ray.train.tensorflow.TensorflowTrainer.restore#

classmethod TensorflowTrainer.restore(path: str, train_loop_per_worker: Optional[Union[Callable[[], None], Callable[[Dict], None]]] = None, train_loop_config: Optional[Dict] = None, **kwargs) → ray.train.data_parallel_trainer.DataParallelTrainer#

Restores a DataParallelTrainer from a previously interrupted/failed run.

Parameters

  • train_loop_per_worker – Optionally re-specified train loop function. This should be used to re-specify a function that is not restorable in a new Ray cluster (e.g., it holds onto outdated object references). This should be the same training loop that was passed to the original trainer constructor.

  • train_loop_config – Optionally re-specified train config. This should similarly be used if the original train_loop_config contained outdated object references, and it should not be modified from what was originally passed in.

See BaseTrainer.restore() for descriptions of the other arguments.

Returns

A restored instance of the DataParallelTrainer subclass that is calling this method.

Return type

DataParallelTrainer