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#include <iostream>
#include <vector>
#include <boost/program_options.hpp>
#include <boost/functional/hash.hpp>
#ifndef HAVE_OLD_CPP
# include <unordered_map>
#else
# include <tr1/unordered_map>
namespace std { using std::tr1::unordered_map; }
#endif
#include "prob.h"
#include "tdict.h"
#include "ns.h"
#include "filelib.h"
#include "stringlib.h"
using namespace std;
namespace po = boost::program_options;
void InitCommandLine(int argc, char** argv, po::variables_map* conf) {
po::options_description opts("Configuration options");
opts.add_options()
("input,i",po::value<vector<string> >(), "Files to read k-best lists from")
("scale,a",po::value<vector<double> >(), "Posterior scaling factors (per file)")
("offset,b",po::value<vector<double> >(), "Log posterior offsets (per file)")
("evaluation_metric,m",po::value<string>()->default_value("ibm_bleu"), "Evaluation metric")
("output_list,L", "Show reranked list as output")
("help,h", "Help");
po::options_description dcmdline_options;
dcmdline_options.add(opts);
po::store(parse_command_line(argc, argv, dcmdline_options), *conf);
bool flag = false;
if (flag || conf->count("help")) {
cerr << dcmdline_options << endl;
exit(1);
}
}
struct ScoreComparer {
bool operator()(const pair<vector<WordID>, prob_t>& a, const pair<vector<WordID>, prob_t>& b) const {
return a.second > b.second;
}
};
struct LossComparer {
bool operator()(const pair<vector<WordID>, prob_t>& a, const pair<vector<WordID>, prob_t>& b) const {
return a.second < b.second;
}
};
bool ReadKBestList(const vector<double>& mbr_scale,
const vector<double>& mbr_offset,
const vector<ReadFile*>& rfs,
string* sent_id,
vector<pair<vector<WordID>, prob_t> >* list) {
static string cache_id;
pair<vector<WordID>, prob_t> tmp_pair;
static vector<pair<vector<WordID>, prob_t> > cache_pair(rfs.size());
list->clear();
string cur_id;
if (cache_pair[0].first.size() > 0) {
for (unsigned i = 0; i < cache_pair.size(); ++i)
list->push_back(cache_pair[i]);
cur_id = cache_id;
cache_pair.clear();
cache_pair.resize(rfs.size());
}
string line;
string tstr;
for (unsigned fi = 0; fi < rfs.size(); ++fi) {
istream& in = *rfs[fi]->stream();
while(getline(in, line)) {
size_t p1 = line.find(" ||| ");
if (p1 == string::npos) { cerr << "Bad format: " << line << endl; abort(); }
size_t p2 = line.find(" ||| ", p1 + 4);
if (p2 == string::npos) { cerr << "Bad format: " << line << endl; abort(); }
size_t p3 = line.rfind(" ||| ");
cache_id = line.substr(0, p1);
tstr = line.substr(p1 + 5, p2 - p1 - 5);
double val = strtod(line.substr(p3 + 5).c_str(), NULL) * mbr_scale[fi] + mbr_offset[fi];
TD::ConvertSentence(tstr, &tmp_pair.first);
tmp_pair.second.logeq(val);
if (cur_id.empty()) cur_id = cache_id;
if (cur_id == cache_id) {
list->push_back(tmp_pair);
*sent_id = cur_id;
tmp_pair.first.clear();
} else {
swap(cache_pair[fi], tmp_pair);
break;
}
}
}
sort(list->begin(), list->end(), ScoreComparer());
// for (unsigned i = 0; i < list->size(); ++i) {
// cerr << TD::GetString((*list)[i].first) << " ||| " << (*list)[i].second << endl;
//}
//cerr << endl;
return !list->empty();
}
int main(int argc, char** argv) {
po::variables_map conf;
InitCommandLine(argc, argv, &conf);
const string smetric = conf["evaluation_metric"].as<string>();
EvaluationMetric* metric = EvaluationMetric::Instance(smetric);
const bool is_loss = (UppercaseString(smetric) == "TER");
const bool output_list = conf.count("output_list") > 0;
vector<string> file;
if (conf.count("input") == 0)
file.push_back("-");
else
file = conf["input"].as<vector<string> >();
vector<double> mbr_scale;
if (conf.count("scale")) mbr_scale = conf["scale"].as<vector<double> >();
vector<double> mbr_offset;
if (conf.count("offset")) mbr_offset = conf["offset"].as<vector<double> >();
if (file.size() > mbr_scale.size()) mbr_scale.resize(file.size(), 1.0);
if (file.size() > mbr_offset.size()) mbr_offset.resize(file.size(), 0.0);
if (file.size() != mbr_scale.size()) {
cerr << file.size() << " files specified but " << mbr_scale.size() << " scale factors given!\n";
return 1;
}
if (file.size() != mbr_offset.size()) {
cerr << file.size() << " files specified but " << mbr_offset.size() << " scale factors given!\n";
return 1;
}
for (unsigned i = 0; i < file.size(); ++i)
cerr << "Kbest file " << (i+1) << ": " << file[i] << "\t(scale=" << mbr_scale[i] << ", offset=" << mbr_offset[i] << ")\n";
vector<pair<vector<WordID>, prob_t> > list;
vector<ReadFile*> rfs(file.size());
for (unsigned i = 0; i < file.size(); ++i)
rfs[i] = new ReadFile(file[i]);
string sent_id;
while(ReadKBestList(mbr_scale, mbr_offset, rfs, &sent_id, &list)) {
vector<prob_t> joints(list.size());
const prob_t max_score = list.front().second;
prob_t marginal = prob_t::Zero();
for (int i = 0 ; i < list.size(); ++i) {
const prob_t joint = list[i].second / max_score;
joints[i] = joint;
//cerr << "list[" << i << "] joint=" << log(joint) << endl;
marginal += joint;
}
int mbr_idx = -1;
vector<double> mbr_scores(output_list ? list.size() : 0);
double mbr_loss = numeric_limits<double>::max();
for (int i = 0 ; i < list.size(); ++i) {
const vector<vector<WordID> > refs(1, list[i].first);
boost::shared_ptr<SegmentEvaluator> segeval = metric->
CreateSegmentEvaluator(refs);
double wl_acc = 0;
for (int j = 0; j < list.size(); ++j) {
if (i != j) {
SufficientStats ss;
segeval->Evaluate(list[j].first, &ss);
double loss = 1.0 - metric->ComputeScore(ss);
if (is_loss) loss = 1.0 - loss;
double weighted_loss = loss * (joints[j] / marginal).as_float();
wl_acc += weighted_loss;
if ((!output_list) && wl_acc > mbr_loss) break;
}
}
if (output_list) mbr_scores[i] = wl_acc;
if (wl_acc < mbr_loss) {
mbr_loss = wl_acc;
mbr_idx = i;
}
}
// cerr << "ML translation: " << TD::GetString(list[0].first) << endl;
cerr << "MBR Best idx: " << mbr_idx << endl;
if (output_list) {
for (int i = 0; i < list.size(); ++i)
list[i].second.logeq(mbr_scores[i]);
sort(list.begin(), list.end(), LossComparer());
for (int i = 0; i < list.size(); ++i)
cout << sent_id << " ||| "
<< TD::GetString(list[i].first) << " ||| "
<< log(list[i].second) << endl;
} else {
cout << TD::GetString(list[mbr_idx].first) << endl;
}
}
return 0;
}
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