code: def test_telemetry(self):
      shared_example = tf.train.Example()
      shared_example.features.feature[
          _IDENTIFIER1
      ].int64_list.value.append(1)
  
      base_example = tf.train.Example()
      base_example.CopyFrom(shared_example)
      test_example = tf.train.Example()
      test_example.CopyFrom(base_example)
  
      # Add Identifier 2 to base example only.
      base_example.features.feature[
          _IDENTIFIER2
      ].int64_list.value.append(2)
  
      p = beam.Pipeline(runner=beam_runner_util.get_test_runner())
      baseline_data = p | "Create Base" >> beam.Create([base_example])
      test_data = p | "Create Test" >> beam.Create([test_example])
      _ = (
          baseline_data,
          test_data,
      ) | feature_skew_detector.DetectFeatureSkewImpl(
          [_IDENTIFIER1, _IDENTIFIER2]
      )
      runner = p.run()
      runner.wait_until_finish()
      result_metrics = runner.metrics()
  
      # Test example does not have Identifier 2.
      actual_counter = result_metrics.query(
          beam.metrics.metric.MetricsFilter().with_name(
              "examples_with_missing_identifier_features"
          )
      )["counters"]
      self.assertLen(actual_counter, 1)
      self.assertEqual(actual_counter[0].committed, 1)
  
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 12 for calling the FeatureSkewDetectorTest obj's underlying member method code with example usage: obj.test_telemetry() without return types