PyTorch Version: 1.8.1
Torchvision Version: 0.9.1
Good idea. Let me try your suggestion and get back.
I am using Global, unstructured, absolute magnitude & iterative pruning by using “torch.nn.utils.prune” for which computing global sparsity is important. The algo used involves using a trained model as follows:


prune p% of smallest magnitude weights globally (p = 20%)


Fine-tune for n epochs to recover from the damage caused due to pruning