Description
Computes derivatives from C++ code through Clad's automatic differentiation support. It is useful for developers and researchers working on optimization, machine learning, simulation, or numerical methods.
Generated derivatives should be tested against known cases. Numerical code can fail silently when assumptions about types, precision, or control flow are wrong.