Hello all,

I am very new to Julia, and I intend to migrate from Matlab to Julia. I was very intrigued with automatic differentiation, and worked out a few problems by hand, to understand the concepts behind reverse mode and forward mode AD. But in all these, it seems that you need to have a function in hand (say f(x,y) = x^2+x*y).

I have the following issue though, I have an equation lc, which is a function of six variables: px, py, pz, phi, theta, psi. Here, the variables phi, px, py and pz are dependent on psi and theta, but I do not have their mathematical expressions. Is it possible to implement reverse AD to find the derivatives of lc, with respect to psi and theta? How to do so in enzyme? I profusely apologize for the lack of MWE.