Fixed the dead link bug in the API documentation (#48969)

* first pr

* Revise nn.py

* Revise nn.py 2.0

* Revise rnn.py;test=document_fix

* test=document_fix
Co-authored-by: NLigoml <39876205+Ligoml@users.noreply.github.com>

python/paddle/distributed/launch/main.py

@@ -36,7 +36,7 @@ def launch():
 
 
     Base Parameters:
-        - ``--master``: The master/rendezvous server, support http:// and etcd://, default with http://. e.g., ``--master=127.0.0.1:8080``. Default ``--master=None``.
+        - ``--master``: The master/rendezvous server, support ``http://`` and ``etcd://``, default with ``http://``. e.g., ``--master=127.0.0.1:8080``. Default ``--master=None``.
 
         - ``--rank``: The rank of the node, can be auto assigned by master. Default ``--rank=-1``.
 

python/paddle/fluid/dygraph/nn.py

@@ -37,6 +37,7 @@ from ..data_feeder import (
     check_type,
     check_dtype,
 )
+
 from ..param_attr import ParamAttr
 from ..initializer import Normal, Constant, NumpyArrayInitializer
 from .. import unique_name

python/paddle/fluid/framework.py

@@ -1384,7 +1384,7 @@ class Variable(metaclass=VariableMetaClass):
                                                 shape=[-1, 23, 48],
                                                 dtype='float32')
 
-        In `Dygraph <../../user_guides/howto/dygraph/DyGraph.html>`_  Mode:
+        In Dygraph  Mode:
 
         .. code-block:: python
 
@@ -1861,7 +1861,7 @@ class Variable(metaclass=VariableMetaClass):
         """
         Indicating if we stop gradient from current Variable
 
-        **Notes: This Property has default value as** ``True`` **in** `Dygraph <../../user_guides/howto/dygraph/DyGraph.html>`_ **mode, while Parameter's default value is False. However, in Static Graph Mode all Variable's default stop_gradient value is** ``False``
+        **Notes: This Property has default value as** ``True`` **in** Dygraph **mode, while Parameter's default value is False. However, in Static Graph Mode all Variable's default stop_gradient value is** ``False``
 
         Examples:
           .. code-block:: python
@@ -1903,7 +1903,7 @@ class Variable(metaclass=VariableMetaClass):
 
             **1. All Variable's persistable is** ``False`` **except Parameters.**
 
-            **2. In** `Dygraph <../../user_guides/howto/dygraph/DyGraph.html>`_ **mode, this property should not be changed**
+            **2. In** Dygraph **mode, this property should not be changed**
 
         Examples:
           .. code-block:: python
@@ -1952,7 +1952,7 @@ class Variable(metaclass=VariableMetaClass):
         """
         Indicating name of current Variable
 
-        **Notes: If it has two or more Varaible share the same name in the same** :ref:`api_guide_Block_en` **, it means these Variable will share content in no-** `Dygraph <../../user_guides/howto/dygraph/DyGraph.html>`_ **mode. This is how we achieve Parameter sharing**
+        **Notes: If it has two or more Varaible share the same name in the same** :ref:`api_guide_Block_en` **, it means these Variable will share content in no-** Dygraph **mode. This is how we achieve Parameter sharing**
 
         Examples:
           .. code-block:: python
@@ -1982,7 +1982,7 @@ class Variable(metaclass=VariableMetaClass):
           import paddle.fluid as fluid
 
           x = fluid.data(name="x", shape=[-1, 23, 48], dtype='float32')
-          print(x.grad_name) # output is "x@GRAD"
+          print(x.grad_name) # output is ``x@GRAD``
 
         """
         return self.name + "@GRAD"
@@ -2043,7 +2043,7 @@ class Variable(metaclass=VariableMetaClass):
 
             **1. This is a read-only property**
 
-            **2. Don't support this property in** `Dygraph <../../user_guides/howto/dygraph/DyGraph.html>`_ **mode, it's value should be** ``0(int)``
+            **2. Don't support this property in** Dygraph **mode, it's value should be** ``0(int)``
 
         Examples:
           .. code-block:: python

python/paddle/fluid/layers/rnn.py

@@ -494,7 +494,6 @@ def dynamic_lstm(
     name=None,
 ):
     r"""
-	:api_attr: Static Graph
 
     **Note**:
         1. This OP only supports LoDTensor as inputs. If you need to deal with Tensor, please use :ref:`api_fluid_layers_lstm` .
@@ -684,12 +683,11 @@ def lstm(
     seed=-1,
 ):
     r"""
-	:api_attr: Static Graph
 
     **Note**:
         This OP only supports running on GPU devices.
 
-    This OP implements LSTM operation - `Hochreiter, S., & Schmidhuber, J. (1997) <http://deeplearning.cs.cmu.edu/pdfs/Hochreiter97_lstm.pdf>`_ .
+    This OP implements LSTM operation - `Hochreiter, S., & Schmidhuber, J. (1997) <https://blog.xpgreat.com/file/lstm.pdf>`_ .
 
     The implementation of this OP does not include diagonal/peephole connections.
     Please refer to `Gers, F. A., & Schmidhuber, J. (2000) <ftp://ftp.idsia.ch/pub/juergen/TimeCount-IJCNN2000.pdf>`_ .
@@ -742,7 +740,6 @@ def lstm(
                          If set None, default initializer will be used. Default: None.
         seed(int, optional): Seed for dropout in LSTM, If it's -1, dropout will use random seed. Default: 1.
 
-
     Returns:
         tuple ( :ref:`api_guide_Variable_en` , :ref:`api_guide_Variable_en` , :ref:`api_guide_Variable_en` ) :
 
@@ -757,7 +754,6 @@ def lstm(
                           shape is :math:`[num\_layers, batch\_size, hidden\_size]` \
                           if is_bidirec set to True, shape will be :math:`[num\_layers*2, batch\_size, hidden\_size]`
 
-
     Examples:
         .. code-block:: python
 
@@ -875,7 +871,6 @@ def dynamic_lstmp(
     proj_clip=None,
 ):
     r"""
-	:api_attr: Static Graph
 
     **Note**:
         1. In order to improve efficiency, users must first map the input of dimension [T, hidden_size] to input of [T, 4 * hidden_size], and then pass it to this OP.
@@ -1100,7 +1095,6 @@ def dynamic_gru(
     origin_mode=False,
 ):
     r"""
-	:api_attr: Static Graph
 
     **Note: The input type of this must be LoDTensor. If the input type to be
     processed is Tensor, use** :ref:`api_fluid_layers_StaticRNN` .
@@ -1270,7 +1264,6 @@ def gru_unit(
     origin_mode=False,
 ):
     r"""
-	:api_attr: Static Graph
 
     Gated Recurrent Unit (GRU) RNN cell. This operator performs GRU calculations for
     one time step and it supports these two modes: