Source code for speechbrain.utils.fetching

"""Downloads or otherwise fetches pretrained models

Authors:
 * Aku Rouhe 2021
 * Samuele Cornell 2021
 * Andreas Nautsch 2022, 2023
 * Sylvain de Langen 2024
 * Peter Plantinga 2024
"""

import pathlib
import platform
import shutil
import urllib.error
import urllib.request
import warnings
from collections import namedtuple
from enum import Enum
from typing import Optional, Union

import huggingface_hub
from requests.exceptions import HTTPError

from speechbrain.utils.logger import get_logger

logger = get_logger(__name__)


[docs] class FetchFrom(Enum): """Designator where to fetch models/audios from. Note: HuggingFace repository sources and local folder sources may be confused if their source type is undefined. """ LOCAL = 1 HUGGING_FACE = 2 URI = 3
# For easier use FetchSource = namedtuple("FetchSource", ["FetchFrom", "path"]) FetchSource.__doc__ = ( """NamedTuple describing a source path and how to fetch it""" ) FetchSource.__hash__ = lambda self: hash(self.path) FetchSource.encode = lambda self, *args, **kwargs: "_".join( (str(self.path), str(self.FetchFrom)) ).encode(*args, **kwargs) # FetchSource.__str__ = lambda self: str(self.path)
[docs] class LocalStrategy(Enum): """Describes what strategy should be chosen for fetching and linking to local files when using :func:`~fetch`.""" SYMLINK = 1 """If the file is remote and not in cache, fetch it (potentially to cache). Then, create a symbolic link in the destination folder to the local file, if necessary. .. warning:: Windows requires extra configuration to enable symbolic links, as it is a potential security risk on this platform. You either need to run Python as an administrator, or to enable developer mode. See `MS docs <https://docs.microsoft.com/en-us/windows/apps/get-started/enable-your-device-for-development>`_. Additionally, the `huggingface_hub` library makes a use of symlinks that is independently controlled. See `HF hub docs <https://huggingface.co/docs/huggingface_hub/how-to-cache#limitations>`_ for reference. """ COPY = 2 """If the file is remote and not in cache, fetch it (potentially to cache). Then, create a copy of the local file in the destination folder, if necessary. """ COPY_SKIP_CACHE = 3 """If the file is remote and not in cache, fetch it, preferably directly to the destination directory. Then, create a copy in the destination folder to the local file, if necessary.""" NO_LINK = 4 """If the file is remote and not in cache, fetch it (potentially to cache). Then, return the local path to it, even if it is not the destination folder (e.g. it might be located in a cache directory). .. note:: **This strategy may break code that does not expect this behavior,** since the destination folder is no longer guaranteed to contain a copy or link to the file. """
[docs] def guess_source(source: Union[str, FetchSource]) -> FetchSource: """From a given `FetchSource` or string source identifier, attempts to guess the matching :class:`~FetchFrom` (e.g. local or URI). If `source` is already a `FetchSource`, it is returned as-is. Arguments --------- source : str or FetchSource Where to look for the file. :func:`~fetch` interprets this path using the following logic: - First, if the source begins with "http://" or "https://", it is interpreted as a web address and the file is downloaded. - Second, if the source is a valid directory path, the file is either linked, copied or directly returned depending on the local strategy. - Otherwise, the source is interpreted as a HuggingFace model hub ID, and the file is downloaded from there (potentially with caching). Returns ------- tuple of (FetchFrom, str)""" if isinstance(source, FetchSource): return source if pathlib.Path(source).is_dir(): return FetchFrom.LOCAL, source uri_supported_schemes = ( "http:", "https:", ) if source.startswith(uri_supported_schemes): return FetchFrom.URI, source return FetchFrom.HUGGING_FACE, source
[docs] def fetch( filename, source: Union[str, FetchSource], savedir: Optional[Union[str, pathlib.Path]] = None, overwrite: bool = False, allow_updates: bool = False, allow_network: bool = True, save_filename: Optional[str] = None, use_auth_token: bool = False, revision: Optional[str] = None, huggingface_cache_dir: Optional[Union[str, pathlib.Path]] = None, local_strategy: Optional[LocalStrategy] = LocalStrategy.SYMLINK, ): """Fetches a local path, remote URL or remote HuggingFace file, downloading it locally if necessary and returns the local path. When a `savedir` is specified, but the file already exists locally elsewhere, the specified :class:`~LocalStrategy` chooses whether to copy or symlink it. If `<savedir>/<save_filename>` exists locally, it is returned as is (unless using `overwrite` or `allow_updates`). The `HF_HOME` environment (default: `~/.cache/huggingface`) `selects the cache directory for HF <https://huggingface.co/docs/huggingface_hub/guides/manage-cache#manage-huggingfacehub-cache-system>`__. To prefer directly downloading to `savedir`, specify `local_strategy=LocalStrategy.COPY_SKIP_CACHE`. **HF cache is always looked up first if possible.** Arguments --------- filename : str Name of the file including extensions. source : str or FetchSource Local or remote root path for the filename. The final path is determined by `<source>/<filename>`. See :func:`~guess_source` for how the path kind is deduced. savedir : str, optional If specified, directory under which the files will be available (possibly as a copy or symlink depending on `local_strategy`). Must be specified when downloading from an URL. overwrite : bool, defaults to `False` Allows the destination to be recreated by copy/symlink/fetch. This does **not** skip the HuggingFace cache (see `allow_updates`). allow_updates : bool, defaults to `True` If `True`, for a remote file on HF, check for updates and download newer revisions if available. If `False`, when the requested files are available locally, load them without fetching from HF. allow_network : bool, defaults to `True` If `True`, network accesses are allowed. If `False`, then remote URLs or HF won't be fetched, regardless of any other parameter. save_filename : str, optional, defaults to `None` The filename to use for saving this file. Defaults to the `filename` argument if not given or `None`. use_auth_token : bool, defaults to `False` If `True`, use HuggingFace's `auth_token` to enable loading private models from the Hub. revision : str, optional, defaults to `None` HuggingFace Hub model revision (Git branch name/tag/commit hash) to pin to a specific version. When changing the revision while local files might still exist, `allow_updates` must be `True`. huggingface_cache_dir: str, optional, defaults to `None` Path to HuggingFace cache; if `None`, `assumes the default cache location <https://huggingface.co/docs/huggingface_hub/guides/manage-cache#manage-huggingfacehub-cache-system>`__. Ignored if using `LocalStrategy.COPY_SKIP_CACHE`. Please prefer to let the user specify the cache directory themselves through the environment. local_strategy : LocalStrategy, optional Which strategy to use for local file storage -- see `LocalStrategy` for options. Ignored unless `savedir` is provided, default is `LocalStrategy.SYMLINK` which adds a link to the downloaded/cached file in the `savedir`. Returns ------- pathlib.Path Path to file on local file system. Raises ------ ValueError If file is not found """ if save_filename is None: save_filename = filename fetch_from, source = guess_source(source) source_path = f"{source}/{filename}" if savedir is not None: savedir = pathlib.Path(savedir) savedir.mkdir(parents=True, exist_ok=True) destination = (savedir / save_filename).absolute() else: destination = None local_strategy = LocalStrategy.NO_LINK # only HF supports updates should_try_update = overwrite or ( fetch_from == FetchFrom.HUGGING_FACE and allow_updates ) # Check if file is already present at destination if ( destination is not None and destination.exists() and not should_try_update ): file_kind = "symlink" if destination.is_symlink() else "file" logger.info( "Fetch %s: Using %s found at '%s'", filename, file_kind, str(destination), ) return destination if fetch_from == FetchFrom.LOCAL: source_path = pathlib.Path(source_path).absolute() return link_with_strategy(source_path, destination, local_strategy) if fetch_from == FetchFrom.URI: if destination is None: raise ValueError( f"Fetch {filename}: `savedir` must be specified for URI fetches" ) if not allow_network: # TODO: streamline exceptions? raise ValueError( f"Fetch {filename}: File was not found locally and " "`allow_network` was disabled." ) logger.info("Fetch %s: Downloading '%s'", filename, str(source_path)) try: urllib.request.urlretrieve(source_path, destination) except urllib.error.URLError as e: raise ValueError( f"Interpreted '{source}' as web address, but could not download." ) from e return destination assert fetch_from == FetchFrom.HUGGING_FACE # Assume we are fetching from HF at this point # Interpret source as huggingface hub ID try: kwargs = { "repo_id": source, "filename": filename, "use_auth_token": use_auth_token, "revision": revision, "local_files_only": not allow_network, } logger.info( "Fetch %s: Fetching from HuggingFace Hub '%s' if not cached", str(filename), str(source), ) # Directly save to destination if local_strategy == LocalStrategy.COPY_SKIP_CACHE: fetched_file = huggingface_hub.hf_hub_download( **kwargs, local_dir=savedir, local_dir_use_symlinks=False, force_filename=save_filename, ) return pathlib.Path(fetched_file).absolute() # Otherwise, normal huggingface download to cache fetched_file = huggingface_hub.hf_hub_download( **kwargs, cache_dir=huggingface_cache_dir, ) fetched_file = pathlib.Path(fetched_file).absolute() except HTTPError as e: if "404 Client Error" in str(e): raise ValueError("File not found on HF hub") from e raise return link_with_strategy(fetched_file, destination, local_strategy)