diff --git a/face_swapper/src/networks/aad.py b/face_swapper/src/networks/aad.py
index b766979..c018e96 100644
--- a/face_swapper/src/networks/aad.py
+++ b/face_swapper/src/networks/aad.py
@@ -51,7 +51,7 @@ class AADResBlock(nn.Module):
 			intermediate_channels = input_channels if index < (num_blocks - 1) else output_channels
 			primary_add_blocks.extend(
 				[
-					AADLayer(input_channels, attribute_channels, identity_channels),
+					FeatureModulation(input_channels, attribute_channels, identity_channels),
 					nn.ReLU(inplace = True),
 					nn.Conv2d(input_channels, intermediate_channels, kernel_size = 3, padding = 1, bias = False)
 				]
@@ -61,7 +61,7 @@ class AADResBlock(nn.Module):
 	def prepare_auxiliary_add_blocks(self, input_channels : int, attribute_channels : int, identity_channels : int, output_channels : int) -> None:
 		if input_channels > output_channels:
 			auxiliary_add_blocks = AADSequential(
-				AADLayer(input_channels, attribute_channels, identity_channels),
+				FeatureModulation(input_channels, attribute_channels, identity_channels),
 				nn.ReLU(inplace = True),
 				nn.Conv2d(input_channels, output_channels, kernel_size = 3, padding = 1, bias = False)
 			)
@@ -84,14 +84,14 @@ class AADSequential(nn.Module):
 
 	def forward(self, feature_map : Tensor, attribute_embedding : Embedding, identity_embedding : Embedding) -> Tensor:
 		for layer in self.layers:
-			if isinstance(layer, AADLayer):
+			if isinstance(layer, FeatureModulation):
 				feature_map = layer(feature_map, attribute_embedding, identity_embedding)
 			else:
 				feature_map = layer(feature_map)
 		return feature_map
 
 
-class AADLayer(nn.Module):
+class FeatureModulation(nn.Module):
 	def __init__(self, input_channels : int, attribute_channels : int, identity_channels : int) -> None:
 		super().__init__()
 		self.input_channels = input_channels