Can I switch off git diff (change detection?)

In this case I have data and then set of pickles created from the data

Nothing in mind, just wanted to know if there was one 🙂

Ok, but doesn't work for me though. Can you or AgitatedDove14 help me in linking to relevant code so that I can see what's wrong?

Thanks you! Does this go as a root logging {} element in the main conf? outside SDK right?

As per - https://clear.ml/docs/latest/docs/references/sdk/task#connect

In this case, particularly because of pickle protocol version between 3.7 and 3.8

+1 to this question

forking and using the latest code fixes the boto issue at least

Think I will have to fork and play around with it 🙂

Yes, I have no experience with triton does it do lazy loading? Was wondering how it can handle 10s, 100s of models. If we load balance across a set of these engine containers with say 100 models and all of these models get traffic but distribution is not even, each of those engine container will load all those 100 models?

I am also not understanding how clearml-serving is doing the version for models in triton.

Yeah please if you can share some general active ones to discuss both algos and engineering side

Like it said, it works, but goes into the error loop

Progress with boto3 added, but fails:

Only allowed to have ssh key, not username-password

As of now solving by updating the git config locally before creating the task

AgitatedDove14 - are there cases when it tries to skip steps?

I also have a pipelines.yaml which i convert to a pipeline

Anything that is shown in git status as untracked? So ignore .gitignored. and maybe a oaram or config to say include untracked. Anyway, it's only a nice to have feature.

AgitatedDove14 - it does have boto but the clearml-serving installation and code refers to older commit hash and hence the task was not using them - https://github.com/allegroai/clearml-serving/blob/main/clearml_serving/serving_service.py#L217

Will debug a bit more and see what’s up

Would be good to have frequentish releases if possible 🙂

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...

Sorry, don’t get it

that or in clearml.conf or both

From the code - it’s supposed to not cache if task override is different? I also have task_override that adds a version which changes each run

Got the engine running.

curl <serving-engine-ip>:8000/v2/models/keras_mnist/versions/1What’s the serving-engine-ip supposed to be?