same result from what I can see. But I was under the assumption that use_cuda = None is going make the thing run on CPU no matter what.
On Saturday, November 12, 2016 at 9:31:12 AM UTC-7, Pascal Lamblin wrote: > > What about the default of "use_cuda=None"? > > On Fri, Nov 11, 2016, Ragav Venkatesan wrote: > > I use theano.sandbox.rng_mrg.MRG_RandomStreams to generate a 2D (and 1D > ) > > dropout masks for applying dropouts. I create it so, > > > > srng = MRG_RandomStreams(rng.randint(1,89324723894), use_cuda = True) > > mask = srng.binomial (n=1, p=1-dropout_rate,size=params.shape,dtype = > > floatX) > > > > otuput = params *mask. > > > > doing this operation is doing two things. > > > > 1. If I use the libgpuarray backend, and I have two GPUS, the mask is > being > > created in another GPU from the one I have used in config.device. > > 2. If I use it with use_cuda = False, it is creating the data in the > same > > GPU, but then the code does not run on GPU.. > > > > Appreciate any help. > > > > -- > > > > --- > > 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. > > > -- > Pascal > -- --- 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.
