Thanks!

I've updated my feature request to describe that as well. A textual description is not necessarily a preview 😅 For now I'll use the debug samples.

These kind of things definitely show how ClearML was designed originally only for neural networks tbh, where images are almost always only part of the dataset. Same goes for the consistent use of iteration everywhere 😞

I wouldn't mind going the requests route if I could find the API end point from the SDK?

I couldn't find it directly in the SDK at least (in the APIClient)... 🤔

Thanks LazyFish41 , that explains it 👍

Don't even need to specify json=... 😉 Thanks!

Since this is a single process, most of these are only needed once when our "initializer" task starts and loads.

Ah. In the extra_vm_bash_script of the AWS autoscaler.

We're not using the docker setup though. The CLI run by the autoscaler is python -m clearml_agent --config-file /root/clearml.conf daemon --queue aws_small , so no docker

There's not much (or anything) in the log to provide...

` (.venv) 15:42 [0:user@server$~] CLEARML_CONFIG_FILE=~/agent_clearml.conf clearml-agent daemon --queue default on_prem --detached --order-fairness
Environment variables set from configuration: ['AWS_ACCESS_KEY_ID', 'AWS_SECRET_ACCESS_KEY', 'AWS_DEFAULT_REGION']
...

https://github.com/allegroai/clearml/pull/533 🙂

It's okay 🙂 I was originally hoping to delete my "initializer" task, but I'll just archive it if someone is interested in the worker data etc. Setting the queue is quite nice.

I think this should get my team excited enough 😄

I believe that happens natively thanks to pyhocon? No idea why it fails on mac

Anyway sounds good! 🙂

https://pypi.org/project/python-dotenv/

The tl;dr is that some of our users like poetry and others prefer pip . Since pip install git+.... stores the git data, it seems trivial to first try and install based on pip , and only later on poetry , since the pip would crash with poetry as it stores git data elsewhere (in poetry.lock )

Not necessarily on the same branch, no

Thanks SuccessfulKoala55 and AgitatedDove14 ! We'll go through the hoops of setting up mongo on AWS then.
We're working to decouple the data from the helm chart, seems like a dangerous idea to store long term data on k8s in case of failure 😅

I am; it seems like maybe a couple of hours?

@<1523701205467926528:profile|AgitatedDove14> this

I narrowed the bug down to the "fix" in 1.8.1, see my other post

I'm saying it's a bug

After the task was initialized? 🤔

Woot! What about clearml-agent 1.2.0? 🙂

Let me know if there's any additional information that can help SuccessfulKoala55 !

The deferred_init input argument to Task.init is bool by default, so checking type(deferred_init) == int makes no sense to begin with, and is altering the flow.

Could also be related to K8, so pinging JuicyFox94 just in case 😉

Yeah I figured (2) would be the way to go actually 😄

An internal project I've accidentally made with a hidden tag while playing around with the ClearML internal code.

My current workaround is to use poetry and tell users to delete poetry.lock if they want their environment copied verbatim