class_docstr: Computes min label position metric.
code: def merge_accumulators(
      self, accumulators: Iterable[_TJURDiscriminationAccumulator]
  ) -> _TJURDiscriminationAccumulator:
      accumulators = iter(accumulators)
      result = next(accumulators)
      for accumulator in accumulators:
          result.total_negative_weighted_predictions += (
              accumulator.total_negative_weighted_predictions
          )
          result.total_negative_weighted_labels += (
              accumulator.total_negative_weighted_labels
          )
          result.total_positive_weighted_predictions += (
              accumulator.total_positive_weighted_predictions
          )
          result.total_positive_weighted_labels += (
              accumulator.total_positive_weighted_labels
          )
      return result
  
imports: from typing import Any, Dict, Iterable, Optional
  import apache_beam
  from tensorflow_model_analysis.metrics import metric_types
  from tensorflow_model_analysis.metrics import metric_util
  from tensorflow_model_analysis.proto import config_pb2
label_desc: Use image node_id 4 for calling the _TJURDiscriminationCombiner obj's underlying member method code with example usage: obj.merge_accumulators(accumulators) and returns: result