when using the first checkout action, it goes checks out the repo

we are running the agent on the same machine AgitatedDove14 , it worked before upgrading the clearml... we never set these credentials

the curl refers to the master

this?

Cool - what kind of objects are returned by .artifacts. getitem ? I want to check their docs

TimelyPenguin76 , this can safely be set to s3:// right?

I'm using pipe.start_locally so I imagine I don't have to .wait() right?

glad I managed to help back in some way

but can't right now

So just to be clear - the file server has nothing to do with the storage?

inference table is a pandas dataframe

Thanks Alon

I don't fully get it - it says it has to be enqueued

So prior to doing any work on the trains autoscaler servcice, I should first create a auto scaling group in AWS?

Cool - so that means the fileserver which comes with the host will stay emtpy? Or is there anything else being stored there?

so when I'm on the machine through SSH

AgitatedDove14 ⬆ please help 🙏

SuccessfulKoala55 here it is

What does that mean? How can I access this data?

Okay SuccessfulKoala55 , problem solved! Indeed the problem was that there is not .git folder. I updated necessary things to make the checkout action get the actual repo and now it works

It wasn't really clear to me what "standalone" means, maybe it will be better to add to the error

Error: Standalone

(no .git folder found)

script detected 'tasks/hp_optimization.py', but no requirements provided

and I'm using the same credentials

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

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 Task object has a method called Task.execute_remotely

Look it up here:
https://allegro.ai/docs/task.html#trains.task.Task.execute_remotely

the explicity of the variable queue makes it feels like it runs somewhere else

Okay so regarding the version - we are using 1.1.1

The thing with this error it that it happens sometimes, and when it happens it never goes away...
I don't know what causes it, but we have one host where it works okay, then someone else checks out the repo and tried and it fails for this error, while another guy can do the same and it will work for him

I'll check if this works tomorrow

When I ran the clearml-task --name ... -project ... -script .... it failed saying not requiremetns was found