code: 
  """simple docstring"""
  
  
  
  
  
  
  
  import numpy as np
  def 			__UpperCAmelCase		(		a_			:		List[str]    ,  a_			:		Any				)     ->       Optional[int]:
     _UpperCAmelCase   	=					np.array(a_				)
     _UpperCAmelCase   	=					np.array(a_				)
  
     _UpperCAmelCase   	=					abs(predict - actual				)
     _UpperCAmelCase   	=					difference.mean()
  
     return score
  def 			__UpperCAmelCase		(		a_			:		List[str]    ,  a_			:		int				)     ->       str:
     _UpperCAmelCase   	=					np.array(a_				)
     _UpperCAmelCase   	=					np.array(a_				)
  
     _UpperCAmelCase   	=					predict - actual
     _UpperCAmelCase   	=					np.square(a_				)
  
     _UpperCAmelCase   	=					square_diff.mean()
     return score
  def 			__UpperCAmelCase		(		a_			:		List[Any]    ,  a_			:		Any				)     ->       Dict:
     _UpperCAmelCase   	=					np.array(a_				)
     _UpperCAmelCase   	=					np.array(a_				)
  
     _UpperCAmelCase   	=					predict - actual
     _UpperCAmelCase   	=					np.square(a_				)
     _UpperCAmelCase   	=					square_diff.mean()
     _UpperCAmelCase   	=					np.sqrt(a_				)
     return score
  def 			__UpperCAmelCase		(		a_			:		int    ,  a_			:		Optional[int]				)     ->       List[Any]:
     _UpperCAmelCase   	=					np.array(a_				)
     _UpperCAmelCase   	=					np.array(a_				)
  
     _UpperCAmelCase   	=					np.log(predict + 1				)
     _UpperCAmelCase   	=					np.log(actual + 1				)
  
     _UpperCAmelCase   	=					log_predict - log_actual
     _UpperCAmelCase   	=					np.square(a_				)
     _UpperCAmelCase   	=					square_diff.mean()
  
     _UpperCAmelCase   	=					np.sqrt(a_				)
  
     return score
  def 			__UpperCAmelCase		(		a_			:		int    ,  a_			:		Dict				)     ->       str:
     _UpperCAmelCase   	=					np.array(a_				)
     _UpperCAmelCase   	=					np.array(a_				)
  
     _UpperCAmelCase   	=					predict - actual
     _UpperCAmelCase   	=					np.sum(a_				) / len(a_				)
     _UpperCAmelCase   	=					np.sum(a_				) / len(a_				)
     # print(numerator, denumerator)
     _UpperCAmelCase   	=					float(a_				) / denumerator * 1_00
  
     return score
  
  
  def 			__UpperCAmelCase		(		a_			:		int    ,  a_			:		Any				)     ->       str:
     return np.mean(np.array(a_				) == np.array(a_				)				)
  
  
style_context: 
  """simple docstring"""
  
  
  
  
  
  
  
  import warnings
  
  from .generation import FlaxGenerationMixin
  
  
  
  
  
  
  class     __a			(					lowerCAmelCase_			):
         # warning at import time
         warnings.warn(
             'Importing `FlaxGenerationMixin` from `src/transformers/generation_flax_utils.py` is deprecated and will '
             'be removed in Transformers v5. Import as `from transformers import FlaxGenerationMixin` instead.'				,	lowerCAmelCase_				,	)
  
  