revamp docs for Wide ResNet

docs/source/models/resnext.rst

@@ -10,7 +10,7 @@ paper.
 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
 ``torchvision.models.resnet.ResNet`` base class. Please refer to the `source
 code

docs/source/models/wide_resnet.rst

@@ -0,0 +1,25 @@
+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

docs/source/models_new.rst

@@ -50,6 +50,7 @@ weights:
    models/swin_transformer
    models/vgg
    models/vision_transformer
+   models/wide_resnet
 
 
 Table of all available classification weights

torchvision/models/resnet.py

@@ -738,17 +738,28 @@ def resnext101_32x8d(
 def wide_resnet50_2(
     *, weights: Optional[Wide_ResNet50_2_Weights] = None, progress: bool = True, **kwargs: Any
 ) -> ResNet:
-    r"""Wide ResNet-50-2 model from
-    `"Wide Residual Networks" <https://arxiv.org/pdf/1605.07146.pdf>`_.
+    """Wide ResNet-50-2 model from
+    `Wide Residual Networks <https://arxiv.org/abs/1605.07146>`_.
 
     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
     convolutions is the same, e.g. last block in ResNet-50 has 2048-512-2048
     channels, and in Wide ResNet-50-2 has 2048-1024-2048.
 
     Args:
-        weights (Wide_ResNet50_2_Weights, optional): The pretrained weights for the model
-        progress (bool): If True, displays a progress bar of the download to stderr
+        weights (:class:`~torchvision.models.Wide_ResNet50_2_Weights`, optional): The
+            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)
 
@@ -760,17 +771,28 @@ def wide_resnet50_2(
 def wide_resnet101_2(
     *, weights: Optional[Wide_ResNet101_2_Weights] = None, progress: bool = True, **kwargs: Any
 ) -> ResNet:
-    r"""Wide ResNet-101-2 model from
-    `"Wide Residual Networks" <https://arxiv.org/pdf/1605.07146.pdf>`_.
+    """Wide ResNet-101-2 model from
+    `Wide Residual Networks <https://arxiv.org/abs/1605.07146>`_.
 
     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
     convolutions is the same, e.g. last block in ResNet-50 has 2048-512-2048
     channels, and in Wide ResNet-50-2 has 2048-1024-2048.
 
     Args:
-        weights (Wide_ResNet101_2_Weights, optional): The pretrained weights for the model
-        progress (bool): If True, displays a progress bar of the download to stderr
+        weights (:class:`~torchvision.models.Wide_ResNet101_2_Weights`, optional): The
+            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)