Hi, I’m trying to understand adapative average pooling 2d does.
For example, for the following code:
input = torch.randn(1,1,4,4)
m = torch.nn.AdaptiveAvgPool2d((5,7))
output = m(input)
it executes fine but what confuses me is why it works even the input HxW is less than kernel size. Does it automatically padding 0 to the size of the kernel ?
Thanks a lot,