class_docstr: Generate feature level statistics using combiner function.
  
  This interface is a simplification of CombinerStatsGenerator for the special
  case of statistics that do not require cross-feature computations. It mirrors
  a beam.CombineFn for the values of a specific feature.
docstr: Merges several accumulators to a single accumulator value.
  
  Args:
    accumulators: The accumulators to merge.
  
  Returns:
    The merged accumulator.
docstr_tok: ["Merges","several","accumulators","to","a","single","accumulator","value",".","Args",":","accumulators",":","The","accumulators","to","merge",".","Returns",":","The","merged","accumulator","."]
code: def merge_accumulators(
      self, accumulators: Iterable[ACCTYPE]
  ) -> ACCTYPE:
      """Merges several accumulators to a single accumulator value.
  
      Args:
        accumulators: The accumulators to merge.
  
      Returns:
        The merged accumulator.
      """
      raise NotImplementedError
  
imports: from __future__ import absolute_import
  from __future__ import division
  from __future__ import print_function
  import abc
  from typing import Any, Dict, Generic, Hashable, Iterable, List, Optional, Text, TypeVar
  import apache_beam
  import pyarrow
  from tensorflow_data_validation import types
  from tensorflow_data_validation.statistics.generators import input_batch
  from tensorflow_metadata.proto.v0 import schema_pb2
  from tensorflow_metadata.proto.v0 import statistics_pb2
label_desc: Use image node_id 4 for calling the CombinerFeatureStatsGenerator obj's underlying member method code with example usage: obj.merge_accumulators(accumulators) without return types