Files
Rbm/source/main.cpp
T
2019-10-24 18:54:40 +00:00

130 lines
2.8 KiB
C++

#include <streambuf>
#include <cstdio>
#include <cmath>
#include <armadillo>
#include "Rbm.hpp"
class RbmListener : public Rbm::IListener
{
public:
RbmListener() {}
virtual ~RbmListener() {}
bool onProgress(const Rbm::Status &status)
{
std::cout << "Progress : " << 100*status.progress << " %" << std::endl;
std::cout << "epoch : " << status.epoch << std::endl;
std::cout << "trainingSizeRemain: " << status.trainingSizeRemain << 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;
}
};
arma::mat loadTraining(const char *pFilename)
{
uint32_t numTraining = 0;
uint32_t numVisible = 0;
FILE *pFile;
pFile = fopen(pFilename,"r");
if (!pFile)
{
return 0;
}
int result = fscanf(pFile, "%d\n", &numTraining);
if (result < 0)
{
return 0;
}
result = fscanf(pFile, "%d\n", &numVisible);
if (result < 0)
{
return 0;
}
arma::mat data = arma::zeros(numTraining, numVisible);
uint32_t i, j;
for (i=0; i < numTraining; i++)
{
for (j=0; j < numVisible; j++)
{
float v;
int result = fscanf(pFile, "%f", &v);
if (result > 0)
{
data(i, j) = v;
}
}
}
fclose(pFile);
return data;
}
void saveWeight(const char *pFilename, size_t numVisibleX, size_t numVisibleY, const arma::mat &w, const arma::mat &bv, const arma::mat &bh)
{
FILE *pFile;
pFile = fopen(pFilename,"w");
if (!pFile)
return;
size_t numHidden = bh.n_elem;
size_t numVisible = bv.n_elem;
fprintf(pFile, "%d %d %d\n", (int)numVisibleX, (int)numVisibleY, (int)numHidden);
uint32_t i, j;
for (i=0; i < numVisible; i++)
{
fprintf(pFile, "%3.6f\n", bv(i));
}
for (i=0; i < numHidden; i++)
{
fprintf(pFile, "%3.6f\n", bh(i));
}
for (i=0; i < numVisible; i++)
{
for (j=0; j < numHidden; j++)
{
fprintf(pFile, "%3.6f ", w(i,j));
}
fprintf(pFile, "\n");
}
fclose(pFile);
}
int main()
{
printf("Hallo, Welt!\n");
RbmListener statusDisplay;
Rbm::Params params;
arma::mat batch = loadTraining("mnist_2.training.dat");
size_t numTraining = batch.n_rows;
size_t numVisible = batch.n_cols;
size_t numHidden = 64;
printf("Loaded %d training samples\n", (int)numTraining);
arma::mat w = arma::zeros(numVisible, numHidden);
arma::mat bv = arma::zeros(1, numVisible);
arma::mat bh = arma::zeros(1, numHidden);
Rbm rbm(params, w, bv, bh);
rbm.train(batch, 1000, 100, &statusDisplay);
saveWeight("mnist_2.weights.dat", 28, 28, w, bv, bh);
arma::mat v = arma::randu(numTraining, numVisible);
arma::mat h = rbm.toHiddenProbs(v);
arma::mat r = rbm.toVisibleProbs(h);
return 0;
}