Great start! I'm not sure if I'll be able to commit time during the hackathon, but I'd like to help with this extension once I have a leaner period at work. I hope this will be open-source & accept contributions @<1541954607595393024:profile|BattyCrocodile47>

JitteryCoyote63 CostlyOstrich36 want to echo the statement that documentation should warn against the snap installation of docker.

I also want to highlight that the snap installation has major problems when it comes to volume mounting of priviliged paths etc. On my baremetal instance, even the docker-compose up started having problems which was resolved only when I switched to the docker documentation's installation.

Thanks @<1523701087100473344:profile|SuccessfulKoala55>

Thanks @<1523701070390366208:profile|CostlyOstrich36> . We were only changing this for each output_uri, but this makes our lives a bit easier. Thanks :)

DistinctShark58 I don't think Hyper Datasets is available in self-hosted ClearML community. Correct me if I am wrong.

What is weird is that (I think?) it worked Friday when I used it for another model object. Not sure what is happening here.

hey CostlyOstrich36 I have shared the log file that prints out device IDs, credentials, endpoints, etc on personal chat to avoid sharing anything accidentally that I might not have identified as a security problem. I have retracted most of those things, but just wanted to be sure.

@<1523701070390366208:profile|CostlyOstrich36> any thoughts?

@<1523701087100473344:profile|SuccessfulKoala55> What would be the recommended command to delete/unregister an agent? None of the CLI commands seemed relevant to this operation other than the clearml-agent daemon --stop command that seems to only be stopping running instances of the agent and not unregistering it.

Hi SuccessfulKoala55 I want to trigger a retraining pipeline every set cadence of a few months.

Hi @<1532170113770328064:profile|DelightfulElephant81> , there is a self-hosted version of ClearML that has access to all of the community edition features. You can use docker-compose/Helm to run it on your server. If you want to self-host the server while needing paid features like HyperDatasets, RBAC, ClearML Serving etc, you can choose to have the enterprise version.
See this: None

I'd like to understand this as well. I moved my data & model versioning to AWS S3. So, can I get rid of the fileserver? Can I use Cloudwatch to work with logs rather than (what I assume is being done by) Elasticsearch?

@<1523701205467926528:profile|AgitatedDove14> this worked and gave me what I exactly needed. Thanks.

Hi @<1523701070390366208:profile|CostlyOstrich36> , sorry to tag you directly. Is this something that you have clarity on? Our team currently has an exploration where we are trying to see how we can optimize the pipeline we've already defined for the edge device.

@<1523701087100473344:profile|SuccessfulKoala55> for training experiments, I do see the scalars show the learning rate etc being picked up from the model training. They update real-time along with the scalars related to GPU & CPU monitoring that I showed above. However, the console doesn't show any sort of logs and just remains a blank screen

This is on a self-hosted instance of ClearML running on docker-compose as a PoC

Hey CostlyOstrich36 , do you want me to share a specific part of the execution section? There is quite a bit of content hidden under scroll.

Other information about the experiments are visible, yes.

I do see plots, yes.
Scalars, sometimes I do and sometimes I don't. I am not reporting any scalars manually in my experiments. Whenever I do see scalars, it has been the monitoring values of CPU & GPU like below.

Hi @<1523701087100473344:profile|SuccessfulKoala55> this is what I see in the Settings page

• WebApp: 1.8.0-254 • Server: 1.8.0-254 • API: 2.22

For more context here, I am using the docker compose self hosted version running on Linux systems.

SuccessfulKoala55 Thanks for letting me know. I'll immediately give this a try.

Sure @<1523701435869433856:profile|SmugDolphin23> . Thanks for the quick response.

Let me know if you need more information from me. I can add that information in a git issue if you want to track it that way.

For other people's reference: None

@<1523701087100473344:profile|SuccessfulKoala55> I have also tried using the API reference listed None to unregister a worker. However, it goes unregistered for a few seconds and comes back up on the UI. The Post request returns with a 200 response and says that the job is done.

For the people who are going to visit this thread later, what I found works is basically providing all the defining parameters of the clearml worker and then passing the arg --stop in the command.
Ex: sudo clearml-agent daemon --detached --queue gpu_default gpu_priority --gpus 0 --docker --stop
What didn't work for me: sudo clearml-agent daemon --stop <worker-id>

Hey @<1523701087100473344:profile|SuccessfulKoala55> that was actually my first approach. I used the command clearml-agent daemon --stop <worker-id>
However, this is what I saw:

CostlyOstrich36

Hi @<1523701070390366208:profile|CostlyOstrich36> , I took a look at the CLI & SDK documentation for the Dataset class, but it didn't look like I had an option to control the preview. Am I looking at the wrong place? Apologies if I missed something from the documentation.

It says that the environment setup is completed, and it has cloned the project as well, but why is it facing an issue here?

Is there a way I can auto-increment the iteration value instead of specifying an integer? SuccessfulKoala55