[3/N] Use pyupgrade --py39-plus to improve code (#36936)

Use pyupgrade --py39-plus to improve code

Signed-off-by: cyy <cyyever@outlook.com>

src/transformers/dynamic_module_utils.py

@@ -90,7 +90,7 @@ def get_relative_imports(module_file: Union[str, os.PathLike]) -> list[str]:
         module_file (`str` or `os.PathLike`): The module file to inspect.
 
     Returns:
-        `List[str]`: The list of relative imports in the module.
+        `list[str]`: The list of relative imports in the module.
     """
     with open(module_file, encoding="utf-8") as f:
         content = f.read()
@@ -112,7 +112,7 @@ def get_relative_import_files(module_file: Union[str, os.PathLike]) -> list[str]
         module_file (`str` or `os.PathLike`): The module file to inspect.
 
     Returns:
-        `List[str]`: The list of all relative imports a given module needs (recursively), which will give us the list
+        `list[str]`: The list of all relative imports a given module needs (recursively), which will give us the list
         of module files a given module needs.
     """
     no_change = False
@@ -144,7 +144,7 @@ def get_imports(filename: Union[str, os.PathLike]) -> list[str]:
         filename (`str` or `os.PathLike`): The module file to inspect.
 
     Returns:
-        `List[str]`: The list of all packages required to use the input module.
+        `list[str]`: The list of all packages required to use the input module.
     """
     with open(filename, encoding="utf-8") as f:
         content = f.read()
@@ -175,7 +175,7 @@ def check_imports(filename: Union[str, os.PathLike]) -> list[str]:
         filename (`str` or `os.PathLike`): The module file to check.
 
     Returns:
-        `List[str]`: The list of relative imports in the file.
+        `list[str]`: The list of relative imports in the file.
     """
     imports = get_imports(filename)
     missing_packages = []

src/transformers/model_debugging_utils.py

@@ -1,4 +1,3 @@
-# coding=utf-8
 # Copyright 2025 The HuggingFace Inc. team.
 # All rights reserved.
 #

src/transformers/utils/__init__.py

@@ -1,5 +1,4 @@
 #!/usr/bin/env python
-# coding=utf-8
 
 # Copyright 2021 The HuggingFace Inc. team. All rights reserved.
 #
@@ -16,7 +15,6 @@
 # limitations under the License.
 
 from functools import lru_cache
-from typing import FrozenSet
 
 from huggingface_hub import get_full_repo_name  # for backward compatibility
 from huggingface_hub.constants import HF_HUB_DISABLE_TELEMETRY as DISABLE_TELEMETRY  # for backward compatibility
@@ -300,8 +298,8 @@ def check_min_version(min_version):
         )
 
 
-@lru_cache()
+@lru_cache
-def get_available_devices() -> FrozenSet[str]:
+def get_available_devices() -> frozenset[str]:
     """
     Returns a frozenset of devices available for the current PyTorch installation.
     """

src/transformers/utils/attention_visualizer.py

@@ -1,4 +1,3 @@
-# coding=utf-8
 # Copyright 2025 The HuggingFace Inc. team.
 #
 # Licensed under the Apache License, Version 2.0 (the "License");

src/transformers/utils/backbone_utils.py

@@ -1,4 +1,3 @@
-# coding=utf-8
 # Copyright 2023 The HuggingFace Inc. team.
 #
 # Licensed under the Apache License, Version 2.0 (the "License");
@@ -17,7 +16,8 @@
 
 import enum
 import inspect
-from typing import TYPE_CHECKING, Iterable, List, Optional, Tuple, Union
+from collections.abc import Iterable
+from typing import TYPE_CHECKING, Optional, Union
 
 
 if TYPE_CHECKING:
@@ -75,9 +75,9 @@ def verify_out_features_out_indices(
 
 
 def _align_output_features_output_indices(
-    out_features: Optional[List[str]],
+    out_features: Optional[list[str]],
-    out_indices: Optional[Union[List[int], Tuple[int]]],
+    out_indices: Optional[Union[list[int], tuple[int]]],
-    stage_names: List[str],
+    stage_names: list[str],
 ):
     """
     Finds the corresponding `out_features` and `out_indices` for the given `stage_names`.
@@ -106,10 +106,10 @@ def _align_output_features_output_indices(
 
 
 def get_aligned_output_features_output_indices(
-    out_features: Optional[List[str]],
+    out_features: Optional[list[str]],
-    out_indices: Optional[Union[List[int], Tuple[int]]],
+    out_indices: Optional[Union[list[int], tuple[int]]],
-    stage_names: List[str],
+    stage_names: list[str],
-) -> Tuple[List[str], List[int]]:
+) -> tuple[list[str], list[int]]:
     """
     Get the `out_features` and `out_indices` so that they are aligned.
 
@@ -198,7 +198,7 @@ class BackboneMixin:
         return self._out_features
 
     @out_features.setter
-    def out_features(self, out_features: List[str]):
+    def out_features(self, out_features: list[str]):
         """
         Set the out_features attribute. This will also update the out_indices attribute to match the new out_features.
         """
@@ -211,7 +211,7 @@ class BackboneMixin:
         return self._out_indices
 
     @out_indices.setter
-    def out_indices(self, out_indices: Union[Tuple[int], List[int]]):
+    def out_indices(self, out_indices: Union[tuple[int], list[int]]):
         """
         Set the out_indices attribute. This will also update the out_features attribute to match the new out_indices.
         """
@@ -264,7 +264,7 @@ class BackboneConfigMixin:
         return self._out_features
 
     @out_features.setter
-    def out_features(self, out_features: List[str]):
+    def out_features(self, out_features: list[str]):
         """
         Set the out_features attribute. This will also update the out_indices attribute to match the new out_features.
         """
@@ -277,7 +277,7 @@ class BackboneConfigMixin:
         return self._out_indices
 
     @out_indices.setter
-    def out_indices(self, out_indices: Union[Tuple[int], List[int]]):
+    def out_indices(self, out_indices: Union[tuple[int], list[int]]):
         """
         Set the out_indices attribute. This will also update the out_features attribute to match the new out_indices.
         """

src/transformers/utils/chat_template_utils.py

@@ -19,7 +19,7 @@ import types
 from contextlib import contextmanager
 from datetime import datetime
 from functools import lru_cache
-from typing import Any, Callable, Dict, List, Optional, Tuple, Union, get_args, get_origin, get_type_hints
+from typing import Any, Callable, Optional, Union, get_args, get_origin, get_type_hints
 
 from packaging import version
 
@@ -71,7 +71,7 @@ class DocstringParsingException(Exception):
     pass
 
 
-def _get_json_schema_type(param_type: str) -> Dict[str, str]:
+def _get_json_schema_type(param_type: str) -> dict[str, str]:
     type_mapping = {
         int: {"type": "integer"},
         float: {"type": "number"},
@@ -87,7 +87,7 @@ def _get_json_schema_type(param_type: str) -> Dict[str, str]:
     return type_mapping.get(param_type, {"type": "object"})
 
 
-def _parse_type_hint(hint: str) -> Dict:
+def _parse_type_hint(hint: str) -> dict:
     origin = get_origin(hint)
     args = get_args(hint)
 
@@ -152,7 +152,7 @@ def _parse_type_hint(hint: str) -> Dict:
     raise TypeHintParsingException("Couldn't parse this type hint, likely due to a custom class or object: ", hint)
 
 
-def _convert_type_hints_to_json_schema(func: Callable) -> Dict:
+def _convert_type_hints_to_json_schema(func: Callable) -> dict:
     type_hints = get_type_hints(func)
     signature = inspect.signature(func)
     required = []
@@ -173,7 +173,7 @@ def _convert_type_hints_to_json_schema(func: Callable) -> Dict:
     return schema
 
 
-def parse_google_format_docstring(docstring: str) -> Tuple[Optional[str], Optional[Dict], Optional[str]]:
+def parse_google_format_docstring(docstring: str) -> tuple[Optional[str], Optional[dict], Optional[str]]:
     """
     Parses a Google-style docstring to extract the function description,
     argument descriptions, and return description.
@@ -206,7 +206,7 @@ def parse_google_format_docstring(docstring: str) -> Tuple[Optional[str], Option
     return description, args_dict, returns
 
 
-def get_json_schema(func: Callable) -> Dict:
+def get_json_schema(func: Callable) -> dict:
     """
     This function generates a JSON schema for a given function, based on its docstring and type hints. This is
     mostly used for passing lists of tools to a chat template. The JSON schema contains the name and description of
@@ -398,7 +398,7 @@ def _compile_jinja_template(chat_template):
             return self._rendered_blocks or self._generation_indices
 
         @contextmanager
-        def activate_tracker(self, rendered_blocks: List[int], generation_indices: List[int]):
+        def activate_tracker(self, rendered_blocks: list[int], generation_indices: list[int]):
             try:
                 if self.is_active():
                     raise ValueError("AssistantTracker should not be reused before closed")

src/transformers/utils/fx.py

@@ -1,4 +1,3 @@
-# coding=utf-8
 # Copyright 2021 The HuggingFace Team. All rights reserved.
 #
 # Licensed under the Apache License, Version 2.0 (the "License");
@@ -24,7 +23,7 @@ import os
 import random
 import sys
 import warnings
-from typing import Any, Callable, Dict, List, Literal, Optional, Tuple, Type, Union
+from typing import Any, Callable, Literal, Optional, Union
 
 import torch
 import torch.utils._pytree as pytree
@@ -78,9 +77,9 @@ _IS_IN_DEBUG_MODE = os.environ.get("FX_DEBUG_MODE", "").upper() in ENV_VARS_TRUE
 
 
 def _generate_supported_model_class_names(
-    model_name: Type[PretrainedConfig],
+    model_name: type[PretrainedConfig],
-    supported_tasks: Optional[Union[str, List[str]]] = None,
+    supported_tasks: Optional[Union[str, list[str]]] = None,
-) -> List[str]:
+) -> list[str]:
     task_mapping = {
         "default": MODEL_MAPPING_NAMES,
         "pretraining": MODEL_FOR_PRETRAINING_MAPPING_NAMES,
@@ -590,7 +589,7 @@ def operator_getitem(a, b):
     return operator.getitem(a, b)
 
 
-_MANUAL_META_OVERRIDES: Dict[Callable, Callable] = {
+_MANUAL_META_OVERRIDES: dict[Callable, Callable] = {
     torch.nn.Embedding: torch_nn_embedding,
     torch.nn.functional.embedding: torch_nn_functional_embedding,
     torch.nn.LayerNorm: torch_nn_layernorm,
@@ -716,7 +715,7 @@ class HFCacheProxy(HFProxy):
     Proxy that represents an instance of `transformers.cache_utils.Cache`.
     """
 
-    def install_orig_cache_cls(self, orig_cache_cls: Type[Cache]):
+    def install_orig_cache_cls(self, orig_cache_cls: type[Cache]):
         self._orig_cache_cls = orig_cache_cls
 
     @property
@@ -770,8 +769,8 @@ class HFProxyableClassMeta(type):
     def __new__(
         cls,
         name: str,
-        bases: Tuple[Type, ...],
+        bases: tuple[type, ...],
-        attrs: Dict[str, Any],
+        attrs: dict[str, Any],
         proxy_factory_fn: Optional[Callable[[Node], Proxy]] = None,
     ):
         cls = super().__new__(cls, name, bases, attrs)
@@ -794,7 +793,7 @@ class HFProxyableClassMeta(type):
         return cls
 
 
-def gen_constructor_wrapper(target: Callable) -> Tuple[Callable, Callable]:
+def gen_constructor_wrapper(target: Callable) -> tuple[Callable, Callable]:
     """
     Wraps `target` to be proxyable. Used for tensor creators like `torch.ones`, `torch.arange` and so on.
     """
@@ -813,7 +812,7 @@ def _proxies_to_metas(v):
     return v
 
 
-def create_cache_proxy_factory_fn(orig_cache_cls: Type[Cache]) -> Callable[[Node], HFCacheProxy]:
+def create_cache_proxy_factory_fn(orig_cache_cls: type[Cache]) -> Callable[[Node], HFCacheProxy]:
     def cache_proxy_factory_fn(n: Node) -> HFCacheProxy:
         global _CURRENT_TRACER
         if not isinstance(_CURRENT_TRACER, HFTracer):
@@ -849,7 +848,7 @@ ProxyableStaticCache = HFProxyableClassMeta(
 )
 
 
-def _generate_random_int(low: int = 10, high: int = 20, forbidden_values: Optional[List[int]] = None):
+def _generate_random_int(low: int = 10, high: int = 20, forbidden_values: Optional[list[int]] = None):
     if forbidden_values is None:
         forbidden_values = []
     value = random.randint(low, high)
@@ -899,8 +898,8 @@ class HFTracer(Tracer):
             )
 
     def _generate_dummy_input(
-        self, model: "PreTrainedModel", input_name: str, shape: List[int], input_names: List[str]
+        self, model: "PreTrainedModel", input_name: str, shape: list[int], input_names: list[str]
-    ) -> Dict[str, torch.Tensor]:
+    ) -> dict[str, torch.Tensor]:
         """Generates dummy input for model inference recording."""
         # Retrieving the model class, either from the "class_for_deserialization" attribute if the model was restored
         # from pickle, or from the "__class__" attribute in the general case.
@@ -1181,7 +1180,7 @@ class HFTracer(Tracer):
             return attr_val
 
     # Needed for PyTorch 1.13+
-    def getattr(self, attr: str, attr_val: Any, parameter_proxy_cache: Dict[str, Any]):
+    def getattr(self, attr: str, attr_val: Any, parameter_proxy_cache: dict[str, Any]):
         return self._module_getattr(attr, attr_val, parameter_proxy_cache)
 
     def call_module(self, m, forward, args, kwargs):
@@ -1233,8 +1232,8 @@ class HFTracer(Tracer):
     def trace(
         self,
         root: Union[torch.nn.Module, Callable[..., Any]],
-        concrete_args: Optional[Dict[str, Any]] = None,
+        concrete_args: Optional[dict[str, Any]] = None,
-        dummy_inputs: Optional[Dict[str, Any]] = None,
+        dummy_inputs: Optional[dict[str, Any]] = None,
         complete_concrete_args_with_inputs_not_in_dummy_inputs: bool = True,
     ) -> Graph:
         """
@@ -1422,7 +1421,7 @@ class HFTracer(Tracer):
         return attribute
 
 
-def get_concrete_args(model: nn.Module, input_names: List[str]):
+def get_concrete_args(model: nn.Module, input_names: list[str]):
     sig = inspect.signature(model.forward)
 
     if not (set(input_names) <= set(sig.parameters.keys())):
@@ -1450,9 +1449,9 @@ def check_if_model_is_supported(model: "PreTrainedModel"):
 
 def symbolic_trace(
     model: "PreTrainedModel",
-    input_names: Optional[List[str]] = None,
+    input_names: Optional[list[str]] = None,
     disable_check: bool = False,
-    tracer_cls: Type[HFTracer] = HFTracer,
+    tracer_cls: type[HFTracer] = HFTracer,
 ) -> GraphModule:
     """
     Performs symbolic tracing on the model.

src/transformers/utils/generic.py

@@ -21,12 +21,12 @@ import os
 import tempfile
 import warnings
 from collections import OrderedDict, UserDict
-from collections.abc import MutableMapping
+from collections.abc import Iterable, MutableMapping
 from contextlib import ExitStack, contextmanager
 from dataclasses import fields, is_dataclass
 from enum import Enum
 from functools import partial, wraps
-from typing import Any, ContextManager, Dict, Iterable, List, Optional, Tuple, TypedDict
+from typing import Any, ContextManager, Optional, TypedDict
 
 import numpy as np
 from packaging import version
@@ -465,7 +465,7 @@ class ModelOutput(OrderedDict):
         args = tuple(getattr(self, field.name) for field in fields(self))
         return callable, args, *remaining
 
-    def to_tuple(self) -> Tuple[Any]:
+    def to_tuple(self) -> tuple[Any]:
         """
         Convert self to a tuple containing all the attributes/keys that are not `None`.
         """
@@ -475,7 +475,7 @@ class ModelOutput(OrderedDict):
 if is_torch_available():
     import torch.utils._pytree as _torch_pytree
 
-    def _model_output_flatten(output: ModelOutput) -> Tuple[List[Any], "_torch_pytree.Context"]:
+    def _model_output_flatten(output: ModelOutput) -> tuple[list[Any], "_torch_pytree.Context"]:
         return list(output.values()), list(output.keys())
 
     def _model_output_unflatten(
@@ -542,7 +542,7 @@ class ContextManagers:
     in the `fastcore` library.
     """
 
-    def __init__(self, context_managers: List[ContextManager]):
+    def __init__(self, context_managers: list[ContextManager]):
         self.context_managers = context_managers
         self.stack = ExitStack()
 
@@ -883,7 +883,7 @@ class LossKwargs(TypedDict, total=False):
     num_items_in_batch: Optional[int]
 
 
-def is_timm_config_dict(config_dict: Dict[str, Any]) -> bool:
+def is_timm_config_dict(config_dict: dict[str, Any]) -> bool:
     """Checks whether a config dict is a timm config dict."""
     return "pretrained_cfg" in config_dict
 
@@ -903,13 +903,13 @@ def is_timm_local_checkpoint(pretrained_model_path: str) -> bool:
 
     # pretrained_model_path is a file
     if is_file and pretrained_model_path.endswith(".json"):
-        with open(pretrained_model_path, "r") as f:
+        with open(pretrained_model_path) as f:
             config_dict = json.load(f)
         return is_timm_config_dict(config_dict)
 
     # pretrained_model_path is a directory with a config.json
     if is_dir and os.path.exists(os.path.join(pretrained_model_path, "config.json")):
-        with open(os.path.join(pretrained_model_path, "config.json"), "r") as f:
+        with open(os.path.join(pretrained_model_path, "config.json")) as f:
             config_dict = json.load(f)
         return is_timm_config_dict(config_dict)
 

src/transformers/utils/hub.py

@@ -23,7 +23,7 @@ import tempfile
 import warnings
 from concurrent import futures
 from pathlib import Path
-from typing import Dict, List, Optional, Union
+from typing import Optional, Union
 from urllib.parse import urlparse
 from uuid import uuid4
 
@@ -168,7 +168,7 @@ def define_sagemaker_information():
     return sagemaker_object
 
 
-def http_user_agent(user_agent: Union[Dict, str, None] = None) -> str:
+def http_user_agent(user_agent: Union[dict, str, None] = None) -> str:
     """
     Formats a user-agent string with basic info about a request.
     """
@@ -270,17 +270,17 @@ def cached_file(
 
 def cached_files(
     path_or_repo_id: Union[str, os.PathLike],
-    filenames: List[str],
+    filenames: list[str],
     cache_dir: Optional[Union[str, os.PathLike]] = None,
     force_download: bool = False,
     resume_download: Optional[bool] = None,
-    proxies: Optional[Dict[str, str]] = None,
+    proxies: Optional[dict[str, str]] = None,
     token: Optional[Union[bool, str]] = None,
     revision: Optional[str] = None,
     local_files_only: bool = False,
     subfolder: str = "",
     repo_type: Optional[str] = None,
-    user_agent: Optional[Union[str, Dict[str, str]]] = None,
+    user_agent: Optional[Union[str, dict[str, str]]] = None,
     _raise_exceptions_for_gated_repo: bool = True,
     _raise_exceptions_for_missing_entries: bool = True,
     _raise_exceptions_for_connection_errors: bool = True,
@@ -378,7 +378,7 @@ def cached_files(
             if not os.path.isfile(resolved_file):
                 if _raise_exceptions_for_missing_entries and filename != os.path.join(subfolder, "config.json"):
                     revision_ = "main" if revision is None else revision
-                    raise EnvironmentError(
+                    raise OSError(
                         f"{path_or_repo_id} does not appear to have a file named {filename}. Checkout "
                         f"'https://huggingface.co/{path_or_repo_id}/tree/{revision_}' for available files."
                     )
@@ -410,7 +410,7 @@ def cached_files(
                 elif not _raise_exceptions_for_missing_entries:
                     file_counter += 1
                 else:
-                    raise EnvironmentError(f"Could not locate {filename} inside {path_or_repo_id}.")
+                    raise OSError(f"Could not locate {filename} inside {path_or_repo_id}.")
 
     # Either all the files were found, or some were _CACHED_NO_EXIST but we do not raise for missing entries
     if file_counter == len(full_filenames):
@@ -453,14 +453,14 @@ def cached_files(
     except Exception as e:
         # We cannot recover from them
         if isinstance(e, RepositoryNotFoundError) and not isinstance(e, GatedRepoError):
-            raise EnvironmentError(
+            raise OSError(
                 f"{path_or_repo_id} is not a local folder and is not a valid model identifier "
                 "listed on 'https://huggingface.co/models'\nIf this is a private repository, make sure to pass a token "
                 "having permission to this repo either by logging in with `huggingface-cli login` or by passing "
                 "`token=<your_token>`"
             ) from e
         elif isinstance(e, RevisionNotFoundError):
-            raise EnvironmentError(
+            raise OSError(
                 f"{revision} is not a valid git identifier (branch name, tag name or commit id) that exists "
                 "for this model name. Check the model page at "
                 f"'https://huggingface.co/{path_or_repo_id}' for available revisions."
@@ -478,7 +478,7 @@ def cached_files(
         if isinstance(e, GatedRepoError):
             if not _raise_exceptions_for_gated_repo:
                 return None
-            raise EnvironmentError(
+            raise OSError(
                 "You are trying to access a gated repo.\nMake sure to have access to it at "
                 f"https://huggingface.co/{path_or_repo_id}.\n{str(e)}"
             ) from e
@@ -488,7 +488,7 @@ def cached_files(
             # Here we only raise if both flags for missing entry and connection errors are True (because it can be raised
             # even when `local_files_only` is True, in which case raising for connections errors only would not make sense)
             elif _raise_exceptions_for_missing_entries:
-                raise EnvironmentError(
+                raise OSError(
                     f"We couldn't connect to '{HUGGINGFACE_CO_RESOLVE_ENDPOINT}' to load the files, and couldn't find them in the"
                     f" cached files.\nCheckout your internet connection or see how to run the library in offline mode at"
                     " 'https://huggingface.co/docs/transformers/installation#offline-mode'."
@@ -498,9 +498,7 @@ def cached_files(
         elif isinstance(e, HTTPError) and not isinstance(e, EntryNotFoundError):
             if not _raise_exceptions_for_connection_errors:
                 return None
-            raise EnvironmentError(
+            raise OSError(f"There was a specific connection error when trying to load {path_or_repo_id}:\n{e}")
-                f"There was a specific connection error when trying to load {path_or_repo_id}:\n{e}"
-            )
 
     resolved_files = [
         _get_cache_file_to_return(path_or_repo_id, filename, cache_dir, revision) for filename in full_filenames
@@ -632,7 +630,7 @@ def has_file(
     path_or_repo: Union[str, os.PathLike],
     filename: str,
     revision: Optional[str] = None,
-    proxies: Optional[Dict[str, str]] = None,
+    proxies: Optional[dict[str, str]] = None,
     token: Optional[Union[bool, str]] = None,
     *,
     local_files_only: bool = False,
@@ -707,19 +705,17 @@ def has_file(
         return True
     except GatedRepoError as e:
         logger.error(e)
-        raise EnvironmentError(
+        raise OSError(
             f"{path_or_repo} is a gated repository. Make sure to request access at "
             f"https://huggingface.co/{path_or_repo} and pass a token having permission to this repo either by "
             "logging in with `huggingface-cli login` or by passing `token=<your_token>`."
         ) from e
     except RepositoryNotFoundError as e:
         logger.error(e)
-        raise EnvironmentError(
+        raise OSError(f"{path_or_repo} is not a local folder or a valid repository name on 'https://hf.co'.") from e
-            f"{path_or_repo} is not a local folder or a valid repository name on 'https://hf.co'."
-        ) from e
     except RevisionNotFoundError as e:
         logger.error(e)
-        raise EnvironmentError(
+        raise OSError(
             f"{revision} is not a valid git identifier (branch name, tag name or commit id) that exists for this "
             f"model name. Check the model page at 'https://huggingface.co/{path_or_repo}' for available revisions."
         ) from e
@@ -780,7 +776,7 @@ class PushToHubMixin:
         self,
         working_dir: Union[str, os.PathLike],
         repo_id: str,
-        files_timestamps: Dict[str, float],
+        files_timestamps: dict[str, float],
         commit_message: Optional[str] = None,
         token: Optional[Union[bool, str]] = None,
         create_pr: bool = False,
@@ -867,7 +863,7 @@ class PushToHubMixin:
         safe_serialization: bool = True,
         revision: Optional[str] = None,
         commit_description: Optional[str] = None,
-        tags: Optional[List[str]] = None,
+        tags: Optional[list[str]] = None,
         **deprecated_kwargs,
     ) -> str:
         """
@@ -1101,7 +1097,7 @@ def get_checkpoint_shard_files(
     if not os.path.isfile(index_filename):
         raise ValueError(f"Can't find a checkpoint index ({index_filename}) in {pretrained_model_name_or_path}.")
 
-    with open(index_filename, "r") as f:
+    with open(index_filename) as f:
         index = json.loads(f.read())
 
     shard_filenames = sorted(set(index["weight_map"].values()))
@@ -1136,7 +1132,7 @@ def get_checkpoint_shard_files(
 
 def create_and_tag_model_card(
     repo_id: str,
-    tags: Optional[List[str]] = None,
+    tags: Optional[list[str]] = None,
     token: Optional[str] = None,
     ignore_metadata_errors: bool = False,
 ):

src/transformers/utils/logging.py

@@ -1,4 +1,3 @@
-# coding=utf-8
 # Copyright 2020 Optuna, Hugging Face
 #
 # Licensed under the Apache License, Version 2.0 (the "License");

src/transformers/utils/model_parallel_utils.py

@@ -1,4 +1,3 @@
-# coding=utf-8
 # Copyright 2020 The HuggingFace Team. All rights reserved.
 #
 # Licensed under the Apache License, Version 2.0 (the "License");

src/transformers/utils/notebook.py

@@ -1,4 +1,3 @@
-# coding=utf-8
 # Copyright 2020 Hugging Face
 #
 # Licensed under the Apache License, Version 2.0 (the "License");

src/transformers/utils/peft_utils.py

@@ -13,7 +13,7 @@
 # limitations under the License.
 import importlib
 import os
-from typing import Dict, Optional, Union
+from typing import Optional, Union
 
 from packaging import version
 
@@ -31,7 +31,7 @@ def find_adapter_config_file(
     cache_dir: Optional[Union[str, os.PathLike]] = None,
     force_download: bool = False,
     resume_download: Optional[bool] = None,
-    proxies: Optional[Dict[str, str]] = None,
+    proxies: Optional[dict[str, str]] = None,
     token: Optional[Union[bool, str]] = None,
     revision: Optional[str] = None,
     local_files_only: bool = False,

src/transformers/utils/sentencepiece_model_pb2_new.py

@@ -1,4 +1,3 @@
-# -*- coding: utf-8 -*-
 # Generated by the protocol buffer compiler.  DO NOT EDIT!
 # source: sentencepiece_model.proto
 """Generated protocol buffer code."""