code: def testPruneFunctionalModelWithLayerReused(self):
      # The model reuses the Dense() layer. Make sure it's only pruned once.
      inp = keras.Input(shape=(10,))
      dense_layer = layers.Dense(10)
      x = dense_layer(inp)
      x = dense_layer(x)
      model = keras.Model(inputs=[inp], outputs=[x])
      pruned_model = prune.prune_low_magnitude(model, **self.params)
      self.assertEqual(self._count_pruned_layers(pruned_model), 1)
  
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 19 for calling the PruneTest obj's underlying member method code with example usage: obj.testPruneFunctionalModelWithLayerReused() without return types