diff --git a/dataset.py b/dataset.py
old mode 100644
new mode 100755
index 771ba1c..a73bc6b
--- a/dataset.py
+++ b/dataset.py
@@ -27,6 +27,8 @@ class Batch_Balanced_Dataset(object):
         _AlignCollate = AlignCollate(imgH=opt.imgH, imgW=opt.imgW)
         self.data_loader_list = []
         self.dataloader_iter_list = []
+        batch_size_list = []
+        Total_batch_size = 0
         for selected_d, batch_ratio_d in zip(opt.select_data, opt.batch_ratio):
             _batch_size = max(round(opt.batch_size * float(batch_ratio_d)), 1)
             print('-' * 80)
@@ -45,6 +47,8 @@ class Batch_Balanced_Dataset(object):
                            for offset, length in zip(_accumulate(dataset_split), dataset_split)]
             print(f'num total samples of {selected_d}: {total_number_dataset} x {opt.total_data_usage_ratio} (total_data_usage_ratio) = {len(_dataset)}')
             print(f'num samples of {selected_d} per batch: {opt.batch_size} x {float(batch_ratio_d)} (batch_ratio) = {_batch_size}')
+            batch_size_list.append(str(_batch_size))
+            Total_batch_size += _batch_size
 
             _data_loader = torch.utils.data.DataLoader(
                 _dataset, batch_size=_batch_size,
@@ -54,6 +58,9 @@ class Batch_Balanced_Dataset(object):
             self.data_loader_list.append(_data_loader)
             self.dataloader_iter_list.append(iter(_data_loader))
         print('-' * 80)
+        print('Total_batch_size: ', '+'.join(batch_size_list), '=', str(Total_batch_size))
+        opt.batch_size = Total_batch_size
+        print('-' * 80)
 
     def get_batch(self):
         balanced_batch_images = []