diff --git a/python/paddle/tensor/math.py b/python/paddle/tensor/math.py
index 5ff3d733b24baf47513bcb9cd587bd940debec69..4d9f170d39ee4c6df1b802a9fb9a9c3142ccb4be 100644
--- a/python/paddle/tensor/math.py
+++ b/python/paddle/tensor/math.py
@@ -500,16 +500,19 @@ def add(x, y, name=None):
 
         Out=X+Y
 
-        X : a tensor of any dimension.
-        Y: a tensor whose dimensions must be less than or equal to the dimensions of X.
+    $X$ the tensor of any dimension.
+    $Y$ the tensor whose dimensions must be less than or equal to the dimensions of $X$.
 
     There are two cases for this operator:
-    1. The shape of Y is the same with X.
-    2. The shape of Y is a continuous subsequence of X.
+
+    1. The shape of $Y$ is the same with $X$.
+    2. The shape of $Y$ is a continuous subsequence of $X$.
+
     For case 2:
-    1. Broadcast Y to match the shape of X, where axis is the start dimension index for broadcasting Y onto X.
-    2. If axis is -1 (default), axis=rank(X)−rank(Y).
-    3. The trailing dimensions of size 1 for Y will be ignored for the consideration of subsequence, such as shape(Y) = (2, 1) => (2).
+
+    1. Broadcast $Y$ to match the shape of $X$, where axis is the start dimension index for broadcasting $Y$ onto $X$.
+    2. If $axis$ is -1 (default), $axis$=rank($X$)−rank($Y$).
+    3. The trailing dimensions of size 1 for $Y$ will be ignored for the consideration of subsequence, such as shape($Y$) = (2, 1) => (2).
 
         For example:
 
@@ -523,13 +526,12 @@ def add(x, y, name=None):
             shape(X) = (2, 3, 4, 5), shape(Y) = (2, 1), with axis=0
 
     Args:
-        x (Tensor) – (Variable), Tensor or LoDTensor of any dimensions. Its dtype should be int32, int64, float32, float64.
-        y (Tensor) – (Variable), Tensor or LoDTensor of any dimensions. Its dtype should be int32, int64, float32, float64.
-        with_quant_attr (BOOLEAN) – Whether the operator has attributes used by quantization.
-        name (string, optional) – Name of the output. Default is None. It’s used to print debug info for developers. Details: :ref:`api_guide_Name`
+        x (Tensor): Tensor or LoDTensor of any dimensions. Its dtype should be int32, int64, float32, float64.
+        y (Tensor): Tensor or LoDTensor of any dimensions. Its dtype should be int32, int64, float32, float64.
+        name (string, optional): For details, please refer to :ref:`api_guide_Name`. Generally, no setting is required. Default: None.
 
     Returns:
-        N-dimension tensor. A location into which the result is stored. It’s dimension equals with x
+        N-D Tensor. A location into which the result is stored. It’s dimension equals with x.
 
     Examples:
 
@@ -1079,10 +1081,9 @@ def fmin(x, y, name=None):
     return _elementwise_op(LayerHelper(op_type, **locals()))
 
 for func in [
-        add,
         multiply
 ]:
-    proto_dict = {'add': 'elementwise_add', 'multiply': 'elementwise_mul'}
+    proto_dict = {'multiply': 'elementwise_mul'}
     op_proto = OpProtoHolder.instance().get_op_proto(proto_dict[func.__name__])
 
     additional_args_lines = [