Add native PyTorch EfficientNet B1 and B2 weights. Not quite where I want them, but hitting the brick wall and moving on to other projects...

README.md

@@ -78,6 +78,16 @@ I've leveraged the training scripts in this repository to train a few of the mod
 | spnasnet_100 | 74.084 (25.916)  | 91.818 (8.182) | 4.42M | bilinear |
 | seresnet18 | 71.742 (28.258) | 90.334 (9.666) | 11.8M | bicubic |
 
+#### @ 240x240
+|Model | Prec@1 (Err) | Prec@5 (Err) | Param # | Image Scaling  |
+|---|---|---|---|---|
+| efficientnet_b1 | 78.692 (21.308) | 94.086 (5.914) | 7.79M | bicubic |
+
+#### @ 260x260
+|Model | Prec@1 (Err) | Prec@5 (Err) | Param # | Image Scaling  |
+|---|---|---|---|---|
+| efficientnet_b2 | 79.668 (20.332) | 94.634 (5.366) | 9.11M | bicubic |
+
 ### Ported Weights
 
 #### @ 224x224

timm/models/gen_efficientnet.py

@@ -81,15 +81,17 @@ default_cfgs = {
         url='https://github.com/rwightman/pytorch-image-models/releases/download/v0.1-weights/efficientnet_b0-d6904d92.pth',
         interpolation='bicubic'),
     'efficientnet_b1': _cfg(
-        url='', input_size=(3, 240, 240), pool_size=(8, 8)),
+        url='https://github.com/rwightman/pytorch-image-models/releases/download/v0.1-weights/efficientnet_b1-533bc792.pth',
+        input_size=(3, 240, 240), pool_size=(8, 8), interpolation='bicubic', crop_pct=0.882),
     'efficientnet_b2': _cfg(
-        url='', input_size=(3, 260, 260), pool_size=(9, 9)),
+        url='https://github.com/rwightman/pytorch-image-models/releases/download/v0.1-weights/efficientnet_b2-d4105846.pth',
+        input_size=(3, 260, 260), pool_size=(9, 9), interpolation='bicubic', crop_pct=0.890),
     'efficientnet_b3': _cfg(
-        url='', input_size=(3, 300, 300), pool_size=(10, 10)),
+        url='', input_size=(3, 300, 300), pool_size=(10, 10), crop_pct=0.904),
     'efficientnet_b4': _cfg(
-        url='', input_size=(3, 380, 380), pool_size=(12, 12)),
+        url='', input_size=(3, 380, 380), pool_size=(12, 12), crop_pct=0.922),
     'efficientnet_b5': _cfg(
-        url='', input_size=(3, 456, 456), pool_size=(15, 15)),
+        url='', input_size=(3, 456, 456), pool_size=(15, 15), crop_pct=0.934),
     'tf_efficientnet_b0': _cfg(
         url='https://github.com/rwightman/pytorch-image-models/releases/download/v0.1-weights/tf_efficientnet_b0-0af12548.pth',
         input_size=(3, 224, 224), interpolation='bicubic'),