private void InitWeights(ArtificialNeuralNetworkConfig config)
{
switch (config.ActivationType)
{
case ActivationTypes.ReLU:
InitWeightsReLU();
break;
default:
InitWeightsDefault();
break;
}
}
public ArtificialNeuralNetwork(ArtificialNeuralNetworkConfig config)
{
_config = config;
LearningRate = config.LearningRate;
foreach (int neuronCount in config.NeuronCounts)
{
var prevLayer = Layers.Count > 0 ? Layers[Layers.Count - 1] : null;
Layers.Add(new Layer(neuronCount, prevLayer));
}
Layers[0].CreateInputConnections(config.InputDimensions);
Layers[Layers.Count - 1].CreateOutputConnections();
InitWeights(config);
}
public static ArtificialNeuralNetwork Load(string fileName)
{
ArtificialNeuralNetwork ann = null;
using (var stream = new FileStream(fileName, FileMode.Open))
{
using (var reader = new BinaryReader(stream))
{
ArtificialNeuralNetworkConfig config = new ArtificialNeuralNetworkConfig();
config.InputDimensions = reader.ReadInt32();
config.NeuronCounts = new int[reader.ReadInt32()];
for (var i = 0; i < config.NeuronCounts.Length; i++)
{
config.NeuronCounts[i] = reader.ReadInt32();
}
config.LearningRate = reader.ReadDouble();
config.ActivationType = (ActivationTypes)reader.ReadInt32();
ann = new ArtificialNeuralNetwork(config);
foreach (var layer in ann.Layers)
{
foreach (var neuron in layer.Neurons)
{
foreach (var incomingConnection in neuron.IncomingConnections)
{
incomingConnection.Weight = reader.ReadDouble();
}
}
}
reader.Close();
}
}
return(ann);
}
