code: def testPrunesZeroSparsity_IsNoOp(self):
      model = keras_test_utils.build_simple_dense_model()
  
      model2 = keras_test_utils.build_simple_dense_model()
      model2.set_weights(model.get_weights())
  
      params = self.params
      params["pruning_schedule"] = pruning_schedule.ConstantSparsity(
          target_sparsity=0, begin_step=0, frequency=1
      )
      pruned_model = prune.prune_low_magnitude(model2, **params)
  
      x_train = (np.random.rand(20, 10),)
      y_train = keras.utils.to_categorical(
          np.random.randint(5, size=(20, 1)), 5
      )
  
      self._train_model(
          model, epochs=1, x_train=x_train, y_train=y_train
      )
      self._train_model(
          pruned_model, epochs=1, x_train=x_train, y_train=y_train
      )
  
      self._assert_weights_different_objects(model, pruned_model)
      self._assert_weights_same_values(model, pruned_model)
  
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 8 for calling the PruneIntegrationTest obj's underlying member method code with example usage: obj.testPrunesZeroSparsity_IsNoOp() without return types