I am using Ipopt.jl as my optimizer and would like to compute the function value and its gradient in the same Julia function (for performance reasons).
See this example: https://github.com/JuliaOpt/Ipopt.jl/blob/master/example/hs071.jl
Here the function value and gradient and hessian are all specified with a different Julia function. I however need the function value to compute my gradient, so I end up calculating it anyway in my gradient evaluation function (thereby computing it twice).
Is there a workaround such that one can combine the function and gradient evaluation in the same Julia call? In the same way as NLopt.jl does that?