mirror of
https://github.com/saymrwulf/onnxruntime.git
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linux trt package pipeline (#7537)
This commit is contained in:
George Wu
GitHub
parent
8eaa4c33e2
commit
faea7a222d
5 changed files with 189 additions and 1 deletions
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variables:
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PackageName: 'Microsoft.ML.OnnxRuntime.Gpu.Tensorrt'
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jobs:
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- job: Linux_C_API_Packaging_GPU_TensorRT_x64
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workspace:
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clean: all
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timeoutInMinutes: 120
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pool: 'Onnxruntime-Linux-GPU'
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variables:
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CUDA_VERSION: '11.1'
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steps:
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- template: templates/set-version-number-variables-step.yml
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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_cuda11_1_tensorrt7_2
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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: onnxruntimecuda111trt72build
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- task: CmdLine@2
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inputs:
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script: |
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mkdir -p $HOME/.onnx
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docker run --gpus all -e CC=/opt/rh/devtoolset-8/root/usr/bin/cc -e CXX=/opt/rh/devtoolset-8/root/usr/bin/c++ -e CFLAGS="-Wp,-D_FORTIFY_SOURCE=2 -Wp,-D_GLIBCXX_ASSERTIONS -fstack-protector-strong -fstack-clash-protection -fcf-protection -O3 -Wl,--strip-all" -e CXXFLAGS="-Wp,-D_FORTIFY_SOURCE=2 -Wp,-D_GLIBCXX_ASSERTIONS -fstack-protector-strong -fstack-clash-protection -fcf-protection -O3 -Wl,--strip-all" -e NVIDIA_VISIBLE_DEVICES=all --rm --volume /data/onnx:/data/onnx:ro --volume $(Build.SourcesDirectory):/onnxruntime_src --volume $(Build.BinariesDirectory):/build \
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--volume /data/models:/build/models:ro --volume $HOME/.onnx:/home/onnxruntimedev/.onnx -e NIGHTLY_BUILD onnxruntimecuda111trt72build \
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/opt/python/cp37-cp37m/bin/python3 /onnxruntime_src/tools/ci_build/build.py --build_dir /build --config Release \
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--skip_submodule_sync --parallel --build_shared_lib --use_tensorrt --cuda_version=$(CUDA_VERSION) --cuda_home=/usr/local/cuda-$(CUDA_VERSION) --cudnn_home=/usr --tensorrt_home=/usr --cmake_extra_defines CMAKE_CUDA_HOST_COMPILER=/opt/rh/devtoolset-8/root/usr/bin/cc
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workingDirectory: $(Build.SourcesDirectory)
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- template: templates/c-api-artifacts-package-and-publish-steps-posix.yml
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parameters:
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buildConfig: 'Release'
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artifactName: 'onnxruntime-linux-x64-gpu-tensorrt-$(OnnxRuntimeVersion)'
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artifactNameNoVersionString: 'onnxruntime-linux-x64-gpu-tensorrt'
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libraryName: 'libonnxruntime.so.$(OnnxRuntimeVersion)'
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commitId: $(OnnxRuntimeGitCommitHash)
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artifactCopyScript: 'tools/ci_build/github/linux/copy_strip_binary_trt.sh'
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- template: templates/component-governance-component-detection-steps.yml
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parameters :
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condition : 'succeeded'
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- template: templates/clean-agent-build-directory-step.yml
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@ -20,12 +20,16 @@ parameters:
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- name: commitId
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type: string
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default: ''
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- name: artifactCopyScript
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type: string
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default: 'tools/ci_build/github/linux/copy_strip_binary.sh'
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steps:
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- task: ShellScript@2
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displayName: 'Copy build artifacts for zipping'
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inputs:
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scriptPath: 'tools/ci_build/github/linux/copy_strip_binary.sh'
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scriptPath: '${{parameters.artifactCopyScript}}'
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args: '-r $(Build.BinariesDirectory) -a ${{parameters.artifactName}} -l ${{parameters.libraryName}} -c ${{parameters.buildConfig}} -s $(Build.SourcesDirectory) -t ${{parameters.commitId}}'
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workingDirectory: '$(Build.BinariesDirectory)/${{parameters.buildConfig}}'
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57
tools/ci_build/github/linux/copy_strip_binary_trt.sh
Normal file
57
tools/ci_build/github/linux/copy_strip_binary_trt.sh
Normal file
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#!/bin/bash
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set -e -o -x
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while getopts r:a:l:c:s:t: parameter_Option
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do case "${parameter_Option}"
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in
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r) BINARY_DIR=${OPTARG};;
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a) ARTIFACT_NAME=${OPTARG};;
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l) LIB_NAME=${OPTARG};;
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c) BUILD_CONFIG=${OPTARG};;
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s) SOURCE_DIR=${OPTARG};;
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t) COMMIT_ID=${OPTARG};;
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esac
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done
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EXIT_CODE=1
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uname -a
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mkdir $BINARY_DIR/$ARTIFACT_NAME
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mkdir $BINARY_DIR/$ARTIFACT_NAME/lib
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mkdir $BINARY_DIR/$ARTIFACT_NAME/include
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echo "Directories created"
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cp $BINARY_DIR/$BUILD_CONFIG/$LIB_NAME $BINARY_DIR/$ARTIFACT_NAME/lib
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cp $BINARY_DIR/$BUILD_CONFIG/libonnxruntime_providers_shared.so $BINARY_DIR/$ARTIFACT_NAME/lib
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cp $BINARY_DIR/$BUILD_CONFIG/libonnxruntime_providers_tensorrt.so $BINARY_DIR/$ARTIFACT_NAME/lib
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echo "Copy debug symbols in a separate file and strip the original binary."
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if [[ $LIB_NAME == *.dylib ]]
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then
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dsymutil $BINARY_DIR/$ARTIFACT_NAME/lib/$LIB_NAME -o $BINARY_DIR/$ARTIFACT_NAME/lib/$LIB_NAME.dSYM
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strip -S $BINARY_DIR/$ARTIFACT_NAME/lib/$LIB_NAME
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ln -s $LIB_NAME $BINARY_DIR/$ARTIFACT_NAME/lib/libonnxruntime.dylib
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elif [[ $LIB_NAME == *.so.* ]]
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then
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ln -s $LIB_NAME $BINARY_DIR/$ARTIFACT_NAME/lib/libonnxruntime.so
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fi
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cp $SOURCE_DIR/include/onnxruntime/core/session/onnxruntime_c_api.h $BINARY_DIR/$ARTIFACT_NAME/include
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cp $SOURCE_DIR/include/onnxruntime/core/session/onnxruntime_cxx_api.h $BINARY_DIR/$ARTIFACT_NAME/include
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cp $SOURCE_DIR/include/onnxruntime/core/session/onnxruntime_cxx_inline.h $BINARY_DIR/$ARTIFACT_NAME/include
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cp $SOURCE_DIR/include/onnxruntime/core/providers/cpu/cpu_provider_factory.h $BINARY_DIR/$ARTIFACT_NAME/include
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cp $SOURCE_DIR/include/onnxruntime/core/providers/cuda/cuda_provider_factory.h $BINARY_DIR/$ARTIFACT_NAME/include
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cp $SOURCE_DIR/include/onnxruntime/core/providers/tensorrt/tensorrt_provider_factory.h $BINARY_DIR/$ARTIFACT_NAME/include
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cp $SOURCE_DIR/include/onnxruntime/core/session/onnxruntime_session_options_config_keys.h $BINARY_DIR/$ARTIFACT_NAME/include
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# copy the README, licence and TPN
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cp $SOURCE_DIR/README.md $BINARY_DIR/$ARTIFACT_NAME/README.md
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cp $SOURCE_DIR/docs/Privacy.md $BINARY_DIR/$ARTIFACT_NAME/Privacy.md
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cp $SOURCE_DIR/LICENSE $BINARY_DIR/$ARTIFACT_NAME/LICENSE
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cp $SOURCE_DIR/ThirdPartyNotices.txt $BINARY_DIR/$ARTIFACT_NAME/ThirdPartyNotices.txt
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cp $SOURCE_DIR/VERSION_NUMBER $BINARY_DIR/$ARTIFACT_NAME/VERSION_NUMBER
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echo $COMMIT_ID > $BINARY_DIR/$ARTIFACT_NAME/GIT_COMMIT_ID
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EXIT_CODE=$?
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set -e
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exit $EXIT_CODE
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FROM nvcr.io/nvidia/cuda:11.1-cudnn8-devel-centos7
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#We need CUDA, TensorRT and manylinux. But the CUDA Toolkit End User License Agreement says NVIDIA CUDA Driver Libraries(libcuda.so, libnvidia-ptxjitcompiler.so) are only distributable in applications that meet this criteria:
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#1. The application was developed starting from a NVIDIA CUDA container obtained from Docker Hub or the NVIDIA GPU Cloud, and
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#2. The resulting application is packaged as a Docker container and distributed to users on Docker Hub or the NVIDIA GPU Cloud only.
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#So we use CUDA as the base image then add manylinux and TensorRT on top of it.
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#Build manylinux2014 docker image begin
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ENV AUDITWHEEL_ARCH x86_64
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ENV AUDITWHEEL_PLAT manylinux2014_$AUDITWHEEL_ARCH
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ENV LC_ALL en_US.UTF-8
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ENV LANG en_US.UTF-8
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ENV LANGUAGE en_US.UTF-8
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ENV DEVTOOLSET_ROOTPATH /opt/rh/devtoolset-9/root
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ENV PATH $DEVTOOLSET_ROOTPATH/usr/bin:$PATH
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ENV LD_LIBRARY_PATH $DEVTOOLSET_ROOTPATH/usr/lib64:$DEVTOOLSET_ROOTPATH/usr/lib:$DEVTOOLSET_ROOTPATH/usr/lib64/dyninst:$DEVTOOLSET_ROOTPATH/usr/lib/dyninst:/usr/local/lib64:/usr/local/lib
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ENV PKG_CONFIG_PATH /usr/local/lib/pkgconfig
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COPY manylinux2014_build_scripts /manylinux2014_build_scripts
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RUN bash /manylinux2014_build_scripts/build.sh 8 && rm -r manylinux2014_build_scripts && yum downgrade -y glibc-2.17-317.el7 glibc-common-2.17-317.el7 glibc-devel-2.17-317.el7 glibc-headers-2.17-317.el7
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ENV SSL_CERT_FILE=/opt/_internal/certs.pem
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#Build manylinux2014 docker image end
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#Install TensorRT 7.2.2.2
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RUN yum install -y wget
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RUN cd /tmp &&\
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wget --no-check-certificate https://developer.download.nvidia.com/compute/machine-learning/repos/rhel7/x86_64/nvidia-machine-learning-repo-rhel7-1.0.0-1.x86_64.rpm &&\
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rpm -Uvh nvidia-machine-learning-repo-*.rpm
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RUN yum install -y libnvinfer7-7.2.2-1.cuda11.1 libnvparsers7-7.2.2-1.cuda11.1 libnvinfer-plugin7-7.2.2-1.cuda11.1 libnvonnxparsers7-7.2.2-1.cuda11.1 libnvinfer-devel-7.2.2-1.cuda11.1 libnvparsers-devel-7.2.2-1.cuda11.1 libnvinfer-plugin-devel-7.2.2-1.cuda11.1
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#Add our own dependencies
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ADD scripts /tmp/scripts
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RUN cd /tmp/scripts && /tmp/scripts/manylinux/install_centos.sh && /tmp/scripts/manylinux/install_deps.sh && rm -rf /tmp/scripts
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ARG BUILD_UID=1001
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ARG BUILD_USER=onnxruntimedev
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RUN adduser --uid $BUILD_UID $BUILD_USER
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WORKDIR /home/$BUILD_USER
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USER $BUILD_USER
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ENV PATH /usr/local/gradle/bin:/usr/local/dotnet:$PATH
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FROM nvcr.io/nvidia/cuda:11.0-cudnn8-devel-centos7
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#We need CUDA, TensorRT and manylinux. But the CUDA Toolkit End User License Agreement says NVIDIA CUDA Driver Libraries(libcuda.so, libnvidia-ptxjitcompiler.so) are only distributable in applications that meet this criteria:
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#1. The application was developed starting from a NVIDIA CUDA container obtained from Docker Hub or the NVIDIA GPU Cloud, and
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#2. The resulting application is packaged as a Docker container and distributed to users on Docker Hub or the NVIDIA GPU Cloud only.
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#So we use CUDA as the base image then add manylinux and TensorRT on top of it.
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#Build manylinux2014 docker image begin
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ENV AUDITWHEEL_ARCH x86_64
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ENV AUDITWHEEL_PLAT manylinux2014_$AUDITWHEEL_ARCH
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ENV LC_ALL en_US.UTF-8
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ENV LANG en_US.UTF-8
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ENV LANGUAGE en_US.UTF-8
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ENV DEVTOOLSET_ROOTPATH /opt/rh/devtoolset-9/root
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ENV PATH $DEVTOOLSET_ROOTPATH/usr/bin:$PATH
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ENV LD_LIBRARY_PATH $DEVTOOLSET_ROOTPATH/usr/lib64:$DEVTOOLSET_ROOTPATH/usr/lib:$DEVTOOLSET_ROOTPATH/usr/lib64/dyninst:$DEVTOOLSET_ROOTPATH/usr/lib/dyninst:/usr/local/lib64:/usr/local/lib
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ENV PKG_CONFIG_PATH /usr/local/lib/pkgconfig
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COPY manylinux2014_build_scripts /manylinux2014_build_scripts
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RUN bash /manylinux2014_build_scripts/build.sh 8 && rm -r manylinux2014_build_scripts && yum downgrade -y glibc-2.17-317.el7 glibc-common-2.17-317.el7 glibc-devel-2.17-317.el7 glibc-headers-2.17-317.el7
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ENV SSL_CERT_FILE=/opt/_internal/certs.pem
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#Build manylinux2014 docker image end
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#Install TensorRT 7.2.2.2
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RUN yum install -y wget
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RUN cd /tmp &&\
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wget --no-check-certificate https://developer.download.nvidia.com/compute/machine-learning/repos/rhel7/x86_64/nvidia-machine-learning-repo-rhel7-1.0.0-1.x86_64.rpm &&\
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rpm -Uvh nvidia-machine-learning-repo-*.rpm
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RUN yum install -y libnvinfer7-7.2.2-1.cuda11.0 libnvparsers7-7.2.2-1.cuda11.0 libnvinfer-plugin7-7.2.2-1.cuda11.0 libnvonnxparsers7-7.2.2-1.cuda11.0 libnvinfer-devel-7.2.2-1.cuda11.0 libnvparsers-devel-7.2.2-1.cuda11.0 libnvinfer-plugin-devel-7.2.2-1.cuda11.0
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#Add our own dependencies
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ADD scripts /tmp/scripts
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RUN cd /tmp/scripts && /tmp/scripts/manylinux/install_centos.sh && /tmp/scripts/manylinux/install_deps.sh && rm -rf /tmp/scripts
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ARG BUILD_UID=1001
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ARG BUILD_USER=onnxruntimedev
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RUN adduser --uid $BUILD_UID $BUILD_USER
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WORKDIR /home/$BUILD_USER
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USER $BUILD_USER
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ENV PATH /usr/local/gradle/bin:/usr/local/dotnet:$PATH
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