Use commit hash to look in cache instead of calling head (#18534)

* Use commit hash to look in cache instead of calling head

* Add tests

* Add attr for local configs too

* Stupid typos

* Fix tests

* Update src/transformers/utils/hub.py
Co-authored-by: Julien Chaumond <julien@huggingface.co>

* Address Julien's comments
Co-authored-by: Julien Chaumond <julien@huggingface.co>

src/transformers/configuration_utils.py

@@ -27,7 +27,15 @@ from packaging import version
 
 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 @@ class PretrainedConfig(PushToHubMixin):
 
         # 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 @@ class PretrainedConfig(PushToHubMixin):
         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 @@ class PretrainedConfig(PushToHubMixin):
         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 @@ class PretrainedConfig(PushToHubMixin):
                     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 @@ class PretrainedConfig(PushToHubMixin):
         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 @@ class PretrainedConfig(PushToHubMixin):
         # 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 @@ class PretrainedConfig(PushToHubMixin):
             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 @@ class FlaxPreTrainedModel(PushToHubMixin, FlaxGenerationMixin):
         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 @@ class FlaxPreTrainedModel(PushToHubMixin, FlaxGenerationMixin):
                 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 @@ class FlaxPreTrainedModel(PushToHubMixin, FlaxGenerationMixin):
                         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 @@ class FlaxPreTrainedModel(PushToHubMixin, FlaxGenerationMixin):
                 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 @@ class TFPreTrainedModel(tf.keras.Model, TFModelUtilsMixin, TFGenerationMixin, Pu
         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 @@ class TFPreTrainedModel(tf.keras.Model, TFModelUtilsMixin, TFGenerationMixin, Pu
                 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 @@ class TFPreTrainedModel(tf.keras.Model, TFModelUtilsMixin, TFGenerationMixin, Pu
                         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 @@ class TFPreTrainedModel(tf.keras.Model, TFModelUtilsMixin, TFGenerationMixin, Pu
                 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

@@ -1840,6 +1840,7 @@ class PreTrainedModel(nn.Module, ModuleUtilsMixin, GenerationMixin, PushToHubMix
         load_in_8bit = kwargs.pop("load_in_8bit", False)
         int8_threshold = kwargs.pop("int8_threshold", 6.0)
         subfolder = kwargs.pop("subfolder", "")
+        commit_hash = kwargs.pop("_commit_hash", None)
 
         if trust_remote_code is True:
             logger.warning(
@@ -1918,6 +1919,9 @@ class PreTrainedModel(nn.Module, ModuleUtilsMixin, GenerationMixin, PushToHubMix
         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
@@ -2004,6 +2008,7 @@ class PreTrainedModel(nn.Module, ModuleUtilsMixin, GenerationMixin, PushToHubMix
                         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)
 
@@ -2078,6 +2083,7 @@ class PreTrainedModel(nn.Module, ModuleUtilsMixin, GenerationMixin, PushToHubMix
                 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 ...dynamic_module_utils import get_class_from_dynamic_module
 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 @@ class AutoTokenizer:
 
         # 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 pathlib import Path
 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)

src/transformers/tokenization_utils_base.py

@@ -42,7 +42,7 @@ from .utils import (
     add_end_docstrings,
     cached_file,
     copy_func,
-    get_file_from_repo,
+    extract_commit_hash,
     is_flax_available,
     is_offline_mode,
     is_tf_available,
@@ -1651,6 +1651,7 @@ class PreTrainedTokenizerBase(SpecialTokensMixin, PushToHubMixin):
         subfolder = kwargs.pop("subfolder", None)
         from_pipeline = kwargs.pop("_from_pipeline", None)
         from_auto_class = kwargs.pop("_from_auto", False)
+        commit_hash = kwargs.pop("_commit_hash", None)
 
         user_agent = {"file_type": "tokenizer", "from_auto_class": from_auto_class, "is_fast": "Fast" in cls.__name__}
         if from_pipeline is not None:
@@ -1690,7 +1691,7 @@ class PreTrainedTokenizerBase(SpecialTokensMixin, PushToHubMixin):
             if "tokenizer_file" in vocab_files:
                 # Try to get the tokenizer config to see if there are versioned tokenizer files.
                 fast_tokenizer_file = FULL_TOKENIZER_FILE
-                resolved_config_file = get_file_from_repo(
+                resolved_config_file = cached_file(
                     pretrained_model_name_or_path,
                     TOKENIZER_CONFIG_FILE,
                     cache_dir=cache_dir,
@@ -1701,7 +1702,12 @@ class PreTrainedTokenizerBase(SpecialTokensMixin, PushToHubMixin):
                     revision=revision,
                     local_files_only=local_files_only,
                     subfolder=subfolder,
+                    user_agent=user_agent,
+                    _raise_exceptions_for_missing_entries=False,
+                    _raise_exceptions_for_connection_errors=False,
+                    _commit_hash=commit_hash,
                 )
+                commit_hash = extract_commit_hash(resolved_config_file, commit_hash)
                 if resolved_config_file is not None:
                     with open(resolved_config_file, encoding="utf-8") as reader:
                         tokenizer_config = json.load(reader)
@@ -1730,7 +1736,9 @@ class PreTrainedTokenizerBase(SpecialTokensMixin, PushToHubMixin):
                     subfolder=subfolder,
                     _raise_exceptions_for_missing_entries=False,
                     _raise_exceptions_for_connection_errors=False,
+                    _commit_hash=commit_hash,
                 )
+                commit_hash = extract_commit_hash(resolved_vocab_files[file_id], commit_hash)
 
         if len(unresolved_files) > 0:
             logger.info(
@@ -1763,6 +1771,7 @@ class PreTrainedTokenizerBase(SpecialTokensMixin, PushToHubMixin):
             use_auth_token=use_auth_token,
             cache_dir=cache_dir,
             local_files_only=local_files_only,
+            _commit_hash=commit_hash,
             **kwargs,
         )
 
@@ -1776,6 +1785,7 @@ class PreTrainedTokenizerBase(SpecialTokensMixin, PushToHubMixin):
         use_auth_token=None,
         cache_dir=None,
         local_files_only=False,
+        _commit_hash=None,
         **kwargs
     ):
         # We instantiate fast tokenizers based on a slow tokenizer if we don't have access to the tokenizer.json
@@ -1791,6 +1801,7 @@ class PreTrainedTokenizerBase(SpecialTokensMixin, PushToHubMixin):
                 use_auth_token=use_auth_token,
                 cache_dir=cache_dir,
                 local_files_only=local_files_only,
+                _commit_hash=_commit_hash,
                 **(copy.deepcopy(kwargs)),
             )
         else:
@@ -1823,6 +1834,7 @@ class PreTrainedTokenizerBase(SpecialTokensMixin, PushToHubMixin):
                     use_auth_token=use_auth_token,
                     cache_dir=cache_dir,
                     local_files_only=local_files_only,
+                    _commit_hash=_commit_hash,
                 )
                 config_tokenizer_class = config.tokenizer_class
             except (OSError, ValueError, KeyError):

src/transformers/utils/__init__.py

@@ -63,6 +63,7 @@ from .hub import (
     cached_file,
     default_cache_path,
     define_sagemaker_information,
+    extract_commit_hash,
     get_cached_models,
     get_file_from_repo,
     get_full_repo_name,

src/transformers/utils/hub.py

@@ -38,6 +38,7 @@ from huggingface_hub import (
     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.utils import EntryNotFoundError, RepositoryNotFoundError, RevisionNotFoundError
 from requests.exceptions import HTTPError
 from transformers.utils.logging import tqdm
@@ -200,11 +201,27 @@ def http_user_agent(user_agent: Union[Dict, str, None] = None) -> str:
     return ua
 
 
-def try_to_load_from_cache(cache_dir, repo_id, filename, revision=None):
+def extract_commit_hash(resolved_file: Optional[str], commit_hash: Optional[str]):
+    """
+    Extracts the commit hash from a resolved filename toward a cache file.
+    """
+    if resolved_file is None or commit_hash is not None:
+        return commit_hash
+
+    search = re.search(r"snapshots/([^/]+)/", resolved_file)
+    if search is None:
+        return None
+    commit_hash = search.groups()[0]
+    return commit_hash if REGEX_COMMIT_HASH.match(commit_hash) else None
+
+
+def try_to_load_from_cache(cache_dir, repo_id, filename, revision=None, commit_hash=None):
     """
     Explores the cache to return the latest cached file for a given revision.
     """
-    if revision is None:
+    if commit_hash is not None and revision is not None:
+        raise ValueError("`commit_hash` and `revision` are mutually exclusive, pick one only.")
+    if revision is None and commit_hash is None:
         revision = "main"
 
     model_id = repo_id.replace("/", "--")
@@ -216,18 +233,19 @@ def try_to_load_from_cache(cache_dir, repo_id, filename, revision=None):
         if not os.path.isdir(os.path.join(model_cache, subfolder)):
             return None
 
-    # Resolve refs (for instance to convert main to the associated commit sha)
-    cached_refs = os.listdir(os.path.join(model_cache, "refs"))
-    if revision in cached_refs:
-        with open(os.path.join(model_cache, "refs", revision)) as f:
-            revision = f.read()
+    if commit_hash is None:
+        # Resolve refs (for instance to convert main to the associated commit sha)
+        cached_refs = os.listdir(os.path.join(model_cache, "refs"))
+        if revision in cached_refs:
+            with open(os.path.join(model_cache, "refs", revision)) as f:
+                commit_hash = f.read()
 
     cached_shas = os.listdir(os.path.join(model_cache, "snapshots"))
-    if revision not in cached_shas:
+    if commit_hash not in cached_shas:
         # No cache for this revision and we won't try to return a random revision
         return None
 
-    cached_file = os.path.join(model_cache, "snapshots", revision, filename)
+    cached_file = os.path.join(model_cache, "snapshots", commit_hash, filename)
     return cached_file if os.path.isfile(cached_file) else None
 
 
@@ -265,8 +283,9 @@ def cached_file(
     local_files_only: bool = False,
     subfolder: str = "",
     user_agent: Optional[Union[str, Dict[str, str]]] = None,
-    _raise_exceptions_for_missing_entries=True,
-    _raise_exceptions_for_connection_errors=True,
+    _raise_exceptions_for_missing_entries: bool = True,
+    _raise_exceptions_for_connection_errors: bool = True,
+    _commit_hash: Optional[str] = None,
 ):
     """
     Tries to locate a file in a local folder and repo, downloads and cache it if necessary.
@@ -318,6 +337,13 @@ def cached_file(
     # Download a model weight from the Hub and cache it.
     model_weights_file = cached_file("bert-base-uncased", "pytorch_model.bin")
     ```"""
+    # Private arguments
+    #     _raise_exceptions_for_missing_entries: if False, do not raise an exception for missing entries but return
+    #         None.
+    #     _raise_exceptions_for_connection_errors: if False, do not raise an exception for connection errors but return
+    #         None.
+    #     _commit_hash: passed when we are chaining several calls to various files (e.g. when loading a tokenizer or
+    #         a pipeline). If files are cached for this commit hash, avoid calls to head and get from the cache.
     if is_offline_mode() and not local_files_only:
         logger.info("Offline mode: forcing local_files_only=True")
         local_files_only = True
@@ -339,6 +365,13 @@ def cached_file(
         cache_dir = TRANSFORMERS_CACHE
     if isinstance(cache_dir, Path):
         cache_dir = str(cache_dir)
+
+    if _commit_hash is not None:
+        # If the file is cached under that commit hash, we return it directly.
+        resolved_file = try_to_load_from_cache(cache_dir, path_or_repo_id, full_filename, commit_hash=_commit_hash)
+        if resolved_file is not None:
+            return resolved_file
+
     user_agent = http_user_agent(user_agent)
     try:
         # Load from URL or cache if already cached
@@ -803,6 +836,7 @@ def get_checkpoint_shard_files(
     user_agent=None,
     revision=None,
     subfolder="",
+    _commit_hash=None,
 ):
     """
     For a given model:
@@ -848,6 +882,7 @@ def get_checkpoint_shard_files(
                 user_agent=user_agent,
                 revision=revision,
                 subfolder=subfolder,
+                _commit_hash=_commit_hash,
             )
         # We have already dealt with RepositoryNotFoundError and RevisionNotFoundError when getting the index, so
         # we don't have to catch them here.

tests/models/auto/test_modeling_auto.py

@@ -24,6 +24,7 @@ from transformers.models.auto.configuration_auto import CONFIG_MAPPING
 from transformers.testing_utils import (
     DUMMY_UNKNOWN_IDENTIFIER,
     SMALL_MODEL_IDENTIFIER,
+    RequestCounter,
     require_scatter,
     require_torch,
     slow,
@@ -354,3 +355,21 @@ class AutoModelTest(unittest.TestCase):
     def test_model_from_flax_suggestion(self):
         with self.assertRaisesRegex(EnvironmentError, "Use `from_flax=True` to load this model"):
             _ = AutoModel.from_pretrained("hf-internal-testing/tiny-bert-flax-only")
+
+    def test_cached_model_has_minimum_calls_to_head(self):
+        # Make sure we have cached the model.
+        _ = AutoModel.from_pretrained("hf-internal-testing/tiny-random-bert")
+        with RequestCounter() as counter:
+            _ = AutoModel.from_pretrained("hf-internal-testing/tiny-random-bert")
+            self.assertEqual(counter.get_request_count, 0)
+            self.assertEqual(counter.head_request_count, 1)
+            self.assertEqual(counter.other_request_count, 0)
+
+        # With a sharded checkpoint
+        _ = AutoModel.from_pretrained("hf-internal-testing/tiny-random-bert-sharded")
+        with RequestCounter() as counter:
+            _ = AutoModel.from_pretrained("hf-internal-testing/tiny-random-bert-sharded")
+            self.assertEqual(counter.get_request_count, 0)
+            # There is no pytorch_model.bin so we still get one call for this one.
+            self.assertEqual(counter.head_request_count, 2)
+            self.assertEqual(counter.other_request_count, 0)

tests/models/auto/test_modeling_tf_auto.py

@@ -21,6 +21,7 @@ from transformers import CONFIG_MAPPING, AutoConfig, BertConfig, GPT2Config, T5C
 from transformers.testing_utils import (
     DUMMY_UNKNOWN_IDENTIFIER,
     SMALL_MODEL_IDENTIFIER,
+    RequestCounter,
     require_tensorflow_probability,
     require_tf,
     slow,
@@ -287,3 +288,21 @@ class TFAutoModelTest(unittest.TestCase):
     def test_model_from_pt_suggestion(self):
         with self.assertRaisesRegex(EnvironmentError, "Use `from_pt=True` to load this model"):
             _ = TFAutoModel.from_pretrained("hf-internal-testing/tiny-bert-pt-only")
+
+    def test_cached_model_has_minimum_calls_to_head(self):
+        # Make sure we have cached the model.
+        _ = TFAutoModel.from_pretrained("hf-internal-testing/tiny-random-bert")
+        with RequestCounter() as counter:
+            _ = TFAutoModel.from_pretrained("hf-internal-testing/tiny-random-bert")
+            self.assertEqual(counter.get_request_count, 0)
+            self.assertEqual(counter.head_request_count, 1)
+            self.assertEqual(counter.other_request_count, 0)
+
+        # With a sharded checkpoint
+        _ = TFAutoModel.from_pretrained("ArthurZ/tiny-random-bert-sharded")
+        with RequestCounter() as counter:
+            _ = TFAutoModel.from_pretrained("ArthurZ/tiny-random-bert-sharded")
+            self.assertEqual(counter.get_request_count, 0)
+            # There is no pytorch_model.bin so we still get one call for this one.
+            self.assertEqual(counter.head_request_count, 2)
+            self.assertEqual(counter.other_request_count, 0)

tests/models/auto/test_tokenization_auto.py

@@ -48,6 +48,7 @@ from transformers.testing_utils import (
     DUMMY_DIFF_TOKENIZER_IDENTIFIER,
     DUMMY_UNKNOWN_IDENTIFIER,
     SMALL_MODEL_IDENTIFIER,
+    RequestCounter,
     require_tokenizers,
     slow,
 )
@@ -213,6 +214,7 @@ class AutoTokenizerTest(unittest.TestCase):
     def test_get_tokenizer_config(self):
         # Check we can load the tokenizer config of an online model.
         config = get_tokenizer_config("bert-base-cased")
+        _ = config.pop("_commit_hash", None)
         # If we ever update bert-base-cased tokenizer config, this dict here will need to be updated.
         self.assertEqual(config, {"do_lower_case": False})
 
@@ -340,3 +342,13 @@ class AutoTokenizerTest(unittest.TestCase):
             EnvironmentError, r"aaaaaa is not a valid git identifier \(branch name, tag name or commit id\)"
         ):
             _ = AutoTokenizer.from_pretrained(DUMMY_UNKNOWN_IDENTIFIER, revision="aaaaaa")
+
+    def test_cached_tokenizer_has_minimum_calls_to_head(self):
+        # Make sure we have cached the tokenizer.
+        _ = AutoTokenizer.from_pretrained("hf-internal-testing/tiny-random-bert")
+        with RequestCounter() as counter:
+            _ = AutoTokenizer.from_pretrained("hf-internal-testing/tiny-random-bert")
+            self.assertEqual(counter.get_request_count, 0)
+            # We still have one extra call because the model does not have a added_tokens.json file
+            self.assertEqual(counter.head_request_count, 2)
+            self.assertEqual(counter.other_request_count, 0)

tests/pipelines/test_pipelines_common.py

@@ -49,6 +49,7 @@ from transformers.testing_utils import (
     TOKEN,
     USER,
     CaptureLogger,
+    RequestCounter,
     is_pipeline_test,
     is_staging_test,
     nested_simplify,
@@ -877,6 +878,16 @@ class CustomPipelineTest(unittest.TestCase):
             [{"label": "LABEL_0", "score": 0.505}],
         )
 
+    def test_cached_pipeline_has_minimum_calls_to_head(self):
+        # Make sure we have cached the pipeline.
+        _ = pipeline("text-classification", model="hf-internal-testing/tiny-random-bert")
+        with RequestCounter() as counter:
+            _ = pipeline("text-classification", model="hf-internal-testing/tiny-random-bert")
+            self.assertEqual(counter.get_request_count, 0)
+            # We still have one extra call because the model does not have a added_tokens.json file
+            self.assertEqual(counter.head_request_count, 2)
+            self.assertEqual(counter.other_request_count, 0)
+
 
 @require_torch
 @is_staging_test

tests/test_configuration_common.py

@@ -246,7 +246,7 @@ class ConfigPushToHubTester(unittest.TestCase):
         config.push_to_hub("test-config", use_auth_token=self._token)
 
         new_config = BertConfig.from_pretrained(f"{USER}/test-config")
-        for k, v in config.__dict__.items():
+        for k, v in config.to_dict().items():
             if k != "transformers_version":
                 self.assertEqual(v, getattr(new_config, k))
 
@@ -258,7 +258,7 @@ class ConfigPushToHubTester(unittest.TestCase):
             config.save_pretrained(tmp_dir, repo_id="test-config", push_to_hub=True, use_auth_token=self._token)
 
         new_config = BertConfig.from_pretrained(f"{USER}/test-config")
-        for k, v in config.__dict__.items():
+        for k, v in config.to_dict().items():
             if k != "transformers_version":
                 self.assertEqual(v, getattr(new_config, k))
 
@@ -269,7 +269,7 @@ class ConfigPushToHubTester(unittest.TestCase):
         config.push_to_hub("valid_org/test-config-org", use_auth_token=self._token)
 
         new_config = BertConfig.from_pretrained("valid_org/test-config-org")
-        for k, v in config.__dict__.items():
+        for k, v in config.to_dict().items():
             if k != "transformers_version":
                 self.assertEqual(v, getattr(new_config, k))
 
@@ -283,7 +283,7 @@ class ConfigPushToHubTester(unittest.TestCase):
             )
 
         new_config = BertConfig.from_pretrained("valid_org/test-config-org")
-        for k, v in config.__dict__.items():
+        for k, v in config.to_dict().items():
             if k != "transformers_version":
                 self.assertEqual(v, getattr(new_config, k))
 
@@ -323,7 +323,9 @@ class ConfigTestUtils(unittest.TestCase):
         base_config = PretrainedConfig()
         missing_keys = [key for key in base_config.__dict__ if key not in config_common_kwargs]
         # If this part of the test fails, you have arguments to addin config_common_kwargs above.
-        self.assertListEqual(missing_keys, ["is_encoder_decoder", "_name_or_path", "transformers_version"])
+        self.assertListEqual(
+            missing_keys, ["is_encoder_decoder", "_name_or_path", "_commit_hash", "transformers_version"]
+        )
         keys_with_defaults = [key for key, value in config_common_kwargs.items() if value == getattr(base_config, key)]
         if len(keys_with_defaults) > 0:
             raise ValueError(