mirror of
https://github.com/saymrwulf/onnxruntime.git
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eafd67b8fd
1. Update CUDA version from 11.4 to 11.6.
2. Update Manylinux version
3. Upgrade GCC version from 10 to 11 for most x86_64 pipelines. CentOS 7 ARM64 doesn't have GCC 11 yet.
4. Refactor python packaging pipeline:
a. Split Linux GPU build job to two parts, build and test, so that the
build part doesn't need to use a GPU machine
b. Make the Linux GPU build job and Linux CPU build job more similar: share the same bash script and yaml file.
5. Temporarily disable Attention_Mask1D_Fp16_B2_FusedNoPadding because it is causing one of our packaging pipeline to fail. I have created an ADO task for this.
76 lines
2.9 KiB
YAML
76 lines
2.9 KiB
YAML
parameters:
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- name: RunOnnxRuntimeTests
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displayName: Run Tests?
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type: boolean
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default: true
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stages:
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- stage: cuda
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dependsOn: []
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jobs:
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- template: templates/win-gpu-ci.yml
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parameters:
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BuildConfig: 'RelWithDebInfo'
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EnvSetupScript: setup_env_cuda_11.bat
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buildArch: x64
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additionalBuildFlags: --enable_pybind --build_java --build_nodejs --use_cuda --cuda_version=11.6 --cuda_home="C:\Program Files\NVIDIA GPU Computing Toolkit\CUDA\v11.6" --enable_cuda_profiling --cmake_extra_defines CMAKE_CUDA_ARCHITECTURES=52
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msbuildPlatform: x64
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isX86: false
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job_name_suffix: x64_RelWithDebInfo
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RunOnnxRuntimeTests: ${{ parameters.RunOnnxRuntimeTests }}
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RunStaticCodeAnalysis: false
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ORT_EP_NAME: CUDA
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MachinePool: onnxruntime-Win2019-GPU
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- stage: training
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dependsOn: []
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jobs:
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- template: templates/win-gpu-ci.yml
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parameters:
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BuildConfig: 'RelWithDebInfo'
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EnvSetupScript: setup_env_cuda_11.bat
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buildArch: x64
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additionalBuildFlags: --enable_pybind --enable_training --use_cuda --cuda_version=11.6 --cuda_home="C:\Program Files\NVIDIA GPU Computing Toolkit\CUDA\v11.6" --skip_onnx_tests --cmake_extra_defines CMAKE_CUDA_ARCHITECTURES=52
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msbuildPlatform: x64
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isX86: false
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job_name_suffix: x64_RelWithDebInfo
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RunOnnxRuntimeTests: ${{ parameters.RunOnnxRuntimeTests }}
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RunStaticCodeAnalysis: false
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ORT_EP_NAME: CUDA
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MachinePool: onnxruntime-Win2019-GPU-training
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isTraining: true
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- stage: dml
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dependsOn: []
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jobs:
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- template: templates/win-gpu-ci.yml
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parameters:
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BuildConfig: 'RelWithDebInfo'
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EnvSetupScript: setup_env.bat
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buildArch: x64
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additionalBuildFlags: --enable_pybind --use_dml --enable_wcos --use_winml
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msbuildPlatform: x64
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isX86: false
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job_name_suffix: x64_RelWithDebInfo
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RunOnnxRuntimeTests: ${{ parameters.RunOnnxRuntimeTests }}
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RunStaticCodeAnalysis: false
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ORT_EP_NAME: DML
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MachinePool: onnxruntime-Win2019-GPU-dml
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- stage: kernelDocumentation
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dependsOn: []
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jobs:
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- template: templates/win-gpu-ci.yml
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parameters:
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BuildConfig: 'RelWithDebInfo'
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EnvSetupScript: setup_env_cuda_11.bat
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buildArch: x64
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additionalBuildFlags: --gen_doc validate --skip_tests --enable_pybind --use_dml --use_cuda --cuda_version=11.6 --cuda_home="C:\Program Files\NVIDIA GPU Computing Toolkit\CUDA\v11.6" --enable_cuda_profiling --cmake_extra_defines CMAKE_CUDA_ARCHITECTURES=52 --cmake_extra_defines onnxruntime_BUILD_UNIT_TESTS=OFF
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msbuildPlatform: x64
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isX86: false
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job_name_suffix: x64_RelWithDebInfo
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RunOnnxRuntimeTests: false
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RunStaticCodeAnalysis: false
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ORT_EP_NAME: CUDA # It doesn't really matter which EP is selected here since this stage is for documentation.
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MachinePool: Win-CPU-2019
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DocUpdateNeeded: true
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