public NeuralNetwork(int[] layerSizes)
{
//UnityEngine.Random.InitState(505);
neuronLayers = new NeuronLayer[layerSizes.Length];
for (int iLayer = 0; iLayer < layerSizes.Length; ++iLayer)
{
var numNeuronsInLayer = layerSizes[iLayer];
// create neurons
var currNeuronLayer = new NeuronLayer();
currNeuronLayer.InitNeurons(numNeuronsInLayer);
// connect to previous neurons
if (iLayer > 0)
{
var prevNeuronLayer = neuronLayers[iLayer - 1];
for (int iNeuron = 0; iNeuron < numNeuronsInLayer; ++iNeuron)
{
var neuron = currNeuronLayer.neurons[iNeuron];
neuron.InitWeights(prevNeuronLayer.neurons.Length);
}
}
neuronLayers[iLayer] = currNeuronLayer;
}
}
public NeuralNetwork(NeuralNetwork other)
{
neuronLayers = new NeuronLayer[other.neuronLayers.Length];
// copy layers
for (int iLayer = 0; iLayer < other.neuronLayers.Length; ++iLayer)
{
var otherNeuronLayer = other.neuronLayers[iLayer];
var currNeuronLayer = new NeuronLayer();
currNeuronLayer.InitNeurons(otherNeuronLayer.neurons.Length);
// copy neurons
for (int iNeuron = 0; iNeuron < currNeuronLayer.neurons.Length; ++iNeuron)
{
var otherNeuron = otherNeuronLayer.neurons[iNeuron];
// copy other neurons
if (otherNeuron.weights != null)
{
var currNeuron = currNeuronLayer.neurons[iNeuron];
currNeuron.InitWeights(otherNeuron.weights.Length);
// copy weights
for (int iWeight = 0; iWeight < otherNeuron.weights.Length; ++iWeight)
{
currNeuron.weights[iWeight] = otherNeuron.weights[iWeight];
currNeuron.val = 0.0f;
}
}
}
neuronLayers[iLayer] = currNeuronLayer;
}
}
public NeuronalNetwork(NeuronalNetwork aSource)
{
input = new NeuronLayer(aSource.input);
output = new NeuronLayer(aSource.output);
var last = input;
for (int i = 0; i < aSource.layers.Count; i++)
{
var layer = new NeuronLayer(aSource.layers[i]);
layers.Add(layer);
layer.InitNeurons(last, aSource.layers[i]);
last = layer;
}
output.InitNeurons(last, aSource.output);
}
public NeuronalNetwork(int aInputCount, int aOutputCount, params int[] aMiddleLayers)
{
input = new NeuronLayer(ENeuronType.Input, aInputCount);
output = new NeuronLayer(ENeuronType.Output, aOutputCount);
if (aMiddleLayers != null)
{
for (int i = 0; i < aMiddleLayers.Length; i++)
{
layers.Add(new NeuronLayer(ENeuronType.Hidden, aMiddleLayers[i]));
}
}
var last = input;
for (int i = 0; i < layers.Count; i++)
{
layers[i].InitNeurons(last);
last = layers[i];
}
output.InitNeurons(last);
// init all neurons with random values
Mutate(-1);
}
