Use commit hash to look in cache instead of calling head

src/transformers/configuration_utils.py

@@ -27,7 +27,15 @@
 
 from . import __version__
 from .dynamic_module_utils import custom_object_save
-from .utils import CONFIG_NAME, PushToHubMixin, cached_file, copy_func, is_torch_available, logging
+from .utils import (
+    CONFIG_NAME,
+    PushToHubMixin,
+    cached_file,
+    copy_func,
+    extract_commit_hash,
+    is_torch_available,
+    logging,
+)
 
 
 logger = logging.get_logger(__name__)
@@ -343,6 +351,8 @@ def __init__(self, **kwargs):
 
         # Name or path to the pretrained checkpoint
         self._name_or_path = str(kwargs.pop("name_or_path", ""))
+        # Config hash
+        self._commit_hash = kwargs.pop("_commit_hash", None)
 
         # Drop the transformers version info
         self.transformers_version = kwargs.pop("transformers_version", None)
@@ -539,6 +549,8 @@ def get_config_dict(
         original_kwargs = copy.deepcopy(kwargs)
         # Get config dict associated with the base config file
         config_dict, kwargs = cls._get_config_dict(pretrained_model_name_or_path, **kwargs)
+        if "_commit_hash" in config_dict:
+            original_kwargs["_commit_hash"] = config_dict["_commit_hash"]
 
         # That config file may point us toward another config file to use.
         if "configuration_files" in config_dict:
@@ -564,6 +576,7 @@ def _get_config_dict(
         subfolder = kwargs.pop("subfolder", "")
         from_pipeline = kwargs.pop("_from_pipeline", None)
         from_auto_class = kwargs.pop("_from_auto", False)
+        commit_hash = kwargs.pop("_commit_hash", None)
 
         if trust_remote_code is True:
             logger.warning(
@@ -599,7 +612,9 @@ def _get_config_dict(
                     user_agent=user_agent,
                     revision=revision,
                     subfolder=subfolder,
+                    _commit_hash=commit_hash,
                 )
+                commit_hash = extract_commit_hash(resolved_config_file, commit_hash)
             except EnvironmentError:
                 # Raise any environment error raise by `cached_file`. It will have a helpful error message adapted to
                 # the original exception.
@@ -616,6 +631,7 @@ def _get_config_dict(
         try:
             # Load config dict
             config_dict = cls._dict_from_json_file(resolved_config_file)
+            config_dict["_commit_hash"] = commit_hash
         except (json.JSONDecodeError, UnicodeDecodeError):
             raise EnvironmentError(
                 f"It looks like the config file at '{resolved_config_file}' is not a valid JSON file."
@@ -648,6 +664,9 @@ def from_dict(cls, config_dict: Dict[str, Any], **kwargs) -> "PretrainedConfig":
         # We remove them so they don't appear in `return_unused_kwargs`.
         kwargs.pop("_from_auto", None)
         kwargs.pop("_from_pipeline", None)
+        # The commit hash might have been updated in the `config_dict`, we don't want the kwargs to erase that update.
+        if "_commit_hash" in kwargs and "_commit_hash" in config_dict:
+            kwargs["_commit_hash"] = config_dict["_commit_hash"]
 
         config = cls(**config_dict)
 
@@ -751,6 +770,8 @@ def to_dict(self) -> Dict[str, Any]:
             output["model_type"] = self.__class__.model_type
         if "_auto_class" in output:
             del output["_auto_class"]
+        if "_commit_hash" in output:
+            del output["_commit_hash"]
 
         # Transformers version when serializing the model
         output["transformers_version"] = __version__

src/transformers/modeling_flax_utils.py

@@ -595,6 +595,7 @@ def from_pretrained(
         from_auto_class = kwargs.pop("_from_auto", False)
         _do_init = kwargs.pop("_do_init", True)
         subfolder = kwargs.pop("subfolder", "")
+        commit_hash = kwargs.pop("_commit_hash", None)
 
         if trust_remote_code is True:
             logger.warning(
@@ -625,11 +626,15 @@ def from_pretrained(
                 revision=revision,
                 _from_auto=from_auto_class,
                 _from_pipeline=from_pipeline,
+                _commit_hash=commit_hash,
                 **kwargs,
             )
         else:
             model_kwargs = kwargs
 
+        if commit_hash is None:
+            commit_hash = getattr(config, "_commit_hash", None)
+
         # Add the dtype to model_kwargs
         model_kwargs["dtype"] = dtype
 
@@ -682,6 +687,7 @@ def from_pretrained(
                         revision=revision,
                         subfolder=subfolder,
                         _raise_exceptions_for_missing_entries=False,
+                        _commit_hash=commit_hash,
                     )
                     resolved_archive_file = cached_file(pretrained_model_name_or_path, filename, **cached_file_kwargs)
 
@@ -748,6 +754,7 @@ def from_pretrained(
                 use_auth_token=use_auth_token,
                 user_agent=user_agent,
                 revision=revision,
+                _commit_hash=commit_hash,
             )
 
         # init random models

src/transformers/modeling_tf_utils.py

@@ -2161,6 +2161,7 @@ def from_pretrained(cls, pretrained_model_name_or_path, *model_args, **kwargs):
         from_pipeline = kwargs.pop("_from_pipeline", None)
         from_auto_class = kwargs.pop("_from_auto", False)
         subfolder = kwargs.pop("subfolder", "")
+        commit_hash = kwargs.pop("_commit_hash", None)
 
         if trust_remote_code is True:
             logger.warning(
@@ -2191,11 +2192,15 @@ def from_pretrained(cls, pretrained_model_name_or_path, *model_args, **kwargs):
                 revision=revision,
                 _from_auto=from_auto_class,
                 _from_pipeline=from_pipeline,
+                _commit_hash=commit_hash,
                 **kwargs,
             )
         else:
             model_kwargs = kwargs
 
+        if commit_hash is None:
+            commit_hash = getattr(config, "_commit_hash", None)
+
         # This variable will flag if we're loading a sharded checkpoint. In this case the archive file is just the
         # index of the files.
         is_sharded = False
@@ -2253,6 +2258,7 @@ def from_pretrained(cls, pretrained_model_name_or_path, *model_args, **kwargs):
                         revision=revision,
                         subfolder=subfolder,
                         _raise_exceptions_for_missing_entries=False,
+                        _commit_hash=commit_hash,
                     )
                     resolved_archive_file = cached_file(pretrained_model_name_or_path, filename, **cached_file_kwargs)
 
@@ -2320,6 +2326,7 @@ def from_pretrained(cls, pretrained_model_name_or_path, *model_args, **kwargs):
                 use_auth_token=use_auth_token,
                 user_agent=user_agent,
                 revision=revision,
+                _commit_hash=commit_hash,
             )
 
         config.name_or_path = pretrained_model_name_or_path

src/transformers/modeling_utils.py

@@ -1795,6 +1795,7 @@ def from_pretrained(cls, pretrained_model_name_or_path: Optional[Union[str, os.P
         offload_folder = kwargs.pop("offload_folder", None)
         offload_state_dict = kwargs.pop("offload_state_dict", None)
         subfolder = kwargs.pop("subfolder", "")
+        commit_hash = kwargs.pop("_commit_hash", None)
 
         if trust_remote_code is True:
             logger.warning(
@@ -1852,6 +1853,9 @@ def from_pretrained(cls, pretrained_model_name_or_path: Optional[Union[str, os.P
         else:
             model_kwargs = kwargs
 
+        if commit_hash is None:
+            commit_hash = getattr(config, "_commit_hash", None)
+
         # This variable will flag if we're loading a sharded checkpoint. In this case the archive file is just the
         # index of the files.
         is_sharded = False
@@ -1938,6 +1942,7 @@ def from_pretrained(cls, pretrained_model_name_or_path: Optional[Union[str, os.P
                         revision=revision,
                         subfolder=subfolder,
                         _raise_exceptions_for_missing_entries=False,
+                        _commit_hash=commit_hash,
                     )
                     resolved_archive_file = cached_file(pretrained_model_name_or_path, filename, **cached_file_kwargs)
 
@@ -2012,6 +2017,7 @@ def from_pretrained(cls, pretrained_model_name_or_path: Optional[Union[str, os.P
                 user_agent=user_agent,
                 revision=revision,
                 subfolder=subfolder,
+                _commit_hash=commit_hash,
             )
 
         # load pt weights early so that we know which dtype to init the model under

src/transformers/models/auto/tokenization_auto.py

@@ -25,7 +25,7 @@
 from ...tokenization_utils import PreTrainedTokenizer
 from ...tokenization_utils_base import TOKENIZER_CONFIG_FILE
 from ...tokenization_utils_fast import PreTrainedTokenizerFast
-from ...utils import get_file_from_repo, is_sentencepiece_available, is_tokenizers_available, logging
+from ...utils import cached_file, extract_commit_hash, is_sentencepiece_available, is_tokenizers_available, logging
 from ..encoder_decoder import EncoderDecoderConfig
 from .auto_factory import _LazyAutoMapping
 from .configuration_auto import (
@@ -389,7 +389,8 @@ def get_tokenizer_config(
     tokenizer.save_pretrained("tokenizer-test")
     tokenizer_config = get_tokenizer_config("tokenizer-test")
     ```"""
-    resolved_config_file = get_file_from_repo(
+    commit_hash = kwargs.get("_commit_hash", None)
+    resolved_config_file = cached_file(
         pretrained_model_name_or_path,
         TOKENIZER_CONFIG_FILE,
         cache_dir=cache_dir,
@@ -399,13 +400,19 @@ def get_tokenizer_config(
         use_auth_token=use_auth_token,
         revision=revision,
         local_files_only=local_files_only,
+        _raise_exceptions_for_missing_entries=False,
+        _raise_exceptions_for_connection_errors=False,
+        _commit_hash=commit_hash,
     )
     if resolved_config_file is None:
         logger.info("Could not locate the tokenizer configuration file, will try to use the model config instead.")
         return {}
+    commit_hash = extract_commit_hash(resolved_config_file, commit_hash)
 
     with open(resolved_config_file, encoding="utf-8") as reader:
-        return json.load(reader)
+        result = json.load(reader)
+    result["_commit_hash"] = commit_hash
+    return result
 
 
 class AutoTokenizer:
@@ -532,6 +539,8 @@ def from_pretrained(cls, pretrained_model_name_or_path, *inputs, **kwargs):
 
         # Next, let's try to use the tokenizer_config file to get the tokenizer class.
         tokenizer_config = get_tokenizer_config(pretrained_model_name_or_path, **kwargs)
+        if "_commit_hash" in tokenizer_config:
+            kwargs["_commit_hash"] = tokenizer_config["_commit_hash"]
         config_tokenizer_class = tokenizer_config.get("tokenizer_class")
         tokenizer_auto_map = None
         if "auto_map" in tokenizer_config:

src/transformers/pipelines/__init__.py

@@ -557,7 +557,12 @@ def pipeline(
     # Make sure we only pass use_auth_token once as a kwarg (it used to be possible to pass it in model_kwargs,
     # this is to keep BC).
     use_auth_token = model_kwargs.pop("use_auth_token", use_auth_token)
-    hub_kwargs = {"revision": revision, "use_auth_token": use_auth_token, "trust_remote_code": trust_remote_code}
+    hub_kwargs = {
+        "revision": revision,
+        "use_auth_token": use_auth_token,
+        "trust_remote_code": trust_remote_code,
+        "_commit_hash": None,
+    }
 
     if task is None and model is None:
         raise RuntimeError(
@@ -583,8 +588,10 @@ def pipeline(
     # Instantiate config if needed
     if isinstance(config, str):
         config = AutoConfig.from_pretrained(config, _from_pipeline=task, **hub_kwargs, **model_kwargs)
+        hub_kwargs["_commit_hash"] = config._commit_hash
     elif config is None and isinstance(model, str):
         config = AutoConfig.from_pretrained(model, _from_pipeline=task, **hub_kwargs, **model_kwargs)
+        hub_kwargs["_commit_hash"] = config._commit_hash
 
     custom_tasks = {}
     if config is not None and len(getattr(config, "custom_pipelines", {})) > 0:
@@ -639,6 +646,7 @@ def pipeline(
         )
         if config is None and isinstance(model, str):
             config = AutoConfig.from_pretrained(model, _from_pipeline=task, **hub_kwargs, **model_kwargs)
+            hub_kwargs["_commit_hash"] = config._commit_hash
 
     if device_map is not None:
         if "device_map" in model_kwargs:
@@ -672,6 +680,7 @@ def pipeline(
     )
 
     model_config = model.config
+    hub_kwargs["_commit_hash"] = model.config._commit_hash
 
     load_tokenizer = type(model_config) in TOKENIZER_MAPPING or model_config.tokenizer_class is not None
     load_feature_extractor = type(model_config) in FEATURE_EXTRACTOR_MAPPING or feature_extractor is not None

src/transformers/testing_utils.py

@@ -31,6 +31,7 @@
 from typing import Iterator, List, Union
 from unittest import mock
 
+import huggingface_hub
 from transformers import logging as transformers_logging
 
 from .deepspeed import is_deepspeed_available
@@ -1588,3 +1589,30 @@ def run_command(command: List[str], return_stdout=False):
         raise SubprocessCallException(
             f"Command `{' '.join(command)}` failed with the following error:\n\n{e.output.decode()}"
         ) from e
+
+
+class RequestCounter:
+    """
+    Helper class that will count all requests made online.
+    """
+
+    def __enter__(self):
+        self.head_request_count = 0
+        self.get_request_count = 0
+        self.other_request_count = 0
+        self.old_request = huggingface_hub.file_download.requests.request
+        huggingface_hub.file_download.requests.request = self.new_request
+        return self
+
+    def __exit__(self, *args, **kwargs):
+        huggingface_hub.file_download.requests.request = self.old_request
+
+    def new_request(self, method, **kwargs):
+        if method == "GET":
+            self.get_request_count += 1
+        elif method == "HEAD":
+            self.head_request_count += 1
+        else:
+            self.other_request_count += 1
+
+        return self.old_request(method=method, **kwargs)