使用rv_continuous生成随机变量时，如何解决scipy.stats中的内存泄漏?

问题描述

以下最小示例似乎遭受内存泄漏(使用SciPy verison 0.17.0测试)

The following minimal example appears to suffer from memory leak (tested using SciPy verison 0.17.0)

import resource
from scipy.stats import rv_continuous

class Rv(rv_continuous):

    def __init__(self, x):
        rv_continuous.__init__(self, a=0, b=1)
        self.x = x

    def _pdf(self, y):
        return 1


def call_rv(x):
    rv = Rv(x)
    # if the line below is commented out, memory usage stays constant
    s = rv.rvs()

    return 1

for k in range(10000):
    x = call_rv(k)
    if k%1000==0:
        mem = resource.getrusage(resource.RUSAGE_SELF).ru_maxrss
        print 'Memory usage: %s (kb)' % mem

在我的示例中，我不了解是什么导致了泄漏.值得注意的是，当注释掉随机变量生成s = rv.rvs()时，不会发生泄漏.

I don't understand what causes the leak in my example. Notably, when the random variate generation s = rv.rvs() is commented out, the leak doesn't occur.

使用rv_continuous和随机变量生成时如何避免内存泄漏?

How can the memory leak be avoided when using rv_continuous and random variate generation?

推荐答案

这不是内存泄漏，最终将把内存返回给操作系统.

This is not a memory leak, the memory is going to be returned to the OS, eventually.

rv = Rv(x)

在循环中创建一个新实例.请勿这样做，您的内存消耗将得到控制.如果要生成N个变量，请创建一次实例，然后执行.rvs(size=N).

creates a new instance in the loop. Don't do that, and your memory consumption will be in check.If you want to generate N variates, create the instance once and then do .rvs(size=N).

这篇关于使用rv_continuous生成随机变量时，如何解决scipy.stats中的内存泄漏?的文章就介绍到这了，希望我们推荐的答案对大家有所帮助，也希望大家多多支持！