ray.tune.Trainable.save

Trainable.save(checkpoint_dir: str | None = None) → _TrainingResult

Saves the current model state to a checkpoint.

Subclasses should override save_checkpoint() instead to save state.

Parameters:

checkpoint_dir – Optional dir to place the checkpoint.

Returns:

The given or created checkpoint directory.

Note the return value matches up with what is expected of restore().

DeveloperAPI: This API may change across minor Ray releases.