Add doc for data layer (#6858)

python/paddle/v2/fluid/layers/io.py

@@ -12,20 +12,9 @@ def data(name,
          type=core.VarDesc.VarType.LOD_TENSOR,
          stop_gradient=True):
     """
-    Data Layer.
+    **Data Layer**
 
-    Args:
-       name: The name/alias of the function
-       shape: Tuple declaring the shape.
-       append_batch_size: Whether or not to append the data as a batch.
-       dtype: The type of data : float32, float_16, int etc
-       type: The output type. By default it is LOD_TENSOR.
-       lod_level(int): The LoD Level. 0 means the input data is not a sequence.
-       main_program: Name of the main program that calls this
-       startup_program: Name of the startup program
-       stop_gradient: A boolean that mentions whether gradient should flow.
-
-    This function takes in input and based on whether data has
+    This function takes in the input and based on whether data has
     to be returned back as a minibatch, it creates the global variable using
     the helper functions. The global variables can be accessed by all the
     following operations and layers in the graph.
@@ -33,6 +22,24 @@ def data(name,
     All the input variables of this function are passed in as local variables
     to the LayerHelper constructor.
 
+    Args:
+       name(str): The name/alias of the function
+       shape(list): Tuple declaring the shape.
+       append_batch_size(bool): Whether or not to append the data as a batch.
+       dtype(int|float): The type of data : float32, float_16, int etc
+       type(VarType): The output type. By default it is LOD_TENSOR.
+       lod_level(int): The LoD Level. 0 means the input data is not a sequence.
+       main_program(Program): Name of the main program that calls this
+       startup_program(Program): Name of the startup program
+       stop_gradient(bool): A boolean that mentions whether gradient should flow.
+
+    Returns:
+        Variable: The global variable that gives access to the data.
+
+    Examples:
+        .. code-block:: python
+
+          data = fluid.layers.data(name='x', shape=[784], dtype='float32')
     """
     helper = LayerHelper('data', **locals())
     shape = list(shape)