What's the best way to refresh TensorBoard after new events/logs were added?

Question

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.

Answer 1

It turns out that TensorBoard backend refreshes the logs every minute. This has been reported as a TensorFlow issue.

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.

Answer 2

I advise to always start tensorboard with --reload_multifile True to force reloading all event files.