mirror of
https://github.com/saymrwulf/onnxruntime.git
synced 2026-06-09 00:30:53 +00:00
814638cdff
* link to folder instead of READMEs inside folder (#3938) otherwise hard to find the source code * [Node.js binding] fix linux build (#3927) * [Node.js binding] add build flag for node.js binding (#3948) * [Nodejs binding] create a new pipeline to generate signed binaries (#4104) * add yml files * update pipeline * fix yaml syntax * yaml pop BuildCSharp * udpate yaml * do not stage codesign summary * fix build: pipeline Node.js version to 12.16.3 (#4145) * [Node.js binding] upgrade node-addon-api to 3.0 (#4148) * [Node.js binding] add linux and mac package (#4157) * try mac pipeline * fix path separator * copy prebuilds folder * split esrp yaml for win/mac * disable mac signing temporarily * add linux * fix indent * add nodetool in linux * add nodetool in win-ci-2019 * replace linux build by custom docker scripts * use manylinux as node 12.16 not working on centos6 * try ubuntu * loosen timeout for test case - multiple runs calls * add script to support update nodejs binding version (#4164) * [java] Adds a CUDA test (#3956) * [java] - adding a cuda enabled test. * Adding --build_java to the windows gpu ci pipeline. * Removing a stray line from the unit tests that always enabled CUDA for Java. * Update OnnxRuntime.java for OS X environment. (#3985) onnxruntime init failure due to wrong path of reading native libraries. In OS X 64 system, the arch name is detected as x86 which generates invalid path to read native libraries. Exception java.lang.UnsatisfiedLinkError: no onnxruntime in java.library.path at java.lang.ClassLoader.loadLibrary(ClassLoader.java:1867) at java.lang.Runtime.loadLibrary0(Runtime.java:870) at java.lang.System.loadLibrary(System.java:1122) at ai.onnxruntime.OnnxRuntime.load(OnnxRuntime.java:174) at ai.onnxruntime.OnnxRuntime.init(OnnxRuntime.java:81) at ai.onnxruntime.OrtEnvironment.<clinit>(OrtEnvironment.java:24) * Create Java publishing pipeline (#3944) Create CPU and GPu Java publishing pipelines. Final jars are tested on all platforms. However, signing and publishing to maven are manual steps. * Change group id to com.microsoft.onnxruntime per requirements. * Java GPu artifact naming (#4179) Modify gradle build so artifactID has _gpu for GPU builds. Pass USE_CUDA flag on CUDA build Adjust publishing pipelines to extract POM from a correct path. Co-Authored-By: @Craigacp * bump up ORT version to 1.3.1 (#4181) * move back to toolset 14.16 to possibly work around nvcc bug (#4180) * Symbolic shape inference exit on models without onnx opset used (#4090) * Symbolic shape inference exit on models without onnx opset used * Temporary fix for ConvTranspose with symbolic input dims Co-authored-by: Changming Sun <me@sunchangming.com> * Fix Nuphar test failure * Enlarge the read buffer size in C#/Java test code (#4150) 1. Enlarge the read buffer size further, so that our code can run even faster. TODO: need apply the similar changes to python some other language bindings. 2. Add coreml_VGG16_ImageNet to the test exclusion set of x86_32. It is not a new model but previously we didn't run the test against x86_32. * Temporarily disable windows static analysis CI job * skip model coreml_Imputer-LogisticRegression_sklearn_load_breast_cancer * Delete unused variable Co-authored-by: Prasanth Pulavarthi <prasantp@microsoft.com> Co-authored-by: Yulong Wang <yulongw@microsoft.com> Co-authored-by: Adam Pocock <adam.pocock@oracle.com> Co-authored-by: jji2019 <49252772+jji2019@users.noreply.github.com> Co-authored-by: Dmitri Smirnov <yuslepukhin@users.noreply.github.com> Co-authored-by: Dmitri Smirnov <dmitrism@microsoft.com> Co-authored-by: George Wu <jywu@microsoft.com> Co-authored-by: KeDengMS <kedeng@microsoft.com> Co-authored-by: Changming Sun <me@sunchangming.com> Co-authored-by: Changming Sun <chasun@microsoft.com>
69 lines
2.8 KiB
Text
69 lines
2.8 KiB
Text
FROM mcr.microsoft.com/dotnet-buildtools/prereqs:centos-6-50f0d02-20190918213956
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ENV NVIDIA_VISIBLE_DEVICES all
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ENV NVIDIA_DRIVER_CAPABILITIES compute,utility
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ADD scripts /tmp/scripts
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RUN cd /tmp/scripts && /tmp/scripts/install_centos.sh
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ENV JAVA_HOME /usr/lib/jvm/jre-1.8.0-openjdk.x86_64
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ENV PATH /opt/rh/devtoolset-2/root/usr/bin:${JAVA_HOME}/bin:${PATH}
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RUN /tmp/scripts/install_deps.sh -p 3.6 && rm -rf /tmp/scripts
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ENV PATH ${PATH}:/usr/local/gradle/bin
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#Below are copied from https://gitlab.com/nvidia/container-images/cuda/tree/master/dist/centos6
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RUN NVIDIA_GPGKEY_SUM=d1be581509378368edeec8c1eb2958702feedf3bc3d17011adbf24efacce4ab5 && \
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curl -fsSL https://developer.download.nvidia.com/compute/cuda/repos/rhel6/x86_64/7fa2af80.pub | sed '/^Version/d' > /etc/pki/rpm-gpg/RPM-GPG-KEY-NVIDIA && \
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echo "$NVIDIA_GPGKEY_SUM /etc/pki/rpm-gpg/RPM-GPG-KEY-NVIDIA" | sha256sum -c -
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COPY cuda_manylinux2010.repo /etc/yum.repos.d/cuda.repo
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ENV CUDA_VERSION 10.1.243
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ENV CUDA_PKG_VERSION 10-1-$CUDA_VERSION-1
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RUN yum install -y \
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cuda-cudart-$CUDA_PKG_VERSION \
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cuda-compat-10-1 \
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cuda-libraries-$CUDA_PKG_VERSION \
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cuda-nvtx-$CUDA_PKG_VERSION \
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libcublas10-10.2.1.243-1 \
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cuda-nvml-dev-$CUDA_PKG_VERSION \
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cuda-command-line-tools-$CUDA_PKG_VERSION \
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cuda-libraries-dev-$CUDA_PKG_VERSION \
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cuda-minimal-build-$CUDA_PKG_VERSION \
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libcublas-devel-10.2.1.243-1 \
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&& \
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ln -s cuda-10.1 /usr/local/cuda && \
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rpm -e --nodeps gcc gcc-c++ && \
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rm -rf /var/cache/yum/*
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# nvidia-docker 1.0
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RUN echo "/usr/local/nvidia/lib" >> /etc/ld.so.conf.d/nvidia.conf && \
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echo "/usr/local/nvidia/lib64" >> /etc/ld.so.conf.d/nvidia.conf
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ENV PATH /usr/local/nvidia/bin:/usr/local/cuda/bin:${PATH}
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ENV LD_LIBRARY_PATH /usr/local/nvidia/lib:/usr/local/nvidia/lib64:${LD_LIBRARY_PATH}
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# nvidia-container-runtime
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ENV NVIDIA_VISIBLE_DEVICES all
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ENV NVIDIA_DRIVER_CAPABILITIES compute,utility
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ENV NVIDIA_REQUIRE_CUDA "cuda>=10.1 brand=tesla,driver>=384,driver<385 brand=tesla,driver>=396,driver<397 brand=tesla,driver>=410,driver<411"
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ENV LIBRARY_PATH /usr/local/cuda/lib64/stubs
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ENV CUDNN_VERSION 7.6.5.32
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LABEL com.nvidia.cudnn.version="${CUDNN_VERSION}"
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# cuDNN license: https://developer.nvidia.com/cudnn/license_agreement
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RUN CUDNN_DOWNLOAD_SUM=7eaec8039a2c30ab0bc758d303588767693def6bf49b22485a2c00bf2e136cb3 && \
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curl -fsSL http://developer.download.nvidia.com/compute/redist/cudnn/v7.6.5/cudnn-10.1-linux-x64-v7.6.5.32.tgz -O && \
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echo "$CUDNN_DOWNLOAD_SUM cudnn-10.1-linux-x64-v7.6.5.32.tgz" | sha256sum -c - && \
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tar --no-same-owner -xzf cudnn-10.1-linux-x64-v7.6.5.32.tgz -C /usr/local && \
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rm cudnn-10.1-linux-x64-v7.6.5.32.tgz && \
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ldconfig
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ARG BUILD_UID=1000
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ARG BUILD_USER=onnxruntimedev
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RUN /usr/sbin/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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