tf.raw_ops.LSTMBlockCellGrad

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Computes the LSTM cell backward propagation for 1 timestep.

This implementation is to be used in conjunction of LSTMBlockCell.

x A Tensor. Must be one of the following types: half, float32. The input to the LSTM cell, shape (batch_size, num_inputs).
cs_prev A Tensor. Must have the same type as x. The previous cell state.
h_prev A Tensor. Must have the same type as x. The previous h state.
w A Tensor. Must have the same type as x. The weight matrix.
wci A Tensor. Must have the same type as x. The weight matrix for input gate peephole connection.
wcf A Tensor. Must have the same type as x. The weight matrix for forget gate peephole connection.
wco A Tensor. Must have the same type as x. The weight matrix for output gate peephole connection.
b A Tensor. Must have the same type as x. The bias vector.
i A Tensor. Must have the same type as x. The input gate.
cs A Tensor. Must have the same type as x. The cell state before the tanh.
f A Tensor. Must have the same type as x. The forget gate.
o A Tensor. Must have the same type as x. The output gate.
ci A Tensor. Must have the same type as x. The cell input.
co A Tensor. Must have the same type as x. The cell after the tanh.
cs_grad A Tensor. Must have the same type as x. The current gradient of cs.
h_grad A Tensor. Must have the same type as x. The gradient of h vector.
use_peephole A bool. Whether the cell uses peephole connections.
name A name for the operation (optional).

A tuple of Tensor objects (c