diff --git a/models.py b/models.py
index 8a3460da..066fe0ca 100755
--- a/models.py
+++ b/models.py
@@ -22,12 +22,12 @@ def create_modules(module_defs, img_size, arc):
         if mdef['type'] == 'convolutional':
             bn = int(mdef['batch_normalize'])
             filters = int(mdef['filters'])
-            kernel_size = int(mdef['size'])
+            size = int(mdef['size'])
             stride = int(mdef['stride']) if 'stride' in mdef else (int(mdef['stride_y']), int(mdef['stride_x']))
-            pad = (kernel_size - 1) // 2 if int(mdef['pad']) else 0
+            pad = (size - 1) // 2 if int(mdef['pad']) else 0
             modules.add_module('Conv2d', nn.Conv2d(in_channels=output_filters[-1],
                                                    out_channels=filters,
-                                                   kernel_size=kernel_size,
+                                                   kernel_size=size,
                                                    stride=stride,
                                                    padding=pad,
                                                    bias=not bn))
@@ -40,10 +40,10 @@ def create_modules(module_defs, img_size, arc):
                 modules.add_module('activation', Swish())
 
         elif mdef['type'] == 'maxpool':
-            kernel_size = int(mdef['size'])
+            size = int(mdef['size'])
             stride = int(mdef['stride'])
-            maxpool = nn.MaxPool2d(kernel_size=kernel_size, stride=stride, padding=int((kernel_size - 1) // 2))
-            if kernel_size == 2 and stride == 1:  # yolov3-tiny
+            maxpool = nn.MaxPool2d(kernel_size=size, stride=stride, padding=int((size - 1) // 2))
+            if size == 2 and stride == 1:  # yolov3-tiny
                 modules.add_module('ZeroPad2d', nn.ZeroPad2d((0, 1, 0, 1)))
                 modules.add_module('MaxPool2d', maxpool)
             else: