code: def testMakePrunableWorksOnKerasRNNLayerWithPrunableCell(self):
      cell1 = layers.LSTMCell(10)
      cell2 = MinimalRNNCellPrunable(5)
      layer = layers.RNN([cell1, cell2])
      with self.assertRaises(AttributeError):
          layer.get_prunable_weights()
  
      PruneRegistry.make_prunable(layer)
      keras.Sequential([layer]).build(input_shape=(2, 3, 4))
  
      expected_weights = [
          cell1.kernel,
          cell1.recurrent_kernel,
          cell2.kernel,
          cell2.recurrent_kernel,
      ]
      self.assertEqual(expected_weights, layer.get_prunable_weights())
  
imports: from absl.testing import parameterized
  import tensorflow
  from tensorflow_model_optimization.python.core.sparsity.keras import prunable_layer
  from tensorflow_model_optimization.python.core.sparsity.keras import prune_registry
label_desc: Use image node_id 10 for calling the PruneRegistryTest obj's underlying member method code with example usage: obj.testMakePrunableWorksOnKerasRNNLayerWithPrunableCell() without return types