It would rather correspond to  track_running_stats=True  and set to evaluation mode ( bn.eval() ), which would then use the initial running stats.

That sounds like it will freeze the statistics (eg. mean and variance) but it also sounds like it will freeze gamma and beta which appear to be learnable in AffineChannel.
I think I might be able to mimic theAffineChannel operation by creating a vector of torch.ones([num_channels]) and torch.zeros([num_channels]) and using these for gamma and beta respectively. I’ll give it a shot and see how it goes.