How do display different runs in TensorBoard?
TensorflowTensorboardTensorflow Problem Overview
Tensorflow Solutions
Solution 1 - Tensorflow
In addition to TensorBoard scanning subdirectories (so you can pass a directory containing the directories with your runs), you can also pass multiple directories to TensorBoard explicitly and give custom names (example taken from the --help output):
tensorboard --logdir=name1:/path/to/logs/1,name2:/path/to/logs/2
More information can be found at the TensorBoard documentation.
In recent versions of TensorBoard, aliasing this way requires a different argument, however its use is discouraged (quote from current documentation on github - linked above):
> Logdir & Logdir_spec (Legacy Mode)
>
> You may also pass a comma separated list of log directories, and
> TensorBoard will watch each directory. You can also assign names to
> individual log directories by putting a colon between the name and the
> path, as in
>
> tensorboard --logdir_spec name1:/path/to/logs/1,name2:/path/to/logs/2
>
> This flag (--logdir_spec) is discouraged and can usually be avoided.
> TensorBoard walks log directories recursively; for finer-grained
> control, prefer using a symlink tree. Some features may not work when
> using --logdir_spec instead of --logdir.
Solution 2 - Tensorflow
I found the answer to my own question on github (https://github.com/tensorflow/tensorflow/issues/1548).
You need to put your logs in a subfolder e.g. /logs/run1/ and then run tensorboard on the root folder e.g. /logs/.
Solution 3 - Tensorflow
New version of tensorboard changed logdir to logdir_spec:
tensorboard --logdir_spec=name1:/path/to/logs/1,name2:/path/to/logs/2
Solution 4 - Tensorflow
It seems that just declaring it like this is ok:
writer = SummaryWriter(logdir='/runs/you_tag')
Then tensorboard will create a you_tag
folder below runs/
, in the meantime, the web application will refresh and find you_tag
.