A tool that automatically reannotates Java projects using graph learning models. Undo split: cat nullgtn-update.tar.part-* > nullgtn-update.tar To run: sudo docker run -d -p 2222:22 --gpus all nullgtn-update:latestORsudo docker start nullgtn-update ssh root@127.0.0.1 -p 2222Password: NullGTNv.4 Requirements: Host OS: Tested on Ubuntu 24.04. Use other Linux at your own risk.NVIDIA GPU required with at least 16 GB memory. Make sure drivers are installed and update on both host and guest: # 1. Update package listssudo apt-get update # 2. List available NVIDIA drivers for your GPUsudo ubuntu-drivers list --gpgpu # 3. Automatically install the best server/compute driversudo ubuntu-drivers install --gpgpu # 4. Reboot to load the new driversudo reboot On host, make sure the --gpus flag is available for Docker: # A. Add NVIDIA.s GPG key and repositorycurl -fsSL https://nvidia.github.io/libnvidia-container/gpgkey \ | sudo gpg --dearmor -o /usr/share/keyrings/nvidia-container-toolkit-keyring.gpg \ && curl -s -L https://nvidia.github.io/libnvidia-container/stable/deb/nvidia-container-toolkit.list \ | sed 's#deb https://#deb [signed-by=/usr/share/keyrings/nvidia-container-toolkit-keyring.gpg] https://#g' \ | sudo tee /etc/apt/sources.list.d/nvidia-container-toolkit.list # B. Install the toolkitsudo apt-get updatesudo apt-get install -y nvidia-container-toolkit # C. Tell Docker to use it and restartsudo nvidia-ctk runtime configure --runtime=dockersudo systemctl restart docker Directories: precision_recall: Show precision. Use the conda environment: conda activate naenvwarnings: Generate warning logs. Use the conda environment: conda activate nullgtn See README.md in each subdirectory for directions.