ResumeSettings
Full path:
schola.scripts.rllib.settings.ResumeSettings
schola.scripts.rllib.settings.ResumeSettings
ResumeSettings
ResumeSettings(resume_from=None)Bases: object
Dataclass for resume settings used in the RLlib training process. This class defines the parameters for resuming training from a saved checkpoint. This allows you to continue training from a previously saved model checkpoint instead of starting from scratch. This is useful for long training jobs or if you want to experiment with different hyperparameters without losing progress.
Methods
| Item | Description |
|---|---|
| init | — |
Attributes
| Item | Description |
|---|---|
| name | — |
| resume_from | Path to a checkpoint to resume training from. |
Parameters
resume_from (Annotated[Path | None, Parameter(validator=(Path(exists=True, file_okay=True, dir_okay=False, ext=()),))])
init
__init__(resume_from=None)Parameters
resume_from (Annotated[Path | None, Parameter(validator=(Path(exists=True, file_okay=True, dir_okay=False, ext=()),))])
Returns
None
name
name: strresume_from
= None resume_from: Annotated[Path | None, Parameter(validator=Path(exists=True, file_okay=True, dir_okay=False, ext=()))]Path to a checkpoint to resume training from. This allows you to continue training from a previously saved model checkpoint instead of starting from scratch. This is useful for long training jobs or if you want to experiment with different hyperparameters without losing progress. If set to None, training will start from scratch.