Format the doc of layers.auc

python/paddle/fluid/layers/metric.py

@@ -59,13 +59,13 @@ def auc(input, label, curve='ROC', num_thresholds=200):
     This implementation computes the AUC according to forward output and label.
     It is used very widely in binary classification evaluation. 
 
-    As a note: If input label contains values other than 0 and 1, it will be 
-    cast to bool. You can find the relevant definitions `here 
-     <https://en.wikipedia.org/wiki/Receiver_operating_characteristic
-      #Area_under_the_curve>`_.
+    Note: If input label contains values other than 0 and 1, it will be cast 
+    to `bool`. Find the relevant definitions `here <https://en.wikipedia.org\
+    /wiki/Receiver_operating_characteristic#Area_under_the_curve>`_.
 
     There are two types of possible curves:
-    1. ROC: Receiver operating characteristic
+
+        1. ROC: Receiver operating characteristic;
         2. PR: Precision Recall
 
     Args: