Alan Du extended PyTorch’s NestedTensor functionality by implementing log_softmax support in the pytorch/pytorch repository. He focused on enabling log-probability computations directly on NestedTensor structures, removing the need to convert them to dense tensors. This work required a deep understanding of tensor operations and machine learning workflows, as well as proficiency in Python programming. By addressing the challenge of supporting log_softmax for non-standard tensor layouts, Alan laid the groundwork for broader tensor-layout compatibility in machine learning applications. The feature delivered targeted improvements for users working with complex data structures, reflecting a focused and technically sound engineering contribution.