// Start is called before the first frame update
void Start()
{
int[] hiddens = { 100, 100, 100, 100, 100, 100, 100 };
nn = new MutatableNeuralNetwork(2, hiddens, 1, 0.2f, NeuralNetwork.NetworkType.Supervised);
float[] input1 = { 0, 0 };
float[] target1 = { 0.1f };
float[] input2 = { 1, 1 };
float[] target2 = { 0.1f };
float[] input3 = { 1, 0 };
float[] target3 = { 0.9f };
float[] input4 = { 0, 1 };
float[] target4 = { 0.9f };
float[][] inputs = { input1, input2, input3, input4 };
float[][] targets = { target1, target2, target3, target4 };
//int[] hiddens = { 2 };
//nn = new NeuralNetwork(2, hiddens, 1);
//print(nn.WriteString());
//NeuralNetwork nn2 = new NeuralNetwork(nn.WriteString());
//print(nn2.WriteString());
//for (int i = 0; i < 10000; i++)
//{
// int data = (int)Random.Range(0, 3.99999f);
// nn.Train(inputs[data], targets[data]);
// Random.InitState((int)System.DateTime.Now.Ticks);
//}
//StartCoroutine(train(60000));
}
public new MutatableNeuralNetwork Duplicate()
{
MutatableNeuralNetwork output = new MutatableNeuralNetwork(inputs, hiddens, outputs, LearningRate, type);
for (int i = 0; i < layers.Length; i++)
{
output.layers[i] = layers[i].duplicate();
}
for (int i = 0; i < biases.Length; i++)
{
output.biases[i] = biases[i].duplicate();
}
output.aFunctions = (int[][])aFunctions.Clone();
return(output);
}
public void updateNN(MutatableNeuralNetwork m)
{
nn = m;
}