public void InitializeLayers(ILayerInitializer initializer)
{
foreach (var layer in Layers)
{
initializer.Initialize(layer);
}
}
public static Network Build(NetworkDefinition definition, ILayerInitializer initializer)
{
var network = new Network(BuildLayers(definition.Layers, definition.InputSize));
network.InitializeLayers(initializer);
return(network);
}
public AgentNetwork(AgentNetworkDefinition definition, ILayerInitializer initializer)
{
InputCoder = new AgentNetworkInputCoder(definition.ViewRadius);
var lastLayer = new NetworkLayerDefinition(definition.LastLayerActivationFunction, 1);
var networkDefinition = new NetworkDefinition(InputCoder.EncodedSize, definition.Layers.Concat(new[] { lastLayer }));
Network = NetworkBuilder.Build(networkDefinition, initializer);
}
public Layer(int numberOfNeuronsInPreviousLayer, int numberOfNeurons, ILayerInitializer layerInitializer,
IActivation outputActivation)
{
Weights = Matrix <double> .Build.Dense(numberOfNeuronsInPreviousLayer, numberOfNeurons, layerInitializer.GetWeight);
Biases = Vector <double> .Build.Dense(numberOfNeurons, layerInitializer.GetBias);
OutputActivation = outputActivation;
previousDeltaWeights = Matrix <double> .Build.Dense(Weights.RowCount, Weights.ColumnCount);
previousDeltaBiases = Vector <double> .Build.Dense(Biases.Count);
}
