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

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Merged
metab0t merged 2 commits into from
Feb 13, 2026
Merged

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

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020cc7b
feat: add symmetric Hessian pattern support.
eminyouskn Feb 12, 2026
ee342a7
use refs to avoid unnecessary copy
eminyouskn Feb 12, 2026
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26 changes: 18 additions & 8 deletions include/pyoptinterface/knitro_model.hpp
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Original file line number Diff line number Diff line change
Expand Up @@ -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_;

Expand Down Expand Up @@ -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)
Expand Down Expand Up @@ -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];
Expand All @@ -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];
Expand All @@ -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++)
Expand All @@ -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]]);
Expand Down