git-svn-id: http://moon:8086/svn/software/trunk/projects/Rbm@807 b431acfa-c32f-4a4a-93f1-934dc6c82436
263 lines
4.9 KiB
C++
263 lines
4.9 KiB
C++
#include <iostream>
|
|
#include <fstream>
|
|
#include <streambuf>
|
|
#include <cstdio>
|
|
#include <cmath>
|
|
#include <string>
|
|
#include <cassert>
|
|
#include <armadillo>
|
|
#include <jsoncpp/json/json.h>
|
|
#include "Rbm.hpp"
|
|
#include "Layer.hpp"
|
|
#include "Stack.hpp"
|
|
|
|
using namespace std;
|
|
using namespace arma;
|
|
|
|
class RbmListener : public Rbm::IListener
|
|
{
|
|
public:
|
|
RbmListener() {}
|
|
virtual ~RbmListener() {}
|
|
|
|
bool onProgress(Rbm *pRbm, const Rbm::Status &status)
|
|
{
|
|
std::cout << "Progress : " << status.progress << " %" << std::endl;
|
|
std::cout << "error (per mini batch) = " << status.err << std::endl;
|
|
std::cout << "error (total) = " << status.err_total << std::endl;
|
|
std::cout << "L1 = " << status.L1 << std::endl;
|
|
std::cout << "L2 = " << status.L2 << std::endl;
|
|
|
|
return true;
|
|
}
|
|
};
|
|
|
|
const char punctuation[] = {' ', '.', '!', '?', 0};
|
|
const int NUM_CODES = 1 + 26 + 10;
|
|
const int SEQ_LENGTH = 5;
|
|
|
|
int char_is(char c, const char *pTable)
|
|
{
|
|
int found = 0;
|
|
while(*pTable)
|
|
{
|
|
if (c == *pTable)
|
|
{
|
|
found = 1;
|
|
break;
|
|
}
|
|
pTable++;
|
|
}
|
|
return found;
|
|
}
|
|
|
|
int ch2idx(char c)
|
|
{
|
|
c = toupper(c);
|
|
|
|
int index = 0;
|
|
if (isalpha(c))
|
|
{
|
|
index = 1+ (int)(c-'A');
|
|
}
|
|
if (isdigit(c))
|
|
{
|
|
index = 1+26+(int)(c-'0');
|
|
}
|
|
return index;
|
|
}
|
|
|
|
char idx2ch(int index)
|
|
{
|
|
char c = '?';
|
|
if (index == 0)
|
|
{
|
|
c = ' ';
|
|
}
|
|
else if (index >= 1 and index < 27)
|
|
{
|
|
c = (char)(index + 'A' - 1);
|
|
}
|
|
else if (index >= 27 and index < 38)
|
|
{
|
|
c = (char)(index + '0' - 27);
|
|
}
|
|
return c;
|
|
}
|
|
|
|
arma::mat createTraining(const string &filename, size_t seq_len)
|
|
{
|
|
FILE *pFile;
|
|
|
|
pFile = fopen(filename.c_str(), "r");
|
|
|
|
if (!pFile)
|
|
{
|
|
std::cout << "Could not open " << filename << "!" << std::endl;
|
|
return 0;
|
|
}
|
|
|
|
int numTraining = 0;
|
|
int numVisible = seq_len*NUM_CODES;
|
|
|
|
arma::mat batch = arma::zeros(numTraining, numVisible);
|
|
arma::mat pattern = arma::zeros(seq_len, NUM_CODES);
|
|
|
|
int last_index = ch2idx(' ');
|
|
while(!feof(pFile))
|
|
{
|
|
char c;
|
|
int result = fread(&c, 1, 1, pFile);
|
|
if (result < 0)
|
|
{
|
|
break;
|
|
}
|
|
|
|
int index = ch2idx(c);
|
|
if (index == 0 and last_index == 0)
|
|
{
|
|
continue;
|
|
}
|
|
last_index = index;
|
|
pattern = arma::shift(pattern, 1);
|
|
arma::mat data = arma::zeros(1, NUM_CODES);
|
|
data[index] = 1;
|
|
pattern.row(0) = data;
|
|
arma::mat pattern_vector = pattern.as_row();
|
|
batch.insert_rows(batch.n_rows, pattern_vector);
|
|
}
|
|
fclose(pFile);
|
|
|
|
return batch;
|
|
}
|
|
|
|
struct Rnn
|
|
{
|
|
Rnn(Layer *layer)
|
|
: nV(layer->numVisible() - layer->context().n_cols)
|
|
, nH(layer->numHidden())
|
|
, nVx(layer->numVisibleX())
|
|
, nVy(layer->numVisibleY())
|
|
, nC(layer->context().n_cols)
|
|
{
|
|
|
|
}
|
|
size_t nV;
|
|
size_t nH;
|
|
size_t nVx;
|
|
size_t nVy;
|
|
size_t nC;
|
|
|
|
arma::mat vcVec_to_vMat(arma::mat const &vcVec)
|
|
{
|
|
arma::mat vVec = vcVec.submat(0, 0, 0, nV-1);
|
|
arma::mat vMat = arma::reshape(vVec, nVx, nVy);
|
|
return vMat;
|
|
}
|
|
|
|
arma::mat curr_vec(arma::mat const &vcVec)
|
|
{
|
|
arma::mat vMat = vcVec_to_vMat(vcVec);
|
|
|
|
return vMat.col(nVy-1);
|
|
}
|
|
|
|
arma::mat vcVec_next_step(arma::mat const &vcVec, arma::mat const &h)
|
|
{
|
|
arma::mat vMat = arma::shift(vcVec_to_vMat(vcVec), 1, 1);
|
|
arma::mat vVec = vMat.as_row();
|
|
|
|
arma::mat vcVec_next = arma::join_rows(vVec, h);
|
|
return vcVec_next;
|
|
}
|
|
|
|
};
|
|
|
|
arma::mat to_curr(arma::mat v)
|
|
{
|
|
return v.cols(0, NUM_CODES-1);
|
|
}
|
|
|
|
arma::mat to_next(arma::mat v)
|
|
{
|
|
return v.cols(NUM_CODES, 2*NUM_CODES-1);
|
|
}
|
|
|
|
#define CREATE_TRAINING 0
|
|
int main()
|
|
{
|
|
#if CREATE_TRAINING
|
|
arma::mat batch = createTraining("moby_ch1.txt", SEQ_LENGTH);
|
|
batch.save("poet.training.dat", arma::arma_ascii);
|
|
return 0;
|
|
#endif
|
|
|
|
Stack stack(".", "poet5");
|
|
|
|
// Load project
|
|
stack.load();
|
|
|
|
// Load weights
|
|
stack.loadWeights();
|
|
|
|
// Load training
|
|
stack.loadTrainingBatch();
|
|
|
|
Layer *layer = stack.getLayer(0);
|
|
int numTraining = stack.trainingBatch().n_rows;
|
|
|
|
arma::mat t = stack.trainingBatch();
|
|
|
|
arma::mat h = layer->toHiddenProbs(t);
|
|
arma::mat r = layer->toVisibleProbs(h);
|
|
|
|
layer->params().gibbsDoSampleHidden = false;
|
|
layer->params().gibbsDoSampleVisible = false;
|
|
|
|
Rnn rnn(layer);
|
|
|
|
printf("\nStimulus: Training\n");
|
|
for (int i=0; i < numTraining; i++)
|
|
{
|
|
arma::mat curr = rnn.curr_vec(t.row(i));
|
|
char c = idx2ch(curr.index_max());
|
|
putchar(c);
|
|
}
|
|
printf("\n");
|
|
|
|
h = layer->toHiddenProbs(t.row(0));
|
|
printf("Stimulus: Next char and current h\n");
|
|
for (int i=1; i < numTraining+1; i++)
|
|
{
|
|
arma::mat r;
|
|
layer->gibbs_hv(h, r);
|
|
arma::mat curr = rnn.curr_vec(r);
|
|
arma::mat v = rnn.vcVec_next_step(r, h);
|
|
|
|
layer->gibbs_vh(v, h);
|
|
|
|
char c = idx2ch(curr.index_max());
|
|
putchar(c);
|
|
}
|
|
printf("\n");
|
|
|
|
h = layer->toHiddenProbs(t.row(0));
|
|
printf("Stimulus: Current h\n");
|
|
for (int i=1; i < numTraining+1; i++)
|
|
{
|
|
arma::mat r;
|
|
layer->gibbs_hv(h, r);
|
|
arma::mat curr = rnn.curr_vec(r);
|
|
arma::mat v = rnn.vcVec_next_step(arma::zeros(1, r.n_cols), h);
|
|
|
|
layer->gibbs_vh(v, h);
|
|
|
|
char c = idx2ch(curr.index_max());
|
|
putchar(c);
|
|
}
|
|
|
|
printf("\n\nEnd of program\n");
|
|
|
|
return 0;
|
|
}
|