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- Layer: removed legacy training load/save

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git-svn-id: http://moon:8086/svn/software/trunk/projects/Rbm@779 b431acfa-c32f-4a4a-93f1-934dc6c82436
This commit is contained in:
jens
2022-01-10 16:00:39 +00:00
parent 408af988cb
commit c9cb208275
1 changed files with 4 additions and 71 deletions
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source/Stack.cpp
+4 -71
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@@ -239,54 +239,13 @@ size_t Stack::loadTrainingBatch(bool doNormalize)
if (success)
{
if (doNormalize)
{
m_trainingBatch = Rbm::normalize(m_trainingBatch);
}
std::cout << "Loaded " << m_trainingBatch.n_rows << " training samples\n";
return m_trainingBatch.n_rows;
}
uint32_t numTraining = 0;
uint32_t numVisible = 0;
FILE *pFile = fopen(filename.c_str(), "r");
if (!pFile)
{
std::cout << "Could not open " << filename << "!" << std::endl;
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;
}
m_trainingBatch = 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)
{
m_trainingBatch(i, j) = v;
}
}
}
fclose(pFile);
std::cout << "Loaded " << numTraining << " training samples\n";
if (doNormalize)
{
m_trainingBatch = Rbm::normalize(m_trainingBatch);
}
return numTraining;
}
size_t Stack::saveTrainingBatch()
@@ -299,32 +258,6 @@ size_t Stack::saveTrainingBatch()
std::cout << "Saved " << m_trainingBatch.n_rows << " training samples\n";
return m_trainingBatch.n_rows;
}
FILE *pFile = fopen(filename.c_str(), "w");
if (!pFile)
{
std::cout << "Could not open " << filename << "!" << std::endl;
return 0;
}
fprintf(pFile, "%u\n", (uint32_t)m_trainingBatch.n_rows);
fprintf(pFile, "%u\n", (uint32_t)m_trainingBatch.n_cols);
uint32_t i, j;
for (i=0; i < m_trainingBatch.n_rows; i++)
{
for (j=0; j < m_trainingBatch.n_cols; j++)
{
fprintf(pFile, "%3.6f\n", m_trainingBatch(i, j));
}
}
fclose(pFile);
std::cout << "Saved " << m_trainingBatch.n_rows << " training samples\n";
return m_trainingBatch.n_rows;
}
size_t Stack::numTraining()