Understood. Thank you.

On Thursday, December 1, 2016 at 11:21:36 AM UTC-7, nouiz wrote:
>
> There was a fix to the random stream in the new back-end. This could fix 
> that.
>
> But you should use not use_cuda=True with the new back-end, this is for 
> the old back-end only.
>
> On Sat, Nov 12, 2016 at 9:50 PM, Ragav Venkatesan <[email protected] 
> <javascript:>> wrote:
>
>> I'm sorry I want to correct myself. use_cuda =None is not creating a new 
>> process on another GPU and is running as usual. Only using use_cuda = True 
>> in libgpuarray mode has this issue.
>>
>>
>> On Saturday, November 12, 2016 at 7:46:17 PM UTC-7, Ragav Venkatesan 
>> wrote:
>>>
>>> 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. 
>>>> > 
>>>> > -- 
>>>> > 
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>>>>
>>>>
>>>> -- 
>>>> Pascal 
>>>>
>>> -- 
>>
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