我正在按照official tutorial中的说明尝试使用Google Cloud中的TPU训练变压器模型。
运行后，加载数据工作正常t2t-trainer \
--model=transformer \
--hparams_set=transformer_tpu \
--problem=translate_ende_wmt32k_packed \
--train_steps=500000 \
--eval_steps=3000 \
--data_dir=$DATA_DIR \
--output_dir=$OUT_DIR \
--use_tpu=True \
--cloud_tpu_name=$TPU_NAME
培训确实按预期开始，并且输出可能看起来像这样：
I1118 14:48:18.978163 140580835792320 tpu_estimator.py:2307] global_step/sec: 15.2942 [114/1944]
INFO:tensorflow:examples/sec: 978.827
I1118 14:48:18.978595 140580835792320 tpu_estimator.py:2308] examples/sec: 978.827
INFO:tensorflow:Enqueue next (100) batch(es) of data to infeed.
I1118 14:48:18.979720 140580835792320 tpu_estimator.py:600] Enqueue next (100) batch(es) of data to infeed.
INFO:tensorflow:Dequeue next (100) batch(es) of data from outfeed.
I1118 14:48:18.979935 140580835792320 tpu_estimator.py:604] Dequeue next (100) batch(es) of data from outfeed.
I1118 14:48:24.292932 140577566803712 transport.py:157] Attempting refresh to obtain initial access_token
WARNING:tensorflow:TPUPollingThread found TPU tpuv3-8 in state READY, and health HEALTHY.
W1118 14:48:24.353135 140577566803712 preempted_hook.py:91] TPUPollingThread found TPU tpuv3-8 in state READY, and health HEALTHY.
INFO:tensorflow:loss = 1.8486812, step = 113800 (6.536 sec)
I1118 14:48:25.512768 140580835792320 basic_session_run_hooks.py:260] loss = 1.8486812, step = 113800 (6.536 sec)
INFO:tensorflow:global_step/sec: 15.2986
I1118 14:48:25.514695 140580835792320 tpu_estimator.py:2307] global_step/sec: 15.2986
INFO:tensorflow:examples/sec: 979.11
I1118 14:48:25.515115 140580835792320 tpu_estimator.py:2308] examples/sec: 979.11
INFO:tensorflow:Enqueue next (100) batch(es) of data to infeed.
I1118 14:48:25.516618 140580835792320 tpu_estimator.py:600] Enqueue next (100) batch(es) of data to infeed.
INFO:tensorflow:Dequeue next (100) batch(es) of data from outfeed.
I1118 14:48:25.516829 140580835792320 tpu_estimator.py:604] Dequeue next (100) batch(es) of data from outfeed.
INFO:tensorflow:Outfeed finished for iteration (388, 47)
I1118 14:48:28.761935 140577575196416 tpu_estimator.py:279] Outfeed finished for iteration (388, 47)
INFO:tensorflow:loss = 1.5237397, step = 113900 (6.573 sec)
I1118 14:48:32.086134 140580835792320 basic_session_run_hooks.py:260] loss = 1.5237397, step = 113900 (6.573 sec)
但是，有时并且经过不确定的迭代次数（有时少于25k，有时超过400k，有时从不），训练突然停止。没有错误信息，但是没有更多的进展。在这种情况下，我得到以下输出：
I1120 13:40:33.828651 140684764419520 tpu_estimator.py:2307] global_step/sec: 16.3988
INFO:tensorflow:examples/sec: 1049.52
I1120 13:40:33.829339 140684764419520 tpu_estimator.py:2308] examples/sec: 1049.52
INFO:tensorflow:Enqueue next (1000) batch(es) of data to infeed.
I1120 13:40:33.830607 140684764419520 tpu_estimator.py:600] Enqueue next (1000) batch(es) of data to infeed.
INFO:tensorflow:Dequeue next (1000) batch(es) of data from outfeed.
I1120 13:40:33.830862 140684764419520 tpu_estimator.py:604] Dequeue next (1000) batch(es) of data from outfeed.
INFO:tensorflow:Outfeed finished for iteration (7, 0)
I1120 13:40:34.267921 140681504278272 tpu_estimator.py:279] Outfeed finished for iteration (7, 0)
I1120 13:40:39.989195 140681495885568 transport.py:157] Attempting refresh to obtain initial access_token
WARNING:tensorflow:TPUPollingThread found TPU tpuv3-5 in state READY, and health HEALTHY.
W1120 13:40:40.056418 140681495885568 preempted_hook.py:91] TPUPollingThread found TPU tpuv3-5 in state READY, and health HEALTHY.
I1120 13:41:10.124164 140681495885568 transport.py:157] Attempting refresh to obtain initial access_token
WARNING:tensorflow:TPUPollingThread found TPU tpuv3-5 in state READY, and health HEALTHY.
W1120 13:41:10.177670 140681495885568 preempted_hook.py:91] TPUPollingThread found TPU tpuv3-5 in state READY, and health HEALTHY.
I1120 13:41:40.259634 140681495885568 transport.py:157] Attempting refresh to obtain initial access_token
WARNING:tensorflow:TPUPollingThread found TPU tpuv3-5 in state READY, and health HEALTHY.
W1120 13:41:40.309398 140681495885568 preempted_hook.py:91] TPUPollingThread found TPU tpuv3-5 in state READY, and health HEALTHY.
I1120 13:42:10.377460 140681495885568 transport.py:157] Attempting refresh to obtain initial access_token
WARNING:tensorflow:TPUPollingThread found TPU tpuv3-5 in state READY, and health UNKNOWN.
W1120 13:42:10.431982 140681495885568 preempted_hook.py:91] TPUPollingThread found TPU tpuv3-5 in state READY, and health UNKNOWN.
I1120 13:42:40.508342 140681495885568 transport.py:157] Attempting refresh to obtain initial access_token
WARNING:tensorflow:TPUPollingThread found TPU tpuv3-5 in state READY, and health HEALTHY.
W1120 13:42:40.567739 140681495885568 preempted_hook.py:91] TPUPollingThread found TPU tpuv3-5 in state READY, and health HEALTHY.
I1120 13:43:10.638391 140681495885568 transport.py:157] Attempting refresh to obtain initial access_token
WARNING:tensorflow:TPUPollingThread found TPU tpuv3-5 in state READY, and health HEALTHY.
W1120 13:43:10.694900 140681495885568 preempted_hook.py:91] TPUPollingThread found TPU tpuv3-5 in state READY, and health HEALTHY.
I1120 13:43:40.763782 140681495885568 transport.py:157] Attempting refresh to obtain initial access_token
WARNING:tensorflow:TPUPollingThread found TPU tpuv3-5 in state READY, and health HEALTHY.
W1120 13:43:40.810777 140681495885568 preempted_hook.py:91] TPUPollingThread found TPU tpuv3-5 in state READY, and health HEALTHY.
I1120 13:44:10.889873 140681495885568 transport.py:157] Attempting refresh to obtain initial access_token
WARNING:tensorflow:TPUPollingThread found TPU tpuv3-5 in state READY, and health HEALTHY.
W1120 13:44:10.942733 140681495885568 preempted_hook.py:91] TPUPollingThread found TPU tpuv3-5 in state READY, and health HEALTHY.
I1120 13:44:41.011034 140681495885568 transport.py:157] Attempting refresh to obtain initial access_token
WARNING:tensorflow:TPUPollingThread found TPU tpuv3-5 in state READY, and health HEALTHY.
W1120 13:44:41.066553 140681495885568 preempted_hook.py:91] TPUPollingThread found TPU tpuv3-5 in state READY, and health HEALTHY.
请注意，报告的健康状况为UNKNOWN一次，可能与此问题相关，也可能无关。
要继续训练，我必须停止该过程，然后再次运行训练命令。然后它将加载最新的检查点并继续训练，直到最终再次停止。
我正在tmux会话中运行训练命令，因此这不应由我与Google Cloud之间的连接问题引起。实际上，我可以完全关闭所有窗口，并从另一台PC连接到正在运行的培训课程。
我已经看到了问题TPU training freezes in the middle of training，但是我使用的是预定义模型，并且我的存储桶在同一区域中定义（us-central1-a中的TPU，us-central1中的存储桶）。
编辑：如果相关，我目前正在免费试用1个月，我是通过申请TensorFlow Research Cloud项目获得的。也许这些群集节点的稳定性不如付费群集节点稳定？
Edit2：也许这与GitHub问题TPU dies after 3hrs (e.g. with no 'health' state)（和the follow up）有关？请注意，问题已解决，但给出的答案似乎与问题无关。另外，我已经在我的云VM中检查了文件/usr/local/lib/python2.7/dist-packages/tensorflow_core/python/tpu/preempted_hook.py，并且两个链接的更改都已合并。
答案 0 :(得分：0)
在TFRC的TPU培训时，我遇到了同样的问题。如警告所述，即使我们按照指示进行操作，TPU和Google Cloud之间的连接似乎也有问题。
我尝试了几种解决方案：
删除gcloud配置文件夹
rm -rf〜/ .config / gcloud
更新gcloud sdk：
gcloud组件更新
通过IAM允许TPU访问Cloud Bucket link！
TPU挂起错误仍然会发生，但发生频率较低。希望它可以对您的情况有所帮助，或者您可以找到通用的解决方案。
答案 1 :(得分：0)