





'''simple docstring'''


import numpy as np




def       A							(      _UpperCAmelCase   :				List[Any]						,_UpperCAmelCase   :				Any					)  ->				Any:


  '''simple docstring'''




  __lowerCAmelCase		:    int			     =  np.array(_UpperCAmelCase					)
  __lowerCAmelCase		:    int			     =  np.array(_UpperCAmelCase					)

  __lowerCAmelCase		:    Optional[Any]			     =  abs(predict - actual					)
  __lowerCAmelCase		:    List[Any]			     =  difference.mean()

  return score




def       A							(      _UpperCAmelCase   :				Dict						,_UpperCAmelCase   :				str					)  ->				Optional[Any]:


  '''simple docstring'''




  __lowerCAmelCase		:    Any			     =  np.array(_UpperCAmelCase					)
  __lowerCAmelCase		:    Optional[Any]			     =  np.array(_UpperCAmelCase					)

  __lowerCAmelCase		:    Optional[Any]			     =  predict - actual
  __lowerCAmelCase		:    List[Any]			     =  np.square(_UpperCAmelCase					)

  __lowerCAmelCase		:    str			     =  square_diff.mean()
  return score




def       A							(      _UpperCAmelCase   :				Optional[int]						,_UpperCAmelCase   :				List[str]					)  ->				Optional[Any]:


  '''simple docstring'''




  __lowerCAmelCase		:    List[Any]			     =  np.array(_UpperCAmelCase					)
  __lowerCAmelCase		:    Tuple			     =  np.array(_UpperCAmelCase					)

  __lowerCAmelCase		:    Tuple			     =  predict - actual
  __lowerCAmelCase		:    Optional[int]			     =  np.square(_UpperCAmelCase					)
  __lowerCAmelCase		:    Dict			     =  square_diff.mean()
  __lowerCAmelCase		:    Union[str, Any]			     =  np.sqrt(_UpperCAmelCase					)
  return score




def       A							(      _UpperCAmelCase   :				Any						,_UpperCAmelCase   :				Any					)  ->				Any:


  '''simple docstring'''




  __lowerCAmelCase		:    Optional[Any]			     =  np.array(_UpperCAmelCase					)
  __lowerCAmelCase		:    str			     =  np.array(_UpperCAmelCase					)

  __lowerCAmelCase		:    Tuple			     =  np.log(predict + 1					)
  __lowerCAmelCase		:    int			     =  np.log(actual + 1					)

  __lowerCAmelCase		:    str			     =  log_predict - log_actual
  __lowerCAmelCase		:    Optional[int]			     =  np.square(_UpperCAmelCase					)
  __lowerCAmelCase		:    Any			     =  square_diff.mean()

  __lowerCAmelCase		:    List[Any]			     =  np.sqrt(_UpperCAmelCase					)

  return score




def       A							(      _UpperCAmelCase   :				str						,_UpperCAmelCase   :				Optional[int]					)  ->				List[Any]:


  '''simple docstring'''




  __lowerCAmelCase		:    Tuple			     =  np.array(_UpperCAmelCase					)
  __lowerCAmelCase		:    Any			     =  np.array(_UpperCAmelCase					)

  __lowerCAmelCase		:    str			     =  predict - actual
  __lowerCAmelCase		:    List[str]			     =  np.sum(_UpperCAmelCase					) / len(_UpperCAmelCase					)
  __lowerCAmelCase		:    Optional[int]			     =  np.sum(_UpperCAmelCase					) / len(_UpperCAmelCase					)
  # print(numerator, denumerator)
  __lowerCAmelCase		:    Optional[int]			     =  float(_UpperCAmelCase					) / denumerator * 1_0_0

  return score




def       A							(      _UpperCAmelCase   :				Union[str, Any]						,_UpperCAmelCase   :				str					)  ->				Tuple:


  '''simple docstring'''




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












'''simple docstring'''


from typing import Callable




def       A							(      _UpperCAmelCase   :				Callable					)  ->				Dict:


  '''simple docstring'''




  def wrapper(_UpperCAmelCase   :				Optional[Any]					):
    __lowerCAmelCase		:    List[Any]			     =  function_with_docstring.__doc__
    return target_function

  return wrapper





