By the way, will downloading still happen if the datasets is available in the cache folder? Any specific settings to add to Dataset.get_local_copy()?
May I know where to set the cert to in env variable?
@<1526734383564722176:profile|BoredBat47> Just to check if u need to do update-ca-certificates or equivalent?
seems like it was broken for numpy version 1.24.1.
Tried with numpy 1.23.5 and it works.
Hi Bart, yes. Running with inference container.
OK let me try by adding to vol mount.
Thanks AgitatedDove14 . Specifically, I wanted to use my own clearml server and Triton. Thus, I attempted to use --engine-container-args during launch but error saying no such flag. Looked into --help but I guessed it is not updated yet.
CostlyOstrich36 I mean the dataset object in clearml as well as the data that is tied to this object.
The intent is to bring over to another clearlml setup and keep some form of traceability.
And just a suggestion which maybe I can post in GitHub issue too.
It is not very clear what are the purpose of the project name and name, even after I read the --help. Perhaps this is something that can be made clearer when updating the docu?
Just to add, when I run the pipeline locally it works as well.
Ah I think I was not very clear on my requirement. I was looking at porting project level, not entire clearml data over. Is it possible instead?
Hi TimelyPenguin76 , nope. I don't see any errors. That's why not sure what went wrong
I guess we need to understand the purpose of the various states. So far only "archive, draft, publish". Did I miss any?
Yea. Added an issue. We can follow up from there. Really hope that clearml serving can work, is a nice project.
@<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 ...
This is what I got. and when I see http400 error in the console.
JuicyFox94 and SuccessfulKoala55 Thanks alot. Indeed it is caused by dirty cookies.
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.
It gets rerouted to http://app.clearml.home.ai/dashboard . with the same network error.
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.
@<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.
@<1523701070390366208:profile|CostlyOstrich36> This is output_uri or where do I put this url?
@<1523701070390366208:profile|CostlyOstrich36> Yes. I'm running on k8s
Hi @<1523701070390366208:profile|CostlyOstrich36> , basically
- I uploaded dataset using clearml Datasets. The output_uri is pointed to my s3, thus the dataset is stored in s3. My s3 is setup with http only.
- When I retrieve the dataset for training, using
Dataset.get(), I encountered ssl cert error as the url to retrieve data washttps://<s3url>/...instead ofs3://<s3url>/...which is http. This is weird as the dataset url is without https. - I am not too sure why and I susp...
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?
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.
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?
I have yet to figure out how to do so, would appreciate if u could give some guidance