public void SetNeuralNetwork(IFunctionApproximator fapp)
{
FeedForwardDeepNeuralNetwork ffnn = fapp as FeedForwardDeepNeuralNetwork;
if (null == ffnn)
{
throw new Exception("Only supporting FeedForwardDeepNeuralNetwork at this stage.");
}
this.hiddenLayers = new Layer[ffnn.GetNumberOfHiddenLayers()];
for (int i = 0; i < hiddenLayers.Length; ++i)
{
this.hiddenLayers[i] = ffnn.GetHiddenLayer(i);
}
this.outputLayer = ffnn.GetOutputLayer();
this.hiddenSensitivities = new LayerSensitivity[ffnn.GetNumberOfHiddenLayers()];
for (int i = 0; i < hiddenLayers.Length; ++i)
{
this.hiddenSensitivities[i] = new LayerSensitivity(ffnn.GetHiddenLayer(i));
}
this.outputSensitivity = new LayerSensitivity(outputLayer);
}
public void SetNeuralNetwork(IFunctionApproximator fapp)
{
FeedForwardNeuralNetwork ffnn = fapp as FeedForwardNeuralNetwork;
this.hiddenLayer = ffnn.GetHiddenLayer();
this.outputLayer = ffnn.GetOutputLayer();
this.hiddenSensitivity = new LayerSensitivity(hiddenLayer);
this.outputSensitivity = new LayerSensitivity(outputLayer);
}
public Matrix SensitivityMatrixFromSucceedingLayer(LayerSensitivity nextLayerSensitivity)
{
Layer nextLayer = nextLayerSensitivity.GetLayer();
Matrix derivativeMatrix = CreateDerivativeMatrix(layer.GetLastInducedField());
Matrix weightTranspose = nextLayer.GetWeightMatrix()
.Transpose();
Matrix calculatedSensitivityMatrix
= derivativeMatrix.Times(weightTranspose)
.Times(nextLayerSensitivity.GetSensitivityMatrix());
sensitivityMatrix = calculatedSensitivityMatrix.Copy();
return(sensitivityMatrix);
}
public static Matrix CalculateWeightUpdates(LayerSensitivity layerSensitivity,
Vector previousLayerActivationOrInput,
double alpha)
{
Layer layer = layerSensitivity.GetLayer();
Matrix activationTranspose = previousLayerActivationOrInput.Transpose();
Matrix weightUpdateMatrix
= layerSensitivity.GetSensitivityMatrix()
.Times(activationTranspose)
.Times(alpha)
.Times(-1.0);
layer.AcceptNewWeightUpdate(weightUpdateMatrix.Copy());
return(weightUpdateMatrix);
}
public static Vector CalculateBiasUpdates(LayerSensitivity layerSensitivity,
double alpha)
{
Layer layer = layerSensitivity.GetLayer();
Matrix biasUpdateMatrix
= layerSensitivity.GetSensitivityMatrix()
.Times(alpha)
.Times(-1.0);
Vector result = new Vector(biasUpdateMatrix.GetRowDimension());
for (int i = 0; i < biasUpdateMatrix.GetRowDimension(); ++i)
{
result.SetValue(i, biasUpdateMatrix.Get(i, 0));
}
layer.AcceptNewBiasUpdate(result.CopyVector());
return(result);
}
public Vector CalculateBiasUpdates(LayerSensitivity layerSensitivity,
double alpha,
double momentum)
{
Layer layer = layerSensitivity.GetLayer();
Matrix biasUpdateMatrixWithoutMomentum = layerSensitivity.GetSensitivityMatrix().Times(alpha).Times(-1.0);
Matrix biasUpdateMatrixWithMomentum
= layer.GetLastBiasUpdateVector()
.Times(momentum)
.Plus(biasUpdateMatrixWithoutMomentum
.Times(1.0 - momentum));
Vector result = new Vector(biasUpdateMatrixWithMomentum.GetRowDimension());
for (int i = 0; i < biasUpdateMatrixWithMomentum.GetRowDimension(); ++i)
{
result.SetValue(i, biasUpdateMatrixWithMomentum.Get(i, 0));
}
layer.AcceptNewBiasUpdate(result.CopyVector());
return(result);
}
public Matrix CalculateWeightUpdates(LayerSensitivity layerSensitivity,
Vector previousLayerActivationOrInput,
double alpha,
double momentum)
{
Layer layer = layerSensitivity.GetLayer();
Matrix activationTranspose = previousLayerActivationOrInput.Transpose();
Matrix momentumLessUpdate
= layerSensitivity.GetSensitivityMatrix()
.Times(activationTranspose)
.Times(alpha)
.Times(-1.0);
Matrix updateWithMomentum
= layer.GetLastWeightUpdateMatrix()
.Times(momentum)
.Plus(momentumLessUpdate.Times(1.0 - momentum));
layer.AcceptNewWeightUpdate(updateWithMomentum.Copy());
return(updateWithMomentum);
}
