code: def step(self, action):
      self.action = action
      self.correct = action == 0
      self._done = random.choice([False, True])
      if self._done:
          self.env.logger.add_scalar("acc", self.correct * 100)
  
imports: import os
  import random
  import sys
  from pathlib import Path
  import pytest
  import torch
  import torch.nn
  from gym import spaces
  from tianshou.policy import PPOPolicy
  from qlib.config import C
  from qlib.log import set_log_with_config
  from qlib.rl.interpreter import StateInterpreter, ActionInterpreter
  from qlib.rl.simulator import Simulator
  from qlib.rl.reward import Reward
  from qlib.rl.trainer import Trainer, TrainingVessel, EarlyStopping, Checkpoint
label_desc: Use image node_id 2 for calling the ZeroSimulator obj's underlying member method code with example usage: obj.step(action) without return types