10686681ded0802f4f234064367a78a57144270e,tests/attacks/inference/test_membership_inference.py,,test_black_box_loss_tabular,#Any#Any#Any#,86

Before Change

@pytest.mark.parametrize("model_type", ["nn", "rf", "gb"])
def test_black_box_loss_tabular(model_type, get_tabular_classifier_list, get_iris_dataset):
    classifier_list = get_tabular_classifier_list(MembershipInferenceBlackBox)
    if not classifier_list:
        logging.warning("Couldn"t perform this test because no classifier is defined")
        return

    for classifier in classifier_list:
        if type(classifier).__name__ == "PyTorchClassifier" or type(classifier).__name__ == "TensorFlowV2Classifier":
            attack = MembershipInferenceBlackBox(classifier, input_type="loss", attack_model_type=model_type)
            backend_check_membership_accuracy(attack, get_iris_dataset, attack_train_ratio, 0.15)


@pytest.mark.only_with_platform("keras")
@pytest.mark.skipif(keras.__version__.startswith("2.2"), reason="requires Keras 2.3.0 or higher")
def test_black_box_keras_loss(get_iris_dataset):
    (x_train, y_train), (_, _) = get_iris_dataset

After Change

@pytest.mark.parametrize("model_type", ["nn", "rf", "gb"])
def test_black_box_loss_tabular(model_type, tabular_dl_estimator_for_attack, get_iris_dataset):
    try:
        classifier = tabular_dl_estimator_for_attack(MembershipInferenceBlackBox)
        if type(classifier).__name__ == "PyTorchClassifier" or type(classifier).__name__ == "TensorFlowV2Classifier":
            attack = MembershipInferenceBlackBox(classifier, input_type="loss", attack_model_type=model_type)
            backend_check_membership_accuracy(attack, get_iris_dataset, attack_train_ratio, 0.15)
    except ARTTestException as e:
        add_warning(e)


@pytest.mark.skipMlFramework("tensorflow", "pytorch", "scikitlearn", "mxnet", "kerastf")
@pytest.mark.skipif(keras.__version__.startswith("2.2"), reason="requires Keras 2.3.0 or higher")
def test_black_box_keras_loss(get_iris_dataset):
    try:

Instances