train = get_stories(tar.extractfile(challenge.format("train")))
test = get_stories(tar.extractfile(challenge.format("test")))
vocab = sorted(reduce(lambda x, y: x | y, (set(story + q + [answer]) for story, q, answer in train + test)))
// Reserve 0 for masking via pad_sequences
vocab_size = len(vocab) + 1
word_idx = dict((c, i + 1) for i, c in enumerate(vocab))
After Change
train = get_stories(tar.extractfile(challenge.format("train")))
test = get_stories(tar.extractfile(challenge.format("test")))
vocab = set()
for story, q, answer in train + test:
vocab |= set(story + q + [answer])
vocab = sorted(vocab)
