diff --git a/paddle/fluid/API.spec b/paddle/fluid/API.spec
index bdbfaa86d2fec5ee32f2651f2c9ef9cb682b9ff4..9a849387d2c0a4c1838252b21d09c834f4675b19 100644
--- a/paddle/fluid/API.spec
+++ b/paddle/fluid/API.spec
@@ -126,7 +126,7 @@ paddle.fluid.initializer.NumpyArrayInitializer.__init__ (ArgSpec(args=['self', '
 paddle.fluid.embedding (ArgSpec(args=['input', 'size', 'is_sparse', 'is_distributed', 'padding_idx', 'param_attr', 'dtype'], varargs=None, keywords=None, defaults=(False, False, None, None, 'float32')), ('document', 'd4ac047e0d5e6b7b1c5ff6ef7d7cfff5'))
 paddle.fluid.one_hot (ArgSpec(args=['input', 'depth', 'allow_out_of_range'], varargs=None, keywords=None, defaults=(False,)), ('document', 'eef66730acc806088f9e8ba90252bda1'))
 paddle.fluid.layers.fc (ArgSpec(args=['input', 'size', 'num_flatten_dims', 'param_attr', 'bias_attr', 'act', 'name'], varargs=None, keywords=None, defaults=(1, None, None, None, None)), ('document', '0dc8181f14a33f91fbae9385a9b3d9fd'))
-paddle.fluid.layers.center_loss (ArgSpec(args=['input', 'label', 'num_classes', 'alpha', 'param_attr', 'update_center'], varargs=None, keywords=None, defaults=(True,)), ('document', '7129819d94625c6104054e8187768589'))
+paddle.fluid.layers.center_loss (ArgSpec(args=['input', 'label', 'num_classes', 'alpha', 'param_attr', 'update_center'], varargs=None, keywords=None, defaults=(True,)), ('document', '18112442f55b5862bbec8feee841c905'))
 paddle.fluid.layers.embedding (ArgSpec(args=['input', 'size', 'is_sparse', 'is_distributed', 'padding_idx', 'param_attr', 'dtype'], varargs=None, keywords=None, defaults=(False, False, None, None, 'float32')), ('document', 'd8e405486a1e4e189b51d6ee28d67b1e'))
 paddle.fluid.layers.dynamic_lstm (ArgSpec(args=['input', 'size', 'h_0', 'c_0', 'param_attr', 'bias_attr', 'use_peepholes', 'is_reverse', 'gate_activation', 'cell_activation', 'candidate_activation', 'dtype', 'name'], varargs=None, keywords=None, defaults=(None, None, None, None, True, False, 'sigmoid', 'tanh', 'tanh', 'float32', None)), ('document', '6d3ee14da70adfa36d85c40b18716ef2'))
 paddle.fluid.layers.dynamic_lstmp (ArgSpec(args=['input', 'size', 'proj_size', 'param_attr', 'bias_attr', 'use_peepholes', 'is_reverse', 'gate_activation', 'cell_activation', 'candidate_activation', 'proj_activation', 'dtype', 'name', 'h_0', 'c_0', 'cell_clip', 'proj_clip'], varargs=None, keywords=None, defaults=(None, None, True, False, 'sigmoid', 'tanh', 'tanh', 'tanh', 'float32', None, None, None, None, None)), ('document', 'c37d51aad655c8a9f9b045c64717320a'))
@@ -212,10 +212,10 @@ paddle.fluid.layers.resize_bilinear (ArgSpec(args=['input', 'out_shape', 'scale'
 paddle.fluid.layers.resize_trilinear (ArgSpec(args=['input', 'out_shape', 'scale', 'name', 'actual_shape', 'align_corners', 'align_mode', 'data_format'], varargs=None, keywords=None, defaults=(None, None, None, None, True, 1, 'NCDHW')), ('document', '5b4d0f823f94c260fe5e6f7eec60a797'))
 paddle.fluid.layers.resize_nearest (ArgSpec(args=['input', 'out_shape', 'scale', 'name', 'actual_shape', 'align_corners', 'data_format'], varargs=None, keywords=None, defaults=(None, None, None, None, True, 'NCHW')), ('document', '0107a5cbae1aef3f381d3d769a6068eb'))
 paddle.fluid.layers.gather (ArgSpec(args=['input', 'index', 'overwrite'], varargs=None, keywords=None, defaults=(True,)), ('document', 'f985c9b66e3aec96fa753a8eb44c991c'))
-paddle.fluid.layers.gather_nd (ArgSpec(args=['input', 'index', 'name'], varargs=None, keywords=None, defaults=(None,)), ('document', '3cc24f9cf135770aa6263dba25b457f9'))
+paddle.fluid.layers.gather_nd (ArgSpec(args=['input', 'index', 'name'], varargs=None, keywords=None, defaults=(None,)), ('document', 'a7d625028525167b138106f574dffdf9'))
 paddle.fluid.layers.scatter (ArgSpec(args=['input', 'index', 'updates', 'name', 'overwrite'], varargs=None, keywords=None, defaults=(None, True)), ('document', '69b22affd4a6326502af166f04c095ab'))
-paddle.fluid.layers.scatter_nd_add (ArgSpec(args=['ref', 'index', 'updates', 'name'], varargs=None, keywords=None, defaults=(None,)), ('document', 'c2fa5ee7484b52b95a28abf1d8827cd0'))
-paddle.fluid.layers.scatter_nd (ArgSpec(args=['index', 'updates', 'shape', 'name'], varargs=None, keywords=None, defaults=(None,)), ('document', '14b5449ce42f8ff4ac4ce79b41c86cc5'))
+paddle.fluid.layers.scatter_nd_add (ArgSpec(args=['ref', 'index', 'updates', 'name'], varargs=None, keywords=None, defaults=(None,)), ('document', '2607b5c9369fbc52f208de066a80fc25'))
+paddle.fluid.layers.scatter_nd (ArgSpec(args=['index', 'updates', 'shape', 'name'], varargs=None, keywords=None, defaults=(None,)), ('document', 'e43f1d3a938b35da246aea3e72a020ec'))
 paddle.fluid.layers.sequence_scatter (ArgSpec(args=['input', 'index', 'updates', 'name'], varargs=None, keywords=None, defaults=(None,)), ('document', 'abe3f714120117a5a3d3e639853932bf'))
 paddle.fluid.layers.random_crop (ArgSpec(args=['x', 'shape', 'seed'], varargs=None, keywords=None, defaults=(None,)), ('document', '042af0b8abea96b40c22f6e70d99e042'))
 paddle.fluid.layers.mean_iou (ArgSpec(args=['input', 'label', 'num_classes'], varargs=None, keywords=None, defaults=None), ('document', 'e714b4aa7993dfe9c1a38886875dbaac'))
@@ -307,7 +307,7 @@ paddle.fluid.layers.deformable_conv (ArgSpec(args=['input', 'offset', 'mask', 'n
 paddle.fluid.layers.unfold (ArgSpec(args=['x', 'kernel_sizes', 'strides', 'paddings', 'dilations', 'name'], varargs=None, keywords=None, defaults=(1, 0, 1, None)), ('document', '3f884662ad443d9ecc2b3734b4f61ad6'))
 paddle.fluid.layers.deformable_roi_pooling (ArgSpec(args=['input', 'rois', 'trans', 'no_trans', 'spatial_scale', 'group_size', 'pooled_height', 'pooled_width', 'part_size', 'sample_per_part', 'trans_std', 'position_sensitive', 'name'], varargs=None, keywords=None, defaults=(False, 1.0, [1, 1], 1, 1, None, 1, 0.1, False, None)), ('document', '47c5d1c890b36fa00ff3285c9398f613'))
 paddle.fluid.layers.filter_by_instag (ArgSpec(args=['ins', 'ins_tag', 'filter_tag', 'is_lod'], varargs=None, keywords=None, defaults=None), ('document', '7703a2088af8de4128b143ff1164ca4a'))
-paddle.fluid.layers.shard_index (ArgSpec(args=['input', 'index_num', 'nshards', 'shard_id', 'ignore_value'], varargs=None, keywords=None, defaults=(-1,)), ('document', 'c4969dd6bf164f9e6a90414ea4f4e5ad'))
+paddle.fluid.layers.shard_index (ArgSpec(args=['input', 'index_num', 'nshards', 'shard_id', 'ignore_value'], varargs=None, keywords=None, defaults=(-1,)), ('document', '3c6b30e9cd57b38d4a5fa1ade887f779'))
 paddle.fluid.layers.hard_swish (ArgSpec(args=['x', 'threshold', 'scale', 'offset', 'name'], varargs=None, keywords=None, defaults=(6.0, 6.0, 3.0, None)), ('document', '6a5152a7015c62cb8278fc24cb456459'))
 paddle.fluid.layers.mse_loss (ArgSpec(args=['input', 'label'], varargs=None, keywords=None, defaults=None), ('document', 'd9ede6469288636e1b3233b461a165c9'))
 paddle.fluid.layers.uniform_random (ArgSpec(args=['shape', 'dtype', 'min', 'max', 'seed'], varargs=None, keywords=None, defaults=('float32', -1.0, 1.0, 0)), ('document', '126ede8ce0e751244b1b54cd359c89d7'))
@@ -341,7 +341,7 @@ paddle.fluid.layers.linspace (ArgSpec(args=['start', 'stop', 'num', 'dtype'], va
 paddle.fluid.layers.zeros_like (ArgSpec(args=['x', 'out'], varargs=None, keywords=None, defaults=(None,)), ('document', 'd88a23bcdc443719b3953593f7cef14a'))
 paddle.fluid.layers.ones_like (ArgSpec(args=['x', 'out'], varargs=None, keywords=None, defaults=(None,)), ('document', 'd18d42059c6b189cbd3fab2fcb206c15'))
 paddle.fluid.layers.diag (ArgSpec(args=['diagonal'], varargs=None, keywords=None, defaults=None), ('document', '88a15e15f0098d549f07a01eaebf9ce3'))
-paddle.fluid.layers.eye (ArgSpec(args=['num_rows', 'num_columns', 'batch_shape', 'dtype'], varargs=None, keywords=None, defaults=(None, None, 'float32')), ('document', '25389d1e239a5d1cda66298f908ec549'))
+paddle.fluid.layers.eye (ArgSpec(args=['num_rows', 'num_columns', 'batch_shape', 'dtype'], varargs=None, keywords=None, defaults=(None, None, 'float32')), ('document', '60cdc70ae43ba69fae36d720ef3016a1'))
 paddle.fluid.layers.While ('paddle.fluid.layers.control_flow.While', ('document', '50110155608a00f43d3d3fd1be41dcb4'))
 paddle.fluid.layers.While.__init__ (ArgSpec(args=['self', 'cond', 'is_test', 'name'], varargs=None, keywords=None, defaults=(False, None)), ('document', '6adf97f83acf6453d4a6a4b1070f3754'))
 paddle.fluid.layers.While.block (ArgSpec(args=['self'], varargs=None, keywords=None, defaults=None), ('document', '6adf97f83acf6453d4a6a4b1070f3754'))
diff --git a/python/paddle/fluid/layers/nn.py b/python/paddle/fluid/layers/nn.py
index 0ac09ffc5478de055deef061dfd9f677271a0bf3..2d6a938a21b5f8f39dc9e5db6c83c031390a5439 100755
--- a/python/paddle/fluid/layers/nn.py
+++ b/python/paddle/fluid/layers/nn.py
@@ -375,8 +375,10 @@ def center_loss(input,
     """
     **Center loss Cost layer**
     
-    This layer accepts input (deep features,the output of the last hidden layer)
-    and target label and return the center loss cost
+    This OP accepts input (deep features,the output of the last hidden layer)
+    and target label and return the center loss cost. The average of the 
+    distances of each sample in the mini-batch from the center of the 
+    corresponding category is calculated as the center loss.
     
     For deep features, :math:`X`, and target labels, :math:`Y`, the equation is:
     
@@ -385,9 +387,9 @@ def center_loss(input,
         Out = \\frac{1}{2}(X - Y)^2
 
     Args:
-        input (Variable): a 2-D tensor with shape[N x M].
+        input (Variable): a 2-D tensor with shape[N x M]. Its dtype should be float32 or float64.
         label (Variable): the groud truth which is a 2-D tensor
-                         with shape[N x 1],where N is the batch size.
+                         with shape[N x 1],where N is the batch size. Its dtype should be int32.
         num_classes (int): the number of classification categories.
         alpha (float|Variable): learning rate of centers.
         param_attr (ParamAttr): Attribute initializer of centers. 
@@ -401,8 +403,8 @@ def center_loss(input,
 
           import paddle.fluid as fluid 
 
-          input = fluid.layers.data(name='x',shape=[20,30],dtype='float32')
-          label = fluid.layers.data(name='y',shape=[20,1],dtype='int64')
+          input = fluid.data(name='x',shape=[20,30],dtype='float32')
+          label = fluid.data(name='y',shape=[20,1],dtype='int64')
           num_classes = 1000
           alpha = 0.01
           param_attr = fluid.initializer.Xavier(uniform=False)
@@ -9573,10 +9575,11 @@ def gather_nd(input, index, name=None):
                          = [23]
 
     Args:
-        input (Variable): The source input
-        index (Variable): The index input with rank > 1, index.shape[-1] <= input.rank
+        input (Variable): The source input. Its dtype should be int32, int64, float32, float64.
+        index (Variable): The index input with rank > 1, index.shape[-1] <= input.rank.
+                          Its dtype should be int32, int64.
         name (str|None): A name for this layer(optional). If set None, the
-                         layer will be named automatically
+                         layer will be named automatically.
 
     Returns:
         output (Variable): A tensor with the shape index.shape[:-1] + input.shape[index.shape[-1]:]
@@ -9586,8 +9589,8 @@ def gather_nd(input, index, name=None):
         .. code-block:: python
 
             import paddle.fluid as fluid
-            x = fluid.layers.data(name='x', shape=[3, 4, 5], dtype='float32')
-            index = fluid.layers.data(name='index', shape=[2, 2], dtype='int32')
+            x = fluid.data(name='x', shape=[3, 4, 5], dtype='float32')
+            index = fluid.data(name='index', shape=[2, 2], dtype='int32')
             output = fluid.layers.gather_nd(x, index)
 
     """
@@ -9662,11 +9665,14 @@ def scatter_nd_add(ref, index, updates, name=None):
     **Scatter_nd_add Layer**
 
     Output is obtained by applying sparse addition to a single value
-    or slice in a Variable. :attr:`ref` is a Tensor with rank :math:`R` 
+    or slice in a Variable. 
+
+    :attr:`ref` is a Tensor with rank :math:`R` 
     and :attr:`index` is a Tensor with rank :math:`K` . Thus, :attr:`index` 
     has shape :math:`[i_0, i_1, ..., i_{K-2}, Q]` where :math:`Q \leq R` . :attr:`updates` 
     is a Tensor with rank :math:`K - 1 + R - Q` and its
     shape is :math:`index.shape[:-1] + ref.shape[index.shape[-1]:]` .
+
     According to the :math:`[i_0, i_1, ..., i_{K-2}]` of :attr:`index` ,
     add the corresponding :attr:`updates` slice to the :attr:`ref` slice
     which is obtained by the last one dimension of :attr:`index` .
@@ -9698,15 +9704,15 @@ def scatter_nd_add(ref, index, updates, name=None):
             output = [[67, 19], [-16, -27]]
 
     Args:
-        ref (Variable): The ref input.
+        ref (Variable): The ref input. Its dtype should be int32, int64, float32, float64.
         index (Variable): The index input with rank > 1 and index.shape[-1] <= ref.rank.
                           Its dtype should be int32 or int64 as it is used as indexes.
-        updates (Variable): The updated value of scatter_nd_add op, and it must have the same type
-                            as ref. It must have the shape index.shape[:-1] + ref.shape[index.shape[-1]:]
-        name (str|None): The output variable name. Default None.
+        updates (Variable): The updated value of scatter_nd_add op, and it must have the same dtype
+                            as ref. It must have the shape index.shape[:-1] + ref.shape[index.shape[-1]:].
+        name (str|None): The output variable name. If set None, the layer will be named automatically.
 
     Returns:
-        output (Variable): The output is a tensor with the same shape and type as ref.
+        output (Variable): The output is a tensor with the same shape and dtype as ref.
 
     Examples:
 
@@ -9714,9 +9720,9 @@ def scatter_nd_add(ref, index, updates, name=None):
 
             import paddle.fluid as fluid
 
-            ref = fluid.layers.data(name='ref', shape=[3, 5, 9, 10], dtype='float32', append_batch_size=False)
-            index = fluid.layers.data(name='index', shape=[3, 2], dtype='int32', append_batch_size=False)
-            updates = fluid.layers.data(name='update', shape=[3, 9, 10], dtype='float32', append_batch_size=False)
+            ref = fluid.data(name='ref', shape=[3, 5, 9, 10], dtype='float32')
+            index = fluid.data(name='index', shape=[3, 2], dtype='int32')
+            updates = fluid.data(name='update', shape=[3, 9, 10], dtype='float32')
 
             output = fluid.layers.scatter_nd_add(ref, index, updates)
     """
@@ -9755,10 +9761,10 @@ def scatter_nd(index, updates, shape, name=None):
     Args:
         index (Variable): The index input with rank > 1 and index.shape[-1] <= len(shape).
                           Its dtype should be int32 or int64 as it is used as indexes.
-        updates (Variable): The updated value of scatter_nd op. 
+        updates (Variable): The updated value of scatter_nd op. Its dtype should be int32, int64, float32, float64.
                             It must have the shape index.shape[:-1] + shape[index.shape[-1]:]
         shape(tuple|list): Shape of output tensor.
-        name (str|None): The output variable name. Default None.
+        name (str|None): The output variable name. If set None, the layer will be named automatically.
 
     Returns:
         output (Variable): The output is a tensor with the same type as :attr:`updates` .
@@ -9769,8 +9775,8 @@ def scatter_nd(index, updates, shape, name=None):
 
             import paddle.fluid as fluid
 
-            index = fluid.layers.data(name='index', shape=[3, 2], dtype='int64', append_batch_size=False)
-            updates = fluid.layers.data(name='update', shape=[3, 9, 10], dtype='float32', append_batch_size=False)
+            index = fluid.data(name='index', shape=[3, 2], dtype='int64')
+            updates = fluid.data(name='update', shape=[3, 9, 10], dtype='float32')
             shape = [3, 5, 9, 10]
 
             output = fluid.layers.scatter_nd(index, updates, shape)
@@ -15359,7 +15365,7 @@ def deformable_roi_pooling(input,
 
 def shard_index(input, index_num, nshards, shard_id, ignore_value=-1):
     """
-    This function recomputes the `input` indices according to the offset of the
+    This operator recomputes the `input` indices according to the offset of the
     shard. The length of the indices is evenly divided into N shards, and if
     the `shard_id` matches the shard with the input index inside, the index is
     recomputed on the basis of the shard offset, elsewise it is set to
@@ -15404,7 +15410,8 @@ def shard_index(input, index_num, nshards, shard_id, ignore_value=-1):
         .. code-block:: python
 
             import paddle.fluid as fluid
-            label = fluid.layers.data(name="label", shape=[1], dtype="int64")
+            batch_size = 32
+            label = fluid.data(name="label", shape=[batch_size, 1], dtype="int64")
             shard_label = fluid.layers.shard_index(input=label,
                                                    index_num=20,
                                                    nshards=2,
diff --git a/python/paddle/fluid/layers/tensor.py b/python/paddle/fluid/layers/tensor.py
index 3a5a43216575c98a99830b86dee02b5699d33dac..e6251c928d500bd70552fc60d80111fcf78b8a79 100644
--- a/python/paddle/fluid/layers/tensor.py
+++ b/python/paddle/fluid/layers/tensor.py
@@ -1018,25 +1018,26 @@ def eye(num_rows, num_columns=None, batch_shape=None, dtype='float32'):
                           If None, default: num_rows.
         batch_shape(list(int)): If provided, the returned tensor will have a leading
                                 batch size of this shape.
-        dtype(string): 'float32'|'int32'|..., the data type of the returned tensor.
+        dtype(string): The data type of the returned tensor.
+                       It should be int32, int64, float16, float32, float64.
 
     Returns:
-        Variable: An identity tensor of shape batch_shape + [num_rows, num_columns].
+        Variable: An identity Tensor or LoDTensor of shape batch_shape + [num_rows, num_columns].
 
     Examples:
         .. code-block:: python
 
           import paddle.fluid as fluid
- 	  data = fluid.layers.eye(3, dtype='int32')
-	  # [[1, 0, 0]
+          data = fluid.layers.eye(3, dtype='int32')
+          # [[1, 0, 0]
           #  [0, 1, 0]
-	  #  [0, 0, 1]]
-    
+          #  [0, 0, 1]]
+
           data = fluid.layers.eye(2, 3, dtype='int32')
-	  # [[1, 0, 0]
+          # [[1, 0, 0]
           #  [0, 1, 0]]
-    
-	  data = fluid.layers.eye(2, batch_shape=[3])
+
+          data = fluid.layers.eye(2, batch_shape=[3])
           # Construct a batch of 3 identity tensors, each 2 x 2.
           # data[i, :, :] is a 2 x 2 identity tensor, i = 0, 1, 2.