diff --git a/fluid/sequence_tagging_for_ner/train.py b/fluid/sequence_tagging_for_ner/train.py
index 02589f34bcc1ce792ae938c6228524c612df34f9..846dbc426a3476c9583bdd891e2b4feca7d3fc4b 100644
--- a/fluid/sequence_tagging_for_ner/train.py
+++ b/fluid/sequence_tagging_for_ner/train.py
@@ -98,27 +98,25 @@ def main(train_data_file, test_data_file, vocab_file, target_file, emb_file,
     for pass_id in xrange(num_passes):
         chunk_evaluator.reset(exe)
         for data in train_reader():
-            print len(data)
             cost, batch_precision, batch_recall, batch_f1_score = exe.run(
                 fluid.default_main_program(),
                 feed=feeder.feed(data),
                 fetch_list=[avg_cost] + chunk_evaluator.metrics)
             if batch_id % 5 == 0:
-                print(
-                    "Pass " + str(pass_id) + ", Batch " + str(batch_id) +
-                    ", Cost " + str(cost[0]) + ", Precision " +
-                    str(batch_precision[0]) + ", Recall " + str(batch_recall[0])
-                    + ", F1_score" + str(batch_f1_score[0]))
+                print("Pass " + str(pass_id) + ", Batch " + str(
+                    batch_id) + ", Cost " + str(cost[0]) + ", Precision " + str(
+                        batch_precision[0]) + ", Recall " + str(batch_recall[0])
+                      + ", F1_score" + str(batch_f1_score[0]))
             batch_id = batch_id + 1
 
         pass_precision, pass_recall, pass_f1_score = chunk_evaluator.eval(exe)
-        print("[TrainSet] pass_id:" + str(pass_id) + " pass_precision:" +
-              str(pass_precision) + " pass_recall:" + str(pass_recall) +
+        print("[TrainSet] pass_id:" + str(pass_id) + " pass_precision:" + str(
+            pass_precision) + " pass_recall:" + str(pass_recall) +
               " pass_f1_score:" + str(pass_f1_score))
         pass_precision, pass_recall, pass_f1_score = test(
             exe, chunk_evaluator, inference_program, test_reader, place)
-        print("[TestSet] pass_id:" + str(pass_id) + " pass_precision:" +
-              str(pass_precision) + " pass_recall:" + str(pass_recall) +
+        print("[TestSet] pass_id:" + str(pass_id) + " pass_precision:" + str(
+            pass_precision) + " pass_recall:" + str(pass_recall) +
               " pass_f1_score:" + str(pass_f1_score))
 
         save_dirname = os.path.join(model_save_dir, "params_pass_%d" % pass_id)