RNN cell composed sequentially of multiple simple cells.
Inherits From: RNNCell
, Layer
, Layer
, Module
tf.compat.v1.nn.rnn_cell.MultiRNNCell(
cells, state_is_tuple=True
)
Example:
num_units = [128, 64]
cells = [BasicLSTMCell(num_units=n) for n in num_units]
stacked_rnn_cell = MultiRNNCell(cells)
Args |
cells
|
list of RNNCells that will be composed in this order.
|
state_is_tuple
|
If True, accepted and returned states are n-tuples,
where n = len(cells) . If False, the states are all concatenated
along the column axis. This latter behavior will soon be
deprecated.
|
Raises |
ValueError
|
if cells is empty (not allowed), or at least one of the
cells returns a state tuple but the flag state_is_tuple is
False .
|
Attributes |
graph
|
|
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
apply
View source
apply(
*args, **kwargs
)
get_initial_state
View source
get_initial_state(
inputs=None, batch_size=None, dtype=None
)
get_losses_for
View source
get_losses_for(
inputs
)
Retrieves losses relevant to a specific set of inputs.
Args |
inputs
|
Input tensor or list/tuple of input tensors.
|
Returns |
List of loss tensors of the layer that depend on inputs .
|
get_updates_for
View source
get_updates_for(
inputs
)
Retrieves updates relevant to a specific set of inputs.
Args |
inputs
|
Input tensor or list/tuple of input tensors.
|
Returns |
List of update ops of the layer that depend on inputs .
|
zero_state
View source
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 .
|