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. - 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
