smoothing_strategy.hxx

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/*
 * smoothing_strategy.hxx
 *
 *  Created on: Jan 7, 2014
 *      Author: bsavchyn
 */

#ifndef SMOOTHING_STRATEGY_HXX_
#define SMOOTHING_STRATEGY_HXX_
#include <opengm/inference/inference.hxx>
#include <opengm/inference/trws/trws_reparametrization.hxx>
#include <algorithm>

namespace opengm{
namespace trws_base{

template<class VALUETYPE>
struct SmoothingParameters
{
    typedef VALUETYPE ValueType;
    typedef enum {ADAPTIVE_DIMINISHING,WC_DIMINISHING,ADAPTIVE_PRECISIONORIENTED,WC_PRECISIONORIENTED,FIXED} SmoothingStrategyType;


   static SmoothingStrategyType getSmoothingStrategyType(const std::string& name)
   {
         if (name.compare("WC_DIMINISHING")==0) return WC_DIMINISHING;
         else if (name.compare("ADAPTIVE_PRECISIONORIENTED")==0)  return ADAPTIVE_PRECISIONORIENTED;
         else if (name.compare("WC_PRECISIONORIENTED")==0)  return WC_PRECISIONORIENTED;
         else if (name.compare("FIXED")==0) return FIXED;
         else return ADAPTIVE_DIMINISHING;
   }

   static std::string getString(SmoothingStrategyType strategytype)
   {
      switch (strategytype)
      {
      case ADAPTIVE_DIMINISHING: return std::string("ADAPTIVE_DIMINISHING");
      case WC_DIMINISHING   : return std::string("WC_DIMINISHING");
      case ADAPTIVE_PRECISIONORIENTED   : return std::string("ADAPTIVE_PRECISIONORIENTED");
      case WC_PRECISIONORIENTED   : return std::string("WC_PRECISIONORIENTED");
      case FIXED: return std::string("FIXED");
      default: return std::string("UNKNOWN");
      }
   }

    SmoothingParameters(ValueType smoothingGapRatio=4,
                    ValueType smoothingValue=0.0,
                    ValueType smoothingDecayMultiplier=-1.0,
                    ValueType precision=0,
                    SmoothingStrategyType smoothingStrategy=ADAPTIVE_DIMINISHING):
            smoothingGapRatio_(smoothingGapRatio),
            smoothingValue_(smoothingValue),
            smoothingDecayMultiplier_(smoothingDecayMultiplier),
            precision_(precision),
            smoothingStrategy_(smoothingStrategy){};

   ValueType smoothingGapRatio_;
   ValueType smoothingValue_;
   ValueType smoothingDecayMultiplier_;
   ValueType precision_;
   SmoothingStrategyType smoothingStrategy_;
};





//template<class VALUETYPE,class GM>
template<class GM>
struct SmoothingBasedInference_Parameter_Base
{
   //typedef VALUETYPE ValueType;
   typedef typename  GM::ValueType ValueType;
   typedef DecompositionStorage<GM> Storage;
   typedef SmoothingParameters<ValueType> SmoothingParametersType;
   typedef SumProdTRWS_Parameters<ValueType> SumProdSolverParametersType;
   typedef MaxSumTRWS_Parameters<ValueType> MaxSumSolverParametersType;
   typedef PrimalLPBound_Parameter<ValueType> PrimalLPEstimatorParametersType;

   SmoothingBasedInference_Parameter_Base(typename Storage::StructureType decompositionType,
                             bool lazyLPPrimalBoundComputation,
                             const SmoothingParametersType& smoothingParameters,
                              const SumProdSolverParametersType& sumProdSolverParameters,
                             const MaxSumSolverParametersType& maxSumSolverParameters,
                             const PrimalLPEstimatorParametersType& primalLPEstimatorParameters):
                                decompositionType_(decompositionType),
                                lazyLPPrimalBoundComputation_(lazyLPPrimalBoundComputation),
                                smoothingParameters_(smoothingParameters),
                                sumProdSolverParameters_(sumProdSolverParameters),
                                maxSumSolverParameters_(maxSumSolverParameters),
                                primalLPEstimatorParameters_(primalLPEstimatorParameters)
   {};
   virtual ~SmoothingBasedInference_Parameter_Base(){};

   typename Storage::StructureType decompositionType_;
   bool lazyLPPrimalBoundComputation_;
   const SmoothingParametersType& getSmoothingParameters()const{return smoothingParameters_;}
   const SumProdSolverParametersType& getSumProdSolverParameters()const{return sumProdSolverParameters_;}
   const MaxSumSolverParametersType& getMaxSumSolverParameters()const{return maxSumSolverParameters_;}
   const PrimalLPEstimatorParametersType& getPrimalLPEstimatorParameters()const{return primalLPEstimatorParameters_;}
protected:
   SmoothingParametersType smoothingParameters_;
   SumProdSolverParametersType sumProdSolverParameters_;
   MaxSumSolverParametersType maxSumSolverParameters_;
   PrimalLPEstimatorParametersType primalLPEstimatorParameters_;
};

//template<class ValueType,class GM>
template<class GM>
//struct SmoothingBasedInference_Parameter : public trws_base::SmoothingBasedInference_Parameter_Base<typename GM::ValueType,GM>
struct SmoothingBasedInference_Parameter : public trws_base::SmoothingBasedInference_Parameter_Base<GM>
{
   typedef typename  GM::ValueType ValueType;
    typedef trws_base::DecompositionStorage<GM> Storage;
   typedef typename trws_base::SmoothingBasedInference_Parameter_Base<GM> parent;
   typedef typename parent::SmoothingParametersType SmoothingParametersType;
   typedef typename parent::SumProdSolverParametersType SumProdSolverParametersType;
   typedef typename parent::MaxSumSolverParametersType MaxSumSolverParametersType;
   typedef typename parent::PrimalLPEstimatorParametersType PrimalLPEstimatorParametersType;
   typedef typename SmoothingParametersType::SmoothingStrategyType SmoothingStrategyType;

   SmoothingBasedInference_Parameter(size_t numOfExternalIterations=0,
             ValueType precision=1.0,
             bool absolutePrecision=true,
             size_t numOfInternalIterations=3,
             typename Storage::StructureType decompositionType=Storage::GENERALSTRUCTURE,
             ValueType smoothingGapRatio=4,
             ValueType startSmoothingValue=0.0,
             ValueType primalBoundPrecision=std::numeric_limits<ValueType>::epsilon(),
             size_t maxPrimalBoundIterationNumber=100,
             size_t presolveMaxIterNumber=100,
             bool canonicalNormalization=true,
             ValueType presolveMinRelativeDualImprovement=0.01,
             bool lazyLPPrimalBoundComputation=true,
             ValueType smoothingDecayMultiplier=-1.0,
             SmoothingStrategyType smoothingStrategy=SmoothingParametersType::ADAPTIVE_DIMINISHING,
//           bool worstCaseSmoothing=false,
             bool fastComputations=true,
             bool verbose=false
             )
    :parent(decompositionType,
          lazyLPPrimalBoundComputation,
          SmoothingParametersType(smoothingGapRatio,startSmoothingValue,smoothingDecayMultiplier,precision,smoothingStrategy),
          //SumProdSolverParametersType(numOfInternalIterations,startSmoothingValue,precision,absolutePrecision,std::numeric_limits<ValueType>::epsilon(),fastComputations,canonicalNormalization),
          SumProdSolverParametersType(numOfInternalIterations,startSmoothingValue,precision,absolutePrecision,0.0,fastComputations,canonicalNormalization),
          MaxSumSolverParametersType(presolveMaxIterNumber,precision,absolutePrecision,presolveMinRelativeDualImprovement,fastComputations,canonicalNormalization),
          PrimalLPEstimatorParametersType(primalBoundPrecision,maxPrimalBoundIterationNumber)
          ),
     numOfExternalIterations_(numOfExternalIterations),
     verbose_(verbose)
     {};

     size_t numOfExternalIterations_;
     bool verbose_;

     /*
      * Main algorithm parameters
      */
     size_t& maxNumberOfIterations(){return numOfExternalIterations_;}
     const size_t& maxNumberOfIterations()const {return numOfExternalIterations_;}

     size_t& numberOfInternalIterations(){return parent::sumProdSolverParameters_.maxNumberOfIterations_;}
     const size_t& numberOfInternalIterations()const{return parent::sumProdSolverParameters_.maxNumberOfIterations_;}

//   ValueType& precision(){return parent::sumProdSolverParameters_.precision_;}
     const ValueType& precision()const{return parent::sumProdSolverParameters_.precision_;}
     void setPrecision(ValueType precision){parent::maxSumSolverParameters_.precision_=parent::sumProdSolverParameters_.precision_=parent::smoothingParameters_.precision_=precision;}

     bool&      isAbsolutePrecision(){return parent::sumProdSolverParameters_.absolutePrecision_;}
     const bool&      isAbsolutePrecision()const {return parent::sumProdSolverParameters_.absolutePrecision_;}

     ValueType& smoothingGapRatio(){return parent::smoothingParameters_.smoothingGapRatio_;}
     const ValueType& smoothingGapRatio()const{return parent::smoothingParameters_.smoothingGapRatio_;}

     bool& lazyLPPrimalBoundComputation(){return parent::lazyLPPrimalBoundComputation_;}
     const bool& lazyLPPrimalBoundComputation()const{return parent::lazyLPPrimalBoundComputation_;}

//   bool& lazyDerivativeComputation(){return lazyDerivativeComputation_;}
//   const bool& lazyDerivativeComputation()const {return lazyDerivativeComputation_;}

      ValueType& smoothingDecayMultiplier(){return parent::smoothingParameters_.smoothingDecayMultiplier_;}
     const ValueType& smoothingDecayMultiplier()const{return parent::smoothingParameters_.smoothingDecayMultiplier_;}

//   bool& worstCaseSmoothing(){return parent::smoothingParameters_.worstCaseSmoothing_;}
//   const bool& worstCaseSmoothing()const{return parent::smoothingParameters_.worstCaseSmoothing_;}
     SmoothingStrategyType& smoothingStrategy(){return parent::smoothingParameters_.smoothingStrategy_;}
     const SmoothingStrategyType& smoothingStrategy()const{return parent::smoothingParameters_.smoothingStrategy_;}

     typename Storage::StructureType& decompositionType(){return parent::decompositionType_;}
     const typename Storage::StructureType& decompositionType()const{return parent::decompositionType_;}

     const ValueType& startSmoothingValue()const{return parent::sumProdSolverParameters_.smoothingValue_;}
     void setStartSmoothingValue(ValueType val){ parent::smoothingParameters_.smoothingValue_=parent::sumProdSolverParameters_.smoothingValue_=val;}//TODO: duplicated!

     const bool& fastComputations()const{return parent::sumProdSolverParameters_.fastComputations_;}
     void setFastComputations(bool fast){parent::sumProdSolverParameters_.fastComputations_=parent::maxSumSolverParameters_.fastComputations_=fast;}

     const bool& canonicalNormalization()const{return parent::sumProdSolverParameters_.canonicalNormalization_;}
     void setCanonicalNormalization(bool canonical){parent::sumProdSolverParameters_.canonicalNormalization_=parent::maxSumSolverParameters_.canonicalNormalization_=canonical;}

     /*
      * Presolve parameters
      */
     size_t& maxNumberOfPresolveIterations(){return parent::maxSumSolverParameters_.maxNumberOfIterations_;}
     const size_t& maxNumberOfPresolveIterations()const{return parent::maxSumSolverParameters_.maxNumberOfIterations_;}

     ValueType& presolveMinRelativeDualImprovement() {return parent::maxSumSolverParameters_.minRelativeDualImprovement_;}
     const ValueType& presolveMinRelativeDualImprovement()const {return parent::maxSumSolverParameters_.minRelativeDualImprovement_;}

     /*
      * Fractional primal bound estimator parameters
      */
     size_t& maxPrimalBoundIterationNumber(){return parent::primalLPEstimatorParameters_.maxIterationNumber_;}
     const size_t& maxPrimalBoundIterationNumber()const{return parent::primalLPEstimatorParameters_.maxIterationNumber_;}

     ValueType& primalBoundRelativePrecision(){return parent::primalLPEstimatorParameters_.relativePrecision_;}
     const ValueType& primalBoundRelativePrecision()const{return parent::primalLPEstimatorParameters_.relativePrecision_;}

     bool& verbose(){return verbose_;}
     const bool& verbose()const{return verbose_;}

#ifdef TRWS_DEBUG_OUTPUT
     void print(std::ostream& fout)const
     {
        fout << "maxNumberOfIterations="<< maxNumberOfIterations()<<std::endl;
        fout << "numberOfInternalIterations="<< numberOfInternalIterations()<<std::endl;
        fout << "precision=" <<precision()<<std::endl;
        fout <<"isAbsolutePrecision=" << isAbsolutePrecision()<< std::endl;
        fout <<"smoothingGapRatio="  << smoothingGapRatio()<< std::endl;
        fout <<"lazyLPPrimalBoundComputation="<<lazyLPPrimalBoundComputation()<< std::endl;
        fout <<"smoothingDecayMultiplier=" << smoothingDecayMultiplier()<< std::endl;

        fout << "smoothing strategy="<<SmoothingParametersType::getString(smoothingStrategy())<<std::endl;
        fout << "decompositionType=" << Storage::getString(decompositionType()) << std::endl;

        fout <<"startSmoothingValue=" << startSmoothingValue()<<std::endl;
        fout <<"fastComputations="<<fastComputations()<<std::endl;
        fout <<"canonicalNormalization="<<canonicalNormalization()<<std::endl;

        /*
         * Presolve parameters
         */
        fout <<"maxNumberOfPresolveIterations="<<maxNumberOfPresolveIterations()<<std::endl;
        fout <<"presolveMinRelativeDualImprovement=" <<presolveMinRelativeDualImprovement()<<std::endl;

        /*
         * Fractional primal bound estimator parameters
         */
        fout <<"maxPrimalBoundIterationNumber="<<maxPrimalBoundIterationNumber()<<std::endl;
        fout <<"primalBoundRelativePrecision=" <<primalBoundRelativePrecision()<<std::endl;
        fout <<"verbose="<<verbose()<<std::endl;
     }
#endif
};



//====================================================================================
template<class GM, class ACC>
class SmoothingBasedInference;

template<class GM,class ACC>
class SmoothingStrategy
{
public:
   typedef ACC AccumulationType;
   typedef GM GraphicalModelType;
   OPENGM_GM_TYPE_TYPEDEFS;
   typedef SmoothingParameters<ValueType> Parameter;

   SmoothingStrategy(ValueType smoothingMultiplier, const Parameter& param=Parameter(), std::ostream& fout=std::cout):
      _fout(fout),
      _initializationStage(true),
      _smoothingMultiplier(smoothingMultiplier),
      _parameters(param),
      _oracleCallsCounter(0){};
   virtual ~SmoothingStrategy(){};
   ValueType InitSmoothing(SmoothingBasedInference<GM,ACC>& smoothInference,
         ValueType primalBound,
         ValueType dualBound){
      //ValueType initialSmoothing=getStartingSmoothing();
      return _InitAdaptiveSmoothing(smoothInference,primalBound,dualBound,getStartingSmoothing(primalBound,dualBound));
   };
   ValueType UpdateSmoothing(ValueType smoothingValue,
         ValueType primalBound,
         ValueType dualBound,
         ValueType smoothDualBound,
         ValueType smoothingDerivative,
         size_t iterationCounter)
   {
   if (SmoothingMustBeDecreased(smoothingValue,primalBound,dualBound,smoothDualBound,smoothingDerivative,iterationCounter))
   {
      smoothingValue=   std::max((ValueType)(smoothingValue/2.0),SmoothingEstimateValue(primalBound,smoothDualBound,smoothingDerivative));

#ifdef TRWS_DEBUG_OUTPUT
    _fout << "Smoothing decreased to = "<<smoothingValue<<std::endl;
#endif
   }
   return smoothingValue;
   };

   bool SmoothingMustBeDecreased(ValueType smoothingValue,
         ValueType primalBound,
         ValueType dualBound,
         ValueType smoothDualBound,
         ValueType smoothingDerivative,
         size_t iterationCounter)
   {
      ValueType rhs=fabs(primalBound-smoothDualBound);

      return (smoothingValue > SmoothingEstimateValue(primalBound,smoothDualBound,smoothingDerivative));
   }


   //---------------------------------------------------

   template<class DualDecompositionStorage >
   static ValueType ComputeSmoothingMultiplier(const DualDecompositionStorage& storage)
   {
      //compute max number of labels
      typename DualDecompositionStorage::LabelType numOfLabels=0;
      for (size_t i=0;i<storage.numberOfSharedVariables();++i)
         numOfLabels=std::max(numOfLabels,storage.numberOfLabels(i));

      //multiplier = \sum_{i=1}^n\log|\SX_i| <= \sum_{i=1}^n numOfLabels
      ValueType multiplier=0;
      ValueType logLabels=log((ValueType)numOfLabels);
      for (size_t i=0;i<storage.numberOfModels();++i)
         multiplier+=storage.size(i)*logLabels;

      return multiplier;
   }

   size_t getOracleCallsCounter()const{return _oracleCallsCounter;}

   virtual ValueType SmoothingEstimateValue(
                     ValueType primalBound,
                     ValueType smoothDualBound,
                     ValueType smoothingDerivative)const=0;

   ValueType getStartingSmoothing(ValueType primalBound,ValueType dualBound)const
   {
      if (_parameters.smoothingValue_ > 0 )
         return _parameters.smoothingValue_;
      else
          return SmoothingEstimateValue(primalBound,dualBound,_smoothingMultiplier);
   }

   ValueType getWorstCaseSmoothing()const{return _parameters.precision_/2.0/_smoothingMultiplier;}


protected:
   ValueType _InitAdaptiveSmoothing(SmoothingBasedInference<GM,ACC>& smoothInference,
         ValueType primalBound,
         ValueType dualBound,
         ValueType initialSmoothing);

   std::ostream& _fout;
   bool _initializationStage;
   ValueType _smoothingMultiplier;
   Parameter _parameters;
   size_t _oracleCallsCounter;
};

template<class GM, class ACC>
typename SmoothingStrategy<GM,ACC>::ValueType
SmoothingStrategy<GM,ACC>::_InitAdaptiveSmoothing(SmoothingBasedInference<GM,ACC>& smoothInference,
      ValueType primalBound,
      ValueType dualBound,
      ValueType smoothing)//initial smoothing
{
#ifdef TRWS_DEBUG_OUTPUT
   _fout <<"_maxsumsolver.value()="<<primalBound<<", _maxsumsolver.bound()="<<dualBound<<std::endl;
   _fout << "Initial smoothing="<<smoothing<<std::endl;
#endif

   ValueType derivativeValue;
   ValueType smoothDualBound=smoothInference.UpdateSmoothDualEstimates(smoothing,&derivativeValue);

   _oracleCallsCounter=1;
   do{
      ++_oracleCallsCounter;
      smoothing*=2;
#ifdef TRWS_DEBUG_OUTPUT
         _fout << "test smoothing = "<<smoothing<<std::endl;
#endif
      smoothDualBound=smoothInference.UpdateSmoothDualEstimates(smoothing,&derivativeValue);
#ifdef TRWS_DEBUG_OUTPUT
         _fout <<"smoothDualBound="<<smoothDualBound<<std::endl;
#endif
   }while (!SmoothingMustBeDecreased(smoothing,primalBound,dualBound,smoothDualBound,derivativeValue,0));
   smoothing/=2.0;


#ifdef TRWS_DEBUG_OUTPUT
   _fout << "Smoothing := "<<smoothing<<std::endl;
#endif
   _initializationStage= false;
   return smoothing;
}

//-----------------------------------------------------------------------

template<class GM,class ACC>
class WorstCasePrecisionOrientedSmoothing : public SmoothingStrategy<GM,ACC>
{
public:
   typedef ACC AccumulationType;
   typedef GM GraphicalModelType;
   OPENGM_GM_TYPE_TYPEDEFS;
   typedef SmoothingParameters<ValueType> Parameter;
   typedef SmoothingStrategy<GM,ACC> parent;

   WorstCasePrecisionOrientedSmoothing(ValueType smoothingMultiplier,const Parameter& param=Parameter(), std::ostream& fout=std::cout)
   :parent(smoothingMultiplier,param,fout)
   {
      if (param.smoothingValue_ > 0 )
         throw std::runtime_error("WorstCasePrecisionOrientedSmoothing()::WorstCasePrecisionOrientedSmoothing(): Error! Starting smoothing value can not be selected manually! parameter.smoothingValue_ must be<0.");
   };
   virtual ValueType SmoothingEstimateValue(
                     ValueType primalBound,
                     ValueType smoothDualBound,
                     ValueType smoothingDerivative)const
   {return parent::getWorstCaseSmoothing();}
};

//-----------------------------------------------------------------------

template<class GM,class ACC>
class AdaptivePrecisionOrientedSmoothing : public SmoothingStrategy<GM,ACC>
{
public:
   typedef ACC AccumulationType;
   typedef GM GraphicalModelType;
   OPENGM_GM_TYPE_TYPEDEFS;
   typedef SmoothingParameters<ValueType> Parameter;
   typedef SmoothingStrategy<GM,ACC> parent;

   AdaptivePrecisionOrientedSmoothing(ValueType smoothingMultiplier,const Parameter& param=Parameter(), std::ostream& fout=std::cout):parent(smoothingMultiplier,param,fout){};

   ValueType SmoothingEstimateValue(ValueType primalBound,
                        ValueType smoothDualBound,
                        ValueType smoothingDerivative)const
   {return parent::_parameters.precision_/2.0/fabs(smoothingDerivative);}

};

//-----------------------------------------------------------------------

template<class GM,class ACC>
class WorstCaseDiminishingSmoothing : public SmoothingStrategy<GM,ACC>
{
public:
   typedef ACC AccumulationType;
   typedef GM GraphicalModelType;
   OPENGM_GM_TYPE_TYPEDEFS;
   typedef SmoothingParameters<ValueType> Parameter;
   typedef SmoothingStrategy<GM,ACC> parent;

   WorstCaseDiminishingSmoothing(ValueType smoothingMultiplier,const Parameter& param=Parameter(), std::ostream& fout=std::cout):parent(smoothingMultiplier,param,fout){};

    ValueType SmoothingEstimateValue(
                  ValueType primalBound,
                  ValueType smoothDualBound,
                  ValueType smoothingDerivative)const
   {return fabs(primalBound-smoothDualBound)/parent::_parameters.smoothingGapRatio_/fabs(parent::_smoothingMultiplier);}

};


//-----------------------------------------------------------------------
template<class GM,class ACC>
class AdaptiveDiminishingSmoothing : public SmoothingStrategy<GM,ACC>
{
public:
   typedef ACC AccumulationType;
   typedef GM GraphicalModelType;
   OPENGM_GM_TYPE_TYPEDEFS;
   typedef SmoothingParameters<ValueType> Parameter;
   typedef SmoothingStrategy<GM,ACC> parent;

   AdaptiveDiminishingSmoothing(ValueType smoothingMultiplier,const Parameter& param=Parameter(), std::ostream& fout=std::cout)
   :parent(smoothingMultiplier,param,fout){};

   ValueType SmoothingEstimateValue(
                  ValueType primalBound,
                  ValueType smoothDualBound,
                  ValueType smoothingDerivative)const
   {return fabs(primalBound-smoothDualBound)/parent::_parameters.smoothingGapRatio_/fabs(smoothingDerivative);}
};

//-----------------------------------------------------------------------

template<class GM,class ACC>
class FixedSmoothing : public SmoothingStrategy<GM,ACC>
{
public:
   typedef ACC AccumulationType;
   typedef GM GraphicalModelType;
   OPENGM_GM_TYPE_TYPEDEFS;
   typedef SmoothingParameters<ValueType> Parameter;
   typedef SmoothingStrategy<GM,ACC> parent;

   FixedSmoothing(ValueType smoothingMultiplier,const Parameter& param=Parameter(), std::ostream& fout=std::cout)
   :parent(smoothingMultiplier,param,fout)
   {
      if (param.smoothingValue_ <= 0 )
         throw std::runtime_error("FixedSmoothing()::FixedSmoothing(): Smoothing value must be positive!");
   };

   ValueType SmoothingEstimateValue(ValueType primalBound,
                  ValueType smoothDualBound,
                  ValueType smoothingDerivative)const
   {return parent::_parameters.smoothingValue_;}
};

//==============================================================
template<class GM, class ACC>
class SmoothingBasedInference : public Inference<GM, ACC>
{
public:
   typedef Inference<GM, ACC> parent;
   typedef ACC AccumulationType;
   typedef GM GraphicalModelType;
   OPENGM_GM_TYPE_TYPEDEFS;

     typedef trws_base::DecompositionStorage<GM> Storage;
     typedef trws_base::SumProdTRWS<GM,ACC> SumProdSolver;
     typedef trws_base::MaxSumTRWS<GM,ACC> MaxSumSolver;
     typedef PrimalLPBound<GM,ACC> PrimalBoundEstimator;

     //typedef typename MaxSumSolver::ReparametrizerType ReparametrizerType;
     typedef TRWS_Reparametrizer<Storage,ACC> ReparametrizerType;
     typedef SmoothingStrategy<GM,ACC> SmoothingStrategyType;

     typedef SmoothingBasedInference_Parameter<GM> Parameter;

     SmoothingBasedInference(const GraphicalModelType& gm, const Parameter& param
#ifdef TRWS_DEBUG_OUTPUT
           ,std::ostream& fout=std::cout
#endif
      ):
     _parameters(param),
     _storage(gm,param.decompositionType_),
     _sumprodsolver(_storage,param.getSumProdSolverParameters()
#ifdef TRWS_DEBUG_OUTPUT
           ,fout
#endif
           ),
     _maxsumsolver(_storage,param.getMaxSumSolverParameters()
#ifdef TRWS_DEBUG_OUTPUT
            ,fout//fout
#endif
           ),
     _estimator(gm,param.getPrimalLPEstimatorParameters()),
#ifdef TRWS_DEBUG_OUTPUT
     _fout(fout),
#endif
     _bestPrimalLPbound(ACC::template neutral<ValueType>()),
     _bestPrimalBound(ACC::template neutral<ValueType>()),
     _bestDualBound(ACC::template ineutral<ValueType>()),
     _bestIntegerBound(ACC::template neutral<ValueType>()),
     _bestIntegerLabeling(_storage.masterModel().numberOfVariables(),0.0)
     {
        ValueType smoothingMultiplier=SmoothingStrategyType::ComputeSmoothingMultiplier(_storage);

        if ( (param.smoothingStrategy()==Parameter::SmoothingParametersType::WC_PRECISIONORIENTED)  ||
            (param.smoothingStrategy()==Parameter::SmoothingParametersType::ADAPTIVE_PRECISIONORIENTED))
           if (!param.isAbsolutePrecision())
              throw std::runtime_error("SmoothingBasedInference: Error: relative precision can be used only with diminishing smoothing.");

        switch (param.smoothingStrategy())
        {
        case Parameter::SmoothingParametersType::ADAPTIVE_DIMINISHING:
           psmoothingStrategy=new typename trws_base::AdaptiveDiminishingSmoothing<GM,ACC>(smoothingMultiplier,param.getSmoothingParameters()
#ifdef TRWS_DEBUG_OUTPUT
                       ,_fout
#endif
                       );
            break;
        case Parameter::SmoothingParametersType::WC_DIMINISHING:
           psmoothingStrategy=new typename trws_base::WorstCaseDiminishingSmoothing<GM,ACC>(smoothingMultiplier,param.getSmoothingParameters()
#ifdef TRWS_DEBUG_OUTPUT
                          ,_fout
#endif
                          );
           break;
        case Parameter::SmoothingParametersType::ADAPTIVE_PRECISIONORIENTED:
             psmoothingStrategy=new typename trws_base::AdaptivePrecisionOrientedSmoothing<GM,ACC>(smoothingMultiplier,param.getSmoothingParameters()
#ifdef TRWS_DEBUG_OUTPUT
                       ,_fout
#endif
                       );
           break;
        case Parameter::SmoothingParametersType::WC_PRECISIONORIENTED:
            psmoothingStrategy=new typename trws_base::WorstCasePrecisionOrientedSmoothing<GM,ACC>(smoothingMultiplier,param.getSmoothingParameters()
#ifdef TRWS_DEBUG_OUTPUT
                       ,_fout
#endif
                       );
           break;
        case   Parameter::SmoothingParametersType::FIXED:
           psmoothingStrategy=new typename trws_base::FixedSmoothing<GM,ACC>(smoothingMultiplier,param.getSmoothingParameters()
           #ifdef TRWS_DEBUG_OUTPUT
                                ,_fout
           #endif
                                );
           break;
        default: throw std::runtime_error("SmoothingBasedInference: Error: Unknown smoothing strategy type");
        };
     }

     virtual ~SmoothingBasedInference(){delete psmoothingStrategy;  }

     InferenceTermination arg(std::vector<LabelType>& out, const size_t = 1) const
     {out = _bestIntegerLabeling;
      return opengm::NORMAL;}
     const GraphicalModelType& graphicalModel() const { return _storage.masterModel(); }

     ValueType bound() const{return _bestDualBound;}
     ValueType value() const{return _bestIntegerBound;}

     ValueType UpdateSmoothDualEstimates(ValueType smoothingValue,ValueType* pderivativeValue);

     void getTreeAgreement(std::vector<bool>& out,std::vector<LabelType>* plabeling=0,std::vector<std::vector<LabelType> >* ptreeLabelings=0){_maxsumsolver.getTreeAgreement(out,plabeling,ptreeLabelings);}
     Storage& getDecompositionStorage(){return _storage;}
     const typename MaxSumSolver::FactorProperties& getFactorProperties()const {return _maxsumsolver.getFactorProperties();}

     ReparametrizerType * getReparametrizer(const typename ReparametrizerType::Parameter& params=typename ReparametrizerType::Parameter())//const //TODO: make it constant
      {return new ReparametrizerType(_storage,_maxsumsolver.getFactorProperties(),params);}

     InferenceTermination marginal(const IndexType varID, IndependentFactorType& out) //const
     {
        _marginalsTemp.resize(_storage.numberOfLabels(varID));
        _sumprodsolver.GetMarginals(varID, _marginalsTemp.begin());
       // OPENGM_ASSERT(_marginalsTemp.size() == out.size());
        out.assign(graphicalModel(), &varID, &varID+1, ACC::template neutral<ValueType>());
        for (LabelType i=0;i<out.size();++i)
           out(i)=_marginalsTemp[i];
          return NORMAL;
     }
protected:
     template<class VISITOR>
     InferenceTermination _Presolve(VISITOR& visitor,size_t* piterCounter=0);
     template<class VISITOR>
     size_t _EstimateStartingSmoothing(VISITOR& visitor);
     bool _UpdateSmoothing(ValueType primalBound,ValueType dualBound, ValueType smoothDualBound, ValueType derivativeValue,size_t iterationCounterPlus1=0);
     ValueType _EstimateRhoDerivative()const;
     ValueType _FastEstimateRhoDerivative()const{return (_sumprodsolver.bound()-_maxsumsolver.bound())/_sumprodsolver.GetSmoothing();}
     void _UpdatePrimalEstimator();
     void _SelectOptimalBoundsAndLabeling();
     bool _isLPBoundComputed()const;
     bool _CheckStoppingCondition(InferenceTermination*);

     Parameter          _parameters;
     Storage            _storage;
     SumProdSolver         _sumprodsolver;
     MaxSumSolver          _maxsumsolver;
     PrimalBoundEstimator  _estimator;
#ifdef TRWS_DEBUG_OUTPUT
     std::ostream& _fout;
#endif
     ValueType     _bestPrimalLPbound;
     ValueType     _bestPrimalBound;//best primal bound overall

     ValueType     _bestDualBound;
     ValueType     _bestIntegerBound;
     std::vector<LabelType> _bestIntegerLabeling;

   SmoothingStrategyType* psmoothingStrategy;
     /*
      * optimization of computations
      */
   //mutable
    typename SumProdSolver::OutputContainerType _marginalsTemp;
};

template<class GM,class ACC>
typename SmoothingBasedInference<GM,ACC>::ValueType
SmoothingBasedInference<GM,ACC>::UpdateSmoothDualEstimates(ValueType smoothingValue,ValueType* pderivativeValue)
{
     _sumprodsolver.SetSmoothing(smoothingValue);
     _sumprodsolver.ForwardMove();
     _sumprodsolver.GetMarginalsAndDerivativeMove();
     *pderivativeValue=_EstimateRhoDerivative();
     return _sumprodsolver.bound();
};

template<class GM,class ACC>
template<class VISITOR>
size_t SmoothingBasedInference<GM,ACC>::_EstimateStartingSmoothing(VISITOR& visitor)
{
   ValueType smoothingValue= psmoothingStrategy->InitSmoothing(*this,_maxsumsolver.value(),_maxsumsolver.bound());
   _sumprodsolver.SetSmoothing(smoothingValue);
   return psmoothingStrategy->getOracleCallsCounter();
};

template<class GM,class ACC>
bool SmoothingBasedInference<GM,ACC>::_UpdateSmoothing(ValueType primalBound,ValueType dualBound, ValueType smoothDualBound, ValueType derivativeValue,size_t iterationCounterPlus1)
{
      ValueType newSmoothing=psmoothingStrategy->UpdateSmoothing(_sumprodsolver.GetSmoothing(),primalBound,dualBound,smoothDualBound,derivativeValue,iterationCounterPlus1-1);
      if (newSmoothing != _sumprodsolver.GetSmoothing())
            {
               _sumprodsolver.SetSmoothing(newSmoothing);
               return true;
            }
      else
         return false;
}

template<class GM,class ACC>
typename SmoothingBasedInference<GM,ACC>::ValueType
SmoothingBasedInference<GM,ACC>::_EstimateRhoDerivative()const
{
   ValueType derivative=0.0;

   for (size_t i=0;i<_storage.numberOfModels();++i)
   {
      ValueType delta;

      ACC::op(_sumprodsolver.getDerivative(i),(_sumprodsolver.getBound(i)-_maxsumsolver.getBound(i))/_sumprodsolver.GetSmoothing(),delta);

      derivative+=delta;
   }

   return derivative;
}

template<class GM,class ACC>
void SmoothingBasedInference<GM,ACC>::_UpdatePrimalEstimator()
{
 std::pair<ValueType,ValueType> bestNorms=std::make_pair((ValueType)0.0,(ValueType)0.0);
 ValueType numberOfVariables=_storage.masterModel().numberOfVariables();
 for (IndexType var=0;var<numberOfVariables;++var)
 {
    _marginalsTemp.resize(_storage.numberOfLabels(var));
    std::pair<ValueType,ValueType> norms=_sumprodsolver.GetMarginals(var, _marginalsTemp.begin());

    bestNorms.second=std::max(bestNorms.second,norms.second);
    bestNorms.first+=norms.first*norms.first;

    transform_inplace(_marginalsTemp.begin(),_marginalsTemp.end(),trws_base::make0ifless<ValueType>(norms.second));

    TransportSolver::_Normalize(_marginalsTemp.begin(),_marginalsTemp.end(),(ValueType)0.0);
    _estimator.setVariable(var,_marginalsTemp.begin());
 }
#ifdef TRWS_DEBUG_OUTPUT
 _fout << "l2 gradient norm="<<sqrt(bestNorms.first)<<", "<<"l_inf gradient norm="<<bestNorms.second<<std::endl;
#endif
};

template<class GM,class ACC>
void SmoothingBasedInference<GM,ACC>::_SelectOptimalBoundsAndLabeling()
{
   //Best integer bound...
   if (ACC::bop(_sumprodsolver.value(),_maxsumsolver.value()))
      {
      _bestIntegerLabeling=_sumprodsolver.arg();
       _bestIntegerBound=_sumprodsolver.value();
      }else
      {
       _bestIntegerLabeling=_maxsumsolver.arg();
       _bestIntegerBound=_maxsumsolver.value();
      }

   //Best primalBound
   ACC::op(_bestPrimalLPbound,_bestIntegerBound,_bestPrimalBound);
#ifdef TRWS_DEBUG_OUTPUT
   _fout << "_bestPrimalBound=" <<_bestPrimalBound<<std::endl;
#endif

   //Best dual bound...
   if (ACC::ibop(_sumprodsolver.bound(),_maxsumsolver.bound()))
       _bestDualBound=_sumprodsolver.bound();
   else
       _bestDualBound=_maxsumsolver.bound();

}

template<class GM,class ACC>
template<class VISITOR>
opengm::InferenceTermination SmoothingBasedInference<GM,ACC>::_Presolve(VISITOR& visitor, size_t* piterCounter)
{
#ifdef TRWS_DEBUG_OUTPUT
    _fout << "Running TRWS presolve..."<<std::endl;
#endif
    return _maxsumsolver.infer_visitor_updates(visitor,piterCounter);
}

template<class GM,class ACC>
bool SmoothingBasedInference<GM,ACC>::_isLPBoundComputed()const
{
   return (!_parameters.lazyLPPrimalBoundComputation_ || !ACC::bop(_sumprodsolver.value(),_bestPrimalBound) );
}

template<class GM,class ACC>
bool SmoothingBasedInference<GM,ACC>::_CheckStoppingCondition(InferenceTermination* preturncode)
{
  if( _isLPBoundComputed())
  {
    _UpdatePrimalEstimator();

   ACC::op(_estimator.getTotalValue(),_bestPrimalLPbound);
#ifdef TRWS_DEBUG_OUTPUT
   _fout << "_primalLPbound=" <<_estimator.getTotalValue()<<std::endl;
#endif
  }
    _SelectOptimalBoundsAndLabeling();

   if (_maxsumsolver.CheckTreeAgreement(preturncode)) return true;

   if (_sumprodsolver.CheckDualityGap(_bestPrimalBound,_maxsumsolver.bound()))
   {
#ifdef TRWS_DEBUG_OUTPUT
     _fout << "SmoothingBasedInference::_CheckStoppingCondition(): Precision attained! Problem solved!"<<std::endl;
#endif
    *preturncode=CONVERGENCE;
    return true;
   }

   return false;
}
//====================================================

}//trws_base
}//opengm

#endif /* SMOOTHING_STRATEGY_HXX_ */