i have a convolution layer as such:
self.conv1 = nn.Conv2d(1, nb_kernels, kernel_size = (2,7))
for an input of shape 2x256
and i want my 2d conv kernel to slide ONLY in the columns direction, that is to keep the dimension where it has 2 rows and slide along the columns (I would also like to keep the columns dimension but that is ok it seems with a padding of 3 in the col dir)
however i dont seem to be able to do it with the kernel size of 2 rows ?
I tried to put a stride
stride=(0, 1) but that is not allowed by pytorch it seems. … I suddenly don’t understand in fact why the kernels ‘wants’ to slide along the rows direction ?
how can i do it?
(i tried padding=(1,3) → but this does not work either because it produces an output of shape [3, 256] … this confuses me … I guess the 3 comes from padding top and bottom so the kernel slides over an input of 4x256 and can therefore slide 3 times?)
ideally i don’t want to use 1d convolutions and channels which i imagine would be a solution