ڧg FddlmZddlmZmZddlZddlmZddlm Z ddl m Z ddl m Z mZmZdd lmZdd lmZmZgd ZGd d ejZGddeZe edejfddddeedededefdZdS))partial)AnyOptionalN)ImageClassification)_log_api_usage_once)register_modelWeights WeightsEnum)_IMAGENET_CATEGORIES)_ovewrite_named_paramhandle_legacy_interface)AlexNetAlexNet_WeightsalexnetcReZdZd dededdffd Zdejdejfd ZxZ S) r? num_classesdropoutreturnNc>tt|tjtjdddddtjdtjdd tjdd d d tjdtjdd tjd d dd tjdtjd ddd tjdtjdddd tjdtjdd  |_tj d|_ tjtj |tj ddtjdtj |tj ddtjdtj d||_ dS)N@ r) kernel_sizestridepaddingT)inplace)rr)rr ir )r%)pi$i)super__init__rnn SequentialConv2dReLU MaxPool2dfeaturesAdaptiveAvgPool2davgpoolDropoutLinear classifier)selfrr __class__s V/var/www/html/ai-engine/env/lib/python3.11/site-packages/torchvision/models/alexnet.pyr(zAlexNet.__init__s D!!! IaAq A A A GD ! ! ! LQq 1 1 1 Ib#1a 8 8 8 GD ! ! ! LQq 1 1 1 Ic3Aq 9 9 9 GD ! ! ! Ic3Aq 9 9 9 GD ! ! ! Ic3Aq 9 9 9 GD ! ! ! LQq 1 1 1   +F33 - J ! ! ! Ik4 ( ( GD ! ! ! J ! ! ! IdD ! ! GD ! ! ! IdK ( (  xc||}||}tj|d}||}|S)Nr )r.r0torchflattenr3)r4r8s r6forwardzAlexNet.forward/sI MM!   LLOO M!Q   OOA  r7)rr) __name__ __module__ __qualname__intfloatr(r:Tensorr< __classcell__)r5s@r6rrs}  C        :%,r7rc `eZdZedeedddedddd d id d d dZeZdS)rzr?r rrr IMAGENET1K_V1DEFAULTr7r6rr7s|G J7.#>>>" .m##   !  M*GGGr7r pretrained)weightsT)rWprogressrWrXkwargsrc t|}|)t|dt|jdt di|}|*|||d|S)aAlexNet model architecture from `One weird trick for parallelizing convolutional neural networks `__. .. 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 :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 `_ for more details about this class. .. autoclass:: torchvision.models.AlexNet_Weights :members: NrrJT)rX check_hashrU)rverifyrlenrRrload_state_dictget_state_dict)rWrXrYmodels r6rrPs:$$W--GfmSl9S5T5TUUU   f  E g44hSW4XXYYY Lr7) functoolsrtypingrrr:torch.nnr)transforms._presetsrutilsr_apir r r _metar _utilsrr__all__ModulerrrSboolrrUr7r6rls 555555''''''6666666666''''''BBBBBBBB 4 3 3#####bi###Lk2,0M!NOOO484%%%1%D%[^%cj%%%PO%%%r7