scvi.dataloaders.SemiSupervisedDataSplitter.on_save_checkpoint

SemiSupervisedDataSplitter.on_save_checkpoint(checkpoint)

Called by Lightning when saving a checkpoint to give you a chance to store anything else you might want to save.

Parameters
checkpoint : {str: Any}Dict[str, Any]

Checkpoint to be saved

Example:

def on_save_checkpoint(self, checkpoint):
    # 99% of use cases you don't need to implement this method
    checkpoint['something_cool_i_want_to_save'] = my_cool_pickable_object

Note

Lightning saves all aspects of training (epoch, global step, etc…) including amp scaling. There is no need for you to store anything about training.

Return type

NoneNone