AutocastCUDA: registered at C:\actions-runner\_work\vision\vision\pytorch\vision\torchvision\csrc\ops\autocast\nms_kernel.cpp:27 [kernel] FuncTorchBatched: #40
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python app.py
Fetching 37 files: 100%|█████████████████████████████████████████████████████████████| 37/37 [00:00<00:00, 1739.34it/s]
G:\Leffa\leffa_utils\SCHP_init_.py:152: FutureWarning: You are using
torch.loadwithweights_only=False(the current default value), which uses the default pickle module implicitly. It is possible to construct malicious pickle data which will execute arbitrary code during unpickling (See https://github.com/pytorch/pytorch/blob/main/SECURITY.md#untrusted-models for more details). In a future release, the default value forweights_onlywill be flipped toTrue. This limits the functions that could be executed during unpickling. Arbitrary objects will no longer be allowed to be loaded via this mode unless they are explicitly allowlisted by the user viatorch.serialization.add_safe_globals. We recommend you start settingweights_only=Truefor any use case where you don't have full control of the loaded file. Please open an issue on GitHub for any issues related to this experimental feature.state_dict = torch.load(ckpt_path, map_location="cpu")["state_dict"]
G:\Leffa\preprocess\openpose\annotator\openpose\body.py:25: FutureWarning: You are using
torch.loadwithweights_only=False(the current default value), which uses the default pickle module implicitly. It is possible to construct malicious pickle data which will execute arbitrary code during unpickling (See https://github.com/pytorch/pytorch/blob/main/SECURITY.md#untrusted-models for more details). In a future release, the default value forweights_onlywill be flipped toTrue. This limits the functions that could be executed during unpickling. Arbitrary objects will no longer be allowed to be loaded via this mode unless they are explicitly allowlisted by the user viatorch.serialization.add_safe_globals. We recommend you start settingweights_only=Truefor any use case where you don't have full control of the loaded file. Please open an issue on GitHub for any issues related to this experimental feature.model_dict = util.transfer(self.model, torch.load(model_path))
G:\Leffa\leffa\model.py:124: FutureWarning: You are using
torch.loadwithweights_only=False(the current default value), which uses the default pickle module implicitly. It is possible to construct malicious pickle data which will execute arbitrary code during unpickling (See https://github.com/pytorch/pytorch/blob/main/SECURITY.md#untrusted-models for more details). In a future release, the default value forweights_onlywill be flipped toTrue. This limits the functions that could be executed during unpickling. Arbitrary objects will no longer be allowed to be loaded via this mode unless they are explicitly allowlisted by the user viatorch.serialization.add_safe_globals. We recommend you start settingweights_only=Truefor any use case where you don't have full control of the loaded file. Please open an issue on GitHub for any issues related to this experimental feature.self.load_state_dict(torch.load(
The config attributes {'decay': 0.9999, 'inv_gamma': 1.0, 'min_decay': 0.0, 'optimization_step': 37000, 'power': 0.6666666666666666, 'update_after_step': 0, 'use_ema_warmup': False} were passed to UNet2DConditionModel, but are not expected and will be ignored. Please verify your config.json configuration file.
The config attributes {'decay': 0.9999, 'inv_gamma': 1.0, 'min_decay': 0.0, 'optimization_step': 37000, 'power': 0.6666666666666666, 'update_after_step': 0, 'use_ema_warmup': False} were passed to UNet2DConditionModel, but are not expected and will be ignored. Please verify your config.json configuration file.
This share link expires in 72 hours. For free permanent hosting and GPU upgrades, run
gradio deployfrom the terminal in the working directory to deploy to Hugging Face Spaces (https://huggingface.co/spaces)100%|████████████████████████████████████████████████████████████████████████████████████| 1/1 [00:00<00:00, 1.87it/s]
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D:\ANACONDA\envs\Leffa\lib\site-packages\torch\functional.py:534: UserWarning: torch.meshgrid: in an upcoming release, it will be required to pass the indexing argument. (Triggered internally at C:\actions-runner_work\pytorch\pytorch\builder\windows\pytorch\aten\src\ATen\native\TensorShape.cpp:3596.)
return _VF.meshgrid(tensors, **kwargs) # type: ignore[attr-defined]
Traceback (most recent call last):
File "D:\ANACONDA\envs\Leffa\lib\site-packages\gradio\queueing.py", line 625, in process_events
response = await route_utils.call_process_api(
File "D:\ANACONDA\envs\Leffa\lib\site-packages\gradio\route_utils.py", line 322, in call_process_api
output = await app.get_blocks().process_api(
File "D:\ANACONDA\envs\Leffa\lib\site-packages\gradio\blocks.py", line 2042, in process_api
result = await self.call_function(
File "D:\ANACONDA\envs\Leffa\lib\site-packages\gradio\blocks.py", line 1589, in call_function
prediction = await anyio.to_thread.run_sync( # type: ignore
File "D:\ANACONDA\envs\Leffa\lib\site-packages\anyio\to_thread.py", line 56, in run_sync
return await get_async_backend().run_sync_in_worker_thread(
File "D:\ANACONDA\envs\Leffa\lib\site-packages\anyio_backends_asyncio.py", line 2461, in run_sync_in_worker_thread
return await future
File "D:\ANACONDA\envs\Leffa\lib\site-packages\anyio_backends_asyncio.py", line 962, in run
result = context.run(func, *args)
File "D:\ANACONDA\envs\Leffa\lib\site-packages\gradio\utils.py", line 883, in wrapper
response = f(*args, **kwargs)
File "G:\Leffa\app.py", line 151, in leffa_predict_vt
return self.leffa_predict(src_image_path, ref_image_path, "virtual_tryon", ref_acceleration, step, scale, seed, vt_model_type, vt_garment_type, vt_repaint)
File "G:\Leffa\app.py", line 104, in leffa_predict
src_image_seg_array = self.densepose_predictor.predict_seg(
File "G:\Leffa\leffa_utils\densepose_predictor.py", line 58, in predict_seg
outputs = self.predict(image)
File "G:\Leffa\leffa_utils\densepose_predictor.py", line 32, in predict
outputs = self.predictor(image)["instances"]
File "G:\Leffa\leffa_utils\detectron2\engine\defaults.py", line 319, in call
predictions = self.model([inputs])[0]
File "D:\ANACONDA\envs\Leffa\lib\site-packages\torch\nn\modules\module.py", line 1736, in _wrapped_call_impl
return self._call_impl(*args, **kwargs)
File "D:\ANACONDA\envs\Leffa\lib\site-packages\torch\nn\modules\module.py", line 1747, in _call_impl
return forward_call(*args, **kwargs)
File "G:\Leffa\leffa_utils\detectron2\modeling\meta_arch\rcnn.py", line 150, in forward
return self.inference(batched_inputs)
File "G:\Leffa\leffa_utils\detectron2\modeling\meta_arch\rcnn.py", line 208, in inference
proposals, _ = self.proposal_generator(images, features, None)
File "D:\ANACONDA\envs\Leffa\lib\site-packages\torch\nn\modules\module.py", line 1736, in _wrapped_call_impl
return self._call_impl(*args, **kwargs)
File "D:\ANACONDA\envs\Leffa\lib\site-packages\torch\nn\modules\module.py", line 1747, in _call_impl
return forward_call(*args, **kwargs)
File "G:\Leffa\leffa_utils\detectron2\modeling\proposal_generator\rpn.py", line 477, in forward
proposals = self.predict_proposals(
File "G:\Leffa\leffa_utils\detectron2\modeling\proposal_generator\rpn.py", line 503, in predict_proposals
return find_top_rpn_proposals(
File "G:\Leffa\leffa_utils\detectron2\modeling\proposal_generator\proposal_utils.py", line 121, in find_top_rpn_proposals
keep = batched_nms(boxes.tensor, scores_per_img, lvl, nms_thresh)
File "G:\Leffa\leffa_utils\detectron2\layers\nms.py", line 20, in batched_nms
return box_ops.batched_nms(boxes.float(), scores, idxs, iou_threshold)
File "D:\ANACONDA\envs\Leffa\lib\site-packages\torchvision\ops\boxes.py", line 75, in batched_nms
return _batched_nms_coordinate_trick(boxes, scores, idxs, iou_threshold)
File "D:\ANACONDA\envs\Leffa\lib\site-packages\torch\jit_trace.py", line 1444, in wrapper
return fn(*args, **kwargs)
File "D:\ANACONDA\envs\Leffa\lib\site-packages\torchvision\ops\boxes.py", line 94, in _batched_nms_coordinate_trick
keep = nms(boxes_for_nms, scores, iou_threshold)
File "D:\ANACONDA\envs\Leffa\lib\site-packages\torchvision\ops\boxes.py", line 41, in nms
return torch.ops.torchvision.nms(boxes, scores, iou_threshold)
File "D:\ANACONDA\envs\Leffa\lib\site-packages\torch_ops.py", line 1116, in call
return self._op(*args, **(kwargs or {}))
NotImplementedError: Could not run 'torchvision::nms' with arguments from the 'CUDA' backend. This could be because the operator doesn't exist for this backend, or was omitted during the selective/custom build process (if using custom build). If you are a Facebook employee using PyTorch on mobile, please visit https://fburl.com/ptmfixes for possible resolutions. 'torchvision::nms' is only available for these backends: [CPU, Meta, QuantizedCPU, BackendSelect, Python, FuncTorchDynamicLayerBackMode, Functionalize, Named, Conjugate, Negative, ZeroTensor, ADInplaceOrView, AutogradOther, AutogradCPU, AutogradCUDA, AutogradXLA, AutogradMPS, AutogradXPU, AutogradHPU, AutogradLazy, AutogradMeta, Tracer, AutocastCPU, AutocastXPU, AutocastMPS, AutocastCUDA, FuncTorchBatched, BatchedNestedTensor, FuncTorchVmapMode, Batched, VmapMode, FuncTorchGradWrapper, PythonTLSSnapshot, FuncTorchDynamicLayerFrontMode, PreDispatch, PythonDispatcher].
CPU: registered at C:\actions-runner_work\vision\vision\pytorch\vision\torchvision\csrc\ops\cpu\nms_kernel.cpp:112 [kernel]
Meta: registered at /dev/null:184 [kernel]
QuantizedCPU: registered at C:\actions-runner_work\vision\vision\pytorch\vision\torchvision\csrc\ops\quantized\cpu\qnms_kernel.cpp:124 [kernel]
BackendSelect: fallthrough registered at C:\actions-runner_work\pytorch\pytorch\builder\windows\pytorch\aten\src\ATen\core\BackendSelectFallbackKernel.cpp:3 [backend fallback]
Python: registered at C:\actions-runner_work\pytorch\pytorch\builder\windows\pytorch\aten\src\ATen\core\PythonFallbackKernel.cpp:153 [backend fallback]
FuncTorchDynamicLayerBackMode: registered at C:\actions-runner_work\pytorch\pytorch\builder\windows\pytorch\aten\src\ATen\functorch\DynamicLayer.cpp:497 [backend fallback]
Functionalize: registered at C:\actions-runner_work\pytorch\pytorch\builder\windows\pytorch\aten\src\ATen\FunctionalizeFallbackKernel.cpp:349 [backend fallback]
Named: registered at C:\actions-runner_work\pytorch\pytorch\builder\windows\pytorch\aten\src\ATen\core\NamedRegistrations.cpp:7 [backend fallback]
Conjugate: registered at C:\actions-runner_work\pytorch\pytorch\builder\windows\pytorch\aten\src\ATen\ConjugateFallback.cpp:17 [backend fallback]
Negative: registered at C:\actions-runner_work\pytorch\pytorch\builder\windows\pytorch\aten\src\ATen\native\NegateFallback.cpp:18 [backend fallback]
ZeroTensor: registered at C:\actions-runner_work\pytorch\pytorch\builder\windows\pytorch\aten\src\ATen\ZeroTensorFallback.cpp:86 [backend fallback]
ADInplaceOrView: fallthrough registered at C:\actions-runner_work\pytorch\pytorch\builder\windows\pytorch\aten\src\ATen\core\VariableFallbackKernel.cpp:96 [backend fallback]
AutogradOther: registered at C:\actions-runner_work\pytorch\pytorch\builder\windows\pytorch\aten\src\ATen\core\VariableFallbackKernel.cpp:63 [backend fallback]
AutogradCPU: registered at C:\actions-runner_work\pytorch\pytorch\builder\windows\pytorch\aten\src\ATen\core\VariableFallbackKernel.cpp:67 [backend fallback]
AutogradCUDA: registered at C:\actions-runner_work\pytorch\pytorch\builder\windows\pytorch\aten\src\ATen\core\VariableFallbackKernel.cpp:75 [backend fallback]
AutogradXLA: registered at C:\actions-runner_work\pytorch\pytorch\builder\windows\pytorch\aten\src\ATen\core\VariableFallbackKernel.cpp:79 [backend fallback]
AutogradMPS: registered at C:\actions-runner_work\pytorch\pytorch\builder\windows\pytorch\aten\src\ATen\core\VariableFallbackKernel.cpp:87 [backend fallback]
AutogradXPU: registered at C:\actions-runner_work\pytorch\pytorch\builder\windows\pytorch\aten\src\ATen\core\VariableFallbackKernel.cpp:71 [backend fallback]
AutogradHPU: registered at C:\actions-runner_work\pytorch\pytorch\builder\windows\pytorch\aten\src\ATen\core\VariableFallbackKernel.cpp:100 [backend fallback]
AutogradLazy: registered at C:\actions-runner_work\pytorch\pytorch\builder\windows\pytorch\aten\src\ATen\core\VariableFallbackKernel.cpp:83 [backend fallback]
AutogradMeta: registered at C:\actions-runner_work\pytorch\pytorch\builder\windows\pytorch\aten\src\ATen\core\VariableFallbackKernel.cpp:91 [backend fallback]
Tracer: registered at C:\actions-runner_work\pytorch\pytorch\builder\windows\pytorch\torch\csrc\autograd\TraceTypeManual.cpp:294 [backend fallback]
AutocastCPU: registered at C:\actions-runner_work\vision\vision\pytorch\vision\torchvision\csrc\ops\autocast\nms_kernel.cpp:34 [kernel]
AutocastXPU: registered at C:\actions-runner_work\vision\vision\pytorch\vision\torchvision\csrc\ops\autocast\nms_kernel.cpp:41 [kernel]
AutocastMPS: fallthrough registered at C:\actions-runner_work\pytorch\pytorch\builder\windows\pytorch\aten\src\ATen\autocast_mode.cpp:209 [backend fallback]
AutocastCUDA: registered at C:\actions-runner_work\vision\vision\pytorch\vision\torchvision\csrc\ops\autocast\nms_kernel.cpp:27 [kernel]
FuncTorchBatched: registered at C:\actions-runner_work\pytorch\pytorch\builder\windows\pytorch\aten\src\ATen\functorch\LegacyBatchingRegistrations.cpp:731 [backend fallback]
BatchedNestedTensor: registered at C:\actions-runner_work\pytorch\pytorch\builder\windows\pytorch\aten\src\ATen\functorch\LegacyBatchingRegistrations.cpp:758 [backend fallback]
FuncTorchVmapMode: fallthrough registered at C:\actions-runner_work\pytorch\pytorch\builder\windows\pytorch\aten\src\ATen\functorch\VmapModeRegistrations.cpp:27 [backend fallback]
Batched: registered at C:\actions-runner_work\pytorch\pytorch\builder\windows\pytorch\aten\src\ATen\LegacyBatchingRegistrations.cpp:1075 [backend fallback]
VmapMode: fallthrough registered at C:\actions-runner_work\pytorch\pytorch\builder\windows\pytorch\aten\src\ATen\VmapModeRegistrations.cpp:33 [backend fallback]
FuncTorchGradWrapper: registered at C:\actions-runner_work\pytorch\pytorch\builder\windows\pytorch\aten\src\ATen\functorch\TensorWrapper.cpp:207 [backend fallback]
PythonTLSSnapshot: registered at C:\actions-runner_work\pytorch\pytorch\builder\windows\pytorch\aten\src\ATen\core\PythonFallbackKernel.cpp:161 [backend fallback]
FuncTorchDynamicLayerFrontMode: registered at C:\actions-runner_work\pytorch\pytorch\builder\windows\pytorch\aten\src\ATen\functorch\DynamicLayer.cpp:493 [backend fallback]
PreDispatch: registered at C:\actions-runner_work\pytorch\pytorch\builder\windows\pytorch\aten\src\ATen\core\PythonFallbackKernel.cpp:165 [backend fallback]
PythonDispatcher: registered at C:\actions-runner_work\pytorch\pytorch\builder\windows\pytorch\aten\src\ATen\core\PythonFallbackKernel.cpp:157 [backend fallback]
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Traceback (most recent call last):
File "D:\ANACONDA\envs\Leffa\lib\site-packages\gradio\queueing.py", line 625, in process_events
response = await route_utils.call_process_api(
File "D:\ANACONDA\envs\Leffa\lib\site-packages\gradio\route_utils.py", line 322, in call_process_api
output = await app.get_blocks().process_api(
File "D:\ANACONDA\envs\Leffa\lib\site-packages\gradio\blocks.py", line 2042, in process_api
result = await self.call_function(
File "D:\ANACONDA\envs\Leffa\lib\site-packages\gradio\blocks.py", line 1589, in call_function
prediction = await anyio.to_thread.run_sync( # type: ignore
File "D:\ANACONDA\envs\Leffa\lib\site-packages\anyio\to_thread.py", line 56, in run_sync
return await get_async_backend().run_sync_in_worker_thread(
File "D:\ANACONDA\envs\Leffa\lib\site-packages\anyio_backends_asyncio.py", line 2461, in run_sync_in_worker_thread
return await future
File "D:\ANACONDA\envs\Leffa\lib\site-packages\anyio_backends_asyncio.py", line 962, in run
result = context.run(func, *args)
File "D:\ANACONDA\envs\Leffa\lib\site-packages\gradio\utils.py", line 883, in wrapper
response = f(*args, **kwargs)
File "G:\Leffa\app.py", line 151, in leffa_predict_vt
return self.leffa_predict(src_image_path, ref_image_path, "virtual_tryon", ref_acceleration, step, scale, seed, vt_model_type, vt_garment_type, vt_repaint)
File "G:\Leffa\app.py", line 104, in leffa_predict
src_image_seg_array = self.densepose_predictor.predict_seg(
File "G:\Leffa\leffa_utils\densepose_predictor.py", line 58, in predict_seg
outputs = self.predict(image)
File "G:\Leffa\leffa_utils\densepose_predictor.py", line 32, in predict
outputs = self.predictor(image)["instances"]
File "G:\Leffa\leffa_utils\detectron2\engine\defaults.py", line 319, in call
predictions = self.model([inputs])[0]
File "D:\ANACONDA\envs\Leffa\lib\site-packages\torch\nn\modules\module.py", line 1736, in _wrapped_call_impl
return self._call_impl(*args, **kwargs)
File "D:\ANACONDA\envs\Leffa\lib\site-packages\torch\nn\modules\module.py", line 1747, in _call_impl
return forward_call(*args, **kwargs)
File "G:\Leffa\leffa_utils\detectron2\modeling\meta_arch\rcnn.py", line 150, in forward
return self.inference(batched_inputs)
File "G:\Leffa\leffa_utils\detectron2\modeling\meta_arch\rcnn.py", line 208, in inference
proposals, _ = self.proposal_generator(images, features, None)
File "D:\ANACONDA\envs\Leffa\lib\site-packages\torch\nn\modules\module.py", line 1736, in _wrapped_call_impl
return self._call_impl(*args, **kwargs)
File "D:\ANACONDA\envs\Leffa\lib\site-packages\torch\nn\modules\module.py", line 1747, in _call_impl
return forward_call(*args, **kwargs)
File "G:\Leffa\leffa_utils\detectron2\modeling\proposal_generator\rpn.py", line 477, in forward
proposals = self.predict_proposals(
File "G:\Leffa\leffa_utils\detectron2\modeling\proposal_generator\rpn.py", line 503, in predict_proposals
return find_top_rpn_proposals(
File "G:\Leffa\leffa_utils\detectron2\modeling\proposal_generator\proposal_utils.py", line 121, in find_top_rpn_proposals
keep = batched_nms(boxes.tensor, scores_per_img, lvl, nms_thresh)
File "G:\Leffa\leffa_utils\detectron2\layers\nms.py", line 20, in batched_nms
return box_ops.batched_nms(boxes.float(), scores, idxs, iou_threshold)
File "D:\ANACONDA\envs\Leffa\lib\site-packages\torchvision\ops\boxes.py", line 75, in batched_nms
return _batched_nms_coordinate_trick(boxes, scores, idxs, iou_threshold)
File "D:\ANACONDA\envs\Leffa\lib\site-packages\torch\jit_trace.py", line 1444, in wrapper
return fn(*args, **kwargs)
File "D:\ANACONDA\envs\Leffa\lib\site-packages\torchvision\ops\boxes.py", line 94, in _batched_nms_coordinate_trick
keep = nms(boxes_for_nms, scores, iou_threshold)
File "D:\ANACONDA\envs\Leffa\lib\site-packages\torchvision\ops\boxes.py", line 41, in nms
return torch.ops.torchvision.nms(boxes, scores, iou_threshold)
File "D:\ANACONDA\envs\Leffa\lib\site-packages\torch_ops.py", line 1116, in call
return self._op(*args, **(kwargs or {}))
NotImplementedError: Could not run 'torchvision::nms' with arguments from the 'CUDA' backend. This could be because the operator doesn't exist for this backend, or was omitted during the selective 6E60 /custom build process (if using custom build). If you are a Facebook employee using PyTorch on mobile, please visit https://fburl.com/ptmfixes for possible resolutions. 'torchvision::nms' is only available for these backends: [CPU, Meta, QuantizedCPU, BackendSelect, Python, FuncTorchDynamicLayerBackMode, Functionalize, Named, Conjugate, Negative, ZeroTensor, ADInplaceOrView, AutogradOther, AutogradCPU, AutogradCUDA, AutogradXLA, AutogradMPS, AutogradXPU, AutogradHPU, AutogradLazy, AutogradMeta, Tracer, AutocastCPU, AutocastXPU, AutocastMPS, AutocastCUDA, FuncTorchBatched, BatchedNestedTensor, FuncTorchVmapMode, Batched, VmapMode, FuncTorchGradWrapper, PythonTLSSnapshot, FuncTorchDynamicLayerFrontMode, PreDispatch, PythonDispatcher].
CPU: registered at C:\actions-runner_work\vision\vision\pytorch\vision\torchvision\csrc\ops\cpu\nms_kernel.cpp:112 [kernel]
Meta: registered at /dev/null:184 [kernel]
QuantizedCPU: registered at C:\actions-runner_work\vision\vision\pytorch\vision\torchvision\csrc\ops\quantized\cpu\qnms_kernel.cpp:124 [kernel]
BackendSelect: fallthrough registered at C:\actions-runner_work\pytorch\pytorch\builder\windows\pytorch\aten\src\ATen\core\BackendSelectFallbackKernel.cpp:3 [backend fallback]
Python: registered at C:\actions-runner_work\pytorch\pytorch\builder\windows\pytorch\aten\src\ATen\core\PythonFallbackKernel.cpp:153 [backend fallback]
FuncTorchDynamicLayerBackMode: registered at C:\actions-runner_work\pytorch\pytorch\builder\windows\pytorch\aten\src\ATen\functorch\DynamicLayer.cpp:497 [backend fallback]
Functionalize: registered at C:\actions-runner_work\pytorch\pytorch\builder\windows\pytorch\aten\src\ATen\FunctionalizeFallbackKernel.cpp:349 [backend fallback]
Named: registered at C:\actions-runner_work\pytorch\pytorch\builder\windows\pytorch\aten\src\ATen\core\NamedRegistrations.cpp:7 [backend fallback]
Conjugate: registered at C:\actions-runner_work\pytorch\pytorch\builder\windows\pytorch\aten\src\ATen\ConjugateFallback.cpp:17 [backend fallback]
Negative: registered at C:\actions-runner_work\pytorch\pytorch\builder\windows\pytorch\aten\src\ATen\native\NegateFallback.cpp:18 [backend fallback]
ZeroTensor: registered at C:\actions-runner_work\pytorch\pytorch\builder\windows\pytorch\aten\src\ATen\ZeroTensorFallback.cpp:86 [backend fallback]
ADInplaceOrView: fallthrough registered at C:\actions-runner_work\pytorch\pytorch\builder\windows\pytorch\aten\src\ATen\core\VariableFallbackKernel.cpp:96 [backend fallback]
AutogradOther: registered at C:\actions-runner_work\pytorch\pytorch\builder\windows\pytorch\aten\src\ATen\core\VariableFallbackKernel.cpp:63 [backend fallback]
AutogradCPU: registered at C:\actions-runner_work\pytorch\pytorch\builder\windows\pytorch\aten\src\ATen\core\VariableFallbackKernel.cpp:67 [backend fallback]
AutogradCUDA: registered at C:\actions-runner_work\pytorch\pytorch\builder\windows\pytorch\aten\src\ATen\core\VariableFallbackKernel.cpp:75 [backend fallback]
AutogradXLA: registered at C:\actions-runner_work\pytorch\pytorch\builder\windows\pytorch\aten\src\ATen\core\VariableFallbackKernel.cpp:79 [backend fallback]
AutogradMPS: registered at C:\actions-runner_work\pytorch\pytorch\builder\windows\pytorch\aten\src\ATen\core\VariableFallbackKernel.cpp:87 [backend fallback]
AutogradXPU: registered at C:\actions-runner_work\pytorch\pytorch\builder\windows\pytorch\aten\src\ATen\core\VariableFallbackKernel.cpp:71 [backend fallback]
AutogradHPU: registered at C:\actions-runner_work\pytorch\pytorch\builder\windows\pytorch\aten\src\ATen\core\VariableFallbackKernel.cpp:100 [backend fallback]
AutogradLazy: registered at C:\actions-runner_work\pytorch\pytorch\builder\windows\pytorch\aten\src\ATen\core\VariableFallbackKernel.cpp:83 [backend fallback]
AutogradMeta: registered at C:\actions-runner_work\pytorch\pytorch\builder\windows\pytorch\aten\src\ATen\core\VariableFallbackKernel.cpp:91 [backend fallback]
Tracer: registered at C:\actions-runner_work\pytorch\pytorch\builder\windows\pytorch\torch\csrc\autograd\TraceTypeManual.cpp:294 [backend fallback]
AutocastCPU: registered at C:\actions-runner_work\vision\vision\pytorch\vision\torchvision\csrc\ops\autocast\nms_kernel.cpp:34 [kernel]
AutocastXPU: registered at C:\actions-runner_work\vision\vision\pytorch\vision\torchvision\csrc\ops\autocast\nms_kernel.cpp:41 [kernel]
AutocastMPS: fallthrough registered at C:\actions-runner_work\pytorch\pytorch\builder\windows\pytorch\aten\src\ATen\autocast_mode.cpp:209 [backend fallback]
AutocastCUDA: registered at C:\actions-runner_work\vision\vision\pytorch\vision\torchvision\csrc\ops\autocast\nms_kernel.cpp:27 [kernel]
FuncTorchBatched: registered at C:\actions-runner_work\pytorch\pytorch\builder\windows\pytorch\aten\src\ATen\functorch\LegacyBatchingRegistrations.cpp:731 [backend fallback]
BatchedNestedTensor: registered at C:\actions-runner_work\pytorch\pytorch\builder\windows\pytorch\aten\src\ATen\functorch\LegacyBatchingRegistrations.cpp:758 [backend fallback]
FuncTorchVmapMode: fallthrough registered at C:\actions-runner_work\pytorch\pytorch\builder\windows\pytorch\aten\src\ATen\functorch\VmapModeRegistrations.cpp:27 [backend fallback]
Batched: registered at C:\actions-runner_work\pytorch\pytorch\builder\windows\pytorch\aten\src\ATen\LegacyBatchingRegistrations.cpp:1075 [backend fallback]
VmapMode: fallthrough registered at C:\actions-runner_work\pytorch\pytorch\builder\windows\pytorch\aten\src\ATen\VmapModeRegistrations.cpp:33 [backend fallback]
FuncTorchGradWrapper: registered at C:\actions-runner_work\pytorch\pytorch\builder\windows\pytorch\aten\src\ATen\functorch\TensorWrapper.cpp:207 [backend fallback]
PythonTLSSnapshot: registered at C:\actions-runner_work\pytorch\pytorch\builder\windows\pytorch\aten\src\ATen\core\PythonFallbackKernel.cpp:161 [backend fallback]
FuncTorchDynamicLayerFrontMode: registered at C:\actions-runner_work\pytorch\pytorch\builder\windows\pytorch\aten\src\ATen\functorch\DynamicLayer.cpp:493 [backend fallback]
PreDispatch: registered at C:\actions-runner_work\pytorch\pytorch\builder\windows\pytorch\aten\src\ATen\core\PythonFallbackKernel.cpp:165 [backend fallback]
PythonDispatcher: registered at C:\actions-runner_work\pytorch\pytorch\builder\windows\pytorch\aten\src\ATen\core\PythonFallbackKernel.cpp:157 [backend fallback]
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