code: def testMergeAccumulators(self):
      computation = tf_metric_wrapper.tf_metric_computations(
          [tf.keras.metrics.MeanSquaredError(name="mse")],
          desired_batch_size=2,
          example_weighted=True,
      )[0]
  
      example1 = {
          "labels": [0.0],
          "predictions": [0.0],
          "example_weights": [1.0],
      }
      example2 = {
          "labels": [0.0],
          "predictions": [0.5],
          "example_weights": [1.0],
      }
      example3 = {
          "labels": [1.0],
          "predictions": [0.3],
          "example_weights": [1.0],
      }
      example4 = {
          "labels": [1.0],
          "predictions": [0.9],
          "example_weights": [1.0],
      }
      example5 = {
          "labels": [1.0],
          "predictions": [0.5],
          "example_weights": [0.0],
      }
  
      computation.combiner.setup()
      combiner_inputs = []
      for e in (example1, example2, example3, example4, example5):
          combiner_inputs.append(
              metric_util.to_standard_metric_inputs(e)
          )
      acc1 = computation.combiner.create_accumulator()
      acc1 = computation.combiner.add_input(acc1, combiner_inputs[0])
      acc1 = computation.combiner.add_input(acc1, combiner_inputs[1])
      acc1 = computation.combiner.add_input(acc1, combiner_inputs[2])
      acc2 = computation.combiner.create_accumulator()
      acc2 = computation.combiner.add_input(acc2, combiner_inputs[3])
      acc2 = computation.combiner.add_input(acc2, combiner_inputs[4])
      acc = computation.combiner.merge_accumulators([acc1, acc2])
  
      got_metrics = computation.combiner.extract_output(acc)
      mse_key = metric_types.MetricKey(
          name="mse", example_weighted=True
      )
      self.assertDictElementsAlmostEqual(got_metrics, {mse_key: 0.1875})
  
imports: from absl.testing import parameterized
  import apache_beam
  from apache_beam.testing import util
  import numpy
  import tensorflow
  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 tf_metric_wrapper
  from tensorflow_model_analysis.proto import config_pb2
label_desc: Use image node_id 12 for calling the NonConfusionMatrixMetricsTest obj's underlying member method code with example usage: obj.testMergeAccumulators() without return types