code: def encode_labels(labels, label_path):
      """Encoding labels according to order in the labels file, so it is compliant with ModelWrapper"""
      labels2 = np.copy(labels)
      encoded = [encoding_function(x, label_path) for x in labels2]
      return encoded
  
file_path: tcav/tcav/tcav_examples/discrete/kdd99_model.py
imports: from __future__ import division
  from __future__ import print_function
  import os
  import tensorflow
  import argparse
  import numpy
  from sklearn.model_selection import train_test_split
  import sklearn.datasets
  from sklearn.preprocessing import OrdinalEncoder
label_desc: Use image node_id 4 for calling a global function with example usage: encode_labels(labels, label_path) and returns: encoded