a PSicJ @spUddlmZddlmZmZmZmZmZmZddl Z ddl m Z ddl m Z ddlmZddlmZmZdd lmZdd lmZmZgd ZGd d d e jZdFeeeefee jdddZgdgdgdgddZ eeeeeeffe!d<eeeeeeedddZ"dedddZ#Gdd d eZ$Gd!d"d"eZ%Gd#d$d$eZ&Gd%d&d&eZ'Gd'd(d(eZ(Gd)d*d*eZ)Gd+d,d,eZ*Gd-d.d.eZ+ed/e$j,fd0dd1d2ee$eeed3d4d5Z-ed/e%j,fd0dd1d2ee%eeed3d6d7Z.ed/e&j,fd0dd1d2ee&eeed3d8d9Z/ed/e'j,fd0dd1d2ee'eeed3d:d;Z0ed/e(j,fd0dd1d2ee(eeed3dd?Z2ed/e*j,fd0dd1d2ee*eeed3d@dAZ3ed/e+j,fd0dd1d2ee+eeed3dBdCZ4ddDlm5Z5e5e$j,j6e&j,j6e(j,j6e*j,j6e%j,j6e'j,j6e)j,j6e+j,j6dEZ7dS)G)partial)UnionListDictAnyOptionalcastN)ImageClassification)_log_api_usage_once) WeightsEnumWeights)_IMAGENET_CATEGORIES)handle_legacy_interface_ovewrite_named_param)VGG VGG11_WeightsVGG11_BN_Weights VGG13_WeightsVGG13_BN_Weights VGG16_WeightsVGG16_BN_Weights VGG19_WeightsVGG19_BN_Weightsvgg11vgg11_bnvgg13vgg13_bnvgg16vgg16_bnvgg19vgg19_bncsBeZdZd ejeeeddfdd Ze j e j dd d Z Z S) rT?N)features num_classes init_weightsdropoutreturnc s tt|||_td|_ttddt dtj |dtddt dtj |dtd||_ |r| D]}t |tjrtjj|jddd|jdurtj|jd q~t |tjrtj|jd tj|jd q~t |tjr~tj|jd d tj|jd q~dS) N)r*ibiT)pfan_outrelu)mode nonlinearityrr g{Gz?)super__init__r r%nnAdaptiveAvgPool2davgpool SequentialLinearReLUDropout classifiermodules isinstanceConv2dinitkaiming_normal_weightbias constant_ BatchNorm2dnormal_)selfr%r&r'r(m __class__R/var/www/html/django/DPS/env/lib/python3.9/site-packages/torchvision/models/vgg.pyr1$s2             z VGG.__init__)xr)cCs.||}||}t|d}||}|S)Nr )r%r4torchflattenr9)rDrJrHrHrIforwardAs     z VGG.forward)r#Tr$) __name__ __module__ __qualname__r2Moduleintboolfloatr1rKTensorrM __classcell__rHrHrFrIr#s  rF)cfg batch_normr)cCsg}d}|D]x}|dkr.|tjdddg7}q tt|}tj||ddd}|rl||t|tjddg7}n||tjddg7}|}q tj|S) NMr ) kernel_sizestrider )r[paddingT)inplace)r2 MaxPool2drrRr<rBr7r5)rWrXlayers in_channelsvconv2drHrHrI make_layersIs rd) @rZrZrgrZrhrZrhrhrZ)rererZrfrfrZrgrgrZrhrhrZrhrhrZ)rererZrfrfrZrgrgrgrZrhrhrhrZrhrhrhrZ)rererZrfrfrZrgrgrgrgrZrhrhrhrhrZrhrhrhrhrZ)ABDEcfgs)rWrXweightsprogresskwargsr)cKsn|dur4d|d<|jddur4t|dt|jdttt||dfi|}|durj||j|d|S)NFr' categoriesr&)rX)ro)metarlenrrdrmload_state_dictget_state_dict)rWrXrnrorpmodelrHrHrI_vggbsrw) rxzUhttps://github.com/pytorch/vision/tree/main/references/classification#alexnet-and-vggzNThese weights were trained from scratch by using a simplified training recipe.)min_sizerqrecipe_docsc @s>eZdZedeeddiedddddid d ZeZd S) rz6https://download.pytorch.org/models/vgg11-8a719046.pth crop_sizeihU ImageNet-1KgzGAQ@gx&1(V@zacc@1zacc@5 num_params_metricsurl transformsrrN rNrOrPrrr _COMMON_META IMAGENET1K_V1DEFAULTrHrHrHrIrus rc @s>eZdZedeeddiedddddid d ZeZd S) rz9https://download.pytorch.org/models/vgg11_bn-6002323d.pthr|r}ijrgHzQ@gp= sV@rrrNrrHrHrHrIrs rc @s>eZdZedeeddiedddddid d ZeZd S) rz6https://download.pytorch.org/models/vgg13-19584684.pthr|r}i(&rgZd{Q@g9vOV@rrrNrrHrHrHrIrs rc @s>eZdZedeeddiedddddid d ZeZd S) rz9https://download.pytorch.org/models/vgg13_bn-abd245e5.pthr|r}i(=rg/$Q@g-V@rrrNrrHrHrHrIrs rc @s~eZdZedeeddiedddddid d Zed eedd d dieddddededdiddd Z eZ dS)rz6https://download.pytorch.org/models/vgg16-397923af.pthr|r}i(+?rgSQ@g rV@rrrzIhttps://download.pytorch.org/models/vgg16_features-amdegroot-88682ab5.pth)g;pΈ?g N]?g| ?)p?rr)r~meanstdNz5https://github.com/amdegroot/ssd.pytorch#training-ssdnana` These weights can't be used for classification because they are missing values in the `classifier` module. Only the `features` module has valid values and can be used for feature extraction. The weights were trained using the original input standardization method as described in the paper. )rrqrzrr{) rNrOrPrrr rrrTZIMAGENET1K_FEATURESrrHrHrHrIrsJ rc @s>eZdZedeeddiedddddid d ZeZd S) rz9https://download.pytorch.org/models/vgg16_bn-6c64b313.pthr|r}i(L?rgףp= WR@g/$V@rrrNrrHrHrHrIrs rc @s>eZdZedeeddiedddddid d ZeZd S) rz6https://download.pytorch.org/models/vgg19-dcbb9e9d.pthr|r}i(0rgMbR@gMbV@rrrNrrHrHrHrIrs rc @s>eZdZedeeddiedddddid d ZeZd S) rz9https://download.pytorch.org/models/vgg19_bn-c79401a0.pthr|r}i([rgˡER@gSV@rrrNrrHrHrHrIrs r pretrained)rnT)rnro)rnrorpr)cKs t|}tdd||fi|S)apVGG-11 from `Very Deep Convolutional Networks for Large-Scale Image Recognition `__. Args: weights (:class:`~torchvision.models.VGG11_Weights`, optional): The pretrained weights to use. See :class:`~torchvision.models.VGG11_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.vgg.VGG`` base class. Please refer to the `source code `_ for more details about this class. .. autoclass:: torchvision.models.VGG11_Weights :members: riF)rverifyrwrnrorprHrHrIr s rcKs t|}tdd||fi|S)a|VGG-11-BN from `Very Deep Convolutional Networks for Large-Scale Image Recognition `__. Args: weights (:class:`~torchvision.models.VGG11_BN_Weights`, optional): The pretrained weights to use. See :class:`~torchvision.models.VGG11_BN_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.vgg.VGG`` base class. Please refer to the `source code `_ for more details about this class. .. autoclass:: torchvision.models.VGG11_BN_Weights :members: riT)rrrwrrHrHrIr9s rcKs t|}tdd||fi|S)apVGG-13 from `Very Deep Convolutional Networks for Large-Scale Image Recognition `__. Args: weights (:class:`~torchvision.models.VGG13_Weights`, optional): The pretrained weights to use. See :class:`~torchvision.models.VGG13_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.vgg.VGG`` base class. Please refer to the `source code `_ for more details about this class. .. autoclass:: torchvision.models.VGG13_Weights :members: rjF)rrrwrrHrHrIrRs rcKs t|}tdd||fi|S)a|VGG-13-BN from `Very Deep Convolutional Networks for Large-Scale Image Recognition `__. Args: weights (:class:`~torchvision.models.VGG13_BN_Weights`, optional): The pretrained weights to use. See :class:`~torchvision.models.VGG13_BN_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.vgg.VGG`` base class. Please refer to the `source code `_ for more details about this class. .. autoclass:: torchvision.models.VGG13_BN_Weights :members: rjT)rrrwrrHrHrIrks rcKs t|}tdd||fi|S)apVGG-16 from `Very Deep Convolutional Networks for Large-Scale Image Recognition `__. Args: weights (:class:`~torchvision.models.VGG16_Weights`, optional): The pretrained weights to use. See :class:`~torchvision.models.VGG16_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.vgg.VGG`` base class. Please refer to the `source code `_ for more details about this class. .. autoclass:: torchvision.models.VGG16_Weights :members: rkF)rrrwrrHrHrIrs rcKs t|}tdd||fi|S)a|VGG-16-BN from `Very Deep Convolutional Networks for Large-Scale Image Recognition `__. Args: weights (:class:`~torchvision.models.VGG16_BN_Weights`, optional): The pretrained weights to use. See :class:`~torchvision.models.VGG16_BN_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.vgg.VGG`` base class. Please refer to the `source code `_ for more details about this class. .. autoclass:: torchvision.models.VGG16_BN_Weights :members: rkT)rrrwrrHrHrIr s r cKs t|}tdd||fi|S)apVGG-19 from `Very Deep Convolutional Networks for Large-Scale Image Recognition `__. Args: weights (:class:`~torchvision.models.VGG19_Weights`, optional): The pretrained weights to use. See :class:`~torchvision.models.VGG19_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.vgg.VGG`` base class. Please refer to the `source code `_ for more details about this class. .. autoclass:: torchvision.models.VGG19_Weights :members: rlF)rrrwrrHrHrIr!s r!cKs t|}tdd||fi|S)a|VGG-19_BN from `Very Deep Convolutional Networks for Large-Scale Image Recognition `__. Args: weights (:class:`~torchvision.models.VGG19_BN_Weights`, optional): The pretrained weights to use. See :class:`~torchvision.models.VGG19_BN_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.vgg.VGG`` base class. Please refer to the `source code `_ for more details about this class. .. autoclass:: torchvision.models.VGG19_BN_Weights :members: rlT)rrrwrrHrHrIr"s r") _ModelURLs)rrrr!rrr r")F)8 functoolsrtypingrrrrrrrKtorch.nnr2Ztransforms._presetsr utilsr _apir r_metar_utilsrr__all__rQrstrrRrSr5rdrm__annotations__rwrrrrrrrrrrrrrrrr r!r"rr model_urlsrHrHrHrIst     &"" -""""""""