Use the CuDNN pool op (theano.sandbox.cuda.dnn.dnn_pool), it doesn't have 
this limitation.

On Tuesday, August 30, 2016 at 4:24:15 AM UTC-4, Kristofer Krus wrote:
>
> Hi nouiz,
>
> If you can make it work, I for one would really appreciate if it was 
> possible to pool an image where the output of the pooling operation has 
> more than 512 columns. I need that since in my network I pool only 
> vertically and not horizontally. I instead use dilated convolution layers 
> where I dilate in the x-direction; this is in order not to loose any 
> spatial information horizontally which is important in my case. For now I 
> will have to crop the image to 512 columns but I would really prefer not to.
>
> Regards
>
> Kristofer
>
> On Friday, May 13, 2011 at 5:31:43 PM UTC+2, nouiz wrote:
>>
>> Hi,
>>
>> It is an NVIDIA gpu card limitation. But we can work around by reusing
>> thread for more then one columns.
>>
>> I updated the gpu function to work around this limitation. So the
>> gradient of the downsample work when the input of the downsample have
>> more then 512/1024 columns. There is still the limitation that the
>> output of the downsample must have less then 512 colomns.
>>
>> If you need it, I can try to make it. Otherwise, it will wait.
>>
>> You must use and update the version on mercurial to have the new 
>> functionnality.
>>
>> HTH,
>>
>> Fred
>>
>> On Fri, May 13, 2011 at 10:34 AM, Sander Dieleman
>> <[email protected]> wrote:
>> > Oh, that's great! I figured this was just an inherent limitation of
>> > the CUDA platform, but if it can be fixed that's even better :)
>> >
>> > On May 13, 3:20 pm, Frédéric Bastien <[email protected]> wrote:
>> >> Hi,
>> >>
>> >> I know how to fix the problem in the code. That way, you won't need
>> >> workaround and it will work in all case.
>> >>
>> >> I will try to put a better error message. The error that you see is
>> >> the error from nvidia that we forwarded.
>> >>
>> >> thanks for the report.
>> >>
>> >> Frédéric Bastien
>> >
>>
>>

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