From 96cd2ac8ee8bebd59286863ea9053e65805963cd Mon Sep 17 00:00:00 2001
From: lilin <lilin@pjlab.org.cn>
Date: Mon, 4 Sep 2023 21:03:37 +0800
Subject: [PATCH] fix pre-commit format

---
 mmaction/models/utils/huggingface.py | 98 ----------------------------
 1 file changed, 98 deletions(-)
 delete mode 100644 mmaction/models/utils/huggingface.py

diff --git a/mmaction/models/utils/huggingface.py b/mmaction/models/utils/huggingface.py
deleted file mode 100644
index 9f3450c05f..0000000000
--- a/mmaction/models/utils/huggingface.py
+++ /dev/null
@@ -1,98 +0,0 @@
-# Copyright (c) OpenMMLab. All rights reserved.
-import contextlib
-from typing import Optional
-
-import transformers
-from mmengine.registry import Registry
-from transformers import AutoConfig, PreTrainedModel
-from transformers.models.auto.auto_factory import _BaseAutoModelClass
-
-from mmaction.registry import MODELS, TOKENIZER
-
-
-def register_hf_tokenizer(
-    cls: Optional[type] = None,
-    registry: Registry = TOKENIZER,
-):
-    """Register HuggingFace-style PreTrainedTokenizerBase class."""
-    if cls is None:
-
-        # use it as a decorator: @register_hf_tokenizer()
-        def _register(cls):
-            register_hf_tokenizer(cls=cls)
-            return cls
-
-        return _register
-
-    def from_pretrained(**kwargs):
-        if ('pretrained_model_name_or_path' not in kwargs
-                and 'name_or_path' not in kwargs):
-            raise TypeError(
-                f'{cls.__name__}.from_pretrained() missing required '
-                "argument 'pretrained_model_name_or_path' or 'name_or_path'.")
-        # `pretrained_model_name_or_path` is too long for config,
-        # add an alias name `name_or_path` here.
-        name_or_path = kwargs.pop('pretrained_model_name_or_path',
-                                  kwargs.pop('name_or_path'))
-        return cls.from_pretrained(name_or_path, **kwargs)
-
-    registry._register_module(module=from_pretrained, module_name=cls.__name__)
-    return cls
-
-
-_load_hf_pretrained_model = True
-
-
-@contextlib.contextmanager
-def no_load_hf_pretrained_model():
-    global _load_hf_pretrained_model
-    _load_hf_pretrained_model = False
-    yield
-    _load_hf_pretrained_model = True
-
-
-def register_hf_model(
-    cls: Optional[type] = None,
-    registry: Registry = MODELS,
-):
-    """Register HuggingFace-style PreTrainedModel class."""
-    if cls is None:
-
-        # use it as a decorator: @register_hf_tokenizer()
-        def _register(cls):
-            register_hf_model(cls=cls)
-            return cls
-
-        return _register
-
-    if issubclass(cls, _BaseAutoModelClass):
-        get_config = AutoConfig.from_pretrained
-        from_config = cls.from_config
-    elif issubclass(cls, PreTrainedModel):
-        get_config = cls.config_class.from_pretrained
-        from_config = cls
-    else:
-        raise TypeError('Not auto model nor pretrained model of huggingface.')
-
-    def build(**kwargs):
-        if ('pretrained_model_name_or_path' not in kwargs
-                and 'name_or_path' not in kwargs):
-            raise TypeError(
-                f'{cls.__name__} missing required argument '
-                '`pretrained_model_name_or_path` or `name_or_path`.')
-        # `pretrained_model_name_or_path` is too long for config,
-        # add an alias name `name_or_path` here.
-        name_or_path = kwargs.pop('pretrained_model_name_or_path',
-                                  kwargs.pop('name_or_path'))
-
-        if kwargs.pop('load_pretrained', True) and _load_hf_pretrained_model:
-            return cls.from_pretrained(name_or_path, **kwargs)
-        else:
-            cfg = get_config(name_or_path, **kwargs)
-            return from_config(cfg)
-
-    registry._register_module(module=build, module_name=cls.__name__)
-    return cls
-
-
-register_hf_model(transformers.)