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533 × Eureka!AgitatedDove14 I still can't get it to work... I couldn't figure out how can I change the clearml version in the runtime of the Cleanup Service as I'm not in control of the agent that executes it
AgitatedDove14 is the scale a part of the problem? Because not only the colors are wrong, the scale does not appear
What does that mean? How can I access this data?
I assume that at some points in the execution, the client (where the task is running) is sending JSONs to the mongo service, and that is what we see in the web UI.
Since we are talking about a case where there is no internet available, maybe these could be dumped into files/stdout and let the user manually insert them.
The manual insertion UX could be something like a CLI copy-paste or and endpoint for files - but since your UX is so good ( 🙂 ) I'm sure you'll figure this part out better
the path to the JSON file
nvidia/cuda:10.1-base-ubuntu18.04
I prefer we debug on my machine (tell me what you want to check) than create a snippet
I don't think the problem is setting that variable, I think it has something to do with it but not that obvious... Because it did work for me in the past, since then we docker-compose up/downed a few times, changed some other things etc... Can't figure out what made it get to this point
to fix it, I excluded this var entirely from the docker-compose
Not sure I understand, if i run pipe.start_locally(run_pipeline_steps_locally=True|False) what is the difference betwee ntrue and false? assuming I want to execute locally
Hahahah thanks for the help SuccessfulKoala55 & CostlyOstrich36
I really do feel it would be a nice to have the ability to easily configure the Cleanup Service to cleanup only specific projects / tasks as its a common use case to have a project dedicated for debugging and alike
Will try this out and report
thx TimelyPenguin76
skimming over this, I can't find how to filter by project name or something similar
I only found Project ID, which I'm not sure what this refers to - I have the project name
I showed you this phenomenon in the UI photos in the other thread
glad I managed to help back in some way
Oh I get it, that also makes sense with the docs directing this at inference jobs and avoiding GPU - because of the 1-N thing
I'm saying that because in the task under "INSTALLED PACKAGES" this is what appears
moreover, in each pipeline I have 10 different settings of task A -> Task b (and then task C), each run 1-2 fails randomly