
"""simple docstring"""


import numpy as np



def        _lowerCamelCase(__UpperCamelCase       ,					__UpperCamelCase			)							->					Optional[Any]:
	_lowerCAmelCase								=np.array(__UpperCamelCase			)
	_lowerCAmelCase								=np.array(__UpperCamelCase			)

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

	return score



def        _lowerCamelCase(__UpperCamelCase       ,					__UpperCamelCase			)							->					Optional[int]:
	_lowerCAmelCase								=np.array(__UpperCamelCase			)
	_lowerCAmelCase								=np.array(__UpperCamelCase			)

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

	_lowerCAmelCase								=square_diff.mean()
	return score



def        _lowerCamelCase(__UpperCamelCase       ,					__UpperCamelCase			)							->					Any:
	_lowerCAmelCase								=np.array(__UpperCamelCase			)
	_lowerCAmelCase								=np.array(__UpperCamelCase			)

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



def        _lowerCamelCase(__UpperCamelCase       ,					__UpperCamelCase			)							->					List[Any]:
	_lowerCAmelCase								=np.array(__UpperCamelCase			)
	_lowerCAmelCase								=np.array(__UpperCamelCase			)

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

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

	_lowerCAmelCase								=np.sqrt(__UpperCamelCase			)

	return score



def        _lowerCamelCase(__UpperCamelCase       ,					__UpperCamelCase			)							->					Union[str, Any]:
	_lowerCAmelCase								=np.array(__UpperCamelCase			)
	_lowerCAmelCase								=np.array(__UpperCamelCase			)

	_lowerCAmelCase								=predict - actual
	_lowerCAmelCase								=np.sum(__UpperCamelCase			) / len(__UpperCamelCase			)
	_lowerCAmelCase								=np.sum(__UpperCamelCase			) / len(__UpperCamelCase			)
	# print(numerator, denumerator)
	_lowerCAmelCase								=float(__UpperCamelCase			) / denumerator * 100

	return score



def        _lowerCamelCase(__UpperCamelCase       ,					__UpperCamelCase			)							->					Union[str, Any]:
	return np.mean(np.array(__UpperCamelCase			) == np.array(__UpperCamelCase			)			)





"""simple docstring"""


def        _lowerCamelCase(__UpperCamelCase = 20			)							->					int:

	try:
		_lowerCAmelCase								=int(__UpperCamelCase			)
	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."""			)
	_lowerCAmelCase								=0
	while 1:
		i += n * (n - 1)
		_lowerCAmelCase								=0
		for j in range(2       ,					__UpperCamelCase			):
			if i % j != 0:
				_lowerCAmelCase								=1
				break
		if nfound == 0:
			if i == 0:
				_lowerCAmelCase								=1
			return i
	return None


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



