Implement BenchmarkRunner

src/MIPLearn.jl

@@ -17,5 +17,20 @@ include("instance/file.jl")
 include("solvers/jump.jl")
 include("solvers/learning.jl")
 include("solvers/macros.jl")
+include("utils/benchmark.jl")
+
+DynamicLazyConstraintsComponent = miplearn.DynamicLazyConstraintsComponent
+UserCutsComponent = miplearn.UserCutsComponent
+ObjectiveValueComponent = miplearn.ObjectiveValueComponent
+PrimalSolutionComponent = miplearn.PrimalSolutionComponent
+StaticLazyConstraintsComponent = miplearn.StaticLazyConstraintsComponent
+MinPrecisionThreshold = miplearn.MinPrecisionThreshold
+
+export DynamicLazyConstraintsComponent,
+       UserCutsComponent,
+       ObjectiveValueComponent,
+       PrimalSolutionComponent,
+       StaticLazyConstraintsComponent,
+       MinPrecisionThreshold
 
 end # module

src/solvers/learning.jl

@@ -11,10 +11,21 @@ struct LearningSolver
 end
 
 
-function LearningSolver(optimizer_factory)::LearningSolver
-    py = miplearn.LearningSolver(solver=JuMPSolver(optimizer_factory))
+function LearningSolver(
+    optimizer_factory;
+    components = nothing,
+    mode::AbstractString = "exact",
+    simulate_perfect::Bool = false,
+    solve_lp::Bool = true,
+)::LearningSolver
     return LearningSolver(
-        py,
+        miplearn.LearningSolver(
+            solver=JuMPSolver(optimizer_factory),
+            mode=mode,
+            solve_lp=solve_lp,
+            simulate_perfect=simulate_perfect,
+            components=components,
+        ),
         optimizer_factory,
     )
 end
@@ -36,7 +47,6 @@ end
 
 function parallel_solve!(solver::LearningSolver, instances::Vector{FileInstance})
     filenames = [instance.filename for instance in instances]
-    optimizer_factory = solver.optimizer_factory
     solver_filename = tempname()
     save(solver_filename, solver)
     @sync @distributed for filename in filenames

src/utils/benchmark.jl

@@ -0,0 +1,68 @@
+#  MIPLearn: Extensible Framework for Learning-Enhanced Mixed-Integer Optimization
+#  Copyright (C) 2020-2021, UChicago Argonne, LLC. All rights reserved.
+#  Released under the modified BSD license. See COPYING.md for more details.
+
+using CSV
+using DataFrames
+
+
+mutable struct BenchmarkRunner
+    solvers::Dict
+    results::Union{Nothing,DataFrame}
+end
+
+
+function BenchmarkRunner(; solvers::Dict)
+    return BenchmarkRunner(
+        solvers,
+        nothing,  # results
+    )
+end
+
+
+function parallel_solve!(
+    runner::BenchmarkRunner,
+    instances::Vector{FileInstance};
+    n_trials::Int = 3,
+)::Nothing
+    for (solver_name, solver) in runner.solvers
+        for i in 1:n_trials
+            for instance in instances
+                stats = solve!(solver, instance)
+                stats["Solver"] = solver_name
+                stats = Dict(k => isnothing(v) ? missing : v for (k, v) in stats)
+                if runner.results === nothing
+                    runner.results = DataFrame(stats)
+                else
+                    push!(runner.results, stats, cols=:union)
+                end
+            end
+        end
+    end
+end
+
+
+function fit!(
+    runner::BenchmarkRunner,
+    instances::Vector{FileInstance}
+)::Nothing
+    for (solver_name, solver) in runner.solvers
+        fit!(solver, instances)
+    end
+end
+
+
+function write_csv!(
+    runner::BenchmarkRunner,
+    filename::AbstractString,
+)::Nothing
+    @info "Writing: $filename"
+    CSV.write(filename, runner.results)
+    return
+end
+
+
+export BenchmarkRunner,
+       parallel_solve!,
+       fit!,
+       write_csv!