






"""simple docstring"""





import numpy as np







def 	lowerCAmelCase_(			SCREAMING_SNAKE_CASE			,						SCREAMING_SNAKE_CASE       )       ->						List[Any]:
    """simple docstring"""

    UpperCamelCase__								=     np.array(SCREAMING_SNAKE_CASE       )
    UpperCamelCase__								=     np.array(SCREAMING_SNAKE_CASE       )

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

    return score







def 	lowerCAmelCase_(			SCREAMING_SNAKE_CASE			,						SCREAMING_SNAKE_CASE       )       ->						Any:
    """simple docstring"""

    UpperCamelCase__								=     np.array(SCREAMING_SNAKE_CASE       )
    UpperCamelCase__								=     np.array(SCREAMING_SNAKE_CASE       )

    UpperCamelCase__								=     predict - actual
    UpperCamelCase__								=     np.square(SCREAMING_SNAKE_CASE       )

    UpperCamelCase__								=     square_diff.mean()
    return score







def 	lowerCAmelCase_(			SCREAMING_SNAKE_CASE			,						SCREAMING_SNAKE_CASE       )       ->						Union[str, Any]:
    """simple docstring"""

    UpperCamelCase__								=     np.array(SCREAMING_SNAKE_CASE       )
    UpperCamelCase__								=     np.array(SCREAMING_SNAKE_CASE       )

    UpperCamelCase__								=     predict - actual
    UpperCamelCase__								=     np.square(SCREAMING_SNAKE_CASE       )
    UpperCamelCase__								=     square_diff.mean()
    UpperCamelCase__								=     np.sqrt(SCREAMING_SNAKE_CASE       )
    return score







def 	lowerCAmelCase_(			SCREAMING_SNAKE_CASE			,						SCREAMING_SNAKE_CASE       )       ->						Optional[int]:
    """simple docstring"""

    UpperCamelCase__								=     np.array(SCREAMING_SNAKE_CASE       )
    UpperCamelCase__								=     np.array(SCREAMING_SNAKE_CASE       )

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

    UpperCamelCase__								=     log_predict - log_actual
    UpperCamelCase__								=     np.square(SCREAMING_SNAKE_CASE       )
    UpperCamelCase__								=     square_diff.mean()

    UpperCamelCase__								=     np.sqrt(SCREAMING_SNAKE_CASE       )

    return score







def 	lowerCAmelCase_(			SCREAMING_SNAKE_CASE			,						SCREAMING_SNAKE_CASE       )       ->						Optional[int]:
    """simple docstring"""

    UpperCamelCase__								=     np.array(SCREAMING_SNAKE_CASE       )
    UpperCamelCase__								=     np.array(SCREAMING_SNAKE_CASE       )

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

    return score







def 	lowerCAmelCase_(			SCREAMING_SNAKE_CASE			,						SCREAMING_SNAKE_CASE       )       ->						int:
    """simple docstring"""

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






'''simple docstring'''







def 				_snake_case (		lowercase = 2_0						)       ->       int:

				try:
								__a       :     Optional[Any]								=	int(lowercase						)
				except (TypeError, ValueError):
								raise TypeError("""Parameter n must be int or castable to int."""						)
				if n <= 0:
								raise ValueError("""Parameter n must be greater than or equal to one."""						)
				__a       :     List[Any]								=	0
				while 1:
								i += n * (n - 1)
								__a       :     Union[str, Any]								=	0
								for j in range(2			,    lowercase						):
												if i % j != 0:
																__a       :     Any								=	1
																break
								if nfound == 0:
												if i == 0:
																__a       :     List[str]								=	1
												return i
				return None


if __name__ == "__main__":
					print(f'''{solution() = }''')