Thanks AgitatedDove14 and TimelyMouse69 . The intention was to have some traceability between the two setups. I think the best way is to enforce some naming convention (for project and name) so we can know how they are related? Any better suggestions?

https://clear.ml/docs/latest/docs/integrations/storage/
Try add the <path to your cert> for s3.credentials.verify.

Do u have an example of how I can define the packages to be installed for every steps of the pipeline?

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

Example i build my docker image using a image in docker hub. In this image, i installed torch and cupy packages. But when i run my experiment in this image, the packages are not found.

Yes, I ran the experiment inside.

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?

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.

Nope. In my local drive

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?

U want to share your clearml.conf here?

By the way, how can I start up the clearml agent using the clearml-agent image instead of SDK? Do u have an example of the docker run command that includes the queue, gpus etc?

Nice. That should work. Thanks

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?

Nice. It is actually dataset.id .

Yes. But I not sure what's the agent running. I only know how to stop it if I have the agent id

I not very sure tbh. Just want to see if this is useful....

I got SSL error few days back and I solved it by adding cert to /etc/ssl/certs and perform update-ca-certificates .

export REQUESTS_CA_BUNDLE=/etc/ssl/certs/ca-certificates.crt

Add this. Note that verify might not work with sdk.aws.s3.verify but sdk.aws.s3.credentials . Pls see the attached image.

Example:
aws {
s3 {
credentials: [
{
` ...

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

Yup. But I happened to reinstall my server and the data is lost. And the agent continue running.

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

Yup, was thinking of bash script.

The intent is to generate some outputs from the clearml task and thinking probably to package it into a docker image for ease of sharing to others that are not plug into our network and able to run the image directly.

Hello CostlyOstrich36 I am facing an issue now. basically i installed all necessary python packages in my docker image. But somehow, the clearml-agent does not seems to be able to detect these global packages. I don't see them in the "installed packages". Any advice?

It return false. Just to share abit more, I have the requirements.txt in gitlab with my codes and are in folders. Do I need to provide a gitlab path?

OK I will send here shortly.

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

Thanks

Cool thanks guys. I am clearer now. Was confused by the obsolete info. Thanks for the clarification.

Yes. The training working well with cuda

Is there a way to troubleshoot further?

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
`...