import numpy as np



def       __SCREAMING_SNAKE_CASE    (   __UpperCamelCase       :			List[Any]					,	__UpperCamelCase       :			Tuple      )				->   List[Any]:







  """simple docstring"""





  SCREAMING_SNAKE_CASE__     				= np.array(__UpperCamelCase      )
  SCREAMING_SNAKE_CASE__     				= np.array(__UpperCamelCase      )

  SCREAMING_SNAKE_CASE__     				= abs(predict - actual      )
  SCREAMING_SNAKE_CASE__     				= difference.mean()

  return score



def       __SCREAMING_SNAKE_CASE    (   __UpperCamelCase       :			Dict					,	__UpperCamelCase       :			str      )				->   List[Any]:







  """simple docstring"""





  SCREAMING_SNAKE_CASE__     				= np.array(__UpperCamelCase      )
  SCREAMING_SNAKE_CASE__     				= np.array(__UpperCamelCase      )

  SCREAMING_SNAKE_CASE__     				= predict - actual
  SCREAMING_SNAKE_CASE__     				= np.square(__UpperCamelCase      )

  SCREAMING_SNAKE_CASE__     				= square_diff.mean()
  return score



def       __SCREAMING_SNAKE_CASE    (   __UpperCamelCase       :			Optional[Any]					,	__UpperCamelCase       :			List[Any]      )				->   Dict:







  """simple docstring"""





  SCREAMING_SNAKE_CASE__     				= np.array(__UpperCamelCase      )
  SCREAMING_SNAKE_CASE__     				= np.array(__UpperCamelCase      )

  SCREAMING_SNAKE_CASE__     				= predict - actual
  SCREAMING_SNAKE_CASE__     				= np.square(__UpperCamelCase      )
  SCREAMING_SNAKE_CASE__     				= square_diff.mean()
  SCREAMING_SNAKE_CASE__     				= np.sqrt(__UpperCamelCase      )
  return score



def       __SCREAMING_SNAKE_CASE    (   __UpperCamelCase       :			Optional[Any]					,	__UpperCamelCase       :			Any      )				->   Union[str, Any]:







  """simple docstring"""





  SCREAMING_SNAKE_CASE__     				= np.array(__UpperCamelCase      )
  SCREAMING_SNAKE_CASE__     				= np.array(__UpperCamelCase      )

  SCREAMING_SNAKE_CASE__     				= np.log(predict + 1      )
  SCREAMING_SNAKE_CASE__     				= np.log(actual + 1      )

  SCREAMING_SNAKE_CASE__     				= log_predict - log_actual
  SCREAMING_SNAKE_CASE__     				= np.square(__UpperCamelCase      )
  SCREAMING_SNAKE_CASE__     				= square_diff.mean()

  SCREAMING_SNAKE_CASE__     				= np.sqrt(__UpperCamelCase      )

  return score



def       __SCREAMING_SNAKE_CASE    (   __UpperCamelCase       :			int					,	__UpperCamelCase       :			List[str]      )				->   List[Any]:







  """simple docstring"""





  SCREAMING_SNAKE_CASE__     				= np.array(__UpperCamelCase      )
  SCREAMING_SNAKE_CASE__     				= np.array(__UpperCamelCase      )

  SCREAMING_SNAKE_CASE__     				= predict - actual
  SCREAMING_SNAKE_CASE__     				= np.sum(__UpperCamelCase      ) / len(__UpperCamelCase      )
  SCREAMING_SNAKE_CASE__     				= np.sum(__UpperCamelCase      ) / len(__UpperCamelCase      )
  # print(numerator, denumerator)
  SCREAMING_SNAKE_CASE__     				= float(__UpperCamelCase      ) / denumerator * 1_00

  return score






def       __SCREAMING_SNAKE_CASE    (   __UpperCamelCase       :			str					,	__UpperCamelCase       :			Any      )				->   List[Any]:







  """simple docstring"""





  return np.mean(np.array(__UpperCamelCase      ) == np.array(__UpperCamelCase      )      )

from hashlib import mda, shaaaa

__lowerCamelCase     :					Dict				  =						(shaaaa, mda)







class __snake_case							:




   def __init__(       self     :							str			,      _lowercase     :							int = 8 ):



     """simple docstring"""






     SCREAMING_SNAKE_CASE__     				= 0B0
     SCREAMING_SNAKE_CASE__     				= size




   def       __a		(       self     :							List[str]			,      _lowercase     :							str ):



     """simple docstring"""






     SCREAMING_SNAKE_CASE__     				= self.hash_(_lowercase )
     self.bitarray |= h




   def       __a		(       self     :							int			,      _lowercase     :							str ):



     """simple docstring"""






     SCREAMING_SNAKE_CASE__     				= self.hash_(_lowercase )
     return (h & self.bitarray) == h




   def __contains__(       self     :							Union[str, Any]			,      _lowercase     :							str ):



     """simple docstring"""






     return self.exists(_lowercase )




   def       __a		(       self     :							Dict			,      _lowercase     :							int ):



     """simple docstring"""






     SCREAMING_SNAKE_CASE__     				= bin(_lowercase )[2:]
     return res.zfill(self.size )




   @property
   def       __a		(       self     :							Tuple ):



     """simple docstring"""






     return self.format_bin(self.bitarray )




   def       __a		(       self     :							Optional[int]			,      _lowercase     :							str ):



     """simple docstring"""






     SCREAMING_SNAKE_CASE__     				= 0B0
     for func in HASH_FUNCTIONS:
       SCREAMING_SNAKE_CASE__     				= (
           int.from_bytes(func(value.encode() ).digest()			,      """little""" ) % self.size
       )
       res |= 2**position
     return res




   def       __a		(       self     :							str			,      _lowercase     :							str ):



     """simple docstring"""






     return self.format_bin(self.hash_(_lowercase ) )




   @property
   def       __a		(       self     :							Union[str, Any] ):



     """simple docstring"""






     SCREAMING_SNAKE_CASE__     				= bin(self.bitarray ).count("""1""" )
     return (n_ones / self.size) ** len(_lowercase )
