Add revamped docs for ConvNext (#5869)

* add convnext.rst

* refactor code

* add convnext
Co-authored-by: Nicolas Hug <contact@nicolas-hug.com>

docs/source/models/convnext.rst

+ConvNeXt
+======
+
+.. currentmodule:: torchvision.models
+
+The ConvNeXt model is based on the `A ConvNet for the 2020s
+<https://arxiv.org/abs/2201.03545>`_ paper.
+
+
+Model builders
+--------------
+
+The following model builders can be used to instantiate a ConvNeXt model, with or
+without pre-trained weights. All the model builders internally rely on the
+``torchvision.models.convnext.ConvNeXt`` base class. Please refer to the `source code
+<https://github.com/pytorch/vision/blob/main/torchvision/models/convnext.py>`_ for
+more details about this class.
+
+.. autosummary::
+   :toctree: generated/
+   :template: function.rst
+
+   convnext_tiny
+   convnext_small
+   convnext_base
+   convnext_large

docs/source/models_new.rst

@@ -36,6 +36,7 @@ weights:
 .. toctree::
    :maxdepth: 1
 
+   models/convnext
    models/efficientnet
    models/efficientnetv2
    models/regnet

torchvision/models/convnext.py

@@ -276,11 +276,21 @@ class ConvNeXt_Large_Weights(WeightsEnum):
 
 @handle_legacy_interface(weights=("pretrained", ConvNeXt_Tiny_Weights.IMAGENET1K_V1))
 def convnext_tiny(*, weights: Optional[ConvNeXt_Tiny_Weights] = None, progress: bool = True, **kwargs: Any) -> ConvNeXt:
-    r"""ConvNeXt Tiny model architecture from the
-    `"A ConvNet for the 2020s" <https://arxiv.org/abs/2201.03545>`_ paper.
+    """ConvNeXt Tiny model architecture from the
+    `A ConvNet for the 2020s <https://arxiv.org/abs/2201.03545>`_ paper.
+
     Args:
-        weights (ConvNeXt_Tiny_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.convnext.ConvNeXt_Tiny_Weights`, optional): The pretrained
+            weights to use. See :class:`~torchvision.models.convnext.ConvNeXt_Tiny_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.convnext.ConvNext``
+            base class. Please refer to the `source code
+            <https://github.com/pytorch/vision/blob/main/torchvision/models/convnext.py>`_
+            for more details about this class.
+
+    .. autoclass:: torchvision.models.convnext.ConvNeXt_Tiny_Weights
+        :members:
     """
     weights = ConvNeXt_Tiny_Weights.verify(weights)
 
@@ -298,11 +308,21 @@ def convnext_tiny(*, weights: Optional[ConvNeXt_Tiny_Weights] = None, progress:
 def convnext_small(
     *, weights: Optional[ConvNeXt_Small_Weights] = None, progress: bool = True, **kwargs: Any
 ) -> ConvNeXt:
-    r"""ConvNeXt Small model architecture from the
-    `"A ConvNet for the 2020s" <https://arxiv.org/abs/2201.03545>`_ paper.
+    """ConvNeXt Small model architecture from the
+    `A ConvNet for the 2020s <https://arxiv.org/abs/2201.03545>`_ paper.
+
     Args:
-        weights (ConvNeXt_Small_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.convnext.ConvNeXt_Small_Weights`, optional): The pretrained
+            weights to use. See :class:`~torchvision.models.convnext.ConvNeXt_Small_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.convnext.ConvNext``
+            base class. Please refer to the `source code
+            <https://github.com/pytorch/vision/blob/main/torchvision/models/convnext.py>`_
+            for more details about this class.
+
+    .. autoclass:: torchvision.models.convnext.ConvNeXt_Small_Weights
+        :members:
     """
     weights = ConvNeXt_Small_Weights.verify(weights)
 
@@ -318,11 +338,21 @@ def convnext_small(
 
 @handle_legacy_interface(weights=("pretrained", ConvNeXt_Base_Weights.IMAGENET1K_V1))
 def convnext_base(*, weights: Optional[ConvNeXt_Base_Weights] = None, progress: bool = True, **kwargs: Any) -> ConvNeXt:
-    r"""ConvNeXt Base model architecture from the
-    `"A ConvNet for the 2020s" <https://arxiv.org/abs/2201.03545>`_ paper.
+    """ConvNeXt Base model architecture from the
+    `A ConvNet for the 2020s <https://arxiv.org/abs/2201.03545>`_ paper.
+
     Args:
-        weights (ConvNeXt_Base_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.convnext.ConvNeXt_Base_Weights`, optional): The pretrained
+            weights to use. See :class:`~torchvision.models.convnext.ConvNeXt_Base_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.convnext.ConvNext``
+            base class. Please refer to the `source code
+            <https://github.com/pytorch/vision/blob/main/torchvision/models/convnext.py>`_
+            for more details about this class.
+
+    .. autoclass:: torchvision.models.convnext.ConvNeXt_Base_Weights
+        :members:
     """
     weights = ConvNeXt_Base_Weights.verify(weights)
 
@@ -340,11 +370,21 @@ def convnext_base(*, weights: Optional[ConvNeXt_Base_Weights] = None, progress:
 def convnext_large(
     *, weights: Optional[ConvNeXt_Large_Weights] = None, progress: bool = True, **kwargs: Any
 ) -> ConvNeXt:
-    r"""ConvNeXt Large model architecture from the
-    `"A ConvNet for the 2020s" <https://arxiv.org/abs/2201.03545>`_ paper.
+    """ConvNeXt Large model architecture from the
+    `A ConvNet for the 2020s <https://arxiv.org/abs/2201.03545>`_ paper.
+
     Args:
-        weights (ConvNeXt_Large_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.convnext.ConvNeXt_Large_Weights`, optional): The pretrained
+            weights to use. See :class:`~torchvision.models.convnext.ConvNeXt_Large_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.convnext.ConvNext``
+            base class. Please refer to the `source code
+            <https://github.com/pytorch/vision/blob/main/torchvision/models/convnext.py>`_
+            for more details about this class.
+
+    .. autoclass:: torchvision.models.convnext.ConvNeXt_Large_Weights
+        :members:
     """
     weights = ConvNeXt_Large_Weights.verify(weights)