class_docstr: A StatsGenerator which computes statistics using a combiner function.
  
  This class computes statistics using a combiner function. It emits partial
  states processing a batch of examples at a time, merges the partial states,
  and finally computes the statistics from the merged partial state at the end.
  
  This object mirrors a beam.CombineFn except for the add_input interface, which
  is expected to be defined by its sub-classes. Specifically, the generator
  must implement the following four methods:
  
  Initializes an accumulator to store the partial state and returns it.
      create_accumulator()
  
  Incorporates a batch of input examples (represented as an arrow RecordBatch)
  into the current accumulator and returns the updated accumulator.
      add_input(accumulator, input_record_batch)
  
  Merge the partial states in the accumulators and returns the accumulator
  containing the merged state.
      merge_accumulators(accumulators)
  
  Compute statistics from the partial state in the accumulator and
  return the result as a DatasetFeatureStatistics proto.
      extract_output(accumulator)
docstr: Returns result of folding a batch of inputs into accumulator.
  
  Args:
    accumulator: The current accumulator, which may be modified and returned
      for efficiency.
    input_record_batch: An Arrow RecordBatch whose columns are features and
      rows are examples. The columns are of type List<primitive> or Null (If a
      feature's value is None across all the examples in the batch, its
      corresponding column is of Null type).
  
  Returns:
    The accumulator after updating the statistics for the batch of inputs.
docstr_tok: ["Returns","result","of","folding","a","batch","of","inputs","into","accumulator",".","Args",":","accumulator",":","The","current","accumulator",",","which","may","be","modified","and","returned","for","efficiency",".","input_record_batch",":","An","Arrow","RecordBatch","whose","columns","are","features","and","rows","are","examples",".","The","columns","are","of","type","List","<","primitive",">","or","Null","(","If","a","feature","'s","value","is","None","across","all","the","examples","in","the","batch",",","its","corresponding","column","is","of","Null","type",")",".","Returns",":","The","accumulator","after","updating","the","statistics","for","the","batch","of","inputs","."]
code: def add_input(
      self, accumulator: ACCTYPE, input_record_batch: pa.RecordBatch
  ) -> ACCTYPE:
      """Returns result of folding a batch of inputs into accumulator.
  
      Args:
        accumulator: The current accumulator, which may be modified and returned
          for efficiency.
        input_record_batch: An Arrow RecordBatch whose columns are features and
          rows are examples. The columns are of type List<primitive> or Null (If a
          feature's value is None across all the examples in the batch, its
          corresponding column is of Null type).
  
      Returns:
        The accumulator after updating the statistics for the batch of inputs.
      """
      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 3 for calling the CombinerStatsGenerator obj's underlying member method code with example usage: obj.add_input(accumulator, input_record_batch) without return types