class_docstr: Wraps a Keras RNN/LSTM/GRU layer to make network state more consistent.
docstr: Return the `state_size` of the cell underlying the RNN layer.
docstr_tok: ["Return","the","`","state_size","`","of","the","cell","underlying","the","RNN","layer","."]
code: def state_size(self):
      """Return the `state_size` of the cell underlying the RNN layer."""
      return self._layer.cell.state_size
  
imports: from __future__ import absolute_import
  from __future__ import division
  from __future__ import print_function
  import tensorflow
  from tf_agents.utils import common
label_desc: Use image node_id 4 for calling the RNNWrapper obj's underlying member method code with example usage: obj.state_size() and returns: self