model_accuracy/server/Dockerfile

# 创建一个基础镜像 
FROM nvidia/cuda:11.2.2-cudnn8-devel-ubuntu20.04

RUN apt-key del 7fa2af80
RUN apt-key adv --fetch-keys https://developer.download.nvidia.com/compute/cuda/repos/ubuntu1804/x86_64/3bf863cc.pub
RUN apt-key adv --fetch-keys https://developer.download.nvidia.com/compute/machine-learning/repos/ubuntu1804/x86_64/7fa2af80.pub

# 重置apt-get
RUN rm -rf /etc/apt/sources.list

RUN echo "deb http://mirrors.tuna.tsinghua.edu.cn/ubuntu/ bionic main restricted universe multiverse" >> /etc/apt/sources.list

RUN apt-get update

RUN apt-get install -y default-jre

RUN apt-get install -y cmake

# 安装conda
# yhyu13 : install additional packages
# 设置apt的源为tsinghua镜像源
RUN sed -i 's/archive.ubuntu.com/mirrors.tuna.tsinghua.edu.cn/g' /etc/apt/sources.list

RUN apt-get update && apt-get install -y curl wget

# 安装conda
RUN curl -O https://repo.anaconda.com/miniconda/Miniconda3-latest-Linux-x86_64.sh \
    && bash Miniconda3-latest-Linux-x86_64.sh -b -p /opt/conda \
    && rm Miniconda3-latest-Linux-x86_64.sh

RUN /opt/conda/bin/conda init bash

RUN mkdir env

# 解压env中的mxnet tensorflow lemon
COPY env/mxnet.tar.gz env/mxnet.tar.gz
RUN mkdir /opt/conda/envs/mxnet
RUN tar -zxvf env/mxnet.tar.gz -C /opt/conda/envs/mxnet

COPY env/tensorflow.tar.gz env/tensorflow.tar.gz
RUN mkdir /opt/conda/envs/tensorflow
RUN tar -zxvf env/tensorflow.tar.gz -C /opt/conda/envs/tensorflow

COPY env/lemon.tar.gz env/lemon.tar.gz
RUN mkdir /opt/conda/envs/lemon
RUN tar -zxvf env/lemon.tar.gz -C /opt/conda/envs/lemon

RUN rm -rf env


# 复制项目文件


COPY lemon_master /app/lemon_master
COPY app.py /app/app.py
COPY tool.py /app/tool.py
# COPY config.yml /app/config.yml

RUN echo "conda activate lemon" >> ~/.bashrc

WORKDIR /app
# 随便启动一个进程空转

ENTRYPOINT ["/bin/bash", "-c", "source ~/.bashrc && /opt/conda/envs/lemon/bin/python app.py"]
# CMD ["/bin/bash"]
# CMD ["tail", "-f", "/dev/null"]