Resume training from model checkpoints

Hi,
Thanks for the great software! Loving the redesign, and the helpful documentation and tutorials.

Related to this previous topic (Resuming training with scVI) , is resuming training now possible with scvi? If I call model.save and then scvi.model.load and then call model.train() again, does that start from the last state, or overwrite it?

It looks like one can enable_checkpointing=True in the Trainer and then can find the path of the last checkpoint with something like model.trainer.callbacks[-1].best_model_path. But then is there a way to pass ckpt_path to Trainer.fit() so that it is used on subsequent calls to model.train()?

Thanks,
David

This is possible and will start from the loaded model weights, though the optimizer state is lost.

I would have to look into this, all kwargs to train get passed to pytorch lightning trainer init. Currently no way to pass kwargs to fit.