add wide resnet

Author: szagoruyko

hubconf.py

@@ -5,7 +5,7 @@
 from torchvision.models.densenet import densenet121, densenet169, densenet201, densenet161
 from torchvision.models.inception import inception_v3
 from torchvision.models.resnet import resnet18, resnet34, resnet50, resnet101, resnet152,\
-    resnext50_32x4d, resnext101_32x8d
+    resnext50_32x4d, resnext101_32x8d, wide_resnet50_2, wide_resnet101_2
 from torchvision.models.squeezenet import squeezenet1_0, squeezenet1_1
 from torchvision.models.vgg import vgg11, vgg13, vgg16, vgg19, vgg11_bn, vgg13_bn, vgg16_bn, vgg19_bn
 from torchvision.models.segmentation import fcn_resnet101, deeplabv3_resnet101

torchvision/models/resnet.py

@@ -14,6 +14,8 @@
     'resnet152': 'https://download.pytorch.org/models/resnet152-b121ed2d.pth',
     'resnext50_32x4d': 'https://download.pytorch.org/models/resnext50_32x4d-7cdf4587.pth',
     'resnext101_32x8d': 'https://download.pytorch.org/models/resnext101_32x8d-8ba56ff5.pth',
+    'wide_resnet50_2': 'https://s3.amazonaws.com/modelzoo-networks/wide_resnet50_2-2e1fed99.pth.tar',
+    'wide_resnet101_2': 'https://s3.amazonaws.com/modelzoo-networks/wide_resnet101_2-32ee1156.pth.tar',
 }
 
 
@@ -294,3 +296,15 @@ def resnext101_32x8d(pretrained=False, progress=True, **kwargs):
     kwargs['width_per_group'] = 8
     return _resnet('resnext101_32x8d', Bottleneck, [3, 4, 23, 3],
                    pretrained, progress, **kwargs)
+
+
+def wide_resnet50_2(pretrained=False, progress=True, **kwargs):
+    kwargs['width_per_group'] = 64 * 2
+    return _resnet('wide_resnet50_2', Bottleneck, [3, 4, 6, 3],
+                   pretrained, progress, **kwargs)
+
+
+def wide_resnet101_2(pretrained=False, progress=True, **kwargs):
+    kwargs['width_per_group'] = 64 * 2
+    return _resnet('wide_resnet101_2', Bottleneck, [3, 4, 23, 3],
+                   pretrained, progress, **kwargs)