diff --git a/mindspore/python/mindspore/ops/operations/sparse_ops.py b/mindspore/python/mindspore/ops/operations/sparse_ops.py
index 4ecac914099..dfcfe1e3aa7 100644
--- a/mindspore/python/mindspore/ops/operations/sparse_ops.py
+++ b/mindspore/python/mindspore/ops/operations/sparse_ops.py
@@ -810,29 +810,32 @@ class Sspaddmm(Primitive):
 
 class SparseAddmm(Primitive):
     """
-    Multiplies sparse matrix `A` by dense matrix `B` * `alpha` and add dense matrix `C` * `beta`.
-    The rank of sparse matrix and dense matrix must equal to `2`.
+    Multiplies sparse matrix `x1` by dense matrix `x2` * `alpha` and add dense matrix `x3` * `beta`.
+    The rank of sparse matrix and dense matrix must equal to `2`. The sparse matrix `x1` is formulated by `x1_indices`,
+    `x1_values` and `x1_shape`.
 
     Inputs:
-        - **indices** (Tensor) - A 2-D Tensor, represents the position of the element in the sparse tensor.
-          Support int32, int64, each element value should be a non-negative int number. The shape is :math:`(n, 2)`.
-        - **values** (Tensor) - A 1-D Tensor, represents the value corresponding to the position in the `indices`.
+        - **x1_indices** (Tensor) - A 2-D Tensor, represents the position of the element in the sparse tensor.
+          Support int32, int64, each element value should be a non-negative int number. The shape is :math:`(N, 2)`.
+        - **x1_values** (Tensor) - A 1-D Tensor, represents the value corresponding to the position in the `indices`.
           Support float32, float64, int8, int16, int32, int64, uint8, uint16, uint32, uint64.
-          The shape should be :math:`(n,)`.
-        - **sparse_shape** (Tensor) - A positive int tuple which specifies the shape of sparse tensor.
-          Support int32, int64, should have 2 elements, represent sparse tensor shape is :math:`(N, C)`.
-        - **x2_dense** (Tensor) - A 2-D Tensor, the dtype is same as `values`.
-        - **x3_dense** (Tensor) - A 2-D Tensor, the dtype is same as `values`.
-        - **alpha** (Tensor) - A 1-D Tensor, the dtype is same as `values`.
-        - **beta** (Tensor) - A 1-D Tensor, the dtype is same as `values`.
+          The shape should be :math:`(N,)`.
+        - **x1_shape** (Tensor) - A positive int tuple which specifies the shape of sparse tensor.
+          Support int32, int64, should have 2 elements, represent sparse tensor shape is :math:`(Q, P)`.
+        - **x2** (Tensor) - A 2-D Dense Tensor, the dtype is same as `values`. The shape should be :math:`(P, M)`.
+        - **x3** (Tensor) - A 2-D Dense Tensor, the dtype is same as `values`. The shape should be :math:`(Q, M)`.
+        - **alpha** (Tensor) - A 1-D Tensor, the dtype is same as `values`. The shape should be :math:`(1,)`.
+        - **beta** (Tensor) - A 1-D Tensor, the dtype is same as `values`. The shape should be :math:`(1,)`.
 
     Outputs:
-        Tensor, the dtype is the same as `values`.
+        Tensor, the dtype is the same as `x1_values`. The shape is the same as `x3`.
 
     Raises:
-        TypeError: If dtype of `indices`, dtype of `values` and dtype of `dense` don't meet the parameter description.
-        ValueError: If `sparse_shape`, shape of `indices, shape of `values`, and shape of `dense` don't meet the
-                    parameter description.
+        TypeError: If dtype of `x1_indices`, dtype of `x1_values` and dtype of `dense` don't meet the parameter
+                   description.
+        ValueError: If shape of `x1_indices`, shape of `x1_values`, shape of `alpha`,
+                    and shape of `beta` don't meet the parameter description.
+        RuntimeError: If `x1_shape`, shape of `x2`, shape of `x3` don't meet the parameter description.
 
     Supported Platforms:
         ``Ascend`` ``CPU``