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#ifndef NEURAL_COLUMN_H
#define NEURAL_COLUMN_H
#include "neural/container.h"
namespace Neural
{
template<typename sigtype>
class Column : public Container<sigtype>
{
public:
Column()
{
}
virtual ~Column()
{
}
virtual void finalize( int iNumInputs )
{
iInputs = iNumInputs;
iWeights = 0;
iBiases = 0;
int iNextInputs = iInputs;
for( typename Container<sigtype>::NodeList::iterator i =
Container<sigtype>::getNodeList().begin(); i; i++ )
{
(*i)->finalize( iNextInputs );
iNextInputs = (*i)->getNumOutputs();
if( (i+1) )
{
lBuffer.append( new sigtype[iNextInputs] );
}
iWeights += (*i)->getNumWeights();
iBiases += (*i)->getNumBiases();
}
}
virtual void process( sigtype *aInput, sigtype *aOutput )
{
typename BufferList::iterator iBuf = lBuffer.begin();
sigtype *pBuffer = aInput;
sigtype *pNextBuffer = *iBuf;
for( typename Container<sigtype>::NodeList::iterator i =
Container<sigtype>::getNodeList().begin(); i; i++ )
{
(*i)->process( pBuffer, pNextBuffer );
pBuffer = pNextBuffer;
if( iBuf )
iBuf++;
if( iBuf )
pNextBuffer = *iBuf;
else
pNextBuffer = aOutput;
}
}
virtual int getNumInputs() const
{
return iInputs;
}
virtual int getNumOutputs() const
{
return Container<sigtype>::getNodeList().last()->getNumOutputs();
}
virtual int getNumWeights() const
{
return iWeights;
}
virtual int getNumBiases() const
{
return iBiases;
}
private:
int iInputs;
int iWeights;
int iBiases;
typedef Bu::List<sigtype *> BufferList;
BufferList lBuffer;
};
};
#endif
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