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[RBM]

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- DrawComponent: use fixed value scaling
- Rbm: fixed weight decay
- Rbm: fixed sparsity


git-svn-id: http://moon:8086/svn/software/trunk/projects/RBM@298 b431acfa-c32f-4a4a-93f1-934dc6c82436
This commit is contained in:
jens
2016-06-22 19:11:09 +00:00
parent 9d00654932
commit 866a0349db
4 changed files with 46 additions and 67 deletions
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Source/DrawComponent.cpp
+6 -21
View File
@@ -29,13 +29,15 @@ void mylog(const char* format, ...);
//[/MiscUserDefs]
//==============================================================================
DrawComponent::DrawComponent (int width, int height)
DrawComponent::DrawComponent (int width, int height, float offset, float scale)
: m_pListener(nullptr)
{
//[UserPreSize]
m_width = width;
m_height = height;
m_offset = offset;
m_scale = scale;
m_scaleX = 1.0;
m_scaleY = 1.0;
m_pG = nullptr;
@@ -231,36 +233,19 @@ RowVectorXd& DrawComponent::getData ()
void DrawComponent::DrawData ()
{
double a;
RowVectorXd temp = m_data;
double min = +1E12;
double max = -1E12;
for (int i=0; i < m_width*m_height; i++)
{
min = std::min<double>(min, (double)temp[i]);
max = std::max<double>(max, (double)temp[i]);
}
if (min < 0)
{
for (int i=0; i < m_width*m_height; i++)
{
temp[i] -= min;
}
max -= min;
}
for (int i=0; i < m_width*m_height; i++)
{
temp[i] /= max;
temp[i] = std::min<double>(1.0, (double)temp[i]);
temp[i] = std::max<double>(-1.0, (double)temp[i]);
}
for (int i=0; i < m_height; i++)
{
for (int j=0; j < m_width; j++)
{
a = std::min<double>(std::max<double>((double)temp[i*m_width + j], 0), 1);
m_pG->setColour(Colour(Colours::white).greyLevel(a));
m_pG->setColour(Colour(Colours::white).greyLevel(m_offset + m_scale*temp[i*m_width + j]));
m_pG->fillRect(m_scaleX*j, m_scaleY*i, m_scaleX, m_scaleY);
}
}
Source/DrawComponent.h
+3 -1
View File
@@ -49,7 +49,7 @@ class DrawComponent : public Component
{
public:
//==============================================================================
DrawComponent (int width, int height);
DrawComponent (int width, int height, float offset=0.0, float scale=1.0);
~DrawComponent();
//==============================================================================
@@ -79,6 +79,8 @@ private:
DrawListener *m_pListener;
int m_width;
int m_height;
float m_offset;
float m_scale;
float m_scaleX;
float m_scaleY;
ScopedPointer<Graphics>m_pG;
Source/Rbm.hpp
+10 -33
View File
@@ -27,7 +27,7 @@ public:
Params()
: m_constantSigma(1.0)
, m_sigmaDecay(1.0)
, m_weightDecay(0.01)
, m_weightDecay(0.00001)
, m_lambda(1.0)
, m_sparsity(0.05)
, m_muWeights(0.1)
@@ -69,17 +69,6 @@ public:
, m_progress(0)
{
Noise_Init(&m_noise, 0x32727155);
#if 1
VectorXd a(4);
a << 1, 2, 3, 4;
VectorXd b(4);
b.array() = -a.array().exp();
cout << b << endl;
#endif
m_variableSigma.fill(m_params.m_constantSigma);
updateHiddenBatch();
}
@@ -289,9 +278,9 @@ public:
{
onProgressChanged();
// When the hidden units are being driven by data, always use stochastic binary states
if (m_params.m_doSampleBatch)
{
// When the hidden units are being driven by data, always use stochastic binary states
sample(batch_sampled, batch);
// Create hidden layer base on sampled training data
@@ -310,10 +299,7 @@ public:
// Update weights (positive phase)
dBiasV_curr = batch.colwise().sum();
if (!m_params.m_doSparse)
{
dBiasH_curr = h.colwise().sum();
}
dW_curr = batch.transpose() * h;
for (gibbs=0; gibbs < m_params.m_numGibbs; gibbs++)
@@ -348,36 +334,27 @@ public:
// Update weights (negative phase)
dBiasV_curr -= m_v.colwise().sum();
if (!m_params.m_doSparse)
{
dBiasH_curr -= h.colwise().sum();
}
dW_curr -= m_v.transpose() * h;
m_w.visibleBias() += mu_biasV*(m_params.m_momentum*dBiasV + (1-m_params.m_momentum)*dBiasV_curr);
dBiasV = dBiasV_curr;
m_w.weights() += mu_w*(m_params.m_momentum*dW + (1-m_params.m_momentum)*dW_curr - m_params.m_weightDecay*m_w.weights());
dW = dW_curr;
if (m_params.m_doSparse)
{
// Create hidden representation given v
toHiddenBatch(h, batch);
dBiasH_curr = m_params.m_sparsity * MatrixXd::Ones(dBiasH.rows(), dBiasH.cols()) - h.colwise().mean();
m_w.hiddenBias() += m_params.m_muSparsity*(m_params.m_momentum*dBiasH + (1-m_params.m_momentum)*dBiasH_curr);
dBiasH = dBiasH_curr;
// cout << "Mean(" << m_sparsity << ") = " << (double)sumBiasH.array().mean() << endl;
// cout << sumBiasH << endl;
MatrixXd h1 = h-MatrixXd::Ones(h.rows(), h.cols())*m_params.m_sparsity;
RowVectorXd hm = h1.colwise().mean();
m_w.hiddenBias() -= m_params.m_muSparsity * hm;
}
else
{
m_w.hiddenBias() += mu_biasH*(m_params.m_momentum*dBiasH + (1-m_params.m_momentum)*dBiasH_curr);
dBiasH = dBiasH_curr;
}
dBiasH = dBiasH_curr;
m_w.weights() -= m_params.m_weightDecay*m_w.weights();
m_w.weights() += mu_w*(m_params.m_momentum*dW + (1-m_params.m_momentum)*dW_curr);
dW = dW_curr;
if (m_variableSigma[0] > sigmaMin)
{
Source/RbmComponent.cpp
+16 -1
View File
@@ -44,7 +44,7 @@ RbmComponent::RbmComponent (Weights &weights, MatrixXd const &batch, RbmComponen
DrawTraining->setListener(this);
addAndMakeVisible (DrawReconstruction = new DrawComponent (vNumX, vNumY));
addAndMakeVisible (DrawWeights = new DrawComponent (vNumX, vNumY));
addAndMakeVisible (DrawWeights = new DrawComponent (vNumX, vNumY, 0.5, 0.5));
addAndMakeVisible (DrawVars = new DrawComponent (vNumX, vNumY));
addAndMakeVisible (DrawHidden = new DrawComponent (hNum, 1));
DrawHidden->setListener(this);
@@ -56,6 +56,21 @@ RbmComponent::RbmComponent (Weights &weights, MatrixXd const &batch, RbmComponen
setSize (430, 130);
resized();
MatrixXd m = MatrixXd::Random(4,3);
MatrixXd m2 = MatrixXd::Zero(4,3);
cout << "Rows = " << m.rows() << ", cols = " << m.cols() << endl;
cout << "m = " << endl << m << endl;
cout << "max = " << endl << m.rowwise().maxCoeff() << endl;
cout << "m.colwise().sum() = " << endl << m.colwise().sum() << endl;
for (MatrixXf::Index i=0; i < m.rows(); i++)
{
MatrixXf::Index j = 8;
cout << "max = " << endl << m.row(i).maxCoeff(&j);
cout << "at row = " << i << ", col = " << j << endl;
m2(i, j) = m(i, j);
}
cout << "m2 = " << endl << m2 << endl;
}
RbmComponent::~RbmComponent()