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.
Returns:
      modified (i.e. pruned) version of the input module
Return type:
      module (nn.Module)
-[ Examples ]-



m = prune.random_unstructured(nn.Linear(2, 3), 'weight', amount=1)
torch.sum(m.weight_mask == 0)
   tensor(1)


