mirror of
https://github.com/moses-smt/mosesdecoder.git
synced 2024-11-10 10:59:21 +03:00
221 lines
5.7 KiB
C++
221 lines
5.7 KiB
C++
#include "HypPackEnumerator.h"
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#include <cassert>
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#include <algorithm>
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#include <boost/unordered_set.hpp>
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using namespace std;
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namespace MosesTuning
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{
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StreamingHypPackEnumerator::StreamingHypPackEnumerator
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(
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vector<std::string> const& featureFiles,
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vector<std::string> const& scoreFiles
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)
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: m_featureFiles(featureFiles),
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m_scoreFiles(scoreFiles)
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{
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if (scoreFiles.size() == 0 || featureFiles.size() == 0) {
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cerr << "No data to process" << endl;
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exit(0);
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}
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if (featureFiles.size() != scoreFiles.size()) {
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cerr << "Error: Number of feature files (" << featureFiles.size() <<
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") does not match number of score files (" << scoreFiles.size() << ")" << endl;
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exit(1);
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}
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m_num_lists = scoreFiles.size();
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m_primed = false;
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m_iNumDense = -1;
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}
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size_t StreamingHypPackEnumerator::num_dense() const
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{
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if(m_iNumDense<0) {
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cerr << "Error: Requested num_dense() for an unprimed StreamingHypPackEnumerator" << endl;
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exit(1);
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}
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return (size_t) m_iNumDense;
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}
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void StreamingHypPackEnumerator::prime()
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{
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m_current_indexes.clear();
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m_current_featureVectors.clear();
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boost::unordered_set<FeatureDataItem> seen;
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m_primed = true;
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for (size_t i = 0; i < m_num_lists; ++i) {
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if (m_featureDataIters[i] == FeatureDataIterator::end()) {
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cerr << "Error: Feature file " << i << " ended prematurely" << endl;
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exit(1);
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}
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if (m_scoreDataIters[i] == ScoreDataIterator::end()) {
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cerr << "Error: Score file " << i << " ended prematurely" << endl;
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exit(1);
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}
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if (m_featureDataIters[i]->size() != m_scoreDataIters[i]->size()) {
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cerr << "Error: For sentence " << m_sentenceId << " features and scores have different size" << endl;
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exit(1);
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}
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for (size_t j = 0; j < m_featureDataIters[i]->size(); ++j) {
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const FeatureDataItem& item = m_featureDataIters[i]->operator[](j);
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// Dedup
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if(seen.find(item)==seen.end()) {
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seen.insert(item);
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// Confirm dense features are always the same
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int iDense = item.dense.size();
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if(m_iNumDense != iDense) {
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if(m_iNumDense==-1) m_iNumDense = iDense;
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else {
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cerr << "Error: expecting constant number of dense features: "
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<< m_iNumDense << " != " << iDense << endl;
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exit(1);
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}
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}
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// Store item for retrieval
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m_current_indexes.push_back(pair<size_t,size_t>(i,j));
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m_current_featureVectors.push_back(MiraFeatureVector(item));
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}
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}
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}
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}
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void StreamingHypPackEnumerator::reset()
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{
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m_featureDataIters.clear();
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m_scoreDataIters.clear();
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for (size_t i = 0; i < m_num_lists; ++i) {
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m_featureDataIters.push_back(FeatureDataIterator(m_featureFiles[i]));
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m_scoreDataIters.push_back(ScoreDataIterator(m_scoreFiles[i]));
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}
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m_sentenceId=0;
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prime();
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}
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bool StreamingHypPackEnumerator::finished()
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{
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return m_featureDataIters[0]==FeatureDataIterator::end();
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}
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void StreamingHypPackEnumerator::next()
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{
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if(!m_primed) {
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cerr << "Enumerating an unprimed HypPackEnumerator" << endl;
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exit(1);
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}
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for (size_t i = 0; i < m_num_lists; ++i) {
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++m_featureDataIters[i];
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++m_scoreDataIters[i];
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}
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m_sentenceId++;
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if(m_sentenceId % 100 == 0) cerr << ".";
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if(!finished()) prime();
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}
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size_t StreamingHypPackEnumerator::cur_size()
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{
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if(!m_primed) {
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cerr << "Querying size from an unprimed HypPackEnumerator" << endl;
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exit(1);
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}
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return m_current_indexes.size();
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}
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const MiraFeatureVector& StreamingHypPackEnumerator::featuresAt(size_t index)
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{
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if(!m_primed) {
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cerr << "Querying features from an unprimed HypPackEnumerator" << endl;
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exit(1);
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}
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return m_current_featureVectors[index];
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}
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const ScoreDataItem& StreamingHypPackEnumerator::scoresAt(size_t index)
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{
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if(!m_primed) {
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cerr << "Querying scores from an unprimed HypPackEnumerator" << endl;
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exit(1);
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}
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const pair<size_t,size_t>& pij = m_current_indexes[index];
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return m_scoreDataIters[pij.first]->operator[](pij.second);
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}
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size_t StreamingHypPackEnumerator::cur_id()
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{
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return m_sentenceId;
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}
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/* --------- RandomAccessHypPackEnumerator ------------- */
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RandomAccessHypPackEnumerator::RandomAccessHypPackEnumerator(vector<string> const& featureFiles,
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vector<string> const& scoreFiles,
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bool no_shuffle)
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{
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StreamingHypPackEnumerator train(featureFiles,scoreFiles);
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size_t index=0;
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for(train.reset(); !train.finished(); train.next()) {
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m_features.push_back(vector<MiraFeatureVector>());
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m_scores.push_back(vector<ScoreDataItem>());
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for(size_t j=0; j<train.cur_size(); j++) {
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m_features.back().push_back(train.featuresAt(j));
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m_scores.back().push_back(train.scoresAt(j));
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}
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m_indexes.push_back(index++);
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}
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m_cur_index = 0;
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m_no_shuffle = no_shuffle;
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m_num_dense = train.num_dense();
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}
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size_t RandomAccessHypPackEnumerator::num_dense() const
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{
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return m_num_dense;
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}
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void RandomAccessHypPackEnumerator::reset()
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{
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m_cur_index = 0;
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if(!m_no_shuffle) random_shuffle(m_indexes.begin(),m_indexes.end());
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}
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bool RandomAccessHypPackEnumerator::finished()
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{
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return m_cur_index >= m_indexes.size();
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}
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void RandomAccessHypPackEnumerator::next()
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{
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m_cur_index++;
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}
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size_t RandomAccessHypPackEnumerator::cur_size()
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{
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assert(m_features[m_indexes[m_cur_index]].size()==m_scores[m_indexes[m_cur_index]].size());
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return m_features[m_indexes[m_cur_index]].size();
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}
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const MiraFeatureVector& RandomAccessHypPackEnumerator::featuresAt(size_t i)
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{
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return m_features[m_indexes[m_cur_index]][i];
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}
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const ScoreDataItem& RandomAccessHypPackEnumerator::scoresAt(size_t i)
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{
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return m_scores[m_indexes[m_cur_index]][i];
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}
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size_t RandomAccessHypPackEnumerator::cur_id()
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{
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return m_indexes[m_cur_index];
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}
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// --Emacs trickery--
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// Local Variables:
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// mode:c++
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// c-basic-offset:2
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// End:
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}
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