class_docstr: Computes binary confusion matrix.
docstr: Merges accumulators.
  
  Args:
    accumulators: Accumulators to be merged
  
  Returns:
    The merged accumulator.
code: def merge_accumulators(
      self,
      accumulators: Iterable[MatrixAccumulator],
  ) -> MatrixAccumulator:
      """Merges accumulators.
  
      Args:
        accumulators: Accumulators to be merged
  
      Returns:
        The merged accumulator.
      """
      accumulators = iter(accumulators)
      result = next(accumulators)
  
      for accumulator in accumulators:
          for threshold in self._thresholds:
              # We need to check if threshold is in the accumulator because the
              # accumulator can be empty (i.e. no input was been added).
              if threshold in accumulator:
                  result[threshold] = self._merge_entry(
                      accumulator=result,
                      threshold=threshold,
                      entry=accumulator[threshold],
                  )
  
      return result
  
file_path: model-analysis/tensorflow_model_analysis/contrib/aggregates/binary_confusion_matrices.py
imports: from typing import Dict, Iterable, List, NamedTuple, Optional, Sequence
  from tensorflow_model_analysis.experimental.lazytf import api
label_desc: Use image node_id 7 for calling the BinaryConfusionMatrices obj's underlying member method code with example usage: obj.merge_accumulators(accumulators) and returns: result