diff --git a/ppocr/data/simple_dataset.py b/ppocr/data/simple_dataset.py
index d2069d0d5fb608650bbaa2002a27a59265e334c5..1099fa44959d5441d793edf9fc0abd97fea430ca 100644
--- a/ppocr/data/simple_dataset.py
+++ b/ppocr/data/simple_dataset.py
@@ -27,17 +27,13 @@ class SimpleDataSet(Dataset):
         global_config = config['Global']
         dataset_config = config[mode]['dataset']
         loader_config = config[mode]['loader']
-        if 'data_num_per_epoch' in loader_config.keys():
-            data_num_per_epoch = loader_config['data_num_per_epoch']
-        else:
-            data_num_per_epoch = None
 
         self.delimiter = dataset_config.get('delimiter', '\t')
         label_file_list = dataset_config.pop('label_file_list')
         data_source_num = len(label_file_list)
         ratio_list = dataset_config.get("ratio_list", [1.0])
         if isinstance(ratio_list, (float, int)):
-            ratio_list = [float(ratio_list)] * len(data_source_num)
+            ratio_list = [float(ratio_list)] * int(data_source_num)
 
         assert len(
             ratio_list
@@ -46,34 +42,26 @@ class SimpleDataSet(Dataset):
         self.do_shuffle = loader_config['shuffle']
 
         logger.info("Initialize indexs of datasets:%s" % label_file_list)
-        self.data_lines = self.get_image_info_list(label_file_list, ratio_list,
-                                                   data_num_per_epoch)
+        self.data_lines = self.get_image_info_list(label_file_list, ratio_list)
         self.data_idx_order_list = list(range(len(self.data_lines)))
         if mode.lower() == "train":
             self.shuffle_data_random()
         self.ops = create_operators(dataset_config['transforms'], global_config)
 
-    def _sample_dataset(self, datas, sample_ratio, data_num_per_epoch=None):
+    def _sample_dataset(self, datas, sample_ratio):
         sample_num = round(len(datas) * sample_ratio)
 
-        if data_num_per_epoch is not None:
-            sample_num = int(data_num_per_epoch * sample_ratio)
-
         nums, rem = int(sample_num // len(datas)), int(sample_num % len(datas))
         return list(datas) * nums + random.sample(datas, rem)
 
-    def get_image_info_list(self,
-                            file_list,
-                            ratio_list,
-                            data_num_per_epoch=None):
+    def get_image_info_list(self, file_list, ratio_list):
         if isinstance(file_list, str):
             file_list = [file_list]
         data_lines = []
         for idx, file in enumerate(file_list):
             with open(file, "rb") as f:
                 lines = f.readlines()
-                lines = self._sample_dataset(lines, ratio_list[idx],
-                                             data_num_per_epoch)
+                lines = self._sample_dataset(lines, ratio_list[idx])
                 data_lines.extend(lines)
         return data_lines