Fix paper links of VGG models (#3684)

Author: NicolasHug

torchvision/models/vgg.py

@@ -104,7 +104,7 @@ def _vgg(arch: str, cfg: str, batch_norm: bool, pretrained: bool, progress: bool
 
 def vgg11(pretrained: bool = False, progress: bool = True, **kwargs: Any) -> VGG:
     r"""VGG 11-layer model (configuration "A") from
-    `"Very Deep Convolutional Networks For Large-Scale Image Recognition" <https://arxiv.org/pdf/1409.1556.pdf>`._
+    `"Very Deep Convolutional Networks For Large-Scale Image Recognition" <https://arxiv.org/pdf/1409.1556.pdf>`_.
 
     Args:
         pretrained (bool): If True, returns a model pre-trained on ImageNet
@@ -115,7 +115,7 @@ def vgg11(pretrained: bool = False, progress: bool = True, **kwargs: Any) -> VGG
 
 def vgg11_bn(pretrained: bool = False, progress: bool = True, **kwargs: Any) -> VGG:
     r"""VGG 11-layer model (configuration "A") with batch normalization
-    `"Very Deep Convolutional Networks For Large-Scale Image Recognition" <https://arxiv.org/pdf/1409.1556.pdf>`._
+    `"Very Deep Convolutional Networks For Large-Scale Image Recognition" <https://arxiv.org/pdf/1409.1556.pdf>`_.
 
     Args:
         pretrained (bool): If True, returns a model pre-trained on ImageNet
@@ -126,7 +126,7 @@ def vgg11_bn(pretrained: bool = False, progress: bool = True, **kwargs: Any) ->
 
 def vgg13(pretrained: bool = False, progress: bool = True, **kwargs: Any) -> VGG:
     r"""VGG 13-layer model (configuration "B")
-    `"Very Deep Convolutional Networks For Large-Scale Image Recognition" <https://arxiv.org/pdf/1409.1556.pdf>`._
+    `"Very Deep Convolutional Networks For Large-Scale Image Recognition" <https://arxiv.org/pdf/1409.1556.pdf>`_.
 
     Args:
         pretrained (bool): If True, returns a model pre-trained on ImageNet
@@ -137,7 +137,7 @@ def vgg13(pretrained: bool = False, progress: bool = True, **kwargs: Any) -> VGG
 
 def vgg13_bn(pretrained: bool = False, progress: bool = True, **kwargs: Any) -> VGG:
     r"""VGG 13-layer model (configuration "B") with batch normalization
-    `"Very Deep Convolutional Networks For Large-Scale Image Recognition" <https://arxiv.org/pdf/1409.1556.pdf>`._
+    `"Very Deep Convolutional Networks For Large-Scale Image Recognition" <https://arxiv.org/pdf/1409.1556.pdf>`_.
 
     Args:
         pretrained (bool): If True, returns a model pre-trained on ImageNet
@@ -148,7 +148,7 @@ def vgg13_bn(pretrained: bool = False, progress: bool = True, **kwargs: Any) ->
 
 def vgg16(pretrained: bool = False, progress: bool = True, **kwargs: Any) -> VGG:
     r"""VGG 16-layer model (configuration "D")
-    `"Very Deep Convolutional Networks For Large-Scale Image Recognition" <https://arxiv.org/pdf/1409.1556.pdf>`._
+    `"Very Deep Convolutional Networks For Large-Scale Image Recognition" <https://arxiv.org/pdf/1409.1556.pdf>`_.
 
     Args:
         pretrained (bool): If True, returns a model pre-trained on ImageNet
@@ -159,7 +159,7 @@ def vgg16(pretrained: bool = False, progress: bool = True, **kwargs: Any) -> VGG
 
 def vgg16_bn(pretrained: bool = False, progress: bool = True, **kwargs: Any) -> VGG:
     r"""VGG 16-layer model (configuration "D") with batch normalization
-    `"Very Deep Convolutional Networks For Large-Scale Image Recognition" <https://arxiv.org/pdf/1409.1556.pdf>`._
+    `"Very Deep Convolutional Networks For Large-Scale Image Recognition" <https://arxiv.org/pdf/1409.1556.pdf>`_.
 
     Args:
         pretrained (bool): If True, returns a model pre-trained on ImageNet
@@ -170,7 +170,7 @@ def vgg16_bn(pretrained: bool = False, progress: bool = True, **kwargs: Any) ->
 
 def vgg19(pretrained: bool = False, progress: bool = True, **kwargs: Any) -> VGG:
     r"""VGG 19-layer model (configuration "E")
-    `"Very Deep Convolutional Networks For Large-Scale Image Recognition" <https://arxiv.org/pdf/1409.1556.pdf>`._
+    `"Very Deep Convolutional Networks For Large-Scale Image Recognition" <https://arxiv.org/pdf/1409.1556.pdf>`_.
 
     Args:
         pretrained (bool): If True, returns a model pre-trained on ImageNet
@@ -181,7 +181,7 @@ def vgg19(pretrained: bool = False, progress: bool = True, **kwargs: Any) -> VGG
 
 def vgg19_bn(pretrained: bool = False, progress: bool = True, **kwargs: Any) -> VGG:
     r"""VGG 19-layer model (configuration 'E') with batch normalization
-    `"Very Deep Convolutional Networks For Large-Scale Image Recognition" <https://arxiv.org/pdf/1409.1556.pdf>`._
+    `"Very Deep Convolutional Networks For Large-Scale Image Recognition" <https://arxiv.org/pdf/1409.1556.pdf>`_.
 
     Args:
         pretrained (bool): If True, returns a model pre-trained on ImageNet