text: import torch
  from copy import deepcopy
  
  from dizoo.classic_control.cartpole.config.cartpole_qrdqn_generation_data_config import main_config, create_config
  from ding.entry import serial_pipeline_offline, collect_demo_data, eval, serial_pipeline
  
  
  def train_cql(args):
      from dizoo.classic_control.cartpole.config.cartpole_cql_config import main_config, create_config
      main_config.exp_name = 'cartpole_cql'
      main_config.policy.collect.data_path = './cartpole/expert_demos.hdf5'
      main_config.policy.collect.data_type = 'hdf5'
      config = deepcopy([main_config, create_config])
      serial_pipeline_offline(config, seed=args.seed)
  
  
  def eval_ckpt(args):
      main_config.exp_name = 'cartpole'
      main_config.policy.learn.learner.load_path = './cartpole/ckpt/ckpt_best.pth.tar'
      main_config.policy.learn.learner.hook.load_ckpt_before_run = './cartpole/ckpt/ckpt_best.pth.tar'
      config = deepcopy([main_config, create_config])
      eval(config, seed=args.seed, load_path=main_config.policy.learn.learner.hook.load_ckpt_before_run)
  
  
  def generate(args):
      main_config.exp_name = 'cartpole'
      main_config.policy.learn.learner.load_path = './cartpole/ckpt/ckpt_best.pth.tar'
      main_config.policy.collect.save_path = './cartpole/expert.pkl'
      main_config.policy.collect.data_type = 'hdf5'
      config = deepcopy([main_config, create_config])
      state_dict = torch.load(main_config.policy.learn.learner.load_path, map_location='cpu')
      collect_demo_data(
          config,
          collect_count=main_config.policy.other.replay_buffer.replay_buffer_size,
          seed=args.seed,
          expert_data_path=main_config.policy.collect.save_path,
          state_dict=state_dict
      )
  
  
  def train_expert(args):
      from dizoo.classic_control.cartpole.config.cartpole_qrdqn_config import main_config, create_config
      main_config.exp_name = 'cartpole'
      config = deepcopy([main_config, create_config])
      serial_pipeline(config, seed=args.seed)
  
  
  if __name__ == "__main__":
      import argparse
  
      parser = argparse.ArgumentParser()
      parser.add_argument('--seed', '-s', type=int, default=10)
      args = parser.parse_args()
  
      train_expert(args)
      eval_ckpt(args)
      generate(args)
      train_cql(args)
  