import tensorflow as tf

                image = self._do_cutout(image, w, h, cutout_size)

            return (image, clazz)

        (images, classes) = _prepare(images, classes)
        dataset = tf.data.Dataset.from_tensor_slices((images, classes)).repeat()
        if is_train:
            dataset = dataset.apply(tf.data.experimental.map_and_batch(map_func=_preprocess_train, batch_size=batch_size))
        else:
            dataset = dataset.batch(batch_size)
        dataset_itr = dataset.make_initializable_iterator()
        (images_batch, classes_batch) = dataset_itr.get_next()
        dataset_init_op = dataset_itr.initializer

