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#include <iostream>
#include "Classifier.h"
#include "vw.h"
#include "ezexample.h"
#include "../moses/Util.h"
namespace Discriminative
{
using namespace std;
VWPredictor::VWPredictor(const string &modelFile, const string &vwOptions)
{
m_VWInstance = VW::initialize(VW_DEFAULT_OPTIONS + " -i " + modelFile + vwOptions);
m_VWParser = VW::initialize(VW_DEFAULT_PARSER_OPTIONS + vwOptions + " --noop");
m_sharedVwInstance = false;
m_ex = new ::ezexample(m_VWInstance, false, m_VWParser);
m_isFirstSource = m_isFirstTarget = true;
}
VWPredictor::VWPredictor(vw *instance, const string &vwOptions)
{
m_VWInstance = instance;
m_VWParser = VW::initialize(vwOptions + " --noop");
m_sharedVwInstance = true;
m_ex = new ::ezexample(m_VWInstance, false, m_VWParser);
m_isFirstSource = m_isFirstTarget = true;
}
VWPredictor::~VWPredictor()
{
delete m_ex;
VW::finish(*m_VWParser);
if (!m_sharedVwInstance)
VW::finish(*m_VWInstance);
}
void VWPredictor::AddLabelIndependentFeature(const StringPiece &name, float value)
{
// label-independent features are kept in a different feature namespace ('s' = source)
if (m_isFirstSource) {
// the first feature of a new example => create the source namespace for
// label-independent features to live in
m_isFirstSource = false;
m_ex->finish();
m_ex->addns('s');
if (DEBUG) std::cerr << "VW :: Setting source namespace\n";
}
AddFeature(name, value); // namespace 's' is set up, add the feature
}
void VWPredictor::AddLabelDependentFeature(const StringPiece &name, float value)
{
// VW does not use the label directly, instead, we do a Cartesian product between source and target feature
// namespaces, where the source namespace ('s') contains label-independent features and the target
// namespace ('t') contains label-dependent features
if (m_isFirstTarget) {
// the first target-side feature => create namespace 't'
m_isFirstTarget = false;
m_ex->addns('t');
if (DEBUG) std::cerr << "VW :: Setting target namespace\n";
}
AddFeature(name, value);
}
void VWPredictor::Train(const StringPiece &label, float loss)
{
throw logic_error("Trying to train during prediction!");
}
float VWPredictor::Predict(const StringPiece &label)
{
m_ex->set_label(label.as_string());
m_isFirstSource = true;
m_isFirstTarget = true;
float loss = m_ex->predict_partial();
if (DEBUG) std::cerr << "VW :: Predicted loss: " << loss << "\n";
m_ex->remns(); // remove target namespace
return loss;
}
void VWPredictor::AddFeature(const StringPiece &name, float value)
{
if (DEBUG) std::cerr << "VW :: Adding feature: " << EscapeSpecialChars(name.as_string()) << ":" << value << "\n";
m_ex->addf(EscapeSpecialChars(name.as_string()), value);
}
} // namespace Discriminative
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