Limits of Keras load_weights skip_mismatch for rollback after a schema change
Goal I want to reuse trained weights from a previous model version after changing the architecture (for example, adding a Dense layer), and I need the process to be rollback-safe: the original layers must keep their trained values, and it must be obvious which parts of the new model were left untouched. Constraints and uncertainty Keras documents model.load_
keras