it might be an issue in the UI due to this unconventional address or network settings

I think this is related to an https://github.com/allegroai/clearml-server/issues/112#issue-1149080358 that seems to be a reoccurring issue across many different setups

Will do! What’s the process for adding task.reset to the public API, just adding it to the docs?

And here is a PR for the other part.

Is the GCP disk image released for it? I get access denied with this link: https://storage.googleapis.com/allegro-files/clearml-server/clearml-server-1-3-0.tar.gz
Cheers!

Ah apologies for getting the wrong end of the stick a bit!

Not sure if it helps you or not, but when the link to an artifact didn't work for me it was because the URL being used was internal to the server (I had an agent that had access to internal endpoints). In my case setting the agent fileserver url to the public domain solved my issue.

CostlyOstrich36 I use the GCP disk image to launch a Compute Engine instance which sits behind an HTTP load balancer

Is that deletion when deleting a task in the GUI?

Thank you 🙂

No worries, thanks for sorting it! 🙂

Another option would be to do
task.close() task.reset()And then execute an agent to pick up that task, but I don’t think reset is part of the public API. Is this risky?

Amazing, task.__dict__ is just what I was looking for!

It seems to be an issue that a few people are having problems with: https://github.com/allegroai/clearml-server/issues/112

From my limited understanding of it, I think it's the client that does the saving and communicating to the fileserver not the server, whereas deletion is done by the GUI/server which I guess could have different permissions somehow?

Yep can do 👍

Awesome, thanks SuccessfulKoala55 .

Thanks CumbersomeCormorant74

Perhaps linked to https://github.com/allegroai/clearml-server/issues/112 ?

Hi CostlyOstrich36 , thanks for getting back to me!

I want to launch multiple tasks from one python process to be run by multiple agents simultaneously.

My current process for launching one task remotely is to use task.execute_remotely , and then I separately spin up a VM and execute a ClearML agent on that VM with the task ID.

Ideally, I would like to create multiple tasks in this way - so do Task.init(…) , set up some configuration, and then task.execute_remotely in a l...

That's great, thank you very much. Will give it a whirl today or tomorrow