import tensorflow as tf

    def _build_data_pipeline(self):

        def normalize(image, label):
            image = tf.cast(image, tf.float32) / 255.0
            return image, label

        dataset = tf.data.TFRecordDataset(["./data/train.tfrecord"])
        dataset = dataset.map(decode)
        dataset = dataset.map(normalize)
        dataset = dataset.batch(50)
        dataset = dataset.take(1)  # keep validating on the same items
        dataset = dataset.repeat()
