I’m trying to understand the difference between nn.Upsample and upsampling via transposed convolution. I wrote an example upsampling a 2x2 identity matrix both ways - can anyone explain why they are different?
https://gist.github.com/katerakelly/3fb565f172df3a371f5178d51e8f1039 221
For bilinear upsampling, it seems that each output should be a function of > 1 input, for smoothing purposes. Yet this is not what nn.Upsample does (it preserves original values) - why is this?