Re-add support for single url files in objects download (#19014)

src/transformers/configuration_utils.py

@@ -32,7 +32,9 @@
     PushToHubMixin,
     cached_file,
     copy_func,
+    download_url,
     extract_commit_hash,
+    is_remote_url,
     is_torch_available,
     logging,
 )
@@ -592,9 +594,12 @@ def _get_config_dict(
 
         is_local = os.path.isdir(pretrained_model_name_or_path)
         if os.path.isfile(os.path.join(subfolder, pretrained_model_name_or_path)):
-            # Soecial case when pretrained_model_name_or_path is a local file
+            # Special case when pretrained_model_name_or_path is a local file
             resolved_config_file = pretrained_model_name_or_path
             is_local = True
+        elif is_remote_url(pretrained_model_name_or_path):
+            configuration_file = pretrained_model_name_or_path
+            resolved_config_file = download_url(pretrained_model_name_or_path)
         else:
             configuration_file = kwargs.pop("_configuration_file", CONFIG_NAME)
 

src/transformers/feature_extraction_utils.py

@@ -31,8 +31,10 @@
     TensorType,
     cached_file,
     copy_func,
+    download_url,
     is_flax_available,
     is_offline_mode,
+    is_remote_url,
     is_tf_available,
     is_torch_available,
     logging,
@@ -386,6 +388,9 @@ def get_feature_extractor_dict(
         if os.path.isfile(pretrained_model_name_or_path):
             resolved_feature_extractor_file = pretrained_model_name_or_path
             is_local = True
+        elif is_remote_url(pretrained_model_name_or_path):
+            feature_extractor_file = pretrained_model_name_or_path
+            resolved_feature_extractor_file = download_url(pretrained_model_name_or_path)
         else:
             feature_extractor_file = FEATURE_EXTRACTOR_NAME
             try:

src/transformers/modeling_flax_utils.py

@@ -47,8 +47,10 @@
     add_start_docstrings_to_model_forward,
     cached_file,
     copy_func,
+    download_url,
     has_file,
     is_offline_mode,
+    is_remote_url,
     logging,
     replace_return_docstrings,
 )
@@ -677,6 +679,9 @@ def from_pretrained(
             elif os.path.isfile(pretrained_model_name_or_path):
                 archive_file = pretrained_model_name_or_path
                 is_local = True
+            elif is_remote_url(pretrained_model_name_or_path):
+                archive_file = pretrained_model_name_or_path
+                resolved_archive_file = download_url(pretrained_model_name_or_path)
             else:
                 filename = WEIGHTS_NAME if from_pt else FLAX_WEIGHTS_NAME
                 try:

src/transformers/modeling_tf_utils.py

@@ -54,9 +54,11 @@
     ModelOutput,
     PushToHubMixin,
     cached_file,
+    download_url,
     find_labels,
     has_file,
     is_offline_mode,
+    is_remote_url,
     logging,
     requires_backends,
     working_or_temp_dir,
@@ -2345,6 +2347,9 @@ def from_pretrained(cls, pretrained_model_name_or_path, *model_args, **kwargs):
             elif os.path.isfile(pretrained_model_name_or_path + ".index"):
                 archive_file = pretrained_model_name_or_path + ".index"
                 is_local = True
+            elif is_remote_url(pretrained_model_name_or_path):
+                archive_file = pretrained_model_name_or_path
+                resolved_archive_file = download_url(pretrained_model_name_or_path)
             else:
                 # set correct filename
                 filename = WEIGHTS_NAME if from_pt else TF2_WEIGHTS_NAME

src/transformers/modeling_utils.py

@@ -59,10 +59,12 @@
     PushToHubMixin,
     cached_file,
     copy_func,
+    download_url,
     has_file,
     is_accelerate_available,
     is_bitsandbytes_available,
     is_offline_mode,
+    is_remote_url,
     logging,
     replace_return_docstrings,
 )
@@ -1998,6 +2000,9 @@ def from_pretrained(cls, pretrained_model_name_or_path: Optional[Union[str, os.P
                     )
                 archive_file = os.path.join(subfolder, pretrained_model_name_or_path + ".index")
                 is_local = True
+            elif is_remote_url(pretrained_model_name_or_path):
+                archive_file = pretrained_model_name_or_path
+                resolved_archive_file = download_url(pretrained_model_name_or_path)
             else:
                 # set correct filename
                 if from_tf:

src/transformers/tokenization_utils_base.py

@@ -42,9 +42,11 @@
     add_end_docstrings,
     cached_file,
     copy_func,
+    download_url,
     extract_commit_hash,
     is_flax_available,
     is_offline_mode,
+    is_remote_url,
     is_tf_available,
     is_tokenizers_available,
     is_torch_available,
@@ -1680,6 +1682,7 @@ def from_pretrained(cls, pretrained_model_name_or_path: Union[str, os.PathLike],
                 FutureWarning,
             )
             file_id = list(cls.vocab_files_names.keys())[0]
+
             vocab_files[file_id] = pretrained_model_name_or_path
         else:
             # At this point pretrained_model_name_or_path is either a directory or a model identifier name
@@ -1723,6 +1726,8 @@ def from_pretrained(cls, pretrained_model_name_or_path: Union[str, os.PathLike],
         for file_id, file_path in vocab_files.items():
             if file_path is None:
                 resolved_vocab_files[file_id] = None
+            elif is_remote_url(file_path):
+                resolved_vocab_files[file_id] = download_url(file_path, proxies=proxies)
             else:
                 resolved_vocab_files[file_id] = cached_file(
                     pretrained_model_name_or_path,

src/transformers/utils/__init__.py

@@ -63,13 +63,15 @@
     cached_file,
     default_cache_path,
     define_sagemaker_information,
+    download_url,
     extract_commit_hash,
     get_cached_models,
     get_file_from_repo,
     get_full_repo_name,
     has_file,
     http_user_agent,
     is_offline_mode,
+    is_remote_url,
     move_cache,
     send_example_telemetry,
 )

src/transformers/utils/hub.py

@@ -19,10 +19,12 @@
 import re
 import shutil
 import sys
+import tempfile
 import traceback
 import warnings
 from pathlib import Path
 from typing import Dict, List, Optional, Tuple, Union
+from urllib.parse import urlparse
 from uuid import uuid4
 
 import huggingface_hub
@@ -37,7 +39,7 @@
     whoami,
 )
 from huggingface_hub.constants import HUGGINGFACE_HEADER_X_LINKED_ETAG, HUGGINGFACE_HEADER_X_REPO_COMMIT
-from huggingface_hub.file_download import REGEX_COMMIT_HASH
+from huggingface_hub.file_download import REGEX_COMMIT_HASH, http_get
 from huggingface_hub.utils import (
     EntryNotFoundError,
     LocalEntryNotFoundError,
@@ -124,6 +126,11 @@ def is_offline_mode():
 _CACHED_NO_EXIST = object()
 
 
+def is_remote_url(url_or_filename):
+    parsed = urlparse(url_or_filename)
+    return parsed.scheme in ("http", "https")
+
+
 def get_cached_models(cache_dir: Union[str, Path] = None) -> List[Tuple]:
     """
     Returns a list of tuples representing model binaries that are cached locally. Each tuple has shape `(model_url,
@@ -541,6 +548,32 @@ def get_file_from_repo(
     )
 
 
+def download_url(url, proxies=None):
+    """
+    Downloads a given url in a temporary file. This function is not safe to use in multiple processes. Its only use is
+    for deprecated behavior allowing to download config/models with a single url instead of using the Hub.
+
+    Args:
+        url (`str`): The url of the file to download.
+        proxies (`Dict[str, str]`, *optional*):
+            A dictionary of proxy servers to use by protocol or endpoint, e.g., `{'http': 'foo.bar:3128',
+            'http://hostname': 'foo.bar:4012'}.` The proxies are used on each request.
+
+    Returns:
+        `str`: The location of the temporary file where the url was downloaded.
+    """
+    warnings.warn(
+        f"Using `from_pretrained` with the url of a file (here {url}) is deprecated and won't be possible anymore in"
+        " v5 of Transformers. You should host your file on the Hub (hf.co) instead and use the repository ID. Note"
+        " that this is not compatible with the caching system (your file will be downloaded at each execution) or"
+        " multiple processes (each process will download the file in a different temporary file)."
+    )
+    tmp_file = tempfile.mktemp()
+    with open(tmp_file, "wb") as f:
+        http_get(url, f, proxies=proxies)
+    return tmp_file
+
+
 def has_file(
     path_or_repo: Union[str, os.PathLike],
     filename: str,