class_docstr: Base class inherited by all RNN decoder classes.
  See :class:`~texar.tf.modules.BasicRNNDecoder` for the argumenrts.
  
  See :meth:`_build` for the inputs and outputs of RNN decoders in general.
  
  .. document private functions
  .. automethod:: _build
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code: def _rnn_output_size(self):
      size = self._cell.output_size
      if self._output_layer is tf.identity:
          return size
      else:
          # To use layer's compute_output_shape, we need to convert the
          # RNNCell's output_size entries into shapes with an unknown
          # batch size.  We then pass this through the layer's
          # compute_output_shape and read off all but the first (batch)
          # dimensions to get the output size of the rnn with the layer
          # applied to the top.
          output_shape_with_unknown_batch = nest.map_structure(
              lambda s: tensor_shape.TensorShape([None]).concatenate(s),
              size,
          )
          layer_output_shape = self._output_layer.compute_output_shape(
              output_shape_with_unknown_batch
          )
          return nest.map_structure(lambda s: s[1:], layer_output_shape)
  
imports: import copy
  import tensorflow
  from tensorflow.contrib.seq2seq import Decoder
  from tensorflow.python.framework import tensor_shape
  from tensorflow.python.util import nest
  from texar.tf.core import layers
  from texar.tf.utils import utils
  from texar.tf.utils.mode import is_train_mode, is_train_mode_py
  from texar.tf.modules.decoders.dynamic_decode import dynamic_decode
  from texar.tf.module_base import ModuleBase
  from texar.tf.modules.decoders import rnn_decoder_helpers
  from texar.tf.utils.dtypes import is_callable
  from texar.tf.utils.shapes import shape_list
  from texar.tf.modules.decoders import tf_helpers
label_desc: Use image node_id 5 for calling the RNNDecoderBase obj's underlying member method code with example usage: obj._rnn_output_size() and returns: size, nest