diff --git a/neural_compressor/compression/pruner/patterns/ninm.py b/neural_compressor/compression/pruner/patterns/ninm.py
index b14edc8bc9f..d02508cbbcd 100644
--- a/neural_compressor/compression/pruner/patterns/ninm.py
+++ b/neural_compressor/compression/pruner/patterns/ninm.py
@@ -368,8 +368,8 @@ def get_pattern_lock_masks(self, modules):
                 mask = torch.ones(orig_shape, device=weight.device)
                 pattern_lock_masks[key] = mask.bool()
                 continue
-            mask = self.get_least_ninm_mask_from_data(weight)
-            mask = self._reshape_2dims_to_orig(mask, orig_shape)
+            reduced_mask = self.get_reduced_masks_from_data(weight, key)
+            mask = self.reshape_reduced_to_orig(reduced_mask, key, orig_shape)
             pattern_lock_masks[key] = mask
         return pattern_lock_masks
 
diff --git a/neural_compressor/compression/pruner/pruners/progressive.py b/neural_compressor/compression/pruner/pruners/progressive.py
index 2e2a460889c..d972c712a18 100644
--- a/neural_compressor/compression/pruner/pruners/progressive.py
+++ b/neural_compressor/compression/pruner/pruners/progressive.py
@@ -23,11 +23,12 @@
 from ..regs import get_reg
 from ..schedulers import get_scheduler
 from ..utils import logger, torch
-from .base import PytorchBasePruner, register_pruner
+from .base import register_pruner
+from .basic import PytorchBasicPruner
 
 
 @register_pruner("pt_progressive")
-class PytorchProgressivePruner(PytorchBasePruner):
+class PytorchProgressivePruner(PytorchBasicPruner):
     """Pruning Pruner.
 
     A Pruner class derived from BasicPruner. In this pruner, mask interpolation will be applied.
@@ -207,12 +208,12 @@ def update_masks_progressive(self, local_step):
         for n in self.masks.keys():
             self.pre_masks[n] = self.masks[n].clone()
         # update new masks
-        if not self.use_progressive:
-            self.masks = self.pattern.get_masks(
-                self.criterion.scores,
-                current_target_sparsity_ratio,
-                self.masks,
-            )
+        # if not self.use_progressive:
+        #     self.masks = self.pattern.get_masks(
+        #         self.criterion.scores,
+        #         current_target_sparsity_ratio,
+        #         self.masks,
+        #     )
         self.masks = self.pattern.get_masks(
             self.criterion.scores,
             current_target_sparsity_ratio,