I would love to implement my case, but I don’t exactly know which functions to add. I can think of a way in which diff can be converted to a scan op but I don’t know if that’ll help with grad or just slow down things. > On Jul 21, 2016, at 2:09 PM, Frédéric Bastien <[email protected]> > wrote: > > We haven't implemetned the grad for the diff op if the input isn't a vector. > > Do you want to implement your cases? > > Fred > > On Thu, Jul 21, 2016 at 11:54 AM, Aditya Gudimella > <[email protected] <mailto:[email protected]>> wrote: > a = shared(np.arange(3*8).reshape(8,3).astype('float32')) > b = diff(a, axis=0) > T.grad(b.norm(2), a) > > > This gives me an error. It's unable to find the gradient of the diff operator > if it has been used on a 2 dimensional tensor. Is this how it was meant to be > or is this a bug? > > -- > > --- > 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 [email protected] > <mailto:[email protected]>. > For more options, visit https://groups.google.com/d/optout > <https://groups.google.com/d/optout>. > > > -- > > --- > You received this message because you are subscribed to a topic in the Google > Groups "theano-users" group. > To unsubscribe from this topic, visit > https://groups.google.com/d/topic/theano-users/r4tLV0BTvGU/unsubscribe > <https://groups.google.com/d/topic/theano-users/r4tLV0BTvGU/unsubscribe>. > To unsubscribe from this group and all its topics, send an email to > [email protected] > <mailto:[email protected]>. > For more options, visit https://groups.google.com/d/optout > <https://groups.google.com/d/optout>.
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