Hi,
I used a resnet50 model(pretrained=True) for training.  I saved the best model in training function like:
model.load_state_dict(best_model_wts)
return model

then i called my training function:
trained_model = training_func(.....)
torch.save(trained_model, 'trained.pth')

Now I want to train again using the weights of my trained model.  So what I did is:
pretrained_weights = torch.load('trained.pth'')
model = resnet50(pretrained=False)
model.load_state_dict(pretrained_weights)

But it throws error:
model.load_state_dict(pretrained_weights)
  File "/home/user/.local/lib/python3.6/site-packages/torch/nn/modules/module.py", line 751, in load_state_dict
    state_dict = state_dict.copy()
  File "/home/user/.local/lib/python3.6/site-packages/torch/nn/modules/module.py", line 539, in __getattr__
    type(self).__name__, name))
AttributeError: 'ResNet' object has no attribute 'copy'

What I am doing wrong, can you please tell me ? I want to use my trained model’s weights to initialize my new training, same model as before resnet50.