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#ifndef _CUUPDATABLE_BIAS_H_
#define _CUUPDATABLE_BIAS_H_
#include "cuComponent.h"
#include "cumatrix.h"
#include "Matrix.h"
#include "Vector.h"
namespace TNet {
/**
* \brief CuUpdatableBias summation function
*
* \ingroup CuNNUpdatable
* Implements forward pass: \f[ Y_i=X_i +{\beta}_i \f]
* Error propagation: \f[ E_i = e_i \f]
*
* Weight adjust:
* for bias: \f[ {\Beta}_i = {\beta}_i - \alpha(1-\mu)e_i - \mu \Delta \f]
* where
* - D for weight decay => penalizing large weight
* - \f$ \alpha \f$ for learning rate
* - \f$ \mu \f$ for momentum => avoiding oscillation
*/
class CuUpdatableBias : public CuUpdatableComponent
{
public:
CuUpdatableBias(size_t nInputs, size_t nOutputs, CuComponent *pPred);
~CuUpdatableBias();
ComponentType GetType() const;
const char* GetName() const;
const CuMatrix<float>& GetErrorOutput();
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);
void Backpropagate();
protected:
CuVector<BaseFloat> mBias; ///< Vector with biases
CuVector<BaseFloat> mBiasCorrection; ///< Vector for bias updates
};
////////////////////////////////////////////////////////////////////////////
// INLINE FUNCTIONS
// CuUpdatableBias::
inline
CuUpdatableBias::
CuUpdatableBias(size_t nInputs, size_t nOutputs, CuComponent *pPred)
: CuUpdatableComponent(nInputs, nOutputs, pPred),
mBias(nOutputs), mBiasCorrection(nOutputs)
{
mBiasCorrection.SetConst(0.0);
}
inline
CuUpdatableBias::
~CuUpdatableBias()
{ }
inline CuComponent::ComponentType
CuUpdatableBias::
GetType() const
{
return CuComponent::UPDATABLEBIAS;
}
inline const char*
CuUpdatableBias::
GetName() const
{
return "<updatablebias>";
}
inline void
CuUpdatableBias::
Backpropagate()
{
}
inline const CuMatrix<BaseFloat>&
CuUpdatableBias::
GetErrorOutput()
{
return GetErrorInput();
}
} //namespace
#endif
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