Operator adding dropout to inputs and outputs of the given cell.
__init__(cell, input_keep_prob=1.0, output_keep_prob=1.0, seed=None)
Create a cell with added input and/or output dropout.
Dropout is never used on the state.
cell: an RNNCell, a projection to output_size is added to it.
input_keep_prob: unit Tensor or float between 0 and 1, input keep probability; if it is float and 1, no input dropout will be added.
output_keep_prob: unit Tensor or float between 0 and 1, output keep probability; if it is float and 1, no output dropout will be added.
seed: (optional) integer, the randomness seed.
TypeError: if cell is not an RNNCell.
ValueError: if keep_prob is not between 0 and 1.
Return zero-filled state tensor(s).
batch_size: int, float, or unit Tensor representing the batch size.
dtype: the data type to use for the state.
state_size is an int or TensorShape, then the return value is a
N-D tensor of shape
[batch_size x state_size] filled with zeros.
state_size is a nested list or tuple, then the return value is
a nested list or tuple (of the same structure) of
2-D tensors with
[batch_size x s] for each s in