diff --git a/ppocr/data/simple_dataset.py b/ppocr/data/simple_dataset.py
index c8708a4ab94f1761551dc9ecbe17316ac0ab67f7..e9c3394cbe930d5169ae005e7582a2902e697b7e 100644
--- a/ppocr/data/simple_dataset.py
+++ b/ppocr/data/simple_dataset.py
@@ -14,7 +14,6 @@
 import numpy as np
 import os
 import random
-import traceback
 from paddle.io import Dataset
 
 from .imaug import transform, create_operators
@@ -46,7 +45,6 @@ class SimpleDataSet(Dataset):
         self.seed = seed
         logger.info("Initialize indexs of datasets:%s" % label_file_list)
         self.data_lines = self.get_image_info_list(label_file_list, ratio_list)
-        self.check_data()
         self.data_idx_order_list = list(range(len(self.data_lines)))
         if self.mode == "train" and self.do_shuffle:
             self.shuffle_data_random()
@@ -103,18 +101,25 @@ class SimpleDataSet(Dataset):
 
     def __getitem__(self, idx):
         file_idx = self.data_idx_order_list[idx]
-        data = self.data_lines[file_idx]
+        data_line = self.data_lines[file_idx]
         try:
+            data_line = data_line.decode('utf-8')
+            substr = data_line.strip("\n").split(self.delimiter)
+            file_name = substr[0]
+            label = substr[1]
+            img_path = os.path.join(self.data_dir, file_name)
+            data = {'img_path': img_path, 'label': label}
+            if not os.path.exists(img_path):
+                raise Exception("{} does not exist!".format(img_path))
             with open(data['img_path'], 'rb') as f:
                 img = f.read()
                 data['image'] = img
             data['ext_data'] = self.get_ext_data()
             outs = transform(data, self.ops)
-        except:
-            error_meg = traceback.format_exc()
+        except Exception as e:
             self.logger.error(
-                "When parsing file {} and label {}, error happened with msg: {}".format(
-                    data['img_path'],data['label'], error_meg))
+                "When parsing line {}, error happened with msg: {}".format(
+                    data_line, e))
             outs = None
         if outs is None:
             # during evaluation, we should fix the idx to get same results for many times of evaluation.
@@ -125,17 +130,3 @@ class SimpleDataSet(Dataset):
 
     def __len__(self):
         return len(self.data_idx_order_list)
-
-    def check_data(self):
-        new_data_lines = []
-        for data_line in self.data_lines:
-            data_line = data_line.decode('utf-8')
-            substr = data_line.strip("\n").strip("\r").split(self.delimiter)
-            file_name = substr[0]
-            label = substr[1]
-            img_path = os.path.join(self.data_dir, file_name)
-            if os.path.exists(img_path):
-                new_data_lines.append({'img_path': img_path, 'label': label})
-            else:
-                self.logger.info("{} does not exist!".format(img_path))
-        self.data_lines = new_data_lines
\ No newline at end of file
diff --git a/ppocr/modeling/architectures/distillation_model.py b/ppocr/modeling/architectures/distillation_model.py
index 2b1d3aae3b7303a61b20db15df5ce4bd9bb7b235..1e95fe574433eaca6f322ff47c8547cc1a29a248 100644
--- a/ppocr/modeling/architectures/distillation_model.py
+++ b/ppocr/modeling/architectures/distillation_model.py
@@ -46,7 +46,7 @@ class DistillationModel(nn.Layer):
                 pretrained = model_config.pop("pretrained")
             model = BaseModel(model_config)
             if pretrained is not None:
-                model = load_pretrained_params(model, pretrained)
+                load_pretrained_params(model, pretrained)
             if freeze_params:
                 for param in model.parameters():
                     param.trainable = False