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