U ʹj @sjddlZddlmZddlmZmZmZddlZddlm Z ddlm Z ddlm Z ddl mZdd lmZmZmZdd lmZdd lmZmZdd lmZmZmZmZmZmZd dlm Z m!Z!m"Z"dddgZ#GdddeZ$GdddeZ%GdddeZ&GdddeZ'GdddeZ(eddedddfddd d!d"eee(efe)e)ee'd#d$dZdS)%N)partial)AnyOptionalUnion)Tensor) functional)ImageClassification)register_modelWeights WeightsEnum)_IMAGENET_CATEGORIES)_ovewrite_named_paramhandle_legacy_interface) BasicConv2d GoogLeNetGoogLeNet_WeightsGoogLeNetOutputs Inception InceptionAux) _fuse_modules _replace_reluquantize_modelQuantizableGoogLeNetGoogLeNet_QuantizedWeights googlenetcsLeZdZeeddfdd ZeedddZd eeddd d Z Z S) QuantizableBasicConv2dNargskwargsreturncstj||t|_dSN)super__init__nnReLUreluselfr r! __class__h/var/www/html/bwave/python/venv/lib/python3.8/site-packages/torchvision/models/quantization/googlenet.pyr%szQuantizableBasicConv2d.__init__xr"cCs"||}||}||}|Sr#)convbnr(r*r0r-r-r.forwards   zQuantizableBasicConv2d.forwardis_qatr"cCst|dddg|dddS)Nr1r2r(T)Zinplace)r)r*r6r-r-r. fuse_model$sz!QuantizableBasicConv2d.fuse_model)N) __name__ __module__ __qualname__rr%rr4rboolr7 __classcell__r-r-r+r.rsrcs6eZdZeeddfdd ZeedddZZS)QuantizableInceptionNrcs&tj|dti|tj|_dSNZ conv_block)r$r%rr&Z quantizedZFloatFunctionalcatr)r+r-r.r%)szQuantizableInception.__init__r/cCs||}|j|dS)Nr)_forwardr?)r*r0outputsr-r-r.r4-s zQuantizableInception.forwardr8r9r:rr%rr4r<r-r-r+r.r=(sr=cs6eZdZeeddfdd ZeedddZZS)QuantizableInceptionAuxNrcs$tj|dti|t|_dSr>)r$r%rr&r'r(r)r+r-r.r%4sz QuantizableInceptionAux.__init__r/cCsJt|d}||}t|d}|||}||}||}|S)N)rDr) FZadaptive_avg_pool2dr1torchflattenr(Zfc1ZdropoutZfc2r3r-r-r.r48s     zQuantizableInceptionAux.forwardrBr-r-r+r.rC2srCcsLeZdZeeddfdd ZeedddZd ee ddd d Z Z S) rNrcs<tj|dtttgi|tjj|_ tjj |_ dS)Nblocks) r$r%rr=rCrFZaoZ quantizationZ QuantStubquantZ DeQuantStubdequantr)r+r-r.r%LszQuantizableGoogLeNet.__init__r/cCsp||}||}||\}}}||}|jo8|j}tjr^|sRt dt |||S| |||SdS)NzCScripted QuantizableGoogleNet always returns GoogleNetOutputs Tuple) Z_transform_inputrIr@rJZtraining aux_logitsrFZjitZ is_scriptingwarningswarnrZ eager_outputs)r*r0aux1aux2Z aux_definedr-r-r.r4Ss       zQuantizableGoogLeNet.forwardr5cCs(|D]}t|tkr||qdS)aFuse conv/bn/relu modules in googlenet model Fuse conv+bn+relu/ conv+relu/conv+bn modules to prepare for quantization. Model is modified in place. Note that this operation does not change numerics and the model after modification is in floating point N)modulestyperr7)r*r6mr-r-r.r7`s  zQuantizableGoogLeNet.fuse_model)N) r8r9r:rr%rrr4rr;r7r<r-r-r+r.rJs c@sHeZdZedeeddddeddejdd d d id d dd dZ e Z dS)rzKhttps://download.pytorch.org/models/quantized/googlenet_fbgemm-c81f6644.pth)Z crop_sizeie)rTfbgemmzdhttps://github.com/pytorch/vision/tree/main/references/classification#post-training-quantized-modelsz ImageNet-1Kg/tQ@g`"YV@)zacc@1zacc@5g+?g#~j<)@z These weights were produced by doing Post Training Quantization (eager mode) on top of the unquantized weights listed below. ) Z num_paramsZmin_size categoriesbackendZrecipeZ unquantizedZ_metricsZ_ops _file_sizeZ_docs)urlZ transformsmetaN) r8r9r:r rr rr IMAGENET1K_V1IMAGENET1K_FBGEMM_V1DEFAULTr-r-r-r.rms( Zquantized_googlenet)nameZ pretrainedcCs|ddrtjStjS)NquantizeF)getrr\rr[)r!r-r-r.s ra)weightsTF)rbprogressr_)rbrcr_r!r"cKs|rtnt|}|dd}|dk rd|kr:t|ddt|ddt|ddt|dt|jdd |jkrt|d |jd |d d }tf|}t ||rt |||dk r| |j |dd |sd|_ d|_d|_n td |S) aGoogLeNet (Inception v1) model architecture from `Going Deeper with Convolutions `__. .. note:: Note that ``quantize = True`` returns a quantized model with 8 bit weights. Quantized models only support inference and run on CPUs. GPU inference is not yet supported. Args: weights (:class:`~torchvision.models.quantization.GoogLeNet_QuantizedWeights` or :class:`~torchvision.models.GoogLeNet_Weights`, optional): The pretrained weights for the model. See :class:`~torchvision.models.quantization.GoogLeNet_QuantizedWeights` 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. quantize (bool, optional): If True, return a quantized version of the model. Default is False. **kwargs: parameters passed to the ``torchvision.models.quantization.QuantizableGoogLeNet`` base class. Please refer to the `source code `_ for more details about this class. .. autoclass:: torchvision.models.quantization.GoogLeNet_QuantizedWeights :members: .. autoclass:: torchvision.models.GoogLeNet_Weights :members: :noindex: rKFNZtransform_inputTZ init_weightsZ num_classesrVrWrU)rcZ check_hashz`auxiliary heads in the pretrained googlenet model are NOT pretrained, so make sure to train them)rrverifyr`rlenrZpoprrrZload_state_dictZget_state_dictrKrNrOrLrM)rbrcr_r!Zoriginal_aux_logitsrWmodelr-r-r.rs2,        )*rL functoolsrtypingrrrrFZtorch.nnr&rrrEZtransforms._presetsr Z_apir r r _metarZ_utilsrrrrrrrrrutilsrrr__all__rr=rCrrr;r-r-r-r.sJ        #