During February 2025, Zhonghanjun focused on improving the stability and resource efficiency of image processing workflows in the modelscope/data-juicer repository. He addressed a memory leak in the ImageNSFWFilter by wrapping model inference with torch.no_grad(), a technique in PyTorch that prevents unnecessary gradient tracking and reduces memory usage during inference. This change enhanced the determinism and reliability of memory consumption, allowing batch jobs to run longer without spikes or failures. Zhonghanjun validated the fix to ensure no impact on user-facing features and prepared the update for production, demonstrating strong skills in deep learning, memory management, and performance optimization using Python.