microduck_rl_tutorial/docker-compose.yml at main · rocPAI-Forge/microduck_rl_tutorial · GitHub

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# One lab image for Instinct and Radeon. The base image includes
# gfx90a, gfx942, gfx1100, gfx1201, and gfx1151; no GPU-family flag.
name: microduck-rl-tutorial

services:
  lab:
    container_name: microduck-rl-tutorial
    build:
      context: .
      dockerfile: Dockerfile
      args:
        BASE_IMAGE: ${BASE_IMAGE:-rocm/pytorch:rocm7.2.4_ubuntu24.04_py3.12_pytorch_release_2.10.0}
        ROCM_TORCH_WHEEL: ${ROCM_TORCH_WHEEL:-}
        ROCM_TRITON_WHEEL: ${ROCM_TRITON_WHEEL:-}
        MICRODUCK_REPO: https://github.com/rocPAI-Forge/microduck_rl_unilab.git
        MICRODUCK_REF: ${MICRODUCK_REF:-20fb528fa6c4a9559155b33e5304568668c7b7e2}
        MICRODUCK_EXPECTED_SHA: ${MICRODUCK_EXPECTED_SHA:-20fb528fa6c4a9559155b33e5304568668c7b7e2}
    image: ${LOCAL_IMAGE:-microduck-rl-tutorial:rocm724-py312}
    devices:
      - /dev/kfd
      - /dev/dri
    group_add:
      - video
    ipc: host
    shm_size: 8gb
    ports:
      - "${LAB_HOST_PORT:-8888}:8888"
      - "${TELEOP_HOST_PORT:-16080}:6080"
    volumes:
      - ./runs:/workspace/runs
      - ./notebooks:/workspace/microduck_rl_tutorial/notebooks
      - ./scripts:/workspace/microduck_rl_tutorial/scripts
      - ./examples:/workspace/microduck_rl_tutorial/examples
    environment:
      HIP_VISIBLE_DEVICES: ${HIP_VISIBLE_DEVICES:-0}
      JUPYTER_PORT: 8888
      LAB_QUICK_MODE: ${LAB_QUICK_MODE:-0}
      DISPLAY: ":1"
      TELEOP_AUTOSTART: ${TELEOP_AUTOSTART:-off}
      TELEOP_PUBLIC_PORT: ${TELEOP_PUBLIC_PORT:-${TELEOP_HOST_PORT:-16080}}
      TELEOP_VNC_PASSWORD: ${TELEOP_VNC_PASSWORD:-microduck}
    security_opt:
      - seccomp:unconfined
    cap_add:
      - SYS_PTRACE
    command: ["jupyter"]