关于deepwalk的随机采样问题

[shexuan]

    def deepwalk_walk(self, walk_length, start_node):

        walk = [start_node]

        while len(walk) < walk_length:
            cur = walk[-1]
            cur_nbrs = list(self.G.neighbors(cur))
            if len(cur_nbrs) > 0:
                walk.append(random.choice(cur_nbrs))
            else:
                break
        return walk

个人觉得上面的函数是否不太妥当，完全没用到，各个结点间的转移概率。各个节点间的转移概率其实是可以统计得到的，是否用上会更好？