docker-compose.yml

# export DUID="$(id -u)"; export DGID="$(id -g)"
# docker compose run --service-ports --rm base
version: "3.9"
name: ezdev

x-data: &data
# Modify the paths before the ':' in next 4 lines to match your system
    volumes:
      - ${HOME}/exp:/exp
      - /work:/work # only needed if your exp, unity-envs or navsim folders are symlinked from here

x-code: &code
    volumes:
      - ${PWD}:/workspace

x-exportx: &exportx
    volumes:
      - /tmp/.X11-unix:/tmp/.X11-unix:rw
      - ${XAUTHORITY}:${XAUTHORITY}
      - $XDG_RUNTIME_DIR:$XDG_RUNTIME_DIR
      - /usr/share/vulkan/icd.d:/usr/share/vulkan/icd.d
    environment:
      - DISPLAY
      - NVIDIA_VISIBLE_DEVICES=all
      - NVIDIA_DRIVER_CAPABILITIES=all
      - XAUTHORITY
      - XDG_RUNTIME_DIR

x-deploy-nvidia: &deploy-nvidia
    deploy:
      resources:
        reservations:
          devices:
            - driver: nvidia
              count: all
              #device_ids: ['0', '3']
              capabilities: [gpu]

x-debian-image: &debian-image
    debian:11.6-slim

x-img: &img
    ${IMAGE:-debian:11.6-slim}

services:

# DUID=`id -u` DGID=`id -g` docker compose build fixid
  fixid:
    image: *img
    build: 
      context: .
      dockerfile: dockerfiles/Dockerfile-fixid
      args: 
        image: *img
        duid: ${DUID:-1000}
        dgid: ${DGID:-1000}

  runtime-base:
    <<: [*data]
    image: *debian-image
    working_dir: /workspace
  
  runtime-base-nvidia:
    extends:
      service: runtime-base
    <<: [*deploy-nvidia]
    command: bash -c "nvidia-smi"

  runtime-base-nvidia-x:
    extends:
      service: runtime-base-nvidia
    <<: [*exportx]
    command: bash -c "nvidia-smi"

  dev-base:
    extends:
      service: runtime-base
    <<: [*code]
  
  dev-base-nvidia:
    extends:
      service: runtime-base-nvidia
    <<: [*code]

  dev-base-nvidia-x:
    extends:
      service: runtime-base-nvidia-x
    <<: [*code]


# Three base
# base - nvidia-smi and glx works, vulkan doesnt work in this
# conda : base with conda-mamba
# ai-conda : ai with conda-mamba 

  base-ubuntu2004:
    image: ghcr.io/armando-fandango/ez/ez:0.4-base-ubuntu2004
    command: bash -c "nvidia-smi; vulkaninfo; glxinfo"
    build: 
      context: .
      dockerfile: dockerfiles/Dockerfile-base-ubuntu2004
      args:
        - from=ubuntu:20.04

  base:
    extends:
      service: dev-base
    image: ghcr.io/armando-fandango/ezdev/ezdev:0.5-base-bullseye-slim
    command: bash -c "lsb_release -a 2> /dev/null ; cmake --version | head -1; echo Node `node --version`; echo yarn `yarn --version`"
    build: 
      context: .
      dockerfile: dockerfiles/Dockerfile-base-ubuntu2004
      args:
        from: *debian-image

  base-x:
    extends:
      service: dev-base-nvidia-x
    image: ghcr.io/armando-fandango/ezdev/ezdev:0.5-base-bullseye-slim
    command: bash -c "echo =========================; \
             echo 'NVIDIA Info:';nvidia-smi -L; nvidia-smi -B; echo =========================; \
             echo 'Vulkan Info:';vulkaninfo 1>/dev/null; vulkaninfo 2>/dev/null | tail +5 | head -5 ; \
             echo 'OpenGL Info:';glxinfo | head -5; echo ==============================; \
             echo 'Run vkcube, vkcubecc, glxgears, glxheads to check out cool graphics test'"
             
  conda:
    extends:
      service: dev-base
    image: ghcr.io/armando-fandango/ezdev/ezdev:0.5-conda-bullseye-slim
    command: bash -c "which python; python -V;
             which conda; conda -V; which mamba; mamba -V"
    build: 
      context: .
      dockerfile: dockerfiles/Dockerfile-conda-ubuntu2004
      args:
        from: ghcr.io/armando-fandango/ezdev/ezdev:0.5-base-bullseye-slim
    ports:
      - "8888"

  iot:
    extends:
      service: runtime-base
    image: ghcr.io/armando-fandango/ezdev/ezdev:0.6-iot-bullseye-slim
    command: bash -c "ls"
    build: 
      context: .
      dockerfile: dockerfiles/Dockerfile-iot-ubuntu2004
      args:
        from: ghcr.io/armando-fandango/ezdev/ezdev:0.5-base-bullseye-slim

  ai:
    extends:
      service: dev-base-nvidia
    image: ghcr.io/armando-fandango/ezdev/ezdev:0.6-ai-conda-bullseye-slim
    command: bash -c "nvidia-smi; which python; python -V;
             which conda; conda -V; which mamba; mamba -V; echo 'torch.cuda:';
             python -c 'import torch; print(torch.cuda.is_available()); print(torch.version.cuda)';
             while sleep 1000; do :; done"
    build: 
      context: .
      dockerfile: dockerfiles/Dockerfile-ai-ubuntu2004
      args:
        from: ghcr.io/armando-fandango/ezdev/ezdev:0.5-conda-bullseye-slim
    ports:
      - "8888"