code: def testMakePrunableWorksOnKerasRNNLayer(self):
      layer = layers.LSTM(10)
      with self.assertRaises(AttributeError):
          layer.get_prunable_weights()
  
      PruneRegistry.make_prunable(layer)
      keras.Sequential([layer]).build(input_shape=(2, 3, 4))
  
      self.assertEqual(
          [layer.cell.kernel, layer.cell.recurrent_kernel],
          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 8 for calling the PruneRegistryTest obj's underlying member method code with example usage: obj.testMakePrunableWorksOnKerasRNNLayer() without return types