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Support for non-square kernels. Added kernel_x and kernel_y variable to ... #76
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…to convolution layer with backward compatibility for kernelsize.
Looks good. Some points: |
Hi rmanor, rasmus, this is no exactly what my pull request was about, I wanted to have non squared inputs(e.g., an spectrogram of 50x600). I'll work in a test case for checking gradients when non squared inputs are present. |
Hi, My change is about non squared kernels, not inputs. As far as I can tell
On Wed, Dec 4, 2013 at 3:05 PM, albertoandreottiATgmail <
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Hey Ran, are you talking about the CNN? are you sure it worked fine? Would you mind taking a look at my pull request to see if my changes make sense to you? Alberto. |
Yes, CNNs. Pretty sure, I will re-check.
On Wed, Dec 4, 2013 at 3:17 PM, albertoandreottiATgmail <
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Hey!, sorry for the confusion. You're right, the net would work as it is with non squared inputs. I needed this non squared average operation for reducing vectors(say 50x1) to a single variable, the only way to achieve this was with an average operation using a non squared kernel. |
Yes! These should definitely be implemented and tested separately. |
anyone has a progress on this issue? |
I'll take a look during the weekend, if you could wait. Thanks, Alberto. On 5 May 2014 17:26, Taygun Kekec notifications@github.com wrote:
José Pablo Alberto Andreotti. |
I remember we had problems with the convn() function in Octave. My branch had a fix for this. Now Octave 3.8.1 is released, so I'll test everything under the new version and see what happens. |
What's the status on this one? |
...convolution layer with backward compatibility for kernelsize.