diff --git a/python/paddle/v2/fluid/layers/control_flow.py b/python/paddle/v2/fluid/layers/control_flow.py
index 588114a275db5fc4c68f483826b3653a183e4162..acc22bef98b6eac4291bb2181e6d5cd7dbe2a768 100644
--- a/python/paddle/v2/fluid/layers/control_flow.py
+++ b/python/paddle/v2/fluid/layers/control_flow.py
@@ -16,6 +16,36 @@ __all__ = [
 
 
 def split_lod_tensor(input, mask, level=0):
+    """
+    **split_lod_tensor**
+
+    This function takes in an input that contains the complete lod information,
+    and takes in a mask which is used to mask certain parts of the input.
+    The output is the true branch and the false branch with the mask applied to
+    the input at a certain level in the tensor.
+
+    Args:
+        input(tuple|list|None): The input tensor that contains complete
+                                lod information needed to construct the output.
+        mask(list): A bool column vector which masks the input.
+        level(int): The specific lod level to rank.
+
+    Returns:
+        Variable: The true branch of tensor as per the mask applied to input.
+        Variable: The false branch of tensor as per the mask applied to input.
+
+    Examples:
+        .. code-block:: python
+
+          x = layers.data(name='x', shape=[1])
+          x.persistable = True
+
+          y = layers.data(name='y', shape=[1])
+          y.persistable = True
+
+          out_true, out_false = layers.split_lod_tensor(
+                input=x, mask=y, level=level)
+    """
     helper = LayerHelper('split_lod_tensor', **locals())
     out_true = helper.create_tmp_variable(dtype=input.dtype)
     out_false = helper.create_tmp_variable(dtype=input.dtype)
@@ -32,6 +62,40 @@ def split_lod_tensor(input, mask, level=0):
 
 
 def merge_lod_tensor(in_true, in_false, x, mask, level=0):
+    """
+    **merge_lod_tensor**
+
+    This function takes in an input :math:`x`, the True branch, the False
+    branch and a binary :math:`mask`. Using this information, this function
+    merges the True and False branches of the tensor into a single Output
+    at a certain lod level indiacted by :math:`level`.
+
+    Args:
+        in_true(tuple|list|None): The True branch to be merged.
+        in_false(tuple|list|None): The False branch to be merged.
+        x(tuple|list|None): The input tensor that contains complete
+                            lod information needed to construct the output.
+        mask(list): A bool column vector which masks the input.
+        level(int): The specific lod level to rank.
+
+    Returns:
+        Variable: The merged output tensor.
+
+    Examples:
+        .. code-block:: python
+
+          x = layers.data(
+                      name='x', shape=[1], dtype='float32', stop_gradient=False)
+          y = layers.data(
+                name='y', shape=[1], dtype='bool', stop_gradient=False)
+
+          level = 0
+
+          out_true, out_false = layers.split_lod_tensor(
+                input=x, mask=y, level=level)
+          out = layers.merge_lod_tensor(
+                in_true=out_true, in_false=out_false, mask=y, x=x, level=level)
+    """
     helper = LayerHelper('merge_lod_tensor', **locals())
     out = helper.create_tmp_variable(dtype=in_true.dtype)
     helper.append_op(