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/*=========================================================================
Program: Insight Segmentation & Registration Toolkit
Module: itkErrorBackPropagationLearningWithMomentum.txx
Language: C++
Date: $Date$
Version: $Revision$
Copyright (c) Insight Software Consortium. All rights reserved.
See ITKCopyright.txt or http://www.itk.org/HTML/Copyright.htm for details.
This software is distributed WITHOUT ANY WARRANTY; without even
the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR
PURPOSE. See the above copyright notices for more information.
=========================================================================*/
#ifndef __itkErrorBackPropagationLearningWithMomentum_txx
#define __itkErrorBackPropagationLearningWithMomentum_txx
#include "itkErrorBackPropagationLearningWithMomentum.h"
#include <fstream>
namespace itk
{
namespace Statistics
{
template<class LayerType, class TTargetVector>
ErrorBackPropagationLearningWithMomentum <LayerType,TTargetVector>
::ErrorBackPropagationLearningWithMomentum()
{
m_Momentum = 0.9; //Default
}
template<class LayerType, class TTargetVector>
void
ErrorBackPropagationLearningWithMomentum<LayerType,TTargetVector>
::Learn(LayerInterfaceType * layer, ValueType lr)
{
typedef typename LayerInterfaceType::WeightSetType::Pointer WeightSetPointer;
WeightSetPointer outputweightset;
WeightSetPointer inputweightset;
outputweightset = layer->GetOutputWeightSet();
inputweightset = layer->GetInputWeightSet();
typedef typename LayerInterfaceType::ValuePointer InterfaceValuePointer;
InterfaceValuePointer DWvalues_m_1 = inputweightset->GetPrevDWValues();
InterfaceValuePointer DWvalues_m_2 = inputweightset->GetPrev_m_2DWValues();
InterfaceValuePointer currentdeltavalues = inputweightset->GetTotalDeltaValues();
InterfaceValuePointer DBValues = inputweightset->GetTotalDeltaBValues();
InterfaceValuePointer PrevDBValues = inputweightset->GetPrevDBValues();
int input_cols = inputweightset->GetNumberOfInputNodes();
int input_rows = inputweightset->GetNumberOfOutputNodes();
vnl_matrix<ValueType> DW_m_1(input_rows, input_cols);
DW_m_1.fill(0);
vnl_matrix<ValueType> DW_m_2(input_rows, input_cols);
DW_m_2.fill(0);
vnl_vector<ValueType> DB_temp;
DB_temp.set_size(inputweightset->GetNumberOfOutputNodes());
DB_temp.fill(0);
vnl_vector<ValueType> DB;
vnl_vector<ValueType> DB_m_1;
DB.set_size(inputweightset->GetNumberOfOutputNodes());
DB_m_1.set_size(inputweightset->GetNumberOfOutputNodes());
DB.fill(0);
DB_m_1.fill(0);
DB.copy_in(DBValues);
DB_m_1.copy_in(PrevDBValues);
if (!inputweightset->GetFirstPass())
{
DW_m_1.copy_in(DWvalues_m_1);
}
if (!inputweightset->GetSecondPass())
{
DW_m_2.copy_in(DWvalues_m_2);
}
vnl_matrix<ValueType> DW_temp(currentdeltavalues,
inputweightset->GetNumberOfOutputNodes(),
inputweightset->GetNumberOfInputNodes());
vnl_matrix<ValueType> DW_temp1(inputweightset->GetNumberOfOutputNodes(),
inputweightset->GetNumberOfInputNodes());
DW_temp1.fill(0);
//Momentum
if (!inputweightset->GetFirstPass())
{
DW_temp1 = (DW_temp * lr *(1 - m_Momentum)) + (DW_m_1 * m_Momentum);
}
else
{
DW_temp1 = DW_temp*lr;
}
DB_temp=(DB*lr);
inputweightset->SetDWValues(DW_temp1.data_block());
inputweightset->SetDBValues(DB_temp.data_block());
}
template<class LayerType, class TTargetVector>
void
ErrorBackPropagationLearningWithMomentum<LayerType,TTargetVector>
::Learn( LayerInterfaceType * itkNotUsed(layer), TTargetVector itkNotUsed(errors),ValueType itkNotUsed(lr))
{
//It appears that this interface should not be called.
//itkExceptionMacrto(<< "This should never be called");
}
/** Print the object */
template<class LayerType, class TTargetVector>
void
ErrorBackPropagationLearningWithMomentum<LayerType,TTargetVector>
::PrintSelf( std::ostream& os, Indent indent ) const
{
os << indent << "ErrorBackPropagationLearningWithMomentum(" << this << ")" << std::endl;
os << indent << "m_Momentum = " << m_Momentum << std::endl;
Superclass::PrintSelf( os, indent );
}
} // end namespace Statistics
} // end namespace itk
#endif
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