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Add files using upload-large-folder tool
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"""
Utilities for working with the local dataset cache.
This file is adapted from the AllenNLP library at https://github.com/allenai/allennlp
Copyright by the AllenNLP authors.
"""
import copy
import io
import json
import os
import posixpath
import re
import shutil
import sys
import tempfile
import time
import urllib
from contextlib import closing, contextmanager
from functools import partial
from hashlib import sha256
from pathlib import Path
from typing import List, Optional, Type, TypeVar, Union
from urllib.parse import urljoin, urlparse
import requests
from datasets import DownloadConfig
from datasets.utils.extract import ExtractManager
from datasets.utils.filelock import FileLock
from .. import __version__, config
from . import logging
logger = logging.get_logger(__name__) # pylint: disable=invalid-name
INCOMPLETE_SUFFIX = ".incomplete"
T = TypeVar("T", str, Path)
def init_hf_modules(hf_modules_cache: Optional[Union[Path, str]] = None) -> str:
"""
Add hf_modules_cache to the python path.
By default hf_modules_cache='~/.cache/huggingface/modules'.
It can also be set with the environment variable HF_MODULES_CACHE.
This is used to add modules such as `datasets_modules`
"""
hf_modules_cache = hf_modules_cache if hf_modules_cache is not None else config.HF_MODULES_CACHE
hf_modules_cache = str(hf_modules_cache)
if hf_modules_cache not in sys.path:
sys.path.append(hf_modules_cache)
os.makedirs(hf_modules_cache, exist_ok=True)
if not os.path.exists(os.path.join(hf_modules_cache, "__init__.py")):
with open(os.path.join(hf_modules_cache, "__init__.py"), "w"):
pass
return hf_modules_cache
def is_remote_url(url_or_filename: str) -> bool:
parsed = urlparse(url_or_filename)
return parsed.scheme in ("http", "https", "s3", "gs", "hdfs", "ftp")
def is_local_path(url_or_filename: str) -> bool:
# On unix the scheme of a local path is empty (for both absolute and relative),
# while on windows the scheme is the drive name (ex: "c") for absolute paths.
# for details on the windows behavior, see https://bugs.python.org/issue42215
return urlparse(url_or_filename).scheme == "" or os.path.ismount(urlparse(url_or_filename).scheme + ":/")
def is_relative_path(url_or_filename: str) -> bool:
return urlparse(url_or_filename).scheme == "" and not os.path.isabs(url_or_filename)
def relative_to_absolute_path(path: T) -> T:
"""Convert relative path to absolute path."""
abs_path_str = os.path.abspath(os.path.expanduser(os.path.expandvars(str(path))))
return Path(abs_path_str) if isinstance(path, Path) else abs_path_str
def hf_bucket_url(identifier: str, filename: str, use_cdn=False, dataset=True) -> str:
if dataset:
endpoint = config.CLOUDFRONT_DATASETS_DISTRIB_PREFIX if use_cdn else config.S3_DATASETS_BUCKET_PREFIX
else:
endpoint = config.CLOUDFRONT_METRICS_DISTRIB_PREFIX if use_cdn else config.S3_METRICS_BUCKET_PREFIX
return "/".join((endpoint, identifier, filename))
def head_hf_s3(
identifier: str, filename: str, use_cdn=False, dataset=True, max_retries=0
) -> Union[requests.Response, Exception]:
return http_head(
hf_bucket_url(identifier=identifier, filename=filename, use_cdn=use_cdn, dataset=dataset),
max_retries=max_retries,
)
def hf_hub_url(path: str, name: str, revision: Optional[str] = None) -> str:
revision = revision or config.HUB_DEFAULT_VERSION
return config.HUB_EVALUATE_URL.format(path=path, name=name, revision=revision)
def url_or_path_join(base_name: str, *pathnames: str) -> str:
if is_remote_url(base_name):
return posixpath.join(base_name, *(str(pathname).replace(os.sep, "/").lstrip("/") for pathname in pathnames))
else:
return Path(base_name, *pathnames).as_posix()
def url_or_path_parent(url_or_path: str) -> str:
if is_remote_url(url_or_path):
return url_or_path[: url_or_path.rindex("/")]
else:
return os.path.dirname(url_or_path)
def hash_url_to_filename(url, etag=None):
"""
Convert `url` into a hashed filename in a repeatable way.
If `etag` is specified, append its hash to the url's, delimited
by a period.
If the url ends with .h5 (Keras HDF5 weights) adds '.h5' to the name
so that TF 2.0 can identify it as a HDF5 file
(see https://github.com/tensorflow/tensorflow/blob/00fad90125b18b80fe054de1055770cfb8fe4ba3/tensorflow/python/keras/engine/network.py#L1380)
"""
url_bytes = url.encode("utf-8")
url_hash = sha256(url_bytes)
filename = url_hash.hexdigest()
if etag:
etag_bytes = etag.encode("utf-8")
etag_hash = sha256(etag_bytes)
filename += "." + etag_hash.hexdigest()
if url.endswith(".py"):
filename += ".py"
return filename
def cached_path(
url_or_filename,
download_config=None,
**download_kwargs,
) -> str:
"""
Given something that might be a URL (or might be a local path),
determine which. If it's a URL, download the file and cache it, and
return the path to the cached file. If it's already a local path,
make sure the file exists and then return the path.
Return:
Local path (string)
Raises:
FileNotFoundError: in case of non-recoverable file
(non-existent or no cache on disk)
ConnectionError: in case of unreachable url
and no cache on disk
ValueError: if it couldn't parse the url or filename correctly
requests.exceptions.ConnectionError: in case of internet connection issue
"""
if download_config is None:
download_config = DownloadConfig(**download_kwargs)
cache_dir = download_config.cache_dir or config.DOWNLOADED_EVALUATE_PATH
if isinstance(cache_dir, Path):
cache_dir = str(cache_dir)
if isinstance(url_or_filename, Path):
url_or_filename = str(url_or_filename)
if is_remote_url(url_or_filename):
# URL, so get it from the cache (downloading if necessary)
output_path = get_from_cache(
url_or_filename,
cache_dir=cache_dir,
force_download=download_config.force_download,
proxies=download_config.proxies,
resume_download=download_config.resume_download,
user_agent=download_config.user_agent,
local_files_only=download_config.local_files_only,
use_etag=download_config.use_etag,
max_retries=download_config.max_retries,
use_auth_token=download_config.use_auth_token,
ignore_url_params=download_config.ignore_url_params,
download_desc=download_config.download_desc,
)
elif os.path.exists(url_or_filename):
# File, and it exists.
output_path = url_or_filename
elif is_local_path(url_or_filename):
# File, but it doesn't exist.
raise FileNotFoundError(f"Local file {url_or_filename} doesn't exist")
else:
# Something unknown
raise ValueError(f"unable to parse {url_or_filename} as a URL or as a local path")
if output_path is None:
return output_path
if download_config.extract_compressed_file:
output_path = ExtractManager(cache_dir=download_config.cache_dir).extract(
output_path, force_extract=download_config.force_extract
)
return output_path
def get_datasets_user_agent(user_agent: Optional[Union[str, dict]] = None) -> str:
ua = f"datasets/{__version__}; python/{config.PY_VERSION}"
ua += f"; pyarrow/{config.PYARROW_VERSION}"
if config.TORCH_AVAILABLE:
ua += f"; torch/{config.TORCH_VERSION}"
if config.TF_AVAILABLE:
ua += f"; tensorflow/{config.TF_VERSION}"
if config.JAX_AVAILABLE:
ua += f"; jax/{config.JAX_VERSION}"
if isinstance(user_agent, dict):
ua += f"; {'; '.join(f'{k}/{v}' for k, v in user_agent.items())}"
elif isinstance(user_agent, str):
ua += "; " + user_agent
return ua
def get_authentication_headers_for_url(url: str, use_auth_token: Optional[Union[str, bool]] = None) -> dict:
"""Handle the HF authentication"""
headers = {}
if url.startswith(config.HF_ENDPOINT):
token = None
if isinstance(use_auth_token, str):
token = use_auth_token
elif bool(use_auth_token):
from huggingface_hub import hf_api
token = hf_api.HfFolder.get_token()
if token:
headers["authorization"] = f"Bearer {token}"
return headers
class OfflineModeIsEnabled(ConnectionError):
pass
def _raise_if_offline_mode_is_enabled(msg: Optional[str] = None):
"""Raise an OfflineModeIsEnabled error (subclass of ConnectionError) if HF_EVALUATE_OFFLINE is True."""
if config.HF_EVALUATE_OFFLINE:
raise OfflineModeIsEnabled(
"Offline mode is enabled." if msg is None else "Offline mode is enabled. " + str(msg)
)
def _retry(
func,
func_args: Optional[tuple] = None,
func_kwargs: Optional[dict] = None,
exceptions: Type[requests.exceptions.RequestException] = requests.exceptions.RequestException,
status_codes: Optional[List[int]] = None,
max_retries: int = 0,
base_wait_time: float = 0.5,
max_wait_time: float = 2,
):
func_args = func_args or ()
func_kwargs = func_kwargs or {}
retry = 0
while True:
try:
return func(*func_args, **func_kwargs)
except exceptions as err:
if retry >= max_retries or (status_codes and err.response.status_code not in status_codes):
raise err
else:
sleep_time = min(max_wait_time, base_wait_time * 2**retry) # Exponential backoff
logger.info(f"{func} timed out, retrying in {sleep_time}s... [{retry/max_retries}]")
time.sleep(sleep_time)
retry += 1
def _request_with_retry(
method: str,
url: str,
max_retries: int = 0,
base_wait_time: float = 0.5,
max_wait_time: float = 2,
timeout: float = 10.0,
**params,
) -> requests.Response:
"""Wrapper around requests to retry in case it fails with a ConnectTimeout, with exponential backoff.
Note that if the environment variable HF_EVALUATE_OFFLINE is set to 1, then a OfflineModeIsEnabled error is raised.
Args:
method (str): HTTP method, such as 'GET' or 'HEAD'.
url (str): The URL of the resource to fetch.
max_retries (int): Maximum number of retries, defaults to 0 (no retries).
base_wait_time (float): Duration (in seconds) to wait before retrying the first time. Wait time between
retries then grows exponentially, capped by max_wait_time.
max_wait_time (float): Maximum amount of time between two retries, in seconds.
**params: Params to pass to :obj:`requests.request`.
"""
_raise_if_offline_mode_is_enabled(f"Tried to reach {url}")
tries, success = 0, False
while not success:
tries += 1
try:
response = requests.request(method=method.upper(), url=url, timeout=timeout, **params)
success = True
except (requests.exceptions.ConnectTimeout, requests.exceptions.ConnectionError) as err:
if tries > max_retries:
raise err
else:
logger.info(f"{method} request to {url} timed out, retrying... [{tries/max_retries}]")
sleep_time = min(max_wait_time, base_wait_time * 2 ** (tries - 1)) # Exponential backoff
time.sleep(sleep_time)
return response
def ftp_head(url, timeout=10.0):
_raise_if_offline_mode_is_enabled(f"Tried to reach {url}")
try:
with closing(urllib.request.urlopen(url, timeout=timeout)) as r:
r.read(1)
except Exception:
return False
return True
def ftp_get(url, temp_file, timeout=10.0):
_raise_if_offline_mode_is_enabled(f"Tried to reach {url}")
try:
logger.info(f"Getting through FTP {url} into {temp_file.name}")
with closing(urllib.request.urlopen(url, timeout=timeout)) as r:
shutil.copyfileobj(r, temp_file)
except urllib.error.URLError as e:
raise ConnectionError(e) from None
def http_get(
url, temp_file, proxies=None, resume_size=0, headers=None, cookies=None, timeout=100.0, max_retries=0, desc=None
):
headers = copy.deepcopy(headers) or {}
headers["user-agent"] = get_datasets_user_agent(user_agent=headers.get("user-agent"))
if resume_size > 0:
headers["Range"] = f"bytes={resume_size:d}-"
response = _request_with_retry(
method="GET",
url=url,
stream=True,
proxies=proxies,
headers=headers,
cookies=cookies,
max_retries=max_retries,
timeout=timeout,
)
if response.status_code == 416: # Range not satisfiable
return
content_length = response.headers.get("Content-Length")
total = resume_size + int(content_length) if content_length is not None else None
with logging.tqdm(
unit="B",
unit_scale=True,
total=total,
initial=resume_size,
desc=desc or "Downloading",
disable=not logging.is_progress_bar_enabled(),
) as progress:
for chunk in response.iter_content(chunk_size=1024):
progress.update(len(chunk))
temp_file.write(chunk)
def http_head(
url, proxies=None, headers=None, cookies=None, allow_redirects=True, timeout=10.0, max_retries=0
) -> requests.Response:
headers = copy.deepcopy(headers) or {}
headers["user-agent"] = get_datasets_user_agent(user_agent=headers.get("user-agent"))
response = _request_with_retry(
method="HEAD",
url=url,
proxies=proxies,
headers=headers,
cookies=cookies,
allow_redirects=allow_redirects,
timeout=timeout,
max_retries=max_retries,
)
return response
def request_etag(url: str, use_auth_token: Optional[Union[str, bool]] = None) -> Optional[str]:
headers = get_authentication_headers_for_url(url, use_auth_token=use_auth_token)
response = http_head(url, headers=headers, max_retries=3)
response.raise_for_status()
etag = response.headers.get("ETag") if response.ok else None
return etag
def get_from_cache(
url,
cache_dir=None,
force_download=False,
proxies=None,
etag_timeout=100,
resume_download=False,
user_agent=None,
local_files_only=False,
use_etag=True,
max_retries=0,
use_auth_token=None,
ignore_url_params=False,
download_desc=None,
) -> str:
"""
Given a URL, look for the corresponding file in the local cache.
If it's not there, download it. Then return the path to the cached file.
Return:
Local path (string)
Raises:
FileNotFoundError: in case of non-recoverable file
(non-existent or no cache on disk)
ConnectionError: in case of unreachable url
and no cache on disk
"""
if cache_dir is None:
cache_dir = config.HF_EVALUATE_CACHE
if isinstance(cache_dir, Path):
cache_dir = str(cache_dir)
os.makedirs(cache_dir, exist_ok=True)
if ignore_url_params:
# strip all query parameters and #fragments from the URL
cached_url = urljoin(url, urlparse(url).path)
else:
cached_url = url # additional parameters may be added to the given URL
connected = False
response = None
cookies = None
etag = None
head_error = None
# Try a first time to file the file on the local file system without eTag (None)
# if we don't ask for 'force_download' then we spare a request
filename = hash_url_to_filename(cached_url, etag=None)
cache_path = os.path.join(cache_dir, filename)
if os.path.exists(cache_path) and not force_download and not use_etag:
return cache_path
# Prepare headers for authentication
headers = get_authentication_headers_for_url(url, use_auth_token=use_auth_token)
if user_agent is not None:
headers["user-agent"] = user_agent
# We don't have the file locally or we need an eTag
if not local_files_only:
if url.startswith("ftp://"):
connected = ftp_head(url)
try:
response = http_head(
url,
allow_redirects=True,
proxies=proxies,
timeout=etag_timeout,
max_retries=max_retries,
headers=headers,
)
if response.status_code == 200: # ok
etag = response.headers.get("ETag") if use_etag else None
for k, v in response.cookies.items():
# In some edge cases, we need to get a confirmation token
if k.startswith("download_warning") and "drive.google.com" in url:
url += "&confirm=" + v
cookies = response.cookies
connected = True
# Fix Google Drive URL to avoid Virus scan warning
if "drive.google.com" in url and "confirm=" not in url:
url += "&confirm=t"
# In some edge cases, head request returns 400 but the connection is actually ok
elif (
(response.status_code == 400 and "firebasestorage.googleapis.com" in url)
or (response.status_code == 405 and "drive.google.com" in url)
or (
response.status_code == 403
and (
re.match(r"^https?://github.com/.*?/.*?/releases/download/.*?/.*?$", url)
or re.match(r"^https://.*?s3.*?amazonaws.com/.*?$", response.url)
)
)
or (response.status_code == 403 and "ndownloader.figstatic.com" in url)
):
connected = True
logger.info(f"Couldn't get ETag version for url {url}")
elif response.status_code == 401 and config.HF_ENDPOINT in url and use_auth_token is None:
raise ConnectionError(
f"Unauthorized for URL {url}. Please use the parameter ``use_auth_token=True`` after logging in with ``huggingface-cli login``"
)
except (OSError, requests.exceptions.Timeout) as e:
# not connected
head_error = e
pass
# connected == False = we don't have a connection, or url doesn't exist, or is otherwise inaccessible.
# try to get the last downloaded one
if not connected:
if os.path.exists(cache_path) and not force_download:
return cache_path
if local_files_only:
raise FileNotFoundError(
f"Cannot find the requested files in the cached path at {cache_path} and outgoing traffic has been"
" disabled. To enable file online look-ups, set 'local_files_only' to False."
)
elif response is not None and response.status_code == 404:
raise FileNotFoundError(f"Couldn't find file at {url}")
_raise_if_offline_mode_is_enabled(f"Tried to reach {url}")
if head_error is not None:
raise ConnectionError(f"Couldn't reach {url} ({repr(head_error)})")
elif response is not None:
raise ConnectionError(f"Couldn't reach {url} (error {response.status_code})")
else:
raise ConnectionError(f"Couldn't reach {url}")
# Try a second time
filename = hash_url_to_filename(cached_url, etag)
cache_path = os.path.join(cache_dir, filename)
if os.path.exists(cache_path) and not force_download:
return cache_path
# From now on, connected is True.
# Prevent parallel downloads of the same file with a lock.
lock_path = cache_path + ".lock"
with FileLock(lock_path):
if resume_download:
incomplete_path = cache_path + ".incomplete"
@contextmanager
def _resumable_file_manager():
with open(incomplete_path, "a+b") as f:
yield f
temp_file_manager = _resumable_file_manager
if os.path.exists(incomplete_path):
resume_size = os.stat(incomplete_path).st_size
else:
resume_size = 0
else:
temp_file_manager = partial(tempfile.NamedTemporaryFile, dir=cache_dir, delete=False)
resume_size = 0
# Download to temporary file, then copy to cache dir once finished.
# Otherwise you get corrupt cache entries if the download gets interrupted.
with temp_file_manager() as temp_file:
logger.info(f"{url} not found in cache or force_download set to True, downloading to {temp_file.name}")
# GET file object
if url.startswith("ftp://"):
ftp_get(url, temp_file)
else:
http_get(
url,
temp_file,
proxies=proxies,
resume_size=resume_size,
headers=headers,
cookies=cookies,
max_retries=max_retries,
desc=download_desc,
)
logger.info(f"storing {url} in cache at {cache_path}")
shutil.move(temp_file.name, cache_path)
logger.info(f"creating metadata file for {cache_path}")
meta = {"url": url, "etag": etag}
meta_path = cache_path + ".json"
with open(meta_path, "w", encoding="utf-8") as meta_file:
json.dump(meta, meta_file)
return cache_path
def add_start_docstrings(*docstr):
def docstring_decorator(fn):
fn.__doc__ = "".join(docstr) + "\n\n" + (fn.__doc__ if fn.__doc__ is not None else "")
return fn
return docstring_decorator
def add_end_docstrings(*docstr):
def docstring_decorator(fn):
fn.__doc__ = (fn.__doc__ if fn.__doc__ is not None else "") + "\n\n" + "".join(docstr)
return fn
return docstring_decorator
def estimate_dataset_size(paths):
return sum(path.stat().st_size for path in paths)
def readline(f: io.RawIOBase):
# From: https://github.com/python/cpython/blob/d27e2f4d118e7a9909b6a3e5da06c5ff95806a85/Lib/_pyio.py#L525
res = bytearray()
while True:
b = f.read(1)
if not b:
break
res += b
if res.endswith(b"\n"):
break
return bytes(res)