class_docstr: Base class for cells wrappers V2 compatibility.
  
  This class along with `rnn_cell_impl._RNNCellWrapperV1` allows to define
  wrappers that are compatible with V1 and V2, and defines helper methods for
  this purpose.
class_docstr_tok: ["Base","class","for","cells","wrappers","V2","compatibility",".","This","class","along","with","`","rnn_cell_impl._RNNCellWrapperV1","`","allows","to","define","wrappers","that","are","compatible","with","V1","and","V2",",","and","defines","helper","methods","for","this","purpose","."]
code: def get_config(self):
      config = {
          "cell": {
              "class_name": self.cell.__class__.__name__,
              "config": self.cell.get_config(),
          },
      }
      base_config = super(_RNNCellWrapperV2, self).get_config()
      return dict(list(base_config.items()) + list(config.items()))
  
imports: from tensorflow.python.keras.layers import recurrent
  from tensorflow.python.keras.layers.legacy_rnn import rnn_cell_wrapper_impl
  from tensorflow.python.keras.utils import tf_inspect
  from tensorflow.python.util.deprecation import deprecated
  from tensorflow.python.util.tf_export import tf_export
label_desc: Use image node_id 4 for calling the _RNNCellWrapperV2 obj's underlying member method code with example usage: obj.get_config() and returns: dict