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https://github.com/saymrwulf/onnxruntime.git
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5a7f65b831
1. Fix training e2e pipeline. The failure was caused by my recent change #7632. The fix is adding "--cmake_extra_defines CMAKE_CUDA_ARCHITECTURES=70" to the build parameters because the machines are with V100 GPUs. 2. Simplify Nuphar pipeline. It doesn't need to install a separated ONNX version(1.5.0) 3. Fix a problem that run_dockerbuild.sh ignored OS version parameter. Now because it starts to take effect, I also set python version to the system default one(3.8 for ubuntu 20.04)
9 lines
399 B
YAML
9 lines
399 B
YAML
jobs:
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- template: templates/linux-ci.yml
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parameters:
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AgentPool : 'Linux-Multi-GPU'
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JobName: 'Linux_CI_Multi_GPU_TensorRT_Dev'
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# The latest TensorRT container only supports ubuntu20.04 and python 3.8
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RunDockerBuildArgs: '-o ubuntu20.04 -p 3.8 -d tensorrt -r $(Build.BinariesDirectory) -p 3.8 -x "--enable_multi_device_test"'
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DoNugetPack: 'false'
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ArtifactName: 'drop-linux'
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