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vt-vl-lab / 3d-photo-inpainting

[CVPR 2020] 3D Photography using Context-aware Layered Depth Inpainting
https://shihmengli.github.io/3D-Photo-Inpainting/
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Error #70

Closed cesar-xyz closed 4 years ago

cesar-xyz commented 4 years ago

Start Running 3D_Photo ... Loading edge model at 1593325872.7909162 0%| | 0/1 [01:17<?, ?it/s] Traceback (most recent call last): File "main.py", line 80, in map_location=torch.device(device)) File "/Users/---/anaconda3/envs/3DPhotoCreator/lib/python3.7/site-packages/torch/serialization.py", line 426, in load return _load(f, map_location, pickle_module, **pickle_load_args) File "/Users/---//anaconda3/envs/3DPhotoCreator/lib/python3.7/site-packages/torch/serialization.py", line 613, in _load result = unpickler.load() File "/Users/---//anaconda3/envs/3DPhotoCreator/lib/python3.7/site-packages/torch/serialization.py", line 576, in persistent_load deserialized_objects[root_key] = restore_location(obj, location) File "/Users/---//anaconda3/envs/3DPhotoCreator/lib/python3.7/site-packages/torch/serialization.py", line 446, in restore_location return default_restore_location(storage, str(map_location)) File "/Users/---//anaconda3/envs/3DPhotoCreator/lib/python3.7/site-packages/torch/serialization.py", line 155, in default_restore_location result = fn(storage, location) File "/Users/---//anaconda3/envs/3DPhotoCreator/lib/python3.7/site-packages/torch/serialization.py", line 131, in _cuda_deserialize device = validate_cuda_device(location) File "/Users/---//anaconda3/envs/3DPhotoCreator/lib/python3.7/site-packages/torch/serialization.py", line 115, in validate_cuda_device raise RuntimeError('Attempting to deserialize object on a CUDA ' RuntimeError: Attempting to deserialize object on a CUDA device but torch.cuda.is_available() is False. If you are running on a CPU-only machine, please use torch.load with map_location=torch.device('cpu') to map your storages to the CPU.

freeman5 commented 4 years ago

RuntimeError: Attempting to deserialize object on a CUDA device but torch.cuda.is_available() is False. If you are running on a CPU-only machine, please use torch.load with map_location=torch.device('cpu') to map your storages to the CPU.

Its already say in documentation or other issue you just have to delete the 0 at gpu argument in argument.yml