During February 2026, Jie Yang focused on stabilizing infinity-norm computation for symbolic tensors with dynamic shapes in the pytorch/pytorch repository. Jie addressed a regression in _foreach_norm by replacing numel() with sym_numel() and integrating TORCH_SYM_CHECK to validate symbolic sizes during tracing. This approach ensured correct infinity-norm results for empty tensors and maintained compatibility for both symbolic and concrete tensors across tracing scenarios. Jie’s work involved C++ and CUDA, leveraging expertise in numerical computing and tensor operations. The solution included comprehensive test coverage and followed a complete development workflow, from code fix and validation to review and mainline integration.