



"""simple docstring"""







import numpy as np


def       __SCREAMING_SNAKE_CASE      (   __UpperCAmelCase					,							__UpperCAmelCase	):
		_lowercase							:      Union[str, Any]			=					np.array(_snake_case	)
		_lowercase							:      Any			=					np.array(_snake_case	)

		_lowercase							:      int			=					abs(predict - actual	)
		_lowercase							:      Tuple			=					difference.mean()

		return score


def       __SCREAMING_SNAKE_CASE      (   __UpperCAmelCase					,							__UpperCAmelCase	):
		_lowercase							:      int			=					np.array(_snake_case	)
		_lowercase							:      Any			=					np.array(_snake_case	)

		_lowercase							:      Optional[int]			=					predict - actual
		_lowercase							:      Optional[Any]			=					np.square(_snake_case	)

		_lowercase							:      List[Any]			=					square_diff.mean()
		return score


def       __SCREAMING_SNAKE_CASE      (   __UpperCAmelCase					,							__UpperCAmelCase	):
		_lowercase							:      Optional[int]			=					np.array(_snake_case	)
		_lowercase							:      Optional[int]			=					np.array(_snake_case	)

		_lowercase							:      Dict			=					predict - actual
		_lowercase							:      List[Any]			=					np.square(_snake_case	)
		_lowercase							:      Union[str, Any]			=					square_diff.mean()
		_lowercase							:      str			=					np.sqrt(_snake_case	)
		return score


def       __SCREAMING_SNAKE_CASE      (   __UpperCAmelCase					,							__UpperCAmelCase	):
		_lowercase							:      int			=					np.array(_snake_case	)
		_lowercase							:      Tuple			=					np.array(_snake_case	)

		_lowercase							:      Tuple			=					np.log(predict + 1	)
		_lowercase							:      Optional[int]			=					np.log(actual + 1	)

		_lowercase							:      str			=					log_predict - log_actual
		_lowercase							:      Tuple			=					np.square(_snake_case	)
		_lowercase							:      Any			=					square_diff.mean()

		_lowercase							:      Union[str, Any]			=					np.sqrt(_snake_case	)

		return score


def       __SCREAMING_SNAKE_CASE      (   __UpperCAmelCase					,							__UpperCAmelCase	):
		_lowercase							:      Any			=					np.array(_snake_case	)
		_lowercase							:      Union[str, Any]			=					np.array(_snake_case	)

		_lowercase							:      str			=					predict - actual
		_lowercase							:      Union[str, Any]			=					np.sum(_snake_case	) / len(_snake_case	)
		_lowercase							:      Dict			=					np.sum(_snake_case	) / len(_snake_case	)
		# print(numerator, denumerator)
		_lowercase							:      int			=					float(_snake_case	) / denumerator * 100

		return score


def       __SCREAMING_SNAKE_CASE      (   __UpperCAmelCase					,							__UpperCAmelCase	):
		return np.mean(np.array(_snake_case	) == np.array(_snake_case	)	)











"""simple docstring"""







import sys

def _a (		_snake_case      ,       _snake_case							):







      """simple docstring"""






      if not numbers:
            return 0
      if target == 0 and target in numbers:
            return 0
      if not isinstance(_snake_case      ,       (list, tuple)							) or not all(
          isinstance(_snake_case      ,       _snake_case							) for number in numbers							):
            raise ValueError("""numbers must be an iterable of integers"""							)

      UpperCAmelCase							=       UpperCAmelCase							=       UpperCAmelCase							=       0
      UpperCAmelCase							=       sys.maxsize

      while right < len(_snake_case							):
            curr_sum += numbers[right]
            while curr_sum >= target and left <= right:
                  UpperCAmelCase							=       min(_snake_case      ,       right - left + 1							)
                  curr_sum -= numbers[left]
                  left += 1
            right += 1

      return 0 if min_len == sys.maxsize else min_len



