When I use F.instance_norm with batch_size = 1 everything runs fine.
But with higher batch size I got some size errors.
Each element of my batch is a person so I want to gives weights to normalize per persons per channels e.g : batch of 3 persons 64 channels and wathever 2D size => weights of size 3,64.
If I get it right instanceNorm is perfect for that but I cannot pass other thing that 64 element to F.instance_norm(weights=…)
I tried (3,64), 192 (3*64), but it only accept 64 elements (which is wrong because I want parameters per channels per batch)
Instance norm does not use per-element weight. It doesn’t make sense as a network layer. You can just do the affine transform yourself after instance norm…