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2b8677b210
1. Add openvino GPU nightly build pipeline, this test is running on Intel Up square Edge device. The device are host locally not from Azure VM. We persist a smaller model test data on Edge device. 2. Update the build condition for openvino GPU so it works for GPU_FP32, GPU_FP16 3. add option to install_ubuntu.sh to exclude the package used for nuphar, so that we can save some disk space as the Edge device usually have limited disk space.
30 lines
1.2 KiB
YAML
30 lines
1.2 KiB
YAML
parameters:
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AgentPool : 'Linux-CPU'
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JobName : 'Linux_CI_Dev'
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BuildCommand: 'tools/ci_build/github/linux/run_dockerbuild.sh -o ubuntu16.04 -d cpu -r $(Build.BinariesDirectory) -x "--use_mklml --use_tvm --build_wheel"'
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DoNugetPack: 'false'
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NuPackScript: ''
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ArtifactName: 'drop-linux'
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TimeoutInMinutes: 120
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jobs:
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- job: ${{ parameters.JobName }}
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timeoutInMinutes: ${{ parameters.TimeoutInMinutes }}
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pool: ${{ parameters.AgentPool }}
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steps:
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- template: linux-set-variables-and-download.yml
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- script: ${{ parameters.BuildCommand }}
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displayName: 'Command Line Script'
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- ${{ if eq(parameters['DoNugetPack'], 'true') }}:
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- script: |
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${{ parameters.NuPackScript }}
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displayName: 'Create Artifacts'
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- task: PublishPipelineArtifact@0
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displayName: 'Publish Pipeline Artifact'
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inputs:
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artifactName: ${{ parameters.ArtifactName }}
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targetPath: '$(Build.ArtifactStagingDirectory)'
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- task: ms.vss-governance-buildtask.governance-build-task-component-detection.ComponentGovernanceComponentDetection@0
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displayName: 'Component Detection'
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condition: succeeded()
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- template: clean-agent-build-directory-step.yml
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