code: def testStripPruningSequentialModel(self):
      model = keras.Sequential(
          [
              layers.Dense(10),
              layers.Dense(10),
          ]
      )
  
      pruned_model = prune.prune_low_magnitude(model, **self.params)
      stripped_model = prune.strip_pruning(pruned_model)
      self.assertEqual(self._count_pruned_layers(stripped_model), 0)
      self.assertEqual(model.get_config(), stripped_model.get_config())
  
imports: import json
  import tempfile
  import numpy
  import tensorflow
  from tensorflow_model_optimization.python.core.keras import test_utils
  from tensorflow_model_optimization.python.core.sparsity.keras import prunable_layer
  from tensorflow_model_optimization.python.core.sparsity.keras import prune
  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 24 for calling the PruneTest obj's underlying member method code with example usage: obj.testStripPruningSequentialModel() without return types