I have a question regarding model saving in PyTorch. Let’s say you run a series of experiments and change the code gradually during the project. However, if I save the model state_dict, I would need the exact source code to use the previous pre_trained models. Is there any good way to save a PyTorch model with just enough information to load it even when the source code changes (without the need to go back to the exact git commit that generated the network)? Tensorflow has this option and saves the model and the graph at the same time.  I suppose this is possible with TorchScript, but sometimes TorchScript has limited functionality.