a4376fc2e3c1eec67decf36bc0a1771ad17a771e,src/attacks/newtonfool_unittest.py,TestNewtonFool,test_krclassifier,#TestNewtonFool#,71

Before Change

        krc.fit(x_train, y_train, batch_size=batch_size, nb_epochs=2)

        print(krc.predict(x_test))
        print(krc.predict(x_test, logits=True))
        grads = krc.class_gradient(x_test, logits=False)
        import numpy as np
        print("min is: ", np.min(grads), ", max is: ", np.max(grads))

After Change

        y_pred = krc.predict(x_test)
        y_pred_adv = krc.predict(x_test_adv)
        y_pred_bool = y_pred.max(axis=1, keepdims=1) == y_pred
        y_pred_max = y_pred.max(axis=1)
        y_pred_adv_max = y_pred_adv[y_pred_bool]
        self.assertTrue((y_pred_max >= y_pred_adv_max).all())

Instances