diff --git a/net.py b/net.py
index 4841dad..1791517 100644
--- a/net.py
+++ b/net.py
@@ -327,7 +327,7 @@ class DetailFeatureExtraction(nn.Module):
         super(DetailFeatureExtraction, self).__init__()
         INNmodules = [DetailNode(use) for _ in range(num_layers)]
         self.net = nn.Sequential(*INNmodules)
-        self.enhancement_module = WTConv2d(32, 32)
+        # self.enhancement_module = WTConv2d(32, 32)
 
     def forward(self, x): # 1 64 128 128
         z1, z2 = x[:, :x.shape[1] // 2], x[:, x.shape[1] // 2:x.shape[1]] # 1 32 128 128
@@ -346,7 +346,7 @@ class DetailFeatureFusion(nn.Module):
         super(DetailFeatureFusion, self).__init__()
         INNmodules = [DetailNode() for _ in range(num_layers)]
         self.net = nn.Sequential(*INNmodules)
-        self.enhancement_module = WTConv2d(32, 32)
+        # self.enhancement_module = WTConv2d(32, 32)
 
     def forward(self, x): # 1 64 128 128
         z1, z2 = x[:, :x.shape[1] // 2], x[:, x.shape[1] // 2:x.shape[1]] # 1 32 128 128
@@ -582,7 +582,7 @@ class DetailFeatureExtractionSAR(nn.Module):
         super(DetailFeatureExtractionSAR, self).__init__()
         INNmodules = [DetailNode(useBlock=1) for _ in range(num_layers)]
         self.net = nn.Sequential(*INNmodules)
-        self.enhancement_module = WTConv2d(32, 32)
+        # self.enhancement_module = WTConv2d(32, 32)
 
     def forward(self, x): # 1 64 128 128
         z1, z2 = x[:, :x.shape[1] // 2], x[:, x.shape[1] // 2:x.shape[1]] # 1 32 128 128