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Source code for torch.distributed.checkpoint.fsspec

# Mypy will not try inferring the types of any 3rd party libraries installed.
# mypy: ignore-errors

import io
import os
from contextlib import contextmanager
from pathlib import Path
from typing import Generator, Optional, Union

import fsspec
from fsspec import AbstractFileSystem
from fsspec.core import url_to_fs

from torch.distributed.checkpoint.filesystem import (
    FileSystemBase,
    FileSystemReader,
    FileSystemWriter,
)

__all__ = [
    "FsspecWriter",
    "FsspecReader",
]


class FileSystem(FileSystemBase):
    def __init__(self) -> None:
        self.fs: Optional[AbstractFileSystem] = None

    @contextmanager
    def create_stream(
        self, path: Union[str, os.PathLike], mode: str
    ) -> Generator[io.IOBase, None, None]:
        assert self.fs is not None
        with self.fs.transaction:
            with fsspec.open(str(path), mode) as stream:
                yield stream

    def concat_path(
        self, path: Union[str, os.PathLike], suffix: str
    ) -> Union[str, os.PathLike]:
        return os.path.join(path, suffix)

    def init_path(self, path: Union[str, os.PathLike]) -> Union[str, os.PathLike]:
        self.fs, _ = url_to_fs(path)
        return path

    def rename(
        self, path: Union[str, os.PathLike], new_path: Union[str, os.PathLike]
    ) -> None:
        self.fs.rename(path, new_path)

    def mkdir(self, path: [str, os.PathLike]) -> None:
        self.fs.makedirs(path, exist_ok=True)

    @classmethod
    def validate_checkpoint_id(cls, checkpoint_id: Union[str, os.PathLike]) -> bool:
        if isinstance(checkpoint_id, Path):
            return False

        try:
            url_to_fs(checkpoint_id)
        except ValueError as e:
            return False

        return True


[docs]class FsspecWriter(FileSystemWriter): """ Basic implementation of StorageWriter using FFspec. This implementation makes the following assumptions and simplifications: * The checkpoint path is an empty or non-existing directory. * File creation is atomic The checkpoint consist of one file per write request plus a `.metadata` file with the serialized metadata. """ def __init__( self, path: Union[str, os.PathLike], single_file_per_rank: bool = True, sync_files: bool = True, thread_count: int = 1, per_thread_copy_ahead: int = 10_000_000, ) -> None: """ Initialize the writer pointing to `path`. Args: path: directory where the checkpoint will be written to. single_file_per_rank: Produce one file per rank instead of one file per tensor/blob. Default to True. sync_files : force files to be synced to permanent storage. Default to True. thread_count: Number of IO threads to use to write. Default to 1. per_thread_copy_ahead: How many bytes to copy from the GPU ahead of saving then. Default 10Mb. N. B. If sync_files is disabled, there's no guarantee that the checkpoint will be consistent in the case of a failure. """ super().__init__( path, single_file_per_rank, sync_files, thread_count, per_thread_copy_ahead ) self.fs = FileSystem() self.path = self.fs.init_path(path) @classmethod def validate_checkpoint_id(cls, checkpoint_id: Union[str, os.PathLike]) -> bool: return FileSystem.validate_checkpoint_id(checkpoint_id)
[docs]class FsspecReader(FileSystemReader): def __init__(self, path: Union[str, os.PathLike]) -> None: super().__init__(path) self.fs = FileSystem() self.path = self.fs.init_path(path) @classmethod def validate_checkpoint_id(cls, checkpoint_id: Union[str, os.PathLike]) -> bool: return FileSystem.check(checkpoint_id)

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