mirror of
https://github.com/saymrwulf/onnxruntime.git
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### Description The patch release will fix the following issues: 1. A coding problem in test/shared_lib/test_inference.cc that it should use ASSERT_NEAR to test float values instead of ASSERT_EQ. Without this change, some DNNL/OpenVino tests would fail on some AMD CPUs. 2. A misaligned error in cublasGemmBatchedHelper function. The error only occurs when the GPU's CUDA Compute capability >=80. (In other words: with TensorFloat-32 support) 3. A build issue that build with onnxruntime_ENABLE_MEMORY_PROFILE was broken in 1.15.0 release. 4. Native onnxruntime library not loading in Azure App Service. It is because in 1.15.0 we introduced a Windows API call to SetThreadDescription. Though the API is available in all Windows 10 versions, some sandbox environments block using the API. 5. An alignment problem for xnnpack EP on Intel/AMD CPUs on PC platforms. 6. Some training header files were missing in the 1.15.0 training NuGet package. 7. Some fields in OrtCUDAProviderOptionsV2 struct are not initialized. --------- Co-authored-by: cao lei <jslhcl@gmail.com> Co-authored-by: Lei Cao <leca@microsoft.com> Co-authored-by: Scott McKay <skottmckay@gmail.com> Co-authored-by: Baiju Meswani <bmeswani@microsoft.com> Co-authored-by: JiCheng <wejoncy@163.com> Co-authored-by: Yuriy Chernyshov <thegeorg@yandex-team.com> Co-authored-by: Artur <artur@vaadin.com> Co-authored-by: Dale Phurrough <dale@hidale.com> Co-authored-by: Yi Zhang <zhanyi@microsoft.com>
76 lines
2.8 KiB
YAML
76 lines
2.8 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: 5eda9aded5462201e6310105728d33016e637ea7
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jobs:
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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: onnxruntime-Ubuntu2004-AMD-CPU
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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 DORT 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 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_dort.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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