How to use the lineflow.reducers.FlatMap function in lineflow

def test_flat_map(self):
        reduced = reducers.FlatMap(lambda x: [x] * 3)(self.data)
        expected = [[x] * 3 for x in self.data]
        expected = [x for xs in expected for x in xs]
        for x, y in zip(reduced, expected):
            self.assertEqual(x, y)
        self.assertTrue(reduced._done)
        for x, y in zip(reduced, expected):
            self.assertEqual(x, y)

def build_vocab(dataset, cache='vocab.pkl'):
    if not osp.isfile(cache):
        seen = {}

        def extract_tokens(x):
            tokens = x['question']
            context = x['context']
            if context not in seen:
                seen[context] = True
                tokens += context
            return tokens

        counter = Counter(FlatMap(extract_tokens)(dataset))
        words, _ = zip(*counter.most_common())
        token_to_index = dict(zip(words, range(len(words))))
        with open(cache, 'wb') as f:
            pickle.dump((token_to_index, words), f)
    else:
        with open(cache, 'rb') as f:
            token_to_index, words = pickle.load(f)

    return token_to_index, words