The solution you suggest is irrelevant to the issue mentioned in the article. Even if you use np.random.RandomState, or any other "explicit RNG state", that state will still be copied in the fork() call.
The post just stresses that one should be careful when using random states and multiprocessing, so you should either reseed after forking or using multiprocess/multithread-aware RNG API.
The post just stresses that one should be careful when using random states and multiprocessing, so you should either reseed after forking or using multiprocess/multithread-aware RNG API.