[v1.0] Remove more deprecated stuff (#3345)

* remove constants.-hf_cache_home

* remove smoothly_deprecate_use_auth_token

* remove get_token_permission

* remove update_repo_visibility

* remove is_write_action arg

* remove write_permission arg from login methods

* new parameter skip_if_logged_in in login methods

* Remove resume_download / force_filename parameters

* Remove deprecated local_dir_use_symlinks parameter

* Remove deprecated language, library, task, tags from list_models

* Return commit URL in upload_file/upload_folder (previously url to file/folder on the Hub)

* fix upload_file/upload_folder tests

* smoothly_deprecate_legacy_arguments everywhere

* code quality

* fix tests

* fix xet tests

Author: Wauplin

docs/source/de/guides/integrations.md

@@ -82,7 +82,7 @@ Obwohl dieser Ansatz flexibel ist, hat er einige Nachteile, insbesondere in Bezu
 - `token`: zum Herunterladen aus einem privaten Repository
 - `revision`: zum Herunterladen von einem spezifischen Branch
 - `cache_dir`: um Dateien in einem spezifischen Verzeichnis zu cachen
-- `force_download`/`resume_download`/`local_files_only`: um den Cache wieder zu verwenden oder nicht
+- `force_download`/`local_files_only`: um den Cache wieder zu verwenden oder nicht
 - `api_endpoint`/`proxies`: HTTP-Session konfigurieren
 
 Beim Pushen von Modellen werden ähnliche Parameter unterstützt:
@@ -203,7 +203,6 @@ class PyTorchModelHubMixin(ModelHubMixin):
       cache_dir: str,
       force_download: bool,
       proxies: Optional[dict],
-      resume_download: bool,
       local_files_only: bool,
       token: Union[str, bool, None],
       map_location: str = "cpu", # zusätzliches Argument
@@ -221,8 +220,6 @@ class PyTorchModelHubMixin(ModelHubMixin):
             revision=revision,
             cache_dir=cache_dir,
             force_download=force_download,
-            proxies=proxies,
-            resume_download=resume_download,
             token=token,
             local_files_only=local_files_only,
          )
@@ -242,9 +239,9 @@ Und das war's! Ihre Bibliothek ermöglicht es Benutzern nun, Dateien vom und zum
 Lassen Sie uns die beiden Ansätze, die wir gesehen haben, schnell mit ihren Vor- und Nachteilen zusammenfassen. Die untenstehende Tabelle ist nur indikativ. Ihr Framework könnte einige Besonderheiten haben, die Sie berücksichtigen müssen. Dieser Leitfaden soll nur Richtlinien und Ideen geben, wie Sie die Integration handhaben können. Kontaktieren Sie uns in jedem Fall, wenn Sie Fragen haben!
 
 <!-- Generated using https://www.tablesgenerator.com/markdown_tables -->
-| Integration | Mit Helfern | Mit [`ModelHubMixin`] |
-|:---:|:---:|:---:|
-| Benutzererfahrung | `model = load_from_hub(...)`<br>`push_to_hub(model, ...)` | `model = MyModel.from_pretrained(...)`<br>`model.push_to_hub(...)` |
-| Flexibilität | Sehr flexibel.<br>Sie haben die volle Kontrolle über die Implementierung. | Weniger flexibel.<br>Ihr Framework muss eine Modellklasse haben. |
-| Wartung | Mehr Wartung, um Unterstützung für Konfiguration und neue Funktionen hinzuzufügen. Könnte auch das Beheben von Benutzerproblemen erfordern. | Weniger Wartung, da die meisten Interaktionen mit dem Hub in `huggingface_hub` implementiert sind. |
-| Dokumentation/Typ-Annotation| Manuell zu schreiben. | Teilweise durch `huggingface_hub` behandelt. |
+|         Integration          |                                                                 Mit Helfern                                                                 |                                       Mit [`ModelHubMixin`]                                        |
+| :--------------------------: | :-----------------------------------------------------------------------------------------------------------------------------------------: | :------------------------------------------------------------------------------------------------: |
+|      Benutzererfahrung       |                                          `model = load_from_hub(...)`<br>`push_to_hub(model, ...)`                                          |                 `model = MyModel.from_pretrained(...)`<br>`model.push_to_hub(...)`                 |
+|         Flexibilität         |                                  Sehr flexibel.<br>Sie haben die volle Kontrolle über die Implementierung.                                  |                  Weniger flexibel.<br>Ihr Framework muss eine Modellklasse haben.                  |
+|           Wartung            | Mehr Wartung, um Unterstützung für Konfiguration und neue Funktionen hinzuzufügen. Könnte auch das Beheben von Benutzerproblemen erfordern. | Weniger Wartung, da die meisten Interaktionen mit dem Hub in `huggingface_hub` implementiert sind. |
+| Dokumentation/Typ-Annotation |                                                            Manuell zu schreiben.                                                            |                            Teilweise durch `huggingface_hub` behandelt.                            |

docs/source/en/guides/integrations.md

@@ -244,8 +244,6 @@ class PyTorchModelHubMixin(ModelHubMixin):
       revision: str,
       cache_dir: str,
       force_download: bool,
-      proxies: Optional[dict],
-      resume_download: bool,
       local_files_only: bool,
       token: Union[str, bool, None],
       map_location: str = "cpu", # additional argument
@@ -265,8 +263,6 @@ class PyTorchModelHubMixin(ModelHubMixin):
             revision=revision,
             cache_dir=cache_dir,
             force_download=force_download,
-            proxies=proxies,
-            resume_download=resume_download,
             token=token,
             local_files_only=local_files_only,
             )
@@ -428,11 +424,11 @@ Your framework might have some specificities that you need to address. This guid
 ideas on how to handle integration. In any case, feel free to contact us if you have any questions!
 
 <!-- Generated using https://www.tablesgenerator.com/markdown_tables -->
-| Integration | Using helpers | Using [`ModelHubMixin`] |
-|:---:|:---:|:---:|
-| User experience | `model = load_from_hub(...)`<br>`push_to_hub(model, ...)` | `model = MyModel.from_pretrained(...)`<br>`model.push_to_hub(...)` |
-| Flexibility | Very flexible.<br>You fully control the implementation. | Less flexible.<br>Your framework must have a model class. |
-| Maintenance | More maintenance to add support for configuration, and new features. Might also require fixing issues reported by users. | Less maintenance as most of the interactions with the Hub are implemented in `huggingface_hub`. |
-| Documentation / Type annotation | To be written manually. | Partially handled by `huggingface_hub`. |
-| Download counter | To be handled manually. | Enabled by default if class has a `config` attribute. |
-| Model card | To be handled manually | Generated by default with library_name, tags, etc. |
+|           Integration           |                                                      Using helpers                                                       |                                     Using [`ModelHubMixin`]                                     |
+| :-----------------------------: | :----------------------------------------------------------------------------------------------------------------------: | :---------------------------------------------------------------------------------------------: |
+|         User experience         |                                `model = load_from_hub(...)`<br>`push_to_hub(model, ...)`                                 |               `model = MyModel.from_pretrained(...)`<br>`model.push_to_hub(...)`                |
+|           Flexibility           |                                 Very flexible.<br>You fully control the implementation.                                  |                    Less flexible.<br>Your framework must have a model class.                    |
+|           Maintenance           | More maintenance to add support for configuration, and new features. Might also require fixing issues reported by users. | Less maintenance as most of the interactions with the Hub are implemented in `huggingface_hub`. |
+| Documentation / Type annotation |                                                 To be written manually.                                                  |                             Partially handled by `huggingface_hub`.                             |
+|        Download counter         |                                                 To be handled manually.                                                  |                      Enabled by default if class has a `config` attribute.                      |
+|           Model card            |                                                  To be handled manually                                                  |                       Generated by default with library_name, tags, etc.                        |

docs/source/en/package_reference/utilities.md

@@ -255,20 +255,6 @@ huggingface_hub.utils._validators.HFValidationError: Cannot have -- or .. in rep
 
 >>> my_cool_method(repo_id="other..repo..id")
 huggingface_hub.utils._validators.HFValidationError: Cannot have -- or .. in repo_id: 'other..repo..id'.
-
->>> @validate_hf_hub_args
-... def my_cool_auth_method(token: str):
-...     print(token)
-
->>> my_cool_auth_method(token="a token")
-"a token"
-
->>> my_cool_auth_method(use_auth_token="a use_auth_token")
-"a use_auth_token"
-
->>> my_cool_auth_method(token="a token", use_auth_token="a use_auth_token")
-UserWarning: Both `token` and `use_auth_token` are passed (...). `use_auth_token` value will be ignored.
-"a token"
 ```
 
 #### validate_hf_hub_args
@@ -288,8 +274,8 @@ validated.
 
 [[autodoc]] utils.validate_repo_id
 
-#### smoothly_deprecate_use_auth_token
+#### smoothly_deprecate_legacy_arguments
 
 Not exactly a validator, but ran as well.
 
-[[autodoc]] utils.smoothly_deprecate_use_auth_token
+[[autodoc]] utils.smoothly_deprecate_legacy_arguments

docs/source/fr/guides/integrations.md

@@ -223,8 +223,6 @@ class PyTorchModelHubMixin(ModelHubMixin):
       revision: str,
       cache_dir: str,
       force_download: bool,
-      proxies: Optional[dict],
-      resume_download: bool,
       local_files_only: bool,
       token: Union[str, bool, None],
       map_location: str = "cpu", # argument supplémentaire
@@ -242,8 +240,6 @@ class PyTorchModelHubMixin(ModelHubMixin):
             revision=revision,
             cache_dir=cache_dir,
             force_download=force_download,
-            proxies=proxies,
-            resume_download=resume_download,
             token=token,
             local_files_only=local_files_only,
          )

docs/source/ko/guides/integrations.md

@@ -81,7 +81,7 @@ def push_to_hub(model: MyModelClass, repo_name: str) -> None:
 - `token`: 개인 리포지토리에서 다운로드하기 위한 토큰
 - `revision`: 특정 브랜치에서 다운로드하기 위한 리비전
 - `cache_dir`: 특정 디렉터리에 파일을 캐시하기 위한 디렉터리
-- `force_download`/`resume_download`/`local_files_only`: 캐시를 재사용할 것인지 여부를 결정하는 매개변수
+- `force_download`/`local_files_only`: 캐시를 재사용할 것인지 여부를 결정하는 매개변수
 - `proxies`: HTTP 세션 구성
 
 모델을 푸시할 때는 유사한 매개변수가 지원됩니다:
@@ -212,7 +212,6 @@ class PyTorchModelHubMixin(ModelHubMixin):
       cache_dir: str,
       force_download: bool,
       proxies: Optional[dict],
-      resume_download: bool,
       local_files_only: bool,
       token: Union[str, bool, None],
       map_location: str = "cpu", # 추가 인자
@@ -232,8 +231,6 @@ class PyTorchModelHubMixin(ModelHubMixin):
             revision=revision,
             cache_dir=cache_dir,
             force_download=force_download,
-            proxies=proxies,
-            resume_download=resume_download,
             token=token,
             local_files_only=local_files_only,
             )

docs/source/ko/package_reference/utilities.md

@@ -199,20 +199,6 @@ huggingface_hub.utils._validators.HFValidationError: Cannot have -- or .. in rep
 
 >>> my_cool_method(repo_id="other..repo..id")
 huggingface_hub.utils._validators.HFValidationError: Cannot have -- or .. in repo_id: 'other..repo..id'.
-
->>> @validate_hf_hub_args
-... def my_cool_auth_method(token: str):
-...     print(token)
-
->>> my_cool_auth_method(token="a token")
-"a token"
-
->>> my_cool_auth_method(use_auth_token="a use_auth_token")
-"a use_auth_token"
-
->>> my_cool_auth_method(token="a token", use_auth_token="a use_auth_token")
-UserWarning: Both `token` and `use_auth_token` are passed (...). `use_auth_token` value will be ignored.
-"a token"
 ```
 
 #### validate_hf_hub_args[[huggingface_hub.utils.validate_hf_hub_args]]
@@ -230,9 +216,3 @@ UserWarning: Both `token` and `use_auth_token` are passed (...). `use_auth_token
 #### repo_id[[huggingface_hub.utils.validate_repo_id]]
 
 [[autodoc]] utils.validate_repo_id
-
-#### smoothly_deprecate_use_auth_token[[huggingface_hub.utils.smoothly_deprecate_use_auth_token]]
-
-정확히 검증기는 아니지만, 잘 실행됩니다.
-
-[[autodoc]] utils.smoothly_deprecate_use_auth_token

src/huggingface_hub/__init__.py

@@ -217,7 +217,6 @@
         "get_safetensors_metadata",
         "get_space_runtime",
         "get_space_variables",
-        "get_token_permission",
         "get_user_overview",
         "get_webhook",
         "grant_access",
@@ -278,7 +277,6 @@
         "update_collection_metadata",
         "update_inference_endpoint",
         "update_repo_settings",
-        "update_repo_visibility",
         "update_webhook",
         "upload_file",
         "upload_folder",
@@ -885,7 +883,6 @@
     "get_space_variables",
     "get_tf_storage_size",
     "get_token",
-    "get_token_permission",
     "get_torch_storage_id",
     "get_torch_storage_size",
     "get_user_overview",
@@ -977,7 +974,6 @@
     "update_collection_metadata",
     "update_inference_endpoint",
     "update_repo_settings",
-    "update_repo_visibility",
     "update_webhook",
     "upload_file",
     "upload_folder",
@@ -1247,7 +1243,6 @@ def __dir__():
         get_safetensors_metadata,  # noqa: F401
         get_space_runtime,  # noqa: F401
         get_space_variables,  # noqa: F401
-        get_token_permission,  # noqa: F401
         get_user_overview,  # noqa: F401
         get_webhook,  # noqa: F401
         grant_access,  # noqa: F401
@@ -1308,7 +1303,6 @@ def __dir__():
         update_collection_metadata,  # noqa: F401
         update_inference_endpoint,  # noqa: F401
         update_repo_settings,  # noqa: F401
-        update_repo_visibility,  # noqa: F401
         update_webhook,  # noqa: F401
         upload_file,  # noqa: F401
         upload_folder,  # noqa: F401

src/huggingface_hub/_login.py

@@ -41,7 +41,7 @@
     _save_token,
     get_stored_tokens,
 )
-from .utils._deprecation import _deprecate_arguments, _deprecate_positional_args
+from .utils._deprecation import _deprecate_positional_args
 
 
 logger = logging.get_logger(__name__)
@@ -55,18 +55,12 @@
 """
 
 
-@_deprecate_arguments(
-    version="1.0",
-    deprecated_args="write_permission",
-    custom_message="Fine-grained tokens added complexity to the permissions, making it irrelevant to check if a token has 'write' access.",
-)
 @_deprecate_positional_args(version="1.0")
 def login(
     token: Optional[str] = None,
     *,
     add_to_git_credential: bool = False,
-    new_session: bool = True,
-    write_permission: bool = False,
+    skip_if_logged_in: bool = False,
 ) -> None:
     """Login the machine to access the Hub.
 
@@ -96,10 +90,8 @@ def login(
             is configured, a warning will be displayed to the user. If `token` is `None`,
             the value of `add_to_git_credential` is ignored and will be prompted again
             to the end user.
-        new_session (`bool`, defaults to `True`):
-            If `True`, will request a token even if one is already saved on the machine.
-        write_permission (`bool`):
-            Ignored and deprecated argument.
+        skip_if_logged_in (`bool`, defaults to `False`):
+            If `True`, do not prompt for token if user is already logged in.
     Raises:
         [`ValueError`](https://docs.python.org/3/library/exceptions.html#ValueError)
             If an organization token is passed. Only personal account tokens are valid
@@ -119,9 +111,9 @@ def login(
             )
         _login(token, add_to_git_credential=add_to_git_credential)
     elif is_notebook():
-        notebook_login(new_session=new_session)
+        notebook_login(skip_if_logged_in=skip_if_logged_in)
     else:
-        interpreter_login(new_session=new_session)
+        interpreter_login(skip_if_logged_in=skip_if_logged_in)
 
 
 def logout(token_name: Optional[str] = None) -> None:
@@ -236,13 +228,8 @@ def auth_list() -> None:
 ###
 
 
-@_deprecate_arguments(
-    version="1.0",
-    deprecated_args="write_permission",
-    custom_message="Fine-grained tokens added complexity to the permissions, making it irrelevant to check if a token has 'write' access.",
-)
 @_deprecate_positional_args(version="1.0")
-def interpreter_login(*, new_session: bool = True, write_permission: bool = False) -> None:
+def interpreter_login(*, skip_if_logged_in: bool = False) -> None:
     """
     Displays a prompt to log in to the HF website and store the token.
 
@@ -253,12 +240,10 @@ def interpreter_login(*, new_session: bool = True, write_permission: bool = Fals
     For more details, see [`login`].
 
     Args:
-        new_session (`bool`, defaults to `True`):
-            If `True`, will request a token even if one is already saved on the machine.
-        write_permission (`bool`):
-            Ignored and deprecated argument.
+        skip_if_logged_in (`bool`, defaults to `False`):
+            If `True`, do not prompt for token if user is already logged in.
     """
-    if not new_session and get_token() is not None:
+    if not skip_if_logged_in and get_token() is not None:
         logger.info("User is already logged in.")
         return
 
@@ -308,13 +293,8 @@ def interpreter_login(*, new_session: bool = True, write_permission: bool = Fals
 notebooks. </center>"""
 
 
-@_deprecate_arguments(
-    version="1.0",
-    deprecated_args="write_permission",
-    custom_message="Fine-grained tokens added complexity to the permissions, making it irrelevant to check if a token has 'write' access.",
-)
 @_deprecate_positional_args(version="1.0")
-def notebook_login(*, new_session: bool = True, write_permission: bool = False) -> None:
+def notebook_login(*, skip_if_logged_in: bool = False) -> None:
     """
     Displays a widget to log in to the HF website and store the token.
 
@@ -325,10 +305,8 @@ def notebook_login(*, new_session: bool = True, write_permission: bool = False)
     For more details, see [`login`].
 
     Args:
-        new_session (`bool`, defaults to `True`):
-            If `True`, will request a token even if one is already saved on the machine.
-        write_permission (`bool`):
-            Ignored and deprecated argument.
+        skip_if_logged_in (`bool`, defaults to `False`):
+            If `True`, do not prompt for token if user is already logged in.
     """
     try:
         import ipywidgets.widgets as widgets  # type: ignore
@@ -338,7 +316,7 @@ def notebook_login(*, new_session: bool = True, write_permission: bool = False)
             "The `notebook_login` function can only be used in a notebook (Jupyter or"
             " Colab) and you need the `ipywidgets` module: `pip install ipywidgets`."
         )
-    if not new_session and get_token() is not None:
+    if not skip_if_logged_in and get_token() is not None:
         logger.info("User is already logged in.")
         return
 

src/huggingface_hub/_snapshot_download.py

@@ -1,6 +1,6 @@
 import os
 from pathlib import Path
-from typing import Iterable, Literal, Optional, Union
+from typing import Iterable, Optional, Union
 
 import httpx
 from tqdm.auto import tqdm as base_tqdm
@@ -46,9 +46,6 @@ def snapshot_download(
     tqdm_class: Optional[type[base_tqdm]] = None,
     headers: Optional[dict[str, str]] = None,
     endpoint: Optional[str] = None,
-    # Deprecated args
-    local_dir_use_symlinks: Union[bool, Literal["auto"]] = "auto",
-    resume_download: Optional[bool] = None,
 ) -> str:
     """Download repo files.
 
@@ -303,12 +300,10 @@ def _inner_hf_hub_download(repo_file: str):
             endpoint=endpoint,
             cache_dir=cache_dir,
             local_dir=local_dir,
-            local_dir_use_symlinks=local_dir_use_symlinks,
             library_name=library_name,
             library_version=library_version,
             user_agent=user_agent,
             etag_timeout=etag_timeout,
-            resume_download=resume_download,
             force_download=force_download,
             token=token,
             headers=headers,