Files
Rbm/source/Stack.cpp
T
jens fa2014b4dd - trainingdata always contains context
- load / store training batch with context
- on load: add context part to  legacy training batches 
- removed Rbm::setBatch()

git-svn-id: http://moon:8086/svn/software/trunk/projects/Rbm@790 b431acfa-c32f-4a4a-93f1-934dc6c82436
2022-01-12 08:12:35 +00:00

289 lines
5.7 KiB
C++

/*
* 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: Stack.cpp
* Author: jens
*
* Created on 25. Oktober 2019, 18:26
*/
#include <cassert>
#include "Stack.hpp"
using namespace std;
Stack::Stack(const std::string &dir, const std::string &name)
: m_dir(dir)
, m_name(name)
, m_pLayers(nullptr)
{
}
Stack::Stack(const Stack& orig)
: m_dir(orig.m_dir)
, m_name(orig.m_name)
, m_pLayers(orig.m_pLayers)
{
}
Stack::~Stack()
{
Layer *pLayer = m_pLayers;
while(pLayer)
{
Layer *pNextLayer = pLayer->next;
delete pLayer;
pLayer = pNextLayer;
}
}
void Stack::setName(const std::string& name)
{
m_name = name;
}
size_t Stack::numLayers()
{
size_t count = 0;
Layer *pLayer = m_pLayers;
while(pLayer)
{
count++;
pLayer = pLayer->next;
}
return count;
}
void Stack::addLayer(Layer *pOtherLayer)
{
if (!m_pLayers)
{
m_pLayers = pOtherLayer;
pOtherLayer->prev = nullptr;
}
else
{
Layer *pLayer = m_pLayers;
while(pLayer->next)
{
pLayer = pLayer->next;
}
pLayer->next = pOtherLayer;
pOtherLayer->prev = pLayer;
}
}
void Stack::delLayer(Layer* pLayer)
{
assert(!"Stack::delLayer: Not implemented!");
}
Layer* Stack::getLayer(size_t layerId) const
{
Layer *pLayer = m_pLayers;
while(pLayer)
{
if (pLayer->id() == layerId)
{
return pLayer;
}
pLayer = pLayer->next;
}
return nullptr;
}
bool Stack::load(LayerConstructor *pLayerConstructor)
{
std::cout << "Importing Project " << m_name << std::endl;
ifstream ifs(m_dir + "/" + m_name + string(".prj"));
Json::Reader reader;
Json::Value project;
reader.parse(ifs, project);
const string &name = project["stack"]["name"].asString();
Json::Value &layers = project["stack"]["layers"];
for (int i=0; i < layers.size(); i++)
{
Json::Value &layer = layers[i];
string layername = layer["name"].asString();
int numVisibleX = layer["numVisibleX"].asInt();
int numVisibleY = layer["numVisibleY"].asInt();
int numHidden = layer["numHidden"].asInt();
int numContext = layer["numContext"].asInt();
Layer *pLayer = nullptr;
if (!pLayerConstructor)
{
pLayer = new Layer(layername, i, numVisibleX, numVisibleY, numHidden, numContext);
}
else
{
pLayer = pLayerConstructor->onConstruct(layername, i, numVisibleX, numVisibleY, numHidden, numContext);
}
assert(pLayer != nullptr);
pLayer->fromJson(layer["rbm"]);
addLayer(pLayer);
}
return true;
}
bool Stack::save()
{
std::cout << "Exporting Project " << m_name << std::endl;
ofstream ofs(m_dir + "/" + m_name + string(".prj"));
Json::StyledWriter writer;
Json::Value project;
project["stack"]["name"] = m_name;
Json::Value layers(Json::arrayValue);
Layer *pLayer = m_pLayers;
while(pLayer)
{
layers.append(pLayer->toJson());
pLayer = pLayer->next;
}
project["stack"]["layers"] = layers;
ofs << writer.write(project);
return true;
}
void Stack::weightsInit(double stddev)
{
Layer *pLayer = m_pLayers;
while(pLayer)
{
pLayer->weightsInit(stddev);
pLayer = pLayer->next;
}
}
bool Stack::loadWeights()
{
Layer *pLayer = m_pLayers;
while(pLayer)
{
if (!pLayer->weightsLoad(m_dir, m_name))
{
return false;
}
pLayer = pLayer->next;
}
return true;
}
bool Stack::saveWeights()
{
Layer *pLayer = m_pLayers;
while(pLayer)
{
if (!pLayer->weightsSave(m_dir, m_name))
{
return false;
}
pLayer = pLayer->next;
}
return true;
}
void Stack::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& Stack::trainingBatch()
{
return m_trainingBatch;
}
arma::mat Stack::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 Stack::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 numContext = getLayer(0)->context().n_cols;
size_t numTraining = m_trainingBatch.n_rows;
if (numContext > 0 and m_trainingBatch.n_cols != getLayer(0)->numVisible())
{
arma::mat training_with_ctx = arma::join_rows(m_trainingBatch, arma::zeros(numTraining, numContext));
m_trainingBatch = training_with_ctx;
}
return m_trainingBatch.n_rows;
}
size_t Stack::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 Stack::numTraining()
{
return m_trainingBatch.n_rows;
}
void Stack::addTraining(const arma::mat &toAdd)
{
m_trainingBatch.insert_rows(m_trainingBatch.n_rows, toAdd);
}
void Stack::delTraining(int index)
{
m_trainingBatch.shed_row(index);
}