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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 the AllenNLP library at https://github.com/allenai/allennlp |
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Copyright by the AllenNLP authors. |
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""" |
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from __future__ import (absolute_import, division, print_function, unicode_literals) |
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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 tempfile |
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from functools import wraps |
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from hashlib import sha256 |
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import sys |
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from io import open |
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import boto3 |
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import requests |
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from botocore.exceptions import ClientError |
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from tqdm import tqdm |
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from urllib.parse import urlparse |
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try: |
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from pathlib import Path |
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PYTORCH_PRETRAINED_BERT_CACHE = Path(os.getenv('PYTORCH_PRETRAINED_BERT_CACHE', |
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Path.home() / '.pytorch_pretrained_bert')) |
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except (AttributeError, ImportError): |
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PYTORCH_PRETRAINED_BERT_CACHE = os.getenv('PYTORCH_PRETRAINED_BERT_CACHE', |
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os.path.join(os.path.expanduser("~"), '.pytorch_pretrained_bert')) |
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logger = logging.getLogger(__name__) |
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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_PRETRAINED_BERT_CACHE |
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if sys.version_info[0] == 3 and 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_PRETRAINED_BERT_CACHE |
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if sys.version_info[0] == 3 and isinstance(url_or_filename, Path): |
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url_or_filename = str(url_or_filename) |
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if sys.version_info[0] == 3 and 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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return get_from_cache(url_or_filename, cache_dir) |
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elif os.path.exists(url_or_filename): |
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return url_or_filename |
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elif parsed.scheme == '': |
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raise EnvironmentError("file {} not found".format(url_or_filename)) |
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else: |
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raise ValueError("unable to parse {} as a URL or as a local path".format(url_or_filename)) |
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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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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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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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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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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 http_get(url, temp_file): |
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req = requests.get(url, stream=True) |
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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: |
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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_PRETRAINED_BERT_CACHE |
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if sys.version_info[0] == 3 and 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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if url.startswith("s3://"): |
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etag = s3_etag(url) |
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else: |
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response = requests.head(url, allow_redirects=True) |
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if response.status_code != 200: |
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raise IOError("HEAD request failed for url {} with status code {}" |
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.format(url, response.status_code)) |
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etag = response.headers.get("ETag") |
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filename = url_to_filename(url, etag) |
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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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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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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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temp_file.flush() |
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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', encoding="utf-8") as meta_file: |
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json.dump(meta, meta_file) |
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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 |