void ConnectFeatureMaps(NeuronBase[] next,Link[][] kernelCollection,Bias bias,Dictionary<Link,List<Connection>> map)
{
SharedWeight weight=new SharedWeight(next.Length);
SharedWeight biasWeight=new SharedWeight(next.Length);
for(var i=0;i<kernelCollection.Length;i++){
ConnectKernel(next[i],kernelCollection[i],weight,map);
if(bias!=null){
Map(bias,next[i],biasWeight,map);
}
}
}
public override void Connect(Link[] prior,NeuronBase[] next,Bias bias)
{
Utility.Verify(prior,x => x!=null && prior.Length>0,"Invalid prior layer");
Utility.Verify(next,x => x!=null && next.Length>0,"Invalid next layer");
Utility.Verify(() => next.Length % NextFeatureMapsCount==0,"NextFeatureMapsCount - next layer size conflict");
Utility.Verify(() => prior.Length % PriorFeatureMapsCount==0,"PriorFeatureMapsCount - prior layer size conflict");
Link[][] fmp=GetFeatureMaps(prior,PriorFeatureMapsCount);
Link[][] fmn=GetFeatureMaps(next,NextFeatureMapsCount);
Link[][][] kernelCollection=GetKernelCollection(fmp,KernelSize,Overlap);
Dictionary<Link,List<Connection>> map=new Dictionary<Link,List<Connection>>();
for(int f=0;f<fmn.Length;f++) {
Neuron[] nextFeatureMap=fmn[f].Select(x => (Neuron)x).ToArray();
for(int p=0;p<fmp.Length;p++) {
bool inSchema=Schema[p][f];
if(inSchema)
ConnectFeatureMaps(nextFeatureMap,kernelCollection[p],map);
}
if(bias!=null) {
Weight weight=new SharedWeight(nextFeatureMap.Length);
foreach(Neuron node in nextFeatureMap)
Map(bias,node,weight,map);
}
}
foreach(Link link in prior)
link.Next= map[link].ToArray();
foreach(Neuron node in next)
node.Previous=map[node].ToArray();
if(bias!=null){
if(bias.Next==null)
bias.Next=new Connection[] { };
bias.Next=bias.Next.Concat(map[bias]).ToArray();
}
}
public override void Connect(Link[] prior, NeuronBase[] next, Bias bias)
{
Utility.Verify(prior, x => x != null && prior.Length > 0, "Invalid prior layer");
Utility.Verify(next, x => x != null && next.Length > 0, "Invalid next layer");
Utility.Verify(() => next.Length % NextFeatureMapsCount == 0, "NextFeatureMapsCount - next layer size conflict");
Utility.Verify(() => prior.Length % PriorFeatureMapsCount == 0, "PriorFeatureMapsCount - prior layer size conflict");
Link[][] fmp = GetFeatureMaps(prior, PriorFeatureMapsCount);
Link[][] fmn = GetFeatureMaps(next, NextFeatureMapsCount);
Link[][][] kernelCollection = GetKernelCollection(fmp, KernelSize, Overlap);
Dictionary <Link, List <Connection> > map = new Dictionary <Link, List <Connection> >();
for (int f = 0; f < fmn.Length; f++)
{
Neuron[] nextFeatureMap = fmn[f].Select(x => (Neuron)x).ToArray();
for (int p = 0; p < fmp.Length; p++)
{
bool inSchema = Schema[p][f];
if (inSchema)
{
ConnectFeatureMaps(nextFeatureMap, kernelCollection[p], map);
}
}
if (bias != null)
{
Weight weight = new SharedWeight(nextFeatureMap.Length);
foreach (Neuron node in nextFeatureMap)
{
Map(bias, node, weight, map);
}
}
}
foreach (Link link in prior)
{
link.Next = map[link].ToArray();
}
foreach (Neuron node in next)
{
node.Previous = map[node].ToArray();
}
if (bias != null)
{
if (bias.Next == null)
{
bias.Next = new Connection[] { }
}
;
bias.Next = bias.Next.Concat(map[bias]).ToArray();
}
}
void ConnectFeatureMaps(Neuron[] next, Link[][] kernelCollection, Dictionary <Link, List <Connection> > map)
{
Weight[] weights = Utility.Generate(() => new SharedWeight(kernelCollection.Length), KernelSize * KernelSize).ToArray();
for (int i = 0; i < kernelCollection.Length; i++)
{
for (var j = 0; j < kernelCollection[i].Length; j++)
{
Link link = kernelCollection[i][j];
Map(link, next[i], weights[j], map);
}
}
}
void Map(Link a, Link b, Weight weight, Dictionary <Link, List <Connection> > map)
{
Connection connection = new Connection(weight, a, (NeuronBase)b);
if (!map.ContainsKey(a))
{
map[a] = new List <Connection>();
}
map[a].Add(connection);
if (!map.ContainsKey(b))
{
map[b] = new List <Connection>();
}
map[b].Add(connection);
}
}
void ConnectKernel(NeuronBase neuron,Link[] kernel,SharedWeight weight,Dictionary<Link,List<Connection>> map)
{
foreach(Link link in kernel) {
Map(link,neuron,weight,map);
}
}
public override void Connect(Link[] prior, NeuronBase[] next, Bias bias)
{
Utility.Verify(prior, x => x != null && prior.Length > 0, "Invalid prior layer");
Utility.Verify(next, x => x != null && next.Length > 0, "Invalid next layer");
Utility.Verify(() => next.Length % FeatureMapsCount == 0, "FeatureMapsCount - next layer size conflict");
Utility.Verify(() => prior.Length % FeatureMapsCount == 0, "FeatureMapsCount - prior layer size conflict");
Link[][] c = GetFeatureMaps(prior, FeatureMapsCount);
NeuronBase[][] s = GetFeatureMaps(next, FeatureMapsCount);
Link[][][] kernelCollection = GetKernelCollection(c, 2, 0); //always x/2
Dictionary <Link, List <Connection> > map = new Dictionary <Link, List <Connection> >();
for (var i = 0; i < kernelCollection.Length; i++)
{
ConnectFeatureMaps(s[i], kernelCollection[i], bias, map);
}
foreach (Link link in prior)
{
link.Next = map[link].ToArray();
}
foreach (NeuronBase neuron in next)
{
neuron.Previous = map[neuron].ToArray();
}
if (bias != null)
{
if (bias.Next == null)
{
bias.Next = new Connection[] { }
}
;
bias.Next = bias.Next.Concat(map[bias]).ToArray();
}
}
void ConnectFeatureMaps(NeuronBase[] next, Link[][] kernelCollection, Bias bias, Dictionary <Link, List <Connection> > map)
{
SharedWeight weight = new SharedWeight(next.Length);
SharedWeight biasWeight = new SharedWeight(next.Length);
for (var i = 0; i < kernelCollection.Length; i++)
{
ConnectKernel(next[i], kernelCollection[i], weight, map);
if (bias != null)
{
Map(bias, next[i], biasWeight, map);
}
}
}
void ConnectKernel(NeuronBase neuron, Link[] kernel, SharedWeight weight, Dictionary <Link, List <Connection> > map)
{
foreach (Link link in kernel)
{
Map(link, neuron, weight, map);
}
}
void Map(Link a, Link b, Weight weight, Dictionary <Link, List <Connection> > map)
{
Connection connection = new Connection(weight, a, (NeuronBase)b);
if (!map.ContainsKey(a))
{
map[a] = new List <Connection>();
}
map[a].Add(connection);
if (!map.ContainsKey(b))
{
map[b] = new List <Connection>();
}
map[b].Add(connection);
}
}