/**
* Allows to dump the search lattice in case it is needed.
* Note that, in this code we do not care if in case of an
* error we do not close the files. This is because lattice
* dumping is only needed while model training, plus it should
* work without throwing any errors. So if it happens then
* it is not a big problem.
* @param de_params the decoder parameters
*/
inline void dump_search_lattice(const de_parameters & de_params) const {
LOG_DEBUG1 << "Dumping the search lattice for the translation task " << m_task_id << END_LOG;
//Create the file names, we do not add the session id and job id as
//the tasks in training mode are issued unique task ids.
const string file_name = de_params.m_lattices_folder + "/" + to_string(m_task_id) + ".";
const string scores_file_name = file_name + de_params.m_scores_file_ext;
const string lattice_file_name = file_name + de_params.m_lattice_file_ext;
//Open the output stream to the files
ofstream scores_file(scores_file_name), lattice_file(lattice_file_name);
try {
//Check that the files are open
ASSERT_CONDITION_THROW(!scores_file.is_open(), string("Could not open: ") +
scores_file_name + string(" for writing"));
ASSERT_CONDITION_THROW(!lattice_file.is_open(), string("Could not open: ") +
lattice_file_name + string(" for writing"));
//Call the sentence decoder to do dumping.
m_decoder.dump_search_lattice(lattice_file, scores_file);
} catch (std::exception & ex) {
//Close the lattice files
LOG_ERROR << ex.what() << END_LOG;
close_lattice_files(scores_file, lattice_file);
//Re-throw an exception, do not use the exception object as it would
//create a copy of it loosing all needed additional information.
throw;
}
//Close the lattice files
close_lattice_files(scores_file, lattice_file);
}
int main(int argc, char *argv[]) {
std::string solver_name(rokko::serial_dense_solver::default_solver());
std::string lattice_file("xyz.dat");
if (argc >= 2) solver_name = argv[1];
if (argc >= 3) lattice_file = argv[2];
std::cout.precision(5);
int num_sites;
std::vector<std::pair<int, int> > lattice;
std::vector<boost::tuple<double, double, double> > coupling;
rokko::read_lattice_file(lattice_file, num_sites, lattice, coupling);
int dim = 1 << num_sites;
rokko::serial_dense_solver solver(solver_name);
solver.initialize(argc, argv);
std::cout << "Eigenvalue decomposition of XYZ model" << std::endl
<< "solver = " << solver_name << std::endl
<< "lattice file = " << lattice_file << std::endl
<< "number of sites = " << num_sites << std::endl
<< "number of bonds = " << lattice.size() << std::endl
<< "matrix dimension = " << dim << std::endl;
rokko::localized_matrix<double, matrix_major> mat(dim, dim);
rokko::xyz_hamiltonian::generate(num_sites, lattice, coupling, mat);
rokko::localized_vector<double> eigval(dim);
rokko::localized_matrix<double, matrix_major> eigvec(dim, dim);
try {
solver.diagonalize(mat, eigval, eigvec);
}
catch (const char *e) {
std::cout << "Exception : " << e << std::endl;
exit(22);
}
rokko::xyz_hamiltonian::generate(num_sites, lattice, coupling, mat);
std::cout << "smallest eigenvalues:";
for (int i = 0; i < std::min(dim, 10); ++i) std::cout << ' ' << eigval(i);
std::cout << std::endl;
std::cout << "residual of the smallest eigenvalue/vector: |x A x - lambda| = "
<< std::abs(eigvec.col(0).transpose() * mat * eigvec.col(0) - eigval(0))
<< std::endl;
solver.finalize();
}
