tf.contrib.rnn.MultiRNNCell

class tf.contrib.rnn.MultiRNNCell

class tf.contrib.rnn.core_rnn_cell.MultiRNNCell

See the guide: RNN and Cells (contrib) > Core RNN Cell wrappers (RNNCells that wrap other RNNCells)

RNN cell composed sequentially of multiple simple cells.

Properties

output_size

state_size

Methods

__init__(cells, state_is_tuple=True)

Create a RNN cell composed sequentially of a number of RNNCells.

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.

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 x 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 x s] for each s in state_size.

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