mirror of
https://github.com/moses-smt/mosesdecoder.git
synced 2024-09-11 19:27:11 +03:00
122 lines
3.8 KiB
C++
122 lines
3.8 KiB
C++
#include <iostream>
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#include "Classifier.h"
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#include "vw.h"
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#include "ezexample.h"
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#include "../moses/Util.h"
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namespace Discriminative
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{
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using namespace std;
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VWPredictor::VWPredictor(const string &modelFile, const string &vwOptions)
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{
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m_VWInstance = VW::initialize(VW_DEFAULT_OPTIONS + " -i " + modelFile + vwOptions);
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m_VWParser = VW::initialize(VW_DEFAULT_PARSER_OPTIONS + vwOptions + " --noop");
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m_sharedVwInstance = false;
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m_ex = new ::ezexample(m_VWInstance, false, m_VWParser);
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m_isFirstSource = m_isFirstTarget = true;
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}
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VWPredictor::VWPredictor(vw *instance, const string &vwOptions)
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{
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m_VWInstance = instance;
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m_VWParser = VW::initialize(vwOptions + " --noop");
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m_sharedVwInstance = true;
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m_ex = new ::ezexample(m_VWInstance, false, m_VWParser);
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m_isFirstSource = m_isFirstTarget = true;
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}
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VWPredictor::~VWPredictor()
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{
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delete m_ex;
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VW::finish(*m_VWParser);
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if (!m_sharedVwInstance)
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VW::finish(*m_VWInstance);
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}
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FeatureType VWPredictor::AddLabelIndependentFeature(const StringPiece &name, float value)
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{
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// label-independent features are kept in a different feature namespace ('s' = source)
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if (m_isFirstSource) {
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// the first feature of a new example => create the source namespace for
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// label-independent features to live in
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m_isFirstSource = false;
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m_ex->finish();
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m_ex->addns('s');
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if (DEBUG) std::cerr << "VW :: Setting source namespace\n";
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}
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return AddFeature(name, value); // namespace 's' is set up, add the feature
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}
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FeatureType VWPredictor::AddLabelDependentFeature(const StringPiece &name, float value)
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{
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// VW does not use the label directly, instead, we do a Cartesian product between source and target feature
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// namespaces, where the source namespace ('s') contains label-independent features and the target
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// namespace ('t') contains label-dependent features
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if (m_isFirstTarget) {
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// the first target-side feature => create namespace 't'
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m_isFirstTarget = false;
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m_ex->addns('t');
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if (DEBUG) std::cerr << "VW :: Setting target namespace\n";
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}
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return AddFeature(name, value);
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}
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void VWPredictor::AddLabelIndependentFeatureVector(const FeatureVector &features)
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{
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if (m_isFirstSource) {
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// the first feature of a new example => create the source namespace for
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// label-independent features to live in
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m_isFirstSource = false;
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m_ex->finish();
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m_ex->addns('s');
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if (DEBUG) std::cerr << "VW :: Setting source namespace\n";
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}
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// add each feature index using this "low level" call to VW
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for (FeatureVector::const_iterator it = features.begin(); it != features.end(); it++)
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m_ex->addf(it->first, it->second);
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}
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void VWPredictor::AddLabelDependentFeatureVector(const FeatureVector &features)
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{
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if (m_isFirstTarget) {
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// the first target-side feature => create namespace 't'
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m_isFirstTarget = false;
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m_ex->addns('t');
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if (DEBUG) std::cerr << "VW :: Setting target namespace\n";
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}
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// add each feature index using this "low level" call to VW
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for (FeatureVector::const_iterator it = features.begin(); it != features.end(); it++)
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m_ex->addf(it->first, it->second);
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}
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void VWPredictor::Train(const StringPiece &label, float loss)
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{
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throw logic_error("Trying to train during prediction!");
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}
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float VWPredictor::Predict(const StringPiece &label)
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{
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m_ex->set_label(label.as_string());
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m_isFirstSource = true;
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m_isFirstTarget = true;
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float loss = m_ex->predict_partial();
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if (DEBUG) std::cerr << "VW :: Predicted loss: " << loss << "\n";
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m_ex->remns(); // remove target namespace
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return loss;
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}
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FeatureType VWPredictor::AddFeature(const StringPiece &name, float value)
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{
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if (DEBUG) std::cerr << "VW :: Adding feature: " << EscapeSpecialChars(name.as_string()) << ":" << value << "\n";
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return std::make_pair(m_ex->addf(EscapeSpecialChars(name.as_string()), value), value);
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}
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} // namespace Discriminative
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