Hey Paul, glad to see you in here but sorry that you're having issues. Jst a quick clarification if I can, you said 'set up using docker'.. do you mean you did a 'docker-compose up' or some other commands such as only starting specific parts/docker containers only ?

there is a --docker flag for clearml-agent that will build containers :)

Never a problem Tim.. although it does prompt me to try and figure out a/b model testing myself ... I see everything as a "potential blog post" 😄 😄

Stupid question Tim (and I understand that maybe your code is under NDA etc but) can you show the python code that you need to a/b against ?

I swear, I literally made this point in my zettelkasten
- demonstration/walkthrough/first steps - would require people to register for theseso I definitely think the demo/first steps is a great idea 👍

quick question if I may, are you running clearml-agent with --docker mode or without ? are you running the clearml-agent on the same machine as the path exists on another machine entirely ?

mea culpa

There will be a roadmap for the community up and on the blog this Monday.. It may not be as detailed as you would like but I am always happy to yak about specific requests 👍 👍

Howdy and Morning @<1687643893996195840:profile|RoundCat60> .. docker when using overlay2 doesn't have it's mount points show up in a 'df' btw, they will only appear in a 'df -a', mostly because since they are simply 'overlays', they don't (technically) consume any space (I mean, the files are still in the /var/lib but not for the space counting practices used by df)

this is why I was suggesting a find, maybe with a 'du' .. actually.. let me try that here.. 2s

maybe I am entirely wrong .. I read clearml-session as running a remote 'headless container with jupyter'.. but not on k8s.. or rather... the pre-requisites say that 'ssh access', which you won't have in a k8s cluster (I would hope). I mean.. exposing the ssh port on a k8s cluster is jst a security nightmare.

I may have to let someone with more know-how on the histogram and graphing answer if there is anyway to change graph layout though

I would think that a combination of kubernetes (I believe the preferred way to support multiple users at once, but open to being wrong) and individual queue's is probably the solution here.

for example; in kubernetes you could setup an agent to listen to bob-queue and another agent to listen to alice-queue. In the kubernetes dashboard you could assign a certain amount of cpu/memory and if using taints, gpu or not.

oh .. no worries at all then.. you are free to do whatever you want to with it.. but I don't think it's designed with what you are trying to do in mind sadly

the one you are in 🙂

You may also want to brush up on the security and firewalls for AWS.. those always seem to be voodoo as far as I can tell 😄

👍

open to being totally wrong 🙂

Shameless plug here ; https://clear.ml/blog/jupyter-notebooks-used-as-clearml-workers/

this whole area is a WIP of course, but I am trying to capture some of the really interesting Q and A from here so that they don't jst disappear into the void 🙂

I am so used to pip install, I default to there 😄

you're not going to get the same performance as you would from your own dual xeon with 128gb of ram etc 🙂

aaahhh.. I will wager good money Sir that you are then using ipython in vscode which is probably trying to do something "fancy" with the interpreter

from the look of those two graphs, the underlying data is totally different 😕

if you see it in the community server, then I believe the answer is "yes" - although don't hold me accountable on this 😄

Hello E.K, do you have any examples handy to show us the difference ?

the one on the right, for example, has no data points at around the 19 mark

the part that I am concerned on is that the first pair of graphs you showed, the dataset (even from jst looking at it) are very different 😕

laughs okily dokily Sir.. noted and noted 👍
I must admit, I have been using plotly and matplotlib for years and.. I have never used animations once. I am old school though 🙂

I assume that clearml's is on the right ?

clearml-deploy is clearml-serving but with other parts more intwined such as ci/cd prompts/callbacks, if you think clearml-deploy has a bit more love given to it, I believe that will put you on the right track, but at it's core, it's the same idea Sir.

the hyper datasets have always been there in the enterprise offering. It allows you to query datasets and perform functions such as updating labels on an image without an entire re-batching. I think we are trying to find a way to bring this to...

do you have code that you can share ?