class_docstr: Uniform randomly sampled hyperparameter object.
class_docstr_tok: ["Uniform","randomly","sampled","hyperparameter","object","."]
docstr: Return a list of all the valid values of the Parameter. If ``self.step_size`` is not defined, return 100 points
  between min/max values.
  
  :return: list of dicts {name: float}
docstr_tok: ["Return","a","list","of","all","the","valid","values","of","the","Parameter",".","If","``","self.step_size","``","is","not","defined",",","return","100","points","between","min\/max","values",".",":","return",":","list","of","dicts","{","name",":","float","}"]
code: def to_list(self):
      # type: () -> Sequence[Mapping[str, float]]
      """
      Return a list of all the valid values of the Parameter. If ``self.step_size`` is not defined, return 100 points
      between min/max values.
  
      :return: list of dicts {name: float}
      """
      step_size = (
          self.step_size or (self.max_value - self.min_value) / 100.0
      )
      steps = (self.max_value - self.min_value) / step_size
      values = [
          self.min_value + v * step_size for v in range(0, int(steps))
      ]
      if self.include_max and (
          not values or values[-1] < self.max_value
      ):
          values.append(self.max_value)
      return [{self.name: v} for v in values]
  
imports: import sys
  from itertools import product
  from random import Random
  from typing import Mapping, Any, Sequence, Optional, Union
label_desc: Use image node_id 3 for calling the UniformParameterRange obj's underlying member method code with example usage: obj.to_list() and returns: unknown