


'''simple docstring'''


from math import factorial



class 	__lowerCAmelCase		:


  '''simple docstring'''







  def __init__(							self :       Union[str, Any]	,_a :       List[str]	,_a :       Optional[int] ):

        '''simple docstring'''




        A_						:  Optional[int]          =				real
        if isinstance(_a	,_a ):
              A_						:  str          =				[1] * rank
        else:
              A_						:  Dict          =				rank






  def __repr__(							self :       Tuple ):

        '''simple docstring'''




        return (
            f'{self.real}+'
            f'{"+".join(str(_a )+"E"+str(n+1 )for n,dual in enumerate(self.duals ) )}'
        )






  def        _a							(							self :       List[Any] ):

        '''simple docstring'''




        A_						:  Dict          =				self.duals.copy()
        while cur[-1] == 0:
              cur.pop(-1 )
        return Dual(self.real	,_a )






  def __add__(							self :       Optional[int]	,_a :       List[Any] ):

        '''simple docstring'''




        if not isinstance(_a	,_a ):
              return Dual(self.real + other	,self.duals )
        A_						:  Dict          =				self.duals.copy()
        A_						:  Dict          =				other.duals.copy()
        if len(_a ) > len(_a ):
              o_dual.extend([1] * (len(_a ) - len(_a )) )
        elif len(_a ) < len(_a ):
              s_dual.extend([1] * (len(_a ) - len(_a )) )
        A_						:  str          =				[]
        for i in range(len(_a ) ):
              new_duals.append(s_dual[i] + o_dual[i] )
        return Dual(self.real + other.real	,_a )

  a_  					=							__add__






  def __sub__(							self :       Optional[int]	,_a :       Tuple ):

        '''simple docstring'''




        return self + other * -1






  def __mul__(							self :       List[Any]	,_a :       Tuple ):

        '''simple docstring'''




        if not isinstance(_a	,_a ):
              A_						:  Optional[int]          =				[]
              for i in self.duals:
                    new_duals.append(i * other )
              return Dual(self.real * other	,_a )
        A_						:  int          =				[0] * (len(self.duals ) + len(other.duals ) + 1)
        for i, item in enumerate(self.duals ):
              for j, jtem in enumerate(other.duals ):
                    new_duals[i + j + 1] += item * jtem
        for k in range(len(self.duals ) ):
              new_duals[k] += self.duals[k] * other.real
        for index in range(len(other.duals ) ):
              new_duals[index] += other.duals[index] * self.real
        return Dual(self.real * other.real	,_a )

  a_  					=							__mul__






  def __truediv__(							self :       Dict	,_a :       Dict ):

        '''simple docstring'''




        if not isinstance(_a	,_a ):
              A_						:  List[str]          =				[]
              for i in self.duals:
                    new_duals.append(i / other )
              return Dual(self.real / other	,_a )
        raise ValueError






  def __floordiv__(							self :       Any	,_a :       Tuple ):

        '''simple docstring'''




        if not isinstance(_a	,_a ):
              A_						:  Optional[Any]          =				[]
              for i in self.duals:
                    new_duals.append(i // other )
              return Dual(self.real // other	,_a )
        raise ValueError






  def __pow__(							self :       str	,_a :       Union[str, Any] ):

        '''simple docstring'''




        if n < 0 or isinstance(_a	,_a ):
              raise ValueError("""power must be a positive integer""" )
        if n == 0:
              return 1
        if n == 1:
              return self
        A_						:  int          =				self
        for _ in range(n - 1 ):
              x *= self
        return x







def      lowerCamelCase					(      lowerCamelCase  :      List[Any]							,						lowerCamelCase  :      str							,						lowerCamelCase  :      int):
      if not callable(lowerCamelCase):
            raise ValueError("""differentiate() requires a function as input for func""")
      if not isinstance(lowerCamelCase							,						(float, int)):
            raise ValueError("""differentiate() requires a float as input for position""")
      if not isinstance(lowerCamelCase							,						lowerCamelCase):
            raise ValueError("""differentiate() requires an int as input for order""")
      A_						:  Tuple          =				Dual(lowerCamelCase							,						1)
      A_						:  int          =				func(lowerCamelCase)
      if order == 0:
            return result.real
      return result.duals[order - 1] * factorial(lowerCamelCase)


if __name__ == "__main__":
     import doctest

     doctest.testmod()




     def      lowerCamelCase					(      lowerCamelCase  :      List[Any]):
           return y**2 * y**4






     print(differentiate(f, 9, 2))




'''simple docstring'''


from ... import PretrainedConfig


__magic_name__			=      {
    'sijunhe/nezha-cn-base': 'https://huggingface.co/sijunhe/nezha-cn-base/resolve/main/config.json',
}



class 	__lowerCAmelCase		(							__SCREAMING_SNAKE_CASE    ):


  '''simple docstring'''







  a_  					=							NEZHA_PRETRAINED_CONFIG_ARCHIVE_MAP
  a_  					=							"""nezha"""






  def __init__(							self :       int	,_a :       Union[str, Any]=21128	,_a :       int=768	,_a :       Any=12	,_a :       List[str]=12	,_a :       str=3072	,_a :       int="gelu"	,_a :       int=0.1	,_a :       str=0.1	,_a :       Tuple=512	,_a :       List[Any]=64	,_a :       Dict=2	,_a :       List[Any]=0.02	,_a :       Optional[Any]=1e-12	,_a :       List[Any]=0.1	,_a :       Union[str, Any]=0	,_a :       Any=2	,_a :       Union[str, Any]=3	,_a :       int=True	,**_a :       int	,):

        '''simple docstring'''




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

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