class_docstr: factor type parameter
      
class_docstr_tok: ["factor","type","parameter"]
code: def step(self, action):
      tmp = copy.deepcopy(self)
      tmp.partition[action[0]] = int(
          tmp.partition[action[0]] / action[2]
      )
      tmp.partition[action[1]] = int(
          tmp.partition[action[1]] * action[2]
      )
  
      return tmp
  
imports: import math
  import random
  import logging
  import copy
  import nni
  from nni.tuner import Tuner
label_desc: Use image node_id 3 for calling the Factor obj's underlying member method code with example usage: obj.step(action) and returns: tmp