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MIPLearn.jl
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FileInstance: Make interface simpler to use

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master
Alinson S. Xavier 3 years ago
parent 9b3a0da5f7
commit 5618330793
Signed by: isoron
GPG Key ID: 0DA8E4B9E1109DCA
6 changed files with 262 additions and 212 deletions
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Manifest.toml
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@ -1,582 +1,602 @@
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uuid = "ea8e919c-243c-51af-8825-aaa63cd721ce" uuid = "ea8e919c-243c-51af-8825-aaa63cd721ce"
[[Scratch]] [[deps.Scratch]]
deps = ["Dates"] deps = ["Dates"]
git-tree-sha1 = "f94f779c94e58bf9ea243e77a37e16d9de9126bd" git-tree-sha1 = "f94f779c94e58bf9ea243e77a37e16d9de9126bd"
uuid = "6c6a2e73-6563-6170-7368-637461726353" uuid = "6c6a2e73-6563-6170-7368-637461726353"
version = "1.1.1" version = "1.1.1"
[[SentinelArrays]] [[deps.SentinelArrays]]
deps = ["Dates", "Random"] deps = ["Dates", "Random"]
git-tree-sha1 = "db8481cf5d6278a121184809e9eb1628943c7704" git-tree-sha1 = "db8481cf5d6278a121184809e9eb1628943c7704"
uuid = "91c51154-3ec4-41a3-a24f-3f23e20d615c" uuid = "91c51154-3ec4-41a3-a24f-3f23e20d615c"
version = "1.3.13" version = "1.3.13"
[[Serialization]] [[deps.Serialization]]
uuid = "9e88b42a-f829-5b0c-bbe9-9e923198166b" uuid = "9e88b42a-f829-5b0c-bbe9-9e923198166b"
[[SharedArrays]] [[deps.SharedArrays]]
deps = ["Distributed", "Mmap", "Random", "Serialization"] deps = ["Distributed", "Mmap", "Random", "Serialization"]
uuid = "1a1011a3-84de-559e-8e89-a11a2f7dc383" uuid = "1a1011a3-84de-559e-8e89-a11a2f7dc383"
[[Sockets]] [[deps.Sockets]]
uuid = "6462fe0b-24de-5631-8697-dd941f90decc" uuid = "6462fe0b-24de-5631-8697-dd941f90decc"
[[SortingAlgorithms]] [[deps.SortingAlgorithms]]
deps = ["DataStructures"] deps = ["DataStructures"]
git-tree-sha1 = "b3363d7460f7d098ca0912c69b082f75625d7508" git-tree-sha1 = "b3363d7460f7d098ca0912c69b082f75625d7508"
uuid = "a2af1166-a08f-5f64-846c-94a0d3cef48c" uuid = "a2af1166-a08f-5f64-846c-94a0d3cef48c"
version = "1.0.1" version = "1.0.1"
[[SparseArrays]] [[deps.SparseArrays]]
deps = ["LinearAlgebra", "Random"] deps = ["LinearAlgebra", "Random"]
uuid = "2f01184e-e22b-5df5-ae63-d93ebab69eaf" uuid = "2f01184e-e22b-5df5-ae63-d93ebab69eaf"
[[SpecialFunctions]] [[deps.SpecialFunctions]]
deps = ["ChainRulesCore", "IrrationalConstants", "LogExpFunctions", "OpenLibm_jll", "OpenSpecFun_jll"] deps = ["ChainRulesCore", "IrrationalConstants", "LogExpFunctions", "OpenLibm_jll", "OpenSpecFun_jll"]
git-tree-sha1 = "d75bda01f8c31ebb72df80a46c88b25d1c79c56d" git-tree-sha1 = "d75bda01f8c31ebb72df80a46c88b25d1c79c56d"
uuid = "276daf66-3868-5448-9aa4-cd146d93841b" uuid = "276daf66-3868-5448-9aa4-cd146d93841b"
version = "2.1.7" version = "2.1.7"
[[StaticArrays]] [[deps.StaticArrays]]
deps = ["LinearAlgebra", "Random", "StaticArraysCore", "Statistics"] deps = ["LinearAlgebra", "Random", "StaticArraysCore", "Statistics"]
git-tree-sha1 = "8803c6dea034ab8cd988abe4a91e5589d61c7416" git-tree-sha1 = "dfec37b90740e3b9aa5dc2613892a3fc155c3b42"
uuid = "90137ffa-7385-5640-81b9-e52037218182" uuid = "90137ffa-7385-5640-81b9-e52037218182"
version = "1.5.4" version = "1.5.6"
[[StaticArraysCore]] [[deps.StaticArraysCore]]
git-tree-sha1 = "5b413a57dd3cea38497d745ce088ac8592fbb5be" git-tree-sha1 = "ec2bd695e905a3c755b33026954b119ea17f2d22"
uuid = "1e83bf80-4336-4d27-bf5d-d5a4f845583c" uuid = "1e83bf80-4336-4d27-bf5d-d5a4f845583c"
version = "1.1.0" version = "1.3.0"
[[Statistics]] [[deps.Statistics]]
deps = ["LinearAlgebra", "SparseArrays"] deps = ["LinearAlgebra", "SparseArrays"]
uuid = "10745b16-79ce-11e8-11f9-7d13ad32a3b2" uuid = "10745b16-79ce-11e8-11f9-7d13ad32a3b2"
[[TOML]] [[deps.TOML]]
deps = ["Dates"] deps = ["Dates"]
uuid = "fa267f1f-6049-4f14-aa54-33bafae1ed76" uuid = "fa267f1f-6049-4f14-aa54-33bafae1ed76"
[[TableTraits]] [[deps.TableTraits]]
deps = ["IteratorInterfaceExtensions"] deps = ["IteratorInterfaceExtensions"]
git-tree-sha1 = "c06b2f539df1c6efa794486abfb6ed2022561a39" git-tree-sha1 = "c06b2f539df1c6efa794486abfb6ed2022561a39"
uuid = "3783bdb8-4a98-5b6b-af9a-565f29a5fe9c" uuid = "3783bdb8-4a98-5b6b-af9a-565f29a5fe9c"
version = "1.0.1" version = "1.0.1"
[[Tables]] [[deps.Tables]]
deps = ["DataAPI", "DataValueInterfaces", "IteratorInterfaceExtensions", "LinearAlgebra", "OrderedCollections", "TableTraits", "Test"] deps = ["DataAPI", "DataValueInterfaces", "IteratorInterfaceExtensions", "LinearAlgebra", "OrderedCollections", "TableTraits", "Test"]
git-tree-sha1 = "5ce79ce186cc678bbb5c5681ca3379d1ddae11a1" git-tree-sha1 = "5ce79ce186cc678bbb5c5681ca3379d1ddae11a1"
uuid = "bd369af6-aec1-5ad0-b16a-f7cc5008161c" uuid = "bd369af6-aec1-5ad0-b16a-f7cc5008161c"
version = "1.7.0" version = "1.7.0"
[[Tar]] [[deps.Tar]]
deps = ["ArgTools", "SHA"] deps = ["ArgTools", "SHA"]
uuid = "a4e569a6-e804-4fa4-b0f3-eef7a1d5b13e" uuid = "a4e569a6-e804-4fa4-b0f3-eef7a1d5b13e"
[[Test]] [[deps.Test]]
deps = ["InteractiveUtils", "Logging", "Random", "Serialization"] deps = ["InteractiveUtils", "Logging", "Random", "Serialization"]
uuid = "8dfed614-e22c-5e08-85e1-65c5234f0b40" uuid = "8dfed614-e22c-5e08-85e1-65c5234f0b40"
[[TimerOutputs]] [[deps.TimerOutputs]]
deps = ["ExprTools", "Printf"] deps = ["ExprTools", "Printf"]
git-tree-sha1 = "9dfcb767e17b0849d6aaf85997c98a5aea292513" git-tree-sha1 = "9dfcb767e17b0849d6aaf85997c98a5aea292513"
uuid = "a759f4b9-e2f1-59dc-863e-4aeb61b1ea8f" uuid = "a759f4b9-e2f1-59dc-863e-4aeb61b1ea8f"
version = "0.5.21" version = "0.5.21"
[[TranscodingStreams]] [[deps.TranscodingStreams]]
deps = ["Random", "Test"] deps = ["Random", "Test"]
git-tree-sha1 = "216b95ea110b5972db65aa90f88d8d89dcb8851c" git-tree-sha1 = "8a75929dcd3c38611db2f8d08546decb514fcadf"
uuid = "3bb67fe8-82b1-5028-8e26-92a6c54297fa" uuid = "3bb67fe8-82b1-5028-8e26-92a6c54297fa"
version = "0.9.6" version = "0.9.9"
[[UUIDs]] [[deps.UUIDs]]
deps = ["Random", "SHA"] deps = ["Random", "SHA"]
uuid = "cf7118a7-6976-5b1a-9a39-7adc72f591a4" uuid = "cf7118a7-6976-5b1a-9a39-7adc72f591a4"
[[Unicode]] [[deps.Unicode]]
uuid = "4ec0a83e-493e-50e2-b9ac-8f72acf5a8f5" uuid = "4ec0a83e-493e-50e2-b9ac-8f72acf5a8f5"
[[VersionParsing]] [[deps.VersionParsing]]
git-tree-sha1 = "58d6e80b4ee071f5efd07fda82cb9fbe17200868" git-tree-sha1 = "58d6e80b4ee071f5efd07fda82cb9fbe17200868"
uuid = "81def892-9a0e-5fdd-b105-ffc91e053289" uuid = "81def892-9a0e-5fdd-b105-ffc91e053289"
version = "1.3.0" version = "1.3.0"
[[WeakRefStrings]] [[deps.WeakRefStrings]]
deps = ["DataAPI", "InlineStrings", "Parsers"] deps = ["DataAPI", "InlineStrings", "Parsers"]
git-tree-sha1 = "b1be2855ed9ed8eac54e5caff2afcdb442d52c23" git-tree-sha1 = "b1be2855ed9ed8eac54e5caff2afcdb442d52c23"
uuid = "ea10d353-3f73-51f8-a26c-33c1cb351aa5" uuid = "ea10d353-3f73-51f8-a26c-33c1cb351aa5"
version = "1.4.2" version = "1.4.2"
[[Zlib_jll]] [[deps.Zlib_jll]]
deps = ["Libdl"] deps = ["Libdl"]
uuid = "83775a58-1f1d-513f-b197-d71354ab007a" uuid = "83775a58-1f1d-513f-b197-d71354ab007a"
[[nghttp2_jll]] [[deps.libblastrampoline_jll]]
deps = ["Artifacts", "Libdl", "OpenBLAS_jll"]
uuid = "8e850b90-86db-534c-a0d3-1478176c7d93"
[[deps.nghttp2_jll]]
deps = ["Artifacts", "Libdl"] deps = ["Artifacts", "Libdl"]
uuid = "8e850ede-7688-5339-a07c-302acd2aaf8d" uuid = "8e850ede-7688-5339-a07c-302acd2aaf8d"
[[p7zip_jll]] [[deps.p7zip_jll]]
deps = ["Artifacts", "Libdl"] deps = ["Artifacts", "Libdl"]
uuid = "3f19e933-33d8-53b3-aaab-bd5110c3b7a0" uuid = "3f19e933-33d8-53b3-aaab-bd5110c3b7a0"

2
Project.toml
Unescape View File

@ -16,8 +16,10 @@ JSON = "682c06a0-de6a-54ab-a142-c8b1cf79cde6"
JuMP = "4076af6c-e467-56ae-b986-b466b2749572" JuMP = "4076af6c-e467-56ae-b986-b466b2749572"
Logging = "56ddb016-857b-54e1-b83d-db4d58db5568" Logging = "56ddb016-857b-54e1-b83d-db4d58db5568"
MathOptInterface = "b8f27783-ece8-5eb3-8dc8-9495eed66fee" MathOptInterface = "b8f27783-ece8-5eb3-8dc8-9495eed66fee"
OrderedCollections = "bac558e1-5e72-5ebc-8fee-abe8a469f55d"
PackageCompiler = "9b87118b-4619-50d2-8e1e-99f35a4d4d9d" PackageCompiler = "9b87118b-4619-50d2-8e1e-99f35a4d4d9d"
Printf = "de0858da-6303-5e67-8744-51eddeeeb8d7" Printf = "de0858da-6303-5e67-8744-51eddeeeb8d7"
ProgressBars = "49802e3a-d2f1-5c88-81d8-b72133a6f568"
PyCall = "438e738f-606a-5dbb-bf0a-cddfbfd45ab0" PyCall = "438e738f-606a-5dbb-bf0a-cddfbfd45ab0"
Random = "9a3f8284-a2c9-5f02-9a11-845980a1fd5c" Random = "9a3f8284-a2c9-5f02-9a11-845980a1fd5c"
SparseArrays = "2f01184e-e22b-5df5-ae63-d93ebab69eaf" SparseArrays = "2f01184e-e22b-5df5-ae63-d93ebab69eaf"

47
src/instance/file_instance.jl
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@ -3,6 +3,8 @@
# Released under the modified BSD license. See COPYING.md for more details. # Released under the modified BSD license. See COPYING.md for more details.
using JLD2 using JLD2
using Distributed
using ProgressBars
import Base: flush import Base: flush
mutable struct FileInstance <: Instance mutable struct FileInstance <: Instance
@ -20,8 +22,9 @@ mutable struct FileInstance <: Instance
)::FileInstance )::FileInstance
instance = new(nothing, nothing, filename, nothing, build_model, mode) instance = new(nothing, nothing, filename, nothing, build_model, mode)
instance.py = PyFileInstance(instance) instance.py = PyFileInstance(instance)
if mode != "r" || isfile("$filename.h5") h5_filename = replace(filename, ".jld2" => ".h5")
instance.sample = Hdf5Sample("$filename.h5", mode = mode) if mode != "r" || isfile(h5_filename)
instance.sample = Hdf5Sample(h5_filename, mode = mode)
end end
instance.filename = filename instance.filename = filename
return instance return instance
@ -107,33 +110,38 @@ function load(filename::AbstractString, build_model::Function)
end end
end end
function save(data::AbstractVector, dirname::String)::Nothing function save(data::AbstractVector, dirname::String)::Vector{String}
mkpath(dirname) mkpath(dirname)
filenames = []
for (i, d) in enumerate(data) for (i, d) in enumerate(data)
filename = joinpath(dirname, @sprintf("%06d.jld2", i)) filename = joinpath(dirname, @sprintf("%06d.jld2", i))
push!(filenames, filename)
jldsave(filename, data = d) jldsave(filename, data = d)
end end
return filenames
end end
function solve!( function fit!(
solver::LearningSolver, solver::LearningSolver,
filenames::Vector, filenames::Vector,
build_model::Function; build_model::Function;
tee::Bool = false, tee::Bool = false,
) )
for filename in filenames instances = [FileInstance(f, build_model) for f in filenames]
solve!(solver, filename, build_model; tee) fit!(solver, instances)
end
end end
function fit!( function solve!(
solver::LearningSolver, solver::LearningSolver,
filenames::Vector, filenames::Vector,
build_model::Function; build_model::Function;
tee::Bool = false, tee::Bool = false,
progress::Bool = false,
) )
instances = [FileInstance(f, build_model) for f in filenames] if progress
fit!(solver, instances) filenames = ProgressBar(filenames)
end
return [solve!(solver, f, build_model; tee) for f in filenames]
end end
function solve!( function solve!(
@ -142,7 +150,24 @@ function solve!(
build_model::Function; build_model::Function;
tee::Bool = false, tee::Bool = false,
) )
solve!(solver, FileInstance(filename, build_model); tee) instance = FileInstance(filename, build_model)
stats = solve!(solver, instance; tee)
instance.sample.file.close()
return stats
end
function parallel_solve!(
solver::LearningSolver,
filenames::Vector,
build_model::Function;
tee::Bool = false,
)
solver_filename = tempname()
save(solver_filename, solver)
@sync @distributed for filename in filenames
local_solver = load_solver(solver_filename)
solve!(local_solver, filename, build_model; tee)
end
end end
function __init_PyFileInstance__() function __init_PyFileInstance__()

79
src/utils/benchmark.jl
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@ -4,57 +4,60 @@
using CSV using CSV
using DataFrames using DataFrames
using OrderedCollections
function run_benchmarks(;
optimizer,
train_instances::Vector{<:AbstractString},
test_instances::Vector{<:AbstractString},
build_model::Function,
progress::Bool = false,
output_filename::String,
)
solvers = OrderedDict(
"baseline" => LearningSolver(optimizer),
"ml-exact" => LearningSolver(optimizer),
"ml-heuristic" => LearningSolver(optimizer, mode="heuristic"),
)
#solve!(solvers["baseline"], train_instances, build_model; progress)
fit!(solvers["ml-exact"], train_instances, build_model)
fit!(solvers["ml-heuristic"], train_instances, build_model)
mutable struct BenchmarkRunner stats = OrderedDict()
solvers::Dict for (solver_name, solver) in solvers
results::Union{Nothing,DataFrame} stats[solver_name] = solve!(solver, test_instances, build_model; progress)
py::PyCall.PyObject
function BenchmarkRunner(; solvers::Dict)
return new(
solvers,
nothing, # results
miplearn.BenchmarkRunner(
Dict(sname => solver.py for (sname, solver) in solvers),
),
)
end
end end
function solve!( results = nothing
runner::BenchmarkRunner, for (solver_name, solver_stats) in stats
instances::Vector{FileInstance}; for (i, s) in enumerate(solver_stats)
n_trials::Int = 1,
)::Nothing
instances = repeat(instances, n_trials)
for (solver_name, solver) in runner.solvers
@info "benchmark $solver_name"
stats = [
solve!(solver, instance, discard_output = true, tee = true) for
instance in instances
]
for (i, s) in enumerate(stats)
s["Solver"] = solver_name s["Solver"] = solver_name
s["Instance"] = instances[i].filename s["Instance"] = test_instances[i]
s = Dict(k => isnothing(v) ? missing : v for (k, v) in s) s = Dict(k => isnothing(v) ? missing : v for (k, v) in s)
if runner.results === nothing if results === nothing
runner.results = DataFrame(s) results = DataFrame(s)
else else
push!(runner.results, s, cols = :union) push!(results, s, cols = :union)
end
end end
@info "benchmark $solver_name [done]"
end end
end end
CSV.write(output_filename, results)
function fit!(runner::BenchmarkRunner, instances::Vector{FileInstance})::Nothing # fig_filename = "$(tempname()).svg"
@python_call runner.py.fit([instance.py for instance in instances]) # df = pyimport("pandas").read_csv(csv_filename)
# miplearn.benchmark.plot(df, output=fig_filename)
# open(fig_filename) do f
# display("image/svg+xml", read(f, String))
# end
return
end end
function write_csv!(runner::BenchmarkRunner, filename::AbstractString)::Nothing function run_benchmarks(; solvers, instance_filenames, build_model, output_filename)
CSV.write(filename, runner.results) runner = BenchmarkRunner(; solvers)
return instances = [FileInstance(f, build_model) for f in instance_filenames]
solve!(runner, instances)
write_csv!(runner, output_filename)
end end
export BenchmarkRunner, solve!, fit!, write_csv! export BenchmarkRunner, solve!, fit!, write_csv!

18
test/instance/file_instance_test.jl
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@ -9,24 +9,24 @@ using Cbc
@testset "FileInstance" begin @testset "FileInstance" begin
@testset "Solve (knapsack)" begin @testset "Solve (knapsack)" begin
data = KnapsackData() data = KnapsackData()
filename = tempname() basename = tempname()
MIPLearn.save_data(filename, data) MIPLearn.save_data("$basename.jld2", data)
instance = FileInstance(filename, build_knapsack_model) instance = FileInstance("$basename.jld2", build_knapsack_model)
solver = LearningSolver(Cbc.Optimizer) solver = LearningSolver(Cbc.Optimizer)
solve!(solver, instance) solve!(solver, instance)
h5 = Hdf5Sample("$filename.h5") h5 = Hdf5Sample("$basename.h5")
@test h5.get_scalar("mip_wallclock_time") > 0 @test h5.get_scalar("mip_wallclock_time") > 0
end end
@testset "Solve (vpm2)" begin @testset "Solve (danoint)" begin
data = Dict("filename" => joinpath(@__DIR__, "../fixtures/danoint.mps.gz")) data = Dict("filename" => joinpath(@__DIR__, "../fixtures/danoint.mps.gz"))
build_model(data) = read_from_file(data["filename"]) build_model(data) = read_from_file(data["filename"])
filename = tempname() basename = tempname()
MIPLearn.save_data(filename, data) MIPLearn.save_data("$basename.jld2", data)
instance = FileInstance(filename, build_model) instance = FileInstance("$basename.jld2", build_model)
solver = LearningSolver(optimizer_with_attributes(Cbc.Optimizer, "seconds" => 1.0)) solver = LearningSolver(optimizer_with_attributes(Cbc.Optimizer, "seconds" => 1.0))
solve!(solver, instance) solve!(solver, instance)
h5 = Hdf5Sample("$filename.h5") h5 = Hdf5Sample("$basename.h5")
@test h5.get_scalar("mip_wallclock_time") > 0 @test h5.get_scalar("mip_wallclock_time") > 0
end end

8
test/instance/jump_instance_test.jl
Unescape View File

@ -51,12 +51,12 @@ end
@testset "FileInstance" begin @testset "FileInstance" begin
data = nothing data = nothing
filename = tempname() basename = tempname()
MIPLearn.save_data(filename, data) MIPLearn.save_data("$basename.jld2", data)
instance = FileInstance(filename, build_model) instance = FileInstance("$basename.jld2", build_model)
solver = LearningSolver(Cbc.Optimizer) solver = LearningSolver(Cbc.Optimizer)
solve!(solver, instance) solve!(solver, instance)
h5 = MIPLearn.Hdf5Sample("$filename.h5") h5 = MIPLearn.Hdf5Sample("$basename.h5")
@test h5.get_array("mip_var_values") == [1.0, 0.0] @test h5.get_array("mip_var_values") == [1.0, 0.0]
end end
end end

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