code: def step(self):
      return dict(
          episode_reward_mean=self.config.reward_amt * self.iteration,
          episode_len_mean=self.config.reward_amt,
          timesteps_this_iter=self.config.iter_timesteps,
          time_this_iter_s=self.config.iter_time,
          info={},
      )
  
imports: import os
  import pickle
  import time
  import numpy
  from ray.tune import result
  from ray.rllib.algorithms.algorithm import Algorithm, AlgorithmConfig
  from ray.rllib.utils.annotations import override
label_desc: Use image node_id 2 for calling the _ParameterTuningTrainer obj's underlying member method code with example usage: obj.step() and returns: dict