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MIPLearn.jl/test/instance/jump_test.jl

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# 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 MIPLearn
@testset "JuMPInstance" begin
@testset "Save and load" begin
# Build instance and solve
model = model = build_knapsack_model()
instance = JuMPInstance(model)
solver = LearningSolver(Gurobi.Optimizer)
stats = solve!(solver, instance)
@test length(instance.py.samples) == 1
# Save model to file
filename = tempname()
save(filename, instance)
@test isfile(filename)
# Read model from file
loaded = load_jump_instance(filename)
x = variable_by_name(loaded.model, "x")
@test loaded.model.ext[:miplearn][:variable_features][x] == [1.0]
@test loaded.model.ext[:miplearn][:variable_categories][x] == "cat1"
@test loaded.model.ext[:miplearn][:instance_features] == [5.0]
@test length(loaded.py.samples) == 1
end
end