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Unverified Commit f861003c authored by Abhijit Deo's avatar Abhijit Deo Committed by GitHub
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revamp docs for Wide ResNet (#5907)



* init

* minor change

* typo
Co-authored-by: default avatarNicolas Hug <contact@nicolas-hug.com>
parent 29211740
...@@ -10,7 +10,7 @@ paper. ...@@ -10,7 +10,7 @@ paper.
Model builders Model builders
-------------- --------------
The following model builders can be used to instantiate an ResNext model, with or The following model builders can be used to instantiate a ResNext model, with or
without pre-trained weights. All the model builders internally rely on the without pre-trained weights. All the model builders internally rely on the
``torchvision.models.resnet.ResNet`` base class. Please refer to the `source ``torchvision.models.resnet.ResNet`` base class. Please refer to the `source
code code
......
Wide ResNet
===========
.. currentmodule:: torchvision.models
The Wide ResNet model is based on the `Wide Residual Networks <https://arxiv.org/abs/1605.07146>`__
paper.
Model builders
--------------
The following model builders can be used to instantiate a Wide ResNet model, with or
without pre-trained weights. All the model builders internally rely on the
``torchvision.models.resnet.ResNet`` base class. Please refer to the `source
code
<https://github.com/pytorch/vision/blob/main/torchvision/models/resnet.py>`_ for
more details about this class.
.. autosummary::
:toctree: generated/
:template: function.rst
wide_resnet50_2
wide_resnet101_2
...@@ -50,6 +50,7 @@ weights: ...@@ -50,6 +50,7 @@ weights:
models/swin_transformer models/swin_transformer
models/vgg models/vgg
models/vision_transformer models/vision_transformer
models/wide_resnet
Table of all available classification weights Table of all available classification weights
......
...@@ -738,8 +738,8 @@ def resnext101_32x8d( ...@@ -738,8 +738,8 @@ def resnext101_32x8d(
def wide_resnet50_2( def wide_resnet50_2(
*, weights: Optional[Wide_ResNet50_2_Weights] = None, progress: bool = True, **kwargs: Any *, weights: Optional[Wide_ResNet50_2_Weights] = None, progress: bool = True, **kwargs: Any
) -> ResNet: ) -> ResNet:
r"""Wide ResNet-50-2 model from """Wide ResNet-50-2 model from
`"Wide Residual Networks" <https://arxiv.org/pdf/1605.07146.pdf>`_. `Wide Residual Networks <https://arxiv.org/abs/1605.07146>`_.
The model is the same as ResNet except for the bottleneck number of channels The model is the same as ResNet except for the bottleneck number of channels
which is twice larger in every block. The number of channels in outer 1x1 which is twice larger in every block. The number of channels in outer 1x1
...@@ -747,8 +747,19 @@ def wide_resnet50_2( ...@@ -747,8 +747,19 @@ def wide_resnet50_2(
channels, and in Wide ResNet-50-2 has 2048-1024-2048. channels, and in Wide ResNet-50-2 has 2048-1024-2048.
Args: Args:
weights (Wide_ResNet50_2_Weights, optional): The pretrained weights for the model weights (:class:`~torchvision.models.Wide_ResNet50_2_Weights`, optional): The
progress (bool): If True, displays a progress bar of the download to stderr pretrained weights to use. See
:class:`~torchvision.models.Wide_ResNet50_2_Weights` below for
more details, and possible values. By default, no pre-trained
weights are used.
progress (bool, optional): If True, displays a progress bar of the
download to stderr. Default is True.
**kwargs: parameters passed to the ``torchvision.models.resnet.ResNet``
base class. Please refer to the `source code
<https://github.com/pytorch/vision/blob/main/torchvision/models/resnet.py>`_
for more details about this class.
.. autoclass:: torchvision.models.Wide_ResNet50_2_Weights
:members:
""" """
weights = Wide_ResNet50_2_Weights.verify(weights) weights = Wide_ResNet50_2_Weights.verify(weights)
...@@ -760,8 +771,8 @@ def wide_resnet50_2( ...@@ -760,8 +771,8 @@ def wide_resnet50_2(
def wide_resnet101_2( def wide_resnet101_2(
*, weights: Optional[Wide_ResNet101_2_Weights] = None, progress: bool = True, **kwargs: Any *, weights: Optional[Wide_ResNet101_2_Weights] = None, progress: bool = True, **kwargs: Any
) -> ResNet: ) -> ResNet:
r"""Wide ResNet-101-2 model from """Wide ResNet-101-2 model from
`"Wide Residual Networks" <https://arxiv.org/pdf/1605.07146.pdf>`_. `Wide Residual Networks <https://arxiv.org/abs/1605.07146>`_.
The model is the same as ResNet except for the bottleneck number of channels The model is the same as ResNet except for the bottleneck number of channels
which is twice larger in every block. The number of channels in outer 1x1 which is twice larger in every block. The number of channels in outer 1x1
...@@ -769,8 +780,19 @@ def wide_resnet101_2( ...@@ -769,8 +780,19 @@ def wide_resnet101_2(
channels, and in Wide ResNet-50-2 has 2048-1024-2048. channels, and in Wide ResNet-50-2 has 2048-1024-2048.
Args: Args:
weights (Wide_ResNet101_2_Weights, optional): The pretrained weights for the model weights (:class:`~torchvision.models.Wide_ResNet101_2_Weights`, optional): The
progress (bool): If True, displays a progress bar of the download to stderr pretrained weights to use. See
:class:`~torchvision.models.Wide_ResNet101_2_Weights` below for
more details, and possible values. By default, no pre-trained
weights are used.
progress (bool, optional): If True, displays a progress bar of the
download to stderr. Default is True.
**kwargs: parameters passed to the ``torchvision.models.resnet.ResNet``
base class. Please refer to the `source code
<https://github.com/pytorch/vision/blob/main/torchvision/models/resnet.py>`_
for more details about this class.
.. autoclass:: torchvision.models.Wide_ResNet101_2_Weights
:members:
""" """
weights = Wide_ResNet101_2_Weights.verify(weights) weights = Wide_ResNet101_2_Weights.verify(weights)
......
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