diff --git a/python/paddle/fluid/layers/layer_function_generator.py b/python/paddle/fluid/layers/layer_function_generator.py
index 6026237d0b623f9953da6cbf7a97019d31aa881b..fb5e454e94fd7ef1bd4c7e6b671df4598908e74f 100644
--- a/python/paddle/fluid/layers/layer_function_generator.py
+++ b/python/paddle/fluid/layers/layer_function_generator.py
@@ -230,15 +230,22 @@ def templatedoc():
         and AddInput. The ${name} is Python snake style. i.e., xxx_xxx.
     * ${{name}_type}: The type of ${name}.
 
-
     Returns:
-        Decorated funciton.
+        Decorated function.
     """
 
     def __impl__(func):
         op_proto = OpProtoHolder.instance().get_op_proto(func.__name__)
         tmpl = string.Template(func.__doc__)
-        args = {"comment": " ".join(op_proto.comment.split())}
+
+        comment_lines = op_proto.comment.split("\n")
+        comment = ""
+        for line in comment_lines:
+            line = line.lstrip()
+            comment += line
+            comment += "\n"
+
+        args = {"comment": comment}
         for each_input in op_proto.inputs:
             input_name = _convert_(each_input.name)
             args["{0}_comment".format(input_name)] = each_input.comment
diff --git a/python/paddle/fluid/layers/nn.py b/python/paddle/fluid/layers/nn.py
index acebeaebbb64dcf0d8966a21ecb244285499fb6c..970a186fac533e082cba5200441ff4c60846d44a 100644
--- a/python/paddle/fluid/layers/nn.py
+++ b/python/paddle/fluid/layers/nn.py
@@ -799,7 +799,22 @@ def gru_unit(input,
     return updated_hidden, reset_hidden_pre, gate
 
 
+@templatedoc()
 def linear_chain_crf(input, label, param_attr=None):
+    """
+    Linear Chain CRF.
+
+    ${comment}
+
+    Args:
+        input(${emission_type}): ${emission_comment}
+        label(${label_type}): ${label_comment}
+        param_attr(ParamAttr): The attribute of the learnable parameter.
+
+    Returns:
+        ${log_likelihood_comment}
+
+    """
     helper = LayerHelper('linear_chain_crf', **locals())
     size = input.shape[1]
     transition = helper.create_parameter(
@@ -825,7 +840,19 @@ def linear_chain_crf(input, label, param_attr=None):
     return log_likelihood
 
 
+@templatedoc()
 def crf_decoding(input, param_attr, label=None):
+    """
+    ${comment}
+
+    Args:
+        input(${emission_type}): ${emission_comment}
+        param_attr(ParamAttr): The parameter attribute for training.
+        label(${label_type}): ${label_comment}
+
+    Returns:
+        ${viterbi_path_comment}
+    """
     helper = LayerHelper('crf_decoding', **locals())
     transition = helper.get_parameter(param_attr.name)
     viterbi_path = helper.create_tmp_variable(dtype=helper.input_dtype())