From 61116151cce8fe5b397555a65f7b55001b8e416b Mon Sep 17 00:00:00 2001 From: Mattias Ellert 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