diff --git a/docs/source/models/alexnet.rst b/docs/source/models/alexnet.rst index 50d541632ef..080c241983b 100644 --- a/docs/source/models/alexnet.rst +++ b/docs/source/models/alexnet.rst @@ -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 -`__. -paper. +`__ +paper. The implemented architecture is slightly different from the original one, +and is based on `One weird trick for parallelizing convolutional neural networks +`__. Model builders diff --git a/torchvision/models/alexnet.py b/torchvision/models/alexnet.py index 5be705ca532..97877c52060 100644 --- a/torchvision/models/alexnet.py +++ b/torchvision/models/alexnet.py @@ -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 - `__ paper. + """AlexNet model architecture from `One weird trick for parallelizing convolutional neural networks `__. The required minimum input size of the model is 63x63. + .. note:: + AlexNet was originally introduced in the `ImageNet Classification with + Deep Convolutional Neural Networks + `__ + 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