Cost Estimation interface (#14)
See issue #13 Reviewed-on: Rubydragon/MetagraphOptimization.jl#14 Co-authored-by: Anton Reinhard <anton.reinhard@proton.me> Co-committed-by: Anton Reinhard <anton.reinhard@proton.me>
This commit is contained in:
Anton Reinhard
@ -1,4 +1,5 @@
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[deps]
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AccurateArithmetic = "22286c92-06ac-501d-9306-4abd417d9753"
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QEDbase = "10e22c08-3ccb-4172-bfcf-7d7aa3d04d93"
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Random = "9a3f8284-a2c9-5f02-9a11-845980a1fd5c"
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Test = "8dfed614-e22c-5e08-85e1-65c5234f0b40"
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@ -6,6 +6,8 @@ using Test
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include("unit_tests_tasks.jl")
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include("unit_tests_nodes.jl")
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include("unit_tests_properties.jl")
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include("unit_tests_estimator.jl")
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include("unit_tests_abcmodel.jl")
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include("node_reduction.jl")
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include("unit_tests_graph.jl")
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include("unit_tests_execution.jl")
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26
test/unit_tests_abcmodel.jl
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26
test/unit_tests_abcmodel.jl
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@ -0,0 +1,26 @@
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using MetagraphOptimization
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using QEDbase
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import MetagraphOptimization.interaction_result
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def_momentum = SFourMomentum(1.0, 0.0, 0.0, 0.0)
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testparticleTypes = [ParticleA, ParticleB, ParticleC]
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testparticles = [ParticleA(def_momentum), ParticleB(def_momentum), ParticleC(def_momentum)]
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@testset "Unit Tests ABC-Model" begin
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@testset "Interaction Result" begin
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for p1 in testparticleTypes, p2 in testparticleTypes
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if (p1 == p2)
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@test_throws AssertionError interaction_result(p1, p2)
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else
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@test interaction_result(p1, p2) == setdiff(testparticleTypes, [p1, p2])[1]
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end
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end
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end
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@testset "Vertex" begin
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@test isapprox(MetagraphOptimization.vertex(), 1 / 137.0)
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end
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end
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println("ABC-Model Unit Tests Complete!")
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99
test/unit_tests_estimator.jl
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99
test/unit_tests_estimator.jl
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@ -0,0 +1,99 @@
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function test_op_specific(estimator, graph, nf::NodeFusion)
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estimate = operation_effect(estimator, graph, nf)
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data_reduce = data(nf.input[2].task)
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@test isapprox(estimate.data, -data_reduce)
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@test isapprox(estimate.computeEffort, 0; atol = eps(Float64))
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@test isapprox(estimate.computeIntensity, 0; atol = eps(Float64))
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return nothing
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end
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function test_op_specific(estimator, graph, nr::NodeReduction)
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estimate = operation_effect(estimator, graph, nr)
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data_reduce = data(nr.input[1].task) * (length(nr.input) - 1)
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compute_effort_reduce = compute_effort(nr.input[1].task) * (length(nr.input) - 1)
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@test isapprox(estimate.data, -data_reduce; atol = eps(Float64))
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@test isapprox(estimate.computeEffort, -compute_effort_reduce)
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@test isapprox(estimate.computeIntensity, compute_effort_reduce / data_reduce)
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return nothing
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end
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function test_op_specific(estimator, graph, ns::NodeSplit)
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estimate = operation_effect(estimator, graph, ns)
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copies = length(ns.input.parents) - 1
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data_increase = data(ns.input.task) * copies
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compute_effort_increase = compute_effort(ns.input.task) * copies
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@test isapprox(estimate.data, data_increase; atol = eps(Float64))
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@test isapprox(estimate.computeEffort, compute_effort_increase)
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@test isapprox(estimate.computeIntensity, compute_effort_increase / data_increase)
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return nothing
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end
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function test_op(estimator, graph, op)
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#=
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See issue #16
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estimate_before = graph_cost(estimator, graph)
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estimate = operation_effect(estimator, graph, op)
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push_operation!(graph, op)
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estimate_after_apply = graph_cost(estimator, graph)
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reset_graph!(graph)
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@test isapprox((estimate_before + estimate).data, estimate_after_apply.data)
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@test isapprox((estimate_before + estimate).computeEffort, estimate_after_apply.computeEffort)
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@test isapprox((estimate_before + estimate).computeIntensity, estimate_after_apply.computeIntensity)
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=#
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test_op_specific(estimator, graph, op)
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return nothing
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end
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@testset "Unit Tests Estimator" begin
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@testset "Global Metric Estimator" for (graph_string, exp_data, exp_computeEffort) in
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zip(["AB->AB", "AB->ABBB"], [976, 10944], [53, 1075])
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estimator = GlobalMetricEstimator()
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@test cost_type(estimator) == CDCost
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graph = parse_dag(joinpath(@__DIR__, "..", "input", "$(graph_string).txt"), ABCModel())
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@testset "Graph Cost" begin
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estimate = graph_cost(estimator, graph)
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@test estimate.data == exp_data
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@test estimate.computeEffort == exp_computeEffort
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@test isapprox(estimate.computeIntensity, exp_computeEffort / exp_data)
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end
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@testset "Operation Cost" begin
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ops = get_operations(graph)
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nfs = copy(ops.nodeFusions)
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nrs = copy(ops.nodeReductions)
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nss = copy(ops.nodeSplits)
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println(
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"Testing $(length(ops.nodeFusions))xNF, $(length(ops.nodeReductions))xNR, $(length(ops.nodeSplits))xNS",
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)
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for nf in nfs
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test_op(estimator, graph, nf)
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end
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for nr in nrs
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test_op(estimator, graph, nr)
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end
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for ns in nss
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test_op(estimator, graph, ns)
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end
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end
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end
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end
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println("Estimator Unit Tests Complete!")
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@ -1,9 +1,51 @@
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import MetagraphOptimization.ABCParticle
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import MetagraphOptimization.interaction_result
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using QEDbase
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using AccurateArithmetic
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include("../examples/profiling_utilities.jl")
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const RTOL = sqrt(eps(Float64))
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function check_particle_reverse_moment(p1::SFourMomentum, p2::SFourMomentum)
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@test isapprox(abs(p1.E), abs(p2.E))
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@test isapprox(p1.px, -p2.px)
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@test isapprox(p1.py, -p2.py)
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@test isapprox(p1.pz, -p2.pz)
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return nothing
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end
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function ground_truth_graph_result(input::ABCProcessInput)
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# formula for one diagram:
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# u_Bp * iλ * u_Ap * S_C * u_B * iλ * u_A
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# for the second diagram:
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# u_B * iλ * u_Ap * S_C * u_Bp * iλ * u_Ap
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# the "u"s are all 1, we ignore the i, λ is 1/137.
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constant = (1 / 137.0)^2
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# calculate particle C in diagram 1
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diagram1_C = ParticleC(input.inParticles[1].momentum + input.inParticles[2].momentum)
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diagram2_C = ParticleC(input.inParticles[1].momentum + input.outParticles[2].momentum)
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diagram1_Cp = ParticleC(input.outParticles[1].momentum + input.outParticles[2].momentum)
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diagram2_Cp = ParticleC(input.outParticles[1].momentum + input.inParticles[2].momentum)
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check_particle_reverse_moment(diagram1_Cp.momentum, diagram1_C.momentum)
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check_particle_reverse_moment(diagram2_Cp.momentum, diagram2_C.momentum)
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@test isapprox(getMass2(diagram1_C.momentum), getMass2(diagram1_Cp.momentum))
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@test isapprox(getMass2(diagram2_C.momentum), getMass2(diagram2_Cp.momentum))
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inner1 = MetagraphOptimization.inner_edge(diagram1_C)
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inner2 = MetagraphOptimization.inner_edge(diagram2_C)
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diagram1_result = inner1 * constant
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diagram2_result = inner2 * constant
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return sum_kbn([diagram1_result, diagram2_result])
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end
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@testset "Unit Tests Execution" begin
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machine = get_machine_info()
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@ -23,29 +65,29 @@ include("../examples/profiling_utilities.jl")
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ParticleB(SFourMomentum(0.823648, 0.835061, 0.474802, -0.277915)),
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],
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)
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expected_result = 0.00013916495566048735
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expected_result = ground_truth_graph_result(particles_2_2)
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@testset "AB->AB no optimization" begin
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for _ in 1:10 # test in a loop because graph layout should not change the result
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graph = parse_dag(joinpath(@__DIR__, "..", "input", "AB->AB.txt"), ABCModel())
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@test isapprox(execute(graph, process_2_2, machine, particles_2_2), expected_result; rtol = 0.001)
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@test isapprox(execute(graph, process_2_2, machine, particles_2_2), expected_result; rtol = RTOL)
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# graph should be fully scheduled after being executed
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@test is_scheduled(graph)
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func = get_compute_function(graph, process_2_2, machine)
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@test isapprox(func(particles_2_2), expected_result; rtol = 0.001)
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@test isapprox(func(particles_2_2), expected_result; rtol = RTOL)
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end
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end
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@testset "AB->AB after random walk" begin
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for i in 1:1000
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for i in 1:200
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graph = parse_dag(joinpath(@__DIR__, "..", "input", "AB->AB.txt"), ABCModel())
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random_walk!(graph, 50)
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@test is_valid(graph)
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@test isapprox(execute(graph, process_2_2, machine, particles_2_2), expected_result; rtol = 0.001)
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@test isapprox(execute(graph, process_2_2, machine, particles_2_2), expected_result; rtol = RTOL)
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# graph should be fully scheduled after being executed
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@test is_scheduled(graph)
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@ -63,20 +105,20 @@ include("../examples/profiling_utilities.jl")
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@testset "AB->ABBB no optimization" begin
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for _ in 1:5 # test in a loop because graph layout should not change the result
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graph = parse_dag(joinpath(@__DIR__, "..", "input", "AB->ABBB.txt"), ABCModel())
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@test isapprox(execute(graph, process_2_4, machine, particles_2_4), expected_result; rtol = 0.001)
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@test isapprox(execute(graph, process_2_4, machine, particles_2_4), expected_result; rtol = RTOL)
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func = get_compute_function(graph, process_2_4, machine)
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@test isapprox(func(particles_2_4), expected_result; rtol = 0.001)
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@test isapprox(func(particles_2_4), expected_result; rtol = RTOL)
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end
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end
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@testset "AB->ABBB after random walk" begin
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for i in 1:200
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for i in 1:50
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graph = parse_dag(joinpath(@__DIR__, "..", "input", "AB->ABBB.txt"), ABCModel())
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random_walk!(graph, 100)
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@test is_valid(graph)
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@test isapprox(execute(graph, process_2_4, machine, particles_2_4), expected_result; rtol = 0.001)
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@test isapprox(execute(graph, process_2_4, machine, particles_2_4), expected_result; rtol = RTOL)
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end
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end
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@ -105,8 +147,8 @@ include("../examples/profiling_utilities.jl")
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# try execute
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@test is_valid(graph)
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expected_result = 0.00013916495566048735
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@test isapprox(execute(graph, process_2_2, machine, particles_2_2), expected_result; rtol = 0.001)
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expected_result = ground_truth_graph_result(particles_2_2)
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@test isapprox(execute(graph, process_2_2, machine, particles_2_2), expected_result; rtol = RTOL)
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end
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@ -135,8 +177,8 @@ include("../examples/profiling_utilities.jl")
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# try execute
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@test is_valid(graph)
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expected_result = 0.00013916495566048735
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@test isapprox(execute(graph, process_2_2, machine, particles_2_2), expected_result; rtol = 0.001)
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expected_result = ground_truth_graph_result(particles_2_2)
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@test isapprox(execute(graph, process_2_2, machine, particles_2_2), expected_result; rtol = RTOL)
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end
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@testset "AB->AB fusion edge case" for _ in 1:20
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@ -169,8 +211,8 @@ include("../examples/profiling_utilities.jl")
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# try execute
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@test is_valid(graph)
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expected_result = 0.00013916495566048735
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@test isapprox(execute(graph, process_2_2, machine, particles_2_2), expected_result; rtol = 0.001)
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expected_result = ground_truth_graph_result(particles_2_2)
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@test isapprox(execute(graph, process_2_2, machine, particles_2_2), expected_result; rtol = RTOL)
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end
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end
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