public void FromGenome(Genome genome, int numofInputs, int neuronsPerHidden, int numOfOutputs)
{
ReleaseNet();
outputAmount = numOfOutputs;
inputAmount = numofInputs;
int weightsForHidden = numofInputs * neuronsPerHidden;
NLayer hidden = new NLayer();
List <Neuron> neurons = new List <Neuron>();
for (int i = 0; i < neuronsPerHidden; i++)
{
//init
neurons.Add(new Neuron());
List <float> weights = new List <float>();
//init
for (int j = 0; j < numofInputs + 1; j++)
{
weights.Add(0.0f);
weights[j] = genome.weights[i * neuronsPerHidden + j];
}
neurons[i].weights = new List <float>();
neurons[i].Initilise(weights, numofInputs);
}
hidden.LoadLayer(neurons);
//Debug.Log ("fromgenome, hiddenlayer neruons#: " + neurons.Count);
//Debug.Log ("fromgenome, hiddenlayer numInput: " + neurons [0].numInputs);
this.hiddenLayers.Add(hidden);
//Clear weights and reasign the weights to the output
int weightsForOutput = neuronsPerHidden * numOfOutputs;
List <Neuron> outneurons = new List <Neuron> ();
for (int i = 0; i < numOfOutputs; i++)
{
outneurons.Add(new Neuron());
List <float> weights = new List <float>();
for (int j = 0; j < neuronsPerHidden + 1; j++)
{
weights.Add(0.0f);
weights[j] = genome.weights[i * neuronsPerHidden + j];
}
outneurons[i].weights = new List <float>();
outneurons[i].Initilise(weights, neuronsPerHidden);
}
this.outputLayer = new NLayer();
this.outputLayer.LoadLayer(outneurons);
//Debug.Log ("fromgenome, outputlayer neruons#: " + outneurons.Count);
//Debug.Log ("fromgenome, outputlayer numInput: " + outneurons [0].numInputs);
}
public void FromGenome(Genome genome, int numofInputs, int neuronsPerHidden, int numOfOutputs)
{
ReleaseNet();
outputAmount = numOfOutputs;
NLayer hidden = new NLayer();
List <Neuron> neurons = new List <Neuron>();
for (int i = 0; i < neuronsPerHidden; i++)
{
neurons.Add(new Neuron());
List <float> weights = new List <float>();
for (int j = 0; j < numofInputs + 1; j++)
{
weights.Add(0.0f);
weights[j] = genome.weights[i * neuronsPerHidden + j];
}
neurons[i].weights = new List <float>();
neurons[i].Initilise(weights, numofInputs);
}
hidden.LoadLayer(neurons);
this.hiddenLayers.Add(hidden);
//Clear weights and reasign the weights to the output
List <Neuron> outneurons = new List <Neuron> ();
for (int i = 0; i < numOfOutputs; i++)
{
outneurons.Add(new Neuron());
List <float> weights = new List <float>();
for (int j = 0; j < neuronsPerHidden + 1; j++)
{
weights.Add(0.0f);
weights[j] = genome.weights[i * neuronsPerHidden + j];
}
outneurons[i].weights = new List <float>();
outneurons[i].Initilise(weights, neuronsPerHidden);
}
this.outputLayer = new NLayer();
this.outputLayer.LoadLayer(outneurons);
}
