code: def test_prune_model(self):
      model = keras.Sequential(
          [
              keras.layers.Dense(10, input_shape=(10,)),
              keras.layers.Dense(2),
          ]
      )
      pruned_model = sparsity_tooling.prune_for_benchmark(
          model, target_sparsity=0.8, block_size=(1, 1)
      )
  
      for layer in pruned_model.layers:
          self.assertEqual((1, 1), layer.block_size)
      test_utils.assert_model_sparsity(self, 0.8, pruned_model)
  
file_path: model-optimization/tensorflow_model_optimization/python/core/sparsity/keras/tools/sparsity_tooling_test.py
imports: import tensorflow
  from tensorflow_model_optimization.python.core.sparsity.keras import pruning_wrapper
  from tensorflow_model_optimization.python.core.sparsity.keras import test_utils
  from tensorflow_model_optimization.python.core.sparsity.keras.tools import sparsity_tooling
label_desc: Use image node_id 1 for calling the SparsityToolingTest obj's underlying member method code with example usage: obj.test_prune_model() without return types