Worked on the google/flax repository to address a bug in the Flax library’s Sequential module, ensuring that empty Sequential modules now act as identity functions. Using Python and leveraging deep learning and machine learning expertise, implemented changes in flax/nnx/helpers.py so that empty Sequential modules consistently return their inputs, regardless of whether they receive single values, multiple positional arguments, keyword arguments, or no arguments. Developed comprehensive tests in tests/nnx/helpers_test.py to validate this identity behavior across diverse input scenarios. This work improved the robustness of the API and reduced the risk of regressions in workflows dependent on identity-preserving modules.