298178ce60c17dce5044964e2221461b94f499a4,tests/attacks/inference/test_membership_inference.py,,test_black_box_image,#Any#Any#,91

Before Change

    for classifier in classifier_list:
        attack = MembershipInferenceBlackBox(classifier)
        // train attack model using only attack_train_ratio of data
        attack.fit(x_train[:attack_train_size], y_train[:attack_train_size],
                   x_test[:attack_test_size], y_test[:attack_test_size])
        // infer attacked feature on remainder of data
        inferred_train = attack.infer(x_train[attack_train_size:], y_train[attack_train_size:])
        inferred_test = attack.infer(x_test[attack_test_size:], y_test[attack_test_size:])
        // check accuracy
        train_pos = sum(inferred_train) / len(inferred_train)
        test_pos = sum(inferred_test) / len(inferred_test)
        assert (train_pos > test_pos or
                train_pos == pytest.approx(test_pos, abs=0.03) or
                test_pos == 1)

After Change

    for classifier in classifier_list:
        attack = MembershipInferenceBlackBox(classifier)
        backend_check_membership_accuracy(attack, get_default_mnist_subset, attack_train_ratio, 0.03)


@pytest.mark.parametrize("model_type", ["nn", "rf", "gb"])
def test_black_box_tabular(model_type, get_tabular_classifier_list, get_iris_dataset):

Instances