public void Complex_WeightOne()
{
var connList = new List <WeightedDirectedConnection <double> >
{
new WeightedDirectedConnection <double>(0, 4, 1.0),
new WeightedDirectedConnection <double>(1, 4, 1.0),
new WeightedDirectedConnection <double>(1, 5, 1.0),
new WeightedDirectedConnection <double>(3, 4, 1.0),
new WeightedDirectedConnection <double>(4, 2, 0.9),
new WeightedDirectedConnection <double>(5, 3, 1.0)
};
// Create graph.
var digraph = WeightedDirectedGraphAcyclicBuilder <double> .Create(connList, 2, 2);
// Create neural net and run tests.
var actFn = new Logistic();
var net = new NeuralNetAcyclic(digraph, actFn.Fn);
Complex_WeightOne_Inner(net, actFn);
// Create vectorized neural net and run tests.
var vnet = new NeuralNet.Double.Vectorized.NeuralNetAcyclic(digraph, actFn.Fn);
Complex_WeightOne_Inner(vnet, actFn);
}
static NeuralNetAcyclicBenchmarks()
{
// TODO: Load neural nets directly, instead of loading a genome and decoding.
var metaNeatGenome = new MetaNeatGenome <double>(12, 1, true, new ActivationFunctions.LeakyReLU());
var genomeLoader = NeatGenomeLoaderFactory.CreateLoaderDouble(metaNeatGenome);
var genome = genomeLoader.Load("data/genomes/binary11.genome");
var genomeDecoder = new NeatGenomeDecoderAcyclic();
__nn = (NeuralNetAcyclic)genomeDecoder.Decode(genome);
// Set some non-zero random input values.
var rng = RandomDefaults.CreateRandomSource();
for (int i = 0; i < __nn.InputVector.Length; i++)
{
__nn.InputVector[i] = rng.NextDouble();
}
}
public void SingleInput_WeightOne()
{
var connList = new List <WeightedDirectedConnection <double> >();
connList.Add(new WeightedDirectedConnection <double>(0, 1, 1.0));
// Create graph.
var digraph = WeightedDirectedGraphAcyclicBuilder <double> .Create(connList, 1, 1);
// Create neural net and run tests.
var actFn = new Logistic();
var net = new NeuralNetAcyclic(digraph, actFn.Fn);
SingleInput_WeightOne_Inner(net, actFn);
// Create vectorized neural net and run tests.
var vnet = new NeuralNet.Double.Vectorized.NeuralNetAcyclic(digraph, actFn.Fn);
SingleInput_WeightOne_Inner(vnet, actFn);
}
public void SingleInput_WeightZero()
{
var connList = new LightweightList <WeightedDirectedConnection <double> > {
new WeightedDirectedConnection <double>(0, 1, 0.0)
};
var connSpan = connList.AsSpan();
// Create graph.
var digraph = WeightedDirectedGraphAcyclicBuilder <double> .Create(connSpan, 1, 1);
// Create neural net and run tests.
var actFn = new Logistic();
var net = new NeuralNetAcyclic(digraph, actFn.Fn);
SingleInput_WeightZero_Inner(net);
// Create vectorized neural net and run tests.
var vnet = new NeuralNets.Double.Vectorized.NeuralNetAcyclic(digraph, actFn.Fn);
SingleInput_WeightZero_Inner(vnet);
}
public void TwoInputs_WeightHalf()
{
var connList = new List <WeightedDirectedConnection <double> >
{
new WeightedDirectedConnection <double>(0, 2, 0.5),
new WeightedDirectedConnection <double>(1, 2, 0.5)
};
// Create graph.
var digraph = WeightedDirectedGraphAcyclicBuilder <double> .Create(connList, 2, 1);
// Create neural net and run tests.
var actFn = new Logistic();
var net = new NeuralNetAcyclic(digraph, actFn.Fn);
TwoInputs_WeightHalf_Inner(net, actFn);
// Create vectorized neural net and run tests.
var vnet = new NeuralNet.Double.Vectorized.NeuralNetAcyclic(digraph, actFn.Fn);
TwoInputs_WeightHalf_Inner(vnet, actFn);
}
public void MultipleInputsOutputs()
{
var connList = new List <WeightedDirectedConnection <double> >
{
new WeightedDirectedConnection <double>(0, 5, 1.0),
new WeightedDirectedConnection <double>(1, 3, 1.0),
new WeightedDirectedConnection <double>(2, 4, 1.0)
};
// Create graph.
var digraph = WeightedDirectedGraphAcyclicBuilder <double> .Create(connList, 3, 3);
// Create neural net and run tests.
var actFn = new Logistic();
var net = new NeuralNetAcyclic(digraph, actFn.Fn);
MultipleInputsOutputs_Inner(net, actFn);
// Create vectorized neural net and run tests.
var vnet = new NeuralNet.Double.Vectorized.NeuralNetAcyclic(digraph, actFn.Fn);
MultipleInputsOutputs_Inner(vnet, actFn);
}
public void HiddenNode()
{
var connList = new List <WeightedDirectedConnection <double> >
{
new WeightedDirectedConnection <double>(0, 3, 0.5),
new WeightedDirectedConnection <double>(1, 3, 0.5),
new WeightedDirectedConnection <double>(3, 2, 2.0)
};
// Create graph.
var digraph = WeightedDirectedGraphAcyclicBuilder <double> .Create(connList, 2, 1);
// Create neural net and run tests.
var actFn = new Logistic();
var net = new NeuralNetAcyclic(digraph, actFn.Fn);
HiddenNode_Inner(net, actFn);
// Create vectorized neural net and run tests.
var vnet = new NeuralNets.Double.Vectorized.NeuralNetAcyclic(digraph, actFn.Fn);
HiddenNode_Inner(vnet, actFn);
}
