

default_mask (torch.Tensor) -- mask from previous
           pruning iteration.
Returns:
     new mask that combines the effects of the "default_mask" and
     the new mask from the current pruning "method" (of same
     dimensions as "default_mask" and "t").
Return type:
     mask (torch.Tensor)


prune(t, default_mask=None, importance_scores=None)
  Computes and returns a pruned version of input tensor "t"
  according to the pruning rule specified in "compute_mask()".

  Parameters:
     * **t** (*torch.Tensor*) -- tensor to prune (of same
       dimensions as "default_mask").

     * **importance_scores** (*torch.Tensor*) -- tensor of
       importance scores (of same shape as "t") used to compute
       mask for pruning "t". The values in this tensor indicate
       the importance of the corresponding elements in the "t"
       that is being pruned. If unspecified or None, the tensor
