Feature request - load best checkpoint

Currently there is a function TrainableModel.delete_checkpoints(best_checkpoint_metric) which removes all checkpoints except the best and the latest.

Unfortunately, there is no straight-forward way to load the weights according to the best checkpoint.
It would be nice if such function existed.

Example signature:

class TrainableModel:
    def load_checkpoint(which: int | Literal["best"] | Literal["latest"] = "latest", best_checkpoint_metric: str = "val/reward"):
        """
        Args: 
          which (int | Literal["best"] | Literal["latest"]) - The type of checkpoint to load.
            - "best" loads the best checkpoint according to the `best_checkpoint_metric"
            - "latest" loads the latest checkpoint available
            - integer value determines the step number of the checkpoint.
          best_checkpoint_metric (str) - the name of the metric determining which checkpoint is best.
          """
          ...

Start by locating TrainableModel.delete_checkpoints and the checkpoint-loading entry points. Trace how checkpoint steps and best_checkpoint_metric are recorded, then verify that loading supports the requested best, latest, and integer-step choices with the documented default metric.