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[215/275] Linking CXX shared library libcuml++.so
FAILED: libcuml++.so
: && /datasets/thead/mambaforge/envs/cuml-dev-23.12-dgx15/bin/x86_64-conda-linux-gnu-c++ -fPIC -fvisibility-inlines-hidden -fmessage-length=0 -march=nocona -mtune=haswell -ftree-vectorize -fPIC -fstack-protector-strong -fno-plt -O2 -ffunction-sections -pipe -isystem /datasets/thead/mambaforge/envs/cuml-dev-23.12-dgx15/include  -I/datasets/thead/mambaforge/envs/cuml-dev-23.12-dgx15/targets/x86_64-linux/include  -L/datasets/thead/mambaforge/envs/cuml-dev-23.12-dgx15/targets/x86_64-linux/lib -L/datasets/thead/mambaforge/envs/cuml-dev-23.12-dgx15/targets/x86_64-linux/lib/stubs -O3 -DNDEBUG  -Wl,-O2 -Wl,--sort-common -Wl,--as-needed -Wl,-z,relro -Wl,-z,now -Wl,--disable-new-dtags -Wl,--gc-sections -Wl,--allow-shlib-undefined -Wl,-rpath,/datasets/thead/mambaforge/envs/cuml-dev-23.12-dgx15/lib -Wl,-rpath-link,/datasets/thead/mambaforge/envs/cuml-dev-23.12-dgx15/lib -L/datasets/thead/mambaforge/envs/cuml-dev-23.12-dgx15/lib  -L/datasets/thead/mamb

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conda-forge/osx-arm64                                       Using cache
conda-forge/noarch                                          Using cache


Looking for: ['python=3.9', 'numpy=1.19.5', 'blas', 'scipy=1.6.0', 'cython=3.0.10', 'joblib', 'threadpoolctl', 'matplotlib=3.3.4', 'pandas=1.1.5', 'pyamg', "pytest[version='<8']", 'pytest-xdist', 'pillow', 'pip', 'ninja', 'meson-python', 'scikit-image=0.17.2', 'seaborn', 'memory_profiler', 'compilers', 'sphinx=6.0.0', 'sphinx-gallery=0.15.0', 'sphinx-copybutton=0.5.2', 'numpydoc=1.2.0', 'sphinx-prompt=1.3.0', 'plotly=5.14.0', 'polars=0.19.12', 'pooch', 'pip']


Could not solve for environment specs
The following packages are incompatible
├─ numpy 1.19.5**  is installable with the potential options

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Building for bare metal

Checkout https://github.com/rapidsai/gpu-xb-ai:

git clone https://github.com/rapidsai/gpu-xb-ai

Create a conda environment from conda/environments/gpu-xb-ai-legate-all.yaml:

conda env create -f conda/environments/gpu-xb-ai-legate-all.yaml

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==================================================================================== short test summary info ====================================================================================
FAILED sklearn/model_selection/tests/test_split.py::test_array_api_train_test_split[True-None-cupy.array_api-None-None] - ValueError: The truth value of an array with more than one element is ambiguous. Use a.any() or a.all()
FAILED sklearn/model_selection/tests/test_split.py::test_array_api_train_test_split[True-stratify1-cupy-None-None] - ValueError: kind can only be None or 'stable'
FAILED sklearn/model_selection/tests/test_split.py::test_array_api_train_test_split[True-stratify1-cupy.array_api-None-None] - ValueError: The least populated class in y has only 1 member, which is too few. The minimum number of groups for any class cannot be less than 2.
FAILED sklearn/model_selection/tests/test_split.py::test_array_api_train_test_split[False-None-cupy.array_api-None-None] - ValueError: The truth value of an array with 

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from dask_mpi import initialize
from dask import distributed


def dask_info():
    distributed.print("woah i'm running!")
    distributed.print("ncores:", client.ncores())
    distributed.print()
    distributed.print(client.scheduler_info())

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# packages in environment at /opt/conda/envs/rapids-23.06:
#
# Name                    Version                   Build  Channel
_libgcc_mutex             0.1                 conda_forge    conda-forge
_openmp_mutex             4.5                       2_gnu    conda-forge
aiohttp                   3.8.5           py310h2372a71_0    conda-forge
aiosignal                 1.3.1              pyhd8ed1ab_0    conda-forge
anyio                     3.7.1              pyhd8ed1ab_0    conda-forge
aom                       3.5.0                h27087fc_0    conda-forge
appdirs                   1.4.4              pyh9f0ad1d_0    conda-forge

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---------------------------------------------------------------------------
ImportError                               Traceback (most recent call last)
File /opt/conda/envs/rapids-23.06/lib/python3.10/site-packages/cupy/__init__.py:17
     16 try:
---> 17     from cupy import _core  # NOQA
     18 except ImportError as exc:

File /opt/conda/envs/rapids-23.06/lib/python3.10/site-packages/cupy/_core/__init__.py:3
      1 # mypy: ignore-errors
----> 3 from cupy._core import core  # NOQA

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# packages in environment at /opt/conda:
#
# Name                    Version                   Build  Channel
_libgcc_mutex             0.1                 conda_forge    conda-forge
_openmp_mutex             4.5                       2_gnu    conda-forge
absl-py                   1.4.0                    pypi_0    pypi
aiohttp                   3.8.4                    pypi_0    pypi
aiohttp-cors              0.7.0                    pypi_0    pypi
aiorwlock                 1.3.0                    pypi_0    pypi
aiosignal                 1.3.1                    pypi_0    pypi

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import time
import math
import numpy as np
import torch

from cuml.neighbors import NearestNeighbors


def cuml_kneighbors(query, data, n_neighbors):
    knn = NearestNeighbors(

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from sklearn.linear_model import SGDClassifier
from sklearn.datasets import make_classification
import numpy as np


X, y = make_classification(n_features=5, random_state=42)

rng = np.random.RandomState(10)

# According to the docs https://scikit-learn.org/stable/common_pitfalls.html#id2