code: def tutorial_vpg(ctxt=None):
      """Train VPG with PointEnv environment.
  
      Args:
          ctxt (ExperimentContext): The experiment configuration used by
              :class:`~Trainer` to create the :class:`~Snapshotter`.
  
      """
      set_seed(100)
      trainer = Trainer(ctxt)
      env = PointEnv()
      policy = GaussianMLPPolicy(env.spec)
      sampler = LocalSampler(
          agents=policy,
          envs=env,
          max_episode_length=env.spec.max_episode_length,
      )
      algo = SimpleVPG(env.spec, policy, sampler)
      trainer.setup(algo, env)
      trainer.train(n_epochs=200, batch_size=4000)
  
file_path: garage/src/garage/examples/torch/tutorial_vpg.py
imports: import numpy
  import torch
  from garage import EpisodeBatch, log_performance, wrap_experiment
  from garage.envs import PointEnv
  from garage.experiment.deterministic import set_seed
  from garage.np import discount_cumsum
  from garage.sampler import LocalSampler
  from garage.torch.policies import GaussianMLPPolicy
  from garage.trainer import Trainer
label_desc: Use image node_id 1 for calling a global function with example usage: tutorial_vpg(ctxt) without return types