diff --git a/main_custom.py b/main_custom.py
index 7985488949223dca9e125d87214fe18e006d36ee..65b27ff39a61c7c771d609de13053b44c51be7c2 100644
--- a/main_custom.py
+++ b/main_custom.py
@@ -285,26 +285,26 @@ def save_pred(model, data_val, forward, output_path, file = False):
                 rt, intensity = rt.float(), intensity.float()
             if torch.cuda.is_available():
                 seq, charge, rt, intensity = seq.cuda(), charge.cuda(), rt.cuda(), intensity.cuda()
-            pr_rt, pr_intensity = model.forward(seq, charge)
-            pred_rt.extend(pr_rt.data.cpu().tolist())
-            pred_int.extend(pr_intensity.data.cpu().tolist())
-            seqs.extend(seq.data.cpu().tolist())
-            charges.extend(charge.data.cpu().tolist())
-            true_rt.extend(rt.data.cpu().tolist())
-            true_int.extend(intensity.data.cpu().tolist())
-            file_list.extend([files])
+                pr_rt, pr_intensity = model.forward(seq, charge)
+                pred_rt.extend(pr_rt.data.cpu().tolist())
+                pred_int.extend(pr_intensity.data.cpu().tolist())
+                seqs.extend(seq.data.cpu().tolist())
+                charges.extend(charge.data.cpu().tolist())
+                true_rt.extend(rt.data.cpu().tolist())
+                true_int.extend(intensity.data.cpu().tolist())
+                file_list.extend([files])
         else :
             for seq, charge, rt, intensity in data_val:
                 rt, intensity = rt.float(), intensity.float()
             if torch.cuda.is_available():
                 seq, charge, rt, intensity = seq.cuda(), charge.cuda(), rt.cuda(), intensity.cuda()
-            pr_rt, pr_intensity = model.forward(seq, charge)
-            pred_rt.extend(pr_rt.data.cpu().tolist())
-            pred_int.extend(pr_intensity.data.cpu().tolist())
-            seqs.extend(seq.data.cpu().tolist())
-            charges.extend(charge.data.cpu().tolist())
-            true_rt.extend(rt.data.cpu().tolist())
-            true_int.extend(intensity.data.cpu().tolist())
+                pr_rt, pr_intensity = model.forward(seq, charge)
+                pred_rt.extend(pr_rt.data.cpu().tolist())
+                pred_int.extend(pr_intensity.data.cpu().tolist())
+                seqs.extend(seq.data.cpu().tolist())
+                charges.extend(charge.data.cpu().tolist())
+                true_rt.extend(rt.data.cpu().tolist())
+                true_int.extend(intensity.data.cpu().tolist())
 
         data_frame['rt pred'] = pred_rt
         data_frame['seq'] = seqs