- integrated RnnStack

git-svn-id: http://moon:8086/svn/software/trunk/projects/Rbm@826 b431acfa-c32f-4a4a-93f1-934dc6c82436

source/RnnStack.cpp

@@ -13,8 +13,9 @@
 
 #include "RnnStack.hpp"
 
-RnnStack::RnnStack(const std::string &name)
+RnnStack::RnnStack(const std::string &name, size_t numContext)
 : AStack(StackType::Rnn, name)
+, m_numContext(numContext)
 {
 }
 
@@ -22,13 +23,82 @@ RnnStack::~RnnStack()
 {
 }
 
+size_t RnnStack::getSeqLen()
+{
+	return numLayers();
+}
+
+size_t RnnStack::numContext()
+{
+	return m_numContext;
+}
+
+arma::mat RnnStack::v_to_vc(const arma::mat& v) const
+{
+	arma::mat c = arma::zeros(v.n_rows, m_numContext);
+	return arma::join_rows(v, c);
+}
+
+arma::mat RnnStack::v_to_vc(const arma::mat& v, const arma::mat& c) const
+{
+	return arma::join_rows(v, c);
+}
+
+arma::mat RnnStack::vc_to_c(const arma::mat& vc) const
+{
+	size_t numVisible = vc.n_cols;
+	
+	if (m_numContext == 0)
+	{
+		return arma::mat(1, 0);
+	}
+	return vc.submat(0, numVisible - m_numContext, 0, numVisible - 1);
+}
+
+arma::mat RnnStack::vc_to_v(const arma::mat& vc) const
+{
+	size_t numVisible = vc.n_cols;
+	return vc.submat(0, 0, vc.n_rows - 1, numVisible - m_numContext - 1);
+}
+
+arma::mat RnnStack::trainingBatchFrom(size_t layerId, const arma::mat& batch)
+{
+	arma::mat vc = batch;
+	Layer *pLayer = getLayer(0);
+	while (pLayer)
+	{
+		if (layerId == pLayer->id())
+		{
+			break;
+		}
+		arma::mat c = pLayer->to_h_gibbs(vc);
+		arma::mat v = arma::shift(vc_to_v(vc), layerId, 1);
+		vc = v_to_vc(v, c);
+		pLayer = pLayer->next;
+	}
+	return vc;
+}
 
 void RnnStack::train(const arma::mat& batch, Rbm::IListener* pListener)
 {
-
+	arma::mat thisBatch = batch;
+	Layer *pLayer = getLayer(0);
+	while (pLayer)
+	{
+		thisBatch = trainingBatchFrom(pLayer->id(), thisBatch);
+		pLayer->train(thisBatch, pListener);
+		pLayer = pLayer->next;
+	}
 }
 
 void RnnStack::train(size_t layerId, const arma::mat& batch, Rbm::IListener* pListener)
 {
-
+	arma::mat thisBatch = batch;
+	Layer *pLayer = getLayer(layerId);
+	if (pLayer)
+	{
+		thisBatch = trainingBatchFrom(pLayer->id(), batch);
+		pLayer->train(thisBatch, pListener);
+	}
 }
+