text: """This script is a test that fails when MAML-VPG performance is too low."""
  import torch
  
  from garage.envs import HalfCheetahDirEnv, normalize
  from garage.envs.base import GarageEnv
  from garage.experiment import deterministic, LocalRunner
  from garage.np.baselines import LinearFeatureBaseline
  from garage.torch.algos import MAMLVPG
  from garage.torch.policies import GaussianMLPPolicy
  from tests.fixtures import snapshot_config
  
  
  class TestMAMLVPG:
      """Test class for MAML-VPG."""
  
      def setup_method(self):
          """Setup method which is called before every test."""
          self.env = GarageEnv(
              normalize(HalfCheetahDirEnv(), expected_action_scale=10.))
          self.policy = GaussianMLPPolicy(
              env_spec=self.env.spec,
              hidden_sizes=(64, 64),
              hidden_nonlinearity=torch.tanh,
              output_nonlinearity=None,
          )
          self.baseline = LinearFeatureBaseline(env_spec=self.env.spec)
  
      def teardown_method(self):
          """Teardown method which is called after every test."""
          self.env.close()
  
      def test_ppo_pendulum(self):
          """Test PPO with Pendulum environment."""
          deterministic.set_seed(0)
  
          rollouts_per_task = 5
          max_path_length = 100
  
          runner = LocalRunner(snapshot_config)
          algo = MAMLVPG(env=self.env,
                         policy=self.policy,
                         baseline=self.baseline,
                         max_path_length=max_path_length,
                         meta_batch_size=5,
                         discount=0.99,
                         gae_lambda=1.,
                         inner_lr=0.1,
                         num_grad_updates=1)
  
          runner.setup(algo, self.env)
          last_avg_ret = runner.train(n_epochs=10,
                                      batch_size=rollouts_per_task *
                                      max_path_length)
  
          assert last_avg_ret > -5
  