Fix spinenet bug

codes/models/archs/spinenet_arch.py

@@ -299,16 +299,15 @@ class SpineNet(nn.Module):
                     constant_init(m.bn2, 0)
 
     def forward(self, input):
-        # Spinenet is pretrained on the standard pytorch input norm. The image will need to
-        # be normalized before feeding it through.
+        if self.conv1 is not None:
             if self.use_input_norm:
                 mean = torch.Tensor([0.485, 0.456, 0.406]).view(1, 3, 1, 1).to(input.device)
                 std = torch.Tensor([0.229, 0.224, 0.225]).view(1, 3, 1, 1).to(input.device)
                 input = (input - mean) / std
-
-        if self.conv1 is not None:
             feat = self.conv1(input)
             feat = self.maxpool(feat)
+        else:
+            feat = input
         feat1 = self.init_block1(feat)
         feat2 = self.init_block2(feat1)
         block_feats = [feat1, feat2]