Files
Rbm/source/RnnStack.cpp
T
jens 9a8ad70a0b - improved RnnStack
- AStack: context doesn't belong o training data

git-svn-id: http://moon:8086/svn/software/trunk/projects/Rbm@827 b431acfa-c32f-4a4a-93f1-934dc6c82436
2022-01-18 14:27:39 +00:00

132 lines
2.9 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: RnnStack.cpp
* Author: jens
*
* Created on 17. Januar 2022, 12:43
*/
#include "RnnStack.hpp"
RnnStack::RnnStack(const std::string &name, size_t numContext)
: AStack(StackType::Rnn, name)
, m_numContext(numContext)
{
}
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 v_to_vc(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)
{
Layer *pLayer = getLayer(0);
arma::mat c = arma::zeros(batch.n_rows, m_numContext);
arma::mat v = vc_to_v(batch);
arma::mat vc = v_to_vc(v, c);
while (pLayer)
{
if (layerId == pLayer->id())
{
break;
}
c = pLayer->to_h_gibbs(vc);
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)
{
// thisBatch = {padding | batch}
int numTraining = batch.n_rows;
arma::mat padding = arma::zeros(getSeqLen()-1, batch.n_cols);
arma::mat batch_padded = arma::join_cols(padding, batch);
arma::mat c = arma::zeros(numTraining, m_numContext);
for (int i=0; i < getSeqLen(); i++)
{
Layer *pLayer = getLayer(i);
int k = getSeqLen()-i-1;
arma::mat batch_shifted = batch_padded.rows(k, numTraining+k-1);
arma::mat vc = v_to_vc(batch_shifted, c);
pLayer->train(vc, pListener);
c = pLayer->to_h_gibbs(vc);
pLayer = pLayer->next;
}
}
void RnnStack::train(size_t layerId, const arma::mat& batch, Rbm::IListener* pListener)
{
}
arma::mat RnnStack::step_forward(arma::mat &state, const arma::mat& v_curr)
{
arma::mat c = arma::zeros(1, m_numContext);
arma::mat z = arma::zeros(arma::size(v_curr));
arma::mat r;
if (state.is_empty())
{
state = arma::zeros(getSeqLen(), v_curr.n_cols);
}
state = arma::shift(state, 1, 0);
state.row(0) = v_curr;
for (int j=0; j < getSeqLen(); j++)
{
Layer *pLayer = getLayer(j);
arma::mat v = arma::join_rows(state.row(j), z);
arma::mat vc = v_to_vc(v, c);
c = pLayer->to_h_gibbs(vc);
vc = pLayer->to_v_gibbs(c);
r = to_next(vc_to_v(vc));
}
return r;
}