Hey SuccessfulKoala55 Like I mentioned, I have a spacy ner model that I need to serve for inference.

AgitatedDove14 - any thoughts on this?

AlertBlackbird30 - i don’t understand why it can’t be a focus though. Probably missing some context.

from here: https://github.com/allegroai/clearml/blob/5a9155b2039413280f13dfded1121470c4c4323d/examples/pipeline/pipeline_controller.py#L29

For now that's a quick thing, but for actual use I will need a proper model (pkl) and the .py

Ok the doc needs fix

The agent ip? Generally what’s the expected pattern to deploy and scale this for multiple models?

Awesome

AgitatedDove14 - i had not used the autoscaler since it asks for access key. Mainly looking for GPU use cases - with sagemaker one can choose any instance they want and use it, autoscaler would need set instance configured right? need to revisit. Also I want to use the k8s glue if not for this. Suggestions?

Generally like the kedro project and pipeline setup that I have seen so far, but haven’t started using it in anger yet. Been looking at clearml as well, so wanted to check how well these two work together

Task.add_requirements would fit the bill yeah, thanks

Maybe two thing here:

If Task.init() is called in an already running task, don’t reset auto_connect_frameworks? (if i am understanding the behaviour right) Option to disable these in the clearml.conf

Was asking about using iam roles without keys

Thanks AgitatedDove14 - i get overall what you are saying. Have to get glue setup, which I couldn’t understand fully, so that’s a different topic 🙂

Yeah was planning to use nested projects for that

Do people generally update the same model “entry”? That feels so wrong to me…how do you reproduce a older model version or do a rollback etc?

Ok, got it thanks. Would be cool to let it get untracked as well, especially if we want to as an option

Would this be it? https://github.com/allegroai/clearml-agent/commit/6470b16b70165cdab0159ce5613521917e861d79

Thanks

Nothing. nothing apparent at least

AgitatedDove14 - apologies for late reply. So to give context this in a Sagemaker notebook which has conda envs.

I use a lifecycle like this to pip install a package (a .tar.gz downloaded from s3) in a conda env- https://github.com/aws-samples/amazon-sagemaker-notebook-instance-lifecycle-config-samples/blob/master/scripts/install-pip-package-single-environment/on-start.sh

In the notebook I can do things like create experiments and so on. Now the problem is in running the cloned experimen...

Thanks AnxiousSeal95

So didn’t want to update the defaults

Thanks for the fast responses as usual AgitatedDove14 🙂

Interesting. How do you do PVC? by using the yaml template optionn?

What’s overrides_yaml vs template_yaml?

And then comes back again

Not able to understand what’s really happening in the links

Yeah, when doing:

task.set_base_docker( "nvidia/cuda:11.4.1-cudnn8-runtime-ubuntu20.04", docker_setup_bash_script=script, )

Is updating that needed in this case?