/// <summary>
/// Creates a new instance of a <see cref="NeuralNet"/>
/// </summary>
/// <param name="numInputs">The number of nodes in the input layer</param>
/// <param name="numOutputs">The number of nodes in the output layer</param>
public NeuralNet(int numInputs, int numOutputs)
{
if (numInputs <= 0)
{
throw new ArgumentOutOfRangeException(nameof(numInputs), "You must have at least one input node");
}
if (numOutputs <= 0)
{
throw new ArgumentOutOfRangeException(nameof(numOutputs), "You must have at least one output node");
}
Inputs = new NeuralNetLayer(numInputs);
Outputs = new NeuralNetLayer(numOutputs);
}
/// <summary>
/// Adds a hidden layer to the neural net and returns the new layer.
/// </summary>
/// <param name="numNeurons">The number of neurons in the layer</param>
public void AddHiddenLayer(int numNeurons)
{
if (numNeurons <= 0)
{
throw new ArgumentOutOfRangeException(nameof(numNeurons), "You cannot add a hidden layer without any nodes");
}
if (IsConnected)
{
throw new InvalidOperationException("Cannot add a new layer after the network has been evaluated.");
}
var layer = new NeuralNetLayer(numNeurons);
_hiddenLayers.Add(layer);
}
/// <summary>
/// Connects this layer to the <paramref name="nextLayer"/>, forming connections between each node in this
/// layer and each node in the next layer.
/// </summary>
/// <param name="nextLayer">The layer to connect to</param>
internal void ConnectTo([NotNull] NeuralNetLayer nextLayer)
{
_nextLayer = nextLayer ?? throw new ArgumentNullException(nameof(nextLayer));
_neurons.Each(source => nextLayer.Each(source.ConnectTo));
}
