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33 lines
1.2 KiB
33 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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import tempfile
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from miplearn.solvers.learning import LearningSolver
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from miplearn.solvers.gurobi import GurobiSolver
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from miplearn.features.sample import Hdf5Sample
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from miplearn.instance.file import FileInstance
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def test_usage() -> None:
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# Create original instance
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original = GurobiSolver().build_test_instance_knapsack()
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# Save instance to disk
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filename = tempfile.mktemp()
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FileInstance.save(original, filename)
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sample = Hdf5Sample(filename)
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assert len(sample.get_array("pickled")) > 0
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# Solve instance from disk
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solver = LearningSolver(solver=GurobiSolver())
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solver._solve(FileInstance(filename))
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# Assert HDF5 contains training data
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sample = FileInstance(filename).get_samples()[0]
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assert sample.get_scalar("mip_lower_bound") == 1183.0
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assert sample.get_scalar("mip_upper_bound") == 1183.0
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assert len(sample.get_array("lp_var_values")) == 5
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assert len(sample.get_array("mip_var_values")) == 5
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