text: from rllab.algos.trpo import TRPO
  from rllab.baselines.linear_feature_baseline import LinearFeatureBaseline
  from rllab.envs.mujoco.swimmer_env import SwimmerEnv
  from rllab.envs.normalized_env import normalize
  from rllab.policies.gaussian_mlp_policy import GaussianMLPPolicy
  
  env = normalize(SwimmerEnv())
  
  policy = GaussianMLPPolicy(
      env_spec=env.spec,
      # The neural network policy should have two hidden layers, each with 32 hidden units.
      hidden_sizes=(32, 32)
  )
  
  baseline = LinearFeatureBaseline(env_spec=env.spec)
  
  algo = TRPO(
      env=env,
      policy=policy,
      baseline=baseline,
      batch_size=4000,
      max_path_length=500,
      n_itr=40,
      discount=0.99,
      step_size=0.01,
  )
  algo.train()
  