@ani0075 You can extend the module with whatever pruning technique you want. There is an ongoing conversation about what to include here at this issue: https://github.com/pytorch/pytorch/issues/39765 6
I can help with the implementation, whether it ends up making it into the official list of pytorch supported methods, or it ends up living in your own separate repository.
Either way, I’d recommend subclassing BasePruningMethod so that you can take advantage of all the pre-packaged functionalities provided by the base class, and remain compatible with the pruning “language” of PyTorch pruning. The bottom portion of the pruning tutorial 4 shows how to extend the module with your own custom pruning module (through a very simple example, in that case).
For reverse L1 unstructured, this should be a super easy change in the LnStructured code from largest=True to largest=False when computing the topk, as documented in the code here: https://github.com/pytorch/pytorch/blob/master/torch/nn/utils/prune.py#L709