


from ...configuration_utils import PretrainedConfig
from ...utils import logging


UpperCAmelCase_				:			List[str]   =	logging.get_logger(__name__)

UpperCAmelCase_				:			List[Any]   =	{
    'SCUT-DLVCLab/lilt-roberta-en-base': (
        'https://huggingface.co/SCUT-DLVCLab/lilt-roberta-en-base/resolve/main/config.json'
    ),
}
class 			SCREAMING_SNAKE_CASE__  (    lowercase__      ):
      snake_case__    :					int					       =						'''lilt'''
      def __init__(	self    :	str					,							SCREAMING_SNAKE_CASE__    :	Optional[int]=3_0_5_2_2					,							SCREAMING_SNAKE_CASE__    :	Tuple=7_6_8					,							SCREAMING_SNAKE_CASE__    :	Optional[int]=1_2					,							SCREAMING_SNAKE_CASE__    :	List[Any]=1_2					,							SCREAMING_SNAKE_CASE__    :	Optional[Any]=3_0_7_2					,							SCREAMING_SNAKE_CASE__    :	Optional[Any]="gelu"					,							SCREAMING_SNAKE_CASE__    :	Tuple=0.1					,							SCREAMING_SNAKE_CASE__    :	Union[str, Any]=0.1					,							SCREAMING_SNAKE_CASE__    :	Optional[Any]=5_1_2					,							SCREAMING_SNAKE_CASE__    :	Tuple=2					,							SCREAMING_SNAKE_CASE__    :	int=0.02					,							SCREAMING_SNAKE_CASE__    :	int=1E-12					,							SCREAMING_SNAKE_CASE__    :	Optional[Any]=0					,							SCREAMING_SNAKE_CASE__    :	Optional[int]="absolute"					,							SCREAMING_SNAKE_CASE__    :	Any=None					,							SCREAMING_SNAKE_CASE__    :	List[str]=4					,							SCREAMING_SNAKE_CASE__    :	Any=1_0_2_4					,							**SCREAMING_SNAKE_CASE__    :	List[Any]					,							)		->      Union[str, Any]:
             super().__init__(pad_token_id=SCREAMING_SNAKE_CASE__					,							**SCREAMING_SNAKE_CASE__					)

             a_ :		Dict							=  vocab_size
             a_ :		int							=  hidden_size
             a_ :		Optional[Any]							=  num_hidden_layers
             a_ :		Optional[int]							=  num_attention_heads
             a_ :		List[str]							=  hidden_act
             a_ :		Optional[int]							=  intermediate_size
             a_ :		str							=  hidden_dropout_prob
             a_ :		Optional[int]							=  attention_probs_dropout_prob
             a_ :		Union[str, Any]							=  max_position_embeddings
             a_ :		Optional[Any]							=  type_vocab_size
             a_ :		Any							=  initializer_range
             a_ :		str							=  layer_norm_eps
             a_ :		List[Any]							=  position_embedding_type
             a_ :		List[Any]							=  classifier_dropout
             a_ :		Optional[Any]							=  channel_shrink_ratio
             a_ :		Tuple							=  max_ad_position_embeddings






def 	SCREAMING_SNAKE_CASE_						(      __A			:      list    )     ->		bool:

       """simple docstring"""

       if not isinstance(__A  ,   __A    ):
              raise ValueError('Input series is not valid, valid series - [2, 4, 6]'    )
       if len(__A    ) == 0:
              raise ValueError('Input list must be a non empty list'    )
       if len(__A    ) == 1:
              return True
       a_ :		Tuple							=  series[1] - series[0]
       for index in range(len(__A    ) - 1    ):
              if series[index + 1] - series[index] != common_diff:
                     return False
       return True







def 	SCREAMING_SNAKE_CASE_						(      __A			:      list    )     ->		float:

       """simple docstring"""

       if not isinstance(__A  ,   __A    ):
              raise ValueError('Input series is not valid, valid series - [2, 4, 6]'    )
       if len(__A    ) == 0:
              raise ValueError('Input list must be a non empty list'    )
       a_ :		str							=  0
       for val in series:
              answer += val
       return answer / len(__A    )


if __name__ == "__main__":
   import doctest

   doctest.testmod()


