'''simple docstring'''


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


__snake_case						  =		logging.get_logger(__name__)

__snake_case						  =		{
    """SCUT-DLVCLab/lilt-roberta-en-base""": (
        """https://huggingface.co/SCUT-DLVCLab/lilt-roberta-en-base/resolve/main/config.json"""
    ),
}





class       _a    (		__a      ):


  """simple docstring"""

  A_    							=						'''lilt'''




  def __init__(		self      :       Union[str, Any]   ,				lowercase_      :       Optional[int]=30_522   ,				lowercase_      :       Tuple=768   ,				lowercase_      :       Optional[Any]=12   ,				lowercase_      :       Dict=12   ,				lowercase_      :       List[Any]=3_072   ,				lowercase_      :       str="gelu"   ,				lowercase_      :       Any=0.1   ,				lowercase_      :       Dict=0.1   ,				lowercase_      :       Dict=512   ,				lowercase_      :       Dict=2   ,				lowercase_      :       Optional[Any]=0.0_2   ,				lowercase_      :       int=1e-12   ,				lowercase_      :       int=0   ,				lowercase_      :       str="absolute"   ,				lowercase_      :       Optional[int]=None   ,				lowercase_      :       Dict=4   ,				lowercase_      :       Union[str, Any]=1_024   ,				**lowercase_      :       Tuple   ,				):







    '''simple docstring'''


    super().__init__(pad_token_id=lowercase_   ,				**lowercase_      )

    lowercase_     =       vocab_size
    lowercase_     =       hidden_size
    lowercase_     =       num_hidden_layers
    lowercase_     =       num_attention_heads
    lowercase_     =       hidden_act
    lowercase_     =       intermediate_size
    lowercase_     =       hidden_dropout_prob
    lowercase_     =       attention_probs_dropout_prob
    lowercase_     =       max_position_embeddings
    lowercase_     =       type_vocab_size
    lowercase_     =       initializer_range
    lowercase_     =       layer_norm_eps
    lowercase_     =       position_embedding_type
    lowercase_     =       classifier_dropout
    lowercase_     =       channel_shrink_ratio
    lowercase_     =       max_ad_position_embeddings


'''simple docstring'''


def   A_      (       SCREAMING_SNAKE_CASE_						)			->bool:
  if num < 0:
    return False

  lowercase_     =       num
  lowercase_     =       0
  while num > 0:
    lowercase_     =       rev_num * 10 + (num % 10)
    num //= 10

  return num_copy == rev_num


if __name__ == "__main__":
       import doctest

       doctest.testmod()

