code: def testMHALayerReachesTargetSparsity(self):
      inp = tf.keras.layers.Input(shape=(32, 32), batch_size=100)
      x = tf.keras.layers.MultiHeadAttention(num_heads=2, key_dim=16)(
          query=inp, value=inp
      )
      out = tf.keras.layers.Flatten()(x)
      model = tf.keras.Model(inputs=inp, outputs=out)
      model = prune.prune_low_magnitude(model, **self.params)
      x_train = np.random.uniform(size=(500, 32, 32))
      y_train = np.random.randint(low=0, high=1024, size=(500,))
      model.compile(
          optimizer=tf.keras.optimizers.Adam(learning_rate=1e-4),
          loss=tf.keras.losses.SparseCategoricalCrossentropy(
              from_logits=True
          ),
          metrics=[
              tf.keras.metrics.SparseCategoricalAccuracy(
                  name="accuracy"
              )
          ],
      )
      test_utils.assert_model_sparsity(self, 0.0, model)
      model.fit(
          x_train,
          y_train,
          epochs=1,
          batch_size=100,
          callbacks=[pruning_callbacks.UpdatePruningStep()],
      )
      test_utils.assert_model_sparsity(self, 0.5, model)
      self._check_strip_pruning_matches_original(model, 0.5, x_train)
  
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 24 for calling the PruneIntegrationTest obj's underlying member method code with example usage: obj.testMHALayerReachesTargetSparsity() without return types