View source on GitHub
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This is an adaptor to time-reverse a FusedRNNCell.
Inherits From: FusedRNNCell
tf.contrib.rnn.TimeReversedFusedRNN(
cell
)
For example,
cell = tf.compat.v1.nn.rnn_cell.BasicRNNCell(10)
fw_lstm = tf.contrib.rnn.FusedRNNCellAdaptor(cell, use_dynamic_rnn=True)
bw_lstm = tf.contrib.rnn.TimeReversedFusedRNN(fw_lstm)
fw_out, fw_state = fw_lstm(inputs)
bw_out, bw_state = bw_lstm(inputs)
Methods
__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 of time_len tensors of shape [batch_size x input_size].
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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 type dtype.
|
dtype
|
The data type for the initial state and expected output. Required
if initial_state is not provided or RNN state has a heterogeneous
dtype.
|
sequence_length
|
Specifies the length of each sequence in inputs. An
int32 or int64 vector (tensor) size [batch_size], values in [0,
time_len).
Defaults to time_len for each element.
|
scope
|
VariableScope or string for the created subgraph; defaults to
class name.
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| Returns | |
|---|---|
A pair containing:
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