RЦi"9 *%SrSSKJrJrJrJrJrJrJr SSK r SSK J r SSK J s J r SSKJrJr SSKJr SSKJr SSKJr SS KJrJr S /r/S Q/S Q/S Q/SQS.r\\\\\\44\S'\"SS\ R@55r!"SS \ R@5r"S\#S\\\ RH44Sjr%S\S\&S\S\"4Sjr'S(S\S\\\44Sjjr(\"\("SS9\("SS9\("SS9\("SS9\("SS9\("SS9\("SS9\("SS9S.5r)\S)S\&S\S\"4S jj5r*\S)S\&S\S\"4S!jj5r+\S)S\&S\S\"4S"jj5r,\S)S\&S\S\"4S#jj5r-\S)S\&S\S\"4S$jj5r.\S)S\&S\S\"4S%jj5r/\S)S\&S\S\"4S&jj5r0\S)S\&S\S\"4S'jj5r1g)*zVGG Adapted from https://github.com/pytorch/vision 'vgg.py' (BSD-3-Clause) with a few changes for timm functionality. Copyright 2021 Ross Wightman )AnyDictListOptionalTypeUnioncastNIMAGENET_DEFAULT_MEANIMAGENET_DEFAULT_STD)ClassifierHead)build_model_with_cfg)register_notrace_module)register_modelgenerate_default_cfgsVGG) @Mrrrrrrrr)rrrrrrrrrrrrrrr)rrrrrrrrrrrrrrrrrr)rrrrrrrrrrrrrrrrrrrrr)vgg11vgg13vgg16vgg19cfgsc^\rSrSrSrSSSSS\R \RSS4 S \S \S \S \ S \ S\ \RS\ \RSS4U4Sjjjr S\ RS\ R4SjrSrU=r$)ConvMlpzpConvolutional MLP block for VGG head. Replaces traditional Linear layers with Conv2d layers in the classifier. r?g?N in_features out_features kernel_size mlp_ratio drop_rate act_layer conv_layerreturnc >XS.n [T U]5 X0l[X$-5n U"XU4SS0U D6UlU"S5Ul[ R"U5UlU"XS4SS0U D6Ul U"S5Ul g)a=Initialize ConvMlp. Args: in_features: Number of input features. out_features: Number of output features. kernel_size: Kernel size for first conv layer. mlp_ratio: Ratio for hidden layer size. drop_rate: Dropout rate. act_layer: Activation layer type. conv_layer: Convolution layer type. devicedtypebiasTrN) super__init__input_kernel_sizeintfc1act1nnDropoutdropfc2act2) selfr$r%r&r'r(r)r*r.r/dd mid_features __class__s N/var/www/html/ai-image-ml/venv/lib/python3.13/site-packages/timm/models/vgg.pyr2ConvMlp.__init__&s. / !,<34 kV4VSUVdO JJy) l!M$M"MdO xcURSUR:dURSUR:a\[URURS5[URURS54n[R"X5nUR U5nUR U5nURU5nURU5nURU5nU$)zGForward pass. Args: x: Input tensor. Returns: Output tensor. ) shaper3maxFadaptive_avg_pool2dr5r6r9r:r;)r<rC output_sizes r@forwardConvMlp.forwardGs 772;// /1772;AWAW3Wt55qwwr{CSI_I_abahahikalEmnK%%a5A HHQK IIaL IIaL HHQK IIaLrB)r6r;r9r5r:r3)__name__ __module__ __qualname____firstlineno____doc__r7ReLUConv2dr4floatrModuler2torchTensorrL__static_attributes__ __classcell__r?s@r@rrs # $ "")+*,))$$$ $  $  $BII$RYY$ $$B%,,rBrc^\rSrSrSrSSSS\R \RSSS SS4 S \\ S \ S \ S \ S\ S\ \RS\ \RS\\ \RS\S\ SS4U4Sjjjr\R$R&S#S\S\\\ 44Sjj5r\R$R&S$S\SS4Sjj5r\R$R&S\R4Sj5rS%S \ S\\SS4SjjrS\R4S\R44SjrS#S\R4S\S\R44SjjrS\R4S\R44S jrS&S!jrS"rU=r $)'r\zVGG model architecture. Based on `Very Deep Convolutional Networks for Large-Scale Image Recognition` - https://arxiv.org/abs/1409.1556  r#Navggcfg num_classesin_chans output_strider'r)r* norm_layer global_poolr(r+c 4>[TU]5 XS.n US:XdeX lX0lXlSUlUSLUl/UlUnSn[Rn/nUHn[U5S- nUS:Xa8URR[XSU3S95 UU"S S S 9/- nUS -nMO[[U5nU"UU4S SS .U D6nUbUUU"U40U D6U"S S9/- nO UUU"S S9/- nUnM [R"U6UlURR[XS[U5S- 3S95 XlSUl['UUR$S4UU UUS.U D6Ul[+UR$U4U U S.U D6UlUR/5 g)aInitialize VGG model. Args: cfg: Configuration list defining network architecture. num_classes: Number of classes for classification. in_chans: Number of input channels. output_stride: Output stride of network. mlp_ratio: Ratio for MLP hidden layer size. act_layer: Activation layer type. conv_layer: Convolution layer type. norm_layer: Normalization layer type. global_pool: Global pooling type. drop_rate: Dropout rate. r-r`FNrrz features.)num_chs reductionmodule)r&strider_)r&paddingT)inplacer!r")r'r(r)r*) pool_typer()r1r2rcrdr(grad_checkpointinguse_norm feature_infor7 MaxPool2dlenappenddictr r4 Sequentialfeatures num_featureshead_hidden_sizer pre_logitsr head_initialize_weights)r<rbrcrdrer'r)r*rfrgr(r.r/r=prev_chs net_stride pool_layerlayersvlast_idxconv2dr?s r@r2 VGG.__init__cs:  /"""& ""'"$.  \\ "$A6{QHCx!!((h_hiqhr]s)tu:!A>??a aL#HaPQPRP)vz!':r':Id??F v.    hW`adekalopap`qUr!st$ $!   ! !    !    #  ! !  "        "rBcoarsec[SSS9$)zGroup matcher for parameter groups. Args: coarse: Whether to use coarse grouping. Returns: Dictionary of grouped parameters. z ^features\.0z^features\.(\d+))stemblocks)rw)r<rs r@ group_matcherVGG.group_matchers1DEErBenablec U(aS5eg)zgEnable or disable gradient checkpointing. Args: enable: Whether to enable gradient checkpointing. z$gradient checkpointing not supportedN)r<rs r@set_grad_checkpointingVGG.set_grad_checkpointingsAAAz6rBc.URR$)z?K   s)DkJ'    E LrBurlc 2USSSSS[[SSSS . UE$) zCreate default configuration dictionary. Args: url: Model weight URL. **kwargs: Additional configuration options. Returns: Configuration dictionary. r^)r_r)r"r"g?bilinearz features.0rz bsd-3-clause) rrc input_size pool_sizecrop_pct interpolationmeanstd first_conv classifierlicenser )rrs r@_cfgrDs5=vJ%.B")!    rBztimm/) hf_hub_id)z vgg11.tv_in1kz vgg13.tv_in1kz vgg16.tv_in1kz vgg19.tv_in1kzvgg11_bn.tv_in1kzvgg13_bn.tv_in1kzvgg16_bn.tv_in1kzvgg19_bn.tv_in1kc 2[S0UD6n[SSU0UD6$)zVGG 11-layer model (configuration "A") from `"Very Deep Convolutional Networks For Large-Scale Image Recognition" `._ rr)rrwrrr model_argss r@rre" J  D: D DDrBc R[SS[R0UD6n[SSU0UD6$)zVGG 11-layer model (configuration "A") with batch normalization `"Very Deep Convolutional Networks For Large-Scale Image Recognition" `._ rfrr)vgg11_bnrwr7rrrs r@rrn- ::6:J  Gj GJ GGrBc 2[S0UD6n[SSU0UD6$)zVGG 13-layer model (configuration "B") `"Very Deep Convolutional Networks For Large-Scale Image Recognition" `._ rr)rrrs r@rrwrrBc R[SS[R0UD6n[SSU0UD6$)zVGG 13-layer model (configuration "B") with batch normalization `"Very Deep Convolutional Networks For Large-Scale Image Recognition" `._ rfrr)vgg13_bnrrs r@rrrrBc 2[S0UD6n[SSU0UD6$)zVGG 16-layer model (configuration "D") `"Very Deep Convolutional Networks For Large-Scale Image Recognition" `._ rr)rrrs r@rrrrBc R[SS[R0UD6n[SSU0UD6$)zVGG 16-layer model (configuration "D") with batch normalization `"Very Deep Convolutional Networks For Large-Scale Image Recognition" `._ rfrr)vgg16_bnrrs r@rrrrBc 2[S0UD6n[SSU0UD6$)zVGG 19-layer model (configuration "E") `"Very Deep Convolutional Networks For Large-Scale Image Recognition" `._ rr)rrrs r@rrrrBc R[SS[R0UD6n[SSU0UD6$)zVGG 19-layer model (configuration 'E') with batch normalization `"Very Deep Convolutional Networks For Large-Scale Image Recognition" `._ rfrr)vgg19_bnrrs r@rrrrB)r)2rRtypingrrrrrrr rWtorch.nnr7torch.nn.functional functionalrI timm.datar r timm.layersr _builderr _features_fxr _registryrr__all__rrr4__annotations__rVrrrwrXrrrr default_cfgsrrrrrrrrrrBr@rs@?? A&*1< 'N V e t *d3U38_% %&9bii99xt-"))t-n4Dell):$;.$##4cT#s(^*%G,G,G,G,w/w/w/w/ &  EdEcEcEEHHHHHEdEcEcEEHHHHHEdEcEcEEHHHHHEdEcEcEEHHHHHrB