You don't need to pass the shape. This is optional information. In fact, currently we don't use it anymore. We used it in the past. Maybe we will use it again later. But in all cases, it was optional.
On Fri, Jul 7, 2017 at 5:31 AM Feras Almasri <[email protected]> wrote: > I checked theano documentation and it says this > > You can give None for any element of the list to specify that this > element is not known at compile time. > http://deeplearning.net/software/theano/library/tensor/nnet/conv.html > > As I said I don't want to use any upper level on top of theano I'm just > using pure theano. I think in my case it is working well because I'm using > a convent that broadcast the same image size all over the network since > there is no down sampling there is no need to re compute the image batch > size in each different batch image size. But I don't realy now why theano > need to compute the image size before ceating the model while by using > keras or lasagne it could work. > > Anyway my problem is solved here and it is not necessary to recompile the > model, but I guess in different cases this could be important specially of > the network is used in live run. another very important proposal is to add > separated convolution network to theano framework. > > On Thursday, July 6, 2017 at 12:03:01 AM UTC+2, nouiz wrote: > >> Pure Theano Do not expect shapes. By default shapes can changes. You just >> need to be consistent in the computation you do on the shapes. >> >> If you set the batchsize shape to None, you are not using pure Theano. >> >> Do you use lasagne? Keras? >> >> Can you show the code where you set the shape to None? >> >> Fred >> >> Le mer. 5 juil. 2017 08:01, Feras Almasri <[email protected]> a écrit : >> > I found that it is possible to change the batch size during the run time >>> by defining the batch size to None. But the pooling layer in case of >>> averaging or same size doesn't have this option and should be defined in >>> different way. >>> >>> >>> On Tuesday, July 4, 2017 at 11:21:04 PM UTC+2, Feras Almasri wrote: >>>> >>>> I'm re-initiating another model in a loop because I'm testing different >>>> batch sizes so I have to re initiate the model again. it seems in my code >>>> that every time I'm re initiating the model the old model still in the GPU >>>> and not deleted. is there any way to delete the model before initiating the >>>> second ? >>>> >>> -- >>> >>> --- >>> 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. > -- --- 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.
