U (d@sddlmZddlmZmZddlZddlmZddlm Z ddl m Z ddl m Z mZdd lmZdd lmZmZd d d gZGdd d ejZGdd d e Zedejfddddeeeeeddd ZddlmZed ejjiZdS))partial)AnyOptionalN)ImageClassification)_log_api_usage_once) WeightsEnumWeights)_IMAGENET_CATEGORIES)handle_legacy_interface_ovewrite_named_paramAlexNetAlexNet_Weightsalexnetcs<eZdZd eeddfdd Zejejddd ZZ S) r?N) num_classesdropoutreturncs$tt|ttjddddddtjddtjddd tjdd d dd tjddtjddd tjd d ddd tjddtjd dddd tjddtjddddd tjddtjddd  |_t d|_ ttj |dt ddtjddtj |dt ddtjddt d||_ dS)N@ r) kernel_sizestridepaddingT)Zinplace)rr)rrir)r )pi$i)super__init__rnnZ SequentialZConv2dZReLUZ MaxPool2dfeaturesZAdaptiveAvgPool2davgpoolZDropoutZLinear classifier)selfrr __class__>/tmp/pip-unpacked-wheel-vx7f76es/torchvision/models/alexnet.pyr#s6                 zAlexNet.__init__)xrcCs.||}||}t|d}||}|S)Nr)r%r&torchflattenr')r(r-r+r+r,forward/s     zAlexNet.forward)rr) __name__ __module__ __qualname__intfloatr#r.ZTensorr0 __classcell__r+r+r)r,rsc @s>eZdZedeeddddedddd d id d d ZeZdS)rzprogress)r>r?kwargsrcKsPt|}|dk r(t|dt|jdtf|}|dk rL||j|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: Nrr9)r?)rverifyr lenr;rZload_state_dictZget_state_dict)r>r?r@modelr+r+r,rNs  ) _ModelURLs) functoolsrtypingrrr.Ztorch.nnr$Ztransforms._presetsrutilsrZ_apir r Z_metar _utilsr r __all__Modulerrr<boolrrDr:Z model_urlsr+r+r+r,s&      &")