diff --git a/face_swapper/src/models/generator.py b/face_swapper/src/models/generator.py
index 60c3f6b..d6fa9b6 100644
--- a/face_swapper/src/models/generator.py
+++ b/face_swapper/src/models/generator.py
@@ -16,18 +16,18 @@ class Generator(nn.Module):
 		id_channels = CONFIG.getint('training.model.generator', 'id_channels')
 		num_blocks = CONFIG.getint('training.model.generator', 'num_blocks')
 
-		self.attribute_encoder = UNet()
-		self.attribute_generator = AADGenerator(id_channels, num_blocks)
-		self.attribute_encoder.apply(init_weight)
-		self.attribute_generator.apply(init_weight)
+		self.unet = UNet()
+		self.aad_generator = AADGenerator(id_channels, num_blocks)
+		self.unet.apply(init_weight)
+		self.aad_generator.apply(init_weight)
 
 	def forward(self, source_embedding : Embedding, target_tensor : Tensor) -> Tensor:
 		target_attributes = self.get_attributes(target_tensor)
-		output_tensor = self.attribute_generator(target_attributes, source_embedding)
+		output_tensor = self.aad_generator(target_attributes, source_embedding)
 		return output_tensor
 
 	def get_attributes(self, input_tensor : Tensor) -> Attributes:
-		return self.attribute_encoder(input_tensor)
+		return self.unet(input_tensor)
 
 
 def init_weight(module : nn.Module) -> None:
diff --git a/face_swapper/src/training.py b/face_swapper/src/training.py
index d7c14fd..388a987 100644
--- a/face_swapper/src/training.py
+++ b/face_swapper/src/training.py
@@ -17,7 +17,7 @@ from .helper import calc_id_embedding
 from .models.discriminator import Discriminator
 from .models.generator import Generator
 from .models.loss import FaceSwapperLoss
-from .types import Batch, Embedding, TargetAttributes, VisionTensor
+from .types import Batch, Embedding, VisionTensor
 
 CONFIG = configparser.ConfigParser()
 CONFIG.read('config.ini')
@@ -31,9 +31,9 @@ class FaceSwapperTrainer(lightning.LightningModule, FaceSwapperLoss):
 		self.discriminator = Discriminator()
 		self.automatic_optimization = CONFIG.getboolean('training.trainer', 'automatic_optimization')
 
-	def forward(self, target_tensor : VisionTensor, source_embedding : Embedding) -> Tuple[VisionTensor, TargetAttributes]:
-		output = self.generator(source_embedding, target_tensor)
-		return output
+	def forward(self, target_tensor : VisionTensor, source_embedding : Embedding) -> Tensor:
+		output_tensor = self.generator(source_embedding, target_tensor)
+		return output_tensor
 
 	def configure_optimizers(self) -> Tuple[Optimizer, Optimizer]:
 		learning_rate = CONFIG.getfloat('training.trainer', 'learning_rate')