from tensorflow.contrib.eager.python.examples.spinn import data

    # 1. Create and load a fake SNLI data file and a fake GloVe embedding file.
    snli_1_0_dir = os.path.join(self._temp_data_dir, "snli/snli_1.0")
    fake_train_file = self._create_test_data(snli_1_0_dir)

    vocab = data.load_vocabulary(self._temp_data_dir)
    word2index, embed = data.load_word_vectors(self._temp_data_dir, vocab)

    train_data = data.SnliData(fake_train_file, word2index)
    dev_data = data.SnliData(fake_train_file, word2index)
    test_data = data.SnliData(fake_train_file, word2index)

    # 2. Create a fake config.
    config = _test_spinn_config(
        data.WORD_VECTOR_LEN, 4,
        logdir=os.path.join(self._temp_data_dir, "logdir"))

    # 3. Test training of a SPINN model.
    trainer = spinn.train_or_infer_spinn(
