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- refactored

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- use Armadillo for load/save of weight and training data

git-svn-id: http://moon:8086/svn/software/trunk/projects/Rbm@775 b431acfa-c32f-4a4a-93f1-934dc6c82436
This commit is contained in:
jens
2022-01-10 15:25:52 +00:00
parent 952cf26930
commit ff2086a1ff
9 changed files with 125 additions and 65 deletions
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source/main.cpp
+5 -5
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@@ -82,13 +82,13 @@ int main()
RbmListener statusDisplay;
Stack stack(project);
stack.loadTraining();
stack.loadTrainingBatch();
stack.addTraining(stack.trainingData().row(1));
printf("There are %d training samples\n", (int)stack.trainingData().n_rows);
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.trainingData().n_rows);
printf("There are %d training samples\n", (int)stack.trainingBatch().n_rows);
#if 1
const int numLayers = 4;
@@ -129,7 +129,7 @@ int main()
stack.saveWeights();
Layer *layer = stack.getLayer(0);
arma::mat v = arma::randu(stack.trainingData().n_rows, layer->bv().n_elem);
arma::mat v = arma::randu(stack.trainingBatch().n_rows, layer->bv().n_elem);
arma::mat h = layer->toHiddenProbs(v);
arma::mat r = layer->toVisibleProbs(h);
return 0;