diff --git a/data/transforms.py b/data/transforms.py
index eecde8bd..5fe7da60 100644
--- a/data/transforms.py
+++ b/data/transforms.py
@@ -183,11 +183,11 @@ def transforms_imagenet_eval(
 
     if isinstance(img_size, tuple):
         assert len(img_size) == 2
-        if img_size[0] == img_size[1]:
+        if img_size[-1] == img_size[-2]:
             # fall-back to older behaviour so Resize scales to shortest edge if target is square
             scale_size = int(math.floor(img_size[0] / crop_pct))
         else:
-            scale_size = tuple([int(x[0] / crop_pct) for x in img_size])
+            scale_size = tuple([int(x / crop_pct) for x in img_size])
     else:
         scale_size = int(math.floor(img_size / crop_pct))
 
diff --git a/models/senet.py b/models/senet.py
index 28438683..75ffc398 100644
--- a/models/senet.py
+++ b/models/senet.py
@@ -25,7 +25,7 @@ __all__ = ['SENet', 'senet154', 'seresnet50', 'seresnet101', 'seresnet152',
 
 def _cfg(url=''):
     return {
-        'url': url, 'num_classes': 1000, 'input_size': (3, 224, 244), 'pool_size': (7, 7),
+        'url': url, 'num_classes': 1000, 'input_size': (3, 224, 224), 'pool_size': (7, 7),
         'crop_pct': 0.875, 'interpolation': 'bilinear',
         'mean': IMAGENET_DEFAULT_MEAN, 'std': IMAGENET_DEFAULT_STD,
         'first_conv': 'layer0.conv1', 'classifier': 'last_linear',