ray.train.RunConfig

class ray.train.RunConfig(name: str | None = None, storage_path: str | None = None, storage_filesystem: pyarrow.fs.FileSystem | None = None, failure_config: FailureConfig | None = None, checkpoint_config: CheckpointConfig | None = None, sync_config: str = 'DEPRECATED', verbose: str = 'DEPRECATED', stop: str = 'DEPRECATED', callbacks: List[UserCallback] | None = None, progress_reporter: str = 'DEPRECATED', log_to_file: str = 'DEPRECATED', local_dir: str | None = None)

Bases: RunConfig

Runtime configuration for training runs.

Parameters:

• name – Name of the trial or experiment. If not provided, will be deduced from the Trainable.

• storage_path – [Beta] Path where all results and checkpoints are persisted. Can be a local directory or a destination on cloud storage. For multi-node training/tuning runs, this must be set to a shared storage location (e.g., S3, NFS). This defaults to the local ~/ray_results directory.

• storage_filesystem – [Beta] A custom filesystem to use for storage. If this is provided, storage_path should be a path with its prefix stripped (e.g., s3://bucket/path -> bucket/path).

• failure_config – Failure mode configuration.

• checkpoint_config – Checkpointing configuration.

• callbacks – [DeveloperAPI] A list of callbacks that the Ray Train controller will invoke during training.

Methods

Attributes

callbacks
checkpoint_config
failure_config
local_dir
log_to_file
name
progress_reporter
stop
storage_filesystem
storage_path
sync_config
verbose