modify style

src/llmtuner/model/utils/visual.py

@@ -8,7 +8,7 @@ from ...extras.logging import get_logger
 
 
 if TYPE_CHECKING:
-    from transformers import PretrainedConfig, PreTrainedModel, LlavaConfig
+    from transformers import LlavaConfig, PretrainedConfig, PreTrainedModel
 
     from ...hparams import ModelArguments
 
@@ -29,8 +29,10 @@ def autocast_projector_dtype(
     ) -> "torch.Tensor":
         return output.to(model_args.compute_dtype)
 
-    if hasattr(model, mm_projector_name) and (getattr(model.config, "quantization_method", None)
-                                              or "Yi" in getattr(model.config.text_config, "_name_or_path", None)):
+    if hasattr(model, mm_projector_name) and (
+        getattr(model.config, "quantization_method", None)
+        or "Yi" in getattr(model.config.text_config, "_name_or_path", None)
+    ):
         logger.info("Casting multimodal projector outputs in {}.".format(model_args.compute_dtype))
         mm_projector: "torch.nn.Module" = getattr(model, mm_projector_name)
         mm_projector.register_forward_hook(_mm_projector_forward_post_hook)

src/llmtuner/train/sft/trainer.py

@@ -5,7 +5,7 @@ from typing import TYPE_CHECKING, Any, Dict, List, Optional, Tuple, Union
 
 import numpy as np
 import torch
-from transformers import Seq2SeqTrainer, ProcessorMixin
+from transformers import ProcessorMixin, Seq2SeqTrainer
 
 from ...extras.constants import IGNORE_INDEX
 from ...extras.logging import get_logger
@@ -127,4 +127,4 @@ class CustomSeq2SeqTrainer(Seq2SeqTrainer):
         if self.processor is not None:
             if output_dir is None:
                 output_dir = self.args.output_dir
-            getattr(self.processor, "image_processor").save_pretrained(output_dir)
+            getattr(self.processor, "image_processor").save_pretrained(output_dir)