diff --git a/mindspore/nn/optim/adam.py b/mindspore/nn/optim/adam.py
index d5d2d2d4e00..b9cfa75af78 100755
--- a/mindspore/nn/optim/adam.py
+++ b/mindspore/nn/optim/adam.py
@@ -553,8 +553,8 @@ class AdamOffload(Optimizer):
         >>> conv_params = list(filter(lambda x: 'conv' in x.name, net.trainable_params()))
         >>> no_conv_params = list(filter(lambda x: 'conv' not in x.name, net.trainable_params()))
         >>> group_params = [{'params': conv_params, 'weight_decay': 0.01},
-        >>>                 {'params': no_conv_params, 'lr': 0.01},
-        >>>                 {'order_params': net.trainable_params()}]
+        ...                 {'params': no_conv_params, 'lr': 0.01},
+        ...                 {'order_params': net.trainable_params()}]
         >>> optim = nn.AdamOffload(group_params, learning_rate=0.1, weight_decay=0.0)
         >>> # The conv_params's parameters will use default learning rate of 0.1 and weight decay of 0.01.
         >>> # The no_conv_params's parameters will use learning rate of 0.01 and defaule weight decay of 0.0.
diff --git a/mindspore/nn/wrap/grad_reducer.py b/mindspore/nn/wrap/grad_reducer.py
index b3cd4c1e4c4..9f1e8a16a79 100644
--- a/mindspore/nn/wrap/grad_reducer.py
+++ b/mindspore/nn/wrap/grad_reducer.py
@@ -265,7 +265,7 @@ class DistributedGradReducer(Cell):
         >>>
         >>> device_id = int(os.environ["DEVICE_ID"])
         >>> context.set_context(mode=context.GRAPH_MODE, device_target="Ascend", save_graphs=True,
-        >>>                     device_id=int(device_id))
+        ...                     device_id=int(device_id))
         >>> init()
         >>> context.reset_auto_parallel_context()
         >>> context.set_auto_parallel_context(parallel_mode=ParallelMode.DATA_PARALLEL)
diff --git a/mindspore/ops/composite/base.py b/mindspore/ops/composite/base.py
index e5610b66ce6..1ecbff297ce 100644
--- a/mindspore/ops/composite/base.py
+++ b/mindspore/ops/composite/base.py
@@ -384,9 +384,11 @@ class MultitypeFuncGraph(MultitypeFuncGraph_):
         >>> @add.register("Tensor", "Tensor")
         ... def add_tensor(x, y):
         ...     return tensor_add(x, y)
-        >>> add(1, 2)
+        >>> ourput = add(1, 2)
+        >>> print(output)
         3
-        >>> add(Tensor(1, mstype.float32), Tensor(2, mstype.float32))
+        >>> output = add(Tensor(1, mstype.float32), Tensor(2, mstype.float32))
+        >>> print(output)
         Tensor(shape=[], dtype=Float32, 3)
     """
 
@@ -470,11 +472,13 @@ class HyperMap(HyperMap_):
         ...     return F.square(x)
         >>>
         >>> common_map = HyperMap()
-        >>> common_map(square, nest_tensor_list)
+        >>> output = common_map(square, nest_tensor_list)
+        >>> print(output)
         ((Tensor(shape=[], dtype=Float32, 1), Tensor(shape=[], dtype=Float32, 4)),
         (Tensor(shape=[], dtype=Float32, 9), Tensor(shape=[], dtype=Float32, 16))
         >>> square_map = HyperMap(square)
-        >>> square_map(nest_tensor_list)
+        >>> output = square_map(nest_tensor_list)
+        >>> print(output)
         ((Tensor(shape=[], dtype=Float32, 1), Tensor(shape=[], dtype=Float32, 4)),
         (Tensor(shape=[], dtype=Float32, 9), Tensor(shape=[], dtype=Float32, 16))
     """
@@ -531,10 +535,12 @@ class Map(Map_):
         ...     return F.square(x)
         >>>
         >>> common_map = Map()
-        >>> common_map(square, tensor_list)
+        >>> output = common_map(square, tensor_list)
+        >>> print(output)
         (Tensor(shape=[], dtype=Float32, 1), Tensor(shape=[], dtype=Float32, 4), Tensor(shape=[], dtype=Float32, 9))
         >>> square_map = Map(square)
-        >>> square_map(tensor_list)
+        >>> output = square_map(tensor_list)
+        >>> print(output)
         (Tensor(shape=[], dtype=Float32, 1), Tensor(shape=[], dtype=Float32, 4), Tensor(shape=[], dtype=Float32, 9))
     """
 
diff --git a/mindspore/ops/primitive.py b/mindspore/ops/primitive.py
index b06299f498a..4a8ef37b5a0 100644
--- a/mindspore/ops/primitive.py
+++ b/mindspore/ops/primitive.py
@@ -35,9 +35,9 @@ class Primitive(Primitive_):
         >>> # or work with prim_attr_register:
         >>> # init a Primitive class with attr1 and attr2
         >>> class Add(Primitive):
-        >>>     @prim_attr_register
-        >>>     def __init__(self, attr1, attr2):
-        >>>         # check attr1 and attr2 or do some initializations
+        ...     @prim_attr_register
+        ...     def __init__(self, attr1, attr2):
+        ...         # check attr1 and attr2 or do some initializations
         >>> # init a Primitive obj with attr1=1 and attr2=2
         >>> add = Add(attr1=1, attr2=2)
     """