class_docstr: TopK sample mean aggregate.
  
  Attributes:
    k_list: topk list used to truncate prediction. E.g., in an retrieval results
      of ['dog', 'cat', 'pig'], k=[2] means only ['dog', 'cat'] is used as the
      prediction. The default is None, which means all outputs in each
      prediction is included. Effectively k=None is same as k=[inf].
    metrics: The metrics to be computed.
    input_type: input encoding type, must be multiclass(-multioutput).
code: def __post_init__(self):
      if self.input_type not in (
          InputType.MULTICLASS_MULTIOUTPUT,
          InputType.MULTICLASS,
      ):
          raise NotImplementedError(
              f'"{str(self.input_type)}" is not supported.'
          )
  
imports: from collections.abc import Sequence
  import dataclasses
  from typing import Any
  import numpy
  from numpy import typing
  from tensorflow_model_analysis.experimental.lazytf import api
  from tensorflow_model_analysis.experimental.metrics.aggregates import _classification
label_desc: Use image node_id 1 for calling the TopKSamplewiseMeanAggFn obj's underlying member method code with example usage: obj.__post_init__() without return types