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mosesdecoder/phrase-extract/consolidate-main.cpp
U-DESKTOP-ONHNTIV\hieuh 626a53e7df compile error on 4.9.3 on cygwin
2015-08-05 18:15:09 +01:00

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/***********************************************************************
Moses - factored phrase-based language decoder
Copyright (C) 2009 University of Edinburgh
This library is free software; you can redistribute it and/or
modify it under the terms of the GNU Lesser General Public
License as published by the Free Software Foundation; either
version 2.1 of the License, or (at your option) any later version.
This library is distributed in the hope that it will be useful,
but WITHOUT ANY WARRANTY; without even the implied warranty of
MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU
Lesser General Public License for more details.
You should have received a copy of the GNU Lesser General Public
License along with this library; if not, write to the Free Software
Foundation, Inc., 51 Franklin Street, Fifth Floor, Boston, MA 02110-1301 USA
***********************************************************************/
#include <cstdlib>
#include <vector>
#include <string>
#include "util/exception.hh"
#include "moses/Util.h"
#include "InputFileStream.h"
#include "OutputFileStream.h"
#include "PropertiesConsolidator.h"
bool countsProperty = false;
bool goodTuringFlag = false;
bool hierarchicalFlag = false;
bool kneserNeyFlag = false;
bool logProbFlag = false;
bool lowCountFlag = false;
bool onlyDirectFlag = false;
bool partsOfSpeechFlag = false;
bool phraseCountFlag = false;
bool sourceLabelsFlag = false;
bool sparseCountBinFeatureFlag = false;
std::vector< int > countBin;
float minScore0 = 0;
float minScore2 = 0;
std::vector< float > countOfCounts;
std::vector< float > goodTuringDiscount;
float kneserNey_D1, kneserNey_D2, kneserNey_D3, totalCount = -1;
void processFiles( const std::string&, const std::string&, const std::string&, const std::string&, const std::string&, const std::string& );
void loadCountOfCounts( const std::string& );
void breakdownCoreAndSparse( const std::string &combined, std::string &core, std::string &sparse );
bool getLine( Moses::InputFileStream &file, std::vector< std::string > &item );
inline float maybeLogProb( float a )
{
return logProbFlag ? std::log(a) : a;
}
inline bool isNonTerminal( const std::string &word )
{
return (word.length()>=3 && word[0] == '[' && word[word.length()-1] == ']');
}
int main(int argc, char* argv[])
{
std::cerr << "Consolidate v2.0 written by Philipp Koehn" << std::endl
<< "consolidating direct and indirect rule tables" << std::endl;
if (argc < 4) {
std::cerr <<
"syntax: "
"consolidate phrase-table.direct "
"phrase-table.indirect "
"phrase-table.consolidated "
"[--Hierarchical] [--OnlyDirect] [--PhraseCount] "
"[--GoodTuring counts-of-counts-file] "
"[--KneserNey counts-of-counts-file] [--LowCountFeature] "
"[--SourceLabels source-labels-file] "
"[--PartsOfSpeech parts-of-speech-file] "
"[--MinScore id:threshold[,id:threshold]*]"
<< std::endl;
exit(1);
}
const std::string fileNameDirect = argv[1];
const std::string fileNameIndirect = argv[2];
const std::string fileNameConsolidated = argv[3];
std::string fileNameCountOfCounts;
std::string fileNameSourceLabelSet;
std::string fileNamePartsOfSpeechVocabulary;
for(int i=4; i<argc; i++) {
if (strcmp(argv[i],"--Hierarchical") == 0) {
hierarchicalFlag = true;
std::cerr << "processing hierarchical rules" << std::endl;
} else if (strcmp(argv[i],"--OnlyDirect") == 0) {
onlyDirectFlag = true;
std::cerr << "only including direct translation scores p(e|f)" << std::endl;
} else if (strcmp(argv[i],"--PhraseCount") == 0) {
phraseCountFlag = true;
std::cerr << "including the phrase count feature" << std::endl;
} else if (strcmp(argv[i],"--GoodTuring") == 0) {
goodTuringFlag = true;
UTIL_THROW_IF2(i+1==argc, "specify count of count files for Good Turing discounting!");
fileNameCountOfCounts = argv[++i];
std::cerr << "adjusting phrase translation probabilities with Good Turing discounting" << std::endl;
} else if (strcmp(argv[i],"--KneserNey") == 0) {
kneserNeyFlag = true;
UTIL_THROW_IF2(i+1==argc, "specify count of count files for Kneser Ney discounting!");
fileNameCountOfCounts = argv[++i];
std::cerr << "adjusting phrase translation probabilities with Kneser Ney discounting" << std::endl;
} else if (strcmp(argv[i],"--LowCountFeature") == 0) {
lowCountFlag = true;
std::cerr << "including the low count feature" << std::endl;
} else if (strcmp(argv[i],"--CountBinFeature") == 0 ||
strcmp(argv[i],"--SparseCountBinFeature") == 0) {
if (strcmp(argv[i],"--SparseCountBinFeature") == 0)
sparseCountBinFeatureFlag = true;
std::cerr << "include "<< (sparseCountBinFeatureFlag ? "sparse " : "") << "count bin feature:";
int prev = 0;
while(i+1<argc && argv[i+1][0]>='0' && argv[i+1][0]<='9') {
int binCount = std::atoi( argv[++i] );
countBin.push_back( binCount );
if (prev+1 == binCount) {
std::cerr << " " << binCount;
} else {
std::cerr << " " << (prev+1) << "-" << binCount;
}
prev = binCount;
}
std::cerr << " " << (prev+1) << "+" << std::endl;
} else if (strcmp(argv[i],"--LogProb") == 0) {
logProbFlag = true;
std::cerr << "using log-probabilities" << std::endl;
} else if (strcmp(argv[i],"--Counts") == 0) {
countsProperty = true;
std::cerr << "output counts as a property" << std::endl;;
} else if (strcmp(argv[i],"--SourceLabels") == 0) {
sourceLabelsFlag = true;
UTIL_THROW_IF2(i+1==argc, "specify source label set file!");
fileNameSourceLabelSet = argv[++i];
std::cerr << "processing source labels property" << std::endl;
} else if (strcmp(argv[i],"--PartsOfSpeech") == 0) {
partsOfSpeechFlag = true;
UTIL_THROW_IF2(i+1==argc, "specify parts-of-speech file!");
fileNamePartsOfSpeechVocabulary = argv[++i];
std::cerr << "processing parts-of-speech property" << std::endl;
} else if (strcmp(argv[i],"--MinScore") == 0) {
std::string setting = argv[++i];
bool done = false;
while (!done) {
std::string single_setting;
size_t pos;
if ((pos = setting.find(",")) != std::string::npos) {
single_setting = setting.substr(0, pos);
setting.erase(0, pos + 1);
} else {
single_setting = setting;
done = true;
}
pos = single_setting.find(":");
UTIL_THROW_IF2(pos == std::string::npos, "faulty MinScore setting '" << single_setting << "' in '" << argv[i] << "'");
unsigned int field = atoll( single_setting.substr(0,pos).c_str() );
float threshold = std::atof( single_setting.substr(pos+1).c_str() );
if (field == 0) {
minScore0 = threshold;
std::cerr << "setting minScore0 to " << threshold << std::endl;
} else if (field == 2) {
minScore2 = threshold;
std::cerr << "setting minScore2 to " << threshold << std::endl;
} else {
UTIL_THROW2("MinScore currently only supported for indirect (0) and direct (2) phrase translation probabilities");
}
}
} else {
UTIL_THROW2("unknown option " << argv[i]);
}
}
processFiles( fileNameDirect, fileNameIndirect, fileNameConsolidated, fileNameCountOfCounts, fileNameSourceLabelSet, fileNamePartsOfSpeechVocabulary );
}
void loadCountOfCounts( const std::string& fileNameCountOfCounts )
{
Moses::InputFileStream fileCountOfCounts(fileNameCountOfCounts);
UTIL_THROW_IF2(fileCountOfCounts.fail(), "could not open count of counts file " << fileNameCountOfCounts);
countOfCounts.push_back(0.0);
std::string line;
while (getline(fileCountOfCounts, line)) {
if (totalCount < 0)
totalCount = std::atof( line.c_str() ); // total number of distinct phrase pairs
else
countOfCounts.push_back( std::atof( line.c_str() ) );
}
fileCountOfCounts.Close();
// compute Good Turing discounts
if (goodTuringFlag) {
goodTuringDiscount.push_back(0.01); // floor value
for( size_t i=1; i<countOfCounts.size()-1; i++ ) {
goodTuringDiscount.push_back(((float)i+1)/(float)i*((countOfCounts[i+1]+0.1) / ((float)countOfCounts[i]+0.1)));
if (goodTuringDiscount[i]>1)
goodTuringDiscount[i] = 1;
if (goodTuringDiscount[i]<goodTuringDiscount[i-1])
goodTuringDiscount[i] = goodTuringDiscount[i-1];
}
}
// compute Kneser Ney co-efficients [Chen&Goodman, 1998]
float Y = countOfCounts[1] / (countOfCounts[1] + 2*countOfCounts[2]);
kneserNey_D1 = 1 - 2*Y * countOfCounts[2] / countOfCounts[1];
kneserNey_D2 = 2 - 3*Y * countOfCounts[3] / countOfCounts[2];
kneserNey_D3 = 3 - 4*Y * countOfCounts[4] / countOfCounts[3];
// sanity constraints
if (kneserNey_D1 > 0.9) kneserNey_D1 = 0.9;
if (kneserNey_D2 > 1.9) kneserNey_D2 = 1.9;
if (kneserNey_D3 > 2.9) kneserNey_D3 = 2.9;
}
void processFiles( const std::string& fileNameDirect,
const std::string& fileNameIndirect,
const std::string& fileNameConsolidated,
const std::string& fileNameCountOfCounts,
const std::string& fileNameSourceLabelSet,
const std::string& fileNamePartsOfSpeechVocabulary )
{
if (goodTuringFlag || kneserNeyFlag)
loadCountOfCounts( fileNameCountOfCounts );
// open input files
Moses::InputFileStream fileDirect(fileNameDirect);
UTIL_THROW_IF2(fileDirect.fail(), "could not open phrase table file " << fileNameDirect);
Moses::InputFileStream fileIndirect(fileNameIndirect);
UTIL_THROW_IF2(fileIndirect.fail(), "could not open phrase table file " << fileNameIndirect);
// open output file: consolidated phrase table
Moses::OutputFileStream fileConsolidated;
bool success = fileConsolidated.Open(fileNameConsolidated);
UTIL_THROW_IF2(!success, "could not open output file " << fileNameConsolidated);
// create properties consolidator
// (in case any additional phrase property requires further processing)
MosesTraining::PropertiesConsolidator propertiesConsolidator = MosesTraining::PropertiesConsolidator();
if (sourceLabelsFlag) {
propertiesConsolidator.ActivateSourceLabelsProcessing(fileNameSourceLabelSet);
}
if (partsOfSpeechFlag) {
propertiesConsolidator.ActivatePartsOfSpeechProcessing(fileNamePartsOfSpeechVocabulary);
}
// loop through all extracted phrase translations
int i=0;
while(true) {
// Print progress dots to stderr.
i++;
if (i%100000 == 0) std::cerr << "." << std::flush;
std::vector< std::string > itemDirect, itemIndirect;
if (! getLine(fileIndirect, itemIndirect) ||
! getLine(fileDirect, itemDirect))
break;
// direct: target source alignment probabilities
// indirect: source target probabilities
// consistency checks
UTIL_THROW_IF2(itemDirect[0].compare( itemIndirect[0] ) != 0,
"target phrase does not match in line " << i << ": '" << itemDirect[0] << "' != '" << itemIndirect[0] << "'");
UTIL_THROW_IF2(itemDirect[1].compare( itemIndirect[1] ) != 0,
"source phrase does not match in line " << i << ": '" << itemDirect[1] << "' != '" << itemIndirect[1] << "'");
// SCORES ...
std::string directScores, directSparseScores, indirectScores, indirectSparseScores;
breakdownCoreAndSparse( itemDirect[3], directScores, directSparseScores );
breakdownCoreAndSparse( itemIndirect[3], indirectScores, indirectSparseScores );
std::vector<std::string> directCounts;
Moses::Tokenize( directCounts, itemDirect[4] );
std::vector<std::string> indirectCounts;
Moses::Tokenize( indirectCounts, itemIndirect[4] );
float countF = std::atof( directCounts[0].c_str() );
float countE = std::atof( indirectCounts[0].c_str() );
float countEF = std::atof( indirectCounts[1].c_str() );
float n1_F, n1_E;
if (kneserNeyFlag) {
n1_F = std::atof( directCounts[2].c_str() );
n1_E = std::atof( indirectCounts[2].c_str() );
}
// Good Turing discounting
float adjustedCountEF = countEF;
if (goodTuringFlag && countEF+0.99999 < goodTuringDiscount.size()-1)
adjustedCountEF *= goodTuringDiscount[(int)(countEF+0.99998)];
float adjustedCountEF_indirect = adjustedCountEF;
// Kneser Ney discounting [Foster et al, 2006]
if (kneserNeyFlag) {
float D = kneserNey_D3;
if (countEF < 2) D = kneserNey_D1;
else if (countEF < 3) D = kneserNey_D2;
if (D > countEF) D = countEF - 0.01; // sanity constraint
float p_b_E = n1_E / totalCount; // target phrase prob based on distinct
float alpha_F = D * n1_F / countF; // available mass
adjustedCountEF = countEF - D + countF * alpha_F * p_b_E;
// for indirect
float p_b_F = n1_F / totalCount; // target phrase prob based on distinct
float alpha_E = D * n1_E / countE; // available mass
adjustedCountEF_indirect = countEF - D + countE * alpha_E * p_b_F;
}
// drop due to MinScore thresholding
if ((minScore0 > 0 && adjustedCountEF_indirect/countE < minScore0) ||
(minScore2 > 0 && adjustedCountEF /countF < minScore2)) {
continue;
}
// output phrase pair
fileConsolidated << itemDirect[0] << " ||| ";
if (partsOfSpeechFlag) {
// write POS factor from property
std::vector<std::string> targetTokens;
Moses::Tokenize( targetTokens, itemDirect[1] );
std::vector<std::string> propertyValuePOS;
propertiesConsolidator.GetPOSPropertyValueFromPropertiesString(itemDirect[5], propertyValuePOS);
size_t targetTerminalIndex = 0;
for (std::vector<std::string>::const_iterator targetTokensIt=targetTokens.begin();
targetTokensIt!=targetTokens.end(); ++targetTokensIt) {
fileConsolidated << *targetTokensIt;
if (!isNonTerminal(*targetTokensIt)) {
assert(propertyValuePOS.size() > targetTerminalIndex);
fileConsolidated << "|" << propertyValuePOS[targetTerminalIndex];
++targetTerminalIndex;
}
fileConsolidated << " ";
}
fileConsolidated << "|||";
} else {
fileConsolidated << itemDirect[1] << " |||";
}
// prob indirect
if (!onlyDirectFlag) {
fileConsolidated << " " << maybeLogProb(adjustedCountEF_indirect/countE);
fileConsolidated << " " << indirectScores;
}
// prob direct
fileConsolidated << " " << maybeLogProb(adjustedCountEF/countF);
fileConsolidated << " " << directScores;
// phrase count feature
if (phraseCountFlag) {
fileConsolidated << " " << maybeLogProb(2.718);
}
// low count feature
if (lowCountFlag) {
fileConsolidated << " " << maybeLogProb(std::exp(-1.0/countEF));
}
// count bin feature (as a core feature)
if (countBin.size()>0 && !sparseCountBinFeatureFlag) {
bool foundBin = false;
for(size_t i=0; i < countBin.size(); i++) {
if (!foundBin && countEF <= countBin[i]) {
fileConsolidated << " " << maybeLogProb(2.718);
foundBin = true;
} else {
fileConsolidated << " " << maybeLogProb(1);
}
}
fileConsolidated << " " << maybeLogProb( foundBin ? 1 : 2.718 );
}
// alignment
fileConsolidated << " |||";
if (!itemDirect[2].empty()) {
fileConsolidated << " " << itemDirect[2];;
}
// counts, for debugging
fileConsolidated << " ||| " << countE << " " << countF << " " << countEF;
// sparse features
fileConsolidated << " |||";
if (directSparseScores.compare("") != 0)
fileConsolidated << " " << directSparseScores;
if (indirectSparseScores.compare("") != 0)
fileConsolidated << " " << indirectSparseScores;
// count bin feature (as a sparse feature)
if (sparseCountBinFeatureFlag) {
bool foundBin = false;
for(size_t i=0; i < countBin.size(); i++) {
if (!foundBin && countEF <= countBin[i]) {
fileConsolidated << " cb_";
if (i == 0 && countBin[i] > 1)
fileConsolidated << "1_";
else if (i > 0 && countBin[i-1]+1 < countBin[i])
fileConsolidated << (countBin[i-1]+1) << "_";
fileConsolidated << countBin[i] << " 1";
foundBin = true;
}
}
if (!foundBin) {
fileConsolidated << " cb_max 1";
}
}
// arbitrary key-value pairs
fileConsolidated << " |||";
if (itemDirect.size() >= 6) {
propertiesConsolidator.ProcessPropertiesString(itemDirect[5], fileConsolidated);
}
if (countsProperty) {
fileConsolidated << " {{Counts " << countE << " " << countF << " " << countEF << "}}";
}
fileConsolidated << std::endl;
}
fileDirect.Close();
fileIndirect.Close();
fileConsolidated.Close();
// We've been printing progress dots to stderr. End the line.
std::cerr << std::endl;
}
void breakdownCoreAndSparse( const std::string &combined, std::string &core, std::string &sparse )
{
core = "";
sparse = "";
std::vector<std::string> score;
Moses::Tokenize( score, combined );
for(size_t i=0; i<score.size(); i++) {
if ((score[i][0] >= '0' && score[i][0] <= '9') || i+1 == score.size())
core += " " + score[i];
else {
sparse += " " + score[i];
sparse += " " + score[++i];
}
}
if (core.size() > 0 ) core = core.substr(1);
if (sparse.size() > 0 ) sparse = sparse.substr(1);
}
bool getLine( Moses::InputFileStream &file, std::vector< std::string > &item )
{
if (file.eof())
return false;
std::string line;
if (!getline(file, line))
return false;
Moses::TokenizeMultiCharSeparator(item, line, " ||| ");
return true;
}
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