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- # 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-x64-2.317.0.tar.gz && \
- curl -o $FILENAME -L https://github.com/actions/runner/releases/download/v2.317.0/$FILENAME && \
- tar xzf $FILENAME && \
- rm $FILENAME
- # Install runner dependencies
- ENV RUNNER_ALLOW_RUNASROOT=1
- ENV DEBIAN_FRONTEND=noninteractive
- RUN pip install --no-cache-dir pytest-cov
- 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
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