ray: [dashboard] Ray Dashboard not showing [tune] tab
What is the problem?
Ray Dashboard does not always display the Tune tab. And it seems random when it does display.
The first time that I used Ray the Tune tab worked fine(this was about a week ago), but from the day after until now the tab is not showing.
Except for yesterday, I did ray.shutdown() and then ray.init() again, and suddenly the tune tab was there(the web url went up to http://127.0.0.1:8266 from http://127.0.0.1:8265). The problem now was that when I was putting in the path to the tuning results nothing happened when pressing submit.
When I now do ray.shutdown() and then ray.init() again, this doesn’t work. (the web url also doesn’t go up)
I am running MacOS 10.15.5 with python 3.7.7
Reproduction (REQUIRED)
I used a new pyenv environment and did the following:
-
pip install -U https://s3-us-west-2.amazonaws.com/ray-wheels/latest/ray-1.1.0.dev0-cp37-cp37m-macosx_10_13_intel.whl -
python -
import ray -
ray.init() -
This is what is showing on http://127.0.0.1:8265:
Note: I get this warning: File descriptor limit 256 is too low for production servers and may result in connection errors. At least 8192 is recommended. --- Fix with 'ulimit -n 8192'
- I have verified my script runs in a clean environment and reproduces the issue.
- I have verified the issue also occurs with the latest wheels. @mfitton
About this issue
- Original URL
- State: open
- Created 4 years ago
- Comments: 17 (10 by maintainers)
Yeah, updating the docs is definitely a good idea. I’d argue that we want to have a
Tunetab in any case, but if the dependencies are not found, display a message with these install commands instead.Thanks @krficke, doing the steps you mentioned works!
I couldn’t find this information on the docs, maybe I missed it. Otherwise I think it’s useful to add it to the Installing ray or Ray Dashboard page.
@scottsun94 I think the tune tab is a useful feature since we can monitor the score and parameters conveniently without more coding. Tensorboard and ML flow are powerful tools, but we need to add more tensorboard logs manually, distributed logging is also problematic for tensorboard.
It would be nice if ray can write a tensorboard log and start a local TB server automatically. In such case the tune tab is unnecessary and the power of tensorboard is utilized.
Hi @JorDikk, thanks for raising this issue.
The Tune tab depends on the following dependencies:
The usual recommendation is to install
pip install "ray[tune]"even after installing the latest wheels, as this will install dependencies such as pandas and tabulate. However, it currently does not install tensorboard, as it is tensorflow specific. So the Tune tab still wouldn’t show.cc @simon-mo can we make the dependency on tensorboard optional and just not show a tensorboard tab/display a note if it is not found?