protected void InitCache(List <ILayer> s_forwardRNN, List <ILayer> s_backwardRNN, IOutputLayer outputLayer)
{
forwardHiddenLayers = s_forwardRNN;
backwardHiddenLayers = s_backwardRNN;
//Initialize output layer
OutputLayer = outputLayer;
forwardCellList = new List <Neuron[]>();
backwardCellList = new List <Neuron[]>();
for (int i = 0; i < numOfLayers; i++)
{
var forwardCells = new Neuron[MaxSeqLength];
var backwardCells = new Neuron[MaxSeqLength];
for (int j = 0; j < MaxSeqLength; j++)
{
if (forwardHiddenLayers[i] is DropoutLayer)
{
forwardCells[j] = new DropoutNeuron(forwardHiddenLayers[i].LayerSize);
backwardCells[j] = new DropoutNeuron(forwardHiddenLayers[i].LayerSize);
}
else if (forwardHiddenLayers[i] is LSTMLayer)
{
forwardCells[j] = new LSTMNeuron(forwardHiddenLayers[i].LayerSize);
backwardCells[j] = new LSTMNeuron(forwardHiddenLayers[i].LayerSize);
}
else
{
forwardCells[j] = new Neuron(forwardHiddenLayers[i].LayerSize);
backwardCells[j] = new Neuron(forwardHiddenLayers[i].LayerSize);
}
}
forwardCellList.Add(forwardCells);
backwardCellList.Add(backwardCells);
}
OutputCells = new Neuron[MaxSeqLength];
for (var i = 0; i < MaxSeqLength; i++)
{
OutputCells[i] = new Neuron(OutputLayer.LayerSize);
}
InitLayersOutputCache();
}
public void InitCache(List <SimpleLayer> s_forwardRNN, List <SimpleLayer> s_backwardRNN, SimpleLayer outputLayer)
{
forwardHiddenLayers = s_forwardRNN;
backwardHiddenLayers = s_backwardRNN;
//Initialize output layer
OutputLayer = outputLayer;
forwardCellList = new List <Neuron[]>();
backwardCellList = new List <Neuron[]>();
fErrLayers = new List <float[][]>();
bErrLayers = new List <float[][]>();
for (int i = 0; i < numOfLayers; i++)
{
var forwardCells = new Neuron[MaxSeqLength];
var backwardCells = new Neuron[MaxSeqLength];
var fErrLayer = new float[MaxSeqLength][];
var bErrLayer = new float[MaxSeqLength][];
for (int j = 0; j < MaxSeqLength; j++)
{
if (forwardHiddenLayers[i] is DropoutLayer)
{
forwardCells[j] = new DropoutNeuron();
backwardCells[j] = new DropoutNeuron();
((DropoutNeuron)forwardCells[j]).mask = new bool[forwardHiddenLayers[i].LayerSize];
((DropoutNeuron)backwardCells[j]).mask = new bool[forwardHiddenLayers[i].LayerSize];
}
else if (forwardHiddenLayers[i] is LSTMLayer)
{
var lstmForwardCell = new LSTMNeuron();
var lstmBackwardCell = new LSTMNeuron();
lstmForwardCell.LSTMCells = new LSTMCell[forwardHiddenLayers[i].LayerSize];
lstmBackwardCell.LSTMCells = new LSTMCell[forwardHiddenLayers[i].LayerSize];
for (int k = 0; k < forwardHiddenLayers[i].LayerSize; k++)
{
lstmForwardCell.LSTMCells[k] = new LSTMCell();
lstmBackwardCell.LSTMCells[k] = new LSTMCell();
}
forwardCells[j] = lstmForwardCell;
backwardCells[j] = lstmBackwardCell;
}
else
{
forwardCells[j] = new Neuron();
backwardCells[j] = new Neuron();
}
forwardCells[j].Cells = new float[forwardHiddenLayers[i].LayerSize];
forwardCells[j].PrevCellOutputs = new float[forwardHiddenLayers[i].LayerSize];
backwardCells[j].Cells = new float[forwardHiddenLayers[i].LayerSize];
backwardCells[j].PrevCellOutputs = new float[forwardHiddenLayers[i].LayerSize];
fErrLayer[j] = new float[forwardHiddenLayers[i].LayerSize];
bErrLayer[j] = new float[forwardHiddenLayers[i].LayerSize];
}
forwardCellList.Add(forwardCells);
backwardCellList.Add(backwardCells);
fErrLayers.Add(fErrLayer);
bErrLayers.Add(bErrLayer);
}
InitOutputLayerCache();
}
