code: def testPruneModelRecursively(self):
      internal_model = keras.Sequential(
          [keras.layers.Dense(10, input_shape=(10,))]
      )
      original_model = keras.Sequential(
          [
              internal_model,
              layers.Dense(10),
          ]
      )
      pruned_model = prune.prune_low_magnitude(
          original_model, **self.params
      )
      self.assertEqual(self._count_pruned_layers(pruned_model), 2)
  
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 21 for calling the PruneTest obj's underlying member method code with example usage: obj.testPruneModelRecursively() without return types