docs: def deprocess_input(input_array, input_range=(0, 255)):
      """Utility function to scale the `input_array` to `input_range` throwing away high frequency artifacts.
  
      Args:
          input_array: An N-dim numpy array.
          input_range: Specifies the input range as a `(min, max)` tuple to rescale the `input_array`.
  
      Returns:
          The rescaled `input_array`.
      """
      # normalize tensor: center on 0., ensure std is 0.1
      input_array = input_array.copy()
      input_array -= input_array.mean()
      input_array /= (input_array.std() + K.epsilon())
      input_array *= 0.1
  
      # clip to [0, 1]
      input_array += 0.5
      input_array = np.clip(input_array, 0, 1)
  
      # Convert to `input_range`
      return (input_range[1] - input_range[0]) * input_array + input_range[0]