• I have tried using the latest released version of Numba
• I have included below a minimal working reproducer

In trying to replace numpy's setxor1d (which is unfortunately not supported by Numba), I came across an error that does occur for (integer) ndarrays but not for lists.
In my case the setxor1d can be replaced by [i for i in a if i not in b], but for the sake of testing, here i

Problem:
catboost version: 0.23.2
Operating System: all
Tutorial: https://github.com/catboost/tutorials/blob/master/custom_loss/custom_metric_tutorial.md

Impossible to use custom metric (С++).

Code example

from catboost import CatBoost
train_data = [[1, 4, 5, 6],
 

Improve readability of thread id based branches by giving them more descriptive names.

e.g.

if (!t) // is actually a t == 0

and

https://github.com/rapidsai/cudf/blob/57ef76927373d7260b6a0eda781e59a4c563d36e/cpp/src/io/statistics/column_stats.cu#L285
Is actually a lane_id == 0
As demonstrated in rapidsai/cudf#6241 (comment), pr

Current implementation of join can be improved by performing the operation in a single call to the backend kernel instead of multiple calls.

This is a fairly easy kernel and may be a good issue for someone getting to know CUDA/ArrayFire internals. Ping me if you want additional info.

Would it make sense to add a variadic overload of make_zip_iterator that composes the existing make_zip_iterator with make_tuple? I have this in my own code, and I find that it reduces syntactic overhead.

template<typename... Iterators>
__host__ __device__
  zip_iterator<thrust::tuple<Iterators...>> make_zip_iterator(thrust::tuple<Iterators...> t)
{
    return zip_iterator<thrust::tupl

Report needed documentation

We do not have documentation specifying the different treelite Operator values that FIL supports. (https://github.com/dmlc/treelite/blob/46c8390aed4491ea97a017d447f921efef9f03ef/include/treelite/base.h#L40)

Report needed documentation
https://github.com/rapidsai/cuml/blob/branch-0.15/cpp/test/sg/fil_test.cu
There are multiple places in the fil_test.cu file

I often use -v just to see that something is going on, but a progress bar (enabled by default) would serve the same purpose and be more concise.

We can just factor out the code from futhark bench for this.

Thank you for this fantastic work!

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

Thx!