o V h2 @s~ddlZddlmZddlmZddlmZmZmZm Z m Z ddl Z ddl m Z ddlm mZddl mZddlmZddlmZd d lmZmZmZd d lmZd d lmZmZgd ZedgdZ ee ee ede _!e Z"Gddde j#Z$Gddde j#Z%Gddde j#Z&Gddde j#Z'GdddeZ(eede(j)fddddde e(de*d ed!e$fd"d#Z+dS)$N) namedtuple)partial)AnyCallableListOptionalTuple)Tensor)ImageClassification)_log_api_usage_once)register_modelWeights WeightsEnum)_IMAGENET_CATEGORIES)_ovewrite_named_paramhandle_legacy_interface) GoogLeNetGoogLeNetOutputs_GoogLeNetOutputsGoogLeNet_Weights googlenetr)logits aux_logits2 aux_logits1cseZdZddgZ       dd ededed eed eeed e j fd e de ddffdd Z de de fddZde dee ee ee ffddZejjde de dee defddZde defddZZS)r aux_logitstransform_inputTFN皙?ffffff? num_classes init_weightsblocks.dropout dropout_auxreturnc stt||durtttg}|durtdtd}t |dkr-t dt ||d}|d} |d} ||_ ||_ |ddd ddd |_ tjdddd |_|dddd |_|dd ddd|_tjdddd |_| d dddddd|_| dddd ddd|_tjdddd |_| dd ddddd|_| ddddddd|_| ddddddd|_| ddddddd|_| ddddddd|_tjdddd |_| d dddddd|_| d d!d d!ddd|_|r| d||d"|_| d||d"|_ nd|_d|_ t!d#|_"tj#|d$|_$t%d%||_&|rM|'D]9} t(| tj)s%t(| tj%r4t*jj+j,| j-d&d'd(dd)qt(| tj.rKtj+/| j-dtj+/| j0dqdSdS)*NzThe default weight initialization of GoogleNet will be changed in future releases of torchvision. If you wish to keep the old behavior (which leads to long initialization times due to scipy/scipy#11299), please set init_weights=True.Tz%blocks length should be 3 instead of rr r @) kernel_sizestridepadding)r+ ceil_moder*r*r,` i0ipi ii@i@i)r$)r r pgg{Gz?)meanstdab)1super__init__r BasicConv2d Inception InceptionAuxwarningswarn FutureWarninglen ValueErrorrrconv1nn MaxPool2dmaxpool1conv2conv3maxpool2 inception3a inception3bmaxpool3 inception4a inception4b inception4c inception4d inception4emaxpool4 inception5a inception5baux1aux2AdaptiveAvgPool2davgpoolDropoutr$Linearfcmodules isinstanceConv2dtorchinit trunc_normal_weight BatchNorm2d constant_bias) selfr!rrr"r#r$r% conv_blockinception_blockinception_aux_blockm __class__P/var/www/vscode/kcb/lib/python3.10/site-packages/torchvision/models/googlenet.pyrF sf     zGoogLeNet.__init__xcCs||jr F$7 rcs|eZdZ ddededededededed eed ejfd dffd d Zde d e e fddZ de d e fddZ Z S)rHN in_channelsch1x1ch3x3redch3x3ch5x5redch5x5 pool_projrs.r&c st|dur t}|||dd|_t|||dd|||ddd|_t|||dd|||ddd|_ttjddddd|||dd|_ dS)Nr r.r'r0T)r*r+r,r-) rErFrGbranch1rP Sequentialbranch2branch3rQbranch4) rrrrrrrrrrsrwryrzrFs    zInception.__init__r{cCs8||}||}||}||}||||g}|Sr)rrrr)rrr{rrrroutputsryryrzrs     zInception._forwardcCs||}t|dSr)rrkr})rrr{rryryrzrs  zInception.forwardr)rrrrrrrPrrFr rrrrryryrwrzrHs.     rHc sXeZdZ  ddededeedejfdeddf fd d Z d e de fd d Z Z S)rINr rr!rs.r$r&csTt|dur t}||ddd|_tdd|_td||_tj|d|_ dS)Nr2r r.ir?r=) rErFrGconvrPrffc1fc2rer$)rrrr!rsr$rwryrzrFs zInceptionAux.__init__r{cCsNt|d}||}t|d}tj||dd}||}||}|S)N)rr Tinplace) Fadaptive_avg_pool2drrkrrelurr$rrrr{ryryrzrs     zInceptionAux.forward)Nr ) rrrrrrrPrrrFr rrryryrwrzrIsrIcs@eZdZdedededdffdd Zdedefd d ZZS) rGr out_channelskwargsr&Nc s8ttj||fddi||_tj|dd|_dS)NrqFgMbP?)eps)rErFrPrjrrobn)rrrrrrwryrzrF s zBasicConv2d.__init__r{cCs"||}||}tj|ddS)NTr)rrrrrryryrzrs  zBasicConv2d.forward) rrrrrrFr rrryryrwrzrG srGc @sBeZdZedeeddddedddd d id d d ddZeZdS)rz:https://download.pytorch.org/models/googlenet-1378be20.pthr:) crop_sizeie)rzOhttps://github.com/pytorch/vision/tree/main/references/classification#googlenetz ImageNet-1KgoqQ@gRaV@)zacc@1zacc@5g+?g!rhH@z1These weights are ported from the original paper.) num_paramsmin_size categoriesrecipe_metrics_ops _file_size_docs)url transformsmetaN) rrrrrr r IMAGENET1K_V1DEFAULTryryryrzrs& r pretrained)weightsT)rprogressrrrr&cKst|}|dd}|dur0d|vrt|ddt|ddt|ddt|dt|jdtd i|}|durW||j|dd |sRd|_ d|_ d|_ |St d |S) aGoogLeNet (Inception v1) model architecture from `Going Deeper with Convolutions `_. Args: weights (:class:`~torchvision.models.GoogLeNet_Weights`, optional): The pretrained weights for the model. See :class:`~torchvision.models.GoogLeNet_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.GoogLeNet`` base class. Please refer to the `source code `_ for more details about this class. .. autoclass:: torchvision.models.GoogLeNet_Weights :members: rFNrTr"r!r)r check_hashz`auxiliary heads in the pretrained googlenet model are NOT pretrained, so make sure to train themry)rverifygetrrMrrload_state_dictget_state_dictrrarbrJrK)rrroriginal_aux_logitsmodelryryrzr-s(     r),rJ collectionsr functoolsrtypingrrrrrrktorch.nnrPtorch.nn.functional functionalrr transforms._presetsr utilsr _apirrr_metar_utilsrr__all__r__annotations__rrrrHrIrGrrrrryryryrzs4       /# .