tf.nn.static_state_saving_rnn

Aliases:

  • tf.contrib.rnn.static_state_saving_rnn
  • tf.nn.static_state_saving_rnn
tf.nn.static_state_saving_rnn(
    cell,
    inputs,
    state_saver,
    state_name,
    sequence_length=None,
    scope=None
)

Defined in tensorflow/python/ops/rnn.py.

See the guide: RNN and Cells (contrib) > Recurrent Neural Networks

RNN that accepts a state saver for time-truncated RNN calculation.

Args:

  • cell: An instance of RNNCell.
  • inputs: A length T list of inputs, each a Tensor of shape [batch_size, input_size].
  • state_saver: A state saver object with methods state and save_state.
  • state_name: Python string or tuple of strings. The name to use with the state_saver. If the cell returns tuples of states (i.e., cell.state_size is a tuple) then state_name should be a tuple of strings having the same length as cell.state_size. Otherwise it should be a single string.
  • sequence_length: (optional) An int32/int64 vector size [batch_size]. See the documentation for rnn() for more details about sequence_length.
  • scope: VariableScope for the created subgraph; defaults to "rnn".

Returns:

A pair (outputs, state) where: outputs is a length T list of outputs (one for each input) states is the final state

Raises:

  • TypeError: If cell is not an instance of RNNCell.
  • ValueError: If inputs is None or an empty list, or if the arity and type of state_name does not match that of cell.state_size.