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b20daeda81
* Try manually installing trt8.4 in multi-gpu pipeline * Remove stmts that clean up cmake, ctest. Update tensorrt repository name passed to get_docker_image.py * Update trt and cudnn home * Don't install trtexec cli tool. * Increase job timeout * Revert timeout change and use trt placeholder builder build option
36 lines
1.6 KiB
Text
36 lines
1.6 KiB
Text
# Tag: nvidia/cuda:11.6.1-cudnn8-devel-ubuntu20.04
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# Label: com.nvidia.cuda.version: 11.6.1
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# Label: com.nvidia.cudnn.version: 8.4.0
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# Ubuntu 20.04
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FROM nvidia/cuda:11.6.1-cudnn8-devel-ubuntu20.04
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ARG PYTHON_VERSION=3.8
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ARG DEBIAN_FRONTEND=noninteractive
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ADD scripts /tmp/scripts
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RUN /tmp/scripts/install_ubuntu.sh -p $PYTHON_VERSION && /tmp/scripts/install_os_deps.sh && /tmp/scripts/install_python_deps.sh -p $PYTHON_VERSION && rm -rf /tmp/scripts
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# Install TensorRT
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RUN v="8.4.1-1+cuda11.6" &&\
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apt-key adv --fetch-keys https://developer.download.nvidia.com/compute/cuda/repos/ubuntu2004/x86_64/7fa2af80.pub &&\
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apt-get update &&\
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sudo apt-get install -y libnvinfer8=${v} libnvonnxparsers8=${v} libnvparsers8=${v} libnvinfer-plugin8=${v} \
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libnvinfer-dev=${v} libnvonnxparsers-dev=${v} libnvparsers-dev=${v} libnvinfer-plugin-dev=${v} \
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python3-libnvinfer=${v}
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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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ARG BUILD_USER=onnxruntimedev
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ARG BUILD_UID=1000
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WORKDIR /home/$BUILD_USER
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RUN adduser --gecos 'onnxruntime Build User' --disabled-password $BUILD_USER --uid $BUILD_UID
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USER $BUILD_USER
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