original_docstring: 
          Compute perturbation between input and denoising_examples.
          Args:
              multiplying_factor: float.
  
          Returns:
              numpy.ndarray. The perturbation that is multiplied by multiplying_factor.
          
docstring: Compute perturbation between input and denoising_examples.
docstring_tokens: Compute perturbation between input and denoising_examples .
code: def perturbation(self, multiplying_factor=1.0):
          """
          Compute perturbation between input and denoising_examples.
          Args:
              multiplying_factor: float.
  
          Returns:
              numpy.ndarray. The perturbation that is multiplied by multiplying_factor.
          """
          assert self.__input is not None
          assert (self.__denoising_sample is not None) or \
                 (self.__bad_denoising_example is not None)
          if self.__denoising_sample is not None:
              return multiplying_factor * (
                  self.__denoising_sample - self.__input)
          else:
              return multiplying_factor * (
                  self.__bad_denoising_example - self.__input)
code_tokens: def perturbation ( self , multiplying_factor = 1.0 ) : assert self . __input is not None assert ( self . __denoising_sample is not None ) or ( self . __bad_denoising_example is not None ) if self . __denoising_sample is not None : return multiplying_factor * ( self . __denoising_sample - self . __input ) else : return multiplying_factor * ( self . __bad_denoising_example - self . __input )
short_docstring: Compute perturbation between input and denoising_examples.
short_docstring_tokens: Compute perturbation between input and denoising_examples .
comment: """
          Compute perturbation between input and denoising_examples.
          Args:
              multiplying_factor: float.
  
          Returns:
              numpy.ndarray. The perturbation that is multiplied by multiplying_factor.
          """