While waiting for our Python wizard to shed light on this, I note that,
from the documentation of PyArray_FROM_OTF
https://urldefense.us/v3/__https://numpy.org/devdocs/user/c-info.how-to-extend.html*converting-an-arbitrary-sequence-object__;Iw!!G_uCfscf7eWS!cPqvd3brsxbc9HOSop19DutpF2hSdn6iPY382KBUd45kJQBA2AyAU5Neifq0WTDf49xH3CybbVSfg7gg6NOaKMOEYdkmd8Y$
,
we have
The object can be any Python object convertible to an ndarray. If the
object is already (a subclass of) the ndarray that satisfies the
requirements then a new reference is returned.
I guess we should call "del" on the ndarray returned by iarray_s after
having called self.set_attr('__array__', array) in this case, but let's
wait for Lisandro to confirm
Il giorno ven 3 mag 2024 alle ore 11:42 Samar Khatiwala <
[email protected]> ha scritto:
> Hi Matt, Thanks so much for the quick reply! Regarding #2, I put some
> debug statement in my code and what I find is that when I use
> createWithArray on my Cython-allocated numpy array, the destructor I set
> for it is no longer called when I delete
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> Hi Matt,
>
> Thanks so much for the quick reply!
>
> Regarding #2, I put some debug statement in my code and what I find is
> that when I use createWithArray on my Cython-allocated numpy array, the
> destructor I set for it is no longer called when I delete the array. (If I
> don’t use createWithArray then the destructor is triggered.) I interpret
> that to suggest that the petsc4py Vec is somehow ’taking over’ management
> of the numpy array. But I don’t understand where that could be
> happening. (I don’t think it has to do with the actual freeing of memory by
> PETSc's VecDestroy.)
>
> createWithArray calls iarray_s which in turn calls PyArray_FROM_OTF.
> Could it be there’s something going on there? The numpy documentation is
> unclear.
>
> Lisandro: do you have any thoughts on this?
>
> Thanks,
>
> Samar
>
> On May 2, 2024, at 11:56 PM, Matthew Knepley <[email protected]> wrote:
>
> On Thu, May 2, 2024 at 12:53 PM Samar Khatiwala <
> [email protected]> wrote:
>
>> This Message Is From an External Sender
>> This message came from outside your organization.
>>
>>
>> Hello,
>>
>> I have a couple of questions about createWithArray in petsc4py:
>>
>> 1) What is the correct usage for creating a standard MPI Vec with it?
>> Something like this seems to work but is it right?:
>>
>> On each rank do:
>> a = np.zeros(localSize)
>> v = PETSc.Vec().createWithArray(a, comm=PETSc.COMM_WORLD)
>>
>> Is that all it takes?
>>
>>
> That looks right to me.
>
>> 2) Who ‘owns’ the underlying memory for a Vec created with the
>> createWithArray method, i.e., who is responsible for managing it and doing
>> garbage collection? In my problem, the numpy array is created in a Cython
>> module where memory is allocated, and a pointer to it is associated with a
>> numpy ndarray via PyArray_SimpleNewFromData and PyArray_SetBaseObject. I
>> have a deallocator method of my own that is called when the numpy array is
>> deleted/goes out of scope/whenever python does garbage collection. All of
>> that works fine. But if I use this array to create a Vec with
>> createWithArray what happens when the Vec is, e.g., destroyed? Will my
>> deallocator be called?
>>
>> No. The PETSc struct will be deallocated, but the storage will not be
> touched.
>
> Thanks,
>
> Matt
>
>> Or does petsc4py know that it doesn’t own the memory and won’t attempt to
>> free it? I can’t quite figure out from the petsc4py code what is going on.
>> And help would be appreciated.
>>
>> Thanks very much.
>>
>> Samar
>>
>>
>>
>
> --
> What most experimenters take for granted before they begin their
> experiments is infinitely more interesting than any results to which their
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