class_docstr: Wraps a Keras RNN/LSTM/GRU layer to make network state more consistent.
code: def get_config(self):
      config = {
          "layer": {
              "class_name": self._layer.__class__.__name__,
              "config": self._layer.get_config(),
          }
      }
      base_config = dict(super(RNNWrapper, self).get_config())
      base_config.update(config)
      return base_config
  
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 6 for calling the RNNWrapper obj's underlying member method code with example usage: obj.get_config() and returns: base_config