class_docstr: Wrapper for the three sketches for a single feature.
class_docstr_tok: ["Wrapper","for","the","three","sketches","for","a","single","feature","."]
code: def __init__(self, distinct, topk_unweighted, topk_weighted=None):
      self._distinct = distinct
      self._topk_unweighted = topk_unweighted
      self._topk_weighted = topk_weighted
  
imports: import collections
  from typing import Dict, Iterable, Optional, Text
  import apache_beam
  import numpy
  import pyarrow
  from tensorflow_data_validation import constants
  from tensorflow_data_validation import types
  from tensorflow_data_validation.arrow import arrow_util
  from tensorflow_data_validation.statistics.generators import stats_generator
  from tensorflow_data_validation.utils import schema_util
  from tensorflow_data_validation.utils import stats_util
  from tensorflow_data_validation.utils import top_k_uniques_stats_util
  from tensorflow_data_validation.utils.example_weight_map import ExampleWeightMap
  from tfx_bsl.arrow import array_util
  from tfx_bsl.sketches import KmvSketch
  from tfx_bsl.sketches import MisraGriesSketch
  from tensorflow_metadata.proto.v0 import schema_pb2
  from tensorflow_metadata.proto.v0 import statistics_pb2
label_desc: Use image node_id 1 to create a new _CombinedSketch object from inherited base classes: object with example: obj = _CombinedSketch(distinct, topk_unweighted, topk_weighted)