[miscellaneous] docker usage

기타 유용한 Docker 명령어에 대해 작성합니다.

Make Dockerfile

Get docker image
- docker pull nvidia/cuda:11.6.1-devel-ubuntu20.04
Dockerfile
- 반드시 파일의 제목은 Dockerfile 이어야 한다. (확장자는 없음.)

Example Dockerfile

# 기존 이미지를 기반으로 사용
# Use nvidia/cuda version matches your server
FROM nvidia/cuda:11.6.1-cudnn8-devel-ubuntu20.04

# 필요한 패키지 설치
# Install ubuntu apt packages. Do not remove default packages.
RUN apt-get update
# opencv-python error
RUN apt-get update && DEBIAN_FRONTEND=noninteractive apt-get install\
    libgl1\
    libgl1-mesa-glx \ 
    libglib2.0-0 -y && \
    rm -rf /var/lib/apt/lists/*
RUN apt-get update && DEBIAN_FRONTEND=noninteractive apt-get install -y \
    wget \
    apt-utils \
    build-essential \
    ca-certificates \
    curl \
    git \
    htop \
    sudo \
    vim \
    python3-dev \
    python3-pip \
    && rm -rf /var/lib/apt/lists/*

# Miniconda 설치
RUN wget https://repo.anaconda.com/miniconda/Miniconda3-latest-Linux-x86_64.sh -O /miniconda.sh
RUN bash /miniconda.sh -b -p /miniconda
ENV PATH="/miniconda/bin:${PATH}"

# Conda를 이용해 Python3 설치 및 Python 패키지 설치
RUN conda install -y python=3.9 && \
    pip3 --no-cache-dir install --upgrade \
    pip \
    setuptools \
    ipython \
    ipdb \
    matplotlib \
    pandas \
    scipy \
    torch \
    jupyter \
    torchvision \
    torchtext \
    torchsummary \
    slacker \
    tqdm

# # 사용자 설정
# ARG UNAME
# ARG UID
# ARG GID

# # Ensure that the group and user are created successfully
# RUN if [ -z "$UNAME" ] || [ -z "$UID" ] || [ -z "$GID" ]; then echo "UNAME, UID, and GID arguments are required" && exit 1; fi && \
#     addgroup --gid ${GID} ${UNAME} && \
#     useradd -m -u ${UID} -g ${GID} -s /bin/bash ${UNAME} && \
#     adduser ${UNAME} sudo

# USER ${UNAME}
# WORKDIR /home/${UNAME}

CMD [ "/bin/bash" ]

Build Log

joonhyung@devbox:~/dockers/joonh_cu116$ docker build -t joonh_cu116 .
[+] Building 260.0s (11/11) FINISHED                                                                                                                                                    
 => [internal] load .dockerignore                                                                                                                                                  0.0s
 => => transferring context: 2B                                                                                                                                                    0.0s
 => [internal] load build definition from Dockerfile                                                                                                                               0.0s
 => => transferring dockerfile: 1.72kB                                                                                                                                             0.0s
 => [internal] load metadata for docker.io/nvidia/cuda:11.6.1-cudnn8-devel-ubuntu20.04                                                                                             0.0s
 => [1/7] FROM docker.io/nvidia/cuda:11.6.1-cudnn8-devel-ubuntu20.04                                                                                                               0.0s
 => CACHED [2/7] RUN apt-get update                                                                                                                                                0.0s
 => [3/7] RUN apt-get update && DEBIAN_FRONTEND=noninteractive apt-get install    libgl1    libgl1-mesa-glx     libglib2.0-0 -y &&     rm -rf /var/lib/apt/lists/*                19.2s
 => [4/7] RUN apt-get update && DEBIAN_FRONTEND=noninteractive apt-get install -y     wget     apt-utils     build-essential     ca-certificates     curl     git     htop     s  24.1s
 => [5/7] RUN wget https://repo.anaconda.com/miniconda/Miniconda3-latest-Linux-x86_64.sh -O /miniconda.sh                                                                          3.0s
 => [6/7] RUN bash /miniconda.sh -b -p /miniconda                                                                                                                                  6.4s
 => [7/7] RUN conda install -y python=3.9 &&     pip3 --no-cache-dir install --upgrade     pip     setuptools     ipython     ipdb     matplotlib     pandas     scipy     torc  177.4s
 => exporting to image                                                                                                                                                            29.8s
 => => exporting layers                                                                                                                                                           29.8s
 => => writing image sha256:48e3f2be75424e71be48c75d5472c90a9bf5ac9c94586bd723127d5bed67714b                                                                                       0.0s 
 => => naming to docker.io/library/joonh_cu116

Build docker image

docker build -t [이미지 이름:이미지 버전] [Dockerfile의 경로]
docker build -t joonh_cu116 .
docker build --build-arg UNAME=joonhyung-lee --build-arg UID=1001 --build-arg GID=1001 -t joonh_cu116 .

Get built docker images

docker images
>>> joonh_cu116    latest    7c1bae5ab933   33 seconds ago   9.56GB

Start Docker Container

docker run -v [로컬_경로]:[컨테이너_경로] -it --gpus all [이미지_이름]:[태그] /bin/bash
docker run -v /home/joonhyung/python/:/home/root/python -it --gpus all joonh_cu116:latest /bin/bash

Commit and Push Docker Container

get information about container

joonhyung@devbox:~/dockers/joonh_cu116$ docker ps
CONTAINER ID   IMAGE                              COMMAND                  CREATED             STATUS             PORTS                                       NAMES
79b602e29923   c2e91d98d3ed                       "/opt/nvidia/nvidia_…"   About an hour ago   Up About an hour                                               magical_neumann

Commit

docker commit CONTAINER IMAGE_NAME
joonhyung@devbox:~/dockers/joonh_cu116$ docker commit 79b602e29923 joonh_cu116:v00
sha256:f50aabee25697dc96bc80f76fd231c74d1fbfe77cb47698a4ec89e0b84c5ba81

docker images로 image가 적절하게 생성되었는지 확인 가능.

  joonhyung@devbox:~/dockers/joonh_cu116$ docker images
  REPOSITORY                                                  TAG                               IMAGE ID       CREATED          SIZE
  joonh_cu116                                                 v00                               f50aabee2569   14 seconds ago   31GB

Build `Dockerfile`

Add lines

FROM joonh_cu116:v00
# Install ubuntu apt packages.
RUN sudo apt update && sudo apt install -y <ubuntu-packages>

Build New version
- ```
docker build -t joonh_cu116:v01 .
```

  joonhyung@devbox:~/dockers/joonh_cu116_v00$ docker login -u joonhyunglee
  Password: 
  WARNING! Your password will be stored unencrypted in /home/joonhyung/.docker/config.json.
  Configure a credential helper to remove this warning. See
  https://docs.docker.com/engine/reference/commandline/login/#credentials-store

  Login Succeeded

push on Docker

joonhyung@devbox:~/dockers/joonh_cu116_v00$ docker push joonhyunglee/joonh_cu116:v01

Make Dockerfile

Example Dockerfile

Build docker image

Get built docker images

Start Docker Container

Commit and Push Docker Container

get information about container

Commit

Build Dockerfile

Login Docker server

push on Docker

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Build `Dockerfile`