Worked on the pytorch/pytorch repository to enhance the reliability of model export workflows, focusing on complex scenarios involving shared parameters and nested dictionary inputs. Addressed critical bugs by preserving original parameter names during strict mode exports and updating parameter mapping logic to prevent overwriting, thereby improving API stability for production deployments. Implemented targeted unit tests to verify naming integrity and ensure robust parameter identity. Additionally, resolved export failures caused by unordered dictionary keys within nested argument tuples, allowing for more flexible input specifications. Leveraged deep learning, machine learning, and Python expertise to deliver well-tested, production-ready improvements to PyTorch’s export functionality.