RAPIDS + Dask-ML sample notebooks

[xyz00000]

getting this:

Exception: "TypeError('Implicit conversion to a host NumPy array via array is not allowed, To explicitly construct a GPU matrix, consider using .to_cupy()\nTo explicitly construct a host matrix, consider using .to_numpy().')"

after running cell: mode = "gpu-random" model_rf = RandomForestClassifier()

Any ideas?

mode = "gpu-random" with timed("XGB-" + mode): & mode = "gpu-grid" with timed("XGB-" + mode):

works great.

[jacobtomlinson]

Could you let us know which notebook you're having trouble with and which versions of RAPIDS you're running? Thanks :)

[xyz00000]

thanks @jacobtomlinson (jacob), rapids 23.10 (cuda11_py310_231011_gd3958fe_0 rapidsai) and jupyter notebook (pip install jupyterlab 4.0.9), best steve

https://docs.rapids.ai/deployment/stable/examples/xgboost-randomforest-gpu-hpo-dask/notebook/

[jacobtomlinson]

Ok great, I'm going to transfer this issue over to our deployment docs repo where that notebook lives.

We are about to do some testing of these notebooks ahead of the 23.12 release, so I'll ensure this one is high priority.

[skirui-source]

I was able to run through the notebook and also seeing the same error :

• tested on rapids 23.10.00a cuda12_py310_230925_g9c72ff5_5 rapidsai-nightly

[xyz00000]

@skirui-source im 7 years self taught python but i think it's something to do with how dask-ml (2023.3.24) feeds the test data (maybe attempting an additional conversion) into the random forest model.

@jacobtomlinson Would be nice to get a feature_importances (sklearn) through the gpu too?