[fbsync] Fix alexnet docs (#5905)

Summary: Co-authored-by: Vasilis Vryniotis <[email protected]>

Reviewed By: jdsgomes, NicolasHug

Differential Revision: D36095712

fbshipit-source-id: f4e5d432da3b2ca53200224d6c05d7983b71c081

Author: YosuaMichael

docs/source/models/alexnet.rst

@@ -3,8 +3,9 @@ AlexNet
 
 .. currentmodule:: torchvision.models
 
-The AlexNet model is based on the `ImageNet Classification with Deep Convolutional Neural Networks
- <https://papers.nips.cc/paper/2012/hash/c399862d3b9d6b76c8436e924a68c45b-Abstract.html>`__
+The AlexNet model is based on the
+`ImageNet Classification with Deep Convolutional Neural Networks
+<https://papers.nips.cc/paper/2012/hash/c399862d3b9d6b76c8436e924a68c45b-Abstract.html>`__.
 paper.
 
 

torchvision/models/alexnet.py

@@ -72,26 +72,26 @@ class AlexNet_Weights(WeightsEnum):
 
 @handle_legacy_interface(weights=("pretrained", AlexNet_Weights.IMAGENET1K_V1))
 def alexnet(*, weights: Optional[AlexNet_Weights] = None, progress: bool = True, **kwargs: Any) -> AlexNet:
-    r"""AlexNet model architecture from the
-       `ImageNet Classification with Deep Convolutional Neural Networks
-    <https://papers.nips.cc/paper/2012/hash/c399862d3b9d6b76c8436e924a68c45b-Abstract.html>`_ paper.
-       The required minimum input size of the model is 63x63.
-
-       Args:
-           weights (:class:`~torchvision.models.AlexNet_Weights`, optional): The
-               pretrained weights to use. See
-               :class:`~torchvision.models.AlexNet_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.squeezenet.AlexNet``
-               base class. Please refer to the `source code
-               <https://github.com/pytorch/vision/blob/main/torchvision/models/alexnet.py>`_
-               for more details about this class.
-
-       .. autoclass:: torchvision.models.AlexNet_Weights
-           :members:
+    """AlexNet model architecture from the `ImageNet Classification with Deep Convolutional Neural Networks
+    <https://papers.nips.cc/paper/2012/hash/c399862d3b9d6b76c8436e924a68c45b-Abstract.html>`__ paper.
+
+    The required minimum input size of the model is 63x63.
+
+    Args:
+        weights (:class:`~torchvision.models.AlexNet_Weights`, optional): The
+            pretrained weights to use. See
+            :class:`~torchvision.models.AlexNet_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.squeezenet.AlexNet``
+            base class. Please refer to the `source code
+            <https://github.com/pytorch/vision/blob/main/torchvision/models/alexnet.py>`_
+            for more details about this class.
+
+    .. autoclass:: torchvision.models.AlexNet_Weights
+        :members:
     """
 
     weights = AlexNet_Weights.verify(weights)