chore: import upstream snapshot with attribution
This commit is contained in:
wehub-resource-sync
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# Copyright (c) Facebook, Inc. and its affiliates.
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#
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# This source code is licensed under the MIT license found in the
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# LICENSE file in the root directory of this source tree.
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"""
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Utilities for working with the local dataset cache.
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This file is adapted from `AllenNLP <https://github.com/allenai/allennlp>`_.
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and `huggingface <https://github.com/huggingface>`_.
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"""
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import fnmatch
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import json
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import logging
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import os
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import shutil
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import tarfile
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import tempfile
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from functools import partial, wraps
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from hashlib import sha256
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from io import open
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try:
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from torch.hub import _get_torch_home
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torch_cache_home = _get_torch_home()
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except ImportError:
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torch_cache_home = os.path.expanduser(
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os.getenv(
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"TORCH_HOME", os.path.join(os.getenv("XDG_CACHE_HOME", "~/.cache"), "torch")
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)
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)
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default_cache_path = os.path.join(torch_cache_home, "pytorch_fairseq")
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try:
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from urllib.parse import urlparse
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except ImportError:
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from urlparse import urlparse
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try:
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from pathlib import Path
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PYTORCH_FAIRSEQ_CACHE = Path(os.getenv("PYTORCH_FAIRSEQ_CACHE", default_cache_path))
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except (AttributeError, ImportError):
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PYTORCH_FAIRSEQ_CACHE = os.getenv("PYTORCH_FAIRSEQ_CACHE", default_cache_path)
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CONFIG_NAME = "config.json"
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WEIGHTS_NAME = "pytorch_model.bin"
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logger = logging.getLogger(__name__) # pylint: disable=invalid-name
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def load_archive_file(archive_file):
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# redirect to the cache, if necessary
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try:
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resolved_archive_file = cached_path(archive_file, cache_dir=None)
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except EnvironmentError:
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logger.info(
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"Archive name '{}' was not found in archive name list. "
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"We assumed '{}' was a path or URL but couldn't find any file "
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"associated to this path or URL.".format(
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archive_file,
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archive_file,
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)
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)
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return None
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if resolved_archive_file == archive_file:
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logger.info("loading archive file {}".format(archive_file))
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else:
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logger.info(
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"loading archive file {} from cache at {}".format(
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archive_file, resolved_archive_file
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)
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)
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# Extract archive to temp dir and replace .tar.bz2 if necessary
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tempdir = None
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if not os.path.isdir(resolved_archive_file):
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tempdir = tempfile.mkdtemp()
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logger.info(
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"extracting archive file {} to temp dir {}".format(
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resolved_archive_file, tempdir
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)
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)
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ext = os.path.splitext(archive_file)[1][1:]
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with tarfile.open(resolved_archive_file, "r:" + ext) as archive:
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top_dir = os.path.commonprefix(archive.getnames())
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archive.extractall(tempdir)
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os.remove(resolved_archive_file)
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shutil.move(os.path.join(tempdir, top_dir), resolved_archive_file)
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shutil.rmtree(tempdir)
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return resolved_archive_file
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def url_to_filename(url, etag=None):
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"""
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Convert `url` into a hashed filename in a repeatable way.
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If `etag` is specified, append its hash to the URL's, delimited
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by a period.
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"""
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url_bytes = url.encode("utf-8")
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url_hash = sha256(url_bytes)
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filename = url_hash.hexdigest()
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if etag:
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etag_bytes = etag.encode("utf-8")
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etag_hash = sha256(etag_bytes)
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filename += "." + etag_hash.hexdigest()
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return filename
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def filename_to_url(filename, cache_dir=None):
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"""
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Return the url and etag (which may be ``None``) stored for `filename`.
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Raise ``EnvironmentError`` if `filename` or its stored metadata do not exist.
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"""
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if cache_dir is None:
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cache_dir = PYTORCH_FAIRSEQ_CACHE
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if isinstance(cache_dir, Path):
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cache_dir = str(cache_dir)
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cache_path = os.path.join(cache_dir, filename)
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if not os.path.exists(cache_path):
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raise EnvironmentError("file {} not found".format(cache_path))
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meta_path = cache_path + ".json"
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if not os.path.exists(meta_path):
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raise EnvironmentError("file {} not found".format(meta_path))
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with open(meta_path, encoding="utf-8") as meta_file:
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metadata = json.load(meta_file)
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url = metadata["url"]
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etag = metadata["etag"]
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return url, etag
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def cached_path(url_or_filename, cache_dir=None):
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"""
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Given something that might be a URL (or might be a local path),
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determine which. If it's a URL, download the file and cache it, and
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return the path to the cached file. If it's already a local path,
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make sure the file exists and then return the path.
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"""
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if cache_dir is None:
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cache_dir = PYTORCH_FAIRSEQ_CACHE
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if isinstance(url_or_filename, Path):
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url_or_filename = str(url_or_filename)
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if isinstance(cache_dir, Path):
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cache_dir = str(cache_dir)
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parsed = urlparse(url_or_filename)
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if parsed.scheme in ("http", "https", "s3"):
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# URL, so get it from the cache (downloading if necessary)
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return get_from_cache(url_or_filename, cache_dir)
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elif os.path.exists(url_or_filename):
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# File, and it exists.
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return url_or_filename
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elif parsed.scheme == "":
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# File, but it doesn't exist.
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raise EnvironmentError("file {} not found".format(url_or_filename))
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else:
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# Something unknown
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raise ValueError(
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"unable to parse {} as a URL or as a local path".format(url_or_filename)
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)
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def split_s3_path(url):
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"""Split a full s3 path into the bucket name and path."""
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parsed = urlparse(url)
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if not parsed.netloc or not parsed.path:
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raise ValueError("bad s3 path {}".format(url))
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bucket_name = parsed.netloc
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s3_path = parsed.path
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# Remove '/' at beginning of path.
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if s3_path.startswith("/"):
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s3_path = s3_path[1:]
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return bucket_name, s3_path
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def s3_request(func):
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"""
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Wrapper function for s3 requests in order to create more helpful error
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messages.
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"""
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@wraps(func)
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def wrapper(url, *args, **kwargs):
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from botocore.exceptions import ClientError
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try:
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return func(url, *args, **kwargs)
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except ClientError as exc:
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if int(exc.response["Error"]["Code"]) == 404:
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raise EnvironmentError("file {} not found".format(url))
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else:
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raise
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return wrapper
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@s3_request
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def s3_etag(url):
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"""Check ETag on S3 object."""
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import boto3
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s3_resource = boto3.resource("s3")
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bucket_name, s3_path = split_s3_path(url)
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s3_object = s3_resource.Object(bucket_name, s3_path)
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return s3_object.e_tag
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@s3_request
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def s3_get(url, temp_file):
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"""Pull a file directly from S3."""
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import boto3
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s3_resource = boto3.resource("s3")
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bucket_name, s3_path = split_s3_path(url)
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s3_resource.Bucket(bucket_name).download_fileobj(s3_path, temp_file)
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def request_wrap_timeout(func, url):
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import requests
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for attempt, timeout in enumerate([10, 20, 40, 60, 60]):
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try:
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return func(timeout=timeout)
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except requests.exceptions.Timeout as e:
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logger.warning(
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"Request for %s timed-out (attempt %d). Retrying with a timeout of %d secs",
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url,
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attempt,
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timeout,
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exc_info=e,
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)
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continue
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raise RuntimeError(f"Unable to fetch file {url}")
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def http_get(url, temp_file):
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import requests
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from tqdm import tqdm
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req = request_wrap_timeout(partial(requests.get, url, stream=True), url)
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content_length = req.headers.get("Content-Length")
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total = int(content_length) if content_length is not None else None
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progress = tqdm(unit="B", total=total)
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for chunk in req.iter_content(chunk_size=1024):
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if chunk: # filter out keep-alive new chunks
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progress.update(len(chunk))
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temp_file.write(chunk)
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progress.close()
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def get_from_cache(url, cache_dir=None):
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"""
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Given a URL, look for the corresponding dataset in the local cache.
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If it's not there, download it. Then return the path to the cached file.
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"""
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if cache_dir is None:
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cache_dir = PYTORCH_FAIRSEQ_CACHE
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if isinstance(cache_dir, Path):
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cache_dir = str(cache_dir)
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if not os.path.exists(cache_dir):
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os.makedirs(cache_dir)
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# Get eTag to add to filename, if it exists.
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if url.startswith("s3://"):
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etag = s3_etag(url)
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else:
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try:
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import requests
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response = request_wrap_timeout(
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partial(requests.head, url, allow_redirects=True), url
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)
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if response.status_code != 200:
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etag = None
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else:
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etag = response.headers.get("ETag")
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except RuntimeError:
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etag = None
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filename = url_to_filename(url, etag)
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# get cache path to put the file
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cache_path = os.path.join(cache_dir, filename)
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# If we don't have a connection (etag is None) and can't identify the file
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# try to get the last downloaded one
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if not os.path.exists(cache_path) and etag is None:
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matching_files = fnmatch.filter(os.listdir(cache_dir), filename + ".*")
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matching_files = list(filter(lambda s: not s.endswith(".json"), matching_files))
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if matching_files:
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cache_path = os.path.join(cache_dir, matching_files[-1])
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if not os.path.exists(cache_path):
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# Download to temporary file, then copy to cache dir once finished.
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# Otherwise you get corrupt cache entries if the download gets interrupted.
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with tempfile.NamedTemporaryFile() as temp_file:
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logger.info("%s not found in cache, downloading to %s", url, temp_file.name)
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# GET file object
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if url.startswith("s3://"):
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s3_get(url, temp_file)
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else:
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http_get(url, temp_file)
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# we are copying the file before closing it, so flush to avoid truncation
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temp_file.flush()
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# shutil.copyfileobj() starts at the current position, so go to the start
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temp_file.seek(0)
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logger.info("copying %s to cache at %s", temp_file.name, cache_path)
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with open(cache_path, "wb") as cache_file:
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shutil.copyfileobj(temp_file, cache_file)
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logger.info("creating metadata file for %s", cache_path)
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meta = {"url": url, "etag": etag}
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meta_path = cache_path + ".json"
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with open(meta_path, "w") as meta_file:
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output_string = json.dumps(meta)
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meta_file.write(output_string)
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logger.info("removing temp file %s", temp_file.name)
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return cache_path
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def read_set_from_file(filename):
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"""
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Extract a de-duped collection (set) of text from a file.
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Expected file format is one item per line.
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"""
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collection = set()
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with open(filename, "r", encoding="utf-8") as file_:
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for line in file_:
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collection.add(line.rstrip())
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return collection
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def get_file_extension(path, dot=True, lower=True):
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ext = os.path.splitext(path)[1]
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ext = ext if dot else ext[1:]
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return ext.lower() if lower else ext
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