Hi @<1674226153906245632:profile|PreciousCoral74> , you certainly can, just use the Logger module 🙂
None

CrookedWalrus33 Hi 🙂
I don't see any specific problem that can arise from that as long as it has Docker installed AND has all the system requirements (CPU/RAM)

FrothyShrimp23 , I think this is more of a product design - The idea of a published task is one that cannot be easily changed afterwards. What is your use case for wanting to often unpublish tasks? Why publish them to begin with? And why manually?

Hi @<1529633468214939648:profile|CostlyElephant1> , it looks like thats the environment setup. Can you share the full log?

Looping in @<1523703436166565888:profile|DeterminedCrab71> & @<1523701435869433856:profile|SmugDolphin23> for visibility

BoredPigeon26 , are images from previous iterations still showing?

Hi @<1534706830800850944:profile|ZealousCoyote89> , can you please add the full log?

TimelyPenguin76 , what do you think?

Hi @<1539417873305309184:profile|DangerousMole43> , if understand correctly, you basically want to have some logic in your pipeline that will launch jobs according to some "trigger"?

I would suggest structuring everything around the Task object. After you clone and enqueue the agent can handle all the required packages / environment. You can even set environment variables so it won't try to create a new env but use the existing one in the docker container.

Hi @<1676762887223250944:profile|FancyKangaroo34> , it would be possible for example if the docker image has a different python version from what you ran on previously

Hi @<1691620905270120448:profile|LooseReindeer62> , I would suggest a machine that can run dockers

No. You need the server.

Is something failing? I think that's the suggested method

Hi @<1655744373268156416:profile|StickyShrimp60> , do you have any code that can reproduce this behavior?

Hi AttractiveShrimp45 . You input min value as 0, max value as 1 and step as 1?

Hi GorgeousMole24 , I think for this your best option would be using the API to extract this information.
` from clearml.backend_api.session.client import APIClient

client = APIClient() `is the pythonic usage

Hi @<1562973083189383168:profile|GrievingDuck15> , I think you'll need to re-register it

Setting the upload destination correctly and doing the same steps again

Hi @<1634001106403069952:profile|DefeatedMole42> , the Pro plan is monthly payment according to usage. You can find more information here - None

Hi @<1594863230964994048:profile|DangerousBee35> , this is pretty much it. I think the default one suggested is a good one

Hi @<1715900788393381888:profile|BitingSpider17> , you need to set it in the environment where you are running the agent. Basically export it as an env variable and then run the agent

Hi @<1523704157695905792:profile|VivaciousBadger56> , you can configure Task.init(..., output_uri=True) and this will save the models to the clearml file server

Can you please provide full logs of everything?

Hi @<1638712150060961792:profile|SilkyCrocodile89> , how did you upload them and as what?

Can you share a snippet just to reproduce this?

128GB RAM, 32 cores and 2 GPUs.

WOW 😮 I'm so jealous

However, after a while my container will exit, but also the clearml-server stops responding correctly. WebUI will not show updates and only a few experiments are shown at all. After restarting the apiserver, the clearml-server works correctly again.

Do you get any errors on how/why the container exist? Which container is it?

Hi @<1603560525352931328:profile|BeefyOwl35> , can you please elaborate on what you mean by running the build command?

Can you add a full log?

Hi @<1574931886449364992:profile|JealousDove55> , as long as you're running python code I think ClearML can help you with logging, visibility & automation.

Can you elaborate a bit on your use case?

Hi @<1752139558343938048:profile|ScatteredLizard17> , the two of supported types of instances by the ClearML autoscaler are on demand/spot instances, nothing to do with reserved ones