khA` dZddlmZmZmZddlmZddlmZm Z m Z m Z m Z ddl Z ddlmZddlmZmZddlmZmZmZmZmZmZdd lmZdd lmZmZdd lm Z m!Z!d gZ"eGd dZ#dZ$eGddZ%eGddZ& ddZ'GddejPZ)GddejPZ*GddejPZ+GddejPZ,Gd d!ejPZ-Gd"d#ejPZ.d$d%d$d&d'd'ej^ej`df d(Z1d)Z2d*Z3d+Z4d,e&d-e5d.e6d/e e7effd0Z8Gd1d ejPZ9dd2Z:e;did3e&e#d4d5d6d78e%d9d:d;d?@dAe&e#dBd$d6d78e%d9d:d;dC@dDe&e#dBd$d6d78e%d9dEd;ddFd=d>C@dGe&e#d4d5d6d78e%d9dEd;d%ddd=d>H@dIe&e#d%d$dd'8e%dJdKd&dLdMdNd>dO@dPe&e#d%d$dd'8e%dQdKdRdSdTddU@dVe&e#d%d$dd'8e%dWdKdRdSdTddU@dXe&e#d%d$dd'8e%dWdKd&d=ddYddZ@d[e&e#d%d$dd'8e%dJdKd&d=dddU@d\e&e#d%d$dd'8e%dJdKd&d=dd>dd]@d^e'd=d=_d`e'dadb_dce'dde'dedf_dge'd=d=d>hdie'dadbd>hdje'd>kdle'dedfd>hdme'dYe;dFnodpe'dYdedfqdre&e#dsd$d&d'8e%dtdEd&dud=d=dYvdwdxe'dedfdydz{d|e'dedfdydzdYe;dFn}Ze!ide>ddde>de>de>ddde>ddde>de>de>de>dddddde>ddddde>dde>dddddde>dddddde>ddddddde>ddddddde>dddddde>ddddde>de>ddddde>ddddde>de>ddddde>dddddddZ?e dde9fdZ@e dde9fdZAe dde9fdZBe dde9fdZCe dde9fdZDe dde9fdZEe dde9fdZFe dde9fdZGe dde9fdZHe dde9fdZIe dde9fdZJe dde9fdZKe dde9fdZLe dde9fdZMe dde9fdZNe dde9fdZOe dde9fdZPe dde9fdZQe dde9fdZRe dde9fdZSe dde9fdZTe dde9fd„ZUe dde9fdÄZVy)aPyTorch CspNet A PyTorch implementation of Cross Stage Partial Networks including: * CSPResNet50 * CSPResNeXt50 * CSPDarkNet53 * and DarkNet53 for good measure Based on paper `CSPNet: A New Backbone that can Enhance Learning Capability of CNN` - https://arxiv.org/abs/1911.11929 Reference impl via darknet cfg files at https://github.com/WongKinYiu/CrossStagePartialNetworks Hacked together by / Copyright 2020 Ross Wightman ) dataclassasdictreplace)partial)AnyDictOptionalTupleUnionNIMAGENET_DEFAULT_MEANIMAGENET_DEFAULT_STD)ClassifierHead ConvNormActDropPathget_attncreate_act_layermake_divisible)build_model_with_cfg) named_applyMATCH_PREV_GROUP)register_modelgenerate_default_cfgsCspNetceZdZUdZeeeedffed<dZeeeedffed<dZ eed<dZ eee fed <dZ e e ed <y ) CspStemCfg .out_chsstride kernel_sizepaddingpoolN)__name__ __module__ __qualname__rr intr __annotations__r!r#r%strr&r N/var/www/teggl/fontify/venv/lib/python3.12/site-packages/timm/models/cspnet.pyrrsd+-GU3c3h' (-*+FE#uS#X& '+K!GU38_!D(3-r.rct|ttfs|f}t|}||z }|dkr|d|St||df|zzS)Nr) isinstancetuplelistlen)xncurr_npad_ns r/_pad_argr:(sV a% ' D VF JE z!u aeX%% &&r.ceZdZUdZeedfed<dZeedfed<dZe eeedffed<dZ e eeedffed <d Z e e ee dffed <d Z e e ee dffed <d Ze eeedffed<dZee eeedffed<dZee eeefed<dZe eeefed<dZe eeefed<d Ze e ee dffed<d Ze eeedffed<d Ze eeedffed<dZy) CspStagesCfgr"r"r .depthrr r!rgroups? block_ratio bottle_ratioFavg_downN attn_layer attn_kwargscsp stage_typebottle block_type expand_ratio cross_linear down_growthct|j}t|j|k(sJt|j||_t|j ||_t|j ||_t|j||_t|j||_t|j||_ t|j||_ t|j||_ t|j||_ t|j||_ t|j||_t|j||_yN)r5r?rr:r!rErGrHrIrJrKrMrOrPrQrR)selfr7s r/ __post_init__zCspStagesCfg.__post_init__Fs  O4<< A%%%t{{A. t{{A. #D$4$4a8$T%6%6: 2 "4??A6#D$4$4a8"4??A6"4??A6$T%6%6:$T%6%6:#D$4$4a8r.)r'r(r)r?r r*r+rr!r rErGfloatrHrIboolrJr r,rKrrMrOrPrQrRrVr-r.r/r<r<3s)E5c?)4GU38_4*+FE#uS#X& '+*+FE#uS#X& '+36KueE3J//0646L%uUCZ0016.3HeD%c **+38!.>*>?RS!".  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A-15B [[_""599b"X1#=> r.rrs@r/rrWs4$!<[|r.rc8eZdZdZdddddedffd ZdZxZS) DarkStagezDarkNet stage.rFrNFc  tt| | xs|} t| j d| j d}| j dd}| rWt j|dk(rt jdnt jt||fdd|d||_ nt||fd|| ||d ||_ |}tt||z}t j|_t|D]=}|jj!t#|| d |||||| | |nd d | |}?y) Nr_rarzrbr rrr"rrxrr-)rrrrrrrrrrrrr*rrrrr,)rUrrr!r|r?rGrHrErrIrrrrrbrrrrs r/rzDarkStage.__init__sP i')'38\%5%5k%B|O_O_`lOmn ##J5 ]]#)Q; QBKKMFGc1VcWbcDN )2-.v_e!2%02DNE'K"789 mmo u %A KK " "3q68,%!)*3*?)A,R ,, %H %r.cJ|j|}|j|}|SrT)rrrUr6s r/rzDarkStage.forwards" NN1  KKNr.rrs@r/rrs($,%\r.rr"rr r$c dtj} g} t|ttfs|g}t |} | sJ|dvsJd} |} | dz }d}t |D]\}}d|dz}|dk(r|dkDs ||k(r |dkDr|sdnd}|dkDr| | j| | j|t| ||||dk(r|nd||||z}|} t| |djd |g } |r|dkDsJ| | j| |E| jd tjd dd | jd|| dd}n*| jd tjd dd d }|dz}t| |djd |g } | j| | | fS)N)rr rconvrr r$)r!r%r_ra.r[num_chs reductionmoduler&r")r#r!r%aa)channelsr!) rrr2r3r4r5 enumerateappendrrrjoin MaxPool2d)in_chansrr#r!r&r%r_rarbr[ feature_info stem_depth prev_featrlast_idx stem_striderchs conv_name conv_stride pool_names r/create_csp_stemrs ==?DL gt} -)WJ : Y  IHA~HKG$h31q5'N FvzqH}RS\`agh ?y4    *  ; c; AvG2! $   {" [SY[dReIfg h zz     *   OOFBLLQqRS$T U OOD(HQ"G HI OOFBLLQqRS$T UIq [SY[dReIfg  "  r.c|jd}|dvsJ|dk(r@|jdd|jdd|jddt}||fS|dk(r t}||fSt}||fS)NrM)rdrLrlrdrPrQrRrL)rrrr) stage_argsrMstage_fns r/ _get_stage_fnrs -J / // /V~t,~t,}d+ Z  u  Z  Z r.ct|jd}|dvsJ|dk(rt|fS|dk(rt|fSt|fS)NrO)rdedgerNrdr)rrrrv)rrOs r/ _get_block_fnr sP -J 3 33 3V*$$ v *$$ **r.c|jd}|jddxsi}|t|}|r t|fi|}||fS)NrJrK)rrr)rrJrKs r/ _get_attn_fnr )sR -J..5;Kj)  ;{;J z !!r.cfgdrop_path_rate output_stride stem_featc *t|j}t|jj}|sdg|znrt j d|t |jjj|jjDcgc]}|jc}|d<t|jDcgc]%}tt|j|'}}t|j|j} d} |d} |d} |} g}g}t|D]\}}t!|\}}t#|\}}t%|\}}|j'd}|dk7r| r|j)| | |k\r |dkDr| |z} d}| |z} | dvrdnd }||| fi|||| ||j*|d | gz }|d } t| | d | } |j)| t-j.||fScc}wcc}w)Nrrrzrrrr!rr r )r!rr|rrbrJrzstages.r)rr\r5r?rlinspacesumrtolistzipvaluesrkeysr_rarrr r rrrbrr)r r rrcfg_dict num_stagesr6rrrr| net_striderrrr\ stage_idxrrattn_fnr!rs r/create_csp_stagesr3s2 cjj!HSZZ%%&J7ETFZ/"^^A~s3::CSCS?TU[[\_\f\f\l\lmnn [CFHYCZ[$s8==?F34[J[-->>L H;'J#HIL F!*:!6_ :,Z8*,Z8**:6) Q;9    *  &6A:  HFf &&0a8     )\\     i(Z'R[Q\H]^ 3_6 " ==& !< //S o[s H  *Hc0eZdZdZ ddeffd ZejjddZ ejjddZ ejjde jfdZ dded eefd Zd Zdd efd ZdZxZS)raCross Stage Partial base model. Paper: `CSPNet: A New Backbone that can Enhance Learning Capability of CNN` - https://arxiv.org/abs/1911.11929 Ref Impl: https://github.com/WongKinYiu/CrossStagePartialNetworks NOTE: There are differences in the way I handle the 1x1 'expansion' conv in this impl vs the darknet impl. 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