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[R-package]: add num_trees_per_iter, num_trees, and num_iter methods #8264

[R-package]: add num_trees_per_iter, num_trees, and num_iter methods

[R-package]: add num_trees_per_iter, num_trees, and num_iter methods #8264

Workflow file for this run

name: CUDA Version
on:
push:
branches:
- master
pull_request:
branches:
- master
# Run manually by clicking a button in the UI
workflow_dispatch:
inputs:
restart_docker:
description: 'Restart nvidia-docker on the runner before building?'
required: true
type: boolean
default: false
# automatically cancel in-progress builds if another commit is pushed
concurrency:
group: ${{ github.workflow }}-${{ github.ref }}
cancel-in-progress: true
jobs:
# Optionally reinstall + restart docker on the runner before building.
# This is safe as long as only 1 of these jobs runs at a time.
restart-docker:
name: set up docker
runs-on: [self-hosted, linux]
timeout-minutes: 30
steps:
- name: Setup or update software on host machine
if: ${{ inputs.restart_docker }}
run: |
# install core packages
sudo apt-get update
sudo apt-get install --no-install-recommends -y \
apt-transport-https \
ca-certificates \
curl \
gnupg-agent \
lsb-release \
software-properties-common
# set up nvidia-docker
curl -fsSL https://download.docker.com/linux/ubuntu/gpg | sudo apt-key add -
sudo add-apt-repository "deb [arch=amd64] https://download.docker.com/linux/ubuntu $(lsb_release -cs) stable" -y
curl -sL https://nvidia.github.io/nvidia-docker/gpgkey | sudo apt-key add -
curl -sL https://nvidia.github.io/nvidia-docker/$(. /etc/os-release;echo $ID$VERSION_ID)/nvidia-docker.list | sudo tee /etc/apt/sources.list.d/nvidia-docker.list
sudo apt-get update
sudo apt-get install --no-install-recommends -y \
containerd.io \
docker-ce \
docker-ce-cli \
nvidia-docker2
sudo chmod a+rw /var/run/docker.sock
sudo systemctl restart docker
- name: mark job successful
run: |
exit 0
test:
name: ${{ matrix.task }} ${{ matrix.cuda_version }} ${{ matrix.method }} (${{ matrix.linux_version }}, ${{ matrix.compiler }}, Python ${{ matrix.python_version }})
runs-on: [self-hosted, linux]
needs: [restart-docker]
container:
image: nvcr.io/nvidia/cuda:${{ matrix.cuda_version }}-devel-${{ matrix.linux_version }}
env:
CMAKE_BUILD_PARALLEL_LEVEL: 4
COMPILER: ${{ matrix.compiler }}
CONDA: /tmp/miniforge
DEBIAN_FRONTEND: noninteractive
METHOD: ${{ matrix.method }}
OS_NAME: linux
PYTHON_VERSION: ${{ matrix.python_version }}
TASK: ${{ matrix.task }}
SKBUILD_STRICT_CONFIG: true
options: --gpus all
timeout-minutes: 30
strategy:
fail-fast: false
matrix:
include:
- method: wheel
compiler: gcc
python_version: "3.10"
cuda_version: "11.8.0"
linux_version: "ubuntu20.04"
task: cuda
- method: source
compiler: gcc
python_version: "3.12"
cuda_version: "12.2.0"
linux_version: "ubuntu22.04"
task: cuda
- method: pip
compiler: clang
python_version: "3.11"
cuda_version: "11.8.0"
linux_version: "ubuntu20.04"
task: cuda
steps:
- name: Install latest git
run: |
apt-get update
apt-get install --no-install-recommends -y \
ca-certificates \
software-properties-common
add-apt-repository ppa:git-core/ppa -y
apt-get update
apt-get install --no-install-recommends -y \
git
- name: Checkout repository
uses: actions/checkout@v4
with:
fetch-depth: 5
submodules: true
- name: Setup and run tests
run: |
export BUILD_DIRECTORY="$GITHUB_WORKSPACE"
export PATH=$CONDA/bin:$PATH
# check GPU usage
nvidia-smi
# build and test
$GITHUB_WORKSPACE/.ci/setup.sh
$GITHUB_WORKSPACE/.ci/test.sh
all-cuda-jobs-successful:
if: always()
runs-on: ubuntu-latest
needs: [test]
steps:
- name: Note that all tests succeeded
uses: re-actors/[email protected]
with:
jobs: ${{ toJSON(needs) }}