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

Alright,
Thanks a lot!

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

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?

the environment setting you added to your vault is only applied inside the instance when the agent starts running there, not as part of the command that starts the instance.
The most common DevOps practice for having these kind of variables in the init script but not completely exposed to the naked eye is by adding something like

export MY_ENV_VAR=$(echo '<base64-encoded secret>' | base64 --decode)

to the init script （編集済み)

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:

GrumpySeaurchin29 Thank you!

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

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)

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

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

Yes, Thank you!

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

All machines are under my company's ownership

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?

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.

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

I got the same issue as well last night.

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.

no, it is AWS EC2

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

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

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

I am using the github actions given server.

clearml 1.2.0 pypi_0 pypi

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)

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.

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)

Thanks a lot 👍