code: def test_adv_debias_old_reproduce(old_adult):
      """Test that the old AdversarialDebiasing is reproducible."""
      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()
      tf.reset_default_graph()
      sess = tf.Session()
      old_adv_deb2 = OldAdversarialDebiasing(
          unprivileged_groups=[{"sex": 0}],
          privileged_groups=[{"sex": 1}],
          scope_name="old_classifier",
          sess=sess,
          num_epochs=5,
          seed=123,
      )
      old_preds2 = old_adv_deb2.fit_predict(old_adult)
      sess.close()
  
      assert np.allclose(old_preds.labels, old_preds2.labels)
  
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 1 for calling a global function with example usage: test_adv_debias_old_reproduce(old_adult) without return types