Thanks for the report. Here is a fix: https://github.com/Theano/Theano/pull/6396
Mostly, we where calling the scipy function per element instead of per tensor! Frédéric On Thu, Sep 7, 2017 at 12:03 PM Juan Camilo Gamboa Higuera < juancami...@gmail.com> wrote: > if you launch ipython and try something like this: > > import numpy as np > import theano > import theano.tensor as tt > from scipy.special import erfinv > > z = tt.vector() > y = tt.erfinv(z) > > f = theano.function([z], y) > f.trust_input = True > > x = np.linspace(-1,1,1000000) > > %timeit f(x) > > %timeit erfinv(x) > > You'll notice the theano version takes about 60-90 times longer than the > call to scipy.special.erfinv. Since theano does not have a c code > implementation for erfinv, it uses the same scipy.special,erfinv function. > > I've also tried modifying the Erfinv Op in theano.scalar.basic_scipy to > provide a c code implementation (taken from here: > https://stackoverflow.com/questions/27229371/inverse-error-function-in-c). > This speeds up the resulting function slightly, but it is still around 50 > times slower than just calling scipy.special.erfinv. > > So my question is, where does this massive overhead come from? Anyn ideas > on how to sidestep this issue? Note that this is for the CPU version. On > GPU everything is fine. > > -- Juan Camilo > > -- > > --- > You received this message because you are subscribed to the Google Groups > "theano-users" group. > To unsubscribe from this group and stop receiving emails from it, send an > email to theano-users+unsubscr...@googlegroups.com. > For more options, visit https://groups.google.com/d/optout. > -- --- You received this message because you are subscribed to the Google Groups "theano-users" group. To unsubscribe from this group and stop receiving emails from it, send an email to theano-users+unsubscr...@googlegroups.com. For more options, visit https://groups.google.com/d/optout.
