code: def testMeanName(self):
      feature_key_path = ["features", "age"]
      name = "name_to_verify_123_!@#"
      expected_mean = 38.5
      mean_metric_key = metric_types.MetricKey(name=name)
      mean_metric_computation = stats.Mean(
          feature_key_path, name=name
      ).computations()[0]
  
      with beam.Pipeline() as pipeline:
          result = _compute_mean_metric(
              pipeline, mean_metric_computation
          )
  
          def check_result(got):
              try:
                  got_metrics = self._check_got(
                      got, mean_metric_computation
                  )
                  self.assertDictElementsAlmostEqual(
                      got_metrics, {mean_metric_key: expected_mean}
                  )
  
              except AssertionError as err:
                  raise util.BeamAssertException(err)
  
          util.assert_that(result, check_result, label="result")
  
imports: from absl.testing import parameterized
  import apache_beam
  from apache_beam.testing import util
  import numpy
  import tensorflow
  import tensorflow_model_analysis
  from tensorflow_model_analysis.eval_saved_model import testutil
  from tensorflow_model_analysis.metrics import metric_types
  from tensorflow_model_analysis.metrics import metric_util
  from tensorflow_model_analysis.metrics import stats
  from google.protobuf import text_format
label_desc: Use image node_id 4 for calling the MeanTestValidExamples obj's underlying member method code with example usage: obj.testMeanName() without return types