diff --git a/gfpgan/archs/gfpganv1_arch.py b/gfpgan/archs/gfpganv1_arch.py
index eaf3162..34ae5a2 100644
--- a/gfpgan/archs/gfpganv1_arch.py
+++ b/gfpgan/archs/gfpganv1_arch.py
@@ -3,7 +3,6 @@ import random
 import torch
 from basicsr.archs.stylegan2_arch import (ConvLayer, EqualConv2d, EqualLinear, ResBlock, ScaledLeakyReLU,
                                           StyleGAN2Generator)
-from basicsr.ops.fused_act import FusedLeakyReLU
 from basicsr.utils.registry import ARCH_REGISTRY
 from torch import nn
 from torch.nn import functional as F
@@ -170,10 +169,7 @@ class ConvUpLayer(nn.Module):
 
         # activation
         if activate:
-            if bias:
-                self.activation = FusedLeakyReLU(out_channels)
-            else:
-                self.activation = ScaledLeakyReLU(0.2)
+            self.activation = ScaledLeakyReLU(0.2)
         else:
             self.activation = None
 
diff --git a/gfpgan/archs/stylegan2_bilinear_arch.py b/gfpgan/archs/stylegan2_bilinear_arch.py
index 1342ee3..5cffb44 100644
--- a/gfpgan/archs/stylegan2_bilinear_arch.py
+++ b/gfpgan/archs/stylegan2_bilinear_arch.py
@@ -1,7 +1,6 @@
 import math
 import random
 import torch
-from basicsr.ops.fused_act import FusedLeakyReLU, fused_leaky_relu
 from basicsr.utils.registry import ARCH_REGISTRY
 from torch import nn
 from torch.nn import functional as F
@@ -190,7 +189,7 @@ class StyleConv(nn.Module):
             sample_mode=sample_mode,
             interpolation_mode=interpolation_mode)
         self.weight = nn.Parameter(torch.zeros(1))  # for noise injection
-        self.activate = FusedLeakyReLU(out_channels)
+        self.activate = ScaledLeakyReLU()
 
     def forward(self, x, style, noise=None):
         # modulate
@@ -568,10 +567,7 @@ class ConvLayer(nn.Sequential):
                 and not activate))
         # activation
         if activate:
-            if bias:
-                layers.append(FusedLeakyReLU(out_channels))
-            else:
-                layers.append(ScaledLeakyReLU(0.2))
+            layers.append(ScaledLeakyReLU(0.2))
 
         super(ConvLayer, self).__init__(*layers)