as a followup on this one @<1523701070390366208:profile|CostlyOstrich36> .
how do I make my agent install python 3.9 and not 3.7?

agent.default_python: 3.9
agent.python_binary: 3.9

but getting in the task:

Python executable with version '3.9' requested by the Task, not found in path, using '/clearml_agent_venv/bin/python3' (v3.7.3) instead

I see,
is there a possibility to "clear" a queue from python?
A "purge" method for :
clearml.backend_api.session.client.Queue
?
I can only watch the current length of the queue, how do I remove all task/ specific tasks?

Thanks a lot 👍

I am using the github actions given server.

1.2.0

I am not a staff member. But it seems like something quite trivial with not much effort.
if you can avoid conda and don't need the c++ dependencies that conda takes care of
(and since you can convert to pip fomat , you probably can).

Wouldn't this work?
https://gist.github.com/pemagrg1/f959c19ec18fee3ce2ff9b3b86b67c16

I took it offline with Alon shomrat from ClearML.
It seems like that the problem is solved (at least for now).
It's hard for me to tell why, and also for him.

The thing is this.
My optimizer works a bit different.
my "optimized task" is actually a task that gets a specific
Hyper parameters and then enqueus more tasks (each one on different object)

TimelyPenguin76 Maybe you were able to find the problem ?
I don't remember what was the solution.
Might just updated my ClearML version...

It's a private image (based off of this image).
` ======================================
Welcome to the Google Deep Learning VM

Version: pytorch-gpu.1-11.m91
Based on: Debian GNU/Linux 10 (buster) (GNU/Linux 4.19.0-21-cloud-amd64 x86_64\n) `I am leaving the docker line empty, so I assume there's no docker spun up for my agent,

My task runs just fine.
But no GPU.
(When it demands GPU it collapses).
Looking at the VM features on GCP UI it seems no GPU was defined for the VM.

CostlyOstrich36
Thank you,
Solved,
I messaged with Alon from your team and he will upload an update to the old repository.

Should note that it works when i run the container locally (with no external env variables).

Alright,
Thanks a lot!

yep

e.g.
my_optimizer = an_optimizer.get_optimizer() plot_optimization_history(my_optimizer._study)Since my_optimizer._study is an optuna object

So anyway,
you can pickle the above object (pickle the study).
But you can't actually pickle the optimizer itself as you said/

Yes, Thank you!

Nope. It gives me errors.
Just like the guy that replied in the thread I linked in my previous reply here.

Adding the flags he added also didn't help

Still no good, managed to apply with errors only

Just found this thread,
https://clearml.slack.com/archives/CTK20V944/p1639037799391000
Will try to follow and see (although it looks the same like what I tried)

Ok, seems like the problem is solved.
These uncommited changes were already applied to the local branch, but the git apply error wasn't very informative.

Thanks!

no, it is AWS EC2

folder is rather small.
3.5MB
Am able to see it in the artifacts.
but can't download it (the address is wrong)

As a matter of fact, all my tasks are "running" state although some of them have failed

All machines are under my company's ownership

Using an autoscaler service(on 24/7 EC2 machine)
that triggers EC2 workers (with an AMI I saved prior to activation)

Hope that helps