On 9 April 2013 13:09, mark florisson <markflorisso...@gmail.com> wrote:
> > > > On 8 April 2013 13:04, Sebastian Berg <sebast...@sipsolutions.net> wrote: > >> On Mon, 2013-04-08 at 12:31 +0200, Dag Sverre Seljebotn wrote: >> > On 04/08/2013 09:59 AM, Sebastian Berg wrote: >> > > On Mon, 2013-04-08 at 08:42 +0200, Dag Sverre Seljebotn wrote: >> > >> On 04/06/2013 04:19 PM, Nathaniel Smith wrote: >> > >>> Hi all, >> > >>> >> > >>> If you build current numpy master with >> > >>> NPY_RELAXED_STRIDES_CHECKING=1 python setup.py install >> > >>> then Cython code using ndarrays starts blowing up, e.g.: >> > >>> >> > >>> # foo.pyx >> > >>> def add_one(array): >> > >>> cdef double[::1] a = array >> > >>> a[0] += 1. >> > >>> return array >> > >>> >> > >>>>>> foo.add_one(np.ascontiguousarray(np.arange(10.)[::100])) >> > >>> Traceback (most recent call last): >> > >>> File "<stdin>", line 1, in <module> >> > >>> File "foo.pyx", line 2, in foo.add_one (foo.c:1210) >> > >>> cdef double[::1] a = array >> > >>> ValueError: Buffer and memoryview are not contiguous in the same >> dimension. >> > >>> >> > >>> The problem (as discussed before) is that Cython has an >> unnecessarily >> > >>> strict definition of "contiguous", so NPY_RELAXED_STRIDES_CHECKING=1 >> > >>> pretty much breaks all existing compiled Cython modules. >> > >>> >> <snip> >> > >> >> > >> I guess you have changed your implementation of PEP 3118 too >> slightly on >> > >> the NumPy side? Is this undefined in the PEP or are you now not in >> > >> strict adherence to it? >> > >> >> > > >> > > Hi, >> > > >> > > maybe I will have a look at that, but not sure if I will manage. The >> > > PEP 3118 is a point, but it does not seem to cover this (probably we >> > > should try to get a clarification into 3118). I am still wondering >> > > whether for buffers that are requested contiguous numpy should set the >> > > strides again, since it cannot hurt. Would that make a difference for >> > > Cython? I expected Cython just got any buffer and then checked the >> > > strides instead of requesting the buffer contiguous and then double >> > > checking. >> > >> > At least when I implemented >> > >> > cdef np.ndarray[double, mode='fortran'] arr >> > >> > that relies on PEP 3118 contiguous-flags and I did no checking myself. >> > Lots of Cython code does this instead of memoryviews (I still write my >> > own code that way). >> >> Yeah, though even if numpy "fixes" the buffer strides, `arr.strides` >> points at the original array I believe, leaving it to the user. But that >> just means users have to be a bit more careful with strides. >> >> I think I will have numpy "fix" the buffers stride anyway (when >> requested contiguous through the buffer protocol). I cannot think of >> any reason not to do it and it may work around bugs in extensions which >> may not even be aware of numpy's existence. >> >> > >> > The memory views OTOH does their own checking, but I also see plenty of >> > references to PyBUF_C_CONTIGUOUS etc. inside >> > Cython/Utility/MemoryView.pyx, so perhaps it does both. Mark would have >> > the definitive answer here. >> > >> >> After a quick check, it seems to me that those are there for exposing >> the memoryviews buffer and not for getting a buffer from another object. > > > Yeah, I think most of the checking is in MemoryView_C.c, when obtaining > the memoryview. I don't know how well buffer producers check these flags, > but maybe we can simply remove some of those checks, or amend them > otherwise. I'll try to look into it one of these days. > OTOH if someone else wants to take a crack at it, I'll be happy to review patches as well. > >> - Sebastian >> >> > Dag Sverre >> > _______________________________________________ >> > cython-devel mailing list >> > cython-devel@python.org >> > http://mail.python.org/mailman/listinfo/cython-devel >> > >> >> >> _______________________________________________ >> cython-devel mailing list >> cython-devel@python.org >> http://mail.python.org/mailman/listinfo/cython-devel >> > >
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