refine sum stack api doc (#17923)

test=develop

Author: zhaoyuchen2018

paddle/fluid/API.spec

@@ -176,7 +176,7 @@ paddle.fluid.layers.leaky_relu (ArgSpec(args=['x', 'alpha', 'name'], varargs=Non
 paddle.fluid.layers.soft_relu (ArgSpec(args=['x', 'threshold', 'name'], varargs=None, keywords=None, defaults=(40.0, None)), ('document', '3490ed5c9835ae039a82979daf3918a4'))
 paddle.fluid.layers.flatten (ArgSpec(args=['x', 'axis', 'name'], varargs=None, keywords=None, defaults=(1, None)), ('document', 'cb295c13cb957db85cd9609269d7784d'))
 paddle.fluid.layers.sequence_mask (ArgSpec(args=['x', 'maxlen', 'dtype', 'name'], varargs=None, keywords=None, defaults=(None, 'int64', None)), ('document', '767cea598dee8e2b94f04110fa6b7e67'))
-paddle.fluid.layers.stack (ArgSpec(args=['x', 'axis'], varargs=None, keywords=None, defaults=(0,)), ('document', '43a9fef72d45df3bc58f52b93cdb61cb'))
+paddle.fluid.layers.stack (ArgSpec(args=['x', 'axis'], varargs=None, keywords=None, defaults=(0,)), ('document', 'e8d86c47e92bcb878ff8022b6f66cec2'))
 paddle.fluid.layers.pad2d (ArgSpec(args=['input', 'paddings', 'mode', 'pad_value', 'data_format', 'name'], varargs=None, keywords=None, defaults=([0, 0, 0, 0], 'constant', 0.0, 'NCHW', None)), ('document', '3f3abdb795a5c2aad8c2312249551ce5'))
 paddle.fluid.layers.unstack (ArgSpec(args=['x', 'axis', 'num'], varargs=None, keywords=None, defaults=(0, None)), ('document', 'b0c4ca08d4eb295189e1b107c920d093'))
 paddle.fluid.layers.sequence_enumerate (ArgSpec(args=['input', 'win_size', 'pad_value', 'name'], varargs=None, keywords=None, defaults=(0, None)), ('document', '2e49e97069beb57ee89d54ed088ae2da'))
@@ -196,7 +196,7 @@ paddle.fluid.layers.uniform_random_batch_size_like (ArgSpec(args=['input', 'shap
 paddle.fluid.layers.gaussian_random (ArgSpec(args=['shape', 'mean', 'std', 'seed', 'dtype'], varargs=None, keywords=None, defaults=(0.0, 1.0, 0, 'float32')), ('document', '8c78ccb77e291e4a0f0673d34823ce4b'))
 paddle.fluid.layers.sampling_id (ArgSpec(args=['x', 'min', 'max', 'seed', 'dtype'], varargs=None, keywords=None, defaults=(0.0, 1.0, 0, 'float32')), ('document', '35428949368cad5121dd37f8522ef8b0'))
 paddle.fluid.layers.gaussian_random_batch_size_like (ArgSpec(args=['input', 'shape', 'input_dim_idx', 'output_dim_idx', 'mean', 'std', 'seed', 'dtype'], varargs=None, keywords=None, defaults=(0, 0, 0.0, 1.0, 0, 'float32')), ('document', '9e520987168f8ddb7dd71ffd68aa352c'))
-paddle.fluid.layers.sum (ArgSpec(args=['x'], varargs=None, keywords=None, defaults=None), ('document', 'a418e3ccb5e2ac21bd60f5cc221d5860'))
+paddle.fluid.layers.sum (ArgSpec(args=['x'], varargs=None, keywords=None, defaults=None), ('document', '4527fd90e222f67b5f7451fb0cf7c845'))
 paddle.fluid.layers.slice (ArgSpec(args=['input', 'axes', 'starts', 'ends'], varargs=None, keywords=None, defaults=None), ('document', '3ca6a761570d86e303e473afba99bb49'))
 paddle.fluid.layers.shape (ArgSpec(args=['input'], varargs=None, keywords=None, defaults=None), ('document', 'bf61c8f79d795a8371bdb3b5468aa82b'))
 paddle.fluid.layers.rank (ArgSpec(args=['input'], varargs=None, keywords=None, defaults=None), ('document', 'ee1386c42ecc8f424fe3fb21862fefc2'))

python/paddle/fluid/layers/nn.py

@@ -9266,8 +9266,8 @@ def stack(x, axis=0):
         .. code-block:: python
 
             import paddle.fluid.layers as layers
-            x1 = layers.data(name='x1', shape[1, 2], dtype='int32')
-            x2 = layers.data(name='x2', shape[1, 2], dtype='int32')
+            x1 = layers.data(name='x1', shape=[1, 2], dtype='int32')
+            x2 = layers.data(name='x2', shape=[1, 2], dtype='int32')
             data = layers.stack([x1,x2])
 
     """
@@ -9615,8 +9615,10 @@ def sum(x):
     Examples:
         .. code-block:: python
 
-            input = layers.data(name="input", shape=[13, 11], dtype='float32')
-            out = layers.sum(input)
+            import paddle.fluid.layers as layers
+            input0 = layers.data(name="input0", shape=[13, 11], dtype='float32')
+            input1 = layers.data(name="input1", shape=[13, 11], dtype='float32')
+            out = layers.sum([input0,input1])
     """
 
     helper = LayerHelper('sum', **locals())