BlockLSTMGrad

public final class BlockLSTMGrad

Computes the LSTM cell backward propagation for the entire time sequence.

This implementation is to be used in conjunction of BlockLSTMV2.

Constants

String OP_NAME The name of this op, as known by TensorFlow core engine

Public Methods

Output <T>
bGrad ()
The gradient for w to be back-propped.
static <T extends TNumber > BlockLSTMGrad <T>
create ( Scope scope, Operand < TInt64 > seqLenMax, Operand <T> x, Operand <T> csPrev, Operand <T> hPrev, Operand <T> w, Operand <T> wci, Operand <T> wcf, Operand <T> wco, Operand <T> b, Operand <T> i, Operand <T> cs, Operand <T> f, Operand <T> o, Operand <T> ci, Operand <T> co, Operand <T> h, Operand <T> csGrad, Operand <T> hGrad, Boolean usePeephole)
Factory method to create a class wrapping a new BlockLSTMGrad operation.
Output <T>
csPrevGrad ()
The gradient of cs_prev to be back-propped.
Output <T>
hPrevGrad ()
The gradient of h_prev to be back-propped.
Output <T>
wGrad ()
The gradient for w to be back-propped.
Output <T>
wcfGrad ()
The gradient for wcf to be back-propped.
Output <T>
wciGrad ()
The gradient for wci to be back-propped.
Output <T>
wcoGrad ()
The gradient for wco to be back-propped.
Output <T>
xGrad ()
The gradient of x to be back-propped.

Inherited Methods

Constants

public static final String OP_NAME

The name of this op, as known by TensorFlow core engine

Constant Value: "BlockLSTMGradV2"

Public Methods

public Output <T> bGrad ()

The gradient for w to be back-propped.

public static BlockLSTMGrad <T> create ( Scope scope, Operand < TInt64 > seqLenMax, Operand <T> x, Operand <T> csPrev, Operand <T> hPrev, Operand <T> w, Operand <T> wci, Operand <T> wcf, Operand <T> wco, Operand <T> b, Operand <T> i, Operand <T> cs, Operand <T> f, Operand <T> o, Operand <T> ci, Operand <T> co, Operand <T> h, Operand <T> csGrad, Operand <T> hGrad, Boolean usePeephole)

Factory method to create a class wrapping a new BlockLSTMGrad operation.

Parameters
scope current scope
seqLenMax Maximum time length actually used by this input. Outputs are padded with zeros beyond this length.
x The sequence input to the LSTM, shape (timelen, batch_size, num_inputs).
csPrev Value of the initial cell state.
hPrev Initial output of cell (to be used for peephole).
w The weight matrix.
wci The weight matrix for input gate peephole connection.
wcf The weight matrix for forget gate peephole connection.
wco The weight matrix for output gate peephole connection.
b The bias vector.
i The input gate over the whole time sequence.
cs The cell state before the tanh over the whole time sequence.
f The forget gate over the whole time sequence.
o The output gate over the whole time sequence.
ci The cell input over the whole time sequence.
co The cell after the tanh over the whole time sequence.
h The output h vector over the whole time sequence.
csGrad The current gradient of cs.
hGrad The gradient of h vector.
usePeephole Whether to use peephole weights.
Returns
  • a new instance of BlockLSTMGrad

public Output <T> csPrevGrad ()

The gradient of cs_prev to be back-propped.

public Output <T> hPrevGrad ()

The gradient of h_prev to be back-propped.

public Output <T> wGrad ()

The gradient for w to be back-propped.

public Output <T> wcfGrad ()

The gradient for wcf to be back-propped.

public Output <T> wciGrad ()

The gradient for wci to be back-propped.

public Output <T> wcoGrad ()

The gradient for wco to be back-propped.

public Output <T> xGrad ()

The gradient of x to be back-propped.