python - 即使在 gc.collect() 之后，分配给 Python 的内存也不会在 Linux 中释放回来

Question

我在 Python 中编写的代码没有按应有的方式释放内存。内存由 Python 占用，但即使不再使用也不会释放。即使你用 ctrl+c 中断正在运行的程序。删除变量并运行 gc.collect() 它似乎没有收集。或者与 Ipython 中相同并运行 %reset。内存不会被释放并且运行 gc.collect() 没有效果。我在 Windows 中对此进行了测试，因为我想看看它是否可能与垃圾收集器库一起使用。看来是这样的。在 Linux 中运行下面的代码，然后也在 Windows 中运行。然后比较内存占用。您将需要安装 numpy 和 scipy。非常感谢对此问题的任何帮助或见解。

导入模型，创建实例，然后运行 ​​createSpecific()。

这是在 Ubuntu 10.04 中展示此行为的代码:

from numpy import array, maximum,intersect1d, meshgrid, std, log, log10, zeros, ones, argwhere, abs, arange, size, copy, sqrt, sin, cos, pi, vstack, hstack, zeros, exp, max, mean, savetxt, loadtxt,  minimum,  linspace,  where
from numpy.fft import fft
from scipy.stats import f_oneway, kruskal, sem, scoreatpercentile
#import matplotlib
#matplotlib.use('cairo.pdf')
from matplotlib.pyplot import plot, clf, show, cla, xlim, xscale, imshow, ylabel, xlabel, figure, savefig, close,  bar,  title,  xticks, yticks, axes, axis
from matplotlib.axes import Axes
from mpl_toolkits.mplot3d import Axes3D
#from enthought.mayavi import mlab
from matplotlib import cm
import matplotlib.pyplot as plt
import os
from time import clock
from timeit import Timer
class Model:

#Constructors and default includes
    def __init__(self, prevAud = None,  debug=False):

        if (prevAud == None):
            self.fs=16000. #sample rate
            self.lowFreq=60. 
            self.hiFreq=5000.     
            self.numFilt=300 #number of channel
            self.EarQ = 9.26449   #9.26449
            self.minBW = 24.7     #24.7
            self.integrationWindow=.01
            self.sliceAt=.035
            self.maxOverallInhibit = 0.1
            self.winLen = int(self.fs*self.integrationWindow+.01) #default integration window 10 ms
            self.fullWind = 0.300
            self.outShortWindow = None
            self.siderArray = None
            self.maxNormalizeValue = .284     # Optimized at .284
            self.outputSemiModel = None
            self.semitones = 11
            self.activationTrace = None
        return




    def setErbScale(self, erbScale = None):
        if (erbScale ==None):
            self.erbScale = arange(100,500,5)
        else:
            self.erbScale = erbScale        

    def trainModel(self,soundVec=None, fs=None, lowfreq=None, highfreq=None, numfilt=None, figto=0, savefig = 'N', prompts=False, plotter=False):
        self.setErbScale()
        templateArray = self.intWindow(self.halfWaveRec(self.creGammatone(soundVec))) 
        for i in xrange(templateArray[0].size):        
            self.outerTest(self.innerTest(templateArray[:,i]))

        return templateArray   


    def createSpecific(self, freqArray = None, semitones = 11, timeforHarm = .3, soundVec=None, fs=None, lowfreq=None, highfreq=None, numfilt=None, figto=0, saveData='N', fileDir='TempRunT/', prompts=False, plotter=False):
        if (freqArray == None):
            self.setErbScale()
            freqArray = self.erbScale
        if (type(semitones) == int):
            semitones = arange(semitones+1)
        totalRuns = int(timeforHarm/self.integrationWindow+.001)
        inhibitWindowArray = zeros((freqArray.size,(semitones.size),self.numFilt,totalRuns))
        for x in xrange(freqArray.size):
            tempHarm = self.makeHarmonicAmpMod(freqArray[x],timeforHarm, numHarm=7,modulation=10)
            for y in semitones:
                tempChord = self.makeSemiChordAmpMod(tempHarm, freqArray[x],timeforHarm,modulation=10,numHarm=7,semi=y)
                inhibitWindowArray[x,y] = self.trainModel( tempChord, savefig = 'N', plotter=plotter)


        self.inhibitWindowArray = inhibitWindowArray

    def creGammatone(self, soundVec):

        temp = zeros((300,soundVec.size))
        for i in xrange(temp[:,0].size):
            temp[i] = -1**i*soundVec
        return temp

    def halfWaveRec(self, halfWaveFilts):

        filtShape = halfWaveFilts.shape
        if (filtShape[1] != int(self.fs*self.fullWind)):
            halfWaveFilts = hstack((halfWaveFilts,zeros((self.numFilt,int(self.fs*self.fullWind)-filtShape[1]))))
        temp = zeros((halfWaveFilts[:,0].size,halfWaveFilts[0].size))
        halfWaveFilts = maximum(halfWaveFilts,temp)

        del temp                
        return halfWaveFilts

    def intWindow(self, integratedFilts):
        winlen = self.winLen

        length = integratedFilts[0].size/winlen
        mod = integratedFilts[0].size%winlen
        outShortWindow = zeros((integratedFilts[:,0].size,length))
        meanval = 0

        if (mod != 0):
            for i in xrange(integratedFilts[:,0].size):
                mean(integratedFilts[i,0:-mod].reshape(length,winlen),1,out=outShortWindow[i])
        else:
            for i in xrange(integratedFilts[:,0].size):
                mean(integratedFilts[i].reshape(length,winlen),1,out=outShortWindow[i])
        del integratedFilts
        return outShortWindow    

    def innerTest(self, window):
        temper = copy(window)
        sider = 7
        st = .04
        sizer = temper.size
        inhibVal = 0
        for j in xrange(sider):
            inhibVal = (temper[0:j+sider+1].sum())*(sider*2+1)/(sider+1+j)
            window[j] += - st*(inhibVal)
        for j in xrange(sider,sizer - sider):
            inhibVal = temper[j-sider:j+sider+1].sum()
            window[j] += - st*(inhibVal)
        for j in xrange(sizer-sider, sizer):
            inhibVal = (temper[j-sider:sizer].sum())*(sider*2+1)/(sider+sizer-j)
            window[j] += - st*(inhibVal)

        maxsub = max(window) * self.maxOverallInhibit
        window += - maxsub    
        del temper
        return window

    def outerTest(self, window):
        newSatValue = scoreatpercentile(window, (76))
        numones = where(window > newSatValue)
        window[numones]=1
        self.maxSatValue = newSatValue
        del numones
        return window

    def makeHarmonicAmpMod(self, freq = 100, time = 1.,modulation=10, fsamp=None, numHarm=7):
        if fsamp == None: fsamp = self.fs
        samples = arange(time*fsamp)
        signal = 0
        for x in xrange(1,(numHarm+1),1):
            signal = signal + sin(samples/float(fsamp)*x*freq*2*pi)
        signal = (signal)*maximum(zeros(time*fsamp),sin((samples/float(fsamp)*modulation*2*pi)))
        return signal

    def makeSemiChordAmpMod(self, harmVec = None, freq=100, time = 1.,  modulation=10, fsamp=None, numHarm=7, semi = 2):
        if (harmVec == None): harmVec = self.makeHarmonicAmpMod(freq,time,modulation,fsamp,numHarm)
        if (semi == 0): return harmVec
        return harmVec + self.makeHarmonicAmpMod(freq*(2**(semi/12.)),time,modulation,fsamp,numHarm)

Answer 1

虚拟内存不是稀缺资源。没有必要将它返回给系统，因为每个进程都有自己的地址空间。你的实际问题是什么？这种行为给您带来了什么问题？