code: def test_empty_features_not_equivalent_to_missing(self):
      base_example_1 = text_format.Parse(
          """
          features {
            feature {
              key: "id"
              value { int64_list { value: 1 } }
            }
            feature {
              key: "val"
              value {}
            }
          }
          """,
          tf.train.Example(),
      )
      test_example = text_format.Parse(
          """
          features {
            feature {
              key: "id"
              value { int64_list { value: 1 } }
            }
          }
          """,
          tf.train.Example(),
      )
      with beam.Pipeline(
          runner=beam_runner_util.get_test_runner()
      ) as p:
          baseline_examples = p | "Create Base" >> beam.Create(
              [base_example_1]
          )
          test_examples = p | "Create Test" >> beam.Create(
              [test_example]
          )
          skew_result, _ = _unpack_results(
              (baseline_examples, test_examples)
              | feature_skew_detector.DetectFeatureSkewImpl(
                  ["id"],
                  [],
                  allow_duplicate_identifiers=True,
                  sample_size=10,
              )
          )
          expected_result = [
              text_format.Parse(
                  """
          feature_name: 'val'
          """,
                  feature_skew_results_pb2.FeatureSkew(),
              ),
          ]
          util.assert_that(
              skew_result,
              test_util.make_skew_result_equal_fn(
                  self, expected_result
              ),
          )
  
      runner = p.run()
      runner.wait_until_finish()
  
imports: import traceback
  from absl.testing import absltest
  from absl.testing import parameterized
  import apache_beam
  from apache_beam.testing import util
  import tensorflow
  from tensorflow_data_validation.utils import beam_runner_util
  from tensorflow_data_validation.skew import feature_skew_detector
  from tensorflow_data_validation.skew.protos import feature_skew_results_pb2
  from tensorflow_data_validation.utils import test_util
  from google.protobuf import text_format
label_desc: Use image node_id 11 for calling the FeatureSkewDetectorTest obj's underlying member method code with example usage: obj.test_empty_features_not_equivalent_to_missing() without return types