static void Main(string[] args)
{
var a = new WiredNeuralArchitecture(
InputLength,
OutputLength,
NodeCount,
new Factory<OperationNode<double>>(() => new ActivationNeuron(new SigmoidActivationFunction { Alpha = 1.05 })),
new Factory<OperationNode<double>>(() => new ActivationNeuron(new LinearActivationFunction(1.05))),
new Factory<ComputationConnection<double>>(() => new Synapse()));
Console.WriteLine("Creating Wired Network ...");
var net = a.CreateNetwork();
Console.WriteLine("Done.");
Console.WriteLine();
Console.WriteLine("Begin test, number of iterations: {0}", TestIterationCount);
var sw = new Stopwatch();
var t = new UnorderedTraining(net);
t.EnsureScriptRun();
sw.Start();
lock (net.SyncRoot)
{
for (int i = 0; i < TestIterationCount; i++)
{
//net.Iteration();
t.BackwardIteration();
}
}
sw.Stop();
Console.WriteLine("Total Millisec: {0}", sw.ElapsedMilliseconds);
Console.WriteLine("Press any ...");
Console.ReadKey();
}
static NeuralNetwork CreateNetwork(ISupervisedFeatureMatrixProvider matrixProv, params ILearningRule[] rules)
{
Contract.Requires(matrixProv != null);
Contract.Requires(rules != null);
Contract.Requires(rules.Length > 0);
IFactory<Synapse> synapseFactory = new Factory<Synapse>(() => new Synapse(rules));
IFactory<ActivationNeuron> neuronFactorySig = new Factory<ActivationNeuron>(() => new ActivationNeuron(new SigmoidActivationFunction(1.05), rules));
IFactory<ActivationNeuron> neuronFactoryLin = new Factory<ActivationNeuron>(() => new ActivationNeuron(new LinearActivationFunction(1.05), rules));
//INeuralArchitecture arch = new LayeredNeuralArchitecture(
// new NeuralMLABuilder(
// false,
// new ConnectionLayerDefinition<double>(synapseFactory),
// matrixProv.MatrixWidth,
// new OperationNodeLayerDefinition<double>(neuronFactorySig, 20),
// new OperationNodeLayerDefinition<double>(neuronFactorySig, 10),
// new OperationNodeLayerDefinition<double>(neuronFactoryLin, matrixProv.OutputMatrixWidth)));
INeuralArchitecture arch = new WiredNeuralArchitecture(matrixProv.MatrixWidth, matrixProv.OutputMatrixWidth, Properties.Settings.Default.NeuronCount, neuronFactorySig, neuronFactoryLin, synapseFactory);
return arch.CreateNetwork();
}
static NeuralNetwork CreateNetwork(bool recurrent, params ILearningRule[] rules)
{
Contract.Requires(rules != null);
Contract.Requires(rules.Length > 0);
int inputSize;
if (!recurrent)
{
inputSize = Properties.Settings.Default.SampleSize * Properties.Settings.Default.SampleSize + 1;
}
else
{
inputSize = Properties.Settings.Default.SampleSize + 1;
}
IFactory<Synapse> synapseFactory = new Factory<Synapse>(() => new Synapse(rules));
IFactory<ActivationNeuron> neuronFactorySig = new Factory<ActivationNeuron>(() => new ActivationNeuron(new SigmoidActivationFunction(1.05), rules));
IFactory<ActivationNeuron> neuronFactoryLin = new Factory<ActivationNeuron>(() => new ActivationNeuron(new LinearActivationFunction(1.05), rules));
//INeuralArchitecture arch = new LayeredNeuralArchitecture(
// new NeuralMLABuilder(
// false,
// new ConnectionLayerDefinition<double>(synapseFactory),
// inputSize,
// new OperationNodeLayerDefinition<double>(neuronFactorySig, 20),
// new OperationNodeLayerDefinition<double>(neuronFactorySig, 10),
// new OperationNodeLayerDefinition<double>(neuronFactoryLin, 1)));
INeuralArchitecture arch = new WiredNeuralArchitecture(inputSize, 1, Properties.Settings.Default.NeuronCount, neuronFactorySig, neuronFactoryLin, synapseFactory, recurrent);
//INeuralArchitecture arch = new WiredNeuralArchitecture(3, 1, 2, neuronFactorySig, neuronFactoryLin, synapseFactory, recurrent);
return arch.CreateNetwork();
}
static NeuralNetwork CreateNetwork(int inputSize, int outputSize, params ILearningRule[] rules)
{
IFactory<Synapse> synapseFactory = new Factory<Synapse>(() => new Synapse(rules));
IFactory<ActivationNeuron> neuronFactorySig = new Factory<ActivationNeuron>(() => new ActivationNeuron(new SigmoidActivationFunction(1.05), rules));
IFactory<ActivationNeuron> neuronFactoryLin = new Factory<ActivationNeuron>(() => new ActivationNeuron(new LinearActivationFunction(1.05), rules));
//INeuralArchitecture arch = new LayeredNeuralArchitecture(
// new NeuralMLABuilder(
// false,
// new ConnectionLayerDefinition<double>(synapseFactory),
// inputSize,
// new OperationNodeLayerDefinition<double>(neuronFactorySig, 10),
// new OperationNodeLayerDefinition<double>(neuronFactorySig, 6),
// new OperationNodeLayerDefinition<double>(neuronFactoryLin, outputSize)));
INeuralArchitecture arch = new WiredNeuralArchitecture(
inputSize,
outputSize,
Properties.Settings.Default.NeuronCount,
neuronFactorySig,
neuronFactoryLin,
synapseFactory,
Properties.Settings.Default.NumberOfIterations != 1);
return arch.CreateNetwork();
}
