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py-linux-gpu.yml
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75 lines (63 loc) · 2.23 KB
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parameters:
- name: arch
type: string
- name: machine_pool
type: string
- name: extra_build_arg
type: string
default: ''
- name: cmake_build_type
type: string
default: 'Release'
values:
- Debug
- Release
- RelWithDebInfo
- MinSizeRel
jobs:
- job: Linux_py_GPU_Wheels_${{ parameters.arch }}
timeoutInMinutes: 240
workspace:
clean: all
pool: ${{ parameters.machine_pool }}
variables:
# The build machine pool doesn't have dotnet, so it can't run CG.
skipComponentGovernanceDetection: true
steps:
- checkout: self
clean: true
submodules: recursive
- template: set-nightly-build-option-variable-step.yml
- template: get-docker-image-steps.yml
parameters:
Dockerfile: tools/ci_build/github/linux/docker/Dockerfile.manylinux2_28_cuda
Context: tools/ci_build/github/linux/docker
DockerBuildArgs: "
--network=host
--build-arg BASEIMAGE=nvidia/cuda:11.8.0-devel-ubi8
--build-arg TRT_VERSION=8.6.1.6-1.cuda11.8
--build-arg INSTALL_CUDNN=true
--build-arg BUILD_UID=$( id -u )
--build-arg PLATFORM=${{ parameters.arch }}
"
Repository: onnxruntimecuda118xtrt86build${{ parameters.arch }}
- task: Bash@3
displayName: 'Build Python Wheel'
inputs:
targetType: filePath
filePath: tools/ci_build/github/linux/run_python_dockerbuild.sh
# please check ONNXRUNTIME_CUDA_VERSION in tools/ci_build/github/linux/build_linux_arm64_python_package.sh
arguments: -i onnxruntimecuda118xtrt86build${{ parameters.arch }} -d "GPU" -c ${{ parameters.cmake_build_type }} -x "${{ parameters.extra_build_arg }}"
- task: PublishBuildArtifacts@1
displayName: 'Publish Artifact: ONNXRuntime python wheel'
inputs:
PathtoPublish: '$(Build.BinariesDirectory)/dist'
ArtifactName: onnxruntime_gpu
- task: PublishPipelineArtifact@0
displayName: 'Publish Test Binaries'
inputs:
artifactName: 'drop-linux-gpu-${{ parameters.arch }}'
targetPath: '$(Build.BinariesDirectory)/Release'
- task: mspremier.PostBuildCleanup.PostBuildCleanup-task.PostBuildCleanup@3
displayName: 'Clean Agent Directories'
condition: always()