diff --git a/python/paddle/nn/functional/common.py b/python/paddle/nn/functional/common.py
index 6204a4fdbb82bb992d364547ebe3f4ec5afd6298..f18a7749791e7bfa6e642a701f29e3c59c29ebaf 100644
--- a/python/paddle/nn/functional/common.py
+++ b/python/paddle/nn/functional/common.py
@@ -1996,7 +1996,7 @@ def class_center_sample(label, num_classes, num_samples, group=None):
     For more information, Partial FC: Training 10 Million Identities on a Single Machine
     arxiv: https://arxiv.org/abs/2010.05222
 
-    .. hint::
+    Note:
         If the number of the positive class centers is greater than the input num_samples, it keeps all the positive
         class centers and the shape of sampled_class_center will be [num_positive_class_centers].
 
diff --git a/python/paddle/nn/layer/rnn.py b/python/paddle/nn/layer/rnn.py
index 61e731c045a08b93b263b1a2714dd014166cd53a..dbdb83ba5a7e9b71d15c4d691e9b2a42732f6521 100644
--- a/python/paddle/nn/layer/rnn.py
+++ b/python/paddle/nn/layer/rnn.py
@@ -1164,7 +1164,7 @@ class RNN(Layer):
         - **final_states** (Tensor|list|tuple): final states of the cell. Tensor or a possibly nested structure of tensors which has the same structure with intial state. Each tensor in final states has the same shape and dtype as the corresponding tensor in initial states.
 
     Notes:
-        This class is a low level API for wrapping rnn cell into a RNN network.
+        This class is a low-level API for wrapping rnn cell into a RNN network.
         Users should take care of the state of the cell. If `initial_states` is
         passed to the `forward` method, make sure that it satisfies the
         requirements of the cell.