diff --git a/mindspore/ops/operations/math_ops.py b/mindspore/ops/operations/math_ops.py
index 08cd481582d14828cae70c57ae17fc796154c8c8..af0deacc16f9f9729a5122cef96848af994dd994 100644
--- a/mindspore/ops/operations/math_ops.py
+++ b/mindspore/ops/operations/math_ops.py
@@ -1888,7 +1888,7 @@ class Cosh(PrimitiveWithInfer):
 
 class Asinh(PrimitiveWithInfer):
     """
-    Compute inverse hyperbolic cosine of x element-wise.
+    Compute inverse hyperbolic sine of x element-wise.
 
     Inputs:
         - **input_x** (Tensor) - The shape of tensor is :math:`(x_1, x_2, ..., x_R)`.
@@ -2645,7 +2645,7 @@ class Sin(PrimitiveWithInfer):
 
 class Asin(PrimitiveWithInfer):
     """
-    Computes arccosine of input element-wise.
+    Computes arcsine of input element-wise.
 
     Inputs:
         - **input_x** (Tensor) - The shape of tensor is :math:`(x_1, x_2, ..., x_R)`.
diff --git a/mindspore/ops/operations/nn_ops.py b/mindspore/ops/operations/nn_ops.py
index b6556d01f4679f899bc7dfdbf186bcb291d5fbfa..24b081bdad3b8d7a94228f909443860a490a3ff1 100644
--- a/mindspore/ops/operations/nn_ops.py
+++ b/mindspore/ops/operations/nn_ops.py
@@ -1905,7 +1905,7 @@ class ApplyCenteredRMSProp(PrimitiveWithInfer):
         >>> mean_grad = Tensor(np.arange(12).astype(np.float32).reshape(2, 3, 2), mindspore.float32)
         >>> mean_square = Tensor(np.arange(-8, 4).astype(np.float32).reshape(2, 3, 2), mindspore.float32)
         >>> moment = Tensor(np.arange(12).astype(np.float32).reshape(2, 3, 2), mindspore.float32)
-        >>> grad = Tensor(np.arange(12).astype(np.float32).rehspae(2, 3, 2), mindspore.float32)
+        >>> grad = Tensor(np.arange(12).astype(np.float32).reshape(2, 3, 2), mindspore.float32)
         >>> learning_rate = Tensor(0.9, mindspore.float32)
         >>> decay = 0.0
         >>> momentum = 1e-10