code: def test_missing_feature(self, is_sparse):
      strategy = self._get_strategy()
      with strategy.scope():
          optimizer = tpu_embedding_v2_utils.SGD(learning_rate=0.1)
          mid_level_api = tpu_embedding_v2.TPUEmbedding(
              feature_config=tpu_embedding_v2_utils.FeatureConfig(
                  table=self.table_video, name="watched"
              ),
              optimizer=optimizer,
          )
      # Create sparse or ragged feature with last sample missing.
      if is_sparse:
          features = sparse_tensor.SparseTensor(
              indices=self.feature_watched_indices[:-1],
              values=self.feature_watched_values[:-1],
              dense_shape=[self.data_batch_size, 2],
          )
      else:
          features = ragged_tensor.RaggedTensor.from_row_lengths(
              row_lengths=[1, 2, 2, 0],
              values=self.feature_watched_values[:-1],
          )
  
      dataset = dataset_ops.DatasetV2.from_tensors(features)
  
      dataset = (
          dataset.unbatch()
          .repeat()
          .batch(
              self.batch_size * strategy.num_replicas_in_sync,
              drop_remainder=True,
          )
      )
      dataset_iter = iter(
          strategy.experimental_distribute_dataset(
              dataset,
              options=distribute_lib.InputOptions(
                  experimental_fetch_to_device=False
              ),
          )
      )
  
      @def_function.function
      def test_fn():
          def get_activations():
              return mid_level_api.dequeue()
  
          mid_level_api.enqueue(next(dataset_iter), training=False)
          return strategy.run(get_activations)
  
      test_fn()
  
imports: from absl.testing import parameterized
  import numpy
  from tensorflow.python.compat import v2_compat
  from tensorflow.python.data.ops import dataset_ops
  from tensorflow.python.distribute import distribute_lib
  from tensorflow.python.eager import def_function
  from tensorflow.python.framework import sparse_tensor
  from tensorflow.python.framework.tensor_shape import TensorShape
  from tensorflow.python.ops import array_ops
  from tensorflow.python.ops import init_ops_v2
  from tensorflow.python.ops.ragged import ragged_tensor
  from tensorflow.python.platform import test
  from tensorflow.python.tpu import tpu_embedding_v2
  from tensorflow.python.tpu import tpu_embedding_v2_utils
  from tensorflow.python.tpu.tests import tpu_embedding_base_test
  from tensorflow.python.util import nest
label_desc: Use image node_id 6 for calling the TPUEmbeddingTest obj's underlying member method code with example usage: obj.test_missing_feature(is_sparse) and returns: strategy, mid_level_api