如何通过try-except语句突破这种for循环？

Question

我有一个引用https://machinetalk.org/2019/03/29/neural-machine-translation-with-attention-mechanism/?unapproved=67&moderation-hash=ea8e5dcb97c8236f68291788fbd746a7#comment-67:-的for循环，其中包含try-except块的摘录

for e in range(NUM_EPOCHS):
    en_initial_states = encoder.init_states(BATCH_SIZE)

    for batch, (source_seq, target_seq_in, target_seq_out) in enumerate(dataset.take(-1)):
        loss = train_step(source_seq, target_seq_in,
                          target_seq_out, en_initial_states)

        if batch % 100 == 0:
                print('Epoch {} Batch {} Loss {:.4f}'.format(
                    e + 1, batch, loss.numpy()))


    try:
        test_target_text,net_words = predict()
    except Exception:
      continue

    if loss <=0.0001:
       break

我希望从循环中走出来，不执行try块，离开所有东西，简单地从两个循环中走出来，即内循环和外循环以及整个try-except块。我不知道出了什么问题，因为在内/外循环块中使用if条件不起作用。

Answer 1

这可能是嵌套循环的问题，如this answer所述。他们建议使用return，但是你的循环需要写成一个函数。如果这没有吸引力，您可以尝试使用不同级别的break语句，如一些答案中所示。使用for，else构造(explained here)，我认为您的代码应该如下所示

for e in range(NUM_EPOCHS):
    en_initial_states = encoder.init_states(BATCH_SIZE)

    for batch, (source_seq, target_seq_in, target_seq_out) in enumerate(dataset.take(-1)):
        loss = train_step(source_seq, target_seq_in,
                          target_seq_out, en_initial_states)

        if batch % 100 == 0:
                print('Epoch {} Batch {} Loss {:.4f}'.format(
                    e + 1, batch, loss.numpy()))


    try:
        test_target_text,net_words = predict()
    except Exception:
      continue

    if loss <=0.0001:
       break
else:
    continue ###executed if inner loop did NOT break
break  ###executed if inner loop DID break