Developed an attention backend auto-selection warning feature for the hao-ai-lab/FastVideo repository, focusing on backend development and logging using Python. The implementation detects when a layer requests an unsupported attention backend, logs a warning, and defaults to automatic backend selection to maintain runtime stability. This approach improves observability and debugging by making backend selection behavior transparent to users, reducing confusion and potential support issues related to misconfiguration. The change was isolated to a single feature, aligning with the project’s diagnostic-centric and safe-default philosophy for video processing workloads, and demonstrates a methodical approach to enhancing reliability without introducing unnecessary complexity.