f4503bb3a3be014b452f54d8e2d187bb6419f627,autokeras/classifier.py,ImageClassifier,predict,#ImageClassifier#Any#,216

Before Change

            init = tf.global_variables_initializer()
            sess.run(init)
            backend.set_session(sess)
        x_test = x_test.astype("float32") / 255
        model = self.load_searcher().load_best_model().produce_model()
        return self.y_encoder.inverse_transform(model.predict(x_test, ))

After Change

        outputs = []
        with torch.no_grad():
            for index, inputs in enumerate(test_loader):
                outputs.append(model(inputs).numpy())
        output = reduce(lambda x, y: np.concatenate((x, y)), outputs)
        return self.y_encoder.inverse_transform(output)

Instances