basically, subj. I want my code to operate deterministically, so I’m using the following initialization:
manual_seed = 1234
random.seed(manual_seed)
np.random.seed(manual_seed)
torch.manual_seed(manual_seed)
torch.cuda.manual_seed(manual_seed)

during training the loss function values (and some other metrics) are always the same from run to run, which makes me think the actual model is deterministic. At (deterministic) checkpoints the model is saved as follows:
torch.save(net.state_dict(), model_filename)
However, the diff tool indicates a difference between model files from run to run, hence the question.
Thanks,