code: def run_train_episode(agent, env):
      obs_list, action_list, reward_list = [], [], []
      obs = env.reset()
      while True:
          obs_list.append(obs)
          action = agent.sample(obs)
          action_list.append(action)
  
          obs, reward, done, info = env.step(action)
          reward_list.append(reward)
  
          if done:
              break
      return obs_list, action_list, reward_list
  
file_path: PARL/examples/QuickStart/train.py
imports: import os
  import gym
  import numpy
  import parl
  from parl.utils import logger
  from parl.env import CompatWrapper, is_gym_version_ge
  from cartpole_model import CartpoleModel
  from cartpole_agent import CartpoleAgent
  import argparse
label_desc: Use image node_id 1 for calling a global function with example usage: run_train_episode(agent, env) and returns: obs_list,  action_list,  reward_list