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Fixing AlexNet references (#5962)
* Fixing AlexNet references * Fix doc rendering
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docs/source/models/alexnet.rst

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.. currentmodule:: torchvision.models
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The AlexNet model is based on the
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The AlexNet model was originally introduced in the
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`ImageNet Classification with Deep Convolutional Neural Networks
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<https://papers.nips.cc/paper/2012/hash/c399862d3b9d6b76c8436e924a68c45b-Abstract.html>`__.
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paper.
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<https://papers.nips.cc/paper/2012/hash/c399862d3b9d6b76c8436e924a68c45b-Abstract.html>`__
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paper. The implemented architecture is slightly different from the original one,
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and is based on `One weird trick for parallelizing convolutional neural networks
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<https://arxiv.org/abs/1404.5997>`__.
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Model builders

torchvision/models/alexnet.py

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@@ -72,11 +72,17 @@ class AlexNet_Weights(WeightsEnum):
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@handle_legacy_interface(weights=("pretrained", AlexNet_Weights.IMAGENET1K_V1))
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def alexnet(*, weights: Optional[AlexNet_Weights] = None, progress: bool = True, **kwargs: Any) -> AlexNet:
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"""AlexNet model architecture from the `ImageNet Classification with Deep Convolutional Neural Networks
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<https://papers.nips.cc/paper/2012/hash/c399862d3b9d6b76c8436e924a68c45b-Abstract.html>`__ paper.
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"""AlexNet model architecture from `One weird trick for parallelizing convolutional neural networks <https://arxiv.org/abs/1404.5997>`__.
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The required minimum input size of the model is 63x63.
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.. note::
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AlexNet was originally introduced in the `ImageNet Classification with
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Deep Convolutional Neural Networks
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<https://papers.nips.cc/paper/2012/hash/c399862d3b9d6b76c8436e924a68c45b-Abstract.html>`__
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paper. Our implementation is based instead on the "One weird trick"
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paper above.
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Args:
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weights (:class:`~torchvision.models.AlexNet_Weights`, optional): The
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pretrained weights to use. See

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