/* funcao responsavel pela montagem do arquivo. Une todos processos. */
void mount(char* fileFrom, char* fileTo) {
set_table s_table;
label_table l_table = build_labels(fileFrom, &s_table);
print_file(fileFrom, fileTo, l_table, s_table);
free_tables(s_table, l_table);
}
void Postagger::test(void) {
const char * model_file = test_opt.model_file.c_str();
ifstream mfs(model_file, std::ifstream::binary);
if (!mfs) {
ERROR_LOG("Failed to load model");
return;
}
model = new Model;
if (!model->load(mfs)) {
ERROR_LOG("Failed to load model");
return;
}
TRACE_LOG("Number of labels [%d]", model->num_labels());
TRACE_LOG("Number of features [%d]", model->space.num_features());
TRACE_LOG("Number of dimension [%d]", model->space.dim());
const char * test_file = test_opt.test_file.c_str();
ifstream ifs(test_file);
if (!ifs) {
ERROR_LOG("Failed to open holdout file.");
return;
}
decoder = new Decoder(model->num_labels());
PostaggerReader reader(ifs, true);
PostaggerWriter writer(cout);
Instance * inst = NULL;
int num_recalled_tags = 0;
int num_tags = 0;
double before = get_time();
while ((inst = reader.next())) {
int len = inst->size();
inst->tagsidx.resize(len);
for (int i = 0; i < len; ++ i) {
inst->tagsidx[i] = model->labels.index(inst->tags[i]);
}
extract_features(inst);
calculate_scores(inst, true);
decoder->decode(inst);
build_labels(inst, inst->predicted_tags);
writer.write(inst);
num_recalled_tags += inst->num_corrected_predicted_tags();
num_tags += inst->size();
delete inst;
}
double after = get_time();
double p = (double)num_recalled_tags / num_tags;
TRACE_LOG("P: %lf ( %d / %d )", p, num_recalled_tags, num_tags);
TRACE_LOG("Eclipse time %lf", after - before);
sleep(1000000);
return;
}