/// <summary>
/// Initializes a new Network Layer. A network layer is sub neural network made up of inputs, hidden layer(s) and an output layer.
/// </summary>
/// <param name="inputNodes">Number of Nodes at the input layer (includes bias Node).</param>
/// <param name="outputNodes">Number of Nodes at the output layer.</param>
/// <param name="isFullyConnected">Indicates whether the output layer of this network is fully connected with the next Network Layer / Network.</param>
/// <param name="hiddenLayers">Number of Nodes in each layer and the number of layers, where the array length is the number of
/// layers and each value is the number of Nodes in that layer.</param>
/// <param name="fnNodeInitializer">Function for creating a new Node at each layer (zero-based) and Node index (zero-based). The 0 index layer corresponds to the input layer.</param>
/// <param name="isAutoencoder">Determines whether this Network layer is an auto-encoding layer.</param>
/// <param name="layerConnections">(Optional) Connection properties for this Network where the first dimension is the layer, second the Node index in that layer,
/// and third the Node indexes in the next layer to pair with.<para>For example: 1 => 2 => [2, 3] will link Node 2 in layer 1 to Nodes 2 + 3 in layer 2.</para></param>
/// <param name="createBiasNodes">(Optional) Indicates whether bias nodes are automatically created (thus bypassing the <paramref name="fnNodeInitializer"/> function).</param>
/// <param name="linkBiasNodes">(Optional) Indicates whether bias nodes in hidden layers are automatically linked to their respective hidden nodes.
/// <para>If this is set to True, it will override any bias node connections specified in parameter <paramref name="layerConnections"/></para></param>
public NetworkLayer(int inputNodes, int outputNodes, bool isFullyConnected, int[] hiddenLayers, Func <int, int, Neuron> fnNodeInitializer,
bool isAutoencoder = false, int[][][] layerConnections = null, bool createBiasNodes = true, bool linkBiasNodes = true) : base()
{
this.IsFullyConnected = isFullyConnected;
this.IsAutoencoder = isAutoencoder;
if (!this.IsFullyConnected && (layerConnections == null || layerConnections.Length != (2 + hiddenLayers.Length)))
{
throw new ArgumentException("Connections must be supplied when the output layer is not fully connected with the next Network Layer.", nameof(layerConnections));
}
IFunction ident = new Ident();
this.In = new Neuron[inputNodes];
this.In[0] = new Neuron {
Label = "B0", ActivationFunction = ident
};
// create input nodes
for (int i = 1; i < this.In.Length; i++)
{
this.In[i] = fnNodeInitializer(0, i);
}
// create hidden layers
Neuron[][] hiddenNodes = new Neuron[hiddenLayers.Length][];
for (int hiddenLayer = 0; hiddenLayer < hiddenLayers.Count(); hiddenLayer++)
{
hiddenNodes[hiddenLayer] = new Neuron[hiddenLayers[hiddenLayer]];
for (int h = 0; h < hiddenLayers[hiddenLayer]; h++)
{
if (h == 0)
{
// create the bias node in this layer
if (createBiasNodes)
{
hiddenNodes[hiddenLayer][0] = new Neuron {
Label = $"B{hiddenLayer + 1}", ActivationFunction = ident
}
}
;
else
{
hiddenNodes[hiddenLayer][0] = fnNodeInitializer(hiddenLayer + 1, h);
}
}
else
{
// create the hidden node in this layer
hiddenNodes[hiddenLayer][h] = fnNodeInitializer(hiddenLayer + 1, h);
}
}
// do hidden to hidden node connections
if (hiddenLayer > 0 && (hiddenLayer != hiddenLayers.Length - 1))
{
bool useConnection = (layerConnections != null && layerConnections[hiddenLayer + 1] != null);
if (linkBiasNodes)
{
for (int node = 1; node < hiddenNodes[hiddenLayer].Length; node++)
{
Edge.Create(hiddenNodes[hiddenLayer - 1][0], hiddenNodes[hiddenLayer][node]);
}
}
// connect nodes in previous layer with this layer
for (int h = 0; h < hiddenLayers[hiddenLayer - 1]; h++)
{
if (linkBiasNodes && h == 0)
{
continue;
}
// check for connection properties
if (useConnection && layerConnections[hiddenLayer + 1].Length > h && layerConnections[hiddenLayer + 1][h] != null)
{
// use connection properties
foreach (int connection in layerConnections[hiddenLayer + 1][h])
{
Edge.Create(hiddenNodes[hiddenLayer - 1][h], hiddenNodes[hiddenLayer][connection]);
}
}
}
}
}
// creating output nodes
this.Out = new Neuron[outputNodes];
for (int i = 0; i < outputNodes; i++)
{
this.Out[i] = fnNodeInitializer(hiddenLayers.Length + 1, i);
}
// link last hidden layer with output nodes
for (int i = 0; i < this.Out.Length; i++)
{
for (int j = 0; j < hiddenNodes.Last().Length; j++)
{
Edge.Create(hiddenNodes.Last().ElementAt(j), this.Out[i]);
}
}
}
