





import logging

from transformers.configuration_utils import PretrainedConfig


UpperCamelCase__      =logging.getLogger(__name__)





class 			lowerCAmelCase__( _A    ):






       '''simple docstring'''


       __snake_case 			=    'masked_bert'




       def __init__(      self    ,						__lowerCamelCase=3_0_5_2_2    ,						__lowerCamelCase=7_6_8    ,						__lowerCamelCase=1_2    ,						__lowerCamelCase=1_2    ,						__lowerCamelCase=3_0_7_2    ,						__lowerCamelCase="gelu"    ,						__lowerCamelCase=0.1    ,						__lowerCamelCase=0.1    ,						__lowerCamelCase=5_1_2    ,						__lowerCamelCase=2    ,						__lowerCamelCase=0.02    ,						__lowerCamelCase=1E-12    ,						__lowerCamelCase=0    ,						__lowerCamelCase="topK"    ,						__lowerCamelCase="constant"    ,						__lowerCamelCase=0.0    ,						**__lowerCamelCase    ,						)			->     Union[str, Any]:
            super().__init__(pad_token_id=UpperCamelCase__    ,						**UpperCamelCase__							)

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









def     lowerCamelCase__			(__lowerCamelCase,       __lowerCamelCase	):
     if a < 0 or b < 0:
          raise ValueError("the value of both inputs must be positive"	)
     _SCREAMING_SNAKE_CASE       :	Optional[Any]						    =							str(bin(__lowerCamelCase	)	)[2:]  # remove the leading "0b"
     _SCREAMING_SNAKE_CASE       :	List[str]						    =							str(bin(__lowerCamelCase	)	)[2:]
     _SCREAMING_SNAKE_CASE       :	Optional[Any]						    =							max(len(__lowerCamelCase	),       len(__lowerCamelCase	)	)
     return "0b" + "".join(
         str(int("1" in (char_a, char_b)	)	)
         for char_a, char_b in zip(a_binary.zfill(__lowerCamelCase	),       b_binary.zfill(__lowerCamelCase	)	)	)


if __name__ == "__main__":
       import doctest

       doctest.testmod()