Further isolated the error and it seems to come in from the sum function in
numpy. I will probe further later but the code below causes the memory usage to
go up and up. If you change sum below to some other function there are no
issues.
from numpy import arange, sum
for x in range(10000000):
inhibVal = sum(arange(15))
Cheers,
Jeff
Message: 3
Date: Sun, 22 May 2011 09:32:10 -0500
From: Bruce Southey<[email protected]>
Subject: Re: [Numpy-discussion] Python memory management issues using
Linux. Maybe Numpy, related.
To: Discussion of Numerical Python<[email protected]>
Message-ID:<[email protected]>
Content-Type: text/plain; charset=ISO-8859-1
On Sun, May 22, 2011 at 8:42 AM, Ralf Gommers
<[email protected]> wrote:
>
>
> On Sun, May 22, 2011 at 2:54 PM, Jeffrey Spencer<[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
>
> _______________________________________________
> NumPy-Discussion mailing list
> [email protected]
> http://mail.scipy.org/mailman/listinfo/numpy-discussion
>
A good OS is likely to keep Python module in memory just because it
knows that it might be requested again. However, from the little I
know (too much LWN), if Linux needs that memory it will reclaim that
memory only when it needs it or part of some other process.
Measuring memory usage using simple tools (like ps or top) are very
far from sufficient, so exactly how do you know that the memory has
not been released?
Bruce
--
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[email protected]
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