导入Numpy后初始化Python多进程Manager触发EOFError问题求助

之前运行Python多进程代码一切正常，仅添加了一行未实际调用的import numpy as np语句后，执行manager = mp.Manager()时就触发了EOFError。我了解Numpy和多进程存在一些历史问题，但从未遇到过这种仅导入就直接报错的情况，希望有人能解释原因。

相关代码如下：

import multiprocessing as mp
import time

import numpy as np
fn = 'test_out.json'

def worker(arg, q):
    '''stupidly simulates long running process'''
    start = time.perf_counter()
    s = 'this is a test'
    txt = s
    for i in range(200000):
        txt += s 
    done = time.perf_counter() - start
    with open(fn, 'rb') as f:
        size = len(f.read())
    res = 'Process' + str(arg), str(size), done
    q.put(res)
    return res

def listener(q):
    '''listens for messages on the q, writes to file. '''

    with open(fn, 'w') as f:
        while 1:
            m = q.get()
            if m == 'kill':
                f.write('killed')
                break
            f.write(str(m) + '\n')
            f.flush()

def main():
    #must use Manager queue here, or will not work
    manager = mp.Manager()
    q = manager.Queue()    
    pool = mp.Pool(mp.cpu_count() + 2)

    #put listener to work first
    watcher = pool.apply_async(listener, (q,))

    #fire off workers
    jobs = []
    for i in range(80):
        job = pool.apply_async(worker, (i, q))
        jobs.append(job)

    # collect results from the workers through the pool result queue
    for job in jobs: 
        job.get()

    #now we are done, kill the listener
    q.put('kill')
    pool.close()
    pool.join()

if __name__ == "__main__":
   main()

我原本以为添加未使用的Numpy导入不会影响代码运行结果。

内容的提问来源于stack exchange，提问作者JamesVR