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* Upgrade gpu build to CUDA 10 + cudnn 7.3 * update the yaml file for python package building * switch to the cuda9.1 docker file if the CUDA_VER is cuda9.1-cudnn7.1
43 lines
1.6 KiB
Text
43 lines
1.6 KiB
Text
# Tag: nvidia/cuda:10.0-cudnn7-devel-ubuntu16.04
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# Label: com.nvidia.cuda.version: 10.0.130
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# Label: com.nvidia.cudnn.version: 7.3.1.20
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# Ubuntu 16.04.5
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FROM nvidia/cuda@sha256:362e4e25aa46a18dfa834360140e91b61cdb0a3a2796c8e09dadb268b9de3f6b
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ARG PYTHON_VERSION=3.5
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ADD scripts /tmp/scripts
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ENV PATH="/opt/cmake/bin:${PATH}"
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RUN /tmp/scripts/install_ubuntu.sh -p ${PYTHON_VERSION} && /tmp/scripts/install_deps.sh && rm -rf /tmp/scripts
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WORKDIR /root
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# Allow configure to pick up GDK and CuDNN where it expects it.
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# (Note: $CUDNN_VERSION is defined by NVidia's base image)
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RUN _CUDNN_VERSION=$(echo $CUDNN_VERSION | cut -d. -f1-2) && \
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mkdir -p /usr/local/cudnn-$_CUDNN_VERSION/cuda/include && \
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ln -s /usr/include/cudnn.h /usr/local/cudnn-$_CUDNN_VERSION/cuda/include/cudnn.h && \
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mkdir -p /usr/local/cudnn-$_CUDNN_VERSION/cuda/lib64 && \
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ln -s /etc/alternatives/libcudnn_so /usr/local/cudnn-$_CUDNN_VERSION/cuda/lib64/libcudnn.so && \
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ln -s /usr/local/cudnn{-$_CUDNN_VERSION,}
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# Build and Install LLVM
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ARG LLVM_VERSION=6.0.1
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RUN cd /tmp && \
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wget --no-verbose http://releases.llvm.org/$LLVM_VERSION/llvm-$LLVM_VERSION.src.tar.xz && \
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xz -d llvm-$LLVM_VERSION.src.tar.xz && \
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tar xvf llvm-$LLVM_VERSION.src.tar && \
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cd llvm-$LLVM_VERSION.src && \
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mkdir -p build && \
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cd build && \
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cmake .. -DCMAKE_BUILD_TYPE=Release && \
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cmake --build . -- -j$(nproc) && \
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cmake -DCMAKE_INSTALL_PREFIX=/usr/local/llvm-$LLVM_VERSION -DBUILD_TYPE=Release -P cmake_install.cmake && \
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cd /tmp && \
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rm -rf llvm*
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ENV LD_LIBRARY_PATH /usr/local/openblas/lib:$LD_LIBRARY_PATH
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ARG BUILD_USER=onnxruntimedev
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WORKDIR /home/$BUILD_USER
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