diff --git a/mindspore/ops/composite/base.py b/mindspore/ops/composite/base.py
index 37c5f4a3c8..044c56f8de 100644
--- a/mindspore/ops/composite/base.py
+++ b/mindspore/ops/composite/base.py
@@ -75,6 +75,15 @@ def core(fn=None, **flags):
         fn (Function): Function to add flag. Default: None.
         flags (dict): The following flags can be set core, which indicates that this is a core function or
                       other flag. Default: None.
+
+    Supported Platforms:
+        ``Ascend`` ``GPU``
+
+    Examples:
+        >>> net = Net()
+        >>> net = core(net, predit=True)
+        >>> print(hasattr(net, '_mindspore_flags'))
+        True
     """
     # need set the attr and access on c++
 
diff --git a/mindspore/ops/composite/clip_ops.py b/mindspore/ops/composite/clip_ops.py
index 8f1b1c9af5..b68b5f26c1 100644
--- a/mindspore/ops/composite/clip_ops.py
+++ b/mindspore/ops/composite/clip_ops.py
@@ -42,6 +42,22 @@ def clip_by_value(x, clip_value_min, clip_value_max):
 
     Returns:
           Tensor, a clipped Tensor.
+
+    Supported Platforms:
+        ``Ascend`` ``GPU``
+
+    Examples:
+        >>> import numpy as np
+        >>> from mindspore import Tensor
+        >>> from mindspore.ops import composite as C
+        >>> import mindspore.common.dtype as mstype
+        >>> min_value = Tensor(5, mstype.float32)
+        >>> max_value = Tensor(20, mstype.float32)
+        >>> x = Tensor(np.array([[1., 25., 5., 7.], [4., 11., 6., 21.]]), mstype.float32)
+        >>> output = C.clip_by_value(x, min_value, max_value)
+        >>> print(output)
+        [[ 5. 20.  5.  7.]
+         [ 5. 11.  6. 20.]]
     """
     min_op = P.Minimum()
     max_op = P.Maximum()