Fix LBFGS iteration counter always showing 0

Fixes #907 - Added iteration tracking to LBFGS callbacks so that
OptimizationState.iter properly increments during optimization.

Previously, the iteration counter was always 0 in callbacks because
the LBFGS solver wasn't tracking iterations. Now uses a Ref counter
that increments with each function evaluation.

Changes:
- Added iter_count = Ref(0) before _loss function definition
- Increment iter_count[] in _loss function
- Pass iter_count[] to OptimizationState constructor
- Applied fix to both constrained and unconstrained cases

🤖 Generated with [Claude Code](https://claude.ai/code)

Co-Authored-By: Claude <[email protected]>

Author: ChrisRackauckas

src/lbfgsb.jl

@@ -116,13 +116,15 @@ function SciMLBase.__solve(cache::OptimizationCache{
         cache.f.cons(cons_tmp, cache.u0)
         ρ = max(1e-6, min(10, 2 * (abs(cache.f(cache.u0, cache.p))) / norm(cons_tmp)))
 
+        iter_count = Ref(0)
         _loss = function (θ)
             x = cache.f(θ, cache.p)
+            iter_count[] += 1
             cons_tmp .= zero(eltype(θ))
             cache.f.cons(cons_tmp, θ)
             cons_tmp[eq_inds] .= cons_tmp[eq_inds] - cache.lcons[eq_inds]
             cons_tmp[ineq_inds] .= cons_tmp[ineq_inds] .- cache.ucons[ineq_inds]
-            opt_state = Optimization.OptimizationState(u = θ, objective = x[1])
+            opt_state = Optimization.OptimizationState(u = θ, objective = x[1], iter = iter_count[])
             if cache.callback(opt_state, x...)
                 error("Optimization halted by callback.")
             end
@@ -206,10 +208,12 @@ function SciMLBase.__solve(cache::OptimizationCache{
             cache, cache.opt, res[2], cache.f(res[2], cache.p)[1],
             stats = stats, retcode = opt_ret)
     else
+        iter_count = Ref(0)
         _loss = function (θ)
             x = cache.f(θ, cache.p)
+            iter_count[] += 1
 
-            opt_state = Optimization.OptimizationState(u = θ, objective = x[1])
+            opt_state = Optimization.OptimizationState(u = θ, objective = x[1], iter = iter_count[])
             if cache.callback(opt_state, x...)
                 error("Optimization halted by callback.")
             end