[xdoctest] reformat example code with google style in No. 246 and 247 (#56475)

python/paddle/incubate/autotune.py

@@ -56,29 +56,29 @@ def set_config(config=None):
     Examples:
         .. code-block:: python
 
-            import paddle
-            import json
-
-            # config is a dict.
-            config = {
-                "kernel": {
-                    "enable": True,
-                    "tuning_range": [1, 5],
-                },
-                "layout": {
-                    "enable": True,
-                },
-                "dataloader": {
-                    "enable": True,
-                }
-            }
-            paddle.incubate.autotune.set_config(config)
-
-            # config is the path of json file.
-            config_json = json.dumps(config)
-            with open('config.json', 'w') as json_file:
-                json_file.write(config_json)
-            paddle.incubate.autotune.set_config('config.json')
+            >>> import paddle
+            >>> import json
+
+            >>> # config is a dict.
+            >>> config = {
+            ...     "kernel": {
+            ...         "enable": True,
+            ...         "tuning_range": [1, 5],
+            ...     },
+            ...     "layout": {
+            ...         "enable": True,
+            ...     },
+            ...     "dataloader": {
+            ...         "enable": True,
+            ...     }
+            >>> }
+            >>> paddle.incubate.autotune.set_config(config)
+
+            >>> # config is the path of json file.
+            >>> config_json = json.dumps(config)
+            >>> with open('config.json', 'w') as json_file:
+            ...     json_file.write(config_json)
+            >>> paddle.incubate.autotune.set_config('config.json')
 
     """
     if config is None:

python/paddle/incubate/distributed/fleet/base.py

@@ -343,12 +343,13 @@ class DistributedOptimizer(metaclass=abc.ABCMeta):
         Examples:
             .. code-block:: python
 
-                loss = network()
-                optimizer = fluid.optimizer.SGD(learning_rate=0.1)
-                params_grads = optimizer.backward(loss)
-                # you may append operations for params_grads here
-                # ...
-                optimizer.apply_gradients(params_grads)
+                >>> # doctest: +SKIP('The network is not defined.')
+                >>> loss = network()
+                >>> optimizer = fluid.optimizer.SGD(learning_rate=0.1)
+                >>> params_grads = optimizer.backward(loss)
+                >>> # you may append operations for params_grads here
+                >>> # ...
+                >>> optimizer.apply_gradients(params_grads)
         """
         pass