添加新事件/日志后刷新 TensorBoard 的最佳方法是什么? [英] What's the best way to refresh TensorBoard after new events/logs were added?
问题描述
在打开的 TensorBoard 会话中快速查看最新事件文件中更新图形的最佳方法是什么?重新运行我的 Python 应用程序会导致创建一个新的日志文件，其中包含潜在的新事件/图表.然而，TensorBoard 似乎没有注意到这些差异，除非重新启动.
What is the best way to quickly see the updated graph in the most recent event file in an open TensorBoard session? Re-running my Python app results in a new log file being created with potentially new events/graph. However, TensorBoard does not seem to notice those differences, unless restarted.
推荐答案
事实证明，TensorBoard 后端每分钟刷新一次日志.这已被报告为 TensorFlow 问题.
It turns out that TensorBoard backend refreshes the logs every minute. This has been reported as a TensorFlow issue.
可以使用 TensorBoard 进程的 --reload_interval 标志配置重载间隔，但该选项目前仅在 master 中可用，0.8 版本尚未发布.
The reload interval can be configured using the --reload_interval flag of the TensorBoard process, but this option is currently only available in master and as of version 0.8 has not been released.
这篇关于添加新事件/日志后刷新 TensorBoard 的最佳方法是什么?的文章就介绍到这了，希望我们推荐的答案对大家有所帮助，也希望大家多多支持IT屋！
