itkRegularStepGradientDescentOptimizerv4.h

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/*=========================================================================
 *
 *  Copyright NumFOCUS
 *
 *  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 itkRegularStepGradientDescentOptimizerv4_h
#define itkRegularStepGradientDescentOptimizerv4_h
 
#include "itkGradientDescentOptimizerv4.h"
#include <itkCompensatedSummation.h>
 
namespace itk
{
template <typename TInternalComputationValueType = double>
class ITK_TEMPLATE_EXPORT RegularStepGradientDescentOptimizerv4
  : public GradientDescentOptimizerv4Template<TInternalComputationValueType>
{
public:
  ITK_DISALLOW_COPY_AND_MOVE(RegularStepGradientDescentOptimizerv4);
 
  using Self = RegularStepGradientDescentOptimizerv4;
  using Superclass = GradientDescentOptimizerv4Template<TInternalComputationValueType>;
  using Pointer = SmartPointer<Self>;
  using ConstPointer = SmartPointer<const Self>;
 
  itkTypeMacro(RegularStepGradientDescentOptimizerv4, GradientDescentOptimizerv4Template);
 
  itkNewMacro(Self);
 
 
  using InternalComputationValueType = TInternalComputationValueType;
 
  using DerivativeType = typename Superclass::DerivativeType;
 
  using MeasureType = typename Superclass::MeasureType;
  using IndexRangeType = typename Superclass::IndexRangeType;
  using ScalesType = typename Superclass::ScalesType;
  using ParametersType = typename Superclass::ParametersType;
 
  using CompensatedSummationType = CompensatedSummation<InternalComputationValueType>;
 
  itkSetMacro(MinimumStepLength, TInternalComputationValueType);
  itkGetConstReferenceMacro(MinimumStepLength, TInternalComputationValueType);
 
  itkSetMacro(RelaxationFactor, TInternalComputationValueType);
  itkGetConstReferenceMacro(RelaxationFactor, TInternalComputationValueType);
 
  itkSetMacro(GradientMagnitudeTolerance, TInternalComputationValueType);
  itkGetConstReferenceMacro(GradientMagnitudeTolerance, TInternalComputationValueType);
 
  itkSetMacro(CurrentLearningRateRelaxation, MeasureType);
  itkGetConstReferenceMacro(CurrentLearningRateRelaxation, MeasureType);
 
  void
  StartOptimization(bool doOnlyInitialization = false) override;
 
  void
  EstimateLearningRate() override;
 
  double
  GetCurrentStepLength() const;
 
protected:
  void
  AdvanceOneStep() override;
 
  void
  ModifyGradientByScalesOverSubRange(const IndexRangeType & subrange) override;
  void
  ModifyGradientByLearningRateOverSubRange(const IndexRangeType & subrange) override;
 
 
  RegularStepGradientDescentOptimizerv4();
 
  ~RegularStepGradientDescentOptimizerv4() override = default;
 
  void
  PrintSelf(std::ostream & os, Indent indent) const override;
 
 
private:
  TInternalComputationValueType m_RelaxationFactor;
 
  TInternalComputationValueType m_MinimumStepLength;
 
  TInternalComputationValueType m_GradientMagnitudeTolerance;
 
  MeasureType m_CurrentLearningRateRelaxation;
};
 
} // end namespace itk
 
#ifndef ITK_MANUAL_INSTANTIATION
#  include "itkRegularStepGradientDescentOptimizerv4.hxx"
#endif
 
#endif