在Linux中，gc.collect()后Python分配的内存仍未释放
我在Python中写了一段代码，但它的内存释放不太正常。Python占用了内存，但即使不再使用，这部分内存也不会被释放。即使你用ctrl+c强制停止程序，删除变量后再运行gc.collect()，内存似乎也没有被回收。就算在Ipython中运行%reset，内存也不会释放，gc.collect()也没有效果。我在Windows上测试了这个问题，想看看是不是和垃圾回收库有关，结果发现确实是这样。你可以在Linux和Windows上运行下面的代码，然后比较一下内存使用情况。你需要安装numpy和scipy。对此问题的任何帮助或见解都非常感谢。
导入模型，创建一个实例，然后运行createSpecific()。
以下是在Ubuntu 10.04中表现出这种情况的代码：
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)
2 个回答
1
虚拟内存并不是一种稀缺资源。每个程序都有自己的地址空间，所以不需要把它归还给系统。你真正遇到的问题是什么呢？这种情况给你带来了什么困扰？
0
我安装了最新版本的numpy，问题就解决了。我猜这个问题可能出在numpy的某个功能上。不过我没时间去深入研究这个问题。