diff --git a/examples/model_compress/pruning/auto_pruners_torch.py b/examples/model_compress/pruning/auto_pruners_torch.py
index 51f3c12680..9bd596d880 100644
--- a/examples/model_compress/pruning/auto_pruners_torch.py
+++ b/examples/model_compress/pruning/auto_pruners_torch.py
@@ -186,7 +186,7 @@ def get_trained_model_optimizer(args, device, train_loader, val_loader, criterio
 
         if args.save_model:
             torch.save(state_dict, os.path.join(args.experiment_data_dir, 'model_trained.pth'))
-            print('Model trained saved to %s', args.experiment_data_dir)
+            print('Model trained saved to %s' % args.experiment_data_dir)
 
     return model, optimizer
 
@@ -312,7 +312,7 @@ def evaluator(model):
     if args.save_model:
         pruner.export_model(
             os.path.join(args.experiment_data_dir, 'model_masked.pth'), os.path.join(args.experiment_data_dir, 'mask.pth'))
-        print('Masked model saved to %s', args.experiment_data_dir)
+        print('Masked model saved to %s' % args.experiment_data_dir)
 
     # model speed up
     if args.speed_up:
@@ -336,7 +336,7 @@ def evaluator(model):
             result['performance']['speedup'] = evaluation_result
 
             torch.save(model.state_dict(), os.path.join(args.experiment_data_dir, 'model_speed_up.pth'))
-            print('Speed up model saved to %s', args.experiment_data_dir)
+            print('Speed up model saved to %s' % args.experiment_data_dir)
         flops, params, _ = count_flops_params(model, get_input_size(args.dataset))
         result['flops']['speedup'] = flops
         result['params']['speedup'] = params
@@ -367,7 +367,7 @@ def evaluator(model):
                 torch.save(model.state_dict(), os.path.join(args.experiment_data_dir, 'model_fine_tuned.pth'))
 
     print('Evaluation result (fine tuned): %s' % best_acc)
-    print('Fined tuned model saved to %s', args.experiment_data_dir)
+    print('Fined tuned model saved to %s' % args.experiment_data_dir)
     result['performance']['finetuned'] = best_acc
 
     with open(os.path.join(args.experiment_data_dir, 'result.json'), 'w+') as f: