多处理 pool.map 不从函数调用返回

Question

我有一个简短的 sn-p 呼叫 pool.map 挂断。它不会在任何合理的时间内返回。这个想法是有几个点列表并找到与另一个点列表对应的度量。

    import numpy as np
    import multiprocessing
    import scipy.spatial as ss

    def dist(args): # returns the sum of distances of the nearest neighbors.
        kdSet, points = args
        dist, _ = kdSet.query(points)
        return np.sum(dist)

    #just define some points to play with
    points = np.array([[13.27, 25.49], [13.18, 25.39], [13.08, 25.39], 
                       [12.99, 25.39], [12.89, 25.39], [12.80, 25.39],
                       [12.71, 25.39], [12.61, 25.30], [12.52, 25.30]]) 
    pointList = [points + idx for idx in range(3)] #creates a list of points

    #create a list of KDTrees for fast lookup. Add some number to make them a little different from pointList
    kdTreeList = [ss.KDTree(pointsLocal + idx/10) for idx, pointsLocal in enumerate(pointList)] 

    #this part works fine: serial execution
    distances = list(map(dist, zip(kdTreeList, pointList)))
    print(distances)

    #this part hangs, if called as multiprocess, expected the same result as above
    with multiprocessing.Pool() as pool:
        print('Calling pool.map')
        distancesMultiprocess = pool.map(dist, zip(kdTreeList, pointList)) #<-This call does not return, but uses the CPU 100%
    print(distancesMultiprocess)

按顺序调用函数可以正常工作。但是如果在 pool.map 函数中调用它既不会给出错误也不会返回任何东西。它只是挂在那里。 CPU 负载达到 100%，所以发生了一些事情。

出于测试目的删除 KDTree 类并没有显示不同的结果。

由于没有抛出错误，我不知道这里出了什么问题。有什么提示吗？

Answer 1

非常感谢 juanpa.arrivillaga 添加

    if __name__ == "__main__":

成功了。