diff --git a/models.py b/models.py
index c7bb0b80..347264fd 100755
--- a/models.py
+++ b/models.py
@@ -15,7 +15,7 @@ def create_modules(module_defs):
     hyperparams = module_defs.pop(0)
     output_filters = [int(hyperparams['channels'])]
     module_list = nn.ModuleList()
-    yolo_layer_count = 0
+
     for i, module_def in enumerate(module_defs):
         modules = nn.Sequential()
 
@@ -66,9 +66,8 @@ def create_modules(module_defs):
             nc = int(module_def['classes'])  # number of classes
             img_size = hyperparams['height']
             # Define detection layer
-            yolo_layer = YOLOLayer(anchors, nc, img_size, yolo_layer_count, cfg=hyperparams['cfg'])
+            yolo_layer = YOLOLayer(anchors, nc, img_size, cfg=hyperparams['cfg'])
             modules.add_module('yolo_%d' % i, yolo_layer)
-            yolo_layer_count += 1
 
         # Register module list and number of output filters
         module_list.append(modules)
@@ -100,7 +99,7 @@ class Upsample(nn.Module):
 
 
 class YOLOLayer(nn.Module):
-    def __init__(self, anchors, nc, img_size, yolo_layer, cfg):
+    def __init__(self, anchors, nc, img_size, cfg):
         super(YOLOLayer, self).__init__()
 
         self.anchors = torch.Tensor(anchors)