char const* NOTES = "ZF_and_E means unnormalized scaled features.\n" "For grammars with one nonterminal: F_and_E is joint,\n" "F_given_E and E_given_F are conditional.\n" "TODO: group rules by root nonterminal and then normalize.\n"; #include #include #include #include #include #include #include "prob.h" #include "filelib.h" #include "trule.h" #include "weights.h" namespace po = boost::program_options; using namespace std; typedef std::tr1::unordered_map, prob_t, boost::hash > > MarginalMap; void InitCommandLine(int argc, char** argv, po::variables_map* conf) { po::options_description opts("Configuration options"); opts.add_options() ("grammar,g", po::value(), "Grammar file") ("weights,w", po::value(), "Weights file") ("unnormalized,u", "Always include ZF_and_E unnormalized score (default: only if sum was >1)") ; po::options_description clo("Command line options"); clo.add_options() ("config,c", po::value(), "Configuration file") ("help,h", "Print this help message and exit"); po::options_description dconfig_options, dcmdline_options; dconfig_options.add(opts); dcmdline_options.add(opts).add(clo); po::store(parse_command_line(argc, argv, dcmdline_options), *conf); if (conf->count("config")) { const string cfg = (*conf)["config"].as(); cerr << "Configuration file: " << cfg << endl; ifstream config(cfg.c_str()); po::store(po::parse_config_file(config, dconfig_options), *conf); } po::notify(*conf); if (conf->count("help") || !conf->count("grammar") || !conf->count("weights")) { cerr << dcmdline_options << endl; cerr << NOTES << endl; exit(1); } } int main(int argc, char** argv) { po::variables_map conf; InitCommandLine(argc, argv, &conf); const string wfile = conf["weights"].as(); const string gfile = conf["grammar"].as(); vector w; Weights::InitFromFile(wfile, &w); MarginalMap e_tots; MarginalMap f_tots; prob_t tot; { ReadFile rf(gfile); assert(*rf.stream()); istream& in = *rf.stream(); cerr << "Computing marginals...\n"; int lc = 0; while(in) { string line; getline(in, line); ++lc; if (line.empty()) continue; TRule tr(line, true); if (tr.GetFeatureValues().empty()) cerr << "Line " << lc << ": empty features - may introduce bias\n"; prob_t prob; prob.logeq(tr.GetFeatureValues().dot(w)); e_tots[tr.e_] += prob; f_tots[tr.f_] += prob; tot += prob; } } bool normalized = (fabs(log(tot)) < 0.001); cerr << "Total: " << tot << (normalized ? " [normalized]" : " [scaled]") << endl; ReadFile rf(gfile); istream&in = *rf.stream(); while(in) { string line; getline(in, line); if (line.empty()) continue; TRule tr(line, true); const double lp = tr.GetFeatureValues().dot(w); if (std::isinf(lp)) { continue; } tr.scores_.clear(); cout << tr.AsString() << " ||| F_and_E=" << lp - log(tot); if (!normalized || conf.count("unnormalized")) { cout << ";ZF_and_E=" << lp; } cout << ";F_given_E=" << lp - log(e_tots[tr.e_]) << ";E_given_F=" << lp - log(f_tots[tr.f_]) << endl; } return 0; }