> Hi, > > I second James here, Theano do many of those optimizations. Only > advanced coder can do better then Theano in most case, but that will > take them much more time. If you find some optimization that you do > and Theano don't, tell us. We want to add them :) > > Fred
I am sure Theano does an excellent job of expressions that matter. But I think to get the best symbolic reduction of an expression is a hard, as in, an AI hard problem. Correct me if I am wrong though. One can come up with perverse corner cases using algebraic or trigonometric identities, expressions that are hundreds of terms long but whose derivatives are simple, perhaps even a constant. But all that matters is how well it does for the common cases and am hearing that it does extremely well. I will be happy if it can reduce simple things like the following (a very common form in Theano's domain) \phi(x) - \phi(y) - dot( x-y, \grad_phi(y)) evaluated for \phi(x) = \sum_i (x_i log x_i) - x_i to \sum_i x_i log(x_i / y_i) on the set sum(x) = sum(y) = 1 In anycase I think this is a digression and rather not pollute this thread with peripheral (nonethless very interesting) issues. _______________________________________________ NumPy-Discussion mailing list NumPy-Discussion@scipy.org http://mail.scipy.org/mailman/listinfo/numpy-discussion
