Fix issue #2005 (https://github.com/microsoft/nni/issues/2005) (#2012)

src/sdk/pynni/nni/compression/torch/pruners.py

@@ -113,7 +113,7 @@ class AGP_Pruner(Pruner):
             if k == 0 or target_sparsity >= 1 or target_sparsity <= 0:
                 return mask
             # if we want to generate new mask, we should update weigth first
-            w_abs = weight.abs() * mask
+            w_abs = weight.abs() * mask['weight']
             threshold = torch.topk(w_abs.view(-1), k, largest=False)[0].max()
             new_mask = {'weight': torch.gt(w_abs, threshold).type_as(weight)}
             self.mask_dict.update({op_name: new_mask})