Update resnext init

models/resnext.py

@@ -80,11 +80,10 @@ class ResNeXt(nn.Module):
 
         for m in self.modules():
             if isinstance(m, nn.Conv2d):
-                n = m.kernel_size[0] * m.kernel_size[1] * m.out_channels
+                nn.init.kaiming_normal_(m.weight, mode='fan_out', nonlinearity='relu')
-                m.weight.data.normal_(0, math.sqrt(2. / n))
             elif isinstance(m, nn.BatchNorm2d):
-                m.weight.data.fill_(1)
+                nn.init.constant_(m.weight, 1.)
-                m.bias.data.zero_()
+                nn.init.constant_(m.bias, 0.)
 
     def _make_layer(self, block, planes, blocks, stride=1):
         downsample = None