Add inception docs

docs/source/models.rst

@@ -457,7 +457,7 @@ ConvNeXt
     convnext_large
 
 SwinTransformer
---------
+---------------
 
 .. autosummary::
     :toctree: generated/

docs/source/models/inception.rst

@@ -0,0 +1,23 @@
+Inception V3
+============
+
+.. currentmodule:: torchvision.models
+
+The EfficientNet model is based on the `Rethinking the Inception Architecture for Computer Vision <https://arxiv.org/abs/1512.00567>`__
+paper.
+
+
+Model builders
+--------------
+
+The following model builders can be used to instanciate an InceptionV3 model, with or
+without pre-trained weights. All the model builders internally rely on the
+``torchvision.models.efficientnet.Inception3`` base class. Please refer to the `source
+code <https://github.com/pytorch/vision/blob/main/torchvision/models/inception.py>`_ for
+more details about this class.
+
+.. autosummary::
+    :toctree: generated/
+    :template: function.rst
+
+    inception_v3

docs/source/models_new.rst

@@ -42,6 +42,7 @@ weights:
    models/efficientnet
    models/efficientnetv2
    models/googlenet
+   models/inception
    models/mobilenetv2
    models/mobilenetv3
    models/regnet

torchvision/models/googlenet.py

@@ -307,7 +307,7 @@ def googlenet(*, weights: Optional[GoogLeNet_Weights] = None, progress: bool = T
             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.squeezenet.GoogLeNet``
+        **kwargs: parameters passed to the ``torchvision.models.GoogLeNet``
             base class. Please refer to the `source code
             <https://github.com/pytorch/vision/blob/main/torchvision/models/googlenet.py>`_
             for more details about this class.

torchvision/models/inception.py

@@ -427,21 +427,30 @@ class Inception_V3_Weights(WeightsEnum):
 
 @handle_legacy_interface(weights=("pretrained", Inception_V3_Weights.IMAGENET1K_V1))
 def inception_v3(*, weights: Optional[Inception_V3_Weights] = None, progress: bool = True, **kwargs: Any) -> Inception3:
-    r"""Inception v3 model architecture from
-    `"Rethinking the Inception Architecture for Computer Vision" <http://arxiv.org/abs/1512.00567>`_.
+    """
+    Inception v3 model architecture from
+    `Rethinking the Inception Architecture for Computer Vision <http://arxiv.org/abs/1512.00567>`_.
     The required minimum input size of the model is 75x75.
 
     .. note::
         **Important**: In contrast to the other models the inception_v3 expects tensors with a size of
         N x 3 x 299 x 299, so ensure your images are sized accordingly.
 
     Args:
-        weights (Inception_V3_Weights, optional): The pretrained weights for the model
-        progress (bool): If True, displays a progress bar of the download to stderr
-        aux_logits (bool): If True, add an auxiliary branch that can improve training.
-            Default: *True*
-        transform_input (bool): If True, preprocesses the input according to the method with which it
-            was trained on ImageNet. Default: True if ``weights=Inception_V3_Weights.IMAGENET1K_V1``, else False.
+        weights (:class:`~torchvision.models.Inception_V3_Weights`, optional): The
+            pretrained weights for the model. See
+            :class:`~torchvision.models.Inception_V3_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.Inception3``
+            base class. Please refer to the `source code
+            <https://github.com/pytorch/vision/blob/main/torchvision/models/inception.py>`_
+            for more details about this class.
+
+    .. autoclass:: torchvision.models.Inception_V3_Weights
+        :members:
     """
     weights = Inception_V3_Weights.verify(weights)