[KNITRO] Use reduced hessian pattern for hessian evaluations (#76)

* feat: add symmetric Hessian pattern support.

* use refs to avoid unnecessary copy

Author: eminyouskn

include/pyoptinterface/knitro_model.hpp

@@ -142,6 +142,7 @@ struct CallbackEvaluator
 	CppAD::sparse_rcv<std::vector<size_t>, std::vector<V>> jac_;
 	CppAD::sparse_jac_work jac_work_;
 	CppAD::sparse_rc<std::vector<size_t>> hess_pattern_;
+	CppAD::sparse_rc<std::vector<size_t>> hess_pattern_symm_;
 	CppAD::sparse_rcv<std::vector<size_t>, std::vector<V>> hess_;
 	CppAD::sparse_hes_work hess_work_;
 
@@ -171,10 +172,19 @@ struct CallbackEvaluator
 			select_rows[fun_rows[k]] = true;
 		}
 		fun.rev_hes_sparsity(select_rows, false, true, hess_pattern_);
+		for (size_t k = 0; k < hess_pattern_.nnz(); k++)
+		{
+			size_t row = hess_pattern_.row()[k];
+			size_t col = hess_pattern_.col()[k];
+			if (row <= col)
+			{
+				hess_pattern_symm_.push_back(row, col);
+			}
+		}
 		x.resize(fun.Domain(), 0.0);
 		w.resize(fun.Range(), 0.0);
 		jac_ = CppAD::sparse_rcv<std::vector<size_t>, std::vector<V>>(jac_pattern_);
-		hess_ = CppAD::sparse_rcv<std::vector<size_t>, std::vector<V>>(hess_pattern_);
+		hess_ = CppAD::sparse_rcv<std::vector<size_t>, std::vector<V>>(hess_pattern_symm_);
 	}
 
 	void eval_fun(const V *req_x, V *res_y, bool aggregate = false)
@@ -204,7 +214,7 @@ struct CallbackEvaluator
 			x[i] = req_x[indexVars[i]];
 		}
 		fun.sparse_jac_rev(x, jac_, jac_pattern_, jac_coloring_, jac_work_);
-		auto jac = jac_.val();
+		auto& jac = jac_.val();
 		for (size_t i = 0; i < jac_.nnz(); i++)
 		{
 			res_jac[i] = jac[i];
@@ -229,7 +239,7 @@ struct CallbackEvaluator
 			}
 		}
 		fun.sparse_hes(x, w, hess_, hess_pattern_, hess_coloring_, hess_work_);
-		auto hess = hess_.val();
+		auto& hess = hess_.val();
 		for (size_t i = 0; i < hess_.nnz(); i++)
 		{
 			res_hess[i] = hess[i];
@@ -241,8 +251,8 @@ struct CallbackEvaluator
 		CallbackPattern pattern;
 		pattern.indexCons = indexCons;
 
-		auto jac_rows = jac_pattern_.row();
-		auto jac_cols = jac_pattern_.col();
+		auto& jac_rows = jac_pattern_.row();
+		auto& jac_cols = jac_pattern_.col();
 		if (indexCons.empty())
 		{
 			for (size_t k = 0; k < jac_pattern_.nnz(); k++)
@@ -259,9 +269,9 @@ struct CallbackEvaluator
 			}
 		}
 
-		auto hess_rows = hess_pattern_.row();
-		auto hess_cols = hess_pattern_.col();
-		for (size_t k = 0; k < hess_pattern_.nnz(); k++)
+		auto& hess_rows = hess_pattern_symm_.row();
+		auto& hess_cols = hess_pattern_symm_.col();
+		for (size_t k = 0; k < hess_pattern_symm_.nnz(); k++)
 		{
 			pattern.hessIndexVars1.push_back(indexVars[hess_rows[k]]);
 			pattern.hessIndexVars2.push_back(indexVars[hess_cols[k]]);