diff --git a/python/paddle/incubate/xpu/resnet_block.py b/python/paddle/incubate/xpu/resnet_block.py
index 6690b2543c31dc36e0838420e8c38af19c670ce6..081583b6a8c4080c3c13b81f414d585697f56cc1 100644
--- a/python/paddle/incubate/xpu/resnet_block.py
+++ b/python/paddle/incubate/xpu/resnet_block.py
@@ -398,33 +398,34 @@ class ResNetBasicBlock(Layer):
     Examples:
         .. code-block:: python
 
-            # required: xpu
-            import paddle
-            from paddle.incubate.xpu.resnet_block import ResNetBasicBlock
-
-            ch_in = 4
-            ch_out = 8
-            x = paddle.uniform((2, ch_in, 16, 16), dtype='float32', min=-1., max=1.)
-            resnet_basic_block = ResNetBasicBlock(num_channels1=ch_in,
-                                                num_filter1=ch_out,
-                                                filter1_size=3,
-                                                num_channels2=ch_out,
-                                                num_filter2=ch_out,
-                                                filter2_size=3,
-                                                num_channels3=ch_in,
-                                                num_filter3=ch_out,
-                                                filter3_size=1,
-                                                stride1=1,
-                                                stride2=1,
-                                                stride3=1,
-                                                act='relu',
-                                                padding1=1,
-                                                padding2=1,
-                                                padding3=0,
-                                                has_shortcut=True)
-            out = resnet_basic_block.forward(x)
-
-            print(out.shape) # [2, 8, 16, 16]
+            >>> # doctest: +REQUIRES(env: XPU)
+            >>> import paddle
+            >>> from paddle.incubate.xpu.resnet_block import ResNetBasicBlock
+
+            >>> ch_in = 4
+            >>> ch_out = 8
+            >>> x = paddle.uniform((2, ch_in, 16, 16), dtype='float32', min=-1., max=1.)
+            >>> resnet_basic_block = ResNetBasicBlock(num_channels1=ch_in,
+            ...                                     num_filter1=ch_out,
+            ...                                     filter1_size=3,
+            ...                                     num_channels2=ch_out,
+            ...                                     num_filter2=ch_out,
+            ...                                     filter2_size=3,
+            ...                                     num_channels3=ch_in,
+            ...                                     num_filter3=ch_out,
+            ...                                     filter3_size=1,
+            ...                                     stride1=1,
+            ...                                     stride2=1,
+            ...                                     stride3=1,
+            ...                                     act='relu',
+            ...                                     padding1=1,
+            ...                                     padding2=1,
+            ...                                     padding3=0,
+            ...                                     has_shortcut=True)
+            >>> out = resnet_basic_block.forward(x)
+
+            >>> print(out.shape)
+            [2, 8, 16, 16]
 
     """