From 61116151cce8fe5b397555a65f7b55001b8e416b Mon Sep 17 00:00:00 2001
From: Mattias Ellert <mattias.ellert@physics.uu.se>
Date: Fri, 23 Apr 2021 21:39:17 +0200
Subject: [PATCH] Compat with no f-strings

---
 tutorials/tmva/PyTorch_Generate_CNN_Model.py | 12 ++++++------
 1 file changed, 6 insertions(+), 6 deletions(-)

diff --git a/tutorials/tmva/PyTorch_Generate_CNN_Model.py b/tutorials/tmva/PyTorch_Generate_CNN_Model.py
index 7024112f03..5a314f86dd 100644
--- a/tutorials/tmva/PyTorch_Generate_CNN_Model.py
+++ b/tutorials/tmva/PyTorch_Generate_CNN_Model.py
@@ -56,7 +56,7 @@ def fit(model, train_loader, val_loader, num_epochs, batch_size, optimizer, crit
             # print train statistics
             running_train_loss += train_loss.item()
             if i % 4 == 3:    # print every 4 mini-batches
-                print(f"[{epoch+1}, {i+1}] train loss: {running_train_loss / 4 :.3f}")
+                print("[{}, {}] train loss: {:.3f}".format(epoch+1, i+1, running_train_loss / 4))
                 running_train_loss = 0.0
 
         if schedule:
@@ -75,15 +75,15 @@ def fit(model, train_loader, val_loader, num_epochs, batch_size, optimizer, crit
 
             curr_val = running_val_loss / len(val_loader)
             if save_best:
-               if best_val==None:
-                   best_val = curr_val
-               best_val = save_best(model, curr_val, best_val)
+                if best_val is None:
+                    best_val = curr_val
+                best_val = save_best(model, curr_val, best_val)
 
             # print val statistics per epoch
-            print(f"[{epoch+1}] val loss: {curr_val :.3f}")
+            print("[{}] val loss: {:.3f}".format(epoch+1, curr_val))
             running_val_loss = 0.0
 
-    print(f"Finished Training on {epoch+1} Epochs!")
+    print("Finished Training on {} Epochs!".format(epoch+1))
 
     return model
 
-- 
2.30.2