code: def get_features_range(model_settings):
      """Returns the expected min/max for generated features.
  
      Args:
        model_settings: Information about the current model being trained.
  
      Returns:
        Min/max float pair holding the range of features.
  
      Raises:
        Exception: If preprocessing mode isn't recognized.
      """
      # TODO(petewarden): These values have been derived from the observed ranges
      # of spectrogram and MFCC inputs. If the preprocessing pipeline changes,
      # they may need to be updated.
      if model_settings["preprocess"] == "average":
          features_min = 0.0
          features_max = 127.5
      elif model_settings["preprocess"] == "mfcc":
          features_min = -247.0
          features_max = 30.0
      elif model_settings["preprocess"] == "micro":
          features_min = 0.0
          features_max = 26.0
      else:
          raise Exception(
              'Unknown preprocess mode "%s" (should be "mfcc",'
              ' "average", or "micro")' % (model_settings["preprocess"])
          )
      return features_min, features_max
  
imports: import hashlib
  import math
  import os.path
  import random
  import re
  import sys
  import tarfile
  import numpy
  import urllib
  import tensorflow
  from tensorflow.python.ops import gen_audio_ops
  from tensorflow.python.ops import io_ops
  from tensorflow.python.platform import gfile
  from tensorflow.python.util import compat
label_desc: Use image node_id 5 for calling a global function with example usage: get_features_range(model_settings) and returns: features_min,  features_max