code: def testBleuMultipleExamples(self, examples_key, expected_score):
      combined_example = _EXAMPLES[examples_key]
      list_of_examples = []
      # Convert combined_example into a list of multiple examples
      for i, prediction in enumerate(combined_example["predictions"]):
          list_of_examples.append(
              {
                  constants.LABELS_KEY: np.expand_dims(
                      np.array(combined_example["labels"])[:, i], axis=1
                  ),
                  constants.PREDICTIONS_KEY: [prediction],
              }
          )
  
      key = metric_types.MetricKey(name=bleu._BLEU_NAME_DEFAULT)
      computation = bleu.Bleu().computations()[0]
      with beam.Pipeline() as pipeline:
          result = _get_result(
              pipeline, list_of_examples, computation.combiner
          )
  
          def check_result(got):
              try:
                  got_metrics = self._check_got(got, key)
                  self.assertAlmostEqual(
                      expected_score, got_metrics[key].score, places=2
                  )
  
              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 import constants
  from tensorflow_model_analysis.eval_saved_model import testutil
  from tensorflow_model_analysis.evaluators import metrics_plots_and_validations_evaluator
  from tensorflow_model_analysis.metrics import bleu
  from tensorflow_model_analysis.metrics import metric_types
  from tensorflow_model_analysis.metrics import metric_util
  from tensorflow_model_analysis.slicer import slicer_lib
  from google.protobuf import text_format
label_desc: Use image node_id 10 for calling the BleuTest obj's underlying member method code with example usage: obj.testBleuMultipleExamples(examples_key, expected_score) without return types