class_docstr: Uniform float distribution.
  
  Parameters
  ----------
  lower: float
      Inclusive lower bound of distribution.
  upper: float
      Inclusive upper bound of distribution.
  log: bool, default = False:
      If True, the distribution will be log-uniform.
code: def get_hyperopt(self, label):
      from hyperopt import hp
  
      if self.log:
          return hp.loguniform(
              label, np.log(self.lower), np.log(self.upper)
          )
      else:
          return hp.uniform(label, 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 5 for calling the UniformDistribution obj's underlying member method code with example usage: obj.get_hyperopt(label) and returns: hp, hp