fix data_feed_desc.py example run error (#17452)

* fix data_feed_desc.py example run error
test=develop
test=test=document_preview

* fix data_feed_desc.py example display error
test=develop
test=document_preview

* update API.spec for DataFeedDesc
test=develop
test=document_preview

paddle/fluid/API.spec

@@ -36,10 +36,10 @@ paddle.fluid.ParallelExecutor.run (ArgSpec(args=['self', 'fetch_list', 'feed', '
 paddle.fluid.create_lod_tensor (ArgSpec(args=['data', 'recursive_seq_lens', 'place'], varargs=None, keywords=None, defaults=None), ('document', 'b82ea20e2dc5ff2372e0643169ca47ff'))
 paddle.fluid.create_random_int_lodtensor (ArgSpec(args=['recursive_seq_lens', 'base_shape', 'place', 'low', 'high'], varargs=None, keywords=None, defaults=None), ('document', '74dc6d23185d90a7a50fbac19f5b65fb'))
 paddle.fluid.DataFeedDesc.__init__ (ArgSpec(args=['self', 'proto_file'], varargs=None, keywords=None, defaults=None), ('document', '6adf97f83acf6453d4a6a4b1070f3754'))
-paddle.fluid.DataFeedDesc.desc (ArgSpec(args=['self'], varargs=None, keywords=None, defaults=None), ('document', '4294493e31c4bc9fc4bd48753044235f'))
-paddle.fluid.DataFeedDesc.set_batch_size (ArgSpec(args=['self', 'batch_size'], varargs=None, keywords=None, defaults=None), ('document', '8d9f44601e0a99dd431f14fd9250cd21'))
-paddle.fluid.DataFeedDesc.set_dense_slots (ArgSpec(args=['self', 'dense_slots_name'], varargs=None, keywords=None, defaults=None), ('document', 'eb894b464bbcd1b4bc8038398954f766'))
-paddle.fluid.DataFeedDesc.set_use_slots (ArgSpec(args=['self', 'use_slots_name'], varargs=None, keywords=None, defaults=None), ('document', '415c56600ce4e198c071cad01409a690'))
+paddle.fluid.DataFeedDesc.desc (ArgSpec(args=['self'], varargs=None, keywords=None, defaults=None), ('document', '75283b5f03ec7b6f74bfca9881a37428'))
+paddle.fluid.DataFeedDesc.set_batch_size (ArgSpec(args=['self', 'batch_size'], varargs=None, keywords=None, defaults=None), ('document', '68df53d3ea0f24063bf7689e82c2b82e'))
+paddle.fluid.DataFeedDesc.set_dense_slots (ArgSpec(args=['self', 'dense_slots_name'], varargs=None, keywords=None, defaults=None), ('document', 'd5a78553cd94fe64148399797055d8ad'))
+paddle.fluid.DataFeedDesc.set_use_slots (ArgSpec(args=['self', 'use_slots_name'], varargs=None, keywords=None, defaults=None), ('document', '88d229ea9f892ce8d2922cf028c8bb3a'))
 paddle.fluid.CompiledProgram.__init__ (ArgSpec(args=['self', 'program_or_graph'], varargs=None, keywords=None, defaults=None), ('document', '6adf97f83acf6453d4a6a4b1070f3754'))
 paddle.fluid.CompiledProgram.with_data_parallel (ArgSpec(args=['self', 'loss_name', 'build_strategy', 'exec_strategy', 'share_vars_from', 'places'], varargs=None, keywords=None, defaults=(None, None, None, None, None)), ('document', '0e17773521634ef798fddd7d2ea3ef96'))
 paddle.fluid.CompiledProgram.with_inference_optimize (ArgSpec(args=['self', 'config'], varargs=None, keywords=None, defaults=None), ('document', '9e5b009d850191a010e859189c127fd8'))

python/paddle/fluid/data_feed_desc.py

@@ -24,28 +24,32 @@ class DataFeedDesc(object):
     currently only used for AsyncExecutor (See comments for class AsyncExecutor
     for a brief introduction)
 
-    DataFeedDesc shall be initialized from a valid protobuf message from disk:
-    >>> data_feed = fluid.DataFeedDesc('data.proto')
+    DataFeedDesc shall be initialized from a valid protobuf message from disk.
 
     See :code:`paddle/fluid/framework/data_feed.proto` for message definition.
     A typical message might look like:
 
-    >>> name: "MultiSlotDataFeed"
-    >>> batch_size: 2
-    >>> multi_slot_desc {
-    >>>     slots {
-    >>>         name: "words"
-    >>>         type: "uint64"
-    >>>         is_dense: false
-    >>>         is_used: true
-    >>>     }
-    >>>     slots {
-    >>>         name: "label"
-    >>>         type: "uint64"
-    >>>         is_dense: false
-    >>>         is_used: true
-    >>>     }
-    >>> }
+    .. code-block:: python
+
+      f = open("data.proto", "w")
+      print >> f, 'name: "MultiSlotDataFeed"'
+      print >> f, 'batch_size: 2'
+      print >> f, 'multi_slot_desc {'
+      print >> f, '    slots {'
+      print >> f, '         name: "words"'
+      print >> f, '         type: "uint64"'
+      print >> f, '         is_dense: false'
+      print >> f, '         is_used: true'
+      print >> f, '     }'
+      print >> f, '     slots {'
+      print >> f, '         name: "label"'
+      print >> f, '         type: "uint64"'
+      print >> f, '         is_dense: false'
+      print >> f, '         is_used: true'
+      print >> f, '    }'
+      print >> f, '}'
+      f.close()
+      data_feed = fluid.DataFeedDesc('data.proto')
 
     However, users usually shouldn't care about the message format; instead,
     they are encouragd to use :code:`Data Generator` as a tool to generate a
@@ -54,16 +58,23 @@ class DataFeedDesc(object):
 
     DataFeedDesc can also be changed during runtime. Once you got familiar with
     what each field mean, you can modify it to better suit your need. E.g.:
-    >>> data_feed.set_batch_size(128)
-    >>> data_feed.set_dense_slots('wd')  # The slot named 'wd' will be dense
-    >>> data_feed.set_use_slots('wd')    # The slot named 'wd' will be used
+
+    .. code-block:: python
+
+      data_feed = fluid.DataFeedDesc('data.proto')
+      data_feed.set_batch_size(128)
+      data_feed.set_dense_slots('wd')  # The slot named 'wd' will be dense
+      data_feed.set_use_slots('wd')    # The slot named 'wd' will be used
 
     Finally, the content can be dumped out for debugging purpose:
-    >>> print(data_feed.desc())
+
+    .. code-block:: python
+
+      print(data_feed.desc())
 
     Args:
         proto_file(string): Disk file containing a data feed description.
-    
+
     """
 
     def __init__(self, proto_file):
@@ -82,8 +93,28 @@ class DataFeedDesc(object):
         Set batch size. Will be effective during training
 
         Example:
-            >>> data_feed = fluid.DataFeedDesc('data.proto')
-            >>> data_feed.set_batch_size(128)
+            .. code-block:: python
+
+              f = open("data.proto", "w")
+              print >> f, 'name: "MultiSlotDataFeed"'
+              print >> f, 'batch_size: 2'
+              print >> f, 'multi_slot_desc {'
+              print >> f, '    slots {'
+              print >> f, '         name: "words"'
+              print >> f, '         type: "uint64"'
+              print >> f, '         is_dense: false'
+              print >> f, '         is_used: true'
+              print >> f, '     }'
+              print >> f, '     slots {'
+              print >> f, '         name: "label"'
+              print >> f, '         type: "uint64"'
+              print >> f, '         is_dense: false'
+              print >> f, '         is_used: true'
+              print >> f, '    }'
+              print >> f, '}'
+              f.close()
+              data_feed = fluid.DataFeedDesc('data.proto')
+              data_feed.set_batch_size(128)
 
         Args:
             batch_size: batch size
@@ -98,8 +129,28 @@ class DataFeedDesc(object):
         sparse slot will be fed into a LoDTensor
 
         Example:
-            >>> data_feed = fluid.DataFeedDesc('data.proto')
-            >>> data_feed.set_dense_slots(['words'])
+            .. code-block:: python
+
+              f = open("data.proto", "w")
+              print >> f, 'name: "MultiSlotDataFeed"'
+              print >> f, 'batch_size: 2'
+              print >> f, 'multi_slot_desc {'
+              print >> f, '    slots {'
+              print >> f, '         name: "words"'
+              print >> f, '         type: "uint64"'
+              print >> f, '         is_dense: false'
+              print >> f, '         is_used: true'
+              print >> f, '     }'
+              print >> f, '     slots {'
+              print >> f, '         name: "label"'
+              print >> f, '         type: "uint64"'
+              print >> f, '         is_dense: false'
+              print >> f, '         is_used: true'
+              print >> f, '    }'
+              print >> f, '}'
+              f.close()
+              data_feed = fluid.DataFeedDesc('data.proto')
+              data_feed.set_dense_slots(['words'])
 
         Args:
             dense_slots_name: a list of slot names which will be set dense
@@ -109,7 +160,7 @@ class DataFeedDesc(object):
         """
         if self.proto_desc.name != "MultiSlotDataFeed":
             raise ValueError(
-                "Only MultiSlotDataFeed need set_dense_slots, pls check your datafeed.proto"
+                "Only MultiSlotDataFeed needs set_dense_slots, please check your datafeed.proto"
             )
         for name in dense_slots_name:
             self.proto_desc.multi_slot_desc.slots[self.__name_to_index[
@@ -122,8 +173,28 @@ class DataFeedDesc(object):
         ones will be used for a specific model.
 
         Example:
-            >>> data_feed = fluid.DataFeedDesc('data.proto')
-            >>> data_feed.set_use_slots(['words'])
+            .. code-block:: python
+
+              f = open("data.proto", "w")
+              print >> f, 'name: "MultiSlotDataFeed"'
+              print >> f, 'batch_size: 2'
+              print >> f, 'multi_slot_desc {'
+              print >> f, '    slots {'
+              print >> f, '         name: "words"'
+              print >> f, '         type: "uint64"'
+              print >> f, '         is_dense: false'
+              print >> f, '         is_used: true'
+              print >> f, '     }'
+              print >> f, '     slots {'
+              print >> f, '         name: "label"'
+              print >> f, '         type: "uint64"'
+              print >> f, '         is_dense: false'
+              print >> f, '         is_used: true'
+              print >> f, '    }'
+              print >> f, '}'
+              f.close()
+              data_feed = fluid.DataFeedDesc('data.proto')
+              data_feed.set_use_slots(['words'])
 
         Args:
             use_slots_name: a list of slot names which will be used in training
@@ -133,7 +204,7 @@ class DataFeedDesc(object):
         """
         if self.proto_desc.name != "MultiSlotDataFeed":
             raise ValueError(
-                "Only MultiSlotDataFeed need set_use_slots, pls check your datafeed.proto"
+                "Only MultiSlotDataFeed needs set_use_slots, please check your datafeed.proto"
             )
         for name in use_slots_name:
             self.proto_desc.multi_slot_desc.slots[self.__name_to_index[
@@ -144,8 +215,28 @@ class DataFeedDesc(object):
         Returns a protobuf message for this DataFeedDesc
 
         Example:
-            >>> data_feed = fluid.DataFeedDesc('data.proto')
-            >>> print(data_feed.desc())
+            .. code-block:: python
+
+              f = open("data.proto", "w")
+              print >> f, 'name: "MultiSlotDataFeed"'
+              print >> f, 'batch_size: 2'
+              print >> f, 'multi_slot_desc {'
+              print >> f, '    slots {'
+              print >> f, '         name: "words"'
+              print >> f, '         type: "uint64"'
+              print >> f, '         is_dense: false'
+              print >> f, '         is_used: true'
+              print >> f, '     }'
+              print >> f, '     slots {'
+              print >> f, '         name: "label"'
+              print >> f, '         type: "uint64"'
+              print >> f, '         is_dense: false'
+              print >> f, '         is_used: true'
+              print >> f, '    }'
+              print >> f, '}'
+              f.close()
+              data_feed = fluid.DataFeedDesc('data.proto')
+              print(data_feed.desc())
 
         Returns:
             A string message