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

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

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.

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