docker-compose.yml

version: "3.9"
services:
  terminal-ide-18-py3.8-cuda10.2-service:
    image: terminal-ide:ubuntu18.04-py3.8-cuda10.2
    build:
      context: .
      dockerfile: Dockerfile
      args:
        - baseimage=nvidia/cuda:10.2-devel-ubuntu18.04 # baseimage  
        - pythonversion=python3.8
        - uid=1001  # uid of the host
        - user=${USER}
    ports:
      - 8899:8899  # jupyterlab
    volumes:
      - /tmp/.X11-unix:/tmp/.X11-unix  # sync host clipboard
    environment:
      - DISPLAY  # sync host clipboard
      - TZ=Asia/Singapore  # set the desired time zone
    hostname: laptop-docker
    container_name: terminal-ide-18-py3.8-cuda10.2-container
    stdin_open: true
    tty: true
    runtime: "nvidia"
    network_mode: "bridge"
  terminal-ide-18-py3.8-cuda11.1-service:
    image: terminal-ide:ubuntu18.04-py3.8-cuda11.1
    build:
      context: .
      dockerfile: Dockerfile
      args:
        - baseimage=nvidia/cuda:11.1-devel-ubuntu18.04 # baseimage  
        - pythonversion=python3.8
        - uid=1001  # uid of the host
        - user=${USER}
      network: host
    ports:
      - 8899:8899  # jupyterlab
    volumes:
      - /tmp/.X11-unix:/tmp/.X11-unix  # sync host clipboard
    environment:
      - DISPLAY  # sync host clipboard
      - TZ=Asia/Kolkata  # set the desired time zone
    hostname: laptop-docker
    container_name: terminal-ide-18-py3.8-cuda11.1-container
    stdin_open: true
    tty: true
    runtime: "nvidia"
    network_mode: "bridge"
  terminal-ide-18-py3.8-cuda11.1-kf-service:
    image: terminal-ide:ubuntu18.04-py3.8-cuda11.1-kf
    build:
      context: .
      dockerfile: DockerfileKF
      args:
        - baseimage=nvidia/cuda:11.1.1-devel-ubuntu18.04 # baseimage  
        - pythonversion=python3.8
        - uid=1000  # uid of the host
        - user=jovyan
      network: host