diff --git a/python/paddle/incubate/nn/functional/fused_rotary_position_embedding.py b/python/paddle/incubate/nn/functional/fused_rotary_position_embedding.py
index fe591a6be48fd..3fd80ffbaaa80 100644
--- a/python/paddle/incubate/nn/functional/fused_rotary_position_embedding.py
+++ b/python/paddle/incubate/nn/functional/fused_rotary_position_embedding.py
@@ -46,33 +46,44 @@ def fused_rotary_position_embedding(
 
         ..  code-block:: python
 
-            # required: gpu
-            import paddle
-            from paddle.incubate.nn.functional import fused_rotary_position_embedding
-
-            # batch_size = 2
-            # seq_len = 8
-            # num_heads = 2
-            # head_dim = 10
-
-            # q, k, v: [batch_size, seq_len, num_heads, head_dim]
-            q = paddle.randn([2, 8, 2, 10], dtype='float16')
-            k = paddle.randn([2, 8, 2, 10], dtype='float16')
-            v = paddle.randn([2, 8, 2, 10], dtype='float16')
-
-            # sin, cos: [1, seq_len, 1, head_dim]
-            x = paddle.randn([1, 8, 1, 10], dtype='float16')
-            y = paddle.randn([1, 8, 1, 10], dtype='float16')
-            sin = paddle.sin(x)
-            cos = paddle.cos(y)
-
-            # position_ids: [batch_size, seq_len]
-            position_ids = paddle.randint(high=8, shape=[2, 8], dtype='int64')
-
-            # out_q, out_k, out_v: [batch_size, seq_len, num_heads, head_dim]
-            out_q, out_k, out_v = fused_rotary_position_embedding(q, k, v, sin=sin, cos=cos, position_ids=position_ids, use_neox_rotary_style=False)
-            print(out_q.shape)
-            # [2, 8, 2, 10]
+            >>> # required: gpu
+            >>> # doctest: +REQUIRES(env:GPU)
+            >>> import paddle
+            >>> from paddle.incubate.nn.functional import fused_rotary_position_embedding
+
+            >>> # batch_size = 2
+            >>> # seq_len = 2
+            >>> # num_heads = 2
+            >>> # head_dim = 2
+
+            >>> paddle.seed(1024)
+
+            >>> # q, k, v: [batch_size, seq_len, num_heads, head_dim]
+            >>> q = paddle.randn([2, 2, 2, 2], dtype='float16')
+            >>> k = paddle.randn([2, 2, 2, 2], dtype='float16')
+            >>> v = paddle.randn([2, 2, 2, 2], dtype='float16')
+
+            >>> # sin, cos: [1, seq_len, 1, head_dim]
+            >>> x = paddle.randn([1, 2, 1, 2], dtype='float16')
+            >>> y = paddle.randn([1, 2, 1, 2], dtype='float16')
+            >>> sin = paddle.sin(x)
+            >>> cos = paddle.cos(y)
+
+            >>> # position_ids: [batch_size, seq_len]
+            >>> position_ids = paddle.randint(high=2, shape=[2, 2], dtype='int64')
+
+            >>> # out_q, out_k, out_v: [batch_size, seq_len, num_heads, head_dim]
+            >>> out_q, out_k, out_v = fused_rotary_position_embedding(q, k, v, sin=sin, cos=cos, position_ids=position_ids, use_neox_rotary_style=False)
+            >>> print(out_q)
+            Tensor(shape=[2, 2, 2, 2], dtype=float16, place=Place(gpu:0), stop_gradient=True,
+            [[[[-0.54931641,  0.64990234],
+               [-1.08691406,  1.18261719]],
+              [[ 0.57812500,  0.11749268],
+               [-0.63281250,  0.15551758]]],
+             [[[-0.77050781,  0.07733154],
+               [-0.73730469, -0.16735840]],
+              [[ 0.07116699, -0.90966797],
+               [-0.03628540, -0.20202637]]]])
     """
     if in_dynamic_mode():
         return _C_ops.fused_rotary_position_embedding(