private List<INeuron> CreateLayer(int layerSize, List<IInput> inputs)
{
var layerBias = new BiasInput(1.0d);
var layer = new List<INeuron>();
for (var i = 0; i < layerSize; i++)
{
var neuron = new Neuron(_activation);
neuron.RegisterInput(layerBias, Util.GetRandomWeight());
inputs.ForEach(input => neuron.RegisterInput(input, Util.GetRandomWeight()));
layer.Add(neuron);
}
return layer;
}
public List<INeuron> RestoreLayer(LayerModel layerModel, List<IInput> inputs)
{
var layerBias = new BiasInput(1.0d);
var layer = new List<INeuron>();
foreach (var model in layerModel.Neurons)
{
var neuron = new Neuron(_activation);
neuron.RegisterInput(layerBias, model.InputWeights[0]);
var inputWeights = model.InputWeights.Skip(1).ToArray();
for (int j = 0; j < inputs.Count; j++)
{
neuron.RegisterInput(inputs[j], inputWeights[j]);
}
layer.Add(neuron);
}
return layer;
}