e06fa429553cd8a183f4fe57ea07e311b4f6ef4e,tests/classifiers/test_tensorflow.py,TestTensorFlowClassifier,test_fit_generator,#TestTensorFlowClassifier#,81

Before Change

        logger.info("Accuracy after fitting TF classifier with generator: %.2f%%", (accuracy * 100))
        self.assertEqual(accuracy, 0.65)
        tf.reset_default_graph()
        sess.close()

    def test_nb_classes(self):
        classifier, sess = get_classifier_tf()

After Change

            self.assertAlmostEqual(y_predicted[0, i], y_expected[0][i], places=4)

    def test_fit_generator(self):
        if not self.is_version_2:
            classifier, sess = get_classifier_tf()

            // Create TensorFlow data generator
            x_tensor = tf.convert_to_tensor(self.x_train.reshape(10, 100, 28, 28, 1))
            y_tensor = tf.convert_to_tensor(self.y_train.reshape(10, 100, 10))
            dataset = tf.data.Dataset.from_tensor_slices((x_tensor, y_tensor))
            iterator = dataset.make_initializable_iterator()
            data_gen = TFDataGenerator(sess=sess, iterator=iterator, iterator_type="initializable", iterator_arg={},
                                       size=1000, batch_size=100)

            // Test fit and predict
            classifier.fit_generator(data_gen, nb_epochs=2)
            predictions = classifier.predict(self.x_test)
            predictions_class = np.argmax(predictions, axis=1)
            true_class = np.argmax(self.y_test, axis=1)
            accuracy = np.sum(predictions_class == true_class) / len(true_class)

            logger.info("Accuracy after fitting TensorFlow classifier with generator: %.2f%%", (accuracy * 100))
            self.assertEqual(accuracy, 0.65)

    def test_nb_classes(self):
        self.assertEqual(self.classifier.nb_classes(), 10)

    def test_input_shape(self):

Instances