Ah ok thereโs only optimizer.stop in the example
just that the task itself is still Running state
The "Optimizer task" will continue to run as long as there are sub-Tasks it launched.
Is anything else running/pending ?
The Optimizer task is taking a lot of time to complete. Is it doing something here:
It completed after the max_job limit (10)
Yep this is optuna "testing the water"
I am running from noebook and cell has returned
Well the Task will close when you shut down the notebook ๐
Yeah, Curious - is a lot of clearml usecases not geared for notebooks?
I am running from noebook and cell has returned
how do you see things being used as the most normal way?
Tried context provider for Task?
I guess that would only make sense inside notebooks ?!
The job itself doesnโt have any other param
So this is optuna ๐ the idea is it will test which parameters have potential (with early stopping), then launch a subset of the selected parameters
You mean the job with the exact same arguments ?
Yes
You mean the job with the exact same arguments ?
do you have other arguments you are passing ?
Are you using Optuna / HBOB ?
Notice Optuna will do TPE & hyper band Bayesian optimization to find the best combination
Ok, just my ignorance then?ย
LOL, no it is just that with a single discrete parameter the strategy makes less sense ๐
Yeah, Curious - is a lot of clearml usecases not geared for notebooks?
That is somewhat correct, notebooks are not actually used with a lot of deep-learning projects as they require entire repository to support.
I guess generally speaking the workflow is, "test your code" (i.e. small scale with limited data), then clone and enqueue for remote execution.
That said, I think it will be great to expand the support.
TrickySheep9 I like the idea of context for Tasks, can you expand on how this is used as part of a (jupyter) workflow ?