Solved by googlebot in post #6 
              
              
                No, you’d reload optimizer’s state_dict if you want to pause/resume training at epoch N>0 for whatever reason. If model or dataset changes, that should be considered a new run from epoch 0; you’re free to reload parameters from model.load_state_dict(strict=False) for it, there is no need for old opt…