code: def test_cpu_sequence_lookup_sparse(self):
      feature_config = (
          tpu_embedding_v2_utils.FeatureConfig(
              table=self.table_user,
              name="friends",
              max_sequence_length=2,
          ),
      )
      optimizer = tpu_embedding_v2_utils.SGD(learning_rate=0.1)
      mid_level = tpu_embedding_for_serving.TPUEmbeddingForServing(
          feature_config=feature_config, optimizer=optimizer
      )
      features = self._get_sparse_tensors()[2:3]
      result = mid_level(features, weights=None)
  
      golden = self._numpy_sequence_lookup(
          mid_level.embedding_tables[self.table_user].numpy(),
          features[0].indices.numpy(),
          features[0].values.numpy(),
          self.data_batch_size,
          feature_config[0].max_sequence_length,
          self.table_user.dim,
      )
  
      self.assertAllClose(result[0], golden)
  
imports: import numpy
  from tensorflow.python.compat import v2_compat
  from tensorflow.python.framework import constant_op
  from tensorflow.python.framework import dtypes
  from tensorflow.python.framework import sparse_tensor
  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_for_serving
  from tensorflow.python.tpu import tpu_embedding_v2_utils
  from tensorflow.python.util import nest
label_desc: Use image node_id 15 for calling the TPUEmbeddingForServingTest obj's underlying member method code with example usage: obj.test_cpu_sequence_lookup_sparse() without return types