code: def load_adult():
      """Loads ADULT a2a as in LIBSVM and preprocesses to combine training and validation data."""
      # https://www.csie.ntu.edu.tw/~cjlin/libsvmtools/datasets/binary.html
  
      x = pd.read_csv("adult.csv")
      kf = KFold(n_splits=10)
      for train_index, test_index in kf.split(x):
          train, test = x.iloc[train_index, :], x.iloc[test_index, :]
      train_data = train.iloc[:, range(x.shape[1] - 1)].values.astype(
          "float32"
      )
      test_data = test.iloc[:, range(x.shape[1] - 1)].values.astype(
          "float32"
      )
  
      train_labels = (
          (train.iloc[:, x.shape[1] - 1] == 1).astype("int32").values
      )
      test_labels = (
          (test.iloc[:, x.shape[1] - 1] == 1).astype("int32").values
      )
  
      return train_data, train_labels, test_data, test_labels
  
file_path: privacy/research/GDP_2019/adult_tutorial.py
imports: from __future__ import absolute_import
  from __future__ import division
  from __future__ import print_function
  from absl import app
  from absl import flags
  import numpy
  import pandas
  from sklearn.model_selection import KFold
  import tensorflow
  from tensorflow import estimator
  from tensorflow.compat.v1 import estimator
  from tensorflow_privacy.privacy.analysis.gdp_accountant import compute_eps_poisson
  from tensorflow_privacy.privacy.analysis.gdp_accountant import compute_mu_poisson
  from tensorflow_privacy.privacy.optimizers import dp_optimizer
label_desc: Use image node_id 2 for calling a global function with example usage: load_adult() and returns: train_data,  train_labels,  test_data,  test_labels