internal static BetaSimilarity[] GetVector(int x)
{
BetaSimilarity[] vector = new BetaSimilarity[x];
for (int i = 0; i < x; i++)
{
vector[i] = new BetaSimilarity();
}
return vector;
}
internal static BetaSimilarity[][] GetTensor2(int x, int y)
{
BetaSimilarity[][] tensor = new BetaSimilarity[x][];
for (int i = 0; i < x; i++)
{
tensor[i] = GetVector(y);
}
return tensor;
}
internal static BetaSimilarity[] GetVector(int x)
{
BetaSimilarity[] vector = new BetaSimilarity[x];
for (int i = 0; i < x; i++)
{
vector[i] = new BetaSimilarity();
}
return(vector);
}
internal static BetaSimilarity[][] GetTensor2(int x, int y)
{
BetaSimilarity[][] tensor = new BetaSimilarity[x][];
for (int i = 0; i < x; i++)
{
tensor[i] = GetVector(y);
}
return(tensor);
}
//Implementation of focusing by content (Page 8, Unit 3.3.1 Focusing by Content)
internal ContentAddressing(BetaSimilarity[] betaSimilarities)
{
BetaSimilarities = betaSimilarities;
ContentVector = UnitFactory.GetVector(betaSimilarities.Length);
//Subtracting max increase numerical stability
double max = BetaSimilarities.Max(similarity => similarity.BetaSimilarityMeasure.Value);
double sum = 0;
for (int i = 0; i < BetaSimilarities.Length; i++)
{
BetaSimilarity unit = BetaSimilarities[i];
double weight = Math.Exp(unit.BetaSimilarityMeasure.Value - max);
ContentVector[i].Value = weight;
sum += weight;
}
foreach (Unit unit in ContentVector)
{
unit.Value = unit.Value/sum;
}
}
//Implementation of focusing by content (Page 8, Unit 3.3.1 Focusing by Content)
internal ContentAddressing(BetaSimilarity[] betaSimilarities)
{
BetaSimilarities = betaSimilarities;
ContentVector = UnitFactory.GetVector(betaSimilarities.Length);
//Subtracting max increase numerical stability
double max = BetaSimilarities.Max(similarity => similarity.BetaSimilarityMeasure.Value);
double sum = 0;
for (int i = 0; i < BetaSimilarities.Length; i++)
{
BetaSimilarity unit = BetaSimilarities[i];
double weight = Math.Exp(unit.BetaSimilarityMeasure.Value - max);
ContentVector[i].Value = weight;
sum += weight;
}
foreach (Unit unit in ContentVector)
{
unit.Value = unit.Value / sum;
}
}
internal MemoryState Process(Head[] heads)
{
int headCount = heads.Length;
int memoryColumnsN = _memory.CellCountN;
ReadData[] newReadDatas = new ReadData[headCount];
HeadSetting[] newHeadSettings = new HeadSetting[headCount];
for (int i = 0; i < headCount; i++)
{
Head head = heads[i];
BetaSimilarity[] similarities = new BetaSimilarity[_memory.CellCountN];
for (int j = 0; j < memoryColumnsN; j++)
{
Unit[] memoryColumn = _memory.Data[j];
SimilarityMeasure similarity = new SimilarityMeasure(new CosineSimilarityFunction(), head.KeyVector, memoryColumn);
similarities[j] = new BetaSimilarity(head.Beta, similarity);
}
ContentAddressing ca = new ContentAddressing(similarities);
GatedAddressing ga = new GatedAddressing(head.Gate, ca, _headSettings[i]);
ShiftedAddressing sa = new ShiftedAddressing(head.Shift, ga);
newHeadSettings[i] = new HeadSetting(head.Gamma, sa);
newReadDatas[i] = new ReadData(newHeadSettings[i], _memory);
}
NTMMemory newMemory = new NTMMemory(newHeadSettings, heads, _memory);
return new MemoryState(newMemory, newHeadSettings, newReadDatas);
}