fix paddle.fleet en-doc for apis in dynamic mode (#27354)

* fix fleet dynamic-mode en-doc;test=develop

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

@@ -608,11 +608,18 @@ class Fleet(object):
     @dygraph_only
     def distributed_model(self, model):
         """
-        Return dygraph distributed data parallel model (Layer)
-        Only work in dygraph mode
+        Return distributed data parallel model (Only work in dygraph mode)
+
+        Args:
+            model (Layer): the user-defind model which inherits Layer.
+
+        Returns:
+            distributed data parallel model which inherits Layer.
 
         Examples:
+
             .. code-block:: python
+
                 import paddle
                 import paddle.nn as nn
                 from paddle.distributed import fleet
@@ -626,7 +633,6 @@ class Fleet(object):
                     def forward(self, x):
                         return self._linear2(self._linear1(x))
 
-            def train():
                 # 1. enable dynamic mode
                 paddle.disable_static()
 
@@ -658,8 +664,7 @@ class Fleet(object):
                 adam.step()
                 adam.clear_grad()
 
-            if __name__ == '__main__':
-                paddle.distributed.spawn(train)
+
         """
         assert model is not None
         self.model = paddle.DataParallel(model)
@@ -669,13 +674,14 @@ class Fleet(object):
     def state_dict(self):
         """
         Get state dict information from optimizer.
-        Only work in dygraph mode
+        (Only work in dygraph mode)
 
         Returns: 
             state_dict(dict) : dict contains all the Tensor used by optimizer
 
         Examples:
             .. code-block:: python
+
                 import numpy as np
                 import paddle
                 from paddle.distributed import fleet
@@ -700,15 +706,17 @@ class Fleet(object):
     def set_state_dict(self, state_dict):
         """
         Load optimizer state dict.
-        Only work in dygraph mode
+        (Only work in dygraph mode)
 
         Args: 
             state_dict(dict) : Dict contains all the Tensor needed by optimizer
 
-        Returns: None 
+        Returns:
+            None
 
         Examples:
             .. code-block:: python
+
                 import numpy as np
                 import paddle
                 from paddle.distributed import fleet
@@ -736,15 +744,17 @@ class Fleet(object):
     def set_lr(self, value):
         """
         Set the value of the learning rate manually in the optimizer. 
-        Only work in dygraph mode
+        (Only work in dygraph mode)
 
         Args:
             value (float|Tensor): the value of learning rate
 
-        Returns: None 
+        Returns: 
+            None 
 
         Examples:
             .. code-block:: python
+
                 import numpy as np
                 import paddle
                 from paddle.distributed import fleet
@@ -780,13 +790,14 @@ class Fleet(object):
     def get_lr(self):
         """
         Get current step learning rate.
-        Only work in dygraph mode
+        (Only work in dygraph mode)
 
         Returns:
             float: The learning rate of the current step.
 
         Examples:
             .. code-block:: python
+
                 import numpy as np
                 import paddle
                 from paddle.distributed import fleet
@@ -813,9 +824,10 @@ class Fleet(object):
     def step(self):
         """
         Execute the optimizer once.
-        Only work in dygraph mode
+        (Only work in dygraph mode)
 
-        Returns: None
+        Returns:
+            None
 
         Examples:
             .. code-block:: python
@@ -833,7 +845,6 @@ class Fleet(object):
                     def forward(self, x):
                         return self._linear2(self._linear1(x))
 
-            def train():
                 # 1. enable dynamic mode
                 paddle.disable_static()
 
@@ -865,8 +876,6 @@ class Fleet(object):
                 adam.step()
                 adam.clear_grad()
 
-            if __name__ == '__main__':
-                paddle.distributed.spawn(train)
 
         """
         # imitate target optimizer retrieval
@@ -875,10 +884,11 @@ class Fleet(object):
     @dygraph_only
     def clear_grad(self):
         """
-        Execute the optimizer once.
-        Only work in dygraph mode
+        Clear the gradients of all optimized parameters for model.
+        (Only work in dygraph mode)
 
-        Returns: None
+        Returns: 
+            None
 
         Examples:
             .. code-block:: python
@@ -896,7 +906,6 @@ class Fleet(object):
                     def forward(self, x):
                         return self._linear2(self._linear1(x))
 
-            def train():
                 # 1. enable dynamic mode
                 paddle.disable_static()
 
@@ -928,8 +937,6 @@ class Fleet(object):
                 adam.step()
                 adam.clear_grad()
 
-            if __name__ == '__main__':
-                paddle.distributed.spawn(train)
         """
         # imitate target optimizer retrieval
         return self.user_defined_optimizer.clear_grad()