code: def step(self, action):
      slate = [self.candidates[i] for i in action]
      reward = simulate_reward(slate, self._reward_prng)
      obs = self._sample_candidates()
      done = False
      info = {"documents": self.candidates}
      return obs, reward, done, info
  
imports: from collections import namedtuple
  from typing import List, Optional
  import gym
  import numpy
  from gym.utils import seeding
  from gym.wrappers.time_limit import TimeLimit
  from reagent.core.dataclasses import dataclass
  from reagent.gym.envs.env_wrapper import EnvWrapper
  from reagent.gym.envs.recsim import RecsimObsPreprocessor
  from reagent.gym.envs.wrappers.recsim import ValueWrapper
  from scipy.special import expit, logit
label_desc: Use image node_id 4 for calling the ToyVMEnv obj's underlying member method code with example usage: obj.step(action) and returns: obs,  reward,  done,  info