Much reduced code exhibiting the issue. This shouldn't use much memory
but just keeps going up and up because the copied window I assume gets
left around and not taken up by the garbage collector.
On 22/05/11 23:42, Ralf Gommers wrote:
On Sun, May 22, 2011 at 2:54 PM, Jeffrey Spencer
<[email protected] <mailto:[email protected]>> wrote:
Sorry. I attached here the class and script to run it. It is just
a minimalistic example of what I'm really doing that exhibits the
same behavior. All the script does is run at.createSpecific after
instantiating the class. I have seen this exhibited on many other
cases but it runs fine in Windows XP. Here is what the script does:
import MemoryLeak
at = MemoryLeak.Model()
at.createSpecific()
That manages to eat up all my cpu cycles for about 5 minutes, but no
leak (on OS X). I also don't see anything in the code that can
potentially give problems. I suggest you strip this down a lot more so
you can isolate the problem.
If in your original code you were making a lot of figures in one of
those for loops without explicitly closing them, that could perhaps be
a problem. But you removed all I/O and matplotlib related code already
(except for imports and some keywords).
Ralf
from numpy import zeros, ones, max, copy, arange
def innerTest(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)
return window
for x in range(10000):
#inhibitWindowArray[0,0] = train( arange(10000))
innerTest(arange(400))
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