Is your feature request related to a problem? Please describe.
While porting some code from SKL to cuML, I have noticed the following:

SKL:
from sklearn.model_selection import train_test_split
cuML:
from cuml.preprocessing.model_selection import train_test_split

If I try to do from cuml.model_selection import train_test_split, the following error is displayed:
`ModuleNotFoundE

Thank you for this fantastic work!

Could it be possible the fit_transform() method returns the KL divergence of the run?

Thx!

Segmented reduce uses the same template type OffsetIteratorT for begin and end offsets

static CUB_RUNTIME_FUNCTION cudaError_t cub::DeviceSegmentedReduce::Sum
    (   void *              d_temp_storage,
        size_t &            temp_storage_bytes,
        InputIteratorT      d_in,
        OutputIteratorT     d_out,
        int                 num_segments,
        OffsetIterato

The version of device_copy_n which takes a CUDA stream argument
https://github.com/clara-parabricks/GenomeWorks/blob/74e6424c156a7ee15b4137d4788a4257ee6482c4/common/base/include/claraparabricks/genomeworks/utils/cudautils.hpp#L138
should be renamed to device_copy_n_async to make the non-blocking behavior more obvious.

The blocking three-argument version of device_copy_n should remain