[Add] Paddle 代码 CI 中引入 xdoctest 检查

python/paddle/distribution/beta.py

@@ -55,31 +55,35 @@ class Beta(exponential_family.ExponentialFamily):
 
         .. code-block:: python
 
-            import paddle
-
-            # scale input
-            beta = paddle.distribution.Beta(alpha=0.5, beta=0.5)
-            print(beta.mean)
-            # Tensor(shape=[], dtype=float32, place=CUDAPlace(0), stop_gradient=True,
-            #        0.50000000)
-            print(beta.variance)
-            # Tensor(shape=[], dtype=float32, place=CUDAPlace(0), stop_gradient=True,
-            #        0.12500000)
-            print(beta.entropy())
-            # Tensor(shape=[], dtype=float32, place=CUDAPlace(0), stop_gradient=True,
-            #        0.12500000)
-
-            # tensor input with broadcast
-            beta = paddle.distribution.Beta(alpha=paddle.to_tensor([0.2, 0.4]), beta=0.6)
-            print(beta.mean)
-            # Tensor(shape=[2], dtype=float32, place=CUDAPlace(0), stop_gradient=True,
-            #        [0.25000000, 0.40000001])
-            print(beta.variance)
-            # Tensor(shape=[2], dtype=float32, place=CUDAPlace(0), stop_gradient=True,
-            #        [0.10416666, 0.12000000])
-            print(beta.entropy())
-            # Tensor(shape=[2], dtype=float32, place=CUDAPlace(0), stop_gradient=True,
-            #        [-1.91923141, -0.38095069])
+            >>> import paddle
+
+            >>> # scale input
+            >>> beta = paddle.distribution.Beta(alpha=0.5, beta=0.5)
+            >>> print(beta.mean)
+            Tensor(shape=[1], dtype=float32, place=Place(cpu), stop_gradient=True,
+            [0.50000000])
+
+            >>> print(beta.variance)
+            Tensor(shape=[1], dtype=float32, place=Place(cpu), stop_gradient=True,
+            [0.12500000])
+
+            >>> print(beta.entropy())
+            Tensor(shape=[1], dtype=float32, place=Place(cpu), stop_gradient=True,
+            [-0.24156499])
+
+            >>> # tensor input with broadcast
+            >>> beta = paddle.distribution.Beta(alpha=paddle.to_tensor([0.2, 0.4]), beta=0.6)
+            >>> print(beta.mean)
+            Tensor(shape=[2], dtype=float32, place=Place(cpu), stop_gradient=True,
+            [0.25000000, 0.40000001])
+
+            >>> print(beta.variance)
+            Tensor(shape=[2], dtype=float32, place=Place(cpu), stop_gradient=True,
+            [0.10416666, 0.12000000])
+
+            >>> print(beta.entropy())
+            Tensor(shape=[2], dtype=float32, place=Place(cpu), stop_gradient=True,
+            [-1.91923141, -0.38095081])
     """
 
     def __init__(self, alpha, beta):

python/requirements.txt

@@ -7,3 +7,4 @@ decorator
 astor
 paddle_bfloat==0.1.7
 opt_einsum==3.3.0
+xdoctest