private void UpdateLayer(int PWhichLayer, bool PForward, AutoencoderWeights PWeights)
{
int beginlayer = PWhichLayer - 1;
if (PForward)
{
Utility.WithinBounds("Cannot update this layer!!!", PWhichLayer, 1, numlayers);
}
else
{
Utility.WithinBounds("Cannot update this layer!!!", PWhichLayer, 0, numlayers - 1);
beginlayer = PWhichLayer + 1;
}
RBMLayer thislayer = layers[PWhichLayer];
RBMLayer previouslayer = layers[beginlayer];
double input = 0;
double[] states = previouslayer.GetStates();
for (int i = 0; i < thislayer.Count; i++)
{
for (int j = 0; j < previouslayer.Count; j++)
{
if (!PForward)
{
input += PWeights.GetWeightSet(beginlayer - 1).GetWeight(i, j) * states[j];
}
else
{
input += PWeights.GetWeightSet(beginlayer).GetWeight(j, i) * states[j];
}
}
thislayer.SetState(i, input);
input = 0;
}
}
private void PerformPreTraining(int PPreSynapticLayer)
{
RBMLearningRate sentlearnrate = new RBMLearningRate(learnrate.prelrweights[PPreSynapticLayer]
, learnrate.prelrbiases[PPreSynapticLayer]
, learnrate.premomweights[PPreSynapticLayer]
, learnrate.premombiases[PPreSynapticLayer]);
RBMTrainer.Train(layers[PPreSynapticLayer], layers[PPreSynapticLayer + 1], trainingdata[PPreSynapticLayer]
, sentlearnrate, recognitionweights.GetWeightSet(PPreSynapticLayer));
}
////////////////////////////////////////////////////////////////////////////////////////////////////
/// <summary> Performs the pre training action. </summary>
///
/// <param name="PPreSynapticLayer"> The pre synaptic layer. </param>
////////////////////////////////////////////////////////////////////////////////////////////////////
private void PerformPreTraining(int PPreSynapticLayer)
{
RestrictedBoltzmannMachineLearningRate sentlearnrate = new RestrictedBoltzmannMachineLearningRate(
learnrate.preLearningRateWeights[PPreSynapticLayer],
learnrate.preLearningRateBiases[PPreSynapticLayer],
learnrate.preMomentumWeights[PPreSynapticLayer],
learnrate.preMomentumBiases[PPreSynapticLayer]);
RestrictedBoltzmannMachineTrainer.Train(layers[PPreSynapticLayer], layers[PPreSynapticLayer + 1],
trainingdata[PPreSynapticLayer], sentlearnrate, recognitionweights.GetWeightSet(PPreSynapticLayer));
}
private void WakePhase()
{
for (int i = 0; i < numlayers - 1; i++)
{
double[] visstates = layers[i].GetStates();
double[] visact = layers[i].GetActivities();
double[] hidstates = layers[i + 1].GetStates();
double[] hidact = layers[i + 1].GetActivities();
double curlearnrate = learnrate.finelrweights[i];
for (int j = 0; j < layers[i].Count; j++)
{
for (int k = 0; k < layers[i + 1].Count; k++)
{
generativeweights.GetWeightSet(i).ModifyWeight(j, k, curlearnrate *
CalculateFineTuneTrain(hidstates[k], visstates[j], visact[j]));
}
}
}
}