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[BUG] set_cover Python: fix UB in vector transforms and swapped GuidedTabuSearch bindings #5121

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[BUG] set_cover Python: fix UB in vector transforms and swapped GuidedTabuSearch bindings #5121

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11 changes: 7 additions & 4 deletions ortools/set_cover/python/set_cover.cc
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Original file line number Diff line number Diff line change
Expand Up @@ -71,7 +71,8 @@ using ::py::make_iterator;
std::vector<SubsetIndex> VectorIntToVectorSubsetIndex(
absl::Span<const BaseInt> ints) {
std::vector<SubsetIndex> subs;
std::transform(ints.begin(), ints.end(), subs.begin(),
subs.reserve(ints.size());
std::transform(ints.begin(), ints.end(), std::back_inserter(subs),
[](int subset) -> SubsetIndex { return SubsetIndex(subset); });
return subs;
}
Expand Down Expand Up @@ -199,9 +200,11 @@ PYBIND11_MODULE(set_cover, m) {
.def_property_readonly("all_subsets",
[](SetCoverModel& model) -> std::vector<BaseInt> {
std::vector<BaseInt> subsets;
subsets.reserve(model.all_subsets().size());
std::transform(
model.all_subsets().begin(),
model.all_subsets().end(), subsets.begin(),
model.all_subsets().end(),
std::back_inserter(subsets),
[](const SubsetIndex element) -> BaseInt {
return element.value();
});
Expand Down Expand Up @@ -555,9 +558,9 @@ PYBIND11_MODULE(set_cover, m) {
return heuristic.NextSolution(
BoolVectorToSubsetBoolVector(in_focus));
})
.def("get_lagrangian_factor", &GuidedTabuSearch::SetLagrangianFactor,
.def("set_lagrangian_factor", &GuidedTabuSearch::SetLagrangianFactor,
arg("factor"))
.def("set_lagrangian_factor", &GuidedTabuSearch::GetLagrangianFactor)
.def("get_lagrangian_factor", &GuidedTabuSearch::GetLagrangianFactor)
.def("set_epsilon", &GuidedTabuSearch::SetEpsilon, arg("r"))
.def("get_epsilon", &GuidedTabuSearch::GetEpsilon)
.def("set_penalty_factor", &GuidedTabuSearch::SetPenaltyFactor,
Expand Down
29 changes: 29 additions & 0 deletions ortools/set_cover/python/set_cover_test.py
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Original file line number Diff line number Diff line change
Expand Up @@ -222,6 +222,35 @@ def test_knights_cover_trivial(self):
inv.check_consistency(set_cover.consistency_level.FREE_AND_UNCOVERED)
)

def test_all_subsets_property(self):
model = create_knights_cover_model(4, 4)
all_subs = model.all_subsets
self.assertLen(all_subs, model.num_subsets)
self.assertEqual(all_subs, list(range(model.num_subsets)))

def test_focus_based_next_solution(self):
model = create_knights_cover_model(8, 8)
self.assertTrue(model.compute_feasibility())
inv = set_cover.SetCoverInvariant(model)

focus = list(range(model.num_subsets))
greedy = set_cover.GreedySolutionGenerator(inv)
self.assertTrue(greedy.next_solution(focus))
self.assertEqual(inv.num_uncovered_elements(), 0)

def test_guided_tabu_search_lagrangian_factor(self):
model = create_knights_cover_model(8, 8)
self.assertTrue(model.compute_feasibility())
inv = set_cover.SetCoverInvariant(model)

greedy = set_cover.GreedySolutionGenerator(inv)
self.assertTrue(greedy.next_solution())

gts = set_cover.GuidedTabuSearch(inv)
gts.initialize()
gts.set_lagrangian_factor(0.5)
self.assertAlmostEqual(gts.get_lagrangian_factor(), 0.5)

# TODO(user): KnightsCoverGreedyAndTabu, KnightsCoverGreedyRandomClear,
# KnightsCoverElementDegreeRandomClear, KnightsCoverRandomClearMip,
# KnightsCoverMip
Expand Down