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Class FusedRNNCellAdaptor
This is an adaptor for RNNCell classes to be used with FusedRNNCell
.
Inherits From: FusedRNNCell
__init__
__init__(
cell,
use_dynamic_rnn=False
)
Initialize the adaptor.
Args:
cell
: an instance of a subclass of arnn_cell.RNNCell
.use_dynamic_rnn
: whether to use dynamic (or static) RNN.
Methods
tf.contrib.rnn.FusedRNNCellAdaptor.__call__
__call__(
inputs,
initial_state=None,
dtype=None,
sequence_length=None,
scope=None
)
Run this fused RNN on inputs, starting from the given state.
Args:
inputs
:3-D
tensor with shape[time_len x batch_size x input_size]
or a list oftime_len
tensors of shape[batch_size x input_size]
.initial_state
: either a tensor with shape[batch_size x state_size]
or a tuple with shapes[batch_size x s] for s in state_size
, if the cell takes tuples. If this is not provided, the cell is expected to create a zero initial state of typedtype
.dtype
: The data type for the initial state and expected output. Required ifinitial_state
is not provided or RNN state has a heterogeneous dtype.sequence_length
: Specifies the length of each sequence in inputs. Anint32
orint64
vector (tensor) size[batch_size]
, values in[0, time_len)
. Defaults totime_len
for each element.scope
:VariableScope
orstring
for the created subgraph; defaults to class name.
Returns:
A pair containing:
- Output: A
3-D
tensor of shape[time_len x batch_size x output_size]
or a list oftime_len
tensors of shape[batch_size x output_size]
, to match the type of theinputs
. - Final state: Either a single
2-D
tensor, or a tuple of tensors matching the arity and shapes ofinitial_state
.