test_with_dbd.py 文件源码

def test_detector(self):
        dataset, user_vocab, system_vocab = self.Reader.get_dataset()
        _labels = self.Reader.get_labels()
        labels = [lb.label for lb in _labels]
        model = self.make_model(user_vocab, system_vocab)
        model_if = model.create_interface(self.buckets, self.TRAIN_DIR)

        train_x, test_x, train_t, test_t = train_test_split(dataset, labels, test_size=0.2, random_state=42)

        with tf.Session() as sess:
            detector = Detector(sess, model_if)
            detector.train(sess, train_x, train_t)
            y = [detector.predict(sess, p) for p in test_x]

        report = classification_report(test_t, y, target_names=DbdReader.get_label_names())
        print(report)