a PSic @sddlZddlmZddlmZmZmZddlZddlm Z ddlm Z ddlm Z ddl mZdd lmZmZdd lmZdd lmZmZdd lmZmZmZmZmZmZd dlmZm Z m!Z!gdZ"GdddeZ#GdddeZ$GdddeZ%GdddeZ&GdddeZ'edddfddddd eee'efe(e(ee&d!d"d#Zdd$lm)Z)dd%lm*Z*e)d&e'j+j,iZ-dS)'N)partial)AnyOptionalUnion)Tensor) functional)ImageClassification) WeightsEnumWeights)_IMAGENET_CATEGORIES)handle_legacy_interface_ovewrite_named_param)GoogLeNetOutputs BasicConv2d Inception InceptionAux GoogLeNetGoogLeNet_Weights) _fuse_modules _replace_reluquantize_model)QuantizableGoogLeNetGoogLeNet_QuantizedWeights googlenetcsLeZdZeeddfdd ZeedddZd eeddd d Z Z S) QuantizableBasicConv2dNargskwargsreturncs tj|i|t|_dSN)super__init__nnReLUreluselfrr  __class__e/var/www/html/django/DPS/env/lib/python3.9/site-packages/torchvision/models/quantization/googlenet.pyr$szQuantizableBasicConv2d.__init__xr!cCs"||}||}||}|Sr"convbnr'r)r/r,r,r-forwards   zQuantizableBasicConv2d.forwardis_qatr!cCst|gd|dddS)Nr0T)inplace)r)r)r6r,r,r- fuse_model$sz!QuantizableBasicConv2d.fuse_model)N) __name__ __module__ __qualname__rr$rr4rboolr8 __classcell__r,r,r*r-rsrcs6eZdZeeddfdd ZeedddZZS)QuantizableInceptionNrcs&tj|dti|tj|_dSN conv_block)r#r$rr% quantizedFloatFunctionalcatr(r*r,r-r$)szQuantizableInception.__init__r.cCs||}|j|dS)Nr)_forwardrC)r)r/outputsr,r,r-r4-s zQuantizableInception.forwardr9r:r;rr$rr4r=r,r,r*r-r>(sr>cs6eZdZeeddfdd ZeedddZZS)QuantizableInceptionAuxNrcs$tj|dti|t|_dSr?)r#r$rr%r&r'r(r*r,r-r$4sz QuantizableInceptionAux.__init__r.cCsJt|d}||}t|d}|||}||}||}|S)N)rHr) Fadaptive_avg_pool2dr1torchflattenr'fc1dropoutfc2r3r,r,r-r48s     zQuantizableInceptionAux.forwardrFr,r,r*r-rG2srGcsLeZdZeeddfdd ZeedddZd ee ddd d Z Z S) rNrcs<tj|dtttgi|tjj|_ tjj |_ dS)Nblocks) r#r$rr>rGrKao quantization QuantStubquant DeQuantStubdequantr(r*r,r-r$LszQuantizableGoogLeNet.__init__r.cCsp||}||}||\}}}||}|jo8|j}tjr^|sRt dt |||S| |||SdS)NzCScripted QuantizableGoogleNet always returns GoogleNetOutputs Tuple) _transform_inputrTrDrVtraining aux_logitsrKjit is_scriptingwarningswarnr eager_outputs)r)r/aux1aux2 aux_definedr,r,r-r4Ss       zQuantizableGoogLeNet.forwardr5cCs(|D]}t|tur||qdS)aFuse conv/bn/relu modules in googlenet model Fuse conv+bn+relu/ conv+relu/conv+bn modules to prepare for quantization. Model is modified in place. Note that this operation does not change numerics and the model after modification is in floating point N)modulestyperr8)r)r6mr,r,r-r8`s  zQuantizableGoogLeNet.fuse_model)N) r9r:r;rr$rrr4rr<r8r=r,r,r*r-rJs rc @sDeZdZedeeddddeddejdd d d id d dZ e Z dS)rzKhttps://download.pytorch.org/models/quantized/googlenet_fbgemm-c00238cf.pth) crop_sizeie)rgfbgemmzdhttps://github.com/pytorch/vision/tree/main/references/classification#post-training-quantized-modelsz ImageNet-1Kg/tQ@g`"YV@)zacc@1zacc@5z These weights were produced by doing Post Training Quantization (eager mode) on top of the unquantized weights listed below. ) num_paramsmin_size categoriesbackendrecipeZ unquantized_metrics_docs)url transformsmetaN) r9r:r;r rr r r IMAGENET1K_V1IMAGENET1K_FBGEMM_V1DEFAULTr,r,r,r-rms$ r pretrainedcCs|ddrtjStjS)NquantizeF)getrrtrrs)r r,r,r-s ry)weightsTF)rzprogressrw)rzr{rwr r!cKs|rtnt|}|dd}|durd|vr:t|ddt|ddt|ddt|dt|jdd |jvrt|d |jd |d d }tfi|}t ||rt |||dur| |j |d |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: rYFNtransform_inputT init_weights num_classesrkrlrh)r{z`auxiliary heads in the pretrained googlenet model are NOT pretrained, so make sure to train them)rrverifyrxrlenrrpoprrrload_state_dictget_state_dictrYr_r`r\r])rzr{rwr original_aux_logitsrlmodelr,r,r-rs2+       r) _ModelURLs) model_urlsZgooglenet_fbgemm).r\ functoolsrtypingrrrrKtorch.nnr%rrrIZtransforms._presetsr _apir r _metar _utilsrrrrrrrrrutilsrrr__all__rr>rGrrr<rrrtrpZquant_model_urlsr,r,r,r-sN        # D