diff --git a/mindspore/nn/layer/math.py b/mindspore/nn/layer/math.py
index 1ecb20056e2b73b0850fe2d1972c1e252060a973..cf18d1cf0f4454d474e8c1c0600b333b0591249d 100644
--- a/mindspore/nn/layer/math.py
+++ b/mindspore/nn/layer/math.py
@@ -132,23 +132,19 @@ class Range(Cell):
 
 class LinSpace(Cell):
     r"""
-    Generates values in an interval. And return the corresponding interpolation accroding to assist.
+    Generates values in an interval.
 
     Args:
-        - **start** (Union[int, float]) - The start of interval, With shape of 0-D.
-        - **stop** (Union[int, float]) - The end of interval, With shape of 0-D.
-        - **num** (int) - ticks number in the interval, the ticks include start and stop value.
-          With shape of 0-D.
+        start (Union[int, float]): The start of interval. With shape of 0-D.
+        stop (Union[int, float]): The end of interval. With shape of 0-D.
+        num (int): ticks number in the interval, the ticks include start and stop value. With shape of 0-D.
 
     Outputs:
         Tensor, With type same as `start`. The shape is 1-D with length of `num`.
 
     Examples:
-        >>> linspace = nn.LinSpace()
-        >>> start = Tensor(1, mindspore.float32)
-        >>> stop = Tensor(10, mindspore.float32)
-        >>> num = Tensor(5, mindspore.int32)
-        >>> output = linspace(start, stop, num)
+        >>> linspace = nn.LinSpace(1, 10, 5)
+        >>> output = linspace()
         [1, 3.25, 5.5, 7.75, 10]
     """
 
diff --git a/mindspore/ops/operations/nn_ops.py b/mindspore/ops/operations/nn_ops.py
index 7117e494e491f52b4d904a593ef24a86515ab825..3c7615ce6e983467a2149fdc990d4d1d1527a0f1 100644
--- a/mindspore/ops/operations/nn_ops.py
+++ b/mindspore/ops/operations/nn_ops.py
@@ -2711,7 +2711,7 @@ class ROIAlign(PrimitiveWithInfer):
     Examples:
         >>> input_tensor = Tensor(np.array([[[[1., 2.], [3., 4.]]]]), mindspore.float32)
         >>> rois = Tensor(np.array([[0, 0.2, 0.3, 0.2, 0.3]]), mindspore.float32)
-        >>> roi_align = P.ROIAlign(1, 1, 0.5, 2)
+        >>> roi_align = P.ROIAlign(2, 2, 0.5, 2)
         >>> output_tensor = roi_align(input_tensor, rois)
         >>> assert output_tensor == Tensor(np.array([[[[2.15]]]]), mindspore.float32)
     """
@@ -4980,4 +4980,5 @@ class LRN(PrimitiveWithInfer):
         return x_dtype
 
     def infer_shape(self, x_shape):
+        validator.check_integer("x_shape", len(x_shape), 4, Rel.EQ, self.name)
         return x_shape