diff --git a/python/paddle/nn/layer/conv.py b/python/paddle/nn/layer/conv.py
index 5b6d295458cfa..c96c8b0872910 100644
--- a/python/paddle/nn/layer/conv.py
+++ b/python/paddle/nn/layer/conv.py
@@ -601,7 +601,7 @@ class Conv2D(_ConvNd):
         out_channels(int): The number of output channels produced by the convolution.
         kernel_size(int|list|tuple): The size of the convolving kernel.
         stride(int|list|tuple, optional): The stride size. If stride is a list/tuple, it must
-            contain three integers, (stride_H, stride_W). Otherwise, the
+            contain two integers, (stride_H, stride_W). Otherwise, the
             stride_H = stride_W = stride. The default value is 1.
         padding(int|str|tuple|list, optional): The padding size. Padding coule be in one of the following forms.
             1. a string in ['valid', 'same'].
@@ -611,9 +611,9 @@ class Conv2D(_ConvNd):
             5. a list or tuple of pairs of ints. It has the form [[pad_before, pad_after], [pad_before, pad_after], ...]. Note that, the batch dimension and channel dimension are also included. Each pair of integers correspond to the amount of padding for a dimension of the input. Padding in batch dimension and channel dimension should be [0, 0] or (0, 0).
             The default value is 0.
         dilation(int|list|tuple, optional): The dilation size. If dilation is a list/tuple, it must
-            contain three integers, (dilation_D, dilation_H, dilation_W). Otherwise, the
-            dilation_D = dilation_H = dilation_W = dilation. The default value is 1.
-        groups(int, optional): The groups number of the Conv3D Layer. According to grouped
+            contain two integers, (dilation_H, dilation_W). Otherwise, the
+            dilation_H = dilation_W = dilation. The default value is 1.
+        groups(int, optional): The groups number of the Conv2D Layer. According to grouped
             convolution in Alex Krizhevsky's Deep CNN paper: when group=2,
             the first half of the filters is only connected to the first half
             of the input channels, while the second half of the filters is only
diff --git a/python/paddle/static/nn/common.py b/python/paddle/static/nn/common.py
index 6af70651c72a0..41f1b82d7e419 100644
--- a/python/paddle/static/nn/common.py
+++ b/python/paddle/static/nn/common.py
@@ -860,7 +860,7 @@ def conv2d(
             of conv2d. If it is set to None or one attribute of ParamAttr, conv2d
             will create ParamAttr as param_attr. If the Initializer of the param_attr
             is not set, the parameter is initialized with :math:`Normal(0.0, std)`,
-            and the :math:`std` is :math:`(\\frac{2.0 }{filter\_elem\_num})^{0.5}`. Default: None.
+            and the :math:`std` is :math:`(\frac{2.0 }{filter\_elem\_num})^{0.5}`. Default: None.
         bias_attr (ParamAttr|bool|None, optional): The parameter attribute for the bias of conv2d.
             If it is set to False, no bias will be added to the output units.
             If it is set to None or one attribute of ParamAttr, conv2d