diff --git a/mindspore/python/mindspore/ops/function/math_func.py b/mindspore/python/mindspore/ops/function/math_func.py
index 822c97cf8b3..a7c33132053 100644
--- a/mindspore/python/mindspore/ops/function/math_func.py
+++ b/mindspore/python/mindspore/ops/function/math_func.py
@@ -6233,20 +6233,20 @@ def dstack(inputs):
           [ 6. 12.]]]
     """
     if not isinstance(inputs, (tuple, list)):
-        raise TypeError(f"For 'dstack', 'diff', 'inputs' must be list or tuple of tensors, but got {type(inputs)}")
+        raise TypeError(f"For 'dstack', 'inputs' must be list or tuple of tensors, but got {type(inputs)}")
     if not inputs:
-        raise TypeError(f"For 'dstack', 'diff', 'inputs' can not be empty.")
+        raise TypeError(f"For 'dstack', 'inputs' can not be empty.")
     trans_inputs = ()
     for tensor in inputs:
         if not isinstance(tensor, Tensor):
-            raise TypeError(f"For 'dstack', 'diff', each elements of 'inputs' must be Tensor, but got {type(tensor)}")
+            raise TypeError(f"For 'dstack', each elements of 'inputs' must be Tensor, but got {type(tensor)}")
         if tensor.ndim <= 1:
             tensor = _expand(tensor, 2)
         if tensor.ndim == 2:
             tensor = P.ExpandDims()(tensor, 2)
         trans_inputs += (tensor,)
     if not trans_inputs:
-        raise ValueError("For 'dstack', 'diff', at least one tensor is needed to concatenate.")
+        raise ValueError("For 'dstack', at least one tensor is needed to concatenate.")
     return P.Concat(2)(trans_inputs)
 
 
@@ -6627,15 +6627,15 @@ def vstack(inputs):
          [1 5 9]]
     """
     if not isinstance(inputs, (tuple, list)):
-        msg = f"List or tuple of tensors are required, but got {type(inputs)}"
+        msg = f"For 'vstack', list or tuple of tensors are required, but got {type(inputs)}"
         raise TypeError(msg)
     if not inputs:
-        msg = "Inputs can not be empty"
+        msg = "For 'vstack', inputs can not be empty"
         raise TypeError(msg)
     trans_tup = ()
     for tensor in inputs:
         if not isinstance(tensor, Tensor):
-            msg = f"Tensor is required, but got {type(tensor)}"
+            msg = f"For 'vstack', Tensor is required, but got {type(tensor)}"
             raise TypeError(msg)
         if tensor.ndim <= 1:
             shape = P.Shape()(tensor)
@@ -6647,7 +6647,7 @@ def vstack(inputs):
             tensor = P.Reshape()(tensor, tuple(shape))
         trans_tup += (tensor,)
     if not trans_tup:
-        raise ValueError("Need at least one tensor to concatenate.")
+        raise ValueError("For 'vstack', need at least one tensor to concatenate.")
     out = P.Concat(0)(trans_tup)
     return out
 
@@ -6866,6 +6866,11 @@ def copysign(x, other):
     return P.Select()(less_zero, P.Neg()(pos_tensor), pos_tensor)
 
 
+@constexpr
+def _check_non_negative_int(arg_value, arg_name, prim_name):
+    validator.check_non_negative_int(arg_value, arg_name, prim_name)
+
+
 def hann_window(window_length, periodic=True):
     r"""
     Generates a Hann Window.
@@ -6897,19 +6902,12 @@ def hann_window(window_length, periodic=True):
         >>> print(out.asnumpy())
         [0.        0.3454915 0.9045085 0.9045085 0.3454915]
     """
-    if not isinstance(window_length, int):
-        raise TypeError(
-            f"For 'hann_window', 'window_length' must be a non-negative integer, but got {type(window_length)}"
-        )
-    if window_length < 0:
-        raise ValueError(
-            f"For 'hann_window', 'window_length' must be a non-negative integer, but got {window_length}"
-        )
+    _check_non_negative_int(window_length, 'window_length', 'hann_window')
     if window_length <= 1:
         return Tensor(np.ones(window_length))
     if not isinstance(periodic, (bool, np.bool_)):
         raise TypeError(
-            f"For 'kaiser_window', 'periodic' must be a variable of Boolean type, but got {type(periodic)}"
+            f"For 'hann_window', 'periodic' must be a variable of Boolean type, but got {type(periodic)}"
         )
     if periodic:
         window_length = window_length + 1
@@ -7834,14 +7832,7 @@ def kaiser_window(window_length, periodic=True, beta=12.0):
         [5.27734413e-05 1.01719688e-01 7.92939834e-01 7.92939834e-01
          1.01719688e-01]
     """
-    if not isinstance(window_length, int):
-        raise TypeError(
-            f"For 'kaiser_window', 'window_length' must be a non-negative integer, but got {type(window_length)}"
-        )
-    if window_length < 0:
-        raise ValueError(
-            f"For 'kaiser_window', 'window_length' must be a non-negative integer, but got {window_length}"
-        )
+    _check_non_negative_int(window_length, 'window_length', 'kaiser_window')
     if window_length <= 1:
         return Tensor(np.ones(window_length))
     if not isinstance(periodic, bool):