Benchmark

https://juliasmoothoptimizers.github.io/SolverBenchmark.jl/latest/tutorial/ In this tutorial we illustrate the main uses of SolverBenchmark.

The Julia file corresponding to this tutorial can be found here.

using LinearAlgebra, NLPModels, Stopping

include("backls.jl")
include("uncons.jl")

using DataFrames, Printf, SolverBenchmark

CUTEst is a collection of test problems

using CUTEst

problems_unconstrained = CUTEst.select(contype="unc")
n = length(problems_unconstrained) #240

printstyled("Benchmark solvers: \n", color = :green)

#Names of 3 solvers:
names = [:armijo, :wolfe, :armijo_wolfe]
p1 = PrmUn(); p2 = PrmUn(ls_func = wolfe); p3 = PrmUn(ls_func = armijo_wolfe)
paramDict = Dict(:armijo => p1, :wolfe => p2, :armijo_wolfe => p3)
#Initialization of the DataFrame for n problems.
stats = Dict(name => DataFrame(:id => 1:n,
         :name => [@sprintf("prob%s", problems_unconstrained[i]) for i = 1:n],
         :nvar => zeros(Int64, n),
         :status => [:Unknown for i = 1:n],
         :f => NaN*ones(n),
         :t => NaN*ones(n),
         :iter => zeros(Int64, n),
         :eval_f => zeros(Int64, n),
         :eval_g => zeros(Int64, n),
         :eval_H => zeros(Int64, n),
         :score => NaN*ones(n)) for name in names)

for i=1:n
  nlp_cutest = CUTEst.CUTEstModel(problems_unconstrained[i])
  @show i, problems_unconstrained[i], nlp_cutest.meta.nvar
  #update the stopping with the new problem
  stop_nlp = NLPStopping(nlp_cutest,
                         unconstrained_check,
                         NLPAtX(nlp_cutest.meta.x0),
                         max_iter = 20)

  for name in names

    #solve the problem
    global_newton(stop_nlp, paramDict[name])

    #update the stats from the Stopping
    stats[name].nvar[i] = nlp_cutest.meta.nvar
    stats[name].status[i] = status(stop_nlp)
    stats[name].f[i] = stop_nlp.current_state.fx == nothing ? NaN : stop_nlp.current_state.fx
    stats[name].t[i] = stop_nlp.current_state.current_time == nothing ? NaN : stop_nlp.current_state.current_time - stop_nlp.meta.start_time
    stats[name].iter[i] = stop_nlp.meta.nb_of_stop
    stats[name].score[i] = unconstrained_check(nlp_cutest, stop_nlp.current_state)
    stats[name].eval_f[i] = getfield(stop_nlp.current_state.evals, :neval_obj)
    stats[name].eval_g[i] = getfield(stop_nlp.current_state.evals, :neval_grad)
    stats[name].eval_H[i] = getfield(stop_nlp.current_state.evals, :neval_hess)

    #reinitialize the Stopping and the nlp
    reinit!(stop_nlp, rstate = true, x = nlp_cutest.meta.x0)
    reset!(stop_nlp.pb)
  end

  #finalize nlp
  finalize(nlp_cutest)
end #end of main loop

for name in names
@show stats[name]
end