[mcj]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=’cpu’ to map your storages to the CPU.-马春杰杰

/usr/local/python3/lib/python3.6/site-packages/torch/serialization.py:454: SourceChangeWarning: source code of class 'model.SSD300' has changed. you can retrieve the original source code by accessing the object's source attribute or set `torch.nn.Module.dump_patches = True` and use the patch tool to revert the changes.
  warnings.warn(msg, SourceChangeWarning)
Traceback (most recent call last):
  File "train.py", line 234, in <module>
    main()
  File "train.py", line 57, in main
    checkpoint = torch.load(checkpoint)
  File "/usr/local/python3/lib/python3.6/site-packages/torch/serialization.py", line 387, in load
    return _load(f, map_location, pickle_module, **pickle_load_args)
  File "/usr/local/python3/lib/python3.6/site-packages/torch/serialization.py", line 574, in _load
    result = unpickler.load()
  File "/usr/local/python3/lib/python3.6/site-packages/torch/serialization.py", line 537, in persistent_load
    deserialized_objects[root_key] = restore_location(obj, location)
  File "/usr/local/python3/lib/python3.6/site-packages/torch/serialization.py", line 119, in default_restore_location
    result = fn(storage, location)
  File "/usr/local/python3/lib/python3.6/site-packages/torch/serialization.py", line 95, in _cuda_deserialize
    device = validate_cuda_device(location)
  File "/usr/local/python3/lib/python3.6/site-packages/torch/serialization.py", line 79, 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='cpu' to map your storages to the CPU.

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/usr/local/python3/lib/python3.6/site-packages/torch/serialization.py:454: SourceChangeWarning: source code of class 'model.SSD300' has changed. you can retrieve the original source code by accessing the object's source attribute or set `torch.nn.Module.dump_patches = True` and use the patch tool to revert the changes.

warnings.warn(msg, SourceChangeWarning)

Traceback (most recent call last):

File "train.py", line 234, in <module>

main()

File "train.py", line 57, in main

checkpoint = torch.load(checkpoint)

File "/usr/local/python3/lib/python3.6/site-packages/torch/serialization.py", line 387, in load

return _load(f, map_location, pickle_module, **pickle_load_args)

File "/usr/local/python3/lib/python3.6/site-packages/torch/serialization.py", line 574, in _load

result = unpickler.load()

File "/usr/local/python3/lib/python3.6/site-packages/torch/serialization.py", line 537, in persistent_load

deserialized_objects[root_key] = restore_location(obj, location)

File "/usr/local/python3/lib/python3.6/site-packages/torch/serialization.py", line 119, in default_restore_location

result = fn(storage, location)

File "/usr/local/python3/lib/python3.6/site-packages/torch/serialization.py", line 95, in _cuda_deserialize

device = validate_cuda_device(location)

File "/usr/local/python3/lib/python3.6/site-packages/torch/serialization.py", line 79, 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='cpu' to map your storages to the CPU.