ray.train.Checkpoint

class ray.train.Checkpoint(path: str | PathLike, filesystem: pyarrow.fs.FileSystem | None = None)

A reference to data persisted as a directory in local or remote storage.

Access the checkpoint contents locally using checkpoint.to_directory() or checkpoint.as_directory.

Example creating a checkpoint using Checkpoint.from_directory:

>>> from ray.train import Checkpoint
>>> checkpoint = Checkpoint.from_directory("/tmp/example_checkpoint_dir")
>>> checkpoint.filesystem  
<pyarrow._fs.LocalFileSystem object...
>>> checkpoint.path
'/tmp/example_checkpoint_dir'

Example creating a checkpoint from a remote URI:

>>> checkpoint = Checkpoint("s3://bucket/path/to/checkpoint")
>>> checkpoint.filesystem  
<pyarrow._s3fs.S3FileSystem object...
>>> checkpoint.path
'bucket/path/to/checkpoint'

Example creating a checkpoint with a custom filesystem:

>>> checkpoint = Checkpoint(
...     path="bucket/path/to/checkpoint",
...     filesystem=pyarrow.fs.S3FileSystem(),
... )
>>> checkpoint.filesystem  
<pyarrow._s3fs.S3FileSystem object...
>>> checkpoint.path
'bucket/path/to/checkpoint'

path

A path on the filesystem containing the checkpoint contents.

filesystem

PyArrow FileSystem that can be used to access data at the path.

PublicAPI (beta): This API is in beta and may change before becoming stable.

Methods

__init__	Construct a Checkpoint.
as_directory	Returns checkpoint contents in a local directory as a context.
from_directory	Create checkpoint object from a local directory.
get_metadata	Return the metadata dict stored with the checkpoint.
set_metadata	Set the metadata stored with this checkpoint.
to_directory	Write checkpoint data to a local directory.
update_metadata	Update the metadata stored with this checkpoint.