When I train an network, I see that the BatchNorm2d weights are becoming negative. Is this possible? Any way to prevent this?
In the default setup batchnorm layers use affine parameters (weight and bias) as well as the running estimates. Neither of those tensors is bounded in any way.
If you want to enforce a certain range you might e.g. clip the weight after an update.