private void init(StochasticLayer hidden, StochasticLayer visible)
{
this.hidden = hidden;
this.visible = visible;
inputsCount = hidden.InputsCount;
hiddenCount = hidden.Neurons.Length;
weightsGradient = new double[inputsCount][];
for (int i = 0; i < weightsGradient.Length; i++)
weightsGradient[i] = new double[hiddenCount];
visibleBiasGradient = new double[inputsCount];
hiddenBiasGradient = new double[hiddenCount];
weightsUpdates = new double[inputsCount][];
for (int i = 0; i < weightsUpdates.Length; i++)
weightsUpdates[i] = new double[hiddenCount];
visibleBiasUpdates = new double[inputsCount];
hiddenBiasUpdates = new double[hiddenCount];
storage = new ThreadLocal<ParallelStorage>(() =>
new ParallelStorage(inputsCount, hiddenCount));
}
/// <summary>
/// Creates a new <see cref="RestrictedBoltzmannMachine"/>.
/// </summary>
///
/// <param name="function">The activation function to use in the network neurons.</param>
/// <param name="inputsCount">The number of inputs for the machine.</param>
/// <param name="hiddenNeurons">The number of hidden neurons in the machine.</param>
///
public RestrictedBoltzmannMachine(IStochasticFunction function, int inputsCount, int hiddenNeurons)
: base(function, inputsCount, 1)
{
this.visible = new StochasticLayer(function, inputsCount, hiddenNeurons);
this.hidden = new StochasticLayer(function, hiddenNeurons, inputsCount);
base.layers[0] = hidden;
}
/// <summary>
/// Creates a new <see cref="RestrictedBoltzmannMachine"/>.
/// </summary>
///
/// <param name="hidden">The hidden layer to be added in the machine.</param>
/// <param name="visible">The visible layer to be added in the machine.</param>
///
public RestrictedBoltzmannMachine(StochasticLayer hidden, StochasticLayer visible)
: base(null, hidden.InputsCount, 0)
{
this.hidden = hidden;
this.visible = visible;
base.layers[0] = hidden;
}
private void createAlgorithms()
{
algorithms = new IUnsupervisedLearning[network.Machines.Count];
for (int i = 0; i < network.Machines.Count; i++)
{
StochasticLayer hidden = network.Machines[i].Hidden;
StochasticLayer visible = network.Machines[i].Visible;
algorithms[i] = configure(hidden, visible, i);
}
}
/// <summary>
/// Creates a new <see cref="ContrastiveDivergenceLearning"/> algorithm.
/// </summary>
///
/// <param name="hidden">The hidden layer of the hidden-visible layer pair to be trained.</param>
/// <param name="visible">The visible layer of the hidden-visible layer pair to be trained.</param>
///
public ContrastiveDivergenceLearning(StochasticLayer hidden, StochasticLayer visible)
{
init(hidden, visible);
}
