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Class RNNCell
Abstract object representing an RNN cell.
Inherits From: Layer
Aliases:
Every RNNCell must have the properties below and implement call with
the signature (output, next_state) = call(input, state). The optional
third input argument, scope, is allowed for backwards compatibility
purposes; but should be left off for new subclasses.
This definition of cell differs from the definition used in the literature. In the literature, 'cell' refers to an object with a single scalar output. This definition refers to a horizontal array of such units.
An RNN cell, in the most abstract setting, is anything that has
a state and performs some operation that takes a matrix of inputs.
This operation results in an output matrix with self.output_size columns.
If self.state_size is an integer, this operation also results in a new
state matrix with self.state_size columns. If self.state_size is a
(possibly nested tuple of) TensorShape object(s), then it should return a
matching structure of Tensors having shape [batch_size].concatenate(s)
for each s in self.batch_size.
__init__
__init__(
trainable=True,
name=None,
dtype=None,
**kwargs
)
Properties
graph
DEPRECATED FUNCTION
output_size
Integer or TensorShape: size of outputs produced by this cell.
scope_name
state_size
size(s) of state(s) used by this cell.
It can be represented by an Integer, a TensorShape or a tuple of Integers or TensorShapes.
Methods
tf.nn.rnn_cell.RNNCell.get_initial_state
get_initial_state(
inputs=None,
batch_size=None,
dtype=None
)
tf.nn.rnn_cell.RNNCell.zero_state
zero_state(
batch_size,
dtype
)
Return zero-filled state tensor(s).
Args:
batch_size: int, float, or unit Tensor representing the batch size.dtype: the data type to use for the state.
Returns:
If state_size is an int or TensorShape, then the return value is a
N-D tensor of shape [batch_size, state_size] filled with zeros.
If 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
the shapes [batch_size, s] for each s in state_size.