BernoulliRBM.h

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#ifndef GRT_BERNOULLI_RBM_HEADER
#define GRT_BERNOULLI_RBM_HEADER

#include "../../Util/GRTTypedefs.h"
#include "../../DataStructures/MatrixFloat.h"
#include "../../CoreModules/MLBase.h"

GRT_BEGIN_NAMESPACE

class GRT_API BernoulliRBM : public MLBase{
 
 public:
 BernoulliRBM(const UINT numHiddenUnits = 100,const UINT maxNumEpochs = 1000,const Float learningRate = 1,const Float learningRateUpdate = 1,const Float momentum = 0.5,const bool useScaling = true,const bool randomiseTrainingOrder = true);
 
 virtual ~BernoulliRBM();
 
 bool predict_(VectorFloat &inputData);
 
 bool predict_(VectorFloat &inputData,VectorFloat &outputData);
 
 bool predict_(const MatrixFloat &inputData,MatrixFloat &outputData,const UINT rowIndex);
 
 virtual bool train_(MatrixFloat &data);
 
 virtual bool reset();
 
 virtual bool clear();
 
 virtual bool save( std::fstream &file ) const;
 
 virtual bool load( std::fstream &file );
 
 bool reconstruct(const VectorFloat &input,VectorFloat &output);
 
 virtual bool print() const;
 
 bool getRandomizeWeightsForTraining() const;
 UINT getNumVisibleUnits() const;
 UINT getNumHiddenUnits() const;
 VectorFloat getOutputData() const;
 const MatrixFloat& getWeights() const;
 
 bool setNumHiddenUnits(const UINT numHiddenUnits);
 bool setMomentum(const Float momentum);
 bool setLearningRateUpdate(const Float learningRateUpdate);
 bool setRandomizeWeightsForTraining(const bool randomizeWeightsForTraining);
 bool setBatchSize(const UINT batchSize);
 bool setBatchStepSize(const UINT batchStepSize);
 
 //Tell the compiler we are using the base class train method to stop hidden virtual function warnings
 using MLBase::save;
 using MLBase::load;
 using MLBase::train; 
 using MLBase::predict; 
 using MLBase::train_; 
 using MLBase::predict_; 
 
 protected:
 bool loadLegacyModelFromFile( std::fstream &file );
 
 inline Float sigmoidRandom(const Float &x){
 return (1.0 / (1.0 + exp(-x)) > rand.getRandomNumberUniform(0.0,1.0)) ? 1.0 : 0.0;
 }
 
 bool randomizeWeightsForTraining;
 UINT numVisibleUnits;
 UINT numHiddenUnits;
 UINT batchSize;
 UINT batchStepSize;
 Float momentum;
 Float learningRateUpdate;
 MatrixFloat weightsMatrix;
 VectorFloat visibleLayerBias;
 VectorFloat hiddenLayerBias;
 VectorFloat ph_mean;
 VectorFloat ph_sample;
 VectorFloat nv_means;
 VectorFloat nv_samples;
 VectorFloat nh_means;
 VectorFloat nh_samples;
 VectorFloat outputData;
 Vector<MinMax> ranges;
 Random rand;
 
 struct BatchIndexs{
 UINT startIndex;
 UINT endIndex;
 UINT batchSize;
 };
 typedef struct BatchIndexs BatchIndexs;
 
};

GRT_END_NAMESPACE

#endif //GRT_BERNOULLI_RBM_HEADER