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Solve the following problem using Python, implementing the functions described below, one line at a time
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Description:
 def sample_trajectories(self, rollout_length, batch_info) -> Trajectories: """ Sample batch of trajectories and return them """

        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={}
        )