When it don't work on the GPU, we fall back to the CPU and transfer the
data. This slow down execution, bit make it work.

That is why it give you the impression it work event on GPU.

Fred

Le 17 oct. 2016 11:23, "Léo Crestel" <crestel.leop...@gmail.com> a écrit :

> Hello,
>
> I want to use GPUs with Theano, and read here (http://deeplearning.net/
> software/theano/tutorial/examples.html#using-random-numbers) that I have
> to import this
>
> from theano.sandbox.rng_mrg import MRG_RandomStreams as RandomStreams
>
> instead of this
>
> from theano.tensor.shared_randomstreams import RandomStreams
>
> However, I have the feeling that both are working with GPU, since I got
> random numbers as expected when running the above code with the GPU :
> import theano
> # from theano.sandbox.rng_mrg import MRG_RandomStreams as RandomStreams
> from theano.tensor.shared_randomstreams import RandomStreams
>
>
> if __name__ == '__main__':
>     rng = RandomStreams()
>
>     def get_random():
>         out = rng.uniform((2,2), dtype=theano.config.floatX)
>         fonction = theano.function(inputs=[],
>                                    outputs=[out],
>                                    name='test'
>                                    )
>         return fonction
>
>     fonc = get_random()
>     for i in range(5):
>         print(fonc())
>
> Is it normal ? I have the confirmation that i'm running the code on the
> GPU,
> Using gpu device 0: GeForce GTX TITAN X (CNMeM is enabled with initial
> size: 90.0% of memory, cuDNN not available)
>
> So why is it working ?
>
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