updates

models.py

@@ -35,15 +35,15 @@ def create_modules(module_defs, img_size, arc):
                                                    bias=not bn))
             if bn:
                 modules.add_module('BatchNorm2d', nn.BatchNorm2d(filters, momentum=0.1))
+            else:
+                routs.append(i)  # detection output (goes into yolo layer)
+
             if mdef['activation'] == 'leaky':  # activation study https://github.com/ultralytics/yolov3/issues/441
                 modules.add_module('activation', nn.LeakyReLU(0.1, inplace=True))
                 # modules.add_module('activation', nn.PReLU(num_parameters=1, init=0.10))
             elif mdef['activation'] == 'swish':
                 modules.add_module('activation', Swish())
 
-            if not bn:  # detection output layer
-                routs.append(i)
-
         elif mdef['type'] == 'maxpool':
             size = mdef['size']
             stride = mdef['stride']