Li Jiang
Li Jiang
Close as no active response for a long time. Please reopen it or create a new issue if needed.
Thank you, @fingoldo , for the feedback! Would you like to raise a PR for the fix?
> @thinkall It seems like older versions of ray[tune] are not compatible with pydantic v2. I bumped it to `ray[tune]>=2.9` in setup.py, but that might be a more significant dependency...
In fact, pydantic is not pinned in FLAML. If you don't install ray[tune], you're good to go with any pydantic version. autogen module is not updated in FLAML for a...
> @thinkall Oh you're totally right. We're using ray[tune], which is where the Pydantic dependency must be coming from. > > Do you think FLAML can be compatible with newer...
Hi @lepennec , there is no task "classifier". Please use "classification" instead. https://microsoft.github.io/FLAML/docs/Use-Cases/Task-Oriented-AutoML Thanks.
Btw, python 3.12 is not fully tested yet. Use python 3.11 or 3.10 if possible.
> Sorry for the error in the code. I was using "classification" in my code, but I rewrote it with an error above. The issue is still here with >...
Hi @hari-ushankar, thanks for reaching out. Yes, FLAML can support customized learners. Please check out the doc [here](https://microsoft.github.io/FLAML/docs/Use-Cases/Task-Oriented-AutoML#guidelines-on-tuning-a-custom-estimator).
Hi @hari-ushankar , do you mean search hyperparameters for a gpytorch model? Is this [doc](https://microsoft.github.io/FLAML/docs/Examples/Tune-PyTorch) the example you're looking for?