From 21b4c35ae90c5d28f0671e3339e2fd30666d39be Mon Sep 17 00:00:00 2001 From: Sangwoo Han Date: Wed, 6 Nov 2019 23:38:35 +0900 Subject: [PATCH] Update README.md --- README.md | 140 +++++++++++++++++++++++++++++++++++----------- images/image5.png | Bin 0 -> 1233697 bytes images/image6.png | Bin 0 -> 661562 bytes 3 files changed, 108 insertions(+), 32 deletions(-) create mode 100644 images/image5.png create mode 100644 images/image6.png diff --git a/README.md b/README.md index 1b7aa14..8f06009 100644 --- a/README.md +++ b/README.md @@ -46,7 +46,7 @@ $ sudo apt-get update $ sudo apt-get install docker-ce docker-ce-cli containerd.io ``` -### 7. docker 그룹 추가 (Optional) +### 7. docker 그룹 추가 (Optional, 권장) docker command는 root 권한을 요구하므로 매번 docker command를 입력하려면 sudo 명령으로 실행해야 함. 이를 완화하기 위해 docker command를 사용하는 user를 docker 그룹에 포함시켜 sudo @@ -68,9 +68,8 @@ $ docker run --rm hello-world # test run 정상적으로 실행되는지 확인 ### 8. docker-compose 설치하기 -`docker-compose`는 [multi-container](#Container) Docker application을 정의하고 -실행하는 툴인데 단일 [container](#Container)를 실행하고 관리하기에도 매우 유용하다. -사용법은 [docker-compose](#docker-compose) section에서 다루도록 한다. +`docker-compose`는 [multi-container](#Docker\ 용어\ 설명) Docker application을 정의하고 +실행하는 툴인데 단일 [container](#Docker\ 용어\ 설명)를 실행하고 관리하기에도 매우 유용하다. ```sh $ sudo curl -L "https://github.com/docker/compose/releases/download/1.24.1/docker-compose-$(uname -s)-$(uname -m)" -o /usr/local/bin/docker-compose # docker-compose 다운로드 @@ -78,8 +77,13 @@ $ sudo chmod +x /usr/local/bin/docker-compose # 실행권한 부여 $ docker-compose --version # 버전 확인 ``` +#### Update + +- 2019-11-04 + 현재 최신 docker compose file version (v 3.7)에서 `gpus` flag가 지원하지 않아 docker-compose 활용을 보류함. + ### 9. [NVIDIA Container Toolkit](https://github.com/NVIDIA/nvidia-docker) 설치 -GPU 자원을 Docker [Container](#Container)에서 사용하기 위해서는 NVIDIA Container +GPU 자원을 Docker [Container](#Docker\ 용어\ 설명)에서 사용하기 위해서는 NVIDIA Container Toolkit을 설치하여야 한다. #### Prerequisite @@ -104,48 +108,120 @@ $ docker run --rm --gpus all nvidia/cuda:9.0-base nvidia-smi ![Image1](./images/image1.png) -### 10. GPU-Accelerated Tensorflow 및 Jupyter Notebook을 Container에서 실행해보기 +### 10. Dockerfile 작성하기 + +Docker를 사용하여 원하는 개발환경을 구축하기 위해서는 Docker Hub와 같은 open repository에서 +미리 빌드된 이미지를 사용하거나 사용자가 직접 이미지를 빌드해야 한다. Official 이미지를 +사용하면 미리 세팅된 환경을 구축할 수 있지만 customizing이 다소 힘들다. 따라서 여기서는 +Dockerfile를 작성해 직접 이미지를 빌드하여 입맛에 맞게 환경을 셋팅하는 방법을 알아 볼 것이다. +구축할 환경은 다음과 같다. + +* Ubuntu 18.04 +* cuda 10.0 +* cudnn 7.6 +* Anaconda3 (python3.7) +* tensorflow 2.0 (Dockerfile를 수정하여 pytorch를 설치할 수 있음) +* jupyter lab (jupyter notebook의 확장 버전) + +#### Dockerfile + +```Dockerfile +# cuda 및 cudnn이 미리 세팅된 official image 가져오기 +FROM nvidia/cuda:10.0-cudnn7-devel-ubuntu18.04 + +# 생성될 container의 환경변수 설정 +ENV LANG=C.UTF-8 LC_ALL=C.UTF-8 +ENV PATH /opt/conda/bin:$PATH + +# apt repository 업데이트 및 필요한 패키지 설치 +RUN apt-get update --fix-missing && apt-get install -y wget bzip2 ca-certificates \ + libglib2.0-0 libxext6 libsm6 libxrender1 \ + git mercurial subversion && \ + apt-get clean && \ + rm -rf /var/lib/apt/lists/* + +# Anaconda3 설치 +RUN wget --quiet https://repo.anaconda.com/archive/Anaconda3-2019.10-Linux-x86_64.sh -O ~/anaconda.sh && \ + /bin/bash ~/anaconda.sh -b -p /opt/conda && \ + rm ~/anaconda.sh && \ + ln -s /opt/conda/etc/profile.d/conda.sh /etc/profile.d/conda.sh && \ + echo ". /opt/conda/etc/profile.d/conda.sh" >> ~/.bashrc && \ + echo "conda activate base" >> ~/.bashrc && \ + cp ~/.bashrc /etc/bash.bashrc && \ + chmod 777 /etc/bash.bashrc + +# Jupyter lab workspace 생성 +RUN mkdir -p /jupyter-lab && chmod 777 /jupyter-lab + +# conda 패키지 설치 +RUN conda update -y conda && \ + conda install -y tensorflow-gpu=2.0.0 nodejs black && \ + conda update -y jupyterlab && \ + conda clean -y -a + +# volume mount 지정 +VOLUME ["/opt/conda/share/jupyter/lab", "/root/.jupyter", "/jupyter-lab"] + +# working directory 지정 +WORKDIR /jupyter-lab + +# 8888 포트 사용 +EXPOSE 8888 + +# container 실행시 entrypoint command +ENTRYPOINT ["/bin/bash", "-c", "source /etc/bash.bashrc && jupyter lab --ip 0.0.0.0 --no-browser --allow-root"] +``` -#### 실행 +#### Image 빌드하기 ```sh -$ docker run \ - -it \ # container와 상호작용하기 위한 옵션 (키보드 입력) - --rm \ # container 프로세스가 exit하면 자동으로 container을 삭제 - -p 8888:8888 \ # host와 container의 포트 mapping - -u $(id -u):$(id -g) \ # host의 유저 id와 그룹 id로 container 실행 - --gpus all \ # 모든 gpu 리소스 사용 - tensorflow/tensorflow:2.0.0-gpu-py3-jupyter # 사용할 docker image +$ docker build -t [태그이름] . # Dockerfile이 위치한 디렉토리에서 ``` -![Image2](./images/image2.png) +태그이름 형식: [repository name]/[image name]:[tag] +e.g. realappsdev/tf:latest -#### 접속하기 +#### 빌드된 이미지 확인 -http://[server ip]:8888/?token=[token] - -![Image3](./images/image3.png) +```sh +$ docker images -#### 테스트 +REPOSITORY TAG IMAGE ID CREATED SIZE +realappsdev/tf latest 9eb19b0a20b2 4 hours ago 9.07GB +nvidia/cuda 10.0-cudnn7-devel-ubuntu18.04 eaf2ceb9de1a 2 months ago 3.08GB +hello-world latest fce289e99eb9 10 months ago 1.84kB +``` -

- -

+#### 컨테이너 실행 -## Docker 용어 설명 +```sh +$ docker run --init \ # 컨테이너에 init 실행 + -it \ # interactive & pseudo-tty + --name jupyter-lab \ # 컨테이너 이름 지정 + -p 8888:8888 \ # 포트 개방 + -v jupyter_lab_app:/opt/conda/share/jupyter/lab \ # named volume + -v jupyter_lab_config:/root/.jupyter \ # named volume + -v /data/jupyter-lab:/jupyter-lab \ # bind host filesystem + --gpus all \ # gpu 리소스 사용 + realappsdev/tf # 이미지 이름 +``` -### Image +host 머신에 /data/jupyter-lab 디렉토리가 존재해야 함. (또는 다른 디렉토리로 지정 가능) -TODO +![Image5](./images/image5.png) -### Container +#### Jupyter lab 접속 -TODO +http://[server-ip]:8888 -## Docker 기본 명령 +![Image6](images/image6.png) -TODO +## Docker 용어 설명 -## docker-compose +공식적인 설명은 다음 링크 참고. +[Docker Glossary](https://docs.docker.com/glossary/) -TODO +| Term | Definition | +| ----------------- | :---------------------------------------------------------- | +| Image | 가상머신에서 사용되는 스냅샷과 비슷한 개념. | +| Container | Image의 runtime 인스턴스. java에 비유하면 image는 class, conatiner는 객체 | diff --git a/images/image5.png b/images/image5.png new file mode 100644 index 0000000000000000000000000000000000000000..29c265163f7689c61636b73a76e86a9b0023e115 GIT binary patch literal 1233697 zcmZU)1yodB-#$!tcMsjt9W!({D$US{C@qW#4BarKprnAHq<~0DH%dvVNP~pZF$}}Z zf4J}GdEa+^->h}k*(dhioPB%Iim~^I^%ZZe8lGG1XDwzNY`54C z+(e^vT70}wvDB^_X8t^HNfz#vl|K9^>@uT-^`7=hF!`ravc>%zTedc{YafESAHK-$ zvzuR6D8;Mgz$wM{qt7p}r)$!o4B0ys@F3c3}- 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