feature-vector-reader.H

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#ifndef RERANKER_FEATURE_VECTOR_READER_H_
#define RERANKER_FEATURE_VECTOR_READER_H_

#include <cmath>
#include <string>

#include "../proto/model.pb.h"
#include "feature-vector.H"
#include "symbol-table.H"

namespace reranker {

using confusion_learning::FeatureMessage;
using confusion_learning::FeatureVecMessage;

using std::string;

template <typename FV>
class FeatureVectorReader {
 public:
  void Read(const FeatureVecMessage &fv_message,
            FV &features,
            Symbols *symbols) const {
    for (int i = 0; i < fv_message.feature_size(); ++i) {
      const FeatureMessage &feature_msg = fv_message.feature(i);
      int uid = feature_msg.id();
      if (symbols != NULL &&
          feature_msg.has_name() && ! feature_msg.name().empty()) {
        uid = symbols->GetIndex(feature_msg.name());
      }
      double value = feature_msg.value();
      if (std::isnan(value)) {
        cerr << "FeatureVectorReader: WARNING: feature " << uid
             << " has value that is NaN" << endl;
      } else {
        features.IncrementWeight(uid, value);
      }
    }
  }
};

template <typename V>
class FeatureVectorReader<FeatureVector<string,V> >  {
 public:
  void Read(const FeatureVecMessage &fv_message,
            FeatureVector<string,V> &features,
            Symbols *symbols) const {
    for (int i = 0; i < fv_message.feature_size(); ++i) {
      const FeatureMessage &feature_msg = fv_message.feature(i);
      double value = feature_msg.value();
      if (std::isnan(value)) {
        cerr << "FeatureVectorReader: WARNING: feature " << feature_msg.name()
             << " has value that is NaN" << endl;
      } else {
        features.IncrementWeight(feature_msg.name(), value);
      }
    }
  }
};

}  // namespace reranker

#endif