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50 lines
1.6 KiB
50 lines
1.6 KiB
# MIPLearn: Extensible Framework for Learning-Enhanced Mixed-Integer Optimization
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# Copyright (C) 2020, 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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from miplearn import GurobiSolver
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from miplearn.features import FeaturesExtractor
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from tests.fixtures.knapsack import get_knapsack_instance
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def test_knapsack() -> None:
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for solver_factory in [GurobiSolver]:
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solver = solver_factory()
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instance = get_knapsack_instance(solver)
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model = instance.to_model()
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solver.set_instance(instance, model)
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extractor = FeaturesExtractor(solver)
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features = extractor.extract(instance)
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assert features["Variables"] == {
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"x": {
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0: {
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"Category": "default",
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"User features": [23.0, 505.0],
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},
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1: {
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"Category": "default",
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"User features": [26.0, 352.0],
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},
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2: {
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"Category": "default",
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"User features": [20.0, 458.0],
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},
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3: {
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"Category": "default",
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"User features": [18.0, 220.0],
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},
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}
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}
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assert features["Constraints"]["eq_capacity"] == {
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"LHS": {
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"x[0]": 23.0,
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"x[1]": 26.0,
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"x[2]": 20.0,
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"x[3]": 18.0,
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},
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"Sense": "<",
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"RHS": 67.0,
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"Category": "eq_capacity",
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"User features": [0.0],
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}
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