class_docstr: Computes NDCG (normalized discounted cumulative gain).
class_docstr_tok: ["Computes","NDCG","(","normalized","discounted","cumulative","gain",")","."]
code: def merge_accumulators(
      self, accumulators: Iterable[_NDCGAccumulator]
  ) -> _NDCGAccumulator:
      accumulators = iter(accumulators)
      result = next(accumulators)
      for accumulator in accumulators:
          result.ndcg = [
              a + b for a, b in zip(result.ndcg, accumulator.ndcg)
          ]
          result.total_weighted_examples += (
              accumulator.total_weighted_examples
          )
      return result
  
imports: from typing import Dict, Iterable, List, Optional, Tuple, Union
  import apache_beam
  import numpy
  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 8 for calling the _NDCGCombiner obj's underlying member method code with example usage: obj.merge_accumulators(accumulators) and returns: result