Hi, You can probably have a look at the implementation in Lasagne. https://github.com/Lasagne/Recipes/blob/master/examples/lstm_text_generation.py#L119-L156 Instead of the Dense, you can use a convolution layer for your case
Cheers, Ramana On Tuesday, June 20, 2017 at 6:42:39 AM UTC+5:30, Sunjeet Jena wrote: > > 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]> 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]. >>> 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.
