class_docstr: Contains parameters to tune.
code: def __post_init__(self):
      if not any(dataclasses.asdict(self).values()):
          raise ValueError(
              "ParametersToTune must have at least 1 parameter "
              "to tune."
          )
  
imports: import logging
  import math
  from numbers import Number
  import pipeline_dp
  from pipeline_dp import dp_computations
  from pipeline_dp import pipeline_backend
  from pipeline_dp import input_validators
  from pipeline_dp.dataset_histograms import histograms
  import analysis
  from analysis import metrics
  from analysis import utility_analysis
  from analysis import dp_strategy_selector
  import dataclasses
  from dataclasses import dataclass
  from typing import Callable, List, Optional, Tuple, Union, Sequence
  from enum import Enum
  import numpy
label_desc: Use image node_id 1 for calling the ParametersToTune obj's underlying member method code with example usage: obj.__post_init__() without return types