diff --git a/nnunetv2/training/nnUNetTrainer/variants/data_augmentation/nnUNetTrainerDA5.py b/nnunetv2/training/nnUNetTrainer/variants/data_augmentation/nnUNetTrainerDA5.py
index f1c283fd1..7250fb845 100644
--- a/nnunetv2/training/nnUNetTrainer/variants/data_augmentation/nnUNetTrainerDA5.py
+++ b/nnunetv2/training/nnUNetTrainer/variants/data_augmentation/nnUNetTrainerDA5.py
@@ -233,7 +233,7 @@ def get_training_transforms(patch_size: Union[np.ndarray, Tuple[int]],
 
         tr_transforms.append(
             BrightnessGradientAdditiveTransform(
-                _transform_scale,
+                _brightnessadditive_localgamma_transform_scale,
                 (-0.5, 1.5),
                 max_strength=_brightness_gradient_additive_max_strength,
                 mean_centered=False,
@@ -245,7 +245,7 @@ def get_training_transforms(patch_size: Union[np.ndarray, Tuple[int]],
 
         tr_transforms.append(
             LocalGammaTransform(
-                _transform_scale,
+                _brightnessadditive_localgamma_transform_scale,
                 (-0.5, 1.5),
                 _local_gamma_gamma,
                 same_for_all_channels=False,
@@ -353,15 +353,19 @@ def get_dataloaders(self):
 
         return mt_gen_train, mt_gen_val
 
-def _transform_scale(x, y):
+
+def _brightnessadditive_localgamma_transform_scale(x, y):
     return np.exp(np.random.uniform(np.log(x[y] // 6), np.log(x[y])))
 
+
 def _brightness_gradient_additive_max_strength(_x, _y):
     return np.random.uniform(-5, -1) if np.random.uniform() < 0.5 else np.random.uniform(1, 5)
 
+
 def _local_gamma_gamma():
     return np.random.uniform(0.01, 0.8) if np.random.uniform() < 0.5 else np.random.uniform(1.5, 4)
 
+
 class nnUNetTrainerDA5Segord0(nnUNetTrainerDA5):
     def get_dataloaders(self):
         """