diff --git a/mindspore/python/mindspore/ops/operations/math_ops.py b/mindspore/python/mindspore/ops/operations/math_ops.py
index f274aa4491d..302f5fc5b34 100644
--- a/mindspore/python/mindspore/ops/operations/math_ops.py
+++ b/mindspore/python/mindspore/ops/operations/math_ops.py
@@ -3596,7 +3596,7 @@ class ApproximateEqual(_LogicBinaryOp):
 
     Examples:
         >>> x = Tensor(np.array([1, 2, 3]), mindspore.float32)
-        >>> y = Tensor(np.array([2, 4, 6]), mindspore.float32)
+        >>> y = Tensor(np.array([2, 3, 6]), mindspore.float32)
         >>> approximate_equal = ops.ApproximateEqual(2.)
         >>> output = approximate_equal(x, y)
         >>> print(output)
diff --git a/mindspore/python/mindspore/ops/operations/nn_ops.py b/mindspore/python/mindspore/ops/operations/nn_ops.py
index 59befd181d1..1edb24cba6f 100644
--- a/mindspore/python/mindspore/ops/operations/nn_ops.py
+++ b/mindspore/python/mindspore/ops/operations/nn_ops.py
@@ -5988,12 +5988,12 @@ class SparseApplyAdagrad(Primitive):
         ...
         >>> net = Net()
         >>> grad = Tensor(np.array([[[0.7]]]).astype(np.float32))
-        >>> indices = Tensor([0], mindspore.int32)
+        >>> indices = Tensor([1], mindspore.int32)
         >>> output = net(grad, indices)
         >>> print(output)
         (Tensor(shape=[1, 1, 1], dtype=Float32, value=
-        [[[1.99999988e-01]]]), Tensor(shape=[1, 1, 1], dtype=Float32, value=
-        [[[1.00000001e-01]]]))
+        [[[ 2.00000003e-01]]]), Tensor(shape=[1, 1, 1], dtype=Float32, value=
+        [[[ 1.00000001e-01]]]))
     """
 
     __mindspore_signature__ = (