






"""simple docstring"""


from ... import PretrainedConfig


_UpperCamelCase    :   List[Any]   			=						{
    'sijunhe/nezha-cn-base': 'https://huggingface.co/sijunhe/nezha-cn-base/resolve/main/config.json',
}






class 						snake_case  (  UpperCAmelCase	):
    __magic_name__ :    Any   					=					NEZHA_PRETRAINED_CONFIG_ARCHIVE_MAP
    __magic_name__ :    List[str]   					=					'''nezha'''





    def __init__(							self     : Dict    ,		A     : List[Any]=2_1_1_2_8    ,		A     : List[Any]=7_6_8    ,		A     : str=1_2    ,		A     : Optional[Any]=1_2    ,		A     : Dict=3_0_7_2    ,		A     : Any="gelu"    ,		A     : List[str]=0.1    ,		A     : int=0.1    ,		A     : Optional[int]=5_1_2    ,		A     : Optional[int]=6_4    ,		A     : List[Any]=2    ,		A     : Optional[Any]=0.02    ,		A     : Optional[Any]=1E-12    ,		A     : str=0.1    ,		A     : Union[str, Any]=0    ,		A     : str=2    ,		A     : Tuple=3    ,		A     : str=True    ,		**A     : Optional[int]    ,		):


      '''simple docstring'''




      super().__init__(pad_token_id=A    ,		bos_token_id=A    ,		eos_token_id=A    ,		**A      )

      a					:      Optional[Any]    =       vocab_size
      a					:      Tuple    =       hidden_size
      a					:      Tuple    =       num_hidden_layers
      a					:      List[Any]    =       num_attention_heads
      a					:      Any    =       hidden_act
      a					:      Optional[Any]    =       intermediate_size
      a					:      str    =       hidden_dropout_prob
      a					:      Any    =       attention_probs_dropout_prob
      a					:      Optional[Any]    =       max_position_embeddings
      a					:      Dict    =       max_relative_position
      a					:      Dict    =       type_vocab_size
      a					:      Tuple    =       initializer_range
      a					:      List[str]    =       layer_norm_eps
      a					:      List[str]    =       classifier_dropout
      a					:      str    =       use_cache












"""simple docstring"""


def       snake_case  (A_				:str     ,      A_				:bool = False				):







  '''simple docstring'''

  if not isinstance(A_     ,      A_				):
    a					:      Union[str, Any]    =       f'''Expected string as input, found {type(A_				)}'''
    raise ValueError(A_				)
  if not isinstance(A_     ,      A_				):
    a					:      Optional[int]    =       f'''Expected boolean as use_pascal parameter, found {type(A_				)}'''
    raise ValueError(A_				)

  a					:      Tuple    =       input_str.split('_'				)

  a					:      Dict    =       0 if use_pascal else 1

  a					:      int    =       words[start_index:]

  a					:      int    =       [word[0].upper() + word[1:] for word in words_to_capitalize]

  a					:      List[str]    =       '' if use_pascal else words[0]

  return "".join([initial_word, *capitalized_words]				)


if __name__ == "__main__":
   from doctest import testmod

   testmod()




