44b6e6737a3385e9d5013bd7d90a96ff1648d94d,tests/attacks/evasion/test_fast_gradient.py,,test_l2_norm_images,#Any#Any#,233

Before Change

    for classifier in image_classifier_list:
        // TODO this if statement must be removed once we have a classifier for both image and tabular data
        if classifier is None:
            logging.warning("Couldn"t perform  this test because no classifier is defined")
            return

        attack = FastGradientMethod(classifier, eps=1, norm=2, batch_size=128)
        x_test_adv = attack.generate(x_test_mnist)

        utils_test.assert_almost_equal_mean(x_test_mnist, x_test_adv, 0.007636424, decimal=0.002)

After Change

        return

    for classifier in image_classifier_list:
        if FastGradientMethod.is_valid_classifier_type(classifier) is False:
            continue

        attack = FastGradientMethod(classifier, eps=1, norm=2, batch_size=128)
        x_test_adv = attack.generate(x_test_mnist)

        utils_test.assert_almost_equal_mean(x_test_mnist, x_test_adv, 0.007636424, decimal=0.002)

Instances