I was looking at:
http://pytorch.org/docs/stable/_modules/torch/nn/modules/batchnorm.html#BatchNorm2d 11
and I didn’t see how how F.batch_norm works. I looked in the docs but could find it and perhaps it seems that it might be written in C which I dont know.
My question is how does batch_norm updates its parameters during training vs inference? When are the mean variance for example updated? What happens to them during inference mode? Are they just fixed?