8905df4a18
* Basic script for using compilation database. * Add `GENERATE_COMPILATION_DATABASE' to CMake. * Rearrange CMakeLists.txt. * Add basic python clang-tidy script. * Remove modernize-use-auto. * Add clang-tidy to Jenkins * Refine logic for correct path detection In Jenkins, the project root is of form /home/ubuntu/workspace/xgboost_PR-XXXX * Run clang-tidy in CUDA 9.2 container * Use clang_tidy container
46 lines
1.6 KiB
Docker
46 lines
1.6 KiB
Docker
ARG CUDA_VERSION
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FROM nvidia/cuda:$CUDA_VERSION-devel-ubuntu18.04
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# Environment
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ENV DEBIAN_FRONTEND noninteractive
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# Install all basic requirements
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RUN \
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apt-get update && \
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apt-get install -y tar unzip wget git build-essential cmake python3 python3-pip llvm-7 clang-tidy-7 clang-7
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# Set default clang-tidy version
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RUN \
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update-alternatives --install /usr/bin/clang-tidy clang-tidy /usr/bin/clang-tidy-7 100 && \
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update-alternatives --install /usr/bin/clang clang /usr/bin/clang-7 100
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# NCCL2 (License: https://docs.nvidia.com/deeplearning/sdk/nccl-sla/index.html)
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RUN \
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export CUDA_SHORT=`echo $CUDA_VERSION | egrep -o '[0-9]+\.[0-9]'` && \
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if [ "${CUDA_SHORT}" != "10.0" ]; then \
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wget https://developer.download.nvidia.com/compute/redist/nccl/v2.2/nccl_2.2.13-1%2Bcuda${CUDA_SHORT}_x86_64.txz && \
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tar xf "nccl_2.2.13-1+cuda${CUDA_SHORT}_x86_64.txz" && \
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cp nccl_2.2.13-1+cuda${CUDA_SHORT}_x86_64/include/nccl.h /usr/include && \
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cp nccl_2.2.13-1+cuda${CUDA_SHORT}_x86_64/lib/* /usr/lib && \
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rm -f nccl_2.2.13-1+cuda${CUDA_SHORT}_x86_64.txz && \
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rm -r nccl_2.2.13-1+cuda${CUDA_SHORT}_x86_64; fi
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# Install Python packages
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RUN \
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pip3 install pyyaml
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ENV GOSU_VERSION 1.10
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# Install lightweight sudo (not bound to TTY)
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RUN set -ex; \
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wget -O /usr/local/bin/gosu "https://github.com/tianon/gosu/releases/download/$GOSU_VERSION/gosu-amd64" && \
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chmod +x /usr/local/bin/gosu && \
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gosu nobody true
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# Default entry-point to use if running locally
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# It will preserve attributes of created files
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COPY entrypoint.sh /scripts/
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WORKDIR /workspace
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ENTRYPOINT ["/scripts/entrypoint.sh"]
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