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8 changes: 5 additions & 3 deletions docs/source/models/alexnet.rst
Original file line number Diff line number Diff line change
Expand Up @@ -3,10 +3,12 @@ AlexNet

.. currentmodule:: torchvision.models

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


Model builders
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10 changes: 8 additions & 2 deletions torchvision/models/alexnet.py
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Expand Up @@ -72,11 +72,17 @@ 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:
"""AlexNet model architecture from the `ImageNet Classification with Deep Convolutional Neural Networks
<https://papers.nips.cc/paper/2012/hash/c399862d3b9d6b76c8436e924a68c45b-Abstract.html>`__ paper.
"""AlexNet model architecture from `One weird trick for parallelizing convolutional neural networks <https://arxiv.org/abs/1404.5997>`__.

The required minimum input size of the model is 63x63.

.. note::
AlexNet was originally introduced in the `ImageNet Classification with
Deep Convolutional Neural Networks
<https://papers.nips.cc/paper/2012/hash/c399862d3b9d6b76c8436e924a68c45b-Abstract.html>`__
paper. Our implementation is based instead on the "One weird trick"
paper above.

Args:
weights (:class:`~torchvision.models.AlexNet_Weights`, optional): The
pretrained weights to use. See
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