





import logging

from transformers import PretrainedConfig


_snake_case  :    List[str]						    =  logging.getLogger(__name__)


_snake_case  :    Optional[int]						    =  {
    'bertabs-finetuned-cnndm': 'https://huggingface.co/remi/bertabs-finetuned-cnndm-extractive-abstractive-summarization/resolve/main/config.json',
}



class 				_UpperCAmelCase    (    _UpperCamelCase    ):

  """simple docstring"""


  a_        = """bertabs"""






  def __init__(				self :		List[str]					,  lowerCAmelCase_ :		Optional[int]=3_0_5_2_2					,  lowerCAmelCase_ :		List[Any]=5_1_2					,  lowerCAmelCase_ :		int=6					,  lowerCAmelCase_ :		List[str]=5_1_2					,  lowerCAmelCase_ :		List[str]=8					,  lowerCAmelCase_ :		List[Any]=5_1_2					,  lowerCAmelCase_ :		Optional[Any]=0.2					,  lowerCAmelCase_ :		Dict=6					,  lowerCAmelCase_ :		List[Any]=7_6_8					,  lowerCAmelCase_ :		Any=8					,  lowerCAmelCase_ :		Union[str, Any]=2_0_4_8					,  lowerCAmelCase_ :		Dict=0.2					,  **lowerCAmelCase_ :		int					,  )							->						Tuple:
     super().__init__(**lowerCAmelCase_     )

     __lowerCAmelCase								=	vocab_size
     __lowerCAmelCase								=	max_pos

     __lowerCAmelCase								=	enc_layers
     __lowerCAmelCase								=	enc_hidden_size
     __lowerCAmelCase								=	enc_heads
     __lowerCAmelCase								=	enc_ff_size
     __lowerCAmelCase								=	enc_dropout

     __lowerCAmelCase								=	dec_layers
     __lowerCAmelCase								=	dec_hidden_size
     __lowerCAmelCase								=	dec_heads
     __lowerCAmelCase								=	dec_ff_size
     __lowerCAmelCase								=	dec_dropout








def   a_    ( lowerCAmelCase_      :			int	):

   if p < 2:
      raise ValueError('p should not be less than 2!'	)
   elif p == 2:
      return True

   __lowerCAmelCase								=	4
   __lowerCAmelCase								=	(1 << p) - 1
   for _ in range(p - 2	):
      __lowerCAmelCase								=	((s * s) - 2) % m
   return s == 0


if __name__ == "__main__":
     print(lucas_lehmer_test(7))
     print(lucas_lehmer_test(11))

