I would like to add that the cost function is looping over the input tensors.
I need these loops to be differentiable, so I've implemented them with scan/map. But in this answer <https://groups.google.com/forum/#!msg/theano-users/uqYtNlpwiHw/k-3QCro0SbkJ> I saw that it is possible to compile a theano function and call it with a Python for loop. So again I don't know what's best.. Should I compile a step of the loop in a theano function, and then loop with Python's for op ? Or should I compile a theano function with the whole cost (where the loops are now done with scan) ? Or should I just compile one theano function, with the network and the cost ? Thank you for your help ! Le mardi 4 juillet 2017 10:20:17 UTC-4, Sym a écrit : > > Hi, > > I have a fairly complex cost function, composed of various pieces that > are looping over the data. > > Should I compile the total cost as a theano function or not ? > Would the network still be able to compute gradients if I do this ? > Would it be faster / slower than compiling everything (network + cost > functions) in one theano function ? > > I am not sure about what would be the benefits of doing this, if there are > any. > -- --- 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.
