunk_patch_embed_proj_bias: `TorchScriptTensor(f32[1024])`,\np_trunk_pos_embed: `TorchScriptTensor(f32[1, 1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_weight: `TorchScriptTensor(f32[3072, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_bias: `TorchScriptTensor(f32[3072])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_weight: `TorchScriptTensor(f32[1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_bias: `TorchScriptTensor(f32[1024])`,\n...\n)\n## Return values\n", + "text":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___10___norm2_bias[name=p_getattr_l__self___trunk_blocks___10___norm2_bias]. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"FxOnnxInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":414 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0008", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___10___mlp_fc1_weight[name=p_getattr_l__self___trunk_blocks___10___mlp_fc1_weight]. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature FxOnnxInterpreter.run_node\n- self: \n- node: fx.Node(p_getattr_l__self___trunk_blocks___10___mlp_fc1_weight)[placeholder]:Tensor(f32[4096, 1024])\n- fx_graph_module: torch.fx.GraphModule(timm_models_vision_transformer_VisionTransformer)\n- onnxfunction_dispatcher: \n- op_level_debug: False\n- onnxscript_graph: \n- onnxscript_tracer: \n- fx_name_to_onnxscript_value: Dict[length=132](\nx: `TorchScriptTensor(f32[4, 3, 512, 512])`,\np_trunk_patch_embed_proj_weight: `TorchScriptTensor(f32[1024, 3, 16, 16])`,\np_trunk_patch_embed_proj_bias: `TorchScriptTensor(f32[1024])`,\np_trunk_pos_embed: `TorchScriptTensor(f32[1, 1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_weight: `TorchScriptTensor(f32[3072, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_bias: `TorchScriptTensor(f32[3072])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_weight: `TorchScriptTensor(f32[1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_bias: `TorchScriptTensor(f32[1024])`,\n...\n)\n## Return values\n", + "text":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___10___mlp_fc1_weight[name=p_getattr_l__self___trunk_blocks___10___mlp_fc1_weight]. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"FxOnnxInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":414 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0008", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___10___mlp_fc1_bias[name=p_getattr_l__self___trunk_blocks___10___mlp_fc1_bias]. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature FxOnnxInterpreter.run_node\n- self: \n- node: fx.Node(p_getattr_l__self___trunk_blocks___10___mlp_fc1_bias)[placeholder]:Tensor(f32[4096])\n- fx_graph_module: torch.fx.GraphModule(timm_models_vision_transformer_VisionTransformer)\n- onnxfunction_dispatcher: \n- op_level_debug: False\n- onnxscript_graph: \n- onnxscript_tracer: \n- fx_name_to_onnxscript_value: Dict[length=133](\nx: `TorchScriptTensor(f32[4, 3, 512, 512])`,\np_trunk_patch_embed_proj_weight: `TorchScriptTensor(f32[1024, 3, 16, 16])`,\np_trunk_patch_embed_proj_bias: `TorchScriptTensor(f32[1024])`,\np_trunk_pos_embed: `TorchScriptTensor(f32[1, 1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_weight: `TorchScriptTensor(f32[3072, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_bias: `TorchScriptTensor(f32[3072])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_weight: `TorchScriptTensor(f32[1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_bias: `TorchScriptTensor(f32[1024])`,\n...\n)\n## Return values\n", + "text":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___10___mlp_fc1_bias[name=p_getattr_l__self___trunk_blocks___10___mlp_fc1_bias]. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"FxOnnxInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":414 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0008", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___10___mlp_fc2_weight[name=p_getattr_l__self___trunk_blocks___10___mlp_fc2_weight]. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature FxOnnxInterpreter.run_node\n- self: \n- node: fx.Node(p_getattr_l__self___trunk_blocks___10___mlp_fc2_weight)[placeholder]:Tensor(f32[1024, 4096])\n- fx_graph_module: torch.fx.GraphModule(timm_models_vision_transformer_VisionTransformer)\n- onnxfunction_dispatcher: \n- op_level_debug: False\n- onnxscript_graph: \n- onnxscript_tracer: \n- fx_name_to_onnxscript_value: Dict[length=134](\nx: `TorchScriptTensor(f32[4, 3, 512, 512])`,\np_trunk_patch_embed_proj_weight: `TorchScriptTensor(f32[1024, 3, 16, 16])`,\np_trunk_patch_embed_proj_bias: `TorchScriptTensor(f32[1024])`,\np_trunk_pos_embed: `TorchScriptTensor(f32[1, 1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_weight: `TorchScriptTensor(f32[3072, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_bias: `TorchScriptTensor(f32[3072])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_weight: `TorchScriptTensor(f32[1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_bias: `TorchScriptTensor(f32[1024])`,\n...\n)\n## Return values\n", + "text":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___10___mlp_fc2_weight[name=p_getattr_l__self___trunk_blocks___10___mlp_fc2_weight]. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"FxOnnxInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":414 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0008", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___10___mlp_fc2_bias[name=p_getattr_l__self___trunk_blocks___10___mlp_fc2_bias]. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature FxOnnxInterpreter.run_node\n- self: \n- node: fx.Node(p_getattr_l__self___trunk_blocks___10___mlp_fc2_bias)[placeholder]:Tensor(f32[1024])\n- fx_graph_module: torch.fx.GraphModule(timm_models_vision_transformer_VisionTransformer)\n- onnxfunction_dispatcher: \n- op_level_debug: False\n- onnxscript_graph: \n- onnxscript_tracer: \n- fx_name_to_onnxscript_value: Dict[length=135](\nx: `TorchScriptTensor(f32[4, 3, 512, 512])`,\np_trunk_patch_embed_proj_weight: `TorchScriptTensor(f32[1024, 3, 16, 16])`,\np_trunk_patch_embed_proj_bias: `TorchScriptTensor(f32[1024])`,\np_trunk_pos_embed: `TorchScriptTensor(f32[1, 1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_weight: `TorchScriptTensor(f32[3072, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_bias: `TorchScriptTensor(f32[3072])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_weight: `TorchScriptTensor(f32[1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_bias: `TorchScriptTensor(f32[1024])`,\n...\n)\n## Return values\n", + "text":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___10___mlp_fc2_bias[name=p_getattr_l__self___trunk_blocks___10___mlp_fc2_bias]. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"FxOnnxInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":414 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0008", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___11___norm1_weight[name=p_getattr_l__self___trunk_blocks___11___norm1_weight]. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature FxOnnxInterpreter.run_node\n- self: \n- node: fx.Node(p_getattr_l__self___trunk_blocks___11___norm1_weight)[placeholder]:Tensor(f32[1024])\n- fx_graph_module: torch.fx.GraphModule(timm_models_vision_transformer_VisionTransformer)\n- onnxfunction_dispatcher: \n- op_level_debug: False\n- onnxscript_graph: \n- onnxscript_tracer: \n- fx_name_to_onnxscript_value: Dict[length=136](\nx: `TorchScriptTensor(f32[4, 3, 512, 512])`,\np_trunk_patch_embed_proj_weight: `TorchScriptTensor(f32[1024, 3, 16, 16])`,\np_trunk_patch_embed_proj_bias: `TorchScriptTensor(f32[1024])`,\np_trunk_pos_embed: `TorchScriptTensor(f32[1, 1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_weight: `TorchScriptTensor(f32[3072, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_bias: `TorchScriptTensor(f32[3072])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_weight: `TorchScriptTensor(f32[1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_bias: `TorchScriptTensor(f32[1024])`,\n...\n)\n## Return values\n", + "text":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___11___norm1_weight[name=p_getattr_l__self___trunk_blocks___11___norm1_weight]. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"FxOnnxInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":414 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0008", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___11___norm1_bias[name=p_getattr_l__self___trunk_blocks___11___norm1_bias]. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature FxOnnxInterpreter.run_node\n- self: \n- node: fx.Node(p_getattr_l__self___trunk_blocks___11___norm1_bias)[placeholder]:Tensor(f32[1024])\n- fx_graph_module: torch.fx.GraphModule(timm_models_vision_transformer_VisionTransformer)\n- onnxfunction_dispatcher: \n- op_level_debug: False\n- onnxscript_graph: \n- onnxscript_tracer: \n- fx_name_to_onnxscript_value: Dict[length=137](\nx: `TorchScriptTensor(f32[4, 3, 512, 512])`,\np_trunk_patch_embed_proj_weight: `TorchScriptTensor(f32[1024, 3, 16, 16])`,\np_trunk_patch_embed_proj_bias: `TorchScriptTensor(f32[1024])`,\np_trunk_pos_embed: `TorchScriptTensor(f32[1, 1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_weight: `TorchScriptTensor(f32[3072, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_bias: `TorchScriptTensor(f32[3072])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_weight: `TorchScriptTensor(f32[1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_bias: `TorchScriptTensor(f32[1024])`,\n...\n)\n## Return values\n", + "text":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___11___norm1_bias[name=p_getattr_l__self___trunk_blocks___11___norm1_bias]. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"FxOnnxInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":414 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0008", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___11___attn_qkv_weight[name=p_getattr_l__self___trunk_blocks___11___attn_qkv_weight]. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature FxOnnxInterpreter.run_node\n- self: \n- node: fx.Node(p_getattr_l__self___trunk_blocks___11___attn_qkv_weight)[placeholder]:Tensor(f32[3072, 1024])\n- fx_graph_module: torch.fx.GraphModule(timm_models_vision_transformer_VisionTransformer)\n- onnxfunction_dispatcher: \n- op_level_debug: False\n- onnxscript_graph: \n- onnxscript_tracer: \n- fx_name_to_onnxscript_value: Dict[length=138](\nx: `TorchScriptTensor(f32[4, 3, 512, 512])`,\np_trunk_patch_embed_proj_weight: `TorchScriptTensor(f32[1024, 3, 16, 16])`,\np_trunk_patch_embed_proj_bias: `TorchScriptTensor(f32[1024])`,\np_trunk_pos_embed: `TorchScriptTensor(f32[1, 1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_weight: `TorchScriptTensor(f32[3072, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_bias: `TorchScriptTensor(f32[3072])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_weight: `TorchScriptTensor(f32[1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_bias: `TorchScriptTensor(f32[1024])`,\n...\n)\n## Return values\n", + "text":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___11___attn_qkv_weight[name=p_getattr_l__self___trunk_blocks___11___attn_qkv_weight]. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"FxOnnxInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":414 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0008", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___11___attn_qkv_bias[name=p_getattr_l__self___trunk_blocks___11___attn_qkv_bias]. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature FxOnnxInterpreter.run_node\n- self: \n- node: fx.Node(p_getattr_l__self___trunk_blocks___11___attn_qkv_bias)[placeholder]:Tensor(f32[3072])\n- fx_graph_module: torch.fx.GraphModule(timm_models_vision_transformer_VisionTransformer)\n- onnxfunction_dispatcher: \n- op_level_debug: False\n- onnxscript_graph: \n- onnxscript_tracer: \n- fx_name_to_onnxscript_value: Dict[length=139](\nx: `TorchScriptTensor(f32[4, 3, 512, 512])`,\np_trunk_patch_embed_proj_weight: `TorchScriptTensor(f32[1024, 3, 16, 16])`,\np_trunk_patch_embed_proj_bias: `TorchScriptTensor(f32[1024])`,\np_trunk_pos_embed: `TorchScriptTensor(f32[1, 1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_weight: `TorchScriptTensor(f32[3072, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_bias: `TorchScriptTensor(f32[3072])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_weight: `TorchScriptTensor(f32[1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_bias: `TorchScriptTensor(f32[1024])`,\n...\n)\n## Return values\n", + "text":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___11___attn_qkv_bias[name=p_getattr_l__self___trunk_blocks___11___attn_qkv_bias]. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"FxOnnxInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":414 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0008", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___11___attn_proj_weight[name=p_getattr_l__self___trunk_blocks___11___attn_proj_weight]. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature FxOnnxInterpreter.run_node\n- self: \n- node: fx.Node(p_getattr_l__self___trunk_blocks___11___attn_proj_weight)[placeholder]:Tensor(f32[1024, 1024])\n- fx_graph_module: torch.fx.GraphModule(timm_models_vision_transformer_VisionTransformer)\n- onnxfunction_dispatcher: \n- op_level_debug: False\n- onnxscript_graph: \n- onnxscript_tracer: \n- fx_name_to_onnxscript_value: Dict[length=140](\nx: `TorchScriptTensor(f32[4, 3, 512, 512])`,\np_trunk_patch_embed_proj_weight: `TorchScriptTensor(f32[1024, 3, 16, 16])`,\np_trunk_patch_embed_proj_bias: `TorchScriptTensor(f32[1024])`,\np_trunk_pos_embed: `TorchScriptTensor(f32[1, 1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_weight: `TorchScriptTensor(f32[3072, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_bias: `TorchScriptTensor(f32[3072])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_weight: `TorchScriptTensor(f32[1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_bias: `TorchScriptTensor(f32[1024])`,\n...\n)\n## Return values\n", + "text":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___11___attn_proj_weight[name=p_getattr_l__self___trunk_blocks___11___attn_proj_weight]. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"FxOnnxInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":414 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0008", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___11___attn_proj_bias[name=p_getattr_l__self___trunk_blocks___11___attn_proj_bias]. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature FxOnnxInterpreter.run_node\n- self: \n- node: fx.Node(p_getattr_l__self___trunk_blocks___11___attn_proj_bias)[placeholder]:Tensor(f32[1024])\n- fx_graph_module: torch.fx.GraphModule(timm_models_vision_transformer_VisionTransformer)\n- onnxfunction_dispatcher: \n- op_level_debug: False\n- onnxscript_graph: \n- onnxscript_tracer: \n- fx_name_to_onnxscript_value: Dict[length=141](\nx: `TorchScriptTensor(f32[4, 3, 512, 512])`,\np_trunk_patch_embed_proj_weight: `TorchScriptTensor(f32[1024, 3, 16, 16])`,\np_trunk_patch_embed_proj_bias: `TorchScriptTensor(f32[1024])`,\np_trunk_pos_embed: `TorchScriptTensor(f32[1, 1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_weight: `TorchScriptTensor(f32[3072, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_bias: `TorchScriptTensor(f32[3072])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_weight: `TorchScriptTensor(f32[1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_bias: `TorchScriptTensor(f32[1024])`,\n...\n)\n## Return values\n", + "text":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___11___attn_proj_bias[name=p_getattr_l__self___trunk_blocks___11___attn_proj_bias]. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"FxOnnxInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":414 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0008", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___11___norm2_weight[name=p_getattr_l__self___trunk_blocks___11___norm2_weight]. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature FxOnnxInterpreter.run_node\n- self: \n- node: fx.Node(p_getattr_l__self___trunk_blocks___11___norm2_weight)[placeholder]:Tensor(f32[1024])\n- fx_graph_module: torch.fx.GraphModule(timm_models_vision_transformer_VisionTransformer)\n- onnxfunction_dispatcher: \n- op_level_debug: False\n- onnxscript_graph: \n- onnxscript_tracer: \n- fx_name_to_onnxscript_value: Dict[length=142](\nx: `TorchScriptTensor(f32[4, 3, 512, 512])`,\np_trunk_patch_embed_proj_weight: `TorchScriptTensor(f32[1024, 3, 16, 16])`,\np_trunk_patch_embed_proj_bias: `TorchScriptTensor(f32[1024])`,\np_trunk_pos_embed: `TorchScriptTensor(f32[1, 1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_weight: `TorchScriptTensor(f32[3072, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_bias: `TorchScriptTensor(f32[3072])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_weight: `TorchScriptTensor(f32[1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_bias: `TorchScriptTensor(f32[1024])`,\n...\n)\n## Return values\n", + "text":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___11___norm2_weight[name=p_getattr_l__self___trunk_blocks___11___norm2_weight]. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"FxOnnxInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":414 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0008", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___11___norm2_bias[name=p_getattr_l__self___trunk_blocks___11___norm2_bias]. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature FxOnnxInterpreter.run_node\n- self: \n- node: fx.Node(p_getattr_l__self___trunk_blocks___11___norm2_bias)[placeholder]:Tensor(f32[1024])\n- fx_graph_module: torch.fx.GraphModule(timm_models_vision_transformer_VisionTransformer)\n- onnxfunction_dispatcher: \n- op_level_debug: False\n- onnxscript_graph: \n- onnxscript_tracer: \n- fx_name_to_onnxscript_value: Dict[length=143](\nx: `TorchScriptTensor(f32[4, 3, 512, 512])`,\np_trunk_patch_embed_proj_weight: `TorchScriptTensor(f32[1024, 3, 16, 16])`,\np_trunk_patch_embed_proj_bias: `TorchScriptTensor(f32[1024])`,\np_trunk_pos_embed: `TorchScriptTensor(f32[1, 1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_weight: `TorchScriptTensor(f32[3072, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_bias: `TorchScriptTensor(f32[3072])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_weight: `TorchScriptTensor(f32[1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_bias: `TorchScriptTensor(f32[1024])`,\n...\n)\n## Return values\n", + "text":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___11___norm2_bias[name=p_getattr_l__self___trunk_blocks___11___norm2_bias]. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"FxOnnxInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":414 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0008", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___11___mlp_fc1_weight[name=p_getattr_l__self___trunk_blocks___11___mlp_fc1_weight]. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature FxOnnxInterpreter.run_node\n- self: \n- node: fx.Node(p_getattr_l__self___trunk_blocks___11___mlp_fc1_weight)[placeholder]:Tensor(f32[4096, 1024])\n- fx_graph_module: torch.fx.GraphModule(timm_models_vision_transformer_VisionTransformer)\n- onnxfunction_dispatcher: \n- op_level_debug: False\n- onnxscript_graph: \n- onnxscript_tracer: \n- fx_name_to_onnxscript_value: Dict[length=144](\nx: `TorchScriptTensor(f32[4, 3, 512, 512])`,\np_trunk_patch_embed_proj_weight: `TorchScriptTensor(f32[1024, 3, 16, 16])`,\np_trunk_patch_embed_proj_bias: `TorchScriptTensor(f32[1024])`,\np_trunk_pos_embed: `TorchScriptTensor(f32[1, 1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_weight: `TorchScriptTensor(f32[3072, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_bias: `TorchScriptTensor(f32[3072])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_weight: `TorchScriptTensor(f32[1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_bias: `TorchScriptTensor(f32[1024])`,\n...\n)\n## Return values\n", + "text":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___11___mlp_fc1_weight[name=p_getattr_l__self___trunk_blocks___11___mlp_fc1_weight]. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"FxOnnxInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":414 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0008", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___11___mlp_fc1_bias[name=p_getattr_l__self___trunk_blocks___11___mlp_fc1_bias]. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature FxOnnxInterpreter.run_node\n- self: \n- node: fx.Node(p_getattr_l__self___trunk_blocks___11___mlp_fc1_bias)[placeholder]:Tensor(f32[4096])\n- fx_graph_module: torch.fx.GraphModule(timm_models_vision_transformer_VisionTransformer)\n- onnxfunction_dispatcher: \n- op_level_debug: False\n- onnxscript_graph: \n- onnxscript_tracer: \n- fx_name_to_onnxscript_value: Dict[length=145](\nx: `TorchScriptTensor(f32[4, 3, 512, 512])`,\np_trunk_patch_embed_proj_weight: `TorchScriptTensor(f32[1024, 3, 16, 16])`,\np_trunk_patch_embed_proj_bias: `TorchScriptTensor(f32[1024])`,\np_trunk_pos_embed: `TorchScriptTensor(f32[1, 1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_weight: `TorchScriptTensor(f32[3072, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_bias: `TorchScriptTensor(f32[3072])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_weight: `TorchScriptTensor(f32[1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_bias: `TorchScriptTensor(f32[1024])`,\n...\n)\n## Return values\n", + "text":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___11___mlp_fc1_bias[name=p_getattr_l__self___trunk_blocks___11___mlp_fc1_bias]. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"FxOnnxInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":414 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0008", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___11___mlp_fc2_weight[name=p_getattr_l__self___trunk_blocks___11___mlp_fc2_weight]. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature FxOnnxInterpreter.run_node\n- self: \n- node: fx.Node(p_getattr_l__self___trunk_blocks___11___mlp_fc2_weight)[placeholder]:Tensor(f32[1024, 4096])\n- fx_graph_module: torch.fx.GraphModule(timm_models_vision_transformer_VisionTransformer)\n- onnxfunction_dispatcher: \n- op_level_debug: False\n- onnxscript_graph: \n- onnxscript_tracer: \n- fx_name_to_onnxscript_value: Dict[length=146](\nx: `TorchScriptTensor(f32[4, 3, 512, 512])`,\np_trunk_patch_embed_proj_weight: `TorchScriptTensor(f32[1024, 3, 16, 16])`,\np_trunk_patch_embed_proj_bias: `TorchScriptTensor(f32[1024])`,\np_trunk_pos_embed: `TorchScriptTensor(f32[1, 1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_weight: `TorchScriptTensor(f32[3072, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_bias: `TorchScriptTensor(f32[3072])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_weight: `TorchScriptTensor(f32[1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_bias: `TorchScriptTensor(f32[1024])`,\n...\n)\n## Return values\n", + "text":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___11___mlp_fc2_weight[name=p_getattr_l__self___trunk_blocks___11___mlp_fc2_weight]. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"FxOnnxInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":414 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0008", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___11___mlp_fc2_bias[name=p_getattr_l__self___trunk_blocks___11___mlp_fc2_bias]. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature FxOnnxInterpreter.run_node\n- self: \n- node: fx.Node(p_getattr_l__self___trunk_blocks___11___mlp_fc2_bias)[placeholder]:Tensor(f32[1024])\n- fx_graph_module: torch.fx.GraphModule(timm_models_vision_transformer_VisionTransformer)\n- onnxfunction_dispatcher: \n- op_level_debug: False\n- onnxscript_graph: \n- onnxscript_tracer: \n- fx_name_to_onnxscript_value: Dict[length=147](\nx: `TorchScriptTensor(f32[4, 3, 512, 512])`,\np_trunk_patch_embed_proj_weight: `TorchScriptTensor(f32[1024, 3, 16, 16])`,\np_trunk_patch_embed_proj_bias: `TorchScriptTensor(f32[1024])`,\np_trunk_pos_embed: `TorchScriptTensor(f32[1, 1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_weight: `TorchScriptTensor(f32[3072, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_bias: `TorchScriptTensor(f32[3072])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_weight: `TorchScriptTensor(f32[1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_bias: `TorchScriptTensor(f32[1024])`,\n...\n)\n## Return values\n", + "text":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___11___mlp_fc2_bias[name=p_getattr_l__self___trunk_blocks___11___mlp_fc2_bias]. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"FxOnnxInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":414 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0008", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___12___norm1_weight[name=p_getattr_l__self___trunk_blocks___12___norm1_weight]. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature FxOnnxInterpreter.run_node\n- self: \n- node: fx.Node(p_getattr_l__self___trunk_blocks___12___norm1_weight)[placeholder]:Tensor(f32[1024])\n- fx_graph_module: torch.fx.GraphModule(timm_models_vision_transformer_VisionTransformer)\n- onnxfunction_dispatcher: \n- op_level_debug: False\n- onnxscript_graph: \n- onnxscript_tracer: \n- fx_name_to_onnxscript_value: Dict[length=148](\nx: `TorchScriptTensor(f32[4, 3, 512, 512])`,\np_trunk_patch_embed_proj_weight: `TorchScriptTensor(f32[1024, 3, 16, 16])`,\np_trunk_patch_embed_proj_bias: `TorchScriptTensor(f32[1024])`,\np_trunk_pos_embed: `TorchScriptTensor(f32[1, 1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_weight: `TorchScriptTensor(f32[3072, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_bias: `TorchScriptTensor(f32[3072])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_weight: `TorchScriptTensor(f32[1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_bias: `TorchScriptTensor(f32[1024])`,\n...\n)\n## Return values\n", + "text":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___12___norm1_weight[name=p_getattr_l__self___trunk_blocks___12___norm1_weight]. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"FxOnnxInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":414 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0008", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___12___norm1_bias[name=p_getattr_l__self___trunk_blocks___12___norm1_bias]. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature FxOnnxInterpreter.run_node\n- self: \n- node: fx.Node(p_getattr_l__self___trunk_blocks___12___norm1_bias)[placeholder]:Tensor(f32[1024])\n- fx_graph_module: torch.fx.GraphModule(timm_models_vision_transformer_VisionTransformer)\n- onnxfunction_dispatcher: \n- op_level_debug: False\n- onnxscript_graph: \n- onnxscript_tracer: \n- fx_name_to_onnxscript_value: Dict[length=149](\nx: `TorchScriptTensor(f32[4, 3, 512, 512])`,\np_trunk_patch_embed_proj_weight: `TorchScriptTensor(f32[1024, 3, 16, 16])`,\np_trunk_patch_embed_proj_bias: `TorchScriptTensor(f32[1024])`,\np_trunk_pos_embed: `TorchScriptTensor(f32[1, 1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_weight: `TorchScriptTensor(f32[3072, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_bias: `TorchScriptTensor(f32[3072])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_weight: `TorchScriptTensor(f32[1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_bias: `TorchScriptTensor(f32[1024])`,\n...\n)\n## Return values\n", + "text":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___12___norm1_bias[name=p_getattr_l__self___trunk_blocks___12___norm1_bias]. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"FxOnnxInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":414 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0008", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___12___attn_qkv_weight[name=p_getattr_l__self___trunk_blocks___12___attn_qkv_weight]. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature FxOnnxInterpreter.run_node\n- self: \n- node: fx.Node(p_getattr_l__self___trunk_blocks___12___attn_qkv_weight)[placeholder]:Tensor(f32[3072, 1024])\n- fx_graph_module: torch.fx.GraphModule(timm_models_vision_transformer_VisionTransformer)\n- onnxfunction_dispatcher: \n- op_level_debug: False\n- onnxscript_graph: \n- onnxscript_tracer: \n- fx_name_to_onnxscript_value: Dict[length=150](\nx: `TorchScriptTensor(f32[4, 3, 512, 512])`,\np_trunk_patch_embed_proj_weight: `TorchScriptTensor(f32[1024, 3, 16, 16])`,\np_trunk_patch_embed_proj_bias: `TorchScriptTensor(f32[1024])`,\np_trunk_pos_embed: `TorchScriptTensor(f32[1, 1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_weight: `TorchScriptTensor(f32[3072, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_bias: `TorchScriptTensor(f32[3072])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_weight: `TorchScriptTensor(f32[1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_bias: `TorchScriptTensor(f32[1024])`,\n...\n)\n## Return values\n", + "text":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___12___attn_qkv_weight[name=p_getattr_l__self___trunk_blocks___12___attn_qkv_weight]. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"FxOnnxInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":414 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0008", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___12___attn_qkv_bias[name=p_getattr_l__self___trunk_blocks___12___attn_qkv_bias]. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature FxOnnxInterpreter.run_node\n- self: \n- node: fx.Node(p_getattr_l__self___trunk_blocks___12___attn_qkv_bias)[placeholder]:Tensor(f32[3072])\n- fx_graph_module: torch.fx.GraphModule(timm_models_vision_transformer_VisionTransformer)\n- onnxfunction_dispatcher: \n- op_level_debug: False\n- onnxscript_graph: \n- onnxscript_tracer: \n- fx_name_to_onnxscript_value: Dict[length=151](\nx: `TorchScriptTensor(f32[4, 3, 512, 512])`,\np_trunk_patch_embed_proj_weight: `TorchScriptTensor(f32[1024, 3, 16, 16])`,\np_trunk_patch_embed_proj_bias: `TorchScriptTensor(f32[1024])`,\np_trunk_pos_embed: `TorchScriptTensor(f32[1, 1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_weight: `TorchScriptTensor(f32[3072, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_bias: `TorchScriptTensor(f32[3072])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_weight: `TorchScriptTensor(f32[1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_bias: `TorchScriptTensor(f32[1024])`,\n...\n)\n## Return values\n", + "text":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___12___attn_qkv_bias[name=p_getattr_l__self___trunk_blocks___12___attn_qkv_bias]. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"FxOnnxInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":414 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0008", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___12___attn_proj_weight[name=p_getattr_l__self___trunk_blocks___12___attn_proj_weight]. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature FxOnnxInterpreter.run_node\n- self: \n- node: fx.Node(p_getattr_l__self___trunk_blocks___12___attn_proj_weight)[placeholder]:Tensor(f32[1024, 1024])\n- fx_graph_module: torch.fx.GraphModule(timm_models_vision_transformer_VisionTransformer)\n- onnxfunction_dispatcher: \n- op_level_debug: False\n- onnxscript_graph: \n- onnxscript_tracer: \n- fx_name_to_onnxscript_value: Dict[length=152](\nx: `TorchScriptTensor(f32[4, 3, 512, 512])`,\np_trunk_patch_embed_proj_weight: `TorchScriptTensor(f32[1024, 3, 16, 16])`,\np_trunk_patch_embed_proj_bias: `TorchScriptTensor(f32[1024])`,\np_trunk_pos_embed: `TorchScriptTensor(f32[1, 1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_weight: `TorchScriptTensor(f32[3072, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_bias: `TorchScriptTensor(f32[3072])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_weight: `TorchScriptTensor(f32[1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_bias: `TorchScriptTensor(f32[1024])`,\n...\n)\n## Return values\n", + "text":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___12___attn_proj_weight[name=p_getattr_l__self___trunk_blocks___12___attn_proj_weight]. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"FxOnnxInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":414 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0008", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___12___attn_proj_bias[name=p_getattr_l__self___trunk_blocks___12___attn_proj_bias]. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature FxOnnxInterpreter.run_node\n- self: \n- node: fx.Node(p_getattr_l__self___trunk_blocks___12___attn_proj_bias)[placeholder]:Tensor(f32[1024])\n- fx_graph_module: torch.fx.GraphModule(timm_models_vision_transformer_VisionTransformer)\n- onnxfunction_dispatcher: \n- op_level_debug: False\n- onnxscript_graph: \n- onnxscript_tracer: \n- fx_name_to_onnxscript_value: Dict[length=153](\nx: `TorchScriptTensor(f32[4, 3, 512, 512])`,\np_trunk_patch_embed_proj_weight: `TorchScriptTensor(f32[1024, 3, 16, 16])`,\np_trunk_patch_embed_proj_bias: `TorchScriptTensor(f32[1024])`,\np_trunk_pos_embed: `TorchScriptTensor(f32[1, 1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_weight: `TorchScriptTensor(f32[3072, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_bias: `TorchScriptTensor(f32[3072])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_weight: `TorchScriptTensor(f32[1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_bias: `TorchScriptTensor(f32[1024])`,\n...\n)\n## Return values\n", + "text":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___12___attn_proj_bias[name=p_getattr_l__self___trunk_blocks___12___attn_proj_bias]. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"FxOnnxInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":414 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0008", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___12___norm2_weight[name=p_getattr_l__self___trunk_blocks___12___norm2_weight]. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature FxOnnxInterpreter.run_node\n- self: \n- node: fx.Node(p_getattr_l__self___trunk_blocks___12___norm2_weight)[placeholder]:Tensor(f32[1024])\n- fx_graph_module: torch.fx.GraphModule(timm_models_vision_transformer_VisionTransformer)\n- onnxfunction_dispatcher: \n- op_level_debug: False\n- onnxscript_graph: \n- onnxscript_tracer: \n- fx_name_to_onnxscript_value: Dict[length=154](\nx: `TorchScriptTensor(f32[4, 3, 512, 512])`,\np_trunk_patch_embed_proj_weight: `TorchScriptTensor(f32[1024, 3, 16, 16])`,\np_trunk_patch_embed_proj_bias: `TorchScriptTensor(f32[1024])`,\np_trunk_pos_embed: `TorchScriptTensor(f32[1, 1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_weight: `TorchScriptTensor(f32[3072, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_bias: `TorchScriptTensor(f32[3072])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_weight: `TorchScriptTensor(f32[1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_bias: `TorchScriptTensor(f32[1024])`,\n...\n)\n## Return values\n", + "text":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___12___norm2_weight[name=p_getattr_l__self___trunk_blocks___12___norm2_weight]. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"FxOnnxInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":414 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0008", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___12___norm2_bias[name=p_getattr_l__self___trunk_blocks___12___norm2_bias]. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature FxOnnxInterpreter.run_node\n- self: \n- node: fx.Node(p_getattr_l__self___trunk_blocks___12___norm2_bias)[placeholder]:Tensor(f32[1024])\n- fx_graph_module: torch.fx.GraphModule(timm_models_vision_transformer_VisionTransformer)\n- onnxfunction_dispatcher: \n- op_level_debug: False\n- onnxscript_graph: \n- onnxscript_tracer: \n- fx_name_to_onnxscript_value: Dict[length=155](\nx: `TorchScriptTensor(f32[4, 3, 512, 512])`,\np_trunk_patch_embed_proj_weight: `TorchScriptTensor(f32[1024, 3, 16, 16])`,\np_trunk_patch_embed_proj_bias: `TorchScriptTensor(f32[1024])`,\np_trunk_pos_embed: `TorchScriptTensor(f32[1, 1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_weight: `TorchScriptTensor(f32[3072, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_bias: `TorchScriptTensor(f32[3072])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_weight: `TorchScriptTensor(f32[1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_bias: `TorchScriptTensor(f32[1024])`,\n...\n)\n## Return values\n", + "text":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___12___norm2_bias[name=p_getattr_l__self___trunk_blocks___12___norm2_bias]. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"FxOnnxInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":414 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0008", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___12___mlp_fc1_weight[name=p_getattr_l__self___trunk_blocks___12___mlp_fc1_weight]. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature FxOnnxInterpreter.run_node\n- self: \n- node: fx.Node(p_getattr_l__self___trunk_blocks___12___mlp_fc1_weight)[placeholder]:Tensor(f32[4096, 1024])\n- fx_graph_module: torch.fx.GraphModule(timm_models_vision_transformer_VisionTransformer)\n- onnxfunction_dispatcher: \n- op_level_debug: False\n- onnxscript_graph: \n- onnxscript_tracer: \n- fx_name_to_onnxscript_value: Dict[length=156](\nx: `TorchScriptTensor(f32[4, 3, 512, 512])`,\np_trunk_patch_embed_proj_weight: `TorchScriptTensor(f32[1024, 3, 16, 16])`,\np_trunk_patch_embed_proj_bias: `TorchScriptTensor(f32[1024])`,\np_trunk_pos_embed: `TorchScriptTensor(f32[1, 1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_weight: `TorchScriptTensor(f32[3072, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_bias: `TorchScriptTensor(f32[3072])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_weight: `TorchScriptTensor(f32[1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_bias: `TorchScriptTensor(f32[1024])`,\n...\n)\n## Return values\n", + "text":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___12___mlp_fc1_weight[name=p_getattr_l__self___trunk_blocks___12___mlp_fc1_weight]. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"FxOnnxInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":414 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0008", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___12___mlp_fc1_bias[name=p_getattr_l__self___trunk_blocks___12___mlp_fc1_bias]. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature FxOnnxInterpreter.run_node\n- self: \n- node: fx.Node(p_getattr_l__self___trunk_blocks___12___mlp_fc1_bias)[placeholder]:Tensor(f32[4096])\n- fx_graph_module: torch.fx.GraphModule(timm_models_vision_transformer_VisionTransformer)\n- onnxfunction_dispatcher: \n- op_level_debug: False\n- onnxscript_graph: \n- onnxscript_tracer: \n- fx_name_to_onnxscript_value: Dict[length=157](\nx: `TorchScriptTensor(f32[4, 3, 512, 512])`,\np_trunk_patch_embed_proj_weight: `TorchScriptTensor(f32[1024, 3, 16, 16])`,\np_trunk_patch_embed_proj_bias: `TorchScriptTensor(f32[1024])`,\np_trunk_pos_embed: `TorchScriptTensor(f32[1, 1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_weight: `TorchScriptTensor(f32[3072, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_bias: `TorchScriptTensor(f32[3072])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_weight: `TorchScriptTensor(f32[1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_bias: `TorchScriptTensor(f32[1024])`,\n...\n)\n## Return values\n", + "text":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___12___mlp_fc1_bias[name=p_getattr_l__self___trunk_blocks___12___mlp_fc1_bias]. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"FxOnnxInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":414 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0008", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___12___mlp_fc2_weight[name=p_getattr_l__self___trunk_blocks___12___mlp_fc2_weight]. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature FxOnnxInterpreter.run_node\n- self: \n- node: fx.Node(p_getattr_l__self___trunk_blocks___12___mlp_fc2_weight)[placeholder]:Tensor(f32[1024, 4096])\n- fx_graph_module: torch.fx.GraphModule(timm_models_vision_transformer_VisionTransformer)\n- onnxfunction_dispatcher: \n- op_level_debug: False\n- onnxscript_graph: \n- onnxscript_tracer: \n- fx_name_to_onnxscript_value: Dict[length=158](\nx: `TorchScriptTensor(f32[4, 3, 512, 512])`,\np_trunk_patch_embed_proj_weight: `TorchScriptTensor(f32[1024, 3, 16, 16])`,\np_trunk_patch_embed_proj_bias: `TorchScriptTensor(f32[1024])`,\np_trunk_pos_embed: `TorchScriptTensor(f32[1, 1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_weight: `TorchScriptTensor(f32[3072, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_bias: `TorchScriptTensor(f32[3072])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_weight: `TorchScriptTensor(f32[1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_bias: `TorchScriptTensor(f32[1024])`,\n...\n)\n## Return values\n", + "text":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___12___mlp_fc2_weight[name=p_getattr_l__self___trunk_blocks___12___mlp_fc2_weight]. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"FxOnnxInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":414 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0008", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___12___mlp_fc2_bias[name=p_getattr_l__self___trunk_blocks___12___mlp_fc2_bias]. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature FxOnnxInterpreter.run_node\n- self: \n- node: fx.Node(p_getattr_l__self___trunk_blocks___12___mlp_fc2_bias)[placeholder]:Tensor(f32[1024])\n- fx_graph_module: torch.fx.GraphModule(timm_models_vision_transformer_VisionTransformer)\n- onnxfunction_dispatcher: \n- op_level_debug: False\n- onnxscript_graph: \n- onnxscript_tracer: \n- fx_name_to_onnxscript_value: Dict[length=159](\nx: `TorchScriptTensor(f32[4, 3, 512, 512])`,\np_trunk_patch_embed_proj_weight: `TorchScriptTensor(f32[1024, 3, 16, 16])`,\np_trunk_patch_embed_proj_bias: `TorchScriptTensor(f32[1024])`,\np_trunk_pos_embed: `TorchScriptTensor(f32[1, 1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_weight: `TorchScriptTensor(f32[3072, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_bias: `TorchScriptTensor(f32[3072])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_weight: `TorchScriptTensor(f32[1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_bias: `TorchScriptTensor(f32[1024])`,\n...\n)\n## Return values\n", + "text":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___12___mlp_fc2_bias[name=p_getattr_l__self___trunk_blocks___12___mlp_fc2_bias]. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"FxOnnxInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":414 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0008", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___13___norm1_weight[name=p_getattr_l__self___trunk_blocks___13___norm1_weight]. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature FxOnnxInterpreter.run_node\n- self: \n- node: fx.Node(p_getattr_l__self___trunk_blocks___13___norm1_weight)[placeholder]:Tensor(f32[1024])\n- fx_graph_module: torch.fx.GraphModule(timm_models_vision_transformer_VisionTransformer)\n- onnxfunction_dispatcher: \n- op_level_debug: False\n- onnxscript_graph: \n- onnxscript_tracer: \n- fx_name_to_onnxscript_value: Dict[length=160](\nx: `TorchScriptTensor(f32[4, 3, 512, 512])`,\np_trunk_patch_embed_proj_weight: `TorchScriptTensor(f32[1024, 3, 16, 16])`,\np_trunk_patch_embed_proj_bias: `TorchScriptTensor(f32[1024])`,\np_trunk_pos_embed: `TorchScriptTensor(f32[1, 1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_weight: `TorchScriptTensor(f32[3072, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_bias: `TorchScriptTensor(f32[3072])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_weight: `TorchScriptTensor(f32[1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_bias: `TorchScriptTensor(f32[1024])`,\n...\n)\n## Return values\n", + "text":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___13___norm1_weight[name=p_getattr_l__self___trunk_blocks___13___norm1_weight]. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"FxOnnxInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":414 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0008", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___13___norm1_bias[name=p_getattr_l__self___trunk_blocks___13___norm1_bias]. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature FxOnnxInterpreter.run_node\n- self: \n- node: fx.Node(p_getattr_l__self___trunk_blocks___13___norm1_bias)[placeholder]:Tensor(f32[1024])\n- fx_graph_module: torch.fx.GraphModule(timm_models_vision_transformer_VisionTransformer)\n- onnxfunction_dispatcher: \n- op_level_debug: False\n- onnxscript_graph: \n- onnxscript_tracer: \n- fx_name_to_onnxscript_value: Dict[length=161](\nx: `TorchScriptTensor(f32[4, 3, 512, 512])`,\np_trunk_patch_embed_proj_weight: `TorchScriptTensor(f32[1024, 3, 16, 16])`,\np_trunk_patch_embed_proj_bias: `TorchScriptTensor(f32[1024])`,\np_trunk_pos_embed: `TorchScriptTensor(f32[1, 1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_weight: `TorchScriptTensor(f32[3072, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_bias: `TorchScriptTensor(f32[3072])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_weight: `TorchScriptTensor(f32[1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_bias: `TorchScriptTensor(f32[1024])`,\n...\n)\n## Return values\n", + "text":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___13___norm1_bias[name=p_getattr_l__self___trunk_blocks___13___norm1_bias]. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"FxOnnxInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":414 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0008", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___13___attn_qkv_weight[name=p_getattr_l__self___trunk_blocks___13___attn_qkv_weight]. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature FxOnnxInterpreter.run_node\n- self: \n- node: fx.Node(p_getattr_l__self___trunk_blocks___13___attn_qkv_weight)[placeholder]:Tensor(f32[3072, 1024])\n- fx_graph_module: torch.fx.GraphModule(timm_models_vision_transformer_VisionTransformer)\n- onnxfunction_dispatcher: \n- op_level_debug: False\n- onnxscript_graph: \n- onnxscript_tracer: \n- fx_name_to_onnxscript_value: Dict[length=162](\nx: `TorchScriptTensor(f32[4, 3, 512, 512])`,\np_trunk_patch_embed_proj_weight: `TorchScriptTensor(f32[1024, 3, 16, 16])`,\np_trunk_patch_embed_proj_bias: `TorchScriptTensor(f32[1024])`,\np_trunk_pos_embed: `TorchScriptTensor(f32[1, 1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_weight: `TorchScriptTensor(f32[3072, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_bias: `TorchScriptTensor(f32[3072])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_weight: `TorchScriptTensor(f32[1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_bias: `TorchScriptTensor(f32[1024])`,\n...\n)\n## Return values\n", + "text":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___13___attn_qkv_weight[name=p_getattr_l__self___trunk_blocks___13___attn_qkv_weight]. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"FxOnnxInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":414 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0008", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___13___attn_qkv_bias[name=p_getattr_l__self___trunk_blocks___13___attn_qkv_bias]. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature FxOnnxInterpreter.run_node\n- self: \n- node: fx.Node(p_getattr_l__self___trunk_blocks___13___attn_qkv_bias)[placeholder]:Tensor(f32[3072])\n- fx_graph_module: torch.fx.GraphModule(timm_models_vision_transformer_VisionTransformer)\n- onnxfunction_dispatcher: \n- op_level_debug: False\n- onnxscript_graph: \n- onnxscript_tracer: \n- fx_name_to_onnxscript_value: Dict[length=163](\nx: `TorchScriptTensor(f32[4, 3, 512, 512])`,\np_trunk_patch_embed_proj_weight: `TorchScriptTensor(f32[1024, 3, 16, 16])`,\np_trunk_patch_embed_proj_bias: `TorchScriptTensor(f32[1024])`,\np_trunk_pos_embed: `TorchScriptTensor(f32[1, 1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_weight: `TorchScriptTensor(f32[3072, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_bias: `TorchScriptTensor(f32[3072])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_weight: `TorchScriptTensor(f32[1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_bias: `TorchScriptTensor(f32[1024])`,\n...\n)\n## Return values\n", + "text":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___13___attn_qkv_bias[name=p_getattr_l__self___trunk_blocks___13___attn_qkv_bias]. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"FxOnnxInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":414 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0008", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___13___attn_proj_weight[name=p_getattr_l__self___trunk_blocks___13___attn_proj_weight]. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature FxOnnxInterpreter.run_node\n- self: \n- node: fx.Node(p_getattr_l__self___trunk_blocks___13___attn_proj_weight)[placeholder]:Tensor(f32[1024, 1024])\n- fx_graph_module: torch.fx.GraphModule(timm_models_vision_transformer_VisionTransformer)\n- onnxfunction_dispatcher: \n- op_level_debug: False\n- onnxscript_graph: \n- onnxscript_tracer: \n- fx_name_to_onnxscript_value: Dict[length=164](\nx: `TorchScriptTensor(f32[4, 3, 512, 512])`,\np_trunk_patch_embed_proj_weight: `TorchScriptTensor(f32[1024, 3, 16, 16])`,\np_trunk_patch_embed_proj_bias: `TorchScriptTensor(f32[1024])`,\np_trunk_pos_embed: `TorchScriptTensor(f32[1, 1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_weight: `TorchScriptTensor(f32[3072, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_bias: `TorchScriptTensor(f32[3072])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_weight: `TorchScriptTensor(f32[1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_bias: `TorchScriptTensor(f32[1024])`,\n...\n)\n## Return values\n", + "text":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___13___attn_proj_weight[name=p_getattr_l__self___trunk_blocks___13___attn_proj_weight]. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"FxOnnxInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":414 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0008", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___13___attn_proj_bias[name=p_getattr_l__self___trunk_blocks___13___attn_proj_bias]. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature FxOnnxInterpreter.run_node\n- self: \n- node: fx.Node(p_getattr_l__self___trunk_blocks___13___attn_proj_bias)[placeholder]:Tensor(f32[1024])\n- fx_graph_module: torch.fx.GraphModule(timm_models_vision_transformer_VisionTransformer)\n- onnxfunction_dispatcher: \n- op_level_debug: False\n- onnxscript_graph: \n- onnxscript_tracer: \n- fx_name_to_onnxscript_value: Dict[length=165](\nx: `TorchScriptTensor(f32[4, 3, 512, 512])`,\np_trunk_patch_embed_proj_weight: `TorchScriptTensor(f32[1024, 3, 16, 16])`,\np_trunk_patch_embed_proj_bias: `TorchScriptTensor(f32[1024])`,\np_trunk_pos_embed: `TorchScriptTensor(f32[1, 1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_weight: `TorchScriptTensor(f32[3072, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_bias: `TorchScriptTensor(f32[3072])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_weight: `TorchScriptTensor(f32[1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_bias: `TorchScriptTensor(f32[1024])`,\n...\n)\n## Return values\n", + "text":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___13___attn_proj_bias[name=p_getattr_l__self___trunk_blocks___13___attn_proj_bias]. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"FxOnnxInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":414 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0008", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___13___norm2_weight[name=p_getattr_l__self___trunk_blocks___13___norm2_weight]. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature FxOnnxInterpreter.run_node\n- self: \n- node: fx.Node(p_getattr_l__self___trunk_blocks___13___norm2_weight)[placeholder]:Tensor(f32[1024])\n- fx_graph_module: torch.fx.GraphModule(timm_models_vision_transformer_VisionTransformer)\n- onnxfunction_dispatcher: \n- op_level_debug: False\n- onnxscript_graph: \n- onnxscript_tracer: \n- fx_name_to_onnxscript_value: Dict[length=166](\nx: `TorchScriptTensor(f32[4, 3, 512, 512])`,\np_trunk_patch_embed_proj_weight: `TorchScriptTensor(f32[1024, 3, 16, 16])`,\np_trunk_patch_embed_proj_bias: `TorchScriptTensor(f32[1024])`,\np_trunk_pos_embed: `TorchScriptTensor(f32[1, 1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_weight: `TorchScriptTensor(f32[3072, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_bias: `TorchScriptTensor(f32[3072])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_weight: `TorchScriptTensor(f32[1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_bias: `TorchScriptTensor(f32[1024])`,\n...\n)\n## Return values\n", + "text":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___13___norm2_weight[name=p_getattr_l__self___trunk_blocks___13___norm2_weight]. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"FxOnnxInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":414 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0008", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___13___norm2_bias[name=p_getattr_l__self___trunk_blocks___13___norm2_bias]. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature FxOnnxInterpreter.run_node\n- self: \n- node: fx.Node(p_getattr_l__self___trunk_blocks___13___norm2_bias)[placeholder]:Tensor(f32[1024])\n- fx_graph_module: torch.fx.GraphModule(timm_models_vision_transformer_VisionTransformer)\n- onnxfunction_dispatcher: \n- op_level_debug: False\n- onnxscript_graph: \n- onnxscript_tracer: \n- fx_name_to_onnxscript_value: Dict[length=167](\nx: `TorchScriptTensor(f32[4, 3, 512, 512])`,\np_trunk_patch_embed_proj_weight: `TorchScriptTensor(f32[1024, 3, 16, 16])`,\np_trunk_patch_embed_proj_bias: `TorchScriptTensor(f32[1024])`,\np_trunk_pos_embed: `TorchScriptTensor(f32[1, 1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_weight: `TorchScriptTensor(f32[3072, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_bias: `TorchScriptTensor(f32[3072])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_weight: `TorchScriptTensor(f32[1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_bias: `TorchScriptTensor(f32[1024])`,\n...\n)\n## Return values\n", + "text":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___13___norm2_bias[name=p_getattr_l__self___trunk_blocks___13___norm2_bias]. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"FxOnnxInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":414 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0008", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___13___mlp_fc1_weight[name=p_getattr_l__self___trunk_blocks___13___mlp_fc1_weight]. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature FxOnnxInterpreter.run_node\n- self: \n- node: fx.Node(p_getattr_l__self___trunk_blocks___13___mlp_fc1_weight)[placeholder]:Tensor(f32[4096, 1024])\n- fx_graph_module: torch.fx.GraphModule(timm_models_vision_transformer_VisionTransformer)\n- onnxfunction_dispatcher: \n- op_level_debug: False\n- onnxscript_graph: \n- onnxscript_tracer: \n- fx_name_to_onnxscript_value: Dict[length=168](\nx: `TorchScriptTensor(f32[4, 3, 512, 512])`,\np_trunk_patch_embed_proj_weight: `TorchScriptTensor(f32[1024, 3, 16, 16])`,\np_trunk_patch_embed_proj_bias: `TorchScriptTensor(f32[1024])`,\np_trunk_pos_embed: `TorchScriptTensor(f32[1, 1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_weight: `TorchScriptTensor(f32[3072, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_bias: `TorchScriptTensor(f32[3072])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_weight: `TorchScriptTensor(f32[1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_bias: `TorchScriptTensor(f32[1024])`,\n...\n)\n## Return values\n", + "text":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___13___mlp_fc1_weight[name=p_getattr_l__self___trunk_blocks___13___mlp_fc1_weight]. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"FxOnnxInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":414 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0008", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___13___mlp_fc1_bias[name=p_getattr_l__self___trunk_blocks___13___mlp_fc1_bias]. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature FxOnnxInterpreter.run_node\n- self: \n- node: fx.Node(p_getattr_l__self___trunk_blocks___13___mlp_fc1_bias)[placeholder]:Tensor(f32[4096])\n- fx_graph_module: torch.fx.GraphModule(timm_models_vision_transformer_VisionTransformer)\n- onnxfunction_dispatcher: \n- op_level_debug: False\n- onnxscript_graph: \n- onnxscript_tracer: \n- fx_name_to_onnxscript_value: Dict[length=169](\nx: `TorchScriptTensor(f32[4, 3, 512, 512])`,\np_trunk_patch_embed_proj_weight: `TorchScriptTensor(f32[1024, 3, 16, 16])`,\np_trunk_patch_embed_proj_bias: `TorchScriptTensor(f32[1024])`,\np_trunk_pos_embed: `TorchScriptTensor(f32[1, 1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_weight: `TorchScriptTensor(f32[3072, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_bias: `TorchScriptTensor(f32[3072])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_weight: `TorchScriptTensor(f32[1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_bias: `TorchScriptTensor(f32[1024])`,\n...\n)\n## Return values\n", + "text":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___13___mlp_fc1_bias[name=p_getattr_l__self___trunk_blocks___13___mlp_fc1_bias]. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"FxOnnxInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":414 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0008", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___13___mlp_fc2_weight[name=p_getattr_l__self___trunk_blocks___13___mlp_fc2_weight]. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature FxOnnxInterpreter.run_node\n- self: \n- node: fx.Node(p_getattr_l__self___trunk_blocks___13___mlp_fc2_weight)[placeholder]:Tensor(f32[1024, 4096])\n- fx_graph_module: torch.fx.GraphModule(timm_models_vision_transformer_VisionTransformer)\n- onnxfunction_dispatcher: \n- op_level_debug: False\n- onnxscript_graph: \n- onnxscript_tracer: \n- fx_name_to_onnxscript_value: Dict[length=170](\nx: `TorchScriptTensor(f32[4, 3, 512, 512])`,\np_trunk_patch_embed_proj_weight: `TorchScriptTensor(f32[1024, 3, 16, 16])`,\np_trunk_patch_embed_proj_bias: `TorchScriptTensor(f32[1024])`,\np_trunk_pos_embed: `TorchScriptTensor(f32[1, 1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_weight: `TorchScriptTensor(f32[3072, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_bias: `TorchScriptTensor(f32[3072])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_weight: `TorchScriptTensor(f32[1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_bias: `TorchScriptTensor(f32[1024])`,\n...\n)\n## Return values\n", + "text":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___13___mlp_fc2_weight[name=p_getattr_l__self___trunk_blocks___13___mlp_fc2_weight]. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"FxOnnxInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":414 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0008", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___13___mlp_fc2_bias[name=p_getattr_l__self___trunk_blocks___13___mlp_fc2_bias]. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature FxOnnxInterpreter.run_node\n- self: \n- node: fx.Node(p_getattr_l__self___trunk_blocks___13___mlp_fc2_bias)[placeholder]:Tensor(f32[1024])\n- fx_graph_module: torch.fx.GraphModule(timm_models_vision_transformer_VisionTransformer)\n- onnxfunction_dispatcher: \n- op_level_debug: False\n- onnxscript_graph: \n- onnxscript_tracer: \n- fx_name_to_onnxscript_value: Dict[length=171](\nx: `TorchScriptTensor(f32[4, 3, 512, 512])`,\np_trunk_patch_embed_proj_weight: `TorchScriptTensor(f32[1024, 3, 16, 16])`,\np_trunk_patch_embed_proj_bias: `TorchScriptTensor(f32[1024])`,\np_trunk_pos_embed: `TorchScriptTensor(f32[1, 1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_weight: `TorchScriptTensor(f32[3072, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_bias: `TorchScriptTensor(f32[3072])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_weight: `TorchScriptTensor(f32[1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_bias: `TorchScriptTensor(f32[1024])`,\n...\n)\n## Return values\n", + "text":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___13___mlp_fc2_bias[name=p_getattr_l__self___trunk_blocks___13___mlp_fc2_bias]. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"FxOnnxInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":414 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0008", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___14___norm1_weight[name=p_getattr_l__self___trunk_blocks___14___norm1_weight]. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature FxOnnxInterpreter.run_node\n- self: \n- node: fx.Node(p_getattr_l__self___trunk_blocks___14___norm1_weight)[placeholder]:Tensor(f32[1024])\n- fx_graph_module: torch.fx.GraphModule(timm_models_vision_transformer_VisionTransformer)\n- onnxfunction_dispatcher: \n- op_level_debug: False\n- onnxscript_graph: \n- onnxscript_tracer: \n- fx_name_to_onnxscript_value: Dict[length=172](\nx: `TorchScriptTensor(f32[4, 3, 512, 512])`,\np_trunk_patch_embed_proj_weight: `TorchScriptTensor(f32[1024, 3, 16, 16])`,\np_trunk_patch_embed_proj_bias: `TorchScriptTensor(f32[1024])`,\np_trunk_pos_embed: `TorchScriptTensor(f32[1, 1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_weight: `TorchScriptTensor(f32[3072, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_bias: `TorchScriptTensor(f32[3072])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_weight: `TorchScriptTensor(f32[1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_bias: `TorchScriptTensor(f32[1024])`,\n...\n)\n## Return values\n", + "text":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___14___norm1_weight[name=p_getattr_l__self___trunk_blocks___14___norm1_weight]. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"FxOnnxInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":414 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0008", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___14___norm1_bias[name=p_getattr_l__self___trunk_blocks___14___norm1_bias]. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature FxOnnxInterpreter.run_node\n- self: \n- node: fx.Node(p_getattr_l__self___trunk_blocks___14___norm1_bias)[placeholder]:Tensor(f32[1024])\n- fx_graph_module: torch.fx.GraphModule(timm_models_vision_transformer_VisionTransformer)\n- onnxfunction_dispatcher: \n- op_level_debug: False\n- onnxscript_graph: \n- onnxscript_tracer: \n- fx_name_to_onnxscript_value: Dict[length=173](\nx: `TorchScriptTensor(f32[4, 3, 512, 512])`,\np_trunk_patch_embed_proj_weight: `TorchScriptTensor(f32[1024, 3, 16, 16])`,\np_trunk_patch_embed_proj_bias: `TorchScriptTensor(f32[1024])`,\np_trunk_pos_embed: `TorchScriptTensor(f32[1, 1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_weight: `TorchScriptTensor(f32[3072, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_bias: `TorchScriptTensor(f32[3072])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_weight: `TorchScriptTensor(f32[1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_bias: `TorchScriptTensor(f32[1024])`,\n...\n)\n## Return values\n", + "text":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___14___norm1_bias[name=p_getattr_l__self___trunk_blocks___14___norm1_bias]. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"FxOnnxInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":414 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0008", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___14___attn_qkv_weight[name=p_getattr_l__self___trunk_blocks___14___attn_qkv_weight]. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature FxOnnxInterpreter.run_node\n- self: \n- node: fx.Node(p_getattr_l__self___trunk_blocks___14___attn_qkv_weight)[placeholder]:Tensor(f32[3072, 1024])\n- fx_graph_module: torch.fx.GraphModule(timm_models_vision_transformer_VisionTransformer)\n- onnxfunction_dispatcher: \n- op_level_debug: False\n- onnxscript_graph: \n- onnxscript_tracer: \n- fx_name_to_onnxscript_value: Dict[length=174](\nx: `TorchScriptTensor(f32[4, 3, 512, 512])`,\np_trunk_patch_embed_proj_weight: `TorchScriptTensor(f32[1024, 3, 16, 16])`,\np_trunk_patch_embed_proj_bias: `TorchScriptTensor(f32[1024])`,\np_trunk_pos_embed: `TorchScriptTensor(f32[1, 1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_weight: `TorchScriptTensor(f32[3072, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_bias: `TorchScriptTensor(f32[3072])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_weight: `TorchScriptTensor(f32[1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_bias: `TorchScriptTensor(f32[1024])`,\n...\n)\n## Return values\n", + "text":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___14___attn_qkv_weight[name=p_getattr_l__self___trunk_blocks___14___attn_qkv_weight]. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"FxOnnxInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":414 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0008", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___14___attn_qkv_bias[name=p_getattr_l__self___trunk_blocks___14___attn_qkv_bias]. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature FxOnnxInterpreter.run_node\n- self: \n- node: fx.Node(p_getattr_l__self___trunk_blocks___14___attn_qkv_bias)[placeholder]:Tensor(f32[3072])\n- fx_graph_module: torch.fx.GraphModule(timm_models_vision_transformer_VisionTransformer)\n- onnxfunction_dispatcher: \n- op_level_debug: False\n- onnxscript_graph: \n- onnxscript_tracer: \n- fx_name_to_onnxscript_value: Dict[length=175](\nx: `TorchScriptTensor(f32[4, 3, 512, 512])`,\np_trunk_patch_embed_proj_weight: `TorchScriptTensor(f32[1024, 3, 16, 16])`,\np_trunk_patch_embed_proj_bias: `TorchScriptTensor(f32[1024])`,\np_trunk_pos_embed: `TorchScriptTensor(f32[1, 1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_weight: `TorchScriptTensor(f32[3072, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_bias: `TorchScriptTensor(f32[3072])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_weight: `TorchScriptTensor(f32[1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_bias: `TorchScriptTensor(f32[1024])`,\n...\n)\n## Return values\n", + "text":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___14___attn_qkv_bias[name=p_getattr_l__self___trunk_blocks___14___attn_qkv_bias]. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"FxOnnxInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":414 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0008", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___14___attn_proj_weight[name=p_getattr_l__self___trunk_blocks___14___attn_proj_weight]. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature FxOnnxInterpreter.run_node\n- self: \n- node: fx.Node(p_getattr_l__self___trunk_blocks___14___attn_proj_weight)[placeholder]:Tensor(f32[1024, 1024])\n- fx_graph_module: torch.fx.GraphModule(timm_models_vision_transformer_VisionTransformer)\n- onnxfunction_dispatcher: \n- op_level_debug: False\n- onnxscript_graph: \n- onnxscript_tracer: \n- fx_name_to_onnxscript_value: Dict[length=176](\nx: `TorchScriptTensor(f32[4, 3, 512, 512])`,\np_trunk_patch_embed_proj_weight: `TorchScriptTensor(f32[1024, 3, 16, 16])`,\np_trunk_patch_embed_proj_bias: `TorchScriptTensor(f32[1024])`,\np_trunk_pos_embed: `TorchScriptTensor(f32[1, 1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_weight: `TorchScriptTensor(f32[3072, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_bias: `TorchScriptTensor(f32[3072])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_weight: `TorchScriptTensor(f32[1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_bias: `TorchScriptTensor(f32[1024])`,\n...\n)\n## Return values\n", + "text":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___14___attn_proj_weight[name=p_getattr_l__self___trunk_blocks___14___attn_proj_weight]. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"FxOnnxInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":414 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0008", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___14___attn_proj_bias[name=p_getattr_l__self___trunk_blocks___14___attn_proj_bias]. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature FxOnnxInterpreter.run_node\n- self: \n- node: fx.Node(p_getattr_l__self___trunk_blocks___14___attn_proj_bias)[placeholder]:Tensor(f32[1024])\n- fx_graph_module: torch.fx.GraphModule(timm_models_vision_transformer_VisionTransformer)\n- onnxfunction_dispatcher: \n- op_level_debug: False\n- onnxscript_graph: \n- onnxscript_tracer: \n- fx_name_to_onnxscript_value: Dict[length=177](\nx: `TorchScriptTensor(f32[4, 3, 512, 512])`,\np_trunk_patch_embed_proj_weight: `TorchScriptTensor(f32[1024, 3, 16, 16])`,\np_trunk_patch_embed_proj_bias: `TorchScriptTensor(f32[1024])`,\np_trunk_pos_embed: `TorchScriptTensor(f32[1, 1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_weight: `TorchScriptTensor(f32[3072, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_bias: `TorchScriptTensor(f32[3072])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_weight: `TorchScriptTensor(f32[1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_bias: `TorchScriptTensor(f32[1024])`,\n...\n)\n## Return values\n", + "text":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___14___attn_proj_bias[name=p_getattr_l__self___trunk_blocks___14___attn_proj_bias]. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"FxOnnxInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":414 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0008", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___14___norm2_weight[name=p_getattr_l__self___trunk_blocks___14___norm2_weight]. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature FxOnnxInterpreter.run_node\n- self: \n- node: fx.Node(p_getattr_l__self___trunk_blocks___14___norm2_weight)[placeholder]:Tensor(f32[1024])\n- fx_graph_module: torch.fx.GraphModule(timm_models_vision_transformer_VisionTransformer)\n- onnxfunction_dispatcher: \n- op_level_debug: False\n- onnxscript_graph: \n- onnxscript_tracer: \n- fx_name_to_onnxscript_value: Dict[length=178](\nx: `TorchScriptTensor(f32[4, 3, 512, 512])`,\np_trunk_patch_embed_proj_weight: `TorchScriptTensor(f32[1024, 3, 16, 16])`,\np_trunk_patch_embed_proj_bias: `TorchScriptTensor(f32[1024])`,\np_trunk_pos_embed: `TorchScriptTensor(f32[1, 1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_weight: `TorchScriptTensor(f32[3072, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_bias: `TorchScriptTensor(f32[3072])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_weight: `TorchScriptTensor(f32[1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_bias: `TorchScriptTensor(f32[1024])`,\n...\n)\n## Return values\n", + "text":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___14___norm2_weight[name=p_getattr_l__self___trunk_blocks___14___norm2_weight]. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"FxOnnxInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":414 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0008", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___14___norm2_bias[name=p_getattr_l__self___trunk_blocks___14___norm2_bias]. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature FxOnnxInterpreter.run_node\n- self: \n- node: fx.Node(p_getattr_l__self___trunk_blocks___14___norm2_bias)[placeholder]:Tensor(f32[1024])\n- fx_graph_module: torch.fx.GraphModule(timm_models_vision_transformer_VisionTransformer)\n- onnxfunction_dispatcher: \n- op_level_debug: False\n- onnxscript_graph: \n- onnxscript_tracer: \n- fx_name_to_onnxscript_value: Dict[length=179](\nx: `TorchScriptTensor(f32[4, 3, 512, 512])`,\np_trunk_patch_embed_proj_weight: `TorchScriptTensor(f32[1024, 3, 16, 16])`,\np_trunk_patch_embed_proj_bias: `TorchScriptTensor(f32[1024])`,\np_trunk_pos_embed: `TorchScriptTensor(f32[1, 1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_weight: `TorchScriptTensor(f32[3072, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_bias: `TorchScriptTensor(f32[3072])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_weight: `TorchScriptTensor(f32[1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_bias: `TorchScriptTensor(f32[1024])`,\n...\n)\n## Return values\n", + "text":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___14___norm2_bias[name=p_getattr_l__self___trunk_blocks___14___norm2_bias]. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"FxOnnxInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":414 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0008", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___14___mlp_fc1_weight[name=p_getattr_l__self___trunk_blocks___14___mlp_fc1_weight]. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature FxOnnxInterpreter.run_node\n- self: \n- node: fx.Node(p_getattr_l__self___trunk_blocks___14___mlp_fc1_weight)[placeholder]:Tensor(f32[4096, 1024])\n- fx_graph_module: torch.fx.GraphModule(timm_models_vision_transformer_VisionTransformer)\n- onnxfunction_dispatcher: \n- op_level_debug: False\n- onnxscript_graph: \n- onnxscript_tracer: \n- fx_name_to_onnxscript_value: Dict[length=180](\nx: `TorchScriptTensor(f32[4, 3, 512, 512])`,\np_trunk_patch_embed_proj_weight: `TorchScriptTensor(f32[1024, 3, 16, 16])`,\np_trunk_patch_embed_proj_bias: `TorchScriptTensor(f32[1024])`,\np_trunk_pos_embed: `TorchScriptTensor(f32[1, 1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_weight: `TorchScriptTensor(f32[3072, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_bias: `TorchScriptTensor(f32[3072])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_weight: `TorchScriptTensor(f32[1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_bias: `TorchScriptTensor(f32[1024])`,\n...\n)\n## Return values\n", + "text":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___14___mlp_fc1_weight[name=p_getattr_l__self___trunk_blocks___14___mlp_fc1_weight]. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"FxOnnxInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":414 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0008", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___14___mlp_fc1_bias[name=p_getattr_l__self___trunk_blocks___14___mlp_fc1_bias]. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature FxOnnxInterpreter.run_node\n- self: \n- node: fx.Node(p_getattr_l__self___trunk_blocks___14___mlp_fc1_bias)[placeholder]:Tensor(f32[4096])\n- fx_graph_module: torch.fx.GraphModule(timm_models_vision_transformer_VisionTransformer)\n- onnxfunction_dispatcher: \n- op_level_debug: False\n- onnxscript_graph: \n- onnxscript_tracer: \n- fx_name_to_onnxscript_value: Dict[length=181](\nx: `TorchScriptTensor(f32[4, 3, 512, 512])`,\np_trunk_patch_embed_proj_weight: `TorchScriptTensor(f32[1024, 3, 16, 16])`,\np_trunk_patch_embed_proj_bias: `TorchScriptTensor(f32[1024])`,\np_trunk_pos_embed: `TorchScriptTensor(f32[1, 1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_weight: `TorchScriptTensor(f32[3072, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_bias: `TorchScriptTensor(f32[3072])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_weight: `TorchScriptTensor(f32[1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_bias: `TorchScriptTensor(f32[1024])`,\n...\n)\n## Return values\n", + "text":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___14___mlp_fc1_bias[name=p_getattr_l__self___trunk_blocks___14___mlp_fc1_bias]. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"FxOnnxInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":414 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0008", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___14___mlp_fc2_weight[name=p_getattr_l__self___trunk_blocks___14___mlp_fc2_weight]. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature FxOnnxInterpreter.run_node\n- self: \n- node: fx.Node(p_getattr_l__self___trunk_blocks___14___mlp_fc2_weight)[placeholder]:Tensor(f32[1024, 4096])\n- fx_graph_module: torch.fx.GraphModule(timm_models_vision_transformer_VisionTransformer)\n- onnxfunction_dispatcher: \n- op_level_debug: False\n- onnxscript_graph: \n- onnxscript_tracer: \n- fx_name_to_onnxscript_value: Dict[length=182](\nx: `TorchScriptTensor(f32[4, 3, 512, 512])`,\np_trunk_patch_embed_proj_weight: `TorchScriptTensor(f32[1024, 3, 16, 16])`,\np_trunk_patch_embed_proj_bias: `TorchScriptTensor(f32[1024])`,\np_trunk_pos_embed: `TorchScriptTensor(f32[1, 1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_weight: `TorchScriptTensor(f32[3072, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_bias: `TorchScriptTensor(f32[3072])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_weight: `TorchScriptTensor(f32[1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_bias: `TorchScriptTensor(f32[1024])`,\n...\n)\n## Return values\n", + "text":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___14___mlp_fc2_weight[name=p_getattr_l__self___trunk_blocks___14___mlp_fc2_weight]. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"FxOnnxInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":414 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0008", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___14___mlp_fc2_bias[name=p_getattr_l__self___trunk_blocks___14___mlp_fc2_bias]. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature FxOnnxInterpreter.run_node\n- self: \n- node: fx.Node(p_getattr_l__self___trunk_blocks___14___mlp_fc2_bias)[placeholder]:Tensor(f32[1024])\n- fx_graph_module: torch.fx.GraphModule(timm_models_vision_transformer_VisionTransformer)\n- onnxfunction_dispatcher: \n- op_level_debug: False\n- onnxscript_graph: \n- onnxscript_tracer: \n- fx_name_to_onnxscript_value: Dict[length=183](\nx: `TorchScriptTensor(f32[4, 3, 512, 512])`,\np_trunk_patch_embed_proj_weight: `TorchScriptTensor(f32[1024, 3, 16, 16])`,\np_trunk_patch_embed_proj_bias: `TorchScriptTensor(f32[1024])`,\np_trunk_pos_embed: `TorchScriptTensor(f32[1, 1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_weight: `TorchScriptTensor(f32[3072, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_bias: `TorchScriptTensor(f32[3072])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_weight: `TorchScriptTensor(f32[1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_bias: `TorchScriptTensor(f32[1024])`,\n...\n)\n## Return values\n", + "text":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___14___mlp_fc2_bias[name=p_getattr_l__self___trunk_blocks___14___mlp_fc2_bias]. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"FxOnnxInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":414 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0008", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___15___norm1_weight[name=p_getattr_l__self___trunk_blocks___15___norm1_weight]. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature FxOnnxInterpreter.run_node\n- self: \n- node: fx.Node(p_getattr_l__self___trunk_blocks___15___norm1_weight)[placeholder]:Tensor(f32[1024])\n- fx_graph_module: torch.fx.GraphModule(timm_models_vision_transformer_VisionTransformer)\n- onnxfunction_dispatcher: \n- op_level_debug: False\n- onnxscript_graph: \n- onnxscript_tracer: \n- fx_name_to_onnxscript_value: Dict[length=184](\nx: `TorchScriptTensor(f32[4, 3, 512, 512])`,\np_trunk_patch_embed_proj_weight: `TorchScriptTensor(f32[1024, 3, 16, 16])`,\np_trunk_patch_embed_proj_bias: `TorchScriptTensor(f32[1024])`,\np_trunk_pos_embed: `TorchScriptTensor(f32[1, 1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_weight: `TorchScriptTensor(f32[3072, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_bias: `TorchScriptTensor(f32[3072])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_weight: `TorchScriptTensor(f32[1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_bias: `TorchScriptTensor(f32[1024])`,\n...\n)\n## Return values\n", + "text":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___15___norm1_weight[name=p_getattr_l__self___trunk_blocks___15___norm1_weight]. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"FxOnnxInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":414 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0008", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___15___norm1_bias[name=p_getattr_l__self___trunk_blocks___15___norm1_bias]. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature FxOnnxInterpreter.run_node\n- self: \n- node: fx.Node(p_getattr_l__self___trunk_blocks___15___norm1_bias)[placeholder]:Tensor(f32[1024])\n- fx_graph_module: torch.fx.GraphModule(timm_models_vision_transformer_VisionTransformer)\n- onnxfunction_dispatcher: \n- op_level_debug: False\n- onnxscript_graph: \n- onnxscript_tracer: \n- fx_name_to_onnxscript_value: Dict[length=185](\nx: `TorchScriptTensor(f32[4, 3, 512, 512])`,\np_trunk_patch_embed_proj_weight: `TorchScriptTensor(f32[1024, 3, 16, 16])`,\np_trunk_patch_embed_proj_bias: `TorchScriptTensor(f32[1024])`,\np_trunk_pos_embed: `TorchScriptTensor(f32[1, 1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_weight: `TorchScriptTensor(f32[3072, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_bias: `TorchScriptTensor(f32[3072])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_weight: `TorchScriptTensor(f32[1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_bias: `TorchScriptTensor(f32[1024])`,\n...\n)\n## Return values\n", + "text":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___15___norm1_bias[name=p_getattr_l__self___trunk_blocks___15___norm1_bias]. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"FxOnnxInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":414 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0008", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___15___attn_qkv_weight[name=p_getattr_l__self___trunk_blocks___15___attn_qkv_weight]. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature FxOnnxInterpreter.run_node\n- self: \n- node: fx.Node(p_getattr_l__self___trunk_blocks___15___attn_qkv_weight)[placeholder]:Tensor(f32[3072, 1024])\n- fx_graph_module: torch.fx.GraphModule(timm_models_vision_transformer_VisionTransformer)\n- onnxfunction_dispatcher: \n- op_level_debug: False\n- onnxscript_graph: \n- onnxscript_tracer: \n- fx_name_to_onnxscript_value: Dict[length=186](\nx: `TorchScriptTensor(f32[4, 3, 512, 512])`,\np_trunk_patch_embed_proj_weight: `TorchScriptTensor(f32[1024, 3, 16, 16])`,\np_trunk_patch_embed_proj_bias: `TorchScriptTensor(f32[1024])`,\np_trunk_pos_embed: `TorchScriptTensor(f32[1, 1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_weight: `TorchScriptTensor(f32[3072, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_bias: `TorchScriptTensor(f32[3072])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_weight: `TorchScriptTensor(f32[1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_bias: `TorchScriptTensor(f32[1024])`,\n...\n)\n## Return values\n", + "text":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___15___attn_qkv_weight[name=p_getattr_l__self___trunk_blocks___15___attn_qkv_weight]. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"FxOnnxInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":414 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0008", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___15___attn_qkv_bias[name=p_getattr_l__self___trunk_blocks___15___attn_qkv_bias]. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature FxOnnxInterpreter.run_node\n- self: \n- node: fx.Node(p_getattr_l__self___trunk_blocks___15___attn_qkv_bias)[placeholder]:Tensor(f32[3072])\n- fx_graph_module: torch.fx.GraphModule(timm_models_vision_transformer_VisionTransformer)\n- onnxfunction_dispatcher: \n- op_level_debug: False\n- onnxscript_graph: \n- onnxscript_tracer: \n- fx_name_to_onnxscript_value: Dict[length=187](\nx: `TorchScriptTensor(f32[4, 3, 512, 512])`,\np_trunk_patch_embed_proj_weight: `TorchScriptTensor(f32[1024, 3, 16, 16])`,\np_trunk_patch_embed_proj_bias: `TorchScriptTensor(f32[1024])`,\np_trunk_pos_embed: `TorchScriptTensor(f32[1, 1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_weight: `TorchScriptTensor(f32[3072, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_bias: `TorchScriptTensor(f32[3072])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_weight: `TorchScriptTensor(f32[1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_bias: `TorchScriptTensor(f32[1024])`,\n...\n)\n## Return values\n", + "text":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___15___attn_qkv_bias[name=p_getattr_l__self___trunk_blocks___15___attn_qkv_bias]. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"FxOnnxInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":414 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0008", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___15___attn_proj_weight[name=p_getattr_l__self___trunk_blocks___15___attn_proj_weight]. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature FxOnnxInterpreter.run_node\n- self: \n- node: fx.Node(p_getattr_l__self___trunk_blocks___15___attn_proj_weight)[placeholder]:Tensor(f32[1024, 1024])\n- fx_graph_module: torch.fx.GraphModule(timm_models_vision_transformer_VisionTransformer)\n- onnxfunction_dispatcher: \n- op_level_debug: False\n- onnxscript_graph: \n- onnxscript_tracer: \n- fx_name_to_onnxscript_value: Dict[length=188](\nx: `TorchScriptTensor(f32[4, 3, 512, 512])`,\np_trunk_patch_embed_proj_weight: `TorchScriptTensor(f32[1024, 3, 16, 16])`,\np_trunk_patch_embed_proj_bias: `TorchScriptTensor(f32[1024])`,\np_trunk_pos_embed: `TorchScriptTensor(f32[1, 1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_weight: `TorchScriptTensor(f32[3072, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_bias: `TorchScriptTensor(f32[3072])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_weight: `TorchScriptTensor(f32[1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_bias: `TorchScriptTensor(f32[1024])`,\n...\n)\n## Return values\n", + "text":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___15___attn_proj_weight[name=p_getattr_l__self___trunk_blocks___15___attn_proj_weight]. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"FxOnnxInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":414 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0008", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___15___attn_proj_bias[name=p_getattr_l__self___trunk_blocks___15___attn_proj_bias]. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature FxOnnxInterpreter.run_node\n- self: \n- node: fx.Node(p_getattr_l__self___trunk_blocks___15___attn_proj_bias)[placeholder]:Tensor(f32[1024])\n- fx_graph_module: torch.fx.GraphModule(timm_models_vision_transformer_VisionTransformer)\n- onnxfunction_dispatcher: \n- op_level_debug: False\n- onnxscript_graph: \n- onnxscript_tracer: \n- fx_name_to_onnxscript_value: Dict[length=189](\nx: `TorchScriptTensor(f32[4, 3, 512, 512])`,\np_trunk_patch_embed_proj_weight: `TorchScriptTensor(f32[1024, 3, 16, 16])`,\np_trunk_patch_embed_proj_bias: `TorchScriptTensor(f32[1024])`,\np_trunk_pos_embed: `TorchScriptTensor(f32[1, 1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_weight: `TorchScriptTensor(f32[3072, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_bias: `TorchScriptTensor(f32[3072])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_weight: `TorchScriptTensor(f32[1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_bias: `TorchScriptTensor(f32[1024])`,\n...\n)\n## Return values\n", + "text":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___15___attn_proj_bias[name=p_getattr_l__self___trunk_blocks___15___attn_proj_bias]. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"FxOnnxInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":414 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0008", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___15___norm2_weight[name=p_getattr_l__self___trunk_blocks___15___norm2_weight]. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature FxOnnxInterpreter.run_node\n- self: \n- node: fx.Node(p_getattr_l__self___trunk_blocks___15___norm2_weight)[placeholder]:Tensor(f32[1024])\n- fx_graph_module: torch.fx.GraphModule(timm_models_vision_transformer_VisionTransformer)\n- onnxfunction_dispatcher: \n- op_level_debug: False\n- onnxscript_graph: \n- onnxscript_tracer: \n- fx_name_to_onnxscript_value: Dict[length=190](\nx: `TorchScriptTensor(f32[4, 3, 512, 512])`,\np_trunk_patch_embed_proj_weight: `TorchScriptTensor(f32[1024, 3, 16, 16])`,\np_trunk_patch_embed_proj_bias: `TorchScriptTensor(f32[1024])`,\np_trunk_pos_embed: `TorchScriptTensor(f32[1, 1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_weight: `TorchScriptTensor(f32[3072, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_bias: `TorchScriptTensor(f32[3072])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_weight: `TorchScriptTensor(f32[1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_bias: `TorchScriptTensor(f32[1024])`,\n...\n)\n## Return values\n", + "text":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___15___norm2_weight[name=p_getattr_l__self___trunk_blocks___15___norm2_weight]. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"FxOnnxInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":414 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0008", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___15___norm2_bias[name=p_getattr_l__self___trunk_blocks___15___norm2_bias]. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature FxOnnxInterpreter.run_node\n- self: \n- node: fx.Node(p_getattr_l__self___trunk_blocks___15___norm2_bias)[placeholder]:Tensor(f32[1024])\n- fx_graph_module: torch.fx.GraphModule(timm_models_vision_transformer_VisionTransformer)\n- onnxfunction_dispatcher: \n- op_level_debug: False\n- onnxscript_graph: \n- onnxscript_tracer: \n- fx_name_to_onnxscript_value: Dict[length=191](\nx: `TorchScriptTensor(f32[4, 3, 512, 512])`,\np_trunk_patch_embed_proj_weight: `TorchScriptTensor(f32[1024, 3, 16, 16])`,\np_trunk_patch_embed_proj_bias: `TorchScriptTensor(f32[1024])`,\np_trunk_pos_embed: `TorchScriptTensor(f32[1, 1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_weight: `TorchScriptTensor(f32[3072, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_bias: `TorchScriptTensor(f32[3072])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_weight: `TorchScriptTensor(f32[1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_bias: `TorchScriptTensor(f32[1024])`,\n...\n)\n## Return values\n", + "text":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___15___norm2_bias[name=p_getattr_l__self___trunk_blocks___15___norm2_bias]. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"FxOnnxInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":414 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0008", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___15___mlp_fc1_weight[name=p_getattr_l__self___trunk_blocks___15___mlp_fc1_weight]. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature FxOnnxInterpreter.run_node\n- self: \n- node: fx.Node(p_getattr_l__self___trunk_blocks___15___mlp_fc1_weight)[placeholder]:Tensor(f32[4096, 1024])\n- fx_graph_module: torch.fx.GraphModule(timm_models_vision_transformer_VisionTransformer)\n- onnxfunction_dispatcher: \n- op_level_debug: False\n- onnxscript_graph: \n- onnxscript_tracer: \n- fx_name_to_onnxscript_value: Dict[length=192](\nx: `TorchScriptTensor(f32[4, 3, 512, 512])`,\np_trunk_patch_embed_proj_weight: `TorchScriptTensor(f32[1024, 3, 16, 16])`,\np_trunk_patch_embed_proj_bias: `TorchScriptTensor(f32[1024])`,\np_trunk_pos_embed: `TorchScriptTensor(f32[1, 1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_weight: `TorchScriptTensor(f32[3072, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_bias: `TorchScriptTensor(f32[3072])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_weight: `TorchScriptTensor(f32[1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_bias: `TorchScriptTensor(f32[1024])`,\n...\n)\n## Return values\n", + "text":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___15___mlp_fc1_weight[name=p_getattr_l__self___trunk_blocks___15___mlp_fc1_weight]. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"FxOnnxInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":414 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0008", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___15___mlp_fc1_bias[name=p_getattr_l__self___trunk_blocks___15___mlp_fc1_bias]. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature FxOnnxInterpreter.run_node\n- self: \n- node: fx.Node(p_getattr_l__self___trunk_blocks___15___mlp_fc1_bias)[placeholder]:Tensor(f32[4096])\n- fx_graph_module: torch.fx.GraphModule(timm_models_vision_transformer_VisionTransformer)\n- onnxfunction_dispatcher: \n- op_level_debug: False\n- onnxscript_graph: \n- onnxscript_tracer: \n- fx_name_to_onnxscript_value: Dict[length=193](\nx: `TorchScriptTensor(f32[4, 3, 512, 512])`,\np_trunk_patch_embed_proj_weight: `TorchScriptTensor(f32[1024, 3, 16, 16])`,\np_trunk_patch_embed_proj_bias: `TorchScriptTensor(f32[1024])`,\np_trunk_pos_embed: `TorchScriptTensor(f32[1, 1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_weight: `TorchScriptTensor(f32[3072, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_bias: `TorchScriptTensor(f32[3072])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_weight: `TorchScriptTensor(f32[1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_bias: `TorchScriptTensor(f32[1024])`,\n...\n)\n## Return values\n", + "text":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___15___mlp_fc1_bias[name=p_getattr_l__self___trunk_blocks___15___mlp_fc1_bias]. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"FxOnnxInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":414 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0008", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___15___mlp_fc2_weight[name=p_getattr_l__self___trunk_blocks___15___mlp_fc2_weight]. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature FxOnnxInterpreter.run_node\n- self: \n- node: fx.Node(p_getattr_l__self___trunk_blocks___15___mlp_fc2_weight)[placeholder]:Tensor(f32[1024, 4096])\n- fx_graph_module: torch.fx.GraphModule(timm_models_vision_transformer_VisionTransformer)\n- onnxfunction_dispatcher: \n- op_level_debug: False\n- onnxscript_graph: \n- onnxscript_tracer: \n- fx_name_to_onnxscript_value: Dict[length=194](\nx: `TorchScriptTensor(f32[4, 3, 512, 512])`,\np_trunk_patch_embed_proj_weight: `TorchScriptTensor(f32[1024, 3, 16, 16])`,\np_trunk_patch_embed_proj_bias: `TorchScriptTensor(f32[1024])`,\np_trunk_pos_embed: `TorchScriptTensor(f32[1, 1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_weight: `TorchScriptTensor(f32[3072, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_bias: `TorchScriptTensor(f32[3072])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_weight: `TorchScriptTensor(f32[1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_bias: `TorchScriptTensor(f32[1024])`,\n...\n)\n## Return values\n", + "text":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___15___mlp_fc2_weight[name=p_getattr_l__self___trunk_blocks___15___mlp_fc2_weight]. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"FxOnnxInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":414 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0008", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___15___mlp_fc2_bias[name=p_getattr_l__self___trunk_blocks___15___mlp_fc2_bias]. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature FxOnnxInterpreter.run_node\n- self: \n- node: fx.Node(p_getattr_l__self___trunk_blocks___15___mlp_fc2_bias)[placeholder]:Tensor(f32[1024])\n- fx_graph_module: torch.fx.GraphModule(timm_models_vision_transformer_VisionTransformer)\n- onnxfunction_dispatcher: \n- op_level_debug: False\n- onnxscript_graph: \n- onnxscript_tracer: \n- fx_name_to_onnxscript_value: Dict[length=195](\nx: `TorchScriptTensor(f32[4, 3, 512, 512])`,\np_trunk_patch_embed_proj_weight: `TorchScriptTensor(f32[1024, 3, 16, 16])`,\np_trunk_patch_embed_proj_bias: `TorchScriptTensor(f32[1024])`,\np_trunk_pos_embed: `TorchScriptTensor(f32[1, 1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_weight: `TorchScriptTensor(f32[3072, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_bias: `TorchScriptTensor(f32[3072])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_weight: `TorchScriptTensor(f32[1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_bias: `TorchScriptTensor(f32[1024])`,\n...\n)\n## Return values\n", + "text":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___15___mlp_fc2_bias[name=p_getattr_l__self___trunk_blocks___15___mlp_fc2_bias]. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"FxOnnxInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":414 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0008", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___16___norm1_weight[name=p_getattr_l__self___trunk_blocks___16___norm1_weight]. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature FxOnnxInterpreter.run_node\n- self: \n- node: fx.Node(p_getattr_l__self___trunk_blocks___16___norm1_weight)[placeholder]:Tensor(f32[1024])\n- fx_graph_module: torch.fx.GraphModule(timm_models_vision_transformer_VisionTransformer)\n- onnxfunction_dispatcher: \n- op_level_debug: False\n- onnxscript_graph: \n- onnxscript_tracer: \n- fx_name_to_onnxscript_value: Dict[length=196](\nx: `TorchScriptTensor(f32[4, 3, 512, 512])`,\np_trunk_patch_embed_proj_weight: `TorchScriptTensor(f32[1024, 3, 16, 16])`,\np_trunk_patch_embed_proj_bias: `TorchScriptTensor(f32[1024])`,\np_trunk_pos_embed: `TorchScriptTensor(f32[1, 1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_weight: `TorchScriptTensor(f32[3072, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_bias: `TorchScriptTensor(f32[3072])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_weight: `TorchScriptTensor(f32[1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_bias: `TorchScriptTensor(f32[1024])`,\n...\n)\n## Return values\n", + "text":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___16___norm1_weight[name=p_getattr_l__self___trunk_blocks___16___norm1_weight]. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"FxOnnxInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":414 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0008", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___16___norm1_bias[name=p_getattr_l__self___trunk_blocks___16___norm1_bias]. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature FxOnnxInterpreter.run_node\n- self: \n- node: fx.Node(p_getattr_l__self___trunk_blocks___16___norm1_bias)[placeholder]:Tensor(f32[1024])\n- fx_graph_module: torch.fx.GraphModule(timm_models_vision_transformer_VisionTransformer)\n- onnxfunction_dispatcher: \n- op_level_debug: False\n- onnxscript_graph: \n- onnxscript_tracer: \n- fx_name_to_onnxscript_value: Dict[length=197](\nx: `TorchScriptTensor(f32[4, 3, 512, 512])`,\np_trunk_patch_embed_proj_weight: `TorchScriptTensor(f32[1024, 3, 16, 16])`,\np_trunk_patch_embed_proj_bias: `TorchScriptTensor(f32[1024])`,\np_trunk_pos_embed: `TorchScriptTensor(f32[1, 1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_weight: `TorchScriptTensor(f32[3072, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_bias: `TorchScriptTensor(f32[3072])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_weight: `TorchScriptTensor(f32[1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_bias: `TorchScriptTensor(f32[1024])`,\n...\n)\n## Return values\n", + "text":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___16___norm1_bias[name=p_getattr_l__self___trunk_blocks___16___norm1_bias]. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"FxOnnxInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":414 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0008", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___16___attn_qkv_weight[name=p_getattr_l__self___trunk_blocks___16___attn_qkv_weight]. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature FxOnnxInterpreter.run_node\n- self: \n- node: fx.Node(p_getattr_l__self___trunk_blocks___16___attn_qkv_weight)[placeholder]:Tensor(f32[3072, 1024])\n- fx_graph_module: torch.fx.GraphModule(timm_models_vision_transformer_VisionTransformer)\n- onnxfunction_dispatcher: \n- op_level_debug: False\n- onnxscript_graph: \n- onnxscript_tracer: \n- fx_name_to_onnxscript_value: Dict[length=198](\nx: `TorchScriptTensor(f32[4, 3, 512, 512])`,\np_trunk_patch_embed_proj_weight: `TorchScriptTensor(f32[1024, 3, 16, 16])`,\np_trunk_patch_embed_proj_bias: `TorchScriptTensor(f32[1024])`,\np_trunk_pos_embed: `TorchScriptTensor(f32[1, 1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_weight: `TorchScriptTensor(f32[3072, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_bias: `TorchScriptTensor(f32[3072])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_weight: `TorchScriptTensor(f32[1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_bias: `TorchScriptTensor(f32[1024])`,\n...\n)\n## Return values\n", + "text":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___16___attn_qkv_weight[name=p_getattr_l__self___trunk_blocks___16___attn_qkv_weight]. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"FxOnnxInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":414 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0008", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___16___attn_qkv_bias[name=p_getattr_l__self___trunk_blocks___16___attn_qkv_bias]. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature FxOnnxInterpreter.run_node\n- self: \n- node: fx.Node(p_getattr_l__self___trunk_blocks___16___attn_qkv_bias)[placeholder]:Tensor(f32[3072])\n- fx_graph_module: torch.fx.GraphModule(timm_models_vision_transformer_VisionTransformer)\n- onnxfunction_dispatcher: \n- op_level_debug: False\n- onnxscript_graph: \n- onnxscript_tracer: \n- fx_name_to_onnxscript_value: Dict[length=199](\nx: `TorchScriptTensor(f32[4, 3, 512, 512])`,\np_trunk_patch_embed_proj_weight: `TorchScriptTensor(f32[1024, 3, 16, 16])`,\np_trunk_patch_embed_proj_bias: `TorchScriptTensor(f32[1024])`,\np_trunk_pos_embed: `TorchScriptTensor(f32[1, 1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_weight: `TorchScriptTensor(f32[3072, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_bias: `TorchScriptTensor(f32[3072])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_weight: `TorchScriptTensor(f32[1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_bias: `TorchScriptTensor(f32[1024])`,\n...\n)\n## Return values\n", + "text":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___16___attn_qkv_bias[name=p_getattr_l__self___trunk_blocks___16___attn_qkv_bias]. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"FxOnnxInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":414 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0008", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___16___attn_proj_weight[name=p_getattr_l__self___trunk_blocks___16___attn_proj_weight]. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature FxOnnxInterpreter.run_node\n- self: \n- node: fx.Node(p_getattr_l__self___trunk_blocks___16___attn_proj_weight)[placeholder]:Tensor(f32[1024, 1024])\n- fx_graph_module: torch.fx.GraphModule(timm_models_vision_transformer_VisionTransformer)\n- onnxfunction_dispatcher: \n- op_level_debug: False\n- onnxscript_graph: \n- onnxscript_tracer: \n- fx_name_to_onnxscript_value: Dict[length=200](\nx: `TorchScriptTensor(f32[4, 3, 512, 512])`,\np_trunk_patch_embed_proj_weight: `TorchScriptTensor(f32[1024, 3, 16, 16])`,\np_trunk_patch_embed_proj_bias: `TorchScriptTensor(f32[1024])`,\np_trunk_pos_embed: `TorchScriptTensor(f32[1, 1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_weight: `TorchScriptTensor(f32[3072, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_bias: `TorchScriptTensor(f32[3072])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_weight: `TorchScriptTensor(f32[1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_bias: `TorchScriptTensor(f32[1024])`,\n...\n)\n## Return values\n", + "text":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___16___attn_proj_weight[name=p_getattr_l__self___trunk_blocks___16___attn_proj_weight]. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"FxOnnxInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":414 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0008", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___16___attn_proj_bias[name=p_getattr_l__self___trunk_blocks___16___attn_proj_bias]. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature FxOnnxInterpreter.run_node\n- self: \n- node: fx.Node(p_getattr_l__self___trunk_blocks___16___attn_proj_bias)[placeholder]:Tensor(f32[1024])\n- fx_graph_module: torch.fx.GraphModule(timm_models_vision_transformer_VisionTransformer)\n- onnxfunction_dispatcher: \n- op_level_debug: False\n- onnxscript_graph: \n- onnxscript_tracer: \n- fx_name_to_onnxscript_value: Dict[length=201](\nx: `TorchScriptTensor(f32[4, 3, 512, 512])`,\np_trunk_patch_embed_proj_weight: `TorchScriptTensor(f32[1024, 3, 16, 16])`,\np_trunk_patch_embed_proj_bias: `TorchScriptTensor(f32[1024])`,\np_trunk_pos_embed: `TorchScriptTensor(f32[1, 1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_weight: `TorchScriptTensor(f32[3072, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_bias: `TorchScriptTensor(f32[3072])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_weight: `TorchScriptTensor(f32[1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_bias: `TorchScriptTensor(f32[1024])`,\n...\n)\n## Return values\n", + "text":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___16___attn_proj_bias[name=p_getattr_l__self___trunk_blocks___16___attn_proj_bias]. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"FxOnnxInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":414 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0008", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___16___norm2_weight[name=p_getattr_l__self___trunk_blocks___16___norm2_weight]. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature FxOnnxInterpreter.run_node\n- self: \n- node: fx.Node(p_getattr_l__self___trunk_blocks___16___norm2_weight)[placeholder]:Tensor(f32[1024])\n- fx_graph_module: torch.fx.GraphModule(timm_models_vision_transformer_VisionTransformer)\n- onnxfunction_dispatcher: \n- op_level_debug: False\n- onnxscript_graph: \n- onnxscript_tracer: \n- fx_name_to_onnxscript_value: Dict[length=202](\nx: `TorchScriptTensor(f32[4, 3, 512, 512])`,\np_trunk_patch_embed_proj_weight: `TorchScriptTensor(f32[1024, 3, 16, 16])`,\np_trunk_patch_embed_proj_bias: `TorchScriptTensor(f32[1024])`,\np_trunk_pos_embed: `TorchScriptTensor(f32[1, 1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_weight: `TorchScriptTensor(f32[3072, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_bias: `TorchScriptTensor(f32[3072])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_weight: `TorchScriptTensor(f32[1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_bias: `TorchScriptTensor(f32[1024])`,\n...\n)\n## Return values\n", + "text":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___16___norm2_weight[name=p_getattr_l__self___trunk_blocks___16___norm2_weight]. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"FxOnnxInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":414 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0008", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___16___norm2_bias[name=p_getattr_l__self___trunk_blocks___16___norm2_bias]. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature FxOnnxInterpreter.run_node\n- self: \n- node: fx.Node(p_getattr_l__self___trunk_blocks___16___norm2_bias)[placeholder]:Tensor(f32[1024])\n- fx_graph_module: torch.fx.GraphModule(timm_models_vision_transformer_VisionTransformer)\n- onnxfunction_dispatcher: \n- op_level_debug: False\n- onnxscript_graph: \n- onnxscript_tracer: \n- fx_name_to_onnxscript_value: Dict[length=203](\nx: `TorchScriptTensor(f32[4, 3, 512, 512])`,\np_trunk_patch_embed_proj_weight: `TorchScriptTensor(f32[1024, 3, 16, 16])`,\np_trunk_patch_embed_proj_bias: `TorchScriptTensor(f32[1024])`,\np_trunk_pos_embed: `TorchScriptTensor(f32[1, 1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_weight: `TorchScriptTensor(f32[3072, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_bias: `TorchScriptTensor(f32[3072])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_weight: `TorchScriptTensor(f32[1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_bias: `TorchScriptTensor(f32[1024])`,\n...\n)\n## Return values\n", + "text":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___16___norm2_bias[name=p_getattr_l__self___trunk_blocks___16___norm2_bias]. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"FxOnnxInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":414 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0008", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___16___mlp_fc1_weight[name=p_getattr_l__self___trunk_blocks___16___mlp_fc1_weight]. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature FxOnnxInterpreter.run_node\n- self: \n- node: fx.Node(p_getattr_l__self___trunk_blocks___16___mlp_fc1_weight)[placeholder]:Tensor(f32[4096, 1024])\n- fx_graph_module: torch.fx.GraphModule(timm_models_vision_transformer_VisionTransformer)\n- onnxfunction_dispatcher: \n- op_level_debug: False\n- onnxscript_graph: \n- onnxscript_tracer: \n- fx_name_to_onnxscript_value: Dict[length=204](\nx: `TorchScriptTensor(f32[4, 3, 512, 512])`,\np_trunk_patch_embed_proj_weight: `TorchScriptTensor(f32[1024, 3, 16, 16])`,\np_trunk_patch_embed_proj_bias: `TorchScriptTensor(f32[1024])`,\np_trunk_pos_embed: `TorchScriptTensor(f32[1, 1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_weight: `TorchScriptTensor(f32[3072, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_bias: `TorchScriptTensor(f32[3072])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_weight: `TorchScriptTensor(f32[1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_bias: `TorchScriptTensor(f32[1024])`,\n...\n)\n## Return values\n", + "text":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___16___mlp_fc1_weight[name=p_getattr_l__self___trunk_blocks___16___mlp_fc1_weight]. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"FxOnnxInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":414 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0008", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___16___mlp_fc1_bias[name=p_getattr_l__self___trunk_blocks___16___mlp_fc1_bias]. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature FxOnnxInterpreter.run_node\n- self: \n- node: fx.Node(p_getattr_l__self___trunk_blocks___16___mlp_fc1_bias)[placeholder]:Tensor(f32[4096])\n- fx_graph_module: torch.fx.GraphModule(timm_models_vision_transformer_VisionTransformer)\n- onnxfunction_dispatcher: \n- op_level_debug: False\n- onnxscript_graph: \n- onnxscript_tracer: \n- fx_name_to_onnxscript_value: Dict[length=205](\nx: `TorchScriptTensor(f32[4, 3, 512, 512])`,\np_trunk_patch_embed_proj_weight: `TorchScriptTensor(f32[1024, 3, 16, 16])`,\np_trunk_patch_embed_proj_bias: `TorchScriptTensor(f32[1024])`,\np_trunk_pos_embed: `TorchScriptTensor(f32[1, 1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_weight: `TorchScriptTensor(f32[3072, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_bias: `TorchScriptTensor(f32[3072])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_weight: `TorchScriptTensor(f32[1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_bias: `TorchScriptTensor(f32[1024])`,\n...\n)\n## Return values\n", + "text":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___16___mlp_fc1_bias[name=p_getattr_l__self___trunk_blocks___16___mlp_fc1_bias]. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"FxOnnxInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":414 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0008", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___16___mlp_fc2_weight[name=p_getattr_l__self___trunk_blocks___16___mlp_fc2_weight]. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature FxOnnxInterpreter.run_node\n- self: \n- node: fx.Node(p_getattr_l__self___trunk_blocks___16___mlp_fc2_weight)[placeholder]:Tensor(f32[1024, 4096])\n- fx_graph_module: torch.fx.GraphModule(timm_models_vision_transformer_VisionTransformer)\n- onnxfunction_dispatcher: \n- op_level_debug: False\n- onnxscript_graph: \n- onnxscript_tracer: \n- fx_name_to_onnxscript_value: Dict[length=206](\nx: `TorchScriptTensor(f32[4, 3, 512, 512])`,\np_trunk_patch_embed_proj_weight: `TorchScriptTensor(f32[1024, 3, 16, 16])`,\np_trunk_patch_embed_proj_bias: `TorchScriptTensor(f32[1024])`,\np_trunk_pos_embed: `TorchScriptTensor(f32[1, 1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_weight: `TorchScriptTensor(f32[3072, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_bias: `TorchScriptTensor(f32[3072])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_weight: `TorchScriptTensor(f32[1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_bias: `TorchScriptTensor(f32[1024])`,\n...\n)\n## Return values\n", + "text":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___16___mlp_fc2_weight[name=p_getattr_l__self___trunk_blocks___16___mlp_fc2_weight]. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"FxOnnxInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":414 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0008", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___16___mlp_fc2_bias[name=p_getattr_l__self___trunk_blocks___16___mlp_fc2_bias]. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature FxOnnxInterpreter.run_node\n- self: \n- node: fx.Node(p_getattr_l__self___trunk_blocks___16___mlp_fc2_bias)[placeholder]:Tensor(f32[1024])\n- fx_graph_module: torch.fx.GraphModule(timm_models_vision_transformer_VisionTransformer)\n- onnxfunction_dispatcher: \n- op_level_debug: False\n- onnxscript_graph: \n- onnxscript_tracer: \n- fx_name_to_onnxscript_value: Dict[length=207](\nx: `TorchScriptTensor(f32[4, 3, 512, 512])`,\np_trunk_patch_embed_proj_weight: `TorchScriptTensor(f32[1024, 3, 16, 16])`,\np_trunk_patch_embed_proj_bias: `TorchScriptTensor(f32[1024])`,\np_trunk_pos_embed: `TorchScriptTensor(f32[1, 1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_weight: `TorchScriptTensor(f32[3072, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_bias: `TorchScriptTensor(f32[3072])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_weight: `TorchScriptTensor(f32[1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_bias: `TorchScriptTensor(f32[1024])`,\n...\n)\n## Return values\n", + "text":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___16___mlp_fc2_bias[name=p_getattr_l__self___trunk_blocks___16___mlp_fc2_bias]. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"FxOnnxInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":414 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0008", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___17___norm1_weight[name=p_getattr_l__self___trunk_blocks___17___norm1_weight]. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature FxOnnxInterpreter.run_node\n- self: \n- node: fx.Node(p_getattr_l__self___trunk_blocks___17___norm1_weight)[placeholder]:Tensor(f32[1024])\n- fx_graph_module: torch.fx.GraphModule(timm_models_vision_transformer_VisionTransformer)\n- onnxfunction_dispatcher: \n- op_level_debug: False\n- onnxscript_graph: \n- onnxscript_tracer: \n- fx_name_to_onnxscript_value: Dict[length=208](\nx: `TorchScriptTensor(f32[4, 3, 512, 512])`,\np_trunk_patch_embed_proj_weight: `TorchScriptTensor(f32[1024, 3, 16, 16])`,\np_trunk_patch_embed_proj_bias: `TorchScriptTensor(f32[1024])`,\np_trunk_pos_embed: `TorchScriptTensor(f32[1, 1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_weight: `TorchScriptTensor(f32[3072, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_bias: `TorchScriptTensor(f32[3072])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_weight: `TorchScriptTensor(f32[1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_bias: `TorchScriptTensor(f32[1024])`,\n...\n)\n## Return values\n", + "text":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___17___norm1_weight[name=p_getattr_l__self___trunk_blocks___17___norm1_weight]. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"FxOnnxInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":414 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0008", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___17___norm1_bias[name=p_getattr_l__self___trunk_blocks___17___norm1_bias]. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature FxOnnxInterpreter.run_node\n- self: \n- node: fx.Node(p_getattr_l__self___trunk_blocks___17___norm1_bias)[placeholder]:Tensor(f32[1024])\n- fx_graph_module: torch.fx.GraphModule(timm_models_vision_transformer_VisionTransformer)\n- onnxfunction_dispatcher: \n- op_level_debug: False\n- onnxscript_graph: \n- onnxscript_tracer: \n- fx_name_to_onnxscript_value: Dict[length=209](\nx: `TorchScriptTensor(f32[4, 3, 512, 512])`,\np_trunk_patch_embed_proj_weight: `TorchScriptTensor(f32[1024, 3, 16, 16])`,\np_trunk_patch_embed_proj_bias: `TorchScriptTensor(f32[1024])`,\np_trunk_pos_embed: `TorchScriptTensor(f32[1, 1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_weight: `TorchScriptTensor(f32[3072, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_bias: `TorchScriptTensor(f32[3072])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_weight: `TorchScriptTensor(f32[1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_bias: `TorchScriptTensor(f32[1024])`,\n...\n)\n## Return values\n", + "text":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___17___norm1_bias[name=p_getattr_l__self___trunk_blocks___17___norm1_bias]. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"FxOnnxInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":414 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0008", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___17___attn_qkv_weight[name=p_getattr_l__self___trunk_blocks___17___attn_qkv_weight]. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature FxOnnxInterpreter.run_node\n- self: \n- node: fx.Node(p_getattr_l__self___trunk_blocks___17___attn_qkv_weight)[placeholder]:Tensor(f32[3072, 1024])\n- fx_graph_module: torch.fx.GraphModule(timm_models_vision_transformer_VisionTransformer)\n- onnxfunction_dispatcher: \n- op_level_debug: False\n- onnxscript_graph: \n- onnxscript_tracer: \n- fx_name_to_onnxscript_value: Dict[length=210](\nx: `TorchScriptTensor(f32[4, 3, 512, 512])`,\np_trunk_patch_embed_proj_weight: `TorchScriptTensor(f32[1024, 3, 16, 16])`,\np_trunk_patch_embed_proj_bias: `TorchScriptTensor(f32[1024])`,\np_trunk_pos_embed: `TorchScriptTensor(f32[1, 1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_weight: `TorchScriptTensor(f32[3072, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_bias: `TorchScriptTensor(f32[3072])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_weight: `TorchScriptTensor(f32[1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_bias: `TorchScriptTensor(f32[1024])`,\n...\n)\n## Return values\n", + "text":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___17___attn_qkv_weight[name=p_getattr_l__self___trunk_blocks___17___attn_qkv_weight]. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"FxOnnxInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":414 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0008", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___17___attn_qkv_bias[name=p_getattr_l__self___trunk_blocks___17___attn_qkv_bias]. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature FxOnnxInterpreter.run_node\n- self: \n- node: fx.Node(p_getattr_l__self___trunk_blocks___17___attn_qkv_bias)[placeholder]:Tensor(f32[3072])\n- fx_graph_module: torch.fx.GraphModule(timm_models_vision_transformer_VisionTransformer)\n- onnxfunction_dispatcher: \n- op_level_debug: False\n- onnxscript_graph: \n- onnxscript_tracer: \n- fx_name_to_onnxscript_value: Dict[length=211](\nx: `TorchScriptTensor(f32[4, 3, 512, 512])`,\np_trunk_patch_embed_proj_weight: `TorchScriptTensor(f32[1024, 3, 16, 16])`,\np_trunk_patch_embed_proj_bias: `TorchScriptTensor(f32[1024])`,\np_trunk_pos_embed: `TorchScriptTensor(f32[1, 1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_weight: `TorchScriptTensor(f32[3072, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_bias: `TorchScriptTensor(f32[3072])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_weight: `TorchScriptTensor(f32[1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_bias: `TorchScriptTensor(f32[1024])`,\n...\n)\n## Return values\n", + "text":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___17___attn_qkv_bias[name=p_getattr_l__self___trunk_blocks___17___attn_qkv_bias]. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"FxOnnxInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":414 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0008", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___17___attn_proj_weight[name=p_getattr_l__self___trunk_blocks___17___attn_proj_weight]. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature FxOnnxInterpreter.run_node\n- self: \n- node: fx.Node(p_getattr_l__self___trunk_blocks___17___attn_proj_weight)[placeholder]:Tensor(f32[1024, 1024])\n- fx_graph_module: torch.fx.GraphModule(timm_models_vision_transformer_VisionTransformer)\n- onnxfunction_dispatcher: \n- op_level_debug: False\n- onnxscript_graph: \n- onnxscript_tracer: \n- fx_name_to_onnxscript_value: Dict[length=212](\nx: `TorchScriptTensor(f32[4, 3, 512, 512])`,\np_trunk_patch_embed_proj_weight: `TorchScriptTensor(f32[1024, 3, 16, 16])`,\np_trunk_patch_embed_proj_bias: `TorchScriptTensor(f32[1024])`,\np_trunk_pos_embed: `TorchScriptTensor(f32[1, 1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_weight: `TorchScriptTensor(f32[3072, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_bias: `TorchScriptTensor(f32[3072])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_weight: `TorchScriptTensor(f32[1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_bias: `TorchScriptTensor(f32[1024])`,\n...\n)\n## Return values\n", + "text":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___17___attn_proj_weight[name=p_getattr_l__self___trunk_blocks___17___attn_proj_weight]. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"FxOnnxInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":414 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0008", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___17___attn_proj_bias[name=p_getattr_l__self___trunk_blocks___17___attn_proj_bias]. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature FxOnnxInterpreter.run_node\n- self: \n- node: fx.Node(p_getattr_l__self___trunk_blocks___17___attn_proj_bias)[placeholder]:Tensor(f32[1024])\n- fx_graph_module: torch.fx.GraphModule(timm_models_vision_transformer_VisionTransformer)\n- onnxfunction_dispatcher: \n- op_level_debug: False\n- onnxscript_graph: \n- onnxscript_tracer: \n- fx_name_to_onnxscript_value: Dict[length=213](\nx: `TorchScriptTensor(f32[4, 3, 512, 512])`,\np_trunk_patch_embed_proj_weight: `TorchScriptTensor(f32[1024, 3, 16, 16])`,\np_trunk_patch_embed_proj_bias: `TorchScriptTensor(f32[1024])`,\np_trunk_pos_embed: `TorchScriptTensor(f32[1, 1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_weight: `TorchScriptTensor(f32[3072, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_bias: `TorchScriptTensor(f32[3072])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_weight: `TorchScriptTensor(f32[1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_bias: `TorchScriptTensor(f32[1024])`,\n...\n)\n## Return values\n", + "text":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___17___attn_proj_bias[name=p_getattr_l__self___trunk_blocks___17___attn_proj_bias]. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"FxOnnxInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":414 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0008", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___17___norm2_weight[name=p_getattr_l__self___trunk_blocks___17___norm2_weight]. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature FxOnnxInterpreter.run_node\n- self: \n- node: fx.Node(p_getattr_l__self___trunk_blocks___17___norm2_weight)[placeholder]:Tensor(f32[1024])\n- fx_graph_module: torch.fx.GraphModule(timm_models_vision_transformer_VisionTransformer)\n- onnxfunction_dispatcher: \n- op_level_debug: False\n- onnxscript_graph: \n- onnxscript_tracer: \n- fx_name_to_onnxscript_value: Dict[length=214](\nx: `TorchScriptTensor(f32[4, 3, 512, 512])`,\np_trunk_patch_embed_proj_weight: `TorchScriptTensor(f32[1024, 3, 16, 16])`,\np_trunk_patch_embed_proj_bias: `TorchScriptTensor(f32[1024])`,\np_trunk_pos_embed: `TorchScriptTensor(f32[1, 1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_weight: `TorchScriptTensor(f32[3072, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_bias: `TorchScriptTensor(f32[3072])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_weight: `TorchScriptTensor(f32[1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_bias: `TorchScriptTensor(f32[1024])`,\n...\n)\n## Return values\n", + "text":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___17___norm2_weight[name=p_getattr_l__self___trunk_blocks___17___norm2_weight]. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"FxOnnxInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":414 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0008", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___17___norm2_bias[name=p_getattr_l__self___trunk_blocks___17___norm2_bias]. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature FxOnnxInterpreter.run_node\n- self: \n- node: fx.Node(p_getattr_l__self___trunk_blocks___17___norm2_bias)[placeholder]:Tensor(f32[1024])\n- fx_graph_module: torch.fx.GraphModule(timm_models_vision_transformer_VisionTransformer)\n- onnxfunction_dispatcher: \n- op_level_debug: False\n- onnxscript_graph: \n- onnxscript_tracer: \n- fx_name_to_onnxscript_value: Dict[length=215](\nx: `TorchScriptTensor(f32[4, 3, 512, 512])`,\np_trunk_patch_embed_proj_weight: `TorchScriptTensor(f32[1024, 3, 16, 16])`,\np_trunk_patch_embed_proj_bias: `TorchScriptTensor(f32[1024])`,\np_trunk_pos_embed: `TorchScriptTensor(f32[1, 1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_weight: `TorchScriptTensor(f32[3072, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_bias: `TorchScriptTensor(f32[3072])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_weight: `TorchScriptTensor(f32[1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_bias: `TorchScriptTensor(f32[1024])`,\n...\n)\n## Return values\n", + "text":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___17___norm2_bias[name=p_getattr_l__self___trunk_blocks___17___norm2_bias]. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"FxOnnxInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":414 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0008", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___17___mlp_fc1_weight[name=p_getattr_l__self___trunk_blocks___17___mlp_fc1_weight]. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature FxOnnxInterpreter.run_node\n- self: \n- node: fx.Node(p_getattr_l__self___trunk_blocks___17___mlp_fc1_weight)[placeholder]:Tensor(f32[4096, 1024])\n- fx_graph_module: torch.fx.GraphModule(timm_models_vision_transformer_VisionTransformer)\n- onnxfunction_dispatcher: \n- op_level_debug: False\n- onnxscript_graph: \n- onnxscript_tracer: \n- fx_name_to_onnxscript_value: Dict[length=216](\nx: `TorchScriptTensor(f32[4, 3, 512, 512])`,\np_trunk_patch_embed_proj_weight: `TorchScriptTensor(f32[1024, 3, 16, 16])`,\np_trunk_patch_embed_proj_bias: `TorchScriptTensor(f32[1024])`,\np_trunk_pos_embed: `TorchScriptTensor(f32[1, 1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_weight: `TorchScriptTensor(f32[3072, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_bias: `TorchScriptTensor(f32[3072])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_weight: `TorchScriptTensor(f32[1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_bias: `TorchScriptTensor(f32[1024])`,\n...\n)\n## Return values\n", + "text":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___17___mlp_fc1_weight[name=p_getattr_l__self___trunk_blocks___17___mlp_fc1_weight]. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"FxOnnxInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":414 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0008", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___17___mlp_fc1_bias[name=p_getattr_l__self___trunk_blocks___17___mlp_fc1_bias]. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature FxOnnxInterpreter.run_node\n- self: \n- node: fx.Node(p_getattr_l__self___trunk_blocks___17___mlp_fc1_bias)[placeholder]:Tensor(f32[4096])\n- fx_graph_module: torch.fx.GraphModule(timm_models_vision_transformer_VisionTransformer)\n- onnxfunction_dispatcher: \n- op_level_debug: False\n- onnxscript_graph: \n- onnxscript_tracer: \n- fx_name_to_onnxscript_value: Dict[length=217](\nx: `TorchScriptTensor(f32[4, 3, 512, 512])`,\np_trunk_patch_embed_proj_weight: `TorchScriptTensor(f32[1024, 3, 16, 16])`,\np_trunk_patch_embed_proj_bias: `TorchScriptTensor(f32[1024])`,\np_trunk_pos_embed: `TorchScriptTensor(f32[1, 1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_weight: `TorchScriptTensor(f32[3072, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_bias: `TorchScriptTensor(f32[3072])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_weight: `TorchScriptTensor(f32[1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_bias: `TorchScriptTensor(f32[1024])`,\n...\n)\n## Return values\n", + "text":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___17___mlp_fc1_bias[name=p_getattr_l__self___trunk_blocks___17___mlp_fc1_bias]. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"FxOnnxInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":414 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0008", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___17___mlp_fc2_weight[name=p_getattr_l__self___trunk_blocks___17___mlp_fc2_weight]. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature FxOnnxInterpreter.run_node\n- self: \n- node: fx.Node(p_getattr_l__self___trunk_blocks___17___mlp_fc2_weight)[placeholder]:Tensor(f32[1024, 4096])\n- fx_graph_module: torch.fx.GraphModule(timm_models_vision_transformer_VisionTransformer)\n- onnxfunction_dispatcher: \n- op_level_debug: False\n- onnxscript_graph: \n- onnxscript_tracer: \n- fx_name_to_onnxscript_value: Dict[length=218](\nx: `TorchScriptTensor(f32[4, 3, 512, 512])`,\np_trunk_patch_embed_proj_weight: `TorchScriptTensor(f32[1024, 3, 16, 16])`,\np_trunk_patch_embed_proj_bias: `TorchScriptTensor(f32[1024])`,\np_trunk_pos_embed: `TorchScriptTensor(f32[1, 1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_weight: `TorchScriptTensor(f32[3072, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_bias: `TorchScriptTensor(f32[3072])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_weight: `TorchScriptTensor(f32[1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_bias: `TorchScriptTensor(f32[1024])`,\n...\n)\n## Return values\n", + "text":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___17___mlp_fc2_weight[name=p_getattr_l__self___trunk_blocks___17___mlp_fc2_weight]. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"FxOnnxInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":414 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0008", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___17___mlp_fc2_bias[name=p_getattr_l__self___trunk_blocks___17___mlp_fc2_bias]. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature FxOnnxInterpreter.run_node\n- self: \n- node: fx.Node(p_getattr_l__self___trunk_blocks___17___mlp_fc2_bias)[placeholder]:Tensor(f32[1024])\n- fx_graph_module: torch.fx.GraphModule(timm_models_vision_transformer_VisionTransformer)\n- onnxfunction_dispatcher: \n- op_level_debug: False\n- onnxscript_graph: \n- onnxscript_tracer: \n- fx_name_to_onnxscript_value: Dict[length=219](\nx: `TorchScriptTensor(f32[4, 3, 512, 512])`,\np_trunk_patch_embed_proj_weight: `TorchScriptTensor(f32[1024, 3, 16, 16])`,\np_trunk_patch_embed_proj_bias: `TorchScriptTensor(f32[1024])`,\np_trunk_pos_embed: `TorchScriptTensor(f32[1, 1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_weight: `TorchScriptTensor(f32[3072, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_bias: `TorchScriptTensor(f32[3072])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_weight: `TorchScriptTensor(f32[1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_bias: `TorchScriptTensor(f32[1024])`,\n...\n)\n## Return values\n", + "text":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___17___mlp_fc2_bias[name=p_getattr_l__self___trunk_blocks___17___mlp_fc2_bias]. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"FxOnnxInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":414 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0008", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___18___norm1_weight[name=p_getattr_l__self___trunk_blocks___18___norm1_weight]. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature FxOnnxInterpreter.run_node\n- self: \n- node: fx.Node(p_getattr_l__self___trunk_blocks___18___norm1_weight)[placeholder]:Tensor(f32[1024])\n- fx_graph_module: torch.fx.GraphModule(timm_models_vision_transformer_VisionTransformer)\n- onnxfunction_dispatcher: \n- op_level_debug: False\n- onnxscript_graph: \n- onnxscript_tracer: \n- fx_name_to_onnxscript_value: Dict[length=220](\nx: `TorchScriptTensor(f32[4, 3, 512, 512])`,\np_trunk_patch_embed_proj_weight: `TorchScriptTensor(f32[1024, 3, 16, 16])`,\np_trunk_patch_embed_proj_bias: `TorchScriptTensor(f32[1024])`,\np_trunk_pos_embed: `TorchScriptTensor(f32[1, 1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_weight: `TorchScriptTensor(f32[3072, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_bias: `TorchScriptTensor(f32[3072])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_weight: `TorchScriptTensor(f32[1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_bias: `TorchScriptTensor(f32[1024])`,\n...\n)\n## Return values\n", + "text":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___18___norm1_weight[name=p_getattr_l__self___trunk_blocks___18___norm1_weight]. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"FxOnnxInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":414 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0008", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___18___norm1_bias[name=p_getattr_l__self___trunk_blocks___18___norm1_bias]. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature FxOnnxInterpreter.run_node\n- self: \n- node: fx.Node(p_getattr_l__self___trunk_blocks___18___norm1_bias)[placeholder]:Tensor(f32[1024])\n- fx_graph_module: torch.fx.GraphModule(timm_models_vision_transformer_VisionTransformer)\n- onnxfunction_dispatcher: \n- op_level_debug: False\n- onnxscript_graph: \n- onnxscript_tracer: \n- fx_name_to_onnxscript_value: Dict[length=221](\nx: `TorchScriptTensor(f32[4, 3, 512, 512])`,\np_trunk_patch_embed_proj_weight: `TorchScriptTensor(f32[1024, 3, 16, 16])`,\np_trunk_patch_embed_proj_bias: `TorchScriptTensor(f32[1024])`,\np_trunk_pos_embed: `TorchScriptTensor(f32[1, 1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_weight: `TorchScriptTensor(f32[3072, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_bias: `TorchScriptTensor(f32[3072])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_weight: `TorchScriptTensor(f32[1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_bias: `TorchScriptTensor(f32[1024])`,\n...\n)\n## Return values\n", + "text":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___18___norm1_bias[name=p_getattr_l__self___trunk_blocks___18___norm1_bias]. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"FxOnnxInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":414 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0008", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___18___attn_qkv_weight[name=p_getattr_l__self___trunk_blocks___18___attn_qkv_weight]. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature FxOnnxInterpreter.run_node\n- self: \n- node: fx.Node(p_getattr_l__self___trunk_blocks___18___attn_qkv_weight)[placeholder]:Tensor(f32[3072, 1024])\n- fx_graph_module: torch.fx.GraphModule(timm_models_vision_transformer_VisionTransformer)\n- onnxfunction_dispatcher: \n- op_level_debug: False\n- onnxscript_graph: \n- onnxscript_tracer: \n- fx_name_to_onnxscript_value: Dict[length=222](\nx: `TorchScriptTensor(f32[4, 3, 512, 512])`,\np_trunk_patch_embed_proj_weight: `TorchScriptTensor(f32[1024, 3, 16, 16])`,\np_trunk_patch_embed_proj_bias: `TorchScriptTensor(f32[1024])`,\np_trunk_pos_embed: `TorchScriptTensor(f32[1, 1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_weight: `TorchScriptTensor(f32[3072, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_bias: `TorchScriptTensor(f32[3072])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_weight: `TorchScriptTensor(f32[1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_bias: `TorchScriptTensor(f32[1024])`,\n...\n)\n## Return values\n", + "text":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___18___attn_qkv_weight[name=p_getattr_l__self___trunk_blocks___18___attn_qkv_weight]. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"FxOnnxInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":414 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0008", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___18___attn_qkv_bias[name=p_getattr_l__self___trunk_blocks___18___attn_qkv_bias]. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature FxOnnxInterpreter.run_node\n- self: \n- node: fx.Node(p_getattr_l__self___trunk_blocks___18___attn_qkv_bias)[placeholder]:Tensor(f32[3072])\n- fx_graph_module: torch.fx.GraphModule(timm_models_vision_transformer_VisionTransformer)\n- onnxfunction_dispatcher: \n- op_level_debug: False\n- onnxscript_graph: \n- onnxscript_tracer: \n- fx_name_to_onnxscript_value: Dict[length=223](\nx: `TorchScriptTensor(f32[4, 3, 512, 512])`,\np_trunk_patch_embed_proj_weight: `TorchScriptTensor(f32[1024, 3, 16, 16])`,\np_trunk_patch_embed_proj_bias: `TorchScriptTensor(f32[1024])`,\np_trunk_pos_embed: `TorchScriptTensor(f32[1, 1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_weight: `TorchScriptTensor(f32[3072, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_bias: `TorchScriptTensor(f32[3072])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_weight: `TorchScriptTensor(f32[1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_bias: `TorchScriptTensor(f32[1024])`,\n...\n)\n## Return values\n", + "text":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___18___attn_qkv_bias[name=p_getattr_l__self___trunk_blocks___18___attn_qkv_bias]. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"FxOnnxInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":414 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0008", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___18___attn_proj_weight[name=p_getattr_l__self___trunk_blocks___18___attn_proj_weight]. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature FxOnnxInterpreter.run_node\n- self: \n- node: fx.Node(p_getattr_l__self___trunk_blocks___18___attn_proj_weight)[placeholder]:Tensor(f32[1024, 1024])\n- fx_graph_module: torch.fx.GraphModule(timm_models_vision_transformer_VisionTransformer)\n- onnxfunction_dispatcher: \n- op_level_debug: False\n- onnxscript_graph: \n- onnxscript_tracer: \n- fx_name_to_onnxscript_value: Dict[length=224](\nx: `TorchScriptTensor(f32[4, 3, 512, 512])`,\np_trunk_patch_embed_proj_weight: `TorchScriptTensor(f32[1024, 3, 16, 16])`,\np_trunk_patch_embed_proj_bias: `TorchScriptTensor(f32[1024])`,\np_trunk_pos_embed: `TorchScriptTensor(f32[1, 1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_weight: `TorchScriptTensor(f32[3072, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_bias: `TorchScriptTensor(f32[3072])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_weight: `TorchScriptTensor(f32[1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_bias: `TorchScriptTensor(f32[1024])`,\n...\n)\n## Return values\n", + "text":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___18___attn_proj_weight[name=p_getattr_l__self___trunk_blocks___18___attn_proj_weight]. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"FxOnnxInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":414 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0008", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___18___attn_proj_bias[name=p_getattr_l__self___trunk_blocks___18___attn_proj_bias]. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature FxOnnxInterpreter.run_node\n- self: \n- node: fx.Node(p_getattr_l__self___trunk_blocks___18___attn_proj_bias)[placeholder]:Tensor(f32[1024])\n- fx_graph_module: torch.fx.GraphModule(timm_models_vision_transformer_VisionTransformer)\n- onnxfunction_dispatcher: \n- op_level_debug: False\n- onnxscript_graph: \n- onnxscript_tracer: \n- fx_name_to_onnxscript_value: Dict[length=225](\nx: `TorchScriptTensor(f32[4, 3, 512, 512])`,\np_trunk_patch_embed_proj_weight: `TorchScriptTensor(f32[1024, 3, 16, 16])`,\np_trunk_patch_embed_proj_bias: `TorchScriptTensor(f32[1024])`,\np_trunk_pos_embed: `TorchScriptTensor(f32[1, 1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_weight: `TorchScriptTensor(f32[3072, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_bias: `TorchScriptTensor(f32[3072])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_weight: `TorchScriptTensor(f32[1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_bias: `TorchScriptTensor(f32[1024])`,\n...\n)\n## Return values\n", + "text":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___18___attn_proj_bias[name=p_getattr_l__self___trunk_blocks___18___attn_proj_bias]. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"FxOnnxInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":414 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0008", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___18___norm2_weight[name=p_getattr_l__self___trunk_blocks___18___norm2_weight]. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature FxOnnxInterpreter.run_node\n- self: \n- node: fx.Node(p_getattr_l__self___trunk_blocks___18___norm2_weight)[placeholder]:Tensor(f32[1024])\n- fx_graph_module: torch.fx.GraphModule(timm_models_vision_transformer_VisionTransformer)\n- onnxfunction_dispatcher: \n- op_level_debug: False\n- onnxscript_graph: \n- onnxscript_tracer: \n- fx_name_to_onnxscript_value: Dict[length=226](\nx: `TorchScriptTensor(f32[4, 3, 512, 512])`,\np_trunk_patch_embed_proj_weight: `TorchScriptTensor(f32[1024, 3, 16, 16])`,\np_trunk_patch_embed_proj_bias: `TorchScriptTensor(f32[1024])`,\np_trunk_pos_embed: `TorchScriptTensor(f32[1, 1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_weight: `TorchScriptTensor(f32[3072, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_bias: `TorchScriptTensor(f32[3072])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_weight: `TorchScriptTensor(f32[1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_bias: `TorchScriptTensor(f32[1024])`,\n...\n)\n## Return values\n", + "text":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___18___norm2_weight[name=p_getattr_l__self___trunk_blocks___18___norm2_weight]. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"FxOnnxInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":414 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0008", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___18___norm2_bias[name=p_getattr_l__self___trunk_blocks___18___norm2_bias]. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature FxOnnxInterpreter.run_node\n- self: \n- node: fx.Node(p_getattr_l__self___trunk_blocks___18___norm2_bias)[placeholder]:Tensor(f32[1024])\n- fx_graph_module: torch.fx.GraphModule(timm_models_vision_transformer_VisionTransformer)\n- onnxfunction_dispatcher: \n- op_level_debug: False\n- onnxscript_graph: \n- onnxscript_tracer: \n- fx_name_to_onnxscript_value: Dict[length=227](\nx: `TorchScriptTensor(f32[4, 3, 512, 512])`,\np_trunk_patch_embed_proj_weight: `TorchScriptTensor(f32[1024, 3, 16, 16])`,\np_trunk_patch_embed_proj_bias: `TorchScriptTensor(f32[1024])`,\np_trunk_pos_embed: `TorchScriptTensor(f32[1, 1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_weight: `TorchScriptTensor(f32[3072, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_bias: `TorchScriptTensor(f32[3072])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_weight: `TorchScriptTensor(f32[1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_bias: `TorchScriptTensor(f32[1024])`,\n...\n)\n## Return values\n", + "text":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___18___norm2_bias[name=p_getattr_l__self___trunk_blocks___18___norm2_bias]. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"FxOnnxInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":414 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0008", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___18___mlp_fc1_weight[name=p_getattr_l__self___trunk_blocks___18___mlp_fc1_weight]. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature FxOnnxInterpreter.run_node\n- self: \n- node: fx.Node(p_getattr_l__self___trunk_blocks___18___mlp_fc1_weight)[placeholder]:Tensor(f32[4096, 1024])\n- fx_graph_module: torch.fx.GraphModule(timm_models_vision_transformer_VisionTransformer)\n- onnxfunction_dispatcher: \n- op_level_debug: False\n- onnxscript_graph: \n- onnxscript_tracer: \n- fx_name_to_onnxscript_value: Dict[length=228](\nx: `TorchScriptTensor(f32[4, 3, 512, 512])`,\np_trunk_patch_embed_proj_weight: `TorchScriptTensor(f32[1024, 3, 16, 16])`,\np_trunk_patch_embed_proj_bias: `TorchScriptTensor(f32[1024])`,\np_trunk_pos_embed: `TorchScriptTensor(f32[1, 1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_weight: `TorchScriptTensor(f32[3072, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_bias: `TorchScriptTensor(f32[3072])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_weight: `TorchScriptTensor(f32[1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_bias: `TorchScriptTensor(f32[1024])`,\n...\n)\n## Return values\n", + "text":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___18___mlp_fc1_weight[name=p_getattr_l__self___trunk_blocks___18___mlp_fc1_weight]. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"FxOnnxInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":414 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0008", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___18___mlp_fc1_bias[name=p_getattr_l__self___trunk_blocks___18___mlp_fc1_bias]. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature FxOnnxInterpreter.run_node\n- self: \n- node: fx.Node(p_getattr_l__self___trunk_blocks___18___mlp_fc1_bias)[placeholder]:Tensor(f32[4096])\n- fx_graph_module: torch.fx.GraphModule(timm_models_vision_transformer_VisionTransformer)\n- onnxfunction_dispatcher: \n- op_level_debug: False\n- onnxscript_graph: \n- onnxscript_tracer: \n- fx_name_to_onnxscript_value: Dict[length=229](\nx: `TorchScriptTensor(f32[4, 3, 512, 512])`,\np_trunk_patch_embed_proj_weight: `TorchScriptTensor(f32[1024, 3, 16, 16])`,\np_trunk_patch_embed_proj_bias: `TorchScriptTensor(f32[1024])`,\np_trunk_pos_embed: `TorchScriptTensor(f32[1, 1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_weight: `TorchScriptTensor(f32[3072, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_bias: `TorchScriptTensor(f32[3072])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_weight: `TorchScriptTensor(f32[1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_bias: `TorchScriptTensor(f32[1024])`,\n...\n)\n## Return values\n", + "text":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___18___mlp_fc1_bias[name=p_getattr_l__self___trunk_blocks___18___mlp_fc1_bias]. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"FxOnnxInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":414 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0008", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___18___mlp_fc2_weight[name=p_getattr_l__self___trunk_blocks___18___mlp_fc2_weight]. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature FxOnnxInterpreter.run_node\n- self: \n- node: fx.Node(p_getattr_l__self___trunk_blocks___18___mlp_fc2_weight)[placeholder]:Tensor(f32[1024, 4096])\n- fx_graph_module: torch.fx.GraphModule(timm_models_vision_transformer_VisionTransformer)\n- onnxfunction_dispatcher: \n- op_level_debug: False\n- onnxscript_graph: \n- onnxscript_tracer: \n- fx_name_to_onnxscript_value: Dict[length=230](\nx: `TorchScriptTensor(f32[4, 3, 512, 512])`,\np_trunk_patch_embed_proj_weight: `TorchScriptTensor(f32[1024, 3, 16, 16])`,\np_trunk_patch_embed_proj_bias: `TorchScriptTensor(f32[1024])`,\np_trunk_pos_embed: `TorchScriptTensor(f32[1, 1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_weight: `TorchScriptTensor(f32[3072, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_bias: `TorchScriptTensor(f32[3072])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_weight: `TorchScriptTensor(f32[1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_bias: `TorchScriptTensor(f32[1024])`,\n...\n)\n## Return values\n", + "text":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___18___mlp_fc2_weight[name=p_getattr_l__self___trunk_blocks___18___mlp_fc2_weight]. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"FxOnnxInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":414 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0008", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___18___mlp_fc2_bias[name=p_getattr_l__self___trunk_blocks___18___mlp_fc2_bias]. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature FxOnnxInterpreter.run_node\n- self: \n- node: fx.Node(p_getattr_l__self___trunk_blocks___18___mlp_fc2_bias)[placeholder]:Tensor(f32[1024])\n- fx_graph_module: torch.fx.GraphModule(timm_models_vision_transformer_VisionTransformer)\n- onnxfunction_dispatcher: \n- op_level_debug: False\n- onnxscript_graph: \n- onnxscript_tracer: \n- fx_name_to_onnxscript_value: Dict[length=231](\nx: `TorchScriptTensor(f32[4, 3, 512, 512])`,\np_trunk_patch_embed_proj_weight: `TorchScriptTensor(f32[1024, 3, 16, 16])`,\np_trunk_patch_embed_proj_bias: `TorchScriptTensor(f32[1024])`,\np_trunk_pos_embed: `TorchScriptTensor(f32[1, 1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_weight: `TorchScriptTensor(f32[3072, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_bias: `TorchScriptTensor(f32[3072])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_weight: `TorchScriptTensor(f32[1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_bias: `TorchScriptTensor(f32[1024])`,\n...\n)\n## Return values\n", + "text":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___18___mlp_fc2_bias[name=p_getattr_l__self___trunk_blocks___18___mlp_fc2_bias]. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"FxOnnxInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":414 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0008", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___19___norm1_weight[name=p_getattr_l__self___trunk_blocks___19___norm1_weight]. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature FxOnnxInterpreter.run_node\n- self: \n- node: fx.Node(p_getattr_l__self___trunk_blocks___19___norm1_weight)[placeholder]:Tensor(f32[1024])\n- fx_graph_module: torch.fx.GraphModule(timm_models_vision_transformer_VisionTransformer)\n- onnxfunction_dispatcher: \n- op_level_debug: False\n- onnxscript_graph: \n- onnxscript_tracer: \n- fx_name_to_onnxscript_value: Dict[length=232](\nx: `TorchScriptTensor(f32[4, 3, 512, 512])`,\np_trunk_patch_embed_proj_weight: `TorchScriptTensor(f32[1024, 3, 16, 16])`,\np_trunk_patch_embed_proj_bias: `TorchScriptTensor(f32[1024])`,\np_trunk_pos_embed: `TorchScriptTensor(f32[1, 1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_weight: `TorchScriptTensor(f32[3072, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_bias: `TorchScriptTensor(f32[3072])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_weight: `TorchScriptTensor(f32[1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_bias: `TorchScriptTensor(f32[1024])`,\n...\n)\n## Return values\n", + "text":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___19___norm1_weight[name=p_getattr_l__self___trunk_blocks___19___norm1_weight]. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"FxOnnxInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":414 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0008", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___19___norm1_bias[name=p_getattr_l__self___trunk_blocks___19___norm1_bias]. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature FxOnnxInterpreter.run_node\n- self: \n- node: fx.Node(p_getattr_l__self___trunk_blocks___19___norm1_bias)[placeholder]:Tensor(f32[1024])\n- fx_graph_module: torch.fx.GraphModule(timm_models_vision_transformer_VisionTransformer)\n- onnxfunction_dispatcher: \n- op_level_debug: False\n- onnxscript_graph: \n- onnxscript_tracer: \n- fx_name_to_onnxscript_value: Dict[length=233](\nx: `TorchScriptTensor(f32[4, 3, 512, 512])`,\np_trunk_patch_embed_proj_weight: `TorchScriptTensor(f32[1024, 3, 16, 16])`,\np_trunk_patch_embed_proj_bias: `TorchScriptTensor(f32[1024])`,\np_trunk_pos_embed: `TorchScriptTensor(f32[1, 1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_weight: `TorchScriptTensor(f32[3072, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_bias: `TorchScriptTensor(f32[3072])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_weight: `TorchScriptTensor(f32[1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_bias: `TorchScriptTensor(f32[1024])`,\n...\n)\n## Return values\n", + "text":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___19___norm1_bias[name=p_getattr_l__self___trunk_blocks___19___norm1_bias]. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"FxOnnxInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":414 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0008", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___19___attn_qkv_weight[name=p_getattr_l__self___trunk_blocks___19___attn_qkv_weight]. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature FxOnnxInterpreter.run_node\n- self: \n- node: fx.Node(p_getattr_l__self___trunk_blocks___19___attn_qkv_weight)[placeholder]:Tensor(f32[3072, 1024])\n- fx_graph_module: torch.fx.GraphModule(timm_models_vision_transformer_VisionTransformer)\n- onnxfunction_dispatcher: \n- op_level_debug: False\n- onnxscript_graph: \n- onnxscript_tracer: \n- fx_name_to_onnxscript_value: Dict[length=234](\nx: `TorchScriptTensor(f32[4, 3, 512, 512])`,\np_trunk_patch_embed_proj_weight: `TorchScriptTensor(f32[1024, 3, 16, 16])`,\np_trunk_patch_embed_proj_bias: `TorchScriptTensor(f32[1024])`,\np_trunk_pos_embed: `TorchScriptTensor(f32[1, 1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_weight: `TorchScriptTensor(f32[3072, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_bias: `TorchScriptTensor(f32[3072])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_weight: `TorchScriptTensor(f32[1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_bias: `TorchScriptTensor(f32[1024])`,\n...\n)\n## Return values\n", + "text":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___19___attn_qkv_weight[name=p_getattr_l__self___trunk_blocks___19___attn_qkv_weight]. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"FxOnnxInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":414 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0008", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___19___attn_qkv_bias[name=p_getattr_l__self___trunk_blocks___19___attn_qkv_bias]. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature FxOnnxInterpreter.run_node\n- self: \n- node: fx.Node(p_getattr_l__self___trunk_blocks___19___attn_qkv_bias)[placeholder]:Tensor(f32[3072])\n- fx_graph_module: torch.fx.GraphModule(timm_models_vision_transformer_VisionTransformer)\n- onnxfunction_dispatcher: \n- op_level_debug: False\n- onnxscript_graph: \n- onnxscript_tracer: \n- fx_name_to_onnxscript_value: Dict[length=235](\nx: `TorchScriptTensor(f32[4, 3, 512, 512])`,\np_trunk_patch_embed_proj_weight: `TorchScriptTensor(f32[1024, 3, 16, 16])`,\np_trunk_patch_embed_proj_bias: `TorchScriptTensor(f32[1024])`,\np_trunk_pos_embed: `TorchScriptTensor(f32[1, 1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_weight: `TorchScriptTensor(f32[3072, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_bias: `TorchScriptTensor(f32[3072])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_weight: `TorchScriptTensor(f32[1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_bias: `TorchScriptTensor(f32[1024])`,\n...\n)\n## Return values\n", + "text":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___19___attn_qkv_bias[name=p_getattr_l__self___trunk_blocks___19___attn_qkv_bias]. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"FxOnnxInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":414 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0008", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___19___attn_proj_weight[name=p_getattr_l__self___trunk_blocks___19___attn_proj_weight]. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature FxOnnxInterpreter.run_node\n- self: \n- node: fx.Node(p_getattr_l__self___trunk_blocks___19___attn_proj_weight)[placeholder]:Tensor(f32[1024, 1024])\n- fx_graph_module: torch.fx.GraphModule(timm_models_vision_transformer_VisionTransformer)\n- onnxfunction_dispatcher: \n- op_level_debug: False\n- onnxscript_graph: \n- onnxscript_tracer: \n- fx_name_to_onnxscript_value: Dict[length=236](\nx: `TorchScriptTensor(f32[4, 3, 512, 512])`,\np_trunk_patch_embed_proj_weight: `TorchScriptTensor(f32[1024, 3, 16, 16])`,\np_trunk_patch_embed_proj_bias: `TorchScriptTensor(f32[1024])`,\np_trunk_pos_embed: `TorchScriptTensor(f32[1, 1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_weight: `TorchScriptTensor(f32[3072, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_bias: `TorchScriptTensor(f32[3072])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_weight: `TorchScriptTensor(f32[1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_bias: `TorchScriptTensor(f32[1024])`,\n...\n)\n## Return values\n", + "text":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___19___attn_proj_weight[name=p_getattr_l__self___trunk_blocks___19___attn_proj_weight]. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"FxOnnxInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":414 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0008", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___19___attn_proj_bias[name=p_getattr_l__self___trunk_blocks___19___attn_proj_bias]. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature FxOnnxInterpreter.run_node\n- self: \n- node: fx.Node(p_getattr_l__self___trunk_blocks___19___attn_proj_bias)[placeholder]:Tensor(f32[1024])\n- fx_graph_module: torch.fx.GraphModule(timm_models_vision_transformer_VisionTransformer)\n- onnxfunction_dispatcher: \n- op_level_debug: False\n- onnxscript_graph: \n- onnxscript_tracer: \n- fx_name_to_onnxscript_value: Dict[length=237](\nx: `TorchScriptTensor(f32[4, 3, 512, 512])`,\np_trunk_patch_embed_proj_weight: `TorchScriptTensor(f32[1024, 3, 16, 16])`,\np_trunk_patch_embed_proj_bias: `TorchScriptTensor(f32[1024])`,\np_trunk_pos_embed: `TorchScriptTensor(f32[1, 1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_weight: `TorchScriptTensor(f32[3072, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_bias: `TorchScriptTensor(f32[3072])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_weight: `TorchScriptTensor(f32[1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_bias: `TorchScriptTensor(f32[1024])`,\n...\n)\n## Return values\n", + "text":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___19___attn_proj_bias[name=p_getattr_l__self___trunk_blocks___19___attn_proj_bias]. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"FxOnnxInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":414 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0008", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___19___norm2_weight[name=p_getattr_l__self___trunk_blocks___19___norm2_weight]. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature FxOnnxInterpreter.run_node\n- self: \n- node: fx.Node(p_getattr_l__self___trunk_blocks___19___norm2_weight)[placeholder]:Tensor(f32[1024])\n- fx_graph_module: torch.fx.GraphModule(timm_models_vision_transformer_VisionTransformer)\n- onnxfunction_dispatcher: \n- op_level_debug: False\n- onnxscript_graph: \n- onnxscript_tracer: \n- fx_name_to_onnxscript_value: Dict[length=238](\nx: `TorchScriptTensor(f32[4, 3, 512, 512])`,\np_trunk_patch_embed_proj_weight: `TorchScriptTensor(f32[1024, 3, 16, 16])`,\np_trunk_patch_embed_proj_bias: `TorchScriptTensor(f32[1024])`,\np_trunk_pos_embed: `TorchScriptTensor(f32[1, 1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_weight: `TorchScriptTensor(f32[3072, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_bias: `TorchScriptTensor(f32[3072])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_weight: `TorchScriptTensor(f32[1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_bias: `TorchScriptTensor(f32[1024])`,\n...\n)\n## Return values\n", + "text":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___19___norm2_weight[name=p_getattr_l__self___trunk_blocks___19___norm2_weight]. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"FxOnnxInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":414 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0008", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___19___norm2_bias[name=p_getattr_l__self___trunk_blocks___19___norm2_bias]. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature FxOnnxInterpreter.run_node\n- self: \n- node: fx.Node(p_getattr_l__self___trunk_blocks___19___norm2_bias)[placeholder]:Tensor(f32[1024])\n- fx_graph_module: torch.fx.GraphModule(timm_models_vision_transformer_VisionTransformer)\n- onnxfunction_dispatcher: \n- op_level_debug: False\n- onnxscript_graph: \n- onnxscript_tracer: \n- fx_name_to_onnxscript_value: Dict[length=239](\nx: `TorchScriptTensor(f32[4, 3, 512, 512])`,\np_trunk_patch_embed_proj_weight: `TorchScriptTensor(f32[1024, 3, 16, 16])`,\np_trunk_patch_embed_proj_bias: `TorchScriptTensor(f32[1024])`,\np_trunk_pos_embed: `TorchScriptTensor(f32[1, 1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_weight: `TorchScriptTensor(f32[3072, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_bias: `TorchScriptTensor(f32[3072])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_weight: `TorchScriptTensor(f32[1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_bias: `TorchScriptTensor(f32[1024])`,\n...\n)\n## Return values\n", + "text":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___19___norm2_bias[name=p_getattr_l__self___trunk_blocks___19___norm2_bias]. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"FxOnnxInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":414 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0008", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___19___mlp_fc1_weight[name=p_getattr_l__self___trunk_blocks___19___mlp_fc1_weight]. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature FxOnnxInterpreter.run_node\n- self: \n- node: fx.Node(p_getattr_l__self___trunk_blocks___19___mlp_fc1_weight)[placeholder]:Tensor(f32[4096, 1024])\n- fx_graph_module: torch.fx.GraphModule(timm_models_vision_transformer_VisionTransformer)\n- onnxfunction_dispatcher: \n- op_level_debug: False\n- onnxscript_graph: \n- onnxscript_tracer: \n- fx_name_to_onnxscript_value: Dict[length=240](\nx: `TorchScriptTensor(f32[4, 3, 512, 512])`,\np_trunk_patch_embed_proj_weight: `TorchScriptTensor(f32[1024, 3, 16, 16])`,\np_trunk_patch_embed_proj_bias: `TorchScriptTensor(f32[1024])`,\np_trunk_pos_embed: `TorchScriptTensor(f32[1, 1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_weight: `TorchScriptTensor(f32[3072, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_bias: `TorchScriptTensor(f32[3072])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_weight: `TorchScriptTensor(f32[1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_bias: `TorchScriptTensor(f32[1024])`,\n...\n)\n## Return values\n", + "text":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___19___mlp_fc1_weight[name=p_getattr_l__self___trunk_blocks___19___mlp_fc1_weight]. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"FxOnnxInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":414 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0008", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___19___mlp_fc1_bias[name=p_getattr_l__self___trunk_blocks___19___mlp_fc1_bias]. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature FxOnnxInterpreter.run_node\n- self: \n- node: fx.Node(p_getattr_l__self___trunk_blocks___19___mlp_fc1_bias)[placeholder]:Tensor(f32[4096])\n- fx_graph_module: torch.fx.GraphModule(timm_models_vision_transformer_VisionTransformer)\n- onnxfunction_dispatcher: \n- op_level_debug: False\n- onnxscript_graph: \n- onnxscript_tracer: \n- fx_name_to_onnxscript_value: Dict[length=241](\nx: `TorchScriptTensor(f32[4, 3, 512, 512])`,\np_trunk_patch_embed_proj_weight: `TorchScriptTensor(f32[1024, 3, 16, 16])`,\np_trunk_patch_embed_proj_bias: `TorchScriptTensor(f32[1024])`,\np_trunk_pos_embed: `TorchScriptTensor(f32[1, 1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_weight: `TorchScriptTensor(f32[3072, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_bias: `TorchScriptTensor(f32[3072])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_weight: `TorchScriptTensor(f32[1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_bias: `TorchScriptTensor(f32[1024])`,\n...\n)\n## Return values\n", + "text":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___19___mlp_fc1_bias[name=p_getattr_l__self___trunk_blocks___19___mlp_fc1_bias]. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"FxOnnxInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":414 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0008", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___19___mlp_fc2_weight[name=p_getattr_l__self___trunk_blocks___19___mlp_fc2_weight]. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature FxOnnxInterpreter.run_node\n- self: \n- node: fx.Node(p_getattr_l__self___trunk_blocks___19___mlp_fc2_weight)[placeholder]:Tensor(f32[1024, 4096])\n- fx_graph_module: torch.fx.GraphModule(timm_models_vision_transformer_VisionTransformer)\n- onnxfunction_dispatcher: \n- op_level_debug: False\n- onnxscript_graph: \n- onnxscript_tracer: \n- fx_name_to_onnxscript_value: Dict[length=242](\nx: `TorchScriptTensor(f32[4, 3, 512, 512])`,\np_trunk_patch_embed_proj_weight: `TorchScriptTensor(f32[1024, 3, 16, 16])`,\np_trunk_patch_embed_proj_bias: `TorchScriptTensor(f32[1024])`,\np_trunk_pos_embed: `TorchScriptTensor(f32[1, 1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_weight: `TorchScriptTensor(f32[3072, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_bias: `TorchScriptTensor(f32[3072])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_weight: `TorchScriptTensor(f32[1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_bias: `TorchScriptTensor(f32[1024])`,\n...\n)\n## Return values\n", + "text":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___19___mlp_fc2_weight[name=p_getattr_l__self___trunk_blocks___19___mlp_fc2_weight]. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"FxOnnxInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":414 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0008", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___19___mlp_fc2_bias[name=p_getattr_l__self___trunk_blocks___19___mlp_fc2_bias]. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature FxOnnxInterpreter.run_node\n- self: \n- node: fx.Node(p_getattr_l__self___trunk_blocks___19___mlp_fc2_bias)[placeholder]:Tensor(f32[1024])\n- fx_graph_module: torch.fx.GraphModule(timm_models_vision_transformer_VisionTransformer)\n- onnxfunction_dispatcher: \n- op_level_debug: False\n- onnxscript_graph: \n- onnxscript_tracer: \n- fx_name_to_onnxscript_value: Dict[length=243](\nx: `TorchScriptTensor(f32[4, 3, 512, 512])`,\np_trunk_patch_embed_proj_weight: `TorchScriptTensor(f32[1024, 3, 16, 16])`,\np_trunk_patch_embed_proj_bias: `TorchScriptTensor(f32[1024])`,\np_trunk_pos_embed: `TorchScriptTensor(f32[1, 1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_weight: `TorchScriptTensor(f32[3072, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_bias: `TorchScriptTensor(f32[3072])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_weight: `TorchScriptTensor(f32[1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_bias: `TorchScriptTensor(f32[1024])`,\n...\n)\n## Return values\n", + "text":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___19___mlp_fc2_bias[name=p_getattr_l__self___trunk_blocks___19___mlp_fc2_bias]. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"FxOnnxInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":414 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0008", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___20___norm1_weight[name=p_getattr_l__self___trunk_blocks___20___norm1_weight]. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature FxOnnxInterpreter.run_node\n- self: \n- node: fx.Node(p_getattr_l__self___trunk_blocks___20___norm1_weight)[placeholder]:Tensor(f32[1024])\n- fx_graph_module: torch.fx.GraphModule(timm_models_vision_transformer_VisionTransformer)\n- onnxfunction_dispatcher: \n- op_level_debug: False\n- onnxscript_graph: \n- onnxscript_tracer: \n- fx_name_to_onnxscript_value: Dict[length=244](\nx: `TorchScriptTensor(f32[4, 3, 512, 512])`,\np_trunk_patch_embed_proj_weight: `TorchScriptTensor(f32[1024, 3, 16, 16])`,\np_trunk_patch_embed_proj_bias: `TorchScriptTensor(f32[1024])`,\np_trunk_pos_embed: `TorchScriptTensor(f32[1, 1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_weight: `TorchScriptTensor(f32[3072, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_bias: `TorchScriptTensor(f32[3072])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_weight: `TorchScriptTensor(f32[1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_bias: `TorchScriptTensor(f32[1024])`,\n...\n)\n## Return values\n", + "text":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___20___norm1_weight[name=p_getattr_l__self___trunk_blocks___20___norm1_weight]. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"FxOnnxInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":414 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0008", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___20___norm1_bias[name=p_getattr_l__self___trunk_blocks___20___norm1_bias]. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature FxOnnxInterpreter.run_node\n- self: \n- node: fx.Node(p_getattr_l__self___trunk_blocks___20___norm1_bias)[placeholder]:Tensor(f32[1024])\n- fx_graph_module: torch.fx.GraphModule(timm_models_vision_transformer_VisionTransformer)\n- onnxfunction_dispatcher: \n- op_level_debug: False\n- onnxscript_graph: \n- onnxscript_tracer: \n- fx_name_to_onnxscript_value: Dict[length=245](\nx: `TorchScriptTensor(f32[4, 3, 512, 512])`,\np_trunk_patch_embed_proj_weight: `TorchScriptTensor(f32[1024, 3, 16, 16])`,\np_trunk_patch_embed_proj_bias: `TorchScriptTensor(f32[1024])`,\np_trunk_pos_embed: `TorchScriptTensor(f32[1, 1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_weight: `TorchScriptTensor(f32[3072, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_bias: `TorchScriptTensor(f32[3072])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_weight: `TorchScriptTensor(f32[1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_bias: `TorchScriptTensor(f32[1024])`,\n...\n)\n## Return values\n", + "text":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___20___norm1_bias[name=p_getattr_l__self___trunk_blocks___20___norm1_bias]. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"FxOnnxInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":414 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0008", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___20___attn_qkv_weight[name=p_getattr_l__self___trunk_blocks___20___attn_qkv_weight]. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature FxOnnxInterpreter.run_node\n- self: \n- node: fx.Node(p_getattr_l__self___trunk_blocks___20___attn_qkv_weight)[placeholder]:Tensor(f32[3072, 1024])\n- fx_graph_module: torch.fx.GraphModule(timm_models_vision_transformer_VisionTransformer)\n- onnxfunction_dispatcher: \n- op_level_debug: False\n- onnxscript_graph: \n- onnxscript_tracer: \n- fx_name_to_onnxscript_value: Dict[length=246](\nx: `TorchScriptTensor(f32[4, 3, 512, 512])`,\np_trunk_patch_embed_proj_weight: `TorchScriptTensor(f32[1024, 3, 16, 16])`,\np_trunk_patch_embed_proj_bias: `TorchScriptTensor(f32[1024])`,\np_trunk_pos_embed: `TorchScriptTensor(f32[1, 1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_weight: `TorchScriptTensor(f32[3072, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_bias: `TorchScriptTensor(f32[3072])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_weight: `TorchScriptTensor(f32[1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_bias: `TorchScriptTensor(f32[1024])`,\n...\n)\n## Return values\n", + "text":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___20___attn_qkv_weight[name=p_getattr_l__self___trunk_blocks___20___attn_qkv_weight]. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"FxOnnxInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":414 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0008", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___20___attn_qkv_bias[name=p_getattr_l__self___trunk_blocks___20___attn_qkv_bias]. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature FxOnnxInterpreter.run_node\n- self: \n- node: fx.Node(p_getattr_l__self___trunk_blocks___20___attn_qkv_bias)[placeholder]:Tensor(f32[3072])\n- fx_graph_module: torch.fx.GraphModule(timm_models_vision_transformer_VisionTransformer)\n- onnxfunction_dispatcher: \n- op_level_debug: False\n- onnxscript_graph: \n- onnxscript_tracer: \n- fx_name_to_onnxscript_value: Dict[length=247](\nx: `TorchScriptTensor(f32[4, 3, 512, 512])`,\np_trunk_patch_embed_proj_weight: `TorchScriptTensor(f32[1024, 3, 16, 16])`,\np_trunk_patch_embed_proj_bias: `TorchScriptTensor(f32[1024])`,\np_trunk_pos_embed: `TorchScriptTensor(f32[1, 1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_weight: `TorchScriptTensor(f32[3072, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_bias: `TorchScriptTensor(f32[3072])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_weight: `TorchScriptTensor(f32[1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_bias: `TorchScriptTensor(f32[1024])`,\n...\n)\n## Return values\n", + "text":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___20___attn_qkv_bias[name=p_getattr_l__self___trunk_blocks___20___attn_qkv_bias]. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"FxOnnxInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":414 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0008", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___20___attn_proj_weight[name=p_getattr_l__self___trunk_blocks___20___attn_proj_weight]. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature FxOnnxInterpreter.run_node\n- self: \n- node: fx.Node(p_getattr_l__self___trunk_blocks___20___attn_proj_weight)[placeholder]:Tensor(f32[1024, 1024])\n- fx_graph_module: torch.fx.GraphModule(timm_models_vision_transformer_VisionTransformer)\n- onnxfunction_dispatcher: \n- op_level_debug: False\n- onnxscript_graph: \n- onnxscript_tracer: \n- fx_name_to_onnxscript_value: Dict[length=248](\nx: `TorchScriptTensor(f32[4, 3, 512, 512])`,\np_trunk_patch_embed_proj_weight: `TorchScriptTensor(f32[1024, 3, 16, 16])`,\np_trunk_patch_embed_proj_bias: `TorchScriptTensor(f32[1024])`,\np_trunk_pos_embed: `TorchScriptTensor(f32[1, 1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_weight: `TorchScriptTensor(f32[3072, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_bias: `TorchScriptTensor(f32[3072])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_weight: `TorchScriptTensor(f32[1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_bias: `TorchScriptTensor(f32[1024])`,\n...\n)\n## Return values\n", + "text":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___20___attn_proj_weight[name=p_getattr_l__self___trunk_blocks___20___attn_proj_weight]. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"FxOnnxInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":414 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0008", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___20___attn_proj_bias[name=p_getattr_l__self___trunk_blocks___20___attn_proj_bias]. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature FxOnnxInterpreter.run_node\n- self: \n- node: fx.Node(p_getattr_l__self___trunk_blocks___20___attn_proj_bias)[placeholder]:Tensor(f32[1024])\n- fx_graph_module: torch.fx.GraphModule(timm_models_vision_transformer_VisionTransformer)\n- onnxfunction_dispatcher: \n- op_level_debug: False\n- onnxscript_graph: \n- onnxscript_tracer: \n- fx_name_to_onnxscript_value: Dict[length=249](\nx: `TorchScriptTensor(f32[4, 3, 512, 512])`,\np_trunk_patch_embed_proj_weight: `TorchScriptTensor(f32[1024, 3, 16, 16])`,\np_trunk_patch_embed_proj_bias: `TorchScriptTensor(f32[1024])`,\np_trunk_pos_embed: `TorchScriptTensor(f32[1, 1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_weight: `TorchScriptTensor(f32[3072, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_bias: `TorchScriptTensor(f32[3072])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_weight: `TorchScriptTensor(f32[1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_bias: `TorchScriptTensor(f32[1024])`,\n...\n)\n## Return values\n", + "text":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___20___attn_proj_bias[name=p_getattr_l__self___trunk_blocks___20___attn_proj_bias]. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"FxOnnxInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":414 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0008", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___20___norm2_weight[name=p_getattr_l__self___trunk_blocks___20___norm2_weight]. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature FxOnnxInterpreter.run_node\n- self: \n- node: fx.Node(p_getattr_l__self___trunk_blocks___20___norm2_weight)[placeholder]:Tensor(f32[1024])\n- fx_graph_module: torch.fx.GraphModule(timm_models_vision_transformer_VisionTransformer)\n- onnxfunction_dispatcher: \n- op_level_debug: False\n- onnxscript_graph: \n- onnxscript_tracer: \n- fx_name_to_onnxscript_value: Dict[length=250](\nx: `TorchScriptTensor(f32[4, 3, 512, 512])`,\np_trunk_patch_embed_proj_weight: `TorchScriptTensor(f32[1024, 3, 16, 16])`,\np_trunk_patch_embed_proj_bias: `TorchScriptTensor(f32[1024])`,\np_trunk_pos_embed: `TorchScriptTensor(f32[1, 1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_weight: `TorchScriptTensor(f32[3072, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_bias: `TorchScriptTensor(f32[3072])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_weight: `TorchScriptTensor(f32[1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_bias: `TorchScriptTensor(f32[1024])`,\n...\n)\n## Return values\n", + "text":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___20___norm2_weight[name=p_getattr_l__self___trunk_blocks___20___norm2_weight]. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"FxOnnxInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":414 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0008", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___20___norm2_bias[name=p_getattr_l__self___trunk_blocks___20___norm2_bias]. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature FxOnnxInterpreter.run_node\n- self: \n- node: fx.Node(p_getattr_l__self___trunk_blocks___20___norm2_bias)[placeholder]:Tensor(f32[1024])\n- fx_graph_module: torch.fx.GraphModule(timm_models_vision_transformer_VisionTransformer)\n- onnxfunction_dispatcher: \n- op_level_debug: False\n- onnxscript_graph: \n- onnxscript_tracer: \n- fx_name_to_onnxscript_value: Dict[length=251](\nx: `TorchScriptTensor(f32[4, 3, 512, 512])`,\np_trunk_patch_embed_proj_weight: `TorchScriptTensor(f32[1024, 3, 16, 16])`,\np_trunk_patch_embed_proj_bias: `TorchScriptTensor(f32[1024])`,\np_trunk_pos_embed: `TorchScriptTensor(f32[1, 1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_weight: `TorchScriptTensor(f32[3072, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_bias: `TorchScriptTensor(f32[3072])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_weight: `TorchScriptTensor(f32[1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_bias: `TorchScriptTensor(f32[1024])`,\n...\n)\n## Return values\n", + "text":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___20___norm2_bias[name=p_getattr_l__self___trunk_blocks___20___norm2_bias]. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"FxOnnxInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":414 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0008", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___20___mlp_fc1_weight[name=p_getattr_l__self___trunk_blocks___20___mlp_fc1_weight]. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature FxOnnxInterpreter.run_node\n- self: \n- node: fx.Node(p_getattr_l__self___trunk_blocks___20___mlp_fc1_weight)[placeholder]:Tensor(f32[4096, 1024])\n- fx_graph_module: torch.fx.GraphModule(timm_models_vision_transformer_VisionTransformer)\n- onnxfunction_dispatcher: \n- op_level_debug: False\n- onnxscript_graph: \n- onnxscript_tracer: \n- fx_name_to_onnxscript_value: Dict[length=252](\nx: `TorchScriptTensor(f32[4, 3, 512, 512])`,\np_trunk_patch_embed_proj_weight: `TorchScriptTensor(f32[1024, 3, 16, 16])`,\np_trunk_patch_embed_proj_bias: `TorchScriptTensor(f32[1024])`,\np_trunk_pos_embed: `TorchScriptTensor(f32[1, 1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_weight: `TorchScriptTensor(f32[3072, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_bias: `TorchScriptTensor(f32[3072])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_weight: `TorchScriptTensor(f32[1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_bias: `TorchScriptTensor(f32[1024])`,\n...\n)\n## Return values\n", + "text":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___20___mlp_fc1_weight[name=p_getattr_l__self___trunk_blocks___20___mlp_fc1_weight]. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"FxOnnxInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":414 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0008", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___20___mlp_fc1_bias[name=p_getattr_l__self___trunk_blocks___20___mlp_fc1_bias]. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature FxOnnxInterpreter.run_node\n- self: \n- node: fx.Node(p_getattr_l__self___trunk_blocks___20___mlp_fc1_bias)[placeholder]:Tensor(f32[4096])\n- fx_graph_module: torch.fx.GraphModule(timm_models_vision_transformer_VisionTransformer)\n- onnxfunction_dispatcher: \n- op_level_debug: False\n- onnxscript_graph: \n- onnxscript_tracer: \n- fx_name_to_onnxscript_value: Dict[length=253](\nx: `TorchScriptTensor(f32[4, 3, 512, 512])`,\np_trunk_patch_embed_proj_weight: `TorchScriptTensor(f32[1024, 3, 16, 16])`,\np_trunk_patch_embed_proj_bias: `TorchScriptTensor(f32[1024])`,\np_trunk_pos_embed: `TorchScriptTensor(f32[1, 1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_weight: `TorchScriptTensor(f32[3072, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_bias: `TorchScriptTensor(f32[3072])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_weight: `TorchScriptTensor(f32[1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_bias: `TorchScriptTensor(f32[1024])`,\n...\n)\n## Return values\n", + "text":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___20___mlp_fc1_bias[name=p_getattr_l__self___trunk_blocks___20___mlp_fc1_bias]. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"FxOnnxInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":414 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0008", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___20___mlp_fc2_weight[name=p_getattr_l__self___trunk_blocks___20___mlp_fc2_weight]. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature FxOnnxInterpreter.run_node\n- self: \n- node: fx.Node(p_getattr_l__self___trunk_blocks___20___mlp_fc2_weight)[placeholder]:Tensor(f32[1024, 4096])\n- fx_graph_module: torch.fx.GraphModule(timm_models_vision_transformer_VisionTransformer)\n- onnxfunction_dispatcher: \n- op_level_debug: False\n- onnxscript_graph: \n- onnxscript_tracer: \n- fx_name_to_onnxscript_value: Dict[length=254](\nx: `TorchScriptTensor(f32[4, 3, 512, 512])`,\np_trunk_patch_embed_proj_weight: `TorchScriptTensor(f32[1024, 3, 16, 16])`,\np_trunk_patch_embed_proj_bias: `TorchScriptTensor(f32[1024])`,\np_trunk_pos_embed: `TorchScriptTensor(f32[1, 1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_weight: `TorchScriptTensor(f32[3072, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_bias: `TorchScriptTensor(f32[3072])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_weight: `TorchScriptTensor(f32[1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_bias: `TorchScriptTensor(f32[1024])`,\n...\n)\n## Return values\n", + "text":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___20___mlp_fc2_weight[name=p_getattr_l__self___trunk_blocks___20___mlp_fc2_weight]. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"FxOnnxInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":414 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0008", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___20___mlp_fc2_bias[name=p_getattr_l__self___trunk_blocks___20___mlp_fc2_bias]. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature FxOnnxInterpreter.run_node\n- self: \n- node: fx.Node(p_getattr_l__self___trunk_blocks___20___mlp_fc2_bias)[placeholder]:Tensor(f32[1024])\n- fx_graph_module: torch.fx.GraphModule(timm_models_vision_transformer_VisionTransformer)\n- onnxfunction_dispatcher: \n- op_level_debug: False\n- onnxscript_graph: \n- onnxscript_tracer: \n- fx_name_to_onnxscript_value: Dict[length=255](\nx: `TorchScriptTensor(f32[4, 3, 512, 512])`,\np_trunk_patch_embed_proj_weight: `TorchScriptTensor(f32[1024, 3, 16, 16])`,\np_trunk_patch_embed_proj_bias: `TorchScriptTensor(f32[1024])`,\np_trunk_pos_embed: `TorchScriptTensor(f32[1, 1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_weight: `TorchScriptTensor(f32[3072, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_bias: `TorchScriptTensor(f32[3072])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_weight: `TorchScriptTensor(f32[1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_bias: `TorchScriptTensor(f32[1024])`,\n...\n)\n## Return values\n", + "text":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___20___mlp_fc2_bias[name=p_getattr_l__self___trunk_blocks___20___mlp_fc2_bias]. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"FxOnnxInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":414 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0008", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___21___norm1_weight[name=p_getattr_l__self___trunk_blocks___21___norm1_weight]. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature FxOnnxInterpreter.run_node\n- self: \n- node: fx.Node(p_getattr_l__self___trunk_blocks___21___norm1_weight)[placeholder]:Tensor(f32[1024])\n- fx_graph_module: torch.fx.GraphModule(timm_models_vision_transformer_VisionTransformer)\n- onnxfunction_dispatcher: \n- op_level_debug: False\n- onnxscript_graph: \n- onnxscript_tracer: \n- fx_name_to_onnxscript_value: Dict[length=256](\nx: `TorchScriptTensor(f32[4, 3, 512, 512])`,\np_trunk_patch_embed_proj_weight: `TorchScriptTensor(f32[1024, 3, 16, 16])`,\np_trunk_patch_embed_proj_bias: `TorchScriptTensor(f32[1024])`,\np_trunk_pos_embed: `TorchScriptTensor(f32[1, 1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_weight: `TorchScriptTensor(f32[3072, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_bias: `TorchScriptTensor(f32[3072])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_weight: `TorchScriptTensor(f32[1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_bias: `TorchScriptTensor(f32[1024])`,\n...\n)\n## Return values\n", + "text":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___21___norm1_weight[name=p_getattr_l__self___trunk_blocks___21___norm1_weight]. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"FxOnnxInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":414 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0008", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___21___norm1_bias[name=p_getattr_l__self___trunk_blocks___21___norm1_bias]. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature FxOnnxInterpreter.run_node\n- self: \n- node: fx.Node(p_getattr_l__self___trunk_blocks___21___norm1_bias)[placeholder]:Tensor(f32[1024])\n- fx_graph_module: torch.fx.GraphModule(timm_models_vision_transformer_VisionTransformer)\n- onnxfunction_dispatcher: \n- op_level_debug: False\n- onnxscript_graph: \n- onnxscript_tracer: \n- fx_name_to_onnxscript_value: Dict[length=257](\nx: `TorchScriptTensor(f32[4, 3, 512, 512])`,\np_trunk_patch_embed_proj_weight: `TorchScriptTensor(f32[1024, 3, 16, 16])`,\np_trunk_patch_embed_proj_bias: `TorchScriptTensor(f32[1024])`,\np_trunk_pos_embed: `TorchScriptTensor(f32[1, 1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_weight: `TorchScriptTensor(f32[3072, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_bias: `TorchScriptTensor(f32[3072])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_weight: `TorchScriptTensor(f32[1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_bias: `TorchScriptTensor(f32[1024])`,\n...\n)\n## Return values\n", + "text":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___21___norm1_bias[name=p_getattr_l__self___trunk_blocks___21___norm1_bias]. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"FxOnnxInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":414 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0008", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___21___attn_qkv_weight[name=p_getattr_l__self___trunk_blocks___21___attn_qkv_weight]. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature FxOnnxInterpreter.run_node\n- self: \n- node: fx.Node(p_getattr_l__self___trunk_blocks___21___attn_qkv_weight)[placeholder]:Tensor(f32[3072, 1024])\n- fx_graph_module: torch.fx.GraphModule(timm_models_vision_transformer_VisionTransformer)\n- onnxfunction_dispatcher: \n- op_level_debug: False\n- onnxscript_graph: \n- onnxscript_tracer: \n- fx_name_to_onnxscript_value: Dict[length=258](\nx: `TorchScriptTensor(f32[4, 3, 512, 512])`,\np_trunk_patch_embed_proj_weight: `TorchScriptTensor(f32[1024, 3, 16, 16])`,\np_trunk_patch_embed_proj_bias: `TorchScriptTensor(f32[1024])`,\np_trunk_pos_embed: `TorchScriptTensor(f32[1, 1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_weight: `TorchScriptTensor(f32[3072, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_bias: `TorchScriptTensor(f32[3072])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_weight: `TorchScriptTensor(f32[1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_bias: `TorchScriptTensor(f32[1024])`,\n...\n)\n## Return values\n", + "text":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___21___attn_qkv_weight[name=p_getattr_l__self___trunk_blocks___21___attn_qkv_weight]. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"FxOnnxInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":414 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0008", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___21___attn_qkv_bias[name=p_getattr_l__self___trunk_blocks___21___attn_qkv_bias]. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature FxOnnxInterpreter.run_node\n- self: \n- node: fx.Node(p_getattr_l__self___trunk_blocks___21___attn_qkv_bias)[placeholder]:Tensor(f32[3072])\n- fx_graph_module: torch.fx.GraphModule(timm_models_vision_transformer_VisionTransformer)\n- onnxfunction_dispatcher: \n- op_level_debug: False\n- onnxscript_graph: \n- onnxscript_tracer: \n- fx_name_to_onnxscript_value: Dict[length=259](\nx: `TorchScriptTensor(f32[4, 3, 512, 512])`,\np_trunk_patch_embed_proj_weight: `TorchScriptTensor(f32[1024, 3, 16, 16])`,\np_trunk_patch_embed_proj_bias: `TorchScriptTensor(f32[1024])`,\np_trunk_pos_embed: `TorchScriptTensor(f32[1, 1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_weight: `TorchScriptTensor(f32[3072, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_bias: `TorchScriptTensor(f32[3072])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_weight: `TorchScriptTensor(f32[1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_bias: `TorchScriptTensor(f32[1024])`,\n...\n)\n## Return values\n", + "text":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___21___attn_qkv_bias[name=p_getattr_l__self___trunk_blocks___21___attn_qkv_bias]. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"FxOnnxInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":414 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0008", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___21___attn_proj_weight[name=p_getattr_l__self___trunk_blocks___21___attn_proj_weight]. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature FxOnnxInterpreter.run_node\n- self: \n- node: fx.Node(p_getattr_l__self___trunk_blocks___21___attn_proj_weight)[placeholder]:Tensor(f32[1024, 1024])\n- fx_graph_module: torch.fx.GraphModule(timm_models_vision_transformer_VisionTransformer)\n- onnxfunction_dispatcher: \n- op_level_debug: False\n- onnxscript_graph: \n- onnxscript_tracer: \n- fx_name_to_onnxscript_value: Dict[length=260](\nx: `TorchScriptTensor(f32[4, 3, 512, 512])`,\np_trunk_patch_embed_proj_weight: `TorchScriptTensor(f32[1024, 3, 16, 16])`,\np_trunk_patch_embed_proj_bias: `TorchScriptTensor(f32[1024])`,\np_trunk_pos_embed: `TorchScriptTensor(f32[1, 1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_weight: `TorchScriptTensor(f32[3072, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_bias: `TorchScriptTensor(f32[3072])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_weight: `TorchScriptTensor(f32[1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_bias: `TorchScriptTensor(f32[1024])`,\n...\n)\n## Return values\n", + "text":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___21___attn_proj_weight[name=p_getattr_l__self___trunk_blocks___21___attn_proj_weight]. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"FxOnnxInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":414 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0008", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___21___attn_proj_bias[name=p_getattr_l__self___trunk_blocks___21___attn_proj_bias]. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature FxOnnxInterpreter.run_node\n- self: \n- node: fx.Node(p_getattr_l__self___trunk_blocks___21___attn_proj_bias)[placeholder]:Tensor(f32[1024])\n- fx_graph_module: torch.fx.GraphModule(timm_models_vision_transformer_VisionTransformer)\n- onnxfunction_dispatcher: \n- op_level_debug: False\n- onnxscript_graph: \n- onnxscript_tracer: \n- fx_name_to_onnxscript_value: Dict[length=261](\nx: `TorchScriptTensor(f32[4, 3, 512, 512])`,\np_trunk_patch_embed_proj_weight: `TorchScriptTensor(f32[1024, 3, 16, 16])`,\np_trunk_patch_embed_proj_bias: `TorchScriptTensor(f32[1024])`,\np_trunk_pos_embed: `TorchScriptTensor(f32[1, 1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_weight: `TorchScriptTensor(f32[3072, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_bias: `TorchScriptTensor(f32[3072])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_weight: `TorchScriptTensor(f32[1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_bias: `TorchScriptTensor(f32[1024])`,\n...\n)\n## Return values\n", + "text":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___21___attn_proj_bias[name=p_getattr_l__self___trunk_blocks___21___attn_proj_bias]. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"FxOnnxInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":414 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0008", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___21___norm2_weight[name=p_getattr_l__self___trunk_blocks___21___norm2_weight]. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature FxOnnxInterpreter.run_node\n- self: \n- node: fx.Node(p_getattr_l__self___trunk_blocks___21___norm2_weight)[placeholder]:Tensor(f32[1024])\n- fx_graph_module: torch.fx.GraphModule(timm_models_vision_transformer_VisionTransformer)\n- onnxfunction_dispatcher: \n- op_level_debug: False\n- onnxscript_graph: \n- onnxscript_tracer: \n- fx_name_to_onnxscript_value: Dict[length=262](\nx: `TorchScriptTensor(f32[4, 3, 512, 512])`,\np_trunk_patch_embed_proj_weight: `TorchScriptTensor(f32[1024, 3, 16, 16])`,\np_trunk_patch_embed_proj_bias: `TorchScriptTensor(f32[1024])`,\np_trunk_pos_embed: `TorchScriptTensor(f32[1, 1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_weight: `TorchScriptTensor(f32[3072, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_bias: `TorchScriptTensor(f32[3072])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_weight: `TorchScriptTensor(f32[1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_bias: `TorchScriptTensor(f32[1024])`,\n...\n)\n## Return values\n", + "text":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___21___norm2_weight[name=p_getattr_l__self___trunk_blocks___21___norm2_weight]. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"FxOnnxInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":414 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0008", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___21___norm2_bias[name=p_getattr_l__self___trunk_blocks___21___norm2_bias]. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature FxOnnxInterpreter.run_node\n- self: \n- node: fx.Node(p_getattr_l__self___trunk_blocks___21___norm2_bias)[placeholder]:Tensor(f32[1024])\n- fx_graph_module: torch.fx.GraphModule(timm_models_vision_transformer_VisionTransformer)\n- onnxfunction_dispatcher: \n- op_level_debug: False\n- onnxscript_graph: \n- onnxscript_tracer: \n- fx_name_to_onnxscript_value: Dict[length=263](\nx: `TorchScriptTensor(f32[4, 3, 512, 512])`,\np_trunk_patch_embed_proj_weight: `TorchScriptTensor(f32[1024, 3, 16, 16])`,\np_trunk_patch_embed_proj_bias: `TorchScriptTensor(f32[1024])`,\np_trunk_pos_embed: `TorchScriptTensor(f32[1, 1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_weight: `TorchScriptTensor(f32[3072, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_bias: `TorchScriptTensor(f32[3072])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_weight: `TorchScriptTensor(f32[1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_bias: `TorchScriptTensor(f32[1024])`,\n...\n)\n## Return values\n", + "text":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___21___norm2_bias[name=p_getattr_l__self___trunk_blocks___21___norm2_bias]. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"FxOnnxInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":414 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0008", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___21___mlp_fc1_weight[name=p_getattr_l__self___trunk_blocks___21___mlp_fc1_weight]. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature FxOnnxInterpreter.run_node\n- self: \n- node: fx.Node(p_getattr_l__self___trunk_blocks___21___mlp_fc1_weight)[placeholder]:Tensor(f32[4096, 1024])\n- fx_graph_module: torch.fx.GraphModule(timm_models_vision_transformer_VisionTransformer)\n- onnxfunction_dispatcher: \n- op_level_debug: False\n- onnxscript_graph: \n- onnxscript_tracer: \n- fx_name_to_onnxscript_value: Dict[length=264](\nx: `TorchScriptTensor(f32[4, 3, 512, 512])`,\np_trunk_patch_embed_proj_weight: `TorchScriptTensor(f32[1024, 3, 16, 16])`,\np_trunk_patch_embed_proj_bias: `TorchScriptTensor(f32[1024])`,\np_trunk_pos_embed: `TorchScriptTensor(f32[1, 1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_weight: `TorchScriptTensor(f32[3072, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_bias: `TorchScriptTensor(f32[3072])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_weight: `TorchScriptTensor(f32[1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_bias: `TorchScriptTensor(f32[1024])`,\n...\n)\n## Return values\n", + "text":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___21___mlp_fc1_weight[name=p_getattr_l__self___trunk_blocks___21___mlp_fc1_weight]. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"FxOnnxInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":414 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0008", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___21___mlp_fc1_bias[name=p_getattr_l__self___trunk_blocks___21___mlp_fc1_bias]. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature FxOnnxInterpreter.run_node\n- self: \n- node: fx.Node(p_getattr_l__self___trunk_blocks___21___mlp_fc1_bias)[placeholder]:Tensor(f32[4096])\n- fx_graph_module: torch.fx.GraphModule(timm_models_vision_transformer_VisionTransformer)\n- onnxfunction_dispatcher: \n- op_level_debug: False\n- onnxscript_graph: \n- onnxscript_tracer: \n- fx_name_to_onnxscript_value: Dict[length=265](\nx: `TorchScriptTensor(f32[4, 3, 512, 512])`,\np_trunk_patch_embed_proj_weight: `TorchScriptTensor(f32[1024, 3, 16, 16])`,\np_trunk_patch_embed_proj_bias: `TorchScriptTensor(f32[1024])`,\np_trunk_pos_embed: `TorchScriptTensor(f32[1, 1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_weight: `TorchScriptTensor(f32[3072, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_bias: `TorchScriptTensor(f32[3072])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_weight: `TorchScriptTensor(f32[1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_bias: `TorchScriptTensor(f32[1024])`,\n...\n)\n## Return values\n", + "text":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___21___mlp_fc1_bias[name=p_getattr_l__self___trunk_blocks___21___mlp_fc1_bias]. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"FxOnnxInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":414 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0008", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___21___mlp_fc2_weight[name=p_getattr_l__self___trunk_blocks___21___mlp_fc2_weight]. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature FxOnnxInterpreter.run_node\n- self: \n- node: fx.Node(p_getattr_l__self___trunk_blocks___21___mlp_fc2_weight)[placeholder]:Tensor(f32[1024, 4096])\n- fx_graph_module: torch.fx.GraphModule(timm_models_vision_transformer_VisionTransformer)\n- onnxfunction_dispatcher: \n- op_level_debug: False\n- onnxscript_graph: \n- onnxscript_tracer: \n- fx_name_to_onnxscript_value: Dict[length=266](\nx: `TorchScriptTensor(f32[4, 3, 512, 512])`,\np_trunk_patch_embed_proj_weight: `TorchScriptTensor(f32[1024, 3, 16, 16])`,\np_trunk_patch_embed_proj_bias: `TorchScriptTensor(f32[1024])`,\np_trunk_pos_embed: `TorchScriptTensor(f32[1, 1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_weight: `TorchScriptTensor(f32[3072, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_bias: `TorchScriptTensor(f32[3072])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_weight: `TorchScriptTensor(f32[1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_bias: `TorchScriptTensor(f32[1024])`,\n...\n)\n## Return values\n", + "text":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___21___mlp_fc2_weight[name=p_getattr_l__self___trunk_blocks___21___mlp_fc2_weight]. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"FxOnnxInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":414 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0008", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___21___mlp_fc2_bias[name=p_getattr_l__self___trunk_blocks___21___mlp_fc2_bias]. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature FxOnnxInterpreter.run_node\n- self: \n- node: fx.Node(p_getattr_l__self___trunk_blocks___21___mlp_fc2_bias)[placeholder]:Tensor(f32[1024])\n- fx_graph_module: torch.fx.GraphModule(timm_models_vision_transformer_VisionTransformer)\n- onnxfunction_dispatcher: \n- op_level_debug: False\n- onnxscript_graph: \n- onnxscript_tracer: \n- fx_name_to_onnxscript_value: Dict[length=267](\nx: `TorchScriptTensor(f32[4, 3, 512, 512])`,\np_trunk_patch_embed_proj_weight: `TorchScriptTensor(f32[1024, 3, 16, 16])`,\np_trunk_patch_embed_proj_bias: `TorchScriptTensor(f32[1024])`,\np_trunk_pos_embed: `TorchScriptTensor(f32[1, 1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_weight: `TorchScriptTensor(f32[3072, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_bias: `TorchScriptTensor(f32[3072])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_weight: `TorchScriptTensor(f32[1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_bias: `TorchScriptTensor(f32[1024])`,\n...\n)\n## Return values\n", + "text":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___21___mlp_fc2_bias[name=p_getattr_l__self___trunk_blocks___21___mlp_fc2_bias]. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"FxOnnxInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":414 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0008", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___22___norm1_weight[name=p_getattr_l__self___trunk_blocks___22___norm1_weight]. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature FxOnnxInterpreter.run_node\n- self: \n- node: fx.Node(p_getattr_l__self___trunk_blocks___22___norm1_weight)[placeholder]:Tensor(f32[1024])\n- fx_graph_module: torch.fx.GraphModule(timm_models_vision_transformer_VisionTransformer)\n- onnxfunction_dispatcher: \n- op_level_debug: False\n- onnxscript_graph: \n- onnxscript_tracer: \n- fx_name_to_onnxscript_value: Dict[length=268](\nx: `TorchScriptTensor(f32[4, 3, 512, 512])`,\np_trunk_patch_embed_proj_weight: `TorchScriptTensor(f32[1024, 3, 16, 16])`,\np_trunk_patch_embed_proj_bias: `TorchScriptTensor(f32[1024])`,\np_trunk_pos_embed: `TorchScriptTensor(f32[1, 1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_weight: `TorchScriptTensor(f32[3072, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_bias: `TorchScriptTensor(f32[3072])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_weight: `TorchScriptTensor(f32[1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_bias: `TorchScriptTensor(f32[1024])`,\n...\n)\n## Return values\n", + "text":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___22___norm1_weight[name=p_getattr_l__self___trunk_blocks___22___norm1_weight]. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"FxOnnxInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":414 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0008", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___22___norm1_bias[name=p_getattr_l__self___trunk_blocks___22___norm1_bias]. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature FxOnnxInterpreter.run_node\n- self: \n- node: fx.Node(p_getattr_l__self___trunk_blocks___22___norm1_bias)[placeholder]:Tensor(f32[1024])\n- fx_graph_module: torch.fx.GraphModule(timm_models_vision_transformer_VisionTransformer)\n- onnxfunction_dispatcher: \n- op_level_debug: False\n- onnxscript_graph: \n- onnxscript_tracer: \n- fx_name_to_onnxscript_value: Dict[length=269](\nx: `TorchScriptTensor(f32[4, 3, 512, 512])`,\np_trunk_patch_embed_proj_weight: `TorchScriptTensor(f32[1024, 3, 16, 16])`,\np_trunk_patch_embed_proj_bias: `TorchScriptTensor(f32[1024])`,\np_trunk_pos_embed: `TorchScriptTensor(f32[1, 1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_weight: `TorchScriptTensor(f32[3072, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_bias: `TorchScriptTensor(f32[3072])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_weight: `TorchScriptTensor(f32[1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_bias: `TorchScriptTensor(f32[1024])`,\n...\n)\n## Return values\n", + "text":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___22___norm1_bias[name=p_getattr_l__self___trunk_blocks___22___norm1_bias]. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"FxOnnxInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":414 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0008", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___22___attn_qkv_weight[name=p_getattr_l__self___trunk_blocks___22___attn_qkv_weight]. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature FxOnnxInterpreter.run_node\n- self: \n- node: fx.Node(p_getattr_l__self___trunk_blocks___22___attn_qkv_weight)[placeholder]:Tensor(f32[3072, 1024])\n- fx_graph_module: torch.fx.GraphModule(timm_models_vision_transformer_VisionTransformer)\n- onnxfunction_dispatcher: \n- op_level_debug: False\n- onnxscript_graph: \n- onnxscript_tracer: \n- fx_name_to_onnxscript_value: Dict[length=270](\nx: `TorchScriptTensor(f32[4, 3, 512, 512])`,\np_trunk_patch_embed_proj_weight: `TorchScriptTensor(f32[1024, 3, 16, 16])`,\np_trunk_patch_embed_proj_bias: `TorchScriptTensor(f32[1024])`,\np_trunk_pos_embed: `TorchScriptTensor(f32[1, 1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_weight: `TorchScriptTensor(f32[3072, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_bias: `TorchScriptTensor(f32[3072])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_weight: `TorchScriptTensor(f32[1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_bias: `TorchScriptTensor(f32[1024])`,\n...\n)\n## Return values\n", + "text":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___22___attn_qkv_weight[name=p_getattr_l__self___trunk_blocks___22___attn_qkv_weight]. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"FxOnnxInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":414 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0008", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___22___attn_qkv_bias[name=p_getattr_l__self___trunk_blocks___22___attn_qkv_bias]. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature FxOnnxInterpreter.run_node\n- self: \n- node: fx.Node(p_getattr_l__self___trunk_blocks___22___attn_qkv_bias)[placeholder]:Tensor(f32[3072])\n- fx_graph_module: torch.fx.GraphModule(timm_models_vision_transformer_VisionTransformer)\n- onnxfunction_dispatcher: \n- op_level_debug: False\n- onnxscript_graph: \n- onnxscript_tracer: \n- fx_name_to_onnxscript_value: Dict[length=271](\nx: `TorchScriptTensor(f32[4, 3, 512, 512])`,\np_trunk_patch_embed_proj_weight: `TorchScriptTensor(f32[1024, 3, 16, 16])`,\np_trunk_patch_embed_proj_bias: `TorchScriptTensor(f32[1024])`,\np_trunk_pos_embed: `TorchScriptTensor(f32[1, 1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_weight: `TorchScriptTensor(f32[3072, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_bias: `TorchScriptTensor(f32[3072])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_weight: `TorchScriptTensor(f32[1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_bias: `TorchScriptTensor(f32[1024])`,\n...\n)\n## Return values\n", + "text":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___22___attn_qkv_bias[name=p_getattr_l__self___trunk_blocks___22___attn_qkv_bias]. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"FxOnnxInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":414 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0008", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___22___attn_proj_weight[name=p_getattr_l__self___trunk_blocks___22___attn_proj_weight]. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature FxOnnxInterpreter.run_node\n- self: \n- node: fx.Node(p_getattr_l__self___trunk_blocks___22___attn_proj_weight)[placeholder]:Tensor(f32[1024, 1024])\n- fx_graph_module: torch.fx.GraphModule(timm_models_vision_transformer_VisionTransformer)\n- onnxfunction_dispatcher: \n- op_level_debug: False\n- onnxscript_graph: \n- onnxscript_tracer: \n- fx_name_to_onnxscript_value: Dict[length=272](\nx: `TorchScriptTensor(f32[4, 3, 512, 512])`,\np_trunk_patch_embed_proj_weight: `TorchScriptTensor(f32[1024, 3, 16, 16])`,\np_trunk_patch_embed_proj_bias: `TorchScriptTensor(f32[1024])`,\np_trunk_pos_embed: `TorchScriptTensor(f32[1, 1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_weight: `TorchScriptTensor(f32[3072, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_bias: `TorchScriptTensor(f32[3072])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_weight: `TorchScriptTensor(f32[1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_bias: `TorchScriptTensor(f32[1024])`,\n...\n)\n## Return values\n", + "text":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___22___attn_proj_weight[name=p_getattr_l__self___trunk_blocks___22___attn_proj_weight]. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"FxOnnxInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":414 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0008", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___22___attn_proj_bias[name=p_getattr_l__self___trunk_blocks___22___attn_proj_bias]. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature FxOnnxInterpreter.run_node\n- self: \n- node: fx.Node(p_getattr_l__self___trunk_blocks___22___attn_proj_bias)[placeholder]:Tensor(f32[1024])\n- fx_graph_module: torch.fx.GraphModule(timm_models_vision_transformer_VisionTransformer)\n- onnxfunction_dispatcher: \n- op_level_debug: False\n- onnxscript_graph: \n- onnxscript_tracer: \n- fx_name_to_onnxscript_value: Dict[length=273](\nx: `TorchScriptTensor(f32[4, 3, 512, 512])`,\np_trunk_patch_embed_proj_weight: `TorchScriptTensor(f32[1024, 3, 16, 16])`,\np_trunk_patch_embed_proj_bias: `TorchScriptTensor(f32[1024])`,\np_trunk_pos_embed: `TorchScriptTensor(f32[1, 1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_weight: `TorchScriptTensor(f32[3072, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_bias: `TorchScriptTensor(f32[3072])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_weight: `TorchScriptTensor(f32[1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_bias: `TorchScriptTensor(f32[1024])`,\n...\n)\n## Return values\n", + "text":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___22___attn_proj_bias[name=p_getattr_l__self___trunk_blocks___22___attn_proj_bias]. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"FxOnnxInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":414 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0008", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___22___norm2_weight[name=p_getattr_l__self___trunk_blocks___22___norm2_weight]. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature FxOnnxInterpreter.run_node\n- self: \n- node: fx.Node(p_getattr_l__self___trunk_blocks___22___norm2_weight)[placeholder]:Tensor(f32[1024])\n- fx_graph_module: torch.fx.GraphModule(timm_models_vision_transformer_VisionTransformer)\n- onnxfunction_dispatcher: \n- op_level_debug: False\n- onnxscript_graph: \n- onnxscript_tracer: \n- fx_name_to_onnxscript_value: Dict[length=274](\nx: `TorchScriptTensor(f32[4, 3, 512, 512])`,\np_trunk_patch_embed_proj_weight: `TorchScriptTensor(f32[1024, 3, 16, 16])`,\np_trunk_patch_embed_proj_bias: `TorchScriptTensor(f32[1024])`,\np_trunk_pos_embed: `TorchScriptTensor(f32[1, 1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_weight: `TorchScriptTensor(f32[3072, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_bias: `TorchScriptTensor(f32[3072])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_weight: `TorchScriptTensor(f32[1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_bias: `TorchScriptTensor(f32[1024])`,\n...\n)\n## Return values\n", + "text":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___22___norm2_weight[name=p_getattr_l__self___trunk_blocks___22___norm2_weight]. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"FxOnnxInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":414 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0008", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___22___norm2_bias[name=p_getattr_l__self___trunk_blocks___22___norm2_bias]. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature FxOnnxInterpreter.run_node\n- self: \n- node: fx.Node(p_getattr_l__self___trunk_blocks___22___norm2_bias)[placeholder]:Tensor(f32[1024])\n- fx_graph_module: torch.fx.GraphModule(timm_models_vision_transformer_VisionTransformer)\n- onnxfunction_dispatcher: \n- op_level_debug: False\n- onnxscript_graph: \n- onnxscript_tracer: \n- fx_name_to_onnxscript_value: Dict[length=275](\nx: `TorchScriptTensor(f32[4, 3, 512, 512])`,\np_trunk_patch_embed_proj_weight: `TorchScriptTensor(f32[1024, 3, 16, 16])`,\np_trunk_patch_embed_proj_bias: `TorchScriptTensor(f32[1024])`,\np_trunk_pos_embed: `TorchScriptTensor(f32[1, 1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_weight: `TorchScriptTensor(f32[3072, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_bias: `TorchScriptTensor(f32[3072])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_weight: `TorchScriptTensor(f32[1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_bias: `TorchScriptTensor(f32[1024])`,\n...\n)\n## Return values\n", + "text":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___22___norm2_bias[name=p_getattr_l__self___trunk_blocks___22___norm2_bias]. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"FxOnnxInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":414 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0008", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___22___mlp_fc1_weight[name=p_getattr_l__self___trunk_blocks___22___mlp_fc1_weight]. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature FxOnnxInterpreter.run_node\n- self: \n- node: fx.Node(p_getattr_l__self___trunk_blocks___22___mlp_fc1_weight)[placeholder]:Tensor(f32[4096, 1024])\n- fx_graph_module: torch.fx.GraphModule(timm_models_vision_transformer_VisionTransformer)\n- onnxfunction_dispatcher: \n- op_level_debug: False\n- onnxscript_graph: \n- onnxscript_tracer: \n- fx_name_to_onnxscript_value: Dict[length=276](\nx: `TorchScriptTensor(f32[4, 3, 512, 512])`,\np_trunk_patch_embed_proj_weight: `TorchScriptTensor(f32[1024, 3, 16, 16])`,\np_trunk_patch_embed_proj_bias: `TorchScriptTensor(f32[1024])`,\np_trunk_pos_embed: `TorchScriptTensor(f32[1, 1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_weight: `TorchScriptTensor(f32[3072, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_bias: `TorchScriptTensor(f32[3072])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_weight: `TorchScriptTensor(f32[1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_bias: `TorchScriptTensor(f32[1024])`,\n...\n)\n## Return values\n", + "text":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___22___mlp_fc1_weight[name=p_getattr_l__self___trunk_blocks___22___mlp_fc1_weight]. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"FxOnnxInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":414 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0008", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___22___mlp_fc1_bias[name=p_getattr_l__self___trunk_blocks___22___mlp_fc1_bias]. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature FxOnnxInterpreter.run_node\n- self: \n- node: fx.Node(p_getattr_l__self___trunk_blocks___22___mlp_fc1_bias)[placeholder]:Tensor(f32[4096])\n- fx_graph_module: torch.fx.GraphModule(timm_models_vision_transformer_VisionTransformer)\n- onnxfunction_dispatcher: \n- op_level_debug: False\n- onnxscript_graph: \n- onnxscript_tracer: \n- fx_name_to_onnxscript_value: Dict[length=277](\nx: `TorchScriptTensor(f32[4, 3, 512, 512])`,\np_trunk_patch_embed_proj_weight: `TorchScriptTensor(f32[1024, 3, 16, 16])`,\np_trunk_patch_embed_proj_bias: `TorchScriptTensor(f32[1024])`,\np_trunk_pos_embed: `TorchScriptTensor(f32[1, 1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_weight: `TorchScriptTensor(f32[3072, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_bias: `TorchScriptTensor(f32[3072])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_weight: `TorchScriptTensor(f32[1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_bias: `TorchScriptTensor(f32[1024])`,\n...\n)\n## Return values\n", + "text":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___22___mlp_fc1_bias[name=p_getattr_l__self___trunk_blocks___22___mlp_fc1_bias]. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"FxOnnxInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":414 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0008", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___22___mlp_fc2_weight[name=p_getattr_l__self___trunk_blocks___22___mlp_fc2_weight]. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature FxOnnxInterpreter.run_node\n- self: \n- node: fx.Node(p_getattr_l__self___trunk_blocks___22___mlp_fc2_weight)[placeholder]:Tensor(f32[1024, 4096])\n- fx_graph_module: torch.fx.GraphModule(timm_models_vision_transformer_VisionTransformer)\n- onnxfunction_dispatcher: \n- op_level_debug: False\n- onnxscript_graph: \n- onnxscript_tracer: \n- fx_name_to_onnxscript_value: Dict[length=278](\nx: `TorchScriptTensor(f32[4, 3, 512, 512])`,\np_trunk_patch_embed_proj_weight: `TorchScriptTensor(f32[1024, 3, 16, 16])`,\np_trunk_patch_embed_proj_bias: `TorchScriptTensor(f32[1024])`,\np_trunk_pos_embed: `TorchScriptTensor(f32[1, 1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_weight: `TorchScriptTensor(f32[3072, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_bias: `TorchScriptTensor(f32[3072])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_weight: `TorchScriptTensor(f32[1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_bias: `TorchScriptTensor(f32[1024])`,\n...\n)\n## Return values\n", + "text":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___22___mlp_fc2_weight[name=p_getattr_l__self___trunk_blocks___22___mlp_fc2_weight]. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"FxOnnxInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":414 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0008", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___22___mlp_fc2_bias[name=p_getattr_l__self___trunk_blocks___22___mlp_fc2_bias]. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature FxOnnxInterpreter.run_node\n- self: \n- node: fx.Node(p_getattr_l__self___trunk_blocks___22___mlp_fc2_bias)[placeholder]:Tensor(f32[1024])\n- fx_graph_module: torch.fx.GraphModule(timm_models_vision_transformer_VisionTransformer)\n- onnxfunction_dispatcher: \n- op_level_debug: False\n- onnxscript_graph: \n- onnxscript_tracer: \n- fx_name_to_onnxscript_value: Dict[length=279](\nx: `TorchScriptTensor(f32[4, 3, 512, 512])`,\np_trunk_patch_embed_proj_weight: `TorchScriptTensor(f32[1024, 3, 16, 16])`,\np_trunk_patch_embed_proj_bias: `TorchScriptTensor(f32[1024])`,\np_trunk_pos_embed: `TorchScriptTensor(f32[1, 1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_weight: `TorchScriptTensor(f32[3072, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_bias: `TorchScriptTensor(f32[3072])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_weight: `TorchScriptTensor(f32[1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_bias: `TorchScriptTensor(f32[1024])`,\n...\n)\n## Return values\n", + "text":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___22___mlp_fc2_bias[name=p_getattr_l__self___trunk_blocks___22___mlp_fc2_bias]. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"FxOnnxInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":414 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0008", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___23___norm1_weight[name=p_getattr_l__self___trunk_blocks___23___norm1_weight]. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature FxOnnxInterpreter.run_node\n- self: \n- node: fx.Node(p_getattr_l__self___trunk_blocks___23___norm1_weight)[placeholder]:Tensor(f32[1024])\n- fx_graph_module: torch.fx.GraphModule(timm_models_vision_transformer_VisionTransformer)\n- onnxfunction_dispatcher: \n- op_level_debug: False\n- onnxscript_graph: \n- onnxscript_tracer: \n- fx_name_to_onnxscript_value: Dict[length=280](\nx: `TorchScriptTensor(f32[4, 3, 512, 512])`,\np_trunk_patch_embed_proj_weight: `TorchScriptTensor(f32[1024, 3, 16, 16])`,\np_trunk_patch_embed_proj_bias: `TorchScriptTensor(f32[1024])`,\np_trunk_pos_embed: `TorchScriptTensor(f32[1, 1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_weight: `TorchScriptTensor(f32[3072, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_bias: `TorchScriptTensor(f32[3072])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_weight: `TorchScriptTensor(f32[1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_bias: `TorchScriptTensor(f32[1024])`,\n...\n)\n## Return values\n", + "text":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___23___norm1_weight[name=p_getattr_l__self___trunk_blocks___23___norm1_weight]. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"FxOnnxInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":414 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0008", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___23___norm1_bias[name=p_getattr_l__self___trunk_blocks___23___norm1_bias]. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature FxOnnxInterpreter.run_node\n- self: \n- node: fx.Node(p_getattr_l__self___trunk_blocks___23___norm1_bias)[placeholder]:Tensor(f32[1024])\n- fx_graph_module: torch.fx.GraphModule(timm_models_vision_transformer_VisionTransformer)\n- onnxfunction_dispatcher: \n- op_level_debug: False\n- onnxscript_graph: \n- onnxscript_tracer: \n- fx_name_to_onnxscript_value: Dict[length=281](\nx: `TorchScriptTensor(f32[4, 3, 512, 512])`,\np_trunk_patch_embed_proj_weight: `TorchScriptTensor(f32[1024, 3, 16, 16])`,\np_trunk_patch_embed_proj_bias: `TorchScriptTensor(f32[1024])`,\np_trunk_pos_embed: `TorchScriptTensor(f32[1, 1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_weight: `TorchScriptTensor(f32[3072, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_bias: `TorchScriptTensor(f32[3072])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_weight: `TorchScriptTensor(f32[1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_bias: `TorchScriptTensor(f32[1024])`,\n...\n)\n## Return values\n", + "text":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___23___norm1_bias[name=p_getattr_l__self___trunk_blocks___23___norm1_bias]. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"FxOnnxInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":414 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0008", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___23___attn_qkv_weight[name=p_getattr_l__self___trunk_blocks___23___attn_qkv_weight]. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature FxOnnxInterpreter.run_node\n- self: \n- node: fx.Node(p_getattr_l__self___trunk_blocks___23___attn_qkv_weight)[placeholder]:Tensor(f32[3072, 1024])\n- fx_graph_module: torch.fx.GraphModule(timm_models_vision_transformer_VisionTransformer)\n- onnxfunction_dispatcher: \n- op_level_debug: False\n- onnxscript_graph: \n- onnxscript_tracer: \n- fx_name_to_onnxscript_value: Dict[length=282](\nx: `TorchScriptTensor(f32[4, 3, 512, 512])`,\np_trunk_patch_embed_proj_weight: `TorchScriptTensor(f32[1024, 3, 16, 16])`,\np_trunk_patch_embed_proj_bias: `TorchScriptTensor(f32[1024])`,\np_trunk_pos_embed: `TorchScriptTensor(f32[1, 1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_weight: `TorchScriptTensor(f32[3072, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_bias: `TorchScriptTensor(f32[3072])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_weight: `TorchScriptTensor(f32[1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_bias: `TorchScriptTensor(f32[1024])`,\n...\n)\n## Return values\n", + "text":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___23___attn_qkv_weight[name=p_getattr_l__self___trunk_blocks___23___attn_qkv_weight]. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"FxOnnxInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":414 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0008", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___23___attn_qkv_bias[name=p_getattr_l__self___trunk_blocks___23___attn_qkv_bias]. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature FxOnnxInterpreter.run_node\n- self: \n- node: fx.Node(p_getattr_l__self___trunk_blocks___23___attn_qkv_bias)[placeholder]:Tensor(f32[3072])\n- fx_graph_module: torch.fx.GraphModule(timm_models_vision_transformer_VisionTransformer)\n- onnxfunction_dispatcher: \n- op_level_debug: False\n- onnxscript_graph: \n- onnxscript_tracer: \n- fx_name_to_onnxscript_value: Dict[length=283](\nx: `TorchScriptTensor(f32[4, 3, 512, 512])`,\np_trunk_patch_embed_proj_weight: `TorchScriptTensor(f32[1024, 3, 16, 16])`,\np_trunk_patch_embed_proj_bias: `TorchScriptTensor(f32[1024])`,\np_trunk_pos_embed: `TorchScriptTensor(f32[1, 1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_weight: `TorchScriptTensor(f32[3072, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_bias: `TorchScriptTensor(f32[3072])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_weight: `TorchScriptTensor(f32[1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_bias: `TorchScriptTensor(f32[1024])`,\n...\n)\n## Return values\n", + "text":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___23___attn_qkv_bias[name=p_getattr_l__self___trunk_blocks___23___attn_qkv_bias]. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"FxOnnxInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":414 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0008", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___23___attn_proj_weight[name=p_getattr_l__self___trunk_blocks___23___attn_proj_weight]. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature FxOnnxInterpreter.run_node\n- self: \n- node: fx.Node(p_getattr_l__self___trunk_blocks___23___attn_proj_weight)[placeholder]:Tensor(f32[1024, 1024])\n- fx_graph_module: torch.fx.GraphModule(timm_models_vision_transformer_VisionTransformer)\n- onnxfunction_dispatcher: \n- op_level_debug: False\n- onnxscript_graph: \n- onnxscript_tracer: \n- fx_name_to_onnxscript_value: Dict[length=284](\nx: `TorchScriptTensor(f32[4, 3, 512, 512])`,\np_trunk_patch_embed_proj_weight: `TorchScriptTensor(f32[1024, 3, 16, 16])`,\np_trunk_patch_embed_proj_bias: `TorchScriptTensor(f32[1024])`,\np_trunk_pos_embed: `TorchScriptTensor(f32[1, 1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_weight: `TorchScriptTensor(f32[3072, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_bias: `TorchScriptTensor(f32[3072])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_weight: `TorchScriptTensor(f32[1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_bias: `TorchScriptTensor(f32[1024])`,\n...\n)\n## Return values\n", + "text":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___23___attn_proj_weight[name=p_getattr_l__self___trunk_blocks___23___attn_proj_weight]. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"FxOnnxInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":414 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0008", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___23___attn_proj_bias[name=p_getattr_l__self___trunk_blocks___23___attn_proj_bias]. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature FxOnnxInterpreter.run_node\n- self: \n- node: fx.Node(p_getattr_l__self___trunk_blocks___23___attn_proj_bias)[placeholder]:Tensor(f32[1024])\n- fx_graph_module: torch.fx.GraphModule(timm_models_vision_transformer_VisionTransformer)\n- onnxfunction_dispatcher: \n- op_level_debug: False\n- onnxscript_graph: \n- onnxscript_tracer: \n- fx_name_to_onnxscript_value: Dict[length=285](\nx: `TorchScriptTensor(f32[4, 3, 512, 512])`,\np_trunk_patch_embed_proj_weight: `TorchScriptTensor(f32[1024, 3, 16, 16])`,\np_trunk_patch_embed_proj_bias: `TorchScriptTensor(f32[1024])`,\np_trunk_pos_embed: `TorchScriptTensor(f32[1, 1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_weight: `TorchScriptTensor(f32[3072, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_bias: `TorchScriptTensor(f32[3072])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_weight: `TorchScriptTensor(f32[1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_bias: `TorchScriptTensor(f32[1024])`,\n...\n)\n## Return values\n", + "text":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___23___attn_proj_bias[name=p_getattr_l__self___trunk_blocks___23___attn_proj_bias]. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"FxOnnxInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":414 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0008", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___23___norm2_weight[name=p_getattr_l__self___trunk_blocks___23___norm2_weight]. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature FxOnnxInterpreter.run_node\n- self: \n- node: fx.Node(p_getattr_l__self___trunk_blocks___23___norm2_weight)[placeholder]:Tensor(f32[1024])\n- fx_graph_module: torch.fx.GraphModule(timm_models_vision_transformer_VisionTransformer)\n- onnxfunction_dispatcher: \n- op_level_debug: False\n- onnxscript_graph: \n- onnxscript_tracer: \n- fx_name_to_onnxscript_value: Dict[length=286](\nx: `TorchScriptTensor(f32[4, 3, 512, 512])`,\np_trunk_patch_embed_proj_weight: `TorchScriptTensor(f32[1024, 3, 16, 16])`,\np_trunk_patch_embed_proj_bias: `TorchScriptTensor(f32[1024])`,\np_trunk_pos_embed: `TorchScriptTensor(f32[1, 1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_weight: `TorchScriptTensor(f32[3072, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_bias: `TorchScriptTensor(f32[3072])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_weight: `TorchScriptTensor(f32[1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_bias: `TorchScriptTensor(f32[1024])`,\n...\n)\n## Return values\n", + "text":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___23___norm2_weight[name=p_getattr_l__self___trunk_blocks___23___norm2_weight]. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"FxOnnxInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":414 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0008", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___23___norm2_bias[name=p_getattr_l__self___trunk_blocks___23___norm2_bias]. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature FxOnnxInterpreter.run_node\n- self: \n- node: fx.Node(p_getattr_l__self___trunk_blocks___23___norm2_bias)[placeholder]:Tensor(f32[1024])\n- fx_graph_module: torch.fx.GraphModule(timm_models_vision_transformer_VisionTransformer)\n- onnxfunction_dispatcher: \n- op_level_debug: False\n- onnxscript_graph: \n- onnxscript_tracer: \n- fx_name_to_onnxscript_value: Dict[length=287](\nx: `TorchScriptTensor(f32[4, 3, 512, 512])`,\np_trunk_patch_embed_proj_weight: `TorchScriptTensor(f32[1024, 3, 16, 16])`,\np_trunk_patch_embed_proj_bias: `TorchScriptTensor(f32[1024])`,\np_trunk_pos_embed: `TorchScriptTensor(f32[1, 1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_weight: `TorchScriptTensor(f32[3072, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_bias: `TorchScriptTensor(f32[3072])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_weight: `TorchScriptTensor(f32[1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_bias: `TorchScriptTensor(f32[1024])`,\n...\n)\n## Return values\n", + "text":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___23___norm2_bias[name=p_getattr_l__self___trunk_blocks___23___norm2_bias]. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"FxOnnxInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":414 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0008", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___23___mlp_fc1_weight[name=p_getattr_l__self___trunk_blocks___23___mlp_fc1_weight]. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature FxOnnxInterpreter.run_node\n- self: \n- node: fx.Node(p_getattr_l__self___trunk_blocks___23___mlp_fc1_weight)[placeholder]:Tensor(f32[4096, 1024])\n- fx_graph_module: torch.fx.GraphModule(timm_models_vision_transformer_VisionTransformer)\n- onnxfunction_dispatcher: \n- op_level_debug: False\n- onnxscript_graph: \n- onnxscript_tracer: \n- fx_name_to_onnxscript_value: Dict[length=288](\nx: `TorchScriptTensor(f32[4, 3, 512, 512])`,\np_trunk_patch_embed_proj_weight: `TorchScriptTensor(f32[1024, 3, 16, 16])`,\np_trunk_patch_embed_proj_bias: `TorchScriptTensor(f32[1024])`,\np_trunk_pos_embed: `TorchScriptTensor(f32[1, 1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_weight: `TorchScriptTensor(f32[3072, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_bias: `TorchScriptTensor(f32[3072])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_weight: `TorchScriptTensor(f32[1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_bias: `TorchScriptTensor(f32[1024])`,\n...\n)\n## Return values\n", + "text":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___23___mlp_fc1_weight[name=p_getattr_l__self___trunk_blocks___23___mlp_fc1_weight]. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"FxOnnxInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":414 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0008", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___23___mlp_fc1_bias[name=p_getattr_l__self___trunk_blocks___23___mlp_fc1_bias]. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature FxOnnxInterpreter.run_node\n- self: \n- node: fx.Node(p_getattr_l__self___trunk_blocks___23___mlp_fc1_bias)[placeholder]:Tensor(f32[4096])\n- fx_graph_module: torch.fx.GraphModule(timm_models_vision_transformer_VisionTransformer)\n- onnxfunction_dispatcher: \n- op_level_debug: False\n- onnxscript_graph: \n- onnxscript_tracer: \n- fx_name_to_onnxscript_value: Dict[length=289](\nx: `TorchScriptTensor(f32[4, 3, 512, 512])`,\np_trunk_patch_embed_proj_weight: `TorchScriptTensor(f32[1024, 3, 16, 16])`,\np_trunk_patch_embed_proj_bias: `TorchScriptTensor(f32[1024])`,\np_trunk_pos_embed: `TorchScriptTensor(f32[1, 1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_weight: `TorchScriptTensor(f32[3072, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_bias: `TorchScriptTensor(f32[3072])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_weight: `TorchScriptTensor(f32[1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_bias: `TorchScriptTensor(f32[1024])`,\n...\n)\n## Return values\n", + "text":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___23___mlp_fc1_bias[name=p_getattr_l__self___trunk_blocks___23___mlp_fc1_bias]. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"FxOnnxInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":414 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0008", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___23___mlp_fc2_weight[name=p_getattr_l__self___trunk_blocks___23___mlp_fc2_weight]. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature FxOnnxInterpreter.run_node\n- self: \n- node: fx.Node(p_getattr_l__self___trunk_blocks___23___mlp_fc2_weight)[placeholder]:Tensor(f32[1024, 4096])\n- fx_graph_module: torch.fx.GraphModule(timm_models_vision_transformer_VisionTransformer)\n- onnxfunction_dispatcher: \n- op_level_debug: False\n- onnxscript_graph: \n- onnxscript_tracer: \n- fx_name_to_onnxscript_value: Dict[length=290](\nx: `TorchScriptTensor(f32[4, 3, 512, 512])`,\np_trunk_patch_embed_proj_weight: `TorchScriptTensor(f32[1024, 3, 16, 16])`,\np_trunk_patch_embed_proj_bias: `TorchScriptTensor(f32[1024])`,\np_trunk_pos_embed: `TorchScriptTensor(f32[1, 1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_weight: `TorchScriptTensor(f32[3072, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_bias: `TorchScriptTensor(f32[3072])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_weight: `TorchScriptTensor(f32[1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_bias: `TorchScriptTensor(f32[1024])`,\n...\n)\n## Return values\n", + "text":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___23___mlp_fc2_weight[name=p_getattr_l__self___trunk_blocks___23___mlp_fc2_weight]. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"FxOnnxInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":414 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0008", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___23___mlp_fc2_bias[name=p_getattr_l__self___trunk_blocks___23___mlp_fc2_bias]. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature FxOnnxInterpreter.run_node\n- self: \n- node: fx.Node(p_getattr_l__self___trunk_blocks___23___mlp_fc2_bias)[placeholder]:Tensor(f32[1024])\n- fx_graph_module: torch.fx.GraphModule(timm_models_vision_transformer_VisionTransformer)\n- onnxfunction_dispatcher: \n- op_level_debug: False\n- onnxscript_graph: \n- onnxscript_tracer: \n- fx_name_to_onnxscript_value: Dict[length=291](\nx: `TorchScriptTensor(f32[4, 3, 512, 512])`,\np_trunk_patch_embed_proj_weight: `TorchScriptTensor(f32[1024, 3, 16, 16])`,\np_trunk_patch_embed_proj_bias: `TorchScriptTensor(f32[1024])`,\np_trunk_pos_embed: `TorchScriptTensor(f32[1, 1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_weight: `TorchScriptTensor(f32[3072, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_bias: `TorchScriptTensor(f32[3072])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_weight: `TorchScriptTensor(f32[1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_bias: `TorchScriptTensor(f32[1024])`,\n...\n)\n## Return values\n", + "text":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___23___mlp_fc2_bias[name=p_getattr_l__self___trunk_blocks___23___mlp_fc2_bias]. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"FxOnnxInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":414 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0008", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Node: placeholder:p_trunk_norm_weight[name=p_trunk_norm_weight]. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature FxOnnxInterpreter.run_node\n- self: \n- node: fx.Node(p_trunk_norm_weight)[placeholder]:Tensor(f32[1024])\n- fx_graph_module: torch.fx.GraphModule(timm_models_vision_transformer_VisionTransformer)\n- onnxfunction_dispatcher: \n- op_level_debug: False\n- onnxscript_graph: \n- onnxscript_tracer: \n- fx_name_to_onnxscript_value: Dict[length=292](\nx: `TorchScriptTensor(f32[4, 3, 512, 512])`,\np_trunk_patch_embed_proj_weight: `TorchScriptTensor(f32[1024, 3, 16, 16])`,\np_trunk_patch_embed_proj_bias: `TorchScriptTensor(f32[1024])`,\np_trunk_pos_embed: `TorchScriptTensor(f32[1, 1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_weight: `TorchScriptTensor(f32[3072, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_bias: `TorchScriptTensor(f32[3072])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_weight: `TorchScriptTensor(f32[1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_bias: `TorchScriptTensor(f32[1024])`,\n...\n)\n## Return values\n", + "text":"FX Node: placeholder:p_trunk_norm_weight[name=p_trunk_norm_weight]. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"FxOnnxInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":414 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0008", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Node: placeholder:p_trunk_norm_bias[name=p_trunk_norm_bias]. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature FxOnnxInterpreter.run_node\n- self: \n- node: fx.Node(p_trunk_norm_bias)[placeholder]:Tensor(f32[1024])\n- fx_graph_module: torch.fx.GraphModule(timm_models_vision_transformer_VisionTransformer)\n- onnxfunction_dispatcher: \n- op_level_debug: False\n- onnxscript_graph: \n- onnxscript_tracer: \n- fx_name_to_onnxscript_value: Dict[length=293](\nx: `TorchScriptTensor(f32[4, 3, 512, 512])`,\np_trunk_patch_embed_proj_weight: `TorchScriptTensor(f32[1024, 3, 16, 16])`,\np_trunk_patch_embed_proj_bias: `TorchScriptTensor(f32[1024])`,\np_trunk_pos_embed: `TorchScriptTensor(f32[1, 1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_weight: `TorchScriptTensor(f32[3072, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_bias: `TorchScriptTensor(f32[3072])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_weight: `TorchScriptTensor(f32[1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_bias: `TorchScriptTensor(f32[1024])`,\n...\n)\n## Return values\n", + "text":"FX Node: placeholder:p_trunk_norm_bias[name=p_trunk_norm_bias]. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"FxOnnxInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":414 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0008", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Node: placeholder:p_trunk_attn_pool_latent[name=p_trunk_attn_pool_latent]. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature FxOnnxInterpreter.run_node\n- self: \n- node: fx.Node(p_trunk_attn_pool_latent)[placeholder]:Tensor(f32[1, 1, 1024])\n- fx_graph_module: torch.fx.GraphModule(timm_models_vision_transformer_VisionTransformer)\n- onnxfunction_dispatcher: \n- op_level_debug: False\n- onnxscript_graph: \n- onnxscript_tracer: \n- fx_name_to_onnxscript_value: Dict[length=294](\nx: `TorchScriptTensor(f32[4, 3, 512, 512])`,\np_trunk_patch_embed_proj_weight: `TorchScriptTensor(f32[1024, 3, 16, 16])`,\np_trunk_patch_embed_proj_bias: `TorchScriptTensor(f32[1024])`,\np_trunk_pos_embed: `TorchScriptTensor(f32[1, 1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_weight: `TorchScriptTensor(f32[3072, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_bias: `TorchScriptTensor(f32[3072])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_weight: `TorchScriptTensor(f32[1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_bias: `TorchScriptTensor(f32[1024])`,\n...\n)\n## Return values\n", + "text":"FX Node: placeholder:p_trunk_attn_pool_latent[name=p_trunk_attn_pool_latent]. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"FxOnnxInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":414 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0008", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Node: placeholder:p_trunk_attn_pool_q_weight[name=p_trunk_attn_pool_q_weight]. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature FxOnnxInterpreter.run_node\n- self: \n- node: fx.Node(p_trunk_attn_pool_q_weight)[placeholder]:Tensor(f32[1024, 1024])\n- fx_graph_module: torch.fx.GraphModule(timm_models_vision_transformer_VisionTransformer)\n- onnxfunction_dispatcher: \n- op_level_debug: False\n- onnxscript_graph: \n- onnxscript_tracer: \n- fx_name_to_onnxscript_value: Dict[length=295](\nx: `TorchScriptTensor(f32[4, 3, 512, 512])`,\np_trunk_patch_embed_proj_weight: `TorchScriptTensor(f32[1024, 3, 16, 16])`,\np_trunk_patch_embed_proj_bias: `TorchScriptTensor(f32[1024])`,\np_trunk_pos_embed: `TorchScriptTensor(f32[1, 1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_weight: `TorchScriptTensor(f32[3072, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_bias: `TorchScriptTensor(f32[3072])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_weight: `TorchScriptTensor(f32[1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_bias: `TorchScriptTensor(f32[1024])`,\n...\n)\n## Return values\n", + "text":"FX Node: placeholder:p_trunk_attn_pool_q_weight[name=p_trunk_attn_pool_q_weight]. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"FxOnnxInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":414 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0008", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Node: placeholder:p_trunk_attn_pool_q_bias[name=p_trunk_attn_pool_q_bias]. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature FxOnnxInterpreter.run_node\n- self: \n- node: fx.Node(p_trunk_attn_pool_q_bias)[placeholder]:Tensor(f32[1024])\n- fx_graph_module: torch.fx.GraphModule(timm_models_vision_transformer_VisionTransformer)\n- onnxfunction_dispatcher: \n- op_level_debug: False\n- onnxscript_graph: \n- onnxscript_tracer: \n- fx_name_to_onnxscript_value: Dict[length=296](\nx: `TorchScriptTensor(f32[4, 3, 512, 512])`,\np_trunk_patch_embed_proj_weight: `TorchScriptTensor(f32[1024, 3, 16, 16])`,\np_trunk_patch_embed_proj_bias: `TorchScriptTensor(f32[1024])`,\np_trunk_pos_embed: `TorchScriptTensor(f32[1, 1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_weight: `TorchScriptTensor(f32[3072, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_bias: `TorchScriptTensor(f32[3072])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_weight: `TorchScriptTensor(f32[1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_bias: `TorchScriptTensor(f32[1024])`,\n...\n)\n## Return values\n", + "text":"FX Node: placeholder:p_trunk_attn_pool_q_bias[name=p_trunk_attn_pool_q_bias]. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"FxOnnxInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":414 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0008", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Node: placeholder:p_trunk_attn_pool_kv_weight[name=p_trunk_attn_pool_kv_weight]. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature FxOnnxInterpreter.run_node\n- self: \n- node: fx.Node(p_trunk_attn_pool_kv_weight)[placeholder]:Tensor(f32[2048, 1024])\n- fx_graph_module: torch.fx.GraphModule(timm_models_vision_transformer_VisionTransformer)\n- onnxfunction_dispatcher: \n- op_level_debug: False\n- onnxscript_graph: \n- onnxscript_tracer: \n- fx_name_to_onnxscript_value: Dict[length=297](\nx: `TorchScriptTensor(f32[4, 3, 512, 512])`,\np_trunk_patch_embed_proj_weight: `TorchScriptTensor(f32[1024, 3, 16, 16])`,\np_trunk_patch_embed_proj_bias: `TorchScriptTensor(f32[1024])`,\np_trunk_pos_embed: `TorchScriptTensor(f32[1, 1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_weight: `TorchScriptTensor(f32[3072, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_bias: `TorchScriptTensor(f32[3072])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_weight: `TorchScriptTensor(f32[1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_bias: `TorchScriptTensor(f32[1024])`,\n...\n)\n## Return values\n", + "text":"FX Node: placeholder:p_trunk_attn_pool_kv_weight[name=p_trunk_attn_pool_kv_weight]. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"FxOnnxInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":414 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0008", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Node: placeholder:p_trunk_attn_pool_kv_bias[name=p_trunk_attn_pool_kv_bias]. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature FxOnnxInterpreter.run_node\n- self: \n- node: fx.Node(p_trunk_attn_pool_kv_bias)[placeholder]:Tensor(f32[2048])\n- fx_graph_module: torch.fx.GraphModule(timm_models_vision_transformer_VisionTransformer)\n- onnxfunction_dispatcher: \n- op_level_debug: False\n- onnxscript_graph: \n- onnxscript_tracer: \n- fx_name_to_onnxscript_value: Dict[length=298](\nx: `TorchScriptTensor(f32[4, 3, 512, 512])`,\np_trunk_patch_embed_proj_weight: `TorchScriptTensor(f32[1024, 3, 16, 16])`,\np_trunk_patch_embed_proj_bias: `TorchScriptTensor(f32[1024])`,\np_trunk_pos_embed: `TorchScriptTensor(f32[1, 1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_weight: `TorchScriptTensor(f32[3072, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_bias: `TorchScriptTensor(f32[3072])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_weight: `TorchScriptTensor(f32[1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_bias: `TorchScriptTensor(f32[1024])`,\n...\n)\n## Return values\n", + "text":"FX Node: placeholder:p_trunk_attn_pool_kv_bias[name=p_trunk_attn_pool_kv_bias]. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"FxOnnxInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":414 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0008", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Node: placeholder:p_trunk_attn_pool_proj_weight[name=p_trunk_attn_pool_proj_weight]. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature FxOnnxInterpreter.run_node\n- self: \n- node: fx.Node(p_trunk_attn_pool_proj_weight)[placeholder]:Tensor(f32[1024, 1024])\n- fx_graph_module: torch.fx.GraphModule(timm_models_vision_transformer_VisionTransformer)\n- onnxfunction_dispatcher: \n- op_level_debug: False\n- onnxscript_graph: \n- onnxscript_tracer: \n- fx_name_to_onnxscript_value: Dict[length=299](\nx: `TorchScriptTensor(f32[4, 3, 512, 512])`,\np_trunk_patch_embed_proj_weight: `TorchScriptTensor(f32[1024, 3, 16, 16])`,\np_trunk_patch_embed_proj_bias: `TorchScriptTensor(f32[1024])`,\np_trunk_pos_embed: `TorchScriptTensor(f32[1, 1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_weight: `TorchScriptTensor(f32[3072, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_bias: `TorchScriptTensor(f32[3072])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_weight: `TorchScriptTensor(f32[1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_bias: `TorchScriptTensor(f32[1024])`,\n...\n)\n## Return values\n", + "text":"FX Node: placeholder:p_trunk_attn_pool_proj_weight[name=p_trunk_attn_pool_proj_weight]. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"FxOnnxInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":414 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0008", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Node: placeholder:p_trunk_attn_pool_proj_bias[name=p_trunk_attn_pool_proj_bias]. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature FxOnnxInterpreter.run_node\n- self: \n- node: fx.Node(p_trunk_attn_pool_proj_bias)[placeholder]:Tensor(f32[1024])\n- fx_graph_module: torch.fx.GraphModule(timm_models_vision_transformer_VisionTransformer)\n- onnxfunction_dispatcher: \n- op_level_debug: False\n- onnxscript_graph: \n- onnxscript_tracer: \n- fx_name_to_onnxscript_value: Dict[length=300](\nx: `TorchScriptTensor(f32[4, 3, 512, 512])`,\np_trunk_patch_embed_proj_weight: `TorchScriptTensor(f32[1024, 3, 16, 16])`,\np_trunk_patch_embed_proj_bias: `TorchScriptTensor(f32[1024])`,\np_trunk_pos_embed: `TorchScriptTensor(f32[1, 1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_weight: `TorchScriptTensor(f32[3072, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_bias: `TorchScriptTensor(f32[3072])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_weight: `TorchScriptTensor(f32[1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_bias: `TorchScriptTensor(f32[1024])`,\n...\n)\n## Return values\n", + "text":"FX Node: placeholder:p_trunk_attn_pool_proj_bias[name=p_trunk_attn_pool_proj_bias]. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"FxOnnxInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":414 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0008", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Node: placeholder:p_trunk_attn_pool_norm_weight[name=p_trunk_attn_pool_norm_weight]. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature FxOnnxInterpreter.run_node\n- self: \n- node: fx.Node(p_trunk_attn_pool_norm_weight)[placeholder]:Tensor(f32[1024])\n- fx_graph_module: torch.fx.GraphModule(timm_models_vision_transformer_VisionTransformer)\n- onnxfunction_dispatcher: \n- op_level_debug: False\n- onnxscript_graph: \n- onnxscript_tracer: \n- fx_name_to_onnxscript_value: Dict[length=301](\nx: `TorchScriptTensor(f32[4, 3, 512, 512])`,\np_trunk_patch_embed_proj_weight: `TorchScriptTensor(f32[1024, 3, 16, 16])`,\np_trunk_patch_embed_proj_bias: `TorchScriptTensor(f32[1024])`,\np_trunk_pos_embed: `TorchScriptTensor(f32[1, 1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_weight: `TorchScriptTensor(f32[3072, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_bias: `TorchScriptTensor(f32[3072])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_weight: `TorchScriptTensor(f32[1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_bias: `TorchScriptTensor(f32[1024])`,\n...\n)\n## Return values\n", + "text":"FX Node: placeholder:p_trunk_attn_pool_norm_weight[name=p_trunk_attn_pool_norm_weight]. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"FxOnnxInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":414 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0008", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Node: placeholder:p_trunk_attn_pool_norm_bias[name=p_trunk_attn_pool_norm_bias]. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature FxOnnxInterpreter.run_node\n- self: \n- node: fx.Node(p_trunk_attn_pool_norm_bias)[placeholder]:Tensor(f32[1024])\n- fx_graph_module: torch.fx.GraphModule(timm_models_vision_transformer_VisionTransformer)\n- onnxfunction_dispatcher: \n- op_level_debug: False\n- onnxscript_graph: \n- onnxscript_tracer: \n- fx_name_to_onnxscript_value: Dict[length=302](\nx: `TorchScriptTensor(f32[4, 3, 512, 512])`,\np_trunk_patch_embed_proj_weight: `TorchScriptTensor(f32[1024, 3, 16, 16])`,\np_trunk_patch_embed_proj_bias: `TorchScriptTensor(f32[1024])`,\np_trunk_pos_embed: `TorchScriptTensor(f32[1, 1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_weight: `TorchScriptTensor(f32[3072, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_bias: `TorchScriptTensor(f32[3072])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_weight: `TorchScriptTensor(f32[1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_bias: `TorchScriptTensor(f32[1024])`,\n...\n)\n## Return values\n", + "text":"FX Node: placeholder:p_trunk_attn_pool_norm_bias[name=p_trunk_attn_pool_norm_bias]. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"FxOnnxInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":414 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0008", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Node: placeholder:p_trunk_attn_pool_mlp_fc1_weight[name=p_trunk_attn_pool_mlp_fc1_weight]. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature FxOnnxInterpreter.run_node\n- self: \n- node: fx.Node(p_trunk_attn_pool_mlp_fc1_weight)[placeholder]:Tensor(f32[4096, 1024])\n- fx_graph_module: torch.fx.GraphModule(timm_models_vision_transformer_VisionTransformer)\n- onnxfunction_dispatcher: \n- op_level_debug: False\n- onnxscript_graph: \n- onnxscript_tracer: \n- fx_name_to_onnxscript_value: Dict[length=303](\nx: `TorchScriptTensor(f32[4, 3, 512, 512])`,\np_trunk_patch_embed_proj_weight: `TorchScriptTensor(f32[1024, 3, 16, 16])`,\np_trunk_patch_embed_proj_bias: `TorchScriptTensor(f32[1024])`,\np_trunk_pos_embed: `TorchScriptTensor(f32[1, 1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_weight: `TorchScriptTensor(f32[3072, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_bias: `TorchScriptTensor(f32[3072])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_weight: `TorchScriptTensor(f32[1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_bias: `TorchScriptTensor(f32[1024])`,\n...\n)\n## Return values\n", + "text":"FX Node: placeholder:p_trunk_attn_pool_mlp_fc1_weight[name=p_trunk_attn_pool_mlp_fc1_weight]. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"FxOnnxInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":414 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0008", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Node: placeholder:p_trunk_attn_pool_mlp_fc1_bias[name=p_trunk_attn_pool_mlp_fc1_bias]. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature FxOnnxInterpreter.run_node\n- self: \n- node: fx.Node(p_trunk_attn_pool_mlp_fc1_bias)[placeholder]:Tensor(f32[4096])\n- fx_graph_module: torch.fx.GraphModule(timm_models_vision_transformer_VisionTransformer)\n- onnxfunction_dispatcher: \n- op_level_debug: False\n- onnxscript_graph: \n- onnxscript_tracer: \n- fx_name_to_onnxscript_value: Dict[length=304](\nx: `TorchScriptTensor(f32[4, 3, 512, 512])`,\np_trunk_patch_embed_proj_weight: `TorchScriptTensor(f32[1024, 3, 16, 16])`,\np_trunk_patch_embed_proj_bias: `TorchScriptTensor(f32[1024])`,\np_trunk_pos_embed: `TorchScriptTensor(f32[1, 1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_weight: `TorchScriptTensor(f32[3072, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_bias: `TorchScriptTensor(f32[3072])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_weight: `TorchScriptTensor(f32[1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_bias: `TorchScriptTensor(f32[1024])`,\n...\n)\n## Return values\n", + "text":"FX Node: placeholder:p_trunk_attn_pool_mlp_fc1_bias[name=p_trunk_attn_pool_mlp_fc1_bias]. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"FxOnnxInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":414 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0008", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Node: placeholder:p_trunk_attn_pool_mlp_fc2_weight[name=p_trunk_attn_pool_mlp_fc2_weight]. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature FxOnnxInterpreter.run_node\n- self: \n- node: fx.Node(p_trunk_attn_pool_mlp_fc2_weight)[placeholder]:Tensor(f32[1024, 4096])\n- fx_graph_module: torch.fx.GraphModule(timm_models_vision_transformer_VisionTransformer)\n- onnxfunction_dispatcher: \n- op_level_debug: False\n- onnxscript_graph: \n- onnxscript_tracer: \n- fx_name_to_onnxscript_value: Dict[length=305](\nx: `TorchScriptTensor(f32[4, 3, 512, 512])`,\np_trunk_patch_embed_proj_weight: `TorchScriptTensor(f32[1024, 3, 16, 16])`,\np_trunk_patch_embed_proj_bias: `TorchScriptTensor(f32[1024])`,\np_trunk_pos_embed: `TorchScriptTensor(f32[1, 1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_weight: `TorchScriptTensor(f32[3072, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_bias: `TorchScriptTensor(f32[3072])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_weight: `TorchScriptTensor(f32[1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_bias: `TorchScriptTensor(f32[1024])`,\n...\n)\n## Return values\n", + "text":"FX Node: placeholder:p_trunk_attn_pool_mlp_fc2_weight[name=p_trunk_attn_pool_mlp_fc2_weight]. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"FxOnnxInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":414 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0008", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Node: placeholder:p_trunk_attn_pool_mlp_fc2_bias[name=p_trunk_attn_pool_mlp_fc2_bias]. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature FxOnnxInterpreter.run_node\n- self: \n- node: fx.Node(p_trunk_attn_pool_mlp_fc2_bias)[placeholder]:Tensor(f32[1024])\n- fx_graph_module: torch.fx.GraphModule(timm_models_vision_transformer_VisionTransformer)\n- onnxfunction_dispatcher: \n- op_level_debug: False\n- onnxscript_graph: \n- onnxscript_tracer: \n- fx_name_to_onnxscript_value: Dict[length=306](\nx: `TorchScriptTensor(f32[4, 3, 512, 512])`,\np_trunk_patch_embed_proj_weight: `TorchScriptTensor(f32[1024, 3, 16, 16])`,\np_trunk_patch_embed_proj_bias: `TorchScriptTensor(f32[1024])`,\np_trunk_pos_embed: `TorchScriptTensor(f32[1, 1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_weight: `TorchScriptTensor(f32[3072, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_bias: `TorchScriptTensor(f32[3072])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_weight: `TorchScriptTensor(f32[1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_bias: `TorchScriptTensor(f32[1024])`,\n...\n)\n## Return values\n", + "text":"FX Node: placeholder:p_trunk_attn_pool_mlp_fc2_bias[name=p_trunk_attn_pool_mlp_fc2_bias]. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"FxOnnxInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":414 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0008", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Node: placeholder:x[name=x]. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature FxOnnxInterpreter.run_node\n- self: \n- node: fx.Node(x)[placeholder]:Tensor(f32[4, 3, 512, 512])\n- fx_graph_module: torch.fx.GraphModule(timm_layers_patch_embed_PatchEmbed)\n- onnxfunction_dispatcher: \n- op_level_debug: False\n- onnxscript_graph: \n- onnxscript_tracer: \n- fx_name_to_onnxscript_value: Dict[length=0](\nNone)\n## Return values\n", + "text":"FX Node: placeholder:x[name=x]. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"FxOnnxInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":414 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0008", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Node: placeholder:p_trunk_patch_embed_proj_weight[name=p_trunk_patch_embed_proj_weight]. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature FxOnnxInterpreter.run_node\n- self: \n- node: fx.Node(p_trunk_patch_embed_proj_weight)[placeholder]:Tensor(f32[1024, 3, 16, 16])\n- fx_graph_module: torch.fx.GraphModule(timm_layers_patch_embed_PatchEmbed)\n- onnxfunction_dispatcher: \n- op_level_debug: False\n- onnxscript_graph: \n- onnxscript_tracer: \n- fx_name_to_onnxscript_value: Dict[length=1](\nx: `TorchScriptTensor(f32[4, 3, 512, 512])`,\n)\n## Return values\n", + "text":"FX Node: placeholder:p_trunk_patch_embed_proj_weight[name=p_trunk_patch_embed_proj_weight]. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"FxOnnxInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":414 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0008", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Node: placeholder:p_trunk_patch_embed_proj_bias[name=p_trunk_patch_embed_proj_bias]. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature FxOnnxInterpreter.run_node\n- self: \n- node: fx.Node(p_trunk_patch_embed_proj_bias)[placeholder]:Tensor(f32[1024])\n- fx_graph_module: torch.fx.GraphModule(timm_layers_patch_embed_PatchEmbed)\n- onnxfunction_dispatcher: \n- op_level_debug: False\n- onnxscript_graph: \n- onnxscript_tracer: \n- fx_name_to_onnxscript_value: Dict[length=2](\nx: `TorchScriptTensor(f32[4, 3, 512, 512])`,\np_trunk_patch_embed_proj_weight: `TorchScriptTensor(f32[1024, 3, 16, 16])`,\n)\n## Return values\n", + "text":"FX Node: placeholder:p_trunk_patch_embed_proj_bias[name=p_trunk_patch_embed_proj_bias]. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"FxOnnxInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":414 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0008", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Node: placeholder:x[name=x]. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature FxOnnxInterpreter.run_node\n- self: \n- node: fx.Node(x)[placeholder]:Tensor(f32[4, 3, 512, 512])\n- fx_graph_module: torch.fx.GraphModule(torch_nn_modules_conv_Conv2d)\n- onnxfunction_dispatcher: \n- op_level_debug: False\n- onnxscript_graph: \n- onnxscript_tracer: \n- fx_name_to_onnxscript_value: Dict[length=0](\nNone)\n## Return values\n", + "text":"FX Node: placeholder:x[name=x]. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"FxOnnxInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":414 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0008", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Node: placeholder:p_trunk_patch_embed_proj_weight[name=p_trunk_patch_embed_proj_weight]. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature FxOnnxInterpreter.run_node\n- self: \n- node: fx.Node(p_trunk_patch_embed_proj_weight)[placeholder]:Tensor(f32[1024, 3, 16, 16])\n- fx_graph_module: torch.fx.GraphModule(torch_nn_modules_conv_Conv2d)\n- onnxfunction_dispatcher: \n- op_level_debug: False\n- onnxscript_graph: \n- onnxscript_tracer: \n- fx_name_to_onnxscript_value: Dict[length=1](\nx: `TorchScriptTensor(f32[4, 3, 512, 512])`,\n)\n## Return values\n", + "text":"FX Node: placeholder:p_trunk_patch_embed_proj_weight[name=p_trunk_patch_embed_proj_weight]. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"FxOnnxInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":414 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0008", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Node: placeholder:p_trunk_patch_embed_proj_bias[name=p_trunk_patch_embed_proj_bias]. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature FxOnnxInterpreter.run_node\n- self: \n- node: fx.Node(p_trunk_patch_embed_proj_bias)[placeholder]:Tensor(f32[1024])\n- fx_graph_module: torch.fx.GraphModule(torch_nn_modules_conv_Conv2d)\n- onnxfunction_dispatcher: \n- op_level_debug: False\n- onnxscript_graph: \n- onnxscript_tracer: \n- fx_name_to_onnxscript_value: Dict[length=2](\nx: `TorchScriptTensor(f32[4, 3, 512, 512])`,\np_trunk_patch_embed_proj_weight: `TorchScriptTensor(f32[1024, 3, 16, 16])`,\n)\n## Return values\n", + "text":"FX Node: placeholder:p_trunk_patch_embed_proj_bias[name=p_trunk_patch_embed_proj_bias]. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"FxOnnxInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":414 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0008", + "stacks":[] + }, + { + "message":{ + "markdown":"Searching operator overload: 'aten.convolution.default' in onnx registry...\n\n\n## Additional Message:\n\n## Function Signature\n### Function Signature OnnxFunctionDispatcher.get_function_overloads\n- self: \n- node: fx.Node(aten.convolution.default)[call_function]:Tensor(f32[4, 1024, 32, 32])\n- diagnostic_context: \n## Return values\nList[length=1](\nregistration.ONNXFunction(aten::convolution.default, is_custom=False, is_complex=False),\n)", + "text":"Searching operator overload: 'aten.convolution.default' in onnx registry...\n" + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"OnnxFunctionDispatcher.get_function_overloads" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/onnxfunction_dispatcher.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":353 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0016", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Node: aten.convolution.default. \nONNX Node: aten_convolution[opset=pkg.onnxscript.torch_lib;is_custom=False]. \n\n\n## Additional Message:\n\n## Function Signature\n### Function Signature OnnxFunctionDispatcher._find_the_perfect_or_nearest_match_onnxfunction\n- self: \n- node: fx.Node(aten.convolution.default)[call_function]:Tensor(f32[4, 1024, 32, 32])\n- default_and_custom_functions: List[length=1](\nregistration.ONNXFunction(aten::convolution.default, is_custom=False, is_complex=False),\n)\n- onnx_args: Tuple[length=9](\n`TorchScriptTensor(f32[4, 3, 512, 512])`,\n`TorchScriptTensor(f32[1024, 3, 16, 16])`,\n`TorchScriptTensor(f32[1024])`,\nList[length=2](\n16,\n16,\n),\nList[length=2](\n0,\n0,\n),\nList[length=2](\n1,\n1,\n),\nFalse,\nList[length=2](\n0,\n0,\n),\n1,\n)\n- onnx_kwargs: Dict[length=0](\nNone)\n- diagnostic_context: \n## Checking perfect match...\n`TracedOnnxFunction(aten_convolution)`\nmatch score: -1\n## Return values\n`TracedOnnxFunction(aten_convolution)`", + "text":"FX Node: aten.convolution.default. \nONNX Node: aten_convolution[opset=pkg.onnxscript.torch_lib;is_custom=False]. \n" + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"OnnxFunctionDispatcher._find_the_perfect_or_nearest_match_onnxfunction" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/onnxfunction_dispatcher.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":199 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0014", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Node: call_function:aten.convolution.default[name=convolution]. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature FxOnnxInterpreter.run_node\n- self: \n- node: fx.Node(aten.convolution.default)[call_function]:Tensor(f32[4, 1024, 32, 32])\n- fx_graph_module: torch.fx.GraphModule(torch_nn_modules_conv_Conv2d)\n- onnxfunction_dispatcher: \n- op_level_debug: False\n- onnxscript_graph: \n- onnxscript_tracer: \n- fx_name_to_onnxscript_value: Dict[length=3](\nx: `TorchScriptTensor(f32[4, 3, 512, 512])`,\np_trunk_patch_embed_proj_weight: `TorchScriptTensor(f32[1024, 3, 16, 16])`,\np_trunk_patch_embed_proj_bias: `TorchScriptTensor(f32[1024])`,\n)\n## PyTorch source information\n```\n File \"/home/thebears/.local/lib/python3.10/site-packages/open_clip/timm_model.py\", line 196, in forward\n x = self.trunk(x)\n File \"/home/thebears/.local/lib/python3.10/site-packages/torch/nn/modules/module.py\", line 1725, in _call_impl\n return forward_call(*args, **kwargs)\n File \"/home/thebears/.local/lib/python3.10/site-packages/timm/models/vision_transformer.py\", line 853, in forward\n x = self.forward_features(x)\n File \"/home/thebears/.local/lib/python3.10/site-packages/timm/models/vision_transformer.py\", line 827, in forward_features\n x = self.patch_embed(x)\n File \"/home/thebears/.local/lib/python3.10/site-packages/torch/nn/modules/module.py\", line 1725, in _call_impl\n return forward_call(*args, **kwargs)\n File \"/home/thebears/.local/lib/python3.10/site-packages/timm/layers/patch_embed.py\", line 131, in forward\n x = self.proj(x)\n\n```\n## Return values\n", + "text":"FX Node: call_function:aten.convolution.default[name=convolution]. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"FxOnnxInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":414 + } + } + }, + { + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/open_clip/timm_model.py" + }, + "region":{ + "snippet":{ + "text":"x = self.trunk(x)" + }, + "startLine":196 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0008", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Node: output:output[name=output]. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature FxOnnxInterpreter.run_node\n- self: \n- node: fx.Node(output)[output]:None\n- fx_graph_module: torch.fx.GraphModule(torch_nn_modules_conv_Conv2d)\n- onnxfunction_dispatcher: \n- op_level_debug: False\n- onnxscript_graph: \n- onnxscript_tracer: \n- fx_name_to_onnxscript_value: Dict[length=4](\nx: `TorchScriptTensor(f32[4, 3, 512, 512])`,\np_trunk_patch_embed_proj_weight: `TorchScriptTensor(f32[1024, 3, 16, 16])`,\np_trunk_patch_embed_proj_bias: `TorchScriptTensor(f32[1024])`,\nconvolution: `TorchScriptTensor(f32[4, 1024, 32, 32])`,\n)\n## Return values\n", + "text":"FX Node: output:output[name=output]. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"FxOnnxInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":414 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0008", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Graph: torch_nn_modules_conv_Conv2d. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature FxOnnxInterpreter.run\n- self: \n- fx_graph_module: torch.fx.GraphModule(torch_nn_modules_conv_Conv2d)\n- onnxfunction_dispatcher: \n- op_level_debug: False\n- parent_onnxscript_graph: \n## Return values\n", + "text":"FX Graph: torch_nn_modules_conv_Conv2d. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"FxOnnxInterpreter.run" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":496 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0007", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Node: call_module:trunk_patch_embed_proj_1[name=trunk_patch_embed_proj_1]. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature FxOnnxInterpreter.run_node\n- self: \n- node: fx.Node(trunk_patch_embed_proj_1)[call_module]:Tensor(f32[4, 1024, 32, 32])\n- fx_graph_module: torch.fx.GraphModule(timm_layers_patch_embed_PatchEmbed)\n- onnxfunction_dispatcher: \n- op_level_debug: False\n- onnxscript_graph: \n- onnxscript_tracer: \n- fx_name_to_onnxscript_value: Dict[length=3](\nx: `TorchScriptTensor(f32[4, 3, 512, 512])`,\np_trunk_patch_embed_proj_weight: `TorchScriptTensor(f32[1024, 3, 16, 16])`,\np_trunk_patch_embed_proj_bias: `TorchScriptTensor(f32[1024])`,\n)\n## PyTorch source information\n```\n File \"/home/thebears/.local/lib/python3.10/site-packages/open_clip/timm_model.py\", line 196, in forward\n x = self.trunk(x)\n File \"/home/thebears/.local/lib/python3.10/site-packages/torch/nn/modules/module.py\", line 1725, in _call_impl\n return forward_call(*args, **kwargs)\n File \"/home/thebears/.local/lib/python3.10/site-packages/timm/models/vision_transformer.py\", line 853, in forward\n x = self.forward_features(x)\n File \"/home/thebears/.local/lib/python3.10/site-packages/timm/models/vision_transformer.py\", line 827, in forward_features\n x = self.patch_embed(x)\n File \"/home/thebears/.local/lib/python3.10/site-packages/torch/nn/modules/module.py\", line 1725, in _call_impl\n return forward_call(*args, **kwargs)\n File \"/home/thebears/.local/lib/python3.10/site-packages/timm/layers/patch_embed.py\", line 131, in forward\n x = self.proj(x)\n\n```\n## Return values\n", + "text":"FX Node: call_module:trunk_patch_embed_proj_1[name=trunk_patch_embed_proj_1]. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"FxOnnxInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":414 + } + } + }, + { + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/open_clip/timm_model.py" + }, + "region":{ + "snippet":{ + "text":"x = self.trunk(x)" + }, + "startLine":196 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0008", + "stacks":[] + }, + { + "message":{ + "markdown":"Searching operator overload: 'aten.view.default' in onnx registry...\n\n\n## Additional Message:\n\n## Function Signature\n### Function Signature OnnxFunctionDispatcher.get_function_overloads\n- self: \n- node: fx.Node(aten.view.default)[call_function]:Tensor(f32[4, 1024, 1024])\n- diagnostic_context: \n## Return values\nList[length=1](\nregistration.ONNXFunction(aten::view.default, is_custom=False, is_complex=False),\n)", + "text":"Searching operator overload: 'aten.view.default' in onnx registry...\n" + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"OnnxFunctionDispatcher.get_function_overloads" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/onnxfunction_dispatcher.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":353 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0016", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Node: aten.view.default. \nONNX Node: aten_view[opset=pkg.onnxscript.torch_lib;is_custom=False]. \n\n\n## Additional Message:\n\n## Function Signature\n### Function Signature OnnxFunctionDispatcher._find_the_perfect_or_nearest_match_onnxfunction\n- self: \n- node: fx.Node(aten.view.default)[call_function]:Tensor(f32[4, 1024, 1024])\n- default_and_custom_functions: List[length=1](\nregistration.ONNXFunction(aten::view.default, is_custom=False, is_complex=False),\n)\n- onnx_args: Tuple[length=2](\n`TorchScriptTensor(f32[4, 1024, 32, 32])`,\nList[length=3](\n4,\n1024,\n1024,\n),\n)\n- onnx_kwargs: Dict[length=0](\nNone)\n- diagnostic_context: \n## Checking perfect match...\n`TracedOnnxFunction(aten_view)`\nmatch score: 2\n## Return values\n`TracedOnnxFunction(aten_view)`", + "text":"FX Node: aten.view.default. \nONNX Node: aten_view[opset=pkg.onnxscript.torch_lib;is_custom=False]. \n" + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"OnnxFunctionDispatcher._find_the_perfect_or_nearest_match_onnxfunction" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/onnxfunction_dispatcher.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":199 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0014", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Node: call_function:aten.view.default[name=view]. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature FxOnnxInterpreter.run_node\n- self: \n- node: fx.Node(aten.view.default)[call_function]:Tensor(f32[4, 1024, 1024])\n- fx_graph_module: torch.fx.GraphModule(timm_layers_patch_embed_PatchEmbed)\n- onnxfunction_dispatcher: \n- op_level_debug: False\n- onnxscript_graph: \n- onnxscript_tracer: \n- fx_name_to_onnxscript_value: Dict[length=4](\nx: `TorchScriptTensor(f32[4, 3, 512, 512])`,\np_trunk_patch_embed_proj_weight: `TorchScriptTensor(f32[1024, 3, 16, 16])`,\np_trunk_patch_embed_proj_bias: `TorchScriptTensor(f32[1024])`,\ntrunk_patch_embed_proj_1: `TorchScriptTensor(f32[4, 1024, 32, 32])`,\n)\n## PyTorch source information\n```\n File \"/home/thebears/.local/lib/python3.10/site-packages/open_clip/timm_model.py\", line 196, in forward\n x = self.trunk(x)\n File \"/home/thebears/.local/lib/python3.10/site-packages/torch/nn/modules/module.py\", line 1725, in _call_impl\n return forward_call(*args, **kwargs)\n File \"/home/thebears/.local/lib/python3.10/site-packages/timm/models/vision_transformer.py\", line 853, in forward\n x = self.forward_features(x)\n File \"/home/thebears/.local/lib/python3.10/site-packages/timm/models/vision_transformer.py\", line 827, in forward_features\n x = self.patch_embed(x)\n File \"/home/thebears/.local/lib/python3.10/site-packages/torch/nn/modules/module.py\", line 1725, in _call_impl\n return forward_call(*args, **kwargs)\n File \"/home/thebears/.local/lib/python3.10/site-packages/timm/layers/patch_embed.py\", line 133, in forward\n x = x.flatten(2).transpose(1, 2) # NCHW -> NLC\n\n```\n## Return values\n", + "text":"FX Node: call_function:aten.view.default[name=view]. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"FxOnnxInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":414 + } + } + }, + { + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/open_clip/timm_model.py" + }, + "region":{ + "snippet":{ + "text":"x = self.trunk(x)" + }, + "startLine":196 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0008", + "stacks":[] + }, + { + "message":{ + "markdown":"Searching operator overload: 'aten.transpose.int' in onnx registry...\n\n\n## Additional Message:\n\n## Function Signature\n### Function Signature OnnxFunctionDispatcher.get_function_overloads\n- self: \n- node: fx.Node(aten.transpose.int)[call_function]:Tensor(f32[4, 1024, 1024])\n- diagnostic_context: \n## Return values\nList[length=1](\nregistration.ONNXFunction(aten::transpose.int, is_custom=False, is_complex=False),\n)", + "text":"Searching operator overload: 'aten.transpose.int' in onnx registry...\n" + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"OnnxFunctionDispatcher.get_function_overloads" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/onnxfunction_dispatcher.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":353 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0016", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Node: aten.transpose.int. \nONNX Node: aten_transpose[opset=pkg.onnxscript.torch_lib;is_custom=False]. \n\n\n## Additional Message:\n\n## Function Signature\n### Function Signature OnnxFunctionDispatcher._find_the_perfect_or_nearest_match_onnxfunction\n- self: \n- node: fx.Node(aten.transpose.int)[call_function]:Tensor(f32[4, 1024, 1024])\n- default_and_custom_functions: List[length=1](\nregistration.ONNXFunction(aten::transpose.int, is_custom=False, is_complex=False),\n)\n- onnx_args: Tuple[length=3](\n`TorchScriptTensor(f32[4, 1024, 1024])`,\n1,\n2,\n)\n- onnx_kwargs: Dict[length=0](\nNone)\n- diagnostic_context: \n## Checking perfect match...\n`TracedOnnxFunction(aten_transpose)`\nmatch score: 1\n## Return values\n`TracedOnnxFunction(aten_transpose)`", + "text":"FX Node: aten.transpose.int. \nONNX Node: aten_transpose[opset=pkg.onnxscript.torch_lib;is_custom=False]. \n" + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"OnnxFunctionDispatcher._find_the_perfect_or_nearest_match_onnxfunction" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/onnxfunction_dispatcher.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":199 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0014", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Node: call_function:aten.transpose.int[name=transpose]. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature FxOnnxInterpreter.run_node\n- self: \n- node: fx.Node(aten.transpose.int)[call_function]:Tensor(f32[4, 1024, 1024])\n- fx_graph_module: torch.fx.GraphModule(timm_layers_patch_embed_PatchEmbed)\n- onnxfunction_dispatcher: \n- op_level_debug: False\n- onnxscript_graph: \n- onnxscript_tracer: \n- fx_name_to_onnxscript_value: Dict[length=5](\nx: `TorchScriptTensor(f32[4, 3, 512, 512])`,\np_trunk_patch_embed_proj_weight: `TorchScriptTensor(f32[1024, 3, 16, 16])`,\np_trunk_patch_embed_proj_bias: `TorchScriptTensor(f32[1024])`,\ntrunk_patch_embed_proj_1: `TorchScriptTensor(f32[4, 1024, 32, 32])`,\nview: `TorchScriptTensor(f32[4, 1024, 1024])`,\n)\n## PyTorch source information\n```\n File \"/home/thebears/.local/lib/python3.10/site-packages/open_clip/timm_model.py\", line 196, in forward\n x = self.trunk(x)\n File \"/home/thebears/.local/lib/python3.10/site-packages/torch/nn/modules/module.py\", line 1725, in _call_impl\n return forward_call(*args, **kwargs)\n File \"/home/thebears/.local/lib/python3.10/site-packages/timm/models/vision_transformer.py\", line 853, in forward\n x = self.forward_features(x)\n File \"/home/thebears/.local/lib/python3.10/site-packages/timm/models/vision_transformer.py\", line 827, in forward_features\n x = self.patch_embed(x)\n File \"/home/thebears/.local/lib/python3.10/site-packages/torch/nn/modules/module.py\", line 1725, in _call_impl\n return forward_call(*args, **kwargs)\n File \"/home/thebears/.local/lib/python3.10/site-packages/timm/layers/patch_embed.py\", line 133, in forward\n x = x.flatten(2).transpose(1, 2) # NCHW -> NLC\n\n```\n## Return values\n", + "text":"FX Node: call_function:aten.transpose.int[name=transpose]. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"FxOnnxInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":414 + } + } + }, + { + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/open_clip/timm_model.py" + }, + "region":{ + "snippet":{ + "text":"x = self.trunk(x)" + }, + "startLine":196 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0008", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Node: output:output[name=output]. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature FxOnnxInterpreter.run_node\n- self: \n- node: fx.Node(output)[output]:None\n- fx_graph_module: torch.fx.GraphModule(timm_layers_patch_embed_PatchEmbed)\n- onnxfunction_dispatcher: \n- op_level_debug: False\n- onnxscript_graph: \n- onnxscript_tracer: \n- fx_name_to_onnxscript_value: Dict[length=6](\nx: `TorchScriptTensor(f32[4, 3, 512, 512])`,\np_trunk_patch_embed_proj_weight: `TorchScriptTensor(f32[1024, 3, 16, 16])`,\np_trunk_patch_embed_proj_bias: `TorchScriptTensor(f32[1024])`,\ntrunk_patch_embed_proj_1: `TorchScriptTensor(f32[4, 1024, 32, 32])`,\nview: `TorchScriptTensor(f32[4, 1024, 1024])`,\ntranspose: `TorchScriptTensor(f32[4, 1024, 1024])`,\n)\n## Return values\n", + "text":"FX Node: output:output[name=output]. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"FxOnnxInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":414 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0008", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Graph: timm_layers_patch_embed_PatchEmbed. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature FxOnnxInterpreter.run\n- self: \n- fx_graph_module: torch.fx.GraphModule(timm_layers_patch_embed_PatchEmbed)\n- onnxfunction_dispatcher: \n- op_level_debug: False\n- parent_onnxscript_graph: \n## Return values\n", + "text":"FX Graph: timm_layers_patch_embed_PatchEmbed. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"FxOnnxInterpreter.run" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":496 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0007", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Node: call_module:trunk_patch_embed_1[name=trunk_patch_embed_1]. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature FxOnnxInterpreter.run_node\n- self: \n- node: fx.Node(trunk_patch_embed_1)[call_module]:Tensor(f32[4, 1024, 1024])\n- fx_graph_module: torch.fx.GraphModule(timm_models_vision_transformer_VisionTransformer)\n- onnxfunction_dispatcher: \n- op_level_debug: False\n- onnxscript_graph: \n- onnxscript_tracer: \n- fx_name_to_onnxscript_value: Dict[length=307](\nx: `TorchScriptTensor(f32[4, 3, 512, 512])`,\np_trunk_patch_embed_proj_weight: `TorchScriptTensor(f32[1024, 3, 16, 16])`,\np_trunk_patch_embed_proj_bias: `TorchScriptTensor(f32[1024])`,\np_trunk_pos_embed: `TorchScriptTensor(f32[1, 1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_weight: `TorchScriptTensor(f32[3072, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_bias: `TorchScriptTensor(f32[3072])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_weight: `TorchScriptTensor(f32[1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_bias: `TorchScriptTensor(f32[1024])`,\n...\n)\n## PyTorch source information\n```\n File \"/home/thebears/.local/lib/python3.10/site-packages/open_clip/timm_model.py\", line 196, in forward\n x = self.trunk(x)\n File \"/home/thebears/.local/lib/python3.10/site-packages/torch/nn/modules/module.py\", line 1725, in _call_impl\n return forward_call(*args, **kwargs)\n File \"/home/thebears/.local/lib/python3.10/site-packages/timm/models/vision_transformer.py\", line 853, in forward\n x = self.forward_features(x)\n File \"/home/thebears/.local/lib/python3.10/site-packages/timm/models/vision_transformer.py\", line 827, in forward_features\n x = self.patch_embed(x)\n File \"/home/thebears/.local/lib/python3.10/site-packages/torch/nn/modules/module.py\", line 1725, in _call_impl\n return forward_call(*args, **kwargs)\n File \"/home/thebears/.local/lib/python3.10/site-packages/timm/layers/patch_embed.py\", line 131, in forward\n x = self.proj(x)\n\n```\n## Return values\n", + "text":"FX Node: call_module:trunk_patch_embed_1[name=trunk_patch_embed_1]. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"FxOnnxInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":414 + } + } + }, + { + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/open_clip/timm_model.py" + }, + "region":{ + "snippet":{ + "text":"x = self.trunk(x)" + }, + "startLine":196 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0008", + "stacks":[] + }, + { + "message":{ + "markdown":"Searching operator overload: 'aten.add.Tensor' in onnx registry...\n\n\n## Additional Message:\n\n## Function Signature\n### Function Signature OnnxFunctionDispatcher.get_function_overloads\n- self: \n- node: fx.Node(aten.add.Tensor)[call_function]:Tensor(f32[4, 1024, 1024])\n- diagnostic_context: \n## Return values\nList[length=2](\nregistration.ONNXFunction(aten::add.Tensor, is_custom=False, is_complex=False),\nregistration.ONNXFunction(aten::add.Tensor, is_custom=False, is_complex=False),\n)", + "text":"Searching operator overload: 'aten.add.Tensor' in onnx registry...\n" + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"OnnxFunctionDispatcher.get_function_overloads" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/onnxfunction_dispatcher.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":353 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0016", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Node: aten.add.Tensor. \nONNX Node: aten_add[opset=pkg.onnxscript.torch_lib;is_custom=False]. \nONNX Node: aten_logical_or[opset=pkg.onnxscript.torch_lib;is_custom=False]. \n\n\n## Additional Message:\n\n## Function Signature\n### Function Signature OnnxFunctionDispatcher._find_the_perfect_or_nearest_match_onnxfunction\n- self: \n- node: fx.Node(aten.add.Tensor)[call_function]:Tensor(f32[4, 1024, 1024])\n- default_and_custom_functions: List[length=2](\nregistration.ONNXFunction(aten::add.Tensor, is_custom=False, is_complex=False),\nregistration.ONNXFunction(aten::add.Tensor, is_custom=False, is_complex=False),\n)\n- onnx_args: Tuple[length=2](\n`TorchScriptTensor(f32[4, 1024, 1024])`,\n`TorchScriptTensor(f32[1, 1024, 1024])`,\n)\n- onnx_kwargs: Dict[length=1](\nalpha: 1,\n)\n- diagnostic_context: \n## Checking perfect match...\n`TracedOnnxFunction(aten_logical_or)`\n### Failed: attribute mismatch!\nActual {'alpha'} vs expected set()\nThe function is not a nearest match candidate.\n## Checking perfect match...\n`TracedOnnxFunction(aten_add)`\n### Failed: attribute 'alpha' type mismatch!\nActual vs\nExpected AttrType.FLOAT\nmatch score: 1\n### Exact match is not found!\nCannot find a perfect match of symbolic overload, a nearest match is found. Please check the ONNX output carefully. \n\n## Return values\n`TracedOnnxFunction(aten_add)`", + "text":"FX Node: aten.add.Tensor. \nONNX Node: aten_add[opset=pkg.onnxscript.torch_lib;is_custom=False]. \nONNX Node: aten_logical_or[opset=pkg.onnxscript.torch_lib;is_custom=False]. \n" + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"fail", + "level":"warning", + "locations":[ + { + "message":{ + "text":"OnnxFunctionDispatcher._find_the_perfect_or_nearest_match_onnxfunction" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/onnxfunction_dispatcher.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":199 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0014", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Node: call_function:aten.add.Tensor[name=add]. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature FxOnnxInterpreter.run_node\n- self: \n- node: fx.Node(aten.add.Tensor)[call_function]:Tensor(f32[4, 1024, 1024])\n- fx_graph_module: torch.fx.GraphModule(timm_models_vision_transformer_VisionTransformer)\n- onnxfunction_dispatcher: \n- op_level_debug: False\n- onnxscript_graph: \n- onnxscript_tracer: \n- fx_name_to_onnxscript_value: Dict[length=308](\nx: `TorchScriptTensor(f32[4, 3, 512, 512])`,\np_trunk_patch_embed_proj_weight: `TorchScriptTensor(f32[1024, 3, 16, 16])`,\np_trunk_patch_embed_proj_bias: `TorchScriptTensor(f32[1024])`,\np_trunk_pos_embed: `TorchScriptTensor(f32[1, 1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_weight: `TorchScriptTensor(f32[3072, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_bias: `TorchScriptTensor(f32[3072])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_weight: `TorchScriptTensor(f32[1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_bias: `TorchScriptTensor(f32[1024])`,\n...\n)\n## PyTorch source information\n```\n File \"/home/thebears/.local/lib/python3.10/site-packages/open_clip/timm_model.py\", line 196, in forward\n x = self.trunk(x)\n File \"/home/thebears/.local/lib/python3.10/site-packages/torch/nn/modules/module.py\", line 1725, in _call_impl\n return forward_call(*args, **kwargs)\n File \"/home/thebears/.local/lib/python3.10/site-packages/timm/models/vision_transformer.py\", line 853, in forward\n x = self.forward_features(x)\n File \"/home/thebears/.local/lib/python3.10/site-packages/timm/models/vision_transformer.py\", line 828, in forward_features\n x = self._pos_embed(x)\n File \"/home/thebears/.local/lib/python3.10/site-packages/timm/models/vision_transformer.py\", line 718, in _pos_embed\n x = x + pos_embed\n\n```\n## Return values\n", + "text":"FX Node: call_function:aten.add.Tensor[name=add]. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"FxOnnxInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":414 + } + } + }, + { + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/open_clip/timm_model.py" + }, + "region":{ + "snippet":{ + "text":"x = self.trunk(x)" + }, + "startLine":196 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0008", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Node: placeholder:add[name=add]. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature FxOnnxInterpreter.run_node\n- self: \n- node: fx.Node(add)[placeholder]:Tensor(f32[4, 1024, 1024])\n- fx_graph_module: torch.fx.GraphModule(torch_nn_modules_dropout_Dropout)\n- onnxfunction_dispatcher: \n- op_level_debug: False\n- onnxscript_graph: \n- onnxscript_tracer: \n- fx_name_to_onnxscript_value: Dict[length=0](\nNone)\n## PyTorch source information\n```\n File \"/home/thebears/.local/lib/python3.10/site-packages/open_clip/timm_model.py\", line 196, in forward\n x = self.trunk(x)\n File \"/home/thebears/.local/lib/python3.10/site-packages/torch/nn/modules/module.py\", line 1725, in _call_impl\n return forward_call(*args, **kwargs)\n File \"/home/thebears/.local/lib/python3.10/site-packages/timm/models/vision_transformer.py\", line 853, in forward\n x = self.forward_features(x)\n File \"/home/thebears/.local/lib/python3.10/site-packages/timm/models/vision_transformer.py\", line 828, in forward_features\n x = self._pos_embed(x)\n File \"/home/thebears/.local/lib/python3.10/site-packages/timm/models/vision_transformer.py\", line 718, in _pos_embed\n x = x + pos_embed\n\n```\n## Return values\n", + "text":"FX Node: placeholder:add[name=add]. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"FxOnnxInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":414 + } + } + }, + { + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/open_clip/timm_model.py" + }, + "region":{ + "snippet":{ + "text":"x = self.trunk(x)" + }, + "startLine":196 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0008", + "stacks":[] + }, + { + "message":{ + "markdown":"Searching operator overload: 'aten.clone.default' in onnx registry...\n\n\n## Additional Message:\n\n## Function Signature\n### Function Signature OnnxFunctionDispatcher.get_function_overloads\n- self: \n- node: fx.Node(aten.clone.default)[call_function]:Tensor(f32[4, 1024, 1024])\n- diagnostic_context: \n## Return values\nList[length=1](\nregistration.ONNXFunction(aten::clone.default, is_custom=False, is_complex=False),\n)", + "text":"Searching operator overload: 'aten.clone.default' in onnx registry...\n" + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"OnnxFunctionDispatcher.get_function_overloads" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/onnxfunction_dispatcher.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":353 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0016", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Node: aten.clone.default. \nONNX Node: aten_clone[opset=pkg.onnxscript.torch_lib;is_custom=False]. \n\n\n## Additional Message:\n\n## Function Signature\n### Function Signature OnnxFunctionDispatcher._find_the_perfect_or_nearest_match_onnxfunction\n- self: \n- node: fx.Node(aten.clone.default)[call_function]:Tensor(f32[4, 1024, 1024])\n- default_and_custom_functions: List[length=1](\nregistration.ONNXFunction(aten::clone.default, is_custom=False, is_complex=False),\n)\n- onnx_args: Tuple[length=1](\n`TorchScriptTensor(f32[4, 1024, 1024])`,\n)\n- onnx_kwargs: Dict[length=0](\nNone)\n- diagnostic_context: \n## Checking perfect match...\n`TracedOnnxFunction(aten_clone)`\nmatch score: 1\n## Return values\n`TracedOnnxFunction(aten_clone)`", + "text":"FX Node: aten.clone.default. \nONNX Node: aten_clone[opset=pkg.onnxscript.torch_lib;is_custom=False]. \n" + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"OnnxFunctionDispatcher._find_the_perfect_or_nearest_match_onnxfunction" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/onnxfunction_dispatcher.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":199 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0014", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Node: call_function:aten.clone.default[name=clone]. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature FxOnnxInterpreter.run_node\n- self: \n- node: fx.Node(aten.clone.default)[call_function]:Tensor(f32[4, 1024, 1024])\n- fx_graph_module: torch.fx.GraphModule(torch_nn_modules_dropout_Dropout)\n- onnxfunction_dispatcher: \n- op_level_debug: False\n- onnxscript_graph: \n- onnxscript_tracer: \n- fx_name_to_onnxscript_value: Dict[length=1](\nadd: `TorchScriptTensor(f32[4, 1024, 1024])`,\n)\n## PyTorch source information\n```\n File \"/home/thebears/.local/lib/python3.10/site-packages/open_clip/timm_model.py\", line 196, in forward\n x = self.trunk(x)\n File \"/home/thebears/.local/lib/python3.10/site-packages/torch/nn/modules/module.py\", line 1725, in _call_impl\n return forward_call(*args, **kwargs)\n File \"/home/thebears/.local/lib/python3.10/site-packages/timm/models/vision_transformer.py\", line 853, in forward\n x = self.forward_features(x)\n File \"/home/thebears/.local/lib/python3.10/site-packages/timm/models/vision_transformer.py\", line 828, in forward_features\n x = self._pos_embed(x)\n File \"/home/thebears/.local/lib/python3.10/site-packages/timm/models/vision_transformer.py\", line 720, in _pos_embed\n return self.pos_drop(x)\n\n```\n## Return values\n", + "text":"FX Node: call_function:aten.clone.default[name=clone]. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"FxOnnxInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":414 + } + } + }, + { + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/open_clip/timm_model.py" + }, + "region":{ + "snippet":{ + "text":"x = self.trunk(x)" + }, + "startLine":196 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0008", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Node: output:output[name=output]. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature FxOnnxInterpreter.run_node\n- self: \n- node: fx.Node(output)[output]:None\n- fx_graph_module: torch.fx.GraphModule(torch_nn_modules_dropout_Dropout)\n- onnxfunction_dispatcher: \n- op_level_debug: False\n- onnxscript_graph: \n- onnxscript_tracer: \n- fx_name_to_onnxscript_value: Dict[length=2](\nadd: `TorchScriptTensor(f32[4, 1024, 1024])`,\nclone: `TorchScriptTensor(f32[4, 1024, 1024])`,\n)\n## Return values\n", + "text":"FX Node: output:output[name=output]. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"FxOnnxInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":414 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0008", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Graph: torch_nn_modules_dropout_Dropout. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature FxOnnxInterpreter.run\n- self: \n- fx_graph_module: torch.fx.GraphModule(torch_nn_modules_dropout_Dropout)\n- onnxfunction_dispatcher: \n- op_level_debug: False\n- parent_onnxscript_graph: \n## Return values\n", + "text":"FX Graph: torch_nn_modules_dropout_Dropout. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"FxOnnxInterpreter.run" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":496 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0007", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Node: call_module:trunk_pos_drop_1[name=trunk_pos_drop_1]. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature FxOnnxInterpreter.run_node\n- self: \n- node: fx.Node(trunk_pos_drop_1)[call_module]:Tensor(f32[4, 1024, 1024])\n- fx_graph_module: torch.fx.GraphModule(timm_models_vision_transformer_VisionTransformer)\n- onnxfunction_dispatcher: \n- op_level_debug: False\n- onnxscript_graph: \n- onnxscript_tracer: \n- fx_name_to_onnxscript_value: Dict[length=309](\nx: `TorchScriptTensor(f32[4, 3, 512, 512])`,\np_trunk_patch_embed_proj_weight: `TorchScriptTensor(f32[1024, 3, 16, 16])`,\np_trunk_patch_embed_proj_bias: `TorchScriptTensor(f32[1024])`,\np_trunk_pos_embed: `TorchScriptTensor(f32[1, 1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_weight: `TorchScriptTensor(f32[3072, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_bias: `TorchScriptTensor(f32[3072])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_weight: `TorchScriptTensor(f32[1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_bias: `TorchScriptTensor(f32[1024])`,\n...\n)\n## PyTorch source information\n```\n File \"/home/thebears/.local/lib/python3.10/site-packages/open_clip/timm_model.py\", line 196, in forward\n x = self.trunk(x)\n File \"/home/thebears/.local/lib/python3.10/site-packages/torch/nn/modules/module.py\", line 1725, in _call_impl\n return forward_call(*args, **kwargs)\n File \"/home/thebears/.local/lib/python3.10/site-packages/timm/models/vision_transformer.py\", line 853, in forward\n x = self.forward_features(x)\n File \"/home/thebears/.local/lib/python3.10/site-packages/timm/models/vision_transformer.py\", line 828, in forward_features\n x = self._pos_embed(x)\n File \"/home/thebears/.local/lib/python3.10/site-packages/timm/models/vision_transformer.py\", line 720, in _pos_embed\n return self.pos_drop(x)\n\n```\n## Return values\n", + "text":"FX Node: call_module:trunk_pos_drop_1[name=trunk_pos_drop_1]. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"FxOnnxInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":414 + } + } + }, + { + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/open_clip/timm_model.py" + }, + "region":{ + "snippet":{ + "text":"x = self.trunk(x)" + }, + "startLine":196 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0008", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Node: placeholder:clone[name=clone]. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature FxOnnxInterpreter.run_node\n- self: \n- node: fx.Node(clone)[placeholder]:Tensor(f32[4, 1024, 1024])\n- fx_graph_module: torch.fx.GraphModule(torch_nn_modules_container_Sequential)\n- onnxfunction_dispatcher: \n- op_level_debug: False\n- onnxscript_graph: \n- onnxscript_tracer: \n- fx_name_to_onnxscript_value: Dict[length=0](\nNone)\n## PyTorch source information\n```\n File \"/home/thebears/.local/lib/python3.10/site-packages/open_clip/timm_model.py\", line 196, in forward\n x = self.trunk(x)\n File \"/home/thebears/.local/lib/python3.10/site-packages/torch/nn/modules/module.py\", line 1725, in _call_impl\n return forward_call(*args, **kwargs)\n File \"/home/thebears/.local/lib/python3.10/site-packages/timm/models/vision_transformer.py\", line 853, in forward\n x = self.forward_features(x)\n File \"/home/thebears/.local/lib/python3.10/site-packages/timm/models/vision_transformer.py\", line 828, in forward_features\n x = self._pos_embed(x)\n File \"/home/thebears/.local/lib/python3.10/site-packages/timm/models/vision_transformer.py\", line 720, in _pos_embed\n return self.pos_drop(x)\n\n```\n## Return values\n", + "text":"FX Node: placeholder:clone[name=clone]. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"FxOnnxInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":414 + } + } + }, + { + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/open_clip/timm_model.py" + }, + "region":{ + "snippet":{ + "text":"x = self.trunk(x)" + }, + "startLine":196 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0008", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___0___norm1_weight[name=p_getattr_l__self___trunk_blocks___0___norm1_weight]. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature FxOnnxInterpreter.run_node\n- self: \n- node: fx.Node(p_getattr_l__self___trunk_blocks___0___norm1_weight)[placeholder]:Tensor(f32[1024])\n- fx_graph_module: torch.fx.GraphModule(torch_nn_modules_container_Sequential)\n- onnxfunction_dispatcher: \n- op_level_debug: False\n- onnxscript_graph: \n- onnxscript_tracer: \n- fx_name_to_onnxscript_value: Dict[length=1](\nclone: `TorchScriptTensor(f32[4, 1024, 1024])`,\n)\n## Return values\n", + "text":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___0___norm1_weight[name=p_getattr_l__self___trunk_blocks___0___norm1_weight]. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"FxOnnxInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":414 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0008", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___0___norm1_bias[name=p_getattr_l__self___trunk_blocks___0___norm1_bias]. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature FxOnnxInterpreter.run_node\n- self: \n- node: fx.Node(p_getattr_l__self___trunk_blocks___0___norm1_bias)[placeholder]:Tensor(f32[1024])\n- fx_graph_module: torch.fx.GraphModule(torch_nn_modules_container_Sequential)\n- onnxfunction_dispatcher: \n- op_level_debug: False\n- onnxscript_graph: \n- onnxscript_tracer: \n- fx_name_to_onnxscript_value: Dict[length=2](\nclone: `TorchScriptTensor(f32[4, 1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_weight: `TorchScriptTensor(f32[1024])`,\n)\n## Return values\n", + "text":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___0___norm1_bias[name=p_getattr_l__self___trunk_blocks___0___norm1_bias]. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"FxOnnxInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":414 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0008", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___0___attn_qkv_weight[name=p_getattr_l__self___trunk_blocks___0___attn_qkv_weight]. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature FxOnnxInterpreter.run_node\n- self: \n- node: fx.Node(p_getattr_l__self___trunk_blocks___0___attn_qkv_weight)[placeholder]:Tensor(f32[3072, 1024])\n- fx_graph_module: torch.fx.GraphModule(torch_nn_modules_container_Sequential)\n- onnxfunction_dispatcher: \n- op_level_debug: False\n- onnxscript_graph: \n- onnxscript_tracer: \n- fx_name_to_onnxscript_value: Dict[length=3](\nclone: `TorchScriptTensor(f32[4, 1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_bias: `TorchScriptTensor(f32[1024])`,\n)\n## Return values\n", + "text":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___0___attn_qkv_weight[name=p_getattr_l__self___trunk_blocks___0___attn_qkv_weight]. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"FxOnnxInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":414 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0008", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___0___attn_qkv_bias[name=p_getattr_l__self___trunk_blocks___0___attn_qkv_bias]. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature FxOnnxInterpreter.run_node\n- self: \n- node: fx.Node(p_getattr_l__self___trunk_blocks___0___attn_qkv_bias)[placeholder]:Tensor(f32[3072])\n- fx_graph_module: torch.fx.GraphModule(torch_nn_modules_container_Sequential)\n- onnxfunction_dispatcher: \n- op_level_debug: False\n- onnxscript_graph: \n- onnxscript_tracer: \n- fx_name_to_onnxscript_value: Dict[length=4](\nclone: `TorchScriptTensor(f32[4, 1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_weight: `TorchScriptTensor(f32[3072, 1024])`,\n)\n## Return values\n", + "text":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___0___attn_qkv_bias[name=p_getattr_l__self___trunk_blocks___0___attn_qkv_bias]. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"FxOnnxInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":414 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0008", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___0___attn_proj_weight[name=p_getattr_l__self___trunk_blocks___0___attn_proj_weight]. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature FxOnnxInterpreter.run_node\n- self: \n- node: fx.Node(p_getattr_l__self___trunk_blocks___0___attn_proj_weight)[placeholder]:Tensor(f32[1024, 1024])\n- fx_graph_module: torch.fx.GraphModule(torch_nn_modules_container_Sequential)\n- onnxfunction_dispatcher: \n- op_level_debug: False\n- onnxscript_graph: \n- onnxscript_tracer: \n- fx_name_to_onnxscript_value: Dict[length=5](\nclone: `TorchScriptTensor(f32[4, 1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_weight: `TorchScriptTensor(f32[3072, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_bias: `TorchScriptTensor(f32[3072])`,\n)\n## Return values\n", + "text":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___0___attn_proj_weight[name=p_getattr_l__self___trunk_blocks___0___attn_proj_weight]. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"FxOnnxInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":414 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0008", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___0___attn_proj_bias[name=p_getattr_l__self___trunk_blocks___0___attn_proj_bias]. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature FxOnnxInterpreter.run_node\n- self: \n- node: fx.Node(p_getattr_l__self___trunk_blocks___0___attn_proj_bias)[placeholder]:Tensor(f32[1024])\n- fx_graph_module: torch.fx.GraphModule(torch_nn_modules_container_Sequential)\n- onnxfunction_dispatcher: \n- op_level_debug: False\n- onnxscript_graph: \n- onnxscript_tracer: \n- fx_name_to_onnxscript_value: Dict[length=6](\nclone: `TorchScriptTensor(f32[4, 1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_weight: `TorchScriptTensor(f32[3072, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_bias: `TorchScriptTensor(f32[3072])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_weight: `TorchScriptTensor(f32[1024, 1024])`,\n)\n## Return values\n", + "text":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___0___attn_proj_bias[name=p_getattr_l__self___trunk_blocks___0___attn_proj_bias]. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"FxOnnxInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":414 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0008", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___0___norm2_weight[name=p_getattr_l__self___trunk_blocks___0___norm2_weight]. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature FxOnnxInterpreter.run_node\n- self: \n- node: fx.Node(p_getattr_l__self___trunk_blocks___0___norm2_weight)[placeholder]:Tensor(f32[1024])\n- fx_graph_module: torch.fx.GraphModule(torch_nn_modules_container_Sequential)\n- onnxfunction_dispatcher: \n- op_level_debug: False\n- onnxscript_graph: \n- onnxscript_tracer: \n- fx_name_to_onnxscript_value: Dict[length=7](\nclone: `TorchScriptTensor(f32[4, 1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_weight: `TorchScriptTensor(f32[3072, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_bias: `TorchScriptTensor(f32[3072])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_weight: `TorchScriptTensor(f32[1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_bias: `TorchScriptTensor(f32[1024])`,\n)\n## Return values\n", + "text":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___0___norm2_weight[name=p_getattr_l__self___trunk_blocks___0___norm2_weight]. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"FxOnnxInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":414 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0008", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___0___norm2_bias[name=p_getattr_l__self___trunk_blocks___0___norm2_bias]. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature FxOnnxInterpreter.run_node\n- self: \n- node: fx.Node(p_getattr_l__self___trunk_blocks___0___norm2_bias)[placeholder]:Tensor(f32[1024])\n- fx_graph_module: torch.fx.GraphModule(torch_nn_modules_container_Sequential)\n- onnxfunction_dispatcher: \n- op_level_debug: False\n- onnxscript_graph: \n- onnxscript_tracer: \n- fx_name_to_onnxscript_value: Dict[length=8](\nclone: `TorchScriptTensor(f32[4, 1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_weight: `TorchScriptTensor(f32[3072, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_bias: `TorchScriptTensor(f32[3072])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_weight: `TorchScriptTensor(f32[1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm2_weight: `TorchScriptTensor(f32[1024])`,\n)\n## Return values\n", + "text":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___0___norm2_bias[name=p_getattr_l__self___trunk_blocks___0___norm2_bias]. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"FxOnnxInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":414 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0008", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___0___mlp_fc1_weight[name=p_getattr_l__self___trunk_blocks___0___mlp_fc1_weight]. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature FxOnnxInterpreter.run_node\n- self: \n- node: fx.Node(p_getattr_l__self___trunk_blocks___0___mlp_fc1_weight)[placeholder]:Tensor(f32[4096, 1024])\n- fx_graph_module: torch.fx.GraphModule(torch_nn_modules_container_Sequential)\n- onnxfunction_dispatcher: \n- op_level_debug: False\n- onnxscript_graph: \n- onnxscript_tracer: \n- fx_name_to_onnxscript_value: Dict[length=9](\nclone: `TorchScriptTensor(f32[4, 1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_weight: `TorchScriptTensor(f32[3072, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_bias: `TorchScriptTensor(f32[3072])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_weight: `TorchScriptTensor(f32[1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm2_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm2_bias: `TorchScriptTensor(f32[1024])`,\n)\n## Return values\n", + "text":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___0___mlp_fc1_weight[name=p_getattr_l__self___trunk_blocks___0___mlp_fc1_weight]. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"FxOnnxInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":414 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0008", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___0___mlp_fc1_bias[name=p_getattr_l__self___trunk_blocks___0___mlp_fc1_bias]. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature FxOnnxInterpreter.run_node\n- self: \n- node: fx.Node(p_getattr_l__self___trunk_blocks___0___mlp_fc1_bias)[placeholder]:Tensor(f32[4096])\n- fx_graph_module: torch.fx.GraphModule(torch_nn_modules_container_Sequential)\n- onnxfunction_dispatcher: \n- op_level_debug: False\n- onnxscript_graph: \n- onnxscript_tracer: \n- fx_name_to_onnxscript_value: Dict[length=10](\nclone: `TorchScriptTensor(f32[4, 1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_weight: `TorchScriptTensor(f32[3072, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_bias: `TorchScriptTensor(f32[3072])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_weight: `TorchScriptTensor(f32[1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm2_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm2_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___mlp_fc1_weight: `TorchScriptTensor(f32[4096, 1024])`,\n)\n## Return values\n", + "text":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___0___mlp_fc1_bias[name=p_getattr_l__self___trunk_blocks___0___mlp_fc1_bias]. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"FxOnnxInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":414 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0008", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___0___mlp_fc2_weight[name=p_getattr_l__self___trunk_blocks___0___mlp_fc2_weight]. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature FxOnnxInterpreter.run_node\n- self: \n- node: fx.Node(p_getattr_l__self___trunk_blocks___0___mlp_fc2_weight)[placeholder]:Tensor(f32[1024, 4096])\n- fx_graph_module: torch.fx.GraphModule(torch_nn_modules_container_Sequential)\n- onnxfunction_dispatcher: \n- op_level_debug: False\n- onnxscript_graph: \n- onnxscript_tracer: \n- fx_name_to_onnxscript_value: Dict[length=11](\nclone: `TorchScriptTensor(f32[4, 1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_weight: `TorchScriptTensor(f32[3072, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_bias: `TorchScriptTensor(f32[3072])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_weight: `TorchScriptTensor(f32[1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm2_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm2_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___mlp_fc1_weight: `TorchScriptTensor(f32[4096, 1024])`,\n...\n)\n## Return values\n", + "text":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___0___mlp_fc2_weight[name=p_getattr_l__self___trunk_blocks___0___mlp_fc2_weight]. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"FxOnnxInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":414 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0008", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___0___mlp_fc2_bias[name=p_getattr_l__self___trunk_blocks___0___mlp_fc2_bias]. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature FxOnnxInterpreter.run_node\n- self: \n- node: fx.Node(p_getattr_l__self___trunk_blocks___0___mlp_fc2_bias)[placeholder]:Tensor(f32[1024])\n- fx_graph_module: torch.fx.GraphModule(torch_nn_modules_container_Sequential)\n- onnxfunction_dispatcher: \n- op_level_debug: False\n- onnxscript_graph: \n- onnxscript_tracer: \n- fx_name_to_onnxscript_value: Dict[length=12](\nclone: `TorchScriptTensor(f32[4, 1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_weight: `TorchScriptTensor(f32[3072, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_bias: `TorchScriptTensor(f32[3072])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_weight: `TorchScriptTensor(f32[1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm2_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm2_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___mlp_fc1_weight: `TorchScriptTensor(f32[4096, 1024])`,\n...\n)\n## Return values\n", + "text":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___0___mlp_fc2_bias[name=p_getattr_l__self___trunk_blocks___0___mlp_fc2_bias]. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"FxOnnxInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":414 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0008", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___1___norm1_weight[name=p_getattr_l__self___trunk_blocks___1___norm1_weight]. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature FxOnnxInterpreter.run_node\n- self: \n- node: fx.Node(p_getattr_l__self___trunk_blocks___1___norm1_weight)[placeholder]:Tensor(f32[1024])\n- fx_graph_module: torch.fx.GraphModule(torch_nn_modules_container_Sequential)\n- onnxfunction_dispatcher: \n- op_level_debug: False\n- onnxscript_graph: \n- onnxscript_tracer: \n- fx_name_to_onnxscript_value: Dict[length=13](\nclone: `TorchScriptTensor(f32[4, 1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_weight: `TorchScriptTensor(f32[3072, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_bias: `TorchScriptTensor(f32[3072])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_weight: `TorchScriptTensor(f32[1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm2_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm2_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___mlp_fc1_weight: `TorchScriptTensor(f32[4096, 1024])`,\n...\n)\n## Return values\n", + "text":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___1___norm1_weight[name=p_getattr_l__self___trunk_blocks___1___norm1_weight]. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"FxOnnxInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":414 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0008", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___1___norm1_bias[name=p_getattr_l__self___trunk_blocks___1___norm1_bias]. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature FxOnnxInterpreter.run_node\n- self: \n- node: fx.Node(p_getattr_l__self___trunk_blocks___1___norm1_bias)[placeholder]:Tensor(f32[1024])\n- fx_graph_module: torch.fx.GraphModule(torch_nn_modules_container_Sequential)\n- onnxfunction_dispatcher: \n- op_level_debug: False\n- onnxscript_graph: \n- onnxscript_tracer: \n- fx_name_to_onnxscript_value: Dict[length=14](\nclone: `TorchScriptTensor(f32[4, 1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_weight: `TorchScriptTensor(f32[3072, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_bias: `TorchScriptTensor(f32[3072])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_weight: `TorchScriptTensor(f32[1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm2_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm2_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___mlp_fc1_weight: `TorchScriptTensor(f32[4096, 1024])`,\n...\n)\n## Return values\n", + "text":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___1___norm1_bias[name=p_getattr_l__self___trunk_blocks___1___norm1_bias]. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"FxOnnxInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":414 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0008", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___1___attn_qkv_weight[name=p_getattr_l__self___trunk_blocks___1___attn_qkv_weight]. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature FxOnnxInterpreter.run_node\n- self: \n- node: fx.Node(p_getattr_l__self___trunk_blocks___1___attn_qkv_weight)[placeholder]:Tensor(f32[3072, 1024])\n- fx_graph_module: torch.fx.GraphModule(torch_nn_modules_container_Sequential)\n- onnxfunction_dispatcher: \n- op_level_debug: False\n- onnxscript_graph: \n- onnxscript_tracer: \n- fx_name_to_onnxscript_value: Dict[length=15](\nclone: `TorchScriptTensor(f32[4, 1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_weight: `TorchScriptTensor(f32[3072, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_bias: `TorchScriptTensor(f32[3072])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_weight: `TorchScriptTensor(f32[1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm2_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm2_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___mlp_fc1_weight: `TorchScriptTensor(f32[4096, 1024])`,\n...\n)\n## Return values\n", + "text":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___1___attn_qkv_weight[name=p_getattr_l__self___trunk_blocks___1___attn_qkv_weight]. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"FxOnnxInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":414 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0008", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___1___attn_qkv_bias[name=p_getattr_l__self___trunk_blocks___1___attn_qkv_bias]. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature FxOnnxInterpreter.run_node\n- self: \n- node: fx.Node(p_getattr_l__self___trunk_blocks___1___attn_qkv_bias)[placeholder]:Tensor(f32[3072])\n- fx_graph_module: torch.fx.GraphModule(torch_nn_modules_container_Sequential)\n- onnxfunction_dispatcher: \n- op_level_debug: False\n- onnxscript_graph: \n- onnxscript_tracer: \n- fx_name_to_onnxscript_value: Dict[length=16](\nclone: `TorchScriptTensor(f32[4, 1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_weight: `TorchScriptTensor(f32[3072, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_bias: `TorchScriptTensor(f32[3072])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_weight: `TorchScriptTensor(f32[1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm2_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm2_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___mlp_fc1_weight: `TorchScriptTensor(f32[4096, 1024])`,\n...\n)\n## Return values\n", + "text":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___1___attn_qkv_bias[name=p_getattr_l__self___trunk_blocks___1___attn_qkv_bias]. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"FxOnnxInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":414 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0008", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___1___attn_proj_weight[name=p_getattr_l__self___trunk_blocks___1___attn_proj_weight]. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature FxOnnxInterpreter.run_node\n- self: \n- node: fx.Node(p_getattr_l__self___trunk_blocks___1___attn_proj_weight)[placeholder]:Tensor(f32[1024, 1024])\n- fx_graph_module: torch.fx.GraphModule(torch_nn_modules_container_Sequential)\n- onnxfunction_dispatcher: \n- op_level_debug: False\n- onnxscript_graph: \n- onnxscript_tracer: \n- fx_name_to_onnxscript_value: Dict[length=17](\nclone: `TorchScriptTensor(f32[4, 1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_weight: `TorchScriptTensor(f32[3072, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_bias: `TorchScriptTensor(f32[3072])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_weight: `TorchScriptTensor(f32[1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm2_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm2_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___mlp_fc1_weight: `TorchScriptTensor(f32[4096, 1024])`,\n...\n)\n## Return values\n", + "text":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___1___attn_proj_weight[name=p_getattr_l__self___trunk_blocks___1___attn_proj_weight]. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"FxOnnxInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":414 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0008", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___1___attn_proj_bias[name=p_getattr_l__self___trunk_blocks___1___attn_proj_bias]. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature FxOnnxInterpreter.run_node\n- self: \n- node: fx.Node(p_getattr_l__self___trunk_blocks___1___attn_proj_bias)[placeholder]:Tensor(f32[1024])\n- fx_graph_module: torch.fx.GraphModule(torch_nn_modules_container_Sequential)\n- onnxfunction_dispatcher: \n- op_level_debug: False\n- onnxscript_graph: \n- onnxscript_tracer: \n- fx_name_to_onnxscript_value: Dict[length=18](\nclone: `TorchScriptTensor(f32[4, 1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_weight: `TorchScriptTensor(f32[3072, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_bias: `TorchScriptTensor(f32[3072])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_weight: `TorchScriptTensor(f32[1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm2_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm2_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___mlp_fc1_weight: `TorchScriptTensor(f32[4096, 1024])`,\n...\n)\n## Return values\n", + "text":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___1___attn_proj_bias[name=p_getattr_l__self___trunk_blocks___1___attn_proj_bias]. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"FxOnnxInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":414 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0008", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___1___norm2_weight[name=p_getattr_l__self___trunk_blocks___1___norm2_weight]. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature FxOnnxInterpreter.run_node\n- self: \n- node: fx.Node(p_getattr_l__self___trunk_blocks___1___norm2_weight)[placeholder]:Tensor(f32[1024])\n- fx_graph_module: torch.fx.GraphModule(torch_nn_modules_container_Sequential)\n- onnxfunction_dispatcher: \n- op_level_debug: False\n- onnxscript_graph: \n- onnxscript_tracer: \n- fx_name_to_onnxscript_value: Dict[length=19](\nclone: `TorchScriptTensor(f32[4, 1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_weight: `TorchScriptTensor(f32[3072, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_bias: `TorchScriptTensor(f32[3072])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_weight: `TorchScriptTensor(f32[1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm2_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm2_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___mlp_fc1_weight: `TorchScriptTensor(f32[4096, 1024])`,\n...\n)\n## Return values\n", + "text":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___1___norm2_weight[name=p_getattr_l__self___trunk_blocks___1___norm2_weight]. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"FxOnnxInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":414 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0008", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___1___norm2_bias[name=p_getattr_l__self___trunk_blocks___1___norm2_bias]. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature FxOnnxInterpreter.run_node\n- self: \n- node: fx.Node(p_getattr_l__self___trunk_blocks___1___norm2_bias)[placeholder]:Tensor(f32[1024])\n- fx_graph_module: torch.fx.GraphModule(torch_nn_modules_container_Sequential)\n- onnxfunction_dispatcher: \n- op_level_debug: False\n- onnxscript_graph: \n- onnxscript_tracer: \n- fx_name_to_onnxscript_value: Dict[length=20](\nclone: `TorchScriptTensor(f32[4, 1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_weight: `TorchScriptTensor(f32[3072, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_bias: `TorchScriptTensor(f32[3072])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_weight: `TorchScriptTensor(f32[1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm2_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm2_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___mlp_fc1_weight: `TorchScriptTensor(f32[4096, 1024])`,\n...\n)\n## Return values\n", + "text":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___1___norm2_bias[name=p_getattr_l__self___trunk_blocks___1___norm2_bias]. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"FxOnnxInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":414 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0008", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___1___mlp_fc1_weight[name=p_getattr_l__self___trunk_blocks___1___mlp_fc1_weight]. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature FxOnnxInterpreter.run_node\n- self: \n- node: fx.Node(p_getattr_l__self___trunk_blocks___1___mlp_fc1_weight)[placeholder]:Tensor(f32[4096, 1024])\n- fx_graph_module: torch.fx.GraphModule(torch_nn_modules_container_Sequential)\n- onnxfunction_dispatcher: \n- op_level_debug: False\n- onnxscript_graph: \n- onnxscript_tracer: \n- fx_name_to_onnxscript_value: Dict[length=21](\nclone: `TorchScriptTensor(f32[4, 1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_weight: `TorchScriptTensor(f32[3072, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_bias: `TorchScriptTensor(f32[3072])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_weight: `TorchScriptTensor(f32[1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm2_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm2_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___mlp_fc1_weight: `TorchScriptTensor(f32[4096, 1024])`,\n...\n)\n## Return values\n", + "text":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___1___mlp_fc1_weight[name=p_getattr_l__self___trunk_blocks___1___mlp_fc1_weight]. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"FxOnnxInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":414 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0008", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___1___mlp_fc1_bias[name=p_getattr_l__self___trunk_blocks___1___mlp_fc1_bias]. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature FxOnnxInterpreter.run_node\n- self: \n- node: fx.Node(p_getattr_l__self___trunk_blocks___1___mlp_fc1_bias)[placeholder]:Tensor(f32[4096])\n- fx_graph_module: torch.fx.GraphModule(torch_nn_modules_container_Sequential)\n- onnxfunction_dispatcher: \n- op_level_debug: False\n- onnxscript_graph: \n- onnxscript_tracer: \n- fx_name_to_onnxscript_value: Dict[length=22](\nclone: `TorchScriptTensor(f32[4, 1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_weight: `TorchScriptTensor(f32[3072, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_bias: `TorchScriptTensor(f32[3072])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_weight: `TorchScriptTensor(f32[1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm2_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm2_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___mlp_fc1_weight: `TorchScriptTensor(f32[4096, 1024])`,\n...\n)\n## Return values\n", + "text":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___1___mlp_fc1_bias[name=p_getattr_l__self___trunk_blocks___1___mlp_fc1_bias]. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"FxOnnxInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":414 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0008", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___1___mlp_fc2_weight[name=p_getattr_l__self___trunk_blocks___1___mlp_fc2_weight]. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature FxOnnxInterpreter.run_node\n- self: \n- node: fx.Node(p_getattr_l__self___trunk_blocks___1___mlp_fc2_weight)[placeholder]:Tensor(f32[1024, 4096])\n- fx_graph_module: torch.fx.GraphModule(torch_nn_modules_container_Sequential)\n- onnxfunction_dispatcher: \n- op_level_debug: False\n- onnxscript_graph: \n- onnxscript_tracer: \n- fx_name_to_onnxscript_value: Dict[length=23](\nclone: `TorchScriptTensor(f32[4, 1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_weight: `TorchScriptTensor(f32[3072, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_bias: `TorchScriptTensor(f32[3072])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_weight: `TorchScriptTensor(f32[1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm2_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm2_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___mlp_fc1_weight: `TorchScriptTensor(f32[4096, 1024])`,\n...\n)\n## Return values\n", + "text":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___1___mlp_fc2_weight[name=p_getattr_l__self___trunk_blocks___1___mlp_fc2_weight]. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"FxOnnxInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":414 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0008", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___1___mlp_fc2_bias[name=p_getattr_l__self___trunk_blocks___1___mlp_fc2_bias]. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature FxOnnxInterpreter.run_node\n- self: \n- node: fx.Node(p_getattr_l__self___trunk_blocks___1___mlp_fc2_bias)[placeholder]:Tensor(f32[1024])\n- fx_graph_module: torch.fx.GraphModule(torch_nn_modules_container_Sequential)\n- onnxfunction_dispatcher: \n- op_level_debug: False\n- onnxscript_graph: \n- onnxscript_tracer: \n- fx_name_to_onnxscript_value: Dict[length=24](\nclone: `TorchScriptTensor(f32[4, 1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_weight: `TorchScriptTensor(f32[3072, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_bias: `TorchScriptTensor(f32[3072])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_weight: `TorchScriptTensor(f32[1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm2_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm2_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___mlp_fc1_weight: `TorchScriptTensor(f32[4096, 1024])`,\n...\n)\n## Return values\n", + "text":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___1___mlp_fc2_bias[name=p_getattr_l__self___trunk_blocks___1___mlp_fc2_bias]. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"FxOnnxInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":414 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0008", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___2___norm1_weight[name=p_getattr_l__self___trunk_blocks___2___norm1_weight]. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature FxOnnxInterpreter.run_node\n- self: \n- node: fx.Node(p_getattr_l__self___trunk_blocks___2___norm1_weight)[placeholder]:Tensor(f32[1024])\n- fx_graph_module: torch.fx.GraphModule(torch_nn_modules_container_Sequential)\n- onnxfunction_dispatcher: \n- op_level_debug: False\n- onnxscript_graph: \n- onnxscript_tracer: \n- fx_name_to_onnxscript_value: Dict[length=25](\nclone: `TorchScriptTensor(f32[4, 1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_weight: `TorchScriptTensor(f32[3072, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_bias: `TorchScriptTensor(f32[3072])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_weight: `TorchScriptTensor(f32[1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm2_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm2_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___mlp_fc1_weight: `TorchScriptTensor(f32[4096, 1024])`,\n...\n)\n## Return values\n", + "text":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___2___norm1_weight[name=p_getattr_l__self___trunk_blocks___2___norm1_weight]. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"FxOnnxInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":414 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0008", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___2___norm1_bias[name=p_getattr_l__self___trunk_blocks___2___norm1_bias]. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature FxOnnxInterpreter.run_node\n- self: \n- node: fx.Node(p_getattr_l__self___trunk_blocks___2___norm1_bias)[placeholder]:Tensor(f32[1024])\n- fx_graph_module: torch.fx.GraphModule(torch_nn_modules_container_Sequential)\n- onnxfunction_dispatcher: \n- op_level_debug: False\n- onnxscript_graph: \n- onnxscript_tracer: \n- fx_name_to_onnxscript_value: Dict[length=26](\nclone: `TorchScriptTensor(f32[4, 1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_weight: `TorchScriptTensor(f32[3072, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_bias: `TorchScriptTensor(f32[3072])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_weight: `TorchScriptTensor(f32[1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm2_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm2_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___mlp_fc1_weight: `TorchScriptTensor(f32[4096, 1024])`,\n...\n)\n## Return values\n", + "text":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___2___norm1_bias[name=p_getattr_l__self___trunk_blocks___2___norm1_bias]. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"FxOnnxInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":414 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0008", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___2___attn_qkv_weight[name=p_getattr_l__self___trunk_blocks___2___attn_qkv_weight]. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature FxOnnxInterpreter.run_node\n- self: \n- node: fx.Node(p_getattr_l__self___trunk_blocks___2___attn_qkv_weight)[placeholder]:Tensor(f32[3072, 1024])\n- fx_graph_module: torch.fx.GraphModule(torch_nn_modules_container_Sequential)\n- onnxfunction_dispatcher: \n- op_level_debug: False\n- onnxscript_graph: \n- onnxscript_tracer: \n- fx_name_to_onnxscript_value: Dict[length=27](\nclone: `TorchScriptTensor(f32[4, 1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_weight: `TorchScriptTensor(f32[3072, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_bias: `TorchScriptTensor(f32[3072])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_weight: `TorchScriptTensor(f32[1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm2_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm2_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___mlp_fc1_weight: `TorchScriptTensor(f32[4096, 1024])`,\n...\n)\n## Return values\n", + "text":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___2___attn_qkv_weight[name=p_getattr_l__self___trunk_blocks___2___attn_qkv_weight]. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"FxOnnxInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":414 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0008", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___2___attn_qkv_bias[name=p_getattr_l__self___trunk_blocks___2___attn_qkv_bias]. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature FxOnnxInterpreter.run_node\n- self: \n- node: fx.Node(p_getattr_l__self___trunk_blocks___2___attn_qkv_bias)[placeholder]:Tensor(f32[3072])\n- fx_graph_module: torch.fx.GraphModule(torch_nn_modules_container_Sequential)\n- onnxfunction_dispatcher: \n- op_level_debug: False\n- onnxscript_graph: \n- onnxscript_tracer: \n- fx_name_to_onnxscript_value: Dict[length=28](\nclone: `TorchScriptTensor(f32[4, 1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_weight: `TorchScriptTensor(f32[3072, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_bias: `TorchScriptTensor(f32[3072])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_weight: `TorchScriptTensor(f32[1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm2_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm2_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___mlp_fc1_weight: `TorchScriptTensor(f32[4096, 1024])`,\n...\n)\n## Return values\n", + "text":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___2___attn_qkv_bias[name=p_getattr_l__self___trunk_blocks___2___attn_qkv_bias]. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"FxOnnxInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":414 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0008", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___2___attn_proj_weight[name=p_getattr_l__self___trunk_blocks___2___attn_proj_weight]. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature FxOnnxInterpreter.run_node\n- self: \n- node: fx.Node(p_getattr_l__self___trunk_blocks___2___attn_proj_weight)[placeholder]:Tensor(f32[1024, 1024])\n- fx_graph_module: torch.fx.GraphModule(torch_nn_modules_container_Sequential)\n- onnxfunction_dispatcher: \n- op_level_debug: False\n- onnxscript_graph: \n- onnxscript_tracer: \n- fx_name_to_onnxscript_value: Dict[length=29](\nclone: `TorchScriptTensor(f32[4, 1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_weight: `TorchScriptTensor(f32[3072, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_bias: `TorchScriptTensor(f32[3072])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_weight: `TorchScriptTensor(f32[1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm2_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm2_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___mlp_fc1_weight: `TorchScriptTensor(f32[4096, 1024])`,\n...\n)\n## Return values\n", + "text":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___2___attn_proj_weight[name=p_getattr_l__self___trunk_blocks___2___attn_proj_weight]. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"FxOnnxInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":414 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0008", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___2___attn_proj_bias[name=p_getattr_l__self___trunk_blocks___2___attn_proj_bias]. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature FxOnnxInterpreter.run_node\n- self: \n- node: fx.Node(p_getattr_l__self___trunk_blocks___2___attn_proj_bias)[placeholder]:Tensor(f32[1024])\n- fx_graph_module: torch.fx.GraphModule(torch_nn_modules_container_Sequential)\n- onnxfunction_dispatcher: \n- op_level_debug: False\n- onnxscript_graph: \n- onnxscript_tracer: \n- fx_name_to_onnxscript_value: Dict[length=30](\nclone: `TorchScriptTensor(f32[4, 1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_weight: `TorchScriptTensor(f32[3072, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_bias: `TorchScriptTensor(f32[3072])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_weight: `TorchScriptTensor(f32[1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm2_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm2_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___mlp_fc1_weight: `TorchScriptTensor(f32[4096, 1024])`,\n...\n)\n## Return values\n", + "text":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___2___attn_proj_bias[name=p_getattr_l__self___trunk_blocks___2___attn_proj_bias]. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"FxOnnxInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":414 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0008", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___2___norm2_weight[name=p_getattr_l__self___trunk_blocks___2___norm2_weight]. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature FxOnnxInterpreter.run_node\n- self: \n- node: fx.Node(p_getattr_l__self___trunk_blocks___2___norm2_weight)[placeholder]:Tensor(f32[1024])\n- fx_graph_module: torch.fx.GraphModule(torch_nn_modules_container_Sequential)\n- onnxfunction_dispatcher: \n- op_level_debug: False\n- onnxscript_graph: \n- onnxscript_tracer: \n- fx_name_to_onnxscript_value: Dict[length=31](\nclone: `TorchScriptTensor(f32[4, 1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_weight: `TorchScriptTensor(f32[3072, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_bias: `TorchScriptTensor(f32[3072])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_weight: `TorchScriptTensor(f32[1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm2_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm2_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___mlp_fc1_weight: `TorchScriptTensor(f32[4096, 1024])`,\n...\n)\n## Return values\n", + "text":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___2___norm2_weight[name=p_getattr_l__self___trunk_blocks___2___norm2_weight]. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"FxOnnxInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":414 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0008", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___2___norm2_bias[name=p_getattr_l__self___trunk_blocks___2___norm2_bias]. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature FxOnnxInterpreter.run_node\n- self: \n- node: fx.Node(p_getattr_l__self___trunk_blocks___2___norm2_bias)[placeholder]:Tensor(f32[1024])\n- fx_graph_module: torch.fx.GraphModule(torch_nn_modules_container_Sequential)\n- onnxfunction_dispatcher: \n- op_level_debug: False\n- onnxscript_graph: \n- onnxscript_tracer: \n- fx_name_to_onnxscript_value: Dict[length=32](\nclone: `TorchScriptTensor(f32[4, 1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_weight: `TorchScriptTensor(f32[3072, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_bias: `TorchScriptTensor(f32[3072])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_weight: `TorchScriptTensor(f32[1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm2_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm2_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___mlp_fc1_weight: `TorchScriptTensor(f32[4096, 1024])`,\n...\n)\n## Return values\n", + "text":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___2___norm2_bias[name=p_getattr_l__self___trunk_blocks___2___norm2_bias]. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"FxOnnxInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":414 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0008", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___2___mlp_fc1_weight[name=p_getattr_l__self___trunk_blocks___2___mlp_fc1_weight]. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature FxOnnxInterpreter.run_node\n- self: \n- node: fx.Node(p_getattr_l__self___trunk_blocks___2___mlp_fc1_weight)[placeholder]:Tensor(f32[4096, 1024])\n- fx_graph_module: torch.fx.GraphModule(torch_nn_modules_container_Sequential)\n- onnxfunction_dispatcher: \n- op_level_debug: False\n- onnxscript_graph: \n- onnxscript_tracer: \n- fx_name_to_onnxscript_value: Dict[length=33](\nclone: `TorchScriptTensor(f32[4, 1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_weight: `TorchScriptTensor(f32[3072, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_bias: `TorchScriptTensor(f32[3072])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_weight: `TorchScriptTensor(f32[1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm2_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm2_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___mlp_fc1_weight: `TorchScriptTensor(f32[4096, 1024])`,\n...\n)\n## Return values\n", + "text":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___2___mlp_fc1_weight[name=p_getattr_l__self___trunk_blocks___2___mlp_fc1_weight]. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"FxOnnxInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":414 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0008", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___2___mlp_fc1_bias[name=p_getattr_l__self___trunk_blocks___2___mlp_fc1_bias]. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature FxOnnxInterpreter.run_node\n- self: \n- node: fx.Node(p_getattr_l__self___trunk_blocks___2___mlp_fc1_bias)[placeholder]:Tensor(f32[4096])\n- fx_graph_module: torch.fx.GraphModule(torch_nn_modules_container_Sequential)\n- onnxfunction_dispatcher: \n- op_level_debug: False\n- onnxscript_graph: \n- onnxscript_tracer: \n- fx_name_to_onnxscript_value: Dict[length=34](\nclone: `TorchScriptTensor(f32[4, 1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_weight: `TorchScriptTensor(f32[3072, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_bias: `TorchScriptTensor(f32[3072])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_weight: `TorchScriptTensor(f32[1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm2_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm2_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___mlp_fc1_weight: `TorchScriptTensor(f32[4096, 1024])`,\n...\n)\n## Return values\n", + "text":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___2___mlp_fc1_bias[name=p_getattr_l__self___trunk_blocks___2___mlp_fc1_bias]. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"FxOnnxInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":414 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0008", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___2___mlp_fc2_weight[name=p_getattr_l__self___trunk_blocks___2___mlp_fc2_weight]. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature FxOnnxInterpreter.run_node\n- self: \n- node: fx.Node(p_getattr_l__self___trunk_blocks___2___mlp_fc2_weight)[placeholder]:Tensor(f32[1024, 4096])\n- fx_graph_module: torch.fx.GraphModule(torch_nn_modules_container_Sequential)\n- onnxfunction_dispatcher: \n- op_level_debug: False\n- onnxscript_graph: \n- onnxscript_tracer: \n- fx_name_to_onnxscript_value: Dict[length=35](\nclone: `TorchScriptTensor(f32[4, 1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_weight: `TorchScriptTensor(f32[3072, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_bias: `TorchScriptTensor(f32[3072])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_weight: `TorchScriptTensor(f32[1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm2_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm2_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___mlp_fc1_weight: `TorchScriptTensor(f32[4096, 1024])`,\n...\n)\n## Return values\n", + "text":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___2___mlp_fc2_weight[name=p_getattr_l__self___trunk_blocks___2___mlp_fc2_weight]. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"FxOnnxInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":414 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0008", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___2___mlp_fc2_bias[name=p_getattr_l__self___trunk_blocks___2___mlp_fc2_bias]. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature FxOnnxInterpreter.run_node\n- self: \n- node: fx.Node(p_getattr_l__self___trunk_blocks___2___mlp_fc2_bias)[placeholder]:Tensor(f32[1024])\n- fx_graph_module: torch.fx.GraphModule(torch_nn_modules_container_Sequential)\n- onnxfunction_dispatcher: \n- op_level_debug: False\n- onnxscript_graph: \n- onnxscript_tracer: \n- fx_name_to_onnxscript_value: Dict[length=36](\nclone: `TorchScriptTensor(f32[4, 1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_weight: `TorchScriptTensor(f32[3072, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_bias: `TorchScriptTensor(f32[3072])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_weight: `TorchScriptTensor(f32[1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm2_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm2_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___mlp_fc1_weight: `TorchScriptTensor(f32[4096, 1024])`,\n...\n)\n## Return values\n", + "text":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___2___mlp_fc2_bias[name=p_getattr_l__self___trunk_blocks___2___mlp_fc2_bias]. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"FxOnnxInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":414 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0008", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___3___norm1_weight[name=p_getattr_l__self___trunk_blocks___3___norm1_weight]. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature FxOnnxInterpreter.run_node\n- self: \n- node: fx.Node(p_getattr_l__self___trunk_blocks___3___norm1_weight)[placeholder]:Tensor(f32[1024])\n- fx_graph_module: torch.fx.GraphModule(torch_nn_modules_container_Sequential)\n- onnxfunction_dispatcher: \n- op_level_debug: False\n- onnxscript_graph: \n- onnxscript_tracer: \n- fx_name_to_onnxscript_value: Dict[length=37](\nclone: `TorchScriptTensor(f32[4, 1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_weight: `TorchScriptTensor(f32[3072, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_bias: `TorchScriptTensor(f32[3072])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_weight: `TorchScriptTensor(f32[1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm2_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm2_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___mlp_fc1_weight: `TorchScriptTensor(f32[4096, 1024])`,\n...\n)\n## Return values\n", + "text":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___3___norm1_weight[name=p_getattr_l__self___trunk_blocks___3___norm1_weight]. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"FxOnnxInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":414 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0008", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___3___norm1_bias[name=p_getattr_l__self___trunk_blocks___3___norm1_bias]. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature FxOnnxInterpreter.run_node\n- self: \n- node: fx.Node(p_getattr_l__self___trunk_blocks___3___norm1_bias)[placeholder]:Tensor(f32[1024])\n- fx_graph_module: torch.fx.GraphModule(torch_nn_modules_container_Sequential)\n- onnxfunction_dispatcher: \n- op_level_debug: False\n- onnxscript_graph: \n- onnxscript_tracer: \n- fx_name_to_onnxscript_value: Dict[length=38](\nclone: `TorchScriptTensor(f32[4, 1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_weight: `TorchScriptTensor(f32[3072, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_bias: `TorchScriptTensor(f32[3072])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_weight: `TorchScriptTensor(f32[1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm2_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm2_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___mlp_fc1_weight: `TorchScriptTensor(f32[4096, 1024])`,\n...\n)\n## Return values\n", + "text":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___3___norm1_bias[name=p_getattr_l__self___trunk_blocks___3___norm1_bias]. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"FxOnnxInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":414 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0008", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___3___attn_qkv_weight[name=p_getattr_l__self___trunk_blocks___3___attn_qkv_weight]. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature FxOnnxInterpreter.run_node\n- self: \n- node: fx.Node(p_getattr_l__self___trunk_blocks___3___attn_qkv_weight)[placeholder]:Tensor(f32[3072, 1024])\n- fx_graph_module: torch.fx.GraphModule(torch_nn_modules_container_Sequential)\n- onnxfunction_dispatcher: \n- op_level_debug: False\n- onnxscript_graph: \n- onnxscript_tracer: \n- fx_name_to_onnxscript_value: Dict[length=39](\nclone: `TorchScriptTensor(f32[4, 1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_weight: `TorchScriptTensor(f32[3072, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_bias: `TorchScriptTensor(f32[3072])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_weight: `TorchScriptTensor(f32[1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm2_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm2_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___mlp_fc1_weight: `TorchScriptTensor(f32[4096, 1024])`,\n...\n)\n## Return values\n", + "text":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___3___attn_qkv_weight[name=p_getattr_l__self___trunk_blocks___3___attn_qkv_weight]. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"FxOnnxInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":414 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0008", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___3___attn_qkv_bias[name=p_getattr_l__self___trunk_blocks___3___attn_qkv_bias]. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature FxOnnxInterpreter.run_node\n- self: \n- node: fx.Node(p_getattr_l__self___trunk_blocks___3___attn_qkv_bias)[placeholder]:Tensor(f32[3072])\n- fx_graph_module: torch.fx.GraphModule(torch_nn_modules_container_Sequential)\n- onnxfunction_dispatcher: \n- op_level_debug: False\n- onnxscript_graph: \n- onnxscript_tracer: \n- fx_name_to_onnxscript_value: Dict[length=40](\nclone: `TorchScriptTensor(f32[4, 1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_weight: `TorchScriptTensor(f32[3072, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_bias: `TorchScriptTensor(f32[3072])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_weight: `TorchScriptTensor(f32[1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm2_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm2_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___mlp_fc1_weight: `TorchScriptTensor(f32[4096, 1024])`,\n...\n)\n## Return values\n", + "text":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___3___attn_qkv_bias[name=p_getattr_l__self___trunk_blocks___3___attn_qkv_bias]. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"FxOnnxInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":414 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0008", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___3___attn_proj_weight[name=p_getattr_l__self___trunk_blocks___3___attn_proj_weight]. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature FxOnnxInterpreter.run_node\n- self: \n- node: fx.Node(p_getattr_l__self___trunk_blocks___3___attn_proj_weight)[placeholder]:Tensor(f32[1024, 1024])\n- fx_graph_module: torch.fx.GraphModule(torch_nn_modules_container_Sequential)\n- onnxfunction_dispatcher: \n- op_level_debug: False\n- onnxscript_graph: \n- onnxscript_tracer: \n- fx_name_to_onnxscript_value: Dict[length=41](\nclone: `TorchScriptTensor(f32[4, 1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_weight: `TorchScriptTensor(f32[3072, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_bias: `TorchScriptTensor(f32[3072])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_weight: `TorchScriptTensor(f32[1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm2_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm2_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___mlp_fc1_weight: `TorchScriptTensor(f32[4096, 1024])`,\n...\n)\n## Return values\n", + "text":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___3___attn_proj_weight[name=p_getattr_l__self___trunk_blocks___3___attn_proj_weight]. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"FxOnnxInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":414 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0008", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___3___attn_proj_bias[name=p_getattr_l__self___trunk_blocks___3___attn_proj_bias]. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature FxOnnxInterpreter.run_node\n- self: \n- node: fx.Node(p_getattr_l__self___trunk_blocks___3___attn_proj_bias)[placeholder]:Tensor(f32[1024])\n- fx_graph_module: torch.fx.GraphModule(torch_nn_modules_container_Sequential)\n- onnxfunction_dispatcher: \n- op_level_debug: False\n- onnxscript_graph: \n- onnxscript_tracer: \n- fx_name_to_onnxscript_value: Dict[length=42](\nclone: `TorchScriptTensor(f32[4, 1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_weight: `TorchScriptTensor(f32[3072, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_bias: `TorchScriptTensor(f32[3072])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_weight: `TorchScriptTensor(f32[1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm2_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm2_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___mlp_fc1_weight: `TorchScriptTensor(f32[4096, 1024])`,\n...\n)\n## Return values\n", + "text":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___3___attn_proj_bias[name=p_getattr_l__self___trunk_blocks___3___attn_proj_bias]. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"FxOnnxInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":414 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0008", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___3___norm2_weight[name=p_getattr_l__self___trunk_blocks___3___norm2_weight]. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature FxOnnxInterpreter.run_node\n- self: \n- node: fx.Node(p_getattr_l__self___trunk_blocks___3___norm2_weight)[placeholder]:Tensor(f32[1024])\n- fx_graph_module: torch.fx.GraphModule(torch_nn_modules_container_Sequential)\n- onnxfunction_dispatcher: \n- op_level_debug: False\n- onnxscript_graph: \n- onnxscript_tracer: \n- fx_name_to_onnxscript_value: Dict[length=43](\nclone: `TorchScriptTensor(f32[4, 1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_weight: `TorchScriptTensor(f32[3072, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_bias: `TorchScriptTensor(f32[3072])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_weight: `TorchScriptTensor(f32[1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm2_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm2_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___mlp_fc1_weight: `TorchScriptTensor(f32[4096, 1024])`,\n...\n)\n## Return values\n", + "text":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___3___norm2_weight[name=p_getattr_l__self___trunk_blocks___3___norm2_weight]. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"FxOnnxInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":414 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0008", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___3___norm2_bias[name=p_getattr_l__self___trunk_blocks___3___norm2_bias]. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature FxOnnxInterpreter.run_node\n- self: \n- node: fx.Node(p_getattr_l__self___trunk_blocks___3___norm2_bias)[placeholder]:Tensor(f32[1024])\n- fx_graph_module: torch.fx.GraphModule(torch_nn_modules_container_Sequential)\n- onnxfunction_dispatcher: \n- op_level_debug: False\n- onnxscript_graph: \n- onnxscript_tracer: \n- fx_name_to_onnxscript_value: Dict[length=44](\nclone: `TorchScriptTensor(f32[4, 1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_weight: `TorchScriptTensor(f32[3072, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_bias: `TorchScriptTensor(f32[3072])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_weight: `TorchScriptTensor(f32[1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm2_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm2_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___mlp_fc1_weight: `TorchScriptTensor(f32[4096, 1024])`,\n...\n)\n## Return values\n", + "text":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___3___norm2_bias[name=p_getattr_l__self___trunk_blocks___3___norm2_bias]. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"FxOnnxInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":414 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0008", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___3___mlp_fc1_weight[name=p_getattr_l__self___trunk_blocks___3___mlp_fc1_weight]. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature FxOnnxInterpreter.run_node\n- self: \n- node: fx.Node(p_getattr_l__self___trunk_blocks___3___mlp_fc1_weight)[placeholder]:Tensor(f32[4096, 1024])\n- fx_graph_module: torch.fx.GraphModule(torch_nn_modules_container_Sequential)\n- onnxfunction_dispatcher: \n- op_level_debug: False\n- onnxscript_graph: \n- onnxscript_tracer: \n- fx_name_to_onnxscript_value: Dict[length=45](\nclone: `TorchScriptTensor(f32[4, 1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_weight: `TorchScriptTensor(f32[3072, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_bias: `TorchScriptTensor(f32[3072])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_weight: `TorchScriptTensor(f32[1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm2_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm2_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___mlp_fc1_weight: `TorchScriptTensor(f32[4096, 1024])`,\n...\n)\n## Return values\n", + "text":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___3___mlp_fc1_weight[name=p_getattr_l__self___trunk_blocks___3___mlp_fc1_weight]. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"FxOnnxInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":414 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0008", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___3___mlp_fc1_bias[name=p_getattr_l__self___trunk_blocks___3___mlp_fc1_bias]. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature FxOnnxInterpreter.run_node\n- self: \n- node: fx.Node(p_getattr_l__self___trunk_blocks___3___mlp_fc1_bias)[placeholder]:Tensor(f32[4096])\n- fx_graph_module: torch.fx.GraphModule(torch_nn_modules_container_Sequential)\n- onnxfunction_dispatcher: \n- op_level_debug: False\n- onnxscript_graph: \n- onnxscript_tracer: \n- fx_name_to_onnxscript_value: Dict[length=46](\nclone: `TorchScriptTensor(f32[4, 1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_weight: `TorchScriptTensor(f32[3072, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_bias: `TorchScriptTensor(f32[3072])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_weight: `TorchScriptTensor(f32[1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm2_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm2_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___mlp_fc1_weight: `TorchScriptTensor(f32[4096, 1024])`,\n...\n)\n## Return values\n", + "text":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___3___mlp_fc1_bias[name=p_getattr_l__self___trunk_blocks___3___mlp_fc1_bias]. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"FxOnnxInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":414 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0008", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___3___mlp_fc2_weight[name=p_getattr_l__self___trunk_blocks___3___mlp_fc2_weight]. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature FxOnnxInterpreter.run_node\n- self: \n- node: fx.Node(p_getattr_l__self___trunk_blocks___3___mlp_fc2_weight)[placeholder]:Tensor(f32[1024, 4096])\n- fx_graph_module: torch.fx.GraphModule(torch_nn_modules_container_Sequential)\n- onnxfunction_dispatcher: \n- op_level_debug: False\n- onnxscript_graph: \n- onnxscript_tracer: \n- fx_name_to_onnxscript_value: Dict[length=47](\nclone: `TorchScriptTensor(f32[4, 1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_weight: `TorchScriptTensor(f32[3072, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_bias: `TorchScriptTensor(f32[3072])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_weight: `TorchScriptTensor(f32[1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm2_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm2_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___mlp_fc1_weight: `TorchScriptTensor(f32[4096, 1024])`,\n...\n)\n## Return values\n", + "text":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___3___mlp_fc2_weight[name=p_getattr_l__self___trunk_blocks___3___mlp_fc2_weight]. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"FxOnnxInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":414 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0008", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___3___mlp_fc2_bias[name=p_getattr_l__self___trunk_blocks___3___mlp_fc2_bias]. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature FxOnnxInterpreter.run_node\n- self: \n- node: fx.Node(p_getattr_l__self___trunk_blocks___3___mlp_fc2_bias)[placeholder]:Tensor(f32[1024])\n- fx_graph_module: torch.fx.GraphModule(torch_nn_modules_container_Sequential)\n- onnxfunction_dispatcher: \n- op_level_debug: False\n- onnxscript_graph: \n- onnxscript_tracer: \n- fx_name_to_onnxscript_value: Dict[length=48](\nclone: `TorchScriptTensor(f32[4, 1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_weight: `TorchScriptTensor(f32[3072, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_bias: `TorchScriptTensor(f32[3072])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_weight: `TorchScriptTensor(f32[1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm2_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm2_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___mlp_fc1_weight: `TorchScriptTensor(f32[4096, 1024])`,\n...\n)\n## Return values\n", + "text":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___3___mlp_fc2_bias[name=p_getattr_l__self___trunk_blocks___3___mlp_fc2_bias]. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"FxOnnxInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":414 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0008", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___4___norm1_weight[name=p_getattr_l__self___trunk_blocks___4___norm1_weight]. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature FxOnnxInterpreter.run_node\n- self: \n- node: fx.Node(p_getattr_l__self___trunk_blocks___4___norm1_weight)[placeholder]:Tensor(f32[1024])\n- fx_graph_module: torch.fx.GraphModule(torch_nn_modules_container_Sequential)\n- onnxfunction_dispatcher: \n- op_level_debug: False\n- onnxscript_graph: \n- onnxscript_tracer: \n- fx_name_to_onnxscript_value: Dict[length=49](\nclone: `TorchScriptTensor(f32[4, 1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_weight: `TorchScriptTensor(f32[3072, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_bias: `TorchScriptTensor(f32[3072])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_weight: `TorchScriptTensor(f32[1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm2_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm2_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___mlp_fc1_weight: `TorchScriptTensor(f32[4096, 1024])`,\n...\n)\n## Return values\n", + "text":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___4___norm1_weight[name=p_getattr_l__self___trunk_blocks___4___norm1_weight]. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"FxOnnxInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":414 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0008", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___4___norm1_bias[name=p_getattr_l__self___trunk_blocks___4___norm1_bias]. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature FxOnnxInterpreter.run_node\n- self: \n- node: fx.Node(p_getattr_l__self___trunk_blocks___4___norm1_bias)[placeholder]:Tensor(f32[1024])\n- fx_graph_module: torch.fx.GraphModule(torch_nn_modules_container_Sequential)\n- onnxfunction_dispatcher: \n- op_level_debug: False\n- onnxscript_graph: \n- onnxscript_tracer: \n- fx_name_to_onnxscript_value: Dict[length=50](\nclone: `TorchScriptTensor(f32[4, 1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_weight: `TorchScriptTensor(f32[3072, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_bias: `TorchScriptTensor(f32[3072])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_weight: `TorchScriptTensor(f32[1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm2_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm2_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___mlp_fc1_weight: `TorchScriptTensor(f32[4096, 1024])`,\n...\n)\n## Return values\n", + "text":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___4___norm1_bias[name=p_getattr_l__self___trunk_blocks___4___norm1_bias]. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"FxOnnxInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":414 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0008", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___4___attn_qkv_weight[name=p_getattr_l__self___trunk_blocks___4___attn_qkv_weight]. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature FxOnnxInterpreter.run_node\n- self: \n- node: fx.Node(p_getattr_l__self___trunk_blocks___4___attn_qkv_weight)[placeholder]:Tensor(f32[3072, 1024])\n- fx_graph_module: torch.fx.GraphModule(torch_nn_modules_container_Sequential)\n- onnxfunction_dispatcher: \n- op_level_debug: False\n- onnxscript_graph: \n- onnxscript_tracer: \n- fx_name_to_onnxscript_value: Dict[length=51](\nclone: `TorchScriptTensor(f32[4, 1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_weight: `TorchScriptTensor(f32[3072, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_bias: `TorchScriptTensor(f32[3072])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_weight: `TorchScriptTensor(f32[1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm2_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm2_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___mlp_fc1_weight: `TorchScriptTensor(f32[4096, 1024])`,\n...\n)\n## Return values\n", + "text":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___4___attn_qkv_weight[name=p_getattr_l__self___trunk_blocks___4___attn_qkv_weight]. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"FxOnnxInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":414 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0008", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___4___attn_qkv_bias[name=p_getattr_l__self___trunk_blocks___4___attn_qkv_bias]. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature FxOnnxInterpreter.run_node\n- self: \n- node: fx.Node(p_getattr_l__self___trunk_blocks___4___attn_qkv_bias)[placeholder]:Tensor(f32[3072])\n- fx_graph_module: torch.fx.GraphModule(torch_nn_modules_container_Sequential)\n- onnxfunction_dispatcher: \n- op_level_debug: False\n- onnxscript_graph: \n- onnxscript_tracer: \n- fx_name_to_onnxscript_value: Dict[length=52](\nclone: `TorchScriptTensor(f32[4, 1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_weight: `TorchScriptTensor(f32[3072, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_bias: `TorchScriptTensor(f32[3072])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_weight: `TorchScriptTensor(f32[1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm2_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm2_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___mlp_fc1_weight: `TorchScriptTensor(f32[4096, 1024])`,\n...\n)\n## Return values\n", + "text":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___4___attn_qkv_bias[name=p_getattr_l__self___trunk_blocks___4___attn_qkv_bias]. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"FxOnnxInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":414 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0008", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___4___attn_proj_weight[name=p_getattr_l__self___trunk_blocks___4___attn_proj_weight]. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature FxOnnxInterpreter.run_node\n- self: \n- node: fx.Node(p_getattr_l__self___trunk_blocks___4___attn_proj_weight)[placeholder]:Tensor(f32[1024, 1024])\n- fx_graph_module: torch.fx.GraphModule(torch_nn_modules_container_Sequential)\n- onnxfunction_dispatcher: \n- op_level_debug: False\n- onnxscript_graph: \n- onnxscript_tracer: \n- fx_name_to_onnxscript_value: Dict[length=53](\nclone: `TorchScriptTensor(f32[4, 1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_weight: `TorchScriptTensor(f32[3072, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_bias: `TorchScriptTensor(f32[3072])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_weight: `TorchScriptTensor(f32[1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm2_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm2_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___mlp_fc1_weight: `TorchScriptTensor(f32[4096, 1024])`,\n...\n)\n## Return values\n", + "text":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___4___attn_proj_weight[name=p_getattr_l__self___trunk_blocks___4___attn_proj_weight]. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"FxOnnxInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":414 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0008", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___4___attn_proj_bias[name=p_getattr_l__self___trunk_blocks___4___attn_proj_bias]. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature FxOnnxInterpreter.run_node\n- self: \n- node: fx.Node(p_getattr_l__self___trunk_blocks___4___attn_proj_bias)[placeholder]:Tensor(f32[1024])\n- fx_graph_module: torch.fx.GraphModule(torch_nn_modules_container_Sequential)\n- onnxfunction_dispatcher: \n- op_level_debug: False\n- onnxscript_graph: \n- onnxscript_tracer: \n- fx_name_to_onnxscript_value: Dict[length=54](\nclone: `TorchScriptTensor(f32[4, 1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_weight: `TorchScriptTensor(f32[3072, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_bias: `TorchScriptTensor(f32[3072])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_weight: `TorchScriptTensor(f32[1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm2_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm2_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___mlp_fc1_weight: `TorchScriptTensor(f32[4096, 1024])`,\n...\n)\n## Return values\n", + "text":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___4___attn_proj_bias[name=p_getattr_l__self___trunk_blocks___4___attn_proj_bias]. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"FxOnnxInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":414 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0008", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___4___norm2_weight[name=p_getattr_l__self___trunk_blocks___4___norm2_weight]. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature FxOnnxInterpreter.run_node\n- self: \n- node: fx.Node(p_getattr_l__self___trunk_blocks___4___norm2_weight)[placeholder]:Tensor(f32[1024])\n- fx_graph_module: torch.fx.GraphModule(torch_nn_modules_container_Sequential)\n- onnxfunction_dispatcher: \n- op_level_debug: False\n- onnxscript_graph: \n- onnxscript_tracer: \n- fx_name_to_onnxscript_value: Dict[length=55](\nclone: `TorchScriptTensor(f32[4, 1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_weight: `TorchScriptTensor(f32[3072, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_bias: `TorchScriptTensor(f32[3072])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_weight: `TorchScriptTensor(f32[1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm2_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm2_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___mlp_fc1_weight: `TorchScriptTensor(f32[4096, 1024])`,\n...\n)\n## Return values\n", + "text":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___4___norm2_weight[name=p_getattr_l__self___trunk_blocks___4___norm2_weight]. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"FxOnnxInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":414 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0008", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___4___norm2_bias[name=p_getattr_l__self___trunk_blocks___4___norm2_bias]. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature FxOnnxInterpreter.run_node\n- self: \n- node: fx.Node(p_getattr_l__self___trunk_blocks___4___norm2_bias)[placeholder]:Tensor(f32[1024])\n- fx_graph_module: torch.fx.GraphModule(torch_nn_modules_container_Sequential)\n- onnxfunction_dispatcher: \n- op_level_debug: False\n- onnxscript_graph: \n- onnxscript_tracer: \n- fx_name_to_onnxscript_value: Dict[length=56](\nclone: `TorchScriptTensor(f32[4, 1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_weight: `TorchScriptTensor(f32[3072, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_bias: `TorchScriptTensor(f32[3072])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_weight: `TorchScriptTensor(f32[1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm2_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm2_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___mlp_fc1_weight: `TorchScriptTensor(f32[4096, 1024])`,\n...\n)\n## Return values\n", + "text":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___4___norm2_bias[name=p_getattr_l__self___trunk_blocks___4___norm2_bias]. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"FxOnnxInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":414 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0008", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___4___mlp_fc1_weight[name=p_getattr_l__self___trunk_blocks___4___mlp_fc1_weight]. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature FxOnnxInterpreter.run_node\n- self: \n- node: fx.Node(p_getattr_l__self___trunk_blocks___4___mlp_fc1_weight)[placeholder]:Tensor(f32[4096, 1024])\n- fx_graph_module: torch.fx.GraphModule(torch_nn_modules_container_Sequential)\n- onnxfunction_dispatcher: \n- op_level_debug: False\n- onnxscript_graph: \n- onnxscript_tracer: \n- fx_name_to_onnxscript_value: Dict[length=57](\nclone: `TorchScriptTensor(f32[4, 1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_weight: `TorchScriptTensor(f32[3072, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_bias: `TorchScriptTensor(f32[3072])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_weight: `TorchScriptTensor(f32[1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm2_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm2_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___mlp_fc1_weight: `TorchScriptTensor(f32[4096, 1024])`,\n...\n)\n## Return values\n", + "text":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___4___mlp_fc1_weight[name=p_getattr_l__self___trunk_blocks___4___mlp_fc1_weight]. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"FxOnnxInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":414 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0008", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___4___mlp_fc1_bias[name=p_getattr_l__self___trunk_blocks___4___mlp_fc1_bias]. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature FxOnnxInterpreter.run_node\n- self: \n- node: fx.Node(p_getattr_l__self___trunk_blocks___4___mlp_fc1_bias)[placeholder]:Tensor(f32[4096])\n- fx_graph_module: torch.fx.GraphModule(torch_nn_modules_container_Sequential)\n- onnxfunction_dispatcher: \n- op_level_debug: False\n- onnxscript_graph: \n- onnxscript_tracer: \n- fx_name_to_onnxscript_value: Dict[length=58](\nclone: `TorchScriptTensor(f32[4, 1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_weight: `TorchScriptTensor(f32[3072, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_bias: `TorchScriptTensor(f32[3072])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_weight: `TorchScriptTensor(f32[1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm2_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm2_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___mlp_fc1_weight: `TorchScriptTensor(f32[4096, 1024])`,\n...\n)\n## Return values\n", + "text":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___4___mlp_fc1_bias[name=p_getattr_l__self___trunk_blocks___4___mlp_fc1_bias]. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"FxOnnxInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":414 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0008", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___4___mlp_fc2_weight[name=p_getattr_l__self___trunk_blocks___4___mlp_fc2_weight]. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature FxOnnxInterpreter.run_node\n- self: \n- node: fx.Node(p_getattr_l__self___trunk_blocks___4___mlp_fc2_weight)[placeholder]:Tensor(f32[1024, 4096])\n- fx_graph_module: torch.fx.GraphModule(torch_nn_modules_container_Sequential)\n- onnxfunction_dispatcher: \n- op_level_debug: False\n- onnxscript_graph: \n- onnxscript_tracer: \n- fx_name_to_onnxscript_value: Dict[length=59](\nclone: `TorchScriptTensor(f32[4, 1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_weight: `TorchScriptTensor(f32[3072, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_bias: `TorchScriptTensor(f32[3072])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_weight: `TorchScriptTensor(f32[1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm2_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm2_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___mlp_fc1_weight: `TorchScriptTensor(f32[4096, 1024])`,\n...\n)\n## Return values\n", + "text":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___4___mlp_fc2_weight[name=p_getattr_l__self___trunk_blocks___4___mlp_fc2_weight]. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"FxOnnxInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":414 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0008", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___4___mlp_fc2_bias[name=p_getattr_l__self___trunk_blocks___4___mlp_fc2_bias]. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature FxOnnxInterpreter.run_node\n- self: \n- node: fx.Node(p_getattr_l__self___trunk_blocks___4___mlp_fc2_bias)[placeholder]:Tensor(f32[1024])\n- fx_graph_module: torch.fx.GraphModule(torch_nn_modules_container_Sequential)\n- onnxfunction_dispatcher: \n- op_level_debug: False\n- onnxscript_graph: \n- onnxscript_tracer: \n- fx_name_to_onnxscript_value: Dict[length=60](\nclone: `TorchScriptTensor(f32[4, 1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_weight: `TorchScriptTensor(f32[3072, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_bias: `TorchScriptTensor(f32[3072])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_weight: `TorchScriptTensor(f32[1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm2_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm2_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___mlp_fc1_weight: `TorchScriptTensor(f32[4096, 1024])`,\n...\n)\n## Return values\n", + "text":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___4___mlp_fc2_bias[name=p_getattr_l__self___trunk_blocks___4___mlp_fc2_bias]. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"FxOnnxInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":414 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0008", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___5___norm1_weight[name=p_getattr_l__self___trunk_blocks___5___norm1_weight]. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature FxOnnxInterpreter.run_node\n- self: \n- node: fx.Node(p_getattr_l__self___trunk_blocks___5___norm1_weight)[placeholder]:Tensor(f32[1024])\n- fx_graph_module: torch.fx.GraphModule(torch_nn_modules_container_Sequential)\n- onnxfunction_dispatcher: \n- op_level_debug: False\n- onnxscript_graph: \n- onnxscript_tracer: \n- fx_name_to_onnxscript_value: Dict[length=61](\nclone: `TorchScriptTensor(f32[4, 1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_weight: `TorchScriptTensor(f32[3072, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_bias: `TorchScriptTensor(f32[3072])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_weight: `TorchScriptTensor(f32[1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm2_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm2_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___mlp_fc1_weight: `TorchScriptTensor(f32[4096, 1024])`,\n...\n)\n## Return values\n", + "text":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___5___norm1_weight[name=p_getattr_l__self___trunk_blocks___5___norm1_weight]. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"FxOnnxInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":414 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0008", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___5___norm1_bias[name=p_getattr_l__self___trunk_blocks___5___norm1_bias]. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature FxOnnxInterpreter.run_node\n- self: \n- node: fx.Node(p_getattr_l__self___trunk_blocks___5___norm1_bias)[placeholder]:Tensor(f32[1024])\n- fx_graph_module: torch.fx.GraphModule(torch_nn_modules_container_Sequential)\n- onnxfunction_dispatcher: \n- op_level_debug: False\n- onnxscript_graph: \n- onnxscript_tracer: \n- fx_name_to_onnxscript_value: Dict[length=62](\nclone: `TorchScriptTensor(f32[4, 1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_weight: `TorchScriptTensor(f32[3072, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_bias: `TorchScriptTensor(f32[3072])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_weight: `TorchScriptTensor(f32[1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm2_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm2_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___mlp_fc1_weight: `TorchScriptTensor(f32[4096, 1024])`,\n...\n)\n## Return values\n", + "text":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___5___norm1_bias[name=p_getattr_l__self___trunk_blocks___5___norm1_bias]. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"FxOnnxInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":414 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0008", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___5___attn_qkv_weight[name=p_getattr_l__self___trunk_blocks___5___attn_qkv_weight]. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature FxOnnxInterpreter.run_node\n- self: \n- node: fx.Node(p_getattr_l__self___trunk_blocks___5___attn_qkv_weight)[placeholder]:Tensor(f32[3072, 1024])\n- fx_graph_module: torch.fx.GraphModule(torch_nn_modules_container_Sequential)\n- onnxfunction_dispatcher: \n- op_level_debug: False\n- onnxscript_graph: \n- onnxscript_tracer: \n- fx_name_to_onnxscript_value: Dict[length=63](\nclone: `TorchScriptTensor(f32[4, 1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_weight: `TorchScriptTensor(f32[3072, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_bias: `TorchScriptTensor(f32[3072])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_weight: `TorchScriptTensor(f32[1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm2_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm2_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___mlp_fc1_weight: `TorchScriptTensor(f32[4096, 1024])`,\n...\n)\n## Return values\n", + "text":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___5___attn_qkv_weight[name=p_getattr_l__self___trunk_blocks___5___attn_qkv_weight]. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"FxOnnxInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":414 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0008", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___5___attn_qkv_bias[name=p_getattr_l__self___trunk_blocks___5___attn_qkv_bias]. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature FxOnnxInterpreter.run_node\n- self: \n- node: fx.Node(p_getattr_l__self___trunk_blocks___5___attn_qkv_bias)[placeholder]:Tensor(f32[3072])\n- fx_graph_module: torch.fx.GraphModule(torch_nn_modules_container_Sequential)\n- onnxfunction_dispatcher: \n- op_level_debug: False\n- onnxscript_graph: \n- onnxscript_tracer: \n- fx_name_to_onnxscript_value: Dict[length=64](\nclone: `TorchScriptTensor(f32[4, 1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_weight: `TorchScriptTensor(f32[3072, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_bias: `TorchScriptTensor(f32[3072])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_weight: `TorchScriptTensor(f32[1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm2_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm2_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___mlp_fc1_weight: `TorchScriptTensor(f32[4096, 1024])`,\n...\n)\n## Return values\n", + "text":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___5___attn_qkv_bias[name=p_getattr_l__self___trunk_blocks___5___attn_qkv_bias]. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"FxOnnxInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":414 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0008", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___5___attn_proj_weight[name=p_getattr_l__self___trunk_blocks___5___attn_proj_weight]. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature FxOnnxInterpreter.run_node\n- self: \n- node: fx.Node(p_getattr_l__self___trunk_blocks___5___attn_proj_weight)[placeholder]:Tensor(f32[1024, 1024])\n- fx_graph_module: torch.fx.GraphModule(torch_nn_modules_container_Sequential)\n- onnxfunction_dispatcher: \n- op_level_debug: False\n- onnxscript_graph: \n- onnxscript_tracer: \n- fx_name_to_onnxscript_value: Dict[length=65](\nclone: `TorchScriptTensor(f32[4, 1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_weight: `TorchScriptTensor(f32[3072, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_bias: `TorchScriptTensor(f32[3072])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_weight: `TorchScriptTensor(f32[1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm2_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm2_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___mlp_fc1_weight: `TorchScriptTensor(f32[4096, 1024])`,\n...\n)\n## Return values\n", + "text":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___5___attn_proj_weight[name=p_getattr_l__self___trunk_blocks___5___attn_proj_weight]. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"FxOnnxInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":414 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0008", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___5___attn_proj_bias[name=p_getattr_l__self___trunk_blocks___5___attn_proj_bias]. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature FxOnnxInterpreter.run_node\n- self: \n- node: fx.Node(p_getattr_l__self___trunk_blocks___5___attn_proj_bias)[placeholder]:Tensor(f32[1024])\n- fx_graph_module: torch.fx.GraphModule(torch_nn_modules_container_Sequential)\n- onnxfunction_dispatcher: \n- op_level_debug: False\n- onnxscript_graph: \n- onnxscript_tracer: \n- fx_name_to_onnxscript_value: Dict[length=66](\nclone: `TorchScriptTensor(f32[4, 1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_weight: `TorchScriptTensor(f32[3072, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_bias: `TorchScriptTensor(f32[3072])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_weight: `TorchScriptTensor(f32[1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm2_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm2_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___mlp_fc1_weight: `TorchScriptTensor(f32[4096, 1024])`,\n...\n)\n## Return values\n", + "text":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___5___attn_proj_bias[name=p_getattr_l__self___trunk_blocks___5___attn_proj_bias]. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"FxOnnxInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":414 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0008", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___5___norm2_weight[name=p_getattr_l__self___trunk_blocks___5___norm2_weight]. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature FxOnnxInterpreter.run_node\n- self: \n- node: fx.Node(p_getattr_l__self___trunk_blocks___5___norm2_weight)[placeholder]:Tensor(f32[1024])\n- fx_graph_module: torch.fx.GraphModule(torch_nn_modules_container_Sequential)\n- onnxfunction_dispatcher: \n- op_level_debug: False\n- onnxscript_graph: \n- onnxscript_tracer: \n- fx_name_to_onnxscript_value: Dict[length=67](\nclone: `TorchScriptTensor(f32[4, 1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_weight: `TorchScriptTensor(f32[3072, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_bias: `TorchScriptTensor(f32[3072])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_weight: `TorchScriptTensor(f32[1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm2_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm2_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___mlp_fc1_weight: `TorchScriptTensor(f32[4096, 1024])`,\n...\n)\n## Return values\n", + "text":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___5___norm2_weight[name=p_getattr_l__self___trunk_blocks___5___norm2_weight]. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"FxOnnxInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":414 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0008", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___5___norm2_bias[name=p_getattr_l__self___trunk_blocks___5___norm2_bias]. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature FxOnnxInterpreter.run_node\n- self: \n- node: fx.Node(p_getattr_l__self___trunk_blocks___5___norm2_bias)[placeholder]:Tensor(f32[1024])\n- fx_graph_module: torch.fx.GraphModule(torch_nn_modules_container_Sequential)\n- onnxfunction_dispatcher: \n- op_level_debug: False\n- onnxscript_graph: \n- onnxscript_tracer: \n- fx_name_to_onnxscript_value: Dict[length=68](\nclone: `TorchScriptTensor(f32[4, 1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_weight: `TorchScriptTensor(f32[3072, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_bias: `TorchScriptTensor(f32[3072])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_weight: `TorchScriptTensor(f32[1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm2_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm2_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___mlp_fc1_weight: `TorchScriptTensor(f32[4096, 1024])`,\n...\n)\n## Return values\n", + "text":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___5___norm2_bias[name=p_getattr_l__self___trunk_blocks___5___norm2_bias]. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"FxOnnxInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":414 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0008", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___5___mlp_fc1_weight[name=p_getattr_l__self___trunk_blocks___5___mlp_fc1_weight]. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature FxOnnxInterpreter.run_node\n- self: \n- node: fx.Node(p_getattr_l__self___trunk_blocks___5___mlp_fc1_weight)[placeholder]:Tensor(f32[4096, 1024])\n- fx_graph_module: torch.fx.GraphModule(torch_nn_modules_container_Sequential)\n- onnxfunction_dispatcher: \n- op_level_debug: False\n- onnxscript_graph: \n- onnxscript_tracer: \n- fx_name_to_onnxscript_value: Dict[length=69](\nclone: `TorchScriptTensor(f32[4, 1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_weight: `TorchScriptTensor(f32[3072, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_bias: `TorchScriptTensor(f32[3072])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_weight: `TorchScriptTensor(f32[1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm2_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm2_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___mlp_fc1_weight: `TorchScriptTensor(f32[4096, 1024])`,\n...\n)\n## Return values\n", + "text":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___5___mlp_fc1_weight[name=p_getattr_l__self___trunk_blocks___5___mlp_fc1_weight]. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"FxOnnxInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":414 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0008", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___5___mlp_fc1_bias[name=p_getattr_l__self___trunk_blocks___5___mlp_fc1_bias]. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature FxOnnxInterpreter.run_node\n- self: \n- node: fx.Node(p_getattr_l__self___trunk_blocks___5___mlp_fc1_bias)[placeholder]:Tensor(f32[4096])\n- fx_graph_module: torch.fx.GraphModule(torch_nn_modules_container_Sequential)\n- onnxfunction_dispatcher: \n- op_level_debug: False\n- onnxscript_graph: \n- onnxscript_tracer: \n- fx_name_to_onnxscript_value: Dict[length=70](\nclone: `TorchScriptTensor(f32[4, 1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_weight: `TorchScriptTensor(f32[3072, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_bias: `TorchScriptTensor(f32[3072])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_weight: `TorchScriptTensor(f32[1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm2_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm2_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___mlp_fc1_weight: `TorchScriptTensor(f32[4096, 1024])`,\n...\n)\n## Return values\n", + "text":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___5___mlp_fc1_bias[name=p_getattr_l__self___trunk_blocks___5___mlp_fc1_bias]. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"FxOnnxInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":414 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0008", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___5___mlp_fc2_weight[name=p_getattr_l__self___trunk_blocks___5___mlp_fc2_weight]. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature FxOnnxInterpreter.run_node\n- self: \n- node: fx.Node(p_getattr_l__self___trunk_blocks___5___mlp_fc2_weight)[placeholder]:Tensor(f32[1024, 4096])\n- fx_graph_module: torch.fx.GraphModule(torch_nn_modules_container_Sequential)\n- onnxfunction_dispatcher: \n- op_level_debug: False\n- onnxscript_graph: \n- onnxscript_tracer: \n- fx_name_to_onnxscript_value: Dict[length=71](\nclone: `TorchScriptTensor(f32[4, 1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_weight: `TorchScriptTensor(f32[3072, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_bias: `TorchScriptTensor(f32[3072])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_weight: `TorchScriptTensor(f32[1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm2_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm2_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___mlp_fc1_weight: `TorchScriptTensor(f32[4096, 1024])`,\n...\n)\n## Return values\n", + "text":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___5___mlp_fc2_weight[name=p_getattr_l__self___trunk_blocks___5___mlp_fc2_weight]. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"FxOnnxInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":414 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0008", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___5___mlp_fc2_bias[name=p_getattr_l__self___trunk_blocks___5___mlp_fc2_bias]. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature FxOnnxInterpreter.run_node\n- self: \n- node: fx.Node(p_getattr_l__self___trunk_blocks___5___mlp_fc2_bias)[placeholder]:Tensor(f32[1024])\n- fx_graph_module: torch.fx.GraphModule(torch_nn_modules_container_Sequential)\n- onnxfunction_dispatcher: \n- op_level_debug: False\n- onnxscript_graph: \n- onnxscript_tracer: \n- fx_name_to_onnxscript_value: Dict[length=72](\nclone: `TorchScriptTensor(f32[4, 1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_weight: `TorchScriptTensor(f32[3072, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_bias: `TorchScriptTensor(f32[3072])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_weight: `TorchScriptTensor(f32[1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm2_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm2_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___mlp_fc1_weight: `TorchScriptTensor(f32[4096, 1024])`,\n...\n)\n## Return values\n", + "text":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___5___mlp_fc2_bias[name=p_getattr_l__self___trunk_blocks___5___mlp_fc2_bias]. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"FxOnnxInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":414 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0008", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___6___norm1_weight[name=p_getattr_l__self___trunk_blocks___6___norm1_weight]. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature FxOnnxInterpreter.run_node\n- self: \n- node: fx.Node(p_getattr_l__self___trunk_blocks___6___norm1_weight)[placeholder]:Tensor(f32[1024])\n- fx_graph_module: torch.fx.GraphModule(torch_nn_modules_container_Sequential)\n- onnxfunction_dispatcher: \n- op_level_debug: False\n- onnxscript_graph: \n- onnxscript_tracer: \n- fx_name_to_onnxscript_value: Dict[length=73](\nclone: `TorchScriptTensor(f32[4, 1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_weight: `TorchScriptTensor(f32[3072, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_bias: `TorchScriptTensor(f32[3072])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_weight: `TorchScriptTensor(f32[1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm2_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm2_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___mlp_fc1_weight: `TorchScriptTensor(f32[4096, 1024])`,\n...\n)\n## Return values\n", + "text":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___6___norm1_weight[name=p_getattr_l__self___trunk_blocks___6___norm1_weight]. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"FxOnnxInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":414 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0008", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___6___norm1_bias[name=p_getattr_l__self___trunk_blocks___6___norm1_bias]. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature FxOnnxInterpreter.run_node\n- self: \n- node: fx.Node(p_getattr_l__self___trunk_blocks___6___norm1_bias)[placeholder]:Tensor(f32[1024])\n- fx_graph_module: torch.fx.GraphModule(torch_nn_modules_container_Sequential)\n- onnxfunction_dispatcher: \n- op_level_debug: False\n- onnxscript_graph: \n- onnxscript_tracer: \n- fx_name_to_onnxscript_value: Dict[length=74](\nclone: `TorchScriptTensor(f32[4, 1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_weight: `TorchScriptTensor(f32[3072, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_bias: `TorchScriptTensor(f32[3072])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_weight: `TorchScriptTensor(f32[1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm2_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm2_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___mlp_fc1_weight: `TorchScriptTensor(f32[4096, 1024])`,\n...\n)\n## Return values\n", + "text":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___6___norm1_bias[name=p_getattr_l__self___trunk_blocks___6___norm1_bias]. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"FxOnnxInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":414 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0008", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___6___attn_qkv_weight[name=p_getattr_l__self___trunk_blocks___6___attn_qkv_weight]. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature FxOnnxInterpreter.run_node\n- self: \n- node: fx.Node(p_getattr_l__self___trunk_blocks___6___attn_qkv_weight)[placeholder]:Tensor(f32[3072, 1024])\n- fx_graph_module: torch.fx.GraphModule(torch_nn_modules_container_Sequential)\n- onnxfunction_dispatcher: \n- op_level_debug: False\n- onnxscript_graph: \n- onnxscript_tracer: \n- fx_name_to_onnxscript_value: Dict[length=75](\nclone: `TorchScriptTensor(f32[4, 1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_weight: `TorchScriptTensor(f32[3072, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_bias: `TorchScriptTensor(f32[3072])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_weight: `TorchScriptTensor(f32[1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm2_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm2_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___mlp_fc1_weight: `TorchScriptTensor(f32[4096, 1024])`,\n...\n)\n## Return values\n", + "text":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___6___attn_qkv_weight[name=p_getattr_l__self___trunk_blocks___6___attn_qkv_weight]. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"FxOnnxInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":414 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0008", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___6___attn_qkv_bias[name=p_getattr_l__self___trunk_blocks___6___attn_qkv_bias]. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature FxOnnxInterpreter.run_node\n- self: \n- node: fx.Node(p_getattr_l__self___trunk_blocks___6___attn_qkv_bias)[placeholder]:Tensor(f32[3072])\n- fx_graph_module: torch.fx.GraphModule(torch_nn_modules_container_Sequential)\n- onnxfunction_dispatcher: \n- op_level_debug: False\n- onnxscript_graph: \n- onnxscript_tracer: \n- fx_name_to_onnxscript_value: Dict[length=76](\nclone: `TorchScriptTensor(f32[4, 1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_weight: `TorchScriptTensor(f32[3072, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_bias: `TorchScriptTensor(f32[3072])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_weight: `TorchScriptTensor(f32[1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm2_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm2_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___mlp_fc1_weight: `TorchScriptTensor(f32[4096, 1024])`,\n...\n)\n## Return values\n", + "text":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___6___attn_qkv_bias[name=p_getattr_l__self___trunk_blocks___6___attn_qkv_bias]. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"FxOnnxInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":414 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0008", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___6___attn_proj_weight[name=p_getattr_l__self___trunk_blocks___6___attn_proj_weight]. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature FxOnnxInterpreter.run_node\n- self: \n- node: fx.Node(p_getattr_l__self___trunk_blocks___6___attn_proj_weight)[placeholder]:Tensor(f32[1024, 1024])\n- fx_graph_module: torch.fx.GraphModule(torch_nn_modules_container_Sequential)\n- onnxfunction_dispatcher: \n- op_level_debug: False\n- onnxscript_graph: \n- onnxscript_tracer: \n- fx_name_to_onnxscript_value: Dict[length=77](\nclone: `TorchScriptTensor(f32[4, 1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_weight: `TorchScriptTensor(f32[3072, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_bias: `TorchScriptTensor(f32[3072])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_weight: `TorchScriptTensor(f32[1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm2_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm2_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___mlp_fc1_weight: `TorchScriptTensor(f32[4096, 1024])`,\n...\n)\n## Return values\n", + "text":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___6___attn_proj_weight[name=p_getattr_l__self___trunk_blocks___6___attn_proj_weight]. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"FxOnnxInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":414 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0008", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___6___attn_proj_bias[name=p_getattr_l__self___trunk_blocks___6___attn_proj_bias]. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature FxOnnxInterpreter.run_node\n- self: \n- node: fx.Node(p_getattr_l__self___trunk_blocks___6___attn_proj_bias)[placeholder]:Tensor(f32[1024])\n- fx_graph_module: torch.fx.GraphModule(torch_nn_modules_container_Sequential)\n- onnxfunction_dispatcher: \n- op_level_debug: False\n- onnxscript_graph: \n- onnxscript_tracer: \n- fx_name_to_onnxscript_value: Dict[length=78](\nclone: `TorchScriptTensor(f32[4, 1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_weight: `TorchScriptTensor(f32[3072, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_bias: `TorchScriptTensor(f32[3072])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_weight: `TorchScriptTensor(f32[1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm2_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm2_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___mlp_fc1_weight: `TorchScriptTensor(f32[4096, 1024])`,\n...\n)\n## Return values\n", + "text":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___6___attn_proj_bias[name=p_getattr_l__self___trunk_blocks___6___attn_proj_bias]. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"FxOnnxInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":414 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0008", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___6___norm2_weight[name=p_getattr_l__self___trunk_blocks___6___norm2_weight]. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature FxOnnxInterpreter.run_node\n- self: \n- node: fx.Node(p_getattr_l__self___trunk_blocks___6___norm2_weight)[placeholder]:Tensor(f32[1024])\n- fx_graph_module: torch.fx.GraphModule(torch_nn_modules_container_Sequential)\n- onnxfunction_dispatcher: \n- op_level_debug: False\n- onnxscript_graph: \n- onnxscript_tracer: \n- fx_name_to_onnxscript_value: Dict[length=79](\nclone: `TorchScriptTensor(f32[4, 1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_weight: `TorchScriptTensor(f32[3072, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_bias: `TorchScriptTensor(f32[3072])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_weight: `TorchScriptTensor(f32[1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm2_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm2_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___mlp_fc1_weight: `TorchScriptTensor(f32[4096, 1024])`,\n...\n)\n## Return values\n", + "text":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___6___norm2_weight[name=p_getattr_l__self___trunk_blocks___6___norm2_weight]. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"FxOnnxInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":414 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0008", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___6___norm2_bias[name=p_getattr_l__self___trunk_blocks___6___norm2_bias]. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature FxOnnxInterpreter.run_node\n- self: \n- node: fx.Node(p_getattr_l__self___trunk_blocks___6___norm2_bias)[placeholder]:Tensor(f32[1024])\n- fx_graph_module: torch.fx.GraphModule(torch_nn_modules_container_Sequential)\n- onnxfunction_dispatcher: \n- op_level_debug: False\n- onnxscript_graph: \n- onnxscript_tracer: \n- fx_name_to_onnxscript_value: Dict[length=80](\nclone: `TorchScriptTensor(f32[4, 1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_weight: `TorchScriptTensor(f32[3072, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_bias: `TorchScriptTensor(f32[3072])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_weight: `TorchScriptTensor(f32[1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm2_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm2_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___mlp_fc1_weight: `TorchScriptTensor(f32[4096, 1024])`,\n...\n)\n## Return values\n", + "text":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___6___norm2_bias[name=p_getattr_l__self___trunk_blocks___6___norm2_bias]. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"FxOnnxInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":414 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0008", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___6___mlp_fc1_weight[name=p_getattr_l__self___trunk_blocks___6___mlp_fc1_weight]. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature FxOnnxInterpreter.run_node\n- self: \n- node: fx.Node(p_getattr_l__self___trunk_blocks___6___mlp_fc1_weight)[placeholder]:Tensor(f32[4096, 1024])\n- fx_graph_module: torch.fx.GraphModule(torch_nn_modules_container_Sequential)\n- onnxfunction_dispatcher: \n- op_level_debug: False\n- onnxscript_graph: \n- onnxscript_tracer: \n- fx_name_to_onnxscript_value: Dict[length=81](\nclone: `TorchScriptTensor(f32[4, 1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_weight: `TorchScriptTensor(f32[3072, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_bias: `TorchScriptTensor(f32[3072])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_weight: `TorchScriptTensor(f32[1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm2_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm2_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___mlp_fc1_weight: `TorchScriptTensor(f32[4096, 1024])`,\n...\n)\n## Return values\n", + "text":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___6___mlp_fc1_weight[name=p_getattr_l__self___trunk_blocks___6___mlp_fc1_weight]. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"FxOnnxInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":414 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0008", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___6___mlp_fc1_bias[name=p_getattr_l__self___trunk_blocks___6___mlp_fc1_bias]. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature FxOnnxInterpreter.run_node\n- self: \n- node: fx.Node(p_getattr_l__self___trunk_blocks___6___mlp_fc1_bias)[placeholder]:Tensor(f32[4096])\n- fx_graph_module: torch.fx.GraphModule(torch_nn_modules_container_Sequential)\n- onnxfunction_dispatcher: \n- op_level_debug: False\n- onnxscript_graph: \n- onnxscript_tracer: \n- fx_name_to_onnxscript_value: Dict[length=82](\nclone: `TorchScriptTensor(f32[4, 1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_weight: `TorchScriptTensor(f32[3072, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_bias: `TorchScriptTensor(f32[3072])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_weight: `TorchScriptTensor(f32[1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm2_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm2_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___mlp_fc1_weight: `TorchScriptTensor(f32[4096, 1024])`,\n...\n)\n## Return values\n", + "text":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___6___mlp_fc1_bias[name=p_getattr_l__self___trunk_blocks___6___mlp_fc1_bias]. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"FxOnnxInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":414 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0008", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___6___mlp_fc2_weight[name=p_getattr_l__self___trunk_blocks___6___mlp_fc2_weight]. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature FxOnnxInterpreter.run_node\n- self: \n- node: fx.Node(p_getattr_l__self___trunk_blocks___6___mlp_fc2_weight)[placeholder]:Tensor(f32[1024, 4096])\n- fx_graph_module: torch.fx.GraphModule(torch_nn_modules_container_Sequential)\n- onnxfunction_dispatcher: \n- op_level_debug: False\n- onnxscript_graph: \n- onnxscript_tracer: \n- fx_name_to_onnxscript_value: Dict[length=83](\nclone: `TorchScriptTensor(f32[4, 1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_weight: `TorchScriptTensor(f32[3072, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_bias: `TorchScriptTensor(f32[3072])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_weight: `TorchScriptTensor(f32[1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm2_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm2_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___mlp_fc1_weight: `TorchScriptTensor(f32[4096, 1024])`,\n...\n)\n## Return values\n", + "text":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___6___mlp_fc2_weight[name=p_getattr_l__self___trunk_blocks___6___mlp_fc2_weight]. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"FxOnnxInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":414 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0008", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___6___mlp_fc2_bias[name=p_getattr_l__self___trunk_blocks___6___mlp_fc2_bias]. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature FxOnnxInterpreter.run_node\n- self: \n- node: fx.Node(p_getattr_l__self___trunk_blocks___6___mlp_fc2_bias)[placeholder]:Tensor(f32[1024])\n- fx_graph_module: torch.fx.GraphModule(torch_nn_modules_container_Sequential)\n- onnxfunction_dispatcher: \n- op_level_debug: False\n- onnxscript_graph: \n- onnxscript_tracer: \n- fx_name_to_onnxscript_value: Dict[length=84](\nclone: `TorchScriptTensor(f32[4, 1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_weight: `TorchScriptTensor(f32[3072, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_bias: `TorchScriptTensor(f32[3072])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_weight: `TorchScriptTensor(f32[1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm2_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm2_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___mlp_fc1_weight: `TorchScriptTensor(f32[4096, 1024])`,\n...\n)\n## Return values\n", + "text":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___6___mlp_fc2_bias[name=p_getattr_l__self___trunk_blocks___6___mlp_fc2_bias]. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"FxOnnxInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":414 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0008", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___7___norm1_weight[name=p_getattr_l__self___trunk_blocks___7___norm1_weight]. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature FxOnnxInterpreter.run_node\n- self: \n- node: fx.Node(p_getattr_l__self___trunk_blocks___7___norm1_weight)[placeholder]:Tensor(f32[1024])\n- fx_graph_module: torch.fx.GraphModule(torch_nn_modules_container_Sequential)\n- onnxfunction_dispatcher: \n- op_level_debug: False\n- onnxscript_graph: \n- onnxscript_tracer: \n- fx_name_to_onnxscript_value: Dict[length=85](\nclone: `TorchScriptTensor(f32[4, 1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_weight: `TorchScriptTensor(f32[3072, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_bias: `TorchScriptTensor(f32[3072])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_weight: `TorchScriptTensor(f32[1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm2_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm2_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___mlp_fc1_weight: `TorchScriptTensor(f32[4096, 1024])`,\n...\n)\n## Return values\n", + "text":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___7___norm1_weight[name=p_getattr_l__self___trunk_blocks___7___norm1_weight]. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"FxOnnxInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":414 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0008", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___7___norm1_bias[name=p_getattr_l__self___trunk_blocks___7___norm1_bias]. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature FxOnnxInterpreter.run_node\n- self: \n- node: fx.Node(p_getattr_l__self___trunk_blocks___7___norm1_bias)[placeholder]:Tensor(f32[1024])\n- fx_graph_module: torch.fx.GraphModule(torch_nn_modules_container_Sequential)\n- onnxfunction_dispatcher: \n- op_level_debug: False\n- onnxscript_graph: \n- onnxscript_tracer: \n- fx_name_to_onnxscript_value: Dict[length=86](\nclone: `TorchScriptTensor(f32[4, 1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_weight: `TorchScriptTensor(f32[3072, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_bias: `TorchScriptTensor(f32[3072])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_weight: `TorchScriptTensor(f32[1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm2_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm2_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___mlp_fc1_weight: `TorchScriptTensor(f32[4096, 1024])`,\n...\n)\n## Return values\n", + "text":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___7___norm1_bias[name=p_getattr_l__self___trunk_blocks___7___norm1_bias]. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"FxOnnxInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":414 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0008", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___7___attn_qkv_weight[name=p_getattr_l__self___trunk_blocks___7___attn_qkv_weight]. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature FxOnnxInterpreter.run_node\n- self: \n- node: fx.Node(p_getattr_l__self___trunk_blocks___7___attn_qkv_weight)[placeholder]:Tensor(f32[3072, 1024])\n- fx_graph_module: torch.fx.GraphModule(torch_nn_modules_container_Sequential)\n- onnxfunction_dispatcher: \n- op_level_debug: False\n- onnxscript_graph: \n- onnxscript_tracer: \n- fx_name_to_onnxscript_value: Dict[length=87](\nclone: `TorchScriptTensor(f32[4, 1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_weight: `TorchScriptTensor(f32[3072, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_bias: `TorchScriptTensor(f32[3072])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_weight: `TorchScriptTensor(f32[1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm2_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm2_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___mlp_fc1_weight: `TorchScriptTensor(f32[4096, 1024])`,\n...\n)\n## Return values\n", + "text":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___7___attn_qkv_weight[name=p_getattr_l__self___trunk_blocks___7___attn_qkv_weight]. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"FxOnnxInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":414 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0008", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___7___attn_qkv_bias[name=p_getattr_l__self___trunk_blocks___7___attn_qkv_bias]. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature FxOnnxInterpreter.run_node\n- self: \n- node: fx.Node(p_getattr_l__self___trunk_blocks___7___attn_qkv_bias)[placeholder]:Tensor(f32[3072])\n- fx_graph_module: torch.fx.GraphModule(torch_nn_modules_container_Sequential)\n- onnxfunction_dispatcher: \n- op_level_debug: False\n- onnxscript_graph: \n- onnxscript_tracer: \n- fx_name_to_onnxscript_value: Dict[length=88](\nclone: `TorchScriptTensor(f32[4, 1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_weight: `TorchScriptTensor(f32[3072, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_bias: `TorchScriptTensor(f32[3072])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_weight: `TorchScriptTensor(f32[1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm2_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm2_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___mlp_fc1_weight: `TorchScriptTensor(f32[4096, 1024])`,\n...\n)\n## Return values\n", + "text":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___7___attn_qkv_bias[name=p_getattr_l__self___trunk_blocks___7___attn_qkv_bias]. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"FxOnnxInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":414 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0008", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___7___attn_proj_weight[name=p_getattr_l__self___trunk_blocks___7___attn_proj_weight]. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature FxOnnxInterpreter.run_node\n- self: \n- node: fx.Node(p_getattr_l__self___trunk_blocks___7___attn_proj_weight)[placeholder]:Tensor(f32[1024, 1024])\n- fx_graph_module: torch.fx.GraphModule(torch_nn_modules_container_Sequential)\n- onnxfunction_dispatcher: \n- op_level_debug: False\n- onnxscript_graph: \n- onnxscript_tracer: \n- fx_name_to_onnxscript_value: Dict[length=89](\nclone: `TorchScriptTensor(f32[4, 1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_weight: `TorchScriptTensor(f32[3072, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_bias: `TorchScriptTensor(f32[3072])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_weight: `TorchScriptTensor(f32[1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm2_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm2_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___mlp_fc1_weight: `TorchScriptTensor(f32[4096, 1024])`,\n...\n)\n## Return values\n", + "text":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___7___attn_proj_weight[name=p_getattr_l__self___trunk_blocks___7___attn_proj_weight]. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"FxOnnxInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":414 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0008", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___7___attn_proj_bias[name=p_getattr_l__self___trunk_blocks___7___attn_proj_bias]. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature FxOnnxInterpreter.run_node\n- self: \n- node: fx.Node(p_getattr_l__self___trunk_blocks___7___attn_proj_bias)[placeholder]:Tensor(f32[1024])\n- fx_graph_module: torch.fx.GraphModule(torch_nn_modules_container_Sequential)\n- onnxfunction_dispatcher: \n- op_level_debug: False\n- onnxscript_graph: \n- onnxscript_tracer: \n- fx_name_to_onnxscript_value: Dict[length=90](\nclone: `TorchScriptTensor(f32[4, 1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_weight: `TorchScriptTensor(f32[3072, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_bias: `TorchScriptTensor(f32[3072])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_weight: `TorchScriptTensor(f32[1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm2_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm2_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___mlp_fc1_weight: `TorchScriptTensor(f32[4096, 1024])`,\n...\n)\n## Return values\n", + "text":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___7___attn_proj_bias[name=p_getattr_l__self___trunk_blocks___7___attn_proj_bias]. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"FxOnnxInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":414 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0008", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___7___norm2_weight[name=p_getattr_l__self___trunk_blocks___7___norm2_weight]. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature FxOnnxInterpreter.run_node\n- self: \n- node: fx.Node(p_getattr_l__self___trunk_blocks___7___norm2_weight)[placeholder]:Tensor(f32[1024])\n- fx_graph_module: torch.fx.GraphModule(torch_nn_modules_container_Sequential)\n- onnxfunction_dispatcher: \n- op_level_debug: False\n- onnxscript_graph: \n- onnxscript_tracer: \n- fx_name_to_onnxscript_value: Dict[length=91](\nclone: `TorchScriptTensor(f32[4, 1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_weight: `TorchScriptTensor(f32[3072, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_bias: `TorchScriptTensor(f32[3072])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_weight: `TorchScriptTensor(f32[1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm2_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm2_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___mlp_fc1_weight: `TorchScriptTensor(f32[4096, 1024])`,\n...\n)\n## Return values\n", + "text":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___7___norm2_weight[name=p_getattr_l__self___trunk_blocks___7___norm2_weight]. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"FxOnnxInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":414 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0008", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___7___norm2_bias[name=p_getattr_l__self___trunk_blocks___7___norm2_bias]. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature FxOnnxInterpreter.run_node\n- self: \n- node: fx.Node(p_getattr_l__self___trunk_blocks___7___norm2_bias)[placeholder]:Tensor(f32[1024])\n- fx_graph_module: torch.fx.GraphModule(torch_nn_modules_container_Sequential)\n- onnxfunction_dispatcher: \n- op_level_debug: False\n- onnxscript_graph: \n- onnxscript_tracer: \n- fx_name_to_onnxscript_value: Dict[length=92](\nclone: `TorchScriptTensor(f32[4, 1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_weight: `TorchScriptTensor(f32[3072, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_bias: `TorchScriptTensor(f32[3072])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_weight: `TorchScriptTensor(f32[1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm2_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm2_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___mlp_fc1_weight: `TorchScriptTensor(f32[4096, 1024])`,\n...\n)\n## Return values\n", + "text":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___7___norm2_bias[name=p_getattr_l__self___trunk_blocks___7___norm2_bias]. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"FxOnnxInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":414 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0008", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___7___mlp_fc1_weight[name=p_getattr_l__self___trunk_blocks___7___mlp_fc1_weight]. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature FxOnnxInterpreter.run_node\n- self: \n- node: fx.Node(p_getattr_l__self___trunk_blocks___7___mlp_fc1_weight)[placeholder]:Tensor(f32[4096, 1024])\n- fx_graph_module: torch.fx.GraphModule(torch_nn_modules_container_Sequential)\n- onnxfunction_dispatcher: \n- op_level_debug: False\n- onnxscript_graph: \n- onnxscript_tracer: \n- fx_name_to_onnxscript_value: Dict[length=93](\nclone: `TorchScriptTensor(f32[4, 1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_weight: `TorchScriptTensor(f32[3072, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_bias: `TorchScriptTensor(f32[3072])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_weight: `TorchScriptTensor(f32[1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm2_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm2_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___mlp_fc1_weight: `TorchScriptTensor(f32[4096, 1024])`,\n...\n)\n## Return values\n", + "text":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___7___mlp_fc1_weight[name=p_getattr_l__self___trunk_blocks___7___mlp_fc1_weight]. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"FxOnnxInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":414 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0008", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___7___mlp_fc1_bias[name=p_getattr_l__self___trunk_blocks___7___mlp_fc1_bias]. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature FxOnnxInterpreter.run_node\n- self: \n- node: fx.Node(p_getattr_l__self___trunk_blocks___7___mlp_fc1_bias)[placeholder]:Tensor(f32[4096])\n- fx_graph_module: torch.fx.GraphModule(torch_nn_modules_container_Sequential)\n- onnxfunction_dispatcher: \n- op_level_debug: False\n- onnxscript_graph: \n- onnxscript_tracer: \n- fx_name_to_onnxscript_value: Dict[length=94](\nclone: `TorchScriptTensor(f32[4, 1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_weight: `TorchScriptTensor(f32[3072, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_bias: `TorchScriptTensor(f32[3072])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_weight: `TorchScriptTensor(f32[1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm2_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm2_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___mlp_fc1_weight: `TorchScriptTensor(f32[4096, 1024])`,\n...\n)\n## Return values\n", + "text":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___7___mlp_fc1_bias[name=p_getattr_l__self___trunk_blocks___7___mlp_fc1_bias]. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"FxOnnxInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":414 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0008", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___7___mlp_fc2_weight[name=p_getattr_l__self___trunk_blocks___7___mlp_fc2_weight]. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature FxOnnxInterpreter.run_node\n- self: \n- node: fx.Node(p_getattr_l__self___trunk_blocks___7___mlp_fc2_weight)[placeholder]:Tensor(f32[1024, 4096])\n- fx_graph_module: torch.fx.GraphModule(torch_nn_modules_container_Sequential)\n- onnxfunction_dispatcher: \n- op_level_debug: False\n- onnxscript_graph: \n- onnxscript_tracer: \n- fx_name_to_onnxscript_value: Dict[length=95](\nclone: `TorchScriptTensor(f32[4, 1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_weight: `TorchScriptTensor(f32[3072, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_bias: `TorchScriptTensor(f32[3072])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_weight: `TorchScriptTensor(f32[1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm2_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm2_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___mlp_fc1_weight: `TorchScriptTensor(f32[4096, 1024])`,\n...\n)\n## Return values\n", + "text":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___7___mlp_fc2_weight[name=p_getattr_l__self___trunk_blocks___7___mlp_fc2_weight]. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"FxOnnxInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":414 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0008", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___7___mlp_fc2_bias[name=p_getattr_l__self___trunk_blocks___7___mlp_fc2_bias]. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature FxOnnxInterpreter.run_node\n- self: \n- node: fx.Node(p_getattr_l__self___trunk_blocks___7___mlp_fc2_bias)[placeholder]:Tensor(f32[1024])\n- fx_graph_module: torch.fx.GraphModule(torch_nn_modules_container_Sequential)\n- onnxfunction_dispatcher: \n- op_level_debug: False\n- onnxscript_graph: \n- onnxscript_tracer: \n- fx_name_to_onnxscript_value: Dict[length=96](\nclone: `TorchScriptTensor(f32[4, 1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_weight: `TorchScriptTensor(f32[3072, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_bias: `TorchScriptTensor(f32[3072])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_weight: `TorchScriptTensor(f32[1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm2_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm2_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___mlp_fc1_weight: `TorchScriptTensor(f32[4096, 1024])`,\n...\n)\n## Return values\n", + "text":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___7___mlp_fc2_bias[name=p_getattr_l__self___trunk_blocks___7___mlp_fc2_bias]. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"FxOnnxInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":414 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0008", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___8___norm1_weight[name=p_getattr_l__self___trunk_blocks___8___norm1_weight]. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature FxOnnxInterpreter.run_node\n- self: \n- node: fx.Node(p_getattr_l__self___trunk_blocks___8___norm1_weight)[placeholder]:Tensor(f32[1024])\n- fx_graph_module: torch.fx.GraphModule(torch_nn_modules_container_Sequential)\n- onnxfunction_dispatcher: \n- op_level_debug: False\n- onnxscript_graph: \n- onnxscript_tracer: \n- fx_name_to_onnxscript_value: Dict[length=97](\nclone: `TorchScriptTensor(f32[4, 1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_weight: `TorchScriptTensor(f32[3072, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_bias: `TorchScriptTensor(f32[3072])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_weight: `TorchScriptTensor(f32[1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm2_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm2_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___mlp_fc1_weight: `TorchScriptTensor(f32[4096, 1024])`,\n...\n)\n## Return values\n", + "text":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___8___norm1_weight[name=p_getattr_l__self___trunk_blocks___8___norm1_weight]. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"FxOnnxInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":414 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0008", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___8___norm1_bias[name=p_getattr_l__self___trunk_blocks___8___norm1_bias]. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature FxOnnxInterpreter.run_node\n- self: \n- node: fx.Node(p_getattr_l__self___trunk_blocks___8___norm1_bias)[placeholder]:Tensor(f32[1024])\n- fx_graph_module: torch.fx.GraphModule(torch_nn_modules_container_Sequential)\n- onnxfunction_dispatcher: \n- op_level_debug: False\n- onnxscript_graph: \n- onnxscript_tracer: \n- fx_name_to_onnxscript_value: Dict[length=98](\nclone: `TorchScriptTensor(f32[4, 1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_weight: `TorchScriptTensor(f32[3072, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_bias: `TorchScriptTensor(f32[3072])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_weight: `TorchScriptTensor(f32[1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm2_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm2_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___mlp_fc1_weight: `TorchScriptTensor(f32[4096, 1024])`,\n...\n)\n## Return values\n", + "text":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___8___norm1_bias[name=p_getattr_l__self___trunk_blocks___8___norm1_bias]. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"FxOnnxInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":414 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0008", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___8___attn_qkv_weight[name=p_getattr_l__self___trunk_blocks___8___attn_qkv_weight]. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature FxOnnxInterpreter.run_node\n- self: \n- node: fx.Node(p_getattr_l__self___trunk_blocks___8___attn_qkv_weight)[placeholder]:Tensor(f32[3072, 1024])\n- fx_graph_module: torch.fx.GraphModule(torch_nn_modules_container_Sequential)\n- onnxfunction_dispatcher: \n- op_level_debug: False\n- onnxscript_graph: \n- onnxscript_tracer: \n- fx_name_to_onnxscript_value: Dict[length=99](\nclone: `TorchScriptTensor(f32[4, 1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_weight: `TorchScriptTensor(f32[3072, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_bias: `TorchScriptTensor(f32[3072])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_weight: `TorchScriptTensor(f32[1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm2_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm2_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___mlp_fc1_weight: `TorchScriptTensor(f32[4096, 1024])`,\n...\n)\n## Return values\n", + "text":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___8___attn_qkv_weight[name=p_getattr_l__self___trunk_blocks___8___attn_qkv_weight]. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"FxOnnxInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":414 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0008", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___8___attn_qkv_bias[name=p_getattr_l__self___trunk_blocks___8___attn_qkv_bias]. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature FxOnnxInterpreter.run_node\n- self: \n- node: fx.Node(p_getattr_l__self___trunk_blocks___8___attn_qkv_bias)[placeholder]:Tensor(f32[3072])\n- fx_graph_module: torch.fx.GraphModule(torch_nn_modules_container_Sequential)\n- onnxfunction_dispatcher: \n- op_level_debug: False\n- onnxscript_graph: \n- onnxscript_tracer: \n- fx_name_to_onnxscript_value: Dict[length=100](\nclone: `TorchScriptTensor(f32[4, 1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_weight: `TorchScriptTensor(f32[3072, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_bias: `TorchScriptTensor(f32[3072])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_weight: `TorchScriptTensor(f32[1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm2_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm2_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___mlp_fc1_weight: `TorchScriptTensor(f32[4096, 1024])`,\n...\n)\n## Return values\n", + "text":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___8___attn_qkv_bias[name=p_getattr_l__self___trunk_blocks___8___attn_qkv_bias]. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"FxOnnxInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":414 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0008", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___8___attn_proj_weight[name=p_getattr_l__self___trunk_blocks___8___attn_proj_weight]. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature FxOnnxInterpreter.run_node\n- self: \n- node: fx.Node(p_getattr_l__self___trunk_blocks___8___attn_proj_weight)[placeholder]:Tensor(f32[1024, 1024])\n- fx_graph_module: torch.fx.GraphModule(torch_nn_modules_container_Sequential)\n- onnxfunction_dispatcher: \n- op_level_debug: False\n- onnxscript_graph: \n- onnxscript_tracer: \n- fx_name_to_onnxscript_value: Dict[length=101](\nclone: `TorchScriptTensor(f32[4, 1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_weight: `TorchScriptTensor(f32[3072, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_bias: `TorchScriptTensor(f32[3072])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_weight: `TorchScriptTensor(f32[1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm2_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm2_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___mlp_fc1_weight: `TorchScriptTensor(f32[4096, 1024])`,\n...\n)\n## Return values\n", + "text":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___8___attn_proj_weight[name=p_getattr_l__self___trunk_blocks___8___attn_proj_weight]. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"FxOnnxInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":414 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0008", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___8___attn_proj_bias[name=p_getattr_l__self___trunk_blocks___8___attn_proj_bias]. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature FxOnnxInterpreter.run_node\n- self: \n- node: fx.Node(p_getattr_l__self___trunk_blocks___8___attn_proj_bias)[placeholder]:Tensor(f32[1024])\n- fx_graph_module: torch.fx.GraphModule(torch_nn_modules_container_Sequential)\n- onnxfunction_dispatcher: \n- op_level_debug: False\n- onnxscript_graph: \n- onnxscript_tracer: \n- fx_name_to_onnxscript_value: Dict[length=102](\nclone: `TorchScriptTensor(f32[4, 1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_weight: `TorchScriptTensor(f32[3072, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_bias: `TorchScriptTensor(f32[3072])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_weight: `TorchScriptTensor(f32[1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm2_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm2_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___mlp_fc1_weight: `TorchScriptTensor(f32[4096, 1024])`,\n...\n)\n## Return values\n", + "text":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___8___attn_proj_bias[name=p_getattr_l__self___trunk_blocks___8___attn_proj_bias]. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"FxOnnxInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":414 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0008", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___8___norm2_weight[name=p_getattr_l__self___trunk_blocks___8___norm2_weight]. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature FxOnnxInterpreter.run_node\n- self: \n- node: fx.Node(p_getattr_l__self___trunk_blocks___8___norm2_weight)[placeholder]:Tensor(f32[1024])\n- fx_graph_module: torch.fx.GraphModule(torch_nn_modules_container_Sequential)\n- onnxfunction_dispatcher: \n- op_level_debug: False\n- onnxscript_graph: \n- onnxscript_tracer: \n- fx_name_to_onnxscript_value: Dict[length=103](\nclone: `TorchScriptTensor(f32[4, 1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_weight: `TorchScriptTensor(f32[3072, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_bias: `TorchScriptTensor(f32[3072])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_weight: `TorchScriptTensor(f32[1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm2_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm2_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___mlp_fc1_weight: `TorchScriptTensor(f32[4096, 1024])`,\n...\n)\n## Return values\n", + "text":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___8___norm2_weight[name=p_getattr_l__self___trunk_blocks___8___norm2_weight]. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"FxOnnxInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":414 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0008", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___8___norm2_bias[name=p_getattr_l__self___trunk_blocks___8___norm2_bias]. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature FxOnnxInterpreter.run_node\n- self: \n- node: fx.Node(p_getattr_l__self___trunk_blocks___8___norm2_bias)[placeholder]:Tensor(f32[1024])\n- fx_graph_module: torch.fx.GraphModule(torch_nn_modules_container_Sequential)\n- onnxfunction_dispatcher: \n- op_level_debug: False\n- onnxscript_graph: \n- onnxscript_tracer: \n- fx_name_to_onnxscript_value: Dict[length=104](\nclone: `TorchScriptTensor(f32[4, 1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_weight: `TorchScriptTensor(f32[3072, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_bias: `TorchScriptTensor(f32[3072])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_weight: `TorchScriptTensor(f32[1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm2_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm2_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___mlp_fc1_weight: `TorchScriptTensor(f32[4096, 1024])`,\n...\n)\n## Return values\n", + "text":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___8___norm2_bias[name=p_getattr_l__self___trunk_blocks___8___norm2_bias]. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"FxOnnxInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":414 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0008", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___8___mlp_fc1_weight[name=p_getattr_l__self___trunk_blocks___8___mlp_fc1_weight]. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature FxOnnxInterpreter.run_node\n- self: \n- node: fx.Node(p_getattr_l__self___trunk_blocks___8___mlp_fc1_weight)[placeholder]:Tensor(f32[4096, 1024])\n- fx_graph_module: torch.fx.GraphModule(torch_nn_modules_container_Sequential)\n- onnxfunction_dispatcher: \n- op_level_debug: False\n- onnxscript_graph: \n- onnxscript_tracer: \n- fx_name_to_onnxscript_value: Dict[length=105](\nclone: `TorchScriptTensor(f32[4, 1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_weight: `TorchScriptTensor(f32[3072, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_bias: `TorchScriptTensor(f32[3072])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_weight: `TorchScriptTensor(f32[1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm2_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm2_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___mlp_fc1_weight: `TorchScriptTensor(f32[4096, 1024])`,\n...\n)\n## Return values\n", + "text":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___8___mlp_fc1_weight[name=p_getattr_l__self___trunk_blocks___8___mlp_fc1_weight]. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"FxOnnxInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":414 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0008", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___8___mlp_fc1_bias[name=p_getattr_l__self___trunk_blocks___8___mlp_fc1_bias]. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature FxOnnxInterpreter.run_node\n- self: \n- node: fx.Node(p_getattr_l__self___trunk_blocks___8___mlp_fc1_bias)[placeholder]:Tensor(f32[4096])\n- fx_graph_module: torch.fx.GraphModule(torch_nn_modules_container_Sequential)\n- onnxfunction_dispatcher: \n- op_level_debug: False\n- onnxscript_graph: \n- onnxscript_tracer: \n- fx_name_to_onnxscript_value: Dict[length=106](\nclone: `TorchScriptTensor(f32[4, 1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_weight: `TorchScriptTensor(f32[3072, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_bias: `TorchScriptTensor(f32[3072])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_weight: `TorchScriptTensor(f32[1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm2_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm2_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___mlp_fc1_weight: `TorchScriptTensor(f32[4096, 1024])`,\n...\n)\n## Return values\n", + "text":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___8___mlp_fc1_bias[name=p_getattr_l__self___trunk_blocks___8___mlp_fc1_bias]. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"FxOnnxInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":414 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0008", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___8___mlp_fc2_weight[name=p_getattr_l__self___trunk_blocks___8___mlp_fc2_weight]. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature FxOnnxInterpreter.run_node\n- self: \n- node: fx.Node(p_getattr_l__self___trunk_blocks___8___mlp_fc2_weight)[placeholder]:Tensor(f32[1024, 4096])\n- fx_graph_module: torch.fx.GraphModule(torch_nn_modules_container_Sequential)\n- onnxfunction_dispatcher: \n- op_level_debug: False\n- onnxscript_graph: \n- onnxscript_tracer: \n- fx_name_to_onnxscript_value: Dict[length=107](\nclone: `TorchScriptTensor(f32[4, 1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_weight: `TorchScriptTensor(f32[3072, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_bias: `TorchScriptTensor(f32[3072])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_weight: `TorchScriptTensor(f32[1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm2_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm2_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___mlp_fc1_weight: `TorchScriptTensor(f32[4096, 1024])`,\n...\n)\n## Return values\n", + "text":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___8___mlp_fc2_weight[name=p_getattr_l__self___trunk_blocks___8___mlp_fc2_weight]. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"FxOnnxInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":414 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0008", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___8___mlp_fc2_bias[name=p_getattr_l__self___trunk_blocks___8___mlp_fc2_bias]. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature FxOnnxInterpreter.run_node\n- self: \n- node: fx.Node(p_getattr_l__self___trunk_blocks___8___mlp_fc2_bias)[placeholder]:Tensor(f32[1024])\n- fx_graph_module: torch.fx.GraphModule(torch_nn_modules_container_Sequential)\n- onnxfunction_dispatcher: \n- op_level_debug: False\n- onnxscript_graph: \n- onnxscript_tracer: \n- fx_name_to_onnxscript_value: Dict[length=108](\nclone: `TorchScriptTensor(f32[4, 1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_weight: `TorchScriptTensor(f32[3072, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_bias: `TorchScriptTensor(f32[3072])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_weight: `TorchScriptTensor(f32[1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm2_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm2_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___mlp_fc1_weight: `TorchScriptTensor(f32[4096, 1024])`,\n...\n)\n## Return values\n", + "text":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___8___mlp_fc2_bias[name=p_getattr_l__self___trunk_blocks___8___mlp_fc2_bias]. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"FxOnnxInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":414 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0008", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___9___norm1_weight[name=p_getattr_l__self___trunk_blocks___9___norm1_weight]. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature FxOnnxInterpreter.run_node\n- self: \n- node: fx.Node(p_getattr_l__self___trunk_blocks___9___norm1_weight)[placeholder]:Tensor(f32[1024])\n- fx_graph_module: torch.fx.GraphModule(torch_nn_modules_container_Sequential)\n- onnxfunction_dispatcher: \n- op_level_debug: False\n- onnxscript_graph: \n- onnxscript_tracer: \n- fx_name_to_onnxscript_value: Dict[length=109](\nclone: `TorchScriptTensor(f32[4, 1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_weight: `TorchScriptTensor(f32[3072, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_bias: `TorchScriptTensor(f32[3072])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_weight: `TorchScriptTensor(f32[1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm2_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm2_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___mlp_fc1_weight: `TorchScriptTensor(f32[4096, 1024])`,\n...\n)\n## Return values\n", + "text":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___9___norm1_weight[name=p_getattr_l__self___trunk_blocks___9___norm1_weight]. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"FxOnnxInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":414 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0008", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___9___norm1_bias[name=p_getattr_l__self___trunk_blocks___9___norm1_bias]. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature FxOnnxInterpreter.run_node\n- self: \n- node: fx.Node(p_getattr_l__self___trunk_blocks___9___norm1_bias)[placeholder]:Tensor(f32[1024])\n- fx_graph_module: torch.fx.GraphModule(torch_nn_modules_container_Sequential)\n- onnxfunction_dispatcher: \n- op_level_debug: False\n- onnxscript_graph: \n- onnxscript_tracer: \n- fx_name_to_onnxscript_value: Dict[length=110](\nclone: `TorchScriptTensor(f32[4, 1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_weight: `TorchScriptTensor(f32[3072, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_bias: `TorchScriptTensor(f32[3072])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_weight: `TorchScriptTensor(f32[1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm2_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm2_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___mlp_fc1_weight: `TorchScriptTensor(f32[4096, 1024])`,\n...\n)\n## Return values\n", + "text":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___9___norm1_bias[name=p_getattr_l__self___trunk_blocks___9___norm1_bias]. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"FxOnnxInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":414 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0008", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___9___attn_qkv_weight[name=p_getattr_l__self___trunk_blocks___9___attn_qkv_weight]. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature FxOnnxInterpreter.run_node\n- self: \n- node: fx.Node(p_getattr_l__self___trunk_blocks___9___attn_qkv_weight)[placeholder]:Tensor(f32[3072, 1024])\n- fx_graph_module: torch.fx.GraphModule(torch_nn_modules_container_Sequential)\n- onnxfunction_dispatcher: \n- op_level_debug: False\n- onnxscript_graph: \n- onnxscript_tracer: \n- fx_name_to_onnxscript_value: Dict[length=111](\nclone: `TorchScriptTensor(f32[4, 1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_weight: `TorchScriptTensor(f32[3072, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_bias: `TorchScriptTensor(f32[3072])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_weight: `TorchScriptTensor(f32[1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm2_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm2_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___mlp_fc1_weight: `TorchScriptTensor(f32[4096, 1024])`,\n...\n)\n## Return values\n", + "text":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___9___attn_qkv_weight[name=p_getattr_l__self___trunk_blocks___9___attn_qkv_weight]. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"FxOnnxInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":414 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0008", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___9___attn_qkv_bias[name=p_getattr_l__self___trunk_blocks___9___attn_qkv_bias]. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature FxOnnxInterpreter.run_node\n- self: \n- node: fx.Node(p_getattr_l__self___trunk_blocks___9___attn_qkv_bias)[placeholder]:Tensor(f32[3072])\n- fx_graph_module: torch.fx.GraphModule(torch_nn_modules_container_Sequential)\n- onnxfunction_dispatcher: \n- op_level_debug: False\n- onnxscript_graph: \n- onnxscript_tracer: \n- fx_name_to_onnxscript_value: Dict[length=112](\nclone: `TorchScriptTensor(f32[4, 1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_weight: `TorchScriptTensor(f32[3072, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_bias: `TorchScriptTensor(f32[3072])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_weight: `TorchScriptTensor(f32[1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm2_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm2_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___mlp_fc1_weight: `TorchScriptTensor(f32[4096, 1024])`,\n...\n)\n## Return values\n", + "text":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___9___attn_qkv_bias[name=p_getattr_l__self___trunk_blocks___9___attn_qkv_bias]. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"FxOnnxInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":414 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0008", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___9___attn_proj_weight[name=p_getattr_l__self___trunk_blocks___9___attn_proj_weight]. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature FxOnnxInterpreter.run_node\n- self: \n- node: fx.Node(p_getattr_l__self___trunk_blocks___9___attn_proj_weight)[placeholder]:Tensor(f32[1024, 1024])\n- fx_graph_module: torch.fx.GraphModule(torch_nn_modules_container_Sequential)\n- onnxfunction_dispatcher: \n- op_level_debug: False\n- onnxscript_graph: \n- onnxscript_tracer: \n- fx_name_to_onnxscript_value: Dict[length=113](\nclone: `TorchScriptTensor(f32[4, 1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_weight: `TorchScriptTensor(f32[3072, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_bias: `TorchScriptTensor(f32[3072])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_weight: `TorchScriptTensor(f32[1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm2_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm2_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___mlp_fc1_weight: `TorchScriptTensor(f32[4096, 1024])`,\n...\n)\n## Return values\n", + "text":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___9___attn_proj_weight[name=p_getattr_l__self___trunk_blocks___9___attn_proj_weight]. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"FxOnnxInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":414 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0008", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___9___attn_proj_bias[name=p_getattr_l__self___trunk_blocks___9___attn_proj_bias]. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature FxOnnxInterpreter.run_node\n- self: \n- node: fx.Node(p_getattr_l__self___trunk_blocks___9___attn_proj_bias)[placeholder]:Tensor(f32[1024])\n- fx_graph_module: torch.fx.GraphModule(torch_nn_modules_container_Sequential)\n- onnxfunction_dispatcher: \n- op_level_debug: False\n- onnxscript_graph: \n- onnxscript_tracer: \n- fx_name_to_onnxscript_value: Dict[length=114](\nclone: `TorchScriptTensor(f32[4, 1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_weight: `TorchScriptTensor(f32[3072, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_bias: `TorchScriptTensor(f32[3072])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_weight: `TorchScriptTensor(f32[1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm2_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm2_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___mlp_fc1_weight: `TorchScriptTensor(f32[4096, 1024])`,\n...\n)\n## Return values\n", + "text":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___9___attn_proj_bias[name=p_getattr_l__self___trunk_blocks___9___attn_proj_bias]. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"FxOnnxInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":414 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0008", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___9___norm2_weight[name=p_getattr_l__self___trunk_blocks___9___norm2_weight]. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature FxOnnxInterpreter.run_node\n- self: \n- node: fx.Node(p_getattr_l__self___trunk_blocks___9___norm2_weight)[placeholder]:Tensor(f32[1024])\n- fx_graph_module: torch.fx.GraphModule(torch_nn_modules_container_Sequential)\n- onnxfunction_dispatcher: \n- op_level_debug: False\n- onnxscript_graph: \n- onnxscript_tracer: \n- fx_name_to_onnxscript_value: Dict[length=115](\nclone: `TorchScriptTensor(f32[4, 1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_weight: `TorchScriptTensor(f32[3072, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_bias: `TorchScriptTensor(f32[3072])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_weight: `TorchScriptTensor(f32[1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm2_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm2_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___mlp_fc1_weight: `TorchScriptTensor(f32[4096, 1024])`,\n...\n)\n## Return values\n", + "text":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___9___norm2_weight[name=p_getattr_l__self___trunk_blocks___9___norm2_weight]. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"FxOnnxInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":414 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0008", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___9___norm2_bias[name=p_getattr_l__self___trunk_blocks___9___norm2_bias]. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature FxOnnxInterpreter.run_node\n- self: \n- node: fx.Node(p_getattr_l__self___trunk_blocks___9___norm2_bias)[placeholder]:Tensor(f32[1024])\n- fx_graph_module: torch.fx.GraphModule(torch_nn_modules_container_Sequential)\n- onnxfunction_dispatcher: \n- op_level_debug: False\n- onnxscript_graph: \n- onnxscript_tracer: \n- fx_name_to_onnxscript_value: Dict[length=116](\nclone: `TorchScriptTensor(f32[4, 1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_weight: `TorchScriptTensor(f32[3072, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_bias: `TorchScriptTensor(f32[3072])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_weight: `TorchScriptTensor(f32[1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm2_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm2_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___mlp_fc1_weight: `TorchScriptTensor(f32[4096, 1024])`,\n...\n)\n## Return values\n", + "text":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___9___norm2_bias[name=p_getattr_l__self___trunk_blocks___9___norm2_bias]. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"FxOnnxInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":414 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0008", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___9___mlp_fc1_weight[name=p_getattr_l__self___trunk_blocks___9___mlp_fc1_weight]. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature FxOnnxInterpreter.run_node\n- self: \n- node: fx.Node(p_getattr_l__self___trunk_blocks___9___mlp_fc1_weight)[placeholder]:Tensor(f32[4096, 1024])\n- fx_graph_module: torch.fx.GraphModule(torch_nn_modules_container_Sequential)\n- onnxfunction_dispatcher: \n- op_level_debug: False\n- onnxscript_graph: \n- onnxscript_tracer: \n- fx_name_to_onnxscript_value: Dict[length=117](\nclone: `TorchScriptTensor(f32[4, 1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_weight: `TorchScriptTensor(f32[3072, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_bias: `TorchScriptTensor(f32[3072])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_weight: `TorchScriptTensor(f32[1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm2_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm2_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___mlp_fc1_weight: `TorchScriptTensor(f32[4096, 1024])`,\n...\n)\n## Return values\n", + "text":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___9___mlp_fc1_weight[name=p_getattr_l__self___trunk_blocks___9___mlp_fc1_weight]. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"FxOnnxInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":414 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0008", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___9___mlp_fc1_bias[name=p_getattr_l__self___trunk_blocks___9___mlp_fc1_bias]. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature FxOnnxInterpreter.run_node\n- self: \n- node: fx.Node(p_getattr_l__self___trunk_blocks___9___mlp_fc1_bias)[placeholder]:Tensor(f32[4096])\n- fx_graph_module: torch.fx.GraphModule(torch_nn_modules_container_Sequential)\n- onnxfunction_dispatcher: \n- op_level_debug: False\n- onnxscript_graph: \n- onnxscript_tracer: \n- fx_name_to_onnxscript_value: Dict[length=118](\nclone: `TorchScriptTensor(f32[4, 1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_weight: `TorchScriptTensor(f32[3072, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_bias: `TorchScriptTensor(f32[3072])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_weight: `TorchScriptTensor(f32[1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm2_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm2_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___mlp_fc1_weight: `TorchScriptTensor(f32[4096, 1024])`,\n...\n)\n## Return values\n", + "text":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___9___mlp_fc1_bias[name=p_getattr_l__self___trunk_blocks___9___mlp_fc1_bias]. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"FxOnnxInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":414 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0008", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___9___mlp_fc2_weight[name=p_getattr_l__self___trunk_blocks___9___mlp_fc2_weight]. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature FxOnnxInterpreter.run_node\n- self: \n- node: fx.Node(p_getattr_l__self___trunk_blocks___9___mlp_fc2_weight)[placeholder]:Tensor(f32[1024, 4096])\n- fx_graph_module: torch.fx.GraphModule(torch_nn_modules_container_Sequential)\n- onnxfunction_dispatcher: \n- op_level_debug: False\n- onnxscript_graph: \n- onnxscript_tracer: \n- fx_name_to_onnxscript_value: Dict[length=119](\nclone: `TorchScriptTensor(f32[4, 1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_weight: `TorchScriptTensor(f32[3072, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_bias: `TorchScriptTensor(f32[3072])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_weight: `TorchScriptTensor(f32[1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm2_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm2_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___mlp_fc1_weight: `TorchScriptTensor(f32[4096, 1024])`,\n...\n)\n## Return values\n", + "text":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___9___mlp_fc2_weight[name=p_getattr_l__self___trunk_blocks___9___mlp_fc2_weight]. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"FxOnnxInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":414 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0008", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___9___mlp_fc2_bias[name=p_getattr_l__self___trunk_blocks___9___mlp_fc2_bias]. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature FxOnnxInterpreter.run_node\n- self: \n- node: fx.Node(p_getattr_l__self___trunk_blocks___9___mlp_fc2_bias)[placeholder]:Tensor(f32[1024])\n- fx_graph_module: torch.fx.GraphModule(torch_nn_modules_container_Sequential)\n- onnxfunction_dispatcher: \n- op_level_debug: False\n- onnxscript_graph: \n- onnxscript_tracer: \n- fx_name_to_onnxscript_value: Dict[length=120](\nclone: `TorchScriptTensor(f32[4, 1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_weight: `TorchScriptTensor(f32[3072, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_bias: `TorchScriptTensor(f32[3072])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_weight: `TorchScriptTensor(f32[1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm2_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm2_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___mlp_fc1_weight: `TorchScriptTensor(f32[4096, 1024])`,\n...\n)\n## Return values\n", + "text":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___9___mlp_fc2_bias[name=p_getattr_l__self___trunk_blocks___9___mlp_fc2_bias]. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"FxOnnxInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":414 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0008", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___10___norm1_weight[name=p_getattr_l__self___trunk_blocks___10___norm1_weight]. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature FxOnnxInterpreter.run_node\n- self: \n- node: fx.Node(p_getattr_l__self___trunk_blocks___10___norm1_weight)[placeholder]:Tensor(f32[1024])\n- fx_graph_module: torch.fx.GraphModule(torch_nn_modules_container_Sequential)\n- onnxfunction_dispatcher: \n- op_level_debug: False\n- onnxscript_graph: \n- onnxscript_tracer: \n- fx_name_to_onnxscript_value: Dict[length=121](\nclone: `TorchScriptTensor(f32[4, 1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_weight: `TorchScriptTensor(f32[3072, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_bias: `TorchScriptTensor(f32[3072])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_weight: `TorchScriptTensor(f32[1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm2_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm2_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___mlp_fc1_weight: `TorchScriptTensor(f32[4096, 1024])`,\n...\n)\n## Return values\n", + "text":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___10___norm1_weight[name=p_getattr_l__self___trunk_blocks___10___norm1_weight]. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"FxOnnxInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":414 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0008", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___10___norm1_bias[name=p_getattr_l__self___trunk_blocks___10___norm1_bias]. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature FxOnnxInterpreter.run_node\n- self: \n- node: fx.Node(p_getattr_l__self___trunk_blocks___10___norm1_bias)[placeholder]:Tensor(f32[1024])\n- fx_graph_module: torch.fx.GraphModule(torch_nn_modules_container_Sequential)\n- onnxfunction_dispatcher: \n- op_level_debug: False\n- onnxscript_graph: \n- onnxscript_tracer: \n- fx_name_to_onnxscript_value: Dict[length=122](\nclone: `TorchScriptTensor(f32[4, 1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_weight: `TorchScriptTensor(f32[3072, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_bias: `TorchScriptTensor(f32[3072])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_weight: `TorchScriptTensor(f32[1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm2_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm2_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___mlp_fc1_weight: `TorchScriptTensor(f32[4096, 1024])`,\n...\n)\n## Return values\n", + "text":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___10___norm1_bias[name=p_getattr_l__self___trunk_blocks___10___norm1_bias]. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"FxOnnxInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":414 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0008", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___10___attn_qkv_weight[name=p_getattr_l__self___trunk_blocks___10___attn_qkv_weight]. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature FxOnnxInterpreter.run_node\n- self: \n- node: fx.Node(p_getattr_l__self___trunk_blocks___10___attn_qkv_weight)[placeholder]:Tensor(f32[3072, 1024])\n- fx_graph_module: torch.fx.GraphModule(torch_nn_modules_container_Sequential)\n- onnxfunction_dispatcher: \n- op_level_debug: False\n- onnxscript_graph: \n- onnxscript_tracer: \n- fx_name_to_onnxscript_value: Dict[length=123](\nclone: `TorchScriptTensor(f32[4, 1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_weight: `TorchScriptTensor(f32[3072, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_bias: `TorchScriptTensor(f32[3072])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_weight: `TorchScriptTensor(f32[1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm2_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm2_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___mlp_fc1_weight: `TorchScriptTensor(f32[4096, 1024])`,\n...\n)\n## Return values\n", + "text":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___10___attn_qkv_weight[name=p_getattr_l__self___trunk_blocks___10___attn_qkv_weight]. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"FxOnnxInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":414 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0008", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___10___attn_qkv_bias[name=p_getattr_l__self___trunk_blocks___10___attn_qkv_bias]. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature FxOnnxInterpreter.run_node\n- self: \n- node: fx.Node(p_getattr_l__self___trunk_blocks___10___attn_qkv_bias)[placeholder]:Tensor(f32[3072])\n- fx_graph_module: torch.fx.GraphModule(torch_nn_modules_container_Sequential)\n- onnxfunction_dispatcher: \n- op_level_debug: False\n- onnxscript_graph: \n- onnxscript_tracer: \n- fx_name_to_onnxscript_value: Dict[length=124](\nclone: `TorchScriptTensor(f32[4, 1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_weight: `TorchScriptTensor(f32[3072, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_bias: `TorchScriptTensor(f32[3072])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_weight: `TorchScriptTensor(f32[1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm2_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm2_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___mlp_fc1_weight: `TorchScriptTensor(f32[4096, 1024])`,\n...\n)\n## Return values\n", + "text":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___10___attn_qkv_bias[name=p_getattr_l__self___trunk_blocks___10___attn_qkv_bias]. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"FxOnnxInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":414 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0008", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___10___attn_proj_weight[name=p_getattr_l__self___trunk_blocks___10___attn_proj_weight]. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature FxOnnxInterpreter.run_node\n- self: \n- node: fx.Node(p_getattr_l__self___trunk_blocks___10___attn_proj_weight)[placeholder]:Tensor(f32[1024, 1024])\n- fx_graph_module: torch.fx.GraphModule(torch_nn_modules_container_Sequential)\n- onnxfunction_dispatcher: \n- op_level_debug: False\n- onnxscript_graph: \n- onnxscript_tracer: \n- fx_name_to_onnxscript_value: Dict[length=125](\nclone: `TorchScriptTensor(f32[4, 1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_weight: `TorchScriptTensor(f32[3072, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_bias: `TorchScriptTensor(f32[3072])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_weight: `TorchScriptTensor(f32[1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm2_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm2_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___mlp_fc1_weight: `TorchScriptTensor(f32[4096, 1024])`,\n...\n)\n## Return values\n", + "text":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___10___attn_proj_weight[name=p_getattr_l__self___trunk_blocks___10___attn_proj_weight]. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"FxOnnxInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":414 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0008", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___10___attn_proj_bias[name=p_getattr_l__self___trunk_blocks___10___attn_proj_bias]. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature FxOnnxInterpreter.run_node\n- self: \n- node: fx.Node(p_getattr_l__self___trunk_blocks___10___attn_proj_bias)[placeholder]:Tensor(f32[1024])\n- fx_graph_module: torch.fx.GraphModule(torch_nn_modules_container_Sequential)\n- onnxfunction_dispatcher: \n- op_level_debug: False\n- onnxscript_graph: \n- onnxscript_tracer: \n- fx_name_to_onnxscript_value: Dict[length=126](\nclone: `TorchScriptTensor(f32[4, 1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_weight: `TorchScriptTensor(f32[3072, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_bias: `TorchScriptTensor(f32[3072])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_weight: `TorchScriptTensor(f32[1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm2_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm2_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___mlp_fc1_weight: `TorchScriptTensor(f32[4096, 1024])`,\n...\n)\n## Return values\n", + "text":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___10___attn_proj_bias[name=p_getattr_l__self___trunk_blocks___10___attn_proj_bias]. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"FxOnnxInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":414 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0008", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___10___norm2_weight[name=p_getattr_l__self___trunk_blocks___10___norm2_weight]. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature FxOnnxInterpreter.run_node\n- self: \n- node: fx.Node(p_getattr_l__self___trunk_blocks___10___norm2_weight)[placeholder]:Tensor(f32[1024])\n- fx_graph_module: torch.fx.GraphModule(torch_nn_modules_container_Sequential)\n- onnxfunction_dispatcher: \n- op_level_debug: False\n- onnxscript_graph: \n- onnxscript_tracer: \n- fx_name_to_onnxscript_value: Dict[length=127](\nclone: `TorchScriptTensor(f32[4, 1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_weight: `TorchScriptTensor(f32[3072, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_bias: `TorchScriptTensor(f32[3072])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_weight: `TorchScriptTensor(f32[1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm2_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm2_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___mlp_fc1_weight: `TorchScriptTensor(f32[4096, 1024])`,\n...\n)\n## Return values\n", + "text":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___10___norm2_weight[name=p_getattr_l__self___trunk_blocks___10___norm2_weight]. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"FxOnnxInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":414 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0008", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___10___norm2_bias[name=p_getattr_l__self___trunk_blocks___10___norm2_bias]. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature FxOnnxInterpreter.run_node\n- self: \n- node: fx.Node(p_getattr_l__self___trunk_blocks___10___norm2_bias)[placeholder]:Tensor(f32[1024])\n- fx_graph_module: torch.fx.GraphModule(torch_nn_modules_container_Sequential)\n- onnxfunction_dispatcher: \n- op_level_debug: False\n- onnxscript_graph: \n- onnxscript_tracer: \n- fx_name_to_onnxscript_value: Dict[length=128](\nclone: `TorchScriptTensor(f32[4, 1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_weight: `TorchScriptTensor(f32[3072, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_bias: `TorchScriptTensor(f32[3072])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_weight: `TorchScriptTensor(f32[1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm2_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm2_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___mlp_fc1_weight: `TorchScriptTensor(f32[4096, 1024])`,\n...\n)\n## Return values\n", + "text":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___10___norm2_bias[name=p_getattr_l__self___trunk_blocks___10___norm2_bias]. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"FxOnnxInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":414 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0008", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___10___mlp_fc1_weight[name=p_getattr_l__self___trunk_blocks___10___mlp_fc1_weight]. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature FxOnnxInterpreter.run_node\n- self: \n- node: fx.Node(p_getattr_l__self___trunk_blocks___10___mlp_fc1_weight)[placeholder]:Tensor(f32[4096, 1024])\n- fx_graph_module: torch.fx.GraphModule(torch_nn_modules_container_Sequential)\n- onnxfunction_dispatcher: \n- op_level_debug: False\n- onnxscript_graph: \n- onnxscript_tracer: \n- fx_name_to_onnxscript_value: Dict[length=129](\nclone: `TorchScriptTensor(f32[4, 1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_weight: `TorchScriptTensor(f32[3072, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_bias: `TorchScriptTensor(f32[3072])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_weight: `TorchScriptTensor(f32[1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm2_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm2_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___mlp_fc1_weight: `TorchScriptTensor(f32[4096, 1024])`,\n...\n)\n## Return values\n", + "text":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___10___mlp_fc1_weight[name=p_getattr_l__self___trunk_blocks___10___mlp_fc1_weight]. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"FxOnnxInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":414 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0008", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___10___mlp_fc1_bias[name=p_getattr_l__self___trunk_blocks___10___mlp_fc1_bias]. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature FxOnnxInterpreter.run_node\n- self: \n- node: fx.Node(p_getattr_l__self___trunk_blocks___10___mlp_fc1_bias)[placeholder]:Tensor(f32[4096])\n- fx_graph_module: torch.fx.GraphModule(torch_nn_modules_container_Sequential)\n- onnxfunction_dispatcher: \n- op_level_debug: False\n- onnxscript_graph: \n- onnxscript_tracer: \n- fx_name_to_onnxscript_value: Dict[length=130](\nclone: `TorchScriptTensor(f32[4, 1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_weight: `TorchScriptTensor(f32[3072, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_bias: `TorchScriptTensor(f32[3072])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_weight: `TorchScriptTensor(f32[1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm2_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm2_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___mlp_fc1_weight: `TorchScriptTensor(f32[4096, 1024])`,\n...\n)\n## Return values\n", + "text":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___10___mlp_fc1_bias[name=p_getattr_l__self___trunk_blocks___10___mlp_fc1_bias]. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"FxOnnxInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":414 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0008", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___10___mlp_fc2_weight[name=p_getattr_l__self___trunk_blocks___10___mlp_fc2_weight]. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature FxOnnxInterpreter.run_node\n- self: \n- node: fx.Node(p_getattr_l__self___trunk_blocks___10___mlp_fc2_weight)[placeholder]:Tensor(f32[1024, 4096])\n- fx_graph_module: torch.fx.GraphModule(torch_nn_modules_container_Sequential)\n- onnxfunction_dispatcher: \n- op_level_debug: False\n- onnxscript_graph: \n- onnxscript_tracer: \n- fx_name_to_onnxscript_value: Dict[length=131](\nclone: `TorchScriptTensor(f32[4, 1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_weight: `TorchScriptTensor(f32[3072, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_bias: `TorchScriptTensor(f32[3072])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_weight: `TorchScriptTensor(f32[1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm2_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm2_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___mlp_fc1_weight: `TorchScriptTensor(f32[4096, 1024])`,\n...\n)\n## Return values\n", + "text":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___10___mlp_fc2_weight[name=p_getattr_l__self___trunk_blocks___10___mlp_fc2_weight]. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"FxOnnxInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":414 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0008", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___10___mlp_fc2_bias[name=p_getattr_l__self___trunk_blocks___10___mlp_fc2_bias]. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature FxOnnxInterpreter.run_node\n- self: \n- node: fx.Node(p_getattr_l__self___trunk_blocks___10___mlp_fc2_bias)[placeholder]:Tensor(f32[1024])\n- fx_graph_module: torch.fx.GraphModule(torch_nn_modules_container_Sequential)\n- onnxfunction_dispatcher: \n- op_level_debug: False\n- onnxscript_graph: \n- onnxscript_tracer: \n- fx_name_to_onnxscript_value: Dict[length=132](\nclone: `TorchScriptTensor(f32[4, 1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_weight: `TorchScriptTensor(f32[3072, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_bias: `TorchScriptTensor(f32[3072])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_weight: `TorchScriptTensor(f32[1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm2_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm2_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___mlp_fc1_weight: `TorchScriptTensor(f32[4096, 1024])`,\n...\n)\n## Return values\n", + "text":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___10___mlp_fc2_bias[name=p_getattr_l__self___trunk_blocks___10___mlp_fc2_bias]. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"FxOnnxInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":414 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0008", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___11___norm1_weight[name=p_getattr_l__self___trunk_blocks___11___norm1_weight]. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature FxOnnxInterpreter.run_node\n- self: \n- node: fx.Node(p_getattr_l__self___trunk_blocks___11___norm1_weight)[placeholder]:Tensor(f32[1024])\n- fx_graph_module: torch.fx.GraphModule(torch_nn_modules_container_Sequential)\n- onnxfunction_dispatcher: \n- op_level_debug: False\n- onnxscript_graph: \n- onnxscript_tracer: \n- fx_name_to_onnxscript_value: Dict[length=133](\nclone: `TorchScriptTensor(f32[4, 1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_weight: `TorchScriptTensor(f32[3072, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_bias: `TorchScriptTensor(f32[3072])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_weight: `TorchScriptTensor(f32[1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm2_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm2_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___mlp_fc1_weight: `TorchScriptTensor(f32[4096, 1024])`,\n...\n)\n## Return values\n", + "text":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___11___norm1_weight[name=p_getattr_l__self___trunk_blocks___11___norm1_weight]. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"FxOnnxInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":414 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0008", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___11___norm1_bias[name=p_getattr_l__self___trunk_blocks___11___norm1_bias]. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature FxOnnxInterpreter.run_node\n- self: \n- node: fx.Node(p_getattr_l__self___trunk_blocks___11___norm1_bias)[placeholder]:Tensor(f32[1024])\n- fx_graph_module: torch.fx.GraphModule(torch_nn_modules_container_Sequential)\n- onnxfunction_dispatcher: \n- op_level_debug: False\n- onnxscript_graph: \n- onnxscript_tracer: \n- fx_name_to_onnxscript_value: Dict[length=134](\nclone: `TorchScriptTensor(f32[4, 1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_weight: `TorchScriptTensor(f32[3072, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_bias: `TorchScriptTensor(f32[3072])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_weight: `TorchScriptTensor(f32[1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm2_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm2_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___mlp_fc1_weight: `TorchScriptTensor(f32[4096, 1024])`,\n...\n)\n## Return values\n", + "text":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___11___norm1_bias[name=p_getattr_l__self___trunk_blocks___11___norm1_bias]. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"FxOnnxInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":414 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0008", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___11___attn_qkv_weight[name=p_getattr_l__self___trunk_blocks___11___attn_qkv_weight]. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature FxOnnxInterpreter.run_node\n- self: \n- node: fx.Node(p_getattr_l__self___trunk_blocks___11___attn_qkv_weight)[placeholder]:Tensor(f32[3072, 1024])\n- fx_graph_module: torch.fx.GraphModule(torch_nn_modules_container_Sequential)\n- onnxfunction_dispatcher: \n- op_level_debug: False\n- onnxscript_graph: \n- onnxscript_tracer: \n- fx_name_to_onnxscript_value: Dict[length=135](\nclone: `TorchScriptTensor(f32[4, 1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_weight: `TorchScriptTensor(f32[3072, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_bias: `TorchScriptTensor(f32[3072])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_weight: `TorchScriptTensor(f32[1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm2_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm2_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___mlp_fc1_weight: `TorchScriptTensor(f32[4096, 1024])`,\n...\n)\n## Return values\n", + "text":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___11___attn_qkv_weight[name=p_getattr_l__self___trunk_blocks___11___attn_qkv_weight]. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"FxOnnxInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":414 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0008", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___11___attn_qkv_bias[name=p_getattr_l__self___trunk_blocks___11___attn_qkv_bias]. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature FxOnnxInterpreter.run_node\n- self: \n- node: fx.Node(p_getattr_l__self___trunk_blocks___11___attn_qkv_bias)[placeholder]:Tensor(f32[3072])\n- fx_graph_module: torch.fx.GraphModule(torch_nn_modules_container_Sequential)\n- onnxfunction_dispatcher: \n- op_level_debug: False\n- onnxscript_graph: \n- onnxscript_tracer: \n- fx_name_to_onnxscript_value: Dict[length=136](\nclone: `TorchScriptTensor(f32[4, 1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_weight: `TorchScriptTensor(f32[3072, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_bias: `TorchScriptTensor(f32[3072])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_weight: `TorchScriptTensor(f32[1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm2_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm2_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___mlp_fc1_weight: `TorchScriptTensor(f32[4096, 1024])`,\n...\n)\n## Return values\n", + "text":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___11___attn_qkv_bias[name=p_getattr_l__self___trunk_blocks___11___attn_qkv_bias]. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"FxOnnxInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":414 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0008", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___11___attn_proj_weight[name=p_getattr_l__self___trunk_blocks___11___attn_proj_weight]. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature FxOnnxInterpreter.run_node\n- self: \n- node: fx.Node(p_getattr_l__self___trunk_blocks___11___attn_proj_weight)[placeholder]:Tensor(f32[1024, 1024])\n- fx_graph_module: torch.fx.GraphModule(torch_nn_modules_container_Sequential)\n- onnxfunction_dispatcher: \n- op_level_debug: False\n- onnxscript_graph: \n- onnxscript_tracer: \n- fx_name_to_onnxscript_value: Dict[length=137](\nclone: `TorchScriptTensor(f32[4, 1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_weight: `TorchScriptTensor(f32[3072, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_bias: `TorchScriptTensor(f32[3072])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_weight: `TorchScriptTensor(f32[1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm2_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm2_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___mlp_fc1_weight: `TorchScriptTensor(f32[4096, 1024])`,\n...\n)\n## Return values\n", + "text":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___11___attn_proj_weight[name=p_getattr_l__self___trunk_blocks___11___attn_proj_weight]. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"FxOnnxInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":414 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0008", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___11___attn_proj_bias[name=p_getattr_l__self___trunk_blocks___11___attn_proj_bias]. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature FxOnnxInterpreter.run_node\n- self: \n- node: fx.Node(p_getattr_l__self___trunk_blocks___11___attn_proj_bias)[placeholder]:Tensor(f32[1024])\n- fx_graph_module: torch.fx.GraphModule(torch_nn_modules_container_Sequential)\n- onnxfunction_dispatcher: \n- op_level_debug: False\n- onnxscript_graph: \n- onnxscript_tracer: \n- fx_name_to_onnxscript_value: Dict[length=138](\nclone: `TorchScriptTensor(f32[4, 1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_weight: `TorchScriptTensor(f32[3072, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_bias: `TorchScriptTensor(f32[3072])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_weight: `TorchScriptTensor(f32[1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm2_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm2_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___mlp_fc1_weight: `TorchScriptTensor(f32[4096, 1024])`,\n...\n)\n## Return values\n", + "text":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___11___attn_proj_bias[name=p_getattr_l__self___trunk_blocks___11___attn_proj_bias]. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"FxOnnxInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":414 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0008", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___11___norm2_weight[name=p_getattr_l__self___trunk_blocks___11___norm2_weight]. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature FxOnnxInterpreter.run_node\n- self: \n- node: fx.Node(p_getattr_l__self___trunk_blocks___11___norm2_weight)[placeholder]:Tensor(f32[1024])\n- fx_graph_module: torch.fx.GraphModule(torch_nn_modules_container_Sequential)\n- onnxfunction_dispatcher: \n- op_level_debug: False\n- onnxscript_graph: \n- onnxscript_tracer: \n- fx_name_to_onnxscript_value: Dict[length=139](\nclone: `TorchScriptTensor(f32[4, 1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_weight: `TorchScriptTensor(f32[3072, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_bias: `TorchScriptTensor(f32[3072])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_weight: `TorchScriptTensor(f32[1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm2_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm2_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___mlp_fc1_weight: `TorchScriptTensor(f32[4096, 1024])`,\n...\n)\n## Return values\n", + "text":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___11___norm2_weight[name=p_getattr_l__self___trunk_blocks___11___norm2_weight]. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"FxOnnxInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":414 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0008", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___11___norm2_bias[name=p_getattr_l__self___trunk_blocks___11___norm2_bias]. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature FxOnnxInterpreter.run_node\n- self: \n- node: fx.Node(p_getattr_l__self___trunk_blocks___11___norm2_bias)[placeholder]:Tensor(f32[1024])\n- fx_graph_module: torch.fx.GraphModule(torch_nn_modules_container_Sequential)\n- onnxfunction_dispatcher: \n- op_level_debug: False\n- onnxscript_graph: \n- onnxscript_tracer: \n- fx_name_to_onnxscript_value: Dict[length=140](\nclone: `TorchScriptTensor(f32[4, 1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_weight: `TorchScriptTensor(f32[3072, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_bias: `TorchScriptTensor(f32[3072])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_weight: `TorchScriptTensor(f32[1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm2_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm2_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___mlp_fc1_weight: `TorchScriptTensor(f32[4096, 1024])`,\n...\n)\n## Return values\n", + "text":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___11___norm2_bias[name=p_getattr_l__self___trunk_blocks___11___norm2_bias]. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"FxOnnxInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":414 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0008", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___11___mlp_fc1_weight[name=p_getattr_l__self___trunk_blocks___11___mlp_fc1_weight]. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature FxOnnxInterpreter.run_node\n- self: \n- node: fx.Node(p_getattr_l__self___trunk_blocks___11___mlp_fc1_weight)[placeholder]:Tensor(f32[4096, 1024])\n- fx_graph_module: torch.fx.GraphModule(torch_nn_modules_container_Sequential)\n- onnxfunction_dispatcher: \n- op_level_debug: False\n- onnxscript_graph: \n- onnxscript_tracer: \n- fx_name_to_onnxscript_value: Dict[length=141](\nclone: `TorchScriptTensor(f32[4, 1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_weight: `TorchScriptTensor(f32[3072, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_bias: `TorchScriptTensor(f32[3072])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_weight: `TorchScriptTensor(f32[1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm2_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm2_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___mlp_fc1_weight: `TorchScriptTensor(f32[4096, 1024])`,\n...\n)\n## Return values\n", + "text":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___11___mlp_fc1_weight[name=p_getattr_l__self___trunk_blocks___11___mlp_fc1_weight]. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"FxOnnxInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":414 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0008", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___11___mlp_fc1_bias[name=p_getattr_l__self___trunk_blocks___11___mlp_fc1_bias]. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature FxOnnxInterpreter.run_node\n- self: \n- node: fx.Node(p_getattr_l__self___trunk_blocks___11___mlp_fc1_bias)[placeholder]:Tensor(f32[4096])\n- fx_graph_module: torch.fx.GraphModule(torch_nn_modules_container_Sequential)\n- onnxfunction_dispatcher: \n- op_level_debug: False\n- onnxscript_graph: \n- onnxscript_tracer: \n- fx_name_to_onnxscript_value: Dict[length=142](\nclone: `TorchScriptTensor(f32[4, 1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_weight: `TorchScriptTensor(f32[3072, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_bias: `TorchScriptTensor(f32[3072])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_weight: `TorchScriptTensor(f32[1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm2_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm2_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___mlp_fc1_weight: `TorchScriptTensor(f32[4096, 1024])`,\n...\n)\n## Return values\n", + "text":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___11___mlp_fc1_bias[name=p_getattr_l__self___trunk_blocks___11___mlp_fc1_bias]. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"FxOnnxInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":414 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0008", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___11___mlp_fc2_weight[name=p_getattr_l__self___trunk_blocks___11___mlp_fc2_weight]. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature FxOnnxInterpreter.run_node\n- self: \n- node: fx.Node(p_getattr_l__self___trunk_blocks___11___mlp_fc2_weight)[placeholder]:Tensor(f32[1024, 4096])\n- fx_graph_module: torch.fx.GraphModule(torch_nn_modules_container_Sequential)\n- onnxfunction_dispatcher: \n- op_level_debug: False\n- onnxscript_graph: \n- onnxscript_tracer: \n- fx_name_to_onnxscript_value: Dict[length=143](\nclone: `TorchScriptTensor(f32[4, 1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_weight: `TorchScriptTensor(f32[3072, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_bias: `TorchScriptTensor(f32[3072])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_weight: `TorchScriptTensor(f32[1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm2_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm2_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___mlp_fc1_weight: `TorchScriptTensor(f32[4096, 1024])`,\n...\n)\n## Return values\n", + "text":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___11___mlp_fc2_weight[name=p_getattr_l__self___trunk_blocks___11___mlp_fc2_weight]. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"FxOnnxInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":414 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0008", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___11___mlp_fc2_bias[name=p_getattr_l__self___trunk_blocks___11___mlp_fc2_bias]. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature FxOnnxInterpreter.run_node\n- self: \n- node: fx.Node(p_getattr_l__self___trunk_blocks___11___mlp_fc2_bias)[placeholder]:Tensor(f32[1024])\n- fx_graph_module: torch.fx.GraphModule(torch_nn_modules_container_Sequential)\n- onnxfunction_dispatcher: \n- op_level_debug: False\n- onnxscript_graph: \n- onnxscript_tracer: \n- fx_name_to_onnxscript_value: Dict[length=144](\nclone: `TorchScriptTensor(f32[4, 1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_weight: `TorchScriptTensor(f32[3072, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_bias: `TorchScriptTensor(f32[3072])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_weight: `TorchScriptTensor(f32[1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm2_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm2_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___mlp_fc1_weight: `TorchScriptTensor(f32[4096, 1024])`,\n...\n)\n## Return values\n", + "text":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___11___mlp_fc2_bias[name=p_getattr_l__self___trunk_blocks___11___mlp_fc2_bias]. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"FxOnnxInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":414 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0008", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___12___norm1_weight[name=p_getattr_l__self___trunk_blocks___12___norm1_weight]. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature FxOnnxInterpreter.run_node\n- self: \n- node: fx.Node(p_getattr_l__self___trunk_blocks___12___norm1_weight)[placeholder]:Tensor(f32[1024])\n- fx_graph_module: torch.fx.GraphModule(torch_nn_modules_container_Sequential)\n- onnxfunction_dispatcher: \n- op_level_debug: False\n- onnxscript_graph: \n- onnxscript_tracer: \n- fx_name_to_onnxscript_value: Dict[length=145](\nclone: `TorchScriptTensor(f32[4, 1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_weight: `TorchScriptTensor(f32[3072, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_bias: `TorchScriptTensor(f32[3072])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_weight: `TorchScriptTensor(f32[1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm2_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm2_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___mlp_fc1_weight: `TorchScriptTensor(f32[4096, 1024])`,\n...\n)\n## Return values\n", + "text":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___12___norm1_weight[name=p_getattr_l__self___trunk_blocks___12___norm1_weight]. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"FxOnnxInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":414 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0008", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___12___norm1_bias[name=p_getattr_l__self___trunk_blocks___12___norm1_bias]. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature FxOnnxInterpreter.run_node\n- self: \n- node: fx.Node(p_getattr_l__self___trunk_blocks___12___norm1_bias)[placeholder]:Tensor(f32[1024])\n- fx_graph_module: torch.fx.GraphModule(torch_nn_modules_container_Sequential)\n- onnxfunction_dispatcher: \n- op_level_debug: False\n- onnxscript_graph: \n- onnxscript_tracer: \n- fx_name_to_onnxscript_value: Dict[length=146](\nclone: `TorchScriptTensor(f32[4, 1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_weight: `TorchScriptTensor(f32[3072, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_bias: `TorchScriptTensor(f32[3072])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_weight: `TorchScriptTensor(f32[1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm2_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm2_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___mlp_fc1_weight: `TorchScriptTensor(f32[4096, 1024])`,\n...\n)\n## Return values\n", + "text":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___12___norm1_bias[name=p_getattr_l__self___trunk_blocks___12___norm1_bias]. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"FxOnnxInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":414 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0008", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___12___attn_qkv_weight[name=p_getattr_l__self___trunk_blocks___12___attn_qkv_weight]. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature FxOnnxInterpreter.run_node\n- self: \n- node: fx.Node(p_getattr_l__self___trunk_blocks___12___attn_qkv_weight)[placeholder]:Tensor(f32[3072, 1024])\n- fx_graph_module: torch.fx.GraphModule(torch_nn_modules_container_Sequential)\n- onnxfunction_dispatcher: \n- op_level_debug: False\n- onnxscript_graph: \n- onnxscript_tracer: \n- fx_name_to_onnxscript_value: Dict[length=147](\nclone: `TorchScriptTensor(f32[4, 1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_weight: `TorchScriptTensor(f32[3072, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_bias: `TorchScriptTensor(f32[3072])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_weight: `TorchScriptTensor(f32[1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm2_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm2_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___mlp_fc1_weight: `TorchScriptTensor(f32[4096, 1024])`,\n...\n)\n## Return values\n", + "text":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___12___attn_qkv_weight[name=p_getattr_l__self___trunk_blocks___12___attn_qkv_weight]. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"FxOnnxInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":414 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0008", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___12___attn_qkv_bias[name=p_getattr_l__self___trunk_blocks___12___attn_qkv_bias]. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature FxOnnxInterpreter.run_node\n- self: \n- node: fx.Node(p_getattr_l__self___trunk_blocks___12___attn_qkv_bias)[placeholder]:Tensor(f32[3072])\n- fx_graph_module: torch.fx.GraphModule(torch_nn_modules_container_Sequential)\n- onnxfunction_dispatcher: \n- op_level_debug: False\n- onnxscript_graph: \n- onnxscript_tracer: \n- fx_name_to_onnxscript_value: Dict[length=148](\nclone: `TorchScriptTensor(f32[4, 1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_weight: `TorchScriptTensor(f32[3072, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_bias: `TorchScriptTensor(f32[3072])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_weight: `TorchScriptTensor(f32[1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm2_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm2_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___mlp_fc1_weight: `TorchScriptTensor(f32[4096, 1024])`,\n...\n)\n## Return values\n", + "text":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___12___attn_qkv_bias[name=p_getattr_l__self___trunk_blocks___12___attn_qkv_bias]. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"FxOnnxInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":414 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0008", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___12___attn_proj_weight[name=p_getattr_l__self___trunk_blocks___12___attn_proj_weight]. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature FxOnnxInterpreter.run_node\n- self: \n- node: fx.Node(p_getattr_l__self___trunk_blocks___12___attn_proj_weight)[placeholder]:Tensor(f32[1024, 1024])\n- fx_graph_module: torch.fx.GraphModule(torch_nn_modules_container_Sequential)\n- onnxfunction_dispatcher: \n- op_level_debug: False\n- onnxscript_graph: \n- onnxscript_tracer: \n- fx_name_to_onnxscript_value: Dict[length=149](\nclone: `TorchScriptTensor(f32[4, 1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_weight: `TorchScriptTensor(f32[3072, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_bias: `TorchScriptTensor(f32[3072])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_weight: `TorchScriptTensor(f32[1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm2_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm2_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___mlp_fc1_weight: `TorchScriptTensor(f32[4096, 1024])`,\n...\n)\n## Return values\n", + "text":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___12___attn_proj_weight[name=p_getattr_l__self___trunk_blocks___12___attn_proj_weight]. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"FxOnnxInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":414 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0008", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___12___attn_proj_bias[name=p_getattr_l__self___trunk_blocks___12___attn_proj_bias]. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature FxOnnxInterpreter.run_node\n- self: \n- node: fx.Node(p_getattr_l__self___trunk_blocks___12___attn_proj_bias)[placeholder]:Tensor(f32[1024])\n- fx_graph_module: torch.fx.GraphModule(torch_nn_modules_container_Sequential)\n- onnxfunction_dispatcher: \n- op_level_debug: False\n- onnxscript_graph: \n- onnxscript_tracer: \n- fx_name_to_onnxscript_value: Dict[length=150](\nclone: `TorchScriptTensor(f32[4, 1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_weight: `TorchScriptTensor(f32[3072, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_bias: `TorchScriptTensor(f32[3072])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_weight: `TorchScriptTensor(f32[1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm2_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm2_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___mlp_fc1_weight: `TorchScriptTensor(f32[4096, 1024])`,\n...\n)\n## Return values\n", + "text":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___12___attn_proj_bias[name=p_getattr_l__self___trunk_blocks___12___attn_proj_bias]. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"FxOnnxInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":414 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0008", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___12___norm2_weight[name=p_getattr_l__self___trunk_blocks___12___norm2_weight]. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature FxOnnxInterpreter.run_node\n- self: \n- node: fx.Node(p_getattr_l__self___trunk_blocks___12___norm2_weight)[placeholder]:Tensor(f32[1024])\n- fx_graph_module: torch.fx.GraphModule(torch_nn_modules_container_Sequential)\n- onnxfunction_dispatcher: \n- op_level_debug: False\n- onnxscript_graph: \n- onnxscript_tracer: \n- fx_name_to_onnxscript_value: Dict[length=151](\nclone: `TorchScriptTensor(f32[4, 1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_weight: `TorchScriptTensor(f32[3072, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_bias: `TorchScriptTensor(f32[3072])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_weight: `TorchScriptTensor(f32[1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm2_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm2_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___mlp_fc1_weight: `TorchScriptTensor(f32[4096, 1024])`,\n...\n)\n## Return values\n", + "text":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___12___norm2_weight[name=p_getattr_l__self___trunk_blocks___12___norm2_weight]. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"FxOnnxInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":414 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0008", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___12___norm2_bias[name=p_getattr_l__self___trunk_blocks___12___norm2_bias]. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature FxOnnxInterpreter.run_node\n- self: \n- node: fx.Node(p_getattr_l__self___trunk_blocks___12___norm2_bias)[placeholder]:Tensor(f32[1024])\n- fx_graph_module: torch.fx.GraphModule(torch_nn_modules_container_Sequential)\n- onnxfunction_dispatcher: \n- op_level_debug: False\n- onnxscript_graph: \n- onnxscript_tracer: \n- fx_name_to_onnxscript_value: Dict[length=152](\nclone: `TorchScriptTensor(f32[4, 1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_weight: `TorchScriptTensor(f32[3072, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_bias: `TorchScriptTensor(f32[3072])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_weight: `TorchScriptTensor(f32[1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm2_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm2_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___mlp_fc1_weight: `TorchScriptTensor(f32[4096, 1024])`,\n...\n)\n## Return values\n", + "text":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___12___norm2_bias[name=p_getattr_l__self___trunk_blocks___12___norm2_bias]. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"FxOnnxInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":414 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0008", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___12___mlp_fc1_weight[name=p_getattr_l__self___trunk_blocks___12___mlp_fc1_weight]. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature FxOnnxInterpreter.run_node\n- self: \n- node: fx.Node(p_getattr_l__self___trunk_blocks___12___mlp_fc1_weight)[placeholder]:Tensor(f32[4096, 1024])\n- fx_graph_module: torch.fx.GraphModule(torch_nn_modules_container_Sequential)\n- onnxfunction_dispatcher: \n- op_level_debug: False\n- onnxscript_graph: \n- onnxscript_tracer: \n- fx_name_to_onnxscript_value: Dict[length=153](\nclone: `TorchScriptTensor(f32[4, 1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_weight: `TorchScriptTensor(f32[3072, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_bias: `TorchScriptTensor(f32[3072])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_weight: `TorchScriptTensor(f32[1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm2_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm2_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___mlp_fc1_weight: `TorchScriptTensor(f32[4096, 1024])`,\n...\n)\n## Return values\n", + "text":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___12___mlp_fc1_weight[name=p_getattr_l__self___trunk_blocks___12___mlp_fc1_weight]. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"FxOnnxInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":414 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0008", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___12___mlp_fc1_bias[name=p_getattr_l__self___trunk_blocks___12___mlp_fc1_bias]. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature FxOnnxInterpreter.run_node\n- self: \n- node: fx.Node(p_getattr_l__self___trunk_blocks___12___mlp_fc1_bias)[placeholder]:Tensor(f32[4096])\n- fx_graph_module: torch.fx.GraphModule(torch_nn_modules_container_Sequential)\n- onnxfunction_dispatcher: \n- op_level_debug: False\n- onnxscript_graph: \n- onnxscript_tracer: \n- fx_name_to_onnxscript_value: Dict[length=154](\nclone: `TorchScriptTensor(f32[4, 1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_weight: `TorchScriptTensor(f32[3072, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_bias: `TorchScriptTensor(f32[3072])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_weight: `TorchScriptTensor(f32[1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm2_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm2_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___mlp_fc1_weight: `TorchScriptTensor(f32[4096, 1024])`,\n...\n)\n## Return values\n", + "text":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___12___mlp_fc1_bias[name=p_getattr_l__self___trunk_blocks___12___mlp_fc1_bias]. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"FxOnnxInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":414 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0008", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___12___mlp_fc2_weight[name=p_getattr_l__self___trunk_blocks___12___mlp_fc2_weight]. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature FxOnnxInterpreter.run_node\n- self: \n- node: fx.Node(p_getattr_l__self___trunk_blocks___12___mlp_fc2_weight)[placeholder]:Tensor(f32[1024, 4096])\n- fx_graph_module: torch.fx.GraphModule(torch_nn_modules_container_Sequential)\n- onnxfunction_dispatcher: \n- op_level_debug: False\n- onnxscript_graph: \n- onnxscript_tracer: \n- fx_name_to_onnxscript_value: Dict[length=155](\nclone: `TorchScriptTensor(f32[4, 1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_weight: `TorchScriptTensor(f32[3072, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_bias: `TorchScriptTensor(f32[3072])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_weight: `TorchScriptTensor(f32[1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm2_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm2_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___mlp_fc1_weight: `TorchScriptTensor(f32[4096, 1024])`,\n...\n)\n## Return values\n", + "text":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___12___mlp_fc2_weight[name=p_getattr_l__self___trunk_blocks___12___mlp_fc2_weight]. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"FxOnnxInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":414 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0008", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___12___mlp_fc2_bias[name=p_getattr_l__self___trunk_blocks___12___mlp_fc2_bias]. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature FxOnnxInterpreter.run_node\n- self: \n- node: fx.Node(p_getattr_l__self___trunk_blocks___12___mlp_fc2_bias)[placeholder]:Tensor(f32[1024])\n- fx_graph_module: torch.fx.GraphModule(torch_nn_modules_container_Sequential)\n- onnxfunction_dispatcher: \n- op_level_debug: False\n- onnxscript_graph: \n- onnxscript_tracer: \n- fx_name_to_onnxscript_value: Dict[length=156](\nclone: `TorchScriptTensor(f32[4, 1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_weight: `TorchScriptTensor(f32[3072, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_bias: `TorchScriptTensor(f32[3072])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_weight: `TorchScriptTensor(f32[1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm2_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm2_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___mlp_fc1_weight: `TorchScriptTensor(f32[4096, 1024])`,\n...\n)\n## Return values\n", + "text":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___12___mlp_fc2_bias[name=p_getattr_l__self___trunk_blocks___12___mlp_fc2_bias]. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"FxOnnxInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":414 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0008", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___13___norm1_weight[name=p_getattr_l__self___trunk_blocks___13___norm1_weight]. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature FxOnnxInterpreter.run_node\n- self: \n- node: fx.Node(p_getattr_l__self___trunk_blocks___13___norm1_weight)[placeholder]:Tensor(f32[1024])\n- fx_graph_module: torch.fx.GraphModule(torch_nn_modules_container_Sequential)\n- onnxfunction_dispatcher: \n- op_level_debug: False\n- onnxscript_graph: \n- onnxscript_tracer: \n- fx_name_to_onnxscript_value: Dict[length=157](\nclone: `TorchScriptTensor(f32[4, 1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_weight: `TorchScriptTensor(f32[3072, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_bias: `TorchScriptTensor(f32[3072])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_weight: `TorchScriptTensor(f32[1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm2_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm2_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___mlp_fc1_weight: `TorchScriptTensor(f32[4096, 1024])`,\n...\n)\n## Return values\n", + "text":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___13___norm1_weight[name=p_getattr_l__self___trunk_blocks___13___norm1_weight]. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"FxOnnxInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":414 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0008", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___13___norm1_bias[name=p_getattr_l__self___trunk_blocks___13___norm1_bias]. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature FxOnnxInterpreter.run_node\n- self: \n- node: fx.Node(p_getattr_l__self___trunk_blocks___13___norm1_bias)[placeholder]:Tensor(f32[1024])\n- fx_graph_module: torch.fx.GraphModule(torch_nn_modules_container_Sequential)\n- onnxfunction_dispatcher: \n- op_level_debug: False\n- onnxscript_graph: \n- onnxscript_tracer: \n- fx_name_to_onnxscript_value: Dict[length=158](\nclone: `TorchScriptTensor(f32[4, 1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_weight: `TorchScriptTensor(f32[3072, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_bias: `TorchScriptTensor(f32[3072])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_weight: `TorchScriptTensor(f32[1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm2_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm2_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___mlp_fc1_weight: `TorchScriptTensor(f32[4096, 1024])`,\n...\n)\n## Return values\n", + "text":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___13___norm1_bias[name=p_getattr_l__self___trunk_blocks___13___norm1_bias]. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"FxOnnxInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":414 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0008", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___13___attn_qkv_weight[name=p_getattr_l__self___trunk_blocks___13___attn_qkv_weight]. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature FxOnnxInterpreter.run_node\n- self: \n- node: fx.Node(p_getattr_l__self___trunk_blocks___13___attn_qkv_weight)[placeholder]:Tensor(f32[3072, 1024])\n- fx_graph_module: torch.fx.GraphModule(torch_nn_modules_container_Sequential)\n- onnxfunction_dispatcher: \n- op_level_debug: False\n- onnxscript_graph: \n- onnxscript_tracer: \n- fx_name_to_onnxscript_value: Dict[length=159](\nclone: `TorchScriptTensor(f32[4, 1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_weight: `TorchScriptTensor(f32[3072, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_bias: `TorchScriptTensor(f32[3072])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_weight: `TorchScriptTensor(f32[1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm2_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm2_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___mlp_fc1_weight: `TorchScriptTensor(f32[4096, 1024])`,\n...\n)\n## Return values\n", + "text":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___13___attn_qkv_weight[name=p_getattr_l__self___trunk_blocks___13___attn_qkv_weight]. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"FxOnnxInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":414 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0008", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___13___attn_qkv_bias[name=p_getattr_l__self___trunk_blocks___13___attn_qkv_bias]. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature FxOnnxInterpreter.run_node\n- self: \n- node: fx.Node(p_getattr_l__self___trunk_blocks___13___attn_qkv_bias)[placeholder]:Tensor(f32[3072])\n- fx_graph_module: torch.fx.GraphModule(torch_nn_modules_container_Sequential)\n- onnxfunction_dispatcher: \n- op_level_debug: False\n- onnxscript_graph: \n- onnxscript_tracer: \n- fx_name_to_onnxscript_value: Dict[length=160](\nclone: `TorchScriptTensor(f32[4, 1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_weight: `TorchScriptTensor(f32[3072, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_bias: `TorchScriptTensor(f32[3072])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_weight: `TorchScriptTensor(f32[1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm2_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm2_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___mlp_fc1_weight: `TorchScriptTensor(f32[4096, 1024])`,\n...\n)\n## Return values\n", + "text":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___13___attn_qkv_bias[name=p_getattr_l__self___trunk_blocks___13___attn_qkv_bias]. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"FxOnnxInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":414 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0008", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___13___attn_proj_weight[name=p_getattr_l__self___trunk_blocks___13___attn_proj_weight]. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature FxOnnxInterpreter.run_node\n- self: \n- node: fx.Node(p_getattr_l__self___trunk_blocks___13___attn_proj_weight)[placeholder]:Tensor(f32[1024, 1024])\n- fx_graph_module: torch.fx.GraphModule(torch_nn_modules_container_Sequential)\n- onnxfunction_dispatcher: \n- op_level_debug: False\n- onnxscript_graph: \n- onnxscript_tracer: \n- fx_name_to_onnxscript_value: Dict[length=161](\nclone: `TorchScriptTensor(f32[4, 1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_weight: `TorchScriptTensor(f32[3072, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_bias: `TorchScriptTensor(f32[3072])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_weight: `TorchScriptTensor(f32[1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm2_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm2_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___mlp_fc1_weight: `TorchScriptTensor(f32[4096, 1024])`,\n...\n)\n## Return values\n", + "text":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___13___attn_proj_weight[name=p_getattr_l__self___trunk_blocks___13___attn_proj_weight]. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"FxOnnxInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":414 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0008", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___13___attn_proj_bias[name=p_getattr_l__self___trunk_blocks___13___attn_proj_bias]. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature FxOnnxInterpreter.run_node\n- self: \n- node: fx.Node(p_getattr_l__self___trunk_blocks___13___attn_proj_bias)[placeholder]:Tensor(f32[1024])\n- fx_graph_module: torch.fx.GraphModule(torch_nn_modules_container_Sequential)\n- onnxfunction_dispatcher: \n- op_level_debug: False\n- onnxscript_graph: \n- onnxscript_tracer: \n- fx_name_to_onnxscript_value: Dict[length=162](\nclone: `TorchScriptTensor(f32[4, 1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_weight: `TorchScriptTensor(f32[3072, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_bias: `TorchScriptTensor(f32[3072])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_weight: `TorchScriptTensor(f32[1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm2_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm2_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___mlp_fc1_weight: `TorchScriptTensor(f32[4096, 1024])`,\n...\n)\n## Return values\n", + "text":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___13___attn_proj_bias[name=p_getattr_l__self___trunk_blocks___13___attn_proj_bias]. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"FxOnnxInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":414 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0008", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___13___norm2_weight[name=p_getattr_l__self___trunk_blocks___13___norm2_weight]. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature FxOnnxInterpreter.run_node\n- self: \n- node: fx.Node(p_getattr_l__self___trunk_blocks___13___norm2_weight)[placeholder]:Tensor(f32[1024])\n- fx_graph_module: torch.fx.GraphModule(torch_nn_modules_container_Sequential)\n- onnxfunction_dispatcher: \n- op_level_debug: False\n- onnxscript_graph: \n- onnxscript_tracer: \n- fx_name_to_onnxscript_value: Dict[length=163](\nclone: `TorchScriptTensor(f32[4, 1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_weight: `TorchScriptTensor(f32[3072, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_bias: `TorchScriptTensor(f32[3072])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_weight: `TorchScriptTensor(f32[1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm2_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm2_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___mlp_fc1_weight: `TorchScriptTensor(f32[4096, 1024])`,\n...\n)\n## Return values\n", + "text":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___13___norm2_weight[name=p_getattr_l__self___trunk_blocks___13___norm2_weight]. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"FxOnnxInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":414 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0008", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___13___norm2_bias[name=p_getattr_l__self___trunk_blocks___13___norm2_bias]. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature FxOnnxInterpreter.run_node\n- self: \n- node: fx.Node(p_getattr_l__self___trunk_blocks___13___norm2_bias)[placeholder]:Tensor(f32[1024])\n- fx_graph_module: torch.fx.GraphModule(torch_nn_modules_container_Sequential)\n- onnxfunction_dispatcher: \n- op_level_debug: False\n- onnxscript_graph: \n- onnxscript_tracer: \n- fx_name_to_onnxscript_value: Dict[length=164](\nclone: `TorchScriptTensor(f32[4, 1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_weight: `TorchScriptTensor(f32[3072, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_bias: `TorchScriptTensor(f32[3072])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_weight: `TorchScriptTensor(f32[1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm2_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm2_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___mlp_fc1_weight: `TorchScriptTensor(f32[4096, 1024])`,\n...\n)\n## Return values\n", + "text":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___13___norm2_bias[name=p_getattr_l__self___trunk_blocks___13___norm2_bias]. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"FxOnnxInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":414 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0008", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___13___mlp_fc1_weight[name=p_getattr_l__self___trunk_blocks___13___mlp_fc1_weight]. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature FxOnnxInterpreter.run_node\n- self: \n- node: fx.Node(p_getattr_l__self___trunk_blocks___13___mlp_fc1_weight)[placeholder]:Tensor(f32[4096, 1024])\n- fx_graph_module: torch.fx.GraphModule(torch_nn_modules_container_Sequential)\n- onnxfunction_dispatcher: \n- op_level_debug: False\n- onnxscript_graph: \n- onnxscript_tracer: \n- fx_name_to_onnxscript_value: Dict[length=165](\nclone: `TorchScriptTensor(f32[4, 1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_weight: `TorchScriptTensor(f32[3072, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_bias: `TorchScriptTensor(f32[3072])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_weight: `TorchScriptTensor(f32[1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm2_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm2_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___mlp_fc1_weight: `TorchScriptTensor(f32[4096, 1024])`,\n...\n)\n## Return values\n", + "text":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___13___mlp_fc1_weight[name=p_getattr_l__self___trunk_blocks___13___mlp_fc1_weight]. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"FxOnnxInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":414 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0008", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___13___mlp_fc1_bias[name=p_getattr_l__self___trunk_blocks___13___mlp_fc1_bias]. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature FxOnnxInterpreter.run_node\n- self: \n- node: fx.Node(p_getattr_l__self___trunk_blocks___13___mlp_fc1_bias)[placeholder]:Tensor(f32[4096])\n- fx_graph_module: torch.fx.GraphModule(torch_nn_modules_container_Sequential)\n- onnxfunction_dispatcher: \n- op_level_debug: False\n- onnxscript_graph: \n- onnxscript_tracer: \n- fx_name_to_onnxscript_value: Dict[length=166](\nclone: `TorchScriptTensor(f32[4, 1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_weight: `TorchScriptTensor(f32[3072, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_bias: `TorchScriptTensor(f32[3072])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_weight: `TorchScriptTensor(f32[1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm2_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm2_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___mlp_fc1_weight: `TorchScriptTensor(f32[4096, 1024])`,\n...\n)\n## Return values\n", + "text":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___13___mlp_fc1_bias[name=p_getattr_l__self___trunk_blocks___13___mlp_fc1_bias]. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"FxOnnxInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":414 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0008", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___13___mlp_fc2_weight[name=p_getattr_l__self___trunk_blocks___13___mlp_fc2_weight]. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature FxOnnxInterpreter.run_node\n- self: \n- node: fx.Node(p_getattr_l__self___trunk_blocks___13___mlp_fc2_weight)[placeholder]:Tensor(f32[1024, 4096])\n- fx_graph_module: torch.fx.GraphModule(torch_nn_modules_container_Sequential)\n- onnxfunction_dispatcher: \n- op_level_debug: False\n- onnxscript_graph: \n- onnxscript_tracer: \n- fx_name_to_onnxscript_value: Dict[length=167](\nclone: `TorchScriptTensor(f32[4, 1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_weight: `TorchScriptTensor(f32[3072, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_bias: `TorchScriptTensor(f32[3072])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_weight: `TorchScriptTensor(f32[1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm2_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm2_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___mlp_fc1_weight: `TorchScriptTensor(f32[4096, 1024])`,\n...\n)\n## Return values\n", + "text":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___13___mlp_fc2_weight[name=p_getattr_l__self___trunk_blocks___13___mlp_fc2_weight]. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"FxOnnxInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":414 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0008", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___13___mlp_fc2_bias[name=p_getattr_l__self___trunk_blocks___13___mlp_fc2_bias]. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature FxOnnxInterpreter.run_node\n- self: \n- node: fx.Node(p_getattr_l__self___trunk_blocks___13___mlp_fc2_bias)[placeholder]:Tensor(f32[1024])\n- fx_graph_module: torch.fx.GraphModule(torch_nn_modules_container_Sequential)\n- onnxfunction_dispatcher: \n- op_level_debug: False\n- onnxscript_graph: \n- onnxscript_tracer: \n- fx_name_to_onnxscript_value: Dict[length=168](\nclone: `TorchScriptTensor(f32[4, 1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_weight: `TorchScriptTensor(f32[3072, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_bias: `TorchScriptTensor(f32[3072])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_weight: `TorchScriptTensor(f32[1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm2_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm2_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___mlp_fc1_weight: `TorchScriptTensor(f32[4096, 1024])`,\n...\n)\n## Return values\n", + "text":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___13___mlp_fc2_bias[name=p_getattr_l__self___trunk_blocks___13___mlp_fc2_bias]. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"FxOnnxInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":414 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0008", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___14___norm1_weight[name=p_getattr_l__self___trunk_blocks___14___norm1_weight]. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature FxOnnxInterpreter.run_node\n- self: \n- node: fx.Node(p_getattr_l__self___trunk_blocks___14___norm1_weight)[placeholder]:Tensor(f32[1024])\n- fx_graph_module: torch.fx.GraphModule(torch_nn_modules_container_Sequential)\n- onnxfunction_dispatcher: \n- op_level_debug: False\n- onnxscript_graph: \n- onnxscript_tracer: \n- fx_name_to_onnxscript_value: Dict[length=169](\nclone: `TorchScriptTensor(f32[4, 1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_weight: `TorchScriptTensor(f32[3072, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_bias: `TorchScriptTensor(f32[3072])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_weight: `TorchScriptTensor(f32[1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm2_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm2_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___mlp_fc1_weight: `TorchScriptTensor(f32[4096, 1024])`,\n...\n)\n## Return values\n", + "text":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___14___norm1_weight[name=p_getattr_l__self___trunk_blocks___14___norm1_weight]. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"FxOnnxInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":414 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0008", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___14___norm1_bias[name=p_getattr_l__self___trunk_blocks___14___norm1_bias]. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature FxOnnxInterpreter.run_node\n- self: \n- node: fx.Node(p_getattr_l__self___trunk_blocks___14___norm1_bias)[placeholder]:Tensor(f32[1024])\n- fx_graph_module: torch.fx.GraphModule(torch_nn_modules_container_Sequential)\n- onnxfunction_dispatcher: \n- op_level_debug: False\n- onnxscript_graph: \n- onnxscript_tracer: \n- fx_name_to_onnxscript_value: Dict[length=170](\nclone: `TorchScriptTensor(f32[4, 1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_weight: `TorchScriptTensor(f32[3072, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_bias: `TorchScriptTensor(f32[3072])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_weight: `TorchScriptTensor(f32[1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm2_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm2_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___mlp_fc1_weight: `TorchScriptTensor(f32[4096, 1024])`,\n...\n)\n## Return values\n", + "text":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___14___norm1_bias[name=p_getattr_l__self___trunk_blocks___14___norm1_bias]. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"FxOnnxInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":414 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0008", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___14___attn_qkv_weight[name=p_getattr_l__self___trunk_blocks___14___attn_qkv_weight]. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature FxOnnxInterpreter.run_node\n- self: \n- node: fx.Node(p_getattr_l__self___trunk_blocks___14___attn_qkv_weight)[placeholder]:Tensor(f32[3072, 1024])\n- fx_graph_module: torch.fx.GraphModule(torch_nn_modules_container_Sequential)\n- onnxfunction_dispatcher: \n- op_level_debug: False\n- onnxscript_graph: \n- onnxscript_tracer: \n- fx_name_to_onnxscript_value: Dict[length=171](\nclone: `TorchScriptTensor(f32[4, 1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_weight: `TorchScriptTensor(f32[3072, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_bias: `TorchScriptTensor(f32[3072])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_weight: `TorchScriptTensor(f32[1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm2_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm2_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___mlp_fc1_weight: `TorchScriptTensor(f32[4096, 1024])`,\n...\n)\n## Return values\n", + "text":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___14___attn_qkv_weight[name=p_getattr_l__self___trunk_blocks___14___attn_qkv_weight]. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"FxOnnxInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":414 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0008", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___14___attn_qkv_bias[name=p_getattr_l__self___trunk_blocks___14___attn_qkv_bias]. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature FxOnnxInterpreter.run_node\n- self: \n- node: fx.Node(p_getattr_l__self___trunk_blocks___14___attn_qkv_bias)[placeholder]:Tensor(f32[3072])\n- fx_graph_module: torch.fx.GraphModule(torch_nn_modules_container_Sequential)\n- onnxfunction_dispatcher: \n- op_level_debug: False\n- onnxscript_graph: \n- onnxscript_tracer: \n- fx_name_to_onnxscript_value: Dict[length=172](\nclone: `TorchScriptTensor(f32[4, 1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_weight: `TorchScriptTensor(f32[3072, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_bias: `TorchScriptTensor(f32[3072])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_weight: `TorchScriptTensor(f32[1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm2_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm2_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___mlp_fc1_weight: `TorchScriptTensor(f32[4096, 1024])`,\n...\n)\n## Return values\n", + "text":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___14___attn_qkv_bias[name=p_getattr_l__self___trunk_blocks___14___attn_qkv_bias]. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"FxOnnxInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":414 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0008", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___14___attn_proj_weight[name=p_getattr_l__self___trunk_blocks___14___attn_proj_weight]. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature FxOnnxInterpreter.run_node\n- self: \n- node: fx.Node(p_getattr_l__self___trunk_blocks___14___attn_proj_weight)[placeholder]:Tensor(f32[1024, 1024])\n- fx_graph_module: torch.fx.GraphModule(torch_nn_modules_container_Sequential)\n- onnxfunction_dispatcher: \n- op_level_debug: False\n- onnxscript_graph: \n- onnxscript_tracer: \n- fx_name_to_onnxscript_value: Dict[length=173](\nclone: `TorchScriptTensor(f32[4, 1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_weight: `TorchScriptTensor(f32[3072, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_bias: `TorchScriptTensor(f32[3072])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_weight: `TorchScriptTensor(f32[1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm2_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm2_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___mlp_fc1_weight: `TorchScriptTensor(f32[4096, 1024])`,\n...\n)\n## Return values\n", + "text":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___14___attn_proj_weight[name=p_getattr_l__self___trunk_blocks___14___attn_proj_weight]. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"FxOnnxInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":414 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0008", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___14___attn_proj_bias[name=p_getattr_l__self___trunk_blocks___14___attn_proj_bias]. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature FxOnnxInterpreter.run_node\n- self: \n- node: fx.Node(p_getattr_l__self___trunk_blocks___14___attn_proj_bias)[placeholder]:Tensor(f32[1024])\n- fx_graph_module: torch.fx.GraphModule(torch_nn_modules_container_Sequential)\n- onnxfunction_dispatcher: \n- op_level_debug: False\n- onnxscript_graph: \n- onnxscript_tracer: \n- fx_name_to_onnxscript_value: Dict[length=174](\nclone: `TorchScriptTensor(f32[4, 1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_weight: `TorchScriptTensor(f32[3072, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_bias: `TorchScriptTensor(f32[3072])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_weight: `TorchScriptTensor(f32[1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm2_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm2_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___mlp_fc1_weight: `TorchScriptTensor(f32[4096, 1024])`,\n...\n)\n## Return values\n", + "text":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___14___attn_proj_bias[name=p_getattr_l__self___trunk_blocks___14___attn_proj_bias]. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"FxOnnxInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":414 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0008", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___14___norm2_weight[name=p_getattr_l__self___trunk_blocks___14___norm2_weight]. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature FxOnnxInterpreter.run_node\n- self: \n- node: fx.Node(p_getattr_l__self___trunk_blocks___14___norm2_weight)[placeholder]:Tensor(f32[1024])\n- fx_graph_module: torch.fx.GraphModule(torch_nn_modules_container_Sequential)\n- onnxfunction_dispatcher: \n- op_level_debug: False\n- onnxscript_graph: \n- onnxscript_tracer: \n- fx_name_to_onnxscript_value: Dict[length=175](\nclone: `TorchScriptTensor(f32[4, 1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_weight: `TorchScriptTensor(f32[3072, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_bias: `TorchScriptTensor(f32[3072])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_weight: `TorchScriptTensor(f32[1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm2_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm2_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___mlp_fc1_weight: `TorchScriptTensor(f32[4096, 1024])`,\n...\n)\n## Return values\n", + "text":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___14___norm2_weight[name=p_getattr_l__self___trunk_blocks___14___norm2_weight]. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"FxOnnxInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":414 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0008", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___14___norm2_bias[name=p_getattr_l__self___trunk_blocks___14___norm2_bias]. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature FxOnnxInterpreter.run_node\n- self: \n- node: fx.Node(p_getattr_l__self___trunk_blocks___14___norm2_bias)[placeholder]:Tensor(f32[1024])\n- fx_graph_module: torch.fx.GraphModule(torch_nn_modules_container_Sequential)\n- onnxfunction_dispatcher: \n- op_level_debug: False\n- onnxscript_graph: \n- onnxscript_tracer: \n- fx_name_to_onnxscript_value: Dict[length=176](\nclone: `TorchScriptTensor(f32[4, 1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_weight: `TorchScriptTensor(f32[3072, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_bias: `TorchScriptTensor(f32[3072])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_weight: `TorchScriptTensor(f32[1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm2_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm2_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___mlp_fc1_weight: `TorchScriptTensor(f32[4096, 1024])`,\n...\n)\n## Return values\n", + "text":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___14___norm2_bias[name=p_getattr_l__self___trunk_blocks___14___norm2_bias]. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"FxOnnxInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":414 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0008", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___14___mlp_fc1_weight[name=p_getattr_l__self___trunk_blocks___14___mlp_fc1_weight]. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature FxOnnxInterpreter.run_node\n- self: \n- node: fx.Node(p_getattr_l__self___trunk_blocks___14___mlp_fc1_weight)[placeholder]:Tensor(f32[4096, 1024])\n- fx_graph_module: torch.fx.GraphModule(torch_nn_modules_container_Sequential)\n- onnxfunction_dispatcher: \n- op_level_debug: False\n- onnxscript_graph: \n- onnxscript_tracer: \n- fx_name_to_onnxscript_value: Dict[length=177](\nclone: `TorchScriptTensor(f32[4, 1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_weight: `TorchScriptTensor(f32[3072, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_bias: `TorchScriptTensor(f32[3072])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_weight: `TorchScriptTensor(f32[1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm2_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm2_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___mlp_fc1_weight: `TorchScriptTensor(f32[4096, 1024])`,\n...\n)\n## Return values\n", + "text":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___14___mlp_fc1_weight[name=p_getattr_l__self___trunk_blocks___14___mlp_fc1_weight]. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"FxOnnxInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":414 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0008", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___14___mlp_fc1_bias[name=p_getattr_l__self___trunk_blocks___14___mlp_fc1_bias]. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature FxOnnxInterpreter.run_node\n- self: \n- node: fx.Node(p_getattr_l__self___trunk_blocks___14___mlp_fc1_bias)[placeholder]:Tensor(f32[4096])\n- fx_graph_module: torch.fx.GraphModule(torch_nn_modules_container_Sequential)\n- onnxfunction_dispatcher: \n- op_level_debug: False\n- onnxscript_graph: \n- onnxscript_tracer: \n- fx_name_to_onnxscript_value: Dict[length=178](\nclone: `TorchScriptTensor(f32[4, 1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_weight: `TorchScriptTensor(f32[3072, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_bias: `TorchScriptTensor(f32[3072])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_weight: `TorchScriptTensor(f32[1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm2_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm2_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___mlp_fc1_weight: `TorchScriptTensor(f32[4096, 1024])`,\n...\n)\n## Return values\n", + "text":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___14___mlp_fc1_bias[name=p_getattr_l__self___trunk_blocks___14___mlp_fc1_bias]. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"FxOnnxInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":414 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0008", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___14___mlp_fc2_weight[name=p_getattr_l__self___trunk_blocks___14___mlp_fc2_weight]. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature FxOnnxInterpreter.run_node\n- self: \n- node: fx.Node(p_getattr_l__self___trunk_blocks___14___mlp_fc2_weight)[placeholder]:Tensor(f32[1024, 4096])\n- fx_graph_module: torch.fx.GraphModule(torch_nn_modules_container_Sequential)\n- onnxfunction_dispatcher: \n- op_level_debug: False\n- onnxscript_graph: \n- onnxscript_tracer: \n- fx_name_to_onnxscript_value: Dict[length=179](\nclone: `TorchScriptTensor(f32[4, 1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_weight: `TorchScriptTensor(f32[3072, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_bias: `TorchScriptTensor(f32[3072])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_weight: `TorchScriptTensor(f32[1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm2_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm2_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___mlp_fc1_weight: `TorchScriptTensor(f32[4096, 1024])`,\n...\n)\n## Return values\n", + "text":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___14___mlp_fc2_weight[name=p_getattr_l__self___trunk_blocks___14___mlp_fc2_weight]. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"FxOnnxInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":414 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0008", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___14___mlp_fc2_bias[name=p_getattr_l__self___trunk_blocks___14___mlp_fc2_bias]. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature FxOnnxInterpreter.run_node\n- self: \n- node: fx.Node(p_getattr_l__self___trunk_blocks___14___mlp_fc2_bias)[placeholder]:Tensor(f32[1024])\n- fx_graph_module: torch.fx.GraphModule(torch_nn_modules_container_Sequential)\n- onnxfunction_dispatcher: \n- op_level_debug: False\n- onnxscript_graph: \n- onnxscript_tracer: \n- fx_name_to_onnxscript_value: Dict[length=180](\nclone: `TorchScriptTensor(f32[4, 1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_weight: `TorchScriptTensor(f32[3072, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_bias: `TorchScriptTensor(f32[3072])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_weight: `TorchScriptTensor(f32[1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm2_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm2_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___mlp_fc1_weight: `TorchScriptTensor(f32[4096, 1024])`,\n...\n)\n## Return values\n", + "text":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___14___mlp_fc2_bias[name=p_getattr_l__self___trunk_blocks___14___mlp_fc2_bias]. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"FxOnnxInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":414 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0008", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___15___norm1_weight[name=p_getattr_l__self___trunk_blocks___15___norm1_weight]. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature FxOnnxInterpreter.run_node\n- self: \n- node: fx.Node(p_getattr_l__self___trunk_blocks___15___norm1_weight)[placeholder]:Tensor(f32[1024])\n- fx_graph_module: torch.fx.GraphModule(torch_nn_modules_container_Sequential)\n- onnxfunction_dispatcher: \n- op_level_debug: False\n- onnxscript_graph: \n- onnxscript_tracer: \n- fx_name_to_onnxscript_value: Dict[length=181](\nclone: `TorchScriptTensor(f32[4, 1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_weight: `TorchScriptTensor(f32[3072, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_bias: `TorchScriptTensor(f32[3072])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_weight: `TorchScriptTensor(f32[1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm2_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm2_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___mlp_fc1_weight: `TorchScriptTensor(f32[4096, 1024])`,\n...\n)\n## Return values\n", + "text":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___15___norm1_weight[name=p_getattr_l__self___trunk_blocks___15___norm1_weight]. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"FxOnnxInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":414 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0008", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___15___norm1_bias[name=p_getattr_l__self___trunk_blocks___15___norm1_bias]. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature FxOnnxInterpreter.run_node\n- self: \n- node: fx.Node(p_getattr_l__self___trunk_blocks___15___norm1_bias)[placeholder]:Tensor(f32[1024])\n- fx_graph_module: torch.fx.GraphModule(torch_nn_modules_container_Sequential)\n- onnxfunction_dispatcher: \n- op_level_debug: False\n- onnxscript_graph: \n- onnxscript_tracer: \n- fx_name_to_onnxscript_value: Dict[length=182](\nclone: `TorchScriptTensor(f32[4, 1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_weight: `TorchScriptTensor(f32[3072, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_bias: `TorchScriptTensor(f32[3072])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_weight: `TorchScriptTensor(f32[1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm2_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm2_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___mlp_fc1_weight: `TorchScriptTensor(f32[4096, 1024])`,\n...\n)\n## Return values\n", + "text":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___15___norm1_bias[name=p_getattr_l__self___trunk_blocks___15___norm1_bias]. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"FxOnnxInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":414 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0008", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___15___attn_qkv_weight[name=p_getattr_l__self___trunk_blocks___15___attn_qkv_weight]. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature FxOnnxInterpreter.run_node\n- self: \n- node: fx.Node(p_getattr_l__self___trunk_blocks___15___attn_qkv_weight)[placeholder]:Tensor(f32[3072, 1024])\n- fx_graph_module: torch.fx.GraphModule(torch_nn_modules_container_Sequential)\n- onnxfunction_dispatcher: \n- op_level_debug: False\n- onnxscript_graph: \n- onnxscript_tracer: \n- fx_name_to_onnxscript_value: Dict[length=183](\nclone: `TorchScriptTensor(f32[4, 1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_weight: `TorchScriptTensor(f32[3072, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_bias: `TorchScriptTensor(f32[3072])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_weight: `TorchScriptTensor(f32[1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm2_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm2_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___mlp_fc1_weight: `TorchScriptTensor(f32[4096, 1024])`,\n...\n)\n## Return values\n", + "text":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___15___attn_qkv_weight[name=p_getattr_l__self___trunk_blocks___15___attn_qkv_weight]. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"FxOnnxInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":414 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0008", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___15___attn_qkv_bias[name=p_getattr_l__self___trunk_blocks___15___attn_qkv_bias]. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature FxOnnxInterpreter.run_node\n- self: \n- node: fx.Node(p_getattr_l__self___trunk_blocks___15___attn_qkv_bias)[placeholder]:Tensor(f32[3072])\n- fx_graph_module: torch.fx.GraphModule(torch_nn_modules_container_Sequential)\n- onnxfunction_dispatcher: \n- op_level_debug: False\n- onnxscript_graph: \n- onnxscript_tracer: \n- fx_name_to_onnxscript_value: Dict[length=184](\nclone: `TorchScriptTensor(f32[4, 1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_weight: `TorchScriptTensor(f32[3072, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_bias: `TorchScriptTensor(f32[3072])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_weight: `TorchScriptTensor(f32[1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm2_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm2_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___mlp_fc1_weight: `TorchScriptTensor(f32[4096, 1024])`,\n...\n)\n## Return values\n", + "text":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___15___attn_qkv_bias[name=p_getattr_l__self___trunk_blocks___15___attn_qkv_bias]. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"FxOnnxInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":414 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0008", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___15___attn_proj_weight[name=p_getattr_l__self___trunk_blocks___15___attn_proj_weight]. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature FxOnnxInterpreter.run_node\n- self: \n- node: fx.Node(p_getattr_l__self___trunk_blocks___15___attn_proj_weight)[placeholder]:Tensor(f32[1024, 1024])\n- fx_graph_module: torch.fx.GraphModule(torch_nn_modules_container_Sequential)\n- onnxfunction_dispatcher: \n- op_level_debug: False\n- onnxscript_graph: \n- onnxscript_tracer: \n- fx_name_to_onnxscript_value: Dict[length=185](\nclone: `TorchScriptTensor(f32[4, 1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_weight: `TorchScriptTensor(f32[3072, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_bias: `TorchScriptTensor(f32[3072])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_weight: `TorchScriptTensor(f32[1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm2_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm2_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___mlp_fc1_weight: `TorchScriptTensor(f32[4096, 1024])`,\n...\n)\n## Return values\n", + "text":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___15___attn_proj_weight[name=p_getattr_l__self___trunk_blocks___15___attn_proj_weight]. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"FxOnnxInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":414 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0008", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___15___attn_proj_bias[name=p_getattr_l__self___trunk_blocks___15___attn_proj_bias]. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature FxOnnxInterpreter.run_node\n- self: \n- node: fx.Node(p_getattr_l__self___trunk_blocks___15___attn_proj_bias)[placeholder]:Tensor(f32[1024])\n- fx_graph_module: torch.fx.GraphModule(torch_nn_modules_container_Sequential)\n- onnxfunction_dispatcher: \n- op_level_debug: False\n- onnxscript_graph: \n- onnxscript_tracer: \n- fx_name_to_onnxscript_value: Dict[length=186](\nclone: `TorchScriptTensor(f32[4, 1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_weight: `TorchScriptTensor(f32[3072, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_bias: `TorchScriptTensor(f32[3072])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_weight: `TorchScriptTensor(f32[1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm2_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm2_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___mlp_fc1_weight: `TorchScriptTensor(f32[4096, 1024])`,\n...\n)\n## Return values\n", + "text":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___15___attn_proj_bias[name=p_getattr_l__self___trunk_blocks___15___attn_proj_bias]. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"FxOnnxInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":414 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0008", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___15___norm2_weight[name=p_getattr_l__self___trunk_blocks___15___norm2_weight]. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature FxOnnxInterpreter.run_node\n- self: \n- node: fx.Node(p_getattr_l__self___trunk_blocks___15___norm2_weight)[placeholder]:Tensor(f32[1024])\n- fx_graph_module: torch.fx.GraphModule(torch_nn_modules_container_Sequential)\n- onnxfunction_dispatcher: \n- op_level_debug: False\n- onnxscript_graph: \n- onnxscript_tracer: \n- fx_name_to_onnxscript_value: Dict[length=187](\nclone: `TorchScriptTensor(f32[4, 1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_weight: `TorchScriptTensor(f32[3072, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_bias: `TorchScriptTensor(f32[3072])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_weight: `TorchScriptTensor(f32[1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm2_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm2_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___mlp_fc1_weight: `TorchScriptTensor(f32[4096, 1024])`,\n...\n)\n## Return values\n", + "text":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___15___norm2_weight[name=p_getattr_l__self___trunk_blocks___15___norm2_weight]. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"FxOnnxInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":414 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0008", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___15___norm2_bias[name=p_getattr_l__self___trunk_blocks___15___norm2_bias]. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature FxOnnxInterpreter.run_node\n- self: \n- node: fx.Node(p_getattr_l__self___trunk_blocks___15___norm2_bias)[placeholder]:Tensor(f32[1024])\n- fx_graph_module: torch.fx.GraphModule(torch_nn_modules_container_Sequential)\n- onnxfunction_dispatcher: \n- op_level_debug: False\n- onnxscript_graph: \n- onnxscript_tracer: \n- fx_name_to_onnxscript_value: Dict[length=188](\nclone: `TorchScriptTensor(f32[4, 1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_weight: `TorchScriptTensor(f32[3072, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_bias: `TorchScriptTensor(f32[3072])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_weight: `TorchScriptTensor(f32[1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm2_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm2_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___mlp_fc1_weight: `TorchScriptTensor(f32[4096, 1024])`,\n...\n)\n## Return values\n", + "text":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___15___norm2_bias[name=p_getattr_l__self___trunk_blocks___15___norm2_bias]. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"FxOnnxInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":414 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0008", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___15___mlp_fc1_weight[name=p_getattr_l__self___trunk_blocks___15___mlp_fc1_weight]. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature FxOnnxInterpreter.run_node\n- self: \n- node: fx.Node(p_getattr_l__self___trunk_blocks___15___mlp_fc1_weight)[placeholder]:Tensor(f32[4096, 1024])\n- fx_graph_module: torch.fx.GraphModule(torch_nn_modules_container_Sequential)\n- onnxfunction_dispatcher: \n- op_level_debug: False\n- onnxscript_graph: \n- onnxscript_tracer: \n- fx_name_to_onnxscript_value: Dict[length=189](\nclone: `TorchScriptTensor(f32[4, 1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_weight: `TorchScriptTensor(f32[3072, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_bias: `TorchScriptTensor(f32[3072])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_weight: `TorchScriptTensor(f32[1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm2_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm2_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___mlp_fc1_weight: `TorchScriptTensor(f32[4096, 1024])`,\n...\n)\n## Return values\n", + "text":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___15___mlp_fc1_weight[name=p_getattr_l__self___trunk_blocks___15___mlp_fc1_weight]. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"FxOnnxInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":414 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0008", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___15___mlp_fc1_bias[name=p_getattr_l__self___trunk_blocks___15___mlp_fc1_bias]. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature FxOnnxInterpreter.run_node\n- self: \n- node: fx.Node(p_getattr_l__self___trunk_blocks___15___mlp_fc1_bias)[placeholder]:Tensor(f32[4096])\n- fx_graph_module: torch.fx.GraphModule(torch_nn_modules_container_Sequential)\n- onnxfunction_dispatcher: \n- op_level_debug: False\n- onnxscript_graph: \n- onnxscript_tracer: \n- fx_name_to_onnxscript_value: Dict[length=190](\nclone: `TorchScriptTensor(f32[4, 1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_weight: `TorchScriptTensor(f32[3072, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_bias: `TorchScriptTensor(f32[3072])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_weight: `TorchScriptTensor(f32[1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm2_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm2_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___mlp_fc1_weight: `TorchScriptTensor(f32[4096, 1024])`,\n...\n)\n## Return values\n", + "text":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___15___mlp_fc1_bias[name=p_getattr_l__self___trunk_blocks___15___mlp_fc1_bias]. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"FxOnnxInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":414 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0008", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___15___mlp_fc2_weight[name=p_getattr_l__self___trunk_blocks___15___mlp_fc2_weight]. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature FxOnnxInterpreter.run_node\n- self: \n- node: fx.Node(p_getattr_l__self___trunk_blocks___15___mlp_fc2_weight)[placeholder]:Tensor(f32[1024, 4096])\n- fx_graph_module: torch.fx.GraphModule(torch_nn_modules_container_Sequential)\n- onnxfunction_dispatcher: \n- op_level_debug: False\n- onnxscript_graph: \n- onnxscript_tracer: \n- fx_name_to_onnxscript_value: Dict[length=191](\nclone: `TorchScriptTensor(f32[4, 1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_weight: `TorchScriptTensor(f32[3072, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_bias: `TorchScriptTensor(f32[3072])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_weight: `TorchScriptTensor(f32[1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm2_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm2_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___mlp_fc1_weight: `TorchScriptTensor(f32[4096, 1024])`,\n...\n)\n## Return values\n", + "text":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___15___mlp_fc2_weight[name=p_getattr_l__self___trunk_blocks___15___mlp_fc2_weight]. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"FxOnnxInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":414 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0008", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___15___mlp_fc2_bias[name=p_getattr_l__self___trunk_blocks___15___mlp_fc2_bias]. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature FxOnnxInterpreter.run_node\n- self: \n- node: fx.Node(p_getattr_l__self___trunk_blocks___15___mlp_fc2_bias)[placeholder]:Tensor(f32[1024])\n- fx_graph_module: torch.fx.GraphModule(torch_nn_modules_container_Sequential)\n- onnxfunction_dispatcher: \n- op_level_debug: False\n- onnxscript_graph: \n- onnxscript_tracer: \n- fx_name_to_onnxscript_value: Dict[length=192](\nclone: `TorchScriptTensor(f32[4, 1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_weight: `TorchScriptTensor(f32[3072, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_bias: `TorchScriptTensor(f32[3072])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_weight: `TorchScriptTensor(f32[1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm2_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm2_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___mlp_fc1_weight: `TorchScriptTensor(f32[4096, 1024])`,\n...\n)\n## Return values\n", + "text":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___15___mlp_fc2_bias[name=p_getattr_l__self___trunk_blocks___15___mlp_fc2_bias]. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"FxOnnxInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":414 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0008", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___16___norm1_weight[name=p_getattr_l__self___trunk_blocks___16___norm1_weight]. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature FxOnnxInterpreter.run_node\n- self: \n- node: fx.Node(p_getattr_l__self___trunk_blocks___16___norm1_weight)[placeholder]:Tensor(f32[1024])\n- fx_graph_module: torch.fx.GraphModule(torch_nn_modules_container_Sequential)\n- onnxfunction_dispatcher: \n- op_level_debug: False\n- onnxscript_graph: \n- onnxscript_tracer: \n- fx_name_to_onnxscript_value: Dict[length=193](\nclone: `TorchScriptTensor(f32[4, 1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_weight: `TorchScriptTensor(f32[3072, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_bias: `TorchScriptTensor(f32[3072])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_weight: `TorchScriptTensor(f32[1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm2_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm2_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___mlp_fc1_weight: `TorchScriptTensor(f32[4096, 1024])`,\n...\n)\n## Return values\n", + "text":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___16___norm1_weight[name=p_getattr_l__self___trunk_blocks___16___norm1_weight]. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"FxOnnxInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":414 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0008", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___16___norm1_bias[name=p_getattr_l__self___trunk_blocks___16___norm1_bias]. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature FxOnnxInterpreter.run_node\n- self: \n- node: fx.Node(p_getattr_l__self___trunk_blocks___16___norm1_bias)[placeholder]:Tensor(f32[1024])\n- fx_graph_module: torch.fx.GraphModule(torch_nn_modules_container_Sequential)\n- onnxfunction_dispatcher: \n- op_level_debug: False\n- onnxscript_graph: \n- onnxscript_tracer: \n- fx_name_to_onnxscript_value: Dict[length=194](\nclone: `TorchScriptTensor(f32[4, 1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_weight: `TorchScriptTensor(f32[3072, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_bias: `TorchScriptTensor(f32[3072])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_weight: `TorchScriptTensor(f32[1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm2_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm2_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___mlp_fc1_weight: `TorchScriptTensor(f32[4096, 1024])`,\n...\n)\n## Return values\n", + "text":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___16___norm1_bias[name=p_getattr_l__self___trunk_blocks___16___norm1_bias]. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"FxOnnxInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":414 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0008", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___16___attn_qkv_weight[name=p_getattr_l__self___trunk_blocks___16___attn_qkv_weight]. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature FxOnnxInterpreter.run_node\n- self: \n- node: fx.Node(p_getattr_l__self___trunk_blocks___16___attn_qkv_weight)[placeholder]:Tensor(f32[3072, 1024])\n- fx_graph_module: torch.fx.GraphModule(torch_nn_modules_container_Sequential)\n- onnxfunction_dispatcher: \n- op_level_debug: False\n- onnxscript_graph: \n- onnxscript_tracer: \n- fx_name_to_onnxscript_value: Dict[length=195](\nclone: `TorchScriptTensor(f32[4, 1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_weight: `TorchScriptTensor(f32[3072, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_bias: `TorchScriptTensor(f32[3072])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_weight: `TorchScriptTensor(f32[1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm2_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm2_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___mlp_fc1_weight: `TorchScriptTensor(f32[4096, 1024])`,\n...\n)\n## Return values\n", + "text":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___16___attn_qkv_weight[name=p_getattr_l__self___trunk_blocks___16___attn_qkv_weight]. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"FxOnnxInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":414 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0008", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___16___attn_qkv_bias[name=p_getattr_l__self___trunk_blocks___16___attn_qkv_bias]. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature FxOnnxInterpreter.run_node\n- self: \n- node: fx.Node(p_getattr_l__self___trunk_blocks___16___attn_qkv_bias)[placeholder]:Tensor(f32[3072])\n- fx_graph_module: torch.fx.GraphModule(torch_nn_modules_container_Sequential)\n- onnxfunction_dispatcher: \n- op_level_debug: False\n- onnxscript_graph: \n- onnxscript_tracer: \n- fx_name_to_onnxscript_value: Dict[length=196](\nclone: `TorchScriptTensor(f32[4, 1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_weight: `TorchScriptTensor(f32[3072, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_bias: `TorchScriptTensor(f32[3072])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_weight: `TorchScriptTensor(f32[1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm2_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm2_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___mlp_fc1_weight: `TorchScriptTensor(f32[4096, 1024])`,\n...\n)\n## Return values\n", + "text":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___16___attn_qkv_bias[name=p_getattr_l__self___trunk_blocks___16___attn_qkv_bias]. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"FxOnnxInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":414 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0008", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___16___attn_proj_weight[name=p_getattr_l__self___trunk_blocks___16___attn_proj_weight]. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature FxOnnxInterpreter.run_node\n- self: \n- node: fx.Node(p_getattr_l__self___trunk_blocks___16___attn_proj_weight)[placeholder]:Tensor(f32[1024, 1024])\n- fx_graph_module: torch.fx.GraphModule(torch_nn_modules_container_Sequential)\n- onnxfunction_dispatcher: \n- op_level_debug: False\n- onnxscript_graph: \n- onnxscript_tracer: \n- fx_name_to_onnxscript_value: Dict[length=197](\nclone: `TorchScriptTensor(f32[4, 1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_weight: `TorchScriptTensor(f32[3072, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_bias: `TorchScriptTensor(f32[3072])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_weight: `TorchScriptTensor(f32[1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm2_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm2_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___mlp_fc1_weight: `TorchScriptTensor(f32[4096, 1024])`,\n...\n)\n## Return values\n", + "text":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___16___attn_proj_weight[name=p_getattr_l__self___trunk_blocks___16___attn_proj_weight]. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"FxOnnxInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":414 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0008", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___16___attn_proj_bias[name=p_getattr_l__self___trunk_blocks___16___attn_proj_bias]. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature FxOnnxInterpreter.run_node\n- self: \n- node: fx.Node(p_getattr_l__self___trunk_blocks___16___attn_proj_bias)[placeholder]:Tensor(f32[1024])\n- fx_graph_module: torch.fx.GraphModule(torch_nn_modules_container_Sequential)\n- onnxfunction_dispatcher: \n- op_level_debug: False\n- onnxscript_graph: \n- onnxscript_tracer: \n- fx_name_to_onnxscript_value: Dict[length=198](\nclone: `TorchScriptTensor(f32[4, 1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_weight: `TorchScriptTensor(f32[3072, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_bias: `TorchScriptTensor(f32[3072])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_weight: `TorchScriptTensor(f32[1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm2_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm2_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___mlp_fc1_weight: `TorchScriptTensor(f32[4096, 1024])`,\n...\n)\n## Return values\n", + "text":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___16___attn_proj_bias[name=p_getattr_l__self___trunk_blocks___16___attn_proj_bias]. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"FxOnnxInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":414 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0008", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___16___norm2_weight[name=p_getattr_l__self___trunk_blocks___16___norm2_weight]. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature FxOnnxInterpreter.run_node\n- self: \n- node: fx.Node(p_getattr_l__self___trunk_blocks___16___norm2_weight)[placeholder]:Tensor(f32[1024])\n- fx_graph_module: torch.fx.GraphModule(torch_nn_modules_container_Sequential)\n- onnxfunction_dispatcher: \n- op_level_debug: False\n- onnxscript_graph: \n- onnxscript_tracer: \n- fx_name_to_onnxscript_value: Dict[length=199](\nclone: `TorchScriptTensor(f32[4, 1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_weight: `TorchScriptTensor(f32[3072, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_bias: `TorchScriptTensor(f32[3072])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_weight: `TorchScriptTensor(f32[1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm2_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm2_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___mlp_fc1_weight: `TorchScriptTensor(f32[4096, 1024])`,\n...\n)\n## Return values\n", + "text":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___16___norm2_weight[name=p_getattr_l__self___trunk_blocks___16___norm2_weight]. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"FxOnnxInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":414 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0008", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___16___norm2_bias[name=p_getattr_l__self___trunk_blocks___16___norm2_bias]. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature FxOnnxInterpreter.run_node\n- self: \n- node: fx.Node(p_getattr_l__self___trunk_blocks___16___norm2_bias)[placeholder]:Tensor(f32[1024])\n- fx_graph_module: torch.fx.GraphModule(torch_nn_modules_container_Sequential)\n- onnxfunction_dispatcher: \n- op_level_debug: False\n- onnxscript_graph: \n- onnxscript_tracer: \n- fx_name_to_onnxscript_value: Dict[length=200](\nclone: `TorchScriptTensor(f32[4, 1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_weight: `TorchScriptTensor(f32[3072, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_bias: `TorchScriptTensor(f32[3072])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_weight: `TorchScriptTensor(f32[1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm2_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm2_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___mlp_fc1_weight: `TorchScriptTensor(f32[4096, 1024])`,\n...\n)\n## Return values\n", + "text":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___16___norm2_bias[name=p_getattr_l__self___trunk_blocks___16___norm2_bias]. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"FxOnnxInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":414 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0008", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___16___mlp_fc1_weight[name=p_getattr_l__self___trunk_blocks___16___mlp_fc1_weight]. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature FxOnnxInterpreter.run_node\n- self: \n- node: fx.Node(p_getattr_l__self___trunk_blocks___16___mlp_fc1_weight)[placeholder]:Tensor(f32[4096, 1024])\n- fx_graph_module: torch.fx.GraphModule(torch_nn_modules_container_Sequential)\n- onnxfunction_dispatcher: \n- op_level_debug: False\n- onnxscript_graph: \n- onnxscript_tracer: \n- fx_name_to_onnxscript_value: Dict[length=201](\nclone: `TorchScriptTensor(f32[4, 1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_weight: `TorchScriptTensor(f32[3072, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_bias: `TorchScriptTensor(f32[3072])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_weight: `TorchScriptTensor(f32[1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm2_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm2_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___mlp_fc1_weight: `TorchScriptTensor(f32[4096, 1024])`,\n...\n)\n## Return values\n", + "text":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___16___mlp_fc1_weight[name=p_getattr_l__self___trunk_blocks___16___mlp_fc1_weight]. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"FxOnnxInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":414 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0008", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___16___mlp_fc1_bias[name=p_getattr_l__self___trunk_blocks___16___mlp_fc1_bias]. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature FxOnnxInterpreter.run_node\n- self: \n- node: fx.Node(p_getattr_l__self___trunk_blocks___16___mlp_fc1_bias)[placeholder]:Tensor(f32[4096])\n- fx_graph_module: torch.fx.GraphModule(torch_nn_modules_container_Sequential)\n- onnxfunction_dispatcher: \n- op_level_debug: False\n- onnxscript_graph: \n- onnxscript_tracer: \n- fx_name_to_onnxscript_value: Dict[length=202](\nclone: `TorchScriptTensor(f32[4, 1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_weight: `TorchScriptTensor(f32[3072, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_bias: `TorchScriptTensor(f32[3072])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_weight: `TorchScriptTensor(f32[1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm2_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm2_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___mlp_fc1_weight: `TorchScriptTensor(f32[4096, 1024])`,\n...\n)\n## Return values\n", + "text":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___16___mlp_fc1_bias[name=p_getattr_l__self___trunk_blocks___16___mlp_fc1_bias]. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"FxOnnxInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":414 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0008", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___16___mlp_fc2_weight[name=p_getattr_l__self___trunk_blocks___16___mlp_fc2_weight]. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature FxOnnxInterpreter.run_node\n- self: \n- node: fx.Node(p_getattr_l__self___trunk_blocks___16___mlp_fc2_weight)[placeholder]:Tensor(f32[1024, 4096])\n- fx_graph_module: torch.fx.GraphModule(torch_nn_modules_container_Sequential)\n- onnxfunction_dispatcher: \n- op_level_debug: False\n- onnxscript_graph: \n- onnxscript_tracer: \n- fx_name_to_onnxscript_value: Dict[length=203](\nclone: `TorchScriptTensor(f32[4, 1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_weight: `TorchScriptTensor(f32[3072, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_bias: `TorchScriptTensor(f32[3072])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_weight: `TorchScriptTensor(f32[1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm2_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm2_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___mlp_fc1_weight: `TorchScriptTensor(f32[4096, 1024])`,\n...\n)\n## Return values\n", + "text":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___16___mlp_fc2_weight[name=p_getattr_l__self___trunk_blocks___16___mlp_fc2_weight]. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"FxOnnxInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":414 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0008", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___16___mlp_fc2_bias[name=p_getattr_l__self___trunk_blocks___16___mlp_fc2_bias]. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature FxOnnxInterpreter.run_node\n- self: \n- node: fx.Node(p_getattr_l__self___trunk_blocks___16___mlp_fc2_bias)[placeholder]:Tensor(f32[1024])\n- fx_graph_module: torch.fx.GraphModule(torch_nn_modules_container_Sequential)\n- onnxfunction_dispatcher: \n- op_level_debug: False\n- onnxscript_graph: \n- onnxscript_tracer: \n- fx_name_to_onnxscript_value: Dict[length=204](\nclone: `TorchScriptTensor(f32[4, 1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_weight: `TorchScriptTensor(f32[3072, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_bias: `TorchScriptTensor(f32[3072])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_weight: `TorchScriptTensor(f32[1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm2_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm2_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___mlp_fc1_weight: `TorchScriptTensor(f32[4096, 1024])`,\n...\n)\n## Return values\n", + "text":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___16___mlp_fc2_bias[name=p_getattr_l__self___trunk_blocks___16___mlp_fc2_bias]. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"FxOnnxInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":414 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0008", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___17___norm1_weight[name=p_getattr_l__self___trunk_blocks___17___norm1_weight]. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature FxOnnxInterpreter.run_node\n- self: \n- node: fx.Node(p_getattr_l__self___trunk_blocks___17___norm1_weight)[placeholder]:Tensor(f32[1024])\n- fx_graph_module: torch.fx.GraphModule(torch_nn_modules_container_Sequential)\n- onnxfunction_dispatcher: \n- op_level_debug: False\n- onnxscript_graph: \n- onnxscript_tracer: \n- fx_name_to_onnxscript_value: Dict[length=205](\nclone: `TorchScriptTensor(f32[4, 1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_weight: `TorchScriptTensor(f32[3072, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_bias: `TorchScriptTensor(f32[3072])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_weight: `TorchScriptTensor(f32[1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm2_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm2_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___mlp_fc1_weight: `TorchScriptTensor(f32[4096, 1024])`,\n...\n)\n## Return values\n", + "text":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___17___norm1_weight[name=p_getattr_l__self___trunk_blocks___17___norm1_weight]. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"FxOnnxInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":414 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0008", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___17___norm1_bias[name=p_getattr_l__self___trunk_blocks___17___norm1_bias]. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature FxOnnxInterpreter.run_node\n- self: \n- node: fx.Node(p_getattr_l__self___trunk_blocks___17___norm1_bias)[placeholder]:Tensor(f32[1024])\n- fx_graph_module: torch.fx.GraphModule(torch_nn_modules_container_Sequential)\n- onnxfunction_dispatcher: \n- op_level_debug: False\n- onnxscript_graph: \n- onnxscript_tracer: \n- fx_name_to_onnxscript_value: Dict[length=206](\nclone: `TorchScriptTensor(f32[4, 1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_weight: `TorchScriptTensor(f32[3072, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_bias: `TorchScriptTensor(f32[3072])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_weight: `TorchScriptTensor(f32[1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm2_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm2_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___mlp_fc1_weight: `TorchScriptTensor(f32[4096, 1024])`,\n...\n)\n## Return values\n", + "text":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___17___norm1_bias[name=p_getattr_l__self___trunk_blocks___17___norm1_bias]. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"FxOnnxInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":414 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0008", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___17___attn_qkv_weight[name=p_getattr_l__self___trunk_blocks___17___attn_qkv_weight]. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature FxOnnxInterpreter.run_node\n- self: \n- node: fx.Node(p_getattr_l__self___trunk_blocks___17___attn_qkv_weight)[placeholder]:Tensor(f32[3072, 1024])\n- fx_graph_module: torch.fx.GraphModule(torch_nn_modules_container_Sequential)\n- onnxfunction_dispatcher: \n- op_level_debug: False\n- onnxscript_graph: \n- onnxscript_tracer: \n- fx_name_to_onnxscript_value: Dict[length=207](\nclone: `TorchScriptTensor(f32[4, 1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_weight: `TorchScriptTensor(f32[3072, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_bias: `TorchScriptTensor(f32[3072])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_weight: `TorchScriptTensor(f32[1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm2_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm2_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___mlp_fc1_weight: `TorchScriptTensor(f32[4096, 1024])`,\n...\n)\n## Return values\n", + "text":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___17___attn_qkv_weight[name=p_getattr_l__self___trunk_blocks___17___attn_qkv_weight]. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"FxOnnxInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":414 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0008", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___17___attn_qkv_bias[name=p_getattr_l__self___trunk_blocks___17___attn_qkv_bias]. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature FxOnnxInterpreter.run_node\n- self: \n- node: fx.Node(p_getattr_l__self___trunk_blocks___17___attn_qkv_bias)[placeholder]:Tensor(f32[3072])\n- fx_graph_module: torch.fx.GraphModule(torch_nn_modules_container_Sequential)\n- onnxfunction_dispatcher: \n- op_level_debug: False\n- onnxscript_graph: \n- onnxscript_tracer: \n- fx_name_to_onnxscript_value: Dict[length=208](\nclone: `TorchScriptTensor(f32[4, 1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_weight: `TorchScriptTensor(f32[3072, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_bias: `TorchScriptTensor(f32[3072])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_weight: `TorchScriptTensor(f32[1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm2_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm2_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___mlp_fc1_weight: `TorchScriptTensor(f32[4096, 1024])`,\n...\n)\n## Return values\n", + "text":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___17___attn_qkv_bias[name=p_getattr_l__self___trunk_blocks___17___attn_qkv_bias]. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"FxOnnxInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":414 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0008", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___17___attn_proj_weight[name=p_getattr_l__self___trunk_blocks___17___attn_proj_weight]. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature FxOnnxInterpreter.run_node\n- self: \n- node: fx.Node(p_getattr_l__self___trunk_blocks___17___attn_proj_weight)[placeholder]:Tensor(f32[1024, 1024])\n- fx_graph_module: torch.fx.GraphModule(torch_nn_modules_container_Sequential)\n- onnxfunction_dispatcher: \n- op_level_debug: False\n- onnxscript_graph: \n- onnxscript_tracer: \n- fx_name_to_onnxscript_value: Dict[length=209](\nclone: `TorchScriptTensor(f32[4, 1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_weight: `TorchScriptTensor(f32[3072, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_bias: `TorchScriptTensor(f32[3072])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_weight: `TorchScriptTensor(f32[1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm2_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm2_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___mlp_fc1_weight: `TorchScriptTensor(f32[4096, 1024])`,\n...\n)\n## Return values\n", + "text":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___17___attn_proj_weight[name=p_getattr_l__self___trunk_blocks___17___attn_proj_weight]. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"FxOnnxInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":414 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0008", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___17___attn_proj_bias[name=p_getattr_l__self___trunk_blocks___17___attn_proj_bias]. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature FxOnnxInterpreter.run_node\n- self: \n- node: fx.Node(p_getattr_l__self___trunk_blocks___17___attn_proj_bias)[placeholder]:Tensor(f32[1024])\n- fx_graph_module: torch.fx.GraphModule(torch_nn_modules_container_Sequential)\n- onnxfunction_dispatcher: \n- op_level_debug: False\n- onnxscript_graph: \n- onnxscript_tracer: \n- fx_name_to_onnxscript_value: Dict[length=210](\nclone: `TorchScriptTensor(f32[4, 1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_weight: `TorchScriptTensor(f32[3072, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_bias: `TorchScriptTensor(f32[3072])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_weight: `TorchScriptTensor(f32[1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm2_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm2_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___mlp_fc1_weight: `TorchScriptTensor(f32[4096, 1024])`,\n...\n)\n## Return values\n", + "text":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___17___attn_proj_bias[name=p_getattr_l__self___trunk_blocks___17___attn_proj_bias]. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"FxOnnxInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":414 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0008", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___17___norm2_weight[name=p_getattr_l__self___trunk_blocks___17___norm2_weight]. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature FxOnnxInterpreter.run_node\n- self: \n- node: fx.Node(p_getattr_l__self___trunk_blocks___17___norm2_weight)[placeholder]:Tensor(f32[1024])\n- fx_graph_module: torch.fx.GraphModule(torch_nn_modules_container_Sequential)\n- onnxfunction_dispatcher: \n- op_level_debug: False\n- onnxscript_graph: \n- onnxscript_tracer: \n- fx_name_to_onnxscript_value: Dict[length=211](\nclone: `TorchScriptTensor(f32[4, 1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_weight: `TorchScriptTensor(f32[3072, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_bias: `TorchScriptTensor(f32[3072])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_weight: `TorchScriptTensor(f32[1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm2_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm2_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___mlp_fc1_weight: `TorchScriptTensor(f32[4096, 1024])`,\n...\n)\n## Return values\n", + "text":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___17___norm2_weight[name=p_getattr_l__self___trunk_blocks___17___norm2_weight]. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"FxOnnxInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":414 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0008", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___17___norm2_bias[name=p_getattr_l__self___trunk_blocks___17___norm2_bias]. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature FxOnnxInterpreter.run_node\n- self: \n- node: fx.Node(p_getattr_l__self___trunk_blocks___17___norm2_bias)[placeholder]:Tensor(f32[1024])\n- fx_graph_module: torch.fx.GraphModule(torch_nn_modules_container_Sequential)\n- onnxfunction_dispatcher: \n- op_level_debug: False\n- onnxscript_graph: \n- onnxscript_tracer: \n- fx_name_to_onnxscript_value: Dict[length=212](\nclone: `TorchScriptTensor(f32[4, 1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_weight: `TorchScriptTensor(f32[3072, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_bias: `TorchScriptTensor(f32[3072])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_weight: `TorchScriptTensor(f32[1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm2_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm2_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___mlp_fc1_weight: `TorchScriptTensor(f32[4096, 1024])`,\n...\n)\n## Return values\n", + "text":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___17___norm2_bias[name=p_getattr_l__self___trunk_blocks___17___norm2_bias]. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"FxOnnxInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":414 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0008", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___17___mlp_fc1_weight[name=p_getattr_l__self___trunk_blocks___17___mlp_fc1_weight]. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature FxOnnxInterpreter.run_node\n- self: \n- node: fx.Node(p_getattr_l__self___trunk_blocks___17___mlp_fc1_weight)[placeholder]:Tensor(f32[4096, 1024])\n- fx_graph_module: torch.fx.GraphModule(torch_nn_modules_container_Sequential)\n- onnxfunction_dispatcher: \n- op_level_debug: False\n- onnxscript_graph: \n- onnxscript_tracer: \n- fx_name_to_onnxscript_value: Dict[length=213](\nclone: `TorchScriptTensor(f32[4, 1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_weight: `TorchScriptTensor(f32[3072, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_bias: `TorchScriptTensor(f32[3072])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_weight: `TorchScriptTensor(f32[1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm2_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm2_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___mlp_fc1_weight: `TorchScriptTensor(f32[4096, 1024])`,\n...\n)\n## Return values\n", + "text":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___17___mlp_fc1_weight[name=p_getattr_l__self___trunk_blocks___17___mlp_fc1_weight]. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"FxOnnxInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":414 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0008", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___17___mlp_fc1_bias[name=p_getattr_l__self___trunk_blocks___17___mlp_fc1_bias]. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature FxOnnxInterpreter.run_node\n- self: \n- node: fx.Node(p_getattr_l__self___trunk_blocks___17___mlp_fc1_bias)[placeholder]:Tensor(f32[4096])\n- fx_graph_module: torch.fx.GraphModule(torch_nn_modules_container_Sequential)\n- onnxfunction_dispatcher: \n- op_level_debug: False\n- onnxscript_graph: \n- onnxscript_tracer: \n- fx_name_to_onnxscript_value: Dict[length=214](\nclone: `TorchScriptTensor(f32[4, 1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_weight: `TorchScriptTensor(f32[3072, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_bias: `TorchScriptTensor(f32[3072])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_weight: `TorchScriptTensor(f32[1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm2_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm2_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___mlp_fc1_weight: `TorchScriptTensor(f32[4096, 1024])`,\n...\n)\n## Return values\n", + "text":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___17___mlp_fc1_bias[name=p_getattr_l__self___trunk_blocks___17___mlp_fc1_bias]. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"FxOnnxInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":414 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0008", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___17___mlp_fc2_weight[name=p_getattr_l__self___trunk_blocks___17___mlp_fc2_weight]. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature FxOnnxInterpreter.run_node\n- self: \n- node: fx.Node(p_getattr_l__self___trunk_blocks___17___mlp_fc2_weight)[placeholder]:Tensor(f32[1024, 4096])\n- fx_graph_module: torch.fx.GraphModule(torch_nn_modules_container_Sequential)\n- onnxfunction_dispatcher: \n- op_level_debug: False\n- onnxscript_graph: \n- onnxscript_tracer: \n- fx_name_to_onnxscript_value: Dict[length=215](\nclone: `TorchScriptTensor(f32[4, 1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_weight: `TorchScriptTensor(f32[3072, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_bias: `TorchScriptTensor(f32[3072])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_weight: `TorchScriptTensor(f32[1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm2_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm2_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___mlp_fc1_weight: `TorchScriptTensor(f32[4096, 1024])`,\n...\n)\n## Return values\n", + "text":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___17___mlp_fc2_weight[name=p_getattr_l__self___trunk_blocks___17___mlp_fc2_weight]. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"FxOnnxInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":414 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0008", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___17___mlp_fc2_bias[name=p_getattr_l__self___trunk_blocks___17___mlp_fc2_bias]. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature FxOnnxInterpreter.run_node\n- self: \n- node: fx.Node(p_getattr_l__self___trunk_blocks___17___mlp_fc2_bias)[placeholder]:Tensor(f32[1024])\n- fx_graph_module: torch.fx.GraphModule(torch_nn_modules_container_Sequential)\n- onnxfunction_dispatcher: \n- op_level_debug: False\n- onnxscript_graph: \n- onnxscript_tracer: \n- fx_name_to_onnxscript_value: Dict[length=216](\nclone: `TorchScriptTensor(f32[4, 1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_weight: `TorchScriptTensor(f32[3072, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_bias: `TorchScriptTensor(f32[3072])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_weight: `TorchScriptTensor(f32[1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm2_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm2_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___mlp_fc1_weight: `TorchScriptTensor(f32[4096, 1024])`,\n...\n)\n## Return values\n", + "text":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___17___mlp_fc2_bias[name=p_getattr_l__self___trunk_blocks___17___mlp_fc2_bias]. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"FxOnnxInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":414 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0008", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___18___norm1_weight[name=p_getattr_l__self___trunk_blocks___18___norm1_weight]. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature FxOnnxInterpreter.run_node\n- self: \n- node: fx.Node(p_getattr_l__self___trunk_blocks___18___norm1_weight)[placeholder]:Tensor(f32[1024])\n- fx_graph_module: torch.fx.GraphModule(torch_nn_modules_container_Sequential)\n- onnxfunction_dispatcher: \n- op_level_debug: False\n- onnxscript_graph: \n- onnxscript_tracer: \n- fx_name_to_onnxscript_value: Dict[length=217](\nclone: `TorchScriptTensor(f32[4, 1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_weight: `TorchScriptTensor(f32[3072, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_bias: `TorchScriptTensor(f32[3072])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_weight: `TorchScriptTensor(f32[1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm2_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm2_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___mlp_fc1_weight: `TorchScriptTensor(f32[4096, 1024])`,\n...\n)\n## Return values\n", + "text":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___18___norm1_weight[name=p_getattr_l__self___trunk_blocks___18___norm1_weight]. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"FxOnnxInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":414 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0008", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___18___norm1_bias[name=p_getattr_l__self___trunk_blocks___18___norm1_bias]. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature FxOnnxInterpreter.run_node\n- self: \n- node: fx.Node(p_getattr_l__self___trunk_blocks___18___norm1_bias)[placeholder]:Tensor(f32[1024])\n- fx_graph_module: torch.fx.GraphModule(torch_nn_modules_container_Sequential)\n- onnxfunction_dispatcher: \n- op_level_debug: False\n- onnxscript_graph: \n- onnxscript_tracer: \n- fx_name_to_onnxscript_value: Dict[length=218](\nclone: `TorchScriptTensor(f32[4, 1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_weight: `TorchScriptTensor(f32[3072, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_bias: `TorchScriptTensor(f32[3072])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_weight: `TorchScriptTensor(f32[1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm2_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm2_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___mlp_fc1_weight: `TorchScriptTensor(f32[4096, 1024])`,\n...\n)\n## Return values\n", + "text":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___18___norm1_bias[name=p_getattr_l__self___trunk_blocks___18___norm1_bias]. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"FxOnnxInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":414 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0008", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___18___attn_qkv_weight[name=p_getattr_l__self___trunk_blocks___18___attn_qkv_weight]. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature FxOnnxInterpreter.run_node\n- self: \n- node: fx.Node(p_getattr_l__self___trunk_blocks___18___attn_qkv_weight)[placeholder]:Tensor(f32[3072, 1024])\n- fx_graph_module: torch.fx.GraphModule(torch_nn_modules_container_Sequential)\n- onnxfunction_dispatcher: \n- op_level_debug: False\n- onnxscript_graph: \n- onnxscript_tracer: \n- fx_name_to_onnxscript_value: Dict[length=219](\nclone: `TorchScriptTensor(f32[4, 1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_weight: `TorchScriptTensor(f32[3072, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_bias: `TorchScriptTensor(f32[3072])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_weight: `TorchScriptTensor(f32[1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm2_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm2_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___mlp_fc1_weight: `TorchScriptTensor(f32[4096, 1024])`,\n...\n)\n## Return values\n", + "text":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___18___attn_qkv_weight[name=p_getattr_l__self___trunk_blocks___18___attn_qkv_weight]. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"FxOnnxInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":414 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0008", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___18___attn_qkv_bias[name=p_getattr_l__self___trunk_blocks___18___attn_qkv_bias]. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature FxOnnxInterpreter.run_node\n- self: \n- node: fx.Node(p_getattr_l__self___trunk_blocks___18___attn_qkv_bias)[placeholder]:Tensor(f32[3072])\n- fx_graph_module: torch.fx.GraphModule(torch_nn_modules_container_Sequential)\n- onnxfunction_dispatcher: \n- op_level_debug: False\n- onnxscript_graph: \n- onnxscript_tracer: \n- fx_name_to_onnxscript_value: Dict[length=220](\nclone: `TorchScriptTensor(f32[4, 1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_weight: `TorchScriptTensor(f32[3072, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_bias: `TorchScriptTensor(f32[3072])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_weight: `TorchScriptTensor(f32[1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm2_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm2_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___mlp_fc1_weight: `TorchScriptTensor(f32[4096, 1024])`,\n...\n)\n## Return values\n", + "text":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___18___attn_qkv_bias[name=p_getattr_l__self___trunk_blocks___18___attn_qkv_bias]. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"FxOnnxInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":414 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0008", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___18___attn_proj_weight[name=p_getattr_l__self___trunk_blocks___18___attn_proj_weight]. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature FxOnnxInterpreter.run_node\n- self: \n- node: fx.Node(p_getattr_l__self___trunk_blocks___18___attn_proj_weight)[placeholder]:Tensor(f32[1024, 1024])\n- fx_graph_module: torch.fx.GraphModule(torch_nn_modules_container_Sequential)\n- onnxfunction_dispatcher: \n- op_level_debug: False\n- onnxscript_graph: \n- onnxscript_tracer: \n- fx_name_to_onnxscript_value: Dict[length=221](\nclone: `TorchScriptTensor(f32[4, 1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_weight: `TorchScriptTensor(f32[3072, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_bias: `TorchScriptTensor(f32[3072])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_weight: `TorchScriptTensor(f32[1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm2_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm2_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___mlp_fc1_weight: `TorchScriptTensor(f32[4096, 1024])`,\n...\n)\n## Return values\n", + "text":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___18___attn_proj_weight[name=p_getattr_l__self___trunk_blocks___18___attn_proj_weight]. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"FxOnnxInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":414 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0008", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___18___attn_proj_bias[name=p_getattr_l__self___trunk_blocks___18___attn_proj_bias]. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature FxOnnxInterpreter.run_node\n- self: \n- node: fx.Node(p_getattr_l__self___trunk_blocks___18___attn_proj_bias)[placeholder]:Tensor(f32[1024])\n- fx_graph_module: torch.fx.GraphModule(torch_nn_modules_container_Sequential)\n- onnxfunction_dispatcher: \n- op_level_debug: False\n- onnxscript_graph: \n- onnxscript_tracer: \n- fx_name_to_onnxscript_value: Dict[length=222](\nclone: `TorchScriptTensor(f32[4, 1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_weight: `TorchScriptTensor(f32[3072, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_bias: `TorchScriptTensor(f32[3072])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_weight: `TorchScriptTensor(f32[1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm2_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm2_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___mlp_fc1_weight: `TorchScriptTensor(f32[4096, 1024])`,\n...\n)\n## Return values\n", + "text":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___18___attn_proj_bias[name=p_getattr_l__self___trunk_blocks___18___attn_proj_bias]. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"FxOnnxInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":414 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0008", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___18___norm2_weight[name=p_getattr_l__self___trunk_blocks___18___norm2_weight]. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature FxOnnxInterpreter.run_node\n- self: \n- node: fx.Node(p_getattr_l__self___trunk_blocks___18___norm2_weight)[placeholder]:Tensor(f32[1024])\n- fx_graph_module: torch.fx.GraphModule(torch_nn_modules_container_Sequential)\n- onnxfunction_dispatcher: \n- op_level_debug: False\n- onnxscript_graph: \n- onnxscript_tracer: \n- fx_name_to_onnxscript_value: Dict[length=223](\nclone: `TorchScriptTensor(f32[4, 1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_weight: `TorchScriptTensor(f32[3072, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_bias: `TorchScriptTensor(f32[3072])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_weight: `TorchScriptTensor(f32[1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm2_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm2_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___mlp_fc1_weight: `TorchScriptTensor(f32[4096, 1024])`,\n...\n)\n## Return values\n", + "text":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___18___norm2_weight[name=p_getattr_l__self___trunk_blocks___18___norm2_weight]. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"FxOnnxInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":414 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0008", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___18___norm2_bias[name=p_getattr_l__self___trunk_blocks___18___norm2_bias]. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature FxOnnxInterpreter.run_node\n- self: \n- node: fx.Node(p_getattr_l__self___trunk_blocks___18___norm2_bias)[placeholder]:Tensor(f32[1024])\n- fx_graph_module: torch.fx.GraphModule(torch_nn_modules_container_Sequential)\n- onnxfunction_dispatcher: \n- op_level_debug: False\n- onnxscript_graph: \n- onnxscript_tracer: \n- fx_name_to_onnxscript_value: Dict[length=224](\nclone: `TorchScriptTensor(f32[4, 1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_weight: `TorchScriptTensor(f32[3072, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_bias: `TorchScriptTensor(f32[3072])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_weight: `TorchScriptTensor(f32[1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm2_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm2_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___mlp_fc1_weight: `TorchScriptTensor(f32[4096, 1024])`,\n...\n)\n## Return values\n", + "text":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___18___norm2_bias[name=p_getattr_l__self___trunk_blocks___18___norm2_bias]. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"FxOnnxInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":414 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0008", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___18___mlp_fc1_weight[name=p_getattr_l__self___trunk_blocks___18___mlp_fc1_weight]. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature FxOnnxInterpreter.run_node\n- self: \n- node: fx.Node(p_getattr_l__self___trunk_blocks___18___mlp_fc1_weight)[placeholder]:Tensor(f32[4096, 1024])\n- fx_graph_module: torch.fx.GraphModule(torch_nn_modules_container_Sequential)\n- onnxfunction_dispatcher: \n- op_level_debug: False\n- onnxscript_graph: \n- onnxscript_tracer: \n- fx_name_to_onnxscript_value: Dict[length=225](\nclone: `TorchScriptTensor(f32[4, 1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_weight: `TorchScriptTensor(f32[3072, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_bias: `TorchScriptTensor(f32[3072])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_weight: `TorchScriptTensor(f32[1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm2_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm2_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___mlp_fc1_weight: `TorchScriptTensor(f32[4096, 1024])`,\n...\n)\n## Return values\n", + "text":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___18___mlp_fc1_weight[name=p_getattr_l__self___trunk_blocks___18___mlp_fc1_weight]. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"FxOnnxInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":414 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0008", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___18___mlp_fc1_bias[name=p_getattr_l__self___trunk_blocks___18___mlp_fc1_bias]. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature FxOnnxInterpreter.run_node\n- self: \n- node: fx.Node(p_getattr_l__self___trunk_blocks___18___mlp_fc1_bias)[placeholder]:Tensor(f32[4096])\n- fx_graph_module: torch.fx.GraphModule(torch_nn_modules_container_Sequential)\n- onnxfunction_dispatcher: \n- op_level_debug: False\n- onnxscript_graph: \n- onnxscript_tracer: \n- fx_name_to_onnxscript_value: Dict[length=226](\nclone: `TorchScriptTensor(f32[4, 1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_weight: `TorchScriptTensor(f32[3072, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_bias: `TorchScriptTensor(f32[3072])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_weight: `TorchScriptTensor(f32[1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm2_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm2_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___mlp_fc1_weight: `TorchScriptTensor(f32[4096, 1024])`,\n...\n)\n## Return values\n", + "text":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___18___mlp_fc1_bias[name=p_getattr_l__self___trunk_blocks___18___mlp_fc1_bias]. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"FxOnnxInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":414 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0008", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___18___mlp_fc2_weight[name=p_getattr_l__self___trunk_blocks___18___mlp_fc2_weight]. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature FxOnnxInterpreter.run_node\n- self: \n- node: fx.Node(p_getattr_l__self___trunk_blocks___18___mlp_fc2_weight)[placeholder]:Tensor(f32[1024, 4096])\n- fx_graph_module: torch.fx.GraphModule(torch_nn_modules_container_Sequential)\n- onnxfunction_dispatcher: \n- op_level_debug: False\n- onnxscript_graph: \n- onnxscript_tracer: \n- fx_name_to_onnxscript_value: Dict[length=227](\nclone: `TorchScriptTensor(f32[4, 1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_weight: `TorchScriptTensor(f32[3072, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_bias: `TorchScriptTensor(f32[3072])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_weight: `TorchScriptTensor(f32[1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm2_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm2_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___mlp_fc1_weight: `TorchScriptTensor(f32[4096, 1024])`,\n...\n)\n## Return values\n", + "text":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___18___mlp_fc2_weight[name=p_getattr_l__self___trunk_blocks___18___mlp_fc2_weight]. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"FxOnnxInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":414 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0008", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___18___mlp_fc2_bias[name=p_getattr_l__self___trunk_blocks___18___mlp_fc2_bias]. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature FxOnnxInterpreter.run_node\n- self: \n- node: fx.Node(p_getattr_l__self___trunk_blocks___18___mlp_fc2_bias)[placeholder]:Tensor(f32[1024])\n- fx_graph_module: torch.fx.GraphModule(torch_nn_modules_container_Sequential)\n- onnxfunction_dispatcher: \n- op_level_debug: False\n- onnxscript_graph: \n- onnxscript_tracer: \n- fx_name_to_onnxscript_value: Dict[length=228](\nclone: `TorchScriptTensor(f32[4, 1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_weight: `TorchScriptTensor(f32[3072, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_bias: `TorchScriptTensor(f32[3072])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_weight: `TorchScriptTensor(f32[1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm2_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm2_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___mlp_fc1_weight: `TorchScriptTensor(f32[4096, 1024])`,\n...\n)\n## Return values\n", + "text":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___18___mlp_fc2_bias[name=p_getattr_l__self___trunk_blocks___18___mlp_fc2_bias]. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"FxOnnxInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":414 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0008", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___19___norm1_weight[name=p_getattr_l__self___trunk_blocks___19___norm1_weight]. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature FxOnnxInterpreter.run_node\n- self: \n- node: fx.Node(p_getattr_l__self___trunk_blocks___19___norm1_weight)[placeholder]:Tensor(f32[1024])\n- fx_graph_module: torch.fx.GraphModule(torch_nn_modules_container_Sequential)\n- onnxfunction_dispatcher: \n- op_level_debug: False\n- onnxscript_graph: \n- onnxscript_tracer: \n- fx_name_to_onnxscript_value: Dict[length=229](\nclone: `TorchScriptTensor(f32[4, 1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_weight: `TorchScriptTensor(f32[3072, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_bias: `TorchScriptTensor(f32[3072])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_weight: `TorchScriptTensor(f32[1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm2_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm2_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___mlp_fc1_weight: `TorchScriptTensor(f32[4096, 1024])`,\n...\n)\n## Return values\n", + "text":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___19___norm1_weight[name=p_getattr_l__self___trunk_blocks___19___norm1_weight]. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"FxOnnxInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":414 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0008", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___19___norm1_bias[name=p_getattr_l__self___trunk_blocks___19___norm1_bias]. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature FxOnnxInterpreter.run_node\n- self: \n- node: fx.Node(p_getattr_l__self___trunk_blocks___19___norm1_bias)[placeholder]:Tensor(f32[1024])\n- fx_graph_module: torch.fx.GraphModule(torch_nn_modules_container_Sequential)\n- onnxfunction_dispatcher: \n- op_level_debug: False\n- onnxscript_graph: \n- onnxscript_tracer: \n- fx_name_to_onnxscript_value: Dict[length=230](\nclone: `TorchScriptTensor(f32[4, 1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_weight: `TorchScriptTensor(f32[3072, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_bias: `TorchScriptTensor(f32[3072])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_weight: `TorchScriptTensor(f32[1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm2_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm2_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___mlp_fc1_weight: `TorchScriptTensor(f32[4096, 1024])`,\n...\n)\n## Return values\n", + "text":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___19___norm1_bias[name=p_getattr_l__self___trunk_blocks___19___norm1_bias]. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"FxOnnxInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":414 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0008", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___19___attn_qkv_weight[name=p_getattr_l__self___trunk_blocks___19___attn_qkv_weight]. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature FxOnnxInterpreter.run_node\n- self: \n- node: fx.Node(p_getattr_l__self___trunk_blocks___19___attn_qkv_weight)[placeholder]:Tensor(f32[3072, 1024])\n- fx_graph_module: torch.fx.GraphModule(torch_nn_modules_container_Sequential)\n- onnxfunction_dispatcher: \n- op_level_debug: False\n- onnxscript_graph: \n- onnxscript_tracer: \n- fx_name_to_onnxscript_value: Dict[length=231](\nclone: `TorchScriptTensor(f32[4, 1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_weight: `TorchScriptTensor(f32[3072, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_bias: `TorchScriptTensor(f32[3072])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_weight: `TorchScriptTensor(f32[1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm2_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm2_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___mlp_fc1_weight: `TorchScriptTensor(f32[4096, 1024])`,\n...\n)\n## Return values\n", + "text":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___19___attn_qkv_weight[name=p_getattr_l__self___trunk_blocks___19___attn_qkv_weight]. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"FxOnnxInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":414 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0008", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___19___attn_qkv_bias[name=p_getattr_l__self___trunk_blocks___19___attn_qkv_bias]. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature FxOnnxInterpreter.run_node\n- self: \n- node: fx.Node(p_getattr_l__self___trunk_blocks___19___attn_qkv_bias)[placeholder]:Tensor(f32[3072])\n- fx_graph_module: torch.fx.GraphModule(torch_nn_modules_container_Sequential)\n- onnxfunction_dispatcher: \n- op_level_debug: False\n- onnxscript_graph: \n- onnxscript_tracer: \n- fx_name_to_onnxscript_value: Dict[length=232](\nclone: `TorchScriptTensor(f32[4, 1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_weight: `TorchScriptTensor(f32[3072, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_bias: `TorchScriptTensor(f32[3072])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_weight: `TorchScriptTensor(f32[1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm2_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm2_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___mlp_fc1_weight: `TorchScriptTensor(f32[4096, 1024])`,\n...\n)\n## Return values\n", + "text":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___19___attn_qkv_bias[name=p_getattr_l__self___trunk_blocks___19___attn_qkv_bias]. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"FxOnnxInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":414 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0008", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___19___attn_proj_weight[name=p_getattr_l__self___trunk_blocks___19___attn_proj_weight]. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature FxOnnxInterpreter.run_node\n- self: \n- node: fx.Node(p_getattr_l__self___trunk_blocks___19___attn_proj_weight)[placeholder]:Tensor(f32[1024, 1024])\n- fx_graph_module: torch.fx.GraphModule(torch_nn_modules_container_Sequential)\n- onnxfunction_dispatcher: \n- op_level_debug: False\n- onnxscript_graph: \n- onnxscript_tracer: \n- fx_name_to_onnxscript_value: Dict[length=233](\nclone: `TorchScriptTensor(f32[4, 1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_weight: `TorchScriptTensor(f32[3072, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_bias: `TorchScriptTensor(f32[3072])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_weight: `TorchScriptTensor(f32[1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm2_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm2_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___mlp_fc1_weight: `TorchScriptTensor(f32[4096, 1024])`,\n...\n)\n## Return values\n", + "text":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___19___attn_proj_weight[name=p_getattr_l__self___trunk_blocks___19___attn_proj_weight]. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"FxOnnxInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":414 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0008", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___19___attn_proj_bias[name=p_getattr_l__self___trunk_blocks___19___attn_proj_bias]. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature FxOnnxInterpreter.run_node\n- self: \n- node: fx.Node(p_getattr_l__self___trunk_blocks___19___attn_proj_bias)[placeholder]:Tensor(f32[1024])\n- fx_graph_module: torch.fx.GraphModule(torch_nn_modules_container_Sequential)\n- onnxfunction_dispatcher: \n- op_level_debug: False\n- onnxscript_graph: \n- onnxscript_tracer: \n- fx_name_to_onnxscript_value: Dict[length=234](\nclone: `TorchScriptTensor(f32[4, 1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_weight: `TorchScriptTensor(f32[3072, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_bias: `TorchScriptTensor(f32[3072])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_weight: `TorchScriptTensor(f32[1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm2_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm2_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___mlp_fc1_weight: `TorchScriptTensor(f32[4096, 1024])`,\n...\n)\n## Return values\n", + "text":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___19___attn_proj_bias[name=p_getattr_l__self___trunk_blocks___19___attn_proj_bias]. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"FxOnnxInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":414 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0008", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___19___norm2_weight[name=p_getattr_l__self___trunk_blocks___19___norm2_weight]. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature FxOnnxInterpreter.run_node\n- self: \n- node: fx.Node(p_getattr_l__self___trunk_blocks___19___norm2_weight)[placeholder]:Tensor(f32[1024])\n- fx_graph_module: torch.fx.GraphModule(torch_nn_modules_container_Sequential)\n- onnxfunction_dispatcher: \n- op_level_debug: False\n- onnxscript_graph: \n- onnxscript_tracer: \n- fx_name_to_onnxscript_value: Dict[length=235](\nclone: `TorchScriptTensor(f32[4, 1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_weight: `TorchScriptTensor(f32[3072, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_bias: `TorchScriptTensor(f32[3072])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_weight: `TorchScriptTensor(f32[1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm2_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm2_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___mlp_fc1_weight: `TorchScriptTensor(f32[4096, 1024])`,\n...\n)\n## Return values\n", + "text":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___19___norm2_weight[name=p_getattr_l__self___trunk_blocks___19___norm2_weight]. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"FxOnnxInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":414 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0008", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___19___norm2_bias[name=p_getattr_l__self___trunk_blocks___19___norm2_bias]. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature FxOnnxInterpreter.run_node\n- self: \n- node: fx.Node(p_getattr_l__self___trunk_blocks___19___norm2_bias)[placeholder]:Tensor(f32[1024])\n- fx_graph_module: torch.fx.GraphModule(torch_nn_modules_container_Sequential)\n- onnxfunction_dispatcher: \n- op_level_debug: False\n- onnxscript_graph: \n- onnxscript_tracer: \n- fx_name_to_onnxscript_value: Dict[length=236](\nclone: `TorchScriptTensor(f32[4, 1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_weight: `TorchScriptTensor(f32[3072, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_bias: `TorchScriptTensor(f32[3072])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_weight: `TorchScriptTensor(f32[1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm2_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm2_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___mlp_fc1_weight: `TorchScriptTensor(f32[4096, 1024])`,\n...\n)\n## Return values\n", + "text":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___19___norm2_bias[name=p_getattr_l__self___trunk_blocks___19___norm2_bias]. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"FxOnnxInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":414 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0008", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___19___mlp_fc1_weight[name=p_getattr_l__self___trunk_blocks___19___mlp_fc1_weight]. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature FxOnnxInterpreter.run_node\n- self: \n- node: fx.Node(p_getattr_l__self___trunk_blocks___19___mlp_fc1_weight)[placeholder]:Tensor(f32[4096, 1024])\n- fx_graph_module: torch.fx.GraphModule(torch_nn_modules_container_Sequential)\n- onnxfunction_dispatcher: \n- op_level_debug: False\n- onnxscript_graph: \n- onnxscript_tracer: \n- fx_name_to_onnxscript_value: Dict[length=237](\nclone: `TorchScriptTensor(f32[4, 1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_weight: `TorchScriptTensor(f32[3072, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_bias: `TorchScriptTensor(f32[3072])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_weight: `TorchScriptTensor(f32[1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm2_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm2_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___mlp_fc1_weight: `TorchScriptTensor(f32[4096, 1024])`,\n...\n)\n## Return values\n", + "text":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___19___mlp_fc1_weight[name=p_getattr_l__self___trunk_blocks___19___mlp_fc1_weight]. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"FxOnnxInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":414 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0008", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___19___mlp_fc1_bias[name=p_getattr_l__self___trunk_blocks___19___mlp_fc1_bias]. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature FxOnnxInterpreter.run_node\n- self: \n- node: fx.Node(p_getattr_l__self___trunk_blocks___19___mlp_fc1_bias)[placeholder]:Tensor(f32[4096])\n- fx_graph_module: torch.fx.GraphModule(torch_nn_modules_container_Sequential)\n- onnxfunction_dispatcher: \n- op_level_debug: False\n- onnxscript_graph: \n- onnxscript_tracer: \n- fx_name_to_onnxscript_value: Dict[length=238](\nclone: `TorchScriptTensor(f32[4, 1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_weight: `TorchScriptTensor(f32[3072, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_bias: `TorchScriptTensor(f32[3072])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_weight: `TorchScriptTensor(f32[1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm2_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm2_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___mlp_fc1_weight: `TorchScriptTensor(f32[4096, 1024])`,\n...\n)\n## Return values\n", + "text":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___19___mlp_fc1_bias[name=p_getattr_l__self___trunk_blocks___19___mlp_fc1_bias]. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"FxOnnxInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":414 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0008", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___19___mlp_fc2_weight[name=p_getattr_l__self___trunk_blocks___19___mlp_fc2_weight]. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature FxOnnxInterpreter.run_node\n- self: \n- node: fx.Node(p_getattr_l__self___trunk_blocks___19___mlp_fc2_weight)[placeholder]:Tensor(f32[1024, 4096])\n- fx_graph_module: torch.fx.GraphModule(torch_nn_modules_container_Sequential)\n- onnxfunction_dispatcher: \n- op_level_debug: False\n- onnxscript_graph: \n- onnxscript_tracer: \n- fx_name_to_onnxscript_value: Dict[length=239](\nclone: `TorchScriptTensor(f32[4, 1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_weight: `TorchScriptTensor(f32[3072, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_bias: `TorchScriptTensor(f32[3072])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_weight: `TorchScriptTensor(f32[1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm2_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm2_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___mlp_fc1_weight: `TorchScriptTensor(f32[4096, 1024])`,\n...\n)\n## Return values\n", + "text":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___19___mlp_fc2_weight[name=p_getattr_l__self___trunk_blocks___19___mlp_fc2_weight]. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"FxOnnxInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":414 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0008", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___19___mlp_fc2_bias[name=p_getattr_l__self___trunk_blocks___19___mlp_fc2_bias]. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature FxOnnxInterpreter.run_node\n- self: \n- node: fx.Node(p_getattr_l__self___trunk_blocks___19___mlp_fc2_bias)[placeholder]:Tensor(f32[1024])\n- fx_graph_module: torch.fx.GraphModule(torch_nn_modules_container_Sequential)\n- onnxfunction_dispatcher: \n- op_level_debug: False\n- onnxscript_graph: \n- onnxscript_tracer: \n- fx_name_to_onnxscript_value: Dict[length=240](\nclone: `TorchScriptTensor(f32[4, 1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_weight: `TorchScriptTensor(f32[3072, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_bias: `TorchScriptTensor(f32[3072])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_weight: `TorchScriptTensor(f32[1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm2_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm2_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___mlp_fc1_weight: `TorchScriptTensor(f32[4096, 1024])`,\n...\n)\n## Return values\n", + "text":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___19___mlp_fc2_bias[name=p_getattr_l__self___trunk_blocks___19___mlp_fc2_bias]. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"FxOnnxInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":414 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0008", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___20___norm1_weight[name=p_getattr_l__self___trunk_blocks___20___norm1_weight]. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature FxOnnxInterpreter.run_node\n- self: \n- node: fx.Node(p_getattr_l__self___trunk_blocks___20___norm1_weight)[placeholder]:Tensor(f32[1024])\n- fx_graph_module: torch.fx.GraphModule(torch_nn_modules_container_Sequential)\n- onnxfunction_dispatcher: \n- op_level_debug: False\n- onnxscript_graph: \n- onnxscript_tracer: \n- fx_name_to_onnxscript_value: Dict[length=241](\nclone: `TorchScriptTensor(f32[4, 1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_weight: `TorchScriptTensor(f32[3072, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_bias: `TorchScriptTensor(f32[3072])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_weight: `TorchScriptTensor(f32[1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm2_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm2_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___mlp_fc1_weight: `TorchScriptTensor(f32[4096, 1024])`,\n...\n)\n## Return values\n", + "text":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___20___norm1_weight[name=p_getattr_l__self___trunk_blocks___20___norm1_weight]. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"FxOnnxInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":414 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0008", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___20___norm1_bias[name=p_getattr_l__self___trunk_blocks___20___norm1_bias]. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature FxOnnxInterpreter.run_node\n- self: \n- node: fx.Node(p_getattr_l__self___trunk_blocks___20___norm1_bias)[placeholder]:Tensor(f32[1024])\n- fx_graph_module: torch.fx.GraphModule(torch_nn_modules_container_Sequential)\n- onnxfunction_dispatcher: \n- op_level_debug: False\n- onnxscript_graph: \n- onnxscript_tracer: \n- fx_name_to_onnxscript_value: Dict[length=242](\nclone: `TorchScriptTensor(f32[4, 1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_weight: `TorchScriptTensor(f32[3072, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_bias: `TorchScriptTensor(f32[3072])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_weight: `TorchScriptTensor(f32[1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm2_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm2_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___mlp_fc1_weight: `TorchScriptTensor(f32[4096, 1024])`,\n...\n)\n## Return values\n", + "text":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___20___norm1_bias[name=p_getattr_l__self___trunk_blocks___20___norm1_bias]. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"FxOnnxInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":414 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0008", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___20___attn_qkv_weight[name=p_getattr_l__self___trunk_blocks___20___attn_qkv_weight]. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature FxOnnxInterpreter.run_node\n- self: \n- node: fx.Node(p_getattr_l__self___trunk_blocks___20___attn_qkv_weight)[placeholder]:Tensor(f32[3072, 1024])\n- fx_graph_module: torch.fx.GraphModule(torch_nn_modules_container_Sequential)\n- onnxfunction_dispatcher: \n- op_level_debug: False\n- onnxscript_graph: \n- onnxscript_tracer: \n- fx_name_to_onnxscript_value: Dict[length=243](\nclone: `TorchScriptTensor(f32[4, 1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_weight: `TorchScriptTensor(f32[3072, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_bias: `TorchScriptTensor(f32[3072])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_weight: `TorchScriptTensor(f32[1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm2_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm2_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___mlp_fc1_weight: `TorchScriptTensor(f32[4096, 1024])`,\n...\n)\n## Return values\n", + "text":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___20___attn_qkv_weight[name=p_getattr_l__self___trunk_blocks___20___attn_qkv_weight]. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"FxOnnxInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":414 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0008", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___20___attn_qkv_bias[name=p_getattr_l__self___trunk_blocks___20___attn_qkv_bias]. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature FxOnnxInterpreter.run_node\n- self: \n- node: fx.Node(p_getattr_l__self___trunk_blocks___20___attn_qkv_bias)[placeholder]:Tensor(f32[3072])\n- fx_graph_module: torch.fx.GraphModule(torch_nn_modules_container_Sequential)\n- onnxfunction_dispatcher: \n- op_level_debug: False\n- onnxscript_graph: \n- onnxscript_tracer: \n- fx_name_to_onnxscript_value: Dict[length=244](\nclone: `TorchScriptTensor(f32[4, 1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_weight: `TorchScriptTensor(f32[3072, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_bias: `TorchScriptTensor(f32[3072])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_weight: `TorchScriptTensor(f32[1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm2_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm2_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___mlp_fc1_weight: `TorchScriptTensor(f32[4096, 1024])`,\n...\n)\n## Return values\n", + "text":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___20___attn_qkv_bias[name=p_getattr_l__self___trunk_blocks___20___attn_qkv_bias]. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"FxOnnxInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":414 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0008", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___20___attn_proj_weight[name=p_getattr_l__self___trunk_blocks___20___attn_proj_weight]. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature FxOnnxInterpreter.run_node\n- self: \n- node: fx.Node(p_getattr_l__self___trunk_blocks___20___attn_proj_weight)[placeholder]:Tensor(f32[1024, 1024])\n- fx_graph_module: torch.fx.GraphModule(torch_nn_modules_container_Sequential)\n- onnxfunction_dispatcher: \n- op_level_debug: False\n- onnxscript_graph: \n- onnxscript_tracer: \n- fx_name_to_onnxscript_value: Dict[length=245](\nclone: `TorchScriptTensor(f32[4, 1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_weight: `TorchScriptTensor(f32[3072, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_bias: `TorchScriptTensor(f32[3072])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_weight: `TorchScriptTensor(f32[1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm2_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm2_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___mlp_fc1_weight: `TorchScriptTensor(f32[4096, 1024])`,\n...\n)\n## Return values\n", + "text":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___20___attn_proj_weight[name=p_getattr_l__self___trunk_blocks___20___attn_proj_weight]. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"FxOnnxInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":414 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0008", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___20___attn_proj_bias[name=p_getattr_l__self___trunk_blocks___20___attn_proj_bias]. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature FxOnnxInterpreter.run_node\n- self: \n- node: fx.Node(p_getattr_l__self___trunk_blocks___20___attn_proj_bias)[placeholder]:Tensor(f32[1024])\n- fx_graph_module: torch.fx.GraphModule(torch_nn_modules_container_Sequential)\n- onnxfunction_dispatcher: \n- op_level_debug: False\n- onnxscript_graph: \n- onnxscript_tracer: \n- fx_name_to_onnxscript_value: Dict[length=246](\nclone: `TorchScriptTensor(f32[4, 1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_weight: `TorchScriptTensor(f32[3072, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_bias: `TorchScriptTensor(f32[3072])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_weight: `TorchScriptTensor(f32[1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm2_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm2_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___mlp_fc1_weight: `TorchScriptTensor(f32[4096, 1024])`,\n...\n)\n## Return values\n", + "text":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___20___attn_proj_bias[name=p_getattr_l__self___trunk_blocks___20___attn_proj_bias]. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"FxOnnxInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":414 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0008", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___20___norm2_weight[name=p_getattr_l__self___trunk_blocks___20___norm2_weight]. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature FxOnnxInterpreter.run_node\n- self: \n- node: fx.Node(p_getattr_l__self___trunk_blocks___20___norm2_weight)[placeholder]:Tensor(f32[1024])\n- fx_graph_module: torch.fx.GraphModule(torch_nn_modules_container_Sequential)\n- onnxfunction_dispatcher: \n- op_level_debug: False\n- onnxscript_graph: \n- onnxscript_tracer: \n- fx_name_to_onnxscript_value: Dict[length=247](\nclone: `TorchScriptTensor(f32[4, 1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_weight: `TorchScriptTensor(f32[3072, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_bias: `TorchScriptTensor(f32[3072])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_weight: `TorchScriptTensor(f32[1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm2_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm2_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___mlp_fc1_weight: `TorchScriptTensor(f32[4096, 1024])`,\n...\n)\n## Return values\n", + "text":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___20___norm2_weight[name=p_getattr_l__self___trunk_blocks___20___norm2_weight]. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"FxOnnxInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":414 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0008", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___20___norm2_bias[name=p_getattr_l__self___trunk_blocks___20___norm2_bias]. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature FxOnnxInterpreter.run_node\n- self: \n- node: fx.Node(p_getattr_l__self___trunk_blocks___20___norm2_bias)[placeholder]:Tensor(f32[1024])\n- fx_graph_module: torch.fx.GraphModule(torch_nn_modules_container_Sequential)\n- onnxfunction_dispatcher: \n- op_level_debug: False\n- onnxscript_graph: \n- onnxscript_tracer: \n- fx_name_to_onnxscript_value: Dict[length=248](\nclone: `TorchScriptTensor(f32[4, 1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_weight: `TorchScriptTensor(f32[3072, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_bias: `TorchScriptTensor(f32[3072])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_weight: `TorchScriptTensor(f32[1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm2_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm2_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___mlp_fc1_weight: `TorchScriptTensor(f32[4096, 1024])`,\n...\n)\n## Return values\n", + "text":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___20___norm2_bias[name=p_getattr_l__self___trunk_blocks___20___norm2_bias]. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"FxOnnxInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":414 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0008", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___20___mlp_fc1_weight[name=p_getattr_l__self___trunk_blocks___20___mlp_fc1_weight]. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature FxOnnxInterpreter.run_node\n- self: \n- node: fx.Node(p_getattr_l__self___trunk_blocks___20___mlp_fc1_weight)[placeholder]:Tensor(f32[4096, 1024])\n- fx_graph_module: torch.fx.GraphModule(torch_nn_modules_container_Sequential)\n- onnxfunction_dispatcher: \n- op_level_debug: False\n- onnxscript_graph: \n- onnxscript_tracer: \n- fx_name_to_onnxscript_value: Dict[length=249](\nclone: `TorchScriptTensor(f32[4, 1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_weight: `TorchScriptTensor(f32[3072, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_bias: `TorchScriptTensor(f32[3072])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_weight: `TorchScriptTensor(f32[1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm2_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm2_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___mlp_fc1_weight: `TorchScriptTensor(f32[4096, 1024])`,\n...\n)\n## Return values\n", + "text":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___20___mlp_fc1_weight[name=p_getattr_l__self___trunk_blocks___20___mlp_fc1_weight]. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"FxOnnxInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":414 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0008", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___20___mlp_fc1_bias[name=p_getattr_l__self___trunk_blocks___20___mlp_fc1_bias]. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature FxOnnxInterpreter.run_node\n- self: \n- node: fx.Node(p_getattr_l__self___trunk_blocks___20___mlp_fc1_bias)[placeholder]:Tensor(f32[4096])\n- fx_graph_module: torch.fx.GraphModule(torch_nn_modules_container_Sequential)\n- onnxfunction_dispatcher: \n- op_level_debug: False\n- onnxscript_graph: \n- onnxscript_tracer: \n- fx_name_to_onnxscript_value: Dict[length=250](\nclone: `TorchScriptTensor(f32[4, 1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_weight: `TorchScriptTensor(f32[3072, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_bias: `TorchScriptTensor(f32[3072])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_weight: `TorchScriptTensor(f32[1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm2_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm2_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___mlp_fc1_weight: `TorchScriptTensor(f32[4096, 1024])`,\n...\n)\n## Return values\n", + "text":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___20___mlp_fc1_bias[name=p_getattr_l__self___trunk_blocks___20___mlp_fc1_bias]. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"FxOnnxInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":414 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0008", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___20___mlp_fc2_weight[name=p_getattr_l__self___trunk_blocks___20___mlp_fc2_weight]. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature FxOnnxInterpreter.run_node\n- self: \n- node: fx.Node(p_getattr_l__self___trunk_blocks___20___mlp_fc2_weight)[placeholder]:Tensor(f32[1024, 4096])\n- fx_graph_module: torch.fx.GraphModule(torch_nn_modules_container_Sequential)\n- onnxfunction_dispatcher: \n- op_level_debug: False\n- onnxscript_graph: \n- onnxscript_tracer: \n- fx_name_to_onnxscript_value: Dict[length=251](\nclone: `TorchScriptTensor(f32[4, 1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_weight: `TorchScriptTensor(f32[3072, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_bias: `TorchScriptTensor(f32[3072])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_weight: `TorchScriptTensor(f32[1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm2_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm2_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___mlp_fc1_weight: `TorchScriptTensor(f32[4096, 1024])`,\n...\n)\n## Return values\n", + "text":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___20___mlp_fc2_weight[name=p_getattr_l__self___trunk_blocks___20___mlp_fc2_weight]. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"FxOnnxInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":414 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0008", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___20___mlp_fc2_bias[name=p_getattr_l__self___trunk_blocks___20___mlp_fc2_bias]. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature FxOnnxInterpreter.run_node\n- self: \n- node: fx.Node(p_getattr_l__self___trunk_blocks___20___mlp_fc2_bias)[placeholder]:Tensor(f32[1024])\n- fx_graph_module: torch.fx.GraphModule(torch_nn_modules_container_Sequential)\n- onnxfunction_dispatcher: \n- op_level_debug: False\n- onnxscript_graph: \n- onnxscript_tracer: \n- fx_name_to_onnxscript_value: Dict[length=252](\nclone: `TorchScriptTensor(f32[4, 1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_weight: `TorchScriptTensor(f32[3072, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_bias: `TorchScriptTensor(f32[3072])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_weight: `TorchScriptTensor(f32[1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm2_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm2_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___mlp_fc1_weight: `TorchScriptTensor(f32[4096, 1024])`,\n...\n)\n## Return values\n", + "text":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___20___mlp_fc2_bias[name=p_getattr_l__self___trunk_blocks___20___mlp_fc2_bias]. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"FxOnnxInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":414 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0008", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___21___norm1_weight[name=p_getattr_l__self___trunk_blocks___21___norm1_weight]. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature FxOnnxInterpreter.run_node\n- self: \n- node: fx.Node(p_getattr_l__self___trunk_blocks___21___norm1_weight)[placeholder]:Tensor(f32[1024])\n- fx_graph_module: torch.fx.GraphModule(torch_nn_modules_container_Sequential)\n- onnxfunction_dispatcher: \n- op_level_debug: False\n- onnxscript_graph: \n- onnxscript_tracer: \n- fx_name_to_onnxscript_value: Dict[length=253](\nclone: `TorchScriptTensor(f32[4, 1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_weight: `TorchScriptTensor(f32[3072, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_bias: `TorchScriptTensor(f32[3072])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_weight: `TorchScriptTensor(f32[1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm2_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm2_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___mlp_fc1_weight: `TorchScriptTensor(f32[4096, 1024])`,\n...\n)\n## Return values\n", + "text":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___21___norm1_weight[name=p_getattr_l__self___trunk_blocks___21___norm1_weight]. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"FxOnnxInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":414 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0008", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___21___norm1_bias[name=p_getattr_l__self___trunk_blocks___21___norm1_bias]. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature FxOnnxInterpreter.run_node\n- self: \n- node: fx.Node(p_getattr_l__self___trunk_blocks___21___norm1_bias)[placeholder]:Tensor(f32[1024])\n- fx_graph_module: torch.fx.GraphModule(torch_nn_modules_container_Sequential)\n- onnxfunction_dispatcher: \n- op_level_debug: False\n- onnxscript_graph: \n- onnxscript_tracer: \n- fx_name_to_onnxscript_value: Dict[length=254](\nclone: `TorchScriptTensor(f32[4, 1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_weight: `TorchScriptTensor(f32[3072, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_bias: `TorchScriptTensor(f32[3072])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_weight: `TorchScriptTensor(f32[1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm2_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm2_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___mlp_fc1_weight: `TorchScriptTensor(f32[4096, 1024])`,\n...\n)\n## Return values\n", + "text":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___21___norm1_bias[name=p_getattr_l__self___trunk_blocks___21___norm1_bias]. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"FxOnnxInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":414 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0008", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___21___attn_qkv_weight[name=p_getattr_l__self___trunk_blocks___21___attn_qkv_weight]. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature FxOnnxInterpreter.run_node\n- self: \n- node: fx.Node(p_getattr_l__self___trunk_blocks___21___attn_qkv_weight)[placeholder]:Tensor(f32[3072, 1024])\n- fx_graph_module: torch.fx.GraphModule(torch_nn_modules_container_Sequential)\n- onnxfunction_dispatcher: \n- op_level_debug: False\n- onnxscript_graph: \n- onnxscript_tracer: \n- fx_name_to_onnxscript_value: Dict[length=255](\nclone: `TorchScriptTensor(f32[4, 1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_weight: `TorchScriptTensor(f32[3072, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_bias: `TorchScriptTensor(f32[3072])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_weight: `TorchScriptTensor(f32[1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm2_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm2_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___mlp_fc1_weight: `TorchScriptTensor(f32[4096, 1024])`,\n...\n)\n## Return values\n", + "text":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___21___attn_qkv_weight[name=p_getattr_l__self___trunk_blocks___21___attn_qkv_weight]. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"FxOnnxInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":414 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0008", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___21___attn_qkv_bias[name=p_getattr_l__self___trunk_blocks___21___attn_qkv_bias]. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature FxOnnxInterpreter.run_node\n- self: \n- node: fx.Node(p_getattr_l__self___trunk_blocks___21___attn_qkv_bias)[placeholder]:Tensor(f32[3072])\n- fx_graph_module: torch.fx.GraphModule(torch_nn_modules_container_Sequential)\n- onnxfunction_dispatcher: \n- op_level_debug: False\n- onnxscript_graph: \n- onnxscript_tracer: \n- fx_name_to_onnxscript_value: Dict[length=256](\nclone: `TorchScriptTensor(f32[4, 1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_weight: `TorchScriptTensor(f32[3072, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_bias: `TorchScriptTensor(f32[3072])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_weight: `TorchScriptTensor(f32[1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm2_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm2_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___mlp_fc1_weight: `TorchScriptTensor(f32[4096, 1024])`,\n...\n)\n## Return values\n", + "text":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___21___attn_qkv_bias[name=p_getattr_l__self___trunk_blocks___21___attn_qkv_bias]. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"FxOnnxInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":414 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0008", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___21___attn_proj_weight[name=p_getattr_l__self___trunk_blocks___21___attn_proj_weight]. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature FxOnnxInterpreter.run_node\n- self: \n- node: fx.Node(p_getattr_l__self___trunk_blocks___21___attn_proj_weight)[placeholder]:Tensor(f32[1024, 1024])\n- fx_graph_module: torch.fx.GraphModule(torch_nn_modules_container_Sequential)\n- onnxfunction_dispatcher: \n- op_level_debug: False\n- onnxscript_graph: \n- onnxscript_tracer: \n- fx_name_to_onnxscript_value: Dict[length=257](\nclone: `TorchScriptTensor(f32[4, 1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_weight: `TorchScriptTensor(f32[3072, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_bias: `TorchScriptTensor(f32[3072])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_weight: `TorchScriptTensor(f32[1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm2_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm2_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___mlp_fc1_weight: `TorchScriptTensor(f32[4096, 1024])`,\n...\n)\n## Return values\n", + "text":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___21___attn_proj_weight[name=p_getattr_l__self___trunk_blocks___21___attn_proj_weight]. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"FxOnnxInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":414 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0008", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___21___attn_proj_bias[name=p_getattr_l__self___trunk_blocks___21___attn_proj_bias]. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature FxOnnxInterpreter.run_node\n- self: \n- node: fx.Node(p_getattr_l__self___trunk_blocks___21___attn_proj_bias)[placeholder]:Tensor(f32[1024])\n- fx_graph_module: torch.fx.GraphModule(torch_nn_modules_container_Sequential)\n- onnxfunction_dispatcher: \n- op_level_debug: False\n- onnxscript_graph: \n- onnxscript_tracer: \n- fx_name_to_onnxscript_value: Dict[length=258](\nclone: `TorchScriptTensor(f32[4, 1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_weight: `TorchScriptTensor(f32[3072, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_bias: `TorchScriptTensor(f32[3072])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_weight: `TorchScriptTensor(f32[1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm2_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm2_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___mlp_fc1_weight: `TorchScriptTensor(f32[4096, 1024])`,\n...\n)\n## Return values\n", + "text":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___21___attn_proj_bias[name=p_getattr_l__self___trunk_blocks___21___attn_proj_bias]. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"FxOnnxInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":414 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0008", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___21___norm2_weight[name=p_getattr_l__self___trunk_blocks___21___norm2_weight]. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature FxOnnxInterpreter.run_node\n- self: \n- node: fx.Node(p_getattr_l__self___trunk_blocks___21___norm2_weight)[placeholder]:Tensor(f32[1024])\n- fx_graph_module: torch.fx.GraphModule(torch_nn_modules_container_Sequential)\n- onnxfunction_dispatcher: \n- op_level_debug: False\n- onnxscript_graph: \n- onnxscript_tracer: \n- fx_name_to_onnxscript_value: Dict[length=259](\nclone: `TorchScriptTensor(f32[4, 1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_weight: `TorchScriptTensor(f32[3072, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_bias: `TorchScriptTensor(f32[3072])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_weight: `TorchScriptTensor(f32[1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm2_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm2_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___mlp_fc1_weight: `TorchScriptTensor(f32[4096, 1024])`,\n...\n)\n## Return values\n", + "text":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___21___norm2_weight[name=p_getattr_l__self___trunk_blocks___21___norm2_weight]. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"FxOnnxInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":414 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0008", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___21___norm2_bias[name=p_getattr_l__self___trunk_blocks___21___norm2_bias]. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature FxOnnxInterpreter.run_node\n- self: \n- node: fx.Node(p_getattr_l__self___trunk_blocks___21___norm2_bias)[placeholder]:Tensor(f32[1024])\n- fx_graph_module: torch.fx.GraphModule(torch_nn_modules_container_Sequential)\n- onnxfunction_dispatcher: \n- op_level_debug: False\n- onnxscript_graph: \n- onnxscript_tracer: \n- fx_name_to_onnxscript_value: Dict[length=260](\nclone: `TorchScriptTensor(f32[4, 1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_weight: `TorchScriptTensor(f32[3072, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_bias: `TorchScriptTensor(f32[3072])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_weight: `TorchScriptTensor(f32[1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm2_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm2_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___mlp_fc1_weight: `TorchScriptTensor(f32[4096, 1024])`,\n...\n)\n## Return values\n", + "text":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___21___norm2_bias[name=p_getattr_l__self___trunk_blocks___21___norm2_bias]. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"FxOnnxInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":414 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0008", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___21___mlp_fc1_weight[name=p_getattr_l__self___trunk_blocks___21___mlp_fc1_weight]. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature FxOnnxInterpreter.run_node\n- self: \n- node: fx.Node(p_getattr_l__self___trunk_blocks___21___mlp_fc1_weight)[placeholder]:Tensor(f32[4096, 1024])\n- fx_graph_module: torch.fx.GraphModule(torch_nn_modules_container_Sequential)\n- onnxfunction_dispatcher: \n- op_level_debug: False\n- onnxscript_graph: \n- onnxscript_tracer: \n- fx_name_to_onnxscript_value: Dict[length=261](\nclone: `TorchScriptTensor(f32[4, 1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_weight: `TorchScriptTensor(f32[3072, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_bias: `TorchScriptTensor(f32[3072])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_weight: `TorchScriptTensor(f32[1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm2_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm2_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___mlp_fc1_weight: `TorchScriptTensor(f32[4096, 1024])`,\n...\n)\n## Return values\n", + "text":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___21___mlp_fc1_weight[name=p_getattr_l__self___trunk_blocks___21___mlp_fc1_weight]. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"FxOnnxInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":414 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0008", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___21___mlp_fc1_bias[name=p_getattr_l__self___trunk_blocks___21___mlp_fc1_bias]. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature FxOnnxInterpreter.run_node\n- self: \n- node: fx.Node(p_getattr_l__self___trunk_blocks___21___mlp_fc1_bias)[placeholder]:Tensor(f32[4096])\n- fx_graph_module: torch.fx.GraphModule(torch_nn_modules_container_Sequential)\n- onnxfunction_dispatcher: \n- op_level_debug: False\n- onnxscript_graph: \n- onnxscript_tracer: \n- fx_name_to_onnxscript_value: Dict[length=262](\nclone: `TorchScriptTensor(f32[4, 1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_weight: `TorchScriptTensor(f32[3072, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_bias: `TorchScriptTensor(f32[3072])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_weight: `TorchScriptTensor(f32[1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm2_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm2_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___mlp_fc1_weight: `TorchScriptTensor(f32[4096, 1024])`,\n...\n)\n## Return values\n", + "text":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___21___mlp_fc1_bias[name=p_getattr_l__self___trunk_blocks___21___mlp_fc1_bias]. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"FxOnnxInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":414 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0008", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___21___mlp_fc2_weight[name=p_getattr_l__self___trunk_blocks___21___mlp_fc2_weight]. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature FxOnnxInterpreter.run_node\n- self: \n- node: fx.Node(p_getattr_l__self___trunk_blocks___21___mlp_fc2_weight)[placeholder]:Tensor(f32[1024, 4096])\n- fx_graph_module: torch.fx.GraphModule(torch_nn_modules_container_Sequential)\n- onnxfunction_dispatcher: \n- op_level_debug: False\n- onnxscript_graph: \n- onnxscript_tracer: \n- fx_name_to_onnxscript_value: Dict[length=263](\nclone: `TorchScriptTensor(f32[4, 1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_weight: `TorchScriptTensor(f32[3072, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_bias: `TorchScriptTensor(f32[3072])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_weight: `TorchScriptTensor(f32[1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm2_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm2_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___mlp_fc1_weight: `TorchScriptTensor(f32[4096, 1024])`,\n...\n)\n## Return values\n", + "text":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___21___mlp_fc2_weight[name=p_getattr_l__self___trunk_blocks___21___mlp_fc2_weight]. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"FxOnnxInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":414 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0008", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___21___mlp_fc2_bias[name=p_getattr_l__self___trunk_blocks___21___mlp_fc2_bias]. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature FxOnnxInterpreter.run_node\n- self: \n- node: fx.Node(p_getattr_l__self___trunk_blocks___21___mlp_fc2_bias)[placeholder]:Tensor(f32[1024])\n- fx_graph_module: torch.fx.GraphModule(torch_nn_modules_container_Sequential)\n- onnxfunction_dispatcher: \n- op_level_debug: False\n- onnxscript_graph: \n- onnxscript_tracer: \n- fx_name_to_onnxscript_value: Dict[length=264](\nclone: `TorchScriptTensor(f32[4, 1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_weight: `TorchScriptTensor(f32[3072, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_bias: `TorchScriptTensor(f32[3072])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_weight: `TorchScriptTensor(f32[1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm2_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm2_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___mlp_fc1_weight: `TorchScriptTensor(f32[4096, 1024])`,\n...\n)\n## Return values\n", + "text":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___21___mlp_fc2_bias[name=p_getattr_l__self___trunk_blocks___21___mlp_fc2_bias]. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"FxOnnxInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":414 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0008", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___22___norm1_weight[name=p_getattr_l__self___trunk_blocks___22___norm1_weight]. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature FxOnnxInterpreter.run_node\n- self: \n- node: fx.Node(p_getattr_l__self___trunk_blocks___22___norm1_weight)[placeholder]:Tensor(f32[1024])\n- fx_graph_module: torch.fx.GraphModule(torch_nn_modules_container_Sequential)\n- onnxfunction_dispatcher: \n- op_level_debug: False\n- onnxscript_graph: \n- onnxscript_tracer: \n- fx_name_to_onnxscript_value: Dict[length=265](\nclone: `TorchScriptTensor(f32[4, 1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_weight: `TorchScriptTensor(f32[3072, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_bias: `TorchScriptTensor(f32[3072])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_weight: `TorchScriptTensor(f32[1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm2_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm2_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___mlp_fc1_weight: `TorchScriptTensor(f32[4096, 1024])`,\n...\n)\n## Return values\n", + "text":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___22___norm1_weight[name=p_getattr_l__self___trunk_blocks___22___norm1_weight]. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"FxOnnxInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":414 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0008", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___22___norm1_bias[name=p_getattr_l__self___trunk_blocks___22___norm1_bias]. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature FxOnnxInterpreter.run_node\n- self: \n- node: fx.Node(p_getattr_l__self___trunk_blocks___22___norm1_bias)[placeholder]:Tensor(f32[1024])\n- fx_graph_module: torch.fx.GraphModule(torch_nn_modules_container_Sequential)\n- onnxfunction_dispatcher: \n- op_level_debug: False\n- onnxscript_graph: \n- onnxscript_tracer: \n- fx_name_to_onnxscript_value: Dict[length=266](\nclone: `TorchScriptTensor(f32[4, 1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_weight: `TorchScriptTensor(f32[3072, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_bias: `TorchScriptTensor(f32[3072])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_weight: `TorchScriptTensor(f32[1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm2_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm2_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___mlp_fc1_weight: `TorchScriptTensor(f32[4096, 1024])`,\n...\n)\n## Return values\n", + "text":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___22___norm1_bias[name=p_getattr_l__self___trunk_blocks___22___norm1_bias]. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"FxOnnxInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":414 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0008", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___22___attn_qkv_weight[name=p_getattr_l__self___trunk_blocks___22___attn_qkv_weight]. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature FxOnnxInterpreter.run_node\n- self: \n- node: fx.Node(p_getattr_l__self___trunk_blocks___22___attn_qkv_weight)[placeholder]:Tensor(f32[3072, 1024])\n- fx_graph_module: torch.fx.GraphModule(torch_nn_modules_container_Sequential)\n- onnxfunction_dispatcher: \n- op_level_debug: False\n- onnxscript_graph: \n- onnxscript_tracer: \n- fx_name_to_onnxscript_value: Dict[length=267](\nclone: `TorchScriptTensor(f32[4, 1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_weight: `TorchScriptTensor(f32[3072, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_bias: `TorchScriptTensor(f32[3072])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_weight: `TorchScriptTensor(f32[1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm2_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm2_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___mlp_fc1_weight: `TorchScriptTensor(f32[4096, 1024])`,\n...\n)\n## Return values\n", + "text":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___22___attn_qkv_weight[name=p_getattr_l__self___trunk_blocks___22___attn_qkv_weight]. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"FxOnnxInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":414 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0008", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___22___attn_qkv_bias[name=p_getattr_l__self___trunk_blocks___22___attn_qkv_bias]. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature FxOnnxInterpreter.run_node\n- self: \n- node: fx.Node(p_getattr_l__self___trunk_blocks___22___attn_qkv_bias)[placeholder]:Tensor(f32[3072])\n- fx_graph_module: torch.fx.GraphModule(torch_nn_modules_container_Sequential)\n- onnxfunction_dispatcher: \n- op_level_debug: False\n- onnxscript_graph: \n- onnxscript_tracer: \n- fx_name_to_onnxscript_value: Dict[length=268](\nclone: `TorchScriptTensor(f32[4, 1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_weight: `TorchScriptTensor(f32[3072, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_bias: `TorchScriptTensor(f32[3072])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_weight: `TorchScriptTensor(f32[1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm2_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm2_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___mlp_fc1_weight: `TorchScriptTensor(f32[4096, 1024])`,\n...\n)\n## Return values\n", + "text":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___22___attn_qkv_bias[name=p_getattr_l__self___trunk_blocks___22___attn_qkv_bias]. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"FxOnnxInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":414 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0008", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___22___attn_proj_weight[name=p_getattr_l__self___trunk_blocks___22___attn_proj_weight]. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature FxOnnxInterpreter.run_node\n- self: \n- node: fx.Node(p_getattr_l__self___trunk_blocks___22___attn_proj_weight)[placeholder]:Tensor(f32[1024, 1024])\n- fx_graph_module: torch.fx.GraphModule(torch_nn_modules_container_Sequential)\n- onnxfunction_dispatcher: \n- op_level_debug: False\n- onnxscript_graph: \n- onnxscript_tracer: \n- fx_name_to_onnxscript_value: Dict[length=269](\nclone: `TorchScriptTensor(f32[4, 1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_weight: `TorchScriptTensor(f32[3072, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_bias: `TorchScriptTensor(f32[3072])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_weight: `TorchScriptTensor(f32[1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm2_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm2_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___mlp_fc1_weight: `TorchScriptTensor(f32[4096, 1024])`,\n...\n)\n## Return values\n", + "text":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___22___attn_proj_weight[name=p_getattr_l__self___trunk_blocks___22___attn_proj_weight]. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"FxOnnxInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":414 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0008", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___22___attn_proj_bias[name=p_getattr_l__self___trunk_blocks___22___attn_proj_bias]. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature FxOnnxInterpreter.run_node\n- self: \n- node: fx.Node(p_getattr_l__self___trunk_blocks___22___attn_proj_bias)[placeholder]:Tensor(f32[1024])\n- fx_graph_module: torch.fx.GraphModule(torch_nn_modules_container_Sequential)\n- onnxfunction_dispatcher: \n- op_level_debug: False\n- onnxscript_graph: \n- onnxscript_tracer: \n- fx_name_to_onnxscript_value: Dict[length=270](\nclone: `TorchScriptTensor(f32[4, 1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_weight: `TorchScriptTensor(f32[3072, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_bias: `TorchScriptTensor(f32[3072])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_weight: `TorchScriptTensor(f32[1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm2_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm2_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___mlp_fc1_weight: `TorchScriptTensor(f32[4096, 1024])`,\n...\n)\n## Return values\n", + "text":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___22___attn_proj_bias[name=p_getattr_l__self___trunk_blocks___22___attn_proj_bias]. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"FxOnnxInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":414 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0008", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___22___norm2_weight[name=p_getattr_l__self___trunk_blocks___22___norm2_weight]. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature FxOnnxInterpreter.run_node\n- self: \n- node: fx.Node(p_getattr_l__self___trunk_blocks___22___norm2_weight)[placeholder]:Tensor(f32[1024])\n- fx_graph_module: torch.fx.GraphModule(torch_nn_modules_container_Sequential)\n- onnxfunction_dispatcher: \n- op_level_debug: False\n- onnxscript_graph: \n- onnxscript_tracer: \n- fx_name_to_onnxscript_value: Dict[length=271](\nclone: `TorchScriptTensor(f32[4, 1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_weight: `TorchScriptTensor(f32[3072, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_bias: `TorchScriptTensor(f32[3072])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_weight: `TorchScriptTensor(f32[1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm2_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm2_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___mlp_fc1_weight: `TorchScriptTensor(f32[4096, 1024])`,\n...\n)\n## Return values\n", + "text":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___22___norm2_weight[name=p_getattr_l__self___trunk_blocks___22___norm2_weight]. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"FxOnnxInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":414 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0008", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___22___norm2_bias[name=p_getattr_l__self___trunk_blocks___22___norm2_bias]. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature FxOnnxInterpreter.run_node\n- self: \n- node: fx.Node(p_getattr_l__self___trunk_blocks___22___norm2_bias)[placeholder]:Tensor(f32[1024])\n- fx_graph_module: torch.fx.GraphModule(torch_nn_modules_container_Sequential)\n- onnxfunction_dispatcher: \n- op_level_debug: False\n- onnxscript_graph: \n- onnxscript_tracer: \n- fx_name_to_onnxscript_value: Dict[length=272](\nclone: `TorchScriptTensor(f32[4, 1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_weight: `TorchScriptTensor(f32[3072, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_bias: `TorchScriptTensor(f32[3072])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_weight: `TorchScriptTensor(f32[1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm2_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm2_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___mlp_fc1_weight: `TorchScriptTensor(f32[4096, 1024])`,\n...\n)\n## Return values\n", + "text":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___22___norm2_bias[name=p_getattr_l__self___trunk_blocks___22___norm2_bias]. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"FxOnnxInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":414 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0008", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___22___mlp_fc1_weight[name=p_getattr_l__self___trunk_blocks___22___mlp_fc1_weight]. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature FxOnnxInterpreter.run_node\n- self: \n- node: fx.Node(p_getattr_l__self___trunk_blocks___22___mlp_fc1_weight)[placeholder]:Tensor(f32[4096, 1024])\n- fx_graph_module: torch.fx.GraphModule(torch_nn_modules_container_Sequential)\n- onnxfunction_dispatcher: \n- op_level_debug: False\n- onnxscript_graph: \n- onnxscript_tracer: \n- fx_name_to_onnxscript_value: Dict[length=273](\nclone: `TorchScriptTensor(f32[4, 1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_weight: `TorchScriptTensor(f32[3072, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_bias: `TorchScriptTensor(f32[3072])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_weight: `TorchScriptTensor(f32[1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm2_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm2_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___mlp_fc1_weight: `TorchScriptTensor(f32[4096, 1024])`,\n...\n)\n## Return values\n", + "text":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___22___mlp_fc1_weight[name=p_getattr_l__self___trunk_blocks___22___mlp_fc1_weight]. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"FxOnnxInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":414 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0008", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___22___mlp_fc1_bias[name=p_getattr_l__self___trunk_blocks___22___mlp_fc1_bias]. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature FxOnnxInterpreter.run_node\n- self: \n- node: fx.Node(p_getattr_l__self___trunk_blocks___22___mlp_fc1_bias)[placeholder]:Tensor(f32[4096])\n- fx_graph_module: torch.fx.GraphModule(torch_nn_modules_container_Sequential)\n- onnxfunction_dispatcher: \n- op_level_debug: False\n- onnxscript_graph: \n- onnxscript_tracer: \n- fx_name_to_onnxscript_value: Dict[length=274](\nclone: `TorchScriptTensor(f32[4, 1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_weight: `TorchScriptTensor(f32[3072, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_bias: `TorchScriptTensor(f32[3072])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_weight: `TorchScriptTensor(f32[1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm2_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm2_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___mlp_fc1_weight: `TorchScriptTensor(f32[4096, 1024])`,\n...\n)\n## Return values\n", + "text":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___22___mlp_fc1_bias[name=p_getattr_l__self___trunk_blocks___22___mlp_fc1_bias]. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"FxOnnxInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":414 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0008", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___22___mlp_fc2_weight[name=p_getattr_l__self___trunk_blocks___22___mlp_fc2_weight]. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature FxOnnxInterpreter.run_node\n- self: \n- node: fx.Node(p_getattr_l__self___trunk_blocks___22___mlp_fc2_weight)[placeholder]:Tensor(f32[1024, 4096])\n- fx_graph_module: torch.fx.GraphModule(torch_nn_modules_container_Sequential)\n- onnxfunction_dispatcher: \n- op_level_debug: False\n- onnxscript_graph: \n- onnxscript_tracer: \n- fx_name_to_onnxscript_value: Dict[length=275](\nclone: `TorchScriptTensor(f32[4, 1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_weight: `TorchScriptTensor(f32[3072, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_bias: `TorchScriptTensor(f32[3072])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_weight: `TorchScriptTensor(f32[1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm2_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm2_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___mlp_fc1_weight: `TorchScriptTensor(f32[4096, 1024])`,\n...\n)\n## Return values\n", + "text":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___22___mlp_fc2_weight[name=p_getattr_l__self___trunk_blocks___22___mlp_fc2_weight]. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"FxOnnxInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":414 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0008", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___22___mlp_fc2_bias[name=p_getattr_l__self___trunk_blocks___22___mlp_fc2_bias]. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature FxOnnxInterpreter.run_node\n- self: \n- node: fx.Node(p_getattr_l__self___trunk_blocks___22___mlp_fc2_bias)[placeholder]:Tensor(f32[1024])\n- fx_graph_module: torch.fx.GraphModule(torch_nn_modules_container_Sequential)\n- onnxfunction_dispatcher: \n- op_level_debug: False\n- onnxscript_graph: \n- onnxscript_tracer: \n- fx_name_to_onnxscript_value: Dict[length=276](\nclone: `TorchScriptTensor(f32[4, 1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_weight: `TorchScriptTensor(f32[3072, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_bias: `TorchScriptTensor(f32[3072])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_weight: `TorchScriptTensor(f32[1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm2_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm2_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___mlp_fc1_weight: `TorchScriptTensor(f32[4096, 1024])`,\n...\n)\n## Return values\n", + "text":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___22___mlp_fc2_bias[name=p_getattr_l__self___trunk_blocks___22___mlp_fc2_bias]. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"FxOnnxInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":414 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0008", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___23___norm1_weight[name=p_getattr_l__self___trunk_blocks___23___norm1_weight]. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature FxOnnxInterpreter.run_node\n- self: \n- node: fx.Node(p_getattr_l__self___trunk_blocks___23___norm1_weight)[placeholder]:Tensor(f32[1024])\n- fx_graph_module: torch.fx.GraphModule(torch_nn_modules_container_Sequential)\n- onnxfunction_dispatcher: \n- op_level_debug: False\n- onnxscript_graph: \n- onnxscript_tracer: \n- fx_name_to_onnxscript_value: Dict[length=277](\nclone: `TorchScriptTensor(f32[4, 1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_weight: `TorchScriptTensor(f32[3072, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_bias: `TorchScriptTensor(f32[3072])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_weight: `TorchScriptTensor(f32[1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm2_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm2_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___mlp_fc1_weight: `TorchScriptTensor(f32[4096, 1024])`,\n...\n)\n## Return values\n", + "text":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___23___norm1_weight[name=p_getattr_l__self___trunk_blocks___23___norm1_weight]. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"FxOnnxInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":414 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0008", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___23___norm1_bias[name=p_getattr_l__self___trunk_blocks___23___norm1_bias]. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature FxOnnxInterpreter.run_node\n- self: \n- node: fx.Node(p_getattr_l__self___trunk_blocks___23___norm1_bias)[placeholder]:Tensor(f32[1024])\n- fx_graph_module: torch.fx.GraphModule(torch_nn_modules_container_Sequential)\n- onnxfunction_dispatcher: \n- op_level_debug: False\n- onnxscript_graph: \n- onnxscript_tracer: \n- fx_name_to_onnxscript_value: Dict[length=278](\nclone: `TorchScriptTensor(f32[4, 1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_weight: `TorchScriptTensor(f32[3072, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_bias: `TorchScriptTensor(f32[3072])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_weight: `TorchScriptTensor(f32[1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm2_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm2_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___mlp_fc1_weight: `TorchScriptTensor(f32[4096, 1024])`,\n...\n)\n## Return values\n", + "text":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___23___norm1_bias[name=p_getattr_l__self___trunk_blocks___23___norm1_bias]. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"FxOnnxInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":414 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0008", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___23___attn_qkv_weight[name=p_getattr_l__self___trunk_blocks___23___attn_qkv_weight]. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature FxOnnxInterpreter.run_node\n- self: \n- node: fx.Node(p_getattr_l__self___trunk_blocks___23___attn_qkv_weight)[placeholder]:Tensor(f32[3072, 1024])\n- fx_graph_module: torch.fx.GraphModule(torch_nn_modules_container_Sequential)\n- onnxfunction_dispatcher: \n- op_level_debug: False\n- onnxscript_graph: \n- onnxscript_tracer: \n- fx_name_to_onnxscript_value: Dict[length=279](\nclone: `TorchScriptTensor(f32[4, 1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_weight: `TorchScriptTensor(f32[3072, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_bias: `TorchScriptTensor(f32[3072])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_weight: `TorchScriptTensor(f32[1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm2_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm2_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___mlp_fc1_weight: `TorchScriptTensor(f32[4096, 1024])`,\n...\n)\n## Return values\n", + "text":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___23___attn_qkv_weight[name=p_getattr_l__self___trunk_blocks___23___attn_qkv_weight]. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"FxOnnxInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":414 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0008", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___23___attn_qkv_bias[name=p_getattr_l__self___trunk_blocks___23___attn_qkv_bias]. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature FxOnnxInterpreter.run_node\n- self: \n- node: fx.Node(p_getattr_l__self___trunk_blocks___23___attn_qkv_bias)[placeholder]:Tensor(f32[3072])\n- fx_graph_module: torch.fx.GraphModule(torch_nn_modules_container_Sequential)\n- onnxfunction_dispatcher: \n- op_level_debug: False\n- onnxscript_graph: \n- onnxscript_tracer: \n- fx_name_to_onnxscript_value: Dict[length=280](\nclone: `TorchScriptTensor(f32[4, 1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_weight: `TorchScriptTensor(f32[3072, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_bias: `TorchScriptTensor(f32[3072])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_weight: `TorchScriptTensor(f32[1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm2_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm2_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___mlp_fc1_weight: `TorchScriptTensor(f32[4096, 1024])`,\n...\n)\n## Return values\n", + "text":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___23___attn_qkv_bias[name=p_getattr_l__self___trunk_blocks___23___attn_qkv_bias]. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"FxOnnxInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":414 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0008", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___23___attn_proj_weight[name=p_getattr_l__self___trunk_blocks___23___attn_proj_weight]. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature FxOnnxInterpreter.run_node\n- self: \n- node: fx.Node(p_getattr_l__self___trunk_blocks___23___attn_proj_weight)[placeholder]:Tensor(f32[1024, 1024])\n- fx_graph_module: torch.fx.GraphModule(torch_nn_modules_container_Sequential)\n- onnxfunction_dispatcher: \n- op_level_debug: False\n- onnxscript_graph: \n- onnxscript_tracer: \n- fx_name_to_onnxscript_value: Dict[length=281](\nclone: `TorchScriptTensor(f32[4, 1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_weight: `TorchScriptTensor(f32[3072, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_bias: `TorchScriptTensor(f32[3072])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_weight: `TorchScriptTensor(f32[1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm2_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm2_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___mlp_fc1_weight: `TorchScriptTensor(f32[4096, 1024])`,\n...\n)\n## Return values\n", + "text":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___23___attn_proj_weight[name=p_getattr_l__self___trunk_blocks___23___attn_proj_weight]. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"FxOnnxInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":414 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0008", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___23___attn_proj_bias[name=p_getattr_l__self___trunk_blocks___23___attn_proj_bias]. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature FxOnnxInterpreter.run_node\n- self: \n- node: fx.Node(p_getattr_l__self___trunk_blocks___23___attn_proj_bias)[placeholder]:Tensor(f32[1024])\n- fx_graph_module: torch.fx.GraphModule(torch_nn_modules_container_Sequential)\n- onnxfunction_dispatcher: \n- op_level_debug: False\n- onnxscript_graph: \n- onnxscript_tracer: \n- fx_name_to_onnxscript_value: Dict[length=282](\nclone: `TorchScriptTensor(f32[4, 1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_weight: `TorchScriptTensor(f32[3072, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_bias: `TorchScriptTensor(f32[3072])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_weight: `TorchScriptTensor(f32[1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm2_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm2_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___mlp_fc1_weight: `TorchScriptTensor(f32[4096, 1024])`,\n...\n)\n## Return values\n", + "text":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___23___attn_proj_bias[name=p_getattr_l__self___trunk_blocks___23___attn_proj_bias]. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"FxOnnxInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":414 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0008", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___23___norm2_weight[name=p_getattr_l__self___trunk_blocks___23___norm2_weight]. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature FxOnnxInterpreter.run_node\n- self: \n- node: fx.Node(p_getattr_l__self___trunk_blocks___23___norm2_weight)[placeholder]:Tensor(f32[1024])\n- fx_graph_module: torch.fx.GraphModule(torch_nn_modules_container_Sequential)\n- onnxfunction_dispatcher: \n- op_level_debug: False\n- onnxscript_graph: \n- onnxscript_tracer: \n- fx_name_to_onnxscript_value: Dict[length=283](\nclone: `TorchScriptTensor(f32[4, 1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_weight: `TorchScriptTensor(f32[3072, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_bias: `TorchScriptTensor(f32[3072])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_weight: `TorchScriptTensor(f32[1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm2_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm2_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___mlp_fc1_weight: `TorchScriptTensor(f32[4096, 1024])`,\n...\n)\n## Return values\n", + "text":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___23___norm2_weight[name=p_getattr_l__self___trunk_blocks___23___norm2_weight]. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"FxOnnxInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":414 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0008", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___23___norm2_bias[name=p_getattr_l__self___trunk_blocks___23___norm2_bias]. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature FxOnnxInterpreter.run_node\n- self: \n- node: fx.Node(p_getattr_l__self___trunk_blocks___23___norm2_bias)[placeholder]:Tensor(f32[1024])\n- fx_graph_module: torch.fx.GraphModule(torch_nn_modules_container_Sequential)\n- onnxfunction_dispatcher: \n- op_level_debug: False\n- onnxscript_graph: \n- onnxscript_tracer: \n- fx_name_to_onnxscript_value: Dict[length=284](\nclone: `TorchScriptTensor(f32[4, 1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_weight: `TorchScriptTensor(f32[3072, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_bias: `TorchScriptTensor(f32[3072])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_weight: `TorchScriptTensor(f32[1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm2_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm2_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___mlp_fc1_weight: `TorchScriptTensor(f32[4096, 1024])`,\n...\n)\n## Return values\n", + "text":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___23___norm2_bias[name=p_getattr_l__self___trunk_blocks___23___norm2_bias]. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"FxOnnxInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":414 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0008", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___23___mlp_fc1_weight[name=p_getattr_l__self___trunk_blocks___23___mlp_fc1_weight]. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature FxOnnxInterpreter.run_node\n- self: \n- node: fx.Node(p_getattr_l__self___trunk_blocks___23___mlp_fc1_weight)[placeholder]:Tensor(f32[4096, 1024])\n- fx_graph_module: torch.fx.GraphModule(torch_nn_modules_container_Sequential)\n- onnxfunction_dispatcher: \n- op_level_debug: False\n- onnxscript_graph: \n- onnxscript_tracer: \n- fx_name_to_onnxscript_value: Dict[length=285](\nclone: `TorchScriptTensor(f32[4, 1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_weight: `TorchScriptTensor(f32[3072, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_bias: `TorchScriptTensor(f32[3072])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_weight: `TorchScriptTensor(f32[1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm2_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm2_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___mlp_fc1_weight: `TorchScriptTensor(f32[4096, 1024])`,\n...\n)\n## Return values\n", + "text":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___23___mlp_fc1_weight[name=p_getattr_l__self___trunk_blocks___23___mlp_fc1_weight]. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"FxOnnxInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":414 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0008", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___23___mlp_fc1_bias[name=p_getattr_l__self___trunk_blocks___23___mlp_fc1_bias]. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature FxOnnxInterpreter.run_node\n- self: \n- node: fx.Node(p_getattr_l__self___trunk_blocks___23___mlp_fc1_bias)[placeholder]:Tensor(f32[4096])\n- fx_graph_module: torch.fx.GraphModule(torch_nn_modules_container_Sequential)\n- onnxfunction_dispatcher: \n- op_level_debug: False\n- onnxscript_graph: \n- onnxscript_tracer: \n- fx_name_to_onnxscript_value: Dict[length=286](\nclone: `TorchScriptTensor(f32[4, 1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_weight: `TorchScriptTensor(f32[3072, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_bias: `TorchScriptTensor(f32[3072])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_weight: `TorchScriptTensor(f32[1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm2_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm2_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___mlp_fc1_weight: `TorchScriptTensor(f32[4096, 1024])`,\n...\n)\n## Return values\n", + "text":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___23___mlp_fc1_bias[name=p_getattr_l__self___trunk_blocks___23___mlp_fc1_bias]. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"FxOnnxInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":414 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0008", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___23___mlp_fc2_weight[name=p_getattr_l__self___trunk_blocks___23___mlp_fc2_weight]. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature FxOnnxInterpreter.run_node\n- self: \n- node: fx.Node(p_getattr_l__self___trunk_blocks___23___mlp_fc2_weight)[placeholder]:Tensor(f32[1024, 4096])\n- fx_graph_module: torch.fx.GraphModule(torch_nn_modules_container_Sequential)\n- onnxfunction_dispatcher: \n- op_level_debug: False\n- onnxscript_graph: \n- onnxscript_tracer: \n- fx_name_to_onnxscript_value: Dict[length=287](\nclone: `TorchScriptTensor(f32[4, 1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_weight: `TorchScriptTensor(f32[3072, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_bias: `TorchScriptTensor(f32[3072])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_weight: `TorchScriptTensor(f32[1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm2_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm2_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___mlp_fc1_weight: `TorchScriptTensor(f32[4096, 1024])`,\n...\n)\n## Return values\n", + "text":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___23___mlp_fc2_weight[name=p_getattr_l__self___trunk_blocks___23___mlp_fc2_weight]. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"FxOnnxInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":414 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0008", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___23___mlp_fc2_bias[name=p_getattr_l__self___trunk_blocks___23___mlp_fc2_bias]. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature FxOnnxInterpreter.run_node\n- self: \n- node: fx.Node(p_getattr_l__self___trunk_blocks___23___mlp_fc2_bias)[placeholder]:Tensor(f32[1024])\n- fx_graph_module: torch.fx.GraphModule(torch_nn_modules_container_Sequential)\n- onnxfunction_dispatcher: \n- op_level_debug: False\n- onnxscript_graph: \n- onnxscript_tracer: \n- fx_name_to_onnxscript_value: Dict[length=288](\nclone: `TorchScriptTensor(f32[4, 1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_weight: `TorchScriptTensor(f32[3072, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_bias: `TorchScriptTensor(f32[3072])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_weight: `TorchScriptTensor(f32[1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm2_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm2_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___mlp_fc1_weight: `TorchScriptTensor(f32[4096, 1024])`,\n...\n)\n## Return values\n", + "text":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___23___mlp_fc2_bias[name=p_getattr_l__self___trunk_blocks___23___mlp_fc2_bias]. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"FxOnnxInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":414 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0008", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Node: placeholder:clone[name=clone]. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature FxOnnxInterpreter.run_node\n- self: \n- node: fx.Node(clone)[placeholder]:Tensor(f32[4, 1024, 1024])\n- fx_graph_module: torch.fx.GraphModule(timm_models_vision_transformer_Block)\n- onnxfunction_dispatcher: \n- op_level_debug: False\n- onnxscript_graph: \n- onnxscript_tracer: \n- fx_name_to_onnxscript_value: Dict[length=0](\nNone)\n## PyTorch source information\n```\n File \"/home/thebears/.local/lib/python3.10/site-packages/open_clip/timm_model.py\", line 196, in forward\n x = self.trunk(x)\n File \"/home/thebears/.local/lib/python3.10/site-packages/torch/nn/modules/module.py\", line 1725, in _call_impl\n return forward_call(*args, **kwargs)\n File \"/home/thebears/.local/lib/python3.10/site-packages/timm/models/vision_transformer.py\", line 853, in forward\n x = self.forward_features(x)\n File \"/home/thebears/.local/lib/python3.10/site-packages/timm/models/vision_transformer.py\", line 828, in forward_features\n x = self._pos_embed(x)\n File \"/home/thebears/.local/lib/python3.10/site-packages/timm/models/vision_transformer.py\", line 720, in _pos_embed\n return self.pos_drop(x)\n\n```\n## Return values\n", + "text":"FX Node: placeholder:clone[name=clone]. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"FxOnnxInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":414 + } + } + }, + { + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/open_clip/timm_model.py" + }, + "region":{ + "snippet":{ + "text":"x = self.trunk(x)" + }, + "startLine":196 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0008", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___0___norm1_weight[name=p_getattr_l__self___trunk_blocks___0___norm1_weight]. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature FxOnnxInterpreter.run_node\n- self: \n- node: fx.Node(p_getattr_l__self___trunk_blocks___0___norm1_weight)[placeholder]:Tensor(f32[1024])\n- fx_graph_module: torch.fx.GraphModule(timm_models_vision_transformer_Block)\n- onnxfunction_dispatcher: \n- op_level_debug: False\n- onnxscript_graph: \n- onnxscript_tracer: \n- fx_name_to_onnxscript_value: Dict[length=1](\nclone: `TorchScriptTensor(f32[4, 1024, 1024])`,\n)\n## Return values\n", + "text":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___0___norm1_weight[name=p_getattr_l__self___trunk_blocks___0___norm1_weight]. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"FxOnnxInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":414 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0008", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___0___norm1_bias[name=p_getattr_l__self___trunk_blocks___0___norm1_bias]. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature FxOnnxInterpreter.run_node\n- self: \n- node: fx.Node(p_getattr_l__self___trunk_blocks___0___norm1_bias)[placeholder]:Tensor(f32[1024])\n- fx_graph_module: torch.fx.GraphModule(timm_models_vision_transformer_Block)\n- onnxfunction_dispatcher: \n- op_level_debug: False\n- onnxscript_graph: \n- onnxscript_tracer: \n- fx_name_to_onnxscript_value: Dict[length=2](\nclone: `TorchScriptTensor(f32[4, 1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_weight: `TorchScriptTensor(f32[1024])`,\n)\n## Return values\n", + "text":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___0___norm1_bias[name=p_getattr_l__self___trunk_blocks___0___norm1_bias]. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"FxOnnxInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":414 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0008", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___0___attn_qkv_weight[name=p_getattr_l__self___trunk_blocks___0___attn_qkv_weight]. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature FxOnnxInterpreter.run_node\n- self: \n- node: fx.Node(p_getattr_l__self___trunk_blocks___0___attn_qkv_weight)[placeholder]:Tensor(f32[3072, 1024])\n- fx_graph_module: torch.fx.GraphModule(timm_models_vision_transformer_Block)\n- onnxfunction_dispatcher: \n- op_level_debug: False\n- onnxscript_graph: \n- onnxscript_tracer: \n- fx_name_to_onnxscript_value: Dict[length=3](\nclone: `TorchScriptTensor(f32[4, 1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_bias: `TorchScriptTensor(f32[1024])`,\n)\n## Return values\n", + "text":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___0___attn_qkv_weight[name=p_getattr_l__self___trunk_blocks___0___attn_qkv_weight]. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"FxOnnxInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":414 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0008", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___0___attn_qkv_bias[name=p_getattr_l__self___trunk_blocks___0___attn_qkv_bias]. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature FxOnnxInterpreter.run_node\n- self: \n- node: fx.Node(p_getattr_l__self___trunk_blocks___0___attn_qkv_bias)[placeholder]:Tensor(f32[3072])\n- fx_graph_module: torch.fx.GraphModule(timm_models_vision_transformer_Block)\n- onnxfunction_dispatcher: \n- op_level_debug: False\n- onnxscript_graph: \n- onnxscript_tracer: \n- fx_name_to_onnxscript_value: Dict[length=4](\nclone: `TorchScriptTensor(f32[4, 1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_weight: `TorchScriptTensor(f32[3072, 1024])`,\n)\n## Return values\n", + "text":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___0___attn_qkv_bias[name=p_getattr_l__self___trunk_blocks___0___attn_qkv_bias]. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"FxOnnxInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":414 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0008", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___0___attn_proj_weight[name=p_getattr_l__self___trunk_blocks___0___attn_proj_weight]. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature FxOnnxInterpreter.run_node\n- self: \n- node: fx.Node(p_getattr_l__self___trunk_blocks___0___attn_proj_weight)[placeholder]:Tensor(f32[1024, 1024])\n- fx_graph_module: torch.fx.GraphModule(timm_models_vision_transformer_Block)\n- onnxfunction_dispatcher: \n- op_level_debug: False\n- onnxscript_graph: \n- onnxscript_tracer: \n- fx_name_to_onnxscript_value: Dict[length=5](\nclone: `TorchScriptTensor(f32[4, 1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_weight: `TorchScriptTensor(f32[3072, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_bias: `TorchScriptTensor(f32[3072])`,\n)\n## Return values\n", + "text":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___0___attn_proj_weight[name=p_getattr_l__self___trunk_blocks___0___attn_proj_weight]. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"FxOnnxInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":414 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0008", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___0___attn_proj_bias[name=p_getattr_l__self___trunk_blocks___0___attn_proj_bias]. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature FxOnnxInterpreter.run_node\n- self: \n- node: fx.Node(p_getattr_l__self___trunk_blocks___0___attn_proj_bias)[placeholder]:Tensor(f32[1024])\n- fx_graph_module: torch.fx.GraphModule(timm_models_vision_transformer_Block)\n- onnxfunction_dispatcher: \n- op_level_debug: False\n- onnxscript_graph: \n- onnxscript_tracer: \n- fx_name_to_onnxscript_value: Dict[length=6](\nclone: `TorchScriptTensor(f32[4, 1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_weight: `TorchScriptTensor(f32[3072, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_bias: `TorchScriptTensor(f32[3072])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_weight: `TorchScriptTensor(f32[1024, 1024])`,\n)\n## Return values\n", + "text":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___0___attn_proj_bias[name=p_getattr_l__self___trunk_blocks___0___attn_proj_bias]. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"FxOnnxInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":414 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0008", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___0___norm2_weight[name=p_getattr_l__self___trunk_blocks___0___norm2_weight]. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature FxOnnxInterpreter.run_node\n- self: \n- node: fx.Node(p_getattr_l__self___trunk_blocks___0___norm2_weight)[placeholder]:Tensor(f32[1024])\n- fx_graph_module: torch.fx.GraphModule(timm_models_vision_transformer_Block)\n- onnxfunction_dispatcher: \n- op_level_debug: False\n- onnxscript_graph: \n- onnxscript_tracer: \n- fx_name_to_onnxscript_value: Dict[length=7](\nclone: `TorchScriptTensor(f32[4, 1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_weight: `TorchScriptTensor(f32[3072, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_bias: `TorchScriptTensor(f32[3072])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_weight: `TorchScriptTensor(f32[1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_bias: `TorchScriptTensor(f32[1024])`,\n)\n## Return values\n", + "text":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___0___norm2_weight[name=p_getattr_l__self___trunk_blocks___0___norm2_weight]. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"FxOnnxInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":414 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0008", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___0___norm2_bias[name=p_getattr_l__self___trunk_blocks___0___norm2_bias]. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature FxOnnxInterpreter.run_node\n- self: \n- node: fx.Node(p_getattr_l__self___trunk_blocks___0___norm2_bias)[placeholder]:Tensor(f32[1024])\n- fx_graph_module: torch.fx.GraphModule(timm_models_vision_transformer_Block)\n- onnxfunction_dispatcher: \n- op_level_debug: False\n- onnxscript_graph: \n- onnxscript_tracer: \n- fx_name_to_onnxscript_value: Dict[length=8](\nclone: `TorchScriptTensor(f32[4, 1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_weight: `TorchScriptTensor(f32[3072, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_bias: `TorchScriptTensor(f32[3072])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_weight: `TorchScriptTensor(f32[1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm2_weight: `TorchScriptTensor(f32[1024])`,\n)\n## Return values\n", + "text":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___0___norm2_bias[name=p_getattr_l__self___trunk_blocks___0___norm2_bias]. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"FxOnnxInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":414 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0008", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___0___mlp_fc1_weight[name=p_getattr_l__self___trunk_blocks___0___mlp_fc1_weight]. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature FxOnnxInterpreter.run_node\n- self: \n- node: fx.Node(p_getattr_l__self___trunk_blocks___0___mlp_fc1_weight)[placeholder]:Tensor(f32[4096, 1024])\n- fx_graph_module: torch.fx.GraphModule(timm_models_vision_transformer_Block)\n- onnxfunction_dispatcher: \n- op_level_debug: False\n- onnxscript_graph: \n- onnxscript_tracer: \n- fx_name_to_onnxscript_value: Dict[length=9](\nclone: `TorchScriptTensor(f32[4, 1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_weight: `TorchScriptTensor(f32[3072, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_bias: `TorchScriptTensor(f32[3072])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_weight: `TorchScriptTensor(f32[1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm2_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm2_bias: `TorchScriptTensor(f32[1024])`,\n)\n## Return values\n", + "text":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___0___mlp_fc1_weight[name=p_getattr_l__self___trunk_blocks___0___mlp_fc1_weight]. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"FxOnnxInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":414 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0008", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___0___mlp_fc1_bias[name=p_getattr_l__self___trunk_blocks___0___mlp_fc1_bias]. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature FxOnnxInterpreter.run_node\n- self: \n- node: fx.Node(p_getattr_l__self___trunk_blocks___0___mlp_fc1_bias)[placeholder]:Tensor(f32[4096])\n- fx_graph_module: torch.fx.GraphModule(timm_models_vision_transformer_Block)\n- onnxfunction_dispatcher: \n- op_level_debug: False\n- onnxscript_graph: \n- onnxscript_tracer: \n- fx_name_to_onnxscript_value: Dict[length=10](\nclone: `TorchScriptTensor(f32[4, 1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_weight: `TorchScriptTensor(f32[3072, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_bias: `TorchScriptTensor(f32[3072])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_weight: `TorchScriptTensor(f32[1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm2_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm2_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___mlp_fc1_weight: `TorchScriptTensor(f32[4096, 1024])`,\n)\n## Return values\n", + "text":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___0___mlp_fc1_bias[name=p_getattr_l__self___trunk_blocks___0___mlp_fc1_bias]. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"FxOnnxInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":414 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0008", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___0___mlp_fc2_weight[name=p_getattr_l__self___trunk_blocks___0___mlp_fc2_weight]. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature FxOnnxInterpreter.run_node\n- self: \n- node: fx.Node(p_getattr_l__self___trunk_blocks___0___mlp_fc2_weight)[placeholder]:Tensor(f32[1024, 4096])\n- fx_graph_module: torch.fx.GraphModule(timm_models_vision_transformer_Block)\n- onnxfunction_dispatcher: \n- op_level_debug: False\n- onnxscript_graph: \n- onnxscript_tracer: \n- fx_name_to_onnxscript_value: Dict[length=11](\nclone: `TorchScriptTensor(f32[4, 1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_weight: `TorchScriptTensor(f32[3072, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_bias: `TorchScriptTensor(f32[3072])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_weight: `TorchScriptTensor(f32[1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm2_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm2_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___mlp_fc1_weight: `TorchScriptTensor(f32[4096, 1024])`,\n...\n)\n## Return values\n", + "text":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___0___mlp_fc2_weight[name=p_getattr_l__self___trunk_blocks___0___mlp_fc2_weight]. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"FxOnnxInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":414 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0008", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___0___mlp_fc2_bias[name=p_getattr_l__self___trunk_blocks___0___mlp_fc2_bias]. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature FxOnnxInterpreter.run_node\n- self: \n- node: fx.Node(p_getattr_l__self___trunk_blocks___0___mlp_fc2_bias)[placeholder]:Tensor(f32[1024])\n- fx_graph_module: torch.fx.GraphModule(timm_models_vision_transformer_Block)\n- onnxfunction_dispatcher: \n- op_level_debug: False\n- onnxscript_graph: \n- onnxscript_tracer: \n- fx_name_to_onnxscript_value: Dict[length=12](\nclone: `TorchScriptTensor(f32[4, 1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_weight: `TorchScriptTensor(f32[3072, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_bias: `TorchScriptTensor(f32[3072])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_weight: `TorchScriptTensor(f32[1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm2_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm2_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___mlp_fc1_weight: `TorchScriptTensor(f32[4096, 1024])`,\n...\n)\n## Return values\n", + "text":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___0___mlp_fc2_bias[name=p_getattr_l__self___trunk_blocks___0___mlp_fc2_bias]. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"FxOnnxInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":414 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0008", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Node: placeholder:clone[name=clone]. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature FxOnnxInterpreter.run_node\n- self: \n- node: fx.Node(clone)[placeholder]:Tensor(f32[4, 1024, 1024])\n- fx_graph_module: torch.fx.GraphModule(torch_nn_modules_normalization_LayerNorm)\n- onnxfunction_dispatcher: \n- op_level_debug: False\n- onnxscript_graph: \n- onnxscript_tracer: \n- fx_name_to_onnxscript_value: Dict[length=0](\nNone)\n## PyTorch source information\n```\n File \"/home/thebears/.local/lib/python3.10/site-packages/open_clip/timm_model.py\", line 196, in forward\n x = self.trunk(x)\n File \"/home/thebears/.local/lib/python3.10/site-packages/torch/nn/modules/module.py\", line 1725, in _call_impl\n return forward_call(*args, **kwargs)\n File \"/home/thebears/.local/lib/python3.10/site-packages/timm/models/vision_transformer.py\", line 853, in forward\n x = self.forward_features(x)\n File \"/home/thebears/.local/lib/python3.10/site-packages/timm/models/vision_transformer.py\", line 828, in forward_features\n x = self._pos_embed(x)\n File \"/home/thebears/.local/lib/python3.10/site-packages/timm/models/vision_transformer.py\", line 720, in _pos_embed\n return self.pos_drop(x)\n\n```\n## Return values\n", + "text":"FX Node: placeholder:clone[name=clone]. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"FxOnnxInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":414 + } + } + }, + { + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/open_clip/timm_model.py" + }, + "region":{ + "snippet":{ + "text":"x = self.trunk(x)" + }, + "startLine":196 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0008", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___0___norm1_weight[name=p_getattr_l__self___trunk_blocks___0___norm1_weight]. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature FxOnnxInterpreter.run_node\n- self: \n- node: fx.Node(p_getattr_l__self___trunk_blocks___0___norm1_weight)[placeholder]:Tensor(f32[1024])\n- fx_graph_module: torch.fx.GraphModule(torch_nn_modules_normalization_LayerNorm)\n- onnxfunction_dispatcher: \n- op_level_debug: False\n- onnxscript_graph: \n- onnxscript_tracer: \n- fx_name_to_onnxscript_value: Dict[length=1](\nclone: `TorchScriptTensor(f32[4, 1024, 1024])`,\n)\n## Return values\n", + "text":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___0___norm1_weight[name=p_getattr_l__self___trunk_blocks___0___norm1_weight]. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"FxOnnxInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":414 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0008", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___0___norm1_bias[name=p_getattr_l__self___trunk_blocks___0___norm1_bias]. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature FxOnnxInterpreter.run_node\n- self: \n- node: fx.Node(p_getattr_l__self___trunk_blocks___0___norm1_bias)[placeholder]:Tensor(f32[1024])\n- fx_graph_module: torch.fx.GraphModule(torch_nn_modules_normalization_LayerNorm)\n- onnxfunction_dispatcher: \n- op_level_debug: False\n- onnxscript_graph: \n- onnxscript_tracer: \n- fx_name_to_onnxscript_value: Dict[length=2](\nclone: `TorchScriptTensor(f32[4, 1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_weight: `TorchScriptTensor(f32[1024])`,\n)\n## Return values\n", + "text":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___0___norm1_bias[name=p_getattr_l__self___trunk_blocks___0___norm1_bias]. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"FxOnnxInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":414 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0008", + "stacks":[] + }, + { + "message":{ + "markdown":"Searching operator overload: 'aten.native_layer_norm.default' in onnx registry...\n\n\n## Additional Message:\n\n## Function Signature\n### Function Signature OnnxFunctionDispatcher.get_function_overloads\n- self: \n- node: fx.Node(aten.native_layer_norm.default)[call_function]:Tuple[length=3](\nTensor(f32[4, 1024, 1024]),\nTensor(f32[4, 1024, 1]),\nTensor(f32[4, 1024, 1]),\n)\n- diagnostic_context: \n## Return values\nList[length=1](\nregistration.ONNXFunction(aten::native_layer_norm.default, is_custom=False, is_complex=False),\n)", + "text":"Searching operator overload: 'aten.native_layer_norm.default' in onnx registry...\n" + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"OnnxFunctionDispatcher.get_function_overloads" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/onnxfunction_dispatcher.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":353 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0016", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Node: aten.native_layer_norm.default. \nONNX Node: aten_native_layer_norm[opset=pkg.onnxscript.torch_lib;is_custom=False]. \n\n\n## Additional Message:\n\n## Function Signature\n### Function Signature OnnxFunctionDispatcher._find_the_perfect_or_nearest_match_onnxfunction\n- self: \n- node: fx.Node(aten.native_layer_norm.default)[call_function]:Tuple[length=3](\nTensor(f32[4, 1024, 1024]),\nTensor(f32[4, 1024, 1]),\nTensor(f32[4, 1024, 1]),\n)\n- default_and_custom_functions: List[length=1](\nregistration.ONNXFunction(aten::native_layer_norm.default, is_custom=False, is_complex=False),\n)\n- onnx_args: Tuple[length=5](\n`TorchScriptTensor(f32[4, 1024, 1024])`,\nList[length=1](\n1024,\n),\n`TorchScriptTensor(f32[1024])`,\n`TorchScriptTensor(f32[1024])`,\n1e-06,\n)\n- onnx_kwargs: Dict[length=0](\nNone)\n- diagnostic_context: \n## Checking perfect match...\n`TracedOnnxFunction(aten_native_layer_norm)`\nmatch score: 2\n## Return values\n`TracedOnnxFunction(aten_native_layer_norm)`", + "text":"FX Node: aten.native_layer_norm.default. \nONNX Node: aten_native_layer_norm[opset=pkg.onnxscript.torch_lib;is_custom=False]. \n" + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"OnnxFunctionDispatcher._find_the_perfect_or_nearest_match_onnxfunction" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/onnxfunction_dispatcher.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":199 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0014", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Node: call_function:aten.native_layer_norm.default[name=native_layer_norm]. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature FxOnnxInterpreter.run_node\n- self: \n- node: fx.Node(aten.native_layer_norm.default)[call_function]:Tuple[length=3](\nTensor(f32[4, 1024, 1024]),\nTensor(f32[4, 1024, 1]),\nTensor(f32[4, 1024, 1]),\n)\n- fx_graph_module: torch.fx.GraphModule(torch_nn_modules_normalization_LayerNorm)\n- onnxfunction_dispatcher: \n- op_level_debug: False\n- onnxscript_graph: \n- onnxscript_tracer: \n- fx_name_to_onnxscript_value: Dict[length=3](\nclone: `TorchScriptTensor(f32[4, 1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_bias: `TorchScriptTensor(f32[1024])`,\n)\n## PyTorch source information\n```\n File \"/home/thebears/.local/lib/python3.10/site-packages/open_clip/timm_model.py\", line 196, in forward\n x = self.trunk(x)\n File \"/home/thebears/.local/lib/python3.10/site-packages/torch/nn/modules/module.py\", line 1725, in _call_impl\n return forward_call(*args, **kwargs)\n File \"/home/thebears/.local/lib/python3.10/site-packages/timm/models/vision_transformer.py\", line 853, in forward\n x = self.forward_features(x)\n File \"/home/thebears/.local/lib/python3.10/site-packages/timm/models/vision_transformer.py\", line 834, in forward_features\n x = self.blocks(x)\n File \"/home/thebears/.local/lib/python3.10/site-packages/torch/nn/modules/module.py\", line 1725, in _call_impl\n return forward_call(*args, **kwargs)\n File \"/home/thebears/.local/lib/python3.10/site-packages/timm/models/vision_transformer.py\", line 169, in forward\n x = x + self.drop_path1(self.ls1(self.attn(self.norm1(x))))\n\n```\n## Return values\n", + "text":"FX Node: call_function:aten.native_layer_norm.default[name=native_layer_norm]. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"FxOnnxInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":414 + } + } + }, + { + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/open_clip/timm_model.py" + }, + "region":{ + "snippet":{ + "text":"x = self.trunk(x)" + }, + "startLine":196 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0008", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Node: call_function:[name=getitem]. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature FxOnnxInterpreter.run_node\n- self: \n- node: fx.Node()[call_function]:Tensor(f32[4, 1024, 1024])\n- fx_graph_module: torch.fx.GraphModule(torch_nn_modules_normalization_LayerNorm)\n- onnxfunction_dispatcher: \n- op_level_debug: False\n- onnxscript_graph: \n- onnxscript_tracer: \n- fx_name_to_onnxscript_value: Dict[length=4](\nclone: `TorchScriptTensor(f32[4, 1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_bias: `TorchScriptTensor(f32[1024])`,\nnative_layer_norm: Tuple[length=3](\n`TorchScriptTensor(f32[4, 1024, 1024])`,\n`TorchScriptTensor(f32[4, 1024, 1])`,\n`TorchScriptTensor(f32[4, 1024, 1])`,\n),\n)\n## PyTorch source information\n```\n File \"/home/thebears/.local/lib/python3.10/site-packages/open_clip/timm_model.py\", line 196, in forward\n x = self.trunk(x)\n File \"/home/thebears/.local/lib/python3.10/site-packages/torch/nn/modules/module.py\", line 1725, in _call_impl\n return forward_call(*args, **kwargs)\n File \"/home/thebears/.local/lib/python3.10/site-packages/timm/models/vision_transformer.py\", line 853, in forward\n x = self.forward_features(x)\n File \"/home/thebears/.local/lib/python3.10/site-packages/timm/models/vision_transformer.py\", line 834, in forward_features\n x = self.blocks(x)\n File \"/home/thebears/.local/lib/python3.10/site-packages/torch/nn/modules/module.py\", line 1725, in _call_impl\n return forward_call(*args, **kwargs)\n File \"/home/thebears/.local/lib/python3.10/site-packages/timm/models/vision_transformer.py\", line 169, in forward\n x = x + self.drop_path1(self.ls1(self.attn(self.norm1(x))))\n\n```\n## Return values\n", + "text":"FX Node: call_function:[name=getitem]. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"FxOnnxInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":414 + } + } + }, + { + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/open_clip/timm_model.py" + }, + "region":{ + "snippet":{ + "text":"x = self.trunk(x)" + }, + "startLine":196 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0008", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Node: output:output[name=output]. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature FxOnnxInterpreter.run_node\n- self: \n- node: fx.Node(output)[output]:None\n- fx_graph_module: torch.fx.GraphModule(torch_nn_modules_normalization_LayerNorm)\n- onnxfunction_dispatcher: \n- op_level_debug: False\n- onnxscript_graph: \n- onnxscript_tracer: \n- fx_name_to_onnxscript_value: Dict[length=5](\nclone: `TorchScriptTensor(f32[4, 1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_bias: `TorchScriptTensor(f32[1024])`,\nnative_layer_norm: Tuple[length=3](\n`TorchScriptTensor(f32[4, 1024, 1024])`,\n`TorchScriptTensor(f32[4, 1024, 1])`,\n`TorchScriptTensor(f32[4, 1024, 1])`,\n),\ngetitem: `TorchScriptTensor(f32[4, 1024, 1024])`,\n)\n## Return values\n", + "text":"FX Node: output:output[name=output]. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"FxOnnxInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":414 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0008", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Graph: torch_nn_modules_normalization_LayerNorm. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature FxOnnxInterpreter.run\n- self: \n- fx_graph_module: torch.fx.GraphModule(torch_nn_modules_normalization_LayerNorm)\n- onnxfunction_dispatcher: \n- op_level_debug: False\n- parent_onnxscript_graph: \n## Return values\n", + "text":"FX Graph: torch_nn_modules_normalization_LayerNorm. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"FxOnnxInterpreter.run" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":496 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0007", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Node: call_module:getattr_L__self___trunk_blocks___0___norm1_1[name=getattr_l__self___trunk_blocks___0___norm1_1]. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature FxOnnxInterpreter.run_node\n- self: \n- node: fx.Node(getattr_L__self___trunk_blocks___0___norm1_1)[call_module]:Tensor(f32[4, 1024, 1024])\n- fx_graph_module: torch.fx.GraphModule(timm_models_vision_transformer_Block)\n- onnxfunction_dispatcher: \n- op_level_debug: False\n- onnxscript_graph: \n- onnxscript_tracer: \n- fx_name_to_onnxscript_value: Dict[length=13](\nclone: `TorchScriptTensor(f32[4, 1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_weight: `TorchScriptTensor(f32[3072, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_bias: `TorchScriptTensor(f32[3072])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_weight: `TorchScriptTensor(f32[1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm2_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm2_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___mlp_fc1_weight: `TorchScriptTensor(f32[4096, 1024])`,\n...\n)\n## PyTorch source information\n```\n File \"/home/thebears/.local/lib/python3.10/site-packages/open_clip/timm_model.py\", line 196, in forward\n x = self.trunk(x)\n File \"/home/thebears/.local/lib/python3.10/site-packages/torch/nn/modules/module.py\", line 1725, in _call_impl\n return forward_call(*args, **kwargs)\n File \"/home/thebears/.local/lib/python3.10/site-packages/timm/models/vision_transformer.py\", line 853, in forward\n x = self.forward_features(x)\n File \"/home/thebears/.local/lib/python3.10/site-packages/timm/models/vision_transformer.py\", line 834, in forward_features\n x = self.blocks(x)\n File \"/home/thebears/.local/lib/python3.10/site-packages/torch/nn/modules/module.py\", line 1725, in _call_impl\n return forward_call(*args, **kwargs)\n File \"/home/thebears/.local/lib/python3.10/site-packages/timm/models/vision_transformer.py\", line 169, in forward\n x = x + self.drop_path1(self.ls1(self.attn(self.norm1(x))))\n\n```\n## Return values\n", + "text":"FX Node: call_module:getattr_L__self___trunk_blocks___0___norm1_1[name=getattr_l__self___trunk_blocks___0___norm1_1]. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"FxOnnxInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":414 + } + } + }, + { + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/open_clip/timm_model.py" + }, + "region":{ + "snippet":{ + "text":"x = self.trunk(x)" + }, + "startLine":196 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0008", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Node: placeholder:getitem[name=getitem]. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature FxOnnxInterpreter.run_node\n- self: \n- node: fx.Node(getitem)[placeholder]:Tensor(f32[4, 1024, 1024])\n- fx_graph_module: torch.fx.GraphModule(timm_models_vision_transformer_Attention)\n- onnxfunction_dispatcher: \n- op_level_debug: False\n- onnxscript_graph: \n- onnxscript_tracer: \n- fx_name_to_onnxscript_value: Dict[length=0](\nNone)\n## PyTorch source information\n```\n File \"/home/thebears/.local/lib/python3.10/site-packages/open_clip/timm_model.py\", line 196, in forward\n x = self.trunk(x)\n File \"/home/thebears/.local/lib/python3.10/site-packages/torch/nn/modules/module.py\", line 1725, in _call_impl\n return forward_call(*args, **kwargs)\n File \"/home/thebears/.local/lib/python3.10/site-packages/timm/models/vision_transformer.py\", line 853, in forward\n x = self.forward_features(x)\n File \"/home/thebears/.local/lib/python3.10/site-packages/timm/models/vision_transformer.py\", line 834, in forward_features\n x = self.blocks(x)\n File \"/home/thebears/.local/lib/python3.10/site-packages/torch/nn/modules/module.py\", line 1725, in _call_impl\n return forward_call(*args, **kwargs)\n File \"/home/thebears/.local/lib/python3.10/site-packages/timm/models/vision_transformer.py\", line 169, in forward\n x = x + self.drop_path1(self.ls1(self.attn(self.norm1(x))))\n\n```\n## Return values\n", + "text":"FX Node: placeholder:getitem[name=getitem]. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"FxOnnxInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":414 + } + } + }, + { + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/open_clip/timm_model.py" + }, + "region":{ + "snippet":{ + "text":"x = self.trunk(x)" + }, + "startLine":196 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0008", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___0___attn_qkv_weight[name=p_getattr_l__self___trunk_blocks___0___attn_qkv_weight]. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature FxOnnxInterpreter.run_node\n- self: \n- node: fx.Node(p_getattr_l__self___trunk_blocks___0___attn_qkv_weight)[placeholder]:Tensor(f32[3072, 1024])\n- fx_graph_module: torch.fx.GraphModule(timm_models_vision_transformer_Attention)\n- onnxfunction_dispatcher: \n- op_level_debug: False\n- onnxscript_graph: \n- onnxscript_tracer: \n- fx_name_to_onnxscript_value: Dict[length=1](\ngetitem: `TorchScriptTensor(f32[4, 1024, 1024])`,\n)\n## Return values\n", + "text":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___0___attn_qkv_weight[name=p_getattr_l__self___trunk_blocks___0___attn_qkv_weight]. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"FxOnnxInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":414 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0008", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___0___attn_qkv_bias[name=p_getattr_l__self___trunk_blocks___0___attn_qkv_bias]. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature FxOnnxInterpreter.run_node\n- self: \n- node: fx.Node(p_getattr_l__self___trunk_blocks___0___attn_qkv_bias)[placeholder]:Tensor(f32[3072])\n- fx_graph_module: torch.fx.GraphModule(timm_models_vision_transformer_Attention)\n- onnxfunction_dispatcher: \n- op_level_debug: False\n- onnxscript_graph: \n- onnxscript_tracer: \n- fx_name_to_onnxscript_value: Dict[length=2](\ngetitem: `TorchScriptTensor(f32[4, 1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_weight: `TorchScriptTensor(f32[3072, 1024])`,\n)\n## Return values\n", + "text":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___0___attn_qkv_bias[name=p_getattr_l__self___trunk_blocks___0___attn_qkv_bias]. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"FxOnnxInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":414 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0008", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___0___attn_proj_weight[name=p_getattr_l__self___trunk_blocks___0___attn_proj_weight]. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature FxOnnxInterpreter.run_node\n- self: \n- node: fx.Node(p_getattr_l__self___trunk_blocks___0___attn_proj_weight)[placeholder]:Tensor(f32[1024, 1024])\n- fx_graph_module: torch.fx.GraphModule(timm_models_vision_transformer_Attention)\n- onnxfunction_dispatcher: \n- op_level_debug: False\n- onnxscript_graph: \n- onnxscript_tracer: \n- fx_name_to_onnxscript_value: Dict[length=3](\ngetitem: `TorchScriptTensor(f32[4, 1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_weight: `TorchScriptTensor(f32[3072, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_bias: `TorchScriptTensor(f32[3072])`,\n)\n## Return values\n", + "text":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___0___attn_proj_weight[name=p_getattr_l__self___trunk_blocks___0___attn_proj_weight]. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"FxOnnxInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":414 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0008", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___0___attn_proj_bias[name=p_getattr_l__self___trunk_blocks___0___attn_proj_bias]. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature FxOnnxInterpreter.run_node\n- self: \n- node: fx.Node(p_getattr_l__self___trunk_blocks___0___attn_proj_bias)[placeholder]:Tensor(f32[1024])\n- fx_graph_module: torch.fx.GraphModule(timm_models_vision_transformer_Attention)\n- onnxfunction_dispatcher: \n- op_level_debug: False\n- onnxscript_graph: \n- onnxscript_tracer: \n- fx_name_to_onnxscript_value: Dict[length=4](\ngetitem: `TorchScriptTensor(f32[4, 1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_weight: `TorchScriptTensor(f32[3072, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_bias: `TorchScriptTensor(f32[3072])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_weight: `TorchScriptTensor(f32[1024, 1024])`,\n)\n## Return values\n", + "text":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___0___attn_proj_bias[name=p_getattr_l__self___trunk_blocks___0___attn_proj_bias]. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"FxOnnxInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":414 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0008", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Node: placeholder:getitem[name=getitem]. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature FxOnnxInterpreter.run_node\n- self: \n- node: fx.Node(getitem)[placeholder]:Tensor(f32[4, 1024, 1024])\n- fx_graph_module: torch.fx.GraphModule(torch_nn_modules_linear_Linear)\n- onnxfunction_dispatcher: \n- op_level_debug: False\n- onnxscript_graph: \n- onnxscript_tracer: \n- fx_name_to_onnxscript_value: Dict[length=0](\nNone)\n## PyTorch source information\n```\n File \"/home/thebears/.local/lib/python3.10/site-packages/open_clip/timm_model.py\", line 196, in forward\n x = self.trunk(x)\n File \"/home/thebears/.local/lib/python3.10/site-packages/torch/nn/modules/module.py\", line 1725, in _call_impl\n return forward_call(*args, **kwargs)\n File \"/home/thebears/.local/lib/python3.10/site-packages/timm/models/vision_transformer.py\", line 853, in forward\n x = self.forward_features(x)\n File \"/home/thebears/.local/lib/python3.10/site-packages/timm/models/vision_transformer.py\", line 834, in forward_features\n x = self.blocks(x)\n File \"/home/thebears/.local/lib/python3.10/site-packages/torch/nn/modules/module.py\", line 1725, in _call_impl\n return forward_call(*args, **kwargs)\n File \"/home/thebears/.local/lib/python3.10/site-packages/timm/models/vision_transformer.py\", line 169, in forward\n x = x + self.drop_path1(self.ls1(self.attn(self.norm1(x))))\n\n```\n## Return values\n", + "text":"FX Node: placeholder:getitem[name=getitem]. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"FxOnnxInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":414 + } + } + }, + { + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/open_clip/timm_model.py" + }, + "region":{ + "snippet":{ + "text":"x = self.trunk(x)" + }, + "startLine":196 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0008", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___0___attn_qkv_weight[name=p_getattr_l__self___trunk_blocks___0___attn_qkv_weight]. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature FxOnnxInterpreter.run_node\n- self: \n- node: fx.Node(p_getattr_l__self___trunk_blocks___0___attn_qkv_weight)[placeholder]:Tensor(f32[3072, 1024])\n- fx_graph_module: torch.fx.GraphModule(torch_nn_modules_linear_Linear)\n- onnxfunction_dispatcher: \n- op_level_debug: False\n- onnxscript_graph: \n- onnxscript_tracer: \n- fx_name_to_onnxscript_value: Dict[length=1](\ngetitem: `TorchScriptTensor(f32[4, 1024, 1024])`,\n)\n## Return values\n", + "text":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___0___attn_qkv_weight[name=p_getattr_l__self___trunk_blocks___0___attn_qkv_weight]. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"FxOnnxInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":414 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0008", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___0___attn_qkv_bias[name=p_getattr_l__self___trunk_blocks___0___attn_qkv_bias]. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature FxOnnxInterpreter.run_node\n- self: \n- node: fx.Node(p_getattr_l__self___trunk_blocks___0___attn_qkv_bias)[placeholder]:Tensor(f32[3072])\n- fx_graph_module: torch.fx.GraphModule(torch_nn_modules_linear_Linear)\n- onnxfunction_dispatcher: \n- op_level_debug: False\n- onnxscript_graph: \n- onnxscript_tracer: \n- fx_name_to_onnxscript_value: Dict[length=2](\ngetitem: `TorchScriptTensor(f32[4, 1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_weight: `TorchScriptTensor(f32[3072, 1024])`,\n)\n## Return values\n", + "text":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___0___attn_qkv_bias[name=p_getattr_l__self___trunk_blocks___0___attn_qkv_bias]. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"FxOnnxInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":414 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0008", + "stacks":[] + }, + { + "message":{ + "markdown":"Searching operator overload: 'aten.view.default' in onnx registry...\n\n\n## Additional Message:\n\n## Function Signature\n### Function Signature OnnxFunctionDispatcher.get_function_overloads\n- self: \n- node: fx.Node(aten.view.default)[call_function]:Tensor(f32[4096, 1024])\n- diagnostic_context: \n## Return values\nList[length=1](\nregistration.ONNXFunction(aten::view.default, is_custom=False, is_complex=False),\n)", + "text":"Searching operator overload: 'aten.view.default' in onnx registry...\n" + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"OnnxFunctionDispatcher.get_function_overloads" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/onnxfunction_dispatcher.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":353 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0016", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Node: aten.view.default. \nONNX Node: aten_view[opset=pkg.onnxscript.torch_lib;is_custom=False]. \n\n\n## Additional Message:\n\n## Function Signature\n### Function Signature OnnxFunctionDispatcher._find_the_perfect_or_nearest_match_onnxfunction\n- self: \n- node: fx.Node(aten.view.default)[call_function]:Tensor(f32[4096, 1024])\n- default_and_custom_functions: List[length=1](\nregistration.ONNXFunction(aten::view.default, is_custom=False, is_complex=False),\n)\n- onnx_args: Tuple[length=2](\n`TorchScriptTensor(f32[4, 1024, 1024])`,\nList[length=2](\n4096,\n1024,\n),\n)\n- onnx_kwargs: Dict[length=0](\nNone)\n- diagnostic_context: \n## Checking perfect match...\n`TracedOnnxFunction(aten_view)`\nmatch score: 2\n## Return values\n`TracedOnnxFunction(aten_view)`", + "text":"FX Node: aten.view.default. \nONNX Node: aten_view[opset=pkg.onnxscript.torch_lib;is_custom=False]. \n" + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"OnnxFunctionDispatcher._find_the_perfect_or_nearest_match_onnxfunction" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/onnxfunction_dispatcher.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":199 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0014", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Node: call_function:aten.view.default[name=view_1]. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature FxOnnxInterpreter.run_node\n- self: \n- node: fx.Node(aten.view.default)[call_function]:Tensor(f32[4096, 1024])\n- fx_graph_module: torch.fx.GraphModule(torch_nn_modules_linear_Linear)\n- onnxfunction_dispatcher: \n- op_level_debug: False\n- onnxscript_graph: \n- onnxscript_tracer: \n- fx_name_to_onnxscript_value: Dict[length=3](\ngetitem: `TorchScriptTensor(f32[4, 1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_weight: `TorchScriptTensor(f32[3072, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_bias: `TorchScriptTensor(f32[3072])`,\n)\n## PyTorch source information\n```\n File \"/home/thebears/.local/lib/python3.10/site-packages/open_clip/timm_model.py\", line 196, in forward\n x = self.trunk(x)\n File \"/home/thebears/.local/lib/python3.10/site-packages/torch/nn/modules/module.py\", line 1725, in _call_impl\n return forward_call(*args, **kwargs)\n File \"/home/thebears/.local/lib/python3.10/site-packages/timm/models/vision_transformer.py\", line 853, in forward\n x = self.forward_features(x)\n File \"/home/thebears/.local/lib/python3.10/site-packages/timm/models/vision_transformer.py\", line 834, in forward_features\n x = self.blocks(x)\n File \"/home/thebears/.local/lib/python3.10/site-packages/torch/nn/modules/module.py\", line 1725, in _call_impl\n return forward_call(*args, **kwargs)\n File \"/home/thebears/.local/lib/python3.10/site-packages/timm/models/vision_transformer.py\", line 169, in forward\n x = x + self.drop_path1(self.ls1(self.attn(self.norm1(x))))\n File \"/home/thebears/.local/lib/python3.10/site-packages/torch/nn/modules/module.py\", line 1725, in _call_impl\n return forward_call(*args, **kwargs)\n File \"/home/thebears/.local/lib/python3.10/site-packages/timm/models/vision_transformer.py\", line 88, in forward\n qkv = self.qkv(x).reshape(B, N, 3, self.num_heads, self.head_dim).permute(2, 0, 3, 1, 4)\n\n```\n## Return values\n", + "text":"FX Node: call_function:aten.view.default[name=view_1]. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"FxOnnxInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":414 + } + } + }, + { + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/open_clip/timm_model.py" + }, + "region":{ + "snippet":{ + "text":"x = self.trunk(x)" + }, + "startLine":196 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0008", + "stacks":[] + }, + { + "message":{ + "markdown":"Searching operator overload: 'aten.t.default' in onnx registry...\n\n\n## Additional Message:\n\n## Function Signature\n### Function Signature OnnxFunctionDispatcher.get_function_overloads\n- self: \n- node: fx.Node(aten.t.default)[call_function]:Tensor(f32[1024, 3072])\n- diagnostic_context: \n## Return values\nList[length=1](\nregistration.ONNXFunction(aten::t.default, is_custom=False, is_complex=False),\n)", + "text":"Searching operator overload: 'aten.t.default' in onnx registry...\n" + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"OnnxFunctionDispatcher.get_function_overloads" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/onnxfunction_dispatcher.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":353 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0016", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Node: aten.t.default. \nONNX Node: aten_t[opset=pkg.onnxscript.torch_lib;is_custom=False]. \n\n\n## Additional Message:\n\n## Function Signature\n### Function Signature OnnxFunctionDispatcher._find_the_perfect_or_nearest_match_onnxfunction\n- self: \n- node: fx.Node(aten.t.default)[call_function]:Tensor(f32[1024, 3072])\n- default_and_custom_functions: List[length=1](\nregistration.ONNXFunction(aten::t.default, is_custom=False, is_complex=False),\n)\n- onnx_args: Tuple[length=1](\n`TorchScriptTensor(f32[3072, 1024])`,\n)\n- onnx_kwargs: Dict[length=0](\nNone)\n- diagnostic_context: \n## Checking perfect match...\n`TracedOnnxFunction(aten_t)`\nmatch score: 1\n## Return values\n`TracedOnnxFunction(aten_t)`", + "text":"FX Node: aten.t.default. \nONNX Node: aten_t[opset=pkg.onnxscript.torch_lib;is_custom=False]. \n" + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"OnnxFunctionDispatcher._find_the_perfect_or_nearest_match_onnxfunction" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/onnxfunction_dispatcher.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":199 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0014", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Node: call_function:aten.t.default[name=t]. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature FxOnnxInterpreter.run_node\n- self: \n- node: fx.Node(aten.t.default)[call_function]:Tensor(f32[1024, 3072])\n- fx_graph_module: torch.fx.GraphModule(torch_nn_modules_linear_Linear)\n- onnxfunction_dispatcher: \n- op_level_debug: False\n- onnxscript_graph: \n- onnxscript_tracer: \n- fx_name_to_onnxscript_value: Dict[length=4](\ngetitem: `TorchScriptTensor(f32[4, 1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_weight: `TorchScriptTensor(f32[3072, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_bias: `TorchScriptTensor(f32[3072])`,\nview_1: `TorchScriptTensor(f32[4096, 1024])`,\n)\n## PyTorch source information\n```\n File \"/home/thebears/.local/lib/python3.10/site-packages/open_clip/timm_model.py\", line 196, in forward\n x = self.trunk(x)\n File \"/home/thebears/.local/lib/python3.10/site-packages/torch/nn/modules/module.py\", line 1725, in _call_impl\n return forward_call(*args, **kwargs)\n File \"/home/thebears/.local/lib/python3.10/site-packages/timm/models/vision_transformer.py\", line 853, in forward\n x = self.forward_features(x)\n File \"/home/thebears/.local/lib/python3.10/site-packages/timm/models/vision_transformer.py\", line 834, in forward_features\n x = self.blocks(x)\n File \"/home/thebears/.local/lib/python3.10/site-packages/torch/nn/modules/module.py\", line 1725, in _call_impl\n return forward_call(*args, **kwargs)\n File \"/home/thebears/.local/lib/python3.10/site-packages/timm/models/vision_transformer.py\", line 169, in forward\n x = x + self.drop_path1(self.ls1(self.attn(self.norm1(x))))\n File \"/home/thebears/.local/lib/python3.10/site-packages/torch/nn/modules/module.py\", line 1725, in _call_impl\n return forward_call(*args, **kwargs)\n File \"/home/thebears/.local/lib/python3.10/site-packages/timm/models/vision_transformer.py\", line 88, in forward\n qkv = self.qkv(x).reshape(B, N, 3, self.num_heads, self.head_dim).permute(2, 0, 3, 1, 4)\n\n```\n## Return values\n", + "text":"FX Node: call_function:aten.t.default[name=t]. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"FxOnnxInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":414 + } + } + }, + { + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/open_clip/timm_model.py" + }, + "region":{ + "snippet":{ + "text":"x = self.trunk(x)" + }, + "startLine":196 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0008", + "stacks":[] + }, + { + "message":{ + "markdown":"Searching operator overload: 'aten.addmm.default' in onnx registry...\n\n\n## Additional Message:\n\n## Function Signature\n### Function Signature OnnxFunctionDispatcher.get_function_overloads\n- self: \n- node: fx.Node(aten.addmm.default)[call_function]:Tensor(f32[4096, 3072])\n- diagnostic_context: \n## Return values\nList[length=1](\nregistration.ONNXFunction(aten::addmm.default, is_custom=False, is_complex=False),\n)", + "text":"Searching operator overload: 'aten.addmm.default' in onnx registry...\n" + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"OnnxFunctionDispatcher.get_function_overloads" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/onnxfunction_dispatcher.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":353 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0016", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Node: aten.addmm.default. \nONNX Node: aten_addmm[opset=pkg.onnxscript.torch_lib;is_custom=False]. \n\n\n## Additional Message:\n\n## Function Signature\n### Function Signature OnnxFunctionDispatcher._find_the_perfect_or_nearest_match_onnxfunction\n- self: \n- node: fx.Node(aten.addmm.default)[call_function]:Tensor(f32[4096, 3072])\n- default_and_custom_functions: List[length=1](\nregistration.ONNXFunction(aten::addmm.default, is_custom=False, is_complex=False),\n)\n- onnx_args: Tuple[length=3](\n`TorchScriptTensor(f32[3072])`,\n`TorchScriptTensor(f32[4096, 1024])`,\n`TorchScriptTensor(f32[1024, 3072])`,\n)\n- onnx_kwargs: Dict[length=2](\nbeta: 1,\nalpha: 1,\n)\n- diagnostic_context: \n## Checking perfect match...\n`TracedOnnxFunction(aten_addmm)`\n### Failed: attribute 'beta' type mismatch!\nActual vs\nExpected AttrType.FLOAT\n### Failed: attribute 'alpha' type mismatch!\nActual vs\nExpected AttrType.FLOAT\nmatch score: 1\n### Exact match is not found!\nCannot find a perfect match of symbolic overload, a nearest match is found. Please check the ONNX output carefully. \n\n## Return values\n`TracedOnnxFunction(aten_addmm)`", + "text":"FX Node: aten.addmm.default. \nONNX Node: aten_addmm[opset=pkg.onnxscript.torch_lib;is_custom=False]. \n" + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"fail", + "level":"warning", + "locations":[ + { + "message":{ + "text":"OnnxFunctionDispatcher._find_the_perfect_or_nearest_match_onnxfunction" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/onnxfunction_dispatcher.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":199 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0014", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Node: call_function:aten.addmm.default[name=addmm]. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature FxOnnxInterpreter.run_node\n- self: \n- node: fx.Node(aten.addmm.default)[call_function]:Tensor(f32[4096, 3072])\n- fx_graph_module: torch.fx.GraphModule(torch_nn_modules_linear_Linear)\n- onnxfunction_dispatcher: \n- op_level_debug: False\n- onnxscript_graph: \n- onnxscript_tracer: \n- fx_name_to_onnxscript_value: Dict[length=5](\ngetitem: `TorchScriptTensor(f32[4, 1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_weight: `TorchScriptTensor(f32[3072, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_bias: `TorchScriptTensor(f32[3072])`,\nview_1: `TorchScriptTensor(f32[4096, 1024])`,\nt: `TorchScriptTensor(f32[1024, 3072])`,\n)\n## PyTorch source information\n```\n File \"/home/thebears/.local/lib/python3.10/site-packages/open_clip/timm_model.py\", line 196, in forward\n x = self.trunk(x)\n File \"/home/thebears/.local/lib/python3.10/site-packages/torch/nn/modules/module.py\", line 1725, in _call_impl\n return forward_call(*args, **kwargs)\n File \"/home/thebears/.local/lib/python3.10/site-packages/timm/models/vision_transformer.py\", line 853, in forward\n x = self.forward_features(x)\n File \"/home/thebears/.local/lib/python3.10/site-packages/timm/models/vision_transformer.py\", line 834, in forward_features\n x = self.blocks(x)\n File \"/home/thebears/.local/lib/python3.10/site-packages/torch/nn/modules/module.py\", line 1725, in _call_impl\n return forward_call(*args, **kwargs)\n File \"/home/thebears/.local/lib/python3.10/site-packages/timm/models/vision_transformer.py\", line 169, in forward\n x = x + self.drop_path1(self.ls1(self.attn(self.norm1(x))))\n File \"/home/thebears/.local/lib/python3.10/site-packages/torch/nn/modules/module.py\", line 1725, in _call_impl\n return forward_call(*args, **kwargs)\n File \"/home/thebears/.local/lib/python3.10/site-packages/timm/models/vision_transformer.py\", line 88, in forward\n qkv = self.qkv(x).reshape(B, N, 3, self.num_heads, self.head_dim).permute(2, 0, 3, 1, 4)\n\n```\n## Return values\n", + "text":"FX Node: call_function:aten.addmm.default[name=addmm]. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"FxOnnxInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":414 + } + } + }, + { + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/open_clip/timm_model.py" + }, + "region":{ + "snippet":{ + "text":"x = self.trunk(x)" + }, + "startLine":196 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0008", + "stacks":[] + }, + { + "message":{ + "markdown":"Searching operator overload: 'aten.view.default' in onnx registry...\n\n\n## Additional Message:\n\n## Function Signature\n### Function Signature OnnxFunctionDispatcher.get_function_overloads\n- self: \n- node: fx.Node(aten.view.default)[call_function]:Tensor(f32[4, 1024, 3072])\n- diagnostic_context: \n## Return values\nList[length=1](\nregistration.ONNXFunction(aten::view.default, is_custom=False, is_complex=False),\n)", + "text":"Searching operator overload: 'aten.view.default' in onnx registry...\n" + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"OnnxFunctionDispatcher.get_function_overloads" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/onnxfunction_dispatcher.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":353 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0016", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Node: aten.view.default. \nONNX Node: aten_view[opset=pkg.onnxscript.torch_lib;is_custom=False]. \n\n\n## Additional Message:\n\n## Function Signature\n### Function Signature OnnxFunctionDispatcher._find_the_perfect_or_nearest_match_onnxfunction\n- self: \n- node: fx.Node(aten.view.default)[call_function]:Tensor(f32[4, 1024, 3072])\n- default_and_custom_functions: List[length=1](\nregistration.ONNXFunction(aten::view.default, is_custom=False, is_complex=False),\n)\n- onnx_args: Tuple[length=2](\n`TorchScriptTensor(f32[4096, 3072])`,\nList[length=3](\n4,\n1024,\n3072,\n),\n)\n- onnx_kwargs: Dict[length=0](\nNone)\n- diagnostic_context: \n## Checking perfect match...\n`TracedOnnxFunction(aten_view)`\nmatch score: 2\n## Return values\n`TracedOnnxFunction(aten_view)`", + "text":"FX Node: aten.view.default. \nONNX Node: aten_view[opset=pkg.onnxscript.torch_lib;is_custom=False]. \n" + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"OnnxFunctionDispatcher._find_the_perfect_or_nearest_match_onnxfunction" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/onnxfunction_dispatcher.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":199 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0014", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Node: call_function:aten.view.default[name=view_2]. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature FxOnnxInterpreter.run_node\n- self: \n- node: fx.Node(aten.view.default)[call_function]:Tensor(f32[4, 1024, 3072])\n- fx_graph_module: torch.fx.GraphModule(torch_nn_modules_linear_Linear)\n- onnxfunction_dispatcher: \n- op_level_debug: False\n- onnxscript_graph: \n- onnxscript_tracer: \n- fx_name_to_onnxscript_value: Dict[length=6](\ngetitem: `TorchScriptTensor(f32[4, 1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_weight: `TorchScriptTensor(f32[3072, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_bias: `TorchScriptTensor(f32[3072])`,\nview_1: `TorchScriptTensor(f32[4096, 1024])`,\nt: `TorchScriptTensor(f32[1024, 3072])`,\naddmm: `TorchScriptTensor(f32[4096, 3072])`,\n)\n## PyTorch source information\n```\n File \"/home/thebears/.local/lib/python3.10/site-packages/open_clip/timm_model.py\", line 196, in forward\n x = self.trunk(x)\n File \"/home/thebears/.local/lib/python3.10/site-packages/torch/nn/modules/module.py\", line 1725, in _call_impl\n return forward_call(*args, **kwargs)\n File \"/home/thebears/.local/lib/python3.10/site-packages/timm/models/vision_transformer.py\", line 853, in forward\n x = self.forward_features(x)\n File \"/home/thebears/.local/lib/python3.10/site-packages/timm/models/vision_transformer.py\", line 834, in forward_features\n x = self.blocks(x)\n File \"/home/thebears/.local/lib/python3.10/site-packages/torch/nn/modules/module.py\", line 1725, in _call_impl\n return forward_call(*args, **kwargs)\n File \"/home/thebears/.local/lib/python3.10/site-packages/timm/models/vision_transformer.py\", line 169, in forward\n x = x + self.drop_path1(self.ls1(self.attn(self.norm1(x))))\n File \"/home/thebears/.local/lib/python3.10/site-packages/torch/nn/modules/module.py\", line 1725, in _call_impl\n return forward_call(*args, **kwargs)\n File \"/home/thebears/.local/lib/python3.10/site-packages/timm/models/vision_transformer.py\", line 88, in forward\n qkv = self.qkv(x).reshape(B, N, 3, self.num_heads, self.head_dim).permute(2, 0, 3, 1, 4)\n\n```\n## Return values\n", + "text":"FX Node: call_function:aten.view.default[name=view_2]. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"FxOnnxInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":414 + } + } + }, + { + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/open_clip/timm_model.py" + }, + "region":{ + "snippet":{ + "text":"x = self.trunk(x)" + }, + "startLine":196 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0008", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Node: output:output[name=output]. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature FxOnnxInterpreter.run_node\n- self: \n- node: fx.Node(output)[output]:None\n- fx_graph_module: torch.fx.GraphModule(torch_nn_modules_linear_Linear)\n- onnxfunction_dispatcher: \n- op_level_debug: False\n- onnxscript_graph: \n- onnxscript_tracer: \n- fx_name_to_onnxscript_value: Dict[length=7](\ngetitem: `TorchScriptTensor(f32[4, 1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_weight: `TorchScriptTensor(f32[3072, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_bias: `TorchScriptTensor(f32[3072])`,\nview_1: `TorchScriptTensor(f32[4096, 1024])`,\nt: `TorchScriptTensor(f32[1024, 3072])`,\naddmm: `TorchScriptTensor(f32[4096, 3072])`,\nview_2: `TorchScriptTensor(f32[4, 1024, 3072])`,\n)\n## Return values\n", + "text":"FX Node: output:output[name=output]. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"FxOnnxInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":414 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0008", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Graph: torch_nn_modules_linear_Linear. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature FxOnnxInterpreter.run\n- self: \n- fx_graph_module: torch.fx.GraphModule(torch_nn_modules_linear_Linear)\n- onnxfunction_dispatcher: \n- op_level_debug: False\n- parent_onnxscript_graph: \n## Return values\n", + "text":"FX Graph: torch_nn_modules_linear_Linear. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"FxOnnxInterpreter.run" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":496 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0007", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Node: call_module:getattr_L__self___trunk_blocks___0___attn_qkv_1[name=getattr_l__self___trunk_blocks___0___attn_qkv_1]. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature FxOnnxInterpreter.run_node\n- self: \n- node: fx.Node(getattr_L__self___trunk_blocks___0___attn_qkv_1)[call_module]:Tensor(f32[4, 1024, 3072])\n- fx_graph_module: torch.fx.GraphModule(timm_models_vision_transformer_Attention)\n- onnxfunction_dispatcher: \n- op_level_debug: False\n- onnxscript_graph: \n- onnxscript_tracer: \n- fx_name_to_onnxscript_value: Dict[length=5](\ngetitem: `TorchScriptTensor(f32[4, 1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_weight: `TorchScriptTensor(f32[3072, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_bias: `TorchScriptTensor(f32[3072])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_weight: `TorchScriptTensor(f32[1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_bias: `TorchScriptTensor(f32[1024])`,\n)\n## PyTorch source information\n```\n File \"/home/thebears/.local/lib/python3.10/site-packages/open_clip/timm_model.py\", line 196, in forward\n x = self.trunk(x)\n File \"/home/thebears/.local/lib/python3.10/site-packages/torch/nn/modules/module.py\", line 1725, in _call_impl\n return forward_call(*args, **kwargs)\n File \"/home/thebears/.local/lib/python3.10/site-packages/timm/models/vision_transformer.py\", line 853, in forward\n x = self.forward_features(x)\n File \"/home/thebears/.local/lib/python3.10/site-packages/timm/models/vision_transformer.py\", line 834, in forward_features\n x = self.blocks(x)\n File \"/home/thebears/.local/lib/python3.10/site-packages/torch/nn/modules/module.py\", line 1725, in _call_impl\n return forward_call(*args, **kwargs)\n File \"/home/thebears/.local/lib/python3.10/site-packages/timm/models/vision_transformer.py\", line 169, in forward\n x = x + self.drop_path1(self.ls1(self.attn(self.norm1(x))))\n File \"/home/thebears/.local/lib/python3.10/site-packages/torch/nn/modules/module.py\", line 1725, in _call_impl\n return forward_call(*args, **kwargs)\n File \"/home/thebears/.local/lib/python3.10/site-packages/timm/models/vision_transformer.py\", line 88, in forward\n qkv = self.qkv(x).reshape(B, N, 3, self.num_heads, self.head_dim).permute(2, 0, 3, 1, 4)\n\n```\n## Return values\n", + "text":"FX Node: call_module:getattr_L__self___trunk_blocks___0___attn_qkv_1[name=getattr_l__self___trunk_blocks___0___attn_qkv_1]. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"FxOnnxInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":414 + } + } + }, + { + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/open_clip/timm_model.py" + }, + "region":{ + "snippet":{ + "text":"x = self.trunk(x)" + }, + "startLine":196 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0008", + "stacks":[] + }, + { + "message":{ + "markdown":"Searching operator overload: 'aten.view.default' in onnx registry...\n\n\n## Additional Message:\n\n## Function Signature\n### Function Signature OnnxFunctionDispatcher.get_function_overloads\n- self: \n- node: fx.Node(aten.view.default)[call_function]:Tensor(f32[4, 1024, 3, 16, 64])\n- diagnostic_context: \n## Return values\nList[length=1](\nregistration.ONNXFunction(aten::view.default, is_custom=False, is_complex=False),\n)", + "text":"Searching operator overload: 'aten.view.default' in onnx registry...\n" + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"OnnxFunctionDispatcher.get_function_overloads" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/onnxfunction_dispatcher.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":353 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0016", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Node: aten.view.default. \nONNX Node: aten_view[opset=pkg.onnxscript.torch_lib;is_custom=False]. \n\n\n## Additional Message:\n\n## Function Signature\n### Function Signature OnnxFunctionDispatcher._find_the_perfect_or_nearest_match_onnxfunction\n- self: \n- node: fx.Node(aten.view.default)[call_function]:Tensor(f32[4, 1024, 3, 16, 64])\n- default_and_custom_functions: List[length=1](\nregistration.ONNXFunction(aten::view.default, is_custom=False, is_complex=False),\n)\n- onnx_args: Tuple[length=2](\n`TorchScriptTensor(f32[4, 1024, 3072])`,\nList[length=5](\n4,\n1024,\n3,\n16,\n64,\n),\n)\n- onnx_kwargs: Dict[length=0](\nNone)\n- diagnostic_context: \n## Checking perfect match...\n`TracedOnnxFunction(aten_view)`\nmatch score: 2\n## Return values\n`TracedOnnxFunction(aten_view)`", + "text":"FX Node: aten.view.default. \nONNX Node: aten_view[opset=pkg.onnxscript.torch_lib;is_custom=False]. \n" + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"OnnxFunctionDispatcher._find_the_perfect_or_nearest_match_onnxfunction" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/onnxfunction_dispatcher.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":199 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0014", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Node: call_function:aten.view.default[name=view_3]. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature FxOnnxInterpreter.run_node\n- self: \n- node: fx.Node(aten.view.default)[call_function]:Tensor(f32[4, 1024, 3, 16, 64])\n- fx_graph_module: torch.fx.GraphModule(timm_models_vision_transformer_Attention)\n- onnxfunction_dispatcher: \n- op_level_debug: False\n- onnxscript_graph: \n- onnxscript_tracer: \n- fx_name_to_onnxscript_value: Dict[length=6](\ngetitem: `TorchScriptTensor(f32[4, 1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_weight: `TorchScriptTensor(f32[3072, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_bias: `TorchScriptTensor(f32[3072])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_weight: `TorchScriptTensor(f32[1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_bias: `TorchScriptTensor(f32[1024])`,\ngetattr_l__self___trunk_blocks___0___attn_qkv_1: `TorchScriptTensor(f32[4, 1024, 3072])`,\n)\n## PyTorch source information\n```\n File \"/home/thebears/.local/lib/python3.10/site-packages/open_clip/timm_model.py\", line 196, in forward\n x = self.trunk(x)\n File \"/home/thebears/.local/lib/python3.10/site-packages/torch/nn/modules/module.py\", line 1725, in _call_impl\n return forward_call(*args, **kwargs)\n File \"/home/thebears/.local/lib/python3.10/site-packages/timm/models/vision_transformer.py\", line 853, in forward\n x = self.forward_features(x)\n File \"/home/thebears/.local/lib/python3.10/site-packages/timm/models/vision_transformer.py\", line 834, in forward_features\n x = self.blocks(x)\n File \"/home/thebears/.local/lib/python3.10/site-packages/torch/nn/modules/module.py\", line 1725, in _call_impl\n return forward_call(*args, **kwargs)\n File \"/home/thebears/.local/lib/python3.10/site-packages/timm/models/vision_transformer.py\", line 169, in forward\n x = x + self.drop_path1(self.ls1(self.attn(self.norm1(x))))\n File \"/home/thebears/.local/lib/python3.10/site-packages/torch/nn/modules/module.py\", line 1725, in _call_impl\n return forward_call(*args, **kwargs)\n File \"/home/thebears/.local/lib/python3.10/site-packages/timm/models/vision_transformer.py\", line 88, in forward\n qkv = self.qkv(x).reshape(B, N, 3, self.num_heads, self.head_dim).permute(2, 0, 3, 1, 4)\n\n```\n## Return values\n", + "text":"FX Node: call_function:aten.view.default[name=view_3]. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"FxOnnxInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":414 + } + } + }, + { + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/open_clip/timm_model.py" + }, + "region":{ + "snippet":{ + "text":"x = self.trunk(x)" + }, + "startLine":196 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0008", + "stacks":[] + }, + { + "message":{ + "markdown":"Searching operator overload: 'aten.permute.default' in onnx registry...\n\n\n## Additional Message:\n\n## Function Signature\n### Function Signature OnnxFunctionDispatcher.get_function_overloads\n- self: \n- node: fx.Node(aten.permute.default)[call_function]:Tensor(f32[3, 4, 16, 1024, 64])\n- diagnostic_context: \n## Return values\nList[length=1](\nregistration.ONNXFunction(aten::permute.default, is_custom=False, is_complex=False),\n)", + "text":"Searching operator overload: 'aten.permute.default' in onnx registry...\n" + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"OnnxFunctionDispatcher.get_function_overloads" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/onnxfunction_dispatcher.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":353 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0016", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Node: aten.permute.default. \nONNX Node: aten_permute[opset=pkg.onnxscript.torch_lib;is_custom=False]. \n\n\n## Additional Message:\n\n## Function Signature\n### Function Signature OnnxFunctionDispatcher._find_the_perfect_or_nearest_match_onnxfunction\n- self: \n- node: fx.Node(aten.permute.default)[call_function]:Tensor(f32[3, 4, 16, 1024, 64])\n- default_and_custom_functions: List[length=1](\nregistration.ONNXFunction(aten::permute.default, is_custom=False, is_complex=False),\n)\n- onnx_args: Tuple[length=2](\n`TorchScriptTensor(f32[4, 1024, 3, 16, 64])`,\nList[length=5](\n2,\n0,\n3,\n1,\n4,\n),\n)\n- onnx_kwargs: Dict[length=0](\nNone)\n- diagnostic_context: \n## Checking perfect match...\n`TracedOnnxFunction(aten_permute)`\nmatch score: 0\n## Return values\n`TracedOnnxFunction(aten_permute)`", + "text":"FX Node: aten.permute.default. \nONNX Node: aten_permute[opset=pkg.onnxscript.torch_lib;is_custom=False]. \n" + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"OnnxFunctionDispatcher._find_the_perfect_or_nearest_match_onnxfunction" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/onnxfunction_dispatcher.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":199 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0014", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Node: call_function:aten.permute.default[name=permute]. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature FxOnnxInterpreter.run_node\n- self: \n- node: fx.Node(aten.permute.default)[call_function]:Tensor(f32[3, 4, 16, 1024, 64])\n- fx_graph_module: torch.fx.GraphModule(timm_models_vision_transformer_Attention)\n- onnxfunction_dispatcher: \n- op_level_debug: False\n- onnxscript_graph: \n- onnxscript_tracer: \n- fx_name_to_onnxscript_value: Dict[length=7](\ngetitem: `TorchScriptTensor(f32[4, 1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_weight: `TorchScriptTensor(f32[3072, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_bias: `TorchScriptTensor(f32[3072])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_weight: `TorchScriptTensor(f32[1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_bias: `TorchScriptTensor(f32[1024])`,\ngetattr_l__self___trunk_blocks___0___attn_qkv_1: `TorchScriptTensor(f32[4, 1024, 3072])`,\nview_3: `TorchScriptTensor(f32[4, 1024, 3, 16, 64])`,\n)\n## PyTorch source information\n```\n File \"/home/thebears/.local/lib/python3.10/site-packages/open_clip/timm_model.py\", line 196, in forward\n x = self.trunk(x)\n File \"/home/thebears/.local/lib/python3.10/site-packages/torch/nn/modules/module.py\", line 1725, in _call_impl\n return forward_call(*args, **kwargs)\n File \"/home/thebears/.local/lib/python3.10/site-packages/timm/models/vision_transformer.py\", line 853, in forward\n x = self.forward_features(x)\n File \"/home/thebears/.local/lib/python3.10/site-packages/timm/models/vision_transformer.py\", line 834, in forward_features\n x = self.blocks(x)\n File \"/home/thebears/.local/lib/python3.10/site-packages/torch/nn/modules/module.py\", line 1725, in _call_impl\n return forward_call(*args, **kwargs)\n File \"/home/thebears/.local/lib/python3.10/site-packages/timm/models/vision_transformer.py\", line 169, in forward\n x = x + self.drop_path1(self.ls1(self.attn(self.norm1(x))))\n File \"/home/thebears/.local/lib/python3.10/site-packages/torch/nn/modules/module.py\", line 1725, in _call_impl\n return forward_call(*args, **kwargs)\n File \"/home/thebears/.local/lib/python3.10/site-packages/timm/models/vision_transformer.py\", line 88, in forward\n qkv = self.qkv(x).reshape(B, N, 3, self.num_heads, self.head_dim).permute(2, 0, 3, 1, 4)\n\n```\n## Return values\n", + "text":"FX Node: call_function:aten.permute.default[name=permute]. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"FxOnnxInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":414 + } + } + }, + { + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/open_clip/timm_model.py" + }, + "region":{ + "snippet":{ + "text":"x = self.trunk(x)" + }, + "startLine":196 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0008", + "stacks":[] + }, + { + "message":{ + "markdown":"Searching operator overload: 'aten.unbind.int' in onnx registry...\n\n\n## Additional Message:\n\n## Function Signature\n### Function Signature OnnxFunctionDispatcher.get_function_overloads\n- self: \n- node: fx.Node(aten.unbind.int)[call_function]:List[length=3](\nTensor(f32[4, 16, 1024, 64]),\nTensor(f32[4, 16, 1024, 64]),\nTensor(f32[4, 16, 1024, 64]),\n)\n- diagnostic_context: \n## Return values\nList[length=1](\nregistration.ONNXFunction(aten::unbind.int, is_custom=False, is_complex=False),\n)", + "text":"Searching operator overload: 'aten.unbind.int' in onnx registry...\n" + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"OnnxFunctionDispatcher.get_function_overloads" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/onnxfunction_dispatcher.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":353 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0016", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Node: aten.unbind.int. \nONNX Node: aten_unbind[opset=pkg.onnxscript.torch_lib;is_custom=False]. \n\n\n## Additional Message:\n\n## Function Signature\n### Function Signature OnnxFunctionDispatcher._find_the_perfect_or_nearest_match_onnxfunction\n- self: \n- node: fx.Node(aten.unbind.int)[call_function]:List[length=3](\nTensor(f32[4, 16, 1024, 64]),\nTensor(f32[4, 16, 1024, 64]),\nTensor(f32[4, 16, 1024, 64]),\n)\n- default_and_custom_functions: List[length=1](\nregistration.ONNXFunction(aten::unbind.int, is_custom=False, is_complex=False),\n)\n- onnx_args: Tuple[length=1](\n`TorchScriptTensor(f32[3, 4, 16, 1024, 64])`,\n)\n- onnx_kwargs: Dict[length=1](\ndim: 0,\n)\n- diagnostic_context: \n## Checking perfect match...\n`OnnxFunction(aten_unbind)`\nmatch score: 1\n## Return values\n`OnnxFunction(aten_unbind)`", + "text":"FX Node: aten.unbind.int. \nONNX Node: aten_unbind[opset=pkg.onnxscript.torch_lib;is_custom=False]. \n" + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"OnnxFunctionDispatcher._find_the_perfect_or_nearest_match_onnxfunction" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/onnxfunction_dispatcher.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":199 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0014", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Node: call_function:aten.unbind.int[name=unbind]. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature FxOnnxInterpreter.run_node\n- self: \n- node: fx.Node(aten.unbind.int)[call_function]:List[length=3](\nTensor(f32[4, 16, 1024, 64]),\nTensor(f32[4, 16, 1024, 64]),\nTensor(f32[4, 16, 1024, 64]),\n)\n- fx_graph_module: torch.fx.GraphModule(timm_models_vision_transformer_Attention)\n- onnxfunction_dispatcher: \n- op_level_debug: False\n- onnxscript_graph: \n- onnxscript_tracer: \n- fx_name_to_onnxscript_value: Dict[length=8](\ngetitem: `TorchScriptTensor(f32[4, 1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_weight: `TorchScriptTensor(f32[3072, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_bias: `TorchScriptTensor(f32[3072])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_weight: `TorchScriptTensor(f32[1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_bias: `TorchScriptTensor(f32[1024])`,\ngetattr_l__self___trunk_blocks___0___attn_qkv_1: `TorchScriptTensor(f32[4, 1024, 3072])`,\nview_3: `TorchScriptTensor(f32[4, 1024, 3, 16, 64])`,\npermute: `TorchScriptTensor(f32[3, 4, 16, 1024, 64])`,\n)\n## PyTorch source information\n```\n File \"/home/thebears/.local/lib/python3.10/site-packages/open_clip/timm_model.py\", line 196, in forward\n x = self.trunk(x)\n File \"/home/thebears/.local/lib/python3.10/site-packages/torch/nn/modules/module.py\", line 1725, in _call_impl\n return forward_call(*args, **kwargs)\n File \"/home/thebears/.local/lib/python3.10/site-packages/timm/models/vision_transformer.py\", line 853, in forward\n x = self.forward_features(x)\n File \"/home/thebears/.local/lib/python3.10/site-packages/timm/models/vision_transformer.py\", line 834, in forward_features\n x = self.blocks(x)\n File \"/home/thebears/.local/lib/python3.10/site-packages/torch/nn/modules/module.py\", line 1725, in _call_impl\n return forward_call(*args, **kwargs)\n File \"/home/thebears/.local/lib/python3.10/site-packages/timm/models/vision_transformer.py\", line 169, in forward\n x = x + self.drop_path1(self.ls1(self.attn(self.norm1(x))))\n File \"/home/thebears/.local/lib/python3.10/site-packages/torch/nn/modules/module.py\", line 1725, in _call_impl\n return forward_call(*args, **kwargs)\n File \"/home/thebears/.local/lib/python3.10/site-packages/timm/models/vision_transformer.py\", line 89, in forward\n q, k, v = qkv.unbind(0)\n\n```\n## Return values\n", + "text":"FX Node: call_function:aten.unbind.int[name=unbind]. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"FxOnnxInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":414 + } + } + }, + { + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/open_clip/timm_model.py" + }, + "region":{ + "snippet":{ + "text":"x = self.trunk(x)" + }, + "startLine":196 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0008", + "stacks":[] + }, + { + "message":{ + "markdown":"Searching operator overload: '' in onnx registry...\n\n\n## Additional Message:\n\n## Function Signature\n### Function Signature OnnxFunctionDispatcher.get_function_overloads\n- self: \n- node: fx.Node()[call_function]:Tensor(f32[4, 16, 1024, 64])\n- diagnostic_context: \n## Return values\nList[length=1](\nregistration.ONNXFunction(aten::getitem.default, is_custom=False, is_complex=False),\n)", + "text":"Searching operator overload: '' in onnx registry...\n" + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"OnnxFunctionDispatcher.get_function_overloads" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/onnxfunction_dispatcher.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":353 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0016", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Node: . \nONNX Node: aten_getitem[opset=pkg.onnxscript.torch_lib;is_custom=False]. \n\n\n## Additional Message:\n\n## Function Signature\n### Function Signature OnnxFunctionDispatcher._find_the_perfect_or_nearest_match_onnxfunction\n- self: \n- node: fx.Node()[call_function]:Tensor(f32[4, 16, 1024, 64])\n- default_and_custom_functions: List[length=1](\nregistration.ONNXFunction(aten::getitem.default, is_custom=False, is_complex=False),\n)\n- onnx_args: Tuple[length=2](\n`TorchScriptTensor()`,\n0,\n)\n- onnx_kwargs: Dict[length=0](\nNone)\n- diagnostic_context: \n## Checking perfect match...\n`OnnxFunction(aten_getitem)`\n### Failed: input type mismatch for input 'self'!\nActual set() vs\nExpected {'seq(tensor(int8))', 'seq(tensor(complex64))', 'seq(tensor(complex128))', 'seq(tensor(int32))', 'seq(tensor(bfloat16))', 'seq(tensor(float))', 'seq(tensor(int64))', 'seq(tensor(int16))', 'seq(tensor(bool))', 'seq(tensor(uint8))', 'seq(tensor(float16))', 'seq(tensor(double))'}\nmatch score: 1\n### Exact match is not found!\nCannot find a perfect match of symbolic overload, a nearest match is found. Please check the ONNX output carefully. \n\n## Return values\n`OnnxFunction(aten_getitem)`", + "text":"FX Node: . \nONNX Node: aten_getitem[opset=pkg.onnxscript.torch_lib;is_custom=False]. \n" + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"fail", + "level":"warning", + "locations":[ + { + "message":{ + "text":"OnnxFunctionDispatcher._find_the_perfect_or_nearest_match_onnxfunction" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/onnxfunction_dispatcher.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":199 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0014", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Node: call_function:[name=getitem_3]. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature FxOnnxInterpreter.run_node\n- self: \n- node: fx.Node()[call_function]:Tensor(f32[4, 16, 1024, 64])\n- fx_graph_module: torch.fx.GraphModule(timm_models_vision_transformer_Attention)\n- onnxfunction_dispatcher: \n- op_level_debug: False\n- onnxscript_graph: \n- onnxscript_tracer: \n- fx_name_to_onnxscript_value: Dict[length=9](\ngetitem: `TorchScriptTensor(f32[4, 1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_weight: `TorchScriptTensor(f32[3072, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_bias: `TorchScriptTensor(f32[3072])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_weight: `TorchScriptTensor(f32[1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_bias: `TorchScriptTensor(f32[1024])`,\ngetattr_l__self___trunk_blocks___0___attn_qkv_1: `TorchScriptTensor(f32[4, 1024, 3072])`,\nview_3: `TorchScriptTensor(f32[4, 1024, 3, 16, 64])`,\npermute: `TorchScriptTensor(f32[3, 4, 16, 1024, 64])`,\nunbind: `TorchScriptTensor()`,\n)\n## PyTorch source information\n```\n File \"/home/thebears/.local/lib/python3.10/site-packages/open_clip/timm_model.py\", line 196, in forward\n x = self.trunk(x)\n File \"/home/thebears/.local/lib/python3.10/site-packages/torch/nn/modules/module.py\", line 1725, in _call_impl\n return forward_call(*args, **kwargs)\n File \"/home/thebears/.local/lib/python3.10/site-packages/timm/models/vision_transformer.py\", line 853, in forward\n x = self.forward_features(x)\n File \"/home/thebears/.local/lib/python3.10/site-packages/timm/models/vision_transformer.py\", line 834, in forward_features\n x = self.blocks(x)\n File \"/home/thebears/.local/lib/python3.10/site-packages/torch/nn/modules/module.py\", line 1725, in _call_impl\n return forward_call(*args, **kwargs)\n File \"/home/thebears/.local/lib/python3.10/site-packages/timm/models/vision_transformer.py\", line 169, in forward\n x = x + self.drop_path1(self.ls1(self.attn(self.norm1(x))))\n File \"/home/thebears/.local/lib/python3.10/site-packages/torch/nn/modules/module.py\", line 1725, in _call_impl\n return forward_call(*args, **kwargs)\n File \"/home/thebears/.local/lib/python3.10/site-packages/timm/models/vision_transformer.py\", line 89, in forward\n q, k, v = qkv.unbind(0)\n\n```\n## Return values\n", + "text":"FX Node: call_function:[name=getitem_3]. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"FxOnnxInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":414 + } + } + }, + { + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/open_clip/timm_model.py" + }, + "region":{ + "snippet":{ + "text":"x = self.trunk(x)" + }, + "startLine":196 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0008", + "stacks":[] + }, + { + "message":{ + "markdown":"Searching operator overload: '' in onnx registry...\n\n\n## Additional Message:\n\n## Function Signature\n### Function Signature OnnxFunctionDispatcher.get_function_overloads\n- self: \n- node: fx.Node()[call_function]:Tensor(f32[4, 16, 1024, 64])\n- diagnostic_context: \n## Return values\nList[length=1](\nregistration.ONNXFunction(aten::getitem.default, is_custom=False, is_complex=False),\n)", + "text":"Searching operator overload: '' in onnx registry...\n" + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"OnnxFunctionDispatcher.get_function_overloads" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/onnxfunction_dispatcher.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":353 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0016", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Node: . \nONNX Node: aten_getitem[opset=pkg.onnxscript.torch_lib;is_custom=False]. \n\n\n## Additional Message:\n\n## Function Signature\n### Function Signature OnnxFunctionDispatcher._find_the_perfect_or_nearest_match_onnxfunction\n- self: \n- node: fx.Node()[call_function]:Tensor(f32[4, 16, 1024, 64])\n- default_and_custom_functions: List[length=1](\nregistration.ONNXFunction(aten::getitem.default, is_custom=False, is_complex=False),\n)\n- onnx_args: Tuple[length=2](\n`TorchScriptTensor()`,\n1,\n)\n- onnx_kwargs: Dict[length=0](\nNone)\n- diagnostic_context: \n## Checking perfect match...\n`OnnxFunction(aten_getitem)`\n### Failed: input type mismatch for input 'self'!\nActual set() vs\nExpected {'seq(tensor(int8))', 'seq(tensor(complex64))', 'seq(tensor(complex128))', 'seq(tensor(int32))', 'seq(tensor(bfloat16))', 'seq(tensor(float))', 'seq(tensor(int64))', 'seq(tensor(int16))', 'seq(tensor(bool))', 'seq(tensor(uint8))', 'seq(tensor(float16))', 'seq(tensor(double))'}\nmatch score: 1\n### Exact match is not found!\nCannot find a perfect match of symbolic overload, a nearest match is found. Please check the ONNX output carefully. \n\n## Return values\n`OnnxFunction(aten_getitem)`", + "text":"FX Node: . \nONNX Node: aten_getitem[opset=pkg.onnxscript.torch_lib;is_custom=False]. \n" + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"fail", + "level":"warning", + "locations":[ + { + "message":{ + "text":"OnnxFunctionDispatcher._find_the_perfect_or_nearest_match_onnxfunction" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/onnxfunction_dispatcher.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":199 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0014", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Node: call_function:[name=getitem_4]. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature FxOnnxInterpreter.run_node\n- self: \n- node: fx.Node()[call_function]:Tensor(f32[4, 16, 1024, 64])\n- fx_graph_module: torch.fx.GraphModule(timm_models_vision_transformer_Attention)\n- onnxfunction_dispatcher: \n- op_level_debug: False\n- onnxscript_graph: \n- onnxscript_tracer: \n- fx_name_to_onnxscript_value: Dict[length=10](\ngetitem: `TorchScriptTensor(f32[4, 1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_weight: `TorchScriptTensor(f32[3072, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_bias: `TorchScriptTensor(f32[3072])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_weight: `TorchScriptTensor(f32[1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_bias: `TorchScriptTensor(f32[1024])`,\ngetattr_l__self___trunk_blocks___0___attn_qkv_1: `TorchScriptTensor(f32[4, 1024, 3072])`,\nview_3: `TorchScriptTensor(f32[4, 1024, 3, 16, 64])`,\npermute: `TorchScriptTensor(f32[3, 4, 16, 1024, 64])`,\nunbind: `TorchScriptTensor()`,\ngetitem_3: `TorchScriptTensor(f32[4, 16, 1024, 64])`,\n)\n## PyTorch source information\n```\n File \"/home/thebears/.local/lib/python3.10/site-packages/open_clip/timm_model.py\", line 196, in forward\n x = self.trunk(x)\n File \"/home/thebears/.local/lib/python3.10/site-packages/torch/nn/modules/module.py\", line 1725, in _call_impl\n return forward_call(*args, **kwargs)\n File \"/home/thebears/.local/lib/python3.10/site-packages/timm/models/vision_transformer.py\", line 853, in forward\n x = self.forward_features(x)\n File \"/home/thebears/.local/lib/python3.10/site-packages/timm/models/vision_transformer.py\", line 834, in forward_features\n x = self.blocks(x)\n File \"/home/thebears/.local/lib/python3.10/site-packages/torch/nn/modules/module.py\", line 1725, in _call_impl\n return forward_call(*args, **kwargs)\n File \"/home/thebears/.local/lib/python3.10/site-packages/timm/models/vision_transformer.py\", line 169, in forward\n x = x + self.drop_path1(self.ls1(self.attn(self.norm1(x))))\n File \"/home/thebears/.local/lib/python3.10/site-packages/torch/nn/modules/module.py\", line 1725, in _call_impl\n return forward_call(*args, **kwargs)\n File \"/home/thebears/.local/lib/python3.10/site-packages/timm/models/vision_transformer.py\", line 89, in forward\n q, k, v = qkv.unbind(0)\n\n```\n## Return values\n", + "text":"FX Node: call_function:[name=getitem_4]. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"FxOnnxInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":414 + } + } + }, + { + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/open_clip/timm_model.py" + }, + "region":{ + "snippet":{ + "text":"x = self.trunk(x)" + }, + "startLine":196 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0008", + "stacks":[] + }, + { + "message":{ + "markdown":"Searching operator overload: '' in onnx registry...\n\n\n## Additional Message:\n\n## Function Signature\n### Function Signature OnnxFunctionDispatcher.get_function_overloads\n- self: \n- node: fx.Node()[call_function]:Tensor(f32[4, 16, 1024, 64])\n- diagnostic_context: \n## Return values\nList[length=1](\nregistration.ONNXFunction(aten::getitem.default, is_custom=False, is_complex=False),\n)", + "text":"Searching operator overload: '' in onnx registry...\n" + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"OnnxFunctionDispatcher.get_function_overloads" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/onnxfunction_dispatcher.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":353 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0016", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Node: . \nONNX Node: aten_getitem[opset=pkg.onnxscript.torch_lib;is_custom=False]. \n\n\n## Additional Message:\n\n## Function Signature\n### Function Signature OnnxFunctionDispatcher._find_the_perfect_or_nearest_match_onnxfunction\n- self: \n- node: fx.Node()[call_function]:Tensor(f32[4, 16, 1024, 64])\n- default_and_custom_functions: List[length=1](\nregistration.ONNXFunction(aten::getitem.default, is_custom=False, is_complex=False),\n)\n- onnx_args: Tuple[length=2](\n`TorchScriptTensor()`,\n2,\n)\n- onnx_kwargs: Dict[length=0](\nNone)\n- diagnostic_context: \n## Checking perfect match...\n`OnnxFunction(aten_getitem)`\n### Failed: input type mismatch for input 'self'!\nActual set() vs\nExpected {'seq(tensor(int8))', 'seq(tensor(complex64))', 'seq(tensor(complex128))', 'seq(tensor(int32))', 'seq(tensor(bfloat16))', 'seq(tensor(float))', 'seq(tensor(int64))', 'seq(tensor(int16))', 'seq(tensor(bool))', 'seq(tensor(uint8))', 'seq(tensor(float16))', 'seq(tensor(double))'}\nmatch score: 1\n### Exact match is not found!\nCannot find a perfect match of symbolic overload, a nearest match is found. Please check the ONNX output carefully. \n\n## Return values\n`OnnxFunction(aten_getitem)`", + "text":"FX Node: . \nONNX Node: aten_getitem[opset=pkg.onnxscript.torch_lib;is_custom=False]. \n" + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"fail", + "level":"warning", + "locations":[ + { + "message":{ + "text":"OnnxFunctionDispatcher._find_the_perfect_or_nearest_match_onnxfunction" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/onnxfunction_dispatcher.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":199 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0014", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Node: call_function:[name=getitem_5]. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature FxOnnxInterpreter.run_node\n- self: \n- node: fx.Node()[call_function]:Tensor(f32[4, 16, 1024, 64])\n- fx_graph_module: torch.fx.GraphModule(timm_models_vision_transformer_Attention)\n- onnxfunction_dispatcher: \n- op_level_debug: False\n- onnxscript_graph: \n- onnxscript_tracer: \n- fx_name_to_onnxscript_value: Dict[length=11](\ngetitem: `TorchScriptTensor(f32[4, 1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_weight: `TorchScriptTensor(f32[3072, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_bias: `TorchScriptTensor(f32[3072])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_weight: `TorchScriptTensor(f32[1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_bias: `TorchScriptTensor(f32[1024])`,\ngetattr_l__self___trunk_blocks___0___attn_qkv_1: `TorchScriptTensor(f32[4, 1024, 3072])`,\nview_3: `TorchScriptTensor(f32[4, 1024, 3, 16, 64])`,\npermute: `TorchScriptTensor(f32[3, 4, 16, 1024, 64])`,\nunbind: `TorchScriptTensor()`,\ngetitem_3: `TorchScriptTensor(f32[4, 16, 1024, 64])`,\n...\n)\n## PyTorch source information\n```\n File \"/home/thebears/.local/lib/python3.10/site-packages/open_clip/timm_model.py\", line 196, in forward\n x = self.trunk(x)\n File \"/home/thebears/.local/lib/python3.10/site-packages/torch/nn/modules/module.py\", line 1725, in _call_impl\n return forward_call(*args, **kwargs)\n File \"/home/thebears/.local/lib/python3.10/site-packages/timm/models/vision_transformer.py\", line 853, in forward\n x = self.forward_features(x)\n File \"/home/thebears/.local/lib/python3.10/site-packages/timm/models/vision_transformer.py\", line 834, in forward_features\n x = self.blocks(x)\n File \"/home/thebears/.local/lib/python3.10/site-packages/torch/nn/modules/module.py\", line 1725, in _call_impl\n return forward_call(*args, **kwargs)\n File \"/home/thebears/.local/lib/python3.10/site-packages/timm/models/vision_transformer.py\", line 169, in forward\n x = x + self.drop_path1(self.ls1(self.attn(self.norm1(x))))\n File \"/home/thebears/.local/lib/python3.10/site-packages/torch/nn/modules/module.py\", line 1725, in _call_impl\n return forward_call(*args, **kwargs)\n File \"/home/thebears/.local/lib/python3.10/site-packages/timm/models/vision_transformer.py\", line 89, in forward\n q, k, v = qkv.unbind(0)\n\n```\n## Return values\n", + "text":"FX Node: call_function:[name=getitem_5]. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"FxOnnxInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":414 + } + } + }, + { + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/open_clip/timm_model.py" + }, + "region":{ + "snippet":{ + "text":"x = self.trunk(x)" + }, + "startLine":196 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0008", + "stacks":[] + }, + { + "message":{ + "markdown":"Searching operator overload: 'aten._scaled_dot_product_efficient_attention.default' in onnx registry...\n\n\n## Additional Message:\n\n## Function Signature\n### Function Signature OnnxFunctionDispatcher.get_function_overloads\n- self: \n- node: fx.Node(aten._scaled_dot_product_efficient_attention.default)[call_function]:Tuple[length=4](\nTensor(f32[4, 16, 1024, 64]),\nTensor(f32[4, 16, 0]),\nTensor(i64[]),\nTensor(i64[]),\n)\n- diagnostic_context: \n## Return values\nList[length=1](\nregistration.ONNXFunction(aten::_scaled_dot_product_efficient_attention.default, is_custom=False, is_complex=False),\n)", + "text":"Searching operator overload: 'aten._scaled_dot_product_efficient_attention.default' in onnx registry...\n" + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"OnnxFunctionDispatcher.get_function_overloads" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/onnxfunction_dispatcher.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":353 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0016", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Node: aten._scaled_dot_product_efficient_attention.default. \nONNX Node: aten__scaled_dot_product_efficient_attention[opset=pkg.onnxscript.torch_lib;is_custom=False]. \n\n\n## Additional Message:\n\n## Function Signature\n### Function Signature OnnxFunctionDispatcher._find_the_perfect_or_nearest_match_onnxfunction\n- self: \n- node: fx.Node(aten._scaled_dot_product_efficient_attention.default)[call_function]:Tuple[length=4](\nTensor(f32[4, 16, 1024, 64]),\nTensor(f32[4, 16, 0]),\nTensor(i64[]),\nTensor(i64[]),\n)\n- default_and_custom_functions: List[length=1](\nregistration.ONNXFunction(aten::_scaled_dot_product_efficient_attention.default, is_custom=False, is_complex=False),\n)\n- onnx_args: Tuple[length=5](\n`TorchScriptTensor(f32[4, 16, 1024, 64])`,\n`TorchScriptTensor(f32[4, 16, 1024, 64])`,\n`TorchScriptTensor(f32[4, 16, 1024, 64])`,\n,\nFalse,\n)\n- onnx_kwargs: Dict[length=3](\ndropout_p: 0.0,\nis_causal: False,\nscale: ,\n)\n- diagnostic_context: \n## Checking perfect match...\n`TracedOnnxFunction(aten__scaled_dot_product_efficient_attention)`\n### Failed: attribute 'scale' type mismatch!\nActual vs\nExpected AttrType.FLOAT\nmatch score: 2\n### Exact match is not found!\nCannot find a perfect match of symbolic overload, a nearest match is found. Please check the ONNX output carefully. \n\n## Return values\n`TracedOnnxFunction(aten__scaled_dot_product_efficient_attention)`", + "text":"FX Node: aten._scaled_dot_product_efficient_attention.default. \nONNX Node: aten__scaled_dot_product_efficient_attention[opset=pkg.onnxscript.torch_lib;is_custom=False]. \n" + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"fail", + "level":"warning", + "locations":[ + { + "message":{ + "text":"OnnxFunctionDispatcher._find_the_perfect_or_nearest_match_onnxfunction" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/onnxfunction_dispatcher.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":199 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0014", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Node: call_function:aten._scaled_dot_product_efficient_attention.default[name=_scaled_dot_product_efficient_attention]. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature FxOnnxInterpreter.run_node\n- self: \n- node: fx.Node(aten._scaled_dot_product_efficient_attention.default)[call_function]:Tuple[length=4](\nTensor(f32[4, 16, 1024, 64]),\nTensor(f32[4, 16, 0]),\nTensor(i64[]),\nTensor(i64[]),\n)\n- fx_graph_module: torch.fx.GraphModule(timm_models_vision_transformer_Attention)\n- onnxfunction_dispatcher: \n- op_level_debug: False\n- onnxscript_graph: \n- onnxscript_tracer: \n- fx_name_to_onnxscript_value: Dict[length=12](\ngetitem: `TorchScriptTensor(f32[4, 1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_weight: `TorchScriptTensor(f32[3072, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_bias: `TorchScriptTensor(f32[3072])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_weight: `TorchScriptTensor(f32[1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_bias: `TorchScriptTensor(f32[1024])`,\ngetattr_l__self___trunk_blocks___0___attn_qkv_1: `TorchScriptTensor(f32[4, 1024, 3072])`,\nview_3: `TorchScriptTensor(f32[4, 1024, 3, 16, 64])`,\npermute: `TorchScriptTensor(f32[3, 4, 16, 1024, 64])`,\nunbind: `TorchScriptTensor()`,\ngetitem_3: `TorchScriptTensor(f32[4, 16, 1024, 64])`,\n...\n)\n## PyTorch source information\n```\n File \"/home/thebears/.local/lib/python3.10/site-packages/open_clip/timm_model.py\", line 196, in forward\n x = self.trunk(x)\n File \"/home/thebears/.local/lib/python3.10/site-packages/torch/nn/modules/module.py\", line 1725, in _call_impl\n return forward_call(*args, **kwargs)\n File \"/home/thebears/.local/lib/python3.10/site-packages/timm/models/vision_transformer.py\", line 853, in forward\n x = self.forward_features(x)\n File \"/home/thebears/.local/lib/python3.10/site-packages/timm/models/vision_transformer.py\", line 834, in forward_features\n x = self.blocks(x)\n File \"/home/thebears/.local/lib/python3.10/site-packages/torch/nn/modules/module.py\", line 1725, in _call_impl\n return forward_call(*args, **kwargs)\n File \"/home/thebears/.local/lib/python3.10/site-packages/timm/models/vision_transformer.py\", line 169, in forward\n x = x + self.drop_path1(self.ls1(self.attn(self.norm1(x))))\n File \"/home/thebears/.local/lib/python3.10/site-packages/torch/nn/modules/module.py\", line 1725, in _call_impl\n return forward_call(*args, **kwargs)\n File \"/home/thebears/.local/lib/python3.10/site-packages/timm/models/vision_transformer.py\", line 93, in forward\n x = F.scaled_dot_product_attention(\n\n```\n## Return values\n", + "text":"FX Node: call_function:aten._scaled_dot_product_efficient_attention.default[name=_scaled_dot_product_efficient_attention]. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"FxOnnxInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":414 + } + } + }, + { + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/open_clip/timm_model.py" + }, + "region":{ + "snippet":{ + "text":"x = self.trunk(x)" + }, + "startLine":196 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0008", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Node: call_function:[name=getitem_6]. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature FxOnnxInterpreter.run_node\n- self: \n- node: fx.Node()[call_function]:Tensor(f32[4, 16, 1024, 64])\n- fx_graph_module: torch.fx.GraphModule(timm_models_vision_transformer_Attention)\n- onnxfunction_dispatcher: \n- op_level_debug: False\n- onnxscript_graph: \n- onnxscript_tracer: \n- fx_name_to_onnxscript_value: Dict[length=13](\ngetitem: `TorchScriptTensor(f32[4, 1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_weight: `TorchScriptTensor(f32[3072, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_bias: `TorchScriptTensor(f32[3072])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_weight: `TorchScriptTensor(f32[1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_bias: `TorchScriptTensor(f32[1024])`,\ngetattr_l__self___trunk_blocks___0___attn_qkv_1: `TorchScriptTensor(f32[4, 1024, 3072])`,\nview_3: `TorchScriptTensor(f32[4, 1024, 3, 16, 64])`,\npermute: `TorchScriptTensor(f32[3, 4, 16, 1024, 64])`,\nunbind: `TorchScriptTensor()`,\ngetitem_3: `TorchScriptTensor(f32[4, 16, 1024, 64])`,\n...\n)\n## PyTorch source information\n```\n File \"/home/thebears/.local/lib/python3.10/site-packages/open_clip/timm_model.py\", line 196, in forward\n x = self.trunk(x)\n File \"/home/thebears/.local/lib/python3.10/site-packages/torch/nn/modules/module.py\", line 1725, in _call_impl\n return forward_call(*args, **kwargs)\n File \"/home/thebears/.local/lib/python3.10/site-packages/timm/models/vision_transformer.py\", line 853, in forward\n x = self.forward_features(x)\n File \"/home/thebears/.local/lib/python3.10/site-packages/timm/models/vision_transformer.py\", line 834, in forward_features\n x = self.blocks(x)\n File \"/home/thebears/.local/lib/python3.10/site-packages/torch/nn/modules/module.py\", line 1725, in _call_impl\n return forward_call(*args, **kwargs)\n File \"/home/thebears/.local/lib/python3.10/site-packages/timm/models/vision_transformer.py\", line 169, in forward\n x = x + self.drop_path1(self.ls1(self.attn(self.norm1(x))))\n File \"/home/thebears/.local/lib/python3.10/site-packages/torch/nn/modules/module.py\", line 1725, in _call_impl\n return forward_call(*args, **kwargs)\n File \"/home/thebears/.local/lib/python3.10/site-packages/timm/models/vision_transformer.py\", line 93, in forward\n x = F.scaled_dot_product_attention(\n\n```\n## Return values\n", + "text":"FX Node: call_function:[name=getitem_6]. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"FxOnnxInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":414 + } + } + }, + { + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/open_clip/timm_model.py" + }, + "region":{ + "snippet":{ + "text":"x = self.trunk(x)" + }, + "startLine":196 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0008", + "stacks":[] + }, + { + "message":{ + "markdown":"Searching operator overload: 'aten.transpose.int' in onnx registry...\n\n\n## Additional Message:\n\n## Function Signature\n### Function Signature OnnxFunctionDispatcher.get_function_overloads\n- self: \n- node: fx.Node(aten.transpose.int)[call_function]:Tensor(f32[4, 1024, 16, 64])\n- diagnostic_context: \n## Return values\nList[length=1](\nregistration.ONNXFunction(aten::transpose.int, is_custom=False, is_complex=False),\n)", + "text":"Searching operator overload: 'aten.transpose.int' in onnx registry...\n" + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"OnnxFunctionDispatcher.get_function_overloads" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/onnxfunction_dispatcher.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":353 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0016", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Node: aten.transpose.int. \nONNX Node: aten_transpose[opset=pkg.onnxscript.torch_lib;is_custom=False]. \n\n\n## Additional Message:\n\n## Function Signature\n### Function Signature OnnxFunctionDispatcher._find_the_perfect_or_nearest_match_onnxfunction\n- self: \n- node: fx.Node(aten.transpose.int)[call_function]:Tensor(f32[4, 1024, 16, 64])\n- default_and_custom_functions: List[length=1](\nregistration.ONNXFunction(aten::transpose.int, is_custom=False, is_complex=False),\n)\n- onnx_args: Tuple[length=3](\n`TorchScriptTensor(f32[4, 16, 1024, 64])`,\n1,\n2,\n)\n- onnx_kwargs: Dict[length=0](\nNone)\n- diagnostic_context: \n## Checking perfect match...\n`TracedOnnxFunction(aten_transpose)`\nmatch score: 1\n## Return values\n`TracedOnnxFunction(aten_transpose)`", + "text":"FX Node: aten.transpose.int. \nONNX Node: aten_transpose[opset=pkg.onnxscript.torch_lib;is_custom=False]. \n" + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"OnnxFunctionDispatcher._find_the_perfect_or_nearest_match_onnxfunction" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/onnxfunction_dispatcher.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":199 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0014", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Node: call_function:aten.transpose.int[name=transpose_1]. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature FxOnnxInterpreter.run_node\n- self: \n- node: fx.Node(aten.transpose.int)[call_function]:Tensor(f32[4, 1024, 16, 64])\n- fx_graph_module: torch.fx.GraphModule(timm_models_vision_transformer_Attention)\n- onnxfunction_dispatcher: \n- op_level_debug: False\n- onnxscript_graph: \n- onnxscript_tracer: \n- fx_name_to_onnxscript_value: Dict[length=14](\ngetitem: `TorchScriptTensor(f32[4, 1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_weight: `TorchScriptTensor(f32[3072, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_bias: `TorchScriptTensor(f32[3072])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_weight: `TorchScriptTensor(f32[1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_bias: `TorchScriptTensor(f32[1024])`,\ngetattr_l__self___trunk_blocks___0___attn_qkv_1: `TorchScriptTensor(f32[4, 1024, 3072])`,\nview_3: `TorchScriptTensor(f32[4, 1024, 3, 16, 64])`,\npermute: `TorchScriptTensor(f32[3, 4, 16, 1024, 64])`,\nunbind: `TorchScriptTensor()`,\ngetitem_3: `TorchScriptTensor(f32[4, 16, 1024, 64])`,\n...\n)\n## PyTorch source information\n```\n File \"/home/thebears/.local/lib/python3.10/site-packages/open_clip/timm_model.py\", line 196, in forward\n x = self.trunk(x)\n File \"/home/thebears/.local/lib/python3.10/site-packages/torch/nn/modules/module.py\", line 1725, in _call_impl\n return forward_call(*args, **kwargs)\n File \"/home/thebears/.local/lib/python3.10/site-packages/timm/models/vision_transformer.py\", line 853, in forward\n x = self.forward_features(x)\n File \"/home/thebears/.local/lib/python3.10/site-packages/timm/models/vision_transformer.py\", line 834, in forward_features\n x = self.blocks(x)\n File \"/home/thebears/.local/lib/python3.10/site-packages/torch/nn/modules/module.py\", line 1725, in _call_impl\n return forward_call(*args, **kwargs)\n File \"/home/thebears/.local/lib/python3.10/site-packages/timm/models/vision_transformer.py\", line 169, in forward\n x = x + self.drop_path1(self.ls1(self.attn(self.norm1(x))))\n File \"/home/thebears/.local/lib/python3.10/site-packages/torch/nn/modules/module.py\", line 1725, in _call_impl\n return forward_call(*args, **kwargs)\n File \"/home/thebears/.local/lib/python3.10/site-packages/timm/models/vision_transformer.py\", line 104, in forward\n x = x.transpose(1, 2).reshape(B, N, C)\n\n```\n## Return values\n", + "text":"FX Node: call_function:aten.transpose.int[name=transpose_1]. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"FxOnnxInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":414 + } + } + }, + { + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/open_clip/timm_model.py" + }, + "region":{ + "snippet":{ + "text":"x = self.trunk(x)" + }, + "startLine":196 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0008", + "stacks":[] + }, + { + "message":{ + "markdown":"Searching operator overload: 'aten.view.default' in onnx registry...\n\n\n## Additional Message:\n\n## Function Signature\n### Function Signature OnnxFunctionDispatcher.get_function_overloads\n- self: \n- node: fx.Node(aten.view.default)[call_function]:Tensor(f32[4, 1024, 1024])\n- diagnostic_context: \n## Return values\nList[length=1](\nregistration.ONNXFunction(aten::view.default, is_custom=False, is_complex=False),\n)", + "text":"Searching operator overload: 'aten.view.default' in onnx registry...\n" + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"OnnxFunctionDispatcher.get_function_overloads" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/onnxfunction_dispatcher.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":353 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0016", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Node: aten.view.default. \nONNX Node: aten_view[opset=pkg.onnxscript.torch_lib;is_custom=False]. \n\n\n## Additional Message:\n\n## Function Signature\n### Function Signature OnnxFunctionDispatcher._find_the_perfect_or_nearest_match_onnxfunction\n- self: \n- node: fx.Node(aten.view.default)[call_function]:Tensor(f32[4, 1024, 1024])\n- default_and_custom_functions: List[length=1](\nregistration.ONNXFunction(aten::view.default, is_custom=False, is_complex=False),\n)\n- onnx_args: Tuple[length=2](\n`TorchScriptTensor(f32[4, 1024, 16, 64])`,\nList[length=3](\n4,\n1024,\n1024,\n),\n)\n- onnx_kwargs: Dict[length=0](\nNone)\n- diagnostic_context: \n## Checking perfect match...\n`TracedOnnxFunction(aten_view)`\nmatch score: 2\n## Return values\n`TracedOnnxFunction(aten_view)`", + "text":"FX Node: aten.view.default. \nONNX Node: aten_view[opset=pkg.onnxscript.torch_lib;is_custom=False]. \n" + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"OnnxFunctionDispatcher._find_the_perfect_or_nearest_match_onnxfunction" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/onnxfunction_dispatcher.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":199 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0014", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Node: call_function:aten.view.default[name=view_4]. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature FxOnnxInterpreter.run_node\n- self: \n- node: fx.Node(aten.view.default)[call_function]:Tensor(f32[4, 1024, 1024])\n- fx_graph_module: torch.fx.GraphModule(timm_models_vision_transformer_Attention)\n- onnxfunction_dispatcher: \n- op_level_debug: False\n- onnxscript_graph: \n- onnxscript_tracer: \n- fx_name_to_onnxscript_value: Dict[length=15](\ngetitem: `TorchScriptTensor(f32[4, 1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_weight: `TorchScriptTensor(f32[3072, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_bias: `TorchScriptTensor(f32[3072])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_weight: `TorchScriptTensor(f32[1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_bias: `TorchScriptTensor(f32[1024])`,\ngetattr_l__self___trunk_blocks___0___attn_qkv_1: `TorchScriptTensor(f32[4, 1024, 3072])`,\nview_3: `TorchScriptTensor(f32[4, 1024, 3, 16, 64])`,\npermute: `TorchScriptTensor(f32[3, 4, 16, 1024, 64])`,\nunbind: `TorchScriptTensor()`,\ngetitem_3: `TorchScriptTensor(f32[4, 16, 1024, 64])`,\n...\n)\n## PyTorch source information\n```\n File \"/home/thebears/.local/lib/python3.10/site-packages/open_clip/timm_model.py\", line 196, in forward\n x = self.trunk(x)\n File \"/home/thebears/.local/lib/python3.10/site-packages/torch/nn/modules/module.py\", line 1725, in _call_impl\n return forward_call(*args, **kwargs)\n File \"/home/thebears/.local/lib/python3.10/site-packages/timm/models/vision_transformer.py\", line 853, in forward\n x = self.forward_features(x)\n File \"/home/thebears/.local/lib/python3.10/site-packages/timm/models/vision_transformer.py\", line 834, in forward_features\n x = self.blocks(x)\n File \"/home/thebears/.local/lib/python3.10/site-packages/torch/nn/modules/module.py\", line 1725, in _call_impl\n return forward_call(*args, **kwargs)\n File \"/home/thebears/.local/lib/python3.10/site-packages/timm/models/vision_transformer.py\", line 169, in forward\n x = x + self.drop_path1(self.ls1(self.attn(self.norm1(x))))\n File \"/home/thebears/.local/lib/python3.10/site-packages/torch/nn/modules/module.py\", line 1725, in _call_impl\n return forward_call(*args, **kwargs)\n File \"/home/thebears/.local/lib/python3.10/site-packages/timm/models/vision_transformer.py\", line 104, in forward\n x = x.transpose(1, 2).reshape(B, N, C)\n\n```\n## Return values\n", + "text":"FX Node: call_function:aten.view.default[name=view_4]. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"FxOnnxInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":414 + } + } + }, + { + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/open_clip/timm_model.py" + }, + "region":{ + "snippet":{ + "text":"x = self.trunk(x)" + }, + "startLine":196 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0008", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Node: placeholder:view_4[name=view_4]. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature FxOnnxInterpreter.run_node\n- self: \n- node: fx.Node(view_4)[placeholder]:Tensor(f32[4, 1024, 1024])\n- fx_graph_module: torch.fx.GraphModule(torch_nn_modules_linear_Linear)\n- onnxfunction_dispatcher: \n- op_level_debug: False\n- onnxscript_graph: \n- onnxscript_tracer: \n- fx_name_to_onnxscript_value: Dict[length=0](\nNone)\n## PyTorch source information\n```\n File \"/home/thebears/.local/lib/python3.10/site-packages/open_clip/timm_model.py\", line 196, in forward\n x = self.trunk(x)\n File \"/home/thebears/.local/lib/python3.10/site-packages/torch/nn/modules/module.py\", line 1725, in _call_impl\n return forward_call(*args, **kwargs)\n File \"/home/thebears/.local/lib/python3.10/site-packages/timm/models/vision_transformer.py\", line 853, in forward\n x = self.forward_features(x)\n File \"/home/thebears/.local/lib/python3.10/site-packages/timm/models/vision_transformer.py\", line 834, in forward_features\n x = self.blocks(x)\n File \"/home/thebears/.local/lib/python3.10/site-packages/torch/nn/modules/module.py\", line 1725, in _call_impl\n return forward_call(*args, **kwargs)\n File \"/home/thebears/.local/lib/python3.10/site-packages/timm/models/vision_transformer.py\", line 169, in forward\n x = x + self.drop_path1(self.ls1(self.attn(self.norm1(x))))\n File \"/home/thebears/.local/lib/python3.10/site-packages/torch/nn/modules/module.py\", line 1725, in _call_impl\n return forward_call(*args, **kwargs)\n File \"/home/thebears/.local/lib/python3.10/site-packages/timm/models/vision_transformer.py\", line 104, in forward\n x = x.transpose(1, 2).reshape(B, N, C)\n\n```\n## Return values\n", + "text":"FX Node: placeholder:view_4[name=view_4]. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"FxOnnxInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":414 + } + } + }, + { + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/open_clip/timm_model.py" + }, + "region":{ + "snippet":{ + "text":"x = self.trunk(x)" + }, + "startLine":196 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0008", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___0___attn_proj_weight[name=p_getattr_l__self___trunk_blocks___0___attn_proj_weight]. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature FxOnnxInterpreter.run_node\n- self: \n- node: fx.Node(p_getattr_l__self___trunk_blocks___0___attn_proj_weight)[placeholder]:Tensor(f32[1024, 1024])\n- fx_graph_module: torch.fx.GraphModule(torch_nn_modules_linear_Linear)\n- onnxfunction_dispatcher: \n- op_level_debug: False\n- onnxscript_graph: \n- onnxscript_tracer: \n- fx_name_to_onnxscript_value: Dict[length=1](\nview_4: `TorchScriptTensor(f32[4, 1024, 1024])`,\n)\n## Return values\n", + "text":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___0___attn_proj_weight[name=p_getattr_l__self___trunk_blocks___0___attn_proj_weight]. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"FxOnnxInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":414 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0008", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___0___attn_proj_bias[name=p_getattr_l__self___trunk_blocks___0___attn_proj_bias]. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature FxOnnxInterpreter.run_node\n- self: \n- node: fx.Node(p_getattr_l__self___trunk_blocks___0___attn_proj_bias)[placeholder]:Tensor(f32[1024])\n- fx_graph_module: torch.fx.GraphModule(torch_nn_modules_linear_Linear)\n- onnxfunction_dispatcher: \n- op_level_debug: False\n- onnxscript_graph: \n- onnxscript_tracer: \n- fx_name_to_onnxscript_value: Dict[length=2](\nview_4: `TorchScriptTensor(f32[4, 1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_weight: `TorchScriptTensor(f32[1024, 1024])`,\n)\n## Return values\n", + "text":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___0___attn_proj_bias[name=p_getattr_l__self___trunk_blocks___0___attn_proj_bias]. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"FxOnnxInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":414 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0008", + "stacks":[] + }, + { + "message":{ + "markdown":"Searching operator overload: 'aten.view.default' in onnx registry...\n\n\n## Additional Message:\n\n## Function Signature\n### Function Signature OnnxFunctionDispatcher.get_function_overloads\n- self: \n- node: fx.Node(aten.view.default)[call_function]:Tensor(f32[4096, 1024])\n- diagnostic_context: \n## Return values\nList[length=1](\nregistration.ONNXFunction(aten::view.default, is_custom=False, is_complex=False),\n)", + "text":"Searching operator overload: 'aten.view.default' in onnx registry...\n" + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"OnnxFunctionDispatcher.get_function_overloads" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/onnxfunction_dispatcher.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":353 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0016", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Node: aten.view.default. \nONNX Node: aten_view[opset=pkg.onnxscript.torch_lib;is_custom=False]. \n\n\n## Additional Message:\n\n## Function Signature\n### Function Signature OnnxFunctionDispatcher._find_the_perfect_or_nearest_match_onnxfunction\n- self: \n- node: fx.Node(aten.view.default)[call_function]:Tensor(f32[4096, 1024])\n- default_and_custom_functions: List[length=1](\nregistration.ONNXFunction(aten::view.default, is_custom=False, is_complex=False),\n)\n- onnx_args: Tuple[length=2](\n`TorchScriptTensor(f32[4, 1024, 1024])`,\nList[length=2](\n4096,\n1024,\n),\n)\n- onnx_kwargs: Dict[length=0](\nNone)\n- diagnostic_context: \n## Checking perfect match...\n`TracedOnnxFunction(aten_view)`\nmatch score: 2\n## Return values\n`TracedOnnxFunction(aten_view)`", + "text":"FX Node: aten.view.default. \nONNX Node: aten_view[opset=pkg.onnxscript.torch_lib;is_custom=False]. \n" + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"OnnxFunctionDispatcher._find_the_perfect_or_nearest_match_onnxfunction" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/onnxfunction_dispatcher.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":199 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0014", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Node: call_function:aten.view.default[name=view_5]. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature FxOnnxInterpreter.run_node\n- self: \n- node: fx.Node(aten.view.default)[call_function]:Tensor(f32[4096, 1024])\n- fx_graph_module: torch.fx.GraphModule(torch_nn_modules_linear_Linear)\n- onnxfunction_dispatcher: \n- op_level_debug: False\n- onnxscript_graph: \n- onnxscript_tracer: \n- fx_name_to_onnxscript_value: Dict[length=3](\nview_4: `TorchScriptTensor(f32[4, 1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_weight: `TorchScriptTensor(f32[1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_bias: `TorchScriptTensor(f32[1024])`,\n)\n## PyTorch source information\n```\n File \"/home/thebears/.local/lib/python3.10/site-packages/open_clip/timm_model.py\", line 196, in forward\n x = self.trunk(x)\n File \"/home/thebears/.local/lib/python3.10/site-packages/torch/nn/modules/module.py\", line 1725, in _call_impl\n return forward_call(*args, **kwargs)\n File \"/home/thebears/.local/lib/python3.10/site-packages/timm/models/vision_transformer.py\", line 853, in forward\n x = self.forward_features(x)\n File \"/home/thebears/.local/lib/python3.10/site-packages/timm/models/vision_transformer.py\", line 834, in forward_features\n x = self.blocks(x)\n File \"/home/thebears/.local/lib/python3.10/site-packages/torch/nn/modules/module.py\", line 1725, in _call_impl\n return forward_call(*args, **kwargs)\n File \"/home/thebears/.local/lib/python3.10/site-packages/timm/models/vision_transformer.py\", line 169, in forward\n x = x + self.drop_path1(self.ls1(self.attn(self.norm1(x))))\n File \"/home/thebears/.local/lib/python3.10/site-packages/torch/nn/modules/module.py\", line 1725, in _call_impl\n return forward_call(*args, **kwargs)\n File \"/home/thebears/.local/lib/python3.10/site-packages/timm/models/vision_transformer.py\", line 105, in forward\n x = self.proj(x)\n\n```\n## Return values\n", + "text":"FX Node: call_function:aten.view.default[name=view_5]. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"FxOnnxInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":414 + } + } + }, + { + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/open_clip/timm_model.py" + }, + "region":{ + "snippet":{ + "text":"x = self.trunk(x)" + }, + "startLine":196 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0008", + "stacks":[] + }, + { + "message":{ + "markdown":"Searching operator overload: 'aten.t.default' in onnx registry...\n\n\n## Additional Message:\n\n## Function Signature\n### Function Signature OnnxFunctionDispatcher.get_function_overloads\n- self: \n- node: fx.Node(aten.t.default)[call_function]:Tensor(f32[1024, 1024])\n- diagnostic_context: \n## Return values\nList[length=1](\nregistration.ONNXFunction(aten::t.default, is_custom=False, is_complex=False),\n)", + "text":"Searching operator overload: 'aten.t.default' in onnx registry...\n" + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"OnnxFunctionDispatcher.get_function_overloads" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/onnxfunction_dispatcher.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":353 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0016", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Node: aten.t.default. \nONNX Node: aten_t[opset=pkg.onnxscript.torch_lib;is_custom=False]. \n\n\n## Additional Message:\n\n## Function Signature\n### Function Signature OnnxFunctionDispatcher._find_the_perfect_or_nearest_match_onnxfunction\n- self: \n- node: fx.Node(aten.t.default)[call_function]:Tensor(f32[1024, 1024])\n- default_and_custom_functions: List[length=1](\nregistration.ONNXFunction(aten::t.default, is_custom=False, is_complex=False),\n)\n- onnx_args: Tuple[length=1](\n`TorchScriptTensor(f32[1024, 1024])`,\n)\n- onnx_kwargs: Dict[length=0](\nNone)\n- diagnostic_context: \n## Checking perfect match...\n`TracedOnnxFunction(aten_t)`\nmatch score: 1\n## Return values\n`TracedOnnxFunction(aten_t)`", + "text":"FX Node: aten.t.default. \nONNX Node: aten_t[opset=pkg.onnxscript.torch_lib;is_custom=False]. \n" + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"OnnxFunctionDispatcher._find_the_perfect_or_nearest_match_onnxfunction" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/onnxfunction_dispatcher.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":199 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0014", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Node: call_function:aten.t.default[name=t_1]. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature FxOnnxInterpreter.run_node\n- self: \n- node: fx.Node(aten.t.default)[call_function]:Tensor(f32[1024, 1024])\n- fx_graph_module: torch.fx.GraphModule(torch_nn_modules_linear_Linear)\n- onnxfunction_dispatcher: \n- op_level_debug: False\n- onnxscript_graph: \n- onnxscript_tracer: \n- fx_name_to_onnxscript_value: Dict[length=4](\nview_4: `TorchScriptTensor(f32[4, 1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_weight: `TorchScriptTensor(f32[1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_bias: `TorchScriptTensor(f32[1024])`,\nview_5: `TorchScriptTensor(f32[4096, 1024])`,\n)\n## PyTorch source information\n```\n File \"/home/thebears/.local/lib/python3.10/site-packages/open_clip/timm_model.py\", line 196, in forward\n x = self.trunk(x)\n File \"/home/thebears/.local/lib/python3.10/site-packages/torch/nn/modules/module.py\", line 1725, in _call_impl\n return forward_call(*args, **kwargs)\n File \"/home/thebears/.local/lib/python3.10/site-packages/timm/models/vision_transformer.py\", line 853, in forward\n x = self.forward_features(x)\n File \"/home/thebears/.local/lib/python3.10/site-packages/timm/models/vision_transformer.py\", line 834, in forward_features\n x = self.blocks(x)\n File \"/home/thebears/.local/lib/python3.10/site-packages/torch/nn/modules/module.py\", line 1725, in _call_impl\n return forward_call(*args, **kwargs)\n File \"/home/thebears/.local/lib/python3.10/site-packages/timm/models/vision_transformer.py\", line 169, in forward\n x = x + self.drop_path1(self.ls1(self.attn(self.norm1(x))))\n File \"/home/thebears/.local/lib/python3.10/site-packages/torch/nn/modules/module.py\", line 1725, in _call_impl\n return forward_call(*args, **kwargs)\n File \"/home/thebears/.local/lib/python3.10/site-packages/timm/models/vision_transformer.py\", line 105, in forward\n x = self.proj(x)\n\n```\n## Return values\n", + "text":"FX Node: call_function:aten.t.default[name=t_1]. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"FxOnnxInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":414 + } + } + }, + { + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/open_clip/timm_model.py" + }, + "region":{ + "snippet":{ + "text":"x = self.trunk(x)" + }, + "startLine":196 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0008", + "stacks":[] + }, + { + "message":{ + "markdown":"Searching operator overload: 'aten.addmm.default' in onnx registry...\n\n\n## Additional Message:\n\n## Function Signature\n### Function Signature OnnxFunctionDispatcher.get_function_overloads\n- self: \n- node: fx.Node(aten.addmm.default)[call_function]:Tensor(f32[4096, 1024])\n- diagnostic_context: \n## Return values\nList[length=1](\nregistration.ONNXFunction(aten::addmm.default, is_custom=False, is_complex=False),\n)", + "text":"Searching operator overload: 'aten.addmm.default' in onnx registry...\n" + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"OnnxFunctionDispatcher.get_function_overloads" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/onnxfunction_dispatcher.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":353 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0016", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Node: aten.addmm.default. \nONNX Node: aten_addmm[opset=pkg.onnxscript.torch_lib;is_custom=False]. \n\n\n## Additional Message:\n\n## Function Signature\n### Function Signature OnnxFunctionDispatcher._find_the_perfect_or_nearest_match_onnxfunction\n- self: \n- node: fx.Node(aten.addmm.default)[call_function]:Tensor(f32[4096, 1024])\n- default_and_custom_functions: List[length=1](\nregistration.ONNXFunction(aten::addmm.default, is_custom=False, is_complex=False),\n)\n- onnx_args: Tuple[length=3](\n`TorchScriptTensor(f32[1024])`,\n`TorchScriptTensor(f32[4096, 1024])`,\n`TorchScriptTensor(f32[1024, 1024])`,\n)\n- onnx_kwargs: Dict[length=2](\nbeta: 1,\nalpha: 1,\n)\n- diagnostic_context: \n## Checking perfect match...\n`TracedOnnxFunction(aten_addmm)`\n### Failed: attribute 'beta' type mismatch!\nActual vs\nExpected AttrType.FLOAT\n### Failed: attribute 'alpha' type mismatch!\nActual vs\nExpected AttrType.FLOAT\nmatch score: 1\n### Exact match is not found!\nCannot find a perfect match of symbolic overload, a nearest match is found. Please check the ONNX output carefully. \n\n## Return values\n`TracedOnnxFunction(aten_addmm)`", + "text":"FX Node: aten.addmm.default. \nONNX Node: aten_addmm[opset=pkg.onnxscript.torch_lib;is_custom=False]. \n" + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"fail", + "level":"warning", + "locations":[ + { + "message":{ + "text":"OnnxFunctionDispatcher._find_the_perfect_or_nearest_match_onnxfunction" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/onnxfunction_dispatcher.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":199 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0014", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Node: call_function:aten.addmm.default[name=addmm_1]. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature FxOnnxInterpreter.run_node\n- self: \n- node: fx.Node(aten.addmm.default)[call_function]:Tensor(f32[4096, 1024])\n- fx_graph_module: torch.fx.GraphModule(torch_nn_modules_linear_Linear)\n- onnxfunction_dispatcher: \n- op_level_debug: False\n- onnxscript_graph: \n- onnxscript_tracer: \n- fx_name_to_onnxscript_value: Dict[length=5](\nview_4: `TorchScriptTensor(f32[4, 1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_weight: `TorchScriptTensor(f32[1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_bias: `TorchScriptTensor(f32[1024])`,\nview_5: `TorchScriptTensor(f32[4096, 1024])`,\nt_1: `TorchScriptTensor(f32[1024, 1024])`,\n)\n## PyTorch source information\n```\n File \"/home/thebears/.local/lib/python3.10/site-packages/open_clip/timm_model.py\", line 196, in forward\n x = self.trunk(x)\n File \"/home/thebears/.local/lib/python3.10/site-packages/torch/nn/modules/module.py\", line 1725, in _call_impl\n return forward_call(*args, **kwargs)\n File \"/home/thebears/.local/lib/python3.10/site-packages/timm/models/vision_transformer.py\", line 853, in forward\n x = self.forward_features(x)\n File \"/home/thebears/.local/lib/python3.10/site-packages/timm/models/vision_transformer.py\", line 834, in forward_features\n x = self.blocks(x)\n File \"/home/thebears/.local/lib/python3.10/site-packages/torch/nn/modules/module.py\", line 1725, in _call_impl\n return forward_call(*args, **kwargs)\n File \"/home/thebears/.local/lib/python3.10/site-packages/timm/models/vision_transformer.py\", line 169, in forward\n x = x + self.drop_path1(self.ls1(self.attn(self.norm1(x))))\n File \"/home/thebears/.local/lib/python3.10/site-packages/torch/nn/modules/module.py\", line 1725, in _call_impl\n return forward_call(*args, **kwargs)\n File \"/home/thebears/.local/lib/python3.10/site-packages/timm/models/vision_transformer.py\", line 105, in forward\n x = self.proj(x)\n\n```\n## Return values\n", + "text":"FX Node: call_function:aten.addmm.default[name=addmm_1]. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"FxOnnxInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":414 + } + } + }, + { + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/open_clip/timm_model.py" + }, + "region":{ + "snippet":{ + "text":"x = self.trunk(x)" + }, + "startLine":196 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0008", + "stacks":[] + }, + { + "message":{ + "markdown":"Searching operator overload: 'aten.view.default' in onnx registry...\n\n\n## Additional Message:\n\n## Function Signature\n### Function Signature OnnxFunctionDispatcher.get_function_overloads\n- self: \n- node: fx.Node(aten.view.default)[call_function]:Tensor(f32[4, 1024, 1024])\n- diagnostic_context: \n## Return values\nList[length=1](\nregistration.ONNXFunction(aten::view.default, is_custom=False, is_complex=False),\n)", + "text":"Searching operator overload: 'aten.view.default' in onnx registry...\n" + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"OnnxFunctionDispatcher.get_function_overloads" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/onnxfunction_dispatcher.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":353 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0016", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Node: aten.view.default. \nONNX Node: aten_view[opset=pkg.onnxscript.torch_lib;is_custom=False]. \n\n\n## Additional Message:\n\n## Function Signature\n### Function Signature OnnxFunctionDispatcher._find_the_perfect_or_nearest_match_onnxfunction\n- self: \n- node: fx.Node(aten.view.default)[call_function]:Tensor(f32[4, 1024, 1024])\n- default_and_custom_functions: List[length=1](\nregistration.ONNXFunction(aten::view.default, is_custom=False, is_complex=False),\n)\n- onnx_args: Tuple[length=2](\n`TorchScriptTensor(f32[4096, 1024])`,\nList[length=3](\n4,\n1024,\n1024,\n),\n)\n- onnx_kwargs: Dict[length=0](\nNone)\n- diagnostic_context: \n## Checking perfect match...\n`TracedOnnxFunction(aten_view)`\nmatch score: 2\n## Return values\n`TracedOnnxFunction(aten_view)`", + "text":"FX Node: aten.view.default. \nONNX Node: aten_view[opset=pkg.onnxscript.torch_lib;is_custom=False]. \n" + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"OnnxFunctionDispatcher._find_the_perfect_or_nearest_match_onnxfunction" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/onnxfunction_dispatcher.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":199 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0014", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Node: call_function:aten.view.default[name=view_6]. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature FxOnnxInterpreter.run_node\n- self: \n- node: fx.Node(aten.view.default)[call_function]:Tensor(f32[4, 1024, 1024])\n- fx_graph_module: torch.fx.GraphModule(torch_nn_modules_linear_Linear)\n- onnxfunction_dispatcher: \n- op_level_debug: False\n- onnxscript_graph: \n- onnxscript_tracer: \n- fx_name_to_onnxscript_value: Dict[length=6](\nview_4: `TorchScriptTensor(f32[4, 1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_weight: `TorchScriptTensor(f32[1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_bias: `TorchScriptTensor(f32[1024])`,\nview_5: `TorchScriptTensor(f32[4096, 1024])`,\nt_1: `TorchScriptTensor(f32[1024, 1024])`,\naddmm_1: `TorchScriptTensor(f32[4096, 1024])`,\n)\n## PyTorch source information\n```\n File \"/home/thebears/.local/lib/python3.10/site-packages/open_clip/timm_model.py\", line 196, in forward\n x = self.trunk(x)\n File \"/home/thebears/.local/lib/python3.10/site-packages/torch/nn/modules/module.py\", line 1725, in _call_impl\n return forward_call(*args, **kwargs)\n File \"/home/thebears/.local/lib/python3.10/site-packages/timm/models/vision_transformer.py\", line 853, in forward\n x = self.forward_features(x)\n File \"/home/thebears/.local/lib/python3.10/site-packages/timm/models/vision_transformer.py\", line 834, in forward_features\n x = self.blocks(x)\n File \"/home/thebears/.local/lib/python3.10/site-packages/torch/nn/modules/module.py\", line 1725, in _call_impl\n return forward_call(*args, **kwargs)\n File \"/home/thebears/.local/lib/python3.10/site-packages/timm/models/vision_transformer.py\", line 169, in forward\n x = x + self.drop_path1(self.ls1(self.attn(self.norm1(x))))\n File \"/home/thebears/.local/lib/python3.10/site-packages/torch/nn/modules/module.py\", line 1725, in _call_impl\n return forward_call(*args, **kwargs)\n File \"/home/thebears/.local/lib/python3.10/site-packages/timm/models/vision_transformer.py\", line 105, in forward\n x = self.proj(x)\n\n```\n## Return values\n", + "text":"FX Node: call_function:aten.view.default[name=view_6]. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"FxOnnxInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":414 + } + } + }, + { + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/open_clip/timm_model.py" + }, + "region":{ + "snippet":{ + "text":"x = self.trunk(x)" + }, + "startLine":196 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0008", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Node: output:output[name=output]. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature FxOnnxInterpreter.run_node\n- self: \n- node: fx.Node(output)[output]:None\n- fx_graph_module: torch.fx.GraphModule(torch_nn_modules_linear_Linear)\n- onnxfunction_dispatcher: \n- op_level_debug: False\n- onnxscript_graph: \n- onnxscript_tracer: \n- fx_name_to_onnxscript_value: Dict[length=7](\nview_4: `TorchScriptTensor(f32[4, 1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_weight: `TorchScriptTensor(f32[1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_bias: `TorchScriptTensor(f32[1024])`,\nview_5: `TorchScriptTensor(f32[4096, 1024])`,\nt_1: `TorchScriptTensor(f32[1024, 1024])`,\naddmm_1: `TorchScriptTensor(f32[4096, 1024])`,\nview_6: `TorchScriptTensor(f32[4, 1024, 1024])`,\n)\n## Return values\n", + "text":"FX Node: output:output[name=output]. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"FxOnnxInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":414 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0008", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Graph: torch_nn_modules_linear_Linear. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature FxOnnxInterpreter.run\n- self: \n- fx_graph_module: torch.fx.GraphModule(torch_nn_modules_linear_Linear)\n- onnxfunction_dispatcher: \n- op_level_debug: False\n- parent_onnxscript_graph: \n## Return values\n", + "text":"FX Graph: torch_nn_modules_linear_Linear. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"FxOnnxInterpreter.run" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":496 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0007", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Node: call_module:getattr_L__self___trunk_blocks___0___attn_proj_1[name=getattr_l__self___trunk_blocks___0___attn_proj_1]. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature FxOnnxInterpreter.run_node\n- self: \n- node: fx.Node(getattr_L__self___trunk_blocks___0___attn_proj_1)[call_module]:Tensor(f32[4, 1024, 1024])\n- fx_graph_module: torch.fx.GraphModule(timm_models_vision_transformer_Attention)\n- onnxfunction_dispatcher: \n- op_level_debug: False\n- onnxscript_graph: \n- onnxscript_tracer: \n- fx_name_to_onnxscript_value: Dict[length=16](\ngetitem: `TorchScriptTensor(f32[4, 1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_weight: `TorchScriptTensor(f32[3072, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_bias: `TorchScriptTensor(f32[3072])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_weight: `TorchScriptTensor(f32[1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_bias: `TorchScriptTensor(f32[1024])`,\ngetattr_l__self___trunk_blocks___0___attn_qkv_1: `TorchScriptTensor(f32[4, 1024, 3072])`,\nview_3: `TorchScriptTensor(f32[4, 1024, 3, 16, 64])`,\npermute: `TorchScriptTensor(f32[3, 4, 16, 1024, 64])`,\nunbind: `TorchScriptTensor()`,\ngetitem_3: `TorchScriptTensor(f32[4, 16, 1024, 64])`,\n...\n)\n## PyTorch source information\n```\n File \"/home/thebears/.local/lib/python3.10/site-packages/open_clip/timm_model.py\", line 196, in forward\n x = self.trunk(x)\n File \"/home/thebears/.local/lib/python3.10/site-packages/torch/nn/modules/module.py\", line 1725, in _call_impl\n return forward_call(*args, **kwargs)\n File \"/home/thebears/.local/lib/python3.10/site-packages/timm/models/vision_transformer.py\", line 853, in forward\n x = self.forward_features(x)\n File \"/home/thebears/.local/lib/python3.10/site-packages/timm/models/vision_transformer.py\", line 834, in forward_features\n x = self.blocks(x)\n File \"/home/thebears/.local/lib/python3.10/site-packages/torch/nn/modules/module.py\", line 1725, in _call_impl\n return forward_call(*args, **kwargs)\n File \"/home/thebears/.local/lib/python3.10/site-packages/timm/models/vision_transformer.py\", line 169, in forward\n x = x + self.drop_path1(self.ls1(self.attn(self.norm1(x))))\n File \"/home/thebears/.local/lib/python3.10/site-packages/torch/nn/modules/module.py\", line 1725, in _call_impl\n return forward_call(*args, **kwargs)\n File \"/home/thebears/.local/lib/python3.10/site-packages/timm/models/vision_transformer.py\", line 105, in forward\n x = self.proj(x)\n\n```\n## Return values\n", + "text":"FX Node: call_module:getattr_L__self___trunk_blocks___0___attn_proj_1[name=getattr_l__self___trunk_blocks___0___attn_proj_1]. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"FxOnnxInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":414 + } + } + }, + { + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/open_clip/timm_model.py" + }, + "region":{ + "snippet":{ + "text":"x = self.trunk(x)" + }, + "startLine":196 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0008", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Node: placeholder:view_6[name=view_6]. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature FxOnnxInterpreter.run_node\n- self: \n- node: fx.Node(view_6)[placeholder]:Tensor(f32[4, 1024, 1024])\n- fx_graph_module: torch.fx.GraphModule(torch_nn_modules_dropout_Dropout)\n- onnxfunction_dispatcher: \n- op_level_debug: False\n- onnxscript_graph: \n- onnxscript_tracer: \n- fx_name_to_onnxscript_value: Dict[length=0](\nNone)\n## PyTorch source information\n```\n File \"/home/thebears/.local/lib/python3.10/site-packages/open_clip/timm_model.py\", line 196, in forward\n x = self.trunk(x)\n File \"/home/thebears/.local/lib/python3.10/site-packages/torch/nn/modules/module.py\", line 1725, in _call_impl\n return forward_call(*args, **kwargs)\n File \"/home/thebears/.local/lib/python3.10/site-packages/timm/models/vision_transformer.py\", line 853, in forward\n x = self.forward_features(x)\n File \"/home/thebears/.local/lib/python3.10/site-packages/timm/models/vision_transformer.py\", line 834, in forward_features\n x = self.blocks(x)\n File \"/home/thebears/.local/lib/python3.10/site-packages/torch/nn/modules/module.py\", line 1725, in _call_impl\n return forward_call(*args, **kwargs)\n File \"/home/thebears/.local/lib/python3.10/site-packages/timm/models/vision_transformer.py\", line 169, in forward\n x = x + self.drop_path1(self.ls1(self.attn(self.norm1(x))))\n File \"/home/thebears/.local/lib/python3.10/site-packages/torch/nn/modules/module.py\", line 1725, in _call_impl\n return forward_call(*args, **kwargs)\n File \"/home/thebears/.local/lib/python3.10/site-packages/timm/models/vision_transformer.py\", line 105, in forward\n x = self.proj(x)\n\n```\n## Return values\n", + "text":"FX Node: placeholder:view_6[name=view_6]. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"FxOnnxInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":414 + } + } + }, + { + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/open_clip/timm_model.py" + }, + "region":{ + "snippet":{ + "text":"x = self.trunk(x)" + }, + "startLine":196 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0008", + "stacks":[] + }, + { + "message":{ + "markdown":"Searching operator overload: 'aten.clone.default' in onnx registry...\n\n\n## Additional Message:\n\n## Function Signature\n### Function Signature OnnxFunctionDispatcher.get_function_overloads\n- self: \n- node: fx.Node(aten.clone.default)[call_function]:Tensor(f32[4, 1024, 1024])\n- diagnostic_context: \n## Return values\nList[length=1](\nregistration.ONNXFunction(aten::clone.default, is_custom=False, is_complex=False),\n)", + "text":"Searching operator overload: 'aten.clone.default' in onnx registry...\n" + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"OnnxFunctionDispatcher.get_function_overloads" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/onnxfunction_dispatcher.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":353 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0016", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Node: aten.clone.default. \nONNX Node: aten_clone[opset=pkg.onnxscript.torch_lib;is_custom=False]. \n\n\n## Additional Message:\n\n## Function Signature\n### Function Signature OnnxFunctionDispatcher._find_the_perfect_or_nearest_match_onnxfunction\n- self: \n- node: fx.Node(aten.clone.default)[call_function]:Tensor(f32[4, 1024, 1024])\n- default_and_custom_functions: List[length=1](\nregistration.ONNXFunction(aten::clone.default, is_custom=False, is_complex=False),\n)\n- onnx_args: Tuple[length=1](\n`TorchScriptTensor(f32[4, 1024, 1024])`,\n)\n- onnx_kwargs: Dict[length=0](\nNone)\n- diagnostic_context: \n## Checking perfect match...\n`TracedOnnxFunction(aten_clone)`\nmatch score: 1\n## Return values\n`TracedOnnxFunction(aten_clone)`", + "text":"FX Node: aten.clone.default. \nONNX Node: aten_clone[opset=pkg.onnxscript.torch_lib;is_custom=False]. \n" + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"OnnxFunctionDispatcher._find_the_perfect_or_nearest_match_onnxfunction" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/onnxfunction_dispatcher.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":199 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0014", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Node: call_function:aten.clone.default[name=clone_1]. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature FxOnnxInterpreter.run_node\n- self: \n- node: fx.Node(aten.clone.default)[call_function]:Tensor(f32[4, 1024, 1024])\n- fx_graph_module: torch.fx.GraphModule(torch_nn_modules_dropout_Dropout)\n- onnxfunction_dispatcher: \n- op_level_debug: False\n- onnxscript_graph: \n- onnxscript_tracer: \n- fx_name_to_onnxscript_value: Dict[length=1](\nview_6: `TorchScriptTensor(f32[4, 1024, 1024])`,\n)\n## PyTorch source information\n```\n File \"/home/thebears/.local/lib/python3.10/site-packages/open_clip/timm_model.py\", line 196, in forward\n x = self.trunk(x)\n File \"/home/thebears/.local/lib/python3.10/site-packages/torch/nn/modules/module.py\", line 1725, in _call_impl\n return forward_call(*args, **kwargs)\n File \"/home/thebears/.local/lib/python3.10/site-packages/timm/models/vision_transformer.py\", line 853, in forward\n x = self.forward_features(x)\n File \"/home/thebears/.local/lib/python3.10/site-packages/timm/models/vision_transformer.py\", line 834, in forward_features\n x = self.blocks(x)\n File \"/home/thebears/.local/lib/python3.10/site-packages/torch/nn/modules/module.py\", line 1725, in _call_impl\n return forward_call(*args, **kwargs)\n File \"/home/thebears/.local/lib/python3.10/site-packages/timm/models/vision_transformer.py\", line 169, in forward\n x = x + self.drop_path1(self.ls1(self.attn(self.norm1(x))))\n File \"/home/thebears/.local/lib/python3.10/site-packages/torch/nn/modules/module.py\", line 1725, in _call_impl\n return forward_call(*args, **kwargs)\n File \"/home/thebears/.local/lib/python3.10/site-packages/timm/models/vision_transformer.py\", line 106, in forward\n x = self.proj_drop(x)\n\n```\n## Return values\n", + "text":"FX Node: call_function:aten.clone.default[name=clone_1]. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"FxOnnxInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":414 + } + } + }, + { + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/open_clip/timm_model.py" + }, + "region":{ + "snippet":{ + "text":"x = self.trunk(x)" + }, + "startLine":196 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0008", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Node: output:output[name=output]. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature FxOnnxInterpreter.run_node\n- self: \n- node: fx.Node(output)[output]:None\n- fx_graph_module: torch.fx.GraphModule(torch_nn_modules_dropout_Dropout)\n- onnxfunction_dispatcher: \n- op_level_debug: False\n- onnxscript_graph: \n- onnxscript_tracer: \n- fx_name_to_onnxscript_value: Dict[length=2](\nview_6: `TorchScriptTensor(f32[4, 1024, 1024])`,\nclone_1: `TorchScriptTensor(f32[4, 1024, 1024])`,\n)\n## Return values\n", + "text":"FX Node: output:output[name=output]. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"FxOnnxInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":414 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0008", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Graph: torch_nn_modules_dropout_Dropout. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature FxOnnxInterpreter.run\n- self: \n- fx_graph_module: torch.fx.GraphModule(torch_nn_modules_dropout_Dropout)\n- onnxfunction_dispatcher: \n- op_level_debug: False\n- parent_onnxscript_graph: \n## Return values\n", + "text":"FX Graph: torch_nn_modules_dropout_Dropout. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"FxOnnxInterpreter.run" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":496 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0007", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Node: call_module:getattr_L__self___trunk_blocks___0___attn_proj_drop_1[name=getattr_l__self___trunk_blocks___0___attn_proj_drop_1]. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature FxOnnxInterpreter.run_node\n- self: \n- node: fx.Node(getattr_L__self___trunk_blocks___0___attn_proj_drop_1)[call_module]:Tensor(f32[4, 1024, 1024])\n- fx_graph_module: torch.fx.GraphModule(timm_models_vision_transformer_Attention)\n- onnxfunction_dispatcher: \n- op_level_debug: False\n- onnxscript_graph: \n- onnxscript_tracer: \n- fx_name_to_onnxscript_value: Dict[length=17](\ngetitem: `TorchScriptTensor(f32[4, 1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_weight: `TorchScriptTensor(f32[3072, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_bias: `TorchScriptTensor(f32[3072])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_weight: `TorchScriptTensor(f32[1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_bias: `TorchScriptTensor(f32[1024])`,\ngetattr_l__self___trunk_blocks___0___attn_qkv_1: `TorchScriptTensor(f32[4, 1024, 3072])`,\nview_3: `TorchScriptTensor(f32[4, 1024, 3, 16, 64])`,\npermute: `TorchScriptTensor(f32[3, 4, 16, 1024, 64])`,\nunbind: `TorchScriptTensor()`,\ngetitem_3: `TorchScriptTensor(f32[4, 16, 1024, 64])`,\n...\n)\n## PyTorch source information\n```\n File \"/home/thebears/.local/lib/python3.10/site-packages/open_clip/timm_model.py\", line 196, in forward\n x = self.trunk(x)\n File \"/home/thebears/.local/lib/python3.10/site-packages/torch/nn/modules/module.py\", line 1725, in _call_impl\n return forward_call(*args, **kwargs)\n File \"/home/thebears/.local/lib/python3.10/site-packages/timm/models/vision_transformer.py\", line 853, in forward\n x = self.forward_features(x)\n File \"/home/thebears/.local/lib/python3.10/site-packages/timm/models/vision_transformer.py\", line 834, in forward_features\n x = self.blocks(x)\n File \"/home/thebears/.local/lib/python3.10/site-packages/torch/nn/modules/module.py\", line 1725, in _call_impl\n return forward_call(*args, **kwargs)\n File \"/home/thebears/.local/lib/python3.10/site-packages/timm/models/vision_transformer.py\", line 169, in forward\n x = x + self.drop_path1(self.ls1(self.attn(self.norm1(x))))\n File \"/home/thebears/.local/lib/python3.10/site-packages/torch/nn/modules/module.py\", line 1725, in _call_impl\n return forward_call(*args, **kwargs)\n File \"/home/thebears/.local/lib/python3.10/site-packages/timm/models/vision_transformer.py\", line 106, in forward\n x = self.proj_drop(x)\n\n```\n## Return values\n", + "text":"FX Node: call_module:getattr_L__self___trunk_blocks___0___attn_proj_drop_1[name=getattr_l__self___trunk_blocks___0___attn_proj_drop_1]. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"FxOnnxInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":414 + } + } + }, + { + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/open_clip/timm_model.py" + }, + "region":{ + "snippet":{ + "text":"x = self.trunk(x)" + }, + "startLine":196 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0008", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Node: output:output[name=output]. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature FxOnnxInterpreter.run_node\n- self: \n- node: fx.Node(output)[output]:None\n- fx_graph_module: torch.fx.GraphModule(timm_models_vision_transformer_Attention)\n- onnxfunction_dispatcher: \n- op_level_debug: False\n- onnxscript_graph: \n- onnxscript_tracer: \n- fx_name_to_onnxscript_value: Dict[length=18](\ngetitem: `TorchScriptTensor(f32[4, 1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_weight: `TorchScriptTensor(f32[3072, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_bias: `TorchScriptTensor(f32[3072])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_weight: `TorchScriptTensor(f32[1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_bias: `TorchScriptTensor(f32[1024])`,\ngetattr_l__self___trunk_blocks___0___attn_qkv_1: `TorchScriptTensor(f32[4, 1024, 3072])`,\nview_3: `TorchScriptTensor(f32[4, 1024, 3, 16, 64])`,\npermute: `TorchScriptTensor(f32[3, 4, 16, 1024, 64])`,\nunbind: `TorchScriptTensor()`,\ngetitem_3: `TorchScriptTensor(f32[4, 16, 1024, 64])`,\n...\n)\n## Return values\n", + "text":"FX Node: output:output[name=output]. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"FxOnnxInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":414 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0008", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Graph: timm_models_vision_transformer_Attention. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature FxOnnxInterpreter.run\n- self: \n- fx_graph_module: torch.fx.GraphModule(timm_models_vision_transformer_Attention)\n- onnxfunction_dispatcher: \n- op_level_debug: False\n- parent_onnxscript_graph: \n## Return values\n", + "text":"FX Graph: timm_models_vision_transformer_Attention. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"FxOnnxInterpreter.run" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":496 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0007", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Node: call_module:getattr_L__self___trunk_blocks___0___attn_1[name=getattr_l__self___trunk_blocks___0___attn_1]. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature FxOnnxInterpreter.run_node\n- self: \n- node: fx.Node(getattr_L__self___trunk_blocks___0___attn_1)[call_module]:Tensor(f32[4, 1024, 1024])\n- fx_graph_module: torch.fx.GraphModule(timm_models_vision_transformer_Block)\n- onnxfunction_dispatcher: \n- op_level_debug: False\n- onnxscript_graph: \n- onnxscript_tracer: \n- fx_name_to_onnxscript_value: Dict[length=14](\nclone: `TorchScriptTensor(f32[4, 1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_weight: `TorchScriptTensor(f32[3072, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_bias: `TorchScriptTensor(f32[3072])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_weight: `TorchScriptTensor(f32[1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm2_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm2_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___mlp_fc1_weight: `TorchScriptTensor(f32[4096, 1024])`,\n...\n)\n## PyTorch source information\n```\n File \"/home/thebears/.local/lib/python3.10/site-packages/open_clip/timm_model.py\", line 196, in forward\n x = self.trunk(x)\n File \"/home/thebears/.local/lib/python3.10/site-packages/torch/nn/modules/module.py\", line 1725, in _call_impl\n return forward_call(*args, **kwargs)\n File \"/home/thebears/.local/lib/python3.10/site-packages/timm/models/vision_transformer.py\", line 853, in forward\n x = self.forward_features(x)\n File \"/home/thebears/.local/lib/python3.10/site-packages/timm/models/vision_transformer.py\", line 834, in forward_features\n x = self.blocks(x)\n File \"/home/thebears/.local/lib/python3.10/site-packages/torch/nn/modules/module.py\", line 1725, in _call_impl\n return forward_call(*args, **kwargs)\n File \"/home/thebears/.local/lib/python3.10/site-packages/timm/models/vision_transformer.py\", line 169, in forward\n x = x + self.drop_path1(self.ls1(self.attn(self.norm1(x))))\n File \"/home/thebears/.local/lib/python3.10/site-packages/torch/nn/modules/module.py\", line 1725, in _call_impl\n return forward_call(*args, **kwargs)\n File \"/home/thebears/.local/lib/python3.10/site-packages/timm/models/vision_transformer.py\", line 88, in forward\n qkv = self.qkv(x).reshape(B, N, 3, self.num_heads, self.head_dim).permute(2, 0, 3, 1, 4)\n\n```\n## Return values\n", + "text":"FX Node: call_module:getattr_L__self___trunk_blocks___0___attn_1[name=getattr_l__self___trunk_blocks___0___attn_1]. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"FxOnnxInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":414 + } + } + }, + { + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/open_clip/timm_model.py" + }, + "region":{ + "snippet":{ + "text":"x = self.trunk(x)" + }, + "startLine":196 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0008", + "stacks":[] + }, + { + "message":{ + "markdown":"Searching operator overload: 'aten.add.Tensor' in onnx registry...\n\n\n## Additional Message:\n\n## Function Signature\n### Function Signature OnnxFunctionDispatcher.get_function_overloads\n- self: \n- node: fx.Node(aten.add.Tensor)[call_function]:Tensor(f32[4, 1024, 1024])\n- diagnostic_context: \n## Return values\nList[length=2](\nregistration.ONNXFunction(aten::add.Tensor, is_custom=False, is_complex=False),\nregistration.ONNXFunction(aten::add.Tensor, is_custom=False, is_complex=False),\n)", + "text":"Searching operator overload: 'aten.add.Tensor' in onnx registry...\n" + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"OnnxFunctionDispatcher.get_function_overloads" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/onnxfunction_dispatcher.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":353 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0016", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Node: aten.add.Tensor. \nONNX Node: aten_add[opset=pkg.onnxscript.torch_lib;is_custom=False]. \nONNX Node: aten_logical_or[opset=pkg.onnxscript.torch_lib;is_custom=False]. \n\n\n## Additional Message:\n\n## Function Signature\n### Function Signature OnnxFunctionDispatcher._find_the_perfect_or_nearest_match_onnxfunction\n- self: \n- node: fx.Node(aten.add.Tensor)[call_function]:Tensor(f32[4, 1024, 1024])\n- default_and_custom_functions: List[length=2](\nregistration.ONNXFunction(aten::add.Tensor, is_custom=False, is_complex=False),\nregistration.ONNXFunction(aten::add.Tensor, is_custom=False, is_complex=False),\n)\n- onnx_args: Tuple[length=2](\n`TorchScriptTensor(f32[4, 1024, 1024])`,\n`TorchScriptTensor(f32[4, 1024, 1024])`,\n)\n- onnx_kwargs: Dict[length=1](\nalpha: 1,\n)\n- diagnostic_context: \n## Checking perfect match...\n`TracedOnnxFunction(aten_logical_or)`\n### Failed: attribute mismatch!\nActual {'alpha'} vs expected set()\nThe function is not a nearest match candidate.\n## Checking perfect match...\n`TracedOnnxFunction(aten_add)`\n### Failed: attribute 'alpha' type mismatch!\nActual vs\nExpected AttrType.FLOAT\nmatch score: 1\n### Exact match is not found!\nCannot find a perfect match of symbolic overload, a nearest match is found. Please check the ONNX output carefully. \n\n## Return values\n`TracedOnnxFunction(aten_add)`", + "text":"FX Node: aten.add.Tensor. \nONNX Node: aten_add[opset=pkg.onnxscript.torch_lib;is_custom=False]. \nONNX Node: aten_logical_or[opset=pkg.onnxscript.torch_lib;is_custom=False]. \n" + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"fail", + "level":"warning", + "locations":[ + { + "message":{ + "text":"OnnxFunctionDispatcher._find_the_perfect_or_nearest_match_onnxfunction" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/onnxfunction_dispatcher.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":199 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0014", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Node: call_function:aten.add.Tensor[name=add_1]. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature FxOnnxInterpreter.run_node\n- self: \n- node: fx.Node(aten.add.Tensor)[call_function]:Tensor(f32[4, 1024, 1024])\n- fx_graph_module: torch.fx.GraphModule(timm_models_vision_transformer_Block)\n- onnxfunction_dispatcher: \n- op_level_debug: False\n- onnxscript_graph: \n- onnxscript_tracer: \n- fx_name_to_onnxscript_value: Dict[length=15](\nclone: `TorchScriptTensor(f32[4, 1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_weight: `TorchScriptTensor(f32[3072, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_bias: `TorchScriptTensor(f32[3072])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_weight: `TorchScriptTensor(f32[1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm2_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm2_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___mlp_fc1_weight: `TorchScriptTensor(f32[4096, 1024])`,\n...\n)\n## PyTorch source information\n```\n File \"/home/thebears/.local/lib/python3.10/site-packages/open_clip/timm_model.py\", line 196, in forward\n x = self.trunk(x)\n File \"/home/thebears/.local/lib/python3.10/site-packages/torch/nn/modules/module.py\", line 1725, in _call_impl\n return forward_call(*args, **kwargs)\n File \"/home/thebears/.local/lib/python3.10/site-packages/timm/models/vision_transformer.py\", line 853, in forward\n x = self.forward_features(x)\n File \"/home/thebears/.local/lib/python3.10/site-packages/timm/models/vision_transformer.py\", line 834, in forward_features\n x = self.blocks(x)\n File \"/home/thebears/.local/lib/python3.10/site-packages/torch/nn/modules/module.py\", line 1725, in _call_impl\n return forward_call(*args, **kwargs)\n File \"/home/thebears/.local/lib/python3.10/site-packages/timm/models/vision_transformer.py\", line 169, in forward\n x = x + self.drop_path1(self.ls1(self.attn(self.norm1(x))))\n\n```\n## Return values\n", + "text":"FX Node: call_function:aten.add.Tensor[name=add_1]. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"FxOnnxInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":414 + } + } + }, + { + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/open_clip/timm_model.py" + }, + "region":{ + "snippet":{ + "text":"x = self.trunk(x)" + }, + "startLine":196 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0008", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Node: placeholder:add_1[name=add_1]. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature FxOnnxInterpreter.run_node\n- self: \n- node: fx.Node(add_1)[placeholder]:Tensor(f32[4, 1024, 1024])\n- fx_graph_module: torch.fx.GraphModule(torch_nn_modules_normalization_LayerNorm)\n- onnxfunction_dispatcher: \n- op_level_debug: False\n- onnxscript_graph: \n- onnxscript_tracer: \n- fx_name_to_onnxscript_value: Dict[length=0](\nNone)\n## PyTorch source information\n```\n File \"/home/thebears/.local/lib/python3.10/site-packages/open_clip/timm_model.py\", line 196, in forward\n x = self.trunk(x)\n File \"/home/thebears/.local/lib/python3.10/site-packages/torch/nn/modules/module.py\", line 1725, in _call_impl\n return forward_call(*args, **kwargs)\n File \"/home/thebears/.local/lib/python3.10/site-packages/timm/models/vision_transformer.py\", line 853, in forward\n x = self.forward_features(x)\n File \"/home/thebears/.local/lib/python3.10/site-packages/timm/models/vision_transformer.py\", line 834, in forward_features\n x = self.blocks(x)\n File \"/home/thebears/.local/lib/python3.10/site-packages/torch/nn/modules/module.py\", line 1725, in _call_impl\n return forward_call(*args, **kwargs)\n File \"/home/thebears/.local/lib/python3.10/site-packages/timm/models/vision_transformer.py\", line 169, in forward\n x = x + self.drop_path1(self.ls1(self.attn(self.norm1(x))))\n\n```\n## Return values\n", + "text":"FX Node: placeholder:add_1[name=add_1]. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"FxOnnxInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":414 + } + } + }, + { + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/open_clip/timm_model.py" + }, + "region":{ + "snippet":{ + "text":"x = self.trunk(x)" + }, + "startLine":196 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0008", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___0___norm2_weight[name=p_getattr_l__self___trunk_blocks___0___norm2_weight]. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature FxOnnxInterpreter.run_node\n- self: \n- node: fx.Node(p_getattr_l__self___trunk_blocks___0___norm2_weight)[placeholder]:Tensor(f32[1024])\n- fx_graph_module: torch.fx.GraphModule(torch_nn_modules_normalization_LayerNorm)\n- onnxfunction_dispatcher: \n- op_level_debug: False\n- onnxscript_graph: \n- onnxscript_tracer: \n- fx_name_to_onnxscript_value: Dict[length=1](\nadd_1: `TorchScriptTensor(f32[4, 1024, 1024])`,\n)\n## Return values\n", + "text":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___0___norm2_weight[name=p_getattr_l__self___trunk_blocks___0___norm2_weight]. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"FxOnnxInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":414 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0008", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___0___norm2_bias[name=p_getattr_l__self___trunk_blocks___0___norm2_bias]. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature FxOnnxInterpreter.run_node\n- self: \n- node: fx.Node(p_getattr_l__self___trunk_blocks___0___norm2_bias)[placeholder]:Tensor(f32[1024])\n- fx_graph_module: torch.fx.GraphModule(torch_nn_modules_normalization_LayerNorm)\n- onnxfunction_dispatcher: \n- op_level_debug: False\n- onnxscript_graph: \n- onnxscript_tracer: \n- fx_name_to_onnxscript_value: Dict[length=2](\nadd_1: `TorchScriptTensor(f32[4, 1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___norm2_weight: `TorchScriptTensor(f32[1024])`,\n)\n## Return values\n", + "text":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___0___norm2_bias[name=p_getattr_l__self___trunk_blocks___0___norm2_bias]. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"FxOnnxInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":414 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0008", + "stacks":[] + }, + { + "message":{ + "markdown":"Searching operator overload: 'aten.native_layer_norm.default' in onnx registry...\n\n\n## Additional Message:\n\n## Function Signature\n### Function Signature OnnxFunctionDispatcher.get_function_overloads\n- self: \n- node: fx.Node(aten.native_layer_norm.default)[call_function]:Tuple[length=3](\nTensor(f32[4, 1024, 1024]),\nTensor(f32[4, 1024, 1]),\nTensor(f32[4, 1024, 1]),\n)\n- diagnostic_context: \n## Return values\nList[length=1](\nregistration.ONNXFunction(aten::native_layer_norm.default, is_custom=False, is_complex=False),\n)", + "text":"Searching operator overload: 'aten.native_layer_norm.default' in onnx registry...\n" + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"OnnxFunctionDispatcher.get_function_overloads" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/onnxfunction_dispatcher.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":353 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0016", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Node: aten.native_layer_norm.default. \nONNX Node: aten_native_layer_norm[opset=pkg.onnxscript.torch_lib;is_custom=False]. \n\n\n## Additional Message:\n\n## Function Signature\n### Function Signature OnnxFunctionDispatcher._find_the_perfect_or_nearest_match_onnxfunction\n- self: \n- node: fx.Node(aten.native_layer_norm.default)[call_function]:Tuple[length=3](\nTensor(f32[4, 1024, 1024]),\nTensor(f32[4, 1024, 1]),\nTensor(f32[4, 1024, 1]),\n)\n- default_and_custom_functions: List[length=1](\nregistration.ONNXFunction(aten::native_layer_norm.default, is_custom=False, is_complex=False),\n)\n- onnx_args: Tuple[length=5](\n`TorchScriptTensor(f32[4, 1024, 1024])`,\nList[length=1](\n1024,\n),\n`TorchScriptTensor(f32[1024])`,\n`TorchScriptTensor(f32[1024])`,\n1e-06,\n)\n- onnx_kwargs: Dict[length=0](\nNone)\n- diagnostic_context: \n## Checking perfect match...\n`TracedOnnxFunction(aten_native_layer_norm)`\nmatch score: 2\n## Return values\n`TracedOnnxFunction(aten_native_layer_norm)`", + "text":"FX Node: aten.native_layer_norm.default. \nONNX Node: aten_native_layer_norm[opset=pkg.onnxscript.torch_lib;is_custom=False]. \n" + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"OnnxFunctionDispatcher._find_the_perfect_or_nearest_match_onnxfunction" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/onnxfunction_dispatcher.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":199 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0014", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Node: call_function:aten.native_layer_norm.default[name=native_layer_norm_1]. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature FxOnnxInterpreter.run_node\n- self: \n- node: fx.Node(aten.native_layer_norm.default)[call_function]:Tuple[length=3](\nTensor(f32[4, 1024, 1024]),\nTensor(f32[4, 1024, 1]),\nTensor(f32[4, 1024, 1]),\n)\n- fx_graph_module: torch.fx.GraphModule(torch_nn_modules_normalization_LayerNorm)\n- onnxfunction_dispatcher: \n- op_level_debug: False\n- onnxscript_graph: \n- onnxscript_tracer: \n- fx_name_to_onnxscript_value: Dict[length=3](\nadd_1: `TorchScriptTensor(f32[4, 1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___norm2_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm2_bias: `TorchScriptTensor(f32[1024])`,\n)\n## PyTorch source information\n```\n File \"/home/thebears/.local/lib/python3.10/site-packages/open_clip/timm_model.py\", line 196, in forward\n x = self.trunk(x)\n File \"/home/thebears/.local/lib/python3.10/site-packages/torch/nn/modules/module.py\", line 1725, in _call_impl\n return forward_call(*args, **kwargs)\n File \"/home/thebears/.local/lib/python3.10/site-packages/timm/models/vision_transformer.py\", line 853, in forward\n x = self.forward_features(x)\n File \"/home/thebears/.local/lib/python3.10/site-packages/timm/models/vision_transformer.py\", line 834, in forward_features\n x = self.blocks(x)\n File \"/home/thebears/.local/lib/python3.10/site-packages/torch/nn/modules/module.py\", line 1725, in _call_impl\n return forward_call(*args, **kwargs)\n File \"/home/thebears/.local/lib/python3.10/site-packages/timm/models/vision_transformer.py\", line 170, in forward\n x = x + self.drop_path2(self.ls2(self.mlp(self.norm2(x))))\n\n```\n## Return values\n", + "text":"FX Node: call_function:aten.native_layer_norm.default[name=native_layer_norm_1]. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"FxOnnxInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":414 + } + } + }, + { + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/open_clip/timm_model.py" + }, + "region":{ + "snippet":{ + "text":"x = self.trunk(x)" + }, + "startLine":196 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0008", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Node: call_function:[name=getitem_10]. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature FxOnnxInterpreter.run_node\n- self: \n- node: fx.Node()[call_function]:Tensor(f32[4, 1024, 1024])\n- fx_graph_module: torch.fx.GraphModule(torch_nn_modules_normalization_LayerNorm)\n- onnxfunction_dispatcher: \n- op_level_debug: False\n- onnxscript_graph: \n- onnxscript_tracer: \n- fx_name_to_onnxscript_value: Dict[length=4](\nadd_1: `TorchScriptTensor(f32[4, 1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___norm2_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm2_bias: `TorchScriptTensor(f32[1024])`,\nnative_layer_norm_1: Tuple[length=3](\n`TorchScriptTensor(f32[4, 1024, 1024])`,\n`TorchScriptTensor(f32[4, 1024, 1])`,\n`TorchScriptTensor(f32[4, 1024, 1])`,\n),\n)\n## PyTorch source information\n```\n File \"/home/thebears/.local/lib/python3.10/site-packages/open_clip/timm_model.py\", line 196, in forward\n x = self.trunk(x)\n File \"/home/thebears/.local/lib/python3.10/site-packages/torch/nn/modules/module.py\", line 1725, in _call_impl\n return forward_call(*args, **kwargs)\n File \"/home/thebears/.local/lib/python3.10/site-packages/timm/models/vision_transformer.py\", line 853, in forward\n x = self.forward_features(x)\n File \"/home/thebears/.local/lib/python3.10/site-packages/timm/models/vision_transformer.py\", line 834, in forward_features\n x = self.blocks(x)\n File \"/home/thebears/.local/lib/python3.10/site-packages/torch/nn/modules/module.py\", line 1725, in _call_impl\n return forward_call(*args, **kwargs)\n File \"/home/thebears/.local/lib/python3.10/site-packages/timm/models/vision_transformer.py\", line 170, in forward\n x = x + self.drop_path2(self.ls2(self.mlp(self.norm2(x))))\n\n```\n## Return values\n", + "text":"FX Node: call_function:[name=getitem_10]. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"FxOnnxInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":414 + } + } + }, + { + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/open_clip/timm_model.py" + }, + "region":{ + "snippet":{ + "text":"x = self.trunk(x)" + }, + "startLine":196 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0008", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Node: output:output[name=output]. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature FxOnnxInterpreter.run_node\n- self: \n- node: fx.Node(output)[output]:None\n- fx_graph_module: torch.fx.GraphModule(torch_nn_modules_normalization_LayerNorm)\n- onnxfunction_dispatcher: \n- op_level_debug: False\n- onnxscript_graph: \n- onnxscript_tracer: \n- fx_name_to_onnxscript_value: Dict[length=5](\nadd_1: `TorchScriptTensor(f32[4, 1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___norm2_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm2_bias: `TorchScriptTensor(f32[1024])`,\nnative_layer_norm_1: Tuple[length=3](\n`TorchScriptTensor(f32[4, 1024, 1024])`,\n`TorchScriptTensor(f32[4, 1024, 1])`,\n`TorchScriptTensor(f32[4, 1024, 1])`,\n),\ngetitem_10: `TorchScriptTensor(f32[4, 1024, 1024])`,\n)\n## Return values\n", + "text":"FX Node: output:output[name=output]. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"FxOnnxInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":414 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0008", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Graph: torch_nn_modules_normalization_LayerNorm. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature FxOnnxInterpreter.run\n- self: \n- fx_graph_module: torch.fx.GraphModule(torch_nn_modules_normalization_LayerNorm)\n- onnxfunction_dispatcher: \n- op_level_debug: False\n- parent_onnxscript_graph: \n## Return values\n", + "text":"FX Graph: torch_nn_modules_normalization_LayerNorm. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"FxOnnxInterpreter.run" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":496 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0007", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Node: call_module:getattr_L__self___trunk_blocks___0___norm2_1[name=getattr_l__self___trunk_blocks___0___norm2_1]. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature FxOnnxInterpreter.run_node\n- self: \n- node: fx.Node(getattr_L__self___trunk_blocks___0___norm2_1)[call_module]:Tensor(f32[4, 1024, 1024])\n- fx_graph_module: torch.fx.GraphModule(timm_models_vision_transformer_Block)\n- onnxfunction_dispatcher: \n- op_level_debug: False\n- onnxscript_graph: \n- onnxscript_tracer: \n- fx_name_to_onnxscript_value: Dict[length=16](\nclone: `TorchScriptTensor(f32[4, 1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_weight: `TorchScriptTensor(f32[3072, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_bias: `TorchScriptTensor(f32[3072])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_weight: `TorchScriptTensor(f32[1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm2_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm2_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___mlp_fc1_weight: `TorchScriptTensor(f32[4096, 1024])`,\n...\n)\n## PyTorch source information\n```\n File \"/home/thebears/.local/lib/python3.10/site-packages/open_clip/timm_model.py\", line 196, in forward\n x = self.trunk(x)\n File \"/home/thebears/.local/lib/python3.10/site-packages/torch/nn/modules/module.py\", line 1725, in _call_impl\n return forward_call(*args, **kwargs)\n File \"/home/thebears/.local/lib/python3.10/site-packages/timm/models/vision_transformer.py\", line 853, in forward\n x = self.forward_features(x)\n File \"/home/thebears/.local/lib/python3.10/site-packages/timm/models/vision_transformer.py\", line 834, in forward_features\n x = self.blocks(x)\n File \"/home/thebears/.local/lib/python3.10/site-packages/torch/nn/modules/module.py\", line 1725, in _call_impl\n return forward_call(*args, **kwargs)\n File \"/home/thebears/.local/lib/python3.10/site-packages/timm/models/vision_transformer.py\", line 170, in forward\n x = x + self.drop_path2(self.ls2(self.mlp(self.norm2(x))))\n\n```\n## Return values\n", + "text":"FX Node: call_module:getattr_L__self___trunk_blocks___0___norm2_1[name=getattr_l__self___trunk_blocks___0___norm2_1]. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"FxOnnxInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":414 + } + } + }, + { + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/open_clip/timm_model.py" + }, + "region":{ + "snippet":{ + "text":"x = self.trunk(x)" + }, + "startLine":196 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0008", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Node: placeholder:getitem_10[name=getitem_10]. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature FxOnnxInterpreter.run_node\n- self: \n- node: fx.Node(getitem_10)[placeholder]:Tensor(f32[4, 1024, 1024])\n- fx_graph_module: torch.fx.GraphModule(timm_layers_mlp_Mlp)\n- onnxfunction_dispatcher: \n- op_level_debug: False\n- onnxscript_graph: \n- onnxscript_tracer: \n- fx_name_to_onnxscript_value: Dict[length=0](\nNone)\n## PyTorch source information\n```\n File \"/home/thebears/.local/lib/python3.10/site-packages/open_clip/timm_model.py\", line 196, in forward\n x = self.trunk(x)\n File \"/home/thebears/.local/lib/python3.10/site-packages/torch/nn/modules/module.py\", line 1725, in _call_impl\n return forward_call(*args, **kwargs)\n File \"/home/thebears/.local/lib/python3.10/site-packages/timm/models/vision_transformer.py\", line 853, in forward\n x = self.forward_features(x)\n File \"/home/thebears/.local/lib/python3.10/site-packages/timm/models/vision_transformer.py\", line 834, in forward_features\n x = self.blocks(x)\n File \"/home/thebears/.local/lib/python3.10/site-packages/torch/nn/modules/module.py\", line 1725, in _call_impl\n return forward_call(*args, **kwargs)\n File \"/home/thebears/.local/lib/python3.10/site-packages/timm/models/vision_transformer.py\", line 170, in forward\n x = x + self.drop_path2(self.ls2(self.mlp(self.norm2(x))))\n\n```\n## Return values\n", + "text":"FX Node: placeholder:getitem_10[name=getitem_10]. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"FxOnnxInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":414 + } + } + }, + { + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/open_clip/timm_model.py" + }, + "region":{ + "snippet":{ + "text":"x = self.trunk(x)" + }, + "startLine":196 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0008", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___0___mlp_fc1_weight[name=p_getattr_l__self___trunk_blocks___0___mlp_fc1_weight]. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature FxOnnxInterpreter.run_node\n- self: \n- node: fx.Node(p_getattr_l__self___trunk_blocks___0___mlp_fc1_weight)[placeholder]:Tensor(f32[4096, 1024])\n- fx_graph_module: torch.fx.GraphModule(timm_layers_mlp_Mlp)\n- onnxfunction_dispatcher: \n- op_level_debug: False\n- onnxscript_graph: \n- onnxscript_tracer: \n- fx_name_to_onnxscript_value: Dict[length=1](\ngetitem_10: `TorchScriptTensor(f32[4, 1024, 1024])`,\n)\n## Return values\n", + "text":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___0___mlp_fc1_weight[name=p_getattr_l__self___trunk_blocks___0___mlp_fc1_weight]. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"FxOnnxInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":414 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0008", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___0___mlp_fc1_bias[name=p_getattr_l__self___trunk_blocks___0___mlp_fc1_bias]. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature FxOnnxInterpreter.run_node\n- self: \n- node: fx.Node(p_getattr_l__self___trunk_blocks___0___mlp_fc1_bias)[placeholder]:Tensor(f32[4096])\n- fx_graph_module: torch.fx.GraphModule(timm_layers_mlp_Mlp)\n- onnxfunction_dispatcher: \n- op_level_debug: False\n- onnxscript_graph: \n- onnxscript_tracer: \n- fx_name_to_onnxscript_value: Dict[length=2](\ngetitem_10: `TorchScriptTensor(f32[4, 1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___mlp_fc1_weight: `TorchScriptTensor(f32[4096, 1024])`,\n)\n## Return values\n", + "text":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___0___mlp_fc1_bias[name=p_getattr_l__self___trunk_blocks___0___mlp_fc1_bias]. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"FxOnnxInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":414 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0008", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___0___mlp_fc2_weight[name=p_getattr_l__self___trunk_blocks___0___mlp_fc2_weight]. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature FxOnnxInterpreter.run_node\n- self: \n- node: fx.Node(p_getattr_l__self___trunk_blocks___0___mlp_fc2_weight)[placeholder]:Tensor(f32[1024, 4096])\n- fx_graph_module: torch.fx.GraphModule(timm_layers_mlp_Mlp)\n- onnxfunction_dispatcher: \n- op_level_debug: False\n- onnxscript_graph: \n- onnxscript_tracer: \n- fx_name_to_onnxscript_value: Dict[length=3](\ngetitem_10: `TorchScriptTensor(f32[4, 1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___mlp_fc1_weight: `TorchScriptTensor(f32[4096, 1024])`,\np_getattr_l__self___trunk_blocks___0___mlp_fc1_bias: `TorchScriptTensor(f32[4096])`,\n)\n## Return values\n", + "text":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___0___mlp_fc2_weight[name=p_getattr_l__self___trunk_blocks___0___mlp_fc2_weight]. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"FxOnnxInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":414 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0008", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___0___mlp_fc2_bias[name=p_getattr_l__self___trunk_blocks___0___mlp_fc2_bias]. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature FxOnnxInterpreter.run_node\n- self: \n- node: fx.Node(p_getattr_l__self___trunk_blocks___0___mlp_fc2_bias)[placeholder]:Tensor(f32[1024])\n- fx_graph_module: torch.fx.GraphModule(timm_layers_mlp_Mlp)\n- onnxfunction_dispatcher: \n- op_level_debug: False\n- onnxscript_graph: \n- onnxscript_tracer: \n- fx_name_to_onnxscript_value: Dict[length=4](\ngetitem_10: `TorchScriptTensor(f32[4, 1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___mlp_fc1_weight: `TorchScriptTensor(f32[4096, 1024])`,\np_getattr_l__self___trunk_blocks___0___mlp_fc1_bias: `TorchScriptTensor(f32[4096])`,\np_getattr_l__self___trunk_blocks___0___mlp_fc2_weight: `TorchScriptTensor(f32[1024, 4096])`,\n)\n## Return values\n", + "text":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___0___mlp_fc2_bias[name=p_getattr_l__self___trunk_blocks___0___mlp_fc2_bias]. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"FxOnnxInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":414 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0008", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Node: placeholder:getitem_10[name=getitem_10]. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature FxOnnxInterpreter.run_node\n- self: \n- node: fx.Node(getitem_10)[placeholder]:Tensor(f32[4, 1024, 1024])\n- fx_graph_module: torch.fx.GraphModule(torch_nn_modules_linear_Linear)\n- onnxfunction_dispatcher: \n- op_level_debug: False\n- onnxscript_graph: \n- onnxscript_tracer: \n- fx_name_to_onnxscript_value: Dict[length=0](\nNone)\n## PyTorch source information\n```\n File \"/home/thebears/.local/lib/python3.10/site-packages/open_clip/timm_model.py\", line 196, in forward\n x = self.trunk(x)\n File \"/home/thebears/.local/lib/python3.10/site-packages/torch/nn/modules/module.py\", line 1725, in _call_impl\n return forward_call(*args, **kwargs)\n File \"/home/thebears/.local/lib/python3.10/site-packages/timm/models/vision_transformer.py\", line 853, in forward\n x = self.forward_features(x)\n File \"/home/thebears/.local/lib/python3.10/site-packages/timm/models/vision_transformer.py\", line 834, in forward_features\n x = self.blocks(x)\n File \"/home/thebears/.local/lib/python3.10/site-packages/torch/nn/modules/module.py\", line 1725, in _call_impl\n return forward_call(*args, **kwargs)\n File \"/home/thebears/.local/lib/python3.10/site-packages/timm/models/vision_transformer.py\", line 170, in forward\n x = x + self.drop_path2(self.ls2(self.mlp(self.norm2(x))))\n\n```\n## Return values\n", + "text":"FX Node: placeholder:getitem_10[name=getitem_10]. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"FxOnnxInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":414 + } + } + }, + { + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/open_clip/timm_model.py" + }, + "region":{ + "snippet":{ + "text":"x = self.trunk(x)" + }, + "startLine":196 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0008", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___0___mlp_fc1_weight[name=p_getattr_l__self___trunk_blocks___0___mlp_fc1_weight]. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature FxOnnxInterpreter.run_node\n- self: \n- node: fx.Node(p_getattr_l__self___trunk_blocks___0___mlp_fc1_weight)[placeholder]:Tensor(f32[4096, 1024])\n- fx_graph_module: torch.fx.GraphModule(torch_nn_modules_linear_Linear)\n- onnxfunction_dispatcher: \n- op_level_debug: False\n- onnxscript_graph: \n- onnxscript_tracer: \n- fx_name_to_onnxscript_value: Dict[length=1](\ngetitem_10: `TorchScriptTensor(f32[4, 1024, 1024])`,\n)\n## Return values\n", + "text":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___0___mlp_fc1_weight[name=p_getattr_l__self___trunk_blocks___0___mlp_fc1_weight]. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"FxOnnxInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":414 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0008", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___0___mlp_fc1_bias[name=p_getattr_l__self___trunk_blocks___0___mlp_fc1_bias]. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature FxOnnxInterpreter.run_node\n- self: \n- node: fx.Node(p_getattr_l__self___trunk_blocks___0___mlp_fc1_bias)[placeholder]:Tensor(f32[4096])\n- fx_graph_module: torch.fx.GraphModule(torch_nn_modules_linear_Linear)\n- onnxfunction_dispatcher: \n- op_level_debug: False\n- onnxscript_graph: \n- onnxscript_tracer: \n- fx_name_to_onnxscript_value: Dict[length=2](\ngetitem_10: `TorchScriptTensor(f32[4, 1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___mlp_fc1_weight: `TorchScriptTensor(f32[4096, 1024])`,\n)\n## Return values\n", + "text":"FX Node: placeholder:p_getattr_l__self___trunk_blocks___0___mlp_fc1_bias[name=p_getattr_l__self___trunk_blocks___0___mlp_fc1_bias]. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"FxOnnxInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":414 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0008", + "stacks":[] + }, + { + "message":{ + "markdown":"Searching operator overload: 'aten.view.default' in onnx registry...\n\n\n## Additional Message:\n\n## Function Signature\n### Function Signature OnnxFunctionDispatcher.get_function_overloads\n- self: \n- node: fx.Node(aten.view.default)[call_function]:Tensor(f32[4096, 1024])\n- diagnostic_context: \n## Return values\nList[length=1](\nregistration.ONNXFunction(aten::view.default, is_custom=False, is_complex=False),\n)", + "text":"Searching operator overload: 'aten.view.default' in onnx registry...\n" + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"OnnxFunctionDispatcher.get_function_overloads" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/onnxfunction_dispatcher.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":353 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0016", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Node: aten.view.default. \nONNX Node: aten_view[opset=pkg.onnxscript.torch_lib;is_custom=False]. \n\n\n## Additional Message:\n\n## Function Signature\n### Function Signature OnnxFunctionDispatcher._find_the_perfect_or_nearest_match_onnxfunction\n- self: \n- node: fx.Node(aten.view.default)[call_function]:Tensor(f32[4096, 1024])\n- default_and_custom_functions: List[length=1](\nregistration.ONNXFunction(aten::view.default, is_custom=False, is_complex=False),\n)\n- onnx_args: Tuple[length=2](\n`TorchScriptTensor(f32[4, 1024, 1024])`,\nList[length=2](\n4096,\n1024,\n),\n)\n- onnx_kwargs: Dict[length=0](\nNone)\n- diagnostic_context: \n## Checking perfect match...\n`TracedOnnxFunction(aten_view)`\nmatch score: 2\n## Return values\n`TracedOnnxFunction(aten_view)`", + "text":"FX Node: aten.view.default. \nONNX Node: aten_view[opset=pkg.onnxscript.torch_lib;is_custom=False]. \n" + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"OnnxFunctionDispatcher._find_the_perfect_or_nearest_match_onnxfunction" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/onnxfunction_dispatcher.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":199 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0014", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Node: call_function:aten.view.default[name=view_7]. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature FxOnnxInterpreter.run_node\n- self: \n- node: fx.Node(aten.view.default)[call_function]:Tensor(f32[4096, 1024])\n- fx_graph_module: torch.fx.GraphModule(torch_nn_modules_linear_Linear)\n- onnxfunction_dispatcher: \n- op_level_debug: False\n- onnxscript_graph: \n- onnxscript_tracer: \n- fx_name_to_onnxscript_value: Dict[length=3](\ngetitem_10: `TorchScriptTensor(f32[4, 1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___mlp_fc1_weight: `TorchScriptTensor(f32[4096, 1024])`,\np_getattr_l__self___trunk_blocks___0___mlp_fc1_bias: `TorchScriptTensor(f32[4096])`,\n)\n## PyTorch source information\n```\n File \"/home/thebears/.local/lib/python3.10/site-packages/open_clip/timm_model.py\", line 196, in forward\n x = self.trunk(x)\n File \"/home/thebears/.local/lib/python3.10/site-packages/torch/nn/modules/module.py\", line 1725, in _call_impl\n return forward_call(*args, **kwargs)\n File \"/home/thebears/.local/lib/python3.10/site-packages/timm/models/vision_transformer.py\", line 853, in forward\n x = self.forward_features(x)\n File \"/home/thebears/.local/lib/python3.10/site-packages/timm/models/vision_transformer.py\", line 834, in forward_features\n x = self.blocks(x)\n File \"/home/thebears/.local/lib/python3.10/site-packages/torch/nn/modules/module.py\", line 1725, in _call_impl\n return forward_call(*args, **kwargs)\n File \"/home/thebears/.local/lib/python3.10/site-packages/timm/models/vision_transformer.py\", line 170, in forward\n x = x + self.drop_path2(self.ls2(self.mlp(self.norm2(x))))\n File \"/home/thebears/.local/lib/python3.10/site-packages/torch/nn/modules/module.py\", line 1725, in _call_impl\n return forward_call(*args, **kwargs)\n File \"/home/thebears/.local/lib/python3.10/site-packages/timm/layers/mlp.py\", line 44, in forward\n x = self.fc1(x)\n\n```\n## Return values\n", + "text":"FX Node: call_function:aten.view.default[name=view_7]. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"FxOnnxInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":414 + } + } + }, + { + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/open_clip/timm_model.py" + }, + "region":{ + "snippet":{ + "text":"x = self.trunk(x)" + }, + "startLine":196 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0008", + "stacks":[] + }, + { + "message":{ + "markdown":"Searching operator overload: 'aten.t.default' in onnx registry...\n\n\n## Additional Message:\n\n## Function Signature\n### Function Signature OnnxFunctionDispatcher.get_function_overloads\n- self: \n- node: fx.Node(aten.t.default)[call_function]:Tensor(f32[1024, 4096])\n- diagnostic_context: \n## Return values\nList[length=1](\nregistration.ONNXFunction(aten::t.default, is_custom=False, is_complex=False),\n)", + "text":"Searching operator overload: 'aten.t.default' in onnx registry...\n" + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"OnnxFunctionDispatcher.get_function_overloads" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/onnxfunction_dispatcher.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":353 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0016", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Node: aten.t.default. \nONNX Node: aten_t[opset=pkg.onnxscript.torch_lib;is_custom=False]. \n\n\n## Additional Message:\n\n## Function Signature\n### Function Signature OnnxFunctionDispatcher._find_the_perfect_or_nearest_match_onnxfunction\n- self: \n- node: fx.Node(aten.t.default)[call_function]:Tensor(f32[1024, 4096])\n- default_and_custom_functions: List[length=1](\nregistration.ONNXFunction(aten::t.default, is_custom=False, is_complex=False),\n)\n- onnx_args: Tuple[length=1](\n`TorchScriptTensor(f32[4096, 1024])`,\n)\n- onnx_kwargs: Dict[length=0](\nNone)\n- diagnostic_context: \n## Checking perfect match...\n`TracedOnnxFunction(aten_t)`\nmatch score: 1\n## Return values\n`TracedOnnxFunction(aten_t)`", + "text":"FX Node: aten.t.default. \nONNX Node: aten_t[opset=pkg.onnxscript.torch_lib;is_custom=False]. \n" + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"OnnxFunctionDispatcher._find_the_perfect_or_nearest_match_onnxfunction" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/onnxfunction_dispatcher.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":199 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0014", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Node: call_function:aten.t.default[name=t_2]. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature FxOnnxInterpreter.run_node\n- self: \n- node: fx.Node(aten.t.default)[call_function]:Tensor(f32[1024, 4096])\n- fx_graph_module: torch.fx.GraphModule(torch_nn_modules_linear_Linear)\n- onnxfunction_dispatcher: \n- op_level_debug: False\n- onnxscript_graph: \n- onnxscript_tracer: \n- fx_name_to_onnxscript_value: Dict[length=4](\ngetitem_10: `TorchScriptTensor(f32[4, 1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___mlp_fc1_weight: `TorchScriptTensor(f32[4096, 1024])`,\np_getattr_l__self___trunk_blocks___0___mlp_fc1_bias: `TorchScriptTensor(f32[4096])`,\nview_7: `TorchScriptTensor(f32[4096, 1024])`,\n)\n## PyTorch source information\n```\n File \"/home/thebears/.local/lib/python3.10/site-packages/open_clip/timm_model.py\", line 196, in forward\n x = self.trunk(x)\n File \"/home/thebears/.local/lib/python3.10/site-packages/torch/nn/modules/module.py\", line 1725, in _call_impl\n return forward_call(*args, **kwargs)\n File \"/home/thebears/.local/lib/python3.10/site-packages/timm/models/vision_transformer.py\", line 853, in forward\n x = self.forward_features(x)\n File \"/home/thebears/.local/lib/python3.10/site-packages/timm/models/vision_transformer.py\", line 834, in forward_features\n x = self.blocks(x)\n File \"/home/thebears/.local/lib/python3.10/site-packages/torch/nn/modules/module.py\", line 1725, in _call_impl\n return forward_call(*args, **kwargs)\n File \"/home/thebears/.local/lib/python3.10/site-packages/timm/models/vision_transformer.py\", line 170, in forward\n x = x + self.drop_path2(self.ls2(self.mlp(self.norm2(x))))\n File \"/home/thebears/.local/lib/python3.10/site-packages/torch/nn/modules/module.py\", line 1725, in _call_impl\n return forward_call(*args, **kwargs)\n File \"/home/thebears/.local/lib/python3.10/site-packages/timm/layers/mlp.py\", line 44, in forward\n x = self.fc1(x)\n\n```\n## Return values\n", + "text":"FX Node: call_function:aten.t.default[name=t_2]. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"FxOnnxInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":414 + } + } + }, + { + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/open_clip/timm_model.py" + }, + "region":{ + "snippet":{ + "text":"x = self.trunk(x)" + }, + "startLine":196 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0008", + "stacks":[] + }, + { + "message":{ + "markdown":"Searching operator overload: 'aten.addmm.default' in onnx registry...\n\n\n## Additional Message:\n\n## Function Signature\n### Function Signature OnnxFunctionDispatcher.get_function_overloads\n- self: \n- node: fx.Node(aten.addmm.default)[call_function]:Tensor(f32[4096, 4096])\n- diagnostic_context: \n## Return values\nList[length=1](\nregistration.ONNXFunction(aten::addmm.default, is_custom=False, is_complex=False),\n)", + "text":"Searching operator overload: 'aten.addmm.default' in onnx registry...\n" + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"OnnxFunctionDispatcher.get_function_overloads" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/onnxfunction_dispatcher.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":353 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0016", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Node: aten.addmm.default. \nONNX Node: aten_addmm[opset=pkg.onnxscript.torch_lib;is_custom=False]. \n\n\n## Additional Message:\n\n## Function Signature\n### Function Signature OnnxFunctionDispatcher._find_the_perfect_or_nearest_match_onnxfunction\n- self: \n- node: fx.Node(aten.addmm.default)[call_function]:Tensor(f32[4096, 4096])\n- default_and_custom_functions: List[length=1](\nregistration.ONNXFunction(aten::addmm.default, is_custom=False, is_complex=False),\n)\n- onnx_args: Tuple[length=3](\n`TorchScriptTensor(f32[4096])`,\n`TorchScriptTensor(f32[4096, 1024])`,\n`TorchScriptTensor(f32[1024, 4096])`,\n)\n- onnx_kwargs: Dict[length=2](\nbeta: 1,\nalpha: 1,\n)\n- diagnostic_context: \n## Checking perfect match...\n`TracedOnnxFunction(aten_addmm)`\n### Failed: attribute 'beta' type mismatch!\nActual vs\nExpected AttrType.FLOAT\n### Failed: attribute 'alpha' type mismatch!\nActual vs\nExpected AttrType.FLOAT\nmatch score: 1\n### Exact match is not found!\nCannot find a perfect match of symbolic overload, a nearest match is found. Please check the ONNX output carefully. \n\n## Return values\n`TracedOnnxFunction(aten_addmm)`", + "text":"FX Node: aten.addmm.default. \nONNX Node: aten_addmm[opset=pkg.onnxscript.torch_lib;is_custom=False]. \n" + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"fail", + "level":"warning", + "locations":[ + { + "message":{ + "text":"OnnxFunctionDispatcher._find_the_perfect_or_nearest_match_onnxfunction" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/onnxfunction_dispatcher.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":199 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0014", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Node: call_function:aten.addmm.default[name=addmm_2]. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature FxOnnxInterpreter.run_node\n- self: \n- node: fx.Node(aten.addmm.default)[call_function]:Tensor(f32[4096, 4096])\n- fx_graph_module: torch.fx.GraphModule(torch_nn_modules_linear_Linear)\n- onnxfunction_dispatcher: \n- op_level_debug: False\n- onnxscript_graph: \n- onnxscript_tracer: \n- fx_name_to_onnxscript_value: Dict[length=5](\ngetitem_10: `TorchScriptTensor(f32[4, 1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___mlp_fc1_weight: `TorchScriptTensor(f32[4096, 1024])`,\np_getattr_l__self___trunk_blocks___0___mlp_fc1_bias: `TorchScriptTensor(f32[4096])`,\nview_7: `TorchScriptTensor(f32[4096, 1024])`,\nt_2: `TorchScriptTensor(f32[1024, 4096])`,\n)\n## PyTorch source information\n```\n File \"/home/thebears/.local/lib/python3.10/site-packages/open_clip/timm_model.py\", line 196, in forward\n x = self.trunk(x)\n File \"/home/thebears/.local/lib/python3.10/site-packages/torch/nn/modules/module.py\", line 1725, in _call_impl\n return forward_call(*args, **kwargs)\n File \"/home/thebears/.local/lib/python3.10/site-packages/timm/models/vision_transformer.py\", line 853, in forward\n x = self.forward_features(x)\n File \"/home/thebears/.local/lib/python3.10/site-packages/timm/models/vision_transformer.py\", line 834, in forward_features\n x = self.blocks(x)\n File \"/home/thebears/.local/lib/python3.10/site-packages/torch/nn/modules/module.py\", line 1725, in _call_impl\n return forward_call(*args, **kwargs)\n File \"/home/thebears/.local/lib/python3.10/site-packages/timm/models/vision_transformer.py\", line 170, in forward\n x = x + self.drop_path2(self.ls2(self.mlp(self.norm2(x))))\n File \"/home/thebears/.local/lib/python3.10/site-packages/torch/nn/modules/module.py\", line 1725, in _call_impl\n return forward_call(*args, **kwargs)\n File \"/home/thebears/.local/lib/python3.10/site-packages/timm/layers/mlp.py\", line 44, in forward\n x = self.fc1(x)\n\n```\n## Return values\n", + "text":"FX Node: call_function:aten.addmm.default[name=addmm_2]. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"FxOnnxInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":414 + } + } + }, + { + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/open_clip/timm_model.py" + }, + "region":{ + "snippet":{ + "text":"x = self.trunk(x)" + }, + "startLine":196 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0008", + "stacks":[] + }, + { + "message":{ + "markdown":"Searching operator overload: 'aten.view.default' in onnx registry...\n\n\n## Additional Message:\n\n## Function Signature\n### Function Signature OnnxFunctionDispatcher.get_function_overloads\n- self: \n- node: fx.Node(aten.view.default)[call_function]:Tensor(f32[4, 1024, 4096])\n- diagnostic_context: \n## Return values\nList[length=1](\nregistration.ONNXFunction(aten::view.default, is_custom=False, is_complex=False),\n)", + "text":"Searching operator overload: 'aten.view.default' in onnx registry...\n" + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"OnnxFunctionDispatcher.get_function_overloads" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/onnxfunction_dispatcher.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":353 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0016", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Node: aten.view.default. \nONNX Node: aten_view[opset=pkg.onnxscript.torch_lib;is_custom=False]. \n\n\n## Additional Message:\n\n## Function Signature\n### Function Signature OnnxFunctionDispatcher._find_the_perfect_or_nearest_match_onnxfunction\n- self: \n- node: fx.Node(aten.view.default)[call_function]:Tensor(f32[4, 1024, 4096])\n- default_and_custom_functions: List[length=1](\nregistration.ONNXFunction(aten::view.default, is_custom=False, is_complex=False),\n)\n- onnx_args: Tuple[length=2](\n`TorchScriptTensor(f32[4096, 4096])`,\nList[length=3](\n4,\n1024,\n4096,\n),\n)\n- onnx_kwargs: Dict[length=0](\nNone)\n- diagnostic_context: \n## Checking perfect match...\n`TracedOnnxFunction(aten_view)`\nmatch score: 2\n## Return values\n`TracedOnnxFunction(aten_view)`", + "text":"FX Node: aten.view.default. \nONNX Node: aten_view[opset=pkg.onnxscript.torch_lib;is_custom=False]. \n" + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"OnnxFunctionDispatcher._find_the_perfect_or_nearest_match_onnxfunction" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/onnxfunction_dispatcher.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":199 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0014", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Node: call_function:aten.view.default[name=view_8]. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature FxOnnxInterpreter.run_node\n- self: \n- node: fx.Node(aten.view.default)[call_function]:Tensor(f32[4, 1024, 4096])\n- fx_graph_module: torch.fx.GraphModule(torch_nn_modules_linear_Linear)\n- onnxfunction_dispatcher: \n- op_level_debug: False\n- onnxscript_graph: \n- onnxscript_tracer: \n- fx_name_to_onnxscript_value: Dict[length=6](\ngetitem_10: `TorchScriptTensor(f32[4, 1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___mlp_fc1_weight: `TorchScriptTensor(f32[4096, 1024])`,\np_getattr_l__self___trunk_blocks___0___mlp_fc1_bias: `TorchScriptTensor(f32[4096])`,\nview_7: `TorchScriptTensor(f32[4096, 1024])`,\nt_2: `TorchScriptTensor(f32[1024, 4096])`,\naddmm_2: `TorchScriptTensor(f32[4096, 4096])`,\n)\n## PyTorch source information\n```\n File \"/home/thebears/.local/lib/python3.10/site-packages/open_clip/timm_model.py\", line 196, in forward\n x = self.trunk(x)\n File \"/home/thebears/.local/lib/python3.10/site-packages/torch/nn/modules/module.py\", line 1725, in _call_impl\n return forward_call(*args, **kwargs)\n File \"/home/thebears/.local/lib/python3.10/site-packages/timm/models/vision_transformer.py\", line 853, in forward\n x = self.forward_features(x)\n File \"/home/thebears/.local/lib/python3.10/site-packages/timm/models/vision_transformer.py\", line 834, in forward_features\n x = self.blocks(x)\n File \"/home/thebears/.local/lib/python3.10/site-packages/torch/nn/modules/module.py\", line 1725, in _call_impl\n return forward_call(*args, **kwargs)\n File \"/home/thebears/.local/lib/python3.10/site-packages/timm/models/vision_transformer.py\", line 170, in forward\n x = x + self.drop_path2(self.ls2(self.mlp(self.norm2(x))))\n File \"/home/thebears/.local/lib/python3.10/site-packages/torch/nn/modules/module.py\", line 1725, in _call_impl\n return forward_call(*args, **kwargs)\n File \"/home/thebears/.local/lib/python3.10/site-packages/timm/layers/mlp.py\", line 44, in forward\n x = self.fc1(x)\n\n```\n## Return values\n", + "text":"FX Node: call_function:aten.view.default[name=view_8]. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"FxOnnxInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":414 + } + } + }, + { + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/open_clip/timm_model.py" + }, + "region":{ + "snippet":{ + "text":"x = self.trunk(x)" + }, + "startLine":196 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0008", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Node: output:output[name=output]. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature FxOnnxInterpreter.run_node\n- self: \n- node: fx.Node(output)[output]:None\n- fx_graph_module: torch.fx.GraphModule(torch_nn_modules_linear_Linear)\n- onnxfunction_dispatcher: \n- op_level_debug: False\n- onnxscript_graph: \n- onnxscript_tracer: \n- fx_name_to_onnxscript_value: Dict[length=7](\ngetitem_10: `TorchScriptTensor(f32[4, 1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___mlp_fc1_weight: `TorchScriptTensor(f32[4096, 1024])`,\np_getattr_l__self___trunk_blocks___0___mlp_fc1_bias: `TorchScriptTensor(f32[4096])`,\nview_7: `TorchScriptTensor(f32[4096, 1024])`,\nt_2: `TorchScriptTensor(f32[1024, 4096])`,\naddmm_2: `TorchScriptTensor(f32[4096, 4096])`,\nview_8: `TorchScriptTensor(f32[4, 1024, 4096])`,\n)\n## Return values\n", + "text":"FX Node: output:output[name=output]. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"FxOnnxInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":414 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0008", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Graph: torch_nn_modules_linear_Linear. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature FxOnnxInterpreter.run\n- self: \n- fx_graph_module: torch.fx.GraphModule(torch_nn_modules_linear_Linear)\n- onnxfunction_dispatcher: \n- op_level_debug: False\n- parent_onnxscript_graph: \n## Return values\n", + "text":"FX Graph: torch_nn_modules_linear_Linear. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"FxOnnxInterpreter.run" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":496 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0007", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Node: call_module:getattr_L__self___trunk_blocks___0___mlp_fc1_1[name=getattr_l__self___trunk_blocks___0___mlp_fc1_1]. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature FxOnnxInterpreter.run_node\n- self: \n- node: fx.Node(getattr_L__self___trunk_blocks___0___mlp_fc1_1)[call_module]:Tensor(f32[4, 1024, 4096])\n- fx_graph_module: torch.fx.GraphModule(timm_layers_mlp_Mlp)\n- onnxfunction_dispatcher: \n- op_level_debug: False\n- onnxscript_graph: \n- onnxscript_tracer: \n- fx_name_to_onnxscript_value: Dict[length=5](\ngetitem_10: `TorchScriptTensor(f32[4, 1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___mlp_fc1_weight: `TorchScriptTensor(f32[4096, 1024])`,\np_getattr_l__self___trunk_blocks___0___mlp_fc1_bias: `TorchScriptTensor(f32[4096])`,\np_getattr_l__self___trunk_blocks___0___mlp_fc2_weight: `TorchScriptTensor(f32[1024, 4096])`,\np_getattr_l__self___trunk_blocks___0___mlp_fc2_bias: `TorchScriptTensor(f32[1024])`,\n)\n## PyTorch source information\n```\n File \"/home/thebears/.local/lib/python3.10/site-packages/open_clip/timm_model.py\", line 196, in forward\n x = self.trunk(x)\n File \"/home/thebears/.local/lib/python3.10/site-packages/torch/nn/modules/module.py\", line 1725, in _call_impl\n return forward_call(*args, **kwargs)\n File \"/home/thebears/.local/lib/python3.10/site-packages/timm/models/vision_transformer.py\", line 853, in forward\n x = self.forward_features(x)\n File \"/home/thebears/.local/lib/python3.10/site-packages/timm/models/vision_transformer.py\", line 834, in forward_features\n x = self.blocks(x)\n File \"/home/thebears/.local/lib/python3.10/site-packages/torch/nn/modules/module.py\", line 1725, in _call_impl\n return forward_call(*args, **kwargs)\n File \"/home/thebears/.local/lib/python3.10/site-packages/timm/models/vision_transformer.py\", line 170, in forward\n x = x + self.drop_path2(self.ls2(self.mlp(self.norm2(x))))\n File \"/home/thebears/.local/lib/python3.10/site-packages/torch/nn/modules/module.py\", line 1725, in _call_impl\n return forward_call(*args, **kwargs)\n File \"/home/thebears/.local/lib/python3.10/site-packages/timm/layers/mlp.py\", line 44, in forward\n x = self.fc1(x)\n\n```\n## Return values\n", + "text":"FX Node: call_module:getattr_L__self___trunk_blocks___0___mlp_fc1_1[name=getattr_l__self___trunk_blocks___0___mlp_fc1_1]. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"FxOnnxInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":414 + } + } + }, + { + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/open_clip/timm_model.py" + }, + "region":{ + "snippet":{ + "text":"x = self.trunk(x)" + }, + "startLine":196 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0008", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Node: placeholder:view_8[name=view_8]. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature FxOnnxInterpreter.run_node\n- self: \n- node: fx.Node(view_8)[placeholder]:Tensor(f32[4, 1024, 4096])\n- fx_graph_module: torch.fx.GraphModule(timm_layers_activations_GELUTanh)\n- onnxfunction_dispatcher: \n- op_level_debug: False\n- onnxscript_graph: \n- onnxscript_tracer: \n- fx_name_to_onnxscript_value: Dict[length=0](\nNone)\n## PyTorch source information\n```\n File \"/home/thebears/.local/lib/python3.10/site-packages/open_clip/timm_model.py\", line 196, in forward\n x = self.trunk(x)\n File \"/home/thebears/.local/lib/python3.10/site-packages/torch/nn/modules/module.py\", line 1725, in _call_impl\n return forward_call(*args, **kwargs)\n File \"/home/thebears/.local/lib/python3.10/site-packages/timm/models/vision_transformer.py\", line 853, in forward\n x = self.forward_features(x)\n File \"/home/thebears/.local/lib/python3.10/site-packages/timm/models/vision_transformer.py\", line 834, in forward_features\n x = self.blocks(x)\n File \"/home/thebears/.local/lib/python3.10/site-packages/torch/nn/modules/module.py\", line 1725, in _call_impl\n return forward_call(*args, **kwargs)\n File \"/home/thebears/.local/lib/python3.10/site-packages/timm/models/vision_transformer.py\", line 170, in forward\n x = x + self.drop_path2(self.ls2(self.mlp(self.norm2(x))))\n File \"/home/thebears/.local/lib/python3.10/site-packages/torch/nn/modules/module.py\", line 1725, in _call_impl\n return forward_call(*args, **kwargs)\n File \"/home/thebears/.local/lib/python3.10/site-packages/timm/layers/mlp.py\", line 44, in forward\n x = self.fc1(x)\n\n```\n## Return values\n", + "text":"FX Node: placeholder:view_8[name=view_8]. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"FxOnnxInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":414 + } + } + }, + { + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/open_clip/timm_model.py" + }, + "region":{ + "snippet":{ + "text":"x = self.trunk(x)" + }, + "startLine":196 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0008", + "stacks":[] + }, + { + "message":{ + "markdown":"Searching operator overload: 'aten.gelu.default' in onnx registry...\n\n\n## Additional Message:\n\n## Function Signature\n### Function Signature OnnxFunctionDispatcher.get_function_overloads\n- self: \n- node: fx.Node(aten.gelu.default)[call_function]:Tensor(f32[4, 1024, 4096])\n- diagnostic_context: \n## Return values\nList[length=1](\nregistration.ONNXFunction(aten::gelu.default, is_custom=False, is_complex=False),\n)", + "text":"Searching operator overload: 'aten.gelu.default' in onnx registry...\n" + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"OnnxFunctionDispatcher.get_function_overloads" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/onnxfunction_dispatcher.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":353 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0016", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Node: aten.gelu.default. \nONNX Node: aten_gelu[opset=pkg.onnxscript.torch_lib;is_custom=False]. \n\n\n## Additional Message:\n\n## Function Signature\n### Function Signature OnnxFunctionDispatcher._find_the_perfect_or_nearest_match_onnxfunction\n- self: \n- node: fx.Node(aten.gelu.default)[call_function]:Tensor(f32[4, 1024, 4096])\n- default_and_custom_functions: List[length=1](\nregistration.ONNXFunction(aten::gelu.default, is_custom=False, is_complex=False),\n)\n- onnx_args: Tuple[length=1](\n`TorchScriptTensor(f32[4, 1024, 4096])`,\n)\n- onnx_kwargs: Dict[length=1](\napproximate: tanh,\n)\n- diagnostic_context: \n## Checking perfect match...\n`TracedOnnxFunction(aten_gelu)`\nmatch score: 1\n## Return values\n`TracedOnnxFunction(aten_gelu)`", + "text":"FX Node: aten.gelu.default. \nONNX Node: aten_gelu[opset=pkg.onnxscript.torch_lib;is_custom=False]. \n" + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"informational", + "level":"none", + "locations":[ + { + "message":{ + "text":"OnnxFunctionDispatcher._find_the_perfect_or_nearest_match_onnxfunction" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/onnxfunction_dispatcher.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":199 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0014", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Node: call_function:aten.gelu.default[name=gelu]. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature FxOnnxInterpreter.run_node\n- self: \n- node: fx.Node(aten.gelu.default)[call_function]:Tensor(f32[4, 1024, 4096])\n- fx_graph_module: torch.fx.GraphModule(timm_layers_activations_GELUTanh)\n- onnxfunction_dispatcher: \n- op_level_debug: False\n- onnxscript_graph: \n- onnxscript_tracer: \n- fx_name_to_onnxscript_value: Dict[length=1](\nview_8: `TorchScriptTensor(f32[4, 1024, 4096])`,\n)\n## PyTorch source information\n```\n File \"/home/thebears/.local/lib/python3.10/site-packages/open_clip/timm_model.py\", line 196, in forward\n x = self.trunk(x)\n File \"/home/thebears/.local/lib/python3.10/site-packages/torch/nn/modules/module.py\", line 1725, in _call_impl\n return forward_call(*args, **kwargs)\n File \"/home/thebears/.local/lib/python3.10/site-packages/timm/models/vision_transformer.py\", line 853, in forward\n x = self.forward_features(x)\n File \"/home/thebears/.local/lib/python3.10/site-packages/timm/models/vision_transformer.py\", line 834, in forward_features\n x = self.blocks(x)\n File \"/home/thebears/.local/lib/python3.10/site-packages/torch/nn/modules/module.py\", line 1725, in _call_impl\n return forward_call(*args, **kwargs)\n File \"/home/thebears/.local/lib/python3.10/site-packages/timm/models/vision_transformer.py\", line 170, in forward\n x = x + self.drop_path2(self.ls2(self.mlp(self.norm2(x))))\n File \"/home/thebears/.local/lib/python3.10/site-packages/torch/nn/modules/module.py\", line 1725, in _call_impl\n return forward_call(*args, **kwargs)\n File \"/home/thebears/.local/lib/python3.10/site-packages/timm/layers/mlp.py\", line 45, in forward\n x = self.act(x)\n File \"/home/thebears/.local/lib/python3.10/site-packages/torch/nn/modules/module.py\", line 1725, in _call_impl\n return forward_call(*args, **kwargs)\n File \"/home/thebears/.local/lib/python3.10/site-packages/timm/layers/activations.py\", line 159, in forward\n return F.gelu(input, approximate='tanh')\n\n```\n## Exception log\n```\nTraceback (most recent call last):\n\n File \"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/diagnostics/infra/decorator.py\", line 136, in wrapper\n return_values = fn(*args, **kwargs)\n\n File \"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py\", line 471, in run_node\n self.call_function(\n\n File \"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py\", line 703, in call_function\n ] = symbolic_fn(*onnx_args, **onnx_kwargs)\n\n File \"/home/thebears/.local/lib/python3.10/site-packages/onnxscript/values.py\", line 625, in __call__\n return self.func(*args, **kwargs)\n\n File \"/home/thebears/.local/lib/python3.10/site-packages/onnxscript/function_libs/torch_lib/ops/nn.py\", line 474, in aten_gelu\n result = _aten_gelu_approximate_tanh(self)\n\n File \"/home/thebears/.local/lib/python3.10/site-packages/onnxscript/function_libs/torch_lib/ops/nn.py\", line 496, in _aten_gelu_approximate_tanh\n cubed = op.Pow(self, ir.tensor(3, dtype=self.dtype))\n\n File \"/home/thebears/.local/lib/python3.10/site-packages/onnx_ir/_convenience/_constructors.py\", line 103, in tensor\n raise TypeError(f\"dtype must be an instance of DataType. dtype={dtype}\")\n\nTypeError: dtype must be an instance of DataType. dtype=torch.float32\n\n```", + "text":"FX Node: call_function:aten.gelu.default[name=gelu]. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"fail", + "level":"error", + "locations":[ + { + "message":{ + "text":"FxOnnxInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":414 + } + } + }, + { + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/open_clip/timm_model.py" + }, + "region":{ + "snippet":{ + "text":"x = self.trunk(x)" + }, + "startLine":196 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0008", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Graph: timm_layers_activations_GELUTanh. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature FxOnnxInterpreter.run\n- self: \n- fx_graph_module: torch.fx.GraphModule(timm_layers_activations_GELUTanh)\n- onnxfunction_dispatcher: \n- op_level_debug: False\n- parent_onnxscript_graph: \n## Exception log\n```\nTraceback (most recent call last):\n\n File \"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/diagnostics/infra/decorator.py\", line 136, in wrapper\n return_values = fn(*args, **kwargs)\n\n File \"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py\", line 577, in run\n self.run_node(\n\n File \"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/diagnostics/infra/decorator.py\", line 152, in wrapper\n ctx.log_and_raise_if_error(diag)\n\n File \"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/diagnostics/infra/context.py\", line 369, in log_and_raise_if_error\n raise diagnostic.source_exception\n\n File \"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/diagnostics/infra/decorator.py\", line 136, in wrapper\n return_values = fn(*args, **kwargs)\n\n File \"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py\", line 471, in run_node\n self.call_function(\n\n File \"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py\", line 703, in call_function\n ] = symbolic_fn(*onnx_args, **onnx_kwargs)\n\n File \"/home/thebears/.local/lib/python3.10/site-packages/onnxscript/values.py\", line 625, in __call__\n return self.func(*args, **kwargs)\n\n File \"/home/thebears/.local/lib/python3.10/site-packages/onnxscript/function_libs/torch_lib/ops/nn.py\", line 474, in aten_gelu\n result = _aten_gelu_approximate_tanh(self)\n\n File \"/home/thebears/.local/lib/python3.10/site-packages/onnxscript/function_libs/torch_lib/ops/nn.py\", line 496, in _aten_gelu_approximate_tanh\n cubed = op.Pow(self, ir.tensor(3, dtype=self.dtype))\n\n File \"/home/thebears/.local/lib/python3.10/site-packages/onnx_ir/_convenience/_constructors.py\", line 103, in tensor\n raise TypeError(f\"dtype must be an instance of DataType. dtype={dtype}\")\n\nTypeError: dtype must be an instance of DataType. dtype=torch.float32\n\n```", + "text":"FX Graph: timm_layers_activations_GELUTanh. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"fail", + "level":"error", + "locations":[ + { + "message":{ + "text":"FxOnnxInterpreter.run" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":496 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0007", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Node: call_module:getattr_L__self___trunk_blocks___0___mlp_act_1[name=getattr_l__self___trunk_blocks___0___mlp_act_1]. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature FxOnnxInterpreter.run_node\n- self: \n- node: fx.Node(getattr_L__self___trunk_blocks___0___mlp_act_1)[call_module]:Tensor(f32[4, 1024, 4096])\n- fx_graph_module: torch.fx.GraphModule(timm_layers_mlp_Mlp)\n- onnxfunction_dispatcher: \n- op_level_debug: False\n- onnxscript_graph: \n- onnxscript_tracer: \n- fx_name_to_onnxscript_value: Dict[length=6](\ngetitem_10: `TorchScriptTensor(f32[4, 1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___mlp_fc1_weight: `TorchScriptTensor(f32[4096, 1024])`,\np_getattr_l__self___trunk_blocks___0___mlp_fc1_bias: `TorchScriptTensor(f32[4096])`,\np_getattr_l__self___trunk_blocks___0___mlp_fc2_weight: `TorchScriptTensor(f32[1024, 4096])`,\np_getattr_l__self___trunk_blocks___0___mlp_fc2_bias: `TorchScriptTensor(f32[1024])`,\ngetattr_l__self___trunk_blocks___0___mlp_fc1_1: `TorchScriptTensor(f32[4, 1024, 4096])`,\n)\n## PyTorch source information\n```\n File \"/home/thebears/.local/lib/python3.10/site-packages/open_clip/timm_model.py\", line 196, in forward\n x = self.trunk(x)\n File \"/home/thebears/.local/lib/python3.10/site-packages/torch/nn/modules/module.py\", line 1725, in _call_impl\n return forward_call(*args, **kwargs)\n File \"/home/thebears/.local/lib/python3.10/site-packages/timm/models/vision_transformer.py\", line 853, in forward\n x = self.forward_features(x)\n File \"/home/thebears/.local/lib/python3.10/site-packages/timm/models/vision_transformer.py\", line 834, in forward_features\n x = self.blocks(x)\n File \"/home/thebears/.local/lib/python3.10/site-packages/torch/nn/modules/module.py\", line 1725, in _call_impl\n return forward_call(*args, **kwargs)\n File \"/home/thebears/.local/lib/python3.10/site-packages/timm/models/vision_transformer.py\", line 170, in forward\n x = x + self.drop_path2(self.ls2(self.mlp(self.norm2(x))))\n File \"/home/thebears/.local/lib/python3.10/site-packages/torch/nn/modules/module.py\", line 1725, in _call_impl\n return forward_call(*args, **kwargs)\n File \"/home/thebears/.local/lib/python3.10/site-packages/timm/layers/mlp.py\", line 45, in forward\n x = self.act(x)\n File \"/home/thebears/.local/lib/python3.10/site-packages/torch/nn/modules/module.py\", line 1725, in _call_impl\n return forward_call(*args, **kwargs)\n File \"/home/thebears/.local/lib/python3.10/site-packages/timm/layers/activations.py\", line 159, in forward\n return F.gelu(input, approximate='tanh')\n\n```\n## Exception log\n```\nTraceback (most recent call last):\n\n File \"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/diagnostics/infra/decorator.py\", line 136, in wrapper\n return_values = fn(*args, **kwargs)\n\n File \"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py\", line 482, in run_node\n self.call_module(\n\n File \"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py\", line 811, in call_module\n sub_onnxscript_graph = self.run(\n\n File \"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/diagnostics/infra/decorator.py\", line 152, in wrapper\n ctx.log_and_raise_if_error(diag)\n\n File \"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/diagnostics/infra/context.py\", line 369, in log_and_raise_if_error\n raise diagnostic.source_exception\n\n File \"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/diagnostics/infra/decorator.py\", line 136, in wrapper\n return_values = fn(*args, **kwargs)\n\n File \"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py\", line 577, in run\n self.run_node(\n\n File \"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/diagnostics/infra/decorator.py\", line 152, in wrapper\n ctx.log_and_raise_if_error(diag)\n\n File \"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/diagnostics/infra/context.py\", line 369, in log_and_raise_if_error\n raise diagnostic.source_exception\n\n File \"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/diagnostics/infra/decorator.py\", line 136, in wrapper\n return_values = fn(*args, **kwargs)\n\n File \"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py\", line 471, in run_node\n self.call_function(\n\n File \"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py\", line 703, in call_function\n ] = symbolic_fn(*onnx_args, **onnx_kwargs)\n\n File \"/home/thebears/.local/lib/python3.10/site-packages/onnxscript/values.py\", line 625, in __call__\n return self.func(*args, **kwargs)\n\n File \"/home/thebears/.local/lib/python3.10/site-packages/onnxscript/function_libs/torch_lib/ops/nn.py\", line 474, in aten_gelu\n result = _aten_gelu_approximate_tanh(self)\n\n File \"/home/thebears/.local/lib/python3.10/site-packages/onnxscript/function_libs/torch_lib/ops/nn.py\", line 496, in _aten_gelu_approximate_tanh\n cubed = op.Pow(self, ir.tensor(3, dtype=self.dtype))\n\n File \"/home/thebears/.local/lib/python3.10/site-packages/onnx_ir/_convenience/_constructors.py\", line 103, in tensor\n raise TypeError(f\"dtype must be an instance of DataType. dtype={dtype}\")\n\nTypeError: dtype must be an instance of DataType. dtype=torch.float32\n\n```", + "text":"FX Node: call_module:getattr_L__self___trunk_blocks___0___mlp_act_1[name=getattr_l__self___trunk_blocks___0___mlp_act_1]. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"fail", + "level":"error", + "locations":[ + { + "message":{ + "text":"FxOnnxInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":414 + } + } + }, + { + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/open_clip/timm_model.py" + }, + "region":{ + "snippet":{ + "text":"x = self.trunk(x)" + }, + "startLine":196 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0008", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Graph: timm_layers_mlp_Mlp. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature FxOnnxInterpreter.run\n- self: \n- fx_graph_module: torch.fx.GraphModule(timm_layers_mlp_Mlp)\n- onnxfunction_dispatcher: \n- op_level_debug: False\n- parent_onnxscript_graph: \n## Exception log\n```\nTraceback (most recent call last):\n\n File \"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/diagnostics/infra/decorator.py\", line 136, in wrapper\n return_values = fn(*args, **kwargs)\n\n File \"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py\", line 577, in run\n self.run_node(\n\n File \"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/diagnostics/infra/decorator.py\", line 152, in wrapper\n ctx.log_and_raise_if_error(diag)\n\n File \"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/diagnostics/infra/context.py\", line 369, in log_and_raise_if_error\n raise diagnostic.source_exception\n\n File \"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/diagnostics/infra/decorator.py\", line 136, in wrapper\n return_values = fn(*args, **kwargs)\n\n File \"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py\", line 482, in run_node\n self.call_module(\n\n File \"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py\", line 811, in call_module\n sub_onnxscript_graph = self.run(\n\n File \"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/diagnostics/infra/decorator.py\", line 152, in wrapper\n ctx.log_and_raise_if_error(diag)\n\n File \"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/diagnostics/infra/context.py\", line 369, in log_and_raise_if_error\n raise diagnostic.source_exception\n\n File \"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/diagnostics/infra/decorator.py\", line 136, in wrapper\n return_values = fn(*args, **kwargs)\n\n File \"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py\", line 577, in run\n self.run_node(\n\n File \"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/diagnostics/infra/decorator.py\", line 152, in wrapper\n ctx.log_and_raise_if_error(diag)\n\n File \"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/diagnostics/infra/context.py\", line 369, in log_and_raise_if_error\n raise diagnostic.source_exception\n\n File \"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/diagnostics/infra/decorator.py\", line 136, in wrapper\n return_values = fn(*args, **kwargs)\n\n File \"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py\", line 471, in run_node\n self.call_function(\n\n File \"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py\", line 703, in call_function\n ] = symbolic_fn(*onnx_args, **onnx_kwargs)\n\n File \"/home/thebears/.local/lib/python3.10/site-packages/onnxscript/values.py\", line 625, in __call__\n return self.func(*args, **kwargs)\n\n File \"/home/thebears/.local/lib/python3.10/site-packages/onnxscript/function_libs/torch_lib/ops/nn.py\", line 474, in aten_gelu\n result = _aten_gelu_approximate_tanh(self)\n\n File \"/home/thebears/.local/lib/python3.10/site-packages/onnxscript/function_libs/torch_lib/ops/nn.py\", line 496, in _aten_gelu_approximate_tanh\n cubed = op.Pow(self, ir.tensor(3, dtype=self.dtype))\n\n File \"/home/thebears/.local/lib/python3.10/site-packages/onnx_ir/_convenience/_constructors.py\", line 103, in tensor\n raise TypeError(f\"dtype must be an instance of DataType. dtype={dtype}\")\n\nTypeError: dtype must be an instance of DataType. dtype=torch.float32\n\n```", + "text":"FX Graph: timm_layers_mlp_Mlp. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"fail", + "level":"error", + "locations":[ + { + "message":{ + "text":"FxOnnxInterpreter.run" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":496 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0007", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Node: call_module:getattr_L__self___trunk_blocks___0___mlp_1[name=getattr_l__self___trunk_blocks___0___mlp_1]. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature FxOnnxInterpreter.run_node\n- self: \n- node: fx.Node(getattr_L__self___trunk_blocks___0___mlp_1)[call_module]:Tensor(f32[4, 1024, 1024])\n- fx_graph_module: torch.fx.GraphModule(timm_models_vision_transformer_Block)\n- onnxfunction_dispatcher: \n- op_level_debug: False\n- onnxscript_graph: \n- onnxscript_tracer: \n- fx_name_to_onnxscript_value: Dict[length=17](\nclone: `TorchScriptTensor(f32[4, 1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_weight: `TorchScriptTensor(f32[3072, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_bias: `TorchScriptTensor(f32[3072])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_weight: `TorchScriptTensor(f32[1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm2_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm2_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___mlp_fc1_weight: `TorchScriptTensor(f32[4096, 1024])`,\n...\n)\n## PyTorch source information\n```\n File \"/home/thebears/.local/lib/python3.10/site-packages/open_clip/timm_model.py\", line 196, in forward\n x = self.trunk(x)\n File \"/home/thebears/.local/lib/python3.10/site-packages/torch/nn/modules/module.py\", line 1725, in _call_impl\n return forward_call(*args, **kwargs)\n File \"/home/thebears/.local/lib/python3.10/site-packages/timm/models/vision_transformer.py\", line 853, in forward\n x = self.forward_features(x)\n File \"/home/thebears/.local/lib/python3.10/site-packages/timm/models/vision_transformer.py\", line 834, in forward_features\n x = self.blocks(x)\n File \"/home/thebears/.local/lib/python3.10/site-packages/torch/nn/modules/module.py\", line 1725, in _call_impl\n return forward_call(*args, **kwargs)\n File \"/home/thebears/.local/lib/python3.10/site-packages/timm/models/vision_transformer.py\", line 170, in forward\n x = x + self.drop_path2(self.ls2(self.mlp(self.norm2(x))))\n File \"/home/thebears/.local/lib/python3.10/site-packages/torch/nn/modules/module.py\", line 1725, in _call_impl\n return forward_call(*args, **kwargs)\n File \"/home/thebears/.local/lib/python3.10/site-packages/timm/layers/mlp.py\", line 44, in forward\n x = self.fc1(x)\n\n```\n## Exception log\n```\nTraceback (most recent call last):\n\n File \"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/diagnostics/infra/decorator.py\", line 136, in wrapper\n return_values = fn(*args, **kwargs)\n\n File \"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py\", line 482, in run_node\n self.call_module(\n\n File \"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py\", line 811, in call_module\n sub_onnxscript_graph = self.run(\n\n File \"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/diagnostics/infra/decorator.py\", line 152, in wrapper\n ctx.log_and_raise_if_error(diag)\n\n File \"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/diagnostics/infra/context.py\", line 369, in log_and_raise_if_error\n raise diagnostic.source_exception\n\n File \"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/diagnostics/infra/decorator.py\", line 136, in wrapper\n return_values = fn(*args, **kwargs)\n\n File \"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py\", line 577, in run\n self.run_node(\n\n File \"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/diagnostics/infra/decorator.py\", line 152, in wrapper\n ctx.log_and_raise_if_error(diag)\n\n File \"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/diagnostics/infra/context.py\", line 369, in log_and_raise_if_error\n raise diagnostic.source_exception\n\n File \"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/diagnostics/infra/decorator.py\", line 136, in wrapper\n return_values = fn(*args, **kwargs)\n\n File \"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py\", line 482, in run_node\n self.call_module(\n\n File \"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py\", line 811, in call_module\n sub_onnxscript_graph = self.run(\n\n File \"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/diagnostics/infra/decorator.py\", line 152, in wrapper\n ctx.log_and_raise_if_error(diag)\n\n File \"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/diagnostics/infra/context.py\", line 369, in log_and_raise_if_error\n raise diagnostic.source_exception\n\n File \"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/diagnostics/infra/decorator.py\", line 136, in wrapper\n return_values = fn(*args, **kwargs)\n\n File \"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py\", line 577, in run\n self.run_node(\n\n File \"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/diagnostics/infra/decorator.py\", line 152, in wrapper\n ctx.log_and_raise_if_error(diag)\n\n File \"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/diagnostics/infra/context.py\", line 369, in log_and_raise_if_error\n raise diagnostic.source_exception\n\n File \"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/diagnostics/infra/decorator.py\", line 136, in wrapper\n return_values = fn(*args, **kwargs)\n\n File \"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py\", line 471, in run_node\n self.call_function(\n\n File \"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py\", line 703, in call_function\n ] = symbolic_fn(*onnx_args, **onnx_kwargs)\n\n File \"/home/thebears/.local/lib/python3.10/site-packages/onnxscript/values.py\", line 625, in __call__\n return self.func(*args, **kwargs)\n\n File \"/home/thebears/.local/lib/python3.10/site-packages/onnxscript/function_libs/torch_lib/ops/nn.py\", line 474, in aten_gelu\n result = _aten_gelu_approximate_tanh(self)\n\n File \"/home/thebears/.local/lib/python3.10/site-packages/onnxscript/function_libs/torch_lib/ops/nn.py\", line 496, in _aten_gelu_approximate_tanh\n cubed = op.Pow(self, ir.tensor(3, dtype=self.dtype))\n\n File \"/home/thebears/.local/lib/python3.10/site-packages/onnx_ir/_convenience/_constructors.py\", line 103, in tensor\n raise TypeError(f\"dtype must be an instance of DataType. dtype={dtype}\")\n\nTypeError: dtype must be an instance of DataType. dtype=torch.float32\n\n```", + "text":"FX Node: call_module:getattr_L__self___trunk_blocks___0___mlp_1[name=getattr_l__self___trunk_blocks___0___mlp_1]. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"fail", + "level":"error", + "locations":[ + { + "message":{ + "text":"FxOnnxInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":414 + } + } + }, + { + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/open_clip/timm_model.py" + }, + "region":{ + "snippet":{ + "text":"x = self.trunk(x)" + }, + "startLine":196 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0008", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Graph: timm_models_vision_transformer_Block. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature FxOnnxInterpreter.run\n- self: \n- fx_graph_module: torch.fx.GraphModule(timm_models_vision_transformer_Block)\n- onnxfunction_dispatcher: \n- op_level_debug: False\n- parent_onnxscript_graph: \n## Exception log\n```\nTraceback (most recent call last):\n\n File \"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/diagnostics/infra/decorator.py\", line 136, in wrapper\n return_values = fn(*args, **kwargs)\n\n File \"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py\", line 577, in run\n self.run_node(\n\n File \"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/diagnostics/infra/decorator.py\", line 152, in wrapper\n ctx.log_and_raise_if_error(diag)\n\n File \"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/diagnostics/infra/context.py\", line 369, in log_and_raise_if_error\n raise diagnostic.source_exception\n\n File \"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/diagnostics/infra/decorator.py\", line 136, in wrapper\n return_values = fn(*args, **kwargs)\n\n File \"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py\", line 482, in run_node\n self.call_module(\n\n File \"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py\", line 811, in call_module\n sub_onnxscript_graph = self.run(\n\n File \"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/diagnostics/infra/decorator.py\", line 152, in wrapper\n ctx.log_and_raise_if_error(diag)\n\n File \"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/diagnostics/infra/context.py\", line 369, in log_and_raise_if_error\n raise diagnostic.source_exception\n\n File \"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/diagnostics/infra/decorator.py\", line 136, in wrapper\n return_values = fn(*args, **kwargs)\n\n File \"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py\", line 577, in run\n self.run_node(\n\n File \"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/diagnostics/infra/decorator.py\", line 152, in wrapper\n ctx.log_and_raise_if_error(diag)\n\n File \"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/diagnostics/infra/context.py\", line 369, in log_and_raise_if_error\n raise diagnostic.source_exception\n\n File \"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/diagnostics/infra/decorator.py\", line 136, in wrapper\n return_values = fn(*args, **kwargs)\n\n File \"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py\", line 482, in run_node\n self.call_module(\n\n File \"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py\", line 811, in call_module\n sub_onnxscript_graph = self.run(\n\n File \"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/diagnostics/infra/decorator.py\", line 152, in wrapper\n ctx.log_and_raise_if_error(diag)\n\n File \"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/diagnostics/infra/context.py\", line 369, in log_and_raise_if_error\n raise diagnostic.source_exception\n\n File \"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/diagnostics/infra/decorator.py\", line 136, in wrapper\n return_values = fn(*args, **kwargs)\n\n File \"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py\", line 577, in run\n self.run_node(\n\n File \"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/diagnostics/infra/decorator.py\", line 152, in wrapper\n ctx.log_and_raise_if_error(diag)\n\n File \"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/diagnostics/infra/context.py\", line 369, in log_and_raise_if_error\n raise diagnostic.source_exception\n\n File \"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/diagnostics/infra/decorator.py\", line 136, in wrapper\n return_values = fn(*args, **kwargs)\n\n File \"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py\", line 471, in run_node\n self.call_function(\n\n File \"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py\", line 703, in call_function\n ] = symbolic_fn(*onnx_args, **onnx_kwargs)\n\n File \"/home/thebears/.local/lib/python3.10/site-packages/onnxscript/values.py\", line 625, in __call__\n return self.func(*args, **kwargs)\n\n File \"/home/thebears/.local/lib/python3.10/site-packages/onnxscript/function_libs/torch_lib/ops/nn.py\", line 474, in aten_gelu\n result = _aten_gelu_approximate_tanh(self)\n\n File \"/home/thebears/.local/lib/python3.10/site-packages/onnxscript/function_libs/torch_lib/ops/nn.py\", line 496, in _aten_gelu_approximate_tanh\n cubed = op.Pow(self, ir.tensor(3, dtype=self.dtype))\n\n File \"/home/thebears/.local/lib/python3.10/site-packages/onnx_ir/_convenience/_constructors.py\", line 103, in tensor\n raise TypeError(f\"dtype must be an instance of DataType. dtype={dtype}\")\n\nTypeError: dtype must be an instance of DataType. dtype=torch.float32\n\n```", + "text":"FX Graph: timm_models_vision_transformer_Block. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"fail", + "level":"error", + "locations":[ + { + "message":{ + "text":"FxOnnxInterpreter.run" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":496 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0007", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Node: call_module:trunk_blocks_0_1[name=trunk_blocks_0_1]. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature FxOnnxInterpreter.run_node\n- self: \n- node: fx.Node(trunk_blocks_0_1)[call_module]:Tensor(f32[4, 1024, 1024])\n- fx_graph_module: torch.fx.GraphModule(torch_nn_modules_container_Sequential)\n- onnxfunction_dispatcher: \n- op_level_debug: False\n- onnxscript_graph: \n- onnxscript_tracer: \n- fx_name_to_onnxscript_value: Dict[length=289](\nclone: `TorchScriptTensor(f32[4, 1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_weight: `TorchScriptTensor(f32[3072, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_bias: `TorchScriptTensor(f32[3072])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_weight: `TorchScriptTensor(f32[1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm2_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm2_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___mlp_fc1_weight: `TorchScriptTensor(f32[4096, 1024])`,\n...\n)\n## PyTorch source information\n```\n File \"/home/thebears/.local/lib/python3.10/site-packages/open_clip/timm_model.py\", line 196, in forward\n x = self.trunk(x)\n File \"/home/thebears/.local/lib/python3.10/site-packages/torch/nn/modules/module.py\", line 1725, in _call_impl\n return forward_call(*args, **kwargs)\n File \"/home/thebears/.local/lib/python3.10/site-packages/timm/models/vision_transformer.py\", line 853, in forward\n x = self.forward_features(x)\n File \"/home/thebears/.local/lib/python3.10/site-packages/timm/models/vision_transformer.py\", line 834, in forward_features\n x = self.blocks(x)\n File \"/home/thebears/.local/lib/python3.10/site-packages/torch/nn/modules/module.py\", line 1725, in _call_impl\n return forward_call(*args, **kwargs)\n File \"/home/thebears/.local/lib/python3.10/site-packages/timm/models/vision_transformer.py\", line 169, in forward\n x = x + self.drop_path1(self.ls1(self.attn(self.norm1(x))))\n\n```\n## Exception log\n```\nTraceback (most recent call last):\n\n File \"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/diagnostics/infra/decorator.py\", line 136, in wrapper\n return_values = fn(*args, **kwargs)\n\n File \"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py\", line 482, in run_node\n self.call_module(\n\n File \"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py\", line 811, in call_module\n sub_onnxscript_graph = self.run(\n\n File \"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/diagnostics/infra/decorator.py\", line 152, in wrapper\n ctx.log_and_raise_if_error(diag)\n\n File \"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/diagnostics/infra/context.py\", line 369, in log_and_raise_if_error\n raise diagnostic.source_exception\n\n File \"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/diagnostics/infra/decorator.py\", line 136, in wrapper\n return_values = fn(*args, **kwargs)\n\n File \"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py\", line 577, in run\n self.run_node(\n\n File \"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/diagnostics/infra/decorator.py\", line 152, in wrapper\n ctx.log_and_raise_if_error(diag)\n\n File \"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/diagnostics/infra/context.py\", line 369, in log_and_raise_if_error\n raise diagnostic.source_exception\n\n File \"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/diagnostics/infra/decorator.py\", line 136, in wrapper\n return_values = fn(*args, **kwargs)\n\n File \"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py\", line 482, in run_node\n self.call_module(\n\n File \"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py\", line 811, in call_module\n sub_onnxscript_graph = self.run(\n\n File \"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/diagnostics/infra/decorator.py\", line 152, in wrapper\n ctx.log_and_raise_if_error(diag)\n\n File \"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/diagnostics/infra/context.py\", line 369, in log_and_raise_if_error\n raise diagnostic.source_exception\n\n File \"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/diagnostics/infra/decorator.py\", line 136, in wrapper\n return_values = fn(*args, **kwargs)\n\n File \"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py\", line 577, in run\n self.run_node(\n\n File \"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/diagnostics/infra/decorator.py\", line 152, in wrapper\n ctx.log_and_raise_if_error(diag)\n\n File \"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/diagnostics/infra/context.py\", line 369, in log_and_raise_if_error\n raise diagnostic.source_exception\n\n File \"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/diagnostics/infra/decorator.py\", line 136, in wrapper\n return_values = fn(*args, **kwargs)\n\n File \"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py\", line 482, in run_node\n self.call_module(\n\n File \"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py\", line 811, in call_module\n sub_onnxscript_graph = self.run(\n\n File \"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/diagnostics/infra/decorator.py\", line 152, in wrapper\n ctx.log_and_raise_if_error(diag)\n\n File \"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/diagnostics/infra/context.py\", line 369, in log_and_raise_if_error\n raise diagnostic.source_exception\n\n File \"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/diagnostics/infra/decorator.py\", line 136, in wrapper\n return_values = fn(*args, **kwargs)\n\n File \"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py\", line 577, in run\n self.run_node(\n\n File \"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/diagnostics/infra/decorator.py\", line 152, in wrapper\n ctx.log_and_raise_if_error(diag)\n\n File \"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/diagnostics/infra/context.py\", line 369, in log_and_raise_if_error\n raise diagnostic.source_exception\n\n File \"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/diagnostics/infra/decorator.py\", line 136, in wrapper\n return_values = fn(*args, **kwargs)\n\n File \"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py\", line 471, in run_node\n self.call_function(\n\n File \"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py\", line 703, in call_function\n ] = symbolic_fn(*onnx_args, **onnx_kwargs)\n\n File \"/home/thebears/.local/lib/python3.10/site-packages/onnxscript/values.py\", line 625, in __call__\n return self.func(*args, **kwargs)\n\n File \"/home/thebears/.local/lib/python3.10/site-packages/onnxscript/function_libs/torch_lib/ops/nn.py\", line 474, in aten_gelu\n result = _aten_gelu_approximate_tanh(self)\n\n File \"/home/thebears/.local/lib/python3.10/site-packages/onnxscript/function_libs/torch_lib/ops/nn.py\", line 496, in _aten_gelu_approximate_tanh\n cubed = op.Pow(self, ir.tensor(3, dtype=self.dtype))\n\n File \"/home/thebears/.local/lib/python3.10/site-packages/onnx_ir/_convenience/_constructors.py\", line 103, in tensor\n raise TypeError(f\"dtype must be an instance of DataType. dtype={dtype}\")\n\nTypeError: dtype must be an instance of DataType. dtype=torch.float32\n\n```", + "text":"FX Node: call_module:trunk_blocks_0_1[name=trunk_blocks_0_1]. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"fail", + "level":"error", + "locations":[ + { + "message":{ + "text":"FxOnnxInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":414 + } + } + }, + { + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/open_clip/timm_model.py" + }, + "region":{ + "snippet":{ + "text":"x = self.trunk(x)" + }, + "startLine":196 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0008", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Graph: torch_nn_modules_container_Sequential. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature FxOnnxInterpreter.run\n- self: \n- fx_graph_module: torch.fx.GraphModule(torch_nn_modules_container_Sequential)\n- onnxfunction_dispatcher: \n- op_level_debug: False\n- parent_onnxscript_graph: \n## Exception log\n```\nTraceback (most recent call last):\n\n File \"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/diagnostics/infra/decorator.py\", line 136, in wrapper\n return_values = fn(*args, **kwargs)\n\n File \"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py\", line 577, in run\n self.run_node(\n\n File \"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/diagnostics/infra/decorator.py\", line 152, in wrapper\n ctx.log_and_raise_if_error(diag)\n\n File \"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/diagnostics/infra/context.py\", line 369, in log_and_raise_if_error\n raise diagnostic.source_exception\n\n File \"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/diagnostics/infra/decorator.py\", line 136, in wrapper\n return_values = fn(*args, **kwargs)\n\n File \"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py\", line 482, in run_node\n self.call_module(\n\n File \"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py\", line 811, in call_module\n sub_onnxscript_graph = self.run(\n\n File \"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/diagnostics/infra/decorator.py\", line 152, in wrapper\n ctx.log_and_raise_if_error(diag)\n\n File \"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/diagnostics/infra/context.py\", line 369, in log_and_raise_if_error\n raise diagnostic.source_exception\n\n File \"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/diagnostics/infra/decorator.py\", line 136, in wrapper\n return_values = fn(*args, **kwargs)\n\n File \"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py\", line 577, in run\n self.run_node(\n\n File \"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/diagnostics/infra/decorator.py\", line 152, in wrapper\n ctx.log_and_raise_if_error(diag)\n\n File \"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/diagnostics/infra/context.py\", line 369, in log_and_raise_if_error\n raise diagnostic.source_exception\n\n File \"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/diagnostics/infra/decorator.py\", line 136, in wrapper\n return_values = fn(*args, **kwargs)\n\n File \"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py\", line 482, in run_node\n self.call_module(\n\n File \"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py\", line 811, in call_module\n sub_onnxscript_graph = self.run(\n\n File \"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/diagnostics/infra/decorator.py\", line 152, in wrapper\n ctx.log_and_raise_if_error(diag)\n\n File \"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/diagnostics/infra/context.py\", line 369, in log_and_raise_if_error\n raise diagnostic.source_exception\n\n File \"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/diagnostics/infra/decorator.py\", line 136, in wrapper\n return_values = fn(*args, **kwargs)\n\n File \"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py\", line 577, in run\n self.run_node(\n\n File \"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/diagnostics/infra/decorator.py\", line 152, in wrapper\n ctx.log_and_raise_if_error(diag)\n\n File \"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/diagnostics/infra/context.py\", line 369, in log_and_raise_if_error\n raise diagnostic.source_exception\n\n File \"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/diagnostics/infra/decorator.py\", line 136, in wrapper\n return_values = fn(*args, **kwargs)\n\n File \"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py\", line 482, in run_node\n self.call_module(\n\n File \"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py\", line 811, in call_module\n sub_onnxscript_graph = self.run(\n\n File \"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/diagnostics/infra/decorator.py\", line 152, in wrapper\n ctx.log_and_raise_if_error(diag)\n\n File \"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/diagnostics/infra/context.py\", line 369, in log_and_raise_if_error\n raise diagnostic.source_exception\n\n File \"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/diagnostics/infra/decorator.py\", line 136, in wrapper\n return_values = fn(*args, **kwargs)\n\n File \"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py\", line 577, in run\n self.run_node(\n\n File \"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/diagnostics/infra/decorator.py\", line 152, in wrapper\n ctx.log_and_raise_if_error(diag)\n\n File \"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/diagnostics/infra/context.py\", line 369, in log_and_raise_if_error\n raise diagnostic.source_exception\n\n File \"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/diagnostics/infra/decorator.py\", line 136, in wrapper\n return_values = fn(*args, **kwargs)\n\n File \"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py\", line 471, in run_node\n self.call_function(\n\n File \"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py\", line 703, in call_function\n ] = symbolic_fn(*onnx_args, **onnx_kwargs)\n\n File \"/home/thebears/.local/lib/python3.10/site-packages/onnxscript/values.py\", line 625, in __call__\n return self.func(*args, **kwargs)\n\n File \"/home/thebears/.local/lib/python3.10/site-packages/onnxscript/function_libs/torch_lib/ops/nn.py\", line 474, in aten_gelu\n result = _aten_gelu_approximate_tanh(self)\n\n File \"/home/thebears/.local/lib/python3.10/site-packages/onnxscript/function_libs/torch_lib/ops/nn.py\", line 496, in _aten_gelu_approximate_tanh\n cubed = op.Pow(self, ir.tensor(3, dtype=self.dtype))\n\n File \"/home/thebears/.local/lib/python3.10/site-packages/onnx_ir/_convenience/_constructors.py\", line 103, in tensor\n raise TypeError(f\"dtype must be an instance of DataType. dtype={dtype}\")\n\nTypeError: dtype must be an instance of DataType. dtype=torch.float32\n\n```", + "text":"FX Graph: torch_nn_modules_container_Sequential. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"fail", + "level":"error", + "locations":[ + { + "message":{ + "text":"FxOnnxInterpreter.run" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":496 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0007", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Node: call_module:trunk_blocks_1[name=trunk_blocks_1]. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature FxOnnxInterpreter.run_node\n- self: \n- node: fx.Node(trunk_blocks_1)[call_module]:Tensor(f32[4, 1024, 1024])\n- fx_graph_module: torch.fx.GraphModule(timm_models_vision_transformer_VisionTransformer)\n- onnxfunction_dispatcher: \n- op_level_debug: False\n- onnxscript_graph: \n- onnxscript_tracer: \n- fx_name_to_onnxscript_value: Dict[length=310](\nx: `TorchScriptTensor(f32[4, 3, 512, 512])`,\np_trunk_patch_embed_proj_weight: `TorchScriptTensor(f32[1024, 3, 16, 16])`,\np_trunk_patch_embed_proj_bias: `TorchScriptTensor(f32[1024])`,\np_trunk_pos_embed: `TorchScriptTensor(f32[1, 1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_weight: `TorchScriptTensor(f32[3072, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_bias: `TorchScriptTensor(f32[3072])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_weight: `TorchScriptTensor(f32[1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_bias: `TorchScriptTensor(f32[1024])`,\n...\n)\n## PyTorch source information\n```\n File \"/home/thebears/.local/lib/python3.10/site-packages/open_clip/timm_model.py\", line 196, in forward\n x = self.trunk(x)\n File \"/home/thebears/.local/lib/python3.10/site-packages/torch/nn/modules/module.py\", line 1725, in _call_impl\n return forward_call(*args, **kwargs)\n File \"/home/thebears/.local/lib/python3.10/site-packages/timm/models/vision_transformer.py\", line 853, in forward\n x = self.forward_features(x)\n File \"/home/thebears/.local/lib/python3.10/site-packages/timm/models/vision_transformer.py\", line 834, in forward_features\n x = self.blocks(x)\n File \"/home/thebears/.local/lib/python3.10/site-packages/torch/nn/modules/module.py\", line 1725, in _call_impl\n return forward_call(*args, **kwargs)\n File \"/home/thebears/.local/lib/python3.10/site-packages/timm/models/vision_transformer.py\", line 169, in forward\n x = x + self.drop_path1(self.ls1(self.attn(self.norm1(x))))\n\n```\n## Exception log\n```\nTraceback (most recent call last):\n\n File \"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/diagnostics/infra/decorator.py\", line 136, in wrapper\n return_values = fn(*args, **kwargs)\n\n File \"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py\", line 482, in run_node\n self.call_module(\n\n File \"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py\", line 811, in call_module\n sub_onnxscript_graph = self.run(\n\n File \"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/diagnostics/infra/decorator.py\", line 152, in wrapper\n ctx.log_and_raise_if_error(diag)\n\n File \"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/diagnostics/infra/context.py\", line 369, in log_and_raise_if_error\n raise diagnostic.source_exception\n\n File \"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/diagnostics/infra/decorator.py\", line 136, in wrapper\n return_values = fn(*args, **kwargs)\n\n File \"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py\", line 577, in run\n self.run_node(\n\n File \"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/diagnostics/infra/decorator.py\", line 152, in wrapper\n ctx.log_and_raise_if_error(diag)\n\n File \"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/diagnostics/infra/context.py\", line 369, in log_and_raise_if_error\n raise diagnostic.source_exception\n\n File \"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/diagnostics/infra/decorator.py\", line 136, in wrapper\n return_values = fn(*args, **kwargs)\n\n File \"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py\", line 482, in run_node\n self.call_module(\n\n File \"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py\", line 811, in call_module\n sub_onnxscript_graph = self.run(\n\n File \"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/diagnostics/infra/decorator.py\", line 152, in wrapper\n ctx.log_and_raise_if_error(diag)\n\n File \"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/diagnostics/infra/context.py\", line 369, in log_and_raise_if_error\n raise diagnostic.source_exception\n\n File \"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/diagnostics/infra/decorator.py\", line 136, in wrapper\n return_values = fn(*args, **kwargs)\n\n File \"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py\", line 577, in run\n self.run_node(\n\n File \"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/diagnostics/infra/decorator.py\", line 152, in wrapper\n ctx.log_and_raise_if_error(diag)\n\n File \"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/diagnostics/infra/context.py\", line 369, in log_and_raise_if_error\n raise diagnostic.source_exception\n\n File \"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/diagnostics/infra/decorator.py\", line 136, in wrapper\n return_values = fn(*args, **kwargs)\n\n File \"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py\", line 482, in run_node\n self.call_module(\n\n File \"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py\", line 811, in call_module\n sub_onnxscript_graph = self.run(\n\n File \"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/diagnostics/infra/decorator.py\", line 152, in wrapper\n ctx.log_and_raise_if_error(diag)\n\n File \"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/diagnostics/infra/context.py\", line 369, in log_and_raise_if_error\n raise diagnostic.source_exception\n\n File \"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/diagnostics/infra/decorator.py\", line 136, in wrapper\n return_values = fn(*args, **kwargs)\n\n File \"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py\", line 577, in run\n self.run_node(\n\n File \"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/diagnostics/infra/decorator.py\", line 152, in wrapper\n ctx.log_and_raise_if_error(diag)\n\n File \"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/diagnostics/infra/context.py\", line 369, in log_and_raise_if_error\n raise diagnostic.source_exception\n\n File \"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/diagnostics/infra/decorator.py\", line 136, in wrapper\n return_values = fn(*args, **kwargs)\n\n File \"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py\", line 482, in run_node\n self.call_module(\n\n File \"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py\", line 811, in call_module\n sub_onnxscript_graph = self.run(\n\n File \"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/diagnostics/infra/decorator.py\", line 152, in wrapper\n ctx.log_and_raise_if_error(diag)\n\n File \"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/diagnostics/infra/context.py\", line 369, in log_and_raise_if_error\n raise diagnostic.source_exception\n\n File \"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/diagnostics/infra/decorator.py\", line 136, in wrapper\n return_values = fn(*args, **kwargs)\n\n File \"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py\", line 577, in run\n self.run_node(\n\n File \"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/diagnostics/infra/decorator.py\", line 152, in wrapper\n ctx.log_and_raise_if_error(diag)\n\n File \"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/diagnostics/infra/context.py\", line 369, in log_and_raise_if_error\n raise diagnostic.source_exception\n\n File \"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/diagnostics/infra/decorator.py\", line 136, in wrapper\n return_values = fn(*args, **kwargs)\n\n File \"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py\", line 471, in run_node\n self.call_function(\n\n File \"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py\", line 703, in call_function\n ] = symbolic_fn(*onnx_args, **onnx_kwargs)\n\n File \"/home/thebears/.local/lib/python3.10/site-packages/onnxscript/values.py\", line 625, in __call__\n return self.func(*args, **kwargs)\n\n File \"/home/thebears/.local/lib/python3.10/site-packages/onnxscript/function_libs/torch_lib/ops/nn.py\", line 474, in aten_gelu\n result = _aten_gelu_approximate_tanh(self)\n\n File \"/home/thebears/.local/lib/python3.10/site-packages/onnxscript/function_libs/torch_lib/ops/nn.py\", line 496, in _aten_gelu_approximate_tanh\n cubed = op.Pow(self, ir.tensor(3, dtype=self.dtype))\n\n File \"/home/thebears/.local/lib/python3.10/site-packages/onnx_ir/_convenience/_constructors.py\", line 103, in tensor\n raise TypeError(f\"dtype must be an instance of DataType. dtype={dtype}\")\n\nTypeError: dtype must be an instance of DataType. dtype=torch.float32\n\n```", + "text":"FX Node: call_module:trunk_blocks_1[name=trunk_blocks_1]. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"fail", + "level":"error", + "locations":[ + { + "message":{ + "text":"FxOnnxInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":414 + } + } + }, + { + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/open_clip/timm_model.py" + }, + "region":{ + "snippet":{ + "text":"x = self.trunk(x)" + }, + "startLine":196 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0008", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Graph: timm_models_vision_transformer_VisionTransformer. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature FxOnnxInterpreter.run\n- self: \n- fx_graph_module: torch.fx.GraphModule(timm_models_vision_transformer_VisionTransformer)\n- onnxfunction_dispatcher: \n- op_level_debug: False\n- parent_onnxscript_graph: \n## Exception log\n```\nTraceback (most recent call last):\n\n File \"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/diagnostics/infra/decorator.py\", line 136, in wrapper\n return_values = fn(*args, **kwargs)\n\n File \"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py\", line 577, in run\n self.run_node(\n\n File \"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/diagnostics/infra/decorator.py\", line 152, in wrapper\n ctx.log_and_raise_if_error(diag)\n\n File \"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/diagnostics/infra/context.py\", line 369, in log_and_raise_if_error\n raise diagnostic.source_exception\n\n File \"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/diagnostics/infra/decorator.py\", line 136, in wrapper\n return_values = fn(*args, **kwargs)\n\n File \"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py\", line 482, in run_node\n self.call_module(\n\n File \"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py\", line 811, in call_module\n sub_onnxscript_graph = self.run(\n\n File \"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/diagnostics/infra/decorator.py\", line 152, in wrapper\n ctx.log_and_raise_if_error(diag)\n\n File \"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/diagnostics/infra/context.py\", line 369, in log_and_raise_if_error\n raise diagnostic.source_exception\n\n File \"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/diagnostics/infra/decorator.py\", line 136, in wrapper\n return_values = fn(*args, **kwargs)\n\n File \"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py\", line 577, in run\n self.run_node(\n\n File \"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/diagnostics/infra/decorator.py\", line 152, in wrapper\n ctx.log_and_raise_if_error(diag)\n\n File \"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/diagnostics/infra/context.py\", line 369, in log_and_raise_if_error\n raise diagnostic.source_exception\n\n File \"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/diagnostics/infra/decorator.py\", line 136, in wrapper\n return_values = fn(*args, **kwargs)\n\n File \"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py\", line 482, in run_node\n self.call_module(\n\n File \"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py\", line 811, in call_module\n sub_onnxscript_graph = self.run(\n\n File \"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/diagnostics/infra/decorator.py\", line 152, in wrapper\n ctx.log_and_raise_if_error(diag)\n\n File \"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/diagnostics/infra/context.py\", line 369, in log_and_raise_if_error\n raise diagnostic.source_exception\n\n File \"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/diagnostics/infra/decorator.py\", line 136, in wrapper\n return_values = fn(*args, **kwargs)\n\n File \"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py\", line 577, in run\n self.run_node(\n\n File \"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/diagnostics/infra/decorator.py\", line 152, in wrapper\n ctx.log_and_raise_if_error(diag)\n\n File \"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/diagnostics/infra/context.py\", line 369, in log_and_raise_if_error\n raise diagnostic.source_exception\n\n File \"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/diagnostics/infra/decorator.py\", line 136, in wrapper\n return_values = fn(*args, **kwargs)\n\n File \"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py\", line 482, in run_node\n self.call_module(\n\n File \"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py\", line 811, in call_module\n sub_onnxscript_graph = self.run(\n\n File \"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/diagnostics/infra/decorator.py\", line 152, in wrapper\n ctx.log_and_raise_if_error(diag)\n\n File \"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/diagnostics/infra/context.py\", line 369, in log_and_raise_if_error\n raise diagnostic.source_exception\n\n File \"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/diagnostics/infra/decorator.py\", line 136, in wrapper\n return_values = fn(*args, **kwargs)\n\n File \"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py\", line 577, in run\n self.run_node(\n\n File \"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/diagnostics/infra/decorator.py\", line 152, in wrapper\n ctx.log_and_raise_if_error(diag)\n\n File \"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/diagnostics/infra/context.py\", line 369, in log_and_raise_if_error\n raise diagnostic.source_exception\n\n File \"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/diagnostics/infra/decorator.py\", line 136, in wrapper\n return_values = fn(*args, **kwargs)\n\n File \"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py\", line 482, in run_node\n self.call_module(\n\n File \"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py\", line 811, in call_module\n sub_onnxscript_graph = self.run(\n\n File \"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/diagnostics/infra/decorator.py\", line 152, in wrapper\n ctx.log_and_raise_if_error(diag)\n\n File \"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/diagnostics/infra/context.py\", line 369, in log_and_raise_if_error\n raise diagnostic.source_exception\n\n File \"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/diagnostics/infra/decorator.py\", line 136, in wrapper\n return_values = fn(*args, **kwargs)\n\n File \"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py\", line 577, in run\n self.run_node(\n\n File \"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/diagnostics/infra/decorator.py\", line 152, in wrapper\n ctx.log_and_raise_if_error(diag)\n\n File \"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/diagnostics/infra/context.py\", line 369, in log_and_raise_if_error\n raise diagnostic.source_exception\n\n File \"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/diagnostics/infra/decorator.py\", line 136, in wrapper\n return_values = fn(*args, **kwargs)\n\n File \"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py\", line 471, in run_node\n self.call_function(\n\n File \"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py\", line 703, in call_function\n ] = symbolic_fn(*onnx_args, **onnx_kwargs)\n\n File \"/home/thebears/.local/lib/python3.10/site-packages/onnxscript/values.py\", line 625, in __call__\n return self.func(*args, **kwargs)\n\n File \"/home/thebears/.local/lib/python3.10/site-packages/onnxscript/function_libs/torch_lib/ops/nn.py\", line 474, in aten_gelu\n result = _aten_gelu_approximate_tanh(self)\n\n File \"/home/thebears/.local/lib/python3.10/site-packages/onnxscript/function_libs/torch_lib/ops/nn.py\", line 496, in _aten_gelu_approximate_tanh\n cubed = op.Pow(self, ir.tensor(3, dtype=self.dtype))\n\n File \"/home/thebears/.local/lib/python3.10/site-packages/onnx_ir/_convenience/_constructors.py\", line 103, in tensor\n raise TypeError(f\"dtype must be an instance of DataType. dtype={dtype}\")\n\nTypeError: dtype must be an instance of DataType. dtype=torch.float32\n\n```", + "text":"FX Graph: timm_models_vision_transformer_VisionTransformer. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"fail", + "level":"error", + "locations":[ + { + "message":{ + "text":"FxOnnxInterpreter.run" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":496 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0007", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Node: call_module:trunk_1[name=trunk_1]. \n\n## Additional Message:\n\n## Function Signature\n### Function Signature FxOnnxInterpreter.run_node\n- self: \n- node: fx.Node(trunk_1)[call_module]:Tensor(f32[4, 1024])\n- fx_graph_module: torch.fx.GraphModule()\n- onnxfunction_dispatcher: \n- op_level_debug: False\n- onnxscript_graph: \n- onnxscript_tracer: \n- fx_name_to_onnxscript_value: Dict[length=307](\np_trunk_pos_embed: `TorchScriptTensor(f32[1, 1024, 1024])`,\np_trunk_attn_pool_latent: `TorchScriptTensor(f32[1, 1, 1024])`,\np_trunk_patch_embed_proj_weight: `TorchScriptTensor(f32[1024, 3, 16, 16])`,\np_trunk_patch_embed_proj_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_weight: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___norm1_bias: `TorchScriptTensor(f32[1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_weight: `TorchScriptTensor(f32[3072, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_qkv_bias: `TorchScriptTensor(f32[3072])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_weight: `TorchScriptTensor(f32[1024, 1024])`,\np_getattr_l__self___trunk_blocks___0___attn_proj_bias: `TorchScriptTensor(f32[1024])`,\n...\n)\n## PyTorch source information\n```\n File \"/home/thebears/.local/lib/python3.10/site-packages/open_clip/timm_model.py\", line 196, in forward\n x = self.trunk(x)\n File \"/home/thebears/.local/lib/python3.10/site-packages/torch/nn/modules/module.py\", line 1725, in _call_impl\n return forward_call(*args, **kwargs)\n File \"/home/thebears/.local/lib/python3.10/site-packages/timm/models/vision_transformer.py\", line 853, in forward\n x = self.forward_features(x)\n File \"/home/thebears/.local/lib/python3.10/site-packages/timm/models/vision_transformer.py\", line 827, in forward_features\n x = self.patch_embed(x)\n File \"/home/thebears/.local/lib/python3.10/site-packages/torch/nn/modules/module.py\", line 1725, in _call_impl\n return forward_call(*args, **kwargs)\n File \"/home/thebears/.local/lib/python3.10/site-packages/timm/layers/patch_embed.py\", line 131, in forward\n x = self.proj(x)\n\n```\n## Exception log\n```\nTraceback (most recent call last):\n\n File \"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/diagnostics/infra/decorator.py\", line 136, in wrapper\n return_values = fn(*args, **kwargs)\n\n File \"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py\", line 482, in run_node\n self.call_module(\n\n File \"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py\", line 811, in call_module\n sub_onnxscript_graph = self.run(\n\n File \"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/diagnostics/infra/decorator.py\", line 152, in wrapper\n ctx.log_and_raise_if_error(diag)\n\n File \"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/diagnostics/infra/context.py\", line 369, in log_and_raise_if_error\n raise diagnostic.source_exception\n\n File \"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/diagnostics/infra/decorator.py\", line 136, in wrapper\n return_values = fn(*args, **kwargs)\n\n File \"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py\", line 577, in run\n self.run_node(\n\n File \"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/diagnostics/infra/decorator.py\", line 152, in wrapper\n ctx.log_and_raise_if_error(diag)\n\n File \"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/diagnostics/infra/context.py\", line 369, in log_and_raise_if_error\n raise diagnostic.source_exception\n\n File \"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/diagnostics/infra/decorator.py\", line 136, in wrapper\n return_values = fn(*args, **kwargs)\n\n File \"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py\", line 482, in run_node\n self.call_module(\n\n File \"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py\", line 811, in call_module\n sub_onnxscript_graph = self.run(\n\n File \"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/diagnostics/infra/decorator.py\", line 152, in wrapper\n ctx.log_and_raise_if_error(diag)\n\n File \"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/diagnostics/infra/context.py\", line 369, in log_and_raise_if_error\n raise diagnostic.source_exception\n\n File \"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/diagnostics/infra/decorator.py\", line 136, in wrapper\n return_values = fn(*args, **kwargs)\n\n File \"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py\", line 577, in run\n self.run_node(\n\n File \"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/diagnostics/infra/decorator.py\", line 152, in wrapper\n ctx.log_and_raise_if_error(diag)\n\n File \"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/diagnostics/infra/context.py\", line 369, in log_and_raise_if_error\n raise diagnostic.source_exception\n\n File \"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/diagnostics/infra/decorator.py\", line 136, in wrapper\n return_values = fn(*args, **kwargs)\n\n File \"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py\", line 482, in run_node\n self.call_module(\n\n File \"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py\", line 811, in call_module\n sub_onnxscript_graph = self.run(\n\n File \"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/diagnostics/infra/decorator.py\", line 152, in wrapper\n ctx.log_and_raise_if_error(diag)\n\n File \"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/diagnostics/infra/context.py\", line 369, in log_and_raise_if_error\n raise diagnostic.source_exception\n\n File \"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/diagnostics/infra/decorator.py\", line 136, in wrapper\n return_values = fn(*args, **kwargs)\n\n File \"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py\", line 577, in run\n self.run_node(\n\n File \"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/diagnostics/infra/decorator.py\", line 152, in wrapper\n ctx.log_and_raise_if_error(diag)\n\n File \"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/diagnostics/infra/context.py\", line 369, in log_and_raise_if_error\n raise diagnostic.source_exception\n\n File \"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/diagnostics/infra/decorator.py\", line 136, in wrapper\n return_values = fn(*args, **kwargs)\n\n File \"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py\", line 482, in run_node\n self.call_module(\n\n File \"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py\", line 811, in call_module\n sub_onnxscript_graph = self.run(\n\n File \"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/diagnostics/infra/decorator.py\", line 152, in wrapper\n ctx.log_and_raise_if_error(diag)\n\n File \"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/diagnostics/infra/context.py\", line 369, in log_and_raise_if_error\n raise diagnostic.source_exception\n\n File \"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/diagnostics/infra/decorator.py\", line 136, in wrapper\n return_values = fn(*args, **kwargs)\n\n File \"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py\", line 577, in run\n self.run_node(\n\n File \"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/diagnostics/infra/decorator.py\", line 152, in wrapper\n ctx.log_and_raise_if_error(diag)\n\n File \"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/diagnostics/infra/context.py\", line 369, in log_and_raise_if_error\n raise diagnostic.source_exception\n\n File \"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/diagnostics/infra/decorator.py\", line 136, in wrapper\n return_values = fn(*args, **kwargs)\n\n File \"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py\", line 482, in run_node\n self.call_module(\n\n File \"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py\", line 811, in call_module\n sub_onnxscript_graph = self.run(\n\n File \"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/diagnostics/infra/decorator.py\", line 152, in wrapper\n ctx.log_and_raise_if_error(diag)\n\n File \"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/diagnostics/infra/context.py\", line 369, in log_and_raise_if_error\n raise diagnostic.source_exception\n\n File \"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/diagnostics/infra/decorator.py\", line 136, in wrapper\n return_values = fn(*args, **kwargs)\n\n File \"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py\", line 577, in run\n self.run_node(\n\n File \"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/diagnostics/infra/decorator.py\", line 152, in wrapper\n ctx.log_and_raise_if_error(diag)\n\n File \"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/diagnostics/infra/context.py\", line 369, in log_and_raise_if_error\n raise diagnostic.source_exception\n\n File \"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/diagnostics/infra/decorator.py\", line 136, in wrapper\n return_values = fn(*args, **kwargs)\n\n File \"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py\", line 471, in run_node\n self.call_function(\n\n File \"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py\", line 703, in call_function\n ] = symbolic_fn(*onnx_args, **onnx_kwargs)\n\n File \"/home/thebears/.local/lib/python3.10/site-packages/onnxscript/values.py\", line 625, in __call__\n return self.func(*args, **kwargs)\n\n File \"/home/thebears/.local/lib/python3.10/site-packages/onnxscript/function_libs/torch_lib/ops/nn.py\", line 474, in aten_gelu\n result = _aten_gelu_approximate_tanh(self)\n\n File \"/home/thebears/.local/lib/python3.10/site-packages/onnxscript/function_libs/torch_lib/ops/nn.py\", line 496, in _aten_gelu_approximate_tanh\n cubed = op.Pow(self, ir.tensor(3, dtype=self.dtype))\n\n File \"/home/thebears/.local/lib/python3.10/site-packages/onnx_ir/_convenience/_constructors.py\", line 103, in tensor\n raise TypeError(f\"dtype must be an instance of DataType. dtype={dtype}\")\n\nTypeError: dtype must be an instance of DataType. dtype=torch.float32\n\n```", + "text":"FX Node: call_module:trunk_1[name=trunk_1]. " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"fail", + "level":"error", + "locations":[ + { + "message":{ + "text":"FxOnnxInterpreter.run_node" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":414 + } + } + }, + { + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/open_clip/timm_model.py" + }, + "region":{ + "snippet":{ + "text":"x = self.trunk(x)" + }, + "startLine":196 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0008", + "stacks":[] + }, + { + "message":{ + "markdown":"FX Graph: . \n\n## Additional Message:\n\n## Function Signature\n### Function Signature FxOnnxInterpreter.run\n- self: \n- fx_graph_module: torch.fx.GraphModule()\n- onnxfunction_dispatcher: \n- op_level_debug: False\n## Exception log\n```\nTraceback (most recent call last):\n\n File \"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/diagnostics/infra/decorator.py\", line 136, in wrapper\n return_values = fn(*args, **kwargs)\n\n File \"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py\", line 577, in run\n self.run_node(\n\n File \"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/diagnostics/infra/decorator.py\", line 152, in wrapper\n ctx.log_and_raise_if_error(diag)\n\n File \"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/diagnostics/infra/context.py\", line 369, in log_and_raise_if_error\n raise diagnostic.source_exception\n\n File \"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/diagnostics/infra/decorator.py\", line 136, in wrapper\n return_values = fn(*args, **kwargs)\n\n File \"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py\", line 482, in run_node\n self.call_module(\n\n File \"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py\", line 811, in call_module\n sub_onnxscript_graph = self.run(\n\n File \"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/diagnostics/infra/decorator.py\", line 152, in wrapper\n ctx.log_and_raise_if_error(diag)\n\n File \"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/diagnostics/infra/context.py\", line 369, in log_and_raise_if_error\n raise diagnostic.source_exception\n\n File \"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/diagnostics/infra/decorator.py\", line 136, in wrapper\n return_values = fn(*args, **kwargs)\n\n File \"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py\", line 577, in run\n self.run_node(\n\n File \"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/diagnostics/infra/decorator.py\", line 152, in wrapper\n ctx.log_and_raise_if_error(diag)\n\n File \"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/diagnostics/infra/context.py\", line 369, in log_and_raise_if_error\n raise diagnostic.source_exception\n\n File \"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/diagnostics/infra/decorator.py\", line 136, in wrapper\n return_values = fn(*args, **kwargs)\n\n File \"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py\", line 482, in run_node\n self.call_module(\n\n File \"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py\", line 811, in call_module\n sub_onnxscript_graph = self.run(\n\n File \"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/diagnostics/infra/decorator.py\", line 152, in wrapper\n ctx.log_and_raise_if_error(diag)\n\n File \"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/diagnostics/infra/context.py\", line 369, in log_and_raise_if_error\n raise diagnostic.source_exception\n\n File \"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/diagnostics/infra/decorator.py\", line 136, in wrapper\n return_values = fn(*args, **kwargs)\n\n File \"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py\", line 577, in run\n self.run_node(\n\n File \"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/diagnostics/infra/decorator.py\", line 152, in wrapper\n ctx.log_and_raise_if_error(diag)\n\n File \"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/diagnostics/infra/context.py\", line 369, in log_and_raise_if_error\n raise diagnostic.source_exception\n\n File \"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/diagnostics/infra/decorator.py\", line 136, in wrapper\n return_values = fn(*args, **kwargs)\n\n File \"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py\", line 482, in run_node\n self.call_module(\n\n File \"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py\", line 811, in call_module\n sub_onnxscript_graph = self.run(\n\n File \"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/diagnostics/infra/decorator.py\", line 152, in wrapper\n ctx.log_and_raise_if_error(diag)\n\n File \"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/diagnostics/infra/context.py\", line 369, in log_and_raise_if_error\n raise diagnostic.source_exception\n\n File \"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/diagnostics/infra/decorator.py\", line 136, in wrapper\n return_values = fn(*args, **kwargs)\n\n File \"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py\", line 577, in run\n self.run_node(\n\n File \"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/diagnostics/infra/decorator.py\", line 152, in wrapper\n ctx.log_and_raise_if_error(diag)\n\n File \"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/diagnostics/infra/context.py\", line 369, in log_and_raise_if_error\n raise diagnostic.source_exception\n\n File \"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/diagnostics/infra/decorator.py\", line 136, in wrapper\n return_values = fn(*args, **kwargs)\n\n File \"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py\", line 482, in run_node\n self.call_module(\n\n File \"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py\", line 811, in call_module\n sub_onnxscript_graph = self.run(\n\n File \"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/diagnostics/infra/decorator.py\", line 152, in wrapper\n ctx.log_and_raise_if_error(diag)\n\n File \"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/diagnostics/infra/context.py\", line 369, in log_and_raise_if_error\n raise diagnostic.source_exception\n\n File \"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/diagnostics/infra/decorator.py\", line 136, in wrapper\n return_values = fn(*args, **kwargs)\n\n File \"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py\", line 577, in run\n self.run_node(\n\n File \"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/diagnostics/infra/decorator.py\", line 152, in wrapper\n ctx.log_and_raise_if_error(diag)\n\n File \"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/diagnostics/infra/context.py\", line 369, in log_and_raise_if_error\n raise diagnostic.source_exception\n\n File \"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/diagnostics/infra/decorator.py\", line 136, in wrapper\n return_values = fn(*args, **kwargs)\n\n File \"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py\", line 482, in run_node\n self.call_module(\n\n File \"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py\", line 811, in call_module\n sub_onnxscript_graph = self.run(\n\n File \"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/diagnostics/infra/decorator.py\", line 152, in wrapper\n ctx.log_and_raise_if_error(diag)\n\n File \"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/diagnostics/infra/context.py\", line 369, in log_and_raise_if_error\n raise diagnostic.source_exception\n\n File \"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/diagnostics/infra/decorator.py\", line 136, in wrapper\n return_values = fn(*args, **kwargs)\n\n File \"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py\", line 577, in run\n self.run_node(\n\n File \"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/diagnostics/infra/decorator.py\", line 152, in wrapper\n ctx.log_and_raise_if_error(diag)\n\n File \"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/diagnostics/infra/context.py\", line 369, in log_and_raise_if_error\n raise diagnostic.source_exception\n\n File \"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/diagnostics/infra/decorator.py\", line 136, in wrapper\n return_values = fn(*args, **kwargs)\n\n File \"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py\", line 471, in run_node\n self.call_function(\n\n File \"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py\", line 703, in call_function\n ] = symbolic_fn(*onnx_args, **onnx_kwargs)\n\n File \"/home/thebears/.local/lib/python3.10/site-packages/onnxscript/values.py\", line 625, in __call__\n return self.func(*args, **kwargs)\n\n File \"/home/thebears/.local/lib/python3.10/site-packages/onnxscript/function_libs/torch_lib/ops/nn.py\", line 474, in aten_gelu\n result = _aten_gelu_approximate_tanh(self)\n\n File \"/home/thebears/.local/lib/python3.10/site-packages/onnxscript/function_libs/torch_lib/ops/nn.py\", line 496, in _aten_gelu_approximate_tanh\n cubed = op.Pow(self, ir.tensor(3, dtype=self.dtype))\n\n File \"/home/thebears/.local/lib/python3.10/site-packages/onnx_ir/_convenience/_constructors.py\", line 103, in tensor\n raise TypeError(f\"dtype must be an instance of DataType. dtype={dtype}\")\n\nTypeError: dtype must be an instance of DataType. dtype=torch.float32\n\n```", + "text":"FX Graph: . " + }, + "codeFlows":[ + { + "threadFlows":[ + { + "locations":[] + } + ] + } + ], + "graphs":[], + "kind":"fail", + "level":"error", + "locations":[ + { + "message":{ + "text":"FxOnnxInterpreter.run" + }, + "physicalLocation":{ + "artifactLocation":{ + "uri":"/home/thebears/.local/lib/python3.10/site-packages/torch/onnx/_internal/fx/fx_onnx_interpreter.py" + }, + "region":{ + "snippet":{ + "text":"@_beartype.beartype" + }, + "startLine":496 + } + } + } + ], + "properties":{ + "tags":[] + }, + "ruleId":"FXE0007", + "stacks":[] + } + ] + } + ], + "version":"2.1.0", + "schemaUri":"https://docs.oasis-open.org/sarif/sarif/v2.1.0/cs01/schemas/sarif-schema-2.1.0.json" +} \ No newline at end of file diff --git a/saved.png b/saved.png new file mode 100644 index 0000000000000000000000000000000000000000..61a4d9e69db8d60af24f4250f3352a918f94b746 GIT binary patch literal 265671 zcmeAS@N?(olHy`uVBq!ia0y~yU}|7sV0^&A#=yW}dhyN^1_lPp64!{5;QX|b^2DN4 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model_name.replace('-','_').lower() + '_'+datetime.now().strftime('%Y%m%d') +ONNX_FILE_PATH=os.path.join(rt_dir, fname + '.onnx') +ENGINE_FILE_PATH = os.path.splitext(ONNX_FILE_PATH)[0]+'.engine' # %% -pretrained_name = "webli" -model_name = "ViT-L-16-SigLIP-512" - - -model_name = 'ViT-SO400M-16-SigLIP2-512' -ONNX_FILE_PATH = "/home/thebears/local/source/so400m_siglip2_512.onnx" -#model_name, pretrained_name = ('ViT-B-16-quickgelu', 'openai') model, _, preprocess = open_clip.create_model_and_transforms( model_name, pretrained=pretrained_name ) +# %% + +model_gpu = model.cuda() +scores = list() +all_means = list() +with torch.no_grad(): + for fr_num, img in enumerate(imgs): + + tensor_raw = torch.tensor(img[None,:,:,0:3]) + tensor_perm = tensor_raw.permute([0, 3, 1, 2]).to(torch.float32) / 255 + tensor_reshaped = preprocess.transforms[0](tensor_perm) + tensor_mean = preprocess.transforms[-1](tensor_reshaped) + all_means.append(tensor_mean) + imp = model_gpu.encode_image(tensor_mean.cuda()) + + print(fr_num) + scores.append((fr_num, imp.detach().cpu().numpy())) +# %% +np.save('dump_so400m',np.concatenate([x[1] for x in scores])) + + # %% with torch.no_grad(): et = time.time() + if True: - tensor_raw = arrays_to_score[0][0,:,:,0:3][None,:,:,:] + + tensor_raw = torch.concat(arrays_to_score)[0:4, :, :, 0:3] tensor_perm = tensor_raw.permute([0, 3, 1, 2]).to(torch.float32) / 255 tensor_reshaped = preprocess.transforms[0](tensor_perm) tensor_mean = preprocess.transforms[-1](tensor_reshaped) else: - tensor_raw = torch.concat(arrays_to_score)[0:4, :, :, 0:3] + tensor_raw = torch.concat(arrays_to_score)[0, :, :, 0:3] tensor_perm = tensor_raw.permute([0, 3, 1, 2]).to(torch.float32) / 255 tensor_reshaped = preprocess.transforms[1](preprocess.transforms[0](tensor_perm)) tensor_mean = preprocess.transforms[-1](tensor_reshaped) - imp = model.encode_image(tensor_mean) + #imp = model.encode_image(tensor_mean) + imp = model_gpu.encode_image(tensor_mean.cuda()) st = time.time() print((st - et) / tensor_raw.shape[0], tensor_raw.shape[0]/(st - et) ) + +from_model_on_gpu = imp.detach().cpu().numpy() + + - from_model_on_gpu = imp.cpu().numpy() # %% -ENGINE_FILE_PATH = os.path.splitext(ONNX_FILE_PATH)[0]+'.trt' + torch.onnx.export( - model.visual, - tensor_mean, + model.visual.cuda(), + tensor_mean.cuda(), ONNX_FILE_PATH, input_names=["input"], output_names=["output"], ) -# %% + X_test = tensor_mean.cpu().numpy() sess = rt.InferenceSession( ONNX_FILE_PATH, providers=rt.get_available_providers()) @@ -106,7 +137,7 @@ def norm(v): print(np.dot(norm(pred_onx), norm(from_model_on_gpu).T)) -# %% + TRT_LOGGER = trt.Logger() def build_engine_from_onnx(onnx_file_path, use_fp16=True): """ @@ -142,7 +173,7 @@ def build_engine_from_onnx(onnx_file_path, use_fp16=True): # Enable FP16 precision if requested and if the GPU supports it if use_fp16: if builder.platform_has_fast_fp16: -# config.set_flag(trt.BuilderFlag.FP16) + config.set_flag(trt.BuilderFlag.FP16) print("FP16 enabled successfully") else: print("Warning: GPU doesn't support fast FP16, using FP32 instead") @@ -160,7 +191,7 @@ def build_engine_from_onnx(onnx_file_path, use_fp16=True): -engine = build_engine_from_onnx(ONNX_FILE_PATH, use_fp16=False) +engine = build_engine_from_onnx(ONNX_FILE_PATH, use_fp16=True) with open(ENGINE_FILE_PATH, "wb") as f: f.write(engine)