#ifndef _CUDISCRETE_LINEARITY_H_ #define _CUDISCRETE_LINEARITY_H_ #include "cuComponent.h" #include "cumatrix.h" #include "Matrix.h" #include "Vector.h" #include <vector> namespace TNet { /** * \brief CuDiscreteLinearity Summation function * * \ingroup CuNNUpdatable * Similar to CuSharedLinearity except that mBias is not shared, * only mLinearity is used as multiple instances. * \sa CuBiasedLinearity */ class CuDiscreteLinearity : public CuUpdatableComponent { public: CuDiscreteLinearity(size_t nInputs, size_t nOutputs, CuComponent *pPred); ~CuDiscreteLinearity(); ComponentType GetType() const; const char* GetName() const; void PropagateFnc(const CuMatrix<BaseFloat>& X, CuMatrix<BaseFloat>& Y); void BackpropagateFnc(const CuMatrix<BaseFloat>& X, CuMatrix<BaseFloat>& Y); void Update(); void ReadFromStream(std::istream& rIn); void WriteToStream(std::ostream& rOut); protected: std::vector<CuMatrix<BaseFloat> > mLinearity; ///< Matrix with neuron weights CuVector<BaseFloat> mBias; ///< Vector with biases std::vector<CuMatrix<BaseFloat> > mLinearityCorrection; ///< Matrix for linearity updates CuVector<BaseFloat> mBiasCorrection; ///< Vector for bias updates size_t mNBlocks; }; //////////////////////////////////////////////////////////////////////////// // INLINE FUNCTIONS // CuDiscreteLinearity:: inline CuDiscreteLinearity:: CuDiscreteLinearity(size_t nInputs, size_t nOutputs, CuComponent *pPred) : CuUpdatableComponent(nInputs, nOutputs, pPred), //mLinearity(nInputs,nOutputs), mBias(nOutputs), //mLinearityCorrection(nInputs,nOutputs), mBiasCorrection(nOutputs) mNBlocks(0) { //mLinearityCorrection.SetConst(0.0); //mBiasCorrection.SetConst(0.0); } inline CuDiscreteLinearity:: ~CuDiscreteLinearity() { } inline CuComponent::ComponentType CuDiscreteLinearity:: GetType() const { return CuComponent::DISCRETE_LINEARITY; } inline const char* CuDiscreteLinearity:: GetName() const { return "<discretelinearity>"; } } //namespace #endif