Move mask_factor and noise_factor to modifier block

hyperswap/README.md

@@ -90,14 +90,18 @@ mask_weight = 5.0
 [training.trainer]
 accumulate_size = 4
 gradient_clip = 20.0
-mask_factor = 0.01
-noise_factor = 0.05
 max_epochs = 50
 strategy = auto
 precision = 16-mixed
 preview_frequency = 100
 ```
 
+```
+[training.modifier]
+mask_factor = 0.01
+noise_factor = 0.05
+```
+
 ```
 [training.optimizer.generator]
 learning_rate = 0.0004

hyperswap/config.ini

@@ -48,13 +48,15 @@ mask_weight =
 [training.trainer]
 accumulate_size =
 gradient_clip =
-mask_factor =
-noise_factor =
 max_epochs =
 strategy =
 precision =
 preview_frequency =
 
+[training.modifier]
+mask_factor =
+noise_factor =
+
 [training.optimizer.generator]
 learning_rate =
 momentum =

hyperswap/src/training.py

@@ -35,9 +35,9 @@ class HyperSwapTrainer(LightningModule):
 		self.config_face_masker_path = config_parser.get('training.model', 'face_masker_path')
 		self.config_accumulate_size = config_parser.getfloat('training.trainer', 'accumulate_size')
 		self.config_gradient_clip = config_parser.getfloat('training.trainer', 'gradient_clip')
-		self.config_mask_factor = config_parser.getfloat('training.trainer', 'mask_factor')
-		self.config_noise_factor = config_parser.getfloat('training.trainer', 'noise_factor')
 		self.config_preview_frequency = config_parser.getint('training.trainer', 'preview_frequency')
+		self.config_mask_factor = config_parser.getfloat('training.modifier', 'mask_factor')
+		self.config_noise_factor = config_parser.getfloat('training.modifier', 'noise_factor')
 		self.config_generator_learning_rate = config_parser.getfloat('training.optimizer.generator', 'learning_rate')
 		self.config_generator_momentum = config_parser.getfloat('training.optimizer.generator', 'momentum')
 		self.config_generator_scheduler_factor = config_parser.getfloat('training.optimizer.generator', 'scheduler_factor')