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/*=========================================================================
*
* Copyright Insight Software Consortium
*
* Licensed under the Apache License, Version 2.0 (the "License");
* you may not use this file except in compliance with the License.
* You may obtain a copy of the License at
*
* http://www.apache.org/licenses/LICENSE-2.0.txt
*
* Unless required by applicable law or agreed to in writing, software
* distributed under the License is distributed on an "AS IS" BASIS,
* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
* See the License for the specific language governing permissions and
* limitations under the License.
*
*=========================================================================*/
#ifndef itkErrorBackPropagationLearningWithMomentum_hxx
#define itkErrorBackPropagationLearningWithMomentum_hxx
#include "itkErrorBackPropagationLearningWithMomentum.h"
#include "vnl/vnl_matrix.h"
#include <fstream>
namespace itk
{
namespace Statistics
{
template<typename LayerType, typename TTargetVector>
ErrorBackPropagationLearningWithMomentum <LayerType,TTargetVector>
::ErrorBackPropagationLearningWithMomentum()
{
m_Momentum = 0.9; //Default
}
template<typename LayerType, typename TTargetVector>
void
ErrorBackPropagationLearningWithMomentum<LayerType,TTargetVector>
::Learn(LayerInterfaceType * layer, ValueType lr)
{
typedef typename LayerInterfaceType::WeightSetType::Pointer WeightSetPointer;
//WeightSetConstPointer outputweightset = layer->GetOutputWeightSet();
WeightSetPointer inputweightset = layer->GetModifiableInputWeightSet();
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();
const int input_cols = inputweightset->GetNumberOfInputNodes();
const 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<typename LayerType, typename 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<typename LayerType, typename 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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