This was pretty hairy to debug, but I tracked it down:
In [14]: np.dtype(np.uintp)
Out[14]: dtype('uint32')
In [15]: np.dtype(np.uintp) == np.dtype(np.uint32)
Out[15]: True
In [17]: hash(np.dtype(np.uintp))
Out[17]: 1198097502
In [18]: hash(np.dtype(np.uint32))
Out[18]: -98813048
I encountered the problem when using gpuarray.arange which causes one
argument to be set to uintp in the following line elementwise.py:144:
arguments.append(ScalarArg(np.uintp, "n"))
Can anyone test if this replicates with his numpy (mine is 1.6.1)?
Thomas
On Fri, Dec 30, 2011 at 9:36 PM, Andreas Kloeckner
<li...@informa.tiker.net> wrote:
> On Fri, 30 Dec 2011 20:03:44 +0100, Thomas Wiecki <thomas_wie...@brown.edu>
> wrote:
>> Hi Andreas,
>>
>> glad to see that you followed up on this issue. I will try to boil it
>> down but noticed that when I was investigating the issue back then I
>> could not easily reproduce the problem. For some reason the dict
>> stored dtype was hashing to something else. Can you easily point me to
>> the place where the dict is created?
>
> Sure.
>
> - Initial fill in pycuda.compyte.dtype._fill_dtype_registry().
> - Vector types added in pycuda.gpuarray._create_vector_types().
>
> Andreas
>
> PS: Please make sure to keep the list cc'd.
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