class_docstr: Generates feature level statistics for natural language stats.
  
  A combiner that uses a pluggable NL classifier to generate natural language
  stats for input examples. After the statistics are combined it classifies
  as NL iff both the stats represent enough values (self._values_threshold)
  and the match ratio is high enough (self._match_ratio).
docstr: Return a fresh, empty accumulator.
  
  Returns:
    An empty accumulator.
docstr_tok: ["Return","a","fresh",",","empty","accumulator",".","Returns",":","An","empty","accumulator","."]
code: def create_accumulator(self) -> _PartialNLStats:
      """Return a fresh, empty accumulator.
  
      Returns:
        An empty accumulator.
      """
      return _PartialNLStats()
  
imports: from __future__ import absolute_import
  from __future__ import division
  from __future__ import print_function
  import abc
  from typing import Optional
  import numpy
  import pyarrow
  import six
  from tensorflow_data_validation import types
  from tensorflow_data_validation.statistics.generators import stats_generator
  from tensorflow_data_validation.utils import stats_util
  from tfx_bsl.arrow import array_util
  from typing import Iterable, Text
  from tensorflow_metadata.proto.v0 import statistics_pb2
label_desc: Use image node_id 2 for calling the NLDomainInferringStatsGenerator obj's underlying member method code with example usage: obj.create_accumulator() and returns: _PartialNLStats