public double[] Compute(Options options, double[] inputs)
{
var inputLayer = Layers[0];
if (inputs.Length != inputLayer.Neurons.Count)
{
throw new ArgumentException($"Invalid number of inputs. Expected: {inputLayer.Neurons.Count}");
}
for (int i = 0; i < inputs.Length; i++)
{
inputLayer.Neurons[i].Value = inputs[i];
}
var prevLayer = inputLayer; // Previous layer is input layer.
for (var i = 1; i < Layers.Count; i++)
{
for (var j = 0; j < Layers[i].Neurons.Count; j++)
{
// For each Neuron in each layer.
var sum = 0.0;
for (var k = 0; k < prevLayer.Neurons.Count; k++)
{
// Every Neuron in the previous layer is an input to each Neuron in
// the next layer.
sum += prevLayer.Neurons[k].Value *
Layers[i].Neurons[j].Weights[k];
}
// Compute the activation of the Neuron.
Layers[i].Neurons[j].Value = options.Activation(sum);
}
prevLayer = Layers[i];
}
// All outputs of the Network.
var lastLayer = Layers.Last();
return(lastLayer.Neurons.Select(n => n.Value).ToArray());
}