o پi% @sdZddlmZddlmZmZddlmZddlm Z ddl m Z m Z ddl mZGd d d ejZd2d d Zd3ddZe eddeddeddeddddeddddddeddddddedddeddddZe d2d efd!d"Ze d2d efd#d$Ze d2d efd%d&Ze d2d efd'd(Ze d2d efd)d*Ze d2d efd+d,Ze d2d efd-d.Ze d2d efd/d0Zd1S)4a ResNeSt Models Paper: `ResNeSt: Split-Attention Networks` - https://arxiv.org/abs/2004.08955 Adapted from original PyTorch impl w/ weights at https://github.com/zhanghang1989/ResNeSt by Hang Zhang Modified for torchscript compat, and consistency with timm by Ross Wightman )nnIMAGENET_DEFAULT_MEANIMAGENET_DEFAULT_STD) SplitAttn)build_model_with_cfg)register_modelgenerate_default_cfgs)ResNetcs\eZdZdZdZdddddddddddejejddddffdd Zd d Z d d Z Z S) ResNestBottleneckzResNet Bottleneck rN@Fc stt|| dks J|dusJ|dusJ|dusJt||d|}| p,| } |r:|dks5| r:|}d}nd}||_tj||ddd|_|||_|dd|_ |dkrb| rbtj d|dd nd|_ |jdkrt ||d|| | ||||d |_ t|_t|_t|_n%tj||d|| | |dd |_ |||_|dur|nt|_|dd|_|dkr| stj d|dd nd|_tj||d ddd|_||d |_|dd|_||_dS) NrgP@rF) kernel_sizebiasT)inplace)padding)rstriderdilationgroupsradix norm_layer drop_layer)rrrrrrr )superr __init__intrrConv2dconv1bn1act1 AvgPool2d avd_firstrconv2Identitybn2 drop_blockact2avd_lastconv3bn3act3 downsample)selfinplanesplanesrr,r cardinality base_widthavdr"is_first reduce_firstrfirst_dilation act_layerr attn_layeraa_layerr& drop_path group_width avd_stride __class__G/home/ubuntu/.local/lib/python3.10/site-packages/timm/models/resnest.pyrsH      "         "  zResNestBottleneck.__init__cCs*t|jdddurtj|jjdSdS)Nweight)getattrr*rinitzeros_r@)r-r>r>r?zero_init_lastWsz ResNestBottleneck.zero_init_lastcCs|}||}||}||}|jdur||}||}||}||}||}|jdur9||}| |}| |}|j durM| |}||7}| |}|SN) rrr r"r#r%r&r'r(r)r*r,r+)r-xshortcutoutr>r>r?forward[s&                zResNestBottleneck.forward) __name__ __module__ __qualname____doc__ expansionrReLU BatchNorm2drrDrI __classcell__r>r>r<r?r s.?r FcKstt||fi|SrE)rr )variant pretrainedkwargsr>r>r?_create_resnestxsrUc Ks|dddddttddd |S) Ni)rrW)rXg?bilinearzconv1.0fc) url num_classes input_size pool_sizecrop_pct interpolationmeanstd first_conv classifierr)r[rTr>r>r?_cfgsreztimm/) hf_hub_id)rrg)rh)rfr]r^)r@ri) rjgJ +?bicubic)rfr]r^r_r`)rrl) rmgV-?)rfr`)zresnest14d.gluon_in1kzresnest26d.gluon_in1kzresnest50d.in1kzresnest101e.in1kzresnest200e.in1kzresnest269e.in1kzresnest50d_4s2x40d.in1kzresnest50d_1s4x24d.in1kreturnc KDttgddddddtdddd d }tdd |it|fi|S)z5 ResNeSt-14d model. Weights ported from GluonCV. )rrrrdeep TrrFrr2r"blocklayers stem_type stem_widthavg_downr1r0 block_args resnest14drSN)r{dictr rUrSrT model_kwargsr>r>r?r{   r{c Kro)z5 ResNeSt-26d model. Weights ported from GluonCV. )rrrrrrrrrprqTrrrrFrsrt resnest26drSN)rr|r~r>r>r?rrrc Kro)z ResNeSt-50d model. Matches paper ResNeSt-50 model, https://arxiv.org/abs/2004.08955 Since this codebase supports all possible variations, 'd' for deep stem, stem_width 32, avg in downsample. rr rrprqTrrrrFrsrt resnest50drSN)rr|r~r>r>r?r   rc KDttgddddddtddddd }td d |it|fi|S)z ResNeSt-101e model. Matches paper ResNeSt-101 model, https://arxiv.org/abs/2004.08955 Since this codebase supports all possible variations, 'e' for deep stem, stem_width 64, avg in downsample. )rr rrprTrrrFrsrt resnest101erSN)rr|r~r>r>r?rrrc Kr)z ResNeSt-200e model. Matches paper ResNeSt-200 model, https://arxiv.org/abs/2004.08955 Since this codebase supports all possible variations, 'e' for deep stem, stem_width 64, avg in downsample. )r$rrprTrrrFrsrt resnest200erSN)rr|r~r>r>r?rrrc Kr)z ResNeSt-269e model. Matches paper ResNeSt-269 model, https://arxiv.org/abs/2004.08955 Since this codebase supports all possible variations, 'e' for deep stem, stem_width 64, avg in downsample. )r0rhrprTrrrFrsrt resnest269erSN)rr|r~r>r>r?rrrc KDttgddddddtddddd }td d |it|fi|S)z]ResNeSt-50 4s2x40d from https://github.com/zhanghang1989/ResNeSt/blob/master/ablation.md rrprqT(rrr rsrtresnest50d_4s2x40drSN)rr|r~r>r>r?rrrc Kr)z]ResNeSt-50 1s4x24d from https://github.com/zhanghang1989/ResNeSt/blob/master/ablation.md rrprqTrr rrsrtresnest50d_1s4x24drSN)rr|r~r>r>r?rrrN)F)rV)rMtorchr timm.datarr timm.layersr_builderr _registryr r resnetr Moduler rUre default_cfgsr{rrrrrrrr>r>r>r?sf     f