text: import argparse
  import pprint
  from ray import tune
  import ray
  from ray.rllib.agents.a3c.a2c import (
      A2C_DEFAULT_CONFIG as DEFAULT_CONFIG,
      A2CTrainer)
  
  
  if __name__ == "__main__":
      trainer = A2CTrainer
      parser = argparse.ArgumentParser()
      parser.add_argument('--env',
                          help='Gym env name.')
      args = parser.parse_args()
      config = DEFAULT_CONFIG.copy()
      config_update = {
                   "env": args.env,
                   "num_gpus": 1,
                   "num_workers": 50,
                   "evaluation_num_workers": 10,
                   "evaluation_interval": 1,
                   "use_gae": True
              }
      config.update(config_update)
      pp = pprint.PrettyPrinter(indent=4)
      pp.pprint(config)
      ray.init()
      tune.run(trainer,
               stop={"timesteps_total": 2000000},
               config=config
               )
  