"git@developer.sourcefind.cn:OpenDAS/torch-harmonics.git" did not exist on "39298ffe1d5aea9f8a8f5d2d4d9ec487abb05b83"
Unverified Commit cd1728d0 authored by Nicolas Hug's avatar Nicolas Hug Committed by GitHub
Browse files

Fix paper links of VGG models (#3684)

parent 79ee22da
......@@ -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
......
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