Don’t use the .data attribute.
If you are copying the trainable parameters to side branches, I would recommend to copy everything (all parameters and buffers) to these branches. This might give you a “good initialization” for the training of these classifiers.
I’m not sure, if this approach is better train training from scratch, but I can see the similarity to using a pretrained model for a new classification task.