LnStructured
class torch.nn.utils.prune.LnStructured(amount, n, dim=- 1)
Prune entire (currently unpruned) channels in a tensor based on
   their L"n"-norm.
Parameters:
      * amount (int or float) -- quantity of channels to
        prune. If "float", should be between 0.0 and 1.0 and represent
        the fraction of parameters to prune. If "int", it represents
        the absolute number of parameters to prune.
  * **n** (*int**, **float**, **inf**, **-inf**, **'fro'**,
    **'nuc'*) -- See documentation of valid entries for argument
    "p" in "torch.norm()".

  * **dim** (*int**, **optional*) -- index of the dim along which
    we define channels to prune. Default: -1.

classmethod apply(module, name, amount, n, dim, importance_scores=None)
  Adds the forward pre-hook that enables pruning on the fly and
  the reparametrization of a tensor in terms of the original
  tensor and the pruning mask.

  Parameters:
