diff --git a/src/model/common.py b/src/model/common.py
index aeee3351..d5b159d4 100644
--- a/src/model/common.py
+++ b/src/model/common.py
@@ -26,7 +26,7 @@ def __init__(
         self, conv, in_channels, out_channels, kernel_size, stride=1, bias=False,
         bn=True, act=nn.ReLU(True)):
 
-        m = [conv(in_channels, out_channels, kernel_size, bias=bias)]
+        m = [conv(in_channels, out_channels, kernel_size, bias=(bias and not bn))]
         if bn:
             m.append(nn.BatchNorm2d(out_channels))
         if act is not None:
@@ -42,7 +42,7 @@ def __init__(
         super(ResBlock, self).__init__()
         m = []
         for i in range(2):
-            m.append(conv(n_feats, n_feats, kernel_size, bias=bias))
+            m.append(conv(n_feats, n_feats, kernel_size, bias=(bias and not bn)))
             if bn:
                 m.append(nn.BatchNorm2d(n_feats))
             if i == 0:
@@ -63,7 +63,7 @@ def __init__(self, conv, scale, n_feats, bn=False, act=False, bias=True):
         m = []
         if (scale & (scale - 1)) == 0:    # Is scale = 2^n?
             for _ in range(int(math.log(scale, 2))):
-                m.append(conv(n_feats, 4 * n_feats, 3, bias))
+                m.append(conv(n_feats, 4 * n_feats, 3, bias=(bias and not bn)))
                 m.append(nn.PixelShuffle(2))
                 if bn:
                     m.append(nn.BatchNorm2d(n_feats))