code: def sample_transitions(self, batch_size, batch_info, discount_factor=None) -> Transitions:
          
          indexes = self.backend.sample_batch_transitions(batch_size)
          transition_tensors = self.backend.get_transitions(indexes)
  
          return Trajectories(
              num_steps=batch_size,
              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={}
          ).to_transitions()
docs: Sample batch of transitions and return them