code: def normalize(array, min_value=0., max_value=1.):
      
      arr_min = np.min(array)
      arr_max = np.max(array)
      normalized = (array - arr_min) / (arr_max - arr_min + K.epsilon())
      return (max_value - min_value) * normalized + min_value
docs: Normalizes the numpy array to (min_value, max_value)
  
      Args:
          array: The numpy array
          min_value: The min value in normalized array (Default value = 0)
          max_value: The max value in normalized array (Default value = 1)
  
      Returns:
          The array normalized to range between (min_value, max_value)