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https://github.com/ANL-CEEESA/MIPLearn.git
synced 2025-12-06 01:18:52 -06:00
Rename before/after_solve to before/after_solve_mip
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@@ -80,7 +80,7 @@ def test_drop_redundant():
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component.classifiers = classifiers
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# LearningSolver calls before_solve
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component.before_solve(solver, instance, None)
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component.before_solve_mip(solver, instance, None)
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# Should query list of constraints
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internal.get_constraint_ids.assert_called_once()
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@@ -123,7 +123,7 @@ def test_drop_redundant():
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# LearningSolver calls after_solve
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training_data = {}
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component.after_solve(solver, instance, None, {}, training_data)
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component.after_solve_mip(solver, instance, None, {}, training_data)
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# Should query slack for all inequalities
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internal.get_inequality_slacks.assert_called_once()
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@@ -147,7 +147,7 @@ def test_drop_redundant_with_check_feasibility():
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component.classifiers = classifiers
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# LearningSolver call before_solve
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component.before_solve(solver, instance, None)
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component.before_solve_mip(solver, instance, None)
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# Assert constraints are extracted
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assert internal.extract_constraint.call_count == 2
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@@ -22,14 +22,14 @@ def test_composite():
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cc = CompositeComponent([c1, c2])
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# Should broadcast before_solve
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cc.before_solve(solver, instance, model)
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c1.before_solve.assert_has_calls([call(solver, instance, model)])
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c2.before_solve.assert_has_calls([call(solver, instance, model)])
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cc.before_solve_mip(solver, instance, model)
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c1.before_solve_mip.assert_has_calls([call(solver, instance, model)])
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c2.before_solve_mip.assert_has_calls([call(solver, instance, model)])
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# Should broadcast after_solve
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cc.after_solve(solver, instance, model, {}, {})
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c1.after_solve.assert_has_calls([call(solver, instance, model, {}, {})])
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c2.after_solve.assert_has_calls([call(solver, instance, model, {}, {})])
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cc.after_solve_mip(solver, instance, model, {}, {})
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c1.after_solve_mip.assert_has_calls([call(solver, instance, model, {}, {})])
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c2.after_solve_mip.assert_has_calls([call(solver, instance, model, {}, {})])
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# Should broadcast fit
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cc.fit([1, 2, 3])
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@@ -85,7 +85,7 @@ def test_lazy_before():
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component.classifiers["a"].predict_proba = Mock(return_value=[[0.95, 0.05]])
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component.classifiers["b"].predict_proba = Mock(return_value=[[0.02, 0.80]])
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component.before_solve(solver, instances[0], models[0])
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component.before_solve_mip(solver, instances[0], models[0])
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# Should ask classifier likelihood of each constraint being violated
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expected_x_test_a = np.array([[67.0, 21.75, 1287.92]])
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@@ -68,7 +68,7 @@ def test_usage_with_solver():
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)
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# LearningSolver calls before_solve
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component.before_solve(solver, instance, None)
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component.before_solve_mip(solver, instance, None)
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# Should ask if instance has static lazy constraints
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instance.has_static_lazy_constraints.assert_called_once()
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