On Thursday, October 1, 2015 at 1:57:33 AM UTC-5, Jori Mäntysalo wrote:
>
> On Wed, 30 Sep 2015, Travis Scrimshaw wrote:
>
> > Actually, it's not surprising that your seeing an increase in memory
> usage.
> > Note P7 is a list with strong references to each of the posets, so they
> > cannot be garbage collected. Since the results of meet_matrix are
> cached,
> > you increase your memory usage.
>
> I am not sure if I understood. Why is meet_matrix re-calculated or
> re-copied in memory?
>
>
It's not. By having a *list* of all of the posets, you are not allowing the
*posets* to be garbage collected, and hence, the (cached) meet matrix
associated to each of them.
> Compare that with this:
> >
> > sage: P7 = Posets(7)
> > . . .
> > sage: for P in P7:
> > . . .
> > ....: gc.collect()
> >
> > The call to the garbage collector is not necessary, but you see that the
> > memory usage is bounded.
>
> Without gc.collect() it still eats memory. Of course it might trigger
> garbage collection when memory usage is big enought.
>
Notice that P7 is not a list, but a class with an iterator.
>
> But in any case, there is no way to run some codes that iterate over all
> posets of size n when n is too big. This is because there is no way to ask
> UniqueRepresentation to release memory. Or --- will gc.collect() do this
> also?
>
> It does release memory when there are no *strong* references back to the
object. A strong reference is would be something like P = Poset({}) or L =
[Poset({})], a top-level variable that points to the object in some
capacity (like being an element in a list).
Simon,
Do you know off-hand if is it safe to dynamically add in a class to the
MRO of a subclass of UniqueRepresentation?
Best,
Travis
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