public static IEnumerable <INodeLink> MakeLink(this IEnumerable <INode> nodes, int width, int filterSize, int offsetX, int offsetY, Func <int, int, IWeight> getWeight)
{
var inputNodes = nodes.ToArray();
var height = inputNodes.Length / width;
var bias = new NodeLink {
InputNode = new ValueNode()
{
Value = 1
}, Weight = Weight.Make(DLF.GetRandomWeight())
};
var links = (
from y in Enumerable.Range(0, filterSize)
from x in Enumerable.Range(0, filterSize)
where (offsetX + x) < width
where (offsetY + y) < height
let nodeIndex = ((offsetY + y) * width) + offsetX + x
let inputNode = inputNodes[nodeIndex]
select new NodeLink {
InputNode = inputNode, Weight = getWeight(x, y)
})
.ToArray();
return
(new[] { bias }.Concat(links).ToArray());
}
public ConvolutionLayer(ILayer before, ValueTuple <int, int, int> filter
, Func <IEnumerable <double>, IEnumerable <double> > activation
, Func <double, bool> ignoreUpdate = null)
{
(int filterSize, int stride, int filterCount) = filter;
this.CalcFunction = DLF.CalcFunction;
this.ActivationFunction = activation;
this.UpdateWeightFunction = DLF.UpdateWeight(ignoreUpdate);
int width, height, chSize = 0;
if (before is I2DLayer dLayer)
{
width = dLayer.OutputWidth;
height = dLayer.OutputHeight;
chSize = dLayer.OutputCh;
}
else
{
width = before.Nodes.Count();
height = 1;
chSize = 1;
}
var xSize = (int)Math.Ceiling((width - filterSize) / (double)stride);
var ySize = (int)Math.Ceiling((height - filterSize) / (double)stride);
this.OutputWidth = xSize;
this.OutputHeight = ySize;
this.OutputCh = filterCount;
this.Nodes = (
from filterIndex in Enumerable.Range(0, filterCount)
let weights = (
from fx in Enumerable.Range(0, filterSize)
from fy in Enumerable.Range(0, filterSize)
select Weight.Make(DLF.GetRandomWeight(), xSize * ySize * chSize))
.ToArray()
from y in Enumerable.Range(0, height - filterSize).Where(i => i % stride == 0)
from x in Enumerable.Range(0, width - filterSize).Where(i => i % stride == 0)
let links =
from channelOffset in Enumerable.Range(0, chSize)
let lx = before.Nodes.MakeLink(width, filterSize, x, y + (channelOffset * height), (wx, wy) => weights[(wy * filterSize) + wx]).ToArray()
select lx
let node = new Node(ActivationFunction, links.SelectMany(l => l).ToArray())
select node).ToArray();
}
