September 2025 monthly summary for pytorch/executorch: Focused on restoring and stabilizing the QNN backend integration to ensure robustness of Qualcomm Neural Network (QNN) acceleration support in executorch. Reintroduced removed components and added comprehensive build/test scripts for the QNN wheel, enabling reliable packaging and validation. This work improved packaging reliability, CI feedback, and readiness for production deployments of QNN-enabled workflows.

May 2025 monthly summary for pytorch/ao focused on enhancing quantization coverage in convolution operations. Delivered a targeted feature that expands recognition of convolution types during quantization by refining the _is_conv_node function and aligning tests accordingly. The change improves quantization accuracy and performance for a broader set of conv ops in quantized models.