class_docstr: Computes total attributions.
code: def extract_output(
      self, accumulator: Dict[str, List[float]]
  ) -> Dict[
      metric_types.AttributionsKey, Dict[str, Union[float, np.ndarray]]
  ]:
      result = {}
      for k, v in accumulator.items():
          result[k] = v[0] if len(v) == 1 else np.array(v)
      return {self._key: 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 6 for calling the _TotalAttributionsCombiner obj's underlying member method code with example usage: obj.extract_output(accumulator) and returns: dict