class_docstr: This wrapper augments a RNN layer so that the weights can be clustered.
  
  The weight_name of a single cell in RNN layers is marked with an index in
  registry. In the wrapper layer, the index needs to be removed for matching
  the attribute of the cell layer.
code: def get_return_layer_cell(self, index):
      return_layer_cell = (
          self.layer.forward_layer.cell
          if index == 0
          else self.layer.backward_layer.cell
      )
      return return_layer_cell
  
imports: import operator
  import tensorflow
  from tensorflow_model_optimization.python.core.clustering.keras import cluster_config
  from tensorflow_model_optimization.python.core.clustering.keras import clusterable_layer
  from tensorflow_model_optimization.python.core.clustering.keras import clustering_centroids
  from tensorflow_model_optimization.python.core.clustering.keras import clustering_registry
label_desc: Use image node_id 2 for calling the ClusterWeightsRNN obj's underlying member method code with example usage: obj.get_return_layer_cell(index) and returns: return_layer_cell