mirror of
https://github.com/saymrwulf/onnxruntime.git
synced 2026-05-26 22:35:43 +00:00
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.
144 lines
5.4 KiB
YAML
144 lines
5.4 KiB
YAML
resources:
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repositories:
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- repository: manylinux
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type: Github
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endpoint: Microsoft
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name: pypa/manylinux
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ref: 1a61614cabfd6b91c6afd6d9e172cc5b838c65fe
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jobs:
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- job: BuildAndTestEagerMode
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timeoutInMinutes: 120
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workspace:
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clean: all
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pool: Linux-CPU-2019
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steps:
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- checkout: self
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clean: true
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submodules: recursive
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- template: templates/get-docker-image-steps.yml
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parameters:
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Dockerfile: tools/ci_build/github/linux/docker/Dockerfile.manylinux2014_eager_cpu
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Context: tools/ci_build/github/linux/docker
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DockerBuildArgs: "--build-arg BUILD_UID=$( id -u )"
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Repository: onnxruntimecpubuildeagermode
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- task: CmdLine@2
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displayName: 'build'
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inputs:
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script: |
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mkdir -p $HOME/.onnx
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docker run --rm \
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--volume /data/onnx:/data/onnx:ro \
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--volume $(Build.SourcesDirectory):/onnxruntime_src \
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--volume $(Build.BinariesDirectory):/build \
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--volume $HOME/.onnx:/home/onnxruntimedev/.onnx \
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-e ALLOW_RELEASED_ONNX_OPSET_ONLY=0 \
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-e NIGHTLY_BUILD \
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-e BUILD_BUILDNUMBER \
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onnxruntimecpubuildeagermode \
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/opt/python/cp38-cp38/bin/python3 /onnxruntime_src/tools/ci_build/build.py \
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--build_dir /build --cmake_generator Ninja \
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--config Debug Release \
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--skip_submodule_sync \
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--build_shared_lib \
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--parallel \
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--build_eager_mode --enable_training --build_wheel --skip_test
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workingDirectory: $(Build.SourcesDirectory)
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- task: CmdLine@2
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displayName: 'install ortmodule extension and test'
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inputs:
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script: |
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mkdir -p $HOME/.onnx
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docker run --rm \
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--volume /data/onnx:/data/onnx:ro \
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--volume $(Build.SourcesDirectory):/onnxruntime_src \
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--volume $(Build.BinariesDirectory):/build \
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--volume $HOME/.onnx:/home/onnxruntimedev/.onnx \
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-e ALLOW_RELEASED_ONNX_OPSET_ONLY=0 \
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-e NIGHTLY_BUILD \
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-e BUILD_BUILDNUMBER \
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onnxruntimecpubuildeagermode \
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bash -c "export PYTHONPATH=/build/Release && /opt/python/cp38-cp38/bin/python3 -m onnxruntime.training.ortmodule.torch_cpp_extensions.install &&\
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/opt/python/cp38-cp38/bin/python3 /onnxruntime_src/tools/ci_build/build.py \
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--build_dir /build --cmake_generator Ninja \
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--config Release \
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--skip_submodule_sync \
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--build_shared_lib \
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--parallel \
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--build_eager_mode --enable_training --build_wheel --test"
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workingDirectory: $(Build.SourcesDirectory)
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- template: templates/clean-agent-build-directory-step.yml
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# This pipeline builds the latest PyTorch commit from source
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# and use it in ORT tests. See Dockerfile.manylinux2014_lort_cpu
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# for the installation steps. Idally, we should only use one pipeline
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# for eager mode and LazyTensor, but we split them due to recent
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# PyTorch's breaking changes.
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#
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# TODO: once ORT eager mode can run with latest PyTorch commit, we
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# should
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# 1. Set --build_eager_mode when running build.py in the
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# first "task" below.
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# 2. Copy the second "task" above as the third task below.
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- job: BuildAndTestLazyTensor
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timeoutInMinutes: 120
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workspace:
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clean: all
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pool: Linux-CPU-2019
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steps:
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- checkout: self
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clean: true
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submodules: recursive
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- template: templates/get-docker-image-steps.yml
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parameters:
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Dockerfile: tools/ci_build/github/linux/docker/Dockerfile.manylinux2014_lort_cpu
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Context: tools/ci_build/github/linux/docker
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DockerBuildArgs: "--build-arg BUILD_UID=$( id -u )"
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Repository: onnxruntimecpubuildlort
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- task: CmdLine@2
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displayName: 'Build ORT for Python 3.9'
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inputs:
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script: |
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docker run --rm \
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--volume $(Build.SourcesDirectory):/onnxruntime_src \
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--volume $(Build.BinariesDirectory):/build \
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-e ALLOW_RELEASED_ONNX_OPSET_ONLY=0 \
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-e NIGHTLY_BUILD \
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-e BUILD_BUILDNUMBER \
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onnxruntimecpubuildlort \
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/opt/python/cp39-cp39/bin/python3.9 /onnxruntime_src/tools/ci_build/build.py \
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--build_dir /build --cmake_generator Ninja \
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--config Release \
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--skip_submodule_sync \
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--build_shared_lib \
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--parallel \
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--enable_lazy_tensor --enable_training --build_wheel --skip_test \
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workingDirectory: $(Build.SourcesDirectory)
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- task: CmdLine@2
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displayName: 'Test LORT with Python 3.9'
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inputs:
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script: |
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docker run --rm \
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--volume $(Build.SourcesDirectory):/onnxruntime_src \
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--volume $(Build.BinariesDirectory):/build \
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-e ALLOW_RELEASED_ONNX_OPSET_ONLY=0 \
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-e NIGHTLY_BUILD \
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-e BUILD_BUILDNUMBER \
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onnxruntimecpubuildlort \
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bash -c "
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export LORT_CHECK_BASELINE=1 && \
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export LORT_DUMP_GRAPH=1 && \
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export LORT_DUMP_ATEN_OP_HISTORY=1 && \
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export PYTHONPATH=/build/Release && \
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/opt/python/cp39-cp39/bin/python3.9 -m pip install /build/Release/dist/*.whl && \
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/opt/python/cp39-cp39/bin/python3.9 /onnxruntime_src/orttraining/orttraining/test/python/orttraining_test_lort.py"
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workingDirectory: $(Build.SourcesDirectory)
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condition: succeededOrFailed()
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- template: templates/clean-agent-build-directory-step.yml
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