code: def test_adv_debias_old(old_adult, new_adult):
      """Test that the predictions of the old and new AdversarialDebiasing match."""
      X, y, _ = new_adult
      tf.reset_default_graph()
      sess = tf.Session()
      old_adv_deb = OldAdversarialDebiasing(
          unprivileged_groups=[{"sex": 0}],
          privileged_groups=[{"sex": 1}],
          scope_name="old_classifier",
          sess=sess,
          num_epochs=5,
          seed=123,
      )
      old_preds = old_adv_deb.fit_predict(old_adult)
      sess.close()
      adv_deb = AdversarialDebiasing(
          "sex", num_epochs=5, random_state=123
      )
      new_preds = adv_deb.fit(X, y).predict(X)
      adv_deb.sess_.close()
      assert np.allclose(old_preds.labels.flatten(), new_preds)
  
file_path: AIF360/tests/sklearn/test_adversarial_debiasing.py
imports: import numpy
  from sklearn.model_selection import GridSearchCV
  from sklearn.metrics import accuracy_score
  import tensorflow.compat.v1
  from aif360.algorithms.inprocessing import AdversarialDebiasing
  from aif360.sklearn.inprocessing import AdversarialDebiasing
label_desc: Use image node_id 2 for calling a global function with example usage: test_adv_debias_old(old_adult, new_adult) without return types