Optimizer interface and sample implementation (#19)

Reviewed-on: Rubydragon/MetagraphOptimization.jl#19
Co-authored-by: Anton Reinhard <anton.reinhard@proton.me>
Co-committed-by: Anton Reinhard <anton.reinhard@proton.me>

test/runtests.jl

@@ -11,6 +11,7 @@ using Test
     include("node_reduction.jl")
     include("unit_tests_graph.jl")
     include("unit_tests_execution.jl")
+    include("unit_tests_optimization.jl")
 
     include("known_graphs.jl")
 end

test/unit_tests_estimator.jl

@@ -38,9 +38,6 @@ function test_op_specific(estimator, graph, ns::NodeSplit)
 end
 
 function test_op(estimator, graph, op)
-    #=
-    See issue #16
-
     estimate_before = graph_cost(estimator, graph)
 
     estimate = operation_effect(estimator, graph, op)
@@ -52,7 +49,6 @@ function test_op(estimator, graph, op)
     @test isapprox((estimate_before + estimate).data, estimate_after_apply.data)
     @test isapprox((estimate_before + estimate).computeEffort, estimate_after_apply.computeEffort)
     @test isapprox((estimate_before + estimate).computeIntensity, estimate_after_apply.computeIntensity)
-    =#
 
     test_op_specific(estimator, graph, op)
     return nothing
@@ -81,9 +77,6 @@ end
             nrs = copy(ops.nodeReductions)
             nss = copy(ops.nodeSplits)
 
-            println(
-                "Testing $(length(ops.nodeFusions))xNF, $(length(ops.nodeReductions))xNR, $(length(ops.nodeSplits))xNS",
-            )
             for nf in nfs
                 test_op(estimator, graph, nf)
             end

test/unit_tests_execution.jl

@@ -3,10 +3,10 @@ import MetagraphOptimization.interaction_result
 
 using QEDbase
 using AccurateArithmetic
-
-include("../examples/profiling_utilities.jl")
+using Random
 
 const RTOL = sqrt(eps(Float64))
+RNG = Random.default_rng()
 
 function check_particle_reverse_moment(p1::SFourMomentum, p2::SFourMomentum)
     @test isapprox(abs(p1.E), abs(p2.E))
@@ -83,7 +83,7 @@ end
     @testset "AB->AB after random walk" begin
         for i in 1:200
             graph = parse_dag(joinpath(@__DIR__, "..", "input", "AB->AB.txt"), ABCModel())
-            random_walk!(graph, 50)
+            optimize!(RandomWalkOptimizer(RNG), graph, 50)
 
             @test is_valid(graph)
 
@@ -115,7 +115,7 @@ end
     @testset "AB->ABBB after random walk" begin
         for i in 1:50
             graph = parse_dag(joinpath(@__DIR__, "..", "input", "AB->ABBB.txt"), ABCModel())
-            random_walk!(graph, 100)
+            optimize!(RandomWalkOptimizer(RNG), graph, 100)
             @test is_valid(graph)
 
             @test isapprox(execute(graph, process_2_4, machine, particles_2_4), expected_result; rtol = RTOL)

test/unit_tests_graph.jl

@@ -135,6 +135,12 @@ import MetagraphOptimization.partners
     @test length(operations) == (nodeFusions = 10, nodeReductions = 0, nodeSplits = 0)
     @test length(graph.dirtyNodes) == 0
 
+    i = 0
+    for op in operations
+        i += 1
+    end
+    @test i == 10
+
     @test operations == get_operations(graph)
     nf = first(operations.nodeFusions)
 

test/unit_tests_optimization.jl

@@ -0,0 +1,42 @@
+using Random
+
+RNG = Random.default_rng()
+
+@testset "Unit Tests Optimization" begin
+    graph = parse_dag(joinpath(@__DIR__, "..", "input", "AB->ABBB.txt"), ABCModel())
+
+    # create the optimizers
+    FIXPOINT_OPTIMIZERS = [GreedyOptimizer(GlobalMetricEstimator()), ReductionOptimizer()]
+    NO_FIXPOINT_OPTIMIZERS = [RandomWalkOptimizer(RNG)]
+
+    @testset "Optimizer $optimizer" for optimizer in vcat(NO_FIXPOINT_OPTIMIZERS, FIXPOINT_OPTIMIZERS)
+        @test operation_stack_length(graph) == 0
+        @test optimize_step!(optimizer, graph)
+
+        @test !fixpoint_reached(optimizer, graph)
+        @test operation_stack_length(graph) == 1
+
+        @test optimize!(optimizer, graph, 10)
+
+        @test !fixpoint_reached(optimizer, graph)
+
+        reset_graph!(graph)
+    end
+
+    @testset "Fixpoint optimizer $optimizer" for optimizer in FIXPOINT_OPTIMIZERS
+        @test operation_stack_length(graph) == 0
+
+        optimize_to_fixpoint!(optimizer, graph)
+
+        @test fixpoint_reached(optimizer, graph)
+        @test !optimize_step!(optimizer, graph)
+        @test !optimize!(optimizer, graph, 10)
+
+        reset_graph!(graph)
+    end
+
+    @testset "No fixpoint optimizer $optimizer" for optimizer in NO_FIXPOINT_OPTIMIZERS
+        @test_throws MethodError optimize_to_fixpoint!(optimizer, graph)
+    end
+end
+println("Optimization Unit Tests Complete!")

test/unit_tests_properties.jl

@@ -5,18 +5,10 @@
     @test prop.data == 0.0
     @test prop.computeEffort == 0.0
     @test prop.computeIntensity == 0.0
-    @test prop.cost == 0.0
     @test prop.noNodes == 0.0
     @test prop.noEdges == 0.0
 
-    prop2 = (
-        data = 5.0,
-        computeEffort = 6.0,
-        computeIntensity = 6.0 / 5.0,
-        cost = 0.0,
-        noNodes = 2,
-        noEdges = 3,
-    )::GraphProperties
+    prop2 = (data = 5.0, computeEffort = 6.0, computeIntensity = 6.0 / 5.0, noNodes = 2, noEdges = 3)::GraphProperties
 
     @test prop + prop2 == prop2
     @test prop2 - prop == prop2
@@ -25,27 +17,18 @@
     @test negProp.data == -5.0
     @test negProp.computeEffort == -6.0
     @test negProp.computeIntensity == 6.0 / 5.0
-    @test negProp.cost == 0.0
     @test negProp.noNodes == -2
     @test negProp.noEdges == -3
 
     @test negProp + prop2 == GraphProperties()
 
-    prop3 = (
-        data = 7.0,
-        computeEffort = 3.0,
-        computeIntensity = 7.0 / 3.0,
-        cost = 0.0,
-        noNodes = -3,
-        noEdges = 2,
-    )::GraphProperties
+    prop3 = (data = 7.0, computeEffort = 3.0, computeIntensity = 7.0 / 3.0, noNodes = -3, noEdges = 2)::GraphProperties
 
     propSum = prop2 + prop3
 
     @test propSum.data == 12.0
     @test propSum.computeEffort == 9.0
     @test propSum.computeIntensity == 9.0 / 12.0
-    @test propSum.cost == 0.0
     @test propSum.noNodes == -1
     @test propSum.noEdges == 5
 end