I'm trying to do it, but each time I want to test something, it takes a long time to rebuild numpy to test it. Is there a way to don't recompile everything for each test?
thanks Fred On Fri, May 10, 2013 at 1:34 PM, Charles R Harris <charlesr.har...@gmail.com > wrote: > > > On Fri, May 10, 2013 at 10:08 AM, Frédéric Bastien <no...@nouiz.org>wrote: > >> Hi, >> >> it popped again on the Theano mailing list that this don't work: >> >> np.arange(10) <= a_theano_vector. >> >> The reason is that __array_priority__ isn't respected for that class of >> operation. >> >> This page explain the problem and give a work around: >> >> >> http://stackoverflow.com/questions/14619449/how-can-i-override-comparisons-between-numpys-ndarray-and-my-type >> >> The work around is to make a python function that will decide witch >> version of the comparator to call and do the call. Then we tell NumPy to >> use that function instead of its current function with: >> np.set_numeric_ops(...) >> >> But if we do that, when we import theano, we will slow down all normal >> numpy comparison for the user, as when <= is execute, first there will be >> numpy c code executed, that will call the python function to decide witch >> version to do, then if it is 2 numpy ndarray, it will call again numpy c >> code. >> >> That isn't a good solution. We could do the same override in C, but then >> theano work the same when there isn't a c++ compiler. That isn't nice. >> >> What do you think of changing them to check for __array_priority__ before >> doing the comparison? >> > > This looks like an oversight and should be fixed. > > Chuck > > _______________________________________________ > NumPy-Discussion mailing list > NumPy-Discussion@scipy.org > http://mail.scipy.org/mailman/listinfo/numpy-discussion > >
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