diff --git a/uncompiledmodels/driving_off_policy.onnx b/uncompiledmodels/driving_off_policy.onnx index f84f6c3c2c..53fbc367a8 100644 Binary files a/uncompiledmodels/driving_off_policy.onnx and b/uncompiledmodels/driving_off_policy.onnx differ diff --git a/uncompiledmodels/driving_policy.onnx b/uncompiledmodels/driving_on_policy.onnx similarity index 61% rename from uncompiledmodels/driving_policy.onnx rename to uncompiledmodels/driving_on_policy.onnx index 8a8944997a..e9fb94d7ba 100644 Binary files a/uncompiledmodels/driving_policy.onnx and b/uncompiledmodels/driving_on_policy.onnx differ diff --git a/uncompiledmodels/driving_vision.onnx b/uncompiledmodels/driving_vision.onnx index 044c11a4f0..d3f7dc8e67 100644 --- a/uncompiledmodels/driving_vision.onnx +++ b/uncompiledmodels/driving_vision.onnx @@ -8,7 +8,7 @@ pkg.torch.onnx.class_hierarchy:['__main__.FlattenedVisionModel', 'aten._to_copy.default']J pkg.torch.onnx.fx_node%_to_copy : [num_users=1] = call_function[target=torch.ops.aten._to_copy.default](args = (%inputs_img,), kwargs = {dtype: torch.float16})J. pkg.torch.onnx.name_scopes['', '_to_copy']J -pkg.torch.onnx.stack_traceFile "/home/batman/xx3/./ml_tools/openpilot_compile/compile_supercombo.py", line 86, in forward +pkg.torch.onnx.stack_traceFile "/home/batman/xx3/./ml_tools/openpilot_compile/compile_supercombo.py", line 82, in forward return torch.cat([*self.forward_dict(inputs).values(), self.pad], dim=1)  big_img @@ -19,7 +19,7 @@ _to_copy_1node__to_copy_1"Cast* pkg.torch.onnx.class_hierarchy:['__main__.FlattenedVisionModel', 'aten._to_copy.default']J pkg.torch.onnx.fx_node%_to_copy_1 : [num_users=1] = call_function[target=torch.ops.aten._to_copy.default](args = (%inputs_big_img,), kwargs = {dtype: torch.float16})J0 pkg.torch.onnx.name_scopes['', '_to_copy_1']J -pkg.torch.onnx.stack_traceFile "/home/batman/xx3/./ml_tools/openpilot_compile/compile_supercombo.py", line 86, in forward +pkg.torch.onnx.stack_traceFile "/home/batman/xx3/./ml_tools/openpilot_compile/compile_supercombo.py", line 82, in forward return torch.cat([*self.forward_dict(inputs).values(), self.pad], dim=1)  _to_copy @@ -30,7 +30,7 @@ _to_copy_1catnode_cat"Concat* pkg.torch.onnx.class_hierarchy5['__main__.FlattenedVisionModel', 'aten.cat.default']J pkg.torch.onnx.fx_nodez%cat : [num_users=1] = call_function[target=torch.ops.aten.cat.default](args = ([%_to_copy, %_to_copy_1], 1), kwargs = {})J) pkg.torch.onnx.name_scopes ['', 'cat']J -pkg.torch.onnx.stack_traceFile "/home/batman/xx3/./ml_tools/openpilot_compile/compile_supercombo.py", line 86, in forward +pkg.torch.onnx.stack_traceFile "/home/batman/xx3/./ml_tools/openpilot_compile/compile_supercombo.py", line 82, in forward return torch.cat([*self.forward_dict(inputs).values(), self.pad], dim=1)  cat @@ -39,7 +39,7 @@ _to_copy_1catnode_cat"Concat* pkg.torch.onnx.class_hierarchyZ['__main__.FlattenedVisionModel', 'xx.training.path.supercombo.Vision', 'aten.sub.Tensor']J pkg.torch.onnx.fx_node%sub : [num_users=1] = call_function[target=torch.ops.aten.sub.Tensor](args = (%cat, %b_vision_model_vision__mean), kwargs = {})J@ pkg.torch.onnx.name_scopes"['', 'vision_model.vision', 'sub']J -pkg.torch.onnx.stack_traceFile "/home/batman/xx3/./ml_tools/openpilot_compile/compile_supercombo.py", line 86, in forward +pkg.torch.onnx.stack_traceFile "/home/batman/xx3/./ml_tools/openpilot_compile/compile_supercombo.py", line 82, in forward return torch.cat([*self.forward_dict(inputs).values(), self.pad], dim=1) File "/home/batman/xx3/xx/training/path/supercombo.py", line 184, in forward x = (x - self._mean) / self._std @@ -50,7 +50,7 @@ _to_copy_1catnode_cat"Concat* pkg.torch.onnx.class_hierarchyZ['__main__.FlattenedVisionModel', 'xx.training.path.supercombo.Vision', 'aten.div.Tensor']J pkg.torch.onnx.fx_node%div : [num_users=1] = call_function[target=torch.ops.aten.div.Tensor](args = (%sub, %b_vision_model_vision__std), kwargs = {})J@ pkg.torch.onnx.name_scopes"['', 'vision_model.vision', 'div']J -pkg.torch.onnx.stack_traceFile "/home/batman/xx3/./ml_tools/openpilot_compile/compile_supercombo.py", line 86, in forward +pkg.torch.onnx.stack_traceFile "/home/batman/xx3/./ml_tools/openpilot_compile/compile_supercombo.py", line 82, in forward return torch.cat([*self.forward_dict(inputs).values(), self.pad], dim=1) File "/home/batman/xx3/xx/training/path/supercombo.py", line 184, in forward x = (x - self._mean) / self._std @@ -67,7 +67,7 @@ _to_copy_1catnode_cat"Concat* pkg.torch.onnx.class_hierarchy['__main__.FlattenedVisionModel', 'xx.training.path.supercombo.Vision', 'timm.models.fastvit.FastVit', 'torch.nn.modules.container.Sequential', 'timm.models.fastvit.MobileOneBlock', 'torch.nn.modules.conv.Conv2d', 'aten.conv2d.default']J pkg.torch.onnx.fx_node%conv2d : [num_users=1] = call_function[target=torch.ops.aten.conv2d.default](args = (%div, %p_vision_model_vision__en_stem_0_reparam_conv_weight, %p_vision_model_vision__en_stem_0_reparam_conv_bias, [2, 2], [1, 1]), kwargs = {})J pkg.torch.onnx.name_scopes['', 'vision_model.vision', 'vision_model.vision._en', 'vision_model.vision._en.stem', 'vision_model.vision._en.stem.0', 'vision_model.vision._en.stem.0.reparam_conv', 'conv2d']J -pkg.torch.onnx.stack_traceFile "/home/batman/xx3/./ml_tools/openpilot_compile/compile_supercombo.py", line 86, in forward +pkg.torch.onnx.stack_traceFile "/home/batman/xx3/./ml_tools/openpilot_compile/compile_supercombo.py", line 82, in forward return torch.cat([*self.forward_dict(inputs).values(), self.pad], dim=1) File "/home/batman/xx3/xx/training/path/supercombo.py", line 185, in forward return self._en(x).flatten(1) @@ -86,7 +86,7 @@ _to_copy_1catnode_cat"Concat* pkg.torch.onnx.class_hierarchy['__main__.FlattenedVisionModel', 'xx.training.path.supercombo.Vision', 'timm.models.fastvit.FastVit', 'torch.nn.modules.container.Sequential', 'timm.models.fastvit.MobileOneBlock', 'timm.layers.activations.GELUTanh', 'aten.gelu.default']J pkg.torch.onnx.fx_nodez%gelu : [num_users=1] = call_function[target=torch.ops.aten.gelu.default](args = (%conv2d,), kwargs = {approximate: tanh})J pkg.torch.onnx.name_scopes['', 'vision_model.vision', 'vision_model.vision._en', 'vision_model.vision._en.stem', 'vision_model.vision._en.stem.0', 'vision_model.vision._en.stem.0.act', 'gelu']J -pkg.torch.onnx.stack_traceFile "/home/batman/xx3/./ml_tools/openpilot_compile/compile_supercombo.py", line 86, in forward +pkg.torch.onnx.stack_traceFile "/home/batman/xx3/./ml_tools/openpilot_compile/compile_supercombo.py", line 82, in forward return torch.cat([*self.forward_dict(inputs).values(), self.pad], dim=1) File "/home/batman/xx3/xx/training/path/supercombo.py", line 185, in forward return self._en(x).flatten(1) @@ -111,7 +111,7 @@ _to_copy_1catnode_cat"Concat* pkg.torch.onnx.class_hierarchy['__main__.FlattenedVisionModel', 'xx.training.path.supercombo.Vision', 'timm.models.fastvit.FastVit', 'torch.nn.modules.container.Sequential', 'timm.models.fastvit.MobileOneBlock', 'torch.nn.modules.conv.Conv2d', 'aten.conv2d.default']J pkg.torch.onnx.fx_node%conv2d_1 : [num_users=1] = call_function[target=torch.ops.aten.conv2d.default](args = (%gelu, %p_vision_model_vision__en_stem_1_reparam_conv_weight, %p_vision_model_vision__en_stem_1_reparam_conv_bias, [2, 2], [1, 1], [1, 1], 64), kwargs = {})J pkg.torch.onnx.name_scopes['', 'vision_model.vision', 'vision_model.vision._en', 'vision_model.vision._en.stem', 'vision_model.vision._en.stem.1', 'vision_model.vision._en.stem.1.reparam_conv', 'conv2d_1']J -pkg.torch.onnx.stack_traceFile "/home/batman/xx3/./ml_tools/openpilot_compile/compile_supercombo.py", line 86, in forward +pkg.torch.onnx.stack_traceFile "/home/batman/xx3/./ml_tools/openpilot_compile/compile_supercombo.py", line 82, in forward return torch.cat([*self.forward_dict(inputs).values(), self.pad], dim=1) File "/home/batman/xx3/xx/training/path/supercombo.py", line 185, in forward return self._en(x).flatten(1) @@ -130,7 +130,7 @@ _to_copy_1catnode_cat"Concat* pkg.torch.onnx.class_hierarchy['__main__.FlattenedVisionModel', 'xx.training.path.supercombo.Vision', 'timm.models.fastvit.FastVit', 'torch.nn.modules.container.Sequential', 'timm.models.fastvit.MobileOneBlock', 'timm.layers.activations.GELUTanh', 'aten.gelu.default']J pkg.torch.onnx.fx_node~%gelu_1 : [num_users=1] = call_function[target=torch.ops.aten.gelu.default](args = (%conv2d_1,), kwargs = {approximate: tanh})J pkg.torch.onnx.name_scopes['', 'vision_model.vision', 'vision_model.vision._en', 'vision_model.vision._en.stem', 'vision_model.vision._en.stem.1', 'vision_model.vision._en.stem.1.act', 'gelu_1']J -pkg.torch.onnx.stack_traceFile "/home/batman/xx3/./ml_tools/openpilot_compile/compile_supercombo.py", line 86, in forward +pkg.torch.onnx.stack_traceFile "/home/batman/xx3/./ml_tools/openpilot_compile/compile_supercombo.py", line 82, in forward return torch.cat([*self.forward_dict(inputs).values(), self.pad], dim=1) File "/home/batman/xx3/xx/training/path/supercombo.py", line 185, in forward return self._en(x).flatten(1) @@ -155,7 +155,7 @@ _to_copy_1catnode_cat"Concat* pkg.torch.onnx.class_hierarchy['__main__.FlattenedVisionModel', 'xx.training.path.supercombo.Vision', 'timm.models.fastvit.FastVit', 'torch.nn.modules.container.Sequential', 'timm.models.fastvit.MobileOneBlock', 'torch.nn.modules.conv.Conv2d', 'aten.conv2d.default']J pkg.torch.onnx.fx_node%conv2d_2 : [num_users=1] = call_function[target=torch.ops.aten.conv2d.default](args = (%gelu_1, %p_vision_model_vision__en_stem_2_reparam_conv_weight, %p_vision_model_vision__en_stem_2_reparam_conv_bias), kwargs = {})J pkg.torch.onnx.name_scopes['', 'vision_model.vision', 'vision_model.vision._en', 'vision_model.vision._en.stem', 'vision_model.vision._en.stem.2', 'vision_model.vision._en.stem.2.reparam_conv', 'conv2d_2']J -pkg.torch.onnx.stack_traceFile "/home/batman/xx3/./ml_tools/openpilot_compile/compile_supercombo.py", line 86, in forward +pkg.torch.onnx.stack_traceFile "/home/batman/xx3/./ml_tools/openpilot_compile/compile_supercombo.py", line 82, in forward return torch.cat([*self.forward_dict(inputs).values(), self.pad], dim=1) File "/home/batman/xx3/xx/training/path/supercombo.py", line 185, in forward return self._en(x).flatten(1) @@ -174,7 +174,7 @@ _to_copy_1catnode_cat"Concat* pkg.torch.onnx.class_hierarchy['__main__.FlattenedVisionModel', 'xx.training.path.supercombo.Vision', 'timm.models.fastvit.FastVit', 'torch.nn.modules.container.Sequential', 'timm.models.fastvit.MobileOneBlock', 'timm.layers.activations.GELUTanh', 'aten.gelu.default']J pkg.torch.onnx.fx_node~%gelu_2 : [num_users=1] = call_function[target=torch.ops.aten.gelu.default](args = (%conv2d_2,), kwargs = {approximate: tanh})J pkg.torch.onnx.name_scopes['', 'vision_model.vision', 'vision_model.vision._en', 'vision_model.vision._en.stem', 'vision_model.vision._en.stem.2', 'vision_model.vision._en.stem.2.act', 'gelu_2']J -pkg.torch.onnx.stack_traceFile "/home/batman/xx3/./ml_tools/openpilot_compile/compile_supercombo.py", line 86, in forward +pkg.torch.onnx.stack_traceFile "/home/batman/xx3/./ml_tools/openpilot_compile/compile_supercombo.py", line 82, in forward return torch.cat([*self.forward_dict(inputs).values(), self.pad], dim=1) File "/home/batman/xx3/xx/training/path/supercombo.py", line 185, in forward return self._en(x).flatten(1) @@ -199,7 +199,7 @@ Gvision_model.vision._en.stages.0.blocks.0.token_mixer.reparam_conv.biasconv2d pkg.torch.onnx.class_hierarchy['__main__.FlattenedVisionModel', 'xx.training.path.supercombo.Vision', 'timm.models.fastvit.FastVit', 'timm.models.fastvit.FastVitStage', 'torch.nn.modules.container.Sequential', 'timm.models.fastvit.RepMixerBlock', 'timm.models.fastvit.RepMixer', 'torch.nn.modules.conv.Conv2d', 'aten.conv2d.default']J pkg.torch.onnx.fx_node%conv2d_3 : [num_users=2] = call_function[target=torch.ops.aten.conv2d.default](args = (%gelu_2, %p_vision_model_vision__en_stages_0_blocks_0_token_mixer_reparam_conv_weight, %p_vision_model_vision__en_stages_0_blocks_0_token_mixer_reparam_conv_bias, [1, 1], [1, 1], [1, 1], 64), kwargs = {})J pkg.torch.onnx.name_scopes['', 'vision_model.vision', 'vision_model.vision._en', 'vision_model.vision._en.stages.0', 'vision_model.vision._en.stages.0.blocks', 'vision_model.vision._en.stages.0.blocks.0', 'vision_model.vision._en.stages.0.blocks.0.token_mixer', 'vision_model.vision._en.stages.0.blocks.0.token_mixer.reparam_conv', 'conv2d_3']J -pkg.torch.onnx.stack_traceFile "/home/batman/xx3/./ml_tools/openpilot_compile/compile_supercombo.py", line 86, in forward +pkg.torch.onnx.stack_traceFile "/home/batman/xx3/./ml_tools/openpilot_compile/compile_supercombo.py", line 82, in forward return torch.cat([*self.forward_dict(inputs).values(), self.pad], dim=1) File "/home/batman/xx3/xx/training/path/supercombo.py", line 185, in forward return self._en(x).flatten(1) @@ -229,7 +229,7 @@ Cvision_model.vision._en.stages.0.blocks.0.mlp.conv.conv.weight_biasgetitem n pkg.torch.onnx.class_hierarchy['__main__.FlattenedVisionModel', 'xx.training.path.supercombo.Vision', 'timm.models.fastvit.FastVit', 'timm.models.fastvit.FastVitStage', 'torch.nn.modules.container.Sequential', 'timm.models.fastvit.RepMixerBlock', 'timm.models.fastvit.ConvMlp', 'timm.layers.conv_bn_act.ConvNormAct', 'timm.layers.norm_act.BatchNormAct2d', 'aten._native_batch_norm_legit_no_training.default']J pkg.torch.onnx.fx_node%_native_batch_norm_legit_no_training : [num_users=1] = call_function[target=torch.ops.aten._native_batch_norm_legit_no_training.default](args = (%conv2d_4, %p_vision_model_vision__en_stages_0_blocks_0_mlp_conv_bn_weight, %p_vision_model_vision__en_stages_0_blocks_0_mlp_conv_bn_bias, %b_vision_model_vision__en_stages_0_blocks_0_mlp_conv_bn_running_mean, %b_vision_model_vision__en_stages_0_blocks_0_mlp_conv_bn_running_var, 0.1, 1e-05), kwargs = {})J pkg.torch.onnx.name_scopes['', 'vision_model.vision', 'vision_model.vision._en', 'vision_model.vision._en.stages.0', 'vision_model.vision._en.stages.0.blocks', 'vision_model.vision._en.stages.0.blocks.0', 'vision_model.vision._en.stages.0.blocks.0.mlp', 'vision_model.vision._en.stages.0.blocks.0.mlp.conv', 'vision_model.vision._en.stages.0.blocks.0.mlp.conv.bn', '_native_batch_norm_legit_no_training']J -pkg.torch.onnx.stack_trace File "/home/batman/xx3/./ml_tools/openpilot_compile/compile_supercombo.py", line 86, in forward +pkg.torch.onnx.stack_trace File "/home/batman/xx3/./ml_tools/openpilot_compile/compile_supercombo.py", line 82, in forward return torch.cat([*self.forward_dict(inputs).values(), self.pad], dim=1) File "/home/batman/xx3/xx/training/path/supercombo.py", line 185, in forward return self._en(x).flatten(1) @@ -260,7 +260,7 @@ Cvision_model.vision._en.stages.0.blocks.0.mlp.conv.conv.weight_biasgetitem n pkg.torch.onnx.class_hierarchy['__main__.FlattenedVisionModel', 'xx.training.path.supercombo.Vision', 'timm.models.fastvit.FastVit', 'timm.models.fastvit.FastVitStage', 'torch.nn.modules.container.Sequential', 'timm.models.fastvit.RepMixerBlock', 'timm.models.fastvit.ConvMlp', 'torch.nn.modules.conv.Conv2d', 'aten.conv2d.default']J pkg.torch.onnx.fx_node%conv2d_5 : [num_users=1] = call_function[target=torch.ops.aten.conv2d.default](args = (%getitem, %p_vision_model_vision__en_stages_0_blocks_0_mlp_fc1_weight, %p_vision_model_vision__en_stages_0_blocks_0_mlp_fc1_bias), kwargs = {})J pkg.torch.onnx.name_scopes['', 'vision_model.vision', 'vision_model.vision._en', 'vision_model.vision._en.stages.0', 'vision_model.vision._en.stages.0.blocks', 'vision_model.vision._en.stages.0.blocks.0', 'vision_model.vision._en.stages.0.blocks.0.mlp', 'vision_model.vision._en.stages.0.blocks.0.mlp.fc1', 'conv2d_5']J -pkg.torch.onnx.stack_trace File "/home/batman/xx3/./ml_tools/openpilot_compile/compile_supercombo.py", line 86, in forward +pkg.torch.onnx.stack_trace File "/home/batman/xx3/./ml_tools/openpilot_compile/compile_supercombo.py", line 82, in forward return torch.cat([*self.forward_dict(inputs).values(), self.pad], dim=1) File "/home/batman/xx3/xx/training/path/supercombo.py", line 185, in forward return self._en(x).flatten(1) @@ -283,7 +283,7 @@ Cvision_model.vision._en.stages.0.blocks.0.mlp.conv.conv.weight_biasgetitem n pkg.torch.onnx.class_hierarchy['__main__.FlattenedVisionModel', 'xx.training.path.supercombo.Vision', 'timm.models.fastvit.FastVit', 'timm.models.fastvit.FastVitStage', 'torch.nn.modules.container.Sequential', 'timm.models.fastvit.RepMixerBlock', 'timm.models.fastvit.ConvMlp', 'timm.layers.activations.GELUTanh', 'aten.gelu.default']J pkg.torch.onnx.fx_node~%gelu_3 : [num_users=1] = call_function[target=torch.ops.aten.gelu.default](args = (%conv2d_5,), kwargs = {approximate: tanh})J pkg.torch.onnx.name_scopes['', 'vision_model.vision', 'vision_model.vision._en', 'vision_model.vision._en.stages.0', 'vision_model.vision._en.stages.0.blocks', 'vision_model.vision._en.stages.0.blocks.0', 'vision_model.vision._en.stages.0.blocks.0.mlp', 'vision_model.vision._en.stages.0.blocks.0.mlp.act', 'gelu_3']J -pkg.torch.onnx.stack_traceFile "/home/batman/xx3/./ml_tools/openpilot_compile/compile_supercombo.py", line 86, in forward +pkg.torch.onnx.stack_traceFile "/home/batman/xx3/./ml_tools/openpilot_compile/compile_supercombo.py", line 82, in forward return torch.cat([*self.forward_dict(inputs).values(), self.pad], dim=1) File "/home/batman/xx3/xx/training/path/supercombo.py", line 185, in forward return self._en(x).flatten(1) @@ -312,7 +312,7 @@ Cvision_model.vision._en.stages.0.blocks.0.mlp.conv.conv.weight_biasgetitem n pkg.torch.onnx.class_hierarchy['__main__.FlattenedVisionModel', 'xx.training.path.supercombo.Vision', 'timm.models.fastvit.FastVit', 'timm.models.fastvit.FastVitStage', 'torch.nn.modules.container.Sequential', 'timm.models.fastvit.RepMixerBlock', 'timm.models.fastvit.ConvMlp', 'torch.nn.modules.conv.Conv2d', 'aten.conv2d.default']J pkg.torch.onnx.fx_node%conv2d_6 : [num_users=1] = call_function[target=torch.ops.aten.conv2d.default](args = (%clone, %p_vision_model_vision__en_stages_0_blocks_0_mlp_fc2_weight, %p_vision_model_vision__en_stages_0_blocks_0_mlp_fc2_bias), kwargs = {})J pkg.torch.onnx.name_scopes['', 'vision_model.vision', 'vision_model.vision._en', 'vision_model.vision._en.stages.0', 'vision_model.vision._en.stages.0.blocks', 'vision_model.vision._en.stages.0.blocks.0', 'vision_model.vision._en.stages.0.blocks.0.mlp', 'vision_model.vision._en.stages.0.blocks.0.mlp.fc2', 'conv2d_6']J -pkg.torch.onnx.stack_trace File "/home/batman/xx3/./ml_tools/openpilot_compile/compile_supercombo.py", line 86, in forward +pkg.torch.onnx.stack_trace File "/home/batman/xx3/./ml_tools/openpilot_compile/compile_supercombo.py", line 82, in forward return torch.cat([*self.forward_dict(inputs).values(), self.pad], dim=1) File "/home/batman/xx3/xx/training/path/supercombo.py", line 185, in forward return self._en(x).flatten(1) @@ -335,7 +335,7 @@ Cvision_model.vision._en.stages.0.blocks.0.mlp.conv.conv.weight_biasgetitem n pkg.torch.onnx.class_hierarchy['__main__.FlattenedVisionModel', 'xx.training.path.supercombo.Vision', 'timm.models.fastvit.FastVit', 'timm.models.fastvit.FastVitStage', 'torch.nn.modules.container.Sequential', 'timm.models.fastvit.RepMixerBlock', 'timm.models.fastvit.LayerScale2d', 'aten.mul.Tensor']J pkg.torch.onnx.fx_node%mul : [num_users=1] = call_function[target=torch.ops.aten.mul.Tensor](args = (%clone_1, %p_vision_model_vision__en_stages_0_blocks_0_layer_scale_gamma), kwargs = {})J pkg.torch.onnx.name_scopes['', 'vision_model.vision', 'vision_model.vision._en', 'vision_model.vision._en.stages.0', 'vision_model.vision._en.stages.0.blocks', 'vision_model.vision._en.stages.0.blocks.0', 'vision_model.vision._en.stages.0.blocks.0.layer_scale', 'mul']J -pkg.torch.onnx.stack_traceFile "/home/batman/xx3/./ml_tools/openpilot_compile/compile_supercombo.py", line 86, in forward +pkg.torch.onnx.stack_traceFile "/home/batman/xx3/./ml_tools/openpilot_compile/compile_supercombo.py", line 82, in forward return torch.cat([*self.forward_dict(inputs).values(), self.pad], dim=1) File "/home/batman/xx3/xx/training/path/supercombo.py", line 185, in forward return self._en(x).flatten(1) @@ -356,7 +356,7 @@ Cvision_model.vision._en.stages.0.blocks.0.mlp.conv.conv.weight_biasgetitem n pkg.torch.onnx.class_hierarchy['__main__.FlattenedVisionModel', 'xx.training.path.supercombo.Vision', 'timm.models.fastvit.FastVit', 'timm.models.fastvit.FastVitStage', 'torch.nn.modules.container.Sequential', 'timm.models.fastvit.RepMixerBlock', 'aten.add.Tensor']J pkg.torch.onnx.fx_nodem%add : [num_users=1] = call_function[target=torch.ops.aten.add.Tensor](args = (%conv2d_3, %mul), kwargs = {})J pkg.torch.onnx.name_scopes['', 'vision_model.vision', 'vision_model.vision._en', 'vision_model.vision._en.stages.0', 'vision_model.vision._en.stages.0.blocks', 'vision_model.vision._en.stages.0.blocks.0', 'add']J -pkg.torch.onnx.stack_traceFile "/home/batman/xx3/./ml_tools/openpilot_compile/compile_supercombo.py", line 86, in forward +pkg.torch.onnx.stack_traceFile "/home/batman/xx3/./ml_tools/openpilot_compile/compile_supercombo.py", line 82, in forward return torch.cat([*self.forward_dict(inputs).values(), self.pad], dim=1) File "/home/batman/xx3/xx/training/path/supercombo.py", line 185, in forward return self._en(x).flatten(1) @@ -381,7 +381,7 @@ Gvision_model.vision._en.stages.0.blocks.1.token_mixer.reparam_conv.biasconv2d pkg.torch.onnx.class_hierarchy['__main__.FlattenedVisionModel', 'xx.training.path.supercombo.Vision', 'timm.models.fastvit.FastVit', 'timm.models.fastvit.FastVitStage', 'torch.nn.modules.container.Sequential', 'timm.models.fastvit.RepMixerBlock', 'timm.models.fastvit.RepMixer', 'torch.nn.modules.conv.Conv2d', 'aten.conv2d.default']J pkg.torch.onnx.fx_node%conv2d_7 : [num_users=2] = call_function[target=torch.ops.aten.conv2d.default](args = (%add, %p_vision_model_vision__en_stages_0_blocks_1_token_mixer_reparam_conv_weight, %p_vision_model_vision__en_stages_0_blocks_1_token_mixer_reparam_conv_bias, [1, 1], [1, 1], [1, 1], 64), kwargs = {})J pkg.torch.onnx.name_scopes['', 'vision_model.vision', 'vision_model.vision._en', 'vision_model.vision._en.stages.0', 'vision_model.vision._en.stages.0.blocks', 'vision_model.vision._en.stages.0.blocks.1', 'vision_model.vision._en.stages.0.blocks.1.token_mixer', 'vision_model.vision._en.stages.0.blocks.1.token_mixer.reparam_conv', 'conv2d_7']J -pkg.torch.onnx.stack_traceFile "/home/batman/xx3/./ml_tools/openpilot_compile/compile_supercombo.py", line 86, in forward +pkg.torch.onnx.stack_traceFile "/home/batman/xx3/./ml_tools/openpilot_compile/compile_supercombo.py", line 82, in forward return torch.cat([*self.forward_dict(inputs).values(), self.pad], dim=1) File "/home/batman/xx3/xx/training/path/supercombo.py", line 185, in forward return self._en(x).flatten(1) @@ -411,7 +411,7 @@ Cvision_model.vision._en.stages.0.blocks.1.mlp.conv.conv.weight_bias getitem_3 pkg.torch.onnx.class_hierarchy['__main__.FlattenedVisionModel', 'xx.training.path.supercombo.Vision', 'timm.models.fastvit.FastVit', 'timm.models.fastvit.FastVitStage', 'torch.nn.modules.container.Sequential', 'timm.models.fastvit.RepMixerBlock', 'timm.models.fastvit.ConvMlp', 'timm.layers.conv_bn_act.ConvNormAct', 'timm.layers.norm_act.BatchNormAct2d', 'aten._native_batch_norm_legit_no_training.default']J pkg.torch.onnx.fx_node%_native_batch_norm_legit_no_training_1 : [num_users=1] = call_function[target=torch.ops.aten._native_batch_norm_legit_no_training.default](args = (%conv2d_8, %p_vision_model_vision__en_stages_0_blocks_1_mlp_conv_bn_weight, %p_vision_model_vision__en_stages_0_blocks_1_mlp_conv_bn_bias, %b_vision_model_vision__en_stages_0_blocks_1_mlp_conv_bn_running_mean, %b_vision_model_vision__en_stages_0_blocks_1_mlp_conv_bn_running_var, 0.1, 1e-05), kwargs = {})J pkg.torch.onnx.name_scopes['', 'vision_model.vision', 'vision_model.vision._en', 'vision_model.vision._en.stages.0', 'vision_model.vision._en.stages.0.blocks', 'vision_model.vision._en.stages.0.blocks.1', 'vision_model.vision._en.stages.0.blocks.1.mlp', 'vision_model.vision._en.stages.0.blocks.1.mlp.conv', 'vision_model.vision._en.stages.0.blocks.1.mlp.conv.bn', '_native_batch_norm_legit_no_training_1']J -pkg.torch.onnx.stack_trace File "/home/batman/xx3/./ml_tools/openpilot_compile/compile_supercombo.py", line 86, in forward +pkg.torch.onnx.stack_trace File "/home/batman/xx3/./ml_tools/openpilot_compile/compile_supercombo.py", line 82, in forward return torch.cat([*self.forward_dict(inputs).values(), self.pad], dim=1) File "/home/batman/xx3/xx/training/path/supercombo.py", line 185, in forward return self._en(x).flatten(1) @@ -442,7 +442,7 @@ Cvision_model.vision._en.stages.0.blocks.1.mlp.conv.conv.weight_bias getitem_3 pkg.torch.onnx.class_hierarchy['__main__.FlattenedVisionModel', 'xx.training.path.supercombo.Vision', 'timm.models.fastvit.FastVit', 'timm.models.fastvit.FastVitStage', 'torch.nn.modules.container.Sequential', 'timm.models.fastvit.RepMixerBlock', 'timm.models.fastvit.ConvMlp', 'torch.nn.modules.conv.Conv2d', 'aten.conv2d.default']J pkg.torch.onnx.fx_node%conv2d_9 : [num_users=1] = call_function[target=torch.ops.aten.conv2d.default](args = (%getitem_3, %p_vision_model_vision__en_stages_0_blocks_1_mlp_fc1_weight, %p_vision_model_vision__en_stages_0_blocks_1_mlp_fc1_bias), kwargs = {})J pkg.torch.onnx.name_scopes['', 'vision_model.vision', 'vision_model.vision._en', 'vision_model.vision._en.stages.0', 'vision_model.vision._en.stages.0.blocks', 'vision_model.vision._en.stages.0.blocks.1', 'vision_model.vision._en.stages.0.blocks.1.mlp', 'vision_model.vision._en.stages.0.blocks.1.mlp.fc1', 'conv2d_9']J -pkg.torch.onnx.stack_trace File "/home/batman/xx3/./ml_tools/openpilot_compile/compile_supercombo.py", line 86, in forward +pkg.torch.onnx.stack_trace File "/home/batman/xx3/./ml_tools/openpilot_compile/compile_supercombo.py", line 82, in forward return torch.cat([*self.forward_dict(inputs).values(), self.pad], dim=1) File "/home/batman/xx3/xx/training/path/supercombo.py", line 185, in forward return self._en(x).flatten(1) @@ -465,7 +465,7 @@ Cvision_model.vision._en.stages.0.blocks.1.mlp.conv.conv.weight_bias getitem_3 pkg.torch.onnx.class_hierarchy['__main__.FlattenedVisionModel', 'xx.training.path.supercombo.Vision', 'timm.models.fastvit.FastVit', 'timm.models.fastvit.FastVitStage', 'torch.nn.modules.container.Sequential', 'timm.models.fastvit.RepMixerBlock', 'timm.models.fastvit.ConvMlp', 'timm.layers.activations.GELUTanh', 'aten.gelu.default']J pkg.torch.onnx.fx_node~%gelu_4 : [num_users=1] = call_function[target=torch.ops.aten.gelu.default](args = (%conv2d_9,), kwargs = {approximate: tanh})J pkg.torch.onnx.name_scopes['', 'vision_model.vision', 'vision_model.vision._en', 'vision_model.vision._en.stages.0', 'vision_model.vision._en.stages.0.blocks', 'vision_model.vision._en.stages.0.blocks.1', 'vision_model.vision._en.stages.0.blocks.1.mlp', 'vision_model.vision._en.stages.0.blocks.1.mlp.act', 'gelu_4']J -pkg.torch.onnx.stack_traceFile "/home/batman/xx3/./ml_tools/openpilot_compile/compile_supercombo.py", line 86, in forward +pkg.torch.onnx.stack_traceFile "/home/batman/xx3/./ml_tools/openpilot_compile/compile_supercombo.py", line 82, in forward return torch.cat([*self.forward_dict(inputs).values(), self.pad], dim=1) File "/home/batman/xx3/xx/training/path/supercombo.py", line 185, in forward return self._en(x).flatten(1) @@ -494,7 +494,7 @@ Cvision_model.vision._en.stages.0.blocks.1.mlp.conv.conv.weight_bias getitem_3 pkg.torch.onnx.class_hierarchy['__main__.FlattenedVisionModel', 'xx.training.path.supercombo.Vision', 'timm.models.fastvit.FastVit', 'timm.models.fastvit.FastVitStage', 'torch.nn.modules.container.Sequential', 'timm.models.fastvit.RepMixerBlock', 'timm.models.fastvit.ConvMlp', 'torch.nn.modules.conv.Conv2d', 'aten.conv2d.default']J pkg.torch.onnx.fx_node%conv2d_10 : [num_users=1] = call_function[target=torch.ops.aten.conv2d.default](args = (%clone_2, %p_vision_model_vision__en_stages_0_blocks_1_mlp_fc2_weight, %p_vision_model_vision__en_stages_0_blocks_1_mlp_fc2_bias), kwargs = {})J pkg.torch.onnx.name_scopes['', 'vision_model.vision', 'vision_model.vision._en', 'vision_model.vision._en.stages.0', 'vision_model.vision._en.stages.0.blocks', 'vision_model.vision._en.stages.0.blocks.1', 'vision_model.vision._en.stages.0.blocks.1.mlp', 'vision_model.vision._en.stages.0.blocks.1.mlp.fc2', 'conv2d_10']J -pkg.torch.onnx.stack_trace File "/home/batman/xx3/./ml_tools/openpilot_compile/compile_supercombo.py", line 86, in forward +pkg.torch.onnx.stack_trace File "/home/batman/xx3/./ml_tools/openpilot_compile/compile_supercombo.py", line 82, in forward return torch.cat([*self.forward_dict(inputs).values(), self.pad], dim=1) File "/home/batman/xx3/xx/training/path/supercombo.py", line 185, in forward return self._en(x).flatten(1) @@ -518,7 +518,7 @@ node_mul_1"MulJ pkg.torch.onnx.class_hierarchy['__main__.FlattenedVisionModel', 'xx.training.path.supercombo.Vision', 'timm.models.fastvit.FastVit', 'timm.models.fastvit.FastVitStage', 'torch.nn.modules.container.Sequential', 'timm.models.fastvit.RepMixerBlock', 'timm.models.fastvit.LayerScale2d', 'aten.mul.Tensor']J pkg.torch.onnx.fx_node%mul_1 : [num_users=1] = call_function[target=torch.ops.aten.mul.Tensor](args = (%clone_3, %p_vision_model_vision__en_stages_0_blocks_1_layer_scale_gamma), kwargs = {})J pkg.torch.onnx.name_scopes['', 'vision_model.vision', 'vision_model.vision._en', 'vision_model.vision._en.stages.0', 'vision_model.vision._en.stages.0.blocks', 'vision_model.vision._en.stages.0.blocks.1', 'vision_model.vision._en.stages.0.blocks.1.layer_scale', 'mul_1']J -pkg.torch.onnx.stack_traceFile "/home/batman/xx3/./ml_tools/openpilot_compile/compile_supercombo.py", line 86, in forward +pkg.torch.onnx.stack_traceFile "/home/batman/xx3/./ml_tools/openpilot_compile/compile_supercombo.py", line 82, in forward return torch.cat([*self.forward_dict(inputs).values(), self.pad], dim=1) File "/home/batman/xx3/xx/training/path/supercombo.py", line 185, in forward return self._en(x).flatten(1) @@ -540,7 +540,7 @@ node_add_1"AddJ pkg.torch.onnx.class_hierarchy['__main__.FlattenedVisionModel', 'xx.training.path.supercombo.Vision', 'timm.models.fastvit.FastVit', 'timm.models.fastvit.FastVitStage', 'torch.nn.modules.container.Sequential', 'timm.models.fastvit.RepMixerBlock', 'aten.add.Tensor']J pkg.torch.onnx.fx_nodeq%add_1 : [num_users=1] = call_function[target=torch.ops.aten.add.Tensor](args = (%conv2d_7, %mul_1), kwargs = {})J pkg.torch.onnx.name_scopes['', 'vision_model.vision', 'vision_model.vision._en', 'vision_model.vision._en.stages.0', 'vision_model.vision._en.stages.0.blocks', 'vision_model.vision._en.stages.0.blocks.1', 'add_1']J -pkg.torch.onnx.stack_traceFile "/home/batman/xx3/./ml_tools/openpilot_compile/compile_supercombo.py", line 86, in forward +pkg.torch.onnx.stack_traceFile "/home/batman/xx3/./ml_tools/openpilot_compile/compile_supercombo.py", line 82, in forward return torch.cat([*self.forward_dict(inputs).values(), self.pad], dim=1) File "/home/batman/xx3/xx/training/path/supercombo.py", line 185, in forward return self._en(x).flatten(1) @@ -565,7 +565,7 @@ Dvision_model.vision._en.stages.1.downsample.proj.0.reparam_conv.bias conv2d_11 pkg.torch.onnx.class_hierarchy['__main__.FlattenedVisionModel', 'xx.training.path.supercombo.Vision', 'timm.models.fastvit.FastVit', 'timm.models.fastvit.FastVitStage', 'timm.models.fastvit.PatchEmbed', 'torch.nn.modules.container.Sequential', 'timm.models.fastvit.ReparamLargeKernelConv', 'torch.nn.modules.conv.Conv2d', 'aten.conv2d.default']J pkg.torch.onnx.fx_node%conv2d_11 : [num_users=1] = call_function[target=torch.ops.aten.conv2d.default](args = (%add_1, %p_vision_model_vision__en_stages_1_downsample_proj_0_reparam_conv_weight, %p_vision_model_vision__en_stages_1_downsample_proj_0_reparam_conv_bias, [2, 2], [3, 3], [1, 1], 64), kwargs = {})J pkg.torch.onnx.name_scopes['', 'vision_model.vision', 'vision_model.vision._en', 'vision_model.vision._en.stages.1', 'vision_model.vision._en.stages.1.downsample', 'vision_model.vision._en.stages.1.downsample.proj', 'vision_model.vision._en.stages.1.downsample.proj.0', 'vision_model.vision._en.stages.1.downsample.proj.0.reparam_conv', 'conv2d_11']J -pkg.torch.onnx.stack_traceFile "/home/batman/xx3/./ml_tools/openpilot_compile/compile_supercombo.py", line 86, in forward +pkg.torch.onnx.stack_traceFile "/home/batman/xx3/./ml_tools/openpilot_compile/compile_supercombo.py", line 82, in forward return torch.cat([*self.forward_dict(inputs).values(), self.pad], dim=1) File "/home/batman/xx3/xx/training/path/supercombo.py", line 185, in forward return self._en(x).flatten(1) @@ -594,7 +594,7 @@ Dvision_model.vision._en.stages.1.downsample.proj.1.reparam_conv.bias conv2d_12 pkg.torch.onnx.class_hierarchy['__main__.FlattenedVisionModel', 'xx.training.path.supercombo.Vision', 'timm.models.fastvit.FastVit', 'timm.models.fastvit.FastVitStage', 'timm.models.fastvit.PatchEmbed', 'torch.nn.modules.container.Sequential', 'timm.models.fastvit.MobileOneBlock', 'torch.nn.modules.conv.Conv2d', 'aten.conv2d.default']J pkg.torch.onnx.fx_node%conv2d_12 : [num_users=1] = call_function[target=torch.ops.aten.conv2d.default](args = (%conv2d_11, %p_vision_model_vision__en_stages_1_downsample_proj_1_reparam_conv_weight, %p_vision_model_vision__en_stages_1_downsample_proj_1_reparam_conv_bias), kwargs = {})J pkg.torch.onnx.name_scopes['', 'vision_model.vision', 'vision_model.vision._en', 'vision_model.vision._en.stages.1', 'vision_model.vision._en.stages.1.downsample', 'vision_model.vision._en.stages.1.downsample.proj', 'vision_model.vision._en.stages.1.downsample.proj.1', 'vision_model.vision._en.stages.1.downsample.proj.1.reparam_conv', 'conv2d_12']J -pkg.torch.onnx.stack_traceFile "/home/batman/xx3/./ml_tools/openpilot_compile/compile_supercombo.py", line 86, in forward +pkg.torch.onnx.stack_traceFile "/home/batman/xx3/./ml_tools/openpilot_compile/compile_supercombo.py", line 82, in forward return torch.cat([*self.forward_dict(inputs).values(), self.pad], dim=1) File "/home/batman/xx3/xx/training/path/supercombo.py", line 185, in forward return self._en(x).flatten(1) @@ -617,7 +617,7 @@ Dvision_model.vision._en.stages.1.downsample.proj.1.reparam_conv.bias conv2d_12 pkg.torch.onnx.class_hierarchy['__main__.FlattenedVisionModel', 'xx.training.path.supercombo.Vision', 'timm.models.fastvit.FastVit', 'timm.models.fastvit.FastVitStage', 'timm.models.fastvit.PatchEmbed', 'torch.nn.modules.container.Sequential', 'timm.models.fastvit.MobileOneBlock', 'timm.layers.activations.GELUTanh', 'aten.gelu.default']J pkg.torch.onnx.fx_node%gelu_5 : [num_users=1] = call_function[target=torch.ops.aten.gelu.default](args = (%conv2d_12,), kwargs = {approximate: tanh})J pkg.torch.onnx.name_scopes['', 'vision_model.vision', 'vision_model.vision._en', 'vision_model.vision._en.stages.1', 'vision_model.vision._en.stages.1.downsample', 'vision_model.vision._en.stages.1.downsample.proj', 'vision_model.vision._en.stages.1.downsample.proj.1', 'vision_model.vision._en.stages.1.downsample.proj.1.act', 'gelu_5']J -pkg.torch.onnx.stack_traceFile "/home/batman/xx3/./ml_tools/openpilot_compile/compile_supercombo.py", line 86, in forward +pkg.torch.onnx.stack_traceFile "/home/batman/xx3/./ml_tools/openpilot_compile/compile_supercombo.py", line 82, in forward return torch.cat([*self.forward_dict(inputs).values(), self.pad], dim=1) File "/home/batman/xx3/xx/training/path/supercombo.py", line 185, in forward return self._en(x).flatten(1) @@ -646,7 +646,7 @@ Gvision_model.vision._en.stages.1.blocks.0.token_mixer.reparam_conv.bias conv2d pkg.torch.onnx.class_hierarchy['__main__.FlattenedVisionModel', 'xx.training.path.supercombo.Vision', 'timm.models.fastvit.FastVit', 'timm.models.fastvit.FastVitStage', 'torch.nn.modules.container.Sequential', 'timm.models.fastvit.RepMixerBlock', 'timm.models.fastvit.RepMixer', 'torch.nn.modules.conv.Conv2d', 'aten.conv2d.default']J pkg.torch.onnx.fx_node%conv2d_13 : [num_users=2] = call_function[target=torch.ops.aten.conv2d.default](args = (%gelu_5, %p_vision_model_vision__en_stages_1_blocks_0_token_mixer_reparam_conv_weight, %p_vision_model_vision__en_stages_1_blocks_0_token_mixer_reparam_conv_bias, [1, 1], [1, 1], [1, 1], 128), kwargs = {})J pkg.torch.onnx.name_scopes['', 'vision_model.vision', 'vision_model.vision._en', 'vision_model.vision._en.stages.1', 'vision_model.vision._en.stages.1.blocks', 'vision_model.vision._en.stages.1.blocks.0', 'vision_model.vision._en.stages.1.blocks.0.token_mixer', 'vision_model.vision._en.stages.1.blocks.0.token_mixer.reparam_conv', 'conv2d_13']J -pkg.torch.onnx.stack_traceFile "/home/batman/xx3/./ml_tools/openpilot_compile/compile_supercombo.py", line 86, in forward +pkg.torch.onnx.stack_traceFile "/home/batman/xx3/./ml_tools/openpilot_compile/compile_supercombo.py", line 82, in forward return torch.cat([*self.forward_dict(inputs).values(), self.pad], dim=1) File "/home/batman/xx3/xx/training/path/supercombo.py", line 185, in forward return self._en(x).flatten(1) @@ -676,7 +676,7 @@ Cvision_model.vision._en.stages.1.blocks.0.mlp.conv.conv.weight_bias getitem_6 pkg.torch.onnx.class_hierarchy['__main__.FlattenedVisionModel', 'xx.training.path.supercombo.Vision', 'timm.models.fastvit.FastVit', 'timm.models.fastvit.FastVitStage', 'torch.nn.modules.container.Sequential', 'timm.models.fastvit.RepMixerBlock', 'timm.models.fastvit.ConvMlp', 'timm.layers.conv_bn_act.ConvNormAct', 'timm.layers.norm_act.BatchNormAct2d', 'aten._native_batch_norm_legit_no_training.default']J pkg.torch.onnx.fx_node%_native_batch_norm_legit_no_training_2 : [num_users=1] = call_function[target=torch.ops.aten._native_batch_norm_legit_no_training.default](args = (%conv2d_14, %p_vision_model_vision__en_stages_1_blocks_0_mlp_conv_bn_weight, %p_vision_model_vision__en_stages_1_blocks_0_mlp_conv_bn_bias, %b_vision_model_vision__en_stages_1_blocks_0_mlp_conv_bn_running_mean, %b_vision_model_vision__en_stages_1_blocks_0_mlp_conv_bn_running_var, 0.1, 1e-05), kwargs = {})J pkg.torch.onnx.name_scopes['', 'vision_model.vision', 'vision_model.vision._en', 'vision_model.vision._en.stages.1', 'vision_model.vision._en.stages.1.blocks', 'vision_model.vision._en.stages.1.blocks.0', 'vision_model.vision._en.stages.1.blocks.0.mlp', 'vision_model.vision._en.stages.1.blocks.0.mlp.conv', 'vision_model.vision._en.stages.1.blocks.0.mlp.conv.bn', '_native_batch_norm_legit_no_training_2']J -pkg.torch.onnx.stack_trace File "/home/batman/xx3/./ml_tools/openpilot_compile/compile_supercombo.py", line 86, in forward +pkg.torch.onnx.stack_trace File "/home/batman/xx3/./ml_tools/openpilot_compile/compile_supercombo.py", line 82, in forward return torch.cat([*self.forward_dict(inputs).values(), self.pad], dim=1) File "/home/batman/xx3/xx/training/path/supercombo.py", line 185, in forward return self._en(x).flatten(1) @@ -707,7 +707,7 @@ Cvision_model.vision._en.stages.1.blocks.0.mlp.conv.conv.weight_bias getitem_6 pkg.torch.onnx.class_hierarchy['__main__.FlattenedVisionModel', 'xx.training.path.supercombo.Vision', 'timm.models.fastvit.FastVit', 'timm.models.fastvit.FastVitStage', 'torch.nn.modules.container.Sequential', 'timm.models.fastvit.RepMixerBlock', 'timm.models.fastvit.ConvMlp', 'torch.nn.modules.conv.Conv2d', 'aten.conv2d.default']J pkg.torch.onnx.fx_node%conv2d_15 : [num_users=1] = call_function[target=torch.ops.aten.conv2d.default](args = (%getitem_6, %p_vision_model_vision__en_stages_1_blocks_0_mlp_fc1_weight, %p_vision_model_vision__en_stages_1_blocks_0_mlp_fc1_bias), kwargs = {})J pkg.torch.onnx.name_scopes['', 'vision_model.vision', 'vision_model.vision._en', 'vision_model.vision._en.stages.1', 'vision_model.vision._en.stages.1.blocks', 'vision_model.vision._en.stages.1.blocks.0', 'vision_model.vision._en.stages.1.blocks.0.mlp', 'vision_model.vision._en.stages.1.blocks.0.mlp.fc1', 'conv2d_15']J -pkg.torch.onnx.stack_trace File "/home/batman/xx3/./ml_tools/openpilot_compile/compile_supercombo.py", line 86, in forward +pkg.torch.onnx.stack_trace File "/home/batman/xx3/./ml_tools/openpilot_compile/compile_supercombo.py", line 82, in forward return torch.cat([*self.forward_dict(inputs).values(), self.pad], dim=1) File "/home/batman/xx3/xx/training/path/supercombo.py", line 185, in forward return self._en(x).flatten(1) @@ -730,7 +730,7 @@ Cvision_model.vision._en.stages.1.blocks.0.mlp.conv.conv.weight_bias getitem_6 pkg.torch.onnx.class_hierarchy['__main__.FlattenedVisionModel', 'xx.training.path.supercombo.Vision', 'timm.models.fastvit.FastVit', 'timm.models.fastvit.FastVitStage', 'torch.nn.modules.container.Sequential', 'timm.models.fastvit.RepMixerBlock', 'timm.models.fastvit.ConvMlp', 'timm.layers.activations.GELUTanh', 'aten.gelu.default']J pkg.torch.onnx.fx_node%gelu_6 : [num_users=1] = call_function[target=torch.ops.aten.gelu.default](args = (%conv2d_15,), kwargs = {approximate: tanh})J pkg.torch.onnx.name_scopes['', 'vision_model.vision', 'vision_model.vision._en', 'vision_model.vision._en.stages.1', 'vision_model.vision._en.stages.1.blocks', 'vision_model.vision._en.stages.1.blocks.0', 'vision_model.vision._en.stages.1.blocks.0.mlp', 'vision_model.vision._en.stages.1.blocks.0.mlp.act', 'gelu_6']J -pkg.torch.onnx.stack_traceFile "/home/batman/xx3/./ml_tools/openpilot_compile/compile_supercombo.py", line 86, in forward +pkg.torch.onnx.stack_traceFile "/home/batman/xx3/./ml_tools/openpilot_compile/compile_supercombo.py", line 82, in forward return torch.cat([*self.forward_dict(inputs).values(), self.pad], dim=1) File "/home/batman/xx3/xx/training/path/supercombo.py", line 185, in forward return self._en(x).flatten(1) @@ -759,7 +759,7 @@ Cvision_model.vision._en.stages.1.blocks.0.mlp.conv.conv.weight_bias getitem_6 pkg.torch.onnx.class_hierarchy['__main__.FlattenedVisionModel', 'xx.training.path.supercombo.Vision', 'timm.models.fastvit.FastVit', 'timm.models.fastvit.FastVitStage', 'torch.nn.modules.container.Sequential', 'timm.models.fastvit.RepMixerBlock', 'timm.models.fastvit.ConvMlp', 'torch.nn.modules.conv.Conv2d', 'aten.conv2d.default']J pkg.torch.onnx.fx_node%conv2d_16 : [num_users=1] = call_function[target=torch.ops.aten.conv2d.default](args = (%clone_4, %p_vision_model_vision__en_stages_1_blocks_0_mlp_fc2_weight, %p_vision_model_vision__en_stages_1_blocks_0_mlp_fc2_bias), kwargs = {})J pkg.torch.onnx.name_scopes['', 'vision_model.vision', 'vision_model.vision._en', 'vision_model.vision._en.stages.1', 'vision_model.vision._en.stages.1.blocks', 'vision_model.vision._en.stages.1.blocks.0', 'vision_model.vision._en.stages.1.blocks.0.mlp', 'vision_model.vision._en.stages.1.blocks.0.mlp.fc2', 'conv2d_16']J -pkg.torch.onnx.stack_trace File "/home/batman/xx3/./ml_tools/openpilot_compile/compile_supercombo.py", line 86, in forward +pkg.torch.onnx.stack_trace File "/home/batman/xx3/./ml_tools/openpilot_compile/compile_supercombo.py", line 82, in forward return torch.cat([*self.forward_dict(inputs).values(), self.pad], dim=1) File "/home/batman/xx3/xx/training/path/supercombo.py", line 185, in forward return self._en(x).flatten(1) @@ -783,7 +783,7 @@ node_mul_2"MulJ pkg.torch.onnx.class_hierarchy['__main__.FlattenedVisionModel', 'xx.training.path.supercombo.Vision', 'timm.models.fastvit.FastVit', 'timm.models.fastvit.FastVitStage', 'torch.nn.modules.container.Sequential', 'timm.models.fastvit.RepMixerBlock', 'timm.models.fastvit.LayerScale2d', 'aten.mul.Tensor']J pkg.torch.onnx.fx_node%mul_2 : [num_users=1] = call_function[target=torch.ops.aten.mul.Tensor](args = (%clone_5, %p_vision_model_vision__en_stages_1_blocks_0_layer_scale_gamma), kwargs = {})J pkg.torch.onnx.name_scopes['', 'vision_model.vision', 'vision_model.vision._en', 'vision_model.vision._en.stages.1', 'vision_model.vision._en.stages.1.blocks', 'vision_model.vision._en.stages.1.blocks.0', 'vision_model.vision._en.stages.1.blocks.0.layer_scale', 'mul_2']J -pkg.torch.onnx.stack_traceFile "/home/batman/xx3/./ml_tools/openpilot_compile/compile_supercombo.py", line 86, in forward +pkg.torch.onnx.stack_traceFile "/home/batman/xx3/./ml_tools/openpilot_compile/compile_supercombo.py", line 82, in forward return torch.cat([*self.forward_dict(inputs).values(), self.pad], dim=1) File "/home/batman/xx3/xx/training/path/supercombo.py", line 185, in forward return self._en(x).flatten(1) @@ -805,7 +805,7 @@ node_add_2"AddJ pkg.torch.onnx.class_hierarchy['__main__.FlattenedVisionModel', 'xx.training.path.supercombo.Vision', 'timm.models.fastvit.FastVit', 'timm.models.fastvit.FastVitStage', 'torch.nn.modules.container.Sequential', 'timm.models.fastvit.RepMixerBlock', 'aten.add.Tensor']J pkg.torch.onnx.fx_noder%add_2 : [num_users=1] = call_function[target=torch.ops.aten.add.Tensor](args = (%conv2d_13, %mul_2), kwargs = {})J pkg.torch.onnx.name_scopes['', 'vision_model.vision', 'vision_model.vision._en', 'vision_model.vision._en.stages.1', 'vision_model.vision._en.stages.1.blocks', 'vision_model.vision._en.stages.1.blocks.0', 'add_2']J -pkg.torch.onnx.stack_traceFile "/home/batman/xx3/./ml_tools/openpilot_compile/compile_supercombo.py", line 86, in forward +pkg.torch.onnx.stack_traceFile "/home/batman/xx3/./ml_tools/openpilot_compile/compile_supercombo.py", line 82, in forward return torch.cat([*self.forward_dict(inputs).values(), self.pad], dim=1) File "/home/batman/xx3/xx/training/path/supercombo.py", line 185, in forward return self._en(x).flatten(1) @@ -830,7 +830,7 @@ Gvision_model.vision._en.stages.1.blocks.1.token_mixer.reparam_conv.bias conv2d pkg.torch.onnx.class_hierarchy['__main__.FlattenedVisionModel', 'xx.training.path.supercombo.Vision', 'timm.models.fastvit.FastVit', 'timm.models.fastvit.FastVitStage', 'torch.nn.modules.container.Sequential', 'timm.models.fastvit.RepMixerBlock', 'timm.models.fastvit.RepMixer', 'torch.nn.modules.conv.Conv2d', 'aten.conv2d.default']J pkg.torch.onnx.fx_node%conv2d_17 : [num_users=2] = call_function[target=torch.ops.aten.conv2d.default](args = (%add_2, %p_vision_model_vision__en_stages_1_blocks_1_token_mixer_reparam_conv_weight, %p_vision_model_vision__en_stages_1_blocks_1_token_mixer_reparam_conv_bias, [1, 1], [1, 1], [1, 1], 128), kwargs = {})J pkg.torch.onnx.name_scopes['', 'vision_model.vision', 'vision_model.vision._en', 'vision_model.vision._en.stages.1', 'vision_model.vision._en.stages.1.blocks', 'vision_model.vision._en.stages.1.blocks.1', 'vision_model.vision._en.stages.1.blocks.1.token_mixer', 'vision_model.vision._en.stages.1.blocks.1.token_mixer.reparam_conv', 'conv2d_17']J -pkg.torch.onnx.stack_traceFile "/home/batman/xx3/./ml_tools/openpilot_compile/compile_supercombo.py", line 86, in forward +pkg.torch.onnx.stack_traceFile "/home/batman/xx3/./ml_tools/openpilot_compile/compile_supercombo.py", line 82, in forward return torch.cat([*self.forward_dict(inputs).values(), self.pad], dim=1) File "/home/batman/xx3/xx/training/path/supercombo.py", line 185, in forward return self._en(x).flatten(1) @@ -860,7 +860,7 @@ Cvision_model.vision._en.stages.1.blocks.1.mlp.conv.conv.weight_bias getitem_9 pkg.torch.onnx.class_hierarchy['__main__.FlattenedVisionModel', 'xx.training.path.supercombo.Vision', 'timm.models.fastvit.FastVit', 'timm.models.fastvit.FastVitStage', 'torch.nn.modules.container.Sequential', 'timm.models.fastvit.RepMixerBlock', 'timm.models.fastvit.ConvMlp', 'timm.layers.conv_bn_act.ConvNormAct', 'timm.layers.norm_act.BatchNormAct2d', 'aten._native_batch_norm_legit_no_training.default']J pkg.torch.onnx.fx_node%_native_batch_norm_legit_no_training_3 : [num_users=1] = call_function[target=torch.ops.aten._native_batch_norm_legit_no_training.default](args = (%conv2d_18, %p_vision_model_vision__en_stages_1_blocks_1_mlp_conv_bn_weight, %p_vision_model_vision__en_stages_1_blocks_1_mlp_conv_bn_bias, %b_vision_model_vision__en_stages_1_blocks_1_mlp_conv_bn_running_mean, %b_vision_model_vision__en_stages_1_blocks_1_mlp_conv_bn_running_var, 0.1, 1e-05), kwargs = {})J pkg.torch.onnx.name_scopes['', 'vision_model.vision', 'vision_model.vision._en', 'vision_model.vision._en.stages.1', 'vision_model.vision._en.stages.1.blocks', 'vision_model.vision._en.stages.1.blocks.1', 'vision_model.vision._en.stages.1.blocks.1.mlp', 'vision_model.vision._en.stages.1.blocks.1.mlp.conv', 'vision_model.vision._en.stages.1.blocks.1.mlp.conv.bn', '_native_batch_norm_legit_no_training_3']J -pkg.torch.onnx.stack_trace File "/home/batman/xx3/./ml_tools/openpilot_compile/compile_supercombo.py", line 86, in forward +pkg.torch.onnx.stack_trace File "/home/batman/xx3/./ml_tools/openpilot_compile/compile_supercombo.py", line 82, in forward return torch.cat([*self.forward_dict(inputs).values(), self.pad], dim=1) File "/home/batman/xx3/xx/training/path/supercombo.py", line 185, in forward return self._en(x).flatten(1) @@ -891,7 +891,7 @@ Cvision_model.vision._en.stages.1.blocks.1.mlp.conv.conv.weight_bias getitem_9 pkg.torch.onnx.class_hierarchy['__main__.FlattenedVisionModel', 'xx.training.path.supercombo.Vision', 'timm.models.fastvit.FastVit', 'timm.models.fastvit.FastVitStage', 'torch.nn.modules.container.Sequential', 'timm.models.fastvit.RepMixerBlock', 'timm.models.fastvit.ConvMlp', 'torch.nn.modules.conv.Conv2d', 'aten.conv2d.default']J pkg.torch.onnx.fx_node%conv2d_19 : [num_users=1] = call_function[target=torch.ops.aten.conv2d.default](args = (%getitem_9, %p_vision_model_vision__en_stages_1_blocks_1_mlp_fc1_weight, %p_vision_model_vision__en_stages_1_blocks_1_mlp_fc1_bias), kwargs = {})J pkg.torch.onnx.name_scopes['', 'vision_model.vision', 'vision_model.vision._en', 'vision_model.vision._en.stages.1', 'vision_model.vision._en.stages.1.blocks', 'vision_model.vision._en.stages.1.blocks.1', 'vision_model.vision._en.stages.1.blocks.1.mlp', 'vision_model.vision._en.stages.1.blocks.1.mlp.fc1', 'conv2d_19']J -pkg.torch.onnx.stack_trace File "/home/batman/xx3/./ml_tools/openpilot_compile/compile_supercombo.py", line 86, in forward +pkg.torch.onnx.stack_trace File "/home/batman/xx3/./ml_tools/openpilot_compile/compile_supercombo.py", line 82, in forward return torch.cat([*self.forward_dict(inputs).values(), self.pad], dim=1) File "/home/batman/xx3/xx/training/path/supercombo.py", line 185, in forward return self._en(x).flatten(1) @@ -914,7 +914,7 @@ Cvision_model.vision._en.stages.1.blocks.1.mlp.conv.conv.weight_bias getitem_9 pkg.torch.onnx.class_hierarchy['__main__.FlattenedVisionModel', 'xx.training.path.supercombo.Vision', 'timm.models.fastvit.FastVit', 'timm.models.fastvit.FastVitStage', 'torch.nn.modules.container.Sequential', 'timm.models.fastvit.RepMixerBlock', 'timm.models.fastvit.ConvMlp', 'timm.layers.activations.GELUTanh', 'aten.gelu.default']J pkg.torch.onnx.fx_node%gelu_7 : [num_users=1] = call_function[target=torch.ops.aten.gelu.default](args = (%conv2d_19,), kwargs = {approximate: tanh})J pkg.torch.onnx.name_scopes['', 'vision_model.vision', 'vision_model.vision._en', 'vision_model.vision._en.stages.1', 'vision_model.vision._en.stages.1.blocks', 'vision_model.vision._en.stages.1.blocks.1', 'vision_model.vision._en.stages.1.blocks.1.mlp', 'vision_model.vision._en.stages.1.blocks.1.mlp.act', 'gelu_7']J -pkg.torch.onnx.stack_traceFile "/home/batman/xx3/./ml_tools/openpilot_compile/compile_supercombo.py", line 86, in forward +pkg.torch.onnx.stack_traceFile "/home/batman/xx3/./ml_tools/openpilot_compile/compile_supercombo.py", line 82, in forward return torch.cat([*self.forward_dict(inputs).values(), self.pad], dim=1) File "/home/batman/xx3/xx/training/path/supercombo.py", line 185, in forward return self._en(x).flatten(1) @@ -943,7 +943,7 @@ Cvision_model.vision._en.stages.1.blocks.1.mlp.conv.conv.weight_bias getitem_9 pkg.torch.onnx.class_hierarchy['__main__.FlattenedVisionModel', 'xx.training.path.supercombo.Vision', 'timm.models.fastvit.FastVit', 'timm.models.fastvit.FastVitStage', 'torch.nn.modules.container.Sequential', 'timm.models.fastvit.RepMixerBlock', 'timm.models.fastvit.ConvMlp', 'torch.nn.modules.conv.Conv2d', 'aten.conv2d.default']J pkg.torch.onnx.fx_node%conv2d_20 : [num_users=1] = call_function[target=torch.ops.aten.conv2d.default](args = (%clone_6, %p_vision_model_vision__en_stages_1_blocks_1_mlp_fc2_weight, %p_vision_model_vision__en_stages_1_blocks_1_mlp_fc2_bias), kwargs = {})J pkg.torch.onnx.name_scopes['', 'vision_model.vision', 'vision_model.vision._en', 'vision_model.vision._en.stages.1', 'vision_model.vision._en.stages.1.blocks', 'vision_model.vision._en.stages.1.blocks.1', 'vision_model.vision._en.stages.1.blocks.1.mlp', 'vision_model.vision._en.stages.1.blocks.1.mlp.fc2', 'conv2d_20']J -pkg.torch.onnx.stack_trace File "/home/batman/xx3/./ml_tools/openpilot_compile/compile_supercombo.py", line 86, in forward +pkg.torch.onnx.stack_trace File "/home/batman/xx3/./ml_tools/openpilot_compile/compile_supercombo.py", line 82, in forward return torch.cat([*self.forward_dict(inputs).values(), self.pad], dim=1) File "/home/batman/xx3/xx/training/path/supercombo.py", line 185, in forward return self._en(x).flatten(1) @@ -967,7 +967,7 @@ node_mul_3"MulJ pkg.torch.onnx.class_hierarchy['__main__.FlattenedVisionModel', 'xx.training.path.supercombo.Vision', 'timm.models.fastvit.FastVit', 'timm.models.fastvit.FastVitStage', 'torch.nn.modules.container.Sequential', 'timm.models.fastvit.RepMixerBlock', 'timm.models.fastvit.LayerScale2d', 'aten.mul.Tensor']J pkg.torch.onnx.fx_node%mul_3 : [num_users=1] = call_function[target=torch.ops.aten.mul.Tensor](args = (%clone_7, %p_vision_model_vision__en_stages_1_blocks_1_layer_scale_gamma), kwargs = {})J pkg.torch.onnx.name_scopes['', 'vision_model.vision', 'vision_model.vision._en', 'vision_model.vision._en.stages.1', 'vision_model.vision._en.stages.1.blocks', 'vision_model.vision._en.stages.1.blocks.1', 'vision_model.vision._en.stages.1.blocks.1.layer_scale', 'mul_3']J -pkg.torch.onnx.stack_traceFile "/home/batman/xx3/./ml_tools/openpilot_compile/compile_supercombo.py", line 86, in forward +pkg.torch.onnx.stack_traceFile "/home/batman/xx3/./ml_tools/openpilot_compile/compile_supercombo.py", line 82, in forward return torch.cat([*self.forward_dict(inputs).values(), self.pad], dim=1) File "/home/batman/xx3/xx/training/path/supercombo.py", line 185, in forward return self._en(x).flatten(1) @@ -989,7 +989,7 @@ node_add_3"AddJ pkg.torch.onnx.class_hierarchy['__main__.FlattenedVisionModel', 'xx.training.path.supercombo.Vision', 'timm.models.fastvit.FastVit', 'timm.models.fastvit.FastVitStage', 'torch.nn.modules.container.Sequential', 'timm.models.fastvit.RepMixerBlock', 'aten.add.Tensor']J pkg.torch.onnx.fx_noder%add_3 : [num_users=1] = call_function[target=torch.ops.aten.add.Tensor](args = (%conv2d_17, %mul_3), kwargs = {})J pkg.torch.onnx.name_scopes['', 'vision_model.vision', 'vision_model.vision._en', 'vision_model.vision._en.stages.1', 'vision_model.vision._en.stages.1.blocks', 'vision_model.vision._en.stages.1.blocks.1', 'add_3']J -pkg.torch.onnx.stack_traceFile "/home/batman/xx3/./ml_tools/openpilot_compile/compile_supercombo.py", line 86, in forward +pkg.torch.onnx.stack_traceFile "/home/batman/xx3/./ml_tools/openpilot_compile/compile_supercombo.py", line 82, in forward return torch.cat([*self.forward_dict(inputs).values(), self.pad], dim=1) File "/home/batman/xx3/xx/training/path/supercombo.py", line 185, in forward return self._en(x).flatten(1) @@ -1014,7 +1014,7 @@ Dvision_model.vision._en.stages.2.downsample.proj.0.reparam_conv.bias conv2d_21 pkg.torch.onnx.class_hierarchy['__main__.FlattenedVisionModel', 'xx.training.path.supercombo.Vision', 'timm.models.fastvit.FastVit', 'timm.models.fastvit.FastVitStage', 'timm.models.fastvit.PatchEmbed', 'torch.nn.modules.container.Sequential', 'timm.models.fastvit.ReparamLargeKernelConv', 'torch.nn.modules.conv.Conv2d', 'aten.conv2d.default']J pkg.torch.onnx.fx_node%conv2d_21 : [num_users=1] = call_function[target=torch.ops.aten.conv2d.default](args = (%add_3, %p_vision_model_vision__en_stages_2_downsample_proj_0_reparam_conv_weight, %p_vision_model_vision__en_stages_2_downsample_proj_0_reparam_conv_bias, [2, 2], [3, 3], [1, 1], 128), kwargs = {})J pkg.torch.onnx.name_scopes['', 'vision_model.vision', 'vision_model.vision._en', 'vision_model.vision._en.stages.2', 'vision_model.vision._en.stages.2.downsample', 'vision_model.vision._en.stages.2.downsample.proj', 'vision_model.vision._en.stages.2.downsample.proj.0', 'vision_model.vision._en.stages.2.downsample.proj.0.reparam_conv', 'conv2d_21']J -pkg.torch.onnx.stack_traceFile "/home/batman/xx3/./ml_tools/openpilot_compile/compile_supercombo.py", line 86, in forward +pkg.torch.onnx.stack_traceFile "/home/batman/xx3/./ml_tools/openpilot_compile/compile_supercombo.py", line 82, in forward return torch.cat([*self.forward_dict(inputs).values(), self.pad], dim=1) File "/home/batman/xx3/xx/training/path/supercombo.py", line 185, in forward return self._en(x).flatten(1) @@ -1043,7 +1043,7 @@ Dvision_model.vision._en.stages.2.downsample.proj.1.reparam_conv.bias conv2d_22 pkg.torch.onnx.class_hierarchy['__main__.FlattenedVisionModel', 'xx.training.path.supercombo.Vision', 'timm.models.fastvit.FastVit', 'timm.models.fastvit.FastVitStage', 'timm.models.fastvit.PatchEmbed', 'torch.nn.modules.container.Sequential', 'timm.models.fastvit.MobileOneBlock', 'torch.nn.modules.conv.Conv2d', 'aten.conv2d.default']J pkg.torch.onnx.fx_node%conv2d_22 : [num_users=1] = call_function[target=torch.ops.aten.conv2d.default](args = (%conv2d_21, %p_vision_model_vision__en_stages_2_downsample_proj_1_reparam_conv_weight, %p_vision_model_vision__en_stages_2_downsample_proj_1_reparam_conv_bias), kwargs = {})J pkg.torch.onnx.name_scopes['', 'vision_model.vision', 'vision_model.vision._en', 'vision_model.vision._en.stages.2', 'vision_model.vision._en.stages.2.downsample', 'vision_model.vision._en.stages.2.downsample.proj', 'vision_model.vision._en.stages.2.downsample.proj.1', 'vision_model.vision._en.stages.2.downsample.proj.1.reparam_conv', 'conv2d_22']J -pkg.torch.onnx.stack_traceFile "/home/batman/xx3/./ml_tools/openpilot_compile/compile_supercombo.py", line 86, in forward +pkg.torch.onnx.stack_traceFile "/home/batman/xx3/./ml_tools/openpilot_compile/compile_supercombo.py", line 82, in forward return torch.cat([*self.forward_dict(inputs).values(), self.pad], dim=1) File "/home/batman/xx3/xx/training/path/supercombo.py", line 185, in forward return self._en(x).flatten(1) @@ -1066,7 +1066,7 @@ Dvision_model.vision._en.stages.2.downsample.proj.1.reparam_conv.bias conv2d_22 pkg.torch.onnx.class_hierarchy['__main__.FlattenedVisionModel', 'xx.training.path.supercombo.Vision', 'timm.models.fastvit.FastVit', 'timm.models.fastvit.FastVitStage', 'timm.models.fastvit.PatchEmbed', 'torch.nn.modules.container.Sequential', 'timm.models.fastvit.MobileOneBlock', 'timm.layers.activations.GELUTanh', 'aten.gelu.default']J pkg.torch.onnx.fx_node%gelu_8 : [num_users=1] = call_function[target=torch.ops.aten.gelu.default](args = (%conv2d_22,), kwargs = {approximate: tanh})J pkg.torch.onnx.name_scopes['', 'vision_model.vision', 'vision_model.vision._en', 'vision_model.vision._en.stages.2', 'vision_model.vision._en.stages.2.downsample', 'vision_model.vision._en.stages.2.downsample.proj', 'vision_model.vision._en.stages.2.downsample.proj.1', 'vision_model.vision._en.stages.2.downsample.proj.1.act', 'gelu_8']J -pkg.torch.onnx.stack_traceFile "/home/batman/xx3/./ml_tools/openpilot_compile/compile_supercombo.py", line 86, in forward +pkg.torch.onnx.stack_traceFile "/home/batman/xx3/./ml_tools/openpilot_compile/compile_supercombo.py", line 82, in forward return torch.cat([*self.forward_dict(inputs).values(), self.pad], dim=1) File "/home/batman/xx3/xx/training/path/supercombo.py", line 185, in forward return self._en(x).flatten(1) @@ -1095,7 +1095,7 @@ Gvision_model.vision._en.stages.2.blocks.0.token_mixer.reparam_conv.bias conv2d pkg.torch.onnx.class_hierarchy['__main__.FlattenedVisionModel', 'xx.training.path.supercombo.Vision', 'timm.models.fastvit.FastVit', 'timm.models.fastvit.FastVitStage', 'torch.nn.modules.container.Sequential', 'timm.models.fastvit.RepMixerBlock', 'timm.models.fastvit.RepMixer', 'torch.nn.modules.conv.Conv2d', 'aten.conv2d.default']J pkg.torch.onnx.fx_node%conv2d_23 : [num_users=2] = call_function[target=torch.ops.aten.conv2d.default](args = (%gelu_8, %p_vision_model_vision__en_stages_2_blocks_0_token_mixer_reparam_conv_weight, %p_vision_model_vision__en_stages_2_blocks_0_token_mixer_reparam_conv_bias, [1, 1], [1, 1], [1, 1], 256), kwargs = {})J pkg.torch.onnx.name_scopes['', 'vision_model.vision', 'vision_model.vision._en', 'vision_model.vision._en.stages.2', 'vision_model.vision._en.stages.2.blocks', 'vision_model.vision._en.stages.2.blocks.0', 'vision_model.vision._en.stages.2.blocks.0.token_mixer', 'vision_model.vision._en.stages.2.blocks.0.token_mixer.reparam_conv', 'conv2d_23']J -pkg.torch.onnx.stack_traceFile "/home/batman/xx3/./ml_tools/openpilot_compile/compile_supercombo.py", line 86, in forward +pkg.torch.onnx.stack_traceFile "/home/batman/xx3/./ml_tools/openpilot_compile/compile_supercombo.py", line 82, in forward return torch.cat([*self.forward_dict(inputs).values(), self.pad], dim=1) File "/home/batman/xx3/xx/training/path/supercombo.py", line 185, in forward return self._en(x).flatten(1) @@ -1126,7 +1126,7 @@ getitem_12 node_Conv_190"Conv* pkg.torch.onnx.class_hierarchy['__main__.FlattenedVisionModel', 'xx.training.path.supercombo.Vision', 'timm.models.fastvit.FastVit', 'timm.models.fastvit.FastVitStage', 'torch.nn.modules.container.Sequential', 'timm.models.fastvit.RepMixerBlock', 'timm.models.fastvit.ConvMlp', 'timm.layers.conv_bn_act.ConvNormAct', 'timm.layers.norm_act.BatchNormAct2d', 'aten._native_batch_norm_legit_no_training.default']J pkg.torch.onnx.fx_node%_native_batch_norm_legit_no_training_4 : [num_users=1] = call_function[target=torch.ops.aten._native_batch_norm_legit_no_training.default](args = (%conv2d_24, %p_vision_model_vision__en_stages_2_blocks_0_mlp_conv_bn_weight, %p_vision_model_vision__en_stages_2_blocks_0_mlp_conv_bn_bias, %b_vision_model_vision__en_stages_2_blocks_0_mlp_conv_bn_running_mean, %b_vision_model_vision__en_stages_2_blocks_0_mlp_conv_bn_running_var, 0.1, 1e-05), kwargs = {})J pkg.torch.onnx.name_scopes['', 'vision_model.vision', 'vision_model.vision._en', 'vision_model.vision._en.stages.2', 'vision_model.vision._en.stages.2.blocks', 'vision_model.vision._en.stages.2.blocks.0', 'vision_model.vision._en.stages.2.blocks.0.mlp', 'vision_model.vision._en.stages.2.blocks.0.mlp.conv', 'vision_model.vision._en.stages.2.blocks.0.mlp.conv.bn', '_native_batch_norm_legit_no_training_4']J -pkg.torch.onnx.stack_trace File "/home/batman/xx3/./ml_tools/openpilot_compile/compile_supercombo.py", line 86, in forward +pkg.torch.onnx.stack_trace File "/home/batman/xx3/./ml_tools/openpilot_compile/compile_supercombo.py", line 82, in forward return torch.cat([*self.forward_dict(inputs).values(), self.pad], dim=1) File "/home/batman/xx3/xx/training/path/supercombo.py", line 185, in forward return self._en(x).flatten(1) @@ -1158,7 +1158,7 @@ getitem_12 pkg.torch.onnx.class_hierarchy['__main__.FlattenedVisionModel', 'xx.training.path.supercombo.Vision', 'timm.models.fastvit.FastVit', 'timm.models.fastvit.FastVitStage', 'torch.nn.modules.container.Sequential', 'timm.models.fastvit.RepMixerBlock', 'timm.models.fastvit.ConvMlp', 'torch.nn.modules.conv.Conv2d', 'aten.conv2d.default']J pkg.torch.onnx.fx_node%conv2d_25 : [num_users=1] = call_function[target=torch.ops.aten.conv2d.default](args = (%getitem_12, %p_vision_model_vision__en_stages_2_blocks_0_mlp_fc1_weight, %p_vision_model_vision__en_stages_2_blocks_0_mlp_fc1_bias), kwargs = {})J pkg.torch.onnx.name_scopes['', 'vision_model.vision', 'vision_model.vision._en', 'vision_model.vision._en.stages.2', 'vision_model.vision._en.stages.2.blocks', 'vision_model.vision._en.stages.2.blocks.0', 'vision_model.vision._en.stages.2.blocks.0.mlp', 'vision_model.vision._en.stages.2.blocks.0.mlp.fc1', 'conv2d_25']J -pkg.torch.onnx.stack_trace File "/home/batman/xx3/./ml_tools/openpilot_compile/compile_supercombo.py", line 86, in forward +pkg.torch.onnx.stack_trace File "/home/batman/xx3/./ml_tools/openpilot_compile/compile_supercombo.py", line 82, in forward return torch.cat([*self.forward_dict(inputs).values(), self.pad], dim=1) File "/home/batman/xx3/xx/training/path/supercombo.py", line 185, in forward return self._en(x).flatten(1) @@ -1181,7 +1181,7 @@ getitem_12 pkg.torch.onnx.class_hierarchy['__main__.FlattenedVisionModel', 'xx.training.path.supercombo.Vision', 'timm.models.fastvit.FastVit', 'timm.models.fastvit.FastVitStage', 'torch.nn.modules.container.Sequential', 'timm.models.fastvit.RepMixerBlock', 'timm.models.fastvit.ConvMlp', 'timm.layers.activations.GELUTanh', 'aten.gelu.default']J pkg.torch.onnx.fx_node%gelu_9 : [num_users=1] = call_function[target=torch.ops.aten.gelu.default](args = (%conv2d_25,), kwargs = {approximate: tanh})J pkg.torch.onnx.name_scopes['', 'vision_model.vision', 'vision_model.vision._en', 'vision_model.vision._en.stages.2', 'vision_model.vision._en.stages.2.blocks', 'vision_model.vision._en.stages.2.blocks.0', 'vision_model.vision._en.stages.2.blocks.0.mlp', 'vision_model.vision._en.stages.2.blocks.0.mlp.act', 'gelu_9']J -pkg.torch.onnx.stack_traceFile "/home/batman/xx3/./ml_tools/openpilot_compile/compile_supercombo.py", line 86, in forward +pkg.torch.onnx.stack_traceFile "/home/batman/xx3/./ml_tools/openpilot_compile/compile_supercombo.py", line 82, in forward return torch.cat([*self.forward_dict(inputs).values(), self.pad], dim=1) File "/home/batman/xx3/xx/training/path/supercombo.py", line 185, in forward return self._en(x).flatten(1) @@ -1210,7 +1210,7 @@ getitem_12 pkg.torch.onnx.class_hierarchy['__main__.FlattenedVisionModel', 'xx.training.path.supercombo.Vision', 'timm.models.fastvit.FastVit', 'timm.models.fastvit.FastVitStage', 'torch.nn.modules.container.Sequential', 'timm.models.fastvit.RepMixerBlock', 'timm.models.fastvit.ConvMlp', 'torch.nn.modules.conv.Conv2d', 'aten.conv2d.default']J pkg.torch.onnx.fx_node%conv2d_26 : [num_users=1] = call_function[target=torch.ops.aten.conv2d.default](args = (%clone_8, %p_vision_model_vision__en_stages_2_blocks_0_mlp_fc2_weight, %p_vision_model_vision__en_stages_2_blocks_0_mlp_fc2_bias), kwargs = {})J pkg.torch.onnx.name_scopes['', 'vision_model.vision', 'vision_model.vision._en', 'vision_model.vision._en.stages.2', 'vision_model.vision._en.stages.2.blocks', 'vision_model.vision._en.stages.2.blocks.0', 'vision_model.vision._en.stages.2.blocks.0.mlp', 'vision_model.vision._en.stages.2.blocks.0.mlp.fc2', 'conv2d_26']J -pkg.torch.onnx.stack_trace File "/home/batman/xx3/./ml_tools/openpilot_compile/compile_supercombo.py", line 86, in forward +pkg.torch.onnx.stack_trace File "/home/batman/xx3/./ml_tools/openpilot_compile/compile_supercombo.py", line 82, in forward return torch.cat([*self.forward_dict(inputs).values(), self.pad], dim=1) File "/home/batman/xx3/xx/training/path/supercombo.py", line 185, in forward return self._en(x).flatten(1) @@ -1234,7 +1234,7 @@ node_mul_4"MulJ pkg.torch.onnx.class_hierarchy['__main__.FlattenedVisionModel', 'xx.training.path.supercombo.Vision', 'timm.models.fastvit.FastVit', 'timm.models.fastvit.FastVitStage', 'torch.nn.modules.container.Sequential', 'timm.models.fastvit.RepMixerBlock', 'timm.models.fastvit.LayerScale2d', 'aten.mul.Tensor']J pkg.torch.onnx.fx_node%mul_4 : [num_users=1] = call_function[target=torch.ops.aten.mul.Tensor](args = (%clone_9, %p_vision_model_vision__en_stages_2_blocks_0_layer_scale_gamma), kwargs = {})J pkg.torch.onnx.name_scopes['', 'vision_model.vision', 'vision_model.vision._en', 'vision_model.vision._en.stages.2', 'vision_model.vision._en.stages.2.blocks', 'vision_model.vision._en.stages.2.blocks.0', 'vision_model.vision._en.stages.2.blocks.0.layer_scale', 'mul_4']J -pkg.torch.onnx.stack_traceFile "/home/batman/xx3/./ml_tools/openpilot_compile/compile_supercombo.py", line 86, in forward +pkg.torch.onnx.stack_traceFile "/home/batman/xx3/./ml_tools/openpilot_compile/compile_supercombo.py", line 82, in forward return torch.cat([*self.forward_dict(inputs).values(), self.pad], dim=1) File "/home/batman/xx3/xx/training/path/supercombo.py", line 185, in forward return self._en(x).flatten(1) @@ -1256,7 +1256,7 @@ node_add_4"AddJ pkg.torch.onnx.class_hierarchy['__main__.FlattenedVisionModel', 'xx.training.path.supercombo.Vision', 'timm.models.fastvit.FastVit', 'timm.models.fastvit.FastVitStage', 'torch.nn.modules.container.Sequential', 'timm.models.fastvit.RepMixerBlock', 'aten.add.Tensor']J pkg.torch.onnx.fx_noder%add_4 : [num_users=1] = call_function[target=torch.ops.aten.add.Tensor](args = (%conv2d_23, %mul_4), kwargs = {})J pkg.torch.onnx.name_scopes['', 'vision_model.vision', 'vision_model.vision._en', 'vision_model.vision._en.stages.2', 'vision_model.vision._en.stages.2.blocks', 'vision_model.vision._en.stages.2.blocks.0', 'add_4']J -pkg.torch.onnx.stack_traceFile "/home/batman/xx3/./ml_tools/openpilot_compile/compile_supercombo.py", line 86, in forward +pkg.torch.onnx.stack_traceFile "/home/batman/xx3/./ml_tools/openpilot_compile/compile_supercombo.py", line 82, in forward return torch.cat([*self.forward_dict(inputs).values(), self.pad], dim=1) File "/home/batman/xx3/xx/training/path/supercombo.py", line 185, in forward return self._en(x).flatten(1) @@ -1281,7 +1281,7 @@ Gvision_model.vision._en.stages.2.blocks.1.token_mixer.reparam_conv.bias conv2d pkg.torch.onnx.class_hierarchy['__main__.FlattenedVisionModel', 'xx.training.path.supercombo.Vision', 'timm.models.fastvit.FastVit', 'timm.models.fastvit.FastVitStage', 'torch.nn.modules.container.Sequential', 'timm.models.fastvit.RepMixerBlock', 'timm.models.fastvit.RepMixer', 'torch.nn.modules.conv.Conv2d', 'aten.conv2d.default']J pkg.torch.onnx.fx_node%conv2d_27 : [num_users=2] = call_function[target=torch.ops.aten.conv2d.default](args = (%add_4, %p_vision_model_vision__en_stages_2_blocks_1_token_mixer_reparam_conv_weight, %p_vision_model_vision__en_stages_2_blocks_1_token_mixer_reparam_conv_bias, [1, 1], [1, 1], [1, 1], 256), kwargs = {})J pkg.torch.onnx.name_scopes['', 'vision_model.vision', 'vision_model.vision._en', 'vision_model.vision._en.stages.2', 'vision_model.vision._en.stages.2.blocks', 'vision_model.vision._en.stages.2.blocks.1', 'vision_model.vision._en.stages.2.blocks.1.token_mixer', 'vision_model.vision._en.stages.2.blocks.1.token_mixer.reparam_conv', 'conv2d_27']J -pkg.torch.onnx.stack_traceFile "/home/batman/xx3/./ml_tools/openpilot_compile/compile_supercombo.py", line 86, in forward +pkg.torch.onnx.stack_traceFile "/home/batman/xx3/./ml_tools/openpilot_compile/compile_supercombo.py", line 82, in forward return torch.cat([*self.forward_dict(inputs).values(), self.pad], dim=1) File "/home/batman/xx3/xx/training/path/supercombo.py", line 185, in forward return self._en(x).flatten(1) @@ -1312,7 +1312,7 @@ getitem_15 node_Conv_192"Conv* pkg.torch.onnx.class_hierarchy['__main__.FlattenedVisionModel', 'xx.training.path.supercombo.Vision', 'timm.models.fastvit.FastVit', 'timm.models.fastvit.FastVitStage', 'torch.nn.modules.container.Sequential', 'timm.models.fastvit.RepMixerBlock', 'timm.models.fastvit.ConvMlp', 'timm.layers.conv_bn_act.ConvNormAct', 'timm.layers.norm_act.BatchNormAct2d', 'aten._native_batch_norm_legit_no_training.default']J pkg.torch.onnx.fx_node%_native_batch_norm_legit_no_training_5 : [num_users=1] = call_function[target=torch.ops.aten._native_batch_norm_legit_no_training.default](args = (%conv2d_28, %p_vision_model_vision__en_stages_2_blocks_1_mlp_conv_bn_weight, %p_vision_model_vision__en_stages_2_blocks_1_mlp_conv_bn_bias, %b_vision_model_vision__en_stages_2_blocks_1_mlp_conv_bn_running_mean, %b_vision_model_vision__en_stages_2_blocks_1_mlp_conv_bn_running_var, 0.1, 1e-05), kwargs = {})J pkg.torch.onnx.name_scopes['', 'vision_model.vision', 'vision_model.vision._en', 'vision_model.vision._en.stages.2', 'vision_model.vision._en.stages.2.blocks', 'vision_model.vision._en.stages.2.blocks.1', 'vision_model.vision._en.stages.2.blocks.1.mlp', 'vision_model.vision._en.stages.2.blocks.1.mlp.conv', 'vision_model.vision._en.stages.2.blocks.1.mlp.conv.bn', '_native_batch_norm_legit_no_training_5']J -pkg.torch.onnx.stack_trace File "/home/batman/xx3/./ml_tools/openpilot_compile/compile_supercombo.py", line 86, in forward +pkg.torch.onnx.stack_trace File "/home/batman/xx3/./ml_tools/openpilot_compile/compile_supercombo.py", line 82, in forward return torch.cat([*self.forward_dict(inputs).values(), self.pad], dim=1) File "/home/batman/xx3/xx/training/path/supercombo.py", line 185, in forward return self._en(x).flatten(1) @@ -1344,7 +1344,7 @@ getitem_15 pkg.torch.onnx.class_hierarchy['__main__.FlattenedVisionModel', 'xx.training.path.supercombo.Vision', 'timm.models.fastvit.FastVit', 'timm.models.fastvit.FastVitStage', 'torch.nn.modules.container.Sequential', 'timm.models.fastvit.RepMixerBlock', 'timm.models.fastvit.ConvMlp', 'torch.nn.modules.conv.Conv2d', 'aten.conv2d.default']J pkg.torch.onnx.fx_node%conv2d_29 : [num_users=1] = call_function[target=torch.ops.aten.conv2d.default](args = (%getitem_15, %p_vision_model_vision__en_stages_2_blocks_1_mlp_fc1_weight, %p_vision_model_vision__en_stages_2_blocks_1_mlp_fc1_bias), kwargs = {})J pkg.torch.onnx.name_scopes['', 'vision_model.vision', 'vision_model.vision._en', 'vision_model.vision._en.stages.2', 'vision_model.vision._en.stages.2.blocks', 'vision_model.vision._en.stages.2.blocks.1', 'vision_model.vision._en.stages.2.blocks.1.mlp', 'vision_model.vision._en.stages.2.blocks.1.mlp.fc1', 'conv2d_29']J -pkg.torch.onnx.stack_trace File "/home/batman/xx3/./ml_tools/openpilot_compile/compile_supercombo.py", line 86, in forward +pkg.torch.onnx.stack_trace File "/home/batman/xx3/./ml_tools/openpilot_compile/compile_supercombo.py", line 82, in forward return torch.cat([*self.forward_dict(inputs).values(), self.pad], dim=1) File "/home/batman/xx3/xx/training/path/supercombo.py", line 185, in forward return self._en(x).flatten(1) @@ -1367,7 +1367,7 @@ getitem_15 pkg.torch.onnx.class_hierarchy['__main__.FlattenedVisionModel', 'xx.training.path.supercombo.Vision', 'timm.models.fastvit.FastVit', 'timm.models.fastvit.FastVitStage', 'torch.nn.modules.container.Sequential', 'timm.models.fastvit.RepMixerBlock', 'timm.models.fastvit.ConvMlp', 'timm.layers.activations.GELUTanh', 'aten.gelu.default']J pkg.torch.onnx.fx_node%gelu_10 : [num_users=1] = call_function[target=torch.ops.aten.gelu.default](args = (%conv2d_29,), kwargs = {approximate: tanh})J pkg.torch.onnx.name_scopes['', 'vision_model.vision', 'vision_model.vision._en', 'vision_model.vision._en.stages.2', 'vision_model.vision._en.stages.2.blocks', 'vision_model.vision._en.stages.2.blocks.1', 'vision_model.vision._en.stages.2.blocks.1.mlp', 'vision_model.vision._en.stages.2.blocks.1.mlp.act', 'gelu_10']J -pkg.torch.onnx.stack_traceFile "/home/batman/xx3/./ml_tools/openpilot_compile/compile_supercombo.py", line 86, in forward +pkg.torch.onnx.stack_traceFile "/home/batman/xx3/./ml_tools/openpilot_compile/compile_supercombo.py", line 82, in forward return torch.cat([*self.forward_dict(inputs).values(), self.pad], dim=1) File "/home/batman/xx3/xx/training/path/supercombo.py", line 185, in forward return self._en(x).flatten(1) @@ -1396,7 +1396,7 @@ getitem_15 pkg.torch.onnx.class_hierarchy['__main__.FlattenedVisionModel', 'xx.training.path.supercombo.Vision', 'timm.models.fastvit.FastVit', 'timm.models.fastvit.FastVitStage', 'torch.nn.modules.container.Sequential', 'timm.models.fastvit.RepMixerBlock', 'timm.models.fastvit.ConvMlp', 'torch.nn.modules.conv.Conv2d', 'aten.conv2d.default']J pkg.torch.onnx.fx_node%conv2d_30 : [num_users=1] = call_function[target=torch.ops.aten.conv2d.default](args = (%clone_10, %p_vision_model_vision__en_stages_2_blocks_1_mlp_fc2_weight, %p_vision_model_vision__en_stages_2_blocks_1_mlp_fc2_bias), kwargs = {})J pkg.torch.onnx.name_scopes['', 'vision_model.vision', 'vision_model.vision._en', 'vision_model.vision._en.stages.2', 'vision_model.vision._en.stages.2.blocks', 'vision_model.vision._en.stages.2.blocks.1', 'vision_model.vision._en.stages.2.blocks.1.mlp', 'vision_model.vision._en.stages.2.blocks.1.mlp.fc2', 'conv2d_30']J -pkg.torch.onnx.stack_trace File "/home/batman/xx3/./ml_tools/openpilot_compile/compile_supercombo.py", line 86, in forward +pkg.torch.onnx.stack_trace File "/home/batman/xx3/./ml_tools/openpilot_compile/compile_supercombo.py", line 82, in forward return torch.cat([*self.forward_dict(inputs).values(), self.pad], dim=1) File "/home/batman/xx3/xx/training/path/supercombo.py", line 185, in forward return self._en(x).flatten(1) @@ -1420,7 +1420,7 @@ node_mul_5"MulJ pkg.torch.onnx.class_hierarchy['__main__.FlattenedVisionModel', 'xx.training.path.supercombo.Vision', 'timm.models.fastvit.FastVit', 'timm.models.fastvit.FastVitStage', 'torch.nn.modules.container.Sequential', 'timm.models.fastvit.RepMixerBlock', 'timm.models.fastvit.LayerScale2d', 'aten.mul.Tensor']J pkg.torch.onnx.fx_node%mul_5 : [num_users=1] = call_function[target=torch.ops.aten.mul.Tensor](args = (%clone_11, %p_vision_model_vision__en_stages_2_blocks_1_layer_scale_gamma), kwargs = {})J pkg.torch.onnx.name_scopes['', 'vision_model.vision', 'vision_model.vision._en', 'vision_model.vision._en.stages.2', 'vision_model.vision._en.stages.2.blocks', 'vision_model.vision._en.stages.2.blocks.1', 'vision_model.vision._en.stages.2.blocks.1.layer_scale', 'mul_5']J -pkg.torch.onnx.stack_traceFile "/home/batman/xx3/./ml_tools/openpilot_compile/compile_supercombo.py", line 86, in forward +pkg.torch.onnx.stack_traceFile "/home/batman/xx3/./ml_tools/openpilot_compile/compile_supercombo.py", line 82, in forward return torch.cat([*self.forward_dict(inputs).values(), self.pad], dim=1) File "/home/batman/xx3/xx/training/path/supercombo.py", line 185, in forward return self._en(x).flatten(1) @@ -1442,7 +1442,7 @@ node_add_5"AddJ pkg.torch.onnx.class_hierarchy['__main__.FlattenedVisionModel', 'xx.training.path.supercombo.Vision', 'timm.models.fastvit.FastVit', 'timm.models.fastvit.FastVitStage', 'torch.nn.modules.container.Sequential', 'timm.models.fastvit.RepMixerBlock', 'aten.add.Tensor']J pkg.torch.onnx.fx_noder%add_5 : [num_users=1] = call_function[target=torch.ops.aten.add.Tensor](args = (%conv2d_27, %mul_5), kwargs = {})J pkg.torch.onnx.name_scopes['', 'vision_model.vision', 'vision_model.vision._en', 'vision_model.vision._en.stages.2', 'vision_model.vision._en.stages.2.blocks', 'vision_model.vision._en.stages.2.blocks.1', 'add_5']J -pkg.torch.onnx.stack_traceFile "/home/batman/xx3/./ml_tools/openpilot_compile/compile_supercombo.py", line 86, in forward +pkg.torch.onnx.stack_traceFile "/home/batman/xx3/./ml_tools/openpilot_compile/compile_supercombo.py", line 82, in forward return torch.cat([*self.forward_dict(inputs).values(), self.pad], dim=1) File "/home/batman/xx3/xx/training/path/supercombo.py", line 185, in forward return self._en(x).flatten(1) @@ -1467,7 +1467,7 @@ Gvision_model.vision._en.stages.2.blocks.2.token_mixer.reparam_conv.bias conv2d pkg.torch.onnx.class_hierarchy['__main__.FlattenedVisionModel', 'xx.training.path.supercombo.Vision', 'timm.models.fastvit.FastVit', 'timm.models.fastvit.FastVitStage', 'torch.nn.modules.container.Sequential', 'timm.models.fastvit.RepMixerBlock', 'timm.models.fastvit.RepMixer', 'torch.nn.modules.conv.Conv2d', 'aten.conv2d.default']J pkg.torch.onnx.fx_node%conv2d_31 : [num_users=2] = call_function[target=torch.ops.aten.conv2d.default](args = (%add_5, %p_vision_model_vision__en_stages_2_blocks_2_token_mixer_reparam_conv_weight, %p_vision_model_vision__en_stages_2_blocks_2_token_mixer_reparam_conv_bias, [1, 1], [1, 1], [1, 1], 256), kwargs = {})J pkg.torch.onnx.name_scopes['', 'vision_model.vision', 'vision_model.vision._en', 'vision_model.vision._en.stages.2', 'vision_model.vision._en.stages.2.blocks', 'vision_model.vision._en.stages.2.blocks.2', 'vision_model.vision._en.stages.2.blocks.2.token_mixer', 'vision_model.vision._en.stages.2.blocks.2.token_mixer.reparam_conv', 'conv2d_31']J -pkg.torch.onnx.stack_traceFile "/home/batman/xx3/./ml_tools/openpilot_compile/compile_supercombo.py", line 86, in forward +pkg.torch.onnx.stack_traceFile "/home/batman/xx3/./ml_tools/openpilot_compile/compile_supercombo.py", line 82, in forward return torch.cat([*self.forward_dict(inputs).values(), self.pad], dim=1) File "/home/batman/xx3/xx/training/path/supercombo.py", line 185, in forward return self._en(x).flatten(1) @@ -1498,7 +1498,7 @@ getitem_18 node_Conv_194"Conv* pkg.torch.onnx.class_hierarchy['__main__.FlattenedVisionModel', 'xx.training.path.supercombo.Vision', 'timm.models.fastvit.FastVit', 'timm.models.fastvit.FastVitStage', 'torch.nn.modules.container.Sequential', 'timm.models.fastvit.RepMixerBlock', 'timm.models.fastvit.ConvMlp', 'timm.layers.conv_bn_act.ConvNormAct', 'timm.layers.norm_act.BatchNormAct2d', 'aten._native_batch_norm_legit_no_training.default']J pkg.torch.onnx.fx_node%_native_batch_norm_legit_no_training_6 : [num_users=1] = call_function[target=torch.ops.aten._native_batch_norm_legit_no_training.default](args = (%conv2d_32, %p_vision_model_vision__en_stages_2_blocks_2_mlp_conv_bn_weight, %p_vision_model_vision__en_stages_2_blocks_2_mlp_conv_bn_bias, %b_vision_model_vision__en_stages_2_blocks_2_mlp_conv_bn_running_mean, %b_vision_model_vision__en_stages_2_blocks_2_mlp_conv_bn_running_var, 0.1, 1e-05), kwargs = {})J pkg.torch.onnx.name_scopes['', 'vision_model.vision', 'vision_model.vision._en', 'vision_model.vision._en.stages.2', 'vision_model.vision._en.stages.2.blocks', 'vision_model.vision._en.stages.2.blocks.2', 'vision_model.vision._en.stages.2.blocks.2.mlp', 'vision_model.vision._en.stages.2.blocks.2.mlp.conv', 'vision_model.vision._en.stages.2.blocks.2.mlp.conv.bn', '_native_batch_norm_legit_no_training_6']J -pkg.torch.onnx.stack_trace File "/home/batman/xx3/./ml_tools/openpilot_compile/compile_supercombo.py", line 86, in forward +pkg.torch.onnx.stack_trace File "/home/batman/xx3/./ml_tools/openpilot_compile/compile_supercombo.py", line 82, in forward return torch.cat([*self.forward_dict(inputs).values(), self.pad], dim=1) File "/home/batman/xx3/xx/training/path/supercombo.py", line 185, in forward return self._en(x).flatten(1) @@ -1530,7 +1530,7 @@ getitem_18 pkg.torch.onnx.class_hierarchy['__main__.FlattenedVisionModel', 'xx.training.path.supercombo.Vision', 'timm.models.fastvit.FastVit', 'timm.models.fastvit.FastVitStage', 'torch.nn.modules.container.Sequential', 'timm.models.fastvit.RepMixerBlock', 'timm.models.fastvit.ConvMlp', 'torch.nn.modules.conv.Conv2d', 'aten.conv2d.default']J pkg.torch.onnx.fx_node%conv2d_33 : [num_users=1] = call_function[target=torch.ops.aten.conv2d.default](args = (%getitem_18, %p_vision_model_vision__en_stages_2_blocks_2_mlp_fc1_weight, %p_vision_model_vision__en_stages_2_blocks_2_mlp_fc1_bias), kwargs = {})J pkg.torch.onnx.name_scopes['', 'vision_model.vision', 'vision_model.vision._en', 'vision_model.vision._en.stages.2', 'vision_model.vision._en.stages.2.blocks', 'vision_model.vision._en.stages.2.blocks.2', 'vision_model.vision._en.stages.2.blocks.2.mlp', 'vision_model.vision._en.stages.2.blocks.2.mlp.fc1', 'conv2d_33']J -pkg.torch.onnx.stack_trace File "/home/batman/xx3/./ml_tools/openpilot_compile/compile_supercombo.py", line 86, in forward +pkg.torch.onnx.stack_trace File "/home/batman/xx3/./ml_tools/openpilot_compile/compile_supercombo.py", line 82, in forward return torch.cat([*self.forward_dict(inputs).values(), self.pad], dim=1) File "/home/batman/xx3/xx/training/path/supercombo.py", line 185, in forward return self._en(x).flatten(1) @@ -1553,7 +1553,7 @@ getitem_18 pkg.torch.onnx.class_hierarchy['__main__.FlattenedVisionModel', 'xx.training.path.supercombo.Vision', 'timm.models.fastvit.FastVit', 'timm.models.fastvit.FastVitStage', 'torch.nn.modules.container.Sequential', 'timm.models.fastvit.RepMixerBlock', 'timm.models.fastvit.ConvMlp', 'timm.layers.activations.GELUTanh', 'aten.gelu.default']J pkg.torch.onnx.fx_node%gelu_11 : [num_users=1] = call_function[target=torch.ops.aten.gelu.default](args = (%conv2d_33,), kwargs = {approximate: tanh})J pkg.torch.onnx.name_scopes['', 'vision_model.vision', 'vision_model.vision._en', 'vision_model.vision._en.stages.2', 'vision_model.vision._en.stages.2.blocks', 'vision_model.vision._en.stages.2.blocks.2', 'vision_model.vision._en.stages.2.blocks.2.mlp', 'vision_model.vision._en.stages.2.blocks.2.mlp.act', 'gelu_11']J -pkg.torch.onnx.stack_traceFile "/home/batman/xx3/./ml_tools/openpilot_compile/compile_supercombo.py", line 86, in forward +pkg.torch.onnx.stack_traceFile "/home/batman/xx3/./ml_tools/openpilot_compile/compile_supercombo.py", line 82, in forward return torch.cat([*self.forward_dict(inputs).values(), self.pad], dim=1) File "/home/batman/xx3/xx/training/path/supercombo.py", line 185, in forward return self._en(x).flatten(1) @@ -1582,7 +1582,7 @@ getitem_18 pkg.torch.onnx.class_hierarchy['__main__.FlattenedVisionModel', 'xx.training.path.supercombo.Vision', 'timm.models.fastvit.FastVit', 'timm.models.fastvit.FastVitStage', 'torch.nn.modules.container.Sequential', 'timm.models.fastvit.RepMixerBlock', 'timm.models.fastvit.ConvMlp', 'torch.nn.modules.conv.Conv2d', 'aten.conv2d.default']J pkg.torch.onnx.fx_node%conv2d_34 : [num_users=1] = call_function[target=torch.ops.aten.conv2d.default](args = (%clone_12, %p_vision_model_vision__en_stages_2_blocks_2_mlp_fc2_weight, %p_vision_model_vision__en_stages_2_blocks_2_mlp_fc2_bias), kwargs = {})J pkg.torch.onnx.name_scopes['', 'vision_model.vision', 'vision_model.vision._en', 'vision_model.vision._en.stages.2', 'vision_model.vision._en.stages.2.blocks', 'vision_model.vision._en.stages.2.blocks.2', 'vision_model.vision._en.stages.2.blocks.2.mlp', 'vision_model.vision._en.stages.2.blocks.2.mlp.fc2', 'conv2d_34']J -pkg.torch.onnx.stack_trace File "/home/batman/xx3/./ml_tools/openpilot_compile/compile_supercombo.py", line 86, in forward +pkg.torch.onnx.stack_trace File "/home/batman/xx3/./ml_tools/openpilot_compile/compile_supercombo.py", line 82, in forward return torch.cat([*self.forward_dict(inputs).values(), self.pad], dim=1) File "/home/batman/xx3/xx/training/path/supercombo.py", line 185, in forward return self._en(x).flatten(1) @@ -1606,7 +1606,7 @@ node_mul_6"MulJ pkg.torch.onnx.class_hierarchy['__main__.FlattenedVisionModel', 'xx.training.path.supercombo.Vision', 'timm.models.fastvit.FastVit', 'timm.models.fastvit.FastVitStage', 'torch.nn.modules.container.Sequential', 'timm.models.fastvit.RepMixerBlock', 'timm.models.fastvit.LayerScale2d', 'aten.mul.Tensor']J pkg.torch.onnx.fx_node%mul_6 : [num_users=1] = call_function[target=torch.ops.aten.mul.Tensor](args = (%clone_13, %p_vision_model_vision__en_stages_2_blocks_2_layer_scale_gamma), kwargs = {})J pkg.torch.onnx.name_scopes['', 'vision_model.vision', 'vision_model.vision._en', 'vision_model.vision._en.stages.2', 'vision_model.vision._en.stages.2.blocks', 'vision_model.vision._en.stages.2.blocks.2', 'vision_model.vision._en.stages.2.blocks.2.layer_scale', 'mul_6']J -pkg.torch.onnx.stack_traceFile "/home/batman/xx3/./ml_tools/openpilot_compile/compile_supercombo.py", line 86, in forward +pkg.torch.onnx.stack_traceFile "/home/batman/xx3/./ml_tools/openpilot_compile/compile_supercombo.py", line 82, in forward return torch.cat([*self.forward_dict(inputs).values(), self.pad], dim=1) File "/home/batman/xx3/xx/training/path/supercombo.py", line 185, in forward return self._en(x).flatten(1) @@ -1628,7 +1628,7 @@ node_add_6"AddJ pkg.torch.onnx.class_hierarchy['__main__.FlattenedVisionModel', 'xx.training.path.supercombo.Vision', 'timm.models.fastvit.FastVit', 'timm.models.fastvit.FastVitStage', 'torch.nn.modules.container.Sequential', 'timm.models.fastvit.RepMixerBlock', 'aten.add.Tensor']J pkg.torch.onnx.fx_noder%add_6 : [num_users=1] = call_function[target=torch.ops.aten.add.Tensor](args = (%conv2d_31, %mul_6), kwargs = {})J pkg.torch.onnx.name_scopes['', 'vision_model.vision', 'vision_model.vision._en', 'vision_model.vision._en.stages.2', 'vision_model.vision._en.stages.2.blocks', 'vision_model.vision._en.stages.2.blocks.2', 'add_6']J -pkg.torch.onnx.stack_traceFile "/home/batman/xx3/./ml_tools/openpilot_compile/compile_supercombo.py", line 86, in forward +pkg.torch.onnx.stack_traceFile "/home/batman/xx3/./ml_tools/openpilot_compile/compile_supercombo.py", line 82, in forward return torch.cat([*self.forward_dict(inputs).values(), self.pad], dim=1) File "/home/batman/xx3/xx/training/path/supercombo.py", line 185, in forward return self._en(x).flatten(1) @@ -1653,7 +1653,7 @@ Gvision_model.vision._en.stages.2.blocks.3.token_mixer.reparam_conv.bias conv2d pkg.torch.onnx.class_hierarchy['__main__.FlattenedVisionModel', 'xx.training.path.supercombo.Vision', 'timm.models.fastvit.FastVit', 'timm.models.fastvit.FastVitStage', 'torch.nn.modules.container.Sequential', 'timm.models.fastvit.RepMixerBlock', 'timm.models.fastvit.RepMixer', 'torch.nn.modules.conv.Conv2d', 'aten.conv2d.default']J pkg.torch.onnx.fx_node%conv2d_35 : [num_users=2] = call_function[target=torch.ops.aten.conv2d.default](args = (%add_6, %p_vision_model_vision__en_stages_2_blocks_3_token_mixer_reparam_conv_weight, %p_vision_model_vision__en_stages_2_blocks_3_token_mixer_reparam_conv_bias, [1, 1], [1, 1], [1, 1], 256), kwargs = {})J pkg.torch.onnx.name_scopes['', 'vision_model.vision', 'vision_model.vision._en', 'vision_model.vision._en.stages.2', 'vision_model.vision._en.stages.2.blocks', 'vision_model.vision._en.stages.2.blocks.3', 'vision_model.vision._en.stages.2.blocks.3.token_mixer', 'vision_model.vision._en.stages.2.blocks.3.token_mixer.reparam_conv', 'conv2d_35']J -pkg.torch.onnx.stack_traceFile "/home/batman/xx3/./ml_tools/openpilot_compile/compile_supercombo.py", line 86, in forward +pkg.torch.onnx.stack_traceFile "/home/batman/xx3/./ml_tools/openpilot_compile/compile_supercombo.py", line 82, in forward return torch.cat([*self.forward_dict(inputs).values(), self.pad], dim=1) File "/home/batman/xx3/xx/training/path/supercombo.py", line 185, in forward return self._en(x).flatten(1) @@ -1684,7 +1684,7 @@ getitem_21 node_Conv_196"Conv* pkg.torch.onnx.class_hierarchy['__main__.FlattenedVisionModel', 'xx.training.path.supercombo.Vision', 'timm.models.fastvit.FastVit', 'timm.models.fastvit.FastVitStage', 'torch.nn.modules.container.Sequential', 'timm.models.fastvit.RepMixerBlock', 'timm.models.fastvit.ConvMlp', 'timm.layers.conv_bn_act.ConvNormAct', 'timm.layers.norm_act.BatchNormAct2d', 'aten._native_batch_norm_legit_no_training.default']J pkg.torch.onnx.fx_node%_native_batch_norm_legit_no_training_7 : [num_users=1] = call_function[target=torch.ops.aten._native_batch_norm_legit_no_training.default](args = (%conv2d_36, %p_vision_model_vision__en_stages_2_blocks_3_mlp_conv_bn_weight, %p_vision_model_vision__en_stages_2_blocks_3_mlp_conv_bn_bias, %b_vision_model_vision__en_stages_2_blocks_3_mlp_conv_bn_running_mean, %b_vision_model_vision__en_stages_2_blocks_3_mlp_conv_bn_running_var, 0.1, 1e-05), kwargs = {})J pkg.torch.onnx.name_scopes['', 'vision_model.vision', 'vision_model.vision._en', 'vision_model.vision._en.stages.2', 'vision_model.vision._en.stages.2.blocks', 'vision_model.vision._en.stages.2.blocks.3', 'vision_model.vision._en.stages.2.blocks.3.mlp', 'vision_model.vision._en.stages.2.blocks.3.mlp.conv', 'vision_model.vision._en.stages.2.blocks.3.mlp.conv.bn', '_native_batch_norm_legit_no_training_7']J -pkg.torch.onnx.stack_trace File "/home/batman/xx3/./ml_tools/openpilot_compile/compile_supercombo.py", line 86, in forward +pkg.torch.onnx.stack_trace File "/home/batman/xx3/./ml_tools/openpilot_compile/compile_supercombo.py", line 82, in forward return torch.cat([*self.forward_dict(inputs).values(), self.pad], dim=1) File "/home/batman/xx3/xx/training/path/supercombo.py", line 185, in forward return self._en(x).flatten(1) @@ -1716,7 +1716,7 @@ getitem_21 pkg.torch.onnx.class_hierarchy['__main__.FlattenedVisionModel', 'xx.training.path.supercombo.Vision', 'timm.models.fastvit.FastVit', 'timm.models.fastvit.FastVitStage', 'torch.nn.modules.container.Sequential', 'timm.models.fastvit.RepMixerBlock', 'timm.models.fastvit.ConvMlp', 'torch.nn.modules.conv.Conv2d', 'aten.conv2d.default']J pkg.torch.onnx.fx_node%conv2d_37 : [num_users=1] = call_function[target=torch.ops.aten.conv2d.default](args = (%getitem_21, %p_vision_model_vision__en_stages_2_blocks_3_mlp_fc1_weight, %p_vision_model_vision__en_stages_2_blocks_3_mlp_fc1_bias), kwargs = {})J pkg.torch.onnx.name_scopes['', 'vision_model.vision', 'vision_model.vision._en', 'vision_model.vision._en.stages.2', 'vision_model.vision._en.stages.2.blocks', 'vision_model.vision._en.stages.2.blocks.3', 'vision_model.vision._en.stages.2.blocks.3.mlp', 'vision_model.vision._en.stages.2.blocks.3.mlp.fc1', 'conv2d_37']J -pkg.torch.onnx.stack_trace File "/home/batman/xx3/./ml_tools/openpilot_compile/compile_supercombo.py", line 86, in forward +pkg.torch.onnx.stack_trace File "/home/batman/xx3/./ml_tools/openpilot_compile/compile_supercombo.py", line 82, in forward return torch.cat([*self.forward_dict(inputs).values(), self.pad], dim=1) File "/home/batman/xx3/xx/training/path/supercombo.py", line 185, in forward return self._en(x).flatten(1) @@ -1739,7 +1739,7 @@ getitem_21 pkg.torch.onnx.class_hierarchy['__main__.FlattenedVisionModel', 'xx.training.path.supercombo.Vision', 'timm.models.fastvit.FastVit', 'timm.models.fastvit.FastVitStage', 'torch.nn.modules.container.Sequential', 'timm.models.fastvit.RepMixerBlock', 'timm.models.fastvit.ConvMlp', 'timm.layers.activations.GELUTanh', 'aten.gelu.default']J pkg.torch.onnx.fx_node%gelu_12 : [num_users=1] = call_function[target=torch.ops.aten.gelu.default](args = (%conv2d_37,), kwargs = {approximate: tanh})J pkg.torch.onnx.name_scopes['', 'vision_model.vision', 'vision_model.vision._en', 'vision_model.vision._en.stages.2', 'vision_model.vision._en.stages.2.blocks', 'vision_model.vision._en.stages.2.blocks.3', 'vision_model.vision._en.stages.2.blocks.3.mlp', 'vision_model.vision._en.stages.2.blocks.3.mlp.act', 'gelu_12']J -pkg.torch.onnx.stack_traceFile "/home/batman/xx3/./ml_tools/openpilot_compile/compile_supercombo.py", line 86, in forward +pkg.torch.onnx.stack_traceFile "/home/batman/xx3/./ml_tools/openpilot_compile/compile_supercombo.py", line 82, in forward return torch.cat([*self.forward_dict(inputs).values(), self.pad], dim=1) File "/home/batman/xx3/xx/training/path/supercombo.py", line 185, in forward return self._en(x).flatten(1) @@ -1768,7 +1768,7 @@ getitem_21 pkg.torch.onnx.class_hierarchy['__main__.FlattenedVisionModel', 'xx.training.path.supercombo.Vision', 'timm.models.fastvit.FastVit', 'timm.models.fastvit.FastVitStage', 'torch.nn.modules.container.Sequential', 'timm.models.fastvit.RepMixerBlock', 'timm.models.fastvit.ConvMlp', 'torch.nn.modules.conv.Conv2d', 'aten.conv2d.default']J pkg.torch.onnx.fx_node%conv2d_38 : [num_users=1] = call_function[target=torch.ops.aten.conv2d.default](args = (%clone_14, %p_vision_model_vision__en_stages_2_blocks_3_mlp_fc2_weight, %p_vision_model_vision__en_stages_2_blocks_3_mlp_fc2_bias), kwargs = {})J pkg.torch.onnx.name_scopes['', 'vision_model.vision', 'vision_model.vision._en', 'vision_model.vision._en.stages.2', 'vision_model.vision._en.stages.2.blocks', 'vision_model.vision._en.stages.2.blocks.3', 'vision_model.vision._en.stages.2.blocks.3.mlp', 'vision_model.vision._en.stages.2.blocks.3.mlp.fc2', 'conv2d_38']J -pkg.torch.onnx.stack_trace File "/home/batman/xx3/./ml_tools/openpilot_compile/compile_supercombo.py", line 86, in forward +pkg.torch.onnx.stack_trace File "/home/batman/xx3/./ml_tools/openpilot_compile/compile_supercombo.py", line 82, in forward return torch.cat([*self.forward_dict(inputs).values(), self.pad], dim=1) File "/home/batman/xx3/xx/training/path/supercombo.py", line 185, in forward return self._en(x).flatten(1) @@ -1792,7 +1792,7 @@ node_mul_7"MulJ pkg.torch.onnx.class_hierarchy['__main__.FlattenedVisionModel', 'xx.training.path.supercombo.Vision', 'timm.models.fastvit.FastVit', 'timm.models.fastvit.FastVitStage', 'torch.nn.modules.container.Sequential', 'timm.models.fastvit.RepMixerBlock', 'timm.models.fastvit.LayerScale2d', 'aten.mul.Tensor']J pkg.torch.onnx.fx_node%mul_7 : [num_users=1] = call_function[target=torch.ops.aten.mul.Tensor](args = (%clone_15, %p_vision_model_vision__en_stages_2_blocks_3_layer_scale_gamma), kwargs = {})J pkg.torch.onnx.name_scopes['', 'vision_model.vision', 'vision_model.vision._en', 'vision_model.vision._en.stages.2', 'vision_model.vision._en.stages.2.blocks', 'vision_model.vision._en.stages.2.blocks.3', 'vision_model.vision._en.stages.2.blocks.3.layer_scale', 'mul_7']J -pkg.torch.onnx.stack_traceFile "/home/batman/xx3/./ml_tools/openpilot_compile/compile_supercombo.py", line 86, in forward +pkg.torch.onnx.stack_traceFile "/home/batman/xx3/./ml_tools/openpilot_compile/compile_supercombo.py", line 82, in forward return torch.cat([*self.forward_dict(inputs).values(), self.pad], dim=1) File "/home/batman/xx3/xx/training/path/supercombo.py", line 185, in forward return self._en(x).flatten(1) @@ -1814,7 +1814,7 @@ node_add_7"AddJ pkg.torch.onnx.class_hierarchy['__main__.FlattenedVisionModel', 'xx.training.path.supercombo.Vision', 'timm.models.fastvit.FastVit', 'timm.models.fastvit.FastVitStage', 'torch.nn.modules.container.Sequential', 'timm.models.fastvit.RepMixerBlock', 'aten.add.Tensor']J pkg.torch.onnx.fx_noder%add_7 : [num_users=1] = call_function[target=torch.ops.aten.add.Tensor](args = (%conv2d_35, %mul_7), kwargs = {})J pkg.torch.onnx.name_scopes['', 'vision_model.vision', 'vision_model.vision._en', 'vision_model.vision._en.stages.2', 'vision_model.vision._en.stages.2.blocks', 'vision_model.vision._en.stages.2.blocks.3', 'add_7']J -pkg.torch.onnx.stack_traceFile "/home/batman/xx3/./ml_tools/openpilot_compile/compile_supercombo.py", line 86, in forward +pkg.torch.onnx.stack_traceFile "/home/batman/xx3/./ml_tools/openpilot_compile/compile_supercombo.py", line 82, in forward return torch.cat([*self.forward_dict(inputs).values(), self.pad], dim=1) File "/home/batman/xx3/xx/training/path/supercombo.py", line 185, in forward return self._en(x).flatten(1) @@ -1839,7 +1839,7 @@ Gvision_model.vision._en.stages.2.blocks.4.token_mixer.reparam_conv.bias conv2d pkg.torch.onnx.class_hierarchy['__main__.FlattenedVisionModel', 'xx.training.path.supercombo.Vision', 'timm.models.fastvit.FastVit', 'timm.models.fastvit.FastVitStage', 'torch.nn.modules.container.Sequential', 'timm.models.fastvit.RepMixerBlock', 'timm.models.fastvit.RepMixer', 'torch.nn.modules.conv.Conv2d', 'aten.conv2d.default']J pkg.torch.onnx.fx_node%conv2d_39 : [num_users=2] = call_function[target=torch.ops.aten.conv2d.default](args = (%add_7, %p_vision_model_vision__en_stages_2_blocks_4_token_mixer_reparam_conv_weight, %p_vision_model_vision__en_stages_2_blocks_4_token_mixer_reparam_conv_bias, [1, 1], [1, 1], [1, 1], 256), kwargs = {})J pkg.torch.onnx.name_scopes['', 'vision_model.vision', 'vision_model.vision._en', 'vision_model.vision._en.stages.2', 'vision_model.vision._en.stages.2.blocks', 'vision_model.vision._en.stages.2.blocks.4', 'vision_model.vision._en.stages.2.blocks.4.token_mixer', 'vision_model.vision._en.stages.2.blocks.4.token_mixer.reparam_conv', 'conv2d_39']J -pkg.torch.onnx.stack_traceFile "/home/batman/xx3/./ml_tools/openpilot_compile/compile_supercombo.py", line 86, in forward +pkg.torch.onnx.stack_traceFile "/home/batman/xx3/./ml_tools/openpilot_compile/compile_supercombo.py", line 82, in forward return torch.cat([*self.forward_dict(inputs).values(), self.pad], dim=1) File "/home/batman/xx3/xx/training/path/supercombo.py", line 185, in forward return self._en(x).flatten(1) @@ -1870,7 +1870,7 @@ getitem_24 node_Conv_198"Conv* pkg.torch.onnx.class_hierarchy['__main__.FlattenedVisionModel', 'xx.training.path.supercombo.Vision', 'timm.models.fastvit.FastVit', 'timm.models.fastvit.FastVitStage', 'torch.nn.modules.container.Sequential', 'timm.models.fastvit.RepMixerBlock', 'timm.models.fastvit.ConvMlp', 'timm.layers.conv_bn_act.ConvNormAct', 'timm.layers.norm_act.BatchNormAct2d', 'aten._native_batch_norm_legit_no_training.default']J pkg.torch.onnx.fx_node%_native_batch_norm_legit_no_training_8 : [num_users=1] = call_function[target=torch.ops.aten._native_batch_norm_legit_no_training.default](args = (%conv2d_40, %p_vision_model_vision__en_stages_2_blocks_4_mlp_conv_bn_weight, %p_vision_model_vision__en_stages_2_blocks_4_mlp_conv_bn_bias, %b_vision_model_vision__en_stages_2_blocks_4_mlp_conv_bn_running_mean, %b_vision_model_vision__en_stages_2_blocks_4_mlp_conv_bn_running_var, 0.1, 1e-05), kwargs = {})J pkg.torch.onnx.name_scopes['', 'vision_model.vision', 'vision_model.vision._en', 'vision_model.vision._en.stages.2', 'vision_model.vision._en.stages.2.blocks', 'vision_model.vision._en.stages.2.blocks.4', 'vision_model.vision._en.stages.2.blocks.4.mlp', 'vision_model.vision._en.stages.2.blocks.4.mlp.conv', 'vision_model.vision._en.stages.2.blocks.4.mlp.conv.bn', '_native_batch_norm_legit_no_training_8']J -pkg.torch.onnx.stack_trace File "/home/batman/xx3/./ml_tools/openpilot_compile/compile_supercombo.py", line 86, in forward +pkg.torch.onnx.stack_trace File "/home/batman/xx3/./ml_tools/openpilot_compile/compile_supercombo.py", line 82, in forward return torch.cat([*self.forward_dict(inputs).values(), self.pad], dim=1) File "/home/batman/xx3/xx/training/path/supercombo.py", line 185, in forward return self._en(x).flatten(1) @@ -1902,7 +1902,7 @@ getitem_24 pkg.torch.onnx.class_hierarchy['__main__.FlattenedVisionModel', 'xx.training.path.supercombo.Vision', 'timm.models.fastvit.FastVit', 'timm.models.fastvit.FastVitStage', 'torch.nn.modules.container.Sequential', 'timm.models.fastvit.RepMixerBlock', 'timm.models.fastvit.ConvMlp', 'torch.nn.modules.conv.Conv2d', 'aten.conv2d.default']J pkg.torch.onnx.fx_node%conv2d_41 : [num_users=1] = call_function[target=torch.ops.aten.conv2d.default](args = (%getitem_24, %p_vision_model_vision__en_stages_2_blocks_4_mlp_fc1_weight, %p_vision_model_vision__en_stages_2_blocks_4_mlp_fc1_bias), kwargs = {})J pkg.torch.onnx.name_scopes['', 'vision_model.vision', 'vision_model.vision._en', 'vision_model.vision._en.stages.2', 'vision_model.vision._en.stages.2.blocks', 'vision_model.vision._en.stages.2.blocks.4', 'vision_model.vision._en.stages.2.blocks.4.mlp', 'vision_model.vision._en.stages.2.blocks.4.mlp.fc1', 'conv2d_41']J -pkg.torch.onnx.stack_trace File "/home/batman/xx3/./ml_tools/openpilot_compile/compile_supercombo.py", line 86, in forward +pkg.torch.onnx.stack_trace File "/home/batman/xx3/./ml_tools/openpilot_compile/compile_supercombo.py", line 82, in forward return torch.cat([*self.forward_dict(inputs).values(), self.pad], dim=1) File "/home/batman/xx3/xx/training/path/supercombo.py", line 185, in forward return self._en(x).flatten(1) @@ -1925,7 +1925,7 @@ getitem_24 pkg.torch.onnx.class_hierarchy['__main__.FlattenedVisionModel', 'xx.training.path.supercombo.Vision', 'timm.models.fastvit.FastVit', 'timm.models.fastvit.FastVitStage', 'torch.nn.modules.container.Sequential', 'timm.models.fastvit.RepMixerBlock', 'timm.models.fastvit.ConvMlp', 'timm.layers.activations.GELUTanh', 'aten.gelu.default']J pkg.torch.onnx.fx_node%gelu_13 : [num_users=1] = call_function[target=torch.ops.aten.gelu.default](args = (%conv2d_41,), kwargs = {approximate: tanh})J pkg.torch.onnx.name_scopes['', 'vision_model.vision', 'vision_model.vision._en', 'vision_model.vision._en.stages.2', 'vision_model.vision._en.stages.2.blocks', 'vision_model.vision._en.stages.2.blocks.4', 'vision_model.vision._en.stages.2.blocks.4.mlp', 'vision_model.vision._en.stages.2.blocks.4.mlp.act', 'gelu_13']J -pkg.torch.onnx.stack_traceFile "/home/batman/xx3/./ml_tools/openpilot_compile/compile_supercombo.py", line 86, in forward +pkg.torch.onnx.stack_traceFile "/home/batman/xx3/./ml_tools/openpilot_compile/compile_supercombo.py", line 82, in forward return torch.cat([*self.forward_dict(inputs).values(), self.pad], dim=1) File "/home/batman/xx3/xx/training/path/supercombo.py", line 185, in forward return self._en(x).flatten(1) @@ -1954,7 +1954,7 @@ getitem_24 pkg.torch.onnx.class_hierarchy['__main__.FlattenedVisionModel', 'xx.training.path.supercombo.Vision', 'timm.models.fastvit.FastVit', 'timm.models.fastvit.FastVitStage', 'torch.nn.modules.container.Sequential', 'timm.models.fastvit.RepMixerBlock', 'timm.models.fastvit.ConvMlp', 'torch.nn.modules.conv.Conv2d', 'aten.conv2d.default']J pkg.torch.onnx.fx_node%conv2d_42 : [num_users=1] = call_function[target=torch.ops.aten.conv2d.default](args = (%clone_16, %p_vision_model_vision__en_stages_2_blocks_4_mlp_fc2_weight, %p_vision_model_vision__en_stages_2_blocks_4_mlp_fc2_bias), kwargs = {})J pkg.torch.onnx.name_scopes['', 'vision_model.vision', 'vision_model.vision._en', 'vision_model.vision._en.stages.2', 'vision_model.vision._en.stages.2.blocks', 'vision_model.vision._en.stages.2.blocks.4', 'vision_model.vision._en.stages.2.blocks.4.mlp', 'vision_model.vision._en.stages.2.blocks.4.mlp.fc2', 'conv2d_42']J -pkg.torch.onnx.stack_trace File "/home/batman/xx3/./ml_tools/openpilot_compile/compile_supercombo.py", line 86, in forward +pkg.torch.onnx.stack_trace File "/home/batman/xx3/./ml_tools/openpilot_compile/compile_supercombo.py", line 82, in forward return torch.cat([*self.forward_dict(inputs).values(), self.pad], dim=1) File "/home/batman/xx3/xx/training/path/supercombo.py", line 185, in forward return self._en(x).flatten(1) @@ -1978,7 +1978,7 @@ node_mul_8"MulJ pkg.torch.onnx.class_hierarchy['__main__.FlattenedVisionModel', 'xx.training.path.supercombo.Vision', 'timm.models.fastvit.FastVit', 'timm.models.fastvit.FastVitStage', 'torch.nn.modules.container.Sequential', 'timm.models.fastvit.RepMixerBlock', 'timm.models.fastvit.LayerScale2d', 'aten.mul.Tensor']J pkg.torch.onnx.fx_node%mul_8 : [num_users=1] = call_function[target=torch.ops.aten.mul.Tensor](args = (%clone_17, %p_vision_model_vision__en_stages_2_blocks_4_layer_scale_gamma), kwargs = {})J pkg.torch.onnx.name_scopes['', 'vision_model.vision', 'vision_model.vision._en', 'vision_model.vision._en.stages.2', 'vision_model.vision._en.stages.2.blocks', 'vision_model.vision._en.stages.2.blocks.4', 'vision_model.vision._en.stages.2.blocks.4.layer_scale', 'mul_8']J -pkg.torch.onnx.stack_traceFile "/home/batman/xx3/./ml_tools/openpilot_compile/compile_supercombo.py", line 86, in forward +pkg.torch.onnx.stack_traceFile "/home/batman/xx3/./ml_tools/openpilot_compile/compile_supercombo.py", line 82, in forward return torch.cat([*self.forward_dict(inputs).values(), self.pad], dim=1) File "/home/batman/xx3/xx/training/path/supercombo.py", line 185, in forward return self._en(x).flatten(1) @@ -2000,7 +2000,7 @@ node_add_8"AddJ pkg.torch.onnx.class_hierarchy['__main__.FlattenedVisionModel', 'xx.training.path.supercombo.Vision', 'timm.models.fastvit.FastVit', 'timm.models.fastvit.FastVitStage', 'torch.nn.modules.container.Sequential', 'timm.models.fastvit.RepMixerBlock', 'aten.add.Tensor']J pkg.torch.onnx.fx_noder%add_8 : [num_users=1] = call_function[target=torch.ops.aten.add.Tensor](args = (%conv2d_39, %mul_8), kwargs = {})J pkg.torch.onnx.name_scopes['', 'vision_model.vision', 'vision_model.vision._en', 'vision_model.vision._en.stages.2', 'vision_model.vision._en.stages.2.blocks', 'vision_model.vision._en.stages.2.blocks.4', 'add_8']J -pkg.torch.onnx.stack_traceFile "/home/batman/xx3/./ml_tools/openpilot_compile/compile_supercombo.py", line 86, in forward +pkg.torch.onnx.stack_traceFile "/home/batman/xx3/./ml_tools/openpilot_compile/compile_supercombo.py", line 82, in forward return torch.cat([*self.forward_dict(inputs).values(), self.pad], dim=1) File "/home/batman/xx3/xx/training/path/supercombo.py", line 185, in forward return self._en(x).flatten(1) @@ -2025,7 +2025,7 @@ Gvision_model.vision._en.stages.2.blocks.5.token_mixer.reparam_conv.bias conv2d pkg.torch.onnx.class_hierarchy['__main__.FlattenedVisionModel', 'xx.training.path.supercombo.Vision', 'timm.models.fastvit.FastVit', 'timm.models.fastvit.FastVitStage', 'torch.nn.modules.container.Sequential', 'timm.models.fastvit.RepMixerBlock', 'timm.models.fastvit.RepMixer', 'torch.nn.modules.conv.Conv2d', 'aten.conv2d.default']J pkg.torch.onnx.fx_node%conv2d_43 : [num_users=2] = call_function[target=torch.ops.aten.conv2d.default](args = (%add_8, %p_vision_model_vision__en_stages_2_blocks_5_token_mixer_reparam_conv_weight, %p_vision_model_vision__en_stages_2_blocks_5_token_mixer_reparam_conv_bias, [1, 1], [1, 1], [1, 1], 256), kwargs = {})J pkg.torch.onnx.name_scopes['', 'vision_model.vision', 'vision_model.vision._en', 'vision_model.vision._en.stages.2', 'vision_model.vision._en.stages.2.blocks', 'vision_model.vision._en.stages.2.blocks.5', 'vision_model.vision._en.stages.2.blocks.5.token_mixer', 'vision_model.vision._en.stages.2.blocks.5.token_mixer.reparam_conv', 'conv2d_43']J -pkg.torch.onnx.stack_traceFile "/home/batman/xx3/./ml_tools/openpilot_compile/compile_supercombo.py", line 86, in forward +pkg.torch.onnx.stack_traceFile "/home/batman/xx3/./ml_tools/openpilot_compile/compile_supercombo.py", line 82, in forward return torch.cat([*self.forward_dict(inputs).values(), self.pad], dim=1) File "/home/batman/xx3/xx/training/path/supercombo.py", line 185, in forward return self._en(x).flatten(1) @@ -2056,7 +2056,7 @@ getitem_27 node_Conv_200"Conv* pkg.torch.onnx.class_hierarchy['__main__.FlattenedVisionModel', 'xx.training.path.supercombo.Vision', 'timm.models.fastvit.FastVit', 'timm.models.fastvit.FastVitStage', 'torch.nn.modules.container.Sequential', 'timm.models.fastvit.RepMixerBlock', 'timm.models.fastvit.ConvMlp', 'timm.layers.conv_bn_act.ConvNormAct', 'timm.layers.norm_act.BatchNormAct2d', 'aten._native_batch_norm_legit_no_training.default']J pkg.torch.onnx.fx_node%_native_batch_norm_legit_no_training_9 : [num_users=1] = call_function[target=torch.ops.aten._native_batch_norm_legit_no_training.default](args = (%conv2d_44, %p_vision_model_vision__en_stages_2_blocks_5_mlp_conv_bn_weight, %p_vision_model_vision__en_stages_2_blocks_5_mlp_conv_bn_bias, %b_vision_model_vision__en_stages_2_blocks_5_mlp_conv_bn_running_mean, %b_vision_model_vision__en_stages_2_blocks_5_mlp_conv_bn_running_var, 0.1, 1e-05), kwargs = {})J pkg.torch.onnx.name_scopes['', 'vision_model.vision', 'vision_model.vision._en', 'vision_model.vision._en.stages.2', 'vision_model.vision._en.stages.2.blocks', 'vision_model.vision._en.stages.2.blocks.5', 'vision_model.vision._en.stages.2.blocks.5.mlp', 'vision_model.vision._en.stages.2.blocks.5.mlp.conv', 'vision_model.vision._en.stages.2.blocks.5.mlp.conv.bn', '_native_batch_norm_legit_no_training_9']J -pkg.torch.onnx.stack_trace File "/home/batman/xx3/./ml_tools/openpilot_compile/compile_supercombo.py", line 86, in forward +pkg.torch.onnx.stack_trace File "/home/batman/xx3/./ml_tools/openpilot_compile/compile_supercombo.py", line 82, in forward return torch.cat([*self.forward_dict(inputs).values(), self.pad], dim=1) File "/home/batman/xx3/xx/training/path/supercombo.py", line 185, in forward return self._en(x).flatten(1) @@ -2088,7 +2088,7 @@ getitem_27 pkg.torch.onnx.class_hierarchy['__main__.FlattenedVisionModel', 'xx.training.path.supercombo.Vision', 'timm.models.fastvit.FastVit', 'timm.models.fastvit.FastVitStage', 'torch.nn.modules.container.Sequential', 'timm.models.fastvit.RepMixerBlock', 'timm.models.fastvit.ConvMlp', 'torch.nn.modules.conv.Conv2d', 'aten.conv2d.default']J pkg.torch.onnx.fx_node%conv2d_45 : [num_users=1] = call_function[target=torch.ops.aten.conv2d.default](args = (%getitem_27, %p_vision_model_vision__en_stages_2_blocks_5_mlp_fc1_weight, %p_vision_model_vision__en_stages_2_blocks_5_mlp_fc1_bias), kwargs = {})J pkg.torch.onnx.name_scopes['', 'vision_model.vision', 'vision_model.vision._en', 'vision_model.vision._en.stages.2', 'vision_model.vision._en.stages.2.blocks', 'vision_model.vision._en.stages.2.blocks.5', 'vision_model.vision._en.stages.2.blocks.5.mlp', 'vision_model.vision._en.stages.2.blocks.5.mlp.fc1', 'conv2d_45']J -pkg.torch.onnx.stack_trace File "/home/batman/xx3/./ml_tools/openpilot_compile/compile_supercombo.py", line 86, in forward +pkg.torch.onnx.stack_trace File "/home/batman/xx3/./ml_tools/openpilot_compile/compile_supercombo.py", line 82, in forward return torch.cat([*self.forward_dict(inputs).values(), self.pad], dim=1) File "/home/batman/xx3/xx/training/path/supercombo.py", line 185, in forward return self._en(x).flatten(1) @@ -2111,7 +2111,7 @@ getitem_27 pkg.torch.onnx.class_hierarchy['__main__.FlattenedVisionModel', 'xx.training.path.supercombo.Vision', 'timm.models.fastvit.FastVit', 'timm.models.fastvit.FastVitStage', 'torch.nn.modules.container.Sequential', 'timm.models.fastvit.RepMixerBlock', 'timm.models.fastvit.ConvMlp', 'timm.layers.activations.GELUTanh', 'aten.gelu.default']J pkg.torch.onnx.fx_node%gelu_14 : [num_users=1] = call_function[target=torch.ops.aten.gelu.default](args = (%conv2d_45,), kwargs = {approximate: tanh})J pkg.torch.onnx.name_scopes['', 'vision_model.vision', 'vision_model.vision._en', 'vision_model.vision._en.stages.2', 'vision_model.vision._en.stages.2.blocks', 'vision_model.vision._en.stages.2.blocks.5', 'vision_model.vision._en.stages.2.blocks.5.mlp', 'vision_model.vision._en.stages.2.blocks.5.mlp.act', 'gelu_14']J -pkg.torch.onnx.stack_traceFile "/home/batman/xx3/./ml_tools/openpilot_compile/compile_supercombo.py", line 86, in forward +pkg.torch.onnx.stack_traceFile "/home/batman/xx3/./ml_tools/openpilot_compile/compile_supercombo.py", line 82, in forward return torch.cat([*self.forward_dict(inputs).values(), self.pad], dim=1) File "/home/batman/xx3/xx/training/path/supercombo.py", line 185, in forward return self._en(x).flatten(1) @@ -2140,7 +2140,7 @@ getitem_27 pkg.torch.onnx.class_hierarchy['__main__.FlattenedVisionModel', 'xx.training.path.supercombo.Vision', 'timm.models.fastvit.FastVit', 'timm.models.fastvit.FastVitStage', 'torch.nn.modules.container.Sequential', 'timm.models.fastvit.RepMixerBlock', 'timm.models.fastvit.ConvMlp', 'torch.nn.modules.conv.Conv2d', 'aten.conv2d.default']J pkg.torch.onnx.fx_node%conv2d_46 : [num_users=1] = call_function[target=torch.ops.aten.conv2d.default](args = (%clone_18, %p_vision_model_vision__en_stages_2_blocks_5_mlp_fc2_weight, %p_vision_model_vision__en_stages_2_blocks_5_mlp_fc2_bias), kwargs = {})J pkg.torch.onnx.name_scopes['', 'vision_model.vision', 'vision_model.vision._en', 'vision_model.vision._en.stages.2', 'vision_model.vision._en.stages.2.blocks', 'vision_model.vision._en.stages.2.blocks.5', 'vision_model.vision._en.stages.2.blocks.5.mlp', 'vision_model.vision._en.stages.2.blocks.5.mlp.fc2', 'conv2d_46']J -pkg.torch.onnx.stack_trace File "/home/batman/xx3/./ml_tools/openpilot_compile/compile_supercombo.py", line 86, in forward +pkg.torch.onnx.stack_trace File "/home/batman/xx3/./ml_tools/openpilot_compile/compile_supercombo.py", line 82, in forward return torch.cat([*self.forward_dict(inputs).values(), self.pad], dim=1) File "/home/batman/xx3/xx/training/path/supercombo.py", line 185, in forward return self._en(x).flatten(1) @@ -2164,7 +2164,7 @@ node_mul_9"MulJ pkg.torch.onnx.class_hierarchy['__main__.FlattenedVisionModel', 'xx.training.path.supercombo.Vision', 'timm.models.fastvit.FastVit', 'timm.models.fastvit.FastVitStage', 'torch.nn.modules.container.Sequential', 'timm.models.fastvit.RepMixerBlock', 'timm.models.fastvit.LayerScale2d', 'aten.mul.Tensor']J pkg.torch.onnx.fx_node%mul_9 : [num_users=1] = call_function[target=torch.ops.aten.mul.Tensor](args = (%clone_19, %p_vision_model_vision__en_stages_2_blocks_5_layer_scale_gamma), kwargs = {})J pkg.torch.onnx.name_scopes['', 'vision_model.vision', 'vision_model.vision._en', 'vision_model.vision._en.stages.2', 'vision_model.vision._en.stages.2.blocks', 'vision_model.vision._en.stages.2.blocks.5', 'vision_model.vision._en.stages.2.blocks.5.layer_scale', 'mul_9']J -pkg.torch.onnx.stack_traceFile "/home/batman/xx3/./ml_tools/openpilot_compile/compile_supercombo.py", line 86, in forward +pkg.torch.onnx.stack_traceFile "/home/batman/xx3/./ml_tools/openpilot_compile/compile_supercombo.py", line 82, in forward return torch.cat([*self.forward_dict(inputs).values(), self.pad], dim=1) File "/home/batman/xx3/xx/training/path/supercombo.py", line 185, in forward return self._en(x).flatten(1) @@ -2186,7 +2186,7 @@ node_add_9"AddJ pkg.torch.onnx.class_hierarchy['__main__.FlattenedVisionModel', 'xx.training.path.supercombo.Vision', 'timm.models.fastvit.FastVit', 'timm.models.fastvit.FastVitStage', 'torch.nn.modules.container.Sequential', 'timm.models.fastvit.RepMixerBlock', 'aten.add.Tensor']J pkg.torch.onnx.fx_noder%add_9 : [num_users=1] = call_function[target=torch.ops.aten.add.Tensor](args = (%conv2d_43, %mul_9), kwargs = {})J pkg.torch.onnx.name_scopes['', 'vision_model.vision', 'vision_model.vision._en', 'vision_model.vision._en.stages.2', 'vision_model.vision._en.stages.2.blocks', 'vision_model.vision._en.stages.2.blocks.5', 'add_9']J -pkg.torch.onnx.stack_traceFile "/home/batman/xx3/./ml_tools/openpilot_compile/compile_supercombo.py", line 86, in forward +pkg.torch.onnx.stack_traceFile "/home/batman/xx3/./ml_tools/openpilot_compile/compile_supercombo.py", line 82, in forward return torch.cat([*self.forward_dict(inputs).values(), self.pad], dim=1) File "/home/batman/xx3/xx/training/path/supercombo.py", line 185, in forward return self._en(x).flatten(1) @@ -2211,7 +2211,7 @@ Dvision_model.vision._en.stages.3.downsample.proj.0.reparam_conv.bias conv2d_47 pkg.torch.onnx.class_hierarchy['__main__.FlattenedVisionModel', 'xx.training.path.supercombo.Vision', 'timm.models.fastvit.FastVit', 'timm.models.fastvit.FastVitStage', 'timm.models.fastvit.PatchEmbed', 'torch.nn.modules.container.Sequential', 'timm.models.fastvit.ReparamLargeKernelConv', 'torch.nn.modules.conv.Conv2d', 'aten.conv2d.default']J pkg.torch.onnx.fx_node%conv2d_47 : [num_users=1] = call_function[target=torch.ops.aten.conv2d.default](args = (%add_9, %p_vision_model_vision__en_stages_3_downsample_proj_0_reparam_conv_weight, %p_vision_model_vision__en_stages_3_downsample_proj_0_reparam_conv_bias, [2, 2], [3, 3], [1, 1], 256), kwargs = {})J pkg.torch.onnx.name_scopes['', 'vision_model.vision', 'vision_model.vision._en', 'vision_model.vision._en.stages.3', 'vision_model.vision._en.stages.3.downsample', 'vision_model.vision._en.stages.3.downsample.proj', 'vision_model.vision._en.stages.3.downsample.proj.0', 'vision_model.vision._en.stages.3.downsample.proj.0.reparam_conv', 'conv2d_47']J -pkg.torch.onnx.stack_traceFile "/home/batman/xx3/./ml_tools/openpilot_compile/compile_supercombo.py", line 86, in forward +pkg.torch.onnx.stack_traceFile "/home/batman/xx3/./ml_tools/openpilot_compile/compile_supercombo.py", line 82, in forward return torch.cat([*self.forward_dict(inputs).values(), self.pad], dim=1) File "/home/batman/xx3/xx/training/path/supercombo.py", line 185, in forward return self._en(x).flatten(1) @@ -2240,7 +2240,7 @@ Dvision_model.vision._en.stages.3.downsample.proj.1.reparam_conv.bias conv2d_48 pkg.torch.onnx.class_hierarchy['__main__.FlattenedVisionModel', 'xx.training.path.supercombo.Vision', 'timm.models.fastvit.FastVit', 'timm.models.fastvit.FastVitStage', 'timm.models.fastvit.PatchEmbed', 'torch.nn.modules.container.Sequential', 'timm.models.fastvit.MobileOneBlock', 'torch.nn.modules.conv.Conv2d', 'aten.conv2d.default']J pkg.torch.onnx.fx_node%conv2d_48 : [num_users=1] = call_function[target=torch.ops.aten.conv2d.default](args = (%conv2d_47, %p_vision_model_vision__en_stages_3_downsample_proj_1_reparam_conv_weight, %p_vision_model_vision__en_stages_3_downsample_proj_1_reparam_conv_bias), kwargs = {})J pkg.torch.onnx.name_scopes['', 'vision_model.vision', 'vision_model.vision._en', 'vision_model.vision._en.stages.3', 'vision_model.vision._en.stages.3.downsample', 'vision_model.vision._en.stages.3.downsample.proj', 'vision_model.vision._en.stages.3.downsample.proj.1', 'vision_model.vision._en.stages.3.downsample.proj.1.reparam_conv', 'conv2d_48']J -pkg.torch.onnx.stack_traceFile "/home/batman/xx3/./ml_tools/openpilot_compile/compile_supercombo.py", line 86, in forward +pkg.torch.onnx.stack_traceFile "/home/batman/xx3/./ml_tools/openpilot_compile/compile_supercombo.py", line 82, in forward return torch.cat([*self.forward_dict(inputs).values(), self.pad], dim=1) File "/home/batman/xx3/xx/training/path/supercombo.py", line 185, in forward return self._en(x).flatten(1) @@ -2263,7 +2263,7 @@ Dvision_model.vision._en.stages.3.downsample.proj.1.reparam_conv.bias conv2d_48 pkg.torch.onnx.class_hierarchy['__main__.FlattenedVisionModel', 'xx.training.path.supercombo.Vision', 'timm.models.fastvit.FastVit', 'timm.models.fastvit.FastVitStage', 'timm.models.fastvit.PatchEmbed', 'torch.nn.modules.container.Sequential', 'timm.models.fastvit.MobileOneBlock', 'timm.layers.activations.GELUTanh', 'aten.gelu.default']J pkg.torch.onnx.fx_node%gelu_15 : [num_users=1] = call_function[target=torch.ops.aten.gelu.default](args = (%conv2d_48,), kwargs = {approximate: tanh})J pkg.torch.onnx.name_scopes['', 'vision_model.vision', 'vision_model.vision._en', 'vision_model.vision._en.stages.3', 'vision_model.vision._en.stages.3.downsample', 'vision_model.vision._en.stages.3.downsample.proj', 'vision_model.vision._en.stages.3.downsample.proj.1', 'vision_model.vision._en.stages.3.downsample.proj.1.act', 'gelu_15']J -pkg.torch.onnx.stack_traceFile "/home/batman/xx3/./ml_tools/openpilot_compile/compile_supercombo.py", line 86, in forward +pkg.torch.onnx.stack_traceFile "/home/batman/xx3/./ml_tools/openpilot_compile/compile_supercombo.py", line 82, in forward return torch.cat([*self.forward_dict(inputs).values(), self.pad], dim=1) File "/home/batman/xx3/xx/training/path/supercombo.py", line 185, in forward return self._en(x).flatten(1) @@ -2292,7 +2292,7 @@ Gvision_model.vision._en.stages.3.blocks.0.token_mixer.reparam_conv.bias conv2d pkg.torch.onnx.class_hierarchy['__main__.FlattenedVisionModel', 'xx.training.path.supercombo.Vision', 'timm.models.fastvit.FastVit', 'timm.models.fastvit.FastVitStage', 'torch.nn.modules.container.Sequential', 'timm.models.fastvit.RepMixerBlock', 'timm.models.fastvit.RepMixer', 'torch.nn.modules.conv.Conv2d', 'aten.conv2d.default']J pkg.torch.onnx.fx_node%conv2d_49 : [num_users=2] = call_function[target=torch.ops.aten.conv2d.default](args = (%gelu_15, %p_vision_model_vision__en_stages_3_blocks_0_token_mixer_reparam_conv_weight, %p_vision_model_vision__en_stages_3_blocks_0_token_mixer_reparam_conv_bias, [1, 1], [1, 1], [1, 1], 512), kwargs = {})J pkg.torch.onnx.name_scopes['', 'vision_model.vision', 'vision_model.vision._en', 'vision_model.vision._en.stages.3', 'vision_model.vision._en.stages.3.blocks', 'vision_model.vision._en.stages.3.blocks.0', 'vision_model.vision._en.stages.3.blocks.0.token_mixer', 'vision_model.vision._en.stages.3.blocks.0.token_mixer.reparam_conv', 'conv2d_49']J -pkg.torch.onnx.stack_traceFile "/home/batman/xx3/./ml_tools/openpilot_compile/compile_supercombo.py", line 86, in forward +pkg.torch.onnx.stack_traceFile "/home/batman/xx3/./ml_tools/openpilot_compile/compile_supercombo.py", line 82, in forward return torch.cat([*self.forward_dict(inputs).values(), self.pad], dim=1) File "/home/batman/xx3/xx/training/path/supercombo.py", line 185, in forward return self._en(x).flatten(1) @@ -2323,7 +2323,7 @@ getitem_30 node_Conv_202"Conv* pkg.torch.onnx.class_hierarchy['__main__.FlattenedVisionModel', 'xx.training.path.supercombo.Vision', 'timm.models.fastvit.FastVit', 'timm.models.fastvit.FastVitStage', 'torch.nn.modules.container.Sequential', 'timm.models.fastvit.RepMixerBlock', 'timm.models.fastvit.ConvMlp', 'timm.layers.conv_bn_act.ConvNormAct', 'timm.layers.norm_act.BatchNormAct2d', 'aten._native_batch_norm_legit_no_training.default']J pkg.torch.onnx.fx_node%_native_batch_norm_legit_no_training_10 : [num_users=1] = call_function[target=torch.ops.aten._native_batch_norm_legit_no_training.default](args = (%conv2d_50, %p_vision_model_vision__en_stages_3_blocks_0_mlp_conv_bn_weight, %p_vision_model_vision__en_stages_3_blocks_0_mlp_conv_bn_bias, %b_vision_model_vision__en_stages_3_blocks_0_mlp_conv_bn_running_mean, %b_vision_model_vision__en_stages_3_blocks_0_mlp_conv_bn_running_var, 0.1, 1e-05), kwargs = {})J pkg.torch.onnx.name_scopes['', 'vision_model.vision', 'vision_model.vision._en', 'vision_model.vision._en.stages.3', 'vision_model.vision._en.stages.3.blocks', 'vision_model.vision._en.stages.3.blocks.0', 'vision_model.vision._en.stages.3.blocks.0.mlp', 'vision_model.vision._en.stages.3.blocks.0.mlp.conv', 'vision_model.vision._en.stages.3.blocks.0.mlp.conv.bn', '_native_batch_norm_legit_no_training_10']J -pkg.torch.onnx.stack_trace File "/home/batman/xx3/./ml_tools/openpilot_compile/compile_supercombo.py", line 86, in forward +pkg.torch.onnx.stack_trace File "/home/batman/xx3/./ml_tools/openpilot_compile/compile_supercombo.py", line 82, in forward return torch.cat([*self.forward_dict(inputs).values(), self.pad], dim=1) File "/home/batman/xx3/xx/training/path/supercombo.py", line 185, in forward return self._en(x).flatten(1) @@ -2355,7 +2355,7 @@ getitem_30 pkg.torch.onnx.class_hierarchy['__main__.FlattenedVisionModel', 'xx.training.path.supercombo.Vision', 'timm.models.fastvit.FastVit', 'timm.models.fastvit.FastVitStage', 'torch.nn.modules.container.Sequential', 'timm.models.fastvit.RepMixerBlock', 'timm.models.fastvit.ConvMlp', 'torch.nn.modules.conv.Conv2d', 'aten.conv2d.default']J pkg.torch.onnx.fx_node%conv2d_51 : [num_users=1] = call_function[target=torch.ops.aten.conv2d.default](args = (%getitem_30, %p_vision_model_vision__en_stages_3_blocks_0_mlp_fc1_weight, %p_vision_model_vision__en_stages_3_blocks_0_mlp_fc1_bias), kwargs = {})J pkg.torch.onnx.name_scopes['', 'vision_model.vision', 'vision_model.vision._en', 'vision_model.vision._en.stages.3', 'vision_model.vision._en.stages.3.blocks', 'vision_model.vision._en.stages.3.blocks.0', 'vision_model.vision._en.stages.3.blocks.0.mlp', 'vision_model.vision._en.stages.3.blocks.0.mlp.fc1', 'conv2d_51']J -pkg.torch.onnx.stack_trace File "/home/batman/xx3/./ml_tools/openpilot_compile/compile_supercombo.py", line 86, in forward +pkg.torch.onnx.stack_trace File "/home/batman/xx3/./ml_tools/openpilot_compile/compile_supercombo.py", line 82, in forward return torch.cat([*self.forward_dict(inputs).values(), self.pad], dim=1) File "/home/batman/xx3/xx/training/path/supercombo.py", line 185, in forward return self._en(x).flatten(1) @@ -2378,7 +2378,7 @@ getitem_30 pkg.torch.onnx.class_hierarchy['__main__.FlattenedVisionModel', 'xx.training.path.supercombo.Vision', 'timm.models.fastvit.FastVit', 'timm.models.fastvit.FastVitStage', 'torch.nn.modules.container.Sequential', 'timm.models.fastvit.RepMixerBlock', 'timm.models.fastvit.ConvMlp', 'timm.layers.activations.GELUTanh', 'aten.gelu.default']J pkg.torch.onnx.fx_node%gelu_16 : [num_users=1] = call_function[target=torch.ops.aten.gelu.default](args = (%conv2d_51,), kwargs = {approximate: tanh})J pkg.torch.onnx.name_scopes['', 'vision_model.vision', 'vision_model.vision._en', 'vision_model.vision._en.stages.3', 'vision_model.vision._en.stages.3.blocks', 'vision_model.vision._en.stages.3.blocks.0', 'vision_model.vision._en.stages.3.blocks.0.mlp', 'vision_model.vision._en.stages.3.blocks.0.mlp.act', 'gelu_16']J -pkg.torch.onnx.stack_traceFile "/home/batman/xx3/./ml_tools/openpilot_compile/compile_supercombo.py", line 86, in forward +pkg.torch.onnx.stack_traceFile "/home/batman/xx3/./ml_tools/openpilot_compile/compile_supercombo.py", line 82, in forward return torch.cat([*self.forward_dict(inputs).values(), self.pad], dim=1) File "/home/batman/xx3/xx/training/path/supercombo.py", line 185, in forward return self._en(x).flatten(1) @@ -2407,7 +2407,7 @@ getitem_30 pkg.torch.onnx.class_hierarchy['__main__.FlattenedVisionModel', 'xx.training.path.supercombo.Vision', 'timm.models.fastvit.FastVit', 'timm.models.fastvit.FastVitStage', 'torch.nn.modules.container.Sequential', 'timm.models.fastvit.RepMixerBlock', 'timm.models.fastvit.ConvMlp', 'torch.nn.modules.conv.Conv2d', 'aten.conv2d.default']J pkg.torch.onnx.fx_node%conv2d_52 : [num_users=1] = call_function[target=torch.ops.aten.conv2d.default](args = (%clone_20, %p_vision_model_vision__en_stages_3_blocks_0_mlp_fc2_weight, %p_vision_model_vision__en_stages_3_blocks_0_mlp_fc2_bias), kwargs = {})J pkg.torch.onnx.name_scopes['', 'vision_model.vision', 'vision_model.vision._en', 'vision_model.vision._en.stages.3', 'vision_model.vision._en.stages.3.blocks', 'vision_model.vision._en.stages.3.blocks.0', 'vision_model.vision._en.stages.3.blocks.0.mlp', 'vision_model.vision._en.stages.3.blocks.0.mlp.fc2', 'conv2d_52']J -pkg.torch.onnx.stack_trace File "/home/batman/xx3/./ml_tools/openpilot_compile/compile_supercombo.py", line 86, in forward +pkg.torch.onnx.stack_trace File "/home/batman/xx3/./ml_tools/openpilot_compile/compile_supercombo.py", line 82, in forward return torch.cat([*self.forward_dict(inputs).values(), self.pad], dim=1) File "/home/batman/xx3/xx/training/path/supercombo.py", line 185, in forward return self._en(x).flatten(1) @@ -2430,7 +2430,7 @@ getitem_30 pkg.torch.onnx.class_hierarchy['__main__.FlattenedVisionModel', 'xx.training.path.supercombo.Vision', 'timm.models.fastvit.FastVit', 'timm.models.fastvit.FastVitStage', 'torch.nn.modules.container.Sequential', 'timm.models.fastvit.RepMixerBlock', 'timm.models.fastvit.LayerScale2d', 'aten.mul.Tensor']J pkg.torch.onnx.fx_node%mul_10 : [num_users=1] = call_function[target=torch.ops.aten.mul.Tensor](args = (%clone_21, %p_vision_model_vision__en_stages_3_blocks_0_layer_scale_gamma), kwargs = {})J pkg.torch.onnx.name_scopes['', 'vision_model.vision', 'vision_model.vision._en', 'vision_model.vision._en.stages.3', 'vision_model.vision._en.stages.3.blocks', 'vision_model.vision._en.stages.3.blocks.0', 'vision_model.vision._en.stages.3.blocks.0.layer_scale', 'mul_10']J -pkg.torch.onnx.stack_traceFile "/home/batman/xx3/./ml_tools/openpilot_compile/compile_supercombo.py", line 86, in forward +pkg.torch.onnx.stack_traceFile "/home/batman/xx3/./ml_tools/openpilot_compile/compile_supercombo.py", line 82, in forward return torch.cat([*self.forward_dict(inputs).values(), self.pad], dim=1) File "/home/batman/xx3/xx/training/path/supercombo.py", line 185, in forward return self._en(x).flatten(1) @@ -2451,7 +2451,7 @@ getitem_30 pkg.torch.onnx.class_hierarchy['__main__.FlattenedVisionModel', 'xx.training.path.supercombo.Vision', 'timm.models.fastvit.FastVit', 'timm.models.fastvit.FastVitStage', 'torch.nn.modules.container.Sequential', 'timm.models.fastvit.RepMixerBlock', 'aten.add.Tensor']J pkg.torch.onnx.fx_nodet%add_10 : [num_users=1] = call_function[target=torch.ops.aten.add.Tensor](args = (%conv2d_49, %mul_10), kwargs = {})J pkg.torch.onnx.name_scopes['', 'vision_model.vision', 'vision_model.vision._en', 'vision_model.vision._en.stages.3', 'vision_model.vision._en.stages.3.blocks', 'vision_model.vision._en.stages.3.blocks.0', 'add_10']J -pkg.torch.onnx.stack_traceFile "/home/batman/xx3/./ml_tools/openpilot_compile/compile_supercombo.py", line 86, in forward +pkg.torch.onnx.stack_traceFile "/home/batman/xx3/./ml_tools/openpilot_compile/compile_supercombo.py", line 82, in forward return torch.cat([*self.forward_dict(inputs).values(), self.pad], dim=1) File "/home/batman/xx3/xx/training/path/supercombo.py", line 185, in forward return self._en(x).flatten(1) @@ -2476,7 +2476,7 @@ Gvision_model.vision._en.stages.3.blocks.1.token_mixer.reparam_conv.bias conv2d pkg.torch.onnx.class_hierarchy['__main__.FlattenedVisionModel', 'xx.training.path.supercombo.Vision', 'timm.models.fastvit.FastVit', 'timm.models.fastvit.FastVitStage', 'torch.nn.modules.container.Sequential', 'timm.models.fastvit.RepMixerBlock', 'timm.models.fastvit.RepMixer', 'torch.nn.modules.conv.Conv2d', 'aten.conv2d.default']J pkg.torch.onnx.fx_node%conv2d_53 : [num_users=2] = call_function[target=torch.ops.aten.conv2d.default](args = (%add_10, %p_vision_model_vision__en_stages_3_blocks_1_token_mixer_reparam_conv_weight, %p_vision_model_vision__en_stages_3_blocks_1_token_mixer_reparam_conv_bias, [1, 1], [1, 1], [1, 1], 512), kwargs = {})J pkg.torch.onnx.name_scopes['', 'vision_model.vision', 'vision_model.vision._en', 'vision_model.vision._en.stages.3', 'vision_model.vision._en.stages.3.blocks', 'vision_model.vision._en.stages.3.blocks.1', 'vision_model.vision._en.stages.3.blocks.1.token_mixer', 'vision_model.vision._en.stages.3.blocks.1.token_mixer.reparam_conv', 'conv2d_53']J -pkg.torch.onnx.stack_traceFile "/home/batman/xx3/./ml_tools/openpilot_compile/compile_supercombo.py", line 86, in forward +pkg.torch.onnx.stack_traceFile "/home/batman/xx3/./ml_tools/openpilot_compile/compile_supercombo.py", line 82, in forward return torch.cat([*self.forward_dict(inputs).values(), self.pad], dim=1) File "/home/batman/xx3/xx/training/path/supercombo.py", line 185, in forward return self._en(x).flatten(1) @@ -2507,7 +2507,7 @@ getitem_33 node_Conv_204"Conv* pkg.torch.onnx.class_hierarchy['__main__.FlattenedVisionModel', 'xx.training.path.supercombo.Vision', 'timm.models.fastvit.FastVit', 'timm.models.fastvit.FastVitStage', 'torch.nn.modules.container.Sequential', 'timm.models.fastvit.RepMixerBlock', 'timm.models.fastvit.ConvMlp', 'timm.layers.conv_bn_act.ConvNormAct', 'timm.layers.norm_act.BatchNormAct2d', 'aten._native_batch_norm_legit_no_training.default']J pkg.torch.onnx.fx_node%_native_batch_norm_legit_no_training_11 : [num_users=1] = call_function[target=torch.ops.aten._native_batch_norm_legit_no_training.default](args = (%conv2d_54, %p_vision_model_vision__en_stages_3_blocks_1_mlp_conv_bn_weight, %p_vision_model_vision__en_stages_3_blocks_1_mlp_conv_bn_bias, %b_vision_model_vision__en_stages_3_blocks_1_mlp_conv_bn_running_mean, %b_vision_model_vision__en_stages_3_blocks_1_mlp_conv_bn_running_var, 0.1, 1e-05), kwargs = {})J pkg.torch.onnx.name_scopes['', 'vision_model.vision', 'vision_model.vision._en', 'vision_model.vision._en.stages.3', 'vision_model.vision._en.stages.3.blocks', 'vision_model.vision._en.stages.3.blocks.1', 'vision_model.vision._en.stages.3.blocks.1.mlp', 'vision_model.vision._en.stages.3.blocks.1.mlp.conv', 'vision_model.vision._en.stages.3.blocks.1.mlp.conv.bn', '_native_batch_norm_legit_no_training_11']J -pkg.torch.onnx.stack_trace File "/home/batman/xx3/./ml_tools/openpilot_compile/compile_supercombo.py", line 86, in forward +pkg.torch.onnx.stack_trace File "/home/batman/xx3/./ml_tools/openpilot_compile/compile_supercombo.py", line 82, in forward return torch.cat([*self.forward_dict(inputs).values(), self.pad], dim=1) File "/home/batman/xx3/xx/training/path/supercombo.py", line 185, in forward return self._en(x).flatten(1) @@ -2539,7 +2539,7 @@ getitem_33 pkg.torch.onnx.class_hierarchy['__main__.FlattenedVisionModel', 'xx.training.path.supercombo.Vision', 'timm.models.fastvit.FastVit', 'timm.models.fastvit.FastVitStage', 'torch.nn.modules.container.Sequential', 'timm.models.fastvit.RepMixerBlock', 'timm.models.fastvit.ConvMlp', 'torch.nn.modules.conv.Conv2d', 'aten.conv2d.default']J pkg.torch.onnx.fx_node%conv2d_55 : [num_users=1] = call_function[target=torch.ops.aten.conv2d.default](args = (%getitem_33, %p_vision_model_vision__en_stages_3_blocks_1_mlp_fc1_weight, %p_vision_model_vision__en_stages_3_blocks_1_mlp_fc1_bias), kwargs = {})J pkg.torch.onnx.name_scopes['', 'vision_model.vision', 'vision_model.vision._en', 'vision_model.vision._en.stages.3', 'vision_model.vision._en.stages.3.blocks', 'vision_model.vision._en.stages.3.blocks.1', 'vision_model.vision._en.stages.3.blocks.1.mlp', 'vision_model.vision._en.stages.3.blocks.1.mlp.fc1', 'conv2d_55']J -pkg.torch.onnx.stack_trace File "/home/batman/xx3/./ml_tools/openpilot_compile/compile_supercombo.py", line 86, in forward +pkg.torch.onnx.stack_trace File "/home/batman/xx3/./ml_tools/openpilot_compile/compile_supercombo.py", line 82, in forward return torch.cat([*self.forward_dict(inputs).values(), self.pad], dim=1) File "/home/batman/xx3/xx/training/path/supercombo.py", line 185, in forward return self._en(x).flatten(1) @@ -2562,7 +2562,7 @@ getitem_33 pkg.torch.onnx.class_hierarchy['__main__.FlattenedVisionModel', 'xx.training.path.supercombo.Vision', 'timm.models.fastvit.FastVit', 'timm.models.fastvit.FastVitStage', 'torch.nn.modules.container.Sequential', 'timm.models.fastvit.RepMixerBlock', 'timm.models.fastvit.ConvMlp', 'timm.layers.activations.GELUTanh', 'aten.gelu.default']J pkg.torch.onnx.fx_node%gelu_17 : [num_users=1] = call_function[target=torch.ops.aten.gelu.default](args = (%conv2d_55,), kwargs = {approximate: tanh})J pkg.torch.onnx.name_scopes['', 'vision_model.vision', 'vision_model.vision._en', 'vision_model.vision._en.stages.3', 'vision_model.vision._en.stages.3.blocks', 'vision_model.vision._en.stages.3.blocks.1', 'vision_model.vision._en.stages.3.blocks.1.mlp', 'vision_model.vision._en.stages.3.blocks.1.mlp.act', 'gelu_17']J -pkg.torch.onnx.stack_traceFile "/home/batman/xx3/./ml_tools/openpilot_compile/compile_supercombo.py", line 86, in forward +pkg.torch.onnx.stack_traceFile "/home/batman/xx3/./ml_tools/openpilot_compile/compile_supercombo.py", line 82, in forward return torch.cat([*self.forward_dict(inputs).values(), self.pad], dim=1) File "/home/batman/xx3/xx/training/path/supercombo.py", line 185, in forward return self._en(x).flatten(1) @@ -2591,7 +2591,7 @@ getitem_33 pkg.torch.onnx.class_hierarchy['__main__.FlattenedVisionModel', 'xx.training.path.supercombo.Vision', 'timm.models.fastvit.FastVit', 'timm.models.fastvit.FastVitStage', 'torch.nn.modules.container.Sequential', 'timm.models.fastvit.RepMixerBlock', 'timm.models.fastvit.ConvMlp', 'torch.nn.modules.conv.Conv2d', 'aten.conv2d.default']J pkg.torch.onnx.fx_node%conv2d_56 : [num_users=1] = call_function[target=torch.ops.aten.conv2d.default](args = (%clone_22, %p_vision_model_vision__en_stages_3_blocks_1_mlp_fc2_weight, %p_vision_model_vision__en_stages_3_blocks_1_mlp_fc2_bias), kwargs = {})J pkg.torch.onnx.name_scopes['', 'vision_model.vision', 'vision_model.vision._en', 'vision_model.vision._en.stages.3', 'vision_model.vision._en.stages.3.blocks', 'vision_model.vision._en.stages.3.blocks.1', 'vision_model.vision._en.stages.3.blocks.1.mlp', 'vision_model.vision._en.stages.3.blocks.1.mlp.fc2', 'conv2d_56']J -pkg.torch.onnx.stack_trace File "/home/batman/xx3/./ml_tools/openpilot_compile/compile_supercombo.py", line 86, in forward +pkg.torch.onnx.stack_trace File "/home/batman/xx3/./ml_tools/openpilot_compile/compile_supercombo.py", line 82, in forward return torch.cat([*self.forward_dict(inputs).values(), self.pad], dim=1) File "/home/batman/xx3/xx/training/path/supercombo.py", line 185, in forward return self._en(x).flatten(1) @@ -2614,7 +2614,7 @@ getitem_33 pkg.torch.onnx.class_hierarchy['__main__.FlattenedVisionModel', 'xx.training.path.supercombo.Vision', 'timm.models.fastvit.FastVit', 'timm.models.fastvit.FastVitStage', 'torch.nn.modules.container.Sequential', 'timm.models.fastvit.RepMixerBlock', 'timm.models.fastvit.LayerScale2d', 'aten.mul.Tensor']J pkg.torch.onnx.fx_node%mul_11 : [num_users=1] = call_function[target=torch.ops.aten.mul.Tensor](args = (%clone_23, %p_vision_model_vision__en_stages_3_blocks_1_layer_scale_gamma), kwargs = {})J pkg.torch.onnx.name_scopes['', 'vision_model.vision', 'vision_model.vision._en', 'vision_model.vision._en.stages.3', 'vision_model.vision._en.stages.3.blocks', 'vision_model.vision._en.stages.3.blocks.1', 'vision_model.vision._en.stages.3.blocks.1.layer_scale', 'mul_11']J -pkg.torch.onnx.stack_traceFile "/home/batman/xx3/./ml_tools/openpilot_compile/compile_supercombo.py", line 86, in forward +pkg.torch.onnx.stack_traceFile "/home/batman/xx3/./ml_tools/openpilot_compile/compile_supercombo.py", line 82, in forward return torch.cat([*self.forward_dict(inputs).values(), self.pad], dim=1) File "/home/batman/xx3/xx/training/path/supercombo.py", line 185, in forward return self._en(x).flatten(1) @@ -2635,7 +2635,7 @@ getitem_33 pkg.torch.onnx.class_hierarchy['__main__.FlattenedVisionModel', 'xx.training.path.supercombo.Vision', 'timm.models.fastvit.FastVit', 'timm.models.fastvit.FastVitStage', 'torch.nn.modules.container.Sequential', 'timm.models.fastvit.RepMixerBlock', 'aten.add.Tensor']J pkg.torch.onnx.fx_nodet%add_11 : [num_users=1] = call_function[target=torch.ops.aten.add.Tensor](args = (%conv2d_53, %mul_11), kwargs = {})J pkg.torch.onnx.name_scopes['', 'vision_model.vision', 'vision_model.vision._en', 'vision_model.vision._en.stages.3', 'vision_model.vision._en.stages.3.blocks', 'vision_model.vision._en.stages.3.blocks.1', 'add_11']J -pkg.torch.onnx.stack_traceFile "/home/batman/xx3/./ml_tools/openpilot_compile/compile_supercombo.py", line 86, in forward +pkg.torch.onnx.stack_traceFile "/home/batman/xx3/./ml_tools/openpilot_compile/compile_supercombo.py", line 82, in forward return torch.cat([*self.forward_dict(inputs).values(), self.pad], dim=1) File "/home/batman/xx3/xx/training/path/supercombo.py", line 185, in forward return self._en(x).flatten(1) @@ -2660,7 +2660,7 @@ getitem_33 pkg.torch.onnx.class_hierarchy['__main__.FlattenedVisionModel', 'xx.training.path.supercombo.Vision', 'timm.models.fastvit.FastVit', 'timm.models.fastvit.MobileOneBlock', 'torch.nn.modules.conv.Conv2d', 'aten.conv2d.default']J pkg.torch.onnx.fx_node%conv2d_57 : [num_users=2] = call_function[target=torch.ops.aten.conv2d.default](args = (%add_11, %p_vision_model_vision__en_final_conv_reparam_conv_weight, %p_vision_model_vision__en_final_conv_reparam_conv_bias, [1, 1], [1, 1], [1, 1], 512), kwargs = {})J pkg.torch.onnx.name_scopes['', 'vision_model.vision', 'vision_model.vision._en', 'vision_model.vision._en.final_conv', 'vision_model.vision._en.final_conv.reparam_conv', 'conv2d_57']J -pkg.torch.onnx.stack_traceFile "/home/batman/xx3/./ml_tools/openpilot_compile/compile_supercombo.py", line 86, in forward +pkg.torch.onnx.stack_traceFile "/home/batman/xx3/./ml_tools/openpilot_compile/compile_supercombo.py", line 82, in forward return torch.cat([*self.forward_dict(inputs).values(), self.pad], dim=1) File "/home/batman/xx3/xx/training/path/supercombo.py", line 185, in forward return self._en(x).flatten(1) @@ -2680,7 +2680,7 @@ ReduceMean* pkg.torch.onnx.class_hierarchy['__main__.FlattenedVisionModel', 'xx.training.path.supercombo.Vision', 'timm.models.fastvit.FastVit', 'timm.models.fastvit.MobileOneBlock', 'timm.layers.squeeze_excite.SEModule', 'aten.mean.dim']J pkg.torch.onnx.fx_nodeu%mean : [num_users=1] = call_function[target=torch.ops.aten.mean.dim](args = (%conv2d_57, [2, 3], True), kwargs = {})J pkg.torch.onnx.name_scopes['', 'vision_model.vision', 'vision_model.vision._en', 'vision_model.vision._en.final_conv', 'vision_model.vision._en.final_conv.se', 'mean']J -pkg.torch.onnx.stack_traceFile "/home/batman/xx3/./ml_tools/openpilot_compile/compile_supercombo.py", line 86, in forward +pkg.torch.onnx.stack_traceFile "/home/batman/xx3/./ml_tools/openpilot_compile/compile_supercombo.py", line 82, in forward return torch.cat([*self.forward_dict(inputs).values(), self.pad], dim=1) File "/home/batman/xx3/xx/training/path/supercombo.py", line 185, in forward return self._en(x).flatten(1) @@ -2703,7 +2703,7 @@ ReduceMean* pkg.torch.onnx.class_hierarchy['__main__.FlattenedVisionModel', 'xx.training.path.supercombo.Vision', 'timm.models.fastvit.FastVit', 'timm.models.fastvit.MobileOneBlock', 'timm.layers.squeeze_excite.SEModule', 'torch.nn.modules.conv.Conv2d', 'aten.conv2d.default']J pkg.torch.onnx.fx_node%conv2d_58 : [num_users=1] = call_function[target=torch.ops.aten.conv2d.default](args = (%mean, %p_vision_model_vision__en_final_conv_se_fc1_weight, %p_vision_model_vision__en_final_conv_se_fc1_bias), kwargs = {})J pkg.torch.onnx.name_scopes['', 'vision_model.vision', 'vision_model.vision._en', 'vision_model.vision._en.final_conv', 'vision_model.vision._en.final_conv.se', 'vision_model.vision._en.final_conv.se.fc1', 'conv2d_58']J -pkg.torch.onnx.stack_traceFile "/home/batman/xx3/./ml_tools/openpilot_compile/compile_supercombo.py", line 86, in forward +pkg.torch.onnx.stack_traceFile "/home/batman/xx3/./ml_tools/openpilot_compile/compile_supercombo.py", line 82, in forward return torch.cat([*self.forward_dict(inputs).values(), self.pad], dim=1) File "/home/batman/xx3/xx/training/path/supercombo.py", line 185, in forward return self._en(x).flatten(1) @@ -2721,7 +2721,7 @@ ReduceMean* pkg.torch.onnx.class_hierarchy['__main__.FlattenedVisionModel', 'xx.training.path.supercombo.Vision', 'timm.models.fastvit.FastVit', 'timm.models.fastvit.MobileOneBlock', 'timm.layers.squeeze_excite.SEModule', 'torch.nn.modules.activation.ReLU', 'aten.relu.default']J pkg.torch.onnx.fx_nodel%relu : [num_users=1] = call_function[target=torch.ops.aten.relu.default](args = (%conv2d_58,), kwargs = {})J pkg.torch.onnx.name_scopes['', 'vision_model.vision', 'vision_model.vision._en', 'vision_model.vision._en.final_conv', 'vision_model.vision._en.final_conv.se', 'vision_model.vision._en.final_conv.se.act', 'relu']J -pkg.torch.onnx.stack_traceFile "/home/batman/xx3/./ml_tools/openpilot_compile/compile_supercombo.py", line 86, in forward +pkg.torch.onnx.stack_traceFile "/home/batman/xx3/./ml_tools/openpilot_compile/compile_supercombo.py", line 82, in forward return torch.cat([*self.forward_dict(inputs).values(), self.pad], dim=1) File "/home/batman/xx3/xx/training/path/supercombo.py", line 185, in forward return self._en(x).flatten(1) @@ -2746,7 +2746,7 @@ ReduceMean* pkg.torch.onnx.class_hierarchy['__main__.FlattenedVisionModel', 'xx.training.path.supercombo.Vision', 'timm.models.fastvit.FastVit', 'timm.models.fastvit.MobileOneBlock', 'timm.layers.squeeze_excite.SEModule', 'torch.nn.modules.conv.Conv2d', 'aten.conv2d.default']J pkg.torch.onnx.fx_node%conv2d_59 : [num_users=1] = call_function[target=torch.ops.aten.conv2d.default](args = (%relu, %p_vision_model_vision__en_final_conv_se_fc2_weight, %p_vision_model_vision__en_final_conv_se_fc2_bias), kwargs = {})J pkg.torch.onnx.name_scopes['', 'vision_model.vision', 'vision_model.vision._en', 'vision_model.vision._en.final_conv', 'vision_model.vision._en.final_conv.se', 'vision_model.vision._en.final_conv.se.fc2', 'conv2d_59']J -pkg.torch.onnx.stack_traceFile "/home/batman/xx3/./ml_tools/openpilot_compile/compile_supercombo.py", line 86, in forward +pkg.torch.onnx.stack_traceFile "/home/batman/xx3/./ml_tools/openpilot_compile/compile_supercombo.py", line 82, in forward return torch.cat([*self.forward_dict(inputs).values(), self.pad], dim=1) File "/home/batman/xx3/xx/training/path/supercombo.py", line 185, in forward return self._en(x).flatten(1) @@ -2764,7 +2764,7 @@ ReduceMean* pkg.torch.onnx.class_hierarchy['__main__.FlattenedVisionModel', 'xx.training.path.supercombo.Vision', 'timm.models.fastvit.FastVit', 'timm.models.fastvit.MobileOneBlock', 'timm.layers.squeeze_excite.SEModule', 'timm.layers.activations.Sigmoid', 'aten.sigmoid.default']J pkg.torch.onnx.fx_noder%sigmoid : [num_users=1] = call_function[target=torch.ops.aten.sigmoid.default](args = (%conv2d_59,), kwargs = {})J pkg.torch.onnx.name_scopes['', 'vision_model.vision', 'vision_model.vision._en', 'vision_model.vision._en.final_conv', 'vision_model.vision._en.final_conv.se', 'vision_model.vision._en.final_conv.se.gate', 'sigmoid']J -pkg.torch.onnx.stack_traceFile "/home/batman/xx3/./ml_tools/openpilot_compile/compile_supercombo.py", line 86, in forward +pkg.torch.onnx.stack_traceFile "/home/batman/xx3/./ml_tools/openpilot_compile/compile_supercombo.py", line 82, in forward return torch.cat([*self.forward_dict(inputs).values(), self.pad], dim=1) File "/home/batman/xx3/xx/training/path/supercombo.py", line 185, in forward return self._en(x).flatten(1) @@ -2783,7 +2783,7 @@ ReduceMean* pkg.torch.onnx.class_hierarchy['__main__.FlattenedVisionModel', 'xx.training.path.supercombo.Vision', 'timm.models.fastvit.FastVit', 'timm.models.fastvit.MobileOneBlock', 'timm.layers.squeeze_excite.SEModule', 'aten.mul.Tensor']J pkg.torch.onnx.fx_nodeu%mul_12 : [num_users=1] = call_function[target=torch.ops.aten.mul.Tensor](args = (%conv2d_57, %sigmoid), kwargs = {})J pkg.torch.onnx.name_scopes['', 'vision_model.vision', 'vision_model.vision._en', 'vision_model.vision._en.final_conv', 'vision_model.vision._en.final_conv.se', 'mul_12']J -pkg.torch.onnx.stack_traceFile "/home/batman/xx3/./ml_tools/openpilot_compile/compile_supercombo.py", line 86, in forward +pkg.torch.onnx.stack_traceFile "/home/batman/xx3/./ml_tools/openpilot_compile/compile_supercombo.py", line 82, in forward return torch.cat([*self.forward_dict(inputs).values(), self.pad], dim=1) File "/home/batman/xx3/xx/training/path/supercombo.py", line 185, in forward return self._en(x).flatten(1) @@ -2800,7 +2800,7 @@ ReduceMean* pkg.torch.onnx.class_hierarchy['__main__.FlattenedVisionModel', 'xx.training.path.supercombo.Vision', 'timm.models.fastvit.FastVit', 'timm.models.fastvit.MobileOneBlock', 'timm.layers.activations.GELUTanh', 'aten.gelu.default']J pkg.torch.onnx.fx_node}%gelu_18 : [num_users=1] = call_function[target=torch.ops.aten.gelu.default](args = (%mul_12,), kwargs = {approximate: tanh})J pkg.torch.onnx.name_scopes['', 'vision_model.vision', 'vision_model.vision._en', 'vision_model.vision._en.final_conv', 'vision_model.vision._en.final_conv.act', 'gelu_18']J -pkg.torch.onnx.stack_traceFile "/home/batman/xx3/./ml_tools/openpilot_compile/compile_supercombo.py", line 86, in forward +pkg.torch.onnx.stack_traceFile "/home/batman/xx3/./ml_tools/openpilot_compile/compile_supercombo.py", line 82, in forward return torch.cat([*self.forward_dict(inputs).values(), self.pad], dim=1) File "/home/batman/xx3/xx/training/path/supercombo.py", line 185, in forward return self._en(x).flatten(1) @@ -2820,7 +2820,7 @@ ReduceMean* pkg.torch.onnx.class_hierarchy['__main__.FlattenedVisionModel', 'xx.training.path.supercombo.Vision', 'timm.models.fastvit.FastVit', 'timm.layers.classifier.ClassifierHead', 'timm.layers.adaptive_avgmax_pool.SelectAdaptivePool2d', 'torch.nn.modules.pooling.AdaptiveAvgPool2d', 'aten.mean.dim']J pkg.torch.onnx.fx_nodew%mean_1 : [num_users=1] = call_function[target=torch.ops.aten.mean.dim](args = (%gelu_18, [-1, -2], True), kwargs = {})J pkg.torch.onnx.name_scopes['', 'vision_model.vision', 'vision_model.vision._en', 'vision_model.vision._en.head', 'vision_model.vision._en.head.global_pool', 'vision_model.vision._en.head.global_pool.pool', 'mean_1']J -pkg.torch.onnx.stack_traceFile "/home/batman/xx3/./ml_tools/openpilot_compile/compile_supercombo.py", line 86, in forward +pkg.torch.onnx.stack_traceFile "/home/batman/xx3/./ml_tools/openpilot_compile/compile_supercombo.py", line 82, in forward return torch.cat([*self.forward_dict(inputs).values(), self.pad], dim=1) File "/home/batman/xx3/xx/training/path/supercombo.py", line 185, in forward return self._en(x).flatten(1) @@ -2840,7 +2840,7 @@ ReduceMean* pkg.torch.onnx.class_hierarchy['__main__.FlattenedVisionModel', 'xx.training.path.supercombo.Vision', 'timm.models.fastvit.FastVit', 'timm.layers.classifier.ClassifierHead', 'timm.layers.adaptive_avgmax_pool.SelectAdaptivePool2d', 'torch.nn.modules.flatten.Flatten', 'aten.view.default']J pkg.torch.onnx.fx_nodes%view : [num_users=1] = call_function[target=torch.ops.aten.view.default](args = (%mean_1, [1, 1024]), kwargs = {})J pkg.torch.onnx.name_scopes['', 'vision_model.vision', 'vision_model.vision._en', 'vision_model.vision._en.head', 'vision_model.vision._en.head.global_pool', 'vision_model.vision._en.head.global_pool.flatten', 'view']J -pkg.torch.onnx.stack_traceFile "/home/batman/xx3/./ml_tools/openpilot_compile/compile_supercombo.py", line 86, in forward +pkg.torch.onnx.stack_traceFile "/home/batman/xx3/./ml_tools/openpilot_compile/compile_supercombo.py", line 82, in forward return torch.cat([*self.forward_dict(inputs).values(), self.pad], dim=1) File "/home/batman/xx3/xx/training/path/supercombo.py", line 185, in forward return self._en(x).flatten(1) @@ -2864,7 +2864,7 @@ $vision_model.vision._en.head.fc.biaslinear node_linear"Gemm* pkg.torch.onnx.class_hierarchy['__main__.FlattenedVisionModel', 'xx.training.path.supercombo.Vision', 'timm.models.fastvit.FastVit', 'timm.layers.classifier.ClassifierHead', 'torch.nn.modules.linear.Linear', 'aten.linear.default']J pkg.torch.onnx.fx_node%linear : [num_users=3] = call_function[target=torch.ops.aten.linear.default](args = (%clone_24, %p_vision_model_vision__en_head_fc_weight, %p_vision_model_vision__en_head_fc_bias), kwargs = {})J pkg.torch.onnx.name_scopes['', 'vision_model.vision', 'vision_model.vision._en', 'vision_model.vision._en.head', 'vision_model.vision._en.head.fc', 'linear']J -pkg.torch.onnx.stack_traceFile "/home/batman/xx3/./ml_tools/openpilot_compile/compile_supercombo.py", line 86, in forward +pkg.torch.onnx.stack_traceFile "/home/batman/xx3/./ml_tools/openpilot_compile/compile_supercombo.py", line 82, in forward return torch.cat([*self.forward_dict(inputs).values(), self.pad], dim=1) File "/home/batman/xx3/xx/training/path/supercombo.py", line 185, in forward return self._en(x).flatten(1) @@ -2886,7 +2886,7 @@ $vision_model.vision._en.head.fc.biaslinear node_linear"Gemm* pkg.torch.onnx.class_hierarchy['__main__.FlattenedVisionModel', 'xx.training.path.supercombo.Policy', 'xx.training.path.supercombo.PointSummarizer', 'xx.training.lib.layers.ResBlock', 'torch.nn.modules.container.Sequential', 'torch.nn.modules.linear.Linear', 'aten.linear.default']J pkg.torch.onnx.fx_node%linear_1 : [num_users=1] = call_function[target=torch.ops.aten.linear.default](args = (%linear, %p_vision_model_point_policy_summarizer_resblock_block_a_0_weight, %p_vision_model_point_policy_summarizer_resblock_block_a_0_bias), kwargs = {})J pkg.torch.onnx.name_scopes['', 'vision_model.point_policy', 'vision_model.point_policy.summarizer', 'vision_model.point_policy.summarizer.resblock', 'vision_model.point_policy.summarizer.resblock.block_a', 'vision_model.point_policy.summarizer.resblock.block_a.0', 'linear_1']J -pkg.torch.onnx.stack_traceFile "/home/batman/xx3/./ml_tools/openpilot_compile/compile_supercombo.py", line 86, in forward +pkg.torch.onnx.stack_traceFile "/home/batman/xx3/./ml_tools/openpilot_compile/compile_supercombo.py", line 82, in forward return torch.cat([*self.forward_dict(inputs).values(), self.pad], dim=1) File "/home/batman/xx3/xx/training/path/supercombo.py", line 131, in forward summary_outs = self.summarizer(vision_features) @@ -2911,7 +2911,7 @@ stash_type pkg.torch.onnx.class_hierarchy['__main__.FlattenedVisionModel', 'xx.training.path.supercombo.Policy', 'xx.training.path.supercombo.PointSummarizer', 'xx.training.lib.layers.ResBlock', 'torch.nn.modules.container.Sequential', 'torch.nn.modules.normalization.LayerNorm', 'aten.layer_norm.default']J pkg.torch.onnx.fx_node%layer_norm : [num_users=1] = call_function[target=torch.ops.aten.layer_norm.default](args = (%linear_1, [1024], %p_vision_model_point_policy_summarizer_resblock_block_a_1_weight, %p_vision_model_point_policy_summarizer_resblock_block_a_1_bias), kwargs = {})J pkg.torch.onnx.name_scopes['', 'vision_model.point_policy', 'vision_model.point_policy.summarizer', 'vision_model.point_policy.summarizer.resblock', 'vision_model.point_policy.summarizer.resblock.block_a', 'vision_model.point_policy.summarizer.resblock.block_a.1', 'layer_norm']J -pkg.torch.onnx.stack_traceFile "/home/batman/xx3/./ml_tools/openpilot_compile/compile_supercombo.py", line 86, in forward +pkg.torch.onnx.stack_traceFile "/home/batman/xx3/./ml_tools/openpilot_compile/compile_supercombo.py", line 82, in forward return torch.cat([*self.forward_dict(inputs).values(), self.pad], dim=1) File "/home/batman/xx3/xx/training/path/supercombo.py", line 131, in forward summary_outs = self.summarizer(vision_features) @@ -2930,7 +2930,7 @@ layer_normrelu_1 node_relu_1"ReluJ pkg.torch.onnx.class_hierarchy['__main__.FlattenedVisionModel', 'xx.training.path.supercombo.Policy', 'xx.training.path.supercombo.PointSummarizer', 'xx.training.lib.layers.ResBlock', 'torch.nn.modules.container.Sequential', 'torch.nn.modules.activation.ReLU', 'aten.relu.default']J pkg.torch.onnx.fx_nodeo%relu_1 : [num_users=1] = call_function[target=torch.ops.aten.relu.default](args = (%layer_norm,), kwargs = {})J pkg.torch.onnx.name_scopes['', 'vision_model.point_policy', 'vision_model.point_policy.summarizer', 'vision_model.point_policy.summarizer.resblock', 'vision_model.point_policy.summarizer.resblock.block_a', 'vision_model.point_policy.summarizer.resblock.block_a.2', 'relu_1']J -pkg.torch.onnx.stack_traceFile "/home/batman/xx3/./ml_tools/openpilot_compile/compile_supercombo.py", line 86, in forward +pkg.torch.onnx.stack_traceFile "/home/batman/xx3/./ml_tools/openpilot_compile/compile_supercombo.py", line 82, in forward return torch.cat([*self.forward_dict(inputs).values(), self.pad], dim=1) File "/home/batman/xx3/xx/training/path/supercombo.py", line 131, in forward summary_outs = self.summarizer(vision_features) @@ -2954,7 +2954,7 @@ layer_normrelu_1 node_relu_1"ReluJ pkg.torch.onnx.class_hierarchy['__main__.FlattenedVisionModel', 'xx.training.path.supercombo.Policy', 'xx.training.path.supercombo.PointSummarizer', 'xx.training.lib.layers.ResBlock', 'torch.nn.modules.container.Sequential', 'torch.nn.modules.linear.Linear', 'aten.linear.default']J pkg.torch.onnx.fx_node%linear_2 : [num_users=1] = call_function[target=torch.ops.aten.linear.default](args = (%relu_1, %p_vision_model_point_policy_summarizer_resblock_block_a_3_weight, %p_vision_model_point_policy_summarizer_resblock_block_a_3_bias), kwargs = {})J pkg.torch.onnx.name_scopes['', 'vision_model.point_policy', 'vision_model.point_policy.summarizer', 'vision_model.point_policy.summarizer.resblock', 'vision_model.point_policy.summarizer.resblock.block_a', 'vision_model.point_policy.summarizer.resblock.block_a.3', 'linear_2']J -pkg.torch.onnx.stack_traceFile "/home/batman/xx3/./ml_tools/openpilot_compile/compile_supercombo.py", line 86, in forward +pkg.torch.onnx.stack_traceFile "/home/batman/xx3/./ml_tools/openpilot_compile/compile_supercombo.py", line 82, in forward return torch.cat([*self.forward_dict(inputs).values(), self.pad], dim=1) File "/home/batman/xx3/xx/training/path/supercombo.py", line 131, in forward summary_outs = self.summarizer(vision_features) @@ -2978,7 +2978,7 @@ stash_type pkg.torch.onnx.class_hierarchy['__main__.FlattenedVisionModel', 'xx.training.path.supercombo.Policy', 'xx.training.path.supercombo.PointSummarizer', 'xx.training.lib.layers.ResBlock', 'torch.nn.modules.container.Sequential', 'torch.nn.modules.normalization.LayerNorm', 'aten.layer_norm.default']J pkg.torch.onnx.fx_node%layer_norm_1 : [num_users=1] = call_function[target=torch.ops.aten.layer_norm.default](args = (%linear_2, [512], %p_vision_model_point_policy_summarizer_resblock_block_a_4_weight, %p_vision_model_point_policy_summarizer_resblock_block_a_4_bias), kwargs = {})J pkg.torch.onnx.name_scopes['', 'vision_model.point_policy', 'vision_model.point_policy.summarizer', 'vision_model.point_policy.summarizer.resblock', 'vision_model.point_policy.summarizer.resblock.block_a', 'vision_model.point_policy.summarizer.resblock.block_a.4', 'layer_norm_1']J -pkg.torch.onnx.stack_traceFile "/home/batman/xx3/./ml_tools/openpilot_compile/compile_supercombo.py", line 86, in forward +pkg.torch.onnx.stack_traceFile "/home/batman/xx3/./ml_tools/openpilot_compile/compile_supercombo.py", line 82, in forward return torch.cat([*self.forward_dict(inputs).values(), self.pad], dim=1) File "/home/batman/xx3/xx/training/path/supercombo.py", line 131, in forward summary_outs = self.summarizer(vision_features) @@ -2998,7 +2998,7 @@ stash_type pkg.torch.onnx.class_hierarchy['__main__.FlattenedVisionModel', 'xx.training.path.supercombo.Policy', 'xx.training.path.supercombo.PointSummarizer', 'xx.training.lib.layers.ResBlock', 'aten.add.Tensor']J pkg.torch.onnx.fx_nodew%add_12 : [num_users=1] = call_function[target=torch.ops.aten.add.Tensor](args = (%linear, %layer_norm_1), kwargs = {})J pkg.torch.onnx.name_scopes['', 'vision_model.point_policy', 'vision_model.point_policy.summarizer', 'vision_model.point_policy.summarizer.resblock', 'add_12']J -pkg.torch.onnx.stack_traceFile "/home/batman/xx3/./ml_tools/openpilot_compile/compile_supercombo.py", line 86, in forward +pkg.torch.onnx.stack_traceFile "/home/batman/xx3/./ml_tools/openpilot_compile/compile_supercombo.py", line 82, in forward return torch.cat([*self.forward_dict(inputs).values(), self.pad], dim=1) File "/home/batman/xx3/xx/training/path/supercombo.py", line 131, in forward summary_outs = self.summarizer(vision_features) @@ -3012,7 +3012,7 @@ stash_type pkg.torch.onnx.class_hierarchy['__main__.FlattenedVisionModel', 'xx.training.path.supercombo.Policy', 'xx.training.path.supercombo.PointSummarizer', 'xx.training.lib.layers.ResBlock', 'torch.nn.modules.container.Sequential', 'torch.nn.modules.activation.ReLU', 'aten.relu.default']J pkg.torch.onnx.fx_nodek%relu_2 : [num_users=2] = call_function[target=torch.ops.aten.relu.default](args = (%add_12,), kwargs = {})J pkg.torch.onnx.name_scopes['', 'vision_model.point_policy', 'vision_model.point_policy.summarizer', 'vision_model.point_policy.summarizer.resblock', 'vision_model.point_policy.summarizer.resblock.block_b', 'vision_model.point_policy.summarizer.resblock.block_b.0', 'relu_2']J -pkg.torch.onnx.stack_traceFile "/home/batman/xx3/./ml_tools/openpilot_compile/compile_supercombo.py", line 86, in forward +pkg.torch.onnx.stack_traceFile "/home/batman/xx3/./ml_tools/openpilot_compile/compile_supercombo.py", line 82, in forward return torch.cat([*self.forward_dict(inputs).values(), self.pad], dim=1) File "/home/batman/xx3/xx/training/path/supercombo.py", line 131, in forward summary_outs = self.summarizer(vision_features) @@ -3036,7 +3036,7 @@ stash_type pkg.torch.onnx.class_hierarchy['__main__.FlattenedVisionModel', 'xx.training.path.supercombo.Policy', 'xx.training.path.supercombo.PointSummarizer', 'xx.training.lib.layers.ResBlock', 'torch.nn.modules.container.Sequential', 'torch.nn.modules.linear.Linear', 'aten.linear.default']J pkg.torch.onnx.fx_node%linear_3 : [num_users=1] = call_function[target=torch.ops.aten.linear.default](args = (%relu_2, %p_vision_model_point_policy_summarizer_resblock_block_b_1_weight, %p_vision_model_point_policy_summarizer_resblock_block_b_1_bias), kwargs = {})J pkg.torch.onnx.name_scopes['', 'vision_model.point_policy', 'vision_model.point_policy.summarizer', 'vision_model.point_policy.summarizer.resblock', 'vision_model.point_policy.summarizer.resblock.block_b', 'vision_model.point_policy.summarizer.resblock.block_b.1', 'linear_3']J -pkg.torch.onnx.stack_traceFile "/home/batman/xx3/./ml_tools/openpilot_compile/compile_supercombo.py", line 86, in forward +pkg.torch.onnx.stack_traceFile "/home/batman/xx3/./ml_tools/openpilot_compile/compile_supercombo.py", line 82, in forward return torch.cat([*self.forward_dict(inputs).values(), self.pad], dim=1) File "/home/batman/xx3/xx/training/path/supercombo.py", line 131, in forward summary_outs = self.summarizer(vision_features) @@ -3060,7 +3060,7 @@ stash_type pkg.torch.onnx.class_hierarchy['__main__.FlattenedVisionModel', 'xx.training.path.supercombo.Policy', 'xx.training.path.supercombo.PointSummarizer', 'xx.training.lib.layers.ResBlock', 'torch.nn.modules.container.Sequential', 'torch.nn.modules.normalization.LayerNorm', 'aten.layer_norm.default']J pkg.torch.onnx.fx_node%layer_norm_2 : [num_users=1] = call_function[target=torch.ops.aten.layer_norm.default](args = (%linear_3, [1024], %p_vision_model_point_policy_summarizer_resblock_block_b_2_weight, %p_vision_model_point_policy_summarizer_resblock_block_b_2_bias), kwargs = {})J pkg.torch.onnx.name_scopes['', 'vision_model.point_policy', 'vision_model.point_policy.summarizer', 'vision_model.point_policy.summarizer.resblock', 'vision_model.point_policy.summarizer.resblock.block_b', 'vision_model.point_policy.summarizer.resblock.block_b.2', 'layer_norm_2']J -pkg.torch.onnx.stack_traceFile "/home/batman/xx3/./ml_tools/openpilot_compile/compile_supercombo.py", line 86, in forward +pkg.torch.onnx.stack_traceFile "/home/batman/xx3/./ml_tools/openpilot_compile/compile_supercombo.py", line 82, in forward return torch.cat([*self.forward_dict(inputs).values(), self.pad], dim=1) File "/home/batman/xx3/xx/training/path/supercombo.py", line 131, in forward summary_outs = self.summarizer(vision_features) @@ -3078,7 +3078,7 @@ stash_type pkg.torch.onnx.class_hierarchy['__main__.FlattenedVisionModel', 'xx.training.path.supercombo.Policy', 'xx.training.path.supercombo.PointSummarizer', 'xx.training.lib.layers.ResBlock', 'torch.nn.modules.container.Sequential', 'torch.nn.modules.activation.ReLU', 'aten.relu.default']J pkg.torch.onnx.fx_nodeq%relu_3 : [num_users=1] = call_function[target=torch.ops.aten.relu.default](args = (%layer_norm_2,), kwargs = {})J pkg.torch.onnx.name_scopes['', 'vision_model.point_policy', 'vision_model.point_policy.summarizer', 'vision_model.point_policy.summarizer.resblock', 'vision_model.point_policy.summarizer.resblock.block_b', 'vision_model.point_policy.summarizer.resblock.block_b.3', 'relu_3']J -pkg.torch.onnx.stack_traceFile "/home/batman/xx3/./ml_tools/openpilot_compile/compile_supercombo.py", line 86, in forward +pkg.torch.onnx.stack_traceFile "/home/batman/xx3/./ml_tools/openpilot_compile/compile_supercombo.py", line 82, in forward return torch.cat([*self.forward_dict(inputs).values(), self.pad], dim=1) File "/home/batman/xx3/xx/training/path/supercombo.py", line 131, in forward summary_outs = self.summarizer(vision_features) @@ -3102,7 +3102,7 @@ stash_type pkg.torch.onnx.class_hierarchy['__main__.FlattenedVisionModel', 'xx.training.path.supercombo.Policy', 'xx.training.path.supercombo.PointSummarizer', 'xx.training.lib.layers.ResBlock', 'torch.nn.modules.container.Sequential', 'torch.nn.modules.linear.Linear', 'aten.linear.default']J pkg.torch.onnx.fx_node%linear_4 : [num_users=1] = call_function[target=torch.ops.aten.linear.default](args = (%relu_3, %p_vision_model_point_policy_summarizer_resblock_block_b_4_weight, %p_vision_model_point_policy_summarizer_resblock_block_b_4_bias), kwargs = {})J pkg.torch.onnx.name_scopes['', 'vision_model.point_policy', 'vision_model.point_policy.summarizer', 'vision_model.point_policy.summarizer.resblock', 'vision_model.point_policy.summarizer.resblock.block_b', 'vision_model.point_policy.summarizer.resblock.block_b.4', 'linear_4']J -pkg.torch.onnx.stack_traceFile "/home/batman/xx3/./ml_tools/openpilot_compile/compile_supercombo.py", line 86, in forward +pkg.torch.onnx.stack_traceFile "/home/batman/xx3/./ml_tools/openpilot_compile/compile_supercombo.py", line 82, in forward return torch.cat([*self.forward_dict(inputs).values(), self.pad], dim=1) File "/home/batman/xx3/xx/training/path/supercombo.py", line 131, in forward summary_outs = self.summarizer(vision_features) @@ -3126,7 +3126,7 @@ stash_type pkg.torch.onnx.class_hierarchy['__main__.FlattenedVisionModel', 'xx.training.path.supercombo.Policy', 'xx.training.path.supercombo.PointSummarizer', 'xx.training.lib.layers.ResBlock', 'torch.nn.modules.container.Sequential', 'torch.nn.modules.normalization.LayerNorm', 'aten.layer_norm.default']J pkg.torch.onnx.fx_node%layer_norm_3 : [num_users=1] = call_function[target=torch.ops.aten.layer_norm.default](args = (%linear_4, [512], %p_vision_model_point_policy_summarizer_resblock_block_b_5_weight, %p_vision_model_point_policy_summarizer_resblock_block_b_5_bias), kwargs = {})J pkg.torch.onnx.name_scopes['', 'vision_model.point_policy', 'vision_model.point_policy.summarizer', 'vision_model.point_policy.summarizer.resblock', 'vision_model.point_policy.summarizer.resblock.block_b', 'vision_model.point_policy.summarizer.resblock.block_b.5', 'layer_norm_3']J -pkg.torch.onnx.stack_traceFile "/home/batman/xx3/./ml_tools/openpilot_compile/compile_supercombo.py", line 86, in forward +pkg.torch.onnx.stack_traceFile "/home/batman/xx3/./ml_tools/openpilot_compile/compile_supercombo.py", line 82, in forward return torch.cat([*self.forward_dict(inputs).values(), self.pad], dim=1) File "/home/batman/xx3/xx/training/path/supercombo.py", line 131, in forward summary_outs = self.summarizer(vision_features) @@ -3145,7 +3145,7 @@ stash_type pkg.torch.onnx.class_hierarchy['__main__.FlattenedVisionModel', 'xx.training.path.supercombo.Policy', 'xx.training.path.supercombo.PointSummarizer', 'xx.training.lib.layers.ResBlock', 'aten.add.Tensor']J pkg.torch.onnx.fx_nodew%add_13 : [num_users=1] = call_function[target=torch.ops.aten.add.Tensor](args = (%relu_2, %layer_norm_3), kwargs = {})J pkg.torch.onnx.name_scopes['', 'vision_model.point_policy', 'vision_model.point_policy.summarizer', 'vision_model.point_policy.summarizer.resblock', 'add_13']J -pkg.torch.onnx.stack_traceFile "/home/batman/xx3/./ml_tools/openpilot_compile/compile_supercombo.py", line 86, in forward +pkg.torch.onnx.stack_traceFile "/home/batman/xx3/./ml_tools/openpilot_compile/compile_supercombo.py", line 82, in forward return torch.cat([*self.forward_dict(inputs).values(), self.pad], dim=1) File "/home/batman/xx3/xx/training/path/supercombo.py", line 131, in forward summary_outs = self.summarizer(vision_features) @@ -3159,7 +3159,7 @@ stash_type pkg.torch.onnx.class_hierarchy['__main__.FlattenedVisionModel', 'xx.training.path.supercombo.Policy', 'xx.training.path.supercombo.PointSummarizer', 'xx.training.lib.layers.ResBlock', 'torch.nn.modules.activation.ReLU', 'aten.relu.default']J pkg.torch.onnx.fx_nodek%relu_4 : [num_users=2] = call_function[target=torch.ops.aten.relu.default](args = (%add_13,), kwargs = {})J pkg.torch.onnx.name_scopes['', 'vision_model.point_policy', 'vision_model.point_policy.summarizer', 'vision_model.point_policy.summarizer.resblock', 'vision_model.point_policy.summarizer.resblock.final_relu', 'relu_4']J -pkg.torch.onnx.stack_traceFile "/home/batman/xx3/./ml_tools/openpilot_compile/compile_supercombo.py", line 86, in forward +pkg.torch.onnx.stack_traceFile "/home/batman/xx3/./ml_tools/openpilot_compile/compile_supercombo.py", line 82, in forward return torch.cat([*self.forward_dict(inputs).values(), self.pad], dim=1) File "/home/batman/xx3/xx/training/path/supercombo.py", line 131, in forward summary_outs = self.summarizer(vision_features) @@ -3181,7 +3181,7 @@ stash_type pkg.torch.onnx.class_hierarchy['__main__.FlattenedVisionModel', 'xx.training.path.supercombo.Policy', 'xx.training.path.supercombo.Hydra', 'xx.training.lib.layers.ResBlock', 'torch.nn.modules.container.Sequential', 'torch.nn.modules.linear.Linear', 'aten.linear.default']J pkg.torch.onnx.fx_node%linear_5 : [num_users=1] = call_function[target=torch.ops.aten.linear.default](args = (%relu_4, %p_vision_model_point_policy_hydra_resblock_block_a_0_weight, %p_vision_model_point_policy_hydra_resblock_block_a_0_bias), kwargs = {})J pkg.torch.onnx.name_scopes['', 'vision_model.point_policy', 'vision_model.point_policy.hydra', 'vision_model.point_policy.hydra.resblock', 'vision_model.point_policy.hydra.resblock.block_a', 'vision_model.point_policy.hydra.resblock.block_a.0', 'linear_5']J -pkg.torch.onnx.stack_traceFile "/home/batman/xx3/./ml_tools/openpilot_compile/compile_supercombo.py", line 86, in forward +pkg.torch.onnx.stack_traceFile "/home/batman/xx3/./ml_tools/openpilot_compile/compile_supercombo.py", line 82, in forward return torch.cat([*self.forward_dict(inputs).values(), self.pad], dim=1) File "/home/batman/xx3/xx/training/path/supercombo.py", line 132, in forward policy_outs = self.hydra(summary_outs) @@ -3205,7 +3205,7 @@ stash_type pkg.torch.onnx.class_hierarchy['__main__.FlattenedVisionModel', 'xx.training.path.supercombo.Policy', 'xx.training.path.supercombo.Hydra', 'xx.training.lib.layers.ResBlock', 'torch.nn.modules.container.Sequential', 'torch.nn.modules.normalization.LayerNorm', 'aten.layer_norm.default']J pkg.torch.onnx.fx_node%layer_norm_4 : [num_users=1] = call_function[target=torch.ops.aten.layer_norm.default](args = (%linear_5, [1024], %p_vision_model_point_policy_hydra_resblock_block_a_1_weight, %p_vision_model_point_policy_hydra_resblock_block_a_1_bias), kwargs = {})J pkg.torch.onnx.name_scopes['', 'vision_model.point_policy', 'vision_model.point_policy.hydra', 'vision_model.point_policy.hydra.resblock', 'vision_model.point_policy.hydra.resblock.block_a', 'vision_model.point_policy.hydra.resblock.block_a.1', 'layer_norm_4']J -pkg.torch.onnx.stack_traceFile "/home/batman/xx3/./ml_tools/openpilot_compile/compile_supercombo.py", line 86, in forward +pkg.torch.onnx.stack_traceFile "/home/batman/xx3/./ml_tools/openpilot_compile/compile_supercombo.py", line 82, in forward return torch.cat([*self.forward_dict(inputs).values(), self.pad], dim=1) File "/home/batman/xx3/xx/training/path/supercombo.py", line 132, in forward policy_outs = self.hydra(summary_outs) @@ -3223,7 +3223,7 @@ stash_type pkg.torch.onnx.class_hierarchy['__main__.FlattenedVisionModel', 'xx.training.path.supercombo.Policy', 'xx.training.path.supercombo.Hydra', 'xx.training.lib.layers.ResBlock', 'torch.nn.modules.container.Sequential', 'torch.nn.modules.activation.ReLU', 'aten.relu.default']J pkg.torch.onnx.fx_nodeq%relu_5 : [num_users=1] = call_function[target=torch.ops.aten.relu.default](args = (%layer_norm_4,), kwargs = {})J pkg.torch.onnx.name_scopes['', 'vision_model.point_policy', 'vision_model.point_policy.hydra', 'vision_model.point_policy.hydra.resblock', 'vision_model.point_policy.hydra.resblock.block_a', 'vision_model.point_policy.hydra.resblock.block_a.2', 'relu_5']J -pkg.torch.onnx.stack_traceFile "/home/batman/xx3/./ml_tools/openpilot_compile/compile_supercombo.py", line 86, in forward +pkg.torch.onnx.stack_traceFile "/home/batman/xx3/./ml_tools/openpilot_compile/compile_supercombo.py", line 82, in forward return torch.cat([*self.forward_dict(inputs).values(), self.pad], dim=1) File "/home/batman/xx3/xx/training/path/supercombo.py", line 132, in forward policy_outs = self.hydra(summary_outs) @@ -3247,7 +3247,7 @@ stash_type pkg.torch.onnx.class_hierarchy['__main__.FlattenedVisionModel', 'xx.training.path.supercombo.Policy', 'xx.training.path.supercombo.Hydra', 'xx.training.lib.layers.ResBlock', 'torch.nn.modules.container.Sequential', 'torch.nn.modules.linear.Linear', 'aten.linear.default']J pkg.torch.onnx.fx_node%linear_6 : [num_users=1] = call_function[target=torch.ops.aten.linear.default](args = (%relu_5, %p_vision_model_point_policy_hydra_resblock_block_a_3_weight, %p_vision_model_point_policy_hydra_resblock_block_a_3_bias), kwargs = {})J pkg.torch.onnx.name_scopes['', 'vision_model.point_policy', 'vision_model.point_policy.hydra', 'vision_model.point_policy.hydra.resblock', 'vision_model.point_policy.hydra.resblock.block_a', 'vision_model.point_policy.hydra.resblock.block_a.3', 'linear_6']J -pkg.torch.onnx.stack_traceFile "/home/batman/xx3/./ml_tools/openpilot_compile/compile_supercombo.py", line 86, in forward +pkg.torch.onnx.stack_traceFile "/home/batman/xx3/./ml_tools/openpilot_compile/compile_supercombo.py", line 82, in forward return torch.cat([*self.forward_dict(inputs).values(), self.pad], dim=1) File "/home/batman/xx3/xx/training/path/supercombo.py", line 132, in forward policy_outs = self.hydra(summary_outs) @@ -3271,7 +3271,7 @@ stash_type pkg.torch.onnx.class_hierarchy['__main__.FlattenedVisionModel', 'xx.training.path.supercombo.Policy', 'xx.training.path.supercombo.Hydra', 'xx.training.lib.layers.ResBlock', 'torch.nn.modules.container.Sequential', 'torch.nn.modules.normalization.LayerNorm', 'aten.layer_norm.default']J pkg.torch.onnx.fx_node%layer_norm_5 : [num_users=1] = call_function[target=torch.ops.aten.layer_norm.default](args = (%linear_6, [512], %p_vision_model_point_policy_hydra_resblock_block_a_4_weight, %p_vision_model_point_policy_hydra_resblock_block_a_4_bias), kwargs = {})J pkg.torch.onnx.name_scopes['', 'vision_model.point_policy', 'vision_model.point_policy.hydra', 'vision_model.point_policy.hydra.resblock', 'vision_model.point_policy.hydra.resblock.block_a', 'vision_model.point_policy.hydra.resblock.block_a.4', 'layer_norm_5']J -pkg.torch.onnx.stack_traceFile "/home/batman/xx3/./ml_tools/openpilot_compile/compile_supercombo.py", line 86, in forward +pkg.torch.onnx.stack_traceFile "/home/batman/xx3/./ml_tools/openpilot_compile/compile_supercombo.py", line 82, in forward return torch.cat([*self.forward_dict(inputs).values(), self.pad], dim=1) File "/home/batman/xx3/xx/training/path/supercombo.py", line 132, in forward policy_outs = self.hydra(summary_outs) @@ -3291,7 +3291,7 @@ stash_type pkg.torch.onnx.class_hierarchy['__main__.FlattenedVisionModel', 'xx.training.path.supercombo.Policy', 'xx.training.path.supercombo.Hydra', 'xx.training.lib.layers.ResBlock', 'aten.add.Tensor']J pkg.torch.onnx.fx_nodew%add_14 : [num_users=1] = call_function[target=torch.ops.aten.add.Tensor](args = (%relu_4, %layer_norm_5), kwargs = {})J pkg.torch.onnx.name_scopesz['', 'vision_model.point_policy', 'vision_model.point_policy.hydra', 'vision_model.point_policy.hydra.resblock', 'add_14']J -pkg.torch.onnx.stack_traceFile "/home/batman/xx3/./ml_tools/openpilot_compile/compile_supercombo.py", line 86, in forward +pkg.torch.onnx.stack_traceFile "/home/batman/xx3/./ml_tools/openpilot_compile/compile_supercombo.py", line 82, in forward return torch.cat([*self.forward_dict(inputs).values(), self.pad], dim=1) File "/home/batman/xx3/xx/training/path/supercombo.py", line 132, in forward policy_outs = self.hydra(summary_outs) @@ -3305,7 +3305,7 @@ stash_type pkg.torch.onnx.class_hierarchy['__main__.FlattenedVisionModel', 'xx.training.path.supercombo.Policy', 'xx.training.path.supercombo.Hydra', 'xx.training.lib.layers.ResBlock', 'torch.nn.modules.container.Sequential', 'torch.nn.modules.activation.ReLU', 'aten.relu.default']J pkg.torch.onnx.fx_nodek%relu_6 : [num_users=2] = call_function[target=torch.ops.aten.relu.default](args = (%add_14,), kwargs = {})J pkg.torch.onnx.name_scopes['', 'vision_model.point_policy', 'vision_model.point_policy.hydra', 'vision_model.point_policy.hydra.resblock', 'vision_model.point_policy.hydra.resblock.block_b', 'vision_model.point_policy.hydra.resblock.block_b.0', 'relu_6']J -pkg.torch.onnx.stack_traceFile "/home/batman/xx3/./ml_tools/openpilot_compile/compile_supercombo.py", line 86, in forward +pkg.torch.onnx.stack_traceFile "/home/batman/xx3/./ml_tools/openpilot_compile/compile_supercombo.py", line 82, in forward return torch.cat([*self.forward_dict(inputs).values(), self.pad], dim=1) File "/home/batman/xx3/xx/training/path/supercombo.py", line 132, in forward policy_outs = self.hydra(summary_outs) @@ -3329,7 +3329,7 @@ stash_type pkg.torch.onnx.class_hierarchy['__main__.FlattenedVisionModel', 'xx.training.path.supercombo.Policy', 'xx.training.path.supercombo.Hydra', 'xx.training.lib.layers.ResBlock', 'torch.nn.modules.container.Sequential', 'torch.nn.modules.linear.Linear', 'aten.linear.default']J pkg.torch.onnx.fx_node%linear_7 : [num_users=1] = call_function[target=torch.ops.aten.linear.default](args = (%relu_6, %p_vision_model_point_policy_hydra_resblock_block_b_1_weight, %p_vision_model_point_policy_hydra_resblock_block_b_1_bias), kwargs = {})J pkg.torch.onnx.name_scopes['', 'vision_model.point_policy', 'vision_model.point_policy.hydra', 'vision_model.point_policy.hydra.resblock', 'vision_model.point_policy.hydra.resblock.block_b', 'vision_model.point_policy.hydra.resblock.block_b.1', 'linear_7']J -pkg.torch.onnx.stack_traceFile "/home/batman/xx3/./ml_tools/openpilot_compile/compile_supercombo.py", line 86, in forward +pkg.torch.onnx.stack_traceFile "/home/batman/xx3/./ml_tools/openpilot_compile/compile_supercombo.py", line 82, in forward return torch.cat([*self.forward_dict(inputs).values(), self.pad], dim=1) File "/home/batman/xx3/xx/training/path/supercombo.py", line 132, in forward policy_outs = self.hydra(summary_outs) @@ -3353,7 +3353,7 @@ stash_type pkg.torch.onnx.class_hierarchy['__main__.FlattenedVisionModel', 'xx.training.path.supercombo.Policy', 'xx.training.path.supercombo.Hydra', 'xx.training.lib.layers.ResBlock', 'torch.nn.modules.container.Sequential', 'torch.nn.modules.normalization.LayerNorm', 'aten.layer_norm.default']J pkg.torch.onnx.fx_node%layer_norm_6 : [num_users=1] = call_function[target=torch.ops.aten.layer_norm.default](args = (%linear_7, [1024], %p_vision_model_point_policy_hydra_resblock_block_b_2_weight, %p_vision_model_point_policy_hydra_resblock_block_b_2_bias), kwargs = {})J pkg.torch.onnx.name_scopes['', 'vision_model.point_policy', 'vision_model.point_policy.hydra', 'vision_model.point_policy.hydra.resblock', 'vision_model.point_policy.hydra.resblock.block_b', 'vision_model.point_policy.hydra.resblock.block_b.2', 'layer_norm_6']J -pkg.torch.onnx.stack_traceFile "/home/batman/xx3/./ml_tools/openpilot_compile/compile_supercombo.py", line 86, in forward +pkg.torch.onnx.stack_traceFile "/home/batman/xx3/./ml_tools/openpilot_compile/compile_supercombo.py", line 82, in forward return torch.cat([*self.forward_dict(inputs).values(), self.pad], dim=1) File "/home/batman/xx3/xx/training/path/supercombo.py", line 132, in forward policy_outs = self.hydra(summary_outs) @@ -3371,7 +3371,7 @@ stash_type pkg.torch.onnx.class_hierarchy['__main__.FlattenedVisionModel', 'xx.training.path.supercombo.Policy', 'xx.training.path.supercombo.Hydra', 'xx.training.lib.layers.ResBlock', 'torch.nn.modules.container.Sequential', 'torch.nn.modules.activation.ReLU', 'aten.relu.default']J pkg.torch.onnx.fx_nodeq%relu_7 : [num_users=1] = call_function[target=torch.ops.aten.relu.default](args = (%layer_norm_6,), kwargs = {})J pkg.torch.onnx.name_scopes['', 'vision_model.point_policy', 'vision_model.point_policy.hydra', 'vision_model.point_policy.hydra.resblock', 'vision_model.point_policy.hydra.resblock.block_b', 'vision_model.point_policy.hydra.resblock.block_b.3', 'relu_7']J -pkg.torch.onnx.stack_traceFile "/home/batman/xx3/./ml_tools/openpilot_compile/compile_supercombo.py", line 86, in forward +pkg.torch.onnx.stack_traceFile "/home/batman/xx3/./ml_tools/openpilot_compile/compile_supercombo.py", line 82, in forward return torch.cat([*self.forward_dict(inputs).values(), self.pad], dim=1) File "/home/batman/xx3/xx/training/path/supercombo.py", line 132, in forward policy_outs = self.hydra(summary_outs) @@ -3395,7 +3395,7 @@ stash_type pkg.torch.onnx.class_hierarchy['__main__.FlattenedVisionModel', 'xx.training.path.supercombo.Policy', 'xx.training.path.supercombo.Hydra', 'xx.training.lib.layers.ResBlock', 'torch.nn.modules.container.Sequential', 'torch.nn.modules.linear.Linear', 'aten.linear.default']J pkg.torch.onnx.fx_node%linear_8 : [num_users=1] = call_function[target=torch.ops.aten.linear.default](args = (%relu_7, %p_vision_model_point_policy_hydra_resblock_block_b_4_weight, %p_vision_model_point_policy_hydra_resblock_block_b_4_bias), kwargs = {})J pkg.torch.onnx.name_scopes['', 'vision_model.point_policy', 'vision_model.point_policy.hydra', 'vision_model.point_policy.hydra.resblock', 'vision_model.point_policy.hydra.resblock.block_b', 'vision_model.point_policy.hydra.resblock.block_b.4', 'linear_8']J -pkg.torch.onnx.stack_traceFile "/home/batman/xx3/./ml_tools/openpilot_compile/compile_supercombo.py", line 86, in forward +pkg.torch.onnx.stack_traceFile "/home/batman/xx3/./ml_tools/openpilot_compile/compile_supercombo.py", line 82, in forward return torch.cat([*self.forward_dict(inputs).values(), self.pad], dim=1) File "/home/batman/xx3/xx/training/path/supercombo.py", line 132, in forward policy_outs = self.hydra(summary_outs) @@ -3419,7 +3419,7 @@ stash_type pkg.torch.onnx.class_hierarchy['__main__.FlattenedVisionModel', 'xx.training.path.supercombo.Policy', 'xx.training.path.supercombo.Hydra', 'xx.training.lib.layers.ResBlock', 'torch.nn.modules.container.Sequential', 'torch.nn.modules.normalization.LayerNorm', 'aten.layer_norm.default']J pkg.torch.onnx.fx_node%layer_norm_7 : [num_users=1] = call_function[target=torch.ops.aten.layer_norm.default](args = (%linear_8, [512], %p_vision_model_point_policy_hydra_resblock_block_b_5_weight, %p_vision_model_point_policy_hydra_resblock_block_b_5_bias), kwargs = {})J pkg.torch.onnx.name_scopes['', 'vision_model.point_policy', 'vision_model.point_policy.hydra', 'vision_model.point_policy.hydra.resblock', 'vision_model.point_policy.hydra.resblock.block_b', 'vision_model.point_policy.hydra.resblock.block_b.5', 'layer_norm_7']J -pkg.torch.onnx.stack_traceFile "/home/batman/xx3/./ml_tools/openpilot_compile/compile_supercombo.py", line 86, in forward +pkg.torch.onnx.stack_traceFile "/home/batman/xx3/./ml_tools/openpilot_compile/compile_supercombo.py", line 82, in forward return torch.cat([*self.forward_dict(inputs).values(), self.pad], dim=1) File "/home/batman/xx3/xx/training/path/supercombo.py", line 132, in forward policy_outs = self.hydra(summary_outs) @@ -3439,7 +3439,7 @@ stash_type pkg.torch.onnx.class_hierarchy['__main__.FlattenedVisionModel', 'xx.training.path.supercombo.Policy', 'xx.training.path.supercombo.Hydra', 'xx.training.lib.layers.ResBlock', 'aten.add.Tensor']J pkg.torch.onnx.fx_nodew%add_15 : [num_users=1] = call_function[target=torch.ops.aten.add.Tensor](args = (%relu_6, %layer_norm_7), kwargs = {})J pkg.torch.onnx.name_scopesz['', 'vision_model.point_policy', 'vision_model.point_policy.hydra', 'vision_model.point_policy.hydra.resblock', 'add_15']J -pkg.torch.onnx.stack_traceFile "/home/batman/xx3/./ml_tools/openpilot_compile/compile_supercombo.py", line 86, in forward +pkg.torch.onnx.stack_traceFile "/home/batman/xx3/./ml_tools/openpilot_compile/compile_supercombo.py", line 82, in forward return torch.cat([*self.forward_dict(inputs).values(), self.pad], dim=1) File "/home/batman/xx3/xx/training/path/supercombo.py", line 132, in forward policy_outs = self.hydra(summary_outs) @@ -3453,7 +3453,7 @@ stash_type pkg.torch.onnx.class_hierarchy['__main__.FlattenedVisionModel', 'xx.training.path.supercombo.Policy', 'xx.training.path.supercombo.Hydra', 'xx.training.lib.layers.ResBlock', 'torch.nn.modules.activation.ReLU', 'aten.relu.default']J pkg.torch.onnx.fx_nodek%relu_8 : [num_users=5] = call_function[target=torch.ops.aten.relu.default](args = (%add_15,), kwargs = {})J pkg.torch.onnx.name_scopes['', 'vision_model.point_policy', 'vision_model.point_policy.hydra', 'vision_model.point_policy.hydra.resblock', 'vision_model.point_policy.hydra.resblock.final_relu', 'relu_8']J -pkg.torch.onnx.stack_traceFile "/home/batman/xx3/./ml_tools/openpilot_compile/compile_supercombo.py", line 86, in forward +pkg.torch.onnx.stack_traceFile "/home/batman/xx3/./ml_tools/openpilot_compile/compile_supercombo.py", line 82, in forward return torch.cat([*self.forward_dict(inputs).values(), self.pad], dim=1) File "/home/batman/xx3/xx/training/path/supercombo.py", line 132, in forward policy_outs = self.hydra(summary_outs) @@ -3475,7 +3475,7 @@ stash_type pkg.torch.onnx.class_hierarchy['__main__.FlattenedVisionModel', 'xx.training.path.supercombo.Policy', 'xx.training.path.supercombo.Hydra', 'torch.nn.modules.linear.Linear', 'aten.linear.default']J pkg.torch.onnx.fx_node%linear_9 : [num_users=1] = call_function[target=torch.ops.aten.linear.default](args = (%clone_25, %p_vision_model_point_policy_hydra_in_layer_meta_weight, %p_vision_model_point_policy_hydra_in_layer_meta_bias), kwargs = {})J pkg.torch.onnx.name_scopes['', 'vision_model.point_policy', 'vision_model.point_policy.hydra', 'vision_model.point_policy.hydra.in_layer.meta', 'linear_9']J -pkg.torch.onnx.stack_traceFile "/home/batman/xx3/./ml_tools/openpilot_compile/compile_supercombo.py", line 86, in forward +pkg.torch.onnx.stack_traceFile "/home/batman/xx3/./ml_tools/openpilot_compile/compile_supercombo.py", line 82, in forward return torch.cat([*self.forward_dict(inputs).values(), self.pad], dim=1) File "/home/batman/xx3/xx/training/path/supercombo.py", line 132, in forward policy_outs = self.hydra(summary_outs) @@ -3489,7 +3489,7 @@ stash_type pkg.torch.onnx.class_hierarchy['__main__.FlattenedVisionModel', 'xx.training.path.supercombo.Policy', 'xx.training.path.supercombo.Hydra', 'torch.nn.modules.activation.ReLU', 'aten.relu.default']J pkg.torch.onnx.fx_nodem%relu_9 : [num_users=2] = call_function[target=torch.ops.aten.relu.default](args = (%linear_9,), kwargs = {})J pkg.torch.onnx.name_scopesv['', 'vision_model.point_policy', 'vision_model.point_policy.hydra', 'vision_model.point_policy.hydra.relu', 'relu_9']J -pkg.torch.onnx.stack_traceFile "/home/batman/xx3/./ml_tools/openpilot_compile/compile_supercombo.py", line 86, in forward +pkg.torch.onnx.stack_traceFile "/home/batman/xx3/./ml_tools/openpilot_compile/compile_supercombo.py", line 82, in forward return torch.cat([*self.forward_dict(inputs).values(), self.pad], dim=1) File "/home/batman/xx3/xx/training/path/supercombo.py", line 132, in forward policy_outs = self.hydra(summary_outs) @@ -3509,7 +3509,7 @@ stash_type pkg.torch.onnx.class_hierarchy['__main__.FlattenedVisionModel', 'xx.training.path.supercombo.Policy', 'xx.training.path.supercombo.Hydra', 'torch.nn.modules.linear.Linear', 'aten.linear.default']J pkg.torch.onnx.fx_node%linear_10 : [num_users=1] = call_function[target=torch.ops.aten.linear.default](args = (%clone_26, %p_vision_model_point_policy_hydra_in_layer_desire_pred_weight, %p_vision_model_point_policy_hydra_in_layer_desire_pred_bias), kwargs = {})J pkg.torch.onnx.name_scopes['', 'vision_model.point_policy', 'vision_model.point_policy.hydra', 'vision_model.point_policy.hydra.in_layer.desire_pred', 'linear_10']J -pkg.torch.onnx.stack_traceFile "/home/batman/xx3/./ml_tools/openpilot_compile/compile_supercombo.py", line 86, in forward +pkg.torch.onnx.stack_traceFile "/home/batman/xx3/./ml_tools/openpilot_compile/compile_supercombo.py", line 82, in forward return torch.cat([*self.forward_dict(inputs).values(), self.pad], dim=1) File "/home/batman/xx3/xx/training/path/supercombo.py", line 132, in forward policy_outs = self.hydra(summary_outs) @@ -3523,7 +3523,7 @@ stash_type pkg.torch.onnx.class_hierarchy['__main__.FlattenedVisionModel', 'xx.training.path.supercombo.Policy', 'xx.training.path.supercombo.Hydra', 'torch.nn.modules.activation.ReLU', 'aten.relu.default']J pkg.torch.onnx.fx_nodeo%relu_10 : [num_users=2] = call_function[target=torch.ops.aten.relu.default](args = (%linear_10,), kwargs = {})J pkg.torch.onnx.name_scopesw['', 'vision_model.point_policy', 'vision_model.point_policy.hydra', 'vision_model.point_policy.hydra.relu', 'relu_10']J -pkg.torch.onnx.stack_traceFile "/home/batman/xx3/./ml_tools/openpilot_compile/compile_supercombo.py", line 86, in forward +pkg.torch.onnx.stack_traceFile "/home/batman/xx3/./ml_tools/openpilot_compile/compile_supercombo.py", line 82, in forward return torch.cat([*self.forward_dict(inputs).values(), self.pad], dim=1) File "/home/batman/xx3/xx/training/path/supercombo.py", line 132, in forward policy_outs = self.hydra(summary_outs) @@ -3543,7 +3543,7 @@ stash_type pkg.torch.onnx.class_hierarchy['__main__.FlattenedVisionModel', 'xx.training.path.supercombo.Policy', 'xx.training.path.supercombo.Hydra', 'torch.nn.modules.linear.Linear', 'aten.linear.default']J pkg.torch.onnx.fx_node%linear_11 : [num_users=1] = call_function[target=torch.ops.aten.linear.default](args = (%clone_27, %p_vision_model_point_policy_hydra_in_layer_road_transform_weight, %p_vision_model_point_policy_hydra_in_layer_road_transform_bias), kwargs = {})J pkg.torch.onnx.name_scopes['', 'vision_model.point_policy', 'vision_model.point_policy.hydra', 'vision_model.point_policy.hydra.in_layer.road_transform', 'linear_11']J -pkg.torch.onnx.stack_traceFile "/home/batman/xx3/./ml_tools/openpilot_compile/compile_supercombo.py", line 86, in forward +pkg.torch.onnx.stack_traceFile "/home/batman/xx3/./ml_tools/openpilot_compile/compile_supercombo.py", line 82, in forward return torch.cat([*self.forward_dict(inputs).values(), self.pad], dim=1) File "/home/batman/xx3/xx/training/path/supercombo.py", line 132, in forward policy_outs = self.hydra(summary_outs) @@ -3557,7 +3557,7 @@ stash_type pkg.torch.onnx.class_hierarchy['__main__.FlattenedVisionModel', 'xx.training.path.supercombo.Policy', 'xx.training.path.supercombo.Hydra', 'torch.nn.modules.activation.ReLU', 'aten.relu.default']J pkg.torch.onnx.fx_nodeo%relu_11 : [num_users=2] = call_function[target=torch.ops.aten.relu.default](args = (%linear_11,), kwargs = {})J pkg.torch.onnx.name_scopesw['', 'vision_model.point_policy', 'vision_model.point_policy.hydra', 'vision_model.point_policy.hydra.relu', 'relu_11']J -pkg.torch.onnx.stack_traceFile "/home/batman/xx3/./ml_tools/openpilot_compile/compile_supercombo.py", line 86, in forward +pkg.torch.onnx.stack_traceFile "/home/batman/xx3/./ml_tools/openpilot_compile/compile_supercombo.py", line 82, in forward return torch.cat([*self.forward_dict(inputs).values(), self.pad], dim=1) File "/home/batman/xx3/xx/training/path/supercombo.py", line 132, in forward policy_outs = self.hydra(summary_outs) @@ -3577,7 +3577,7 @@ stash_type pkg.torch.onnx.class_hierarchy['__main__.FlattenedVisionModel', 'xx.training.path.supercombo.Policy', 'xx.training.path.supercombo.Hydra', 'torch.nn.modules.linear.Linear', 'aten.linear.default']J pkg.torch.onnx.fx_node%linear_12 : [num_users=1] = call_function[target=torch.ops.aten.linear.default](args = (%clone_28, %p_vision_model_point_policy_hydra_in_layer_pose_weight, %p_vision_model_point_policy_hydra_in_layer_pose_bias), kwargs = {})J pkg.torch.onnx.name_scopes['', 'vision_model.point_policy', 'vision_model.point_policy.hydra', 'vision_model.point_policy.hydra.in_layer.pose', 'linear_12']J -pkg.torch.onnx.stack_traceFile "/home/batman/xx3/./ml_tools/openpilot_compile/compile_supercombo.py", line 86, in forward +pkg.torch.onnx.stack_traceFile "/home/batman/xx3/./ml_tools/openpilot_compile/compile_supercombo.py", line 82, in forward return torch.cat([*self.forward_dict(inputs).values(), self.pad], dim=1) File "/home/batman/xx3/xx/training/path/supercombo.py", line 132, in forward policy_outs = self.hydra(summary_outs) @@ -3591,7 +3591,7 @@ stash_type pkg.torch.onnx.class_hierarchy['__main__.FlattenedVisionModel', 'xx.training.path.supercombo.Policy', 'xx.training.path.supercombo.Hydra', 'torch.nn.modules.activation.ReLU', 'aten.relu.default']J pkg.torch.onnx.fx_nodeo%relu_12 : [num_users=2] = call_function[target=torch.ops.aten.relu.default](args = (%linear_12,), kwargs = {})J pkg.torch.onnx.name_scopesw['', 'vision_model.point_policy', 'vision_model.point_policy.hydra', 'vision_model.point_policy.hydra.relu', 'relu_12']J -pkg.torch.onnx.stack_traceFile "/home/batman/xx3/./ml_tools/openpilot_compile/compile_supercombo.py", line 86, in forward +pkg.torch.onnx.stack_traceFile "/home/batman/xx3/./ml_tools/openpilot_compile/compile_supercombo.py", line 82, in forward return torch.cat([*self.forward_dict(inputs).values(), self.pad], dim=1) File "/home/batman/xx3/xx/training/path/supercombo.py", line 132, in forward policy_outs = self.hydra(summary_outs) @@ -3611,7 +3611,7 @@ Dvision_model.point_policy.hydra.in_layer.wide_from_device_euler.bias linear_13 pkg.torch.onnx.class_hierarchy['__main__.FlattenedVisionModel', 'xx.training.path.supercombo.Policy', 'xx.training.path.supercombo.Hydra', 'torch.nn.modules.linear.Linear', 'aten.linear.default']J pkg.torch.onnx.fx_node%linear_13 : [num_users=1] = call_function[target=torch.ops.aten.linear.default](args = (%clone_29, %p_vision_model_point_policy_hydra_in_layer_wide_from_device_euler_weight, %p_vision_model_point_policy_hydra_in_layer_wide_from_device_euler_bias), kwargs = {})J pkg.torch.onnx.name_scopes['', 'vision_model.point_policy', 'vision_model.point_policy.hydra', 'vision_model.point_policy.hydra.in_layer.wide_from_device_euler', 'linear_13']J -pkg.torch.onnx.stack_traceFile "/home/batman/xx3/./ml_tools/openpilot_compile/compile_supercombo.py", line 86, in forward +pkg.torch.onnx.stack_traceFile "/home/batman/xx3/./ml_tools/openpilot_compile/compile_supercombo.py", line 82, in forward return torch.cat([*self.forward_dict(inputs).values(), self.pad], dim=1) File "/home/batman/xx3/xx/training/path/supercombo.py", line 132, in forward policy_outs = self.hydra(summary_outs) @@ -3625,7 +3625,7 @@ Dvision_model.point_policy.hydra.in_layer.wide_from_device_euler.bias linear_13 pkg.torch.onnx.class_hierarchy['__main__.FlattenedVisionModel', 'xx.training.path.supercombo.Policy', 'xx.training.path.supercombo.Hydra', 'torch.nn.modules.activation.ReLU', 'aten.relu.default']J pkg.torch.onnx.fx_nodeo%relu_13 : [num_users=2] = call_function[target=torch.ops.aten.relu.default](args = (%linear_13,), kwargs = {})J pkg.torch.onnx.name_scopesw['', 'vision_model.point_policy', 'vision_model.point_policy.hydra', 'vision_model.point_policy.hydra.relu', 'relu_13']J -pkg.torch.onnx.stack_traceFile "/home/batman/xx3/./ml_tools/openpilot_compile/compile_supercombo.py", line 86, in forward +pkg.torch.onnx.stack_traceFile "/home/batman/xx3/./ml_tools/openpilot_compile/compile_supercombo.py", line 82, in forward return torch.cat([*self.forward_dict(inputs).values(), self.pad], dim=1) File "/home/batman/xx3/xx/training/path/supercombo.py", line 132, in forward policy_outs = self.hydra(summary_outs) @@ -3645,7 +3645,7 @@ Dvision_model.point_policy.hydra.in_layer.wide_from_device_euler.bias linear_13 pkg.torch.onnx.class_hierarchy['__main__.FlattenedVisionModel', 'xx.training.path.supercombo.Policy', 'xx.training.path.supercombo.Hydra', 'torch.nn.modules.container.Sequential', 'torch.nn.modules.linear.Linear', 'aten.linear.default']J pkg.torch.onnx.fx_node%linear_14 : [num_users=1] = call_function[target=torch.ops.aten.linear.default](args = (%relu_9, %p_vision_model_point_policy_hydra_res_layer_meta_0_weight, %p_vision_model_point_policy_hydra_res_layer_meta_0_bias), kwargs = {})J pkg.torch.onnx.name_scopes['', 'vision_model.point_policy', 'vision_model.point_policy.hydra', 'vision_model.point_policy.hydra.res_layer.meta', 'vision_model.point_policy.hydra.res_layer.meta.0', 'linear_14']J -pkg.torch.onnx.stack_traceFile "/home/batman/xx3/./ml_tools/openpilot_compile/compile_supercombo.py", line 86, in forward +pkg.torch.onnx.stack_traceFile "/home/batman/xx3/./ml_tools/openpilot_compile/compile_supercombo.py", line 82, in forward return torch.cat([*self.forward_dict(inputs).values(), self.pad], dim=1) File "/home/batman/xx3/xx/training/path/supercombo.py", line 132, in forward policy_outs = self.hydra(summary_outs) @@ -3661,7 +3661,7 @@ Dvision_model.point_policy.hydra.in_layer.wide_from_device_euler.bias linear_13 pkg.torch.onnx.class_hierarchy['__main__.FlattenedVisionModel', 'xx.training.path.supercombo.Policy', 'xx.training.path.supercombo.Hydra', 'torch.nn.modules.container.Sequential', 'torch.nn.modules.activation.ReLU', 'aten.relu.default']J pkg.torch.onnx.fx_nodeo%relu_14 : [num_users=1] = call_function[target=torch.ops.aten.relu.default](args = (%linear_14,), kwargs = {})J pkg.torch.onnx.name_scopes['', 'vision_model.point_policy', 'vision_model.point_policy.hydra', 'vision_model.point_policy.hydra.res_layer.meta', 'vision_model.point_policy.hydra.res_layer.meta.1', 'relu_14']J -pkg.torch.onnx.stack_traceFile "/home/batman/xx3/./ml_tools/openpilot_compile/compile_supercombo.py", line 86, in forward +pkg.torch.onnx.stack_traceFile "/home/batman/xx3/./ml_tools/openpilot_compile/compile_supercombo.py", line 82, in forward return torch.cat([*self.forward_dict(inputs).values(), self.pad], dim=1) File "/home/batman/xx3/xx/training/path/supercombo.py", line 132, in forward policy_outs = self.hydra(summary_outs) @@ -3683,7 +3683,7 @@ Dvision_model.point_policy.hydra.in_layer.wide_from_device_euler.bias linear_13 pkg.torch.onnx.class_hierarchy['__main__.FlattenedVisionModel', 'xx.training.path.supercombo.Policy', 'xx.training.path.supercombo.Hydra', 'torch.nn.modules.container.Sequential', 'torch.nn.modules.linear.Linear', 'aten.linear.default']J pkg.torch.onnx.fx_node%linear_15 : [num_users=1] = call_function[target=torch.ops.aten.linear.default](args = (%relu_14, %p_vision_model_point_policy_hydra_res_layer_meta_2_weight, %p_vision_model_point_policy_hydra_res_layer_meta_2_bias), kwargs = {})J pkg.torch.onnx.name_scopes['', 'vision_model.point_policy', 'vision_model.point_policy.hydra', 'vision_model.point_policy.hydra.res_layer.meta', 'vision_model.point_policy.hydra.res_layer.meta.2', 'linear_15']J -pkg.torch.onnx.stack_traceFile "/home/batman/xx3/./ml_tools/openpilot_compile/compile_supercombo.py", line 86, in forward +pkg.torch.onnx.stack_traceFile "/home/batman/xx3/./ml_tools/openpilot_compile/compile_supercombo.py", line 82, in forward return torch.cat([*self.forward_dict(inputs).values(), self.pad], dim=1) File "/home/batman/xx3/xx/training/path/supercombo.py", line 132, in forward policy_outs = self.hydra(summary_outs) @@ -3700,7 +3700,7 @@ Dvision_model.point_policy.hydra.in_layer.wide_from_device_euler.bias linear_13 pkg.torch.onnx.class_hierarchy['__main__.FlattenedVisionModel', 'xx.training.path.supercombo.Policy', 'xx.training.path.supercombo.Hydra', 'aten.add.Tensor']J pkg.torch.onnx.fx_nodet%add_16 : [num_users=1] = call_function[target=torch.ops.aten.add.Tensor](args = (%relu_9, %linear_15), kwargs = {})Jl pkg.torch.onnx.name_scopesN['', 'vision_model.point_policy', 'vision_model.point_policy.hydra', 'add_16']J -pkg.torch.onnx.stack_traceFile "/home/batman/xx3/./ml_tools/openpilot_compile/compile_supercombo.py", line 86, in forward +pkg.torch.onnx.stack_traceFile "/home/batman/xx3/./ml_tools/openpilot_compile/compile_supercombo.py", line 82, in forward return torch.cat([*self.forward_dict(inputs).values(), self.pad], dim=1) File "/home/batman/xx3/xx/training/path/supercombo.py", line 132, in forward policy_outs = self.hydra(summary_outs) @@ -3712,7 +3712,7 @@ Dvision_model.point_policy.hydra.in_layer.wide_from_device_euler.bias linear_13 pkg.torch.onnx.class_hierarchy['__main__.FlattenedVisionModel', 'xx.training.path.supercombo.Policy', 'xx.training.path.supercombo.Hydra', 'torch.nn.modules.activation.ReLU', 'aten.relu.default']J pkg.torch.onnx.fx_nodel%relu_15 : [num_users=1] = call_function[target=torch.ops.aten.relu.default](args = (%add_16,), kwargs = {})J pkg.torch.onnx.name_scopesw['', 'vision_model.point_policy', 'vision_model.point_policy.hydra', 'vision_model.point_policy.hydra.relu', 'relu_15']J -pkg.torch.onnx.stack_traceFile "/home/batman/xx3/./ml_tools/openpilot_compile/compile_supercombo.py", line 86, in forward +pkg.torch.onnx.stack_traceFile "/home/batman/xx3/./ml_tools/openpilot_compile/compile_supercombo.py", line 82, in forward return torch.cat([*self.forward_dict(inputs).values(), self.pad], dim=1) File "/home/batman/xx3/xx/training/path/supercombo.py", line 132, in forward policy_outs = self.hydra(summary_outs) @@ -3732,7 +3732,7 @@ Dvision_model.point_policy.hydra.in_layer.wide_from_device_euler.bias linear_13 pkg.torch.onnx.class_hierarchy['__main__.FlattenedVisionModel', 'xx.training.path.supercombo.Policy', 'xx.training.path.supercombo.Hydra', 'torch.nn.modules.container.Sequential', 'torch.nn.modules.linear.Linear', 'aten.linear.default']J pkg.torch.onnx.fx_node%linear_16 : [num_users=1] = call_function[target=torch.ops.aten.linear.default](args = (%relu_10, %p_vision_model_point_policy_hydra_res_layer_desire_pred_0_weight, %p_vision_model_point_policy_hydra_res_layer_desire_pred_0_bias), kwargs = {})J pkg.torch.onnx.name_scopes['', 'vision_model.point_policy', 'vision_model.point_policy.hydra', 'vision_model.point_policy.hydra.res_layer.desire_pred', 'vision_model.point_policy.hydra.res_layer.desire_pred.0', 'linear_16']J -pkg.torch.onnx.stack_traceFile "/home/batman/xx3/./ml_tools/openpilot_compile/compile_supercombo.py", line 86, in forward +pkg.torch.onnx.stack_traceFile "/home/batman/xx3/./ml_tools/openpilot_compile/compile_supercombo.py", line 82, in forward return torch.cat([*self.forward_dict(inputs).values(), self.pad], dim=1) File "/home/batman/xx3/xx/training/path/supercombo.py", line 132, in forward policy_outs = self.hydra(summary_outs) @@ -3748,7 +3748,7 @@ Dvision_model.point_policy.hydra.in_layer.wide_from_device_euler.bias linear_13 pkg.torch.onnx.class_hierarchy['__main__.FlattenedVisionModel', 'xx.training.path.supercombo.Policy', 'xx.training.path.supercombo.Hydra', 'torch.nn.modules.container.Sequential', 'torch.nn.modules.activation.ReLU', 'aten.relu.default']J pkg.torch.onnx.fx_nodeo%relu_16 : [num_users=1] = call_function[target=torch.ops.aten.relu.default](args = (%linear_16,), kwargs = {})J pkg.torch.onnx.name_scopes['', 'vision_model.point_policy', 'vision_model.point_policy.hydra', 'vision_model.point_policy.hydra.res_layer.desire_pred', 'vision_model.point_policy.hydra.res_layer.desire_pred.1', 'relu_16']J -pkg.torch.onnx.stack_traceFile "/home/batman/xx3/./ml_tools/openpilot_compile/compile_supercombo.py", line 86, in forward +pkg.torch.onnx.stack_traceFile "/home/batman/xx3/./ml_tools/openpilot_compile/compile_supercombo.py", line 82, in forward return torch.cat([*self.forward_dict(inputs).values(), self.pad], dim=1) File "/home/batman/xx3/xx/training/path/supercombo.py", line 132, in forward policy_outs = self.hydra(summary_outs) @@ -3770,7 +3770,7 @@ Dvision_model.point_policy.hydra.in_layer.wide_from_device_euler.bias linear_13 pkg.torch.onnx.class_hierarchy['__main__.FlattenedVisionModel', 'xx.training.path.supercombo.Policy', 'xx.training.path.supercombo.Hydra', 'torch.nn.modules.container.Sequential', 'torch.nn.modules.linear.Linear', 'aten.linear.default']J pkg.torch.onnx.fx_node%linear_17 : [num_users=1] = call_function[target=torch.ops.aten.linear.default](args = (%relu_16, %p_vision_model_point_policy_hydra_res_layer_desire_pred_2_weight, %p_vision_model_point_policy_hydra_res_layer_desire_pred_2_bias), kwargs = {})J pkg.torch.onnx.name_scopes['', 'vision_model.point_policy', 'vision_model.point_policy.hydra', 'vision_model.point_policy.hydra.res_layer.desire_pred', 'vision_model.point_policy.hydra.res_layer.desire_pred.2', 'linear_17']J -pkg.torch.onnx.stack_traceFile "/home/batman/xx3/./ml_tools/openpilot_compile/compile_supercombo.py", line 86, in forward +pkg.torch.onnx.stack_traceFile "/home/batman/xx3/./ml_tools/openpilot_compile/compile_supercombo.py", line 82, in forward return torch.cat([*self.forward_dict(inputs).values(), self.pad], dim=1) File "/home/batman/xx3/xx/training/path/supercombo.py", line 132, in forward policy_outs = self.hydra(summary_outs) @@ -3787,7 +3787,7 @@ Dvision_model.point_policy.hydra.in_layer.wide_from_device_euler.bias linear_13 pkg.torch.onnx.class_hierarchy['__main__.FlattenedVisionModel', 'xx.training.path.supercombo.Policy', 'xx.training.path.supercombo.Hydra', 'aten.add.Tensor']J pkg.torch.onnx.fx_nodeu%add_17 : [num_users=1] = call_function[target=torch.ops.aten.add.Tensor](args = (%relu_10, %linear_17), kwargs = {})Jl pkg.torch.onnx.name_scopesN['', 'vision_model.point_policy', 'vision_model.point_policy.hydra', 'add_17']J -pkg.torch.onnx.stack_traceFile "/home/batman/xx3/./ml_tools/openpilot_compile/compile_supercombo.py", line 86, in forward +pkg.torch.onnx.stack_traceFile "/home/batman/xx3/./ml_tools/openpilot_compile/compile_supercombo.py", line 82, in forward return torch.cat([*self.forward_dict(inputs).values(), self.pad], dim=1) File "/home/batman/xx3/xx/training/path/supercombo.py", line 132, in forward policy_outs = self.hydra(summary_outs) @@ -3799,7 +3799,7 @@ Dvision_model.point_policy.hydra.in_layer.wide_from_device_euler.bias linear_13 pkg.torch.onnx.class_hierarchy['__main__.FlattenedVisionModel', 'xx.training.path.supercombo.Policy', 'xx.training.path.supercombo.Hydra', 'torch.nn.modules.activation.ReLU', 'aten.relu.default']J pkg.torch.onnx.fx_nodel%relu_17 : [num_users=1] = call_function[target=torch.ops.aten.relu.default](args = (%add_17,), kwargs = {})J pkg.torch.onnx.name_scopesw['', 'vision_model.point_policy', 'vision_model.point_policy.hydra', 'vision_model.point_policy.hydra.relu', 'relu_17']J -pkg.torch.onnx.stack_traceFile "/home/batman/xx3/./ml_tools/openpilot_compile/compile_supercombo.py", line 86, in forward +pkg.torch.onnx.stack_traceFile "/home/batman/xx3/./ml_tools/openpilot_compile/compile_supercombo.py", line 82, in forward return torch.cat([*self.forward_dict(inputs).values(), self.pad], dim=1) File "/home/batman/xx3/xx/training/path/supercombo.py", line 132, in forward policy_outs = self.hydra(summary_outs) @@ -3819,7 +3819,7 @@ Avision_model.point_policy.hydra.res_layer.road_transform.0.weight pkg.torch.onnx.class_hierarchy['__main__.FlattenedVisionModel', 'xx.training.path.supercombo.Policy', 'xx.training.path.supercombo.Hydra', 'torch.nn.modules.container.Sequential', 'torch.nn.modules.linear.Linear', 'aten.linear.default']J pkg.torch.onnx.fx_node%linear_18 : [num_users=1] = call_function[target=torch.ops.aten.linear.default](args = (%relu_11, %p_vision_model_point_policy_hydra_res_layer_road_transform_0_weight, %p_vision_model_point_policy_hydra_res_layer_road_transform_0_bias), kwargs = {})J pkg.torch.onnx.name_scopes['', 'vision_model.point_policy', 'vision_model.point_policy.hydra', 'vision_model.point_policy.hydra.res_layer.road_transform', 'vision_model.point_policy.hydra.res_layer.road_transform.0', 'linear_18']J -pkg.torch.onnx.stack_traceFile "/home/batman/xx3/./ml_tools/openpilot_compile/compile_supercombo.py", line 86, in forward +pkg.torch.onnx.stack_traceFile "/home/batman/xx3/./ml_tools/openpilot_compile/compile_supercombo.py", line 82, in forward return torch.cat([*self.forward_dict(inputs).values(), self.pad], dim=1) File "/home/batman/xx3/xx/training/path/supercombo.py", line 132, in forward policy_outs = self.hydra(summary_outs) @@ -3835,7 +3835,7 @@ Avision_model.point_policy.hydra.res_layer.road_transform.0.weight pkg.torch.onnx.class_hierarchy['__main__.FlattenedVisionModel', 'xx.training.path.supercombo.Policy', 'xx.training.path.supercombo.Hydra', 'torch.nn.modules.container.Sequential', 'torch.nn.modules.activation.ReLU', 'aten.relu.default']J pkg.torch.onnx.fx_nodeo%relu_18 : [num_users=1] = call_function[target=torch.ops.aten.relu.default](args = (%linear_18,), kwargs = {})J pkg.torch.onnx.name_scopes['', 'vision_model.point_policy', 'vision_model.point_policy.hydra', 'vision_model.point_policy.hydra.res_layer.road_transform', 'vision_model.point_policy.hydra.res_layer.road_transform.1', 'relu_18']J -pkg.torch.onnx.stack_traceFile "/home/batman/xx3/./ml_tools/openpilot_compile/compile_supercombo.py", line 86, in forward +pkg.torch.onnx.stack_traceFile "/home/batman/xx3/./ml_tools/openpilot_compile/compile_supercombo.py", line 82, in forward return torch.cat([*self.forward_dict(inputs).values(), self.pad], dim=1) File "/home/batman/xx3/xx/training/path/supercombo.py", line 132, in forward policy_outs = self.hydra(summary_outs) @@ -3857,7 +3857,7 @@ Avision_model.point_policy.hydra.res_layer.road_transform.2.weight pkg.torch.onnx.class_hierarchy['__main__.FlattenedVisionModel', 'xx.training.path.supercombo.Policy', 'xx.training.path.supercombo.Hydra', 'torch.nn.modules.container.Sequential', 'torch.nn.modules.linear.Linear', 'aten.linear.default']J pkg.torch.onnx.fx_node%linear_19 : [num_users=1] = call_function[target=torch.ops.aten.linear.default](args = (%relu_18, %p_vision_model_point_policy_hydra_res_layer_road_transform_2_weight, %p_vision_model_point_policy_hydra_res_layer_road_transform_2_bias), kwargs = {})J pkg.torch.onnx.name_scopes['', 'vision_model.point_policy', 'vision_model.point_policy.hydra', 'vision_model.point_policy.hydra.res_layer.road_transform', 'vision_model.point_policy.hydra.res_layer.road_transform.2', 'linear_19']J -pkg.torch.onnx.stack_traceFile "/home/batman/xx3/./ml_tools/openpilot_compile/compile_supercombo.py", line 86, in forward +pkg.torch.onnx.stack_traceFile "/home/batman/xx3/./ml_tools/openpilot_compile/compile_supercombo.py", line 82, in forward return torch.cat([*self.forward_dict(inputs).values(), self.pad], dim=1) File "/home/batman/xx3/xx/training/path/supercombo.py", line 132, in forward policy_outs = self.hydra(summary_outs) @@ -3874,7 +3874,7 @@ Avision_model.point_policy.hydra.res_layer.road_transform.2.weight pkg.torch.onnx.class_hierarchy['__main__.FlattenedVisionModel', 'xx.training.path.supercombo.Policy', 'xx.training.path.supercombo.Hydra', 'aten.add.Tensor']J pkg.torch.onnx.fx_nodeu%add_18 : [num_users=1] = call_function[target=torch.ops.aten.add.Tensor](args = (%relu_11, %linear_19), kwargs = {})Jl pkg.torch.onnx.name_scopesN['', 'vision_model.point_policy', 'vision_model.point_policy.hydra', 'add_18']J -pkg.torch.onnx.stack_traceFile "/home/batman/xx3/./ml_tools/openpilot_compile/compile_supercombo.py", line 86, in forward +pkg.torch.onnx.stack_traceFile "/home/batman/xx3/./ml_tools/openpilot_compile/compile_supercombo.py", line 82, in forward return torch.cat([*self.forward_dict(inputs).values(), self.pad], dim=1) File "/home/batman/xx3/xx/training/path/supercombo.py", line 132, in forward policy_outs = self.hydra(summary_outs) @@ -3886,7 +3886,7 @@ Avision_model.point_policy.hydra.res_layer.road_transform.2.weight pkg.torch.onnx.class_hierarchy['__main__.FlattenedVisionModel', 'xx.training.path.supercombo.Policy', 'xx.training.path.supercombo.Hydra', 'torch.nn.modules.activation.ReLU', 'aten.relu.default']J pkg.torch.onnx.fx_nodel%relu_19 : [num_users=1] = call_function[target=torch.ops.aten.relu.default](args = (%add_18,), kwargs = {})J pkg.torch.onnx.name_scopesw['', 'vision_model.point_policy', 'vision_model.point_policy.hydra', 'vision_model.point_policy.hydra.relu', 'relu_19']J -pkg.torch.onnx.stack_traceFile "/home/batman/xx3/./ml_tools/openpilot_compile/compile_supercombo.py", line 86, in forward +pkg.torch.onnx.stack_traceFile "/home/batman/xx3/./ml_tools/openpilot_compile/compile_supercombo.py", line 82, in forward return torch.cat([*self.forward_dict(inputs).values(), self.pad], dim=1) File "/home/batman/xx3/xx/training/path/supercombo.py", line 132, in forward policy_outs = self.hydra(summary_outs) @@ -3906,7 +3906,7 @@ Avision_model.point_policy.hydra.res_layer.road_transform.2.weight pkg.torch.onnx.class_hierarchy['__main__.FlattenedVisionModel', 'xx.training.path.supercombo.Policy', 'xx.training.path.supercombo.Hydra', 'torch.nn.modules.container.Sequential', 'torch.nn.modules.linear.Linear', 'aten.linear.default']J pkg.torch.onnx.fx_node%linear_20 : [num_users=1] = call_function[target=torch.ops.aten.linear.default](args = (%relu_12, %p_vision_model_point_policy_hydra_res_layer_pose_0_weight, %p_vision_model_point_policy_hydra_res_layer_pose_0_bias), kwargs = {})J pkg.torch.onnx.name_scopes['', 'vision_model.point_policy', 'vision_model.point_policy.hydra', 'vision_model.point_policy.hydra.res_layer.pose', 'vision_model.point_policy.hydra.res_layer.pose.0', 'linear_20']J -pkg.torch.onnx.stack_traceFile "/home/batman/xx3/./ml_tools/openpilot_compile/compile_supercombo.py", line 86, in forward +pkg.torch.onnx.stack_traceFile "/home/batman/xx3/./ml_tools/openpilot_compile/compile_supercombo.py", line 82, in forward return torch.cat([*self.forward_dict(inputs).values(), self.pad], dim=1) File "/home/batman/xx3/xx/training/path/supercombo.py", line 132, in forward policy_outs = self.hydra(summary_outs) @@ -3922,7 +3922,7 @@ Avision_model.point_policy.hydra.res_layer.road_transform.2.weight pkg.torch.onnx.class_hierarchy['__main__.FlattenedVisionModel', 'xx.training.path.supercombo.Policy', 'xx.training.path.supercombo.Hydra', 'torch.nn.modules.container.Sequential', 'torch.nn.modules.activation.ReLU', 'aten.relu.default']J pkg.torch.onnx.fx_nodeo%relu_20 : [num_users=1] = call_function[target=torch.ops.aten.relu.default](args = (%linear_20,), kwargs = {})J pkg.torch.onnx.name_scopes['', 'vision_model.point_policy', 'vision_model.point_policy.hydra', 'vision_model.point_policy.hydra.res_layer.pose', 'vision_model.point_policy.hydra.res_layer.pose.1', 'relu_20']J -pkg.torch.onnx.stack_traceFile "/home/batman/xx3/./ml_tools/openpilot_compile/compile_supercombo.py", line 86, in forward +pkg.torch.onnx.stack_traceFile "/home/batman/xx3/./ml_tools/openpilot_compile/compile_supercombo.py", line 82, in forward return torch.cat([*self.forward_dict(inputs).values(), self.pad], dim=1) File "/home/batman/xx3/xx/training/path/supercombo.py", line 132, in forward policy_outs = self.hydra(summary_outs) @@ -3944,7 +3944,7 @@ Avision_model.point_policy.hydra.res_layer.road_transform.2.weight pkg.torch.onnx.class_hierarchy['__main__.FlattenedVisionModel', 'xx.training.path.supercombo.Policy', 'xx.training.path.supercombo.Hydra', 'torch.nn.modules.container.Sequential', 'torch.nn.modules.linear.Linear', 'aten.linear.default']J pkg.torch.onnx.fx_node%linear_21 : [num_users=1] = call_function[target=torch.ops.aten.linear.default](args = (%relu_20, %p_vision_model_point_policy_hydra_res_layer_pose_2_weight, %p_vision_model_point_policy_hydra_res_layer_pose_2_bias), kwargs = {})J pkg.torch.onnx.name_scopes['', 'vision_model.point_policy', 'vision_model.point_policy.hydra', 'vision_model.point_policy.hydra.res_layer.pose', 'vision_model.point_policy.hydra.res_layer.pose.2', 'linear_21']J -pkg.torch.onnx.stack_traceFile "/home/batman/xx3/./ml_tools/openpilot_compile/compile_supercombo.py", line 86, in forward +pkg.torch.onnx.stack_traceFile "/home/batman/xx3/./ml_tools/openpilot_compile/compile_supercombo.py", line 82, in forward return torch.cat([*self.forward_dict(inputs).values(), self.pad], dim=1) File "/home/batman/xx3/xx/training/path/supercombo.py", line 132, in forward policy_outs = self.hydra(summary_outs) @@ -3961,7 +3961,7 @@ Avision_model.point_policy.hydra.res_layer.road_transform.2.weight pkg.torch.onnx.class_hierarchy['__main__.FlattenedVisionModel', 'xx.training.path.supercombo.Policy', 'xx.training.path.supercombo.Hydra', 'aten.add.Tensor']J pkg.torch.onnx.fx_nodeu%add_19 : [num_users=1] = call_function[target=torch.ops.aten.add.Tensor](args = (%relu_12, %linear_21), kwargs = {})Jl pkg.torch.onnx.name_scopesN['', 'vision_model.point_policy', 'vision_model.point_policy.hydra', 'add_19']J -pkg.torch.onnx.stack_traceFile "/home/batman/xx3/./ml_tools/openpilot_compile/compile_supercombo.py", line 86, in forward +pkg.torch.onnx.stack_traceFile "/home/batman/xx3/./ml_tools/openpilot_compile/compile_supercombo.py", line 82, in forward return torch.cat([*self.forward_dict(inputs).values(), self.pad], dim=1) File "/home/batman/xx3/xx/training/path/supercombo.py", line 132, in forward policy_outs = self.hydra(summary_outs) @@ -3973,7 +3973,7 @@ Avision_model.point_policy.hydra.res_layer.road_transform.2.weight pkg.torch.onnx.class_hierarchy['__main__.FlattenedVisionModel', 'xx.training.path.supercombo.Policy', 'xx.training.path.supercombo.Hydra', 'torch.nn.modules.activation.ReLU', 'aten.relu.default']J pkg.torch.onnx.fx_nodel%relu_21 : [num_users=1] = call_function[target=torch.ops.aten.relu.default](args = (%add_19,), kwargs = {})J pkg.torch.onnx.name_scopesw['', 'vision_model.point_policy', 'vision_model.point_policy.hydra', 'vision_model.point_policy.hydra.relu', 'relu_21']J -pkg.torch.onnx.stack_traceFile "/home/batman/xx3/./ml_tools/openpilot_compile/compile_supercombo.py", line 86, in forward +pkg.torch.onnx.stack_traceFile "/home/batman/xx3/./ml_tools/openpilot_compile/compile_supercombo.py", line 82, in forward return torch.cat([*self.forward_dict(inputs).values(), self.pad], dim=1) File "/home/batman/xx3/xx/training/path/supercombo.py", line 132, in forward policy_outs = self.hydra(summary_outs) @@ -3993,7 +3993,7 @@ Gvision_model.point_policy.hydra.res_layer.wide_from_device_euler.0.bias linear pkg.torch.onnx.class_hierarchy['__main__.FlattenedVisionModel', 'xx.training.path.supercombo.Policy', 'xx.training.path.supercombo.Hydra', 'torch.nn.modules.container.Sequential', 'torch.nn.modules.linear.Linear', 'aten.linear.default']J pkg.torch.onnx.fx_node%linear_22 : [num_users=1] = call_function[target=torch.ops.aten.linear.default](args = (%relu_13, %p_vision_model_point_policy_hydra_res_layer_wide_from_device_euler_0_weight, %p_vision_model_point_policy_hydra_res_layer_wide_from_device_euler_0_bias), kwargs = {})J pkg.torch.onnx.name_scopes['', 'vision_model.point_policy', 'vision_model.point_policy.hydra', 'vision_model.point_policy.hydra.res_layer.wide_from_device_euler', 'vision_model.point_policy.hydra.res_layer.wide_from_device_euler.0', 'linear_22']J -pkg.torch.onnx.stack_traceFile "/home/batman/xx3/./ml_tools/openpilot_compile/compile_supercombo.py", line 86, in forward +pkg.torch.onnx.stack_traceFile "/home/batman/xx3/./ml_tools/openpilot_compile/compile_supercombo.py", line 82, in forward return torch.cat([*self.forward_dict(inputs).values(), self.pad], dim=1) File "/home/batman/xx3/xx/training/path/supercombo.py", line 132, in forward policy_outs = self.hydra(summary_outs) @@ -4009,7 +4009,7 @@ Gvision_model.point_policy.hydra.res_layer.wide_from_device_euler.0.bias linear pkg.torch.onnx.class_hierarchy['__main__.FlattenedVisionModel', 'xx.training.path.supercombo.Policy', 'xx.training.path.supercombo.Hydra', 'torch.nn.modules.container.Sequential', 'torch.nn.modules.activation.ReLU', 'aten.relu.default']J pkg.torch.onnx.fx_nodeo%relu_22 : [num_users=1] = call_function[target=torch.ops.aten.relu.default](args = (%linear_22,), kwargs = {})J pkg.torch.onnx.name_scopes['', 'vision_model.point_policy', 'vision_model.point_policy.hydra', 'vision_model.point_policy.hydra.res_layer.wide_from_device_euler', 'vision_model.point_policy.hydra.res_layer.wide_from_device_euler.1', 'relu_22']J -pkg.torch.onnx.stack_traceFile "/home/batman/xx3/./ml_tools/openpilot_compile/compile_supercombo.py", line 86, in forward +pkg.torch.onnx.stack_traceFile "/home/batman/xx3/./ml_tools/openpilot_compile/compile_supercombo.py", line 82, in forward return torch.cat([*self.forward_dict(inputs).values(), self.pad], dim=1) File "/home/batman/xx3/xx/training/path/supercombo.py", line 132, in forward policy_outs = self.hydra(summary_outs) @@ -4031,7 +4031,7 @@ Gvision_model.point_policy.hydra.res_layer.wide_from_device_euler.2.bias linear pkg.torch.onnx.class_hierarchy['__main__.FlattenedVisionModel', 'xx.training.path.supercombo.Policy', 'xx.training.path.supercombo.Hydra', 'torch.nn.modules.container.Sequential', 'torch.nn.modules.linear.Linear', 'aten.linear.default']J pkg.torch.onnx.fx_node%linear_23 : [num_users=1] = call_function[target=torch.ops.aten.linear.default](args = (%relu_22, %p_vision_model_point_policy_hydra_res_layer_wide_from_device_euler_2_weight, %p_vision_model_point_policy_hydra_res_layer_wide_from_device_euler_2_bias), kwargs = {})J pkg.torch.onnx.name_scopes['', 'vision_model.point_policy', 'vision_model.point_policy.hydra', 'vision_model.point_policy.hydra.res_layer.wide_from_device_euler', 'vision_model.point_policy.hydra.res_layer.wide_from_device_euler.2', 'linear_23']J -pkg.torch.onnx.stack_traceFile "/home/batman/xx3/./ml_tools/openpilot_compile/compile_supercombo.py", line 86, in forward +pkg.torch.onnx.stack_traceFile "/home/batman/xx3/./ml_tools/openpilot_compile/compile_supercombo.py", line 82, in forward return torch.cat([*self.forward_dict(inputs).values(), self.pad], dim=1) File "/home/batman/xx3/xx/training/path/supercombo.py", line 132, in forward policy_outs = self.hydra(summary_outs) @@ -4048,7 +4048,7 @@ Gvision_model.point_policy.hydra.res_layer.wide_from_device_euler.2.bias linear pkg.torch.onnx.class_hierarchy['__main__.FlattenedVisionModel', 'xx.training.path.supercombo.Policy', 'xx.training.path.supercombo.Hydra', 'aten.add.Tensor']J pkg.torch.onnx.fx_nodeu%add_20 : [num_users=1] = call_function[target=torch.ops.aten.add.Tensor](args = (%relu_13, %linear_23), kwargs = {})Jl pkg.torch.onnx.name_scopesN['', 'vision_model.point_policy', 'vision_model.point_policy.hydra', 'add_20']J -pkg.torch.onnx.stack_traceFile "/home/batman/xx3/./ml_tools/openpilot_compile/compile_supercombo.py", line 86, in forward +pkg.torch.onnx.stack_traceFile "/home/batman/xx3/./ml_tools/openpilot_compile/compile_supercombo.py", line 82, in forward return torch.cat([*self.forward_dict(inputs).values(), self.pad], dim=1) File "/home/batman/xx3/xx/training/path/supercombo.py", line 132, in forward policy_outs = self.hydra(summary_outs) @@ -4060,7 +4060,7 @@ Gvision_model.point_policy.hydra.res_layer.wide_from_device_euler.2.bias linear pkg.torch.onnx.class_hierarchy['__main__.FlattenedVisionModel', 'xx.training.path.supercombo.Policy', 'xx.training.path.supercombo.Hydra', 'torch.nn.modules.activation.ReLU', 'aten.relu.default']J pkg.torch.onnx.fx_nodel%relu_23 : [num_users=1] = call_function[target=torch.ops.aten.relu.default](args = (%add_20,), kwargs = {})J pkg.torch.onnx.name_scopesw['', 'vision_model.point_policy', 'vision_model.point_policy.hydra', 'vision_model.point_policy.hydra.relu', 'relu_23']J -pkg.torch.onnx.stack_traceFile "/home/batman/xx3/./ml_tools/openpilot_compile/compile_supercombo.py", line 86, in forward +pkg.torch.onnx.stack_traceFile "/home/batman/xx3/./ml_tools/openpilot_compile/compile_supercombo.py", line 82, in forward return torch.cat([*self.forward_dict(inputs).values(), self.pad], dim=1) File "/home/batman/xx3/xx/training/path/supercombo.py", line 132, in forward policy_outs = self.hydra(summary_outs) @@ -4080,7 +4080,7 @@ Gvision_model.point_policy.hydra.res_layer.wide_from_device_euler.2.bias linear pkg.torch.onnx.class_hierarchy['__main__.FlattenedVisionModel', 'xx.training.path.supercombo.Policy', 'xx.training.path.supercombo.Hydra', 'torch.nn.modules.linear.Linear', 'aten.linear.default']J pkg.torch.onnx.fx_node%linear_24 : [num_users=1] = call_function[target=torch.ops.aten.linear.default](args = (%relu_15, %p_vision_model_point_policy_hydra_final_layer_meta_weight, %p_vision_model_point_policy_hydra_final_layer_meta_bias), kwargs = {})J pkg.torch.onnx.name_scopes['', 'vision_model.point_policy', 'vision_model.point_policy.hydra', 'vision_model.point_policy.hydra.final_layer.meta', 'linear_24']J -pkg.torch.onnx.stack_traceFile "/home/batman/xx3/./ml_tools/openpilot_compile/compile_supercombo.py", line 86, in forward +pkg.torch.onnx.stack_traceFile "/home/batman/xx3/./ml_tools/openpilot_compile/compile_supercombo.py", line 82, in forward return torch.cat([*self.forward_dict(inputs).values(), self.pad], dim=1) File "/home/batman/xx3/xx/training/path/supercombo.py", line 132, in forward policy_outs = self.hydra(summary_outs) @@ -4100,7 +4100,7 @@ Gvision_model.point_policy.hydra.res_layer.wide_from_device_euler.2.bias linear pkg.torch.onnx.class_hierarchy['__main__.FlattenedVisionModel', 'xx.training.path.supercombo.Policy', 'xx.training.path.supercombo.Hydra', 'torch.nn.modules.linear.Linear', 'aten.linear.default']J pkg.torch.onnx.fx_node%linear_25 : [num_users=1] = call_function[target=torch.ops.aten.linear.default](args = (%relu_17, %p_vision_model_point_policy_hydra_final_layer_desire_pred_weight, %p_vision_model_point_policy_hydra_final_layer_desire_pred_bias), kwargs = {})J pkg.torch.onnx.name_scopes['', 'vision_model.point_policy', 'vision_model.point_policy.hydra', 'vision_model.point_policy.hydra.final_layer.desire_pred', 'linear_25']J -pkg.torch.onnx.stack_traceFile "/home/batman/xx3/./ml_tools/openpilot_compile/compile_supercombo.py", line 86, in forward +pkg.torch.onnx.stack_traceFile "/home/batman/xx3/./ml_tools/openpilot_compile/compile_supercombo.py", line 82, in forward return torch.cat([*self.forward_dict(inputs).values(), self.pad], dim=1) File "/home/batman/xx3/xx/training/path/supercombo.py", line 132, in forward policy_outs = self.hydra(summary_outs) @@ -4120,7 +4120,7 @@ Avision_model.point_policy.hydra.final_layer.road_transform.weight pkg.torch.onnx.class_hierarchy['__main__.FlattenedVisionModel', 'xx.training.path.supercombo.Policy', 'xx.training.path.supercombo.Hydra', 'torch.nn.modules.linear.Linear', 'aten.linear.default']J pkg.torch.onnx.fx_node%linear_26 : [num_users=1] = call_function[target=torch.ops.aten.linear.default](args = (%relu_19, %p_vision_model_point_policy_hydra_final_layer_road_transform_weight, %p_vision_model_point_policy_hydra_final_layer_road_transform_bias), kwargs = {})J pkg.torch.onnx.name_scopes['', 'vision_model.point_policy', 'vision_model.point_policy.hydra', 'vision_model.point_policy.hydra.final_layer.road_transform', 'linear_26']J -pkg.torch.onnx.stack_traceFile "/home/batman/xx3/./ml_tools/openpilot_compile/compile_supercombo.py", line 86, in forward +pkg.torch.onnx.stack_traceFile "/home/batman/xx3/./ml_tools/openpilot_compile/compile_supercombo.py", line 82, in forward return torch.cat([*self.forward_dict(inputs).values(), self.pad], dim=1) File "/home/batman/xx3/xx/training/path/supercombo.py", line 132, in forward policy_outs = self.hydra(summary_outs) @@ -4140,7 +4140,7 @@ Avision_model.point_policy.hydra.final_layer.road_transform.weight pkg.torch.onnx.class_hierarchy['__main__.FlattenedVisionModel', 'xx.training.path.supercombo.Policy', 'xx.training.path.supercombo.Hydra', 'torch.nn.modules.linear.Linear', 'aten.linear.default']J pkg.torch.onnx.fx_node%linear_27 : [num_users=1] = call_function[target=torch.ops.aten.linear.default](args = (%relu_21, %p_vision_model_point_policy_hydra_final_layer_pose_weight, %p_vision_model_point_policy_hydra_final_layer_pose_bias), kwargs = {})J pkg.torch.onnx.name_scopes['', 'vision_model.point_policy', 'vision_model.point_policy.hydra', 'vision_model.point_policy.hydra.final_layer.pose', 'linear_27']J -pkg.torch.onnx.stack_traceFile "/home/batman/xx3/./ml_tools/openpilot_compile/compile_supercombo.py", line 86, in forward +pkg.torch.onnx.stack_traceFile "/home/batman/xx3/./ml_tools/openpilot_compile/compile_supercombo.py", line 82, in forward return torch.cat([*self.forward_dict(inputs).values(), self.pad], dim=1) File "/home/batman/xx3/xx/training/path/supercombo.py", line 132, in forward policy_outs = self.hydra(summary_outs) @@ -4160,7 +4160,7 @@ Gvision_model.point_policy.hydra.final_layer.wide_from_device_euler.bias linear pkg.torch.onnx.class_hierarchy['__main__.FlattenedVisionModel', 'xx.training.path.supercombo.Policy', 'xx.training.path.supercombo.Hydra', 'torch.nn.modules.linear.Linear', 'aten.linear.default']J pkg.torch.onnx.fx_node%linear_28 : [num_users=1] = call_function[target=torch.ops.aten.linear.default](args = (%relu_23, %p_vision_model_point_policy_hydra_final_layer_wide_from_device_euler_weight, %p_vision_model_point_policy_hydra_final_layer_wide_from_device_euler_bias), kwargs = {})J pkg.torch.onnx.name_scopes['', 'vision_model.point_policy', 'vision_model.point_policy.hydra', 'vision_model.point_policy.hydra.final_layer.wide_from_device_euler', 'linear_28']J -pkg.torch.onnx.stack_traceFile "/home/batman/xx3/./ml_tools/openpilot_compile/compile_supercombo.py", line 86, in forward +pkg.torch.onnx.stack_traceFile "/home/batman/xx3/./ml_tools/openpilot_compile/compile_supercombo.py", line 82, in forward return torch.cat([*self.forward_dict(inputs).values(), self.pad], dim=1) File "/home/batman/xx3/xx/training/path/supercombo.py", line 132, in forward policy_outs = self.hydra(summary_outs) @@ -4182,7 +4182,7 @@ node_cat_1"Concat* pkg.torch.onnx.class_hierarchy5['__main__.FlattenedVisionModel', 'aten.cat.default']J pkg.torch.onnx.fx_node%cat_1 : [num_users=1] = call_function[target=torch.ops.aten.cat.default](args = ([%linear_24, %linear_25, %linear_27, %linear_28, %linear_26, %detach, %p_pad], 1), kwargs = {})J+ pkg.torch.onnx.name_scopes ['', 'cat_1']J -pkg.torch.onnx.stack_traceFile "/home/batman/xx3/./ml_tools/openpilot_compile/compile_supercombo.py", line 86, in forward +pkg.torch.onnx.stack_traceFile "/home/batman/xx3/./ml_tools/openpilot_compile/compile_supercombo.py", line 82, in forward return torch.cat([*self.forward_dict(inputs).values(), self.pad], dim=1) main_graph* BpadJ*@