Add dirty check for ipopt

Author: metab0t

include/pyoptinterface/ipopt_model.hpp

@@ -240,6 +240,7 @@ struct IpoptModel : public OnesideLinearConstraintMixin<IpoptModel>,
 	Hashmap<std::string, std::string> m_options_str;
 
 	IpoptResult m_result;
+	bool m_is_dirty = true;
 	enum ApplicationReturnStatus m_status;
 
 	std::unique_ptr<IpoptProblemInfo, IpoptfreeproblemT> m_problem = nullptr;

lib/ipopt_model.cpp

@@ -80,6 +80,8 @@ VariableIndex IpoptModel::add_variable(double lb, double ub, double start, const
 		m_var_names.emplace(vi.index, name);
 	}
 
+	m_is_dirty = true;
+
 	return vi;
 }
 
@@ -216,6 +218,8 @@ ConstraintIndex IpoptModel::add_linear_constraint(const ScalarAffineFunction &f,
 	m_linear_con_lb.push_back(lb);
 	m_linear_con_ub.push_back(ub);
 
+	m_is_dirty = true;
+
 	return con;
 }
 
@@ -257,6 +261,8 @@ ConstraintIndex IpoptModel::add_quadratic_constraint(const ScalarQuadraticFuncti
 	m_quadratic_con_lb.push_back(lb);
 	m_quadratic_con_ub.push_back(ub);
 
+	m_is_dirty = true;
+
 	return con;
 }
 
@@ -285,6 +291,8 @@ void IpoptModel::set_objective(const ExprBuilder &expr, ObjectiveSense sense)
 	{
 		throw std::runtime_error("Only linear and quadratic objective is supported");
 	}
+
+	m_is_dirty = true;
 }
 
 void IpoptModel::_set_linear_objective(const ScalarAffineFunction &expr)
@@ -369,6 +377,8 @@ ConstraintIndex IpoptModel::add_single_nl_constraint(size_t graph_index,
 	nl_constraint_graph_memberships.push_back(ConstraintGraphMembership{
 	    .graph = (int)graph_index, .rank = (int)graph.m_constraint_outputs.size() - 1});
 
+	m_is_dirty = true;
+
 	return ConstraintIndex(ConstraintType::IPOPT_NL, constraint_index);
 }
 
@@ -636,8 +646,6 @@ void IpoptModel::analyze_structure()
 
 		nl_constraint_map_ext2int[i_nl_con] = index_base + i_graph_rank;
 	}
-	/*fmt::print("constraint_indices_offsets {}\n", m_nl_evaluator.constraint_indices_offsets);
-	fmt::print("nl_constraint_map_ext2int {}\n", nl_constraint_map_ext2int);*/
 
 	// construct the lower bound and upper bound of the constraints
 	auto n_constraints = m_linear_con_evaluator.n_constraints +
@@ -754,6 +762,7 @@ void IpoptModel::optimize()
 	                             &m_result.obj_val, m_result.mult_g.data(),
 	                             m_result.mult_x_L.data(), m_result.mult_x_U.data(), (void *)this);
 	m_result.is_valid = true;
+	m_is_dirty = false;
 }
 
 void IpoptModel::load_current_solution()

lib/ipopt_model_ext.cpp

@@ -43,6 +43,7 @@ NB_MODULE(ipopt_model_ext, m)
 	    .def(nb::init<>())
 	    .def("close", &IpoptModel::close)
 	    .def_ro("m_status", &IpoptModel::m_status)
+	    .def_rw("m_is_dirty", &IpoptModel::m_is_dirty)
 	    .def("add_variable", &IpoptModel::add_variable, nb::arg("lb") = -INFINITY,
 	         nb::arg("ub") = INFINITY, nb::arg("start") = 0.0, nb::arg("name") = "")
 	    .def("get_variable_lb", &IpoptModel::get_variable_lb)

src/pyoptinterface/_src/ipopt.py

@@ -130,6 +130,9 @@ def get_rawstatusstring(model):
 
 
 def get_terminationstatus(model):
+    is_dirty = model.m_is_dirty
+    if is_dirty:
+        return TerminationStatusCode.OPTIMIZE_NOT_CALLED
     status = model.m_status
     if (
         status == ApplicationReturnStatus.Solve_Succeeded
@@ -511,6 +514,8 @@ def add_nl_objective(self, expr):
             self.graph_instance_to_index[graph] = graph_index
             self.graph_instances.append(graph)
 
+        self.m_is_dirty = True
+
     def optimize(self):
         self._find_similar_graphs()
         self._compile_evaluators()

tests/test_nlp.py

@@ -80,7 +80,8 @@ def test_easy_nlp(nlp_model_ctor):
 
 
 def test_nlfunc_ifelse(nlp_model_ctor):
-    if nlp_model_ctor is not ipopt.Model:
+    model = nlp_model_ctor()
+    if not isinstance(model, ipopt.Model):
         pytest.skip("ifelse is only supported in IPOPT")
 
     for x_, fx in zip([0.2, 0.5, 1.0, 2.0, 3.0], [0.2, 0.5, 1.0, 4.0, 9.0]):
@@ -100,6 +101,53 @@ def test_nlfunc_ifelse(nlp_model_ctor):
         assert x_value == pytest.approx(x_)
 
 
+def test_ipopt_optimizer_not_called():
+    model = ipopt.Model()
+
+    x = model.add_variable(lb=0.0, ub=10.0)
+    termination_status = model.get_model_attribute(poi.ModelAttribute.TerminationStatus)
+    assert termination_status == poi.TerminationStatusCode.OPTIMIZE_NOT_CALLED
+
+    model.set_objective(x**2)
+    model.optimize()
+    termination_status = model.get_model_attribute(poi.ModelAttribute.TerminationStatus)
+    assert termination_status == poi.TerminationStatusCode.LOCALLY_SOLVED
+
+    model.add_linear_constraint(x >= 0.5)
+    termination_status = model.get_model_attribute(poi.ModelAttribute.TerminationStatus)
+    assert termination_status == poi.TerminationStatusCode.OPTIMIZE_NOT_CALLED
+
+    model.optimize()
+    termination_status = model.get_model_attribute(poi.ModelAttribute.TerminationStatus)
+    assert termination_status == poi.TerminationStatusCode.LOCALLY_SOLVED
+
+    model.add_quadratic_constraint(x**2 >= 0.36)
+    termination_status = model.get_model_attribute(poi.ModelAttribute.TerminationStatus)
+    assert termination_status == poi.TerminationStatusCode.OPTIMIZE_NOT_CALLED
+
+    model.optimize()
+    termination_status = model.get_model_attribute(poi.ModelAttribute.TerminationStatus)
+    assert termination_status == poi.TerminationStatusCode.LOCALLY_SOLVED
+
+    with nl.graph():
+        model.add_nl_constraint(nl.exp(x) <= 100.0)
+    termination_status = model.get_model_attribute(poi.ModelAttribute.TerminationStatus)
+    assert termination_status == poi.TerminationStatusCode.OPTIMIZE_NOT_CALLED
+
+    model.optimize()
+    termination_status = model.get_model_attribute(poi.ModelAttribute.TerminationStatus)
+    assert termination_status == poi.TerminationStatusCode.LOCALLY_SOLVED
+
+    with nl.graph():
+        model.add_nl_objective(nl.log(x))
+    termination_status = model.get_model_attribute(poi.ModelAttribute.TerminationStatus)
+    assert termination_status == poi.TerminationStatusCode.OPTIMIZE_NOT_CALLED
+
+    model.optimize()
+    termination_status = model.get_model_attribute(poi.ModelAttribute.TerminationStatus)
+    assert termination_status == poi.TerminationStatusCode.LOCALLY_SOLVED
+
+
 if __name__ == "__main__":
 
     def c():