The running stats are not parameters (they do not get gradients and the optimizer won’t update them), but buffers, which will be updated during the forward pass.
You could call .eval() on the batchnorm layers to apply the running stats instead of calculating and using the batch statistics and updating the running stats (which would be the case during .train()).