- create training data

git-svn-id: http://moon:8086/svn/software/trunk/projects/Rbm@795 b431acfa-c32f-4a4a-93f1-934dc6c82436
This commit is contained in:
2022-01-12 18:18:43 +00:00
parent 7c4b6fdb24
commit b69c735f5d
+49 -68
View File
@@ -29,79 +29,60 @@ class RbmListener : public Rbm::IListener
}
};
arma::mat createTraining(const string &filename)
{
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 = 26 + 10;
arma::mat batch = arma::zeros(numTraining, numVisible);
while(!feof(pFile))
{
char c;
int result = fread(&c, 1, 1, pFile);
if (result < 0)
{
break;
}
c = toupper(c);
int index;
if (isalpha(c))
{
index = (int)(c-'A');
}
if (isdigit(c))
{
index = (int)(c-'0');
}
arma::mat data = arma::zeros(1, numVisible);
data[index] = 1;
batch.insert_rows(batch.n_rows, data);
}
fclose(pFile);
return batch;
}
int main()
{
printf("Hallo, Welt!\n");
const string project("context99");
const string project("poet");
Stack stack(".", project);
#if CREATE_TEST
stack.addTraining(stack.trainingBatch().row(1));
printf("There are %d training samples\n", (int)stack.trainingBatch().n_rows);
stack.delTraining(0);
printf("There are %d training samples\n", (int)stack.trainingBatch().n_rows);
const int numLayers = 4;
int i = 0;
Layer *lowerLayer = new Layer("Layer", i, 16, 16, 8);
stack.addLayer(lowerLayer);
for (++i; i < numLayers; i++)
{
Layer *layer = new Layer("Layer", i, lowerLayer->bh().n_elem, 1, lowerLayer->bh().n_elem >> 1);
layer->params().learningRate = lowerLayer->params().learningRate/2;
layer->params().numEpochs = lowerLayer->params().numEpochs/2;
lowerLayer = layer;
stack.addLayer(layer);
}
// Save project
stack.save();
// Shake weights
stack.weightsInit(0.01);
// Save weights
stack.saveWeights();
#else
// Load project
stack.load();
// Load weights
stack.loadWeights();
// Load training
stack.loadTrainingBatch();
#endif
#if TRAIN_TEST
RbmListener statusDisplay;
// Train stack
stack.train(&statusDisplay);
// Save weights
stack.saveWeights();
#endif
Layer *layer = stack.getLayer(0);
arma::mat v = stack.trainingBatch();
v.print("t");
layer->calcContextBatch(v);
arma::mat h = layer->toHiddenProbs(v);
arma::mat r = layer->toVisibleProbs(h);
v.print("v1");
r = layer->upDownPass(v);
r.print("v2");
arma::mat err = Rbm::rms_error(r-v);
err.print("err");
arma::mat batch = createTraining("moby_ch1.txt");
batch.save("poet.training.dat", arma::arma_ascii);
return 0;
}