Re: [Numpy-discussion] np.dot and 'out' bug
Hi, It's to be expected. You are overwritten one of your input vector while it is still being used. So not a numpy bug ;) Matthieu 2013/5/23 Pierre Haessig pierre.haes...@crans.org Hi Nicolas, Le 23/05/2013 15:45, Nicolas Rougier a écrit : if I use either a or b as output, results are wrong (and nothing in the dot documentation prevents me from doing this): a = np.array([[1, 2], [3, 4]]) b = np.array([[1, 2], [3, 4]]) np.dot(a,b,out=a) - array([[ 6, 20], [15, 46]]) Can anyone confirm this behavior ? (tested using numpy 1.7.1) I just reproduced the same weird results with numpy 1.6.2 best, Pierre ___ NumPy-Discussion mailing list NumPy-Discussion@scipy.org http://mail.scipy.org/mailman/listinfo/numpy-discussion -- Information System Engineer, Ph.D. Blog: http://matt.eifelle.com LinkedIn: http://www.linkedin.com/in/matthieubrucher Music band: http://liliejay.com/ ___ NumPy-Discussion mailing list NumPy-Discussion@scipy.org http://mail.scipy.org/mailman/listinfo/numpy-discussion
Re: [Numpy-discussion] np.dot and 'out' bug
On Thu, May 23, 2013 at 3:19 PM, Matthieu Brucher matthieu.bruc...@gmail.com wrote: Hi, It's to be expected. You are overwritten one of your input vector while it is still being used. So not a numpy bug ;) Sure, that's clearly what's going on, but numpy shouldn't let you silently shoot yourself in the foot like that. Re-using input as output is a very common operation, and usually supported fine. Probably we should silently make a copy of any input(s) that overlap with the output? For high-dimensional dot, buffering temprary subspaces would still be more memory efficient than anything users could reasonably accomplish by hand. -n ___ NumPy-Discussion mailing list NumPy-Discussion@scipy.org http://mail.scipy.org/mailman/listinfo/numpy-discussion
Re: [Numpy-discussion] np.dot and 'out' bug
Sure, that's clearly what's going on, but numpy shouldn't let you silently shoot yourself in the foot like that. Re-using input as output is a very common operation, and usually supported fine. Probably we should silently make a copy of any input(s) that overlap with the output? For high-dimensional dot, buffering temprary subspaces would still be more memory efficient than anything users could reasonably accomplish by hand. Also, from a user point of view it is difficult to sort out which functions currently allow 'out=a' or out=b' since nothing in the 'dot' documentation warned me about such problem. Nicolas ___ NumPy-Discussion mailing list NumPy-Discussion@scipy.org http://mail.scipy.org/mailman/listinfo/numpy-discussion
Re: [Numpy-discussion] np.dot and 'out' bug
In my point of view, you should never use an output argument equal to an input argument. It can impede a lot of optimizations. Matthieu 2013/5/23 Nicolas Rougier nicolas.roug...@inria.fr Sure, that's clearly what's going on, but numpy shouldn't let you silently shoot yourself in the foot like that. Re-using input as output is a very common operation, and usually supported fine. Probably we should silently make a copy of any input(s) that overlap with the output? For high-dimensional dot, buffering temprary subspaces would still be more memory efficient than anything users could reasonably accomplish by hand. Also, from a user point of view it is difficult to sort out which functions currently allow 'out=a' or out=b' since nothing in the 'dot' documentation warned me about such problem. Nicolas ___ NumPy-Discussion mailing list NumPy-Discussion@scipy.org http://mail.scipy.org/mailman/listinfo/numpy-discussion -- Information System Engineer, Ph.D. Blog: http://matt.eifelle.com LinkedIn: http://www.linkedin.com/in/matthieubrucher Music band: http://liliejay.com/ ___ NumPy-Discussion mailing list NumPy-Discussion@scipy.org http://mail.scipy.org/mailman/listinfo/numpy-discussion
Re: [Numpy-discussion] np.dot and 'out' bug
On Thu, May 23, 2013 at 3:57 PM, Matthieu Brucher matthieu.bruc...@gmail.com wrote: In my point of view, you should never use an output argument equal to an input argument. It can impede a lot of optimizations. This is a fine philosophy in some cases, but a non-starter in others. Python doesn't have optimizations in the first place, and in-place operations are often critical for managing memory usage. '+=' is an important operator, and in numpy it's just 'np.add(a, b, out=a)' under the hood. On Thu, May 23, 2013 at 3:50 PM, Nicolas Rougier nicolas.roug...@inria.fr wrote: Also, from a user point of view it is difficult to sort out which functions currently allow 'out=a' or out=b' since nothing in the 'dot' documentation warned me about such problem. That's because AFAIK all functions allow out=a and out=b, except for those which contain bugs :-). Can you file a bug in the bug tracker so this won't get lost? -n ___ NumPy-Discussion mailing list NumPy-Discussion@scipy.org http://mail.scipy.org/mailman/listinfo/numpy-discussion
Re: [Numpy-discussion] np.dot and 'out' bug
Can you file a bug in the bug tracker so this won't get lost? Done. ___ NumPy-Discussion mailing list NumPy-Discussion@scipy.org http://mail.scipy.org/mailman/listinfo/numpy-discussion
