code: def prepare_dataset(labels_path):
      """Fetches data from sklearn.
  
      Encodes categorical variables with Ordinal Encoding
      """
      data, labels = sklearn.datasets.fetch_kddcup99(return_X_y=True)
      encoded_data = encode_variables(data)
      encoded_labels = encode_labels(labels, labels_path)
      return encoded_data, encoded_labels
  
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 6 for calling a global function with example usage: prepare_dataset(labels_path) and returns: encoded_data,  encoded_labels