training problem

[meroluo]

Thank you for your wonderful work!
I want to train a model with my own dataset, but there are something wrong in the process.
The error is described as below:

===> Loading datasets
===> Building model
/home/luomeilu/anaconda3/envs/py2/lib/python2.7/site-packages/torch/nn/_reduction.py:49: UserWarning: size_average and reduce args will be deprecated, please use reduction='sum' instead.
warnings.warn(warning.format(ret))
===> Setting GPU
===> load model model/model_epoch_28.pth
/home/luomeilu/anaconda3/envs/py2/lib/python2.7/site-packages/torch/serialization.py:435: SourceChangeWarning: source code of class 'torch.nn.parallel.data_parallel.DataParallel' 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)
/home/luomeilu/anaconda3/envs/py2/lib/python2.7/site-packages/torch/serialization.py:435: SourceChangeWarning: source code of class 'torch.nn.modules.conv.Conv2d' 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)
/home/luomeilu/anaconda3/envs/py2/lib/python2.7/site-packages/torch/serialization.py:435: SourceChangeWarning: source code of class 'torch.nn.modules.activation.ReLU' 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 "main.py", line 128, in
main()
File "main.py", line 69, in main
model.load_state_dict(weights['model'].state_dict())
File "/home/luomeilu/anaconda3/envs/py2/lib/python2.7/site-packages/torch/nn/modules/module.py", line 769, in load_state_dict
self.class.name, "\n\t".join(error_msgs)))
RuntimeError: Error(s) in loading state_dict for DRRN:
Missing key(s) in state_dict: "input.weight", "conv1.weight", "conv2.weight", "output.weight".
Unexpected key(s) in state_dict: "module.input.weight", "module.conv1.weight", "module.conv2.weight", "module.output.weight".

It seems that the parameters in model are miss? I can't understand the error, hoping you can give me some suggestions. Sincerely appreciate for your reply.

[xsacha]

You need to remove module from the state_dict because it was trained with data parallel.
You can do model = model.module to achieve the same thing, I believe.