How does batch norm behave in pytorch depending if one is in training mode or eval/inference mode?

I was looking at:

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?