modify some style

src/llmtuner/train/sft/workflow.py

@@ -17,12 +17,7 @@ from .trainer import CustomSeq2SeqTrainer
 if TYPE_CHECKING:
     from transformers import Seq2SeqTrainingArguments, TrainerCallback
 
-    from ...hparams import (
-        DataArguments,
-        FinetuningArguments,
-        GeneratingArguments,
-        ModelArguments,
-    )
+    from ...hparams import DataArguments, FinetuningArguments, GeneratingArguments, ModelArguments
 
 
 def run_sft(
@@ -36,14 +31,7 @@ def run_sft(
     tokenizer_modules = load_tokenizer(model_args)
     tokenizer = tokenizer_modules["tokenizer"]
     processor = tokenizer_modules["processor"]
-    dataset = get_dataset(
-        tokenizer,
-        model_args,
-        data_args,
-        training_args,
-        stage="sft",
-        processor=processor,
-    )
+    dataset = get_dataset(tokenizer, model_args, data_args, training_args, stage="sft", processor=processor)
     model = load_model(tokenizer, model_args, finetuning_args, training_args.do_train)
 
     if training_args.predict_with_generate:
@@ -54,7 +42,7 @@ def run_sft(
 
     data_collator = DataCollatorForSeq2Seq(
         tokenizer=tokenizer,
-        pad_to_multiple_of=(8 if tokenizer.padding_side == "right" else None),  # for shift short attention
+        pad_to_multiple_of=8 if tokenizer.padding_side == "right" else None,  # for shift short attention
         label_pad_token_id=(IGNORE_INDEX if data_args.ignore_pad_token_for_loss else tokenizer.pad_token_id),
     )
 
@@ -72,7 +60,7 @@ def run_sft(
         tokenizer=tokenizer,
         data_collator=data_collator,
         callbacks=callbacks,
-        compute_metrics=(ComputeMetrics(tokenizer) if training_args.predict_with_generate else None),
+        compute_metrics=ComputeMetrics(tokenizer) if training_args.predict_with_generate else None,
         **split_dataset(dataset, data_args, training_args),
     )