@@ -42,13 +42,15 @@ def _cfg(url='', **kwargs):
4242 interpolation = 'bicubic' ),
4343 'resnet26d' : _cfg (
4444 url = 'https://github.com/rwightman/pytorch-image-models/releases/download/v0.1-weights/resnet26d-69e92c46.pth' ,
45- interpolation = 'bicubic' ),
45+ interpolation = 'bicubic' ,
46+ first_conv = 'conv1.0' ),
4647 'resnet50' : _cfg (
4748 url = 'https://github.com/rwightman/pytorch-image-models/releases/download/v0.1-weights/resnet50_ram-a26f946b.pth' ,
4849 interpolation = 'bicubic' ),
4950 'resnet50d' : _cfg (
5051 url = '' ,
51- interpolation = 'bicubic' ),
52+ interpolation = 'bicubic' ,
53+ first_conv = 'conv1.0' ),
5254 'resnet101' : _cfg (url = 'https://download.pytorch.org/models/resnet101-5d3b4d8f.pth' ),
5355 'resnet152' : _cfg (url = 'https://download.pytorch.org/models/resnet152-b121ed2d.pth' ),
5456 'tv_resnet34' : _cfg (url = 'https://download.pytorch.org/models/resnet34-333f7ec4.pth' ),
@@ -62,7 +64,8 @@ def _cfg(url='', **kwargs):
6264 interpolation = 'bicubic' ),
6365 'resnext50d_32x4d' : _cfg (
6466 url = 'https://github.com/rwightman/pytorch-image-models/releases/download/v0.1-weights/resnext50d_32x4d-103e99f8.pth' ,
65- interpolation = 'bicubic' ),
67+ interpolation = 'bicubic' ,
68+ first_conv = 'conv1.0' ),
6669 'resnext101_32x4d' : _cfg (url = '' ),
6770 'resnext101_32x8d' : _cfg (url = 'https://download.pytorch.org/models/resnext101_32x8d-8ba56ff5.pth' ),
6871 'resnext101_64x4d' : _cfg (url = '' ),
@@ -118,7 +121,8 @@ def _cfg(url='', **kwargs):
118121 interpolation = 'bicubic' ),
119122 'seresnet50tn' : _cfg (
120123 url = '' ,
121- interpolation = 'bicubic' ),
124+ interpolation = 'bicubic' ,
125+ first_conv = 'conv1.0' ),
122126 'seresnet101' : _cfg (
123127 url = '' ,
124128 interpolation = 'bicubic' ),
@@ -132,13 +136,16 @@ def _cfg(url='', **kwargs):
132136 interpolation = 'bicubic' ),
133137 'seresnext26d_32x4d' : _cfg (
134138 url = 'https://github.com/rwightman/pytorch-image-models/releases/download/v0.1-weights/seresnext26d_32x4d-80fa48a3.pth' ,
135- interpolation = 'bicubic' ),
139+ interpolation = 'bicubic' ,
140+ first_conv = 'conv1.0' ),
136141 'seresnext26t_32x4d' : _cfg (
137142 url = 'https://github.com/rwightman/pytorch-image-models/releases/download/v0.1-weights/seresnext26t_32x4d-361bc1c4.pth' ,
138- interpolation = 'bicubic' ),
143+ interpolation = 'bicubic' ,
144+ first_conv = 'conv1.0' ),
139145 'seresnext26tn_32x4d' : _cfg (
140146 url = 'https://github.com/rwightman/pytorch-image-models/releases/download/v0.1-weights/seresnext26tn_32x4d-569cb627.pth' ,
141- interpolation = 'bicubic' ),
147+ interpolation = 'bicubic' ,
148+ first_conv = 'conv1.0' ),
142149 'seresnext50_32x4d' : _cfg (
143150 interpolation = 'bicubic' ),
144151 'seresnext101_32x4d' : _cfg (
@@ -149,7 +156,8 @@ def _cfg(url='', **kwargs):
149156 interpolation = 'bicubic' ),
150157 'senet154' : _cfg (
151158 url = '' ,
152- interpolation = 'bicubic' ),
159+ interpolation = 'bicubic' ,
160+ first_conv = 'conv1.0' ),
153161
154162 # Efficient Channel Attention ResNets
155163 'ecaresnet18' : _cfg (),
@@ -159,21 +167,26 @@ def _cfg(url='', **kwargs):
159167 interpolation = 'bicubic' ),
160168 'ecaresnet50d' : _cfg (
161169 url = 'https://imvl-automl-sh.oss-cn-shanghai.aliyuncs.com/darts/hyperml/hyperml/job_45402/outputs/ECAResNet50D_833caf58.pth' ,
162- interpolation = 'bicubic' ),
170+ interpolation = 'bicubic' ,
171+ first_conv = 'conv1.0' ),
163172 'ecaresnet50d_pruned' : _cfg (
164173 url = 'https://imvl-automl-sh.oss-cn-shanghai.aliyuncs.com/darts/hyperml/hyperml/job_45899/outputs/ECAResNet50D_P_9c67f710.pth' ,
165- interpolation = 'bicubic' ),
174+ interpolation = 'bicubic' ,
175+ first_conv = 'conv1.0' ),
166176 'ecaresnet101d' : _cfg (
167177 url = 'https://imvl-automl-sh.oss-cn-shanghai.aliyuncs.com/darts/hyperml/hyperml/job_45402/outputs/ECAResNet101D_281c5844.pth' ,
168- interpolation = 'bicubic' ),
178+ interpolation = 'bicubic' ,
179+ first_conv = 'conv1.0' ),
169180 'ecaresnet101d_pruned' : _cfg (
170181 url = 'https://imvl-automl-sh.oss-cn-shanghai.aliyuncs.com/darts/hyperml/hyperml/job_45610/outputs/ECAResNet101D_P_75a3370e.pth' ,
171- interpolation = 'bicubic' ),
182+ interpolation = 'bicubic' ,
183+ first_conv = 'conv1.0' ),
172184
173185 # Efficient Channel Attention ResNeXts
174186 'ecaresnext26tn_32x4d' : _cfg (
175187 url = '' ,
176- interpolation = 'bicubic' ),
188+ interpolation = 'bicubic' ,
189+ first_conv = 'conv1.0' ),
177190 'ecaresnext50_32x4d' : _cfg (
178191 url = '' ,
179192 interpolation = 'bicubic' ),
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