Permuting the output of the linear layer would assign the out_features dimension to dim1, which is the “channels” dimension in batchnorm layers.
I assumed this is the expected use case, since @Michael_Moran defined the size of these dimensions both as 1024. dim1 in the original output of the linear layer (size of 32) is the “additional” dimension and is often used e.g. for the temporal dimension.
If this approach is correct or not depends on the use case and might be wrong for you so you would have to explain a bit what you are trying to achieve.