diff --git a/python/paddle/nn/functional/conv.py b/python/paddle/nn/functional/conv.py
index 26f07c2f9a11c7f7e3a70ae70a85ea4a2a72ed14..f1d66a9e3a1b573c02803f8174f8f6ddc180a400 100644
--- a/python/paddle/nn/functional/conv.py
+++ b/python/paddle/nn/functional/conv.py
@@ -1244,10 +1244,10 @@ def conv3d(x,
             where M is the number of filters(output channels), g is the number of groups,
             kD, kH, kW are the filter's depth, height and width respectively.
         bias (Tensor, optional): The bias, a Tensor of shape [M, ].
-        stride (int|list|tuple): The stride size. It means the stride in convolution. If stride is a 
+        stride (int|list|tuple, optional): The stride size. It means the stride in convolution. If stride is a 
             list/tuple, it must contain three integers, (stride_depth, stride_height, stride_width). 
             Otherwise, stride_depth = stride_height = stride_width = stride. Default: stride = 1.
-        padding (string|int|list|tuple): The padding size. It means the number of zero-paddings 
+        padding (string|int|list|tuple, optional): The padding size. It means the number of zero-paddings 
             on both sides for each dimension. If `padding` is a string, either 'VALID' or
             'SAME' which is the padding algorithm. If padding size is a tuple or list,
             it could be in three forms: `[pad_depth, pad_height, pad_width]` or
@@ -1257,20 +1257,20 @@ def conv3d(x,
             when `data_format` is `"NDHWC"`, `padding` can be in the form
             `[[0,0], [pad_depth_front, pad_depth_back], [pad_height_top, pad_height_bottom], [pad_width_left, pad_width_right], [0,0]]`.
             Default: padding = 0.
-        dilation (int|list|tuple): The dilation size. It means the spacing between the kernel points. 
+        dilation (int|list|tuple, optional): The dilation size. It means the spacing between the kernel points. 
             If dilation is a list/tuple, it must contain three integers, (dilation_depth, dilation_height,
             dilation_width). Otherwise, dilation_depth = dilation_height = dilation_width = dilation. 
             Default: dilation = 1.
-        groups (int): The groups number of the Conv3D Layer. According to grouped
+        groups (int, optional): The groups number of the Conv3D 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
             connected to the second half of the input channels. Default: groups=1
         data_format (str, optional): Specify the data format of the input, and the data format of the output 
-            will be consistent with that of the input. An optional string from: `"NCHW"`, `"NHWC"`.
-            The default is `"NCHW"`. When it is `"NCHW"`, the data is stored in the order of:
-            `[batch_size, input_channels, input_height, input_width]`.
-        name(str|None): For detailed information, please refer 
+            will be consistent with that of the input. An optional string from: `"NCDHW"`, `"NDHWC"`.
+            The default is `"NCDHW"`. When it is `"NCDHW"`, the data is stored in the order of:
+            `[batch_size, input_channels, input_depth, input_height, input_width]`.
+        name(str|None, optional): For detailed information, please refer 
            to :ref:`api_guide_Name`. Usually name is no need to set and 
            None by default.