65007a1aebc07f13513f3feab3831a14ed72e732,art/attacks/newtonfool_unittest.py,TestNewtonFool,test_krclassifier,#TestNewtonFool#,125

Before Change

        (x_train, y_train), (x_test, _) = self.mnist

        // Create simple CNN
        model = Sequential()
        model.add(Conv2D(4, kernel_size=(5, 5), activation="relu", input_shape=(28, 28, 1)))
        model.add(MaxPooling2D(pool_size=(2, 2)))
        model.add(Flatten())
        model.add(Dense(10, activation="softmax"))

        model.compile(loss=keras.losses.categorical_crossentropy, optimizer=keras.optimizers.Adam(lr=0.01),
                      metrics=["accuracy"])

        // Get classifier
        krc = KerasClassifier((0, 1), model, use_logits=False)
        krc.fit(x_train, y_train, batch_size=BATCH_SIZE, nb_epochs=2)

        // Attack
        // import time
        nf = NewtonFool(krc, max_iter=5)

After Change

        :return:
        
        // Build KerasClassifier
        krc, sess = get_classifier_kr()

        // Get MNIST
        (_, _), (x_test, _) = self.mnist

Instances