code: def pre_trained_trpo_cartpole(
      ctxt=None,
      snapshot_dir="data/local/experiment/trpo_gym_tf_cartpole",
      seed=1,
  ):
      """Use pre-trained TRPO and reusume experiment.
  
      Args:
          ctxt (garage.experiment.ExperimentContext): The experiment
              configuration used by Trainer to create the snapshotter.
          snapshot_dir (path): directory to snapshot
          seed (int): Used to seed the random number generator to produce
              determinism.
  
      """
      set_seed(seed)
      with TFTrainer(snapshot_config=ctxt) as trainer:
          trainer.restore(snapshot_dir)
          trainer.resume(n_epochs=30, batch_size=8000)
  
file_path: garage/src/garage/examples/tf/trpo_gym_tf_cartpole_pretrained.py
imports: import tensorflow
  from garage import wrap_experiment
  from garage.envs import GymEnv
  from garage.experiment.deterministic import set_seed
  from garage.np.baselines import LinearFeatureBaseline
  from garage.sampler import RaySampler
  from garage.tf.algos import TRPO
  from garage.tf.policies import CategoricalMLPPolicy
  from garage.trainer import TFTrainer
label_desc: Use image node_id 2 for calling a global function with example usage: pre_trained_trpo_cartpole(ctxt, snapshot_dir, seed) without return types