f90c78bd5444f77936566e9a67d9a7513fd3be48,tensorflow_privacy/privacy/membership_inference_attack/keras_evaluation_example.py,,main,#Any#,70

Before Change

                                             (train_data, train_labels),
                                             (test_data, test_labels),
                                             [])
  print("all_thresh_loss_advantage",
        attack_results["all_thresh_loss_advantage"])


if __name__ == "__main__":
  app.run(main)

After Change

      attack_types=[AttackType.THRESHOLD_ATTACK, AttackType.K_NEAREST_NEIGHBORS]
      )

  attack_properties, attack_values = get_all_attack_results(attack_results)
  print("\n".join(["  %s: %.4f" % (", ".join(p), r) for p, r in
                   zip(attack_properties, attack_values)]))

Instances