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feat: cuda test

feat: cuda test #11

Workflow file for this run

name: lightgbm
# https://lightgbm.readthedocs.io/en/latest/Installation-Guide.html#id18
# https://github.com/microsoft/LightGBM/tree/master/python-package#build-gpu-version
on:
push:
branches:
- lightgbm
workflow_dispatch:
jobs:
build:
runs-on: windows-2022
steps:
- uses: actions/setup-python@v5
with:
python-version: '3.10'
- name: boost
uses: MarkusJx/install-boost@main
id: install-boost
with:
platform_version: 2022
boost_version: 1.86.0
toolset: msvc
cache: false
# - name: cuda-toolkit
# uses: Jimver/cuda-toolkit@master
# id: cuda-toolkit
# # https://docs.nvidia.com/cuda/archive/12.6.2/cuda-installation-guide-microsoft-windows/index.html#id3
# with:
# cuda: '12.1.1'
# method: 'network'
# sub-packages: '["nvcc", "visual_studio_integration"]'
# # Disable caching of the CUDA binaries, since it does not give us any significant performance improvement
# use-github-cache: "false"
# # 在GITHUB_ENV中输出CUDA_PATH
# - name: echo version
# run: |
# nvcc -V
# echo ${{ steps.cuda-toolkit.outputs.cuda }}
# echo ${{ steps.install-boost.outputs.BOOST_VER }}
- name: Configure build
run: |
echo $HOME
# cmake -B build -S . -A x64 -DUSE_GPU=1 -DBOOST_ROOT=$BOOST_ROOT
# cmake -B build -S . -A x64 -DUSE_GPU=1 -DBOOST_ROOT=BOOST_ROOT -DOpenCL_LIBRARY="C:/Program Files/NVIDIA GPU Computing Toolkit/CUDA/v10.0/lib/x64/OpenCL.lib" -DOpenCL_INCLUDE_DIR="C:/Program Files/NVIDIA GPU Computing Toolkit/CUDA/v10.0/include"
python -V
pip wheel lightgbm --config-settings=cmake.define.Boost_ROOT=$BOOST_ROOT
# pip wheel lightgbm \
# --config-settings=cmake.define.USE_GPU=ON \
# --config-settings=cmake.define.OpenCL_INCLUDE_DIR=$CUDA_PATH/include \
# --config-settings=cmake.define.Boost_ROOT=$BOOST_ROOT
env:
BOOST_ROOT: ${{ steps.install-boost.outputs.BOOST_ROOT }}
- name: Upload all wheel files
uses: actions/upload-artifact@v4
with:
name: lightgbm-wheels
path: ' d:\a\win-whl\win-whl\*lightgbm*.whl'
if-no-files-found: error