diff --git a/mindspore/ops/operations/math_ops.py b/mindspore/ops/operations/math_ops.py
index 9fccff0622..53ee6738cf 100644
--- a/mindspore/ops/operations/math_ops.py
+++ b/mindspore/ops/operations/math_ops.py
@@ -319,7 +319,7 @@ class ReduceMean(_Reduce):
         Tensor, has the same dtype as the 'input_x'.
 
         - If axis is (), and keep_dims is false,
-          the output is a 0-D tensor representing the sum of all elements in the input tensor.
+          the output is a 0-D tensor representing the mean of all elements in the input tensor.
         - If axis is int, set as 2, and keep_dims is false,
           the shape of output is :math:`(x_1, x_3, ..., x_R)`.
         - If axis is tuple(int), set as (2, 3), and keep_dims is false,
diff --git a/mindspore/ops/operations/nn_ops.py b/mindspore/ops/operations/nn_ops.py
index d2b6f9a397..f1b9100c16 100644
--- a/mindspore/ops/operations/nn_ops.py
+++ b/mindspore/ops/operations/nn_ops.py
@@ -233,7 +233,7 @@ class Softsign(PrimitiveWithInfer):
     The function is shown as follows:
 
     .. math::
-        \text{output} = \frac{\text{input_x}}{1 + \abs{\text{input_x}}},
+        \text{output} = \frac{\text{input_x}}{1 + \left| \text{input_x} \right|},
 
     Inputs:
         - **input_x** (Tensor) - The input tensor whose data type should be float16 or float32.