Method SinglePassLSTM

SinglePassLSTM(TensorFloat, TensorFloat, TensorFloat, TensorFloat, TensorInt, TensorFloat, TensorFloat, TensorFloat, TensorFloat, RnnActivation[], float[], float[], bool, float, bool, int, RnnLayout)

Computes a single pass LSTM either forward or reverse dirIndex and layout are used to calculate where to index the various tensors in bidirectional and batch first layout passes X has given layout W, R are cropped to single direction P, B are full number of directions Y has given layout and full number of directions (matches output of Layer) Y_h, Y_c are SequenceFirst layout and cropped to single direction HtxRT and XsixWT are temp vectors of the correct dimension for the intermediate results of the matmuls activations, activationAlpha and activationBeta have full number of dimensions

Declaration

protected virtual void SinglePassLSTM(TensorFloat X, TensorFloat W, TensorFloat R, TensorFloat B, TensorInt sequenceLens, TensorFloat P, TensorFloat Y, TensorFloat Y_h, TensorFloat Y_c, RnnActivation[] activations, float[] activationAlpha, float[] activationBeta, bool inputForget, float clip, bool isReverse, int dirIndex, RnnLayout layout)

Parameters

Type	Name	Description
TensorFloat	X	The input tensor.
TensorFloat	W	The weights tensor.
TensorFloat	R	The recurrence weights tensor.
TensorFloat	B	The bias tensor.
TensorInt	sequenceLens	Optional tensor specifying lengths of the sequences in a batch.
TensorFloat	P	The weight tensor for the peepholes.
TensorFloat	Y	The output tensor.
TensorFloat	Y_h	The output tensor for the last hidden.
TensorFloat	Y_c	The output tensor for the last cell.
RnnActivation[]	activations	The activations.
float[]	activationAlpha	The activation alpha value.
float[]	activationBeta	The activation beta value.
bool	inputForget	Whether to couple the input and forget gates.
float	clip	The cell clip threshold.
bool	isReverse	Whether the direction is reverse.
int	dirIndex	Which pass this is in a bidirectional LSTM.
RnnLayout	layout	The layout of the tensors.