make style

examples/run_lm_finetuning.py

@@ -228,8 +228,10 @@ def train(args, train_dataset, model: PreTrainedModel, tokenizer: PreTrainedToke
     )
 
     # Check if saved optimizer or scheduler states exist
-    if args.model_name_or_path and os.path.isfile(os.path.join(args.model_name_or_path, "optimizer.pt")) and os.path.isfile(
-        os.path.join(args.model_name_or_path, "scheduler.pt")
+    if (
+        args.model_name_or_path
+        and os.path.isfile(os.path.join(args.model_name_or_path, "optimizer.pt"))
+        and os.path.isfile(os.path.join(args.model_name_or_path, "scheduler.pt"))
     ):
         # Load in optimizer and scheduler states
         optimizer.load_state_dict(torch.load(os.path.join(args.model_name_or_path, "optimizer.pt")))
@@ -587,9 +589,7 @@ def main():
     if args.should_continue:
         sorted_checkpoints = _sorted_checkpoints(args)
         if len(sorted_checkpoints) == 0:
-            raise ValueError(
-                "Used --should_continue but no checkpoint was found in --output_dir."
-            )
+            raise ValueError("Used --should_continue but no checkpoint was found in --output_dir.")
         else:
             args.model_name_or_path = sorted_checkpoints[-1]