public static void AssertActivationFunctionsEqual(Neuron.ActivationFunction left,
Neuron.ActivationFunction right, params double[] values)
{
foreach (var value in values)
{
Assert.AreEqual(left(value), right(value));
}
}
public static Layer Generate(int dimension, int inputDimension, double minimumWeight = -1.0,
double maximumWeight = 1, [CanBeNull] Neuron.ActivationFunction activation = null)
{
if (dimension < 1)
{
throw new ArgumentException("The layer dimension must be at least 1", nameof(dimension));
}
var neurons = new Neuron[dimension];
for (var i = 0; i < dimension; i++)
{
neurons[i] = Neuron.Generate(inputDimension, minimumWeight, maximumWeight, activation);
}
return(new Layer(neurons));
}
public static Network Generate([NotNull] int[] layerDimensions, double minimumWeight = -1.0,
double maximumWeight = 1.0,
[CanBeNull] Neuron.ActivationFunction activation = null)
{
if (layerDimensions.Length == 0)
{
throw new ArgumentException("There must be at least one layer", nameof(layerDimensions));
}
var layers = new Layer[layerDimensions.Length - 1];
for (var layerIndex = 1; layerIndex < layerDimensions.Length; layerIndex++)
{
var dimension = layerDimensions[layerIndex];
var inputDimension = layerDimensions[layerIndex - 1];
var layer = Layer.Generate(dimension, inputDimension, minimumWeight, maximumWeight, activation);
layers[layerIndex - 1] = layer;
}
return(new Network(layerDimensions[0], layers));
}
