code: def testPruneModel(self):
      self.model.add(Prune(layers.Conv2D(32, 5)))
      self.model.add(Prune(layers.MaxPooling2D((2, 2), (2, 2))))
      self.model.add(Prune(layers.Conv2D(64, 5)))
      self.model.add(Prune(layers.MaxPooling2D((2, 2), (2, 2))))
      self.model.add(Prune(layers.Flatten()))
      self.model.add(Prune(layers.Dense(1024)))
      self.model.add(Prune(layers.Dropout(0.4)))
      self.model.add(Prune(layers.Dense(10)))
      self.model.build(input_shape=(1, 28, 28, 1))
  
      self._check_mask_count(expected_mask_count=4)
  
      # Test serialization
      model_config = self.model.get_config()
      for layer in model_config["layers"]:
          layer.pop("build_config", None)
      self.assertEqual(
          model_config,
          self.model.__class__.from_config(
              self.model.get_config(),
              custom_objects={
                  "PruneLowMagnitude": pruning_wrapper.PruneLowMagnitude
              },
          ).get_config(),
      )
  
imports: from __future__ import absolute_import
  from __future__ import division
  from __future__ import print_function
  import tensorflow
  from tensorflow_model_optimization.python.core.sparsity.keras import pruning_schedule
  from tensorflow_model_optimization.python.core.sparsity.keras import pruning_wrapper
label_desc: Use image node_id 7 for calling the PruningWrapperTest obj's underlying member method code with example usage: obj.testPruneModel() without return types