


'''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













import logging

from transformers import PretrainedConfig


_lowerCAmelCase				:   str						       =						logging.getLogger(__name__)


_lowerCAmelCase				:   Dict						       =						{
    '''bertabs-finetuned-cnndm''': '''https://huggingface.co/remi/bertabs-finetuned-cnndm-extractive-abstractive-summarization/resolve/main/config.json''',
}


class        __magic_name__	(				lowerCamelCase__				):





     """simple docstring"""



     __UpperCamelCase            =  '''bertabs'''



     def __init__(				self							:Optional[int]      ,   snake_case							:Any=30_522      ,   snake_case							:List[str]=512      ,   snake_case							:str=6      ,   snake_case							:int=512      ,   snake_case							:Optional[Any]=8      ,   snake_case							:Tuple=512      ,   snake_case							:str=0.2      ,   snake_case							:Any=6      ,   snake_case							:Optional[Any]=768      ,   snake_case							:Optional[Any]=8      ,   snake_case							:List[Any]=2_048      ,   snake_case							:Dict=0.2      ,   **snake_case							:List[str]      ,   ):





        '''simple docstring'''




        super().__init__(**snake_case	)

        A_       :					List[str]        =      vocab_size
        A_       :					int        =      max_pos

        A_       :					Tuple        =      enc_layers
        A_       :					Tuple        =      enc_hidden_size
        A_       :					str        =      enc_heads
        A_       :					Optional[Any]        =      enc_ff_size
        A_       :					Optional[Any]        =      enc_dropout

        A_       :					List[str]        =      dec_layers
        A_       :					List[Any]        =      dec_hidden_size
        A_       :					Optional[int]        =      dec_heads
        A_       :					Any        =      dec_ff_size
        A_       :					Optional[int]        =      dec_dropout
