Implementing "Same" padding for 3d convolution in Pytorch


I was wondering if there were any helpful implementations of a 3d convolution which maintains size for irregular dimensions (ie not square).


You mean irregular dimensions of the kernel? If so, yes you can set a per-dimension padding that will match the kernel size in that dimension.

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