mirror of
https://github.com/moses-smt/mosesdecoder.git
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38e145e556
Reduce creating std::string objects, too. In both ScoreArray and FeatureArray classes, the private members to track sentence indices (namely, "m_index") were unnecessarily declared as std::string, but it's better to directly declare them as 'int'.
171 lines
3.8 KiB
C++
171 lines
3.8 KiB
C++
/*
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* FeatureData.cpp
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* mert - Minimum Error Rate Training
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*
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* Created by Nicola Bertoldi on 13/05/08.
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*
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*/
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#include "FeatureData.h"
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#include <limits>
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#include "FileStream.h"
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#include "Util.h"
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using namespace std;
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namespace MosesTuning
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{
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FeatureData::FeatureData()
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: m_num_features(0) {}
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void FeatureData::save(ostream* os, bool bin)
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{
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for (featdata_t::iterator i = m_array.begin(); i != m_array.end(); i++)
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i->save(os, bin);
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}
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void FeatureData::save(const string &file, bool bin)
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{
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if (file.empty()) return;
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TRACE_ERR("saving the array into " << file << endl);
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ofstream ofs(file.c_str(), ios::out); // matches a stream with a file. Opens the file
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ostream* os = &ofs;
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save(os, bin);
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ofs.close();
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}
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void FeatureData::save(bool bin) {
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save(&cout, bin);
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}
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void FeatureData::load(istream* is, const SparseVector& sparseWeights)
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{
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FeatureArray entry;
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while (!is->eof()) {
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if (!is->good()) {
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cerr << "ERROR FeatureData::load inFile.good()" << endl;
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}
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entry.clear();
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entry.load(is, sparseWeights);
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if (entry.size() == 0)
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break;
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if (size() == 0)
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setFeatureMap(entry.Features());
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add(entry);
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}
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}
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void FeatureData::load(const string &file, const SparseVector& sparseWeights)
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{
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TRACE_ERR("loading feature data from " << file << endl);
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inputfilestream input_stream(file); // matches a stream with a file. Opens the file
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if (!input_stream) {
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throw runtime_error("Unable to open feature file: " + file);
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}
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istream* is = &input_stream;
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load(is, sparseWeights);
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input_stream.close();
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}
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void FeatureData::add(FeatureArray& e)
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{
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if (exists(e.getIndex())) { // array at position e.getIndex() already exists
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//enlarge array at position e.getIndex()
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size_t pos = getIndex(e.getIndex());
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m_array.at(pos).merge(e);
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} else {
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m_array.push_back(e);
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setIndex();
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}
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}
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void FeatureData::add(FeatureStats& e, int sent_idx)
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{
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if (exists(sent_idx)) { // array at position e.getIndex() already exists
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//enlarge array at position e.getIndex()
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size_t pos = getIndex(sent_idx);
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// TRACE_ERR("Inserting " << e << " in array " << sent_idx << std::endl);
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m_array.at(pos).add(e);
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} else {
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// TRACE_ERR("Creating a new entry in the array and inserting " << e << std::endl);
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FeatureArray a;
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a.NumberOfFeatures(m_num_features);
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a.Features(m_features);
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a.setIndex(sent_idx);
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a.add(e);
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add(a);
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}
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}
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bool FeatureData::check_consistency() const
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{
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if (m_array.size() == 0)
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return true;
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for (featdata_t::const_iterator i = m_array.begin(); i != m_array.end(); i++)
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if (!i->check_consistency()) return false;
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return true;
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}
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void FeatureData::setIndex()
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{
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size_t j=0;
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for (featdata_t::iterator i = m_array.begin(); i !=m_array.end(); i++) {
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m_index_to_array_name[j]=(*i).getIndex();
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m_array_name_to_index[(*i).getIndex()] = j;
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j++;
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}
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}
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void FeatureData::setFeatureMap(const string& feat)
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{
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m_num_features = 0;
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m_features = feat;
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vector<string> buf;
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Tokenize(feat.c_str(), ' ', &buf);
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for (vector<string>::const_iterator it = buf.begin();
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it != buf.end(); ++it) {
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const size_t size = m_index_to_feature_name.size();
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m_feature_name_to_index[*it] = size;
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m_index_to_feature_name[size] = *it;
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++m_num_features;
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}
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}
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string FeatureData::ToString() const {
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string res;
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{
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stringstream ss;
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ss << "number of features: " << m_num_features
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<< ", features: " << m_features;
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res.append(ss.str());
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}
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res.append("feature_id_map = { ");
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for (map<string, size_t>::const_iterator it = m_feature_name_to_index.begin();
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it != m_feature_name_to_index.end(); ++it) {
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stringstream ss;
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ss << it->first << " => " << it->second << ", ";
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res.append(ss.str());
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}
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res.append("}");
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return res;
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}
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}
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