class_docstr: Computes total attributions.
code: def merge_accumulators(
      self, accumulators: Iterable[Dict[str, List[float]]]
  ) -> Dict[str, List[float]]:
      accumulators = iter(accumulators)
      result = next(accumulators)
      for accumulator in accumulators:
          for k, v in accumulator.items():
              if k in result:
                  self._sum(result[k], v)
              else:
                  result[k] = v
      return result
  
imports: import functools
  from typing import Any, Dict, Iterable, List, Optional, Union
  import apache_beam
  import numpy
  from tensorflow_model_analysis import constants
  from tensorflow_model_analysis.metrics import example_count
  from tensorflow_model_analysis.metrics import metric_specs
  from tensorflow_model_analysis.metrics import metric_types
  from tensorflow_model_analysis.metrics import metric_util
  from tensorflow_model_analysis.proto import config_pb2
  from tensorflow_model_analysis.utils import util
label_desc: Use image node_id 5 for calling the _TotalAttributionsCombiner obj's underlying member method code with example usage: obj.merge_accumulators(accumulators) and returns: result