private static IGenomeDecoder <NeatGenome <double>, IBlackBox <double> > CreateGenomeDecoder(
INeatExperiment <double> neatExperiment)
{
if (neatExperiment.IsAcyclic)
{
return(NeatGenomeDecoderFactory.CreateGenomeDecoderAcyclic(
neatExperiment.EnableHardwareAcceleratedNeuralNets));
}
return(NeatGenomeDecoderFactory.CreateGenomeDecoderCyclic(
neatExperiment.CyclesPerActivation,
neatExperiment.EnableHardwareAcceleratedNeuralNets));
}
private static void VerifyNeuralNetResponseInner(bool enableHardwareAcceleration)
{
var activationFnFactory = new DefaultActivationFunctionFactory <double>(enableHardwareAcceleration);
var metaNeatGenome = new MetaNeatGenome <double>(4, 1, true, activationFnFactory.GetActivationFunction("LeakyReLU"));
// Load test genome.
NeatGenomeLoader <double> loader = NeatGenomeLoaderFactory.CreateLoaderDouble(metaNeatGenome);
NeatGenome <double> genome = loader.Load("TestData/binary-three-multiplexer.genome");
// Decode genome to a neural net.
var genomeDecoder = NeatGenomeDecoderFactory.CreateGenomeDecoderAcyclic();
IBlackBox <double> blackBox = genomeDecoder.Decode(genome);
// Evaluate the neural net.
var evaluator = new BinaryThreeMultiplexerEvaluator();
// Confirm the expected fitness (to a limited amount of precision to allow for small variations of floating point
// results that can occur as a result of platform/environmental variations).
FitnessInfo fitnessInfo = evaluator.Evaluate(blackBox);
Assert.Equal(107.50554956432657, fitnessInfo.PrimaryFitness, 6);
}
private IGenomeListEvaluator <NeatGenome <double> > CreateGenomeListEvaluator(
out int inputCount, out int outputCount)
{
var genomeDecoder = NeatGenomeDecoderFactory.CreateGenomeAcyclicDecoder(true);
IBlackBoxEvaluationScheme <double> blackBoxEvaluationScheme = new BinaryElevenMultiplexerEvaluationScheme();
//// Create function regression evaluation scheme.
//int sampleResolution = 20;
//double sampleMin = 0;
//double sampleMax = 6.283185;
//var paramSamplingInfo = new ParamSamplingInfo(sampleMin, sampleMax, sampleResolution);
//IBlackBoxEvaluationScheme<double> blackBoxEvaluationScheme = new FuncRegressionEvaluationScheme(FunctionFactory.GetFunction(FunctionId.Sin), paramSamplingInfo, 0.3);
var genomeListEvaluator = GenomeListEvaluatorFactory.CreateEvaluator(
genomeDecoder,
blackBoxEvaluationScheme,
createConcurrentEvaluator: true);
inputCount = blackBoxEvaluationScheme.InputCount;
outputCount = blackBoxEvaluationScheme.OutputCount;
return(genomeListEvaluator);
}
