


'''simple docstring'''



import logging

from transformers.configuration_utils import PretrainedConfig


A__						:   Union[str, Any]				=    logging.getLogger(__name__)





class   UpperCAmelCase_    (_UpperCAmelCase    ):





    """simple docstring"""






    lowerCamelCase    :   Dict					=     'masked_bert'







    def __init__(				self     ,	SCREAMING_SNAKE_CASE_=3_05_22     ,	SCREAMING_SNAKE_CASE_=7_68     ,	SCREAMING_SNAKE_CASE_=12     ,	SCREAMING_SNAKE_CASE_=12     ,	SCREAMING_SNAKE_CASE_=30_72     ,	SCREAMING_SNAKE_CASE_="gelu"     ,	SCREAMING_SNAKE_CASE_=0.1     ,	SCREAMING_SNAKE_CASE_=0.1     ,	SCREAMING_SNAKE_CASE_=5_12     ,	SCREAMING_SNAKE_CASE_=2     ,	SCREAMING_SNAKE_CASE_=0.0_2     ,	SCREAMING_SNAKE_CASE_=1E-12     ,	SCREAMING_SNAKE_CASE_=0     ,	SCREAMING_SNAKE_CASE_="topK"     ,	SCREAMING_SNAKE_CASE_="constant"     ,	SCREAMING_SNAKE_CASE_=0.0     ,	**SCREAMING_SNAKE_CASE_     ,	)							->	Optional[Any]:
         super().__init__(pad_token_id=SCREAMING_SNAKE_CASE_     ,	**SCREAMING_SNAKE_CASE_      )

         __lowerCamelCase  :      List[Any]														=						vocab_size
         __lowerCamelCase  :      Dict														=						hidden_size
         __lowerCamelCase  :      Union[str, Any]														=						num_hidden_layers
         __lowerCamelCase  :      List[Any]														=						num_attention_heads
         __lowerCamelCase  :      str														=						hidden_act
         __lowerCamelCase  :      Union[str, Any]														=						intermediate_size
         __lowerCamelCase  :      str														=						hidden_dropout_prob
         __lowerCamelCase  :      Tuple														=						attention_probs_dropout_prob
         __lowerCamelCase  :      int														=						max_position_embeddings
         __lowerCamelCase  :      Any														=						type_vocab_size
         __lowerCamelCase  :      List[Any]														=						initializer_range
         __lowerCamelCase  :      Union[str, Any]														=						layer_norm_eps
         __lowerCamelCase  :      List[Any]														=						pruning_method
         __lowerCamelCase  :      Dict														=						mask_init
         __lowerCamelCase  :      List[Any]														=						mask_scale













from typing import TYPE_CHECKING

from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available, is_vision_available


__lowerCamelCase			:	List[Any]					    =	{
    """configuration_chinese_clip""": [
        """CHINESE_CLIP_PRETRAINED_CONFIG_ARCHIVE_MAP""",
        """ChineseCLIPConfig""",
        """ChineseCLIPOnnxConfig""",
        """ChineseCLIPTextConfig""",
        """ChineseCLIPVisionConfig""",
    ],
    """processing_chinese_clip""": ["""ChineseCLIPProcessor"""],
}

try:
    if not is_vision_available():
        raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
    pass
else:
    __lowerCamelCase			:	Tuple					    =	["""ChineseCLIPFeatureExtractor"""]
    __lowerCamelCase			:	List[str]					    =	["""ChineseCLIPImageProcessor"""]

try:
    if not is_torch_available():
        raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
    pass
else:
    __lowerCamelCase			:	str					    =	[
        """CHINESE_CLIP_PRETRAINED_MODEL_ARCHIVE_LIST""",
        """ChineseCLIPModel""",
        """ChineseCLIPPreTrainedModel""",
        """ChineseCLIPTextModel""",
        """ChineseCLIPVisionModel""",
    ]

if TYPE_CHECKING:
    from .configuration_chinese_clip import (
        CHINESE_CLIP_PRETRAINED_CONFIG_ARCHIVE_MAP,
        ChineseCLIPConfig,
        ChineseCLIPOnnxConfig,
        ChineseCLIPTextConfig,
        ChineseCLIPVisionConfig,
    )
    from .processing_chinese_clip import ChineseCLIPProcessor

    try:
        if not is_vision_available():
            raise OptionalDependencyNotAvailable()
    except OptionalDependencyNotAvailable:
        pass
    else:
        from .feature_extraction_chinese_clip import ChineseCLIPFeatureExtractor, ChineseCLIPImageProcessor

    try:
        if not is_torch_available():
            raise OptionalDependencyNotAvailable()
    except OptionalDependencyNotAvailable:
        pass
    else:
        from .modeling_chinese_clip import (
            CHINESE_CLIP_PRETRAINED_MODEL_ARCHIVE_LIST,
            ChineseCLIPModel,
            ChineseCLIPPreTrainedModel,
            ChineseCLIPTextModel,
            ChineseCLIPVisionModel,
        )

else:
    import sys

    __lowerCamelCase			:	Any					    =	_LazyModule(__name__, globals()["""__file__"""], _import_structure, module_spec=__spec__)
