fc81d77c1e18719b58c2437e8408972ad90ce547,tests/classifiers/test_keras.py,TestKerasClassifier,test_loss_gradient,#TestKerasClassifier#,241

Before Change

        grads = classifier.loss_gradient(x_test, y_test)

        self.assertTrue(np.array(grads.shape == (NB_TEST, 28, 28, 1)).all())
        self.assertNotEqual(np.sum(grads), 0)

    def test_functional_model(self):
        // Need to update the functional_model code to produce a model with more than one input and output layers...
        keras_model = KerasClassifier(self.functional_model, clip_values=(0, 1), input_layer=1, output_layer=1)

After Change

    def test_loss_gradient(self):
        (_, _), (x_test, y_test) = self.mnist
        classifier = get_classifier_kr()

        // Test gradient
        grads = classifier.loss_gradient(x_test, y_test)

Instances