BTW, be careful that for k in range(0, K-1):
loops from 0 to K-2. Also, you can drop the first term when it's 0. On Wednesday, February 15, 2017 at 12:33:40 PM UTC+1, albit...@gmail.com wrote: > > Hi, > > *Goal * > In the context of a learning algorithm, I want to calculate the > product: > > B = A[K-1] x A[K-1] x .... A[0], > > where each A[k] is a (sparse, if it helps to know) matrix of size N*N and > "x" denotes the theano.dot() product . > > *Question * > * How can I do that for fairly large matrices, say each A[k] is *100x100* > ? * > > *Things I've tried (t is theano and tt is theano.tensor):* > > - *For loop* > > B = tt.eye(n=self.N, m=N)for k in range(0, K-1): > B = t.dot(A[k], B) > > *Pro*: simple, works fine for N = 10 > *Con*: If N >> (say N = 100), I get this error: > File "/usr/local/lib/python2.7/dist-packages/theano/gof/graph.py", line > 392, in __init__self.auto_name = 'auto_' + str(next(self.__count__)) > RuntimeError: maximum recursion depth exceeded while getting the str of an > object > > > - *Theano scan or reduce* > > results, _ = t.scan(fn=lambda k, tmp: tt.dot(A[k], tmp), > outputs_info=tt.eye(n=N, m=N), > sequences=[tt.arange(K, dtype='int64')]) > B = results[-1] > > > > *Pro*: works even for large matrices > *Con*: Epoch become incredibly slow (200,000 seconds instead of 500~1,000) > > > > Any help or advice would be much appreciated. > > Thanks > Oussama > > > -- --- 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.
