避免在标准错误上打印张量流 [英] Avoid tensorflow print on standard error

问题描述

有谁知道是否有一种方法可以防止 tensorflow 用 gpus 的内存分配日志污染标准错误?.我注意到当执行以下命令时:

anyone knows if there is a method to prevent tensorflow from polluting standard error with gpus' memory allocation log?. I noted that when the following command is executed:

with tf.Session() as sess:

tensorflow 在标准错误上打印关于内存和 GPU 资源分配的日志.类似的东西:

tensorflow prints on standard error a log about memory and gpu resources allocation. Something like:

I tensorflow/core/common_runtime/local_device.cc:25] Local device intra op parallelism threads: 48
Graphics Device pciBusID 0000:02:00.0
Free memory: 11.75GiB
...

出于重要原因，我想避免这种打印.

For important reasons, I wanna avoid this printing.

推荐答案

此问题最近已修复，如果您升级到 TensorFlow 0.12 或更高版本，则应该可用.

This was recently fixed, and should be available if you upgrade to TensorFlow 0.12 or later.

要禁用 TensorFlow 的所有日志输出，请在启动 Python 之前设置以下环境变量:

To disable all logging output from TensorFlow, set the following environment variable before launching Python:

$ export TF_CPP_MIN_LOG_LEVEL=3
$ python ...

您还可以通过更改TF_CPP_MIN_LOG_LEVEL的值来调整详细程度:

You can also adjust the verbosity by changing the value of TF_CPP_MIN_LOG_LEVEL:

• 0 = 记录所有消息(默认行为)
• 1 = INFO 消息不打印
• 2 = INFO 和 WARNING 消息不打印
• 3 = INFO、WARNING 和 ERROR 消息不打印

• 0 = all messages are logged (default behavior)
• 1 = INFO messages are not printed
• 2 = INFO and WARNING messages are not printed
• 3 = INFO, WARNING, and ERROR messages are not printed

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