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#include <iostream>
#include <fstream>
#include <vector>
#include <boost/lexical_cast.hpp>
#include <boost/program_options.hpp>
#include "filelib.h"
#include "tdict.h"
#include "prob.h"
#include "hg.h"
#include "hg_io.h"
#include "viterbi.h"
#include "kbest.h"
namespace po = boost::program_options;
using namespace std;
void InitCommandLine(int argc, char** argv, po::variables_map* conf) {
po::options_description opts("Configuration options");
opts.add_options()
("input,i", po::value<string>(), "REQ. Lattice input file (PLF), - for STDIN")
("prior_scale,p", po::value<double>()->default_value(1.0), "Scale path probabilities by this amount < 1 flattens, > 1 sharpens")
("weight,w", po::value<vector<double> >(), "Weight(s) for arc features")
("output,o", po::value<string>()->default_value("plf"), "Output format (text, plf)")
("command,c", po::value<string>()->default_value("push"), "Operation to perform: push, graphviz, 1best, 2best ...")
("help,h", "Print this help message and exit");
po::options_description clo("Command line options");
po::options_description dcmdline_options;
dcmdline_options.add(opts);
po::store(parse_command_line(argc, argv, dcmdline_options), *conf);
po::notify(*conf);
if (conf->count("help") || conf->count("input") == 0) {
cerr << dcmdline_options << endl;
exit(1);
}
}
int main(int argc, char **argv) {
po::variables_map conf;
InitCommandLine(argc, argv, &conf);
string infile = conf["input"].as<string>();
ReadFile rf(infile);
istream* in = rf.stream();
assert(*in);
SparseVector<double> wts;
vector<double> wv;
if (conf.count("weight") > 0) wv = conf["weight"].as<vector<double> >();
if (wv.empty()) wv.push_back(1.0);
for (int i = 0; i < wv.size(); ++i) {
const string fname = "Feature_" + boost::lexical_cast<string>(i);
cerr << "[INFO] Arc weight " << (i+1) << " = " << wv[i] << endl;
wts.set_value(FD::Convert(fname), wv[i]);
}
const string cmd = conf["command"].as<string>();
const bool push_weights = cmd == "push";
const bool output_plf = cmd == "plf";
const bool graphviz = cmd == "graphviz";
const bool kbest = cmd.rfind("best") == (cmd.size() - 4) && cmd.size() > 4;
int k = 1;
if (kbest) {
k = boost::lexical_cast<int>(cmd.substr(0, cmd.size() - 4));
cerr << "KBEST = " << k << endl;
}
const double scale = conf["prior_scale"].as<double>();
int lc = 0;
while(*in) {
++lc;
string plf;
getline(*in, plf);
if (plf.empty()) continue;
Hypergraph hg;
HypergraphIO::ReadFromPLF(plf, &hg);
hg.Reweight(wts);
if (graphviz) hg.PrintGraphviz();
if (push_weights) hg.PushWeightsToSource(scale);
if (output_plf) {
cout << HypergraphIO::AsPLF(hg) << endl;
} else {
KBest::KBestDerivations<vector<WordID>, ESentenceTraversal> kbest(hg, k);
for (int i = 0; i < k; ++i) {
const KBest::KBestDerivations<vector<WordID>, ESentenceTraversal>::Derivation* d =
kbest.LazyKthBest(hg.nodes_.size() - 1, i);
if (!d) break;
cout << lc << " ||| " << TD::GetString(d->yield) << " ||| " << d->score << endl;
}
}
}
return 0;
}
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