class_docstr: Operator adding an output projection to the given cell.
  
  Note: in many cases it may be more efficient to not use this wrapper,
  but instead concatenate the whole sequence of your outputs in time,
  do the projection on this batch-concatenated sequence, then split it
  if needed or directly feed into a softmax.
code: def state_size(self):
      return self._cell.state_size
  
imports: from __future__ import absolute_import
  from __future__ import division
  from __future__ import print_function
  import math
  from tensorflow.python.framework import constant_op
  from tensorflow.python.framework import dtypes
  from tensorflow.python.framework import ops
  from tensorflow.python.ops import array_ops
  from tensorflow.python.ops import embedding_ops
  from tensorflow.python.ops import init_ops
  from tensorflow.python.ops import math_ops
  from tensorflow.python.ops import nn_ops
  from tensorflow.python.ops import rnn_cell_impl
  from tensorflow.python.ops import variable_scope
  from tensorflow.python.platform import tf_logging
  from tensorflow.python.util import nest
label_desc: Use image node_id 2 for calling the OutputProjectionWrapper obj's underlying member method code with example usage: obj.state_size() and returns: self