import importlib.util
import json
import logging
import os
import shutil
import tarfile
import tempfile
from functools import partial
from hashlib import sha256
from pathlib import Path
from typing import Any, BinaryIO, Dict, List, Optional, Union
from urllib.parse import urlparse
from zipfile import ZipFile, is_zipfile
import huggingface_hub
import requests
import tqdm
from filelock import FileLock
from transformers.utils.hub import cached_file as hf_cached_file
from relik.common.log import get_logger
# name constants
WEIGHTS_NAME = "weights.pt"
ONNX_WEIGHTS_NAME = "weights.onnx"
CONFIG_NAME = "config.yaml"
LABELS_NAME = "labels.json"
# SAPIENZANLP_USER_NAME = "sapienzanlp"
SAPIENZANLP_USER_NAME = "riccorl"
SAPIENZANLP_HF_MODEL_REPO_URL = "riccorl/{model_id}"
SAPIENZANLP_HF_MODEL_REPO_ARCHIVE_URL = (
f"{SAPIENZANLP_HF_MODEL_REPO_URL}/resolve/main/model.zip"
)
# path constants
SAPIENZANLP_CACHE_DIR = os.getenv("SAPIENZANLP_CACHE_DIR", Path.home() / ".sapienzanlp")
SAPIENZANLP_DATE_FORMAT = "%Y-%m-%d %H-%M-%S"
logger = get_logger(__name__)
def sapienzanlp_model_urls(model_id: str) -> str:
"""
Returns the URL for a possible SapienzaNLP valid model.
Args:
model_id (:obj:`str`):
A SapienzaNLP model id.
Returns:
:obj:`str`: The url for the model id.
"""
# check if there is already the namespace of the user
if "/" in model_id:
return model_id
return SAPIENZANLP_HF_MODEL_REPO_URL.format(model_id=model_id)
def is_package_available(package_name: str) -> bool:
"""
Check if a package is available.
Args:
package_name (`str`): The name of the package to check.
"""
return importlib.util.find_spec(package_name) is not None
def load_json(path: Union[str, Path]) -> Any:
"""
Load a json file provided in input.
Args:
path (`Union[str, Path]`): The path to the json file to load.
Returns:
`Any`: The loaded json file.
"""
with open(path, encoding="utf8") as f:
return json.load(f)
def dump_json(document: Any, path: Union[str, Path], indent: Optional[int] = None):
"""
Dump input to json file.
Args:
document (`Any`): The document to dump.
path (`Union[str, Path]`): The path to dump the document to.
indent (`Optional[int]`): The indent to use for the json file.
"""
with open(path, "w", encoding="utf8") as outfile:
json.dump(document, outfile, indent=indent)
def get_md5(path: Path):
"""
Get the MD5 value of a path.
"""
import hashlib
with path.open("rb") as fin:
data = fin.read()
return hashlib.md5(data).hexdigest()
def file_exists(path: Union[str, os.PathLike]) -> bool:
"""
Check if the file at :obj:`path` exists.
Args:
path (:obj:`str`, :obj:`os.PathLike`):
Path to check.
Returns:
:obj:`bool`: :obj:`True` if the file exists.
"""
return Path(path).exists()
def dir_exists(path: Union[str, os.PathLike]) -> bool:
"""
Check if the directory at :obj:`path` exists.
Args:
path (:obj:`str`, :obj:`os.PathLike`):
Path to check.
Returns:
:obj:`bool`: :obj:`True` if the directory exists.
"""
return Path(path).is_dir()
def is_remote_url(url_or_filename: Union[str, Path]):
"""
Returns :obj:`True` if the input path is an url.
Args:
url_or_filename (:obj:`str`, :obj:`Path`):
path to check.
Returns:
:obj:`bool`: :obj:`True` if the input path is an url, :obj:`False` otherwise.
"""
if isinstance(url_or_filename, Path):
url_or_filename = str(url_or_filename)
parsed = urlparse(url_or_filename)
return parsed.scheme in ("http", "https")
def url_to_filename(resource: str, etag: str = None) -> str:
"""
Convert a `resource` into a hashed filename in a repeatable way.
If `etag` is specified, append its hash to the resources's, delimited
by a period.
"""
resource_bytes = resource.encode("utf-8")
resource_hash = sha256(resource_bytes)
filename = resource_hash.hexdigest()
if etag:
etag_bytes = etag.encode("utf-8")
etag_hash = sha256(etag_bytes)
filename += "." + etag_hash.hexdigest()
return filename
def download_resource(
url: str,
temp_file: BinaryIO,
headers=None,
):
"""
Download remote file.
"""
if headers is None:
headers = {}
r = requests.get(url, stream=True, headers=headers)
r.raise_for_status()
content_length = r.headers.get("Content-Length")
total = int(content_length) if content_length is not None else None
progress = tqdm(
unit="B",
unit_scale=True,
total=total,
desc="Downloading",
disable=logger.level in [logging.NOTSET],
)
for chunk in r.iter_content(chunk_size=1024):
if chunk: # filter out keep-alive new chunks
progress.update(len(chunk))
temp_file.write(chunk)
progress.close()
def download_and_cache(
url: Union[str, Path],
cache_dir: Union[str, Path] = None,
force_download: bool = False,
):
if cache_dir is None:
cache_dir = SAPIENZANLP_CACHE_DIR
if isinstance(url, Path):
url = str(url)
# check if cache dir exists
Path(cache_dir).mkdir(parents=True, exist_ok=True)
# check if file is private
headers = {}
try:
r = requests.head(url, allow_redirects=False, timeout=10)
r.raise_for_status()
except requests.exceptions.HTTPError:
if r.status_code == 401:
hf_token = huggingface_hub.HfFolder.get_token()
if hf_token is None:
raise ValueError(
"You need to login to HuggingFace to download this model "
"(use the `huggingface-cli login` command)"
)
headers["Authorization"] = f"Bearer {hf_token}"
etag = None
try:
r = requests.head(url, allow_redirects=True, timeout=10, headers=headers)
r.raise_for_status()
etag = r.headers.get("X-Linked-Etag") or r.headers.get("ETag")
# We favor a custom header indicating the etag of the linked resource, and
# we fallback to the regular etag header.
# If we don't have any of those, raise an error.
if etag is None:
raise OSError(
"Distant resource does not have an ETag, we won't be able to reliably ensure reproducibility."
)
# In case of a redirect,
# save an extra redirect on the request.get call,
# and ensure we download the exact atomic version even if it changed
# between the HEAD and the GET (unlikely, but hey).
if 300 <= r.status_code <= 399:
url = r.headers["Location"]
except (requests.exceptions.SSLError, requests.exceptions.ProxyError):
# Actually raise for those subclasses of ConnectionError
raise
except (requests.exceptions.ConnectionError, requests.exceptions.Timeout):
# Otherwise, our Internet connection is down.
# etag is None
pass
# get filename from the url
filename = url_to_filename(url, etag)
# get cache path to put the file
cache_path = cache_dir / filename
# the file is already here, return it
if file_exists(cache_path) and not force_download:
logger.info(
f"{url} found in cache, set `force_download=True` to force the download"
)
return cache_path
cache_path = str(cache_path)
# Prevent parallel downloads of the same file with a lock.
lock_path = cache_path + ".lock"
with FileLock(lock_path):
# If the download just completed while the lock was activated.
if file_exists(cache_path) and not force_download:
# Even if returning early like here, the lock will be released.
return cache_path
temp_file_manager = partial(
tempfile.NamedTemporaryFile, mode="wb", dir=cache_dir, delete=False
)
# 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}"
)
download_resource(url, temp_file, headers)
logger.info(f"storing {url} in cache at {cache_path}")
os.replace(temp_file.name, cache_path)
# NamedTemporaryFile creates a file with hardwired 0600 perms (ignoring umask), so fixing it.
umask = os.umask(0o666)
os.umask(umask)
os.chmod(cache_path, 0o666 & ~umask)
logger.info(f"creating metadata file for {cache_path}")
meta = {"url": url} # , "etag": etag}
meta_path = cache_path + ".json"
with open(meta_path, "w") as meta_file:
json.dump(meta, meta_file)
return cache_path
def download_from_hf(
path_or_repo_id: Union[str, Path],
filenames: Optional[List[str]],
cache_dir: Union[str, Path] = None,
force_download: bool = False,
resume_download: bool = False,
proxies: Optional[Dict[str, str]] = None,
use_auth_token: Optional[Union[bool, str]] = None,
revision: Optional[str] = None,
local_files_only: bool = False,
subfolder: str = "",
):
if isinstance(path_or_repo_id, Path):
path_or_repo_id = str(path_or_repo_id)
downloaded_paths = []
for filename in filenames:
downloaded_path = hf_cached_file(
path_or_repo_id,
filename,
cache_dir=cache_dir,
force_download=force_download,
proxies=proxies,
resume_download=resume_download,
use_auth_token=use_auth_token,
revision=revision,
local_files_only=local_files_only,
subfolder=subfolder,
)
downloaded_paths.append(downloaded_path)
# we want the folder where the files are downloaded
# the best guess is the parent folder of the first file
probably_the_folder = Path(downloaded_paths[0]).parent
return probably_the_folder
def model_name_or_path_resolver(model_name_or_dir: Union[str, os.PathLike]) -> str:
"""
Resolve a model name or directory to a model archive name or directory.
Args:
model_name_or_dir (:obj:`str` or :obj:`os.PathLike`):
A model name or directory.
Returns:
:obj:`str`: The model archive name or directory.
"""
if is_remote_url(model_name_or_dir):
# if model_name_or_dir is a URL
# download it and try to load
model_archive = model_name_or_dir
elif Path(model_name_or_dir).is_dir() or Path(model_name_or_dir).is_file():
# if model_name_or_dir is a local directory or
# an archive file try to load it
model_archive = model_name_or_dir
else:
# probably model_name_or_dir is a sapienzanlp model id
# guess the url and try to download
model_name_or_dir_ = model_name_or_dir
# raise ValueError(f"Providing a model id is not supported yet.")
model_archive = sapienzanlp_model_urls(model_name_or_dir_)
return model_archive
def from_cache(
url_or_filename: Union[str, Path],
cache_dir: Union[str, Path] = None,
force_download: bool = False,
resume_download: bool = False,
proxies: Optional[Dict[str, str]] = None,
use_auth_token: Optional[Union[bool, str]] = None,
revision: Optional[str] = None,
local_files_only: bool = False,
subfolder: str = "",
filenames: Optional[List[str]] = None,
) -> Path:
"""
Given something that could be either a local path or a URL (or a SapienzaNLP model id),
determine which one and return a path to the corresponding file.
Args:
url_or_filename (:obj:`str` or :obj:`Path`):
A path to a local file or a URL (or a SapienzaNLP model id).
cache_dir (:obj:`str` or :obj:`Path`, `optional`):
Path to a directory in which a downloaded file will be cached.
force_download (:obj:`bool`, `optional`, defaults to :obj:`False`):
Whether or not to re-download the file even if it already exists.
resume_download (:obj:`bool`, `optional`, defaults to :obj:`False`):
Whether or not to delete incompletely received files. Attempts to resume the download if such a file
exists.
proxies (:obj:`Dict[str, str]`, `optional`):
A dictionary of proxy servers to use by protocol or endpoint, e.g., :obj:`{'http': 'foo.bar:3128',
'http://hostname': 'foo.bar:4012'}.` The proxies are used on each request.
use_auth_token (:obj:`Union[bool, str]`, `optional`):
Optional string or boolean to use as Bearer token for remote files. If :obj:`True`, will get token from
:obj:`~transformers.hf_api.HfApi`. If :obj:`str`, will use that string as token.
revision (:obj:`str`, `optional`):
The specific model version to use. It can be a branch name, a tag name, or a commit id, since we use a
git-based system for storing models and other artifacts on huggingface.co, so ``revision`` can be any
identifier allowed by git.
local_files_only (:obj:`bool`, `optional`, defaults to :obj:`False`):
Whether or not to raise an error if the file to be downloaded is local.
subfolder (:obj:`str`, `optional`):
In case the relevant file is in a subfolder of the URL, specify it here.
filenames (:obj:`List[str]`, `optional`):
List of filenames to look for in the directory structure.
Returns:
:obj:`Path`: Path to the cached file.
"""
url_or_filename = model_name_or_path_resolver(url_or_filename)
if cache_dir is None:
cache_dir = SAPIENZANLP_CACHE_DIR
if file_exists(url_or_filename):
logger.info(f"{url_or_filename} is a local path or file")
output_path = url_or_filename
elif is_remote_url(url_or_filename):
# URL, so get it from the cache (downloading if necessary)
output_path = download_and_cache(
url_or_filename,
cache_dir=cache_dir,
force_download=force_download,
)
else:
if filenames is None:
filenames = [WEIGHTS_NAME, CONFIG_NAME, LABELS_NAME]
output_path = download_from_hf(
url_or_filename,
filenames,
cache_dir,
force_download,
resume_download,
proxies,
use_auth_token,
revision,
local_files_only,
subfolder,
)
# if is_hf_hub_url(url_or_filename):
# HuggingFace Hub
# output_path = hf_hub_download_url(url_or_filename)
# elif is_remote_url(url_or_filename):
# # URL, so get it from the cache (downloading if necessary)
# output_path = download_and_cache(
# url_or_filename,
# cache_dir=cache_dir,
# force_download=force_download,
# )
# elif file_exists(url_or_filename):
# logger.info(f"{url_or_filename} is a local path or file")
# # File, and it exists.
# output_path = url_or_filename
# elif urlparse(url_or_filename).scheme == "":
# # File, but it doesn't exist.
# raise EnvironmentError(f"file {url_or_filename} not found")
# else:
# # Something unknown
# raise ValueError(
# f"unable to parse {url_or_filename} as a URL or as a local path"
# )
if dir_exists(output_path) or (
not is_zipfile(output_path) and not tarfile.is_tarfile(output_path)
):
return Path(output_path)
# Path where we extract compressed archives
# for now it will extract it in the same folder
# maybe implement extraction in the sapienzanlp folder
# when using local archive path?
logger.info("Extracting compressed archive")
output_dir, output_file = os.path.split(output_path)
output_extract_dir_name = output_file.replace(".", "-") + "-extracted"
output_path_extracted = os.path.join(output_dir, output_extract_dir_name)
# already extracted, do not extract
if (
os.path.isdir(output_path_extracted)
and os.listdir(output_path_extracted)
and not force_download
):
return Path(output_path_extracted)
# Prevent parallel extractions
lock_path = output_path + ".lock"
with FileLock(lock_path):
shutil.rmtree(output_path_extracted, ignore_errors=True)
os.makedirs(output_path_extracted)
if is_zipfile(output_path):
with ZipFile(output_path, "r") as zip_file:
zip_file.extractall(output_path_extracted)
zip_file.close()
elif tarfile.is_tarfile(output_path):
tar_file = tarfile.open(output_path)
tar_file.extractall(output_path_extracted)
tar_file.close()
else:
raise EnvironmentError(
f"Archive format of {output_path} could not be identified"
)
# remove lock file, is it safe?
os.remove(lock_path)
return Path(output_path_extracted)
def is_str_a_path(maybe_path: str) -> bool:
"""
Check if a string is a path.
Args:
maybe_path (`str`): The string to check.
Returns:
`bool`: `True` if the string is a path, `False` otherwise.
"""
# first check if it is a path
if Path(maybe_path).exists():
return True
# check if it is a relative path
if Path(os.path.join(os.getcwd(), maybe_path)).exists():
return True
# otherwise it is not a path
return False
def relative_to_absolute_path(path: str) -> os.PathLike:
"""
Convert a relative path to an absolute path.
Args:
path (`str`): The relative path to convert.
Returns:
`os.PathLike`: The absolute path.
"""
if not is_str_a_path(path):
raise ValueError(f"{path} is not a path")
if Path(path).exists():
return Path(path).absolute()
if Path(os.path.join(os.getcwd(), path)).exists():
return Path(os.path.join(os.getcwd(), path)).absolute()
raise ValueError(f"{path} is not a path")
def to_config(object_to_save: Any) -> Dict[str, Any]:
"""
Convert an object to a dictionary.
Returns:
`Dict[str, Any]`: The dictionary representation of the object.
"""
def obj_to_dict(obj):
match obj:
case dict():
data = {}
for k, v in obj.items():
data[k] = obj_to_dict(v)
return data
case list() | tuple():
return [obj_to_dict(x) for x in obj]
case object(__dict__=_):
data = {
"_target_": f"{obj.__class__.__module__}.{obj.__class__.__name__}",
}
for k, v in obj.__dict__.items():
if not k.startswith("_"):
data[k] = obj_to_dict(v)
return data
case _:
return obj
return obj_to_dict(object_to_save)
def get_callable_from_string(callable_fn: str) -> Any:
"""
Get a callable from a string.
Args:
callable_fn (`str`):
The string representation of the callable.
Returns:
`Any`: The callable.
"""
# separate the function name from the module name
module_name, function_name = callable_fn.rsplit(".", 1)
# import the module
module = importlib.import_module(module_name)
# get the function
return getattr(module, function_name)