public override void InsertIn(NeuralBuilder builder)
{
builder.FCLayer
(
Size,
Activation
);
}
public override void InsertIn(NeuralBuilder builder)
{
builder.PoolLayer
(
Filter,
Stride,
Type
);
}
public override void InsertIn(NeuralBuilder builder)
{
builder.ConvLayer
(
Size,
Filter,
Stride,
Padding,
Activation
);
}
public override void InsertIn(NeuralBuilder builder)
{
if (Reshape)
{
builder.AdaptLayer
(
Shape,
Normalize,
Activation
);
}
else
{
builder.AdaptLayer
(
Normalize,
Activation
);
}
}
private static void Main(string[] args)
{
var network = NeuralBuilder.BuildFullConnected(Math.Tanh, 1, 20, 20, 1);
var mutationDic = new Dictionary <IMutation, double>
{
{ new WeigthMutate(), 1 },
{ new ConnectSynapse(), 0.5 },
{ new RemoveSynapse(), 0.5 },
// {new ConnectNeuron(Math.Tanh), 0.4},
{ new MultiMutate(new[] { new WeigthMutate(), new WeigthMutate() }), 0.5 },
{ new MultiMutate(new[] { new ConnectSynapse(), new ConnectSynapse() }), 0.2 }
};
var specie = new Species(FitFunc, network, mutationDic);
specie.OnImprovement += OnImprovement;
specie.Sensitivity = 0.0001;
lastFit = FitFunc(network);
startTime = DateTime.Now;
while (true)
{
specie.Iteration();
specie.Sensitivity *= 0.9999;
if (network.LoopDetected())
{
Console.WriteLine("LOOP!");
}
}
network.MetricsRecitate();
NeuralBuilder.BuildDOTGraph(network, "outgraph.dot");
}
public void Dispose()
{
builder?.Dispose();
builder = null;
Clear();
}
public abstract void InsertIn(NeuralBuilder builder);
