Function bind_svm_rank_trainer

tools/python/src/svm_rank_trainer.cpp:123–158

// ----------------------------------------------------------------------------------------

void bind_svm_rank_trainer(py::module& m)
{
    py::class_<ranking_pair<sample_type> >(m, "ranking_pair")
        .def(py::init())
        .def_readwrite("relevant", &ranking_pair<sample_type>::relevant)
        .def_readwrite("nonrelevant", &ranking_pair<sample_type>::nonrelevant)
        .def(py::pickle(&getstate<ranking_pair<sample_type>>, &setstate<ranking_pair<sample_type>>));

    py::class_<ranking_pair<sparse_vect> >(m, "sparse_ranking_pair")
        .def(py::init())
        .def_readwrite("relevant", &ranking_pair<sparse_vect>::relevant)
        .def_readwrite("nonrelevant", &ranking_pair<sparse_vect>::nonrelevant)
        .def(py::pickle(&getstate<ranking_pair<sparse_vect>>, &setstate<ranking_pair<sparse_vect>>));

    py::bind_vector<ranking_pairs>(m, "ranking_pairs")
        .def("clear", &ranking_pairs::clear)
        .def("resize", resize<ranking_pairs>)
        .def("extend", extend_vector_with_python_list<ranking_pair<sample_type>>)
        .def(py::pickle(&getstate<ranking_pairs>, &setstate<ranking_pairs>));

    py::bind_vector<sparse_ranking_pairs>(m, "sparse_ranking_pairs")
        .def("clear", &sparse_ranking_pairs::clear)
        .def("resize", resize<sparse_ranking_pairs>)
        .def("extend", extend_vector_with_python_list<ranking_pair<sparse_vect>>)
        .def(py::pickle(&getstate<sparse_ranking_pairs>, &setstate<sparse_ranking_pairs>));

    add_ranker<svm_rank_trainer<linear_kernel<sample_type> > >(m, "svm_rank_trainer");
    add_ranker<svm_rank_trainer<sparse_linear_kernel<sparse_vect> > >(m, "svm_rank_trainer_sparse");

    m.def("cross_validate_ranking_trainer", &_cross_ranking_validate_trainer<
                svm_rank_trainer<linear_kernel<sample_type> >,sample_type>,
                py::arg("trainer"), py::arg("samples"), py::arg("folds") );
    m.def("cross_validate_ranking_trainer", &_cross_ranking_validate_trainer<
                svm_rank_trainer<sparse_linear_kernel<sparse_vect> > ,sparse_vect>,
                py::arg("trainer"), py::arg("samples"), py::arg("folds") );
}