Update bias_auc.py

bias_auc.py

@@ -146,11 +146,11 @@ class BiasAUC(evaluate.Metric):
             mean_value = np.power(np.sum(metric_values)/(len(result) - 1),  1/power_value)
             result['Overall generalized mean'][f"{metric}"] = mean_value
         y_preds = [output[1] for output in outputs]
-        try:
-            result['Overall generalized mean']["Overall AUC"] = roc_auc_score(labels, y_preds)
-        except ValueError:
-            result['Overall generalized mean']["Overall AUC"] = np.nan
-        return result        
+        # try:
+        #     result['Overall generalized mean']["Overall AUC"] = roc_auc_score(labels, y_preds)
+        # except ValueError:
+        #     result['Overall generalized mean']["Overall AUC"] = np.nan
+        # return result        
     
     def _compute(self, target, label, output, subgroups=None):
         if subgroups is None: