Worked on enhancing module introspection capabilities in the google/flax repository by developing a new API for traversing module structures. Built the iter_module_children function, which allows iteration over module children within a graph node, streamlining the process of inspecting and analyzing nested modules in Flax. This addition supports improved debugging and model analysis workflows, making it easier for developers to navigate complex deep learning architectures. The work demonstrated proficiency in Python, deep learning, and library development, with careful attention to version-controlled API design. The contribution focused on expanding tooling for machine learning practitioners working with modular neural network components.