Google Tensorflow 中的事件文件 [英] Event files in Google Tensorflow

问题描述

我正在使用 Tensorflow 构建神经网络，我想在 Tensorboard 上显示训练结果.到目前为止一切正常.但是我有一个关于 Tensorboard 的事件文件"的问题.我注意到每次运行 python 脚本时，它都会生成不同的事件文件.当我运行我的本地服务器时$ python/usr/local/lib/python2.7/dist-packages/tensorflow/tensorboard/tensorboard.py --logdir=/home/project/tmp/，如果有就显示错误超过 1 个事件文件.这似乎很烦人，因为每当我运行本地服务器时，我都必须删除所有以前的事件文件才能使其工作.所以我想知道是否有任何解决方案可以防止这个问题.我真的很感激.

I am using Tensorflow to build up the Neural Network, and I would like to show training results on the Tensorboard. So far everything works fine. But I have a question on "event file" for the Tensorboard. I notice that every time when I run my python script, it generates different event files. And when I run my local server using $ python /usr/local/lib/python2.7/dist-packages/tensorflow/tensorboard/tensorboard.py --logdir=/home/project/tmp/, it shows up error if there are more than 1 event files. It seems to be annoying since whenever I run my local server, I have to delete all previous event files to make it work. So I'm wondering if there is any solution to prevent this issue. I would really appreciate it.

推荐答案

从 TensorBoard 的角度来看，最好的解决方案是为您的实验创建一个根目录，例如~/tensorflow/mnist_experiment，然后为每次运行创建一个新的子目录，例如~/tensorflow/mnist_experiment/run1/...

The best solution from a TensorBoard perspective is to have a root directory for your experiment, e.g. ~/tensorflow/mnist_experiment, and then to create a new subdirectory for each run, e.g. ~/tensorflow/mnist_experiment/run1/...

然后针对根目录运行 TensorBoard，并且每次调用代码时，将 SummaryWriter 设置为指向一个新的子目录.然后，TensorBoard 将正确解释所有事件文件，并且还可以轻松地在不同的运行之间进行比较.

Then run TensorBoard against the root directory, and every time you invoke your code, setup the SummaryWriter pointing to a new subdirectory. TensorBoard will then interpret all of the event files correctly, and it will also make it easy to compare between your different runs.

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