57 lines
1.7 KiB
Docker
57 lines
1.7 KiB
Docker
ARG PYTORCH="1.8.1"
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ARG CUDA="10.2"
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ARG CUDNN="7"
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FROM pytorch/pytorch:${PYTORCH}-cuda${CUDA}-cudnn${CUDNN}-devel
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# fetch the key refer to https://forums.developer.nvidia.com/t/18-04-cuda-docker-image-is-broken/212892/9
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RUN apt-key adv --fetch-keys https://developer.download.nvidia.com/compute/cuda/repos/ubuntu1804/x86_64/3bf863cc.pub 32
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RUN apt-key adv --fetch-keys https://developer.download.nvidia.com/compute/machine-learning/repos/ubuntu1804/x86_64/7fa2af80.pub
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ARG MMENGINE="0.7.1"
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ARG MMCV="2.0.0"
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ARG MMCLS="1.0.0rc6"
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ENV PYTHONUNBUFFERED TRUE
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RUN apt-get update && \
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DEBIAN_FRONTEND=noninteractive apt-get install --no-install-recommends -y \
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ca-certificates \
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g++ \
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openjdk-11-jre-headless \
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# MMDet Requirements
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ffmpeg libsm6 libxext6 git ninja-build libglib2.0-0 libsm6 libxrender-dev libxext6 \
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&& rm -rf /var/lib/apt/lists/*
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ENV PATH="/opt/conda/bin:$PATH"
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RUN export FORCE_CUDA=1
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# TORCHSEVER
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RUN pip install torchserve torch-model-archiver
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RUN pip install nvgpu
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# MMLAB
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ARG PYTORCH
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ARG CUDA
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RUN pip install mmengine==${MMENGINE}
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RUN ["/bin/bash", "-c", "pip install mmcv==${MMCV} -f https://download.openmmlab.com/mmcv/dist/cu${CUDA//./}/torch${PYTORCH}/index.html"]
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RUN pip install mmcls==${MMCLS}
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RUN useradd -m model-server \
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&& mkdir -p /home/model-server/tmp
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COPY entrypoint.sh /usr/local/bin/entrypoint.sh
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RUN chmod +x /usr/local/bin/entrypoint.sh \
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&& chown -R model-server /home/model-server
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COPY config.properties /home/model-server/config.properties
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RUN mkdir /home/model-server/model-store && chown -R model-server /home/model-server/model-store
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EXPOSE 8080 8081 8082
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USER model-server
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WORKDIR /home/model-server
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ENV TEMP=/home/model-server/tmp
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ENTRYPOINT ["/usr/local/bin/entrypoint.sh"]
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CMD ["serve"]
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