[BUG] AttributeError: 'DataFrame' object has no attribute 'unique'

[Nithish-Chowdary]

Describe the bug I'm trying to build a Random Forest Regressor using cuml.dask.ensemble.RandomForestRegressor. collab V100 GPUs are used.

Steps/Code to reproduce bug from cuml.dask.ensemble import RandomForestRegressor as cuRF from dask_ml.model_selection import train_test_split

train, test = train_test_split(Data, test_size=0.2, shuffle=True, random_state=42)

train_labels = train[single_label].map_partitions(cudf.from_pandas) train_features = train[target_features].map_partitions(cudf.from_pandas) test_labels = test[single_label].map_partitions(cudf.from_pandas) test_features = test[target_features].map_partitions(cudf.from_pandas)

model = cuRF(n_estimators=100, random_state=42, verbose = True)

model.fit(train_features, train_labels)

Expected behavior I want the model to fit

Environment details (please complete the following information):

• Environment location: Google Collab
• GPU Model/Driver: Tesla V100-SXM2-16GB' GPU
• CUDA: [9.2]
• Method of cuDF & cuML install: [conda, Docker, or from source] !pip install cudf-cu11 dask-cudf-cu11 cuml-cu11 cugraph-cu11 --extra-index-url=https://pypi.ngc.nvidia.com !rm -rf /usr/local/lib/python3.8/dist-packages/cupy* !pip install cupy-cuda11x

[dantegd]

Thanks for the issue @Nithish-Chowdary, the ussue is that CUDA 9.2 is not supported, the packages that are being installed require CUDA 11.2 as a minimum, with the cu12 versions being usable in any CUDA 12.0 system.

[Nithish-Chowdary]

Thanks for reaching out, Sorry for providing the wrong CUDA Version

my CUDA version is 12.2

[dantegd]

Unfortunately, the version provided by nvidia-smi just corresponds to the driver's CUDA version (i.e. the CUDA that came bundled with the driver), and doesn't necessarily correspond with the CTK of an environment. For example with conda one could have a driver for CUDA 12.x and have CUDA 11.x in the conda env. Since you are using pip to install, and cu11 then you'd need a CUDA 11, you can check that probably by typing nvcc --version in the command line

[Nithish-Chowdary]

Thanks for quick response

I am installing these packages !pip install --extra-index-url=https://pypi.nvidia.com cudf-cu12==24.2. dask-cudf-cu12==24.2. cuml-cu12==24.2.*

and cuda version is