a7cd7a15a9baf741f2b4fcd32f3d8055827889b5,examples/word_language_model/predict.py,,,#,11

Before Change

learner.initialize()

if not args.cuda:
    learner.module_ = torch.load(args.checkpoint, map_location=lambda storage, location: "cpu")
else:
    learner.module_ = torch.load(args.checkpoint)

hidden = learner.module_.init_hidden(1)
input = Variable(torch.rand(1, 1).mul(ntokens).long(), volatile=True)
if args.cuda:
    input = input.cuda()

p = learner.predict_proba(np.array([[
    corpus.dictionary.word2idx["fish"],
    corpus.dictionary.word2idx["sees"],
    corpus.dictionary.word2idx["man"],

After Change

words = [corpus.dictionary.idx2word[n] for n in range(10)]

print(words)

p = learner.predict_proba(np.array([[
    corpus.dictionary.word2idx["fish"],
    corpus.dictionary.word2idx["sees"],

Instances