code: def sample_trajectories(self, rollout_length, batch_info) -> Trajectories:
          
          indexes = self.backend.sample_batch_trajectories(rollout_length)
          transition_tensors = self.backend.get_trajectories(indexes, rollout_length)
  
          return Trajectories(
              num_steps=rollout_length,
              num_envs=self.backend.num_envs,
              environment_information=None,
              transition_tensors={k: torch.from_numpy(v) for k, v in transition_tensors.items()},
              rollout_tensors={}
          )
docs: Sample batch of trajectories and return them