Add prox_evals

Author: MohamedLaghdafHABIBOULLAH

src/LM_alg.jl

@@ -255,6 +255,7 @@ function SolverCore.solve!(
 
   local ξ1::T
   local ρk::T = zero(T)
+  local prox_evals::Int = 0
 
   residual!(nls, xk, Fk)
   jtprod_residual!(nls, xk, Fk, ∇fk)
@@ -273,6 +274,7 @@ function SolverCore.solve!(
   set_objective!(stats, fk + hk)
   set_solver_specific!(stats, :smooth_obj, fk)
   set_solver_specific!(stats, :nonsmooth_obj, hk)
+  set_solver_specific!(stats, :prox_evals, prox_evals + 1)
 
   φ1 = let Fk = Fk, ∇fk = ∇fk
     d -> dot(Fk, Fk) / 2 + dot(∇fk, d) # ∇fk = Jk^T Fk
@@ -329,6 +331,7 @@ function SolverCore.solve!(
       )
     end
 
+    prox_evals += solver.substats.iter
     s .= solver.substats.solution
 
     xkn .= xk .+ s
@@ -402,6 +405,7 @@ function SolverCore.solve!(
     set_solver_specific!(stats, :nonsmooth_obj, hk)
     set_iter!(stats, stats.iter + 1)
     set_time!(stats, time() - start_time)
+    set_solver_specific!(stats, :prox_evals, prox_evals + 1)
 
     ν = θ / (σmax^2 + σk) # ‖J'J + σₖ I‖ = ‖J‖² + σₖ
 

src/R2N.jl

@@ -291,6 +291,7 @@ function SolverCore.solve!(
 
   local ξ1::T
   local ρk::T = zero(T)
+  local prox_evals::Int = 0
 
   fk = obj(nlp, xk)
   grad!(nlp, xk, ∇fk)
@@ -317,6 +318,7 @@ function SolverCore.solve!(
   set_solver_specific!(stats, :nonsmooth_obj, hk)
   set_solver_specific!(stats, :sigma, σk)
   set_solver_specific!(stats, :sigma_cauchy, 1/ν₁)
+  set_solver_specific!(stats, :prox_evals, prox_evals + 1)
   m_monotone > 1 && (m_fh_hist[stats.iter % (m_monotone - 1) + 1] = fk + hk)
 
   φ1 = let ∇fk = ∇fk
@@ -386,6 +388,7 @@ function SolverCore.solve!(
       )
     end
 
+    prox_evals += solver.substats.iter
     s .= solver.substats.solution
 
     if norm(s) > β * norm(s1)
@@ -470,6 +473,7 @@ function SolverCore.solve!(
     set_solver_specific!(stats, :sigma_cauchy, 1/ν₁)
     set_iter!(stats, stats.iter + 1)
     set_time!(stats, time() - start_time)
+    set_solver_specific!(stats, :prox_evals, prox_evals + 1)
 
     @. mν∇fk = - ν₁ * ∇fk
     prox!(s1, ψ, mν∇fk, ν₁)

src/TR_alg.jl

@@ -266,6 +266,7 @@ function SolverCore.solve!(
 
   local ξ1::T
   local ρk = zero(T)
+  local prox_evals::Int = 0
 
   α = 1 / eps(T)
   β = 1 / eps(T)
@@ -291,6 +292,7 @@ function SolverCore.solve!(
   set_objective!(stats, fk + hk)
   set_solver_specific!(stats, :smooth_obj, fk)
   set_solver_specific!(stats, :nonsmooth_obj, hk)
+  set_solver_specific!(stats, :prox_evals, prox_evals + 1)
 
   # models
   φ1 = let ∇fk = ∇fk
@@ -369,7 +371,8 @@ function SolverCore.solve!(
         )
       end
     end
-
+    
+    prox_evals += solver.substats.iter
     s .= solver.substats.solution
 
     xkn .= xk .+ s
@@ -454,6 +457,7 @@ function SolverCore.solve!(
     set_solver_specific!(stats, :nonsmooth_obj, hk)
     set_iter!(stats, stats.iter + 1)
     set_time!(stats, time() - start_time)
+    set_solver_specific!(stats, :prox_evals, prox_evals + 1)
 
     ν₁ = α * Δk / (1 + λmax * (α * Δk + 1))
     @. mν∇fk = -ν₁ * ∇fk

src/utils.jl

@@ -114,5 +114,6 @@ function RegularizedExecutionStats(reg_nlp::AbstractRegularizedNLPModel{T, V}) w
   set_solver_specific!(stats, :sigma, T(Inf))
   set_solver_specific!(stats, :sigma_cauchy, T(Inf))
   set_solver_specific!(stats, :radius, T(Inf))
+  set_solver_specific!(stats, :prox_evals, T(Inf))
   return stats
 end