- refactored

git-svn-id: http://moon:8086/svn/software/trunk/projects/Rbm@815 b431acfa-c32f-4a4a-93f1-934dc6c82436

source/DeepStack.cpp

@@ -0,0 +1,163 @@
+/*
+ * To change this license header, choose License Headers in Project Properties.
+ * To change this template file, choose Tools | Templates
+ * and open the template in the editor.
+ */
+
+/* 
+ * File:   DeepStack.cpp
+ * Author: jens
+ * 
+ * Created on 25. Oktober 2019, 18:26
+ */
+#include <cassert>
+#include "DeepStack.hpp"
+
+using namespace std;
+
+DeepStack::DeepStack(const std::string &dir, const std::string &name, StackType type)
+: AStack(dir, type, name)
+{
+}
+
+DeepStack::DeepStack(const DeepStack& orig)
+: AStack(orig)
+{
+}
+
+DeepStack::~DeepStack()
+{ 
+}
+
+void DeepStack::weightsInit(double stddev)
+{
+	Layer *pLayer = m_pLayers;
+	while(pLayer)
+	{
+		pLayer->weightsInit(stddev);
+		pLayer = pLayer->next;
+	}
+}
+
+bool DeepStack::loadWeights()
+{
+	Layer *pLayer = m_pLayers;
+	while(pLayer)
+	{
+		if (!pLayer->weightsLoad(m_dir, m_name))
+		{
+			return false;
+		}
+		pLayer = pLayer->next;
+	}
+	return true;
+}
+
+bool DeepStack::saveWeights()
+{
+	Layer *pLayer = m_pLayers;
+	while(pLayer)
+	{
+		if (!pLayer->weightsSave(m_dir, m_name))
+		{
+			return false;
+		}
+		pLayer = pLayer->next;
+	}
+	return true;
+}
+
+void DeepStack::train(Rbm::IListener* pListener)
+{
+	Layer *pLayer = m_pLayers;
+	while(pLayer)
+	{
+		std::cout << m_name << ": " << " Training of layer " << std::to_string(pLayer->id()) << std::endl;
+		pLayer->calcContextBatch(m_trainingBatch);
+		pLayer->train(m_trainingBatch, pListener);
+		pLayer = pLayer->next;
+	}
+}
+
+arma::mat& DeepStack::trainingBatch()
+{
+	return m_trainingBatch;
+}
+
+arma::mat DeepStack::trainingBatch(Layer* pThatLayer)
+{
+	arma::mat thisBatch = m_trainingBatch;
+	Layer *pLayer = m_pLayers;
+	while (pLayer)
+	{
+		if (pLayer->id() == pThatLayer->id())
+		{
+			break;
+		}
+		thisBatch = pLayer->toHiddenProbs(thisBatch);
+		pLayer = pLayer->next;
+	}
+	return thisBatch;
+}
+
+size_t DeepStack::loadTrainingBatch(bool doNormalize)
+{
+	std::string filename = m_dir + "/" + m_name + ".training.dat";
+	std::string path = m_dir + "/" + m_name + ".training.dat";
+	bool success = m_trainingBatch.load(filename, arma::arma_ascii);
+
+	if (success)
+	{
+		if (doNormalize)
+		{
+			m_trainingBatch = Rbm::normalize(m_trainingBatch);
+		}
+		std::cout << "Loaded " << m_trainingBatch.n_rows << " training samples\n";
+	}
+	
+	// Migrate context part to training data
+	size_t numTraining = m_trainingBatch.n_rows;
+	size_t numVisible = getLayer(0)->numVisible();
+	
+	if (m_trainingBatch.n_cols < numVisible)
+	{
+		size_t diff = numVisible - m_trainingBatch.n_cols;
+		arma::mat training_with_ctx = arma::join_rows(m_trainingBatch, arma::zeros(numTraining, diff));
+		m_trainingBatch = training_with_ctx;
+	}
+	else if (m_trainingBatch.n_cols > numVisible)
+	{
+		m_trainingBatch = m_trainingBatch.submat(0, 0, numTraining-1, numVisible-1);
+	}
+
+	return m_trainingBatch.n_rows;
+}
+
+size_t DeepStack::saveTrainingBatch()
+{
+	std::string filename = m_dir + "/" + m_name + ".training.dat";
+	bool success = m_trainingBatch.save(filename, arma::arma_ascii);
+
+	if (success)
+	{
+		std::cout << "Saved " << m_trainingBatch.n_rows << " training samples\n";
+	}
+	
+	return m_trainingBatch.n_rows;
+}
+
+size_t DeepStack::numTraining()
+{
+	return m_trainingBatch.n_rows;
+}
+
+void DeepStack::addTraining(const arma::mat &toAdd)
+{ 
+	m_trainingBatch.insert_rows(m_trainingBatch.n_rows, toAdd);
+}
+
+void DeepStack::delTraining(int index)
+{
+	m_trainingBatch.shed_row(index);
+}
+