Hi everyone 
I have a general question regarding saving and loading models in PyTorch.
My case:

I save a checkpoint consisting of the model.state_dict, optimizer.state_dict, and the last epoch.
The saved checkpoint refers to the best performing model, evaluated by accuracy.
I load all the three checkpoint entries and resume…However, I do not want to continue training but I want to use the saved state and make one forward pass to get the same accuracy as I had when I saved the checkpoint. How can I do that?

Basically, I want to be able to reproduce my results, since I have not figured out how to seed in PyTorch. It somehow does not really work…So I figured I can do it by saving and loading models.
Any help is very much appreciated!
All the best,
snowe