/// <summary>
/// Testing
/// </summary>
/// <param name="numInputs"></param>
/// <param name="numOutputs"></param>
/// <param name="numLayers"></param>
public FeedForwardNet(int numInputs, int numOutputs, int numLayers)
{
AbstractNode abNode;
this.InputNode = new InputNode(numInputs);
abNode = (AbstractNode)this.InputNode;
LayerOfNeurons curLayer = new LayerOfNeurons(ref abNode, numOutputs, ActivationFunctions.defaultActivationFunction);
for (int i = 0; i < numLayers - 1; i++)
{
abNode = (AbstractNode)curLayer;
curLayer = new LayerOfNeurons(ref abNode, numOutputs, ActivationFunctions.defaultActivationFunction);
}
abNode = (AbstractNode)curLayer;
this.OutputNode = new OutputNode(ref abNode);
}
public FeedForwardNet(ref FeedForwardNet copyNet)
{
AbstractNode abNode;
InputNode inNode = copyNet.InputNode;
this.InputNode = new InputNode(ref inNode);
abNode = (AbstractNode)this.InputNode;
//original layer
LayerOfNeurons curOrgLayer = (LayerOfNeurons)inNode.OutputNode;
//copy layer
LayerOfNeurons curCpyLayer = new LayerOfNeurons(ref curOrgLayer, ref abNode);
while (curOrgLayer.OutputNode.GetType() == typeof(LayerOfNeurons))
{
curOrgLayer = (LayerOfNeurons)curOrgLayer.OutputNode;
abNode = (AbstractNode)curCpyLayer;
curCpyLayer = new LayerOfNeurons(ref curOrgLayer, ref abNode);
}
abNode = (AbstractNode)curCpyLayer;
this.OutputNode = new OutputNode(ref abNode);
}
