diff --git a/models.py b/models.py
index 7884e603..616cb924 100755
--- a/models.py
+++ b/models.py
@@ -224,7 +224,7 @@ class Darknet(nn.Module):
 
         self.module_defs = parse_model_cfg(cfg)
         self.module_list, self.routs = create_modules(self.module_defs, img_size)
-        self.yolo_layers = get_yolo_layers(self)
+        self.yolo_layers = torch_utils.find_modules(self, mclass=YOLOLayer)
         # torch_utils.initialize_weights(self)
 
         # Darknet Header https://github.com/AlexeyAB/darknet/issues/2914#issuecomment-496675346
@@ -333,10 +333,6 @@ class Darknet(nn.Module):
         torch_utils.model_info(self, verbose)
 
 
-def get_yolo_layers(model):
-    return [i for i, m in enumerate(model.module_list) if m.__class__.__name__ == 'YOLOLayer']  # [89, 101, 113]
-
-
 def load_darknet_weights(self, weights, cutoff=-1):
     # Parses and loads the weights stored in 'weights'
 
diff --git a/utils/torch_utils.py b/utils/torch_utils.py
index 9d2491f3..0e1ade3a 100644
--- a/utils/torch_utils.py
+++ b/utils/torch_utils.py
@@ -59,6 +59,11 @@ def initialize_weights(model):
             m.momentum = 0.03
 
 
+def find_modules(model, mclass=nn.Conv2d):
+    # finds layer indices matching module class 'mclass'
+    return [i for i, m in enumerate(model.module_list) if isinstance(m, mclass)]
+
+
 def fuse_conv_and_bn(conv, bn):
     # https://tehnokv.com/posts/fusing-batchnorm-and-conv/
     with torch.no_grad():