If you don't mind could you advice me how can I then possibly join a CNN architecture with RNN and back propagate through time. Do I need to use scan function for the CNN also? If I have 't' frames to consider then if I take the convolution outputs of all these 't' frames and then put them in a RNN network using scan function will it work?
On Tuesday, 20 June 2017 03:45:46 UTC+5:30, nouiz wrote: > > Sadly, no. > > Fred > > Le lun. 19 juin 2017 06:39, Sunjeet Jena <[email protected] > <javascript:>> a écrit : > >> Can we implement it using normal 'for' function of python? Like, saving >> all the parameters in a list and then taking the gradient . >> >> >> On Monday, 19 June 2017 10:42:24 UTC+5:30, Jesse Livezey wrote: >>> >>> You can use the scan function to create RNN architectures. >>> >>> http://deeplearning.net/software/theano/library/scan.html >>> >>> On Sunday, June 18, 2017 at 4:13:44 PM UTC-7, Sunjeet Jena wrote: >>>> >>>> I am building a multi-layer RNN network and thus need a way to back >>>> propagate through time in Theano. Does theano automatically knows how to >>>> unfold the network as a feed forward network? >>>> >>> -- >> >> --- >> 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] <javascript:>. >> 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 [email protected]. For more options, visit https://groups.google.com/d/optout.
