class_docstr: Creates histogram from labels, predictions, and example weights.
class_docstr_tok: ["Creates","histogram","from","labels",",","predictions",",","and","example","weights","."]
code: def merge_accumulators(
      self, accumulators: Iterable[_CalibrationHistogramCombinerAcctype]
  ) -> _CalibrationHistogramCombinerAcctype:
      it = iter(accumulators)
      result = next(it)
      for acc in it:
          for bucket_id, bucket in acc.items():
              if bucket_id not in result:
                  new_bucket = Bucket(bucket_id, 0.0, 0.0, 0.0)
                  new_bucket.merge(bucket)
                  result[bucket_id] = new_bucket
              else:
                  result[bucket_id].merge(bucket)
      return result
  
file_path: model-analysis/tensorflow_model_analysis/metrics/calibration_histogram.py
imports: import dataclasses
  import operator
  from typing import Dict, Iterable, List, 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 5 for calling the _CalibrationHistogramCombiner obj's underlying member method code with example usage: obj.merge_accumulators(accumulators) and returns: result