/* * MiraWeightVector.h * kbmira - k-best Batch MIRA * * A self-averaging weight-vector. Good for * perceptron learning as well. * */ #ifndef MERT_MIRA_WEIGHT_VECTOR_H #define MERT_MIRA_WEIGHT_VECTOR_H #include #include #include "MiraFeatureVector.h" namespace MosesTuning { class AvgWeightVector; class MiraWeightVector { public: /** * Constructor, initializes to the zero vector */ MiraWeightVector(); /** * Constructor with provided initial vector * \param init Initial feature values */ MiraWeightVector(const std::vector& init); /** * Update a the model * \param fv Feature vector to be added to the weights * \param tau FV will be scaled by this value before update */ void update(const MiraFeatureVector& fv, float tau); /** * Perform an empty update (affects averaging) */ void tick(); /** * Score a feature vector according to the model * \param fv Feature vector to be scored */ ValType score(const MiraFeatureVector& fv) const; /** * Squared norm of the weight vector */ ValType sqrNorm() const; /** * Return an averaged view of this weight vector */ AvgWeightVector avg(); friend class AvgWeightVector; friend std::ostream& operator<<(std::ostream& o, const MiraWeightVector& e); private: /** * Updates a weight and lazily updates its total */ void update(std::size_t index, ValType delta); /** * Make sure everyone's total is up-to-date */ void fixTotals(); /** * Helper to handle out-of-range weights */ ValType weight(std::size_t index) const; std::vector m_weights; std::vector m_totals; std::vector m_lastUpdated; std::size_t m_numUpdates; }; /** * Averaged view of a weight vector */ class AvgWeightVector { public: AvgWeightVector(const MiraWeightVector& wv); ValType score(const MiraFeatureVector& fv) const; ValType weight(std::size_t index) const; std::size_t size() const; private: const MiraWeightVector& m_wv; }; #endif // MERT_WEIGHT_VECTOR_H // --Emacs trickery-- // Local Variables: // mode:c++ // c-basic-offset:2 // End: }