diff --git a/python/paddle/fluid/initializer.py b/python/paddle/fluid/initializer.py
index df42516a43eaab8543928570cde233b5f34bcb29..4ffaedee55e59f9ba6b484ab40cc4a19fd4a13a0 100644
--- a/python/paddle/fluid/initializer.py
+++ b/python/paddle/fluid/initializer.py
@@ -1,4 +1,4 @@
-#   Copyright (c) 2018 PaddlePaddle Authors. All Rights Reserved.
+#   Copyright (c) 2022 PaddlePaddle Authors. All Rights Reserved.
 #
 # Licensed under the Apache License, Version 2.0 (the "License");
 # you may not use this file except in compliance with the License.
@@ -686,11 +686,9 @@ class MSRAInitializer(Initializer):
         \frac{gain}{\sqrt{{fan\_in}}}
 
     Args:
-        uniform (bool): whether to use uniform or normal distribution
-        fan_in (float32|None): fan_in (in_features) of trainable Tensor,\
-        If None, it will be infered automaticly. If you don't want to use in_features of the Tensor,\
-        you can set the value of 'fan_in' smartly by yourself. default is None.
-        seed (int32): random seed
+        uniform (bool, optional): whether to use uniform or normal distribution
+        fan_in (float32|None, optional): fan_in (in_features) of trainable Tensor, If None, it will be infered automaticly. If you don't want to use in_features of the Tensor, you can set the value of 'fan_in' smartly by yourself. default is None.
+        seed (int32, optional): random seed.
         negative_slope (float, optional): negative_slope (only used with leaky_relu). default is 0.0.
         nonlinearity(str, optional): the non-linear function. default is relu.
 
diff --git a/python/paddle/nn/initializer/kaiming.py b/python/paddle/nn/initializer/kaiming.py
index 8760c15096f8f6d707f31683327aaafe56a7ed70..38394eb5b93168e66929eed9e4490060edc5581e 100644
--- a/python/paddle/nn/initializer/kaiming.py
+++ b/python/paddle/nn/initializer/kaiming.py
@@ -1,4 +1,4 @@
-#   Copyright (c) 2020 PaddlePaddle Authors. All Rights Reserved.
+#   Copyright (c) 2022 PaddlePaddle Authors. All Rights Reserved.
 #
 # Licensed under the Apache License, Version 2.0 (the "License");
 # you may not use this file except in compliance with the License.
@@ -36,9 +36,7 @@ class KaimingNormal(MSRAInitializer):
         \frac{gain}{\sqrt{{fan\_in}}}
 
     Args:
-        fan_in (float32|None): fan_in (in_features) of trainable Tensor,\
-        If None, it will be infered automaticly. If you don't want to use in_features of the Tensor,\
-        you can set the value of 'fan_in' smartly by yourself. default is None.
+        fan_in (float32|None, optional): fan_in (in_features) of trainable Tensor, If None, it will be infered automaticly. If you don't want to use in_features of the Tensor, you can set the value of 'fan_in' smartly by yourself. default is None.
         negative_slope (float, optional): negative_slope (only used with leaky_relu). default is 0.0.
         nonlinearity(str, optional): the non-linear function. default is relu.
 
@@ -47,7 +45,7 @@ class KaimingNormal(MSRAInitializer):
 
     Examples:
         .. code-block:: python
-          :name: code-example1
+
             import paddle
             import paddle.nn as nn
 
@@ -84,9 +82,7 @@ class KaimingUniform(MSRAInitializer):
         x = gain \times \sqrt{\frac{3}{fan\_in}}
 
     Args:
-        fan_in (float32|None): fan_in (in_features) of trainable Tensor,\
-        If None, it will be infered automaticly. If you don't want to use in_features of the Tensor,\
-        you can set the value of 'fan_in' smartly by yourself. default is None.
+        fan_in (float32|None, optional): fan_in (in_features) of trainable Tensor, If None, it will be infered automaticly. If you don't want to use in_features of the Tensor, you can set the value of 'fan_in' smartly by yourself. default is None.
         negative_slope (float, optional): negative_slope (only used with leaky_relu). default is 0.0.
         nonlinearity(str, optional): the non-linear function. default is relu.
 
@@ -95,7 +91,7 @@ class KaimingUniform(MSRAInitializer):
 
     Examples:
         .. code-block:: python
-          :name: code-example1
+
             import paddle
             import paddle.nn as nn