'Convert 1 hot probabilities to sentences.
Args:
prob (Tensor): Word probabilities of each sentence of batch.
Of size (vocab_size, batch_size * (max_sentence_length+1))
Returns:
list containing sentences'

def prob_to_word(self, prob):

    sents = []
    if (not isinstance(prob, np.ndarray)):
        prob = prob.get()
    words = [self.index_to_vocab[x] for x in np.argmax(prob, axis=0).tolist()]
    for sent_index in xrange(self.be.bsz):
        sent = []
        for i in xrange(self.max_sentence_length):
            word = words[((self.be.bsz * i) + sent_index)]
            sent.append(word)
            if (((i > 0) and (word == self.end_token)) or (i >= 20)):
                break
        sents.append('    '.join(sent))
    return sents
