diff --git a/debug/accuracy_tools/msprobe/pytorch/dump/module_dump/module_processer.py b/debug/accuracy_tools/msprobe/pytorch/dump/module_dump/module_processer.py
index d9b67c93175641cbd0009c1f58562787626d375f..4f148008ebf9bc40b76535d1adae476d6a8bf7c1 100644
--- a/debug/accuracy_tools/msprobe/pytorch/dump/module_dump/module_processer.py
+++ b/debug/accuracy_tools/msprobe/pytorch/dump/module_dump/module_processer.py
@@ -47,30 +47,33 @@ class ModuleProcesser:
 
     def __init__(self, scope):
         self.scope = scope if isinstance(scope, (ModuleRangeScope, MixRangeScope)) else None
-        BackwardHook.setup_input_hook = ModuleProcesser.clone_return_value(BackwardHook.setup_input_hook)
-        BackwardHook.setup_output_hook = ModuleProcesser.clone_return_value(BackwardHook.setup_output_hook)
+        BackwardHook.setup_input_hook = ModuleProcesser.modify_view_type_return_value(BackwardHook.setup_input_hook)
+        BackwardHook.setup_output_hook = ModuleProcesser.modify_view_type_return_value(BackwardHook.setup_output_hook)
         replace_checkpoint()
 
     @staticmethod
-    def clone_return_value(func):
+    def modify_view_type_return_value(func):
         @wraps(func)
-        def clone_return_value_func(*args, **kwargs):
+        def modify_view_type_return_value_func(*args, **kwargs):
             result = func(*args, **kwargs)
-            return ModuleProcesser.clone_if_tensor(result)
+            return ModuleProcesser.modify_view_type(result)
 
-        return clone_return_value_func
+        return modify_view_type_return_value_func
 
     @staticmethod
-    @recursion_depth_decorator("ModuleDump: ModuleProcesser.clone_if_tensor", max_depth=Const.DUMP_MAX_DEPTH)
-    def clone_if_tensor(result):
+    @recursion_depth_decorator("ModuleDump: ModuleProcesser.modify_view_type", max_depth=Const.DUMP_MAX_DEPTH)
+    def modify_view_type(result):
         if isinstance(result, torch.Tensor) and not is_float8_tensor(result):
-            return result.clone()
+            if hasattr(result, "_base") and result._base is not None:
+                if torch._C._autograd._get_creation_meta(result) != torch._C._autograd.CreationMeta(0):
+                    torch._C._autograd._set_creation_meta(result, torch._C._autograd.CreationMeta(0))
+            return result
         elif type(result) is tuple:
-            return tuple(ModuleProcesser.clone_if_tensor(x) for x in result)
+            return tuple(ModuleProcesser.modify_view_type(x) for x in result)
         elif type(result) is list:
-            return list(ModuleProcesser.clone_if_tensor(x) for x in result)
+            return list(ModuleProcesser.modify_view_type(x) for x in result)
         elif type(result) is dict:
-            return {k: ModuleProcesser.clone_if_tensor(v) for k, v in result.items()}
+            return {k: ModuleProcesser.modify_view_type(v) for k, v in result.items()}
         else:
             return result