我正试图使用python中的多处理池同时运行许多计算。每次计算完成后，我都想将结果保存在一个文件中以备将来使用。在下面的代码中，我试图测试这个想法。在windows上，我得到了每次计算不同输出的预期结果。Linux上的相同代码有一个问题，因为它为所有计算输出相同的结果。我不知道如何在Linux上解决这个问题。此外，我很乐意知道如何在每次计算完成时保存数据，而不是等待所有计算完成，然后同时保存所有输出。我曾尝试使用本网站上的示例使用python实现不同类型的并行计算，但在Linux上无法解决这个问题。在过去的两天里，我也在寻找解决方案，但找不到或不明白如何解决这个问题。如有任何帮助，我们将不胜感激。
这是我的代码：
import multiprocessing
from functools import partial
import numpy as np
rng=np.random.default_rng()
import time
def sim(data_in_1, data_in_2, data_in_3, batch_num, run_number):
file_str='run_'+str(run_number)+'.npy'
temp=rng.choice(1000,5);
time.sleep(temp[0]/1000)
for i in range(temp[0]):
a=np.sqrt(temp[1])
return run_number, a, temp
def main():
processes_num=8
batch_num=1;
num_of_calculations=8*2
iterable=range(num_of_calculations);
data_in_1=20;
data_in_2=10;
data_in_3=1;
pool = multiprocessing.Pool(processes=processes_num)
func = partial(sim, data_in_1, data_in_2, data_in_3, batch_num)
results=pool.map(func, iterable)
for r in results:
out1=r
file_str='run_'+str(out1[0])+'.npy'
with open(file_str, 'wb') as f:
np.save(f,out1[1])
np.save(f,out1[2])
print('saved run '+ str(out1[0]))
pool.close()
pool.join()
print('Batch no. '+str(batch_num)+' is finished.')
for run_number in range(num_of_calculations):
file_str='run_'+str(run_number)+'.npy'
with open(file_str, 'rb') as f:
temp=np.load(f)
temp=np.load(f)
print('result of run ' + str(run_number) +' is: ' + str(temp))
if __name__ == "__main__":
main()
窗口输出：
saved run 0
saved run 1
saved run 2
saved run 3
saved run 4
saved run 5
saved run 6
saved run 7
saved run 8
saved run 9
saved run 10
saved run 11
saved run 12
saved run 13
saved run 14
saved run 15
Batch no. 1 is finished.
result of run 0 is: [173 600 438 195 877]
result of run 1 is: [925 710 727 604 759]
result of run 2 is: [883 645 558 875 205]
result of run 3 is: [843 541 597 605 513]
result of run 4 is: [342 439 406 101 192]
result of run 5 is: [472 279 796 99 774]
result of run 6 is: [443 982 49 314 854]
result of run 7 is: [383 45 923 356 156]
result of run 8 is: [344 597 675 615 297]
result of run 9 is: [605 241 523 241 570]
result of run 10 is: [330 457 172 670 130]
result of run 11 is: [ 38 926 902 659 782]
result of run 12 is: [573 150 435 216 765]
result of run 13 is: [178 851 878 155 431]
result of run 14 is: [929 749 730 368 504]
result of run 15 is: [235 310 836 940 701]
Linux上相同代码的输出：
saved run 0
saved run 1
saved run 2
saved run 3
saved run 4
saved run 5
saved run 6
saved run 7
saved run 8
saved run 9
saved run 10
saved run 11
saved run 12
saved run 13
saved run 14
saved run 15
Batch no. 1 is finished.
result of run 0 is: [ 9 218 388 265 856]
result of run 1 is: [ 9 218 388 265 856]
result of run 2 is: [ 9 218 388 265 856]
result of run 3 is: [ 9 218 388 265 856]
result of run 4 is: [ 9 218 388 265 856]
result of run 5 is: [ 9 218 388 265 856]
result of run 6 is: [ 9 218 388 265 856]
result of run 7 is: [ 9 218 388 265 856]
result of run 8 is: [715 532 364 775 437]
result of run 9 is: [715 532 364 775 437]
result of run 10 is: [715 532 364 775 437]
result of run 11 is: [715 532 364 775 437]
result of run 12 is: [715 532 364 775 437]
result of run 13 is: [715 532 364 775 437]
result of run 14 is: [715 532 364 775 437]
result of run 15 is: [715 532 364 775 437]
因此，在Linux中，随机数生成器种子是从父代继承的，但在windows中，每个进程都会更改它。这就是为什么我在Linux上一直得到同样的结果。所以我移动了行：
rng=np.random.default_rng()
从全局到函数内部"；sim"；这就成功了。