If I understood correctly, if I tried to print(os.environ["MUJOCO_GL"]) after the clearml Task is created, this should be set?

Yes.

Good to know the --debug flag exists in master! 😄

Hi @<1523701087100473344:profile|SuccessfulKoala55> Thank you very much.
Is there some way to verify the server uses the correct configuration files? (E.g. see it in the logs/web ui). I Just tried it does not work.
At least I can see the async_delete service complains about a missing secret, so I can start debugging there. I am using the same config as for my agents, but somehow for async_delete it does not work...

Thank you very much!

I just tested with remote_execution and the problem seems to exist there, too. It is just that when the task switches from local to remote execution (i.e. exists the local script) the local scalars will appear, but no scalar of remote execution will show up. So also the iteration will not update. However, at least for remote execution I get live console output.

Just like in the git repo.

I do not have a global cuda install on this machine. Everything except for the driver is installed via conda.

How can I see that?
I have venv_update.enabled: true and detect_with_conda_freeze: true

Or maybe even better: How can I get all the information of the "INFO" page in the WebUI of a task?

I mean that locally I was able to install the correct version without a problem.

I forgot to add this:
` Here is my error:

Traceback (most recent call last):
File "src/run_gym.py", line 25, in <module>
print(os.environ["MUJOCO_GL"])
File "/home/tim/.clearml/venvs-builds/3.7/lib/python3.7/os.py", line 681, in getitem
raise KeyError(key) from None
KeyError: 'MUJOCO_GL' `
This is at the top of my script.

fyi: NVIDIA-SMI 460.56 Driver Version: 460.56 CUDA Version: 11.2

Thank you. The reports feature is super cool! Greetings to the team. One of the best features for educational use!

Thank you very much. I am going to try that.

conda 4.9.2

Can you give me an example how I can add a second fileserver?

Perfect, will try it. fyi: The conda_channels that I used are from clearml-agent init

And then also use priority_optional_packages: ["carla"]

For now I can tell you that with conda_freeze: true it fails, but with conda_freeze: false it works!

Thanks, that makes sense. Can you also explain what task_log_buffer_capacity does?

AgitatedDove14

Ah, thanks a lot. So for example the CleanUp Service ( https://github.com/allegroai/clearml/blob/master/examples/services/cleanup/cleanup_service.py ) should have no troubles deleting the artifacts.

Yea, that I knew 😄 But somehow I didn't think about the clearml.conf

I got some warnings about broken packages. I cleaned the conda cache with conda clean -a ` and now it installed fine!

For me this does not work (at least with nested tqdm bars, did not try single ones yet).

latest for everything.

Okay, great! I just want to run the cleanup services, however I am running into ssh issues so I wanted to restart it to try to debug.

This is the venc

Maybe related question: Will there be some documentation about clearml internals with the new documentation? ClearML seems to store stuff that's relevant to script execution outside of clearml.Task if I am not mistaken. I would like to learn a little bit about what the code structure / internal mechanism is.