jens/Rbm-legacy
1
0
Fork 0
Code Issues Pull Requests Packages Projects Releases Wiki Activity

[RBM]

Browse Source 
- GUI: added gaussian hidden, added mini batch size
- Rbm: added mini batch training revised sample functions, reverted to old weight decay


git-svn-id: http://moon:8086/svn/software/trunk/projects/RBM@305 b431acfa-c32f-4a4a-93f1-934dc6c82436
This commit is contained in:
jens
2016-07-07 19:27:33 +00:00
parent 4979ab41b4
commit 57cdfd7065
4 changed files with 161 additions and 87 deletions
Download Patch File Download Diff File Expand all files Collapse all files
Source/Rbm.hpp
+10 -3
View File
@@ -29,6 +29,7 @@ public:
, m_muSparsity(0.01)
, m_momentum(0.5)
, m_useVisibleGaussian(false)
, m_useHiddenGaussian(false)
, m_doRaoBlackwell(true)
, m_doSampleVisible(false)
, m_doSampleBatch(false)
@@ -36,6 +37,7 @@ public:
, m_doNormalizeData(false)
, m_doLearnVariance(false)
, m_numGibbs(1)
, m_miniBatchSize(100)
{
}
@@ -48,6 +50,7 @@ public:
double m_muSparsity;
double m_momentum;
bool m_useVisibleGaussian;
bool m_useHiddenGaussian;
bool m_doRaoBlackwell;
bool m_doSampleVisible;
bool m_doSampleBatch;
@@ -55,6 +58,7 @@ public:
bool m_doNormalizeData;
bool m_doLearnVariance;
size_t m_numGibbs;
size_t m_miniBatchSize;
};
Rbm(Weights &weights, const MatrixXd &batch);
@@ -68,7 +72,8 @@ public:
static void probsGaussian(MatrixXd &src, const MatrixXd &sigma);
static void probsGaussian(RowVectorXd &src, const RowVectorXd &sigma);
void sampleGaussian(MatrixXd &dst, MatrixXd const &src, const MatrixXd &sigma);
void sampleGaussian(MatrixXd &src, const MatrixXd &sigma);
void sampleGaussian(MatrixXd &srcDst, const MatrixXd &sigma);
void sampleGaussian(MatrixXd &srcDst, const double &sigma);
RowVectorXd normalizeData(RowVectorXd const &src, RowVectorXd const &mu, RowVectorXd const &var);
RowVectorXd calcMean(MatrixXd const &batch);
RowVectorXd calcSigma(MatrixXd const &batch);
@@ -85,6 +90,7 @@ public:
void setLambda(double value);
void setSparsity(double value);
void setUseVisibleGaussian(bool flag);
void setUseHiddenGaussian(bool flag);
void setDoRaoBlackwell(bool flag);
void setDoSampleVisible(bool flag);
void setDoSampleBatch(bool flag);
@@ -92,11 +98,11 @@ public:
void setNormalizeData(bool flag);
void setDoLearnVariance(bool flag);
void setNumGibbs(size_t value);
void setMiniBatchSize(size_t size);
void setMuWeights(double value);
void setMuSparsity(double value);
void setMomentum(double value);
MatrixXd const& getHiddenBatch();
MatrixXd const& getVisibleBatch();
MatrixXd const& getBatch();
void updateHiddenBatch();
Params const& params();
@@ -104,12 +110,13 @@ public:
private:
Weights &m_w;
MatrixXd const &m_batch;
MatrixXd m_v;
MatrixXd m_h;
RowVectorXd m_variableSigma;
noise_gen_t m_noise;
double m_progress;
Params m_params;
void noiseGaussian(MatrixXd &dst);
void noiseUniform(MatrixXd &dst);
protected:
virtual void onProgressChanged()