diff --git a/uncompiledmodels/driving_off_policy.onnx b/uncompiledmodels/driving_off_policy.onnx index 9473720d5..9809ff165 100644 Binary files a/uncompiledmodels/driving_off_policy.onnx and b/uncompiledmodels/driving_off_policy.onnx differ diff --git a/uncompiledmodels/driving_on_policy.onnx b/uncompiledmodels/driving_on_policy.onnx index 464613c71..f52e6e2aa 100644 Binary files a/uncompiledmodels/driving_on_policy.onnx and b/uncompiledmodels/driving_on_policy.onnx differ diff --git a/uncompiledmodels/driving_vision.onnx b/uncompiledmodels/driving_vision.onnx index a4f1b74e5..0e9012654 100644 --- a/uncompiledmodels/driving_vision.onnx +++ b/uncompiledmodels/driving_vision.onnx @@ -9,7 +9,7 @@ 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/xx2/./ml_tools/openpilot_compile/compile_supercombo.py", line 82, in forward +pkg.torch.onnx.stack_traceFile "/home/batman/xx3/./ml_tools/openpilot_compile/compile_supercombo.py", line 86, in forward return torch.cat([*self.forward_dict(inputs).values(), self.pad], dim=1)  big_img @@ -20,7 +20,7 @@ _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/xx2/./ml_tools/openpilot_compile/compile_supercombo.py", line 82, in forward +pkg.torch.onnx.stack_traceFile "/home/batman/xx3/./ml_tools/openpilot_compile/compile_supercombo.py", line 86, in forward return torch.cat([*self.forward_dict(inputs).values(), self.pad], dim=1)  _to_copy @@ -31,9 +31,9 @@ _to_copy_1catnode_cat"Concat* pkg.torch.onnx.class_hierarchy[['__main__.FlattenedVisionModel', 'xx.training.path.supercombo.Vision', '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"['', 'vision_model.vision', 'cat']J -pkg.torch.onnx.stack_traceFile "/home/batman/xx2/./ml_tools/openpilot_compile/compile_supercombo.py", line 82, in forward +pkg.torch.onnx.stack_traceFile "/home/batman/xx3/./ml_tools/openpilot_compile/compile_supercombo.py", line 86, in forward return torch.cat([*self.forward_dict(inputs).values(), self.pad], dim=1) - File "/home/batman/xx2/xx/training/path/supercombo.py", line 190, in forward + File "/home/batman/xx3/xx/training/path/supercombo.py", line 190, in forward x = torch.cat([x[name] for name in self.config.input_frame_names], dim=1)  cat @@ -42,9 +42,9 @@ _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/xx2/./ml_tools/openpilot_compile/compile_supercombo.py", line 82, in forward +pkg.torch.onnx.stack_traceFile "/home/batman/xx3/./ml_tools/openpilot_compile/compile_supercombo.py", line 86, in forward return torch.cat([*self.forward_dict(inputs).values(), self.pad], dim=1) - File "/home/batman/xx2/xx/training/path/supercombo.py", line 191, in forward + File "/home/batman/xx3/xx/training/path/supercombo.py", line 191, in forward return {ModelInputs.FEATURES: self._en((x - self._mean) / self._std)}  sub @@ -53,9 +53,9 @@ _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/xx2/./ml_tools/openpilot_compile/compile_supercombo.py", line 82, in forward +pkg.torch.onnx.stack_traceFile "/home/batman/xx3/./ml_tools/openpilot_compile/compile_supercombo.py", line 86, in forward return torch.cat([*self.forward_dict(inputs).values(), self.pad], dim=1) - File "/home/batman/xx2/xx/training/path/supercombo.py", line 191, in forward + File "/home/batman/xx3/xx/training/path/supercombo.py", line 191, in forward return {ModelInputs.FEATURES: self._en((x - self._mean) / self._std)}  div @@ -70,17 +70,17 @@ _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/xx2/./ml_tools/openpilot_compile/compile_supercombo.py", line 82, in forward +pkg.torch.onnx.stack_traceFile "/home/batman/xx3/./ml_tools/openpilot_compile/compile_supercombo.py", line 86, in forward return torch.cat([*self.forward_dict(inputs).values(), self.pad], dim=1) - File "/home/batman/xx2/xx/training/path/supercombo.py", line 191, in forward + File "/home/batman/xx3/xx/training/path/supercombo.py", line 191, in forward return {ModelInputs.FEATURES: self._en((x - self._mean) / self._std)} - File "/home/batman/xx2/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1418, in forward + File "/home/batman/xx3/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1418, in forward x = self.forward_features(x) - File "/home/batman/xx2/.venv/lib/python3.12/site-packages/torch/nn/modules/container.py", line 253, in forward + File "/home/batman/xx3/.venv/lib/python3.12/site-packages/torch/nn/modules/container.py", line 253, in forward input = module(input) - File "/home/batman/xx2/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 155, in forward + File "/home/batman/xx3/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 155, in forward return self.act(self.se(self.reparam_conv(x))) - File "/home/batman/xx2/.venv/lib/python3.12/site-packages/torch/nn/modules/conv.py", line 553, in forward + File "/home/batman/xx3/.venv/lib/python3.12/site-packages/torch/nn/modules/conv.py", line 553, in forward return self._conv_forward(input, self.weight, self.bias)  conv2dgelu node_gelu"Gelu* @@ -89,17 +89,17 @@ _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/xx2/./ml_tools/openpilot_compile/compile_supercombo.py", line 82, in forward +pkg.torch.onnx.stack_traceFile "/home/batman/xx3/./ml_tools/openpilot_compile/compile_supercombo.py", line 86, in forward return torch.cat([*self.forward_dict(inputs).values(), self.pad], dim=1) - File "/home/batman/xx2/xx/training/path/supercombo.py", line 191, in forward + File "/home/batman/xx3/xx/training/path/supercombo.py", line 191, in forward return {ModelInputs.FEATURES: self._en((x - self._mean) / self._std)} - File "/home/batman/xx2/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1418, in forward + File "/home/batman/xx3/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1418, in forward x = self.forward_features(x) - File "/home/batman/xx2/.venv/lib/python3.12/site-packages/torch/nn/modules/container.py", line 253, in forward + File "/home/batman/xx3/.venv/lib/python3.12/site-packages/torch/nn/modules/container.py", line 253, in forward input = module(input) - File "/home/batman/xx2/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 155, in forward + File "/home/batman/xx3/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 155, in forward return self.act(self.se(self.reparam_conv(x))) - File "/home/batman/xx2/.venv/lib/python3.12/site-packages/timm/layers/activations.py", line 159, in forward + File "/home/batman/xx3/.venv/lib/python3.12/site-packages/timm/layers/activations.py", line 159, in forward return F.gelu(input, approximate='tanh')  gelu @@ -114,17 +114,17 @@ _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/xx2/./ml_tools/openpilot_compile/compile_supercombo.py", line 82, in forward +pkg.torch.onnx.stack_traceFile "/home/batman/xx3/./ml_tools/openpilot_compile/compile_supercombo.py", line 86, in forward return torch.cat([*self.forward_dict(inputs).values(), self.pad], dim=1) - File "/home/batman/xx2/xx/training/path/supercombo.py", line 191, in forward + File "/home/batman/xx3/xx/training/path/supercombo.py", line 191, in forward return {ModelInputs.FEATURES: self._en((x - self._mean) / self._std)} - File "/home/batman/xx2/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1418, in forward + File "/home/batman/xx3/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1418, in forward x = self.forward_features(x) - File "/home/batman/xx2/.venv/lib/python3.12/site-packages/torch/nn/modules/container.py", line 253, in forward + File "/home/batman/xx3/.venv/lib/python3.12/site-packages/torch/nn/modules/container.py", line 253, in forward input = module(input) - File "/home/batman/xx2/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 155, in forward + File "/home/batman/xx3/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 155, in forward return self.act(self.se(self.reparam_conv(x))) - File "/home/batman/xx2/.venv/lib/python3.12/site-packages/torch/nn/modules/conv.py", line 553, in forward + File "/home/batman/xx3/.venv/lib/python3.12/site-packages/torch/nn/modules/conv.py", line 553, in forward return self._conv_forward(input, self.weight, self.bias)  conv2d_1gelu_1 node_gelu_1"Gelu* @@ -133,17 +133,17 @@ _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/xx2/./ml_tools/openpilot_compile/compile_supercombo.py", line 82, in forward +pkg.torch.onnx.stack_traceFile "/home/batman/xx3/./ml_tools/openpilot_compile/compile_supercombo.py", line 86, in forward return torch.cat([*self.forward_dict(inputs).values(), self.pad], dim=1) - File "/home/batman/xx2/xx/training/path/supercombo.py", line 191, in forward + File "/home/batman/xx3/xx/training/path/supercombo.py", line 191, in forward return {ModelInputs.FEATURES: self._en((x - self._mean) / self._std)} - File "/home/batman/xx2/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1418, in forward + File "/home/batman/xx3/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1418, in forward x = self.forward_features(x) - File "/home/batman/xx2/.venv/lib/python3.12/site-packages/torch/nn/modules/container.py", line 253, in forward + File "/home/batman/xx3/.venv/lib/python3.12/site-packages/torch/nn/modules/container.py", line 253, in forward input = module(input) - File "/home/batman/xx2/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 155, in forward + File "/home/batman/xx3/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 155, in forward return self.act(self.se(self.reparam_conv(x))) - File "/home/batman/xx2/.venv/lib/python3.12/site-packages/timm/layers/activations.py", line 159, in forward + File "/home/batman/xx3/.venv/lib/python3.12/site-packages/timm/layers/activations.py", line 159, in forward return F.gelu(input, approximate='tanh')  gelu_1 @@ -158,17 +158,17 @@ _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/xx2/./ml_tools/openpilot_compile/compile_supercombo.py", line 82, in forward +pkg.torch.onnx.stack_traceFile "/home/batman/xx3/./ml_tools/openpilot_compile/compile_supercombo.py", line 86, in forward return torch.cat([*self.forward_dict(inputs).values(), self.pad], dim=1) - File "/home/batman/xx2/xx/training/path/supercombo.py", line 191, in forward + File "/home/batman/xx3/xx/training/path/supercombo.py", line 191, in forward return {ModelInputs.FEATURES: self._en((x - self._mean) / self._std)} - File "/home/batman/xx2/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1418, in forward + File "/home/batman/xx3/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1418, in forward x = self.forward_features(x) - File "/home/batman/xx2/.venv/lib/python3.12/site-packages/torch/nn/modules/container.py", line 253, in forward + File "/home/batman/xx3/.venv/lib/python3.12/site-packages/torch/nn/modules/container.py", line 253, in forward input = module(input) - File "/home/batman/xx2/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 155, in forward + File "/home/batman/xx3/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 155, in forward return self.act(self.se(self.reparam_conv(x))) - File "/home/batman/xx2/.venv/lib/python3.12/site-packages/torch/nn/modules/conv.py", line 553, in forward + File "/home/batman/xx3/.venv/lib/python3.12/site-packages/torch/nn/modules/conv.py", line 553, in forward return self._conv_forward(input, self.weight, self.bias)  conv2d_2gelu_2 node_gelu_2"Gelu* @@ -177,17 +177,17 @@ _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/xx2/./ml_tools/openpilot_compile/compile_supercombo.py", line 82, in forward +pkg.torch.onnx.stack_traceFile "/home/batman/xx3/./ml_tools/openpilot_compile/compile_supercombo.py", line 86, in forward return torch.cat([*self.forward_dict(inputs).values(), self.pad], dim=1) - File "/home/batman/xx2/xx/training/path/supercombo.py", line 191, in forward + File "/home/batman/xx3/xx/training/path/supercombo.py", line 191, in forward return {ModelInputs.FEATURES: self._en((x - self._mean) / self._std)} - File "/home/batman/xx2/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1418, in forward + File "/home/batman/xx3/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1418, in forward x = self.forward_features(x) - File "/home/batman/xx2/.venv/lib/python3.12/site-packages/torch/nn/modules/container.py", line 253, in forward + File "/home/batman/xx3/.venv/lib/python3.12/site-packages/torch/nn/modules/container.py", line 253, in forward input = module(input) - File "/home/batman/xx2/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 155, in forward + File "/home/batman/xx3/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 155, in forward return self.act(self.se(self.reparam_conv(x))) - File "/home/batman/xx2/.venv/lib/python3.12/site-packages/timm/layers/activations.py", line 159, in forward + File "/home/batman/xx3/.venv/lib/python3.12/site-packages/timm/layers/activations.py", line 159, in forward return F.gelu(input, approximate='tanh')  gelu_2 @@ -202,21 +202,21 @@ 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_trace File "/home/batman/xx2/./ml_tools/openpilot_compile/compile_supercombo.py", line 82, in forward +pkg.torch.onnx.stack_trace File "/home/batman/xx3/./ml_tools/openpilot_compile/compile_supercombo.py", line 86, in forward return torch.cat([*self.forward_dict(inputs).values(), self.pad], dim=1) - File "/home/batman/xx2/xx/training/path/supercombo.py", line 191, in forward + File "/home/batman/xx3/xx/training/path/supercombo.py", line 191, in forward return {ModelInputs.FEATURES: self._en((x - self._mean) / self._std)} - File "/home/batman/xx2/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1418, in forward + File "/home/batman/xx3/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1418, in forward x = self.forward_features(x) - File "/home/batman/xx2/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1167, in forward + File "/home/batman/xx3/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1167, in forward x = self.blocks(x) - File "/home/batman/xx2/.venv/lib/python3.12/site-packages/torch/nn/modules/container.py", line 253, in forward + File "/home/batman/xx3/.venv/lib/python3.12/site-packages/torch/nn/modules/container.py", line 253, in forward input = module(input) - File "/home/batman/xx2/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1001, in forward + File "/home/batman/xx3/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1001, in forward x = self.token_mixer(x) - File "/home/batman/xx2/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 717, in forward + File "/home/batman/xx3/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 717, in forward x = self.reparam_conv(x) - File "/home/batman/xx2/.venv/lib/python3.12/site-packages/torch/nn/modules/conv.py", line 553, in forward + File "/home/batman/xx3/.venv/lib/python3.12/site-packages/torch/nn/modules/conv.py", line 553, in forward return self._conv_forward(input, self.weight, self.bias)  conv2d_3 @@ -234,23 +234,23 @@ Cvision_model.vision._en.stages.0.blocks.0.mlp.conv.conv.weight_biasgetitem n 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/xx2/./ml_tools/openpilot_compile/compile_supercombo.py", line 82, in forward +File "/home/batman/xx3/./ml_tools/openpilot_compile/compile_supercombo.py", line 86, in forward return torch.cat([*self.forward_dict(inputs).values(), self.pad], dim=1) - File "/home/batman/xx2/xx/training/path/supercombo.py", line 191, in forward + File "/home/batman/xx3/xx/training/path/supercombo.py", line 191, in forward return {ModelInputs.FEATURES: self._en((x - self._mean) / self._std)} - File "/home/batman/xx2/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1418, in forward + File "/home/batman/xx3/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1418, in forward x = self.forward_features(x) - File "/home/batman/xx2/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1167, in forward + File "/home/batman/xx3/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1167, in forward x = self.blocks(x) - File "/home/batman/xx2/.venv/lib/python3.12/site-packages/torch/nn/modules/container.py", line 253, in forward + File "/home/batman/xx3/.venv/lib/python3.12/site-packages/torch/nn/modules/container.py", line 253, in forward input = module(input) - File "/home/batman/xx2/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1002, in forward + File "/home/batman/xx3/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1002, in forward x = x + self.drop_path(self.layer_scale(self.mlp(x))) - File "/home/batman/xx2/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 814, in forward + File "/home/batman/xx3/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 814, in forward x = self.conv(x) - File "/home/batman/xx2/.venv/lib/python3.12/site-packages/timm/layers/conv_bn_act.py", line 94, in forward + File "/home/batman/xx3/.venv/lib/python3.12/site-packages/timm/layers/conv_bn_act.py", line 94, in forward x = self.bn(x) - File "/home/batman/xx2/xx/training/path/allnorm.py", line 60, in forward + File "/home/batman/xx3/xx/training/path/allnorm.py", line 60, in forward return self.act(self.drop(self._allnorm_forward(x)))  getitem @@ -265,21 +265,21 @@ File "/home/batman/xx2/./ml_tools/openpilot_compile/compile_supercombo.py", line 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/xx2/./ml_tools/openpilot_compile/compile_supercombo.py", line 82, in forward +pkg.torch.onnx.stack_trace File "/home/batman/xx3/./ml_tools/openpilot_compile/compile_supercombo.py", line 86, in forward return torch.cat([*self.forward_dict(inputs).values(), self.pad], dim=1) - File "/home/batman/xx2/xx/training/path/supercombo.py", line 191, in forward + File "/home/batman/xx3/xx/training/path/supercombo.py", line 191, in forward return {ModelInputs.FEATURES: self._en((x - self._mean) / self._std)} - File "/home/batman/xx2/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1418, in forward + File "/home/batman/xx3/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1418, in forward x = self.forward_features(x) - File "/home/batman/xx2/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1167, in forward + File "/home/batman/xx3/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1167, in forward x = self.blocks(x) - File "/home/batman/xx2/.venv/lib/python3.12/site-packages/torch/nn/modules/container.py", line 253, in forward + File "/home/batman/xx3/.venv/lib/python3.12/site-packages/torch/nn/modules/container.py", line 253, in forward input = module(input) - File "/home/batman/xx2/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1002, in forward + File "/home/batman/xx3/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1002, in forward x = x + self.drop_path(self.layer_scale(self.mlp(x))) - File "/home/batman/xx2/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 815, in forward + File "/home/batman/xx3/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 815, in forward x = self.fc1(x) - File "/home/batman/xx2/.venv/lib/python3.12/site-packages/torch/nn/modules/conv.py", line 553, in forward + File "/home/batman/xx3/.venv/lib/python3.12/site-packages/torch/nn/modules/conv.py", line 553, in forward return self._conv_forward(input, self.weight, self.bias)  conv2d_5gelu_3 node_gelu_3"Gelu* @@ -288,21 +288,21 @@ File "/home/batman/xx2/./ml_tools/openpilot_compile/compile_supercombo.py", line 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_trace File "/home/batman/xx2/./ml_tools/openpilot_compile/compile_supercombo.py", line 82, in forward +pkg.torch.onnx.stack_trace File "/home/batman/xx3/./ml_tools/openpilot_compile/compile_supercombo.py", line 86, in forward return torch.cat([*self.forward_dict(inputs).values(), self.pad], dim=1) - File "/home/batman/xx2/xx/training/path/supercombo.py", line 191, in forward + File "/home/batman/xx3/xx/training/path/supercombo.py", line 191, in forward return {ModelInputs.FEATURES: self._en((x - self._mean) / self._std)} - File "/home/batman/xx2/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1418, in forward + File "/home/batman/xx3/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1418, in forward x = self.forward_features(x) - File "/home/batman/xx2/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1167, in forward + File "/home/batman/xx3/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1167, in forward x = self.blocks(x) - File "/home/batman/xx2/.venv/lib/python3.12/site-packages/torch/nn/modules/container.py", line 253, in forward + File "/home/batman/xx3/.venv/lib/python3.12/site-packages/torch/nn/modules/container.py", line 253, in forward input = module(input) - File "/home/batman/xx2/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1002, in forward + File "/home/batman/xx3/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1002, in forward x = x + self.drop_path(self.layer_scale(self.mlp(x))) - File "/home/batman/xx2/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 816, in forward + File "/home/batman/xx3/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 816, in forward x = self.act(x) - File "/home/batman/xx2/.venv/lib/python3.12/site-packages/timm/layers/activations.py", line 159, in forward + File "/home/batman/xx3/.venv/lib/python3.12/site-packages/timm/layers/activations.py", line 159, in forward return F.gelu(input, approximate='tanh')  gelu_3 @@ -317,21 +317,21 @@ File "/home/batman/xx2/./ml_tools/openpilot_compile/compile_supercombo.py", line 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/xx2/./ml_tools/openpilot_compile/compile_supercombo.py", line 82, in forward +pkg.torch.onnx.stack_trace File "/home/batman/xx3/./ml_tools/openpilot_compile/compile_supercombo.py", line 86, in forward return torch.cat([*self.forward_dict(inputs).values(), self.pad], dim=1) - File "/home/batman/xx2/xx/training/path/supercombo.py", line 191, in forward + File "/home/batman/xx3/xx/training/path/supercombo.py", line 191, in forward return {ModelInputs.FEATURES: self._en((x - self._mean) / self._std)} - File "/home/batman/xx2/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1418, in forward + File "/home/batman/xx3/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1418, in forward x = self.forward_features(x) - File "/home/batman/xx2/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1167, in forward + File "/home/batman/xx3/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1167, in forward x = self.blocks(x) - File "/home/batman/xx2/.venv/lib/python3.12/site-packages/torch/nn/modules/container.py", line 253, in forward + File "/home/batman/xx3/.venv/lib/python3.12/site-packages/torch/nn/modules/container.py", line 253, in forward input = module(input) - File "/home/batman/xx2/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1002, in forward + File "/home/batman/xx3/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1002, in forward x = x + self.drop_path(self.layer_scale(self.mlp(x))) - File "/home/batman/xx2/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 818, in forward + File "/home/batman/xx3/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 818, in forward x = self.fc2(x) - File "/home/batman/xx2/.venv/lib/python3.12/site-packages/torch/nn/modules/conv.py", line 553, in forward + File "/home/batman/xx3/.venv/lib/python3.12/site-packages/torch/nn/modules/conv.py", line 553, in forward return self._conv_forward(input, self.weight, self.bias)  conv2d_6 @@ -340,19 +340,19 @@ File "/home/batman/xx2/./ml_tools/openpilot_compile/compile_supercombo.py", line 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/xx2/./ml_tools/openpilot_compile/compile_supercombo.py", line 82, in forward +pkg.torch.onnx.stack_traceFile "/home/batman/xx3/./ml_tools/openpilot_compile/compile_supercombo.py", line 86, in forward return torch.cat([*self.forward_dict(inputs).values(), self.pad], dim=1) - File "/home/batman/xx2/xx/training/path/supercombo.py", line 191, in forward + File "/home/batman/xx3/xx/training/path/supercombo.py", line 191, in forward return {ModelInputs.FEATURES: self._en((x - self._mean) / self._std)} - File "/home/batman/xx2/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1418, in forward + File "/home/batman/xx3/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1418, in forward x = self.forward_features(x) - File "/home/batman/xx2/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1167, in forward + File "/home/batman/xx3/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1167, in forward x = self.blocks(x) - File "/home/batman/xx2/.venv/lib/python3.12/site-packages/torch/nn/modules/container.py", line 253, in forward + File "/home/batman/xx3/.venv/lib/python3.12/site-packages/torch/nn/modules/container.py", line 253, in forward input = module(input) - File "/home/batman/xx2/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1002, in forward + File "/home/batman/xx3/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1002, in forward x = x + self.drop_path(self.layer_scale(self.mlp(x))) - File "/home/batman/xx2/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 646, in forward + File "/home/batman/xx3/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 646, in forward return x.mul_(self.gamma) if self.inplace else x * self.gamma  conv2d_3 @@ -361,17 +361,17 @@ File "/home/batman/xx2/./ml_tools/openpilot_compile/compile_supercombo.py", line 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/xx2/./ml_tools/openpilot_compile/compile_supercombo.py", line 82, in forward +pkg.torch.onnx.stack_traceFile "/home/batman/xx3/./ml_tools/openpilot_compile/compile_supercombo.py", line 86, in forward return torch.cat([*self.forward_dict(inputs).values(), self.pad], dim=1) - File "/home/batman/xx2/xx/training/path/supercombo.py", line 191, in forward + File "/home/batman/xx3/xx/training/path/supercombo.py", line 191, in forward return {ModelInputs.FEATURES: self._en((x - self._mean) / self._std)} - File "/home/batman/xx2/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1418, in forward + File "/home/batman/xx3/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1418, in forward x = self.forward_features(x) - File "/home/batman/xx2/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1167, in forward + File "/home/batman/xx3/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1167, in forward x = self.blocks(x) - File "/home/batman/xx2/.venv/lib/python3.12/site-packages/torch/nn/modules/container.py", line 253, in forward + File "/home/batman/xx3/.venv/lib/python3.12/site-packages/torch/nn/modules/container.py", line 253, in forward input = module(input) - File "/home/batman/xx2/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1002, in forward + File "/home/batman/xx3/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1002, in forward x = x + self.drop_path(self.layer_scale(self.mlp(x)))  add @@ -386,21 +386,21 @@ 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_trace File "/home/batman/xx2/./ml_tools/openpilot_compile/compile_supercombo.py", line 82, in forward +pkg.torch.onnx.stack_trace File "/home/batman/xx3/./ml_tools/openpilot_compile/compile_supercombo.py", line 86, in forward return torch.cat([*self.forward_dict(inputs).values(), self.pad], dim=1) - File "/home/batman/xx2/xx/training/path/supercombo.py", line 191, in forward + File "/home/batman/xx3/xx/training/path/supercombo.py", line 191, in forward return {ModelInputs.FEATURES: self._en((x - self._mean) / self._std)} - File "/home/batman/xx2/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1418, in forward + File "/home/batman/xx3/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1418, in forward x = self.forward_features(x) - File "/home/batman/xx2/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1167, in forward + File "/home/batman/xx3/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1167, in forward x = self.blocks(x) - File "/home/batman/xx2/.venv/lib/python3.12/site-packages/torch/nn/modules/container.py", line 253, in forward + File "/home/batman/xx3/.venv/lib/python3.12/site-packages/torch/nn/modules/container.py", line 253, in forward input = module(input) - File "/home/batman/xx2/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1001, in forward + File "/home/batman/xx3/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1001, in forward x = self.token_mixer(x) - File "/home/batman/xx2/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 717, in forward + File "/home/batman/xx3/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 717, in forward x = self.reparam_conv(x) - File "/home/batman/xx2/.venv/lib/python3.12/site-packages/torch/nn/modules/conv.py", line 553, in forward + File "/home/batman/xx3/.venv/lib/python3.12/site-packages/torch/nn/modules/conv.py", line 553, in forward return self._conv_forward(input, self.weight, self.bias)  conv2d_7 @@ -418,23 +418,23 @@ Cvision_model.vision._en.stages.0.blocks.1.mlp.conv.conv.weight_bias getitem_3 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/xx2/./ml_tools/openpilot_compile/compile_supercombo.py", line 82, in forward +File "/home/batman/xx3/./ml_tools/openpilot_compile/compile_supercombo.py", line 86, in forward return torch.cat([*self.forward_dict(inputs).values(), self.pad], dim=1) - File "/home/batman/xx2/xx/training/path/supercombo.py", line 191, in forward + File "/home/batman/xx3/xx/training/path/supercombo.py", line 191, in forward return {ModelInputs.FEATURES: self._en((x - self._mean) / self._std)} - File "/home/batman/xx2/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1418, in forward + File "/home/batman/xx3/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1418, in forward x = self.forward_features(x) - File "/home/batman/xx2/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1167, in forward + File "/home/batman/xx3/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1167, in forward x = self.blocks(x) - File "/home/batman/xx2/.venv/lib/python3.12/site-packages/torch/nn/modules/container.py", line 253, in forward + File "/home/batman/xx3/.venv/lib/python3.12/site-packages/torch/nn/modules/container.py", line 253, in forward input = module(input) - File "/home/batman/xx2/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1002, in forward + File "/home/batman/xx3/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1002, in forward x = x + self.drop_path(self.layer_scale(self.mlp(x))) - File "/home/batman/xx2/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 814, in forward + File "/home/batman/xx3/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 814, in forward x = self.conv(x) - File "/home/batman/xx2/.venv/lib/python3.12/site-packages/timm/layers/conv_bn_act.py", line 94, in forward + File "/home/batman/xx3/.venv/lib/python3.12/site-packages/timm/layers/conv_bn_act.py", line 94, in forward x = self.bn(x) - File "/home/batman/xx2/xx/training/path/allnorm.py", line 60, in forward + File "/home/batman/xx3/xx/training/path/allnorm.py", line 60, in forward return self.act(self.drop(self._allnorm_forward(x)))  getitem_3 @@ -449,21 +449,21 @@ File "/home/batman/xx2/./ml_tools/openpilot_compile/compile_supercombo.py", line 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/xx2/./ml_tools/openpilot_compile/compile_supercombo.py", line 82, in forward +pkg.torch.onnx.stack_trace File "/home/batman/xx3/./ml_tools/openpilot_compile/compile_supercombo.py", line 86, in forward return torch.cat([*self.forward_dict(inputs).values(), self.pad], dim=1) - File "/home/batman/xx2/xx/training/path/supercombo.py", line 191, in forward + File "/home/batman/xx3/xx/training/path/supercombo.py", line 191, in forward return {ModelInputs.FEATURES: self._en((x - self._mean) / self._std)} - File "/home/batman/xx2/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1418, in forward + File "/home/batman/xx3/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1418, in forward x = self.forward_features(x) - File "/home/batman/xx2/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1167, in forward + File "/home/batman/xx3/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1167, in forward x = self.blocks(x) - File "/home/batman/xx2/.venv/lib/python3.12/site-packages/torch/nn/modules/container.py", line 253, in forward + File "/home/batman/xx3/.venv/lib/python3.12/site-packages/torch/nn/modules/container.py", line 253, in forward input = module(input) - File "/home/batman/xx2/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1002, in forward + File "/home/batman/xx3/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1002, in forward x = x + self.drop_path(self.layer_scale(self.mlp(x))) - File "/home/batman/xx2/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 815, in forward + File "/home/batman/xx3/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 815, in forward x = self.fc1(x) - File "/home/batman/xx2/.venv/lib/python3.12/site-packages/torch/nn/modules/conv.py", line 553, in forward + File "/home/batman/xx3/.venv/lib/python3.12/site-packages/torch/nn/modules/conv.py", line 553, in forward return self._conv_forward(input, self.weight, self.bias)  conv2d_9gelu_4 node_gelu_4"Gelu* @@ -472,21 +472,21 @@ File "/home/batman/xx2/./ml_tools/openpilot_compile/compile_supercombo.py", line 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_trace File "/home/batman/xx2/./ml_tools/openpilot_compile/compile_supercombo.py", line 82, in forward +pkg.torch.onnx.stack_trace File "/home/batman/xx3/./ml_tools/openpilot_compile/compile_supercombo.py", line 86, in forward return torch.cat([*self.forward_dict(inputs).values(), self.pad], dim=1) - File "/home/batman/xx2/xx/training/path/supercombo.py", line 191, in forward + File "/home/batman/xx3/xx/training/path/supercombo.py", line 191, in forward return {ModelInputs.FEATURES: self._en((x - self._mean) / self._std)} - File "/home/batman/xx2/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1418, in forward + File "/home/batman/xx3/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1418, in forward x = self.forward_features(x) - File "/home/batman/xx2/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1167, in forward + File "/home/batman/xx3/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1167, in forward x = self.blocks(x) - File "/home/batman/xx2/.venv/lib/python3.12/site-packages/torch/nn/modules/container.py", line 253, in forward + File "/home/batman/xx3/.venv/lib/python3.12/site-packages/torch/nn/modules/container.py", line 253, in forward input = module(input) - File "/home/batman/xx2/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1002, in forward + File "/home/batman/xx3/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1002, in forward x = x + self.drop_path(self.layer_scale(self.mlp(x))) - File "/home/batman/xx2/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 816, in forward + File "/home/batman/xx3/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 816, in forward x = self.act(x) - File "/home/batman/xx2/.venv/lib/python3.12/site-packages/timm/layers/activations.py", line 159, in forward + File "/home/batman/xx3/.venv/lib/python3.12/site-packages/timm/layers/activations.py", line 159, in forward return F.gelu(input, approximate='tanh')  gelu_4 @@ -501,21 +501,21 @@ File "/home/batman/xx2/./ml_tools/openpilot_compile/compile_supercombo.py", line 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/xx2/./ml_tools/openpilot_compile/compile_supercombo.py", line 82, in forward +pkg.torch.onnx.stack_trace File "/home/batman/xx3/./ml_tools/openpilot_compile/compile_supercombo.py", line 86, in forward return torch.cat([*self.forward_dict(inputs).values(), self.pad], dim=1) - File "/home/batman/xx2/xx/training/path/supercombo.py", line 191, in forward + File "/home/batman/xx3/xx/training/path/supercombo.py", line 191, in forward return {ModelInputs.FEATURES: self._en((x - self._mean) / self._std)} - File "/home/batman/xx2/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1418, in forward + File "/home/batman/xx3/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1418, in forward x = self.forward_features(x) - File "/home/batman/xx2/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1167, in forward + File "/home/batman/xx3/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1167, in forward x = self.blocks(x) - File "/home/batman/xx2/.venv/lib/python3.12/site-packages/torch/nn/modules/container.py", line 253, in forward + File "/home/batman/xx3/.venv/lib/python3.12/site-packages/torch/nn/modules/container.py", line 253, in forward input = module(input) - File "/home/batman/xx2/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1002, in forward + File "/home/batman/xx3/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1002, in forward x = x + self.drop_path(self.layer_scale(self.mlp(x))) - File "/home/batman/xx2/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 818, in forward + File "/home/batman/xx3/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 818, in forward x = self.fc2(x) - File "/home/batman/xx2/.venv/lib/python3.12/site-packages/torch/nn/modules/conv.py", line 553, in forward + File "/home/batman/xx3/.venv/lib/python3.12/site-packages/torch/nn/modules/conv.py", line 553, in forward return self._conv_forward(input, self.weight, self.bias)  conv2d_10 @@ -525,19 +525,19 @@ 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/xx2/./ml_tools/openpilot_compile/compile_supercombo.py", line 82, in forward +pkg.torch.onnx.stack_traceFile "/home/batman/xx3/./ml_tools/openpilot_compile/compile_supercombo.py", line 86, in forward return torch.cat([*self.forward_dict(inputs).values(), self.pad], dim=1) - File "/home/batman/xx2/xx/training/path/supercombo.py", line 191, in forward + File "/home/batman/xx3/xx/training/path/supercombo.py", line 191, in forward return {ModelInputs.FEATURES: self._en((x - self._mean) / self._std)} - File "/home/batman/xx2/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1418, in forward + File "/home/batman/xx3/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1418, in forward x = self.forward_features(x) - File "/home/batman/xx2/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1167, in forward + File "/home/batman/xx3/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1167, in forward x = self.blocks(x) - File "/home/batman/xx2/.venv/lib/python3.12/site-packages/torch/nn/modules/container.py", line 253, in forward + File "/home/batman/xx3/.venv/lib/python3.12/site-packages/torch/nn/modules/container.py", line 253, in forward input = module(input) - File "/home/batman/xx2/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1002, in forward + File "/home/batman/xx3/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1002, in forward x = x + self.drop_path(self.layer_scale(self.mlp(x))) - File "/home/batman/xx2/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 646, in forward + File "/home/batman/xx3/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 646, in forward return x.mul_(self.gamma) if self.inplace else x * self.gamma  conv2d_7 @@ -547,17 +547,17 @@ 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/xx2/./ml_tools/openpilot_compile/compile_supercombo.py", line 82, in forward +pkg.torch.onnx.stack_traceFile "/home/batman/xx3/./ml_tools/openpilot_compile/compile_supercombo.py", line 86, in forward return torch.cat([*self.forward_dict(inputs).values(), self.pad], dim=1) - File "/home/batman/xx2/xx/training/path/supercombo.py", line 191, in forward + File "/home/batman/xx3/xx/training/path/supercombo.py", line 191, in forward return {ModelInputs.FEATURES: self._en((x - self._mean) / self._std)} - File "/home/batman/xx2/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1418, in forward + File "/home/batman/xx3/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1418, in forward x = self.forward_features(x) - File "/home/batman/xx2/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1167, in forward + File "/home/batman/xx3/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1167, in forward x = self.blocks(x) - File "/home/batman/xx2/.venv/lib/python3.12/site-packages/torch/nn/modules/container.py", line 253, in forward + File "/home/batman/xx3/.venv/lib/python3.12/site-packages/torch/nn/modules/container.py", line 253, in forward input = module(input) - File "/home/batman/xx2/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1002, in forward + File "/home/batman/xx3/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1002, in forward x = x + self.drop_path(self.layer_scale(self.mlp(x)))  add_1 @@ -572,21 +572,21 @@ 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_trace File "/home/batman/xx2/./ml_tools/openpilot_compile/compile_supercombo.py", line 82, in forward +pkg.torch.onnx.stack_trace File "/home/batman/xx3/./ml_tools/openpilot_compile/compile_supercombo.py", line 86, in forward return torch.cat([*self.forward_dict(inputs).values(), self.pad], dim=1) - File "/home/batman/xx2/xx/training/path/supercombo.py", line 191, in forward + File "/home/batman/xx3/xx/training/path/supercombo.py", line 191, in forward return {ModelInputs.FEATURES: self._en((x - self._mean) / self._std)} - File "/home/batman/xx2/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1418, in forward + File "/home/batman/xx3/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1418, in forward x = self.forward_features(x) - File "/home/batman/xx2/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1162, in forward + File "/home/batman/xx3/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1162, in forward x = self.downsample(x) - File "/home/batman/xx2/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 628, in forward + File "/home/batman/xx3/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 628, in forward x = self.proj(x) - File "/home/batman/xx2/.venv/lib/python3.12/site-packages/torch/nn/modules/container.py", line 253, in forward + File "/home/batman/xx3/.venv/lib/python3.12/site-packages/torch/nn/modules/container.py", line 253, in forward input = module(input) - File "/home/batman/xx2/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 376, in forward + File "/home/batman/xx3/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 376, in forward out = self.reparam_conv(x) - File "/home/batman/xx2/.venv/lib/python3.12/site-packages/torch/nn/modules/conv.py", line 553, in forward + File "/home/batman/xx3/.venv/lib/python3.12/site-packages/torch/nn/modules/conv.py", line 553, in forward return self._conv_forward(input, self.weight, self.bias)  conv2d_11 @@ -601,21 +601,21 @@ 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_trace File "/home/batman/xx2/./ml_tools/openpilot_compile/compile_supercombo.py", line 82, in forward +pkg.torch.onnx.stack_trace File "/home/batman/xx3/./ml_tools/openpilot_compile/compile_supercombo.py", line 86, in forward return torch.cat([*self.forward_dict(inputs).values(), self.pad], dim=1) - File "/home/batman/xx2/xx/training/path/supercombo.py", line 191, in forward + File "/home/batman/xx3/xx/training/path/supercombo.py", line 191, in forward return {ModelInputs.FEATURES: self._en((x - self._mean) / self._std)} - File "/home/batman/xx2/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1418, in forward + File "/home/batman/xx3/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1418, in forward x = self.forward_features(x) - File "/home/batman/xx2/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1162, in forward + File "/home/batman/xx3/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1162, in forward x = self.downsample(x) - File "/home/batman/xx2/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 628, in forward + File "/home/batman/xx3/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 628, in forward x = self.proj(x) - File "/home/batman/xx2/.venv/lib/python3.12/site-packages/torch/nn/modules/container.py", line 253, in forward + File "/home/batman/xx3/.venv/lib/python3.12/site-packages/torch/nn/modules/container.py", line 253, in forward input = module(input) - File "/home/batman/xx2/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 155, in forward + File "/home/batman/xx3/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 155, in forward return self.act(self.se(self.reparam_conv(x))) - File "/home/batman/xx2/.venv/lib/python3.12/site-packages/torch/nn/modules/conv.py", line 553, in forward + File "/home/batman/xx3/.venv/lib/python3.12/site-packages/torch/nn/modules/conv.py", line 553, in forward return self._conv_forward(input, self.weight, self.bias)  conv2d_12gelu_5 node_gelu_5"Gelu* @@ -624,21 +624,21 @@ 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_trace File "/home/batman/xx2/./ml_tools/openpilot_compile/compile_supercombo.py", line 82, in forward +pkg.torch.onnx.stack_trace File "/home/batman/xx3/./ml_tools/openpilot_compile/compile_supercombo.py", line 86, in forward return torch.cat([*self.forward_dict(inputs).values(), self.pad], dim=1) - File "/home/batman/xx2/xx/training/path/supercombo.py", line 191, in forward + File "/home/batman/xx3/xx/training/path/supercombo.py", line 191, in forward return {ModelInputs.FEATURES: self._en((x - self._mean) / self._std)} - File "/home/batman/xx2/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1418, in forward + File "/home/batman/xx3/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1418, in forward x = self.forward_features(x) - File "/home/batman/xx2/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1162, in forward + File "/home/batman/xx3/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1162, in forward x = self.downsample(x) - File "/home/batman/xx2/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 628, in forward + File "/home/batman/xx3/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 628, in forward x = self.proj(x) - File "/home/batman/xx2/.venv/lib/python3.12/site-packages/torch/nn/modules/container.py", line 253, in forward + File "/home/batman/xx3/.venv/lib/python3.12/site-packages/torch/nn/modules/container.py", line 253, in forward input = module(input) - File "/home/batman/xx2/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 155, in forward + File "/home/batman/xx3/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 155, in forward return self.act(self.se(self.reparam_conv(x))) - File "/home/batman/xx2/.venv/lib/python3.12/site-packages/timm/layers/activations.py", line 159, in forward + File "/home/batman/xx3/.venv/lib/python3.12/site-packages/timm/layers/activations.py", line 159, in forward return F.gelu(input, approximate='tanh')  gelu_5 @@ -653,21 +653,21 @@ 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_trace File "/home/batman/xx2/./ml_tools/openpilot_compile/compile_supercombo.py", line 82, in forward +pkg.torch.onnx.stack_trace File "/home/batman/xx3/./ml_tools/openpilot_compile/compile_supercombo.py", line 86, in forward return torch.cat([*self.forward_dict(inputs).values(), self.pad], dim=1) - File "/home/batman/xx2/xx/training/path/supercombo.py", line 191, in forward + File "/home/batman/xx3/xx/training/path/supercombo.py", line 191, in forward return {ModelInputs.FEATURES: self._en((x - self._mean) / self._std)} - File "/home/batman/xx2/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1418, in forward + File "/home/batman/xx3/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1418, in forward x = self.forward_features(x) - File "/home/batman/xx2/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1167, in forward + File "/home/batman/xx3/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1167, in forward x = self.blocks(x) - File "/home/batman/xx2/.venv/lib/python3.12/site-packages/torch/nn/modules/container.py", line 253, in forward + File "/home/batman/xx3/.venv/lib/python3.12/site-packages/torch/nn/modules/container.py", line 253, in forward input = module(input) - File "/home/batman/xx2/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1001, in forward + File "/home/batman/xx3/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1001, in forward x = self.token_mixer(x) - File "/home/batman/xx2/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 717, in forward + File "/home/batman/xx3/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 717, in forward x = self.reparam_conv(x) - File "/home/batman/xx2/.venv/lib/python3.12/site-packages/torch/nn/modules/conv.py", line 553, in forward + File "/home/batman/xx3/.venv/lib/python3.12/site-packages/torch/nn/modules/conv.py", line 553, in forward return self._conv_forward(input, self.weight, self.bias)  conv2d_13 @@ -685,23 +685,23 @@ Cvision_model.vision._en.stages.1.blocks.0.mlp.conv.conv.weight_bias getitem_6 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/xx2/./ml_tools/openpilot_compile/compile_supercombo.py", line 82, in forward +File "/home/batman/xx3/./ml_tools/openpilot_compile/compile_supercombo.py", line 86, in forward return torch.cat([*self.forward_dict(inputs).values(), self.pad], dim=1) - File "/home/batman/xx2/xx/training/path/supercombo.py", line 191, in forward + File "/home/batman/xx3/xx/training/path/supercombo.py", line 191, in forward return {ModelInputs.FEATURES: self._en((x - self._mean) / self._std)} - File "/home/batman/xx2/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1418, in forward + File "/home/batman/xx3/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1418, in forward x = self.forward_features(x) - File "/home/batman/xx2/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1167, in forward + File "/home/batman/xx3/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1167, in forward x = self.blocks(x) - File "/home/batman/xx2/.venv/lib/python3.12/site-packages/torch/nn/modules/container.py", line 253, in forward + File "/home/batman/xx3/.venv/lib/python3.12/site-packages/torch/nn/modules/container.py", line 253, in forward input = module(input) - File "/home/batman/xx2/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1002, in forward + File "/home/batman/xx3/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1002, in forward x = x + self.drop_path(self.layer_scale(self.mlp(x))) - File "/home/batman/xx2/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 814, in forward + File "/home/batman/xx3/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 814, in forward x = self.conv(x) - File "/home/batman/xx2/.venv/lib/python3.12/site-packages/timm/layers/conv_bn_act.py", line 94, in forward + File "/home/batman/xx3/.venv/lib/python3.12/site-packages/timm/layers/conv_bn_act.py", line 94, in forward x = self.bn(x) - File "/home/batman/xx2/xx/training/path/allnorm.py", line 60, in forward + File "/home/batman/xx3/xx/training/path/allnorm.py", line 60, in forward return self.act(self.drop(self._allnorm_forward(x)))  getitem_6 @@ -716,21 +716,21 @@ File "/home/batman/xx2/./ml_tools/openpilot_compile/compile_supercombo.py", line 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/xx2/./ml_tools/openpilot_compile/compile_supercombo.py", line 82, in forward +pkg.torch.onnx.stack_trace File "/home/batman/xx3/./ml_tools/openpilot_compile/compile_supercombo.py", line 86, in forward return torch.cat([*self.forward_dict(inputs).values(), self.pad], dim=1) - File "/home/batman/xx2/xx/training/path/supercombo.py", line 191, in forward + File "/home/batman/xx3/xx/training/path/supercombo.py", line 191, in forward return {ModelInputs.FEATURES: self._en((x - self._mean) / self._std)} - File "/home/batman/xx2/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1418, in forward + File "/home/batman/xx3/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1418, in forward x = self.forward_features(x) - File "/home/batman/xx2/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1167, in forward + File "/home/batman/xx3/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1167, in forward x = self.blocks(x) - File "/home/batman/xx2/.venv/lib/python3.12/site-packages/torch/nn/modules/container.py", line 253, in forward + File "/home/batman/xx3/.venv/lib/python3.12/site-packages/torch/nn/modules/container.py", line 253, in forward input = module(input) - File "/home/batman/xx2/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1002, in forward + File "/home/batman/xx3/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1002, in forward x = x + self.drop_path(self.layer_scale(self.mlp(x))) - File "/home/batman/xx2/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 815, in forward + File "/home/batman/xx3/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 815, in forward x = self.fc1(x) - File "/home/batman/xx2/.venv/lib/python3.12/site-packages/torch/nn/modules/conv.py", line 553, in forward + File "/home/batman/xx3/.venv/lib/python3.12/site-packages/torch/nn/modules/conv.py", line 553, in forward return self._conv_forward(input, self.weight, self.bias)  conv2d_15gelu_6 node_gelu_6"Gelu* @@ -739,21 +739,21 @@ File "/home/batman/xx2/./ml_tools/openpilot_compile/compile_supercombo.py", line 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_trace File "/home/batman/xx2/./ml_tools/openpilot_compile/compile_supercombo.py", line 82, in forward +pkg.torch.onnx.stack_trace File "/home/batman/xx3/./ml_tools/openpilot_compile/compile_supercombo.py", line 86, in forward return torch.cat([*self.forward_dict(inputs).values(), self.pad], dim=1) - File "/home/batman/xx2/xx/training/path/supercombo.py", line 191, in forward + File "/home/batman/xx3/xx/training/path/supercombo.py", line 191, in forward return {ModelInputs.FEATURES: self._en((x - self._mean) / self._std)} - File "/home/batman/xx2/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1418, in forward + File "/home/batman/xx3/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1418, in forward x = self.forward_features(x) - File "/home/batman/xx2/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1167, in forward + File "/home/batman/xx3/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1167, in forward x = self.blocks(x) - File "/home/batman/xx2/.venv/lib/python3.12/site-packages/torch/nn/modules/container.py", line 253, in forward + File "/home/batman/xx3/.venv/lib/python3.12/site-packages/torch/nn/modules/container.py", line 253, in forward input = module(input) - File "/home/batman/xx2/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1002, in forward + File "/home/batman/xx3/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1002, in forward x = x + self.drop_path(self.layer_scale(self.mlp(x))) - File "/home/batman/xx2/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 816, in forward + File "/home/batman/xx3/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 816, in forward x = self.act(x) - File "/home/batman/xx2/.venv/lib/python3.12/site-packages/timm/layers/activations.py", line 159, in forward + File "/home/batman/xx3/.venv/lib/python3.12/site-packages/timm/layers/activations.py", line 159, in forward return F.gelu(input, approximate='tanh')  gelu_6 @@ -768,21 +768,21 @@ File "/home/batman/xx2/./ml_tools/openpilot_compile/compile_supercombo.py", line 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/xx2/./ml_tools/openpilot_compile/compile_supercombo.py", line 82, in forward +pkg.torch.onnx.stack_trace File "/home/batman/xx3/./ml_tools/openpilot_compile/compile_supercombo.py", line 86, in forward return torch.cat([*self.forward_dict(inputs).values(), self.pad], dim=1) - File "/home/batman/xx2/xx/training/path/supercombo.py", line 191, in forward + File "/home/batman/xx3/xx/training/path/supercombo.py", line 191, in forward return {ModelInputs.FEATURES: self._en((x - self._mean) / self._std)} - File "/home/batman/xx2/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1418, in forward + File "/home/batman/xx3/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1418, in forward x = self.forward_features(x) - File "/home/batman/xx2/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1167, in forward + File "/home/batman/xx3/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1167, in forward x = self.blocks(x) - File "/home/batman/xx2/.venv/lib/python3.12/site-packages/torch/nn/modules/container.py", line 253, in forward + File "/home/batman/xx3/.venv/lib/python3.12/site-packages/torch/nn/modules/container.py", line 253, in forward input = module(input) - File "/home/batman/xx2/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1002, in forward + File "/home/batman/xx3/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1002, in forward x = x + self.drop_path(self.layer_scale(self.mlp(x))) - File "/home/batman/xx2/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 818, in forward + File "/home/batman/xx3/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 818, in forward x = self.fc2(x) - File "/home/batman/xx2/.venv/lib/python3.12/site-packages/torch/nn/modules/conv.py", line 553, in forward + File "/home/batman/xx3/.venv/lib/python3.12/site-packages/torch/nn/modules/conv.py", line 553, in forward return self._conv_forward(input, self.weight, self.bias)  conv2d_16 @@ -792,19 +792,19 @@ 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/xx2/./ml_tools/openpilot_compile/compile_supercombo.py", line 82, in forward +pkg.torch.onnx.stack_traceFile "/home/batman/xx3/./ml_tools/openpilot_compile/compile_supercombo.py", line 86, in forward return torch.cat([*self.forward_dict(inputs).values(), self.pad], dim=1) - File "/home/batman/xx2/xx/training/path/supercombo.py", line 191, in forward + File "/home/batman/xx3/xx/training/path/supercombo.py", line 191, in forward return {ModelInputs.FEATURES: self._en((x - self._mean) / self._std)} - File "/home/batman/xx2/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1418, in forward + File "/home/batman/xx3/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1418, in forward x = self.forward_features(x) - File "/home/batman/xx2/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1167, in forward + File "/home/batman/xx3/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1167, in forward x = self.blocks(x) - File "/home/batman/xx2/.venv/lib/python3.12/site-packages/torch/nn/modules/container.py", line 253, in forward + File "/home/batman/xx3/.venv/lib/python3.12/site-packages/torch/nn/modules/container.py", line 253, in forward input = module(input) - File "/home/batman/xx2/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1002, in forward + File "/home/batman/xx3/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1002, in forward x = x + self.drop_path(self.layer_scale(self.mlp(x))) - File "/home/batman/xx2/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 646, in forward + File "/home/batman/xx3/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 646, in forward return x.mul_(self.gamma) if self.inplace else x * self.gamma  conv2d_13 @@ -814,17 +814,17 @@ 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/xx2/./ml_tools/openpilot_compile/compile_supercombo.py", line 82, in forward +pkg.torch.onnx.stack_traceFile "/home/batman/xx3/./ml_tools/openpilot_compile/compile_supercombo.py", line 86, in forward return torch.cat([*self.forward_dict(inputs).values(), self.pad], dim=1) - File "/home/batman/xx2/xx/training/path/supercombo.py", line 191, in forward + File "/home/batman/xx3/xx/training/path/supercombo.py", line 191, in forward return {ModelInputs.FEATURES: self._en((x - self._mean) / self._std)} - File "/home/batman/xx2/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1418, in forward + File "/home/batman/xx3/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1418, in forward x = self.forward_features(x) - File "/home/batman/xx2/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1167, in forward + File "/home/batman/xx3/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1167, in forward x = self.blocks(x) - File "/home/batman/xx2/.venv/lib/python3.12/site-packages/torch/nn/modules/container.py", line 253, in forward + File "/home/batman/xx3/.venv/lib/python3.12/site-packages/torch/nn/modules/container.py", line 253, in forward input = module(input) - File "/home/batman/xx2/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1002, in forward + File "/home/batman/xx3/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1002, in forward x = x + self.drop_path(self.layer_scale(self.mlp(x)))  add_2 @@ -839,21 +839,21 @@ 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_trace File "/home/batman/xx2/./ml_tools/openpilot_compile/compile_supercombo.py", line 82, in forward +pkg.torch.onnx.stack_trace File "/home/batman/xx3/./ml_tools/openpilot_compile/compile_supercombo.py", line 86, in forward return torch.cat([*self.forward_dict(inputs).values(), self.pad], dim=1) - File "/home/batman/xx2/xx/training/path/supercombo.py", line 191, in forward + File "/home/batman/xx3/xx/training/path/supercombo.py", line 191, in forward return {ModelInputs.FEATURES: self._en((x - self._mean) / self._std)} - File "/home/batman/xx2/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1418, in forward + File "/home/batman/xx3/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1418, in forward x = self.forward_features(x) - File "/home/batman/xx2/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1167, in forward + File "/home/batman/xx3/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1167, in forward x = self.blocks(x) - File "/home/batman/xx2/.venv/lib/python3.12/site-packages/torch/nn/modules/container.py", line 253, in forward + File "/home/batman/xx3/.venv/lib/python3.12/site-packages/torch/nn/modules/container.py", line 253, in forward input = module(input) - File "/home/batman/xx2/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1001, in forward + File "/home/batman/xx3/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1001, in forward x = self.token_mixer(x) - File "/home/batman/xx2/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 717, in forward + File "/home/batman/xx3/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 717, in forward x = self.reparam_conv(x) - File "/home/batman/xx2/.venv/lib/python3.12/site-packages/torch/nn/modules/conv.py", line 553, in forward + File "/home/batman/xx3/.venv/lib/python3.12/site-packages/torch/nn/modules/conv.py", line 553, in forward return self._conv_forward(input, self.weight, self.bias)  conv2d_17 @@ -871,23 +871,23 @@ Cvision_model.vision._en.stages.1.blocks.1.mlp.conv.conv.weight_bias getitem_9 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/xx2/./ml_tools/openpilot_compile/compile_supercombo.py", line 82, in forward +File "/home/batman/xx3/./ml_tools/openpilot_compile/compile_supercombo.py", line 86, in forward return torch.cat([*self.forward_dict(inputs).values(), self.pad], dim=1) - File "/home/batman/xx2/xx/training/path/supercombo.py", line 191, in forward + File "/home/batman/xx3/xx/training/path/supercombo.py", line 191, in forward return {ModelInputs.FEATURES: self._en((x - self._mean) / self._std)} - File "/home/batman/xx2/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1418, in forward + File "/home/batman/xx3/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1418, in forward x = self.forward_features(x) - File "/home/batman/xx2/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1167, in forward + File "/home/batman/xx3/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1167, in forward x = self.blocks(x) - File "/home/batman/xx2/.venv/lib/python3.12/site-packages/torch/nn/modules/container.py", line 253, in forward + File "/home/batman/xx3/.venv/lib/python3.12/site-packages/torch/nn/modules/container.py", line 253, in forward input = module(input) - File "/home/batman/xx2/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1002, in forward + File "/home/batman/xx3/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1002, in forward x = x + self.drop_path(self.layer_scale(self.mlp(x))) - File "/home/batman/xx2/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 814, in forward + File "/home/batman/xx3/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 814, in forward x = self.conv(x) - File "/home/batman/xx2/.venv/lib/python3.12/site-packages/timm/layers/conv_bn_act.py", line 94, in forward + File "/home/batman/xx3/.venv/lib/python3.12/site-packages/timm/layers/conv_bn_act.py", line 94, in forward x = self.bn(x) - File "/home/batman/xx2/xx/training/path/allnorm.py", line 60, in forward + File "/home/batman/xx3/xx/training/path/allnorm.py", line 60, in forward return self.act(self.drop(self._allnorm_forward(x)))  getitem_9 @@ -902,21 +902,21 @@ File "/home/batman/xx2/./ml_tools/openpilot_compile/compile_supercombo.py", line 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/xx2/./ml_tools/openpilot_compile/compile_supercombo.py", line 82, in forward +pkg.torch.onnx.stack_trace File "/home/batman/xx3/./ml_tools/openpilot_compile/compile_supercombo.py", line 86, in forward return torch.cat([*self.forward_dict(inputs).values(), self.pad], dim=1) - File "/home/batman/xx2/xx/training/path/supercombo.py", line 191, in forward + File "/home/batman/xx3/xx/training/path/supercombo.py", line 191, in forward return {ModelInputs.FEATURES: self._en((x - self._mean) / self._std)} - File "/home/batman/xx2/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1418, in forward + File "/home/batman/xx3/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1418, in forward x = self.forward_features(x) - File "/home/batman/xx2/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1167, in forward + File "/home/batman/xx3/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1167, in forward x = self.blocks(x) - File "/home/batman/xx2/.venv/lib/python3.12/site-packages/torch/nn/modules/container.py", line 253, in forward + File "/home/batman/xx3/.venv/lib/python3.12/site-packages/torch/nn/modules/container.py", line 253, in forward input = module(input) - File "/home/batman/xx2/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1002, in forward + File "/home/batman/xx3/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1002, in forward x = x + self.drop_path(self.layer_scale(self.mlp(x))) - File "/home/batman/xx2/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 815, in forward + File "/home/batman/xx3/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 815, in forward x = self.fc1(x) - File "/home/batman/xx2/.venv/lib/python3.12/site-packages/torch/nn/modules/conv.py", line 553, in forward + File "/home/batman/xx3/.venv/lib/python3.12/site-packages/torch/nn/modules/conv.py", line 553, in forward return self._conv_forward(input, self.weight, self.bias)  conv2d_19gelu_7 node_gelu_7"Gelu* @@ -925,21 +925,21 @@ File "/home/batman/xx2/./ml_tools/openpilot_compile/compile_supercombo.py", line 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_trace File "/home/batman/xx2/./ml_tools/openpilot_compile/compile_supercombo.py", line 82, in forward +pkg.torch.onnx.stack_trace File "/home/batman/xx3/./ml_tools/openpilot_compile/compile_supercombo.py", line 86, in forward return torch.cat([*self.forward_dict(inputs).values(), self.pad], dim=1) - File "/home/batman/xx2/xx/training/path/supercombo.py", line 191, in forward + File "/home/batman/xx3/xx/training/path/supercombo.py", line 191, in forward return {ModelInputs.FEATURES: self._en((x - self._mean) / self._std)} - File "/home/batman/xx2/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1418, in forward + File "/home/batman/xx3/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1418, in forward x = self.forward_features(x) - File "/home/batman/xx2/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1167, in forward + File "/home/batman/xx3/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1167, in forward x = self.blocks(x) - File "/home/batman/xx2/.venv/lib/python3.12/site-packages/torch/nn/modules/container.py", line 253, in forward + File "/home/batman/xx3/.venv/lib/python3.12/site-packages/torch/nn/modules/container.py", line 253, in forward input = module(input) - File "/home/batman/xx2/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1002, in forward + File "/home/batman/xx3/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1002, in forward x = x + self.drop_path(self.layer_scale(self.mlp(x))) - File "/home/batman/xx2/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 816, in forward + File "/home/batman/xx3/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 816, in forward x = self.act(x) - File "/home/batman/xx2/.venv/lib/python3.12/site-packages/timm/layers/activations.py", line 159, in forward + File "/home/batman/xx3/.venv/lib/python3.12/site-packages/timm/layers/activations.py", line 159, in forward return F.gelu(input, approximate='tanh')  gelu_7 @@ -954,21 +954,21 @@ File "/home/batman/xx2/./ml_tools/openpilot_compile/compile_supercombo.py", line 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/xx2/./ml_tools/openpilot_compile/compile_supercombo.py", line 82, in forward +pkg.torch.onnx.stack_trace File "/home/batman/xx3/./ml_tools/openpilot_compile/compile_supercombo.py", line 86, in forward return torch.cat([*self.forward_dict(inputs).values(), self.pad], dim=1) - File "/home/batman/xx2/xx/training/path/supercombo.py", line 191, in forward + File "/home/batman/xx3/xx/training/path/supercombo.py", line 191, in forward return {ModelInputs.FEATURES: self._en((x - self._mean) / self._std)} - File "/home/batman/xx2/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1418, in forward + File "/home/batman/xx3/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1418, in forward x = self.forward_features(x) - File "/home/batman/xx2/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1167, in forward + File "/home/batman/xx3/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1167, in forward x = self.blocks(x) - File "/home/batman/xx2/.venv/lib/python3.12/site-packages/torch/nn/modules/container.py", line 253, in forward + File "/home/batman/xx3/.venv/lib/python3.12/site-packages/torch/nn/modules/container.py", line 253, in forward input = module(input) - File "/home/batman/xx2/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1002, in forward + File "/home/batman/xx3/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1002, in forward x = x + self.drop_path(self.layer_scale(self.mlp(x))) - File "/home/batman/xx2/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 818, in forward + File "/home/batman/xx3/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 818, in forward x = self.fc2(x) - File "/home/batman/xx2/.venv/lib/python3.12/site-packages/torch/nn/modules/conv.py", line 553, in forward + File "/home/batman/xx3/.venv/lib/python3.12/site-packages/torch/nn/modules/conv.py", line 553, in forward return self._conv_forward(input, self.weight, self.bias)  conv2d_20 @@ -978,19 +978,19 @@ 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/xx2/./ml_tools/openpilot_compile/compile_supercombo.py", line 82, in forward +pkg.torch.onnx.stack_traceFile "/home/batman/xx3/./ml_tools/openpilot_compile/compile_supercombo.py", line 86, in forward return torch.cat([*self.forward_dict(inputs).values(), self.pad], dim=1) - File "/home/batman/xx2/xx/training/path/supercombo.py", line 191, in forward + File "/home/batman/xx3/xx/training/path/supercombo.py", line 191, in forward return {ModelInputs.FEATURES: self._en((x - self._mean) / self._std)} - File "/home/batman/xx2/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1418, in forward + File "/home/batman/xx3/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1418, in forward x = self.forward_features(x) - File "/home/batman/xx2/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1167, in forward + File "/home/batman/xx3/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1167, in forward x = self.blocks(x) - File "/home/batman/xx2/.venv/lib/python3.12/site-packages/torch/nn/modules/container.py", line 253, in forward + File "/home/batman/xx3/.venv/lib/python3.12/site-packages/torch/nn/modules/container.py", line 253, in forward input = module(input) - File "/home/batman/xx2/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1002, in forward + File "/home/batman/xx3/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1002, in forward x = x + self.drop_path(self.layer_scale(self.mlp(x))) - File "/home/batman/xx2/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 646, in forward + File "/home/batman/xx3/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 646, in forward return x.mul_(self.gamma) if self.inplace else x * self.gamma  conv2d_17 @@ -1000,17 +1000,17 @@ 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/xx2/./ml_tools/openpilot_compile/compile_supercombo.py", line 82, in forward +pkg.torch.onnx.stack_traceFile "/home/batman/xx3/./ml_tools/openpilot_compile/compile_supercombo.py", line 86, in forward return torch.cat([*self.forward_dict(inputs).values(), self.pad], dim=1) - File "/home/batman/xx2/xx/training/path/supercombo.py", line 191, in forward + File "/home/batman/xx3/xx/training/path/supercombo.py", line 191, in forward return {ModelInputs.FEATURES: self._en((x - self._mean) / self._std)} - File "/home/batman/xx2/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1418, in forward + File "/home/batman/xx3/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1418, in forward x = self.forward_features(x) - File "/home/batman/xx2/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1167, in forward + File "/home/batman/xx3/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1167, in forward x = self.blocks(x) - File "/home/batman/xx2/.venv/lib/python3.12/site-packages/torch/nn/modules/container.py", line 253, in forward + File "/home/batman/xx3/.venv/lib/python3.12/site-packages/torch/nn/modules/container.py", line 253, in forward input = module(input) - File "/home/batman/xx2/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1002, in forward + File "/home/batman/xx3/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1002, in forward x = x + self.drop_path(self.layer_scale(self.mlp(x)))  add_3 @@ -1025,21 +1025,21 @@ 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_trace File "/home/batman/xx2/./ml_tools/openpilot_compile/compile_supercombo.py", line 82, in forward +pkg.torch.onnx.stack_trace File "/home/batman/xx3/./ml_tools/openpilot_compile/compile_supercombo.py", line 86, in forward return torch.cat([*self.forward_dict(inputs).values(), self.pad], dim=1) - File "/home/batman/xx2/xx/training/path/supercombo.py", line 191, in forward + File "/home/batman/xx3/xx/training/path/supercombo.py", line 191, in forward return {ModelInputs.FEATURES: self._en((x - self._mean) / self._std)} - File "/home/batman/xx2/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1418, in forward + File "/home/batman/xx3/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1418, in forward x = self.forward_features(x) - File "/home/batman/xx2/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1162, in forward + File "/home/batman/xx3/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1162, in forward x = self.downsample(x) - File "/home/batman/xx2/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 628, in forward + File "/home/batman/xx3/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 628, in forward x = self.proj(x) - File "/home/batman/xx2/.venv/lib/python3.12/site-packages/torch/nn/modules/container.py", line 253, in forward + File "/home/batman/xx3/.venv/lib/python3.12/site-packages/torch/nn/modules/container.py", line 253, in forward input = module(input) - File "/home/batman/xx2/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 376, in forward + File "/home/batman/xx3/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 376, in forward out = self.reparam_conv(x) - File "/home/batman/xx2/.venv/lib/python3.12/site-packages/torch/nn/modules/conv.py", line 553, in forward + File "/home/batman/xx3/.venv/lib/python3.12/site-packages/torch/nn/modules/conv.py", line 553, in forward return self._conv_forward(input, self.weight, self.bias)  conv2d_21 @@ -1054,21 +1054,21 @@ 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_trace File "/home/batman/xx2/./ml_tools/openpilot_compile/compile_supercombo.py", line 82, in forward +pkg.torch.onnx.stack_trace File "/home/batman/xx3/./ml_tools/openpilot_compile/compile_supercombo.py", line 86, in forward return torch.cat([*self.forward_dict(inputs).values(), self.pad], dim=1) - File "/home/batman/xx2/xx/training/path/supercombo.py", line 191, in forward + File "/home/batman/xx3/xx/training/path/supercombo.py", line 191, in forward return {ModelInputs.FEATURES: self._en((x - self._mean) / self._std)} - File "/home/batman/xx2/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1418, in forward + File "/home/batman/xx3/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1418, in forward x = self.forward_features(x) - File "/home/batman/xx2/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1162, in forward + File "/home/batman/xx3/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1162, in forward x = self.downsample(x) - File "/home/batman/xx2/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 628, in forward + File "/home/batman/xx3/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 628, in forward x = self.proj(x) - File "/home/batman/xx2/.venv/lib/python3.12/site-packages/torch/nn/modules/container.py", line 253, in forward + File "/home/batman/xx3/.venv/lib/python3.12/site-packages/torch/nn/modules/container.py", line 253, in forward input = module(input) - File "/home/batman/xx2/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 155, in forward + File "/home/batman/xx3/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 155, in forward return self.act(self.se(self.reparam_conv(x))) - File "/home/batman/xx2/.venv/lib/python3.12/site-packages/torch/nn/modules/conv.py", line 553, in forward + File "/home/batman/xx3/.venv/lib/python3.12/site-packages/torch/nn/modules/conv.py", line 553, in forward return self._conv_forward(input, self.weight, self.bias)  conv2d_22gelu_8 node_gelu_8"Gelu* @@ -1077,21 +1077,21 @@ 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_trace File "/home/batman/xx2/./ml_tools/openpilot_compile/compile_supercombo.py", line 82, in forward +pkg.torch.onnx.stack_trace File "/home/batman/xx3/./ml_tools/openpilot_compile/compile_supercombo.py", line 86, in forward return torch.cat([*self.forward_dict(inputs).values(), self.pad], dim=1) - File "/home/batman/xx2/xx/training/path/supercombo.py", line 191, in forward + File "/home/batman/xx3/xx/training/path/supercombo.py", line 191, in forward return {ModelInputs.FEATURES: self._en((x - self._mean) / self._std)} - File "/home/batman/xx2/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1418, in forward + File "/home/batman/xx3/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1418, in forward x = self.forward_features(x) - File "/home/batman/xx2/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1162, in forward + File "/home/batman/xx3/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1162, in forward x = self.downsample(x) - File "/home/batman/xx2/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 628, in forward + File "/home/batman/xx3/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 628, in forward x = self.proj(x) - File "/home/batman/xx2/.venv/lib/python3.12/site-packages/torch/nn/modules/container.py", line 253, in forward + File "/home/batman/xx3/.venv/lib/python3.12/site-packages/torch/nn/modules/container.py", line 253, in forward input = module(input) - File "/home/batman/xx2/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 155, in forward + File "/home/batman/xx3/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 155, in forward return self.act(self.se(self.reparam_conv(x))) - File "/home/batman/xx2/.venv/lib/python3.12/site-packages/timm/layers/activations.py", line 159, in forward + File "/home/batman/xx3/.venv/lib/python3.12/site-packages/timm/layers/activations.py", line 159, in forward return F.gelu(input, approximate='tanh')  gelu_8 @@ -1106,21 +1106,21 @@ 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_trace File "/home/batman/xx2/./ml_tools/openpilot_compile/compile_supercombo.py", line 82, in forward +pkg.torch.onnx.stack_trace File "/home/batman/xx3/./ml_tools/openpilot_compile/compile_supercombo.py", line 86, in forward return torch.cat([*self.forward_dict(inputs).values(), self.pad], dim=1) - File "/home/batman/xx2/xx/training/path/supercombo.py", line 191, in forward + File "/home/batman/xx3/xx/training/path/supercombo.py", line 191, in forward return {ModelInputs.FEATURES: self._en((x - self._mean) / self._std)} - File "/home/batman/xx2/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1418, in forward + File "/home/batman/xx3/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1418, in forward x = self.forward_features(x) - File "/home/batman/xx2/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1167, in forward + File "/home/batman/xx3/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1167, in forward x = self.blocks(x) - File "/home/batman/xx2/.venv/lib/python3.12/site-packages/torch/nn/modules/container.py", line 253, in forward + File "/home/batman/xx3/.venv/lib/python3.12/site-packages/torch/nn/modules/container.py", line 253, in forward input = module(input) - File "/home/batman/xx2/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1001, in forward + File "/home/batman/xx3/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1001, in forward x = self.token_mixer(x) - File "/home/batman/xx2/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 717, in forward + File "/home/batman/xx3/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 717, in forward x = self.reparam_conv(x) - File "/home/batman/xx2/.venv/lib/python3.12/site-packages/torch/nn/modules/conv.py", line 553, in forward + File "/home/batman/xx3/.venv/lib/python3.12/site-packages/torch/nn/modules/conv.py", line 553, in forward return self._conv_forward(input, self.weight, self.bias)  conv2d_23 @@ -1139,23 +1139,23 @@ getitem_12 node_Conv_291"Conv* 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/xx2/./ml_tools/openpilot_compile/compile_supercombo.py", line 82, in forward +File "/home/batman/xx3/./ml_tools/openpilot_compile/compile_supercombo.py", line 86, in forward return torch.cat([*self.forward_dict(inputs).values(), self.pad], dim=1) - File "/home/batman/xx2/xx/training/path/supercombo.py", line 191, in forward + File "/home/batman/xx3/xx/training/path/supercombo.py", line 191, in forward return {ModelInputs.FEATURES: self._en((x - self._mean) / self._std)} - File "/home/batman/xx2/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1418, in forward + File "/home/batman/xx3/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1418, in forward x = self.forward_features(x) - File "/home/batman/xx2/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1167, in forward + File "/home/batman/xx3/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1167, in forward x = self.blocks(x) - File "/home/batman/xx2/.venv/lib/python3.12/site-packages/torch/nn/modules/container.py", line 253, in forward + File "/home/batman/xx3/.venv/lib/python3.12/site-packages/torch/nn/modules/container.py", line 253, in forward input = module(input) - File "/home/batman/xx2/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1002, in forward + File "/home/batman/xx3/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1002, in forward x = x + self.drop_path(self.layer_scale(self.mlp(x))) - File "/home/batman/xx2/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 814, in forward + File "/home/batman/xx3/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 814, in forward x = self.conv(x) - File "/home/batman/xx2/.venv/lib/python3.12/site-packages/timm/layers/conv_bn_act.py", line 94, in forward + File "/home/batman/xx3/.venv/lib/python3.12/site-packages/timm/layers/conv_bn_act.py", line 94, in forward x = self.bn(x) - File "/home/batman/xx2/xx/training/path/allnorm.py", line 60, in forward + File "/home/batman/xx3/xx/training/path/allnorm.py", line 60, in forward return self.act(self.drop(self._allnorm_forward(x)))  @@ -1171,21 +1171,21 @@ 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/xx2/./ml_tools/openpilot_compile/compile_supercombo.py", line 82, in forward +pkg.torch.onnx.stack_trace File "/home/batman/xx3/./ml_tools/openpilot_compile/compile_supercombo.py", line 86, in forward return torch.cat([*self.forward_dict(inputs).values(), self.pad], dim=1) - File "/home/batman/xx2/xx/training/path/supercombo.py", line 191, in forward + File "/home/batman/xx3/xx/training/path/supercombo.py", line 191, in forward return {ModelInputs.FEATURES: self._en((x - self._mean) / self._std)} - File "/home/batman/xx2/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1418, in forward + File "/home/batman/xx3/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1418, in forward x = self.forward_features(x) - File "/home/batman/xx2/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1167, in forward + File "/home/batman/xx3/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1167, in forward x = self.blocks(x) - File "/home/batman/xx2/.venv/lib/python3.12/site-packages/torch/nn/modules/container.py", line 253, in forward + File "/home/batman/xx3/.venv/lib/python3.12/site-packages/torch/nn/modules/container.py", line 253, in forward input = module(input) - File "/home/batman/xx2/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1002, in forward + File "/home/batman/xx3/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1002, in forward x = x + self.drop_path(self.layer_scale(self.mlp(x))) - File "/home/batman/xx2/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 815, in forward + File "/home/batman/xx3/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 815, in forward x = self.fc1(x) - File "/home/batman/xx2/.venv/lib/python3.12/site-packages/torch/nn/modules/conv.py", line 553, in forward + File "/home/batman/xx3/.venv/lib/python3.12/site-packages/torch/nn/modules/conv.py", line 553, in forward return self._conv_forward(input, self.weight, self.bias)  conv2d_25gelu_9 node_gelu_9"Gelu* @@ -1194,21 +1194,21 @@ 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_trace File "/home/batman/xx2/./ml_tools/openpilot_compile/compile_supercombo.py", line 82, in forward +pkg.torch.onnx.stack_trace File "/home/batman/xx3/./ml_tools/openpilot_compile/compile_supercombo.py", line 86, in forward return torch.cat([*self.forward_dict(inputs).values(), self.pad], dim=1) - File "/home/batman/xx2/xx/training/path/supercombo.py", line 191, in forward + File "/home/batman/xx3/xx/training/path/supercombo.py", line 191, in forward return {ModelInputs.FEATURES: self._en((x - self._mean) / self._std)} - File "/home/batman/xx2/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1418, in forward + File "/home/batman/xx3/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1418, in forward x = self.forward_features(x) - File "/home/batman/xx2/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1167, in forward + File "/home/batman/xx3/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1167, in forward x = self.blocks(x) - File "/home/batman/xx2/.venv/lib/python3.12/site-packages/torch/nn/modules/container.py", line 253, in forward + File "/home/batman/xx3/.venv/lib/python3.12/site-packages/torch/nn/modules/container.py", line 253, in forward input = module(input) - File "/home/batman/xx2/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1002, in forward + File "/home/batman/xx3/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1002, in forward x = x + self.drop_path(self.layer_scale(self.mlp(x))) - File "/home/batman/xx2/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 816, in forward + File "/home/batman/xx3/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 816, in forward x = self.act(x) - File "/home/batman/xx2/.venv/lib/python3.12/site-packages/timm/layers/activations.py", line 159, in forward + File "/home/batman/xx3/.venv/lib/python3.12/site-packages/timm/layers/activations.py", line 159, in forward return F.gelu(input, approximate='tanh')  gelu_9 @@ -1223,21 +1223,21 @@ 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/xx2/./ml_tools/openpilot_compile/compile_supercombo.py", line 82, in forward +pkg.torch.onnx.stack_trace File "/home/batman/xx3/./ml_tools/openpilot_compile/compile_supercombo.py", line 86, in forward return torch.cat([*self.forward_dict(inputs).values(), self.pad], dim=1) - File "/home/batman/xx2/xx/training/path/supercombo.py", line 191, in forward + File "/home/batman/xx3/xx/training/path/supercombo.py", line 191, in forward return {ModelInputs.FEATURES: self._en((x - self._mean) / self._std)} - File "/home/batman/xx2/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1418, in forward + File "/home/batman/xx3/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1418, in forward x = self.forward_features(x) - File "/home/batman/xx2/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1167, in forward + File "/home/batman/xx3/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1167, in forward x = self.blocks(x) - File "/home/batman/xx2/.venv/lib/python3.12/site-packages/torch/nn/modules/container.py", line 253, in forward + File "/home/batman/xx3/.venv/lib/python3.12/site-packages/torch/nn/modules/container.py", line 253, in forward input = module(input) - File "/home/batman/xx2/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1002, in forward + File "/home/batman/xx3/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1002, in forward x = x + self.drop_path(self.layer_scale(self.mlp(x))) - File "/home/batman/xx2/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 818, in forward + File "/home/batman/xx3/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 818, in forward x = self.fc2(x) - File "/home/batman/xx2/.venv/lib/python3.12/site-packages/torch/nn/modules/conv.py", line 553, in forward + File "/home/batman/xx3/.venv/lib/python3.12/site-packages/torch/nn/modules/conv.py", line 553, in forward return self._conv_forward(input, self.weight, self.bias)  conv2d_26 @@ -1247,19 +1247,19 @@ 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/xx2/./ml_tools/openpilot_compile/compile_supercombo.py", line 82, in forward +pkg.torch.onnx.stack_traceFile "/home/batman/xx3/./ml_tools/openpilot_compile/compile_supercombo.py", line 86, in forward return torch.cat([*self.forward_dict(inputs).values(), self.pad], dim=1) - File "/home/batman/xx2/xx/training/path/supercombo.py", line 191, in forward + File "/home/batman/xx3/xx/training/path/supercombo.py", line 191, in forward return {ModelInputs.FEATURES: self._en((x - self._mean) / self._std)} - File "/home/batman/xx2/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1418, in forward + File "/home/batman/xx3/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1418, in forward x = self.forward_features(x) - File "/home/batman/xx2/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1167, in forward + File "/home/batman/xx3/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1167, in forward x = self.blocks(x) - File "/home/batman/xx2/.venv/lib/python3.12/site-packages/torch/nn/modules/container.py", line 253, in forward + File "/home/batman/xx3/.venv/lib/python3.12/site-packages/torch/nn/modules/container.py", line 253, in forward input = module(input) - File "/home/batman/xx2/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1002, in forward + File "/home/batman/xx3/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1002, in forward x = x + self.drop_path(self.layer_scale(self.mlp(x))) - File "/home/batman/xx2/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 646, in forward + File "/home/batman/xx3/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 646, in forward return x.mul_(self.gamma) if self.inplace else x * self.gamma  conv2d_23 @@ -1269,17 +1269,17 @@ 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/xx2/./ml_tools/openpilot_compile/compile_supercombo.py", line 82, in forward +pkg.torch.onnx.stack_traceFile "/home/batman/xx3/./ml_tools/openpilot_compile/compile_supercombo.py", line 86, in forward return torch.cat([*self.forward_dict(inputs).values(), self.pad], dim=1) - File "/home/batman/xx2/xx/training/path/supercombo.py", line 191, in forward + File "/home/batman/xx3/xx/training/path/supercombo.py", line 191, in forward return {ModelInputs.FEATURES: self._en((x - self._mean) / self._std)} - File "/home/batman/xx2/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1418, in forward + File "/home/batman/xx3/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1418, in forward x = self.forward_features(x) - File "/home/batman/xx2/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1167, in forward + File "/home/batman/xx3/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1167, in forward x = self.blocks(x) - File "/home/batman/xx2/.venv/lib/python3.12/site-packages/torch/nn/modules/container.py", line 253, in forward + File "/home/batman/xx3/.venv/lib/python3.12/site-packages/torch/nn/modules/container.py", line 253, in forward input = module(input) - File "/home/batman/xx2/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1002, in forward + File "/home/batman/xx3/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1002, in forward x = x + self.drop_path(self.layer_scale(self.mlp(x)))  add_4 @@ -1294,21 +1294,21 @@ 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_trace File "/home/batman/xx2/./ml_tools/openpilot_compile/compile_supercombo.py", line 82, in forward +pkg.torch.onnx.stack_trace File "/home/batman/xx3/./ml_tools/openpilot_compile/compile_supercombo.py", line 86, in forward return torch.cat([*self.forward_dict(inputs).values(), self.pad], dim=1) - File "/home/batman/xx2/xx/training/path/supercombo.py", line 191, in forward + File "/home/batman/xx3/xx/training/path/supercombo.py", line 191, in forward return {ModelInputs.FEATURES: self._en((x - self._mean) / self._std)} - File "/home/batman/xx2/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1418, in forward + File "/home/batman/xx3/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1418, in forward x = self.forward_features(x) - File "/home/batman/xx2/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1167, in forward + File "/home/batman/xx3/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1167, in forward x = self.blocks(x) - File "/home/batman/xx2/.venv/lib/python3.12/site-packages/torch/nn/modules/container.py", line 253, in forward + File "/home/batman/xx3/.venv/lib/python3.12/site-packages/torch/nn/modules/container.py", line 253, in forward input = module(input) - File "/home/batman/xx2/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1001, in forward + File "/home/batman/xx3/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1001, in forward x = self.token_mixer(x) - File "/home/batman/xx2/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 717, in forward + File "/home/batman/xx3/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 717, in forward x = self.reparam_conv(x) - File "/home/batman/xx2/.venv/lib/python3.12/site-packages/torch/nn/modules/conv.py", line 553, in forward + File "/home/batman/xx3/.venv/lib/python3.12/site-packages/torch/nn/modules/conv.py", line 553, in forward return self._conv_forward(input, self.weight, self.bias)  conv2d_27 @@ -1327,23 +1327,23 @@ getitem_15 node_Conv_293"Conv* 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/xx2/./ml_tools/openpilot_compile/compile_supercombo.py", line 82, in forward +File "/home/batman/xx3/./ml_tools/openpilot_compile/compile_supercombo.py", line 86, in forward return torch.cat([*self.forward_dict(inputs).values(), self.pad], dim=1) - File "/home/batman/xx2/xx/training/path/supercombo.py", line 191, in forward + File "/home/batman/xx3/xx/training/path/supercombo.py", line 191, in forward return {ModelInputs.FEATURES: self._en((x - self._mean) / self._std)} - File "/home/batman/xx2/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1418, in forward + File "/home/batman/xx3/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1418, in forward x = self.forward_features(x) - File "/home/batman/xx2/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1167, in forward + File "/home/batman/xx3/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1167, in forward x = self.blocks(x) - File "/home/batman/xx2/.venv/lib/python3.12/site-packages/torch/nn/modules/container.py", line 253, in forward + File "/home/batman/xx3/.venv/lib/python3.12/site-packages/torch/nn/modules/container.py", line 253, in forward input = module(input) - File "/home/batman/xx2/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1002, in forward + File "/home/batman/xx3/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1002, in forward x = x + self.drop_path(self.layer_scale(self.mlp(x))) - File "/home/batman/xx2/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 814, in forward + File "/home/batman/xx3/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 814, in forward x = self.conv(x) - File "/home/batman/xx2/.venv/lib/python3.12/site-packages/timm/layers/conv_bn_act.py", line 94, in forward + File "/home/batman/xx3/.venv/lib/python3.12/site-packages/timm/layers/conv_bn_act.py", line 94, in forward x = self.bn(x) - File "/home/batman/xx2/xx/training/path/allnorm.py", line 60, in forward + File "/home/batman/xx3/xx/training/path/allnorm.py", line 60, in forward return self.act(self.drop(self._allnorm_forward(x)))  @@ -1359,21 +1359,21 @@ 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/xx2/./ml_tools/openpilot_compile/compile_supercombo.py", line 82, in forward +pkg.torch.onnx.stack_trace File "/home/batman/xx3/./ml_tools/openpilot_compile/compile_supercombo.py", line 86, in forward return torch.cat([*self.forward_dict(inputs).values(), self.pad], dim=1) - File "/home/batman/xx2/xx/training/path/supercombo.py", line 191, in forward + File "/home/batman/xx3/xx/training/path/supercombo.py", line 191, in forward return {ModelInputs.FEATURES: self._en((x - self._mean) / self._std)} - File "/home/batman/xx2/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1418, in forward + File "/home/batman/xx3/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1418, in forward x = self.forward_features(x) - File "/home/batman/xx2/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1167, in forward + File "/home/batman/xx3/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1167, in forward x = self.blocks(x) - File "/home/batman/xx2/.venv/lib/python3.12/site-packages/torch/nn/modules/container.py", line 253, in forward + File "/home/batman/xx3/.venv/lib/python3.12/site-packages/torch/nn/modules/container.py", line 253, in forward input = module(input) - File "/home/batman/xx2/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1002, in forward + File "/home/batman/xx3/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1002, in forward x = x + self.drop_path(self.layer_scale(self.mlp(x))) - File "/home/batman/xx2/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 815, in forward + File "/home/batman/xx3/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 815, in forward x = self.fc1(x) - File "/home/batman/xx2/.venv/lib/python3.12/site-packages/torch/nn/modules/conv.py", line 553, in forward + File "/home/batman/xx3/.venv/lib/python3.12/site-packages/torch/nn/modules/conv.py", line 553, in forward return self._conv_forward(input, self.weight, self.bias)  conv2d_29gelu_10 node_gelu_10"Gelu* @@ -1382,21 +1382,21 @@ 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_trace File "/home/batman/xx2/./ml_tools/openpilot_compile/compile_supercombo.py", line 82, in forward +pkg.torch.onnx.stack_trace File "/home/batman/xx3/./ml_tools/openpilot_compile/compile_supercombo.py", line 86, in forward return torch.cat([*self.forward_dict(inputs).values(), self.pad], dim=1) - File "/home/batman/xx2/xx/training/path/supercombo.py", line 191, in forward + File "/home/batman/xx3/xx/training/path/supercombo.py", line 191, in forward return {ModelInputs.FEATURES: self._en((x - self._mean) / self._std)} - File "/home/batman/xx2/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1418, in forward + File "/home/batman/xx3/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1418, in forward x = self.forward_features(x) - File "/home/batman/xx2/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1167, in forward + File "/home/batman/xx3/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1167, in forward x = self.blocks(x) - File "/home/batman/xx2/.venv/lib/python3.12/site-packages/torch/nn/modules/container.py", line 253, in forward + File "/home/batman/xx3/.venv/lib/python3.12/site-packages/torch/nn/modules/container.py", line 253, in forward input = module(input) - File "/home/batman/xx2/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1002, in forward + File "/home/batman/xx3/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1002, in forward x = x + self.drop_path(self.layer_scale(self.mlp(x))) - File "/home/batman/xx2/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 816, in forward + File "/home/batman/xx3/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 816, in forward x = self.act(x) - File "/home/batman/xx2/.venv/lib/python3.12/site-packages/timm/layers/activations.py", line 159, in forward + File "/home/batman/xx3/.venv/lib/python3.12/site-packages/timm/layers/activations.py", line 159, in forward return F.gelu(input, approximate='tanh')  gelu_10 @@ -1411,21 +1411,21 @@ 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/xx2/./ml_tools/openpilot_compile/compile_supercombo.py", line 82, in forward +pkg.torch.onnx.stack_trace File "/home/batman/xx3/./ml_tools/openpilot_compile/compile_supercombo.py", line 86, in forward return torch.cat([*self.forward_dict(inputs).values(), self.pad], dim=1) - File "/home/batman/xx2/xx/training/path/supercombo.py", line 191, in forward + File "/home/batman/xx3/xx/training/path/supercombo.py", line 191, in forward return {ModelInputs.FEATURES: self._en((x - self._mean) / self._std)} - File "/home/batman/xx2/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1418, in forward + File "/home/batman/xx3/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1418, in forward x = self.forward_features(x) - File "/home/batman/xx2/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1167, in forward + File "/home/batman/xx3/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1167, in forward x = self.blocks(x) - File "/home/batman/xx2/.venv/lib/python3.12/site-packages/torch/nn/modules/container.py", line 253, in forward + File "/home/batman/xx3/.venv/lib/python3.12/site-packages/torch/nn/modules/container.py", line 253, in forward input = module(input) - File "/home/batman/xx2/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1002, in forward + File "/home/batman/xx3/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1002, in forward x = x + self.drop_path(self.layer_scale(self.mlp(x))) - File "/home/batman/xx2/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 818, in forward + File "/home/batman/xx3/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 818, in forward x = self.fc2(x) - File "/home/batman/xx2/.venv/lib/python3.12/site-packages/torch/nn/modules/conv.py", line 553, in forward + File "/home/batman/xx3/.venv/lib/python3.12/site-packages/torch/nn/modules/conv.py", line 553, in forward return self._conv_forward(input, self.weight, self.bias)  conv2d_30 @@ -1435,19 +1435,19 @@ 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/xx2/./ml_tools/openpilot_compile/compile_supercombo.py", line 82, in forward +pkg.torch.onnx.stack_traceFile "/home/batman/xx3/./ml_tools/openpilot_compile/compile_supercombo.py", line 86, in forward return torch.cat([*self.forward_dict(inputs).values(), self.pad], dim=1) - File "/home/batman/xx2/xx/training/path/supercombo.py", line 191, in forward + File "/home/batman/xx3/xx/training/path/supercombo.py", line 191, in forward return {ModelInputs.FEATURES: self._en((x - self._mean) / self._std)} - File "/home/batman/xx2/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1418, in forward + File "/home/batman/xx3/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1418, in forward x = self.forward_features(x) - File "/home/batman/xx2/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1167, in forward + File "/home/batman/xx3/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1167, in forward x = self.blocks(x) - File "/home/batman/xx2/.venv/lib/python3.12/site-packages/torch/nn/modules/container.py", line 253, in forward + File "/home/batman/xx3/.venv/lib/python3.12/site-packages/torch/nn/modules/container.py", line 253, in forward input = module(input) - File "/home/batman/xx2/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1002, in forward + File "/home/batman/xx3/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1002, in forward x = x + self.drop_path(self.layer_scale(self.mlp(x))) - File "/home/batman/xx2/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 646, in forward + File "/home/batman/xx3/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 646, in forward return x.mul_(self.gamma) if self.inplace else x * self.gamma  conv2d_27 @@ -1457,17 +1457,17 @@ 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/xx2/./ml_tools/openpilot_compile/compile_supercombo.py", line 82, in forward +pkg.torch.onnx.stack_traceFile "/home/batman/xx3/./ml_tools/openpilot_compile/compile_supercombo.py", line 86, in forward return torch.cat([*self.forward_dict(inputs).values(), self.pad], dim=1) - File "/home/batman/xx2/xx/training/path/supercombo.py", line 191, in forward + File "/home/batman/xx3/xx/training/path/supercombo.py", line 191, in forward return {ModelInputs.FEATURES: self._en((x - self._mean) / self._std)} - File "/home/batman/xx2/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1418, in forward + File "/home/batman/xx3/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1418, in forward x = self.forward_features(x) - File "/home/batman/xx2/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1167, in forward + File "/home/batman/xx3/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1167, in forward x = self.blocks(x) - File "/home/batman/xx2/.venv/lib/python3.12/site-packages/torch/nn/modules/container.py", line 253, in forward + File "/home/batman/xx3/.venv/lib/python3.12/site-packages/torch/nn/modules/container.py", line 253, in forward input = module(input) - File "/home/batman/xx2/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1002, in forward + File "/home/batman/xx3/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1002, in forward x = x + self.drop_path(self.layer_scale(self.mlp(x)))  add_5 @@ -1482,21 +1482,21 @@ 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_trace File "/home/batman/xx2/./ml_tools/openpilot_compile/compile_supercombo.py", line 82, in forward +pkg.torch.onnx.stack_trace File "/home/batman/xx3/./ml_tools/openpilot_compile/compile_supercombo.py", line 86, in forward return torch.cat([*self.forward_dict(inputs).values(), self.pad], dim=1) - File "/home/batman/xx2/xx/training/path/supercombo.py", line 191, in forward + File "/home/batman/xx3/xx/training/path/supercombo.py", line 191, in forward return {ModelInputs.FEATURES: self._en((x - self._mean) / self._std)} - File "/home/batman/xx2/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1418, in forward + File "/home/batman/xx3/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1418, in forward x = self.forward_features(x) - File "/home/batman/xx2/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1167, in forward + File "/home/batman/xx3/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1167, in forward x = self.blocks(x) - File "/home/batman/xx2/.venv/lib/python3.12/site-packages/torch/nn/modules/container.py", line 253, in forward + File "/home/batman/xx3/.venv/lib/python3.12/site-packages/torch/nn/modules/container.py", line 253, in forward input = module(input) - File "/home/batman/xx2/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1001, in forward + File "/home/batman/xx3/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1001, in forward x = self.token_mixer(x) - File "/home/batman/xx2/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 717, in forward + File "/home/batman/xx3/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 717, in forward x = self.reparam_conv(x) - File "/home/batman/xx2/.venv/lib/python3.12/site-packages/torch/nn/modules/conv.py", line 553, in forward + File "/home/batman/xx3/.venv/lib/python3.12/site-packages/torch/nn/modules/conv.py", line 553, in forward return self._conv_forward(input, self.weight, self.bias)  conv2d_31 @@ -1515,23 +1515,23 @@ getitem_18 node_Conv_295"Conv* 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/xx2/./ml_tools/openpilot_compile/compile_supercombo.py", line 82, in forward +File "/home/batman/xx3/./ml_tools/openpilot_compile/compile_supercombo.py", line 86, in forward return torch.cat([*self.forward_dict(inputs).values(), self.pad], dim=1) - File "/home/batman/xx2/xx/training/path/supercombo.py", line 191, in forward + File "/home/batman/xx3/xx/training/path/supercombo.py", line 191, in forward return {ModelInputs.FEATURES: self._en((x - self._mean) / self._std)} - File "/home/batman/xx2/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1418, in forward + File "/home/batman/xx3/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1418, in forward x = self.forward_features(x) - File "/home/batman/xx2/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1167, in forward + File "/home/batman/xx3/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1167, in forward x = self.blocks(x) - File "/home/batman/xx2/.venv/lib/python3.12/site-packages/torch/nn/modules/container.py", line 253, in forward + File "/home/batman/xx3/.venv/lib/python3.12/site-packages/torch/nn/modules/container.py", line 253, in forward input = module(input) - File "/home/batman/xx2/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1002, in forward + File "/home/batman/xx3/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1002, in forward x = x + self.drop_path(self.layer_scale(self.mlp(x))) - File "/home/batman/xx2/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 814, in forward + File "/home/batman/xx3/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 814, in forward x = self.conv(x) - File "/home/batman/xx2/.venv/lib/python3.12/site-packages/timm/layers/conv_bn_act.py", line 94, in forward + File "/home/batman/xx3/.venv/lib/python3.12/site-packages/timm/layers/conv_bn_act.py", line 94, in forward x = self.bn(x) - File "/home/batman/xx2/xx/training/path/allnorm.py", line 60, in forward + File "/home/batman/xx3/xx/training/path/allnorm.py", line 60, in forward return self.act(self.drop(self._allnorm_forward(x)))  @@ -1547,21 +1547,21 @@ 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/xx2/./ml_tools/openpilot_compile/compile_supercombo.py", line 82, in forward +pkg.torch.onnx.stack_trace File "/home/batman/xx3/./ml_tools/openpilot_compile/compile_supercombo.py", line 86, in forward return torch.cat([*self.forward_dict(inputs).values(), self.pad], dim=1) - File "/home/batman/xx2/xx/training/path/supercombo.py", line 191, in forward + File "/home/batman/xx3/xx/training/path/supercombo.py", line 191, in forward return {ModelInputs.FEATURES: self._en((x - self._mean) / self._std)} - File "/home/batman/xx2/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1418, in forward + File "/home/batman/xx3/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1418, in forward x = self.forward_features(x) - File "/home/batman/xx2/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1167, in forward + File "/home/batman/xx3/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1167, in forward x = self.blocks(x) - File "/home/batman/xx2/.venv/lib/python3.12/site-packages/torch/nn/modules/container.py", line 253, in forward + File "/home/batman/xx3/.venv/lib/python3.12/site-packages/torch/nn/modules/container.py", line 253, in forward input = module(input) - File "/home/batman/xx2/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1002, in forward + File "/home/batman/xx3/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1002, in forward x = x + self.drop_path(self.layer_scale(self.mlp(x))) - File "/home/batman/xx2/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 815, in forward + File "/home/batman/xx3/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 815, in forward x = self.fc1(x) - File "/home/batman/xx2/.venv/lib/python3.12/site-packages/torch/nn/modules/conv.py", line 553, in forward + File "/home/batman/xx3/.venv/lib/python3.12/site-packages/torch/nn/modules/conv.py", line 553, in forward return self._conv_forward(input, self.weight, self.bias)  conv2d_33gelu_11 node_gelu_11"Gelu* @@ -1570,21 +1570,21 @@ 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_trace File "/home/batman/xx2/./ml_tools/openpilot_compile/compile_supercombo.py", line 82, in forward +pkg.torch.onnx.stack_trace File "/home/batman/xx3/./ml_tools/openpilot_compile/compile_supercombo.py", line 86, in forward return torch.cat([*self.forward_dict(inputs).values(), self.pad], dim=1) - File "/home/batman/xx2/xx/training/path/supercombo.py", line 191, in forward + File "/home/batman/xx3/xx/training/path/supercombo.py", line 191, in forward return {ModelInputs.FEATURES: self._en((x - self._mean) / self._std)} - File "/home/batman/xx2/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1418, in forward + File "/home/batman/xx3/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1418, in forward x = self.forward_features(x) - File "/home/batman/xx2/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1167, in forward + File "/home/batman/xx3/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1167, in forward x = self.blocks(x) - File "/home/batman/xx2/.venv/lib/python3.12/site-packages/torch/nn/modules/container.py", line 253, in forward + File "/home/batman/xx3/.venv/lib/python3.12/site-packages/torch/nn/modules/container.py", line 253, in forward input = module(input) - File "/home/batman/xx2/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1002, in forward + File "/home/batman/xx3/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1002, in forward x = x + self.drop_path(self.layer_scale(self.mlp(x))) - File "/home/batman/xx2/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 816, in forward + File "/home/batman/xx3/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 816, in forward x = self.act(x) - File "/home/batman/xx2/.venv/lib/python3.12/site-packages/timm/layers/activations.py", line 159, in forward + File "/home/batman/xx3/.venv/lib/python3.12/site-packages/timm/layers/activations.py", line 159, in forward return F.gelu(input, approximate='tanh')  gelu_11 @@ -1599,21 +1599,21 @@ 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/xx2/./ml_tools/openpilot_compile/compile_supercombo.py", line 82, in forward +pkg.torch.onnx.stack_trace File "/home/batman/xx3/./ml_tools/openpilot_compile/compile_supercombo.py", line 86, in forward return torch.cat([*self.forward_dict(inputs).values(), self.pad], dim=1) - File "/home/batman/xx2/xx/training/path/supercombo.py", line 191, in forward + File "/home/batman/xx3/xx/training/path/supercombo.py", line 191, in forward return {ModelInputs.FEATURES: self._en((x - self._mean) / self._std)} - File "/home/batman/xx2/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1418, in forward + File "/home/batman/xx3/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1418, in forward x = self.forward_features(x) - File "/home/batman/xx2/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1167, in forward + File "/home/batman/xx3/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1167, in forward x = self.blocks(x) - File "/home/batman/xx2/.venv/lib/python3.12/site-packages/torch/nn/modules/container.py", line 253, in forward + File "/home/batman/xx3/.venv/lib/python3.12/site-packages/torch/nn/modules/container.py", line 253, in forward input = module(input) - File "/home/batman/xx2/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1002, in forward + File "/home/batman/xx3/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1002, in forward x = x + self.drop_path(self.layer_scale(self.mlp(x))) - File "/home/batman/xx2/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 818, in forward + File "/home/batman/xx3/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 818, in forward x = self.fc2(x) - File "/home/batman/xx2/.venv/lib/python3.12/site-packages/torch/nn/modules/conv.py", line 553, in forward + File "/home/batman/xx3/.venv/lib/python3.12/site-packages/torch/nn/modules/conv.py", line 553, in forward return self._conv_forward(input, self.weight, self.bias)  conv2d_34 @@ -1623,19 +1623,19 @@ 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/xx2/./ml_tools/openpilot_compile/compile_supercombo.py", line 82, in forward +pkg.torch.onnx.stack_traceFile "/home/batman/xx3/./ml_tools/openpilot_compile/compile_supercombo.py", line 86, in forward return torch.cat([*self.forward_dict(inputs).values(), self.pad], dim=1) - File "/home/batman/xx2/xx/training/path/supercombo.py", line 191, in forward + File "/home/batman/xx3/xx/training/path/supercombo.py", line 191, in forward return {ModelInputs.FEATURES: self._en((x - self._mean) / self._std)} - File "/home/batman/xx2/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1418, in forward + File "/home/batman/xx3/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1418, in forward x = self.forward_features(x) - File "/home/batman/xx2/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1167, in forward + File "/home/batman/xx3/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1167, in forward x = self.blocks(x) - File "/home/batman/xx2/.venv/lib/python3.12/site-packages/torch/nn/modules/container.py", line 253, in forward + File "/home/batman/xx3/.venv/lib/python3.12/site-packages/torch/nn/modules/container.py", line 253, in forward input = module(input) - File "/home/batman/xx2/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1002, in forward + File "/home/batman/xx3/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1002, in forward x = x + self.drop_path(self.layer_scale(self.mlp(x))) - File "/home/batman/xx2/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 646, in forward + File "/home/batman/xx3/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 646, in forward return x.mul_(self.gamma) if self.inplace else x * self.gamma  conv2d_31 @@ -1645,17 +1645,17 @@ 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/xx2/./ml_tools/openpilot_compile/compile_supercombo.py", line 82, in forward +pkg.torch.onnx.stack_traceFile "/home/batman/xx3/./ml_tools/openpilot_compile/compile_supercombo.py", line 86, in forward return torch.cat([*self.forward_dict(inputs).values(), self.pad], dim=1) - File "/home/batman/xx2/xx/training/path/supercombo.py", line 191, in forward + File "/home/batman/xx3/xx/training/path/supercombo.py", line 191, in forward return {ModelInputs.FEATURES: self._en((x - self._mean) / self._std)} - File "/home/batman/xx2/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1418, in forward + File "/home/batman/xx3/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1418, in forward x = self.forward_features(x) - File "/home/batman/xx2/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1167, in forward + File "/home/batman/xx3/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1167, in forward x = self.blocks(x) - File "/home/batman/xx2/.venv/lib/python3.12/site-packages/torch/nn/modules/container.py", line 253, in forward + File "/home/batman/xx3/.venv/lib/python3.12/site-packages/torch/nn/modules/container.py", line 253, in forward input = module(input) - File "/home/batman/xx2/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1002, in forward + File "/home/batman/xx3/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1002, in forward x = x + self.drop_path(self.layer_scale(self.mlp(x)))  add_6 @@ -1670,21 +1670,21 @@ 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_trace File "/home/batman/xx2/./ml_tools/openpilot_compile/compile_supercombo.py", line 82, in forward +pkg.torch.onnx.stack_trace File "/home/batman/xx3/./ml_tools/openpilot_compile/compile_supercombo.py", line 86, in forward return torch.cat([*self.forward_dict(inputs).values(), self.pad], dim=1) - File "/home/batman/xx2/xx/training/path/supercombo.py", line 191, in forward + File "/home/batman/xx3/xx/training/path/supercombo.py", line 191, in forward return {ModelInputs.FEATURES: self._en((x - self._mean) / self._std)} - File "/home/batman/xx2/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1418, in forward + File "/home/batman/xx3/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1418, in forward x = self.forward_features(x) - File "/home/batman/xx2/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1167, in forward + File "/home/batman/xx3/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1167, in forward x = self.blocks(x) - File "/home/batman/xx2/.venv/lib/python3.12/site-packages/torch/nn/modules/container.py", line 253, in forward + File "/home/batman/xx3/.venv/lib/python3.12/site-packages/torch/nn/modules/container.py", line 253, in forward input = module(input) - File "/home/batman/xx2/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1001, in forward + File "/home/batman/xx3/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1001, in forward x = self.token_mixer(x) - File "/home/batman/xx2/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 717, in forward + File "/home/batman/xx3/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 717, in forward x = self.reparam_conv(x) - File "/home/batman/xx2/.venv/lib/python3.12/site-packages/torch/nn/modules/conv.py", line 553, in forward + File "/home/batman/xx3/.venv/lib/python3.12/site-packages/torch/nn/modules/conv.py", line 553, in forward return self._conv_forward(input, self.weight, self.bias)  conv2d_35 @@ -1703,23 +1703,23 @@ getitem_21 node_Conv_297"Conv* 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/xx2/./ml_tools/openpilot_compile/compile_supercombo.py", line 82, in forward +File "/home/batman/xx3/./ml_tools/openpilot_compile/compile_supercombo.py", line 86, in forward return torch.cat([*self.forward_dict(inputs).values(), self.pad], dim=1) - File "/home/batman/xx2/xx/training/path/supercombo.py", line 191, in forward + File "/home/batman/xx3/xx/training/path/supercombo.py", line 191, in forward return {ModelInputs.FEATURES: self._en((x - self._mean) / self._std)} - File "/home/batman/xx2/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1418, in forward + File "/home/batman/xx3/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1418, in forward x = self.forward_features(x) - File "/home/batman/xx2/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1167, in forward + File "/home/batman/xx3/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1167, in forward x = self.blocks(x) - File "/home/batman/xx2/.venv/lib/python3.12/site-packages/torch/nn/modules/container.py", line 253, in forward + File "/home/batman/xx3/.venv/lib/python3.12/site-packages/torch/nn/modules/container.py", line 253, in forward input = module(input) - File "/home/batman/xx2/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1002, in forward + File "/home/batman/xx3/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1002, in forward x = x + self.drop_path(self.layer_scale(self.mlp(x))) - File "/home/batman/xx2/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 814, in forward + File "/home/batman/xx3/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 814, in forward x = self.conv(x) - File "/home/batman/xx2/.venv/lib/python3.12/site-packages/timm/layers/conv_bn_act.py", line 94, in forward + File "/home/batman/xx3/.venv/lib/python3.12/site-packages/timm/layers/conv_bn_act.py", line 94, in forward x = self.bn(x) - File "/home/batman/xx2/xx/training/path/allnorm.py", line 60, in forward + File "/home/batman/xx3/xx/training/path/allnorm.py", line 60, in forward return self.act(self.drop(self._allnorm_forward(x)))  @@ -1735,21 +1735,21 @@ 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/xx2/./ml_tools/openpilot_compile/compile_supercombo.py", line 82, in forward +pkg.torch.onnx.stack_trace File "/home/batman/xx3/./ml_tools/openpilot_compile/compile_supercombo.py", line 86, in forward return torch.cat([*self.forward_dict(inputs).values(), self.pad], dim=1) - File "/home/batman/xx2/xx/training/path/supercombo.py", line 191, in forward + File "/home/batman/xx3/xx/training/path/supercombo.py", line 191, in forward return {ModelInputs.FEATURES: self._en((x - self._mean) / self._std)} - File "/home/batman/xx2/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1418, in forward + File "/home/batman/xx3/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1418, in forward x = self.forward_features(x) - File "/home/batman/xx2/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1167, in forward + File "/home/batman/xx3/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1167, in forward x = self.blocks(x) - File "/home/batman/xx2/.venv/lib/python3.12/site-packages/torch/nn/modules/container.py", line 253, in forward + File "/home/batman/xx3/.venv/lib/python3.12/site-packages/torch/nn/modules/container.py", line 253, in forward input = module(input) - File "/home/batman/xx2/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1002, in forward + File "/home/batman/xx3/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1002, in forward x = x + self.drop_path(self.layer_scale(self.mlp(x))) - File "/home/batman/xx2/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 815, in forward + File "/home/batman/xx3/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 815, in forward x = self.fc1(x) - File "/home/batman/xx2/.venv/lib/python3.12/site-packages/torch/nn/modules/conv.py", line 553, in forward + File "/home/batman/xx3/.venv/lib/python3.12/site-packages/torch/nn/modules/conv.py", line 553, in forward return self._conv_forward(input, self.weight, self.bias)  conv2d_37gelu_12 node_gelu_12"Gelu* @@ -1758,21 +1758,21 @@ 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_trace File "/home/batman/xx2/./ml_tools/openpilot_compile/compile_supercombo.py", line 82, in forward +pkg.torch.onnx.stack_trace File "/home/batman/xx3/./ml_tools/openpilot_compile/compile_supercombo.py", line 86, in forward return torch.cat([*self.forward_dict(inputs).values(), self.pad], dim=1) - File "/home/batman/xx2/xx/training/path/supercombo.py", line 191, in forward + File "/home/batman/xx3/xx/training/path/supercombo.py", line 191, in forward return {ModelInputs.FEATURES: self._en((x - self._mean) / self._std)} - File "/home/batman/xx2/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1418, in forward + File "/home/batman/xx3/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1418, in forward x = self.forward_features(x) - File "/home/batman/xx2/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1167, in forward + File "/home/batman/xx3/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1167, in forward x = self.blocks(x) - File "/home/batman/xx2/.venv/lib/python3.12/site-packages/torch/nn/modules/container.py", line 253, in forward + File "/home/batman/xx3/.venv/lib/python3.12/site-packages/torch/nn/modules/container.py", line 253, in forward input = module(input) - File "/home/batman/xx2/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1002, in forward + File "/home/batman/xx3/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1002, in forward x = x + self.drop_path(self.layer_scale(self.mlp(x))) - File "/home/batman/xx2/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 816, in forward + File "/home/batman/xx3/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 816, in forward x = self.act(x) - File "/home/batman/xx2/.venv/lib/python3.12/site-packages/timm/layers/activations.py", line 159, in forward + File "/home/batman/xx3/.venv/lib/python3.12/site-packages/timm/layers/activations.py", line 159, in forward return F.gelu(input, approximate='tanh')  gelu_12 @@ -1787,21 +1787,21 @@ 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/xx2/./ml_tools/openpilot_compile/compile_supercombo.py", line 82, in forward +pkg.torch.onnx.stack_trace File "/home/batman/xx3/./ml_tools/openpilot_compile/compile_supercombo.py", line 86, in forward return torch.cat([*self.forward_dict(inputs).values(), self.pad], dim=1) - File "/home/batman/xx2/xx/training/path/supercombo.py", line 191, in forward + File "/home/batman/xx3/xx/training/path/supercombo.py", line 191, in forward return {ModelInputs.FEATURES: self._en((x - self._mean) / self._std)} - File "/home/batman/xx2/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1418, in forward + File "/home/batman/xx3/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1418, in forward x = self.forward_features(x) - File "/home/batman/xx2/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1167, in forward + File "/home/batman/xx3/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1167, in forward x = self.blocks(x) - File "/home/batman/xx2/.venv/lib/python3.12/site-packages/torch/nn/modules/container.py", line 253, in forward + File "/home/batman/xx3/.venv/lib/python3.12/site-packages/torch/nn/modules/container.py", line 253, in forward input = module(input) - File "/home/batman/xx2/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1002, in forward + File "/home/batman/xx3/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1002, in forward x = x + self.drop_path(self.layer_scale(self.mlp(x))) - File "/home/batman/xx2/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 818, in forward + File "/home/batman/xx3/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 818, in forward x = self.fc2(x) - File "/home/batman/xx2/.venv/lib/python3.12/site-packages/torch/nn/modules/conv.py", line 553, in forward + File "/home/batman/xx3/.venv/lib/python3.12/site-packages/torch/nn/modules/conv.py", line 553, in forward return self._conv_forward(input, self.weight, self.bias)  conv2d_38 @@ -1811,19 +1811,19 @@ 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/xx2/./ml_tools/openpilot_compile/compile_supercombo.py", line 82, in forward +pkg.torch.onnx.stack_traceFile "/home/batman/xx3/./ml_tools/openpilot_compile/compile_supercombo.py", line 86, in forward return torch.cat([*self.forward_dict(inputs).values(), self.pad], dim=1) - File "/home/batman/xx2/xx/training/path/supercombo.py", line 191, in forward + File "/home/batman/xx3/xx/training/path/supercombo.py", line 191, in forward return {ModelInputs.FEATURES: self._en((x - self._mean) / self._std)} - File "/home/batman/xx2/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1418, in forward + File "/home/batman/xx3/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1418, in forward x = self.forward_features(x) - File "/home/batman/xx2/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1167, in forward + File "/home/batman/xx3/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1167, in forward x = self.blocks(x) - File "/home/batman/xx2/.venv/lib/python3.12/site-packages/torch/nn/modules/container.py", line 253, in forward + File "/home/batman/xx3/.venv/lib/python3.12/site-packages/torch/nn/modules/container.py", line 253, in forward input = module(input) - File "/home/batman/xx2/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1002, in forward + File "/home/batman/xx3/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1002, in forward x = x + self.drop_path(self.layer_scale(self.mlp(x))) - File "/home/batman/xx2/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 646, in forward + File "/home/batman/xx3/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 646, in forward return x.mul_(self.gamma) if self.inplace else x * self.gamma  conv2d_35 @@ -1833,17 +1833,17 @@ 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/xx2/./ml_tools/openpilot_compile/compile_supercombo.py", line 82, in forward +pkg.torch.onnx.stack_traceFile "/home/batman/xx3/./ml_tools/openpilot_compile/compile_supercombo.py", line 86, in forward return torch.cat([*self.forward_dict(inputs).values(), self.pad], dim=1) - File "/home/batman/xx2/xx/training/path/supercombo.py", line 191, in forward + File "/home/batman/xx3/xx/training/path/supercombo.py", line 191, in forward return {ModelInputs.FEATURES: self._en((x - self._mean) / self._std)} - File "/home/batman/xx2/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1418, in forward + File "/home/batman/xx3/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1418, in forward x = self.forward_features(x) - File "/home/batman/xx2/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1167, in forward + File "/home/batman/xx3/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1167, in forward x = self.blocks(x) - File "/home/batman/xx2/.venv/lib/python3.12/site-packages/torch/nn/modules/container.py", line 253, in forward + File "/home/batman/xx3/.venv/lib/python3.12/site-packages/torch/nn/modules/container.py", line 253, in forward input = module(input) - File "/home/batman/xx2/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1002, in forward + File "/home/batman/xx3/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1002, in forward x = x + self.drop_path(self.layer_scale(self.mlp(x)))  add_7 @@ -1858,21 +1858,21 @@ 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_trace File "/home/batman/xx2/./ml_tools/openpilot_compile/compile_supercombo.py", line 82, in forward +pkg.torch.onnx.stack_trace File "/home/batman/xx3/./ml_tools/openpilot_compile/compile_supercombo.py", line 86, in forward return torch.cat([*self.forward_dict(inputs).values(), self.pad], dim=1) - File "/home/batman/xx2/xx/training/path/supercombo.py", line 191, in forward + File "/home/batman/xx3/xx/training/path/supercombo.py", line 191, in forward return {ModelInputs.FEATURES: self._en((x - self._mean) / self._std)} - File "/home/batman/xx2/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1418, in forward + File "/home/batman/xx3/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1418, in forward x = self.forward_features(x) - File "/home/batman/xx2/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1167, in forward + File "/home/batman/xx3/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1167, in forward x = self.blocks(x) - File "/home/batman/xx2/.venv/lib/python3.12/site-packages/torch/nn/modules/container.py", line 253, in forward + File "/home/batman/xx3/.venv/lib/python3.12/site-packages/torch/nn/modules/container.py", line 253, in forward input = module(input) - File "/home/batman/xx2/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1001, in forward + File "/home/batman/xx3/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1001, in forward x = self.token_mixer(x) - File "/home/batman/xx2/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 717, in forward + File "/home/batman/xx3/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 717, in forward x = self.reparam_conv(x) - File "/home/batman/xx2/.venv/lib/python3.12/site-packages/torch/nn/modules/conv.py", line 553, in forward + File "/home/batman/xx3/.venv/lib/python3.12/site-packages/torch/nn/modules/conv.py", line 553, in forward return self._conv_forward(input, self.weight, self.bias)  conv2d_39 @@ -1891,23 +1891,23 @@ getitem_24 node_Conv_299"Conv* 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/xx2/./ml_tools/openpilot_compile/compile_supercombo.py", line 82, in forward +File "/home/batman/xx3/./ml_tools/openpilot_compile/compile_supercombo.py", line 86, in forward return torch.cat([*self.forward_dict(inputs).values(), self.pad], dim=1) - File "/home/batman/xx2/xx/training/path/supercombo.py", line 191, in forward + File "/home/batman/xx3/xx/training/path/supercombo.py", line 191, in forward return {ModelInputs.FEATURES: self._en((x - self._mean) / self._std)} - File "/home/batman/xx2/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1418, in forward + File "/home/batman/xx3/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1418, in forward x = self.forward_features(x) - File "/home/batman/xx2/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1167, in forward + File "/home/batman/xx3/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1167, in forward x = self.blocks(x) - File "/home/batman/xx2/.venv/lib/python3.12/site-packages/torch/nn/modules/container.py", line 253, in forward + File "/home/batman/xx3/.venv/lib/python3.12/site-packages/torch/nn/modules/container.py", line 253, in forward input = module(input) - File "/home/batman/xx2/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1002, in forward + File "/home/batman/xx3/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1002, in forward x = x + self.drop_path(self.layer_scale(self.mlp(x))) - File "/home/batman/xx2/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 814, in forward + File "/home/batman/xx3/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 814, in forward x = self.conv(x) - File "/home/batman/xx2/.venv/lib/python3.12/site-packages/timm/layers/conv_bn_act.py", line 94, in forward + File "/home/batman/xx3/.venv/lib/python3.12/site-packages/timm/layers/conv_bn_act.py", line 94, in forward x = self.bn(x) - File "/home/batman/xx2/xx/training/path/allnorm.py", line 60, in forward + File "/home/batman/xx3/xx/training/path/allnorm.py", line 60, in forward return self.act(self.drop(self._allnorm_forward(x)))  @@ -1923,21 +1923,21 @@ 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/xx2/./ml_tools/openpilot_compile/compile_supercombo.py", line 82, in forward +pkg.torch.onnx.stack_trace File "/home/batman/xx3/./ml_tools/openpilot_compile/compile_supercombo.py", line 86, in forward return torch.cat([*self.forward_dict(inputs).values(), self.pad], dim=1) - File "/home/batman/xx2/xx/training/path/supercombo.py", line 191, in forward + File "/home/batman/xx3/xx/training/path/supercombo.py", line 191, in forward return {ModelInputs.FEATURES: self._en((x - self._mean) / self._std)} - File "/home/batman/xx2/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1418, in forward + File "/home/batman/xx3/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1418, in forward x = self.forward_features(x) - File "/home/batman/xx2/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1167, in forward + File "/home/batman/xx3/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1167, in forward x = self.blocks(x) - File "/home/batman/xx2/.venv/lib/python3.12/site-packages/torch/nn/modules/container.py", line 253, in forward + File "/home/batman/xx3/.venv/lib/python3.12/site-packages/torch/nn/modules/container.py", line 253, in forward input = module(input) - File "/home/batman/xx2/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1002, in forward + File "/home/batman/xx3/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1002, in forward x = x + self.drop_path(self.layer_scale(self.mlp(x))) - File "/home/batman/xx2/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 815, in forward + File "/home/batman/xx3/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 815, in forward x = self.fc1(x) - File "/home/batman/xx2/.venv/lib/python3.12/site-packages/torch/nn/modules/conv.py", line 553, in forward + File "/home/batman/xx3/.venv/lib/python3.12/site-packages/torch/nn/modules/conv.py", line 553, in forward return self._conv_forward(input, self.weight, self.bias)  conv2d_41gelu_13 node_gelu_13"Gelu* @@ -1946,21 +1946,21 @@ 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_trace File "/home/batman/xx2/./ml_tools/openpilot_compile/compile_supercombo.py", line 82, in forward +pkg.torch.onnx.stack_trace File "/home/batman/xx3/./ml_tools/openpilot_compile/compile_supercombo.py", line 86, in forward return torch.cat([*self.forward_dict(inputs).values(), self.pad], dim=1) - File "/home/batman/xx2/xx/training/path/supercombo.py", line 191, in forward + File "/home/batman/xx3/xx/training/path/supercombo.py", line 191, in forward return {ModelInputs.FEATURES: self._en((x - self._mean) / self._std)} - File "/home/batman/xx2/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1418, in forward + File "/home/batman/xx3/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1418, in forward x = self.forward_features(x) - File "/home/batman/xx2/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1167, in forward + File "/home/batman/xx3/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1167, in forward x = self.blocks(x) - File "/home/batman/xx2/.venv/lib/python3.12/site-packages/torch/nn/modules/container.py", line 253, in forward + File "/home/batman/xx3/.venv/lib/python3.12/site-packages/torch/nn/modules/container.py", line 253, in forward input = module(input) - File "/home/batman/xx2/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1002, in forward + File "/home/batman/xx3/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1002, in forward x = x + self.drop_path(self.layer_scale(self.mlp(x))) - File "/home/batman/xx2/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 816, in forward + File "/home/batman/xx3/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 816, in forward x = self.act(x) - File "/home/batman/xx2/.venv/lib/python3.12/site-packages/timm/layers/activations.py", line 159, in forward + File "/home/batman/xx3/.venv/lib/python3.12/site-packages/timm/layers/activations.py", line 159, in forward return F.gelu(input, approximate='tanh')  gelu_13 @@ -1975,21 +1975,21 @@ 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/xx2/./ml_tools/openpilot_compile/compile_supercombo.py", line 82, in forward +pkg.torch.onnx.stack_trace File "/home/batman/xx3/./ml_tools/openpilot_compile/compile_supercombo.py", line 86, in forward return torch.cat([*self.forward_dict(inputs).values(), self.pad], dim=1) - File "/home/batman/xx2/xx/training/path/supercombo.py", line 191, in forward + File "/home/batman/xx3/xx/training/path/supercombo.py", line 191, in forward return {ModelInputs.FEATURES: self._en((x - self._mean) / self._std)} - File "/home/batman/xx2/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1418, in forward + File "/home/batman/xx3/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1418, in forward x = self.forward_features(x) - File "/home/batman/xx2/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1167, in forward + File "/home/batman/xx3/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1167, in forward x = self.blocks(x) - File "/home/batman/xx2/.venv/lib/python3.12/site-packages/torch/nn/modules/container.py", line 253, in forward + File "/home/batman/xx3/.venv/lib/python3.12/site-packages/torch/nn/modules/container.py", line 253, in forward input = module(input) - File "/home/batman/xx2/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1002, in forward + File "/home/batman/xx3/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1002, in forward x = x + self.drop_path(self.layer_scale(self.mlp(x))) - File "/home/batman/xx2/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 818, in forward + File "/home/batman/xx3/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 818, in forward x = self.fc2(x) - File "/home/batman/xx2/.venv/lib/python3.12/site-packages/torch/nn/modules/conv.py", line 553, in forward + File "/home/batman/xx3/.venv/lib/python3.12/site-packages/torch/nn/modules/conv.py", line 553, in forward return self._conv_forward(input, self.weight, self.bias)  conv2d_42 @@ -1999,19 +1999,19 @@ 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/xx2/./ml_tools/openpilot_compile/compile_supercombo.py", line 82, in forward +pkg.torch.onnx.stack_traceFile "/home/batman/xx3/./ml_tools/openpilot_compile/compile_supercombo.py", line 86, in forward return torch.cat([*self.forward_dict(inputs).values(), self.pad], dim=1) - File "/home/batman/xx2/xx/training/path/supercombo.py", line 191, in forward + File "/home/batman/xx3/xx/training/path/supercombo.py", line 191, in forward return {ModelInputs.FEATURES: self._en((x - self._mean) / self._std)} - File "/home/batman/xx2/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1418, in forward + File "/home/batman/xx3/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1418, in forward x = self.forward_features(x) - File "/home/batman/xx2/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1167, in forward + File "/home/batman/xx3/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1167, in forward x = self.blocks(x) - File "/home/batman/xx2/.venv/lib/python3.12/site-packages/torch/nn/modules/container.py", line 253, in forward + File "/home/batman/xx3/.venv/lib/python3.12/site-packages/torch/nn/modules/container.py", line 253, in forward input = module(input) - File "/home/batman/xx2/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1002, in forward + File "/home/batman/xx3/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1002, in forward x = x + self.drop_path(self.layer_scale(self.mlp(x))) - File "/home/batman/xx2/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 646, in forward + File "/home/batman/xx3/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 646, in forward return x.mul_(self.gamma) if self.inplace else x * self.gamma  conv2d_39 @@ -2021,17 +2021,17 @@ 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/xx2/./ml_tools/openpilot_compile/compile_supercombo.py", line 82, in forward +pkg.torch.onnx.stack_traceFile "/home/batman/xx3/./ml_tools/openpilot_compile/compile_supercombo.py", line 86, in forward return torch.cat([*self.forward_dict(inputs).values(), self.pad], dim=1) - File "/home/batman/xx2/xx/training/path/supercombo.py", line 191, in forward + File "/home/batman/xx3/xx/training/path/supercombo.py", line 191, in forward return {ModelInputs.FEATURES: self._en((x - self._mean) / self._std)} - File "/home/batman/xx2/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1418, in forward + File "/home/batman/xx3/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1418, in forward x = self.forward_features(x) - File "/home/batman/xx2/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1167, in forward + File "/home/batman/xx3/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1167, in forward x = self.blocks(x) - File "/home/batman/xx2/.venv/lib/python3.12/site-packages/torch/nn/modules/container.py", line 253, in forward + File "/home/batman/xx3/.venv/lib/python3.12/site-packages/torch/nn/modules/container.py", line 253, in forward input = module(input) - File "/home/batman/xx2/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1002, in forward + File "/home/batman/xx3/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1002, in forward x = x + self.drop_path(self.layer_scale(self.mlp(x)))  add_8 @@ -2046,21 +2046,21 @@ 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_trace File "/home/batman/xx2/./ml_tools/openpilot_compile/compile_supercombo.py", line 82, in forward +pkg.torch.onnx.stack_trace File "/home/batman/xx3/./ml_tools/openpilot_compile/compile_supercombo.py", line 86, in forward return torch.cat([*self.forward_dict(inputs).values(), self.pad], dim=1) - File "/home/batman/xx2/xx/training/path/supercombo.py", line 191, in forward + File "/home/batman/xx3/xx/training/path/supercombo.py", line 191, in forward return {ModelInputs.FEATURES: self._en((x - self._mean) / self._std)} - File "/home/batman/xx2/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1418, in forward + File "/home/batman/xx3/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1418, in forward x = self.forward_features(x) - File "/home/batman/xx2/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1167, in forward + File "/home/batman/xx3/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1167, in forward x = self.blocks(x) - File "/home/batman/xx2/.venv/lib/python3.12/site-packages/torch/nn/modules/container.py", line 253, in forward + File "/home/batman/xx3/.venv/lib/python3.12/site-packages/torch/nn/modules/container.py", line 253, in forward input = module(input) - File "/home/batman/xx2/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1001, in forward + File "/home/batman/xx3/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1001, in forward x = self.token_mixer(x) - File "/home/batman/xx2/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 717, in forward + File "/home/batman/xx3/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 717, in forward x = self.reparam_conv(x) - File "/home/batman/xx2/.venv/lib/python3.12/site-packages/torch/nn/modules/conv.py", line 553, in forward + File "/home/batman/xx3/.venv/lib/python3.12/site-packages/torch/nn/modules/conv.py", line 553, in forward return self._conv_forward(input, self.weight, self.bias)  conv2d_43 @@ -2079,23 +2079,23 @@ getitem_27 node_Conv_301"Conv* 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/xx2/./ml_tools/openpilot_compile/compile_supercombo.py", line 82, in forward +File "/home/batman/xx3/./ml_tools/openpilot_compile/compile_supercombo.py", line 86, in forward return torch.cat([*self.forward_dict(inputs).values(), self.pad], dim=1) - File "/home/batman/xx2/xx/training/path/supercombo.py", line 191, in forward + File "/home/batman/xx3/xx/training/path/supercombo.py", line 191, in forward return {ModelInputs.FEATURES: self._en((x - self._mean) / self._std)} - File "/home/batman/xx2/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1418, in forward + File "/home/batman/xx3/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1418, in forward x = self.forward_features(x) - File "/home/batman/xx2/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1167, in forward + File "/home/batman/xx3/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1167, in forward x = self.blocks(x) - File "/home/batman/xx2/.venv/lib/python3.12/site-packages/torch/nn/modules/container.py", line 253, in forward + File "/home/batman/xx3/.venv/lib/python3.12/site-packages/torch/nn/modules/container.py", line 253, in forward input = module(input) - File "/home/batman/xx2/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1002, in forward + File "/home/batman/xx3/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1002, in forward x = x + self.drop_path(self.layer_scale(self.mlp(x))) - File "/home/batman/xx2/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 814, in forward + File "/home/batman/xx3/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 814, in forward x = self.conv(x) - File "/home/batman/xx2/.venv/lib/python3.12/site-packages/timm/layers/conv_bn_act.py", line 94, in forward + File "/home/batman/xx3/.venv/lib/python3.12/site-packages/timm/layers/conv_bn_act.py", line 94, in forward x = self.bn(x) - File "/home/batman/xx2/xx/training/path/allnorm.py", line 60, in forward + File "/home/batman/xx3/xx/training/path/allnorm.py", line 60, in forward return self.act(self.drop(self._allnorm_forward(x)))  @@ -2111,21 +2111,21 @@ 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/xx2/./ml_tools/openpilot_compile/compile_supercombo.py", line 82, in forward +pkg.torch.onnx.stack_trace File "/home/batman/xx3/./ml_tools/openpilot_compile/compile_supercombo.py", line 86, in forward return torch.cat([*self.forward_dict(inputs).values(), self.pad], dim=1) - File "/home/batman/xx2/xx/training/path/supercombo.py", line 191, in forward + File "/home/batman/xx3/xx/training/path/supercombo.py", line 191, in forward return {ModelInputs.FEATURES: self._en((x - self._mean) / self._std)} - File "/home/batman/xx2/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1418, in forward + File "/home/batman/xx3/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1418, in forward x = self.forward_features(x) - File "/home/batman/xx2/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1167, in forward + File "/home/batman/xx3/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1167, in forward x = self.blocks(x) - File "/home/batman/xx2/.venv/lib/python3.12/site-packages/torch/nn/modules/container.py", line 253, in forward + File "/home/batman/xx3/.venv/lib/python3.12/site-packages/torch/nn/modules/container.py", line 253, in forward input = module(input) - File "/home/batman/xx2/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1002, in forward + File "/home/batman/xx3/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1002, in forward x = x + self.drop_path(self.layer_scale(self.mlp(x))) - File "/home/batman/xx2/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 815, in forward + File "/home/batman/xx3/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 815, in forward x = self.fc1(x) - File "/home/batman/xx2/.venv/lib/python3.12/site-packages/torch/nn/modules/conv.py", line 553, in forward + File "/home/batman/xx3/.venv/lib/python3.12/site-packages/torch/nn/modules/conv.py", line 553, in forward return self._conv_forward(input, self.weight, self.bias)  conv2d_45gelu_14 node_gelu_14"Gelu* @@ -2134,21 +2134,21 @@ 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_trace File "/home/batman/xx2/./ml_tools/openpilot_compile/compile_supercombo.py", line 82, in forward +pkg.torch.onnx.stack_trace File "/home/batman/xx3/./ml_tools/openpilot_compile/compile_supercombo.py", line 86, in forward return torch.cat([*self.forward_dict(inputs).values(), self.pad], dim=1) - File "/home/batman/xx2/xx/training/path/supercombo.py", line 191, in forward + File "/home/batman/xx3/xx/training/path/supercombo.py", line 191, in forward return {ModelInputs.FEATURES: self._en((x - self._mean) / self._std)} - File "/home/batman/xx2/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1418, in forward + File "/home/batman/xx3/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1418, in forward x = self.forward_features(x) - File "/home/batman/xx2/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1167, in forward + File "/home/batman/xx3/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1167, in forward x = self.blocks(x) - File "/home/batman/xx2/.venv/lib/python3.12/site-packages/torch/nn/modules/container.py", line 253, in forward + File "/home/batman/xx3/.venv/lib/python3.12/site-packages/torch/nn/modules/container.py", line 253, in forward input = module(input) - File "/home/batman/xx2/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1002, in forward + File "/home/batman/xx3/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1002, in forward x = x + self.drop_path(self.layer_scale(self.mlp(x))) - File "/home/batman/xx2/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 816, in forward + File "/home/batman/xx3/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 816, in forward x = self.act(x) - File "/home/batman/xx2/.venv/lib/python3.12/site-packages/timm/layers/activations.py", line 159, in forward + File "/home/batman/xx3/.venv/lib/python3.12/site-packages/timm/layers/activations.py", line 159, in forward return F.gelu(input, approximate='tanh')  gelu_14 @@ -2163,21 +2163,21 @@ 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/xx2/./ml_tools/openpilot_compile/compile_supercombo.py", line 82, in forward +pkg.torch.onnx.stack_trace File "/home/batman/xx3/./ml_tools/openpilot_compile/compile_supercombo.py", line 86, in forward return torch.cat([*self.forward_dict(inputs).values(), self.pad], dim=1) - File "/home/batman/xx2/xx/training/path/supercombo.py", line 191, in forward + File "/home/batman/xx3/xx/training/path/supercombo.py", line 191, in forward return {ModelInputs.FEATURES: self._en((x - self._mean) / self._std)} - File "/home/batman/xx2/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1418, in forward + File "/home/batman/xx3/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1418, in forward x = self.forward_features(x) - File "/home/batman/xx2/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1167, in forward + File "/home/batman/xx3/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1167, in forward x = self.blocks(x) - File "/home/batman/xx2/.venv/lib/python3.12/site-packages/torch/nn/modules/container.py", line 253, in forward + File "/home/batman/xx3/.venv/lib/python3.12/site-packages/torch/nn/modules/container.py", line 253, in forward input = module(input) - File "/home/batman/xx2/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1002, in forward + File "/home/batman/xx3/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1002, in forward x = x + self.drop_path(self.layer_scale(self.mlp(x))) - File "/home/batman/xx2/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 818, in forward + File "/home/batman/xx3/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 818, in forward x = self.fc2(x) - File "/home/batman/xx2/.venv/lib/python3.12/site-packages/torch/nn/modules/conv.py", line 553, in forward + File "/home/batman/xx3/.venv/lib/python3.12/site-packages/torch/nn/modules/conv.py", line 553, in forward return self._conv_forward(input, self.weight, self.bias)  conv2d_46 @@ -2187,19 +2187,19 @@ 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/xx2/./ml_tools/openpilot_compile/compile_supercombo.py", line 82, in forward +pkg.torch.onnx.stack_traceFile "/home/batman/xx3/./ml_tools/openpilot_compile/compile_supercombo.py", line 86, in forward return torch.cat([*self.forward_dict(inputs).values(), self.pad], dim=1) - File "/home/batman/xx2/xx/training/path/supercombo.py", line 191, in forward + File "/home/batman/xx3/xx/training/path/supercombo.py", line 191, in forward return {ModelInputs.FEATURES: self._en((x - self._mean) / self._std)} - File "/home/batman/xx2/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1418, in forward + File "/home/batman/xx3/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1418, in forward x = self.forward_features(x) - File "/home/batman/xx2/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1167, in forward + File "/home/batman/xx3/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1167, in forward x = self.blocks(x) - File "/home/batman/xx2/.venv/lib/python3.12/site-packages/torch/nn/modules/container.py", line 253, in forward + File "/home/batman/xx3/.venv/lib/python3.12/site-packages/torch/nn/modules/container.py", line 253, in forward input = module(input) - File "/home/batman/xx2/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1002, in forward + File "/home/batman/xx3/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1002, in forward x = x + self.drop_path(self.layer_scale(self.mlp(x))) - File "/home/batman/xx2/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 646, in forward + File "/home/batman/xx3/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 646, in forward return x.mul_(self.gamma) if self.inplace else x * self.gamma  conv2d_43 @@ -2209,17 +2209,17 @@ 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/xx2/./ml_tools/openpilot_compile/compile_supercombo.py", line 82, in forward +pkg.torch.onnx.stack_traceFile "/home/batman/xx3/./ml_tools/openpilot_compile/compile_supercombo.py", line 86, in forward return torch.cat([*self.forward_dict(inputs).values(), self.pad], dim=1) - File "/home/batman/xx2/xx/training/path/supercombo.py", line 191, in forward + File "/home/batman/xx3/xx/training/path/supercombo.py", line 191, in forward return {ModelInputs.FEATURES: self._en((x - self._mean) / self._std)} - File "/home/batman/xx2/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1418, in forward + File "/home/batman/xx3/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1418, in forward x = self.forward_features(x) - File "/home/batman/xx2/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1167, in forward + File "/home/batman/xx3/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1167, in forward x = self.blocks(x) - File "/home/batman/xx2/.venv/lib/python3.12/site-packages/torch/nn/modules/container.py", line 253, in forward + File "/home/batman/xx3/.venv/lib/python3.12/site-packages/torch/nn/modules/container.py", line 253, in forward input = module(input) - File "/home/batman/xx2/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1002, in forward + File "/home/batman/xx3/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1002, in forward x = x + self.drop_path(self.layer_scale(self.mlp(x)))  add_9 @@ -2234,21 +2234,21 @@ 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_trace File "/home/batman/xx2/./ml_tools/openpilot_compile/compile_supercombo.py", line 82, in forward +pkg.torch.onnx.stack_trace File "/home/batman/xx3/./ml_tools/openpilot_compile/compile_supercombo.py", line 86, in forward return torch.cat([*self.forward_dict(inputs).values(), self.pad], dim=1) - File "/home/batman/xx2/xx/training/path/supercombo.py", line 191, in forward + File "/home/batman/xx3/xx/training/path/supercombo.py", line 191, in forward return {ModelInputs.FEATURES: self._en((x - self._mean) / self._std)} - File "/home/batman/xx2/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1418, in forward + File "/home/batman/xx3/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1418, in forward x = self.forward_features(x) - File "/home/batman/xx2/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1162, in forward + File "/home/batman/xx3/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1162, in forward x = self.downsample(x) - File "/home/batman/xx2/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 628, in forward + File "/home/batman/xx3/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 628, in forward x = self.proj(x) - File "/home/batman/xx2/.venv/lib/python3.12/site-packages/torch/nn/modules/container.py", line 253, in forward + File "/home/batman/xx3/.venv/lib/python3.12/site-packages/torch/nn/modules/container.py", line 253, in forward input = module(input) - File "/home/batman/xx2/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 376, in forward + File "/home/batman/xx3/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 376, in forward out = self.reparam_conv(x) - File "/home/batman/xx2/.venv/lib/python3.12/site-packages/torch/nn/modules/conv.py", line 553, in forward + File "/home/batman/xx3/.venv/lib/python3.12/site-packages/torch/nn/modules/conv.py", line 553, in forward return self._conv_forward(input, self.weight, self.bias)  conv2d_47 @@ -2263,21 +2263,21 @@ 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_trace File "/home/batman/xx2/./ml_tools/openpilot_compile/compile_supercombo.py", line 82, in forward +pkg.torch.onnx.stack_trace File "/home/batman/xx3/./ml_tools/openpilot_compile/compile_supercombo.py", line 86, in forward return torch.cat([*self.forward_dict(inputs).values(), self.pad], dim=1) - File "/home/batman/xx2/xx/training/path/supercombo.py", line 191, in forward + File "/home/batman/xx3/xx/training/path/supercombo.py", line 191, in forward return {ModelInputs.FEATURES: self._en((x - self._mean) / self._std)} - File "/home/batman/xx2/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1418, in forward + File "/home/batman/xx3/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1418, in forward x = self.forward_features(x) - File "/home/batman/xx2/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1162, in forward + File "/home/batman/xx3/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1162, in forward x = self.downsample(x) - File "/home/batman/xx2/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 628, in forward + File "/home/batman/xx3/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 628, in forward x = self.proj(x) - File "/home/batman/xx2/.venv/lib/python3.12/site-packages/torch/nn/modules/container.py", line 253, in forward + File "/home/batman/xx3/.venv/lib/python3.12/site-packages/torch/nn/modules/container.py", line 253, in forward input = module(input) - File "/home/batman/xx2/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 155, in forward + File "/home/batman/xx3/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 155, in forward return self.act(self.se(self.reparam_conv(x))) - File "/home/batman/xx2/.venv/lib/python3.12/site-packages/torch/nn/modules/conv.py", line 553, in forward + File "/home/batman/xx3/.venv/lib/python3.12/site-packages/torch/nn/modules/conv.py", line 553, in forward return self._conv_forward(input, self.weight, self.bias)  conv2d_48gelu_15 node_gelu_15"Gelu* @@ -2286,21 +2286,21 @@ 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_trace File "/home/batman/xx2/./ml_tools/openpilot_compile/compile_supercombo.py", line 82, in forward +pkg.torch.onnx.stack_trace File "/home/batman/xx3/./ml_tools/openpilot_compile/compile_supercombo.py", line 86, in forward return torch.cat([*self.forward_dict(inputs).values(), self.pad], dim=1) - File "/home/batman/xx2/xx/training/path/supercombo.py", line 191, in forward + File "/home/batman/xx3/xx/training/path/supercombo.py", line 191, in forward return {ModelInputs.FEATURES: self._en((x - self._mean) / self._std)} - File "/home/batman/xx2/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1418, in forward + File "/home/batman/xx3/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1418, in forward x = self.forward_features(x) - File "/home/batman/xx2/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1162, in forward + File "/home/batman/xx3/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1162, in forward x = self.downsample(x) - File "/home/batman/xx2/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 628, in forward + File "/home/batman/xx3/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 628, in forward x = self.proj(x) - File "/home/batman/xx2/.venv/lib/python3.12/site-packages/torch/nn/modules/container.py", line 253, in forward + File "/home/batman/xx3/.venv/lib/python3.12/site-packages/torch/nn/modules/container.py", line 253, in forward input = module(input) - File "/home/batman/xx2/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 155, in forward + File "/home/batman/xx3/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 155, in forward return self.act(self.se(self.reparam_conv(x))) - File "/home/batman/xx2/.venv/lib/python3.12/site-packages/timm/layers/activations.py", line 159, in forward + File "/home/batman/xx3/.venv/lib/python3.12/site-packages/timm/layers/activations.py", line 159, in forward return F.gelu(input, approximate='tanh')  gelu_15 @@ -2315,21 +2315,21 @@ 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_trace File "/home/batman/xx2/./ml_tools/openpilot_compile/compile_supercombo.py", line 82, in forward +pkg.torch.onnx.stack_trace File "/home/batman/xx3/./ml_tools/openpilot_compile/compile_supercombo.py", line 86, in forward return torch.cat([*self.forward_dict(inputs).values(), self.pad], dim=1) - File "/home/batman/xx2/xx/training/path/supercombo.py", line 191, in forward + File "/home/batman/xx3/xx/training/path/supercombo.py", line 191, in forward return {ModelInputs.FEATURES: self._en((x - self._mean) / self._std)} - File "/home/batman/xx2/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1418, in forward + File "/home/batman/xx3/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1418, in forward x = self.forward_features(x) - File "/home/batman/xx2/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1167, in forward + File "/home/batman/xx3/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1167, in forward x = self.blocks(x) - File "/home/batman/xx2/.venv/lib/python3.12/site-packages/torch/nn/modules/container.py", line 253, in forward + File "/home/batman/xx3/.venv/lib/python3.12/site-packages/torch/nn/modules/container.py", line 253, in forward input = module(input) - File "/home/batman/xx2/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1001, in forward + File "/home/batman/xx3/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1001, in forward x = self.token_mixer(x) - File "/home/batman/xx2/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 717, in forward + File "/home/batman/xx3/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 717, in forward x = self.reparam_conv(x) - File "/home/batman/xx2/.venv/lib/python3.12/site-packages/torch/nn/modules/conv.py", line 553, in forward + File "/home/batman/xx3/.venv/lib/python3.12/site-packages/torch/nn/modules/conv.py", line 553, in forward return self._conv_forward(input, self.weight, self.bias)  conv2d_49 @@ -2348,23 +2348,23 @@ getitem_30 node_Conv_303"Conv* 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/xx2/./ml_tools/openpilot_compile/compile_supercombo.py", line 82, in forward +File "/home/batman/xx3/./ml_tools/openpilot_compile/compile_supercombo.py", line 86, in forward return torch.cat([*self.forward_dict(inputs).values(), self.pad], dim=1) - File "/home/batman/xx2/xx/training/path/supercombo.py", line 191, in forward + File "/home/batman/xx3/xx/training/path/supercombo.py", line 191, in forward return {ModelInputs.FEATURES: self._en((x - self._mean) / self._std)} - File "/home/batman/xx2/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1418, in forward + File "/home/batman/xx3/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1418, in forward x = self.forward_features(x) - File "/home/batman/xx2/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1167, in forward + File "/home/batman/xx3/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1167, in forward x = self.blocks(x) - File "/home/batman/xx2/.venv/lib/python3.12/site-packages/torch/nn/modules/container.py", line 253, in forward + File "/home/batman/xx3/.venv/lib/python3.12/site-packages/torch/nn/modules/container.py", line 253, in forward input = module(input) - File "/home/batman/xx2/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1002, in forward + File "/home/batman/xx3/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1002, in forward x = x + self.drop_path(self.layer_scale(self.mlp(x))) - File "/home/batman/xx2/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 814, in forward + File "/home/batman/xx3/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 814, in forward x = self.conv(x) - File "/home/batman/xx2/.venv/lib/python3.12/site-packages/timm/layers/conv_bn_act.py", line 94, in forward + File "/home/batman/xx3/.venv/lib/python3.12/site-packages/timm/layers/conv_bn_act.py", line 94, in forward x = self.bn(x) - File "/home/batman/xx2/xx/training/path/allnorm.py", line 60, in forward + File "/home/batman/xx3/xx/training/path/allnorm.py", line 60, in forward return self.act(self.drop(self._allnorm_forward(x)))  @@ -2380,21 +2380,21 @@ 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/xx2/./ml_tools/openpilot_compile/compile_supercombo.py", line 82, in forward +pkg.torch.onnx.stack_trace File "/home/batman/xx3/./ml_tools/openpilot_compile/compile_supercombo.py", line 86, in forward return torch.cat([*self.forward_dict(inputs).values(), self.pad], dim=1) - File "/home/batman/xx2/xx/training/path/supercombo.py", line 191, in forward + File "/home/batman/xx3/xx/training/path/supercombo.py", line 191, in forward return {ModelInputs.FEATURES: self._en((x - self._mean) / self._std)} - File "/home/batman/xx2/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1418, in forward + File "/home/batman/xx3/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1418, in forward x = self.forward_features(x) - File "/home/batman/xx2/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1167, in forward + File "/home/batman/xx3/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1167, in forward x = self.blocks(x) - File "/home/batman/xx2/.venv/lib/python3.12/site-packages/torch/nn/modules/container.py", line 253, in forward + File "/home/batman/xx3/.venv/lib/python3.12/site-packages/torch/nn/modules/container.py", line 253, in forward input = module(input) - File "/home/batman/xx2/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1002, in forward + File "/home/batman/xx3/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1002, in forward x = x + self.drop_path(self.layer_scale(self.mlp(x))) - File "/home/batman/xx2/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 815, in forward + File "/home/batman/xx3/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 815, in forward x = self.fc1(x) - File "/home/batman/xx2/.venv/lib/python3.12/site-packages/torch/nn/modules/conv.py", line 553, in forward + File "/home/batman/xx3/.venv/lib/python3.12/site-packages/torch/nn/modules/conv.py", line 553, in forward return self._conv_forward(input, self.weight, self.bias)  conv2d_51gelu_16 node_gelu_16"Gelu* @@ -2403,21 +2403,21 @@ 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_trace File "/home/batman/xx2/./ml_tools/openpilot_compile/compile_supercombo.py", line 82, in forward +pkg.torch.onnx.stack_trace File "/home/batman/xx3/./ml_tools/openpilot_compile/compile_supercombo.py", line 86, in forward return torch.cat([*self.forward_dict(inputs).values(), self.pad], dim=1) - File "/home/batman/xx2/xx/training/path/supercombo.py", line 191, in forward + File "/home/batman/xx3/xx/training/path/supercombo.py", line 191, in forward return {ModelInputs.FEATURES: self._en((x - self._mean) / self._std)} - File "/home/batman/xx2/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1418, in forward + File "/home/batman/xx3/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1418, in forward x = self.forward_features(x) - File "/home/batman/xx2/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1167, in forward + File "/home/batman/xx3/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1167, in forward x = self.blocks(x) - File "/home/batman/xx2/.venv/lib/python3.12/site-packages/torch/nn/modules/container.py", line 253, in forward + File "/home/batman/xx3/.venv/lib/python3.12/site-packages/torch/nn/modules/container.py", line 253, in forward input = module(input) - File "/home/batman/xx2/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1002, in forward + File "/home/batman/xx3/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1002, in forward x = x + self.drop_path(self.layer_scale(self.mlp(x))) - File "/home/batman/xx2/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 816, in forward + File "/home/batman/xx3/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 816, in forward x = self.act(x) - File "/home/batman/xx2/.venv/lib/python3.12/site-packages/timm/layers/activations.py", line 159, in forward + File "/home/batman/xx3/.venv/lib/python3.12/site-packages/timm/layers/activations.py", line 159, in forward return F.gelu(input, approximate='tanh')  gelu_16 @@ -2432,21 +2432,21 @@ 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/xx2/./ml_tools/openpilot_compile/compile_supercombo.py", line 82, in forward +pkg.torch.onnx.stack_trace File "/home/batman/xx3/./ml_tools/openpilot_compile/compile_supercombo.py", line 86, in forward return torch.cat([*self.forward_dict(inputs).values(), self.pad], dim=1) - File "/home/batman/xx2/xx/training/path/supercombo.py", line 191, in forward + File "/home/batman/xx3/xx/training/path/supercombo.py", line 191, in forward return {ModelInputs.FEATURES: self._en((x - self._mean) / self._std)} - File "/home/batman/xx2/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1418, in forward + File "/home/batman/xx3/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1418, in forward x = self.forward_features(x) - File "/home/batman/xx2/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1167, in forward + File "/home/batman/xx3/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1167, in forward x = self.blocks(x) - File "/home/batman/xx2/.venv/lib/python3.12/site-packages/torch/nn/modules/container.py", line 253, in forward + File "/home/batman/xx3/.venv/lib/python3.12/site-packages/torch/nn/modules/container.py", line 253, in forward input = module(input) - File "/home/batman/xx2/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1002, in forward + File "/home/batman/xx3/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1002, in forward x = x + self.drop_path(self.layer_scale(self.mlp(x))) - File "/home/batman/xx2/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 818, in forward + File "/home/batman/xx3/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 818, in forward x = self.fc2(x) - File "/home/batman/xx2/.venv/lib/python3.12/site-packages/torch/nn/modules/conv.py", line 553, in forward + File "/home/batman/xx3/.venv/lib/python3.12/site-packages/torch/nn/modules/conv.py", line 553, in forward return self._conv_forward(input, self.weight, self.bias)  conv2d_52 @@ -2455,19 +2455,19 @@ 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/xx2/./ml_tools/openpilot_compile/compile_supercombo.py", line 82, in forward +pkg.torch.onnx.stack_traceFile "/home/batman/xx3/./ml_tools/openpilot_compile/compile_supercombo.py", line 86, in forward return torch.cat([*self.forward_dict(inputs).values(), self.pad], dim=1) - File "/home/batman/xx2/xx/training/path/supercombo.py", line 191, in forward + File "/home/batman/xx3/xx/training/path/supercombo.py", line 191, in forward return {ModelInputs.FEATURES: self._en((x - self._mean) / self._std)} - File "/home/batman/xx2/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1418, in forward + File "/home/batman/xx3/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1418, in forward x = self.forward_features(x) - File "/home/batman/xx2/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1167, in forward + File "/home/batman/xx3/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1167, in forward x = self.blocks(x) - File "/home/batman/xx2/.venv/lib/python3.12/site-packages/torch/nn/modules/container.py", line 253, in forward + File "/home/batman/xx3/.venv/lib/python3.12/site-packages/torch/nn/modules/container.py", line 253, in forward input = module(input) - File "/home/batman/xx2/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1002, in forward + File "/home/batman/xx3/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1002, in forward x = x + self.drop_path(self.layer_scale(self.mlp(x))) - File "/home/batman/xx2/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 646, in forward + File "/home/batman/xx3/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 646, in forward return x.mul_(self.gamma) if self.inplace else x * self.gamma  conv2d_49 @@ -2476,17 +2476,17 @@ 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/xx2/./ml_tools/openpilot_compile/compile_supercombo.py", line 82, in forward +pkg.torch.onnx.stack_traceFile "/home/batman/xx3/./ml_tools/openpilot_compile/compile_supercombo.py", line 86, in forward return torch.cat([*self.forward_dict(inputs).values(), self.pad], dim=1) - File "/home/batman/xx2/xx/training/path/supercombo.py", line 191, in forward + File "/home/batman/xx3/xx/training/path/supercombo.py", line 191, in forward return {ModelInputs.FEATURES: self._en((x - self._mean) / self._std)} - File "/home/batman/xx2/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1418, in forward + File "/home/batman/xx3/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1418, in forward x = self.forward_features(x) - File "/home/batman/xx2/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1167, in forward + File "/home/batman/xx3/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1167, in forward x = self.blocks(x) - File "/home/batman/xx2/.venv/lib/python3.12/site-packages/torch/nn/modules/container.py", line 253, in forward + File "/home/batman/xx3/.venv/lib/python3.12/site-packages/torch/nn/modules/container.py", line 253, in forward input = module(input) - File "/home/batman/xx2/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1002, in forward + File "/home/batman/xx3/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1002, in forward x = x + self.drop_path(self.layer_scale(self.mlp(x)))  add_10 @@ -2501,21 +2501,21 @@ 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_trace File "/home/batman/xx2/./ml_tools/openpilot_compile/compile_supercombo.py", line 82, in forward +pkg.torch.onnx.stack_trace File "/home/batman/xx3/./ml_tools/openpilot_compile/compile_supercombo.py", line 86, in forward return torch.cat([*self.forward_dict(inputs).values(), self.pad], dim=1) - File "/home/batman/xx2/xx/training/path/supercombo.py", line 191, in forward + File "/home/batman/xx3/xx/training/path/supercombo.py", line 191, in forward return {ModelInputs.FEATURES: self._en((x - self._mean) / self._std)} - File "/home/batman/xx2/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1418, in forward + File "/home/batman/xx3/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1418, in forward x = self.forward_features(x) - File "/home/batman/xx2/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1167, in forward + File "/home/batman/xx3/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1167, in forward x = self.blocks(x) - File "/home/batman/xx2/.venv/lib/python3.12/site-packages/torch/nn/modules/container.py", line 253, in forward + File "/home/batman/xx3/.venv/lib/python3.12/site-packages/torch/nn/modules/container.py", line 253, in forward input = module(input) - File "/home/batman/xx2/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1001, in forward + File "/home/batman/xx3/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1001, in forward x = self.token_mixer(x) - File "/home/batman/xx2/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 717, in forward + File "/home/batman/xx3/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 717, in forward x = self.reparam_conv(x) - File "/home/batman/xx2/.venv/lib/python3.12/site-packages/torch/nn/modules/conv.py", line 553, in forward + File "/home/batman/xx3/.venv/lib/python3.12/site-packages/torch/nn/modules/conv.py", line 553, in forward return self._conv_forward(input, self.weight, self.bias)  conv2d_53 @@ -2534,23 +2534,23 @@ getitem_33 node_Conv_305"Conv* 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/xx2/./ml_tools/openpilot_compile/compile_supercombo.py", line 82, in forward +File "/home/batman/xx3/./ml_tools/openpilot_compile/compile_supercombo.py", line 86, in forward return torch.cat([*self.forward_dict(inputs).values(), self.pad], dim=1) - File "/home/batman/xx2/xx/training/path/supercombo.py", line 191, in forward + File "/home/batman/xx3/xx/training/path/supercombo.py", line 191, in forward return {ModelInputs.FEATURES: self._en((x - self._mean) / self._std)} - File "/home/batman/xx2/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1418, in forward + File "/home/batman/xx3/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1418, in forward x = self.forward_features(x) - File "/home/batman/xx2/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1167, in forward + File "/home/batman/xx3/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1167, in forward x = self.blocks(x) - File "/home/batman/xx2/.venv/lib/python3.12/site-packages/torch/nn/modules/container.py", line 253, in forward + File "/home/batman/xx3/.venv/lib/python3.12/site-packages/torch/nn/modules/container.py", line 253, in forward input = module(input) - File "/home/batman/xx2/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1002, in forward + File "/home/batman/xx3/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1002, in forward x = x + self.drop_path(self.layer_scale(self.mlp(x))) - File "/home/batman/xx2/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 814, in forward + File "/home/batman/xx3/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 814, in forward x = self.conv(x) - File "/home/batman/xx2/.venv/lib/python3.12/site-packages/timm/layers/conv_bn_act.py", line 94, in forward + File "/home/batman/xx3/.venv/lib/python3.12/site-packages/timm/layers/conv_bn_act.py", line 94, in forward x = self.bn(x) - File "/home/batman/xx2/xx/training/path/allnorm.py", line 60, in forward + File "/home/batman/xx3/xx/training/path/allnorm.py", line 60, in forward return self.act(self.drop(self._allnorm_forward(x)))  @@ -2566,21 +2566,21 @@ 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/xx2/./ml_tools/openpilot_compile/compile_supercombo.py", line 82, in forward +pkg.torch.onnx.stack_trace File "/home/batman/xx3/./ml_tools/openpilot_compile/compile_supercombo.py", line 86, in forward return torch.cat([*self.forward_dict(inputs).values(), self.pad], dim=1) - File "/home/batman/xx2/xx/training/path/supercombo.py", line 191, in forward + File "/home/batman/xx3/xx/training/path/supercombo.py", line 191, in forward return {ModelInputs.FEATURES: self._en((x - self._mean) / self._std)} - File "/home/batman/xx2/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1418, in forward + File "/home/batman/xx3/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1418, in forward x = self.forward_features(x) - File "/home/batman/xx2/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1167, in forward + File "/home/batman/xx3/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1167, in forward x = self.blocks(x) - File "/home/batman/xx2/.venv/lib/python3.12/site-packages/torch/nn/modules/container.py", line 253, in forward + File "/home/batman/xx3/.venv/lib/python3.12/site-packages/torch/nn/modules/container.py", line 253, in forward input = module(input) - File "/home/batman/xx2/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1002, in forward + File "/home/batman/xx3/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1002, in forward x = x + self.drop_path(self.layer_scale(self.mlp(x))) - File "/home/batman/xx2/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 815, in forward + File "/home/batman/xx3/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 815, in forward x = self.fc1(x) - File "/home/batman/xx2/.venv/lib/python3.12/site-packages/torch/nn/modules/conv.py", line 553, in forward + File "/home/batman/xx3/.venv/lib/python3.12/site-packages/torch/nn/modules/conv.py", line 553, in forward return self._conv_forward(input, self.weight, self.bias)  conv2d_55gelu_17 node_gelu_17"Gelu* @@ -2589,21 +2589,21 @@ 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_trace File "/home/batman/xx2/./ml_tools/openpilot_compile/compile_supercombo.py", line 82, in forward +pkg.torch.onnx.stack_trace File "/home/batman/xx3/./ml_tools/openpilot_compile/compile_supercombo.py", line 86, in forward return torch.cat([*self.forward_dict(inputs).values(), self.pad], dim=1) - File "/home/batman/xx2/xx/training/path/supercombo.py", line 191, in forward + File "/home/batman/xx3/xx/training/path/supercombo.py", line 191, in forward return {ModelInputs.FEATURES: self._en((x - self._mean) / self._std)} - File "/home/batman/xx2/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1418, in forward + File "/home/batman/xx3/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1418, in forward x = self.forward_features(x) - File "/home/batman/xx2/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1167, in forward + File "/home/batman/xx3/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1167, in forward x = self.blocks(x) - File "/home/batman/xx2/.venv/lib/python3.12/site-packages/torch/nn/modules/container.py", line 253, in forward + File "/home/batman/xx3/.venv/lib/python3.12/site-packages/torch/nn/modules/container.py", line 253, in forward input = module(input) - File "/home/batman/xx2/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1002, in forward + File "/home/batman/xx3/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1002, in forward x = x + self.drop_path(self.layer_scale(self.mlp(x))) - File "/home/batman/xx2/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 816, in forward + File "/home/batman/xx3/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 816, in forward x = self.act(x) - File "/home/batman/xx2/.venv/lib/python3.12/site-packages/timm/layers/activations.py", line 159, in forward + File "/home/batman/xx3/.venv/lib/python3.12/site-packages/timm/layers/activations.py", line 159, in forward return F.gelu(input, approximate='tanh')  gelu_17 @@ -2618,21 +2618,21 @@ 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/xx2/./ml_tools/openpilot_compile/compile_supercombo.py", line 82, in forward +pkg.torch.onnx.stack_trace File "/home/batman/xx3/./ml_tools/openpilot_compile/compile_supercombo.py", line 86, in forward return torch.cat([*self.forward_dict(inputs).values(), self.pad], dim=1) - File "/home/batman/xx2/xx/training/path/supercombo.py", line 191, in forward + File "/home/batman/xx3/xx/training/path/supercombo.py", line 191, in forward return {ModelInputs.FEATURES: self._en((x - self._mean) / self._std)} - File "/home/batman/xx2/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1418, in forward + File "/home/batman/xx3/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1418, in forward x = self.forward_features(x) - File "/home/batman/xx2/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1167, in forward + File "/home/batman/xx3/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1167, in forward x = self.blocks(x) - File "/home/batman/xx2/.venv/lib/python3.12/site-packages/torch/nn/modules/container.py", line 253, in forward + File "/home/batman/xx3/.venv/lib/python3.12/site-packages/torch/nn/modules/container.py", line 253, in forward input = module(input) - File "/home/batman/xx2/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1002, in forward + File "/home/batman/xx3/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1002, in forward x = x + self.drop_path(self.layer_scale(self.mlp(x))) - File "/home/batman/xx2/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 818, in forward + File "/home/batman/xx3/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 818, in forward x = self.fc2(x) - File "/home/batman/xx2/.venv/lib/python3.12/site-packages/torch/nn/modules/conv.py", line 553, in forward + File "/home/batman/xx3/.venv/lib/python3.12/site-packages/torch/nn/modules/conv.py", line 553, in forward return self._conv_forward(input, self.weight, self.bias)  conv2d_56 @@ -2641,19 +2641,19 @@ 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/xx2/./ml_tools/openpilot_compile/compile_supercombo.py", line 82, in forward +pkg.torch.onnx.stack_traceFile "/home/batman/xx3/./ml_tools/openpilot_compile/compile_supercombo.py", line 86, in forward return torch.cat([*self.forward_dict(inputs).values(), self.pad], dim=1) - File "/home/batman/xx2/xx/training/path/supercombo.py", line 191, in forward + File "/home/batman/xx3/xx/training/path/supercombo.py", line 191, in forward return {ModelInputs.FEATURES: self._en((x - self._mean) / self._std)} - File "/home/batman/xx2/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1418, in forward + File "/home/batman/xx3/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1418, in forward x = self.forward_features(x) - File "/home/batman/xx2/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1167, in forward + File "/home/batman/xx3/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1167, in forward x = self.blocks(x) - File "/home/batman/xx2/.venv/lib/python3.12/site-packages/torch/nn/modules/container.py", line 253, in forward + File "/home/batman/xx3/.venv/lib/python3.12/site-packages/torch/nn/modules/container.py", line 253, in forward input = module(input) - File "/home/batman/xx2/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1002, in forward + File "/home/batman/xx3/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1002, in forward x = x + self.drop_path(self.layer_scale(self.mlp(x))) - File "/home/batman/xx2/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 646, in forward + File "/home/batman/xx3/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 646, in forward return x.mul_(self.gamma) if self.inplace else x * self.gamma  conv2d_53 @@ -2662,17 +2662,17 @@ 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/xx2/./ml_tools/openpilot_compile/compile_supercombo.py", line 82, in forward +pkg.torch.onnx.stack_traceFile "/home/batman/xx3/./ml_tools/openpilot_compile/compile_supercombo.py", line 86, in forward return torch.cat([*self.forward_dict(inputs).values(), self.pad], dim=1) - File "/home/batman/xx2/xx/training/path/supercombo.py", line 191, in forward + File "/home/batman/xx3/xx/training/path/supercombo.py", line 191, in forward return {ModelInputs.FEATURES: self._en((x - self._mean) / self._std)} - File "/home/batman/xx2/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1418, in forward + File "/home/batman/xx3/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1418, in forward x = self.forward_features(x) - File "/home/batman/xx2/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1167, in forward + File "/home/batman/xx3/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1167, in forward x = self.blocks(x) - File "/home/batman/xx2/.venv/lib/python3.12/site-packages/torch/nn/modules/container.py", line 253, in forward + File "/home/batman/xx3/.venv/lib/python3.12/site-packages/torch/nn/modules/container.py", line 253, in forward input = module(input) - File "/home/batman/xx2/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1002, in forward + File "/home/batman/xx3/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1002, in forward x = x + self.drop_path(self.layer_scale(self.mlp(x)))  add_11 @@ -2687,15 +2687,15 @@ 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/xx2/./ml_tools/openpilot_compile/compile_supercombo.py", line 82, in forward +pkg.torch.onnx.stack_traceFile "/home/batman/xx3/./ml_tools/openpilot_compile/compile_supercombo.py", line 86, in forward return torch.cat([*self.forward_dict(inputs).values(), self.pad], dim=1) - File "/home/batman/xx2/xx/training/path/supercombo.py", line 191, in forward + File "/home/batman/xx3/xx/training/path/supercombo.py", line 191, in forward return {ModelInputs.FEATURES: self._en((x - self._mean) / self._std)} - File "/home/batman/xx2/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1418, in forward + File "/home/batman/xx3/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1418, in forward x = self.forward_features(x) - File "/home/batman/xx2/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 155, in forward + File "/home/batman/xx3/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 155, in forward return self.act(self.se(self.reparam_conv(x))) - File "/home/batman/xx2/.venv/lib/python3.12/site-packages/torch/nn/modules/conv.py", line 553, in forward + File "/home/batman/xx3/.venv/lib/python3.12/site-packages/torch/nn/modules/conv.py", line 553, in forward return self._conv_forward(input, self.weight, self.bias) conv2d_57 @@ -2707,15 +2707,15 @@ 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/xx2/./ml_tools/openpilot_compile/compile_supercombo.py", line 82, in forward +pkg.torch.onnx.stack_traceFile "/home/batman/xx3/./ml_tools/openpilot_compile/compile_supercombo.py", line 86, in forward return torch.cat([*self.forward_dict(inputs).values(), self.pad], dim=1) - File "/home/batman/xx2/xx/training/path/supercombo.py", line 191, in forward + File "/home/batman/xx3/xx/training/path/supercombo.py", line 191, in forward return {ModelInputs.FEATURES: self._en((x - self._mean) / self._std)} - File "/home/batman/xx2/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1418, in forward + File "/home/batman/xx3/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1418, in forward x = self.forward_features(x) - File "/home/batman/xx2/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 155, in forward + File "/home/batman/xx3/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 155, in forward return self.act(self.se(self.reparam_conv(x))) - File "/home/batman/xx2/.venv/lib/python3.12/site-packages/timm/layers/squeeze_excite.py", line 56, in forward + File "/home/batman/xx3/.venv/lib/python3.12/site-packages/timm/layers/squeeze_excite.py", line 56, in forward x_se = x.mean((2, 3), keepdim=True)  mean @@ -2730,17 +2730,17 @@ 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/xx2/./ml_tools/openpilot_compile/compile_supercombo.py", line 82, in forward +pkg.torch.onnx.stack_traceFile "/home/batman/xx3/./ml_tools/openpilot_compile/compile_supercombo.py", line 86, in forward return torch.cat([*self.forward_dict(inputs).values(), self.pad], dim=1) - File "/home/batman/xx2/xx/training/path/supercombo.py", line 191, in forward + File "/home/batman/xx3/xx/training/path/supercombo.py", line 191, in forward return {ModelInputs.FEATURES: self._en((x - self._mean) / self._std)} - File "/home/batman/xx2/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1418, in forward + File "/home/batman/xx3/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1418, in forward x = self.forward_features(x) - File "/home/batman/xx2/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 155, in forward + File "/home/batman/xx3/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 155, in forward return self.act(self.se(self.reparam_conv(x))) - File "/home/batman/xx2/.venv/lib/python3.12/site-packages/timm/layers/squeeze_excite.py", line 60, in forward + File "/home/batman/xx3/.venv/lib/python3.12/site-packages/timm/layers/squeeze_excite.py", line 60, in forward x_se = self.fc1(x_se) - File "/home/batman/xx2/.venv/lib/python3.12/site-packages/torch/nn/modules/conv.py", line 553, in forward + File "/home/batman/xx3/.venv/lib/python3.12/site-packages/torch/nn/modules/conv.py", line 553, in forward return self._conv_forward(input, self.weight, self.bias)  conv2d_58relu node_relu"ReluJ @@ -2748,17 +2748,17 @@ 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/xx2/./ml_tools/openpilot_compile/compile_supercombo.py", line 82, in forward +pkg.torch.onnx.stack_traceFile "/home/batman/xx3/./ml_tools/openpilot_compile/compile_supercombo.py", line 86, in forward return torch.cat([*self.forward_dict(inputs).values(), self.pad], dim=1) - File "/home/batman/xx2/xx/training/path/supercombo.py", line 191, in forward + File "/home/batman/xx3/xx/training/path/supercombo.py", line 191, in forward return {ModelInputs.FEATURES: self._en((x - self._mean) / self._std)} - File "/home/batman/xx2/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1418, in forward + File "/home/batman/xx3/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1418, in forward x = self.forward_features(x) - File "/home/batman/xx2/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 155, in forward + File "/home/batman/xx3/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 155, in forward return self.act(self.se(self.reparam_conv(x))) - File "/home/batman/xx2/.venv/lib/python3.12/site-packages/timm/layers/squeeze_excite.py", line 61, in forward + File "/home/batman/xx3/.venv/lib/python3.12/site-packages/timm/layers/squeeze_excite.py", line 61, in forward x_se = self.act(self.bn(x_se)) - File "/home/batman/xx2/.venv/lib/python3.12/site-packages/torch/nn/modules/activation.py", line 143, in forward + File "/home/batman/xx3/.venv/lib/python3.12/site-packages/torch/nn/modules/activation.py", line 143, in forward return F.relu(input, inplace=self.inplace)  relu @@ -2773,17 +2773,17 @@ 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/xx2/./ml_tools/openpilot_compile/compile_supercombo.py", line 82, in forward +pkg.torch.onnx.stack_traceFile "/home/batman/xx3/./ml_tools/openpilot_compile/compile_supercombo.py", line 86, in forward return torch.cat([*self.forward_dict(inputs).values(), self.pad], dim=1) - File "/home/batman/xx2/xx/training/path/supercombo.py", line 191, in forward + File "/home/batman/xx3/xx/training/path/supercombo.py", line 191, in forward return {ModelInputs.FEATURES: self._en((x - self._mean) / self._std)} - File "/home/batman/xx2/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1418, in forward + File "/home/batman/xx3/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1418, in forward x = self.forward_features(x) - File "/home/batman/xx2/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 155, in forward + File "/home/batman/xx3/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 155, in forward return self.act(self.se(self.reparam_conv(x))) - File "/home/batman/xx2/.venv/lib/python3.12/site-packages/timm/layers/squeeze_excite.py", line 62, in forward + File "/home/batman/xx3/.venv/lib/python3.12/site-packages/timm/layers/squeeze_excite.py", line 62, in forward x_se = self.fc2(x_se) - File "/home/batman/xx2/.venv/lib/python3.12/site-packages/torch/nn/modules/conv.py", line 553, in forward + File "/home/batman/xx3/.venv/lib/python3.12/site-packages/torch/nn/modules/conv.py", line 553, in forward return self._conv_forward(input, self.weight, self.bias)  conv2d_59sigmoid node_sigmoid"SigmoidJ @@ -2791,17 +2791,17 @@ 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/xx2/./ml_tools/openpilot_compile/compile_supercombo.py", line 82, in forward +pkg.torch.onnx.stack_traceFile "/home/batman/xx3/./ml_tools/openpilot_compile/compile_supercombo.py", line 86, in forward return torch.cat([*self.forward_dict(inputs).values(), self.pad], dim=1) - File "/home/batman/xx2/xx/training/path/supercombo.py", line 191, in forward + File "/home/batman/xx3/xx/training/path/supercombo.py", line 191, in forward return {ModelInputs.FEATURES: self._en((x - self._mean) / self._std)} - File "/home/batman/xx2/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1418, in forward + File "/home/batman/xx3/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1418, in forward x = self.forward_features(x) - File "/home/batman/xx2/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 155, in forward + File "/home/batman/xx3/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 155, in forward return self.act(self.se(self.reparam_conv(x))) - File "/home/batman/xx2/.venv/lib/python3.12/site-packages/timm/layers/squeeze_excite.py", line 63, in forward + File "/home/batman/xx3/.venv/lib/python3.12/site-packages/timm/layers/squeeze_excite.py", line 63, in forward return x * self.gate(x_se) - File "/home/batman/xx2/.venv/lib/python3.12/site-packages/timm/layers/activations.py", line 57, in forward + File "/home/batman/xx3/.venv/lib/python3.12/site-packages/timm/layers/activations.py", line 57, in forward return x.sigmoid_() if self.inplace else x.sigmoid() conv2d_57 @@ -2810,15 +2810,15 @@ 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/xx2/./ml_tools/openpilot_compile/compile_supercombo.py", line 82, in forward +pkg.torch.onnx.stack_traceFile "/home/batman/xx3/./ml_tools/openpilot_compile/compile_supercombo.py", line 86, in forward return torch.cat([*self.forward_dict(inputs).values(), self.pad], dim=1) - File "/home/batman/xx2/xx/training/path/supercombo.py", line 191, in forward + File "/home/batman/xx3/xx/training/path/supercombo.py", line 191, in forward return {ModelInputs.FEATURES: self._en((x - self._mean) / self._std)} - File "/home/batman/xx2/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1418, in forward + File "/home/batman/xx3/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1418, in forward x = self.forward_features(x) - File "/home/batman/xx2/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 155, in forward + File "/home/batman/xx3/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 155, in forward return self.act(self.se(self.reparam_conv(x))) - File "/home/batman/xx2/.venv/lib/python3.12/site-packages/timm/layers/squeeze_excite.py", line 63, in forward + File "/home/batman/xx3/.venv/lib/python3.12/site-packages/timm/layers/squeeze_excite.py", line 63, in forward return x * self.gate(x_se) mul_12gelu_18 node_gelu_18"Gelu* @@ -2827,15 +2827,15 @@ 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/xx2/./ml_tools/openpilot_compile/compile_supercombo.py", line 82, in forward +pkg.torch.onnx.stack_traceFile "/home/batman/xx3/./ml_tools/openpilot_compile/compile_supercombo.py", line 86, in forward return torch.cat([*self.forward_dict(inputs).values(), self.pad], dim=1) - File "/home/batman/xx2/xx/training/path/supercombo.py", line 191, in forward + File "/home/batman/xx3/xx/training/path/supercombo.py", line 191, in forward return {ModelInputs.FEATURES: self._en((x - self._mean) / self._std)} - File "/home/batman/xx2/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1418, in forward + File "/home/batman/xx3/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1418, in forward x = self.forward_features(x) - File "/home/batman/xx2/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 155, in forward + File "/home/batman/xx3/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 155, in forward return self.act(self.se(self.reparam_conv(x))) - File "/home/batman/xx2/.venv/lib/python3.12/site-packages/timm/layers/activations.py", line 159, in forward + File "/home/batman/xx3/.venv/lib/python3.12/site-packages/timm/layers/activations.py", line 159, in forward return F.gelu(input, approximate='tanh')  gelu_18 @@ -2847,17 +2847,17 @@ 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/xx2/./ml_tools/openpilot_compile/compile_supercombo.py", line 82, in forward +pkg.torch.onnx.stack_traceFile "/home/batman/xx3/./ml_tools/openpilot_compile/compile_supercombo.py", line 86, in forward return torch.cat([*self.forward_dict(inputs).values(), self.pad], dim=1) - File "/home/batman/xx2/xx/training/path/supercombo.py", line 191, in forward + File "/home/batman/xx3/xx/training/path/supercombo.py", line 191, in forward return {ModelInputs.FEATURES: self._en((x - self._mean) / self._std)} - File "/home/batman/xx2/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1421, in forward + File "/home/batman/xx3/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1421, in forward x = self.forward_head(x) - File "/home/batman/xx2/.venv/lib/python3.12/site-packages/timm/layers/classifier.py", line 137, in forward + File "/home/batman/xx3/.venv/lib/python3.12/site-packages/timm/layers/classifier.py", line 137, in forward x = self.global_pool(x) - File "/home/batman/xx2/.venv/lib/python3.12/site-packages/timm/layers/adaptive_avgmax_pool.py", line 172, in forward + File "/home/batman/xx3/.venv/lib/python3.12/site-packages/timm/layers/adaptive_avgmax_pool.py", line 172, in forward x = self.pool(x) - File "/home/batman/xx2/.venv/lib/python3.12/site-packages/torch/nn/modules/pooling.py", line 1510, in forward + File "/home/batman/xx3/.venv/lib/python3.12/site-packages/torch/nn/modules/pooling.py", line 1510, in forward return F.adaptive_avg_pool2d(input, self.output_size)  mean_1 @@ -2867,17 +2867,17 @@ 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/xx2/./ml_tools/openpilot_compile/compile_supercombo.py", line 82, in forward +pkg.torch.onnx.stack_traceFile "/home/batman/xx3/./ml_tools/openpilot_compile/compile_supercombo.py", line 86, in forward return torch.cat([*self.forward_dict(inputs).values(), self.pad], dim=1) - File "/home/batman/xx2/xx/training/path/supercombo.py", line 191, in forward + File "/home/batman/xx3/xx/training/path/supercombo.py", line 191, in forward return {ModelInputs.FEATURES: self._en((x - self._mean) / self._std)} - File "/home/batman/xx2/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1421, in forward + File "/home/batman/xx3/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1421, in forward x = self.forward_head(x) - File "/home/batman/xx2/.venv/lib/python3.12/site-packages/timm/layers/classifier.py", line 137, in forward + File "/home/batman/xx3/.venv/lib/python3.12/site-packages/timm/layers/classifier.py", line 137, in forward x = self.global_pool(x) - File "/home/batman/xx2/.venv/lib/python3.12/site-packages/timm/layers/adaptive_avgmax_pool.py", line 173, in forward + File "/home/batman/xx3/.venv/lib/python3.12/site-packages/timm/layers/adaptive_avgmax_pool.py", line 173, in forward x = self.flatten(x) - File "/home/batman/xx2/.venv/lib/python3.12/site-packages/torch/nn/modules/flatten.py", line 55, in forward + File "/home/batman/xx3/.venv/lib/python3.12/site-packages/torch/nn/modules/flatten.py", line 55, in forward return input.flatten(self.start_dim, self.end_dim)  view @@ -2891,15 +2891,15 @@ $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/xx2/./ml_tools/openpilot_compile/compile_supercombo.py", line 82, in forward +pkg.torch.onnx.stack_traceFile "/home/batman/xx3/./ml_tools/openpilot_compile/compile_supercombo.py", line 86, in forward return torch.cat([*self.forward_dict(inputs).values(), self.pad], dim=1) - File "/home/batman/xx2/xx/training/path/supercombo.py", line 191, in forward + File "/home/batman/xx3/xx/training/path/supercombo.py", line 191, in forward return {ModelInputs.FEATURES: self._en((x - self._mean) / self._std)} - File "/home/batman/xx2/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1421, in forward + File "/home/batman/xx3/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1421, in forward x = self.forward_head(x) - File "/home/batman/xx2/.venv/lib/python3.12/site-packages/timm/layers/classifier.py", line 141, in forward + File "/home/batman/xx3/.venv/lib/python3.12/site-packages/timm/layers/classifier.py", line 141, in forward x = self.fc(x) - File "/home/batman/xx2/.venv/lib/python3.12/site-packages/torch/nn/modules/linear.py", line 134, in forward + File "/home/batman/xx3/.venv/lib/python3.12/site-packages/torch/nn/modules/linear.py", line 134, in forward return F.linear(input, self.weight, self.bias)  linear @@ -2914,15 +2914,15 @@ stash_type pkg.torch.onnx.class_hierarchy['__main__.FlattenedVisionModel', 'xx.training.path.supercombo.Policy', 'xx.training.path.supercombo.PointSummarizer', '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, [512], %p_vision_model_point_policy_summarizer_mlp1_layer_norm_weight, %p_vision_model_point_policy_summarizer_mlp1_layer_norm_bias, 1e-05, False), kwargs = {})J pkg.torch.onnx.name_scopes['', 'vision_model.point_policy', 'vision_model.point_policy.summarizer', 'vision_model.point_policy.summarizer.mlp1', 'vision_model.point_policy.summarizer.mlp1.layer_norm', 'layer_norm']J -pkg.torch.onnx.stack_traceFile "/home/batman/xx2/./ml_tools/openpilot_compile/compile_supercombo.py", line 82, in forward +pkg.torch.onnx.stack_traceFile "/home/batman/xx3/./ml_tools/openpilot_compile/compile_supercombo.py", line 86, in forward return torch.cat([*self.forward_dict(inputs).values(), self.pad], dim=1) - File "/home/batman/xx2/xx/training/path/supercombo.py", line 125, in forward + File "/home/batman/xx3/xx/training/path/supercombo.py", line 125, in forward summary_outs = self.summarizer(vision_features) - File "/home/batman/xx2/xx/training/path/supercombo.py", line 32, in forward + File "/home/batman/xx3/xx/training/path/supercombo.py", line 32, in forward x = self.mlp1(x) + x - File "/home/batman/xx2/.venv/lib/python3.12/site-packages/torch/nn/modules/container.py", line 253, in forward + File "/home/batman/xx3/.venv/lib/python3.12/site-packages/torch/nn/modules/container.py", line 253, in forward input = module(input) - File "/home/batman/xx2/.venv/lib/python3.12/site-packages/torch/nn/modules/normalization.py", line 229, in forward + File "/home/batman/xx3/.venv/lib/python3.12/site-packages/torch/nn/modules/normalization.py", line 229, in forward return F.layer_norm(  @@ -2936,15 +2936,15 @@ layer_norm pkg.torch.onnx.class_hierarchy['__main__.FlattenedVisionModel', 'xx.training.path.supercombo.Policy', 'xx.training.path.supercombo.PointSummarizer', '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 = (%layer_norm, %p_vision_model_point_policy_summarizer_mlp1_c_fc_weight), kwargs = {})J pkg.torch.onnx.name_scopes['', 'vision_model.point_policy', 'vision_model.point_policy.summarizer', 'vision_model.point_policy.summarizer.mlp1', 'vision_model.point_policy.summarizer.mlp1.c_fc', 'linear_1']J -pkg.torch.onnx.stack_traceFile "/home/batman/xx2/./ml_tools/openpilot_compile/compile_supercombo.py", line 82, in forward +pkg.torch.onnx.stack_traceFile "/home/batman/xx3/./ml_tools/openpilot_compile/compile_supercombo.py", line 86, in forward return torch.cat([*self.forward_dict(inputs).values(), self.pad], dim=1) - File "/home/batman/xx2/xx/training/path/supercombo.py", line 125, in forward + File "/home/batman/xx3/xx/training/path/supercombo.py", line 125, in forward summary_outs = self.summarizer(vision_features) - File "/home/batman/xx2/xx/training/path/supercombo.py", line 32, in forward + File "/home/batman/xx3/xx/training/path/supercombo.py", line 32, in forward x = self.mlp1(x) + x - File "/home/batman/xx2/.venv/lib/python3.12/site-packages/torch/nn/modules/container.py", line 253, in forward + File "/home/batman/xx3/.venv/lib/python3.12/site-packages/torch/nn/modules/container.py", line 253, in forward input = module(input) - File "/home/batman/xx2/.venv/lib/python3.12/site-packages/torch/nn/modules/linear.py", line 134, in forward + File "/home/batman/xx3/.venv/lib/python3.12/site-packages/torch/nn/modules/linear.py", line 134, in forward return F.linear(input, self.weight, self.bias)  linear_1gelu_19 node_gelu_19"Gelu* @@ -2953,15 +2953,15 @@ layer_norm pkg.torch.onnx.class_hierarchy['__main__.FlattenedVisionModel', 'xx.training.path.supercombo.Policy', 'xx.training.path.supercombo.PointSummarizer', 'torch.nn.modules.container.Sequential', 'torch.nn.modules.activation.GELU', 'aten.gelu.default']J pkg.torch.onnx.fx_node%gelu_19 : [num_users=1] = call_function[target=torch.ops.aten.gelu.default](args = (%linear_1,), kwargs = {approximate: tanh})J pkg.torch.onnx.name_scopes['', 'vision_model.point_policy', 'vision_model.point_policy.summarizer', 'vision_model.point_policy.summarizer.mlp1', 'vision_model.point_policy.summarizer.mlp1.act', 'gelu_19']J -pkg.torch.onnx.stack_traceFile "/home/batman/xx2/./ml_tools/openpilot_compile/compile_supercombo.py", line 82, in forward +pkg.torch.onnx.stack_traceFile "/home/batman/xx3/./ml_tools/openpilot_compile/compile_supercombo.py", line 86, in forward return torch.cat([*self.forward_dict(inputs).values(), self.pad], dim=1) - File "/home/batman/xx2/xx/training/path/supercombo.py", line 125, in forward + File "/home/batman/xx3/xx/training/path/supercombo.py", line 125, in forward summary_outs = self.summarizer(vision_features) - File "/home/batman/xx2/xx/training/path/supercombo.py", line 32, in forward + File "/home/batman/xx3/xx/training/path/supercombo.py", line 32, in forward x = self.mlp1(x) + x - File "/home/batman/xx2/.venv/lib/python3.12/site-packages/torch/nn/modules/container.py", line 253, in forward + File "/home/batman/xx3/.venv/lib/python3.12/site-packages/torch/nn/modules/container.py", line 253, in forward input = module(input) - File "/home/batman/xx2/.venv/lib/python3.12/site-packages/torch/nn/modules/activation.py", line 816, in forward + File "/home/batman/xx3/.venv/lib/python3.12/site-packages/torch/nn/modules/activation.py", line 816, in forward return F.gelu(input, approximate=self.approximate)  gelu_19 @@ -2974,15 +2974,15 @@ layer_norm pkg.torch.onnx.class_hierarchy['__main__.FlattenedVisionModel', 'xx.training.path.supercombo.Policy', 'xx.training.path.supercombo.PointSummarizer', '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 = (%gelu_19, %p_vision_model_point_policy_summarizer_mlp1_c_proj_weight), kwargs = {})J pkg.torch.onnx.name_scopes['', 'vision_model.point_policy', 'vision_model.point_policy.summarizer', 'vision_model.point_policy.summarizer.mlp1', 'vision_model.point_policy.summarizer.mlp1.c_proj', 'linear_2']J -pkg.torch.onnx.stack_traceFile "/home/batman/xx2/./ml_tools/openpilot_compile/compile_supercombo.py", line 82, in forward +pkg.torch.onnx.stack_traceFile "/home/batman/xx3/./ml_tools/openpilot_compile/compile_supercombo.py", line 86, in forward return torch.cat([*self.forward_dict(inputs).values(), self.pad], dim=1) - File "/home/batman/xx2/xx/training/path/supercombo.py", line 125, in forward + File "/home/batman/xx3/xx/training/path/supercombo.py", line 125, in forward summary_outs = self.summarizer(vision_features) - File "/home/batman/xx2/xx/training/path/supercombo.py", line 32, in forward + File "/home/batman/xx3/xx/training/path/supercombo.py", line 32, in forward x = self.mlp1(x) + x - File "/home/batman/xx2/.venv/lib/python3.12/site-packages/torch/nn/modules/container.py", line 253, in forward + File "/home/batman/xx3/.venv/lib/python3.12/site-packages/torch/nn/modules/container.py", line 253, in forward input = module(input) - File "/home/batman/xx2/.venv/lib/python3.12/site-packages/torch/nn/modules/linear.py", line 134, in forward + File "/home/batman/xx3/.venv/lib/python3.12/site-packages/torch/nn/modules/linear.py", line 134, in forward return F.linear(input, self.weight, self.bias)  linear_2 @@ -2991,11 +2991,11 @@ layer_norm pkg.torch.onnx.class_hierarchy['__main__.FlattenedVisionModel', 'xx.training.path.supercombo.Policy', 'xx.training.path.supercombo.PointSummarizer', 'aten.add.Tensor']J pkg.torch.onnx.fx_nodes%add_12 : [num_users=2] = call_function[target=torch.ops.aten.add.Tensor](args = (%clone_25, %linear), kwargs = {})Jq pkg.torch.onnx.name_scopesS['', 'vision_model.point_policy', 'vision_model.point_policy.summarizer', 'add_12']J -pkg.torch.onnx.stack_traceFile "/home/batman/xx2/./ml_tools/openpilot_compile/compile_supercombo.py", line 82, in forward +pkg.torch.onnx.stack_traceFile "/home/batman/xx3/./ml_tools/openpilot_compile/compile_supercombo.py", line 86, in forward return torch.cat([*self.forward_dict(inputs).values(), self.pad], dim=1) - File "/home/batman/xx2/xx/training/path/supercombo.py", line 125, in forward + File "/home/batman/xx3/xx/training/path/supercombo.py", line 125, in forward summary_outs = self.summarizer(vision_features) - File "/home/batman/xx2/xx/training/path/supercombo.py", line 32, in forward + File "/home/batman/xx3/xx/training/path/supercombo.py", line 32, in forward x = self.mlp1(x) + x  add_12 @@ -3009,15 +3009,15 @@ stash_type pkg.torch.onnx.class_hierarchy['__main__.FlattenedVisionModel', 'xx.training.path.supercombo.Policy', 'xx.training.path.supercombo.PointSummarizer', '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 = (%add_12, [512], %p_vision_model_point_policy_summarizer_mlp2_layer_norm_weight, %p_vision_model_point_policy_summarizer_mlp2_layer_norm_bias, 1e-05, False), kwargs = {})J pkg.torch.onnx.name_scopes['', 'vision_model.point_policy', 'vision_model.point_policy.summarizer', 'vision_model.point_policy.summarizer.mlp2', 'vision_model.point_policy.summarizer.mlp2.layer_norm', 'layer_norm_1']J -pkg.torch.onnx.stack_traceFile "/home/batman/xx2/./ml_tools/openpilot_compile/compile_supercombo.py", line 82, in forward +pkg.torch.onnx.stack_traceFile "/home/batman/xx3/./ml_tools/openpilot_compile/compile_supercombo.py", line 86, in forward return torch.cat([*self.forward_dict(inputs).values(), self.pad], dim=1) - File "/home/batman/xx2/xx/training/path/supercombo.py", line 125, in forward + File "/home/batman/xx3/xx/training/path/supercombo.py", line 125, in forward summary_outs = self.summarizer(vision_features) - File "/home/batman/xx2/xx/training/path/supercombo.py", line 33, in forward + File "/home/batman/xx3/xx/training/path/supercombo.py", line 33, in forward x = self.mlp2(x) + x - File "/home/batman/xx2/.venv/lib/python3.12/site-packages/torch/nn/modules/container.py", line 253, in forward + File "/home/batman/xx3/.venv/lib/python3.12/site-packages/torch/nn/modules/container.py", line 253, in forward input = module(input) - File "/home/batman/xx2/.venv/lib/python3.12/site-packages/torch/nn/modules/normalization.py", line 229, in forward + File "/home/batman/xx3/.venv/lib/python3.12/site-packages/torch/nn/modules/normalization.py", line 229, in forward return F.layer_norm(  layer_norm_1 @@ -3030,15 +3030,15 @@ stash_type pkg.torch.onnx.class_hierarchy['__main__.FlattenedVisionModel', 'xx.training.path.supercombo.Policy', 'xx.training.path.supercombo.PointSummarizer', '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 = (%layer_norm_1, %p_vision_model_point_policy_summarizer_mlp2_c_fc_weight), kwargs = {})J pkg.torch.onnx.name_scopes['', 'vision_model.point_policy', 'vision_model.point_policy.summarizer', 'vision_model.point_policy.summarizer.mlp2', 'vision_model.point_policy.summarizer.mlp2.c_fc', 'linear_3']J -pkg.torch.onnx.stack_traceFile "/home/batman/xx2/./ml_tools/openpilot_compile/compile_supercombo.py", line 82, in forward +pkg.torch.onnx.stack_traceFile "/home/batman/xx3/./ml_tools/openpilot_compile/compile_supercombo.py", line 86, in forward return torch.cat([*self.forward_dict(inputs).values(), self.pad], dim=1) - File "/home/batman/xx2/xx/training/path/supercombo.py", line 125, in forward + File "/home/batman/xx3/xx/training/path/supercombo.py", line 125, in forward summary_outs = self.summarizer(vision_features) - File "/home/batman/xx2/xx/training/path/supercombo.py", line 33, in forward + File "/home/batman/xx3/xx/training/path/supercombo.py", line 33, in forward x = self.mlp2(x) + x - File "/home/batman/xx2/.venv/lib/python3.12/site-packages/torch/nn/modules/container.py", line 253, in forward + File "/home/batman/xx3/.venv/lib/python3.12/site-packages/torch/nn/modules/container.py", line 253, in forward input = module(input) - File "/home/batman/xx2/.venv/lib/python3.12/site-packages/torch/nn/modules/linear.py", line 134, in forward + File "/home/batman/xx3/.venv/lib/python3.12/site-packages/torch/nn/modules/linear.py", line 134, in forward return F.linear(input, self.weight, self.bias)  linear_3gelu_20 node_gelu_20"Gelu* @@ -3047,15 +3047,15 @@ stash_type pkg.torch.onnx.class_hierarchy['__main__.FlattenedVisionModel', 'xx.training.path.supercombo.Policy', 'xx.training.path.supercombo.PointSummarizer', 'torch.nn.modules.container.Sequential', 'torch.nn.modules.activation.GELU', 'aten.gelu.default']J pkg.torch.onnx.fx_node%gelu_20 : [num_users=1] = call_function[target=torch.ops.aten.gelu.default](args = (%linear_3,), kwargs = {approximate: tanh})J pkg.torch.onnx.name_scopes['', 'vision_model.point_policy', 'vision_model.point_policy.summarizer', 'vision_model.point_policy.summarizer.mlp2', 'vision_model.point_policy.summarizer.mlp2.act', 'gelu_20']J -pkg.torch.onnx.stack_traceFile "/home/batman/xx2/./ml_tools/openpilot_compile/compile_supercombo.py", line 82, in forward +pkg.torch.onnx.stack_traceFile "/home/batman/xx3/./ml_tools/openpilot_compile/compile_supercombo.py", line 86, in forward return torch.cat([*self.forward_dict(inputs).values(), self.pad], dim=1) - File "/home/batman/xx2/xx/training/path/supercombo.py", line 125, in forward + File "/home/batman/xx3/xx/training/path/supercombo.py", line 125, in forward summary_outs = self.summarizer(vision_features) - File "/home/batman/xx2/xx/training/path/supercombo.py", line 33, in forward + File "/home/batman/xx3/xx/training/path/supercombo.py", line 33, in forward x = self.mlp2(x) + x - File "/home/batman/xx2/.venv/lib/python3.12/site-packages/torch/nn/modules/container.py", line 253, in forward + File "/home/batman/xx3/.venv/lib/python3.12/site-packages/torch/nn/modules/container.py", line 253, in forward input = module(input) - File "/home/batman/xx2/.venv/lib/python3.12/site-packages/torch/nn/modules/activation.py", line 816, in forward + File "/home/batman/xx3/.venv/lib/python3.12/site-packages/torch/nn/modules/activation.py", line 816, in forward return F.gelu(input, approximate=self.approximate)  gelu_20 @@ -3068,15 +3068,15 @@ stash_type pkg.torch.onnx.class_hierarchy['__main__.FlattenedVisionModel', 'xx.training.path.supercombo.Policy', 'xx.training.path.supercombo.PointSummarizer', '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 = (%gelu_20, %p_vision_model_point_policy_summarizer_mlp2_c_proj_weight), kwargs = {})J pkg.torch.onnx.name_scopes['', 'vision_model.point_policy', 'vision_model.point_policy.summarizer', 'vision_model.point_policy.summarizer.mlp2', 'vision_model.point_policy.summarizer.mlp2.c_proj', 'linear_4']J -pkg.torch.onnx.stack_traceFile "/home/batman/xx2/./ml_tools/openpilot_compile/compile_supercombo.py", line 82, in forward +pkg.torch.onnx.stack_traceFile "/home/batman/xx3/./ml_tools/openpilot_compile/compile_supercombo.py", line 86, in forward return torch.cat([*self.forward_dict(inputs).values(), self.pad], dim=1) - File "/home/batman/xx2/xx/training/path/supercombo.py", line 125, in forward + File "/home/batman/xx3/xx/training/path/supercombo.py", line 125, in forward summary_outs = self.summarizer(vision_features) - File "/home/batman/xx2/xx/training/path/supercombo.py", line 33, in forward + File "/home/batman/xx3/xx/training/path/supercombo.py", line 33, in forward x = self.mlp2(x) + x - File "/home/batman/xx2/.venv/lib/python3.12/site-packages/torch/nn/modules/container.py", line 253, in forward + File "/home/batman/xx3/.venv/lib/python3.12/site-packages/torch/nn/modules/container.py", line 253, in forward input = module(input) - File "/home/batman/xx2/.venv/lib/python3.12/site-packages/torch/nn/modules/linear.py", line 134, in forward + File "/home/batman/xx3/.venv/lib/python3.12/site-packages/torch/nn/modules/linear.py", line 134, in forward return F.linear(input, self.weight, self.bias)  linear_4 @@ -3085,11 +3085,11 @@ stash_type pkg.torch.onnx.class_hierarchy['__main__.FlattenedVisionModel', 'xx.training.path.supercombo.Policy', 'xx.training.path.supercombo.PointSummarizer', 'aten.add.Tensor']J pkg.torch.onnx.fx_nodes%add_13 : [num_users=9] = call_function[target=torch.ops.aten.add.Tensor](args = (%clone_26, %add_12), kwargs = {})Jq pkg.torch.onnx.name_scopesS['', 'vision_model.point_policy', 'vision_model.point_policy.summarizer', 'add_13']J -pkg.torch.onnx.stack_traceFile "/home/batman/xx2/./ml_tools/openpilot_compile/compile_supercombo.py", line 82, in forward +pkg.torch.onnx.stack_traceFile "/home/batman/xx3/./ml_tools/openpilot_compile/compile_supercombo.py", line 86, in forward return torch.cat([*self.forward_dict(inputs).values(), self.pad], dim=1) - File "/home/batman/xx2/xx/training/path/supercombo.py", line 125, in forward + File "/home/batman/xx3/xx/training/path/supercombo.py", line 125, in forward summary_outs = self.summarizer(vision_features) - File "/home/batman/xx2/xx/training/path/supercombo.py", line 33, in forward + File "/home/batman/xx3/xx/training/path/supercombo.py", line 33, in forward x = self.mlp2(x) + x  add_13 @@ -3103,15 +3103,15 @@ stash_type 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.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 = (%add_13, [512], %p_vision_model_point_policy_hydra_head_mlp_pose_layer_norm_weight, %p_vision_model_point_policy_hydra_head_mlp_pose_layer_norm_bias, 1e-05, False), kwargs = {})J pkg.torch.onnx.name_scopes['', 'vision_model.point_policy', 'vision_model.point_policy.hydra', 'vision_model.point_policy.hydra.head_mlp.pose', 'vision_model.point_policy.hydra.head_mlp.pose.layer_norm', 'layer_norm_2']J -pkg.torch.onnx.stack_traceFile "/home/batman/xx2/./ml_tools/openpilot_compile/compile_supercombo.py", line 82, in forward +pkg.torch.onnx.stack_traceFile "/home/batman/xx3/./ml_tools/openpilot_compile/compile_supercombo.py", line 86, in forward return torch.cat([*self.forward_dict(inputs).values(), self.pad], dim=1) - File "/home/batman/xx2/xx/training/path/supercombo.py", line 126, in forward + File "/home/batman/xx3/xx/training/path/supercombo.py", line 126, in forward policy_outs = self.hydra(summary_outs) - File "/home/batman/xx2/xx/training/path/supercombo.py", line 105, in forward + File "/home/batman/xx3/xx/training/path/supercombo.py", line 105, in forward k: self.head_mlp[k](in_feats) + in_feats if k in self.head_mlp else in_feats - File "/home/batman/xx2/.venv/lib/python3.12/site-packages/torch/nn/modules/container.py", line 253, in forward + File "/home/batman/xx3/.venv/lib/python3.12/site-packages/torch/nn/modules/container.py", line 253, in forward input = module(input) - File "/home/batman/xx2/.venv/lib/python3.12/site-packages/torch/nn/modules/normalization.py", line 229, in forward + File "/home/batman/xx3/.venv/lib/python3.12/site-packages/torch/nn/modules/normalization.py", line 229, in forward return F.layer_norm(  layer_norm_2 @@ -3124,15 +3124,15 @@ stash_type 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_5 : [num_users=1] = call_function[target=torch.ops.aten.linear.default](args = (%layer_norm_2, %p_vision_model_point_policy_hydra_head_mlp_pose_c_fc_weight), kwargs = {})J pkg.torch.onnx.name_scopes['', 'vision_model.point_policy', 'vision_model.point_policy.hydra', 'vision_model.point_policy.hydra.head_mlp.pose', 'vision_model.point_policy.hydra.head_mlp.pose.c_fc', 'linear_5']J -pkg.torch.onnx.stack_traceFile "/home/batman/xx2/./ml_tools/openpilot_compile/compile_supercombo.py", line 82, in forward +pkg.torch.onnx.stack_traceFile "/home/batman/xx3/./ml_tools/openpilot_compile/compile_supercombo.py", line 86, in forward return torch.cat([*self.forward_dict(inputs).values(), self.pad], dim=1) - File "/home/batman/xx2/xx/training/path/supercombo.py", line 126, in forward + File "/home/batman/xx3/xx/training/path/supercombo.py", line 126, in forward policy_outs = self.hydra(summary_outs) - File "/home/batman/xx2/xx/training/path/supercombo.py", line 105, in forward + File "/home/batman/xx3/xx/training/path/supercombo.py", line 105, in forward k: self.head_mlp[k](in_feats) + in_feats if k in self.head_mlp else in_feats - File "/home/batman/xx2/.venv/lib/python3.12/site-packages/torch/nn/modules/container.py", line 253, in forward + File "/home/batman/xx3/.venv/lib/python3.12/site-packages/torch/nn/modules/container.py", line 253, in forward input = module(input) - File "/home/batman/xx2/.venv/lib/python3.12/site-packages/torch/nn/modules/linear.py", line 134, in forward + File "/home/batman/xx3/.venv/lib/python3.12/site-packages/torch/nn/modules/linear.py", line 134, in forward return F.linear(input, self.weight, self.bias)  linear_5gelu_21 node_gelu_21"Gelu* @@ -3141,15 +3141,15 @@ stash_type 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.GELU', 'aten.gelu.default']J pkg.torch.onnx.fx_node%gelu_21 : [num_users=1] = call_function[target=torch.ops.aten.gelu.default](args = (%linear_5,), kwargs = {approximate: tanh})J pkg.torch.onnx.name_scopes['', 'vision_model.point_policy', 'vision_model.point_policy.hydra', 'vision_model.point_policy.hydra.head_mlp.pose', 'vision_model.point_policy.hydra.head_mlp.pose.act', 'gelu_21']J -pkg.torch.onnx.stack_traceFile "/home/batman/xx2/./ml_tools/openpilot_compile/compile_supercombo.py", line 82, in forward +pkg.torch.onnx.stack_traceFile "/home/batman/xx3/./ml_tools/openpilot_compile/compile_supercombo.py", line 86, in forward return torch.cat([*self.forward_dict(inputs).values(), self.pad], dim=1) - File "/home/batman/xx2/xx/training/path/supercombo.py", line 126, in forward + File "/home/batman/xx3/xx/training/path/supercombo.py", line 126, in forward policy_outs = self.hydra(summary_outs) - File "/home/batman/xx2/xx/training/path/supercombo.py", line 105, in forward + File "/home/batman/xx3/xx/training/path/supercombo.py", line 105, in forward k: self.head_mlp[k](in_feats) + in_feats if k in self.head_mlp else in_feats - File "/home/batman/xx2/.venv/lib/python3.12/site-packages/torch/nn/modules/container.py", line 253, in forward + File "/home/batman/xx3/.venv/lib/python3.12/site-packages/torch/nn/modules/container.py", line 253, in forward input = module(input) - File "/home/batman/xx2/.venv/lib/python3.12/site-packages/torch/nn/modules/activation.py", line 816, in forward + File "/home/batman/xx3/.venv/lib/python3.12/site-packages/torch/nn/modules/activation.py", line 816, in forward return F.gelu(input, approximate=self.approximate)  gelu_21 @@ -3162,15 +3162,15 @@ stash_type 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_6 : [num_users=1] = call_function[target=torch.ops.aten.linear.default](args = (%gelu_21, %p_vision_model_point_policy_hydra_head_mlp_pose_c_proj_weight), kwargs = {})J pkg.torch.onnx.name_scopes['', 'vision_model.point_policy', 'vision_model.point_policy.hydra', 'vision_model.point_policy.hydra.head_mlp.pose', 'vision_model.point_policy.hydra.head_mlp.pose.c_proj', 'linear_6']J -pkg.torch.onnx.stack_traceFile "/home/batman/xx2/./ml_tools/openpilot_compile/compile_supercombo.py", line 82, in forward +pkg.torch.onnx.stack_traceFile "/home/batman/xx3/./ml_tools/openpilot_compile/compile_supercombo.py", line 86, in forward return torch.cat([*self.forward_dict(inputs).values(), self.pad], dim=1) - File "/home/batman/xx2/xx/training/path/supercombo.py", line 126, in forward + File "/home/batman/xx3/xx/training/path/supercombo.py", line 126, in forward policy_outs = self.hydra(summary_outs) - File "/home/batman/xx2/xx/training/path/supercombo.py", line 105, in forward + File "/home/batman/xx3/xx/training/path/supercombo.py", line 105, in forward k: self.head_mlp[k](in_feats) + in_feats if k in self.head_mlp else in_feats - File "/home/batman/xx2/.venv/lib/python3.12/site-packages/torch/nn/modules/container.py", line 253, in forward + File "/home/batman/xx3/.venv/lib/python3.12/site-packages/torch/nn/modules/container.py", line 253, in forward input = module(input) - File "/home/batman/xx2/.venv/lib/python3.12/site-packages/torch/nn/modules/linear.py", line 134, in forward + File "/home/batman/xx3/.venv/lib/python3.12/site-packages/torch/nn/modules/linear.py", line 134, in forward return F.linear(input, self.weight, self.bias)  linear_6 @@ -3179,11 +3179,11 @@ stash_type 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_nodes%add_14 : [num_users=1] = call_function[target=torch.ops.aten.add.Tensor](args = (%clone_27, %add_13), kwargs = {})Jl pkg.torch.onnx.name_scopesN['', 'vision_model.point_policy', 'vision_model.point_policy.hydra', 'add_14']J -pkg.torch.onnx.stack_traceFile "/home/batman/xx2/./ml_tools/openpilot_compile/compile_supercombo.py", line 82, in forward +pkg.torch.onnx.stack_traceFile "/home/batman/xx3/./ml_tools/openpilot_compile/compile_supercombo.py", line 86, in forward return torch.cat([*self.forward_dict(inputs).values(), self.pad], dim=1) - File "/home/batman/xx2/xx/training/path/supercombo.py", line 126, in forward + File "/home/batman/xx3/xx/training/path/supercombo.py", line 126, in forward policy_outs = self.hydra(summary_outs) - File "/home/batman/xx2/xx/training/path/supercombo.py", line 105, in forward + File "/home/batman/xx3/xx/training/path/supercombo.py", line 105, in forward k: self.head_mlp[k](in_feats) + in_feats if k in self.head_mlp else in_feats  add_13 @@ -3197,13 +3197,13 @@ 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_7 : [num_users=1] = call_function[target=torch.ops.aten.linear.default](args = (%add_13, %p_vision_model_point_policy_hydra_final_layer_lane_lines_weight, %p_vision_model_point_policy_hydra_final_layer_lane_lines_bias), kwargs = {})J pkg.torch.onnx.name_scopes['', 'vision_model.point_policy', 'vision_model.point_policy.hydra', 'vision_model.point_policy.hydra.final_layer.lane_lines', 'linear_7']J -pkg.torch.onnx.stack_traceFile "/home/batman/xx2/./ml_tools/openpilot_compile/compile_supercombo.py", line 82, in forward +pkg.torch.onnx.stack_traceFile "/home/batman/xx3/./ml_tools/openpilot_compile/compile_supercombo.py", line 86, in forward return torch.cat([*self.forward_dict(inputs).values(), self.pad], dim=1) - File "/home/batman/xx2/xx/training/path/supercombo.py", line 126, in forward + File "/home/batman/xx3/xx/training/path/supercombo.py", line 126, in forward policy_outs = self.hydra(summary_outs) - File "/home/batman/xx2/xx/training/path/supercombo.py", line 108, in forward + File "/home/batman/xx3/xx/training/path/supercombo.py", line 108, in forward ret = {k: v(head_feats[k]) for k,v in self.final_layer.items()} - File "/home/batman/xx2/.venv/lib/python3.12/site-packages/torch/nn/modules/linear.py", line 134, in forward + File "/home/batman/xx3/.venv/lib/python3.12/site-packages/torch/nn/modules/linear.py", line 134, in forward return F.linear(input, self.weight, self.bias)  add_13 @@ -3217,13 +3217,13 @@ Bvision_model.point_policy.hydra.final_layer.lane_lines_prob.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_8 : [num_users=1] = call_function[target=torch.ops.aten.linear.default](args = (%add_13, %p_vision_model_point_policy_hydra_final_layer_lane_lines_prob_weight, %p_vision_model_point_policy_hydra_final_layer_lane_lines_prob_bias), kwargs = {})J pkg.torch.onnx.name_scopes['', 'vision_model.point_policy', 'vision_model.point_policy.hydra', 'vision_model.point_policy.hydra.final_layer.lane_lines_prob', 'linear_8']J -pkg.torch.onnx.stack_traceFile "/home/batman/xx2/./ml_tools/openpilot_compile/compile_supercombo.py", line 82, in forward +pkg.torch.onnx.stack_traceFile "/home/batman/xx3/./ml_tools/openpilot_compile/compile_supercombo.py", line 86, in forward return torch.cat([*self.forward_dict(inputs).values(), self.pad], dim=1) - File "/home/batman/xx2/xx/training/path/supercombo.py", line 126, in forward + File "/home/batman/xx3/xx/training/path/supercombo.py", line 126, in forward policy_outs = self.hydra(summary_outs) - File "/home/batman/xx2/xx/training/path/supercombo.py", line 108, in forward + File "/home/batman/xx3/xx/training/path/supercombo.py", line 108, in forward ret = {k: v(head_feats[k]) for k,v in self.final_layer.items()} - File "/home/batman/xx2/.venv/lib/python3.12/site-packages/torch/nn/modules/linear.py", line 134, in forward + File "/home/batman/xx3/.venv/lib/python3.12/site-packages/torch/nn/modules/linear.py", line 134, in forward return F.linear(input, self.weight, self.bias)  add_13 @@ -3237,13 +3237,13 @@ Bvision_model.point_policy.hydra.final_layer.lane_lines_prob.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_9 : [num_users=1] = call_function[target=torch.ops.aten.linear.default](args = (%add_13, %p_vision_model_point_policy_hydra_final_layer_road_edges_weight, %p_vision_model_point_policy_hydra_final_layer_road_edges_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_edges', 'linear_9']J -pkg.torch.onnx.stack_traceFile "/home/batman/xx2/./ml_tools/openpilot_compile/compile_supercombo.py", line 82, in forward +pkg.torch.onnx.stack_traceFile "/home/batman/xx3/./ml_tools/openpilot_compile/compile_supercombo.py", line 86, in forward return torch.cat([*self.forward_dict(inputs).values(), self.pad], dim=1) - File "/home/batman/xx2/xx/training/path/supercombo.py", line 126, in forward + File "/home/batman/xx3/xx/training/path/supercombo.py", line 126, in forward policy_outs = self.hydra(summary_outs) - File "/home/batman/xx2/xx/training/path/supercombo.py", line 108, in forward + File "/home/batman/xx3/xx/training/path/supercombo.py", line 108, in forward ret = {k: v(head_feats[k]) for k,v in self.final_layer.items()} - File "/home/batman/xx2/.venv/lib/python3.12/site-packages/torch/nn/modules/linear.py", line 134, in forward + File "/home/batman/xx3/.venv/lib/python3.12/site-packages/torch/nn/modules/linear.py", line 134, in forward return F.linear(input, self.weight, self.bias) add_13 @@ -3257,13 +3257,13 @@ Bvision_model.point_policy.hydra.final_layer.lane_lines_prob.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_10 : [num_users=1] = call_function[target=torch.ops.aten.linear.default](args = (%add_13, %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_10']J -pkg.torch.onnx.stack_traceFile "/home/batman/xx2/./ml_tools/openpilot_compile/compile_supercombo.py", line 82, in forward +pkg.torch.onnx.stack_traceFile "/home/batman/xx3/./ml_tools/openpilot_compile/compile_supercombo.py", line 86, in forward return torch.cat([*self.forward_dict(inputs).values(), self.pad], dim=1) - File "/home/batman/xx2/xx/training/path/supercombo.py", line 126, in forward + File "/home/batman/xx3/xx/training/path/supercombo.py", line 126, in forward policy_outs = self.hydra(summary_outs) - File "/home/batman/xx2/xx/training/path/supercombo.py", line 108, in forward + File "/home/batman/xx3/xx/training/path/supercombo.py", line 108, in forward ret = {k: v(head_feats[k]) for k,v in self.final_layer.items()} - File "/home/batman/xx2/.venv/lib/python3.12/site-packages/torch/nn/modules/linear.py", line 134, in forward + File "/home/batman/xx3/.venv/lib/python3.12/site-packages/torch/nn/modules/linear.py", line 134, in forward return F.linear(input, self.weight, self.bias)  add_13 @@ -3277,13 +3277,13 @@ Bvision_model.point_policy.hydra.final_layer.lane_lines_prob.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_11 : [num_users=1] = call_function[target=torch.ops.aten.linear.default](args = (%add_13, %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_11']J -pkg.torch.onnx.stack_traceFile "/home/batman/xx2/./ml_tools/openpilot_compile/compile_supercombo.py", line 82, in forward +pkg.torch.onnx.stack_traceFile "/home/batman/xx3/./ml_tools/openpilot_compile/compile_supercombo.py", line 86, in forward return torch.cat([*self.forward_dict(inputs).values(), self.pad], dim=1) - File "/home/batman/xx2/xx/training/path/supercombo.py", line 126, in forward + File "/home/batman/xx3/xx/training/path/supercombo.py", line 126, in forward policy_outs = self.hydra(summary_outs) - File "/home/batman/xx2/xx/training/path/supercombo.py", line 108, in forward + File "/home/batman/xx3/xx/training/path/supercombo.py", line 108, in forward ret = {k: v(head_feats[k]) for k,v in self.final_layer.items()} - File "/home/batman/xx2/.venv/lib/python3.12/site-packages/torch/nn/modules/linear.py", line 134, in forward + File "/home/batman/xx3/.venv/lib/python3.12/site-packages/torch/nn/modules/linear.py", line 134, in forward return F.linear(input, self.weight, self.bias)  add_13 @@ -3297,13 +3297,13 @@ 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_12 : [num_users=1] = call_function[target=torch.ops.aten.linear.default](args = (%add_13, %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_12']J -pkg.torch.onnx.stack_traceFile "/home/batman/xx2/./ml_tools/openpilot_compile/compile_supercombo.py", line 82, in forward +pkg.torch.onnx.stack_traceFile "/home/batman/xx3/./ml_tools/openpilot_compile/compile_supercombo.py", line 86, in forward return torch.cat([*self.forward_dict(inputs).values(), self.pad], dim=1) - File "/home/batman/xx2/xx/training/path/supercombo.py", line 126, in forward + File "/home/batman/xx3/xx/training/path/supercombo.py", line 126, in forward policy_outs = self.hydra(summary_outs) - File "/home/batman/xx2/xx/training/path/supercombo.py", line 108, in forward + File "/home/batman/xx3/xx/training/path/supercombo.py", line 108, in forward ret = {k: v(head_feats[k]) for k,v in self.final_layer.items()} - File "/home/batman/xx2/.venv/lib/python3.12/site-packages/torch/nn/modules/linear.py", line 134, in forward + File "/home/batman/xx3/.venv/lib/python3.12/site-packages/torch/nn/modules/linear.py", line 134, in forward return F.linear(input, self.weight, self.bias)  add_13 @@ -3317,13 +3317,13 @@ 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_13 : [num_users=1] = call_function[target=torch.ops.aten.linear.default](args = (%add_13, %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_13']J -pkg.torch.onnx.stack_traceFile "/home/batman/xx2/./ml_tools/openpilot_compile/compile_supercombo.py", line 82, in forward +pkg.torch.onnx.stack_traceFile "/home/batman/xx3/./ml_tools/openpilot_compile/compile_supercombo.py", line 86, in forward return torch.cat([*self.forward_dict(inputs).values(), self.pad], dim=1) - File "/home/batman/xx2/xx/training/path/supercombo.py", line 126, in forward + File "/home/batman/xx3/xx/training/path/supercombo.py", line 126, in forward policy_outs = self.hydra(summary_outs) - File "/home/batman/xx2/xx/training/path/supercombo.py", line 108, in forward + File "/home/batman/xx3/xx/training/path/supercombo.py", line 108, in forward ret = {k: v(head_feats[k]) for k,v in self.final_layer.items()} - File "/home/batman/xx2/.venv/lib/python3.12/site-packages/torch/nn/modules/linear.py", line 134, in forward + File "/home/batman/xx3/.venv/lib/python3.12/site-packages/torch/nn/modules/linear.py", line 134, in forward return F.linear(input, self.weight, self.bias) add_14 @@ -3337,13 +3337,13 @@ 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_14 : [num_users=1] = call_function[target=torch.ops.aten.linear.default](args = (%add_14, %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_14']J -pkg.torch.onnx.stack_traceFile "/home/batman/xx2/./ml_tools/openpilot_compile/compile_supercombo.py", line 82, in forward +pkg.torch.onnx.stack_traceFile "/home/batman/xx3/./ml_tools/openpilot_compile/compile_supercombo.py", line 86, in forward return torch.cat([*self.forward_dict(inputs).values(), self.pad], dim=1) - File "/home/batman/xx2/xx/training/path/supercombo.py", line 126, in forward + File "/home/batman/xx3/xx/training/path/supercombo.py", line 126, in forward policy_outs = self.hydra(summary_outs) - File "/home/batman/xx2/xx/training/path/supercombo.py", line 108, in forward + File "/home/batman/xx3/xx/training/path/supercombo.py", line 108, in forward ret = {k: v(head_feats[k]) for k,v in self.final_layer.items()} - File "/home/batman/xx2/.venv/lib/python3.12/site-packages/torch/nn/modules/linear.py", line 134, in forward + File "/home/batman/xx3/.venv/lib/python3.12/site-packages/torch/nn/modules/linear.py", line 134, in forward return F.linear(input, self.weight, self.bias) linear_14 @@ -3352,13 +3352,13 @@ 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', 'xx.training.lib.layers.ScaleLayer', 'aten.mul.Tensor']J pkg.torch.onnx.fx_node%mul_13 : [num_users=1] = call_function[target=torch.ops.aten.mul.Tensor](args = (%linear_14, %p_vision_model_point_policy_hydra_scale_layer_pose_scale), kwargs = {})J pkg.torch.onnx.name_scopes['', 'vision_model.point_policy', 'vision_model.point_policy.hydra', 'vision_model.point_policy.hydra.scale_layer.pose', 'mul_13']J -pkg.torch.onnx.stack_traceFile "/home/batman/xx2/./ml_tools/openpilot_compile/compile_supercombo.py", line 82, in forward +pkg.torch.onnx.stack_traceFile "/home/batman/xx3/./ml_tools/openpilot_compile/compile_supercombo.py", line 86, in forward return torch.cat([*self.forward_dict(inputs).values(), self.pad], dim=1) - File "/home/batman/xx2/xx/training/path/supercombo.py", line 126, in forward + File "/home/batman/xx3/xx/training/path/supercombo.py", line 126, in forward policy_outs = self.hydra(summary_outs) - File "/home/batman/xx2/xx/training/path/supercombo.py", line 110, in forward + File "/home/batman/xx3/xx/training/path/supercombo.py", line 110, in forward ret[k] = self.scale_layer[k](ret[k]) - File "/home/batman/xx2/xx/training/lib/layers.py", line 36, in forward + File "/home/batman/xx3/xx/training/lib/layers.py", line 36, in forward return x * self.scale  linear_7 @@ -3377,7 +3377,7 @@ 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_7, %linear_8, %linear_9, %linear_10, %linear_11, %mul_13, %linear_13, %linear_12, %detach, %p_pad], 1), kwargs = {})J+ pkg.torch.onnx.name_scopes ['', 'cat_1']J -pkg.torch.onnx.stack_traceFile "/home/batman/xx2/./ml_tools/openpilot_compile/compile_supercombo.py", line 82, in forward +pkg.torch.onnx.stack_traceFile "/home/batman/xx3/./ml_tools/openpilot_compile/compile_supercombo.py", line 86, in forward return torch.cat([*self.forward_dict(inputs).values(), self.pad], dim=1) main_graph* BpadJ*@