mirror of
https://github.com/saymrwulf/onnxruntime.git
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24eda3df33
In this PR, we 1. create some APIs for creating NVTX objects 2. apply those APIs in pipeline-related operators and sequential executor. As a result, we can explicitly see how a pipeline schedule is run by GPUs in Nvidia's visual profiler. Note that these APIs are Linux only due to Nvidia's limited support.
32 lines
934 B
YAML
32 lines
934 B
YAML
trigger: none
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jobs:
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- template: templates/linux-ci.yml
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parameters:
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AgentPool : 'Linux-GPU-CUDA10'
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JobName: 'Onnxruntime_Linux_GPU_Training'
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SubmoduleCheckoutMode: 'recursive'
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# TODO --skip_onnx_tests is used to disable onnx_test_runner test.
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# onnx_test_runner test occasionally causes "CUDA failure 77: an illegal memory access was encountered"
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# remove --skip_onnx_tests when the test failures are fixed.
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BuildCommand: >
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tools/ci_build/github/linux/run_dockerbuild.sh
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-o ubuntu16.04 -d gpu -r $(Build.BinariesDirectory)
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-x "
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--enable_training
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--config $(buildConfig)
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--skip_onnx_tests
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--build_wheel
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--enable_nvtx_profile
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"
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DoNugetPack: 'false'
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ArtifactName: 'drop-linux'
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TimeoutInMinutes: 90
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Strategy:
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maxParallel: 2
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matrix:
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Debug:
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buildConfig: Debug
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Release:
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buildConfig: Release
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