Expresses requirements for sparse matrix backends like DynMatrix.
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#include <modular_linalg.H>
template<typename T>
{
{
m.rows() } -> std::convertible_to<size_t>;
{
m.cols() } -> std::convertible_to<size_t>;
{
m.read_ne(
r, c) } -> std::convertible_to<uint64_t>;
{
mut_m.traverse_allocated([](
uint64_t &) {
return true; }) } -> std::convertible_to<bool>;
{
mut_m.set_dimension(
r, c) };
}
Expresses requirements for sparse matrix backends like DynMatrix.
Divide_Conquer_DP_Result< Cost > divide_and_conquer_partition_dp(const size_t groups, const size_t n, Transition_Cost_Fn transition_cost, const Cost inf=dp_optimization_detail::default_inf< Cost >())
Optimize partition DP using divide-and-conquer optimization.
std::decay_t< typename HeadC::Item_Type > T
FooMap m(5, fst_unit_pair_hash, snd_unit_pair_hash)
Expresses requirements for sparse matrix backends like DynMatrix.
Definition at line 62 of file modular_linalg.H.