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
[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 |
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 |
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
==================================================================================== 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 |
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()) |
# 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 |
--------------------------------------------------------------------------- | |
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 |
# 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 |
import time | |
import math | |
import numpy as np | |
import torch | |
from cuml.neighbors import NearestNeighbors | |
def cuml_kneighbors(query, data, n_neighbors): | |
knn = NearestNeighbors( |
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 |