public void initWeights()
{
int b, a;
for (b = 0; b < LayerSize; b++)
{
for (a = 0; a < SparseFeatureSize; a++)
{
SparseWeights[b][a] = RNNHelper.RandInitWeight();
}
}
for (b = 0; b < LayerSize; b++)
{
for (a = 0; a < DenseFeatureSize; a++)
{
DenseWeights[b][a] = RNNHelper.RandInitWeight();
}
}
for (b = 0; b < LayerSize; b++)
{
for (a = 0; a < LayerSize; a++)
{
BpttWeights[b][a] = RNNHelper.RandInitWeight();
}
}
}
public virtual void InitializeWeights(int sparseFeatureSize, int denseFeatureSize)
{
if (denseFeatureSize > 0)
{
Logger.WriteLine("Initializing dense feature matrix. layer size = {0}, feature size = {1}", LayerSize, denseFeatureSize);
DenseFeatureSize = denseFeatureSize;
DenseWeights = new Matrix <float>(LayerSize, denseFeatureSize);
for (var i = 0; i < DenseWeights.Height; i++)
{
for (var j = 0; j < DenseWeights.Width; j++)
{
DenseWeights[i][j] = RNNHelper.RandInitWeight();
}
}
}
if (sparseFeatureSize > 0)
{
Logger.WriteLine("Initializing sparse feature matrix. layer size = {0}, feature size = {1}", LayerSize, sparseFeatureSize);
SparseFeatureSize = sparseFeatureSize;
SparseWeights = new Matrix <float>(LayerSize, SparseFeatureSize);
for (var i = 0; i < SparseWeights.Height; i++)
{
for (var j = 0; j < SparseWeights.Width; j++)
{
SparseWeights[i][j] = RNNHelper.RandInitWeight();
}
}
}
InitializeInternalTrainingParameters();
}
private void CreateCell(BinaryReader br)
{
if (br != null)
{
//Load weight from input file
for (int i = 0; i < LayerSize; i++)
{
cell[i].wPeepholeIn = br.ReadDouble();
cell[i].wPeepholeForget = br.ReadDouble();
cell[i].wPeepholeOut = br.ReadDouble();
cell[i].wCellIn = br.ReadDouble();
cell[i].wCellForget = br.ReadDouble();
cell[i].wCellState = br.ReadDouble();
cell[i].wCellOut = br.ReadDouble();
}
}
else
{
//Initialize weight by random number
for (int i = 0; i < LayerSize; i++)
{
//internal weights, also important
cell[i].wPeepholeIn = RNNHelper.RandInitWeight();
cell[i].wPeepholeForget = RNNHelper.RandInitWeight();
cell[i].wPeepholeOut = RNNHelper.RandInitWeight();
cell[i].wCellIn = RNNHelper.RandInitWeight();
cell[i].wCellForget = RNNHelper.RandInitWeight();
cell[i].wCellState = RNNHelper.RandInitWeight();
cell[i].wCellOut = RNNHelper.RandInitWeight();
}
}
}
public void Init(int LayerSize, int DenseFeatureSize, bool hasDeri = true)
{
layerSize = LayerSize;
denseFeatureSize = DenseFeatureSize;
weights = new float[LayerSize][];
if (hasDeri)
{
deri = new float[LayerSize][];
}
else
{
deri = null;
}
for (var i = 0; i < LayerSize; i++)
{
weights[i] = new float[DenseFeatureSize];
if (hasDeri)
{
deri[i] = new float[DenseFeatureSize];
}
for (var j = 0; j < DenseFeatureSize; j++)
{
weights[i][j] = RNNHelper.RandInitWeight();
}
}
}
private Vector4 InitializeLSTMWeight()
{
Vector4 w;
//initialise each weight to random value
w.X = RNNHelper.RandInitWeight();
w.Y = RNNHelper.RandInitWeight();
w.Z = RNNHelper.RandInitWeight();
w.W = RNNHelper.RandInitWeight();
return(w);
}
public void InitWeights(int LayerSize, int DenseFeatureSize)
{
layerSize = LayerSize;
denseFeatureSize = DenseFeatureSize;
weights = new float[layerSize][];
for (var i = 0; i < layerSize; i++)
{
weights[i] = new float[denseFeatureSize];
for (var j = 0; j < denseFeatureSize; j++)
{
weights[i][j] = RNNHelper.RandInitWeight();
}
}
}
public virtual void InitializeWeights(int sparseFeatureSize, int denseFeatureSize)
{
if (denseFeatureSize > 0)
{
DenseFeatureSize = denseFeatureSize;
DenseWeights = new Matrix <double>(LayerSize, denseFeatureSize);
for (int i = 0; i < DenseWeights.Height; i++)
{
for (int j = 0; j < DenseWeights.Width; j++)
{
DenseWeights[i][j] = RNNHelper.RandInitWeight();
}
}
}
}
private void InitializeCellWeights(BinaryReader br)
{
CellWeights = new LSTMCellWeight[LayerSize];
CellWeightsDeri = new LSTMCellWeightDeri[LayerSize];
if (br != null)
{
//Load weight from input file
for (var i = 0; i < LayerSize; i++)
{
CellWeights[i] = new LSTMCellWeight();
CellWeights[i].wPeepholeIn = br.ReadDouble();
CellWeights[i].wPeepholeForget = br.ReadDouble();
CellWeights[i].wPeepholeOut = br.ReadDouble();
CellWeights[i].wCellIn = br.ReadDouble();
CellWeights[i].wCellForget = br.ReadDouble();
CellWeights[i].wCellState = br.ReadDouble();
CellWeights[i].wCellOut = br.ReadDouble();
CellWeightsDeri[i] = new LSTMCellWeightDeri();
}
}
else
{
//Initialize weight by random number
for (var i = 0; i < LayerSize; i++)
{
CellWeights[i] = new LSTMCellWeight();
//internal weights, also important
CellWeights[i].wPeepholeIn = RNNHelper.RandInitWeight();
CellWeights[i].wPeepholeForget = RNNHelper.RandInitWeight();
CellWeights[i].wPeepholeOut = RNNHelper.RandInitWeight();
CellWeights[i].wCellIn = RNNHelper.RandInitWeight();
CellWeights[i].wCellForget = RNNHelper.RandInitWeight();
CellWeights[i].wCellState = RNNHelper.RandInitWeight();
CellWeights[i].wCellOut = RNNHelper.RandInitWeight();
CellWeightsDeri[i] = new LSTMCellWeightDeri();
}
}
}