private void computeTotalGradient(
Gradients totalGradients, Gradients partialGradients, SetOfIOPairs trainingSet) {
// na zaciatku sa inicializuju gradienty (total)
totalGradients.resetGradients();
// partialGradients.resetGradients();
// Gradients totalGradients = new Gradients(this);
// Gradients partialGradients = new Gradients(this); /***/
for (SetOfIOPairs.IOPair pair : trainingSet.pairs) { // pre kazdy par trenovacej mnoziny
// partialGradients = computeGradient(pair.inputs, pair.outputs);
computeGradient(partialGradients, pair.inputs, pair.outputs);
for (int il = this.numberOfLayers() - 1; il >= 1; il--) { // pre vsetky vrstvy okrem poslednej
NeuralLayer currentLayer = this.getLayer(il);
for (int in = 0;
in < currentLayer.numberOfNeurons();
in++) { // pre vsetky neurony na currentLayer
// upravime gradient prahov :
totalGradients.incrementThreshold(il, in, partialGradients.getThreshold(il, in));
for (int ii = 0;
ii < currentLayer.lowerLayer().numberOfNeurons();
ii++) { // pre vsetky vstupy
totalGradients.incrementWeight(il, in, ii, partialGradients.getWeight(il, in, ii));
}
}
} // end for layer
} // end foreach
// return totalGradients;
} // end method
