[CodeStyle][py2][U008] remove unnecessary args in `super()` for some example code (#47643)

* [CodeStyle][py2][U008] remove unnecessary args in `super()` for some example code

* empty commit, test=document_fix

python/paddle/distributed/spawn.py

@@ -531,7 +531,7 @@ def spawn(func, args=(), nprocs=-1, join=True, daemon=False, **options):
 
             class LinearNet(nn.Layer):
                 def __init__(self):
-                    super(LinearNet, self).__init__()
+                    super().__init__()
                     self._linear1 = nn.Linear(10, 10)
                     self._linear2 = nn.Linear(10, 1)
 

python/paddle/fluid/dygraph/jit.py

@@ -1573,7 +1573,7 @@ class TracedLayer:
 
                 class ExampleLayer(paddle.nn.Layer):
                     def __init__(self):
-                        super(ExampleLayer, self).__init__()
+                        super().__init__()
                         self._fc = paddle.nn.Linear(3, 10)
 
                     def forward(self, input):
@@ -1591,7 +1591,7 @@ class TracedLayer:
                 print(out_static_graph[0].shape) # (2, 10)
 
                 # save the static graph model for inference
-                static_layer.save_inference_model(dirname='./saved_infer_model')
+                static_layer.save_inference_model('./saved_infer_model')
 
         """
         assert isinstance(
@@ -1623,7 +1623,7 @@ class TracedLayer:
 
                 class ExampleLayer(paddle.nn.Layer):
                     def __init__(self):
-                        super(ExampleLayer, self).__init__()
+                        super().__init__()
                         self._fc = paddle.nn.Linear(3, 10)
 
                     def forward(self, input):
@@ -1728,7 +1728,7 @@ class TracedLayer:
 
                 class ExampleLayer(paddle.nn.Layer):
                     def __init__(self):
-                        super(ExampleLayer, self).__init__()
+                        super().__init__()
                         self._fc = paddle.nn.Linear(3, 10)
 
                     def forward(self, input):