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#ifndef _ACT_FUN_I_
#define _ACT_FUN_I_
#include "Component.h"
namespace TNet
{
/**
* Sigmoid activation function
*/
class Sigmoid : public Component
{
public:
Sigmoid(size_t nInputs, size_t nOutputs, Component *pPred)
: Component(nInputs,nOutputs,pPred)
{ }
ComponentType GetType() const
{ return SIGMOID; }
const char* GetName() const
{ return "<sigmoid>"; }
Component* Clone() const
{ return new Sigmoid(GetNInputs(),GetNOutputs(),NULL); }
protected:
void PropagateFnc(const BfMatrix& X, BfMatrix& Y);
void BackpropagateFnc(const BfMatrix& X, BfMatrix& Y);
};
/**
* Softmax activation function
*/
class Softmax : public Component
{
public:
Softmax(size_t nInputs, size_t nOutputs, Component *pPred)
: Component(nInputs,nOutputs,pPred)
{ }
ComponentType GetType() const
{ return SOFTMAX; }
const char* GetName() const
{ return "<softmax>"; }
Component* Clone() const
{ return new Softmax(GetNInputs(),GetNOutputs(),NULL); }
protected:
void PropagateFnc(const BfMatrix& X, BfMatrix& Y);
void BackpropagateFnc(const BfMatrix& X, BfMatrix& Y);
};
/**
* BlockSoftmax activation function.
* It is several softmaxes in one.
* The dimensions of softmaxes are given by integer vector.
* During backpropagation:
* If the derivatives sum up to 0, they are backpropagated.
* If the derivatives sup up to 1, they are discarded
* (like this we know that the softmax was 'inactive').
*/
class BlockSoftmax : public Component
{
public:
BlockSoftmax(size_t nInputs, size_t nOutputs, Component *pPred)
: Component(nInputs,nOutputs,pPred)
{ }
ComponentType GetType() const
{ return BLOCK_SOFTMAX; }
const char* GetName() const
{ return "<blocksoftmax>"; }
Component* Clone() const
{ return new BlockSoftmax(*this); }
void ReadFromStream(std::istream& rIn);
void WriteToStream(std::ostream& rOut);
protected:
void PropagateFnc(const BfMatrix& X, BfMatrix& Y);
void BackpropagateFnc(const BfMatrix& X, BfMatrix& Y);
private:
Vector<int> mDim;
Vector<int> mDimOffset;
};
} //namespace
#endif
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