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47 lines
1.5 KiB
47 lines
1.5 KiB
# MIPLearn: Extensible Framework for Learning-Enhanced Mixed-Integer Optimization
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# Copyright (C) 2020-2022, 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 typing import List, Dict, Any
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from unittest.mock import Mock
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from sklearn.dummy import DummyClassifier
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from miplearn.components.primal.actions import SetWarmStart
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from miplearn.components.primal.joint import JointVarsPrimalComponent
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from miplearn.extractors.fields import H5FieldsExtractor
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def test_joint(multiknapsack_h5: List[str]) -> None:
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# Create mock classifier
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clf = Mock(wraps=DummyClassifier())
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# Create and fit component
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comp = JointVarsPrimalComponent(
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clf=clf,
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extractor=H5FieldsExtractor(instance_fields=["static_var_obj_coeffs"]),
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action=SetWarmStart(),
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)
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comp.fit(multiknapsack_h5)
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# Should call fit method with correct arguments
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clf.fit.assert_called()
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x, y = clf.fit.call_args.args
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assert x.shape == (3, 100)
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assert y.shape == (3, 100)
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# Call before-mip
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stats: Dict[str, Any] = {}
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model = Mock()
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comp.before_mip(multiknapsack_h5[0], model, stats)
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# Should call predict with correct args
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clf.predict.assert_called()
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(x_test,) = clf.predict.call_args.args
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assert x_test.shape == (1, 100)
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# Should set warm starts
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model.set_warm_starts.assert_called()
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names, starts, _ = model.set_warm_starts.call_args.args
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assert len(names) == 100
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assert starts.shape == (1, 100)
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