diff --git a/fluid/text_classification/train.py b/fluid/text_classification/train.py
index ea3e43f5b5bfe1744205b273b992c5f71e4ef855..9078f4788319dbf76677c86eef53445fa1e85c1a 100644
--- a/fluid/text_classification/train.py
+++ b/fluid/text_classification/train.py
@@ -55,7 +55,7 @@ def train(train_reader,
     feeder = fluid.DataFeeder(feed_list=[data, label], place=place)
 
     # For internal continuous evaluation
-    if 'CE_MODE_X' in os.environ:
+    if "CE_MODE_X" in os.environ:
         fluid.default_startup_program().random_seed = 110
     exe.run(fluid.default_startup_program())
     for pass_id in xrange(pass_num):
@@ -80,7 +80,7 @@ def train(train_reader,
 
         pass_end = time.time()
         # For internal continuous evaluation
-        if 'CE_MODE_X' in os.environ:
+        if "CE_MODE_X" in os.environ:
             print("kpis	train_acc	%f" % avg_acc)
             print("kpis	train_cost	%f" % avg_cost)
             print("kpis	train_duration	%f" % (pass_end - pass_start))
diff --git a/fluid/text_classification/utils.py b/fluid/text_classification/utils.py
index 874679c3e2f9fe0c640d6da4f25d503023adcb65..3c2fc559e7b257731c1dcfcb239a04b4846d1097 100644
--- a/fluid/text_classification/utils.py
+++ b/fluid/text_classification/utils.py
@@ -65,7 +65,7 @@ def prepare_data(data_type="imdb",
             raise RuntimeError("No such dataset")
 
     if data_type == "imdb":
-        if 'CE_MODE_X' in os.environ:
+        if "CE_MODE_X" in os.environ:
             train_reader = paddle.batch(
                 paddle.dataset.imdb.train(word_dict), batch_size=batch_size)