Add pretrained weights for FBNet-C

README.md

@@ -118,6 +118,7 @@ I've leveraged the training scripts in this repository to train a few of the mod
 | SE-ResNeXt-26 (32x4d) | 77.104 (22.896) | 93.316 (6.684) | 16.8M | bicubic |
 | SE-ResNet-34 | 74.808 (25.192) | 92.124 (7.876) | 22M | bilinear |
 | SE-ResNet-18 | 71.742 (28.258) | 90.334 (9.666) | 11.8M | bicubic |
+| FBNet-C | 74.830 (25.170 | 92.124 (7.876) | 5.6M | bilinear |
 | Single-Path NASNet 1.00 | 74.084 (25.916)  | 91.818 (8.182) | 4.42M | bilinear |
 
 ### Ported Weights

models/genmobilenet.py

@@ -63,7 +63,7 @@ default_cfgs = {
     'mobilenetv3_100': _cfg(url=''),
     'chamnetv1_100': _cfg(url=''),
     'chamnetv2_100': _cfg(url=''),
-    'fbnetc_100': _cfg(url=''),
+    'fbnetc_100': _cfg(url='https://www.dropbox.com/s/0ku2tztuibrynld/fbnetc_100-f49a0c5f.pth?dl=1'),
     'spnasnet_100': _cfg(url='https://www.dropbox.com/s/iieopt18rytkgaa/spnasnet_100-048bc3f4.pth?dl=1'),
 }
 
@@ -1227,6 +1227,9 @@ def mobilenetv3_100(num_classes, in_chans=3, pretrained=False, **kwargs):
 def fbnetc_100(num_classes, in_chans=3, pretrained=False, **kwargs):
     """ FBNet-C """
     default_cfg = default_cfgs['fbnetc_100']
+    if pretrained:
+        # pretrained model trained with non-default BN epsilon
+        kwargs['bn_eps'] = _BN_EPS_TF_DEFAULT
     model = _gen_fbnetc(1.0, num_classes=num_classes, in_chans=in_chans, **kwargs)
     model.default_cfg = default_cfg
     if pretrained: