How do Monitored Training Sessions work?
可以将文章内容翻译成中文,广告屏蔽插件可能会导致该功能失效(如失效,请关闭广告屏蔽插件后再试): 问题: I'm trying to understand the difference between using tf.Session and tf.train.MonitoredTrainingSession , and where I might prefer one over the other. It seems that when I use the latter, I can avoid many "chores" such as initializing variables, starting queue runners, or setting up file writers for summary operations. On the other hand, with a monitored training session, I cannot specify the computation graph I want to use explicitly. All of this seems rather mysterious to me. Is there some underlying philosophy behind how these classes were