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#ifndef _BIASED_LINEARITY_H_
#define _BIASED_LINEARITY_H_
#include "Component.h"
#include "Matrix.h"
#include "Vector.h"
namespace TNet {
class BiasedLinearity : public UpdatableComponent
{
public:
BiasedLinearity(size_t nInputs, size_t nOutputs, Component *pPred);
~BiasedLinearity() { }
ComponentType GetType() const
{ return BIASED_LINEARITY; }
const char* GetName() const
{ return "<BiasedLinearity>"; }
Component* Clone() const;
void PropagateFnc(const Matrix<BaseFloat>& X, Matrix<BaseFloat>& Y);
void BackpropagateFnc(const Matrix<BaseFloat>& X, Matrix<BaseFloat>& Y);
void ReadFromStream(std::istream& rIn);
void WriteToStream(std::ostream& rOut);
/// calculate gradient
void Gradient();
/// accumulate gradient from other components
void AccuGradient(const UpdatableComponent& src, int thr, int thrN);
/// update weights, reset the accumulator
void Update(int thr, int thrN);
protected:
Matrix<BaseFloat> mLinearity; ///< Matrix with neuron weights
Vector<BaseFloat> mBias; ///< Vector with biases
const Matrix<BaseFloat>* mpLinearity;
const Vector<BaseFloat>* mpBias;
Matrix<BaseFloat> mLinearityCorrection; ///< Matrix for linearity updates
Vector<BaseFloat> mBiasCorrection; ///< Vector for bias updates
Matrix<double> mLinearityCorrectionAccu; ///< Matrix for summing linearity updates
Vector<double> mBiasCorrectionAccu; ///< Vector for summing bias updates
};
////////////////////////////////////////////////////////////////////////////
// INLINE FUNCTIONS
// BiasedLinearity::
inline
BiasedLinearity::
BiasedLinearity(size_t nInputs, size_t nOutputs, Component *pPred)
: UpdatableComponent(nInputs, nOutputs, pPred),
mLinearity(), mBias(), //cloned instaces don't need this
mpLinearity(&mLinearity), mpBias(&mBias),
mLinearityCorrection(nInputs,nOutputs), mBiasCorrection(nOutputs),
mLinearityCorrectionAccu(), mBiasCorrectionAccu() //cloned instances don't need this
{ }
inline
Component*
BiasedLinearity::
Clone() const
{
BiasedLinearity* ptr = new BiasedLinearity(GetNInputs(), GetNOutputs(), NULL);
ptr->mpLinearity = mpLinearity; //copy pointer from currently active weights
ptr->mpBias = mpBias; //...
ptr->mLearningRate = mLearningRate;
return ptr;
}
} //namespace
#endif
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