Doesn't run without GPU

[allenday]

$ ls link2checkpoints_distributed/
PoseNet_52_epoch_without_optimizer_statue.pth
$ python3 ./demo_image.py --resume --opt-level O0 --image ~/in.jpg --output ~/out.jpg
[...]
Traceback (most recent call last):
  File "./demo_image.py", line 631, in <module>
    loss_scale=args.loss_scale)
  File "/Library/Frameworks/Python.framework/Versions/3.6/lib/python3.6/site-packages/apex-0.1-py3.6.egg/apex/amp/frontend.py", line 358, in initialize
    return _initialize(models, optimizers, _amp_state.opt_properties, num_losses, cast_model_outputs)
  File "/Library/Frameworks/Python.framework/Versions/3.6/lib/python3.6/site-packages/apex-0.1-py3.6.egg/apex/amp/_initialize.py", line 171, in _initialize
    check_params_fp32(models)
  File "/Library/Frameworks/Python.framework/Versions/3.6/lib/python3.6/site-packages/apex-0.1-py3.6.egg/apex/amp/_initialize.py", line 93, in check_params_fp32
    name, param.type()))
  File "/Library/Frameworks/Python.framework/Versions/3.6/lib/python3.6/site-packages/apex-0.1-py3.6.egg/apex/amp/_amp_state.py", line 32, in warn_or_err
    raise RuntimeError(msg)
RuntimeError: Found param posenet.pre.conv1.weight with type torch.FloatTensor, expected torch.cuda.FloatTensor.
When using amp.initialize, you need to provide a model with parameters
located on a CUDA device before passing it no matter what optimization level
you chose. Use model.to('cuda') to use the default device.

Please advise.

[hellojialee]

Hi @allenday, thank you for your interest. The used train_distributed.py (distributed training with Apex) only considers training model using GPU just as the README said.

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