class_docstr: Integration tests for clustering RNN layers.
code: def testClusterBidirectional(self):
      model = keras.models.Sequential()
      model.add(
          keras.layers.Embedding(
              self.max_features, 16, input_length=self.maxlen
          )
      )
      model.add(keras.layers.Bidirectional(keras.layers.SimpleRNN(16)))
      model.add(keras.layers.Dense(1))
      model.add(keras.layers.Activation("sigmoid"))
  
      self._clusterTrainStrip(model)
  
      self._assertNbUniqueWeights(
          weight=model.layers[1].forward_layer.cell.kernel,
          expected_unique_weights=self.params_clustering[
              "number_of_clusters"
          ],
      )
      self._assertNbUniqueWeights(
          weight=model.layers[1].forward_layer.cell.recurrent_kernel,
          expected_unique_weights=self.params_clustering[
              "number_of_clusters"
          ],
      )
      self._assertNbUniqueWeights(
          weight=model.layers[0].embeddings,
          expected_unique_weights=self.params_clustering[
              "number_of_clusters"
          ],
      )
  
imports: import os
  import tempfile
  from absl.testing import parameterized
  import numpy
  import tensorflow
  from tensorflow_model_optimization.python.core.clustering.keras import cluster
  from tensorflow_model_optimization.python.core.clustering.keras import cluster_config
  from tensorflow_model_optimization.python.core.clustering.keras.experimental import cluster
label_desc: Use image node_id 8 for calling the ClusterRNNIntegrationTest obj's underlying member method code with example usage: obj.testClusterBidirectional() without return types