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35 lines
1.2 KiB
35 lines
1.2 KiB
# MIPLearn: Extensible Framework for Learning-Enhanced Mixed-Integer Optimization
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# Copyright (C) 2020-2021, UChicago Argonne, LLC. All rights reserved.
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# Released under the modified BSD license. See COPYING.md for more details.
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@testset "JuMPInstance" begin
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@testset "save and load" begin
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# Create basic model
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model = Model()
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@variable(model, x, Bin)
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@variable(model, y, Bin)
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@objective(model, Max, x + y)
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@feature(x, [1.0])
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@category(x, "cat1")
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@feature(model, [5.0])
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# Solve
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instance = JuMPInstance(model)
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solver = LearningSolver(Gurobi.Optimizer)
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stats = solve!(solver, instance)
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@test length(instance.py.samples) == 1
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# Save model to file
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filename = tempname()
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save(filename, instance)
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@test isfile(filename)
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# Read model from file
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loaded = load_jump_instance(filename)
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x = variable_by_name(loaded.model, "x")
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@test loaded.model.ext[:miplearn][:variable_features][x] == [1.0]
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@test loaded.model.ext[:miplearn][:variable_categories][x] == "cat1"
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@test loaded.model.ext[:miplearn][:instance_features] == [5.0]
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@test length(loaded.py.samples) == 1
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end
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end |