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Fix paper links of VGG models #3684

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Apr 19, 2021
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Fix paper links of VGG models #3684

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16 changes: 8 additions & 8 deletions torchvision/models/vgg.py
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Original file line number Diff line number Diff line change
Expand Up @@ -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
Expand All @@ -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
Expand All @@ -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
Expand All @@ -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
Expand All @@ -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
Expand All @@ -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
Expand All @@ -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
Expand All @@ -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
Expand Down