code: def train(env_id, num_timesteps, seed):
      """
      Train PPO1 model for the Mujoco environment, for testing purposes
  
      :param env_id: (str) Environment ID
      :param num_timesteps: (int) The total number of samples
      :param seed: (int) The initial seed for training
      """
      env = make_mujoco_env(env_id, seed)
      model = PPO1(
          MlpPolicy,
          env,
          timesteps_per_actorbatch=2048,
          clip_param=0.2,
          entcoeff=0.0,
          optim_epochs=10,
          optim_stepsize=3e-4,
          optim_batchsize=64,
          gamma=0.99,
          lam=0.95,
          schedule="linear",
      )
      model.learn(total_timesteps=num_timesteps)
      env.close()
  
imports: from stable_baselines.ppo1 import PPO1
  from stable_baselines.common.policies import MlpPolicy
  from stable_baselines.common.cmd_util import make_mujoco_env, mujoco_arg_parser
  from stable_baselines import logger
label_desc: Use image node_id 1 for calling a global function with example usage: train(env_id, num_timesteps, seed) without return types