Hi István, István Lorentz <isti_...@yahoo.com> writes: > [snip] > Note, when working with pure numpy arrays, the results is always in a > new copy. I'm using the regular __div__ operator, not the __idiv__ > which I understand should be in-place modifier. I noticed similar > optimization for the neutral elements in pyopencl array __add__, > __sub__ operators. One might ask why am I dividing with '1' in the > first place, but actually the '1' comes as a result of a previous > calculation.
That's an excellent point, thanks for bringing this to my attention. This should now be fixed in git, in both PyOpenCL and PyCUDA. Andreas
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