Dockerfile-runner

# Ultralytics YOLO 🚀, AGPL-3.0 license
# Builds GitHub actions CI runner image for deployment to DockerHub https://hub.docker.com/r/ultralytics/ultralytics
# Image is CUDA-optimized for YOLOv8 single/multi-GPU training and inference tests

# Start FROM Ultralytics GPU image
FROM ultralytics/ultralytics:latest

# Set the working directory
WORKDIR /actions-runner

# Download and unpack the latest runner from https://github.com/actions/runner
RUN FILENAME=actions-runner-linux-x64-2.309.0.tar.gz && \
    curl -o $FILENAME -L https://github.com/actions/runner/releases/download/v2.309.0/$FILENAME && \
    tar xzf $FILENAME && \
    rm $FILENAME

# Install runner dependencies
ENV RUNNER_ALLOW_RUNASROOT=1
ENV DEBIAN_FRONTEND=noninteractive
RUN ./bin/installdependencies.sh && \
    apt-get -y install libicu-dev

# Inline ENTRYPOINT command to configure and start runner with default TOKEN and NAME
ENTRYPOINT sh -c './config.sh --url https://github.com/ultralytics/ultralytics \
                              --token ${GITHUB_RUNNER_TOKEN:-TOKEN} \
                              --name ${GITHUB_RUNNER_NAME:-NAME} \
                              --labels gpu-latest \
                              --replace && \
                  ./run.sh'


# Usage Examples -------------------------------------------------------------------------------------------------------

# Build and Push
# t=ultralytics/ultralytics:latest-runner && sudo docker build -f docker/Dockerfile-runner -t $t . && sudo docker push $t

# Pull and Run in detached mode with access to GPUs 0 and 1
# t=ultralytics/ultralytics:latest-runner && sudo docker run -d -e GITHUB_RUNNER_TOKEN=TOKEN -e GITHUB_RUNNER_NAME=NAME --ipc=host --gpus '"device=0,1"' $t