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版本：最新版本(unreleased)

加载器镜像构建流程

构建业务镜像流程​

1. 构建要求​

  • Docker (20.10.0 or above)
  • 基于conda环境的服务（一个conda环境对应一个服务）

2. envd 安装​

pip install --pre --upgrade envd
envd bootstrap

3. 导出当前的conda环境清单​

conda env export > env.yaml

4.编写build.envd文件​

选择要加载的基础镜像和配置conda的python版本​

  • base(language="python3.8", os="ubuntu20.4")
  • 可选的base镜像
    • aiges_cpu
    • aiges_gpu

安装指定路径下的conda env环境清单​

  • install.conda_packages(env_file="env.yaml")

安装系统依赖（将要安装的依赖写入name列表中，以逗号分开）​

  • install.system_packages(name = ["..."])

将服务代码拷贝到业务镜像中​

  • io.copy(src="./detectron2", dest="/")

离线安装（需要先进行文件拷贝然后进行安装）​

  • io.copy(src="./detectron2", dest="/")
  • run(commands=["pip install -e /detectron2",])

安装源设置​

  • config.pip_index()
  • config.conda_channel()

示例（存在可选的其他安装接口）​

def build():
    mirror_config() 
    base(language="python3.8", os="ubuntu20.4")                          # 加载基础镜像并设置conda内置的python版本
    install.python_packages(name = [
        "torch==1.10",
        "openmim"
    ])
    install.conda_packages(channel= ["pytorch"], env_file = "env.yaml")   # 指定路径下进行conda yaml环境安装
    install.python_packages(requirements="build.txt")                     # 指定路径下进行requirments.txt安装
    install.system_packages(name = [                                      # 系统依赖安装
        "libgl1-mesa-glx"
    ])
    run(commands=[
        "mim install mmcv-full",                                           # 通过第三方工具mim来进行安装
    ])

    io.copy(src="./detectron2", dest="/")                                  # 本地文件到镜像的拷贝
    run(commands=[                                                         # 离线进行依赖包安装
        "pip install -e /detectron2",
    ])
def mirror_config():                                                       #下载源配置
    config.pip_index(url = "https://pypi.tuna.tsinghua.edu.cn/simple")
    config.conda_channel(channel="""
    channels:
    - defaults
    show_channel_urls: true
    default_channels:
    - https://repo.anaconda.com/pkgs/main
    - https://mirrors.tuna.tsinghua.edu.cn/anaconda/pkgs/main/
    - https://mirrors.tuna.tsinghua.edu.cn/anaconda/pkgs/free/
    - https://mirrors.tuna.tsinghua.edu.cn/anaconda/cloud/pytorch/
    - https://mirrors.tuna.tsinghua.edu.cn/anaconda/cloud/menpo/
    - https://mirrors.tuna.tsinghua.edu.cn/anaconda/cloud/bioconda/
    - https://mirrors.tuna.tsinghua.edu.cn/anaconda/cloud/msys2/
    - https://mirrors.tuna.tsinghua.edu.cn/anaconda/cloud/conda-forge/
    custom_channels:
    conda-forge: https://mirrors.tuna.tsinghua.edu.cn/anaconda/cloud
    msys2: https://mirrors.tuna.tsinghua.edu.cn/anaconda/cloud
    bioconda: https://mirrors.tuna.tsinghua.edu.cn/anaconda/cloud
    menpo: https://mirrors.tuna.tsinghua.edu.cn/anaconda/cloud
    pytorch: https://mirrors.tuna.tsinghua.edu.cn/anaconda/cloud
    pytorch-lts: https://mirrors.tuna.tsinghua.edu.cn/anaconda/cloud
    simpleitk: https://mirrors.tuna.tsinghua.edu.cn/anaconda/cloud
    """)

5. 通过envd进行镜像构建​

envd build -t 镜像名:TAG -f build.envd

示例：envd build -t yolo:v1.0.0 -f build.envd