[NFC] polish applications/Chat/examples/train_reward_model.py code style (#4271)

applications/Chat/examples/train_reward_model.py

@@ -150,9 +150,7 @@ def train(args):
                                  pin_memory=True)
 
     lr_scheduler = CosineAnnealingLR(optim, train_dataloader.__len__() // 100)
-    strategy_dict = strategy.prepare(
-        dict(model=model, optimizer=optim, lr_scheduler=lr_scheduler)
-    )
+    strategy_dict = strategy.prepare(dict(model=model, optimizer=optim, lr_scheduler=lr_scheduler))
     model = strategy_dict['model']
     optim = strategy_dict['optimizer']
     lr_scheduler = strategy_dict['lr_scheduler']
@@ -163,9 +161,7 @@ def train(args):
                                  loss_fn=loss_fn,
                                  max_epochs=args.max_epochs)
 
-    trainer.fit(train_dataloader=train_dataloader,
-                valid_dataloader=valid_dataloader,
-                eval_dataloader=eval_dataloader)
+    trainer.fit(train_dataloader=train_dataloader, valid_dataloader=valid_dataloader, eval_dataloader=eval_dataloader)
     # save model checkpoint after fitting on only rank0
     strategy.save_model(model, args.save_path, only_rank0=True)
     # save optimizer checkpoint on all ranks