code: def testRougeMultipleExampleWeights(self, rouge_type):
      example = {
          constants.LABELS_KEY: "testing one two",
          constants.PREDICTIONS_KEY: "testing",
          constants.EXAMPLE_WEIGHTS_KEY: [0.4, 0.6],
      }
      rouge_computation = rouge.Rouge(rouge_type).computations()[0]
      with self.assertRaises(ValueError):
          with beam.Pipeline() as pipeline:
              _get_result(
                  pipeline=pipeline,
                  examples=[example],
                  combiner=rouge_computation.combiner,
              )
  
imports: import statistics
  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 metric_types
  from tensorflow_model_analysis.metrics import metric_util
  from tensorflow_model_analysis.metrics import rouge
  from tensorflow_model_analysis.slicer import slicer_lib
  from google.protobuf import text_format
  from rouge_score import tokenizers
label_desc: Use image node_id 6 for calling the RogueTest obj's underlying member method code with example usage: obj.testRougeMultipleExampleWeights(rouge_type) without return types