Modeling Optimization Problems

using ModelingToolkit, Optimization, OptimizationOptimJL

@variables x y
@parameters a b
loss = (a - x)^2 + b * (y - x^2)^2
@named sys = OptimizationSystem(loss,[x,y],[a,b])

u0 = [
    x=>1.0
    y=>2.0
]
p = [
    a => 6.0
    b => 7.0
]

prob = OptimizationProblem(sys,u0,p,grad=true,hess=true)
solve(prob,Newton())

Needs more text but it's super cool and auto-parallelizes and sparsifies too. Plus you can hierarchically nest systems to have it generate huge optimization problems.