code: def testPruneWithHighSparsity(self):
      params = self.params
      params["pruning_schedule"] = pruning_schedule.ConstantSparsity(
          target_sparsity=0.99, begin_step=0, frequency=1
      )
  
      model = prune.prune_low_magnitude(
          keras_test_utils.build_simple_dense_model(), **params
      )
      self._train_model(model, epochs=1)
      for layer in model.layers:
          if isinstance(layer, pruning_wrapper.PruneLowMagnitude):
              for weight in layer.layer.get_prunable_weights():
                  self.assertEqual(
                      1,
                      np.count_nonzero(
                          tf.keras.backend.get_value(weight)
                      ),
                  )
  
imports: import tempfile
  from absl.testing import parameterized
  import numpy
  import tensorflow
  from tensorflow_model_optimization.python.core.keras import test_utils
  from tensorflow_model_optimization.python.core.sparsity.keras import prune
  from tensorflow_model_optimization.python.core.sparsity.keras import prune_registry
  from tensorflow_model_optimization.python.core.sparsity.keras import pruning_callbacks
  from tensorflow_model_optimization.python.core.sparsity.keras import pruning_schedule
  from tensorflow_model_optimization.python.core.sparsity.keras import pruning_wrapper
  from tensorflow_model_optimization.python.core.sparsity.keras import test_utils
label_desc: Use image node_id 9 for calling the PruneIntegrationTest obj's underlying member method code with example usage: obj.testPruneWithHighSparsity() without return types