Good question, SuccessfulKoala55

My thoughts are orbiting around environment orchestration and having a bit more control over how an environment is created. I understand that the easiest form of the configuration is to implement it on the clearml-agent side and run a daemon with the configuration as required, whether that be using venv's or docker containers. Of course this limits the deployment type to the queue that the daemon is listening to.

I was considering if that by exposing the experiment creation process in a more granular fashion by using Task.create() as you can pass arguments like specific docker containers and execution scripts with the experiment. This would allow you more control on how environments are created but on an experiment by experiment basis, rather than a queue basis.

Hi VivaciousPenguin66 , what's the use-case for replicating what Task.init() does using Task.create() ? 🙂