How to unseed a random sequence previously seeded in numpy?

I'm trying to generate random numbers within a multiprosses function. My issue is I need to seed the first part of the random generation but not the second part. What I tried is unseed the generator by picking a random Int (np.random.seed(np.random.randint(100000000))), but because I first seeded the generator, I pick the same Int for the rest of the generation.

So I get the same sequence for each process.

0 [0.5488135  0.71518937 0.60276338 0.54488318 0.4236548 ]
0 [0.91989807 0.99511873 0.6750629  0.60976887 0.65852849]
1 [0.5488135  0.71518937 0.60276338 0.54488318 0.4236548 ]
1 [0.91989807 0.99511873 0.6750629  0.60976887 0.65852849]
2 [0.5488135  0.71518937 0.60276338 0.54488318 0.4236548 ]
2 [0.91989807 0.99511873 0.6750629  0.60976887 0.65852849]

Here a MWE

import numpy as np
import multiprocessing
import random


class mp_worker_class():

    def __init__(self,):
        pass

    @classmethod
    def start(self, nb=None, seed=None, nbcore=None):
        lfp_p=np.empty((nbcore,nb))
        pipe_list = []
        for h in range(nbcore):
            recv_end, send_end = multiprocessing.Pipe( )
            p = multiprocessing.Process(target=self.mp_worker , args=(h, nb, seed, send_end ))
            p.start()
            pipe_list.append(recv_end)

        for idx, recv_end in enumerate(pipe_list):
            lfp_p[idx,:]=recv_end.recv()


        return lfp_p

    @classmethod
    def mp_worker(self,h, nb=None, seed=None, send_end=None):
        np.random.seed(seed)
        np.random.seed(0)
        print(h,np.random.rand(5))
        #trying to undo the seed
        np.random.seed(np.random.randint(100000000))
        print(h, np.random.rand(5))
        send_end.send(np.random.rand(5))
        return

if __name__ == '__main__':
    print(mp_worker_class().start(nb=10, seed=1, nbcore=3 ))