I see. Was wondering any advantage to do it any of the ways.

Hi SuccessfulKoala55 Thanks for pointing me to this repo. Was using this repo.

I didn't manage to find in this repo that if we still require to label the node app=clearml, like what was mentioned in the deprecated repo. Although from the values.yaml, the node selector is empty. Would u be able to advise?

How is the clearml data handled now then? Thanks

SuccessfulKoala55 i tried comment off fileserver, clearml dockers started but it doesn't seems to be able to start well. When I access clearml via webbrowser, site cannot be reached.

Just to confirm, I commented off these in docker-compose.yaml.

apiserver:
command:
- apiserver
container_name: clearml-apiserver
image: allegroai/clearml:latest
restart: unless-stopped
volumes:
- /opt/clearml/logs:/var/log/clearml
`...

Thanks. The examples uses upload_artifact which stores the files in output_uri. What if I do not want to save it but simply pass to next step, is there a way to do so?

@<1523701205467926528:profile|AgitatedDove14> do u mean not using helm but fill up the values and install with the yaml files directly? E.g. kubectl apply ...

I was browsing clearml agent gihub and saw this. Isn't this for spinning up clearml-agent in a docker and perform like a daemon?

seems like it was broken for numpy version 1.24.1.
Tried with numpy 1.23.5 and it works.

Alright. Thanks CostlyOstrich36

Nice. That should work. Thanks

Hi ExasperatedCrab78 I managed to get it. It was due to ip address set in examples.env.

SdK meaning I run the agent using clearml-agent daemon ....
Alternatively I understand I can also run the agent using docker run allegroai/clearml-agent:latest. But I cannot figure out how to add --restart, --queue, -- gpus flag to the container

Ok. Can I check that only the main script was stored in the task but not the dependent packages?

I guess the more correct way is to upload to some repo where the remote task can still pull from it?

Clearml 1.1.1. Yes, i have boto3 installed too.

Thanks I just realised I didn't add --docker

Yes. The training working well with cuda

Yea. Added an issue. We can follow up from there. Really hope that clearml serving can work, is a nice project.

Not exactly sure yet but I would think user tag for deployed make sense as it should be a deliberated user action. And additional system state is required too since a deployed state should have some pre-requitise system state.

I would also like to ask if clearml has different states for a task, model, or even different task types? Right now I dun see differences, is this a deliberated design?

@<1523701070390366208:profile|CostlyOstrich36> This is output_uri or where do I put this url?

Hi TimelyPenguin76 , nope. I don't see any errors. That's why not sure what went wrong

Nope. In my local drive

May I know where to set the cert to in env variable?

@<1523701205467926528:profile|AgitatedDove14> when my codes get the clearml datasets, it stores in the cache e.g. /$HOME/.clearml/cache....

I wanted it to be in a mounted PV instead, so other pods (in same node) who needed same datasets can use without pulling again.

It gets rerouted to http://app.clearml.home.ai/dashboard . with the same network error.

When I run as regular remote task it works. But when I run as a step in pipeline, it cannot access the same folder in my local machine.

Just to add, when I run the pipeline locally it works as well.

Hi CostlyOstrich36 I have run this task locally at first. This attempt was successful.

When I use this task to run in a pipeline (task was run remotely), it cannot find the external package. This seems logical but I not sure how to resolve this.

SuccessfulKoala55 Nope. I didn't even get to enter my name. I suspect there is some mistake in mapping the data folder.
Was using the template in https://github.com/allegroai/clearml-helm-charts to deploy.

Thanks

@<1523701070390366208:profile|CostlyOstrich36> Yes. I'm running on k8s