code: def testMakePrunableWorksOnKerasPrunableLayer(self):
      layer = layers.Dense(10)
      with self.assertRaises(AttributeError):
          layer.get_prunable_weights()
  
      PruneRegistry.make_prunable(layer)
      # Required since build method sets up the layer weights.
      keras.Sequential([layer]).build(input_shape=(10, 1))
  
      self.assertEqual([layer.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 6 for calling the PruneRegistryTest obj's underlying member method code with example usage: obj.testMakePrunableWorksOnKerasPrunableLayer() without return types