我的问题和问题在两个代码块下面说明.

损失函数

def loss(labels, logits, sequence_lengths, label_lengths, logit_lengths):    
    scores = []
    for i in xrange(runner.batch_size):
        sequence_length = sequence_lengths[i]
        for j in xrange(length):
            label_length = label_lengths[i, j]
            logit_length = logit_lengths[i, j]

             # get top k indices <==> argmax_k(labels[i, j, 0, :], label_length)
            top_labels = np.argpartition(labels[i, j, 0, :], -label_length)[-label_length:]
            top_logits = np.argpartition(logits[i, j, 0, :], -logit_length)[-logit_length:]

            scores.append(edit_distance(top_labels, top_logits))

    return np.mean(scores)

# Levenshtein distance
def edit_distance(s, t):
    n = s.size
    m = t.size
    d = np.zeros((n+1, m+1))
    d[:, 0] = np.arrange(n+1)
    d[0, …