rnn_core.py 文件源码

def zero_state(self, 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`.
    """
    # Keep scope for backwards compatibility.
    with tf.name_scope(type(self).__name__ + "ZeroState", values=[batch_size]):
      return rnn_cell_impl._zero_state_tensors(  # pylint: disable=protected-access
          self.state_size, batch_size, dtype)