Although this issue has been raised before, I am new to PyTorch and am having some difficulty understanding model checkpointing.


How can we save all checkpointable objects for the best model with the least validation loss? I don’t want to save multiple checkpoints corresponding to different iteration/epoch.


What’s the difference between deep cloning checkpointable objects vs using model.state_dict()?