pruning will act.
     * **args** -- arguments passed on to a subclass of
       "BasePruningMethod"

     * **importance_scores** (*torch.Tensor*) -- tensor of
       importance scores (of same shape as module parameter) used
       to compute mask for pruning. The values in this tensor
       indicate the importance of the corresponding elements in
       the parameter being pruned. If unspecified or None, the
       parameter will be used in its place.

     * **kwargs** -- keyword arguments passed on to a subclass of
       a "BasePruningMethod"

apply_mask(module)
  Simply handles the multiplication between the parameter being
  pruned and the generated mask. Fetches the mask and the original
  tensor from the module and returns the pruned version of the
  tensor.

  Parameters:
     **module** (*nn.Module*) -- module containing the tensor to
     prune

  Returns:
     pruned version of the input tensor
