Hi Alex,
On Wed, 8 Feb 2012 19:10:57 -0500, Alex Nitz <alex.n...@ligo.org> wrote:
> I'm new to using pycuda and I've run into the following issue. It seems
> that the definition of __rmul__ in GPUArray asserts that the dtype is
> float32. Is was wondering if there a reason for this? I would like to do
> this operation with other types such as float64.
>
> (line 328 of gpuarray.py)
> def _rdiv_scalar(self, other, out, stream=None):
> """Divides an array by a scalar::
>
> y = n / self
> """
>
> if not self.flags.forc:
> raise RuntimeError("only contiguous arrays may "
> "be used as arguments to this operation")
>
> assert self.dtype == np.float32
>
> func = elementwise.get_rdivide_elwise_kernel(self.dtype)
> func.prepared_async_call(self._grid, self._block, stream,
> self.gpudata, other,
> out.gpudata, self.mem_size)Fixed in git. Thanks for the report. Andreas
pgpwXY1WxJW6o.pgp
Description: PGP signature
_______________________________________________ PyCUDA mailing list PyCUDA@tiker.net http://lists.tiker.net/listinfo/pycuda
