for _ in range(100):
        ix = torch.tensor([[choice]]).to(device)
        output, (state_h, state_c) = net(ix, (state_h, state_c))

        _, top_ix = torch.topk(output[0], k=top_k)
        choices = top_ix.tolist()
        choice = np.random.choice(choices[0])
        words.append(int_to_vocab[choice])

    print(' '.join(words))