Add regnety_160 weights from DeiT teacher model, update that and my regnety_032 weights to use higher test size.

timm/models/regnet.py

@@ -57,12 +57,13 @@ model_cfgs = dict(
 )
 
 
-def _cfg(url=''):
+def _cfg(url='', **kwargs):
     return {
         'url': url, 'num_classes': 1000, 'input_size': (3, 224, 224), 'pool_size': (7, 7),
         'crop_pct': 0.875, 'interpolation': 'bicubic',
         'mean': IMAGENET_DEFAULT_MEAN, 'std': IMAGENET_DEFAULT_STD,
         'first_conv': 'stem.conv', 'classifier': 'head.fc',
+        **kwargs
     }
 
 
@@ -84,12 +85,16 @@ default_cfgs = dict(
     regnety_006=_cfg(url='https://github.com/rwightman/pytorch-image-models/releases/download/v0.1-regnet/regnety_006-c67e57ec.pth'),
     regnety_008=_cfg(url='https://github.com/rwightman/pytorch-image-models/releases/download/v0.1-regnet/regnety_008-dc900dbe.pth'),
     regnety_016=_cfg(url='https://github.com/rwightman/pytorch-image-models/releases/download/v0.1-regnet/regnety_016-54367f74.pth'),
-    regnety_032=_cfg(url='https://github.com/rwightman/pytorch-image-models/releases/download/v0.1-weights/regnety_032_ra-7f2439f9.pth'),
+    regnety_032=_cfg(
+        url='https://github.com/rwightman/pytorch-image-models/releases/download/v0.1-weights/regnety_032_ra-7f2439f9.pth',
+        crop_pct=1.0, test_input_size=(3, 288, 288)),
     regnety_040=_cfg(url='https://github.com/rwightman/pytorch-image-models/releases/download/v0.1-regnet/regnety_040-f0d569f9.pth'),
     regnety_064=_cfg(url='https://github.com/rwightman/pytorch-image-models/releases/download/v0.1-regnet/regnety_064-0a48325c.pth'),
     regnety_080=_cfg(url='https://github.com/rwightman/pytorch-image-models/releases/download/v0.1-regnet/regnety_080-e7f3eb93.pth'),
     regnety_120=_cfg(url='https://github.com/rwightman/pytorch-image-models/releases/download/v0.1-regnet/regnety_120-721ba79a.pth'),
-    regnety_160=_cfg(url='https://dl.fbaipublicfiles.com/deit/regnety_160-a5fe301d.pth'),
+    regnety_160=_cfg(
+        url='https://dl.fbaipublicfiles.com/deit/regnety_160-a5fe301d.pth',  # from Facebook DeiT GitHub repository
+        crop_pct=1.0, test_input_size=(3, 288, 288)),
     regnety_320=_cfg(url='https://github.com/rwightman/pytorch-image-models/releases/download/v0.1-regnet/regnety_320-ba464b29.pth'),
 )
 
@@ -328,11 +333,20 @@ class RegNet(nn.Module):
         return x
 
 
+def _filter_fn(state_dict):
+    """ convert patch embedding weight from manual patchify + linear proj to conv"""
+    if 'model' in state_dict:
+        # For DeiT trained regnety_160 pretraiend model
+        state_dict = state_dict['model']
+    return state_dict
+
+
 def _create_regnet(variant, pretrained, **kwargs):
     return build_model_with_cfg(
         RegNet, variant, pretrained,
         default_cfg=default_cfgs[variant],
         model_cfg=model_cfgs[variant],
+        pretrained_filter_fn=_filter_fn,
         **kwargs)