class_docstr: Uniform integer distribution.
  
  Parameters
  ----------
  lower: int
      Inclusive lower bound of distribution.
  upper: int
      Inclusive upper bound of distribution.
  log: bool, default = False:
      If True, the distribution will be log-uniform.
code: def get_optuna(self):
      import optuna
  
      optuna_version = int(optuna.__version__[0])
  
      if self.log:
          return (
              optuna.distributions.IntDistribution(
                  self.lower, self.upper, log=True
              )
              if optuna_version >= 3
              else optuna.distributions.IntLogUniformDistribution(
                  self.lower, self.upper
              )
          )
      else:
          return (
              optuna.distributions.IntDistribution(
                  self.lower, self.upper
              )
              if optuna_version >= 3
              else optuna.distributions.IntUniformDistribution(
                  self.lower, self.upper
              )
          )
  
imports: from typing import Dict, Optional
  from scipy.stats import loguniform, randint, uniform
  from copy import copy
  import numpy
label_desc: Use image node_id 4 for calling the IntUniformDistribution obj's underlying member method code with example usage: obj.get_optuna() and returns: unknown, unknown