Alright,
Thanks a lot!

Thanks a lot 👍

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

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

1.2.0

Still no good, managed to apply with errors only

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

That helps a lot!
Thanks Martin.
Although I didn't understand why you mentioned torch in my case?
Since I don't use it directly, I guess somewhere along the way multiprocessing does get activated (in HPO)
I would guess it relates to parallelization of Tasks execution of the HyperParameterOptimizer class?

clearml 1.2.0 pypi_0 pypi

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

I do have the configuration vault feature.
I managed to make it work.
Seems like I have been using it wrong.
In order to facilitate the multiple credentials one must use the Clearml SDK obviously.
So I just started using StorageManager and it works.

Thanks.

Update:
Manged to make the credentials attached to the configuration when the task is spinned,
Although boto3 in the script still uses the "default" access keys instead of the newly added keys

I am using the github actions given server.

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)

GrumpySeaurchin29 Thank you!

I tried.
it looks like this,

sudo apt update
sudo apt install amazon-ecr-credential-helper
aws ecr get-login-password --region us-east-1 | docker login --username AWS --password-stdin ****

But my problem is that I can't even see whether it passes my init script properly (tried to add printing comment but I cannot see the output) anywhere (nor scaler, nor task)

Yes, Thank you!

Important to notice I am running my instances on GCP, but the container is on ECR (AWS)

I got the same issue as well last night.

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)

You are right Idan,
I consulted our Private ClearML channel.
you cannot insert these environment variables any other place,
only in init script.
Here is the full quote:

It's generated automatically by HPO script.
So it might be added inside the report completion section

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

yep

I don't think it's related to the region.
I do have the log of the autoscaler.
We also have an autoscaler that was implemented from scarch before ClearML had the autoscaler application.
I wouldn't want to share the autoscaler log with this channel.

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,

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!

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?