private void AdjustWeights(InputExpectedResult irp, int microBatchIndex) {
ResetCurTimer();
double[] actual = Network.GetInputResult(irp.Input);
double[] target = irp.Output;
LogProcess("Load actual / target");
//Set output influence value
for(int nodeIndex = 0; nodeIndex < Network.Nodes[Network.Nodes.Length - 1].Length; nodeIndex++) {
double curTarget = target[nodeIndex];
double curActual = actual[nodeIndex];
Node curNode = Network.Nodes[Network.Nodes.Length - 1][nodeIndex];
foreach(Connection toOutputCon in curNode.GetIncommingConnections()) {
double preCalc = CalcOutputInfuence(toOutputCon, curTarget, curActual);
ConnectionInfluence[toOutputCon][microBatchIndex] = preCalc;
}
}
LogProcess("Set output influence values");
//Fill ConnectionInfluence values
foreach(Connection connection in AllConnections) {
GetConnectionInfluence(connection, microBatchIndex);
}
LogProcess("Fill ConnectionInfluence values");
}
public void Train(InputExpectedResult[] expected) {
for(int batchNr = 0; batchNr * MicroBatchSize < expected.Length; batchNr++) {
//Reset influence values
foreach(var key in AllConnections) {
ConnectionInfluence[key] = new double?[MicroBatchSize];
}
LogProcess("Reset influence values");
Parallel.For(0, MicroBatchSize, (batchIndex) => {
if((batchNr * MicroBatchSize) + batchIndex < expected.Length) {
AdjustWeights(expected[(batchNr * MicroBatchSize) + batchIndex], batchIndex);
}
});
//Update weights
foreach(var con in AllConnections) {
var conInfPair = ConnectionInfluence[con];
double outputInfluence = conInfPair.Sum(d => (d ?? 0) * con.FromNode.Output);
double deltaWeight = -LearningRate * outputInfluence;
con.Weight += deltaWeight;
}
LogProcess("Update weights");
}
}
