void Eval::doBP() {
XenOption* opt = XenOption::getInstance();
double lower = 999999999999;
int lBound = 0;
int hBound = 0;
for(EvalMap::iterator it = ptrDist->begin() ; it != ptrDist->end() ; ++it)
if (it->second < lower) {
lower = it->second;
EvalMap::iterator itH = it;
if (it != ptrDist->begin())
--itH;
EvalMap::iterator itL = it;
if (it != ptrDist->end())
++itL;
lBound = itL->first;
hBound = itH->first;
if (lBound > it->first) { lBound = 0; }
if (hBound < it->first) { hBound = opt->getMaxEvalPC(); }
}
opt->setStep(opt->getStep() / 2);
std::cout << "Requiring eval from " + XenCommon::toString(hBound) + " to " + XenCommon::toString(lBound) + " with step " + XenCommon::toString(opt->getStep()) << std::endl;
doEval(hBound, lBound);
if (opt->getStep() > 1) {
doBP();
}
}
int main(int argc, char* argv[]) {
po::options_description desc("XenC options", 200);
Options opt;
try {
desc.add_options()
("source,s", po::value<std::string>(&opt.sLang)->required(), "source language (fr, en, ...)")
("target,t", po::value<std::string>(&opt.tLang)->default_value(""), "target language (if relevant)")
("in-stext,i", po::value<std::string>(&opt.inSData)->required(), "in-domain source text filename (plain text or gzipped file)")
("out-stext,o", po::value<std::string>(&opt.outSData)->required(), "out-of-domain source text filename (plain text or gzipped file)")
("mode,m", po::value<int>(&opt.mode)->required()->default_value(2), "filtering mode (1, 2, 3 or 4). Default is 2 (monolingual cross-entropy)")
("eval,e", po::value<bool>(&opt.eval)->zero_tokens()->default_value(false), "add this switch to evaluate a filtered file after computation. Eval is always done on source language")
("best-point,b", po::value<bool>(&opt.bp)->zero_tokens()->default_value(false), "add this switch to determinate the best point of a filtered file (eval option is implicit)")
("dev,d", po::value<std::string>(&opt.dev)->default_value(""), "source language dev file for eval or best point (all modes), if different from in-domain text")
("in-ttext", po::value<std::string>(&opt.inTData)->default_value(""), "in-domain target text filename, if target language (plain text or gzipped file)")
("out-ttext", po::value<std::string>(&opt.outTData)->default_value(""), "out-of-domain target text filename, if target language (plain text or gzipped file)")
("mono", po::value<bool>(&opt.mono)->zero_tokens()->default_value(false), "switch to force monolingual mode (if no target language)")
("stem", po::value<bool>(&opt.stem)->zero_tokens()->default_value(false), "switch to activate stem models computation and scoring from stem files")
("in-sstem", po::value<std::string>(&opt.inSStem)->default_value(""), "in-domain source stem filename (plain text or gzipped file)")
("in-tstem", po::value<std::string>(&opt.inTStem)->default_value(""), "in-domain target stem filename (plain text or gzipped file)")
("out-sstem", po::value<std::string>(&opt.outSStem)->default_value(""), "out-of-domain source stem filename (plain text or gzipped file)")
("out-tstem", po::value<std::string>(&opt.outTStem)->default_value(""), "out-of-domain target stem filename (plain text or gzipped file)")
("in-ptable", po::value<std::string>(&opt.iPTable)->default_value(""), "in-domain phrase table filename used in mode 4 scoring")
("out-ptable", po::value<std::string>(&opt.oPTable)->default_value(""), "out-of-domain phrase table filename used in mode 4 scoring")
("local", po::value<bool>(&opt.local)->zero_tokens()->default_value(false), "add a 7th score (local cross-entropy regarding the source phrase)")
("mean", po::value<bool>(&opt.mean)->zero_tokens()->default_value(false), "mean score from 3 OOD sample LMs instead of 1 in mode 2 & 3 (3 times slower + EXPERIMENTAL)")
("sim", po::value<bool>(&opt.sim)->zero_tokens()->default_value(false), "add similarity measures to score computing (EXPERIMENTAL, mode 2 only)")
("sim-only", po::value<bool>(&opt.simOnly)->zero_tokens()->default_value(false), "use only similarity measures (no cross-entropy)")
("vector-size", po::value<int>(&opt.vecSize)->default_value(150), "size of vector for similarity scores, default is 150 (WARNING: the more the slower)")
("step", po::value<int>(&opt.step)->default_value(10), "percentage steps for evaluation. Default is 10 (100%, 90%, ...)")
("s-vocab", po::value<std::string>(&opt.sVocab)->default_value(""), "source language vocab filename for LMs estimation. Default is in-domain source text vocab")
("t-vocab", po::value<std::string>(&opt.tVocab)->default_value(""), "target language vocab filename for LMs estimation. Default is in-domain target text vocab")
("full-vocab", po::value<bool>(&opt.fullVoc)->zero_tokens()->default_value(false), "use in-domain + out-of-domain vocabularies instead of in-domain only")
("in-slm", po::value<std::string>(&opt.inSLM)->default_value(""), "in-domain source language model (LM). Will be estimated if not present")
("out-slm", po::value<std::string>(&opt.outSLM)->default_value(""), "out-of-domain source language model (LM). Will be estimated if not present")
("in-tlm", po::value<std::string>(&opt.inTLM)->default_value(""), "in-domain target language model (LM). Will be estimated if not present")
("out-tlm", po::value<std::string>(&opt.outTLM)->default_value(""), "out-of-domain target language model (LM). Will be estimated if not present")
("order", po::value<int>(&opt.order)->default_value(4), "order for LMs. Default is 4")
("discount", po::value<int>(&opt.discount)->default_value(0), "discounting method for LM estimation. Default is modified KneserNey (0). 1 is GoodTuring, 2 is WittenBell.")
("to-lower", po::value<bool>(&opt.toLower)->default_value(false), "maps vocabulary to lower case for LM estimation. Useful for ASR. Default is false.")
("no-unkisword", po::value<bool>(&opt.noUnkIsWord)->default_value(false), "DO NOT consider <unk> and its probability as a word. Default is false, with respect to common practice.")
("bin-lm", po::value<int>(&opt.binLM)->default_value(1), "whether you want to estimate arpa.gz (0) or binary (1) LMs. Default is 1 (binary)")
("w-file", po::value<std::string>(&opt.wFile)->default_value(""), "filename for weighting the final score (one value per line)")
("log", po::value<bool>(&opt.log)->zero_tokens()->default_value(false), "switch to consider weights in w-file as log values")
("rev", po::value<bool>(&opt.rev)->zero_tokens()->default_value(false), "switch to require descending order sorted output")
("inv", po::value<bool>(&opt.inv)->zero_tokens()->default_value(false), "switch to require inversed calibrated scores (1 - score)")
("threads", po::value<int>(&opt.threads)->default_value(2), "number of threads to run for various operations (eval, sim, ...). Default is 2")
("sorted-only", po::value<bool>(&opt.sortOnly)->zero_tokens()->default_value(false), "switch to save space & time by only outputing the sorted scores file")
("help,h", "displays this help message")
("version,v", "displays program version");
po::variables_map vm;
try {
po::store(po::parse_command_line(argc, argv, desc), vm);
if (vm.count("help") || argc == 1) {
std::cout << "XenC version " + version + " PUBLIC RELEASE. Copyright 2013, Anthony Rousseau, LIUM, University of Le Mans, France." << std::endl << std::endl;
std::cout << desc << std::endl;
std::cout << "Filtering modes:" << std::endl << std::endl;
std::cout << "For all modes (excepted 4), you must provide at least a source language, and in-domain and out-of-domain bitexts. Bitexts MUST NOT contain tabs." << std::endl;
std::cout << "For every text file used, max words per line is 16384 and max chars per line is max words * 16." << std::endl << std::endl;
std::cout << "Also, if no vocabularies and no language models are provided, they will be generated with the following parameters:" << std::endl;
std::cout << "\t- vocabs:\tvocabularies will be created from words of in-domain bitexts." << std::endl;
std::cout << "\t- LMs:\t\torder 4, modified kn-int smoothing, 0-0-0-0 cut-offs, sblm (binary) output format." << std::endl << std::endl;
std::cout << "\t1:" << std::endl;
std::cout << "\tSimple source language perplexity filtering. (Gao & al. 2002)" << std::endl;
std::cout << "\tWill sort the out-of-domain bitext sentences (ascending order)" << std::endl;
std::cout << "\tbased on perplexity scores given by a in-domain language model." << std::endl << std::endl;
std::cout << "\t2:" << std::endl;
std::cout << "\tSource language cross-entropy (Xen) difference filtering. (Moore & Lewis 2010)" << std::endl;
std::cout << "\tWill sort the out-of-domain bitext sentences (ascending order)" << std::endl;
std::cout << "\tbased on (in-source Xen - out-source Xen)." << std::endl << std::endl;
std::cout << "\t3:" << std::endl;
std::cout << "\tBilingual cross-entropy difference filtering. (Axelrod & al. 2011)" << std::endl;
std::cout << "\tWill sort the out-of-domain bitext sentences (ascending order)" << std::endl;
std::cout << "\tbased on (in-source Xen - out-source Xen) + (in-target Xen - out-target Xen)." << std::endl << std::endl;
std::cout << "\t4:" << std::endl;
std::cout << "\tPhrase-table scoring mode. (EXPERIMENTAL)" << std::endl;
std::cout << "\tAdds the cross-entropy score of each phrase pair" << std::endl;
std::cout << "\tin a phrase-table as a sixth feature of the table." << std::endl << std::endl;
std::cout << "\tYou must provide:" << std::endl;
std::cout << "\t\t- in-domain and out-of-domain phrase tables." << std::endl;
std::cout << "\t\t- source and target vocabularies." << std::endl << std::endl;
return 0;
}
if (vm.count("version")) {
std::cout << "XenC version " + version + " PUBLIC RELEASE. Copyright 2013, Anthony Rousseau, LIUM, University of Le Mans, France." << std::endl;
return 0;
}
po::notify(vm);
} catch (po::error& e) {
std::cout << desc << std::endl;
std::cout << e.what() << std::endl;
}
} catch (std::exception& e) {
std::cout << desc << std::endl;
std::cout << e.what() << std::endl;
}
opt.pc = 0;
opt.inToks = 0;
opt.outToks = 0;
if (opt.dev.compare("") == 0) {
if (boost::filesystem::exists(opt.inSData)) {
opt.dev = opt.inSData;
}
else {
std::cerr << "You must at least specify a source in-domain corpus." << std::endl;
return 1;
}
}
// -----------------------------------------------------
// Create singletons & mode
XenOption* xOpt = XenOption::getInstance(&opt);
StaticData* sD = StaticData::getInstance();
boost::shared_ptr<Mode> mode;
switch (xOpt->getMode()) {
case 1:
mode = boost::make_shared<SimplePPL>();
break;
case 2:
mode = boost::make_shared<MonoXEntropy>();
break;
case 3:
mode = boost::make_shared<BiXEntropy>();
break;
case 4:
mode = boost::make_shared<PTScoring>();
break;
default:
break;
}
// -----------------------------------------------------
opt.outName = getOutName(xOpt);
std::string sC = sanityCheck(xOpt); // Check if all mandatory are here
// -----------------------------------------------------
// LAST CHECK BEFORE OPERATIONS
if (sC.compare("0") == 0) {
std::cout << "Source language: " << opt.sLang << std::endl;
if (!opt.mono) { std::cout << "Target language: " << opt.tLang << std::endl; }
if (opt.mode != 4) {
std::cout << "In-domain source data: " << opt.inSData << std::endl;
std::cout << "Out-of-domain source data: " << opt.outSData << std::endl;
if (opt.stem) {
std::cout << "In-domain source stem file: " << opt.inSStem << std::endl;
std::cout << "Out-of-domain source stem file: " << opt.outSStem << std::endl;
}
if (!opt.mono) {
std::cout << "In-domain target data: " << opt.inTData << std::endl;
std::cout << "Out-of-domain target data: " << opt.outTData << std::endl;
if (opt.stem) {
std::cout << "In-domain target stem file: " << opt.inTStem << std::endl;
std::cout << "Out-of-domain target stem file: " << opt.outTStem << std::endl;
}
}
}
else {
std::cout << "Source vocabulary: " << opt.sVocab << std::endl;
std::cout << "Target vocabulary: " << opt.tVocab << std::endl;
std::cout << "In-domain phrase table: " << opt.iPTable << std::endl;
std::cout << "Out-of-domain phrase table: " << opt.oPTable << std::endl;
std::cout << "Output phrase table: " << opt.outName << std::endl;
}
std::cout << "Mode: " << opt.mode << std::endl;
}
else {
std::cerr << std::endl << sC << std::endl;
sD->deleteInstance();
xOpt->deleteInstance();
return 1;
}
// -----------------------------------------------------
try {
// Normal mode
if (!xOpt->getEval()&& !xOpt->getBp()) {
int ret = mode->launch();
if (ret == 0) {
xOpt->deleteInstance();
sD->deleteInstance();
return 0;
}
else {
std::cerr << "Something went wrong." << std::endl;
xOpt->deleteInstance();
sD->deleteInstance();
return 1;
}
}
// Eval or BP
else {
std::string sortedName = xOpt->getOutName() + ".sorted.gz";
std::string distName = xOpt->getOutName() + ".dist";
std::string bpName = xOpt->getOutName() + ".bp";
std::cout << "Sorted output used: " + sortedName << std::endl;
// -----------------------------------------------------
// Proceed to normal mode if not done before
if (!boost::filesystem::exists(sortedName)) {
int ret = mode->launch();
if (ret != 0) {
std::cerr << "Something went wrong." << std::endl;
xOpt->deleteInstance();
sD->deleteInstance();
return 1;
}
}
// -----------------------------------------------------
boost::shared_ptr<XenFile> sorted = boost::make_shared<XenFile>();
sorted->initialize(sortedName);
sD->getXenResult()->initialize(sorted);
sD->getDevCorp()->initialize(xOpt->getDev(), xOpt->getSLang());
// Eval
if (xOpt->getEval()) {
boost::shared_ptr<Eval> ptrEval = boost::make_shared<Eval>();
ptrEval->doEval(100, 0);
int oldStep = xOpt->getStep();
xOpt->setStep(2);
ptrEval->doEval(8, 0);
xOpt->setStep(oldStep);
XenIO::writeEval(ptrEval->getDist(), distName);
}
// BP
else if (xOpt->getBp()) {
boost::shared_ptr<Eval> ptrEval;
if (boost::filesystem::exists(distName.c_str()))
ptrEval = boost::make_shared<Eval>(distName);
else {
ptrEval = boost::make_shared<Eval>();
ptrEval->doEval(100, 0);
int oldStep = xOpt->getStep();
xOpt->setStep(2);
ptrEval->doEval(8, 0);
xOpt->setStep(oldStep);
XenIO::writeEval(ptrEval->getDist(), distName);
}
ptrEval->doBP();
XenIO::writeEval(ptrEval->getDist(), bpName);
}
else { return 1; }
}
} catch (XenCommon::XenCEption &e) {
throw;
}
xOpt->deleteInstance();
sD->deleteInstance();
return 0;
}