vendor/libonnxruntime.dylib in onnxruntime-0.6.2 vs vendor/libonnxruntime.dylib in onnxruntime-0.6.3

- old
+ new

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LA?AπApHCQHz:EH:9H:-H1;!Hn;H; H;H%<Hb<H<H<H(=Hd=H=H=H$>H`>H>|H>sH?jH]?aH?XH?OH@FH]@=H@4H@+HA"H\AHAHAHBI]`H[A\A]A^A_]øLH8Hާfx ,8DMV_hqzllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllFFFFFFFFFFFFFFS|||;8BLV`jt~@UHAWAVAUATSHHHEaHHELsHCHufAHCXHCPL{0L{8DkHC@L)vE/HC8CHσ rbsH?H9wHALE +IL.D(HHHC0HK8ILc@MtLCHσ sL A]0O-u -LHHσ sLAfffff.sLH\HЃ +r.EteumsLyH-HЃ +sLYH A w+ffffff.sL(HЃ rCHKHC HtHK HC(Ht -HK(HH{tHK8HE0AtAAuLI~JAu}I~{-t +sLo.HCЃ -H!qH{XHuȺ -2Ic08u=L{pH |H H;Mt]zH{XHuȺ -2I&08tHCHuILsXHuLL2CxH #H H;M"H[A\A]A^A_]L{hH H H;Mt0L-AHNeE._LH-HЃ w=@sL(-HHЃ -rEeAH]o=H}o40u(sL,AHeXWHnHC`H H H;M.HwHoffffff.UHAWAVATSI=AL$DqA +HK(HH{tHK8HEAtAAuLI~JAu}I~{-t +sLHCЃ +HA;H{XHuȺ +I8u=L{pH ^H H;Mt]zH{XHuȺ +IF8tHCHuILsXHuLlCxH c^H H;M"H[A\A]A^A_]L{hH 7^H H;Mt0LAHNeE._LhHЃ w=@sLHHHЃ +rEeAH}9=H940u(sLAHeXWH9HC`H A]H H;MHwHoffffff.UHAWAVATSI=AL$DqA r$AwQALAL$DyA r$AsQALAL$YЃ rAsQwNLAL$AЃ -rAsQwA AEDÉ[A\A^A_]fUHAWAVAUATSHIHHHHEW)EHEL{8HHHE1L- AtVDHMAAtBE1HEHfffff.HAHEHEHHHH 4ЋC0ȃ IcDLHL*@LC0 +rAsQwA AEDÉ[A\A^A_]fUHAWAVAUATSHIHH[HHEW)EHEL{8HHHE1L- AtVDHMAAtBE1HEHfffff.HAHEHEHHHH 4ЋC0ȃ IcDLHL*@LC0 HMHEHHH9uHH HH?H9sHH@HH9HCHH}V2HM=ffff.HL7LC0 LH=LC0 HMHEHHH9uHHH HH?H9sHH@HH9HCHH}1HMHAHEHEHHHHH!4L,C0C0ȃ h_fDL9HEHHHMHHH Hs;LC0 LC0Affff.LC0 |LC0LH;\LYC0 )LEC0Aw0 -L_@ f _L8L5@f.(T Քf. top1LHp_HDžp1LHp,dHHp1LHpXfc1LHhMƅp1LHpua0ƅp1LHpXaHHp1LHpjH}Ht(H(HH;EH[A\A]A^A_]LcPH}LG HC`HhHCPHKXH`HXW) ƅ +L_@ f _L8L5@f.(T f. Tbop1LHp_HDžp1LHp,dHHp1LHpXfc1LHhMƅp1LHpua0ƅp1LHpXaHHp1LHpjH}HtHhWHH;EH[A\A]A^A_]LcPH}LG HC`HhHCPHKXH`HXW) ƅ HDž0Dž!valufDž%eH@H H HpHXH@e HUHpLL7 LcPH}L HC`HhHCPHKXH`HXW) ƅ HDž0Dž!valufDž%eH@H 1HXHpHXH@e HUHpLL -HHpH}$Hp&@ E 1H}HLcPH}L HC`HhHCPHKXH`HXW) ƅ HDž0Hobject kH!fDž)eyƅ+H@H H8HpHXH@e HUHpLLc LcPH}L +H:tHpH}Hp +@ E 1H}HLcPH}L HC`HhHCPHKXH`HXW) ƅ HDž0Hobject kH!fDž)eyƅ+H@H H8HpHXH@e HUHpLLc LcPH}L HC`HhHCPHKXH`HXW) ƅ HDž0HeparatorH)Hobject sH!ƅ1H@H HkHpHXH@e, HUHpLLLcPH}L HC`HhHCPHKXH`HXW) ƅ HDž0Dž!arrafDž%yH@H HHpHXH@eu -HUHpLLWLcPH}L8 HC`HhHCPHKXH`HXHDž0HDž(ƅ fDž%ctDž!objeƅ'H@H H HpHXH@e HUHpLL LcPH}LyHC`HhHCPHKXH`HXW) ƅ HDž0Hobject kH!fDž)eyƅ+H@H H0 HpHXH@eHUHpLL[LcPH}LHC`HhHCPHKXH`HXW) ƅ HDž0HeparatorH)Hobject sH!ƅ1H@H Hc HpHXH@e$HUHpLLH[PH}LH LH%cH 1HHHPHHPHHH@H@H@HH5H@HHHhHHPH`HXH@H@HHpHX*9HUHpLHHHpH}Hp !XHh!@HP H0 E H} H}H!H} H} HH}HzHH}HeHH@HpH}Hp0 XuIHX9Hh @)JH@5H QHEQHH}HH@H HH}Hn?H@zH nHH}Hl*H@6WH *sHH}H(H@H /HH}HvH@H HH}Ha5H@ttH tlHH}Htn,HHHpH}Hp@t@H@t2H@u& uNEuZH}HH HP tH t H tH0EtH}pH}HtbHH}HtTHH}HtFHH}Hs4HH}Ha"HH}HOHH}H=H> HH}Hl$k]]]]fff.UHAVSGXHˀt:HcCHiQHH?H%HHiQHH?H%kd)ȃv1[A^]H HcH(DILH`H5鲚H LV ILHaH5 HML( ILHaH5HvOL ILHf`H5H4L ILH`H5HLfFtfff.UHAWAVAUATSHIHHHEID$ID$I$H^0Ln8L9tjL5\L}fff. w8EHE 1LLLLffff.LHI9uHHH;EuLH[A\A]A^A_]IA$u IA$t -I|$4Lt fff.UHAWAVATSHHHHEHIAIW)@HDžPƅ@Hparse_erHADžIrorH`H@D'H5U[H`|HHHMHHPHUHxH@H@HH(Ld_(tH8H0 H)HxHHHMHHPHUHMH@H@HH5"H}HHHMHHPHUHMH@H@HHsHEsHESH}HHHMHHPHUHMH@H@HEE(x`@t HPEHuHEuIH߭I$Et$I|$HݮI$I\$ Et H}HFHH;ELH[A\A^A_]H}EAH}(8H8ox,H}Y`#Hp@@HL EH}HEu7EuK(ubxu|`@H}Et HEtH}(t H(tH8xt HxtH}e`{H`iHp:@uH@t HPHW ffffff.UHAWAVAUATSHIHbHHEIEIEAEIEHx error IEHsyntax eIEAEItHAHuHH5DWH}H=H5H};HHHMHHPHUHMH@H@HEHuHEuHEULEt H}Et H}H5VLIcD$0HueLLPM$W)pHEL(HHHpLqHw H L$L%VW)EHELIItIDELuMIIILILuILpHxLLHOAH5UHpHHHMHHPHUHMI8H@H@HHXLLP;LXHhH`LLHHH5ILuHH]L}LLLLC>HTH}1HHHMHHPHUHMH@H@HEHuHEuHEULEt H}EH}yvHYH}GHHHMHHPHUHMH@H@HH5dqH}HHHMHHPHUHMH@H@HEHuHEuHEULEcElXuEp˃wHcH ʩL4L5TW)EHELII{IsDELeMu(4LHHH'ILeHH]L}LLLC<HRH}1HHHMHHPHUHMH@H@HEHuHEuHEULEt H}EH}qH쇚HH;Et{H}SEH}@XHh'EH}pvH}mHqHH;EuLHĘ[A\A]A^A_],H}5 Hp' H}  KMAIEu+Eu?XuVEpH}\Et IEtH}BXt IXtHhEt LPIEuuIEtH}puIpH}HPuyLPIEu-!LPIEtH}Eu3LPIEt#H}hHPu(LPIHPtHPHx2Lr  f.UHSPHHHH{ HH[] fDUHAWAVAUATSHIHHOHHEW)EHEL{8IFHIIE1AtYIFHMAAt=E1HEHpVfHAHEHEHHHH 4ЋC0ȃ  H HcHELHuCUHpINI;N^HIFdELHuUHpINI;NsHIFDHHpWLC0 gIFH@HxLpLHUHpLE3AH8IF LC0 HMHEHHH9uHHH HH?H9sHH@HH9HCHH}OHMHAHEHEHHHHH!4LC0C0ȃ ~fff.HHpVLC0 +HUHpLLWLcPH}L8 HC`HhHCPHKXH`HXHDž0HDž(ƅ fDž%ctDž!objeƅ'H@H H HpHXH@e HUHpLL LcPH}LyHC`HhHCPHKXH`HXW) ƅ HDž0Hobject kH!fDž)eyƅ+H@H H0 HpHXH@eHUHpLL[LcPH}LHC`HhHCPHKXH`HXW) ƅ HDž0HeparatorH)Hobject sH!ƅ1H@H Hc HpHXH@e$HUHpLLH[PH}LH LHE-H 1HHHPHHPHHH@H@H@HH5JH@HHHhHHPH`HXH@H@HHpHX*9HUHpLHH[nHpH}Hp+XHh$@HP H0E H}H}H(H}% H} HH}HzHH}HeHHmHpH}4HpPXuIHX9Hh8@)JH@5H QHEQHH}HH@H HH}Hn?H@zH nHH}Hl*H@6WH *sHH}H(H@H /HH}HvH@H HH}Ha5H@ttH tlHH}Htn,HHEkHpH}Hp@t@H@t2H@u& uNEuZH}HH& HP tH t H tH0EtH}H}HtbHH}HtTHH}HtFHH}Hs4HH}Ha"HH}HOHH}H=H^ HH}Hl$k]]]]fff.UHAVSGXHˀt:HcCHiQHH?H%HHiQHH?H%kd)ȃv1[A^]H HcH(dILH`H5)jH Lv 6ILHaH5KiHMLH ILHaH5]iHvOL ILHf`H5hH4L ILH`H51hHLfFtfff.UHAWAVAUATSHIHIHHEID$ID$I$H^0Ln8L9tjL5&L}fff. w8EHE 1LL&LLffff.LHI9uH6IHH;EuLH[A\A]A^A_]IA$u IA$t +I|$TL fff.UHAWAVATSHHHHHEHIAIW)@HDžPƅ@Hparse_erHADžIrorH`H@D'H5u%H`HHHMHHPHUHxH@H@HH(Ld_(tH8H0 H)Hx0HHHMHHPHUHMH@H@HH5H}HHHMHHPHUHMH@H@HHsHEsHESH}HHHMHHPHUHMH@H@HEE(x`@t HP4EHuHEuIHeI$Et$I|$߂HfI$I\$ Et H}HFHH;ELH[A\A^A_]H}EAH}(8H8x,H}y`#Hp`@HL,EH}HEu7EuK(ubxu|`@H}Et HEtH}(t H(tH8xt HxtH}`{H`iHpZ@uH@t HP7Hw݂ ffffff.UHAWAVAUATSHIHDHHEIEIEAEIEHx error IEHsyntax eIEAEItHAHuHH5d!H}H]߂H5[H}[݂HHHMHHPHUHMH@H@HEHuHEuHEUL݂Et H}߂Et H}߂H5 L܂IcD$0HueLLPM$W)pHELHHHHpLqHw H ZcL$L%!W)EHELIItIDELuMIIILނILuILpHxLLHo߂AH5HpۂHHHMHHPHUHMI8H@H@HHXLLP;LXHhH`LLHHHU݂ILuHH]L}LLLLނC>HH}1ۂHHHMHHPHUHMH@H@HEHuHEuHEULڂEt H}܂EH}܂vHYH}gڂHHHMHHPHUHMH@H@HH5/;H}#ڂHHHMHHPHUHMH@H@HEHuHEuHEULقEcElXuEp˃wHcH +aL4L5;W)EHELނII{IsDELeMu(4LHHHGۂILeHH]L}LLL܂C<HH}1 قHHHMHHPHUHMH@H@HEHuHEuHEUL؂Et H}ڂEH}ڂH,?HH;Et{H}sڂEH}`ڂXHhGڂEH}4ڂpvH}ڂmH>HH;EuLHĘ[A\A]A^A_]LڂH}UׂHpGׂ H}<ׂ KMAIEu+Eu?XuVEpH}|قEt IEtH}bقXt IXtHh?قEt LPIEuuIEtH}قpuIpH}؂HPuyLPIEu-!LPIEtH}؂Eu3LPIEt#H}؂HPu(LPIHPtHPHxR؂LՂ f.UHSPHH0[HH{ՂHH[]؂fDUHAWAVAUATSHIHH<HHEW)EHEL{8IFHIIE1AtYIFHMAAt=E1HEHpVfHAHEHEHHHH 4ЋC0ȃ  H HcHELHuCUHpINI;N^HIFdELHuUHpINI;NsHIFDHHpWLC0 gIFH@HxLpLHHpLE3AH8IF LC0 HMHEHHH9uHHH HH?H9sHH@HH9HCHH}OHMHAHEHEHHHHH!4LC0C0ȃ ~fff.HHpVLC0 tmHMHEHHH9HHG -HH?H9sHH@HH9HCHH}HMIFHEHHHMHHH Hs6LC0 LC0A|:LC0 LC0gIFH@HxLpLHSHpLE+?H8IF L{C0 LgC0AD -{f w"LLWhƅpLHpl]HDžpLHp`f.(T ̵f. l}pLHpgYgƅpLHp\LHHpLHpk*HHpLHpcH}Ht H|HH;EH[A\A]A^A_]LcPH}LHC`HhHCPHKXH`HXW) ƅ +HH?H9sHH@HH9HCHH}HMIFHEHHHMHHH Hs6LC0 LC0A|:LC0 LC0gIFH@HxLpLHHpLE+?H8IF L{C0 LgC0AD +{f w"LLWhƅpLHpl]HDžpLHp`f.(T zf. 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(IB(IJD(J|(LL)HHt9Hfff.AGAIGHAAGIGMHHuH0fff.AGAIGHAAGIGAGAIGHAAGIGAGЈAIGHAAGIGAGAIGHAAGHIIGMM9{L;LsH H{LcM9t+LL)If.AvLSIHuMtLH[A\A]A^A_]|H[A\A]A^A_]E11wHIH耥L萢 UHSH(HHHEHHCH9Ct7H@8uyHxHGH;GH@HHHHGHEH}HEH0@uHHHUHPHMdHH *H H;MuMH([]HEH}HEHC 0@uHHHUHPHMHC H H H;Mt譤*HCH@H@H@HH H H;Mt@UHAWAVAUATSPL7LMM)IID$HH<*HLoM)LHHH9w`II9LBMH}HI9vJ责HH5IHHHHH5HH责H}HILH\HH}IJ IIHB JT J\ LL)HHt7Hf.AGAIGHAAGIGMHHuH0fff.AGAIGHAAGIGAGAIGHAAGIGAGЈAIGHAAGIGAGAIGHAAGHIIGMM9{L?LwHH_LoM9t+LL)If.AvLIHuMtLH[A\A]A^A_]ܡH[A\A]A^A_]E11z$IH㡂L ff.UHAWAVAUATSH(HHHEIHHCH9CtRH@8LxMoM;o IEAEEILLWMeIGHEEILL%H}L}H0@uHHHUHPHMHH GH H;MurH([A\A]A^A_]HEE裠ILL赞H}L}HC 0@uHHHUHPHMHC H H H;Mt襠LL\HCH@H@H@HH H H;MVHLHE HLH. fDUHAWAVAUATSPIIM~I)IIGHH<HMnI)LHHH9HuwYII9LBMI9vCxHH5 HޜHHHH5[HlHxILH'HIJD;B;ILHuJ;IIJL;L!HHM>IVL9HrL)Ht,HߐZXHZHXBHBHRHHuH0r{fZXHrHpBHBZXHrHpBHBZЈXHrHpBHBZXHrHpBH@HBHRI9uM>MfMIINMnM9t#LL)IAt$LIHuMtLH[A\A]A^A_]髝H[A\A]A^A_]E11zLIH话L迚 ILjHu -IHtHSL蓚 ff.UHSH(HHHEHHCH9Ct7H@8uyHxHGH;GH@HHHHGHEH}HEH0@uHHHUHPHMdHH *H 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HcHN(HN0HGxHGpHGhHG`HGXHGPHGHHG@HG8HG0HG(HG HGHGHGHHH]UHSPAHHH1P HH[]ff.UHHG0HOXH9sHGXHG`tHW H9sHO HHOH9s]ffffff.UHHG0HOXH9sHGXHHWH9Ws!tG`u@8ruHHWHO @2]HHWHO 1]UHAWAVAUATSH(AHHHHEAt&L{Lk0L+{HC8I9t-HKXH{XHs`E1HEHH;E\AC`HC(HEHCXHEH{@1H}訝HEHu -H7HH1lHEI)HKXH}H)HUu -HHCHHSPHHS(HC8ILk0Hs`HH{XIUHUH9H}HBH?H9t"C@u HK@HHKPIHKL{H{ I9t.HS0EuEH=HH;Eu]DH([A\A]A^A_]HH@hH H H;Mu4AHH([A\A]A^A_]H莞菞HHH;Et谞fUH]f.UH]>fDUHSPH*HH[]@UHHHxP ]HUHHNH 1H; HD]DUH]ĝfDUHAWAVAUATSH(IIAFAD$II$Ml$IvL貛AF*AD$*AF(fAD$(M|$0Iv0L荛I\$HIvHHL}xH]I|$`Iv`HI$IHAA$AfA$M$ILI$ILH([A\A]A^A_]H]LmIM$Mt3IAF(t I~8蘜AFt I~ 舜L耜IHuI?IHtdHEL0MunH]LmIHEL0MtWI$L9t>@HX@t HxHI9uHEH8M$HEt1LLmIHEuHEu8HEuTL  I|$X蹛HEtLmIHEtI|$@蔛HEtLmIHEtI|$ oL诘 UHAWAVATSIIIGIGII~I+>HHILHgffffffI9st HI_IKHIGM&MvM9u7Bfffff.ID$IL$ HK HCI_H(I_I(M9t HLȘ[A\A^A_]L IM'Mu CIM'Mt8IGL9t9HX@t HxKHI9uI?Mg7Lw Lf.UHAWAVAUATSH8HHHHEHGHGHGHC G HsH}LcMHEH@HEAD$I\$It$ HDIET$H}u -HHMLyMHuMOM`IL9r 1HIIHJH]L0MQAD$MD$I\$ MMLm@IFH9tL9r1IHL9ANHtIVL9uZu01fffff.AT: u:HH9uI~ 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type!!!HHH_tensor HHHot a nonHHHype is nHHHOpaque tH@'HSӁH`H0L+1H5H8L謌 IIƳHEH(HIIƳHHH(H'xEIIƳHEH(HgIIƳHHH(H1II*II0t H@誋HEH(HtIHEH;(t%Lh@t HxzLL9(uH}H(H(HEQEu!`u*HHH(Hu:H}!`tHp HHH(HVHPH;((Lh@t HxΊLL9(uII0t H@袊HEH(HtIHEH;(t%Lh@t HxrLL9(uH}H(H(HEIEu!`u*HHH(Hu6H}`tHpHHH(HtRHPH;(t(Lh@t HxΉLL9(uHHH(H(HP蟉tLÉEtEAL萉HHQ HXQHxIIL{ Mt#HIGHuILPLL{Mt#HIGHuILPLꇁHވEVFIIED4IIE2"IIE IIEH}胈AAu.L菈HHQHWQHwIL/.ffffff.UH]4fDUHAWAVAUATSHHHHEW)EMIIHHEHEHopaque(HMH}H誅H5f́H蛅HH萅H5ŃH聅H}@PHtbHHQ`HHHLLLEt H}S1HHH;EuHHĸ[A\A]A^A_]臇5IHH4eH5́H ́H`LH:#W)0HDž@`ՆHH@(:̒)0H5́VH#CVAH́H`H0L%E1H5 H:L讆iIHH4eH5ˁH ́H`LHn"W)0HDž@0 H@(a˒)0H type!!!HHH_tensor HHHot a nonHHHype is nHHHOpaque tH@'AH\́H`H0L$E1H5 H@L贅 HIAHEH(HHIAHHH(H)zGHIAHEH(HhHIAHHH(H1HI+HI0t H@讄HEH(HtIHEH;(t%Lh@t Hx~LL9(uH}H(H(HEUEu!`u*HHH(Hu:H}%`tHpHHH(HVHPH;((Lh@t Hx҃LL9(uHI0t H@覃HEH(HtIHEH;(t%Lh@t HxvLL9(uH}H(H(HEMEu!`u*HHH(Hu6H}`tHpHHH(HtRHPH;(t(Lh@t Hx҂LL9(uHHH(H(HP裂EtLƂEt`EuZucL蟂HHQ HgQH臂fHIEtHIEt HIEtH}%tu.L7HHQHQHIL'UHAWAVAUATSHIH HHH+HILIcL9LuH]EHELHHHAsHE~dMcE1Aff.JJHMH BD!uJt!fff.J4!H蕃IIM9|HED(HEH1kހt4t-u(HHHQ HQHۀ+u8HƀHHQHQH讀HH[A\A]A^A_]H\&HT&@UHAWAVSPIMt,~ AL@H;Ht+HIuL1H[A^A_]DUHAWAVAUATSH8IIIHHHECIIG0xu HoHH;E"H5Ɓ IGI H)HHL9Mt?1I1IHHHH;HLL9rW)EHEHLuALH=H}/ILuKH]LHuH]EAIufLMH|HH;E/H5-ƁH_HH;EH5<ƁH8[A\A]A^A_]QMWILH HHJLDILHHI ILHHHI LLI9uMtILH}t$11f.I I HHL9r1M7I0MPHPMHLHMHH}Ht H}}1H[HH;EuHH8[A\A]A^A_]}H}z HIH}HtCH}t}t:ucL}HHQHNQHn}6HIƃuLQ}HHQ HQH9}JIL"UHSPCdHHHHljQ 1HH[]Ãu(H|HHQ HQH|Ƀu(H|HHQHQH|H^"HV"fDUHSPH"HxH1HH[]Ãu(HQ|HHQ HQH9|Ƀu(H$|HHQHQH |H!H!fUHH5mÁ]Qf.UHAWAVAUATSPMAAAH{H@H@I$HDhDx Dp1HH[A\A]A^A_]Ãu(Hg{HHQ H/QHO{u(H:{HHQHQH"{H H UHAWAVAUATSHHHHIIHUߘHHEпzHH@HH@HHHHE1O|LH5!|txLH5|LH5|LH5s|LH5\|CHAII9rqKHHII9VU@CHII976CHA II9CHAII9HHH1HݘHH;EHHH[A\A]A^A_]L8HܘHHHHH@H8LHxHEEL%GݘID$HHI@L8HwHܘHHHHDž(HDž HDžHDžDž0H5H!IK\HzLHHl!HLL6'Lt HHQHt HwHHL8HHt H wL~vH5ۘHHvH8!wLgwHܘHH;Ew-HIH5iۘHHuLsHILhHIHHL8HHt H vHuH5ژHH\uH8dvHvt 6HIŃu+LvHHQ HxQHvu0LvHHQHHQHhvILfffff.UHHt]v]ffffff.UHSPH`uH@(H@ H@H@H@@0?H@PH@HH@@H@8@X?H1HH[]Ãu(HuHHQ H_QHuɃu(HjuHHQH2QHRuHHUHSPHHtHHH[]tH[]DUHAWAVATSII^HHt%fL;H{!HtLMuI~8IF8HttI^ HuEI~IFHtv[A\A^A_]etILPLQsCu-4L#L{0MtHIGHtCt H{ tH tLMuy[A\A^A_]DUHAWAVATSHMIHHHH kؘH HMHEILM1E1HHH.FIMu)HuHLgRIMuHEHEIE1H}HEHtHPHטHH;EuLH[A\A^A_]sHIƃt 9HIƃu.L3sHHQHQIsHIH}HEHtHPu+LrHHQ HQIrN9u0LrHHQH}QIrILSUHAWAVATSHMMHHHHH֘HHUHEILM1HIDIMu)HuHLPIMuHEHEIE1H}HEHtHPHb֘HH;EuLH[A\A^A_]rHIƃt 9HIƃu.LqHHQHnQIqHIH}HEHtHPu+L\qHHQ H$QIDqN9u0L(qHHQHQIqILfDUHSPBs HHX՘H8H51۹1qHH[]fffff.UHH$]UHM]HMffff.UHAVSHHtdLs Mt#HIFHuILPLoLsMt#HIFHuILPLnH[A^]o[A^]UHSPHHtHHH[]oH[]DUHHtH]`]fffff.UHSPHHtHHH[]ZoH[]DUHAWAVSPHH@L<H ӘHQHLtpH@HLpH\H bӘHHLDHt IXnHmH5ӘHLzmLH[A^A_]|nfff.UHAWAVSPHHӘHHH LspH@HCpL{HҘHHCCHt H{XunLYmH5ҘHHlLnHH[A^A_]@nfUHAWAVSPHH@HH ҘHQHLtpH@HLpL|H RҘHHLDHt H{XmLlH5ҘHHjlLvmHH[A^A_]m@UHSPHHјHHC@t H{PmHH[]flfff.UHSPHHјHHC@t H{PHmH,lHH[]2m@UHLV0LNXM9sLVXMDu MtF@u#HF@HMI)Åu E1ۅu1Hy>jHFPMI)ÅtL؃t!uOAuLH+F(Hy;HFH+FHx.I9|)HAtH~tAMHGxHGpHGhHG`HGXHGPHGHHG@HG8HG0HG(HG HGHGHGHHHH]AtHNHHNLN At HcHN(HN0HGxHGpHGhHG`HGXHGPHGHHG@HG8HG0HG(HG HGHGHGHHH]UHSPAHHH1P HH[]ff.UHHG0HOXH9sHGXHG`tHW H9sHO HHOH9s]ffffff.UHHG0HOXH9sHGXHHWH9Ws!tG`u@8ruHHWHO @2]HHWHO 1]UHAWAVAUATSH(AHHΘHHEAt&L{Lk0L+{HC8I9t-HKXH{XHs`E1HΘHH;E\AC`HC(HEHCXHEH{@1H}gHEHu +H7HH1gHEI)HKXH}H)HUu +HHCHHSPHHS(HC8ILk0Hs`HH{XIUHUH9H}HBH?H9t"C@u HK@HHKPIHKL{H{ I9t.HS0EuEH}͘HH;Eu]DH([A\A]A^A_]HH@hH T͘H H;Mu4AHH([A\A]A^A_]HhhH ͘HH;EthfUH]f.UH]^gfDUHSPHJgHH[]2h@UHHHxP ]HUHHNH 1H; ˘HD]DUH]gfDUHAWAVAUATSH(IIAFAD$II$Ml$IvLeAF*AD$*AF(fAD$(M|$0Iv0LeI\$HIvHHL}eH]I|$`Iv`HI$IHAA$AfA$M$ILI$ILH([A\A]A^A_]H]LmIM$Mt3IAF(t I~8fAFt I~ fLfIHuI?IHtfHEL0MunH]LmIHEL0MtWI$L9t>@HX@t Hx;fHI9uHEH8M$fHEt1LLmIHEuHEu8HEuTL-c I|$XeHEtLmIHEtI|$@eHEtLmIHEtI|$ eLb UHAWAVATSIIIGIGII~I+>HHILHgffffffI9st,eHI_IKHIGM&MvM9u7Bfffff.ID$IL$ HK HCI_H(I_I(M9t HLb[A\A^A_]Lb IM'Mu CIM'Mt8IGL9t9HX@t HxkdHI9uI?MgWdLa Lf.UHAWAVAUATSH8HHȘHHEHGHGHGHC G HsH}LcMHEH@HEAD$I\$It$ HDIET$H}u +HHMLyMHuMOM`IL9r 1HIIHJH]L0MQAD$MD$I\$ MMLm@IFH9tL9r1IHL9ANHtIVL9uZu01fffff.AT: u:HH9uI~ HLMdMLmHu[M6M_}ffff.IFH9tL9r1IHL9uUAFtIFHM6Mu5DHuMI!HJHf.0bIIt$LHH `ID$(IF(HEIFIH}HGHx H*HHH H*XLHDH Mx'I*O t+Y.fff.H*XO uK ?IrIW1L^f: -(\H,H HH1H,.HCH9HCIM}IGLLt1LmM9r1LIIfDHJHt$HILmI!HJHufDHUHIL2JIH_H@IOLAL9;1IH.DM MLmLMfff.IFH9t L!L9 ANHtIVL9uTu*1AT: u:HH9uI~ HLM LMMLmHutkM6Mof.IFH9t L!L9kAFt"IFHt)M6MuLfff.HufDM$$MSH!HHL0HGM$$M3H\ HH;EuH8[A\A]A^A_]qItI~ 誔IL蝔HEHXHt$fL3Ct H{ |HtLMuHEH8HHtTL蔑 IHEHXHuHBfUHAWAVSPHIHuM~L9w2HCHt HϑHM~L9vLHH[A^A_]Ir*IGLIFHy"HHH H*X1IFHxH*A^F f: +(ަ\H,H HH1H,.HCH9HCIM}IGLLt1LmM9r1LIIfDHJHt$HILmI!HJHufDHUHIL2JIH_H@IOLAL9;1IH.DM MLmLMfff.IFH9t L!L9 ANHtIVL9uTu*1AT: u:HH9uI~ HLM,aLMMLmHutkM6Mof.IFH9t L!L9kAFt"IFHt)M6MuLfff.HufDM$$MSH!HHL0HGM$$M3HØHH;EuH8[A\A]A^A_]=_qItI~ ^IL^HEHXHt$fL3Ct H{ ^H^LMuHEH8HHtt^L[ IHEHXHuHBfUHAWAVSPHIHuM~L9w2HCHt H[HM~L9vLHH[A^A_]Ir*IGLIFHy"HHH H*X1IFHxH*A^F f: - ~ޒ(\H,HH1H,.HC„t0Hr2HHȁAHH9HBL9:HH9HBL9 H[A^A_]fUHAWAVAUATSH(IIMtMLH=kJ<ԒI<$I$Ht趒Mt$I~DHs01Hu}I<$I$HtID$LH)1ff.I4$HI4$HDI4$HDI4$HDHH9uHt#Hfff.I$HHHuIt$HsI\$HNLtL9r1HIHH!I$HL>M<LuH}ffffff.I_Lt'L9r 1HIHH9uLL>MufH!H9tI$H<HMHuIMHAWHtIwHuLIAVt"IvHMH9HHtSt'IN (HMH9t"ff.INH1AT7:1HH9uILHuH4LHL>MMHfIAEt4IMHUH9I t;Iu t>fHUH9thfffff.IuH肑uJIMMHu<fHHtHHHt#fHuHIHuIIHuHI$HHII$HL8LuH}HML>MH([A\A]A^A_]ÿxHH5 ؁HތHHHH5[HlHxIHOL_ UHAWAVAUATSH w^H'H 0H|HHHH1Hi-8ߝHHH/H1H1HHH/H1HH1H@rHFLvLLI I'1˗\ȥIHN1I IIHNHH9LHII!LIHDLLtIH HHHDHH9LIH!HHHHHO@/;jHMMILH/L1ILHH/H1HHsoHLFLLHO@/;jIH'1˗\ȥHL)HHLHHH)HH<AIH HWePIL1H,HHH1Hi-8ߝHHH/H1H1HHH/H1H_IsoIi-8ߝHDLDLLI H|H1IHH/H1H1III/I1ML\IJLH+HLM< J MMIMIH\HLLLL$MHLILIIII+MIHH@H)H]HHUHH@Isofff.HH]H@HUH@MLHLvHVLLLFLHHILNMLHIMLUH^LHMIMIIMHIIM1ILILH+IIHH^L^LHMMLHIMH+IHUH1I1Hi-8ߝLLH/I1I1LLH/L1HHH/H1HsoHLHM1LLH/M1I1LLH/L1HHH1HHH/H1H1HHH/H1H[A\A]A^A_]HrDHJHO@/;jHtHH<>tHH ύ HHWePIHH1HH/H1HfUHAWAVSPII(Ht)L;Ct H{ HLMuIIdžHtIHt7fDL;C(t H{8̉Ct H{ 轉H赉LMuIIdžHt葉MMtJIL9t/ff.HX@t Hx[HI9uILM;AFHuAF0u"AFu+H[A^A_]I~XAF0tI~@AFtI~ H[A^A_]舁f.UHAWAVATSIIIMfI)IID$HH=HI^H)HHHH9wYHH9HBHH9vC{HH5сHᅁHHHH5^HoH{HH<)JLI7IJ4JDM>IvL9H^L)Ht-Hffff.HNHFHvHJHHuH8fHNHFHJHNHFHJHNHFHJHNHFHJHNHFHJHNHFHJHNHFHJHNHFHvHJHI9oM>I^LIIFMFL9t#H{HCH[HtHPI9uMtL[A\A^A_]鹆[A\A^A_]11LIHĆLԃ fff.UHAWAVSPII^8Ht;f.L;C(t H{8LCt H{ =H5LMuI~(IF(HtAFu H[A^A_]I~H[A^A_]@UHAWAVAUATSH(IHHHDHHEH8HHHHLH@H8L(HEEL5M~LI@L8L:L%ILHDž(HDž HDžHDžDž0HHH與HHHJI]HjHHH,HHHLL8Lt H 芄HjH5HHH8 HHH;EuHH([A\A]A^A_]葄HLL8Lt H H䂁HHHH5HHjH8rHHH8[HUHAWAVAUATSPHI豁Mt$HsL蠁M|$0Hs0LLu苁Ml$HHsHLzMt$`Hs`LiHCxID$xLHHHH[A\A]A^A_]HAu+AEuAAuVHEunA$H( I|$pԂAEt -HAEtI|$X跂At HAtI|$@蜂HEt HHEtI|$({A$t -HA$tI|$^H fDUHAWAVAUATSHHIH}/eH5́H ĆHXLEsW)EE HEHoverflowHEHInteger HEEHXHM1LH5HL IEt H}菁L}Mt6HEL9t!HX@t HxjHI9uH}LL}Pxt H}>Xt Hh)E1LmMuUH%IALmMt>HEL9t<ffff.HX@t HxۀHI9uH}LmƀEu -LIL߀L} UHAWAVAUATSHHHHEHHGH)HH9v7 u.HH9sOHHH;Eu:HĈ[A\A]A^A_]THHH;Eu1HĈ[A\A]A^A_]iIHh-eH5[ˁH ˁH}Lh(?W)PHDž`0H`(rʒ)PH elementHH&Hor its eHH H entry fHHHing typeHHH is missHHHSequenceH@.AH΁HuHPLgE1H5]HLZ IALeMuFzIALhMIIPt H`~LeMt6HEL9t!HX@t Hx~HI9uH}LLe~EuEuLhMu&^H}\~EtH}M~LhMt:HpL9tEHX@t Hx"~HI9uHhLp~EtL*~L:{ Lffff.UHAWAVAUATSHHEHHEHHOH)HH9vFu=Tu3HVH9sNLu DH H H;Mt}1H H H;MuHĈ[A\A]A^A_]ÿM}IHh*eH5ȁH ́H}LhFuW)PHDž`0|H`(ǒ)PHts valueHHHy for itHHHype entrHHHissing tHHHMap is mH@'AHˁHuHPLE1H5HJL| IALeMuFzIALhMIIPt H`|LeMt6HEL9t!HX@t Hx{HI9uH}LLe{EuEuLhMu&^H}{EtH}{LhMt:HpL9tEHX@t Hxf{HI9uHhLpK{EtLn{L~x LؐUHAWAVAUATSHHHHHE覼PH;Cu*HH vH H;MuHĘ[A\A]A^A_]4{zIH`(eH5ÁH ,́HxL`02PH@HH́HELHH@HULH_AH́HxLLE1H5yH"Lvz IALeMuFzIAL`MIIHt HXyLeMt6HEL9t!HX@t HxyHI9uH}LLeyEuxu L`Mu)aH}uyxtH}cyL`Mt:HhL9tEHX@t Hx8yHI9uH`LhyEtL@yLPv LUHAWAVAUATSH(IHIHHUHHEH8HHHHLH@H8L9xLHEEL=MgLI@L8LDwL-ILHDž(HDž HDžHDžDž0I6HIQHHzHHHLHH0HQHHHLL8Lt H wHtvH5HHvH8wHHH;EuHH([A\A]A^A_]wHLL8Lt H wHuH -HHHH5HHluH8tvHHH8]vHDUHAWAVAUATSHHHHEHHGH)HH9v7 u.HH9sOHHH;Eu:HĈ[A\A]A^A_]THHH;Eu1HĈ[A\A]A^A_]ivvIHh#eH5[H NɁH}Lh(?W)PHDž`0uH`(r)PH elementHH&Hor its eHH H entry fHHHing typeHHH is missHHHSequenceH@.AHāHuHPLgE1H5]HLZu IALeMuFzIALhMIIPt H`tLeMt6HEL9t!HX@t HxtHI9uH}LLetEuEuLhMu&^H}\tEtH}MtLhMt:HpL9tEHX@t Hx"tHI9uHhLptEtL*tL:q Lffff.UHAWAVAUATSHHEHHEHHOH)HH9vFu=Tu3HVH9sNLu DH H H;Mts1H H H;MuHĈ[A\A]A^A_]ÿMsIHh eH5H OɁH}LhFuW)PHDž`0rH`()PHts valueHHHy for itHHHype entrHHHissing tHHHMap is mH@'AHHuHPLE1H5 HJLr IALeMuFzIALhMIIPt H`rLeMt6HEL9t!HX@t HxqHI9uH}LLeqEuEuLhMu&^H}qEtH}qLhMt:HpL9tEHX@t HxfqHI9uHhLpKqEtLnqL~n LؐUHAWAVAUATSHHHHHEfPH;Cu*HH vH H;MuHĘ[A\A]A^A_]4qpIH`eH5̹H gȁHxL`0PH@HHÁHELHH@HULH_AHÁHxLLE1H5y H"Lvp IALeMuFzIAL`MIIHt HXoLeMt6HEL9t!HX@t HxoHI9uH}LLeoEuxu L`Mu)aH}uoxtH}coL`Mt:HhL9tEHX@t Hx8oHI9uH`LhoEtL@oLPl LUHAWAVAUATSHIHbHHEH8HHHHLH@H8LFnHEEHLkLH@H8LXmL5ILHDž(HDž HDžHDžDž0LLaLH8Lt H mLlH5HHtlH8|mHEHH;EuLH[A\A]A^A_]nILH8Lt H smLWlIH5iHHkH8lLMIH8lL6fDUHAWAVAUATSHHHHEHHOH)HH9vFu=Tu3HVH9sNLu DH 3H H;Mtm1H H H;MuHĈ[A\A]A^A_]ÿlIHh8eH5ѷH ƁH}LhFW)PHDž`00lH`(ȶ)PHts valueHHHy for itHHHype entrHHHissing tHHHMap is mH@'AH1HuHPLE1H5HLk IALeMuFzIALhMIIPt H`BkLeMt6HEL9t!HX@t HxkHI9uH}LLekEuEuLhMu&^H}jEtH}jLhMt:HpL9tEHX@t HxjHI9uHhLpjEtLjLg LؐUHAWAVAUATSHHHHHEfPH;Cu*HH H H;MuHĘ[A\A]A^A_]tj"jIH`eH5 H ,ƁHxL`0GPH@HH%HELHH@HULHAHɼHxLLE1H5HbLi IALeMuFzIAL`MIIHt HXiLeMt6HEL9t!HX@t HxhHI9uH}LLehEuxu L`Mu)aH}hxtH}hL`Mt:HhL9tEHX@t HxxhHI9uH`Lh]hEtLhLe LUHAWAVAUATSPIM.IFL)HHHH9H -H9I^IM)HL<vLgILL9Lff.HSHQHSHsHqHQHCHCHCH[HI9uM.IVIMfIFL9t'fff.HZBt HzKgHI9uMt&LH[A\A]A^A_](gM&MfIFMuH[A\A]A^A_]ÿgHH5H}dHHޘHHH5ܘH ܘHgIHfLc fDUHAWAVAUATSPIII -II_H)HHHHCL9)IOH)HHHTUUUUUUH9wHH9HBIHJH<@.fIH[IHL8dKDmMHSIIwH9tKDH~H{H~HNHKH{HFHFHFHvHH9uM7IGIIIWMGL9t"HX@t Hx{eHI9uMtLH[A\A]A^A_]XeH[A\A]A^A_]E1E1LbHMtL&eHfb fffff.UHAWAVAUATSHHuܘHHEHHOH)HH9vFu=Tu3HVH9sNLu DH #ܘH H;Mtd1H ܘH H;MuHĈ[A\A]A^A_]ÿ}dIHh(eH5H H}LhFW)PHDž`0 dH`()PHts valueHHHy for itHHHype entrHHHissing tHHHMap is mH@'AH!HuHPLE1H5HzLc IALeMuFzIALhMIIPt H`2cLeMt6HEL9t!HX@t Hx cHI9uH}LLebEuEuLhMu&^H}bEtH}bLhMt:HpL9tEHX@t HxbHI9uHhLp{bEtLbL_ LؐUHAWAVAUATSHHH٘HHEPH;Cu*HH ٘H H;MuHĘ[A\A]A^A_]dbbIH`eH5H +HxL`07袚PH@HHHELHH@HULHAHHxLLE1H5HRLa IALeMuFzIAL`MIIHt HX -aLeMt6HEL9t!HX@t Hx`HI9uH}LLe`Euxu L`Mu)aH}`xtH}`L`Mt:HhL9tEHX@t Hxh`HI9uH`LhM`EtLp`L] LUHAWAVAUATSPIHL3HCL)HL9sjLH=upLcM)J<_IKDMMM~LLLILaLL+L{HCMtLH[A\A]A^A_]_H[A\A]A^A_]ÿ_HH51H]H֘HHH5՘HԘH_IHs_L\ ff.UHAWAVAUATSHIIIuMeI)MIIGHH=HMuI)LHHH9waII9LBMLEHuI9vK^HH5OH \H՘HHH5ԘHӘH^LEHuIJ<`^HHuLEN4IJN|M~HLI_LI]M}MuHtHH[A\A]A^A_]]H[A\A]A^A_]E11LD[IH^L[ ff.UHAWAVAUATSHHH"՘HHE6PH;Cu*HH ՘H H;MuHĘ[A\A]A^A_]]r]IH` eH5\H lHxL`0–PH@HHuHELHH@HULHAHHxLLE1H5 HL] IALeMuFzIAL`MIIHt HXj\LeMt6HEL9t!HX@t HxE\HI9uH}LLe+\Euxu L`Mu)aH}\xtH}[L`Mt:HhL9tEHX@t Hx[HI9uH`Lh[EtL[LX LUHAWAVAUATSPIHL3HCL)HL9sjLH>upLcM)J<V[IKDMMM~LLLI\LL+L{HCMtLH[A\A]A^A_]ZH[A\A]A^A_]ÿZHH5HbXH-ҘHHH5ИHϘHZIHZLW ff.UHAWAVAUATSHIIIuMeI)MIIGHH> H?MuI)LHHH9w`II9LBMLEHuI9vKZHH5HWHLјHHH5ϘHϘHZLEHuIJ<YHHuLEN4ABN|M~HLI [LI]M}MuHtHH[A\A]A^A_]]YH[A\A]A^A_]E11LVIHdYLtV fff.UHAWAVAUATSHHИHHEHHOH)HH9vFu=Tu3HVH9sNLu D H 3ИH H;MtY1H ИH H;MuHĈ[A\A]A^A_]ÿXIHh8eH5ѣH `H}LhF赾W)PHDž`00XH`(Ȣ)PHts valueHHHy for itHHHype entrHHHissing tHHHMap is mH@'AH1HuHPLE1H5HLW IALeMuFzIALhMIIPt 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LLLLLLLLLLLLLLHI9uH5lH[A^A_]AQLHHyHHVH`s 1HuyHzH)1fffff.3L30L0D3 L30D0 L00D3@L3PD0@L0PD3`L3pD0`L0pHHuHt.HHfff.D3 3D0 0H HuI9u1HH[A^A_]HHVDUHAWAVAUATSHHlHHEHHC0x u.HHCPH clH H;MuHĨ[A\A]A^A_]!IHPzdH5cH jHhLPZHdHEH$dHEH0HdHEL8HuHUHMLI1AHcHhLLe]E1H5[H6LX IALPMII8t HHLeMt6HEL9t!HX@t HxHI9uH}LLeEuhu LPMu,dH}hhtHxSLPMt:HXL9tEHX@t Hx(HI9uHPLX EtL0L@ LUHAWAVAUATSHHUjHHEHHC0x u.HHCPH 3jH H;MuHĨ[A\A]A^A_]IHPJdH5jaH hHhLPXHaHEHaHEH0HaHEL8HuHUHMLIAH|aHhLL5[E1H5+H3L( IALPMII8t HHLeMt6HEL9t!HX@t HxxHI9uH}LLe^Euhu LPMu,dH}8htHx#LPMt:HXL9tEHX@t HxHI9uHPLXEtLL LUHAWAVSPIILHHfPIvIV H)HHLMjHHILEsWILMIrJ H9J H91IVH)LHt#Hfff.;8HHHHuHBI)11ff.44ttttt t ttttttttHI9uH5yeH[A^A_]I;QLHHyHHVHs 1HuqHzH)1fDLLD L0D L0D@LPD@LPD`LpD`LpH HuHt.H4HD3 3D0 0H HuI9u1HH[A^A_]HHdUHAWAVAUATSHHeHHEHHC0xu.HHCPH eH H;MuHĨ[A\A]A^A_]?IHPdH5 -]H tdHhLPdTH]HEH]HEH0H]HEL8HuHUHMLIAH]HhLLVE1H5ˆHt/L IALPMII8t HH=LeMt6HEL9t!HX@t HxHI9uH}LLeEuhu LPMu,dH}htHxLPMt:HXL9tEHX@t HxHI9uHPLX}EtLL LUHAWAVSPIILHHfPIvIV H)HHLeHHILnWILMIrJ H9J H91D)IVH)Ht#Hf.H;H8HHHHuHPI)11fH4H4HtHtHtHtHtHtHt Ht Ht(Ht(Ht0Ht0Ht8Ht8HI9uH5 aH[A^A_]6QLHHyHHVH s 1HuqHzH)1fDLLD L0D L0D@LPD@LPD`LpD`LpHHuHt.H4HD3 3D0 0H HuI9u1HH[A^A_]HHTUHAWAVAUATSHHaHHEHHC0x u.HHCPH caH H;MuHĨ[A\A]A^A_]!IHPzdH5XH 6`HhLPOHYHEH$YHEH0HYHEL8HuHUHMLI1AHXHhLLeRE1H5[H+LX IALPMII8t HHLeMt6HEL9t!HX@t HxHI9uH}LLeEuhu LPMu,dH}hhtHxSLPMt:HXL9tEHX@t Hx(HI9uHPLX EtL0L@ LUHAWAVAUATSPIILtIMtv^PIwIW H)HHL}aIMu=ILyjWIL^HE1MtHH[LMmIuLH[A\A]A^A_]H5;]H[A\A]A^A_]3QUHAWAVSPIIL(HH'bPIvIV H)HHL`HHILiWIL + ^(\H,HH1H,.HC„t0Hr2HHȁAHH9HBL9:H[H9HBL9 H[A^A_]fUHAWAVAUATSH(IIMtMLH=kJ<\I<$I$Ht\Mt$I~DHs01Hu}I<$I$Ht\ID$LH)1ff.I4$HI4$HDI4$HDI4$HDHH9uHt#Hfff.I$HHHuIt$HsI\$HNLtL9r1HIHH!I$HL>M<LuH}ffffff.I_Lt'L9r 1HIHH9uLL>MufH!H9tI$H<HMHuIMHAWHtIwHuLIAVt"IvHMH9HHtSt'IN (HMH9t"ff.INH1AT7:1HH9uILHuH4LHL>MMHfIAEt4IMHUH9I t;Iu [t>fHUH9thfffff.IuH[uJIMMHu<fHHtHHHt#fHuHIHuIIHuHI$HHII$HL8LuH}HML>MH([A\A]A^A_]ÿYHH5-HVH齘HHH5HHYIHoYLV UHAWAVAUATSH w^H'H 0H|HHHH1Hi-8ߝHHH/H1H1HHH/H1HH1H@rHFLvLLI I'1˗\ȥIHN1I IIHNHH9LHII!LIHDLLtIH HHHDHH9LIH!HHHHHO@/;jHMMILH/L1ILHH/H1HHsoHLFLLHO@/;jIH'1˗\ȥHL)HHLHHH)HH<AIH HWePIL1H,HHH1Hi-8ߝHHH/H1H1HHH/H1H_IsoIi-8ߝHDLDLLI H|H1IHH/H1H1III/I1ML\IJLH+HLM< J MMIMIH\HLLLL$MHLILIIII+MIHH@H)H]HHUHH@Isofff.HH]H@HUH@MLHLvHVLLLFLHHILNMLHIMLUH^LHMIMIIMHIIM1ILILH+IIHH^L^LHMMLHIMH+IHUH1I1Hi-8ߝLLH/I1I1LLH/L1HHH/H1HsoHLHM1LLH/M1I1LLH/L1HHH1HHH/H1H1HHH/H1H[A\A]A^A_]HrDHJHO@/;jHtHH<>tHH ύ HHWePIHH1HH/H1HfUHAWAVSPII(Ht)L;Ct H{ <TH4TLMuIIdžHtTIHt7fDL;C(t H{8SCt H{ SHSLMuIIdžHtSMMtJIL9t/ff.HX@t Hx{SHI9uILM[SAFHuAF0u"AFu+H[A^A_]I~X2SAF0tI~@"SAFtI~ H[A^A_]Sf.UHAWAVATSIIIMfI)IID$HH=HI^H)HHHH9wYHH9HBHH9vCRHH50HPH춘HHH5HHRHH<IRJLI7IJ4JDM>IvL9H^L)Ht-Hffff.HNHFHvHJHHuH8fHNHFHJHNHFHJHNHFHJHNHFHJHNHFHJHNHFHJHNHFHJHNHFHvHJHI9oM>I^LIIFMFL9t#H{HCH[HtHPI9uMtL[A\A^A_]P[A\A^A_]11L%NIHPLM fff.UHAWAVSPII^8Ht;f.L;C(t H{8lPCt H{ ]PHUPLMuI~(IF(Ht7PAFu H[A^A_]I~H[A^A_]P@UHAWAVAUATSH(IHHHHHEH8HHHHLH@H8LHOHEEL5M~LI@L8LZNL%ILHDž(HDž HDžHDžDž0HHHQHHHJI]HQHHH,HHHLL8Lt H NHMH5HH%MH8-NHHH;EuHH([A\A]A^A_]NHLL8Lt H $NHMHHHH5&HHLH8MHHH8{MHUHAWAVAUATSPHIKMt$HsLKM|$0Hs0LLuKMl$HHsHLKMt$`Hs`LKHCxID$xLHHHH[A\A]A^A_]HAu+AEuAAuVHEunA$HHJ I|$pLAEt +HAEtI|$XLAt HAtI|$@LHEt HHEtI|$(LA$t +HA$tI|$~LHI fDUHAWAVAUATSHhLIH}dH51H cHXLEsW)EE HEHoverflowHEHInteger HEEHXHM1LH54ҘHLL IEt H}KL}Mt6HEL9t!HX@t HxKHI9uH}LL}pKxt H}^KXt HhIKE1LmMuUH%IALmMt>HEL9t<ffff.HX@t HxJHI9uH}LmJEu +LILJLH UHAWAVAUATSHHEHHEHHGH)HH9v7 u.HH9sOHHH;Eu:HĈ[A\A]A^A_]THHH;Eu1HĈ[A\A]A^A_]J7JIHhdH5{H ĕH}Lh(?W)PHDž`0IH`(R)PH elementHH&Hor its eHH H entry fHHHing typeHHH is missHHHSequenceH@.AH͘HuHPLgE1H5ϘHLzI IALeMuFzIALhMIIPt H`HLeMt6HEL9t!HX@t HxHHI9uH}LLeHEuEuLhMu&^H}|HEtH}mHLhMt:HpL9tEHX@t HxBHHI9uHhLp'HEtLJHLZE Lffff.UHAWAVAUATSHHHHEHHOH)HH9vFu=Tu3HVH9sNLu DH 3H H;MtG1H H H;MuHĈ[A\A]A^A_]ÿmGIHhdH5H H}LhFuW)PHDž`0GH`(h)PHts valueHHHy for itHHHype entrHHHissing tHHHMap is mH@'AHHuHPLE1H5̘HJLF IALeMuFzIALhMIIPt H`"FLeMt6HEL9t!HX@t HxEHI9uH}LLeEEuEuLhMu&^H}EEtH}ELhMt:HpL9tEHX@t HxEHI9uHhLpkEEtLELB LؐUHAWAVAUATSHHHҩHHEPH;Cu*HH H H;MuHĘ[A\A]A^A_]TEEIH`dH5썁H LHxL`0肊PH@HHHELHH@HULH_AHHxLLE1H5ʘH"LD IALeMuFzIAL`MIIHt HXCLeMt6HEL9t!HX@t HxCHI9uH}LLeCEuxu L`Mu)aH}CxtH}CL`Mt:HhL9tEHX@t HxXCHI9uH`Lh=CEtL`CLp@ LUHAWAVAUATSH(IHIHHHHEH8HХHHHLH@H8LYBLHEEL=MgLI@L8LdAL-ɦILHDž(HDž HDžHDžDž0I6HPHHDHHHLHH0HfPHHHLL8Lt H AH@H5˥HH/@H87AH HH;EuHH([A\A]A^A_]AHLL8Lt H .AH@H +HHHH5(HH?H8@HHH8}@HDUHAWAVAUATSHHEHHEHHGH)HH9v7 u.HH9sOHHH;Eu:HĈ[A\A]A^A_]THHH;Eu1HĈ[A\A]A^A_]@7@IHhdH5{H nH}Lh(?W)PHDž`0?H`(R)PH elementHH&Hor its eHH H entry fHHHing typeHHH is missHHHSequenceH@.AH͎HuHPLgE1H5ŘHLz? IALeMuFzIALhMIIPt H`>LeMt6HEL9t!HX@t Hx>HI9uH}LLe>EuEuLhMu&^H}|>EtH}m>LhMt:HpL9tEHX@t HxB>HI9uHhLp'>EtLJ>LZ; Lffff.UHAWAVAUATSHHHHEHHOH)HH9vFu=Tu3HVH9sNLu DH 3H H;Mt=1H H H;MuHĈ[A\A]A^A_]ÿm=IHhdH5H oH}LhFuW)PHDž`0=H`(h)PHts valueHHHy for itHHHype entrHHHissing tHHHMap is mH@'AHHuHPLE1H5˜HJL< IALeMuFzIALhMIIPt H`"<LeMt6HEL9t!HX@t Hx;HI9uH}LLe;EuEuLhMu&^H};EtH};LhMt:HpL9tEHX@t Hx;HI9uHhLpk;EtL;L8 LؐUHAWAVAUATSHHHҟHHE趁PH;Cu*HH H H;MuHĘ[A\A]A^A_]T;;IH`dH5상H HxL`0BPH@HHHELHH@HULH_AHHxLLE1H5H"L: IALeMuFzIAL`MIIHt HX9LeMt6HEL9t!HX@t Hx9HI9uH}LLe9Euxu L`Mu)aH}9xtH}9L`Mt:HhL9tEHX@t HxX9HI9uH`Lh=9EtL`9Lp6 LUHAWAVAUATSHIHHHEH8HݛHHHLH@H8Lf8HEEH"LkLH@H8Lx7L5ݜILHDž(HDž HDžHDžDž0LLaLH8Lt H 8L6H50HH6H87HHH;EuLH[A\A]A^A_] 8ILH8Lt H 7Lw6IH5HH 6H87LMIH86L6fDUHAWAVAUATSHHśHHEHHOH)HH9vFu=Tu3HVH9sNLu DH sH H;Mt#71H \H H;MuHĈ[A\A]A^A_]ÿ6IHhHdH5H <H}LhFW)PHDž`0P6H`({)PHts valueHHHy for itHHHype entrHHHissing tHHHMap is mH@'AHQHuHPLE1H5!HL5 IALeMuFzIALhMIIPt H`b5LeMt6HEL9t!HX@t Hx=5HI9uH}LLe#5EuEuLhMu&^H}5EtH}4LhMt:HpL9tEHX@t Hx4HI9uHhLp4EtL4L1 LؐUHAWAVAUATSHHHHHEpPH;Cu*HH H H;MuHĘ[A\A]A^A_]4B4IH`dH5,}H LHxL`0GBpPH@HHEHELHH@HULHAH醁HxLLE1H5HbL3 IALeMuFzIAL`MIIHt HX:3LeMt6HEL9t!HX@t Hx3HI9uH}LLe2Euxu L`Mu)aH}2xtH}2L`Mt:HhL9tEHX@t Hx2HI9uH`Lh}2EtL2L/ LUHAWAVAUATSPIM.IFL)HHHH9H +H9I^IM)HL<vL2ILL9Lff.HSHQHSHsHqHQHCHCHCH[HI9uM.IVIMfIFL9t'fff.HZBt Hzk1HI9uMt&LH[A\A]A^A_]H1M&MfIFMuH[A\A]A^A_]ÿ71HH5yH.HHHH5:HKH71IH1L. fDUHAWAVAUATSPIII +II_H)HHHHCL9)IOH)HHHTUUUUUUH9wHH9HBIHJH<@N0IH[IHLX.KDmMHSIIwH9tKDH~H{H~HNHKH{HFHFHFHvHH9uM7IGIIIWMGL9t"HX@t Hx/HI9uMtLH[A\A]A^A_]x/H[A\A]A^A_]E1E1L,HMtLF/H, fffff.UHAWAVAUATSHHHHEHHOH)HH9vFu=Tu3HVH9sNLu DH cH H;Mt/1H LH H;MuHĈ[A\A]A^A_]ÿ.IHh8dH5yH H}LhFW)PHDž`0@.H`(s)PHts valueHHHy for itHHHype entrHHHissing tHHHMap is mH@'AHA}HuHPLE1H5HzL- IALeMuFzIALhMIIPt H`R-LeMt6HEL9t!HX@t Hx--HI9uH}LLe-EuEuLhMu&^H},EtH},LhMt:HpL9tEHX@t Hx,HI9uHhLp,EtL,L) LؐUHAWAVAUATSHHHHHEfiPH;Cu*HH 搘H H;MuHĘ[A\A]A^A_],2,IH`dH5uH KHxL`07hPH@HH5HELHH@HULHAH~HxLLE1H5鱘HRL+ IALeMuFzIAL`MIIHt HX*+LeMt6HEL9t!HX@t Hx+HI9uH}LLe*Euxu L`Mu)aH}*xtH}*L`Mt:HhL9tEHX@t Hx*HI9uH`Lhm*EtL*L' LUHAWAVAUATSPIHL3HCL)HL9sjLH=upLcM)J<*IKDMMM~LLLIl+LL+L{HCMtLH[A\A]A^A_])H[A\A]A^A_]ÿ)HH5QrH"'H HHH5HЋH)IH)L& ff.UHAWAVAUATSHIIIuMeI)MIIGHH=HMuI)LHHH9waII9LBMLEHuI9vK(HH5oqH@&H+HHH5݋HH(LEHuIJ<(HHuLEN4IJN|M~HLI)LI]M}MuHtHH[A\A]A^A_](H[A\A]A^A_]E11Ld%IH#(L3% ff.UHAWAVAUATSHHHbHHEePH;Cu*HH FH H;MuHĘ[A\A]A^A_]''IH`-dH5|pH HxL`0ePH@HHzHELHH@HULHAH9zHxLLE1H5IHL&' IALeMuFzIAL`MIIHt HX&LeMt6HEL9t!HX@t Hxe&HI9uH}LLeK&Euxu L`Mu)aH}%&xtH}&L`Mt:HhL9tEHX@t Hx%HI9uH`Lh%EtL%L# LUHAWAVAUATSPIHL3HCL)HL9sjLH>upLcM)J<v%IKDMMM~LLLI&LL+L{HCMtLH[A\A]A^A_]%H[A\A]A^A_]ÿ%HH5mH"HmHHH5H0H%IH$L" ff.UHAWAVAUATSHIIIuMeI)MIIGHH> H?MuI)LHHH9w`II9LBMLEHuI9vK;$HH5lH!HHHH5>HOH;$LEHuIJ<#HHuLEN4ABN|M~HLI-%LI]M}MuHtHH[A\A]A^A_]}#H[A\A]A^A_]E11L IH#L  fff.UHAWAVAUATSHHŇHHEHHOH)HH9vFu=Tu3HVH9sNLu D H sH H;Mt##1H \H H;MuHĈ[A\A]A^A_]ÿ"IHhHdH5mH H}LhF赾W)PHDž`0P"H`(g)PHts valueHHHy for itHHHype entrHHHissing tHHHMap is mH@'AHQqHuHPLE1H5!HL! IALeMuFzIALhMIIPt H`b!LeMt6HEL9t!HX@t Hx=!HI9uH}LLe#!EuEuLhMu&^H}!EtH} LhMt:HpL9tEHX@t Hx HI9uHhLp EtL L LؐUHAWAVAUATSHHHHHE^PH;Cu*HH H H;MuHĘ[A\A]A^A_] B IH`dH5,iH HxL`0G^PH@HHEsHELHH@HULHAHrHxLLþE1H5HbL IALeMuFzIAL`MIIHt HX:LeMt6HEL9t!HX@t HxHI9uH}LLeEuxu L`Mu)aH}xtH}L`Mt:HhL9tEHX@t HxHI9uH`Lh}EtLL LUHAWAVAUATSPIHL3HCL)HL9sjLH=upLcM)J<&IKDMMM~LLLI|LL+L{HCMtLH[A\A]A^A_]H[A\A]A^A_]ÿHH5afH2HHHH5πHHIHL ff.UHAWAVAUATSHIIIuMeI)MIIGHH=HMuI)LHHH9waII9LBMLEHuI9vKHH5eHPH;HHH5H~HLEHuIJ<HHuLEN4IJN|M~HLILI]M}MuHtHH[A\A]A^A_],H[A\A]A^A_]E11LtIH3LC ff.UHAWAVAUATSHHuHHEHHOH)HH9vFu=Tu3HVH9sNLu DH #H H;Mt1H H H;MuHĈ[A\A]A^A_]ÿ]IHhdH5fH H}LhFeW)PHDž`0H`(X`)PHts valueHHHy for itHHHype entrHHHissing tHHHMap is mH@'AHjHuHPL蛹E1H5ѠH:L IALeMuFzIALhMIIPt H`LeMt6HEL9t!HX@t HxHI9uH}LLeEuEuLhMu&^H}EtH}LhMt:HpL9tEHX@t HxvHI9uHhLp[EtL~L LؐUHAWAVAUATSHHH}HHEfXPH;Cu*HH }H H;MuHĘ[A\A]A^A_]DIH`dH5aH |~HxL`0WPH@HHkHELHH@HULHOAHkHxLLsE1H5HL IALeMuFzIAL`MIIHt HXLeMt6HEL9t!HX@t HxHI9uH}LLeEuxu L`Mu)aH}xtH}sL`Mt:HhL9tEHX@t 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LLLLLLLLLLLLLLHI9uH516H[A^A_]1QLHHyHHVH`s 1HuyHzH)1fffff.3L30L0D3 L30D0 L00D3@L3PD0@L0PD3`L3pD0`L0pHHuHt.HHfff.D3 3D0 0H HuI9u1HH[A^A_]HHVDUHAWAVAUATSHH#HHEHHC0x u.HHCPH #H H;MuHĨ[A\A]A^A_]AタIHPldH5-H 4HhLPZH8.HEHD.HEH0H8.HEL8HuHUHMLI1AH-HhLLe]E1H5DH6Lx IALPMII8t HHLeMt6HEL9t!HX@t HxȽHI9uH}LLe讽Euhu LPMu,dH}舽htHxsLPMt:HXL9tEHX@t HxHHI9uHPLX-EtLPL` LUHAWAVAUATSHH!HHEHHC0x u.HHCPH s!H H;MuHĨ[A\A]A^A_]迼IHPZjdH5+H 2HhLPXH,HEH,HEH0H,HEL8HuHUHMLIAH+HhLL5[E1H5kBH3LH IALPMII8t HH轻LeMt6HEL9t!HX@t Hx蘻HI9uH}LLe~Euhu LPMu,dH}XhtHxCLPMt:HXL9tEHX@t HxHI9uHPLXEtL L0 LUHAWAVSPIILHH75PIvIV H)HHLMjHHILU=WILMIrJ H9J H91IVH)LHt#Hfff.;8HHHHuHBI)11ff.44ttttt t ttttttttHI9uH5/H[A^A_] QLHHyHHVHs 1HuqHzH)1fDLLD L0D L0D@LPD@LPD`LpD`LpH HuHt.H4HD3 3D0 0H HuI9u1HH[A^A_]HHdUHAWAVAUATSHH5HHEHHC0xu.HHCPH H H;MuHĨ[A\A]A^A_]豸_IHPedH5*'H .HhLPdTH'HEH'HEH0H'HEL8HuHUHMLIAH<'HhLLVE1H5 >Ht/L跀 IALPMII8t HH]LeMt6HEL9t!HX@t Hx8HI9uH}LLeEuhu LPMu,dH}htHx㶀LPMt:HXL9tEHX@t Hx踶HI9uHPLX蝶EtLLг LUHAWAVSPIILHHW4PIvIV H)HHLeHHIL8WILMIrJ H9J H91D)IVH)Ht#Hf.H;H8HHHHuHPI)11fH4H4HtHtHtHtHtHtHt Ht Ht(Ht(Ht0Ht0Ht8Ht8HI9uH5)+H[A^A_])QLHHyHHVH s 1HuqHzH)1fDLLD L0D L0D@LPD@LPD`LpD`LpHHuHt.H4HD3 3D0 0H HuI9u1HH[A^A_]HHTUHAWAVAUATSHHHHEHHC0x u.HHCPH H H;MuHĨ[A\A]A^A_]AﳀIHPadH5"H V*HhLPOH8#HEHD#HEH0H8#HEL8HuHUHMLI1AH"HhLLeRE1H59H+Lx IALPMII8t HHLeMt6HEL9t!HX@t HxȲHI9uH}LLe讲Euhu LPMu,dH}舲htHxsLPMt:HXL9tEHX@t HxHHI9uHPLX-EtLPL` LUHAWAVAUATSPIILtIMtvG-PIwIW H)HHL}aIMu=IL4WIL^HE1MtHH[LMmɯIuLH[A\A]A^A_]H5['H[A\A]A^A_]WQUHAWAVSPIIL(HHw0PIvIV H)HHL`HHIL3WIL MIrJ sH9J pH91IVH)LHt%Hfff.;f8HHHHuHPI)11f4Sf4PtSftPtSftPtSftPtSftPtS ftP -tS ftP tSftPHI9uH5[H[A^A_]1QLHHyHHVH0s 1HuqHzH)1fDsLspLpDs Ls0Dp Lp0Ds@LsPDp@LpPDs`LspDp`LppH@HuHt.Ht6Hff.D3 3D0 0H HuI9u1HH[A^A_]HHHKTUHAWAVAUATSHHU\HHEHHC0x -u.HHCPH 3\H H;MuHĨ[A\A]A^A_]IHPJdH5jSH 9[HhLPJHSHEHSHEH0HSHEL8HuHUHMLIAH|SHhLL5ME1H5+}H%L( IALPMII8t HHLeMt6HEL9t!HX@t HxxHI9uH}LLe^Euhu LPMu,dH}8htHx#LPMt:HXL9tEHX@t HxHI9uHPLXEtLL LUHAWAVAUATSHH%ZHHEHHC0x -u.HHCPH ZH H;MuHĨ[A\A]A^A_]oIHPdH5:QH QYHhLPHHQHEHQHEH0HQHEL8HuHUHMLIAHLQHhLLKE1H5zH#L IALPMII8t HHmLeMt6HEL9t!HX@t HxHHI9uH}LLe.Euhu LPMu,dH}htHxLPMt:HXL9tEHX@t HxHI9uHPLXEtLL݀ LUHAWAVSPIIL(HH[PIvIV H)HHLZHHILcWIL +tS ftP tSftPHI9uH5%H[A^A_]PLHHyHHVH0s 1HuqHzH)1fDsLspLpDs Ls0Dp Lp0Ds@LsPDp@LpPDs`LspDp`LppH@HuHt.Ht6Hff.D3 3D0 0H HuI9u1HH[A^A_]HHHKTUHAWAVAUATSHHHHEHHC0x +u.HHCPH sH H;MuHĨ[A\A]A^A_]迮IHPZ\dH5H Y%HhLPJHHEHHEH0HHEL8HuHUHMLIAHHhLL5ME1H5k4H%LH IALPMII8t HH轭LeMt6HEL9t!HX@t Hx蘭HI9uH}LLe~Euhu LPMu,dH}XhtHxCLPMt:HXL9tEHX@t HxHI9uHPLXEtL L0 LUHAWAVAUATSHHeHHEHHC0x +u.HHCPH CH H;MuHĨ[A\A]A^A_]ᬀ菬IHP*ZdH5ZH q#HhLPHHHEHHEH0HHEL8HuHUHMLIAHlHhLLKE1H5;2H#L IALPMII8t HH荫LeMt6HEL9t!HX@t HxhHI9uH}LLeNEuhu LPMu,dH}(htHxLPMt:HXL9tEHX@t Hx誀HI9uHPLXͪEtLL LUHAWAVSPIIL(HHG*PIvIV H)HHLZHHIL%-WIL MIrJ sH9J pH91IVH)LHt%Hfff.;f8HHHHuHPI)11f4Sf4PtSftPtSftPtSftPtSftPtS ftP -tS ftP tSftPHI9uH59UH[A^A_] +QLHHyHHVH0s 1HuqHzH)1fDsLspLpDs Ls0Dp Lp0Ds@LsPDp@LpPDs`LspDp`LppH@HuHt.Ht6Hff.D3 3D0 0H HuI9u1HH[A^A_]HHHKTUHAWAVAUATSHHUHHEHHC0xu.HHCPH UH H;MuHĨ[A\A]A^A_]Qހ݀IHP誋dH5LH $UHhLP$DHHMHEHTMHEH0HHMHEL8HuHUHMLIaAHLHhLLFE1H5vH4L݀ IALPMII8t HH܀LeMt6HEL9t!HX@t Hx܀HI9uH}LLe܀Euhu LPMu,dH}܀htHx܀LPMt:HXL9tEHX@t HxX܀HI9uHPLX=܀EtL`܀Lpـ LUHAWAVAUATSHHSHHEHHC0xu.HHCPH cSH H;MuHĨ[A\A]A^A_]!܀ۀIHPzdH5JH ;SHhLPAHKHEH$KHEH0HKHEL8HuHUHMLI1AHJHhLLeDE1H5[tHLXۀ IALPMII8t HHڀLeMt6HEL9t!HX@t HxڀHI9uH}LLeڀEuhu LPMu,dH}hڀhtHxSڀLPMt:HXL9tEHX@t Hx(ڀHI9uHPLX ڀEtL0ڀL@׀ LUHAWAVSPIIL(HHgQPIvIV H)HHL}SHHILu\WIL -MI rJ 3H9J 0H91I~H)LHt"Hfff.HHHHuHSI)11fff.  LLLLLLLLLLLLLLHI9uH5NH[A^A_]q$QLHHyHHVH`s 1HuyHzH)1fffff.3L30L0D3 L30D0 L00D3@L3PD0@L0PD3`L3pD0`L0pHHuHt.HHfff.D3 3D0 0H HuI9u1HH[A^A_]HHVDUHAWAVAUATSHHOHHEHHC0xu.HHCPH NH H;MuHĨ[A\A]A^A_]׀_׀IHP -dH5*FH OHhLP=HFHEHFHEH0HFHEL8HuHUHMLIAH<FHhLL?E1H5oHLր IALPMII8t HH]րLeMt6HEL9t!HX@t Hx8րHI9uH}LLeրEuhu LPMu,dH}ՀhtHxՀLPMt:HXL9tEHX@t HxՀHI9uHPLXՀEtLՀLҀ LUHAWAVAUATSHHLHHEHHC0xu.HHCPH LH H;MuHĨ[A\A]A^A_]Հ/ՀIHPڂdH5CH MHhLPT;HxDHEHDHEH0HxDHEL8HuHUHMLIAH DHhLL=E1H5mHdLԀ IALPMII8t HH-ԀLeMt6HEL9t!HX@t HxԀHI9uH}LLeӀEuhu LPMu,dH}ӀhtHxӀLPMt:HXL9tEHX@t HxӀHI9uHPLXmӀEtLӀLЀ LUHAWAVSPIIL(HH7KPIvIV H)HHLLHHILUWIL -MI rJ 3H9J 0H91I~H)LHt"Hfff.HHHHuHSI)11fff.  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LLLLLLLLLLLLLLHI9uH5!H[A^A_]!PLHHyHHVH`s 1HuyHzH)1fffff.3L30L0D3 L30D0 L00D3@L3PD0@L0PD3`L3pD0`L0pHHuHt.HHfff.D3 3D0 0H HuI9u1HH[A^A_]HHVDUHAWAVAUATSHHHHEHHC0xu.HHCPH H H;MuHĨ[A\A]A^A_]1ߚIHPzHdH5 H HhLP6H( +HEH4 +HEH0H( +HEL8HuHUHMLI!AH HhLLU9E1H5 HLh IALPMII8t HHݙLeMt6HEL9t!HX@t Hx踙HI9uH}LLe螙Euhu LPMu,dH}xhtHxcLPMt:HXL9tEHX@t Hx8HI9uHPLXEtL@LP LUHAWAVAUATSHHHHEHHC0xu.HHCPH cH H;MuHĨ[A\A]A^A_]诘IHPJFdH5zH HhLP4HHEHHEH0HHEL8HuHUHMLIAHHhLL%7E1H5[HL8 IALPMII8t HH譗LeMt6HEL9t!HX@t Hx舗HI9uH}LLenEuhu LPMu,dH}HhtHx3LPMt:HXL9tEHX@t HxHI9uHPLX햀EtLL  LUHAWAVSPIIL(HHPIvIV H)HHL=FHHILEWIL MIrJ sH9J pH91IVH)LHt%Hfff.;f8HHHHuHPI)11f4Sf4PtSftPtSftPtSftPtSftPtS ftP -tS ftP tSftPHI9uH5YAH[A^A_])QLHHyHHVH0s 1HuqHzH)1fDsLspLpDs Ls0Dp Lp0Ds@LsPDp@LpPDs`LspDp`LppH@HuHt.Ht6Hff.D3 3D0 0H HuI9u1HH[A^A_]HHHKTUHAWAVAUATSHHAHHEHHC0xu.HHCPH AH H;MuHĨ[A\A]A^A_]qʀʀIHPwdH58H BHhLPD0Hh9HEHt9HEH0Hh9HEL8HuHUHMLI聻AH8HhLL2E1H5bHT Lɀ IALPMII8t HHɀLeMt6HEL9t!HX@t HxȀHI9uH}LLeȀEuhu LPMu,dH}ȀhtHxȀLPMt:HXL9tEHX@t HxxȀHI9uHPLX]ȀEtLȀLŀ LUHAWAVAUATSHH?HHEHHC0xu.HHCPH ?H H;MuHĨ[A\A]A^A_]AȀǀIHPudH56H @HhLP.H87HEHD7HEH0H87HEL8HuHUHMLIQAH6HhLL0E1H5{`H$ Lxǀ IALPMII8t HHƀLeMt6HEL9t!HX@t HxƀHI9uH}LLeƀEuhu LPMu,dH}ƀhtHxsƀLPMt:HXL9tEHX@t HxHƀHI9uHPLX-ƀEtLPƀL`À LUHAWAVSPIIL(HHg>PIvIV H)HHL?HHILHWIL +tS ftP tSftPHI9uH5y H[A^A_]yPLHHyHHVH0s 1HuqHzH)1fDsLspLpDs Ls0Dp Lp0Ds@LsPDp@LpPDs`LspDp`LppH@HuHt.Ht6Hff.D3 3D0 0H HuI9u1HH[A^A_]HHHKTUHAWAVAUATSHHHHEHHC0xu.HHCPH H H;MuHĨ[A\A]A^A_]葔?IHPAdH5 +H HhLPD0HHEHHEH0HHEL8HuHUHMLI聻AHHhLL2E1H5HT Lȓ IALPMII8t HH=LeMt6HEL9t!HX@t HxHI9uH}LLeEuhu LPMu,dH}ؒhtHxÒLPMt:HXL9tEHX@t Hx蘒HI9uHPLX}EtL蠒L谏 LUHAWAVAUATSHHHHEHHC0xu.HHCPH H H;MuHĨ[A\A]A^A_]aIHP?dH5H +HhLP.HXHEHdHEH0HXHEL8HuHUHMLIQAHHhLL0E1H5H$ L蘑 IALPMII8t HH LeMt6HEL9t!HX@t Hx萀HI9uH}LLeΐEuhu LPMu,dH}訐htHx蓐LPMt:HXL9tEHX@t HxhHI9uHPLXMEtLpL耍 LUHAWAVSPIIL(HH PIvIV H)HHL?HHILWIL MIrJ sH9J pH91IVH)LHt%Hfff.;f8HHHHuHPI)11f4Sf4PtSftPtSftPtSftPtSftPtS ftP -tS ftP tSftPHI9uH5:H[A^A_]QLHHyHHVH0s 1HuqHzH)1fDsLspLpDs Ls0Dp Lp0Ds@LsPDp@LpPDs`LspDp`LppH@HuHt.Ht6Hff.D3 3D0 0H HuI9u1HH[A^A_]HHHKTUHAWAVAUATSHH5;HHEHHC0xu.HHCPH ;H H;MuHĨ[A\A]A^A_]ÀÀIHP*qdH5J2H <HhLP)H2HEH2HEH0H2HEL8HuHUHMLIAH\2HhLL,E1H5 \HLÀ IALPMII8t HH}€LeMt6HEL9t!HX@t HxX€HI9uH}LLe>€Euhu LPMu,dH}€htHx€LPMt:HXL9tEHX@t HxHI9uHPLXEtLL LUHAWAVAUATSHH9HHEHHC0xu.HHCPH 8H H;MuHĨ[A\A]A^A_]OIHPndH50H :HhLPt'H0HEH0HEH0H0HEL8HuHUHMLI豲AH,0HhLL)E1H5YHL IALPMII8t HHMLeMt6HEL9t!HX@t Hx(HI9uH}LLeEuhu LPMu,dH}迀htHxӿLPMt:HXL9tEHX@t Hx訿HI9uHPLX荿EtL谿L LUHAWAVSPIILHH'5PIvIV H)HHL8HHILAWILMIrJ H9J H91IVH)LHt#Hfff.;8HHHHuHBI)11ff.44ttttt t ttttttttHI9uH5)4H[A^A_] QLHHyHHVHs 1HuqHzH)1fDLLD L0D L0D@LPD@LPD`LpD`LpH HuHt.H4HD3 3D0 0H HuI9u1HH[A^A_]HHdUHAWAVAUATSHH4HHEHHC0xu.HHCPH 4H H;MuHĨ[A\A]A^A_]A＀IHPjdH5+H o6HhLP#H8,HEHD,HEH0H8,HEL8HuHUHMLIQAH+HhLL%E1H5{UH$Lx IALPMII8t HHLeMt6HEL9t!HX@t HxȻHI9uH}LLe讻Euhu LPMu,dH}舻htHxsLPMt:HXL9tEHX@t HxHHI9uHPLX-EtLPL` LUHAWAVAUATSHHu2HHEHHC0xu.HHCPH S2H H;MuHĨ[A\A]A^A_]迺IHPjhdH5)H t4HhLP H*HEH*HEH0H*HEL8HuHUHMLI!AH)HhLLU#E1H5KSHLH IALPMII8t HH轹LeMt6HEL9t!HX@t Hx蘹HI9uH}LLe~Euhu LPMu,dH}XhtHxCLPMt:HXL9tEHX@t HxHI9uHPLXEtL L0 LUHAWAVSPIILHH2PIvIV H)HHLm2HHILe;WILMIrJ H9J H91IVH)LHt#Hfff.;8HHHHuHBI)11ff.44ttttt t ttttttttHI9uH5-H[A^A_]iQLHHyHHVHs 1HuqHzH)1fDLLD L0D L0D@LPD@LPD`LpD`LpH HuHt.H4HD3 3D0 0H HuI9u1HH[A^A_]HHdUHAWAVAUATSHH.HHEHHC0x u.HHCPH -H H;MuHĨ[A\A]A^A_]豶_IHP -ddH5*%H D0HhLPH%HEH%HEH0H%HEL8HuHUHMLIAH<%HhLLE1H5NHL赀 IALPMII8t HH]LeMt6HEL9t!HX@t Hx8HI9uH}LLeEuhu LPMu,dH}htHx㴀LPMt:HXL9tEHX@t Hx踴HI9uHPLX蝴EtLLб LUHAWAVAUATSHH+HHEHHC0x u.HHCPH +H H;MuHĨ[A\A]A^A_]聴/IHPadH5"H R.HhLPTHx#HEH#HEH0Hx#HEL8HuHUHMLI葥AH #HhLLE1H5LHdL踳 IALPMII8t HH-LeMt6HEL9t!HX@t HxHI9uH}LLeEuhu LPMu,dH}ȲhtHx賲LPMt:HXL9tEHX@t Hx舲HI9uHPLXmEtL萲L蠯 LUHAWAVSPIILHH+PIvIV H)HHL+HHIL4WILMIrJ H9J H91D)IVH)Ht#Hf.H;H8HHHHuHPI)11fH4H4HtHtHtHtHtHtHt Ht Ht(Ht(Ht0Ht0Ht8Ht8HI9uH5&H[A^A_]PLHHyHHVH s 1HuqHzH)1fDLLD L0D L0D@LPD@LPD`LpD`LpHHuHt.H4HD3 3D0 0H HuI9u1HH[A^A_]HHTUHAWAVAUATSHHu'HHEHHC0xu.HHCPH S'H H;MuHĨ[A\A]A^A_]迯IHPj]dH5H *HhLPHHEHHEH0HHEL8HuHUHMLI!AHHhLLUE1H5KHHLH IALPMII8t HH轮LeMt6HEL9t!HX@t Hx蘮HI9uH}LLe~Euhu LPMu,dH}XhtHxCLPMt:HXL9tEHX@t HxHI9uHPLXEtL L0 LUHAWAVSPIIL(HHg(PIvIV H)HHLm'HHILe0WIL -MIrJ H9J H91D)IVH)Ht#Hf.H;H8HHHHuHPI)11fH4H4HtHtHtHtHtHtHt Ht Ht(Ht(Ht0Ht0Ht8Ht8HI9uH5"H[A^A_]YPLHHyHHVH s 1HuqHzH)1fDLLD L0D L0D@LPD@LPD`LpD`LpHHuHt.H4HD3 3D0 0H HuI9u1HH[A^A_]HHTUHAWAVAUATSHH#HHEHHC0x u.HHCPH "H H;MuHĨ[A\A]A^A_]衫OIHPXdH5H %HhLPtHHEHHEH0HHEL8HuHUHMLI豜AH,HhLLE1H5CHLت IALPMII8t HHMLeMt6HEL9t!HX@t Hx(HI9uH}LLeEuhu LPMu,dH}詀htHxөLPMt:HXL9tEHX@t Hx訩HI9uHPLX荩EtL谩L LUHAWAVAUATSHH HHEHHC0x u.HHCPH H H;MuHĨ[A\A]A^A_]qIHPVdH5H #HhLPDHhHEHtHEH0HhHEL8HuHUHMLI聚AHHhLLE1H5AHTL訨 IALPMII8t HHLeMt6HEL9t!HX@t HxHI9uH}LLeާEuhu LPMu,dH}踧htHx裧LPMt:HXL9tEHX@t HxxHI9uHPLX]EtL耧L萤 LUHAVSH@I։HHHE0"HE()EH input: HH&Hin the iHH Hnt type HHHor elemeHHHted tensHHHUnsupporH@.H}cEt -HuHU HuH}rEt H}sEHuHEu.PIEt H}JHHH;Eu H@[A^]茦HEuEu$H] H} -Et HEtH}H0 UHAWAVAUATSHHHBHHEHHPhHHt'H#HH;EuHĈ[A\A]A^A_]᥀菥IHh:SdH5^H H}Lh W)PHDž`@2H`( -)PHive typeHH(Hy primitHH Htain onlHHHmust conHHHequence HHHTensor sHf@0sAH6 HuHPL E1H5=H|LФ IALeMuFzIALhMIIPt H`4LeMt6HEL9t!HX@t HxHI9uH}LLeEuEuLhMu&^H}ңEtH}ãLhMt:HpL9tEHX@t Hx蘣HI9uHhLp}EtL蠣L谠 LUHAWAVAUATSPIM7IGL)HHHH9 H -H9MoLL)HL$vLIILLM9tsfff.IUIuHqHqI}HyI]HYHt+HwIuIuIEIEHII9uHqHII9uM/MwIMGIGM9t/LL)Iffffff.IvLhIHuMtLH[A\A]A^A_]H[A\A]A^A_]ÿHH5H肟HMHHH5HHIHL ff.UHAWAVAUATSHIH -HLoMI)IHLIFH9HOH)HHHTUUUUUUH9H}wHH9HBHHHuHH<@#K vLtHDHDL4HEL<LL!HHI9tvHffff.IT$ LLH_IL$HtHHHu$ID$L9 tIfI $HAH9LauIH9uHMHLiHMHEH@HULMOI9tvffff.IUIuIwIwI}IIEIGHt+HwIEIEIEIEIIH9uIwIIH9uL1LiML9LILAM9t*LL)If.IuLfIHuMtLH[A\A]A^A_]}H[A\A]A^A_]1HE1JœHI6LeH}Ht@H耜 UHAWAVAUATSPIM7IGL)HHHH9 H -H9MoLL)HL$vLמIILLM9tsfff.IUIuHqHqI}HyI]HYHt+HwIuIuIEIEHII9uHqHII9uM/MwIMGIGM9t/LL)Iffffff.IvLdIHuMtLH[A\A]A^A_]흀H[A\A]A^A_]ÿ은HH5HRHHHH5HH은IHÝLӚ ff.UHAWAVAUATSH8H -L'LwLL)HHHLCI9vHOL)HHHTUUUUUUH9H}wHL9IBHH1HEHH<@ILHH[HTHDHDHL,L>HI9HMHDHE1HHUHuI H9H]u$@IMHII H9H]HIHtf.IIFHufLLpI9tHI9F |^HILeIN H9}" IIN H9}IMHu@H9}'MfINHufIHtXMfI<$tmIOHIGL98Iffffff.IHAH9Lyuff.III<$uII MfDH0MH HSHP(HH H@HLpI$IMH HtIMI$H]H;H_HCHuHUIOH1HHHuH9LHEL LpHMHEH@HIMM9tuIVIvIuIuI~I}I^I]Ht+HwIvIvIFIFIII9uIuIII9uHUL:LrMHUL*HJHBM9t"LL)IfIvL`IHuMtLH8[A\A]A^A_]ݙH8[A\A]A^A_]1HE1"ILHuo`H}Ht蟙Lߖ UHAWAVAUATSHMHMAHIIEIEIEHۛIIH]L}IsDAEM}Mu.;DMIILIM}IMeAMuLHuLiC7EeMe IE0IE(IE H}CIIsyIsDA$Mt$Mu(5LHHH芘IMu0HI] M}(LHuL♀C>I}8HulH[A\A]A^A_]L襕L蝕 HAEt+HA$uAEuHL I}0AEtI}闀H) UHAWAVATSIIIGIGII~I+>tlHHHHH -H9sQ萗HII?H[HIGIMvL9t!@H肕HIHII9u[A\A^A_]L薔 IM'Mu JIM'Mt?IGL9t@ffffff.HX@t Hx떀HI9uI?MgזL Lf.UHAWAVAUATSHhIIIIHHHEH+6IEI}H衔AGAE I}(Iw H腔I}@Iw8HxgIEpHIDžIExIEpIEhIE`IEXH8H HHHHH@H8HtHEEH HHHHH@HH8HxH HHHHDž(HDž HDžHDžDž0HLqtHH HH_t H蔀MtEH5zH-HLNHLHH5K HH55HA $It$IEt$IET$HH5HIG8I;G@H5H IG8Mg@HL9tXLL5HXHpHDHEPL:LL*HHL9uHLL HufIIEx1H葑HHCHHHKHHHHH8HHt H LH5 -HH藑H8蟒Hh -HH;EuHh[A\A]A^A_]&HIHHIt|H萒nHIbHIHIIHW[IHTXIPIHLHHHHH8Ht H ڑL辐H5HHYH8aMuXt I蚑M&Mt@IE`L9t+ff.HX@t HxkHI9uI>LMe`RLxM4$Mt<IEHL9toff.HX@t HxHI9uI<$MuHHt I}8Ht I}ܐLL LUHAWAVAUATSHHAHHHHHEL8HSHHHLH@H8LLHEEL=IGHHI@L8LHIHHHHDž(HDž HDžHDžDž0EFHH㍀tHH HHH59 HsHH5 -HK Hs!HEs0HES(Ht HHHLJHHL8HHt H ЎL贍H5HHOL[H$HH;EHHH[A\A]A^A_]ÊuVHKDMtTHNl!L5 -f.AuL趏Hu$IIuL81'LcHKMu1H+LL8HHHIL!3LMIeLIH5HHGHSLኀ LIH;LɊ LMIt HaHHL8HHt H )H H5$HH訋L贌LB f.UHSPHbHH[]Ҍ@UHGpu HpHH]HH]fffff.UHAWAVAUATSH8IIHHHHEH}H}HH@L$H|(DluJH}H}L賉H5H}蝉H HQ8EH}{EA$H}MAA LIDDLLMHuHH@H<t XH}AH$HH;Eu_HH8[A\A]A^A_]IH}IH}IL肋HHHx銀tHHH;Et蕋HWHm H-ffff.UHAWAVAUATSHHMIIHoHHEMDMLH)IL$E1H)LOHUHH)H~IELHP`H9MLeW)EHEIsDEH]I'I^HHhILeHH]LuH]uLLȋC4EtH]IELHLP`HLeEt H}L9u<HuI)M~IELLP`L9uID$HPHH;Et E1H8HH;EuLHH[A\A]A^A_]HEt H}艉HɆ UHAWAVSPIH )IAFpt ITM~XMt:IF`L9t%@HX@t Hx+HI9uI~XLM~`M~@Mt7IFHL9t"HX@t Hx눀HI9uI~@LM~HшAF(t I~8AFt I~豈LH[A^A_]鍈UHAWAVATSII~0Ht I~8~M~MI^ L9twf.HsHCHtH{HtHPLcHMtHID$HtI9u fI$LPLI9uI~LM~ 净Au [A\A^A_]I~[A\A^A_]ŇHffffff.UHAWAVSPIIHt8L;C(t H{8|Ct H{ mHeLMuIIdžHtAAF`u&AFHu/AF0u8AFuAAuJH[A^A_]I~p AFHtI~XAF0tI~@놀AFtI~(ۆAtI~H[A^A_]†@UHAWAVAUATSPIF`u$IFIFI:HF0LfXI9sHFXIH^(IFIFIMI)IIDALHL9I rL9J (H9II)1 A HI9uH^Lf IFIFIMI)IIDALHL9NI rL9J (H9II)1 A HI9u M}ILUIFIM>MnL9M}IL(IFIM>MnL9kMIIxHHVH`sB1HMIIxHHVH`1H#LHzH)13L30L0D3 L30D0 L00D3@L3PD0@L0PD3`L3pD0`L0pHHuHt.HHfff.D3 3D0 0H HuM9LIHzH)13L30L0D3 L30D0 L00D3@L3PD0@L0PD3`L3pD0`L0pHHuHt.HHfff.D3 3D0 0H HuM9uLLH[A\A]A^A_]LIL蕀DUHAWAVAUATSHHHHHHEHGHGHGHC G HsH}L{MHEH@HEAGMgIw IDIEWH}yHHMLIMHuL}MqM`HL9r 1HIHHHH]HHQAGMGMg MMH}HCH9tL9r1IHH9KHtHSL9ueu11ffffff.T A: uDHH9uH{ LLMMML}MH}HuqHHUsHCH9tL9r1IHH9uUCtHCH0HHu6fDHuLH!HHHf.H}MϿ@ـILuIvI]H~MI(Iv(L~HEIEIEH}HGHxH*HHH H*XLHHH HL}x1H*O t5Y.w,H]HHHH*XO uH 6HrHV1H^f: +tS ftP tSftPHI9uH5H[A^A_]PLHHyHHVH0s 1HuqHzH)1fDsLspLpDs Ls0Dp Lp0Ds@LsPDp@LpPDs`LspDp`LppH@HuHt.Ht6Hff.D3 3D0 0H HuI9u1HH[A^A_]HHHKTUHAWAVAUATSHHuHHEHHC0xu.HHCPH SH H;MuHĨ[A\A]A^A_]蟍IHP:;dH5jH HhLP)HHEHHEH0HHEL8HuHUHMLIAH|HhLL,E1H5KHL( IALPMII8t HH蝌LeMt6HEL9t!HX@t HxxHI9uH}LLe^Euhu LPMu,dH}8htHx#LPMt:HXL9tEHX@t HxHI9uHPLX݋EtLL LUHAWAVAUATSHHEHHEHHC0xu.HHCPH #H H;MuHĨ[A\A]A^A_]oIHP +9dH5:H HhLPt'HHEHHEH0HHEL8HuHUHMLI豲AHLHhLL)E1H5HL IALPMII8t HHmLeMt6HEL9t!HX@t HxHHI9uH}LLe.Euhu LPMu,dH}htHxLPMt:HXL9tEHX@t HxȉHI9uHPLX證EtLЉL LUHAWAVSPIILHHwPIvIV H)HHL8HHIL WILMIrJ H9J H91IVH)LHt#Hfff.;8HHHHuHBI)11ff.44ttttt t ttttttttHI9uH5IH[A^A_]IPLHHyHHVHs 1HuqHzH)1fDLLD L0D L0D@LPD@LPD`LpD`LpH HuHt.H4HD3 3D0 0H HuI9u1HH[A^A_]HHdUHAWAVAUATSHHHHEHHC0xu.HHCPH H H;MuHĨ[A\A]A^A_]aIHP4dH5H HhLP#HXHEHdHEH0HXHEL8HuHUHMLIQAHHhLL%E1H5 H$L蘆 IALPMII8t HH LeMt6HEL9t!HX@t Hx腀HI9uH}LLe΅Euhu LPMu,dH}訅htHx蓅LPMt:HXL9tEHX@t HxhHI9uHPLXMEtLpL耂 LUHAWAVAUATSHHHHEHHC0xu.HHCPH H H;MuHĨ[A\A]A^A_]1߄IHPz2dH5H HhLP H(HEH4HEH0H(HEL8HuHUHMLI!AHHhLLU#E1H5 +HLh IALPMII8t HH݃LeMt6HEL9t!HX@t Hx踃HI9uH}LLe螃Euhu LPMu,dH}xhtHxcLPMt:HXL9tEHX@t Hx8HI9uHPLXEtL@LP LUHAWAVSPIILHHGPIvIV H)HHLm2HHILuWILMIrJ H9J H91IVH)LHt#Hfff.;8HHHHuHBI)11ff.44ttttt t ttttttttHI9uH5H[A^A_]PLHHyHHVHs 1HuqHzH)1fDLLD L0D L0D@LPD@LPD`LpD`LpH HuHt.H4HD3 3D0 0H 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HMH?HUHuHuHXHHCHC0HKHSHC@H`Ht HhGqH}Ht H}5qLuHEMtLELqHYHH;EuHHĈ[A\A]A^A_]JqIH`Hu$H}Hu>H]HEHu]Lq HhqH}Ht IH}HtH}qH]HEHtIH]HEHtHEHTqLq fff.UHAWAVATSH@HIHXHHEH]1H&FIľH&FIǾH$FHEIL$IT$ H)HtHH9IOIW H)HtHH9Ht%HHHP H)HtHH9ID$0@EHuHULMLLM`HWHH;EIHrHEH]HuHL59.LHTpIHrHEH]HuHL8.LH觯T7HH rHMH]HuHH8.LHnTEt H}}qHVHH;EuLH@[A\A^A_]qHEuHEu HEt H}0qHpq UHHH ԉHHxH@Ht]q]fDUHSPHHԉHH{HCHtqHH[]qfUHAVSIqHH2ԉHH{LDH҉HH[A^]IHdqLq fff.UHAVSIFqHHӉHH{L蓷DHl҉HH[A^]IHqLDq fff.UHAWAVAUATSHHMMIHIHIUHHEЋEHEHEH}HuH}HuHLMM'H}HuHLMMH}HuHLMMuH}HuHLMMH}uuHUH} H]Htc qIHILHHH qH]M>HEHt8Ct H{qHqHDTHH;Et!1IHEH#THH;EuLHH[A\A]A^A_]qILvqH]HEHu 5IH]HEHtCt H{6qH.qLnq fDUHAVSHIHSHHEA>uuHM H}HEHEI^IFHtACt H{qHqH]HEHt!Ct H{qHqHEIFHSHH;Eu 1H[A^]qfUHAVSHIHRHHEA>uuHM H}HEHEI^IFHtACt H{qHqH]HEHt!Ct H{qHqHEIFHBRHH;Eu 1H[A^]qfUHAVSHIH RHHEA>uuHM H}/HEHEI^IFHtACt H{EqH=qH]HEHt!Ct H{qHqHEIFHQHH;Eu 1H[A^]GqfUHAVSHIHKQHHEA> uuHM H} HEHEI^IFHtACt H{qH}qH]HEHt!Ct H{]qHUqHEIFHPHH;Eu 1H[A^]qfUHAVSHIHPHHEA>uuHM H} HEHEI^IFHtACt H{qHqH]HEHt!Ct 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fA(fA(fY%[fAYfD\fD\fA(fYfD(fEYfEXfDYfDXfEYf(fAYfAXfYfXfYfAfXfA\fD^fEXfDXfrffpcfAYf_fA HH9fZ f\([f]D([fD_fA(fY[fXD: fA(fA(fY%[fAYfD\fD\fA(fYfD(fEYfEXfDYfDXfEYf(fAYfAXfYfXfYfAfXfA\fD^fEXfDXfrffpcfAYf_fA HH9LH)fHnHfELL`HxHHMHIHHPHLXLhLpHUMdILMtLjI)E1f)MCZDf\f)Eزqf)E(EDzq(MCLCZf\Ef)E覲qf)E(E蕲q(Uf(MCIIuE1H}LXLhLpt7IK/AZf\f)E?qf)E(E.q(MC HEH9xL`t4HO4ff.AZ\EqAHI9uHĈ[A\A]A^A_]fff.UHAWAVAUATSHHXH^HHEп(跰qHþ H議qHHCHCXHC`HCXHCHHC@HC8HC0HC(HC HCPHCpHCxHCpHChƃHǃfǃHǃHǃƃHHǃHǃHǃHǃHǃHǃHǃHǃHǃHHHǃHǃHǃǃǃHǃ H]@Ix@I@I@H@IW)EHE(qHEHH(HML8L`LhHXLp HMY@IQ@I @I@Iy@HW)`HDžp(葮qH`HH(HpL8L`LhLpHX HhH5hqH}HUH`CH5rH.CH5qH_CHAH5MqH膴CHH;KCHHH *ӉHMH/HUHuHuHXHHCHC0HKHSHC@H`Ht Hh藭qH}Ht H}腭qLuHEMtLELdqHHH;EuHHĈ[A\A]A^A_]蚭qIH`Hu$H}Hu>H]HEHu]LQq HhqH}Ht IH}HtH}۬qH]HEHtIH]HEHtHNEH褬qLq fff.UHAWAVAUATSHHXHHHEп(gqHþ H]qHHCHCXHC`HCXHCHHC@HC8HC0HC(HC HCPHCpHCxHCpHChƃHǃfǃHǃHǃƃHHǃHǃHǃHǃHǃHǃHǃHǃHǃHHHǃHǃHǃǃǃHǃ H]0@I(@I@IX@HP@IW)EHE(讪qHEHH(HML8L`LhHXLp HM @I@I@I@I)@HW)`HDžp(AqH`HH(HpL8L`LhLpHX HhH5qH}HUH`ͳCH5rHޭCH5uHCHA H5qH6CHH;CHHH ΉHMH?HUHuHuHXHHCHC0HKHSHC@H`Ht HhGqH}Ht H}5qLuHEMtLELqH HH;EuHHĈ[A\A]A^A_]JqIH`Hu$H}Hu>H]HEHu]Lq Hh諨qH}Ht IH}HtH}苨qH]HEHtIH]HEHtHEHTqL蔥q fff.UHAWAVATSH@HIH HHEH]1HEIľHEIǾHEHEIL$IT$ H)HtHH9IOIW H)HtHH9Ht%HHHP H)HtHH9ID$0@EHuHULMLLM`H HH;EIHrHEH]HuHL59.LHvTpIHrHEH]HuHL8.LHvT7HH rHMH]HuHH8.LH^vTEt H}}qH HH;EuLH@[A\A^A_]踦qHEuHEu HEt H}0qHpq UHHH ҈HHxH@Ht]q]fDUHSPHHHH{HCHtťqHH[]鷥qfUHAVSI覥qHHRHH{L#DH솉HH[A^]IHdqL褢q fff.UHAVSIFqHHHH{LÂDHHH[A^]IHqLDq fff.UHAWAVAUATSHHMMIHIHi HHEЋEHEHEH}HuH}HuHLMM'H}HuHLMMH}HuHLMMuH}HuHLMMH}uuHUH} H]Htc qIHILHHH qH]M>HEHt8Ct H{ѣqHɣqHdHH;Et!1IHEHCHH;EuLHH[A\A]A^A_]qILvqH]HEHu 5IH]HEHtCt H{6qH.qLnq fDUHAVSHIHHHEA>uuHM H}HEHEI^IFHtACt H{ŢqH轢qH]HEHt!Ct H{蝢qH蕢qHEIFH"HH;Eu 1H[A^]ǢqfUHAVSHIHHHEA>uuHM H}HEHEI^IFHtACt H{qHqH]HEHt!Ct H{ݡqHաqHEIFHbHH;Eu 1H[A^]qfUHAVSHIH+HHEA>uuHM H}/HEHEI^IFHtACt H{EqH=qH]HEHt!Ct H{qHqHEIFHHH;Eu 1H[A^]GqfUHAVSHIHkHHEA> uuHM H} HEHEI^IFHtACt H{腠qH}qH]HEHt!Ct H{]qHUqHEIFHHH;Eu 1H[A^]臠qfUHAVSHIHHHEA>uuHM H} HEHEI^IFHtACt H{şqH轟qH]HEHt!Ct H{蝟qH蕟qHEIFH"HH;Eu 1H[A^]ǟqfUHAWAVAUATSH8MMIH}HHHEHLD0MLD E0qHEf(<f)EHbe zero!HH Hcan not HHHperator HHH Range oHHHdelta inH@(HMH]HTnTEH}AA)A*A*^f: +L,E1MMIEqHEHHHML(HMHU1LڀDHM*Iw1 HL!fnfpfAnfpf8@3fBfnfpHyHHVHs 1HunHzH)1ffDfD fD0fD@fDPfD`fDpH fHuHt,HtHf.FffH HuI9t"DHDHDHL9rH]HH}Ht H}qH[HH;EuHH8[A\A]A^A_]qHEtH}HH}Ht H}uqH赙q ffff.UHAWAVAUATSH8MMIH}HHHEHHLL0MLL M0qHEf(;f)EHbe zero!HH Hcan not HHHperator HHH Range oHHHdelta inH@(HMH]HSkTEH}AI)I*I*^f: +L,E1MMIDqHEHHHML(HMHU1L}DH MJIw1+HL!fHnfpDfInfpDfHnfsfoffs ffs ffK$fHnfpDHyHHVH s 1HuoHzH)1fDfD fD0fD@fDPfD`fDpHfHuHt,HtHf.FffH HuI9t#LHHHHHLHL9rH]HH}Ht H}蟙qH:HH;EuHH8[A\A]A^A_]ؙqHEtH}HH}Ht H}TqH蔖q fff.UHAWAVATSH0LMIIHHHEH_ELNHHE4W.E0ɘqHEf(f)EHbe zero!HH Hcan not HHHperator HHH Range oHHHdelta inH@(HMLhTE/H}! C\EZMZ^f: L,1MIIܿ -qHEHHHMHHMHU1LoDHGMEMHSكHrfHH)ffffff.X@X@X@ X@X@X@X@H XHuHtHHXHuIH}Ht H}qHGHH;EuLH0[A\A^A_]OqHEtH}HH}Ht H}qH q UHAWAVATSH0LMIIHGHHEHELHHEfWf.E0GqHEf(!Jf)EHbe zero!HH Hcan not HHHperator HHH Range oHHHdelta inH@(HML譞TEH} X\EM^f: -L,1MIIܿqHEHHHMHHMHU1LDH=MEMHSكHr\HH)DX@X@X@X@ X@(X@0X@8H@XHuHtHHXHuIH}Ht H}qHEHH;EuLH0[A\A^A_]qHEtH}HH}Ht H}[qHq UHAWAVAUATSH8MMIH}HDHHEHLD0MLD E0qHEf(Gf)EHbe zero!HH Hcan not HHHperator HHH Range oHHHdelta inH@(HMH]HQTEH}AA)A*A*^f: -L,E1MMI/qHEHHHML(HMHU1L蔪DHMEIw1&HL!fnpfpfAnpfpfefBfnpfpHyHHVH0s 1HuzHzH)1fffff.pfDpfDp fDp0fDp@fDpPfDp`fDppH@fHuHt,HtpHf.FffH HuI9t#DHHDfHDHL9rH]HH}Ht H}qH -BHH;EuHH8[A\A]A^A_]qHEtH}HH}Ht H}DqHq fff.UHAVSHPIHAHHE(qHþ H -qHHCHCXHC`HCXHCHHC@HC8HC0HC(HC HCPHCpHCxHCpHChƃHǃfǃHǃHǃƃHHǃHǃHǃHǃHǃHǃHǃHǃHǃHHHǃHǃHǃǃǃHǃ H]H}11eCH@H5qHH+CH5rH,CH5uH]CHH -HQH5t rH}CHH;BCHHH 1HMHHUHuHuIIFIF0INIVIF@H]HEHtHvEHqH7?HH;Eu LHP[A^]qIH]HEHtH1EHwqLq ffffff.UHAWAVSHxIH>HHE(BqHþ H8qHHCHCXHC`HCXHCHHC@HC8HC0HC(HC HCPHCpHCxHCpHChƃHǃfǃHǃHǃƃHHǃHǃHǃHǃHǃHǃHǃHǃHǃHHHǃHǃHǃǃǃHǃ H]H}11CI@HW)EHEqHEHHHMHHM@HW)pHE_qHpHHHMHHxH5IqHUHpLCH5rHCH5kuHCHH HQH5( rH1CHH;CHHH HMH:HUHuHuIIGIG0IOIWIG@HpHt HxyqH}Ht H}gqH]HEHtHEHFqH;HH;EuLHx[A^A_]qIH}Ht0^IH]HEHt+bIHpHu$H}Hu0H]HEHu9Lq HxqH}HtH}qH]HEHtHEEHqLq UHAWAVAUATSHHPH:HHEп(WqHþ HMqHHCHCXHC`HCXHCHHC@HC8HC0HC(HC HCPHCpHCxHCpHChƃHǃfǃHǃHǃƃHHǃHǃHǃHǃHǃHǃHǃHǃHǃHHHǃHǃHǃǃǃHǃ H]H}11CHH@HX@I@I@H@I0@IW)EHE0~qHEHH0HMHXHLhLpHXL` Lx(HM^@HXR@I@IB@Iz@I@HW)`HDžp0qH`HH0HpHXHLhL`LpLx HX(HhH5qHUH`HHHCH5GrHYCH5uHCHH HQH5rHCHH;oCHHH ^HMHHUHuHuHPHHCHC0HKHSHC@H`Ht HhqH}Ht H}ٿqLuHEMtLrEL踿qH37HH;EuHHĘ[A\A]A^A_]qrIH`Hu$H}Hu>H]HEHu]L裼q HhMqH}Ht IH}HtH}-qH]HEHtIH]HEHtHEHqL6q fffff.UHAWAVAUATSHHPH>6HHEп(跾qHþ H譾qHHCHCXHC`HCXHCHHC@HC8HC0HC(HC HCPHCpHCxHCpHChƃHǃfǃHǃHǃƃHHǃHǃHǃHǃHǃHǃHǃHǃHǃHHHǃHǃHǃǃǃHǃ H]H}11CHH<@HX0@Ih@I @HX@I@IW)EHE0޼qHEHH0HMHXHLhLpHXL` Lx(HM@HX@I@I@I@I@HW)`HDžp0ZqH`HH0HpHXHLhL`LpLx HX(HhH5&qHUH`HHCH5rH蹻CH5DuHCHA H5rHCHH;ֲCHHH HMH -HUHuHuHPHHCHC0HKHSHC@H`Ht HhRqH}Ht H}@qLuHEMtLELqH2HH;EuHHĘ[A\A]A^A_]UqrIH`Hu$H}Hu>H]HEHu]L -q Hh贺qH}Ht IH}HtH}蔺qH]HEHtIH]HEHtHEH]qL蝷q DUHAWAVSH8HIH1HHE1HUEIL}ؾHAEHEоH0EHEIW1H~DHEIG0@EH}HuHUHMLEg IH91HH;EuLH8[A^A_]qffff.UHHH "HHxH@Ht]fq]fDUHSPHHHH{HCHt5qHH[]'qfUHAVSIqHH{LMHHHHLTDH孉HH[A^]IHŸqLq ffff.UHAWAVAUATSHH0HHEW)EEIIHEEminMgHhHULDHhHDžhHtCt H{/qH'qA$Et H}qW)EHEEEmaxHhHULL肰DHhHDžhHtCt H{躷qH買qAEt H}蜷qAA.Gr'H /HH;EuHĈ[A\A]A^A_]ɷqwqIHh"eUH5rH IrH}LhHPH HAHrHuLHG E1H5=PHL:q IALhMIIPt H`诶qLeMt6HEL9t!HX@t Hx芶qHI9uH}LLepqEuEuLhMu&^H}MqEtH}>qLhMt:HpL9tEHX@t HxqHI9uHhLpqEt4LqL+q LIEu IEt H}迵qLq UHHH BHHxH@Ht]醵q]fDUHSPHHHH{HCHtUqHH[]GqfUHAWAVAUATSPIIH}1LNEHLk1LL蚓DIHoIL7HEl$Ed$LRHI~7HHuڃH9HOII)LH?H>LHH5fAnfAnHrI H9s!H I9sE1HzLIIfofoIIHHDGAHIHH)1fDA$(_(]$Ad(_(]dHHuMtA$_]L9tjHzLtfoC_fo]BLHL9t:foA_fo]foA_Tfo]\HH9uH<I|;fAnfAnHA(_(])HH9|H9RfAnfAnI)ILI I9sLI L9MIfofoIHIIENAHHM\HtIIL)1ff.Ad(_(]dA$(_(]$HHuMtHA$_]M9twLlj)HPH@tfoA_fo]HOH9tCf.foA_fo]foA_Tfo]\HH9uHEHH[A\A]A^A_]1M1M=Jffff.UHAVSIvqHHHH{LÊDHHH[A^]IH4qLtq fff.UHAVSIqHHHH{LcDHHH[A^]IH԰qLq fff.UHAVSI趰qHHBHH{LDH<HH[A^]IHtqL购q fff.UHAWAVATSHPMIIHH'HHE؋EHEtm  uH3I$IMH}V$HEH}5 HR'HH;EHP[A\A^A_]H3I$IMH}HEЋEȃ vH3I$IMH}HEЋEȃYH3I$IMH}HEЋEȃ<H3I$IMH}PHEЋEȃH3I$IMH}HEЋEȃ NqUHAWAVAUATSHMIHHL&HHEHtpHBHJ H)HtHH8HM)0tGIFIN H)HtH|H8rLƥ"M)0u)@H蕥IHH0HL~HIL0HHuڃH9HOII)LH?H>LHH(0(@,HrI H9s!H I9sE1HzLII((IIHHDGAHmIHH)1ffff.A(_(]AT(_(]THHuMtA_] L9tfHzLt(C_(]B LHL9t8(A_(] (A_D(]LHH9uH<I|/((HA(_(])HH9|H9>I)ILI I9sLI L9MI((IHIIEOAHHM\HtIIL)1AT(_(]TA(_(]HHuMtHA_] M9tsLlj)HPH@t(A_(] HOH9tAfff.(A_(] (A_D(]LHH9uH"HH;Eu2HĨ[A\A]A^A_]1M1M9F"qЪqIHh{XUH5rH [rH}Lh\W)PHDž` sqH`({#)PH scalar.HHHld be a HHHmin shouH@AHrHuHPLJE1H5@CHL=qqIHhWUH5GrH rH}Lh` W)PHDž` 蛩qH`(")PH scalar.HHHld be a HHHmax shouH@AHҩrHuHPLrE1H5hBHLeq IALeMIALhMIIALeMFIALhMnIIPt H`臨qLeMt6HEL9t!HX@t HxbqHI9uH}LLeHqEuEu LhMu-'H}"qEtH}qLhMHpL9HX@t HxqHI9uIPt H`軧qLeMt6HEL9t!HX@t Hx薧qHI9uH}LLe|qEuEuLhMu&^H}YqEtH}JqLhMt:HpL9tEHX@t HxqHI9uHhLpqEtL'qL7q Lf.UHAWAVAUATSHMIHH<HHEHtpHBHJ H)HtHH8HM)0tGIFIN H)HtHH8L֠M)0ud@f)@H褠IHH(HLݻHIL(HHuH9HOII)LH?LHHf(0f(@HrI H9s!H I9sE1HzLIIIHHHDOAHIIH)1fDfAfA\f(f_f(f_f(f]f(f]ffdfAT fA\0f(f_f(f_f(f]f(f]f\ fd0HHuMt0fAfA\f(f_f_f(f]f]ffDL9tsHzLtf(C_f(]B LHL9tCf.f(A_f(] f(A_Df(]LHH9uH<I|0DAf(f_f(f]f)HH9|H9 I)IH IH9s H IH9rqMIITHtJ<1fffff.fTff(f_f(f_f(f]f(f]f\f$HI9uM9tu)HPH@tf(A_f(] HOH9tDff.f(A_f(] f(A_Df(]LHH9uH@HH;Eu"HĨ[A\A]A^A_]1Mq蜢qIHhGPUH5rH rH}Lh\W)PHDž` ?qH`(G)PH scalar.HHHld be a HHHmin shouH@AH^rHuHPL E1H5 ;HL qġqIHhoOUH5rH 6rH}Lh`W)PHDž` gqH`(o)PH scalar.HHHld be a HHHmax shouH@AHrHuHPL> -E1H54:HL1q IALeMIALhMIIALeMFIALhMnIIPt H`SqLeMt6HEL9t!HX@t Hx.qHI9uH}LLeqEuEu LhMu-'H}qEtH}ߟqLhMHpL9HX@t Hx謟qHI9uIPt H`臟qLeMt6HEL9t!HX@t HxbqHI9uH}LLeHqEuEuLhMu&^H}%qEtH}qLhMt:HpL9tEHX@t HxqHI9uHhLpОqEtLqLq LfDUHAWAVAUATSHLIIH HHEHtgHBHJ H)HtHH8HD Mt:IFIN H)HtHJH8@LnD8 AMuALVIIL HHoIHH HHH rI I9LHI9E1HpL¨L9f.ADD8|DA8~A\A\DD8|$DA8"A\HH9uUDA8~މA\HH9u1IIAfnff8Afnf8IHHHrHH~H)1ff.AoAo\f8<f8<f88f88ATA\AoT Ao\0f8<f8<f88f88AT A\0H@HuHt/AoAo\f8<f8<f88f88ATA\L9t<HpL¨|C DD8|DA8~CLLHL9bHkHH;EuHĈ[A\A]A^A_]1HcqʛqIHhuIUH5rH rH}Lh\W)PHDž` mqH`(u)PH scalar.HHHld be a HHHmin shouH@AHrHuHPLDE1H5:4HL7qqIHhHUH5ArH rH}Lh`W)PHDž` 蕚qH`()PH scalar.HHHld be a HHHmax shouH@AH̚rHuHPLlE1H5b3H L_q IALeMIALhMIIALeMFIALhMnIIPt H`聙qLeMt6HEL9t!HX@t Hx\qHI9uH}LLeBqEuEu LhMu-'H}qEtH} qLhMHpL9HX@t HxژqHI9uIPt H`赘qLeMt6HEL9t!HX@t Hx萘qHI9uH}LLevqEuEuLhMu&^H}SqEtH}DqLhMt:HpL9tEHX@t HxqHI9uHhLpqEtL!qL1q L@UHAWAVAUATSHLIIH<HHEHtgHBHJ H)HtHH8HsD Mt:IFIN H)HtH>H84L>D8 E1MuAL&IILHH?IHHHHH rI I9LHI9E1HpL¨xL9f.ADD8rDA8rA\A\DD8r$DA8s"A\HH9uIDA8rމA\HH9u%IIAfnff8Afnf8IHHHrHH~H)1ff.AoAo\ffffATA\AoT Ao\0ffffAT A\0H@HuHt+AoAo\ffffATA\L9t<HpL¨C DD8rDA8rCLLHL9nH HH;EuHĈ[A\A]A^A_]1HgXqqIHhBUH5UrH rH}Lh\.W)PHDž` 詔qH`( )PH scalar.HHHld be a HHHmin shouH@AHȔrHuHPLE1H5v-HLsq.qIHhAUH5}rH rH}Lh`VW)PHDž` ѓqH`( )PH scalar.HHHld be a HHHmax shouH@AHrHuHPLE1H5,HGL蛓q IALeMIALhMIIALeMFIALhMnIIPt H`轒qLeMt6HEL9t!HX@t Hx蘒qHI9uH}LLe~qEuEu LhMu-'H}XqEtH}IqLhMHpL9HX@t HxqHI9uIPt H`qLeMt6HEL9t!HX@t Hx̑qHI9uH}LLe貑qEuEuLhMu&^H}菑qEtH}耑qLhMt:HpL9tEHX@t HxUqHI9uHhLp:qEtL]qLmq LUHAWAVAUATSHMIIH|HHEIHt7HBHJ H)HtHVH8LHyHMu 9I]Mt0IGIO H)HtHH8L9L(L.IIL?HLGIIL(HHƒHu 1Hu{H)1I<HH9|HLI9~HI<I|HH9|%HLI9"I|HH9u#f.LI9~HI|HH9uHtIH9HLI9INIHHH;EuHĈ[A\A]A^A_]ӏq聏qIHh,=UH5ЎrH 6rH}Lh\W)PHDž` $qH`(,)PH scalar.HHHld be a HHHmin shouH@AHCrHuHPLE1H5'HLq詎qIHhT<UH5rH ^rH}Lh`W)PHDž` LqH`(T)PH scalar.HHHld be a HHHmax shouH@AHrHuHPL#E1H5'HLq IALeMIALhMIIALeMFIALhMnIIPt H`8qLeMt6HEL9t!HX@t HxqHI9uH}LLeqEuEu LhMu-'H}ӌqEtH}ČqLhMHpL9HX@t Hx葌qHI9uIPt H`lqLeMt6HEL9t!HX@t HxGqHI9uH}LLe-qEuEuLhMu&^H} -qEtH}qLhMt:HpL9tEHX@t HxЋqHI9uHhLp赋qEtL؋qLq Lff.UHAWAVAUATSHMIIHHHEHtgHBHJ H)HtH`H8VHL(Mt:IGIO H)HtHH8L^HE1MuHLBIIL HL[IIL HHƒHu1H{H)1I<LL9rHHH9rHI<I|LL9r%HHH9s"I|HH9u#f.HH9rHI|HH9uHtIL9IBH9HBIHHH;EuHĈ[A\A]A^A_]CqqIHh7UH5@rH erH}Lh\W)PHDž` 蔉qH`()PH scalar.HHHld be a HHHmin shouH@AHrHuHPLkE1H5a"H -L^qqIHh6UH5hrH rH}Lh`AW)PHDž` 輈qH`()PH scalar.HHHld be a HHHmax shouH@AHrHuHPLE1H5!H2L膈q IALeMIALhMIIALeMFIALhMnIIPt H`訇qLeMt6HEL9t!HX@t Hx胇qHI9uH}LLeiqEuEu LhMu-'H}CqEtH}4qLhMHpL9HX@t HxqHI9uIPt H`܆qLeMt6HEL9t!HX@t Hx跆qHI9uH}LLe蝆qEuEuLhMu&^H}zqEtH}kqLhMt:HpL9tEHX@t Hx@qHI9uHhLp%qEtLHqLXq Lff.UHAWAVSH(HIIHcHHEHHF H+FHH 轅qHE(hĂ)EH0D or 1DHHHld be 0DHHHsor shouHHHAxis tenH@HML3UTo0NqHE(YĂ)EHumSum opHH%Hthe CumSHH Hided to HHH be provHHHsor mustHHHAxis tenH@-HMLTTHF0@tuFHjHc8 H]tH8H;L$HIHHH;E@lqHE(W4)EHor `int6HH(Hnt32_t` HH H type `iHHHld be ofHHHsor shouHHHAxis tenH@04_t`@4HMLSTEt H}΃qHIHH;EuLH([A^A_] qHEuHEu HEt H}胃qHÀq ff.UHAWAVATSH`IHHHEؿ(PqHþ HFqHHCHCXHC`HCXHCHHC@HC8HC0HC(HC HCPHCpHCxHCpHChƃHǃfǃHǃHǃƃHHǃHǃHǃHǃHǃHǃHǃHǃHǃHHHǃHǃHǃǃǃHǃ H]@H5َqH}HvCI@I@HW)EHE蔁qHEHHHML HXHMH5sHUL荅CH5΅rHCH5uHOCHH HQH5fqHoCHH;4xCHHH #HMHHUHuHuIIGIG0IOIWIG@H}Ht H}轀qH]HEHtHVEH蜀qHHH;EuLH`[A\A^A_]׀qIH]HEHt7H EHOqL}q IH}HuH]HEHuLh}q H}qH]HEHt@UHAWAVATSH`IHgHHEؿ(qHþ HqHHCHCXHC`HCXHCHHC@HC8HC0HC(HC HCPHCpHCxHCpHChƃHǃfǃHǃHǃƃHHǃHǃHǃHǃHǃHǃHǃHǃHǃHHHǃHǃHǃǃǃHǃ H]y@H5iqH}HCI螨@I薮@HW)EHE$~qHEHHHML HXHMH5sHULCH5^rH}CH59uH~CHH HQH5qHCHH;tCHHH HMHhCHUHuHuIIGIG0IOIWIG@H}Ht H}M}qH]HEHtHEH,}qHHH;EuLH`[A\A^A_]g}qIH]HEHt7H虖EH|qLzq IH}HuH]HEHuLyq H}|qH]HEHt@UHAWAVATSH`IHHHEؿ(p|qHþ Hf|qHHCHCXHC`HCXHCHHC@HC8HC0HC(HC HCPHCpHCxHCpHChƃHǃfǃHǃHǃƃHHǃHǃHǃHǃHǃHǃHǃHǃHǃHHHǃHǃHǃǃǃHǃ H]I@H5qH}H薃CI.@I&@HW)EHEzqHEHHHML HXHMH5sHUL~CH5~rH>zCH5ɧuHo{CHH HQH5qH|CHH;TqCHHH CHMHjHUHuHuIIGIG0IOIWIG@H}Ht H}yqH]HEHtHvEHyqH7HH;EuLH`[A\A^A_]yqIH]HEHt7H)EHoyqLvq IH}HuH]HEHuLvq H}5yqH]HEHt@UHAWAVATSH`IHHHEؿ(yqHþ HxqHHCHCXHC`HCXHCHHC@HC8HC0HC(HC HCPHCpHCxHCpHChƃHǃfǃHǃHǃƃHHǃHǃHǃHǃHǃHǃHǃHǃHǃHHHǃHǃHǃǃǃHǃ H]٧@H5qH}H&CI辡@I趧@HW)EHEDwqHEHHHML HXHMH5>sHUL={CH5~{rHvCH5YuHwCHH HQH5qHyCHH;mCHHH ӮHMHhHUHuHuIIGIG0IOIWIG@H}Ht H}mvqH]HEHtHEHLvqHHH;EuLH`[A\A^A_]vqIH]HEHt7H蹏EHuqL?sq IH}HuH]HEHuLsq H}uqH]HEHt@UHAWAVATSH`IHHHEؿ(uqHþ HuqHHCHCXHC`HCXHCHHC@HC8HC0HC(HC HCPHCpHCxHCpHChƃHǃfǃHǃHǃƃHHǃHǃHǃHǃHǃHǃHǃHǃHǃHHHǃHǃHǃǃǃHǃ H])@H5qH}H|CIN@IF@HW)EHEsqHEHHHML HXHMH5ΣsHULwCH5xrH^sCH5uHtCHAH5qHuCHH;{jCHHH jHMHHUHuHuIIGIG0IOIWIG@H}Ht 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LPMu,dH}ºphtHx譺pLPMt:HXL9t?HX@t Hx肺pHI9uHPLXgpELLI8t HH9pLmMt6HEL9t!HX@t HxpHI9uH}LLmpEuhu LPMu,dH}ԹphtHx迹pLPMt:HXL9tEHX@t Hx蔹pHI9uHPLXypEtL蜹pL謶p Lffffff.UHAVSI FpHHL~QH[A^]IHpLYp UHAVSI pHHLH[A^]IHٸpLp UHAVSI ƸpHHLΩH[A^]IH虸pLٵp UHAVSI 膸pHHLnH[A^]IHYpL虵p UHAVSHPIH/HHE(4pHþ H*pHHCHCXHC`HCXHCHHC@HC8HC0HC(HC HCPHCpHCxHCpHChƃHǃfǃHǃHǃƃHHǃHǃHǃHǃHǃHǃHǃHǃHǃHHHǃHǃHǃǃǃHǃ H]?H5pH}HZBH53qH[BH5tH茷BHA H5pH賸BHH;xBHHH gHMHHUHuHuIIFIF0INIVIF@H]HEHtHDHpHm-HH;Eu LHP[A^]1pIH]HEHtHgDH譵pLp DUHAVSI薵pHH"HH{LCH̬HH[A^]IHTpL蔲p fff.UHHH ҪHHxH@Ht]p]fDUHSPHHHH{HCHtpHH[]״pfUHAWAVAUATSHIIH/,HHE1LDIMFIEIM H)HH H ޾qHIILHHHHH@HHH;uhL8I L菫IIEJHHhuzHO1H8͖CHUHHhLs^H [qLцSH*+HH;ELLHĸ[A\A]A^A_]L(L0H@H W)EHEH}H@ SAE1E1@IuJ>HEH;EtHHHE LH}SLIIL;@|HU1H8莔CHVIE~YMcHHHHHE1Lh1ffff.DH(H4L:AHLHL9|H}Ht H}qpL0IH)HH;E課pXpIHh`TH5лqH qH}LhHPHCAHTqHuLH(E1H5KHLp[HALhMHHPt H`荱pLeMt6HEL9t!Lh@t HxhpLM9uH}LLeNpEuEuLhMu&^H}+pEtH}pLhMt:HpL9t=Lh@t HxpLM9uHhLpְpEt\LpRLHH}Hu8?HH}Hu*1HH}Hu#HH}HuHH}Ht H}upH赭p ffff.UHAWAVSHxHH'HHEHc7HtzW)EHEH}HOHML]L]MI?I>MMIIIIOHHHxHs91Hh`|H)'HH;EHwH)1fffff.)D)DD )D D0)D0D@)D@DP)DPD`)D`Dp)DpH HuHt$HHfff.)HHuMM)IJJH9sJJH9MIIPHHDpAHs1M}J|pJTpIvH)1DLDLDLDLDLDLD D H HuMt.IIIDID D H IuM9MDD)ICL)HtHB4B4IHuHraM)JDJL1ff.tttttttttttttt44HI9uH}HuLH}UpEW*HuHMH9HHNHt<LEAHH9HHOэBHHsHuy ]HHHHL RHHHH9HMLTL@YLYLBYL Y ;HIT2HHuHt-HQHIH Hf.Y -HHuY|H}ApH}8pH}/pH#HH;Eu|Hx[A^A_]SpHH}pH%p ffff.UHAWAVATSIIIMtMtH1IL9|eLIID$ID$H9t;I<$萬pH~%HH>u7HH֬pHtHt!I$I$M|$Mt$[A\A^A_]ÿEpHH -pH5e!H HZpfffff.UHAWAVAUATSPIIIt$IT$IFIFIMnI\$IF IFHt;~1HH>wL<LpMt HIEIELmI^ Mn(I\$IF0IF(Ht;~1HH>yL<L蚫pMt HIEIEI^0AF8fAF<I$It$IT$I9vuI9VtLIvIVIHII?I>IMIHIIOHHH~Hs 1HulHOH)1()(D)D(D )D (D0)D0(D@)D@(DP)DP(D`)D`(Dp)DpH HuHt$HHfff.(3)0HHuIM)IJ H4H9sH J4H9MIIHHHD^AHs1MN|pJ|pIKH)1ADALDLADALDLADALDLADA D H HuMt6IIILIff.D  D H IuM9MĉD)HJL)HtH@B<B<IHuHraL)JLJD1ff.||||||||||||||<<HH9uLH[A\A]A^A_]M+pHHpH5KHH@pMpHH车pH5HqH pX˦pHH萦pH5HDHp+螦pHHcpH5HH賦p HI?HHI}\pHEH8PpI>HpHtp fff.UHAWAVSHXIHHHEI~/L}L}H}HuHU"fA~G8I_I9_0uMG(_AG8I_I9_0tI(æpH~4HH>L4LpIMt MMG( IG(E1I_0IIIwH$LMHzE$AG<I_0I9_ tAI:pH HH>L4LtpMt HIGI_ IGHs1dAAHL)Hxfo?fo @fo @HfofGfH HuMtfff.HH9uH~,IGIO(HDHcTt<|4HHAG=HHH;Eu!HX[A^A_]IGI_ WppHHʣpH5%H~HpH p @UHAWAVAUATSPHBLpIFHLuLH?II>ML'ID$Ml$HHEI4$L@LHT dOIHLHJH<@(8OHDBTBTX8T$HTXXXHH9|HHHHEH9NLMyMtPMAT NIIIAwIGHHIWWI| MMIIQEGAHHHH4[MOM)MIA($NMސCTIs!LmMuhfffff.LLm@\TXDTX\1TXD9HTXHI9uMt.HLILffff.TXHHu_II(M96] H9)I)Ht:HIHJ<H(MfTXHHHuIrhHMH)LBMLHHZIHIHI(LTX TXTXB TXHHuMIILm I=MHEHI4$L@LHFTKLHLHJH<@("LHffffff.B\TBdTX\8TlHTXXXHH9|HHHHEH9(AFINHC((H` -WHHHLRLH)(bKLffffff.TX TXBTX HTXHH9uHt1HIHH(JTXHHuI [AFINH(H H9)I)Ht<HIHDJ<H(jJf.TXHHHuIrlHMH)LBMLHHZIHIHI(J\TXDTX\TXBDTXHHuLxL}LHIH]TH}LoLhIIEHHHpHEHH4 IIIH HPHLR HXHL L40MH0L\R0L<0(7I1HE H`LeHUHI$TIH}H]HعHPHX@$0TB,TX$8T4TXXXHLL9|LpH}H]HML9HuBf.WW_(ffffff.AL9HuD)HhL)Ht,HEIHHHfD TXIHHuHH]L)ID$HUHHMHHuHH}H ID$HHHH<HEIHH4ILeLeJ $TXTX$TXTXLHu((_HEHM\0TI|`HȹB$0TB,8TXB$TB4TXXXHLL9|Hpffffff.LeHMHUHuH}H9~b)LhI)Ht2HEHH`HMHHMH TXHHHuIsH]HuLeDH]H)HCHUHLeLHuH<HCHLHH4HEHLHHH]LH0@$TXTX$TXTXLHuHMH]HUHuLeH}_HH HP HX I HEI I I I H`(H9X(HM((_LxI9HLuL}LmM $LALHATEHIDMLHJMKDmHI4JkI1(DfAT$TXTA,TXXXHHH9|HHHLxHMH]H9LuL}LmHHL)fW_(Hu(H@HؐW_(Hu(WI)ƹ(DDAA\T_T_ATT_AL T_HI9u(HI H(CfDT_H(HuH9)I)Ht?HIHIJ4H(KCff.TXHHHuIHMH)HBIHMLHHBIHI<HIHIIHILI1(Bfffff.TXTXTXATXHHu_((__M9wIT$H{M$HIJIL}J<LHM4KDmM<O$O,HBHEH)HMHHM(ALEff.CTH}s MѾH}MLE}MLLMMLEBTXBTXCTXCTXHIIHHH9uH}MLEt,HuLIHMfTXHHu_IIIII(L;U (H[A\A]A^A_]DD)IFL)Ht$H(fff.W_I(Hu(HHErL)fffff.W_(HuIFL)LHt&H(d@(ѐC T_I(Hu(HHMCL)KD ((@(DHXT_T_HT_T_HHufUHAWAVAUATSHMH2 HHEH`HUH}HuHMH9ILNI5H}LLH -H H;MH[A\A]A^A_]LELHHHHALEH9HHNLHLHH9H HHMMt$HZHXHII)M9MMOLAHMOJHH@HHIIL9LMHDž1HLHLHHHE1H1HXLL`H0LL8L(PLUH}LIL8LLMHLHXHHH0HH9HHHMH H9HLHI9HLIMH9HLHLIHH HH9HHMH9HLH`LMLH9HHMH9HLHhH9HLH9HLHpHXI)M9MMNMILHIHUIM L`IHXLHPHIH0LIHHH)HL)M)LuLuL}L`LhLpH8L@LHHxHLLL LHIMDH$LL|VHHIHIIEH|HLMH`LhH HHH@HLHHHIHHHBHIHHB0H(LHLD:0JHHHB H81I61M1L0L@XLHHCtHHp CLHcLIH IIuAAAAI9LOHL4HL<IM)MI?I>MLHHPMIr1HIHIL H H9JL91M]I)LHt6Hp43HcHhH4HfDHHuIHXHpHHhH8Hfff.t4TTttTTttTT 4t HI9uMLHHAHHDsAHHhHXHp0HHH(H4IFH)1fffff.ADALT\ATA\DLADA TATAD HHuMt/HLAA\\AALI9H`HXM"@LL0HPN4.ILhM]M9MMIM)DLHtMHXHpHIH`HHLfff.(  )HHuI HXrHpHIH(Hffffff.D( L)D(LL)DD(L L)D (L0 )D0HL9|I9L M)I)IL@HLIIIK HHHH0HHH9s-LLHPH`HI9v L@4MIID$HHHHOHpHIIHPIH`JI)IIIAqHL)J 1L0L@ffff.L\\LD L0T \0T \0D L0HHut2LHLAA\\AALM9HXLhMfH D)HL)t?Hp HcIH`H D)HBBBBIHuHHXLhryHpHIH8Hf.B BTBBLBLBTBTBLBLBTBTBLBL BBT B IL9uIHHHIHL;PLH`FHxHHl +qHEHHHMHHMHU1LzDH'MEMHSكHrfHH)ffffff.X@X@X@ X@X@X@X@H XHuHtHHXHuIH}Ht H}qHHH;EuLH0[A\A^A_]OqHEtH}HH}Ht H}˖qH q UHAWAVATSH0LMIIH>HHEHELHHEfWf.E0GqHEf(f)EHbe zero!HH Hcan not HHHperator HHH Range oHHHdelta inH@(HMLeTEH} \EM^f: +L,1MIIܿ萕qHEHHHMHHMHU1L%xDHMEMHSكHr\HH)DX@X@X@X@ X@(X@0X@8H@XHuHtHHXHuIH}Ht H}褔qH?HH;EuLH0[A\A^A_]ߔqHEtH}HH}Ht H}[qH蛑q UHAWAVAUATSH8MMIH}HHHEHLD0MLlD E0qHEf()f)EHbe zero!HH Hcan not HHHperator HHH Range oHHHdelta inH@(HMH]HAcTEH}AA)A*A*^f: +L,E1MMI/qHEHHHML(HMHU1LuDHMEIw1&HL!fnpfpfAnpfpf'fBfnpfpHyHHVH0s 1HuzHzH)1fffff.pfDpfDp fDp0fDp@fDpPfDp`fDppH@fHuHt,HtpHf.FffH HuI9t#DHHDfHDHL9rH]HH}Ht H}菑qH*HH;EuHH8[A\A]A^A_]ȑqHEtH}HH}Ht H}DqH脎q fff.UHAVSHPIHHHE(qHþ H +qHHCHCXHC`HCXHCHHC@HC8HC0HC(HC HCPHCpHCxHCpHChƃHǃfǃHǃHǃƃHHǃHǃHǃHǃHǃHǃHǃHǃHǃHHHǃHǃHǃǃǃHǃ H]H}11蕝CH;@H5qHH[CH5(rH\CH5buH荔CHH +HQH5tqH譕CHH;rCHHH QHMHHUHuHuIIFIF0INIVIF@H]HEHtHfEH輎qHWHH;Eu LHP[A^]qIH]HEHtH!EHwqL跋q ffffff.UHAWAVSHxIHHHE(BqHþ H8qHHCHCXHC`HCXHCHHC@HC8HC0HC(HC HCPHCpHCxHCpHChƃHǃfǃHǃHǃƃHHǃHǃHǃHǃHǃHǃHǃHǃHǃHHHǃHǃHǃǃǃHǃ H]H}11ÚCI@HW)EHE虌qHEHHHMHHMĻ@HW)pHE_qHpHHHMHHxH5IqHUHpLCH5܊rHCH5uHACHH HQH5(qHaCHH;&CHHH HMH:HUHuHuIIGIG0IOIWIG@HpHt HxyqH}Ht H}gqH]HEHtHEHFqHHH;EuLHx[A^A_]胋qIH}Ht0^IH]HEHt+bIHpHu$H}Hu0H]HEHu9Lq Hx辊qH}HtH}謊qH]HEHtH5EH苊qLˇq UHAWAVAUATSHHPHHHEп(WqHþ HMqHHCHCXHC`HCXHCHHC@HC8HC0HC(HC HCPHCpHCxHCpHChƃHǃfǃHǃHǃƃHHǃHǃHǃHǃHǃHǃHǃHǃHǃHHHǃHǃHǃǃǃHǃ H]H}11ؖCHH @HX@I8@I@H(@I`@IW)EHE0~qHEHH0HMHXHLhLpHXL` Lx(HM获@HX肽@I躹@Ir@I誼@I@HW)`HDžp0qH`HH0HpHXHLhL`LpLx HX(HhH5ƔqHUH`HHxCH5UrH艋CH5uH躌CHH HQH5qHڍCHH;蟂CHHH ~HMHHUHuHuHPHHCHC0HKHSHC@H`Ht HhqH}Ht H}نqLuHEMtLbEL踆qHSHH;EuHHĘ[A\A]A^A_]qrIH`Hu$H}Hu>H]HEHu]L裃q HhMqH}Ht IH}HtH}-qH]HEHtIH]HEHtH蠟EHqL6q fffff.UHAWAVAUATSHHPH^HHEп(跅qHþ H譅qHHCHCXHC`HCXHCHHC@HC8HC0HC(HC HCPHCpHCxHCpHChƃHǃfǃHǃHǃƃHHǃHǃHǃHǃHǃHǃHǃHǃHǃHHHǃHǃHǃǃǃHǃ H]H}118CHHl@HX`@I蘵@IP@H舸@I@IW)EHE0ރqHEHH0HMHXHLhLpHXL` Lx(HM@HX@I@Iҵ@I +@IB@HW)`HDžp0ZqH`HH0HpHXHLhL`LpLx HX(HhH5&qHUH`HH،CH5rHCH5uHCHA H5qHACHH;~CHHH 姉HMH +HUHuHuHPHHCHC0HKHSHC@H`Ht HhRqH}Ht H}@qLuHEMtLɛELqHHH;EuHHĘ[A\A]A^A_]UqrIH`Hu$H}Hu>H]HEHu]L +q Hh贁qH}Ht IH}HtH}蔁qH]HEHtIH]HEHtHEH]qL~q DUHAWAVSH8HIHHHE1HEEIL}ؾH1EHEоH EHEIW1HcDHEIG0@EH}HuHUHMLEg IHYHH;EuLH8[A^A_]qffff.UHHH BcHHxH@Ht]fq]fDUHSPHHcHH{HCHt5qHH[]'qfUHAVSIqHH{LMHbHHHL]DHbHH[A^]IHqL}q ffff.UHAWAVAUATSHH5HHEW)EEIIHEEminMgHhHUL'|DHhHDžhHtCt H{/qH'qA$Et H}qW)EHEEEmaxHhHULL{DHhHDžhHtCt H{~qH~qAEt H}~qAA.Gr'H+HH;EuHĈ[A\A]A^A_]~qw~qIHh,UH5}rH W}rH}LhHPHEAH}rHuLH'E1H5]HL:~q IALhMIIPt H`}qLeMt6HEL9t!HX@t Hx}qHI9uH}LLep}qEuEuLhMu&^H}M}qEtH}>}qLhMt:HpL9tEHX@t Hx}qHI9uHhLp|qEt4L}qL+zq LIEu IEt H}|qLyq UHHH b_HHxH@Ht]|q]fDUHSPHH0_HH{HCHtU|qHH[]G|qfUHAWAVAUATSPIIH}1L>EHLk1LL^DIHOILGEl$Ed$L2HI~GHuڃH9HOII)LH?H>LHH5fAnfAnHrI H9s!H I9sE1HzLIIfofoIIHHDGAHIHH)1fDA$(_(]$Ad(_(]dHHuMtA$_]L9tjHzLtfoC_fo]BLHL9t:foA_fo]foA_Tfo]\HH9uH<I|;fAnfAnHA(_(])HH9|H9RfAnfAnI)ILI I9sLI L9MIfofoIHIIENAHHM\HtIIL)1ff.Ad(_(]dA$(_(]$HHuMtHA$_]M9twLlj)HPH@tfoA_fo]HOH9tCf.foA_fo]foA_Tfo]\HH9uHEHH[A\A]A^A_]1M1M=Jffff.UHAVSIvxqHH"[HH{LUDHZHH[A^]IH4xqLtuq fff.UHAVSIxqHHZHH{LUDHYHH[A^]IHwqLuq fff.UHAVSIwqHHbZHH{L3UDH\YHH[A^]IHtwqLtq fff.UHAWAVATSHPMIIHHۈHHE؋EHEtm  uH3I$IMH}V$HEH}5 HrۈHH;EHP[A\A^A_]H3I$IMH}HEЋEȃ vH3I$IMH}HEЋEȃYH3I$IMH}HEЋEȃ<H3I$IMH}PHEЋEȃH3I$IMH}HEЋEȃ NvqUHAWAVAUATSHMIHHlڈHHEHtpHBHJ H)HtHH8HM)0tGIFIN H)HtH|H8rL覢M)0uׄ)@HuIHHGL^HILGHuڃH9HOII)LH?H>LHH(0(@,HrI H9s!H I9sE1HzLII((IIHHDGAHmIHH)1ffff.A(_(]AT(_(]THHuMtA_] L9tfHzLt(C_(]B LHL9t8(A_(] (A_D(]LHH9uH<I|/((HA(_(])HH9|H9>I)ILI I9sLI L9MI((IHIIEOAHHM\HtIIL)1AT(_(]TA(_(]HHuMtHA_] M9tsLlj)HPH@t(A_(] HOH9tAfff.(A_(] (A_D(]LHH9uHֈHH;Eu2HĨ[A\A]A^A_]1M1M9F"rqqqIHhkUH5-qrH iqrH}Lh\ W)PHDž` sqqH`(ׅ)PH scalar.HHHld be a HHHmin shouH@AHqrHuHPL*E1H5`HL=qqpqIHhUH5UprH prH}Lh` W)PHDž` pqH`(ׅ)PH scalar.HHHld be a HHHmax shouH@AHprHuHPLRE1H5HLepq IALeMIALhMIIALeMFIALhMnIIPt H`oqLeMt6HEL9t!HX@t HxboqHI9uH}LLeHoqEuEu LhMu-'H}"oqEtH}oqLhMHpL9HX@t HxnqHI9uIPt H`nqLeMt6HEL9t!HX@t HxnqHI9uH}LLe|nqEuEuLhMu&^H}YnqEtH}JnqLhMt:HpL9tEHX@t HxnqHI9uHhLpnqEtL'nqL7kq Lf.UHAWAVAUATSHMIHH\҈HHEHtpHBHJ H)HtHH8HM)0tGIFIN H)HtHH8L趝ۄM)0u$f)@H脝IHHGL轸HILGHuH9HOII)LH?LHHf(0f(@HrI H9s!H I9sE1HzLIIIHHHDOAHIIH)1fDfAfA\f(f_f(f_f(f]f(f]ffdfAT fA\0f(f_f(f_f(f]f(f]f\ fd0HHuMt0fAfA\f(f_f_f(f]f]ffDL9tsHzLtf(C_f(]B LHL9tCf.f(A_f(] f(A_Df(]LHH9uH<I|0DAf(f_f(f]f)HH9|H9 I)IH IH9s H IH9rqMIITHtJ<1fffff.fTff(f_f(f_f(f]f(f]f\f$HI9uM9tu)HPH@tf(A_f(] HOH9tDff.f(A_f(] f(A_Df(]LHH9uH`ΈHH;Eu"HĨ[A\A]A^A_]1MiqiqIHh7UH5hrH jrH}Lh\W)PHDž` ?iqH`(υ)PH scalar.HHHld be a HHHmin shouH@AHlirHuHPLE1H5,HL iqhqIHh_UH5!hrH DirH}Lh`W)PHDž` ghqH`(΅)PH scalar.HHHld be a HHHmax shouH@AHhrHuHPLE1H5THL1hq IALeMIALhMIIALeMFIALhMnIIPt H`SgqLeMt6HEL9t!HX@t Hx.gqHI9uH}LLegqEuEu LhMu-'H}fqEtH}fqLhMHpL9HX@t HxfqHI9uIPt H`fqLeMt6HEL9t!HX@t HxbfqHI9uH}LLeHfqEuEuLhMu&^H}%fqEtH}fqLhMt:HpL9tEHX@t HxeqHI9uHhLpeqEtLeqLcq LfDUHAWAVAUATSHLIIH,ʈHHEHtgHBHJ H)HtHH8HD Mt:IFIN H)HtHJH8@LND8 AMuAL6IILGHOIHHGHH rI I9LHI9E1HpL¨L9f.ADD8|DA8~A\A\DD8|$DA8"A\HH9uUDA8~މA\HH9u1IIAfnff8Afnf8IHHHrHH~H)1ff.AoAo\f8<f8<f88f88ATA\AoT Ao\0f8<f8<f88f88AT A\0H@HuHt/AoAo\f8<f8<f88f88ATA\L9t<HpL¨|C DD8|DA8~CLLHL9bHLjHH;EuHĈ[A\A]A^A_]1HccqbqIHheUH5'brH drH}Lh\W)PHDž` mbqH`(ȅ)PH scalar.HHHld be a HHHmin shouH@AHbrHuHPL$E1H5ZHL7bqaqIHhUH5OarH +crH}Lh`W)PHDž` aqH`(Dž)PH scalar.HHHld be a HHHmax shouH@AHarHuHPLLE1H5HL_aq IALeMIALhMIIALeMFIALhMnIIPt H``qLeMt6HEL9t!HX@t Hx\`qHI9uH}LLeB`qEuEu LhMu-'H}`qEtH} `qLhMHpL9HX@t Hx_qHI9uIPt H`_qLeMt6HEL9t!HX@t Hx_qHI9uH}LLev_qEuEuLhMu&^H}S_qEtH}D_qLhMt:HpL9tEHX@t Hx_qHI9uHhLp^qEtL!_qL1\q L@UHAWAVAUATSHLIIH\ÈHHEHtgHBHJ H)HtHH8HSD Mt:IFIN H)HtH>H84LD8 E1MuALIILGHIHHGHH rI I9LHI9E1HpL¨xL9f.ADD8rDA8rA\A\DD8r$DA8s"A\HH9uIDA8rމA\HH9u%IIAfnff8Afnf8IHHHrHH~H)1ff.AoAo\ffffATA\AoT Ao\0ffffAT A\0H@HuHt+AoAo\ffffATA\L9t<HpL¨C DD8rDA8rCLLHL9nHHH;EuHĈ[A\A]A^A_]1HgX\q\qIHh UH5c[rH ^rH}Lh\W)PHDž` [qH`(…)PH scalar.HHHld be a HHHmin shouH@AH[rHuHPL`E1H5HLs[q.[qIHhUH5ZrH *]rH}Lh`6W)PHDž` ZqH`(9)PH scalar.HHHld be a HHHmax shouH@AH[rHuHPLE1H5H'LZq IALeMIALhMIIALeMFIALhMnIIPt H`YqLeMt6HEL9t!HX@t HxYqHI9uH}LLe~YqEuEu LhMu-'H}XYqEtH}IYqLhMHpL9HX@t HxYqHI9uIPt H`XqLeMt6HEL9t!HX@t HxXqHI9uH}LLeXqEuEuLhMu&^H}XqEtH}XqLhMt:HpL9tEHX@t HxUXqHI9uHhLp:XqEtL]XqLmUq LUHAWAVAUATSHMIIHHHEIHt7HBHJ H)HtHVH8LHY}HMu 9I]Mt0IGIO H)HtHH8L}L(L}IIL/GL'IILGHƒHu 1Hu{H)1I<HH9|HLI9~HI<I|HH9|%HLI9"I|HH9u#f.LI9~HI|HH9uHtIH9HLI9INIH5HH;EuHĈ[A\A]A^A_]VqVqIHhUH5UrH DYrH}Lh\W)PHDž` $VqH`()PH scalar.HHHld be a HHHmin shouH@AHQVrHuHPLE1H5܈HzLUqUqIHhDUH5UrH lXrH}Lh`W)PHDž` LUqH`()PH scalar.HHHld be a HHHmax shouH@AHUrHuHPLE1H59ۈHLUq IALeMIALhMIIALeMFIALhMnIIPt H`8TqLeMt6HEL9t!HX@t HxTqHI9uH}LLeSqEuEu LhMu-'H}SqEtH}SqLhMHpL9HX@t HxSqHI9uIPt H`lSqLeMt6HEL9t!HX@t HxGSqHI9uH}LLe-SqEuEuLhMu&^H} +SqEtH}RqLhMt:HpL9tEHX@t HxRqHI9uHhLpRqEtLRqLOq Lff.UHAWAVAUATSHMIIH HHEHtgHBHJ H)HtH`H8VHsL(Mt:IGIO H)HtHH8L>HE1MuHL"IILGL;IILGHƒHu1H{H)1I<LL9rHHH9rHI<I|LL9r%HHH9s"I|HH9u#f.HH9rHI|HH9uHtIL9IBH9HBIHHH;EuHĈ[A\A]A^A_]CQqPqIHhTH5NPrH sTrH}Lh\W)PHDž` PqH`()PH scalar.HHHld be a HHHmin shouH@AHPrHuHPLKE1H5ֈHL^PqPqIHhTH5vOrH SrH}Lh`!W)PHDž` OqH`($)PH scalar.HHHld be a HHHmax shouH@AHPrHuHPLsE1H5ՈHLOq IALeMIALhMIIALeMFIALhMnIIPt H`NqLeMt6HEL9t!HX@t HxNqHI9uH}LLeiNqEuEu LhMu-'H}CNqEtH}4NqLhMHpL9HX@t HxNqHI9uIPt H`MqLeMt6HEL9t!HX@t HxMqHI9uH}LLeMqEuEuLhMu&^H}zMqEtH}kMqLhMt:HpL9tEHX@t Hx@MqHI9uHhLp%MqEtLHMqLXJq Lff.UHAWAVSH(HIIHHHEHHF H+FHH LqHE(()EH0D or 1DHHHld be 0DHHHsor shouHHHAxis tenH@HML#To0NLqHE()EHumSum opHH%Hthe CumSHH Hided to HHH be provHHHsor mustHHHAxis tenH@-HMLTHF0@tuFHJHc8 H=qH8H;L/#HIHHH;E@lKqHE()EHor `int6HH(Hnt32_t` HH H type `iHHHld be ofHHHsor shouHHHAxis tenH@04_t`@4HMLTEt H}JqHiHH;EuLH([A^A_] KqHEuHEu HEt H}JqHGq ff.UHAWAVATSH`IHHHEؿ(PJqHþ HFJqHHCHCXHC`HCXHCHHC@HC8HC0HC(HC HCPHCpHCxHCpHChƃHǃfǃHǃHǃƃHHǃHǃHǃHǃHǃHǃHǃHǃHǃHHHǃHǃHǃǃǃHǃ H]x@H5UqH}HUCI>w@I6}@HW)EHEHqHEHHHML HXHMH5xsHULPCH5LrHNLCH5TuuHMCHH HQH5fqHNCHH;dCCHHH CmHMHHUHuHuIIGIG0IOIWIG@H}Ht H}GqH]HEHtHFaEHGqH7HH;EuLH`[A\A^A_]GqIH]HEHt7H`EHOGqLDq IH}HuH]HEHuLhDq H}GqH]HEHt@UHAWAVATSH`IHHHEؿ(FqHþ HFqHHCHCXHC`HCXHCHHC@HC8HC0HC(HC HCPHCpHCxHCpHChƃHǃfǃHǃHǃƃHHǃHǃHǃHǃHǃHǃHǃHǃHǃHHHǃHǃHǃǃǃHǃ H]z@H5iRqH}H6RCIs@Iy@HW)EHE$EqHEHHHML HXHMH5,usHULMMCH5lIrHHCH5quHJCHH HQH5qH/KCHH;?CHHH iHMHhCHUHuHuIIGIG0IOIWIG@H}Ht H}MDqH]HEHtH]EH,DqHǨHH;EuLH`[A\A^A_]gDqIH]HEHt7H]EHCqLAq IH}HuH]HEHuL@q H}CqH]HEHt@UHAWAVATSH`IHHHEؿ(pCqHþ HfCqHHCHCXHC`HCXHCHHC@HC8HC0HC(HC HCPHCpHCxHCpHChƃHǃfǃHǃHǃƃHHǃHǃHǃHǃHǃHǃHǃHǃHǃHHHǃHǃHǃǃǃHǃ H]yp@H5NqH}HNCI^p@IVv@HW)EHEAqHEHHHML HXHMH5qsHULICH5ErHnECH5tnuHFCHH HQH5qHGCHH;<CHHH cfHMHjHUHuHuIIGIG0IOIWIG@H}Ht H}@qH]HEHtHfZEH@qHWHH;EuLH`[A\A^A_]@qIH]HEHt7HZEHo@qL=q IH}HuH]HEHuL=q H}5@qH]HEHt@UHAWAVATSH`IHHHEؿ(@qHþ H?qHHCHCXHC`HCXHCHHC@HC8HC0HC(HC HCPHCpHCxHCpHChƃHǃfǃHǃHǃƃHHǃHǃHǃHǃHǃHǃHǃHǃHǃHHHǃHǃHǃǃǃHǃ H] s@H5KqH}HVKCIl@Ir@HW)EHED>qHEHHHML HXHMH5LnsHULmFCH5BrHACH5kuH/CCHH HQH5qHODCHH;9CHHH bHMHhHUHuHuIIGIG0IOIWIG@H}Ht H}m=qH]HEHtHVEHL=qH硈HH;EuLH`[A\A^A_]=qIH]HEHt7HVEH<qL?:q IH}HuH]HEHuL:q H}<qH]HEHt@UHAWAVATSH`IH7HHEؿ(<qHþ H<qHHCHCXHC`HCXHCHHC@HC8HC0HC(HC HCPHCpHCxHCpHChƃHǃfǃHǃHǃƃHHǃHǃHǃHǃHǃHǃHǃHǃHǃHHHǃHǃHǃǃǃHǃ H]Yj@H5HqH}HGCI~i@Ivo@HW)EHE:qHEHHHML HXHMH5jsHULBCH5?rH>CH5guH?CHAH5~qH@CHH;5CHHH _HMHHUHuHuIIGIG0IOIWIG@H}Ht H}:qH]HEHtHSEH9qH~HH;EuLH`[A\A^A_]:qIH]HEHt7H@SEH9qL6q IH}HuH]HEHuL6q H}\9qH]HEHtff.UHAWAVATSH`IHǝHHEؿ( 9qHþ H9qHHCHCXHC`HCXHCHHC@HC8HC0HC(HC HCPHCpHCxHCpHChƃHǃfǃHǃHǃƃHHǃHǃHǃHǃHǃHǃHǃHǃHǃHHHǃHǃHǃǃǃHǃ H]l@H5DqH}HvDCIf@Il@HW)EHEd7qHEHHHML HXHMH5lgsHUL?CH5;rH;CH5$duHO<CHAH5={qHv=CHH;;2CHHH \HMHHUHuHuIIGIG0IOIWIG@H}Ht H}6qH]HEHtHPEHs6qHHH;EuLH`[A\A^A_]6qIH]HEHt7HOEH&6qLf3q IH}HuH]HEHuL?3q H}5qH]HEHtff.UHAWAVATSH`IHWHHEؿ(5qHþ H5qHHCHCXHC`HCXHCHHC@HC8HC0HC(HC HCPHCpHCxHCpHChƃHǃfǃHǃHǃƃHHǃHǃHǃHǃHǃHǃHǃHǃHǃHHHǃHǃHǃǃǃHǃ H]b@H59AqH}HACIb@Ih@HW)EHE3qHEHHHML HXHMH5csHUL<CH5<8rH7CH5`uH8CHAH5wqH:CHH;.CHHH XHMHHUHuHuIIGIG0IOIWIG@H}Ht H}$3qH]HEHtHLEH3qHHH;EuLH`[A\A^A_]>3qIH]HEHt7H`LEH2qL/q IH}HuH]HEHuL/q H}|2qH]HEHtff.UHAWAVATSH`IH疈HHEؿ(@2qHþ H62qHHCHCXHC`HCXHCHHC@HC8HC0HC(HC HCPHCpHCxHCpHChƃHǃfǃHǃHǃƃHHǃHǃHǃHǃHǃHǃHǃHǃHǃHHHǃHǃHǃǃǃHǃ H]Ie@H5=qH}H=CI._@I&e@HW)EHE0qHEHHHML HXHMH5`sHUL8CH54rH>4CH5D]uHo5CHAH5]tqH6CHH;[+CHHH :UHMH_HUHuHuIIGIG0IOIWIG@H}Ht H}/qH]HEHtH=IEH/qH.HH;EuLH`[A\A^A_]/qIH]HEHt7HHEHF/qL,q IH}HuH]HEHuL_,q H} /qH]HEHtff.UHAVSI .qHHLH[A^]IH.qL+q UHAWAVATSH@HIH4HHEL%FM&I~ DHsIIFIFHEW)EHEEHexclusivHEfEeH}HUHMH-,DEt H} .qH}uHEHwINHW)EHEEHEHreverseHEH}HUHMH+DHEHEH]HEHCt H{-qH-qH]HEHtCt H{c-qH[-qEt H}L-qH]HtLHECt H{,-qH$-qHHH;EuCH@[A\A^A_]HEEuHEHwIFHEH|HH;Et,-qIEt H},qH]HEHt&Ct H{,qH IEt H},qM&I~IFHtj,qL)q fUHHH HHxH@Ht]6,q]fDUHSPHHHH{HCHt,qHH[]+qfUHAWAVAUATSHIH`IHhHHE1LnEHHC H+CHp LnEIW)EHEH{ HH+{t[HHHH9 +Z+qILeLeIHEHHpHX H)H~LH,qILeHU1L DHH}ƭGHHpHHEHHMLHHHw HEHLcHH@JHW)PHDž`HHx H+xHHHH9 R*qILXLPIH`HHpHX H)H~LH+qLHHXKHP蹬GHxW)0HDž@LPHXL)t\IIHI9' H)qIL8L0KDH@H~LLH*qIL8W)HDž HH9LpL-)qHHHH H5҂HL*qHH`HxLXHHYHxHtHHxH$L0LHHHH HHHHW)HDžLpLV(qHHLN4LHL5(qLLHJW)HDžL'qILKHLL'qHHKHxH$HHL0LHH Ly'qHHt Ha'qH}Lpfffff.H`HXW)HDžL"'qIHLxHHIDLHM,LLL&qLLLKW)HDžL&qILHIHLL&qHLhO<W)HDžLZ&qHHHL<LHL9&qLHJHxHD$HH$HHHHLL0H%qL%qH%qHhHHHHW0%qH`(ʍ)PHa scalarHH Hator on HHHSum operHHHpply CumHHHCannot aH@(HPLSPH`IH}HkoHxt=HxH$L0L1HHHAE1W)HDžLpL~$qILLKHLL]$qHHIW)HDžL$$qILKHLL +$qHHM<HxH$HHL0LHH L#qHHt H#qIL;LpH`LpW)HDžLR#qHMgMMEHHL4LHL&#qLLHN<W)HDžL"qHHHL<LHL"qLIHhN$W)HDžL"qHHHL<LHLp"qLIN$HxHD$HH$HHHHLL0L H"qHh!qH!qIML;hLXIHHt H!qH0Ht H8!qHPHt HX!qH}Ht H}n!qH HH;EuLHĘ[A\A]A^A_]!qH}qH%rH qH1AT"!qIH0TH5%rH %rHPL0'HHHOHP1LHͿH5HoL q(HPqHq H0q It H Q qLeMt6HEL9t!HX@t Hx, qHI9uH}LLe qpt H} qPt H`qE1L0MuTHIAL0Mt:H8L9t5HX@t HxqHI9uH0L8qEu +/LILqHHDžHu#@IHHDžH"Ct H{&qHqH}H IHH HIHHIHHIHHxILLqHH9@IHH!(IHH!kIH0HkIP*H`IHHIHPHIH}HIHHqIHhHqHRIHFIHHtOIHHoqILL[qIHHCqHHuOH0Hu[HPHt HXqH}Ht H}qLAq IHHtHqH0HtH8qHPHuUHAWAVAUATSHMIH/HHEW)EHELH=NH0H(L HN,LJqILuKH]LL6qH]H(H0IMMOH HHIHEHMHEHMHL$H$H8HLH) L]MLhL`LxLpM)IMH}H@LXIt|HH1fDJIM9u<KDHLfHTHHTH;TuHDITHHuE1HL9uH}HD؃ItIHL)ِJIM9u KtHE1JIM9u KTHE1HuHtJIM9u KDHE1H@LXHt H}mqHpHt HxUqH}Ht H}CqH~HH;EuH[A\A]A^A_]|qH}yq HH}HuHH}Ht H}qH.q fDUHAWAVAUATSHHMLIIHHV~HHEHHJLLKIIHHHHH|$H$HHH.0I$IL$LLKIIwHEHuHEHuHt$H$HL +H}HHHHH LL)HH]L}L)HHHHHEHLeH0HHEHXLhLLxHHHHHSHLE1HH IL;uSHITH Hfffff.H\HH\I;\uHDI\H HuE1IH`HHHIM9uWHITHHHt8fDH\HH\I;\uHDH`I\HHuE1L;uH0HE1@HH IL;uHITH E1IH`HHHIM9uWHI\HHHt8fDH\HH\I;\uHDH`I\HHuE1L;]QHXHLLxHt H8rqHHt H ZqH}Ht H}HqH}Ht H}6qHzHH;EuHH[A\A]A^A_]oqHH}HuH}HuH:q H}qH}HtH}qHq ffff.UHAWAVAUATSHLMIIHLmH2zHHEHHJLLKIUI}HhHpHhHpH|$H$HHH*0I$IL$LLKIEIuHhHpHhHpHt$H$HLUIIOLLKIEIuHEHuHEHuHt$H$HhL*0H}HHHHH LL)HLULEM)IHLL)HHH(IHEHHEHHHHHH L]HXLhHHxLHHPHxHXHH`ILLH0IBH@HH8HBHHL0L1Hffffff.XHH HPHH;uSH(IDH Hffffff.IDHIDI;DuIDIDH Hu1HPH`HHHHXHH;uXH0ITHH@Ht:HDIDHIDI;DuIDH`IDHHu1HXHHHHHH`HH; uZH8ITHHHHt<HHDHHDI;DuHDHIDHHu1H`HH;ETHHE1XHH HPHH;uH(ITH 1HPH`HHHLXILHXL;ufH0IDHH@HtAHfff.IDHIDI;DuIDH`IDHHu1HXIHHHHH`HH; u^H8ITHHHHt@Hff.HDHHDI;DuHDHIDHHu1H`L;eHXHxHHPHHXHxH`HHt HqHHt HqH0Ht H8qHHt H qH}Ht H}oqH}Ht H}]qHsHH;EuH[A\A]A^A_]qHH0Hu(HHu4H}HuNH}HuWHI q H8qHHtH qH}Ht HH}HtH}qH}HtH}qH q UHAWAVAUATSH(MMHMHUHH3HUHCLcLkHC H{8H3HLuL}H}LLMM-HCPHEHC`HCXHCPM)t3MILH=uOLqHCPN$Lc`HL qLcXH3HHHUHMMMrH([A\A]A^A_]H} q IHEH8HuHEH8HuL +q H{Xv qHEH8HtH{@a qL +q fUHAWAVAUATSHHqHHEMIHFHH+HHHI)IL9HOH HWH)HH9M)IL9HLAHIffff.HJ\Mt +HyMI HH Mt"Hffffff.HELMwLH t蹿I DHLs袿fH L`HYHHHLHH tIHH>u^H"HHH!H Hy9HH9w2HHy1I)r17DHHH!HxHHy 1IsE1H L`HHJ\IHH MtHǾfHELMLH t虾I DALMs聾MGxDMLMfffff.DHH L`H.fLMjDALMHHBH HNH+HHLHN(H;u)HLHDH HA(HIH HA0HnHH;EuH[A\A]A^A_]< +q qIHP腷TH5SsH rHhLPHHAH+HH0L(H~rHEH\qHEHurHEH8HuH0HMLEL(HEAHrHhLH9E1H5oH؀LL q qIHP袶TH5"RsH *rHhLP HHAH+HH0H HAH+AHH(HrHEH[qHEHrHEH8HuH0HMLEL(HOAHWrHhLHCE1H5yHLVqqIHP謵TH5,QsH 4 rHhLPHHAH+HH0L(H rHEHZqHEH rHEH8HuH0HMLEL(HlAH rHhLH`E1H5H~Lsq IALPMILIALPMILIALPMnII8t HHqLmMt6HEL9t!HX@t HxwqHI9uH}LLm]qEuhu#LPMu36H}4qhtHxqLPMHXL9 HX@t HxqHI9uI8t HHqLmMt6HEL9t!HX@t HxqHI9uH}LLmqEuhu LPMu,dH}bqhtHxMqLPMt:HXL9t?HX@t Hx"qHI9uHPLXqELLI8t HHqLmMt6HEL9t!HX@t HxqHI9uH}LLmqEuhu LPMu,dH}tqhtHx_qLPMt:HXL9tEHX@t Hx4qHI9uHPLXqEtL<qLLq Lffffff.UHAWAVAUATSH8LLHHIHHShHHEH8HfHHHLH@H8LqHHEEL-gMuLI@L8L"qL=gILHDž(HDž HDžHDžDž0I$HvqHHHHH0HqHHH<qHHHޫHHHqHHH身HH0H$qHHHnLL8Lt H "qHqH59fHHqH8qHfHH;EuHH8[A\A]A^A_])qHLL8Lt H qH|q+HxHpHhH`HXHH5eHHpH8qH*HH8qHUHAVSI qHHLH[A^]IHqL)p UHAWAVATSH@HIHdeHHEL%vM&I~JCHIIFIFHEW)EHEEHexclusivHEfEeH}HUHMH]CEt H}<qH}uHEHwINHW)EHEEHEHreverseHEH}HUHMHCHEHEH]HEHCt H{pHpH]HEHtCt H{pHpEt H}|pH]HtLHECt H{\pHTpHcHH;EuCH@[A\A^A_]HEEuHEHwIFHEHcHH;Et\pIEt H}pH]HEHt&Ct H{pH IEt H}pM&I~IFHtpLp fUHHH BHHxH@Ht]fp]fDUHSPHHHH{HCHt5pHH[]'pfUHAWAVAUATSHIH`IHbHHE1LAEHHC H+CHp L@EIW)EHEH{ HH+{t[HHHH9 +pILeLeIHEHHpHX H)H~LHpILeHU1LCHH}GHHpHHEHHMLHHHw HEHLcHH@JHW)PHDž`HHx H+xHHHH9 pILXLPIH`HHpHX H)H~LHpLHHXKHP~GHxW)0HDž@LPHXL)t\IIHI9' HpIL8L0KDH@H~LLHpIL8W)HDž HH9LpL]pHHHH H5äHLpHH`HxLXHHYHxHtHHxH$L0LHHHH HHHHW)HDžLpLpHHLN4LHLepLLHJW)HDžL)pILKHLLpHHKHxH$HHL0LHH LpHHt HpH}Lpfffff.H`HXW)HDžLRpIHLxHHIDLHM,LLLpLLLKW)HDžLpILHIHLLpHLhO<W)HDžLpHHHL<LHLipLHJHxHD$HH$HHHHLL0HpLpHpHhHHHHW0pH`(_)PHa scalarHH Hator on HHHSum operHHHpply CumHHHCannot aH@(HPLSPH`IH}HkoHxt=HxH$L0L1HHHAE1W)HDžLpLpILLKHLLpHHIW)HDžLTpILKHLL:pHHM<HxH$HHL0LHH LpHHt HpIL;LpH`LpW)HDžLpHMgMMEHHL4LHLVpLLHN<W)HDžLpHHHL<LHLpLIHhN$W)HDžLpHHHL<LHLpLIN$HxHD$HH$HHHHLL0L H2pHh&pHpIML;hLXIHHt HpH0Ht H8pHPHt HXpH}Ht H}pH9XHH;EuLHĘ[A\A]A^A_]pH}pHqH qH1A&TRpIH0TH5qH qHPL0WHHHA!HP1LHH56yHjLp(HPpHp H0p It H pLeMt6HEL9t!HX@t Hx\pHI9uH}LLeBppt H}0pPt H`pE1L0MuTHIAL0Mt:H8L9t5HX@t HxpHI9uH0L8pEu +/LILpHHDžHu#@IHHDžH"Ct H{VpHNpH}H IHH HIHHIHHIHHxILLpHH9@IHH!(IHH!kIH0HkIP*H`IHHIHPHIH}HIHHpIHhHpHRIHFIHHtOIHHpILLpIHHspHHuOH0Hu[HPHt HXCpH}Ht 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HxpHI9uH}LLmpEuhu#LPMu36H}dphtHxOpLPMHXL9 HX@t HxpHI9uI8t HHpLmMt6HEL9t!HX@t HxpHI9uH}LLmpEuhu LPMu,dH}phtHx}pLPMt:HXL9t?HX@t HxRpHI9uHPLX7pELLI8t HH pLmMt6HEL9t!HX@t HxpHI9uH}LLmpEuhu LPMu,dH}phtHxpLPMt:HXL9tEHX@t HxdpHI9uHPLXIpEtLlpL|p Lffffff.UHAVSI pHHLH[A^]IHpL)p UHAWAVATSH@HIHd:HHEL%vM&I~JCH[IIFIFHEW)EHEEHexclusivHEfEeH}HUHMH]CEt H}<pH}uHEHwINHW)EHEEHEHreverseHEH}HUHMHCHEHEH]HEHCt H{pHpH]HEHtCt H{pHpEt H}|pH]HtLHECt H{\pHTpH8HH;EuCH@[A\A^A_]HEEuHEHwIFHEH8HH;Et\pIEt H}pH]HEHt&Ct H{pH IEt H}pM&I~IFHtpLp fUHHH BHHxH@Ht]fp]fDUHSPHHHH{HCHt5pHH[]'pfUHAWAVAUATSHIH`IH7HHE1LEHHC H+CHp LEIW)EHEH{ HH+{t[HHHH9 +pILeLeIHEHHpHX H)H~LHpILeHU1LCHH}TGHHpHHEHHMLHHHw HEHLcHH@JHW)PHDž`HHx H+xHHHH9 pILXLPIH`HHpHX H)H~LHpLHHXKHPSGHxW)0HDž@LPHXL)t\IIHI9' HpIL8L0KDH@H~LLHpIL8W)HDž HH9LpL]pHHHH H5yHLpHH`HxLXHHYHxHtHHxH$L0LHHHH HHHHW)HDžLpLpHHLN4LHLepLLHJW)HDžL)pILKHLLpHHKHxH$HHL0LHH LpHHt HpH}Lpfffff.H`HXW)HDžLRpIHLxHHIDLHM,LLLpLLLKW)HDžLpILHIHLLpHLhO<W)HDžLpHHHL<LHLipLHJHxHD$HH$HHHHLL0HpLpHpHhHHHHW0pH`(4)PHa scalarHH Hator on HHHSum operHHHpply CumHHHCannot aH@(HPLSPH`IH}HkoHxt=HxH$L0L1HHHAE1W)HDžLpLpILLKHLLpHHIW)HDžLTpILKHLL:pHHM<HxH$HHL0LHH LpHHt HpIL;LpH`LpW)HDžLpHMgMMEHHL4LHLVpLLHN<W)HDžLpHHHL<LHLpLIHhN$W)HDžLpHHHL<LHLpLIN$HxHD$HH$HHHHLL0L H2pHh&pHpIML;hLXIHHt HpH0Ht H8pHPHt HXpH}Ht H}pH9-HH;EuLHĘ[A\A]A^A_]pH}pHqH qH1A&vTRpIH0uTH5qH qHPL0WdHHHAHP1LHfH56NH?Lp(HPpHp H0p It H pLeMt6HEL9t!HX@t Hx\pHI9uH}LLeBppt H}0pPt H`pE1L0MuTHlIAL0Mt:H8L9t5HX@t HxpHI9uH0L8pEu +/LILpHHDžHu#@IHHDžH"Ct H{VpHNpH}H IHH HIHHIHHIHHxILLpHH9@IHH!(IHH!kIH0HkIP*H`IHHIHPHIH}HIHHpIHhHpHRIHFIHHtOIHHpILLpIHHspHHuOH0Hu[HPHt HXCpH}Ht H}1pLqp IHHtH pH0HtH8pHPHuUHAWAVAUATSHMIH_(HHEW)EHELH=NH0H(L HN,LzpILuKH]LLfpH]H(H0IMMOH HHIHEHMHEHMHL$H$H8HLH L]MLhL`LxLpM)IMH}H@LXIt|HH1fDJIM9u<KDHLfHTHHTH;TuHDITHHuE1HL9uH}HD؃ItIHL)ِJIM9u KtHE1JIM9u KTHE1HuHtJIM9u KDHE1H@LXHt H}pHpHt HxpH}Ht H}spH&HH;EuH[A\A]A^A_]pH}詾p HH}HuHH}Ht H}pH^p fDUHAWAVAUATSHHMLIIHH%HHEHHJLLKIIHHHHH|$H$HHH/I$IL$LLKIIwHEHuHEHuHt$H$HLg +H}HHHHH LL)HH]L}L)HHHHHEHLeH0HHEHXLhLLxHHHHHSHLE1HH IL;uSHITH Hfffff.H\HH\I;\uHDI\H HuE1IH`HHHIM9uWHITHHHt8fDH\HH\I;\uHDH`I\HHuE1L;uH0HE1@HH IL;uHITH E1IH`HHHIM9uWHI\HHHt8fDH\HH\I;\uHDH`I\HHuE1L;]QHXHLLxHt H8袽pHHt H 芽pH}Ht H}xpH}Ht H}fpH"HH;EuHH[A\A]A^A_]蟽pHH}HuH}HuHjp H}pH}HtH}pHEp ffff.UHAWAVAUATSHLMIIHLmHb!HHEHHJLLKIUI}HhHpHhHpH|$H$HHH/I$IL$LLKIEIuHhHpHhHpHt$H$HL5IIOLLKIEIuHEHuHEHuHt$H$HhL7/H}HHHHH LL)HLULEM)IHLL)HHH(IHEHHEHHHHHH L]HXLhHHxLHHPHxHXHH`ILLH0IBH@HH8HBHHL0L1Hffffff.HH HPHH;uIH(IDH HDIDHIDI;DuIDIDH Hu1HPH`HHHHXHH;uXH0ITHH@Ht:HDIDHIDI;DuIDH`IDHHu1HXHHHHHH`HH; uZH8ITHHHHt<HHDHHDI;DuHDHIDHHu1H`HH;EdHHE1HH HPHH;uH(ITH 1HPH`HHHLXILHXL;u\H0IDHH@Ht7HfIDHIDI;DuIDH`IDHHu1HXIHHHHH`HH; u^H8ITHHHHt@Hff.HDHHDI;DuHDHIDHHu1H`L;eHXHxHHPHHXHxH`HHt HpHHt HpH0Ht H8pHHt H ѶpH}Ht H}迶pH}Ht H}譶pHHHH;EuH[A\A]A^A_]pHH0Hu(HHu4H}HuNH}HuWH虳p H8CpHHtH +pH}Ht HH}HtH} pH}HtH}pH9p UHAWAVAUATSH(MMHMHUHH3H0HCLcLkHC H{8H3HLuL}H}LLMM7R-HCPHEHC`HCXHCPM)t3MILH=uOLTpHCPN$Lc`HLCpLcXH3HHHUHMMMrH([A\A]A^A_]H}^p IHEH8HuHEH8HuLp H{XƴpHEH8HtH{@豴pLp fUHAWAVAUATSHH%HHEMIHFHH+HHHI)IL9HOH HWH)HH9M)IL9HLAHIffff.HJ\Mt +HyegMI HH Mt"HDgffffff.HELMwLH t gI DHLsffH L`HYHHHLHH tIHH>u^H"HHH!H Hy9HH9w2HHy1I)r17DHHH!HxHHy]f1IsQfE1H L`HHJ\IHH MtHffHELMLH teI DALMseMGxDMLMfffff.DHH L`H~efLMjDALMHHBH HNH+HHLHN(H;u)HLHDH HA(HIH HA0HHH;EuH[A\A]A^A_]茱p:pIHP^TH5UrH qHhLP?MHHAH+HH0L(HζqHEH"qHEHŶqHEH8HuH0HMLEL(H蕬AHdqHhLHOE1H56H((L蜰pWpIHP]TH5rrH &qHhLP\LHHAH+HH0H HAH+AHH(HصqHEH,qHEHqHEH8HuH0HMLEL(H蟫AHqHhLHNE1H55H2'L覯papIHP\TH5|rH 0qHhLPfKHHAH+HH0L(HqHEHIqHEHFqHEH8HuH0HMLEL(H輪AHqHhLHME1H54HO&Lîp IALPMILIALPMILIALPMnII8t HHpLmMt6HEL9t!HX@t HxǭpHI9uH}LLm譭pEuhu#LPMu36H}脭phtHxopLPMHXL9 HX@t Hx<pHI9uI8t HHpLmMt6HEL9t!HX@t HxpHI9uH}LLmجpEuhu LPMu,dH}責phtHx蝬pLPMt:HXL9t?HX@t HxrpHI9uHPLXWpELLI8t HH)pLmMt6HEL9t!HX@t HxpHI9uH}LLmpEuhu LPMu,dH}īphtHx诫pLPMt:HXL9tEHX@t Hx脫pHI9uHPLXipEtL茫pL蜨p Lffffff.UHAVSI 6pHHLH[A^]IH pLIp UHAWAVATSH@HIHHHEL%M&I~jCHێIIFIFHEW)EHEEHexclusivHEfEeH}HUHMH}CEt H}\pH}uHEHwINHW)EHEEHEHreverseHEH}HUHMHCHEHEH]HEHCt H{۩pHөpH]HEHtCt H{賩pH諩pEt H}蜩pH]HtLHECt H{|pHtpHHH;EuCH@[A\A^A_]HEEuHEHwIFHEH HH;Et|pIEt H} +pH]HEHt&Ct H{pH IEt H}ӨpM&I~IFHt躨pLp fUHHH bHHxH@Ht]醨p]fDUHSPHH0HH{HCHtUpHH[]GpfUHAWAVAUATSHIH`IH HHE1L'DHHC H+CHp LDIW)EHEH{ HH+{t[HHHH9 +誧pILeLeIHEHHpHX H)H~LHpILeHU1LCHH}*GHHpHHEHHMLHH ZHw HEHLcHH@JHW)PHDž`HHx H+xHHHH9 袦pILXLPIH`HHpHX H)H~LHާpLHHXKHP )GHxW)0HDž@LPHXL)t\IIHI9' HpIL8L0KDH@H~LLH<pIL8W)HDž HH9LpL}pHHHH H5NHLަpHH`HxLXHHYHxHtHHxH$L0LHHHH HHHHW)HDžLpL覤pHHLN4LHL腤pLLHJW)HDžLIpILKHLL/pHHKHxH$HHL0LHH LɣpHHt H豣pH}Lpfffff.H`HXW)HDžLrpIHLxHHIDLHM,LLL<pLLLKW)HDžLpILHIHLLߢpHLhO<W)HDžL誢pHHHL<LHL艢pLHJHxHD$HH$HHHHLL0HpLpHpHhHHHHW0pH`( +)PHa scalarHH Hator on HHHSum operHHHpply CumHHHCannot aH@(HPL1qSPH`IH}HkoHxt=HxH$L0L1HHHAE1W)HDžLpLΠpILLKHLL譠pHHIW)HDžLtpILKHLLZpHHM<HxH$HHL0LHH LpHHt 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L+BH HLLt H(m}tIuH`HHH+HH@誦\H@HHHH)t<H11HH<uHHHH9rDH9@HHH9rHH}2DH@HHH)uH]'HH]H1fH<H<H<HH9rW) MuHDž0L}LH)t\IILH=%mIL(L KH0I)ML~LHLmML(H LL*BH HLt H($mH@Ht HH mH`Ht HhmHHt HmHHt HmHHt HmH}Ht H}mH Ht H(mH@Ht HHjmH`Ht HhRmMtL0DL=mMtL0DL(mHJHH;E?LHĈ[A\A]A^A_]HHHHAHHAHHtH@HLH@0H$HHLL蝎LHDžHtsH0DHtmHHDžHtH/DHMmHH!HHCH HHPHmHDžHHuIuHHAHHAHHtH@HLH0H$H HH@L蕍H HDž I]IEHtHH/DHdmH HDž Ht,H.DH=mHHu HDž HHHHCHHHPHmH@H0mmIH~QH5nH #nH}L7W)HDž0mH()Hdo not aHHH shapes HHHp: InputHHHEinsum oH@ lign@$AHnHuHLC9E1H59iHL6msmIH}QH5nH 6nH}L6W)HDž`mHH({)H5knWHmCWAH:nHuHL}8E1H5shHLpm+mIH`|QH5-nH pnH}L`gS5HQDHHnH HnHHnHH@H HLLHHdAHnHuLH7E1H5gH:LmImIH`{QH5KnH nH}L`iq4LPDHH\nH H\nHH@H HLHHk+AHnHuLH6E1H5fHqLmmIH`+{QH5nH nH}L`x3HnH H<nHHnHH@H HLHHL蜺AHinHuLH6E1H5eHLm6H m(HmHm H m IAL`MPIIALmMIAL`M9I:IALmM_IAL`MIIAL}MDIALMlI@t HPmLuMt6HEL9t!HX@t Hx`mHI9uH}LLuFmEuEuL`Mu&^H}#mEtH}mL`Mt:HhL9tIHX@t HxmHI9uH`LhmE -LmLm LI@t HPmLmMt6HEL9t!HX@t HxqmHI9uH}LLmWmEuEuL`Mu&^H}4mEtH}%mL`Mt:HhL9tIHX@t HxmHI9uH`LhmE LmLm LI@t HPmLmMt6HEL9t!HX@t HxmHI9uH}LLmhmEuEuL`Mu&^H}EmEtH}6mL`Mt:HhL9tIHX@t Hx mHI9uH`LhmELmLm LIt HmL}Mt6HEL9t!HX@t HxmHI9uH}LL}ymEuEuLMu&~H}VmEtH}GmLMtZHL9wHX@t HxmHI9uIAL}MuRIALME=IIt HmL}Mt6HEL9t!HX@t HxmHI9uH}LL}tmEELMoHL9HX@t Hx-mHI9uHLmEnL1mHH HH}mErH}mLMiLLmEIHHHHCHHHPHdmIH HjIH HRIHHIHHIH@HAHIHHttHHCHubHHPHmOIHHtwHHCHueHHPHmRIHHt H`mHHHIHHt H)mHHHIH@HSZIH@H;BIH@H#*IH@H IH@HIH HuIH HH(bmIHHt#HHCHuHHPH/mHHtHmH HuRIH HtCH(5IH@Hu7AIHHHHtH]!DHmH@Ht HHmH`HHhmLHHIHHIHHIHHIHHIHHkrIHHyIHHahIHHIPIHH18I11HH H3I11HH@H I11HH`H IHHIHHIHHt6{IHHt#HHCHuHHPHmH}Ht H}mHH HJ8IHHIHH HH(>mH@HHH"mH`HHhmHHDHmHHIHHu)3ILHHuIHHt HmLHHt HymHHHHt HSmH}Hu_H HH@HH`HHHHtHDHmL5m H}mH HtUHAVSH0IHH87HHEI9tH{ H9t.IF I9tKHC I~ H 7HH;EH0[A^]M9v tTHLPH{ HP IF HC HHHQI~ HP HC IF H[ H6HH;EtpHHuPH{ HP HC I~ HHPI~ HP IF H[ HEH}LPHEH}P Mv H86HH;E-mH.H.fDUHAVSH0IHH5HHEI9tH{ H9t.IF I9tKHC I~ H5HH;EH0[A^]M9v tTHLPH{ HP IF HC HHHQI~ HP HC IF H[ Hf5HH;EtpHHuPH{ HP HC I~ HHPI~ HP IF H[ HEH}LPHEH}P Mv H4HH;E-ĽmHn-Hf-fDUHAVSH0IHH4HHEI9tH{ H9t.IF I9tKHC I~ H4HH;EH0[A^]M9v tTHLPH{ HP IF HC HHHQI~ HP HC IF H[ H&4HH;EtpHHuPH{ HP HC I~ HHPI~ HP IF H[ HEH}LPHEH}P Mv H3HH;E-脼mH.,H&,fDUHAWAVAUATSH8LLHHIHHS3HHEH8H1HHHLH@H8L7mHHEEL-2MuLI@L8LBmL=2ILHDž(HDž HDžHDžDž0I$H薽mHHHX.HHHrmHHH4.HHIDHHH;mHHH-HH0HYmHHH3LL8Lt H EmH%mH5<1HHmH8ȹmH1HH;EuHH8[A\A]A^A_]LmHLL8Lt H 迹mH蟸m+H)H)H)H)H)HH50HH mH8mHm)HH8mHV)fDUHAWAVAUATSHILgLoLL)HH9LM)MII6HH=HM)LHHH9H}LE -II9LBMDHuI9诸mHH5DnHmH/HHH5.H-H诸mLHHr IGL9`ILHL9MLCHHtHIHHHHuI@IHIHPIHPIHPIHP IHP(IHP0IHP8H@HuTHuIJ<谷mIHuO LHHr IOL9)ILHL9HZHHt$Hffffff.IHHHHuHj@IHIHAIHAIHAIHA IHA(IHA0IHA8H@Hu IIIPHHAHA~fpDHPH)1fDAADAD AD0HHuHtA~fpDAADI9IHGHHHHHHDBAH%A~fpDK|0IHH)1fffff.DDDHHuMtA~fpDAADH9O4M<MH]~LHLM,mMHELLxLpHtHH[A\A]A^A_]ymH[A\A]A^A_]E1E1KHL)LCHH3I HH)HZHH1H1M.`mIHmL/m UHAVSH0IHHH,HHEI9tH{ H9t.IF I9tKHC I~ H,HH;EH0[A^]M9v tTHLPH{ HP IF HC HHHQI~ HP HC IF H[ H+HH;EtpHHuPH{ HP HC I~ HHPI~ HP IF H[ HEH}LPHEH}P Mv HH+HH;E-mH#H#fDUHAVSH0IHH+HHEI9tH{ H9t.IF I9tKHC I~ H*HH;EH0[A^]M9v tTHLPH{ HP IF HC HHHQI~ HP HC IF H[ Hv*HH;EtpHHuPH{ HP HC I~ HHPI~ HP IF H[ HEH}LPHEH}P Mv H*HH;E-ԲmH~"Hv"fDUHAVSH0IHH)HHEI9tH{ H9t.IF I9tKHC I~ H)HH;EH0[A^]M9v tTHLPH{ HP IF HC HHHQI~ HP HC IF H[ H6)HH;EtpHHuPH{ HP HC I~ HHPI~ HP IF H[ HEH}LPHEH}P Mv H(HH;E-蔱mH>!H6!fDUHH)HHGHHwHH]n%Sfffff.UHAVSHPIH[(HHE(԰mHþ HʰmHHCHCXHC`HCXHCHHC@HC8HC0HC(HC HCPHCpHCxHCpHChƃHǃfǃHǃHǃƃHHǃHǃHǃHǃHǃHǃHǃHǃHǃHHHǃHǃHǃǃǃHǃ H]m<H5]mH}H?H5mH?H5qH,?HH HQH5CmHL?HH;?HHH HMHsHUHuHuIIFIF0INIVIF@H]HEHtHEAH苮mH&HH;Eu LHP[A^]ʮmIH]HEHtHAHFmL膫m fffff.UHAVSHPIH%HHE(mHþ H -mHHCHCXHC`HCXHCHHC@HC8HC0HC(HC HCPHCpHCxHCpHChƃHǃfǃHǃHǃƃHHǃHǃHǃHǃHǃHǃHǃHǃHǃHHHǃHǃHǃǃǃHǃ H]<H5mH}H:?H5mH;?H5qHl?HH HQH5mH茮?HH;Q?HHH @HMHHUHuHuIIFIF0INIVIF@H]HEHtHAH˫mHF#HH;Eu LHP[A^] -mIH]HEHtH@AH膫mLƨm fffff.UHAVSHPIH"HHE(TmHþ HJmHHCHCXHC`HCXHCHHC@HC8HC0HC(HC HCPHCpHCxHCpHChƃHǃfǃHǃHǃƃHHǃHǃHǃHǃHǃHǃHǃHǃHǃHHHǃHǃHǃǃǃHǃ H]-<H5ݶmH}Hz?H5HmH{?H5qH謪?HH HQH5mH̫?HH;葠?HHH HMHHUHuHuIIFIF0INIVIF@H]HEHtHAH mH HH;Eu LHP[A^]JmIH]HEHtHAHƨmLm fffff.UHAVSHPIH HHE(蔨mHþ H芨mHHCHCXHC`HCXHCHHC@HC8HC0HC(HC HCPHCpHCxHCpHChƃHǃfǃHǃHǃƃHHǃHǃHǃHǃHǃHǃHǃHǃHǃHHHǃHǃHǃǃǃHǃ H]m<H5mH}H躯?H5mH軦?H5FqH?HH HQH5mH ?HH;ѝ?HHH ޅHMHHUHuHuIIFIF0INIVIF@H]HEHtHAHKmHHH;Eu LHP[A^]芦mIH]HEHtHAHmLFm fffff.UHAVSHPIH[HHE(ԥmHþ HʥmHHCHCXHC`HCXHCHHC@HC8HC0HC(HC HCPHCpHCxHCpHChƃHǃfǃHǃHǃƃHHǃHǃHǃHǃHǃHǃHǃHǃHǃHHHǃHǃHǃǃǃHǃ H]m<H5]mH}H?H5mH?H5qH,?HH HQH5CmHL?HH;?HHH ܅HMH5HUHuHuIIFIF0INIVIF@H]HEHtHEAH苣mHHH;Eu LHP[A^]ʣmIH]HEHtHAHFmL膠m fffff.UHAVSHPIHHHE(mHþ H -mHHCHCXHC`HCXHCHHC@HC8HC0HC(HC HCPHCpHCxHCpHChƃHǃfǃHǃHǃƃHHǃHǃHǃHǃHǃHǃHǃHǃHǃHHHǃHǃHǃǃǃHǃ H]<H5mH}H:?H5mH;?H5qHl?HH HQH5mH茣?HH;Q?HHH @مHMHգHUHuHuIIFIF0INIVIF@H]HEHtH腺AHˠmHFHH;Eu LHP[A^] -mIH]HEHtH@AH膠mLƝm fffff.UHAVSHPIHHHE(TmHþ HJmHHCHCXHC`HCXHCHHC@HC8HC0HC(HC HCPHCpHCxHCpHChƃHǃfǃHǃHǃƃHHǃHǃHǃHǃHǃHǃHǃHǃHǃHHHǃHǃHǃǃǃHǃ H]-<H5ݫmH}Hz?H5HmH{?H5qH謟?HH HQH5mH̠?HH;葕?HHH օHMHuHUHuHuIIFIF0INIVIF@H]HEHtHŷAH mHHH;Eu LHP[A^]JmIH]HEHtH耷AHƝmLm fffff.UHAVSHPIHHHE(蔝mHþ H芝mHHCHCXHC`HCXHCHHC@HC8HC0HC(HC HCPHCpHCxHCpHChƃHǃfǃHǃHǃƃHHǃHǃHǃHǃHǃHǃHǃHǃHǃHHHǃHǃHǃǃǃHǃ H]m<H5mH}H躤?H5mH軛?H5FqH?HH HQH5mH ?HH;ђ?HHH ӅHMHHUHuHuIIFIF0INIVIF@H]HEHtHAHKmHHH;Eu LHP[A^]芛mIH]HEHtHAHmLFm fffff.UHAVSHPIH[HHE(ԚmHþ HʚmHHCHCXHC`HCXHCHHC@HC8HC0HC(HC HCPHCpHCxHCpHChƃHǃfǃHǃHǃƃHHǃHǃHǃHǃHǃHǃHǃHǃHǃHHHǃHǃHǃǃǃHǃ H]m<H5]mH}H?H5mH?H5qH,?HAH5JmHS?HH;?HHH хHMHHUHuHuIIFIF0INIVIF@H]HEHtHLAH蒘mH HH;Eu LHP[A^]јmIH]HEHtHAHMmL荕m DUHAVSHPIHHHE($mHþ HmHHCHCXHC`HCXHCHHC@HC8HC0HC(HC HCPHCpHCxHCpHChƃHǃfǃHǃHǃƃHHǃHǃHǃHǃHǃHǃHǃHǃHǃHHHǃHǃHǃǃǃHǃ H]<H5mH}HJ?H5mHK?H5qH|?HAH5mH裘?HH;h?HHH W΅HMHlHUHuHuIIFIF0INIVIF@H]HEHtH蜯AHmH] HH;Eu LHP[A^]!mIH]HEHtHWAH蝕mLݒm DUHAVSHPIH HHE(tmHþ HjmHHCHCXHC`HCXHCHHC@HC8HC0HC(HC HCPHCpHCxHCpHChƃHǃfǃHǃHǃƃHHǃHǃHǃHǃHǃHǃHǃHǃHǃHHHǃHǃHǃǃǃHǃ H]M<H5mH}H蚜?H5hmH蛓?H5&qH̔?HAH5mH?HH;踊?HHH ˅HMHHUHuHuIIFIF0INIVIF@H]HEHtHAH2mH -HH;Eu LHP[A^]qmIH]HEHtH觬AHmL-m DUHAVSHPIHK -HHE(ĒmHþ H躒mHHCHCXHC`HCXHCHHC@HC8HC0HC(HC HCPHCpHCxHCpHChƃHǃfǃHǃHǃƃHHǃHǃHǃHǃHǃHǃHǃHǃHǃHHHǃHǃHǃǃǃHǃ H]<H5MmH}H?H5mH?H5vqH?HAH5:mHC?HH;?HHH ȅHMH̕HUHuHuIIFIF0INIVIF@H]HEHtH<AH肐mHHH;Eu LHP[A^]mIH]HEHtHAH=mL}m DUHAVSHPIHHHE(mHþ H -mHHCHCXHC`HCXHCHHC@HC8HC0HC(HC HCPHCpHCxHCpHChƃHǃfǃHǃHǃƃHHǃHǃHǃHǃHǃHǃHǃHǃHǃHHHǃHǃHǃǃǃHǃ H]譹<H5mH}H:?H5nH;?H5ƻqHl?HH HQH5mH茐?HH;Q?HHH @ƅHMHuHUHuHuIIFIF0INIVIF@H]HEHtH腧AHˍmHFHH;Eu LHP[A^] -mIH]HEHtH@AH膍mLƊm fffff.UHAVSHPIHHHE(TmHþ HJmHHCHCXHC`HCXHCHHC@HC8HC0HC(HC HCPHCpHCxHCpHChƃHǃfǃHǃHǃƃHHǃHǃHǃHǃHǃHǃHǃHǃHǃHHHǃHǃHǃǃǃHǃ H]<H5ݘmH}Hz?H5ղnH{?H5qH謌?HH HQH5mH̍?HH;葂?HHH ÅHMHeHUHuHuIIFIF0INIVIF@H]HEHtHŤAH mHHH;Eu LHP[A^]JmIH]HEHtH耤AHƊmLm fffff.UHAVSHPIHHHE(蔊mHþ H芊mHHCHCXHC`HCXHCHHC@HC8HC0HC(HC HCPHCpHCxHCpHChƃHǃfǃHǃHǃƃHHǃHǃHǃHǃHǃHǃHǃHǃHǃHHHǃHǃHǃǃǃHǃ H]m<H5mH}H躑?H5nH軈?H5FqH?HH HQH5mH ?HH;?HHH HMHHUHuHuIIFIF0INIVIF@H]HEHtHAHKmHHH;Eu LHP[A^]芈mIH]HEHtHAHmLFm fffff.UHAVSHPIH[HHE(ԇmHþ HʇmHHCHCXHC`HCXHCHHC@HC8HC0HC(HC HCPHCpHCxHCpHChƃHǃfǃHǃHǃƃHHǃHǃHǃHǃHǃHǃHǃHǃHǃHHHǃHǃHǃǃǃHǃ H]譶<H5]mH}H?H5UnH?H5qH,?HH HQH5CmHL?HH;}?HHH HMHHUHuHuIIFIF0INIVIF@H]HEHtHEAH苅mHHH;Eu LHP[A^]ʅmIH]HEHtHAHFmL膂m fffff.UHAVSHPIHHHE(mHþ H -mHHCHCXHC`HCXHCHHC@HC8HC0HC(HC HCPHCpHCxHCpHChƃHǃfǃHǃHǃƃHHǃHǃHǃHǃHǃHǃHǃHǃHǃHHHǃHǃHǃǃǃHǃ H]譮<H5mH}H:?H5nH;?H5ưqHl?HH HQH5mH茅?HH;Qz?HHH @HMHuHUHuHuIIFIF0INIVIF@H]HEHtH腜AH˂mHFHH;Eu LHP[A^] -mIH]HEHtH@AH膂mLm fffff.UHAVSHPIHHHE(TmHþ HJmHHCHCXHC`HCXHCHHC@HC8HC0HC(HC HCPHCpHCxHCpHChƃHǃfǃHǃHǃƃHHǃHǃHǃHǃHǃHǃHǃHǃHǃHHHǃHǃHǃǃǃHǃ H]<H5ݍmH}Hz?H5էnH{?H5qH謁?HH HQH5mĤ?HH;w?HHH HMHHUHuHuIIFIF0INIVIF@H]HEHtHřAH mHHH;Eu LHP[A^]JmIH]HEHtH耙AHmL}m fffff.UHAVSHPIHHHE(mHþ HmHHCHCXHC`HCXHCHHC@HC8HC0HC(HC HCPHCpHCxHCpHChƃHǃfǃHǃHǃƃHHǃHǃHǃHǃHǃHǃHǃHǃHǃHHHǃHǃHǃǃǃHǃ H]m<H5mH}H躆?H5nH}?H5FqH~?HH HQH5mH ?HH;t?HHH HMHHUHuHuIIFIF0INIVIF@H]HEHtHAHK}mHHH;Eu LHP[A^]}mIH]HEHtHAH}mLFzm fffff.UHAVSHPIH[HHE(|mHþ H|mHHCHCXHC`HCXHCHHC@HC8HC0HC(HC HCPHCpHCxHCpHChƃHǃfǃHǃHǃƃHHǃHǃHǃHǃHǃHǃHǃHǃHǃHHHǃHǃHǃǃǃHǃ H]譫<H5]mH}H?H5UnHz?H5qH,|?HH HQH5CmHL}?HH;r?HHH HMHUHUHuHuIIFIF0INIVIF@H]HEHtHEAHzmHHH;Eu LHP[A^]zmIH]HEHtHAHFzmLwm fffff.UHAVSHPIHHHE(zmHþ H -zmHHCHCXHC`HCXHCHHC@HC8HC0HC(HC HCPHCpHCxHCpHChƃHǃfǃHǃHǃƃHHǃHǃHǃHǃHǃHǃHǃHǃHǃHHHǃHǃHǃǃǃHǃ H]譣<H5mH}H:?H5nH;x?H5ƥqHly?HAH5mHz?HH;Xo?HHH GHMHHUHuHuIIFIF0INIVIF@H]HEHtH茑AHwmHMHH;Eu LHP[A^]xmIH]HEHtHGAHwmLtm DUHAVSHPIHHHE(dwmHþ HZwmHHCHCXHC`HCXHCHHC@HC8HC0HC(HC HCPHCpHCxHCpHChƃHǃfǃHǃHǃƃHHǃHǃHǃHǃHǃHǃHǃHǃHǃHHHǃHǃHǃǃǃHǃ H]<H5mH}H~?H5nHu?H5qHv?HAH5ڹmHw?HH;l?HHH HMHHUHuHuIIFIF0INIVIF@H]HEHtH܎AH"umHHH;Eu LHP[A^]aumIH]HEHtH藎AHtmLrm DUHAVSHPIH;HHE(tmHþ HtmHHCHCXHC`HCXHCHHC@HC8HC0HC(HC HCPHCpHCxHCpHChƃHǃfǃHǃHǃƃHHǃHǃHǃHǃHǃHǃHǃHǃHǃHHHǃHǃHǃǃǃHǃ H]荝<H5=mH}H{?H55nHr?H5fqH t?HAH5*mH3u?HH;i?HHH 窅HMH\HUHuHuIIFIF0INIVIF@H]HEHtH,AHrrmHHH;Eu LHP[A^]rmIH]HEHtHAH-rmLmom DUHAVSHPIHHHE(rmHþ HqmHHCHCXHC`HCXHCHHC@HC8HC0HC(HC HCPHCpHCxHCpHChƃHǃfǃHǃHǃƃHHǃHǃHǃHǃHǃHǃHǃHǃHǃHHHǃHǃHǃǃǃHǃ H]ݠ<H5}mH}H*y?H5nH+p?H5qH\q?HAH5zmHr?HH;Hg?HHH 7HMH HUHuHuIIFIF0INIVIF@H]HEHtH|AHomH=HH;Eu LHP[A^]pmIH]HEHtH7AH}omLlm DUHAVSHPIHHHE(TomHþ HJomHHCHCXHC`HCXHCHHC@HC8HC0HC(HC HCPHCpHCxHCpHChƃHǃfǃHǃHǃƃHHǃHǃHǃHǃHǃHǃHǃHǃHǃHHHǃHǃHǃǃǃHǃ H]<H5zmH}Hzv?H5ٔnH{m?H5qHn?HH HQH5ñmHo?HH;d?HHH HMHHUHuHuIIFIF0INIVIF@H]HEHtHņAH mmHHH;Eu LHP[A^]JmmIH]HEHtH耆AHlmLjm fffff.UHAVSHPIHHHE(lmHþ HlmHHCHCXHC`HCXHCHHC@HC8HC0HC(HC HCPHCpHCxHCpHChƃHǃfǃHǃHǃƃHHǃHǃHǃHǃHǃHǃHǃHǃHǃHHHǃHǃHǃǃǃHǃ H]-<H5xmH}Hs?H5nHj?H5FqHk?HH HQH5mH m?HH;a?HHH HMHHUHuHuIIFIF0INIVIF@H]HEHtHAHKjmHHH;Eu LHP[A^]jmIH]HEHtHAHjmLFgm fffff.UHAVSHPIH[HHE(imHþ HimHHCHCXHC`HCXHCHHC@HC8HC0HC(HC HCPHCpHCxHCpHChƃHǃfǃHǃHǃƃHHǃHǃHǃHǃHǃHǃHǃHǃHǃHHHǃHǃHǃǃǃHǃ H]譒<H5]umH}Hp?H5YnHg?H5qH,i?HH HQH5CmHLj?HH;_?HHH HMHHUHuHuIIFIF0INIVIF@H]HEHtHEAHgmH߄HH;Eu LHP[A^]gmIH]HEHtHAHFgmLdm fffff.UHAVSHPIHބHHE(gmHþ H -gmHHCHCXHC`HCXHCHHC@HC8HC0HC(HC HCPHCpHCxHCpHChƃHǃfǃHǃHǃƃHHǃHǃHǃHǃHǃHǃHǃHǃHǃHHHǃHǃHǃǃǃHǃ H]<H5rmH}H:n?H5nH;e?H5ƒqHlf?HH HQH5mHg?HH;Q\?HHH @HMHHUHuHuIIFIF0INIVIF@H]HEHtH~AHdmHF܄HH;Eu LHP[A^] -emIH]HEHtH@~AHdmLam fffff.UHAVSHPIHۄHHE(TdmHþ HJdmHHCHCXHC`HCXHCHHC@HC8HC0HC(HC HCPHCpHCxHCpHChƃHǃfǃHǃHǃƃHHǃHǃHǃHǃHǃHǃHǃHǃHǃHHHǃHǃHǃǃǃHǃ H]<H5omH}Hzk?H5ىnH{b?H5qHc?HH HQH5æmHd?HH;Y?HHH HMHHUHuHuIIFIF0INIVIF@H]HEHtH{AH bmHلHH;Eu LHP[A^]JbmIH]HEHtH{AHamL_m fffff.UHAVSHPIHلHHE(amHþ HamHHCHCXHC`HCXHCHHC@HC8HC0HC(HC HCPHCpHCxHCpHChƃHǃfǃHǃHǃƃHHǃHǃHǃHǃHǃHǃHǃHǃHǃHHHǃHǃHǃǃǃHǃ H]-<H5mmH}Hh?H5nH_?H5FqH`?HH HQH5mH b?HH;V?HHH HMHeHUHuHuIIFIF0INIVIF@H]HEHtHyAHK_mHքHH;Eu LHP[A^]_mIH]HEHtHxAH_mLF\m fffff.UHAVSHPIH[քHHE(^mHþ H^mHHCHCXHC`HCXHCHHC@HC8HC0HC(HC HCPHCpHCxHCpHChƃHǃfǃHǃHǃƃHHǃHǃHǃHǃHǃHǃHǃHǃHǃHHHǃHǃHǃǃǃHǃ H]譇<H5]jmH}He?H5YnH\?H5qH,^?HH HQH5CmHL_?HH;T?HHH HMHHUHuHuIIFIF0INIVIF@H]HEHtHEvAH\mHԄHH;Eu LHP[A^]\mIH]HEHtHvAHF\mLYm fffff.UHAVSHPIHӄHHE(\mHþ H -\mHHCHCXHC`HCXHCHHC@HC8HC0HC(HC HCPHCpHCxHCpHChƃHǃfǃHǃHǃƃHHǃHǃHǃHǃHǃHǃHǃHǃHǃHHHǃHǃHǃǃǃHǃ H]<H5gmH}H:c?H5nH;Z?H5ƇqHl[?HH HQH5mH\?HH;QQ?HHH @HMHHUHuHuIIFIF0INIVIF@H]HEHtHsAHYmHFфHH;Eu LHP[A^] -ZmIH]HEHtH@sAHYmLVm fffff.UHAVSHPIHЄHHE(TYmHþ HJYmHHCHCXHC`HCXHCHHC@HC8HC0HC(HC HCPHCpHCxHCpHChƃHǃfǃHǃHǃƃHHǃHǃHǃHǃHǃHǃHǃHǃHǃHHHǃHǃHǃǃǃHǃ H]<H5dmH}Hz`?H5~nH{W?H5qHX?HAH5ʛmHY?HH;N?HHH HMHLHUHuHuIIFIF0INIVIF@H]HEHtHpAHWmH΄HH;Eu LHP[A^]QWmIH]HEHtHpAHVmL Tm DUHAVSHPIH+΄HHE(VmHþ HVmHHCHCXHC`HCXHCHHC@HC8HC0HC(HC HCPHCpHCxHCpHChƃHǃfǃHǃHǃƃHHǃHǃHǃHǃHǃHǃHǃHǃHǃHHHǃHǃHǃǃǃHǃ H]=<H5-bmH}H]?H5)|nHT?H5VqHU?HAH5mH#W?HH;K?HHH ׌HMHHUHuHuIIFIF0INIVIF@H]HEHtHnAHbTmH˄HH;Eu LHP[A^]TmIH]HEHtHmAHTmL]Qm DUHAVSHPIH{˄HHE(SmHþ HSmHHCHCXHC`HCXHCHHC@HC8HC0HC(HC HCPHCpHCxHCpHChƃHǃfǃHǃHǃƃHHǃHǃHǃHǃHǃHǃHǃHǃHǃHHHǃHǃHǃǃǃHǃ H]|<H5}_mH}H[?H5yynHR?H5qHLS?HAH5jmHsT?HH;8I?HHH 'HMHHUHuHuIIFIF0INIVIF@H]HEHtHlkAHQmH-ɄHH;Eu LHP[A^]QmIH]HEHtH'kAHmQmLNm DUHAVSHPIHȄHHE(DQmHþ H:QmHHCHCXHC`HCXHCHHC@HC8HC0HC(HC HCPHCpHCxHCpHChƃHǃfǃHǃHǃƃHHǃHǃHǃHǃHǃHǃHǃHǃHǃHHHǃHǃHǃǃǃHǃ H]<H5\mH}HjX?H5vnHkO?H5|qHP?HAH5mHQ?HH;F?HHH wHMH\HUHuHuIIFIF0INIVIF@H]HEHtHhAHOmH}ƄHH;Eu LHP[A^]AOmIH]HEHtHwhAHNmLKm DUHAVSHPIHƄHHE(NmHþ HNmHHCHCXHC`HCXHCHHC@HC8HC0HC(HC HCPHCpHCxHCpHChƃHǃfǃHǃHǃƃHHǃHǃHǃHǃHǃHǃHǃHǃHǃHHHǃHǃHǃǃǃHǃ H]-x<H5ZmH}HU?H5tnHL?H5FzqHM?HH HQH5mH O?HH;C?HHH HMHHUHuHuIIFIF0INIVIF@H]HEHtHfAHKLmHÄHH;Eu LHP[A^]LmIH]HEHtHeAHLmLFIm fffff.UHAVSHPIH[ÄHHE(KmHþ HKmHHCHCXHC`HCXHCHHC@HC8HC0HC(HC HCPHCpHCxHCpHChƃHǃfǃHǃHǃƃHHǃHǃHǃHǃHǃHǃHǃHǃHǃHHHǃHǃHǃǃǃHǃ H]m{<H5]WmH}HR?H5]qnHI?H5wqH,K?HH HQH5CmHLL?HH;A?HHH HMHHUHuHuIIFIF0INIVIF@H]HEHtHEcAHImHHH;Eu LHP[A^]ImIH]HEHtHcAHFImLFm fffff.UHAVSHPIHHHE(ImHþ H -ImHHCHCXHC`HCXHCHHC@HC8HC0HC(HC HCPHCpHCxHCpHChƃHǃfǃHǃHǃƃHHǃHǃHǃHǃHǃHǃHǃHǃHǃHHHǃHǃHǃǃǃHǃ H]q<H5TmH}H:P?H5nnH;G?H5tqHlH?HH HQH5mHI?HH;Q>?HHH @HMHHUHuHuIIFIF0INIVIF@H]HEHtH`AHFmHFHH;Eu LHP[A^] -GmIH]HEHtH@`AHFmLCm fffff.UHAVSHPIH۽HHE(TFmHþ HJFmHHCHCXHC`HCXHCHHC@HC8HC0HC(HC HCPHCpHCxHCpHChƃHǃfǃHǃHǃƃHHǃHǃHǃHǃHǃHǃHǃHǃHǃHHHǃHǃHǃǃǃHǃ H]-u<H5QmH}HzM?H5knH{D?H5rqHE?HH HQH5ÈmHF?HH;;?HHH |HMHHUHuHuIIFIF0INIVIF@H]HEHtH]AH DmHHH;Eu LHP[A^]JDmIH]HEHtH]AHCmLAm fffff.UHAVSHPIHHHE(CmHþ HCmHHCHCXHC`HCXHCHHC@HC8HC0HC(HC HCPHCpHCxHCpHChƃHǃfǃHǃHǃƃHHǃHǃHǃHǃHǃHǃHǃHǃHǃHHHǃHǃHǃǃǃHǃ H]-m<H5OmH}HJ?H5inHA?H5FoqHB?HH HQH5mH D?HH;8?HHH yHMHHUHuHuIIFIF0INIVIF@H]HEHtH[AHKAmHƸHH;Eu LHP[A^]AmIH]HEHtHZAHAmLF>m fffff.UHAVSHPIH[HHE(@mHþ H@mHHCHCXHC`HCXHCHHC@HC8HC0HC(HC HCPHCpHCxHCpHChƃHǃfǃHǃHǃƃHHǃHǃHǃHǃHǃHǃHǃHǃHǃHHHǃHǃHǃǃǃHǃ H]mp<H5]LmH}HG?H5]fnH>?H5lqH,@?HH HQH5CmHLA?HH;6?HHH wHMHHUHuHuIIFIF0INIVIF@H]HEHtHEXAH>mHHH;Eu LHP[A^]>mIH]HEHtHXAHF>mL;m fffff.UHAVSHPIHHHE(>mHþ H ->mHHCHCXHC`HCXHCHHC@HC8HC0HC(HC HCPHCpHCxHCpHChƃHǃfǃHǃHǃƃHHǃHǃHǃHǃHǃHǃHǃHǃHǃHHHǃHǃHǃǃǃHǃ H]f<H5ImH}H:E?H5cnH;<?H5iqHl=?HH HQH5mH>?HH;Q3?HHH @tHMH5HUHuHuIIFIF0INIVIF@H]HEHtHUAH;mHFHH;Eu LHP[A^] -<mIH]HEHtH@UAH;mL8m fffff.UHAVSHPIH۲HHE(T;mHþ HJ;mHHCHCXHC`HCXHCHHC@HC8HC0HC(HC HCPHCpHCxHCpHChƃHǃfǃHǃHǃƃHHǃHǃHǃHǃHǃHǃHǃHǃHǃHHHǃHǃHǃǃǃHǃ H]-j<H5FmH}HzB?H5`nH{9?H5gqH:?HH HQH5}mH;?HH;0?HHH qHMHHUHuHuIIFIF0INIVIF@H]HEHtHRAH 9mHHH;Eu LHP[A^]J9mIH]HEHtHRAH8mL6m fffff.UHAVSHPIHHHE(8mHþ H8mHHCHCXHC`HCXHCHHC@HC8HC0HC(HC HCPHCpHCxHCpHChƃHǃfǃHǃHǃƃHHǃHǃHǃHǃHǃHǃHǃHǃHǃHHHǃHǃHǃǃǃHǃ H]-b<H5DmH}H??H5^nH6?H5FdqH7?HAH5 -{mH9?HH;-?HHH nHMH|HUHuHuIIFIF0INIVIF@H]HEHtH PAHR6mHͭHH;Eu LHP[A^]6mIH]HEHtHOAH 6mLM3m DUHAVSHPIHkHHE(5mHþ H5mHHCHCXHC`HCXHCHHC@HC8HC0HC(HC HCPHCpHCxHCpHChƃHǃfǃHǃHǃƃHHǃHǃHǃHǃHǃHǃHǃHǃHǃHHHǃHǃHǃǃǃHǃ H]}e<H5mAmH}H -=?H5m[nH 4?H5aqH<5?HAH5ZxmHc6?HH;(+?HHH lHMH,HUHuHuIIFIF0INIVIF@H]HEHtH\MAH3mHHH;Eu LHP[A^]3mIH]HEHtHMAH]3mL0m DUHAVSHPIHHHE(43mHþ H*3mHHCHCXHC`HCXHCHHC@HC8HC0HC(HC HCPHCpHCxHCpHChƃHǃfǃHǃHǃƃHHǃHǃHǃHǃHǃHǃHǃHǃHǃHHHǃHǃHǃǃǃHǃ H] \<H5>mH}HZ:?H5XnH[1?H5^qH2?HAH5umH3?HH;x(?HHH giHMHHUHuHuIIFIF0INIVIF@H]HEHtHJAH0mHmHH;Eu LHP[A^]11mIH]HEHtHgJAH0mL-m DUHAVSHPIH HHE(0mHþ Hz0mHHCHCXHC`HCXHCHHC@HC8HC0HC(HC HCPHCpHCxHCpHChƃHǃfǃHǃHǃƃHHǃHǃHǃHǃHǃHǃHǃHǃHǃHHHǃHǃHǃǃǃHǃ H]]_<H5 <mH}H7?H5 VnH.?H56\qH/?HAH5rmH1?HH;%?HHH fHMHHUHuHuIIFIF0INIVIF@H]HEHtHGAHB.mHHH;Eu LHP[A^].mIH]HEHtHGAH-mL=+m DUHAVSHPIH[HHE(-mHþ H-mHHCHCXHC`HCXHCHHC@HC8HC0HC(HC HCPHCpHCxHCpHChƃHǃfǃHǃHǃƃHHǃHǃHǃHǃHǃHǃHǃHǃHǃHHHǃHǃHǃǃǃHǃ H]mW<H5]9mH}H4?H5aSnH+?H5YqH,-?HH HQH5CpmHL.?HH;#?HHH dHMH5HUHuHuIIFIF0INIVIF@H]HEHtHEEAH+mHHH;Eu LHP[A^]+mIH]HEHtHEAHF+mL(m fffff.UHAVSHPIHHHE(+mHþ H -+mHHCHCXHC`HCXHCHHC@HC8HC0HC(HC HCPHCpHCxHCpHChƃHǃfǃHǃHǃƃHHǃHǃHǃHǃHǃHǃHǃHǃHǃHHHǃHǃHǃǃǃHǃ H]Z<H56mH}H:2?H5PnH;)?H5VqHl*?HH HQH5mmH+?HH;Q ?HHH @aHMH5HUHuHuIIFIF0INIVIF@H]HEHtHBAH(mHFHH;Eu LHP[A^] -)mIH]HEHtH@BAH(mL%m fffff.UHAVSHPIH۟HHE(T(mHþ HJ(mHHCHCXHC`HCXHCHHC@HC8HC0HC(HC HCPHCpHCxHCpHChƃHǃfǃHǃHǃƃHHǃHǃHǃHǃHǃHǃHǃHǃHǃHHHǃHǃHǃǃǃHǃ H]-T<H53mH}Hz/?H5MnH{&?H5TqH'?HH HQH5jmH(?HH;?HHH ^HMHHUHuHuIIFIF0INIVIF@H]HEHtH?AH &mHHH;Eu LHP[A^]J&mIH]HEHtH?AH%mL#m fffff.UHAVSHPIHHHE(%mHþ H%mHHCHCXHC`HCXHCHHC@HC8HC0HC(HC HCPHCpHCxHCpHChƃHǃfǃHǃHǃƃHHǃHǃHǃHǃHǃHǃHǃHǃHǃHHHǃHǃHǃǃǃHǃ H]S<H51mH}H,?H5!KnH#?H5FQqH$?HH HQH5hmH &?HH;?HHH [HMHHUHuHuIIFIF0INIVIF@H]HEHtH=AHK#mHƚHH;Eu LHP[A^]#mIH]HEHtH<AH#mLF m fffff.UHAVSHPIH[HHE("mHþ H"mHHCHCXHC`HCXHCHHC@HC8HC0HC(HC HCPHCpHCxHCpHChƃHǃfǃHǃHǃƃHHǃHǃHǃHǃHǃHǃHǃHǃHǃHHHǃHǃHǃǃǃHǃ H]K<H5].mH}H)?H5aHnH ?H5NqH,"?HH HQH5CemHL#?HH;?HHH YHMH HUHuHuIIFIF0INIVIF@H]HEHtHE:AH mHHH;Eu LHP[A^] mIH]HEHtH:AHF mLm fffff.UHAVSHPIHHHE( mHþ H - mHHCHCXHC`HCXHCHHC@HC8HC0HC(HC HCPHCpHCxHCpHChƃHǃfǃHǃHǃƃHHǃHǃHǃHǃHǃHǃHǃHǃHǃHHHǃHǃHǃǃǃHǃ H]N<H5+mH}H:'?H5EnH;?H5KqHl?HH HQH5bmH ?HH;Q?HHH @VHMHeHUHuHuIIFIF0INIVIF@H]HEHtH7AHmHFHH;Eu LHP[A^] -mIH]HEHtH@7AHmLm fffff.UHAVSHPIH۔HHE(TmHþ HJmHHCHCXHC`HCXHCHHC@HC8HC0HC(HC HCPHCpHCxHCpHChƃHǃfǃHǃHǃƃHHǃHǃHǃHǃHǃHǃHǃHǃHǃHHHǃHǃHǃǃǃHǃ H]I<H5(mH}Hz$?H5BnH{?H5IqH?HH HQH5_mH?HH;?HHH SHMHU"HUHuHuIIFIF0INIVIF@H]HEHtH4AH mHHH;Eu LHP[A^]JmIH]HEHtH4AHmLm fffff.UHAVSHPIHHHE(mHþ HmHHCHCXHC`HCXHCHHC@HC8HC0HC(HC HCPHCpHCxHCpHChƃHǃfǃHǃHǃƃHHǃHǃHǃHǃHǃHǃHǃHǃHǃHHHǃHǃHǃǃǃHǃ H]G<H5&mH}H!?H5!@nH?H5FFqH?HH HQH5]mH ?HH;?HHH PHMHU+HUHuHuIIFIF0INIVIF@H]HEHtH2AHKmHƏHH;Eu LHP[A^]mIH]HEHtH1AHmLFm fffff.UHAVSHPIH[HHE(mHþ HmHHCHCXHC`HCXHCHHC@HC8HC0HC(HC HCPHCpHCxHCpHChƃHǃfǃHǃHǃƃHHǃHǃHǃHǃHǃHǃHǃHǃHǃHHHǃHǃHǃǃǃHǃ H]-H<H5]#mH}H?H5a=nH?H5CqH,?HH HQH5CZmHL?HH; ?HHH NHMHu4HUHuHuIIFIF0INIVIF@H]HEHtHE/AHmHHH;Eu LHP[A^]mIH]HEHtH/AHFmLm fffff.UHAVSHPIHHHE(mHþ H -mHHCHCXHC`HCXHCHHC@HC8HC0HC(HC HCPHCpHCxHCpHChƃHǃfǃHǃHǃƃHHǃHǃHǃHǃHǃHǃHǃHǃHǃHHHǃHǃHǃǃǃHǃ H]-F<H5 mH}H:?H5:nH;?H5@qHl?HH HQH5WmH?HH;Q -?HHH @KHMHu=HUHuHuIIFIF0INIVIF@H]HEHtH,AHmHFHH;Eu LHP[A^] -mIH]HEHtH@,AHmLm fffff.UHAVSHPIHۉHHE(TmHþ HJmHHCHCXHC`HCXHCHHC@HC8HC0HC(HC HCPHCpHCxHCpHChƃHǃfǃHǃHǃƃHHǃHǃHǃHǃHǃHǃHǃHǃHǃHHHǃHǃHǃǃǃHǃ H];<H5mH}Hz?H57nH{?H5>qH?HA H5TmH?HH;?HHH HHMHFHUHuHuIIFIF0INIVIF@H]HEHtH)AHmHHH;Eu LHP[A^]QmIH]HEHtH)AHmL m DUHAVSHPIH+HHE(mHþ HmHHCHCXHC`HCXHCHHC@HC8HC0HC(HC HCPHCpHCxHCpHChƃHǃfǃHǃHǃƃHHǃHǃHǃHǃHǃHǃHǃHǃHǃHHHǃHǃHǃǃǃHǃ H]=?<H5-mH}H?H515nH ?H5V;qH?HA H5RmH#?HH;?HHH EHMH,DHUHuHuIIFIF0INIVIF@H]HEHtH'AHb mH݄HH;Eu LHP[A^] mIH]HEHtH&AH mL] -m DUHAVSHPIH{HHE( mHþ H mHHCHCXHC`HCXHCHHC@HC8HC0HC(HC HCPHCpHCxHCpHChƃHǃfǃHǃHǃƃHHǃHǃHǃHǃHǃHǃHǃHǃHǃHHHǃHǃHǃǃǃHǃ H]8<H5}mH}H?H52nH ?H58qHL ?HA H5jOmHs ?HH;8?HHH 'CHMHAHUHuHuIIFIF0INIVIF@H]HEHtHl$AH -mH-HH;Eu LHP[A^] -mIH]HEHtH'$AHm -mLm DUHAVSHPIHˁHHE(D -mHþ H: -mHHCHCXHC`HCXHCHHC@HC8HC0HC(HC HCPHCpHCxHCpHChƃHǃfǃHǃHǃƃHHǃHǃHǃHǃHǃHǃHǃHǃHǃHHHǃHǃHǃǃǃHǃ H]]8<H5mH}Hj?H5/nHk?H55qH ?HA H5LmH -?HH;>HHH w@HMHL?HUHuHuIIFIF0INIVIF@H]HEHtH!AHmH}HH;Eu LHP[A^]AmIH]HEHtHw!AHmLm DUHAVSHPIHHHE(mHþ HmHHCHCXHC`HCXHCHHC@HC8HC0HC(HC HCPHCpHCxHCpHChƃHǃfǃHǃHǃƃHHǃHǃHǃHǃHǃHǃHǃHǃHǃHHHǃHǃHǃǃǃHǃ H]m0<H5mH}H?H5!-nH?H5F3qH?HA H5 -JmH?HH;>HHH =HMH<HUHuHuIIFIF0INIVIF@H]HEHtH AHRmH|HH;Eu LHP[A^]mIH]HEHtHAH mLMm DUHAVSHPIHk|HHE(mHþ HmHHCHCXHC`HCXHCHHC@HC8HC0HC(HC HCPHCpHCxHCpHChƃHǃfǃHǃHǃƃHHǃHǃHǃHǃHǃHǃHǃHǃHǃHHHǃHǃHǃǃǃHǃ H]3<H5mmH}H - ?H5q*nH ?H50qH<?HA H5ZGmHc?HH;(>HHH ;HMHl:HUHuHuIIFIF0INIVIF@H]HEHtH\AHmHzHH;Eu LHP[A^]mIH]HEHtHAH]mLl DUHAVSHPIHyHHE(4mHþ H*mHHCHCXHC`HCXHCHHC@HC8HC0HC(HC HCPHCpHCxHCpHChƃHǃfǃHǃHǃƃHHǃHǃHǃHǃHǃHǃHǃHǃHǃHHHǃHǃHǃǃǃHǃ H].<H5 mH}HZ ?H5'nH[?H5-qH?HA H5DmH?HH;x>HHH g8HMH7HUHuHuIIFIF0INIVIF@H]HEHtHAHlHmwHH;Eu LHP[A^]1mIH]HEHtHgAHlLl DUHAVSHPIH wHHE(lHþ HzlHHCHCXHC`HCXHCHHC@HC8HC0HC(HC HCPHCpHCxHCpHChƃHǃfǃHǃHǃƃHHǃHǃHǃHǃHǃHǃHǃHǃHǃHHHǃHǃHǃǃǃHǃ H],<H5 mH}H?H5%nH>H56+qH>HA H5AmH?HH;>HHH 5HMH5HUHuHuIIFIF0INIVIF@H]HEHtHAHBlHtHH;Eu LHP[A^]lIH]HEHtHAHlL=l DUHAVSHPIH[tHHE(lHþ HlHHCHCXHC`HCXHCHHC@HC8HC0HC(HC HCPHCpHCxHCpHChƃHǃfǃHǃHǃƃHHǃHǃHǃHǃHǃHǃHǃHǃHǃHHHǃHǃHǃǃǃHǃ H]--<H5]mH}H?H5a"nH>H5(qH,>HA H5J?mHS>HH;>HHH 3HMH3HUHuHuIIFIF0INIVIF@H]HEHtHLAHlH rHH;Eu LHP[A^]lIH]HEHtHAHMlLl DUHAVSHPIHqHHE($lHþ HlHHCHCXHC`HCXHCHHC@HC8HC0HC(HC HCPHCpHCxHCpHChƃHǃfǃHǃHǃƃHHǃHǃHǃHǃHǃHǃHǃHǃHǃHHHǃHǃHǃǃǃHǃ H]=+<H5mH}HJ?H5nHK>H5%qH|>HA H5<mH>HH;h>HHH W0HMH0HUHuHuIIFIF0INIVIF@H]HEHtHAHlH]oHH;Eu LHP[A^]!lIH]HEHtHWAHlLl DUHAVSHPIHnHHE(tlHþ HjlHHCHCXHC`HCXHCHHC@HC8HC0HC(HC HCPHCpHCxHCpHChƃHǃfǃHǃHǃƃHHǃHǃHǃHǃHǃHǃHǃHǃHǃHHHǃHǃHǃǃǃHǃ H] !<H5mH}H>H5nH>H5&#qH>HH HQH59mH>HH;>HHH -HMH5.HUHuHuIIFIF0INIVIF@H]HEHtHAH+lHlHH;Eu LHP[A^]jlIH]HEHtHAHlL&l fffff.UHAVSHPIH;lHHE(lHþ HlHHCHCXHC`HCXHCHHC@HC8HC0HC(HC HCPHCpHCxHCpHChƃHǃfǃHǃHǃƃHHǃHǃHǃHǃHǃHǃHǃHǃHǃHHHǃHǃHǃǃǃHǃ H]M$<H5=mH}H>H5EnH>H5f qH >HH HQH5#7mH,>HH;>HHH *HMH<HUHuHuIIFIF0INIVIF@H]HEHtH% AHklHiHH;Eu LHP[A^]lIH]HEHtH AH&lLfl fffff.UHAVSHPIH{iHHE(lHþ HlHHCHCXHC`HCXHCHHC@HC8HC0HC(HC HCPHCpHCxHCpHChƃHǃfǃHǃHǃƃHHǃHǃHǃHǃHǃHǃHǃHǃHǃHHHǃHǃHǃǃǃHǃ H]<H5}lH}H>H5nH>H5qHL>HH HQH5c4mHl>HH;1>HHH (HMHEKHUHuHuIIFIF0INIVIF@H]HEHtHe AHlH&gHH;Eu LHP[A^]lIH]HEHtH AHflLl fffff.UHAVSHPIHfHHE(4lHþ H*lHHCHCXHC`HCXHCHHC@HC8HC0HC(HC HCPHCpHCxHCpHChƃHǃfǃHǃHǃƃHHǃHǃHǃHǃHǃHǃHǃHǃHǃHHHǃHǃHǃǃǃHǃ H] <H5lH}HZ>H5nH[>H5qH>HH HQH51mH>HH;q>HHH `%HMHeTHUHuHuIIFIF0INIVIF@H]HEHtHAHlHfdHH;Eu LHP[A^]*lIH]HEHtH`AHlLl fffff.UHAVSHPIHcHHE(tlHþ HjlHHCHCXHC`HCXHCHHC@HC8HC0HC(HC HCPHCpHCxHCpHChƃHǃfǃHǃHǃƃHHǃHǃHǃHǃHǃHǃHǃHǃHǃHHHǃHǃHǃǃǃHǃ H]M<H5lH}H>H5nH>H5&qH>HH HQH5.mH>HH;>HHH "HMHbHUHuHuIIFIF0INIVIF@H]HEHtHAH+lHaHH;Eu LHP[A^]jlIH]HEHtHAHlL&l fffff.UHAVSHPIH;aHHE(lHþ HlHHCHCXHC`HCXHCHHC@HC8HC0HC(HC HCPHCpHCxHCpHChƃHǃfǃHǃHǃƃHHǃHǃHǃHǃHǃHǃHǃHǃHǃHHHǃHǃHǃǃǃHǃ H]M<H5=lH}H>H5EnH>H5fqH >HA H5*,mH3>HH;>HHH HMHkHUHuHuIIFIF0INIVIF@H]HEHtH,AHrlH^HH;Eu LHP[A^]lIH]HEHtHAH-lLml DUHAVSHPIH^HHE(lHþ HlHHCHCXHC`HCXHCHHC@HC8HC0HC(HC HCPHCpHCxHCpHChƃHǃfǃHǃHǃƃHHǃHǃHǃHǃHǃHǃHǃHǃHǃHHHǃHǃHǃǃǃHǃ H]<H5lH}H*>H5 nH+>H5qH\>HA H5z)mH>HH;H>HHH 7HMH|iHUHuHuIIFIF0INIVIF@H]HEHtH|@HlH=\HH;Eu LHP[A^]lIH]HEHtH7@H}lLl DUHAVSHPIH[HHE(TlHþ HJlHHCHCXHC`HCXHCHHC@HC8HC0HC(HC HCPHCpHCxHCpHChƃHǃfǃHǃHǃƃHHǃHǃHǃHǃHǃHǃHǃHǃHǃHHHǃHǃHǃǃǃHǃ H]-<H5lH}Hz>H5 nH{>H5qH>HA H5&mH>HH;>HHH HMH gHUHuHuIIFIF0INIVIF@H]HEHtH@HlHYHH;Eu LHP[A^]QlIH]HEHtH@HlL l DUHAVSHPIH+YHHE(lHþ HlHHCHCXHC`HCXHCHHC@HC8HC0HC(HC HCPHCpHCxHCpHChƃHǃfǃHǃHǃƃHHǃHǃHǃHǃHǃHǃHǃHǃHǃHHHǃHǃHǃǃǃHǃ H]} -<H5-lH}H>H55nH>H5V qH>HA H5$mH#>HH;>HHH HMHdHUHuHuIIFIF0INIVIF@H]HEHtH@HblHVHH;Eu LHP[A^]lIH]HEHtH@HlL]l DUHAVSHPIH{VHHE(lHþ HlHHCHCXHC`HCXHCHHC@HC8HC0HC(HC HCPHCpHCxHCpHChƃHǃfǃHǃHǃƃHHǃHǃHǃHǃHǃHǃHǃHǃHǃHHHǃHǃHǃǃǃHǃ H] <H5}lH}H>H5nH>H5 -qHL>HA H5j!mHs>HH;8>HHH 'HMH,bHUHuHuIIFIF0INIVIF@H]HEHtHl@HlH-THH;Eu LHP[A^]lIH]HEHtH'@HmlLl DUHAVSHPIHSHHE(DlHþ H:lHHCHCXHC`HCXHCHHC@HC8HC0HC(HC HCPHCpHCxHCpHChƃHǃfǃHǃHǃƃHHǃHǃHǃHǃHǃHǃHǃHǃHǃHHHǃHǃHǃǃǃHǃ H]<H5lH}Hj>H5nHk>H5qH>HH HQH5mH>HH;>HHH pHMH_HUHuHuIIFIF0INIVIF@H]HEHtH@HlHvQHH;Eu LHP[A^]:lIH]HEHtHp@HlLl fffff.UHAVSHPIH QHHE(lHþ HzlHHCHCXHC`HCXHCHHC@HC8HC0HC(HC HCPHCpHCxHCpHChƃHǃfǃHǃHǃƃHHǃHǃHǃHǃHǃHǃHǃHǃHǃHHHǃHǃHǃǃǃHǃ H]<H5 lH}H>H5mH>H56qH>HA H5mH>HH;>HHH HMHnHUHuHuIIFIF0INIVIF@H]HEHtH@HBlHNHH;Eu LHP[A^]lIH]HEHtH@HlL=l DUHAVSHPIH[NHHE(lHþ HlHHCHCXHC`HCXHCHHC@HC8HC0HC(HC HCPHCpHCxHCpHChƃHǃfǃHǃHǃƃHHǃHǃHǃHǃHǃHǃHǃHǃHǃHHHǃHǃHǃǃǃHǃ H]m<H5]lH}H>H5omH>H5qH,>HH HQH5CmHL>HH;>HHH HMHkHUHuHuIIFIF0INIVIF@H]HEHtHE@HlHLHH;Eu LHP[A^]lIH]HEHtH@HFlLl fffff.UHAVSHPIHKHHE(lHþ H -lHHCHCXHC`HCXHCHHC@HC8HC0HC(HC HCPHCpHCxHCpHChƃHǃfǃHǃHǃƃHHǃHǃHǃHǃHǃHǃHǃHǃHǃHHHǃHǃHǃǃǃHǃ H];H5lH}H:>H5mH;>H5pHl>HA H5mH>HH;X>HHH G -HMH zHUHuHuIIFIF0INIVIF@H]HEHtH@HlHMIHH;Eu LHP[A^]lIH]HEHtHG@HlLl DUHAVSHPIHHHHE(dlHþ HZlHHCHCXHC`HCXHCHHC@HC8HC0HC(HC HCPHCpHCxHCpHChƃHǃfǃHǃHǃƃHHǃHǃHǃHǃHǃHǃHǃHǃHǃHHHǃHǃHǃǃǃHǃ H];H5lH}H>H5mH>H5pH>HH HQH5mH>HH;>HHH HMHwHUHuHuIIFIF0INIVIF@H]HEHtH@HlHFHH;Eu LHP[A^]ZlIH]HEHtH@HlLl fffff.UHAVSHPIH+FHHE(lHþ HlHHCHCXHC`HCXHCHHC@HC8HC0HC(HC HCPHCpHCxHCpHChƃHǃfǃHǃHǃƃHHǃHǃHǃHǃHǃHǃHǃHǃHǃHHHǃHǃHǃǃǃHǃ H]=;H5-lH}H>H5DmH>H5VpH>HH HQH5mH>HH;>HHH HMHuHUHuHuIIFIF0INIVIF@H]HEHtH@H[lHCHH;Eu LHP[A^]lIH]HEHtH@HlLVl fffff.UHAVSHPIHkCHHE(lHþ HlHHCHCXHC`HCXHCHHC@HC8HC0HC(HC HCPHCpHCxHCpHChƃHǃfǃHǃHǃƃHHǃHǃHǃHǃHǃHǃHǃHǃHǃHHHǃHǃHǃǃǃHǃ H]};H5mlH}H ->H5mH >H5pH<>HA H5ZmHc>HH;(>HHH HMHHUHuHuIIFIF0INIVIF@H]HEHtH\@HlHAHH;Eu LHP[A^]lIH]HEHtH@H]lLl DUHAVSHPIH@HHE(4lHþ H*lHHCHCXHC`HCXHCHHC@HC8HC0HC(HC HCPHCpHCxHCpHChƃHǃfǃHǃHǃƃHHǃHǃHǃHǃHǃHǃHǃHǃHǃHHHǃHǃHǃǃǃHǃ H];H5lH}HZ>H5mH[>H5pH>HA H5 mH>HH;x>HHH gHMH<HUHuHuIIFIF0INIVIF@H]HEHtH@HlHm>HH;Eu LHP[A^]1lIH]HEHtHg@HlLl DUHAVSHPIH >HHE(lHþ HzlHHCHCXHC`HCXHCHHC@HC8HC0HC(HC HCPHCpHCxHCpHChƃHǃfǃHǃHǃƃHHǃHǃHǃHǃHǃHǃHǃHǃHǃHHHǃHǃHǃǃǃHǃ H];H5 lH}H>H5/mH>H56pH>HH HQH5mH>HH;>HHH HMHŌHUHuHuIIFIF0INIVIF@H]HEHtH@H;lH;HH;Eu LHP[A^]zlIH]HEHtH@HlL6l fffff.UHAVSHPIHK;HHE(lHþ HlHHCHCXHC`HCXHCHHC@HC8HC0HC(HC HCPHCpHCxHCpHChƃHǃfǃHǃHǃƃHHǃHǃHǃHǃHǃHǃHǃHǃHǃHHHǃHǃHǃǃǃHǃ H]];H5MlH}H>H5omH>H5vpH>HH HQH53mH<>HH;>HHH HMHHUHuHuIIFIF0INIVIF@H]HEHtH5@H{lH8HH;Eu LHP[A^]lIH]HEHtH@H6lLvl fffff.UHAVSHPIH8HHE(lHþ HlHHCHCXHC`HCXHCHHC@HC8HC0HC(HC HCPHCpHCxHCpHChƃHǃfǃHǃHǃƃHHǃHǃHǃHǃHǃHǃHǃHǃHǃHHHǃHǃHǃǃǃHǃ H];H5lH}H*>H5mH+>H5pH\>HA H5zmH>HH;H>HHH 7HMH̟HUHuHuIIFIF0INIVIF@H]HEHtH|@H¾lH=6HH;Eu LHP[A^]lIH]HEHtH7@H}lL轻l DUHAVSHPIH5HHE(TlHþ HJlHHCHCXHC`HCXHCHHC@HC8HC0HC(HC HCPHCpHCxHCpHChƃHǃfǃHǃHǃƃHHǃHǃHǃHǃHǃHǃHǃHǃHǃHHHǃHǃHǃǃǃHǃ H];H5lH}Hz>H5mH{>H5pH謽>HA H5mHӾ>HH;蘳>HHH HMH\HUHuHuIIFIF0INIVIF@H]HEHtH@HlH3HH;Eu LHP[A^]QlIH]HEHtH@HͻlL l DUHAVSHPIH+3HHE(褻lHþ H蚻lHHCHCXHC`HCXHCHHC@HC8HC0HC(HC HCPHCpHCxHCpHChƃHǃfǃHǃHǃƃHHǃHǃHǃHǃHǃHǃHǃHǃHǃHHHǃHǃHǃǃǃHǃ H]H52lHTH eH}贿>H5NmHŹ>H5PpH>HH HQH5 lH>HH;۰>HHH HMHߚHUHuHuIIFIF0INIVIF@H]HEHtH@HUlH0HH;Eu LHP[A^]蔹lIH]HEHtH@HlLPl UHAVSHPIHk0HHE(lHþ HڸlHHCHCXHC`HCXHCHHC@HC8HC0HC(HC HCPHCpHCxHCpHChƃHǃfǃHǃHǃƃHHǃHǃHǃHǃHǃHǃHǃHǃHǃHHHǃHǃHǃǃǃHǃ H]H5rlHėH 헇H}>H5mHH 症H׼>H5qmH>H5spH>HH HQH50lH9>HH;>HHH HMHbHUHuHuIIFIF0INIVIF@H]HEHtH2@HxlH-HH;Eu LHP[A^]跶lIH]HEHtH@H3lLsl ff.UHAVSHPIH-HHE(lHþ HlHHCHCXHC`HCXHCHHC@HC8HC0HC(HC HCPHCpHCxHCpHChƃHǃfǃHǃHǃƃHHǃHǃHǃHǃHǃHǃHǃHǃHǃHHHǃHǃHǃǃǃHǃ H]H5lH䔇H H}>H5mHޔH H>H5mH>H5pH9>HA H5WlH`>HH;%>HHH HMHHUHuHuIIFIF0INIVIF@H]HEHtHY@H蟳lH+HH;Eu LHP[A^]޳lIH]HEHtH@HZlL蚰l fUHAVSHPIH*HHE(4lHþ H*lHHCHCXHC`HCXHCHHC@HC8HC0HC(HC HCPHCpHCxHCpHChƃHǃfǃHǃHǃƃHHǃHǃHǃHǃHǃHǃHǃHǃHǃHHHǃHǃHǃǃǃHǃ H];H5lH}HZ>H5mH[>H5pH茲>HH HQH5lH謳>HH;q>HHH `HMHHUHuHuIIFIF0INIVIF@H]HEHtH@HlHf(HH;Eu LHP[A^]*lIH]HEHtH`@H覰lLl fffff.UHAVSHPIH'HHE(tlHþ HjlHHCHCXHC`HCXHCHHC@HC8HC0HC(HC HCPHCpHCxHCpHChƃHǃfǃHǃHǃƃHHǃHǃHǃHǃHǃHǃHǃHǃHǃHHHǃHǃHǃǃǃHǃ H] ;H5lH}H蚷>H5+mH蛮>H5&pH̯>HH HQH5lH>HH;豥>HHH HMHUHUHuHuIIFIF0INIVIF@H]HEHtH@H+lH%HH;Eu LHP[A^]jlIH]HEHtH@HlL&l fffff.UHAVSHPIH;%HHE(购lHþ H読lHHCHCXHC`HCXHCHHC@HC8HC0HC(HC HCPHCpHCxHCpHChƃHǃfǃHǃHǃƃHHǃHǃHǃHǃHǃHǃHǃHǃHǃHHHǃHǃHǃǃǃHǃ H]M;H5=lH}Hڴ>H5kmH۫>H5fpH >HA H5*lH3>HH;>HHH HMHLHUHuHuIIFIF0INIVIF@H]HEHtH,@HrlH"HH;Eu LHP[A^]豫lIH]HEHtH@H-lLml DUHAVSHPIH"HHE(lHþ HlHHCHCXHC`HCXHCHHC@HC8HC0HC(HC HCPHCpHCxHCpHChƃHǃfǃHǃHǃƃHHǃHǃHǃHǃHǃHǃHǃHǃHǃHHHǃHǃHǃǃǃHǃ H];H5lH}H*>H5mH+>H5pH\>HA H5zlH胫>HH;H>HHH 7HMHܫHUHuHuIIFIF0INIVIF@H]HEHtH|@H¨lH= HH;Eu LHP[A^]lIH]HEHtH7@H}lL轥l DUHAVSHPIHHHE(TlHþ HJlHHCHCXHC`HCXHCHHC@HC8HC0HC(HC HCPHCpHCxHCpHChƃHǃfǃHǃHǃƃHHǃHǃHǃHǃHǃHǃHǃHǃHǃHHHǃHǃHǃǃǃHǃ H];H5ݳlH}Hz>H5mH{>H5pH謧>HH HQH5lH̨>HH;葝>HHH ބHMHeHUHuHuIIFIF0INIVIF@H]HEHtHſ@H lHHH;Eu LHP[A^]JlIH]HEHtH耿@HƥlLl fffff.UHAVSHPIHHHE(蔥lHþ H芥lHHCHCXHC`HCXHCHHC@HC8HC0HC(HC HCPHCpHCxHCpHChƃHǃfǃHǃHǃƃHHǃHǃHǃHǃHǃHǃHǃHǃHǃHHHǃHǃHǃǃǃHǃ H]-;H5lH}H躬>H5OmH軣>H5FpH>HH HQH5lH >HH;њ>HHH ۄHMHHUHuHuIIFIF0INIVIF@H]HEHtH@HKlHHH;Eu LHP[A^]芣lIH]HEHtH@HlLFl fffff.UHAVSHPIH[HHE(ԢlHþ HʢlHHCHCXHC`HCXHCHHC@HC8HC0HC(HC HCPHCpHCxHCpHChƃHǃfǃHǃHǃƃHHǃHǃHǃHǃHǃHǃHǃHǃHǃHHHǃHǃHǃǃǃHǃ H]m;H5]lH}H>H5mH>H5pH,>HA H5JlHS>HH;>HHH لHMHHUHuHuIIFIF0INIVIF@H]HEHtHL@H蒠lH HH;Eu LHP[A^]ѠlIH]HEHtH@HMlL荝l DUHAVSHPIHHHE($lHþ HlHHCHCXHC`HCXHCHHC@HC8HC0HC(HC HCPHCpHCxHCpHChƃHǃfǃHǃHǃƃHHǃHǃHǃHǃHǃHǃHǃHǃHǃHHHǃHǃHǃǃǃHǃ H];H5lH}HJ>H5mHK>H5pH|>HA H5lH裠>HH;h>HHH WքHMHHUHuHuIIFIF0INIVIF@H]HEHtH蜷@HlH]HH;Eu LHP[A^]!lIH]HEHtHW@H蝝lLݚl DUHAVSHPIHHHE(tlHþ HjlHHCHCXHC`HCXHCHHC@HC8HC0HC(HC HCPHCpHCxHCpHChƃHǃfǃHǃHǃƃHHǃHǃHǃHǃHǃHǃHǃHǃHǃHHHǃHǃHǃǃǃHǃ H] ;H5lH}H蚤>H53mH蛛>H5&pH̜>HHHQH5lH>HH;豒>HHH ӄHMH5HUHuHuIIFIF0INIVIF@H]HEHtH@H+lHHH;Eu LHP[A^]jlIH]HEHtH蠴@HlL&l fffff.UHAVSHPIH;HHE(贚lHþ H誚lHHCHCXHC`HCXHCHHC@HC8HC0HC(HC HCPHCpHCxHCpHChƃHǃfǃHǃHǃƃHHǃHǃHǃHǃHǃHǃHǃHǃHǃHHHǃHǃHǃǃǃHǃ H]M;H5=lH}Hڡ>H5smHۘ>H5fpH >HHHQH5#lH,>HH;>HHH ЄHMH%HUHuHuIIFIF0INIVIF@H]HEHtH%@HklHHH;Eu LHP[A^]誘lIH]HEHtH@H&lLfl fffff.UHAVSHPIH{HHE(lHþ HlHHCHCXHC`HCXHCHHC@HC8HC0HC(HC HCPHCpHCxHCpHChƃHǃfǃHǃHǃƃHHǃHǃHǃHǃHǃHǃHǃHǃHǃHHHǃHǃHǃǃǃHǃ H];H5}lH}H>H5mH>H5pHL>HH HQH5clHl>HH;1>HHH ΄HMHHUHuHuIIFIF0INIVIF@H]HEHtHe@H諕lH& HH;Eu LHP[A^]lIH]HEHtH @HflL覒l fffff.UHAVSHPIH HHE(4lHþ H*lHHCHCXHC`HCXHCHHC@HC8HC0HC(HC HCPHCpHCxHCpHChƃHǃfǃHǃHǃƃHHǃHǃHǃHǃHǃHǃHǃHǃHǃHHHǃHǃHǃǃǃHǃ H];H5lH}HZ>H5mH[>H5pH茔>HH HQH5lH謕>HH;q>HHH `˄HMH HUHuHuIIFIF0INIVIF@H]HEHtH襬@HlHf -HH;Eu LHP[A^]*lIH]HEHtH`@H覒lLl fffff.UHAVSHPIH HHE(tlHþ HjlHHCHCXHC`HCXHCHHC@HC8HC0HC(HC HCPHCpHCxHCpHChƃHǃfǃHǃHǃƃHHǃHǃHǃHǃHǃHǃHǃHǃHǃHHHǃHǃHǃǃǃHǃ H] ;H5lH}H蚙>H53mH蛐>H5&pH̑>HA H5lH>HH;踇>HHH ȄHMH<HUHuHuIIFIF0INIVIF@H]HEHtH@H2lHHH;Eu LHP[A^]qlIH]HEHtH觩@HlL-l DUHAVSHPIHKHHE(ďlHþ H躏lHHCHCXHC`HCXHCHHC@HC8HC0HC(HC HCPHCpHCxHCpHChƃHǃfǃHǃHǃƃHHǃHǃHǃHǃHǃHǃHǃHǃHǃHHHǃHǃHǃǃǃHǃ H]];H5MlH}H>H5mH>H5vpH>HA H5:lHC>HH;>HHH ńHMHHUHuHuIIFIF0INIVIF@H]HEHtH<@H肍lHHH;Eu LHP[A^]lIH]HEHtH@H=lL}l DUHAVSHPIHHHE(lHþ H -lHHCHCXHC`HCXHCHHC@HC8HC0HC(HC HCPHCpHCxHCpHChƃHǃfǃHǃHǃƃHHǃHǃHǃHǃHǃHǃHǃHǃHǃHHHǃHǃHǃǃǃHǃ H]譶;H5lH}H:>H5ײmH;>H5ƸpHl>HHHQH5lH茍>HH;Q>HHH @ÄHMHHUHuHuIIFIF0INIVIF@H]HEHtH腤@HˊlHFHH;Eu LHP[A^] -lIH]HEHtH@@H膊lLƇl fffff.UHAVSHPIHHHE(TlHþ HJlHHCHCXHC`HCXHCHHC@HC8HC0HC(HC HCPHCpHCxHCpHChƃHǃfǃHǃHǃƃHHǃHǃHǃHǃHǃHǃHǃHǃHǃHHHǃHǃHǃǃǃHǃ H]H5lHiH iH}d>H5mHu>H5pH覉>HH HQH5lHƊ>HH;>HHH zHMHHUHuHuIIFIF0INIVIF@H]HEHtH迡@HlHHH;Eu LHP[A^]DlIH]HEHtHz@HlLl UHAVSHPIHHHE(蔇lHþ H芇lHHCHCXHC`HCXHCHHC@HC8HC0HC(HC HCPHCpHCxHCpHChƃHǃfǃHǃHǃƃHHǃHǃHǃHǃHǃHǃHǃHǃHǃHHHǃHǃHǃǃǃHǃ H]H5"lHfH gH}褋>H5QmH赅>H5@pH>HH HQH5lH>HH;|>HHH HMH?HUHuHuIIFIF0INIVIF@H]HEHtH@HElHHH;Eu LHP[A^]脅lIH]HEHtH躞@HlL@l UHAVSHPIH[HHE(ԄlHþ HʄlHHCHCXHC`HCXHCHHC@HC8HC0HC(HC HCPHCpHCxHCpHChƃHǃfǃHǃHǃƃHHǃHǃHǃHǃHǃHǃHǃHǃHǃHHHǃHǃHǃǃǃHǃ H]H5blH,dH UdH}>H5mH>H5pH&>HA H5DlHM>HH;z>HHH HMHHUHuHuIIFIF0INIVIF@H]HEHtHF@H茂lHHH;Eu LHP[A^]˂lIH]HEHtH@HGlLl ffffff.UHAVSHPIHHHE(lHþ H -lHHCHCXHC`HCXHCHHC@HC8HC0HC(HC HCPHCpHCxHCpHChƃHǃfǃHǃHǃƃHHǃHǃHǃHǃHǃHǃHǃHǃHǃHHHǃHǃHǃǃǃHǃ H]譫;H5lH}H:>H5ۧmH;>H5ƭpHl>HHHQH5lH茂>HH;Qw>HHH @HMH HUHuHuIIFIF0INIVIF@H]HEHtH腙@HlHFHH;Eu LHP[A^] -lIH]HEHtH@@HlL|l fffff.UHAVSHPIHHHE(TlHþ HJlHHCHCXHC`HCXHCHHC@HC8HC0HC(HC HCPHCpHCxHCpHChƃHǃfǃHǃHǃƃHHǃHǃHǃHǃHǃHǃHǃHǃHǃHHHǃHǃHǃǃǃHǃ H]H5lH^H _H}d>H5mHu}>H5pH~>HH HQH5lH>HH;t>HHH zHMH -HUHuHuIIFIF0INIVIF@H]HEHtH迖@H}lHHH;Eu LHP[A^]D}lIH]HEHtHz@H|lLzl UHAVSHPIHHHE(|lHþ H|lHHCHCXHC`HCXHCHHC@HC8HC0HC(HC HCPHCpHCxHCpHChƃHǃfǃHǃHǃƃHHǃHǃHǃHǃHǃHǃHǃHǃHǃHHHǃHǃHǃǃǃHǃ H]H5"lHL\H u\H}褀>H5UmHz>H5@pH{>HH HQH5lH}>HH;q>HHH HMH/HUHuHuIIFIF0INIVIF@H]HEHtH@HEzlHHH;Eu LHP[A^]zlIH]HEHtH躓@HzlL@wl UHAVSHPIH[HHE(ylHþ HylHHCHCXHC`HCXHCHHC@HC8HC0HC(HC HCPHCpHCxHCpHChƃHǃfǃHǃHǃƃHHǃHǃHǃHǃHǃHǃHǃHǃHǃHHHǃHǃHǃǃǃHǃ H]H5blHYH YH}}>H5mHw>H5pH&y>HA H5DlHMz>HH;o>HHH HMHHUHuHuIIFIF0INIVIF@H]HEHtHF@HwlHHH;Eu LHP[A^]wlIH]HEHtH@HGwlLtl ffffff.UHAVSHPIHHHE(wlHþ H -wlHHCHCXHC`HCXHCHHC@HC8HC0HC(HC HCPHCpHCxHCpHChƃHǃfǃHǃHǃƃHHǃHǃHǃHǃHǃHǃHǃHǃHǃHHHǃHǃHǃǃǃHǃ H]譠;H5lH}H:~>HR;H5mHH ~>H5ŜmH!u>H5pHRv>HHHQH5ilHrw>HH;7l>HHH &HMH[HUHuHuIIFIF0INIVIF@H]HEHtHk@HtlH,HH;Eu LHP[A^]tlIH]HEHtH&@HltlLql @UHAVSHPIHHHE(DtlHþ H:tlHHCHCXHC`HCXHCHHC@HC8HC0HC(HC HCPHCpHCxHCpHChƃHǃfǃHǃHǃƃHHǃHǃHǃHǃHǃHǃHǃHǃHǃHHHǃHǃHǃǃǃHǃ H]ݣ;H5lH}Hj{>H肞;H5mHHP{>H5mHQr>H5ܟpHs>HHHQH5lHt>HH;gi>HHH VHMHHUHuHuIIFIF0INIVIF@H]HEHtH蛋@HqlH\HH;Eu LHP[A^] rlIH]HEHtHV@HqlLnl @UHAVSHPIHHHE(tqlHþ HjqlHHCHCXHC`HCXHCHHC@HC8HC0HC(HC HCPHCpHCxHCpHChƃHǃfǃHǃHǃƃHHǃHǃHǃHǃHǃHǃHǃHǃHǃHHHǃHǃHǃǃǃHǃ H] ;H5|lH}Hx>H貛;H5 mHHx>H5%mHo>H5 pHp>HH HQH5ɳlHq>HH;f>HHH HMH -HUHuHuIIFIF0INIVIF@H]HEHtHˈ@HolHHH;Eu LHP[A^]PolIH]HEHtH膈@HnlL ll @UHAVSHPIH+HHE(nlHþ HnlHHCHCXHC`HCXHCHHC@HC8HC0HC(HC HCPHCpHCxHCpHChƃHǃfǃHǃHǃƃHHǃHǃHǃHǃHǃHǃHǃHǃHǃHHHǃHǃHǃǃǃHǃ H]=;H5-zlH}Hu>H;H5PmHHu>H5UmHl>H5<pHm>HH HQH5lHo>HH;c>HHH HMH[HUHuHuIIFIF0INIVIF@H]HEHtH@HAllHHH;Eu LHP[A^]llIH]HEHtH超@HklL<il @UHAVSHPIH[HHE(klHþ HklHHCHCXHC`HCXHCHHC@HC8HC0HC(HC HCPHCpHCxHCpHChƃHǃfǃHǃHǃƃHHǃHǃHǃHǃHǃHǃHǃHǃHǃHHHǃHǃHǃǃǃHǃ H]譔;H5]wlH}Hr>H;H5mHHr>H5mHi>H5lpHk>HH HQH5)lH2l>HH;`>HHH 桄HMHHUHuHuIIFIF0INIVIF@H]HEHtH+@HqilHHH;Eu 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H+HH;EH0[A^]M9v tTHLPH{ HP IF HC HHHQI~ HP HC IF H[ HHH;EtpHHuPH{ HP HC I~ HHPI~ HP IF H[ HEH}LPHEH}P Mv HXHH;E-mH+H+fDUHAVSH0IHHHHEI9tH{ H9t.IF I9tKHC I~ HHH;EH0[A^]M9v tTHLPH{ HP IF HC HHHQI~ HP HC IF H[ HHH;EtpHHuPH{ HP HC I~ HHPI~ HP IF H[ HEH}LPHEH}P Mv HHH;E-ĄmHN*HF*fDUHAVSH0IHHHHEI9tH{ H9t.IF I9tKHC I~ HHH;EH0[A^]M9v tTHLPH{ HP IF HC HHHQI~ HP HC IF H[ HFHH;EtpHHuPH{ HP HC I~ HHPI~ HP IF H[ HEH}LPHEH}P Mv HHH;E-脃mH)H)fDUHAWAVAUATSH8LLHHIHHsHHEH8HHHHLH@H8L7mHHEEL-MuLI@L8LBmL=ILHDž(HDž HDžHDžDž0I$H薄mHHH8+HHHrmHHH+HHDHHH;mHHH*HH0HYmHHH0LL8Lt H EmH%mH5\HHmH8ȀmHHH;EuHH8[A\A]A^A_]LmHLL8Lt H 迀mHm+H&H&H&H&H{&HH5HH mH8mHM&HH8mH6&fDUHAWAVAUATSHILgLoLL)HH9LM)MII6HH=HM)LHHH9H}LE +II9LBMDHuI9mHH5DmH}mHHHH5HHmLHHr IGL9`ILHL9MLCHHtHIHHHHuI@IHIHPIHPIHPIHP IHP(IHP0IHP8H@HuTHuIJ<~mIHuO LHHr IOL9)ILHL9HZHHt$Hffffff.IHHHHuHj@IHIHAIHAIHAIHA IHA(IHA0IHA8H@Hu IIIPHHAHA~fpDHPH)1fDAADAD AD0HHuHtA~fpDAADI9IHGHHHHHHDBAH%A~fpDK|0IHH)1fffff.DDDHHuMtA~fpDAADH9O4M<MH]~LHLM,~mMHELLxLpHtHH[A\A]A^A_]y|mH[A\A]A^A_]E1E1KHL)LCHH3I HH)HZHH1H1M.`ymIH|mL/ym UHAVSH0IHHhHHEI9tH{ H9t.IF I9tKHC I~ H;HH;EH0[A^]M9v tTHLPH{ HP IF HC HHHQI~ HP HC IF H[ H߄HH;EtpHHuPH{ HP HC I~ HHPI~ HP IF H[ HEH}LPHEH}P Mv Hh߄HH;E-{mH H fDUHAVSH0IHH(߄HHEI9tH{ H9t.IF I9tKHC I~ HބHH;EH0[A^]M9v tTHLPH{ HP IF HC HHHQI~ HP HC IF H[ HބHH;EtpHHuPH{ HP HC I~ HHPI~ HP IF H[ HEH}LPHEH}P Mv H(ބHH;E-ymH^HVfDUHAVSH0IHH݄HHEI9tH{ H9t.IF I9tKHC I~ H݄HH;EH0[A^]M9v tTHLPH{ HP IF HC HHHQI~ HP HC IF H[ HV݄HH;EtpHHuPH{ HP HC I~ HHPI~ HP IF H[ HEH}LPHEH}P Mv H܄HH;E-xmHHfDUHH)HHGHHwHH]^Rfffff.UHAVSHPIH{܄HHE(wmHþ HwmHHCHCXHC`HCXHCHHC@HC8HC0HC(HC HCPHCpHCxHCpHChƃHǃfǃHǃHǃƃHHǃHǃHǃHǃHǃHǃHǃHǃHǃHHHǃHǃHǃǃǃHǃ H]蝥<H5]mH}H*?H5ȣmH+z?H51qH\{?HH HQH5CmH||?HH;Aq?HHH HMHsHUHuHuIIFIF0INIVIF@H]HEHtH5AHumH&ڄHH;Eu LHP[A^]umIH]HEHtHAHFumLrm fffff.UHAVSHPIHلHHE(umHþ H +umHHCHCXHC`HCXHCHHC@HC8HC0HC(HC HCPHCpHCxHCpHChƃHǃfǃHǃHǃƃHHǃHǃHǃHǃHǃHǃHǃHǃHǃHHHǃHǃHǃǃǃHǃ H]ݨ<H5mH}Hj?H5mHkw?H5qqHx?HH HQH5mHy?HH;n?HHH `HMHHUHuHuIIFIF0INIVIF@H]HEHtHuAHrmHfׄHH;Eu LHP[A^] +smIH]HEHtH0AHrmLom fffff.UHAVSHPIHքHHE(TrmHþ HJrmHHCHCXHC`HCXHCHHC@HC8HC0HC(HC HCPHCpHCxHCpHChƃHǃfǃHǃHǃƃHHǃHǃHǃHǃHǃHǃHǃHǃHǃHHHǃHǃHǃǃǃHǃ H]]<H5}mH}H}?H5HmHt?H5qHu?HH HQH5ômHv?HH;k?HHH HMHHUHuHuIIFIF0INIVIF@H]HEHtH赉AH pmHԄHH;Eu LHP[A^]JpmIH]HEHtHpAHomLmm fffff.UHAVSHPIH;ԄHHE(omHþ HomHHCHCXHC`HCXHCHHC@HC8HC0HC(HC HCPHCpHCxHCpHChƃHǃfǃHǃHǃƃHHǃHǃHǃHǃHǃHǃHǃHǃHǃHHHǃHǃHǃǃǃHǃ H]蝢<H5{mH}Hz?H5mHq?H5qHs?HH HQH5mH<t?HH;i?HHH HMHHUHuHuIIFIF0INIVIF@H]HEHtHAHKmmHфHH;Eu LHP[A^]mmIH]HEHtH谆AHmmLFjm fffff.UHAVSHPIH{фHHE(lmHþ HlmHHCHCXHC`HCXHCHHC@HC8HC0HC(HC HCPHCpHCxHCpHChƃHǃfǃHǃHǃƃHHǃHǃHǃHǃHǃHǃHǃHǃHǃHHHǃHǃHǃǃǃHǃ H]蝚<H5]xmH}H*x?H5ȘmH+o?H51qH\p?HH HQH5CmH|q?HH;Af?HHH HMH5HUHuHuIIFIF0INIVIF@H]HEHtH5AHjmH&τHH;Eu LHP[A^]jmIH]HEHtHAHFjmLgm fffff.UHAVSHPIH΄HHE(jmHþ H +jmHHCHCXHC`HCXHCHHC@HC8HC0HC(HC HCPHCpHCxHCpHChƃHǃfǃHǃHǃƃHHǃHǃHǃHǃHǃHǃHǃHǃHǃHHHǃHǃHǃǃǃHǃ H]ݝ<H5umH}Hju?H5mHkl?H5qqHm?HH HQH5mHn?HH;c?HHH `HMHգHUHuHuIIFIF0INIVIF@H]HEHtHuAHgmHf̄HH;Eu LHP[A^] +hmIH]HEHtH0AHgmLdm fffff.UHAVSHPIH˄HHE(TgmHþ HJgmHHCHCXHC`HCXHCHHC@HC8HC0HC(HC HCPHCpHCxHCpHChƃHǃfǃHǃHǃƃHHǃHǃHǃHǃHǃHǃHǃHǃHǃHHHǃHǃHǃǃǃHǃ H]]<H5rmH}Hr?H5HmHi?H5qHj?HH HQH5émHk?HH;`?HHH HMHuHUHuHuIIFIF0INIVIF@H]HEHtH~AH emHɄHH;Eu LHP[A^]JemIH]HEHtHp~AHdmLbm fffff.UHAVSHPIH;ɄHHE(dmHþ HdmHHCHCXHC`HCXHCHHC@HC8HC0HC(HC HCPHCpHCxHCpHChƃHǃfǃHǃHǃƃHHǃHǃHǃHǃHǃHǃHǃHǃHǃHHHǃHǃHǃǃǃHǃ H]蝗<H5pmH}Ho?H5mHf?H5qHh?HH HQH5mH<i?HH;^?HHH HMHHUHuHuIIFIF0INIVIF@H]HEHtH{AHKbmHƄHH;Eu LHP[A^]bmIH]HEHtH{AHbmLF_m fffff.UHAVSHPIH{ƄHHE(amHþ HamHHCHCXHC`HCXHCHHC@HC8HC0HC(HC HCPHCpHCxHCpHChƃHǃfǃHǃHǃƃHHǃHǃHǃHǃHǃHǃHǃHǃHǃHHHǃHǃHǃǃǃHǃ H]蝏<H5]mmH}H*m?H5ȍmH+d?H51qH\e?HAH5JmHf?HH;H[?HHH 'HMHHUHuHuIIFIF0INIVIF@H]HEHtH<yAH_mH-ĄHH;Eu LHP[A^]_mIH]HEHtHxAHM_mL\m DUHAVSHPIHÄHHE($_mHþ H_mHHCHCXHC`HCXHCHHC@HC8HC0HC(HC HCPHCpHCxHCpHChƃHǃfǃHǃHǃƃHHǃHǃHǃHǃHǃHǃHǃHǃHǃHHHǃHǃHǃǃǃHǃ H]<H5jmH}Hzj?H5mH{a?H5qHb?HAH5mHc?HH;X?HHH wHMHlHUHuHuIIFIF0INIVIF@H]HEHtHvAH\mH}HH;Eu LHP[A^]!]mIH]HEHtHGvAH\mLYm DUHAVSHPIHHHE(t\mHþ Hj\mHHCHCXHC`HCXHCHHC@HC8HC0HC(HC HCPHCpHCxHCpHChƃHǃfǃHǃHǃƃHHǃHǃHǃHǃHǃHǃHǃHǃHǃHHHǃHǃHǃǃǃHǃ H]}<H5gmH}Hg?H5hmH^?H5чqH_?HAH5mH#a?HH;U?HHH HMHHUHuHuIIFIF0INIVIF@H]HEHtHsAH2ZmH;HH;Eu LHP[A^]qZmIH]HEHtHsAHYmL-Wm DUHAVSHPIHkHHE(YmHþ HYmHHCHCXHC`HCXHCHHC@HC8HC0HC(HC HCPHCpHCxHCpHChƃHǃfǃHǃHǃƃHHǃHǃHǃHǃHǃHǃHǃHǃHǃHHHǃHǃHǃǃǃHǃ H]͌<H5MemH}He?H5mH\?H5!qHL]?HAH5:mHs^?HH;8S?HHH }HMH̕HUHuHuIIFIF0INIVIF@H]HEHtH,qAHWmHHH;Eu LHP[A^]WmIH]HEHtHpAH=WmL}Tm DUHAVSHPIHHHE(WmHþ H +WmHHCHCXHC`HCXHCHHC@HC8HC0HC(HC HCPHCpHCxHCpHChƃHǃfǃHǃHǃƃHHǃHǃHǃHǃHǃHǃHǃHǃHǃHHHǃHǃHǃǃǃHǃ H]݄<H5bmH}Hjb?H5|nHkY?H5qqHZ?HH HQH5mH[?HH;P?HHH `zHMHuHUHuHuIIFIF0INIVIF@H]HEHtHunAHTmHfHH;Eu LHP[A^] +UmIH]HEHtH0nAHTmLQm fffff.UHAVSHPIHHHE(TTmHþ HJTmHHCHCXHC`HCXHCHHC@HC8HC0HC(HC HCPHCpHCxHCpHChƃHǃfǃHǃHǃƃHHǃHǃHǃHǃHǃHǃHǃHǃHǃHHHǃHǃHǃǃǃHǃ H]<H5_mH}H_?H5ynHV?H5qHW?HH HQH5ÖmHX?HH;M?HHH wHMHeHUHuHuIIFIF0INIVIF@H]HEHtHkAH RmHHH;Eu LHP[A^]JRmIH]HEHtHpkAHQmLOm fffff.UHAVSHPIH;HHE(QmHþ HQmHHCHCXHC`HCXHCHHC@HC8HC0HC(HC HCPHCpHCxHCpHChƃHǃfǃHǃHǃƃHHǃHǃHǃHǃHǃHǃHǃHǃHǃHHHǃHǃHǃǃǃHǃ H]~<H5]mH}H\?H5#wnHS?H5|qHU?HH HQH5mH<V?HH;K?HHH tHMHHUHuHuIIFIF0INIVIF@H]HEHtHhAHKOmH泄HH;Eu LHP[A^]OmIH]HEHtHhAHOmLFLm fffff.UHAVSHPIH{HHE(NmHþ HNmHHCHCXHC`HCXHCHHC@HC8HC0HC(HC HCPHCpHCxHCpHChƃHǃfǃHǃHǃƃHHǃHǃHǃHǃHǃHǃHǃHǃHǃHHHǃHǃHǃǃǃHǃ H]݁<H5]ZmH}H*Z?H5ctnH+Q?H51zqH\R?HH HQH5CmH|S?HH;AH?HHH rHMHHUHuHuIIFIF0INIVIF@H]HEHtH5fAHLmH&HH;Eu LHP[A^]LmIH]HEHtHeAHFLmLIm fffff.UHAVSHPIHHHE(LmHþ H +LmHHCHCXHC`HCXHCHHC@HC8HC0HC(HC HCPHCpHCxHCpHChƃHǃfǃHǃHǃƃHHǃHǃHǃHǃHǃHǃHǃHǃHǃHHHǃHǃHǃǃǃHǃ H]y<H5WmH}HjW?H5qnHkN?H5qwqHO?HH HQH5mHP?HH;E?HHH `oHMHuHUHuHuIIFIF0INIVIF@H]HEHtHucAHImHfHH;Eu LHP[A^] +JmIH]HEHtH0cAHImLFm fffff.UHAVSHPIHHHE(TImHþ HJImHHCHCXHC`HCXHCHHC@HC8HC0HC(HC HCPHCpHCxHCpHChƃHǃfǃHǃHǃƃHHǃHǃHǃHǃHǃHǃHǃHǃHǃHHHǃHǃHǃǃǃHǃ H]}<H5TmH}HT?H5nnHK?H5tqHL?HH HQH5ËmHM?HH;B?HHH lHMHHUHuHuIIFIF0INIVIF@H]HEHtH`AH GmHHH;Eu LHP[A^]JGmIH]HEHtHp`AHFmLDm fffff.UHAVSHPIH;HHE(FmHþ HFmHHCHCXHC`HCXHCHHC@HC8HC0HC(HC HCPHCpHCxHCpHChƃHǃfǃHǃHǃƃHHǃHǃHǃHǃHǃHǃHǃHǃHǃHHHǃHǃHǃǃǃHǃ H]s<H5RmH}HQ?H5#lnHH?H5qqHJ?HH HQH5mH<K?HH;@?HHH iHMHHUHuHuIIFIF0INIVIF@H]HEHtH]AHKDmH樄HH;Eu LHP[A^]DmIH]HEHtH]AHDmLFAm fffff.UHAVSHPIH{HHE(CmHþ HCmHHCHCXHC`HCXHCHHC@HC8HC0HC(HC HCPHCpHCxHCpHChƃHǃfǃHǃHǃƃHHǃHǃHǃHǃHǃHǃHǃHǃHǃHHHǃHǃHǃǃǃHǃ H]v<H5]OmH}H*O?H5cinH+F?H51oqH\G?HH HQH5CmH|H?HH;A=?HHH gHMHUHUHuHuIIFIF0INIVIF@H]HEHtH5[AHAmH&HH;Eu LHP[A^]AmIH]HEHtHZAHFAmL>m fffff.UHAVSHPIHHHE(AmHþ H +AmHHCHCXHC`HCXHCHHC@HC8HC0HC(HC HCPHCpHCxHCpHChƃHǃfǃHǃHǃƃHHǃHǃHǃHǃHǃHǃHǃHǃHǃHHHǃHǃHǃǃǃHǃ H]n<H5LmH}HjL?H5fnHkC?H5qlqHD?HAH5mHE?HH;:?HHH gdHMHHUHuHuIIFIF0INIVIF@H]HEHtH|XAH>mHmHH;Eu LHP[A^]?mIH]HEHtH7XAH>mL;m DUHAVSHPIH HHE(d>mHþ HZ>mHHCHCXHC`HCXHCHHC@HC8HC0HC(HC HCPHCpHCxHCpHChƃHǃfǃHǃHǃƃHHǃHǃHǃHǃHǃHǃHǃHǃHǃHHHǃHǃHǃǃǃHǃ H]-r<H5ImH}HI?H5cnH@?H5iqHA?HAH5ڀmHC?HH;7?HHH aHMHHUHuHuIIFIF0INIVIF@H]HEHtHUAH"<mHHH;Eu LHP[A^]a<mIH]HEHtHUAH;mL9m DUHAVSHPIH[HHE(;mHþ H;mHHCHCXHC`HCXHCHHC@HC8HC0HC(HC HCPHCpHCxHCpHChƃHǃfǃHǃHǃƃHHǃHǃHǃHǃHǃHǃHǃHǃHǃHHHǃHǃHǃǃǃHǃ H]h<H5=GmH}H +G?H5CanH >?H5gqH<??HAH5*~mHc@?HH;(5?HHH _HMH\HUHuHuIIFIF0INIVIF@H]HEHtHSAHr9mH HH;Eu LHP[A^]9mIH]HEHtHRAH-9mLm6m DUHAVSHPIHHHE(9mHþ H8mHHCHCXHC`HCXHCHHC@HC8HC0HC(HC HCPHCpHCxHCpHChƃHǃfǃHǃHǃƃHHǃHǃHǃHǃHǃHǃHǃHǃHǃHHHǃHǃHǃǃǃHǃ H] l<H5DmH}HZD?H5^nH[;?H5adqH<?HAH5z{mH=?HH;x2?HHH W\HMH HUHuHuIIFIF0INIVIF@H]HEHtHlPAH6mH]HH;Eu LHP[A^]7mIH]HEHtH'PAH}6mL3m DUHAVSHPIHHHE(T6mHþ HJ6mHHCHCXHC`HCXHCHHC@HC8HC0HC(HC HCPHCpHCxHCpHChƃHǃfǃHǃHǃƃHHǃHǃHǃHǃHǃHǃHǃHǃHǃHHHǃHǃHǃǃǃHǃ H]d<H5AmH}HA?H5[nH8?H5aqH9?HH HQH5xmH:?HH;/?HHH YHMHHUHuHuIIFIF0INIVIF@H]HEHtHMAH 4mHHH;Eu LHP[A^]J4mIH]HEHtHpMAH3mL1m fffff.UHAVSHPIH;HHE(3mHþ H3mHHCHCXHC`HCXHCHHC@HC8HC0HC(HC HCPHCpHCxHCpHChƃHǃfǃHǃHǃƃHHǃHǃHǃHǃHǃHǃHǃHǃHǃHHHǃHǃHǃǃǃHǃ H]]g<H5?mH}H>?H5'YnH5?H5^qH7?HH HQH5vmH<8?HH;-?HHH VHMHHUHuHuIIFIF0INIVIF@H]HEHtHJAHK1mH敄HH;Eu LHP[A^]1mIH]HEHtHJAH1mLF.m fffff.UHAVSHPIH{HHE(0mHþ H0mHHCHCXHC`HCXHCHHC@HC8HC0HC(HC HCPHCpHCxHCpHChƃHǃfǃHǃHǃƃHHǃHǃHǃHǃHǃHǃHǃHǃHǃHHHǃHǃHǃǃǃHǃ H]]<H5]<mH}H*<?H5gVnH+3?H51\qH\4?HH HQH5CsmH|5?HH;A*?HHH THMHHUHuHuIIFIF0INIVIF@H]HEHtH5HAH.mH&HH;Eu LHP[A^].mIH]HEHtHGAHF.mL+m fffff.UHAVSHPIHHHE(.mHþ H +.mHHCHCXHC`HCXHCHHC@HC8HC0HC(HC HCPHCpHCxHCpHChƃHǃfǃHǃHǃƃHHǃHǃHǃHǃHǃHǃHǃHǃHǃHHHǃHǃHǃǃǃHǃ H]a<H59mH}Hj9?H5SnHk0?H5qYqH1?HH HQH5pmH2?HH;'?HHH `QHMHHUHuHuIIFIF0INIVIF@H]HEHtHuEAH+mHfHH;Eu LHP[A^] +,mIH]HEHtH0EAH+mL(m fffff.UHAVSHPIHHHE(T+mHþ HJ+mHHCHCXHC`HCXHCHHC@HC8HC0HC(HC HCPHCpHCxHCpHChƃHǃfǃHǃHǃƃHHǃHǃHǃHǃHǃHǃHǃHǃHǃHHHǃHǃHǃǃǃHǃ H]Y<H56mH}H6?H5PnH-?H5VqH.?HH HQH5mmH/?HH;$?HHH NHMHHUHuHuIIFIF0INIVIF@H]HEHtHBAH )mHHH;Eu LHP[A^]J)mIH]HEHtHpBAH(mL&m fffff.UHAVSHPIH;HHE((mHþ H(mHHCHCXHC`HCXHCHHC@HC8HC0HC(HC HCPHCpHCxHCpHChƃHǃfǃHǃHǃƃHHǃHǃHǃHǃHǃHǃHǃHǃHǃHHHǃHǃHǃǃǃHǃ H]]\<H54mH}H3?H5'NnH*?H5SqH,?HH HQH5kmH<-?HH;"?HHH KHMHeHUHuHuIIFIF0INIVIF@H]HEHtH?AHK&mH抄HH;Eu LHP[A^]&mIH]HEHtH?AH&mLF#m fffff.UHAVSHPIH{HHE(%mHþ H%mHHCHCXHC`HCXHCHHC@HC8HC0HC(HC HCPHCpHCxHCpHChƃHǃfǃHǃHǃƃHHǃHǃHǃHǃHǃHǃHǃHǃHǃHHHǃHǃHǃǃǃHǃ H]R<H5]1mH}H*1?H5gKnH+(?H51QqH\)?HH HQH5ChmH|*?HH;A?HHH IHMHHUHuHuIIFIF0INIVIF@H]HEHtH5=AH#mH&HH;Eu LHP[A^]#mIH]HEHtH<AHF#mL m fffff.UHAVSHPIHHHE(#mHþ H +#mHHCHCXHC`HCXHCHHC@HC8HC0HC(HC HCPHCpHCxHCpHChƃHǃfǃHǃHǃƃHHǃHǃHǃHǃHǃHǃHǃHǃHǃHHHǃHǃHǃǃǃHǃ H]V<H5.mH}Hj.?H5HnHk%?H5qNqH&?HH HQH5emH'?HH;?HHH `FHMHHUHuHuIIFIF0INIVIF@H]HEHtHu:AH mHfHH;Eu LHP[A^] +!mIH]HEHtH0:AH mLm fffff.UHAVSHPIHHHE(T mHþ HJ mHHCHCXHC`HCXHCHHC@HC8HC0HC(HC HCPHCpHCxHCpHChƃHǃfǃHǃHǃƃHHǃHǃHǃHǃHǃHǃHǃHǃHǃHHHǃHǃHǃǃǃHǃ H]N<H5+mH}H+?H5EnH"?H5KqH#?HAH5bmH%?HH;?HHH CHMHLHUHuHuIIFIF0INIVIF@H]HEHtH7AHmHHH;Eu LHP[A^]QmIH]HEHtHw7AHmL m DUHAVSHPIHKHHE(mHþ HmHHCHCXHC`HCXHCHHC@HC8HC0HC(HC HCPHCpHCxHCpHChƃHǃfǃHǃHǃƃHHǃHǃHǃHǃHǃHǃHǃHǃHǃHHHǃHǃHǃǃǃHǃ H]mQ<H5-)mH}H(?H57CnH?H5IqH,!?HAH5`mHS"?HH;?HHH @HMHHUHuHuIIFIF0INIVIF@H]HEHtH 5AHbmHHH;Eu LHP[A^]mIH]HEHtH4AHmL]m DUHAVSHPIHHHE(mHþ HmHHCHCXHC`HCXHCHHC@HC8HC0HC(HC HCPHCpHCxHCpHChƃHǃfǃHǃHǃƃHHǃHǃHǃHǃHǃHǃHǃHǃHǃHHHǃHǃHǃǃǃHǃ H]G<H5}&mH}HJ&?H5@nHK?H5QFqH|?HAH5j]mH?HH;h?HHH G>HMHHUHuHuIIFIF0INIVIF@H]HEHtH\2AHmHM}HH;Eu LHP[A^]mIH]HEHtH2AHmmLm DUHAVSHPIH|HHE(DmHþ H:mHHCHCXHC`HCXHCHHC@HC8HC0HC(HC HCPHCpHCxHCpHChƃHǃfǃHǃHǃƃHHǃHǃHǃHǃHǃHǃHǃHǃHǃHHHǃHǃHǃǃǃHǃ H]MK<H5#mH}H#?H5=nH?H5CqH?HAH5ZmH?HH;?HHH ;HMH\HUHuHuIIFIF0INIVIF@H]HEHtH/AHmHzHH;Eu LHP[A^]AmIH]HEHtHg/AHmLm DUHAVSHPIH;zHHE(mHþ HmHHCHCXHC`HCXHCHHC@HC8HC0HC(HC HCPHCpHCxHCpHChƃHǃfǃHǃHǃƃHHǃHǃHǃHǃHǃHǃHǃHǃHǃHHHǃHǃHǃǃǃHǃ H]]C<H5!mH}H ?H5+;nH?H5@qH?HH HQH5XmH<?HH;?HHH 8HMHHUHuHuIIFIF0INIVIF@H]HEHtH,AHKmHwHH;Eu LHP[A^]mIH]HEHtH,AHmLFm fffff.UHAVSHPIH{wHHE(mHþ HmHHCHCXHC`HCXHCHHC@HC8HC0HC(HC HCPHCpHCxHCpHChƃHǃfǃHǃHǃƃHHǃHǃHǃHǃHǃHǃHǃHǃHǃHHHǃHǃHǃǃǃHǃ H]F<H5]mH}H*?H5k8nH+?H51>qH\?HH HQH5CUmH|?HH;A ?HHH 6HMHHUHuHuIIFIF0INIVIF@H]HEHtH5*AHmH&uHH;Eu LHP[A^]mIH]HEHtH)AHFmL m fffff.UHAVSHPIHtHHE(mHþ H +mHHCHCXHC`HCXHCHHC@HC8HC0HC(HC HCPHCpHCxHCpHChƃHǃfǃHǃHǃƃHHǃHǃHǃHǃHǃHǃHǃHǃHǃHHHǃHǃHǃǃǃHǃ H]=<H5mH}Hj?H55nHk?H5q;qH?HH HQH5RmH?HH; ?HHH `3HMHHUHuHuIIFIF0INIVIF@H]HEHtHu'AH mHfrHH;Eu LHP[A^] +mIH]HEHtH0'AH mL +m fffff.UHAVSHPIHqHHE(T mHþ HJ mHHCHCXHC`HCXHCHHC@HC8HC0HC(HC HCPHCpHCxHCpHChƃHǃfǃHǃHǃƃHHǃHǃHǃHǃHǃHǃHǃHǃHǃHHHǃHǃHǃǃǃHǃ H]]@<H5mH}H?H52nH?H58qH?HH HQH5OmH?HH;?HHH 0HMHHUHuHuIIFIF0INIVIF@H]HEHtH$AH mHoHH;Eu LHP[A^]J mIH]HEHtHp$AH +mLm fffff.UHAVSHPIH;oHHE( +mHþ H +mHHCHCXHC`HCXHCHHC@HC8HC0HC(HC HCPHCpHCxHCpHChƃHǃfǃHǃHǃƃHHǃHǃHǃHǃHǃHǃHǃHǃHǃHHHǃHǃHǃǃǃHǃ H]]8<H5mH}H?H5+0nH ?H55qH?HH HQH5MmH<?HH;?HHH -HMHHUHuHuIIFIF0INIVIF@H]HEHtH!AHKmHlHH;Eu LHP[A^]mIH]HEHtH!AHmLFm fffff.UHAVSHPIH{lHHE(mHþ HmHHCHCXHC`HCXHCHHC@HC8HC0HC(HC HCPHCpHCxHCpHChƃHǃfǃHǃHǃƃHHǃHǃHǃHǃHǃHǃHǃHǃHǃHHHǃHǃHǃǃǃHǃ H];<H5]mH}H*?H5k-nH+ +?H513qH\ ?HH HQH5CJmH| ?HH;A?HHH +HMHHUHuHuIIFIF0INIVIF@H]HEHtH5AHmH&jHH;Eu LHP[A^]mIH]HEHtHAHFmLm fffff.UHAVSHPIHiHHE(mHþ H +mHHCHCXHC`HCXHCHHC@HC8HC0HC(HC HCPHCpHCxHCpHChƃHǃfǃHǃHǃƃHHǃHǃHǃHǃHǃHǃHǃHǃHǃHHHǃHǃHǃǃǃHǃ H]2<H5mH}Hj?H5*nHk?H5q0qH?HH HQH5GmH ?HH;>HHH `(HMH5HUHuHuIIFIF0INIVIF@H]HEHtHuAHmHfgHH;Eu LHP[A^] +mIH]HEHtH0AHmLl fffff.UHAVSHPIHfHHE(TmHþ HJmHHCHCXHC`HCXHCHHC@HC8HC0HC(HC HCPHCpHCxHCpHChƃHǃfǃHǃHǃƃHHǃHǃHǃHǃHǃHǃHǃHǃHǃHHHǃHǃHǃǃǃHǃ H]]5<H5 mH}H ?H5'nH?H5-qH?HH HQH5DmH?HH;>HHH %HMHHUHuHuIIFIF0INIVIF@H]HEHtHAH mHdHH;Eu LHP[A^]JmIH]HEHtHpAHlLl fffff.UHAVSHPIH;dHHE(lHþ HlHHCHCXHC`HCXHCHHC@HC8HC0HC(HC HCPHCpHCxHCpHChƃHǃfǃHǃHǃƃHHǃHǃHǃHǃHǃHǃHǃHǃHǃHHHǃHǃHǃǃǃHǃ H]]-<H5 mH}H +?H5+%nH?H5*qH?HAH5 +BmHC?HH;>HHH "HMH|HUHuHuIIFIF0INIVIF@H]HEHtHAHRlHaHH;Eu LHP[A^]lIH]HEHtHAH lLMl DUHAVSHPIHaHHE(lHþ HlHHCHCXHC`HCXHCHHC@HC8HC0HC(HC HCPHCpHCxHCpHChƃHǃfǃHǃHǃƃHHǃHǃHǃHǃHǃHǃHǃHǃHǃHHHǃHǃHǃǃǃHǃ H]0<H5mmH}H:?H5{"nH;>H5A(qHl?HAH5Z?mH?HH;X>HHH 7 HMH,HUHuHuIIFIF0INIVIF@H]HEHtHLAHlH=_HH;Eu LHP[A^]lIH]HEHtHAH]lLl DUHAVSHPIH^HHE(4lHþ H*lHHCHCXHC`HCXHCHHC@HC8HC0HC(HC HCPHCpHCxHCpHChƃHǃfǃHǃHǃƃHHǃHǃHǃHǃHǃHǃHǃHǃHǃHHHǃHǃHǃǃǃHǃ H]='<H5mH}H?H5nH>H5%qH>HAH5<mH>HH;>HHH HMHHUHuHuIIFIF0INIVIF@H]HEHtHAHlH\HH;Eu LHP[A^]1lIH]HEHtHWAHlLl DUHAVSHPIH+\HHE(lHþ HzlHHCHCXHC`HCXHCHHC@HC8HC0HC(HC HCPHCpHCxHCpHChƃHǃfǃHǃHǃƃHHǃHǃHǃHǃHǃHǃHǃHǃHǃHHHǃHǃHǃǃǃHǃ H]*<H5 mH}H?H5nH>H5"qH >HAH59mH3>HH;>HHH HMHHUHuHuIIFIF0INIVIF@H]HEHtHAHBlHYHH;Eu LHP[A^]lIH]HEHtHAHlL=l DUHAVSHPIH{YHHE(lHþ HlHHCHCXHC`HCXHCHHC@HC8HC0HC(HC HCPHCpHCxHCpHChƃHǃfǃHǃHǃƃHHǃHǃHǃHǃHǃHǃHǃHǃHǃHHHǃHǃHǃǃǃHǃ H]"<H5]mH}H*?H5onH+>H51 qH\>HH HQH5C7mH|>HH;A>HHH HMH5HUHuHuIIFIF0INIVIF@H]HEHtH5 AHlH&WHH;Eu LHP[A^]lIH]HEHtH AHFlLl fffff.UHAVSHPIHVHHE(lHþ H +lHHCHCXHC`HCXHCHHC@HC8HC0HC(HC HCPHCpHCxHCpHChƃHǃfǃHǃHǃƃHHǃHǃHǃHǃHǃHǃHǃHǃHǃHHHǃHǃHǃǃǃHǃ H]%<H5lH}Hj>H5nHk>H5qqH>HH HQH54mH>HH;>HHH `HMH5HUHuHuIIFIF0INIVIF@H]HEHtHu AHlHfTHH;Eu LHP[A^] +lIH]HEHtH0 AHlLl fffff.UHAVSHPIHSHHE(TlHþ HJlHHCHCXHC`HCXHCHHC@HC8HC0HC(HC HCPHCpHCxHCpHChƃHǃfǃHǃHǃƃHHǃHǃHǃHǃHǃHǃHǃHǃHǃHHHǃHǃHǃǃǃHǃ H]]<H5lH}H>H5nH>H5qH>HH HQH51mH>HH;>HHH HMHHUHuHuIIFIF0INIVIF@H]HEHtHAH lHQHH;Eu LHP[A^]JlIH]HEHtHpAHlLl fffff.UHAVSHPIH;QHHE(lHþ HlHHCHCXHC`HCXHCHHC@HC8HC0HC(HC HCPHCpHCxHCpHChƃHǃfǃHǃHǃƃHHǃHǃHǃHǃHǃHǃHǃHǃHǃHHHǃHǃHǃǃǃHǃ H]<H5lH}H>H5/nH>H5qH>HH HQH5/mH<>HH;>HHH HMHHUHuHuIIFIF0INIVIF@H]HEHtHAHKlHNHH;Eu LHP[A^]lIH]HEHtHAHlLFl fffff.UHAVSHPIH{NHHE(lHþ HlHHCHCXHC`HCXHCHHC@HC8HC0HC(HC HCPHCpHCxHCpHChƃHǃfǃHǃHǃƃHHǃHǃHǃHǃHǃHǃHǃHǃHǃHHHǃHǃHǃǃǃHǃ H]<H5]lH}H*>H5onH+>H51qH\>HH HQH5C,mH|>HH;A>HHH HMH HUHuHuIIFIF0INIVIF@H]HEHtH5AHlH&LHH;Eu LHP[A^]lIH]HEHtHAHFlLl fffff.UHAVSHPIHKHHE(lHþ H +lHHCHCXHC`HCXHCHHC@HC8HC0HC(HC HCPHCpHCxHCpHChƃHǃfǃHǃHǃƃHHǃHǃHǃHǃHǃHǃHǃHǃHǃHHHǃHǃHǃǃǃHǃ H]<H5lH}Hj>H5 nHk>H5qqH>HH HQH5)mH>HH;>HHH ` +HMHeHUHuHuIIFIF0INIVIF@H]HEHtHu@HlHfIHH;Eu LHP[A^] +lIH]HEHtH0@HlLl fffff.UHAVSHPIHHHHE(TlHþ HJlHHCHCXHC`HCXHCHHC@HC8HC0HC(HC HCPHCpHCxHCpHChƃHǃfǃHǃHǃƃHHǃHǃHǃHǃHǃHǃHǃHǃHǃHHHǃHǃHǃǃǃHǃ H]<H5lH}H>H5 nH>H5qH>HH HQH5&mH>HH;>HHH HMHU"HUHuHuIIFIF0INIVIF@H]HEHtH@H lHFHH;Eu LHP[A^]JlIH]HEHtHp@HlLl fffff.UHAVSHPIH;FHHE(lHþ HlHHCHCXHC`HCXHCHHC@HC8HC0HC(HC HCPHCpHCxHCpHChƃHǃfǃHǃHǃƃHHǃHǃHǃHǃHǃHǃHǃHǃHǃHHHǃHǃHǃǃǃHǃ H]<H5lH}H>H5/nH>H5 qH>HH HQH5$mH<>HH;>HHH HMHU+HUHuHuIIFIF0INIVIF@H]HEHtH@HKlHCHH;Eu LHP[A^]lIH]HEHtH@HlLFl fffff.UHAVSHPIH{CHHE(lHþ HlHHCHCXHC`HCXHCHHC@HC8HC0HC(HC HCPHCpHCxHCpHChƃHǃfǃHǃHǃƃHHǃHǃHǃHǃHǃHǃHǃHǃHǃHHHǃHǃHǃǃǃHǃ H]]<H5]lH}H*>H5onH+>H51 +qH\>HH HQH5C!mH|>HH;A>HHH HMHu4HUHuHuIIFIF0INIVIF@H]HEHtH5@HlH&AHH;Eu LHP[A^]lIH]HEHtH@HFlLl fffff.UHAVSHPIH@HHE(lHþ H +lHHCHCXHC`HCXHCHHC@HC8HC0HC(HC HCPHCpHCxHCpHChƃHǃfǃHǃHǃƃHHǃHǃHǃHǃHǃHǃHǃHǃHǃHHHǃHǃHǃǃǃHǃ H]]<H5lH}Hj>H5nHk>H5qqH>HH HQH5mH>HH;>HHH `HMHu=HUHuHuIIFIF0INIVIF@H]HEHtHu@HlHf>HH;Eu LHP[A^] +lIH]HEHtH0@HlLl fffff.UHAVSHPIH=HHE(TlHþ HJlHHCHCXHC`HCXHCHHC@HC8HC0HC(HC HCPHCpHCxHCpHChƃHǃfǃHǃHǃƃHHǃHǃHǃHǃHǃHǃHǃHǃHǃHHHǃHǃHǃǃǃHǃ H]<H5lH}H>H5mH>H5qH>HA H5mH>HH;>HHH HMHFHUHuHuIIFIF0INIVIF@H]HEHtH@HlH;HH;Eu LHP[A^]QlIH]HEHtHw@HlL l DUHAVSHPIHK;HHE(lHþ HlHHCHCXHC`HCXHCHHC@HC8HC0HC(HC HCPHCpHCxHCpHChƃHǃfǃHǃHǃƃHHǃHǃHǃHǃHǃHǃHǃHǃHǃHHHǃHǃHǃǃǃHǃ H]m +<H5-lH}H>H5?mH>H5qH,>HA H5mHS>HH;>HHH HMH,DHUHuHuIIFIF0INIVIF@H]HEHtH @HblH8HH;Eu LHP[A^]lIH]HEHtH@HlL]l DUHAVSHPIH8HHE(lHþ HlHHCHCXHC`HCXHCHHC@HC8HC0HC(HC HCPHCpHCxHCpHChƃHǃfǃHǃHǃƃHHǃHǃHǃHǃHǃHǃHǃHǃHǃHHHǃHǃHǃǃǃHǃ H]<H5}lH}HJ>H5mHK>H5QpH|>HA H5jmH>HH;h>HHH GHMHAHUHuHuIIFIF0INIVIF@H]HEHtH\@HlHM6HH;Eu LHP[A^]lIH]HEHtH@HmlLl DUHAVSHPIH5HHE(DlHþ H:lHHCHCXHC`HCXHCHHC@HC8HC0HC(HC HCPHCpHCxHCpHChƃHǃfǃHǃHǃƃHHǃHǃHǃHǃHǃHǃHǃHǃHǃHHHǃHǃHǃǃǃHǃ H]<H5lH}H>H5mH>H5pH>HA H5mH>HH;>HHH HMHL?HUHuHuIIFIF0INIVIF@H]HEHtH@HlH3HH;Eu LHP[A^]AlIH]HEHtHg@HlLl DUHAVSHPIH;3HHE(lHþ HlHHCHCXHC`HCXHCHHC@HC8HC0HC(HC HCPHCpHCxHCpHChƃHǃfǃHǃHǃƃHHǃHǃHǃHǃHǃHǃHǃHǃHǃHHHǃHǃHǃǃǃHǃ H];H5lH}H>H5/mH>H5pH>HA H5 +mHC>HH;>HHH HMH<HUHuHuIIFIF0INIVIF@H]HEHtH@HRlH0HH;Eu LHP[A^]lIH]HEHtH@H lLMl DUHAVSHPIH0HHE(lHþ HlHHCHCXHC`HCXHCHHC@HC8HC0HC(HC HCPHCpHCxHCpHChƃHǃfǃHǃHǃƃHHǃHǃHǃHǃHǃHǃHǃHǃHǃHHHǃHǃHǃǃǃHǃ H];H5mlH}H:>H5mH;>H5ApHl>HA H5ZmH>HH;X>HHH 7HMHl:HUHuHuIIFIF0INIVIF@H]HEHtHL@HlH=.HH;Eu LHP[A^]lIH]HEHtH@H]lLl DUHAVSHPIH-HHE(4lHþ H*lHHCHCXHC`HCXHCHHC@HC8HC0HC(HC HCPHCpHCxHCpHChƃHǃfǃHǃHǃƃHHǃHǃHǃHǃHǃHǃHǃHǃHǃHHHǃHǃHǃǃǃHǃ H];H5lH}H>H5mH>H5pH>HA H5 mH>HH;>HHH HMH7HUHuHuIIFIF0INIVIF@H]HEHtH@HlH+HH;Eu LHP[A^]1lIH]HEHtHW@HlLl DUHAVSHPIH++HHE(lHþ HzlHHCHCXHC`HCXHCHHC@HC8HC0HC(HC HCPHCpHCxHCpHChƃHǃfǃHǃHǃƃHHǃHǃHǃHǃHǃHǃHǃHǃHǃHHHǃHǃHǃǃǃHǃ H] ;H5 lH}H>H5mH>H5pH >HA H5mH3>HH;>HHH HMH5HUHuHuIIFIF0INIVIF@H]HEHtH@HBlH(HH;Eu LHP[A^]lIH]HEHtH@HlL=l DUHAVSHPIH{(HHE(lHþ HlHHCHCXHC`HCXHCHHC@HC8HC0HC(HC HCPHCpHCxHCpHChƃHǃfǃHǃHǃƃHHǃHǃHǃHǃHǃHǃHǃHǃHǃHHHǃHǃHǃǃǃHǃ H]];H5]lH}H*>H5omH+>H51pH\>HA H5JmH>HH;H>HHH 'HMH3HUHuHuIIFIF0INIVIF@H]HEHtH<@HlH-&HH;Eu LHP[A^]lIH]HEHtH@HMlL荾l DUHAVSHPIH%HHE($lHþ HlHHCHCXHC`HCXHCHHC@HC8HC0HC(HC HCPHCpHCxHCpHChƃHǃfǃHǃHǃƃHHǃHǃHǃHǃHǃHǃHǃHǃHǃHHHǃHǃHǃǃǃHǃ H]m;H5lH}Hz>H5mH{>H5pH>HA H5mH>HH;蘺>HHH wHMH0HUHuHuIIFIF0INIVIF@H]HEHtH@HlH}#HH;Eu LHP[A^]!lIH]HEHtHG@H蝾lLݻl DUHAVSHPIH#HHE(tlHþ HjlHHCHCXHC`HCXHCHHC@HC8HC0HC(HC HCPHCpHCxHCpHChƃHǃfǃHǃHǃƃHHǃHǃHǃHǃHǃHǃHǃHǃHǃHHHǃHǃHǃǃǃHǃ H]=;H5lH}H>H5mH>H5pH>HH HQH5mH>HH;>HHH HMH5.HUHuHuIIFIF0INIVIF@H]HEHtH@H+lH HH;Eu LHP[A^]jlIH]HEHtH@HlL&l fffff.UHAVSHPIH[ HHE(贻lHþ H誻lHHCHCXHC`HCXHCHHC@HC8HC0HC(HC HCPHCpHCxHCpHChƃHǃfǃHǃHǃƃHHǃHǃHǃHǃHǃHǃHǃHǃHǃHHHǃHǃHǃǃǃHǃ H]};H5=lH}H +>H5SmH >H5pH<>HH HQH5#lH\>HH;!>HHH ߄HMH<HUHuHuIIFIF0INIVIF@H]HEHtH@HklHHH;Eu LHP[A^]誹lIH]HEHtH@H&lLfl fffff.UHAVSHPIHHHE(lHþ HlHHCHCXHC`HCXHCHHC@HC8HC0HC(HC HCPHCpHCxHCpHChƃHǃfǃHǃHǃƃHHǃHǃHǃHǃHǃHǃHǃHǃHǃHHHǃHǃHǃǃǃHǃ H];H5}lH}HJ>H5mHK>H5QpH|>HH HQH5clH蜽>HH;a>HHH @܄HMHEKHUHuHuIIFIF0INIVIF@H]HEHtHU@H諶lHFHH;Eu LHP[A^]lIH]HEHtH@HflL観l fffff.UHAVSHPIHHHE(4lHþ H*lHHCHCXHC`HCXHCHHC@HC8HC0HC(HC HCPHCpHCxHCpHChƃHǃfǃHǃHǃƃHHǃHǃHǃHǃHǃHǃHǃHǃHǃHHHǃHǃHǃǃǃHǃ H]=;H5lH}H>H5mH苸>H5pH輹>HH HQH5lHܺ>HH;衯>HHH لHMHeTHUHuHuIIFIF0INIVIF@H]HEHtH@HlHHH;Eu LHP[A^]*lIH]HEHtHP@H観lLl fffff.UHAVSHPIHHHE(tlHþ HjlHHCHCXHC`HCXHCHHC@HC8HC0HC(HC HCPHCpHCxHCpHChƃHǃfǃHǃHǃƃHHǃHǃHǃHǃHǃHǃHǃHǃHǃHHHǃHǃHǃǃǃHǃ H]};H5lH}Hʾ>H5mH˵>H5pH>HH HQH5lH>HH;>HHH քHMHbHUHuHuIIFIF0INIVIF@H]HEHtH@H+lHHH;Eu LHP[A^]jlIH]HEHtH@HlL&l fffff.UHAVSHPIH[HHE(贰lHþ H誰lHHCHCXHC`HCXHCHHC@HC8HC0HC(HC HCPHCpHCxHCpHChƃHǃfǃHǃHǃƃHHǃHǃHǃHǃHǃHǃHǃHǃHǃHHHǃHǃHǃǃǃHǃ H]};H5=lH}H +>H5SmH >H5pH<>HA H5*lHc>HH;(>HHH ԄHMHkHUHuHuIIFIF0INIVIF@H]HEHtH@HrlH HH;Eu LHP[A^]豮lIH]HEHtH@H-lLml DUHAVSHPIHHHE(lHþ HlHHCHCXHC`HCXHCHHC@HC8HC0HC(HC HCPHCpHCxHCpHChƃHǃfǃHǃHǃƃHHǃHǃHǃHǃHǃHǃHǃHǃHǃHHHǃHǃHǃǃǃHǃ H];H5lH}HZ>H5mH[>H5apH茱>HA H5zlH賲>HH;x>HHH WфHMH|iHUHuHuIIFIF0INIVIF@H]HEHtHl@H«lH]HH;Eu LHP[A^]lIH]HEHtH'@H}lL轨l DUHAVSHPIHHHE(TlHþ HJlHHCHCXHC`HCXHCHHC@HC8HC0HC(HC HCPHCpHCxHCpHChƃHǃfǃHǃHǃƃHHǃHǃHǃHǃHǃHǃHǃHǃHǃHHHǃHǃHǃǃǃHǃ H]];H5ݶlH}H誶>H5mH諭>H5pHܮ>HA H5lH>HH;Ȥ>HHH ΄HMH gHUHuHuIIFIF0INIVIF@H]HEHtH@HlH HH;Eu LHP[A^]QlIH]HEHtHw@HͨlL l DUHAVSHPIHK HHE(褨lHþ H蚨lHHCHCXHC`HCXHCHHC@HC8HC0HC(HC HCPHCpHCxHCpHChƃHǃfǃHǃHǃƃHHǃHǃHǃHǃHǃHǃHǃHǃHǃHHHǃHǃHǃǃǃHǃ H];H5-lH}H>H5CmH>H5pH,>HA H5lHS>HH;>HHH ˄HMHdHUHuHuIIFIF0INIVIF@H]HEHtH @HblH +HH;Eu LHP[A^]衦lIH]HEHtHǿ@HlL]l DUHAVSHPIH +HHE(lHþ HlHHCHCXHC`HCXHCHHC@HC8HC0HC(HC HCPHCpHCxHCpHChƃHǃfǃHǃHǃƃHHǃHǃHǃHǃHǃHǃHǃHǃHǃHHHǃHǃHǃǃǃHǃ H];H5}lH}HJ>H5mHK>H5QpH|>HA H5jlH裪>HH;h>HHH GɄHMH,bHUHuHuIIFIF0INIVIF@H]HEHtH\@H貣lHMHH;Eu LHP[A^]lIH]HEHtH@HmlL譠l DUHAVSHPIHHHE(DlHþ H:lHHCHCXHC`HCXHCHHC@HC8HC0HC(HC HCPHCpHCxHCpHChƃHǃfǃHǃHǃƃHHǃHǃHǃHǃHǃHǃHǃHǃHǃHHHǃHǃHǃǃǃHǃ H] ;H5ͮlH}H蚮>H5mH蛥>H5pH̦>HH HQH5lH>HH;豜>HHH ƄHMH_HUHuHuIIFIF0INIVIF@H]HEHtH襺@HlHHH;Eu LHP[A^]:lIH]HEHtH`@H趠lLl fffff.UHAVSHPIH+HHE(脠lHþ HzlHHCHCXHC`HCXHCHHC@HC8HC0HC(HC HCPHCpHCxHCpHChƃHǃfǃHǃHǃƃHHǃHǃHǃHǃHǃHǃHǃHǃHǃHHHǃHǃHǃǃǃHǃ H]M;H5 lH}Hګ>H5'mHۢ>H5pH >HA H5lH3>HH;>HHH ÄHMHnHUHuHuIIFIF0INIVIF@H]HEHtH@HBlHHH;Eu LHP[A^]聞lIH]HEHtH觷@HlL=l DUHAVSHPIH{HHE(ԝlHþ HʝlHHCHCXHC`HCXHCHHC@HC8HC0HC(HC HCPHCpHCxHCpHChƃHǃfǃHǃHǃƃHHǃHǃHǃHǃHǃHǃHǃHǃHǃHHHǃHǃHǃǃǃHǃ H];H5]lH}H*>H5}mH+>H51pH\>HH HQH5ClH|>HH;A>HHH HMHkHUHuHuIIFIF0INIVIF@H]HEHtH5@H苛lH&HH;Eu LHP[A^]ʛlIH]HEHtH@HFlL膘l fffff.UHAVSHPIHHHE(lHþ H +lHHCHCXHC`HCXHCHHC@HC8HC0HC(HC HCPHCpHCxHCpHChƃHǃfǃHǃHǃƃHHǃHǃHǃHǃHǃHǃHǃHǃHǃHHHǃHǃHǃǃǃHǃ H];H5lH}Hj>H5mHk>H5qpH蜞>HA H5lHß>HH;舔>HHH gHMH zHUHuHuIIFIF0INIVIF@H]HEHtH|@HҘlHmHH;Eu LHP[A^]lIH]HEHtH7@H荘lL͕l DUHAVSHPIH HHE(dlHþ HZlHHCHCXHC`HCXHCHHC@HC8HC0HC(HC HCPHCpHCxHCpHChƃHǃfǃHǃHǃƃHHǃHǃHǃHǃHǃHǃHǃHǃHǃHHHǃHǃHǃǃǃHǃ H]-;H5lH}H躣>H5mH軚>H5pH>HH HQH5lH >HH;ё>HHH HMHwHUHuHuIIFIF0INIVIF@H]HEHtHů@HlHHH;Eu LHP[A^]ZlIH]HEHtH耯@H֕lLl fffff.UHAVSHPIHKHHE(褕lHþ H蚕lHHCHCXHC`HCXHCHHC@HC8HC0HC(HC HCPHCpHCxHCpHChƃHǃfǃHǃHǃƃHHǃHǃHǃHǃHǃHǃHǃHǃHǃHHHǃHǃHǃǃǃHǃ H]m;H5-lH}H>H5RmH>H5pH,>HH HQH5lHL>HH;>HHH HMHuHUHuHuIIFIF0INIVIF@H]HEHtH@H[lHHH;Eu LHP[A^]蚓lIH]HEHtH@HlLVl fffff.UHAVSHPIHHHE(lHþ HڒlHHCHCXHC`HCXHCHHC@HC8HC0HC(HC HCPHCpHCxHCpHChƃHǃfǃHǃHǃƃHHǃHǃHǃHǃHǃHǃHǃHǃHǃHHHǃHǃHǃǃǃHǃ H];H5mlH}H:>H5mH;>H5ApHl>HA H5ZlH蓗>HH;X>HHH 7HMHHUHuHuIIFIF0INIVIF@H]HEHtHL@H袐lH=HH;Eu LHP[A^]lIH]HEHtH@H]lL蝍l DUHAVSHPIHHHE(4lHþ H*lHHCHCXHC`HCXHCHHC@HC8HC0HC(HC HCPHCpHCxHCpHChƃHǃfǃHǃHǃƃHHǃHǃHǃHǃHǃHǃHǃHǃHǃHHHǃHǃHǃǃǃHǃ H];H5lH}H芛>H5mH苒>H5pH輓>HA H5lH>HH;訉>HHH HMH<HUHuHuIIFIF0INIVIF@H]HEHtH蜧@HlHHH;Eu LHP[A^]1lIH]HEHtHW@H譍lLl DUHAVSHPIH+HHE(脍lHþ HzlHHCHCXHC`HCXHCHHC@HC8HC0HC(HC HCPHCpHCxHCpHChƃHǃfǃHǃHǃƃHHǃHǃHǃHǃHǃHǃHǃHǃHǃHHHǃHǃHǃǃǃHǃ H]M;H5 lH}Hژ>H5=mHۏ>H5pH >HH HQH5lH,>HH;>HHH аHMHŌHUHuHuIIFIF0INIVIF@H]HEHtH@H;lHHH;Eu LHP[A^]zlIH]HEHtH蠤@HlL6l fffff.UHAVSHPIHkHHE(ĊlHþ H躊lHHCHCXHC`HCXHCHHC@HC8HC0HC(HC HCPHCpHCxHCpHChƃHǃfǃHǃHǃƃHHǃHǃHǃHǃHǃHǃHǃHǃHǃHHHǃHǃHǃǃǃHǃ H]荾;H5MlH}H>H5}mH>H5!pHL>HH HQH53lHl>HH;1>HHH HMHHUHuHuIIFIF0INIVIF@H]HEHtH%@H{lHHH;Eu LHP[A^]躈lIH]HEHtH@H6lLvl fffff.UHAVSHPIHHHE(lHþ HlHHCHCXHC`HCXHCHHC@HC8HC0HC(HC HCPHCpHCxHCpHChƃHǃfǃHǃHǃƃHHǃHǃHǃHǃHǃHǃHǃHǃHǃHHHǃHǃHǃǃǃHǃ H]͵;H5lH}HZ>H5mH[>H5apH茋>HA H5zlH賌>HH;x>HHH WHMH̟HUHuHuIIFIF0INIVIF@H]HEHtHl@H…lH]HH;Eu LHP[A^]lIH]HEHtH'@H}lL轂l DUHAVSHPIHHHE(TlHþ HJlHHCHCXHC`HCXHCHHC@HC8HC0HC(HC HCPHCpHCxHCpHChƃHǃfǃHǃHǃƃHHǃHǃHǃHǃHǃHǃHǃHǃHǃHHHǃHǃHǃǃǃHǃ H];H5ݐlH}H誐>H5 mH談>H5pH܈>HA H5lH>HH;~>HHH HMH\HUHuHuIIFIF0INIVIF@H]HEHtH輜@HlHHH;Eu LHP[A^]QlIH]HEHtHw@H͂lL l DUHAVSHPIHKHHE(褂lHþ H蚂lHHCHCXHC`HCXHCHHC@HC8HC0HC(HC HCPHCpHCxHCpHChƃHǃfǃHǃHǃƃHHǃHǃHǃHǃHǃHǃHǃHǃHǃHHHǃHǃHǃǃǃHǃ H]H52lH4IH EIH}>H5\mH>H5pH&>HH HQH5 lHF>HH; |>HHH ꥄHMHߚHUHuHuIIFIF0INIVIF@H]HEHtH@HUlHHH;Eu LHP[A^]蔀lIH]HEHtH躙@HlLP}l UHAVSHPIHHHE(lHþ HlHHCHCXHC`HCXHCHHC@HC8HC0HC(HC HCPHCpHCxHCpHChƃHǃfǃHǃHǃƃHHǃHǃHǃHǃHǃHǃHǃHǃHǃHHHǃHǃHǃǃǃHǃ H]H5rlHFH FH}$>H5mHFH FH>H5mH>H5pHI>HH HQH50lHi>HH;.y>HHH HMHbHUHuHuIIFIF0INIVIF@H]HEHtH"@Hx}lHHH;Eu LHP[A^]}lIH]HEHtHݖ@H3}lLszl ff.UHAVSHPIHHHE(}lHþ H|lHHCHCXHC`HCXHCHHC@HC8HC0HC(HC HCPHCpHCxHCpHChƃHǃfǃHǃHǃƃHHǃHǃHǃHǃHǃHǃHǃHǃHǃHHHǃHǃHǃǃǃHǃ H]H5lHCH CH}D>H5mHCH CH'>H5mH8>H5>pHi>HA H5WlH萁>HH;Uv>HHH 4HMHHUHuHuIIFIF0INIVIF@H]HEHtHI@HzlH:߃HH;Eu LHP[A^]zlIH]HEHtH@HZzlLwl fUHAVSHPIHރHHE(4zlHþ H*zlHHCHCXHC`HCXHCHHC@HC8HC0HC(HC HCPHCpHCxHCpHChƃHǃfǃHǃHǃƃHHǃHǃHǃHǃHǃHǃHǃHǃHǃHHHǃHǃHǃǃǃHǃ H];H5lH}H芅>H5mH|>H5pH}>HH HQH5lH~>HH;s>HHH HMHHUHuHuIIFIF0INIVIF@H]HEHtH蕑@HwlH܃HH;Eu LHP[A^]*xlIH]HEHtHP@HwlLtl fffff.UHAVSHPIH܃HHE(twlHþ HjwlHHCHCXHC`HCXHCHHC@HC8HC0HC(HC HCPHCpHCxHCpHChƃHǃfǃHǃHǃƃHHǃHǃHǃHǃHǃHǃHǃHǃHǃHHHǃHǃHǃǃǃHǃ H]=;H5lH}Hʂ>H59mHy>H5ѢpHz>HH HQH5lH|>HH;p>HHH HMHUHUHuHuIIFIF0INIVIF@H]HEHtHՎ@H+ulHكHH;Eu LHP[A^]julIH]HEHtH萎@HtlL&rl fffff.UHAVSHPIH[كHHE(tlHþ HtlHHCHCXHC`HCXHCHHC@HC8HC0HC(HC HCPHCpHCxHCpHChƃHǃfǃHǃHǃƃHHǃHǃHǃHǃHǃHǃHǃHǃHǃHHHǃHǃHǃǃǃHǃ H]};H5=lH}H +>H5ymH w>H5pH<x>HA H5*lHcy>HH;(n>HHH HMHLHUHuHuIIFIF0INIVIF@H]HEHtH@HrrlH ׃HH;Eu LHP[A^]rlIH]HEHtH׋@H-rlLmol DUHAVSHPIHփHHE(rlHþ HqlHHCHCXHC`HCXHCHHC@HC8HC0HC(HC HCPHCpHCxHCpHChƃHǃfǃHǃHǃƃHHǃHǃHǃHǃHǃHǃHǃHǃHǃHHHǃHǃHǃǃǃHǃ H]ͥ;H5}lH}HZ}>H5ɗmH[t>H5apHu>HA H5zlHv>HH;xk>HHH WHMHܫHUHuHuIIFIF0INIVIF@H]HEHtHl@HolH]ԃHH;Eu LHP[A^]plIH]HEHtH'@H}olLll DUHAVSHPIHӃHHE(TolHþ HJolHHCHCXHC`HCXHCHHC@HC8HC0HC(HC HCPHCpHCxHCpHChƃHǃfǃHǃHǃƃHHǃHǃHǃHǃHǃHǃHǃHǃHǃHHHǃHǃHǃǃǃHǃ H];H5zlH}Hz>H5mHq>H5pHr>HH HQH5ñlHs>HH;h>HHH HMHeHUHuHuIIFIF0INIVIF@H]HEHtH赆@H mlHуHH;Eu LHP[A^]JmlIH]HEHtHp@HllLjl fffff.UHAVSHPIH;уHHE(llHþ HllHHCHCXHC`HCXHCHHC@HC8HC0HC(HC HCPHCpHCxHCpHChƃHǃfǃHǃHǃƃHHǃHǃHǃHǃHǃHǃHǃHǃHǃHHHǃHǃHǃǃǃHǃ H]];H5xlH}Hw>H5]mHn>H5pHp>HH HQH5lH<q>HH;f>HHH HMHHUHuHuIIFIF0INIVIF@H]HEHtH@HKjlH΃HH;Eu LHP[A^]jlIH]HEHtH调@HjlLFgl fffff.UHAVSHPIH{΃HHE(ilHþ HilHHCHCXHC`HCXHCHHC@HC8HC0HC(HC HCPHCpHCxHCpHChƃHǃfǃHǃHǃƃHHǃHǃHǃHǃHǃHǃHǃHǃHǃHHHǃHǃHǃǃǃHǃ H]蝗;H5]ulH}H*u>H5mH+l>H51pH\m>HA H5JlHn>HH;Hc>HHH 'HMHHUHuHuIIFIF0INIVIF@H]HEHtH<@HglH-̃HH;Eu LHP[A^]glIH]HEHtH@HMglLdl DUHAVSHPIH˃HHE($glHþ HglHHCHCXHC`HCXHCHHC@HC8HC0HC(HC HCPHCpHCxHCpHChƃHǃfǃHǃHǃƃHHǃHǃHǃHǃHǃHǃHǃHǃHǃHHHǃHǃHǃǃǃHǃ H];H5rlH}Hzr>H5mH{i>H5pHj>HA H5lHk>HH;`>HHH wHMHHUHuHuIIFIF0INIVIF@H]HEHtH~@HdlH}ɃHH;Eu LHP[A^]!elIH]HEHtHG~@HdlLal DUHAVSHPIHɃHHE(tdlHþ HjdlHHCHCXHC`HCXHCHHC@HC8HC0HC(HC HCPHCpHCxHCpHChƃHǃfǃHǃHǃƃHHǃHǃHǃHǃHǃHǃHǃHǃHǃHHHǃHǃHǃǃǃHǃ H]=;H5olH}Ho>H5AmHf>H5яpHg>HHHQH5lHi>HH;]>HHH HMH5HUHuHuIIFIF0INIVIF@H]HEHtH{@H+blHƃHH;Eu LHP[A^]jblIH]HEHtH{@HalL&_l fffff.UHAVSHPIH[ƃHHE(alHþ HalHHCHCXHC`HCXHCHHC@HC8HC0HC(HC HCPHCpHCxHCpHChƃHǃfǃHǃHǃƃHHǃHǃHǃHǃHǃHǃHǃHǃHǃHHHǃHǃHǃǃǃHǃ H]};H5=mlH}H +m>H5mH d>H5pH<e>HHHQH5#lH\f>HH;![>HHH HMH%HUHuHuIIFIF0INIVIF@H]HEHtHy@Hk_lHăHH;Eu LHP[A^]_lIH]HEHtHx@H&_lLf\l fffff.UHAVSHPIHÃHHE(^lHþ H^lHHCHCXHC`HCXHCHHC@HC8HC0HC(HC HCPHCpHCxHCpHChƃHǃfǃHǃHǃƃHHǃHǃHǃHǃHǃHǃHǃHǃHǃHHHǃHǃHǃǃǃHǃ H]轌;H5}jlH}HJj>H5mHKa>H5QpH|b>HH HQH5clHc>HH;aX>HHH @HMHHUHuHuIIFIF0INIVIF@H]HEHtHUv@H\lHFHH;Eu LHP[A^]\lIH]HEHtHv@Hf\lLYl fffff.UHAVSHPIHHHE(4\lHþ H*\lHHCHCXHC`HCXHCHHC@HC8HC0HC(HC HCPHCpHCxHCpHChƃHǃfǃHǃHǃƃHHǃHǃHǃHǃHǃHǃHǃHǃHǃHHHǃHǃHǃǃǃHǃ H];H5glH}Hg>H5mH^>H5pH_>HH HQH5lH`>HH;U>HHH HMH HUHuHuIIFIF0INIVIF@H]HEHtHs@HYlHHH;Eu LHP[A^]*ZlIH]HEHtHPs@HYlLVl fffff.UHAVSHPIHHHE(tYlHþ HjYlHHCHCXHC`HCXHCHHC@HC8HC0HC(HC HCPHCpHCxHCpHChƃHǃfǃHǃHǃƃHHǃHǃHǃHǃHǃHǃHǃHǃHǃHHHǃHǃHǃǃǃHǃ H]=;H5dlH}Hd>H5AmH[>H5фpH\>HA H5lH#^>HH;R>HHH |HMH<HUHuHuIIFIF0INIVIF@H]HEHtHp@H2WlHͻHH;Eu LHP[A^]qWlIH]HEHtHp@HVlL-Tl DUHAVSHPIHkHHE(VlHþ HVlHHCHCXHC`HCXHCHHC@HC8HC0HC(HC HCPHCpHCxHCpHChƃHǃfǃHǃHǃƃHHǃHǃHǃHǃHǃHǃHǃHǃHǃHHHǃHǃHǃǃǃHǃ H]荊;H5MblH}Hb>H5|mHY>H5!pHLZ>HA H5:lHs[>HH;8P>HHH zHMHHUHuHuIIFIF0INIVIF@H]HEHtH,n@HTlHHH;Eu LHP[A^]TlIH]HEHtHm@H=TlL}Ql DUHAVSHPIHHHE(TlHþ H +TlHHCHCXHC`HCXHCHHC@HC8HC0HC(HC HCPHCpHCxHCpHChƃHǃfǃHǃHǃƃHHǃHǃHǃHǃHǃHǃHǃHǃHǃHHHǃHǃHǃǃǃHǃ H]݁;H5_lH}Hj_>H5ymHkV>H5qpHW>HHHQH5lHX>HH;M>HHH `wHMHHUHuHuIIFIF0INIVIF@H]HEHtHuk@HQlHfHH;Eu LHP[A^] +RlIH]HEHtH0k@HQlLNl fffff.UHAVSHPIHHHE(TQlHþ HJQlHHCHCXHC`HCXHCHHC@HC8HC0HC(HC HCPHCpHCxHCpHChƃHǃfǃHǃHǃƃHHǃHǃHǃHǃHǃHǃHǃHǃHǃHHHǃHǃHǃǃǃHǃ H]H5\lHtH H}Y>H5wmHS>H5|pHT>HH HQH5lHU>HH;J>HHH tHMHHUHuHuIIFIF0INIVIF@H]HEHtHh@HOlHHH;Eu LHP[A^]DOlIH]HEHtHjh@HNlLLl UHAVSHPIH;HHE(NlHþ HNlHHCHCXHC`HCXHCHHC@HC8HC0HC(HC HCPHCpHCxHCpHChƃHǃfǃHǃHǃƃHHǃHǃHǃHǃHǃHǃHǃHǃHǃHHHǃHǃHǃǃǃHǃ H]H5"ZlHH H}V>H5_tmHP>H5ypHR>HH HQH5lH6S>HH;G>HHH qHMH?HUHuHuIIFIF0INIVIF@H]HEHtHe@HELlHఃHH;Eu LHP[A^]LlIH]HEHtHe@HLlL@Il UHAVSHPIH{HHE(KlHþ HKlHHCHCXHC`HCXHCHHC@HC8HC0HC(HC HCPHCpHCxHCpHChƃHǃfǃHǃHǃƃHHǃHǃHǃHǃHǃHǃHǃHǃHǃHHHǃHǃHǃǃǃHǃ H]H5bWlH H 5H}T>H5qmH%N>H5+wpHVO>HA H5DlH}P>HH;BE>HHH !oHMHHUHuHuIIFIF0INIVIF@H]HEHtH6c@HIlH'HH;Eu LHP[A^]IlIH]HEHtHb@HGIlLFl ffffff.UHAVSHPIHHHE(IlHþ H +IlHHCHCXHC`HCXHCHHC@HC8HC0HC(HC HCPHCpHCxHCpHChƃHǃfǃHǃHǃƃHHǃHǃHǃHǃHǃHǃHǃHǃHǃHHHǃHǃHǃǃǃHǃ H]v;H5TlH}HjT>H5nmHkK>H5qtpHL>HHHQH5lHM>HH;B>HHH `lHMH HUHuHuIIFIF0INIVIF@H]HEHtHu`@HFlHfHH;Eu LHP[A^] +GlIH]HEHtH0`@HFlLCl fffff.UHAVSHPIHHHE(TFlHþ HJFlHHCHCXHC`HCXHCHHC@HC8HC0HC(HC HCPHCpHCxHCpHChƃHǃfǃHǃHǃƃHHǃHǃHǃHǃHǃHǃHǃHǃHǃHHHǃHǃHǃǃǃHǃ H]H5QlH H H}N>H5#lmHH>H5qpHI>HH HQH5lHJ>HH;?>HHH iHMH +HUHuHuIIFIF0INIVIF@H]HEHtH]@HDlHHH;Eu LHP[A^]DDlIH]HEHtHj]@HClLAl UHAVSHPIH;HHE(ClHþ HClHHCHCXHC`HCXHCHHC@HC8HC0HC(HC HCPHCpHCxHCpHChƃHǃfǃHǃHǃƃHHǃHǃHǃHǃHǃHǃHǃHǃHǃHHHǃHǃHǃǃǃHǃ H]H5"OlH, H U H}K>H5cimHE>H5npHG>HH HQH5lH6H>HH;<>HHH fHMH/HUHuHuIIFIF0INIVIF@H]HEHtHZ@HEAlHृHH;Eu LHP[A^]AlIH]HEHtHZ@HAlL@>l UHAVSHPIH{HHE(@lHþ H@lHHCHCXHC`HCXHCHHC@HC8HC0HC(HC HCPHCpHCxHCpHChƃHǃfǃHǃHǃƃHHǃHǃHǃHǃHǃHǃHǃHǃHǃHHHǃHǃHǃǃǃHǃ H]H5bLlHlH H}I>H5fmH%C>H5+lpHVD>HA H5DlH}E>HH;B:>HHH !dHMHHUHuHuIIFIF0INIVIF@H]HEHtH6X@H>lH'HH;Eu LHP[A^]>lIH]HEHtHW@HG>lL;l ffffff.UHAVSHPIHHHE(>lHþ H +>lHHCHCXHC`HCXHCHHC@HC8HC0HC(HC HCPHCpHCxHCpHChƃHǃfǃHǃHǃƃHHǃHǃHǃHǃHǃHǃHǃHǃHǃHHHǃHǃHǃǃǃHǃ H]k;H5IlH}HjI>Hl;H5cmHHPI>H5cmHQ@>H5WipHA>HHHQH5ilHB>HH;g7>HHH FaHMH[HUHuHuIIFIF0INIVIF@H]HEHtH[U@H;lHLHH;Eu LHP[A^];lIH]HEHtHU@Hl;lL8l @UHAVSHPIH럃HHE(D;lHþ H:;lHHCHCXHC`HCXHCHHC@HC8HC0HC(HC HCPHCpHCxHCpHChƃHǃfǃHǃHǃƃHHǃHǃHǃHǃHǃHǃHǃHǃHǃHHHǃHǃHǃǃǃHǃ H] o;H5FlH}HF>Hi;H5`mHHF>H5amH=>H5fpH>>HHHQH5}lH?>HH;4>HHH v^HMHHUHuHuIIFIF0INIVIF@H]HEHtHR@H8lH|HH;Eu LHP[A^] 9lIH]HEHtHFR@H8lL5l @UHAVSHPIHHHE(t8lHþ Hj8lHHCHCXHC`HCXHCHHC@HC8HC0HC(HC HCPHCpHCxHCpHChƃHǃfǃHǃHǃƃHHǃHǃHǃHǃHǃHǃHǃHǃHǃHHHǃHǃHǃǃǃHǃ H]=f;H5ClH}HC>Hf;H5.^mHHC>H53^mH:>H5cpH;>HH HQH5zlH=>HH;1>HHH [HMH +HUHuHuIIFIF0INIVIF@H]HEHtHO@H6lHHH;Eu LHP[A^]P6lIH]HEHtHvO@H5lL 3l @UHAVSHPIHKHHE(5lHþ H5lHHCHCXHC`HCXHCHHC@HC8HC0HC(HC HCPHCpHCxHCpHChƃHǃfǃHǃHǃƃHHǃHǃHǃHǃHǃHǃHǃHǃHǃHHHǃHǃHǃǃǃHǃ H]mi;H5-AlH}H@>Hd;H5^[mHH@>H5c[mH7>H5`pH9>HH HQH5wlH2:>HH;.>HHH XHMH[HUHuHuIIFIF0INIVIF@H]HEHtHL@HA3lHܗHH;Eu LHP[A^]3lIH]HEHtHL@H2lL<0l @UHAVSHPIH{HHE(2lHþ H2lHHCHCXHC`HCXHCHHC@HC8HC0HC(HC HCPHCpHCxHCpHChƃHǃfǃHǃHǃƃHHǃHǃHǃHǃHǃHǃHǃHǃHǃHHHǃHǃHǃǃǃHǃ H]_;H5]>lH}H*>>HBa;H5XmHH>>H5XmH5>H5^pHB6>HH HQH5)ulHb7>HH;',>HHH VHMHHUHuHuIIFIF0INIVIF@H]HEHtHJ@Hq0lH HH;Eu LHP[A^]0lIH]HEHtHI@H,0lLl-l @UHAVSHPIHHHE(0lHþ H/lHHCHCXHC`HCXHCHHC@HC8HC0HC(HC HCPHCpHCxHCpHChƃHǃfǃHǃHǃƃHHǃHǃHǃHǃHǃHǃHǃHǃHǃHHHǃHǃHǃǃǃHǃ H] c;H5;lH}HZ;>Hr^;H5UmHH@;>H5UmHA2>H5G[pHr3>HH HQH5YrlH4>HH;W)>HHH 6SHMH HUHuHuIIFIF0INIVIF@H]HEHtHKG@H-lH<HH;Eu LHP[A^]-lIH]HEHtHG@H\-lL*l @UHAVSHPIHۑHHE(4-lHþ H*-lHHCHCXHC`HCXHCHHC@HC8HC0HC(HC HCPHCpHCxHCpHChƃHǃfǃHǃHǃƃHHǃHǃHǃHǃHǃHǃHǃHǃHǃHHHǃHǃHǃǃǃHǃ H]Z;H58lH}H8>H[;H5RmHHp8>H5RmHq/>H5wXpH0>HA H5olH1>HH;&>HHH mPHMH HUHuHuIIFIF0INIVIF@H]HEHtHD@H*lHsHH;Eu LHP[A^]+lIH]HEHtH=D@H*lL'l ff.UHAVSHPIH HHE(d*lHþ HZ*lHHCHCXHC`HCXHCHHC@HC8HC0HC(HC HCPHCpHCxHCpHChƃHǃfǃHǃHǃƃHHǃHǃHǃHǃHǃHǃHǃHǃHǃHHHǃHǃHǃǃǃHǃ H]-^;H55lH}H5>HX;H5PmHH5>H5#PmH,>H5UpH->HA H5llH.>HH;#>HHH MHMHHUHuHuIIFIF0INIVIF@H]HEHtHA@H(lHHH;Eu LHP[A^]G(lIH]HEHtHmA@H'lL%l ff.UHAVSHPIH;HHE('lHþ H'lHHCHCXHC`HCXHCHHC@HC8HC0HC(HC HCPHCpHCxHCpHChƃHǃfǃHǃHǃƃHHǃHǃHǃHǃHǃHǃHǃHǃHǃHHHǃHǃHǃǃǃHǃ H]T;H53lH}H2>HV;H5NMmHH2>H5SMmH)>H5RpH+>HA H5ilH),>HH; >HHH JHMH2HUHuHuIIFIF0INIVIF@H]HEHtH>@H8%lHӉHH;Eu LHP[A^]w%lIH]HEHtH>@H$lL3"l ff.UHAVSHPIHkHHE($lHþ H$lHHCHCXHC`HCXHCHHC@HC8HC0HC(HC HCPHCpHCxHCpHChƃHǃfǃHǃHǃƃHHǃHǃHǃHǃHǃHǃHǃHǃHǃHHHǃHǃHǃǃǃHǃ H]W;H5M0lH}H0>H2S;H5~JmHH0>H5JmH'>H5PpH2(>HA H5 glHY)>HH;>HHH GHMHHUHuHuIIFIF0INIVIF@H]HEHtH<@Hh"lHHH;Eu LHP[A^]"lIH]HEHtH;@H#"lLcl ff.UHAVSHPIHHHE(!lHþ H!lHHCHCXHC`HCXHCHHC@HC8HC0HC(HC HCPHCpHCxHCpHChƃHǃfǃHǃHǃƃHHǃHǃHǃHǃHǃHǃHǃHǃHǃHHHǃHǃHǃǃǃHǃ H]O;H5}-lH}HJ->HbP;H5GmHH0->H5GmH1$>H57MpHb%>HHHQH5IdlH&>HH;G>HHH &EHMHKHUHuHuIIFIF0INIVIF@H]HEHtH;9@HlH,HH;Eu LHP[A^]lIH]HEHtH8@HLlLl @UHAVSHPIH˃HHE($lHþ HlHHCHCXHC`HCXHCHHC@HC8HC0HC(HC HCPHCpHCxHCpHChƃHǃfǃHǃHǃƃHHǃHǃHǃHǃHǃHǃHǃHǃHǃHHHǃHǃHǃǃǃHǃ H]R;H5*lH}Hz*>HM;H5DmHH`*>H5DmHa!>H5gJpH">HHHQH5yalH#>HH;w>HHH VBHMHHUHuHuIIFIF0INIVIF@H]HEHtHk6@HlH\HH;Eu LHP[A^]lIH]HEHtH&6@H|lLl @UHAVSHPIHHHE(TlHþ HJlHHCHCXHC`HCXHCHHC@HC8HC0HC(HC HCPHCpHCxHCpHChƃHǃfǃHǃHǃƃHHǃHǃHǃHǃHǃHǃHǃHǃHǃHHHǃHǃHǃǃǃHǃ H]J;H5'lH}H'>HJ;H5BmHH'>H5BmH>H5GpH>HH HQH5^lH >HH;>HHH ?HMHHUHuHuIIFIF0INIVIF@H]HEHtH3@HlH~HH;Eu LHP[A^]0lIH]HEHtHV3@HlLl @UHAVSHPIH+~HHE(lHþ HzlHHCHCXHC`HCXHCHHC@HC8HC0HC(HC HCPHCpHCxHCpHChƃHǃfǃHǃHǃƃHHǃHǃHǃHǃHǃHǃHǃHǃHǃHHHǃHǃHǃǃǃHǃ H]MM;H5 %lH}H$>HG;H5>?mHH$>H5H?mH>H5DpH>HH HQH5[lH>HH;>HHH <HMHKHUHuHuIIFIF0INIVIF@H]HEHtH0@H!lH{HH;Eu LHP[A^]`lIH]HEHtH0@HlLl @UHAVSHPIH[{HHE(lHþ HlHHCHCXHC`HCXHCHHC@HC8HC0HC(HC HCPHCpHCxHCpHChƃHǃfǃHǃHǃƃHHǃHǃHǃHǃHǃHǃHǃHǃHǃHHHǃHǃHǃǃǃHǃ H]C;H5="lH}H +">H"E;H5n<mHH!>H5x<mH>H5ApH">HH HQH5 YlHB>HH;>HHH 9HMHHUHuHuIIFIF0INIVIF@H]HEHtH-@HQlHxHH;Eu LHP[A^]lIH]HEHtH-@H lLLl @UHAVSHPIHxHHE(lHþ HlHHCHCXHC`HCXHCHHC@HC8HC0HC(HC HCPHCpHCxHCpHChƃHǃfǃHǃHǃƃHHǃHǃHǃHǃHǃHǃHǃHǃHǃHHHǃHǃHǃǃǃHǃ H]F;H5mlH}H:>HRB;H59mHH >H59mH!>H5'?pHR>HH HQH59VlHr>HH;7 >HHH 7HMH{HUHuHuIIFIF0INIVIF@H]HEHtH++@HlHvHH;Eu LHP[A^]lIH]HEHtH*@H<lL|l @UHAVSHPIHuHHE(lHþ H +lHHCHCXHC`HCXHCHHC@HC8HC0HC(HC HCPHCpHCxHCpHChƃHǃfǃHǃHǃƃHHǃHǃHǃHǃHǃHǃHǃHǃHǃHHHǃHǃHǃǃǃHǃ H]>;H5lH}Hj>H?;H56mHHP>H56mHQ>H5W<pH>HA H5pSlH>HH;n +>HHH M4HMH HUHuHuIIFIF0INIVIF@H]HEHtHb(@HlHSsHH;Eu LHP[A^]lIH]HEHtH(@HslL l ff.UHAVSHPIHrHHE(DlHþ H:lHHCHCXHC`HCXHCHHC@HC8HC0HC(HC HCPHCpHCxHCpHChƃHǃfǃHǃHǃƃHHǃHǃHǃHǃHǃHǃHǃHǃHǃHHHǃHǃHǃǃǃHǃ H] B;H5lH}H>H<;H53mHH>H54mH>H59pH>HA H5PlH>HH;>HHH }1HMHHUHuHuIIFIF0INIVIF@H]HEHtH%@H lHpHH;Eu LHP[A^]' lIH]HEHtHM%@H lLl ff.UHAVSHPIHpHHE(t lHþ Hj lHHCHCXHC`HCXHCHHC@HC8HC0HC(HC HCPHCpHCxHCpHChƃHǃfǃHǃHǃƃHHǃHǃHǃHǃHǃHǃHǃHǃHǃHHHǃHǃHǃǃǃHǃ H]}8;H5lH}H>H9;H5.1mHH>H581mH >H56pH>HA H5MlH >HH;>HHH .HMH"HUHuHuIIFIF0INIVIF@H]HEHtH"@H lHmHH;Eu LHP[A^]W lIH]HEHtH}"@HlLl ff.UHAVSHPIHKmHHE(lHþ HlHHCHCXHC`HCXHCHHC@HC8HC0HC(HC HCPHCpHCxHCpHChƃHǃfǃHǃHǃƃHHǃHǃHǃHǃHǃHǃHǃHǃHǃHHHǃHǃHǃǃǃHǃ H];;H5-lH}H>H7;H5^.mHH>H5h.mH +>H53pH >HA H5KlH9 >HH;>HHH +HMHHUHuHuIIFIF0INIVIF@H]HEHtH@HHlHjHH;Eu LHP[A^]lIH]HEHtH@HlLCl ff.UHAVSHPIH{jHHE(lHþ HlHHCHCXHC`HCXHCHHC@HC8HC0HC(HC HCPHCpHCxHCpHChƃHǃfǃHǃHǃƃHHǃHǃHǃHǃHǃHǃHǃHǃHǃHHHǃHǃHǃǃǃHǃ H]]4;H5]lH}H*>HB4;H5+mHH>H5+mH>H51pHB >HH +HQH5)HlHb +>HH;'=HHH )HMH;HUHuHuIIFIF0INIVIF@H]HEHtH@HqlH hHH;Eu LHP[A^]lIH]HEHtH@H,lLll @UHAVSHPIHgHHE(lHþ HlHHCHCXHC`HCXHCHHC@HC8HC0HC(HC HCPHCpHCxHCpHChƃHǃfǃHǃHǃƃHHǃHǃHǃHǃHǃHǃHǃHǃHǃHHHǃHǃHǃǃǃHǃ H] 0;H5lH}HZ>Hr1;H5(mHH@>H5(mHA>H5G.pHr>HH +HQH5YElH>HH;W=HHH 6&HMHHUHuHuIIFIF0INIVIF@H]HEHtHK@HlH<eHH;Eu LHP[A^]lIH]HEHtH@H\lLk @UHAVSHPIHdHHE(4lHþ H*lHHCHCXHC`HCXHCHHC@HC8HC0HC(HC HCPHCpHCxHCpHChƃHǃfǃHǃHǃƃHHǃHǃHǃHǃHǃHǃHǃHǃHǃHHHǃHǃHǃǃǃHǃ H]=3;H5 lH}H >H.;H5%mHHp >H5&mHq>H5w+pH>HH +HQH5BlH>HH;=HHH f#HMH;HUHuHuIIFIF0INIVIF@H]HEHtH{@HkHlbHH;Eu LHP[A^]kIH]HEHtH6@HkLk @UHAVSHPIH bHHE(dkHþ HZkHHCHCXHC`HCXHCHHC@HC8HC0HC(HC HCPHCpHCxHCpHChƃHǃfǃHǃHǃƃHHǃHǃHǃHǃHǃHǃHǃHǃHǃHHHǃHǃHǃǃǃHǃ H]-+;H5lH}H>H+;H5#mHH>H50#mH=H5(pH>HH +HQH5?lH>HH;=HHH HMH HUHuHuIIFIF0INIVIF@H]HEHtH@HkH_HH;Eu LHP[A^]@kIH]HEHtHf@HkLk @UHAVSHPIH;_HHE(kHþ HkHHCHCXHC`HCXHCHHC@HC8HC0HC(HC HCPHCpHCxHCpHChƃHǃfǃHǃHǃƃHHǃHǃHǃHǃHǃHǃHǃHǃHǃHHHǃHǃHǃǃǃHǃ H]].;H5lH}H>H);H5N mHH>H5` mH=H5%pH=HH +HQH5<lH"=HH;=HHH HMH; HUHuHuIIFIF0INIVIF@H]HEHtH@H1kH\HH;Eu LHP[A^]pkIH]HEHtH@HkL,k @UHAVSHPIHk\HHE(kHþ HkHHCHCXHC`HCXHCHHC@HC8HC0HC(HC HCPHCpHCxHCpHChƃHǃfǃHǃHǃƃHHǃHǃHǃHǃHǃHǃHǃHǃHǃHHHǃHǃHǃǃǃHǃ H]M&;H5MlH}H>H2&;H5~mHH>H5mH=H5#pH2=HH HQH5:lHR=HH;=HHH HMH+HUHuHuIIFIF0INIVIF@H]HEHtH @HakHYHH;Eu LHP[A^]kIH]HEHtH@HkL\k @UHAVSHPIHYHHE(kHþ HkHHCHCXHC`HCXHCHHC@HC8HC0HC(HC HCPHCpHCxHCpHChƃHǃfǃHǃHǃƃHHǃHǃHǃHǃHǃHǃHǃHǃHǃHHHǃHǃHǃǃǃHǃ H]!;H5}lH}HJ>Hb#;H5mHH0>H5mH1=H57 pHb=HH HQH5I7lH=HH;G=HHH &HMHHUHuHuIIFIF0INIVIF@H]HEHtH; @HkH,WHH;Eu LHP[A^]kIH]HEHtH @HLkLk @UHAVSHPIHVHHE($kHþ HkHHCHCXHC`HCXHCHHC@HC8HC0HC(HC HCPHCpHCxHCpHChƃHǃfǃHǃHǃƃHHǃHǃHǃHǃHǃHǃHǃHǃHǃHHHǃHǃHǃǃǃHǃ H]-%;H5kH}Hz=H ;H5mHH`=H5mHa=H5gpH=HH HQH5y4lH=HH;w=HHH VHMHK HUHuHuIIFIF0INIVIF@H]HEHtHk @HkH\THH;Eu LHP[A^]kIH]HEHtH& @H|kLk @UHAVSHPIHSHHE(TkHþ HJkHHCHCXHC`HCXHCHHC@HC8HC0HC(HC HCPHCpHCxHCpHChƃHǃfǃHǃHǃƃHHǃHǃHǃHǃHǃHǃHǃHǃHǃHHHǃHǃHǃǃǃHǃ H];H5kH}H=H;H5mHH=H5 mH=H5pH=HH HQH51lH=HH;=HHH HMH HUHuHuIIFIF0INIVIF@H]HEHtH@HkHQHH;Eu LHP[A^]0kIH]HEHtHV@HkLk @UHAVSHPIH+QHHE(kHþ HzkHHCHCXHC`HCXHCHHC@HC8HC0HC(HC HCPHCpHCxHCpHChƃHǃfǃHǃHǃƃHHǃHǃHǃHǃHǃHǃHǃHǃHǃHHHǃHǃHǃǃǃHǃ H]M ;H5 kH}H=H;H5>mHH=H5PmH=H5pH=HH HQH5.lH=HH;=HHH HMHkHUHuHuIIFIF0INIVIF@H]HEHtH@H!kHNHH;Eu LHP[A^]`kIH]HEHtH@HkLk @UHAVSHPIH[NHHE(kHþ HkHHCHCXHC`HCXHCHHC@HC8HC0HC(HC HCPHCpHCxHCpHChƃHǃfǃHǃHǃƃHHǃHǃHǃHǃHǃHǃHǃHǃHǃHHHǃHǃHǃǃǃHǃ H]=;H5=kH}H +=H";H5nmHH=H5mH=H5pH"=HA H5,lHI=HH;=HHH HMHHUHuHuIIFIF0INIVIF@H]HEHtH@HXkHKHH;Eu LHP[A^]kIH]HEHtH@HkLSk ff.UHAVSHPIHKHHE(kHþ HkHHCHCXHC`HCXHCHHC@HC8HC0HC(HC HCPHCpHCxHCpHChƃHǃfǃHǃHǃƃHHǃHǃHǃHǃHǃHǃHǃHǃHǃHHHǃHǃHǃǃǃHǃ H];H5mkH}H:=HR;H5 mHH =H5 mH!=H5'pHR=HA H5@)lHy=HH;>=HHH  +HMHHUHuHuIIFIF0INIVIF@H]HEHtH2?HkH#IHH;Eu LHP[A^]kIH]HEHtH?HCkLk ff.UHAVSHPIHHHHE(kHþ H +kHHCHCXHC`HCXHCHHC@HC8HC0HC(HC HCPHCpHCxHCpHChƃHǃfǃHǃHǃƃHHǃHǃHǃHǃHǃHǃHǃHǃHǃHHHǃHǃHǃǃǃHǃ H];H5kH}Hj=H;H5 mHHP=H5 mHQ=H5WpH=HA H5p&lH=HH;n=HHH MHMH"HUHuHuIIFIF0INIVIF@H]HEHtHb?HkHSFHH;Eu LHP[A^]kIH]HEHtH?HskLk ff.UHAVSHPIHEHHE(DkHþ H:kHHCHCXHC`HCXHCHHC@HC8HC0HC(HC HCPHCpHCxHCpHChƃHǃfǃHǃHǃƃHHǃHǃHǃHǃHǃHǃHǃHǃHǃHHHǃHǃHǃǃǃHǃ H] ;H5kH}H=H;H5mHH=H5mH=H5 pH=HA H5#lH=HH;=HHH }HMHHUHuHuIIFIF0INIVIF@H]HEHtH?HkHCHH;Eu LHP[A^]'kIH]HEHtHM?HkLk ff.UHAVSHPIHCHHE(tkHþ HjkHHCHCXHC`HCXHCHHC@HC8HC0HC(HC HCPHCpHCxHCpHChƃHǃfǃHǃHǃƃHHǃHǃHǃHǃHǃHǃHǃHǃHǃHHHǃHǃHǃǃǃHǃ H]=;H5kH}H=H ;H5.mHH=H5@mH=H5 pH=HA H5 lH =HH;=HHH HMHBHUHuHuIIFIF0INIVIF@H]HEHtH?HkH@HH;Eu LHP[A^]WkIH]HEHtH}?HkLk ff.UHAVSHPIHK@HHE(kHþ HkHHCHCXHC`HCXHCHHC@HC8HC0HC(HC HCPHCpHCxHCpHChƃHǃfǃHǃHǃƃHHǃHǃHǃHǃHǃHǃHǃHǃHǃHHHǃHǃHǃǃǃHǃ H]m ;H5-kH}H=H +;H5^mHH=H5vmH=H5pH=HA H5lH9=HH;=HHH HMHHUHuHuIIFIF0INIVIF@H]HEHtH?HHkH=HH;Eu LHP[A^]kIH]HEHtH?HkLCk ff.UHAVSHPIH{=HHE(kHþ HkHHCHCXHC`HCXHCHHC@HC8HC0HC(HC HCPHCpHCxHCpHChƃHǃfǃHǃHǃƃHHǃHǃHǃHǃHǃHǃHǃHǃHǃHHHǃHǃHǃǃǃHǃ H] ;H5]kH}H*=HB;H5lHH=H5lH=H5pHB=HA H50lHi=HH;.=HHH HMHRHUHuHuIIFIF0INIVIF@H]HEHtH"?HxkH;HH;Eu LHP[A^]kIH]HEHtH?H3kLsk ff.UHAVSHPIH:HHE(kHþ HkHHCHCXHC`HCXHCHHC@HC8HC0HC(HC HCPHCpHCxHCpHChƃHǃfǃHǃHǃƃHHǃHǃHǃHǃHǃHǃHǃHǃHǃHHHǃHǃHǃǃǃHǃ H] ;H5kH}HZ=Hr;H5lHH@=H5lHA=H5GpHr=HA H5`lH=HH;^=HHH =HMHBHUHuHuIIFIF0INIVIF@H]HEHtHR?HkHC8HH;Eu LHP[A^]kIH]HEHtH ?HckLk ff.UHAVSHPIH7HHE(4kHþ H*kHHCHCXHC`HCXHCHHC@HC8HC0HC(HC HCPHCpHCxHCpHChƃHǃfǃHǃHǃƃHHǃHǃHǃHǃHǃHǃHǃHǃHǃHHHǃHǃHǃǃǃHǃ H]=;H5kH}H=H;H5lHHp=H5lHq=H5woH=HA H5lH=HH;=HHH mHMHHUHuHuIIFIF0INIVIF@H]HEHtH?HkHs5HH;Eu LHP[A^]kIH]HEHtH=?HkLk ff.UHAVSHPIH 5HHE(dkHþ HZkHHCHCXHC`HCXHCHHC@HC8HC0HC(HC HCPHCpHCxHCpHChƃHǃfǃHǃHǃƃHHǃHǃHǃHǃHǃHǃHǃHǃHǃHHHǃHǃHǃǃǃHǃ H]-:H5kH}H=H:H5lHH=H5BlH=H5oH=HA H5lH=HH;=HHH HMHHUHuHuIIFIF0INIVIF@H]HEHtH?HkH2HH;Eu LHP[A^]GkIH]HEHtHm?HkLk ff.UHAVSHPIH;2HHE(kHþ HkHHCHCXHC`HCXHCHHC@HC8HC0HC(HC HCPHCpHCxHCpHChƃHǃfǃHǃHǃƃHHǃHǃHǃHǃHǃHǃHǃHǃHǃHHHǃHǃHǃǃǃHǃ H]];H5kH}H=H:H5NlHH=H5rlH=H5oH=HA H5lH)=HH;=HHH HMH HUHuHuIIFIF0INIVIF@H]HEHtH?H8kH/HH;Eu LHP[A^]wkIH]HEHtH?HkL3k ff.UHAVSHPIHk/HHE(kHþ HkHHCHCXHC`HCXHCHHC@HC8HC0HC(HC HCPHCpHCxHCpHChƃHǃfǃHǃHǃƃHHǃHǃHǃHǃHǃHǃHǃHǃHǃHHHǃHǃHǃǃǃHǃ H]:H5MkH}H=H2:H5~lHH=H5lH=H5oH2=HA H5 lHY=HH;=HHH HMH HUHuHuIIFIF0INIVIF@H]HEHtH?HhkH-HH;Eu LHP[A^]kIH]HEHtH?H#kLck ff.UHAVSHPIH,HHE(kHþ HkHHCHCXHC`HCXHCHHC@HC8HC0HC(HC HCPHCpHCxHCpHChƃHǃfǃHǃHǃƃHHǃHǃHǃHǃHǃHǃHǃHǃHǃHHHǃHǃHǃǃǃHǃ H]:H5}kH}HJ=Hb:H5lHH0=H5lH1=H57oHb=HA H5P +lH=HH;N=HHH -HMHHUHuHuIIFIF0INIVIF@H]HEHtHB?HkH3*HH;Eu LHP[A^]kIH]HEHtH?HSkLk ff.UHAVSHPIH)HHE($kHþ HkHHCHCXHC`HCXHCHHC@HC8HC0HC(HC HCPHCpHCxHCpHChƃHǃfǃHǃHǃƃHHǃHǃHǃHǃHǃHǃHǃHǃHǃHHHǃHǃHǃǃǃHǃ 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DUHAVSHPIH;HHE(蔷kHþ H芷kHHCHCXHC`HCXHCHHC@HC8HC0HC(HC HCPHCpHCxHCpHChƃHǃfǃHǃHǃƃHHǃHǃHǃHǃHǃHǃHǃHǃHǃHHHǃHǃHǃǃǃHǃ H]:H5kH}H=H5lH=H5oH=HA H5 +kHC=HH;=HHH ڃHMH:HUHuHuIIFIF0INIVIF@H]HEHtH?HRkHHH;Eu LHP[A^]葵kIH]HEHtH?H kLMk DUHAVSHPIHHHE(kHþ HڴkHHCHCXHC`HCXHCHHC@HC8HC0HC(HC HCPHCpHCxHCpHChƃHǃfǃHǃHǃƃHHǃHǃHǃHǃHǃHǃHǃHǃHǃHHHǃHǃHǃǃǃHǃ H]:H5mkH}H:=H5lH;=H5AoHl=HH HQH5SkH茹=HH;Q=HHH 0؃HMHUOHUHuHuIIFIF0INIVIF@H]HEHtHE?H蛲kH6HH;Eu LHP[A^]ڲkIH]HEHtH?HVkL薯k fffff.UHAVSHPIHHHE($kHþ HkHHCHCXHC`HCXHCHHC@HC8HC0HC(HC HCPHCpHCxHCpHChƃHǃfǃHǃHǃƃHHǃHǃHǃHǃHǃHǃHǃHǃHǃHHHǃHǃHǃǃǃHǃ H]:H5kH}Hz=H59lH{=H5oH謵=HA H5kHӶ=HH;蘫=HHH wՃHMHlMHUHuHuIIFIF0INIVIF@H]HEHtH?HkH}HH;Eu LHP[A^]!kIH]HEHtHG?H蝯kLݬk DUHAVSHPIHHHE(tkHþ HjkHHCHCXHC`HCXHCHHC@HC8HC0HC(HC HCPHCpHCxHCpHChƃHǃfǃHǃHǃƃHHǃHǃHǃHǃHǃHǃHǃHǃHǃHHHǃHǃHǃǃǃHǃ H]:H5kH}Hʺ=H:H5.lHH谺=H5slH豱=H5oH=HAH5kH =HH;Ψ=HHH ҃HMHKHUHuHuIIFIF0INIVIF@H]HEHtH?HkHHH;Eu LHP[A^]WkIH]HEHtH}?HӬkLk ff.UHAVSHPIHKHHE(褬kHþ H蚬kHHCHCXHC`HCXHCHHC@HC8HC0HC(HC 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1MuKkUHAWAVAUATSHHIIHƯHHE1L5?IǃMI1LL->L0LpPM/MoPM9 I0HPhHxLAH1fffff.LLHkHLZAIIH9|H}LbLLLC$HE1E1LHEEeHD3?HHHHH{0HPHHHtHx0HPHf.11HHHHFPHHt HHAPf1HHHH~L(H HxH HH9HNHED9W)0HDž@LuL}M)t[MIHI9LIkHH8H0JH@M~HLLNJkLH81HH0k+>IH0HL(t H8HkE1W)0HDž@LuLmM)t[LHHH9LFHkIL8L0IH@M~LLLIkML8HHuH0LHDžH0HL(t H8GkMH]I}0HPHHI}bAHIMIMPHHHHHH0HH8H@H@H@HHEHXHDž`HhHDžpHxHDžH0H3<MtLfALFkH}Ht H}FkHxHt H}FkH`Ht HhFkHHHt HPuFkH Ht H(]FkHHt HEFkHHt H-FkMMED;$MtL虣ALEkH]Ht#HHCHuHHPHDkHnHH;EuZH[A\A]A^A_]L{AHI0HPH 7H H;Mu#HLLHH[A\A]A^A_]FkEkH0Bk H0Bk IH0HteWIH0HuHRIKIH0HL(t H8DkE1H}Hu]dIH0Ht H8DkL(E1H}Hu-4IH}Hu&IMIH}Ht H}DkHxHH`HHHHH HHHHHMMH]HHHCHHHPHBkL%Ak H}CkH`HWHhCkHHHKHPCkH H?H(~CkHH3HbCkHH'HFCkMLǠAL-CkM IML蠠ALCkH]HL9@k UHAVSHPIH{HHE(BkHþ HBkHHCHCXHC`HCXHCHHC@HC8HC0HC(HC HCPHCpHCxHCpHChƃHǃfǃHǃHǃƃHHǃHǃHǃHǃHǃHǃHǃHǃHǃHHHǃHǃHǃǃǃHǃ H]p:H5]NkH}H*N=H5'klH+E=H51noH\F=HAH5JkHG=HH;H<=HHH 'fHMH /HUHuHuIIFIF0INIVIF@H]HEHtH<Z?H@kH-HH;Eu LHP[A^]@kIH]HEHtHY?HM@kL=k DUHAVSHPIHˤHHE($@kHþ H@kHHCHCXHC`HCXHCHHC@HC8HC0HC(HC HCPHCpHCxHCpHChƃHǃfǃHǃHǃƃHHǃHǃHǃHǃHǃHǃHǃHǃHǃHHHǃHǃHǃǃǃHǃ H]s:H5KkH}HzK=H5whlH{B=H5koHC=HAH5kHD=HH;9=HHH wcHMH9HUHuHuIIFIF0INIVIF@H]HEHtHW?H=kH}HH;Eu LHP[A^]!>kIH]HEHtHGW?H=kL:k DUHAVSHPIHHHE(t=kHþ Hj=kHHCHCXHC`HCXHCHHC@HC8HC0HC(HC HCPHCpHCxHCpHChƃHǃfǃHǃHǃƃHHǃHǃHǃHǃHǃHǃHǃHǃHǃHHHǃHǃHǃǃǃHǃ H]=k:H5HkH}HH=H5elH?=H5hoH@=HAH5kH#B=HH;6=HHH `HMH\:HUHuHuIIFIF0INIVIF@H]HEHtHT?H2;kH͟HH;Eu LHP[A^]q;kIH]HEHtHT?H:kL-8k DUHAVSHPIHkHHE(:kHþ H:kHHCHCXHC`HCXHCHHC@HC8HC0HC(HC HCPHCpHCxHCpHChƃHǃfǃHǃHǃƃHHǃHǃHǃHǃHǃHǃHǃHǃHǃHHHǃHǃHǃǃǃHǃ H]h:H5MFkH}HF=H5clH==H5!foHL>=HAH5:}kHs?=HH;84=HHH ^HMHDHUHuHuIIFIF0INIVIF@H]HEHtH,R?H8kHHH;Eu LHP[A^]8kIH]HEHtHQ?H=8kL}5k DUHAVSHPIHHHE(8kHþ H +8kHHCHCXHC`HCXHCHHC@HC8HC0HC(HC HCPHCpHCxHCpHChƃHǃfǃHǃHǃƃHHǃHǃHǃHǃHǃHǃHǃHǃHǃHHHǃHǃHǃǃǃHǃ H]e:H5CkH}HjC=H5s`lHk:=H5qcoH;=HAH5zkH<=HH;1=HHH g[HMHCHUHuHuIIFIF0INIVIF@H]HEHtH|O?H5kHmHH;Eu LHP[A^]6kIH]HEHtH7O?H5kL2k DUHAVSHPIH HHE(d5kHþ HZ5kHHCHCXHC`HCXHCHHC@HC8HC0HC(HC HCPHCpHCxHCpHChƃHǃfǃHǃHǃƃHHǃHǃHǃHǃHǃHǃHǃHǃHǃHHHǃHǃHǃǃǃHǃ H]-c:H5@kH}H@=H5]lH7=H5`oH8=HAH5wkH:=HH;.=HHH XHMH|BHUHuHuIIFIF0INIVIF@H]HEHtHL?H"3kHHH;Eu LHP[A^]a3kIH]HEHtHL?H2kL0k DUHAVSHPIH[HHE(2kHþ H2kHHCHCXHC`HCXHCHHC@HC8HC0HC(HC HCPHCpHCxHCpHChƃHǃfǃHǃHǃƃHHǃHǃHǃHǃHǃHǃHǃHǃHǃHHHǃHǃHǃǃǃHǃ H]}`:H5=>kH}H +>=H5[lH 5=H5^oH<6=HAH5*ukHc7=HH;(,=HHH VHMHLAHUHuHuIIFIF0INIVIF@H]HEHtHJ?Hr0kH HH;Eu LHP[A^]0kIH]HEHtHI?H-0kLm-k DUHAVSHPIHHHE(0kHþ H/kHHCHCXHC`HCXHCHHC@HC8HC0HC(HC HCPHCpHCxHCpHChƃHǃfǃHǃHǃƃHHǃHǃHǃHǃHǃHǃHǃHǃHǃHHHǃHǃHǃǃǃHǃ H]]:H5;kH}HZ;=H5rXlH[2=H5a[oH3=HA H5zrkH4=HH;x)=HHH WSHMH@HUHuHuIIFIF0INIVIF@H]HEHtHlG?H-kH]HH;Eu LHP[A^].kIH]HEHtH'G?H}-kL*k DUHAVSHPIHHHE(T-kHþ HJ-kHHCHCXHC`HCXHCHHC@HC8HC0HC(HC HCPHCpHCxHCpHChƃHǃfǃHǃHǃƃHHǃHǃHǃHǃHǃHǃHǃHǃHǃHHHǃHǃHǃǃǃHǃ H][:H58kH}H8=H5UlH/=H5XoH0=HA H5okH2=HH;&=HHH PHMH>HUHuHuIIFIF0INIVIF@H]HEHtHD?H+kHHH;Eu LHP[A^]Q+kIH]HEHtHwD?H*kL (k DUHAVSHPIHKHHE(*kHþ H*kHHCHCXHC`HCXHCHHC@HC8HC0HC(HC HCPHCpHCxHCpHChƃHǃfǃHǃHǃƃHHǃHǃHǃHǃHǃHǃHǃHǃHǃHHHǃHǃHǃǃǃHǃ H]mX:H5-6kH}H5=H5SlH,=H5VoH,.=HA H5mkHS/=HH;$=HHH MHMH=HUHuHuIIFIF0INIVIF@H]HEHtH B?Hb(kHHH;Eu LHP[A^](kIH]HEHtHA?H(kL]%k DUHAVSHPIHHHE('kHþ H'kHHCHCXHC`HCXHCHHC@HC8HC0HC(HC HCPHCpHCxHCpHChƃHǃfǃHǃHǃƃHHǃHǃHǃHǃHǃHǃHǃHǃHǃHHHǃHǃHǃǃǃHǃ H]U:H5}3kH}HJ3=H5rPlHK*=H5QSoH|+=HA H5jjkH,=HH;h!=HHH GKHMH<HUHuHuIIFIF0INIVIF@H]HEHtH\??H%kHMHH;Eu LHP[A^]%kIH]HEHtH??Hm%kL"k DUHAVSHPIH뉂HHE(D%kHþ H:%kHHCHCXHC`HCXHCHHC@HC8HC0HC(HC HCPHCpHCxHCpHChƃHǃfǃHǃHǃƃHHǃHǃHǃHǃHǃHǃHǃHǃHǃHHHǃHǃHǃǃǃHǃ H] S:H50kH}H0=H5MlH'=H5PoH(=HA H5gkH)=HH;=HHH HHMH\;HUHuHuIIFIF0INIVIF@H]HEHtH<?H#kHHH;Eu LHP[A^]A#kIH]HEHtHg<?H"kLk DUHSH(H@HHEHCfHnH<fHnflfMHHH FHMHu1HHHㆂHH;Eu +HH([]"kff.UHAVSHPIHHHE("kHþ H!kHHCHCXHC`HCXHCHHC@HC8HC0HC(HC HCPHCpHCxHCpHChƃHǃfǃHǃHǃƃHHǃHǃHǃHǃHǃHǃHǃHǃHǃHHHǃHǃHǃǃǃHǃ H]O:H5-kH}HZ-=H5JlH[$=H5aMoH%=HHHQH5sdkH&=HH;q=HHH PEHMHDHUHuHuIIFIF0INIVIF@H]HEHtHe9?HkHVHH;Eu LHP[A^]kIH]HEHtH 9?HvkLk fffff.UHAVSHPIH냂HHE(DkHþ H:kHHCHCXHC`HCXHCHHC@HC8HC0HC(HC HCPHCpHCxHCpHChƃHǃfǃHǃHǃƃHHǃHǃHǃHǃHǃHǃHǃHǃHǃHHHǃHǃHǃǃǃHǃ H] M:H5*kH}H*=H5GlH!=H5JoH"=HA H5akH#=HH;=HHH BHMHBHUHuHuIIFIF0INIVIF@H]HEHtH6?HkHHH;Eu LHP[A^]AkIH]HEHtHg6?HkLk DUHAVSHPIH;HHE(kHþ HkHHCHCXHC`HCXHCHHC@HC8HC0HC(HC HCPHCpHCxHCpHChƃHǃfǃHǃHǃƃHHǃHǃHǃHǃHǃHǃHǃHǃHǃHHHǃHǃHǃǃǃHǃ H]K:H5(kH}H'=H5$ElH=H5GoH =HH HQH5_kH<!=HH;=HHH ?HMHe@HUHuHuIIFIF0INIVIF@H]HEHtH3?HKkH~HH;Eu LHP[A^]kIH]HEHtH3?HkLFk fffff.UHAVSHPIH{~HHE(kHþ HkHHCHCXHC`HCXHCHHC@HC8HC0HC(HC HCPHCpHCxHCpHChƃHǃfǃHǃHǃƃHHǃHǃHǃHǃHǃHǃHǃHǃHǃHHHǃHǃHǃǃǃHǃ H]I:H5]%kH}H*%=H5dBlH+=H51EoH\=HA H5J\kH=HH;H=HHH '=HMHtHUHuHuIIFIF0INIVIF@H]HEHtH<1?HkH-|HH;Eu LHP[A^]kIH]HEHtH0?HMkLk DUHAWAVAUATSPII1LBZ?II_1LH=IHәAILHDHL=^HHL诉PILH[A\A]A^A_]fDUHAVSHIHH{HHE(kHþ HkHHCHCXHC`HCXHCHHC@HC8HC0HC(HC HCPHCpHCxHCpHChƃHǃfǃHǃHǃƃHHǃHǃHǃHǃHǃHǃHǃHǃHǃHHHǃHǃHǃǃǃHǃ H]H}HpHpHuH5"kH}HUHp=H5?lH=H5AoH=HH + HQH5XkH&=HH;=HHH 9HMHqHUHuHuIIFIF0INIVIF@HpHt Hx>kH}Ht H},kH]HEHtH-?H kHxHH;EuLHĀ[A^]GkIH}Ht0^IH]HEHt+bIHpHu$H}Hu0H]HEHu9Lk HxkH}HtH}rkH]HEHtH,?HQkLk fUHAVSHIHwHHE(!kHþ HkHHCHCXHC`HCXHCHHC@HC8HC0HC(HC HCPHCpHCxHCpHChƃHǃfǃHǃHǃƃHHǃHǃHǃHǃHǃHǃHǃHǃHǃHHHǃHǃHǃǃǃHǃ H]H}HpHpHuH5kH}HUHpD=H5;lHU=H5[>oH=HA H5tUkH=HH;r =HHH Q6HMHqHUHuHuIIFIF0INIVIF@HpHt HxkH}Ht H}kH]HEHtH<*?HkH-uHH;EuLHĀ[A^]kIH}Ht0^IH]HEHt+bIHpHu$H}Hu0H]HEHu9La k Hx kH}HtH}kH]HEHtH)?HkL k UHAWAVAUATSHH0H8HHDtHHEE11R?IľH(HR?LILMnLI|$0HPHMtI~0HPM1HI$ID$PHMt IIGP1HHILLtDH0HMH L8L9LNL}W)@HDžPLmH]L)L8t\IILH=HkILHL@KHPHL8~LLHkILHH@1H(=HH{0HPHLHHAHH HKPHHHHH@Ht HH kHH@HHHHDž`HDžXHDžPHEHhHDžpHxHDžHH0HH@LH}Ht H}; kH}Ht H}) kHpHt Hx kHXHt H` kH0Ht H8 kHHt H kHHt H kHLqHH;EuHĸ[A\A]A^A_] kH@ k HH@Hu)HH}Ht&HH@Ht HHB kH}Hu[H}HudHpHumHXHuyH0HHHHHH( k H} kH}HtH} kHpHtHx kHXHtH` kH0H{H8w kHHoH [ kHHcH? kHk UHAVSH HIHoHHEHU1H#N?H@0@EHH}HUHIHwoHH;Eu LH [A^] kffff.UHAWAVAUATSHH5oHHEIHHHxH{aNH t3HHCH;pu"HQHy H9HBHH*HAPH8tbHH8HKHAHI H9HAVH;HbHCHHHHHHHH;H uHCHHH;H fHAH;HKbHCHHHHHHHH;H upH9gHAVH;H bHCHHHHHHHH;H u/HHH H*XZhHHx -WH*HHH WH*XZpHCHxHAPH8t=HH8H{t\H{HEH]LuH]H]HhHMNZH{HWzHEH]LuH]H]HhHdMN*HzHEH]LuH]H]HhH8MNH}H9tHtHP(HHH;Et(HP HHH;EuHĈ[A\A]A^A_]CAk@kIHhNH5vlH blH}LhW)PHDž`0@kH`(L|)PHs input.HH&Hsors as HH H two tenHHHrequiresHHHtLooper HHHBroadcasH@.AHPlHuHPLAE1H57قHL4@k IALeMuFzIALhMIIPt H`?kLeMt6HEL9t!HX@t Hxs?kHI9uH}LLeY?kEuEuLhMu&^H}6?kEtH}'?kLhMt:HpL9tEHX@t Hx>kHI9uHhLp>kEtZL?kL<k LIH}H9t*IH}H9tIH}H9uHP L;k HtHP(L;k f.UHHH 4HHxH@Ht]F>k]fDUHSPHH3HH{HCHt>kHH[]>kfUHHH 3HHxH@Ht]=k]fDUHSPHH`3HH{HCHt=kHH[]=kfUHHH "3HHxH@Ht]f=k]fDUHSPHH2HH{HCHt5=kHH[]'=kfUHHH 2HHxH@Ht]<k]fDUHSPHH2HH{HCHt<kHH[]<kfUHHH B2HHxH@Ht]<k]fDUHSPHH2HH{HCHtU<kHH[]G<kfUHHH 1HHxH@Ht]<k]fDUHSPHH1HH{HCHt;kHH[];kfUHHH b1HHxH@Ht];k]fDUHSPHH01HH{HCHtu;kHH[]g;kfUHHH 0HHxH@Ht]6;k]fDUHSPHH0HH{HCHt;kHH[]:kfUHAVSI:kHHr0HH{L3>H;HH[A^]IH:kL7k fff.UHHH "0HHxH@Ht]f:k]fDUHSPHH/HH{HCHt5:kHH[]':kfUHSH(HHHEHbfHnHffHnflfMHHH + -HMHu1H1HH3HH;Eu -HH([]9kff.UHAWAVAUATSHHOHH_0Hp(LP0LKULw@LHLYK<M@uAAAAM9MOH MM)MI?I>MIMH]fnEIr'KDHIH9KD5IH91IEH)LHt#Hf. X HHuHBIID KT fLXLLXLLXL X HI9uL]LuLHfoHVHHDsAHLULE+HEHUHT0HEIMT0M^I)E1DCTC\XXBTB\CTCXXBTBIIuMtBB\XXBB\I9H]LULELuL]K4,IfnEI]H9HMHL)LHtHL X) HHuH rQHUIIT0K\0@LX)LLX)LLX)L X) HH9|L9LfnEM)IKD5LHMHUIMIKILIH9sK>IH9sLLEMLHfoIHRIIEBAHLuLIPL)E1Mfff.BB\XXBB\BT B\0XXBT B\0IHuMtIBB\XXBB\M9LELuLLD)IGH)Ht%Hfff. X HHuHr[LEKD JL fDLXLLXLLXL X HI9u[A\A]A^A_]E1M;RE1MM!fUHAWAVAUATSH_ HHWLQ(Hq0LKH MLw@LHLZK<M@uAAAAM9MOH MM)MI?I>MIMH]fnEIr'KDHIH9KD5IH91IEH)LHt#Hf. X HHuHBIID KT fLXLLXLLXL X HI9uL]LuLHfoHVHHDsAHLULE+HEHUHT0HEIMT0M^I)E1DCTC\XXBTB\CTCXXBTBIIuMtBB\XXBB\I9H]LULELuL]K4,IfnEI]H9HMHL)LHtHL X) HHuH rQHUIIT0K\0@LX)LLX)LLX)L X) HH9|L9LfnEM)IKD5LHMHUIMIKILIH9sK>IH9sLLEMLHfoIHRIIEBAHLuLIPL)E1Mfff.BB\XXBB\BT B\0XXBT B\0IHuMtIBB\XXBB\M9LELuLLD)IGH)Ht%Hfff. X HHuHr[LEKD JL fDLXLLXLLXL X HI9u[A\A]A^A_]E1M;RE1MM!fUHAWAVAUATSH_ HHWLI(Hq0HHEIL_0HHuHMH Hw@LGHHHRHULMAuEAAAM9MOL$N,LL)II?I>HEIIML]H]LM:Is1mI?HMHHMI HI HUILHuHI9@I9AI9I91D LMH] +WH*HHH WH*XZpHCHxHAPH8t=HH8H{t\H/HEH]LuH]H]HhHNZH{Hw.HEH]LuH]H]HhHTN*H.HEH]LuH]H]HhH(NH}H9tHtHP(HlHH;Et(HP HlHH;EuHĈ[A\A]A^A_]CkkIHh茵NH5[lH pclH}LhW)PHDž`0kH`( M|)PHs input.HH&Hsors as HH H two tenHHHrequiresHHHtLooper HHHBroadcasH@.AH^clHuHPL!E1H5WH~L4k IALeMuFzIALhMIIPt H`kLeMt6HEL9t!HX@t HxskHI9uH}LLeYkEuEuLhMu&^H}6kEtH}'kLhMt:HpL9tEHX@t HxkHI9uHhLpkEtZLkLk LIH}H9t*IH}H9tIH}H9uHP Lk HtHP(Lk f.UHHH "HHxH@Ht]Fk]fDUHSPHHHH{HCHtkHH[]kfUHHH HHxH@Ht]k]fDUHSPHHHH{HCHtkHH[]kfUHHH BHHxH@Ht]fk]fDUHSPHHHH{HCHt5kHH[]'kfUHHH HHxH@Ht]k]fDUHSPHHHH{HCHtkHH[]kfUHHH bHHxH@Ht]k]fDUHSPHH0HH{HCHtUkHH[]GkfUHHH HHxH@Ht]k]fDUHSPHHHH{HCHtkHH[]kfUHHH HHxH@Ht]k]fDUHSPHHPHH{HCHtukHH[]gkfUHHH HHxH@Ht]6k]fDUHSPHHHH{HCHtkHH[]kfUHAVSIkHHHH{Lc=HHH[A^]IHkLj fff.UHHH BHHxH@Ht]fk]fDUHSPHHHH{HCHt5kHH[]'kfUHSH(HeHHEHbfHnHffHnflfMHHH + +HMHux1H1HHSeHH;Eu +HH([]kff.UHAWAVAUATSHHOHH_0Hp(LP0LKULw@LHLYK<M@uAAAAM9MOH MM)MI?I>MIMH]fnEIr'KDHIH9KD5IH91IEH)LHt#Hf. 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H}JiPt H`5iDžH8Hu!YH'CIǰH8Ht:H@H9t9Lp@t HxiLL9uH8H@iu -*HIHiH]HEHu0IH]HEHtCt H{oiHgiIM,$I|$ID$HtFiLi fffff.UH]f.UHHH ǁHHxH@Ht]i]fDUHSPHHǁHH{HCHtiHH[]ifUHAWAVAUATSHHIHIHHE1H>IMn1HL<IH[L;T@IMH@HI9L%HL'(;}{)`H?HpH]HEH|fHnHfHnflfMH]H]H`H@LHLH}H9t HtHP(HP IHHHH;EuLHĘ[A\A]A^A_]ixiIH`#~MH5zjH kH}L`_6HHH!aAH jHuLHH9E1H5>iHL;i2IAL`MIIHt HXiLmMt6HEL9t!HX@t HxiHI9uH}LLmniEuEuL`Mu&^H}KiEtH}<iL`Mt:HhL9t=HX@t HxiHI9uH`LhiEt3Li)LIH}H9uHP Ht HP(ILi fDUHAWAVATSII)LOLGM4MIrII9II9}1ɉ)HBH)H)HtHIIHHuH.H)IDILfH|H|H|H|H|H|H<H<HH9uLHHAHHD{AH s1M~I|pIDpMgI)1fDؐLؠDߐLߠDذLD߰LDLDLD D HIuMt2HHDIADA ADA H IuI9[A\A^A_]ffffff.UH}{]fUHSPHiHKHSHPHHH >HH[]fff.UH]ifDUH]f.UH]tifDUHSPH giH vHHKHSHPHHH HHH[]ÐUHH fHnH9fHnflHGHOHNHFH}HF]ffffff.UH]f.UH]ifDUHAWAVATSHLMI)LOLGM<M4IrK I9K I91D)IKH)H)HtHfI<I<HHuH.I)ILITfHtHtHtHtHtHtH4H4HI9uLHHNHHDcAH s1M~ITpI|pIL$H)1DߐLߠDڐLڠD߰LDڰLDLDLD D HHuMt2HHLIAD A ADA H IuI9[A\A^A_]ffffff.UHH {H1H9NHD]DUHHށ]UHAVSI(iHHL>uH[A^]IHiLi UHAVSI(viHHL辌H[A^]IHIiLi UHAVSI(6iHHL讝H[A^]IH iLIi 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H`iDžH8Hu!YH}IǰH8Ht:H@H9t9Lp@t HxoiLL9uH8H@Tiu +*HIHeiH]HEHu0IH]HEHtCt H{iHiIM,$I|$ID$HtiLi fffff.UH]f.UHHH bHHxH@Ht]i]fDUHSPHH0HH{HCHtUiHH[]GifUHAWAVAUATSHHIH:HHE1H.>IMn1HL躸<IH[LX@IMH@HI9L]NHLP(k|{)`H?HpH]HEHρfHnHЁfHnflfMH]H]H`H@LH9LH}H9t HtHP(HP IH9HH;EuLHĘ[A\A]A^A_]ZiiIH`裂MH5jH kH}L`_qHHH葛AHkHuLHsE1H5ZHWLLi2IAL`MIIHt HX=iLmMt6HEL9t!HX@t HxiHI9uH}LLmiEuEuL`Mu&^H}iEtH}iL`Mt:HhL9t=HX@t HxiHI9uH`LhiEt3Li)LIH}H9uHP Ht HP(ILi fDUHAWAVAUATSII)HGLOM4MAuEAAAM9MOHELLUM)MI?I>MIM`IrI7HMH<I9s"II9sE1ILAMIID$HH{HLM*ID0LD0LOI)1AoDAoLf8f8DLAoDAo f8f8D HIuHt$AoAoLf8f8AALM9LMteILAtCLCLHL9t=HMLDI|A\LˉLALˉ HI9uOD=IHMI_I9IMHL)LHt/HLffffff.Aof8fAHHuH r[HEHD0I\0foDf8fDoDf8fDoDf8fDof8fHL9|I9QIM)I)M)IIMKH}J H<H9s I<H9MIIZHHDAH I_H)1fooLf8f8LoD oL0f8f8D L0HHuMt'LAoAoLf8f8AALM9thMЉD))HBL)tC LC<IH9t;L)HEJDKLD\L|L<HH9u[A\A]A^A_]1H:Y1MFhUHz{]fUHSPHiHKHSHPHHH nɁHH[]fff.UH]ifDUH]f.UH]ifDUHSPH iH ɁHHKHSHPHHH ȁHHH[]ÐUHH=ɁfHnHiɁfHnflHGHOHNHFHȁHF]ffffff.UH]f.UH]ifDUHAWAVAUATSHL +MI)HOLGM$MAuEAAAM9MOHML4LUM)MI?I>MIMhIrI 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HP(IL^i fDUHAWAVATSII)LOLGM40M1I rII9II9y1ɉ)HBH)H)HtHA AHHuHH)ID IL\0\1\0\1\0\101HH9uLHHAHHD{AH`s 1MuvI|0pID1pMgI)1ېDLDLDLDLDLDLD D HIuMt2HD3Iff.ADA ADA H IuI9[A\A^A_]ffffff.UHb{]fUHSPHGiHKHSHPHHH ~HH[]fff.UH]ifDUH]f.UH]ifDUHSPH ׶iH HHKHSHPHHH HHH[]ÐUHHMfHnHyfHnflHGHOHNHFHHF]ffffff.UH]f.UH]4ifDUHAWAVATSHLMI)LOLGM<M4I rK I9K I91D)IKH)H)HtHfA6A7HHuHI)IL1IT0\\\\\\HI9uLHHNHHDcAH`s 1MuvITpI|pIL$H)1DLDLDLDLDLDLD D HHuMt2HLIff.AD A ADA H IuI9[A\A^A_]ffffff.UHH Ei{H1H9NHD]DUHHձ]UHAVSI(6iHHLH[A^]IH iLIi UHAWAVAUATSHHIHHHEL-M,$I|$c<H$I$ID$ ID$HgID$H蒫<HHH}貣HEH]Ht,L3H{($dCt H{ SiHKiLMuH}HEHt-iH}u'HHH;EuH[A\A]A^A_]_iH6jH jHu1AT`MiHH8`MH5jH pjHPL8TNH HuHHP1HHQH58H6*H覲iuI t H0;iLuMt6HEL9t!HX@t HxiHI9uH}LLuipt H}iPt H`ձiDžH8Hu!YHWIǰH8Ht:H@H9t9Lp@t HxiLL9uH8H@diu +*HIHuiH]HEHu0IH]HEHtCt H{iHiIM,$I|$ID$HtiL&i fffff.UH]f.UHHH rHHxH@Ht]閰i]fDUHSPHH@HH{HCHteiHH[]WifUHAWAVAUATSHHIHHHE1H>=IMn1HLʒ<IH[L2@IMH@HI9L!HL$(V{)`H?HpH]HEH\fHnH讁fHnflfMH]H]H`H@LHILH}H9t HtHP(HP IHHH;EuLHĘ[A\A]A^A_]jiiIH`\MH5(jH QjH}L`_ KHHHuAHjHuLHME1H54Hg&Lۮi2IAL`MIIHt HXMiLmMt6HEL9t!HX@t Hx(iHI9uH}LLmiEuEuL`Mu&^H}iEtH}ܭiL`Mt:HhL9t=HX@t Hx豭iHI9uH`Lh薭iEt3L蹭i)LIH}H9uHP Ht HP(IL螪i fDUHAWAVATSII)LOLGM4pMqIrIQI9IPI9}1ɉ)HBH)H)HtHAKfANHHuH,H)IDIILH|pf|q|pf|q|pf|q<pf<qHH9uLHHAHHD{AH0s1M~I|ppIDqpMgI)1fDXLXD_L_DXLXD_L_DXLXD_L_DX XD_ _H@IuMt2HHDsIADA ADA H IuI9[A\A^A_]ffffff.UHV{]fUHSPHwiHKHSHPHHH HH[]fff.UH]4ifDUH]f.UH]ifDUHSPH iH VHHKHSHPHHH HHH[]ÐUHHfHnHfHnflHGHOHNHFH]HF]ffffff.UH]f.UH]difDUHAWAVATSHLMI)LOLGM<@M4AIrK YI9K XI91D)IKH)H)HtHfA<vfA<wHHuH,I)ILqITptAftBtAftBtAftB4Af4BHI9uLHHNHHDcAH0s1M~IT@pI|ApIL$H)1D_L_DZLZD_L_DZLZD_L_DZLZD_ _DZ ZH@HuMt2HHLCIAD A ADA H IuI9[A\A^A_]ffffff.UHH e^{H1H9NHD]DUHHe]UHAVSI(ViHHLH[A^]IH)iLii UHAWAVAUATSHHIH HHEL-M,$I|$胅<HI$ID$ ID$HID$H貟<HHH}җHEH]Ht,L3H{(DdCt H{ siHkiLMuH}HEHtMiH}u'H HH;EuH[A\A]A^A_]iHVjH jHu1ATTMiHH8TMH5jH jHPL8TCH HuHHP1HHEH5,HVHƦiuI t H0[iLuMt6HEL9t!HX@t Hx6iHI9uH}LLuipt H} +iPt H`iDžH8Hu!YHKIǰH8Ht:H@H9t9Lp@t Hx蟥iLL9uH8H@脥iu +*HIH蕥iH]HEHu0IH]HEHtCt H{/iH'iIM,$I|$ID$HtiLFi fffff.UH]f.UHHH HHxH@Ht]鶤i]fDUHSPHH`HH{HCHt腤iHH[]wifUHAWAVAUATSHHIHHHE1H^=IMn1HL<IH[L&@IMH@HI9L#HLB%(J{)`H?HpH]HEH죁fHnHxfHnflfMH]H]H`H@LHiLH}H9t HtHP(HP IHHH;EuLHĘ[A\A]A^A_]芣i8iIH`PMH5HjH jH}L`_@?HHHiAHjHuLHAE1H5)HLi2IAL`MIIHt HXmiLmMt6HEL9t!HX@t HxHiHI9uH}LLm.iEuEuL`Mu&^H} iEtH}iL`Mt:HhL9t=HX@t HxѡiHI9uH`Lh趡iEt3L١i)LIH}H9uHP Ht HP(IL辞i fDUHAWAVATSII)LOLGM4MIrII9II9sy1ɉ)HBH)H)HtH@AAHHuHH)ID IL f||||||<<HH9uLHHAHHD{AHs 1MuzI|pIDpMgI)1DDLDLDLDLDLDLD D H IuMt2HHDIADA ADA H IuI9[A\A^A_]ffffff.UH$K{]fUHSPH觟iHKHSHPHHH HH[]fff.UH]difDUH]f.UH]DifDUHSPH 7iH HHKHSHPHHH DHHH[]ÐUHHfHnHfHnflHGHOHNHFHHF]ffffff.UH]f.UH]锞ifDUHAWAVATSHLMI)LOLGM<M4IrK I9K I91D)IKH)H)HtHfA<A<HHuHI)IL IT ftttttt44HI9uLHHNHHDcAHs 1MuzITpI|pIL$H)1@DLDLDLDLDLDLD D H HuMt2HHLIAD A ADA H IuI9[A\A^A_]ffffff.UHH S{H1H9NHD]DUHH]UHAVSI(薜iHHLH[A^]IHiiL詙i UHAWAVAUATSHHIHHHEL-~M,$I|$y<HdI$ID$ ID$HID$H<HHH}HEH]Ht,L3H{(脼dCt H{ 賛iH諛iLMuH}HEHt荛iH}u'H!HH;EuH[A\A]A^A_]进iHjH jHu1AT"IMNiHH8HMH5ZjH jHPL8TO7H HuH<HP1HH9H5-!HHiuI t H0蛚iLuMt6HEL9t!HX@t HxviHI9uH}LLu\ipt H}JiPt H`5iDžH8Hu!YH@IǰH8Ht:H@H9t9Lp@t HxߙiLL9uH8H@ęiu +*HIHՙiH]HEHu0IH]HEHtCt H{oiHgiIM,$I|$ID$HtFiL膖i fffff.UH]f.UHHH {HHxH@Ht]i]fDUHSPHH{HH{HCHtŘiHH[]鷘ifUHAWAVAUATSHHIH/HHE1H=IMn1HL*{<IH[L+@IMH@HI9Lm"HL$(>{)`H?HpH]HEHfHnH(fHnflfMH]H]H`H@LH詣LH}H9t HtHP(HP IH/HH;EuLHĘ[A\A]A^A_]ʗixiIH`EMH5jH jH}L`_3HHH^AHjHuLH(6E1H5^HL;i2IAL`MIIHt HX譖iLmMt6HEL9t!HX@t Hx舖iHI9uH}LLmniEuEuL`Mu&^H}KiEtH}<iL`Mt:HhL9t=HX@t HxiHI9uH`LhiEt3Li)LIH}H9uHP Ht HP(ILi fDUHAWAVATSII)LOLGM4MIrII9II9}1ɉ)HBH)H)HtHIIHHuH.H)IDILfH|H|H|H|H|H|H<H<HH9uLHHAHHD{AH s1M~I|pIDpMgI)1fDؐLؠDߐLߠDذLD߰LDLDLD D HIuMt2HHDIADA ADA H IuI9[A\A^A_]ffffff.UHT?{]fUHSPHדiHKHSHPHHH ^HH[]fff.UH]锓ifDUH]f.UH]tifDUHSPH giH HHKHSHPHHH 䔁HHH[]ÐUHH-fHnHYfHnflHGHOHNHFHHF]ffffff.UH]f.UH]ĒifDUHAWAVATSHLMI)LOLGM<M4IrK I9K I91D)IKH)H)HtHfI<I<HHuH.I)ILITfHtHtHtHtHtHtH4H4HI9uLHHNHHDcAH s1M~ITpI|pIL$H)1DߐLߠDڐLڠD߰LDڰLDLDLD D HHuMt2HHLIAD A ADA H IuI9[A\A^A_]ffffff.UHH 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ffffATAH@HuMt*AoAoLffffAATI9[A\A^A_]1Muf.UHd{]fUHSPHbiHKHSHPHHH hHH[]fff.UH]bifDUH]f.UH]bifDUHSPH wbiH hHHKHSHPHHH gHHH[]ÐUHH-ZfHnHgfHnflHGHOHNHFH]gHF]ffffff.UH]f.UH]aifDUHAWAVATSHL2MI)LOLGM$M<I rK 1I9K 0I91D)INH)H)Ht"HfA71@(A<4HHuH I)IL1IT01@*t@t1@*t@t1@*t@t1@(@4HI9uLHHNHHD[AHIL0IT0I{H)1ff.oDoLffffTDoDo ffffTH@HuMt*AoAoLffffAATI9[A\A^A_]1Mufffff.UHH U{H1H9NHD]DUHHUe]UHAVSI(_iHHLH[A^]IH_iL\i UHAWAVAUATSHHIHĀHHEL-!BM,$I|$<<HdeI$ID$ ID$HeID$H"W<HHH}BOHEH]Ht,L3H{(dCt H{ ^iH^iLMuH}HEHt^iH}u'HQÀHH;EuH[A\A]A^A_]^iHƈjH jHu1ATR M~^iHH8 MH5jH ʛjHPL8TH HuHlHP1HH$H5]HH6^iuI t H0]iLuMt6HEL9t!HX@t Hx]iHI9uH}LLu]ipt H}z]iPt H`e]iDžH8Hu!YH7IǰH8Ht:H@H9t9Lp@t Hx]iLL9uH8H@\iu +*HIH]iH]HEHu0IH]HEHtCt H{\iH\iIM,$I|$ID$Htv\iLYi fffff.UH]f.UHHH ?HHxH@Ht]&\i]fDUHSPHH>HH{HCHt[iHH[][ifUHAWAVAUATSHHIH_HHE1HΞ=IMn1HLZ><IH[L[?IMH@HI9LHL"( {)`H?HpH]HEHafHnHafHnflfMH]H]H`H@LHfLH}H9t HtHP(HP IH_HH;EuLHĘ[A\A]A^A_]ZiZiIH`CMH5jH jH}L`_HHH1!AHJjHuLHXE1H5HLkZi2IAL`MIIHt HXYiLmMt6HEL9t!HX@t 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HxrdHI9uHhLpWdEtLzdL芮d Lffff.UHAVSHPIH(|HHE(dHþ H -dHHCHCXHC`HCXHCHHC@HC8HC0HC(HC HCPHCpHCxHCpHChƃHǃfǃHǃHǃƃHHǃHǃHǃHǃHǃHǃHǃHǃHǃHHHǃHǃHǃǃǃHǃ H]3H5dH}H:6H5 fH;6H5hHl6HHHQH5dH茱6HH;Q6HHH @|HMHHUHuHuIIFIF0INIVIF@H]HEHtH8HˮdHF&|HH;Eu LHP[A^] -dIH]HEHtH@8H膮dLƫd fffff.UHAVSHPIH%|HHE(TdHþ HJdHHCHCXHC`HCXHCHHC@HC8HC0HC(HC HCPHCpHCxHCpHChƃHǃfǃHǃHǃƃHHǃHǃHǃHǃHǃHǃHǃHǃHǃHHHǃHǃHǃǃǃHǃ H]3H5ݹdH}Hz6H5 fH{6H5hH謭6HHHQH5dḪ6HH;董6HHH |HMH'HUHuHuIIFIF0INIVIF@H]HEHtH8H dH#|HH;Eu LHP[A^]JdIH]HEHtH8HƫdLd fffff.UHAVSHPIH#|HHE(蔫dHþ H芫dHHCHCXHC`HCXHCHHC@HC8HC0HC(HC HCPHCpHCxHCpHChƃHǃfǃHǃHǃƃHHǃHǃHǃHǃHǃHǃHǃHǃHǃHHHǃHǃHǃǃǃHǃ H]-3H5dH}H躲6H5LfH軩6H5FhH6HH -HQH5dH 6HH;Ѡ6HHH |HMHFHUHuHuIIFIF0INIVIF@H]HEHtH8HKdH |HH;Eu LHP[A^]芩dIH]HEHtH8HdLFd fffff.UHAVSHPIH[ |HHE(ԨdHþ HʨdHHCHCXHC`HCXHCHHC@HC8HC0HC(HC HCPHCpHCxHCpHChƃHǃfǃHǃHǃƃHHǃHǃHǃHǃHǃHǃHǃHǃHǃHHHǃHǃHǃǃǃHǃ H]m3H5]dH}H6H5fH6H5hH,6HH -HQH5CdHL6HH;6HHH |HMHUDHUHuHuIIFIF0INIVIF@H]HEHtHE8H苦dH|HH;Eu LHP[A^]ʦdIH]HEHtH8HFdL膣d fffff.UHAVSHPIH|HHE(dHþ H -dHHCHCXHC`HCXHCHHC@HC8HC0HC(HC 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H^fffff.UHAVSHH|HH{PHCPHtHP Hs8HC8HtH{@HtHPLsHMt#HIFHuILPL˄dH{ Ht H{(赅dHP{|HH{HCHt [A^]鑅d[A^]HfDUHAVSHHO|HH{PHCPHtHP Hs8HC8HtH{@HtHPLsHMt#HIFHuILPL dH{ Ht H{(dHz|HH{HCHtՄdH[A^]ɄdHUHAVSIX趄dHHLH[A^]IH艄dLɁd UHAWAVAUATSHIIH{HHEL-y|M,$I|$]7H||I$ID$PID$HID$@ID$8ID$0ID$(ID$ HEHDžxƅp fDžusADžqtranƅwHXHpHML}7HXHDžXHtCt H{胃dH{dpt H}idHH}pAD$HEHDžxƅp fDžusBDžqtranƅwHXHpHML|7HXHDžXHtCt H{ڂdH҂dpt H}dHH}pAD$W)pƅp -HEDžqalphfDžuaIL$HXHpL{7HXHDžXHtCt H{8dH0dpt H}dHW)pHEƅpDžqbetaƅuIL$HXHpLrz7HXHDžXHtCt H{誁dH袁dpt H}萁dHH{HH;EuHĨ[A\A]A^A_]dndH0HX/HH5eH eHpLXH@H<HeHpH0H+Dž<H5|HH0d΀dH0HXu.HH5eH eHpLXH@Hp<HeHpH0HDž<H5z|H#H0sd;.dH0HX-HH5ceH OeHpLXOH@H<HdfHpH0HDž<H5|HH0ddH0HX5-HH5eH eHpLXH@H0<H0dfHpH0HKDž<H5:|HH03d Iư<HXH'IIư<HXHIIư<HXH{{I|Iư<HXHSITI@t HP+~dL}Mt6HEL9t!HX@t Hx~dHI9uH}LL}}dEupu#HXHu0H}}dptH}}dHXHH`H9Lx@t Hx~}dLL9ufI@t HPY}dL}Mt6HEL9t!HX@t Hx4}dHI9uH}LL}}dEupu#HXHu0H}|dptH}|dHXHH`H9Lx@t Hx|dLL9uI@t HP|dL}Mt6HEL9t!HX@t Hxb|dHI9uH}LL}H|dEupu#HXHu00H}|dptH} |dHXHH`H9Lx@t Hx{dLL9uI@t HP{dL}Mt6HEL9t!HX@t Hx{dHI9uH}LL}v{dEupu HXHu)aH}P{dptH}>{dHXHt:H`H9tXLx@t Hx{dLL9uHXH`zd<teH0{dI|$PID$PHuY]HIpu*1Ipu#IpuIpt H}zdI|$PID$PHtHP It$8ID$8HtI|$@HtHPM|$ I\$HHt#HHCHuHHPH ydI?Ht +f: f: f: f: f: f: f: f: f: f:f:f: f:f:f: AHML9HUtMMMMH] HMH]HUHHL)I1fff.AA4AHI9u[A\A]A^A_]1LEH}f.UHAWAVAUATSHHH b|H HMЅtaH @fHnH fHnflfMH HMHu1H譎H|HH;EuHĈ[A\A]A^A_]贞dbdIHhKHH5eH eH}Lhj:W)PHDž`@dH`(Hv)PH point tHH(HfloatingHH Hrue for HHHust be tHHHribute mHHHfmod attH@0ypes@4AH/eHuHPL<E1H5#|H*L螝d IALeMuFzIALhMIIPt H`dLeMt6HEL9t!HX@t HxݜdHI9uH}LLeÜdEuEuLhMu&^H}蠜dEtH}葜dLhMt:HpL9tEHX@t HxfdHI9uHhLpKdEtLndL~d LؐUH]f.UH]dfDUHSPHdH |HHKHSHHHPH[]fff.UHH|HHGHOHNHF]UH]f.UH]锛dfDUHH`H!|HHELOHGH6HLH)AofEfH~ffEHGPHHHEHMH8HHDHMHH9HHEH}H9HEHEHuHUIAPHEH}AH{HH;EuH`]3dDUHH gvH1H9NHD]DUHH|]UH]f.UH]鄚dfDUHSPHwdH |HHKHSHHHPH[]fff.UHH|HHGHOHNHF]UH]f.UH]dfDUHH`H{HHELOHGH6HL@H)AofEfH~ffEHGPHHHEHMH8HHDHMHH9HHEH}H9HEHEHuHUIAPHEH}AH{HH;EuH`]袙d@UHH gvH1H9NHD]DUHH|]UH]f.UH]dfDUHSPHdH ο|HHKHSHHHPH[]fff.UHH|HHGHOHNHF]UH]f.UH]tdfDUHH`H{HHELOHGH6HL@H)AofEfH~ffEHGPHHHEHMH8HHDHMHH9HHEH}H9HEHEHuHUIAPHEH}AHh{HH;EuH`]d@UHH fvH1H9NHD]DUHHݾ|]UH]f.UH]ddfDUHSPH0WdH |HHKHSHHHPHKHHHK HH HK(HH(H[]@UHH}|HHG(HF(HG HF HGHFHGHOHNHF]UH]f.UH]鴖dfDUHAWAVAUATSHIH2{HHEL6L:I\$HC0HHC(HHC HHCHHCHHHKHHHHs8HHEIt$IHHIt$IT$LLLLLMID$(HHLPHDžhHDž`HDžXHMHpHDžxHHDžHHIt$ HH诊H}Ht H}KdH}Ht H}9dHpHt Hx!dHXHt H` dH0Ht H8dHHt H ٔdHHt HdH\{HH;EuHĘ[A\A]A^A_]dHH}Hu#HH}HuHH}Ht H}idH}HuFHpHuOHXHu[H0HugHHusHHuHdd H}dHpHtHxdHXHtH`dH0HtH8ɓdHHtH 豓dHHtH虓dHِd UHH cvH1H9NHD]DUHH=|]UHAWAVAUATSPHIM|$XHsXLIDŽ$IDŽ$IDŽ$HH+tlI$HEIILH=u_dIM$M$KI$HHH)H~LH%dIM$H[A\A]A^A_]H}d IHEH8HuRI$Hu_I|$pHulI?HuvI|$0HI|$HI<$HLcd I$ dI$HtI$dI|$pHtI|$xޑdI?HtI|$`̑dI|$0HtII|$0HqI|$8襑dI|$HgI|$ 荑dI<$H]I|$vdL趎d fffff.UHAWAVAUATSPIIHIEIEIEI~I+>tIHHH9LdIM}M}IIEI6I^H)H~LHcdIM}M}IE(IE IEI~ I+~tTHHHH9蝐dIMe MeIIE(IvI^ H)H~LHdIMe IE@IE8IE0I~8I+~0tXL}Me0HHHH9wm#dIM}8M}0IIE@Iv0I^8H)H~LHodIM}8IFHINPIMPIEHH[A\A]A^A_]L!dLdL d II<$Ht I}8萏dHEH8Hu "II?HtI} ndI}HtII}Hu +L藌d I}DdL脌d UHAWAVAUATSHj3Ib3HH4WH!WHWL%WdHVHHH VL0HXH VL=4L5oLLL轎d3I3HHVHVHVL-VidHVHHH VL HXH VLLLMd輼3I3Il3Hd3IHfVHSVH@VL=9V dH(VHH H -VL LhHXLpH VH 4HLL-nL跍d&3I3Iּ3I3HHUHUHU ZdHUHH H UL0LxL`HXH UH=A 4H5UL.d蝻3I3IM3IE3HHwUHdUHQU ьdH@UHH H EUL0LxL`HXH 'UL- 4LH5UHm螌d 3I3I轻3I3HHTHTHT AdHTHH H TL0LxL`HXH TLH5TL%mLdA3I93HHTHTHuTL=nT辋dH]THHH bTL0HXH LTLLL袋dѺ3HE3HE3I3Io3H3I3IHTHTHS8+dHSHH8H SHUHHUHPLxLhHX L`(Lp0H SL- +4LH5SL%kLd3I3HHSHSHtSL=mS荊dH\SHHH aSL0HXH KSLLLqd3HE׾3HE莹3I膿3I3H63I3IHSHSHR8dHRHH8H RHUHHUHPL`LhHX Lp(Lx0H RL- 4LH5RL%jL谉d߸3I׾3HHRHRHsRL=lR\dH[RHHH `RL0HXH JRLLL@do3HEf3HE3I蕷3I 3H腽3I轿3IHRHRHQ8ɈdHQHH8H QHUHHUHPL`LhHX Lp(Lx0H QL-4LH5QL%iLd讷3I覽3HHQHQHrQL=kQ+dHZQHHH _QL0HXH IQLLLd~3HEu3HE,3I$3I\3HԽ3I茾3IHQHQHP8蘇dHPHH8H PHUHHUHPL`LhHX Lp(Lx0H PH=k4H5PH]hH[A\A]A^A_]FdUHAWAVAUATSHMIHAAHtlMtgELMLE(HM HUHL(MNWH}tMHDDHLMELMu0u(ueA1H8H[A\A]A^A_]UHAWAVAUATSHH{HHEMIHIHHW.uHM L;Hu[LHMAuEAAAM9MOMM)MI?I>MIMIpE1YIEIMH)Ht +H8HHMN IOH(HAMWEALHH8IT$pNHpH)HH0HH@LHH E1Mffffff.IrLII4L9s*LI H9v1LH)M'LH(s1H0u{L1fLDLD L0DLD@LPDLoD`LpD H IuH0t;H H@ffff.oD  ADA H HuH8HL9Itzffffff.LH)Mt$H fffff.AHHuHr6ff.ADADDADD AD HI9uILML;HOMIfnfpIPHHYH81HHxHHQMHIGHPMoEALHH8IL$0NH0HH(H)H@LHH 1L1H0DLIr"IMHDK4H9v$K;II9sE1LL)MH(tfAnfpH@1DDDHHuH0tLfAnfpAADH8IL9ttfff.LL)Mt$H fffff.E2F4IHuHr3ff.ABABDABDABD IM9uHLLH;HHSH)1@AADAD AD0AD@ADPAD`ADpAAAAAAAAH@HkHt(ILHfffff.AH HuM9t$LL)Kffffff.HHuK<IfnI[H9HMHL)ۉLHtHLA)HHuHrDfff.A)A)DA)D A)D0A)D@A)DPA)D`A)DpH H9|L9M)IMIfnfpIHHHZH 1HZyLHMAuEAAAM9MOMM)MI?I>MIMNIrJL9nKH9a1ICH)LHtHff.AHHuHADADDADD AD DADDADDADDADHI9uK ItpHKH)1f.DDDDDDDH HuHt$IMKLH@AH HuM9t$LI)I ffffff.HIuHN{HH;EMH[A\A]A^A_]LHHNHHxHs 1HuuHOH)1LAALD L0AD AL0D@LPAD@ALPoD`LpAD`ALpH HuHt*HHoD ADA H HuI9K4IICH9HMHL)؉LHt'HLffff.ofAHHuHrgfDA)DA)DD A)D D0A)D0D@A)D@DPA)DPD`A)D`oDpfADpH H9|L9AM)IIJ H9sKH H9MIIHHHDpAHs 1Mu{K HTpILpI~H)1DLDLDLDLDLDLoD D H HuMt0IMJIoD ADA H IuM9;LD)IGH)HtHAHHuHI)HDIL1tttttttttttttt44HI9uzd[zdIHh'HH5eH LeH}LhucW)PHDž`0ydH`(6zx)PH provideHH H_data isHHHred if cHHHis requiHHHc_shape Hf@(dAHeHuHPLE1H5{H6Lyd IALeMuFzIALhMIIPt H`ydLeMt6HEL9t!HX@t HxxdHI9uH}LLexdEuEuLhMu&^H}xdEtH}xdLhMt:HpL9tEHX@t HxrxdHI9uHhLpWxdEtLzxdLud Lffff.UHAVSHPIH{HHE(xdHþ H +xdHHCHCXHC`HCXHCHHC@HC8HC0HC(HC HCPHCpHCxHCpHChƃHǃfǃHǃHǃƃHHǃHǃHǃHǃHǃHǃHǃHǃHǃHHHǃHǃHǃǃǃHǃ H]ݥ3H5dH}Hj6H5eHkz6H5qhH{6HHHQH5dH|6HH;q6HHH `|HMHHUHuHuIIFIF0INIVIF@H]HEHtHu8HudHf{HH;Eu LHP[A^] +vdIH]HEHtH08HudLrd fffff.UHAVSHPIH{HHE(TudHþ HJudHHCHCXHC`HCXHCHHC@HC8HC0HC(HC HCPHCpHCxHCpHChƃHǃfǃHǃHǃƃHHǃHǃHǃHǃHǃHǃHǃHǃHǃHHHǃHǃHǃǃǃHǃ H]3H5݀dH}H誀6H5eHw6H5hHx6HHHQH5÷dHy6HH;n6HHH |HMH'HUHuHuIIFIF0INIVIF@H]HEHtH赌8H sdH{HH;Eu LHP[A^]JsdIH]HEHtHp8HrdLpd fffff.UHAVSHPIH;{HHE(rdHþ HrdHHCHCXHC`HCXHCHHC@HC8HC0HC(HC HCPHCpHCxHCpHChƃHǃfǃHǃHǃƃHHǃHǃHǃHǃHǃHǃHǃHǃHǃHHHǃHǃHǃǃǃHǃ H]]3H5~dH}H}6H5ZeHt6H5hHv6HH +HQH5dH<w6HH;l6HHH |HMHFHUHuHuIIFIF0INIVIF@H]HEHtH8HKpdH{HH;Eu LHP[A^]pdIH]HEHtH谉8HpdLFmd fffff.UHAVSHPIH{{HHE(odHþ HodHHCHCXHC`HCXHCHHC@HC8HC0HC(HC HCPHCpHCxHCpHChƃHǃfǃHǃHǃƃHHǃHǃHǃHǃHǃHǃHǃHǃHǃHHHǃHǃHǃǃǃHǃ 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IH9s$1HxHf.H(H@1Hxf.fAdfAlf\f\f\f\fAdfAlfAdfA,f\f\f\f\fAdfA,HHuH0t+Lf$flf\f\f\f\fA$fAlH8HH9tnfff.HtIB\\CHHH9t3AT\\AT\\THH9uHHIIHIH;XTMHxDH;LLWIEJIIAHhHXL4MAM)111Muv@AHs1LXfDMLXtL1ff.fTff^fTf^fHHuMt#HHxHHhff^fLL;xt9HxH)HHhHfff. ^ -HHuHLHxHL9L IHHt HzcH`Ht HbcHHt HJcHŅzHH;EMLH[A\A]A^A_]H{ c Hm c IHHu^hIHHIH c{IIIHHt H cH`uHHu$H`H^ cHHtnHF cL -c ILH0Lt H cL cH5 -zHH cH0 cL$ -c fff.UHSPHHHLUHLHEM9HHHH[]UHAWAVAUATSHIIIHzHHEW)pHEfDžpkƅrHXHpHML 6HXHDžXHtCt H{ cH cpt H} cHHEHKAW)pHEƅpDžqaxisƅuHXHpH8Li6HXHDžXHtCt H{a cHY cpt H}G cH@8AHzHH;EuHĨ[A\A]A^A_]n c cIHXǸFH5QtdH tdHpLXyAqH@H›AHtdHpLHsE1H5ܣzHLL -c  -cIHX?FH5sdH tdHpLXzpH@H:AHrtdHpLH^sE1H5TzHKLQ -c -cIHX跷FH5AsdH ~sdHpLX~1pH@H貚AHsdHpLHrE1H5̢zHuKL c IALXMIIALXMIIALXMLI~I@t HPcLeMt6HEL9t!HX@t HxcHI9uH}LLecEupu#LXMu0H}cptH}~cLXMH`L9HX@t HxKcHI9uI@t HP&cLeMt6HEL9t!HX@t HxcHI9uH}LLecEupu#LXMu00H}cptH}cLXMH`L9 HX@t HxycHI9uI@t HPTcLeMt6HEL9t!HX@t Hx/cHI9uH}LLecEupu LXMu)aH}cptH}cLXMt:H`L9tEHX@t HxcHI9uHXL`cEt:LcLc LIpuIpt H}XcLc UHAWAVATSH0HIH}zHHED~Df1HKI7Ht3$ALHHDEMHn}zHH;EtkyPcHH](u)EH5qdCH7cCCHMLyEEt H}cH}zHH;EuLH0[A\A^A_]cHEt H}QcHc fUHAWAVATSH0HIH|zHHED~Df1H;H7Ht3$ALHHDEeH^|zHH;EtkyPcHH](u)EH5pdCH'cCCHMLiEEt H}xcH{zHH;EuLH0[A\A^A_]cHEt H}AcHc fUHAWAVAUATSHH{zHHEIHW)pHEƅpDžqaxisƅuHXHpHMH5HXHDžXHtCt H{cHcpt H}cHu-EAHzzHH;EuHĘ[A\A]A^A_]c^cIHX FH5ldH mdHpLXiH@HAHGmdHpLH(lE1H5zHDLc IALXMII@t HPcLeMt6HEL9t!HX@t HxkcHI9uH}LLeQcEupu LXMu)aH}+cptH}cLXMt:H`L9tEHX@t HxcHI9uHXL`cEt,LcLb LIpt H}cLb f.UHSPHFAH։HH[]DUHAWAVAUATSH8EAAHH}HxzHHE1HWD7IƾHGD7MtnHtiHHHP H)HH9HLM*Aʼn$EH}HLDHH6xzHH;EdpcHH](t)EH5&mddHcCdHMH}9Ey0WcHE(2{w)EHf size 1HH Htensor oHHHbe a 1D HHH should HHHk tensorH@(HMH}EEt H}bHHwzHH;EuH8[A\A]A^A_]ÿ bHE( >t)EHnegativeHHHnot be nHHH k must HHHvalue ofH@HMH}%EbbHEuHEu HEt H}bHQb fUHSPHFAH։HH[]DUHAWAVAUATSH8EAAHH}H(vzHHE1HA7IƾHA7MtnHtiHHHP H)HH9HLM*Aʼn$EH}HLD譣HuzHH;EdpbHH](\t)EH5jddHhbCdHMH}Ey0bHE(xw)EHf size 1HH Htensor oHHHbe a 1D HHH should HHHk tensorH@(HMH}.EEt H}=bHtzHH;EuH8[A\A]A^A_]ÿ bHE({;t)EHnegativeHHHnot be nHHH k must HHHvalue ofH@HMH}Eb bHEuHEu HEt H}bHb fUHAWAVAUATSHHszHHEIIIIW)pHEƅpDžqaxisƅuHXHpHML5HXHDžXHtCt H{bHbpt H}bHpEA$W)pƅpHEHlargestHqHXHpH8LG5HXHDžXHtCt H{?bH7bpt H}%bHaH8AHEHDžxƅp fDžuedDžqsortƅwHXHpH0L5HXHDžXHtCt H{bHbpt H}bHCH0AHqzHH;EuHĨ[A\A]A^A_]bQbIHXFH5cdH ddHpLXv`H@HAH:ddHpLHcE1H5zH;Lb bIHXtFH5bdH wddHpLX_H@HoAHddHpLHbE1H5zH2;LbAbIHXFH5vbdH cdHpLXf_H@HAHpddHpLH bE1H5zH:Lb IALXMIIALXMIIALXMLI~I@t HP-bLeMt6HEL9t!HX@t HxbHI9uH}LLebEupu#LXMu0H}bptH}bLXMH`L9HX@t HxbHI9uI@t HP[bLeMt6HEL9t!HX@t Hx6bHI9uH}LLebEupu#LXMu00H}bptH}bLXMH`L9 HX@t HxbHI9uI@t HPbLeMt6HEL9t!HX@t HxdbHI9uH}LLeJbEupu LXMu)aH}$bptH}bLXMt:H`L9tEHX@t HxbHI9uHXL`bEtHLbLb LIpu#IpuIpt H}bLb UHSPHFNDFH։HH[]UHSPHFNDFH։QHH[]UHAWAVAUATSHHulzHHEHILcvD~F1H77IľH77MHHHHP H)HH9LH=L(MD(It$ I+t$HLDHcIt$DH9HN`dHpHM`dHPLHeH0H]HpH(HPL0HILLHEpbHH]f(tf)EH5H`ddHbCdHML\Ez0zbHEf(Tnwf)EHf size 1HH Htensor oHHHbe a 1D HHH should HHHk tensorH@(HMLEEt H}bHjjzHH;E LH[A\A]A^A_]ÿ bHEf("1tf)EHnegativeHHHnot be nHHH k must HHHvalue ofH@HMLL5EPHHHfWf)HDž Mt$ HI)LHHHH=8 -LbILLHIDH M~LHL;bLLHHHILH1H5IHH5M H(HHHLHHCHE\IHHu9HLs9HHHL3HHHx9HL5IH@LPHHXH`H0H8H@IHL,HHHIHEHcHH9HNL's9HHHH?H/HHH*f: H,H9HNHALOHEHbH :{HLxHHHL`Lh HHH(HHH0HPHH8H0HH@HEH]LpHLdHH}H9HLHXfWf)EHEPJbHH]f(jwf)EH5[dIHbCIHMLL׾EEH}bHH~LUIHHus9HLq9HHHLN1HHH8v9HL]3IHN>LPHHXH`H0H8H@IHL,HHHIH$EHcHH9HNLp9HHHH?H/HHH*f: H,H9HNHALOHEHbH :{HLxHHHL`Lh HHH(HHH0HPHH8H0HH@HEH]LpHLFH}H9HLH w<HpHHE|kHpHHEWH*bWI*b^tf.HEHpHPfbH 7{HLxHHHL`Lh HH(H,/H/-fH-HHH0HHH8HPHH@H0HHHHEH]HpHDH}H9HLHLHP(IHP LHIvWH*bWI*b^tf.HEHpHPbH 8{HLxHHHL`Lh HH(H,/H/-fH-HHH0HHH8HPHH@H0HHHHEH]HpHaCH}H9gHLHLdHP(IZvHP LHI7SHP LHLI$HEH}HHHuP0OHtHpHLrE31LuH]H}HHLP0HL9rPbH 5{HLxHHHL`Lh HH(H,/H/-fH-HHH0HHH8HPHH@H0HHHoHP LHLI!HEH}HHHuP0AHtHpHLdE(1LuH]H}HHLP0HL9rH}I9t HtHP(HP IEHHeHTPJbH 5{HLxHHHL`Lh HH(H,/H/-fH-HHH0HHH8HPHH@H0HHH bHbbH ^zHHH5]zH[xHbbH ^zHHH5_]zH(xHb^ZbH u^zHHH5/]zHwHlb.*bH E^zHHH5\zHwH<b ~|zxHH}I9aHH}I9HEH}bHHHEu5HEu'|HHHuakHEu `HEtWH}LHH}I9t HH}I9uHP HHu#HtHP(HHt HbH+b UHAWAVAUATSHHE]zHHEHILcvD~F1H(7IľH(7MHHHHP H)HH9LH L(MD(It$ I+t$HLHcIt$DH9HQdHpHQdHPLHeH0H]HpH(HPL0H:LLH}EpbHH]f(߾tf)EH5QddHbCdHML,Ez0JbHEf($_wf)EHf size 1HH Htensor oHHHbe a 1D HHH should HHHk tensorH@(HML谳EEt H}bH:[zHH;E LH[A\A]A^A_]ÿ bHEf(!tf)EHnegativeHHHnot be nHHH k must HHHvalue ofH@HMLLEPHHHfWf)HDž Mt$ HI)LHHHH=8 -LbILLHIDH M~LHL bLLHHHILH1H5IHH5M H(HHHLHHCHE\IHHf9HLd9HHHLzHHHdi9HL1IHz1LPHHXH`H0H8H@IHL,HHHIHPEHcHH9HNLc9HHHH?H/HHH*f: H,H9HNHALOHEHbH .{HLxHHHL`Lh HHH(HHH0HPHH8H0HH@HEH]LpHL49H}H9HLHXfWf)EHEPbHH]f(Q[wf)EH5PLdIHlbCIHMLL觯EEH}bHH~LUIHHEd9HLVb9HHHLHHHg9HL-/IH/LPHHXH`H0H8H@IHL,HHHIHEHcHH9HNLa9HHHH?H/HHH*f: H,H9HNHALOHEHibH -{HLxHHHL`Lh HHH(HHH0HPHH8H0HH@HEH]LpHL6H}H9HLH w<HpHHE|kHpHHEWH*bWI*b^Ʒtf.HEHpHP6bH +{HLxHHHL`Lh HH(H,/H/-fH-HHH0HHH8HPHH@H0HHHHEH]HpH5H}H9HLHLHP(IHP LHIvWH*bWI*zb^vtf.HEHpHPbH +{HLxHHHL`Lh HH(H,/H/-fH-HHH0HHH8HPHH@H0HHHHEH]HpH14H}H9gHLHLdHP(IZvHP LHI7SHP LHLI$HEH}HHHuP0OHtHpHLBE31LuH]H}HHLP0HL9rP`bH W){HLxHHHL`Lh HH(H,/H/-fH-HHH0HHH8HPHH@H0HHHoHP LHLI!HEH}HHHuP0AHtHpHL4E(1LuH]H}HHLP0HL9rH}I9t HtHP(HP IEHHeHTPbH ){HLxHHHL`Lh HH(H,/H/-fH-HHH0HHH8HPHH@H0HHHbHbbH OzHHH5bNzH+iHbZbH uOzHHH5/NzHhHlb^*bH EOzHHH5MzHhH<b.bH OzHHH5MzHhH b ~|zxHH}I9aHH}I9HEH}mbHHHEu5HEu'|HHHuakHEu `HEtWH}LHH}I9t HH}I9uHP HHu#HtHP(HHt HbHb UHAVSHPIHNzHHE(bHþ HbHHCHCXHC`HCXHCHHC@HC8HC0HC(HC HCPHCpHCxHCpHChƃHǃfǃHǃHǃƃHHǃHǃHǃHǃHǃHǃHǃHǃHǃHHHǃHǃHǃǃǃHǃ H]-2H5bH}H4HR2H5cHH4H55>dH4H5,gH4HH HQH5cH4HH;4HHH {HMHHUHuHuIIFIF0INIVIF@H]HEHtH6H1bHKzHH;Eu LHP[A^]pbIH]HEHtH6HbL,b @UHAVSHPIHKKzHHE(bHþ HbHHCHCXHC`HCXHCHHC@HC8HC0HC(HC HCPHCpHCxHCpHChƃHǃfǃHǃHǃƃHHǃHǃHǃHǃHǃHǃHǃHǃHǃHHHǃHǃHǃǃǃHǃ H]]2H5MbH}H4H2H5)cHH4H5e;dH4H5\fH4HH HQH5cH"4HH;4HHH {HMHHUHuHuIIFIF0INIVIF@H]HEHtH6HabHHzHH;Eu LHP[A^]bIH]HEHtH6HbL\b @UHAVSHPIH{HzHHE(bHþ HbHHCHCXHC`HCXHCHHC@HC8HC0HC(HC HCPHCpHCxHCpHChƃHǃfǃHǃHǃƃHHǃHǃHǃHǃHǃHǃHǃHǃHǃHHHǃHǃHǃǃǃHǃ H]1H5}bH}H4H1H5YcHH4H58dH4H5fH24HH +HHuHLHxHL9L IHHt HzbH`Ht HbbHHt HJbH9zHH;EMLH[A\A]A^A_]H{b Hmb IHHu^hIHHIHb{IIIHHt HbH`uHHu$H`H^bHHtnHFbLb ILH0Lt 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HxkbHI9uH}LLeQbEupu LXMu)aH}+bptH}bLXMt:H`L9tEHX@t HxbHI9uHXL`bEt,LbLb LIpt H}bLb f.UHSPHFAH։HH[]DUHAWAVAUATSH8EAAHH}H,zHHE1HG 7IƾH7 7MtnHtiHHHP H)HH9HLM*Aʼn$EH}HLDHHV,zHH;EdpbHH](t)EH544ddHbCdHMH})Ey0WbHE(/w)EHf size 1HH Htensor oHHHbe a 1D HHH should HHHk tensorH@(HMH}讖EEt H}bHh+zHH;EuH8[A\A]A^A_]ÿ bHE(s)EHnegativeHHHnot be nHHH k must HHHvalue ofH@HMH}EbbHEuHEu HEt H}bHQb fUHSPHFAH։HH[]DUHAWAVAUATSH8EAAHH}HH*zHHE1H7IƾH7MtnHtiHHHP H)HH9HLM*Aʼn$EH}HLD譣H)zHH;EdpbHH](t)EH51ddHhbCdHMH}虔Ey0bHE(-w)EHf size 1HH Htensor oHHHbe a 1D HHH should HHHk tensorH@(HMH}EEt H}=bH(zHH;EuH8[A\A]A^A_]ÿ bHE(;s)EHnegativeHHHnot be nHHH k must HHHvalue ofH@HMH}腓Eb bHEuHEu HEt H}bHb fUHAWAVAUATSHH'zHHEIIIIW)pHEƅpDžqaxisƅuHXHpHML5HXHDžXHtCt H{bHbpt H}bHpEA$W)pƅpHEHlargestHqHXHpH8Lw5HXHDžXHtCt H{?bH7bpt H}%bHaH8AHEHDžxƅp fDžuedDžqsortƅwHXHpH0Lѿ5HXHDžXHtCt H{bHbpt H}bHCH0AH&zHH;EuHĨ[A\A]A^A_]bQbIHXnFH5*dH ,dHpLXV]H@HׇAHH+dHpLH_E1H51GzH8Lb bIHXdnFH5 *dH +dHpLX\H@HOAH+dHpLHs_E1H5FzH8LbAbIHXmFH5)dH *dHpLXF\H@HdžAH~+dHpLH^E1H5!FzH7Lb IALXMIIALXMIIALXMLI~I@t HP-bLeMt6HEL9t!HX@t HxbHI9uH}LLebEupu#LXMu0H}žbptH}賾bLXMH`L9HX@t Hx耾bHI9uI@t HP[bLeMt6HEL9t!HX@t Hx6bHI9uH}LLebEupu#LXMu00H}bptH}bLXMH`L9 HX@t Hx讽bHI9uI@t HP艽bLeMt6HEL9t!HX@t HxdbHI9uH}LLeJbEupu LXMu)aH}$bptH}bLXMt:H`L9tEHX@t HxbHI9uHXL`̼bEtHLbLb LIpu#IpuIpt H}bL迹b UHSPHFNDFH։HH[]UHSPHFNDFH։QHH[]UHAWAVAUATSHH zHHEHILcvD~F1H6IľH6MHHHHP H)HH9LHL(MD(It$ I+t$HLHcIt$DH9H\'dHpH['dHPLHeH0H]HpH(HPL0HILLH蝊EpȺbHH]f(Ϗtf)EH5V'ddHbCdHMLLEz0zbHEf("wf)EHf size 1HH Htensor oHHHbe a 1D HHH should HHHk tensorH@(HMLЉEEt H}bHzHH;E LH[A\A]A^A_]ÿ ȹbHEf(sf)EHnegativeHHHnot be nHHH k must HHHvalue ofH@HMLL%EPHHHfWf)HDž Mt$ HI)LHHHH=8 +LbILLHIDH M~LHL;bLLHHHILH1HF5IHH/5M H(HHHLHHCHE\IHH<9HL:9HHHL0HHH?9HL2IH=LPHHXH`H0H8H@IHL,HHHIHpEHcHH9HNL:9HHHH?H/HHH*f: H,H9HNHALOHEHbH zHLxHHHL`Lh HHH(HHH0HPHH8H0HH@HEH]LpHLdHH}H9HLHXfWf)EHEPJbHH]f(wf)EH5"dIH蜷bCIHMLLDžEEH}bHH~LUIHHe:9HLv89HHHL..HHH(=9HL=0IH.;LPHHXH`H0H8H@IHL,HHHIHEHcHH9HNL79HHHH?H/HHH*f: 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HLZ`tx@UHAVSI(Ɔ`HHLH[A^]IH虆`Lك` UHAWAVAUATSHHIHwHHEL%!ixMeI}c3H5xIEIE IEIEW)EMuE"HEHocabularHEHstring_vHEfEyHhHUHL肍3HhHDžhHtCt H{躅`H貅`Et H}装`Hu'H9wHH;EuHĨ[A\A]A^A_]ׅ`腅`IHh 3DH5DaH hbH}Lh!HPHLDHbHuLH0$DžDH5_ xHL<`H8DHhHHHH8H8Pt H`薄`HEHHHtIHEH;Ht%HX@t Hxf`HH9HuH}HHHHHE=`EuQEuZHhHHHtHpH;HtUHX@t Hx`HH9HuHh4H}݃`EtH}΃`HhHHHuHHHHHp蟃`Dt(L较`IHu ]H8Et H}n`IHt?IEH9t^ffffff.Lx@t Hx;`LL9uI>I]'`MeI}IEHt `H8I` Hfff.UHAWAVSPIHxIM~Mt=IFL9t(HX@t Hx諂`HI9uI~LM~葂`HLexII~IFHHt [A^A_]g`[A^A_]fUHAWAVSPIH4xIM~Mt=IFL9t(HX@t Hx`HI9uI~LM~`HdxII~IFHt`LH[A^A_]ρ`UHAWAVAUATSHHIHH}HNwHHE1L HEHEHCH+CHIIHEHEHEHEHU1Leh3H IHsH]H[H)txHIL}IAE1fffff.HEHpIILH}L9t @8CDI9rffff.WCDI9rHEHH OwH H;MuHH[A\A]A^A_]`fUHAWAVAUATSHAHHwHHEq3Ht*H_H wH H;Mu$HĨ[A\A]A^A_]1H wH H;Mt{`IǃL+``IHh-DH5cH aH}Lh$H{]3IcHH<!x<H58cH8Hu`HPH8}`HuHP1LH5xH5L` IPt H`A`E18uWH%IA8t@HH`LmMu4hIALhMIIALmMt6HEL9t!HX@t Hx~`HI9uH}LLm~`EuEuLhMu&^H}z~`EtH}k~`LhMt:HpL9tJHX@t Hx@~`HI9uHhLp%~`EtLH~`=~`LS{` LH#fffff.UHAWAVAUATSPIII^IHAt MgM IDLuMf.C tLs( -fDM9LIGHt9tH{0L`u5#H{ HLϷ`uffff.1M9BHKHILIHHvLuM9t=AE tI](I9LHGHtt*Iu0LW`u-I9sMLH[A\A]A^A_]Iu HL*`tx@UHAVSI(薵`HHLH[A^]IHi`L該` UHAWAVAUATSHHIH,xHHEL=ѪxM}I}蔎3HE -yIEIE IEIEW)EE HEHcabularyHEHint64_voHEMuEHhHUHL3HhHDžhHtCt H{茴`H脴`Et H}u`Hu'H+xHH;EuHĨ[A\A]A^A_]詴`W`H8HhaDH5.bH 3bH}Lh{HPHDLH.bHuH8HDžLH5 MxHH8` H@LHhHH@H@Pt H`f`LeMt6HEL9t!HX@t HxA`HI9uH}LLe'`EuEuHhHu&^H}`EtH}`HhHt:HpH9tML`@t Hxʲ`LL9uHhHp诲`Lt1H8ʲ`I>Hu%,HH@Et H}u`I>Ht I}d`M}I}IEHtJ`H@膯` fffff.UHSPHHHyHH{Ht H{ `HxHH{HCHHt[]`[]fUHSPHHyHH{Ht H{蹱`HTxHH{HCHt虱`HH[]鋱`ffff.UHAWAVAUATSH8HIH}H(xHHE1HMHEIOI+OIHHMHEHEHEHU1H3H܆HMoM+oIIE1I $Ht:IGJLfff.HQH9A HMHMH -HuL9tH;F }SHEHEufHCHC1H菮`HEHMHKHCHC H(H芮`HIM9NHEHH 'xH H;MuH8[A\A]A^A_]m`H UHAVSI(`HHLH[A^]IHɯ`L ` UHAWAVAUATSHHIH'xHHEL=1xM}I}3HyIEIE IEIEW)EE HEHcabularyHEHint64_voHEMuEHhHUHLd3HhHDžhHtCt H{`H`Et H}ծ`Hu'HK&xHH;EuHĨ[A\A]A^A_] `跮`H8Hh^\DH5d(bH /bH}LhHPH\?LH6)bHuH8HzDžLH5iGxHH8b` H@LHhHH@H@Pt H`ƭ`LeMt6HEL9t!HX@t Hx衭`HI9uH}LLe臭`EuEuHhHu&^H}d`EtH}U`HhHt:HpH9tML`@t Hx*`LL9uHhHp`Lt1H8*`I>Hu%,HH@Et H}լ`I>Ht I}Ĭ`M}I}IEHt説`H@` fffff.UHSPHHyHH{Ht H{i`HxHH{HCHHt[]C`[]fUHSPHHyHH{Ht H{`HxHH{HCHt`HH[]`ffff.UHAWAVAUATSH(IIIH?#xHHE1LHEIOI+OIHHMHEHEHEHU1LU3HݼMGMWM)IMMMt\I1fILLfDHNH9V HMHMH1HuWL9t H;S |C(HHL9rIIGHH`IHL"xHH;EuLH([A\A]A^A_] -`fff.UHAVSI(薪`HHLH[A^]IHi`L詧` UHAWAVAUATSHHIH!xHHEL=џxM}I}蔃3HyIEIE IEIEW)EE HEHcabularyHEHint64_voHEMuEHhHUHL3HhHDžhHtCt H{茩`H脩`Et H}u`Hu'H xHH;EuHĨ[A\A]A^A_]詩`W`H8HhVDH5#bH @*bH}Lh{HPH9LH#bHuH8HDžLH5 BxHH8` H@LHhHH@H@Pt H`f`LeMt6HEL9t!HX@t HxA`HI9uH}LLe'`EuEuHhHu&^H}`EtH}`HhHt:HpH9tML`@t Hxʧ`LL9uHhHp诧`Lt1H8ʧ`I>Hu%,HH@Et H}u`I>Ht I}d`M}I}IEHtJ`H@膤` fffff.UHSPHHxHH{Ht H{ `HxHH{HCHHt[]`[]fUHSPHHxHH{Ht H{蹦`HTxHH{HCHt虦`HH[]鋦`ffff.UHAWAVAUATSH(IIIHxHHE1LHEIOI+OIHHMHEHEHEHU1L3HMGMWM)IMMMt\I1fILLfDHNH9V HMHMH1HuWL9t H;S |C(HHL9rIIGHH芥`IHxHH;EuLH([A\A]A^A_]誥`fff.UHAWAVAUATSHAHHxHHEs3Ht*HaH xH H;Mu$HĨ[A\A]A^A_]1H [xH H;Mt+`IǃLۤ`Ť`IHhpRDH5cH H&bH}Lh$ -H{4~3IcHH<<H5=cH8H%`HPH8b`HuHP1Lc H5\=xHLY` IPt H``E18uWHIA8t@HH`LmMu4hIALhMIIALmMt6HEL9t!HX@t Hxg`HI9uH}LLmM`EuEuLhMu&^H}*`EtH}`LhMt:HpL9tJHX@t Hx`HI9uHhLpբ`EtL``L` LHfffff.UHAWAVAUATSHXIHxHHEп(~`Hþ Ht`HHCHCXHC`HCXHCHHC@HC8HC0HC(HC HCPHCpHCxHCpHChƃHǃfǃHǃHǃƃHHǃHǃHǃHǃHǃHǃHǃHǃHǃHHHǃHǃHǃǃǃHǃ H]W/IO/I/I/HW)EHE ͠`HEHH HML0L`LhHXHMH5aH}HU轤2H5"bHN2H5dH2HAH5`H覢2HH;k2HHH ZxHMH/HUHuHuIIGIG0IOIWIG@H}Ht H}`H]HEHtH荹4Hӟ`HNxHH;EuLHX[A\A]A^A_] `IH]HEHt7H@4H膟`LƜ` IH}HuH]HEHuL蟜` H}L`H]HEHtff.UHAWAVAUATSH8IIHxHHE1HH3EL^ HIOI+OHH9G 1H4HtHHH@ H)HLu95H bLqCHxHH;E -Ȟ`HHEIG(HEHEHHHDžPHH1H3IL蕯II~ 7HtHLH`}. -11HLfH4IM +fDM9LIGHt9tH{0L~`u5#H{ HL~`uffff.1M9BHKHILIHHvLuM9t=AE tI](I9LHGHtt*Iu0LW~`u-I9sMLH[A\A]A^A_]Iu HL*~`tx@UHAVSI(|`HHLH[A^]IHi|`Ly` UHAWAVAUATSHHIHwHHEL=^xM}I}Y3HexIEIE IEIEW)EE HEHcabularyHEHint64_voHEMuEHhHUHL43HhHDžhHtCt H{{`H{`Et H}u{`Hu'H wHH;EuHĨ[A\A]A^A_]{`W{`H8Hh(DH5aH aH}Lh[HPHALHaHuH8HDžLH5)xHH8{` H@LHhHH@H@Pt H`fz`LeMt6HEL9t!HX@t HxAz`HI9uH}LLe'z`EuEuHhHu&^H}z`EtH}y`HhHt:HpH9tML`@t Hxy`LL9uHhHpy`Lt1H8y`I>Hu%,HH@Et H}uy`I>Ht I}dy`M}I}IEHtJy`H@v` fffff.UHSPHHhxHH{Ht H{ y`H[xHH{HCHHt[]x`[]fUHSPHHxHH{Ht H{x`Ht[xHH{HCHtx`HH[]x`ffff.UHAWAVAUATSH8HIH}HwHHE1HMHEIOI+OIHHMHEHEHEHU1H$_3H較HMoM+oIIE1I $Ht:IGJLfff.HQH9A HMHMH +HuL9tH;F }SHEHEufHCHC1Hu`HEHMHKHCHC H(Hu`HIM9NHEHH wH H;MuH8[A\A]A^A_]mw`HUHAVSI(v`HHLH[A^]IHv`L t` UHAWAVAUATSHHIH?wHHEL=QYxM}I}$T3H%xIEIE IEIEW)EE HEHcabularyHEHint64_voHEMuEHhHUHL|3HhHDžhHtCt H{u`Hu`Et H}u`Hu'HkwHH;EuHĨ[A\A]A^A_] v`u`H8HhN#DH5raH aH}LhHPH<<LHDaHuH8HZDžLH5wHH8bu` H@LHhHH@H@Pt H`t`LeMt6HEL9t!HX@t Hxt`HI9uH}LLet`EuEuHhHu&^H}dt`EtH}Ut`HhHt:HpH9tML`@t Hx*t`LL9uHhHpt`Lt1H8*t`I>Hu%,HH@Et H}s`I>Ht I}s`M}I}IEHts`H@p` fffff.UHSPHH(xHH{Ht H{is`H$VxHH{HCHHt[]Cs`[]fUHSPHHصxHH{Ht H{s`HUxHH{HCHtr`HH[]r`ffff.UHAWAVAUATSH(IIIH_wHHE1LHEIOI+OIHHMHEHEHEHU1LY3H轹MGMWM)IMMMt\I1fILLfDHNH9V HMHMH1HuWL9t H;S |C(HHL9rIIGHHq`IHlwHH;EuLH([A\A]A^A_] +r`fff.UHAVSI(q`HHLH[A^]IHiq`Ln` UHAWAVAUATSHHIHwHHEL=SxM}I}N3H%xIEIE IEIEW)EE HEHcabularyHEHint64_voHEMuEHhHUHL4w3HhHDžhHtCt H{p`Hp`Et H}up`Hu'H wHH;EuHĨ[A\A]A^A_]p`Wp`H8HhDH5aH NaH}Lh[ HPH6LHaHuH8HDžLH5)wHH8p` H@LHhHH@H@Pt H`fo`LeMt6HEL9t!HX@t HxAo`HI9uH}LLe'o`EuEuHhHu&^H}o`EtH}n`HhHt:HpH9tML`@t Hxn`LL9uHhHpn`Lt1H8n`I>Hu%,HH@Et H}un`I>Ht I}dn`M}I}IEHtJn`H@k` fffff.UHSPHH(xHH{Ht H{ n`HPxHH{HCHHt[]m`[]fUHSPHHذxHH{Ht H{m`HtPxHH{HCHtm`HH[]m`ffff.UHAWAVAUATSH(IIIHwHHE1LHEIOI+OIHHMHEHEHEHU1L%T3H͸MGMWM)IMMMt\I1fILLfDHNH9V HMHMH1HuWL9t H;S |C(HHL9rIIGHHl`IH wHH;EuLH([A\A]A^A_]l`fff.UHAWAVAUATSHAHHwHHE]3Ht*H^H wH H;Mu$HĨ[A\A]A^A_]1H {wH H;Mt+l`IǃLk`k`IHh`DH5cH VaH}Lh$H{dI3IcHH<c<H5cH8H%k`HPH8bi`HuHP1LC +H5|wHLYk` IPt H`j`E18uWHIA8t@HHj`LmMu4hIALhMIIALmMt6HEL9t!HX@t Hxgj`HI9uH}LLmMj`EuEuLhMu&^H}*j`EtH}j`LhMt:HpL9tJHX@t Hxi`HI9uHhLpi`EtLi`i`Lg` LHfffff.UHAWAVAUATSHXIH%wHHEп(~i`Hþ Hti`HHCHCXHC`HCXHCHHC@HC8HC0HC(HC HCPHCpHCxHCpHChƃHǃfǃHǃHǃƃHHǃHǃHǃHǃHǃHǃHǃHǃHǃHHHǃHǃHǃǃǃHǃ H]臖/I/I7/I//HW)EHE g`HEHH HML0L`LhHXHMH5aH}HUo2H5aH~k2H5HmdHl2HAH5`Hm2HH;b2HHH zxHMH/HUHuHuIIGIG0IOIWIG@H}Ht H}f`H]HEHtH}4Hf`HnwHH;EuLHX[A\A]A^A_] g`IH]HEHt7H04Hf`Lc` IH}HuH]HEHuLc` H}Lf`H]HEHtff.UHAWAVAUATSH8IIHwHHE1HHP3EL^ HIOI+OHH9G 1H4HtHHH@ H)HLu95H HbL8CHwHH;E +e`HHEIG(HEHEHHHDžPHH1H@L3ILuII~6HtHLHe`}. +11HLfH4IM ID$0@ȃ  -IOH HHMtH HcHHIG(HMIID$IL$ H)HHA2f.IG(HLHID$IL$ H)HH L8AHfIG(HLHID$IL$ H)HH L8AfIG(H LHID$IL$ H)HHL8AH5$7IID$IL$ H)HAL$7IT$IL$ H)HA H#7IID$IL$ H)HAH#7IID$IL$ H)H;A3L(HI9LHOL1IH r7MHHI9MLOJ HHHH?H!LJLHDPAIrH)H I11MLLHMtH 1ffAfALfZfZfAfALfAD fAL0fZfZfADfALHHuMt"fAfALfZfZfAfALH9t.I<IKDH)E1BCZBIHuHI9HILOKLOL9L*H HH9HOHLdIL7H MHHH9ILOJ4HLVDуHHHHDHLHH!HHIHHAIHpH)HHHH1ff.MLI0HILI9sHILMLI9Hs1HH1fff.AALAALAD AL0AD AL0AD@ALPAD@ALPfAD`fALpfAD`fALpH HuHt=H Hff.fAD fA fADfA H HuL;HM<IODI)EAAItID AIHIuIH reHI41@ AD ADD ADD AD D ADD ADD ADD ADHD H H9uHI9HILOILOL9!L(HI9LHOHLHH 7MHHI9MLOJ HHIHI!ML$LHDPAIRH)H I11MumLHH|MtH 1fL[[AALD L0[[AD AL0HHuMtL[[AALL9t4KJ<JTH)E1fWB*BIL9uHI9HILOJHOL9"L(HI9LHOHL*IH;7ML KH=HI9LHOL EAAAMI1fffff.LLMt.LLLfff.WH*HHHuI8HI1WH*CWH*DCDWH*DCDWH*DCD WH*DC DWH*DC(DWH*DC0DWH*DC8DHLC@H H9pHI9KLOKLOL9HHHHHcEH9LLLIH8 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ffEW5$f-h_WI*HLL\f(\HH1ffffff.WH*XWZAYA^XfA.f.f(AfUH,HyI9LLfA(WH*\f(\ff(fYfYN LJLH]LHDHLH|fT f\0Uf.HMHD8HD0HD(HD HDHDHDHHH@H9uHHMIL;X)HHHH;PHHH;{H(LHIHPHFHHHH(HBHJLHHxHBXHHLRHHJPHHXHWH*L]MAHEHHPHIHHr`HHRhHAIHH8HH0H 1HHL@Dfffff.Hx'HHHHxHHHHHL1HpE1ffffff.MHHpH IHHHH01HhH8H9tE19fWEH]H`LHH fW1@HHufRHzHZAYZAYXHzHZAfAf"fYXXXH@HuHLH;XuLHhH8H`H]^fH~XH]H`L0MILfW1E11DLHufQHYAYUYHYAY]f.LwH]QHQAYUf.MwIHQAYfA.MGUI@u&H@fHnH@Hn/fff.fHnf.wHHfHnH@H=IML;XL0LL@DHhH8H`H]HHL9HpHHHHpH;x+HHHHHHHH;PH}Ht&H}nT=-ffEW5f-hHHH;AHJkHH;EuH8[A\A]A^A_]nTH}kT HH}Ht H}mTHjT UHH /gH1H9NHD]DUHHm]UHSPHF(N)HvHH HHH[]ffffff.UHAWAVAUATSHHHukHHEW)EIIHE)EHE)pHEH*HD$(H+%HD$ HHD$HpHD$HEH$D$LELMA1L華(IHU1LM'Iǀ} uLLHH*HLcHL}WXHpHLW)`)P)@)0) ))))HDžLeH]L)tcLIILH=dHkTILLKHHL~LLHlTILMEHHpLHL-HHt HjTHHHt HPjTH Ht H(jTHHt HjTHHt%HjTHpHu#HL,HpHt HxbjTH}Ht H}PjTH}Ht H}>jTHkHH;EuHH[A\A]A^A_]wjTHqgT HHpH\HHpHtqHHHHuHHHt HiTHHHuXH HudHHupHHu|HpHH}HH}HHfT HPAiTH HtH()iTHHtHiTHHtHhTHpHxRHHpHc=HHpHN(HHpH9HHpH$HxhTH}HH}shTH}HH}]hTHeT DUHAWAVAUATSHELxHEHkHH]IW)EHE)E)`HEHDžpHpHvHHE)@HDžPL>LfM)HXH8H`teLHL9(LgTIHHHhLHL@IDHPM~3LLLhTMMLHHHHhE1E1MW) HDž0LL)t[IIHI9fTHH(H JH0M)M~HLL<hTLH($AH HUHML`H`AHpHP0EH@TH`W)HDžHuLuI)HtwMII9HHLfTILLO,LMLHHLVgTMML)HDžE1E1E1XeTILLLW)HDžH8HHEHAHEHtH@HHMLH`臸*LXMuH]Ht#HHCHuHHPHdTHHt HdTHHt HdTT< uCH@*HuHp\HI} v H HpwtXI]H}HHuHpHHx:H@H@MmMuH}L5HEHLxHx`7L9ILHH9~VHuHpLHxCMuH}LHEHHx_7OH9W))))))))Mu)HDžL}H]L)tbIIHI9HcTILLKHHLX~LLHUdTILHH`LLHpLx<%HHt HbTHHt HjbTHHt HRbTHHt H:bTHHt H"bTH Ht H( -bTH@HtHhH8aTH`Ht HhaTH}Ht H}aTH}Ht H}aTH.kHH;Eu4LHĨ[A\A]A^A_]HuHpLHxMaTH@^T(H ^TH^T H^T IHHu:DIHHHIHHt H`THHu)HHu5HHuAHHuQH`THHtH`THHtHg`THHHK`TIH HIH@HHHIH]Ht#HHCHuHHPH^THHt H_TL_TLMu -NIMtFLL5IH Hu7AIHXHHHtH*Hd_TH Ht H(L_TH@HtHhH81_TH`HuH}Hu(H}Hu1LS\T Hh^TH}HtH}^TH}HtH}^TL\T UHAWAVAUATSHhH8kHHEMHHII7IOH9HpJD|H]LuH}HEHEH}L0H@L9HUn}dHH)Hl1E1Hunfffff.H]HtWIHC I9|)ff.L9}+LcHCHtHHC I9}HIHuI@I<$ujHII<$uT(]TLp H@HHXI$HMH HtHMI$H}H^"HEI7IOH}IHH)HI9)vL9t HH*L9tI7IWHк*E1HpI9H0HPL论*HwkHH;EC]TI9u ff.I7IOH)I>HHIH]HtkLmHC I9|,fffff.L9}+LkHCHtHHC I9}HIHuI@I}t*IHpL;ptqfHEHII}uֿ(/\TL` H@HHXIEHMH HtHMIEH}H HEIHpL;pI7H}HHGIGH)HHM7I_W)EHEL)HHLkIJ<y[TIILeLmH]IIJ4LV[TH?t@)HHHK!쀽|LEvE1IE1HEHt.L@HHL9h HMHMHHuL9t -L;n LHL!HEDHHHH#HK4H1H>HEH}HOH;OsHHHO#fff.Hu践ILEAA}LHL!HEDHL9kHH HK4HnDH}HGH;GtHHHHG"ILEffffff.IM7IGL)HI9E1I1fHEHt*L@HHH9X HMHMHHuL9tH;^ }=HHL!HEHHHH#HI4Ht@H>AA`HHL!HEHL9tHH HI4HuH}HGH;GtHHHHGM7LEfDHIGL)HH9A AMHpHH;AtkH}HHGHMHHAIwL)H3HpHpH+0HH}I7H}HGH;GtQHHHHGHEuHvH}HHWH)HHHHHHHOHEt0HEH}HGH;GsHHHG HuMIGL)HHLeLuHHMHHH#H{HHH H0tZHt*ID$I+$HHEH}HOH;OsJHHHOI4ID$I;D$tJHHHID$Jf.ID$HHI HH,L4MI4ID$I;D$uLMfDHIGL)HH9ID$I+$HHHHuHEAE1H}H  H)fHEHM7]HIOI9HyL)HHVH8sYLHHED,H}HHED(AAH}HkkHZH)Lf.H7H0HwH0HwH0HwH0Hw H0Hw(H0Hw0H0Hw8H0H@Hu]HtHfff.H7H0HHut/HMHHAAH}L9IWL袲*|t?L)HHEH]HHSH)HHH)HUH{H}HMHHAH}HHWH)HHHtHr!HHHOH)eHEHHAH}Ht<TTHuH}HkHH;E3DHh[A\A]A^A_]H}kHHC^H}OQT HH}HufpHH}HuXb][HH}HuFPHH}Hu8BHH}Hu*4HH}Hu&HH}HuHH}Ht pSTHHuH}HPT @UHAWAVAUATSHHHkHHEHt'HkHH;EuHĘ[A\A]A^A_]]ST STIH`8H5!ZVH ^VHxL`0H^VHELHHuLH迫AH>[VHxLLûE1H5kHbLRT IAL`MIIHt HX+RTLeMt6HEL9t!HX@t HxRTHI9uH}LLeQTEuxu L`Mu)aH}QTxtH}QTL`Mt:HhL9tEHX@t HxQTHI9uH`LhnQTEtLQTLNT L@UHAWAVAUATSHHkHHEHHOH)Hu?HHH*H9HkHH;EuHĈ[A\A]A^A_]=QTPTIHh7H5XVH ZVH}LhW)PHDž`0PTH`(6h)PHdimensioHH Hith two HHHtrices wHHHks on maHHHOnly worH@(ns.AHWZVHuHPLFE1H5<kHL9PTOTIHh7H5 -WVH YVH}LhW)PƅP*HDž`Hismatch.H^Hize mismHYHOutput sHQƅfAHYVHuHPLyE1H5okHLlOT IALhMIIALeMFIALhMnIIPt H`NTLeMt6HEL9t!HX@t HxNTHI9uH}LLegNTEuEu LhMu-'H}ANTEtH}2NTLhMHpL9HX@t HxMTHI9uIPt H`MTLeMt6HEL9t!HX@t HxMTHI9uH}LLeMTEuEuLhMu&^H}xMTEtH}iMTLhMt:HpL9tEHX@t Hx>MTHI9uHhLp#MTEtLFMTLVJT LfUHAWAVATSH`IHIHakHHEEDIH:^IH1HIHH*EH@HUHHRWH*EH 2mHULeHMHEH]H]HULHYX7H}H9tHtHP(HkHH;Et#HP HkHH;Eu H`[A\A^A_]iLTIH}H9uHP L7IT HtHP(L"IT f.UHAWAVAUATSHH5kHHEHHOH)Hu@HXHHn*H9HkHH;EuHĈ[A\A]A^A_]KTjKTIHh7H5RVH UVH}Lh蒱W)PHDž`0 KTH`(h)PHdimensioHH Hith two HHHtrices wHHHks on maHHHOnly worH@(ns.AHTVHuHPLųE1H5kHdLJTsJTIHh7H5QVH TVH}Lh蛰W)PƅP*HDž`Hismatch.H^Hize mismHYHOutput sHQƅfAHTVHuHPLE1H5kHLIT IALhMIIALeMFIALhMnIIPt H`%ITLeMt6HEL9t!HX@t HxITHI9uH}LLeHTEuEu LhMu-'H}HTEtH}HTLhMHpL9HX@t Hx~HTHI9uIPt H`YHTLeMt6HEL9t!HX@t Hx4HTHI9uH}LLeHTEuEuLhMu&^H}GTEtH}GTLhMt:HpL9tEHX@t HxGTHI9uHhLpGTEtLGTLDT LUHAWAVAUATSHXIIHH߾kHHEHL`>ILXIHHJLLHTHH*EH@HEHH@WH*E(FTH -mHLhLxL`HX HEHUL}LLLR7H}I9tHtHP(HkHH;Et%HP HkHH;EuHX[A\A]A^A_]FTHH}I9uHP HCT HtHP(HuCT ffff.UHAWAVAUATSHHkHHEHHOH)HuDHXHHH*H9HJkHH;EuHĈ[A\A]A^A_]FTETIHha7H5LVH PVH}Lh -ޫW)PHDž`0YETH`(h)PHdimensioHH Hith two HHHtrices wHHHks on maHHHOnly worH@(ns.AHLPVHuHPLE1H5kHLETDTIHhj7H5KVH OVH}Lh W)PƅP*HDž`Hismatch.H^Hize mismHYHOutput sHQƅfAHOVHuHPLDE1H5:kHL7DT IALhMIIALeMFIALhMnIIPt H`qCTLeMt6HEL9t!HX@t HxLCTHI9uH}LLe2CTEuEu LhMu-'H} CTEtH}BTLhMHpL9HX@t HxBTHI9uIPt H`BTLeMt6HEL9t!HX@t HxBTHI9uH}LLefBTEuEuLhMu&^H}CBTEtH}4BTLhMt:HpL9tEHX@t Hx BTHI9uHhLpATEtLBTL!?T L@UHAWAVAUATSHH5kHHEIIHI?HH@H8HHHHH@HHHLRL3MnW)EHEMLHHtUM9N$LATIL}HEHO,LmH5eLL}BTLmI?HEHE1E1IFHWH*IHIFH*hpHH@WH*xW)HDž LL)tTLIII9P@THHHJH 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fDUHAWAVAUATSHELxHEHkHH]IW)EHE)E)`HEHDžpHpHvHHE)@HDžPL>LfM)HXH8H`teLHL9.LTIHHHhLHL@IDHPM~3LLL2TMMLHHHHhE1E1MW) HDž0LL)t[IIHI9TTHH(H JH0M)M~HLLTLH($AH HUHML`H`AHpHP0EH@TH`W)HDžHuLuI)HtwMII9HHLsTILLO,LMLHHLTMML)HDžE1E1E1XTILLLW)HDžH8HHEHAHEHtH@HHMLH`c*LXMuH]Ht#HHCHuHHPHbTHHt HFTHHt H.TT< uIH@*HHp -HI}%H HH HpwtXI]H}H^HuHpHHxtH@H@,MgMuH}LHEHLxHxh 7L9ILHH9~VHuHpLHx-MuH}LHEHHx 7OH9W))))))))Mu)HDžL}H]L)tbIIHI9HkTILLKHHLX~LLHTILHH`LLHpLx -HHt H THHt H THHt H THHt H THHt H| TH Ht H(d TH@HtHhH8I TH`Ht Hh1 TH}Ht H} TH}Ht H} THkHH;Eu4LHĨ[A\A]A^A_]HuHpLHx@M$ TH@ -T(H  -TH -T H T IHHu:DIHHHIHHt H2 THHu)HHu5HHuAHHuQH THHtH THHtH THHH TIH HIH@HHHIH]Ht#HHCHuHHPH> -THHt H" TL TLMu -NIMtFLL5IH Hu7AIHXHHHtHhh*H -TH Ht H( -TH@HtHhH8 -TH`HuH}Hu(H}Hu1LT HhW -TH}HtH}E -TH}HtH}3 -TLsT ff.UHAWAVATSH`IHIHkHHEIHIH1HIHH*EH @HUHalHULeHMHH IWH*EHEH]H]HULH}7H}H9tHtHP(HkHH;Et#HP HʀkHH;Eu H`[A\A^A_] TIH}H9uHP L[T HtHP(LFT fffff.UHAWAVAUATSHXIIHHOkHHEHL`LILIHHJLL -THH*EH @HEHHH@WH*E(]TH tlHLhLxL`HX 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HSHHt HSHHt HlSHHt HTSHHt H<SH Ht H($SH@HtHhH8 SH`Ht HhSH}Ht H}SH}Ht H}SHHhkHH;Eu4LHĨ[A\A]A^A_]HuHpLHx@MSH@S(H SHS HS IHHu:DIHHHIHHt HSHHu)HHu5HHuAHHuQHSHHtHSHHtHSHHHeSIH HIH@HHHIH]Ht#HHCHuHHPHSHHt HSLSLMu -NIMtFLL5IH Hu7AIHXHHHtH(L*H~SH Ht H(fSH@HtHhH8KSH`HuH}Hu(H}Hu1LmS HhSH}HtH}SH}HtH}SL3S ff.UHAWAVATSH`IHIHAekHHEuIH=IH1HIHH*EH @HUH!lHULeHMHH IWH*EHEH]H]HULH=6H}H9tHtHP(HdkHH;Et#HP HdkHH;Eu H`[A\A^A_]MSIH}H9uHP LS HtHP(LS fffff.UHAWAVAUATSHXIIHHdkHHEHL`<ILa<IHHJLLSHH*EH @HEHHH@WH*E(SH 4lHLhLxL`HX HEHUL}LLL6H}I9tHtHP(HDckHH;Et%HP H,ckHH;EuHX[A\A]A^A_]SHH}I9uHP HS HtHP(HS fffff.UHAWAVAUATSHHbkHHEIIHIHH@HHHHHH@HHHL:L3MnW)EHEMLHHtKM9N$LSIL}HEHO,LmH5BeLLSLmHEHE1E1IFHWH*IHIFH*hpHH@WH*xW)HDž LL)t[IIHI9SHHHJH M)M~HLLSLHHH(W)0HDž@HHXL)t[IIHI9ZHBSIL8L0KH@H~LLHSIL8HHHHHPHHXHH`H}H7HhH]HHH6H}H9tuHtHP(H0Ht H8hSHHt HPSH}HtHH88SH_kHH;Eu&H[A\A]A^A_]HP H0Hu]SH}ZSHLS H0>S IH0HtcIHHt[IH}HH}IH}H9uHP H0HtKHu#H0Hu:HHuFH}HuR_HP(H0HtIH0HtH8SHHtHSH}HtHH8SL.S fDUHAWAVAUATSHHE^kHHELL0H8HH IffEHEMnMf M)tWH(LHHH=LeSIL}L}IHEMH(~LLLSML}HHL6ILL H}h*IH8LHPL)tIuI}H)H9u>L bLh*HH3HL@IM$ID$HL)H9uWMD$ML$ LL)H9uBL)t1fDI H; u+HH9uM)tG1fDII; u HI9u*LH8L WI|$H<I|$p0L PID$8IL$HI+D$0HHHXIL$PH`LhHpLxH H*@H @HHHH@WH*fօPHlHEHXHEH]H]H@H0LHD6H}H9toHaHP(H}HW[1I7H}H@DLHfHnHQHHwH s,f1HHP H}HHVH)f1oTfoDfoL(o\8odHffoTXffoDhfoLxfHHuHt9Hfffff.HHofoTfHHuffpNffH~I9tHH)H fDH1HHuI7H}Ht H}SH8ZkHH;EuH[A\A]A^A_]SH}S IH}H9uHP H}HtmHuH}Hu_LS HP(H}HtDIH}Ht6IH}Ht(IH}HtIH}Ht IH}HtH}SL8S UHAVSHPIH[YkHHE(SHþ HSHHCHCXHC`HCXHCHHC@HC8HC0HC(HC HCPHCpHCxHCpHChƃHǃfǃHǃHǃƃHHǃHǃHǃHǃHǃHǃHǃHǃHǃHHHǃHǃHǃǃǃHǃ H]m #H5]SH}H%H5UH%H5 XH,%HH -HQH5C$THL%HH;%HHH lHMHEiHUHuHuIIFIF0INIVIF@H]HEHtHE'HSHWkHH;Eu LHP[A^]SIH]HEHtH'HFSLS fffff.UHAVSHPIHVkHHE(SHþ H -SHHCHCXHC`HCXHCHHC@HC8HC0HC(HC HCPHCpHCxHCpHChƃHǃfǃHǃHǃƃHHǃHǃHǃHǃHǃHǃHǃHǃHǃHHHǃHǃHǃǃǃHǃ H]#H5SH}H:%H54UH;%H5 -XHl%HH -HQH5!TH%HH;Q%HHH @lHMHevHUHuHuIIFIF0INIVIF@H]HEHtH'HSHFTkHH;Eu LHP[A^] -SIH]HEHtH@'HSLS fffff.UHAVSHPIHSkHHE(TSHþ HJSHHCHCXHC`HCXHCHHC@HC8HC0HC(HC HCPHCpHCxHCpHChƃHǃfǃHǃHǃƃHHǃHǃHǃHǃHǃHǃHǃHǃHǃHHHǃHǃHǃǃǃHǃ H]#H5SH}Hz%H5tUH{%H5XH%HH HQH5TH%HH;%HHH lHMHEHUHuHuIIFIF0INIVIF@H]HEHtH'H SHQkHH;Eu LHP[A^]JSIH]HEHtH'HSLS fffff.UHAVSHPIHQkHHE(SHþ HSHHCHCXHC`HCXHCHHC@HC8HC0HC(HC HCPHCpHCxHCpHChƃHǃfǃHǃHǃƃHHǃHǃHǃHǃHǃHǃHǃHǃHǃHHHǃHǃHǃǃǃHǃ H]m#H5SH}H%H5UH%H5FXH%HH HQH5TH %HH;%HHH lHMHEHUHuHuIIFIF0INIVIF@H]HEHtH'HKSHNkHH;Eu LHP[A^]SIH]HEHtH'HSLFS fffff.UHAVSHPIH[NkHHE(SHþ HSHHCHCXHC`HCXHCHHC@HC8HC0HC(HC HCPHCpHCxHCpHChƃHǃfǃHǃHǃƃHHǃHǃHǃHǃHǃHǃHǃHǃHǃHHHǃHǃHǃǃǃHǃ H]m#H5]SH}H%H5UH%H5XH,%HA H5JTHS%HH;%HHH  lHMHLHUHuHuIIFIF0INIVIF@H]HEHtHL'HSH LkHH;Eu LHP[A^]SIH]HEHtH'HMSLS DUHAVSHPIHKkHHE($SHþ HSHHCHCXHC`HCXHCHHC@HC8HC0HC(HC HCPHCpHCxHCpHChƃHǃfǃHǃHǃƃHHǃHǃHǃHǃHǃHǃHǃHǃHǃHHHǃHǃHǃǃǃHǃ H]"H5SH}HJ%H5DUHK%H5WH|%HA H5TH%HH;h%HHH W -lHMH\HUHuHuIIFIF0INIVIF@H]HEHtH'HSH]IkHH;Eu LHP[A^]!SIH]HEHtHW'HSLS DUHAVSHPIHHkHHE(tSHþ HjSHHCHCXHC`HCXHCHHC@HC8HC0HC(HC HCPHCpHCxHCpHChƃHǃfǃHǃHǃƃHHǃHǃHǃHǃHǃHǃHǃHǃHǃHHHǃHǃHǃǃǃHǃ H] "H5SH}H%H5UH%H5&WH%HH -HQH5TH%HH;%HHH lHMHe}HUHuHuIIFIF0INIVIF@H]HEHtH'H+SHFkHH;Eu LHP[A^]jSIH]HEHtH'HSL&S fffff.UHAVSHPIH;FkHHE(SHþ HSHHCHCXHC`HCXHCHHC@HC8HC0HC(HC HCPHCpHCxHCpHChƃHǃfǃHǃHǃƃHHǃHǃHǃHǃHǃHǃHǃHǃHǃHHHǃHǃHǃǃǃHǃ H]"H5=SH}H%H5UH%H5fWH %HH -HQH5#TH,%HH;%HHH lHMHʼnHUHuHuIIFIF0INIVIF@H]HEHtH%'HkSHCkHH;Eu LHP[A^]SIH]HEHtH'H&SLfS fffff.UHAVSHPIH{CkHHE(SHþ HSHHCHCXHC`HCXHCHHC@HC8HC0HC(HC HCPHCpHCxHCpHChƃHǃfǃHǃHǃƃHHǃHǃHǃHǃHǃHǃHǃHǃHǃHHHǃHǃHǃǃǃHǃ H]"H5}SH}H%H5UH%H5WHL%HH HQH5cTHl%HH;1%HHH lHMH՘HUHuHuIIFIF0INIVIF@H]HEHtHe'HSH&AkHH;Eu LHP[A^]SIH]HEHtH 'HfSLS fffff.UHAVSHPIH@kHHE(4SHþ H*SHHCHCXHC`HCXHCHHC@HC8HC0HC(HC HCPHCpHCxHCpHChƃHǃfǃHǃHǃƃHHǃHǃHǃHǃHǃHǃHǃHǃHǃHHHǃHǃHǃǃǃHǃ H] "H5SH}HZ%H5]UH[%H5WH%HH HQH5 TH%HH;q%HHH `kHMHՖHUHuHuIIFIF0INIVIF@H]HEHtH'HSHf>kHH;Eu LHP[A^]*SIH]HEHtH`'HSLS fffff.UHAVSHPIH=kHHE(tSHþ HjSHHCHCXHC`HCXHCHHC@HC8HC0HC(HC HCPHCpHCxHCpHChƃHǃfǃHǃHǃƃHHǃHǃHǃHǃHǃHǃHǃHǃHǃHHHǃHǃHǃǃǃHǃ H] "H5SH}H%H5UH%H5&WH%HA H5TH%HH;踻%HHH kHMHܔHUHuHuIIFIF0INIVIF@H]HEHtH'H2SH;kHH;Eu LHP[A^]qSIH]HEHtH'HSL-S DUHAVSHPIHK;kHHE(SHþ HSHHCHCXHC`HCXHCHHC@HC8HC0HC(HC HCPHCpHCxHCpHChƃHǃfǃHǃHǃƃHHǃHǃHǃHǃHǃHǃHǃHǃHǃHHHǃHǃHǃǃǃHǃ H]"H5MSH}H%H5UH%H5vWH%HA H5:THC%HH;%HHH kHMHHUHuHuIIFIF0INIVIF@H]HEHtH<'HSH8kHH;Eu LHP[A^]SIH]HEHtH'H=SL}S DUHAVSHPIH8kHHE(SHþ H -SHHCHCXHC`HCXHCHHC@HC8HC0HC(HC HCPHCpHCxHCpHChƃHǃfǃHǃHǃƃHHǃHǃHǃHǃHǃHǃHǃHǃHǃHHHǃHǃHǃǃǃHǃ H]"H5SH}H:%H5FUH;%H5WHl%HH -HQH5TH%HH;Q%HHH @kHMHHUHuHuIIFIF0INIVIF@H]HEHtH'H˾SHF6kHH;Eu LHP[A^] -SIH]HEHtH@'H膾SLƻS fffff.UHAVSHPIH5kHHE(TSHþ HJSHHCHCXHC`HCXHCHHC@HC8HC0HC(HC HCPHCpHCxHCpHChƃHǃfǃHǃHǃƃHHǃHǃHǃHǃHǃHǃHǃHǃHǃHHHǃHǃHǃǃǃHǃ H]-"H5SH}Hz%H5UH{%H5WH謽%HH -HQH5TH̾%HH;葳%HHH kHMHHUHuHuIIFIF0INIVIF@H]HEHtH'H SH3kHH;Eu LHP[A^]JSIH]HEHtH'HƻSLS fffff.UHAVSHPIH3kHHE(蔻SHþ H芻SHHCHCXHC`HCXHCHHC@HC8HC0HC(HC HCPHCpHCxHCpHChƃHǃfǃHǃHǃƃHHǃHǃHǃHǃHǃHǃHǃHǃHǃHHHǃHǃHǃǃǃHǃ H]-"H5SH}H%H5UH軹%H5FWH%HH HQH5SH %HH;Ѱ%HHH kHMHEHUHuHuIIFIF0INIVIF@H]HEHtH'HKSH0kHH;Eu LHP[A^]芹SIH]HEHtH'HSLFS fffff.UHAVSHPIH[0kHHE(ԸSHþ HʸSHHCHCXHC`HCXHCHHC@HC8HC0HC(HC HCPHCpHCxHCpHChƃHǃfǃHǃHǃƃHHǃHǃHǃHǃHǃHǃHǃHǃHǃHHHǃHǃHǃǃǃHǃ H]"H5]SH}H%H5UH%H5WH,%HH HQH5CSHL%HH;%HHH kHMHEHUHuHuIIFIF0INIVIF@H]HEHtHE'H苶SH.kHH;Eu LHP[A^]ʶSIH]HEHtH'HFSL膳S fffff.UHAVSHPIH-kHHE(SHþ H -SHHCHCXHC`HCXHCHHC@HC8HC0HC(HC HCPHCpHCxHCpHChƃHǃfǃHǃHǃƃHHǃHǃHǃHǃHǃHǃHǃHǃHǃHHHǃHǃHǃǃǃHǃ H]"H5SH}H:%H5FUH;%H5WHl%HA H5SH蓶%HH;X%HHH GkHMHLHUHuHuIIFIF0INIVIF@H]HEHtH'HҳSHM+kHH;Eu LHP[A^]SIH]HEHtHG'H荳SLͰS DUHAVSHPIH*kHHE(dSHþ HZSHHCHCXHC`HCXHCHHC@HC8HC0HC(HC HCPHCpHCxHCpHChƃHǃfǃHǃHǃƃHHǃHǃHǃHǃHǃHǃHǃHǃHǃHHHǃHǃHǃǃǃHǃ H]="H5SH}H芺%H5UH英%H5WH輲%HA H5SH%HH;訨%HHH kHMH\HUHuHuIIFIF0INIVIF@H]HEHtH'H"SH(kHH;Eu LHP[A^]aSIH]HEHtH'HݰSLS DUHAVSHPIH;(kHHE(贰SHþ H誰SHHCHCXHC`HCXHCHHC@HC8HC0HC(HC HCPHCpHCxHCpHChƃHǃfǃHǃHǃƃHHǃHǃHǃHǃHǃHǃHǃHǃHǃHHHǃHǃHǃǃǃHǃ H]M"H5=SH}Hڷ%H5UHۮ%H5fWH %HH -HQH5#SH,%HH;%HHH kHMHeHUHuHuIIFIF0INIVIF@H]HEHtH%'HkSH%kHH;Eu LHP[A^]誮SIH]HEHtH'H&SLfS fffff.UHAVSHPIH{%kHHE(SHþ HSHHCHCXHC`HCXHCHHC@HC8HC0HC(HC HCPHCpHCxHCpHChƃHǃfǃHǃHǃƃHHǃHǃHǃHǃHǃHǃHǃHǃHǃHHHǃHǃHǃǃǃHǃ H]"H5}SH}H%H53UH%H5WHL%HH -HQH5cSHl%HH;1%HHH kHMHUHUHuHuIIFIF0INIVIF@H]HEHtHe'H諫SH&#kHH;Eu LHP[A^]SIH]HEHtH 'HfSL覨S fffff.UHAVSHPIH"kHHE(4SHþ H*SHHCHCXHC`HCXHCHHC@HC8HC0HC(HC HCPHCpHCxHCpHChƃHǃfǃHǃHǃƃHHǃHǃHǃHǃHǃHǃHǃHǃHǃHHHǃHǃHǃǃǃHǃ H]"H5SH}HZ%H5sUH[%H5WH茪%HH HQH5SH謫%HH;q%HHH `kHMHHUHuHuIIFIF0INIVIF@H]HEHtH'HSHf kHH;Eu LHP[A^]*SIH]HEHtH`'H覨SLS fffff.UHAVSHPIHkHHE(tSHþ HjSHHCHCXHC`HCXHCHHC@HC8HC0HC(HC HCPHCpHCxHCpHChƃHǃfǃHǃHǃƃHHǃHǃHǃHǃHǃHǃHǃHǃHǃHHHǃHǃHǃǃǃHǃ H]M"H5SH}H蚯%H5UH蛦%H5&WḨ%HH HQH5SH%HH;豝%HHH kHMHHUHuHuIIFIF0INIVIF@H]HEHtH'H+SHkHH;Eu LHP[A^]jSIH]HEHtH蠿'HSL&S fffff.UHAVSHPIH;kHHE(败SHþ H誥SHHCHCXHC`HCXHCHHC@HC8HC0HC(HC HCPHCpHCxHCpHChƃHǃfǃHǃHǃƃHHǃHǃHǃHǃHǃHǃHǃHǃHǃHHHǃHǃHǃǃǃHǃ H]M"H5=SH}Hڬ%H5UHۣ%H5fWH %HA H5*SH3%HH;%HHH kHMHHUHuHuIIFIF0INIVIF@H]HEHtH,'HrSHkHH;Eu LHP[A^]豣SIH]HEHtH'H-SLmS DUHAVSHPIHkHHE(SHþ HSHHCHCXHC`HCXHCHHC@HC8HC0HC(HC HCPHCpHCxHCpHChƃHǃfǃHǃHǃƃHHǃHǃHǃHǃHǃHǃHǃHǃHǃHHHǃHǃHǃǃǃHǃ H]"H5SH}H*%H5CUH+%H5WH\%HA H5zSH胣%HH;H%HHH 7kHMHHUHuHuIIFIF0INIVIF@H]HEHtH|'H SH=kHH;Eu LHP[A^]SIH]HEHtH7'H}SL轝S DUHAVSHPIHkHHE(TSHþ HJSHHCHCXHC`HCXHCHHC@HC8HC0HC(HC HCPHCpHCxHCpHChƃHǃfǃHǃHǃƃHHǃHǃHǃHǃHǃHǃHǃHǃHǃHHHǃHǃHǃǃǃHǃ H]"H5ݫSH}Hz%H5UH{%H5WH謟%HH -HQH5SH̠%HH;葕%HHH kHMHHUHuHuIIFIF0INIVIF@H]HEHtHŷ'H SHkHH;Eu LHP[A^]JSIH]HEHtH耷'HƝSLS fffff.UHAVSHPIHkHHE(蔝SHþ H芝SHHCHCXHC`HCXHCHHC@HC8HC0HC(HC HCPHCpHCxHCpHChƃHǃfǃHǃHǃƃHHǃHǃHǃHǃHǃHǃHǃHǃHǃHHHǃHǃHǃǃǃHǃ H]-"H5SH}H躤%H5ӢUH軛%H5FWH%HH HQH5SH %HH;ђ%HHH kHMHHUHuHuIIFIF0INIVIF@H]HEHtH'HKSHkHH;Eu LHP[A^]芛SIH]HEHtH'HSLFS fffff.UHAVSHPIH[kHHE(ԚSHþ HʚSHHCHCXHC`HCXHCHHC@HC8HC0HC(HC HCPHCpHCxHCpHChƃHǃfǃHǃHǃƃHHǃHǃHǃHǃHǃHǃHǃHǃHǃHHHǃHǃHǃǃǃHǃ H]m"H5]SH}H%H5UH%H5WH,%HA H5JSHS%HH;%HHH kHMHHUHuHuIIFIF0INIVIF@H]HEHtHL'H蒘SH kHH;Eu LHP[A^]јSIH]HEHtH'HMSL荕S DUHAVSHPIHkHHE($SHþ HSHHCHCXHC`HCXHCHHC@HC8HC0HC(HC HCPHCpHCxHCpHChƃHǃfǃHǃHǃƃHHǃHǃHǃHǃHǃHǃHǃHǃHǃHHHǃHǃHǃǃǃHǃ H]"H5SH}HJ%H5sUHK%H5WH|%HH -HQH5SH蜘%HH;a%HHH PkHMHHUHuHuIIFIF0INIVIF@H]HEHtH蕯'HەSHV kHH;Eu LHP[A^]SIH]HEHtHP'H薕SL֒S fffff.UHAVSHPIH kHHE(dSHþ HZSHHCHCXHC`HCXHCHHC@HC8HC0HC(HC HCPHCpHCxHCpHChƃHǃfǃHǃHǃƃHHǃHǃHǃHǃHǃHǃHǃHǃHǃHHHǃHǃHǃǃǃHǃ H]="H5SH}H芜%H5UH苓%H5WH輔%HH -HQH5SHܕ%HH;衊%HHH kHMHUHUHuHuIIFIF0INIVIF@H]HEHtHլ'HSH -kHH;Eu LHP[A^]ZSIH]HEHtH萬'H֒SLS fffff.UHAVSHPIH+ -kHHE(褒SHþ H蚒SHHCHCXHC`HCXHCHHC@HC8HC0HC(HC HCPHCpHCxHCpHChƃHǃfǃHǃHǃƃHHǃHǃHǃHǃHǃHǃHǃHǃHǃHHHǃHǃHǃǃǃHǃ H]}"H5-SH}Hʙ%H5UHː%H5VWH%HH -HQH5SH%HH;%HHH kHMH%,HUHuHuIIFIF0INIVIF@H]HEHtH'H[SHkHH;Eu LHP[A^]蚐SIH]HEHtHЩ'HSLVS fffff.UHAVSHPIHkkHHE(SHþ HڏSHHCHCXHC`HCXHCHHC@HC8HC0HC(HC HCPHCpHCxHCpHChƃHǃfǃHǃHǃƃHHǃHǃHǃHǃHǃHǃHǃHǃHǃHHHǃHǃHǃǃǃHǃ H]}"H5mSH}H -%H53UH %H5WH<%HH -HQH5SSH\%HH;!%HHH kHMHEKHUHuHuIIFIF0INIVIF@H]HEHtHU'H蛍SHkHH;Eu LHP[A^]ڍSIH]HEHtH'HVSL薊S fffff.UHAVSHPIHkHHE($SHþ HSHHCHCXHC`HCXHCHHC@HC8HC0HC(HC HCPHCpHCxHCpHChƃHǃfǃHǃHǃƃHHǃHǃHǃHǃHǃHǃHǃHǃHǃHHHǃHǃHǃǃǃHǃ H]轶"H5SH}HJ%H5sUHK%H5ָWH|%HH HQH5SH蜍%HH;a%HHH PkHMHEuHUHuHuIIFIF0INIVIF@H]HEHtH蕤'HۊSHVkHH;Eu LHP[A^]SIH]HEHtHP'H薊SLևS fffff.UHAVSHPIHkHHE(dSHþ HZSHHCHCXHC`HCXHCHHC@HC8HC0HC(HC HCPHCpHCxHCpHChƃHǃfǃHǃHǃƃHHǃHǃHǃHǃHǃHǃHǃHǃHǃHHHǃHǃHǃǃǃHǃ H]="H5SH}H芑%H5UH苈%H5WH載%HH HQH5SH܊%HH;%HHH kHMHEsHUHuHuIIFIF0INIVIF@H]HEHtHա'HSHjHH;Eu LHP[A^]ZSIH]HEHtH萡'HևSLS fffff.UHAVSHPIH+jHHE(複SHþ H蚇SHHCHCXHC`HCXHCHHC@HC8HC0HC(HC HCPHCpHCxHCpHChƃHǃfǃHǃHǃƃHHǃHǃHǃHǃHǃHǃHǃHǃHǃHHHǃHǃHǃǃǃHǃ H]}"H5-SH}Hʎ%H5UH˅%H5VWH%HH HQH5SH%HH;|%HHH нkHMHEqHUHuHuIIFIF0INIVIF@H]HEHtH'H[SHjHH;Eu LHP[A^]蚅SIH]HEHtHО'HSLVS fffff.UHAVSHPIHkjHHE(SHþ HڄSHHCHCXHC`HCXHCHHC@HC8HC0HC(HC HCPHCpHCxHCpHChƃHǃfǃHǃHǃƃHHǃHǃHǃHǃHǃHǃHǃHǃHǃHHHǃHǃHǃǃǃHǃ H]}"H5mSH}H -%H53UH %H5WH<%HH HQH5SSH\%HH;!z%HHH kHMHEoHUHuHuIIFIF0INIVIF@H]HEHtHU'H蛂SHjHH;Eu LHP[A^]ڂSIH]HEHtH'HVSLS fffff.UHAVSHPIHjHHE($SHþ HSHHCHCXHC`HCXHCHHC@HC8HC0HC(HC HCPHCpHCxHCpHChƃHǃfǃHǃHǃƃHHǃHǃHǃHǃHǃHǃHǃHǃHǃHHHǃHǃHǃǃǃHǃ H]轫"H5SH}HJ%H5sUHK%H5֭WH|%HH HQH5SH蜂%HH;aw%HHH PkHMHEmHUHuHuIIFIF0INIVIF@H]HEHtH蕙'HSHVjHH;Eu LHP[A^]SIH]HEHtHP'HSL|S fffff.UHAVSHPIHjHHE(dSHþ HZSHHCHCXHC`HCXHCHHC@HC8HC0HC(HC HCPHCpHCxHCpHChƃHǃfǃHǃHǃƃHHǃHǃHǃHǃHǃHǃHǃHǃHǃHHHǃHǃHǃǃǃHǃ H]="H5SH}H芆%H5UH}%H5WH~%HH HQH5SH%HH;t%HHH kHMHEkHUHuHuIIFIF0INIVIF@H]HEHtHՖ'H}SHjHH;Eu LHP[A^]Z}SIH]HEHtH萖'H|SLzS fffff.UHAVSHPIH+jHHE(|SHþ H|SHHCHCXHC`HCXHCHHC@HC8HC0HC(HC HCPHCpHCxHCpHChƃHǃfǃHǃHǃƃHHǃHǃHǃHǃHǃHǃHǃHǃHǃHHHǃHǃHǃǃǃHǃ H]}"H5-SH}Hʃ%H5UHz%H5VWH{%HH HQH5SH}%HH;q%HHH вkHMHEiHUHuHuIIFIF0INIVIF@H]HEHtH'H[zSHjHH;Eu LHP[A^]zSIH]HEHtHГ'HzSLVwS fffff.UHAVSHPIHkjHHE(ySHþ HySHHCHCXHC`HCXHCHHC@HC8HC0HC(HC HCPHCpHCxHCpHChƃHǃfǃHǃHǃƃHHǃHǃHǃHǃHǃHǃHǃHǃHǃHHHǃHǃHǃǃǃHǃ H]}"H5mSH}H -%H53UH x%H5WH<y%HH HQH5SSH\z%HH;!o%HHH kHMHEgHUHuHuIIFIF0INIVIF@H]HEHtHU'HwSHjHH;Eu LHP[A^]wSIH]HEHtH'HVwSLtS fffff.UHAVSHPIHjHHE($wSHþ HwSHHCHCXHC`HCXHCHHC@HC8HC0HC(HC HCPHCpHCxHCpHChƃHǃfǃHǃHǃƃHHǃHǃHǃHǃHǃHǃHǃHǃHǃHHHǃHǃHǃǃǃHǃ H]"H5SH}HJ~%H5s|UHKu%H5֢WH|v%HH HQH5SHw%HH;al%HHH PkHMHEeHUHuHuIIFIF0INIVIF@H]HEHtH蕎'HtSHVjHH;Eu LHP[A^]uSIH]HEHtHP'HtSLqS fffff.UHAVSHPIHjHHE(dtSHþ HZtSHHCHCXHC`HCXHCHHC@HC8HC0HC(HC HCPHCpHCxHCpHChƃHǃfǃHǃHǃƃHHǃHǃHǃHǃHǃHǃHǃHǃHǃHHHǃHǃHǃǃǃHǃ H]"H5SH}H{%H5yUHr%H5WHs%HH HQH5ӶSHt%HH;i%HHH kHMHuHUHuHuIIFIF0INIVIF@H]HEHtHՋ'HrSHjHH;Eu LHP[A^]ZrSIH]HEHtH萋'HqSLoS fffff.UHAVSHPIH+jHHE(qSHþ HqSHHCHCXHC`HCXHCHHC@HC8HC0HC(HC HCPHCpHCxHCpHChƃHǃfǃHǃHǃƃHHǃHǃHǃHǃHǃHǃHǃHǃHǃHHHǃHǃHǃǃǃHǃ H]="H5-}SH}Hx%H5vUHo%H5VWHp%HA H5SH#r%HH;f%HHH קkHMHHUHuHuIIFIF0INIVIF@H]HEHtH'HboSHjHH;Eu LHP[A^]oSIH]HEHtH׈'HoSL]lS DUHAVSHPIH{jHHE(nSHþ HnSHHCHCXHC`HCXHCHHC@HC8HC0HC(HC HCPHCpHCxHCpHChƃHǃfǃHǃHǃƃHHǃHǃHǃHǃHǃHǃHǃHǃHǃHHHǃHǃHǃǃǃHǃ H]͗"H5}zSH}Hv%H5CtUHm%H5WHLn%HA H5jSHso%HH;8d%HHH 'kHMHHUHuHuIIFIF0INIVIF@H]HEHtHl'HlSH-jHH;Eu LHP[A^]lSIH]HEHtH''HmlSLiS DUHAVSHPIHjHHE(DlSHþ H:lSHHCHCXHC`HCXHCHHC@HC8HC0HC(HC HCPHCpHCxHCpHChƃHǃfǃHǃHǃƃHHǃHǃHǃHǃHǃHǃHǃHǃHǃHHHǃHǃHǃǃǃHǃ H]"H5wSH}Hjs%H5qUHkj%H5WHk%HA H5SHl%HH;a%HHH wkHMHHUHuHuIIFIF0INIVIF@H]HEHtH較'HjSH}jHH;Eu LHP[A^]AjSIH]HEHtHw'HiSLfS DUHAVSHPIHjHHE(iSHþ HiSHHCHCXHC`HCXHCHHC@HC8HC0HC(HC HCPHCpHCxHCpHChƃHǃfǃHǃHǃƃHHǃHǃHǃHǃHǃHǃHǃHǃHǃHHHǃHǃHǃǃǃHǃ H]-"H5uSH}Hp%H5nUHg%H5FWHh%HA H5 -SHj%HH;^%HHH ǟkHMH̡HUHuHuIIFIF0INIVIF@H]HEHtH 'HRgSHjHH;Eu LHP[A^]gSIH]HEHtHǀ'H gSLMdS DUHAVSHPIHkjHHE(fSHþ HfSHHCHCXHC`HCXHCHHC@HC8HC0HC(HC HCPHCpHCxHCpHChƃHǃfǃHǃHǃƃHHǃHǃHǃHǃHǃHǃHǃHǃHǃHHHǃHǃHǃǃǃHǃ H]轒"H5mrSH}H -n%H53lUH e%H5WH<f%HA H5ZSHcg%HH;(\%HHH kHMHܟHUHuHuIIFIF0INIVIF@H]HEHtH\~'HdSHjHH;Eu LHP[A^]dSIH]HEHtH~'H]dSLaS DUHAVSHPIHjHHE(4dSHþ H*dSHHCHCXHC`HCXHCHHC@HC8HC0HC(HC HCPHCpHCxHCpHChƃHǃfǃHǃHǃƃHHǃHǃHǃHǃHǃHǃHǃHǃHǃHHHǃHǃHǃǃǃHǃ H]͐"H5oSH}HZk%H5iUH[b%H5WHc%HA H5SHd%HH;xY%HHH gkHMHHUHuHuIIFIF0INIVIF@H]HEHtH{'HaSHmjHH;Eu LHP[A^]1bSIH]HEHtHg{'HaSL^S DUHAVSHPIH jHHE(aSHþ HzaSHHCHCXHC`HCXHCHHC@HC8HC0HC(HC HCPHCpHCxHCpHChƃHǃfǃHǃHǃƃHHǃHǃHǃHǃHǃHǃHǃHǃHǃHHHǃHǃHǃǃǃHǃ H]"H5 mSH}Hh%H5fUH_%H56WH`%HH -HQH5SHa%HH;V%HHH kHMHHUHuHuIIFIF0INIVIF@H]HEHtHx'H;_SHjHH;Eu LHP[A^]z_SIH]HEHtHx'H^SL6\S fffff.UHAVSHPIHKjHHE(^SHþ H^SHHCHCXHC`HCXHCHHC@HC8HC0HC(HC HCPHCpHCxHCpHChƃHǃfǃHǃHǃƃHHǃHǃHǃHǃHǃHǃHǃHǃHǃHHHǃHǃHǃǃǃHǃ H]蝇"H5MjSH}He%H5dUH\%H5vWH^%HH -HQH53SH<_%HH;T%HHH kHMHHUHuHuIIFIF0INIVIF@H]HEHtH5v'H{\SHjHH;Eu LHP[A^]\SIH]HEHtHu'H6\SLvYS fffff.UHAVSHPIHjHHE(\SHþ H[SHHCHCXHC`HCXHCHHC@HC8HC0HC(HC HCPHCpHCxHCpHChƃHǃfǃHǃHǃƃHHǃHǃHǃHǃHǃHǃHǃHǃHǃHHHǃHǃHǃǃǃHǃ H]蝅"H5gSH}H*c%H5]aUH+Z%H5WH\[%HH HQH5sSH|\%HH;AQ%HHH 0kHMHuHUHuHuIIFIF0INIVIF@H]HEHtHus'HYSH6jHH;Eu LHP[A^]YSIH]HEHtH0s'HvYSLVS fffff.UHAVSHPIHjHHE(DYSHþ H:YSHHCHCXHC`HCXHCHHC@HC8HC0HC(HC HCPHCpHCxHCpHChƃHǃfǃHǃHǃƃHHǃHǃHǃHǃHǃHǃHǃHǃHǃHHHǃHǃHǃǃǃHǃ H]"H5dSH}Hj`%H5^UHkW%H5WHX%HH HQH5SHY%HH;N%HHH pkHMHuHUHuHuIIFIF0INIVIF@H]HEHtHp'HVSHvjHH;Eu LHP[A^]:WSIH]HEHtHpp'HVSLSS fffff.UHAVSHPIH jHHE(VSHþ HzVSHHCHCXHC`HCXHCHHC@HC8HC0HC(HC HCPHCpHCxHCpHChƃHǃfǃHǃHǃƃHHǃHǃHǃHǃHǃHǃHǃHǃHǃHHHǃHǃHǃǃǃHǃ H]"H5 bSH}H]%H5[UHT%H56WHU%HA H5SHW%HH;K%HHH kHMH|HUHuHuIIFIF0INIVIF@H]HEHtHm'HBTSHjHH;Eu LHP[A^]TSIH]HEHtHm'HSSL=QS DUHAVSHPIH[jHHE(SSHþ HSSHHCHCXHC`HCXHCHHC@HC8HC0HC(HC HCPHCpHCxHCpHChƃHǃfǃHǃHǃƃHHǃHǃHǃHǃHǃHǃHǃHǃHǃHHHǃHǃHǃǃǃHǃ H]|"H5]_SH}HZ%H5-YUHQ%H5WH,S%HA H5JSHST%HH;I%HHH kHMHHUHuHuIIFIF0INIVIF@H]HEHtHLk'HQSH jHH;Eu LHP[A^]QSIH]HEHtHk'HMQSLNS DUHAVSHPIHjHHE($QSHþ HQSHHCHCXHC`HCXHCHHC@HC8HC0HC(HC HCPHCpHCxHCpHChƃHǃfǃHǃHǃƃHHǃHǃHǃHǃHǃHǃHǃHǃHǃHHHǃHǃHǃǃǃHǃ H]轀"H5\SH}HJX%H5}VUHKO%H5|WH|P%HH -HQH5SHQ%HH;aF%HHH PkHMHHUHuHuIIFIF0INIVIF@H]HEHtHh'HNSHVjHH;Eu LHP[A^]OSIH]HEHtHPh'HNSLKS fffff.UHAVSHPIHjHHE(dNSHþ HZNSHHCHCXHC`HCXHCHHC@HC8HC0HC(HC HCPHCpHCxHCpHChƃHǃfǃHǃHǃƃHHǃHǃHǃHǃHǃHǃHǃHǃHǃHHHǃHǃHǃǃǃHǃ H]}"H5YSH}HU%H5SUHL%H5zWHM%HH HQH5ӐSHN%HH;C%HHH kHMHHUHuHuIIFIF0INIVIF@H]HEHtHe'HLSHjHH;Eu LHP[A^]ZLSIH]HEHtHe'HKSLIS fffff.UHAVSHPIH+jHHE(KSHþ HKSHHCHCXHC`HCXHCHHC@HC8HC0HC(HC HCPHCpHCxHCpHChƃHǃfǃHǃHǃƃHHǃHǃHǃHǃHǃHǃHǃHǃHǃHHHǃHǃHǃǃǃHǃ H]={"H5-WSH}HR%H5PUHI%H5VwWHJ%HA H5SH#L%HH;@%HHH ׁkHMHHUHuHuIIFIF0INIVIF@H]HEHtHc'HbISHjHH;Eu LHP[A^]ISIH]HEHtHb'HISL]FS DUHAVSHPIH{jHHE(HSHþ HHSHHCHCXHC`HCXHCHHC@HC8HC0HC(HC HCPHCpHCxHCpHChƃHǃfǃHǃHǃƃHHǃHǃHǃHǃHǃHǃHǃHǃHǃHHHǃHǃHǃǃǃHǃ H]r"H5}TSH}HP%H5XNUHG%H5tWHLH%HH -HQH5cSHlI%HH;1>%HHH kHMHHUHuHuIIFIF0INIVIF@H]HEHtHe`'HFSH&jHH;Eu LHP[A^]FSIH]HEHtH `'HfFSLCS fffff.UHAVSHPIHjHHE(4FSHþ H*FSHHCHCXHC`HCXHCHHC@HC8HC0HC(HC HCPHCpHCxHCpHChƃHǃfǃHǃHǃƃHHǃHǃHǃHǃHǃHǃHǃHǃHǃHHHǃHǃHǃǃǃHǃ H] o"H5QSH}HZM%H5KUH[D%H5qWHE%HH -HQH5SHF%HH;q;%HHH `|kHMH5HUHuHuIIFIF0INIVIF@H]HEHtH]'HCSHfjHH;Eu LHP[A^]*DSIH]HEHtH`]'HCSL@S fffff.UHAVSHPIHjHHE(tCSHþ HjCSHHCHCXHC`HCXHCHHC@HC8HC0HC(HC HCPHCpHCxHCpHChƃHǃfǃHǃHǃƃHHǃHǃHǃHǃHǃHǃHǃHǃHǃHHHǃHǃHǃǃǃHǃ H]Mr"H5NSH}HJ%H5HUHA%H5&oWHB%HH -HQH5SHC%HH;8%HHH ykHMH$HUHuHuIIFIF0INIVIF@H]HEHtHZ'H+ASHjHH;Eu LHP[A^]jASIH]HEHtHZ'H@SL&>S fffff.UHAVSHPIH;jHHE(@SHþ H@SHHCHCXHC`HCXHCHHC@HC8HC0HC(HC HCPHCpHCxHCpHChƃHǃfǃHǃHǃƃHHǃHǃHǃHǃHǃHǃHǃHǃHǃHHHǃHǃHǃǃǃHǃ H]Mp"H5=LSH}HG%H5FUH>%H5flWH @%HH -HQH5#SH,A%HH;5%HHH vkHMH%CHUHuHuIIFIF0INIVIF@H]HEHtH%X'Hk>SHjHH;Eu LHP[A^]>SIH]HEHtHW'H&>SLf;S fffff.UHAVSHPIH{jHHE(=SHþ H=SHHCHCXHC`HCXHCHHC@HC8HC0HC(HC HCPHCpHCxHCpHChƃHǃfǃHǃHǃƃHHǃHǃHǃHǃHǃHǃHǃHǃHǃHHHǃHǃHǃǃǃHǃ H]g"H5}ISH}HE%H5XCUH<%H5iWHL=%HH HQH5cSHl>%HH;13%HHH tkHMH%mHUHuHuIIFIF0INIVIF@H]HEHtHeU'H;SH&jHH;Eu LHP[A^];SIH]HEHtH U'Hf;SL8S fffff.UHAVSHPIHjHHE(4;SHþ H*;SHHCHCXHC`HCXHCHHC@HC8HC0HC(HC HCPHCpHCxHCpHChƃHǃfǃHǃHǃƃHHǃHǃHǃHǃHǃHǃHǃHǃHǃHHHǃHǃHǃǃǃHǃ H] d"H5FSH}HZB%H5@UH[9%H5fWH:%HH HQH5}SH;%HH;q0%HHH `qkHMH%kHUHuHuIIFIF0INIVIF@H]HEHtHR'H8SHfjHH;Eu LHP[A^]*9SIH]HEHtH`R'H8SL5S fffff.UHAVSHPIHjHHE(t8SHþ Hj8SHHCHCXHC`HCXHCHHC@HC8HC0HC(HC HCPHCpHCxHCpHChƃHǃfǃHǃHǃƃHHǃHǃHǃHǃHǃHǃHǃHǃHǃHHHǃHǃHǃǃǃHǃ H]Mg"H5CSH}H?%H5=UH6%H5&dWH7%HH HQH5zSH8%HH;-%HHH nkHMH%iHUHuHuIIFIF0INIVIF@H]HEHtHO'H+6SHjHH;Eu LHP[A^]j6SIH]HEHtHO'H5SL&3S fffff.UHAVSHPIH;jHHE(5SHþ H5SHHCHCXHC`HCXHCHHC@HC8HC0HC(HC HCPHCpHCxHCpHChƃHǃfǃHǃHǃƃHHǃHǃHǃHǃHǃHǃHǃHǃHǃHHHǃHǃHǃǃǃHǃ H]Me"H5=ASH}H<%H5;UH3%H5faWH 5%HH HQH5#xSH,6%HH;*%HHH kkHMH%gHUHuHuIIFIF0INIVIF@H]HEHtH%M'Hk3SHjHH;Eu LHP[A^]3SIH]HEHtHL'H&3SLf0S fffff.UHAVSHPIH{jHHE(2SHþ H2SHHCHCXHC`HCXHCHHC@HC8HC0HC(HC HCPHCpHCxHCpHChƃHǃfǃHǃHǃƃHHǃHǃHǃHǃHǃHǃHǃHǃHǃHHHǃHǃHǃǃǃHǃ H]\"H5}>SH}H:%H5X8UH1%H5^WHL2%HH HQH5cuSHl3%HH;1(%HHH ikHMH%eHUHuHuIIFIF0INIVIF@H]HEHtHeJ'H0SH&jHH;Eu LHP[A^]0SIH]HEHtH J'Hf0SL-S fffff.UHAVSHPIHjHHE(40SHþ H*0SHHCHCXHC`HCXHCHHC@HC8HC0HC(HC HCPHCpHCxHCpHChƃHǃfǃHǃHǃƃHHǃHǃHǃHǃHǃHǃHǃHǃHǃHHHǃHǃHǃǃǃHǃ H] Y"H5;SH}HZ7%H55UH[.%H5[WH/%HH HQH5rSH0%HH;q%%HHH `fkHMH%cHUHuHuIIFIF0INIVIF@H]HEHtHG'H-SHfjHH;Eu LHP[A^]*.SIH]HEHtH`G'H-SL*S fffff.UHAVSHPIHjHHE(t-SHþ Hj-SHHCHCXHC`HCXHCHHC@HC8HC0HC(HC HCPHCpHCxHCpHChƃHǃfǃHǃHǃƃHHǃHǃHǃHǃHǃHǃHǃHǃHǃHHHǃHǃHǃǃǃHǃ H]M\"H58SH}H4%H52UH+%H5&YWH,%HH HQH5oSH-%HH;"%HHH ckHMH%aHUHuHuIIFIF0INIVIF@H]HEHtHD'H++SHjHH;Eu LHP[A^]j+SIH]HEHtHD'H*SL&(S fffff.UHAVSHPIH;jHHE(*SHþ H*SHHCHCXHC`HCXHCHHC@HC8HC0HC(HC HCPHCpHCxHCpHChƃHǃfǃHǃHǃƃHHǃHǃHǃHǃHǃHǃHǃHǃHǃHHHǃHǃHǃǃǃHǃ H]MZ"H5=6SH}H1%H50UH(%H5fVWH *%HH HQH5#mSH,+%HH;%HHH `kHMH%_HUHuHuIIFIF0INIVIF@H]HEHtH%B'Hk(SHjHH;Eu LHP[A^](SIH]HEHtHA'H&(SLf%S fffff.UHAVSHPIH{jHHE('SHþ H'SHHCHCXHC`HCXHCHHC@HC8HC0HC(HC HCPHCpHCxHCpHChƃHǃfǃHǃHǃƃHHǃHǃHǃHǃHǃHǃHǃHǃHǃHHHǃHǃHǃǃǃHǃ H]S"H5}3SH}H/%H5X-UH&%H5SWHL'%HH HQH5cjSHl(%HH;1%HHH ^kHMH%]HUHuHuIIFIF0INIVIF@H]HEHtHe?'H%SH&jHH;Eu LHP[A^]%SIH]HEHtH ?'Hf%SL"S fffff.UHAVSHPIHjHHE(4%SHþ H*%SHHCHCXHC`HCXHCHHC@HC8HC0HC(HC HCPHCpHCxHCpHChƃHǃfǃHǃHǃƃHHǃHǃHǃHǃHǃHǃHǃHǃHǃHHHǃHǃHǃǃǃHǃ H]Q"H50SH}HZ,%H5*UH[#%H5PWH$%HH HQH5gSH%%HH;q%HHH `[kHMHU~HUHuHuIIFIF0INIVIF@H]HEHtH<'H"SHfjHH;Eu LHP[A^]*#SIH]HEHtH`<'H"SLS fffff.UHAVSHPIHjHHE(t"SHþ Hj"SHHCHCXHC`HCXHCHHC@HC8HC0HC(HC HCPHCpHCxHCpHChƃHǃfǃHǃHǃƃHHǃHǃHǃHǃHǃHǃHǃHǃHǃHHHǃHǃHǃǃǃHǃ H] L"H5-SH}H)%H5'UH %H5&NWH!%HA H5dSH"%HH;%HHH XkHMH<HUHuHuIIFIF0INIVIF@H]HEHtH9'H2 SHjHH;Eu LHP[A^]q SIH]HEHtH9'HSL-S DUHAVSHPIHKjHHE(SHþ HSHHCHCXHC`HCXHCHHC@HC8HC0HC(HC HCPHCpHCxHCpHChƃHǃfǃHǃHǃƃHHǃHǃHǃHǃHǃHǃHǃHǃHǃHHHǃHǃHǃǃǃHǃ H]H"H5M+SH}H&%H5(%UH%H5vKWH%HA H5:bSHC %HH;%HHH UkHMHLHUHuHuIIFIF0INIVIF@H]HEHtH<7'HSHjHH;Eu LHP[A^]SIH]HEHtH6'H=SL}S DUHAVSHPIHjHHE(SHþ H -SHHCHCXHC`HCXHCHHC@HC8HC0HC(HC HCPHCpHCxHCpHChƃHǃfǃHǃHǃƃHHǃHǃHǃHǃHǃHǃHǃHǃHǃHHHǃHǃHǃǃǃHǃ H]K"H5(SH}H:$%H5x"UH;%H5HWHl%HA H5_SH%HH;X%HHH GSkHMH\HUHuHuIIFIF0INIVIF@H]HEHtH4'HSHMjHH;Eu LHP[A^]SIH]HEHtHG4'HSLS DUHAVSHPIHjHHE(dSHþ HZSHHCHCXHC`HCXHCHHC@HC8HC0HC(HC HCPHCpHCxHCpHChƃHǃfǃHǃHǃƃHHǃHǃHǃHǃHǃHǃHǃHǃHǃHHHǃHǃHǃǃǃHǃ H]I"H5%SH}H!%H5UH%H5FWH%HA H5\SH%HH;%HHH PkHMHlHUHuHuIIFIF0INIVIF@H]HEHtH1'H"SHjHH;Eu LHP[A^]aSIH]HEHtH1'HSLS DUHAVSHPIH;jHHE(SHþ HSHHCHCXHC`HCXHCHHC@HC8HC0HC(HC HCPHCpHCxHCpHChƃHǃfǃHǃHǃƃHHǃHǃHǃHǃHǃHǃHǃHǃHǃHHHǃHǃHǃǃǃHǃ H]C"H5=#SH}H%H5UH%H5fCWH %HA H5*ZSH3%HH; %HHH MkHMH|HUHuHuIIFIF0INIVIF@H]HEHtH,/'HrSHjHH;Eu LHP[A^]SIH]HEHtH.'H-SLmS DUHAVSHPIHjHHE(SHþ HSHHCHCXHC`HCXHCHHC@HC8HC0HC(HC HCPHCpHCxHCpHChƃHǃfǃHǃHǃƃHHǃHǃHǃHǃHǃHǃHǃHǃHǃHHHǃHǃHǃǃǃHǃ H]A"H5 SH}H*%H5hUH+%H5@WH\%HA H5zWSH%HH;H -%HHH 7KkHMHHUHuHuIIFIF0INIVIF@H]HEHtH|,'HSH=jHH;Eu LHP[A^]SIH]HEHtH7,'H}SLS DUHAVSHPIHۉjHHE(TSHþ HJSHHCHCXHC`HCXHCHHC@HC8HC0HC(HC HCPHCpHCxHCpHChƃHǃfǃHǃHǃƃHHǃHǃHǃHǃHǃHǃHǃHǃHǃHHHǃHǃHǃǃǃHǃ H];"H5SH}Hz%H5UH{%H5>WH%HH -HQH5TSH%HH;%HHH HkHMHHUHuHuIIFIF0INIVIF@H]HEHtH)'H SHjHH;Eu LHP[A^]JSIH]HEHtH)'HSL S fffff.UHAVSHPIHjHHE(SHþ HSHHCHCXHC`HCXHCHHC@HC8HC0HC(HC HCPHCpHCxHCpHChƃHǃfǃHǃHǃƃHHǃHǃHǃHǃHǃHǃHǃHǃHǃHHHǃHǃHǃǃǃHǃ H]m8"H5SH}H%H5UH %H5F;WH%HH -HQH5RSH %HH;%HHH EkHMHHUHuHuIIFIF0INIVIF@H]HEHtH''HK SHƄjHH;Eu LHP[A^] SIH]HEHtH&'H SLF -S fffff.UHAVSHPIH[jHHE( SHþ H SHHCHCXHC`HCXHCHHC@HC8HC0HC(HC HCPHCpHCxHCpHChƃHǃfǃHǃHǃƃHHǃHǃHǃHǃHǃHǃHǃHǃHǃHHHǃHǃHǃǃǃHǃ H];"H5]SH}H%H5BUH -%H58WH, %HH -HQH5COSHL %HH;%HHH CkHMHHUHuHuIIFIF0INIVIF@H]HEHtHE$'H -SHjHH;Eu LHP[A^] -SIH]HEHtH$'HF -SLS fffff.UHAVSHPIHjHHE( -SHþ H - -SHHCHCXHC`HCXHCHHC@HC8HC0HC(HC HCPHCpHCxHCpHChƃHǃfǃHǃHǃƃHHǃHǃHǃHǃHǃHǃHǃHǃHǃHHHǃHǃHǃǃǃHǃ H]3"H5SH}H:%H5UH;%H55WHl %HH HQH5LSH -%HH;Q$HHH @@kHMHHUHuHuIIFIF0INIVIF@H]HEHtH!'HSHFjHH;Eu LHP[A^] -SIH]HEHtH@!'HSLS fffff.UHAVSHPIH~jHHE(TSHþ HJSHHCHCXHC`HCXHCHHC@HC8HC0HC(HC HCPHCpHCxHCpHChƃHǃfǃHǃHǃƃHHǃHǃHǃHǃHǃHǃHǃHǃHǃHHHǃHǃHǃǃǃHǃ H]-0"H5SH}Hz%H5 UH{%H53WH%HH HQH5ISH%HH;$HHH =kHMHHUHuHuIIFIF0INIVIF@H]HEHtH'H SH|jHH;Eu LHP[A^]JSIH]HEHtH'HSLS fffff.UHAVSHPIH|jHHE(SHþ HSHHCHCXHC`HCXHCHHC@HC8HC0HC(HC HCPHCpHCxHCpHChƃHǃfǃHǃHǃƃHHǃHǃHǃHǃHǃHǃHǃHǃHǃHHHǃHǃHǃǃǃHǃ H]m3"H5SH}H %H5 -UH%H5F0WH%HH HQH5GSH %HH;$HHH :kHMHHUHuHuIIFIF0INIVIF@H]HEHtH'HKSHyjHH;Eu LHP[A^]SIH]HEHtH'HSLFR fffff.UHAVSHPIH[yjHHE(SHþ HSHHCHCXHC`HCXHCHHC@HC8HC0HC(HC HCPHCpHCxHCpHChƃHǃfǃHǃHǃƃHHǃHǃHǃHǃHǃHǃHǃHǃHǃHHHǃHǃHǃǃǃHǃ H]m+"H5] SH}H%H5BUH$H5-WH,%HA H5JDSHS%HH;$HHH 8kHMHHUHuHuIIFIF0INIVIF@H]HEHtHL'HRH wjHH;Eu LHP[A^]RIH]HEHtH'HMRLR DUHAVSHPIHvjHHE($RHþ HRHHCHCXHC`HCXHCHHC@HC8HC0HC(HC HCPHCpHCxHCpHChƃHǃfǃHǃHǃƃHHǃHǃHǃHǃHǃHǃHǃHǃHǃHHHǃHǃHǃǃǃHǃ H]'"H5 -SH}HJ%H5UHK$H5*WH|$HA H5ASH$HH;h$HHH W5kHMH HUHuHuIIFIF0INIVIF@H]HEHtH'HRH]tjHH;Eu LHP[A^]!RIH]HEHtHW'HRLR DUHAVSHPIHsjHHE(tRHþ HjRHHCHCXHC`HCXHCHHC@HC8HC0HC(HC HCPHCpHCxHCpHChƃHǃfǃHǃHǃƃHHǃHǃHǃHǃHǃHǃHǃHǃHǃHHHǃHǃHǃǃǃHǃ H]M+"H5SH}H%H5UH$H5&(WH$HA H5>SH$HH;$HHH 2kHMHHUHuHuIIFIF0INIVIF@H]HEHtH'H2RHqjHH;Eu LHP[A^]qRIH]HEHtH'HRL-R DUHAVSHPIHKqjHHE(RHþ HRHHCHCXHC`HCXHCHHC@HC8HC0HC(HC HCPHCpHCxHCpHChƃHǃfǃHǃHǃƃHHǃHǃHǃHǃHǃHǃHǃHǃHǃHHHǃHǃHǃǃǃHǃ H]]#"H5MSH}H%H5=TH$H5v%WH$HH -HQH53<SH<$HH;$HHH /kHMH%HUHuHuIIFIF0INIVIF@H]HEHtH5'H{RHnjHH;Eu LHP[A^]RIH]HEHtH'H6RLvR fffff.UHAVSHPIHnjHHE(RHþ HRHHCHCXHC`HCXHCHHC@HC8HC0HC(HC HCPHCpHCxHCpHChƃHǃfǃHǃHǃƃHHǃHǃHǃHǃHǃHǃHǃHǃHǃHHHǃHǃHǃǃǃHǃ H]"H5SH}H*$H5}TH+$H5"WH\$HH -HQH5s9SH|$HH;A$HHH 0-kHMH%HUHuHuIIFIF0INIVIF@H]HEHtHu'HRH6ljHH;Eu LHP[A^]RIH]HEHtH0'HvRLR fffff.UHAVSHPIHkjHHE(DRHþ H:RHHCHCXHC`HCXHCHHC@HC8HC0HC(HC HCPHCpHCxHCpHChƃHǃfǃHǃHǃƃHHǃHǃHǃHǃHǃHǃHǃHǃHǃHHHǃHǃHǃǃǃHǃ H]#"H5RH}Hj$H5THk$H5WH$HH -HQH56SH$HH;$HHH p*kHMH%HUHuHuIIFIF0INIVIF@H]HEHtH 'HRHvijHH;Eu LHP[A^]:RIH]HEHtHp 'HRLR fffff.UHAVSHPIH ijHHE(RHþ HzRHHCHCXHC`HCXHCHHC@HC8HC0HC(HC HCPHCpHCxHCpHChƃHǃfǃHǃHǃƃHHǃHǃHǃHǃHǃHǃHǃHǃHǃHHHǃHǃHǃǃǃHǃ H]!"H5 RH}H$H5TH$H56WH$HH -HQH53SH$HH;$HHH 'kHMH%HUHuHuIIFIF0INIVIF@H]HEHtH'H;RHfjHH;Eu LHP[A^]zRIH]HEHtH'HRL6R fffff.UHAVSHPIHKfjHHE(RHþ HRHHCHCXHC`HCXHCHHC@HC8HC0HC(HC HCPHCpHCxHCpHChƃHǃfǃHǃHǃƃHHǃHǃHǃHǃHǃHǃHǃHǃHǃHHHǃHǃHǃǃǃHǃ H]]"H5MRH}H$H5=TH$H5vWH$HH HQH531SH<$HH;$HHH $kHMH%HUHuHuIIFIF0INIVIF@H]HEHtH5'H{RHcjHH;Eu LHP[A^]RIH]HEHtH'H6RLvR fffff.UHAVSHPIHcjHHE(RHþ HRHHCHCXHC`HCXHCHHC@HC8HC0HC(HC HCPHCpHCxHCpHChƃHǃfǃHǃHǃƃHHǃHǃHǃHǃHǃHǃHǃHǃHǃHHHǃHǃHǃǃǃHǃ H]"H5RH}H*$H5}TH+$H5WH\$HH HQH5s.SH|$HH;A$HHH 0"kHMH%HUHuHuIIFIF0INIVIF@H]HEHtHu'HRH6ajHH;Eu LHP[A^]RIH]HEHtH0'HvRLR fffff.UHAVSHPIH`jHHE(DRHþ H:RHHCHCXHC`HCXHCHHC@HC8HC0HC(HC HCPHCpHCxHCpHChƃHǃfǃHǃHǃƃHHǃHǃHǃHǃHǃHǃHǃHǃHǃHHHǃHǃHǃǃǃHǃ H]"H5RH}Hj$H5THk$H5WH$HH HQH5+SH$HH;$HHH pkHMH%HUHuHuIIFIF0INIVIF@H]HEHtH'HRHv^jHH;Eu LHP[A^]:RIH]HEHtHp'HRLR fffff.UHAVSHPIH ^jHHE(RHþ HzRHHCHCXHC`HCXHCHHC@HC8HC0HC(HC HCPHCpHCxHCpHChƃHǃfǃHǃHǃƃHHǃHǃHǃHǃHǃHǃHǃHǃHǃHHHǃHǃHǃǃǃHǃ H]"H5 RH}H$H5TH$H56WH$HH HQH5(SH$HH;$HHH kHMH%HUHuHuIIFIF0INIVIF@H]HEHtH&H;RH[jHH;Eu LHP[A^]zRIH]HEHtH&HRL6R fffff.UHAVSHPIHK[jHHE(RHþ HRHHCHCXHC`HCXHCHHC@HC8HC0HC(HC HCPHCpHCxHCpHChƃHǃfǃHǃHǃƃHHǃHǃHǃHǃHǃHǃHǃHǃHǃHHHǃHǃHǃǃǃHǃ H]] "H5MRH}H$H5=TH$H5vWH$HA H5:&SHC$HH;$HHH kHMH,HUHuHuIIFIF0INIVIF@H]HEHtH<&HRHXjHH;Eu LHP[A^]RIH]HEHtH&H=RL}R DUHAVSHPIHXjHHE(RHþ H -RHHCHCXHC`HCXHCHHC@HC8HC0HC(HC HCPHCpHCxHCpHChƃHǃfǃHǃHǃƃHHǃHǃHǃHǃHǃHǃHǃHǃHǃHHHǃHǃHǃǃǃHǃ H] "H5RH}H:$H5TH;$H5 WHl$HA H5#SH$HH;X$HHH GkHMH<HUHuHuIIFIF0INIVIF@H]HEHtH&HRHMVjHH;Eu LHP[A^]RIH]HEHtHG&HRLR DUHAVSHPIHUjHHE(dRHþ HZRHHCHCXHC`HCXHCHHC@HC8HC0HC(HC HCPHCpHCxHCpHChƃHǃfǃHǃHǃƃHHǃHǃHǃHǃHǃHǃHǃHǃHǃHHHǃHǃHǃǃǃHǃ H]= "H5RH}H$H5TH$H5 -WH$HA H5 SH$HH;$HHH kHMHLHUHuHuIIFIF0INIVIF@H]HEHtH&H"RHSjHH;Eu LHP[A^]aRIH]HEHtH&HRLR DUHAVSHPIH;SjHHE(RHþ HRHHCHCXHC`HCXHCHHC@HC8HC0HC(HC HCPHCpHCxHCpHChƃHǃfǃHǃHǃƃHHǃHǃHǃHǃHǃHǃHǃHǃHǃHHHǃHǃHǃǃǃHǃ H]M "H5=RH}H$H5-TH$H5fWH $HA H5*SH3$HH;$HHH kHMH\HUHuHuIIFIF0INIVIF@H]HEHtH,&HrRHPjHH;Eu LHP[A^]RIH]HEHtH&H-RLmR DUHAVSHPIHPjHHE(RHþ HRHHCHCXHC`HCXHCHHC@HC8HC0HC(HC HCPHCpHCxHCpHChƃHǃfǃHǃHǃƃHHǃHǃHǃHǃHǃHǃHǃHǃHǃHHHǃHǃHǃǃǃHǃ H]"H5RH}H*$H5TH+$H5WH\$HH -HQH5sSH|$HH;A$HHH 0kHMHeHUHuHuIIFIF0INIVIF@H]HEHtHu&HRH6NjHH;Eu LHP[A^]RIH]HEHtH0&HvRLR fffff.UHAVSHPIHMjHHE(DRHþ H:RHHCHCXHC`HCXHCHHC@HC8HC0HC(HC HCPHCpHCxHCpHChƃHǃfǃHǃHǃƃHHǃHǃHǃHǃHǃHǃHǃHǃHǃHHHǃHǃHǃǃǃHǃ H]!H5RH}Hj$H5THk$H5WH$HH -HQH5SH$HH;$HHH p kHMHեHUHuHuIIFIF0INIVIF@H]HEHtH&HRHvKjHH;Eu LHP[A^]:RIH]HEHtHp&HRLR fffff.UHAVSHPIH KjHHE(RHþ HzRHHCHCXHC`HCXHCHHC@HC8HC0HC(HC HCPHCpHCxHCpHChƃHǃfǃHǃHǃƃHHǃHǃHǃHǃHǃHǃHǃHǃHǃHHHǃHǃHǃǃǃHǃ H]"H5 RH}H$H5TH$H56VH$HH -HQH5SH$HH;$HHH kHMHHUHuHuIIFIF0INIVIF@H]HEHtH&H;RHHjHH;Eu LHP[A^]zRIH]HEHtH&HRL6R fffff.UHAVSHPIHKHjHHE(RHþ HRHHCHCXHC`HCXHCHHC@HC8HC0HC(HC HCPHCpHCxHCpHChƃHǃfǃHǃHǃƃHHǃHǃHǃHǃHǃHǃHǃHǃHǃHHHǃHǃHǃǃǃHǃ H]]!H5MRH}H$H5GTH$H5vVH$HH HQH53SH<$HH;$HHH kHMHHUHuHuIIFIF0INIVIF@H]HEHtH5&H{RHEjHH;Eu LHP[A^]RIH]HEHtH&H6RLvR fffff.UHAVSHPIHEjHHE(RHþ HRHHCHCXHC`HCXHCHHC@HC8HC0HC(HC HCPHCpHCxHCpHChƃHǃfǃHǃHǃƃHHǃHǃHǃHǃHǃHǃHǃHǃHǃHHHǃHǃHǃǃǃHǃ H]!H5RH}H*$H5TH+$H5VH\$HH HQH5sSH|$HH;A$HHH 0kHMHHUHuHuIIFIF0INIVIF@H]HEHtHu&HRH6CjHH;Eu LHP[A^]RIH]HEHtH0&HvRLR fffff.UHAVSHPIHBjHHE(DRHþ H:RHHCHCXHC`HCXHCHHC@HC8HC0HC(HC HCPHCpHCxHCpHChƃHǃfǃHǃHǃƃHHǃHǃHǃHǃHǃHǃHǃHǃHǃHHHǃHǃHǃǃǃHǃ H]!H5RH}Hj$H5THk$H5VH$HH HQH5 SH$HH;$HHH pkHMHHUHuHuIIFIF0INIVIF@H]HEHtH&HRHv@jHH;Eu LHP[A^]:RIH]HEHtHp&HRLR fffff.UHAVSHPIH @jHHE(RHþ HzRHHCHCXHC`HCXHCHHC@HC8HC0HC(HC HCPHCpHCxHCpHChƃHǃfǃHǃHǃƃHHǃHǃHǃHǃHǃHǃHǃHǃHǃHHHǃHǃHǃǃǃHǃ H]!H5 RH}H$H5TH$H56VH$HA H5 -SH$HH;Ƚ$HHH jHMHHUHuHuIIFIF0INIVIF@H]HEHtH&HBRH=jHH;Eu LHP[A^]RIH]HEHtH&HRL=R DUHAVSHPIH[=jHHE(RHþ HRHHCHCXHC`HCXHCHHC@HC8HC0HC(HC HCPHCpHCxHCpHChƃHǃfǃHǃHǃƃHHǃHǃHǃHǃHǃHǃHǃHǃHǃHHHǃHǃHǃǃǃHǃ H]!H5]RH}H$H5WTH$H5VH,$HA H5JSHS$HH;$HHH jHMHHUHuHuIIFIF0INIVIF@H]HEHtHL&HRH ;jHH;Eu LHP[A^]RIH]HEHtH&HMRLR DUHAVSHPIH:jHHE($RHþ HRHHCHCXHC`HCXHCHHC@HC8HC0HC(HC HCPHCpHCxHCpHChƃHǃfǃHǃHǃƃHHǃHǃHǃHǃHǃHǃHǃHǃHǃHHHǃHǃHǃǃǃHǃ H]!H5RH}HJ$H5THK$H5VH|$HA H5SH$HH;h$HHH WjHMHHUHuHuIIFIF0INIVIF@H]HEHtH&HRH]8jHH;Eu LHP[A^]!RIH]HEHtHW&HRLݽR DUHAVSHPIH7jHHE(tRHþ HjRHHCHCXHC`HCXHCHHC@HC8HC0HC(HC HCPHCpHCxHCpHChƃHǃfǃHǃHǃƃHHǃHǃHǃHǃHǃHǃHǃHǃHǃHHHǃHǃHǃǃǃHǃ H] !H5RH}H$H5TH蛾$H5&VH̿$HH -HQH5SH$HH;豵$HHH jHMHŴHUHuHuIIFIF0INIVIF@H]HEHtH&H+RH5jHH;Eu LHP[A^]jRIH]HEHtH&HRL&R fffff.UHAVSHPIH;5jHHE(贽RHþ H誽RHHCHCXHC`HCXHCHHC@HC8HC0HC(HC HCPHCpHCxHCpHChƃHǃfǃHǃHǃƃHHǃHǃHǃHǃHǃHǃHǃHǃHǃHHHǃHǃHǃǃǃHǃ H]!H5=RH}H$H5GTHۻ$H5fVH $HH -HQH5#SH,$HH;$HHH jHMHEHUHuHuIIFIF0INIVIF@H]HEHtH%&HkRH2jHH;Eu LHP[A^]誻RIH]HEHtH&H&RLfR fffff.UHAVSHPIH{2jHHE(RHþ HRHHCHCXHC`HCXHCHHC@HC8HC0HC(HC HCPHCpHCxHCpHChƃHǃfǃHǃHǃƃHHǃHǃHǃHǃHǃHǃHǃHǃHǃHHHǃHǃHǃǃǃHǃ H]!H5}RH}H$H5TH$H5VHL$HH HQH5cRHl$HH;1$HHH jHMHHUHuHuIIFIF0INIVIF@H]HEHtHe&H諸RH&0jHH;Eu LHP[A^]RIH]HEHtH &HfRL覵R fffff.UHAVSHPIH/jHHE(4RHþ H*RHHCHCXHC`HCXHCHHC@HC8HC0HC(HC HCPHCpHCxHCpHChƃHǃfǃHǃHǃƃHHǃHǃHǃHǃHǃHǃHǃHǃHǃHHHǃHǃHǃǃǃHǃ H] !H5RH}HZ$H5ǽTH[$H5VH茷$HH HQH5RH謸$HH;q$HHH `jHMHHUHuHuIIFIF0INIVIF@H]HEHtH&HRHf-jHH;Eu LHP[A^]*RIH]HEHtH`&H覵RLR fffff.UHAVSHPIH,jHHE(tRHþ HjRHHCHCXHC`HCXHCHHC@HC8HC0HC(HC HCPHCpHCxHCpHChƃHǃfǃHǃHǃƃHHǃHǃHǃHǃHǃHǃHǃHǃHǃHHHǃHǃHǃǃǃHǃ H] !H5RH}H蚼$H5TH蛳$H5&VH̴$HH HQH5RH$HH;豪$HHH jHMHHUHuHuIIFIF0INIVIF@H]HEHtH&H+RH*jHH;Eu LHP[A^]jRIH]HEHtH&HRL&R fffff.UHAVSHPIH;*jHHE(贲RHþ H課RHHCHCXHC`HCXHCHHC@HC8HC0HC(HC HCPHCpHCxHCpHChƃHǃfǃHǃHǃƃHHǃHǃHǃHǃHǃHǃHǃHǃHǃHHHǃHǃHǃǃǃHǃ H]M!H5=RH}Hڹ$H5GTH۰$H5fVH $HA H5*RH3$HH;$HHH jHMH,HUHuHuIIFIF0INIVIF@H]HEHtH,&HrRH'jHH;Eu LHP[A^]豰RIH]HEHtH&H-RLmR DUHAVSHPIH'jHHE(RHþ HRHHCHCXHC`HCXHCHHC@HC8HC0HC(HC HCPHCpHCxHCpHChƃHǃfǃHǃHǃƃHHǃHǃHǃHǃHǃHǃHǃHǃHǃHHHǃHǃHǃǃǃHǃ H]!H5RH}H*$H5TH+$H5VH\$HA H5zRH胰$HH;H$HHH 7jHMH<HUHuHuIIFIF0INIVIF@H]HEHtH|&H­RH=%jHH;Eu LHP[A^]RIH]HEHtH7&H}RL轪R DUHAVSHPIH$jHHE(TRHþ HJRHHCHCXHC`HCXHCHHC@HC8HC0HC(HC HCPHCpHCxHCpHChƃHǃfǃHǃHǃƃHHǃHǃHǃHǃHǃHǃHǃHǃHǃHHHǃHǃHǃǃǃHǃ H]!H5ݸRH}Hz$H5TH{$H5VH謬$HA H5RHӭ$HH;蘢$HHH jHMHLHUHuHuIIFIF0INIVIF@H]HEHtH&HRH"jHH;Eu LHP[A^]QRIH]HEHtH&HͪRL R DUHAVSHPIH+"jHHE(褪RHþ H蚪RHHCHCXHC`HCXHCHHC@HC8HC0HC(HC HCPHCpHCxHCpHChƃHǃfǃHǃHǃƃHHǃHǃHǃHǃHǃHǃHǃHǃHǃHHHǃHǃHǃǃǃHǃ H]=!H5-RH}Hʱ$H5>TH˨$H5VVH$HH -HQH5RH$HH;$HHH jHMHUHUHuHuIIFIF0INIVIF@H]HEHtH&H[RHjHH;Eu LHP[A^]蚨RIH]HEHtH&HRLVR fffff.UHAVSHPIHkjHHE(RHþ HڧRHHCHCXHC`HCXHCHHC@HC8HC0HC(HC HCPHCpHCxHCpHChƃHǃfǃHǃHǃƃHHǃHǃHǃHǃHǃHǃHǃHǃHǃHHHǃHǃHǃǃǃHǃ H]!H5mRH}H -$H5~TH $H5VH<$HH -HQH5SRH\$HH;!$HHH jHMHU HUHuHuIIFIF0INIVIF@H]HEHtHU&H蛥RHjHH;Eu LHP[A^]ڥRIH]HEHtH&HVRL薢R fffff.UHAVSHPIHjHHE($RHþ HRHHCHCXHC`HCXHCHHC@HC8HC0HC(HC HCPHCpHCxHCpHChƃHǃfǃHǃHǃƃHHǃHǃHǃHǃHǃHǃHǃHǃHǃHHHǃHǃHǃǃǃHǃ H]!H5RH}HJ$H5THK$H5VH|$HH HQH5RH蜥$HH;a$HHH PjHMH#HUHuHuIIFIF0INIVIF@H]HEHtH蕼&HۢRHVjHH;Eu LHP[A^]RIH]HEHtHP&H薢RL֟R fffff.UHAVSHPIHjHHE(dRHþ HZRHHCHCXHC`HCXHCHHC@HC8HC0HC(HC HCPHCpHCxHCpHChƃHǃfǃHǃHǃƃHHǃHǃHǃHǃHǃHǃHǃHǃHǃHHHǃHǃHǃǃǃHǃ H]=!H5RH}H芩$H5TH苠$H5VH輡$HH HQH5RHܢ$HH;街$HHH jHMH!HUHuHuIIFIF0INIVIF@H]HEHtHչ&HRHjHH;Eu LHP[A^]ZRIH]HEHtH萹&H֟RLR fffff.UHAVSHPIH+jHHE(褟RHþ H蚟RHHCHCXHC`HCXHCHHC@HC8HC0HC(HC HCPHCpHCxHCpHChƃHǃfǃHǃHǃƃHHǃHǃHǃHǃHǃHǃHǃHǃHǃHHHǃHǃHǃǃǃHǃ H]=!H5-RH}Hʦ$H5>TH˝$H5VVH$HH HQH5RH$HH;$HHH jHMHHUHuHuIIFIF0INIVIF@H]HEHtH&H[RHjHH;Eu LHP[A^]蚝RIH]HEHtHж&HRLVR fffff.UHAVSHPIHkjHHE(RHþ HڜRHHCHCXHC`HCXHCHHC@HC8HC0HC(HC HCPHCpHCxHCpHChƃHǃfǃHǃHǃƃHHǃHǃHǃHǃHǃHǃHǃHǃHǃHHHǃHǃHǃǃǃHǃ H]}!H5mRH}H -$H5~TH $H5VH<$HA H5ZRHc$HH;($HHH jHMH<6HUHuHuIIFIF0INIVIF@H]HEHtH\&H袚RHjHH;Eu LHP[A^]RIH]HEHtH&H]RL蝗R DUHAVSHPIHjHHE(4RHþ H*RHHCHCXHC`HCXHCHHC@HC8HC0HC(HC HCPHCpHCxHCpHChƃHǃfǃHǃHǃƃHHǃHǃHǃHǃHǃHǃHǃHǃHǃHHHǃHǃHǃǃǃHǃ H] !H5RH}HZ$H5ΟTH[$H5VH茙$HA H5RH賚$HH;x$HHH gjHMHL4HUHuHuIIFIF0INIVIF@H]HEHtH謱&HRHmjHH;Eu LHP[A^]1RIH]HEHtHg&H譗RLR DUHAVSHPIH jHHE(脗RHþ HzRHHCHCXHC`HCXHCHHC@HC8HC0HC(HC HCPHCpHCxHCpHChƃHǃfǃHǃHǃƃHHǃHǃHǃHǃHǃHǃHǃHǃHǃHHHǃHǃHǃǃǃHǃ H]!H5 RH}H語$H5TH諕$H56VHܖ$HA H5RH$HH;Ȍ$HHH jHMH\2HUHuHuIIFIF0INIVIF@H]HEHtH&HBRH jHH;Eu LHP[A^]聕RIH]HEHtH跮&HRL=R DUHAWAVAUATSHHU jHHEHH~@HpHG8H;G0(H' jHH;EuHĈ[A\A]A^A_]R蓔RIHh>B6H5TH TH}LhHPH<%AHTHuLHcE1H5Y-jHLVRRIHhA6H5'TH qTH}Lh9HPH$AHTHuLHE1H5,jHLԓR}蒓RIHh=A6H5TH TH}LhHPH;$AH7THuLHbE1H5X,jHLUR IALhMIIALhMIIALhM:oIlIPt H`脒RLmMt6HEL9t!HX@t Hx_RHI9uH}LLmEREuEu LhMu-H}REtH}RLhMHpL9HX@t HxݑRHI9uIPt H`踑RLmMt6HEL9t!HX@t Hx蓑RHI9uH}LLmyREuEu LhMu-'H}SREtH}DRLhMHpL9HX@t HxRHI9uIPt H`RLmMt6HEL9t!HX@t HxǐRHI9uH}LLm譐REuEuLhMu&^H}芐REtH}{RLhMt:HpL9tEHX@t HxPRHI9uHhLp5REtLXRLhR Lff.UHUHAWAVAUATSHRIH}=6H5TH ~THXLE#W)EHEE&HoverloadHEHmust be HEEed.AHtXHXHMLE1H5(jH?L蓏R IALeMIIEt H}RLeMt6HEL9t!HX@t HxRHI9uH}LLeҎRxuXuLeMu)_H}謎RXtHh藎RLeMt8HEL9tFHX@t HxkRHI9uH}LeVREtLyRL艋R Lfff.UH'UHUHAWAVAUATSHH`IHkjHHEHW)EHEHHHLoI)tMMMII9L觍RILuLuKHEM~,LHLRLLHMLeE11L`LL`MLeHL)HHHA|1HHHH HfDH I ILHMMWM9t)IrL)HHPHsLHuLibHzH)ǸLfHcHHcNHHcNHHcNHH HuHtHff.HcHHHuM)MIIHLHIcH4IqHIIIQPIc HH<AA|YHI< -H HAITI HH9u&HcH4H`HqHIcLHH<AHH`H~0E)LXt*HN0HV8H)HHH)vMMMLINHEHF0HV8H)HHHHHHF8MsHH`HA8L@W)EHEEL8McJ<RHH]LPN4LuIIcHI)HLՊRLuH`Hx0LP8I)I)IH8ALcH@L(LEIHHHE11ff.IJ JDOdK HPHtffffff.IcH+4|8HtItHcI4H4H)HtHHtMdK HHIM9Lr,11fffff.H4JDKDI4HL9rH謉RLXL@W)EHEHDžpI $HuHH)HHEHP1LuHpL`IIWH9t@H98t HH9uH9u.HEH;EtH8HHE@LH)I $HuHpHHpHH)HH9|LeLuM9tUHHHIvL)HHJHs8LHuqHEHPE1E1L`unHqH)ֻLDHc:HHczHHczHHczHH HuHtHff.Hc2HHHuHM)MIW)pHEMtCHI9LԇRHpN,LmHLRLxL`KcDHHH H IMpHHHIMuXLLA'HPLL]IALUIIExHpLxLH)HHHXw6HDžhIE`I;EhaHHIE`HdkHDžhM"1E1ffffff.IE`I;EhtHHIE`8fLHhq'HpLxHPLL]LULH)HDLL)HIQHhI HHh|HHHHHHH HHtIcTH+4|BHtILHcI H H)hHDITHhI HhHHIM9HXHu'HhLHpHt Hx苅RH}HtHPH8sRH}HtH;bRHiHH;Eu:HĨ[A\A]A^A_]þH)HUHXH}HusRH}pRH}eR HpWR HH}HHMH}HHHpHt Hx袄RLXH}HtoHH}Ht H}xRLXH}HtNHH}Ht=H}NRH莁R HHpHLXuH}Hu6H}Hu?HZR HxRH}Ht HH}HtH}RH}HtI<$҃RHR f.UHAWAVAUATSHH%iHHEHu'HiHH;EuHĈ[A\A]A^A_]σR}RIHh(16H5TH kTH}LhW)PHDž`0 RH`(xf)PHld be 1.HH'Hze shoulHH Hutput siHHH axes, oHHHn on allHHHReductioH@/AHTHuHPLE1H5jHlLR IALeMuFzIALhMIIPt H`$RLeMt6HEL9t!HX@t HxRHI9uH}LLeREuEuLhMu&^H}REtH}賁RLhMt:HpL9tEHX@t Hx舁RHI9uHhLpmREtL萁RL~R LUHAWAVAUATSHHiHHEHt9HG H+GHHiHH;EuHĈ[A\A]A^A_]NRRIHh.6H5TH *TH}Lh$W)PƅP$HDž`Hut is nuHYHAxes inpHQfDžallƅcAHTHuHPLE1H5jH(L|R7RIHh-6H5MTH eTH}Lh_W)PHDž`0RH`(rc)PH tensor.HHH vector HHHust be aHHHtensor mHHHAn axes H@'AHTHuHPLE1H5jH4LR IALeMulIALhMIIALhMnIIPt H`~RLeMt6HEL9t!HX@t Hx~RHI9uH}LLe~REuEu LhMu-'H}a~REtH}R~RLhMHpL9HX@t Hx~RHI9uIPt H`}RLeMt6HEL9t!HX@t Hx}RHI9uH}LLe}REuEuLhMu&^H}}REtH}}RLhMt:HpL9tEHX@t Hx^}RHI9uHhLpC}REtLf}RLvzR LfUHAWAVAUATSPAIIIV%HH+HL&HH}HCL(H~lI4$J LH[I $1I;L$uREtM1L迿&HHS1L[%HIHsIH(LLH}R1H[A\A]A^A_]ffff.UHAWAVAUATSHxLMLAHpHxIH}iHHE1&IH]W)EHEI} I+}tNHHHH=*{RILuLuIHEIuI] H)H~LH }RILuW)EHEEH]LHD<AtJH}Ht H}A{RH}Ht H}/{RHiHH;EDHx[A\A]A^A_]LEHEH;EHDxHEE1HpAD4$IH}HHULH]M E1^!V1LL>\%IċtZtzH}LZ4HEHL0Iv5OI9IOLHuLU8AH}L(IOLHuLU(AH}L9.HEHL0Iv5HI9~AHEHL0HXIu5I9LLHI9~IOLHuLU0AVE1H}HOSyRH}vR HH}HuHOHH}HtLH}ayRHvR HH}Hu"HHvR HH}Ht H}'yRH}HuH^vR fDUHSPHH{Ht H{xRHnjHH{HCHHt[]xR[]fff.UHSPHH{Ht H{xRH>njHH{HCHtxRHH[]uxRUHSPHH{Ht H{SxRHmjHH{HCHHt[]-xR[]fff.UHSPHH{Ht H{xRHmjHH{HCHtwRHH[]wRUHSPHH{Ht H{wRHNmjHH{HCHHt[]wR[]fff.UHSPHH{Ht H{cwRHljHH{HCHtCwRHH[]5wRUHSPHH{Ht H{wRHljHH{HCHHt[]vR[]fff.UHSPHH{Ht H{vRH^ljHH{HCHtvRHH[]vRUHAWAVSHIHiHHE0rvRHL=kjL;H{LO%HHEHEHULH&kHHiHH;EuHH[A^A_]avRL;IH{HCHt -uRIHuRLsR UHSPHH{Ht H{uRHNkjHH{HCHHt[]uR[]fff.UHSPHH{Ht H{cuRHjjHH{HCHtCuRHH[]5uRUHSPHF(H1HHHHH[]ÐUHAWAVAUATSHHHeiHHEW)EIIHE)EHE)pHEHHD$(HkHD$ HHD$HpHD$HEH$D$LELM1 1L&IHU1LU%Iǀ} ukLHH(HLkHLy( ~ dWWWTUVXHpHLW)`)P)@)0) ))))HDžLeH]L)tcLIILH=dHPsRILLKHHL~LLHtRILMEHHpLHLHHt HrRHHHt HPrRH Ht H(rRHHt H|rRHHt%HdrRHpHu#HLHpHt Hx3rRH}Ht H}!rRH}Ht H}rRHiHH;EuHH[A\A]A^A_]HrRHBoR HHpH\HHpHtqHHHHuHHHt HqRHHHuXH HudHHupHHu|HpHH}HH}HHhnR HPqRH HtH(pRHHtHpRHHtHpRHpHxRHHpHc=HHpHN(HHpH9HHpH$HxZpRH}HH}DpRH}HH}.pRHnmR fDUHAWAVAUATSHHiHHELL0H HH8IW)EHEIEMe I)tTH(MILH=LoRILuLuKHEMH(~LLpRMLuHfILɀILH}&(IH LHNL)tH8HHRH)H9LNH8(H&HHH2HH?HH>HHATdHH=HHAOT dHHHOHHwHH^H) (ydfA\A$TXADTXAL TXTXHHuH_HtA("dTXATX((XH9~A T dX(XXH9HPH)HHtH( dATXHHuHH)IL ( dfQYTXTXQTXTXHHufMMI}HL)H9uTMEI] HL)H9uAL)t1DI H;u+HH9uL)tB1fDII; -u HH9u%H8LI}HI}pLIE8IMHI+E0HHHXIMPH`LhLpLxH 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A HHuH-ADADDADD AD DADDADDADDADHH9uHHHBHHDAAHs 1MuzI@H)1LAALD L0AD AL0D@LPAD@ALPD`LpAD`ALpH HuMt(HID ADA H IuH9HEL$8L}ILmH}/LMHHGLHpHL0HPL^ICIK HHHL@ffffff.(_BH___HL9|IIII9|N(C) IM9Nofff.WC) IM9+LfAI9}L)LMKH_H(HuC) IM9M9LHLwL8MIFHDXAO,L@L)MIffff.IvCIs (Mukfffff.HHH H ILD __ -_H_HH9u(Mt+HILHL _H(HuC IIL;e6H+MHIKK H9sKK H9MII@HHQHs1LMHLMHEJItpI\pHBH)1DLDLDLDLDLDLD D H HuHt2ILMJHڐADA ADA H HuM9LmMDD)IEL)HtHff.CCIHuHraf.CCCDCDCDCDCD CD CDCDCDCDCDCDCDCDIM9u[A\A]A^A_]fffff.UH]f.UH]鄞QfDUHSPHwQH XjHHKHHH[]@UHHXjHHGHF]UH]f.UH]QfDUHH]2fUHH ezdH1H9NHD]DUHHXj]UHAWAVAUATSHL*LI@HELHpHHIL9{HuLVXH^xIH]LM4MXMx H~0H^8L'H}H9aLMPML}HuL~PLCHuI)HvHuLMH}L]LeK4&AAu0HuH6LI<1(_LL9|LMIs nLMIrdHuN$fffff.I1I<1(_LL9|IqI<E1ې(B_MM9|II9uHuHH;U} LuHL]Le:ffffff.HxHUHR`HuH)HH9L]Le}Lt1HHL9I)I f.K4&A41HL9}LuH$DHXHUHR`L)HH9}Mt1HHIu~I)I fK4&A41HL9}LuHHHIuGfHXHUHR`H)HH9}Lt1HHIu1HHIu[A\A]A^A_]UHAWAVSHIHyiHHE0QHL=~iL;H{L?t$HHEHEHUL8HUjHHiHH;EuHH[A^A_]QL;IH{HCHt -eQIHXQL蘗Q UHSPHH{Ht H{3QHΏiHH{HCHHt[] Q[]fff.UHSPHH{Ht 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HDž0LL)t[IIHI9-THH(H JH0M)M~HLL</TLH($AH HUHML`H`AHpHP0EH@TH`W)HDžHuLuI)HtwMII9HHL-TILLO,LMLHHLV.TMML)HDžE1E1E1X,TILLLW)HDžH8HHEHAHEHtH@HHMLH`w*LXMuH]Ht#HHCHuHHPH+THHt H+THHt H+TT< uCH@芮*HuHpXHI}r H HpwtXI]H}HHuHpHHx:H@H@MmMuH}L5HEHLxHx&7L9ILHH9~VHuHpLHxCMuH}LHEHHx&7OH9W))))))))Mu)HDžL}H]L)tbIIHI9H*TILLKHHLX~LLHU+TILHH`LLHpLx<%HHt H)THHt Hj)THHt HR)THHt H:)THHt H")TH Ht H( +)TH@HtHhH8(TH`Ht Hh(TH}Ht H}(TH}Ht H}(THNkHH;Eu4LHĨ[A\A]A^A_]HuHpLHxM(TH@%T(H %TH%T H%T IHHu:DIHHHIHHt H'THHu)HHu5HHuAHHuQH'THHtH'THHtHg'THHHK'TIH HIH@HHHIH]Ht#HHCHuHHPH%THHt H&TL&TLMu +NIMtFLL5IH Hu7AIHXHHHtH*Hd&TH Ht H(L&TH@HtHhH81&TH`HuH}Hu(H}Hu1LS#T Hh%TH}HtH}%TH}HtH}%TL#T UHAWAVAUATSHhHXkHHEMHHII7IOH9HpJD|H]LuH}HEHEH}L0H@L9HUn}dHH)Hl1E1Hunfffff.H]HtWIHC I9|)ff.L9}+LcHCHtHHC I9}HIHuI@I<$ujHII<$uT($TLp H@HHXI$HMH HtHMI$H}H>HEI7IOH}IHH)HI9)vL9t HHԁ*L9tI7IWH*E1HpI9H0HPL螁*HkHH;EC$TI9u ff.I7IOH)I>HHWIH]HtkLmHC I9|,fffff.L9}+LkHCHtHHC I9}HIHuI@I}t*IHpL;ptqfHEHII}uֿ(/#TL` H@HHXIEHMH HtHMIEH}HHEIHpL;pI7H}HHGIGH)HH`M7I_W)EHEL)HHLkIJ<y"TIILeLmH]IIJ4LV"TH?t@)HHHK!쀽|LEvE1IE1HEHt.L@HHL9h HMHMHHuL9t +L;n LHL!HEDHHHH#HK4H1H>HEH}HOH;OsHHHO#fff.Hu践ILEAA}LHL!HEDHL9kHH HK4HnDH}HGH;GtHHHHG"ILEffffff.IM7IGL)HI9E1I1fHEHt*L@HHH9X HMHMHHuL9tH;^ }=HHL!HEHHHH#HI4Ht@H>AA`HHL!HEHL9tHH HI4HuH}HGH;GtHHHHG}M7LEfDHIGL)HH9A AMHpHH;AtkH}HHGHMHHAIwL)HHpHpH+0HH}I7H}HGH;GtQHHHHGHEuHvH}HHWH)HHHHHHHOHEt0HEH}HGH;GsHHHG HuMIGL)HHLeLuHHMHHH#H{HHH H0tZHt*ID$I+$HHEH}HOH;OsJHHHOI4ID$I;D$tJHHHID$Jf.ID$HHI HH,L4MI4ID$I;D$uLiMfDHIGL)HH9ID$I+$HHHHuHEAE1H}H  H)fHEHM7]HIOI9HyL)HHVH8sYLHHED,H}HHED(AAH}HkkHZH)Lf.H7H0HwH0HwH0HwH0Hw H0Hw(H0Hw0H0Hw8H0H@Hu]HtHfff.H7H0HHut/HMHHAAH}L9IWLy*|t?L)HHEH]HHSH)HHH)HUH{H}HMHHAH}HHWH)HHHtHr!HHHOH)eHEHHAH}Ht<THuH}HkHH;E3DHh[A\A]A^A_]H}kHHC^H}OT HH}HufpHH}HuXb][HH}HuFPHH}Hu8BHH}Hu*4HH}Hu&HH}HuHH}Ht pTHHuH}HT @UHAWAVAUATSHHH~kHHEHt'H~kHH;EuHĘ[A\A]A^A_]]T TIH`7H5/!VH %VHxL`H%VHELHHuLH迫AHL"VHxLL裸E1H5ٟkHBLT IAL`MIIHt HX+TLeMt6HEL9t!HX@t HxTHI9uH}LLeTEuxu L`Mu)aH}TxtH}TL`Mt:HhL9tEHX@t HxTHI9uH`LhnTEtLTLT L@UHAWAVAUATSHH|kHHEHHOH)Hu?HHHߚ*H9H|kHH;EuHĈ[A\A]A^A_]=TTIHh7H5VH !VH}LhW)PHDž`0TH`(Ah)PHdimensioHH Hith two HHHtrices wHHHks on maHHHOnly worH@(ns.AHe!VHuHPL&E1H5\kHŎL9TTIHh7H5VH VH}LhW)PƅP*HDž`Hismatch.H^Hize mismHYHOutput sHQƅfAH VHuHPLYE1H5kHLlT IALhMIIALeMFIALhMnIIPt H`TLeMt6HEL9t!HX@t HxTHI9uH}LLegTEuEu LhMu-'H}ATEtH}2TLhMHpL9HX@t HxTHI9uIPt H`TLeMt6HEL9t!HX@t HxTHI9uH}LLeTEuEuLhMu&^H}xTEtH}iTLhMt:HpL9tEHX@t Hx>THI9uHhLp#TEtLFTLVT LfUHAWAVATSH`IHIHxkHHE%AIH[IH1HIHH*EH@HUHHRWH*EH@lHULeHMHEH]H]HULHI7H}H9tHtHP(HwkHH;Et#HP HwkHH;Eu H`[A\A^A_]iTIH}H9uHP L7T HtHP(L"T f.UHAWAVAUATSHHUwkHHEHHOH)Hu@HXHH^*H9HwkHH;EuHĈ[A\A]A^A_]TjTIHh7H5VH VH}LhrW)PHDž`0 TH`(<h)PHdimensioHH Hith two HHHtrices wHHHks on maHHHOnly worH@(ns.AHVHuHPL襰E1H5ۗkHDLTsTIHh7H5VH VH}Lh{W)PƅP*HDž`Hismatch.H^Hize mismHYHOutput sHQƅfAHVHuHPLدE1H5kHwLT IALhMIIALeMFIALhMnIIPt H`%TLeMt6HEL9t!HX@t HxTHI9uH}LLeTEuEu LhMu-'H}TEtH}TLhMHpL9HX@t Hx~THI9uIPt H`YTLeMt6HEL9t!HX@t Hx4THI9uH}LLeTEuEuLhMu&^H}TEtH}TLhMt:HpL9tEHX@t HxTHI9uHhLpTEtLTL T LUHAWAVAUATSHXIIHHrkHHEHL`;ILUIHHJLLTHH*EH@HEHH@WH*E( TH #lHLhLxL`HX HEHUL}LLL7H}I9tHtHP(H3rkHH;Et%HP HrkHH;EuHX[A\A]A^A_] THH}I9uHP H +T HtHP(Hu +T ffff.UHAWAVAUATSHHqkHHEHHOH)HuDHXHHH誏*H9HjqkHH;EuHĈ[A\A]A^A_] T TIHhQ7H5VH VH}Lh +辨W)PHDž`0Y TH`(a6h)PHdimensioHH Hith two HHHtrices wHHHks on maHHHOnly worH@(ns.AHZVHuHPLE1H5'kHL T TIHhZ7H5VH VH}Lh ǧW)PƅP*HDž`Hismatch.H^Hize mismHYHOutput sHQƅfAHVHuHPL$E1H5ZkHÂL7 T IALhMIIALeMFIALhMnIIPt H`q +TLeMt6HEL9t!HX@t HxL +THI9uH}LLe2 +TEuEu LhMu-'H} +TEtH} TLhMHpL9HX@t Hx THI9uIPt H` TLeMt6HEL9t!HX@t Hx THI9uH}LLef TEuEuLhMu&^H}C TEtH}4 TLhMt:HpL9tEHX@t Hx THI9uHhLpTEtL TL!T L@UHAWAVAUATSHHUmkHHEIIHI?HH@H5HHHHH@HHHLOL3MnW)EHEMLHHtUM9N$LTIL}HEHO,LmH5ReLL} TLmI?HEHE1E1IFHWH*IHIFH*hpHH@WH*xW)HDž LL)tTLIII9PTHHHJH M)M~HLLTLHHH(W)0HDž@HHXL)tUIILH=ZHTIL8L0KH@H~LLHTIL8HHHHHPHHXHH`H}HHhH]HHH 7H}H9tuHtHP(H0Ht H8THHt HTH}HtHH8THVjkHH;Eu&H[A\A]A^A_]HP H0HuTH}THT H0T IH0HtcIHHt[IH}HH}IH}H9uHP H0HtKHu#H0Hu:HHuFH}HuR_HP(H0HtIH0HtH8THHtHTH}HtHH8qTLT fUHAWAVAUATSHHhkHHELL0H8HH IW)EHEMoMg M)tWH(LHHH=tLTILuLuIHEMH(~LLL4TMLuH0HLJILL H}L*IH8LHPL)tIuI}H)H9L芸L*H?IuAAAAI9LOIM)IKH(LH?II>MIK BI%H=IIO BLIRL9IDHzHLfT XT0XHHuHWITM$ID$HL)H9uUMD$ML$ LL)H9u@L)t1@I H; u+HH9uM)tG1fDII; u HI9u*LH8LI|$HCI|$p7LID$8IL$HI+D$0HHHXIL$PH`LhHpLxH H*@H@HHHH@WH*PHlHEHXHEH]H]H@H0LH 7H}H9thHhHP(H}H^bWAH}HDHH#HHPHs'HuiHP H}HH)ȺXXDXDXD XDXDXDXDHH9uHHHXHHuLIrTHTXDXT\XD0XXTXXLXHrHHR L9|((XL9~B X(XXM~IRDփHs 1HuGeLH)1XXDXDXD XDXDXDXDHH9uHt HHfff.XHHuH9}oD)D)HPL)L)HtHXHHuHr>H)HLDXAXAXAXAXAXAXAXH HuAH}Ht H}SH1ckHH;EuH[A\A]A^A_]SH}S IH}H9uHP H}HtmHuH}Hu_LyS HP(H}HtDIH}Ht6IH}Ht(IH}HtIH}Ht IH}HtH}SLS fUHSPHF(N)HvHH HHH[]ffffff.UHAWAVAUATSHHHbkHHEW)EIIHE)EHE)pHEHwHD$(H HD$ H HD$HpHD$HEH$D$LELM豹1L?(IHU1L&Iǀ} uELHHv*HL4uHLYw HpHLW)`)P)@)0) ))))HDžLeH]L)tcLIILH=dHSILLKHHL~LLH:SILMEHHpLHLDHHt HjSHHHt HPRSH Ht H(:SHHt H"SHHt%H +SHpHu#HLHpHt HxSH}Ht H}SH}Ht H}SHP_kHH;EuHH[A\A]A^A_]SHS HHpH\HHpHtqHHHHuHHHt H(SHHHuXH HudHHupHHu|HpHH}HH}HHS HPSH HtH(SHHtHSHHtHpSHpHxRHHpHc=HHpHN(HHpH9HHpH$HxSH}HH}SH}HH}SHS fff.UHAWAVAUATSHELxHEH7]kHH]IW)EHE)E)`HEHDžpHpHvHHE)@HDžPL>LfM)HXH8H`teLHL9(LSIHHHhLHL@IDHPM~3LLLBSMMLHHHHhE1E1MW) HDž0LL)t[IIHI9dSHH(H JH0M)M~HLLSLH($AH HUHML`H`AHpHP0EH@TH`W)HDžHuLuI)HtwMII9HHLSILLO,LMLHHLSMML)HDžE1E1E1XSILLLW)HDžH8HHEHAHEHtH@HHMLH`H*LXMuH]Ht#HHCHuHHPHrSHHt HVSHHt H>ST< uCH@w*HuHpmHI}o H HpwtXI]H}HtHuHpHHxjH@H@BMmMuH}LHEHLxHxn6L9ILHH9~VHuHpLHx#MuH}LHEHHx6OH9W))))))))Mu)HDžL}H]L)tbIIHI9HSILLKHHLX~LLHSILHH`LLHpLx +HHt HSHHt HSHHt HSHHt HSHHt HSH Ht H(zSH@HtHhH8_SH`Ht HhGSH}Ht H}5SH}Ht H}#SHVkHH;Eu4LHĨ[A\A]A^A_]HuHpLHx6M:SH@4S(H &SHS H +S IHHu:DIHHHIHHt HHSHHu)HHu5HHuAHHuQHSHHtHSHHtHSHHHSIH HIH@HHHIH]Ht#HHCHuHHPHTSHHt H8SL0SLMu +NIMtFLL5IH Hu7AIHXHHHtHnM*HSH Ht H(SH@HtHhH8SH`HuH}Hu(H}Hu1LS HhmSH}HtH}[SH}HtH}ISLS UHAWAVATSH`IHIHSkHHEgIHiIH1HIHH*EH@HUHHRWH*EHlHULeHMHEH]H]HULH6H}H9tHtHP(HSkHH;Et#HP HSkHH;Eu H`[A\A^A_]SIH}H9uHP LwS HtHP(LbS 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HD$HpHD$HEH$D$LELMa1L(IHU1L>&Iǀ} uGLHH&E*HLHL HH HHpHLW)`)P)@)0) ))))HDžLeH]L)tcLIILH=dHSILLKHHL~LLHSILMEHHpLHLRHHt HSHHHt HPSH Ht H(SHHt HSHHt%HSHpHu#HLQHpHt HxSH}Ht H}uSH}Ht H}cSH$kHH;EuHH[A\A]A^A_]SH薽S HHpH\HHpHtqHHHHuHHHt HֿSHHHuXH HudHHupHHu|HpHH}HH}HH輼S HPfSH HtH(NSHHtH6SHHtHSHpHxRHHpHc=HHpHN(HHpH9HHpH$Hx设SH}HH}蘾SH}HH}肾SH»S f.UHAWAVAUATSHELxHEH"kHH]IW)EHE)E)`HEHDžpHpHvHHE)@HDžPL>LfM)HXH8H`teLHL9.L趽SIHHHhLHL@IDHPM~3LLLSMMLHHHHhE1E1MW) HDž0LL)t[IIHI9SHH(H JH0M)M~HLL\SLH($AH HUHML`H`AΖHpHP0EH@TH`W)HDžHuLuI)HtwMII9HHL3SILLO,LMLHHLvSMML)HDžE1E1E1XȻSILLLW)HDžH8HHEHAHEHtH@HHMLH`*LXMuH]Ht#HHCHuHHPH"SHHt HSHHt HST< uIH@=*HHpdHI}@H HH HpwtXI]H}HHuHpHHxtH@H@MgMuH}LOHEHLxHx6L9ILHH9~VHuHpLHx-MuH}L訬HEHHxŵ6OH9W))))))))Mu)HDžL}H]L)tbIIHI9H+SILLKHHLX~LLHoSILHH`LLHpLx +HHt H蜸SHHt H脸SHHt HlSHHt HTSHHt H<SH Ht H($SH@HtHhH8 SH`Ht HhSH}Ht H}߷SH}Ht H}ͷSHhkHH;Eu4LHĨ[A\A]A^A_]HuHpLHx@MSH@޴S(H дSH´S H贴S IHHu:DIHHHIHHt HSHHu)HHu5HHuAHHuQH豶SHHtH虶SHHtH聶SHHHeSIH HIH@HHHIH]Ht#HHCHuHHPHSHHt HSLڵSLMu +NIMtFLL5IH Hu7AIHXHHHtH*H~SH Ht H(fSH@HtHhH8KSH`HuH}Hu(H}Hu1LmS HhSH}HtH}SH}HtH}SL3S ff.UHAWAVATSH`IHIHakHHEUIHz:IH1HIHH*EH @HUHAlHULeHMHH IWH*EHEH]H]HULH-6H}H9tHtHP(HkHH;Et#HP HkHH;Eu H`[A\A^A_]MSIH}H9uHP LS HtHP(LS fffff.UHAWAVAUATSHXIIHH/kHHEHL`ILA9IHHJLLٴSHH*EH @HEHHH@WH*E(SH TlHLhLxL`HX HEHUL}LLLϾ6H}I9tHtHP(HdkHH;Et%HP HLkHH;EuHX[A\A]A^A_]SHH}I9uHP H軯S HtHP(H覯S fffff.UHAWAVAUATSHHkHHEIIHIHH@HHHHHH@HHHL7L3MnW)EHEMLHHtKM9N$L蝱SIL}HEHO,LmH5[eLLSLmHEHE1E1IFHWH*IHIFH*hpHH@WH*xW)HDž LL)t[IIHI9ӰSHHHJH M)M~HLLSLHHH(W)0HDž@HHXL)t[IIHI9ZHBSIL8L0KH@H~LLH荱SIL8HHHHHPHHXHH`H}H7HhH]HHH膻6H}H9tuHtHP(H0Ht H8hSHHt HPSH}HtHH88SHkHH;Eu&H[A\A]A^A_]HP H0Hu]SH}ZSHLS H0>S IH0HtcIHHt[IH}HH}IH}H9uHP H0HtKHu#H0Hu:HHuFH}HuR_HP(H0HtIH0HtH8SHHtHSH}HtHH8SL.S fDUHAWAVAUATSHHekHHELL0H8HH IffEHEMnMf M)tWH(LHHH=LeSIL}L}IHEMH(~LLL貮SML}HHL2ILL H}/*IH8LHPL)tIuI}H)H9u>L bL/*HH3HL@IM$ID$HL)H9uWMD$ML$ LL)H9uBL)t1fDI H; u+HH9uM)tG1fDII; u HI9u*LH8L WI|$H<I|$p0L PID$8IL$HI+D$0HHHXIL$PH`LhHpLxH H*@H @HHHH@WH*fօPHlHEHXHEH]H]H@H0LH46H}H9toHaHP(H}HW[1I7H}H@DLHfHnHQHHwH s,f1HHP H}HHVH)f1oTfoDfoL(o\8odHffoTXffoDhfoLxfHHuHt9Hfffff.HHofoTfHHuffpNffH~I9tHH)H fDH1HHuI7H}Ht H}轩SHXkHH;EuH[A\A]A^A_]SH}S IH}H9uHP H}HtmHuH}Hu_L蠦S HP(H}HtDIH}Ht6IH}Ht(IH}HtIH}Ht IH}HtH}SL8S UHAVSHPIH{ kHHE(ԨSHþ HʨSHHCHCXHC`HCXHCHHC@HC8HC0HC(HC HCPHCpHCxHCpHChƃHǃfǃHǃHǃƃHHǃHǃHǃHǃHǃHǃHǃHǃHǃHHHǃHǃHǃǃǃHǃ H]"H5]SH}H*%H5UH+%H51WH\%HH +HQH5CSH|%HH;A%HHH kHMHEiHUHuHuIIFIF0INIVIF@H]HEHtH5'H苦SH& kHH;Eu LHP[A^]ʦSIH]HEHtH'HFSL膣S fffff.UHAVSHPIH +kHHE(SHþ H +SHHCHCXHC`HCXHCHHC@HC8HC0HC(HC HCPHCpHCxHCpHChƃHǃfǃHǃHǃƃHHǃHǃHǃHǃHǃHǃHǃHǃHǃHHHǃHǃHǃǃǃHǃ H]"H5SH}Hj%H5BUHk%H5qWH蜩%HH +HQH5SH輪%HH;聟%HHH `kHMHevHUHuHuIIFIF0INIVIF@H]HEHtHu'HˣSHfkHH;Eu LHP[A^] +SIH]HEHtH0'H膣SLƠS fffff.UHAVSHPIHkHHE(TSHþ HJSHHCHCXHC`HCXHCHHC@HC8HC0HC(HC HCPHCpHCxHCpHChƃHǃfǃHǃHǃƃHHǃHǃHǃHǃHǃHǃHǃHǃHǃHHHǃHǃHǃǃǃHǃ H]"H5ݮSH}H誮%H5UH諥%H5WHܦ%HH HQH5SH%HH;%HHH kHMHEHUHuHuIIFIF0INIVIF@H]HEHtH赺'H SHkHH;Eu LHP[A^]JSIH]HEHtHp'HƠSLS fffff.UHAVSHPIH;kHHE(蔠SHþ H芠SHHCHCXHC`HCXHCHHC@HC8HC0HC(HC HCPHCpHCxHCpHChƃHǃfǃHǃHǃƃHHǃHǃHǃHǃHǃHǃHǃHǃHǃHHHǃHǃHǃǃǃHǃ H]"H5SH}H%H5¥UH%H5WH%HH HQH5SH<%HH;%HHH kHMHEHUHuHuIIFIF0INIVIF@H]HEHtH'HKSHkHH;Eu LHP[A^]芞SIH]HEHtH谷'HSLFS fffff.UHAVSHPIH{kHHE(ԝSHþ HʝSHHCHCXHC`HCXHCHHC@HC8HC0HC(HC HCPHCpHCxHCpHChƃHǃfǃHǃHǃƃHHǃHǃHǃHǃHǃHǃHǃHǃHǃHHHǃHǃHǃǃǃHǃ H]"H5]SH}H*%H5UH+%H51WH\%HA H5JSH胢%HH;H%HHH 'kHMHLHUHuHuIIFIF0INIVIF@H]HEHtH<'H蒛SH-kHH;Eu LHP[A^]ћSIH]HEHtH'HMSL荘S DUHAVSHPIHjHHE($SHþ HSHHCHCXHC`HCXHCHHC@HC8HC0HC(HC HCPHCpHCxHCpHChƃHǃfǃHǃHǃƃHHǃHǃHǃHǃHǃHǃHǃHǃHǃHHHǃHǃHǃǃǃHǃ H]-"H5SH}Hz%H5RUH{%H5WH謞%HA H5SHӟ%HH;蘔%HHH wkHMH\HUHuHuIIFIF0INIVIF@H]HEHtH茲'HSH}jHH;Eu LHP[A^]!SIH]HEHtHG'H蝘SLݕS DUHAVSHPIHjHHE(tSHþ HjSHHCHCXHC`HCXHCHHC@HC8HC0HC(HC HCPHCpHCxHCpHChƃHǃfǃHǃHǃƃHHǃHǃHǃHǃHǃHǃHǃHǃHǃHHHǃHǃHǃǃǃHǃ H]="H5SH}Hʣ%H5UH˚%H5WH%HH +HQH5SH%HH;%HHH kHMHe}HUHuHuIIFIF0INIVIF@H]HEHtHկ'H+SHjHH;Eu LHP[A^]jSIH]HEHtH萯'HSL&S fffff.UHAVSHPIH[jHHE(贕SHþ H誕SHHCHCXHC`HCXHCHHC@HC8HC0HC(HC HCPHCpHCxHCpHChƃHǃfǃHǃHǃƃHHǃHǃHǃHǃHǃHǃHǃHǃHǃHHHǃHǃHǃǃǃHǃ H]"H5=SH}H +%H5UH %H5WH<%HH +HQH5#SH\%HH;!%HHH kHMHʼnHUHuHuIIFIF0INIVIF@H]HEHtH'HkSHjHH;Eu LHP[A^]誓SIH]HEHtHЬ'H&SLfS fffff.UHAVSHPIHjHHE(SHþ HSHHCHCXHC`HCXHCHHC@HC8HC0HC(HC HCPHCpHCxHCpHChƃHǃfǃHǃHǃƃHHǃHǃHǃHǃHǃHǃHǃHǃHǃHHHǃHǃHǃǃǃHǃ H]"H5}SH}HJ%H5+UHK%H5QWH|%HH HQH5cSH蜗%HH;a%HHH @kHMH՘HUHuHuIIFIF0INIVIF@H]HEHtHU'H諐SHFjHH;Eu LHP[A^]SIH]HEHtH'HfSL覍S fffff.UHAVSHPIHjHHE(4SHþ H*SHHCHCXHC`HCXHCHHC@HC8HC0HC(HC HCPHCpHCxHCpHChƃHǃfǃHǃHǃƃHHǃHǃHǃHǃHǃHǃHǃHǃHǃHHHǃHǃHǃǃǃHǃ H]="H5SH}H芛%H5kUH苒%H5WH輓%HH HQH5SHܔ%HH;衉%HHH kHMHՖHUHuHuIIFIF0INIVIF@H]HEHtH蕧'HSHjHH;Eu LHP[A^]*SIH]HEHtHP'H覍SLS fffff.UHAVSHPIHjHHE(tSHþ HjSHHCHCXHC`HCXHCHHC@HC8HC0HC(HC HCPHCpHCxHCpHChƃHǃfǃHǃHǃƃHHǃHǃHǃHǃHǃHǃHǃHǃHǃHHHǃHǃHǃǃǃHǃ H]="H5SH}Hʘ%H5UHˏ%H5ѸWH%HA H5SH#%HH;%HHH ǰkHMHܔHUHuHuIIFIF0INIVIF@H]HEHtHܤ'H2SHjHH;Eu LHP[A^]qSIH]HEHtH藤'HSL-S DUHAVSHPIHkjHHE(ĊSHþ H躊SHHCHCXHC`HCXHCHHC@HC8HC0HC(HC HCPHCpHCxHCpHChƃHǃfǃHǃHǃƃHHǃHǃHǃHǃHǃHǃHǃHǃHǃHHHǃHǃHǃǃǃHǃ H]ͷ"H5MSH}H%H5UH%H5!WHL%HA H5:SHs%HH;8%HHH kHMHHUHuHuIIFIF0INIVIF@H]HEHtH,'H肈SHjHH;Eu LHP[A^]SIH]HEHtH'H=SL}S DUHAVSHPIHjHHE(SHþ H +SHHCHCXHC`HCXHCHHC@HC8HC0HC(HC HCPHCpHCxHCpHChƃHǃfǃHǃHǃƃHHǃHǃHǃHǃHǃHǃHǃHǃHǃHHHǃHǃHǃǃǃHǃ H]ݵ"H5SH}Hj%H5TUHk%H5qWH蜋%HH +HQH5SH輌%HH;聁%HHH `kHMHHUHuHuIIFIF0INIVIF@H]HEHtHu'H˅SHfjHH;Eu LHP[A^] +SIH]HEHtH0'H膅SLƂS fffff.UHAVSHPIHjHHE(TSHþ HJSHHCHCXHC`HCXHCHHC@HC8HC0HC(HC HCPHCpHCxHCpHChƃHǃfǃHǃHǃƃHHǃHǃHǃHǃHǃHǃHǃHǃHǃHHHǃHǃHǃǃǃHǃ H]]"H5ݐSH}H誐%H5UH談%H5WH܈%HH +HQH5SH%HH;~%HHH kHMHHUHuHuIIFIF0INIVIF@H]HEHtH赜'H SHjHH;Eu LHP[A^]JSIH]HEHtHp'HƂSLS fffff.UHAVSHPIH;jHHE(蔂SHþ H节SHHCHCXHC`HCXHCHHC@HC8HC0HC(HC HCPHCpHCxHCpHChƃHǃfǃHǃHǃƃHHǃHǃHǃHǃHǃHǃHǃHǃHǃHHHǃHǃHǃǃǃHǃ H]]"H5SH}H%H5ԇUH%H5WH%HH HQH5SH<%HH;|%HHH kHMHEHUHuHuIIFIF0INIVIF@H]HEHtH'HKSHjHH;Eu LHP[A^]芀SIH]HEHtH谙'HSLF}S fffff.UHAVSHPIH{jHHE(SHþ HSHHCHCXHC`HCXHCHHC@HC8HC0HC(HC HCPHCpHCxHCpHChƃHǃfǃHǃHǃƃHHǃHǃHǃHǃHǃHǃHǃHǃHǃHHHǃHǃHǃǃǃHǃ H]ݬ"H5]SH}H*%H5UH+%H51WH\%HH HQH5CSH|%HH;Ay%HHH kHMHEHUHuHuIIFIF0INIVIF@H]HEHtH5'H}SH&jHH;Eu LHP[A^]}SIH]HEHtH'HF}SLzS fffff.UHAVSHPIHjHHE(}SHþ H +}SHHCHCXHC`HCXHCHHC@HC8HC0HC(HC HCPHCpHCxHCpHChƃHǃfǃHǃHǃƃHHǃHǃHǃHǃHǃHǃHǃHǃHǃHHHǃHǃHǃǃǃHǃ H]ݪ"H5SH}Hj%H5TUHk%H5qWH蜀%HA H5SHÁ%HH;v%HHH gkHMHLHUHuHuIIFIF0INIVIF@H]HEHtH|'HzSHmjHH;Eu LHP[A^]{SIH]HEHtH7'HzSLwS DUHAVSHPIH jHHE(dzSHþ HZzSHHCHCXHC`HCXHCHHC@HC8HC0HC(HC HCPHCpHCxHCpHChƃHǃfǃHǃHǃƃHHǃHǃHǃHǃHǃHǃHǃHǃHǃHHHǃHǃHǃǃǃHǃ H]m"H5SH}H躅%H5UH|%H5WH}%HA H5ڼSH%HH;s%HHH kHMH\HUHuHuIIFIF0INIVIF@H]HEHtH̑'H"xSHjHH;Eu LHP[A^]axSIH]HEHtH臑'HwSLuS DUHAVSHPIH[jHHE(wSHþ HwSHHCHCXHC`HCXHCHHC@HC8HC0HC(HC HCPHCpHCxHCpHChƃHǃfǃHǃHǃƃHHǃHǃHǃHǃHǃHǃHǃHǃHǃHHHǃHǃHǃǃǃHǃ H]}"H5=SH}H +%H5}UH z%H5WH<{%HH +HQH5#SH\|%HH;!q%HHH kHMHeHUHuHuIIFIF0INIVIF@H]HEHtH'HkuSHjHH;Eu LHP[A^]uSIH]HEHtHЎ'H&uSLfrS fffff.UHAVSHPIHjHHE(tSHþ HtSHHCHCXHC`HCXHCHHC@HC8HC0HC(HC HCPHCpHCxHCpHChƃHǃfǃHǃHǃƃHHǃHǃHǃHǃHǃHǃHǃHǃHǃHHHǃHǃHǃǃǃHǃ H]"H5}SH}HJ%H5AzUHKw%H5QWH|x%HH +HQH5cSHy%HH;an%HHH @kHMHUHUHuHuIIFIF0INIVIF@H]HEHtHU'HrSHFjHH;Eu LHP[A^]rSIH]HEHtH'HfrSLoS fffff.UHAVSHPIHjHHE(4rSHþ H*rSHHCHCXHC`HCXHCHHC@HC8HC0HC(HC HCPHCpHCxHCpHChƃHǃfǃHǃHǃƃHHǃHǃHǃHǃHǃHǃHǃHǃHǃHHHǃHǃHǃǃǃHǃ H]"H5}SH}H}%H5wUHt%H5WHu%HH HQH5SHv%HH;k%HHH kHMHHUHuHuIIFIF0INIVIF@H]HEHtH蕉'HoSHjHH;Eu LHP[A^]*pSIH]HEHtHP'HoSLlS fffff.UHAVSHPIHjHHE(toSHþ HjoSHHCHCXHC`HCXHCHHC@HC8HC0HC(HC HCPHCpHCxHCpHChƃHǃfǃHǃHǃƃHHǃHǃHǃHǃHǃHǃHǃHǃHǃHHHǃHǃHǃǃǃHǃ H]}"H5zSH}Hz%H5tUHq%H5њWHr%HH HQH5SHt%HH;h%HHH kHMHHUHuHuIIFIF0INIVIF@H]HEHtHՆ'H+mSHjHH;Eu LHP[A^]jmSIH]HEHtH萆'HlSL&jS fffff.UHAVSHPIH[jHHE(lSHþ HlSHHCHCXHC`HCXHCHHC@HC8HC0HC(HC HCPHCpHCxHCpHChƃHǃfǃHǃHǃƃHHǃHǃHǃHǃHǃHǃHǃHǃHǃHHHǃHǃHǃǃǃHǃ H]}"H5=xSH}H +x%H5rUH o%H5WH<p%HA H5*SHcq%HH;(f%HHH kHMHHUHuHuIIFIF0INIVIF@H]HEHtH'HrjSH jHH;Eu LHP[A^]jSIH]HEHtH׃'H-jSLmgS DUHAVSHPIHjHHE(jSHþ HiSHHCHCXHC`HCXHCHHC@HC8HC0HC(HC HCPHCpHCxHCpHChƃHǃfǃHǃHǃƃHHǃHǃHǃHǃHǃHǃHǃHǃHǃHHHǃHǃHǃǃǃHǃ H] "H5uSH}HZu%H5QoUH[l%H5aWHm%HA H5zSHn%HH;xc%HHH WkHMHHUHuHuIIFIF0INIVIF@H]HEHtHl'HgSH]jHH;Eu LHP[A^]hSIH]HEHtH''H}gSLdS DUHAVSHPIHjHHE(TgSHþ HJgSHHCHCXHC`HCXHCHHC@HC8HC0HC(HC HCPHCpHCxHCpHChƃHǃfǃHǃHǃƃHHǃHǃHǃHǃHǃHǃHǃHǃHǃHHHǃHǃHǃǃǃHǃ H]"H5rSH}Hr%H5lUHi%H5WHj%HH +HQH5éSHk%HH;`%HHH kHMHHUHuHuIIFIF0INIVIF@H]HEHtH~'H eSHjHH;Eu LHP[A^]JeSIH]HEHtHp~'HdSLbS fffff.UHAVSHPIH;jHHE(dSHþ HdSHHCHCXHC`HCXHCHHC@HC8HC0HC(HC HCPHCpHCxHCpHChƃHǃfǃHǃHǃƃHHǃHǃHǃHǃHǃHǃHǃHǃHǃHHHǃHǃHǃǃǃHǃ H]]"H5pSH}Ho%H5iUHf%H5WHh%HH HQH5SH<i%HH;^%HHH kHMHHUHuHuIIFIF0INIVIF@H]HEHtH{'HKbSHjHH;Eu LHP[A^]bSIH]HEHtH{'HbSLF_S fffff.UHAVSHPIH{jHHE(aSHþ HaSHHCHCXHC`HCXHCHHC@HC8HC0HC(HC HCPHCpHCxHCpHChƃHǃfǃHǃHǃƃHHǃHǃHǃHǃHǃHǃHǃHǃHǃHHHǃHǃHǃǃǃHǃ H]蝕"H5]mSH}H*m%H5!gUH+d%H51WH\e%HA H5JSHf%HH;H[%HHH 'kHMHHUHuHuIIFIF0INIVIF@H]HEHtH<y'H_SH-jHH;Eu LHP[A^]_SIH]HEHtHx'HM_SL\S DUHAVSHPIHjHHE($_SHþ H_SHHCHCXHC`HCXHCHHC@HC8HC0HC(HC HCPHCpHCxHCpHChƃHǃfǃHǃHǃƃHHǃHǃHǃHǃHǃHǃHǃHǃHǃHHHǃHǃHǃǃǃHǃ H]"H5jSH}Hzj%H5dUH{a%H5WHb%HH +HQH5SHc%HH;X%HHH pkHMHHUHuHuIIFIF0INIVIF@H]HEHtHv'H\SHvjHH;Eu LHP[A^]]SIH]HEHtH@v'H\SLYS fffff.UHAVSHPIH jHHE(d\SHþ HZ\SHHCHCXHC`HCXHCHHC@HC8HC0HC(HC HCPHCpHCxHCpHChƃHǃfǃHǃHǃƃHHǃHǃHǃHǃHǃHǃHǃHǃHǃHHHǃHǃHǃǃǃHǃ H]m"H5gSH}Hg%H5aUH^%H5WH_%HH +HQH5ӞSH a%HH;U%HHH kHMHUHUHuHuIIFIF0INIVIF@H]HEHtHs'HZSHjHH;Eu LHP[A^]ZZSIH]HEHtHs'HYSLWS fffff.UHAVSHPIHKjHHE(YSHþ HYSHHCHCXHC`HCXHCHHC@HC8HC0HC(HC HCPHCpHCxHCpHChƃHǃfǃHǃHǃƃHHǃHǃHǃHǃHǃHǃHǃHǃHǃHHHǃHǃHǃǃǃHǃ H]譌"H5-eSH}Hd%H5_UH[%H5WH,]%HH +HQH5SHL^%HH;S%HHH |kHMH%,HUHuHuIIFIF0INIVIF@H]HEHtHq'H[WSHjHH;Eu LHP[A^]WSIH]HEHtHp'HWSLVTS fffff.UHAVSHPIHjHHE(VSHþ HVSHHCHCXHC`HCXHCHHC@HC8HC0HC(HC HCPHCpHCxHCpHChƃHǃfǃHǃHǃƃHHǃHǃHǃHǃHǃHǃHǃHǃHǃHHHǃHǃHǃǃǃHǃ H]譊"H5mbSH}H:b%H5A\UH;Y%H5AWHlZ%HH +HQH5SSH[%HH;QP%HHH 0zkHMHEKHUHuHuIIFIF0INIVIF@H]HEHtHEn'HTSH6jHH;Eu LHP[A^]TSIH]HEHtHn'HVTSLQS fffff.UHAVSHPIH˸jHHE($TSHþ HTSHHCHCXHC`HCXHCHHC@HC8HC0HC(HC HCPHCpHCxHCpHChƃHǃfǃHǃHǃƃHHǃHǃHǃHǃHǃHǃHǃHǃHǃHHHǃHǃHǃǃǃHǃ H]"H5_SH}Hz_%H5YUH{V%H5WHW%HH HQH5SHX%HH;M%HHH pwkHMHEuHUHuHuIIFIF0INIVIF@H]HEHtHk'HQSHvjHH;Eu LHP[A^]RSIH]HEHtH@k'HQSLNS fffff.UHAVSHPIH jHHE(dQSHþ HZQSHHCHCXHC`HCXHCHHC@HC8HC0HC(HC HCPHCpHCxHCpHChƃHǃfǃHǃHǃƃHHǃHǃHǃHǃHǃHǃHǃHǃHǃHHHǃHǃHǃǃǃHǃ H]m~"H5\SH}H\%H5VUHS%H5|WHT%HH HQH5ӓSH V%HH;J%HHH tkHMHEsHUHuHuIIFIF0INIVIF@H]HEHtHh'HOSHjHH;Eu LHP[A^]ZOSIH]HEHtHh'HNSLLS fffff.UHAVSHPIHKjHHE(NSHþ HNSHHCHCXHC`HCXHCHHC@HC8HC0HC(HC HCPHCpHCxHCpHChƃHǃfǃHǃHǃƃHHǃHǃHǃHǃHǃHǃHǃHǃHǃHHHǃHǃHǃǃǃHǃ H]譁"H5-ZSH}HY%H5TUHP%H5zWH,R%HH HQH5SHLS%HH;H%HHH qkHMHEqHUHuHuIIFIF0INIVIF@H]HEHtHf'H[LSHjHH;Eu LHP[A^]LSIH]HEHtHe'HLSLVIS fffff.UHAVSHPIHjHHE(KSHþ HKSHHCHCXHC`HCXHCHHC@HC8HC0HC(HC HCPHCpHCxHCpHChƃHǃfǃHǃHǃƃHHǃHǃHǃHǃHǃHǃHǃHǃHǃHHHǃHǃHǃǃǃHǃ H]"H5mWSH}H:W%H5AQUH;N%H5AwWHlO%HH HQH5SSHP%HH;QE%HHH 0okHMHEoHUHuHuIIFIF0INIVIF@H]HEHtHEc'HISH6jHH;Eu LHP[A^]ISIH]HEHtHc'HVISLFS fffff.UHAVSHPIH˭jHHE($ISHþ HISHHCHCXHC`HCXHCHHC@HC8HC0HC(HC HCPHCpHCxHCpHChƃHǃfǃHǃHǃƃHHǃHǃHǃHǃHǃHǃHǃHǃHǃHHHǃHǃHǃǃǃHǃ H]v"H5TSH}HzT%H5NUH{K%H5tWHL%HH HQH5SHM%HH;B%HHH plkHMHEmHUHuHuIIFIF0INIVIF@H]HEHtH`'HFSHvjHH;Eu LHP[A^]GSIH]HEHtH@`'HFSLCS fffff.UHAVSHPIH jHHE(dFSHþ HZFSHHCHCXHC`HCXHCHHC@HC8HC0HC(HC HCPHCpHCxHCpHChƃHǃfǃHǃHǃƃHHǃHǃHǃHǃHǃHǃHǃHǃHǃHHHǃHǃHǃǃǃHǃ H]ms"H5QSH}HQ%H5KUHH%H5qWHI%HH HQH5ӈSH K%HH;?%HHH ikHMHEkHUHuHuIIFIF0INIVIF@H]HEHtH]'HDSHjHH;Eu LHP[A^]ZDSIH]HEHtH]'HCSLAS fffff.UHAVSHPIHKjHHE(CSHþ HCSHHCHCXHC`HCXHCHHC@HC8HC0HC(HC HCPHCpHCxHCpHChƃHǃfǃHǃHǃƃHHǃHǃHǃHǃHǃHǃHǃHǃHǃHHHǃHǃHǃǃǃHǃ H]v"H5-OSH}HN%H5IUHE%H5oWH,G%HH HQH5SHLH%HH;=%HHH fkHMHEiHUHuHuIIFIF0INIVIF@H]HEHtH['H[ASHjHH;Eu LHP[A^]ASIH]HEHtHZ'HASLV>S fffff.UHAVSHPIHjHHE(@SHþ H@SHHCHCXHC`HCXHCHHC@HC8HC0HC(HC HCPHCpHCxHCpHChƃHǃfǃHǃHǃƃHHǃHǃHǃHǃHǃHǃHǃHǃHǃHHHǃHǃHǃǃǃHǃ H]t"H5mLSH}H:L%H5AFUH;C%H5AlWHlD%HH HQH5SSHE%HH;Q:%HHH 0dkHMHEgHUHuHuIIFIF0INIVIF@H]HEHtHEX'H>SH6jHH;Eu LHP[A^]>SIH]HEHtHX'HV>SL;S fffff.UHAVSHPIHˢjHHE($>SHþ H>SHHCHCXHC`HCXHCHHC@HC8HC0HC(HC HCPHCpHCxHCpHChƃHǃfǃHǃHǃƃHHǃHǃHǃHǃHǃHǃHǃHǃHǃHHHǃHǃHǃǃǃHǃ H]-n"H5ISH}HzI%H5CUH{@%H5iWHA%HH HQH5SHB%HH;7%HHH pakHMHEeHUHuHuIIFIF0INIVIF@H]HEHtHU'H;SHvjHH;Eu LHP[A^]<SIH]HEHtH@U'H;SL8S fffff.UHAVSHPIH jHHE(d;SHþ HZ;SHHCHCXHC`HCXHCHHC@HC8HC0HC(HC HCPHCpHCxHCpHChƃHǃfǃHǃHǃƃHHǃHǃHǃHǃHǃHǃHǃHǃHǃHHHǃHǃHǃǃǃHǃ H]-l"H5FSH}HF%H5@UH=%H5fWH>%HH HQH5}SH @%HH;4%HHH ^kHMHuHUHuHuIIFIF0INIVIF@H]HEHtHR'H9SHjHH;Eu LHP[A^]Z9SIH]HEHtHR'H8SL6S fffff.UHAVSHPIHKjHHE(8SHþ H8SHHCHCXHC`HCXHCHHC@HC8HC0HC(HC HCPHCpHCxHCpHChƃHǃfǃHǃHǃƃHHǃHǃHǃHǃHǃHǃHǃHǃHǃHHHǃHǃHǃǃǃHǃ H]mf"H5-DSH}HC%H5>UH:%H5dWH,<%HA H5{SHS=%HH;2%HHH [kHMHHUHuHuIIFIF0INIVIF@H]HEHtH P'Hb6SHjHH;Eu LHP[A^]6SIH]HEHtHO'H6SL]3S DUHAVSHPIHjHHE(5SHþ H5SHHCHCXHC`HCXHCHHC@HC8HC0HC(HC HCPHCpHCxHCpHChƃHǃfǃHǃHǃƃHHǃHǃHǃHǃHǃHǃHǃHǃHǃHHHǃHǃHǃǃǃHǃ H]b"H5}ASH}HJA%H5Q;UHK8%H5QaWH|9%HA H5jxSH:%HH;h/%HHH GYkHMHHUHuHuIIFIF0INIVIF@H]HEHtH\M'H3SHMjHH;Eu LHP[A^]3SIH]HEHtHM'Hm3SL0S DUHAVSHPIHjHHE(D3SHþ H:3SHHCHCXHC`HCXHCHHC@HC8HC0HC(HC HCPHCpHCxHCpHChƃHǃfǃHǃHǃƃHHǃHǃHǃHǃHǃHǃHǃHǃHǃHHHǃHǃHǃǃǃHǃ H]Mf"H5>SH}H>%H58UH5%H5^WH6%HA H5uSH7%HH;,%HHH VkHMHHUHuHuIIFIF0INIVIF@H]HEHtHJ'H1SHjHH;Eu LHP[A^]A1SIH]HEHtHgJ'H0SL-S DUHAVSHPIH;jHHE(0SHþ H0SHHCHCXHC`HCXHCHHC@HC8HC0HC(HC HCPHCpHCxHCpHChƃHǃfǃHǃHǃƃHHǃHǃHǃHǃHǃHǃHǃHǃHǃHHHǃHǃHǃǃǃHǃ H]]d"H5<SH}H;%H55UH2%H5[WH4%HA H5 +sSHC5%HH;*%HHH SkHMH̡HUHuHuIIFIF0INIVIF@H]HEHtHG'HR.SHjHH;Eu LHP[A^].SIH]HEHtHG'H .SLM+S DUHAVSHPIHjHHE(-SHþ H-SHHCHCXHC`HCXHCHHC@HC8HC0HC(HC HCPHCpHCxHCpHChƃHǃfǃHǃHǃƃHHǃHǃHǃHǃHǃHǃHǃHǃHǃHHHǃHǃHǃǃǃHǃ H]]"H5m9SH}H:9%H5A3UH;0%H5AYWHl1%HA H5ZpSH2%HH;X'%HHH 7QkHMHܟHUHuHuIIFIF0INIVIF@H]HEHtHLE'H+SH=jHH;Eu LHP[A^]+SIH]HEHtHE'H]+SL(S DUHAVSHPIHۏjHHE(4+SHþ H*+SHHCHCXHC`HCXHCHHC@HC8HC0HC(HC HCPHCpHCxHCpHChƃHǃfǃHǃHǃƃHHǃHǃHǃHǃHǃHǃHǃHǃHǃHHHǃHǃHǃǃǃHǃ H]["H56SH}H6%H50UH-%H5VWH.%HA H5mSH/%HH;$%HHH NkHMHHUHuHuIIFIF0INIVIF@H]HEHtHB'H(SHjHH;Eu LHP[A^]1)SIH]HEHtHWB'H(SL%S DUHAVSHPIH+jHHE((SHþ Hz(SHHCHCXHC`HCXHCHHC@HC8HC0HC(HC HCPHCpHCxHCpHChƃHǃfǃHǃHǃƃHHǃHǃHǃHǃHǃHǃHǃHǃHǃHHHǃHǃHǃǃǃHǃ H]MV"H5 4SH}H3%H5-UH*%H5SWH ,%HH +HQH5jSH,-%HH;!%HHH KkHMHHUHuHuIIFIF0INIVIF@H]HEHtH?'H;&SH֊jHH;Eu LHP[A^]z&SIH]HEHtH?'H%SL6#S fffff.UHAVSHPIHkjHHE(%SHþ H%SHHCHCXHC`HCXHCHHC@HC8HC0HC(HC HCPHCpHCxHCpHChƃHǃfǃHǃHǃƃHHǃHǃHǃHǃHǃHǃHǃHǃHǃHHHǃHǃHǃǃǃHǃ H]R"H5M1SH}H1%H5++UH(%H5!QWHL)%HH +HQH53hSHl*%HH;1%HHH IkHMHHUHuHuIIFIF0INIVIF@H]HEHtH%='H{#SHjHH;Eu LHP[A^]#SIH]HEHtH<'H6#SLv S fffff.UHAVSHPIHjHHE(#SHþ H"SHHCHCXHC`HCXHCHHC@HC8HC0HC(HC HCPHCpHCxHCpHChƃHǃfǃHǃHǃƃHHǃHǃHǃHǃHǃHǃHǃHǃHǃHHHǃHǃHǃǃǃHǃ H]P"H5.SH}HZ.%H5k(UH[%%H5aNWH&%HH HQH5seSH'%HH;q%HHH PFkHMHuHUHuHuIIFIF0INIVIF@H]HEHtHe:'H SHVjHH;Eu LHP[A^] SIH]HEHtH :'Hv SLS fffff.UHAVSHPIHjHHE(D SHþ H: SHHCHCXHC`HCXHCHHC@HC8HC0HC(HC HCPHCpHCxHCpHChƃHǃfǃHǃHǃƃHHǃHǃHǃHǃHǃHǃHǃHǃHǃHHHǃHǃHǃǃǃHǃ H]MM"H5+SH}H+%H5%UH"%H5KWH#%HH HQH5bSH$%HH;%HHH CkHMHuHUHuHuIIFIF0INIVIF@H]HEHtH7'HSHjHH;Eu LHP[A^]:SIH]HEHtH`7'HSLS fffff.UHAVSHPIH+jHHE(SHþ HzSHHCHCXHC`HCXHCHHC@HC8HC0HC(HC HCPHCpHCxHCpHChƃHǃfǃHǃHǃƃHHǃHǃHǃHǃHǃHǃHǃHǃHǃHHHǃHǃHǃǃǃHǃ H]MK"H5 )SH}H(%H5"UH%H5HWH !%HA H5_SH3"%HH;%HHH @kHMH|HUHuHuIIFIF0INIVIF@H]HEHtH4'HBSHjHH;Eu LHP[A^]SIH]HEHtH4'HSL=S DUHAVSHPIH{jHHE(SHþ HSHHCHCXHC`HCXHCHHC@HC8HC0HC(HC HCPHCpHCxHCpHChƃHǃfǃHǃHǃƃHHǃHǃHǃHǃHǃHǃHǃHǃHǃHHHǃHǃHǃǃǃHǃ H]G"H5]&SH}H*&%H5; UH+%H51FWH\%HA H5J]SH%HH;H%HHH '>kHMHHUHuHuIIFIF0INIVIF@H]HEHtH<2'HSH-}jHH;Eu LHP[A^]SIH]HEHtH1'HMSLS DUHAVSHPIH|jHHE($SHþ HSHHCHCXHC`HCXHCHHC@HC8HC0HC(HC HCPHCpHCxHCpHChƃHǃfǃHǃHǃƃHHǃHǃHǃHǃHǃHǃHǃHǃHǃHHHǃHǃHǃǃǃHǃ H]K"H5#SH}Hz#%H5UH{%H5CWH%HH +HQH5ZSH%HH;%HHH p;kHMHHUHuHuIIFIF0INIVIF@H]HEHtH/'HSHvzjHH;Eu LHP[A^]SIH]HEHtH@/'HSLS fffff.UHAVSHPIH zjHHE(dSHþ HZSHHCHCXHC`HCXHCHHC@HC8HC0HC(HC HCPHCpHCxHCpHChƃHǃfǃHǃHǃƃHHǃHǃHǃHǃHǃHǃHǃHǃHǃHHHǃHǃHǃǃǃHǃ H]-I"H5 SH}H %H5UH%H5@WH%HH HQH5WSH %HH;%HHH 8kHMHHUHuHuIIFIF0INIVIF@H]HEHtH,'HSHwjHH;Eu LHP[A^]ZSIH]HEHtH,'HSLS fffff.UHAVSHPIHKwjHHE(SHþ HSHHCHCXHC`HCXHCHHC@HC8HC0HC(HC HCPHCpHCxHCpHChƃHǃfǃHǃHǃƃHHǃHǃHǃHǃHǃHǃHǃHǃHǃHHHǃHǃHǃǃǃHǃ H]mF"H5-SH}H%H5 UH%H5>WH,%HA H5USHS%HH; %HHH 5kHMHHUHuHuIIFIF0INIVIF@H]HEHtH *'HbSHtjHH;Eu LHP[A^]SIH]HEHtH)'HSL] S DUHAVSHPIHtjHHE(SHþ HSHHCHCXHC`HCXHCHHC@HC8HC0HC(HC HCPHCpHCxHCpHChƃHǃfǃHǃHǃƃHHǃHǃHǃHǃHǃHǃHǃHǃHǃHHHǃHǃHǃǃǃHǃ H]="H5}SH}HJ%H5fUHK%H5Q;WH|%HH +HQH5cRSH%HH;a %HHH @3kHMHHUHuHuIIFIF0INIVIF@H]HEHtHU''H SHFrjHH;Eu LHP[A^] SIH]HEHtH''Hf SL +S fffff.UHAVSHPIHqjHHE(4 SHþ H* SHHCHCXHC`HCXHCHHC@HC8HC0HC(HC HCPHCpHCxHCpHChƃHǃfǃHǃHǃƃHHǃHǃHǃHǃHǃHǃHǃHǃHǃHHHǃHǃHǃǃǃHǃ H]=:"H5SH}H%H5UH%H58WH%HH +HQH5OSH%HH;%HHH 0kHMH5HUHuHuIIFIF0INIVIF@H]HEHtH$'H +SHojHH;Eu LHP[A^]* SIH]HEHtHP$'H +SLS fffff.UHAVSHPIHojHHE(t +SHþ Hj +SHHCHCXHC`HCXHCHHC@HC8HC0HC(HC HCPHCpHCxHCpHChƃHǃfǃHǃHǃƃHHǃHǃHǃHǃHǃHǃHǃHǃHǃHHHǃHǃHǃǃǃHǃ H]}="H5SH}H%H5UH %H55WH %HH +HQH5LSH%HH;%HHH -kHMH$HUHuHuIIFIF0INIVIF@H]HEHtH!'H+SHljHH;Eu LHP[A^]jSIH]HEHtH!'HSL&S fffff.UHAVSHPIH[ljHHE(SHþ HSHHCHCXHC`HCXHCHHC@HC8HC0HC(HC HCPHCpHCxHCpHChƃHǃfǃHǃHǃƃHHǃHǃHǃHǃHǃHǃHǃHǃHǃHHHǃHǃHǃǃǃHǃ H]};"H5=SH}H +%H5& UH +%H53WH< %HH +HQH5#JSH\ %HH;!%HHH +kHMH%CHUHuHuIIFIF0INIVIF@H]HEHtH'HkSHjjHH;Eu LHP[A^]SIH]HEHtH'H&SLfS fffff.UHAVSHPIHijHHE(SHþ HSHHCHCXHC`HCXHCHHC@HC8HC0HC(HC HCPHCpHCxHCpHChƃHǃfǃHǃHǃƃHHǃHǃHǃHǃHǃHǃHǃHǃHǃHHHǃHǃHǃǃǃHǃ H]2"H5}SH}HJ%H5f +UHK%H5Q0WH|%HH HQH5cGSH %HH;a$HHH @(kHMH%mHUHuHuIIFIF0INIVIF@H]HEHtHU'HSHFgjHH;Eu LHP[A^]SIH]HEHtH'HfSLR fffff.UHAVSHPIHfjHHE(4SHþ H*SHHCHCXHC`HCXHCHHC@HC8HC0HC(HC HCPHCpHCxHCpHChƃHǃfǃHǃHǃƃHHǃHǃHǃHǃHǃHǃHǃHǃHǃHHHǃHǃHǃǃǃHǃ H]=/"H5 SH}H %H5UH%H5-WH%HH HQH5DSH%HH;$HHH %kHMH%kHUHuHuIIFIF0INIVIF@H]HEHtH'HRHdjHH;Eu LHP[A^]*SIH]HEHtHP'HRLR fffff.UHAVSHPIHdjHHE(tRHþ HjRHHCHCXHC`HCXHCHHC@HC8HC0HC(HC HCPHCpHCxHCpHChƃHǃfǃHǃHǃƃHHǃHǃHǃHǃHǃHǃHǃHǃHǃHHHǃHǃHǃǃǃHǃ H]}2"H5 +SH}H +%H5UH%H5*WH%HH HQH5ASH%HH;$HHH "kHMH%iHUHuHuIIFIF0INIVIF@H]HEHtH'H+RHajHH;Eu LHP[A^]jRIH]HEHtH'HRL&R fffff.UHAVSHPIH[ajHHE(RHþ HRHHCHCXHC`HCXHCHHC@HC8HC0HC(HC HCPHCpHCxHCpHChƃHǃfǃHǃHǃƃHHǃHǃHǃHǃHǃHǃHǃHǃHǃHHHǃHǃHǃǃǃHǃ H]}0"H5=SH}H +%H5&UH $H5(WH<%HH HQH5#?SH\%HH;!$HHH kHMH%gHUHuHuIIFIF0INIVIF@H]HEHtH'HkRH_jHH;Eu LHP[A^]RIH]HEHtH'H&RLfR fffff.UHAVSHPIH^jHHE(RHþ HRHHCHCXHC`HCXHCHHC@HC8HC0HC(HC HCPHCpHCxHCpHChƃHǃfǃHǃHǃƃHHǃHǃHǃHǃHǃHǃHǃHǃHǃHHHǃHǃHǃǃǃHǃ H]'"H5}SH}HJ%H5fTHK$H5Q%WH|$HH HQH5c<SH$HH;a$HHH @kHMH%eHUHuHuIIFIF0INIVIF@H]HEHtHU'HRHF\jHH;Eu LHP[A^]RIH]HEHtH'HfRLR fffff.UHAVSHPIH[jHHE(4RHþ H*RHHCHCXHC`HCXHCHHC@HC8HC0HC(HC HCPHCpHCxHCpHChƃHǃfǃHǃHǃƃHHǃHǃHǃHǃHǃHǃHǃHǃHǃHHHǃHǃHǃǃǃHǃ H]=$"H5SH}H%H5TH$H5"WH$HH HQH59SH$HH;$HHH kHMH%cHUHuHuIIFIF0INIVIF@H]HEHtH'HRHYjHH;Eu LHP[A^]*RIH]HEHtHP'HRLR fffff.UHAVSHPIHYjHHE(tRHþ HjRHHCHCXHC`HCXHCHHC@HC8HC0HC(HC HCPHCpHCxHCpHChƃHǃfǃHǃHǃƃHHǃHǃHǃHǃHǃHǃHǃHǃHǃHHHǃHǃHǃǃǃHǃ H]}'"H5RH}H$H5TH$H5WH$HH HQH56SH$HH;$HHH kHMH%aHUHuHuIIFIF0INIVIF@H]HEHtH 'H+RHVjHH;Eu LHP[A^]jRIH]HEHtH 'HRL&R fffff.UHAVSHPIH[VjHHE(RHþ HRHHCHCXHC`HCXHCHHC@HC8HC0HC(HC HCPHCpHCxHCpHChƃHǃfǃHǃHǃƃHHǃHǃHǃHǃHǃHǃHǃHǃHǃHHHǃHǃHǃǃǃHǃ H]}%"H5=RH}H +$H5&TH $H5WH<$HH HQH5#4SH\$HH;!$HHH kHMH%_HUHuHuIIFIF0INIVIF@H]HEHtH 'HkRHTjHH;Eu LHP[A^]RIH]HEHtH'H&RLfR fffff.UHAVSHPIHSjHHE(RHþ HRHHCHCXHC`HCXHCHHC@HC8HC0HC(HC HCPHCpHCxHCpHChƃHǃfǃHǃHǃƃHHǃHǃHǃHǃHǃHǃHǃHǃHǃHHHǃHǃHǃǃǃHǃ H]"H5}RH}HJ$H5fTHK$H5QWH|$HH HQH5c1SH$HH;a$HHH @kHMH%]HUHuHuIIFIF0INIVIF@H]HEHtHU'HRHFQjHH;Eu LHP[A^]RIH]HEHtH'HfRLR fffff.UHAVSHPIHPjHHE(4RHþ H*RHHCHCXHC`HCXHCHHC@HC8HC0HC(HC HCPHCpHCxHCpHChƃHǃfǃHǃHǃƃHHǃHǃHǃHǃHǃHǃHǃHǃHǃHHHǃHǃHǃǃǃHǃ H]"H5RH}H$H5TH$H5WH$HH HQH5.SH$HH;$HHH kHMHU~HUHuHuIIFIF0INIVIF@H]HEHtH'HRHNjHH;Eu LHP[A^]*RIH]HEHtHP'HRLR fffff.UHAVSHPIHNjHHE(tRHþ HjRHHCHCXHC`HCXHCHHC@HC8HC0HC(HC HCPHCpHCxHCpHChƃHǃfǃHǃHǃƃHHǃHǃHǃHǃHǃHǃHǃHǃHǃHHHǃHǃHǃǃǃHǃ H]="H5RH}H$H5TH$H5WH$HA H5+SH#$HH;$HHH kHMH<HUHuHuIIFIF0INIVIF@H]HEHtH'H2RHKjHH;Eu LHP[A^]qRIH]HEHtH'HRL-R DUHAVSHPIHkKjHHE(RHþ HRHHCHCXHC`HCXHCHHC@HC8HC0HC(HC HCPHCpHCxHCpHChƃHǃfǃHǃHǃƃHHǃHǃHǃHǃHǃHǃHǃHǃHǃHHHǃHǃHǃǃǃHǃ H]"H5MRH}H$H56TH$H5!WHL$HA H5:)SHs$HH;8$HHH  +kHMHLHUHuHuIIFIF0INIVIF@H]HEHtH,&HRHIjHH;Eu LHP[A^]RIH]HEHtH&H=RL}R DUHAVSHPIHHjHHE(RHþ H +RHHCHCXHC`HCXHCHHC@HC8HC0HC(HC HCPHCpHCxHCpHChƃHǃfǃHǃHǃƃHHǃHǃHǃHǃHǃHǃHǃHǃHǃHHHǃHǃHǃǃǃHǃ H]"H5RH}Hj$H5THk$H5qWH$HA H5&SH$HH;$HHH gkHMH\HUHuHuIIFIF0INIVIF@H]HEHtH|&HRHmFjHH;Eu LHP[A^]RIH]HEHtH7&HRLR DUHAVSHPIH FjHHE(dRHþ HZRHHCHCXHC`HCXHCHHC@HC8HC0HC(HC HCPHCpHCxHCpHChƃHǃfǃHǃHǃƃHHǃHǃHǃHǃHǃHǃHǃHǃHǃHHHǃHǃHǃǃǃHǃ H]-"H5RH}H$H5TH$H5 WH$HA H5#SH$HH;$HHH kHMHlHUHuHuIIFIF0INIVIF@H]HEHtH&H"RHCjHH;Eu LHP[A^]aRIH]HEHtH&HRLR DUHAVSHPIH[CjHHE(RHþ HRHHCHCXHC`HCXHCHHC@HC8HC0HC(HC HCPHCpHCxHCpHChƃHǃfǃHǃHǃƃHHǃHǃHǃHǃHǃHǃHǃHǃHǃHHHǃHǃHǃǃǃHǃ H]"H5=RH}H +$H5&TH $H5 +WH<$HA H5*!SHc$HH;($HHH kHMH|HUHuHuIIFIF0INIVIF@H]HEHtH&HrRH AjHH;Eu LHP[A^]RIH]HEHtH&H-RLmR DUHAVSHPIH@jHHE(RHþ HRHHCHCXHC`HCXHCHHC@HC8HC0HC(HC HCPHCpHCxHCpHChƃHǃfǃHǃHǃƃHHǃHǃHǃHǃHǃHǃHǃHǃHǃHHHǃHǃHǃǃǃHǃ H] "H5RH}HZ$H5vTH[$H5aWH$HA H5zSH$HH;x$HHH WjHMHHUHuHuIIFIF0INIVIF@H]HEHtHl&HRH]>jHH;Eu LHP[A^]RIH]HEHtH'&H}RLR DUHAVSHPIH=jHHE(TRHþ HJRHHCHCXHC`HCXHCHHC@HC8HC0HC(HC HCPHCpHCxHCpHChƃHǃfǃHǃHǃƃHHǃHǃHǃHǃHǃHǃHǃHǃHǃHHHǃHǃHǃǃǃHǃ H]"H5RH}H$H5TH$H5WH$HH +HQH5SH$HH;$HHH jHMHHUHuHuIIFIF0INIVIF@H]HEHtH&H RH;jHH;Eu LHP[A^]JRIH]HEHtHp&HRLR fffff.UHAVSHPIH;;jHHE(RHþ HRHHCHCXHC`HCXHCHHC@HC8HC0HC(HC HCPHCpHCxHCpHChƃHǃfǃHǃHǃƃHHǃHǃHǃHǃHǃHǃHǃHǃHǃHHHǃHǃHǃǃǃHǃ H]"H5RH}H$H5TH$H5WH$HH +HQH5SH<$HH;$HHH jHMHHUHuHuIIFIF0INIVIF@H]HEHtH&HKRH8jHH;Eu LHP[A^]RIH]HEHtH&HRLFR fffff.UHAVSHPIH{8jHHE(RHþ HRHHCHCXHC`HCXHCHHC@HC8HC0HC(HC HCPHCpHCxHCpHChƃHǃfǃHǃHǃƃHHǃHǃHǃHǃHǃHǃHǃHǃHǃHHHǃHǃHǃǃǃHǃ H]"H5]RH}H*$H5PTH+$H51VH\$HH +HQH5CSH|$HH;A$HHH jHMHHUHuHuIIFIF0INIVIF@H]HEHtH5&HRH&6jHH;Eu LHP[A^]RIH]HEHtH&HFRLR fffff.UHAVSHPIH5jHHE(RHþ H +RHHCHCXHC`HCXHCHHC@HC8HC0HC(HC HCPHCpHCxHCpHChƃHǃfǃHǃHǃƃHHǃHǃHǃHǃHǃHǃHǃHǃHǃHHHǃHǃHǃǃǃHǃ H]!H5RH}Hj$H5THk$H5qVH$HH HQH5SH$HH;$HHH `jHMHHUHuHuIIFIF0INIVIF@H]HEHtHu&HRHf3jHH;Eu LHP[A^] +RIH]HEHtH0&HRLR fffff.UHAVSHPIH2jHHE(TRHþ HJRHHCHCXHC`HCXHCHHC@HC8HC0HC(HC HCPHCpHCxHCpHChƃHǃfǃHǃHǃƃHHǃHǃHǃHǃHǃHǃHǃHǃHǃHHHǃHǃHǃǃǃHǃ H]]!H5RH}H$H5TH$H5VH$HH HQH5SH$HH;$HHH jHMHHUHuHuIIFIF0INIVIF@H]HEHtH&H RH0jHH;Eu LHP[A^]JRIH]HEHtHp&HRLR fffff.UHAVSHPIH;0jHHE(RHþ HRHHCHCXHC`HCXHCHHC@HC8HC0HC(HC HCPHCpHCxHCpHChƃHǃfǃHǃHǃƃHHǃHǃHǃHǃHǃHǃHǃHǃHǃHHHǃHǃHǃǃǃHǃ H]!H5RH}H$H5TH$H5VH$HH HQH5SH<$HH;$HHH jHMHHUHuHuIIFIF0INIVIF@H]HEHtH&HKRH-jHH;Eu LHP[A^]RIH]HEHtH&HRLFR fffff.UHAVSHPIH{-jHHE(RHþ HRHHCHCXHC`HCXHCHHC@HC8HC0HC(HC HCPHCpHCxHCpHChƃHǃfǃHǃHǃƃHHǃHǃHǃHǃHǃHǃHǃHǃHǃHHHǃHǃHǃǃǃHǃ H]!H5]RH}H*$H5PTH+$H51VH\$HA H5J SH$HH;H$HHH 'jHMHHUHuHuIIFIF0INIVIF@H]HEHtH<&HRH-+jHH;Eu LHP[A^]RIH]HEHtH&HMRLR DUHAVSHPIH*jHHE($RHþ HRHHCHCXHC`HCXHCHHC@HC8HC0HC(HC HCPHCpHCxHCpHChƃHǃfǃHǃHǃƃHHǃHǃHǃHǃHǃHǃHǃHǃHǃHHHǃHǃHǃǃǃHǃ H]-!H5RH}Hz$H5TH{$H5VH$HA H5SH$HH;蘿$HHH wjHMH HUHuHuIIFIF0INIVIF@H]HEHtH&HRH}(jHH;Eu LHP[A^]!RIH]HEHtHG&HRLR DUHAVSHPIH(jHHE(tRHþ HjRHHCHCXHC`HCXHCHHC@HC8HC0HC(HC HCPHCpHCxHCpHChƃHǃfǃHǃHǃƃHHǃHǃHǃHǃHǃHǃHǃHǃHǃHHHǃHǃHǃǃǃHǃ H]}!H5RH}H$H5TH$H5VH$HA H5SH#$HH;$HHH jHMHHUHuHuIIFIF0INIVIF@H]HEHtH&H2RH%jHH;Eu LHP[A^]qRIH]HEHtH&HRL-R DUHAVSHPIHk%jHHE(RHþ HRHHCHCXHC`HCXHCHHC@HC8HC0HC(HC HCPHCpHCxHCpHChƃHǃfǃHǃHǃƃHHǃHǃHǃHǃHǃHǃHǃHǃHǃHHHǃHǃHǃǃǃHǃ H]!H5MRH}H$H5KTH$H5!VHL$HH +HQH53SHl$HH;1$HHH jHMH%HUHuHuIIFIF0INIVIF@H]HEHtH%&H{RH#jHH;Eu LHP[A^]躾RIH]HEHtH&H6RLvR fffff.UHAVSHPIH"jHHE(RHþ HRHHCHCXHC`HCXHCHHC@HC8HC0HC(HC HCPHCpHCxHCpHChƃHǃfǃHǃHǃƃHHǃHǃHǃHǃHǃHǃHǃHǃHǃHHHǃHǃHǃǃǃHǃ H] !H5RH}HZ$H5TH[$H5aVH$HH +HQH5sSH$HH;q$HHH PjHMH%HUHuHuIIFIF0INIVIF@H]HEHtHe&H軻RHV jHH;Eu LHP[A^]RIH]HEHtH &HvRL趸R fffff.UHAVSHPIHjHHE(DRHþ H:RHHCHCXHC`HCXHCHHC@HC8HC0HC(HC HCPHCpHCxHCpHChƃHǃfǃHǃHǃƃHHǃHǃHǃHǃHǃHǃHǃHǃHǃHHHǃHǃHǃǃǃHǃ H]M!H5RH}H$H5TH蛽$H5VH̾$HH +HQH5RH$HH;豴$HHH jHMH%HUHuHuIIFIF0INIVIF@H]HEHtH&HRHjHH;Eu LHP[A^]:RIH]HEHtH`&H趸RLR fffff.UHAVSHPIH+jHHE(脸RHþ HzRHHCHCXHC`HCXHCHHC@HC8HC0HC(HC HCPHCpHCxHCpHChƃHǃfǃHǃHǃƃHHǃHǃHǃHǃHǃHǃHǃHǃHǃHHHǃHǃHǃǃǃHǃ H]M!H5 RH}H$H5 THۺ$H5VH $HH +HQH5RH,$HH;$HHH jHMH%HUHuHuIIFIF0INIVIF@H]HEHtH&H;RHjHH;Eu LHP[A^]zRIH]HEHtH&HRL6R fffff.UHAVSHPIHkjHHE(ĵRHþ H躵RHHCHCXHC`HCXHCHHC@HC8HC0HC(HC HCPHCpHCxHCpHChƃHǃfǃHǃHǃƃHHǃHǃHǃHǃHǃHǃHǃHǃHǃHHHǃHǃHǃǃǃHǃ H]!H5MRH}H$H5KTH$H5!VHL$HH HQH53RHl$HH;1$HHH jHMH%HUHuHuIIFIF0INIVIF@H]HEHtH%&H{RHjHH;Eu LHP[A^]躳RIH]HEHtH&H6RLvR fffff.UHAVSHPIHjHHE(RHþ HRHHCHCXHC`HCXHCHHC@HC8HC0HC(HC HCPHCpHCxHCpHChƃHǃfǃHǃHǃƃHHǃHǃHǃHǃHǃHǃHǃHǃHǃHHHǃHǃHǃǃǃHǃ H] !H5RH}HZ$H5TH[$H5aVH茶$HH HQH5sRH謷$HH;q$HHH PjHMH%HUHuHuIIFIF0INIVIF@H]HEHtHe&H軰RHVjHH;Eu LHP[A^]RIH]HEHtH &HvRL趭R fffff.UHAVSHPIHjHHE(DRHþ H:RHHCHCXHC`HCXHCHHC@HC8HC0HC(HC HCPHCpHCxHCpHChƃHǃfǃHǃHǃƃHHǃHǃHǃHǃHǃHǃHǃHǃHǃHHHǃHǃHǃǃǃHǃ H]M!H5ͻRH}H蚻$H5˵TH蛲$H5VH̳$HH HQH5RH$HH;豩$HHH jHMH%HUHuHuIIFIF0INIVIF@H]HEHtH&HRHjHH;Eu LHP[A^]:RIH]HEHtH`&H趭RLR fffff.UHAVSHPIH+jHHE(脭RHþ HzRHHCHCXHC`HCXHCHHC@HC8HC0HC(HC HCPHCpHCxHCpHChƃHǃfǃHǃHǃƃHHǃHǃHǃHǃHǃHǃHǃHǃHǃHHHǃHǃHǃǃǃHǃ H]M!H5 RH}Hڸ$H5 THۯ$H5VH $HH HQH5RH,$HH;$HHH jHMH%HUHuHuIIFIF0INIVIF@H]HEHtH&H;RHjHH;Eu LHP[A^]zRIH]HEHtH&HRL6R fffff.UHAVSHPIHkjHHE(ĪRHþ H躪RHHCHCXHC`HCXHCHHC@HC8HC0HC(HC HCPHCpHCxHCpHChƃHǃfǃHǃHǃƃHHǃHǃHǃHǃHǃHǃHǃHǃHǃHHHǃHǃHǃǃǃHǃ H]!H5MRH}H$H5KTH$H5!VHL$HA H5:RHs$HH;8$HHH jHMH,HUHuHuIIFIF0INIVIF@H]HEHtH,&H肨RH jHH;Eu LHP[A^]RIH]HEHtH&H=RL}R DUHAVSHPIH jHHE(RHþ H +RHHCHCXHC`HCXHCHHC@HC8HC0HC(HC HCPHCpHCxHCpHChƃHǃfǃHǃHǃƃHHǃHǃHǃHǃHǃHǃHǃHǃHǃHHHǃHǃHǃǃǃHǃ H]!H5RH}Hj$H5THk$H5qVH蜫$HA H5RHì$HH;舡$HHH gjHMH<HUHuHuIIFIF0INIVIF@H]HEHtH|&HҥRHm +jHH;Eu LHP[A^]RIH]HEHtH7&H荥RL͢R DUHAVSHPIH +jHHE(dRHþ HZRHHCHCXHC`HCXHCHHC@HC8HC0HC(HC HCPHCpHCxHCpHChƃHǃfǃHǃHǃƃHHǃHǃHǃHǃHǃHǃHǃHǃHǃHHHǃHǃHǃǃǃHǃ H]m!H5RH}H躰$H5TH軧$H5VH$HA H5RH$HH;؞$HHH jHMHLHUHuHuIIFIF0INIVIF@H]HEHtH̼&H"RHjHH;Eu LHP[A^]aRIH]HEHtH臼&HݢRLR DUHAVSHPIH[jHHE(财RHþ H誢RHHCHCXHC`HCXHCHHC@HC8HC0HC(HC HCPHCpHCxHCpHChƃHǃfǃHǃHǃƃHHǃHǃHǃHǃHǃHǃHǃHǃHǃHHHǃHǃHǃǃǃHǃ H]}!H5=RH}H +$H5;TH $H5VH<$HA H5*RHc$HH;($HHH jHMH\HUHuHuIIFIF0INIVIF@H]HEHtH&HrRH jHH;Eu LHP[A^]豠RIH]HEHtH׹&H-RLmR DUHAVSHPIHjHHE(RHþ HRHHCHCXHC`HCXHCHHC@HC8HC0HC(HC HCPHCpHCxHCpHChƃHǃfǃHǃHǃƃHHǃHǃHǃHǃHǃHǃHǃHǃHǃHHHǃHǃHǃǃǃHǃ H]!H5RH}HZ$H5TH[$H5aVH茣$HH +HQH5sRH謤$HH;q$HHH PjHMHeHUHuHuIIFIF0INIVIF@H]HEHtHe&H軝RHVjHH;Eu LHP[A^]RIH]HEHtH &HvRL趚R fffff.UHAVSHPIHjHHE(DRHþ H:RHHCHCXHC`HCXHCHHC@HC8HC0HC(HC HCPHCpHCxHCpHChƃHǃfǃHǃHǃƃHHǃHǃHǃHǃHǃHǃHǃHǃHǃHHHǃHǃHǃǃǃHǃ H]M!H5ͨRH}H蚨$H5բTH蛟$H5VH̠$HH +HQH5RH$HH;豖$HHH jHMHեHUHuHuIIFIF0INIVIF@H]HEHtH襴&HRHiHH;Eu LHP[A^]:RIH]HEHtH`&H趚RLR fffff.UHAVSHPIH+iHHE(脚RHþ HzRHHCHCXHC`HCXHCHHC@HC8HC0HC(HC HCPHCpHCxHCpHChƃHǃfǃHǃHǃƃHHǃHǃHǃHǃHǃHǃHǃHǃHǃHHHǃHǃHǃǃǃHǃ H]M!H5 RH}Hڥ$H5THۜ$H5VH $HH +HQH5RH,$HH;$HHH нjHMHHUHuHuIIFIF0INIVIF@H]HEHtH&H;RHiHH;Eu LHP[A^]zRIH]HEHtH蠱&HRL6R fffff.UHAVSHPIHkiHHE(ėRHþ H躗RHHCHCXHC`HCXHCHHC@HC8HC0HC(HC HCPHCpHCxHCpHChƃHǃfǃHǃHǃƃHHǃHǃHǃHǃHǃHǃHǃHǃHǃHHHǃHǃHǃǃǃHǃ H]!H5MRH}H$H5UTH$H5!VHL$HH HQH53RHl$HH;1$HHH jHMHHUHuHuIIFIF0INIVIF@H]HEHtH%&H{RHiHH;Eu LHP[A^]躕RIH]HEHtH&H6RLvR fffff.UHAVSHPIHiHHE(RHþ HRHHCHCXHC`HCXHCHHC@HC8HC0HC(HC HCPHCpHCxHCpHChƃHǃfǃHǃHǃƃHHǃHǃHǃHǃHǃHǃHǃHǃHǃHHHǃHǃHǃǃǃHǃ H] !H5RH}HZ$H5TH[$H5aVH茘$HH HQH5sRH謙$HH;q$HHH PjHMHHUHuHuIIFIF0INIVIF@H]HEHtHe&H軒RHViHH;Eu LHP[A^]RIH]HEHtH &HvRL趏R fffff.UHAVSHPIHiHHE(DRHþ H:RHHCHCXHC`HCXHCHHC@HC8HC0HC(HC HCPHCpHCxHCpHChƃHǃfǃHǃHǃƃHHǃHǃHǃHǃHǃHǃHǃHǃHǃHHHǃHǃHǃǃǃHǃ H] !H5͝RH}H蚝$H5՗TH蛔$H5VH̕$HH HQH5RH$HH;豋$HHH jHMHHUHuHuIIFIF0INIVIF@H]HEHtH襩&HRHiHH;Eu LHP[A^]:RIH]HEHtH`&H趏RLR fffff.UHAVSHPIH+iHHE(脏RHþ HzRHHCHCXHC`HCXHCHHC@HC8HC0HC(HC HCPHCpHCxHCpHChƃHǃfǃHǃHǃƃHHǃHǃHǃHǃHǃHǃHǃHǃHǃHHHǃHǃHǃǃǃHǃ H]M!H5 RH}Hښ$H5THۑ$H5VH $HA H5RH3$HH;$HHH ײjHMHHUHuHuIIFIF0INIVIF@H]HEHtH&HBRHiHH;Eu LHP[A^]聍RIH]HEHtH触&HRL=R DUHAVSHPIH{iHHE(ԌRHþ HʌRHHCHCXHC`HCXHCHHC@HC8HC0HC(HC HCPHCpHCxHCpHChƃHǃfǃHǃHǃƃHHǃHǃHǃHǃHǃHǃHǃHǃHǃHHHǃHǃHǃǃǃHǃ H]ݹ!H5]RH}H*$H5eTH+$H51VH\$HA H5JRH胑$HH;H$HHH 'jHMHHUHuHuIIFIF0INIVIF@H]HEHtH<&H蒊RH-iHH;Eu LHP[A^]ъRIH]HEHtH&HMRL荇R DUHAVSHPIHiHHE($RHþ HRHHCHCXHC`HCXHCHHC@HC8HC0HC(HC HCPHCpHCxHCpHChƃHǃfǃHǃHǃƃHHǃHǃHǃHǃHǃHǃHǃHǃHǃHHHǃHǃHǃǃǃHǃ H]!H5RH}Hz$H5TH{$H5VH謍$HA H5RHӎ$HH;蘃$HHH wjHMHHUHuHuIIFIF0INIVIF@H]HEHtH茡&HRH}iHH;Eu LHP[A^]!RIH]HEHtHG&H蝇RL݄R DUHAVSHPIHiHHE(tRHþ HjRHHCHCXHC`HCXHCHHC@HC8HC0HC(HC HCPHCpHCxHCpHChƃHǃfǃHǃHǃƃHHǃHǃHǃHǃHǃHǃHǃHǃHǃHHHǃHǃHǃǃǃHǃ H]=!H5RH}Hʒ$H5THˉ$H5ѲVH$HH +HQH5RH$HH;$HHH jHMHŴHUHuHuIIFIF0INIVIF@H]HEHtH՞&H+RHiHH;Eu LHP[A^]jRIH]HEHtH萞&HRL&R fffff.UHAVSHPIH[iHHE(贄RHþ H誄RHHCHCXHC`HCXHCHHC@HC8HC0HC(HC HCPHCpHCxHCpHChƃHǃfǃHǃHǃƃHHǃHǃHǃHǃHǃHǃHǃHǃHǃHHHǃHǃHǃǃǃHǃ H]轱!H5=RH}H +$H5UTH $H5VH<$HH +HQH5#RH\$HH;!~$HHH jHMHEHUHuHuIIFIF0INIVIF@H]HEHtH&HkRHiHH;Eu LHP[A^]誂RIH]HEHtHЛ&H&RLfR fffff.UHAVSHPIHiHHE(RHþ HRHHCHCXHC`HCXHCHHC@HC8HC0HC(HC HCPHCpHCxHCpHChƃHǃfǃHǃHǃƃHHǃHǃHǃHǃHǃHǃHǃHǃHǃHHHǃHǃHǃǃǃHǃ H]软!H5}RH}HJ$H5THK$H5QVH|$HH HQH5cRH蜆$HH;a{$HHH @jHMHHUHuHuIIFIF0INIVIF@H]HEHtHU&HRHFiHH;Eu LHP[A^]RIH]HEHtH&HfRL|R fffff.UHAVSHPIHiHHE(4RHþ H*RHHCHCXHC`HCXHCHHC@HC8HC0HC(HC HCPHCpHCxHCpHChƃHǃfǃHǃHǃƃHHǃHǃHǃHǃHǃHǃHǃHǃHǃHHHǃHǃHǃǃǃHǃ H]=!H5RH}H芊$H5ՄTH苁$H5VH輂$HH HQH5RH܃$HH;x$HHH jHMHHUHuHuIIFIF0INIVIF@H]HEHtH蕖&H|RHiHH;Eu LHP[A^]*}RIH]HEHtHP&H|RLyR fffff.UHAVSHPIHiHHE(t|RHþ Hj|RHHCHCXHC`HCXHCHHC@HC8HC0HC(HC HCPHCpHCxHCpHChƃHǃfǃHǃHǃƃHHǃHǃHǃHǃHǃHǃHǃHǃHǃHHHǃHǃHǃǃǃHǃ H]=!H5RH}Hʇ$H5TH~$H5ѧVH$HH HQH5RH$HH;u$HHH jHMHHUHuHuIIFIF0INIVIF@H]HEHtHՓ&H+zRHiHH;Eu LHP[A^]jzRIH]HEHtH萓&HyRL&wR fffff.UHAVSHPIH[iHHE(yRHþ HyRHHCHCXHC`HCXHCHHC@HC8HC0HC(HC HCPHCpHCxHCpHChƃHǃfǃHǃHǃƃHHǃHǃHǃHǃHǃHǃHǃHǃHǃHHHǃHǃHǃǃǃHǃ H]}!H5=RH}H +$H5UTH |$H5VH<}$HA H5*RHc~$HH;(s$HHH jHMH,HUHuHuIIFIF0INIVIF@H]HEHtH&HrwRH iHH;Eu LHP[A^]wRIH]HEHtHא&H-wRLmtR DUHAVSHPIHiHHE(wRHþ HvRHHCHCXHC`HCXHCHHC@HC8HC0HC(HC HCPHCpHCxHCpHChƃHǃfǃHǃHǃƃHHǃHǃHǃHǃHǃHǃHǃHǃHǃHHHǃHǃHǃǃǃHǃ H] !H5RH}HZ$H5|TH[y$H5aVHz$HA H5zRH{$HH;xp$HHH WjHMH<HUHuHuIIFIF0INIVIF@H]HEHtHl&HtRH]iHH;Eu LHP[A^]uRIH]HEHtH'&H}tRLqR DUHAVSHPIHiHHE(TtRHþ HJtRHHCHCXHC`HCXHCHHC@HC8HC0HC(HC HCPHCpHCxHCpHChƃHǃfǃHǃHǃƃHHǃHǃHǃHǃHǃHǃHǃHǃHǃHHHǃHǃHǃǃǃHǃ H]!H5RH}H$H5yTHv$H5VHw$HA H5ʶRHy$HH;m$HHH jHMHLHUHuHuIIFIF0INIVIF@H]HEHtH輋&HrRHiHH;Eu LHP[A^]QrRIH]HEHtHw&HqRL oR DUHAVSHPIHKiHHE(qRHþ HqRHHCHCXHC`HCXHCHHC@HC8HC0HC(HC HCPHCpHCxHCpHChƃHǃfǃHǃHǃƃHHǃHǃHǃHǃHǃHǃHǃHǃHǃHHHǃHǃHǃǃǃHǃ H]m!H5-}RH}H|$H5LwTHs$H5VH,u$HH +HQH5RHLv$HH;k$HHH jHMHUHUHuHuIIFIF0INIVIF@H]HEHtH&H[oRHiHH;Eu LHP[A^]oRIH]HEHtH&HoRLVlR fffff.UHAVSHPIHiHHE(nRHþ HnRHHCHCXHC`HCXHCHHC@HC8HC0HC(HC HCPHCpHCxHCpHChƃHǃfǃHǃHǃƃHHǃHǃHǃHǃHǃHǃHǃHǃHǃHHHǃHǃHǃǃǃHǃ H]!H5mzRH}H:z$H5tTH;q$H5AVHlr$HH +HQH5SRHs$HH;Qh$HHH 0jHMHU HUHuHuIIFIF0INIVIF@H]HEHtHE&HlRH6iHH;Eu LHP[A^]lRIH]HEHtH&HVlRLiR fffff.UHAVSHPIHiHHE($lRHþ HlRHHCHCXHC`HCXHCHHC@HC8HC0HC(HC HCPHCpHCxHCpHChƃHǃfǃHǃHǃƃHHǃHǃHǃHǃHǃHǃHǃHǃHǃHHHǃHǃHǃǃǃHǃ H]!H5wRH}Hzw$H5qTH{n$H5VHo$HH HQH5RHp$HH;e$HHH pjHMH#HUHuHuIIFIF0INIVIF@H]HEHtH腃&HiRHviHH;Eu LHP[A^]jRIH]HEHtH@&HiRLfR fffff.UHAVSHPIH iHHE(diRHþ HZiRHHCHCXHC`HCXHCHHC@HC8HC0HC(HC HCPHCpHCxHCpHChƃHǃfǃHǃHǃƃHHǃHǃHǃHǃHǃHǃHǃHǃHǃHHHǃHǃHǃǃǃHǃ H]m!H5tRH}Ht$H5 oTHk$H5VHl$HH HQH5ӫRH n$HH;b$HHH jHMH!HUHuHuIIFIF0INIVIF@H]HEHtHŀ&HgRHiHH;Eu LHP[A^]ZgRIH]HEHtH耀&HfRLdR fffff.UHAVSHPIHKiHHE(fRHþ HfRHHCHCXHC`HCXHCHHC@HC8HC0HC(HC HCPHCpHCxHCpHChƃHǃfǃHǃHǃƃHHǃHǃHǃHǃHǃHǃHǃHǃHǃHHHǃHǃHǃǃǃHǃ H]m!H5-rRH}Hq$H5LlTHh$H5VH,j$HH HQH5RHLk$HH;`$HHH jHMHHUHuHuIIFIF0INIVIF@H]HEHtH~&H[dRHiHH;Eu LHP[A^]dRIH]HEHtH}&HdRLVaR fffff.UHAVSHPIHiHHE(cRHþ HcRHHCHCXHC`HCXHCHHC@HC8HC0HC(HC HCPHCpHCxHCpHChƃHǃfǃHǃHǃƃHHǃHǃHǃHǃHǃHǃHǃHǃHǃHHHǃHǃHǃǃǃHǃ H]譑!H5moRH}H:o$H5iTH;f$H5AVHlg$HA H5ZRHh$HH;X]$HHH 7jHMH<6HUHuHuIIFIF0INIVIF@H]HEHtHL{&HaRH=iHH;Eu LHP[A^]aRIH]HEHtH{&H]aRL^R DUHAVSHPIHiHHE(4aRHþ H*aRHHCHCXHC`HCXHCHHC@HC8HC0HC(HC HCPHCpHCxHCpHChƃHǃfǃHǃHǃƃHHǃHǃHǃHǃHǃHǃHǃHǃHǃHHHǃHǃHǃǃǃHǃ H]=!H5lRH}Hl$H5fTHc$H5VHd$HA H5RHe$HH;Z$HHH jHMHL4HUHuHuIIFIF0INIVIF@H]HEHtHx&H^RHiHH;Eu LHP[A^]1_RIH]HEHtHWx&H^RL[R DUHAVSHPIH+iHHE(^RHþ Hz^RHHCHCXHC`HCXHCHHC@HC8HC0HC(HC HCPHCpHCxHCpHChƃHǃfǃHǃHǃƃHHǃHǃHǃHǃHǃHǃHǃHǃHǃHHHǃHǃHǃǃǃHǃ H]M!H5 jRH}Hi$H5,dTH`$H5VH b$HA H5RH3c$HH;W$HHH ׁjHMH\2HUHuHuIIFIF0INIVIF@H]HEHtHu&HB\RHiHH;Eu LHP[A^]\RIH]HEHtHu&H[RL=YR DUHAWAVAUATSHHuiHHEHH~@HpHG8H;G0(HGiHH;EuHĈ[A\A]A^A_][R[RIHh. 6H5bTH cTH}LhHPH"AHcTHuLHCE1H5yiHLV[R[RIHh6H55bTH bTH}LhHPH!AHbTHuLHE1H5iH`LZR}ZRIHh-6H5aTH bTH}LhHPH!AHEbTHuLHBE1H5xiHLUZR IALhMIIALhMIIALhM:oIlIPt H`YRLmMt6HEL9t!HX@t Hx_YRHI9uH}LLmEYREuEu LhMu-H}YREtH}YRLhMHpL9HX@t HxXRHI9uIPt H`XRLmMt6HEL9t!HX@t HxXRHI9uH}LLmyXREuEu LhMu-'H}SXREtH}DXRLhMHpL9HX@t HxXRHI9uIPt H`WRLmMt6HEL9t!HX@t HxWRHI9uH}LLmWREuEuLhMu&^H}WREtH}{WRLhMt:HpL9tEHX@t HxPWRHI9uHhLp5WREtLXWRLhTR Lff.UHUHAWAVAUATSHVRIH}6H5^TH bTHXLEW)EHEE&HoverloadHEHmust be HEEed.AH5;XHXHMLE1H5iHLVR IALeMIIEt H}VRLeMt6HEL9t!HX@t HxURHI9uH}LLeURxuXuLeMu)_H}URXtHhURLeMt8HEL9tFHX@t HxkURHI9uH}LeVUREtLyURLRR Lfff.UH'UHUHAWAVAUATSHH`IHiHHEHW)EHEHHHLoI)tMMMII9LTRILuLuKHEM~,LHLURLLHMLeE11L`LL`MLeHL)HHHA|1HHHH HfDH I ILHMMWM9t)IrL)HHPHsLHuLibHzH)ǸLfHcHHcNHHcNHHcNHH HuHtHff.HcHHHuM)MIIHLHIcH4IqHIIIQPIc HH<AA|YHI< +H HAITI HH9u&HcH4H`HqHIcLHH<AHH`H~0E)LXt*HN0HV8H)HHH)vMMMLINHEHF0HV8H)HHHHHHF8MsHH`HA8L@W)EHEEL8McJ<QRHH]LPN4LuIIcHI)HLQRLuH`Hx0LP8I)I)IH8ALcH@L(LEIHHHE11ff.IJ JDOdK HPHtffffff.IcH+4|8HtItHcI4H4H)HtHHtMdK 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A HHuH-ADADDADD AD DADDADDADDADHH9uHHHBHHDAAHs 1MuzI@H)1LAALD L0AD AL0D@LPAD@ALPD`LpAD`ALpH HuMt(HID ADA H IuH9HEL$8L}ILmH}/LMHHGLHpHL0HPL^ICIK HHHL@ffffff.(]BH]]]HL9|IIII9|N(C) IM9Nofff.WC) IM9+LfAI9}L)LMKH]H(HuC) IM9M9LHLwL8MIFHDXAO,L@L)MIffff.IvCIs (Mukfffff.HHH H ILD ]] +]H]HH9u(Mt+HILHL ]H(HuC IIL;e6H+MHIKK H9sKK H9MII@HHQHs1LMHLMHEJItpI\pHBH)1DLDLDLDLDLDLD D H HuHt2ILMJHڐADA ADA H HuM9LmMDD)IEL)HtHff.CCIHuHraf.CCCDCDCDCDCD CD CDCDCDCDCDCDCDCDIM9u[A\A]A^A_]fffff.UH]f.UH]tPfDUHSPHgPH hHHKHHH[]@UHHhHHGHF]UH]f.UH]PfDUHH]2fUHH cH1H9NHD]DUHHh]UHAWAVAUATSHL*LI@HELHpHHIL9{HuLVXH^xIH]LM4MXMx H~0H^8L'H}H9aLMPML}HuL~PLCHuI)HvHuLMH}L]LeK4&AAu0HuH6LI<1(]LL9|LMIs nLMIrdHuN$fffff.I1I<1(]LL9|IqI<E1ې(B]MM9|II9uHuHH;U} LuHL]Le:ffffff.HxHUHR`HuH)HH9L]Le}Lt1HHL9I)I f.K4&A41HL9}LuH$DHXHUHR`L)HH9}Mt1HHIu~I)I fK4&A41HL9}LuHHHIuGfHXHUHR`H)HH9}Lt1HHIu1HHIu[A\A]A^A_]UHAWAVSHIHgHHE0PHL=gL;H{L_"HHEHEHULpHhHH/gHH;EuHH[A^A_]PL;IH{HCHt +UPIHHPLP UHSPHH{Ht H{#PHgHH{HCHHt[]P[]fff.UHSPHH{Ht H{PHgHH{HCHtPHH[]PUHSPHF(H1HHHHH[]ÐUHAWAVAUATSHHH}gHHEW)EIIHE)EHE)pHEHHD$(H HD$ Ho HD$HpHD$HEH$D$LELM1L[$IHU1L~"Iǀ} uELHHf&HL$HLI HpHLW)`)P)@)0) ))))HDžLeH]L)tcLIILH=dHPILLKHHL~LLH*PILMEHHpLHLHHt HZPHHHt HPBPH Ht H(*PHHt HPHHt%HPHpHu#HLHpHt HxPH}Ht H}PH}Ht H}PH@{gHH;EuHH[A\A]A^A_]PHP HHpH\HHpHtqHHHHuHHHt HPHHHuXH HudHHupHHu|HpHH}HH}HHP HPPH HtH(PHHtHxPHHtH`PHpHxRHHpHc=HHpHN(HHpH9HHpH$HxPH}HH}PH}HH}PHP fff.UHAWAVAUATSHH5ygHHELL0H HH8IffEHEIEMe I)tTH(MILH=L5PILuLuKHEMH(~LLPMLuH蒌IL跎ILH}褖&IH LHNL)tH8HHRH)H9LH8`&HAuDكH9HOII)IRHLH?II>MIM AoIH=LHH AoLHyH9HAoT Ao\0f89f89HqfoH AH HPHSMMI}HL)H9uVMEI] HL)H9uCL)t1I H;u+HH9uL)tB1fDII; -u HH9u%H8L,I}HtI}piL.IE8IMHI+E0HHHXIMPH`LhLpLxH H*@H@HHHH@WH*fօPHeiHEHXHELuLuH@H0LLmV3H}I9%HHP(H}Hfofof89I9gmHHfnfpHYHHwHH^H)fof.Aof89Ao\f89AoD f89AoL0f89HHuHtAof89AoTf89f89fpNf89fpf89f~H9HH)I f.9NHHu{HP H}HtxHHHtGAof89AoD f89AoT0Ao\0f89f89H~HH9|fofof89I9~ Ao f89fpf89fpf89f~HHw1HHfpH_HHrHH^H)1fofDAof89Ao\f89AoD 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H}NH&fHH;EuHH[A\A]A^A_].NH(N HHpH\HHpHtqHHHHuHHHt HhNHHHuXH HudHHupHHu|HpHH}HH}HHNN HPNH HtH(NHHtHNHHtHNHpHxRHHpHc=HHpHN(HHpH9HHpH$Hx@NH}HH}*NH}HH}NHTN fff.UHAWAVAUATSHH$fHHEL L8H(HHIW)EHEMnMf M)tWH0LHHH=L臿NIL}L}IHEMH0~LLLNML}HILEIL H}A%IH(LHNL)tHHSH)H9u;L2tHA%HH1I4$H}HHMMM]LL)H9u^MEI] HL)H9uKM)t$1ffffff.I H;u+HI9uL)t;1fDII; +u HH9uL3iI}HI}pL5bIE8IMHI+E0HHHXIMPH`LhLpLxH H*@H@HHHH@WH*PH|gHEHXHEH]H]H@H8LHd1H}H9mHtHP(H}Hu1I4$H}Ht H}7NH!fHH;ECH[A\A]A^A_]A.D@HPAHs1(ML)1(Ȑu(A .ATHC(TUVHz.HB((TUVAT.HJHB((TUVAL Hr.HBHH9lMt'I@u(A .HCHIuI4$H}HHP H}H;NH}8N IH}H9uHP H}HtmHuH}Hu_LN HP(H}HtDIH}Ht6IH}Ht(IH}HtIH}Ht IH}HtH}=NL}N DUH]f.UH]NfDUHSPHNH ΅gHHKHHH[]@UHHgHHGHF]UH]f.UH]餺NfDUHH]2fUHH aH1H9NHD]DUHHg]UHAWAVAUATSHHL.H2LMPLHIzpHuL)}MX IJ0IZ8HMH9WIJXIpHuMzxLHML<LELUL]ff.IxHL]I J49LEE4IrPL}OE1E1fff.I M<E1fDfCnfAn.rfA~MIII9|II9uLELUL]L}O HI;Rp}7MzxHIHL;mPfffff.E1O HI;Rp|HpIJ`HUH)HH9}(L|1IHL;m0ffffff.1IHL;m K<H迸NHH[A\A]A^A_]UHAWAVAUATSHH%fHHEL L0H8HHIW)EHEMnMf M)tWH(LHHH=tL'NIL}L}IHEMH(~LLLtNML}H-IL=IL 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))))HDžLeH]L)tcLIILH=dH6NILLKHHL~LLHzNILMEHHpLHLHHt H読NHHHt HP蒭NH Ht H(zNHHt HbNHHt%HJNHpHu#HLHpHt HxNH}Ht H}NH}Ht H}NHfHH;EuHH[A\A]A^A_].NH(N HHpH\HHpHtqHHHHuHHHt HhNHHHuXH HudHHupHHu|HpHH}HH}HHNN HPNH HtH(NHHtHȫNHHtH谫NHpHxRHHpHc=HHpHN(HHpH9HHpH$Hx@NH}HH}*NH}HH}NHTN fff.UHAWAVAUATSHHHfHHEW)EIIHE)EHE)pHEHUHD$(HkUHD$ HSHD$HpHD$HEH$D$LELM1g1Lo"IHU1L!Iǀ} uELHH,%HL"L/HHpHLW)`)P)@)0) ))))HDžLeH]L)tcLIILH=dHvNILLKHHL~LLH躪NILMEHHpLHL$ +HHt HNHHHt HPҨNH Ht H(躨NHHt H袨NHHt%H芨NHpHu#HL#HpHt HxYNH}Ht H}GNH}Ht H}5NH fHH;EuHH[A\A]A^A_]nNHhN HHpH\HHpHtqHHHHuHHHt H訧NHHHuXH HudHHupHHu|HpHH}HH}HH莤N HP8NH HtH( NHHtHNHHtHNHpHxRHHpHc=HHpHN(HHpH9HHpH$Hx耦NH}HH}jNH}HH}TNH蔣N fff.UHAWAVAUATSHH +fHHEL L8H(HHIW)EHEMnMf M)tWH0LHHH=LǥNIL}L}IHEMH0~LLLNML}HILB+IL H}/(%IH(LHNL)tHHSH)H9u<LrZH'%HHE1M$H}HHMMM]LL)H9u]MEI] HL)H9uJM)t#1fffff.I H;u+HI9uL)t;1fDII; +u HH9uLsOI}HI}pLuHIE8IMHI+E0HHHXIMPH`LhLpLxH H*@H@HHHH@WH*PHpgHEHXHEH]H]H@H8LH褯1H}H9HtHP(H}HuE1M$H}Ht H}vNHfHH;E[H[A\A]A^A_]AHHPHsE11HH)E11fD@t:A4AT9}<9}AAT9}GAT 9@}MHH9uSA4AT9|I9|LGAT9|LGAT 9@|LGHH9uHtIHffff.@tA9@}HHu@A9@|IHHuM$H}HHP H}HbNH}_N IH}H9uHP H}HtmHuH}Hu_L N HP(H}HtDIH}Ht6IH}Ht(IH}HtIH}Ht IH}HtH}dNL褞N fff.UH]f.UH]4NfDUHSPH'NH NmgHHKHHH[]@UHH-mgHHGHF]UH]f.UH]ĠNfDUHH]2fUHH aH1H9NHD]DUHHmg]UHAWAVAUATSHHL.H2LMHLHIypHuL)]MP II0IY8HMH97IIXIpHuMyxLHML<LELMLUff.IxHL]I J49LUEMqPL}OE11ffff.I M<E1fDDGA9DLIMIMI9|II9uLELMLUL}K4HI;Qp},MyxHIHL;mVe@1K4HI;Qp|HpII`HUH)HH9}L|1IHL;m!1IHL;m K<HNHH[A\A]A^A_]UHAWAVAUATSHHefHHEL L0H8HHIW)EHEMnMf M)tWH(LHHH=]LgNIL}L}IHEMH(~LLL负NML}HIL#IL H} %IH8LHPL)tH3HCH)H9uQLSH %HHAD@HpAH1M/NHMUI]HL)H9uXMEMM LL)H9uEL)t1fI H; u+HH9uM)tB1fDII; u HI9u%H8LGI}HI}pL@IE8IMHI+E0HHHXIMPH`LhLpLxH H*@H@HHHH@WH*PH%igHEHXHEH]H]H@H0LH-1H}H9 HtHP(H}HuHI<$H}Ht H}NHfHH;EH[A\A]A^A_]1I<$H}HuL)1fff.AAT9HOMH^9HNMA|HV9HNMA\ H~9HNMHH9uMt$Ifff.A9HOMHIuI<$H}H$(HP H}H fNH}cN IH}H9uHP H}HtmHuH}Hu_LN HP(H}HtDIH}Ht6IH}Ht(IH}HtIH}Ht IH}HtH}hNL託N UH]f.UH]DNfDUHSPH7NH fgHHKHHH[]@UHHfgHHGHF]UH]f.UH]ԙNfDUHH]2fUHH aH1H9NHD]DUHHfg]UHAWAVAUATSHHL.H2LMHLHIypHuL)]MP II0IY8HMH97IIXIpHuMyxLHML<LELMLUff.IxHL]I J49LEE4MQPL}OE11ffff.I M<E1fDC D9DMIOIMI9|II9uLELMLUL}K4HI;Qp}/MyxHIHL;mYh1K4HI;Qp|HpII`HUH)HH9}L|1IHL;m!1IHL;m K<HNHH[A\A]A^A_]UHAWAVSHIHyeHHE0җNHL=~zfL;H{LOu!HHEHEHULHagHHeHH;EuHH[A^A_]NL;IH{HCHt +ENIH8NLxN UHAWAVSHIHeHHE0NHL=yfL;H{Lt!HHEHEHULHbgHH_eHH;EuHH[A^A_]NL;IH{HCHt +腖NIHxNL踓N UHAWAVSHIHeHHE0RNHL=xfL;H{Ls!HHEHEHULHAcgHHeHH;EuHH[A^A_]ANL;IH{HCHt +ŕNIH踕NLN UHSPHH{Ht H{蓕NHNxfHH{HCHHt[]mN[]fff.UHSPHH{Ht H{CNHwfHH{HCHt#NHH[]NUHSPH~*F(Hvt1HH, 1HHHHH[]fff.UHAWAVAUATSHHHEeHHEW)EIIHE)EHE)pHEHG?HD$(H+?HD$ H?=HD$HpHD$HEH$D$LELMP1L/"IHU1Ly!Iǀ} uELHH%HLDLHHpHLW)`)P)@)0) ))))HDžLeH]L)tcLIILH=dH6NILLKHHL~LLHzNILMEHHpLHLHHt H誒NHHHt HP蒒NH Ht H(zNHHt HbNHHt%HJNHpHu#HLwHpHt HxNH}Ht H}NH}Ht H}NHeHH;EuHH[A\A]A^A_].NH(N HHpH\HHpHtqHHHHuHHHt HhNHHHuXH HudHHupHHu|HpHH}HH}HHNN HPNH HtH(NHHtHȐNHHtH谐NHpHxRHHpHc=HHpHN(HHpH9HHpH$Hx@NH}HH}*NH}HH}NHTN fff.UHAWAVAUATSHHHeHHEW)EIIHE)EHE)pHEH:HD$(Hk:HD$ H8HD$HpHD$HEH$D$LELM1L1Lo"IHU1Lu!Iǀ} uELHH%HL脿LHHpHLW)`)P)@)0) ))))HDžLeH]L)tcLIILH=dHvNILLKHHL~LLH躏NILMEHHpLHLD +HHt HNHHHt HPҍNH Ht H(躍NHHt H袍NHHt%H芍NHpHu#HL#sHpHt HxYNH}Ht H}GNH}Ht H}5NHeHH;EuHH[A\A]A^A_]nNHhN HHpH\HHpHtqHHHHuHHHt H訌NHHHuXH HudHHupHHu|HpHH}HH}HH莉N HP8NH HtH( NHHtHNHHtHNHpHxRHHpHc=HHpHN(HHpH9HHpH$Hx耋NH}HH}jNH}HH}TNH蔈N fff.UHAWAVAUATSHHeHHEL L8H(HHIfWf)EHEMnMf M)tWH0LHHH=LŊNIL}L}IHEMH0~LLLNML}HIL@IL H}- %IH(LHNL)tHHSH)H9u;Lp?H %HH1I4$H}HHMMM]LL)H9u\MEI] HL)H9uIM)t"1ffff.I H;u+HI9uL)t;1fDII; +u HH9uLs4I}HI}pLu-IE8IMHI+E0HHHXIMPH`LhLpLxH H*@H @HHHH@WH*PH|VgHEHXHEH]H]H@H8LH褔1H}H9HtHP(H}Hu1I4$H}Ht H}wNHeHH;EeH[A\A]A^A_]Af.D@HPAHs1f(ML)1f(fffff.uf(A f.ATHCf(fTfUfVHzf.HBf(f(fTfUfVATf.HJHBf(f(fTfUfVALHrf.HBHH9YMt&Iؐuf(A f.HCHIuI4$H}HHP H}HYNH}VN IH}H9uHP H}HtmHuH}Hu_LN HP(H}HtDIH}Ht6IH}Ht(IH}HtIH}Ht IH}HtH}[NL蛃N UH]f.UH]4NfDUHSPH'NH SgHHKHHH[]@UHHSgHHGHF]UH]f.UH]ąNfDUHH]2fUHH aH1H9NHD]DUHH}Sg]UHAWAVAUATSHHL.H2LMPLHIzpHuL)}MX IJ0IZ8HMH9WIJXIpHuMzxLHML<LELUL]ff.IxHL]I J49LEM4IrPL}OE1E1fff.I M<E1fDC~fInf.rfI~MIII9|II9uLELUL]L}O HI;Rp}6MzxHIHL;mO~ffff.E1O HI;Rp|HpIJ`HUH)HH9}(L|1IHL;m0ffffff.1IHL;m K<H߃NHH[A\A]A^A_]UHAWAVAUATSHHEeHHEL L0H8HHIfWf)EHEMnMf M)tWH(LHHH=tLENIL}L}IHEMH(~LLL蒄NML}HkILIL H}%IH8LHPL)tH3HCH)H9uQL7Hx%HHAHHPH1HAeHMUI]HL)H9uVMEMM LL)H9uCL)t1I H; u+HH9uM)tB1fDII; u HI9u%H8L,I}HI}pL%IE8IMHI+E0HHHXIMPH`LhLpLxH H*@H @HHHH@WH*PHeOgHEHXHEH]H]H@H0LH 1H}H9$HtHP(H}HuHI4$H}Ht H}ۀNHveHH;EH[A\A]A^A_]1I4$H}HuH)Ⱥ1fff.A f.HGAT_f.HzHF_ALf.HZHF_ADf.HrHF_HH9uHt)HA f.HG_Hf(HuI4$H}H HP H}H-NH}*}N IH}H9uHP H}HtmHuH}Hu_L|N HP(H}HtDIH}Ht6IH}Ht(IH}HtIH}Ht IH}HtH}/NLo|N UH]f.UH]NfDUHSPH~NH LgHHKHHH[]@UHHLgHHGHF]UH]f.UH]~NfDUHH]2fUHH պaH1H9NHD]DUHHLg]UHAWAVAUATSHHL.H2LMPLHIzpHuL)}MX IJ0IZ8HMH9WIJXIpHuMzxLHML<LELUL]ff.IxHL]I J49LEM4IrPL}OE1E1fff.I M<E1fDC~fInf.vfI~MIII9|II9uLELUL]L}O HI;Rp}6MzxHIHL;mO~ffff.E1O HI;Rp|HpIJ`HUH)HH9}(L|1IHL;m0ffffff.1IHL;m K<H|NHH[A\A]A^A_]UHAWAVSHIHeHHE0r|NHL=_fL;H{LY!HHEHEHUL0HQFgHHeHH;EuHH[A^A_]a|NL;IH{HCHt +{NIH{NLyN UHAWAVSHIHYeHHE0{NHL=^^fL;H{L/Y!HHEHEHULpHAGgHHeHH;EuHH[A^A_]{NL;IH{HCHt +%{NIH{NLXxN UHAWAVSHIHeHHE0zNHL=]fL;H{LoX!HHEHEHUL谫HGgHH?eHH;EuHH[A^A_]zNL;IH{HCHt +ezNIHXzNLwN UHAWAVSHIHeHHE02zNHL=\fL;H{LW!HHEHEHULHHgHHeHH;EuHH[A^A_]!zNL;IH{HCHt +yNIHyNLvN UHSPHH{Ht H{syNH.\fHH{HCHHt[]MyN[]fff.UHSPHH{Ht H{#yNH[fHH{HCHtyNHH[]xNUHSPH~*F(Hvt1HH, 1HHHHH[]fff.UHAWAVAUATSHHH%eHHEW)EIIHE)EHE)pHEH'#HD$(H #HD$ H!HD$HpHD$HEH$D$LELM41L"IHU1L]!Iǀ} uELHH$HLL|HHpHLW)`)P)@)0) ))))HDžLeH]L)tcLIILH=dHwNILLKHHL~LLHZxNILMEHHpLHLHHt HvNHHHt HPrvNH Ht H(ZvNHHt HBvNHHt%H*vNHpHu#HL[HpHt HxuNH}Ht H}uNH}Ht H}uNHpeHH;EuHH[A\A]A^A_]vNHsN HHpH\HHpHtqHHHHuHHHt HHuNHHHuXH HudHHupHHu|HpHH}HH}HH.rN HPtNH HtH(tNHHtHtNHHtHtNHpHxRHHpHc=HHpHN(HHpH9HHpH$Hx tNH}HH} +tNH}HH}sNH4qN fff.UHAWAVAUATSHHHeeHHEW)EIIHE)EHE)pHEHgHD$(HKHD$ H_HD$HpHD$HEH$D$LELM01LO"IHU1LX!Iǀ} uELHH$HLDLHHpHLW)`)P)@)0) ))))HDžLeH]L)tcLIILH=dHVrNILLKHHL~LLHsNILMEHHpLHL$ +HHt HqNHHHt HPqNH Ht H(qNHHt HqNHHt%HjqNHpHu#HLWHpHt Hx9qNH}Ht H}'qNH}Ht H}qNHeHH;EuHH[A\A]A^A_]NqNHHnN HHpH\HHpHtqHHHHuHHHt HpNHHHuXH HudHHupHHu|HpHH}HH}HHnmN HPpNH HtH(pNHHtHoNHHtHoNHpHxRHHpHc=HHpHN(HHpH9HHpH$Hx`oNH}HH}JoNH}HH}4oNHtlN fff.UHAWAVAUATSHHeHHEL L8H(HHIW)EHEMnMf M)tWH0LHHH=LnNIL}L}IHEMH0~LLLoNML}H譛IL"IL H}$IH(LHNL)tHHSH)H9u;LR#H$HH1I4$H}HHMMM]LL)H9u^MEI] HL)H9uKM)t$1ffffff.I H;u+HI9uL)t;1fDII; +u HH9uLSI}HI}pLUIE8IMHI+E0HHHXIMPH`LhLpLxH H*@H@HHHH@WH*PH;gHEHXHEH]H]H@H8LHx1H}H9mHtHP(H}Hu1I4$H}Ht H}WlNHeHH;ECH[A\A]A^A_]A.D@HPAHs1(ML)1(Ȑu(A .ATHC(TUVHz.HB((TUVAT.HJHB((TUVAL Hr.HBHH9lMt'I@u(A .HCHIuI4$H}HHP H}H[kNH}XhN IH}H9uHP H}HtmHuH}Hu_LhN HP(H}HtDIH}Ht6IH}Ht(IH}HtIH}Ht IH}HtH}]jNLgN DUH]f.UH]4jNfDUHSPH'jNH 9gHHKHHH[]@UHH8gHHGHF]UH]f.UH]iNfDUHH]2fUHH 5aH1H9NHD]DUHH8g]UHAWAVAUATSHHL.H2LMPLHIzpHuL)}MX IJ0IZ8HMH9WIJXIpHuMzxLHML<LELUL]ff.IxHL]I J49LEE4IrPL}OE1E1fff.I M<E1fDfCnfAn.rfA~MIII9|II9uLELUL]L}O HI;Rp}7MzxHIHL;mPfffff.E1O HI;Rp|HpIJ`HUH)HH9}(L|1IHL;m0ffffff.1IHL;m K<HgNHH[A\A]A^A_]UHAWAVAUATSHHEeHHEL L0H8HHIW)EHEMnMf M)tWH(LHHH=tLGgNIL}L}IHEMH(~LLLhNML}HMILIL H}$IH8LHPL)tH3HCH)H9uQLHz$HHAHHPH1H?eHMUI]HL)H9uXMEMM LL)H9uEL)t1fI H; u+HH9uM)tB1fDII; u HI9u%H8LI}HI}pL IE8IMHI+E0HHHXIMPH`LhLpLxH H*@H@HHHH@WH*PH4gHEHXHEH]H]H@H0LH q1H}H9"HtHP(H}HuHI4$H}Ht H}dNHveHH;EH[A\A]A^A_]1I4$H}HuH)Ⱥ1fff.A .HGAT].HzHF]AL.HZHF]AD .HrHF]HH9uHt+Hfff.A .HG]H(HuI4$H}H HP H}H/dNH},aN IH}H9uHP H}HtmHuH}Hu_L`N HP(H}HtDIH}Ht6IH}Ht(IH}HtIH}Ht IH}HtH}1cNLq`N fUH]f.UH]cNfDUHSPHbNH ^2gHHKHHH[]@UHH=2gHHGHF]UH]f.UH]bNfDUHH]2fUHH aH1H9NHD]DUHH-2g]UHAWAVAUATSHHL.H2LMPLHIzpHuL)}MX IJ0IZ8HMH9WIJXIpHuMzxLHML<LELUL]ff.IxHL]I J49LEE4IrPL}OE1E1fff.I M<E1fDfCnfAn.vfA~MIII9|II9uLELUL]L}O HI;Rp}7MzxHIHL;mPfffff.E1O HI;Rp|HpIJ`HUH)HH9}(L|1IHL;m0ffffff.1IHL;m K<H`NHH[A\A]A^A_]UHAWAVSHIHeHHE0r`NHL=CfL;H{L=!HHEHEHUL0H!0gHHeHH;EuHH[A^A_]a`NL;IH{HCHt +_NIH_NL]N UHSPHH{Ht H{_NHnBfHH{HCHHt[]_N[]fff.UHSPHH{Ht H{c_NHBfHH{HCHtC_NHH[]5_NUHSPH~*F(Hvt1HH, 1HHHHH[]fff.UHAWAVAUATSHHHeeHHEW)EIIHE)EHE)pHEHg HD$(HK HD$ H_HD$HpHD$HEH$D$LELM1LO"IHU1LC!Iǀ} uELHH$HLLHHpHLW)`)P)@)0) ))))HDžLeH]L)tcLIILH=dHV]NILLKHHL~LLH^NILMEHHpLHLHHt H\NHHHt HP\NH Ht H(\NHHt H\NHHt%Hj\NHpHu#HLBHpHt Hx9\NH}Ht H}'\NH}Ht H}\NHeHH;EuHH[A\A]A^A_]N\NHHYN HHpH\HHpHtqHHHHuHHHt H[NHHHuXH HudHHupHHu|HpHH}HH}HHnXN HP[NH HtH([NHHtHZNHHtHZNHpHxRHHpHc=HHpHN(HHpH9HHpH$Hx`ZNH}HH}JZNH}HH}4ZNHtWN fff.UHAWAVAUATSHHHeHHEW)EIIHE)EHE)pHEHHD$(HHD$ HHD$HpHD$HEH$D$LELMQ1L菜"IHU1L.?!Iǀ} uELHH$HLLHHpHLW)`)P)@)0) ))))HDžLeH]L)tcLIILH=dHXNILLKHHL~LLHYNILMEHHpLHL$ HHt H -NHHHt HPNH Ht H(ڐNHHt HNHHt%H誐NHpHu#HLC=HpHt HxyNH}Ht H}gNH}Ht H}UNHfHH;EuHH[A\A]A^A_]莐NH舍N HHpH\HHpHtqHHHHuHHHt HȏNHHHuXH HudHHupHHu|HpHH}HH}HH讌N HPXNH HtH(@NHHtH(NHHtHNHpHxRHHpHc=HHpHN(HHpH9HHpH$Hx蠎NH}HH}芎NH}HH}tNH贋N fff.UHAWAVAUATSHHfHHEL L8H(HHIW)EHEMnMf M)tWH0LHHH=LNIL}L}IHEMH0~LLL4NML}H]ILIL H}_%IH(LHNL)tHHSH)H9u<L H*%HHE1M$H}HHMMM]LL)H9u]MEI] HL)H9uJM)t#1fffff.I H;u+HI9uL)t;1fDII; -u HH9uLI}HI}pLIE8IMHI+E0HHHXIMPH`LhLpLxH H*@H@HHHH@WH*PH<ogHEHXHEH]H]H@H8LHԗ1H}H9HtHP(H}HuE1M$H}Ht H}薋NHfHH;E[H[A\A]A^A_]AHHPHsE11HH)E11fD@t:A4AT9~<9~AAT9~GAT 9@~MHH9uSA4AT9I9LGAT9LGAT 9@LGHH9uHtIHffff.@tA9@~HHu@A9@IHHuM$H}HHP H}H肊NH}N IH}H9uHP H}HtmHuH}Hu_L,N HP(H}HtDIH}Ht6IH}Ht(IH}HtIH}Ht IH}HtH}脉NLĆN fff.UH]f.UH]TNfDUHSPHGNH nlgHHKHHH[]@UHHMlgHHGHF]UH]f.UH]NfDUHH]2fUHH aH1H9NHD]DUHH=lg]UHAWAVAUATSHHL.H2LMHLHIypHuL)]MP II0IY8HMH97IIXIpHuMyxLHML<LELMLUff.IxHL]I J49LUEMqPL}OE11ffff.I M<E1fDDGA9DOINIMI9|II9uLELMLUL}K4HI;Qp},MyxHIHL;mVe@1K4HI;Qp|HpII`HUH)HH9}L|1IHL;m!1IHL;m K<HNHH[A\A]A^A_]UHAWAVAUATSHHeeHHEL L0H8HHIW)EHEMnMf M)tWH(LHHH=]L臆NIL}L}IHEMH(~LLLԇNML}HIL"IL H}%IH8LHPL)tH3HCH)H9uQL2H%HHAD@HpAH1M/NHMUI]HL)H9uXMEMM LL)H9uEL)t1fI H; u+HH9uM)tB1fDII; u HI9u%H8LI}HI}pLIE8IMHI+E0HHHXIMPH`LhLpLxH H*@H@HHHH@WH*PHEhgHEHXHEH]H]H@H0LH]1H}H9 HtHP(H}HuHI<$H}Ht H}NHeHH;EH[A\A]A^A_]1I<$H}HuL)1fff.AAT9HLNH^9HMNA|HV9HMNA\ H~9HMNHH9uMt$Ifff.A9HLNHIuI<$H}H$(HP H}H 膃NH}胀N IH}H9uHP H}HtmHuH}Hu_L0N HP(H}HtDIH}Ht6IH}Ht(IH}HtIH}Ht IH}HtH}舂NLN UH]f.UH]dNfDUHSPHWNH egHHKHHH[]@UHHegHHGHF]UH]f.UH]NfDUHH]2fUHH aH1H9NHD]DUHHeg]UHAWAVAUATSHHL.H2LMHLHIypHuL)]MP II0IY8HMH97IIXIpHuMyxLHML<LELMLUff.IxHL]I J49LEE4MQPL}OE11ffff.I M<E1fDC D9DNILIMI9|II9uLELMLUL}K4HI;Qp}/MyxHIHL;mYh1K4HI;Qp|HpII`HUH)HH9}L|1IHL;m!1IHL;m K<H/NHH[A\A]A^A_]UHAWAVSHIHyeHHE0NHL=~ufL;H{L?Y!HHEHEHULwH!agHHeHH;EuHH[A^A_]NL;IH{HCHt -eNIHXNL|N UHAWAVSHIHeHHE02NHL=tfL;H{LX!HHEHEHULvHagHH_eHH;EuHH[A^A_]!NL;IH{HCHt -~NIH~NL{N UHAWAVSHIHeHHE0r~NHL=sfL;H{LW!HHEHEHUL0vHabgHHeHH;EuHH[A^A_]a~NL;IH{HCHt -}NIH}NL{N UHSPHH{Ht H{}NHNsfHH{HCHHt[]}N[]fff.UHSPHH{Ht H{c}NHrfHH{HCHtC}NHH[]5}NUHSPH~*F(Hvt1HH, 1HHHHH[]fff.UHAWAVAUATSHHHEeHHEW)EIIHE)EHE)pHEHgHD$(HKHD$ H_HD$HpHD$HEH$D$LELM1L_"IHU1L]!Iǀ} uELHH$HLvLHHpHLW)`)P)@)0) ))))HDžLeH]L)tcLIILH=dHV{NILLKHHL~LLH|NILMEHHpLHLHHt HzNHHHt HPzNH Ht H(zNHHt HzNHHt%HjzNHpHu#HL'HpHt Hx9zNH}Ht H}'zNH}Ht H}zNHeHH;EuHH[A\A]A^A_]NzNHHwN HHpH\HHpHtqHHHHuHHHt HyNHHHuXH HudHHupHHu|HpHH}HH}HHnvN HPyNH HtH(yNHHtHxNHHtHxNHpHxRHHpHc=HHpHN(HHpH9HHpH$Hx`xNH}HH}JxNH}HH}4xNHtuN fff.UHAWAVAUATSHHHeHHEW)EIIHE)EHE)pHEHHD$(HHD$ HHD$HpHD$HEH$D$LELMQ1L蟺"IHU1LX!Iǀ} uELHH&$HLqLHHpHLW)`)P)@)0) ))))HDžLeH]L)tcLIILH=dHvNILLKHHL~LLHwNILMEHHpLHLD +XNHHHt HPWNH Ht H(WNHHt HWNHHt%HWNHpHu#HLC=HpHt HxyWNH}Ht H}gWNH}Ht H}UWNHeHH;EuHH[A\A]A^A_]WNHTN HHpH\HHpHtqHHHHuHHHt HVNHHHuXH HudHHupHHu|HpHH}HH}HHSN HPXVNH HtH(@VNHHtH(VNHHtHVNHpHxRHHpHc=HHpHN(HHpH9HHpH$HxUNH}HH}UNH}HH}tUNHRN fff.UHAWAVAUATSHHeHHEL L8H(HHIW)EHEMnMf M)tWH0LHHH=LTNIL}L}IHEMH0~LLL4VNML}H=ILbIL H}O$IH(LHNL)tHHSH)H9u<L H$HHE1M$H}HHMMM]LL)H9u]MEI] HL)H9uJM)t#1fffff.I H;u+HI9uL)t;1fDII; +u HH9uLI}HI}pLIE8IMHI+E0HHHXIMPH`LhLpLxH H*@H@HHHH@WH*PH\#gHEHXHEH]H]H@H8LH^1H}H9HtHP(H}HuE1M$H}Ht H}RNH1eHH;E[H[A\A]A^A_]AHHPHsE11HH)E11fD@t:A4AT9~<9~AAT9~GAT 9@~MHH9uSA4AT9I9LGAT9LGAT 9@LGHH9uHtIHffff.@tA9@~HHu@A9@IHHuM$H}HHP H}HQNH}NN IH}H9uHP H}HtmHuH}Hu_L,NN HP(H}HtDIH}Ht6IH}Ht(IH}HtIH}Ht IH}HtH}PNLMN fff.UH]f.UH]TPNfDUHSPHGPNH gHHKHHH[]@UHHm gHHGHF]UH]f.UH]ONfDUHH]2fUHH aH1H9NHD]DUHH] g]UHAWAVAUATSHHL.H2LMHLHIypHuL)]MP II0IY8HMH97IIXIpHuMyxLHML<LELMLUff.IxHL]I J49LUEMqPL}OE11ffff.I M<E1fDDGA9DOINIMI9|II9uLELMLUL}K4HI;Qp},MyxHIHL;mVe@1K4HI;Qp|HpII`HUH)HH9}L|1IHL;m!1IHL;m K<HNNHH[A\A]A^A_]UHAWAVAUATSHHeHHEL L0H8HHIW)EHEMnMf M)tWH(LHHH=]LMNIL}L}IHEMH(~LLLNNML}HILIL H}$IH8LHPL)tH3HCH)H9uQL2H$HHAD@HpAH1M/NHMUI]HL)H9uXMEMM LL)H9uEL)t1fI H; u+HH9uM)tB1fDII; u HI9u%H8LI}HI}pLIE8IMHI+E0HHHXIMPH`LhLpLxH H*@H@HHHH@WH*PHegHEHXHEH]H]H@H0LHMW1H}H9 HtHP(H}HuHI<$H}Ht H}KNHeHH;EH[A\A]A^A_]1I<$H}HuL)1fff.AAT9HLNH^9HMNA|HV9HMNA\ H~9HMNHH9uMt$Ifff.A9HLNHIuI<$H}H$(HP H}H JNH}GN IH}H9uHP H}HtmHuH}Hu_L0GN HP(H}HtDIH}Ht6IH}Ht(IH}HtIH}Ht IH}HtH}INLFN UH]f.UH]dINfDUHSPHWINH gHHKHHH[]@UHHgHHGHF]UH]f.UH]HNfDUHH]2fUHH aH1H9NHD]DUHHg]UHAWAVAUATSHHL.H2LMHLHIypHuL)]MP II0IY8HMH97IIXIpHuMyxLHML<LELMLUff.IxHL]I J49LEE4MQPL}OE11ffff.I M<E1fDC D9DNILIMI9|II9uLELMLUL}K4HI;Qp}/MyxHIHL;mYh1K4HI;Qp|HpII`HUH)HH9}L|1IHL;m!1IHL;m K<H/GNHH[A\A]A^A_]UHAWAVSHIHeHHE0FNHL=)fL;H{Lo$!HHEHEHULwHAgHH?eHH;EuHH[A^A_]FNL;IH{HCHt +eFNIHXFNLCN UHAWAVSHIH٪eHHE02FNHL=(fL;H{L#!HHEHEHULvHgHHeHH;EuHH[A^A_]!FNL;IH{HCHt +ENIHENLBN UHAWAVSHIHeHHE0rENHL=(fL;H{L"!HHEHEHUL0vHgHHeHH;EuHH[A^A_]aENL;IH{HCHt +DNIHDNLBN UHSPHH{Ht H{DNHn'fHH{HCHHt[]DN[]fff.UHSPHH{Ht H{cDNH'fHH{HCHtCDNHH[]5DNUHSPH~*F(Hvt1HH, 1HHHHH[]fff.UHAWAVAUATSHHHeeHHEW)EIIHE)EHE)pHEHgHD$(HKHD$ H_HD$HpHD$HEH$D$LELM1LO"IHU1L(!Iǀ} uELHH$HLdsLHHpHLW)`)P)@)0) ))))HDžLeH]L)tcLIILH=dHVBNILLKHHL~LLHCNILMEHHpLHLHHt HANHHHt HPANH Ht H(ANHHt HANHHt%HjANHpHu#HL'HpHt Hx9ANH}Ht H}'ANH}Ht H}ANHeHH;EuHH[A\A]A^A_]NANHH>N HHpH\HHpHtqHHHHuHHHt H@NHHHuXH HudHHupHHu|HpHH}HH}HHn=N HP@NH HtH(@NHHtH?NHHtH?NHpHxRHHpHc=HHpHN(HHpH9HHpH$Hx`?NH}HH}J?NH}HH}4?NHt<N fff.UHAWAVAUATSHHHeHHEW)EIIHE)EHE)pHEHHD$(HHD$ HHD$HpHD$HEH$D$LELMQ1L菁"IHU1L.$!Iǀ} uELHH$HLnLHHpHLW)`)P)@)0) ))))HDžLeH]L)tcLIILH=dH=NILLKHHL~LLH>NILMEHHpLHLD HHt H -vNHHHt HPuNH Ht H(uNHHt HuNHHt%HuNHpHu#HLC"HpHt HxyuNH}Ht H}guNH}Ht H}UuNHeHH;EuHH[A\A]A^A_]uNHrN HHpH\HHpHtqHHHHuHHHt HtNHHHuXH HudHHupHHu|HpHH}HH}HHqN HPXtNH HtH(@tNHHtH(tNHHtHtNHpHxRHHpHc=HHpHN(HHpH9HHpH$HxsNH}HH}sNH}HH}tsNHpN fff.UHAWAVAUATSHHeHHEL L8H(HHIfWf)EHEMnMf M)tWH0LHHH=LrNIL}L}IHEMH0~LLL2tNML}H+mILIL H}]$IH(LHNL)tHHSH)H9u;LH($HH1I4$H}HHMMM]LL)H9u\MEI] HL)H9uIM)t"1ffff.I H;u+HI9uL)t;1fDII; -u HH9uLI}HI}pLIE8IMHI+E0HHHXIMPH`LhLpLxH H*@H @HHHH@WH*PHUgHEHXHEH]H]H@H8LH|1H}H9HtHP(H}Hu1I4$H}Ht H}pNHeHH;EeH[A\A]A^A_]Af.D@HPAHs1f(ML)1f(fffff.uf(A f.ATHCf(fTfUfVHzf.HBf(f(fTfUfVATf.HJHBf(f(fTfUfVALHrf.HBHH9YMt&Iؐuf(A f.HCHIuI4$H}HHP H}HyoNH}vlN IH}H9uHP H}HtmHuH}Hu_L#lN HP(H}HtDIH}Ht6IH}Ht(IH}HtIH}Ht IH}HtH}{nNLkN UH]f.UH]TnNfDUHSPHGnNH RgHHKHHH[]@UHHRgHHGHF]UH]f.UH]mNfDUHH]2fUHH aH1H9NHD]DUHHRg]UHAWAVAUATSHHL.H2LMPLHIzpHuL)}MX IJ0IZ8HMH9WIJXIpHuMzxLHML<LELUL]ff.IxHL]I J49LEM4IrPL}OE1E1fff.I M<E1fDC~fInf.rfI~MIII9|II9uLELUL]L}O HI;Rp}6MzxHIHL;mO~ffff.E1O HI;Rp|HpIJ`HUH)HH9}(L|1IHL;m0ffffff.1IHL;m K<HkNHH[A\A]A^A_]UHAWAVAUATSHHEeHHEL L0H8HHIfWf)EHEMnMf M)tWH(LHHH=tLekNIL}L}IHEMH(~LLLlNML}HeILIL H}$IH8LHPL)tH3HCH)H9uQLH$HHAHHPH1HAeHMUI]HL)H9uVMEMM LL)H9uCL)t1I H; u+HH9uM)tB1fDII; u HI9u%H8LI}HI}pLIE8IMHI+E0HHHXIMPH`LhLpLxH H*@H @HHHH@WH*PHNgHEHXHEH]H]H@H0LH=u1H}H9$HtHP(H}HuHI4$H}Ht H}hNHveHH;EH[A\A]A^A_]1I4$H}HuH)Ⱥ1fff.A f.HGAT]f.HzHF]ALf.HZHF]ADf.HrHF]HH9uHt)HA f.HG]Hf(HuI4$H}H HP H}HMhNH}JeN IH}H9uHP H}HtmHuH}Hu_LdN HP(H}HtDIH}Ht6IH}Ht(IH}HtIH}Ht IH}HtH}OgNLdN UH]f.UH]$gNfDUHSPHgNH LgHHKHHH[]@UHHKgHHGHF]UH]f.UH]fNfDUHH]2fUHH ŴaH1H9NHD]DUHHKg]UHAWAVAUATSHHL.H2LMPLHIzpHuL)}MX IJ0IZ8HMH9WIJXIpHuMzxLHML<LELUL]ff.IxHL]I J49LEM4IrPL}OE1E1fff.I M<E1fDC~fInf.vfI~MIII9|II9uLELUL]L}O HI;Rp}6MzxHIHL;mO~ffff.E1O HI;Rp|HpIJ`HUH)HH9}(L|1IHL;m0ffffff.1IHL;m K<HdNHH[A\A]A^A_]UHAWAVSHIHeHHE0dNHL=ZfL;H{L=!HHEHEHULP\HEgHHeHH;EuHH[A^A_]dNL;IH{HCHt -dNIHcNL8aN UHAWAVSHIHYeHHE0cNHL=^YfL;H{L=!HHEHEHUL[HaFgHHeHH;EuHH[A^A_]cNL;IH{HCHt -EcNIH8cNLx`N UHAWAVSHIHeHHE0cNHL=XfL;H{L_<!HHEHEHULZHGgHH?eHH;EuHH[A^A_]cNL;IH{HCHt -bNIHxbNL_N 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0A}D)9NH]I\$EU$DAHcHHHH]I\$ HHH]HPIT$(:HHEB0IcHxHcHE1HELpLXL`HEEU$LEDAHcH A}L}ADIT$02HcHIH]IT$8ML$@IT$H DALcMAHcHIH}DPPASVASH0ID$PMt/IL$XIT$`HcIcHHH1Hufffff.IL$hHHUMHIHMIL$0Hc LuIcHHHUHUMD$pI$HLHuHUHMLMPAVMAWASSA$HEPHEPAt$xHPEM:H]CEI$HHHLxLuHHFD9]IcM$HDHMM I$LI4A9>HHGHHs -tHHGMtHII9s I<IDH9sLuH]6HHLwLHXIs1HHhAHMdtMttLkL+h1fff.ADALADALADALADALADALADALADA ADA H IuHtBI։AHcHHDLHADA ADA H HuH9LXL`LuH]t6H4M H1ATTHTHH9rf.A u@AE$~8I$H AHcH<уNʍDH4MKIM9ID$P8Lp}I$HM;|HxDI$HHM; |PAE$~HIL$XIT$`H HcHcuHH HcH<уNʍDH4LKHH;]|HMID$(HM;9HBbHH;EuHĘ[A\A]A^A_]MKfUH]f.UH]LKfDUHSPHwLKH ^=dHHKHSHHHPH[]fff.UHH-=dHHGHOHNHF]UH]f.UH]LKfDUHAWAVSPID:D9}"fI~Av1>A9uH[A^A_]fff.UHH U^H1H9NHD]DUHH<d]UHAWAVAUATSHHbHHEDIIL?LoMtIEMPLXHX1L]t|IHXLPMtIEHk<dHUL}LmHMHMH`HpHEHpLxLmHMt IEH}H9t$Ht%HP(HDž`HE1 HP H`HDž`I $I$HɉTtHMI|$0HHHuP0M|$0I\$I|$0ID$0H9tGHtHP(HpH}HtBH9t]I?HEH`HDž`HudHP HpH}HuIH`HDž`Hu+JIHHHPHH`HDž`Ht!HHEH}HHHuP0HH}H9t?HtHP(Mt:HIEHu(IELPLHKI$Mu/HP MuI$MtPtTHLoJKHXbHH;EuIHLHĈ[A\A]A^A_] IKHKH ֿbHHH5bHYHHK.HKH bHHH5`bH)HHK HWHMt$HIEHuIELPLGKHYEK HHUHSPHk9dHH_HtHHCHtH[]HHPHH[]FKUHAVSHH9dHLsMt#HIFHuILPLrFKH[A^]bGK@UHSPHWGKH 8dHHKHHHKHHHtHAH[]fUHH8dHHGHFHGHFHtH@]fDUHSPH_HtHHCHtH[]HHPHH[]EKUHAVSII^Ht#HHCHuHHPH|EKL[A^]lFKfffff.UHH6HHH@]ff.UHH ^H1H9NHD]DUHH7d]UH]f.UH]EKfDUHSPHEKH 7dHHKHSHHHPH[]fff.UHH7dHHGHOHNHF]UH]f.UH]tEKfDUHAWAVSPID:D9}"fI~Av1A9uH[A^A_]fff.UHH 5^H1H9NHD]DUHH]7d]ÐUHAVSHPIH[bHHE(DKHþ HDKHHCHCXHC`HCXHCHHC@HC8HC0HC(HC HCPHCpHCxHCpHChƃHǃfǃHǃHǃƃHHǃHǃHǃHǃHǃHǃHǃHǃHǃHHHǃHǃHǃǃǃHǃ H] H5MiMH}HjGH5]hMHBH5pOH,DHA H5JKHSEHH;:HHH {cHMHHUHuHuIIFIF0INIVIF@H]HEHtHL\HBKH bHH;Eu LHP[A^]BKIH]HEHtH\HMBKL?K DUHAWAVAUATSHIIIHbHHE1L;HHL0L8W)`HDžpHCH+CHH.袋.HH`F5LsL{M9t]L`H]fffff.LuHhH;psL0HhIXM9ufDLHBIXM9uW)EHEIH@H`LELH0xH@HH8taHHDž@H}Ht H}@KH`Ht Hh@KHFbHH;EHHĨ[A\A]A^A_]H}tPHUHL.L@HDž@MtAFt I~e@KL]@KH}HdhHHDž@H}H@D@K0@KIH`.H5AeMH eMH}L`XW)@HDžP ?KHP(+~\)@He input.HHHsequenceHHHptr for HHHGot nullH@AHILHuH@L蜨E1H5bH;L?KZHALeMuFzHAL`MHH@t HP>KLeMt6HEL9t!Lh@t Hx>KLM9uH}LLe>KEuEuL`Mu&^H}>KEtH}>KL`Mt:HhL9t=Lh@t HxT>KLM9uH`Lh9>KEtJL\>K@LHL@HDž@Mu+H}HuQH`Ht Hh=KH*;K AFt I~=KL=KH}Ht HH}HtH}=KH`HuHH`HuHH`Huf.UHHH 3cHHxH@Ht]F=K]fDUHSPHH2cHH{HCHt=KHH[]=KfUHAWAVSPI <KHL=2cL;H{L@HHLL2H=/dHHH[A^A_]L;IH{HCHt -<KIHy<KL9K UHAVSHPIH۳bHHE(T<KHþ HJ<KHHCHCXHC`HCXHCHHC@HC8HC0HC(HC HCPHCpHCxHCpHChƃHǃfǃHǃHǃƃHHǃHǃHǃHǃHǃHǃHǃHǃHǃHHHǃHǃHǃǃǃHǃ H]H5`MH}H>HkH5LHH`CH5`MHa:H5gOH;HA H5~KH<HH;~1HHH mrcHMHRHUHuHuIIFIF0INIVIF@H]HEHtHSH9KHsbHH;Eu LHP[A^]7:KIH]HEHtHmSH9KL6K ff.UHAWAVAUATSHIIHbHHE1L螖HHtpHǪ^1L5H<H4HKH+KHH.袋.HHIHbHH;EuLHĈ[A\A]A^A_]T9K9KIHh.H5^MH 6_MH}Lh *W)PHDž` 8KH`(v\)PHe input.HHHsequenceHHHptr for HHHGot nullH@AHBLHuHPLnE1H5dbH zLa8K8KIHh.H5^MH P^MH}Lh#DW)PHDž`07KH`(v\)PHt tensorHH%Houtput tHH Hptr for HHHGot nullHHHLength: HHHSequenceH@-AH^MHuHPLlE1H5bbH yL_7K IALeMIALhMIIALeMFIALhMnIIPt H`6KLeMt6HEL9t!HX@t Hx\6KHI9uH}LLeB6KEuEu LhMu-'H}6KEtH} 6KLhMHpL9HX@t Hx5KHI9uIPt H`5KLeMt6HEL9t!HX@t Hx5KHI9uH}LLev5KEuEuLhMu&^H}S5KEtH}D5KLhMt:HpL9tEHX@t Hx5KHI9uHhLp4KEtL!5KL12K L@UHAWAVATSH`IHGbHHEؿ(4KHþ H4KHHCHCXHC`HCXHCHHC@HC8HC0HC(HC HCPHCpHCxHCpHChƃHǃfǃHǃHǃƃHHǃHǃHǃHǃHǃHǃHǃHǃHǃHHHǃHǃHǃǃǃHǃ H]H59YMH}HV7H޸H5.@KHH<7Id]I\cHW)EHE2KHEHHHML HXHMH5 LHUL6H5YMHt2H5_OH3HA H5vKH4HH;)HHH jcHMHūHUHuHuIIGIG0IOIWIG@H}Ht H}2KH]HEHtHKH1KHtbHH;EuLH`[A\A^A_]42KIH]HEHt7HfKH1KL.K IH}HuH]HEHuL.K H}r1KH]HEHt룐UHAWAVAUATSHIIHbHHE1L^HH LEtHH$H8HSH+SHH.袋.HHHH9H9@HxHy -HH8L(HH8IM}1LL,HLL L`PMuMuPM9#I}0HPhHxL&!H1ff.LLa.KHL!IIH9|H0H`WMH`HkWMH@HuKHEHxH`H8H@L0LMHLHv-xtSH}/KHbHH;EtJ/KLG!II}0HPILLH0KL(IHbHH;EuLHĸ[A\A]A^A_]ÿ!/KIH`.H5 UMH UMHxL`VFW)@HDžP .KHP(m\)@He input.HHHsequenceHHHptr for HHHGot nullH@AH8LHxH@L臗E1H5}bH&pLz.K5.KIH`.H5!TMH TMHxL`YZW)@HDžP0-KHP(_)@Hdex tensHHHt for inHHHptr inpuHHHGot nullHf@ or@"AHTMHxH@L蕖E1H5bH4oL-KC-KIH`.H5/SMH SMHxL`ehW)@HDžP0,KHP(?_)@Hut tensoHH Hfor outpHHHnullptr HHHAt: Got HHHSequenceHf@(rAHESMHxH@L處E1H5bH8nL,K IALeMuFzIAL`MII@t HP+KLeMt6HEL9t!HX@t Hx+KHI9uH}LLe+KEuxu#L`Mu0xH}+KxtH}v+KL`MMHhL9THX@t HxC+KHI9u -IALeMIAL`MIIALeMLIAL`MzII@t HP*KLeMt6HEL9t!HX@t Hx*KHI9uH}LLei*KEuxu#L`Mu00H}@*KxtH}.*KL`MHhL9 HX@t Hx)KHI9uI@t HP)KLeMt6HEL9t!HX@t Hx)KHI9uH}LLe)KEuxu L`Mu)aH}q)KxtH}_)KL`Mt:HhL9tEHX@t Hx4)KHI9uH`Lh)KEt,L<)KLL&K LIxt H}(KL(&K UHAWAVAUATSHHEbHHEHG0@EătuIekHcH bH H;Mt*KHH bH H;MuHĘ[A\A]A^A_](Km(KIHX.H5YNMH ZSMHpLXE蒎HLHEH@HuHUH耘Hp1LH,H5%bHiL"(K I@t HP'KLeMt6HEL9t!HX@t Hx'KHI9uH}LLe{'KEt H}l'Kpt H}Z'KE1LXMuTHSIALXMt:H`L9t5HX@t Hx'KHI9uHXL`&KEu -LIL'KL$K fDUHAVSHPIH;bHHE(&KHþ H&KHHCHCXHC`HCXHCHHC@HC8HC0HC(HC HCPHCpHCxHCpHChƃHǃfǃHǃHǃƃHHǃHǃHǃHǃHǃHǃHǃHǃHǃHHHǃHǃHǃǃǃHǃ H]H5-KMH}HJ)H5LMH$H5fROH &HA H5*iKH3'HH;HHH \cHMHHUHuHuIIFIF0INIVIF@H]HEHtH,>Hr$KHbHH;Eu LHP[A^]$KIH]HEHtH=H-$KLm!K DUHAWAVATSH0IHHbHHEL%cL#H{ZHdHHCW)EE -LsHEEdtypfEeH}HULLH]HEHtCt H{#KHw#KEt H}h#KHtIHךbHH;Eu H0[A\A^A_]#KIEt H}(#KL#H{HCHt#KLO K UHAWAVAUATSHHIIH\bHHEH{HH+H1HH HHwHHIGHHH [HcH赘Y螜RKpDy=R6/ĝ(荛!ƙؘ 芚HH|IHqbHH;EuLHĘ[A\A]A^A_],"K!KIH`.H5GMH WIMHxL`{W)@HDžP0z!KHP(2l\)@HsequenceHH&Hutput seHH Htr for oHHHot nullpHHHEmpty: GHHHSequenceH@.AHGMHxH@L$E1H5bHbL!K KIH`}.H5FMH OHMHxL`IHHMHEH@HuHLr|Hx1LH莉H5bH0bL K I@t HP KL}Mt6HEL9t!HX@t HxKHI9uH}LL}KEt H}Kxt H}KE1L`MuTH赏IAL`Mt:HhL9t8HX@t HxrKHI9uH`LhWKEu &LILIALeMuFzIAL`MII@t HPKLeMt6HEL9t!HX@t HxKHI9uH}LLeKEuxu L`Mu)aH}KxtH}zKL`Mt:HhL9tEHX@t HxOKHI9uH`Lh4KEtLWKLgK Lf RRUHAWAVATSH`IH7bHHEؿ(KHþ HKHHCHCXHC`HCXHCHHC@HC8HC0HC(HC HCPHCpHCxHCpHChƃHǃfǃHǃHǃƃHHǃHǃHǃHǃHǃHǃHǃHǃHǃHHHǃHǃHǃǃǃHǃ H]H5)BMH}HF InFIfLHW)EHEKHEHHHML HXHMH5KHULH5CMH~H5 IOHHA H5_KHHH;HHH ScHMHoHUHuHuIIGIG0IOIWIG@H}Ht H}$KH]HEHtH4HKH~bHH;EuLH`[A\A^A_]>KIH]HEHt7Hp4HKLK IH}HuH]HEHuLK H}|KH]HEHtff.UHAWAVAUATSHHőbHHEHIIW)EHEHHoI?tkH*@MH TBM1AL.H]HKHHCH5HHPHKH@bHH;E 0H(IMl$0ID$I\$ W)PHDž`H)tnH8L0IILH=HWKILXLPKH`HL0H8~LHKILXHEH@HEHHHtH@HhHPH@Ll!HHHt#HHCHuHHPHKHPHt HXKLhLmM4$Mt$PM9tvI|$0HPhI|$Ht<xu6I)!H~N1fLLqKL !HIIH9|%!HI|$0HPHLLHzKH(H{H;{sHhr!HCXHhH IHhPu!H]HHbHH;EuLHĸ[A\A]A^A_]KHPK IHPHuCILHMt#HIFHuILPL'KHPHtjHX KH]Hu^IIIHtACt H{KHKH]Hu*KIH]Hu;IHhOt!H]Ht#HHCHuHHPHKLK fUHAWAVAUATSHIIHύbHHE1LnsIMLUYIMII|$0HPhH9I?Z~H8I|$0I~H0H>MHXH?MH@Hl[KHEHpHXH8H@L0LMHLHW-pt H}cKHތbHH;ELH[A\A]A^A_]þL_XIOI+OHH.袋.HH8H0HHHHH9H9HxH0H9ttupH,<MHXH7<MH@HWZKHEHpHXH0H@L8LMH跒LHB-Hy -HH0I~HH+H1LHnHHHVW)pHEHHpHLH8H0HE1ff.I9H(LLHp.H(HDž(HtCt H{fKH^KLLH HLHpH HDž HteCt H{KH KLfff.LLeHHLHp|HHDžHuDIH8H0L9H9LuGHHpLL!HHDžHtCt H{YKHQKI7HdlHLaMtBLyIIHYL9t7MI)HèfDHo!HèIXuI?L II)LM&KIGIGIHHpHAHxIHEHAIEHbHH;E6KKIHX9.H5z7MH 9MHpLXwW)@HDžP .KHP(O\)@He input.HHHsequenceHHHptr for HHHGot nullH@AH9MHpH@LyE1H5bHRLKKIHXM.H56MH 8MHpLXvW)@HDžP BKHP(j^)@H tensor.HHHinput teHHHptr for HHHGot nullH@AH;LHpH@LyE1H5bHQLKKIHXa.H55MH 7MHpLXuW)@HDžP0VKHP(!_)@HsequenceHH'Houtput sHH Hptr for HHHGot nullHHHInsert: HHHSequenceH@/AH5MHpH@LxE1H5bHPLKI@tHPKLeMuEIALeMt6HEL9t!HX@t HxRKHI9uH}LLe8KEupu#LXMuGuH}KptH} KLXMuIIALXM3H`L9HX@t Hx KHI9uI@tHP KLeMuEIALeMt6HEL9t!HX@t HxS KHI9uH}LLe9 KEupu#LXMuGvH} KptH} KLXMuJIALXM4H`L9HX@t Hx KHI9u I@tHP KLeMuEIALeMt6HEL9t!HX@t HxT KHI9uH}LLe: KEupu LXMu=zH} KptH} KLXMuQIALXMt?H`L9t$HX@t Hx KHI9uHXLL` KEuIL KIpu"ILpMu+nIptbH}WH_{ILpMtEHxL9tCMI)Hèf.Hh!HèIXuHpLx -KL9K Lfff.UHAWAVAUATSPIM'IGL)HH.袋.HH9H袋.H9MwLL)LkXL -KHLM9tCHEM)IƨHIHfHǨL4e!HèHIƨIXuM7MgLHEHI?I_IGM9t"LL)IĨfDLg!IĨHXuMtLH[A\A]A^A_] KH[A\A]A^A_]ÿ KHH5uRKHFKHbHHH5bH~bH KIH KLK ffffff.UHAWAVATSH`IH׀bHHEؿ(P KHþ HF KHHCHCXHC`HCXHCHHC@HC8HC0HC(HC HCPHCpHCxHCpHChƃHǃfǃHǃHǃƃHHǃHǃHǃHǃHǃHǃHǃHǃHǃHHHǃHǃHǃǃǃHǃ H]艕H5-MH}H I2I8HW)EHEKHEHHHML HXHMH5wKHUL H50MHH54OHOHA H5mKKHv HH;;HHH *?cHMHoHUHuHuIIGIG0IOIWIG@H}Ht H}KH]HEHtH] HKH~bHH;EuLH`[A\A^A_]KIH]HEHt7H HVKLK IH}HuH]HEHuLoK H}KH]HEHtff.UHAWAVAUATSHIIH_}bHHE1LbIMLHINI+NHH.袋.HH8LkL0Ht?HH0HHH9H9HxфvHy -HH0LIHH+HN1LH;HIM'I6L _W)pHEHpLH8~v1fff.H;0tSLH H(HLHp#L(HDž(MtAEt I}ZKLRKHH98M|$MMl$MII\$L9L MI)Hèffffff.Ha!HèIXuL I}H=+MHXHH+MH@HhIKHEHpHXH0H@L8LMHȁLHS-ptxH}_KHzbHH;EtoKMI#LM>6KIEIEIEHpID$HxIHEID$LI$HkzbHH;EuLH[A\A]A^A_]ÿKIHX脰.H5(MH ,MHpLXhW)@HDžP0yKHP(1M\)@HsequenceHH&Hutput seHH Htr for oHHHot nullpHHHErase: GHHHSequenceH@.AH(MHpH@L#kE1H5bHCLKKIHX|.H5'MH +MHpLXgW)@HDžP qKHP(?\)@He input.HHHsequenceHHHptr for HHHGot nullH@AH)MHpH@L7jE1H5-bHBL*KI@tHPKLeMuEIALeMt6HEL9t!HX@t HxKHI9uH}LLeoKEupu#LXMuGvH}FKptH}4KLXMuJIALXM4H`L9HX@t HxJHI9u I@tHPJLeMuEIALeMt6HEL9t!HX@t HxJHI9uH}LLepJEupu LXMu=zH}JJptH}8JLXMuQIALXMt?H`L9t$HX@t HxJHI9uHXLL`JEuILJyIptmH}bILpMuVILpMtGHxL9tEMI)Hèfff.H\!HèIXuHpLxIJLJ Lfff.UHAVSHPIHubHHE(JHþ H -JHHCHCXHC`HCXHCHHC@HC8HC0HC(HC HCPHCpHCxHCpHChƃHǃfǃHǃHǃƃHHǃHǃHǃHǃHǃHǃHǃHǃHǃHHHǃHǃHǃǃǃHǃ H]MH5 KH}HH2H5r"MHHH52&MH!H5)OHRHA H5p@KHyHH;>HHH -4cHMHvHUHuHuIIFIF0INIVIF@H]HEHtHrHJH3sbHH;Eu LHP[A^]JIH]HEHtH-HsJLJ ff.UHAWAVAUATSHIHHrbHHEHHLc(MH(I|$HH+Hq1LH^H~HMH0H8E11L=Lx0ffffff.LD=EL9x0`JHH](k^)EPHH5$MJCPHHHM-HHHDžHHtCt H{ JHJEtH}JAE9DH8LSW)EHEH}L1L}@L<H@HLL1L@HDž@MtAFt I~hJL`JD9|L8M|$MtHH0LpHII\$L9t9MI)Hè@HV!HèIXuI>L8H0H&LM}LJIFIFIHEID$HEHHEID$H(HH !pbH H;MuHĸ[A\A]A^A_]JJIHh8.H5yMH E"MH}Lh2^W)PHDž`@0JH`(8s_)PHt sequenHH(Hor outpuHH Hullptr fHHHt: Got nHHHConstrucHHHSequenceHf@0ce@2AHMHuHPL`E1H5͐bHv9LJPJIHh0.H5qMH =!MH}Lh/]W)PHDž` (JH`(A\)PHore inpuHHHe 1 or mHHHMust havHf@ts@AH)!MHuHPL_E1H5bH8LJrIPtH`JLeMuEIALeMt6HEL9t!HX@t HxKJHI9uH}LLe1JEuEu LhMuDmH} JEtH}JLhMuDIALhM.HpL9HX@t HxJHI9uIPtH`JLeMuEIALeMt6HEL9t!HX@t HxRJHI9uH}LLe8JEuEuLhMu:wH}JEtH}JLhMuQIALhMt?HpL9t$HX@t HxJHI9uHhLLpJEuqILJdILuMuVIEtMH}BILuMt;H]L9t<MI)HèfHQ!HèIXuH}Lu/JLoJ LfUHAWAVAUATSHH8H~kbHHEп(JHþ HJHHCHCXHC`HCXHCHHC@HC8HC0HC(HC HCPHCpHCxHCpHChƃHǃfǃHǃHǃƃHHǃHǃHǃHǃHǃHǃHǃHǃHǃHHHǃHǃHǃǃǃHǃ H]I#II"HIW)EHE(>JHEHH(HML8L`LhHXLp HM)I!#IYIQ"IHW)`HDžp(JH`HH(HpL8L`LhLpHX HhH5JH}HUH`-H5H5uMHHII!HW)@HDžP;JH@HHHPL0HXHHH5KH@L(H5MHH5DOHHA H55KHHH;HHH (cHMHkHUHuHuH8HHCHC0HKHSHC@H@Ht HHRJH`Ht Hh:JH}Ht H}(JLuHEMtL LJHgbHH;EuHHĨ[A\A]A^A_]=JIH`Ht?yIH`Ht.hIH`HtWIH@Hu0H`Hu<H}HuVH]HEHuuLJ HH_JH`HtHhGJH}Ht IH}HtH}'JH]HEHtIH]HEHtHHJL0J UHAWAVAUATSH8IIHBfbHHEL%TbM'IHcIfHnfsAGIG ffEHEEEaxisEH}HUHML-H]E1HuLmHEtCt H{"JHJMoEt H}JffEEHEHkeepdimsHEEH}HUHMLH]Hu1LuHEt3Ct H{JHJMwEu#AHEuMwEt H}oJHdbHH;EuH8[A\A]A^A_]JIEu IEt H}.JM'IIGHtJLUJ ffff.UHAWAVATSH@HIIHadbHHE1H0IǾH/IIO0Qʃ -w*H5dHcHH}LHLIvHMHDMHEH_MHEH]HuHUHMH蟭 -H}H-HEIHEEtH}JHcbHH;EtvH}LHLI$CH}LHLIj6,H}LHLI3HH}LHLI|HEIHcbHH;EuLH@[A\A^A_]JHIHJ HEtH}PJIHJ :Qh@UHAWAVAUATSHIHpIIHebbHHEHEID$HEEEEEEW)EHEMt5I@ I;@uDLkHHi L}H]HEHxpHEHx1E11WHuLmL}H]HUI9Hxt)Lffffff.H8 HH9u11LIVHuHt$0HuHt$(HuHt$ HuHt$HuHt$HuHt$HuH4$DLMLL/WI}t_HMH 8L1ALj.H}HtHxH8`JH`bHH;E LH[A\A]A^A_]H8L0L@IEM~LMf W)pHEM)tXMIHI9 -LJHHxHpJHEM~HLL,JLHxW)PHDž`LLHXHEHL`_11H@HH9uEtE fff.HEHHcH9LcHEHpL<W)@LHpH@:HI}tlA1ALH MH kL訕.HHHHHCHrHHPHJEa(IEMd$0HpLxW)HDžI)tfHLHHH9LJILLIHMH~LLcJMLH@HHHHHtH@LLLHH9!HHt#HHCHuHHPHbJHHt HFJLHËEHHcUIHXHL$HcE9Hu!HHcHHLrJHhHL4HHHBHHHHPsE1H)HhHHHRHHHHKvHIIHH HH(E1HLLJI<HJ4 LJH(H<H J4 LqJHH<HJ4 LSJILLL9uHPHLhHHtNHIL<MLHXJIHfLHILJLMLHuH8H90L`LH@HxW)HDžHxH+pHHH趃LxL+pM~oILuE11fDI9tKHpLHH;tHHHHHIL9|HFfDHIL9|W)HDžLLM)t[LHHH9L$JILLIHM~LLLoJMLHH8HHt HJHHLtHJHXH;`sHHQ=!HXXHPHHHcHH?!E1HHHEHHHEH9HpHx谻HH+H~ 1HplHt HeIE1It$0L;MwMtPMgIGHI_L9MI)Hèff.H?!HèIXuI<$L`RI_uLPMHXL9MI)HèH>!HèIXuHPLHL3JID$ID$I$HPIGHXHH`IGW)PHDž`IEHpHHx{JH}H LLXZJHpHuJRJIHp.H5>MH { MHLpwFW)PHDž`@JH`(z_)PH be >= 0HH/Hes must HH(HAll valuHH H input. HHH 'split'HHHvalue inHHHInvalid H@7AH MHHPLHE1H5xbH-!LJ JHJHxJݿJIHpɌ.H5 -MH G -MHLpCEW)PHDž`ƅP&Hould be HYHSplit shHQDža> 0AH -MHHPLGE1H5wbHJ LJHpJIPt H`"JL Mt?H(L9t$HX@t HxJHI9uH LL(Juu&LpMuMHJtHJLpMuIALpMHxL9`HX@t HxIJHI9u7TIHH :IHH>IPt H`JL MuQIAL Mt?H(L9t$HX@t HxJHI9uH LL(Juu&LpMuFHaJtHLJLpMuQIALpMt?HxL9t$HX@t Hx JHI9uHpLLxJEuILJH}HIHpHV]ILPM+II]IEH+Ct H{mJHeJH}HIH}HIHHuXIHHt4H JHHu,IHHuIHHHJvIHHHuIHHt#HHCHuHHPHJHHHeJHHHu IH7!HHHt|HHCHujHHPHJLPMuYII]IEHt(Ct H{JHJHHHuIHHHuLPMtHHXL9tpMI)Hèffff.H(7!HèIXuHPLXiJHpHt HxQJH}Ht H}?JLJ LfUHAWAVAUATSHIHpIIHPbHHEHEID$HEEEEEEW)EHEMt5I@ I;@uDL'YHHi L}H]HEHxpHEHx1E11WHuL/[L}H]HUI9Hxt)Lffffff.H8 HH9u11LIVHuHt$0HuHt$(HuHt$ HuHt$HuHt$HuHt$HuH4$DLMLLOEI}t_HLH XL1AL芅.H}HtHxH8JHNbHH;E LH[A\A]A^A_]H8L0L@IEM~LMf W)pHEM)tXMIHI9 -LJHHxHpJHEM~HLLLJLHxW)PHDž`LL*HXHEHL`_11H@HH9uEtE fff.HEHHcH9LcHEHpL<W)@LHpH@ZHI}tlA1ALHLH Lȃ.HHHHHCHrHHPHJEa(IEMd$0HpLxW)HDžI)tfHLHHH9L<JILLIHMH~LLJMLH@HHHHHtH@LLLHH'!HHt#HHCHuHHPHJHHt HfJL@HËEHHcUIHXHL$HcE9Hu!HHcHHLJHhLN4HHHBHHHHPsE1H)HhHHHRHHHHKvHLHH HH(IE1HLLJI<HJ4 LJI<H(J4 LJHH<HJ4 LzJILH L9uHPHLhHHtQHIL<MLHXJIHDLHILJLMLHuH8H90L`LH@HxW)HDžHxH+pHHHqLxL+pM~oILuE11fDI9tKHpLHH;tHHHHHIL9|HfrfDHIL9|W)HDžLLM)t[LHHH9LDJILLIHM~LLLJMLHH&HHt HJHHLtHJHXH;`sHHq+!HXXHPHHHcHH-!E1HHHEHHHEH9HpHxЩHH+H~ 1Hp茺Ht HSIE1It$0L)MwMtPMgIGHI_L9MI)Hèff.H(-!HèIXuI<$L`RI_uLPMHXL9MI)HèH,!HèIXuHPLHL3JID$ID$I$HPIGHXHH`IGW)PHDž`IEHpHHxJH}H LLXzJHpHuJrJIHp|.H5^LH LHLp4W)PHDž`@JH`( -_)PH be >= 0HH/Hes must HH(HAll valuHH H input. HHH 'split'HHHvalue inHHHInvalid H@7AHLHHPL6E1H5fbHMLJ @JHJHJݿ>JIHpz.H5*LH NLHLpc3W)PHDž`ƅP&Hould be HYHSplit shHQDža> 0AHLHHPL5E1H5ebHjLJHpJIPt H`BJL Mt?H(L9t$HX@t HxJHI9uH LL(Juu&LpMuMHJtHJLpMuIALpMHxL9`HX@t HxiJHI9u7TIHH :IHH>IPt H`JL MuQIAL Mt?H(L9t$HX@t HxJHI9uH LL(Juu&LpMuFHJtHlJLpMuQIALpMt?HxL9t$HX@t Hx-JHI9uHpLLx JEuIL(JH}HIHpHV]ILPM+II]IEH+Ct H{JHJH}HIH}HIHHuXIHHt4H-JHHu,IHHuIHHHJvIHHHuIHHt#HHCHuHHPHJHHHJHHHu IH&!HHHt|HHCHujHHPH:JLPMuYII]IEHt(Ct H{JHJHHHuIHHHuLPMtHHXL9tpMI)Hèffff.HH%!HèIXuHPLXJHpHt HxqJH}Ht H}_JLJ LfUHAWAVAUATSHIHpIIH>bHHEHEID$HEEEEEEW)EHEMt5I@ I;@uDLGGHHi L}H]HEHxpHEHx1E11WHuLOIL}H]HUI9Hxt)Lffffff.H8 HH9u11LIVHuHt$0HuHt$(HuHt$ HuHt$HuHt$HuHt$HuH4$DLMLLo3I}t_HLH xL1ALs.H}HtHxH8JH=bHH;E LH[A\A]A^A_]H8L0L@IEM~LMf W)pHEM)tXMIHI9 -LJHHxHpJHEM~HLLlJLHxW)PHDž`LLzHXHEHL`_11H@HH9uEtE fff.HEHHcH9LcHEHpL<W)@LHpH@zHI}tlA1ALHLH Lq.HHHHHCHrHHPHJEa(IEMd$0HpLxW)HDžI)tfHLHHH9L\JILLIHMH~LLJMLH@HHHHHtH@LLLHH!HHt#HHCHuHHPHJHHt HJLpHËEHHcUIHXHL$HcE9Hu!HHcHHLJHhHL4HHHBHHHHPsE1H)HhHHHRHHHHKvHIIHH HH(E1HLLJI<HJ4 LJH(H<H J4 LJHH<HJ4 LJILLL9uHPHLhHHtNHIL<MLHXJIHfLHIL#JLMLHuH8H90L`LH@HxW)HDžHxH+pHHH_LxL+pM~oILuE11fDI9tKHpLHH;tHHHHHIL9|H`fDHIL9|W)HDžLLM)t[LHHH9LdJILLIHM~LLLJMLHHHHt HJHHLtHվJHXH;`sHH!HXXHPHHHcHH!E1HHHEHHHEH9HpHxHH+H~ 1Hp謨Ht HAIE1It$0L -MwMtPMgIGHI_L9MI)Hèff.HH!HèIXuI<$L`RI_uLPMHXL9MI)HèH!HèIXuHPLHL3.JID$ID$I$HPIGHXHH`IGW)PHDž`IEHpHHx軼JH}H LLX蚼JHpHuJ蒼JIHp=j.H5~LH ULHLp"W)PHDž`@2JH`(^)PH be >= 0HH/Hes must HH(HAll valuHH H input. HHH 'split'HHHvalue inHHHInvalid H@7AHLHHPL$E1H5TbHmLJ `JHƸJH踸Jݿ^JIHp i.H5JLH !LHLp!W)PHDž`ƅP&Hould be HYHSplit shHQDža> 0AHLHHPL#E1H5SbHL޺JHpJIPt H`bJL Mt?H(L9t$HX@t Hx7JHI9uH LL(Juu&LpMuMHJtHӹJLpMuIALpMHxL9`HX@t Hx艹JHI9u7TIHH :IHH>IPt H`/JL MuQIAL Mt?H(L9t$HX@t HxJHI9uH LL(иJuu&LpMuFH衸JtH茸JLpMuQIALpMt?HxL9t$HX@t HxMJHI9uHpLLx-JEuILHJH}HIHpHV]ILPM+II]IEH+Ct H{護JH襷JH}HIH}HIHHuXIHHt4HMJHHu,IHHuIHHH JvIHHHuIHHt#HHCHuHHPHŵJHHH襶JHHHu IH'!HHHt|HHCHujHHPHZJLPMuYII]IEHt(Ct H{"JHJHHHuIHHHuLPMtHHXL9tpMI)Hèffff.Hh!HèIXuHPLX詵JHpHt Hx葵JH}Ht H}JL迲J LfUHAWAVAUATSHIHpIIH,bHHEHEID$HEEEEEEW)EHEMt5I@ I;@uDLg5HHi L}H]HEHxpHEHx1E11WHuLo7L}H]HUI9Hxt)Lffffff.H8 HH9u11LIVHuHt$0HuHt$(HuHt$ HuHt$HuHt$HuHt$HuH4$DLMLL!I}t_H LH L1ALa.H}HtHxH8JH;+bHH;E LH[A\A]A^A_]H8L0L@IEM~LMf W)pHEM)tXMIHI9 -L>JHHxHpJHEM~HLL茴JLHxW)PHDž`LL蚢HXHEHL`_11H@HH9uEtE fff.HEHHcH9LcHEHpL<W)@LHpH@蚚HI}tlA1ALH<LH L`.HHHHHCHrHHPHJEa(IEMd$0HpLxW)HDžI)tfHLHHH9L|JILLIHMH~LLòJMLH@HHHHHtH@LLLHH?!HHt#HHCHuHHPH¯JHHt H覰JLHËEHHcUIHXHL$HcE9Hu!HHcHHLұJHhLN4HHHBHHHHPsE1H)HhHHHRHHHHKvHLHH HH(IE1HLLJI<HJ4 LJI<H(J4 LذJHH<HJ4 L躰JILH L9uHPHLhHHtQHIL<MLHXJIHDLHILCJLMLHuH8H90L`LH@HxW)HDžHxH+pHHHNLxL+pM~oILuE11fDI9tKHpLHH;tHHHHHIL9|HNfDHIL9|W)HDžLLM)t[LHHH9L脭JILLIHM~LLLϮJMLHHHHt HJHHLtHJHXH;`sHH!HXXHPHHHcHH; -!E1HHHEHHHEH9HpHxHH+H~ 1Hp̖Ht H/IE1It$0L*MwMtPMgIGHI_L9MI)Hèff.Hh !HèIXuI<$L`RI_uLPMHXL9MI)HèH !HèIXuHPLHL3NJID$ID$I$HPIGHXHH`IGW)PHDž`IEHpHHx۪JH}H LLX躪JHpHuJ貪JIHp]X.H5LH %LHLpW)PHDž`@RJH`(^)PH be >= 0HH/Hes must HH(HAll valuHH H input. HHH 'split'HHHvalue inHHHInvalid H@7AHLHHPLE1H5BbHLJ 耩JHJHئJݿ~JIHp)W.H5jLH LHLpW)PHDž`ƅP&Hould be HYHSplit shHQDža> 0AHLHHPL E1H5BbHLJHpJIPt H`肨JL Mt?H(L9t$HX@t HxWJHI9uH LL(7Juu&LpMuMHJtHJLpMuIALpMHxL9`HX@t Hx詧JHI9u7TIHH :IHH>IPt H`OJL MuQIAL Mt?H(L9t$HX@t HxJHI9uH LL(Juu&LpMuFHJtH謦JLpMuQIALpMt?HxL9t$HX@t HxmJHI9uHpLLxMJEuILhJH}HIHpHV]ILPM+II]IEH+Ct H{ͥJHťJH}HIH}HIHHuXIHHt4HmJHHu,IHHuIHHH)JvIHHHuIHHt#HHCHuHHPHJHHHŤJHHHu IHG!HHHt|HHCHujHHPHzJLPMuYII]IEHt(Ct H{BJH:JHHHuIHHHuLPMtHHXL9tpMI)Hèffff.H!HèIXuHPLXɣJHpHt Hx豣JH}Ht H}蟣JLߠJ LfUHAWAVAUATSHIHHIHbHHEHEHCHEEEEEEW)EHEMt5I@ I;@uDL#HH -L}HEHLulLu1HE11SHuL%L}HULuI9t(LH8HH9uH1 1LIT$HuHt$0HuHt$(HuHt$ HuHt$HuHt$HuHt$HuH4$DLMLHI}tXH-LH L1ALO.H}HtI>JHfbHH;E8LH[A\A]A^A_]L@H8LHIEM|$Mt$ W)pHEM)Lt_MIHI9 LgJHHxHpJHEML~HLL订JLHxW)PHDž`L}H0HEH11HhLpHH9uEtEfHEHHcH9?LcHEHpL<W)@LHH@ʈH(I}tlA1ALHlLH L8N.HHHHHCHHHPHJEIEMl$0HpLxW)HDžI)tfHxLHHH9!L謟JILLIHMHx~LLJMLH@HHHHHtH@LLLHHo HHt#HHCHuHHPHJHHLt HϞJLtIŋULcuMHhH@H0L<HcMD9u:AօHcHH@DLL豜JIIHuEJH4@1LHPHXH`HHH@IHxHIH@MtIfffff.LH!JHIIuHxHHPH9LLHXH`zHH9@H8HHxW)HDžHxH+pHHH =LLxL+pM~oILuE11fDI9tKHpLHH;tHHHHHIL9|H=fDHIL9|W)HDžLLM)Ht[MIHI9LmJILLKHM~LLL踝JMLHHHHt HJHHLLt HۛJHXH;`sH HXXHPHIcHhH: E1LpHHHHEfH(HHEH9HHxuHH+H~ 1H̅Ht HIE1It$0L*M~MtPMfIFHI^L9t>LpMI)HèHh HèIXuI<$Lp I^,LHL;藚JID$ID$I$HPIFHXHH`IFW)PHDž`IEHpHt Hx(JLHH}H!$LPMtHXL9t4MI)Hèffffff.Hx HèIXuHPLLX贙JHpHpwJ訙JIHpSG.H5LH LHLpW)PHDž`@HJH`(^)PH be >= 0HH/Hes must HH(HAll valuHH H input. HHH 'split'HHHvalue inHHHInvalid H@7AHLHHPLE1H51bHLטJ HJHӕJZJtJIHpF.H5`LH LHLpW)PHDž`ƅP&Hould be HYHSplit shHQDža> 0AHLHHPLE1H50bHLJHpJIPt H`xJH Ht?H(H9t$Lh@t HxMJLL9uH HH(-Juu&LpMuFHJtHJLpMuQIALpMt?HxL9t$HX@t Hx誖JHI9uHpLLx芖JEuIL襖JH}HIHH :IHH3IPt H`JL MuQIAL Mt?H(L9t$HX@t HxܕJHI9uH LL(輕Juu&LpMuFH荕JtHxJLpMuQIALpMt?HxL9t$HX@t Hx9JHI9uHpLLxJEu~IL4JH}HosIHpHBIILPMII]IEHCt H{虔JH葔JH}HIH}HIHHuXHIHHt4H9JHHu,IHHuIHHHJIHHt#HHCHuHHPH轒JHHH蝓JHHHuO{II]IEHtvCt H{gJH_JHHHu]IHHHtNHHCHu<HHPH#JLPMu+hIH HHHuLPMt?HXL9tgMI)Hè@Hh HèIXuHPLX詒JHpHt Hx葒JH}Ht H}JL迏J LfUHAWAVAUATSHxLxDtIIH}L}H bHHEMuM+uIHhH~L2IIMHH]LH!HcH9HMI7L!HcH9HM I7HƸL9tLu!HcH9kLm@HM(ttgLu8HHIIAHxL9tHE0IGHMUIML)HHH)vULMUKJ HWMeIEI9HHL)HHH1LsIIEKJ HLHHHHOMDLLIdLHfInfpDHVHHyH]1HHxHffEHEMHHHH9H<6JIHhHA LmLmMtLuHrH!I9I9LHSHHt#Hfffff.H8H9HHHuH@HHHHQHHQHHQHHQ HHQ(HHQ0HHQ8H@HuI?I!IPHHwH |f1fHHWH)1ېAADAD AD0AD@ADPAD`ADpAڀAڐAڠAڰAAAAH HkHt(ILHfffff.AH HuI9t)LH)IHfff.L"HHHIMH)HLeHHMcH II!fInfpDIHHH{H1H8HVH)f1fDAofAoDfAoL Ao\0Aod@ffAoTPffAoD`fAoLpfHHuHt$ITHfoRfofH HuffpNffH~L9tK ff.HHH9uHUH9uL)HHxHGHǷLHEHͷLHEHeJHEH]HuHUHMLELMH -LeLH[\-EH}fJHbHH;E譌JKHOH)1fffff. 0@P`pDހDސDޠDްDDDDH HuHtLILHfAH HuL9L)JHff.LHHHE1E1MHHHzHHNHtB~fpDHyH)1ADADAD AD0HHu1Ht~fpDADADH9uiLuMt#MgL變JIGIGIM/MwMwLeI$HbHH;ELHx[A\A]A^A_]ILH)HSHHb+JH}蔇J HH}HtH} HEt H}JHHJ UHHH bHHxH@Ht]։J]fDUHSPHH`bHH{HCHt襉JHH[]闉JfUHHH "bHHxH@Ht]fJ]fDUHSPHH~bHH{HCHt5JHH[]'JfUHHH ~bHHxH@Ht]J]fDUHSPHH~bHH{HCHtňJHH[]鷈JfUHHH B~bHHxH@Ht]醈J]fDUHSPHH~bHH{HCHtUJHH[]GJfUHHH }bHHxH@Ht]J]fDUHSPHH}bHH{HCHtJHH[]ׇJfUHHH b}bHHxH@Ht]馇J]fDUHSPHH0}bHH{HCHtuJHH[]gJfUHHH |bHHxH@Ht]6J]fDUHSPHH|bHH{HCHtJHH[]JfUHAVSIJHHr|bHH{L3`HDzcHH[A^]IH褆JLJ fff.UHAVSI膆JHH|bHH{L_HDzcHH[A^]IHDJL脃J fff.UHAVSI&JHHLaH[A^]IHJL9J UHAVSIJHHr{bHH{L3_HzcHH[A^]IH褅JLJ fff.UHAVSI膅JHH{bHH{L^HzcHH[A^]IHDJL脂J fff.UHAVSI&JHHzbHH{Ls^HzcHH[A^]IHJL$J fff.UHAVSI(ƄJHHLΕH[A^]IH虄JLفJ UHAWAVAUATSH8LLHHIHHaHHEH8HaHHHLH@H8L跃JHHEEL-LaMuLI@L8L‚JL=aILHDž(HDž HDžHDžDž0I$HJHHHHH0H4JHHH܅JHHHHH0HJHHH袅JHHHdHHH.LL8Lt H ‚JH袁JH5aHH=JH8EJHaHH;EuHH8[A\A]A^A_]ɂJHLL8Lt H <JHJ+H8H0H(H HHH5aHH芀JH8蒁JHHH8{JHUHAWAVAUATSH8MLHHHHHaHHEH8H:aHHHLH@H8LJHEEL-aM}LI@L8LJL5:aILHDž(HDž HDžHDžDž0HHHHLMHHHLL8Lt H \JH<JH5SaHH~JH8JHaHH;EuHH8[A\A]A^A_]cJHLL8Lt H JH~JHH5aHHL~JH8TJHHH8=JHDUHAWAVAUATSHHaHHEHHC0@t"uOHHcH aH H;Mt-HnHH aH H;MuHĘ[A\A]A^A_]YJJIH`,.H5LH SLHxL`,H{0H@HjLHEHHHuH@HHx1LHH5bHUL~J IHt HXA~JE1LmMuMH=IALmMt6HEL9t!HX@t Hx~JHI9uH}LLm}JEuxu L`Mu=uH}}JxtH}}JL`MuLIAL`Mt:HhL9t5HX@t Hxo}JHI9uH`LhT}JEu -LILm}JL}zJ DUHAWAVAUATSHIIHaHHEI ILLIG0@t|L蔿HMILxffff.Hc HxIFI;FsHHIFHIuzDLLHIu^L!lHMtNIDIFI;Ft&H HHIFHIu!fff.LHHIuHaHH;EuHĘ[A\A]A^A_]B|J{JIH`).H5ܡLH LHxL`I0H@HSLHEHHHuH@HHx1LHH5bH>L{J IHt HX*{JE1LmMuMH&IALmMt6HEL9t!HX@t HxzJHI9uH}LLmzJEuxu L`Mu=uH}zJxtH}zJL`MuLIAL`Mt:HhL9t5HX@t HxXzJHI9uH`Lh=zJEu -LILVzJLfwJ fffff.UHAVSHPIH{aHHE(yJHþ HyJHHCHCXHC`HCXHCHHC@HC8HC0HC(HC HCPHCpHCxHCpHChƃHǃfǃHǃHǃƃHHǃHǃHǃHǃHǃHǃHǃHǃHǃHHHǃHǃHǃǃǃHǃ H]H5KHZeH ZeH}~H5rLHZeH ZeH}11H H5LLHwH5wNHyHH HQH54JH=zHH;oHHH bHMHHUHuHuIIFIF0INIVIF@H]HEHtH6H|wJHaHH;Eu LHP[A^]wJIH]HEHtHH7wJLwtJ ffffff.UHAVSHPIHaHHE(wJHþ HvJHHCHCXHC`HCXHCHHC@HC8HC0HC(HC HCPHCpHCxHCpHChƃHǃfǃHǃHǃƃHHǃHǃHǃHǃHǃHǃHǃHǃHǃHHHǃHǃHǃǃǃHǃ H]H5МKHWeH WeH}{H5LHWeH WeHz11HH5\LHtH5NH-vHA H5KJHTwHH;lHHH bHMH&HUHuHuIIFIF0INIVIF@H]HEHtHMHtJHaHH;Eu LHP[A^]tJIH]HEHtHHNtJLqJ fDUHAVSI6tJHHLH[A^]IH tJLIqJ UHAWAVAUATSHHIH_aHHEL-qibM,$I|$3MHlicI$W)pHEƅpfDžqtoƅsH}HpHMHXmpt H}dsJH}u/EAD$HaHH;EuHĨ[A\A]A^A_]sJ<sJH0HX .H59LH zLHpLX]W)@HDžP rJHP(p_)@Hnot set.HHHe to is HHHAttributH@<HJHpH@H0Dž<H5 bH;H0rJIǰ<LuMuKIǰ<HXHII@t HPqJLuMt6HEL9t!HX@t HxqJHI9uH}LLuqJEupu HXHu)aH}}qJptH}kqJHXHt:H`H9tiLp@t Hx@qJLL9uHXH`%qJ<t H0@qJLuHEMt/AFt I~pJLHIpt H}pJM,$I|$ID$HtpJLmJ fff.UHHH 2fbHHxH@Ht]vpJ]fDUHSPHHfbHH{HCHtEpJHH[]7pJfUHAWAVAUATSPHIH}1H>IM}1HLNIL HI}0GA;D$u]M&MfPMuMuPM9HPhHtSxuML H~g1LLmJHLj IIH9|@ILLLMD'L: HI}0HPHLLHpJHEHH[A\A]A^A_]ÐUHAWAVAUATSHHaHHEЉ LHHHDž(HD> NDpHDžxAu@H IHryHHsM~hI1E1AAH* IHyHHMnIs\10AHDžxAA|LHHyHHVH1H/!LHHyHHrHH~H)1ffo +\ff.f81f81\fvfvff\f81Tf81\ fvfvffT \0HHuHt4f81f81Lffvfvfo\ffLI9t1fn\fffff.< fouff~ HI9uILxA rA Hk IH\wHHM2Is1LHHyHHVH 1HCHzH)1fff.f813f81L3Lf81D3f81L3 D L0f81D3f81L3D@LPf81D3f81L3D`LpH HuHHHf81D3f81 3D HHuHzH)1f823f82L3Lf82D3f82L3D L0f82D3f82L3 -D@LPf82D3 f82L3D`LpHHuHHHf82D3f82 3D HHu1H HI9uDpHDžxAAHM IH>uHH?MIs1LHHyHHVH s1HHzH)1ff823f82L3Lf82D3f82L3D L0f82D3f82L3 -D@LPf82D3 f82L3D`LpHHuHt9HH@f82D3f82 3D HHu  HHI9uILxAA H IHsHH~M'IVDHs1HI)1~^ffffff.<fouVff Ѐ|fotRfL|fouVffL|fotRfLHI9uXff.f Ѐ|fouffL|fotfL|fouffLHI9SHt9HH1~^ffff.<fouff HH9uILxA *A =H IH|rHH M~ Is&1bA ILxALHHyHHVHs1HHzH)1Df813f81L3Lf81D3f81L3 D L0f81D3f81L3D@LPf81D3f81L3D`LpH HuHHHf81D3f81 3D HHukA&HD IH5qHHMcIs1FLHHyHHVH0s1H#HzH)1ff803f80L3pLpf80D3f80L3Dp Lp0f80D3 f80L3(Dp@LpPf80D30f80L38Dp`LppH@HuHHHf80D3f80 3Dp pHHukA&H IHpHHvM\Is1?LHHyHHVH0s1HHzH)1ff803f80L3pLpf80D3f80L3Dp Lp0f80D3 f80L3(Dp@LpPf80D30f80L38Dp`LppH@HuHHHf80D3f80 3Dp pHHudAcH IHnHHfMI rJ #H9HLH91I|$H)LHtHD HHuH/ T TT TT THI9uAILxALHHyHHVH`s 1Hu}HzH)1fffff.3L30L0D3 L30D0 L00D3@L3PD0@L0PoD3`oL3pD0`L0pHHuHt.HHoD3o 3D0 0H HuI9LxDpILxAA -fH IHlHHBM%IrJ #H91J `H9$1IT$H)LHt4H< tf<f<HHHu1f<HHHuH1Ҁ< tSf<f4H| uOftH| tSf<ftH| uOfTHHI9uMff.f4H| tf<ftH| uftH| tf<fTHHI9YA -ILxALHHyHHrHtvH~H)1ffo ]f80f80\fuffufP\Pf80Tf80\fuffufTP \P0H Hu1Ht4f80f80Lffufo~]ffufPLPI9LxDpILxAAfAmHw IHhjHH虐MI rJ #H9HLH91I|$H)LHtH HHuH/ T TT TT THI9uAILxA +tHHGMtHII9s I<IDH9sLuH]6HHLwLHXIs1HHhAHMdtMttLkL+h1fff.ADALADALADALADALADALADALADA ADA H IuHtBI։AHcHHDLHADA ADA H HuH9LXL`LuH]t6H4M H1ATTHTHH9rf.A u@AE$~8I$H AHcH<уNʍDH4KIM9ID$P8Lp}I$HM;|HxDI$HHM; |PAE$~HIL$XIT$`H HcHcuHH HcH<уNʍDH4KHH;]|HMID$(HM;9HbxbHH;EuHĘ[A\A]A^A_]KfUH]f.UH]KfDUHSPHwKH ~cHHKHSHHHPH[]fff.UHHMcHHGHOHNHF]UH]f.UH]KfDUHAWAVSPID:D9}"fI~Av1>A9uH[A^A_]fff.UHH z^H1H9NHD]DUHHc]UHAWAVAUATSHHwbHHEDIIL?LoMtIEMPLXHX1L()t|IHXLPMtIEHcHUL}LmHMHMH`HpHEHpLxLmHMt IEH}H9t$Ht%HP(HDž`HE1 HP H`HDž`I $I$HɉTtHMI|$0HHHuP0M|$0I\$I|$0ID$0H9tGHtHP(HpH}HtBH9t]I?HEH`HDž`HudHP HpH}HuIH`HDž`Hu+JIHHHPHH`HDž`Ht!HHEH}HHHuP0HH}H9t?HtHP(Mt:HIEHu(IELPLKI$Mu/HP MuI$MtPtTHLoKHxtbHH;EuIHLHĈ[A\A]A^A_] KKH sbHHH5rbH9HK.KH sbHHH5rbH HK H7HMt$HIEHuIELPLKHY K HHUHSPHcHH_HtHHCHtH[]HHPHH[] KUHAVSHH7cHLsMt#HIFHuILPLr KH[A^]bK@UHSPHWKH cHHKHHHKHHHtHAH[]fUHHcHHGHFHGHFHtH@]fDUHSPH_HtHHCHtH[]HHPHH[] KUHAVSII^Ht#HHCHuHHPH| KL[A^]l Kfffff.UHH6HHH@]ff.UHH uv^H1H9NHD]DUHHc]UH]f.UH] KfDUHSPH KH cHHKHSHHHPH[]fff.UHHcHHGHOHNHF]UH]f.UH]t KfDUHAWAVSPID:D9}"fI~Av1A9uH[A^A_]fff.UHH v^H1H9NHD]DUHH}c]ÐUHAVSHPIH{pbHHE( KHþ H KHHCHCXHC`HCXHCHHC@HC8HC0HC(HC HCPHCpHCxHCpHChƃHǃfǃHǃHǃƃHHǃHǃHǃHǃHǃHǃHǃHǃHǃHHHǃHǃHǃǃǃHǃ H]=H5[0MH}HH5k/MH+H517OH\HA H5JNKHHH;HHHH '/cHMHHUHuHuIIFIF0INIVIF@H]HEHtH<#H KH-nbHH;Eu LHP[A^] KIH]HEHtH"HM KLK DUHAWAVAUATSHIIIHmbHHE1L;HHL0L8W)`HDžpHCH+CHH.袋.HH`F5LsL{M9t]L`H]fffff.LuHhH;psL0HhIXM9ufDLHBIXM9uW)EHEIH@H`LELH0xH@HH8taHHDž@H}Ht H}KH`Ht HhKHflbHH;EHHĨ[A\A]A^A_]H}tPHUHL.L@HDž@MtAFt I~eKL]KH}HdhHHDž@H}H@DK0KIH`˴.H5O,MH ,MH}L`8W)@HDžP KHP(?\)@He input.HHHsequenceHHHptr for HHHGot nullH@AHLHuH@L|E1H5bH~LKZHALeMuFzHAL`MHH@t HPKLeMt6HEL9t!Lh@t HxKLM9uH}LLeKEuEuL`Mu&^H}KEtH}KL`Mt:HhL9t=Lh@t HxTKLM9uH`Lh9KEtJL\K@LHL@HDž@Mu+H}HuQH`Ht HhKH*K AFt I~KLKH}Ht HH}HtH}KH`HuHH`HuHH`Huf.UHHH "bHHxH@Ht]FK]fDUHSPHHbHH{HCHtKHH[]KfUHAWAVSPI KHL=bL;H{LpHHLL2H]cHHH[A^A_]L;IH{HCHt +KIHyKLK UHAVSHPIHgbHHE(TKHþ HJKHHCHCXHC`HCXHCHHC@HC8HC0HC(HC HCPHCpHCxHCpHChƃHǃfǃHǃHǃƃHHǃHǃHǃHǃHǃHǃHǃHǃHǃHHHǃHǃHǃǃǃHǃ H]轓H5'MH}H +HB6H5KHHH5'MHH5.OHHA H5EKHHH;HHH &cHMHRHUHuHuIIFIF0INIVIF@H]HEHtHHKHebHH;Eu LHP[A^]7KIH]HEHtH]HKLJ ff.UHAWAVAUATSHIIHebHHE1L螖HHtpHl^1LeH<HHKH+KHH.袋.HHIHdbHH;EuLHĈ[A\A]A^A_]TKKIHh蝭.H5%MH D&MH}Lh +W)PHDž` JH`(8\)PHe input.HHHsequenceHHHptr for HHHGot nullH@AH LHuHPLNE1H5bHvLaJJIHh跬.H5%MH ^%MH}Lh#$W)PHDž`0JH`(8\)PHt tensorHH%Houtput tHH Hptr for HHHGot nullHHHLength: HHHSequenceH@-AH#%MHuHPLLE1H5bHuL_J IALeMIALhMIIALeMFIALhMnIIPt H`JLeMt6HEL9t!HX@t Hx\JHI9uH}LLeBJEuEu LhMu-'H}JEtH} JLhMHpL9HX@t HxJHI9uIPt H`JLeMt6HEL9t!HX@t HxJHI9uH}LLevJEuEuLhMu&^H}SJEtH}DJLhMt:HpL9tEHX@t HxJHI9uHhLpJEtL!JL1J L@UHAWAVATSH`IHg`bHHEؿ(JHþ HJHHCHCXHC`HCXHCHHC@HC8HC0HC(HC HCPHCpHCxHCpHChƃHǃfǃHǃHǃƃHHǃHǃHǃHǃHǃHǃHǃHǃHǃHHHǃHǃHǃǃǃHǃ H])H5G MH}HHH5.KHHlI(I.HW)EHEJHEHHHML HXHMH5KHULH5 MHH5&OHHA H5=KHHH;HHH cHMHūHUHuHuIIGIG0IOIWIG@H}Ht H}JH]HEHtHHJH]bHH;EuLH`[A\A^A_]4JIH]HEHt7HVHJLJ IH}HuH]HEHuLJ H}rJH]HEHt룐UHAWAVAUATSHIIH\bHHE1L^HH L5;HH$H8HSH+SHH.袋.HHHH9H9@HxHy +HH8L(HH4IM}1LL\HLL L`PMuMuPM9#I}0HPhHxLz!H1ff.LLaJHLy!IIH9|H0HnMH`HyMH@H<KHEHxH`H8H@L0LMHLHf-xtSH}JH[bHH;EtJJL7y!II}0HPILLHJL(IHZbHH;EuLHĸ[A\A]A^A_]ÿ!JIH`輣.H5MH MHxL`V&W)@HDžP JHP(.\)@He input.HHHsequenceHHHptr for HHHGot nullH@AHKHxH@LgE1H5{bHmLzJ5JIH`Т.H5/MH MHxL`Y:W)@HDžP0JHP(Me_)@Hdex tensHHHt for inHHHptr inpuHHHGot nullHf@ or@"AHMHxH@LuE1H5zbHlLJCJIH`ޡ.H5=MH MHxL`eHW)@HDžP0JHP(^)@Hut tensoHH Hfor outpHHHnullptr HHHAt: Got HHHSequenceHf@(rAHSMHxH@LyE1H5ybHkLJ IALeMuFzIAL`MII@t HPJLeMt6HEL9t!HX@t HxJHI9uH}LLeJEuxu#L`Mu0xH}JxtH}vJL`MMHhL9THX@t HxCJHI9u +IALeMIAL`MIIALeMLIAL`MzII@t HPJLeMt6HEL9t!HX@t HxJHI9uH}LLeiJEuxu#L`Mu00H}@JxtH}.JL`MHhL9 HX@t HxJHI9uI@t HPJLeMt6HEL9t!HX@t HxJHI9uH}LLeJEuxu L`Mu)aH}qJxtH}_JL`Mt:HhL9tEHX@t Hx4JHI9uH`LhJEt,L<JLLJ LIxt H}JL(J UHAWAVAUATSHHeTbHHEHG0@EătuIEhHcH ;TbH H;Mt*+HH !TbH H;MuHĘ[A\A]A^A_]JmJIHX.H5gMH hMHpLXErHHLHEH@HuHUH`Hp1LH H5EubHfL"J I@t HPJLeMt6HEL9t!HX@t HxJHI9uH}LLe{JEt H}lJpt H}ZJE1LXMuTH3IALXMt:H`L9t5HX@t HxJHI9uHXL`JEu +LILJLJ fDUHAVSHPIH[RbHHE(JHþ HJHHCHCXHC`HCXHCHHC@HC8HC0HC(HC HCPHCpHCxHCpHChƃHǃfǃHǃHǃƃHHǃHǃHǃHǃHǃHǃHǃHǃHǃHHHǃHǃHǃǃǃHǃ H]~H5;MH}HzH5MH H5OH<HA H5*0KHcHH;(HHH cHMHHUHuHuIIFIF0INIVIF@H]HEHtHHrJH PbHH;Eu LHP[A^]JIH]HEHtHH-JLmJ DUHAWAVATSH0IHHObHHEL%bL#H{H cHHCW)EE +LsHEEdtypfEeH}HULLH]HEHtCt H{JHwJEt H}hJHtIHNbHH;Eu H0[A\A^A_]JIEt H}(JL#H{HCHtJLOJ UHAWAVAUATSHHIIH|NbHHEH{HH+H1HxHH'HHIGHHH [HcHcYgR7hKhDd=e6Kc/h(f!dgd 1feHHxIHMbHH;EuLHĘ[A\A]A^A_],JJIH`u.H5MH eMHxL`{߄W)@HDžP0zJHP(-\)@HsequenceHH&Hutput seHH Htr for oHHHot nullpHHHEmpty: GHHHSequenceH@.AHMHxH@LE1H5:nbH_LJJIH`m.H5 MH ]MHxL`׃IHMHEH@HuHL"{Hx1LHnH5mbH_LJ I@t HPJL}Mt6HEL9t!HX@t HxJHI9uH}LL}JEt H}Jxt H}JE1L`MuTH蕌IAL`Mt:HhL9t8HX@t HxrJHI9uH`LhWJEu &LILIALeMuFzIAL`MII@t HPJLeMt6HEL9t!HX@t HxJHI9uH}LLeJEuxu L`Mu)aH}JxtH}zJL`Mt:HhL9tEHX@t HxOJHI9uH`Lh4JEtLWJLgJ Lf RRUHAWAVATSH`IHWIbHHEؿ(JHþ HJHHCHCXHC`HCXHCHHC@HC8HC0HC(HC HCPHCpHCxHCpHChƃHǃfǃHǃHǃƃHHǃHǃHǃHǃHǃHǃHǃHǃHǃHHHǃHǃHǃǃǃHǃ H]uH57 MH}HvIIHW)EHEJHEHHHML HXHMH5KHULH5 +MHH5OHHA H5&KHHH;HHH cHMHoHUHuHuIIGIG0IOIWIG@H}Ht H}$JH]HEHtHHJHFbHH;EuLH`[A\A^A_]>JIH]HEHt7H`HJLJ IH}HuH]HEHuLJ H}|JH]HEHtff.UHAWAVAUATSHHEbHHEHIIW)EHEHHI?tkH8MH b M1ALێ.H]HKHHCH5HHPHJH`EbHH;E 0H(IMl$0ID$I\$ W)PHDž`H)tnH8L0IILH=HWJILXLPKH`HL0H8~LHJILXHEH@HEHHHtH@HhHPH@L 3!HHHt#HHCHuHHPHJHPHt HXJLhLmM4$Mt$PM9tvI|$0HPhI|$Ht<xu6Ib!H~N1fLLqJLa!HIIH9|%a!HI|$0HPHLLHzJH(H{H;{sHh9!HCXHhH +IHh@<!H]HH<CbHH;EuLHĸ[A\A]A^A_]JHPJ IHPHuCILHMt#HIFHuILPL'JHPHtjHX JH]Hu^IIIHtACt H{JHJH]Hu*KIH]Hu;IHh?;!H]Ht#HHCHuHHPHJLJ fUHAWAVAUATSHIIHAbHHE1LnsIMLE IMII|$0HPhH9I?IH8I|$0yIH0HMHXHMH@Hl"KHEHpHXH8H@L0LMHLHG-pt H}cJH@bHH;ELH[A\A]A^A_]þLOIOI+OHH.袋.HH8H0HHHHH9H9HxH0H9ttupH:MHXHEMH@HW!KHEHpHXH0H@L8LMH跒LH2-Hy +HH0I~5HH+H1LHnH蠖HHVW)pHEHHpHLH8H0HE1ff.I9H(LLHp.H(HDž(HtCt H{fJH^JLLH HLHpH HDž HteCt H{JH JLfff.LLEHHLHp|HHDžHuDIH8H0L9H9LuGHHpLL!HHDžHtCt H{YJHQJI7HDiHLaMtBLyIIHYL9t7MI)HèfDH6!HèIXuI?L II)LM&JIGIGIHHpHAHxIHEHAIEH4=bHH;E6JJIHX).H5LH MHpLXtW)@HDžP .JHP(F\)@He input.HHHsequenceHHHptr for HHHGot nullH@AHMHpH@LvE1H5 +^bHsOLJJIHX=.H5LH LHpLXsW)@HDžP BJHP(*C^)@H tensor.HHHinput teHHHptr for HHHGot nullH@AHIKHpH@LuE1H5]bHNLJJIHXQ.H5LH LHpLXrW)@HDžP0VJHP(^)@HsequenceHH'Houtput sHH Hptr for HHHGot nullHHHInsert: HHHSequenceH@/AHLHpH@LtE1H5\bHMLJI@tHPJLeMuEIALeMt6HEL9t!HX@t HxRJHI9uH}LLe8JEupu#LXMuGuH}JptH}JLXMuIIALXM3H`L9HX@t HxJHI9uI@tHPJLeMuEIALeMt6HEL9t!HX@t HxSJHI9uH}LLe9JEupu#LXMuGvH}JptH}JLXMuJIALXM4H`L9HX@t HxJHI9u I@tHPJLeMuEIALeMt6HEL9t!HX@t HxTJHI9uH}LLe:JEupu LXMu=zH}JptH}JLXMuQIALXMt?H`L9t$HX@t HxJHI9uHXLL`JEuILJIpu"ILpMu+nIptbH}WH?xILpMtEHxL9tCMI)Hèf.H/!HèIXuHpLxJL9J Lfff.UHAWAVAUATSPIM'IGL)HH.袋.HH9H袋.H9MwLL)LkXLJHLM9tCHEM)IƨHIHfHǨL$,!HèHIƨIXuM7MgLHEHI?I_IGM9t"LL)IĨfDL.!IĨHXuMtLH[A\A]A^A_]JH[A\A]A^A_]ÿJHH5uKHFJH15bHHH53bH2bHJIHJLJ ffffff.UHAWAVATSH`IH4bHHEؿ(PJHþ HFJHHCHCXHC`HCXHCHHC@HC8HC0HC(HC HCPHCpHCxHCpHChƃHǃfǃHǃHǃƃHHǃHǃHǃHǃHǃHǃHǃHǃHǃHHHǃHǃHǃǃǃHǃ H]`H5LH}HI>I6HW)EHEJHEHHHML HXHMH5KHULH5LHNH5TNHHA H5mKHHH;kHHH JbHMHoHUHuHuIIGIG0IOIWIG@H}Ht H}JH]HEHtHMHJH>2bHH;EuLH`[A\A^A_]JIH]HEHt7HHVJLJ IH}HuH]HEHuLoJ H}JH]HEHtff.UHAWAVAUATSHIIH1bHHE1LbIMLINI+NHH.袋.HH8LkL0Ht?HH0HHH9H9HxфvHy +HH0LI%HH+HN1LH;H萇IM'I6L[W)pHEHpLH8~v1fff.H;0tSLHH(HLHp#L(HDž(MtAEt I}ZJLRJHH98M|$MMl$MII\$L9L MI)Hèffffff.H(!HèIXuL I}HKLHXHVLH@HhKHEHpHXH0H@L8LMHȁLHC-ptxH}_JH.bHH;EtoJMI#LM>6JIEIEIEHpID$HxIHEID$LI$H.bHH;EuLH[A\A]A^A_]ÿJIHXtw.H5LH LHpLXeW)@HDžP0yJHP(\)@HsequenceHH&Hutput seHH Htr for oHHHot nullpHHHErase: GHHHSequenceH@.AHLHpH@LhE1H59ObH@LJJIHXlv.H5LH LHpLXdW)@HDžP qJHP(\)@He input.HHHsequenceHHHptr for HHHGot nullH@AHLHpH@LgE1H5MNbH?L*JI@tHPJLeMuEIALeMt6HEL9t!HX@t HxJHI9uH}LLeoJEupu#LXMuGvH}FJptH}4JLXMuJIALXM4H`L9HX@t HxJHI9u I@tHPJLeMuEIALeMt6HEL9t!HX@t HxJHI9uH}LLepJEupu LXMu=zH}JJptH}8JLXMuQIALXMt?H`L9t$HX@t HxJHI9uHXLL`JEuILJyIptmH}bILpMuVILpMtGHxL9tEMI)Hèfff.H"!HèIXuHpLxIJLJ Lfff.UHAVSHPIH)bHHE(JHþ H +JHHCHCXHC`HCXHCHHC@HC8HC0HC(HC HCPHCpHCxHCpHChƃHǃfǃHǃHǃƃHHǃHǃHǃHǃHǃHǃHǃHǃHǃHHHǃHǃHǃǃǃHǃ H]}MH5JH}HHbUH5LHHH5@LHQH5WNHHA H5pKHHH;nHHH MbHMHvHUHuHuIIFIF0INIVIF@H]HEHtHbHJHS'bHH;Eu LHP[A^]JIH]HEHtHHsJL賿J ff.UHAWAVAUATSHIHH&bHHEH HLc(MH(I|$HH+Hq1L踰H^Hg}HMH0H8E11LLx0ffffff.LDEL9x0`JHH](z-^)EPHH5LJCPHHHM-HHHDžHHtCt H{ JHJEtH}JAE9DH8LPW)EHEH}L1L}@LH@HLL1L@HDž@MtAFt I~hJL`JD9|L8M|$MtHH0LpHII\$L9t9MI)Hè@H!HèIXuI>L8H0H&LM}LJIFIFIHEID$HEHHEID$H(HH A$bH H;MuHĸ[A\A]A^A_]߿J荿JIHh(m.H5LH SLH}Lh2[W)PHDž`@0JH`('_)PHt sequenHH(Hor outpuHH Hullptr fHHHt: Got nHHHConstrucHHHSequenceHf@0ce@2AHLHuHPL]E1H5DbHV6LʾJP腾JIHh l.H5LH KLH}Lh/ZW)PHDž` (JH`(P\)PHore inpuHHHe 1 or mHHHMust havHf@ts@AH7LHuHPL\E1H5DbHx5LJrIPtH`聽JLeMuEIALeMt6HEL9t!HX@t HxKJHI9uH}LLe1JEuEu LhMuDmH} JEtH}JLhMuDIALhM.HpL9HX@t Hx貼JHI9uIPtH`舼JLeMuEIALeMt6HEL9t!HX@t HxRJHI9uH}LLe8JEuEuLhMu:wH}JEtH}JLhMuQIALhMt?HpL9t$HX@t HxǻJHI9uHhLLp觻JEuqILŻJdILuMuVIEtMH}BILuMt;H]L9t<MI)HèfH!HèIXuH}Lu/JLoJ LfUHAWAVAUATSHH8HbHHEп(JHþ HJHHCHCXHC`HCXHCHHC@HC8HC0HC(HC HCPHCpHCxHCpHChƃHǃfǃHǃHǃƃHHǃHǃHǃHǃHǃHǃHǃHǃHǃHHHǃHǃHǃǃǃHǃ H]IIIH IW)EHE(>JHEHH(HML8L`LhHXLp HMYIQIIIHW)`HDžp(ѸJH`HH(HpL8L`LhLpHX HhH5JH}HUH`]HeJH5LHHIIHW)@HDžP;JH@HHHPL0HXHHH5#KH@LXH5LHH5NHHA H5JHAHH;HHH bHMHkHUHuHuH8HHCHC0HKHSHC@H@Ht HHRJH`Ht Hh:JH}Ht H}(JLuHEMtLLJHbHH;EuHHĨ[A\A]A^A_]=JIH`Ht?yIH`Ht.hIH`HtWIH@Hu0H`Hu<H}HuVH]HEHuuL赳J HH_JH`HtHhGJH}Ht IH}HtH}'JH]HEHtIH]HEHtHHJL0J UHAWAVAUATSH8IIHbbHHEL%tbM'IHH cIfHnfsAGIG ffEHEEEaxisEH}HUHML]H]E1HuLmHEtCt H{"JHJMoEt H}JffEEHEHkeepdimsHEEH}HUHML޲H]Hu1LuHEt3Ct H{覴JH螴JMwEu#AHEuMwEt H}oJH +bHH;EuH8[A\A]A^A_]諴JIEu IEt H}.JM'IIGHtJLUJ ffff.UHAWAVATSH@HIIHbHHE1HIǾHIIO0Qʃ +w*H5dHcHH}LHLIvHMHRLHEH(&MHEH]HuHUHMHϢ +H}H -HEIHEEtH}JHbHH;EtvH}LHLI$CH}LHLIj6,H}LHLI3HH}LHLI|HEIH>bHH;EuLH@[A\A^A_]޲JHIH謯J HEtH}PJIH良J :Qh@UHAWAVAUATSHIHpIIHbHHEHEID$HEEEEEEW)EHEMt5I@ I;@uDLkHHi L}H]HEHxpHEHx1E11WHuLmL}H]HUI9Hxt)Lffffff.H8 HH9u11LIVHuHt$0HuHt$(HuHt$ HuHt$HuHt$HuHt$HuH4$DLMLL/WI}t_HLH FL1ALZ^.H}HtHxH8`JHbHH;E LH[A\A]A^A_]H8L0L@IEM~LMf W)pHEM)tXMIHI9 +LޯJHHxHpJHEM~HLL,JLHxW)PHDž`LLHXHEHL`_11H@HH9uEtE fff.HEHHcH9LcHEHpL<W)@LHpH@jHI}tlA1ALHLH yL\.HHHHHCHrHHPH胭JEa(IEMd$0HpLxW)HDžI)tfHLHHH9LJILLIHMH~LLcJMLH@HHHHHtH@LLLHH!HHt#HHCHuHHPHbJHHt HFJLHËEHHcUIHXHL$HcE9Hu!HHcHHLrJHhHL4HHHBHHHHPsE1H)HhHHHRHHHHKvHIIHH HH(E1HLL覭JI<HJ4 L菭JH(H<H J4 LqJHH<HJ4 LSJILLL9uHPHLhHHtNHIL<MLHXJIHfLHILJLMLHuH8H90L`LH@HxW)HDžHxH+pHHH薀LxL+pM~oILuE11fDI9tKHpLHH;tHHHHHIL9|H&fDHIL9|W)HDžLLM)t[LHHH9L$JILLIHM~LLLoJMLHHHHt H贩JHHLtH蕩JHXH;`sHHA!HXXHPHHQHcHH!E1HHHEHHHEH9HpHxHH+H~ 1Hp蜗Ht HOdIE1It$0L8MwMtPMgIGHI_L9MI)Hèff.H!HèIXuI<$L`RI_uLPMHXL9MI)HèH!HèIXuHPLHL3JID$ID$I$HPIGHXHH`IGW)PHDž`IEHpHHx{JH}H LLXZJHpHu褧JRJIHpT.H5LLH LHLpWCW)PHDž`@JH`(^)PH be >= 0HH/Hes must HH(HAll valuHH H input. HHH 'split'HHHvalue inHHHInvalid H@7AHLHHPLnEE1H5,bH L聦J JH膣JHxJݿJIHpS.H5LH ULHLp#BW)PHDž`ƅP&Hould be HYHSplit shHQDža> 0AHLHHPLDE1H5+bH*L螥JHp襢JIPt H`"JL Mt?H(L9t$HX@t HxJHI9uH LL(פJuu&LpMuMH訤JtH蓤JLpMuIALpMHxL9`HX@t HxIJHI9u7TIHH :IHH>IPt H`JL MuQIAL Mt?H(L9t$HX@t Hx谣JHI9uH LL(萣Juu&LpMuFHaJtHLJLpMuQIALpMt?HxL9t$HX@t Hx JHI9uHpLLxJEuILJH}HIHpHV]ILPM+II]IEH+Ct H{mJHeJH}HIH}HIHHuXIHHt4H JHHu,IHHuIHHHɡJvIHHHuIHHt#HHCHuHHPH腠JHHHeJHHHu IH HHHt|HHCHujHHPHJLPMuYII]IEHt(Ct H{JHڠJHHHuIHHHuLPMtHHXL9tpMI)Hèffff.H HèIXuHPLXiJHpHt HxQJH}Ht H}?JLJ LfUHAWAVAUATSHIHpIIHbHHEHEID$HEEEEEEW)EHEMt5I@ I;@uDL'YHHi L}H]HEHxpHEHx1E11WHuL/[L}H]HUI9Hxt)Lffffff.H8 HH9u11LIVHuHt$0HuHt$(HuHt$ HuHt$HuHt$HuHt$HuH4$DLMLLOEI}t_HLH fL1ALzL.H}HtHxH8耞JHbHH;E LH[A\A]A^A_]H8L0L@IEM~LMf W)pHEM)tXMIHI9 +LJHHxHpJHEM~HLLLJLHxW)PHDž`LL +HXHEHL`_11H@HH9uEtE fff.HEHHcH9LcHEHpL<W)@LHpH@芉HI}tlA1ALH +LH LJ.HHHHHCHrHHPH裛JEa(IEMd$0HpLxW)HDžI)tfHLHHH9L<JILLIHMH~LL胝JMLH@HHHHHtH@LLLHH HHt#HHCHuHHPH肚JHHt HfJL HËEHHcUIHXHL$HcE9Hu!HHcHHL蒜JHhLN4HHHBHHHHPsE1H)HhHHHRHHHHKvHLHH HH(IE1HLLƛJI<HJ4 L诛JI<H(J4 L蘛JHH<HJ4 LzJILH L9uHPHLhHHtQHIL<MLHXJIHDLHILJLMLHuH8H90L`LH@HxW)HDžHxH+pHHHnLxL+pM~oILuE11fDI9tKHpLHH;tHHHHHIL9|HFofDHIL9|W)HDžLLM)t[LHHH9LDJILLIHM~LLL菙JMLHHHHt HԗJHHLtH赗JHXH;`sHHa HXXHPHHqHcHH E1HHHEHHHEH9HpHxuHH+H~ 1Hp輅Ht HoRIE1It$0L&MwMtPMgIGHI_L9MI)Hèff.H HèIXuI<$L`RI_uLPMHXL9MI)HèH HèIXuHPLHL3JID$ID$I$HPIGHXHH`IGW)PHDž`IEHpHHx蛕JH}H LLXzJHpHuĕJrJIHp C.H5lLH LHLpw1W)PHDž`@JH`(^)PH be >= 0HH/Hes must HH(HAll valuHH H input. HHH 'split'HHHvalue inHHHInvalid H@7AHLHHPL3E1H5bH- L衔J @JH覑JH蘑Jݿ>JIHpA.H58LH \LHLpC0W)PHDž`ƅP&Hould be HYHSplit shHQDža> 0AHLHHPL2E1H5bHJ L输JHpŐJIPt H`BJL Mt?H(L9t$HX@t HxJHI9uH LL(Juu&LpMuMHȒJtH賒JLpMuIALpMHxL9`HX@t HxiJHI9u7TIHH :IHH>IPt H`JL MuQIAL Mt?H(L9t$HX@t HxБJHI9uH LL(谑Juu&LpMuFH聑JtHlJLpMuQIALpMt?HxL9t$HX@t Hx-JHI9uHpLLx JEuIL(JH}HIHpHV]ILPM+II]IEH+Ct H{荐JH腐JH}HIH}HIHHuXIHHt4H-JHHu,IHHuIHHHJvIHHHuIHHt#HHCHuHHPH襎JHHH腏JHHHu IH HHHt|HHCHujHHPH:JLPMuYII]IEHt(Ct H{JHJHHHuIHHHuLPMtHHXL9tpMI)Hèffff.H8 HèIXuHPLX艎JHpHt HxqJH}Ht H}_JL蟋J LfUHAWAVAUATSHIHpIIHaHHEHEID$HEEEEEEW)EHEMt5I@ I;@uDLGGHHi L}H]HEHxpHEHx1E11WHuLOIL}H]HUI9Hxt)Lffffff.H8 HH9u11LIVHuHt$0HuHt$(HuHt$ HuHt$HuHt$HuHt$HuH4$DLMLLo3I}t_HLH L1AL:.H}HtHxH8蠌JH;aHH;E LH[A\A]A^A_]H8L0L@IEM~LMf W)pHEM)tXMIHI9 +LJHHxHpJHEM~HLLlJLHxW)PHDž`LLZHXHEHL`_11H@HH9uEtE fff.HEHHcH9LcHEHpL<W)@LHpH@wHI}tlA1ALH*LH L8.HHHHHCHrHHPHÉJEa(IEMd$0HpLxW)HDžI)tfHLHHH9L\JILLIHMH~LL裋JMLH@HHHHHtH@LLLHH HHt#HHCHuHHPH袈JHHt H膉JLPHËEHHcUIHXHL$HcE9Hu!HHcHHL貊JHhHL4HHHBHHHHPsE1H)HhHHHRHHHHKvHIIHH HH(E1HLLJI<HJ4 LωJH(H<H J4 L豉JHH<HJ4 L蓉JILLL9uHPHLhHHtNHIL<MLHXJIHfLHIL#JLMLHuH8H90L`LH@HxW)HDžHxH+pHHH\LxL+pM~oILuE11fDI9tKHpLHH;tHHHHHIL9|Hf]fDHIL9|W)HDžLLM)t[LHHH9LdJILLIHM~LLL诇JMLHHHHt HJHHLtHՅJHXH;`sHH HXXHPHH葱HcHH E1HHHEHHHEH9HpHx cHH+H~ 1HpsHt H@IE1It$0LMwMtPMgIGHI_L9MI)Hèff.H8 HèIXuI<$L`RI_uLPMHXL9MI)HèH HèIXuHPLHL3.JID$ID$I$HPIGHXHH`IGW)PHDž`IEHpHHx軃JH}H LLX蚃JHpHuJ蒃JIHp-1.H5LH cLHLpW)PHDž`@2JH`(^)PH be >= 0HH/Hes must HH(HAll valuHH H input. HHH 'split'HHHvalue inHHHInvalid H@7AHѮLHHPL!E1H5bHMLJ `JHJHJݿ^JIHp/.H5XLH /LHLpcW)PHDž`ƅP&Hould be HYHSplit shHQDža> 0AHݭLHHPL E1H5bHjLށJHp~JIPt H`bJL Mt?H(L9t$HX@t Hx7JHI9uH LL(Juu&LpMuMHJtHӀJLpMuIALpMHxL9`HX@t Hx艀JHI9u7TIHH :IHH>IPt H`/JL MuQIAL Mt?H(L9t$HX@t HxJHI9uH LL(Juu&LpMuFHJtHJLpMuQIALpMt?HxL9t$HX@t HxMJHI9uHpLLx-JEuILHJH}HIHpHV]ILPM+II]IEH+Ct H{~JH~JH}HIH}HIHHuXIHHt4HM~JHHu,IHHuIHHH ~JvIHHHuIHHt#HHCHuHHPH|JHHH}JHHHu IH HHHt|HHCHujHHPHZ|JLPMuYII]IEHt(Ct H{"}JH}JHHHuIHHHuLPMtHHXL9tpMI)Hèffff.HX HèIXuHPLX|JHpHt Hx|JH}Ht H}|JLyJ LfUHAWAVAUATSHIHpIIHaHHEHEID$HEEEEEEW)EHEMt5I@ I;@uDLg5HHi L}H]HEHxpHEHx1E11WHuLo7L}H]HUI9Hxt)Lffffff.H8 HH9u11LIVHuHt$0HuHt$(HuHt$ HuHt$HuHt$HuHt$HuH4$DLMLL!I}t_HLH L1AL(.H}HtHxH8zJH[aHH;E LH[A\A]A^A_]H8L0L@IEM~LMf W)pHEM)tXMIHI9 +L>zJHHxHpJHEM~HLL{JLHxW)PHDž`LLzHXHEHL`_11H@HH9uEtE fff.HEHHcH9LcHEHpL<W)@LHpH@eHI}tlA1ALHJLH يL&.HHHHHCHrHHPHwJEa(IEMd$0HpLxW)HDžI)tfHLHHH9L|xJILLIHMH~LLyJMLH@HHHHHtH@LLLHH/ HHt#HHCHuHHPHvJHHt HwJLpHËEHHcUIHXHL$HcE9Hu!HHcHHLxJHhLN4HHHBHHHHPsE1H)HhHHHRHHHHKvHLHH HH(IE1HLLxJI<HJ4 LwJI<H(J4 LwJHH<HJ4 LwJILH L9uHPHLhHHtQHIL<MLHXJIHDLHILCwJLMLHuH8H90L`LH@HxW)HDžHxH+pHHHJLxL+pM~oILuE11fDI9tKHpLHH;tHHHHHIL9|HKfDHIL9|W)HDžLLM)t[LHHH9LtJILLIHM~LLLuJMLHHHHt HtJHHLtHsJHXH;`sHH HXXHPHH豟HcHH+ E1HHHEHHHEH9HpHx@QHH+H~ 1HpaHt H.IE1It$0L +MwMtPMgIGHI_L9MI)Hèff.HX HèIXuI<$L`RI_uLPMHXL9MI)HèH HèIXuHPLHL3NrJID$ID$I$HPIGHXHH`IGW)PHDž`IEHpHHxqJH}H LLXqJHpHurJqJIHpM.H5LH 3LHLp W)PHDž`@RqJH`(:^)PH be >= 0HH/Hes must HH(HAll valuHH H input. HHH 'split'HHHvalue inHHHInvalid H@7AHLHHPLE1H5aHmLpJ pJHmJHmJݿ~pJIHp.H5xLH LHLp W)PHDž`ƅP&Hould be HYHSplit shHQDža> 0AHLHHPLE1H5!aHLoJHpmJIPt H`oJL Mt?H(L9t$HX@t HxWoJHI9uH LL(7oJuu&LpMuMHoJtHnJLpMuIALpMHxL9`HX@t HxnJHI9u7TIHH :IHH>IPt H`OnJL MuQIAL Mt?H(L9t$HX@t HxnJHI9uH LL(mJuu&LpMuFHmJtHmJLpMuQIALpMt?HxL9t$HX@t HxmmJHI9uHpLLxMmJEuILhmJH}HIHpHV]ILPM+II]IEH+Ct H{lJHlJH}HIH}HIHHuXIHHt4HmlJHHu,IHHuIHHH)lJvIHHHuIHHt#HHCHuHHPHjJHHHkJHHHu IH7 HHHt|HHCHujHHPHzjJLPMuYII]IEHt(Ct H{BkJH:kJHHHuIHHHuLPMtHHXL9tpMI)Hèffff.Hx HèIXuHPLXjJHpHt HxjJH}Ht H}jJLgJ LfUHAWAVAUATSHIHHIHaHHEHEHCHEEEEEEW)EHEMt5I@ I;@uDL#HH +L}HEHLulLu1HE11SHuL%L}HULuI9t(LH8HH9uH1 1LIT$HuHt$0HuHt$(HuHt$ HuHt$HuHt$HuHt$HuH4$DLMLHI}tXH;LH zL1AL.H}HtI>hJHaHH;E8LH[A\A]A^A_]L@H8LHIEM|$Mt$ W)pHEM)Lt_MIHI9 LghJHHxHpJHEML~HLLiJLHxW)PHDž`LzH0HEH11HhLpHH9uEtEfHEHHcH9?LcHEHpL<W)@LHH@SH(I}tlA1ALHzLH yL(.HHHHHCHHHPHfJEIEMl$0HpLxW)HDžI)tfHxLHHH9!LfJILLIHMHx~LLgJMLH@HHHHHtH@LLLHH_ HHt#HHCHuHHPHdJHHLt HeJLyqIŋULcuMHhH@H0L<HcMD9u:AօHcHH@DLLcJIIHuEJH4@1LHPHXH`HHH@IHxHIH@MtIfffff.LH!cJHIIuHxHHPH9LLHXH`zHH9@H8HHxW)HDžHxH+pHHH9LLxL+pM~oILuE11fDI9tKHpLHH;tHHHHHIL9|Hv:fDHIL9|W)HDžLLM)Ht[MIHI9LmcJILLKHM~LLLdJMLHH۸HHt HcJHHLLt HbJHXH;`sH蕽 HXXHPH謎IcHhH* E1LpHHHHEfH(HHEH9HHx@@HH+H~ 1HPHt HIE1It$0L +M~MtPMfIFHI^L9t>LpMI)HèHX HèIXuI<$Lp I^,LHL;aJID$ID$I$HPIFHXHH`IFW)PHDž`IEHpHt Hx(aJLHH}H!$LPMtHXL9t4MI)Hèffffff.Hh HèIXuHPLLX`JHpHpw`J`JIHpC.H5LH ߏLHLpW)PHDž`@H`JH`(0^)PH be >= 0HH/Hes must HH(HAll valuHH H input. HHH 'split'HHHvalue inHHHInvalid H@7AHLHHPLE1H5aHcL_J H\JH\JZ_Jt_JIHp .H5nLH LHLpyW)PHDž`ƅP&Hould be HYHSplit shHQDža> 0AHLHHPLE1H5aHL^JHp[JIPt H`x^JH Ht?H(H9t$Lh@t HxM^JLL9uH HH(-^Juu&LpMuFH]JtH]JLpMuQIALpMt?HxL9t$HX@t Hx]JHI9uHpLLx]JEuIL]JH}HIHH :IHH3IPt H`]JL MuQIAL Mt?H(L9t$HX@t Hx\JHI9uH LL(\Juu&LpMuFH\JtHx\JLpMuQIALpMt?HxL9t$HX@t Hx9\JHI9uHpLLx\JEu~IL4\JH}HosIHpHBIILPMII]IEHCt H{[JH[JH}HIH}HIHHuXHIHHt4H9[JHHu,IHHuIHHHZJIHHt#HHCHuHHPHYJHHHZJHHHuO{II]IEHtvCt H{gZJH_ZJHHHu]IHHHtNHHCHu<HHPH#YJLPMu+hIH蒷 HHHuLPMt?HXL9tgMI)Hè@HX HèIXuHPLXYJHpHt HxYJH}Ht H}YJLVJ LfUHAWAVAUATSHxLxDtIIH}L}HܽaHHEMuM+uIHhH~L0IIMHH]LH HcH9HMI7L HcH9HM I7HƸL9tLe HcH9kLm@HM(ttgLu8HHIIAHxL9tHE0IGHMUIML)HHH)vULMUKJ HWMeIEI9HHL)HHH1LsIIEKJ HLHHHHOMDLLIdLHfInfpDHVHHyH]1HHxHffEHEMHHHH9H<6WJIHhHA LmLmMtLuHrH!I9I9LHSHHt#Hfffff.H8H9HHHuH@HHHHQHHQHHQHHQ HHQ(HHQ0HHQ8H@HuI?I!IPHHwH |f1fHHWH)1ېAADAD AD0AD@ADPAD`ADpAڀAڐAڠAڰAAAAH HkHt(ILHfffff.AH HuI9t)LH)IHfff.L"HHHIMH)HLeHHMcH II!fInfpDIHHH{H1H8HVH)f1fDAofAoDfAoL Ao\0Aod@ffAoTPffAoD`fAoLpfHHuHt$ITHfoRfofH HuffpNffH~L9tK ff.HHH9uHUH9uL)HHxHGH~LHEH~LHEHeJHEH]HuHUHMLELMH +LeLHK#-EH}fSJHaHH;ESJKHOH)1fffff. 0@P`pDހDސDޠDްDDDDH HuHtLILHfAH HuL9L)JHff.LHHHE1E1MHHHzHHNHtB~fpDHyH)1ADADAD AD0HHu1Ht~fpDADADH9uiLuMt#MgLQJIGIGIM/MwMwLeI$HaHH;ELHx[A\A]A^A_]ILH)HSHHb+QJH}NJ HH}HtH} HEt H}QJHHNJ UHHH 3bHHxH@Ht]PJ]fDUHSPHH3bHH{HCHtPJHH[]PJfUHHH B3bHHxH@Ht]fPJ]fDUHSPHH3bHH{HCHt5PJHH[]'PJfUHHH 2bHHxH@Ht]OJ]fDUHSPHH2bHH{HCHtOJHH[]OJfUHHH b2bHHxH@Ht]OJ]fDUHSPHH02bHH{HCHtUOJHH[]GOJfUHHH 1bHHxH@Ht]OJ]fDUHSPHH1bHH{HCHtNJHH[]NJfUHHH 1bHHxH@Ht]NJ]fDUHSPHHP1bHH{HCHtuNJHH[]gNJfUHHH 1bHHxH@Ht]6NJ]fDUHSPHH0bHH{HCHtNJHH[]MJfUHAVSIMJHH0bHH{Lc+Hd.cHH[A^]IHMJLJJ fff.UHAVSIMJHH20bHH{L+Hd.cHH[A^]IHDMJLJJ fff.UHAVSI&MJHHLaH[A^]IHLJL9JJ UHAVSILJHH/bHH{Lc*H$.cHH[A^]IHLJLIJ fff.UHAVSILJHH2/bHH{L*H$.cHH[A^]IHDLJLIJ fff.UHAVSI&LJHH.bHH{L)H$.cHH[A^]IHKJL$IJ fff.UHAVSI(KJHHLΕH[A^]IHKJLHJ UHAWAVAUATSH8LLHHIHHaHHEH8H.aHHHLH@H8LJJHHEEL-laMuLI@L8LIJL='aILHDž(HDž HDžHDžDž0I$HMJHHHHH0H4IJHHHLJHHH~HH0HHJHHHLJHHHDHHHLL8Lt H IJHHJH5٭aHH=HJH8EIJH.aHH;EuHH8[A\A]A^A_]IJHLL8Lt H <IJHHJ+HHHHHHH5&aHHGJH8HJHHH8{HJHUHAWAVAUATSH8MLHHHHHaHHEH8HZaHHHLH@H8LGJHEEL-aM}LI@L8LFJL5ZaILHDž(HDž HDžHDžDž0HHHHLMHHHLL8Lt H \GJH<FJH5saHHEJH8FJHȫaHH;EuHH8[A\A]A^A_]cGJHLL8Lt H FJHEJHH5aHHLEJH8TFJHHH8=FJHuDUHAWAVAUATSHHaHHEHHC0@t"uOHHcH تaH H;Mt-HkHH aH H;MuHĘ[A\A]A^A_]YFJFJIH`-H5lLH arLHxL` H{0CH@HxrLHEHHHuH@HwHx1LHH5aH5LEJ IHt HXAEJE1LmMuMHIALmMt6HEL9t!HX@t HxEJHI9uH}LLmDJEuxu L`Mu=uH}DJxtH}DJL`MuLIAL`Mt:HhL9t5HX@t HxoDJHI9uH`LhTDJEu +LILmDJL}AJ DUHAWAVAUATSHIIHaHHEI ILLIG0@t|LtHMILxffff.Hc HxIFI;FsHHIFHIuzDLLHIu^LiHMtNIDIFI;Ft&H HHIFHIu!fff.LHHIuHaHH;EuHĘ[A\A]A^A_]BCJBJIH`-H5hLH oLHxL`I0,H@HaoLHEHHHuH@H`Hx1LH|H5aHLBJ IHt HX*BJE1LmMuMHIALmMt6HEL9t!HX@t HxAJHI9uH}LLmAJEuxu L`Mu=uH}AJxtH}AJL`MuLIAL`Mt:HhL9t5HX@t HxXAJHI9uH`Lh=AJEu +LILVAJLf>J fffff.UHAVSHPIHaHHE(@JHþ H@JHHCHCXHC`HCXHCHHC@HC8HC0HC(HC HCPHCpHCxHCpHChƃHǃfǃHǃHǃƃHHǃHǃHǃHǃHǃHǃHǃHǃHǃHHHǃHǃHǃǃǃHǃ H]H5fKHt eH eH}4IH5oLHn eH eHI11H;MH5ZoLHCH5"lNHMDHH HQH54JHmEHH;2:HHH dbHMHHUHuHuIIFIF0INIVIF@H]HEHtH&XH|>JHaHH;Eu LHP[A^]>JIH]HEHtHWH7>JLw;J ffffff.UHAVSHPIHaHHE(>JHþ H=JHHCHCXHC`HCXHCHHC@HC8HC0HC(HC HCPHCpHCxHCpHChƃHǃfǃHǃHǃƃHHǃHǃHǃHǃHǃHǃHǃHǃHǃHHHǃHǃHǃǃǃHǃ H]H5cKHeH eH}DFH5lLH~eH eH'F11HKJH5jlLH,@H52iNH]AHA H5KJHBHH;I7HHH (abHMH&HUHuHuIIFIF0INIVIF@H]HEHtH=UH;JH.aHH;Eu LHP[A^];JIH]HEHtHTHN;JL8J fDUHAVSI6;JHHLH[A^]IH ;JLI8J UHAWAVAUATSHHIHaHHEL-bM,$I|$cHcI$W)pHEƅpfDžqtoƅsH}HpHMH8pt H}d:JH}u/EAD$HaHH;EuHĨ[A\A]A^A_]:J<:JH0HX-H5GjLH jLHpLX=W)@HDžP 9JHP(к^)@Hnot set.HHHe to is HHHAttributH@<HOJHpH@H0Dž<H5aHH09JIǰ<LuMuKIǰ<HXHII@t HP8JLuMt6HEL9t!HX@t Hx8JHI9uH}LLu8JEupu HXHu)aH}}8JptH}k8JHXHt:H`H9tiLp@t Hx@8JLL9uHXH`%8J<t H0@8JLuHEMt/AFt I~7JLHIpt H}7JM,$I|$ID$Ht7JL4J fff.UHHH RbHHxH@Ht]v7J]fDUHSPHH bHH{HCHtE7JHH[]77JfUHAWAVAUATSPHIH}1H.zIM}1HLIL迹 HI}0GA;D$u]M&MfPMuMuPM9HPhHtSxuMLw H~g1LL4JHLZ IIH9|@ILLLMD'L* HI}0HPHLLH7JHEHH[A\A]A^A_]ÐUHAWAVAUATSHHaHHEЉ LHHHDž(HD> NDpHDžxAu@Hq IHRvHHSM~hI1E1AAH IHuHH||MnIs\10AHDžxAA|LHHyHHVH1H/!LHHyHHrHH~H)1ffo [ff.f81f81\fvfvff\f81Tf81\ fvfvffT \0HHuHt4f81f81Lffvfvfo^[ffLI9t1fnN[fffff.< fouff~ HI9uILxA rA H[ IH<tHHݿM2Is1LHHyHHVH 1HCHzH)1fff.f813f81L3Lf81D3f81L3 D L0f81D3f81L3D@LPf81D3f81L3D`LpH HuHHHf81D3f81 3D HHuHzH)1f823f82L3Lf82D3f82L3D L0f82D3f82L3 +D@LPf82D3 f82L3D`LpHHuHHHf82D3f82 3D HHu1H HI9uDpHDžxAAH= IHrHHMIs1LHHyHHVH s1HHzH)1ff823f82L3Lf82D3f82L3D L0f82D3f82L3 +D@LPf82D3 f82L3D`LpHHuHt9HH@f82D3f82 3D HHu  HHI9uILxAA H IHpHH{M'IVDHs1HI)1~^ffffff.<fouVff Ѐ|fotRfL|fouVffL|fotRfLHI9uXff.f Ѐ|fouffL|fotfL|fouffLHI9SHt9HH1~E^ffff.<fouff HH9uILxA *A =H{ IH\oHHM~ Is&1bA ILxALHHyHHVHs1HHzH)1Df813f81L3Lf81D3f81L3 D L0f81D3f81L3D@LPf81D3f81L3D`LpH HuHHHf81D3f81 3D HHukA&H4 IHnHHMcIs1FLHHyHHVH0s1H#HzH)1ff803f80L3pLpf80D3f80L3Dp Lp0f80D3 f80L3(Dp@LpPf80D30f80L38Dp`LppH@HuHHHf80D3f80 3Dp pHHukA&H IHlHHVM\Is1?LHHyHHVH0s1HHzH)1ff803f80L3pLpf80D3f80L3Dp Lp0f80D3 f80L3(Dp@LpPf80D30f80L38Dp`LppH@HuHHHf80D3f80 3Dp pHHudAcHԭ IHkHHFMI rJ #H9HLH91I|$H)LHtHD HHuH/ T TT TT THI9uAILxALHHyHHVH`s 1Hu}HzH)1fffff.3L30L0D3 L30D0 L00D3@L3PD0@L0PoD3`oL3pD0`L0pHHuHt.HHoD3o 3D0 0H HuI9LxDpILxAA +fH IHiHH"|M%IrJ #H91J `H9$1IT$H)LHt4H< tf<f<HHHu1f<HHHuH1Ҁ< tSf<f4H| uOftH| tSf<ftH| uOfTHHI9uMff.f4H| tf<ftH| uftH| tf<fTHHI9YA +ILxALHHyHHrHtvH~H)1ffo Ô]f80f80\fuffufP\Pf80Tf80\fuffufTP \P0H Hu1Ht4f80f80Lffufo>]ffufPLPI9LxDpILxAAfAmHg IHHgHHyMI rJ #H9HLH91I|$H)LHtH HHuH/ T TT TT THI9uAILxA LHHyHHVH`s 1Hu}HzH)1fffff.3L30L0D3 L30D0 L00D3@L3PD0@L0PoD3`oL3pD0`L0pHHuHt.HHoD3o 3D0 0H HuI9LxDpILxA -AH IHhHHrM%IrJ #H91J `H9$1IT$H)LHt4H< tf?f<HHHu1f<HHHuH1Ҁ< tSf?f4H| uOftH| tSf?ftH| uOfTHHI9uMff.f4H| tf?ftH| uftH| tf?fTHHI9YAILxALHHyHHrHtvH~H)1ffo ]f80f80\fuffufP\Pf80Tf80\fuffufTP \P0H Hu1Ht4f80f80Lffufo]ffufPLPI9LxDpILxAH IHfIH0HM~vE1LC4.LZJufHCHC1HXJHHCHHHKHIHM9|LxILxHp>H( HD8DpHDžxA u@H* IHHH<gMIsb1~E1AAH IH褜HHEkM.I1dLHHyHHrH$H~H)1ffo 5\fo=\ffff.oodfvffvff8f~f8f~do\ od0fvffvff8f~\f8f~d HHuHiLHHyHHVH HzH)1fff.L[[LD L0[[D 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HPH)HHHHUH}HtAIHI fUHAWAVAUATSPHL3HCL)HHHH9H -H9LcM)HL<vLIIJ4 HUUUUUUULHHH?HHHRL,M~LHuLLIHuL+HsL{MtLH[A\A]A^A_]`IH[A\A]A^A_]ÿ_IHH5ZIHIH`HHH5B`HS`H_IIH6ILFI fffff.UHAWAVAUATSHxHH}HCHK(H+HILHy0HPHHEEyDHEHEHHE11HEHMfH9HRHDH6HxHtHHHH<L7LwPHY(H{PH;H}HH}H}HHuLuH<H<HpE11E1HhHEI<y8LuH`t7HHMHIHLIIHIu&fDHEHH}HHHuHUIHMLy HuH`HILuLpHhI9\ǃHH}uE11H}LmLII)ME11kff.HEH<H}H}LHUgIHuHMIHY y8uAHEH<H}H}HUJ4"4IHuHMfDy8tIHY y8tHY IMIuH}t6y8u0H]HEHH}HLHuLHUIHuHMHuHxHH;UHEHHx[A\A]A^A_]fffff.UHAWAVAUATSHxIIH`H[`HHELHD(W)pHEIcHp1E~R1LufDLQHEHxH;MsHHxD9|HpLD9|W)EHEIHhHpLELLzHhHH`t^HHDžhH}Ht H} IHpHt Hx IHH`HH;EHHx[A\A]A^A_]H}tMHUHLhHDžhMtAFt I~m ILe IH}HjnHHDžhH}HFJ IHLhHDžhMuH}HuEHpHupH; -I AFt I~ IL IH}Ht HH}HtH} IHpHt HHpHtHHpHtHx IH I UHAWAVAUATSPIHL3HCL)HL9sjLH=upLcM)J<6 IIKDMMM~LLLI ILL+L{HCMtLH[A\A]A^A_] IH[A\A]A^A_]ÿ IHH5qTIHB IH `HHH5`HЀ`H IIH ILI ff.UHHH aHHxH@Ht]F I]fDUHSPHHaHH{HCHt IHH[] IfUHAWAVSPI -IHL=aL;H{L@HH1LOH bHHH[A^A_]L;IH{HCHt - -IIH| -ILI @UHAWAVAUATSHHՁ`HHEIAGAIW)EHEEEaxisEHhHULHhHDžhHtCt H{ IH IEt H} IHEg EW)EEHEHnew_axisHEEHPHUHhL]HPLhHDžPHtCt H{N IHF IHM AOEt H}% IH`HH;EuHĈ[A\A]A^A_]^ I IIHh跶,H5>KH ?KH}Lh 4oW)PHDž`0IH`(W])PHttributeHHH'axis' aHHHe valid HHHMust havH@ AH]NHuHPLxqE1H5n`HJLkI<IALeMuFzIALhMIIPt H`ILeMt6HEL9t!HX@t HxIHI9uH}LLeIEuEuLhMu&^H}jIEtH}[ILhMt:HpL9t=HX@t Hx0IHI9uHhLpIEt,L8I"LIEu IEt H}IL$I fff.UHAWAVSPI IHL=O`L;H{LHH1LHaHHH[A^A_]L;IH{HCHt -YIIHLILI @UHAWAVSPI 3IHL=`L;H{LHH1LH`aHHH[A^A_]L;IH{HCHt -IIHILI @UHAWAVAUATSHHMMHHIHH|`HHEH8H2{`HHHHH@H8HILLHEEL-i|`MuLI@L8HIL=$|`ILHDž(HDž HDžHDžDž0A$It$IEt$IET$HwHE HMLMHD$H $HHHHL,HHHv}LL8Lt H -IHIH5{`HHIH8IHV{`HH;EuHHH[A\A]A^A_]IHLL8Lt H IHdI HsHH5nz`HHIH8IHRsHH8IH;sff.UHAWAVAUATSHLMLEIIIL6LILLHEvI]HeILHH+vI4$LIHEHH<ILHHvHEH0LeIHEHHILHHuHEH0L9IH[A\A]A^A_]H`rHXrHPrHHrH@rH8rH0rUHAWAVAUATSH(IIMgIGI9I?I_HH)vpLuHHAH?LtIJII)I)LHLMt"ILHLH'IHIMwLMdMgIGLulH)HHHALEMt$H}LH=jJ<IIH}1NINL9LuMT$MI)IIVHr!JLI9KL5HLH9LI)DHt#Hffff.H3H1HHHuI8p1ҐH4H4HtHtHtHtHtHtHt Ht Ht(Ht(Ht0Ht0Ht8Ht8Ht@H@L9u M LEH?HUH!HMHqHHJH 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HHILHM<HDžHA1HHHI9HfHnfb+Zf\3Zf|fhH@HpWH*x0HH eaHHHHHHHHHHHHH HHX(HHhLLLL,HI9t HtHP(HP HHHNHuHu}H)κfffff.]_]_HH9uHt0]_((DžW.IG܋ .IGDžfnfn.u z - Z \^ g\A^W\]g\_.z5(,ZT.ңZs" Z()P+H(P\,H`HZj`HH;EuHĈ[A\A]A^A_]HHHI9uHP HH HtHP(HH fDUH]f.UH]dHfDUHSPH0WHH aHHKHSHHHPHKHHHK HH HK(HH(H[]@UHHeaHHG(HF(HG HF HGHFHGHOHNHF]UH]f.UH]HfDUHHHOHwH ILH6H -H9HOHwHH>Hw JHH(H4HTL)H]{.UHH f\H1H9NHD]DUHHa]UHAVSHPIHh`HHE(HHþ HHHHCHCXHC`HCXHCHHC@HC8HC0HC(HC HCPHCpHCxHCpHChƃHǃfǃHǃHǃƃHHǃHǃHǃHǃHǃHǃHǃHǃHǃHHHǃHǃHǃǃǃHǃ H]H5HH}H*H5JH+H5MH\HH HQH5s3IH|HH;AHHH 0'aHMH%?HUHuHuIIFIF0INIVIF@H]HEHtHuHHH6f`HH;Eu LHP[A^]HIH]HEHtH0HvHLH fffff.UHAVSHPIHe`HHE(DHHþ H:HHHCHCXHC`HCXHCHHC@HC8HC0HC(HC HCPHCpHCxHCpHChƃHǃfǃHǃHǃƃHHǃHǃHǃHǃHǃHǃHǃHǃHǃHHHǃHǃHǃǃǃHǃ H]H5HH}HjH5JHkH5MHHA H50IHHH;HHH w$aHMHlYHUHuHuIIFIF0INIVIF@H]HEHtHHHH}c`HH;Eu LHP[A^]AHIH]HEHtHwHHLH DUHAVSHPIHc`HHE(HHþ HHHHCHCXHC`HCXHCHHC@HC8HC0HC(HC HCPHCpHCxHCpHChƃHǃfǃHǃHǃƃHHǃHǃHǃHǃHǃHǃHǃHǃHǃHHHǃHǃHǃǃǃHǃ H]-H5HH}HH5JHH5FMHHH HQH5.IH HH;HHH !aHMHWHUHuHuIIFIF0INIVIF@H]HEHtHHKHH``HH;Eu LHP[A^]HIH]HEHtHHHLFH fffff.UHAVSHPIH[``HHE(HHþ HHHHCHCXHC`HCXHCHHC@HC8HC0HC(HC HCPHCpHCxHCpHChƃHǃfǃHǃHǃƃHHǃHǃHǃHǃHǃHǃHǃHǃHǃHHHǃHǃHǃǃǃHǃ H]mH5]HH}HH5VJHH5MH,HA H5J+IHSHH;HHH aHMHLiHUHuHuIIFIF0INIVIF@H]HEHtHLHHH ^`HH;Eu LHP[A^]HIH]HEHtHHMHLH DUHAVSHPIH]`HHE($HHþ HHHHCHCXHC`HCXHCHHC@HC8HC0HC(HC HCPHCpHCxHCpHChƃHǃfǃHǃHǃƃHHǃHǃHǃHǃHǃHǃHǃHǃHǃHHHǃHǃHǃǃǃHǃ H]H5HH}HJH5JHKH5MH|HH HQH5(IHHH;aHHH PaHMHfHUHuHuIIFIF0INIVIF@H]HEHtHHHHV[`HH;Eu LHP[A^]HIH]HEHtHPHHLH fffff.UHAVSHPIHZ`HHE(dHHþ HZHHHCHCXHC`HCXHCHHC@HC8HC0HC(HC HCPHCpHCxHCpHChƃHǃfǃHǃHǃƃHHǃHǃHǃHǃHǃHǃHǃHǃHǃHHHǃHǃHǃǃǃHǃ H]=H5HH}HH5 JHH5MHHA H5%IHHH;HHH aHMHxHUHuHuIIFIF0INIVIF@H]HEHtHH"HHX`HH;Eu LHP[A^]aHIH]HEHtHHHLH DUHAVSHPIH;X`HHE(HHþ HHHHCHCXHC`HCXHCHHC@HC8HC0HC(HC HCPHCpHCxHCpHChƃHǃfǃHǃHǃƃHHǃHǃHǃHǃHǃHǃHǃHǃHǃHHHǃHǃHǃǃǃHǃ H]H5=HH}HH56 JHH5f MH HH HQH5##IH,HH;HHH aHMHvHUHuHuIIFIF0INIVIF@H]HEHtH%HkHHU`HH;Eu LHP[A^]HIH]HEHtHH&HLfH fffff.UHAVSHPIH{U`HHE(HHþ HHHHCHCXHC`HCXHCHHC@HC8HC0HC(HC HCPHCpHCxHCpHChƃHǃfǃHǃHǃƃHHǃHǃHǃHǃHǃHǃHǃHǃHǃHHHǃHǃHǃǃǃHǃ H] H5}HH}HH5vJHH5 MHLHA H5j IHsHH;8HHH 'aHMHHUHuHuIIFIF0INIVIF@H]HEHtHlHHH-S`HH;Eu LHP[A^]HIH]HEHtH'HmHLH DUHAVSHPIHR`HHE(DHHþ H:HHHCHCXHC`HCXHCHHC@HC8HC0HC(HC HCPHCpHCxHCpHChƃHǃfǃHǃHǃƃHHǃHǃHǃHǃHǃHǃHǃHǃHǃHHHǃHǃHǃǃǃHǃ H]H5HH}HjH5JHkH5MHHH HQH5IHHH;HHH paHMHeHUHuHuIIFIF0INIVIF@H]HEHtHHHHvP`HH;Eu LHP[A^]:HIH]HEHtHpHHLH fffff.UHAVSHPIH P`HHE(HHþ HzHHHCHCXHC`HCXHCHHC@HC8HC0HC(HC HCPHCpHCxHCpHChƃHǃfǃHǃHǃƃHHǃHǃHǃHǃHǃHǃHǃHǃHǃHHHǃHǃHǃǃǃHǃ H]]H5 HH}HH5JHH56MHHA H5IHHH;HHH aHMHHUHuHuIIFIF0INIVIF@H]HEHtHHBHHM`HH;Eu LHP[A^]HIH]HEHtHHHL=H DUHAVSHPIH[M`HHE(HHþ HHHHCHCXHC`HCXHCHHC@HC8HC0HC(HC HCPHCpHCxHCpHChƃHǃfǃHǃHǃƃHHǃHǃHǃHǃHǃHǃHǃHǃHǃHHHǃHǃHǃǃǃHǃ H]H5]HH}HH5VIHH5MH,HH HQH5CIHLHH;HHH aHMH5HUHuHuIIFIF0INIVIF@H]HEHtHEHHHK`HH;Eu LHP[A^]HIH]HEHtHHFHLH fffff.UHAVSHPIHJ`HHE(HHþ H -HHHCHCXHC`HCXHCHHC@HC8HC0HC(HC HCPHCpHCxHCpHChƃHǃfǃHǃHǃƃHHǃHǃHǃHǃHǃHǃHǃHǃHǃHHHǃHǃHǃǃǃHǃ H]H5HH}H:H5IH;H5LHlHA H5IHHH;XHHH G aHMHlHUHuHuIIFIF0INIVIF@H]HEHtHHHHMH`HH;Eu LHP[A^]HIH]HEHtHGHHLH DUHAVSHPIHG`HHE(dHHþ HZHHHCHCXHC`HCXHCHHC@HC8HC0HC(HC HCPHCpHCxHCpHChƃHǃfǃHǃHǃƃHHǃHǃHǃHǃHǃHǃHǃHǃHǃHHHǃHǃHǃǃǃHǃ H]H5HH}HH5IHH5LHHH HQH5IHHH;HHH aHMHHUHuHuIIFIF0INIVIF@H]HEHtHHHHE`HH;Eu LHP[A^]ZHIH]HEHtHHHLH fffff.UHAVSHPIH+E`HHE(HHþ HHHHCHCXHC`HCXHCHHC@HC8HC0HC(HC HCPHCpHCxHCpHChƃHǃfǃHǃHǃƃHHǃHǃHǃHǃHǃHǃHǃHǃHǃHHHǃHǃHǃǃǃHǃ H]=H5-HH}HH5&IHH5VLHHA H5IH#HH;HHH aHMHHUHuHuIIFIF0INIVIF@H]HEHtHHbHHB`HH;Eu LHP[A^]HIH]HEHtHHHL]H DUHAVSHPIH{B`HHE(HHþ HHHHCHCXHC`HCXHCHHC@HC8HC0HC(HC HCPHCpHCxHCpHChƃHǃfǃHǃHǃƃHHǃHǃHǃHǃHǃHǃHǃHǃHǃHHHǃHǃHǃǃǃHǃ H]MH5}HH}HH5vIHH5LHLHH HQH5c IHlHH;1HHH aHMHŵHUHuHuIIFIF0INIVIF@H]HEHtHeHHH&@`HH;Eu LHP[A^]HIH]HEHtH HfHLH fffff.UHAVSHPIH?`HHE(4HHþ H*HHHCHCXHC`HCXHCHHC@HC8HC0HC(HC HCPHCpHCxHCpHChƃHǃfǃHǃHǃƃHHǃHǃHǃHǃHǃHǃHǃHǃHǃHHHǃHǃHǃǃǃHǃ H]H5HH}HZH5IH[H5LHHA H5 -IHHH;xHHH g`HMHHUHuHuIIFIF0INIVIF@H]HEHtHHHHm=`HH;Eu LHP[A^]1HIH]HEHtHgHHLH DUHAVSHPIH =`HHE(HHþ HzHHHCHCXHC`HCXHCHHC@HC8HC0HC(HC HCPHCpHCxHCpHChƃHǃfǃHǃHǃƃHHǃHǃHǃHǃHǃHǃHǃHǃHǃHHHǃHǃHǃǃǃHǃ H]H5 HH}HH5IHH56LHHH HQH5IHHH;HHH `HMHHUHuHuIIFIF0INIVIF@H]HEHtHH;HH:`HH;Eu LHP[A^]zHIH]HEHtHHHL6H fffff.UHAVSHPIHK:`HHE(HHþ HHHHCHCXHC`HCXHCHHC@HC8HC0HC(HC HCPHCpHCxHCpHChƃHǃfǃHǃHǃƃHHǃHǃHǃHǃHǃHǃHǃHǃHǃHHHǃHǃHǃǃǃHǃ H]H5MHH}HH5FIHH5vLHHA H5:IHCHH;HHH `HMHHUHuHuIIFIF0INIVIF@H]HEHtH<HHH7`HH;Eu LHP[A^]HIH]HEHtHH=HL}H DUHAVSHPIH7`HHE(HHþ H -HHHCHCXHC`HCXHCHHC@HC8HC0HC(HC HCPHCpHCxHCpHChƃHǃfǃHǃHǃƃHHǃHǃHǃHǃHǃHǃHǃHǃHǃHHHǃHǃHǃǃǃHǃ H]-H5HH}H:H5IH;H5LHlHH HQH5IHHH;QHHH @`HMHUHUHuHuIIFIF0INIVIF@H]HEHtHH˽HHF5`HH;Eu LHP[A^] -HIH]HEHtH@H膽HLƺH fffff.UHAVSHPIH4`HHE(THHþ HJHHHCHCXHC`HCXHCHHC@HC8HC0HC(HC HCPHCpHCxHCpHChƃHǃfǃHǃHǃƃHHǃHǃHǃHǃHǃHǃHǃHǃHǃHHHǃHǃHǃǃǃHǃ H]mH5HH}HzH5IH{H5LH謼HA H5HHӽHH;蘲HHH `HMHHUHuHuIIFIF0INIVIF@H]HEHtHHHH2`HH;Eu LHP[A^]QHIH]HEHtHHͺHL H DUHAVSHPIH+2`HHE(褺HHþ H蚺HHHCHCXHC`HCXHCHHC@HC8HC0HC(HC HCPHCpHCxHCpHChƃHǃfǃHǃHǃƃHHǃHǃHǃHǃHǃHǃHǃHǃHǃHHHǃHǃHǃǃǃHǃ H]H5-HH}HH5&IH˸H5VLHHH HQH5HHHH;HHH `HMH5HUHuHuIIFIF0INIVIF@H]HEHtHH[HH/`HH;Eu LHP[A^]蚸HIH]HEHtHHHLVH fffff.UHAVSHPIHk/`HHE(HHþ HڷHHHCHCXHC`HCXHCHHC@HC8HC0HC(HC HCPHCpHCxHCpHChƃHǃfǃHǃHǃƃHHǃHǃHǃHǃHǃHǃHǃHǃHǃHHHǃHǃHǃǃǃHǃ H]=H5mHH}H -H5fIH H5LH<HA H5ZHHcHH;(HHH `HMH<HUHuHuIIFIF0INIVIF@H]HEHtH\H袵HH-`HH;Eu LHP[A^]HIH]HEHtHH]HL蝲H DUHAVSHPIH,`HHE(4HHþ H*HHHCHCXHC`HCXHCHHC@HC8HC0HC(HC HCPHCpHCxHCpHChƃHǃfǃHǃHǃƃHHǃHǃHǃHǃHǃHǃHǃHǃHǃHHHǃHǃHǃǃǃHǃ H] H5HH}HZH5IH[H5LH茴HH HQH5HH謵HH;qHHH ``HMHHUHuHuIIFIF0INIVIF@H]HEHtHHHHf*`HH;Eu LHP[A^]*HIH]HEHtH`H覲HLH fffff.UHAVSHPIH)`HHE(tHHþ HjHHHCHCXHC`HCXHCHHC@HC8HC0HC(HC HCPHCpHCxHCpHChƃHǃfǃHǃHǃƃHHǃHǃHǃHǃHǃHǃHǃHǃHǃHHHǃHǃHǃǃǃHǃ H]MH5HH}H蚹H5IH蛰H5&LH̱HA H5HHHH;踧HHH `HMHHUHuHuIIFIF0INIVIF@H]HEHtHH2HH'`HH;Eu LHP[A^]qHIH]HEHtHHHL-H DUHAVSI֯HHHb`HH{L#HaHH[A^]IH蔯HLԬH fff.UHHH `HHxH@Ht]VH]fDUHSPHH`HH{HCHt%HHH[]HfUHAWAVAUATSH8HHHk&`HHE1H -IL?HxID$HM|$ HHILXHI~l1IfWf)`HDžpMJ<IIHI9 LHNHhH`J HpMKNIIIrL9J H9HHNDI)DHtHHHHHHuI8Y1ɐHHHTHTHTHTHTHTHT HT HT(HT(HT0HT0HT8HT8HT@H@L9uHhH11I?M!IpHHyH s 1Hu|HwH)1ffffff.LLD L0D L0D@LPD@LPfD`LpfD`LpHHuHt.H HfDfD  fD H HuM92HhHI)IJ|HhH)IL$It$ HH)HHH)v%HEH`HMH IL$It$ H9tdL`LhH)LL)1fDH9tQH|I\H9t&HuI|HH9u,fDHHH9uHL L`fWf)@HDžPLL)t^LIIHI9CHILHL@KHPHI)M~LL苬HMLHH@1HxHPL+H8IH`HL!I)MIM9LILH0HyHHHILALxHHH(LbHHH LLHILHMLLL'IžLMKDHHKTHHHHIt uIIIf.HCHI|ItHHHHHHIHIII_pffff.HHYHHHDžHx HHH@HIL0IHK|IfWf)HDžMHtJI9hMN<L蠨HHJHHL艨HHMLKDHHHHHxa+HcLHHIIHLpHHEPHH NaHHHHHHHH0HHH(HH H HH(H8HH0HxHH8HHH@HHHHHEfHnfbgSZf\oSZf|W)MfEHUH]LLHY+H}H91H.HP(#ME1fff.HIHHxL0L9}.L(L ESA)IKAH9uH1MuZi1efff.M)H1HHI<HI HHHI|HI\HHI9uMtHHI<IHH<H8HHxHŧHHJIM9 -J4J<+HP H0HpHH;OILL8LeLufDHHXLHE0趥HH }aHHHHH HHHHHHHH Lh(HEfInfbAQZf\IQZf|W)MfEHHLL4+H}I9tHtHP(fffff.HP HHHHH;?fDM1 -HHHHH H IHHHHHHH<IIL8K<M,JJL9vILM9r5sILHƥHHKMLL9vLM9sD@O4M9vIHMM9r'LHHrHMM9rfDHHLL9HHpHH;HHHHt HHLHDžMtLZHH HDž Ht>HH(HDž(Ht"HH@Ht HHHH`HtHH8HHp`HH;EHH8[A\A]A^A_]fWf)EE(HEHexpand sHEHinvalid HEEhapeEHMHHUr+EYH}K転HH`赟HH@觟H H號H IEH}HH`HIH}H9HuvHHHHDžHH HDž HH(HDž(HH@HHP(HHt`IHHpHIHHX0IHH@IH`HIH@HelIH HDž H# IH(HDž(H IH@HIH`HHhIH@HIH@HIH}I99HP HH8IHH#HHHHDžHҟHH HDž H貟HH(HDž(H 蒟HH@Ht HH耟HH`HtHH8eHL襜H 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Hr(H8LHH<IL6K<.MHLL9vILuM9r>|fff.ILHjHHKoMLL9vLuM9sGO4/M9vIHMM9r'LHuHUjHMM9rfHuHH;uH([A\A]A^A_]UHH U[H1H9NHD]DUHHmda]UHAVSIfhHHH]`HH{LAHbaHH[A^]IH$hHLdeH fff.UHAVSIhHHH]`HH{LSAHcaHH[A^]IHgHLeH fff.UHHH B]`HHxH@Ht]gH]fDUHSPHH]`HH{HCHtUgHHH[]GgHfUHAWAVAUATSH8HHH_HHE1H:IL菜HxID$HM|$ HHILVHI~IfWf)`HDžpMJ<IIHI9 |fHNHhH`J HpMKNIIIrL9J H9HHNDI)DHtHHHHHHuI8Y1ɐHHHTHTHTHTHTHTHT HT HT(HT(HT0HT0HT8HT8HT@H@L9uHhH11I?M!IpHHyH s 1Hu|HwH)1ffffff.LLD L0D L0D@LPD@LPfD`LpfD`LpHHuHt.H HfDfD  fD H HuM9-HhHI)IJ|HhH)IL$It$ HH)HHH)v%HEH`HMHIL$It$ H9tdL`LhH)LL)1fDH9tQH|I\H9t&HuI|HH9u,fDHHH9uHL L`fWf)@HDžPLL)t^LIIHI9scHILHL@KHPHI)M~LLdHMLHH@1HAHКL+H8IH`HL!I)MIM9LILH0HyHHHILALbHHH(LbHHH L|bHILHMLLL)IžLMKDHHKTHHHHIt uIIIf.HCHI|ItHHHHHHIHIII_rffff.HHYHHHDžHx fHHH@HIL0IHK|IfWf)HDžMHtJI9fMN<L`HHJHHL`HHMLKDHHHHHx\+HcLHHIIHLpHHEP>`HH \aHHHHHHHH0HHH(HH H HH(H8HH0HxHH8HHH@HHHHHEfHnfb Zf\ Zf|W)MfEHUH]LLHk+H}H9+H(HP(ME1ff.HIHHxL0L9}.L(L ESA)IKAH9uH1MuZi1efff.M)H1HHI<HI HHHI|HI\HHI9uMtHHI<IHH<H8HHxH_HHJIM9J4J<0HP H0HpHH;TIL -L8LeLuff.HHXLHE0]HH ZaHHHHH HHHHHHHH Lh(HEfInfbq Zf\y Zf|W)MfEHHLLdi+H}I9tHtHP(fffff.HP HHHHH;?fDM1 -HHHHH H IHHHHHHH<IML8K<fM,NJgLHL9vILM9r8vfDILH]HHKMLL9vLM9sD@O4gM9vIHMM9r'LHH]HMM9rfDHHLL9HHpHH;HHHHt H[HLHDžMtL[HH HDž Htn[HH(HDž(HtR[HH@Ht HH@[HH`HtHH8%[HH_HH;EHH8[A\A]A^A_]fWf)EE(HEHexpand sHEHinvalid HEEhapeEHMHH*+EYH}KZHH`WHH@WH HWH IEH}KZHH`HIH}H9HuvHHHHDžHH HDž HH(HDž(HH@HHP(HHt`IHHpHIHHX0IHH@IH`HIH@HelIH HDž H# IH(HDž(H IH@HIH`HHhIH@HIH@HIH}I99HP HH8IHH#H(XHHHDžHXHH HDž HWHH(HDž(H WHH@Ht HHWHH`HtHH8WHLTH ffff.UH]f.UH]dWHfDUHSPHPWWHH SaHHsHx HH[]fff.UHHSaHHGH~ HH]ffff.UH]f.UH]VHfDUHAWAVATSIL>L"M9IFINH0IHHxINLL9}.IN IV(L LESA)IKAH9uH1MuZi1efff.M)H1HHI<HI HHHI|HI\HHI9uMtHHI<IHH<IF0H8IF8HH0IF@HZWHIFHHJIM9[A\A^A_]fDUHH U[H1H9NHD]DUHH]Ra]UH]f.UH]dUHfDUHSPH0WUHH >RaHHKHSHHHPHKHHHK HH HK(HH(H[]@UHHQaHHG(HF(HG HF HGHFHGHOHNHF]UH]f.UH]THfDUHAWAVAUATSH(H}H6HHEH9 HUHBHJHHuHHRH2H H HHHHHUHB LB(HHHH<IHHIJ<cL4KJgMML9vIH]M9r3qIHLvUHMKMLL9vH]M9sGKgL9vIILL9r'LHuL%UHIL9rfHuHH;uH([A\A]A^A_]UHH [H1H9NHD]DUHHPa]UHAVSI6SHHHH`HH{L,H$OaHH[A^]IHRHL4PH fff.UHAVSIRHHHbH`HH{L#,H$PaHH[A^]IHRHLOH fff.UHHH H`HHxH@Ht]VRH]fDUHSPHHG`HH{HCHt%RHHH[]RHfUHAWAVAUATSH8HHHk_HHE1H -IL菔HxID$HM|$ HHӔILXAHI~lIfWf)`HDžpMJ<IIHI9 LQHNHhH`J HpMKNIIIrL9J H9HHNDI)DHtHHHHHHuI8Y1ɐHHHTHTHTHTHTHTHT HT HT(HT(HT0HT0HT8HT8HT@H@L9uHhH11I?M!IpHHyH s 1Hu|HwH)1ffffff.LLD L0D L0D@LPD@LPfD`LpfD`LpHHuHt.H HfDfD  fD H HuM92HhHI)IJ|HhH)IL$It$ HH)HHH)v%HEH`HMH讯IL$It$ H9tdL`LhH)LL)1fDH9tQH|I\H9t&HuI|HH9u,fDHHH9uHL L`fWf)@HDžPLL)t^LIIHI9CNHILHL@KHPHI)M~LLOHMLHH@1Hx,HВL+H8IH`HL!I)MIM9LILH0HyHHHILALxMHHH(LbMHHH LLMHILHMLLL'IžLMKDHHKTHHHHIt uIIIf.HCHI|ItHHHHHHIHIII_pffff.HHYHHHDžHx HHH@HIL0IHK|IfWf)HDžMHtJI9hMN<LKHHJHHLKHHMLKDHHHHHxaG+HcLHHIIHLpHHEPKHH HaHHHHHHHH0HHH(HH H HH(H8HH0HxHH8HHH@HHHHHEfHnfbgYf\oYf|W)MfEHUH]LLHYV+H}H91H.HP(#ME1fff.HIHHxL0L9}.L(L ESA)IKAH9uH1MuZi1efff.M)H1HHI<HI HHHI|HI\HHI9uMtHHI<IHH<H8HHxHJHHJIM9 -J4J<+HP H0HpHH;OILL8LeLufDHHXLHE0HHH FaHHHHH HHHHHHHH Lh(HEfInfbAYf\IYf|W)MfEHHLL4T+H}I9tHtHP(fffff.HP HHHHH;?fDM1 -HHHHH H IHHHHHHH<IIL8K<M,JJL9vILM9r5sILHHHHKMLL9vLM9sD@O4M9vIHMM9r'LHHrHHMM9rfDHHLL9HHpHH;HHHHt HFHLHDžMtLZFHH HDž Ht>FHH(HDž(Ht"FHH@Ht HHFHH`HtHH8EHHp_HH;EHH8[A\A]A^A_]fWf)EE(HEHexpand sHEHinvalid HEEhapeEHMHHU+EYH}KEHH`BHH@BH HBH IEH}EHH`HIH}H9HuvHHHHDžHH HDž HH(HDž(HH@HHP(HHt`IHHpHIHHX0IHH@IH`HIH@HelIH HDž H# IH(HDž(H IH@HIH`HHhIH@HIH@HIH}I99HP HH8IHH#HBHHHDžHBHH HDž HBHH(HDž(H BHH@Ht HHBHH`HtHH8eBHL?H ffff.UH]f.UH]4BHfDUHSPHP'BHH ?aHHsHx HH[]fff.UHH?aHHGH~ HH]ffff.UH]f.UH]AHfDUHAWAVATSIL>L"M9IFINH0IHHxINLL9}.IN IV(L LESA)IKAH9uH1MuZi1efff.M)H1HHI<HI HHHI|HI\HHI9uMtHHI<IHH<IF0H8IF8HH0IF@H%BHIFHHJIM9 -[A\A^A_]ÐUHH [H1H9NHD]DUHH>a]UH]f.UH]4@HfDUHSPH0'@HH n>aHHKHSHHHPHKHHHK HH HK(HH(H[]@UHH->aHHG(HF(HG HF HGHFHGHOHNHF]UH]f.UH]?HfDUHAWAVAUATSH(H}H6HHEH9HUHBHJHHuHHRH2H H HHHHHUHB LB(HHHH<IHHIJ<L4JN,L9vIH]M9r@~fffff.IHL6@HMKMLL9vH]M9sGKL9vIILL9r'LHuL?HIL9rfHuHH;uH([A\A]A^A_]UHH e[H1H9NHD]DUHH<a]UHAVSI=HHH3`HH{LCHD;aHH[A^]IH=HL:H fff.UHAVSI=HHH"3`HH{LHD<aHH[A^]IHT=HL:H fff.UHHH 2`HHxH@Ht]=H]fDUHSPHH2`HH{HCHt<HHH[]<HfUHAWAVAUATSH8HHH+_HHE1HILO,HxID$HM|$ HHIL,HI~,IfWf)`HDžpMJ<IIHI9 <HNHhH`J HpMKNIIIrL9J H9HHNDI)DHtHHHHHHuI8Y1ɐHHHTHTHTHTHTHTHT HT HT(HT(HT0HT0HT8HT8HT@H@L9uHhH11I?M!IpHHyH s 1Hu|HwH)1ffffff.LLD L0D L0D@LPD@LPfD`LpfD`LpHHuHt.H HfDfD  fD H HuM92HhHI)IJ|HhH)IL$It$ HH)HHH)v%HEH`HMHnIL$It$ H9tdL`LhH)LL)1fDH9tQH|I\H9t&HuI|HH9u,fDHHH9uHL L`fWf)@HDžPLL)t^LIIHI99HILHL@KHPHI)M~LLK:HMLHH@1H8H萈L+H8IH`HL!I)MIM9LILH0HyHHHILAL88HHH(L"8HHH L 8HILHMLLL)IžLMKDHHKTHHHHIt uIIIf.HCHI|ItHHHHHHIHIII_rffff.HHYHHHDžHxH HHHH@HIL0IHK|IfWf)HDžMHtJI9vMN<L^6HHJHHLG6HHMLKDHHHHHx2+HcLHHIIHLpHHEP5HH 4aHHHHHHHH0HHH(HH H HH(H8HH0HxHH8HHH@HHHHHEfHnfb%Yf\-Yf|W)MfEHUH]LLHA+H}H9/H,HP(!ME1f.HIHHxL0L9}.L(L ESA)IKAH9uH1MuZi1efff.M)H1HHI<HI HHHI|HI\HHI9uMtHHI<IHH<H8HHxH5HHJIM9 -J4J<+HP H0HpHH;_ILL8LeLufDHHXLHE0v3HH 3aHHHHH HHHHHHHH Lh(HEfInfbYf\ Yf|W)MfEHHLL>+H}I9tHtHP(fffff.HP HHHHH;OfDM!1 -HHHHH H IHHHHHHH<IIL8K<M,JJL9vILM9rEILH3HHLHO$$LLL9vLM9sMffff.O4M9vIHMM9r'LHH"3HMM9rfDHHLL9HHpHH;HHHHt H/1HLHDžMtL -1HH HDž Ht0HH(HDž(Ht0HH@Ht HH0HH`HtHH80HH _HH;EHH8[A\A]A^A_]fWf)EE(HEHexpand sHEHinvalid HEEhapeEHMHH+EYH}Kk0HH`e-HH@W-H HI-H IEH}/HH`HIH}H9HuvHHHHDžHH HDž HH(HDž(HH@HHP(HHt`IHHpHIHHX0IHH@IH`HIH@HelIH HDž H# IH(HDž(H IH@HIH`HHhIH@HIH@HIH}I99HP HH8IHH#H-HHHDžH-HH HDž Hb-HH(HDž(H B-HH@Ht HH0-HH`HtHH8-HLU*H ffff.UH]f.UH],HfDUHSPHP,HH +aHHsHx HH[]fff.UHH+aHHGH~ HH]ffff.UH]f.UH]T,HfDUHAWAVATSIL>L"M9IFINH0IHHxINLL9}.IN IV(L LESA)IKAH9uH1MuZi1efff.M)H1HHI<HI HHHI|HI\HHI9uMtHHI<IHH<IF0H8IF8HH0IF@H,HIFHHJIM9 -[A\A^A_]ÐUHH U[H1H9NHD]DUHH*a]UH]f.UH]*HfDUHSPH0*HH ~*aHHKHSHHHPHKHHHK HH HK(HH(H[]@UHH=*aHHG(HF(HG HF HGHFHGHOHNHF]UH]f.UH]4*HfDUHAWAVAUATSH(H}H6HHEH9HUHBHJHHuHHRH2H H HHHHHUHB LB(HHHH<IHHIJ<L4JN,L9vIH]M9r@~fffff.IHL*HMLHO$$LLL9vH]M9s@KL9vIILL9r'LHuL*HIL9rfHuHH;uH([A\A]A^A_]UHH ը[H1H9NHD]DUHH(a]UHAVSI(HHH2`HH{LHT'aHH[A^]IHd(HL%H fff.UHAVSIF(HHH`HH{LHT(aHH[A^]IH(HLD%H fff.UHHH 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HtHH(HDž(HtHH@Ht HHHH`HtHH8uHH_HH;EHH8[A\A]A^A_]fWf)EE(HEHexpand sHEHinvalid HEEhapeEHMHH*EYH}K;HH`5HH@'H HH IEH}HH`HIH}H9HuvHHHHDžHH HDž HH(HDž(HH@HHP(HHt`IHHpHIHHX0IHH@IH`HIH@HelIH HDž H# IH(HDž(H IH@HIH`HHhIH@HIH@HIH}I99HP HH8IHH#HxHHHDžHRHH HDž H2HH(HDž(H HH@Ht HHHH`HtHH8HL%H ffff.UH]f.UH]HfDUHSPHPHH .aHHsHx HH[]fff.UHHaHHGH~ HH]ffff.UH]f.UH]$HfDUHAWAVATSIL>L"M9IFINH0IHHxINLL9}.IN IV(L LESA)IKAH9uH1MuZi1efff.M)H1HHI<HI HHHI|HI\HHI9uMtHHI<IHIF0IN8H8HH1IF@HHIFHHJIM9[A\A^A_]f.UHH [H1H9NHD]DUHHa]UH]f.UH]HfDUHSPH0HH aHHKHSHHHPHKHHHK HH HK(HH(H[]@UHHmaHHG(HF(HG HF HGHFHGHOHNHF]UH]f.UH]HfDUHAWAVAUATSH(H}H6HHEH9 HMHAHQHHuHHIH HL$IHIHHUHB Hr(H8LHH<IL6K<.MHLL9vILuM9r>|fff.ILHHHKoMLL9vLuM9sGO4/M9vIHMM9r'LHuHuHMM9rfHuHH;uH([A\A]A^A_]UHH u[H1H9NHD]DUHH a]UHAVSIHHH `HH{LHaHH[A^]IHDHLH fff.UHAVSI&HHH`HH{LsHaHH[A^]IHHL$H fff.UHHH b`HHxH@Ht]H]fDUHSPHH0`HH{HCHtuHHH[]gHfUHAWAVAUATSH8HHH_HHE1HZUILONHxID$HM|$ HH#UILHI~輔IfWf)`HDžpMJ<IIHI9 HNHhH`J HpMKNIIIrL9J H9HHNDI)DHtHHHHHHuI8Y1ɐHHHTHTHTHTHTHTHT HT HT(HT(HT0HT0HT8HT8HT@H@L9uHhH11I?M!IpHHyH s 1Hu|HwH)1ffffff.LLD L0D L0D@LPD@LPfD`LpfD`LpHHuHt.H HfDfD  fD H HuM9-HhHI)IJ|HhH)IL$It$ HH)HHH)v%HEH`HMHoIL$It$ H9tdL`LhH)LL)1fDH9tQH|I\H9t&HuI|HH9u,fDHHH9uHL L`fWf)@HDžPLL)t^LIIHI9HILHL@KHPHI)M~LLHMLHH@1HHLL+H8IH`HL!I)MIM9LILH0HyHHHILAL HHH(L HHH L HILHMLLL)IžLMKDHHKTHHHHIt uIIIf.HCHI|ItHHHHHHIHIII_rffff.HHYHHHDžHx fHHH@HIL0IHK|IfWf)HDžMHtJI9fMN<L HHJHHL HHMLKDHHHHHx+HcLHHIIHLpHHEP^ HH E aHHHHHHHH0HHH(HH H HH(H8HH0HxHH8HHH@HHHHHEfHnfbYf\Yf|W)MfEHUH]LLH+H}H9+H(HP(ME1ff.HIHHxL0L9}.L(L ESA)IKAH9uH1MuZi1efff.M)H1HHI<HI HHHI|HI\HHI9uMtHHI<IHH<H8HHxH HHJIM9J4J<0HP H0HpHH;TIL -L8LeLuff.HHXLHE0 HH m aHHHHH HHHHHHHH Lh(HEfInfbYf\Yf|W)MfEHHLL+H}I9tHtHP(fffff.HP HHHHH;?fDM1 -HHHHH H IHHHHHHH<IML8K<fM,NJgLHL9vILM9r8vfDILH HHKMLL9vLM9sD@O4gM9vIHMM9r'LHHHMM9rfDHHLL9HHpHH;HHHHt HHLHDžMtLHH HDž HtHH(HDž(HtrHH@Ht HH`HH`HtHH8EHH}_HH;EHH8[A\A]A^A_]fWf)EE(HEHexpand sHEHinvalid HEEhapeEHMHH*EYH}K HH`HH@H HH IEH}kHH`HIH}H9HuvHHHHDžHH HDž 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HHHI|HI\HHI9uMtHHI<IHH<IF0H8IF8HH0IF@HGIFHHJIM9 -[A\A^A_]ÐUHH u\[H1H9NHD]DUHH=`]UH]f.UH]GfDUHSPH0GH `HHKHSHHHPHKHHHK HH HK(HH(H[]@UHH`HHG(HF(HG HF HGHFHGHOHNHF]UH]f.UH]TGfDUHAWAVAUATSH(H}H6HHEH9HUHBHJHHuHHRH2H H HHHHHUHB LB(HHHH<IHHIJ<L4JN,L9vIH]M9r@~fffff.IHLGMLHO$$LLL9vH]M9s@KL9vIILL9r'LHuLGIL9rfHuHH;uH([A\A]A^A_]UHH Z[H1H9NHD]DUHHm`]UHAVSIGHHR_HH{LH`HH[A^]IHGLG fff.UHAVSIfGHH_HH{L賬H`HH[A^]IH$GLdG fff.UHHH _HHxH@Ht]G]fDUHSPHHp_HH{HCHtGHH[]GfUHAWAVAUATSH8HHHI_HHE1HIL?HxID$HM|$ HHcILHI~TIfWf)`HDžpMJ<IIHI9 GNHhH`J HpMKNIIIrL9J H9HHNDI)DHtHHHHHHuI8Y1ɐHHHTHTHTHTHTHTHT HT HT(HT(HT0HT0HT8HT8HT@H@L9uHhH11I?M!IpHHyH s 1Hu|HwH)1ffffff.LLD L0D L0D@LPD@LPfD`LpfD`LpHHuHt.H HfDfD  fD H HuM9HhHI)IJ|HhH)IL$It$ HH)HHH)v%HEH`HMH>0IL$It$ H9tdL`LhH)LL)1fDH9tQH|I\H9t&HuI|HH9u,fDHHH9uHL L`fWf)@HDžPLL)t^LIIHI9GILHL@KHPHI)M~LLGMLHH@1HHL+H8IH`HL!I)MIM9LILH0HyHHHILALGHH(LGHH LGILHMLLL'IžLMKDHHKTHHHHIt uIIIf.HCHI|ItHHHHHHIHIII_pffff.HHYHHHDžHx HHH@HIL0IHK|IfWf)HDžMHtJI9XMN<L0GHJHHLGHMLKDHHHHx*HcLHHIIHLpHHEPGH 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H{HHhHt?HpH9t$Lh@t HxPHLL9uHhHHp0HPu0u LmMu=qH`H0tH@HLmMuEIALmMt6HEL9t!HX@t HxHHI9uH}LLmHEuqILHH}HbfIHH4Iuu&LhMuCH,HtHHLhMuYILhMtJHpL9fff.HX@t HxHHI9uHhLpHPu+0u7HHDH}HPUH`pH0tH@[HHHtLIHHtIHHtIH}HIHHgIH}HIEuEu LhMuA!H}HEtH}HLhMuILhMHpL9HX@t HxKHHI9uIHHIEuEuLhMu7yH}HEtH}HLhMuSILhMtDHpL9tff.HX@t HxHHI9uHhLpHPt H`{H0YH@HLIHHH>HH}H +H}(HH}HIELhMt@HpL9fHX@t HxHHI9uHhLpHPt H`H0tkH@HH}Hu_fH}rHiHYHLhMYLILhM?zIH}Ht H}HLUH ffff.UHAWAVAUATSH8HC`HHEIIII|$ID$H9L9IFHH)IIHOH9xJHH)MIIIMJIv KIDH9]JDH9OHHAH9HGIIIDHtHؐH1H3HHHuI81H4H4HtHtHtHtHtHtHt Ht Ht(Ht(Ht0Ht0Ht8Ht8Ht@H@H9rM,$L)HHHH=IIT$L)HHHLH9wHH9HBHHEHUHt@L9cH<>H*IIIFID$HA`HH;E1LL)HHEH HMHMHHEH}LL}I4$LH)LH)H}H~<HID$HL)H~H}LHHH]H]ID$H]I<$HMI $H}I\$HEIL$HUIT$HMH}H9tHHH)HHHHMHt1HMH@`HH;E$LH8[A\A]A^A_]I?M!I@HHDnAH s 1MuzKDpI]H)1f.DLLDLD L0DLD@LPD D`LpHHuMt.HID D H IuM9u=JDID$HtIL)LHIIH?`HH;EQHJJ LBHHIH5#ILPHH;?`HIH5=`H<`LHHLHHH HHMHEH9uH}Hu(HH HPH)HHHHUH}HtAHHH fUHAWAVAUATSPHL3HCL)HHHH9H +H9LcM)HL<vLHIJ4 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H}%HH4`HH;EuHĈ[A\A]A^A_]^H HIHh},H5KH KH}Lh lW)PHDž`0HH`(P])PHttributeHHH'axis' aHHHe valid HHHMust havH@ AH NHuHPLXnE1H5U`HFLkH<IALeMuFzIALhMIIPt H`HLeMt6HEL9t!HX@t HxHHI9uH}LLeHEuEuLhMu&^H}jHEtH}[HLhMt:HpL9t=HX@t Hx0HHI9uHhLpHEt,L8H"LIEu IEt H}HL$H fff.UHAWAVSPI HHL=o`L;H{L@HH1LHaHHH[A^A_]L;IH{HCHt +YHIHLHLH @UHAWAVSPI 3HHL=߯`L;H{L谪HH1LHaHHH[A^A_]L;IH{HCHt +HIHHLH @UHAWAVAUATSHHMMHHIHH1`HHEH8HR/`HHHHH@H8HHLLHEEL-0`MuLI@L8HHL=D0`ILHDž(HDž HDžHDžDž0A$It$IEt$IET$HtHE HMLMHD$H $HHHHL,HHHVzLL8Lt H +HHHH5!/`HHHH8HHv/`HH;EuHHH[A\A]A^A_]HHLL8Lt H HHdH H`pHH5.`HHHH8HH2pHH8HHpff.UHAWAVAUATSHLMLEIIIL6LHLLH%sI]HeHLHH sI4$LHHEHH<HLHHrHEH0LeHHEHHHLHHrHEH0L9HH[A\A]A^A_]H@oH8oH0oH(oH oHoHoUHAWAVAUATSH(IIMgIGI9I?I_HH)vpLuHHAH?LtIJII)I)LHLMt"ILHLH'HHIMwLMdMgIGLulH)HHHALEMt$H}LH=jJ<IHH}1NINL9LuMT$MI)IIVHr!JLI9KL5HLH9LI)DHt#Hffff.H3H1HHHuI8p1ҐH4H4HtHtHtHtHtHtHt Ht Ht(Ht(Ht0Ht0Ht8Ht8Ht@H@L9u M LEH?HUH!HMHqHHJH H}s1H}NLpLAI)1DLADѐALѠD L0ADѰALD@LPADALD`LpADA HIuHt6H|IJTH1fD7 7D2 2H HuHUH9UH}LEuDOdLuIM_MgMGHt HMgII$IMgH([A\A]A^A_]I HHHH5IHTHH?*`HHH5(`H(`HHIHHLH ffff.UHAWAVAUATSHIIIuMeI)MIIGHH=HMuI)LHHH9waII9LBMLEHuI9vK +HHH5 IHpHH[)`HHH5 (`H'`H +HLEHuIJ<HHHuLEN4IJN|M~HLIHLI]M}MuHtHH[A\A]A^A_]LHH[A\A]A^A_]E11LHIHSHLcH UHAVSHPIH(`HHE(HHþ HHHHCHCXHC`HCXHCHHC@HC8HC0HC(HC HCPHCpHCxHCpHChƃHǃfǃHǃHǃƃHHǃHǃHǃHǃHǃHǃHǃHǃHǃHHHǃHǃHǃǃǃHǃ H]H5JH}HJH5JHKH5QLH|HA H5jIHHH;hHHH G`HMHHUHuHuIIFIF0INIVIF@H]HEHtH\HHHM&`HH;Eu LHP[A^]HIH]HEHtHHmHL譾H DUHAVSIVHHH`HH{LӞHLaHH[A^]IHHLTH fff.UHHH `HHxH@Ht]H]fDUHSPHH`HH{HCHtHHH[]HfUHAWAVAUATSHIHHH %`HHE1LzHH!HH@HHCI1LHHW)EHEHULХIHUL輥IMGHhHPH@LLhL&PH&hPMGH@HLHHHH}Ht H}YHH#`HH;EuHHHĘ[A\A]A^A_]苿H9HIHhl,H5JH JH}LhA[HPH…AHhJHuLH]E1H5E`H6LHiIALhMIIPt H`nHLeMt6HEL9t!HX@t HxIHHI9uH}LLe/HEuEuLhMu&^H} HEtH}HLhMt:HpL9t=HX@t HxҽHHI9uHhLp跽HEtjLڽH`LIH}HuFMIH}Hu8?IH}Hu*1IH}Hu#IH}HuIH}Ht H}HHL舺H UHAWAVAUATSHMH`IHH!`HHEHHL+tXH~OHCH?H;HDHHHH?H9HLHHHD HHILHM<HDžHA1HHHI9HfHnfbbZf\bZf|fhH@HpWH*x0HH aHHHHHHHHHHHHH HHX(HHhLLLL+HI9t HtHP(HP HHHNHuHu}H)κfffff.]_]_HH9uHt0]_((DžW.IG܋ .IGDžfnfn.u z + eZ \^ )\A^W\]l)\_.z5(`ZT.eZs" xeZ()P+H(P\,H`Hz`HH;EuHĈ[A\A]A^A_]HHHI9uHP HH HtHP(HζH fDUH]f.UH]dHfDUHSPH0WHH ƝaHHKHSHHHPHKHHHK HH HK(HH(H[]@UHHaHHG(HF(HG HF HGHFHGHOHNHF]UH]f.UH]鴸HfDUHHHOHwH ILH6H +H9HOHwHH>Hw JHH(H4HTL)H]xB.UHH e(\H1H9NHD]DUHH a]UHAVSHPIH`HHE(HHþ HHHHCHCXHC`HCXHCHHC@HC8HC0HC(HC HCPHCpHCxHCpHChƃHǃfǃHǃHǃƃHHǃHǃHǃHǃHǃHǃHǃHǃHǃHHHǃHǃHǃǃǃHǃ H]H5HH}HZH5IH[H5aLH茻HH HQH5sHH謼HH;qHHH P`HMH%?HUHuHuIIFIF0INIVIF@H]HEHtHeH軵HHV`HH;Eu LHP[A^]HIH]HEHtH HvHL趲H fffff.UHAVSHPIH`HHE(DHHþ H:HHHCHCXHC`HCXHCHHC@HC8HC0HC(HC HCPHCpHCxHCpHChƃHǃfǃHǃHǃƃHHǃHǃHǃHǃHǃHǃHǃHǃHǃHHHǃHǃHǃǃǃHǃ H] H5HH}HH5IH蛷H5LH̸HA H5HHHH;踮HHH `HMHlYHUHuHuIIFIF0INIVIF@H]HEHtHHHH`HH;Eu LHP[A^]AHIH]HEHtHgH轲HLH DUHAVSHPIH;`HHE(蔲HHþ H芲HHHCHCXHC`HCXHCHHC@HC8HC0HC(HC HCPHCpHCxHCpHChƃHǃfǃHǃHǃƃHHǃHǃHǃHǃHǃHǃHǃHǃHǃHHHǃHǃHǃǃǃHǃ H]]H5HH}HH5$IHH5LHHH HQH5HH<HH;HHH `HMHWHUHuHuIIFIF0INIVIF@H]HEHtHHKHH`HH;Eu LHP[A^]芰HIH]HEHtHHHLFH fffff.UHAVSHPIH{`HHE(ԯHHþ HʯHHHCHCXHC`HCXHCHHC@HC8HC0HC(HC HCPHCpHCxHCpHChƃHǃfǃHǃHǃƃHHǃHǃHǃHǃHǃHǃHǃHǃHǃHHHǃHǃHǃǃǃHǃ H]H5]HH}H*H5dIH+H51LH\HA H5JHH胴HH;HHHH '`HMHLiHUHuHuIIFIF0INIVIF@H]HEHtH<H蒭HH-`HH;Eu LHP[A^]ѭHIH]HEHtHHMHL荪H DUHAVSHPIH`HHE($HHþ HHHHCHCXHC`HCXHCHHC@HC8HC0HC(HC HCPHCpHCxHCpHChƃHǃfǃHǃHǃƃHHǃHǃHǃHǃHǃHǃHǃHǃHǃHHHǃHǃHǃǃǃHǃ H]-H5HH}HzH5IH{H5LH謰HH HQH5HH̱HH;葦HHH p`HMHfHUHuHuIIFIF0INIVIF@H]HEHtHH۪HHv`HH;Eu LHP[A^]HIH]HEHtH@H薪HL֧H fffff.UHAVSHPIH `HHE(dHHþ HZHHHCHCXHC`HCXHCHHC@HC8HC0HC(HC HCPHCpHCxHCpHChƃHǃfǃHǃHǃƃHHǃHǃHǃHǃHǃHǃHǃHǃHǃHHHǃHǃHǃǃǃHǃ H]mH5HH}H躵H5IH軬H5LHHA H5HHHH;أHHH `HMHxHUHuHuIIFIF0INIVIF@H]HEHtHH"HH `HH;Eu LHP[A^]aHIH]HEHtHHݧHLH DUHAVSHPIH[ `HHE(货HHþ H誧HHHCHCXHC`HCXHCHHC@HC8HC0HC(HC HCPHCpHCxHCpHChƃHǃfǃHǃHǃƃHHǃHǃHǃHǃHǃHǃHǃHǃHǃHHHǃHǃHǃǃǃHǃ H]H5=HH}H +H5DIH H5LH<HH HQH5#HH\HH;!HHH `HMHvHUHuHuIIFIF0INIVIF@H]HEHtHHkHH +`HH;Eu LHP[A^]誥HIH]HEHtHоH&HLfH fffff.UHAVSHPIH `HHE(HHþ HHHHCHCXHC`HCXHCHHC@HC8HC0HC(HC HCPHCpHCxHCpHChƃHǃfǃHǃHǃƃHHǃHǃHǃHǃHǃHǃHǃHǃHǃHHHǃHǃHǃǃǃHǃ H]=H5}HH}HJH5IHKH5QLH|HA H5jHH裩HH;hHHH G`HMHHUHuHuIIFIF0INIVIF@H]HEHtH\H貢HHM`HH;Eu LHP[A^]HIH]HEHtHHmHL譟H DUHAVSHPIH`HHE(DHHþ H:HHHCHCXHC`HCXHCHHC@HC8HC0HC(HC HCPHCpHCxHCpHChƃHǃfǃHǃHǃƃHHǃHǃHǃHǃHǃHǃHǃHǃHǃHHHǃHǃHǃǃǃHǃ H]MH5ͭHH}H蚭H5IH蛤H5LH̥HH HQH5HHHH;豛HHH `HMHeHUHuHuIIFIF0INIVIF@H]HEHtH襹HHH`HH;Eu LHP[A^]:HIH]HEHtH`H趟HLH fffff.UHAVSHPIH+`HHE(脟HHþ HzHHHCHCXHC`HCXHCHHC@HC8HC0HC(HC HCPHCpHCxHCpHChƃHǃfǃHǃHǃƃHHǃHǃHǃHǃHǃHǃHǃHǃHǃHHHǃHǃHǃǃǃHǃ H]H5 HH}HڪH5IHۡH5LH HA H5HH3HH;HHH `HMHHUHuHuIIFIF0INIVIF@H]HEHtHHBHH`HH;Eu LHP[A^]聝HIH]HEHtH觶HHL=H DUHAVSHPIH{`HHE(ԜHHþ HʜHHHCHCXHC`HCXHCHHC@HC8HC0HC(HC HCPHCpHCxHCpHChƃHǃfǃHǃHǃƃHHǃHǃHǃHǃHǃHǃHǃHǃHǃHHHǃHǃHǃǃǃHǃ H]H5]HH}H*H5dIH+H51LH\HH HQH5CHH|HH;AHHH `HMH5HUHuHuIIFIF0INIVIF@H]HEHtH5H苚HH&_HH;Eu LHP[A^]ʚHIH]HEHtHHFHL膗H fffff.UHAVSHPIH_HHE(HHþ H +HHHCHCXHC`HCXHCHHC@HC8HC0HC(HC HCPHCpHCxHCpHChƃHǃfǃHǃHǃƃHHǃHǃHǃHǃHǃHǃHǃHǃHǃHHHǃHǃHǃǃǃHǃ H]H5HH}HjH5IHkH5qLH蜝HA H5HHÞHH;舓HHH g`HMHlHUHuHuIIFIF0INIVIF@H]HEHtH|HҗHHm_HH;Eu LHP[A^]HIH]HEHtH7H荗HL͔H DUHAVSHPIH _HHE(dHHþ HZHHHCHCXHC`HCXHCHHC@HC8HC0HC(HC HCPHCpHCxHCpHChƃHǃfǃHǃHǃƃHHǃHǃHǃHǃHǃHǃHǃHǃHǃHHHǃHǃHǃǃǃHǃ H]-H5HH}H躢H5IH軙H5LHHH HQH5HH HH;ѐHHH `HMHHUHuHuIIFIF0INIVIF@H]HEHtHŮHHH_HH;Eu LHP[A^]ZHIH]HEHtH耮H֔HLH fffff.UHAVSHPIHK_HHE(褔HHþ H蚔HHHCHCXHC`HCXHCHHC@HC8HC0HC(HC HCPHCpHCxHCpHChƃHǃfǃHǃHǃƃHHǃHǃHǃHǃHǃHǃHǃHǃHǃHHHǃHǃHǃǃǃHǃ H]mH5-HH}HH54IHH5LH,HA H5HHSHH;HHH `HMHHUHuHuIIFIF0INIVIF@H]HEHtH HbHH_HH;Eu LHP[A^]衒HIH]HEHtHǫHHL]H DUHAVSHPIH_HHE(HHþ HHHHCHCXHC`HCXHCHHC@HC8HC0HC(HC HCPHCpHCxHCpHChƃHǃfǃHǃHǃƃHHǃHǃHǃHǃHǃHǃHǃHǃHǃHHHǃHǃHǃǃǃHǃ H]}H5}HH}HJH5IHKH5QLH|HH HQH5cHH蜖HH;aHHH @`HMHŵHUHuHuIIFIF0INIVIF@H]HEHtHUH諏HHF_HH;Eu LHP[A^]HIH]HEHtHHfHL覌H fffff.UHAVSHPIH_HHE(4HHþ H*HHHCHCXHC`HCXHCHHC@HC8HC0HC(HC HCPHCpHCxHCpHChƃHǃfǃHǃHǃƃHHǃHǃHǃHǃHǃHǃHǃHǃHǃHHHǃHǃHǃǃǃHǃ H]H5HH}H芚H5ķIH苑H5LH輒HA H5HHHH;計HHH `HMHHUHuHuIIFIF0INIVIF@H]HEHtH蜦HHH_HH;Eu LHP[A^]1HIH]HEHtHWH譌HLH DUHAVSHPIH+_HHE(脌HHþ HzHHHCHCXHC`HCXHCHHC@HC8HC0HC(HC HCPHCpHCxHCpHChƃHǃfǃHǃHǃƃHHǃHǃHǃHǃHǃHǃHǃHǃHǃHHHǃHǃHǃǃǃHǃ H] H5 HH}HڗH5IHێH5LH HH HQH5HH,HH;HHH Я`HMHHUHuHuIIFIF0INIVIF@H]HEHtHH;HH_HH;Eu LHP[A^]zHIH]HEHtH蠣HHL6H fffff.UHAVSHPIHk_HHE(ĉHHþ H躉HHHCHCXHC`HCXHCHHC@HC8HC0HC(HC HCPHCpHCxHCpHChƃHǃfǃHǃHǃƃHHǃHǃHǃHǃHǃHǃHǃHǃHǃHHHǃHǃHǃǃǃHǃ H]MH5MHH}HH5TIHH5!LHLHA H5:HHsHH;8HHH `HMHHUHuHuIIFIF0INIVIF@H]HEHtH,H肇HH_HH;Eu LHP[A^]HIH]HEHtHH=HL}H DUHAVSHPIH_HHE(HHþ H +HHHCHCXHC`HCXHCHHC@HC8HC0HC(HC HCPHCpHCxHCpHChƃHǃfǃHǃHǃƃHHǃHǃHǃHǃHǃHǃHǃHǃHǃHHHǃHǃHǃǃǃHǃ H]]H5HH}HjH5IHkH5qLH蜊HH HQH5HH輋HH;聀HHH ``HMHUHUHuHuIIFIF0INIVIF@H]HEHtHuH˄HHf_HH;Eu LHP[A^] +HIH]HEHtH0H膄HLƁH fffff.UHAVSHPIH_HHE(THHþ HJHHHCHCXHC`HCXHCHHC@HC8HC0HC(HC HCPHCpHCxHCpHChƃHǃfǃHǃHǃƃHHǃHǃHǃHǃHǃHǃHǃHǃHǃHHHǃHǃHǃǃǃHǃ H]蝹H5ݏHH}H誏H5IH諆H5LH܇HA H5HHHH;}HHH `HMHHUHuHuIIFIF0INIVIF@H]HEHtH輛HHH_HH;Eu LHP[A^]QHIH]HEHtHwH́HL H DUHAVSHPIHK_HHE(褁HHþ H蚁HHHCHCXHC`HCXHCHHC@HC8HC0HC(HC HCPHCpHCxHCpHChƃHǃfǃHǃHǃƃHHǃHǃHǃHǃHǃHǃHǃHǃHǃHHHǃHǃHǃǃǃHǃ H]-H5-HH}HH54IHH5LH,HH HQH5HHLHH;{HHH `HMH5HUHuHuIIFIF0INIVIF@H]HEHtHH[HH_HH;Eu LHP[A^]HIH]HEHtHHHLV|H fffff.UHAVSHPIH_HHE(~HHþ H~HHHCHCXHC`HCXHCHHC@HC8HC0HC(HC HCPHCpHCxHCpHChƃHǃfǃHǃHǃƃHHǃHǃHǃHǃHǃHǃHǃHǃHǃHHHǃHǃHǃǃǃHǃ H]mH5mHH}H:H5tIH;H5ALHlHA H5ZHH蓃HH;XxHHH 7`HMH<HUHuHuIIFIF0INIVIF@H]HEHtHLH|HH=_HH;Eu LHP[A^]|HIH]HEHtHH]|HLyH DUHAVSHPIH_HHE(4|HHþ H*|HHHCHCXHC`HCXHCHHC@HC8HC0HC(HC HCPHCpHCxHCpHChƃHǃfǃHǃHǃƃHHǃHǃHǃHǃHǃHǃHǃHǃHǃHHHǃHǃHǃǃǃHǃ H]=H5HH}H芇H5ĤIH~H5LHHH HQH5HH܀HH;uHHH `HMHHUHuHuIIFIF0INIVIF@H]HEHtH蕓HyHH_HH;Eu LHP[A^]*zHIH]HEHtHPHyHLvH fffff.UHAVSHPIH_HHE(tyHHþ HjyHHHCHCXHC`HCXHCHHC@HC8HC0HC(HC HCPHCpHCxHCpHChƃHǃfǃHǃHǃƃHHǃHǃHǃHǃHǃHǃHǃHǃHǃHHHǃHǃHǃǃǃHǃ H]}H5HH}HʄH5IH{H5ѤLH|HA H5HH#~HH;rHHH ǜ`HMHHUHuHuIIFIF0INIVIF@H]HEHtHܐH2wHH_HH;Eu LHP[A^]qwHIH]HEHtH藐HvHL-tH DUHAVSIvHHHY`HH{LSTH[aHH[A^]IHvHLsH fff.UHHH 2Y`HHxH@Ht]VvH]fDUHSPHHY`HH{HCHt%vHHH[]vHfUHAWAVAUATSH8HHH_HHE1HILHxID$HM|$ HHøIL8HI~\IfWf)`HDžpMJ<IIHI9 LuHNHhH`J HpMKNIIIrL9J H9HHNDI)DHtHHHHHHuI8Y1ɐHHHTHTHTHTHTHTHT HT HT(HT(HT0HT0HT8HT8HT@H@L9uHhH11I?M!IpHHyH s 1Hu|HwH)1ffffff.LLD L0D L0D@LPD@LPfD`LpfD`LpHHuHt.H HfDfD  fD H HuM92HhHI)IJ|HhH)IL$It$ HH)HHH)v%HEH`HMH IL$It$ H9tdL`LhH)LL)1fDH9tQH|I\H9t&HuI|HH9u,fDHHH9uHL L`fWf)@HDžPLL)t^LIIHI9CrHILHL@KHPHI)M~LLsHMLHH@1HTH0L+H8IH`HL!I)MIM9LILH0HyHHHILALxqHHH(LbqHHH LLqHILHMLLL'IžLMKDHHKTHHHHIt uIIIf.HCHI|ItHHHHHHIHIII_pffff.HHYHHHDžHx HHH@HIL0IHK|IfWf)HDžMHtJI9hMN<LoHHJHHLoHHMLKDHHHHHxQk+HcLHHIIHLpHHEPoHH nTaHHHHHHHH0HHH(HH H HH(H8HH0HxHH8HHH@HHHHHEfHnfb'Zf\/Zf|W)MfEHUH]LLHIz+H}H91H.HP(#ME1fff.HIHHxL0L9}.L(L ESA)IKAH9uH1MuZi1efff.M)H1HHI<HI HHHI|HI\HHI9uMtHHI<IHH<H8HHxHnHHJIM9 +J4J<+HP H0HpHH;OILL8LeLufDHHXLHE0lHH RaHHHHH HHHHHHHH Lh(HEfInfbZf\ Zf|W)MfEHHLL$x+H}I9tHtHP(fffff.HP HHHHH;?fDM1 +HHHHH H IHHHHHHH<IIL8K<M,JJL9vILM9r5sILHlHHKMLL9vLM9sD@O4M9vIHMM9r'LHHrlHMM9rfDHHLL9HHpHH;HHHHt HjHLHDžMtLZjHH HDž Ht>jHH(HDž(Ht"jHH@Ht HHjHH`HtHH8iHH_HH;EHH8[A\A]A^A_]fWf)EE(HEHexpand sHEHinvalid HEEhapeEHMHHE9+EYH}KiHH`fHH@fH HfH IEH}iHH`HIH}H9HuvHHHHDžHH HDž HH(HDž(HH@HHP(HHt`IHHpHIHHX0IHH@IH`HIH@HelIH HDž H# IH(HDž(H IH@HIH`HHhIH@HIH@HIH}I99HP HH8IHH#HfHHHDžHfHH HDž HfHH(HDž(H fHH@Ht HHfHH`HtHH8efHLcH 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[H1H9NHD]DUHH Ba]UH]f.UH]\HfDUHSPH0\HH AaHHKHSHHHPHKHHHK HH HK(HH(H[]@UHHAaHHG(HF(HG HF HGHFHGHOHNHF]UH]f.UH]d[HfDUHAWAVAUATSH(H}H6HHEH9HUHBHJHHuHHRH2H H HHHHHUHB LB(HHHH<IHHIJ<L4JN,L9vIH]M9r@~fffff.IHL\HMKMLL9vH]M9sGKL9vIILL9r'LHuL[HIL9rfHuHH;uH([A\A]A^A_]UHH [H1H9NHD]DUHH=@a]UHAVSIYHHH<`HH{LS7H>aHH[A^]IHYHLVH fff.UHAVSIvYHHH"<`HH{L6H?aHH[A^]IH4YHLtVH fff.UHHH ;`HHxH@Ht]XH]fDUHSPHH;`HH{HCHtXHHH[]XHfUHAWAVAUATSH8HHH+_HHE1H蚛IL߈HxID$HM|$ HHcIL}HI~IfWf)`HDžpMJ<IIHI9 WHNHhH`J HpMKNIIIrL9J H9HHNDI)DHtHHHHHHuI8Y1ɐHHHTHTHTHTHTHTHT HT HT(HT(HT0HT0HT8HT8HT@H@L9uHhH11I?M!IpHHyH s 1Hu|HwH)1ffffff.LLD L0D L0D@LPD@LPfD`LpfD`LpHHuHt.H HfDfD  fD H HuM92HhHI)IJ|HhH)IL$It$ HH)HHH)v%HEH`HMHNIL$It$ H9tdL`LhH)LL)1fDH9tQH|I\H9t&HuI|HH9u,fDHHH9uHL L`fWf)@HDžPLL)t^LIIHI9THILHL@KHPHI)M~LL+VHMLHH@1HH7H@L+H8IH`HL!I)MIM9LILH0HyHHHILALTHHH(LTHHH LSHILHMLLL)IžLMKDHHKTHHHHIt uIIIf.HCHI|ItHHHHHHIHIII_rffff.HHYHHHDžHxH HHHH@HIL0IHK|IfWf)HDžMHtJI9vMN<L>RHHJHHL'RHHMLKDHHHHHxM+HcLHHIIHLpHHEPQHH t8aHHHHHHHH0HHH(HH H HH(H8HH0HxHH8HHH@HHHHHEfHnfbYf\Yf|W)MfEHUH]LLH\+H}H9/H,HP(!ME1f.HIHHxL0L9}.L(L ESA)IKAH9uH1MuZi1efff.M)H1HHI<HI HHHI|HI\HHI9uMtHHI<IHH<H8HHxHeQHHJIM9 +J4J<+HP H0HpHH;_ILL8LeLufDHHXLHE0VOHH 6aHHHHH HHHHHHHH Lh(HEfInfbYf\Yf|W)MfEHHLLZ+H}I9tHtHP(fffff.HP HHHHH;OfDM!1 +HHHHH H IHHHHHHH<IIL8K<M,JJL9vILM9rEILHfOHHLHO$$LLL9vLM9sMffff.O4M9vIHMM9r'LHHOHMM9rfDHHLL9HHpHH;HHHHt HMHLHDžMtLLHH HDž HtLHH(HDž(HtLHH@Ht HHLHH`HtHH8LHH _HH;EHH8[A\A]A^A_]fWf)EE(HEHexpand sHEHinvalid HEEhapeEHMHH+EYH}KKLHH`EIHH@7IH H)IH IEH}KHH`HIH}H9HuvHHHHDžHH HDž HH(HDž(HH@HHP(HHt`IHHpHIHHX0IHH@IH`HIH@HelIH HDž H# IH(HDž(H IH@HIH`HHhIH@HIH@HIH}I99HP HH8IHH#HIHHHDžHbIHH HDž HBIHH(HDž(H "IHH@Ht HHIHH`HtHH8HHL5FH ffff.UH]f.UH]HHfDUHSPHPHHH ~/aHHsHx HH[]fff.UHHM/aHHGH~ HH]ffff.UH]f.UH]4HHfDUHAWAVATSIL>L"M9IFINH0IHHxINLL9}.IN IV(L LESA)IKAH9uH1MuZi1efff.M)H1HHI<HI HHHI|HI\HHI9uMtHHI<IHH<IF0H8IF8HH0IF@HHHIFHHJIM9 +[A\A^A_]ÐUHH [H1H9NHD]DUHH.a]UH]f.UH]FHfDUHSPH0FHH -aHHKHSHHHPHKHHHK HH HK(HH(H[]@UHH-aHHG(HF(HG HF HGHFHGHOHNHF]UH]f.UH]FHfDUHAWAVAUATSH(H}H6HHEH9HUHBHJHHuHHRH2H H HHHHHUHB LB(HHHH<IHHIJ<L4JN,L9vIH]M9r@~fffff.IHLFHMLHO$$LLL9vH]M9s@KL9vIILL9r'LHuLuFHIL9rfHuHH;uH([A\A]A^A_]UHH u[H1H9NHD]DUHHM,a]UHAVSIDHHH2'`HH{L"H*aHH[A^]IHDDHLAH fff.UHAVSI&DHHH&`HH{L!H+aHH[A^]IHCHL$AH fff.UHHH &`HHxH@Ht]CH]fDUHSPHHP&`HH{HCHtuCHHH[]gCHfUHAWAVAUATSH8HHHۧ_HHE1HJILOHxID$HM|$ HHILhHI~IfWf)`HDžpMJ<IIHI9 BHNHhH`J HpMKNIIIrL9J H9HHNDI)DHtHHHHHHuI8Y1ɐHHHTHTHTHTHTHTHT HT HT(HT(HT0HT0HT8HT8HT@H@L9uHhH11I?M!IpHHyH s 1Hu|HwH)1ffffff.LLD L0D L0D@LPD@LPfD`LpfD`LpHHuHt.H HfDfD  fD H HuM9HhHI)IJ|HhH)IL$It$ HH)HHH)v%HEH`HMHIL$It$ H9tdL`LhH)LL)1fDH9tQH|I\H9t&HuI|HH9u,fDHHH9uHL L`fWf)@HDžPLL)t^LIIHI9?HILHL@KHPHI)M~LL@HMLHH@1H!H萟L+H8IH`HL!I)MIM9LILH0HyHHHILAL>HHH(L>HHH L>HILHMLLL'IžLMKDHHKTHHHHIt uIIIf.HCHI|ItHHHHHHIHIII_pffff.HHYHHHDžHx HHH@HIL0IHK|IfWf)HDžMHtJI9XMN<L<HHJHHL<HHMLKDHHHHx8+HcLHHIIHLpHHEPc<HH $aHHHHHHHH0HHH(HH H HH(H8HH0HxHH8HHH@HHHHHEfHnfb{Yf\Yf|W)MfEHUH]LLHG+H}H9HHP(ME1HIHHxL0L9}.L(L 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Hr(H8LHH<IL6K<.MHLL9vILuM9r>|fff.ILH1HHKoMLL9vLuM9sGO4/M9vIHMM9r'LHuHU1HMM9rfHuHH;uH([A\A]A^A_]UHH [H1H9NHD]DUHHa]UHAVSIf/HHH`HH{L HaHH[A^]IH$/HLd,H fff.UHAVSI/HHH`HH{L HaHH[A^]IH.HL,H fff.UHHH b`HHxH@Ht].H]fDUHSPHH0`HH{HCHtU.HHH[]G.HfUHAWAVAUATSH8HHH_HHE1H*qILoHxID$HM|$ HHpILhSHI~茰IfWf)`HDžpMJ<IIHI9 |-HNHhH`J HpMKNIIIrL9J H9HHNDI)DHtHHHHHHuI8Y1ɐHHHTHTHTHTHTHTHT HT HT(HT(HT0HT0HT8HT8HT@H@L9uHhH11I?M!IpHHyH s 1Hu|HwH)1ffffff.LLD L0D L0D@LPD@LPfD`LpfD`LpHHuHt.H HfDfD  fD H HuM9-HhHI)IJ|HhH)IL$It$ HH)HHH)v%HEH`HMHIL$It$ H9tdL`LhH)LL)1fDH9tQH|I\H9t&HuI|HH9u,fDHHH9uHL L`fWf)@HDžPLL)t^LIIHI9s*HILHL@KHPHI)M~LL+HMLHH@1H H谗L+H8IH`HL!I)MIM9LILH0HyHHHILAL)HHH(L)HHH L|)HILHMLLL)IžLMKDHHKTHHHHIt uIIIf.HCHI|ItHHHHHHIHIII_rffff.HHYHHHDžHx fHHH@HIL0IHK|IfWf)HDžMHtJI9fMN<L'HHJHHL'HHMLKDHHHHHx#+HcLHHIIHLpHHEP>'HH aHHHHHHHH0HHH(HH H HH(H8HH0HxHH8HHH@HHHHHEfHnfbVYf\^Yf|W)MfEHUH]LLHx2+H}H9+H(HP(ME1ff.HIHHxL0L9}.L(L ESA)IKAH9uH1MuZi1efff.M)H1HHI<HI HHHI|HI\HHI9uMtHHI<IHH<H8HHxH&HHJIM9J4J<0HP H0HpHH;TIL +L8LeLuff.HHXLHE0$HH aHHHHH HHHHHHHH Lh(HEfInfb1Yf\9Yf|W)MfEHHLLT0+H}I9tHtHP(fffff.HP HHHHH;?fDM1 +HHHHH H IHHHHHHH<IML8K<fM,NJgLHL9vILM9r8vfDILH$HHKMLL9vLM9sD@O4gM9vIHMM9r'LHH$HMM9rfDHHLL9HHpHH;HHHHt H"HLHDžMtL"HH HDž Htn"HH(HDž(HtR"HH@Ht HH@"HH`HtHH8%"HH_HH;EHH8[A\A]A^A_]fWf)EE(HEHexpand sHEHinvalid HEEhapeEHMHHu*EYH}K!HH`HH@H HH IEH}K!HH`HIH}H9HuvHHHHDžHH HDž HH(HDž(HH@HHP(HHt`IHHpHIHHX0IHH@IH`HIH@HelIH HDž H# IH(HDž(H IH@HIH`HHhIH@HIH@HIH}I99HP HH8IHH#H(HHHDžHHH HDž HHH(HDž(H HH@Ht HHHH`HtHH8HLH ffff.UH]f.UH]dHfDUHSPHPWHH aHHsHx HH[]fff.UHHaHHGH~ HH]ffff.UH]f.UH]HfDUHAWAVATSIL>L"M9IFINH0IHHxINLL9}.IN IV(L LESA)IKAH9uH1MuZi1efff.M)H1HHI<HI HHHI|HI\HHI9uMtHHI<IHH<IF0H8IF8HH0IF@HZHIFHHJIM9[A\A^A_]fDUHH [H1H9NHD]DUHH}a]UH]f.UH]dHfDUHSPH0WHH ^aHHKHSHHHPHKHHHK HH HK(HH(H[]@UHHaHHG(HF(HG HF HGHFHGHOHNHF]UH]f.UH]HfDUHAWAVAUATSH(H}H6HHEH9 HUHBHJHHuHHRH2H H HHHHHUHB LB(HHHH<IHHIJ<cL4KJgMML9vIH]M9r3qIHLvHMKMLL9vH]M9sGKgL9vIILL9r'LHuL%HIL9rfHuHH;uH([A\A]A^A_]UHH [H1H9NHD]DUHHa]UHAVSI6HHH_HH{LHDaHH[A^]IHHL4H fff.UHAVSIHHH_HH{LSHDaHH[A^]IHHLH fff.UHHH 2_HHxH@Ht]VH]fDUHSPHH_HH{HCHt%HHH[]HfUHAWAVAUATSH8HHH}_HHE1H[ILoHxID$HM|$ HH[IL8>HI~\IfWf)`HDžpMJ<IIHI9 LHNHhH`J HpMKNIIIrL9J H9HHNDI)DHtHHHHHHuI8Y1ɐHHHTHTHTHTHTHTHT HT HT(HT(HT0HT0HT8HT8HT@H@L9uHhH11I?M!IpHHyH s 1Hu|HwH)1ffffff.LLD L0D L0D@LPD@LPfD`LpfD`LpHHuHt.H HfDfD  fD H HuM92HhHI)IJ|HhH)IL$It$ HH)HHH)v%HEH`HMH讯IL$It$ H9tdL`LhH)LL)1fDH9tQH|I\H9t&HuI|HH9u,fDHHH9uHL L`fWf)@HDžPLL)t^LIIHI9CHILHL@KHPHI)M~LLHMLHH@1HH谏L+H8IH`HL!I)MIM9LILH0HyHHHILALxHHH(LbHHH LLHILHMLLL'IžLMKDHHKTHHHHIt uIIIf.HCHI|ItHHHHHHIHIII_pffff.HHYHHHDžHx HHH@HIL0IHK|IfWf)HDžMHtJI9hMN<LHHJHHLHHMLKDHHHHHxQ+HcLHHIIHLpHHEPHH `HHHHHHHH0HHH(HH H HH(H8HH0HxHH8HHH@HHHHHEfHnfb'Yf\/Yf|W)MfEHUH]LLHI+H}H91H.HP(#ME1fff.HIHHxL0L9}.L(L ESA)IKAH9uH1MuZi1efff.M)H1HHI<HI HHHI|HI\HHI9uMtHHI<IHH<H8HHxHHHJIM9 +J4J<+HP H0HpHH;OILL8LeLufDHHXLHE0HH `HHHHH HHHHHHHH Lh(HEfInfbYf\ Yf|W)MfEHHLL$+H}I9tHtHP(fffff.HP HHHHH;?fDM1 +HHHHH H IHHHHHHH<IIL8K<M,JJL9vILM9r5sILHHHKMLL9vLM9sD@O4M9vIHMM9r'LHHrHMM9rfDHHLL9HHpHH;HHHHt H HLHDžMtLZ HH HDž Ht> HH(HDž(Ht" HH@Ht HH HH`HtHH8 HHq_HH;EHH8[A\A]A^A_]fWf)EE(HEHexpand sHEHinvalid HEEhapeEHMHHE*EYH}K HH` HH@ H H H IEH} HH`HIH}H9HuvHHHHDžHH HDž HH(HDž(HH@HHP(HHt`IHHpHIHHX0IHH@IH`HIH@HelIH HDž H# IH(HDž(H IH@HIH`HHhIH@HIH@HIH}I99HP HH8IHH#H HHHDžH HH HDž H HH(HDž(H HH@Ht HH HH`HtHH8e HLH ffff.UH]f.UH]4 HfDUHSPHP' HH `HHsHx HH[]fff.UHH`HHGH~ HH]ffff.UH]f.UH]HfDUHAWAVATSIL>L"M9IFINH0IHHxINLL9}.IN IV(L LESA)IKAH9uH1MuZi1efff.M)H1HHI<HI HHHI|HI\HHI9uMtHHI<IHH<IF0H8IF8HH0IF@H% HIFHHJIM9 +[A\A^A_]ÐUHH [H1H9NHD]DUHH`]UH]f.UH]4HfDUHSPH0'HH `HHKHSHHHPHKHHHK HH HK(HH(H[]@UHHM`HHG(HF(HG HF HGHFHGHOHNHF]UH]f.UH]HfDUHAWAVAUATSH(H}H6HHEH9HUHBHJHHuHHRH2H H HHHHHUHB LB(HHHH<IHHIJ<L4JN,L9vIH]M9r@~fffff.IHL6HMKMLL9vH]M9sGKL9vIILL9r'LHuLHIL9rfHuHH;uH([A\A]A^A_]UHH %~[H1H9NHD]DUHH`]UHAVSIHHH_HH{LsHd`HH[A^]IHHLH fff.UHAVSIHHHB_HH{LHd`HH[A^]IHTHLH fff.UHHH _HHxH@Ht]H]fDUHSPHH_HH{HCHtHHH[]HfUHAWAVAUATSH8HHHKh_HHE1HFIL/)HxID$HM|$ HHFIL(HI~IfWf)`HDžpMJ<IIHI9 HNHhH`J HpMKNIIIrL9J H9HHNDI)DHtHHHHHHuI8Y1ɐHHHTHTHTHTHTHTHT HT HT(HT(HT0HT0HT8HT8HT@H@L9uHhH11I?M!IpHHyH s 1Hu|HwH)1ffffff.LLD L0D L0D@LPD@LPfD`LpfD`LpHHuHt.H HfDfD  fD H HuM92HhHI)IJ|HhH)IL$It$ HH)HHH)v%HEH`HMHnIL$It$ H9tdL`LhH)LL)1fDH9tQH|I\H9t&HuI|HH9u,fDHHH9uHL L`fWf)@HDžPLL)t^LIIHI9HILHL@KHPHI)M~LLKHMLHH@1HhHpL+H8IH`HL!I)MIM9LILH0HyHHHILAL8GHH(L"GHH L GILHMLLL)IžLMKDHHKTHHHHIt uIIIf.HCHI|ItHHHHHHIHIII_rffff.HHYHHHDžHxH HHHH@HIL0IHK|IfWf)HDžMHtJI9vMN<L^GHJHHLGGHMLKDHHHHHx*HcLHHIIHLpHHEPGH `HHHHHHHH0HHH(HH H HH(H8HH0HxHH8HHH@HHHHHEfHnfbYf\Yf|W)MfEHUH]LLH+H}H9/H,HP(!ME1f.HIHHxL0L9}.L(L ESA)IKAH9uH1MuZi1efff.M)H1HHI<HI HHHI|HI\HHI9uMtHHI<IHH<H8HHxHGHJIM9 +J4J<+HP H0HpHH;_ILL8LeLufDHHXLHE0vGH =`HHHHH HHHHHHHH Lh(HEfInfbYf\ɠYf|W)MfEHHLL+H}I9tHtHP(fffff.HP HHHHH;OfDM!1 +HHHHH H IHHHHHHH<IIL8K<M,JJL9vILM9rEILHGHLHO$$LLL9vLM9sMffff.O4M9vIHMM9r'LHH"GMM9rfDHHLL9HHpHH;HHHHt H/GLHDžMtL +GH HDž HtGH(HDž(HtGH@Ht HHGH`HtHH8GH@\_HH;EHH8[A\A]A^A_]fWf)EE(HEHexpand sHEHinvalid HEEhapeEHMHH*EYH}KkGH`eGH@WG HIG IEH}GH`HIH}H9HuvHHHHDžHH HDž HH(HDž(HH@HHP(HHt`IHHpHIHHX0IHH@IH`HIH@HelIH HDž H# IH(HDž(H IH@HIH`HHhIH@HIH@HIH}I99HP HH8IHH#HGHHDžHGH HDž HbGH(HDž(H BGH@Ht HH0GH`HtHH8GLUG ffff.UH]f.UH]GfDUHSPHPGH `HHsHx HH[]fff.UHH`HHGH~ HH]ffff.UH]f.UH]TGfDUHAWAVATSIL>L"M9IFINH0IHHxINLL9}.IN IV(L LESA)IKAH9uH1MuZi1efff.M)H1HHI<HI HHHI|HI\HHI9uMtHHI<IHH<IF0H8IF8HH0IF@HGIFHHJIM9 +[A\A^A_]ÐUHH l[H1H9NHD]DUHH`]UH]f.UH]GfDUHSPH0GH `HHKHSHHHPHKHHHK HH HK(HH(H[]@UHH]`HHG(HF(HG HF HGHFHGHOHNHF]UH]f.UH]4GfDUHAWAVAUATSH(H}H6HHEH9HUHBHJHHuHHRH2H H HHHHHUHB LB(HHHH<IHHIJ<L4JN,L9vIH]M9r@~fffff.IHLGMLHO$$LLL9vH]M9s@KL9vIILL9r'LHuLGIL9rfHuHH;uH([A\A]A^A_]UHH j[H1H9NHD]DUHH`]UHAVSIGHHR_HH{L#Ht`HH[A^]IHdGLG fff.UHAVSIFGHH_HH{LHt`HH[A^]IHGLDG fff.UHHH _HHxH@Ht]G]fDUHSPHHp_HH{HCHtGHH[]GfUHAWAVAUATSH8HHHR_HHE1Hj1ILSHxID$HM|$ HH31ILHI~pIfWf)`HDžpMJ<IIHI9 GNHhH`J HpMKNIIIrL9J H9HHNDI)DHtHHHHHHuI8Y1ɐHHHTHTHTHTHTHTHT HT HT(HT(HT0HT0HT8HT8HT@H@L9uHhH11I?M!IpHHyH s 1Hu|HwH)1ffffff.LLD L0D L0D@LPD@LPfD`LpfD`LpHHuHt.H HfDfD  fD H HuM9HhHI)IJ|HhH)IL$It$ HH)HHH)v%HEH`HMHIL$It$ H9tdL`LhH)LL)1fDH9tQH|I\H9t&HuI|HH9u,fDHHH9uHL L`fWf)@HDžPLL)t^LIIHI9GILHL@KHPHI)M~LLGMLHH@1HHPQL+H8IH`HL!I)MIM9LILH0HyHHHILALGHH(LGHH LGILHMLLL'IžLMKDHHKTHHHHIt uIIIf.HCHI|ItHHHHHHIHIII_pffff.HHYHHHDžHx HHH@HIL0IHK|IfWf)HDžMHtJI9XMN<LGHJHHLGHMLKDHHHHx*HcLHHIIHLpHHEPGH *`HHHHHHHH0HHH(HH H HH(H8HH0HxHH8HHH@HHHHHEfHnfbYf\Yf|W)MfEHUH]LLH*H}H9HHP(ME1HIHHxL0L9}.L(L ESA)IKAH9uH1MuZi1efff.M)H1HHI<HI HHHI|HI\HHI9uMtHHI<IHH8HHxHNGHJIM9J4J<DHP H0HHHH;XILL8LuLeffffff.HHXLHE06GH ]`HHHHH HHHHHHHH Lh(HEfInfbYf\Yf|W)MfEHHLL*H}I9tHtHP(fffff.HP HHHHH;?fDM1 +HHHHH L$IHIHHLHH<HL8I|MHIL9vILM9r?}ffff.ILLFGMI_HLL9vLM9sD@M,M9vHIMM9r'LHLGMM9rfDHHLL9HHHHH;HHHHt HGLHDžMtLGH HDž HtGH(HDž(HtGH@Ht HHGH`HtHH8uGHG_HH;EHH8[A\A]A^A_]fWf)EE(HEHexpand sHEHinvalid HEEhapeEHMHHű*EYH}K;GH`5GH@'G HG IEH}GH`HIH}H9HuvHHHHDžHH HDž HH(HDž(HH@HHP(HHt`IHHpHIHHX0IHH@IH`HIH@HelIH HDž H# IH(HDž(H IH@HIH`HHhIH@HIH@HIH}I99HP HH8IHH#HxGHHDžHRGH HDž H2GH(HDž(H GH@Ht HHGH`HtHH8GL%G ffff.UH]f.UH]GfDUHSPHPGH N`HHsHx HH[]fff.UHH`HHGH~ HH]ffff.UH]f.UH]$GfDUHAWAVATSIL>L"M9IFINH0IHHxINLL9}.IN IV(L LESA)IKAH9uH1MuZi1efff.M)H1HHI<HI HHHI|HI\HHI9uMtHHI<IHIF0IN8H8HH1IF@HGIFHHJIM9[A\A^A_]f.UHH X[H1H9NHD]DUHH`]UH]f.UH]GfDUHSPH0GH `HHKHSHHHPHKHHHK HH HK(HH(H[]@UHH`HHG(HF(HG HF HGHFHGHOHNHF]UH]f.UH]GfDUHAWAVAUATSH(H}H6HHEH9 HMHAHQHHuHHIH HL$IHIHHUHB Hr(H8LHH<IL6K<.MHLL9vILuM9r>|fff.ILHGHKoMLL9vLuM9sGO4/M9vIHMM9r'LHuHuGMM9rfHuHH;uH([A\A]A^A_]UHH 5W[H1H9NHD]DUHH-`]UHAVSIGHH2_HH{LH`HH[A^]IHDGLG fff.UHAVSI&GHHҼ_HH{L裷H`HH[A^]IHGL$G fff.UHHH _HHxH@Ht]G]fDUHSPHHP_HH{HCHtuGHH[]gGfUHAWAVAUATSH8HHH=_HHE1HJIL/KHxID$HM|$ HHILHI~[IfWf)`HDžpMJ<IIHI9 GNHhH`J HpMKNIIIrL9J H9HHNDI)DHtHHHHHHuI8Y1ɐHHHTHTHTHTHTHTHT HT HT(HT(HT0HT0HT8HT8HT@H@L9uHhH11I?M!IpHHyH s 1Hu|HwH)1ffffff.LLD L0D L0D@LPD@LPfD`LpfD`LpHHuHt.H HfDfD  fD H HuM9-HhHI)IJ|HhH)IL$It$ HH)HHH)v%HEH`HMHoIL$It$ H9tdL`LhH)LL)1fDH9tQH|I\H9t&HuI|HH9u,fDHHH9uHL L`fWf)@HDžPLL)t^LIIHI9GILHL@KHPHI)M~LLGMLHH@1HHpIL+H8IH`HL!I)MIM9LILH0HyHHHILALGHH(LGHH LGILHMLLL)IžLMKDHHKTHHHHIt uIIIf.HCHI|ItHHHHHHIHIII_rffff.HHYHHHDžHx fHHH@HIL0IHK|IfWf)HDžMHtJI9fMN<LGHJHHLGHMLKDHHHHHx*HcLHHIIHLpHHEP^GH e`HHHHHHHH0HHH(HH H HH(H8HH0HxHH8HHH@HHHHHEfHnfbvxYf\~xYf|W)MfEHUH]LLH*H}H9+H(HP(ME1ff.HIHHxL0L9}.L(L ESA)IKAH9uH1MuZi1efff.M)H1HHI<HI HHHI|HI\HHI9uMtHHI<IHH<H8HHxHGHJIM9J4J<0HP H0HpHH;TIL +L8LeLuff.HHXLHE0GH `HHHHH HHHHHHHH Lh(HEfInfbQvYf\YvYf|W)MfEHHLLt*H}I9tHtHP(fffff.HP HHHHH;?fDM1 +HHHHH H IHHHHHHH<IML8K<fM,NJgLHL9vILM9r8vfDILHGHKMLL9vLM9sD@O4gM9vIHMM9r'LHHGMM9rfDHHLL9HHpHH;HHHHt HGLHDžMtLGH HDž HtGH(HDž(HtrGH@Ht HH`GH`HtHH8EGH1_HH;EHH8[A\A]A^A_]fWf)EE(HEHexpand sHEHinvalid HEEhapeEHMHH蕜*EYH}K GH`GH@G HG IEH}kGH`HIH}H9HuvHHHHDžHH HDž HH(HDž(HH@HHP(HHt`IHHpHIHHX0IHH@IH`HIH@HelIH HDž H# IH(HDž(H IH@HIH`HHhIH@HIH@HIH}I99HP HH8IHH#HHGHHDžH"GH HDž HGH(HDž(H GH@Ht HHGH`HtHH8GLG ffff.UH]f.UH]GfDUHSPHPwGH ~`HHsHx HH[]fff.UHHM`HHGH~ HH]ffff.UH]f.UH]GfDUHAWAVATSIL>L"M9IFINH0IHHxINLL9}.IN IV(L LESA)IKAH9uH1MuZi1efff.M)H1HHI<HI HHHI|HI\HHI9uMtHHI<IHH<IF0H8IF8HH0IF@HzGIFHHJIM9[A\A^A_]fDUHH 5E[H1H9NHD]DUHH`]UH]f.UH]GfDUHSPH0wGH `HHKHSHHHPHKHHHK HH HK(HH(H[]@UHH`HHG(HF(HG HF HGHFHGHOHNHF]UH]f.UH]GfDUHAWAVAUATSH(H}H6HHEH9 HUHBHJHHuHHRH2H H HHHHHUHB LB(HHHH<IHHIJ<cL4KJgMML9vIH]M9r3qIHLGMKMLL9vH]M9sGKgL9vIILL9r'LHuLEGIL9rfHuHH;uH([A\A]A^A_]UHH C[H1H9NHD]DUHH]`]UHAVSIVGHH_HH{LӢH`HH[A^]IHGLTG fff.UHAVSIGHH_HH{LsH`HH[A^]IHGLG fff.UHHH R_HHxH@Ht]vG]fDUHSPHH _HH{HCHtEGHH[]7GfUHAWAVAUATSH8HHH(_HHE1HILCHxID$HM|$ HHILXHI~|FIfWf)`HDžpMJ<IIHI9 lGNHhH`J HpMKNIIIrL9J H9HHNDI)DHtHHHHHHuI8Y1ɐHHHTHTHTHTHTHTHT HT HT(HT(HT0HT0HT8HT8HT@H@L9uHhH11I?M!IpHHyH s 1Hu|HwH)1ffffff.LLD L0D L0D@LPD@LPfD`LpfD`LpHHuHt.H HfDfD  fD H HuM92HhHI)IJ|HhH)IL$It$ HH)HHH)v%HEH`HMHZIL$It$ H9tdL`LhH)LL)1fDH9tQH|I\H9t&HuI|HH9u,fDHHH9uHL 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HH]ffff.UH]f.UH]ijGfDUHAWAVATSIL>L"M9IFINH0IHHxINLL9}.IN IV(L LESA)IKAH9uH1MuZi1efff.M)H1HHI<HI HHHI|HI\HHI9uMtHHI<IHH<IF0H8IF8HH0IF@HEGIFHHJIM9 +[A\A^A_]ÐUHH 1[H1H9NHD]DUHHM`]UH]f.UH]TGfDUHSPH0GGH .`HHKHSHHHPHKHHHK HH HK(HH(H[]@UHH`HHG(HF(HG HF HGHFHGHOHNHF]UH]f.UH]餱GfDUHAWAVAUATSH(H}H6HHEH9HUHBHJHHuHHRH2H H HHHHHUHB LB(HHHH<IHHIJ<L4JN,L9vIH]M9r@~fffff.IHLVGMKMLL9vH]M9sGKL9vIILL9r'LHuLGIL9rfHuHH;uH([A\A]A^A_]UHH E0[H1H9NHD]DUHH}`]UHAVSIGHH’_HH{L蓍H`HH[A^]IHԯGLG fff.UHAVSI趯GHHb_HH{L3H`HH[A^]IHtGL贬G fff.UHHH _HHxH@Ht]6G]fDUHSPHH_HH{HCHtGHH[]GfUHAWAVAUATSH8HHHk_HHE1HIL8HxID$HM|$ HHILHI~<1IfWf)`HDžpMJ<IIHI9 ,GNHhH`J HpMKNIIIrL9J H9HHNDI)DHtHHHHHHuI8Y1ɐHHHTHTHTHTHTHTHT HT HT(HT(HT0HT0HT8HT8HT@H@L9uHhH11I?M!IpHHyH s 1Hu|HwH)1ffffff.LLD L0D L0D@LPD@LPfD`LpfD`LpHHuHt.H HfDfD  fD H HuM92HhHI)IJ|HhH)IL$It$ HH)HHH)v%HEH`HMHEIL$It$ H9tdL`LhH)LL)1fDH9tQH|I\H9t&HuI|HH9u,fDHHH9uHL L`fWf)@HDžPLL)t^LIIHI9#GILHL@KHPHI)M~LLkGMLHH@1H舍H07L+H8IH`HL!I)MIM9LILH0HyHHHILALXGHH(LBGHH L,GILHMLLL)IžLMKDHHKTHHHHIt 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ELILS,GHxH15IH@HIH@HIH@HIH@HIHxHIHxHIHxHIHxHquIHxHY]IHxHAEIHxH)-IHxHIHxHIHxHIHxHIHxHIHxHIHxHIHxHimIHxHQU@>IAH*GHXHDžXH1CIHXHDžXH ID72IHH8Ht/I()G$IHH8Ht2I(e)G'ILV)GHH4IL4)GHHIHHIH@HIH@HIH@HIH@HIL(GHHILr(GHHDIHH?IHH'IHHIHHIH@HIH@HIH@HIH@HIHHx,IHH`IHHIHHIHH/IHHIH HIH HsIHH,IHHIHH|HIHHd0IH}HEH9uHHP HHtGHM&GHHt;H5&GHH-HuIHHuHHuHHH %GHHHP(HHteIH}HEH9u_HP HHt^H%GHHtRHv%GH HtFH(^%GHHu>GHu@HHuHHuH HuHHHHP(HHtWIH}HEH9u0HP HHt/H$GHH!Hu%HHuHHHzHP(HHtIH}HEH9u,HP HHt/HA$GHHt/!HHHuHHt H$GH@Ht HH#GHxHt H}#GHXHDžXHtCt H{#GH#GL G HP(HHm9UHHH _HHxH@Ht]V#G]fDUHSPHH_HH{HCHt%#GHH[]#GfUHAVSI#GHHLH[A^]IH"GL G UHAWAVAUATSHHIH/^HHEL-A_M,$I|$H -`I$W)EHEEEaxisEIL$HhHUH2HhHDžhHtCt H{*"GH""GEt H}"GHu'H^HH;EuHĘ[A\A]A^A_]G"G!GH@Hh*H5[IH <\IH}LhW)PHDž`0!GH`(\4[)PHte valueHHHttributeHHH'axis' aHHHInvalid HHHMissing/H@&LHYIHuHPH@FDžLH55^HbH@.!G IǰLLuMuKIǰLHhHIIPt H` GLuMt6HEL9t!HX@t Hxc GHI9uH}LLuI GEuEuHhHu&^H}& GEtH} GHhHt:HpH9tELp@t HxGLL9uHhHpGLt%H@GHIEt H}GM,$I|$ID$HtGLG ffffff.UHAVSIfGHHL~H[A^]IH9GLyG UHAWAVAUATSPIHIGHCIIOHKHHLsHC(HC HCI I+t^III9GILc LcKHC(IwMo I)MH~LL GHMLc IG@HC@IG0IO8HK8HC0HCXHCPHCHIPI+HtOLuLcHIII9w\/GILkPLkHKDHCXIwHMwPI)M~LLzGMLkPIG`HC`H[A\A]A^A_]L4GL*G II<$Ht H{PGHEH8Hu II>Ht H{ GLG UHAWAVAUATSH8LLHIIHHǔ^HHEH8H^HHHLH@H8LGHHEEL-@^IEHHI@L8LGL5^ILHDž(HDž HDžHDžDž0I$HGHHHŏI7H(GHHHGHHH蒏HH0HGHHHGHHHXHE0HGHHHHHL8Lt H GH}GH5^HHGH8 GH^HH;EuHH8[A\A]A^A_]GHHHL8Lt H GHG3H HHHHHHH5ґ^HHVGH8^GH越HH8GGH蟊ffffff.UHAWAVATSHPIH^HHEL}IIHMMtHM9IuwHEI|$ H?HHuP0H^HH;EM1LufDH]I|$ HHLP0HH;]|H~8HP1LufDH]I|$ HHLP0HH9]L*HL9LNL}LH~HE$`HEHEHEHEHELeH]H]LHH*H}H9tHtHP(H^HH;Et#HP H^HH;Eu HP[A\A^A_]GGGH ^HHH5ʎ^HHGIH}H9uHP LG HtHP(LG f.UH]f.UH]dGfDUHSPH WGH &#`HHKHSHHHPHKHHH[]@UHH"`HHGHFHGHOHNHF]UH]f.UH]GfDUHAWAVATSHH:^HHEIHIvIFHHH>IH9~I\$HNd#L9|BIHIHL9}0L}f.IFH]Hx Ht3HLP0HL9|H^HH;Eu H[A\A^A_]zG(GH C^HHH5^HƧH:Gfffff.UHH եZH1H9NHD]DUHH!`]UHSPHH"`HH{PHt H{XGH{ HtH{(H[]qGH[]fff.UHSPHH!`HH{PHt H{X9GH{ Ht H{('GHH[]Gff.UHAVSIpGHIvHV!`HH{H[A^]IHGL G DUHHGH !`HH~H]qUHSPHH{PHt H{XGH{ HtH{(H[]kGH[]fDUHSPHH{PHt H{XCGH{ Ht H{(1GHH[]#GDUHHLGHWLO8HcO@HcHLWHIc4Hy LOPIcI4HO J4HHH RI4HGhH@HHGH]Gff.UHH ZH1H9NHD]DUHHM `]UHH] `HHG8Ht HG@H]ZG]f.UHSPHH( `HH{8Ht H{@)GHH[]Gffff.UHAWAVAUATSHIXGHH`HIG0HC0IG(HC(IG HC IIGHCIGIOHKHCHCHHC@HC8IG8Mg@I)tZHELuH8MILH=uXLsGIHMLi@Li8KDIIFHMHu~LLGMMn@IGPIFPLH[A\A]A^A_]HuG IH;Ht HEHx@GH}GL,G @UHAWAVAUATSPHH`HIIF0HC0IF(HC(IF HC IFHCIFINHKHCHCHHC@HC8I~@I+~8tNL{8IILH=uQaGILc@Lc8KHCHIv8M~@I)M~LLGMLc@IFPHCPH[A\A]A^A_]LgG II?Ht H{@GL+G UHHHx8Ht -Hx@]G]@UHSPHH{8Ht H{@GHH[]GUHHLGLOHw HcO(HcHHc4Hy HcO0HW8H4LH vI4HGPH@HHGH]vGf.UHH բZH1H9NHD]DUHHM`]UHAWAVAUATSPIHIGHCIIOHKHHLsHC(HC HCI I+t^III9GILc LcKHC(IwMo I)MH~LLGHMLc IG@HC@IG0IO8HK8HC0HCXHCPHCHIPI+HtOLuLcHIII9w\GILkPLkHKDHCXIwHMwPI)M~LLJGMLkPIG`HC`H[A\A]A^A_]L GL G II<$Ht H{P}GHEH8Hu II>Ht H{ [GL G UHAWAVAUATSH8LLHIIHH^HHEH8H҄^HHHLH@H8L{GHHEEL-^IEHHI@L8L GL5ą^ILHDž(HDž HDžHDžDž0I$HGHHH蕁I7H GHHHGHHHbHH0H GHHHfGHHH(HEH0H GHHH߆HHL8Lt H l GHL GH5c^HH GH8 GH^HH;EuHH8[A\A]A^A_]s GHHHL8Lt H GH G3H|H|H|H|H|H|HH5^HH% GH8- GH|HH8 GHn|fffff.UHSPHH`HH{PHt H{X) GH{ HtH{(H[] GH[]fff.UHSPHHX`HH{PHt H{X GH{ Ht H{( GHH[] Gff.UHAVSIp GHIvH`HH{H[A^]IHm GLG DUHHGH `HH~H]AUHSPHH{PHt H{X# GH{ HtH{(H[] GH[]fDUHSPHH{PHt H{X -GH{ Ht H{( -GHH[] -GDUHHLGHWHw8HO@HLOHH4Hy LWPIcI4HO J4HHH RI4HGhH@HHGH]Gfffff.UHH eZH1H9NHD]DUHH`]UHH`HHG8Ht HG@H] G]f.UHSPHH`HH{8Ht H{@ GHH[] Gffff.UHAWAVAUATSHIX GHHp`HIG0HC0IG(HC(IG HC IIGHCIGIOHKHCHCHHC@HC8IG8Mg@I)tZHELuH8MILH=uXL GIHMLi@Li8KDIIFHMHu~LL^ -GMMn@IGPIFPLH[A\A]A^A_]HG IH;Ht HEHx@GH}GLG @UHAWAVAUATSPHHP`HIIF0HC0IF(HC(IF HC IFHCIFINHKHCHCHHC@HC8I~@I+~8tNL{8IILH=uQGILc@Lc8KHCHIv8M~@I)M~LLM GMLc@IFPHCPH[A\A]A^A_]LG II?Ht H{@GLG UHHHx8Ht -Hx@]dG]@UHSPHH{8Ht H{@CGHH[]5GUHHLGHWHw HO(HH4Hy LcO0HO8J4HH vI4HGPH@HHGH]Gffff.UHH UZH1H9NHD]DUHH`]UHAWAVAUATSPHIHCIGHHKIOIHMwIG(IG IGH{ H+{t^III9;GIMg MgKIG(HsLk I)MH~LL}GHMMg HCHIGHHC@IG@HC0HK8IO8IG0IG`IGXIGPH{XH+{PtOLuMgPIII9wTGIMoXMoPKDIG`HsPH[XH)H~LHGIMoXH[A\A]A^A_]LGLG HI<$Ht IXGHEH8Hu HI>Ht I GH;G UHSPHHH`HH{XHt H{`GH{ HtH{(H[]GH[]fff.UHSPHH`HH{XHt H{`yGH{ Ht H{(gGHH[]YGff.UHAVSIpFGHIvH`HH{H[A^]IH GLMG DUHHGH Y`HH~H]AUHSPHH{XHt H{`GH{ HtH{(H[]GH[]fDUHSPHH{XHt H{`GH{ Ht H{(qGHH[]cGDHLHP8HIHxHpHHLH@LcPHMcMLPPOc MyUHSLXXIcM []H@ N LLHHGff.UHH ZH1H9NHD]DUHH`]UHH`HHG@Ht HGHH]G]f.UHSPHHh`HH{@Ht H{HiGHH[][Gffff.UHAWAVAUATSPHX?GIH`I$HC8ID$8HC0ID$0HC(ID$(HC ID$ MHCID$HCHKIL$ID$ID$PID$HID$@HC@L{HI)tOHEI@LHHH=uILGIMnHMn@IDIFPMHu~LLGMMnHLH[A\A]A^A_]LF II<$Ht I~H;GL3GLsF ff.UHAWAVAUATSPIH`IHHC8IF8HC0IF0HC(IF(HC IF HCIFHCHKINIFIFPIFHIF@H{HH+{@tNM~@IILH=uIGIMfHMf@KIFPHs@H[HH)H~LHGIMfHH[A\A]A^A_]LF HI?Ht I~H+GHkF UHHHx@Ht -HxH]G]@UHSPHH{@Ht H{HFHH[]FUHHHHP HHHxHpL@LH(LcP0HcLIc Hy LcH8H@@J LHH]Gfff.UHH 5ZH1H9NHD]DUHH `]UHAWAVAUATSPHIHCIGHHKIOIHMwIG(IG IGH{ H+{t^III9FIMg MgKIG(HsLk I)MH~LLGHMMg HCHIGHHC@IG@HC0HK8IO8IG0IG`IGXIGPH{XH+{PtOLuMgPIII9wT7FIMoXMoPKDIG`HsPH[XH)H~LHFIMoXH[A\A]A^A_]LDFL:F HI<$Ht IXFHEH8Hu HI>Ht I FHF UHSPHH `HH{XHt H{`iFH{ HtH{(H[]QFH[]fff.UHSPHH `HH{XHt H{`FH{ Ht H{(FHH[]Fff.UHAVSIpFHIvH6 `HH{H[A^]IHFLF DUHHGH -`HH~H]AUHSPHH{XHt H{`cFH{ HtH{(H[]KFH[]fDUHSPHH{XHt H{`#FH{ Ht H{(FHH[]FDHLHP8HIHxHpHHLH@LXHMLPPO MyUHSLXXIcM []H@ N LLHH"Ffffff.UHH UZH1H9NHD]DUHH- -`]UHH= -`HHG@Ht HGHH]:F]f.UHSPHH -`HH{@Ht H{H FHH[]Fffff.UHAWAVAUATSPHXFIH `I$HC8ID$8HC0ID$0HC(ID$(HC ID$ MHCID$HCHKIL$ID$ID$PID$HID$@HC@L{HI)tOHEI@LHHH=uILGFIMnHMn@IDIFPMHu~LLFMMnHLH[A\A]A^A_]LXF II<$Ht I~HFLFLF ff.UHAWAVAUATSPIH`IHHC8IF8HC0IF0HC(IF(HC IF HCIFHCHKINIFIFPIFHIF@H{HH+{@tNM~@IILH=uI9FIMfHMf@KIFPHs@H[HH)H~LHFIMfHH[A\A]A^A_]LGF HI?Ht I~HFH F UHHHx@Ht -HxH]F]@UHSPHH{@Ht H{HFHH[]uFUHHHHP HHHxHpL@LH(HH0I Hy LcH8H@@J LHH]FfUHH ZH1H9NHD]DUHH=`]ÐUHAWAVAUATSH(HUo^HHEIIHHAHq H):LLHHHyHHHcL$Lx:|HI6LL)HI6L|II6L HpHHIHhW)PHDž`M;LH= HN<LFHPJH`HLFHX1L@IHtLp~HPHHHxH9|WH*H0zFH(X)Hger thanHH Hrank larHHHust has HHHtensor mHHHindices Hf@( 0@*HH)HWLHDžHHID$(HIL$0HIL$ HP8H@I|$8HDžHIHLHaLHhHHpHH@HHxHLHHH HPH(H}L0H`HEH]H]H]W)EEHULH*H}H9HtiHtHP(HHtdH0IHELuHuHHLPHL>)Et H}MFHPHu%/HP HHuHHPHt HXFHk^HH;EuHH([A\A]A^A_]FFHP@F IEH}FHPHIHIHPHulvIH}H9uHP HPHuLVHt9HP(HPHu3=IHPHu",IHPHuIHPHt HX -FLJF fUHAWAVATSHIII?IGHH)HL9sxHt"IFIGIGI1LH=u@HHHHH9HML9IH9LFMWMI)IM9LIBHpHrHSH9HH9HL@HHtHf.H HHHHuI@H HH HNH HNH HNH HN H HN(H HN0H HN8H@HuIJ<FIGIJ IOHLIrHKH9J4HLH9vyLBHHtHH3H1HHHuI@H3H1H3HqH3HqH3HqH3Hq H3Hq(H3Hq0H3Hq8H@Hu}LHH~HHJH`~fpDHyH)1DD D0HHuHt~fpDDL9IJIIIPHHDNAH~fpDIQH)1ff.DD D0HHuMt~fpDDL9IM97M)LLIHCL9vKLLH9LHHFHHJHT~fpDHAH)1fffff.AADAD AD0HHuHt~fpDAADI9t|I LH)HrHHtHؐH;H9HHHuHrIHHHHAHHAHHAHHA HHA(HHA0HHA8H@HuKJI[A\A^A_]H LH)LBHH+1HJ4L)L@HH$>1M7F1Hfff.UHAWAVAUATSH(Hee^HHEIIHHAHq H):LLHHHyHHHcL$LxJrHI6LL9uHI6L'rII6LuHpHHIHhW)PHDž`M;LH= HN<L FHPJH`HLFHX1L@IHtLtHPHHHxH9|WH*H0FH("X)Hger thanHH Hrank larHHHust has HHHtensor mHHHindices Hf@( 0@*HH)HWLHDžHHID$(HIL$0HIL$ H`H@I|$8HDžHIHLHqLHhHHpHH@HHxHLHHH HPH(H}L0H_HEH]H]H]W)EEHULH)H}H9HtiHtHP(HHtdH&IHELuHuHHLFHLN)Et H}]FHPHu%/HP HHuHHPHt HX FHa^HH;EuHH([A\A]A^A_]VFHPPF IEH}FHPHIHIHPHulvIH}H9uHP HPHuLVHt9HP(HPHu3=IHPHu",IHPHuIHPHt HXFLZF fUHAWAVATSH`IHw`^HHEؿ(FHþ HFHHCHCXHC`HCXHCHHC@HC8HC0HC(HC HCPHCpHCxHCpHChƃHǃfǃHǃHǃƃHHǃHǃHǃHǃHǃHǃHǃHǃHǃHHHǃHǃHǃǃǃHǃ H])mH5yFH}HIIHW)EHE4FHEHHHML HXHMH5PIHUL-H5F#IHH5FHHAH5 +GHHH;HHH _HMH/HUHuHuIIGIG0IOIWIG@H}Ht H}dFH]HEHtHHCFH]^HH;EuLH`[A\A^A_]~FIH]HEHt7HHFL6F IH}HuH]HEHuLF H}FH]HEHtff.UHAVSHPIH ]^HHE(FHþ HzFHHCHCXHC`HCXHCHHC@HC8HC0HC(HC HCPHCpHCxHCpHChƃHǃfǃHǃHǃƃHHǃHǃHǃHǃHǃHǃHǃHǃHǃHHHǃHǃHǃǃǃHǃ H]iH5 FH}HHBH5LIHHH5 IHH5KHHH HQH5'GHHH;HHH _HMH[HUHuHuIIFIF0INIVIF@H]HEHtHH!FHZ^HH;Eu LHP[A^]`FIH]HEHtHHFLF @UHAVSHPIH;Z^HHE(FHþ HFHHCHCXHC`HCXHCHHC@HC8HC0HC(HC HCPHCpHCxHCpHChƃHǃfǃHǃHǃƃHHǃHǃHǃHǃHǃHǃHǃHǃHǃHHHǃHǃHǃǃǃHǃ H]fH5=FH}HJHrH5JIHHH5IIHH5LKHHH HQH5 %GHHH;HHH _HMHHUHuHuIIFIF0INIVIF@H]HEHtH HQFHW^HH;Eu LHP[A^]FIH]HEHtHH FLLF @UHAVSHPIHkW^HHE(FHþ HFHHCHCXHC`HCXHCHHC@HC8HC0HC(HC HCPHCpHCxHCpHChƃHǃfǃHǃHǃƃHHǃHǃHǃHǃHǃHǃHǃHǃHǃHHHǃHǃHǃǃǃHǃ H]dH5mFH}HzHH5LGIHHH5yIHH5| KH"HA H5@"GHIHH;HHH _HMHBHUHuHuIIFIF0INIVIF@H]HEHtHBHFHU^HH;Eu LHP[A^]FIH]HEHtHHCFLF ff.UHAWAVAUATSH(HHIHT^HHE1H' HHH HHHzLzHr IM)LHHHHM4HLpHC H+CHI9~nPFHH0f(uZf) H5IFHFCFH L) H0HFfWf)HDžHL)HZHHLIILH=jFHLHHJHLM9HHIM)LHHHLr+ID$HIDH9IIIM9HML)Ht"Hfff.IHIHHuH8{1IHITHTITHTITHTIT HT IT(HT(IT0HT0IT8HT8IT@H@L9uL1LM -HI?I!I@HHzH s1MHHGH)1MAALLAD AL0D L0AD@ALPD@LPfAD`ALpfD`LpHHuHt8HHfffff.fADA fD H HuL9IJtHILsHK HL]HHH LI$H(H0fWf)HDžH 1H胷IMH Ht H(FfWf)`f)Pf)@f)0f) HLhHH{0HCPuH(IIFPH8H IIFPH0HPHHHHHQ0RtcL,$HL HI#HHDžHtZCt H{FHFH(uGxL,$HL HIHHDžHuH(6H HxH`H+XPIXf\QXf|H_HEHHxHEH]H]W)MfEHULH )1fWf)EHE0 -FHEf(Zf)EHupportedHHH not supHHHata typeHHHtensor dHHHindices H@&HMMLLf)EH}qFHXHH HxH`H+X@Xf\Xf|H(_HEHHxHEH]H]W)MfEHULH)H}H9MLt HtHP(HP IEHXHt H`FHHt I<$FHM^HH;Eu)LH([A\A]A^A_]J O<H'F]FIH} *H5IH IH LE;fWf)EHE@FHEf(Xf)EHunt mismHH(HInput coHH Hompute: HHHpareForCHHHBase PreHHHGatherNDH@0atch@4AHIH HML=E1H5m^HPLF HFIALXMu@}IALeMIIEt H}FLXMt?H`L9t$HX@t HxFHI9uHXLL`F@u u LeMu,[HPF tH0wFLeMt1HEL9tCHX@t HxRFHI9uH}Le=FE/L\FLlF L0IEH}FHXHLIH}H9uHP HXHHHP(HXHu|IHHHwLIH HtQH(CIHHuELI t@H02LIHXHt H`FHHt I<$FLEF ffff.UHAWAVAUATSH(IIILL)H HMQMqLL)HH9ILH)HHHH= HI)LHHH9LMLU2II9LBM9II9HFHH5GHFHyH^HHH5+G^H<F^HHFMI)LHH9M<LM9HuM]MM)HHItL)HLLVHLIH1ITH9sHtHLI9LMH?L!HUHrIIAQH 1HLMELLMIIJ<!FLIH]I)LHH<IM9HEHMUMM)IMKIr KLH9J HDL9HM)DHt$Hffff.I $HHIHuI8b1I H ILHLILHLILHLIL HL IL(HL(IL0HL0IL8HL8IL@H@L9uE11I?M!IGHHqH H}s1HH}HEHDpH~H)1AALDȐLȠAD AL0DȰLAD@ALPDLAD`ALpD HHuHH}t2IDHHMHLH1ҐD D H HuM9utN|HHEIHM~HHuLnFHEN4HHUH)H~LHLFHEIHMHLyLqH}HtFLqJ4O$I|pHrL)1ɐDϐLϠLDϰLD L0DLD@LPD D`LpHHuHLMt,H H@ADA D  H HuHMI9II<ILII)DHtHِH2H7HHHuI8rc1DH4 +  IEt H}FLMt?HL9t$HX@t HxFHI9uHLLFt HFt HlFE1LhMu#HBIALhMHpL9HX@t HxFHI9uIEt H}FLMt?HL9t$HX@t HxFHI9uHLLFt HFt H~FE1LhMu#-HTIALhMHpL9 HX@t Hx)FHI9uIEt H}FLMt?HL9t$HX@t HxFHI9uHLLFt HFt HFE1LhMu#?HfIALhM!HpL9HX@t Hx;FHI9uIEt H}FLMt?HL9t$HX@t HxFHI9uHLLFt HFt HFE1LhMuTH{IALhMt:HpL9t8HX@t HxXFHI9uHhLp=FEu ELILSFHxH15IH@HIH@HIH@HIH@HIHxHIHxHIHxHIHxHquIHxHY]IHxHAEIHxH)-IHxHIHxHIHxHIHxHIHxHIHxHIHxHIHxHimIHxHQU@>IAHFHXHDžXH1CIHXHDžXH ID72IHH8Ht/I(F$IHH8Ht2I(eF'ILVFHH4IL4FHHIHHIH@HIH@HIH@HIH@HILFHHILrFHHDIHH?IHH'IHHIHHIH@HIH@HIH@HIH@HIHHx,IHH`IHHIHHIHH/IHHIH HIH HsIHH,IHHIHH|HIHHd0IH}HEH9uHHP HHtGHMFHHt;H5FHH-HuIHHuHHuHHH FHHHP(HHteIH}HEH9u_HP HHt^HFHHtRHvFH HtFH(^FHHu>GHu@HHuHHuH HuHHHHP(HHtWIH}HEH9u0HP HHt/HFHH!Hu%HHuHHHzHP(HHtIH}HEH9u,HP HHt/HAFHHt/!HHHuHHt HFH@Ht HHFHxHt H}FHXHDžXHtCt H{FHFLF HP(HHm9UHHH 2^HHxH@Ht]VF]fDUHSPHH^HH{HCHt%FHH[]FfUHAVSIFHHLH[A^]IHFLF UHAWAVAUATSHHIHON^HHEL-a^M,$I|$3H,_I$W)EHEEEaxisEIL$HhHUHbHhHDžhHtCt H{*FH"FEt H}FHu'HM^HH;EuHĘ[A\A]A^A_]GFFH@Hh茖*H5#IH J#IH}LhW)PHDž`0FH`(Z)PHte valueHHHttributeHHH'axis' aHHHInvalid HHHMissing/H@&LH IHuHPH@&DžLH5Un^H_H@.F IǰLLuMuKIǰLHhHIIPt H`FLuMt6HEL9t!HX@t HxcFHI9uH}LLuIFEuEuHhHu&^H}&FEtH}FHhHt:HpH9tELp@t HxFLL9uHhHpFLt%H@FHIEt H}FM,$I|$ID$HtFLF ffffff.UHAVSIfFHHL~H[A^]IH9FLyF UHAWAVAUATSPIHIGHCIIOHKHHLsHC(HC HCI I+t^III9FILc LcKHC(IwMo I)MH~LL FHMLc IG@HC@IG0IO8HK8HC0HCXHCPHCHIPI+HtOLuLcHIII9w\/FILkPLkHKDHCXIwHMwPI)M~LLzFMLkPIG`HC`H[A\A]A^A_]L4FL*F II<$Ht H{PFHEH8Hu II>Ht H{ FLF UHAWAVAUATSH8LLHIIHHH^HHEH8H"G^HHHLH@H8LFHHEEL-`H^IEHHI@L8LFL5H^ILHDž(HDž HDžHDžDž0I$HFHHH襌I7H(FHHHFHHHrHH0HFHHHFHHH8HE0HFHHHHHL8Lt H FH}FH5F^HHFH8 FH G^HH;EuHH8[A\A]A^A_]FHHHL8Lt H FHF3HHH܇HԇḢHćHH5E^HHVFH8^FH薇HH8GFHffffff.UHAWAVATSHPIHF^HHEL}IIHMMtHM9IuwHEI|$ H?HHuP0HE^HH;EM1LufDH]I|$ HHLP0HH;]|H~8HP1LufDH]I|$ HHLP0HH9]L)HL9LNL}LH~He_HEHEHEHEHELeH]H]LHH)H}H9tHtHP(HD^HH;Et#HP HD^HH;Eu HP[A\A^A_]GFFH 0D^HHH5B^HsHFIH}H9uHP LF HtHP(LF f.UH]f.UH]dFfDUHSPH WFH F_HHKHSHHHPHKHHH[]@UHH_HHGHFHGHOHNHF]UH]f.UH]FfDUHAWAVATSHHZC^HHEIHIvIFHHH>IH9~I\$HNd#L9|BIHIHL9}0L}f.IFH]Hx Ht3HLP0HL9|HB^HH;Eu H[A\A^A_]zF(FH cB^HHH5A^HH:Ffffff.UHH gZH1H9NHD]DUHH_]UHSPHH(_HH{PHt H{XFH{ HtH{(H[]qFH[]fff.UHSPHH_HH{PHt H{X9FH{ Ht H{('FHH[]Fff.UHAVSIpFHIvHv_HH{H[A^]IHFL F DUHHGH 9_HH~H]qUHSPHH{PHt H{XFH{ HtH{(H[]kFH[]fDUHSPHH{PHt H{XCFH{ Ht H{(1FHH[]#FDUHHLGHWLO8HcO@HcHLWHIc4Hy LOPIcI4HO J4HHH RI4HGhH@HHGH]Fff.UHH fZH1H9NHD]DUHHm_]UHH}_HHG8Ht HG@H]ZF]f.UHSPHHH_HH{8Ht H{@)FHH[]Fffff.UHAWAVAUATSHIXFHH_HIG0HC0IG(HC(IG HC IIGHCIGIOHKHCHCHHC@HC8IG8Mg@I)tZHELuH8MILH=uXLsFIHMLi@Li8KDIIFHMHu~LLFMMn@IGPIFPLH[A\A]A^A_]HuF IH;Ht HEHx@FH}FL,F @UHAWAVAUATSPHH_HIIF0HC0IF(HC(IF HC IFHCIFINHKHCHCHHC@HC8I~@I+~8tNL{8IILH=uQaFILc@Lc8KHCHIv8M~@I)M~LLFMLc@IFPHCPH[A\A]A^A_]LgF II?Ht H{@FL+F UHHHx8Ht +Hx@]F]@UHSPHH{8Ht H{@FHH[]FUHHLGLOHw HcO(HcHHc4Hy HcO0HW8H4LH vI4HGPH@HHGH]vFf.UHH dZH1H9NHD]DUHHm_]UHAWAVAUATSPIHIGHCIIOHKHHLsHC(HC HCI I+t^III9FILc LcKHC(IwMo I)MH~LLFHMLc IG@HC@IG0IO8HK8HC0HCXHCPHCHIPI+HtOLuLcHIII9w\FILkPLkHKDHCXIwHMwPI)M~LLJFMLkPIG`HC`H[A\A]A^A_]LFLF II<$Ht H{P}FHEH8Hu II>Ht H{ [FLF UHAWAVAUATSH8LLHIIHH:^HHEH8H8^HHHLH@H8L{FHHEEL-0:^IEHHI@L8LFL59^ILHDž(HDž HDžHDžDž0I$HFHHHu~I7HFHHHFHHHB~HH0HFHHHfFHHH~HEH0HFHHH迃HHL8Lt H lFHLFH58^HHFH8FH8^HH;EuHH8[A\A]A^A_]sFHHHL8Lt H FHF3HyHyHyHyHyHyHH57^HH%FH8-FHeyHH8FHNyfffff.UHSPHH_HH{PHt H{X)FH{ HtH{(H[]FH[]fff.UHSPHHx_HH{PHt H{XFH{ Ht H{(FHH[]Fff.UHAVSIpFHIvH_HH{H[A^]IHmFLF DUHHGH _HH~H]AUHSPHH{PHt H{X#FH{ HtH{(H[] FH[]fDUHSPHH{PHt H{XFH{ Ht H{(FHH[]FDUHHLGHWHw8HO@HLOHH4Hy LWPIcI4HO J4HHH RI4HGhH@HHGH]Ffffff.UHH %_ZH1H9NHD]DUHH _]UHH_HHG8Ht HG@H]F]f.UHSPHH_HH{8Ht H{@FHH[]Fffff.UHAWAVAUATSHIXFHH_HIG0HC0IG(HC(IG HC IIGHCIGIOHKHCHCHHC@HC8IG8Mg@I)tZHELuH8MILH=uXLFIHMLi@Li8KDIIFHMHu~LL^FMMn@IGPIFPLH[A\A]A^A_]HF IH;Ht HEHx@FH}FLF @UHAWAVAUATSPHHp_HIIF0HC0IF(HC(IF HC IFHCIFINHKHCHCHHC@HC8I~@I+~8tNL{8IILH=uQFILc@Lc8KHCHIv8M~@I)M~LLMFMLc@IFPHCPH[A\A]A^A_]LF II?Ht H{@FLF UHHHx8Ht +Hx@]dF]@UHSPHH{8Ht H{@CFHH[]5FUHHLGHWHw HO(HH4Hy LcO0HO8J4HH vI4HGPH@HHGH]Fffff.UHH ]ZH1H9NHD]DUHH _]UHAWAVAUATSPHIHCIGHHKIOIHMwIG(IG IGH{ H+{t^III9;FIMg MgKIG(HsLk I)MH~LL}FHMMg HCHIGHHC@IG@HC0HK8IO8IG0IG`IGXIGPH{XH+{PtOLuMgPIII9wTFIMoXMoPKDIG`HsPH[XH)H~LHFIMoXH[A\A]A^A_]LFLF HI<$Ht IXFHEH8Hu HI>Ht I FH;F UHSPHHh_HH{XHt H{`FH{ HtH{(H[]FH[]fff.UHSPHH_HH{XHt H{`yFH{ Ht H{(gFHH[]YFff.UHAVSIpFFHIvH_HH{H[A^]IH FLMF DUHHGH y_HH~H]AUHSPHH{XHt H{`FH{ HtH{(H[]FH[]fDUHSPHH{XHt H{`FH{ Ht H{(qFHH[]cFDHLHP8HIHxHpHHLH@LcPHMcMLPPOc MyUHSLXXIcM []H@ N LLHHFff.UHH uZZH1H9NHD]DUHH_]UHH_HHG@Ht HGHH]F]f.UHSPHH_HH{@Ht H{HiFHH[][Fffff.UHAWAVAUATSPHX?FIH3_I$HC8ID$8HC0ID$0HC(ID$(HC ID$ MHCID$HCHKIL$ID$ID$PID$HID$@HC@L{HI)tOHEI@LHHH=uILFIMnHMn@IDIFPMHu~LLFMMnHLH[A\A]A^A_]LF II<$Ht I~H;FL3FLsF ff.UHAWAVAUATSPIH_IHHC8IF8HC0IF0HC(IF(HC IF HCIFHCHKINIFIFPIFHIF@H{HH+{@tNM~@IILH=uIFIMfHMf@KIFPHs@H[HH)H~LHFIMfHH[A\A]A^A_]LF HI?Ht I~H+FHkF UHHHx@Ht +HxH]F]@UHSPHH{@Ht H{HFHH[]FUHHHHP HHHxHpL@LH(LcP0HcLIc Hy LcH8H@@J LHH]Ffff.UHH WZH1H9NHD]DUHH_]UHAWAVAUATSPHIHCIGHHKIOIHMwIG(IG IGH{ H+{t^III9FIMg MgKIG(HsLk I)MH~LLFHMMg HCHIGHHC@IG@HC0HK8IO8IG0IG`IGXIGPH{XH+{PtOLuMgPIII9wT7FIMoXMoPKDIG`HsPH[XH)H~LHFIMoXH[A\A]A^A_]LDFL:F HI<$Ht IXFHEH8Hu HI>Ht I FHF UHSPHH_HH{XHt H{`iFH{ HtH{(H[]QFH[]fff.UHSPHH_HH{XHt H{`FH{ Ht H{(FHH[]Fff.UHAVSIpFHIvHV_HH{H[A^]IHFLF DUHHGH _HH~H]AUHSPHH{XHt H{`cFH{ HtH{(H[]KFH[]fDUHSPHH{XHt H{`#FH{ Ht H{(FHH[]FDHLHP8HIHxHpHHLH@LXHMLPPO MyUHSLXXIcM []H@ N LLHH"Ffffff.UHH UZH1H9NHD]DUHHM_]UHH]_HHG@Ht HGHH]:F]f.UHSPHH(_HH{@Ht H{H FHH[]Fffff.UHAWAVAUATSPHXFIHӽ_I$HC8ID$8HC0ID$0HC(ID$(HC ID$ MHCID$HCHKIL$ID$ID$PID$HID$@HC@L{HI)tOHEI@LHHH=uILGFIMnHMn@IDIFPMHu~LLFMMnHLH[A\A]A^A_]LXF II<$Ht I~HFLFLF ff.UHAWAVAUATSPIH_IHHC8IF8HC0IF0HC(IF(HC IF HCIFHCHKINIFIFPIFHIF@H{HH+{@tNM~@IILH=uI9FIMfHMf@KIFPHs@H[HH)H~LHFIMfHH[A\A]A^A_]LGF HI?Ht I~H˿FH F UHHHx@Ht +HxH]餿F]@UHSPHH{@Ht H{H胿FHH[]uFUHHHHP HHHxHpL@LH(HH0I Hy LcH8H@@J LHH]FfUHH RZH1H9NHD]DUHH]_]ÐUHAWAVAUATSH(Hu#^HHEIIHHAHq H):LLHHHyHHHcL$Lx*CHI6LLFHI6LCII6LEHpHHIHhW)PHDž`M;LH= HN<LFHPJH`HLFHX1L@IHtL`EHPHHHxH9|WH*H0zFH(SX)Hger thanHH Hrank larHHHust has HHHtensor mHHHindices Hf@( 0@*HHÌ)HWLHDžHHID$(HIL$0HIL$ H05H@I|$8HDžHIHLHaLHhHHpHH@HHxHLHHH HPH(H}L0H _HEH]H]H]W)EEHULH)H}H9HtiHtHP(HHtdHHHELuHuHHL3OHL.)Et H}MFHPHu%/HP HHuHHPHt HXFH^HH;EuHH([A\A]A^A_]FFHP@F IEH}ºFHPHIHIHPHulvIH}H9uHP HPHuLVHt9HP(HPHu3=IHPHu",IHPHuIHPHt HX +FLJF fUHAWAVATSHIII?IGHH)HL9sxHt"IƹFIGIGI1LH=u@HHHHH9HML9IH9L¶FMWMI)IM9LIBHpHrHSH9HH9HL@HHtHf.H HHHHuI@H HH HNH HNH HNH HN H HN(H HN0H HN8H@HuIJ<蔸FIGIJ IOHLIrHKH9J4HLH9vyLBHHtHH3H1HHHuI@H3H1H3HqH3HqH3HqH3Hq H3Hq(H3Hq0H3Hq8H@Hu}LHH~HHJH`~fpDHyH)1DD D0HHuHt~fpDDL9IJIIIPHHDNAH~fpDIQH)1ff.DD D0HHuMt~fpDDL9IM97M)LLIHCL9vKLLH9LHHFHHJHT~fpDHAH)1fffff.AADAD AD0HHuHt~fpDAADI9t|I LH)HrHHtHؐH;H9HHHuHrIHHHHAHHAHHAHHA HHA(HHA0HHA8H@HuKJI[A\A^A_]H LH)LBHH+1HJ4L)L@HH$>1M7F1Hfff.UHAWAVAUATSH(H^HHEIIHHAHq H):LLHHHyHHHcL$Lx:9HI6LL)<HI6L9II6L <HpHHIHhW)PHDž`M;LH= HN<L FHPJH`HLFHX1L@IHtLp;HPHHHxH9|WH*H0芳FH(IX)Hger thanHH Hrank larHHHust has HHHtensor mHHHindices Hf@( 0@*HHӂ)HWLHDžHHID$(HIL$0HIL$ H@H@I|$8HDžHIHLHqLHhHHpHH@HHxHLHHH HPH(H}L0H_HEH]H]H]W)EEHULH躽)H}H9HtiHtHP(HHtdHHHELuHuHHLCEHL>)Et H}]FHPHu%/HP HHuHHPHt HX FH^HH;EuHH([A\A]A^A_]VFHPPF IEH}ҰFHPHIHIHPHulvIH}H9uHP HPHuLVHt9HP(HPHu3=IHPHu",IHPHuIHPHt HXFLZF fUHAWAVATSH`IH^HHEؿ(FHþ HFHHCHCXHC`HCXHCHHC@HC8HC0HC(HC HCPHCpHCxHCpHChƃHǃfǃHǃHǃƃHHǃHǃHǃHǃHǃHǃHǃHǃHǃHHHǃHǃHǃǃǃHǃ H]Y8H5yFH}H趶IIHW)EHE4FHEHHHML HXHMH5(IHUL]H5THHH5FHHAH5 FHFHH; HHH ^HMH/HUHuHuIIGIG0IOIWIG@H}Ht 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HHfFH]HH;EuHH[A\A]A^A_]FJFIH@)H5SHH SHH`L@9oyW)EE(HEHis requiHEHX input HEEred!EAH#FH`HML{E1H5ޫ]HTLFFIH}D)H5RHH &SHH`LEmxW) HDž0 <FH0(?W) Hrst outpHHHo get fiHHHfailed tH@ut!AH#FH`H L {E1H5]HSLF H` -F HALeMuiHALeMHHAL@MHH t H03FLeMt6HEL9t!Lh@t HxFLM9uH}LLeFEu`uLeMu)XH}F`tHpFLeMt1HEL9tNLh@t HxFLM9uH}LeFE{LFH@HovLHEt H}EFLeMt6HEL9t!Lh@t Hx FLM9uH}LLeFEu`u L@Mu,dH}F`tHpFL@Mt:HHL9tILh@t HxFLM9uH@LHFELFH F L(HH`HuJTHH`Hu9CHH@Hu:DHH`HuHH`Ht HhFH@Ht HHFH& F fffff.UHAWAVAUATSH(IIIILL)HHMaIyHL)HH9LEM9LL)HHHH=HL)HHHH9LM3HH9HBH6H9(FHH5VFH FHY]HHH5 ]H]H(FMM)LHH9ILHUL9M]MH]I)HHItL)HLFLHIH1ITI9sItLHH9LH?L!HUHrIIAQH 1HIHu&RLLLm+HH}H< FHLEL}M)LHHIM9H}MUMM)IMKIr KDH9JHDL9HM)DHt Hf.IHHIHuI8c1I H ILHLILHLILHLIL HL IL(HL(IL0HL0IL8HL8IL@H@L9u1HE1I?M!IGHHqH s1HH}HDpH~H)1fff.AALDȐLȠAD AL0DȰLAD@ALPDLAD`ALpD HHuHH}t2IDHHLH1DD D H HuM9ulN|IM~H}HuLW FH}HEHHuI)M~LL4 FH}MHEH8LxHXH}Ht -FMJ4O4I|pHrL)1fDϐLϠAALDϰLAD AL0DLAD@ALPD AD`ALpHHuHIHut1H HfD AD A H HuHUI9LEI<HMHI)DHt0HLEfffff.H2H7HHHuI8s qLEI8rg1fH4 +I(HAH9HMHH)ȉHHt%HHA\A)THHuH LrDA\A)TAT\A)TAT \A)T AT0\A)T0HH9|H9I)IsLIDLI<H9sIDI<H9MI(IxHHDHAHt[HH`H|0IT0IYH)1T\\\T\T\\THHu1ML`t HAA\\\ATA\M9LLHÉ)HCH)Ht&Hf.A \ALHHuHrXI)ID IL 1fL\LL\LL\L \ HI9uHHHpEH}xEH}oEH}HH}E HHpCEHH}HuO\HH}'EHH}EH}Hu*7HH}Hu)HH}HuHH}HtHH8EHE HH}HtH}fUHAVSI EHHLH[A^]IHiELE UHAVSHPIH`]HHE(DEHþ H:EHHCHCXHC`HCXHCHHC@HC8HC0HC(HC HCPHCpHCxHCpHChƃHǃfǃHǃHǃƃHHǃHǃHǃHǃHǃHǃHǃHǃHǃHHHǃHǃHǃǃǃHǃ H]*H5FH}HH5;HHH5'JHHH HQH5>FHHH;HHH ^HMHHUHuHuIIFIF0INIVIF@H]HEHtHHEH^]HH;Eu LHP[A^]:EIH]HEHtH`HELE fffff.UHAVSHPIH+^]HHE(EHþ HzEHHCHCXHC`HCXHCHHC@HC8HC0HC(HC HCPHCpHCxHCpHChƃHǃfǃHǃHǃƃHHǃHǃHǃHǃHǃHǃHǃHǃHǃHHHǃHǃHǃǃǃHǃ H]M*H5 FH}HH5^8HHH5$JH HH HQH5;FH,HH;HHH ^HMH%*HUHuHuIIFIF0INIVIF@H]HEHtHH;EH[]HH;Eu LHP[A^]zEIH]HEHtHHEL6E fffff.UHAVSHPIHk[]HHE(EHþ HEHHCHCXHC`HCXHCHHC@HC8HC0HC(HC HCPHCpHCxHCpHChƃHǃfǃHǃHǃƃHHǃHǃHǃHǃHǃHǃHǃHǃHǃHHHǃHǃHǃǃǃHǃ H]#H5MFH}HH55HHH5!"JHLHH HQH539FHlHH;1HHH ^HMH2HUHuHuIIFIF0INIVIF@H]HEHtH%H{EHY]HH;Eu LHP[A^]EIH]HEHtH H6ELvE fffff.UHAVSHPIHX]HHE(EHþ HEHHCHCXHC`HCXHCHHC@HC8HC0HC(HC HCPHCpHCxHCpHChƃHǃfǃHǃHǃƃHHǃHǃHǃHǃHǃHǃHǃHǃHǃHHHǃHǃHǃǃǃHǃ H] 'H5EH}HZH52HH[H5aJHHH HQH5s6FHHH;qHHH P^HMHe;HUHuHuIIFIF0INIVIF@H]HEHtHe HEHVV]HH;Eu LHP[A^]EIH]HEHtH HvELE fffff.UHAVSHPIHU]HHE(DEHþ H:EHHCHCXHC`HCXHCHHC@HC8HC0HC(HC HCPHCpHCxHCpHChƃHǃfǃHǃHǃƃHHǃHǃHǃHǃHǃHǃHǃHǃHǃHHHǃHǃHǃǃǃHǃ H] H5EH}HH50HHH5JHHH HQH53FHHH;HHH ^HMHDHUHuHuIIFIF0INIVIF@H]HEHtHHEHS]HH;Eu LHP[A^]:EIH]HEHtH`HELE fffff.UHAVSHPIH+S]HHE(EHþ HzEHHCHCXHC`HCXHCHHC@HC8HC0HC(HC HCPHCpHCxHCpHChƃHǃfǃHǃHǃƃHHǃHǃHǃHǃHǃHǃHǃHǃHǃHHHǃHǃHǃǃǃHǃ H] H5 EH}HH5^-HHH5JH HA H50FH3HH;HHH ^HMHLHUHuHuIIFIF0INIVIF@H]HEHtHHBEHP]HH;Eu LHP[A^]EIH]HEHtHHEL=E DUHAVSHPIH{P]HHE(EHþ HEHHCHCXHC`HCXHCHHC@HC8HC0HC(HC HCPHCpHCxHCpHChƃHǃfǃHǃHǃƃHHǃHǃHǃHǃHǃHǃHǃHǃHǃHHHǃHǃHǃǃǃHǃ H]H5]EH}H*H5*HH+H51JH\HA H5J.FHHH;HHHH '^HMH|JHUHuHuIIFIF0INIVIF@H]HEHtH<HEH-N]HH;Eu LHP[A^]EIH]HEHtHHMELE DUHAVSHPIHM]HHE($EHþ HEHHCHCXHC`HCXHCHHC@HC8HC0HC(HC HCPHCpHCxHCpHChƃHǃfǃHǃHǃƃHHǃHǃHǃHǃHǃHǃHǃHǃHǃHHHǃHǃHǃǃǃHǃ H]-H5EH}HzH5'HH{H5JHHA H5+FHHH;HHH w ^HMH,HHUHuHuIIFIF0INIVIF@H]HEHtHHEH}K]HH;Eu LHP[A^]!EIH]HEHtHGHELE DUHAVSHPIHK]HHE(tEHþ HjEHHCHCXHC`HCXHCHHC@HC8HC0HC(HC HCPHCpHCxHCpHChƃHǃfǃHǃHǃƃHHǃHǃHǃHǃHǃHǃHǃHǃHǃHHHǃHǃHǃǃǃHǃ H]}H5EH}HH5N%HHH5JHHA H5(FH#HH;HHH ^HMHEHUHuHuIIFIF0INIVIF@H]HEHtHH2EHH]HH;Eu LHP[A^]qEIH]HEHtHHEL-E DUHAVSHPIHkH]HHE(EHþ HEHHCHCXHC`HCXHCHHC@HC8HC0HC(HC HCPHCpHCxHCpHChƃHǃfǃHǃHǃƃHHǃHǃHǃHǃHǃHǃHǃHǃHǃHHHǃHǃHǃǃǃHǃ H]H5MEH}HH5"HHH5!JHLHA H5:&FHsHH;8HHH ^HMHCHUHuHuIIFIF0INIVIF@H]HEHtH,HEHF]HH;Eu LHP[A^]EIH]HEHtHH=EL}E DUHAVSI&EHH]HH{L裾H^HH[A^]IHEL$E fff.UHHH ]HHxH@Ht]E]fDUHSPHHP]HH{HCHtuEHH[]gEfUHAWAVAUATSHIIHD]HHE1LN#HHHHHHCLc I)It Iu H8uALW)@HDžPHbIH@HfHn IHCHK H)HLt HuFH8u@A?HDž`HHH;PiHHHHW)`HDžpMtALH=nN4LEH`JHpHLEHhLHaIM)HHIH LHE1fA?t!HHH`HhH@IH`HLHHH|HHIHH9t(HOHLH|&HLH9tfff.1HLH}IM9WQH@H`Brb1L@A<tHHH`HhLHL9rH`Ht HhELLH@HHH)H1IILeLuHEH`HDžhH`1LBHHbMMINHHHQINHI@I@ LHHуHH)HMIHSLHHMIJ HE1E1H'E1HLof.MMրHt9J K4H4H9J K4H4H91HAu1f1HAt$J HILHH4H4HHH9MLMHNHLH@JJ<H<H<H|HLL9uf.HHE1LHfffff.K FLLHLBD>B >LIHIuHLtK MMBBLLHHI9fffff.IHHIM9H>HHH@Ht HHfEH?]HH;EuHH[A\A]A^A_]EJEIH@)H5HH HH`L@9OvW)EE(HEHis requiHEHX input HEEred!EAHEH`HMLxE1H5_]HgQLEEIH}4)H5HH 4HH`LEmuW) HDž0 <EH0(TW) Hrst outpHHHo get fiHHHfailed tH@ut!AHEH`H LwE1H5#_]HPLE H` +E HALeMuiHALeMHHAL@MHH t H03ELeMt6HEL9t!Lh@t HxELM9uH}LLeEEu`uLeMu)XH}E`tHpELeMt1HEL9tNLh@t HxELM9uH}LeEE{LEH@HovLHEt H}EELeMt6HEL9t!Lh@t Hx ELM9uH}LLeEEu`u L@Mu,dH}E`tHpEL@Mt:HHL9tILh@t HxELM9uH@LHEELEHE L(HH`HuJTHH`Hu9CHH@Hu:DHH`HuHH`Ht HhEH@Ht HHEH&E fffff.UHAWAVAUATSH(IIIILL)HHMaIyHL)HH9LEM9LL)HHHH=HL)HHHH9LM3HH9HBH6H9(EHH5FHEHy9]HHH5+8]H<7]H(EMM)LHH9ILHUL9M]MH]I)HHItL)HLFLHIH1ITI9sItLHH9LH?L!HUHrIIAQH 1HIHu&RLLLm+HH}H<EHLEL}M)LHHIM9H}MUMM)IMKIr KDH9JHDL9HM)DHt Hf.IHHIHuI8c1I H ILHLILHLILHLIL HL IL(HL(IL0HL0IL8HL8IL@H@L9u1HE1I?M!IGHHqH s1HH}HDpH~H)1fff.AALDȐLȠAD AL0DȰLAD@ALPDLAD`ALpD HHuHH}t2IDHHLH1DD D H HuM9ulN|IM~H}HuLWEH}HEHHuI)M~LL4EH}MHEH8LxHXH}HtEMJ4O4I|pHrL)1fDϐLϠAALDϰLAD AL0DLAD@ALPD AD`ALpHHuHIHut1H HfD AD A H HuHUI9LEI<HMHI)DHt0HLEfffff.H2H7HHHuI8s qLEI8rg1fH4 H4Ht HtHt HtHt HtHt Ht Ht (Ht(Ht 0Ht0Ht 8Ht8Ht -@H@L9uIK|IyM?HI4HHH)IIH)L9LMJLH)MIIILMAIv K HDH9JDH9HHqI9IGIIIDHtHfDHHHHHuI8C1H1H0H\1H\0H\1H\0H\1H\0H\1 H\0 H\1(H\0(H\10H\00H\18H\08H\1@H@L9rI?M!IBHHD~AH s 1MuHEJDpMoI)1ff.DLLDLD L0DLD@LPD D`LpHIuMt.HID D H IuM9uSJDHMHALEHtIL)LEFLEHUL)tLL-FLELH([A\A]A^A_]JJ LFIHFLF UHAVSIVFHH]HH{LH_HH[A^]IHFLTF fff.UHHH ]HHxH@Ht]F]fDUHSPHH`]HH{HCHtFHH[]FfUHAWAVAUATSHIIH|]HHE1LHHHHHHHCLc I)It Iu H8uALW)@HDžPHهIH@H趤H3IHCHK H)HLt HuFH8u@A?HDž`HHH;PiHHHHW)`HDžpMtALH=nN4LJFH`JHpHL3FHhLHIM)HHIH LHE1fA?t!HHH`HhH@IH`HLHHH|HHIHH9t(HOHLH|&HLH9tfff.1HLH}IM9WQH@H`r^b1L@A<tHHH`HhL HL9rH`Ht HhFLLH@HHH)H1IILeLuHEH`HDžhH`1LBHHARMMINHHHQINHI@I@ LHHуHH)HMIHSLHHMIJ HE1E1H'E1HLof.MMրHt9J K4H4H9J K4H4H91HAu1f1HAt$J HILHH4H4HHH9MLMHNHLH@JJ<H<H<H|HLL9uf.HHE1LHfffff.K FLLHLBD>B >LIHIuHLtK MMBBLLHHI9fffff.IHHIM9H>HHH@Ht HHEHw]HH;EuHH[A\A]A^A_]EzEIH@%)H5?HH @HH`L@9eW)EE(HEHis requiHEHX input HEEred!EAHFH`HMLhE1H5]H@L EEIH}t)H5?HH ?HH`LEmdW) HDž0 lEH0(+W) Hrst outpHHHo get fiHHHfailed tH@ut!AH?FH`H L=gE1H53]H?L0E H`:E HALeMuiHALeMHHAL@MHH t H0cELeMt6HEL9t!Lh@t Hx>ELM9uH}LLe$EEu`uLeMu)XH}E`tHpELeMt1HEL9tNLh@t HxELM9uH}LeEE{LEH@HovLHEt H}uELeMt6HEL9t!Lh@t HxPELM9uH}LLe6EEu`u L@Mu,dH}E`tHpEL@Mt:HHL9tILh@t HxELM9uH@LHEELEHE L(HH`HuJTHH`Hu9CHH@Hu:DHH`HuHH`Ht Hh.EH@Ht HHEHVE fffff.UHAVSIEHH]HH{LCH_HH[A^]IHELE fff.UHHH 2]HHxH@Ht]vE]fDUHSPHH]HH{HCHtEEHH[]7EfUHAWAVAUATSHIIHq]HHE1L.=HHHHHHCLc I)It Iu H8uALW)@HDžPHy|IH@HVH><IHCHK H)HLt HuFH8u@A?HDž`HHH;PiHHHHW)`HDžpMtALH=nN4LEH`JHpHLEHhLH{IM)HHIH LHE1fA?t!HHH`HhH@yIH`HLHHfDH|HHIHH9t(HOHLH|&HLH9tfff.1HLH}IM9WQH@H`Sb1L@A<tHHH`HhLHL9rH`Ht HhZELLH@HHH)H1IILeLuHEH`HDžhH`1LHHFMMINHHHQINHI@I@ LHHуHH)HMIHSLHHMIJ HE1E1H'E1HLof.MMրHt9J K4H4H9J K4H4H91HAu1f1HAt$J HILHH4H4HHH9MLMHNHLH@JJ<H<H<H|HLL9uf.HHE1LHfffff.K FLLHLBD>B >LIHIuHLtK MMBBLLHHI9fffff.IHHIM9H>HHH@Ht HH6EHk]HH;EuHH[A\A]A^A_]lEEIH@š)H5c4HH 5HH`L@9?ZW)EE(HEHis requiHEHX input HEEred!EAHFH`HML\E1H5]HW5LEfEIH})H53HH 4HH`LEmYW) HDž0 EH0(d W) Hrst outpHHHo get fiHHHfailed tH@ut!AHFH`H L[E1H5Ӌ]H|4LE H`E HALeMuiHALeMHHAL@MHH t H0ELeMt6HEL9t!Lh@t HxELM9uH}LLeEEu`uLeMu)XH}E`tHpELeMt1HEL9tNLh@t HxgELM9uH}LeREE{LqEH@HovLHEt H}ELeMt6HEL9t!Lh@t HxELM9uH}LLeEEu`u L@Mu,dH}E`tHpEL@Mt:HHL9tILh@t HxpELM9uH@LHUEELtEHE L(HH`HuJTHH`Hu9CHH@Hu:DHH`HuHH`Ht HhEH@Ht HHEHE fffff.UHAVSIEHH"]HH{LH_HH[A^]IHTELE fff.UHHH ]HHxH@Ht]E]fDUHSPHH]HH{HCHtEHH[]EfUHAWAVAUATSHIIH/f]HHE1L1HHHHHHCLc I)It Iu H8uALW)@HDžPHqIH@HHIHCHK H)HLt HuFH8u@I?HDž`HHH;PiHHHHW)`HDžpMtALH=nN4LEH`JHpHLsEHhLH)pIM)HHIH LHE1fI?t!HHH`HhH@IH`HLHHfDH|HHIHH9t(HOHLH|&HLH9tfff.1HLH}IM9WQH@H`Gb1L@I<tHHH`HhLLHL9rH`Ht HhELLH@HHH)H1IILeLuHEH`HDžhH`1LHH;MMINHHHQINHI@I@ LHHуHH)HMIHSLHHMIJ HE1E1H'E1HLof.MMրHt9J K4H4H9J K4H4H91HAu1f1HAt$J HILHH4H4HHH9MLMHNHLH@JJ<H<H<H|HLL9uf.HHE1LHfffff.K FLLHLBD>B >LIHIuHLtK MMBBLLHHI9fffff.IHHIM9H>HHH@Ht HHEHQ`]HH;EuHH[A\A]A^A_] EEIH@e)H5)HH *HH`L@9NW)EE(HEHis requiHEHX input HEEred!EAHOEH`HMLXQE1H5N]H)LKEEIH}贕)H5R(HH *HH`LEm1NW) HDž0 EH0(W) Hrst outpHHHo get fiHHHfailed tH@ut!AHEH`H L}PE1H5s]H)LpE H`zE HALeMuiHALeMHHAL@MHH t H0ELeMt6HEL9t!Lh@t Hx~ELM9uH}LLedEEu`uLeMu)XH}AE`tHp,ELeMt1HEL9tNLh@t HxELM9uH}LeEE{LEH@HovLHEt H}ELeMt6HEL9t!Lh@t HxELM9uH}LLevEEu`u L@Mu,dH}PE`tHp;EL@Mt:HHL9tILh@t HxELM9uH@LHEELEH$E L(HH`HuJTHH`Hu9CHH@Hu:DHH`HuHH`Ht HhnEH@Ht HHVEHE fffff.UHAVSI6EHH]HH{L能H^HH[A^]IHEL4E fff.UHHH r]HHxH@Ht]E]fDUHSPHH@]HH{HCHtEHH[]wEfUHAWAVAUATSHIIHZ]HHE1Ln&HHHHHHCLc I)It Iu H8uALW)@HDžPHeIH@H薂H.IHCHK H)HLt HuOH8uIAW.u HDž`HHH;PHHHHW)`HDžpMtALH=N4L!EH`JHpHL -EHhLHdIMJHHIH LHE1fA.YWu{!HHH`HhH@IH`HLHHfff.H|HHIHH9t(HOHLH|&HLH9tfff.1HLH}IM9G[H@H`2<l1L@A.YWu{HHH`HhLHL9rH`Ht HhpELLH@HHH)H1IILeLuHEH`HDžhH`1LHH/MMwINHHHQINHI@I@ LHHуHH)HMIHSLHHMIJ HE1E1HE1HLeMMրHt9J K4H4H9J K4H4H91HAu1f1HAt$J HILHH4H4HHH9MLMHNHLH@JJ<H<H<H|HLL9uf.HHE1LHfffff.K FLLHLBD>B >LIHIuHLtK MMBBLLHHI9fffff.IHHIM9H>HHH@Ht HHVEHT]HH;EuHH[A\A]A^A_]E:EIH@)H5HH HH`L@9_CW)EE(HEHis requiHEHX input HEEred!EAHEH`HMLEE1H5u]HwLEEIH}4)H5HH HH`LEmBW) HDž0 ,EH0( W) Hrst outpHHHo get fiHHHfailed tH@ut!AHEH`H LDE1H5t]HLE H`E HALeMuiHALeMHHAL@MHH t H0#ELeMt6HEL9t!Lh@t HxELM9uH}LLeEEu`uLeMu)XH}E`tHpELeMt1HEL9tNLh@t HxELM9uH}LerEE{LEH@HovLHEt H}5ELeMt6HEL9t!Lh@t HxELM9uH}LLeEEu`u L@Mu,dH}E`tHpEL@Mt:HHL9tILh@t HxELM9uH@LHuEELEHE L(HH`HuJTHH`Hu9CHH@Hu:DHH`HuHH`Ht HhEH@Ht HHEHE fffff.UHAVSIEHHB]HH{LH^HH[A^]IHtELE fff.UHAVSIVEHH]HH{L裱H^HH[A^]IHELTE fff.UHAVSIEHH]HH{LCH^HH[A^]IHELE fff.UHAVSIEHH"]HH{LH^HH[A^]IHTELE fff.UHAVSI6EHH]HH{L胰H^HH[A^]IHEL4E fff.UHAVSHPIHKN]HHE(EHþ HEHHCHCXHC`HCXHCHHC@HC8HC0HC(HC HCPHCpHCxHCpHChƃHǃfǃHǃHǃƃHHǃHǃHǃHǃHǃHǃHǃHǃHǃHHHǃHǃHǃǃǃHǃ H]H5FH}HHH5@HHHHhH5GHHH5(HHH5BJHHH -HQH5FHHH;HHH ^HMHBHUHuHuIIFIF0INIVIF@H]HEHtHHGEHK]HH;Eu LHP[A^]EIH]HEHtHHELBE f.UHAVSHPIH[K]HHE(EHþ HEHHCHCXHC`HCXHCHHC@HC8HC0HC(HC HCPHCpHCxHCpHChƃHǃfǃHǃHǃƃHHǃHǃHǃHǃHǃHǃHǃHǃHǃHHHǃHǃHǃǃǃHǃ H]H5FH}HHH5PHHHHxH5GHHH58HHH5RIHHA H5FHHH;HHH ^HMH\HUHuHuIIFIF0INIVIF@H]HEHtHH^EHH]HH;Eu LHP[A^]EIH]HEHtHHELYE UHAVSHPIH{H]HHE(EHþ HEHHCHCXHC`HCXHCHHC@HC8HC0HC(HC HCPHCpHCxHCpHChƃHǃfǃHǃHǃƃHHǃHǃHǃHǃHǃHǃHǃHǃHǃHHHǃHǃHǃǃǃHǃ H]H5FH}HHH5pGHHHH5GHHH5XHHH5rIHHH -HQH5/FH8HH;HHH ^HMHQZHUHuHuIIFIF0INIVIF@H]HEHtH1HwEHE]HH;Eu LHP[A^]EIH]HEHtHH2ELrE f.UHAVSHPIHE]HHE(EHþ HEHHCHCXHC`HCXHCHHC@HC8HC0HC(HC HCPHCpHCxHCpHChƃHǃfǃHǃHǃƃHHǃHǃHǃHǃHǃHǃHǃHǃHǃHHHǃHǃHǃǃǃHǃ H]H5FH}H*HH5GHHHH5ϡGHHH5hHHH5IH(HA H5FFHOHH;HHH ^HMHnHUHuHuIIFIF0INIVIF@H]HEHtHHHEH C]HH;Eu LHP[A^]EIH]HEHtHHIELE UHAVSHPIHB]HHE($EHþ HEHHCHCXHC`HCXHCHHC@HC8HC0HC(HC HCPHCpHCxHCpHChƃHǃfǃHǃHǃƃHHǃHǃHǃHǃHǃHǃHǃHǃHǃHHHǃHǃHǃǃǃHǃ H]H5FH}HJHH5GHH0HH5GHHH5 HHH5IHHHH -HQH5_ FHhHH;-HHH ^HMHqkHUHuHuIIFIF0INIVIF@H]HEHtHaHEH"@]HH;Eu LHP[A^]EIH]HEHtHHbELE f.UHAVSHPIH?]HHE(4EHþ H*EHHCHCXHC`HCXHCHHC@HC8HC0HC(HC HCPHCpHCxHCpHChƃHǃfǃHǃHǃƃHHǃHǃHǃHǃHǃHǃHǃHǃHǃHHHǃHǃHǃǃǃHǃ H] H5FH}HZHH5GHH@HH5GHH&H5 HH'H5IHXHA H5v -FHHH;DHHH 3]HMHHuHUHuHuIIFIF0INIVIF@H]HEHtHxHEH9=]HH;Eu LHP[A^]EIH]HEHtH3HyELE UHAVSHPIH<]HHE(TEHþ HJEHHCHCXHC`HCXHCHHC@HC8HC0HC(HC HCPHCpHCxHCpHChƃHǃfǃHǃHǃƃHHǃHǃHǃHǃHǃHǃHǃHǃHǃHHHǃHǃHǃǃǃHǃ H]H5FH}HzHH5GHH`H8H5GHHFH5HHGH5IHxHH -HQH5FHHH;]HHH L]HMHrHUHuHuIIFIF0INIVIF@H]HEHtHHEHR:]HH;Eu LHP[A^]EIH]HEHtHLHELҿE f.UHAVSHPIH9]HHE(dEHþ HZEHHCHCXHC`HCXHCHHC@HC8HC0HC(HC HCPHCpHCxHCpHChƃHǃfǃHǃHǃƃHHǃHǃHǃHǃHǃHǃHǃHǃHǃHHHǃHǃHǃǃǃHǃ H]H5+FH}HH"H5GHHpHHH5/GHHVH5HHWH5IHHA H5FHHH;tHHH c]HMH|HUHuHuIIFIF0INIVIF@H]HEHtHHEHi7]HH;Eu LHP[A^]-EIH]HEHtHcH詿ELE UHAVSHPIH 7]HHE(脿EHþ HzEHHCHCXHC`HCXHCHHC@HC8HC0HC(HC HCPHCpHCxHCpHChƃHǃfǃHǃHǃƃHHǃHǃHǃHǃHǃHǃHǃHǃHǃHHHǃHǃHǃǃǃHǃ H]]H5KFH}HHBH5GHHHH5OGHHvH5HHwH5IH訾HH -HQH5FHȿHH;荴HHH |]HMHzHUHuHuIIFIF0INIVIF@H]HEHtHHEH4]HH;Eu LHP[A^]FEIH]HEHtH|H¼ELE f.UHAVSHPIH4]HHE(蔼EHþ H芼EHHCHCXHC`HCXHCHHC@HC8HC0HC(HC HCPHCpHCxHCpHChƃHǃfǃHǃHǃƃHHǃHǃHǃHǃHǃHǃHǃHǃHǃHHHǃHǃHǃǃǃHǃ H]mH5[FH}HHRH5GHHHH5_GHHH5GH臺H5IH踻HA H5EH߼HH;褱HHH ]HMH8HUHuHuIIFIF0INIVIF@H]HEHtHHEH1]HH;Eu LHP[A^]]EIH]HEHtHHٹELE UHAVSHPIH;1]HHE(费EHþ H誹EHHCHCXHC`HCXHCHHC@HC8HC0HC(HC HCPHCpHCxHCpHChƃHǃfǃHǃHǃƃHHǃHǃHǃHǃHǃHǃHǃHǃHǃHHHǃHǃHǃǃǃHǃ H]H5{FH}HHrH50GHHHH5GHHH5GH觷H52IHظHH -HQH5EHHH;轮HHH 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ff.UHAVSHIHx\HHE(DHþ HDHHCHCXHC`HCXHCHHC@HC8HC0HC(HC HCPHCpHCxHCpHChƃHǃfǃHǃHǃƃHHǃHǃHǃHǃHǃHǃHǃHǃHǃHHHǃHǃHǃǃǃHǃ H]H}Hp?HpHuOH5_DH}HUHpH5RFHH5HH&HA H5DDHMHH;HHH \HMH&HUHuHuIIFIF0INIVIF@HpHt Hx蕢DH}Ht H}胢DH]HEHtHHbDH\HH;EuLHĀ[A^]螢DIH}Ht0^IH]HEHt+bIHpHu$H}Hu0H]HEHu9L1D HxۡDH}HtH}ɡDH]HEHtHbH訡DLD UHAWAVSH8IH \HHEt]HHRH)HHL11DHHH<8uHH IHHH9rQLHrL)tEHIL11DHHI<uHH I<HLH9rIH7\HH;EudLH8[A^A_]ÉEH -FHELuHuHULLLIp'EtH}XDH\HH;Et裠DHgFHELuHuLJLLo'HEu HEt H}DH4D fff.UHAWAVAUATSHIIHpH8\HHE1LII_0HHHPHffHDžHDžID$HxA|$LLMg M+gLcIIG0xIGIO H)HHtH_H8UL豎IIL!IIM9HHL>Mt^1Lfffff.HH;t IHHHHIL9rLL5?HIL9rHHII)MIffPHDž`MHI9HLDILPO4L`LLDLXHLH9utfAnD$Hf~HpH9hdH9cZfH~fnII!H>E1LH9tB1fff.H HxHL9r!ffff.I HHL9r̾LL(HHHC0H;HHHHHKPHHHeH8L AAHpHHHLE11E1HHpHHuMHE1Hfnf~AAID$HI0HpHHtHHH1LIffEHEI} I+}LXH@LIIHI9胛DILeLeHEHKHEIuMu I)M LLDMMLmM)LLHHHHRH)HH9,ffEIHELO|HHtcH;LHLDHTOLH<H 1H<H<H<I<M<ItHHuE1H_HmFHHPHHH]FH}Hi'HEHpHHEPH`ϿLHMtH}nLeH]KDI9$ LHH!HFHLHf ILH9sHtHLI9H H?H!HzHHNH a 1H LH AAIHHI!HpHHH1LHffEHEHy 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K4H4H91HAu1f1HAt$J HILHH4H4HHH9MLMHNHLH@JJ<H<H<H|HLL9uf.HHE1LHfffff.K FLLHLBD>B >LIHIuHLtK MMBBLLHHI9fffff.IHHIM9H>HHH@Ht HHEH1+]HH;EuHH[A\A]A^A_]EzEIH@t)H5HH HH`L@9bW)EE(HEHis requiHEHX input HEEred!EAHEH`HMLdE1H5.L]H=L EEIH}ds)H5 HH HH`LEmaW) HDž0 lEH0(V) Hrst outpHHHo get fiHHHfailed tH@ut!AH?EH`H LdE1H5SK]H<L0E H`:E HALeMuiHALeMHHAL@MHH t H0cELeMt6HEL9t!Lh@t Hx>ELM9uH}LLe$EEu`uLeMu)XH}E`tHpELeMt1HEL9tNLh@t HxELM9uH}LeEE{LEH@HovLHEt H}uELeMt6HEL9t!Lh@t HxPELM9uH}LLe6EEu`u L@Mu,dH}E`tHpEL@Mt:HHL9tILh@t HxELM9uH@LHEELEHE L(HH`HuJTHH`Hu9CHH@Hu:DHH`HuHH`Ht Hh.EH@Ht HHEHVE fffff.UHAVSIEHH]HH{LsH^HH[A^]IHELE fff.UHHH R]HHxH@Ht]vE]fDUHSPHH ]HH{HCHtEEHH[]7EfUHAWAVAUATSHIIH%]HHE1LHHHHHHCLc I)It Iu H8uALW)@HDžPHiCIH@H6H9IHCHK H)HLt HuFH8u@A?HDž`HHH;PiHHHHW)`HDžpMtALH=nN4LEH`JHpHLӿEHhLHyBIM)HHIH LHE1fA?t!HHH`HhH@yIH`HLHHfDH|HHIHH9t(HOHLH|&HLH9tfff.1HLH}IM9WQH@H`Sb1L@A<tHHH`HhLHL9rH`Ht HhZELLH@HHH)H1IILeLuHEH`HDžhH`1LHHCMMINHHHQINHI@I@ LHHуHH)HMIHSLHHMIJ HE1E1H'E1HLof.MMրHt9J K4H4H9J K4H4H91HAu1f1HAt$J HILHH4H4HHH9MLMHNHLH@JJ<H<H<H|HLL9uf.HHE1LHfffff.K FLLHLBD>B >LIHIuHLtK MMBBLLHHI9fffff.IHHIM9H>HHH@Ht HH6EH]HH;EuHH[A\A]A^A_]lEEIH@h)H5qGH GH`L@9WW)EE(HEHis requiHEHX input HEEred!EAHEH`HMLYE1H5@]H72L諺EfEIH}h)H5GH GH`LEmqVW) HDž0 EH0($V) Hrst outpHHHo get fiHHHfailed tH@ut!AHEH`H LXE1H5?]H\1LйE H`ڶE HALeMuiHALeMHHAL@MHH t H0ELeMt6HEL9t!Lh@t Hx޸ELM9uH}LLeĸEEu`uLeMu)XH}衸E`tHp茸ELeMt1HEL9tNLh@t HxgELM9uH}LeREE{LqEH@HovLHEt H}ELeMt6HEL9t!Lh@t HxELM9uH}LLeַEEu`u L@Mu,dH}谷E`tHp蛷EL@Mt:HHL9tILh@t HxpELM9uH@LHUEELtEH脴E L(HH`HuJTHH`Hu9CHH@Hu:DHH`HuHH`Ht HhζEH@Ht HH趶EHE fffff.UHAVSI薶EHHB]HH{LH^HH[A^]IHTEL蔳E fff.UHHH ]HHxH@Ht]E]fDUHSPHH]HH{HCHtEHH[]׵EfUHAWAVAUATSHIIHO]HHE1LHHHHHHCLc I)It Iu H8uALW)@HDžPH 8IH@H֊HIHCHK H)HLt HuFH8u@I?HDž`HHH;PiHHHHW)`HDžpMtALH=nN4L芴EH`JHpHLsEHhLH7IM)HHIH LHE1fI?t!HHH`HhH@IH`HLHHfDH|HHIHH9t(HOHLH|&HLH9tfff.1HLH}IM9WQH@H`Gb1L@I<tHHH`HhLLHL9rH`Ht HhELLH@HHH)H1IILeLuHEH`HDžhH`1L貙HHa8MMINHHHQINHI@I@ LHHуHH)HMIHSLHHMIJ HE1E1H'E1HLof.MMրHt9J K4H4H9J K4H4H91HAu1f1HAt$J HILHH4H4HHH9MLMHNHLH@JJ<H<H<H|HLL9uf.HHE1LHfffff.K FLLHLBD>B >LIHIuHLtK MMBBLLHHI9fffff.IHHIM9H>HHH@Ht HH֯EHq]HH;EuHH[A\A]A^A_] E躯EIH@U])H5GH GH`L@9KW)EE(HEHis requiHEHX input HEEred!EAHOEH`HML8NE1H5n5]H&LKEEIH}\)H5`GH GH`LEmKW) HDž0 謮EH0(V) Hrst outpHHHo get fiHHHfailed tH@ut!AHEH`H L]ME1H54]H%LpE H`zE HALeMuiHALeMHHAL@MHH t H0裭ELeMt6HEL9t!Lh@t Hx~ELM9uH}LLedEEu`uLeMu)XH}AE`tHp,ELeMt1HEL9tNLh@t HxELM9uH}LeEE{LEH@HovLHEt H}赬ELeMt6HEL9t!Lh@t Hx萬ELM9uH}LLevEEu`u L@Mu,dH}PE`tHp;EL@Mt:HHL9tILh@t HxELM9uH@LHEELEH$E L(HH`HuJTHH`Hu9CHH@Hu:DHH`HuHH`Ht HhnEH@Ht HHVEH薨E fffff.UHAVSI6EHH]HH{L賈H^HH[A^]IHEL4E fff.UHHH ]HHxH@Ht]鶪E]fDUHSPHH`]HH{HCHt腪EHH[]wEfUHAWAVAUATSHIIH]HHE1L^HHHHHHCLc I)It Iu H8uALW)@HDžPH,IH@HvHIHCHK H)HLt HuOH8uIAW.u HDž`HHH;PHHHHW)`HDžpMtALH=N4L!EH`JHpHL +EHhLH+IMJHHIH LHE1fA.Wu{!HHH`HhH@IH`HLHHfff.H|HHIHH9t(HOHLH|&HLH9tfff.1HLH}IM9G[H@H`2<l1L@A.Wu{HHH`HhLHL9rH`Ht HhpELLH@HHH)H1IILeLuHEH`HDžhH`1L(HH,MMwINHHHQINHI@I@ LHHуHH)HMIHSLHHMIJ HE1E1HE1HLeMMրHt9J K4H4H9J K4H4H91HAu1f1HAt$J HILHH4H4HHH9MLMHNHLH@JJ<H<H<H|HLL9uf.HHE1LHfffff.K FLLHLBD>B >LIHIuHLtK MMBBLLHHI9fffff.IHHIM9H>HHH@Ht HHVEH]HH;EuHH[A\A]A^A_]茤E:EIH@Q)H5GH GH`L@9?@W)EE(HEHis requiHEHX input HEEred!EAHϴEH`HMLBE1H5)]HWLˣE膣EIH}$Q)H5GH "GH`LEm?W) HDž0 ,EH0(DV) Hrst outpHHHo get fiHHHfailed tH@ut!AHEH`H LAE1H5)]H|LE H`E HALeMuiHALeMHHAL@MHH t H0#ELeMt6HEL9t!Lh@t HxELM9uH}LLeEEu`uLeMu)XH}E`tHp謡ELeMt1HEL9tNLh@t Hx臡ELM9uH}LerEE{L葡EH@HovLHEt H}5ELeMt6HEL9t!Lh@t HxELM9uH}LLeEEu`u L@Mu,dH}РE`tHp軠EL@Mt:HHL9tILh@t Hx萠ELM9uH@LHuEEL蔠EH褝E L(HH`HuJTHH`Hu9CHH@Hu:DHH`HuHH`Ht HhEH@Ht HH֟EHE fffff.UHAVSI趟EHHb]HH{L3}H^HH[A^]IHtEL贜E fff.UHAVSIVEHH]HH{L|H^HH[A^]IHELTE fff.UHAVSIEHH]HH{Ls|H^HH[A^]IH贞ELE fff.UHAVSI薞EHHB]HH{L|H^HH[A^]IHTEL蔛E fff.UHAVSI6EHH]HH{L{H^HH[A^]IHEL4E fff.UHAVSHPIHk]HHE(ĝEHþ H躝EHHCHCXHC`HCXHCHHC@HC8HC0HC(HC HCPHCpHCxHCpHChƃHǃfǃHǃHǃƃHHǃHǃHǃHǃHǃHǃHǃHǃHǃHHHǃHǃHǃǃǃHǃ H]H5FH}HHH5NGHHHH5qGHHH56GHH5IHHH +HQH5EH8HH;HHH ]HMHBHUHuHuIIFIF0INIVIF@H]HEHtHHGEH\HH;Eu LHP[A^]膛EIH]HEHtH謴HELBE f.UHAVSHPIH{\HHE(ԚEHþ HʚEHHCHCXHC`HCXHCHHC@HC8HC0HC(HC HCPHCpHCxHCpHChƃHǃfǃHǃHǃƃHHǃHǃHǃHǃHǃHǃHǃHǃHǃHHHǃHǃHǃǃǃHǃ H]H5FH}H*HH5^GHHHH5nGHHH5FGHH5IH(HA H5EHOHH;HHH ]HMH\HUHuHuIIFIF0INIVIF@H]HEHtHH^EH\HH;Eu LHP[A^]蝘EIH]HEHtHñHELYE UHAVSHPIH\HHE(EHþ HEHHCHCXHC`HCXHCHHC@HC8HC0HC(HC HCPHCpHCxHCpHChƃHǃfǃHǃHǃƃHHǃHǃHǃHǃHǃHǃHǃHǃHǃHHHǃHǃHǃǃǃHǃ H]H5ɽFH}HJHH5~GHH0HH5kGHHH5fGHH5IHHHH +HQH5/EHhHH;-HHH ]HMHQZHUHuHuIIFIF0INIVIF@H]HEHtH!HwEH\HH;Eu LHP[A^]趕EIH]HEHtHܮH2ELrE f.UHAVSHPIH\HHE(EHþ HEHHCHCXHC`HCXHCHHC@HC8HC0HC(HC HCPHCpHCxHCpHChƃHǃfǃHǃHǃƃHHǃHǃHǃHǃHǃHǃHǃHǃHǃHHHǃHǃHǃǃǃHǃ H]H5ٺFH}HZHH5GHH@HH5hGHH&H5vGH'H5-IHXHA H5FEHHH;DHHH #]HMHnHUHuHuIIFIF0INIVIF@H]HEHtH8H莒EH)\HH;Eu LHP[A^]͒EIH]HEHtHHIEL艏E UHAVSHPIH\HHE($EHþ HEHHCHCXHC`HCXHCHHC@HC8HC0HC(HC HCPHCpHCxHCpHChƃHǃfǃHǃHǃƃHHǃHǃHǃHǃHǃHǃHǃHǃHǃHHHǃHǃHǃǃǃHǃ H]-H5FH}HzHH5GHH`H8H5eGHHFH5GHGH5MIHxHH +HQH5_EH蘖HH;]HHH <]HMHqkHUHuHuIIFIF0INIVIF@H]HEHtHQH觏EHB\HH;Eu LHP[A^]EIH]HEHtH HbEL袌E f.UHAVSHPIH\HHE(4EHþ H*EHHCHCXHC`HCXHCHHC@HC8HC0HC(HC HCPHCpHCxHCpHChƃHǃfǃHǃHǃƃHHǃHǃHǃHǃHǃHǃHǃHǃHǃHHHǃHǃHǃǃǃHǃ H]=H5 FH}H芚H"H5GHHpHHH5 cGHHVH5GHWH5]IH舒HA H5vEH诓HH;tHHH S]HMHHuHUHuHuIIFIF0INIVIF@H]HEHtHhH辌EHY\HH;Eu LHP[A^]EIH]HEHtH#HyEL蹉E UHAVSHPIH\HHE(TEHþ HJEHHCHCXHC`HCXHCHHC@HC8HC0HC(HC HCPHCpHCxHCpHChƃHǃfǃHǃHǃƃHHǃHǃHǃHǃHǃHǃHǃHǃHǃHHHǃHǃHǃǃǃHǃ H]H5)FH}H誗HBH5޺GHH萗HhH5-`GHHvH5GHwH5}IH訏HH +HQH5EHȐHH;荅HHH l]HMHrHUHuHuIIFIF0INIVIF@H]HEHtH聣H׉EHr\HH;Eu LHP[A^]EIH]HEHtH<H蒉EL҆E f.UHAVSHPIH \HHE(dEHþ HZEHHCHCXHC`HCXHCHHC@HC8HC0HC(HC HCPHCpHCxHCpHChƃHǃfǃHǃHǃƃHHǃHǃHǃHǃHǃHǃHǃHǃHǃHHHǃHǃHǃǃǃHǃ H]-H59FH}H躔HRH5GHH蠔HxH5=]GHH膔H5GH臋H5IH踌HA H5EHߍHH;褂HHH ]HMH|HUHuHuIIFIF0INIVIF@H]HEHtH蘠HEH\HH;Eu LHP[A^]-EIH]HEHtHSH詆ELE UHAVSHPIH+\HHE(脆EHþ HzEHHCHCXHC`HCXHCHHC@HC8HC0HC(HC HCPHCpHCxHCpHChƃHǃfǃHǃHǃƃHHǃHǃHǃHǃHǃHǃHǃHǃHǃHHHǃHǃHǃǃǃHǃ H]荹H5YFH}HڑHrH5GHHHH5]ZGHH覑H5GH览H5IH؉HH +HQH5EHHH;HHH ]HMHzHUHuHuIIFIF0INIVIF@H]HEHtH豝HEH\HH;Eu LHP[A^]FEIH]HEHtHlHƒELE f.UHAVSHPIH;\HHE(蔃EHþ H芃EHHCHCXHC`HCXHCHHC@HC8HC0HC(HC HCPHCpHCxHCpHChƃHǃfǃHǃHǃƃHHǃHǃHǃHǃHǃHǃHǃHǃHǃHHHǃHǃHǃǃǃHǃ 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HN$E1fff.HEHHIH;ELHDHCDHEHHEIDH;ELHDHCDHEHHEIDH;ELHDHCDLmHEHLIDH;ELHDHCI]H]IM9SL9LMLLeHHAt0IM9$LHDHHHDILHHH;t\LHL,LI)LHH1fM9dMLDI LM9dLHDH HI9uHH]LHHEH HHHH H;H}*H`HL0HDH9@HxHEL+HHH9}/HHE1H 1L0HDH91fDHHEL+H1H H9uL LxHHEL<AHIVH8IF H(H0INIFIV(H8IF@H(H0IN8IF0AFHHe[HH;EuLHh[A\A]A^A_]DfUHAWAVAUATSHH%[HHEHHhHHOLGHHIHL;G uHLL;GuBW)E)E)E)E)EL)p1HPH1W)p)E)E)E)E)EH)HHDžpH HxHDHEHHHMHPHt,HEHPHDHEHLHMHHHEHHw8I@IH0HMIDPHHDaI@HALhIF0JHI\$H)H LHHINHE1E1L@LHE1HHO0L<IH`}1LH)H s1LMuT}HT0H 1fDDDDDDHHuLMt.HHffff.AAHHuLLH)LXHmLII8LhMHL`HIL9s.I0IHI<H9sH0L@LHHHH(H_IIEQAHLwH`HLd0IM)HXH<:HH<E1ff.BDB CDCLBDBL CDC IIuHt)IHXI<9HhLCCLH(H9HH0L@LHLXHD)LI)HtHAAHHuILXr>H`HL A\A\\A\\A\ HI9uMPt=Hp1HHHH;Y|!HH+qHH L9r HqIHHIL;MIMhDPIAUI@HLhIBpJHHXHL)HIRH(E1E1L@LHL8E1H-Rff.Lw0MSITpH1DDDDDDDDDDDDDDDH HuIHXt1J<!HhDDD D D0D0L`MHI9MCBII9~LM)IwH8HIH9LhM\J&HIL9sNH1ILI|H9s9L@LHffff.1IHX>LHH HYHHOHCHI\0LYI)IH`I< H(H<LE1ffff.BDB BDBLBDBL BDB IIuHt*MH`I| HhLBBLH I9L@LHH8I̐H8D)HL)HtHCBIHuHH8rBIL fffff.CBTCTBTCTBTCT BIL9uL`IPItKHp1H0ff.HHHH;Y|1HH+qHH L9rH0 HqIHHIL;H[HH;EuH[A\A]A^A_]薊DUHAVSI&DHHLH[A^]IHDL9D UHAVSIDHHLH[A^]IH蹉DLD UHAWAVSH8HIH6[HHEL=Hl\M>I~gH=]IIFW)EHEEEaxisEH}HUHMHHH]HEHtCt H{DHDEu Ht)H[HH;Eu1H8[A^A_]H}߈DHuHEIFHm[HH;EtDHEt H}諈DM>I~IFHt蒈DH҅D f.UHHH 2k\HHxH@Ht]VD]fDUHSPHHk\HH{HCHt%DHH[]DfUHAWAVAUATSHIIHH[HHE1LHLIƾLIIFIN H)HtH<H82IE I+EH)LHA +HHH;%HL藴H,HKHW) HDž0Mt$HHPHHHL`HX H HH9tH LHoL)HHLHZ^HH H4H HP(HHHHS؃H1AHH FH FHKY'H;HFH ^E1AH3(H[HH;Eu>HH[A\A]A^A_]H FHX'Hn[HH;EtDAuH)1Affff.L$LdLdLdLd Ld(Ld0Ld8HH9uHt H Hfff.L!HHuHHIHHHLeHW)PHDž`H H(H)taHIILH=Ḧ́DILXLPKDH`HH~LHDILXHP1L4gIHPHHt HXPDI~HHԩHLHIW)HDžHLYME1L@HHx(HH;u6LHmZ[ff.HHPHH;sHHHIHM9|&LHPIHM9pHHHELeHHEHHuHHHHMHhHMH`HMHUHXHPHpLxHuHEH}HEH@HPHHH@H8?HHHHt$HwDH HuUHH H>H(CDH[HH;E.gHPD HHHHHHHHHtrHHPHu\HHPHHX蛁DH Huz*HHL1HMtjAFt I~cDLPHH Hu:DHHHuHHHt H!DH Ht H( DHI~D UHAVSIDHHL.H[A^]IHɀDL ~D UHAVSI趀DHHLH[A^]IH艀DL}D UHAWAVSH8HIH[HHEL=c\M>I~]Hm]IIFW)EHEEEaxisEH}HUHMH~H]HEHtCt H{DHDEu Ht)Hn[HH;Eu1H8[A^A_]H}DHuHEIFH=[HH;EtDHEt H}{DM>I~IFHtbDH|D f.UHHH b\HHxH@Ht]&D]fDUHSPHHa\HH{HCHt~DHH[]~DfUHAWAVAUATSHIIHH\[HHE1LHLIƾLIIFIN H)HtH:H80IE I+EH'LHHHH;#HLHcHKHW) HDž0Mt$HHPHHHL`HX H HH9tH LHAL)HHLH,UHH H4H HP{HHHHS؃H1AHH vFH FHP'H;HFH UE1AH*(H~[HH;Eu>HH[A\A]A^A_]H FHO'H@[HH;Et|DAwH)1Affffff.L$LdLdLdLd Ld(Ld0Ld8HH9uHt H Hfff.L!HHuHHIHHHL5HW)PHDž`H H(H)taHIILH=H{DILXLPKDH`HH~LH|DILXHP1L^IHPHHt HX {DI~HH褠HLHIW)HDžHLwPME1L@HHx(HH;u6LH=Q[ff.HHPHH;sHHHIHM9|&LHPIHM9pHH]HELeHHEHHuHHHHMHhHMH`HMHUHXHPHpLxHuHEH}HEH@HPHHH@H8xHHHHt$HGyDH HuSHH H<H(yDH[HH;E,eHPTvD HHHHHHHHHtrHHPHu\HHPHHXkxDH Huz*HHL1HMtjAFt I~3xDLPHH Hu:DHHHuHHHt HwDH Ht H(wDHuD UHAVSIwDHHL.H[A^]IHwDLtD UHAVSHPIHHE(twDHþ HjwDHHCHCXHC`HCXHCHHC@HC8HC0HC(HC HCPHCpHCxHCpHChƃHǃfǃHǃHǃƃHHǃHǃHǃHǃHǃHǃHǃHǃHǃHHHǃHǃHǃǃǃHǃ H]=H5DH}HʂH5FHyH5}DHzHAH5DH#|HH;pHHH ǚ\HMHHUHuHuIIFIF0INIVIF@H]HEHtH܎H2uDH[HH;Eu LHP[A^]quDIH]HEHtH藎HtDL-rD DUHAWAVSHxIHi[HHE(tDHþ HtDHHCHCXHC`HCXHCHHC@HC8HC0HC(HC HCPHCpHCxHCpHChƃHǃfǃHǃHǃƃHHǃHǃHǃHǃHǃHǃHǃHǃHǃHHHǃHǃHǃǃǃHǃ H]苢I胨HW)EHE!sDHEHHHML8HXHMHI@HW)pHErDHpHHHML8HXHxH5DH}HUHpv|H5¶FHvH5HHwHH +HQH5DHxHH;mHHH |\HMHaHUHuHuIIFIF0INIVIF@HpHt HxqDH}Ht H}qDH]HEHtHgHqDHX[HH;EuLHx[A^A_]qDIH}Ht0^IH]HEHt+bIHpHu$H}Hu0H]HEHu9LnD Hx7qDH}HtH}%qDH]HEHtH變HqDLDnD fff.UHAWAVAUATSHH@Hn[HHEп(pDHþ HpDHHCHCXHC`HCXHCHHC@HC8HC0HC(HC HCPHCpHCxHCpHChƃHǃfǃHǃHǃƃHHǃHǃHǃHǃHǃHǃHǃHǃHǃHHHǃHǃHǃǃǃHǃ H]萞HH脤HP踝HX謣H$IܥI蔠ILIW)EHE@nDHEHH@HMHHHHPHPHXHPHXLp Lx(L`0Lh8HM$HHHP̝HXIxI0IH蠠IW)`HDžp@8nDH`HH@HpHHHHPHPHXHPL`Lp Lx(HX0Lh8HhH5zDH}HUH`wH5FHqH5HHrHH HQH5̱DHtHH;hHHH \HMHHUHuHuH@HHCHC0HKHSHC@H`Ht HhmDH}Ht H}mDLuHEMtL荆LlDH~[HH;EuHHĘ[A\A]A^A_]mDIH`Hu$H}Hu>H]HEHu]LiD HhzlDH}Ht IH}HtH}ZlDH]HEHtIH]HEHtHͅH#lDLciD ff.UHAVSHIH[HHE(kDHþ HkDHHCHCXHC`HCXHCHHC@HC8HC0HC(HC HCPHCpHCxHCpHChƃHǃfǃHǃHǃƃHHǃHǃHǃHǃHǃHǃHǃHǃHǃHHHǃHǃHǃǃǃHǃ H]H}Hp?HpHuOH5_wDH}HUHptH5`FH%nH5+HHVoHA H5DDH}pHH;BeHHH !\HMH&HUHuHuIIFIF0INIVIF@HpHt HxiDH}Ht H}iDH]HEHtH HbiDH[HH;EuLHĀ[A^]iDIH}Ht0^IH]HEHt+bIHpHu$H}Hu0H]HEHu9L1fD HxhDH}HtH}hDH]HEHtHRHhDLeD UHAWAVSH8IH)[HHEt]HHRH)HHL11DHHH<8uHH IHHH9rQLHrL)tEHIL11DHHI<uHH I<HLH9rIHW[HH;EudLH8[A^A_]ÉEHFHELuHuHUL LL97'EtH}XgDH[HH;EtgDHuFHELuHuLJLL6'HEu HEt H}fDH4dD fff.UHAWAVAUATSHIIHpHX[HHE1LǩII_0HHHPHffHDžHDžID$HxA|$LLMg M+gLSIIG0xIGIO H)HHtH_H8UL葋IILIIM9HHLl;Mt^1Lfffff.HH;t IHHHHIL9rLL<HIL9rHHII)MIffPHDž`MHI9HLeDILPO4L`LLdDLXHLH9utfAnD$Hf~Hp"H9hH9cZfH~fnII!H>E1LH9tB1fff.H HxHL9r!ffff.I HHL9r̾LLHHHC0H;HHHHHKPHHHeH8L AAHpHHHLE11E1HHpHHuMHE1Hfnf~AAID$HI0HpHHtHHH1LIffEHEI} I+}LXH@LIIHI9bDILeLeHEHKHEIuMu I)M LLcDMMLmM)LLHHHHRH)HH9,ffEIHELO|HHtcH;LHLDHTOLH<H 1H<H<H<I<M<ItHHuE1H_H{FHHPHHH]FH}H0'HEHpHHEPH`ϿLHMtH}nLeH]KDI9$ LHH!HFHLHf ILH9sHtHLI9H H?H!HzHHNH a 1H LH AAIHHI!HpHHH1LHffEHEHy HhH+yLXH@LIIHI9_DILeLeHEHKHEHhHpLp I)MLL`DMMLmM)LLHHHHRH)HH9%ffEIHELO|HHtYH;LHLDHTOLH<H 1H<u2H<u+H<u$I<uM<ItHHuE1LHMtH} LeH]KDI9LHH!HFHLHILH9sHtHLI9H?H!HzHHNH 1H;nLHHpHHH1LƠILffEHEH{ H+{LIIHI9e]DILmLmHEHKDHEHsLs I)MLL^DMMLeM)}LLHHHHRH)HH9ffEIHELO|HHPtdHH:LHLDHTOLH<H 1ff.H<u2H<u+H<u$I<uM<ItHHuE1LHMtH}ͥLmH]KDI9 LHH!HFHLH ILH9sHtHLI9 H?H!HzHHNH  1HL  -HEHE1E1M)D菔DIH:B(H5FH kFHPLffEHE 3DHEfoUfEHmensionsHHH no dimeHHHnsor hasHHHInput teH@AHFHPHMLE1H5,\HLDHEHE1E1M)_蔓DIH?A(H5FH FHPLffEHE 8DHEfoUfEHmensionsHHH no dimeHHHnsor hasHHHInput teH@AHFHPHMLE1H5+\HLDHEHE1E1M)虒DIHD@(H5FH 9FHPLffEHE =DHEfoUfEHmensionsHHH no dimeHHHnsor hasHHHInput teH@AHFHPHML -E1H5+\HLDMM)aMM)fMM)t1IKDI9 1IKDI91IKDI9HyH)1fff.AALLAD AL0D L0AD@ALPD@LPAoD`AoLpD`LpHHuHt8H4Hfff.AoD4Ao 4D3 3H HuH9H IO MI)DHtHH2H1HHHuI8rc1DH<2H<1H|2H|1H|2H|1H|2H|1H|2 H|1 H|2(H|1(H|20H|10H|28HD28HD18H@L9uN<LMLH)HHILH~HDHHIE1HPffpHEHHpL`HL8IIHI9˼L$?L7DILpKH]LL DHxffPHDž`LDHPJH`HHHLӎDHXML`"fPHDž`1HE1E1LpHL I3 -HH@HHLGLLIrHILI9sIDLLI9PH?L!HJHHpH Y1HLpHyH)1@AALLAD AL0D L0AD@ALPD@LPAoD`AoLpD`LpHHuHt8H4Hfff.AoD4Ao 4D3 3H HuH9H IO MI)DHtHH2H1HHHuI8rc1DH<2H<1H|2H|1H|2H|1H|2H|1H|2 H|1 H|2(H|1(H|20H|10H|28HD28HD18H@L9uN<H}H`H)HHILH~ HDHH1HhHPffpHEHHpHIIHI9L$?LDILpKH]LLDHxffPHDž`LˋDHPJH`HHHL誋DHXMHp"fPHDž`1HE1E1IHL IBHH@HHLGLLI?HILI9sIDLLI9?H?L!HJHHpH >1HE?r?HyH)1fDADALLAD AL0D L0AD@ALPD@LPAoD`AoLpD`LpHHuHt8H4Hff.AoD5AoL5D3 3H HuH9H ITOLMI)DHtHH2H1HHHuI8rc1DH<2H<1H|2H|1H|2H|1H|2H|1H|2 H|1 H|2(H|1(H|20H|10H|28HD28HD18H@L9uN<H}H@H)HHILH~ HDHH1H`HhffpHEHHpHIIHI9L,?LDILpKH]LL׈DHxffPHDž`L諈DHPJH`HHHL芈DHXM"fPHDž`1HE1E1LpHL(IzHH@HHLGLLIRxHILI9sIDLLI90xH?L!HJHHpH ,w1HLpwwHNH)1fAALAALAD AL0AD AL0AD@ALPAD@ALPAoD`AoLpAD`ALpHHuHLpt;HHffff.AoDAo ADA H HuI9I4ILpK\H)ӉHt#Hffff.H +HEHE1E1M)D[DIH* (H5FH yFHPLffEHE 3[DHEfoUfEHmensionsHHH no dimeHHHnsor hasHHHInput teH@AHԣFHPHMLE1H5[HLZDHEHE1E1M)_ZDIH/(H5FH FHPLffEHE 8ZDHEfoUfEHmensionsHHH no dimeHHHnsor hasHHHInput teH@AH٢FHPHMLE1H5LYDHEHE1E1M)YDIH4(H5FH GFHPLffEHE =YDHEfoUfEHmensionsHHH no dimeHHHnsor hasHHHInput teH@AHޡFHPHMLE1H5 [HLXDMM)aMM)fMM)t1IKDI9 1IKDI91IKDI9HyH)1fff.AALLAD AL0D L0AD@ALPD@LPAoD`AoLpD`LpHHuHt8H4Hfff.AoD4Ao 4D3 3H HuH9H IO MI)DHtHH2H1HHHuI8rc1DH<2H<1H|2H|1H|2H|1H|2H|1H|2 H|1 H|2(H|1(H|20H|10H|28HD28HD18H@L9uN<LMLH)HHILH~HDHHIE1HPffpHEHHpL`HL8IIHI9˼L$?L7VDILpKH]LL VDHxffPHDž`LUDHPJH`HHHLUDHXML`"fPHDž`1HE1E1LpHL I3 +HH@HHLGLLIrHILI9sIDLLI9PH?L!HJHHpH Y1HLpHyH)1@AALLAD AL0D L0AD@ALPD@LPAoD`AoLpD`LpHHuHt8H4Hfff.AoD4Ao 4D3 3H HuH9H IO MI)DHtHH2H1HHHuI8rc1DH<2H<1H|2H|1H|2H|1H|2H|1H|2 H|1 H|2(H|1(H|20H|10H|28HD28HD18H@L9uN<H}H`H)HHILH~ HDHH1HhHPffpHEHHpHIIHI9L$?LSDILpKH]LLRDHxffPHDž`LRDHPJH`HHHLRDHXMHp"fPHDž`1HE1E1IHL IBHH@HHLGLLI?HILI9sIDLLI9?H?L!HJHHpH >1HE?r?HyH)1fDADALLAD AL0D L0AD@ALPD@LPAoD`AoLpD`LpHHuHt8H4Hff.AoD5AoL5D3 3H HuH9H ITOLMI)DHtHH2H1HHHuI8rc1DH<2H<1H|2H|1H|2H|1H|2H|1H|2 H|1 H|2(H|1(H|20H|10H|28HD28HD18H@L9uN<H}H@H)HHILH~ HDHH1H`HhffpHEHHpHIIHI9L,?LODILpKH]LLODHxffPHDž`LODHPJH`HHHLODHXM"fPHDž`1HE1E1LpHL(IzHH@HHLGLLIRxHILI9sIDLLI90xH?L!HJHHpH ,w1HLpwwHNH)1fAALAALAD AL0AD AL0AD@ALPAD@ALPAoD`AoLpAD`ALpHHuHLpt;HHffff.AoDAo ADA H HuI9I4ILpK\H)ӉHt#Hffff.H HHHHuH8rcK1ɐH HH\ H\H\ H\H\ H\H\ @@ -3848,16 +3814,16 @@ Ht Ht Ht Ht (Ht (Ht 0Ht 0Ht 8Ht 8Ht -@H@H9uI?M!IBHHWH s1HKtpKLpHBH)1DLDLDLDLDLDLoDo D HHuHt>J/IDLILH1foD0o 0D1 1H HuM9L`LpKDIKDK)HIIK 9HIHL0MLIL$IIMBHHLI+HIDH9sHLHLI9 H?L!HPHHyH s$1HJKLpgH_H)1fDAALLAD AL0D L0AD@ALPD@LPAoD`AoLpD`LpHHuHt8H Hfff.AoDAo D H HuI9H<IKTH)‰HtHfDHHHHHuH8rcK 1ҐHHH\H\H\H\H\H\H\ H\ H\(H\(H\0H\0H\8H\8H\@H@H9uOJ<Ir$KDIDH9MJDI9LL`K /ITH)‰Ht"Hfff.H0H7HHHuH8rK 1ffff.H4H4HtHtHtHtHtHtHt Ht Ht(Ht(Ht0Ht0Ht8Ht8Ht@H@H9uI?M!IJHHBH s1HHJtpK\pHHH)1ҐDӐLӠD֐L֠DӰLDְLDLDLoDo D HHuHt>J *ILLHHTH1foD1o 1D2 2H HuM9L`3KDIHHJDHIIHHff0HDž@MLPtdHI9nLDHH8H0JH@H8L)HH~HLILDLH8ffHDž fHDžHLHLMHPE1LPLpffffff.J 1H)HPHH; sHHHHLHMJJJHPHH;sHHHf.HLHpJ J J J H0J IIL;p<H@HHLHHLMIAMGIz1JKHIHHIHL9rIHHH H XHfHKfHDžLuH]L)Lt[IIHI9*H7}DILLKHH~LLH~DILHLHHffH0H8HHHT$HD$H0H8HT$H$HPHHhEff0HDž@HHLuL)t[IIHI9PH3|DIL8L0KH@H~LLH~}DIL8H01LoZHpL L`PHH01 LHH`bHpHE11Mf.H4H4IHH9r/H@IIGI4OI|IIN4H<L$I9I9AI9I9AI9I9@M9H9A1D.D .@ .D H@LHIZHyIQHoCo BoTfBofoOoBodffBo ffoBfofBH H H HuI9H@QwfPHDž`HHLuL)t[IIHI94HyDILXLPKH`H~LLH8{DILXHHPHxHLHL,HFH FH1AC'(HPH}鄜E1MLƅLHDžHDžHDžLLM)LHHHEHt7MHHUHHH`MML11H)HHMLpt#HI>t IHu HtƅHx:"'HHHHHH0HGHHHPHOHHH H HrH)HHHHH)HhHH)HxLLPKHHHhHȀXHxt6HtPL`HL4@HHL{uDIHIuHtH`HHxxDH`LxLHHhHH)HHLHHH`HtTHpHffff.H\HH\H;\u%HDHhH\HH`HuHJ4HpN|N,IM)HHL4L`ILHLL@u4H +@H@H9uI?M!IBHHWH s1HKtpKLpHBH)1DLDLDLDLDLDLoDo D HHuHt>J/IDLILH1foD0o 0D1 1H HuM9L`LpKDIKDK)HIIK 9HIHL0MLIL$IIMBHHLI+HIDH9sHLHLI9 H?L!HPHHyH s$1HJKLpgH_H)1fDAALLAD AL0D L0AD@ALPD@LPAoD`AoLpD`LpHHuHt8H Hfff.AoDAo D H HuI9H<IKTH)‰HtHfDHHHHHuH8rcK 1ҐHHH\H\H\H\H\H\H\ H\ H\(H\(H\0H\0H\8H\8H\@H@H9uOJ<Ir$KDIDH9MJDI9LL`K /ITH)‰Ht"Hfff.H0H7HHHuH8rK 1ffff.H4H4HtHtHtHtHtHtHt Ht Ht(Ht(Ht0Ht0Ht8Ht8Ht@H@H9uI?M!IJHHBH s1HHJtpK\pHHH)1ҐDӐLӠD֐L֠DӰLDְLDLDLoDo D HHuHt>J *ILLHHTH1foD1o 1D2 2H HuM9L`3KDIHHJDHIIHHff0HDž@MLPtdHI9nLFDHH8H0JH@H8L)HH~HLILGDLH8ffHDž fHDžHLHLMHPE1LPLpffffff.J 1H)HPHH; sHHHHLHMJJJHPHH;sHHHf.HLHpJ J J J H0J IIL;p<H@HHLHHLMIAMGIz1JKHIHHIHL9rI|HHH H XHfHKfHDžLuH]L)Lt[IIHI9*H7DDILLKHH~LLHEDILHLHHffH0H8HHHT$HD$H0H8HT$H$HPHHhEff0HDž@HHLuL)t[IIHI9PH3CDIL8L0KH@H~LLH~DDIL8H01L%HpL L`PHH01 LHH`bHpHE11Mf.H4H4IHH9r/H@IIGI4OI|IIN4H<L$I9I9AI9I9AI9I9@M9H9A1D.D .@ .D H@LHIZHyIQHoCo BoTfBofoOoBodffBo ffoBfofBH H H HuI9H@QwfPHDž`HHLuL)t[IIHI94H@DILXLPKH`H~LLH8BDILXHHPHxHLHL,HFH FH1A3'HPH}鄜E1MLƅLHDžHDžHDžLLM)LHHHEHt7MHHUHHH`MML11H)HHMLpt#HI>t IHu HtƅHx:"'HHHHHH0HGHHHPHOHHH H HrH)HHHHH)HhHH)HxLLPKHHHhHȀXHxt6HtPL`HL4@HHL{<DIHIuHtH`HHx?DH`LxLHHhHH)HHLHHH`HtTHpHffff.H\HH\H;\u%HDHhH\HH`HuHJ4HpN|N,IM)HHL4L`ILHLL@u4H IvII HNIHHNNHHHXMnHpHXL|MRHPIHI)IH)HKHHH0HHHhI\pIE1L0KHhGIr4LII I H;HIH9E1LHE)LM)ItIDH HHHIIuIL`L>LL)1f.H<H<H|H|H|H|H|H|H| H| H|(H|(H|0H|0H|8H|8HH9uH s1Hu|H1DÐLàAALDðLAD AL0DLAD@ALPoDo AD`ALpHHuHt1HDàHfDo@oBD(B (H HuL;0HIIIM9MHHXLMHHL4H`HPL$H0IHHHhHLHxIH HHE1HE1H0HHHH`VH`HrAHIHPH HHH;LH HxL91HLAA)LI)It$Iff.HH -HHHIuI^H`H)1@HHH\H\H\H\H\H\H\ H\ H\(H\(H\0H\0H\8H\8HH9uH s1Hx H1Hxffffff.ADҐALҠLADҰALD L0ADALD@LPAoDAo D`LpHHu t4HH HoD9o 9B9BL9H HuH;0HHIIM9I IKHNITM8N IIIMH?I!fHnfpDI@HHwHs1HHPL)IHFH)1 0@P`pDDDDDDDDH HuHt$HPL)IDH@H HuM9HtOI IL9uHNI<IuHMH@HHHHH&IH?I!fHnfpDIPHHwHLLPLxs1HKIHVH)1 0@P`pDDDDDDDDH HuHt!LIITHBH HuL9tDHJ4H@HPHHHHxH)HHHHHuHHpHH[HH@LHHHHHHHLHfHHHHH;(LPLHHL LHHHL$HpHXH HHLIH8MMHXHHHHHLH8H MI)HH)HJ H)IHxLHH)IHHHLHIIHHQMAHIHJ<HBH)H(H@HHh1 LO\HTff.Ir:LHHH HxHH;HL9E1MLDD)LL)HtHfL2M3IHIHuHpLL)1HIHDIDHDIDHDIDHD ID HD(ID(HD0ID0HD8ID8HH9u@H s1H@H(1AALADALAD AL0AD AL0AD@ALPAD@ALPAoD`AoLpAD`ALpHHuH@t=HHhfffff.AoAoLADALH HuL;ffffff.IHL9M[HMLHI<MIIAHxHPMqJ4HNHrH)HHHHE1KMH;Ir+LIHH H9LHH9E1LHEE)LL)ItIܐHH HHIIuHPLL)1HHHTHTHTHTHTHTHT HT HT(HT(HT0HT0HT8HT8HH9u@Hx s1HH1LAALD L0AD AL0D@LPAD@ALPoD`oLpAD`ALpHHuHt3HHooLAALH HuM95fDMIL;-HILMLPL8HXHHAHHHH齄HH)HHLp閄H ?HHHHHHHHHHGHHHpHWH0HHHHHHHVH)H`HhHHxHPH)HXLLPO<HLhL耽Xt2HtDL`HL4@LHLcDIHIuMtH`LLgDH`LHHhHH)HHLHHH`HtQHpHf.H\HH\H;\u%HDHhH\HH`HuK/HHpHpH\HLH)HHLM H`HLPHLHLHK؃HrrHHII HH)JJIYH^IYH^IYH^IYH^ IYH^(IYH^0IYH^8H@IH@HHuJ4N HtHI HHIHuM HHrHHCAAHjIMLHHHxHLiHpHxLDMMMHI)H`N4MI)I HIE1HHI HYH`HrDILHIII\IH9HI LIH91HLL`A)L0I)ItIHHHHHIuILNH`H)1ffff.H<H<H|H|H|H|H|H|H| H| H|(H|(H|0H|0H|8H|8HH9uH s1Hhu|H`1AALLAD AL0D L0AD@ALPD@LPAoD`AoLpD`LpHHuHht3HHxAoAoLLH HuHH9`HILM9L`MGHHxL,M,HPIHHH+PHxIM)HXIL<HIHILIHHE1HH IHjHL IrQLILHI<4I<HPH -IH9HxI4HI H91HLA)L0I)It(Iffffff.H3H1HHHIuIL`L@LH)1f.HHHTHTHTHTHTHTHT HT HT(HT(HT0HT0HT8HT8HH9uH s1u|H`1ɐADϐALϠLADϰALD L0ADALD@LPAoDAo D`LpHHut4HHxAo AoL LH HuL;HK IHIIM9HPI|LH)HJ/K/HFHCHFHCHFHCHFHC HFHC(HFHC0HFHC8H@HI@HHuMLHMtIHIIHIuHHpHHUHHLHHHHHHH LHfffff.HHHHH;LPLHHH<HHHHLHpH(H HHxLHHHHRMIH(H H HHHL,HMtHI)HHHJ4H)HHHH)H)HH@H)HHJH)HHHHHhHHHXHQH<HHHZH)HH8HHL`E1LhKTO yfff.HHrWHILHHH HHHHHH9HH@H9E1LMHD)MM)Ht#Hf.IHHIIHuIpHL)1@IHIDHDIDHDIDHDID HD ID(HD(ID0HD0ID8HD8HH9u@HX s1H8H1AALADALAD AL0AD AL0AD@ALPAD@ALPAoD`AoLpAD`ALpHHuH8t=HHfffff.AoAoLADALH HuHhH9IIIM9LMHxO$LILHH@ID$HhHPIL$HN4HJtpLIHzH)HHXHH8N<IE1HH@II<H_fNIrKLILHHL)HH<HH9H+HLHH91LLA)LI)It&Iffff.HHHHHIuILILH)1ҐH H HLHLHLHLHLHLHL HL HL(HL(HL0HL0HL8HL8HH9u@Hh s1HXH1DƐLƠAALDưLAD AL0DLAD@ALPoDo AD`ALpHHuHXt5HH8AoAoLAALH HuL;@LKILML;xHxILMLPLH(HHAHHHH HH)HH ssfInfpDfLLPO,HLhLXt2HtDL`HL4@LHLSDIHIuMtH`LL WDH`LHHhHH)HHLHHH`HtMHpHfDH\HH\H;\u%HDHhH\HH`HuHpHpLtHLJLHH)IfoHt3ILPuNLL)N$8IM,$Ml$HHHQLPIN$8I\ML<N IIIs HMH?I!IPHH_Hs1HLL)HHHSH)1 0@P`pDDDDDDDDH HuHt'LL)HHTHBH HuM9HtJ L)HH9uN$8IpIu M,$PMGN IILIMH?I!IHHH^Hs1HIHSH)1 0@P`pDDDDDDDDH HuHt(LHH ILHAH HuM9Ht,K MHJI)IHL)HIuHHqHH:OLLHHxHHMLfff.IHII;IHxHHL$HHII L4LHHH)HpHLHtHu<L)LIuM*MjuL)LiLItIM*RH)IMLIIIHILPLH?H!HHWIIAyHLsxE1HL4cMN IILILH?H!HJHH_Ht1H3JHL)HML_M)E1ffff.CC C0C@CPC`CpCDʀCDʐCDʠCDʰCDCDCDCDCI InHLt4KIIM)LITHBH HuHI9LPLHLt&HH LL*HH9u@LIHKH)1@AADAD AD0AD@ADPAD`ADpAAAAAAAAH HkHt(ILHfffff.AH HuI9HLt+I KHLDL)HH9u@OIHFHHHHL)HHjHDžHP1Hf+;oL0LxPHPHHoK4>HHHHHOLLIoMIfInfpDIPHHxHn1H5oNoƅHDžHH'j.jH@8J<KBHNH)1ېAALAALAD AL0AD AL0AD@ALPAD@ALPAoD`AoLpAD`ALpHHuHt2HH@AoDAo ADA H HuI9I4IHpI\H)ӉHt#Hffff.H +HHHIuI^H`H)1@HHH\H\H\H\H\H\H\ H\ H\(H\(H\0H\0H\8H\8HH9uH s1Hx H1Hxffffff.ADҐALҠLADҰALD L0ADALD@LPAoDAo D`LpHHu t4HH HoD9o 9B9BL9H HuH;0HHIIM9I IKHNITM8N IIIMH?I!fHnfpDI@HHwHs1HHPL)IHFH)1 0@P`pDDDDDDDDH HuHt$HPL)IDH@H HuM9HtOI IL9uHNI<IuHMH@HHHHH&IH?I!fHnfpDIPHHwHLLPLxs1HKIHVH)1 0@P`pDDDDDDDDH HuHt!LIITHBH HuL9tDHJ4H@HPHHHHxH)HHHHHuHHpHH[HH@LHHHHHHHLHfHHHHH;(LPLHHL LHHHL$HpHXH HHLIH8MMHXHHHHHLH8H MI)HH)HJ H)IHxLHH)IHHHLHIIHHQMAHIHJ<HBH)H(H@HHh1 LO\HTff.Ir:LHHH HxHH;HL9E1MLDD)LL)HtHfL2M3IHIHuHpLL)1HIHDIDHDIDHDIDHD ID HD(ID(HD0ID0HD8ID8HH9u@H s1H@H(1AALADALAD AL0AD AL0AD@ALPAD@ALPAoD`AoLpAD`ALpHHuH@t=HHhfffff.AoAoLADALH HuL;ffffff.IHL9M[HMLHI<MIIAHxHPMqJ4HNHrH)HHHHE1KMH;Ir+LIHH H9LHH9E1LHEE)LL)ItIܐHH HHIIuHPLL)1HHHTHTHTHTHTHTHT HT HT(HT(HT0HT0HT8HT8HH9u@Hx s1HH1LAALD L0AD AL0D@LPAD@ALPoD`oLpAD`ALpHHuHt3HHooLAALH HuM95fDMIL;-HILMLPL8HXHHAHHHH齄HH)HHLp閄H ?HHHHHHHHHHGHHHpHWH0HHHHHHHVH)H`HhHHxHPH)HXLLPO<HLhL耽Xt2HtDL`HL4@LHL*DIHIuMtH`LL.DH`LHHhHH)HHLHHH`HtQHpHf.H\HH\H;\u%HDHhH\HH`HuK/HHpHpH\HLH)HHLM H`HLPHLHLHK؃HrrHHII HH)JJIYH^IYH^IYH^IYH^ IYH^(IYH^0IYH^8H@IH@HHuJ4N HtHI HHIHuM HHrHHCAAHjIMLHHHxHLiHpHxLDMMMHI)H`N4MI)I HIE1HHI HYH`HrDILHIII\IH9HI LIH91HLL`A)L0I)ItIHHHHHIuILNH`H)1ffff.H<H<H|H|H|H|H|H|H| H| H|(H|(H|0H|0H|8H|8HH9uH s1Hhu|H`1AALLAD AL0D L0AD@ALPD@LPAoD`AoLpD`LpHHuHht3HHxAoAoLLH HuHH9`HILM9L`MGHHxL,M,HPIHHH+PHxIM)HXIL<HIHILIHHE1HH IHjHL IrQLILHI<4I<HPH +IH9HxI4HI H91HLA)L0I)It(Iffffff.H3H1HHHIuIL`L@LH)1f.HHHTHTHTHTHTHTHT HT HT(HT(HT0HT0HT8HT8HH9uH s1u|H`1ɐADϐALϠLADϰALD L0ADALD@LPAoDAo D`LpHHut4HHxAo AoL LH HuL;HK IHIIM9HPI|LH)HJ/K/HFHCHFHCHFHCHFHC HFHC(HFHC0HFHC8H@HI@HHuMLHMtIHIIHIuHHpHHUHHLHHHHHHH LHfffff.HHHHH;LPLHHH<HHHHLHpH(H HHxLHHHHRMIH(H H HHHL,HMtHI)HHHJ4H)HHHH)H)HH@H)HHJH)HHHHHhHHHXHQH<HHHZH)HH8HHL`E1LhKTO yfff.HHrWHILHHH HHHHHH9HH@H9E1LMHD)MM)Ht#Hf.IHHIIHuIpHL)1@IHIDHDIDHDIDHDID HD ID(HD(ID0HD0ID8HD8HH9u@HX s1H8H1AALADALAD AL0AD AL0AD@ALPAD@ALPAoD`AoLpAD`ALpHHuH8t=HHfffff.AoAoLADALH HuHhH9IIIM9LMHxO$LILHH@ID$HhHPIL$HN4HJtpLIHzH)HHXHH8N<IE1HH@II<H_fNIrKLILHHL)HH<HH9H+HLHH91LLA)LI)It&Iffff.HHHHHIuILILH)1ҐH H HLHLHLHLHLHLHL HL HL(HL(HL0HL0HL8HL8HH9u@Hh s1HXH1DƐLƠAALDưLAD AL0DLAD@ALPoDo AD`ALpHHuHXt5HH8AoAoLAALH HuL;@LKILML;xHxILMLPLH(HHAHHHH HH)HH ssfInfpDfLLPO,HLhLXt2HtDL`HL4@LHLDIHIuMtH`LL DH`LHHhHH)HHLHHH`HtMHpHfDH\HH\H;\u%HDHhH\HH`HuHpHpLtHLJLHH)IfoHt3ILPuNLL)N$8IM,$Ml$HHHQLPIN$8I\ML<N IIIs HMH?I!IPHH_Hs1HLL)HHHSH)1 0@P`pDDDDDDDDH HuHt'LL)HHTHBH HuM9HtJ L)HH9uN$8IpIu M,$PMGN IILIMH?I!IHHH^Hs1HIHSH)1 0@P`pDDDDDDDDH HuHt(LHH ILHAH HuM9Ht,K MHJI)IHL)HIuHHqHH:OLLHHxHHMLfff.IHII;IHxHHL$HHII L4LHHH)HpHLHtHu<L)LIuM*MjuL)LiLItIM*RH)IMLIIIHILPLH?H!HHWIIAyHLsxE1HL4cMN IILILH?H!HJHH_Ht1H3JHL)HML_M)E1ffff.CC C0C@CPC`CpCDʀCDʐCDʠCDʰCDCDCDCDCI InHLt4KIIM)LITHBH HuHI9LPLHLt&HH LL*HH9u@LIHKH)1@AADAD AD0AD@ADPAD`ADpAAAAAAAAH HkHt(ILHfffff.AH HuI9HLt+I KHLDL)HH9u@OIHFHHHHL)HHjHDžHP1H;oL0LxPHP芖HHoK4>HHHHHOLLIoMIfInfpDIPHHxHn1H5oNoƅHDžHH'j.jH@8J<KBHNH)1ېAALAALAD AL0AD AL0AD@ALPAD@ALPAoD`AoLpAD`ALpHHuHt2HH@AoDAo ADA H HuI9I4IHpI\H)ӉHt#Hffff.H HHHHuH8rcK1ɐH HH\ H\H\ H\H\ H\H\ @@ -3874,20 +3840,20 @@ Ht Ht (Ht (Ht 0Ht 0Ht 8Ht 8Ht @H@H9uI?M!IBHHWH s1HHpItpKLpHBH)1DLDLDLDLDLDLoDo D HHuHt>J/IDHpILH1DoD0o 0D1 1H HuM9LpKDHhHKDK)HIHK 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-LH;xHLI91LLLI)ht+Hffffff.DDHHHHuIL_HhH)1fffff.DDDDDDDDDDDDDDHH9uH`H s10H1fffff.DLA AL DLAD AL 0DLAD @AL PoDo AD `AL pHHu0t4HHDoDo BD)B )H HuHH9hHhIIIM9aGMuUHICMtEHx@HHtHuHxHxAHxCHHHHH~LxLLffffff.HHHHHH;3L(HHLLHHHpH<HpHHHHIH8MLHHHHHM< ML+8H)HH)IHLHH)IHLHLHI@H`HpEAML pHNH)HHPHHXLHHI@HxH@IHE1,L@K43HLxM)Mu^|fI r5LIHH LH;HLI9E1LLLxM)Mt HfDHHIHuIL\LL)1@TTTTTTTTTTTTTTHH9ufff.H``s1HPH1AD AL A AL AD AL AD AL 0AD AL AD @AL PAoD Ao AD `AL pHHuHPt=HHXffffff.AoDAo AD A H HuL;@MII9MH}LHMLHI@HHXMHEAHI43H@I|pHSH)H`HHHLHHxE1)LK.H@MM)MuPmf.I r*LIHH H9LHI9E1LLMM)MtHxDHHIHuISLL)1ff.12\1\2\1\2\1\2\1\2\1\2\1\2\1\2HH9ufff.H`s1HH`1DLAALDLAD AL0DLAD@ALPoDo AD`ALpHHuHt5HHAoD Ao ADA H HuL;MIL;-HILIL(L8HHHHHHH)HHLpL?H HHHHHHHHH0HAHHHpHyHσHH HNH)HHHHHHHpHxH)HLL(O, HHhHȀXt5IHtGH`HL4@MLHCHIIuIHtH`LL CH`MLHHhHH)HHLHHH`HtIHpHfH\HH\H;\u%HDHhH\HH`HuKD5HHpHpLLMM)KT HLHhHLLMHH(IAEAHrtLHHJ<LL)91ZAZZAZZAZZAZZAZZAZZAZIHHHHuHHIHMtIAIHIuMHHrHHCAAH8IMHHHL(iIN|MXLMHI)N MI)MIE1(H0I4H<LI)HulH rEHILHI<0LLILH9LLLLH91LHLI)HtHfHHHHuIAHhH)1  LLLLLLLLLLLLLLHH9uH`s1HH1@LAALD L0AD AL0D@LPAD@ALPoD`oLpAD`ALpHHuHt3HHoDo ADA H HuH;0 +@H@H9uI?M!IBHHWH s1HKtpKLpHBH)1DLDLDLDLDLDLoDo D HHuHt>J'IDLILH1foD0o 0D1 1H HuM9LpKDHhHKDK!HIDHK 9HIHL0MHL@HOIIMBLLLI6HIDI9sIL LLI9H?L!HPHHqH s$1HJKLpiH^H)1ffffff.AALAALAD AL0AD AL0AD@ALPAD@ALPAoD`AoLpAD`ALpHHuHt2H H@AoDAo AD A H HuI9I4IKTH)‰HtH@HHHHHuH8rcK 1ҐHHH\H\H\H\H\H\H\ H\ H\(H\(H\0H\0H\8H\8H\@H@H9uLOJIr*KIDH9MHJDI9LK 'ITH)‰Ht Hf.H0H3HHHuH8K 1ffff.H4H4HtHtHtHtHtHtHt Ht Ht(Ht(Ht0Ht0Ht8Ht8Ht@H@H9uI?M!IJHHDjAH s1MHJtpKDpIMH)1ffffff.DАLРD֐L֠DаLDְLDLDLoDo D HHuMt>J "ILLHHTI1foD1o 1D2 2H IuM9L@&KDHhHHJDHIHHHff0HDž@HL`tTHI9\6zCHH8H0JH@M)M~HLLCLH8ffHDž fHDžHL諤HL蜤HHPE1LPLpfDJ 1H)HPHH; sHHHHLbHMJJJHPHH;sHHHf.HLbHpJ J J J H0J IIL;p<HHHLHL8LMIAMGI:1KKH I I H I HL9rI\PfH-fHDžLuH]L)Lt[IIHI9O4H@CILLKHH~LLHCILHLHHffH0H8HHHT$HD$H0H8HT$H$HPHHPNbff0HDž@HHLuL)t[IIHI9u3H<CIL8L0KH@H~LLHCIL8H01H褮HpL L`PHH01nMLHpHE11DH4H4IHH9rHIIGI4OI<IIO4I<M,I9I9AI9I9I9I9@M9I9A1D" "@ H6D -LHIZIOIQHfDoCo BoTfBofoIoBodffBo ffoBfofBH H H HuI9fPHDž`HHLuL)t[IIHI9w1HCILXLPKH`H~LLH_CILXHHPHxHLaHH2FH FH1Aaw'HPHB'I'E1LƅLHDžHDžHDžLLM)LHHHEHt&MHHURHHM11H)HHMLpHht.Hfff.I>t IHu HtƅHx) ##HHHHHHHAHHHpHQHσHH0HVH)HHHHHHHpH)HH)H L(K HHHhHȀXHt6HtPL`HL4@HHLCIHIuHtH`HHCH`LLHHhHH)HHLHHH`HtTHpHffff.H\HH\H;\u%HDHhH\HH`HuHJHxHpJ\HH)HL4HhHHLu6HHHqHsMxHHHLN|MHIIH(II)H4H)HM4 IHHHH`MLpIDH@E1+HHHH`LI)Hu]{H r5HII HHL9HHH91HHLI)Ht H@DDHHHHuIDHhH)1D  LLLLLLLLLLLLLLHH9uH`s1HH1@ADALLADALD L0ADALD@LPAoDAo D`LpHHuHt1H@H@o@oBDB H HuHH9h HhHIIM9HHLLHHLMHLxM4H(HLLHHIHHI<HIIHAE1*HIHHLI)huNwH r+II +LH;xHLI91LLLI)ht+Hffffff.DDHHHHuIL_HhH)1fffff.DDDDDDDDDDDDDDHH9uH`H s10H1fffff.DLA AL DLAD AL 0DLAD @AL PoDo AD `AL pHHu0t4HHDoDo BD)B )H HuHH9hHhIIIM9aGMuUHICMtEHx@HHtHuHxHxAHxCHHHHH~LxLLffffff.HHHHHH;3L(HHLLHHHpH<HpHHHHIH8MLHHHHHM< ML+8H)HH)IHLHH)IHLHLHI@H`HpEAML pHNH)HHPHHXLHHI@HxH@IHE1,L@K43HLxM)Mu^|fI r5LIHH LH;HLI9E1LLLxM)Mt HfDHHIHuIL\LL)1@TTTTTTTTTTTTTTHH9ufff.H``s1HPH1AD AL A AL AD AL AD AL 0AD AL AD @AL PAoD Ao AD `AL pHHuHPt=HHXffffff.AoDAo AD A H HuL;@MII9MH}LHMLHI@HHXMHEAHI43H@I|pHSH)H`HHHLHHxE1)LK.H@MM)MuPmf.I r*LIHH H9LHI9E1LLMM)MtHxDHHIHuISLL)1ff.12\1\2\1\2\1\2\1\2\1\2\1\2\1\2HH9ufff.H`s1HH`1DLAALDLAD AL0DLAD@ALPoDo AD`ALpHHuHt5HHAoD Ao ADA H HuL;MIL;-HILIL(L8HHHHHHH)HHLpL?H HHHHHHHHH0HAHHHpHyHσHH HNH)HHHHHHHpHxH)HLL(O, HHhHȀXt5IHtGH`HL4@MLHCHIIuIHtH`LL CH`MLHHhHH)HHLHHH`HtIHpHfH\HH\H;\u%HDHhH\HH`HuKD5HHpHpLLMM)KT HLHhHLLMHH(IAEAHrtLHHJ<LL)91ZAZZAZZAZZAZZAZZAZZAZIHHHHuHHIHMtIAIHIuMHHrHHCAAH8IMHHHL(iIN|MXLMHI)N MI)MIE1(H0I4H<LI)HulH rEHILHI<0LLILH9LLLLH91LHLI)HtHfHHHHuIAHhH)1  LLLLLLLLLLLLLLHH9uH`s1HH1@LAALD L0AD AL0D@LPAD@ALPoD`oLpAD`ALpHHuHt3HHoDo ADA H HuH;0 HhIHHIM9HHL(LH#HL,MJ LHLH+xLHxO$1I)MHHL4MHLME1LLLH s 1HLEILHI<HHI HH9s&HxHHHH9s 1HLH`s1 |H1ҐADALLADALD L0ADALD@LPAoDAo D`LpHHu t4HHAoDAo D H HuH0H9hH0HIHHhLLI)t%HfDDHHHHuIIraHhH)1fD:;D:D;D:D;D:D;D:D;D:D;D:D;D:D;HH9uHhHIIHIIM9HH|LH)HA>C.FCFCFCFCFCFCFCHHIHHuMLHMtIAEIHIuHHpHH LLLfffff.HH HH HH; L(LHHLLHHHpL HpH<HHLIHKH@HHxM MHL,LL)LL)IyL)LLHI\I)HL)IHL)IH`IHPIHLHHXICH8HHEAHQH)HHHHLHHM{E1$HXItLHMI)MuzI r[LILHHH<1HHHH HH9HPHH`HH91LIMI)Mt HDAHIHHuIRLH)1f.A 8 >AL8L>AL8L>AL8L>AL8L>AL8L>AL8L>AL8L>HH9u@H8`s1HH13L3AD5AL5D3 L30AD5 AL50D3@L3PAD5@AL5PoD3`oL3pAD5`AL5pHHuHt3HHfDoD3o 3AD5AL5H HuL;XMLHxIM9MHLHHICH`HxIKHEALHxIL7pH_H)H8I7HPHHXLHHE1M0LK4 -OLM)Muffff.LxI rHLILHHL)LLIH9H+@LLLH9E1LMLM)Mt'Hfff.AHIIHuIRLL)1f.A8>AT8T>AT8T>AT8T>AT8T>AT8T>AT8T>AT8T>HH9u@H``s1HPH81D1L1A2AL2D1L1AD2 AL20D1L1AD2@AL2PoD1o 1AD2`AL2pHHuHPt3HHXoD3o 3AD2A 2H HuL;fMMIHHHL;HILIL(LHHpHH?'HH)HHvƅHDžHHkrHDžHP1H;@HHXPHPSeH$HHCHDžHPHJKH@ןƅHDžHHt HCHHt H CH0Ht H8CHHt HCHHt HCHHHHHH)HHMHLhL耽Xt2HtDL`HL<@LHLGCIHIuMtH`LLnCH`LHHhHH)HHLHHH`HtOHpHH\HH\H;\u%HDHhH\HH`HuHpLpNLHHMLtILL)ItIuDMHu4kDDGMHu#ZALM~CMLMHt9Ht HuE$'E$ED$ALHM=CMLHHAHH!IDHHHHHH;HHL4HpJ8L,HIHt'HLHH<LH)Ht$Hu;DMMtvItIuNE$dDDGMMuRE$ED$GAHMPCMLpLMMuALLM"CMLMIHHAHHƅHDžHHt H;CHHt H #CH0Ht H8 CHHt HCHHt HCHHHLpH@fK>H_H)1 0@P`pD€DD D°DDDDH HuHtIIDH@H HuM9tJ4L)HL&HHHHDžHPHt HXCHHt HCHHt HCH0Ht H8pCHPHt HXXCHpHt Hx@CH}Ht H}.CH}HHK>H_H)1 0@P`pDDDDDDDDH@HuHtIIDH@H HuM9tJ4L)HD&HHHHDžHPHt HX!CHHt H CHHt HCH0Ht H8CHPHt HXCHpHt HxCH}Ht H}CH}HtHH8CHHDžHpHHHCt H{HCH@CHHDžHtCt H{CHCHHtCHHt HCHdQ[HH;Eu2HpH[A\A]A^A_]HDžHHuCCIH['H5 FH IFHPL?ffEHEpTCHH]fo{WfEH5FgHCCgAHfFHPHMLABE1H57r[HL4CTCIH蚆'H5KFH FHPL?ffEHE`CHH]fo*{WfEH5.F[HCC[AHFHPHMLAE1H5vq[HLsC.CIHم'H5FH FHPLS>ffEHE0CHEfo lXfEH4 tensorHHH INT64 tHHHld be anHHHsor shouHHHPads tenH@%AHFHPHML@E1H5p[H0LC?CIH'H5FH FHPLd=ffEHEPCHH]foچUfEH5FDH5CCDAHFHPHML?E1H5o[HoLCHPCmCIH'H5FH FHPL<H7FHEH]HuHH0HP1LH,?H5%o[HL"CBCIH舃'H59FH FHPL<ffEHE0CHEfoK UfEHof valueHHH number HHHas wrongHHH'pads' hHf@ sAH FHPHMLL>E1H5Bn[HL?C_CIH襂'H5VFH FHPL;ffEHE0CHEfohUfEHof valueHHH number HHHas wrongHHH'pads' hHf@ sAH=FHPHMLi=E1H5_m[HL\C|CIH'H5sFH FHPL<:ffEHE0CHEfoUfEHof valueHHH number HHHas wrongHHH'pads' hHf@ sAHZFHPHML<E1H5|l[H%LyC4CIH߀'H5FH FHPLY9HFHEH]HuHpH~HP1LH;H5k[HLC H}CH}CH}CHpCHpCHpCH0CH0CH0qC|HcCnHUC`HGCRH09CDH0+C6H0C(HPCHPC HPC IEt H}yCLMt?HL9t$HX@t HxNCHI9uHLL.Cpt HCPt H`CE1LMu#H@IALMHL9HX@t HxCHI9uUI IALMIALMIIALM&`IALM{I|IALMIALMA1I2IALMlIALMIIALMIIALMIIALMIALMNIIEt H}CLMt?HL9t$HX@t HxCHI9uHLLCpt HCPt H`CE1LMuTH>IALMt:HL9t<HX@t HxUCHI9uHL:CE6 +OLM)Muffff.LxI rHLILHHL)LLIH9H+@LLLH9E1LMLM)Mt'Hfff.AHIIHuIRLL)1f.A8>AT8T>AT8T>AT8T>AT8T>AT8T>AT8T>AT8T>HH9u@H``s1HPH81D1L1A2AL2D1L1AD2 AL20D1L1AD2@AL2PoD1o 1AD2`AL2pHHuHPt3HHXoD3o 3AD2A 2H HuL;fMMIHHHL;HILIL(LHHpHH?'HH)HHvƅHDžHHkrHDžHP1HO;@HHXPHPC,H$HHCHDžHPHJKH@ןƅHDžHHt HCHHt H ۨCH0Ht H8èCHHt H諨CHHt H蓨CHHHHHH)HHMHLhL耽Xt2HtDL`HL<@LHLGCIHIuMtH`LLnCH`LHHhHH)HHLHHH`HtOHpHH\HH\H;\u%HDHhH\HH`HuHpLpNLHHMLtILL)ItIuDMHu4kDDGMHu#ZALM~CMLMHt9Ht HuE$'E$ED$ALHM=CMLHHAHH!IDHHHHHH;HHL4HpJ8L,HIHt'HLHH<LH)Ht$Hu;DMMtvItIuNE$dDDGMMuRE$ED$GAHMPCMLpLMMuALLM"CMLMIHHAHHƅHDžHHt H;CHHt H #CH0Ht H8 CHHt HCHHt HۤCHHHLpH@fK>H_H)1 0@P`pD€DD D°DDDDH HuHtIIDH@H HuM9tJ4L)HL&HHHHDžHPHt HX踣CHHt H蠣CHHt H舣CH0Ht H8pCHPHt HXXCHpHt Hx@CH}Ht H}.CH}HHK>H_H)1 0@P`pDDDDDDDDH@HuHtIIDH@H HuM9tJ4L)HD&HHHHDžHPHt HX!CHHt H CHHt HCH0Ht H8١CHPHt HXCHpHt Hx詡CH}Ht H}藡CH}HtHH8CHHDžHpHHHCt H{HCH@CHHDžHtCt H{CHCHHtCHHt HCH[HH;Eu2HpH[A\A]A^A_]HDžHHuC谠CIHKN'H5EH WEHPL<ffEHEpTCHH]fo=WfEH5EgH覡CCgAHtEHPHML!?E1H5W&[HL4CTCIHM'H5YEH EHPL;ffEHE`蓟CHH]fo<WfEH5<E[HCC[AHEHPHML`>E1H5%[HLsC.CIHL'H5EH EHPL3;ffEHE0ҞCHEfol XfEH4 tensorHHH INT64 tHHHld be anHHHsor shouHHHPads tenH@%AHEHPHMLq=E1H5$[HL脞C?CIHK'H5EH EHPLD:ffEHEPCHH]foHUfEH5EDH5CCDAHEHPHML<E1H5#[HOLÝCHPʚCmCIHK'H5EH EHPLr9HEEHEH]HuHH0HP1LH <H5E#[HL"CBݜCIHxJ'H5GEH EHPL8ffEHE0聜CHEfo TfEHof valueHHH number HHHas wrongHHH'pads' hHf@ sAH.EHPHML,;E1H5b"[HL?C_CIHI'H5dEH EHPL7ffEHE0螛CHEfo(TfEHof valueHHH number HHHas wrongHHH'pads' hHf@ sAHKEHPHMLI:E1H5![HL\C|CIHH'H5EH EHPL7ffEHE0軚CHEfoETfEHof valueHHH number HHHas wrongHHH'pads' hHf@ sAHhEHPHMLf9E1H5 [HLyC4CIHG'H5EH EHPL96H EHEH]HuHpH~HP1LH8H5 [HuLC H}CH}CH}זCHpƖCHp赖CHp褖CH0蓖CH0肖CH0qC|HcCnHUC`HGCRH09CDH0+C6H0C(HPCHPC HPC IEt H}yCLMt?HL9t$HX@t HxNCHI9uHLL.Cpt HCPt H`CE1LMu#H=IALMHL9HX@t Hx诗CHI9uUI 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CHH<IHPHHXCHHwIHHIHHu|IHHIH0HiIH0HQIH0H IH0HNIH0H6IH0HxIH0HIH0HIH0H0lIHH IHHIPkH`ZIH0HIH0HrIH0H{IHpHZIHpHGIHpHfIHpHIHpHIHpH#]IH}Hu&vIH}HueIH}HUH}GIH}HIH}HIH}HIIIIHPHHXIHHIHHIHHIHHIHHIHHIHHIHHujtIHHIHHIHHu)3IHH~IHHt H聾CHHu5H0HuAHHuMHHuYHHuiH 4CH0HtH8CHHtHCHHtHCHH{HнCHHoH贽CHHcH蘽CH0HWH8|CHPHKHX`CHpH?HxDCH}H/3IHHt HCHHu5H0HuAHHuMHHuYHHuiH ʼCH0HtH8貼CHHtH蚼CHHtH肼CHHHfCHHHJCHHH.CH0Ht~H8CHPHtrHXCHpHtfHxCH}HuZaqIHHjHHvH0HuHPHuHpHuH}Ht H}zCH}HHuIHHHHH0HHPHHpHH}Ht H}CH}HtHH8CHpHHHtCt H{ºCH躺CHHu%HHu*LC IHHt脺CHHtHlCL謷C @UHSPHH{0Ht H{8CCH{Ht H{ 1CH̯[HH{HCHHt[] C[]f.UHSPHH{0Ht H{8CH{Ht H{ ѹCHl[HH{HCHt豹CHH[]飹CDUHAWAVSPIP蓹CHL=[L;H{LHHLQH\HHH[A^A_]L;IH{HCHt -+CIHCL^C fDUHAWAVAUATSHIIHo0[HHEAEIE0IE(IE IEIEIEW)`M}ƅ` -Mu HDžpDžavalufDžeeH}H`HHH]Ht7W HEt<Ct H{3CH+C`u%/H HEu`t HpC AE8AE<W)EHE)`HDžpƅ`DžamodeƅeHHH`HML譲HHHDžHHtCt H{eCH]C`t HpHCHMHEHHDHu:H ^E1H}1HA`CUHEр҄HHDHu8H EH}1HAC+UHEр҄HEHH EH}1HAѳCA]Lx -~AE<EH t HH(H t 1H u&H H C1HA H]CtA}<7W)`HDžpƅ`DžapadsƅeHHH`LLHHHDžHHtCt H{肵CHzC`t HpeCHIMI}HH)HHDž`IU I](H)HHH)vH`LIMI}H9uSsHIE(H9tDH)H1@HHxHH9r$ffff.I6HHHH9rEt H}訴CH#,[HH;EuH[A\A]A^A_]û״C腴CHHH,b'H5EH EH`LHW)0HDž@ !CH@(T)0Hte valueHHHttributeHHH'mode' aHHHInvalid H@H`H01HH5L[HHݳCN蘳CHHH?a'H5EH EH`LH.W)0HDž@ 4CH@(T)0Hte valueHHHttributeHHH'pads' aHHHInvalid H@H`H01HH5K[HHCaH 0t H@聲CDž,LeMu"VHv"H ,LeMt6HEL9t!HX@t Hx0CHI9uH}LLeCEu`u#LHMuSH}C`tHpرCLHMu$H ,LHMvHPL9t.HX@t Hx艱CHI9uHHLP7LLP(;H 0t H@>CDž,LeMu"VH3!H ,LeMt6HEL9t!HX@t HxCHI9uH}LLeӰCEu`u#HHHuLH}誰C`tHp蕰CHHHuUH ,HHHt:HPH9t<L`@t HxMCLL9uHHHP2C,uHH H<CEuzH EuhH `uAKHHHHH Eu$DH `t Hp蒯CEt"H}H `t HpjCI>Ht I}(YCI?Ht I}HCH 脬C fff.UHAWAVAUATSHILgLoLL)HH9LM)MII6HH=HM)LHHH9H}LE -II9LBMDHuI9蟮CHH54CHCH%[HHH5$[H#[H蟮CLHHr IGL9`ILHL9MLCHHtHIHHHHuI@IHIHPIHPIHPIHP IHP(IHP0IHP8H@HuTHuIJ<蠭CIHuO LHHr IOL9)ILHL9HZHHt$Hffffff.IHHHHuHj@IHIHAIHAIHAIHA IHA(IHA0IHA8H@Hu IIIPHHAHA~fpDHPH)1fDAADAD AD0HHuHtA~fpDAADI9IHGHHHHHHDBAH%A~fpDK|0IHH)1fffff.DDDHHuMtA~fpDAADH9O4M<MH]~LHLMCMHELLxLpHtHH[A\A]A^A_]iCH[A\A]A^A_]E1E1KHL)LCHH3I HH)HZHH1H1M.PCIHCLC UHAWAVSPIPêCHL=O[L;H{LHHLH\HHH[A^A_]L;IH{HCHt -[CIHNCL莧C fDUHAWAVSPIP3CHL=[L;H{L考HHLHb\HHH[A^A_]L;IH{HCHt -˩CIH辩CLC fDUHAWAVSPIP裩CHL=/[L;H{LHHLaH\HHH[A^A_]L;IH{HCHt -;CIH.CLnC fDUHAWAVAUATSHhHH [HHEHxHE HEHE<ILe0ILmILuXHEHEHE}IL}HCHCHHCHHxHHMHHL`LhLp E@(HMHH8Lx@fHnfpDfJWCH[HH;EuHHh[A\A]A^A_]`CfUHAWAVAUATSHhHHe[HHE9HxHE)HEHEILeILmILu8HEHEHE]IL}HCHCHH_CHHxHHMHHL`LhLp E@(HMHH8Lx@fHnfpDfIWCH[HH;EuHHh[A\A]A^A_]@CfUHAWAVAUATSH(HIHH8[HHEH8Hs[HHHLH@H8LCHHEEL5[M~LI@L8L'CL%l[ILHDž(HDž HDžHDžDž0I]H{CHHH=HH4HHHLL8Lt H 舥CHhCH5[HHCH8 CH[HH;EuHH([A\A]A^A_]菥CHLL8Lt H CHCHHHH5HhCH8pCHHH8YCHUHAWAVAUATSHIIIuMeI)MIIGHH=HMuI)LHHH9waII9LBMLEHuI9vK*CHH5CH萡CH[HH5 [H[H*CLEHuIJ<УCHHuLEN4IJN|M~HLICLI]M}MuHtHH[A\A]A^A_]lCH[A\A]A^A_]E11L贠CIHsCL胠C ff.UHAWAVAUATSH(HH3H~0CHHFPLEHMIHCHPHCHEHMHC HK(HC0H{HLmLeLE L}(H}LuLLLMMUHC`HEHCpHChHC`M)t3MILH=uLLrCHC`N,LkpHLaCLkhHHuHUHMMMsH([A\A]A^A_]H}C IHEH8HuHEH8HuL:C H{hCHEH8HtH{PҡCLC f.UHAWAVAUATSHH%[HHEHHH~H@H+>HHH(H)HH9HHHA HI(H)HH9cM)IL9SHL8L0AILMDHHHLpHHHHH9r=t1L@LMDALMu!I9lLkff.H(L NtMt -MyMI LH MtHtfoffffff.Ht[DHHtOHH tH DELIs8HHHXMu3;DLHHuDELHHHXMt -HyLMI HH MtHp+vfDHgELMWLH tI DHLsfHHLpH9Ls1HHHXH@HH H\HIHH MtH$*f.HELMLH tII DALMs1MH@HNHHHB H+HL0L8HDHB8L9uID1HHHDHB8L9tHHHA@H[HH;EuHĸ[A\A]A^A_]GCCIHhK'H5EH EH}LhHPH.AHEEHuLHE1H56[HdL踝C IALhMIIPt H`-CLmMt6HEL9t!HX@t HxCHI9uH}LLmCEuEuLhMu&^H}˜CEtH}輜CLhMt:HpL9tEHX@t Hx葜CHI9uHhLpvCEtL虜CL詙C Lfff.UHAWAVAUATSHH[HHEH^H(H+L8L0IH HGHGHHHtJIILH=H֛CLHIEN<M}HH@HH贛CM} 1H@E1H(HHQH)HHL+ IL9H8H+0HH8H9AH~H;8 H0LtL+@VIIAH(HIML@JDLeHhHDžPH}HhHPHPH@It#L;8}H0N,ffff.AH@HELhHDžPH}HhHPH NtLeHPLhHDžPH}HhHPUHPII)Hx +IEt H} CLMt?HL9t$HX@t HxCHI9uHLL”CpuPu&LMu6H蓔CPtH`~CLMHL9HX@t HxKCHI9utIEt H},CLMt?HL9t$HX@t HxCHI9uHLLCpuPu&LMu6H貓CPtH`蝓CLMHL9HX@t HxjCHI9uIEt H}KCLMt?HL9t$HX@t Hx CHI9uHLLCpuPu&LMu6&HђCPtH`輒CLMHL9HX@t Hx艒CHI9uIEt H}jCLMt?HL9t$HX@t Hx?CHI9uHLLCpuPu&LMu6EHCPtH`ۑCLMHL9'HX@t Hx訑CHI9uIEt H}艑CLMt?HL9t$HX@t Hx^CHI9uHLL>CpuPu#LMu/gHCPtH`CLMt:HL9tQHX@t HxҐCHI9uHL跐CE4L֐CH}H,LIEt H}}CLMt?HL9t$HX@t HxRCHI9uHLL2CpuPu#LMu/gHCPtH`CLMt:HL9tQHX@t HxƏCHI9uHL諏CE LʏCH}H LIALM:IALMxIIJIALMIALM I IALMFIALMIIALM#IALMZIIEt H}yCLMt?HL9t$HX@t HxNCHI9uHLL.CpuPu&LMu6HCPtH`CLMHL9HX@t Hx跍CHI9uIEt H}蘍CLMt?HL9t$HX@t HxmCHI9uHLLMCpuPu&LMu6&HCPtH` CLMHL9 HX@t Hx֌CHI9uIEt H}跌CLMt?HL9t$HX@t Hx茌CHI9uHLLlCpuPu&LMu6EH=CPtH`(CLMHL9*HX@t HxCHI9uIEt H}֋CLMt?HL9t$HX@t Hx請CHI9uHLL苋CpuPu#LMu/gH_CPtH`JCLMt:HL9tTHX@t HxCHI9uHLCEA L#CHH5 U LILHDžMtwAFt I~菊CL臊CHPHucILHDžMthAFt I~LCLDCHPHuT6IHPHHHX CHH<IHPHHX؉CHHwIHHIHHu|IHHIH0HiIH0HQIH0H IH0HNIH0H6IH0HxIH0HIH0HIH0H0lIHH IHHIPkH`ZIH0HIH0HrIH0H{IHpHZIHpHGIHpHfIHpHIHpHIHpH#]IH}Hu&vIH}HueIH}HUH}GIH}HIH}HIH}HIIIIHPHHXIHHIHHIHHIHHIHHIHHIHHIHHujtIHHIHHIHHu)3IHH~IHHt H聅CHHu5H0HuAHHuMHHuYHHuiH 4CH0HtH8CHHtHCHHtHCHH{HЄCHHoH贄CHHcH蘄CH0HWH8|CHPHKHX`CHpH?HxDCH}H/3IHHt HCHHu5H0HuAHHuMHHuYHHuiH ʃCH0HtH8貃CHHtH蚃CHHtH肃CHHHfCHHHJCHHH.CH0Ht~H8CHPHtrHXCHpHtfHxCH}HuZaqIHHjHHvH0HuHPHuHpHuH}Ht H}zCH}HHuIHHHHH0HHPHHpHH}Ht H}CH}HtHH8CHpHHHtCt H{CH躁CHHu%HHu*L~C IHHt脁CHHtHlCL~C @UHSPHH{0Ht H{8CCH{Ht H{ 1CHc[HH{HCHHt[] C[]f.UHSPHH{0Ht H{8CH{Ht H{ рCHc[HH{HCHt豀CHH[]飀CDUHAWAVSPIP蓀CHL=?c[L;H{L^HHLQH\HHH[A^A_]L;IH{HCHt ++CIHCL^}C fDUHAWAVAUATSHIIHZHHEAEIE0IE(IE IEIEIEW)`M}ƅ` +Mu HDžpDžavalufDžeeH}H`HH2|H]Ht7W HEt<Ct H{3CH+C`u%/H HEu`t Hp~C AE8AE<W)EHE)`HDžpƅ`DžamodeƅeHHH`HML}HHHDžHHtCt H{e~CH]~C`t HpH~CHMHEHHDHu:H lE1H}1HA`{CUHEр҄HHDHu8H ,EH}1HA{C+UHEр҄HEHH EH}1HAzCA]L*ux +~AE<EH t HH(H t 1H u&H H ϑC1HA H]zCtA}<7W)`HDžpƅ`DžapadsƅeHHH`LL*HHHDžHHtCt H{|CHz|C`t Hpe|CHIMI}HH)HHDž`IU I](H)HHH)vH`LIMI}H9uSsHIE(H9tDH)H1@HHxHH9r$ffff.I6HHHH9rEt H}{CHCZHH;EuH[A\A]A^A_]û{C{CHHH)'H5EH EH`LHW)0HDž@ !{CH@(T)0Hte valueHHHttributeHHH'mode' aHHHInvalid H@H`H01HH5[HmHzCNzCHHH/('H5EH EH`LH.W)0HDž@ 4zCH@(T)0Hte valueHHHttributeHHH'pads' aHHHInvalid H@H`H01HH5[HHyCaH 0t H@yCDž,LeMu"VHVH ,LeMt6HEL9t!HX@t Hx0yCHI9uH}LLeyCEu`u#LHMuSH}xC`tHpxCLHMu$H ,LHMvHPL9t.HX@t HxxCHI9uHHLP7LLP(;H 0t H@>xCDž,LeMu"VHH ,LeMt6HEL9t!HX@t HxwCHI9uH}LLewCEu`u#HHHuLH}wC`tHpwCHHHuUH ,HHHt:HPH9t<L`@t HxMwCLL9uHHHP2wC,uHH H<wCEuzH EuhH `uAKHHHHH Eu$DH `t HpvCEt"H}H `t HpjvCI>Ht I}(YvCI?Ht I}HvCH sC fff.UHAWAVAUATSHILgLoLL)HH9LM)MII6HH=HM)LHHH9H}LE +II9LBMDHuI9uCHH54CHsCHZHHH5ZHZHuCLHHr IGL9`ILHL9MLCHHtHIHHHHuI@IHIHPIHPIHPIHP IHP(IHP0IHP8H@HuTHuIJ<tCIHuO LHHr IOL9)ILHL9HZHHt$Hffffff.IHHHHuHj@IHIHAIHAIHAIHA IHA(IHA0IHA8H@Hu IIIPHHAHA~fpDHPH)1fDAADAD AD0HHuHtA~fpDAADI9IHGHHHHHHDBAH%A~fpDK|0IHH)1fffff.DDDHHuMtA~fpDAADH9O4M<MH]~LHLMtCMHELLxLpHtHH[A\A]A^A_]irCH[A\A]A^A_]E1E1KHL)LCHH3I HH)HZHH1H1M.PoCIHrCLoC UHAWAVSPIPqCHL=oT[L;H{L@OHHLHy\HHH[A^A_]L;IH{HCHt +[qCIHNqCLnC fDUHAWAVSPIP3qCHL=S[L;H{LNHHLHx\HHH[A^A_]L;IH{HCHt +pCIHpCLmC fDUHAWAVSPIPpCHL=OS[L;H{L NHHLaHw\HHH[A^A_]L;IH{HCHt +;pCIH.pCLnmC fDUHAWAVAUATSHhHHZHHEIHxHE9HEHElILe`ILmԥILu舦HE?HEHE譟IL}HCHCHHoCHHxHHMHHL`LhLp E@(HMHH8Lx@fHnfpDf WCHZHH;EuHHh[A\A]A^A_]`oCfUHAWAVAUATSHhHHZHHEiHxHEYHEHE ILeILm贤ILuhHEHE֠HE荞IL}HCHCHH_nCHHxHHMHHL`LhLp E@(HMHH8Lx@fHnfpDf WCHZHH;EuHHh[A\A]A^A_]@nCfUHAWAVAUATSH(HIHHXZHHEH8HZHHHLH@H8LmCHHEEL5ZM~LI@L8L'lCL%ZILHDž(HDž HDžHDžDž0I]H{oCHHHHHHHHLL8Lt H lCHhkCH5ZHHkCH8 lCHZHH;EuHH([A\A]A^A_]lCHLL8Lt H lCHjCHHHH5ZHHhjCH8pkCHHH8YkCHUHAWAVAUATSHIIIuMeI)MIIGHH=HMuI)LHHH9waII9LBMLEHuI9vK*kCHH5CHhCH{ZHHH5-ZH>ZH*kCLEHuIJ<jCHHuLEN4IJN|M~HLIlCLI]M}MuHtHH[A\A]A^A_]ljCH[A\A]A^A_]E11LgCIHsjCLgC ff.UHAWAVAUATSH(HH3H~0CHHFPLEHMIHCHPHCHEHMHC HK(HC0H{HLmLeLE L}(H}LuLLLMMUHC`HEHCpHChHC`M)t3MILH=uLLriCHC`N,LkpHLaiCLkhHHuHUHMMMsH([A\A]A^A_]H}fC IHEH8HuHEH8HuL:fC H{hhCHEH8HtH{PhCLfC f.UHAWAVAUATSHHEZHHEHHH~H@H+>HHH(H)HH9HHHA HI(H)HH9cM)IL9SHL8L0AILMDHHHLpHnHHHH9r=T1L@LMDALMu!I9lLkff.H(L NtMt +MyMI LH MtHtfoffffff.Ht[DHHtOHH tH DELIs8yHHHXMu3;DLHHuDELHHHXMt +Hy,MI HH MtHp vfDHgELMWLH tI DHLsfHHLpH9Ls1HHHXH@HH H\HIHH MtH$_*f.HELMLH t)I DALMsMH@HNHHHB H+HL0L8HDHB8L9uID1HHHDHB8L9tHHHA@HZHH;EuHĸ[A\A]A^A_]GeCdCIHh'H5EH EH}LhHPH~+AHSEHuLHE1H5ZHDLdC IALhMIIPt H`-dCLmMt6HEL9t!HX@t HxdCHI9uH}LLmcCEuEuLhMu&^H}cCEtH}cCLhMt:HpL9tEHX@t HxcCHI9uHhLpvcCEtLcCL`C Lfff.UHAWAVAUATSHHZHHEH^H(H+L8L0IH HGHGHHHtJIILH=HbCLHIEN<M}HH@HHbCM} 1H@E1H(HHQH)HHL+ IL9H8H+0HH8H9AH~H;8 H0LtL+@VIIAH(HIML@JDLeHhHDžPH}HhHPHPH@It#L;8}H0N,ffff.AH@HELhHDžPH}HhHPH NtLeHPLhHDžPH}HhHPUHPII)Hx HyI9| Hx -I9~HHHNtIH:[HH;EuHĸ[A\A]A^A_]C覙CIHhQG'H5EH EH}LhHPHO*AH=EHuLHvE1H5l2[HLiC HHsC HALhMHHPt H`ИCLeMt6HEL9t!Lh@t Hx諘CLM9uH}LLe葘CEuEuLhMu&^H}nCEtH}_CLhMt:HpL9tLLh@t Hx4CLM9uHhLpCEt>L<CHHH8Hu6=LHHHH8Ht&HHHHHH8Ht Hx辗CHC fDUHAWAVAUATSPL7MIMLL&MIMLI?I?LH LH HtHt^HH]HtXDHHtLHH t HUHUH DELIs HHE9u"MyB*DHHuDELE9tHI9vH[A\A]A^A_]}IL:H[A\A]A^A_]UHAWAVAUATSPIII^I+HH9HFIGIGIHtFHH=H<H}ZCIM'M,MoLHuFCMoM)uE1E1M)IMFI)MIILL)iKDIraLHtYIqH@tJ|K|K|IYHHt0HI4ĐH HI HLHLH HH[HuHHpMtPM)I41ffff.HtILH HI9uDH -I ILHI9uMELL)ɉƒHs 1HuRyII4L)1ff.ILH ILHLILHLILHLHH9uHHt)LI)K Hff.ItH1HHuH[A\A]A^A_]LܑC HI?Ht I`CH蠑C UHAVSHPIH [HHE(4CHþ H*CHHCHCXHC`HCXHCHHC@HC8HC0HC(HC HCPHCpHCxHCpHChƃHǃfǃHǃHǃƃHHǃHǃHǃHǃHǃHǃHǃHǃHǃHHHǃHǃHǃǃǃHǃ H] H5CH}HZH5%EH[H5GH茓HA H5CH賔HH;xHHH g[HMH|HUHuHuIIFIF0INIVIF@H]HEHtH謫HCHm [HH;Eu LHP[A^]1CIH]HEHtHgH譑CLC DUHAVSHPIH [HHE(脑CHþ HzCHHCHCXHC`HCXHCHHC@HC8HC0HC(HC HCPHCpHCxHCpHChƃHǃfǃHǃHǃƃHHǃHǃHǃHǃHǃHǃHǃHǃHǃHHHǃHǃHǃǃǃHǃ H]H5 CH}H誘H5uEH諏H56GHܐHA H5CHHH;ȆHHH [HMH,$HUHuHuIIFIF0INIVIF@H]HEHtHHBCH[HH;Eu LHP[A^]聏CIH]HEHtH跨HCL=C DUHAVSHPIH[[HHE(ԎCHþ HʎCHHCHCXHC`HCXHCHHC@HC8HC0HC(HC HCPHCpHCxHCpHChƃHǃfǃHǃHǃƃHHǃHǃHǃHǃHǃHǃHǃHǃHǃHHHǃHǃHǃǃǃHǃ H]護H5]CH}HH5EHH5GH,HA H5JCHSHH;HHH [HMH'HUHuHuIIFIF0INIVIF@H]HEHtHLH蒌CH [HH;Eu LHP[A^]ьCIH]HEHtHHMCL草C DUHAVSHPIH[HHE($CHþ HCHHCHCXHC`HCXHCHHC@HC8HC0HC(HC HCPHCpHCxHCpHChƃHǃfǃHǃHǃƃHHǃHǃHǃHǃHǃHǃHǃHǃHǃHHHǃHǃHǃǃǃHǃ H]H5CH}HJH5EHKH5ַGH|HH - HQH5CH蜌HH;aHHH P[HMH-HUHuHuIIFIF0INIVIF@H]HEHtH蕣HۉCHV[HH;Eu LHP[A^]CIH]HEHtHPH薉CLֆC fffff.UHAVSHPIH[HHE(dCHþ HZCHHCHCXHC`HCXHCHHC@HC8HC0HC(HC HCPHCpHCxHCpHChƃHǃfǃHǃHǃƃHHǃHǃHǃHǃHǃHǃHǃHǃHǃHHHǃHǃHǃǃǃHǃ H]H5CH}H芐H5UEH苇H5GH輈HH - HQH5CH܉HH;~HHH [HMHU+HUHuHuIIFIF0INIVIF@H]HEHtHՠHCHZHH;Eu LHP[A^]ZCIH]HEHtH萠HֆCLC fffff.UHAVSHPIH+ZHHE(褆CHþ H蚆CHHCHCXHC`HCXHCHHC@HC8HC0HC(HC HCPHCpHCxHCpHChƃHǃfǃHǃHǃƃHHǃHǃHǃHǃHǃHǃHǃHǃHǃHHHǃHǃHǃǃǃHǃ H]}H5-CH}HʍH5EH˄H5VGHHH - HQH5CHHH;{HHH м[HMH(HUHuHuIIFIF0INIVIF@H]HEHtHH[CHZHH;Eu LHP[A^]蚄CIH]HEHtHНHCLVC fffff.UHAVSHPIHkZHHE(CHþ HڃCHHCHCXHC`HCXHCHHC@HC8HC0HC(HC HCPHCpHCxHCpHChƃHǃfǃHǃHǃƃHHǃHǃHǃHǃHǃHǃHǃHǃHǃHHHǃHǃHǃǃǃHǃ H]}H5DH}H -H袯H5`EHHH5EHH5|GH"HA H5@CHIHH;yHHH [HMHB&HUHuHuIIFIF0INIVIF@H]HEHtHBH舁CHZHH;Eu LHP[A^]ǁCIH]HEHtHHCCL~C ff.UHAVSHPIHZHHE(CHþ H -CHHCHCXHC`HCXHCHHC@HC8HC0HC(HC HCPHCpHCxHCpHChƃHǃfǃHǃHǃƃHHǃHǃHǃHǃHǃHǃHǃHǃHǃHHHǃHǃHǃǃǃHǃ H]譪H5ۦDH}H:H蒭H5EHH H5EH!H5GHRHA H5pCHyHH;>vHHH -[HMH)HUHuHuIIFIF0INIVIF@H]HEHtHrH~CH3ZHH;Eu LHP[A^]~CIH]HEHtH-Hs~CL{C ff.UHAVSHPIHZHHE(D~CHþ H:~CHHCHCXHC`HCXHCHHC@HC8HC0HC(HC HCPHCpHCxHCpHChƃHǃfǃHǃHǃƃHHǃHǃHǃHǃHǃHǃHǃHǃHǃHHHǃHǃHǃǃǃHǃ H]ݧH5 DH}HjHH5EHHPH5,EHQ|H5ܩGH}HH - HQH5CH~HH;gsHHH V[HMH,HUHuHuIIFIF0INIVIF@H]HEHtH蛕H{CH\ZHH;Eu LHP[A^] |CIH]HEHtHVH{CLxC @UHAVSHPIHZHHE(t{CHþ Hj{CHHCHCXHC`HCXHCHHC@HC8HC0HC(HC HCPHCpHCxHCpHChƃHǃfǃHǃHǃƃHHǃHǃHǃHǃHǃHǃHǃHǃHǃHHHǃHǃHǃǃǃHǃ H] H5;DH}H蚂HH5EHH耂H5\EHyH5 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Hx_CLM9uH}LLe_CEuEuLhMu&^H}n_CEtH}__CLhMt:HpL9tLLh@t Hx4_CLM9uHhLp_CEt>L<_CHHH8Hu6=LHHHH8Ht&HHHHHH8Ht Hx^CH[C fDUHAWAVAUATSPL7MIMLL&MIMLI?I?LH LH HtHt^HH]HtXDHHtLHH t HUHUH DELIs HHE9u"MyB*DHHuDELE9tHI9vH[A\A]A^A_]]IL:H[A\A]A^A_]UHAWAVAUATSPIII^I+HH9HFIGIGIHtFHH=H<H}Z]CIM'M,MoLHuF]CMoM)uE1E1M)IMFI)MIILL)iKDIraLHtYIqH@tJ|K|K|IYHHt0HI4ĐH HI HLHLH HH[HuHHpMtPM)I41ffff.HtILH HI9uDH +I ILHI9uMELL)ɉƒHs 1HuRyII4L)1ff.ILH ILHLILHLILHLHH9uHHt)LI)K Hff.ItH1HHuH[A\A]A^A_]LXC HI?Ht I`[CHXC UHAVSHPIHۿZHHE(4[CHþ H*[CHHCHCXHC`HCXHCHHC@HC8HC0HC(HC HCPHCpHCxHCpHChƃHǃfǃHǃHǃƃHHǃHǃHǃHǃHǃHǃHǃHǃHǃHHHǃHǃHǃǃǃHǃ H]=H5fCH}HfH53EH]H5GH^HA H5CH_HH;THHH ~[HMH|HUHuHuIIFIF0INIVIF@H]HEHtHrHXCHZHH;Eu LHP[A^]1YCIH]HEHtHWrHXCLUC DUHAVSHPIH+ZHHE(XCHþ HzXCHHCHCXHC`HCXHCHHC@HC8HC0HC(HC HCPHCpHCxHCpHChƃHǃfǃHǃHǃƃHHǃHǃHǃHǃHǃHǃHǃHǃHǃHHHǃHǃHǃǃǃHǃ H]MH5 dCH}HcH5EHZH5GH \HA H5CH3]HH;QHHH {[HMH,$HUHuHuIIFIF0INIVIF@H]HEHtHoHBVCHݺZHH;Eu LHP[A^]VCIH]HEHtHoHUCL=SC DUHAVSHPIH{ZHHE(UCHþ HUCHHCHCXHC`HCXHCHHC@HC8HC0HC(HC HCPHCpHCxHCpHChƃHǃfǃHǃHǃƃHHǃHǃHǃHǃHǃHǃHǃHǃHǃHHHǃHǃHǃǃǃHǃ H]݂H5]aCH}H*aH5ӠEH+XH51GH\YHA H5JCHZHH;HOHHH 'y[HMH'HUHuHuIIFIF0INIVIF@H]HEHtH<mHSCH-ZHH;Eu LHP[A^]SCIH]HEHtHlHMSCLPC DUHAVSHPIH˷ZHHE($SCHþ HSCHHCHCXHC`HCXHCHHC@HC8HC0HC(HC HCPHCpHCxHCpHChƃHǃfǃHǃHǃƃHHǃHǃHǃHǃHǃHǃHǃHǃHǃHHHǃHǃHǃǃǃHǃ H]-H5^CH}Hz^H5#EH{UH5~GHVHH + HQH5CHWHH;LHHH pv[HMH-HUHuHuIIFIF0INIVIF@H]HEHtHjHPCHvZHH;Eu LHP[A^]QCIH]HEHtH@jHPCLMC fffff.UHAVSHPIH ZHHE(dPCHþ HZPCHHCHCXHC`HCXHCHHC@HC8HC0HC(HC HCPHCpHCxHCpHChƃHǃfǃHǃHǃƃHHǃHǃHǃHǃHǃHǃHǃHǃHǃHHHǃHǃHǃǃǃHǃ H]-H5[CH}H[H5cEHRH5{GHSHH + HQH5ӒCH UHH;IHHH s[HMHU+HUHuHuIIFIF0INIVIF@H]HEHtHgHNCHZHH;Eu LHP[A^]ZNCIH]HEHtHgHMCLKC fffff.UHAVSHPIHKZHHE(MCHþ HMCHHCHCXHC`HCXHCHHC@HC8HC0HC(HC HCPHCpHCxHCpHChƃHǃfǃHǃHǃƃHHǃHǃHǃHǃHǃHǃHǃHǃHǃHHHǃHǃHǃǃǃHǃ H]zH5-YCH}HXH5EHOH5yGH,QHH + HQH5CHLRHH;GHHH p[HMH(HUHuHuIIFIF0INIVIF@H]HEHtHeH[KCHZHH;Eu LHP[A^]KCIH]HEHtHdHKCLVHC fffff.UHAVSHPIHZHHE(JCHþ HJCHHCHCXHC`HCXHCHHC@HC8HC0HC(HC HCPHCpHCxHCpHChƃHǃfǃHǃHǃƃHHǃHǃHǃHǃHǃHǃHǃHǃHǃHHHǃHǃHǃǃǃHǃ H]xH5pDH}H:VHzH5nyEHH VH5ڕEH!MH5'vGHRNHA H5@CHyOHH;>DHHH n[HMHB&HUHuHuIIFIF0INIVIF@H]HEHtH2bHHCH#ZHH;Eu LHP[A^]HCIH]HEHtHaHCHCLEC ff.UHAVSHPIHZHHE(HCHþ H +HCHHCHCXHC`HCXHCHHC@HC8HC0HC(HC HCPHCpHCxHCpHChƃHǃfǃHǃHǃƃHHǃHǃHǃHǃHǃHǃHǃHǃHǃHHHǃHǃHǃǃǃHǃ H]uH5mDH}HjSHxH5vEHHPSH5 +EHQJH5WsGHKHA H5pCHLHH;nAHHH Mk[HMH)HUHuHuIIFIF0INIVIF@H]HEHtHb_HECHSZHH;Eu LHP[A^]ECIH]HEHtH_HsECLBC ff.UHAVSHPIHZHHE(DECHþ H:ECHHCHCXHC`HCXHCHHC@HC8HC0HC(HC HCPHCpHCxHCpHChƃHǃfǃHǃHǃƃHHǃHǃHǃHǃHǃHǃHǃHǃHǃHHHǃHǃHǃǃǃHǃ H] sH5kDH}HPH2uH5sEHHPH5:EHGH5pGHHHH + HQH5CHIHH;>HHH vh[HMH,HUHuHuIIFIF0INIVIF@H]HEHtH\HBCH|ZHH;Eu LHP[A^] CCIH]HEHtHF\HBCL?C @UHAVSHPIHZHHE(tBCHþ HjBCHHCHCXHC`HCXHCHHC@HC8HC0HC(HC HCPHCpHCxHCpHChƃHǃfǃHǃHǃƃHHǃHǃHǃHǃHǃHǃHǃHǃHǃHHHǃHǃHǃǃǃHǃ H]=pH5IhDH}HMH"sH5pEHHMH5jEHDH5mGHEHH + HQH5ɄCHGHH;;HHH e[HMHk*HUHuHuIIFIF0INIVIF@H]HEHtHYH@CHZHH;Eu LHP[A^]P@CIH]HEHtHvYH?CL =C @UHAVSI?CHHLH[A^]IH?CL<C UHAWAVATSH0IHHZHHEL%"[L#H{HcG\HW)EHEEEaxisELsH}HULL=H]HEHtCt H{>CH>CEt H}>CHtIHaZHH;Eu H0[A\A^A_]?CIEt H}>CL#H{HCHty>CL;C UHHH "![HHxH@Ht]F>C]fDUHSPHH [HH{HCHt>CHH[]>CfUHAWAVAUATSHXHHuH}H}ZHHEE11HILuHՀIǾHŀHEMf1HLP HHEHHHEH$LELMLLLuLLjIH}IH蔄HMt LdIL]MLUM +1LL]fffff.HHMHuHHGIILwIAFHEHL)HEH1fAnfp(MHEE1fC8!fC8!dff[[YYBBdfC8!\fC8!d ff[[YYB\ Bd0IHuH}t.fC8!fC8!dff[[YYBB\MJLHL9uQE1H}uHt{EDAHvI<H9HI91ffff.A $D)W*Y IHHH9rHHL9rffff.1HL9rLL]HMHL9+fD1HL9{E1LHW11MHuHAHs1I 4H9vH I9s1HH(HWHHDIAHtIQH)1fA8! fA8!\ [[YY\fA8!T fA8!\ [[YYT \0HHuMt$fA8! fA8!\ [[YY\IHH9t*A $W*Y IHHH9rHL9LIM91IM9HEHH ZH H;MuHX[A\A]A^A_]9CUHAWAVAUATSHL8MHIIIHϝZHHEIF I+FHtHI~׻HIEH8HL读HMHMIG I+GHHuIL{H8CIH`H&H5AEH EHxL`W)@HDžP@M8CHP(W)@H size 1.HH5Hor or siHH0H 1D tensHH(Hcalar orHH Hl or a sHHHt be nulHHHoint musHHHx_zero_pH@=AHgEHxH@LE1H5ZHZL7CIt$I+4$HHHLH +IEI$HcHL8IEHsLHMHIFIN H)HuSHI;EuJMtIOIW H)HH9HZHH;EuHĨ[A\A]A^A_]'7C6CIH`p&H5iEH EHxL`#HDŽEHEH@HuHH8%AHWEHxLHiE1H5ZHL|6C76CIH`&H5˂EH EHxL`&<HDŽEHEH@HuHH8AH$EHxLHE1H5ZHjL5C IALeMulIAL`MIIAL`MII@t HP5CLeMt6HEL9t!HX@t Hx4CHI9uH}LLe4CEuxu L`Mu)aH}4CxtH}4CL`Mt:HhL9t?HX@t Hxz4CHI9uH`Lh_4CELLIAL`MzII@t HP4CLmMt6HEL9t!HX@t Hx3CHI9uH}LLm3CEuxu#L`Mu00H}3CxtH}3CL`MHhL9 HX@t Hxa3CHI9uI@t HP<3CLmMt6HEL9t!HX@t Hx3CHI9uH}LLm2CEuxu L`Mu)aH}2CxtH}2CL`Mt:HhL9tEHX@t Hx2CHI9uH`Lh2CEtL2CL/C LDUHAVSIV2CHHLH[A^]IH)2CLi/C UHAWAVATSH0IHHZHHEL%[L#H{Hc:\HW)EHEEEaxisELsH}HULL/H]HEHtCt H{1CH1CEt H}r1CHtIHZHH;Eu H0[A\A^A_]1CIEt H}21CL#H{HCHt1CLY.C UHHH [HHxH@Ht]0C]fDUHSPHH[HH{HCHt0CHH[]0CfUHAWAVAUATSHXHHuH}HZHHEE11HsILuHusIǾHesHEMf1HLHHEHHHEH$LELMLLLuLLK]IH}返IH4wHMt L褔IL]MLUM +1LL]fffff.HHMHuHHGIILwIAFHEHL)HEH1fAnfp(MHEE1fC81fC81dff[[YYBBdfC81\fC81d ff[[YYB\ Bd0IHuH}t.fC81fC81dff[[YYBB\MJLHL9uQE1H}uHt{EDAHvI<H9HI91ffff.A $D)W*Y IHHH9rHHL9rffff.1HL9rLL]HMHL9+fD1HL9{E1LHW11MHuHAHs1I 4H9vH I9s1HH(HWHHDIAHtIQH)1fA81 fA81\ [[YY\fA81T fA81\ [[YYT \0HHuMt$fA81 fA81\ [[YY\IHH9t*A $W*Y IHHH9rHL9LIM91IM9HEHH ZH H;MuHX[A\A]A^A_]a,CUHAVSI+CHHLH[A^]IH+CL )C UHAWAVATSH0IHHDZHHEL%V[L#H{* H[4\HW)EHEEEaxisELsH}HULL[)H]HEHtCt H{)+CH!+CEt H}+CHtIHZHH;Eu H0[A\A^A_]D+CIEt H}*CL#H{HCHt*CL'C UHHH b [HHxH@Ht]*C]fDUHSPHH0 [HH{HCHtU*CHH[]G*CfUHAWAVAUATSHHH HHZHHE1H#mIǾHmIľHmIMo1HL HH HHHEH$LELMLLL?LVIL,HHpIŰ,MLHH ILHt#H1H < +HH9uDž,HEHHL]M{L}LIHMIIGHHPHHHHJHH)HN41f.H,lMHH<ME1 1fff.CIw1HL(HtH1fD\[[YYAA\T \0[[YYAT A\0HHut \[[YYAA\M9t/JK4LLH)1W* Y HH9uLMIM9HMlHHHH;f.E11HfDM.H FCIw1HLfAnfp(HtH1fff.oodff[[YYA\Ado\ od0ff[[YYA\ Ad0HHuHt+oodff[[YYATA\M9t3JK|LLH)1ɐ4D)W*Y HH9uJOlIM9HHH;1H HEHHxHHH ZH H;MuH[A\A]A^A_]%CN%CIHP&H5qEH /tEHhLP^SW)0HDž@`$CHH@(V)0H5tEYH<&CCYAH>tEHhH0LE1H5ZHSL$C IALeMuFzIALPMII0t H@+$CLeMt6HEL9t!HX@t Hx$CHI9uH}LLe#CEuhu LPMu,dH}#ChtHx#CLPMt:HXL9tEHX@t Hx#CHI9uHPLXk#CEtL#CL C LؐUHAVSIF#CHHLH[A^]IH#CLY C UHAVSI#CHHLH[A^]IH"CL C UHAVSI"CHHLH[A^]IH"CLC UHAVSI"CHHLH[A^]IHY"CLC UHAWAVATSH0IHHԆZHHEL%[L#H{HK+\HW)EHEEEaxisELsH}HULLH]HEHtCt H{!CH!CEt H}!CHtIH1ZHH;Eu H0[A\A^A_]!CIEt H}b!CL#H{HCHtI!CLC UHHH [HHxH@Ht]!C]fDUHSPHH[HH{HCHt CHH[] CfUHAWAVAUATSHhHH]HuH}HIZHHE1HcIƾHcIǾHcIMI1HL!HHEHHHEH$LELMLLLMt +L[~1HELkMHEL_MIHdIHEHEHHMLmHEHtpJ HM1ɐHMHtGE1H]HEB BHEL@LLLMIHEL}I9rfD1HMHH;Mr~J HM1Leffff.HMHtG1DAHEL@1LLLbMHHEL}H9rHMHH;Mr1HMHH;MrHEHH ZH H;MuHh[A\A]A^A_] CfUHAWAVSHXMHIZHHEH}HuHUEMHZH0CH (\HHMHHHMHHHMHHHMHH HMHH(HEHVL}LHL*&H}I9tHtHP(HZHH;Et!HP HZHH;Eu HX[A^A_]?CIH}I9uHP L C HtHP(LC UH]f.UH]CfDUHSPH0CH '\HHKHSHHHPHKHHHK HH HK(HH(H[]@UHH&\HHG(HF(HG HF HGHFHGHOHNHF]UH]f.UH]CfDUHHHHHHOH HH9HOHOH HHOH)H1HO HO( H]P(UHH ջVH1H9NHD]DUHH]&\]UHAVSIVCHHLH[A^]IH)CLiC UHAWAVATSH0IHHZHHEL%ZL#H{H%\HW)EHEEEaxisELsH}HULLH]HEHtCt H{CHCEt H}rCHtIHZHH;Eu H0[A\A^A_]CIEt H}2CL#H{HCHtCLYC UHHH ZHHxH@Ht]C]fDUHSPHHZHH{HCHtCHH[]CfUHAWAVAUATSHhHH]HuH}HZHHE1H]IƾHx]IǾHh]IMI1HLHHEHHHEH$LELMLLLMt +L~1HEL;GHEL/GIHԀIHEHEHHMLmHEHtpJ HM1ɐHMHtGE1H]HEB BHEL@LLLMIHEL}I9rfD1HMHH;Mr~J HM1Leffff.HMHtG1DAHEL@1LLLbMHHEL}H9rHMHH;Mr1HMHH;MrHEHH O}ZH H;MuHh[A\A]A^A_]CfUHAWAVSHXMH}ZHHEH}HuHUEMHZH0VCH "\HHMHHHMHHHMHHHMHH HMHH(HEHVL}LHL#&H}I9tHtHP(H|ZHH;Et!HP Hj|ZHH;Eu HX[A^A_]CIH}I9uHP LC HtHP(LC UH]f.UH]dCfDUHSPH0WCH !\HHKHSHHHPHKHHHK HH HK(HH(H[]@UHH}!\HHG(HF(HG HF HGHFHGHOHNHF]UH]f.UH]CfDUHHHHHHOH HH9HOHOH HHOH)H1HO HO( H]@(UHH նVH1H9NHD]DUHH !\]UHAVSI&CHHLH[A^]IHCL9C UHAVSICHHLH[A^]IHCLC UHAVSHPIH;zZHHE(CHþ HCHHCHCXHC`HCXHCHHC@HC8HC0HC(HC HCPHCpHCxHCpHChƃHǃfǃHǃHǃƃHHǃHǃHǃHǃHǃHǃHǃHǃHǃHHHǃHǃHǃǃǃHǃ H]H}11"HH5 !CHHKH5RdEHH5@GH HHHQH5WCH-HH;HHH 8[HMHF HUHuHuIIFIF0INIVIF@H]HEHtH,H<CHwZHH;Eu LHP[A^]{CIH]HEHtH,HCL7C ffffff.UHAVSHPIHkwZHHE(CHþ HCHHCHCXHC`HCXHCHHC@HC8HC0HC(HC HCPHCpHCxHCpHChƃHǃfǃHǃHǃƃHHǃHǃHǃHǃHǃHǃHǃHǃHǃHHHǃHǃHǃǃǃHǃ H]H}11 HH5=CHH{HEH5aEHHH5haEHH5=GH#HH HQH5 +UCHCHH; HHH 5[HMH<HUHuHuIIFIF0INIVIF@H]HEHtH)HRCHtZHH;Eu LHP[A^]CIH]HEHtH)H CLM C DUHAVSHPIHtZHHE(CHþ HCHHCHCXHC`HCXHCHHC@HC8HC0HC(HC HCPHCpHCxHCpHChƃHǃfǃHǃHǃƃHHǃHǃHǃHǃHǃHǃHǃHǃHǃHHHǃHǃHǃǃǃHǃ H]H}11%H=H5]CHHHBH5^EHHH5^EHH5;GHCHH HQH5*RCHcHH;( HHH 3[HMH$HUHuHuIIFIF0INIVIF@H]HEHtH'Hr CH rZHH;Eu LHP[A^] CIH]HEHtH&H- CLm +C DUHAVSHPIHqZHHE( CHþ H CHHCHCXHC`HCXHCHHC@HC8HC0HC(HC HCPHCpHCxHCpHChƃHǃfǃHǃHǃƃHHǃHǃHǃHǃHǃHǃHǃHǃHǃHHHǃHǃHǃǃǃHǃ H]H}11EH]H5}CHHH?H5[EHH1H5[EH2H588GHcHAH5QOCHHH;OHHH .0[HMHc"HUHuHuIIFIF0INIVIF@H]HEHtHC$H 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H8f:!0AHH9IHH0H@t5HHHHJ4HPHA HHHuH(HH)ILI| HHIHHHHILLHHLHXHIHHC OB OC OB HLMMLHuσx~tH1HHLpHHHHHH;H|MH@L+HL+(HH0H9|81HNHJHLpLHLhHHHHHH;VE~gIcH1HH1@H:HH:H;z|HHH0H9|HHHHHH;|1HHHHHHHH;|[UHAWAVAUATSH(IIHXHHEID$HEI\$Ml$ I9udLuM|$M)￀@HJ;IIM~HLLIm@LI\$ID$Mt$ MtLȣ@HEHLuM|$LH)HAL$9}NHcHHL9tH<蛤@L@HAL$HcI\$HHH3Lt3RLä@MtHtsHELuM9|$ tHEHMIOIID$ HuH}tAL$I\$HcAL$HHH qXH H;MuH([A\A]A^A_]2@@HH襢@H5XHYXH@fUHAWAVAUATSHIIIuMuI)MIIGHH<HMeI)LHHH9waII9LBMLEHuI9vK*@HH5@H萟@H[XHHH5 XHXH*@LEHuILHѡ@HHuLEIIIIIHJL;J;N|;M~HLI @LI]M}MeHtHH[A\A]A^A_]]@H[A\A]A^A_]E11L襞@IHd@Lt@ fff.UHAWAVAUATSHXHXHHEHHLLWHWHwLG(LIHHHHG IHHL;GPHH;GHHH;w@HH;W8LL;W0W)E)E)E)E)E)p)`)P)@)0) M)1HMLH1&IIIMW)E)E)E)E)E)p)`)P)@)0) )H)H(HHLH@ITHPIt(HpHHHH HuHIqhI@IHLMIDHHDYI@HALIF0N$I{H)HLHHINH1H1LLLE1HII`HL<IH}1MI)H s1LMudHHL0H1ff.DDDDDDHHuLMt.HHffff.AAHHuLMI)IdLHLH:LML$LKL9s1H2IHI<H9sLLLILHHHzIIASHwK|0LRM)IHHHLLE1fffff.CDC BDBLCDCL BDB IIuHt)IHI<HLCCLHI9LLLLHff.D)HH)HtHAAHHuHLr>HHT A<|A||A||A| <HI9uHLÃtBH1LfH9HH9H;y|1HH+qHH L9rL HqHLMH;MIMhDIAUI@HLIBpJ<HHHL)HIRH1HE1LL E1H!Fffffff.MA`MSILpH1DDDDDDDDDDDDDDDH HuM<Ht5J<"HADADD AD D0AD0LMHI9HMDCCII9~IM)IWHHHH9HL4N,&KL9sFH1ILH<H9s2LLH1M<HBLHHHyIIANH>K\0HyL)IHI HL4LE1CDC BDBLCDCL BDB IHuHt*MHIT HLCCLHI9LLHI̐D)HL)HtHCCIHuHHrBIL fffff.CBTCTBTCTBTCT BIL9uLI܃tNH1Lfffff.H9HH9H;y|1HH+qHH L9rL HqHHHIL;HXHH;EuHX[A\A]A^A_]R@@UHAWAVAUATSHHXHNXHHEп(ǖ@Hþ H轖@HHCHCXHC`HCXHCHHC@HC8HC0HC(HC HCPHCpHCxHCpHChƃHǃfǃHǃHǃƃHHǃHǃHǃHǃHǃHǃHǃHǃHǃHHHǃHǃHǃǃǃHǃ H]`I蘿IIHHIW)EHE(@HEHH(HML8L`LhHXLp HM9I1IIIYHW)`HDžp(衔@H`HH(HpL8L`LhLpHX HhH5x@H}HUH`H5CHH5DH?HH -HQH5V@H_HH;$HHH XHMH(GHUHuHuHXHHCHC0HKHSHC@H`Ht Hh蠓@H}Ht H}莓@LuHEMtL'Lm@H -XHH;EuHHĈ[A\A]A^A_]裓@IH`Hu$H}Hu>H]HEHu]LZ@ Hh@H}Ht IH}HtH}@H]HEHtIH]HEHtHgH譒@L@ DUHAWAVAUATSHHXH XHHEп(w@Hþ Hm@HHCHCXHC`HCXHCHHC@HC8HC0HC(HC HCPHCpHCxHCpHChƃHǃfǃHǃHǃƃHHǃHǃHǃHǃHǃHǃHǃHǃHǃHHHǃHǃHǃǃǃHǃ H]IHI@IHpIW)EHE(辐@HEHH(HML8L`LhHXLp HMII虻I葾I HW)`HDžp(Q@H`HH(HpL8L`LhLpHX HhH5(@H}HUH`譕H5CH辏H5IDHHH HQH5@HHH;ԆHHH XHMHIHUHuHuHXHHCHC0HKHSHC@H`Ht HhP@H}Ht H}>@LuHEMtLרL@HXHH;EuHHĈ[A\A]A^A_]S@IH`Hu$H}Hu>H]HEHu]L -@ Hh贎@H}Ht IH}HtH}蔎@H]HEHtIH]HEHtHH]@L蝋@ DUHAWAVAUATSHHXHXHHEп('@Hþ H@HHCHCXHC`HCXHCHHC@HC8HC0HC(HC HCPHCpHCxHCpHChƃHǃfǃHǃHǃƃHHǃHǃHǃHǃHǃHǃHǃHǃHǃHHHǃHǃHǃǃǃHǃ H]III診H IW)EHE(n@HEHH(HML8L`LhHXLp HM虶I葼IIIAI蹸HW)`HDžp(@H`HH(HpL8L`LhLpHX HhH5ؘ@H}HUH`]H5qBHnH5DH蟌HA H5@HƍHH;苂HHH zXHMHOEHUHuHuHXHHCHC0HKHSHC@H`Ht Hh@H}Ht H}@LuHEMtL莤LԊ@HOXHH;EuHHĈ[A\A]A^A_] -@IH`Hu$H}Hu>H]HEHu]L@ Hhk@H}Ht IH}HtH}K@H]HEHtIH]HEHtHΣH@LT@ fff.UHAWAVAUATSHHeXHHEMMAIHhDmI_I+HH`H>H)IIH HXLHNHcH9`A$I6L3HcH9EHMI6HƸH9tL HcH9HMHu L6HFI9t>H`Hq HxH.HHL)HHH1LMc1HXHIHtlHBHEHBHEHBHEHEH$H]HuHMLMHLL`CLhLHKX#[HHIIffEHEEbJ<8@HH]H]JHHEAIHLhHu [H?H!HZHHwH sf1fHH^H)f1ffffff.AofAoDfAoL Ao\0Aod@ffAoTPffAoD`fAoLpfHHuHt$I|HfoWfofH HuffpNffH~H9tI ff.H1HH9uHxL)HIcH9uH;Xu LheHpHBHEHBHEHBHEHBHEH BHEHxHD$ HEHD$HpHD$HEHD$HEH$H]HuHMLMHH`MCLhLHU#EH}@HqWHH;EE11LhMBfLHfInfpDHpHHJHLhs1HHqH)1ffff.DD D0D@DPD`DpӀӐӠӰH H{Ht(HTHfffff.BH HuL9Hu t!H I)fffff.L9HIuIL}Mt)LvLIw@LHFHFHHL~L~IEHWHH;EuLHĨ[A\A]A^A_]耄@@H}x@ HH}Ht#H}HEu HEt H}@H!@ fUHAWAVAUATSHHIIH,WHHE1HII$IG0@ȃH HcHHpLHLZHpLHL2CHpLHLk!,HpLHL HpLHL+HpI$HkWHH;EuLHĨ[A\A]A^A_]&@Ԃ@IHX0$H5BH BHpLXrIG0H8HBHEHBHEH@HuH8HMHCHp1LHvH5oXHľLl@!I@t HP@LmMt6HEL9t!HX@t Hx܁@HI9uH}LLm@Et H}賁@pt H}衁@Dž4HXHu!YHIǰ4HXHt:H`H9t9Lh@t HxK@LL9uHXH`0@4u -HILE@ II$L@~@ 000UHAWAVAUATSHHHIIH%WHHEH{UZLL+IGHEEEEW)EHEHHwHt2HHHP H)HL1HoJH}HIwIW H}HHPIIHEHD$HEHD$HEH$LELMLLDI}tYHBH UB1AL-$H}Ht H}@HWHH;ELHĘ[A\A]A^A_]LIEHLxLh W)PHDž`M)t[MIHI9nL @HHXHPJH`M~HLLW@LHXH-vHEHEHHcEHcMHHHHUIcHHH8ƒHpHH)HhHHH@HpHHHxHHHHH11HfDHEHL$IcL9,LPHM$W)0HDž@LXM)t\LHHH9L}@IL8L0IDH@M~LLL~@ML8HHH0[IH0Ht H8 }@LwIDHHL4D9u1LLHS~@IcHHH;IcL$HHLs1H!K dHHHHXHH`1Lffffff.LLL}@K<,HJ40L}@H`J<(K47Lx}@HJ<(HpJ40LZ}@HLxLXH9huHtZHHHHL4HHHLLLHL|@MLIuHHHHH;BBE1E1HEN,IcL9cHPHL,W)0HDž@LXI)ttHLMIHI9 Lz@HH8H0JH@MLH~HL{@LH8HDH0XHH0Ht H82z@H蜋DD9uHJ4HH{@IcIIL;LIEHPH5HXy@H}H%)z@y@H0v@y@IH0J'$H5UBH BHPL0߿W)HDž 0?y@H (T)H tensor.HH Ha vectorHHHmust be HHH tensor HHHAn splitH@(AHBHPHLE1H5XHLx@ HPu@ HALeMuFzHAL0MHHt H @x@LeMt6HEL9t!Lh@t Hxx@LM9uH}LLex@puPu L0Mu,dH}w@PtH`w@L0Mt:H8L9tQLh@t Hxw@LM9uH0L8}w@ELw@H}HLHH0HdbHMuIEMAFt I~w@L w@H}Huv}HH}HufmHH0Hu$.HHPHu)3HH0Ht H8v@HPHt HXv@H}Ht H}v@Hs@ fUHAWAVAUATSHHHIIHWHHEH{OLL+IGHEEEEW)EHEHHHt2HHHP H)HL1HeJH}H責IwIW H}?HHPIIHEHD$HEHD$HEH$LELMLLD\I}tYH0BH B1AL'#$H}Ht H}#u@HWHH;ELHĘ[A\A]A^A_]LIEHLxLh W)PHDž`M)t[MIHI9nLt@HHXHPJH`M~HLLu@LHXHHEHEHHcEHcMHHHHUIcHHH8ƒHpHH)HhHHH@HpHHHxHHHHH11HfDHEHL$IcL9,LPHM$W)0HDž@LXM)t\LHHH9L*s@IL8L0IDH@M~LLLtt@ML8HHH0ZQIH0Ht H8r@L藷IDHHL4D9u1LLHs@IcHHH;IcL$HHLs1H!K dHHHHXHH`1Lffffff.LLLFs@K<,HJ40L/s@H`J<(K47Ls@HJ<(HpJ40Lr@HLxLXH9huHtZHHHHL4HHHLLLHLr@MLIuHHHHH;BBE1E1HEN,IcL9cHPHL,W)0HDž@LXI)ttHLMIHI9 LSp@HH8H0JH@MLH~HLq@LH8HDH0NHH0Ht H8o@H輴DD9uHJ4HH%q@IcIIL;LIEHPH5HX^o@H}H%)o@6o@H0l@?o@IH0$H5BH hBHPL0dտW)HDž 0n@H (T)H tensor.HH Ha vectorHHHmust be HHH tensor HHHAn splitH@(AHBHPHL׿E1H5XH6Ln@ HPk@ HALeMuFzHAL0MHHt H m@LeMt6HEL9t!Lh@t Hxm@LM9uH}LLem@puPu L0Mu,dH}xm@PtH`cm@L0Mt:H8L9tQLh@t Hx8m@LM9uH0L8m@EL<m@H}HLHH0HdbHMuIEMAFt I~l@Ll@H}Huv}HH}HufmHH0Hu$.HHPHu)3HH0Ht H8Kl@HPHt HX3l@H}Ht H}!l@Hai@ fUHAWAVAUATSHHHIIHeWHHEH{ELL+IGHEEEEW)EHEHH跮Ht2HHHP H)HL1H"[JH}HRIwIW H}HHPIIHEHD$HEHD$HEH$LELMLLDI}tYHBH |B1AL$H}Ht H}j@H>WHH;ELHĘ[A\A]A^A_]LIEHLxLh W)PHDž`M)t[MIHI9^LLj@HHXHPJH`M~HLLk@LHXHYHEHEHHcEHcMHHHHUIcHHH(ƒHpHH)HhHHH@HpHHHxHHHHH11Hf.HEHL,IcL9LPHM,W)0HDž@LXM)t[LHHH9Lh@IL8L0IH@M~LLLj@ML8HHH0FIH0Ht H8Nh@L8HDHHL4D9u2HLHi@IcHHH;IcL$HHHs1HK dHHHHXHH`I1LLLLh@K<,HJ40Lh@H`J<(K47Lh@HJ<(HpJ40Lh@HLxLXH9huHtZHHHHL4HHHLLLHL6h@MLIuHHHHH;RBE1E1HEN,IcL9cHPHL,W)0HDž@LXI)ttHLMIHI9 Lf@HH8H0JH@MLH~HLCg@LH8HDH0/DHH0Ht H8e@HlDD9uHJ4HHf@IcIIL;LIEHPHEHXe@H}H59We@d@H0Lb@d@IH0$H5BH BHPL0˿W)HDž 0d@H (gT)H tensor.HH Ha vectorHHHmust be HHH tensor HHHAn splitH@(AHNBHPHLGͿE1H5=WH楾L:d@ HPDa@ HALeMuFzHAL0MHHt H c@LeMt6HEL9t!Lh@t Hxkc@LM9uH}LLeQc@puPu L0Mu,dH}(c@PtH`c@L0Mt:H8L9tQLh@t Hxb@LM9uH0L8b@ELb@H}HLHH0HdbHMuIEMAFt I~ab@LYb@H}Huv}HH}HufmHH0Hu$.HHPHu)3HH0Ht H8a@HPHt HXa@H}Ht H}a@H_@ fUHAWAVAUATSHHHIIHWHHEH{E;LL+IGHEEEEW)EHEHHgHt2HHHP H)HL1HPJH}HIwIW H}HHPIIHEHD$HEHD$HEH$LELMLLDI}tYHBH ErB1ALw$H}Ht H}s`@HWHH;ELHĈ[A\A]A^A_]LIEHLxLh W)PHDž`M)t[MIHI9L_@HHXHPJH`M~HLLGa@LHXH蝎HEHEHHcEHcMHHHUIcHHH[ƒHpHH)HxHIHHHH HHHH1E1fLHEHL,IcL9eLPHM,W)0HDž@LXM)t[LHHH9L^@IL8L0IH@M~LLL_@ML8HHH0<IH0Ht H8^@L1ILDHN48D9u;LLH]_@McMHH;fffff.IcHHs,E1LH[ffffff.HH @HH HhHHpME1fffff.LLHH^@HJ40J<+H^@HJ40HpJ<(Hj^@HJ40HJ<(HL^@ILLhL9xyLHttLMMMLMLHfffff.LLL]@MLHuHMHH;)iHLMHH;CE1E1HEN,IcL9cHPHL,W)0HDž@LXI)ttHLMIHI9 L[@HH8H0JH@MLH~HL\@LH8HDH09HH0Ht H8[@HDD9uHJ4!HHU\@IcIIL;LIEHPHHXZ@H}H Z@fZ@H0W@oZ@IH0$H5%BH BHPL0W)HDž 0Z@H (T)H tensor.HH Ha vectorHHHmust be HHH tensor HHHAn splitH@(AHBHPHL¿E1H5WHfLY@ HPV@ HALeMuFzHAL0MHHt H Y@LeMt6HEL9t!Lh@t HxX@LM9uH}LLeX@puPu L0Mu,dH}X@PtH`X@L0Mt:H8L9tQLh@t HxhX@LM9uH0L8MX@ELlX@H}HLHH0HdbHMuIEMAFt I~W@LW@H}Huv}HH}HufmHH0Hu$.HHPHu)3HH0Ht H8{W@HPHt HXcW@H}Ht H}QW@HT@ fUHAWAVAUATSHhHHIIHWHHEH{0LL+IGHEEEEW)EHEHHHt2HHHP H)HL1HRFJH}H肍IwIW H}HHPIIHEHD$HEHD$HEH$LELMLLD,I}tYHBH gB1AL$H}Ht H}U@HnWHH;E8LHh[A\A]A^A_]LIEHLxHX W)PHDž`L)t\IIHI9H|U@ILXLPKDH`H~LLHV@ILXH1HEL6HEHHcEHcUHHHЋMIcHHHfHHH@H1W1HHEH HcH9LPHHI )0HDž@LXM)HtiLHHH9L=T@IL8L0IH@MLH~LLLzU@ML8HH0g2HH0Ht H8S@H)ILDHH@HL<D9uAHffffff.LLQ@IIHuEIcHH@1LHHHHH@IHHHH@M$ILHQ@HIIuHHH;LLHHIcHHHH;WHHH@HE11HHELN$IcL9LPHM$W)0HDž@LXM)t[MIHI9=LQ@HH8H0JH@M~HLL2S@LH8HLDH00HH0Ht H8jQ@H4'IDD9uPtGHH@HHLf.LHQO@HIIuIcHIL;LIEHPHHXP@H}HQ@P@P@IH0V#H5aBH BHPL0жW)HDž 0KP@H (#T)H tensor.HH Ha vectorHHHmust be HHH tensor HHHAn splitH@(AH -BHPHLE1H5WHLO@H0M@ HPL@ IH0HIALeMuFzIAL0MIIt H &O@LeMt6HEL9t!HX@t HxO@HI9uH}LLeN@puPu L0Mu,dH}N@PtH`N@L0Mt:H8L9tQHX@t Hx~N@HI9uH0L8cN@ELN@H}HLII]IEHCt H{ -N@HN@H}HuIH}HulsDB@IH0Hu2-IH0Ht!H8M@HPHuIHPHt HXM@H}Ht H}qM@LJ@ fUHSPHH{Ht H{ CM@HBXHH{HCHHt[]M@[]fff.UHSPHH{Ht H{ L@HBXHH{HCHtL@HH[]L@UHAWAVSPI8L@HL=?BXL;H{L&HHLQHxYHHH[A^A_]L;IH{HCHt -KL@IH>L@L~I@ fDUHAWAVAUATSHIIHWHHEMuIEIEIEIE ffEHEEEaxisEHPHUHhEHPE1HuLhHDžPtCt H{yK@HqK@MeEt H}^K@I?CffEE -HEEsplifEtHhHULLgMHhHDžhHtCt H{J@HJ@Et H}J@HpIEIMH9tHQH)HHHs+1H&IE HWHH;E9FI?I!IpHH{H sf1fH|HwH)f1fofoDfoL o\0od@ffoTPffoD`foLpfHHuHt,HtHf.oVfofH HuffpNffH~L9tJff.H2HH9uIu H8x0HH9uHWHH;EuHĘ[A\A]A^A_]I@FI@H@Hh#H5лBH BH}Lh"jffPHDž`@H@H`foYTfPHust be >HH0Hvalues mHH(Hte. All HH H attribuHHH 'split'HHHvalue inHHHInvalid Hf@8 0@:LHBHuHPH@qDžLH5`WH H@YH@tIİLL}MuKIİLHhHIIPt H`G@L}Mt6HEL9t!HX@t HxG@HI9uH}LL}qG@EuEuHhHu&^H}NG@EtH}?G@HhHt:HpH9tMLx@t HxG@LL9uHhHpF@LtEH@G@I>Hu9@HIEuII>Hu#IEt H}F@I>Ht I}F@LC@ fUHAWAVSPI8F@HL=<XL;H{LHHL!HqYHHH[A^A_]L;IH{HCHt -F@IHF@LNC@ fDUHAWAVSPI8E@HL=;XL;H{L@HHLHBqYHHH[A^A_]L;IH{HCHt -E@IH~E@LB@ fDUHAWAVAUATSH8LLHIIHHWHHEH8HWHHHLH@H8LD@HHEEL-0WIEHHI@L8LC@L5WILHDž(HDž HDžHDžDž0I$HF@HHH起HLvHHHF@HHH肷HH0HB@HHHF@HHHHHE0HB@HHHHHL8Lt H C@HmB@H5WHHB@H8C@HٺWHH;EuHH8[A\A]A^A_]C@HHHL8Lt H C@HA@3HHH첽H䲽HܲHԲHH5¹WHHFA@H8NB@H覲HH87B@H菲ffffff.UHAWAVAUATSHXLLHHIHHWHHEH8HWHHHLH@H8LA@HHEEL5,WM~LI@L8L@@L-WILHDž(HDž HDžHDžDž0I$HC@HHH踴HE0HM(HU HuLMHD$HL$HT$H4$HHHHL)HHH3LL8Lt H @@H?@H5WHHB?@H8J@@HWHH;EuHHX[A\A]A^A_]@@HLL8Lt H A@@H!?@ H=HH5+WHH>@H8?@HHH8?@HUHAWAVAUATSPLMMIIIH6>@I]H:B@LHHLLIHB@LHHܲHEЋ0L>@HEHHA@LHH豲HEH0L>@HE HHA@LHH腲HE(H0L=@H[A\A]A^A_]HHHHH﮽H箽H߮H׮HϮffffff.UHAWAVAUATSH(HHIHHWHHEH8H<WHHHLH@H8L=@HHEEL%zWMl$LI@L8L<@L=4WILHDž(HDž HDžHDžDž0IHD@@HHHHH0HHHH -@@HHH̰HHH薶LL8Lt H *=@H -<@H5!WHH;@H8<@HvWHH;EuHH([A\A]A^A_]1=@HLL8Lt H <@H;@H蠬H蘬H萬HH5~WHH;@H8 -<@HbHH8;@HKUHAVSHPIHWHHE(<@Hþ H -<@HHCHCXHC`HCXHCHHC@HC8HC0HC(HC HCPHCpHCxHCpHChƃHǃfǃHǃHǃƃHHǃHǃHǃHǃHǃHǃHǃHǃHǃHHHǃHǃHǃǃǃHǃ H]MH5G@H}H>11HEH5BH/:H5gDH`;HH -HQH5w~@H<HH;E1HHH 4rXHMHHUHuHuIIFIF0INIVIF@H]HEHtHySH9@H:WHH;Eu LHP[A^]9@IH]HEHtH4SHz9@L6@ fUHAVSHPIH۰WHHE(T9@Hþ HJ9@HHCHCXHC`HCXHCHHC@HC8HC0HC(HC HCPHCpHCxHCpHChƃHǃfǃHǃHǃƃHHǃHǃHǃHǃHǃHǃHǃHǃHǃHHHǃHǃHǃǃǃHǃ H]荽H5D@H}H;11HNBH5PBHo7H5dDH8HH HQH5{@H9HH;.HHH toXHMH HUHuHuIIFIF0INIVIF@H]HEHtHPH6@HzWHH;Eu LHP[A^]>7@IH]HEHtHtPH6@L3@ fUHAVSHPIHWHHE(6@Hþ H6@HHCHCXHC`HCXHCHHC@HC8HC0HC(HC HCPHCpHCxHCpHChƃHǃfǃHǃHǃƃHHǃHǃHǃHǃHǃHǃHǃHǃHǃHHHǃHǃHǃǃǃHǃ H]ͺH5B@H}H*911H?H5BH4H5:bDH5HA H5x@H7HH;+HHH lXHMHHUHuHuIIFIF0INIVIF@H]HEHtHNHF4@HWHH;Eu LHP[A^]4@IH]HEHtHMH4@LA1@ fUHAWAVSPI(3@HL=o)XL;H{L0 HHLQH_YHHH[A^A_]L;IH{HCHt -{3@IHn3@L0@ fDUHAWAVSHHHIHƪWHHEIGIGIW)EHEH;q+W)EHEEEaxesEH}HULuHL#5Et H}2@H]HtHECaeH}HuHU1@HuHUHH9t9HFH9tH>HJHHHxH9tHH9uHH9H9HHH9LBI)DHt(Hfff.HH9tHXHHHuIruH9H98u(HyH98u0HyH98u8HyH98u@H H9uFfHxHHyH98tHxHHyH98tHxHHyH98tHxHH H9uHH9tHEHM9tLH]HEHtCt H{=1@H51@H}Ht H}#1@HWHH;Eu HH[A^A_]c1@IH]HEHt&Ct H{0@H IEt H}0@H}HuI?Hu(L-@ H}0@I?Ht II?HtI0@L-@ ffffff.UHSPHH{Ht H{S0@H%XHH{HCHHt[]-0@[]fff.UHSPHH{Ht H{0@H%XHH{HCHt/@HH[]/@UHAWAVAUATSHIHIH,WHHE1LrHW)EHEI}< HH+HuHLrH7HHHP H)HHHHH}HfHsHSH}謫HHpH`HUHzW)@HDžPL`HhL)tiLMIILH={H.@ILHL@KHPHML~LLH/@ILHH@1L HH@Ht HH+.@L+LkPHL8LxPM9Hx0HPhHtIxuCHΰH~d1LL,@H詰HIIH9|2H苰IHHx0HPILLH /@I$H`Ht Hhc-@H}Ht H}Q-@H̤WHH;EuLH[A\A]A^A_]-@H@*@$-@IH@#H5BH BH`L@MIW) ƅ $HDž0Hut is nuH)HAxes inpH!fDž1llƅ3AHBH`H L諕E1H5WHJnL,@Y,@IH@#H5ޢBH BH`L@O~W) HDž00+@H0(vQ) H tensor.HHH vector HHHust be aHHHtensor mHHHAn axes H@'AHBH`H L豔E1H5WHPmL+@ HALeMulHAL@MHHAL@MHH t H0*@LeMt6HEL9t!Lh@t Hx*@LM9uH}LLe*@Eu`u#L@Mu36H}z*@`tHpe*@L@MHHL9Lh@t Hx2*@LM9uH t H0 *@LeMt6HEL9t!Lh@t Hx)@LM9uH}LLe)@Eu`u L@Mu,dH})@`tHp)@L@Mt:HHL9tQLh@t Hxh)@LM9uH@LHM)@ELl)@H}HLHH}HHH@HuXHH@HtIHH(@H`Hu=GHH}HuDKHH}Hu6=HH}Hu(/HH`Ht Hh(@H}Ht H}}(@H%@ DUHAWAVAUATSHH՟WHHEHGHGHHFHH+HIM}IEIW)EHEM)Ht^HLHHH=L'@ILuIH]LL'@H]HLIL9uLmN1E1LIL9t1@I<LdLuIHM}IEL)HH9rLmH]HHLH&@LH}HMH9LHt\HH9t)H7HQHf.HHpH9t3HH9uHH9HHEHH9HPH9LAI)DHtHHH9tHXHHHuIruH2H90u(HrH90u0HrH90u8HrH90u@H H9uFfHpHHrH90tHpHHrH90tHpHHrH90tHpHH H9uHH9HEHEH11ffffff.IEH}H)HHH9sH9 uIHcH<tSHt;HcHI7IFI;FtWHHHIFHHML9rWff.IHcH<uHHHML9p*H4IFI;FuLžHMHHML9DH}Ht I}$@HkWHH;EuLH[A\A]A^A_]&%@$@IH0#H5YBH BBHHL05LcEIHLHBHEHBHEHÜBHEH $HHuHUHMLMHAHSBHHLHWE1H5MWHeLJ$@ H}W!@HAL0MHLHt H(#@L}Mt6HEL9t!Lh@t Hx#@LM9uH}LL}n#@huHu#L0Mu/gHxB#@HtHX-#@L0Mt:H8L9thLh@t Hx#@LM9uH0L8"@ELtL#@H}Ht iH}Hu`I>HuiH@ LHH}Ht H}"@LI>Ht4HH}HtHLH}HtH}V"@I>HtI~E"@H@ ffff.UHAWAVAUATSH8LLHIIHHwWHHEH8HWHHHLH@H8L[!@HHEEL-WIEHHI@L8L_ @L5WILHDž(HDž HDžHDžDž0I$H#@HHHuI7H@HHH#@HHHBHH0H@HHHF#@HHHHuHȯHHH™HHL8Lt H O @H/@H5FWHH@H8@HWHH;EuHH8[A\A]A^A_]V @HHHL8Lt H @H@3H辏H趏H讏H規H螏H薏HH5WHH@H8@HhHH8@HQUHAWAVSPI(3@HL=XL;H{LHHLHKYHHH[A^A_]L;IH{HCHt -@IH@L@ fDUHAWAVSPI(@HL=/XL;H{LHHLHJYHHH[A^A_]L;IH{HCHt -;@IH.@Ln@ fDUHAWAVAUATSHIHWHHEп(@Hþ H@HHCHCXHC`HCXHCHHC@HC8HC0HC(HC HCPHCpHCxHCpHChƃHǃfǃHǃHǃƃHHǃHǃHǃHǃHǃHǃHǃHǃHǃHHHǃHǃHǃǃǃHǃ H]GHHMHPIHXKH`FHhLHpLJHxKIMINIGHW)EHEX@HEHHXHMHHHHPHPHXHPH`HPHhHP HpHP(HxHP0Lh8Lp@LxHHXPHMH5(@H}HUHKH5BAHH$H5BHH5HDHAHH HQH5X_@HaHH;&HHH SXHMH --HUHuHuI$ID$ID$0IL$IT$ID$@H}Ht H}@H]HEHtHB4H@HWHH;EuLHĘ[A\A]A^A_]@CIH}HuH]HEHu:L@ H},@H]HEHtIH]HEHtH3H@L5@ ffff.UHAWAVAUATSHIHBWHHEп(@Hþ H@HHCHCXHC`HCXHCHHC@HC8HC0HC(HC HCPHCpHCxHCpHChƃHǃfǃHǃHǃƃHHǃHǃHǃHǃHǃHǃHǃHǃHǃHHHǃHǃHǃǃǃHǃ H]TCHHHIHP|EHXGH`dBHhXHHp FHxFIIIpJICHW)EHEX@HEHHXHMHHHHPHPHXHPH`HPHhHP HpHP(HxHP0Lh8Lp@LxHHXPHMH5M$@H}HUYHGH5o>AHHH5zBHH5[DDHHA H5[@H(HH; 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vectorHHHmust be HHH tensor HHHAn splitH@(AHܾBHPHLE1H5WHF¾LJ@ HPG@ HALeMuFzHAL0MHHt H J@LeMt6HEL9t!Lh@t HxI@LM9uH}LLeI@puPu L0Mu,dH}I@PtH`I@L0Mt:H8L9tQLh@t HxhI@LM9uH0L8MI@ELlI@H}HLHH0HdbHMuIEMAFt I~H@LH@H}Huv}HH}HufmHH0Hu$.HHPHu)3HH0Ht H8{H@HPHt HXcH@H}Ht H}QH@HE@ fUHAWAVAUATSHHHIIHWHHEH{%LL+IGHEEEEW)EHEHH׊Ht2HHHP H)HL1H2mJH}H2IwIW H}HHPIIHEHD$HEHD$HEH$LELMLLD\I}tYHBH XB1AL#H}Ht H}F@HWHH;ELHĘ[A\A]A^A_]LIEHLxLh W)PHDž`M)t[MIHI9nL|F@HHXHPJH`M~HLLG@LHXH;HEHEHHcEHcMHHHHUIcHHH8ƒHpHH)HhHHH@HpHHHxHHHHH11HfDHEHL$IcL9,LPHM$W)0HDž@LXM)t\LHHH9LD@IL8L0IDH@M~LLLDF@ML8HHH0Z'IH0Ht H8}D@LGIDHHL4D9u1LLHE@IcHHH;IcL$HHLs1H!K dHHHHXHH`1Lffffff.LLLE@K<,HJ40LD@H`J<(K47LD@HJ<(HpJ40LD@HLxLXH9huHtZHHHHL4HHHLLLHLVD@MLIuHHHHH;BBE1E1HEN,IcL9cHPHL,W)0HDž@LXI)ttHLMIHI9 L#B@HH8H0JH@MLH~HLcC@LH8HDH0$HH0Ht H8A@HlDD9uHJ4HHB@IcIIL;LIEHPH5HX.A@H}H%)wA@A@H0l>@A@IH0#H5ӲBH FBHPL0ݿW)HDž 0@@H (T)H tensor.HH Ha vectorHHHmust be HHH tensor HHHAn splitH@(AH|BHPHLG߿E1H5}WH淾LZ@@ HPd=@ HALeMuFzHAL0MHHt H ?@LeMt6HEL9t!Lh@t Hx?@LM9uH}LLeq?@puPu L0Mu,dH}H?@PtH`3?@L0Mt:H8L9tQLh@t Hx?@LM9uH0L8>@EL ?@H}HLHH0HdbHMuIEMAFt I~>@Ly>@H}Huv}HH}HufmHH0Hu$.HHPHu)3HH0Ht H8>@HPHt HX>@H}Ht H}=@H1;@ fUHAWAVAUATSHHHIIHUWHHEH{LL+IGHEEEEW)EHEHHwHt2HHHP H)HL1HbJH}HҫIwIW H}蟹HHPIIHEHD$HEHD$HEH$LELMLLDI}tYHBH sNB1AL#H}Ht H}<@H.WHH;ELHĘ[A\A]A^A_]LIEHLxLh W)PHDž`M)t[MIHI9^L<@HHXHPJH`M~HLLg=@LHXHmaHEHEHHcEHcMHHHHUIcHHH(ƒHpHH)HhHHH@HpHHHxHHHHH11Hf.HEHL,IcL9LPHM,W)0HDž@LXM)t[LHHH9L:@IL8L0IH@M~LLL;@ML8HHH0IH0Ht H8:@L迿HDHHL4D9u2HLHd;@IcHHH;IcL$HHHs1HK dHHHHXHH`I1LLLL:@K<,HJ40L:@H`J<(K47L:@HJ<(HpJ40Lz:@HLxLXH9huHtZHHHHL4HHHLLLHL:@MLIuHHHHH;RBE1E1HEN,IcL9cHPHL,W)0HDž@LXI)ttHLMIHI9 L7@HH8H0JH@MLH~HL9@LH8HDH0/HH0Ht H8R7@HDD9uHJ4HH8@IcIIL;LIEHPHEHX6@H}H59'7@6@H04@6@IH0Z#H5BH BHPL0ҿW)HDž 0_6@H (T)H tensor.HH Ha vectorHHHmust be HHH tensor HHHAn splitH@(AH,BHPHLԿE1H5-WHL +6@ HP3@ HALeMuFzHAL0MHHt H `5@LeMt6HEL9t!Lh@t Hx;5@LM9uH}LLe!5@puPu L0Mu,dH}4@PtH`4@L0Mt:H8L9tQLh@t Hx4@LM9uH0L84@EL4@H}HLHH0HdbHMuIEMAFt I~14@L)4@H}Huv}HH}HufmHH0Hu$.HHPHu)3HH0Ht H83@HPHt HX3@H}Ht H}3@H0@ fUHAWAVAUATSHHHIIHWHHEH{ELL+IGHEEEEW)EHEHH'vHt2HHHP H)HL1HXJH}H股IwIW H}OHHPIIHEHD$HEHD$HEH$LELMLLDI}tYH^BH #DB1AL7#H}Ht H}C2@HޖWHH;ELHĈ[A\A]A^A_]LIEHLxLh W)PHDž`M)t[MIHI9L1@HHXHPJH`M~HLL3@LHXHMHEHEHHcEHcMHHHUIcHHH[ƒHpHH)HxHIHHHH HHHH1E1fLHEHL,IcL9eLPHM,W)0HDž@LXM)t[LHHH9Lc0@IL8L0IH@M~LLL1@ML8HHH0IH0Ht H8/@LᖿILDHN48D9u;LLH-1@McMHH;fffff.IcHHs,E1LH[ffffff.HH @HH HhHHpME1fffff.LLHHo0@HJ40J<+HX0@HJ40HpJ<(H:0@HJ40HJ<(H0@ILLhL9xyLHttLMMMLMLHfffff.LLL/@MLHuHMHH;)iHLMHH;CE1E1HEN,IcL9cHPHL,W)0HDž@LXI)ttHLMIHI9 LS-@HH8H0JH@MLH~HL.@LH8HDH0HH0Ht H8,@H̓DD9uHJ4!HH%.@IcIIL;LIEHPHHX^,@H}H ,@6,@H0)@?,@IH0#H5BH BHPL0DȿW)HDž 0+@H (T)H tensor.HH Ha vectorHHHmust be HHH tensor HHHAn splitH@(AHBHPHLwʿE1H5WHL+@ HP(@ HALeMuFzHAL0MHHt H *@LeMt6HEL9t!Lh@t Hx*@LM9uH}LLe*@puPu L0Mu,dH}x*@PtH`c*@L0Mt:H8L9tQLh@t Hx8*@LM9uH0L8*@EL<*@H}HLHH0HdbHMuIEMAFt I~)@L)@H}Huv}HH}HufmHH0Hu$.HHPHu)3HH0Ht H8K)@HPHt HX3)@H}Ht H}!)@Ha&@ fUHAWAVAUATSHhHHIIHWHHEH{LL+IGHEEEEW)EHEHHkHt2HHHP H)HL1HNJH}HIwIW H}ϤHHPIIHEHD$HEHD$HEH$LELMLLD,I}tYHޙBH 9B1AL#H}Ht H}'@H^WHH;E8LHh[A\A]A^A_]LIEHLxHX W)PHDž`L)t\IIHI9HL'@ILXLPKDH`H~LLH(@ILXH|9HEL6HEHHcEHcUHHHЋMIcHHHfHHH@H1W1HHEH HcH9LPHHI )0HDž@LXM)HtiLHHH9L &@IL8L0IH@MLH~LLLJ'@ML8HH0gHH0Ht H8%@H41ILDHH@HL<D9uAHffffff.LLa#@IIHuEIcHH@1LHHHHH@IHHHH@M$ILH"@HIIuHHH;LLHHIcHHHH;WHHH@HE11HHELN$IcL9LPHM$W)0HDž@LXM)t[MIHI9=L#@HH8H0JH@M~HLL%@LH8HLDH0HH0Ht H8:#@H.IDD9uPtGHH@HHLf.LH!!@HIIuIcHIL;LIEHPHHX"@H}H"@a"@{"@IH0#H5?BH ]BHPL0耾W)HDž 0"@H (ST)H tensor.HH Ha vectorHHHmust be HHH tensor HHHAn splitH@(AHBHPHLE1H5WHRL!@H0@ HP@ IH0HIALeMuFzIAL0MIIt H @LeMt6HEL9t!HX@t Hx @HI9uH}LLe @puPu L0Mu,dH} @PtH`y @L0Mt:H8L9tQHX@t HxN @HI9uH0L83 @ELR @H}HLII]IEHCt H{@H@H}HuIH}HulsDB@IH0Hu2-IH0Ht!H8@HPHuIHPHt HXS@H}Ht H}A@L@ fUHSPHH{Ht H{ @HXHH{HCHHt[]@[]fff.UHSPHH{Ht H{ @H~XHH{HCHt@HH[]@UHAWAVSPI8@HL=/XL;H{LHHLQH1YHHH[A^A_]L;IH{HCHt +@IH@LN@ fDUHAWAVAUATSHIIHWHHEMuIEIEIEIE ffEHEEEaxisEHPHUHhHPE1HuLhHDžPtCt H{I@HA@MeEt H}.@I?ffEE +HEEsplifEtHhHULLg#HhHDžhHtCt H{@H@Et H}@HpIEIMH9tHQH)HHHs+1H&IE HWHH;E9FI?I!IpHH{H sf1fH|HwH)f1fofoDfoL o\0od@ffoTPffoD`foLpfHHuHt,HtHf.oVfofH HuffpNffH~L9tJff.H2HH9uIu H8x0HH9uHWHH;EuHĘ[A\A]A^A_]h@@H@Hh#H5BH BH}Lh"ffPHDž`@@H`foJTfPHust be >HH0Hvalues mHH(Hte. All HH H attribuHHH 'split'HHHvalue inHHHInvalid Hf@8 0@:LHjBHuHPH@!DžLH5PWHH@)@tIİLL}MuKIİLHhHIIPt H`@L}Mt6HEL9t!HX@t Hx[@HI9uH}LL}A@EuEuHhHu&^H}@EtH}@HhHt:HpH9tMLx@t Hx@LL9uHhHp@LtEH@@I>Hu9@HIEuII>Hu#IEt H}{@I>Ht I}j@L@ fUHAWAVSPI8S@HL=WL;H{LHHL!Hr+YHHH[A^A_]L;IH{HCHt +@IH@L@ fDUHAWAVSPI8@HL=oWL;H{L@HHLH*YHHH[A^A_]L;IH{HCHt +[@IHN@L@ fDUHAWAVAUATSH8LLHIIHH{WHHEH8HyWHHHLH@H8Lk@HHEEL- {WIEHHI@L8Lo@L5zWILHDž(HDž HDžHDžDž0I$H@HHHeHL6HHH@HHH2HH0H@HHHV@HHHHE0HT@HHHĿHHL8Lt H ]@H=@H5tyWHH@H8@HyWHH;EuHH8[A\A]A^A_]d@HHHL8Lt H @H@3H謺H褺H蜺H蔺H茺H脺HH5xWHH@H8@HVHH8@H?ffffff.UHAWAVAUATSHXLLHHIHHxWHHEH8HvWHHHLH@H8Lg@HHEEL5xWM~LI@L8Lr@L-wWILHDž(HDž HDžHDžDž0I$H@HHHhHE0HM(HU HuLMHD$HL$HT$H4$HHHHL)HHHLL8Lt H @Hw@H5vWHH@H8@HwWHH;EuHHX[A\A]A^A_]@HLL8Lt H @H@ HHH5vWHH@H8@H迷HH8p@H訷UHAWAVAUATSPLMMIIIH6\@I]H +@LHH谺LL腠IH@LHH茺HEЋ0L@HEHH@LHHaHEH0L@HE HH@LHH5HE(H0L@H[A\A]A^A_]H迶H跶H诶H觶H蟶H藶H菶H臶Hffffff.UHAWAVAUATSH(HHIHHtWHHEH8H,sWHHHLH@H8L@HHEEL%jtWMl$LI@L8L@L=$tWILHDž(HDž HDžHDžDž0IH@HHH趸HH0HЪHHH@HHH|HHHFLL8Lt H @H @H5sWHHu @H8}@HfsWHH;EuHH([A\A]A^A_]@HLL8Lt H t@HT @HPHHH@HH5nrWHH @H8 @HHH8 @HUHAVSHPIHrWHHE( @Hþ H @HHCHCXHC`HCXHCHHC@HC8HC0HC(HC HCPHCpHCxHCpHChƃHǃfǃHǃHǃƃHHǃHǃHǃHǃHǃHǃHǃHǃHǃHHHǃHǃHǃǃǃHǃ H]MH5m@H}H11HH5BH/H559DH`HH +HQH5GP@HHH;EHHH $1XHMHHUHuHuIIFIF0INIVIF@H]HEHtH9%H @H*pWHH;Eu LHP[A^] @IH]HEHtH$HJ @L@ fUHAVSHPIHoWHHE($ @Hþ H @HHCHCXHC`HCXHCHHC@HC8HC0HC(HC HCPHCpHCxHCpHChƃHǃfǃHǃHǃƃHHǃHǃHǃHǃHǃHǃHǃHǃHǃHHHǃHǃHǃǃǃHǃ H]荓H5@H}H11HNH5.BHo H5u6DHHH HQH5M@HHH;HHH d.XHMH HUHuHuIIFIF0INIVIF@H]HEHtHy"H@HjmWHH;Eu LHP[A^] @IH]HEHtH4"H@L@ fUHAVSHPIH mWHHE(d@Hþ HZ@HHCHCXHC`HCXHCHHC@HC8HC0HC(HC HCPHCpHCxHCpHChƃHǃfǃHǃHǃƃHHǃHǃHǃHǃHǃHǃHǃHǃHǃHHHǃHǃHǃǃǃHǃ H]͐H5@H}H*11HH5n}BH +H53DH HA H5J@H HH;HHH +XHMHHUHuHuIIFIF0INIVIF@H]HEHtHH@HjWHH;Eu LHP[A^]U@IH]HEHtH{H@L@ fUHAWAVSPI(@HL=_WL;H{L0HHLQHjYHHH[A^A_]L;IH{HCHt +K@IH>@L~@ fDUHAWAVSHHHIHiWHHEIGIGIW)EHEH;qW)EHEEEaxesEH}HULuHL# Et H}@H]HtHECaeH}HuHU@HuHUHH9t9HFH9tH>HJHHHxH9tHH9uHH9H9HHH9LBI)DHt(Hfff.HH9tHXHHHuIruH9H98u(HyH98u0HyH98u8HyH98u@H H9uFfHxHHyH98tHxHHyH98tHxHHyH98tHxHH H9uHH9tHEHM9tL`H]HEHtCt H{ @H@H}Ht H}@HgWHH;Eu HH[A^A_]3@IH]HEHt&Ct H{@H IEt H}@H}HuI?Hu(L? H}u@I?Ht II?HtIW@L? ffffff.UHSPHH{Ht H{#@HWHH{HCHHt[]@[]fff.UHSPHH{Ht H{@HWHH{HCHt@HH[]@UHAWAVAUATSHIHIHfWHHE1LDHW)EHEI}<HH+HuHLHDH7HHHP H)HHH&HH}HoHsHSH}l}HHpH`HUHzW)@HDžPL`HhL)tiLMIILH={Hv@ILHL@KHPHML~LLH@ILHH@1LHH@Ht HH?L+LkPHL8LxPM9Hx0HPhHtIxuCH莂H~d1LL?HiHIIH9|2HKIHHx0HPILLH@I$H`Ht Hh3?H}Ht H}!?HcWHH;EuLH[A\A]A^A_]W?H@Q??IH@菬#H5uBH uBH`L@MW) ƅ $HDž0Hut is nuH)HAxes inpH!fDž1llƅ3AHuBH`H L[E1H5WHuLn?)?IH@ī#H5tBH tBH`L@O.W) HDž00?H0(!CQ) H tensor.HHH vector HHHust be aHHHtensor mHHHAn axes H@'AHtBH`H LaE1H5WHuLt? HALeMulHAL@MHHAL@MHH t H0?LeMt6HEL9t!Lh@t Hx?LM9uH}LLes?Eu`u#L@Mu36H}J?`tHp5?L@MHHL9Lh@t Hx?LM9uH t H0?LeMt6HEL9t!Lh@t Hx?LM9uH}LLe?Eu`u L@Mu,dH}x?`tHpc?L@Mt:HHL9tQLh@t Hx8?LM9uH@LH?EL<?H}HLHH}HHH@HuXHH@HtIHH?H`Hu=GHH}HuDKHH}Hu6=HH}Hu(/HH`Ht Hh_?H}Ht H}M?H? DUHAWAVAUATSHH^WHHEHGHGHHFHH+HIM}IEIW)EHEM)Ht^HLHHH=L?ILuIH]LL?H]HLIL9uLmN1E1LIL9t1@I<LLuIHM}IEL)HH9rLmH]HHLHO?LH}HMH9LHt\HH9t)H7HQHf.HHpH9t3HH9uHH9HHEHH9HPH9LAI)DHtHHH9tHXHHHuIruH2H90u(HrH90u0HrH90u8HrH90u@H H9uFfHpHHrH90tHpHHrH90tHpHHrH90tHpHH H9uHH9HEHEH11ffffff.IEH}H)HHH9sH9 uIHcH<tSHt;HcHI7IFI;FtWHHHIFHHML9rWff.IHcH<uHHHML9p*H4IFI;FuL;HMHHML9DH}Ht I}?H[[WHH;EuLH[A\A]A^A_]??IH0?#H57mBH nBHHL05詒LcEIHLHnBHEHnBHEHnBHEH $HHuHUHMLMHAH1nBHHLHE1H5=|WHmL? H}'?HAL0MHLHt H(}?L}Mt6HEL9t!Lh@t HxX?LM9uH}LL}>?huHu#L0Mu/gHx?HtHX?L0Mt:H8L9thLh@t Hx?LM9uH0L8?ELtL?H}Ht iH}Hu`I>HuiH? 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UHAWAVAUATSHHIHVHHEL- WM,$I|$cH$SXI$W)pƅp +HEDžquppefDžurHXHpHMH;HXHDžXHtCt H{J=?HB=?pt H}0=?Hu2H}AD$HVHH;EuHĨ[A\A]A^A_]Y=?=?H0HX"H5AH AHpLX +پH@H<HAHpH0H۾Dž<H5VH<H0<? Iǰ<HXHII@t HP<?LuMt6HEL9t!HX@t Hx;?HI9uH}LLu;?Eupu HXHu)aH};?ptH};?HXHt:H`H9tELp@t Hxz;?LL9uHXH`_;?<t(H0z;?HIpt H}.;?M,$I|$ID$Ht;?LR8? f.UHAVSI:?HHLH[A^]IH:?L 8? UHAWAVAUATSHxIHEVHHEп(:?Hþ H:?HHCHCXHC`HCXHCHHC@HC8HC0HC(HC HCPHCpHCxHCpHChƃHǃfǃHǃHǃƃHHǃHǃHǃHǃHǃHǃHǃHǃHǃHHHǃHǃHǃǃǃHǃ H]ghImIjIiHW)EHE 8?HEHH HML8L`LhHXHM hIDmI<jItiHW)`HDžp 8?H`HH HpL8L`LhHXHhH5gE?H}HUH`BH5AH-<H53eCH^=HA H5L|?H>HH;J3HHH )]WHMHNHUHuHuIIFIF0INIVIF@H`Ht Hh7?H}Ht H}7?H]HEHtHQHj7?HVHH;EuLHx[A\A]A^A_]7?IH`Hu$H}Hu>H]HEHu]LZ4? Hh7?H}Ht IH}HtH}6?H]HEHtIH]HEHtHWPH6?L3? DUHAWAVSH8HIIH#VHHE1HyIH@0HɃwwHHc HH}LH.1H}LHF H}LH<$H}LHgHEIHVHH;EuuLH8[A^A_]HEHnAHEH]HuHUHH}оH}"HEIHEEtH}5?H(VHH;Et5?HEt#H}f5?IH2? HIH2? 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LIHPHt HX!?IHpH") eIH}H7cIHPHHX ?HpHIHHIH HIHHIHpHHx?H}Hu|IHpHt Hx?H}Ht\I<$?HHuS].IH}H1H}?H H$+IH}Ht H}[?HHt HC?LMtJHL9fHXHxHt Hx?HI9uHL?HHSH}HuH HuOL? H}?H Ht.LIHH=D%IH HtH(j?L? IH Ht H(E?LPMtLHXL9t]ffffff.HXHxHt Hx?HI9uHPLX?HxHplNL? 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UHAVSHIHt5H3LHsLH{ Ht H{(S>H[A^]G>[A^]@UHAVSHIHt#H3LHsLH[A^] >[A^]fDUHAWAVAUATSH(MLEIIHHCHCHLHMHi(ILHuZ%ILIHHvMMMIHEIHHE1L}HMLuE1ffff.I4$LHCH;CtHHHHCIIM9HvIIM9HMHLuLuL}I9H([A\A]A^A_]IH;Hu!IH;Hu IH;Ht H{赟>L> ffff.UHAWAVAUATSH(IH%VHHEMfMM~LLVM9t!M)I|$ M\$(L9uQ}ffff.ID$ I;D$(MM'MuMffff.II|$ M\$(L9t.MI)1fDI9t{I4HH9|nH9| HI9uI)1ff.I9t+H4IH9|H9|RHI9uGfffff.M|$ID$Hm$ff.I$MHPMfMIHt!1H VH H;MuiH([A\A]A^A_]H}LbHuHFHLfI7IHHtII7I~辘IFHEH }VH H;Mt->ffffff.UHAWAVAUATSPIHIH@襝>IM/I_AGMI$IE0IE(IE H{H+;tXLuI IILH=u_Q>IHMLa(La KIIF0H3H[H)H~LH藞>IMf(IF8AGLH[A\A]A^A_]LI> II}Ht HEHx(Ȝ>IH}踜>L> UHAVSHIHt5H3LHsLH{ Ht H{(s>H[A^]g>[A^]@UHAWAVAUATSHHVHHEIIF0xuFII^PILHHVHH;EuHHHHĨ[A\A]A^A_]I>>IHPI"H5 +?H !AHhLP7H@ ?HEHL ?HEI0H@ ?HEH8HuHUHMHM9ýAH +?HhLHm:E1H5!VH L耛> IALPMII8t HH>LmMt6HEL9t!HX@t HxК>HI9uH}LLm趚>Euhu LPMu,dH}萚>htHx{>LPMt:HXL9tEHX@t HxP>HI9uHPLX5>EtLX>Lh> Lff.UHAWAVAUATSHHUHHEIIF0xuFII^PILHHdUHH;EuHHHHĨ[A\A]A^A_]>觙>IHPBG"H5r?H AHhLP5H?HEH?HEI0H?HEH8HuHUHMHMAH?HhLH8E1H5SVHL0> IALPMII8t HH襘>LmMt6HEL9t!HX@t Hx耘>HI9uH}LLmf>Euhu LPMu,dH}@>htHx+>LPMt:HXL9tEHX@t Hx>HI9uHPLX>EtL>L> Lff.UHAVSHIHt#H3LHsLH[A^]鉗>[A^]fDUHAWAVAUATSHHLMLEIIHuHGHGH}HLLHELLHILeLuM>IFL)L9H]sMMvL>IM)MK\5M~LLL]>LuM.I^MfMH]tL跖>HLmPH}EHEHMHHEL1HM1LmE1E1@HEL8MMfIFI9t)AA$IFHH9]fffff.I6I)LHH)ILH?H9wHH9HBHHjHuI>IHuMAC&KT&M~LmLIIL/>LLmLHEL0IIVMnHLmtH|>HH9]LmHMHH9MHH[A\A]A^A_]L詒> IHEH8Ht Hx#>Lc> ff.UHAWAVAUATSH(IHUHHEMfMM~LLVM9t!M)I|$ M\$(L9uQ}ffff.ID$ I;D$(MM'MuMffff.II|$ M\$(L9t.LH)1fDI9t{E,A8|mD8|HH9uI)1ff.I9t+4A@8|@8|QHI9uGfffff.M|$ID$Hm$ff.I$MHPMfMIHt!1H VUH H;MuiH([A\A]A^A_]H}LbHuHFHLfI7IHHtII7I~.IFHEH UH H;Mt蝓>ffffff.UHAWAVAUATSPIHIH@>IM'I_AGMuID$0ID$(ID$ I^I+tPHEI HxbHɒ>IHELh(Lh LHX0I6I^H)H~LH>HEILh(H@8AGLH[A\A]A^A_]L> HI<$Ht HEHx(@>IH}0>Hp> UHAVSHIHt5H3LHsLH{ Ht H{(>H[A^]ב>[A^]@UHAWAVAUATSHHUUHHEIIF0xuEII^PIL^H 'UH H;MuH@HHHĨ[A\A]A^A_]躑>h>IHP?"H53?H AHhLPm-H?HEH?HEI0H?HEH8HuHUHMHM誸AHE?HhLH/E1H5VH}L> IALPMII8t HHf>LmMt6HEL9t!HX@t HxA>HI9uH}LLm'>Euhu LPMu,dH}>htHx>LPMt:HXL9tEHX@t Hx>HI9uHPLX規>EtLɏ>Lٌ> Lfff.UHAWAVAUATSPIII^IHAt MgM IDLuMf.C tLs( -fDM9LIGHt9tH{0L觾>u5#H{ HL菾>uffff.1M9BHKHILIHHvLuM9t=AE tI](I9LHGHtt*Iu0L>u-I9sMLH[A\A]A^A_]Iu HL>tx@UHAWAVATSHIHIH 3VH HMHuHIIHt&1H3VHH;EHH[A\A^A_]ÿ@>HI4$H{ >HC8HEHCHHCIIHHtII7HI~蒀IFH3VHH;E{>IHv>L趸> fffff.UHAWAVAUATSH(LwHMt*HuȊH}t$HBHEHRHUE~ Au;HH>HHUHEE~ Au$@H}IE~ AtMf(fDDIN H]L9IGHt3AHMt Mn0LiH}LH >HMtx 8L9esILH{\fHt;AtMn0HILHuH踻>tyI~IFH3 L9ewHEL0H}HEL0LHEL0HH([A\A]A^A_]UHAWAVAUATSHHE1VHHEIIF0xuEII^PIL~<H 1VH H;MuH@HHHĨ[A\A]A^A_]ʹ>x>IHP#g"H5C(?H &@AHhLPH(?HEH(?HEI0H(?HEH8HuHUHMHMڪAHU(?HhLH"E1H5RVHL> IALPMII8t HHv>LmMt6HEL9t!HX@t HxQ>HI9uH}LLm7>Euhu LPMu,dH}>htHx>LPMt:HXL9tEHX@t Hxѷ>HI9uHPLX趷>EtLٷ>L> Lfff.UHAVSHIHt2H3LHsLC t H{0V>H[A^]J>[A^]UHAWAVAUATSH(LMLEIIHIIFIFILL>ILL;ILILNMMHEIHH @HEIHH@HE1LeHuHMIE1ffffff.H3LI~I;~t 蕴>IFIIM9LOIIM9HuHHMHMLeI9H([A\A]A^A_]IM&MuOIM&Mu BIM&Mt7IFL9t8HX@t Hx˵>HI9uI>Mf践>L> Lf.UHAWAVAUATSHXHMH9HGHEH)HBHEHE1H}IHUHufL9[Bt*@tJL*E>AuDE>AtI^H9ILGMt|At&HEJ|(@HM@uu%HEJ4(DHEJ<(@HM@utJ4*H}HuL$>HUHMutHuH}yIDH9Mtb@tJ<*AuHEJ4(HEJ<(AtHEJt(LIH豵>HLHUty3ffffff.H9wJD*IIHH;EHu1HX[A\A]A^A_]ff.UHAWAVAUATSH(IHIH/+VHHEMt$MtxLmLeM|$LeLm -IH;HsIV IN(MtIMHufI~ Iv(HHKMtoM~IFHu`Mt$MIHu`@>HIuH{ HC8HCHLsII$HHt@I$I7:MLeLmIHt1H-*VHH;Eu6HH([A\A]A^A_]HI|$uwID$H)VHH;EtDz>IH\>L蜯> @UHAWAVSPIIMtLI7LIwLMw MtCIG(L9t.fHX@t Hx>HI9uI H[A^A_]LMw(ֱ>LH[A^A_]ı>fDUHAVSHPIH+)VHHE(褱>Hþ H蚱>HHCHCXHC`HCXHCHHC@HC8HC0HC(HC HCPHCpHCxHCpHChƃHǃfǃHǃHǃƃHHǃHǃHǃHǃHǃHǃHǃHǃHǃHHHǃHǃHǃǃǃHǃ H]H}11赺H5H5>HH+H5.7AH輯H5GBHHH -HQH5>H HH;ҦHHH VHMH&HUHuHuIIFIF0INIVIF@H]HEHtHHL>H&VHH;Eu LHP[A^]苯>IH]HEHtHH>LG> ffffff.UHAVSHPIH[&VHHE(Ԯ>Hþ Hʮ>HHCHCXHC`HCXHCHHC@HC8HC0HC(HC HCPHCpHCxHCpHChƃHǃfǃHǃHǃƃHHǃHǃHǃHǃHǃHǃHǃHǃHǃHHHǃHǃHǃǃǃHǃ H]H}11H2H5M>HH[H5^4AHH5wBHHH HQH54>H=HH;HHH VHMHFHUHuHuIIFIF0INIVIF@H]HEHtH6H|>H#VHH;Eu LHP[A^]軬>IH]HEHtHH7>Lw> ffffff.UHAVSHPIH#VHHE(>Hþ H>HHCHCXHC`HCXHCHHC@HC8HC0HC(HC 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H0?>LeMt6HEL9t!Lh@t Hx>LM9uH}LLe>EuEu L@Mu-'H}ڟ>EtH}˟>L@MHHL9Lh@t Hx蘟>LM9uH t H0s>LeMt6HEL9t!Lh@t HxN>LM9uH}LLe4>EuEuL@Mu&^H}>EtH}>L@Mt:HHL9tTLh@t Hxמ>LM9uH@LH輞>EL۞>H`HLHAL`MHH@t HPV>LeMt6HEL9t!Lh@t Hx1>LM9uH}LLe>EuEuL`Mu&^H}>EtH}>L`Mt:HhL9tILh@t Hx躝>LM9uH`Lh蟝>EL辝>HΚ> LHH H+HH@HHH HH(3>H@HufpHH`HumwHH`Hu\fHH@Hu3=HH`Hu:DHH`Hu)3HH@Ht HH赜>H`Ht Hh蝜>Hݙ> DUHAWAVAUATSHIHVHHEW)EHHMI>tDH#AH t?1A]L&J"HVHH;ELH[A\A]A^A_]ILeHEL8LxPM,$Ml$PM9t{I|$0HPhHtAxu;ILH~T1LL>HLIIH9|*I|$qHI|$0HPHLLH>IHVHH;E4诛>IIIHtCt H{.>H&>Lf> fffff.UHSPHH{Ht H{>HVHH{HCHHt[]͚>[]fff.UHSPHH{Ht H{裚>H>VHH{HCHt胚>HH[]u>UHAWAVSPI(c>HL=VL;H{LsHHLQHWHHH[A^A_]L;IH{HCHt ->IH>L.> fDUHAWAVAUATSHHIH?VHHEID$ID$I$H;uvW)EHEEEaxesEHhHUHL譛HhHDžhHtCt H{5>H->Et H}>Hu'HVHH;EuHĘ[A\A]A^A_]R>>IHhF"H5!AH !AH}Lh(W)PHDž`0裘>H`(kR)PHte valueHHHttributeHHH'axes' aHHHInvalid HHHMissing/H@&LH!AHuHPLYDžLH5H1VHټLE>iIǰLLmMuKIǰLHhHIIPt H`蜗>LmMt6HEL9t!HX@t Hxw>HI9uH}LLm]>EuEuHhHu&^H}:>EtH}+>HhHt:HpH9tJLh@t Hx>LL9uHhHp>Lt8L>I<$Hu08HIEtH}貖>I<$HuII<$Ht -I|$葖>Lѓ> fUHAWAVSPI(s>HL=VL;H{LoHHLaHWHHH[A^A_]L;IH{HCHt - >IH>L>> fDUHAWAVSPI(>HL=oVL;H{L0oHHLHWHHH[A^A_]L;IH{HCHt -{>IHn>L讒> fDUHAVSHPIH VHHE(D>Hþ H:>HHCHCXHC`HCXHCHHC@HC8HC0HC(HC HCPHCpHCxHCpHChƃHǃfǃHǃHǃƃHHǃHǃHǃHǃHǃHǃHǃHǃHǃHHHǃHǃHǃǃǃHǃ H]ݾ H5͠>H}HjH5-AHkH5BH蜔HHHQH5>H輕HH;聊HHH pVHMHeHUHuHuIIFIF0INIVIF@H]HEHtH赬H>Hv -VHH;Eu LHP[A^]:>IH]HEHtHpH趒>L> fffff.UHAVSHPIH -VHHE(脒>Hþ Hz>HHCHCXHC`HCXHCHHC@HC8HC0HC(HC HCPHCpHCxHCpHChƃHǃfǃHǃHǃƃHHǃHǃHǃHǃHǃHǃHǃHǃHǃHHHǃHǃHǃǃǃHǃ H]] H5 >H}H誙H5mAH諐H56BHܑHHHQH5>HHH;HHH VHMHHUHuHuIIFIF0INIVIF@H]HEHtHH;>HVHH;Eu LHP[A^]z>IH]HEHtH谩H>L6> fffff.UHAVSHPIHKVHHE(ď>Hþ H躏>HHCHCXHC`HCXHCHHC@HC8HC0HC(HC HCPHCpHCxHCpHChƃHǃfǃHǃHǃƃHHǃHǃHǃHǃHǃHǃHǃHǃHǃHHHǃHǃHǃǃǃHǃ H]] H5M>H}HH5AHH5vBHHHHQH53>H<HH;HHH VHMHu<HUHuHuIIFIF0INIVIF@H]HEHtH5H{>HVHH;Eu LHP[A^]躍>IH]HEHtHH6>Lv> fffff.UHAVSHPIHVHHE(>Hþ H>HHCHCXHC`HCXHCHHC@HC8HC0HC(HC HCPHCpHCxHCpHChƃHǃfǃHǃHǃƃHHǃHǃHǃHǃHǃHǃHǃHǃHǃHHHǃHǃHǃǃǃHǃ H]蝶 H5>H}H*H5AH+H5BH\HH HQH5s>H|HH;AHHH 0VHMHHUHuHuIIFIF0INIVIF@H]HEHtHuH車>H6VHH;Eu LHP[A^]>IH]HEHtH0Hv>L趇> fffff.UHAVSHPIHVHHE(D>Hþ H:>HHCHCXHC`HCXHCHHC@HC8HC0HC(HC HCPHCpHCxHCpHChƃHǃfǃHǃHǃƃHHǃHǃHǃHǃHǃHǃHǃHǃHǃHHHǃHǃHǃǃǃHǃ H] H5͕>H}HjH5-AHkH5BH蜉HH HQH5>H輊HH;HHH pVHMHeHUHuHuIIFIF0INIVIF@H]HEHtH赡H>HvUHH;Eu LHP[A^]:>IH]HEHtHpH趇>L> fffff.UHAVSHPIH UHHE(脇>Hþ Hz>HHCHCXHC`HCXHCHHC@HC8HC0HC(HC HCPHCpHCxHCpHChƃHǃfǃHǃHǃƃHHǃHǃHǃHǃHǃHǃHǃHǃHǃHHHǃHǃHǃǃǃHǃ H] H5 >H}H誎H5mAH諅H56BH܆HH HQH5>HHH;|HHH VHMHHUHuHuIIFIF0INIVIF@H]HEHtHH;>HUHH;Eu LHP[A^]z>IH]HEHtH谞H>L6> fffff.UHAWAVSHXHHIUHHE„>IH}HYuIHu~H5zVIIHu]HnWIHUHH;EuLHX[A^A_]趄>IIHu$IHu0IIG`H9u<HP ?I>IHtI>IIG`H9tHtHP(I@LH H9uHP Ht HP(IL贃>L> fff.UHSPHH0yVHH{HCHtu>HHt H]>HHt HE>HC`HH9t)HtHP(H{@H H9t$Ht+HH[]`(HP H{@H H9uHH[]` H[]UHSPHHpxVHH{HCHt赂>HHt H蝂>HHt H腂>HC`HH9t%HtHP(HC H{@H9t Ht!HP(HP HC H{@H9uHP HH[])>ff.UHAWAVAUATSH(IIHUHHE1HHIMI_ I+_W)`HDžptCIILH=H誁>H`N4LpHH蓁>LhW)@HDžPAIH@HEHLZHH+HuhMIGIO H)t/IH`H1WH*YH,HHH9rL`LLHHAHHHAHIAJMMIGIO H)t1IH`H1fWH*YH,HHH9rL`LLHHQH@Ht HH>H`Ht Hh>HZUHH;ELH([A\A]A^A_]A~AHIMII~ZHH.H@HHH)HHH)H@H@LMg M+gW) HDž0tCLHHH>8IL~>H HH0HL~>H(IEHHHH{H|MH HH IGIO H)H H`H1ff.WH*YH,HHH9r11MSI^HH>L`LmIHHLLH]>IG I+GHhH+`H9IH`H HLy$L L`HLHHH Ht H(T}>LH@H:AH@HHMw M+wLHH)HHH)vH@~ s HHHMIL@IAMGIv'IIGI I I9stIK H9sg1Kfffff.A?HL9r4s HHHHLsHHHH}>LHHAHHwHs1HIQpKDpH^H)1W( (PDDLLDDLLDDLLDL H HuHt>J7HW( "(PLffffff.D LH HuI9 {>N{>IH`("H5AH AH}L`vH@H AHJ?HuLHE1H5VHL{>H`x>z>IH f("H5"AH dAH}L W)HDž@^z>H(5R)Hs input.HH.Hided as HH(H be provHH Hzes mustHHHes or siHHH of scalHHHOnly oneH@6AH;AHuHLE1H5VHLy>y>IH V'"H5AH TAH}L ߽W)HDž Ny>H( S)Ht index.HHHroi inpuHHHInvalid H@AHPAHuHL%E1H5VHĺLy>x>IH~&"H5:AH |AH}L ޽W)HDž@vx>H(NO)Has inputHH(Hrovided HH HUST be pHHH sizes MHHHcales orHHHEither sHf@0.AHpAHuHL!E1H5VHLx>H u>w>IHi%"H5%AH gAH}LݽW)HDžPaw>HH(V'P)H5ADHx>CDAHAHuHLJE1H5@VH鸼L=w> v>IH$"H5_AH AH}L ݽW)HDž@v>H(C1R)Hs input.HH.Hided as HH(H be provHH Hzes mustHHHes or siHHH of scalHHHOnly oneH@6AHxAHuHL:߽E1H50VHٷL-v> IALeMIALM[I\IALeMFIALMu I!It HOu>LeMt6HEL9t!HX@t Hx*u>HI9uH}LLeu>EuEu LMu-H}t>EtH}t>LM|HL9HX@t Hxt>HI9u9It Ht>LeMt6HEL9t!HX@t Hx^t>HI9uH}LLeDt>EuEu LMu-H}t>EtH}t>LMHL9HX@t Hxs>HI9umIALeMIALMMINIALeM~IAL MIIALeM@IAL MhIIt Hs>LeMt6HEL9t!HX@t Hxr>HI9uH}LLer>EuEuLMu&^H}r>EtH}r>LMt:HL9tTHX@t Hxjr>HI9uHLOr>ELnr>H H&LIt H r>LeMt6HEL9t!HX@t Hxq>HI9uH}LLeq>EuEu L Mu-'H}q>EtH}q>L MH(L9HX@t Hxeq>HI9uIt H@q>LeMt6HEL9t!HX@t Hxq>HI9uH}LLeq>EuEuL Mu&^H}p>EtH}p>L Mt:H(L9tTHX@t Hxp>HI9uH L(p>E}Lp>H@HqxLIAL`MII@t HP#p>LeMt6HEL9t!HX@t Hxo>HI9uH}LLeo>EuEuL`Mu&^H}o>EtH}o>L`Mt:HhL9tIHX@t Hxo>HI9uH`Lhlo>ELo>Ll> LD@><IH`HuT^)IH HtH(o>H@HuIH@Ht HHn>H`Ht Hhn>Ll> ff.UHAWAVAUATSHMLIHIHUHHE1HH誱IMIEI+EIN I+NH91HLOHXHxHp H HL8IFM~ I)LHHLHIL)HH9<H8HJH+ -L9GLMMI}L)aMIH11fDu I H; t1HH9r"HIVLLdHxHX~H`HhDXDH{@HaHC H9HPHEHHRH`H9HPHEHH@H @HDH @L?!HUHH;Ek HXL'LgPII^PLHHm>LI$HUHH;EC IHHHLϹHpHxHXHAHHHHHHH@HLMIHIXCHHh@H I@HDȾHHc>!HUHH;El H:I HHpHHHxHH@HIyH -H`HHhL'M,W)HHH SH;H;@H ~@1AH" -HEHHHEHHLHLùHHHH?HH6HpHH0IH@xA`hHˊTHDL"aIHX{IH{@HgH H9HPHL@H6UHHHLH@H@LLh>HDžDžHrULkLH@H@Lg>L5-UILHDž0HDž(HDž HDžDž8H5@H~ܽ1HH F@H5/@HDHTH۽HLHH"8!t H+h>LH@Lt H(h>Lf>H5UHHf>Lg>HHHHHIHHDHPH@ HD@HL^IHXxIHHx@H:H H9HPH`HDžoIBL@HHHpHxLLHuHuHPHHFHpHuHPLpLl$(L}L|$ AƉD$AĉD$hD$H8H$LLHxH`HLpLXH}I9t3Ht4HP(H}I9u.HP HUHH;E 5HP H}I9tHHP(HSUHH;EHHHPLLd$(L|$ Lt$H8HD$AʼnD$T$HHH0HpL@Lx`hH:QHI9Lt<HtHP(I$H}UHH;E-LH[A\A]A^A_]HP I(HHpHHHxHHL@H IQHHH -H`IHhHH@HHHM,M$W)HHHHLH;t3H@H @1AH"HDž`HHHHHHPHp IHHDHHHDHD,T0LZIHXtIHHx@HQH H9aHPH0LIHAh1lH@H`HPLIĉHA| HH@1HD$0H@H\$(HHD$ L|$Lt$D$H8H$HpHxHhH`MM@H(H`H9THHtHP(HHHKiL@H UHHHLH@H@LLa>HDžDžHEULkLH@H@L`>L5UILHDž0HDž(HDž HDžDž8H5@HԽ1HH @H5@HDHTHԽHLrڽHH0!HDž0LIHA}*HH0HPLIHAHH@HD$@HHD$0L|$(Lt$ ÉD$H8HD$Ld$L,$HH\$8HpHxLHL`H@Hh,T06H0H9HP HHHHt#HHCHuHHPH^>LHPUHH;E`>_>IHu "H51@H @HLSŽHHpAHi?HLHȽE1H5UH3L_>B_>IH "H5@H 1@HLUgŽW)HDž0^>H(:qR)Hbe same.HH'Hshould bHH H tensor HHHd outputHHHinput anHHHRank of H@/AHR@HHLǽE1H5UH+L^> HALMHALM%H"HALM H Ht H]>LMt?HL9t$HX@t Hxs]>HI9uHLLS]>uu#LMu/gH']>tH]>LMt:HL9tMHX@t Hx\>HI9uHL\>EL\>HY> LHt H\>LMt?HL9t$HX@t Hxa\>HI9uHLLA\>uu#LMu/gH\>tH\>LMt:HL9tMHX@t Hx[>HI9uHL[>EL[>HX> 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H{0&>H[A^]>[A^]UHAWAVAUATSH(LMLEIIHIIFIFILLyILLk ILILIVMMHEIHH @HEIHH@HE1LeHuHMIE1ffffff.H3LI~I;~t e>IFIIM9LHWIIM9HuHHMHMLeI9H([A\A]A^A_]IM&MuOIM&Mu BIM&Mt7IFL9t8HX@t Hx蛇>HI9uI>Mf臇>LDŽ> Lf.UHAWAVAUATSHXHMH9HGHEH)HBHEHE1H}IHUHufL9[Bt*@tJL*E>AuDE>AtI^H9ILGMt|At&HEJ|(@HM@uu%HEJ4(DHEJ<(@HM@utJ4*H}HuL>HUHMutHuH}yIDH9Mtb@tJ<*AuHEJ4(HEJ<(AtHEJt(LIH聇>HLHUty3ffffff.H9wJD*IIHH;EHu1HX[A\A]A^A_]ff.UHAWAVAUATSH(IHIHUHHEMt$MtxLmLeM|$LeLm +IH;HsIV IN(MtIMHufI~ Iv(HHKMtoM~IFHu`Mt$MIHu`@>HIuH{ "HC8HCHLsII$HHt@I$I7:MLeLmIHt1HUHH;Eu6HH([A\A]A^A_]HI|$%ID$HUHH;Et藄>IH,>Ll> @UHAWAVSPIIMtLI7LIwLMw MtCIG(L9t.fHX@t Hx˃>HI9uI H[A^A_]LMw(覃>LH[A^A_]锃>fDUHAVSHPIHUHHE(t>Hþ Hj>HHCHCXHC`HCXHCHHC@HC8HC0HC(HC HCPHCpHCxHCpHChƃHǃfǃHǃHǃƃHHǃHǃHǃHǃHǃHǃHǃHǃHǃHHHǃHǃHǃǃǃHǃ H]H}11赐H H5>HH+H5 AH輅H5®BHHH +HQH5>H HH;|HHH VHMH&HUHuHuIIFIF0INIVIF@H]HEHtHƚH>HUHH;Eu LHP[A^][>IH]HEHtH聚H׀>L~> ffffff.UHAVSHPIHKUHHE(褀>Hþ H蚀>HHCHCXHC`HCXHCHHC@HC8HC0HC(HC HCPHCpHCxHCpHChƃHǃfǃHǃHǃƃHHǃHǃHǃHǃHǃHǃHǃHǃHǃHHHǃHǃHǃǃǃHǃ H]H}11HH5>HH[H5<AHH5BHHH 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HALM5H2HALeMHAL@MHHAL@MHHt H&s>LeMt6HEL9t!Lh@t Hxs>LM9uH}LLer>EuEuLMu&^H}r>EtH}r>LMt:HL9tqLh@t Hxr>LM9uHLor>EtLr>H HtBH H2H@HLH t H0r>LeMt6HEL9t!Lh@t Hxq>LM9uH}LLeq>EuEu L@Mu-'H}q>EtH}q>L@MHHL9Lh@t Hxhq>LM9uH t H0Cq>LeMt6HEL9t!Lh@t Hxq>LM9uH}LLeq>EuEuL@Mu&^H}p>EtH}p>L@Mt:HHL9tTLh@t Hxp>LM9uH@LHp>ELp>H`HLHAL`MHH@t HP&p>LeMt6HEL9t!Lh@t Hxp>LM9uH}LLeo>EuEuL`Mu&^H}o>EtH}o>L`Mt:HhL9tILh@t Hxo>LM9uH`Lhoo>ELo>Hl> LHH H+HH@HHH HH(o>H@HufpHH`HumwHH`Hu\fHH@Hu3=HH`Hu:DHH`Hu)3HH@Ht HHn>H`Ht Hhmn>Hk> DUHAWAVAUATSHIHUHHEW)EHHMI>tDHo@H F?1A]L"HUHH;ELH[A\A]A^A_]ILeHEL8LxPM,$Ml$PM9t{I|$0HPhHtAxu;ILjH~T1LLk>HLJIIH9|*I|$1HI|$0HPHLLHn>IHUHH;E4m>IIIHtCt H{l>Hl>L6j> fffff.UHSPHH{Ht H{l>H~OVHH{HCHHt[]l>[]fff.UHSPHH{Ht H{sl>H.OVHH{HCHtSl>HH[]El>UHAWAVSPI(3l>HL=NVL;H{LIHHLQH"WHHH[A^A_]L;IH{HCHt +k>IHk>Lh> fDUHAWAVAUATSHHIH/UHHEID$ID$I$H;guvW)EHEEEaxesEHhHUHLqHhHDžhHtCt H{k>Hj>Et H}j>Hu'HUHH;EuHĘ[A\A]A^A_]"k>j>IHhk"H5@H @H}LhW)PHDž`0sj>H`(jR)PHte valueHHHttributeHHH'axes' aHHHInvalid HHHMissing/H@&LHp@HuHPL DžLH58UHLj>iIǰLLmMuKIǰLHhHIIPt H`li>LmMt6HEL9t!HX@t HxGi>HI9uH}LLm-i>EuEuHhHu&^H} +i>EtH}h>HhHt:HpH9tJLh@t Hxh>LL9uHhHph>Lt8Lh>I<$Hu08HIEtH}h>I<$HuII<$Ht +I|$ah>Le> fUHAWAVSPI(Ch>HL=JVL;H{LEHHLaH2~WHHH[A^A_]L;IH{HCHt +g>IHg>Le> fDUHAWAVSPI(g>HL=_JVL;H{L0EHHLH}WHHH[A^A_]L;IH{HCHt +Kg>IH>g>L~d> fDUHAVSHPIHUHHE(g>Hþ H +g>HHCHCXHC`HCXHCHHC@HC8HC0HC(HC HCPHCpHCxHCpHChƃHǃfǃHǃHǃƃHHǃHǃHǃHǃHǃHǃHǃHǃHǃHHHǃHǃHǃǃǃHǃ H]ݔ H5r>H}HjrH5 @HkiH5qBHjHHHQH5>HkHH;`HHH `VHMHeHUHuHuIIFIF0INIVIF@H]HEHtHu~Hd>HfUHH;Eu LHP[A^] +e>IH]HEHtH0~Hd>La> fffff.UHAVSHPIHUHHE(Td>Hþ HJd>HHCHCXHC`HCXHCHHC@HC8HC0HC(HC HCPHCpHCxHCpHChƃHǃfǃHǃHǃƃHHǃHǃHǃHǃHǃHǃHǃHǃHǃHHHǃHǃHǃǃǃHǃ H]] H5o>H}HoH5K@HfH5BHgHHHQH5æ>HhHH;]HHH VHMHHUHuHuIIFIF0INIVIF@H]HEHtH{H b>HUHH;Eu LHP[A^]Jb>IH]HEHtHp{Ha>L_> fffff.UHAVSHPIH;UHHE(a>Hþ Ha>HHCHCXHC`HCXHCHHC@HC8HC0HC(HC HCPHCpHCxHCpHChƃHǃfǃHǃHǃƃHHǃHǃHǃHǃHǃHǃHǃHǃHǃHHHǃHǃHǃǃǃHǃ H]] H5m>H}HlH5@HcH5BHeHHHQH5>H<fHH;[HHH VHMH%!HUHuHuIIFIF0INIVIF@H]HEHtHxHK_>HUHH;Eu LHP[A^]_>IH]HEHtHxH_>LF\> fffff.UHAVSHPIH{UHHE(^>Hþ H^>HHCHCXHC`HCXHCHHC@HC8HC0HC(HC HCPHCpHCxHCpHChƃHǃfǃHǃHǃƃHHǃHǃHǃHǃHǃHǃHǃHǃHǃHHHǃHǃHǃǃǃHǃ H]蝌 H5]j>H}H*jH5@H+aH51BH\bHH HQH5C>H|cHH;AXHHH VHMH5HUHuHuIIFIF0INIVIF@H]HEHtH5vH\>H&UHH;Eu LHP[A^]\>IH]HEHtHuHF\>LY> fffff.UHAVSHPIHUHHE(\>Hþ H +\>HHCHCXHC`HCXHCHHC@HC8HC0HC(HC HCPHCpHCxHCpHChƃHǃfǃHǃHǃƃHHǃHǃHǃHǃHǃHǃHǃHǃHǃHHHǃHǃHǃǃǃHǃ H] H5g>H}HjgH5 @Hk^H5qBH_HH HQH5>H`HH;UHHH `VHMHEHUHuHuIIFIF0INIVIF@H]HEHtHusHY>HfUHH;Eu LHP[A^] +Z>IH]HEHtH0sHY>LV> fffff.UHAVSHPIHUHHE(TY>Hþ HJY>HHCHCXHC`HCXHCHHC@HC8HC0HC(HC HCPHCpHCxHCpHChƃHǃfǃHǃHǃƃHHǃHǃHǃHǃHǃHǃHǃHǃHǃHHHǃHǃHǃǃǃHǃ H] H5d>H}HdH5K@H[H5BH\HH HQH5Û>H]HH;RHHH |VHMHUHUHuHuIIFIF0INIVIF@H]HEHtHpH W>HUHH;Eu LHP[A^]JW>IH]HEHtHppHV>LT> fffff.UHAVSHPIH;UHHE迈V>HH}L[KH{HunH'9VHHHHu3H mWHHUHH;Eu HHP[A^]V>IH{XHt H{`V>H{@HtH{HV>IHU>L3S> ff.UHSPHH8VHH{HCHtU>H{XHt H{`U>H{@HtH{HH[]U>H[]fDUHSPHH08VHH{HCHtUU>H{XHt H{`CU>H{@Ht H{H1U>HH[]#U>DUHAWAVAUATSH(IIHUHHE1HHIMI_ I+_W)`HDžptCIILH=HT>H`N4LpHHT>LhW)@HDžPA}qIEXH@HEHL.2HH+HunME@IGIO H)t8IH`H1fWH*YH,HHH9rL`LLHHAu|HHɖHAH賖IA}pJMME@IGIO H)t:IH`H1ff.WH*YH,HHH9rL`LLHHAH@Ht HHR>H`Ht HhR>HzUHH;EvLH([A\A]A^A_]A}rqAuxH赕IM?I~PHH.H@HHH)HHH)H@njH@LMg M+gW) HDž0tCLHHH>.ILR>H HH0HLQ>H(IEHHHH{~HtvMH HHʰIGIO H)H H`H1DWH*YH,HHH9r11MSI^HH>L`LvIHHLLHmR>IG I+GHhH+`H9IH`H HL L L`HLHHH Ht H(dP>LH@HJQH@HHMw M+wLHH)HHH)vH@蒊 s HHHMIL@IAMGIv'IIGI I I9stIK H9sg1Kfffff.A?HL9r>s HHHHL|HHHHP>LHHAHHwHs1HIQpKDpH^H)1W( cODDLLDDLLDDLLDL H HuHt>J7HW( OLffffff.D LH HuI9N>^N>IH`!H5@H @H}L`fH@HAHhX?HuLHE1H5DUHżL!N>H`(K>M>IH f!H5@@H @H}L W)HDž@nM>H(Q)Hs input.HH.Hided as HH(H be provHH Hzes mustHHHes or siHHH of scalHHHOnly oneH@6AHY@HuHLE1H5#UHļLM>L>IH V!H50@H r@H}L W)HDž ^L>H(VR)Ht index.HHHroi inpuHHHInvalid H@AHn@HuHLE1H5KUHüL(L>K>IH~!H5X@H @H}L W)HDž@K>H(O)Has inputHH(Hrovided HH HUST be pHHH sizes MHHHcales orHHHEither sHf@0.AH@HuHLE1H5GUH¼L$K>H +H>J>IHi!H5C@H @H}LW)HDžPqJ>HH(&O)H53@DHK>CDAH@HuHL:E1H5pUHLMJ> J>IH!H5}@H @H}LW)HDž@I>H(CQ)Hs input.HH.Hided as HH(H be provHH Hzes mustHHHes or siHHH of scalHHHOnly oneH@6AH@HuHL*E1H5`UHL=I> IALeMIALM[I\IALeMFIALMu I!It H_H>LeMt6HEL9t!HX@t Hx:H>HI9uH}LLe H>EuEu LMu-H}G>EtH}G>LM|HL9HX@t HxG>HI9u9It HG>LeMt6HEL9t!HX@t HxnG>HI9uH}LLeTG>EuEu LMu-H}.G>EtH}G>LMHL9HX@t HxF>HI9umIALeMIALMMINIALeM~IAL MIIALeM@IAL MhIIt HF>LeMt6HEL9t!HX@t HxE>HI9uH}LLeE>EuEuLMu&^H}E>EtH}E>LMt:HL9tTHX@t HxzE>HI9uHL_E>EL~E>H H&LIt HE>LeMt6HEL9t!HX@t HxD>HI9uH}LLeD>EuEu L Mu-'H}D>EtH}D>L MH(L9HX@t HxuD>HI9uIt HPD>LeMt6HEL9t!HX@t Hx+D>HI9uH}LLeD>EuEuL Mu&^H}C>EtH}C>L Mt:H(L9tTHX@t HxC>HI9uH L(C>E}LC>H@HqxLIAL`MII@t HP3C>LeMt6HEL9t!HX@t HxC>HI9uH}LLeB>EuEuL`Mu&^H}B>EtH}B>L`Mt:HhL9tIHX@t HxB>HI9uH`Lh|B>ELB>L?> LD@><IH`HuT^)IH HtH($B>H@HuIH@Ht HHA>H`Ht HhA>L#?> ff.UHAWAVAUATSHMLH0HIIH;UHHE1H誄IMU IEI+EIN I+NH9 1HhHL!'H8HXHHRLMVM~ M)LHHLH@L)HH9;H0HAH+L9>MMI}L)fMIH11Du II;t1HH9r)AD$qLmIH8資ED$tAT$sAD$8At$<I|$IL$(HL$(H|$ t$T$DD$H0H $LLLHLILLHUHH;EIHuUHH;EA|$tH@H @HDH <@HH!H"UHH;EHMH8HH_PM>M~PHLH@>LIHӣUHH;E:LH[A\A]A^A_]ILHLθHpHxH H5IHIBHhLMRHLMIHIx A|$tH@H q@HDȾI IHpIBHxLMRHIqHH@IHHHM,W)HHHhu*HH>H~@H @1AI!LM+wLHLHLǸHHhHHpHHxM:IHP@AHLDcsC0XC8dDk4LijIH8ZHKHL$(HD$ Lt$H0HD$Dl$D$$HHhLHxLPLp@HXdJJH0HtUHHHHH@H0H;>HEEL=UMoLI@L0H;>L5tUILHDž HDžHDžHDžDž(H5@H~ 1A|$tH @H5l@HDHTHHHHHA !t HZ;>LL0Lt H0;>H:>H5KUHH9>H0:>LHUHH;EE;>HHHHHILDzsB8HDHPH@ HDPXLgIH8ˁIL$LHHA|LHhHRAIMBLHHpHxL1HT$0HL$(HHL$ HD$Lt$AljD$H0H$HpHxHHH@IMPX'LILMQHIFH;ILPLf8>HUHH;E*_I(_IHpIBHxIBMBI IQLIHH@IHHIHPHHXIM,W)HHHh8%HH>t#HE@H @1AIm!HHHHHHPHp ILDsHDHHHDHDG8,(dLgeIH8XIL$LHHA6HhHR(H0HĚUHHHHH@H0HM7>HEEL= UMoLI@L0H_6>L5ěUILHDž HDžHDžHDžDž(H5<@H[1A|$tH ӏ@H5@HDHTH-HHHH!K1HT$@HL$8HHL$0HD$(Lt$ AljD$H0HD$Ll$H$HpHxLXL@HPHH,(d156>IH!H5@H 2@HLS:ҽHHAH<@?HLHԽE1H5UH~L5>5>IHH!H5"@H @HLUѽW)HDž0M5>H(5R)Hbe same.HH'Hshould bHH H tensor HHHd outputHHHinput anHHHRank of H@/AH@HHLӽE1H5 UHvL4> HALMHALM%H"HALM H Ht H 4>LMt?HL9t$HX@t Hx3>HI9uHLL3>uu#LMu/gH3>tH}3>LMt:HL9tMHX@t HxR3>HI9uHL73>ELV3>Hb0> LHt H2>LMt?HL9t$HX@t Hx2>HI9uHLL2>uu#LMu/gH2>tHk2>LMt:HL9tMHX@t Hx@2>HI9uHL%2>EnLD2>HP/> LHu/3HBHt{H1>mdHHHM7IMAFt I~k1>Lc1>HHHLL0Lt H1>H0>H58UHH/>H00>H..> HHHt#HHCHuHHPH/>H-> fUHAWAVAUATSHIIHUHHEHEM$MT$M)trIMH1O1fff.IMHt#WI*WH*^ffff.(MuHHHuHHL9rHUHH;EuHH[A\A]A^A_]u{0>/>IH8g!H5@H @HPL8P˽I$HIH n@HMH @HMH ̾@HMH ;@HMH վ@HMH\$HMHL$H$H HuHUHMLELMHAH@HPLHνE1H5EUHL"/> IAL8MII t H0.>LmMt6HEL9t!HX@t Hxr.>HI9uH}LLmX.>puPu L8Mu,dH}/.>PtH`.>L8Mt:H@L9tEHX@t Hx->HI9uH8L@->EtL->L+> Lf.UHAWAVAUATSH(IL]0DUH*UHHEHHHL1LiM)LHI8I@H)HH9ML`HLf~pHffEHEHHH=HLL,>LxHELN$LeHL,>LeffEHEL,>LILmOdLeLH,>LeIGHHhHH<],>HMIJ4HI,>LH?Lt@)HHHJ!HIDH LLL`|?IHH LHhfDHHI>ITLHM LeHLHHHL9I?ME1txL<Hz@H @H@H @EHEʾL1 HUHH;ELH([A\A]A^A_]L]0HI?WI*WH*IWI*I$ ,MAI$1fn O.@U8HHHLL9|IHI?fnp@HHLLuHy1HfnfB~IHHI9Le:DL]0HI?WI*WH*IWI*fnI$ ,Af.wIEHHWH*.vAHH1fn O.@U8IMLL9|I@I?fnp@HHLLeHuHy1HfnfB~IHHI9HxHH@H ,@EHEʾHHHHPLXHEH`LhLpxIHE0HEHE8HEHZH)HHr +L8ff0HDž@MtHM98N4LY(>H0N<L@HLB(>L8HfLxfHDž Mt=M9N4L'>HN<L HL'>LHHH01LHHHLHHLML0HLpEAMM)HLHE1E1fnpfff.MK Iu>1MH fox HfnHfB~IIM9|K1fHHfox Hfnf~DHTHfox Hfnf~HI9uIMkffff.IM94 HL8ff0HDž@MtHM95N4L:&>H0N<L@HL#&>L8HfLxfHDž 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|u;H\t;#HxHpHhH`HH5NRHHs;H8t;H2HH8t;Hff.UHAWAVAUATSHHMLHHHHH?RHHEH8HzRHHHLH@H8L#t;HEEL-RM}LI@L8L5s;HEL5vRILHDž(HDž HDžHDžDž0H$HHHHLM&HHHLL8Lt H s;Htr;H5RHHr;H8s;HRHH;EuHHH[A\A]A^A_]s;HLL8Lt H s;Hq;HH5RHHq;H8r;HHH8ur;Hffff.UHAWAVAUATSPLMLIIIL6Lu;LLHIAuLq;I$Ht;LHHA6Lp;HEHHt;LHHHuLLH[A\A]A^A_]HH HHHHffff.UHAWAVAUATSHHLLHHIHHRHHEH8HNRHHHLH@H8Lp;HHEEL5RMnLI@L8Lp;L=GRILHDž(HDž HDžHDžDž0I$HVs;HHHH0HQo;HHE LMLEH$HHHHHHLL8Lt H 0p;Ho;H5'RHHn;H8o;H|RHH;EuHHH[A\A]A^A_]7p;HLL8Lt H o;Hn;H߸H߸HH5RHHn;H8o;Hp߸HH8o;HY߸UHAWAVAUATSHHLUhLuPLm8Le0L](D}HRHHEHH}HvHsE HtHFHSKDCDK {$D{0C4C8ID$I;$C=IEI;EC>C@HCPHǃHǃHǃHǃHǃHǃpHǃHǃHǃHǃHǃHǃ0Hǃ@HǃpHǃHǃHǃ@HǃPHǃHǃHǃHǃHǃHǃHǃ@HǃPHǃHǃHǃHǃHǃHǃHǃ@HǃPHǃHǃHǃHǃHǃHǃHǃHǃ(Hǃ Hǃ@Hǃ8Hǃ0Hǃ(Hǃ HǃHǃHǃHǃHǃHǃHǃHǃHǃHǃHǃHǃHǃHǃxHǃpHǃhHǃ`HǃXHǃPHǃHHǃ@Hǃ8Hǃ0Hǃ(Hǃ HǃHǃHǃHǃHǃHǃHǃHǃHǃHǃHǃHǃLhLpLU?L}XINH8H@L7?Lu`IOHHHPLiEINHXH`{=u HHH0HhHHHDʋ K(C,i;ȅC<OȋC$N=MуF=MʃF=Mу F=MʉK@HLuHHM@HLQI)H0H8H)3i;IMVI).MTH +HHuP0HHH9LHtHP(HPHǃPHtHEHH HHuP0H`HH9HtHP(HHǃHtHEH@H HHuP0H H@H9HtHP(HHǃHtHEHH HHuP0HHH9HtHP(HHǃHtHEHHr HHuP0HHH9HtHP(HPHǃPHtHEHHN HHuP0H`HH9WHtHP(HHǃHtHEH@H* HHuP0H H@H9&HtHP(HHǃHtHEHH HHuP0HHH9HtHP(H@Hǃ@HtHEHpHHHuP0HPHpH9HtHP(HHǃHtHEH0HHHuP0HH0H9HtHP(HHǃHtHEHHHHuP0HHH9bHtHP(HHǃHtHEHHvHHuP0HHH91HtHP(H@Hǃ@HtHEHpHRHHuP0HPHpH9HtHP(HHǃHtHEHH.HHuP0HHH9HtHP(HHǃHtHEHHHHuP0HHH9HtHP(HCPHCPHtHEHHHHuP0HC`HH9pHtHP(H[HkHHCHUHHPH蓁;H*RHH;E@BHP HHǃHHP HHǃHHP HPHǃPH +HP HHǃH";HP HHǃHSlHP HHǃHHP HPHǃPHHP HHǃHHP HHǃH0HP HHǃHHaHP HPHǃPHyHP HHǃHHP HHǃHHP H@Hǃ@H %HP HHǃH=VHP HHǃHnHP HHǃHHP H@Hǃ@HHP HHǃHHP HHǃH2KHP HCPHCPHc|HP H[HHRHH;EuH[];=;H xRHHH52RHEHO;$ +;H ERHHH5RHEH;~;H RHHH5RHUEH~;~;H RHHH5RH"EH~;q~;H RHHH5fRHDH~;X>~;H yRHHH53RHDHP~;% ~;H FRHHH5RHDH~;};H RHHH5RHVDH};};H RHHH5RH#DH};r};H RHHH5gRHCH};Y?};H zRHHH54RHCHQ};& };H GRHHH5RHCH};|;H RHHH5RHWCH|;|;H RHHH5RH$CH|;s|;H RHHH5hRHBH|;Z@|;H {RHHH55RHBHR|;' |;H HRHHH5RHBH|;{;H RHHH5RHXBH{;{;H RHHH5RH%BH{;t{;H RHHH5iRHAH{;^D{;H RHHH59RHAHV{;.{;H ORHHH5 RHAH&{; H H H H H H H H H Hx Hp Hh H` HX HP HH H@ H8 H0 H( H H UHSHHRHHEHHTHH0Hǃ0HtHEH`H +HHuP0H@H`H9NHtHP(HHǃHtHEHHHHuP0HHH9HtHP(HHǃHtHEHHHHuP0HHH9HtHP(HC@HC@HtHEH{pHHHuP0HCPH{pH9HtHP(H[HHHCHHHPH}w;HRHH;EHP HHǃHHP HHǃHHP HC@HC@H+HP H[HAH|RHH;EuH[]%x;w;H RHHH5RHQ>Hw;w;H RHHH5RH>Hw;^pw;H RHHH5eRH=Hw;.@w;H {RHHH55RH=HRw; HHHH@UHSPHHH[]v;@UHSHHHMRHHEHTHHH`Hǃ`HtHEHHHHuP0HpHH9WHtHP(HHǃHtHEH@HHHuP0H H@H9&HtHP(HHǃHtHEHHHHuP0HHH9HtHP(HCpHCpHtHEHHHHuP0HHHH9HtHP(H[HHHCHHHPHt;HRHH;EHP HHǃHHP HHǃHHP HCpHCpH %HP H[HAHRHH;EuH[]t;ft;H RHHH5[RH:Hxt;3t;H nRHHH5(RH:HEt;^t;H >RHHH5RH:Ht;.s;H RHHH5RHQ:Hs; HHwHoHgUHAWAVAUATSH8LHHIHHRHHEH8HRHHHLH@H8Lr;HHEEL-SRMeLI@L8Lq;L5RILHDž(HDž HDžHDžDž0IHt;HHHH0Hp;HHHt;HHHgHH4HHH!LL8Lt H q;Hp;H5RHHMp;H8Uq;H>RHH;EuHH8[A\A]A^A_]q;HLL8Lt H Lq;H,p;#H(H HHHH5>RHHo;H8p;HHH8p;Hff.UHAWAVAUATSHHMLHHHHH/RHHEH8HjRHHHLH@H8Lo;HEEL-RM}LI@L8Lo;HEL5fRILHDž(HDž HDžHDžDž0H$HHHHLM&HHHLL8Lt H do;HDn;H5{RHHm;H8n;HRHH;EuHHH[A\A]A^A_]ko;HLL8Lt H n;Hm;HH5RHHTm;H8\n;HHH8En;H}ffff.UHAWAVAUATSPLMLIIIL6Lp;LLHIAuLl;I$Hp;LHH`A6Ll;HEHHp;LHH8HuL H[A\A]A^A_]HHHHHHffff.UHAWAVAUATSHHLLHHIHHRHHEH8H>RHHHLH@H8Ll;HHEEL5|RMnLI@L8Lk;L=7RILHDž(HDž HDžHDžDž0I$H&o;HHHH0H!k;HHE LMLEH$HHHHHHLLL8Lt H l;Hj;H5RHH{j;H8k;HlRHH;EuHHH[A\A]A^A_]l;HLL8Lt H zk;HZj;HVHNHH5|RHHi;H8j;H HH8j;H UHAWAVAUATSHHLUhLuPLm8Le0L](D}H}RHHEHH}HvHsE HtHFHSKDCDK {$D{0C4C8ID$I;$C=IEI;EC>C@HCPHǃHǃHǃHǃHǃHǃpHǃHǃHǃHǃHǃHǃ0Hǃ@HǃpHǃHǃHǃ@HǃPHǃHǃHǃHǃHǃHǃHǃ@HǃPHǃHǃHǃHǃHǃHǃHǃ@HǃPHǃHǃHǃHǃHǃHǃHǃHǃ(Hǃ Hǃ@Hǃ8Hǃ0Hǃ(Hǃ HǃHǃHǃHǃHǃHǃHǃHǃHǃHǃHǃHǃHǃHǃxHǃpHǃhHǃ`HǃXHǃPHǃHHǃ@Hǃ8Hǃ0Hǃ(Hǃ HǃHǃHǃHǃHǃHǃHǃHǃHǃHǃHǃHǃLhLpL%tL}XINH8H@LtLu`IOHHHPL9zINHXH`{=u HSHQTH0HhHHHDʋ K(C,e;ȅC<OȋC$N=MуF=MʃF=Mу F=MʉK@HLuHHM@HLQI)H0H8H)3e;IMVI).MTH I?IIAMGIIr/IIGHrH<H9H HpH9A1fttIt HL9rMH0 -ItqIIAMGIIr/IIGHrH<H9H HpH9A1f.ttIt HL9rIMVI)HHH)_h;IEI9E\MIIIHH~HsB1HMIIIHH~H1H HOH)1DLDLD$L4D$L4DDLTDDLTDdLtDdLtH HuHt,H HfDD D +ItqIIAMGIIr/IIGHrH<H9H HpH9A1f.ttIt HL9rIMVI)HHH)/d;IEI9E\MIIIHH~HsB1HMIIIHH~H1H HOH)1DLDLD$L4D$L4DDLTDDLTDdLtDdLtH HuHt,H HfDD D  -H HuM9IEI9EtRHcK$HHHHIEHHHHIEH HHM4$M9t$LcK$MEBHLcAE1ID$LAtCK AXBLHL9TLH)J ILHTIt1DXDDXHH9uJ KK4 I4K<H9@H9AH9I9E1DE =EAICHHDWAHIN0Kt0IBH)1f.DLTXDXDD TXXT D0HHuMt)AALJAXADXDM9xH0AE1ID$LAt K ALAXBLHL9hLH)J4J ILItHT1DXDDXHH9uJO<K K4'I4OK<!I<H9@H9AH9I9E1D5 -EAICHHDVAHwKL0K|0IBH)1ffff.DLTXDXDD TXXT D0HHuMt,JAALLAXADXDM9aO H AE1ID$LAt K ALAXBLHL9qLH)J LILIKTHt1DXDDXHH9uJLEO,K Kt%I4OK"IH9@H9AH9I9E1D LEEAIGHHDZAHKL0Kt0ICH)1@DLTXDXDD TXXT D0HHuMt,JAALLAXADXDM9XOIH@AM1ID$HAtJ ALAXHHH9pI)IMKDIKTHL1f.DXDDXHI9uJMOK K< I<O K"IH9@H9H9I91@- %DHBHHDKAHKL0K|0IAH)1ffff.DLTXDXDD TXXT D0HHuMt,JAALLAXADXDL9ZH`RHH;E)H[A\A]A^A_]LEID$LAm1MRv1M1M1MRyHOH)1DLDLD$L4D$L4DDLTDDLTDdLtDdLtH HuHt,H HfDD D +H HuM9IEI9EtRHcK$HHHHIEHHHHIEH HHM4$M9t$LcK$MEBHLcAE1ID$LAtCK AXBLHL9TLH)J ILHTIt1DXDDXHH9uJ KK4 I4K<H9@H9AH9I9E1DE =EAICHHDWAHIN0Kt0IBH)1f.DLTXDXDD TXXT D0HHuMt)AALJAXADXDM9xH0AE1ID$LAt K ALAXBLHL9hLH)J4J ILItHT1DXDDXHH9uJO<K K4'I4OK<!I<H9@H9AH9I9E1D5 -EAICHHDVAHwKL0K|0IBH)1ffff.DLTXDXDD TXXT D0HHuMt,JAALLAXADXDM9aO H AE1ID$LAt K ALAXBLHL9qLH)J LILIKTHt1DXDDXHH9uJLEO,K Kt%I4OK"IH9@H9AH9I9E1D LEEAIGHHDZAHKL0Kt0ICH)1@DLTXDXDD TXXT D0HHuMt,JAALLAXADXDM9XOIH@AM1ID$HAtJ ALAXHHH9pI)IMKDIKTHL1f.DXDDXHI9uJMOK K< I<O K"IH9@H9H9I91@- %DHBHHDKAHKL0K|0IAH)1ffff.DLTXDXDD TXXT D0HHuMt,JAALLAXADXDL9ZHPRHH;E)H[A\A]A^A_]LEID$LAm1MRv1M1M1MRyHOH)1DLDLD$L4D$L4DDLTDDLTDdLtDdLtH HuHt,H HfDD D  -H HuM9QJJIJJI_;IHHǃHtMHEHHu3^;H RHHH5VRHH^;$ HHuP0HHH9uHP HHǃHu$oHtHP(HHǃHtMHEHHu3];H RHHH5RH~H]; HHuP0HHH9uHP HHǃHu$oHtHP(HHǃHtMHEHHu3?];H ZRHHH5RHHQ]; HHuP0HHH9uHP HPHǃPHu$oHtHP(HPHǃPHtMHEHHu3\;H RHHH5sRH<H\;A HHuP0H`HH9uHP HHǃHu$oHtHP(HHǃHtMHEH@Hu3[;H RHHH5RHH\; -HHuP0H H@H9uHP HHǃHu$oHtHP(HHǃHtMHEHHu3\[;H wRHHH51RHHn[; HHuP0HHH9uHP HHǃHu$oHtHP(HHǃHtMHEHHu3Z;H RHHH5RHYHZ;^ HHuP0HHH9uHP HPHǃPHu$oHtHP(HPHǃPHtMHEHHu3Z;H 5RHHH5RHH,Z;HHuP0H`HH9uHP HHǃHu$oHtHP(HHǃHtMHEH@Hu3yY;H RHHH5NRHHY;HHuP0H H@H9uHP HHǃHu$oHtHP(HHǃHtMHEHHu3X;H RHHH5RHvHX;{HHuP0HHH9uHP HHǃHu$oHtHP(HHǃHtMHEHHu37X;H RRHHH5 RHHIX;HHuP0HHH9uHP HPHǃPHu$oHtHP(HPHǃPHtMHEHHu3W;H RHHH5kRH4HW;9HHuP0H`HH9uHP 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LID1ȉ ցup>fffff.t88fnXf~fff. fnˉ ցu p1t88fnXf~fff. fn.fGIM9[A\A^A_]UHAWAVAUATSHXHOHHEHUH}HuHMH9HHNH(H}LL H OH H;M LeHHIIHAMEH9HHOMILHHHHI9HILMMO6HL)H(M9MMOLAHMOKD?HHLI@0H8MNIHL)HHHDž HH)H0IHDž@1HIE1HIHDžE1HLLqfH}LELIHH8HLLMMLL@HH(HL L0HHLM9LIMHH9HLLHI)L9HLMLLIH41L9LHMH9HLLMLIHyHHLIHPHXH)I9IMHL9LHMH9HLHL9ILH9HLHHL)I9IMNLIK4fHFHUK\%M ^MIAHXLHHHH4VH0LIQHHL)HL)L)LmLmLEL`HhLpH8L@LHHHHHLL LLIBHNH$LHLHJ IHIIEHHHLMMZH HHHH)HHHHBHHxHHHHLLHH`IuHHpHHKD-HHHHC0HLN\+0HCHhIE1M'1Hfff.HBB "HcLLILB HLsH<{Hs#1H}fff.MJ4sH`HHHH9s9HpH9v-1HH ;ffffff.Hx A HcHHH4HL1HADKALKTN\NATKA\KDNLNAoDKAo KoTNoNATKAKDN NH Iut0AoHAoLHoOo\OAHA\HOLOHHH9f.Ht A pwfApHf wHHH9PtNDHcHHhHPfAtM|JfA|MftJAtM<JfA|Mf4JHI9uIIHIIL;H(HHHLHHHT HfAnfpHJHHH@HrHH)1H8oLoTo\o$ffLTff\$HHuHHt(LHo oTff TH9t/Lfff.HD$HH;H|fHHLLHH0LIHxHHH4LXIL2HHLHH`H)HL)IHHxHHHH(HII~HHHLHHpHHHPLHHILXLHHNAHHIK46HHAHHHHHhE1ML"1LLLIHNc,LIHHBHJIs"1Hff.LIHH42LI4vHHLPI IH9sEHI VHpH9v.1LLH -fHxHIHH1LLfAPALPTV\VAPA\PDVLVAoDP AoLP0oTVoVATP A\P0DV VH Hut,oSoLSoPo\PS\SPLPHHI9fHtK4Hf4KfHHHH9XtZH`LLhfffff.DWALUfLWfADUWALUf WfADUHLHuIIHIHL;HH}HXt H}HHH0H*rLMHL91HHPsHH PH H;MuHX[A\A]A^A_]w8fUHAWAVAUATSHHu PHHEHLwHGL9LH8HNH0H HIFHLLHHDž1HLBJH`LhLE1HL(,fHWHHHhHL(HLWM)HHpHxAJ4`HL)I<FI/H -HDIHOAE1Affff.> %=up,fff.t88fnXf~ffnAЉ %=up=ffff.t88fnXf~fff. fn.Iɉw DMDHLAMAH9h1IDE1O<!HF<lj ʁup>fffff.t88fnXf~fff.HA% fn.Ju{}LoMPHOH LIHpLGMNHr)J9HGI9|K$HOIHL9dE1HQLCYfHHIDHL;OEFH8L)H HHHHL_J `McM)LoLIL QLILHHOH H)MJHHH4PE1LpLxL@HHLPHXLIHFHhHxHuLEH]H}L]HMLmL}HELmAAfHLPL`H0L@H0HHHHHH HhH(E1fHL IL9uILxM9H=JLpL@HHLPHXffffff.LxH`D)HcHQHrHcHH)HuCHfffff.Hu(IIICHHDKAHLHHHT0JD~0IqH)1fDZLZTX\XTZ\ZDXLXoDZo ZTXXTZZDX XH HuMt0AoZAoLZAXA\XAZA\ZAXALXL9tyfff.HQLtCZC4XfC4ZfCXLHL9tAJTLJt/f|F\Bf\Ff|B<FBfFf<BHH9uHLoH0LGMHMMJ `IcLH)LJiHHHLHHDžLHDžHHDžBPHhfrHHhHHH ;JL;IL; 91M`HH ~PH H;Mu)H[A\A]A^A_]HH UPH H;Mt%8H8 ffff.UHHGHkLHO0LQv - ׁ/ pfnE1HI IIf])]LHLLfDo 9JfD83rfD83*fEofAr fEofAr fAofo9JffAoffAofo%9JffDofofEfAvfo59Jf( 9J(XfEfD8fAoffofvfDvfDkfDofo 8JfofDfAvfDofDkfXfEfofD8fAofAf8JfofifrfE8f83ffrfD8fEfDfArfArfon4JfDfEfDfE(ED^D^A((3JTA(TfoQKfofffffkfofof8?fvfof8?fvfkfofffofffk((fo 5JfffffkfoKf8K(3JXXfo3JfDofA8fA8flfAfDA(fAqfAqfAof8fr A(fr fo 5JffA(fo-xKfoffA(fffr fr fA8fA8flffqfqfof8fArfArfE8+fD-KfDD*HH-L9(] L)MKHM6J 6Jf2 up0t88fnXf~fff. fn^f~։Gv1@ǃ> 7D8sfnXf~f.   f:LH$ 8fnX5Jf~8D fnE1HIIIf])]LHLLfED(%-5Jffff.fD836fD83~fAofr fAofr fofofo4JffofDo-4JfAfofDofAvfDo4JfAAXfDo 4JfAf8ffofAfofAvfvffAvffDo-V4JfEffofAfAvfAAXfAffof8fof8fofA8fArfArfo=0JfDfDfDfD(ED^D^A((/J(TA(TfDoKfEofDffDffAofffDf(( 0J(X(Xfo/Jf8f8flfAofkfo=1Jfffffkfo%nKf8%UKA(fr fof8A(fr fo 1JffA(fo-~KffA(fffr fr f8f8flfAfEf8fD8fDlfAfDfArfArfE8+fD5KfDfED6HHL9(]L)MKHM2J 2Jfff.2 up0t88fnXf~fff. fn^f~։Gr1@ǃ> 7D8wfnXf~f.   f:LH$]fUHHHOLHI %=up(t88fnX1Jf~ fn q %=up(t88fnX V1Jf~ fnYf~%=GrE1=AA>A .=8wfnX1JfA~ DA Ap up(t88fnX0Jf~% fnA ʉ u p%%t88fnX E0Jf~ fn\f~ʁGr1> ,8wfnX/Jf~   fAp]fUHAWAVATSH`HIHTOHHEMt$L{HCW)EL}HuHEH}LuHEHUйHEHMHHMHEHEI$IL$LHCHuHt$H$ALLH}U8H}L8HOHH;Eu H`[A\A^A_]v~8HH}8H}8HA{8 fUHAWAVAUATSHHIIIHLOHHEЊMSCL MSLMSLMSHIAH*HHH?HHHA@HLI $H9}HH?H=HHI $LL)H1HHI7HD3HHH9eHHH?H>HDHH9HOIM)[^MII9IMM,$I9IMH0<IIH*HHHH?HHHHһHOLI9~8LHHHHt!HsH)H<HHHHHH)I<$MLHHH)HHH4?H9HLHHM1HHH 1HHH9HNHIH9HHHtHH)H<HHHHH)IHOOHH;E?HH?H>HHIM)HsI $HH1LHHI>HHHHH|H9} HHHH?HDHH9HOIHOHH;EWI9IHLH=|)ALMtH=IA@ILMMKLm1LHHH9HNH|HHt)LHHHtHH)H|HHHHH)IHOHH;EH[A\A]A^A_]H=JSz8H}JSHjJSHWJSH}HuHU>HcEHHOH /JSHcEHHOH JSHcEH HOH JSH=JSz8!1z8HH=ISy8Hw8 f.UHAWAVAUATSHhLEHxHIH0HOHHELuM~IF M9L@MNLH8LM -IMHHu4IwHID$HH)HHLyz8HH H8H01HHHDHH I^HHHu0HwHHOHH)HI z8LH H1HH(HDHH0HH8LEHHHHHxHpHHHHHHIHHIH@HI9IMHHH)HJHKH1(J(JHuH`HHXLeHH9ILMHH)H9ILNH IHELHH(HAHL)HHLU~nHEHxHH HHBHEHMHH$E1H}HHULLH H'J'JLUHMLHIIM)L(LXE1fMtWHALLLmHxHEHH$H}LHULM,H 'J'JLUIHLMM9L@ML&HMHMHMH`HP1HI)HI9LOMHPHp1MI)IILHH HHhHHhHMHHHHMHAHEHUHIH(H AH0LT$LT$HH$HD$(HD$ D$H}HuLMIIDH0%J%JLHMHp1@HSHhH +fHxHIHH1LLfAPALPTV\VAPA\PDVLVAoDP AoLP0oTVoVATP A\P0DV VH Hut,oSoLSoPo\PS\SPLPHHI9fHtK4Hf4KfHHHH9XtZH`LLhfffff.DWALUfLWfADUWALUf WfADUHLHuIIHIHL;HH}HXt H}HHH0H*rLMHL91HHPsHH OH H;MuHX[A\A]A^A_]G8fUHAWAVAUATSHHeOHHEHLwHGL9LH8HNH0H HIFHLLHHDž1H8JH`LhLE1HL(,fHWHHHhHL(HLWM)HHpHxAJ4`HL)I<FI/H +HDIHOAE1Affff.> %=up,fff.t88fnXf~ffnAЉ %=up=ffff.t88fnXf~fff. fn.Iɉw DMDHLAMAH9h1IDE1O<!HF<lj ʁup>fffff.t88fnXf~fff.HA% fn.Iu{}LoMPHOH LIHpLGMNHr)J9HGI9|K$HOIHL9dE1HQLCYfHHIDHL;OEFH8L)H HHHHL_J `McM)LoLIL QLILHHOH H)MJHHH4PE1LpLxL@HHLPHXLIHFHhHxHuLEH]H}L]HMLmL}HELmAAfHLPL`H0L@H0HHHHHH HhH(E1fHL IL9uILxM9H]4JLpL@HHLPHXffffff.LxH`D)HcHQHrHcHH)HuCHfffff.Hu(IIICHHDKAHLHHHT0JD~0IqH)1fDZLZTX\XTZ\ZDXLXoDZo ZTXXTZZDX XH HuMt0AoZAoLZAXA\XAZA\ZAXALXL9tyfff.HQLtCZC4XfC4ZfCXLHL9tAJTLJt/f|F\Bf\Ff|B<FBfFf<BHH9uHLoH0LGMHMMJ `IcLH)LJiHHHLHHDžLHDžHHDžBPHhfrHHhHHH1JL;IL; 91M`HH nOH H;Mu)H[A\A]A^A_]HH EOH H;Mt8HՂ8 ffff.UHHGHkLHO0LQv + ׁ/ pfnE1HI IIf])]LHLLfDo !0JfD83rfD83*fEofAr fEofAr fAofo/JffAoffAofo%/JffDofofEfAvfo5/Jf(/J(XfEfD8fAoffofvfDvfDkfDofo 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HHLL]IM L)HHHxDžHHHH9zHqHcI<h1I1f.H9tHHII;6HLH9|(HL]HLI IH;JIM L)HtHu"Hr HL]u DžIEIEPHxW)HDžMtqID$ I+D$HAtHuH HtE1HLnIEt?AYHHL]HHH HHAHx HHL]tuHLLeffff.AYEHH;sHHIHuLL0L]IHuHHAEE)EHHEMt IC0xHpxEH@H+8IIW)HDžHLW)HDžH4H4333333I9LHHHQ4ILKHLHMILH*4LL8LU1HNHMHDLffff.IIHHhHHH4HDDžHH;sCH}L HH +MMMMPE1Ml$HHLXLXHL@L@HEHEID$HHHxIDH}H}HpI$HH`IDHhƅHHDžXHDžPƅ0H}H(H}H H}HUHHHDž@HUHHDž8HUHHUH}HHA|$HHHHHHHHHXHtƅHID$h ƅHMLHPHH@Htƅ0I$ ƅ0MLH8H0H$HxLHL`LLLH LHH;EQ4HGz7HEH4HHEz7HH]HuHHH^ LLHbwcHy7HEH*z7HHy7HH]HuHHHLLHvH{y7HEH&4HHy7HH]HuHHHLLHvHy7HEH^y7HH2y7HH]HuHHH,LLH0v1HEuMTHEuBIHEu7>HEu,3HEu!(HEuHEu HEt H}4H:4 fUHAWAVATSH`IHw +LHHEؿ(Х4Hþ Hƥ4HHCHCXHC`HCXHCHHC@HC8HC0HC(HC HCPHCpHCxHCpHChƃHǃfǃHǃHǃƃHHǃHǃHǃHǃHǃHǃHǃHǃHǃHHHǃHǃHǃǃǃHǃ H]H5Y4H}H&HH55HH IdIHW)EHE4HEHHHML HXHMH56HUL#H5uv7H货H5f4HHAH54H HH;ўHHH LHMH%HUHuHuIIGIG0IOIWIG@H}Ht H}*4H]HEHtH購H 4HLHH;EuLH`[A\A^A_]D4IH]HEHt7HfH輢4L4 IH}HuH]HEHuL՟4 H}肢4H]HEHt룐UH]&fDUHSPHHH[]B4@UHAWAVSPI34HL=߄LL;H{LHHLQHjMHHCXHCPHCHHǃHǃHǃHǃHǃHǃHǃHCxHCpHH[A^A_]L;IH{HCHt +V4IHI4L艞4 UHAWAVSPIHMIIHt I4IILJHtIHtHPMMt#HIFHuILPL軟4IpHt Ix襠4IwHIGHHtIPHtHPMwXMt#HIFHuILPL]4Mw0Mt?IG8L9t*fHX@t Hx+4HI9uI0LMw84ĤLIIIGHHt [A^A_]4[A^A_]HEHEfUHAWAVAUATSHHLLHHIHH3LHHEH8HnLHHHLH@H8L4HHEEL-LMuLI@L8L4L=gLILHDž(HDž HDžHDžDž0I$HV4HHHGHHH24HHHGHHH4HHHGHE0HU(LM LEHMHD$H$HHH9HHHCMLL8Lt H 4Hל4H5LHHr4H8z4HcLHH;EuHHH[A\A]A^A_]4HLL8Lt H q4HQ4HMCHECH=CHH5kLHHϛ4H8ל4HCHH84HBUHAWAVAUATSPLMMIII6艛4I]H[4LHHFA4$Lc4IH64LHHEHEЋ0L<4HEHH 4LHHEHuL+ H[A\A]A^A_]H>BH6BH.BH&BHBHBHBfffff.UHAWAVAUATSHDLHXH`HILm L}LuH_LHHEH(X跛4IFHpHKMHEMwMMMDI]MIMDD$$LH(HI 7I<$Mt#H n7H ]n71AFLIjHLIEH1H`}II~ HLet&L(H}(HHLht ȳIE1L]E1H ƅLm Mt[MMIM L)MI_L)HuWH0 HHLL]IM L)HHHxDžHHHH9zHqHcI<h1I1f.H9tHHII;6HLH9|(HL]HLI IH;JIM L)HtHu"H2 HL]u DžIEIEPHxW)HDžMtqID$ I+D$HAtHuH HtE1HLƳIEt?AYHHL]HHHO HHrH8 HHL]tuHLLeffff.AYEHH;sHHIHuLLeL]IHuHHAEE)EHHEMt IC0xHpxEH@H+8IIW)HDžHLW)HDžH4H4333333I9LHHH!4ILKHLHMILH4LL8LU1HtNHMHDLffff.IIHHhHHH4HDDžHH;sCH}L HH HBHzHrLZ B(Dr,H0HVfDHH$HHHUHL Ly3LL8LLUH [HHHHILHHH HXI HMILElHpHy0AD0I -IJPH H ILHMIL HPHHxIT(AT1IIIT8IL@HL9nE1HDLfff.IIHHhH HH4HDDžHH;sCHML HH:HBHJHrLR B(Dr,H0HRfDHH$HHHUHL L1LL8LH[HHH HID HHHHXI HEID El HpH@0HAD 0ID HEID HPHHxIT (AT 1IIIT 8ID @HL9H`HHH}LLhHhHHHt HP4LMtAHL9t&MI)HHHPHI0uHLL4HHt H4LhH(HSLHH;EuLHĘ[A\A]A^A_]4輖4IHgDH5Oi7H i7H}LVW)HDž0_4H(7H)Hnot valiHH Hoint is HHHb zero pHHHteger : HHHMatmulInHf@(dAHJj7HuHLE1H5/LHײL 4 H4ItH蕕4LeMuEIALeMt6HEL9t!HX@t Hx_4HI9uH}LLeE4EuEuLMu:wH}"4EtH}4LMuQIALMt?HL9t$HX@t HxԔ4HI9uHLL贔4EuzILϔ4jIHHKRIHH|IHHILMJIHHIMuIEMAFt I~4LIIHHIHHuIHHt H蛓4LMtGHL9tiMI)Hff.HHPHI0uHLH4HHt H04H(fLd4 LUHAWAVAUATSHIIHo -LHHE1HUH -HI~0Lht1H}HpLeLHELH`HIHHXHI IMD$HUHMLxLLW)EHULLzI?tsHd7H j51AL?H]Ht#HHCHuHHPH4HZ LHH;ELHĨ[A\A]A^A_]L}IL}IHXMyHLLHEHEHEH]Ht-HCHCHHCHuHHPHP4H]EMHEL@HxHuL?HpHHYHhH@HHDHELPHH L)tHL LcM)HLmu=HELxL HxIuwIHH AH;AthcALm]E1H|THIL9uGHqHcI<u61I1fH9tHHII;uHLH9|AE1Ex]˾H}Y1EHEMHD$H`HD$HL$HpH$DH}HhHULLXxHuH>t{Hb7H 9h51AI=MH]H}tHt HLPH{HHCHeHHPHc4H]HPnHEu1H}(H}H<L}IMH]H}qzd4HIIIHtpCt H{ێ4Hӎ4H}uYlK;IIIHCt H{衎4H虎4H]HumIH]Hu\}IH}tH}tH}HHuPH}t+HHMHAHuH]HHPH04H]Ht#HHCHuHHPH4L@4 HUHAWAVATSHIHTLHHEHfHnHfHnflfMHHELILMt$LI0HPHI|$0HPHIIGPHI$ID$PHHIwL谉H HxH HH9HNH]I|$0HPHHL HI $IL$PHHHHHH8HH@HDžXHDžPHDžHHEH`HDžhHpHDžxHHDžH8HuHH}Ht H},4HxHt H}4H`Ht Hh4HHHt HP4H Ht H(ϋ4HHt H跋4HHt H蟋4HLHH;EuHİ[A\A^A_]ڋ4HH}HuHH}Ht H}W4HxHuFH`HuOHHHu[H HugHHusHHuHO4 H}4H`HtHh4HHHtHP̊4H HtH(贊4HHtH蜊4HHtH脊4Hć4 fff.UHAWAVAUATSHhHuIHLHHEIM<$W)EHEI I+LetPHHL94ILmLmIDHEIwI_ H)H~LH_4MILe E1E1MWHEH)EHEHx HHHP H+xtrHxHpHHL9|胉4ILuLuIHEHpH1HxHH)H~ LHÊ4HxHpILuIG I+GHt+HIL HuiHEHHJH HH+HHuH HtxHEHMH)HHHr`HHHHH<u0BLmLeM)ItIHLHI|tHuHHUH -HHH}Ht H}A4H}Ht H}/4HKHH;EuHh[A\A]A^A_]k4H}h4 H}]4 HH}Hu#HH}HtH}҇4H}HtHH}Hu -H4 H}訇4H4 UHAWAVAUATSHIHH HKHHE1H1LIHH{0uLpHL\HEȾL0LDHEH}HuHMHA HH+AH<t.HuHHx <Ht -Dž<HHHYHH@HHDHELPHHH L)L LkM)Hu3HLxL5 HtpIuoIHH AH;At`[E1H|UHIL9uHHqHcI<u71I1H9tHHII;uHLH9|AE1H0HHt@HC H+CHt HHHz HHx( -Dž(H0ILHHI<tH|5F,E1ELEDL0L)HD$Ll$Lt$HH$D(H HHLHM,lH;tKH^W7H ]51AHx2HKHH;EH H[A\A]A^A_]DH<u1H0&HH7Eu1H0HHH HHpKHH;Eo<44IHX1H5}V7H lX7HpLX W)@HDžP芃4HHP(H)@H5X7tH؄4CtAHyX7HpH@LpE1H5fLHŲLc4 IALeMuFzIALXMII@t HPǂ4LeMt6HEL9t!HX@t Hx袂4HI9uH}LLe舂4Eupu LXMu)aH}b4ptH}P4LXMt:H`L9tEHX@t Hx%4HI9uHXL` -4EtGL-4L=4 LIH HHHtCt H{Ɓ4H辁4L~4 fDUHAWAVATSH`IHKHHEؿ(萁4Hþ H膁4HHCHCXHC`HCXHCHHC@HC8HC0HC(HC HCPHCpHCxHCpHChƃHǃfǃHǃHǃƃHHǃHǃHǃHǃHǃHǃHǃHǃHǃHHHǃHǃHǃǃǃHǃ H])H5W5H}H趈IIFHW)EHE4HEHHHML HXHMH5ί6HUL̓H5lU7H^H5@4H菀HAH54H趁HH;{vHHH jLHMHHUHuHuIIGIG0IOIWIG@H}Ht H}4H]HEHtH蝘H~4H^KHH;EuLH`[A\A^A_]4IH]HEHt7HPH~4L{4 IH}HuH]HEHuL{4 H}\~4H]HEHtff.UHAWAVATSH`IHKHHEؿ( ~4Hþ H~4HHCHCXHC`HCXHCHHC@HC8HC0HC(HC HCPHCpHCxHCpHChƃHǃfǃHǃHǃƃHHǃHǃHǃHǃHǃHǃHǃHǃHǃHHHǃHǃHǃǃǃHǃ H]蹪H55H}HFI螪I֩HW)EHEd|4HEHHHML HXHMH5^6HUL]HEH5Q6HHӄH5Q7H{H54H}HAH5#4H,~HH;rHHH LHMHHUHuHuIIGIG0IOIWIG@H}Ht H}z{4H]HEHtHHY{4HKHH;EuLH`[A\A^A_]{4IH]HEHt7HƔH {4LLx4 IH}HuH]HEHuL%x4 H}z4H]HEHt룐UHAVSHHLHHs0HC0HtH{8HtHPLs@Mt#HIFHuILPLby4H{Ht H{ Lz4HoLHH{HCHt [A^](z4[A^]H-ffff.UHAVSHHgLHHs0HC0HtH{8HtHPLs@Mt#HIFHuILPLx4H{Ht H{ y4H7oLHH{HCHt|y4H[A^]py4Hzf.UH]DUHAVSHHLHHs0HC0HtH{8HtHPLs@Mt#HIFHuILPLw4H{Ht H{ x4HwnLHH{HCHt [A^]x4[A^]Hffff.UHAVSHHLHHs0HC0HtH{8HtHPLs@Mt#HIFHuILPLBw4H{Ht H{ ,x4HmLHH{HCHt x4H[A^]x4H -f.UH]DUHAWAVAUATSHHOHH_0Hp(LP0LKULw@LHLYK<M@uAAAAM9MOH MM)MI?I>MIMH]fnEIr'KDHIH9KD5IH91IEH)LHt#Hf. Y HHuHBIID KT fLYLLYLLYL Y HI9uL]LuLHfoHVHHDsAHLULE+HEHUHT0HEIMT0M^I)E1DCTC\YYBTB\CTCYYBTBIIuMtBB\YYBB\I9H]LULELuL]K4,IfnEI]H9HMHL)LHtHL Y) HHuH rQHUIIT0K\0@LY)LLY)LLY)L Y) HH9|L9LfnEM)IKD5LHMHUIMIKILIH9sK>IH9sLLEMLHfoIHRIIEBAHLuLIPL)E1Mfff.BB\YYBB\BT B\0YYBT B\0IHuMtIBB\YYBB\M9LELuLLD)IGH)Ht%Hfff. Y HHuHr[LEKD JL fDLYLLYLLYL Y HI9u[A\A]A^A_]E1M;RE1MM!fUHAWAVAUATSH_ HHWLQ(Hq0LKH MLw@LHLZK<M@uAAAAM9MOH MM)MI?I>MIMH]fnEIr'KDHIH9KD5IH91IEH)LHt#Hf. Y HHuHBIID KT fLYLLYLLYL Y HI9uL]LuLHfoHVHHDsAHLULE+HEHUHT0HEIMT0M^I)E1DCTC\YYBTB\CTCYYBTBIIuMtBB\YYBB\I9H]LULELuL]K4,IfnEI]H9HMHL)LHtHL Y) HHuH rQHUIIT0K\0@LY)LLY)LLY)L Y) HH9|L9LfnEM)IKD5LHMHUIMIKILIH9sK>IH9sLLEMLHfoIHRIIEBAHLuLIPL)E1Mfff.BB\YYBB\BT B\0YYBT B\0IHuMtIBB\YYBB\M9LELuLLD)IGH)Ht%Hfff. Y HHuHr[LEKD JL fDLYLLYLLYL Y HI9u[A\A]A^A_]E1M;RE1MM!fUHAWAVAUATSH_ HHWLI(Hq0HHEIL_0HHuHMH Hw@LGHHHRHULMAuEAAAM9MOL$N,LL)II?I>HEIIML]H]LM:Is1mI?HMHHMI HI HUILHuHI9@I9AI9I91D LMH] +IJPH H ILHMIL HPHHxIT(AT1IIIT8IL@HL9nE1HDLfff.IIHHhH HH4HDDžHH;sCHML HH:HBHJHrLR B(Dr,H0HRfDHH$HHHUHL L1LL8LH[HHH HID HHHHXI HEID El HpH@0HAD 0ID HEID HPHHxIT (AT 1IIIT 8ID @HL9H`HHH}LL(HhHHHt H 4LMtAHL9t&MI)HHHPHI0uHLLӒ4HHt H軒4LhH(HCKHH;EuLHĘ[A\A]A^A_]ޒ4茒4IH'@H5-e7H e7H}LV.W)HDž0/4H(gH)Hnot valiHH Hoint is HHHb zero pHHHteger : HHHMatmulInHf@(dAH(f7HuHL0E1H5LHg Lۑ4 H4ItHe4LeMuEIALeMt6HEL9t!HX@t Hx/4HI9uH}LLe4EuEuLMu:wH}4EtH}4LMuQIALMt?HL9t$HX@t Hx褐4HI9uHLL脐4EuzIL蟐4jIHHKRIHH|IHHILMJIHHIMuIEMAFt I~4LIIHHIHHuIHHt Hk4LMtGHL9tiMI)Hff.HHPHI0uHL4HHt H4H(6L44 LUHAWAVAUATSHIIH_KHHE1HUHHI~0Lht1H}HpLeLHEL~H`H蟻IHHXH  IMD$HUHMLxLLW)EHULLzI?tsH`7H xf51AL;H]Ht#HHCHuHHPH賌4HJKHH;ELHĨ[A\A]A^A_]L}IL}IHXMy@LLHEHEHEH]Ht-HCHCHHCHuHHPH 4H]EMHEL@HxHuLftHpHHYHhH@HHDHELPHH L)tHL LcM)HLmu=HELxLq HxIuwIHH AH;AthcALm]E1H|THIL9uGHqHcI<u61I1fH9tHHII;uHLH9|AE1Ex]˾H}1EHEMHD$H`HD$HL$HpH$DH}HhHULLXxHuH>t{H`^7H d51AI\9MH]H}tHt HLPH{HHCHeHHPH34H]HPnHEu1H}H}H<L}IMH]H}qz44H0IIIHtpCt H{諊4H裊4H}uYlK;IIIHCt H{q4Hi4H]HumIH]Hu\}IH}tH}tH}HHuPH}t+HHMHAHuH]HHPH4H]Ht#HHCHuHHPHԈ4L4 H/UHAWAVATSHIHDKHHEHfHnHfHnflfMHHELILMt$LI0HPHI|$0HPHIIGPHI$ID$PHHIwL耾H HxH HH9HNH]I|$0HPHHL HI $IL$PHHHHHH8HH@HDžXHDžPHDžHHEH`HDžhHpHDžxHHDžH8Hu`}H}Ht H}4HxHt H}4H`Ht Hhχ4HHHt HP跇4H Ht H(蟇4HHt H臇4HHt Ho4H +KHH;EuHİ[A\A^A_]誇4HH}HuHH}Ht H}'4HxHuFH`HuOHHHu[H HugHHusHHuH4 H}̆4H`HtHh贆4HHHtHP蜆4H HtH(脆4HHtHl4HHtHT4H蔃4 fff.UHAWAVAUATSHhHuIHKHHEIM<$W)EHEI I+LetPHHL94ILmLmIDHEIwI_ H)H~LH/4MILe E1E1MWHEH)EHEHx HHHP H+xtrHxHpHHL9|S4ILuLuIHEHpH1HxHH)H~ LH蓆4HxHpILuIG I+GHt+HIL HuiHEHHJH HH+HHuHs HtxHEHMH)HHHr`HHHHH<u0BLmLeM)ItIHLHI|tHuHHUH +HHH}Ht H}4H}Ht H}4HKHH;EuHh[A\A]A^A_];4H}84 H}-4 HH}Hu#HH}HtH}袃4H}HtHH}Hu +Hˀ4 H}x4H踀4 UHAWAVAUATSHIHH HKHHE1H1LNIHH{0uL0HLHEȾL0LHEH}HuHMHA HH+AH<t.HuHHxl <Ht +Dž<HHHYHH@HHDHELPHHH L)L LkM)Hu3HLxL HtpIuoIHH AH;At`[E1H|UHIL9uHHqHcI<u71I1H9tHHII;uHLH9|AE1H0HHt@HC H+CHt HHH: HH(( +Dž(H0SILHI<tHXj,F,E1ELEDL0LHD$Ll$Lt$HH$D(H HHLHM,lH;tKH<S7H X51AH8.HKHH;EH H[A\A]A^A_]DH<u1H0HH7Eu1H0HHH HH`KHH;Eo 44IHXU-H5[R7H JT7HpLX W)@HDžPZ4HHP(tH)@H5T7tH言4CtAHWT7HpH@L E1H5VLHL34 IALeMuFzIALXMII@t HP~4LeMt6HEL9t!HX@t Hxr~4HI9uH}LLeX~4Eupu LXMu)aH}2~4ptH} ~4LXMt:H`L9tEHX@t Hx}4HI9uHXL`}4EtGL}4L {4 LIH HHHtCt H{}4H}4Lz4 fDUHAWAVATSH`IHKHHEؿ(`}4Hþ HV}4HHCHCXHC`HCXHCHHC@HC8HC0HC(HC HCPHCpHCxHCpHChƃHǃfǃHǃHǃƃHHǃHǃHǃHǃHǃHǃHǃHǃHǃHHHǃHǃHǃǃǃHǃ H])H555H}H趈IIFHW)EHE{4HEHHHML HXHMH56HUL̓H5JQ7H^H54H菀HAH5}4H趁HH;{vHHH ZLHMHHUHuHuIIGIG0IOIWIG@H}Ht H}z4H]HEHtH]Hz4HNKHH;EuLH`[A\A^A_]z4IH]HEHt7HHfz4Lw4 IH}HuH]HEHuLw4 H},z4H]HEHtff.UHAWAVATSH`IHKHHEؿ(y4Hþ Hy4HHCHCXHC`HCXHCHHC@HC8HC0HC(HC HCPHCpHCxHCpHChƃHǃfǃHǃHǃƃHHǃHǃHǃHǃHǃHǃHǃHǃHǃHHHǃHǃHǃǃǃHǃ H]蹪H5ş5H}HFI螪I֩HW)EHE4x4HEHHHML HXHMH5<6HUL]HEH5M6HHӄH5M7H{H54H}HAH54H,~HH;rHHH МLHMHHUHuHuIIGIG0IOIWIG@H}Ht H}Jw4H]HEHtHӐH)w4HKHH;EuLH`[A\A^A_]dw4IH]HEHt7H膐Hv4Lt4 IH}HuH]HEHuLs4 H}v4H]HEHt룐UHAVSHHLHHs0HC0HtH{8HtHPLs@Mt#HIFHuILPL2u4H{Ht H{ v4HXLHH{HCHt [A^]u4[A^]Hffff.UHAVSHHWLHHs0HC0HtH{8HtHPLs@Mt#HIFHuILPLt4H{Ht H{ lu4H'XLHH{HCHtLu4H[A^]@u4H*f.UH]DUHAVSHHLHHs0HC0HtH{8HtHPLs@Mt#HIFHuILPLs4H{Ht H{ t4HgWLHH{HCHt [A^]t4[A^]Hmffff.UHAVSHHLHHs0HC0HtH{8HtHPLs@Mt#HIFHuILPLs4H{Ht H{ s4HVLHH{HCHts4H[A^]s4Hf.UH]DUHAWAVAUATSHHOHH_0Hp(LP0LKULw@LHLYK<M@uAAAAM9MOH MM)MI?I>MIMH]fnEIr'KDHIH9KD5IH91IEH)LHt#Hf. 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52HUH} ;I\$J3HEM,$L}H~RLuMIIJLL52O4H?t+@)HHKLH!HI#H I1 1MM,$Lu(ELmAL$A$HEID$MMtL42UM7LM12 HH}Ht32H12 fff.UHAWAVAUATSPIII^MfLH)HL9IH)HN,;LH<HI)LHHH9IIM9MBMI9/>32HH5{2H02HoIHHH5!IH2IH>32IGLHt/HfHCHC I^HI^IHuHfff.HCHC IFHHINH@H@@IFHHINH@H@@IFHHINH@H@@I^HI^IkxILH22HHIWLH`HHfHAHA HIHuIHHAHA HAHAAHA(HA A,HA8HA0A<HAHHA@ALHAXHAPA\HAhHA`AlHAxHApA|HI;IIIM>IVL)H)H~ HL822IMnMfMtLH[A\A]A^A_]02H[A\A]A^A_]HIHE11kL-2IH}02L-2 DUHAWAVATSIII_IGHH)HHHL9II7H)HHJ3L9H)HHHTUUUUUUH9wHH9HBIHLHH<@/2H[HH K4dAHLHILAttHCH!3HCHCC HCXHCPHCHHC@HC8HC0C,HC$I_H`I_IFIH !3HCHKHCC HCXHCPHCHHC@HC8HC0C,HC$IWHr`IwB`HBhHJpHBxǂHǂHǂHǂHǂHǂHǂƂHǂI_H`I_HHDH= 3H|HDD HDXHDPHDHHD@HD8HD0D,HD$HH`I~HIH3HBHZHBB HBXHBPHBHHB@HB8HB0B,HB$B`HBhHZpHBxǂHǂHǂHǂHǂHǂHǂƂHǂHHHM'IwL9fDH~HyH~HyH~HyH~HyH~H^HYHyHAHAHAFAH~HyHFHFHFHAHAHAFAH~HyHFHFHFH~HHI9<M7MgMIIWIGM9t5I|$Ht -I|$Z+2I\$I|$Ht -I|$A+2II9uMtL[A\A^A_]$+2[A\A^A_]E11rLo(2ff.UHAWAVAUATSHHH bIH HMHw8H}HMHH}u*EH 6IH H;MuHĘ[A\A]A^A_]*2*2IHXMH5 5H -5HpLXǐH}H@Hi(2AH?2HpH@L_E1H5UIHkLR*2 IALeMuFzIALXMII@t HP)2LeMt6HEL9t!HX@t Hx)2HI9uH}LLew)2Eupu LXMu)eH}Q)2ptH}?)2LXMt>H`L9HX@t Hx)2HI9uHXL`(2EuH]HEHu#L&2 L(2H]HEHtCt H{(2H(2L%2 LUHAWAVAUATSHHIHHEЅxRHcHO@HHH)HH9v;HDt HHIHH;EuHĈ[A\A]A^A_]v(2$(2IHhH55H 5H}LhLHPH͸AH5HuLHE1H5IHiL'2 IALhMIIPt H`\'2LmMt6HEL9t!HX@t Hx7'2HI9uH}LLm'2EuEuLhMu&^H}&2EtH}&2LhMt:HpL9tEHX@t Hx&2HI9uHhLp&2EtL&2L#2 Lff.UHAWAVAUATSHHIHHEЅxGHcHO@HWHH)HH9v0HIHH;UuHHDHĈ[A\A]A^A_]q&2&2IHhH55H Y5H}LhGHPHȶAHo5HuLHE1H5IHgL%2 IALhMIIPt H`W%2LmMt6HEL9t!HX@t Hx2%2HI9uH}LLm%2EuEuLhMu&^H}$2EtH}$2LhMt:HpL9tEHX@t Hx$2HI9uHhLp$2EtL$2L!2 LfDUHAWAVAUATSHHIHHEHuH_HLCIt$HH9w"1HHHHHHuLH!HHHtyH8HtqItAHGH9uH9wu#fff.H9r1HHH9u9H?Hu/@HGH9t HL!H9uH9u -H9wH?Huտ#2IHXLH55H Y5HpLXrƉH5HEH@HuHUHAH5HpLHXE1H5NIHdLK#2 HGH rIH H;MuHĘ[A\A]A^A_]0#2IALXMII@t HP"2LmMt6HEL9t!HX@t Hxp"2HI9uH}LLmV"2Eupu LXMu)aH}0"2ptH}"2LXMt:H`L9tEHX@t Hx!2HI9uHXL`!2EtL!2L 2 Lfffff.UH]f.UH]!2fDUHSPH0!2H FKHHKHSHHHPHKHHHK HH HK(HH(H[]@UHHKHHG(HF(HG HF HGHFHGHOHNHF]UH]f.UH] 2fDUHSPHHH ;HH[]ÐUHH .FH1H9NHD]DUHH͋K]UHAWAVAUATSH8IHIHIHHELc HILLNLH;L~HLuID$ L0H@HEI9LHHEI>HoDDDLAtHPAtNIwH9HuuLHHAuPuTHtw1L: uVHI9u^fff.H߉HH9t,IwHHAtHxtHt# 2tIL;u2LuID$ L;pLutLLHK9t-IH}IHH;ELH8[A\A]A^A_]IHKH HHt;HHfffff.H^L9n HCHCH3HuH9tL9j v{MH I\$HLrLcI@H0HH}1PHUHHLAH]HM3HHCHHHPH2MH(H_2IH]Ht#HHCHuHHPH2L2 UH]f.UH]2fDUHSPH2H ވKHHKHHH[]@UHHKHHGHF]UH]f.UH]42fDUHSPH_HHHH߉I@,H[]fffff.UHH +FH1H9NHD]DUHHK]UHAWAVAUATSHH%IHHEЅx[HcHWHBHRH)HHHH9v2HIHH;UuH IHHHĈ[A\A]A^A_]2K2IHhH5D4H /4H}LhsHPHAHa4HuLHE1H5IH]L2 IALhMIIPt H`2LmMt6HEL9t!HX@t Hx^2HI9uH}LLmD2EuEuLhMu&^H}!2EtH}2LhMt:HpL9tEHX@t Hx2HI9uHhLp2EtL2L2 LfUHAWAVAUATSHHH`H IHHEH{HKHqH+qH@HHHH}HPH{]IIEIM0L LpM9HXsoHtZLhI$Ht$HHhI}0HHLP0t IM9rIEH@I9u)I<$u IM9rLI9L}HHfI$HHEHE(y2H PKHHPHHHMHHHXH@HH HEHhHuLRH}I9HtHP(LhM H`HM9ILM9HHL}tvHXtLfff.I$Ht,HHhI}0H\HHhP0IM9uI<$udIM9uLffff.IH9]fLHHL}IH9?@HP LhMLIH9vLIH9eL}HuL9x1LP LP`L4[KK;D-H8LXK IT$HRIB2HpJt2 H0H@JD2Jt2LiL9M)u LXH8ffff.AG HAG@IHLM@A9D$u6AD$A;Gu+I<$I7d2uIHA9D$$Md$tLPIt$(HhuID$H@HxJL0 HhHpJT0JL0L}HuHHL)HHHH9H`HMHEL9t0fff.HXHxHt Hx(2HI9uH}LL}2HIHH;EU2 2HIHHHIL2H`HH4H 41A`HhHDžhHtCt H{2H|2L}MHIHH;EaH`HĨ[A\A]A^A_]ÿP2H kIHHH5%IHHb2. 2H ;IHHH5IHH22 H섯$IH`HHHt;CtH{2IH2HhHDžhHu#IHhHDžhHCt H{W2HO2LuMu2qHILIH}H9t_HtuHP(LuMtAHEL9tSffff.HXHxHt Hx2HI9uH}Lu2L2 HP LuMuLILuMuDUHAWAVAUATSHAAHHIHHED9tnHH D HD: D HDD(HDD(HDpD0D`(HIHH;EuHĈ[A\A]A^A_]`22IHhH54H 4H}Lh6yHPH跣AH4HuLH{E1H5ԫIH}TL2 IALhMIIPt H`F2LmMt6HEL9t!HX@t Hx!2HI9uH}LLm2EuEuLhMu&^H}2EtH}2LhMt:HpL9tEHX@t Hx2HI9uHhLp2EtL2L2 LDUHAWAVAUATSHHՈIHHEHuHH_HH)LG LH+WH9u`H9t -I9pCH9_t-H3HH_HIHH;Eu+HĘ[A\A]A^A_]HuH[IHH;Et+22IH`脾H54H $4HxL`0vW)@HDžP0y2HP(F)@HerminateHHHas not tHHH entry wHHHPreviousHf@ d.@"AH4HxH@L9yE1H5/IHQL,22IH`蒽H54H 24HxL`1 vW)@HDžP@2HP(/E)@Hs 'end'.HH.Hrevious HH(Hr than pHH Hs smalleHHH Value iHHH'start'.HHHInvalid H@6AH4HxH@L#xE1H5IHPL2 IALeMIAL`MIIALeMLIAL`MzII@t HP82LeMt6HEL9t!HX@t Hx2HI9uH}LLe 2Euxu#L`Mu00H} 2xtH} 2L`MHhL9 HX@t Hx 2HI9uI@t HPf 2LeMt6HEL9t!HX@t HxA 2HI9uH}LLe' 2Euxu L`Mu)aH} 2xtH} 2L`Mt:HhL9tEHX@t Hx 2HI9uH`Lh 2EtL 2L 2 Lffffff.UHAWAVAUATSH8HMAIIcI7IHHEH}H0H0HLLM9t`H]HEfff.IcHx0E9fu*IIH)HH9vHHubIM9uHEH0H]tiHcHcH)H˅xQIIH)HH9v7IHHt!HH}HbHMI6HLL9DeHcHD9cIIH)HH9L4LL`LeLHLE0LDe68uaLtUH}tHLeI<$HLHEI<$DeHHuH}HtHtLHHMu fHL91H8[A\A]A^A_]HEM@UHAWAVAUATSH(IIHH;HPH;HLIMkA`LKHHH߉ILtULHHH߉P,uup(Hx,1L}LuL{XLs`M9LeHC@HEffff.IcFHK@HSHH)HH9HL$MtwLoHHH߉HA;MuQH A;M uHHA;Mu?HxIu 2u.H;HLHtHLHUHMu%MvM9S1H([A\A]A^A_]AFHMȉIINHHINHHKhL82H}2ffff.UHAWAVAUATSHHIHHEЅxGHcHO@HWHH)HH9v0H\IHH;UuHHD HĈ[A\A]A^A_]22IHhjH54H 4H}LhmHPHhAH4HuLHpE1H5IH.IL2 IALhMIIPt H`2LmMt6HEL9t!HX@t Hx2HI9uH}LLm2EuEuLhMu&^H}2EtH}2LhMt:HpL9tEHX@t Hx[2HI9uHhLp@2EtLc2Ls2 LfDUHAWAVAUATSHH}IHHEHuHOH_ HH+HH+GHHHH9u_H9q9H9_(t-H3HH_ H3}IHH;Eu/HĘ[A\A]A^A_]HHu{ H}IHH;Et22IH`-H54H 4HxL`6kW)@HDžP "2HP(OC)@Hrt' entrHHHing 'staHHHNo matchHf@y.@AH4HxH@LmE1H5IHFL22IH`IH54H :4HxL`7jW)@HDžP0>2HP(F)@Hhan 'staHH Hlarger tHHHalue is HHH'end'. VHHHInvalid H@(rt'.@,AH4HxH@LlE1H5IHEL2 IALeMIAL`MIIALeMLIAL`MzII@t HP2LeMt6HEL9t!HX@t Hx2HI9uH}LLe2Euxu#L`Mu00H}2xtH}2L`MHhL9 HX@t HxW2HI9uI@t HP22LeMt6HEL9t!HX@t Hx 2HI9uH}LLe2Euxu L`Mu)aH}2xtH}2L`Mt:HhL9tEHX@t Hx2HI9uH`Lhu2EtL2L1 Lff.UHAVSH0HxIHHEW)EHIE(HEHtionProvHEHCPUExecuHEEiderEH{XHuةH@(H H4HH}11PEt H}2HEHHINHHH@IFIH]Ht#HHCHuHHPH}1HwIHH;Eu LH0[A^]2HEt H}F2H1 fffff.UHAWAVATSHIIFIFIH(H -H9HH<@1HINIH[HIFHCHHt3HDHAHAHINHINHHuHff.HAHAHIFHHINH@(H@ H@IFHHINH@(H@ H@IFHHINH@(H@ H@INHINHg[A\A^A_]L*1 IM&Mt3IFL9t4HXHxHt Hx1HI9uI>Mf1L1 LUH]f.UH]T1fDUHSPH(G1H jKHHKHSHHHPHKHHHK HH H[]fff.UHHiKHHG HF HGHFHGHOHNHF]UH]f.UH]1fDUHSPHHH ;HH[]ÐUHH % FH1H9NHD]DUHHiK]UHAWAVAUATSHXIHIHtIHHEL#HEH IH{LFmHtjLuLLAHCL0HKH}LLIcH@ITMdIDI9soHEID$HEHMIL$I$HjIH]HEHaCt H{z1Hr1HsIHH;EJ1I<I -H7I)MIIMIML9+H}HUH)HIHTUUUUUUH9wHH9HBIHHuJH<@1HuILHMKLmLKH}H|H}H]H\L<H<LtHUUUUUUULHHH?HHHRM,M~LLH1HHEL(HEL0HEL8HtH;1LuHEIHEHrIHH;ELHX[A\A]A^A_]E11&Y1 HÃt_HÃtULuHÃuIH1HMHMHEH}1LuoHLuHEMu1H1LuHEMtAFt I~g1L_1H1 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HAG@IHLM@A9D$u6AD$A;Gu+I<$I742uIHA9D$$Md$tLPIt$(HhuID$H@HxJL0 HhHpJT0JL0L}HuHHL)HHHH9H`HMHEL9t0fff.HXHxHt Hx2HI9uH}LL}2HyvIHH;E%2 2HIHHHIL2H`HH4H 41A`\HhHDžhHtCt H{T2HL2L}MHuIHH;EaH`HĨ[A\A]A^A_]ÿ 2H [uIHHH5tIHױH22.2H +uIHHH5sIHnױH2 H蜶$IH`HHHt;CtH{}2IHp2HhHDžhHu#IHhHDžhHCt H{'2H2LuMu2qHLIH}H9t_HtuHP(LuMtAHEL9tSffff.HXHxHt Hx2HI9uH}Lu2L 2 HP LuMuLILuMuDUHAWAVAUATSHAAHHsIHHED9tnHH D HD: D HDD(HDD(HDpD0D`(HsIHH;EuHĈ[A\A]A^A_]022IHhyH54H _4H}Lh檱HPHgհAH4HuLH莭E1H5ĔIH-L2 IALhMIIPt H`2LmMt6HEL9t!HX@t Hx 2HI9uH}LLm 2EuEuLhMu&^H} 2EtH} 2LhMt:HpL9tEHX@t Hxz 2HI9uHhLp_ 2EtL 2L +2 LDUHAWAVAUATSHHqIHHEHuHH_HH)LG LH+WH9u`H9t +I9pCH9_t-H3HH_HvqIHH;Eu+HĘ[A\A]A^A_]HuFHKqIHH;Et 2 2IH`DH54H 4HxL`0讨W)@HDžP0I 2HP(|F)@HerminateHHHas not tHHH entry wHHHPreviousHf@ d.@"AH4HxH@L骱E1H5IHL 2 2IH`RH54H 4HxL`1輧W)@HDžP@W 2HP(E)@Hs 'end'.HH.Hrevious HH(Hr than pHH Hs smalleHHH Value iHHH'start'.HHHInvalid H@6AH4HxH@LөE1H5 IHrL +2 IALeMIAL`MIIALeMLIAL`MzII@t HP +2LeMt6HEL9t!HX@t Hx 2HI9uH}LLe 2Euxu#L`Mu00H} 2xtH} 2L`MHhL9 HX@t Hx[ 2HI9uI@t HP6 2LeMt6HEL9t!HX@t Hx 2HI9uH}LLe2Euxu L`Mu)aH}2xtH}2L`Mt:HhL9tEHX@t Hx2HI9uH`Lhy2EtL2L2 Lffffff.UHAWAVAUATSH8HMAIIcI7IHHEH}H0H0HLLM9t`H]HEfff.IcHx0E9fu*IIH)HH9vHHubIM9uHEH0H]tiHcHcH)H˅xQIIH)HH9v7IHHZt!H H}HbHMI6HLL9DeHcHD9cIIH)HH9L4LL LeLHLE0LDe68uaLtUH}|tHLeI<$HLHEI<$DeHHuH}HtHtLHHMu fHL91H8[A\A]A^A_]HEM@UHAWAVAUATSH(IIHH;HPH;HLIMkA`L HHH߉ILtUL HHH߉P,uup(Hx,1L}LuL{XLs`M9LeHC@HEffff.IcFHK@HSHH)HH9HL$MtwL/ HHH߉HA;MuQH A;M uHHA;Mu?HxIu2u.H;HLHtHLHUHMu%MvM9S1H([A\A]A^A_]AFHMȉIINHHINHHKhL2H}g2ffff.UHAWAVAUATSHHuhIHHEЅxGHcHO@HWHH)HH9v0HLhIHH;UuHHD HĈ[A\A]A^A_]22IHh*H54H 4H}Lh藟HPHʰAH4HuLH?E1H5uIHzLR2 IALhMIIPt H`2LmMt6HEL9t!HX@t Hx2HI9uH}LLm2EuEuLhMu&^H}e2EtH}V2LhMt:HpL9tEHX@t Hx+2HI9uHhLp2EtL32LC1 LfDUHAWAVAUATSHHufIHHEHuHOH_ HH+HH+GHHHH9u_H9q9H9_(t-H3HH_ H#fIHH;Eu/HĘ[A\A]A^A_]HHu+;HeIHH;Et2R2IH`H5d4H 4HxL`6WW)@HDžP 2HP(FC)@Hrt' entrHHHing 'staHHHNo matchHf@y.@AH4HxH@L蠟E1H5ֆIH?xL2n2IH` H54H 4HxL`7sW)@HDžP02HP(6hF)@Hhan 'staHH Hlarger tHHHalue is HHH'end'. VHHHInvalid H@(rt'.@,AH4HxH@L蟞E1H5ՅIH>wL1 IALeMIAL`MIIALeMLIAL`MzII@t HP1LeMt6HEL9t!HX@t Hx1HI9uH}LLe1Euxu#L`Mu00H}l1xtH}Z1L`MHhL9 HX@t Hx'1HI9uI@t HP1LeMt6HEL9t!HX@t Hx1HI9uH}LLe1Euxu L`Mu)aH}1xtH}1L`Mt:HhL9tEHX@t Hx`1HI9uH`LhE1EtLh1Lx1 Lff.UHAVSH0HaIHHEW)EHIE(HEHtionProvHEHCPUExecuHEEiderEH{XHu +H@(H H4HH}11PEt H}1HEHHINHHH@IFIH]Ht#HHCHuHHPHM1H`IHH;Eu LH0[A^]1HEt H}1HV1 fffff.UHAWAVATSHIIFIFIH(H +H9HH<@1HINIH[HIFHCHHt3HDHAHAHINHINHHuHff.HAHAHIFHHINH@(H@ H@IFHHINH@(H@ H@IFHHINH@(H@ H@INHINHg[A\A^A_]L1 IM&Mt3IFL9t4HXHxHt Hxh1HI9uI>MfT1L1 LUH]f.UH]$1fDUHSPH(1H MKHHKHSHHHPHKHHHK HH H[]fff.UHH}MKHHG HF HGHFHGHOHNHF]UH]f.UH]1fDUHSPHHH ;HH[]ÐUHH UEH1H9NHD]DUHHMMK]UHAWAVAUATSHXIHIH]IHHEL#HEHe IH{LiHtjLuLLAHCL0HKH}LLIcH@ITMdIDI9soHEID$HEHMIL$I$HjIH]HEHaCt H{J1HB1H\IHH;EJ1I<I +H7I)MIIMIML9+H}HUH)HIHTUUUUUUH9wHH9HBIHHuJH<@1HuILHMKLmLKH}H|H}H]H\L<H<LtHUUUUUUULHHH?HHHRM,M~LLH1HHEL(HEL0HEL8HtH 1LuHEIHEH[IHH;ELHX[A\A]A^A_]E11&)1 HÃt_HÃtULuHÃuIH1HMHMHEH}1LuoHLuHEMu1H1LuHEMtAFt I~71L/1Ho1 Hffffff.UHAWAVAUATSHHZIHHEIHIIM|$(I0IXH/H@(IL<MI|$0IuRHHHt6HHfHzH9Z HCHCHHuH9tH9Y v1H8r2It$(L%HYIHH;EH(Hȃ8sIH@11LPH@HHINHHH@IFIHHHt#HHCHuHHPH1HXYIHH;EuLHĘ[A\A]A^A_]11IHh<H54H 4H}LhA詐HPH*AH2HuLHQE1H5zIHkLd1 IALhMIIPt H`1LmMt6HEL9t!HX@t Hx1HI9uH}LLm1EuEuLhMu&^H}w1EtH}h1LhMt:HpL9tEHX@t Hx=1HI9uHhLp"1EtLE1LU1 LUHAWAVAUATSH(IHWIHHEI~HPIW)EHELF1IIIsDELeMu(4LHHH1ILeHH]LmLLL1C,H}HMIHMHEHHHtCt H{1H1H]HEHtCt H{1H1Et H}1HuVIHH;EuH([A\A]A^A_]1H}1HEt H}1H1 UHAWAVAUATSH(IHUIH}H +VIHHEL HEL HEH}IH}IL HLx(HuHH Dq L x(uHX 1M9uAt{ t H}HuAH zUIH H;MuH([A\A]A^A_]1ffff.UHAWAVAUATSHH5UIHHE vHiHHQHHt8HHQpHHUIHH;UuHHĈ[A\A]A^A_]a1G1IHhH5N4H -4H}LhhOHPHжAHN4HuLHE1H5-vIHgL +1 IALhMIIPt H`1LmMt6HEL9t!HX@t HxZ1HI9uH}LLm@1EuEuLhMu&^H}1EtH}1LhMt:HpL9tEHX@t Hx1HI9uHhLp1EtL1L1 Lfffff.UHAWAVAUATSPLcoD9n;E2L Lf 1IDILP(t= y(H@ H;A HL9|ffffff.y(H@ HHq HDDALpDLIDDAt2H~H9At/HvHxAu.0ffffff.DH9tXHHxAtHxu-Ht1fDT:u-HI9uMM&Ht 1u M 1H[A\A]A^A_]ð@UHAWAVAUATSHIIIuMuI)MIIGHH<HMeI)LHHH9waII9LBMLEHuI9vK1HH5O52H 1H QIHHH5OIHNIH1LEHuILHa1HHuLEIIIJ;IJD;N|;M~HLI1LI]M}MeHtHH[A\A]A^A_]1H[A\A]A^A_]E11L51IH1L1 fff.UHHGH vHHD]fUHHGH vHHrHt H2HRHTHt]@UHAWAVAUATSHIHOIHHEMnIFIFM.H^L~L9I)Hffffff.LH$L9uLHuH+II<$t H`IǠul81HKHH0H HSHP(HH HMH@HHHI$IH HtII$I~HAIFH`IǠ_HNIHH;EuLH[A\A]A^A_]1HIvLwHe1 ffff.UH]&fDUHSPHHH[]1@UHAWAVATSIH>KIIHt I1I~hHt1I~PHt I~X1I~8Ht I~@|1I~ Ht I~(j1M~MtII^L9tIf.H{Ht H{<1LcH{Ht H{&1LM9uI~ [A\A^A_]LM~[A\A^A_]1UHAWAVAUATSHHuMIHHEIIIHLH II MtHt(Mtd0iHMMtHDLMt<LH tI DHLsܛIEHr %ALMuDHIEHs讛1II!OMt@DLMt4LH t腛I DALMsmALMuDALM.H YLIH H;M\H[A\A]A^A_]IƃtIƃL1Hx IH0LL8H54H "4H HXLE1LLU LHHPHH1LHH,HX@]L@Mt?HHL9t$HX@t Hx1HI9uH@LLH1(t H8~1t Hi111H JIH H;M1IHX\L@MuIIL@Mt:HHL9tZHX@t Hx1HI9uH@LH1(t H81t!H1LIL虋I1L艋H聋UHH]#n UHH]n UHSH(HHIIHHEH}}E؉HuHEuHEUHkHEt H}1HIIHH;Eu +HH([]X1HEt H}1H&1 fffff.UHAWAVAUATSH8IHHKIIHHEH8HGIHHHHH@H8H1HEEL=HIIGHHI@L8H1L%HIILHDž(HDž HDžHDžDž0H5w4HH5o4HIIH@1LHHHߌH5>4HˌAvH-1H5#4 H諌Av H 1H54H苌AvH1H5^2HkIIHLE tHH HL'H54Ht H1HHϑHHL8Lt H |1H`1H5FIHH1H81HFIHH;EuHH8[A\A]A^A_]1$H_HqHtH1HHHL8Lt H 1H1H5EIHHD1H8L1H1 fUHAWAVAUATSPLEAAAIH2H1tKH4LH1tWH4LH1tVH54H[A\A]A^A_]11HDhD` Dx@=1D1DHDhD` DxHHMH1H[A\A]A^A_]H腆DUHHt]1]ffffff.UHHH1]fUHG1]UHG 1]UHG1]UHSPHӋO ;N uO;NuO;NuH?H6g11H[]UH]f.UH]1fDUHAWAVAUATSHHUDIHHEHϽLHHt'H 8DIH H;MuHĈ[A\A]A^A_]11IHhH5>4H 4H}Lh9{W)PHDž`@'1H`(E)PHegistereHH0Hs been rHH(H none haHH Hgger butHHHefaultLoHHHto use DHHHAttempt Hf@8d.@:HuHP1L}H5dIHJVL1 IPt H`V1E1LeMuMH2IALeMt6HEL9t!HX@t Hx1HI9uH}LLe1EuEuLhMu:rH}1EtH}1LhMuLIALhMt:HpL9t5HX@t Hx1HI9uHhLpo1Eu +LIL1L1 UHAWAVAUATSHHMAIIIFIFIL1II +IsDAI^Mu/;D}MIIL1HI^IM>D}MnHLL61B+E~M~ IF0IF(IF LmL 1IIIsDAIMu(4LHHHS1IM~0HI^ Mf(LLL1C'IFHIF@IF8H[A\A]A^A_]Ld1L\1 HAt I~1H1 fffff.UHAWAVAUATSHII6AVINLEFM~ LH1CAF8Mf@Hs L1LeMnXH8LH]yL}MH;>IHHINpI^xH@ILH1IdžhAdžpH|?IHHINpM~pH@IH1H6?IHIFxIdžIdžIdžIdžAdžH[A\A]A^A_]HEH5>IHL1HEL#1M}Mt2IF`L9tFHX@t HxK1HI9uI}M~`61HEt I~P$1HEu/6LHEHEtI~P1Au HEAt I~01H}"1 f.UHAWAVAUATSHIIHO>IHHEH8H<IHHHHH@H8H1HEEL%=IID$HHI@L8H1L==IILHDž(HDž HDžHDžDž0H54HH54 HAuHf1H54 H䁱AuHE1H54 +HÁAuH<1H5:4H袁LHsHHL8Lt H 1H1H57<IHH1H81H<IHH;EuLH[A\A]A^A_]'1HEHWHHHL8Lt H 1Hi1H5;IHH1H8 1H1 UHAWAVAUATSHHIH;IHHEC0fPHs HYHHHHPP0{2sLHS8HHɋCDADECHADECLA DEDs@AAuHH˿X1H IcH E HHHDžHHD<$HHHEEH*HHDžHLtHPHP 1H@H@H 3+KHHXHXHP1HHQ(PAEHHHDžHHtHPHA:IHH;EoLH[A\A]A^A_]HHI]H k1H@H@H *KHHXIE1LHH?Ux L-?IHݎLL H54H 04H/HPLE1LLHH540}s@HM1HPJL0MtvH8L9t[ff.HX@t Hx[1HI9uH0/IEHDžHH8IHH;E~1LL81t H(1t H1IEIEHHHDžHH1H 7IHHH56IHAH1IL0Mu,v72-IHPIL0MtLH8L9fffff.HX@t Hx1HI9uH0L81u.u:HHHDžHHL1 H(1tHMLIHHPHHHDžHHteIHHDžHtHPHY1HHHDžHHk IHHHDžHHIHPLV1 fffff.UHAWAVAUATSPID&McMnMIMLLM9w 1LIHIHHtyHHtqLt3HCL9tL9r1IHH9uND9cHHu:HCL9tH!H9u(D9cHHuHL!IHHuHuп(31HDcHC HCL{HIFHxH*HHH H*XLHDH MHMxoI*AN tsY.wjIIJHIFIVHI^JHHH@IMLL91IHH*XAN uKL-IrIU1LH ^f: - GC(\H,HH1H,.HCH9HCLS -MnIELt(M9w 1LIIIJHHH I!IJHuH!HIHIFHHH[A\A]A^A_]IL{ Mt#HIGHuILPLv1Hj1L1 fUHAWAVAUATSHHJIHHEIIIHsMt$(LH IL$0H9(L8KDsAA M/MGMtI@IcI\$HLH(L@H0LSIHH9w 1HHHI$HHHHt~It;ff.HAH9tH9r1HHH9uSD9qH Hu?HAH9tL!H9u-D9qH 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H躬'H=B'BH=BЬ'W)0ƅ0HDž@HBiasSoftH1Dž9max)HDž PE'HH (<)H5/+IH蓭'CIH`H0H +,H5'H`$HHDžH5e+He+LH0HDžH5e+He+LHb0D$D$$Hn>+H _+L]'1E1H9KD$D$$H/+H e+L$'E1HJD$D$$H 'H _+L'1E1HtOH5Է'HfTAL2+HbH sAHH HHHHH=H=FB1HܩHH9t"Ht#HP(H`Iu'HP H`,t H '0t H@'H=B&'B#H=B'W)ƅHDžHBiasDropHDžout)HDžP{'HH(<)H5,+IHɪ'CIH`HH( +bH5Խ'H`!H"H5K+Hc+E1H'HCD$D$$H;+H `]+Lǵ'1E1HHD$D$$Hc-+H c+L'E1HgHD$D$$Hc+H c+LR'AH(HD$D$$Hc+H c+L_(AHGD$D$$Hxd+H d+L)AHGD$D$$H'H H\+L'1E1H!LD$D$$H\3+H Le+Lx)AHKH5B'HPALs.+H _H5l(HPALe+H^H5)HPAL%e+H^H ^AHHHHHuH=|B1HHH9t"Ht#HP(H`u'HP H`dt H='t H('H=|B^' |BiH=|B>'UW)ƅHDžHIsAllFinHDžite)HDžP賥'HH(H<)H5(+IH'CIH`HHZ + H`H5'H +HMHDžH5c+Hc+LH)HDžH5c+Hc+LH)H5y(HNAL,+H\H5'HNALpc+H\D$D$$H'H hc+Lx(1AHSDD$D$$Hc'H Dc+L>'1E1HHH {\AHHHHHH=yB1HbHH9t"Ht#HP(H`u'HP H`t H苣't Hv'H=yyB謣' HLLG'H`@0t H@ 'H=vBB'$vBH=vB"'W)ƅHDžHnsorFillHHGivenTenHƅ)HDžP艢'HH( <)H5%+IHף'CIH`HHpH`?D$D$$Hw)H =6+L +'1AHAD$D$$H'H 6+Lή'1E1HZFH5'HFAL(+HYH5+H+E1H H5)Hi+E1HH55+HK+E1HH55+H-+E1HH qMAHpHpHHHH=tB1HXHH9teHtfHP(H`u`jH蜠'H`bH w'0RYHP H`et H>'t H)'H=LsB_'QsBH=BsB?'W)`HDžpƅ` +DžaScalfDžee)@HDžPP輟'HHP(Q<)@H5#+IH +'CIH`H`H@H`rD$D$$HZ'H 3+L='1E1H?D$D$$H)'H 3+L'1E1HCH5'HCAL!&+HVDž?H5֘(H0+LH")H gAH@H HHH@H`HH-H=qB1H̝H`H9t"Ht#HP(H`9 @u'HP H` @t HP'`t Hp'H=qB'qBH= qB'W) ƅ HDž0HGRUUnitH!)HDžPu'HH( +<)H5 +IHÞ'CIH`H H%\H`+H51+H1+E1HD$D$$H2+H 2+Lة'1E1H<D$D$$H1+H 1+L'E1Hx<D$D$$H2+H 2+Lc'E1H<<D$D$$H؀-H 2+L''E1H<D$D$$H 2+H 2+L'1E1Hw@H5ר'H@AL#+HSH=nB1HH` t Hq' t H0\'H=nB蒛'nB.H=nBr'W)ƅHDžHnsorFillHHGivenTenHƅ)HDžPٚ'HH(n<)H5 +IH''CIH`HHDH` + H D$D$$H)H .+LR'1AH+:D$D$$H1'H d.+L'1E1H>H5'H,?AL3!+HQH5+H+E1HbH5!)H+E1HDH5-+H+E1H&H5-+Hu+E1HH 9FAHHH0HHH=zlB1H蠘H0H9t"Ht#HP(H` u'HP H`t Hɘ't H贘'H=lB' lBH=kBʘ'W)HDžƅ +DžScalfDže)HDžPG'HH(<)H5+IH蕙'CIH`HHi.H` +H D$D$$Hݨ'H ;,+L'1E1H7D$D$$H'H ,+L'1E1H<H5s'H<AL+HQODž?H5Y(H)+LH!H `AHH xHHHHH H=9jB1HOHH9t"Ht#HP(H`u'HP H`t Hx't Hc'H=iB虖'iBQH=iBy'=W)`ƅ`HDžpHGRUUnitHa)@HDžPP'HHP(;)@H5?+IHF'CIH`H`H@vH` +HH5<*+HA*+E1HD$D$$H}*+H *+LS'1E1H/5D$D$$Ho*+H n*+L'E1H4D$D$$H*+H *+Lޡ'E1H4D$D$$HSy-H *+L'E1H{4D$D$$H*+H *+Lf'1E1H8H5R'H9AL+H0LH=gB1H菓H`@t HP'`t Hpד'H=JgB 'OgBH=@gB'W) HDž0 薓'H0(8) HalizatioHHHanceNormHHHMeanVariHf@nW)HDžP3'HH(;)H5z+IH联'CIH`H HH`HDžH5.H*H)+LHHDžH51I*H')+LH_D$D$$Hw'H J$+LZ'1E1H62D$D$$HF'H 1$+L!'1E1H6H5 'H7AL>+HIH ZAHH rHHHHHvH=eB1HHH9t"Ht#HP(H`u'HP H`et H>' t H0)'H=dB_'dB3H=dB?'W)ƅHDžHScaledTaHfDžnhƅ)HDžP讐'HH(C;)H5+IH'CIH`HHH`dH5c(H'+E1HH5K+H&+E1HD$D$$H'H "+L'1E1H/D$D$$Hߠ'H &+L'1E1HF4H5'H05AL+HGH }XAHH opHHHHHH=bB1H讎HH9t"Ht#HP(H`u'HP H`t H׎'t HŽ'H=UbB'ZbBH=KbB؎'HDžHDžƅ fDžneDžAffiƅW)HDžPJ'HH(;)H5+IH蘏'CIH`HH1H` +HDž?H5a(H@+LH<DžH5+H#+LHD$D$$H'H +Lk'1E1HG-D$D$$HU'H +L2'1E1H1H5'H2ALO+HDH UAHPH mHXHPHpHHH=P`B1H&HpH9t"Ht#HP(H`u'HP H`vt HO't H:'H=_Bp'_B`H=_BP'LW)pƅp$HDžHicSoftplHyHParametrHqfDžusƅ)PHDž`P讋'HH`(C;)PH5+IH'CIH`HpHPH` +dHlH5^(H+E1H H5C+H+E1H D$D$$H'H x+L'1E1H*D$D$$H՛'H ?+L'1E1H>/H5'HX0AL+H|BH uSAH H gkH(H H@HHH=]B1H覉H@H9t"Ht#HP(H`Pu'HP H`Pt H`ω'pt H躉'H=m]B'r]BH=c]BЉ'ھW)0ƅ0HDž@HImageScaH1Dž9ler)HDž PE'HH (;)H5 +IH蓊'CIH`H0H,H` +HH5 +H+E1HeDž?H5͂(H+LHD$D$$H'H d+Lt'1E1HP(D$D$$H`'H K+L;'1E1H,H5''H-ALX+H@H PAHH hHHHHHH=y[B1H/HH9t"Ht#HP(H`u'HP H`t H X'0t H@C'H=[By' [BH=ZBY'qW)HDžƅDžCropƅ)HDžP؆'HH(m;)H5 ++IH&'CIH`HHH` +HH5]/*H+AHH5g(H+E1HD$D$$H/'H +L'1E1H%D$D$$H'H w+Lْ'1E1He*H5Œ'H+AL +H=H 2AHHHHH<H=5YB1HۄHH9t"Ht#HP(H`Hu'HP H`+t H't H'H=XB%'XB?H=XB'+W)ƅHDžHDynamicSHDžliceƅ)HDžPs'HH(;)H5+IH'CIH`HH@ZH` +)H1D$D$$H+H +L'1E1H#D$D$$Hn)H +L)E1H#D$D$$H+H +L)E1HP#D$D$$H+H +LC)AH#D$D$$H!'H +L'1E1H'HW)pHDžfDžpTƅrۀHXH W)@HDžP@臂'HP(O;)@Hr types.HH-Htensor tHH(H to all HH Hut typesHHHand outpHHHn input HHHConstraiH@5HpHXH@H(H5)H'AL+H9H=UB1H3@t HP蜁'LXMt?H`L9t$HX@t Hxq'HI9uHXLL`Q'paH`Jmt H'H=TBL'TBtH=TB,'`W) ƅ HDž0HScaledTaH!fDž)nhƅ+)HDžP蛀'HH(0;)H5+IH'CIH`H HLH` +QHYH5vS(H+E1HH50+H+E1HD$D$$H'H +L،'1E1HD$D$$HĐ'H o+L'1E1H+$H5'H%AL+Hi7H bHAHH T`HHHHHH= SB1H~HH9teHtfHP(H`u`jH~'H`H~'HP H`t Hy~' t H0d~'H=WRB~'\RBгH=MRBz~'W)ƅHDžHSampleOpHƅ)HDžP}'HH(;)H59+IH@'CIH`HH`H5K'H`VHD$D$$H'H z'Ld'1E1H@D$D$$HN'H I'L+'1E1H!IW)HDžfDžTƅ躅HHW)pHDžp|'HH(8)pH5'fH~'CfHHHpL/#H hEAH`H Z]HhH`HHHH=#PB1H{HH9tHtHP(puHP pt H{'LMt?HL9t$HX@t Hx{'HI9uHLL{'H`t HT{'H=WOB{'\OBΰH=MOBj{'W)PƅPHDž`HWithMaskHXHMaxpoolWHQƅ`)0HDž@Pz'HH@(f;)0H5*IH|'CIH`HPH0nH5*'H`5HxHDž HDžƅ fDžETDžNOTSƅH5I+H +LHo +H5JN)H+E1HH5+H+E1HsHDžH5c)H+LHH5M)H+E1H(D$D$$H~'H `+Lc'1E1H?D$D$$HE*H #+L'E1HD$D$$H'H +L'1E1HzH5څ'HAL+H0H &AH0H0HPHHQH=LB1HwHPH9HHP(H 6x'H`<0H@x'Pu}Hw'H`uHw'elHP kH`0wPt H`w'H=KBw'KBH=KBw'W)HDžƅDžRfftƅ)HDžPw'HH(;)H5[*IHbx'CIH`HHܟH5m'H`xHD$D$$H'H +L'1E1HbHDžH5 +HV+LH%HDžH5 +H)+LHHDžH5} +H+LHD$D$$H'H ++LƂ'1E1HRH5'HAL+H-H=IB1HtH`st HLu't H7u'H=ZIBmu'_IBͪH=PIBMu'W)HDžƅ +DžIrfffDžt)HDžPt'HH(_;)H5*IHv'CIH`HHڟH5#'H`.HqD$D$$HW'H g+L<'1E1HH5 +H+AHHDžH5a +H+LHHDžH5? +H+LHD$D$$H'H +L'1E1HH5t'HAL+HR+H=kGB1HrH`5t Hs't Hr'H=,GB/s'1GBH="GBs'W)pƅpHDžHComplexMHqfDžyulƅ{)PHDž`P~r'HH`(;)PH5*IHs'CIH`HpHPe؟H5׆'H`H%D$D$$Hw +H r +L~'1E1HD$D$$HE(H A +L~'E1HD$D$$H +H +L{~'1E1HH5g~'HAL+HE)H=nEB1HpH`(ߟPt H`q'pt Hp'H=/EB"q'4EBH=%EBq'HDžHƅ8HxMulConjH?HComplexMH9ƅGW) HDž0Ppp'HH0(;) H5*IHq'CIH`H8H W֟H5Ʉ'H`HD$D$$Hi+H d+L|'1E1HD$D$$HC(H 3+L|'E1HD$D$$H+H *Lm|'1E1HH5Y|'HAL*H7'H=pCB1HnH`ݟ t H0n'8t HHn'H=1CBo'6CBH='CBn'W)HDž n'H(8)HhDynamicHHHsposeWitHHHConvTranH@Pads@W)HDžP5n'HH(;)H5|*IHo'CIH`HHԟH5'H`HH5B)H+E1HNH5D)H+E1H0H5B)H+E1HH5A)Ha+E1HHDž HDžƅ fDžETDžNOTSƅH55+H +LH[HDžH5A)Hߙ+LHD$D$$H}'H +Ly'1E1H D$D$$H +H m+Lpy'E1HI D$D$$H+H 1+L*~'AH + D$D$$H1@(H +Lx'AH D$D$$H|'H +Lx'1E1HBH5x'H4AL(+H#H y4AHH ;8HHH HH H=?B1HjH H9tLHtMHP(tGH j'H`ٟt;Hj'u/9HP uH`؟ut Hj'H=>Bj'>BeH=>Bj'QW)ƅHDžHFusedConHfDžv)HDžP#j'HH(;)H5j*IHqk'CIH`HH +ПH5|~'H`HHDž HDžƅ fDžETDžNOTSƅH5+Hr+LHH5=)HP+E1HH5F>)H2+E1HH5m=)H+E1HH5(+H+E1HHDžH5=)H͕+LHH5.*H+E1H>H5d+H+E1H D$D$$Hvy'H X+L[u'1E1H7D$D$$H*H +L"u'E1HD$D$$H"<(H +Lt'AHD$D$$H*H +Lt'AH}D$D$$Hx'H e+Lht'1E1H H5Tt'H AL*H2H AHHHHHH=d;B1HjfHH9tLHtMHP(tGH f'H`ԟt;Hf'u/9HP uH`ԟut HWf'H=:Bf':B3H=:Bmf'W)ƅHDžHFusedGemHfDžm)`HDžpPe'HHp(x;)`H5**IH1g'CIH`HH`C˟H5<z'H`GHD$D$$H*H 6*LUr'1E1H1D$D$$HX9(H ^*Lr'E1HD$D$$Hy*H *Lq'E1HD$D$$Hu'H *Lq'1E1H0 H5q'HR 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IMoHPH`Lc`MH`Lp IEHXIM>IE Ht4IcM;},QAUH\{(uAf.L{ IIuHHXH8 HXHr"!HÃ{(tHC(L{ IIxH"M>uHx LhLHP I`cH`HHH * HL HdE1HHLLM pH8V -H]Ix{ HE>L02LpLH5]'H wa'E1HPHLM肓 HH5a'H`HHHqHEqHEQHKHH5a'rFHH5a'^@HH5b'JAHH50b'6KHH5^b'"HP&LMHL9HX@t Hxr#HI9uHH`HHH aHL6 H`HHLLyLLr#t Hq#pt Hq#H`IG(LLq#t Hq#pt Hq#LHHH;HPdMuIFpHXHHDMcnhMIL3AFtXM~(MuL=J>A(tAMfIH L(HL IV(HuHuJ>HhL>HIuHhLpIHXHHDMcMtgIL-(J>L fH@t.Lx(MuMA(tHpHLHLY HIuHhLpIF(HXHHDMc~ MLht-IL f.H3LL"!HIuAtL#H0Ht5f.L3H{($Ct H{ o#Ho#LMuH HDž Hto#H:HH;EH[A\A]A^A_]H=4_>o#ZHPHxW)pHDžHp-H<Dx(pt Hn#HPpD=^>H=^>o#Hh!HP%W)pHDžHPHp HDx,ptzn#n#IHp4H5DX'H Z'HPLpԢW)HDž@)n#H(a~7)His invalHH0Hs model HH(Hame. ThiHH Hhave a nHHHer must HHHnitializHHHSparse iHf@8id@:H4['HPHL֢1H5;H`Lm#om#IHpH5*W'H kY'HPLpӢHH1AHH(k#H#HPHL֢1H5;HLm#(Ll#l#IHpqH5V'H X'HPLpҢIH)Z'HHHY'HHHHHAHo&HPLH[բE1H5Q;HLNl#c l#IHpH5U'H X'HPLp.ҢHH?HHi#AH+#HPHLԢE1H5;HWLk#LPk#^k#IHp H5U'H ZW'HPLpѢIH\X'HHH}X'HHHHH诩AHMn&HPLHӢE1H5;HLj# j#IHpOH5_T'H V'HPLp!ТW)HDžPDj#H(7)Hrmation.HH8Hype infoHH0Ht have tHH(H does noHH H. 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IMoHPH`Lc`MH`Lp IEHXIM>IE Ht4IcM;},QAUH\{(uAf.L{ IIuHHXH8 HXH"!HÃ{(tHC(L{ IIxH5>uHx LhLHP I`cH`HHH * HL HdE1HHLLM pH8V +H]Ix{ H->L02LpLH5=]'H 2a'OE1HPHLM— HH5a'H`HHHqHEqHEQHvKHH5Sa'bFHH5a'N@HH5a':AHH5a'&KHH5b'HP&LMHL9HX@t Hxr#HI9uHH`HHH aHL6 H`HHLLyLL#r#t Hr#pt Hq#H`IG(LLq#t Hq#pt Hq#LHHH;HPdMuIFpHXHHDMcnhMIL3AFtXM~(MuL=2>A(tAMfIH L(HL IV(HuHU2>HhL>HIuHhLpIHXHHDMcMtgIL-2>L fH@t.Lx(MuMA(tHpHLHLY HIuHhLpIF(HXHHDMc~ MLht-IL f.H3LL"!HIuAtL#H0Ht5f.L3H{($Ct H{ o#Ho#LMuH HDž Hto#HB:HH;EH[A\A]A^A_]H=$G>o#ZHPHxW)pHDžHp-H<Dx(pt H +o#HPpD=F>H=F>-o#Hh!HP%W)pHDžHPHpHDx,ptzn#n#IHp4H5W'H @Z'HPLp +W)HDž@9n#H(k7)His invalHH0Hs model HH(Hame. ThiHH Hhave a nHHHer must HHHnitializHHHSparse iHf@8id@:HZ'HPHL 1H5:HPLm#m#IHpH5V'H &Y'HPLp HH1AHH8k#H#HPHL 1H5F:HL#m#(Ll#l#IHpqH5<V'H }X'HPLpIHY'HHHY'HHHHHWAHo&HPLHK E1H5:HL^l#cl#IHpH5U'H W'HPLpHH?HHi#AH;#HPHL +E1H5:HGLk#L`k#nk#IHp H5T'H W'HPLpsIHX'HHH8X'HHHHHAHkn&HPLH E1H5:HLj# j#IHpOH5T'H [V'HPLp!W)HDžPTj#H(l7)Hrmation.HH8Hype infoHH0Ht have tHH(H does noHH H. 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L!L9Ct HCHu (HtHHuaH!HIHIGH):HH;EuH(HH8[A\A]A^A_]#IA$tH{ p#IHc#L# HcUHAWAVAUATSHIHH@H:HHEHL9tAF Iv1`@H( H}L&sH8LMffffff.AEMuIu IDIEUH}艇HLeMHHML$MdIL9r 1HIIHEJH`HHTAEMEMu MMLPHCH9tL9r1IHL9KHtHSL9uau11ffffff.T A:u@HH9uH{ LLM #MHHLPcHHYwHCH9tL9r1IHL9uUCtHCHHHu6fDHuMI!HEJHf(#HIuIIL#HHHCHHEHxH*#fffff.HHH H*XLHDH Mx'WI*Mt+Y.fWH*XMuK $IrIT$1L^f: + Z_4(\H,HH1H,.HCH9HCL&ҞMwIFLHut'L9r 1HIHIHHtHH gH!IHHuIGIWHI_HHH<H@INLL91IH DM3MLEL}LMDHCH9t L!L9/KHtHSL9uQu#1fT A: u6HH9uH{ LLM#MLMLEH}L}toHHsfffff.HCH9t L!L9Ct HCHu (HtHHuaH!HIHIGHY|:HH;EuH(HH8[A\A]A^A_]#IA$tH{ #IHs#L# HSUHAWAVAUATSHIHH@H{:HHEHL9tAF Iv1PvH( H}LH8LMffffff.AEMuIu IDIEUH}yHLeMHHML$MdIL9r 1HIIHEJH`HHTAEMEMu MMLPHCH9tL9r1IHL9KHtHSL9uau11ffffff.T A:u@HH9uH{ LLM#MHHLPcHHYwHCH9tL9r1IHL9uUCtHCHHHu6fDHuMI!HEJHf(#HIuIIL +#HHHCHHEHxH*#fffff.HHH H*XLHDH Mx'WI*Mt+Y.fWH*XMuK $IrIT$1L^f: -( -_4\H,H HH1H,.HCH9HCH}vLeID$Lt/LHM9r 1LIIHMJHt#HH LHI!HMJHuސHEHH]HEJHHKH@IL$L+L9%1IHDMMLPLXHCH9t L!L9 KHtHSL9u^u+1fT A:uCHH9uH{ LLM#MLXHHLPtpHHfHCH9t L!L9kCt#HCHt8HHuMffff.HuH!HHEHHEMmMEH8HHLuf.HsL#HC(HK0HUHJHH`L#`tHpHhHaHxhIHHLeMI|$LcMM9r 1LIIHEJH_HHS`#LhLpL"MXLPDHCL9tL9r1IHL9KHtHSL9uRu)1ffffff.T A:u1HH9uH{ LLM#MLPHHhvfDHCL9tL9r1IHL9uUCtHCHnHHu6fDHuOIM!HEJHf(#HIHpIG H`HhIOIGW)`MwHDžpIHEHxWH*$fff.HHH WH*XHLHDH MxpI*MttY.wkMHMJHHEIL}HEJIH9H@IL$LL91IHH*XMuK $IrIT$1L^f: +(Y4\H,H HH1H,.HCH9HCH}LeID$Lt/LHM9r 1LIIHMJHt#HH LHI!HMJHuސHEHH]HEJHHKH@IL$L+L9%1IHDMMLPLXHCH9t L!L9 KHtHSL9u^u+1fT A:uCHH9uH{ LLM,#MLXHHLPtpHHfHCH9t L!L9kCt#HCHt8HHuMffff.HuH!HHEHHEMmMEH8HHLuf.HsL#HC(HK0HUHJHH`L#`tHpHhHaHxXIHHLeMI|$LcMM9r 1LIIHEJH_HHS`#LhLpL"MXLPDHCL9tL9r1IHL9KHtHSL9uRu)1ffffff.T A:u1HH9uH{ LLM#MLPHHhvfDHCL9tL9r1IHL9uUCtHCHnHHu6fDHuOIM!HEJHf(#HIHpIG H`HhIOIGW)`MwHDžpIHEHxWH*$fff.HHH WH*XHLHDH MxpI*MttY.wkMHMJHHEIL}HEJIH9H@IL$LL91IHH*XMuK $IrIT$1L^f: -(}Y4\H,H HH1H,.HCH9HCH}xpLeID$Lt6M9r1LIIf.HMJHHIRI!HMJHuDLaLMXLPH0fff.HCL9t H!L9KHtHSL9uOu#1fT A:u4HH9uH{ LLM#H0MLPt]HHuPHCL9t H!L9;Ct#HCHtXHHuffff.Hu2XLuHHu,6H!HHEL8HE`LuHHt Hp #Et H}v #HHH8L E1ML}IELLM9t7I4$H}LH]Hu5H@HIM9uMmMuE1H]H #IHILHHH #H@L6H&H m&1A臹H]HEHtCt H{u #Hm #AH]Ht"L3Ct H{ L #HD #LMuH}HEHt& #EuH@HH:HH;EuH@HĨ[A\A]A^A_]E #IH@HHHt8Ct H{ -#HIL -#H]HEHuIH]HEHCH{YIt I ^ -#LV -#`u?I`t3Hp3 -#Eu'VH5zIAt/H{  -#$IEt1H} #H]Hu6VIH #H]Hu<IH]Ht0fffff.L3Ct H{ #H #LMuH}HEHt #L# HyfDUHAWAVAUATSHEAIIHHH€:HHEEHHL`HhL)HL9EL9K<HKHHpfǁHHH)HIcH9rLAHLMPHpfǀHHH)HIcH9vTHHHttI9~I H; -LHHH`J<HpLHJJLHL)HHH9vH)IHHu#IHh蘵H5&H &H}LhnW)PHDž`@#H`(x7)PHng edge.HH5H adding HH0Hied whenHH(Ht specifHH H arg sloHHHion nodeHHHdestinatHHHInvalid H@=HuHP1L)pH5":HHL#yKHHAHHEDeDuHHuHH`J<HpfǁJHEDeDuHHuHlH}:HH;EuHĘ[A\A]A^A_]#A#IHhH5&H &H}LhilW)PHDž`@#H`(B7)PHng edge.HH(Hhen addiHH Hcified wHHHexes speHHHnode indHHHInvalid H@0HuHP1LnH5:H;GL#J#IHhH5&H &H}Lh rkW)PHDž`@#H`(7)PHng edge.HH0Hhen addiHH(Hcified wHH Hslot speHHHode arg HHHsource nHHHInvalid H@8HuHP1LmH5:H6FL#E#IHhH5&H &H}Lh"mjW)PHDž`0#H`(~7)PHng edge.HH Hhen addiHHHsmatch wHHH type miHHHArgumentH@(HuHP1LlH5:HMEL# IPt H`9#E1LeMuMH5sIALeMt6HEL9t!HX@t Hx#HI9uH}LLe#EuEu LhMuD{H}#EtH}#LhMuRIALhM<HpL93HX@t Hx_#HI9uIPt H`5#E1LeMuMH1rIALeMt6HEL9t!HX@t Hx#HI9uH}LLe#EuEu LhMuDwH}#EtH}#LhMuNIALhM8HpL9/HX@t Hx[#HI9uIPt H`1#E1LeMuMH-qIALeMt6HEL9t!HX@t Hx#HI9uH}LLe#EuEu LhMuDsH}#EtH}#LhMuJIALhM4HpL9+HX@t HxW#HI9u IPt H`-#E1LeMuMH)pIALeMt6HEL9t!HX@t Hx"HI9uH}LLe"EuEuLhMu:rH}"EtH}"LhMuLIALhMt:HpL9t5HX@t Hxa"HI9uHhLpF"Eu -LIL_"Lo" UHAWAVAUATSHEAHHIIHrv:HHEEI`IhH)HL9eE\H;HOJHBHHH<H.HHH)HIcH9 -H HHHH)HIcH9vHHHu9LHL)HHH9H)IHHH9HpfǁHED}DuHHuI`J<HpfǁHHHHED}DuHHuHt:HH;EuHĘ[A\A]A^A_]"k"IHhH5&&H r&H}Lh/cW)PHDž`@"H`(x7)PHving edgHH(Hhen remoHH Hcified wHHHexes speHHHnode indHHHInvalid Hf@0e.@2HuHP1LeH5:H_>L"n"IHhH5)&H u&H}Lh9bW)PHDž`@"H`(I 7)PHving edgHH0Hhen remoHH(Hcified wHH Hslot speHHHode arg HHHsource nHHHInvalid Hf@8e.@:HuHP1LdH5:HT=L"c"IHhH5&H j&H}LhFaW)PHDž`@"H`(>94)PHng edge.HH7H removinHH0Hied whenHH(Ht specifHH H arg sloHHHion nodeHHHdestinatHHHInvalid H@?HuHP1LcH5:HA<L"P"IHhH5 &H W&H}LhLx`W)PHDž`0"H`(+7)PHng edge.HHHemoving HHHh when rHHH mismatcHHHArgumentH@%HuHP1LbH5:HX;L" IPt H`D"E1LeMuMH@iIALeMt6HEL9t!HX@t Hx"HI9uH}LLe"EuEu LhMuD{H}"EtH}"LhMuRIALhM<HpL93HX@t Hxj"HI9uIPt H`@"E1LeMuMH<hIALeMt6HEL9t!HX@t Hx"HI9uH}LLe"EuEu LhMuDwH}"EtH}"LhMuNIALhM8HpL9/HX@t Hxf"HI9uIPt H`<"E1LeMuMH8gIALeMt6HEL9t!HX@t Hx"HI9uH}LLe"EuEu LhMuDsH}"EtH}"LhMuJIALhM4HpL9+HX@t Hxb"HI9u IPt H`8"E1LeMuMH4fIALeMt6HEL9t!HX@t Hx"HI9uH}LLe"EuEuLhMu:rH}"EtH}"LhMuLIALhMt:HpL9t5HX@t Hxl"HI9uHhLpQ"Eu -LILj"Lz" fUHAWAVAUATSHxHIIHl:HHEIpHW)E)E)E)pE?E?I(LL6I H&IhHHH@HHHAHHHHH9HHHfffff.W)P)@Dž`?H3LH@I}Ht5A1AaLH&H n&Ufff.IELPMI\$HH.HHH@(H(H{AD$LkIt$ IDIET$H3dHLxMHIMVMHL9r 1HIHHpHHHH AD$%ML$Ml$ M!MHfHCH9tL9r1IHH9KHtHSL9uau*1ffffff.T A:T u?HH9u5 H{ LLM"MHLH HHY$@HDž(AD$LkIt$ IDIET$HbHHLpMHMNMHL9r1HIHHHHHHHAD$jMD$Ml$ MfMHLHCH9tL9r1IHH9aKHtHSL9u[u*1ffffff.T A:T u9HH9u?H{ LL6"LHHHH_f.HCH9tL9r1IHH9Ct)HCHHHuffffff.HuHCH9tL9r1IHH9!CtHCHHHuHuLH!HHHGf.H("IMILH"HIEIEHH@HxH*HHH H*XLHDH Mx'I*HH t+Y.w"HYH*XHH uK 6IrIV1L^f: +(MT4\H,H HH1H,.HCH9HCH}hLeID$Lt6M9r1LIIf.HMJHHIRI!HMJHuDLaLMXLPH0fff.HCL9t H!L9KHtHSL9uOu#1fT A:u4HH9uH{ LLM#H0MLPt]HHuPHCL9t H!L9;Ct#HCHtXHHuffff.Hu2XLuHHu,6H!HHEL8HE`LuHHt Hp #Et H} #HHH8L E1ML}IELLM9t7I4$H}LH]Hu5H@HIM9uMmMuE1H]H #IHILHHH #H@L6HM&H (&1A臹H]HEHtCt H{ #H} #AH]Ht"L3Ct H{ \ #HT #LMuH}HEHt6 #EuH@HHo:HH;EuH@HĨ[A\A]A^A_]U #IH@HHHt8Ct H{ +#HIL +#H]HEHuIH]HEHCH{YIt I n +#Lf +#`u?I`t3HpC +#Eu'VH%IAt/H{ ! +#$IEt1H} +#H]Hu6VIH #H]Hu<IH]Ht0fffff.L3Ct H{ #H #LMuH}HEHt #L# HvfDUHAWAVAUATSHEAIIHHHm:HHEEHHL`HhL)HL9EL9K<HKHHpfǁHHH)HIcH9rLAHLMPHpfǀHHH)HIcH9vTHHHttI9~I H; +LHHH`J<HpLHJJLHL)HHH9vH)IHHu#IHh蘵H5c&H T&H}LhW)PHDž`@#H`(o7)PHng edge.HH5H adding HH0Hied whenHH(Ht specifHH H arg sloHHHion nodeHHHdestinatHHHInvalid H@=HuHP1LH5R:H~L/#yKHHAHHEDeDuHHuHH`J<HpfǁJHEDeDuHHuHlHk:HH;EuHĘ[A\A]A^A_]#Q#IHhH5&H &H}LhYW)PHDž`@#H`( 07)PHng edge.HH(Hhen addiHH Hcified wHHHexes speHHHnode indHHHInvalid H@0HuHP1L艤H5‹:H+}L#Z#IHhH5&H &H}Lh bW)PHDž`@#H`(Um7)PHng edge.HH0Hhen addiHH(Hcified wHH Hslot speHHHode arg HHHsource nHHHInvalid H@8HuHP1L脣H5:H&|L#U#IHhH5&H &H}Lh"]W)PHDž`0#H`(0l7)PHng edge.HH Hhen addiHHHsmatch wHHH type miHHHArgumentH@(HuHP1L蛢H5ԉ:H={L# IPt H`I#E1LeMuMH%IALeMt6HEL9t!HX@t Hx#HI9uH}LLe#EuEu LhMuD{H}#EtH}#LhMuRIALhM<HpL93HX@t Hxo#HI9uIPt H`E#E1LeMuMH!IALeMt6HEL9t!HX@t Hx#HI9uH}LLe#EuEu LhMuDwH}#EtH}#LhMuNIALhM8HpL9/HX@t Hxk#HI9uIPt H`A#E1LeMuMHIALeMt6HEL9t!HX@t Hx#HI9uH}LLe#EuEu LhMuDsH}#EtH}#LhMuJIALhM4HpL9+HX@t Hxg#HI9u IPt H`=#E1LeMuMHIALeMt6HEL9t!HX@t Hx"HI9uH}LLe"EuEuLhMu:rH}"EtH}"LhMuLIALhMt:HpL9t5HX@t Hxq"HI9uHhLpV"Eu +LILo"L" UHAWAVAUATSHEAHHIIHc:HHEEI`IhH)HL9eE\H;HOJHBHHH<H.HHH)HIcH9 +H HHHH)HIcH9vHHHu9LHL)HHH9H)IHHH9HpfǁHED}DuHHuI`J<HpfǁHHHHED}DuHHuH/b:HH;EuHĘ[A\A]A^A_]"{"IHhH5&H -&H}Lh/胙W)PHDž`@"H`(e7)PHving edgHH(Hhen remoHH Hcified wHHHexes speHHHnode indHHHInvalid Hf@0e.@2HuHP1L譛H5:HOtL"~"IHhH5&H 0&H}Lh9膘W)PHDž`@!"H`(6)PHving edgHH0Hhen remoHH(Hcified wHH Hslot speHHHode arg HHHsource nHHHInvalid Hf@8e.@:HuHP1L袚H5ہ:HDsL"s"IHhH5&H %&H}LhF{W)PHDž`@"H`(44)PHng 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DUHAWAVAUATSHhHIIH\8HHEH{hHuHpH2H{hHPHHDžHDžHHLLM9LILLH]DMw HHH HMLcII}tBIOHIGL98I@IHAH9Lyuff.0'!IIVHP(HH H H@HHHIEHH Ht HIEHH0"HIOHWfff.HHHuIL9HHH9LLtwHC K(DC,IuHL'HKHtffff.HHHu#HCH9tHH HAH9HYuHHH9uW)E)EE?IIH)HLLLLL)H9cM9E1fHHK HY HN4Iv HD DDLAtHSt*H~H9}t(HvH{Au')H9tRfHH{AtH{u-Ht\1fDL: u&HI9u@fff.Ht/&!t&fH}Ht L0HLLILL)HI9HHHH)HL0L8LL)H9 + M9E1fff.HHK HY HN4Iv HD DDLAtHSt*H~H9}t(HvH{Au')H9tRfHH{AtH{u-Ht\1fDL: u&HI9u@fff.Ht/%!t&fH}H L0HL0L8ILL)HI9HH0HHfHCHHHLL(H@I9LHMtuH fffff.IEHt.HH HHHHHP0t IL;rHHHXI9u!I}u II9rHI9HHHLHMuAF tIF(IN HHt@IN HHu*1HAHH T%!W) HDž0)HDžIML9L;Iw HH}Ht7H(H(H;0tSHHH(HI9uwf.LH(H;0s*L8H(HI9u@H HH H輴fff.HI9CIML9fff.L;Iw HH}輿Ht7H(HH;tSHHHHI9uwf.LHH;s*L8HHI9u@HHHHܳfff.HI9CINpIHIvI8Lt$H$HHL LyHHt H !H HLLHt H(!I9aIHI9tsMtWIEHt6HH HHHHH P0:IL9ufDI}IL9uHIHH91L L 1LL/HHXHC@HtHcK8;} QS8LtH0H;HHILH HL$HI<$>I$IHH`L0H gLI9LIHH9.LIHH9LIHH9ƅ HDž(ƅ0H LHRUI<$fH%H m%1A\LHH5%H!LH5%H!HHH0HHPH(H H@H@HH L3 t H0L!H]Ht*L3Ct H{ !H!LMuH}HEHt!HHH~8HH;ELHh[A\A]A^A_]H!H]HsI$H]H\yH%H %1ACLIH -H]H =!R!H 8HHH5G8HHd!!H Z8HHH58HH1!!IHH5R%H I%H L4H%HHHH%HHHHHm^AH7%H LHaE1H58HLt! It H !HXHt?H`H9t$Lh@t Hx!LL9uHXHH`!@u u&HHuFHP! tH0}!HHuQIAHHt?HH9t$Lh@t Hx>!LL9uHHH!EuIL9!H]HHܿII$I$HCt H{!H!II$I$HOCt H{!H!H]H<YI tH0S!uIH)!H]HIH ̉H]HHҾIHHuNX{IHHu;EH覾IHHu",IHHuIHHt Hw!H HtH(_!H]Hu8IH]Ht*L3Ct H{ ,!H$!LMuH}HEHt !IHH莾L,! @UHAWAVAUATSH8Hh|8HHEIIAEMeIuIDIEUH}dHMwMH}hMVM]IL9r 1HIIIJHPHHDAEMMMeMML}LMfDHCH9tL9r1IHL9KHtHSL9uWu)1ffffff.T A: u6HH9uXH{ LLM!LMMH}L}/HHcqHCH9tL9r1IHL9uUCtHCHu"ffffff.HHHuMI!IJHLE0!HIILL!HC(HEHCHIGHxH*HHH H*XHuLHDH MxI*AO t Y.H*XAO uK 6IrIV1LH ^f: - `2(\H,HH1H,.HCH9HCLvMwIFLHut'L9r 1HIHIHHtHH gH!IHHuIGIWHI_HHH<H@INLL91IH DM3MLEL}LMDHCH9t L!L9/KHtHSL9uQu#1fT A: u6HH9uH{ LLMD!MLMLEH}L}toHHsfffff.HCH9t L!L9Ct HCHu (HtHHuaH!HIHIGH8HH;EuH(HH8[A\A]A^A_]s!IA$tH{ !IH!L3! HUHAWAVAUATSHHE8HHEIIAIL9t I7IW蹁IIIMgL9MMDHHEȀx8Hp HLHtHI9uNffffff.II;sHMHIHI9uLHujHI9uII`I HIML9MIH0MID$H8L;0tjf.HI;Et=I I;(tHI HI9unLHHI9uWHCIH98HuA@I I;(tH HI HI9uLHHI9uAƆfAdžH:8HH;EuHĨ[A\A]A^A_]!!IH`QH5a$H K%HxL`fvW)@HDžP F!HP(ޣ5)@Ht exist.HHH set musHHHInput toH@AH%HxH@LyE1H58HQL ! 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Lf.UHSPHH0H9tHHVH}ƃHfǃH[]DUHAWAVSPIHIL%r HKH{0HuH{@u+HrHH{0LAƆH[A^A_]@u HH?1ffff.UHAWAVATSIH:IIXHt.fff.L;Ct H{ !H !LMuIHIdžHHt` !Ip薂IHHt,f.L;Ct H{ , !H$ !LMuI8Idž8Ht !M Mt`fDM<$I|$8HtfH !HHuI|$(ID$(Ht !AD$t -I|$ !L !MMuIIdžHtx !IHt0fffff.L;Ct H{ L !HD !LMuIIdžHt !IHt(fDL;Ct H{ !H !LMuIIdžHt !IHt(fDL;Ct H{ !H !LMuIIdžHt !IxHtJfDL#L{(HC(MtIfLI !Ct H{ : !H2 !LMuIhIdžhHt !IPHt IX -!I0Ht I8 -!IHt I  -!IHt I -!IHt I -!IHt I~ -!IIH9t`HtHP(M`MtlIhL9tQf.LcHCH[MtL3L -!I9uI`HP M`MuLMh !MHMtFIPL9t+fH{HCH[HtHPI9uIHLMP !I@HtHHCHI Htf.HV !HHuIIdžHt2 !IHt*L;Ct H{ !H !LMuIIdžHt!IL[A\A^A_]>HHPH!I HMXUH]fDUHSPHHH[]r!@UHAWAVAUATSHHMLHMIHuIH8HHEп=!IHHEH[H]HtHCL,$HME1E1LLHUj1LuI>M&HtHPHt#HHCHuHHPH!I6LHUI?t H$H i$1ALzQII6ƆEHEEHUL>I?t@H5$H $1AL'H~8HH;Eu)LHH[A\A]A^A_]IH~8HH;EtW!IIIHtGCt H{!H.IHt#HHCHuHHPH!L!L! @UHAWAVAUATSHIHH}8HHEHc + Z2(\H,HH1H,.HCH9HCLvMwIFLHut'L9r 1HIHIHHtHH gH!IHHuIGIWHI_HHH<H@INLL91IH DM3MLEL}LMDHCH9t L!L9/KHtHSL9uQu#1fT A: u6HH9uH{ LLMT!MLMLEH}L}toHHsfffff.HCH9t L!L9Ct HCHu (HtHHuaH!HIHIGHw8HH;EuH(HH8[A\A]A^A_]!IA$tH{ !IH!LC! 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H(HXHEH HM誽W)HDžHHxW)HDžH}1UHDžHx1L.1Hx41H91I$LPH9vQI$LHPHt?I$LHPH@H(u H@ @uuH@ DhADE1I$LLLPHHZ x(P H;`svLLLxEt/HI$LHP(II$LHPHLHH;xHHH9fE'MH@ LpMuL5/L+`H@B4W)pHEƅpHput_axesHqHAHscan_inpHEAVHppt H}!IF HcH|HueHLpLiHH;1H˦MHCHHxHH9HHp HH;LHLHHLu}LMb7HHHxf.HH H9ZHpH9tHHpڶH0HpH裪HHHpHH;s HHLHrfHHHH;xI$H@0W)pHEƅpDžqbodyƅuHpLIpt H}MW)pHEHxtt1ALpH1HDžH9r4fLHL;xs6HxHMIHDžH9sHHxL;xrIHHHpLLHHpHt HxI9uw1E1I9iL)IIL;`HHDžH>E1k@u HH?1@u HH?-1&@u HH?1@u HH?1LhlOtI$LLP(HÃ{(ueHS A~(Mv L;`AFjMvZHBكJHLH\5DHxC(H{@HHHS A~(rf{(Ht0HI,C(H{@H^LHC AN HH AFHXMv1Hp]IcVHH+`H 4W)HDžƅ Hput_axesHHAHscan_outHƅHHxRHnLht H^t~nLctE1fff.IF J\HEHtHcM;}QUHDfH}'H}HHH0ZIM9|HEHtYHcM;}QQUHDLhtYHzI@SH3IGHL+fH}LhtH}H4HHuY;x}lHcffff.IF L|HEHtHcM;}QUHDfH}'H}HHL0YHH;x|HXZHBكJHu"Hz@{HBHXHAtHpHYHHp"eHpv]fDLILL;`2MtLCH}lNHHt H"LMtBHL9t'MI)HfH8HI0uHLLH Ht H(H@Ht HHH?~,HH;EuHĈ[A\A]A^A_](IH5N HZLZHpHHpLHB0/IIF IFIF1H5.H7\LK ( IH5HZL[HpHHpLoH//IIG IGIG1H5.H[LyH}kH}](hILH5$HYLZHpHL`yHpLH//IIG IGIG1H5.H[LIpt H}u8MILMIptILMIpt H}KuILgzIEt H} u IEtIL/H HIHpH IH}HH}^IH}HH}3IplIH HIH HIHHILMIHIHIEH}IHHpXMIMLHZHMIHp莟IMu`IMuSxIMuIniIHpXMu1VQIptHH}6ILhHpWMt'LIHpHtHxIH}HHHt HLMtBHL9tpMI)HH訞HI0uHLIH Ht H(1H@Ht HHLY Lfff.UHAWAVAUATSHhMLHHIHxHcx,HHEH0L5x,I^@HLHuv,HH@H0HfHnfLLHEEIFHHIhL0HHL L=qw,ILHDž HDžHDžHDžDž(LL]LLHLxHH9LHH߻HH0LMHH +LHH谻HH0LH]HLHH脻LHUHHL0HHLt HHH5u,HHH0wH`v,HH;EuLHh[A\A]A^A_]HSHeHHHL0HHLt HOH/H5Vu,HH H0H` UHAWAVAUATSHhMLHHIHxHsu,HHEH0L5u,I^@HLHs,HH@H0HfHnfLLHEEIFHHIhL0HHLL=t,ILHDž HDžHDžHDžDž(LLmLLHLxHHILHH︔HH0L]HHLHHHH0L.H]HLHH蔸LHeHHL0HHLt HH H5 s,HH H0Hps,HH;EuLHh[A\A]A^A_] HSHeHHHL0HHLt H_H? H5fr,HH H0 Hp  UHAWAVAUATSHAIHh{(H]uCLk AMMuMtlEEfEA(IG H@HH茏C(H{@5H辺ILk AMMuMuI}@HIMuEEfEvI^ HH;BHIuAFA(RH/H@HuH]/HELc`MIFHEEE1fDM9t^HEH@ J\IF Ht%IcN;}QAVHD'ffffff.HEH8贸H}HXHHJIM9|HEH[A\A]A^A_]@uHH?@uHH?11HH}`H^  fDUHAWAVSH(IHp,HHEH`Hp2D$D$$HNH NL1AH褫 +D$D$$HOH OLAHe +D$D$$HOH OL1AHٯ +H5LHOAH踉 +H5<H@QAH藉 +H5HUQE1Hy +H5H.L>RH +HW)HDž fDžVƅHHkW)ƅ HDžHor typesHHAll TensHƅHHHHٰ +H .H0H tH8H0HPHH~ +H5H +H56H膂 Hz -H5~Q H襀 -LHQHPH9tbHtHP(t HL LMtVHL9t;fDHX@t Hx HI9uHHP uLLt H H`@HD,HH;EuLH([A^A_] IuKUIIHPH9tHtHP(uHP t H@LMtDHL9tOf.HX@t Hx HI9uHLtH LIH`?L ffff.UHAWAVAUATSHIH,HHEIEPIIwW)PHDž`)0HDž@H0HsH]1H襌}uHE+H}EH}@HBHEH@ HpHXH;`s HHXHPHp,YIELPHpHXH;`sHHXIs"HPHpXIiL%@u HH?1fff.HH[LHIEHLHPH8H;@t=H`L8I0L8MgAu9MwI~HucffH0HgL8MgAtL臇AGI@,H踲IMwI~HtIAfLpHXH;`s'L HXLHL9-HPHp}WLHL9IEH@0W)pHEƅpDžqbodyƅuHpLIpt H}MW)pHEHDžHpHdIroLfff.IELHPHHxH;MsHHxHL9r!f.HpLqdHL9rIHHPHpLLH HpHt HxI9uE11I9IELP L)HLxL9HDžHI1L@u HH?B1;@uHH?@uHH? 11H@u HH?1H@u HH?1fDMdIELHP(A|$(LHH H;A|$(H>/uID$ @HpL6]}LuH]4Hp7EHx@HfHH]KLsMHt E~E)LH{@H艮ILsE~E~%I^ HH;7HIuAFE1IFHIF HtD;8}AE~A|$(H?/t/2HH8褭HH5A|$(H/uID$ H@HuH/HH HYHHDLcxMtlIDL#IF Ht$IcN;}QAVHD,fffff.HH8HH袮HL?HIuH(uLw HCuJ腂HH@(Hx@fH詭IHLp CtRL{A^IFكANHuI~@>HĬIFt LH@? HLJHpGLLfHHHL9MtLH}L0MtNH8L9t3MI)Hfffff.HȉHI0uH0LL8THPHt HX<Hv,HH;EuH[A\A]A^A_]u(#IAD$(H50H%GL]GHpHLHpLwH-/IIF IFIF1H5.HALL(IHLH5HN@L@HpHLHpLHW-/IIF IFIF1H5#.H,AL0Ipt H}u(HHGNIptILHHIHpHLIHHIHpHIpH}IL0MIL0Mw9IHHu]g&IHHuJTIHHu9C>IHpHHu"IHpHtHxhIH}誆L0MtCH8L9tYMI)HHxHI0uH0L8 HPHt HXL1 L@UHAWAVAUATSHhMLHHIHxH#s,HHEH0L=r,I_@HLH5q,HH@H0HfHnfLLHEEIGHHIhL0HHLL51r,ILHDž HDžHDžHDžDž(LL=LLHnLxHHLHHmHH0L-HHLHHmH0LLHpsHHL0HHLt HHH5p,HHH0rH;q,HH;EuLHh[A\A]A^A_]HSHeHHHL0HHLt HJH*H51p,HHH0H[ UHAWAVSH(HHyp,HHEHtZC(t+HUp,HH;Eu4HH([A^A_]?H3p,HH;EuHH([A^A_]C(HH5HMH}_<AHuHH'/HHC HCHCE1H5d.Hm;Hqv(/INjC(EH5AHMH}HMeEHuLH '/IIG IGIG1H5.H:L II2IEt H}t$LIEt H}rEtHL ffff.UHAWAVSH(IHn,HHEH`HD$D$$H{}H t?L1AH -D$D$$H?H ?LAH赖 -D$D$$H?H ?LAHv -D$D$$H?H ?Ls1AH -H58H?AHt -HW)HDž fDžVƅHH]W)ƅ HDžHor typesHHAll TensHƅHHHHK -H5rH.L@Hi -H5yH.L@HG -H `.H0H bH8H0HPHHi -H5Hj -H5>"Hm +H59Q H襀 +LH芇HPH9tbHtHP(t H\ LMtVHL9t;fDHX@t Hx+ HI9uHHP uLLt H H`vHtm,HH;EuLH([A^A_] IuKUIIHPH9tHtHP(uHP t HPLMtDHL9tOf.HX@t HxHI9uHLtH LIH`uL ffff.UHAWAVAUATSHIHBl,HHEIEPIIwW)PHDž`)0HDž@H0HsH]1H襌}uHE+H}EH}@HBHEH@ HpHXH;`s HHXHPHp,YIELPHpHXH;`sHHXIs"HPHpXIiL%@u HH?1fff.HH[LHIEHLHPH8H;@t=H`L8I0L8MgAu9MwI~HucffH0HgL8MgAtL臇AGI@,H踲IMwI~HtIAfLpHXH;`s'L HXLHL9-HPHp}WLHL9IEH@0W)pHEƅpDžqbodyƅuHpLIpt H}MW)pHEHDžHpHdIroLfff.IELHPHHxH;MsHHxHL9r!f.HpLqdHL9rIHHPHpLLH HpHt HxI9uE11I9IELP L)HLxL9HDžHI1L@u HH?B1;@uHH?@uHH? 11H@u HH?1H@u HH?1fDMdIELHP(A|$(LHH H;A|$(H/uID$ @HpL6]}LuH]4Hp7EHx@HfHH]KLsMHt E~E)LH{@H艮ILsE~E~%I^ HH;7HIuAFE1IFHIF HtD;8}AE~A|$(H/t/2HH8褭HHEA|$(H/uID$ H@HuH/HH HYHHDLcxMtlIDL#IF Ht$IcN;}QAVHD,fffff.HH8HH貮HL?HIuH(uLw HCuJ腂HH@(Hx@fH詭IHLp CtRL{A^IFكANHuI~@>HĬIFt LH@? HLJHpGLLfHHHL9MtLH}L0MtNH8L9t3MI)Hfffff.HȉHI0uH0LL8dHPHt HXLHc,HH;EuH[A\A]A^A_](3IAD$(H5HFLGHpHLHpLH/IIF IFIF1H5.HALL(IHLH5JH @L=@HpHLHpLH7/IIF IFIF1H5.H,AL@Ipt H}u(HHGNIptILHHIHpHLIHHIHpHIpH}IL0MIL0Mw9IHHu]g&IHHuJTIHHu9C>IHpHHu"IHpHtHxxIH}誆L0MtCH8L9tYMI)HHxHI0uH0L8HPHt HXLA L@UHAWAVAUATSHhMLHHIHxHS`,HHEH0L=_,I_@HLHe^,HH@H0HfHnfLLHEEIGHHIhL0HHLL5a_,ILHDž HDžHDžHDžDž(LLMLLHLxHH)LHHϣHH0L=HHLHH蠣H0LLH`HHL0HHLt HHH5^,HHH0Hk^,HH;EuLHh[A\A]A^A_]HSHeHHHL0HHLt HZH:H5a],HHH0Hk UHAWAVSH(HH],HHEHtZC(t+H],HH;Eu4HH([A^A_]?Hc],HH;EuHH([A^A_]C(HH5rHMH}_<AHuH(Hy/HHC HCHCE1H5D.Hm;Hv(?INjC(EH5HPMH}HMeEHuLH/IIG IGIG1H5̿.H:L  II2IEt H}t$LIEt H}EtHL ffff.UHAWAVSH(IH[,HHEH`HD$D$$H6}H /?L 1AH +D$D$$HW?H U?L AH赖 +D$D$$Hc?H f?LAHv +D$D$$H?H ?L1AH +H57H?AHt +HW)HDž fDžVƅHHݓW)ƅ HDžHor typesHHAll TensHƅHHHHK +H5H.L@Hi +H5H.L@HG +H @.H0H bH8H0HPHHi +H5Hj +H5!Hm He -H5<%Hk -LH<HPH9t`HtHP(t HzLMtTHL9t9@HX@t HxKHI9uHHP uLLt H H`+,Htk,HH;EuLH([A^A_]3IIu>HIIHPH9tHtHP(uHP t HhLMt<HL9t[fHX@t Hx;HI9uHL t H H`1+L? LfUHAWAVAUATSHIHRj,HHEIEPIIwW)PHDž`)0HDž@H0H賵H]1Hw}uHE+H}PtEH}@H肟HEH@ HpHXH;`s HHXHPHplDIELPHpHXH;`sHHXIs"HPHpDIiL%@u HH?1fff.HH[LH>IEHLHPH8H;@t=HLL8I0L8MgAu9MwI~HucffH0HRL8MgAtLrAGI@,HIMwI~Ht5AfLpHXH;`s'L HXLHL9-HPHpBLHL9IEH@0W)pHEƅpDžqbodyƅuHpLIpt H}MW)pHEHDžHpHPIroLfff.IELHPHHxH;MsHHxHL9r!f.HpLOHL9rIHHPHpLLH HpHt HxI9uE11I9IELP L)HLxL9HDžHI1L@u HH?B1;@uHH?@uHH? 11H@u HH?1H@u HH?1fDMdIELHP(A|$(LHHH;A|$(H~/uID$ @HpLvH}LuH]4HpwoEHx@H覚HH]KLsMHt E~E)LH{@HəILsE~E~%I^ HH;"HIuAFE1IFHIF HtD;8}AE~A|$(H/t/2HH8HHuA|$(HP/uID$ H@HuH /HH HYHHDLcxMtlIDL#IF Ht$IcN;}QAVHD,fffff.HH8QHHHLW*HIuH(uLw HCuJmHH@(Hx@fHIHLp CtRL{A^IFكANHuI~@>HIFt LH* HL5HpuLLfHHHL9MtLH}@uL0MtNH8L9t3MI)Hfffff.HuHI0uH0LL8HPHt HX|Ha,HH;EuH[A\A]A^A_](cIAD$(H5pHe2L2HpHL0HpLH8/IIF IFIF1H5.H -LL(IHLH5H+L+HpHL߲HpLH/IIF IFIF1H5c.Hl,LpIpt H}u(HHGNIptILHHIHpHLIHHIHpHIpH}IL0MIL0Mw9IHHu]g&IHHuJTIHHu9C>IHp#rHHu"IHpHtHxIH}qL0MtCH8L9tYMI)HHqHI0uH0L8IHPHt HX1Lq L@UHAWAVSH(IH^,HHEH`H׍D$D$$HKmH D/Lҿ1AHĆ -D$D$$Hl/H j/LAH腆 -D$D$$Hx/H {/LAHF -D$D$$H/H /LC1AH躊 -H5'H/AHd -HW)HDž fDžVƅHHMW)ƅ HDžHor typesHHAll TensHƅHHHH -H5BH.L0H9 -H5IH.L0H -H 0.H0H H8H0HPHHY -H5˽HZ -H5H] +H5g<%Hk +LHrHPH9t`HtHP(t HLMtTHL9t9@HX@t Hx[HI9uHHP uLL*t H H`bHX,HH;EuLH([A^A_]CIIu>HIIHPH9tHtHP(uHP t HxLMt<HL9t[fHX@t HxKHI9uHL0t H H`!aLO LfUHAWAVAUATSHIHW,HHEIEPIIwW)PHDž`)0HDž@H0H賵H]1Hw}uHE+H}PtEH}@H肟HEH@ HpHXH;`s HHXHPHplDIELPHpHXH;`sHHXIs"HPHpDIiL%@u HH?1fff.HH[LH.ӍIEHLHPH8H;@t=HLL8I0L8MgAu9MwI~HucffH0HRL8MgAtLrAGI@,HIMwI~Ht5AfLpHXH;`s'L HXLHL9-HPHpBLHL9IEH@0W)pHEƅpDžqbodyƅuHpLIpt H}MW)pHEHDžHpHPIroLfff.IELHPHHxH;MsHHxHL9r!f.HpLOHL9rIHHPHpLLH HpHt HxI9uE11I9IELP L)HLxL9HDžHI1L@u HH?B1;@uHH?@uHH? 11H@u HH?1H@u HH?1fDMdIELHP(A|$(LHHH;A|$(H^/uID$ @HpLvH}LuH]4HpwoEHx@H覚HH]KLsMHt E~E)LH{@HəILsE~E~%I^ HH;"HIuAFE1IFHIF HtD;8}AE~A|$(H_/t/2HH8HH腚A|$(H0/uID$ H@HuH/HH HYHHDLcxMtlIDL#IF Ht$IcN;}QAVHD,fffff.HH8QHHHLW*HIuH(uLw HCuJmHH@(Hx@fHIHLp CtRL{A^IFكANHuI~@>HIFt LH* HL5HpuLLfHHHL9MtLH}@uL0MtNH8L9t3MI)Hfffff.HuHI0uH0LL8HPHt HXH'O,HH;EuH[A\A]A^A_](sIAD$(H5+H 2LX2HpHL0HpLH/IIF IFIF1H5.H -L!L(IHLH5HI+L}+HpHL߲HpL&Hw/IIF IFIF1H5C.Hl,LIpt H}u(HHGNIptILHHIHpHLIHHIHpHIpH}IL0MIL0Mw9IHHu]g&IHHuJTIHHu9C>IHp#rHHu"IHpHtHxIH}qL0MtCH8L9tYMI)HHqHI0uH0L8YHPHt HXAL L@UHAWAVSH(IHK,HHEH`H D$D$$HmH .L1AHĆ +D$D$$H'/H %/LݺAH腆 +D$D$$H3/H 6/LAHF +D$D$$H^/H p/La1AH躊 +H5'H/AHd +HW)HDž fDžVƅHH譃W)ƅ HDžHor typesHHAll TensHƅHHHH +H5`H.L_0H9 +H5gH.Lh0H +H .H0H H8H0HPHHY +H5HZ +H5H] HU -H5|,VH[ -LH,HPH9t`HtHP(t HJLMtTHL9t9@HX@t HxHI9uHHP uLLt H H`HD[,HH;EuLH([A^A_]IIu>HIIHPH9tHtHP(uHP t H8LMt<HL9t[fHX@t Hx HI9uHLt H H`L LfUHAWAVSH(IH&Z,HHEH`H@ӍD$D$$H&H &L1AHd -D$D$$H&H 'La1AH؆ -H5 -$H)'AH` -H5H(AH` -H5OH(E1Hx` -H5GH}-E1HZ` -H5@H.E1H<` -H5He/E1H` -H5eH.L()H\ -HW)HDž fDžVƅOHH IW)ƅ HDžHor typesHHAll TensHƅHHHH~ -H .H0H H8H0HPHHIU -H5PHZV -H5 H+Y +H57,VH[ +LHbHPH9t`HtHP(t HZLMtTHL9t9@HX@t Hx+HI9uHHP uLLt H H`QHtH,HH;EuLH([A^A_]IIu>HIIHPH9tHtHP(uHP t HHLMt<HL9t[fHX@t HxHI9uHLt H H`PL LfUHAWAVSH(IHVG,HHEH`H0 D$D$$H&H &L1AHd +D$D$$H&H &L1AH؆ +H5#H&AH` +H5;H?(AH` +H5mHT(E1Hx` +H5eH8-E1HZ` +H5^Ht.E1H<` +H5H /E1H` +H5H.L(H\ +HW)HDž fDžVƅOHHW)ƅ HDžHor typesHHAll TensHƅHHHH~ +H .H0H H8H0HPHHIU +H5nHZV +H5p H+Y HnQ -H5#(HJW -LH?(HPH9tgHtHP(t HLMt[HL9t@ff.HX@t HxHI9uHHP uLLt H uH`HV,HH;EuLH([A^A_]IuKUIIHPH9tHtHP(uHP t HLMtDHL9tOf.HX@t HxHI9uHLtH {LIH`L ffff.UHAWAVAUATSHHU,HHEW)EHE)EHEHH@0)pHEƅpHthen_braHqDžynchHpH8Hpt H}Ht'HHpHUHMHHpLxE11H8HH@0W)pHEƅpHelse_braHqDžynchHpIpt H}#Mt'IHpHUHMLLpLxE1E1H8HL@P ILhI)LHH`M)ILXL9qL9HDžPM1<@u HH?1@u HH?#1f.IHH@L4C(A;F(H8HP(ILHr{(HC H LAF(H/uIV R H9H/uI^ A(uMw Cu=@L]AG(I@HɈIMw Ct\L{A^IFكANHtt-LH0I~@HهIFuHL%DHPHHPL9LH@HtHtHH}Ht H}H}Ht H}H:R,HH;EuHĸ[A\A]A^A_](K(LIAF(HHHHD$H)H$H5H)L)HpHPLL$ AHpLH[ /IEIE IEIEE1H5%.H.L2&(HHHHD$H')H$H5H)L)HpHPLL~ AHpH4H/HHC HCHCE1H5.HH(HIH5`H'L,HpH`LXPAHpLH'/I$ID$ ID$ID$E1H5.HL(IH5H'L'HpHhL`AHpLH/I$ID$ ID$ID$E1H5\.HeLi]I1I,IpuIpt H}ELH@HIIpt H}EHILIpt H}vELtkLH@HucfIHuciIH}HufmIH@Hu:=Ipt1H}&Ipt,H}!ILH@HtHtHH}Ht H}H}Ht H}L fUHAWAVAUATSHhMLHHIHxHM,HHEH0L=M,I_@HLHL,HH@H0HfHnfLLHEEIGHHIhL0HHLL5M,ILHDž HDžHDžHDžDž(LL LLHHLxHHLHHHHH0LHHLHHHHH0LLH?NHHL0HHLt HHH5K,HH{H0AH -L,HH;EuLHh[A\A]A^A_]HSHeHHHL0HHLt HHH5K,HHH0H* fUHAWAVAUATSHhMLHHIHxH#K,HHEH0L=J,I_@HLH5I,HH@H0HfHnfLLHEEIGHHIhL0HHLL51J,ILHDž HDžHDžHDžDž(LL=LLHFLxHHLHHEHH0L-HHLHHEHH0LLHoKHHL0HHLt HHH5H,HHH0qH:I,HH;EuLHh[A\A]A^A_]HSHeHHHL0HHLt HIH)H50H,HHH0HZ fUHAWAVAUATSHhMLHHIHxHSH,HHEH0L=G,I_@HLHeF,HH@H0HfHnfLLHEEIGHHIhL0HHLL%aG,ILHDž HDžHDžHDžDž(LLmLLH3CLxHHILHHCHH0L]HHLHHBH0LH]HLHHBHE0LLHxHHHL0HHLt HHH5E,HHH0zHCF,HH;EuLHh[A\A]A^A_]HSHeHHHL0HHLt HRH2H59E,HHH0Hc ff.UHAWAVAUATSHhMLHHIHxHSE,HHEH0L=D,I_@HLHeC,HH@H0HfHnfLLHEEIGHHIhL0HHLL%aD,ILHDž HDžHDžHDžDž(LLmLLH3@LxHHILHH@HH0L]HHLHH?H0LH]HLHH?HE0LLHxEHHL0HHLt HHH5B,HHH0zHCC,HH;EuLHh[A\A]A^A_]HSHeHHHL0HHLt HRH2H59B,HHH0Hc ff.UHAWAVSH(IHvB,HHEH`H萻D$D$$HH SL1E1Hj -D$D$$H6H 7L1AH+o -H5ŸHAH +H5'HJW +LH/^HPH9tgHtHP(t HLMt[HL9t@ff.HX@t HxHI9uHHP uLLt H H`MHD,HH;EuLH([A^A_]IuKUIIHPH9tHtHP(uHP t HLMtDHL9tOf.HX@t HxHI9uHLtH LIH`LL ffff.UHAWAVAUATSHHB,HHEW)EHE)EHEHH@0)pHEƅpHthen_braHqDžynchHpH8Hpt H}Ht'HHpHUHMHHpLxE11H8HH@0W)pHEƅpHelse_braHqDžynchHpIpt H}3Mt'IHpHUHMLLpLxE1E1H8HL@P ILhI)LHH`M)ILXL9qL9HDžPM1<@u HH?1@u HH?#1f.IHH@L4C(A;F(H8HP(ILHr{(HC H LAF(H/uIV R H9Hk/uI^ A(uMw Cu=@L]AG(I@HɈIMw Ct\L{A^IFكANHtt-LH0I~@HهIFuHL%DHPHHPL9LH@HtHtHH}Ht H}H}Ht H}Hj?,HH;EuHĸ[A\A]A^A_](K(LIAF(HHHHD$H)H$H5OHS)Lh)HpHPLL$ AHpLH;.IEIE IEIEE1H5.H.LB&(HHHHD$H(H$H5H(L(HpHPLL~ AHpHDH.HHC HCHCE1H5`.HH(XIH5H'L,HpH`LXPAHpLH.I$ID$ ID$ID$E1H5Π.HL (IH5Hh'Ln'HpHhL`AHpL$Hu.I$ID$ ID$ID$E1H5<.HeLy]I1I,IpuIpt H}ELH@HIIpt H}EHILIpt H}ELtkLH@HucfIHuciIH}HufmIH@Hu:=Ipt1H}&Ipt,H}!ILH@HtHtHH}Ht H}H}Ht H}L fUHAWAVAUATSHhMLHHIHxH#;,HHEH0L=:,I_@HLH59,HH@H0HfHnfLLHEEIGHHIhL0HHLL51:,ILHDž HDžHDžHDžDž(LLLLH~LxHHLHH~HH0L HHLHHp~HH0LLH/HHL0HHLt HHH58,HHH0QH:9,HH;EuLHh[A\A]A^A_]HSHeHHHL0HHLt H)H H508,HHH0H: fUHAWAVAUATSHhMLHHIHxHS8,HHEH0L=7,I_@HLHe6,HH@H0HfHnfLLHEEIGHHIhL0HHLL5a7,ILHDž HDžHDžHDžDž(LLMLLH{LxHH)LHH{HH0L=HHLHH{HH0LLH_HHL0HHLt HHH56,HHH0Hj6,HH;EuLHh[A\A]A^A_]HSHeHHHL0HHLt HYH9H5`5,HHH0Hj fUHAWAVAUATSHhMLHHIHxH5,HHEH0L=.5,I_@HLH3,HH@H0HfHnfL/LHEEIGHHIhL0HHL,L%4,ILHDž HDžHDžHDžDž(LL}LLH#yLxHHYLHHxHH0LmHH*LHHxH0L-H]HLHHxHE0LLHh~HHL0HHLt HHH53,HHH0Hs3,HH;EuLHh[A\A]A^A_]HSHeHHHL0HHLt HbHBH5i2,HHH0Hs ff.UHAWAVAUATSHhMLHHIHxH2,HHEH0L=.2,I_@HLH0,HH@H0HfHnfL/LHEEIGHHIhL0HHL,L%1,ILHDž HDžHDžHDžDž(LL}LLH#vLxHHYLHHuHH0LmHH*LHHuH0L-H]HLHHuHE0LLHh{HHL0HHLt HHH50,HHH0Hs0,HH;EuLHh[A\A]A^A_]HSHeHHHL0HHLt HbHBH5i/,HHH0Hs ff.UHAWAVSH(IH/,HHEH`HD$D$$HSH L 1E1Hj +D$D$$HH LҞ1AH+o +H5HeAH I -H52H=AHH -HW)HDž fDžVƅ<HH 2W)ƅ HDžHor typesHHAll TensHƅHHHHkp -H5H5.L,H艁 -H .H0H H8H0HPHH> -H5hH%? -H5HA +H5PHAHH +HW)HDž fDžVƅ<HHgW)ƅ HDžHor typesHHAll TensHƅHHHHkp +H5ٝH.LH艁 +H .H0H H8H0HPHH> +H5H%? +H5;HA H9: -H5H@ -LH -HPH9tbHtHP(t HLMtVHL9t;fDHX@t HxHI9uHHP uLLZt H EH`kH?,HH;EuLH([A^A_]sIuS]IIIHPH9tHtHP(uHP t HLMt<HL9t[fHX@t Hx{HI9uHL`t H KH`qL LfUHAWAVAUATSHH>,HHEW)EHE)EHEHH@0)pHEƅpHthen_braHqDžynchHpH8Hpt H}Ht'HHpHUHMHHpLxE11H8HH@0W)pHEƅpHelse_braHqDžynchHpIpt H}Mt'IHpHUHMLLpLxE1E1H8HL@P ILhI)LHH`M)ILXL9L9HDžPM.1@u HH?1IHH@L4C(A;F(XH8HP(ILH[{(HC H LAF(H5/HuIV R H9HtLqMt#A(u*IG OfIN LqMuL5$/A(tL}FAG(I@ HqIG LHHPHHPL9LH@Ht/HtH"H}Ht H}H}Ht H}Hy;,HH;EuHĸ[A\A]A^A_]7(K(LIAF(HHHHD$H H$H5HLHpHPLLcAHpLH.IEIE IEIEE1H5d.HmLq&(,HHHHD$HfH$H5-H[LFHpHPLLAHpHsH.HHC HCHCE1H5.HH(IH5H<LHpH`LXAHpLHf.I$ID$ ID$ID$E1H5-.H6L:(IH5 HLHpHhL`AHpLSH.I$ID$ ID$ID$E1H5.HL]I1I,IpuIpt H}(ELGH@HI&ILHIpt H}EHIpt H}ELtkLH@HucfIHuciIH}HufmIH@Hu:=Ipt1H}&Ipt,H}!ILH@Ht1HtH$H}Ht H}H}Ht H}L@ UHAWAVSH(IHV7,HHEH`HpD$D$$HxH 3L˓1E1H_ -D$D$$HH "L1AH d -H5HAH= -H5HAH= -HW)HDž fDžVƅHH&W)ƅ HDžHor typesHHAll TensHƅHHHHKe -H5H.L Hiv -H .H0H H8H0HPHH2 -H5HH4 -H5`H6 +H5H@ +LHFHPH9tbHtHP(t HLMtVHL9t;fDHX@t HxHI9uHHP uLLjt H UH`[6H,,HH;EuLH([A^A_]IuS]IIIHPH9tHtHP(uHP t HLMt<HL9t[fHX@t HxHI9uHLpt H [H`a5L LfUHAWAVAUATSHH+,HHEW)EHE)EHEHH@0)pHEƅpHthen_braHqDžynchHpH8Hpt H}Ht'HHpHUHMHHpLxE11H8HH@0W)pHEƅpHelse_braHqDžynchHpIpt H}Mt'IHpHUHMLLpLxE1E1H8HL@P ILhI)LHH`M)ILXL9L9HDžPM.1@u HH?1IHH@L4C(A;F(XH8HP(ILH[{(HC H LAF(H5/HuIV R H9HtLqMt#A(u*IG OfIN LqMuL5/A(tL}FAG(I@ HqIG LHHPHHPL9LH@Ht?HtH2H}Ht H} H}Ht H}H(,HH;EuHĸ[A\A]A^A_]G(K(LIAF(HHHHD$HH$H5HLHpHPLLcAHpL)Hz.IEIE IEIEE1H5D.HmL&(<HHHHD$H!H$H5HLHpHPLLAHpHH.HHC HCHCE1H5.HH(IH5ZHLHpH`LXAHpLHF.I$ID$ ID$ID$E1H5 .H6LJ(IH5HLHpHhL`AHpLcH.I$ID$ ID$ID$E1H5{.HL]I1I,IpuIpt H}8ELWH@HI&ILHIpt H}EHIpt H}ELtkLH@HucfIHuciIH}HufmIH@Hu:=Ipt1H}&Ipt,H}!ILH@HtAHtH4H}Ht H}"H}Ht H}LP UHAWAVSH(IH$,HHEH`H`D$D$$H3H L1E1H_ +D$D$$HH L1AH d +H5HEAH= +H50HAH= +HW)HDž fDžVƅHH\W)ƅ HDžHor typesHHAll TensHƅHHHHKe +H5H.LHiv +H b.H0H H8H0HPHH2 +H5fH4 +H5H6 H/ -H5H4 -LHHPH9tbHtHP(t H蜽LMtVHL9t;fDHX@t HxkHI9uHHP uLL:t H %H`KH4,HH;EuLH([A^A_]SIuS]IIIHPH9tHtHP(uHP t H舼LMt<HL9t[fHX@t Hx[HI9uHL@t H +H`QL_ LfUHAWAVAUATSHHHIHHh3,HHEH0L%3,M|$@LLHy1,HH@H0HfHnfL3HEEID$HHIhL0LLL6L5{2,ILHDž HDžHDžHDžDž(LL臽LLHM.LHjHHH,.LH3HHL0HHLt H|H\H5c1,HH9H0H1,HH;EuLHH[A\A]A^A_]胺HSHeHHHL0HHLt H׹H跸H50,HH蔸H0ZH UHAWAVSH(IHH1,HHEH{(HC H nAG(tFL4;AG(I@HefIG {(HK IG P;H (IH/{(HuHK I MA(uIG @ EH5HLH}HMLMw HuLAH.IIF IFIF1H5.HL蛸D@uKHH?xeIG {(H ې/I PPH H/,HH;Eu"H([A^A_]12eIG {(;(HH5HA H}AHuHbH.HHC HCHCE1H5.HH軷d(vIƋC(EH5H H}HM,HuLHg.IIF IFIF1H53.H<L@(HH5H H}; AHuHtH.HHC HCHCE1H5.HHͶy(苶HAG(EH5H H}HMAHuHHz.HHC HCHCE1H5E.HNHR I\IEuFMI&I!IBIIEt H}̵Et.H$IEuIEt H}襵tLɵLٲ IEtfDUHAWAVSHHIHH,,HHEH{(SHs H} ELuA(uI_ KHsHuS7L6AG(I@ucHbHI_ KHsHuH{@uKH-dHHsL讻H} H.,,HH;Eu4HH[A^A_]@uHH?@uHH?1|1ʴ(xIH5H H}8AHuLHr.IIF IFIFE1H5=.HFLJ](IƋC(EH5Hh -H}HM AHuLtH.IIF IFIFE1H5.HLͳ(舳IH5Ha H}AHuLH.IIF IFIFE1H5M.HVLZpH!HHHCHEt H}Et9L /HEu HEt H}轲EtL HH} H f.UHAWAVAUATSHHHHIHH),HHEH0L-),Me@LLH',HH@H0HfHnfL譱HHEEIEHHIhL0LL豰H(,HHHDž HDžHDžHDžDž(LLLLH$LLLLH$H0LHHg*HHL0LHt HHͯH5',HH誯H0pH9(,HH;EuHHH[A\A]A^A_]ILI^IHHL0LHt HKH+H52',HHH0ίL\ @UHAWAVAUATSHHHHIHHa',HHEH0L- ',Me@LLHs%,HH@H0HfHnfL-HHEEIEHHIhL0LL1Hv&,HHHDž HDžHDžHDžDž(LL肱LLHH"LLeLLH+"H0LhHH'HHL0LHt HmHMH5T%,HH*H0H%,HH;EuHHH[A\A]A^A_]pILI^IHHL0LHt H˭H諬H5$,HH般H0NLܪ 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H5HE1H D$D$$HpkH ˳LKg1E1H HW)HDž fDžTƅ/HHW)HDž@YH(Y()Hr types.HH-Htensor tHH(H to all HH Hut typesHHHand outpHHHn input HHHConstraiH@5HHHH +H ;.H0H0HPHH H5FH H5H H H5H LH֌HPH9t\HtHP(t HXLMtPHL9t5HX@t HxkXHI9uHHP uLL:Xt H %XH`+ƌH+HH;EuLH([A^A_]SXIu_iILMufIIHPH9tHtHP(uHP t H|WLMt@HL9tKfDHX@t HxKWHI9uHL0WtH WLIH`ŌLET ffff.UHAVSHIHx+HHEH`HR}H5H˰E1HT D$D$$HgH ,L}1E1Hk D$D$$H{gH xLr1E1H H5}H6.LTH  +H5<H6.LI H +H 8.H0H0HPHH H5HH H5Hy H H5e%H LH}ӌHPH9t HtHP(HP H`bÌH+HH;EuLH[A^]UI"IHPH9uHP HtHP(H` ÌL9R UHAVSHIHx+HHEH`HR{HDž(H5 HL(H H57HE1H' D$D$$HeH wL{1E1H> D$D$$HNeH LE1E1H H5a{H4.L H +H5H=5.L H +H R7.H0H0HPHHj H54H{ H5HL H H58yHk LHPьHPH9t HtHP(HP H`5H+HH;EuLH[A^]_SIHPH9uHP Ht HP(IH`L P @UHAVSHIHH+HHEH`H"yDž,H5-NHL,H Dž(?H5HL(H H5H E1H HDž H5HhL H H5^HAH~ D$D$$HbH L^1E1HE H5^HO3.LH +H 5.H0H0HPHH H5|IH- H5C~H HA H5H LHόHPH9t HtHP(HP H`羌Hp+HH;EuLH[A^]QI,I'I"IHPH9uHP HtHP(H`膾LM fff.UHAVSHIH+HHEH`HvDž,H5HDL,H Dž(?H5JH=L(Hj H5^H +E1Hl HDž H5SH%L H H5HLAH D$D$$H~`H LY\1E1H H5E\H1.LlH# +H 3.H0H0HPHH 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D$D$$HH L1E1Hke HW)HDž fDžTƅ达HH(W)HDž@ZH(')Hr types.HH-Htensor tHH(H to all HH Hut typesHHHand outpHHHn input HHHConstraiH@5HHHHf H -H0H0HPHHr4 H5٬H5 H5HT8 H0 H5(/Hs6 LHhHPH9t`HtHP(t HLMtTHL9t9@HX@t HxHI9uHHP uLL躾t H 襾H`H6+HH;EuLH([A^A_]ӾIugqILMunIIIHPH9tHtHP(uHP t HLMtHHL9tgfffff.HX@t Hx軽HI9uHL蠽t H 苽H`L迺 LfUH]f.UH]TfDUHLH -H]fDUHH-H]UH]f.UH]fDUHAWAVAUATSHhIHe4+HHEIEHW)EE -HEEvalufEeHuLHxEt H}薼IEHW)EEHEHsparse_vHMEalueEHuLHEEt H}GIEHW)EHEEHvalue_inH]fEtHuLHEEt H}IEHW)EEHEH]fEtsEHuLHEEt H}蹻IEHW)EHEEHvalue_flH]EoatHuLIEt H}oIEHW)EEHEH]EoatsEHuLHEEt H}*IEHW)EEHEHvalue_stH]EringEHuLIEt H}ܺIEHW)EHEEH_stringsHMH]EHuLELutH}H荺HHxHHHHHHMHDHHHH}HHDHHHLMMHDHHHMHDHHH LEMHDщуῃ@MDщуʀHHDHHUH)H33333333HH!HH!HHHHHH!HHH8HzHHHuH.1L.1LTILccMwLk LHHEIMuIG Ht#IcO;}QAWH\{(u*7HEH84eH}HfHÃ{(tHgC(Ls IIuHt\1LoH}11LHuH>H}H/+HH;EʸMAy(1L 1L/HHELcp(HC HtHcK;}QSH\{(u"/HH;4dHHeHÃ{(tHhC(Ls HV/+HH;EXHh[A\A]A^A_]Mt@AG1L[H}11LvHuH*MAx 1L1L8HHELcpHC HtHcK;}QSH\{(u"/HH;=cHHdHÃ{(tHqC(Ls H_.+HH;E \MtAAD$1LmH}11LHuH<HIƃx@1L"1LHHMcv@HC HtHcK;}QSH\{(A$HH;MbHHcHÃ{(H}MMMuL%.ID$(HuH.1L{1LIA|$LHHEE1ID$ N4IG HtIcO;}QAWH\{(u#0HEH8aH}HcHÃ{(tHC(Ls IIcD$I9|C(,IH5HH}ܳAHuL襲H&-IIF IFIFE1H5-HLV(蹴IH5HH}AHuL2H-IIF IFIFE1H5~-HL苴(FIH5HH}ֻAHuL迱H@-IIF IFIFE1H5 -HLp(ӳIH5HIH}胿AHuLLH-IIF IFIFE1H5-HL襳(`IH5/HH}AHuLٰHZ-IIF IFIFE1H5%-H.L2(IH5HH}轹AHuLfH-IIF IFIFE1H5-HL迲(zIH5IHtH}*:AHuLHt-IIF IFIFE1H5?-HHLL(IH5ֵH5H}'AHuL耯H-IIF IFIFE1H5̑-HLٱ1HHEupwH{HEu`gHkHEuPWH[HEu@GHKHEu07H;HEu 'H+HEuHHEt H}EL}yuHH}jeHEuM]HEuBRHEu7GHEu,<HEu!1HEu&HEu HEtH}fHH蝭 DUHH [(H1H9NHD]DUHH-]UH]f.UH]fDUHH ۯ-H]fDUHHů-H]UH]f.UH]鴯fDUHAWAVAUATSH8IH'+HHEIHW)EE -HEEvalufEeHuLHEt H}KHCH1Lz1L ILccMLk LHHEIfDMuIG Ht#IcO;}QAWH\{(u)6H]H;ZHHy\HÃ{(tHC(Ls IIuH%+HH;EuH8[A\A]A^A_]轮HEt H}KH苫 UHH Y(H1H9NHD]DUHHm-]UH]f.UH]fDUHH S-H]fDUHH=-H]UH]f.UH]餭fDUHAWAVAUATSH8IH%+HHEIHW)EE -HEEvalufEeHuLHEt H};HCH1Lx1LILccMLk LHHEIfDMuIG Ht#IcO;}QAWH\{(u)6H]H;XHHiZHÃ{(tHC(Ls IIuH#+HH;EuH8[A\A]A^A_]譬([IH5*HH}AHuLԩHU-IIF IFIFE1H5 -H)L- HHEt H}ƫEt$LH HEt H}蝫Hݨ DUHH X(H1H9NHD]DUHH=-]UHAWAVAUATSHHHIHH"+HHEH0L%c"+M|$@LLH +HH@H0HfHnfL胪HEEID$HHIhL0LLL膩L5!+ILHDž HDžHDžHDžDž(LL׬LLHLH躬HHH|LHM#HHL0HHLt H̩H謨H5 +HH艨H0OH!+HH;EuLHH[A\A]A^A_]өHSHeHHHL0HHLt H'HH5 +HHH0誨H8 UH]f.UH]ԨfDUH̨H -H]fDUHH-H]UH]f.UH]鄨fDUHAWAVAUATSH8IH+HHEIEHW)EE -HEEvalufEeHuLIEt H}IEHW)EEHEHsparse_vHMEalueEHuLIEt H}̧Mt MMIHuH~.1LTs1LzILccMmLk LHHEIMuIG Ht#IcO;}QAWH\{(u)6H]H;TSHHTHÃ{(tHC(Ls IIuMoMMuL%~.ID$(HuH}.1Lqr1L藽IA|$LHHE1ff.ID$ L4IG HtIcO;}QAWLlA}(u%3LmI}sRLHTIA}(tLAE(Mu HIcD$H9|H+HH;EuH8[A\A]A^A_]G(IH5ĩHH}AHuLnH-IIF IFIFE1H5-HLǥ(肥IH5QHrH}AHuLH|-IIF IFIFE1H5G-HPLT[H'HEuHHEt H}ݤEt'LHEu HEt H}豤H fUHH R(H1H9NHD]DUHHͥ-]UHAWAVAUATSHHHIHH+HHEH0L%s+M|$@LLH+HH@H0HfHnfL蓣HEEID$HHIhL0LLL薢L5+ILHDž HDžHDžHDžDž(LLLLHLHʥHHHLH]HHL0HHLt HܢH輡H5+HH虡H0_H(+HH;EuLHH[A\A]A^A_]HSHeHHHL0HHLt H7HH5+HHH0躡HH UHAWAVSHIHf+HHEH`H耒H9-H0L0LPHLd H5H -L HY H5H-L\ HY H5HV H5H' Hj H5 VHF LH;HPI9t HtHP(HP H` ًHi+HH;EuLHĸ[A^A_](HHPI9uHP HtHP(H`؋Hڝ fUHAWAVSHIH+HHEH`HHɢ-H0L0LPHLc H5IH-Lw H7X H5eH-L HX H5H H5AH H H51 -dH LHHPI9t HtHP(HP H`׋H+HH;EuLHĸ[A^A_]踟HHPI9uHP HtHP(H`\׋Hj fUHAWAVSHIH+HHEH`H蠏HY-H0L0LPHLb H5٫HK-L HV H5H1-L| -HV H55Hv H5HG H H5rHf LH[HPI9t HtHP(HP H`@֋H+HH;EuLHĸ[A^A_]HHHPI9uHP HtHP(H`ՋH fUHAWAVATSHIH+HHEHPH.H-H L L@HL` HW)HDžfDžTƅHH;W)HDž0H($)Htensors.HH&Hmeric teHH Ho all nuHHH types tHHHns inputHHHConstraiH@.HHHHSC H5H-LHHqT H5HB H5H HV H5H2 LH't HLMtIHL9t.f.HX@t Hx軛HI9uHLL蛛t H膛H@I9t HtHP(HP HPӋH+HH;EuLH[A\A^A_]蓛ILMuOIH@I9Iut~It HLMtEHL9HX@t Hx諚HI9uHL萚t H{H@I9uHP HtHP(HPҋL萗 LUHAWAVSH(H+HHEl.t)H+HH;E/Hl.H([A^A_]H=l.tW)ƅHDžHr(uint8)HHtensor(uHƅHDžƅH(uint16)HHƅHDžƅH(uint32)HHƅHDžƅH(uint64)HH ƅ) ƅ HDž0Htensor(iH!Dž)nt8)ƅ-HDžHHDž@HDž8ƅ8Hr(int16)H>H9ƅF)PHDž`ƅPHr(int32)HVHQƅ^HDžxHDžpHDžhƅhHr(int64)HnHiƅv)EEHEHfloat16)HEHtensor(fHMEHEHEHEEHr(float)HUHMEHEEH(double)HMHtensor(dHMEHEE HEHEHEHtensor(bHEEHi.Hi.Hi. %Hi.Hi.HH H i.HHHH=i.HH=ti.HH=ai.HH=Vi.۔HH=Ci.HH=8i.轔H H=%i.HH=i.蟔H8H=i.HH=h.联HPH=h.HH=h.cHhH=h.HH=h.EHuH=h.HH=h.*HuH=h.HH=h.HuH=zh.HH=oh.HuH=_h.HH=Th.ٓHGh.EEEEhP8  !-9t H H=H5g.HHH=g.)Hb +HH;E.H}ŔE*H}貔E!H}蟔EH}茔hHxsPH`Z8HHA H0(HHHݓIEt\IL=Mf.Mt>HIf.L9HX@t Hx苓HI9uH=f.L=f.pEEEEhP8 t HؒH=e.L  H}蹒ESH}覒EJH}蓒EAH}耒h8HxgP,H`N8 HH5 H0HHHёL;fUHAWAVATSHIH +HHEHPH.H-H L L@HLT HW)HDžfDžTƅHH;W)HDž0H($)Htensors.HH&Hmeric teHH Ho all nuHHH types tHHHns inputHHHConstraiH@.HHHHS7 H5H -LHHqH H5HB H5H HV H5H2 LH'؋t HLMtIHL9t.f.HX@t Hx軏HI9uHLL蛏t H膏H@I9t HtHP(HP HPNjH+HH;EuLH[A\A^A_]蓏ILMuOIH@I9Iut~It HLMtEHL9HX@t Hx諎HI9uHL萎t H{H@I9uHP HtHP(HPƋL萋 LUHAWAVSHIH+HHEH`H~Hy-H0L0LPHL9Q H5H-L HE H5Hя-LHE H5H H5Hg HH5H LH{ՋHPI9t HtHP(HP H``ŋH+HH;EuLHĸ[A^A_]hHHPI9uHP HtHP(H` ŋH fUHAVSHIH8+HHEH`HR}D$D$$HH L1E1Hy, D$D$$HwH LT1E1H0 H5@HB-LH.D H Gm-H0H H8H0HPHH H5~H H5%H HH5H LHӋHPH9t HtHP(HP H`ËH+HH;EuLH[A^]螋I"IHPH9uHP HtHP(H`=ËLK UHAVSH1 VHHPHtSH1HPHtCH1HPH(tH@H(u H@ @uu -H@ @u[A^]H1HP(IH1HPHL[A^]Nfff.UHAVSHIH+HHEH`HzD$D$$H(H L 1E1H) D$D$$HH LԖE1H) D$D$$H!H L1E1H4. H5H-LHrA H5HAH H -H0H0HPHHH5HH5VH HH5FHLHЋHPH9t HtHP(HP H`H+HH;EuLH[A^]ψI"IHPH9uHP HtHP(H`nL| @UHAWAVAUATSHIH*HHEHPHxHe-H H H@H(K HW)HDžfDžTƅ-HHW)HDž0臇LH(8$)Htensors.HH&Hmeric teHH Ho all nuHHH types tHHHns inputHHHConstraiH@.HHHH- H5;H'-LH> HDžHHIW)HDžƅfDžO1ƅ肆IHL萄W)@HDžPƅ@DžALessƅE))fDžAƅLHHDžHDžfDžBƅ0IMHLHM~LLHHH@HHHHLHPHH0W)@LHHDžPHHDž(HDž HDž)`HDžpƅ`fDžaO2ƅcIH`LMIW) HDž0ƅ -)0)@fDž0Aƅ2Dž!EquafDž%lHDžXHDžPfDžHBƅJ0lHIH0HwHHL{LdHL0L8L@H H(HPHHH0H0HXW) HDž0H`HhHpHDžHDžHDžx)HDž fDžCƅ臃IHL蕁MIW)HDžƅfDžOrƅ))ƅfDžO1ƅHDžHDžƅfDžO2ƅ0HIHHHL{LހHLLLHHHHH0HHW)HDžHHHHDžHDžHDž)`HDžp HhH`HH HpHHH0HhH`HhkHHhH`HhMHh`HxH`!HxLD LH5H]H5H. HqH5#HMLHBɋLxMtCHL9t(MI)HÀHHÀIǀuHxLLрL`MtAHhL9t&MI)HàHHàI`uH`LLh脀HH0~HrHH0`(4@LHH9XHtHP(t HLMOHL90fDHX@t Hx{HI9uHH[HH;H "HHX 0H@~`Hp~H~H~H~HH9HP LLU~t H@~H@H H9t HtHP(HP HP@H*HH;EuLH[A\A]A^A_]D~HL`MNHBHAahHL}AHAH[HLE}HAA`HgHL}HAE1HHHH92HP =HLMGHH@H H9HHP(HI9tMoAGt IN|ML9uH>|AHI9tMoAGt I |ML9uH{AAH")HM9tMoAGt I{MM9uL{AE1SZH HRYHL`MHhL9MI)HàH=HàI`uHLxMtCHL9t(MI)HÀHHÀIǀuHxLLzL`Mt@HhL9t%MI)HàHHàI`uH`LLhzzHH0tHhE1E1E1t H8zuMu=HzMt,M9tI\$AD$t -I|$yII9uLyt H yAE1E1Ht HXy0uMu:H@yMt)M9tI^AFt I~{yII9uLky`t HpVy1E1t H<yuMu9H yMt(L9tLsCt H{yLM9uLxt HxMt-Au'KDmHHpMkHHàI`uHHH9HtHP(u t HjxLMt>HL9t~@HX@t Hx;xHI9uHL xt H xH@H H9rHP HPHu L룐UHAWAVAUATSHIH2*HHEHPHLhHz-H H H@H: HW)HDžfDžTƅHH\ߒW)HDž0'wLH($)Htensors.HH&Hmeric teHH Ho all nuHHH types tHHHns inputHHHConstraiH@.HHHHm H5۝Hx-LbH. 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LHFHPH9t\HtHP(t HLMtPHL9t5HX@t Hx[HI9uHHP uLL*t H H`6H,+HH;EuLH([A^A_]CIu_iILMufIIHPH9tHtHP(uHP t HlLMt@HL9tKfDHX@t Hx;HI9uHL tH LIH`5L5 ffff.UHAVSHIHh++HHEH`HBH5 HAHAE D$D$$HH L|1E1Hk H5hHZ-LMHF~ H -H0H0HPHH: H5H; H5H> H7 H5.H< LHCHPH9t HtHP(HP H`3H3*+HH;EuLH[A^]I"IHPH9uHP HtHP(H`S3L fUHAWAVSH(IH)+HHEH`HH5C HAHC D$D$$HH JL1E1HVi HW)HDž fDžTƅHHjbW)HDž@UH(')Hr types.HH-Htensor tHH(H to all HH Hut typesHHHand outpHHHn input HHHConstraiH@5HHHHj H -H0H0HPHH]8 H5Hn9 H5H?< H4 H59,H^: LHCAHPH9tkHtHP(t HLMt_HL9tDffffff.HX@t HxHI9uHHP uLLt H H`0H$'+HH;EuLH([A^A_]IugqILMunIIIHPH9tHtHP(uHP t HLMtHHL9tgfffff.HX@t HxHI9uHLt H {H`/L课 LfUHAWAVSH(IH%+HHEH`HH5sHNE1H? H5hHn E1H? D$D$$HH _L1E1Hke HW)HDž fDžTƅ达HH^W)HDž@jH(2')Hr types.HH-Htensor tHH(H to all HH Hut typesHHHand outpHHHn input HHHConstraiH@5HHHHf H -H0H0HPHHr4 H5H5 H5HT8 H0 H5N(/Hs6 LHX=HPH9t`HtHP(t H*LMtTHL9t9@HX@t HxHI9uHHP uLLʾt H 赾H`,HD#+HH;EuLH([A^A_]IugqILMunIIIHPH9tHtHP(uHP t HLMtHHL9tgfffff.HX@t Hx˽HI9uHL谽t H 蛽H`+LϺ LfUH]f.UH]dfDUH\H -H]fDUHHm-H]UH]f.UH]fDUHAWAVAUATSHhIH!+HHEIEHW)EE +HEEvalufEeHuLHxEt H}覼IEHW)EEHEHsparse_vHMEalueEHuLHEEt H}WIEHW)EHEEHvalue_inH]fEtHuLHEEt H} IEHW)EEHEH]fEtsEHuLHEEt H}ɻIEHW)EHEEHvalue_flH]EoatHuLIEt H}IEHW)EEHEH]EoatsEHuLHEEt H}:IEHW)EEHEHvalue_stH]EringEHuLIEt H}IEHW)EHEEH_stringsHMH]EHuLELutH}H蝺HHxHHHHHHMHDHHHH}HHDHHHLMMHDHHHMHDHHH LEMHDщуῃ@MDщуʀHHDHHUH)H33333333HH!HH!HHHHHH!HHH8HzHHHuHx.1L.1LTILccMwLk LHHEIMuIG Ht#IcO;}QAWH\{(u*7HEH84eH}HfHÃ{(tHgC(Ls IIuHt\1LoH}11LHuH>H}H.+HH;EڸMAy(1L 1L/HHELcp(HC HtHcK;}QSH\{(u"/HH;4dHHeHÃ{(tHhC(Ls H+HH;EXHh[A\A]A^A_]Mt@AG1L[H}11LvHuH*MAx 1L1L8HHELcpHC HtHcK;}QSH\{(u"/HH;=cHHdHÃ{(tHqC(Ls H+HH;E \MtAAD$1LmH}11LHuH<HIƃx@1L"1LHHMcv@HC HtHcK;}QSH\{(A$HH;MbHHcHÃ{(H}MMMuL%u.ID$(HuHt.1L{1LIA|$LHHEE1ID$ N4IG HtIcO;}QAWH\{(u#0HEH8aH}H.cHÃ{(tHC(Ls IIcD$I9|C(<IH5HH}ܳAHuL赲H-IIF IFIFE1H5|-HLV(ɴIH5CHH}AHuLBH-IIF IFIFE1H5^|-HL蛴(VIH5зHEH}ֻAHuLϱH -IIF IFIFE1H5{-HL(p(IH5]HH}胿AHuL\H-IIF IFIFE1H5x{-HL赳(pIH5HH}AHuLH:-IIF IFIFE1H5{-H.LB(IH5wHxH}轹AHuLvH-IIF IFIFE1H5z-HLϲ(芲IH5H/H}*:AHuLHT-IIF IFIFE1H5z-HHL\(IH5HH}'AHuL萯H-IIF IFIFE1H5y-HL1HHEupwH{HEu`gHkHEuPWH[HEu@GHKHEu07H;HEu 'H+HEuHHEt H} EL+}yuHH}jeHEuM]HEuBRHEu7GHEu,<HEu!1HEu&HEu HEtH}vHH譭 DUHH uH(H1H9NHD]DUHH՗-]UH]f.UH]fDUH H -H]fDUHH-H]UH]f.UH]įfDUHAWAVAUATSH8IHE+HHEIHW)EE +HEEvalufEeHuLHEt H}[HCH1Lz1L ILccMLk LHHEIfDMuIG Ht#IcO;}QAWH\{(u)6H]H;ZHH\HÃ{(tHC(Ls IIuH,+HH;EuH8[A\A]A^A_]ͮHEt H}[H蛫 UHH EG(H1H9NHD]DUHHM-]UH]f.UH]fDUHH 3-H]fDUHH-H]UH]f.UH]鴭fDUHAWAVAUATSH8IH5+HHEIHW)EE +HEEvalufEeHuLHEt H}KHCH1Lx1LILccMLk LHHEIfDMuIG Ht#IcO;}QAWH\{(u)6H]H;XHHyZHÃ{(tHC(Ls IIuH+HH;EuH8[A\A]A^A_]转(kIH5HhH}AHuLH5-IIF IFIFE1H5t-H)L= HHEt H}֫Et$LH  HEt H}譫H DUHH uE(H1H9NHD]DUHH-]UHAWAVAUATSHHHIHH+HHEH0L%+M|$@LLH +HH@H0HfHnfL蓪HEEID$HHIhL0LLL薩L5+ILHDž HDžHDžHDžDž(LLLLHSLHʬHHHlSLH=YHHL0HHLt HܩH輨H5 +HH虨H0_HH+HH;EuLHH[A\A]A^A_]HSHeHHHL0HHLt H7HH5> +HHH0躨HH UH]f.UH]fDUHܨH -H]fDUHH}-H]UH]f.UH]锨fDUHAWAVAUATSH8IH +HHEIEHW)EE +HEEvalufEeHuLIEt H}*IEHW)EEHEHsparse_vHMEalueEHuLIEt H}ܧMt MMIHuHf.1LTs1LzILccMmLk LHHEIMuIG Ht#IcO;}QAWH\{(u)6H]H;TSHHTHÃ{(tHC(Ls IIuMoMMuL%f.ID$(HuHe.1Lqr1L藽IA|$LHHE1ff.ID$ L4IG HtIcO;}QAWLlA}(u%3LmI}sRLHTIA}(tLAE(Mu HIcD$H9|H ++HH;EuH8[A\A]A^A_]W(IH5HDH}AHuL~Hϼ-IIF IFIFE1H5m-HLץ(蒥IH5 H-H}AHuL H\-IIF IFIFE1H5'm-HPLd[H'HEuHHEt H}Et'LHEu HEt H}H fUHH u?(H1H9NHD]DUHH-]UHAWAVAUATSHHHIHH+HHEH0L%+M|$@LLH +HH@H0HfHnfL裣HEEID$HHIhL0LLL覢L5 +ILHDž HDžHDžHDžDž(LLLLHLLHڥHHH|LLHMRHHL0HHLt HH̡H5+HH詡H0oHX+HH;EuLHH[A\A]A^A_]HSHeHHHL0HHLt HGH'H5N+HHH0ʡHX UHAWAVSHIH+HHEH`HpȌH-H0L0LPHLd H5ɮH-L HY H5Hъ-L HY H5,HV H5lH' Hj H5\ VHF LH+HPI9t HtHP(HP H`H+HH;EuLHĸ[A^A_]8HHPI9uHP HtHP(H`H fUHAWAVSHIH&+HHEH`HnjH-H0L0LPHLc H5YH-L2 H7X H5Hq-L HX H5H H5H H H5 dH LHHPI9t HtHP(HP H` H)+HH;EuLHĸ[A^A_]ȟHHPI9uHP HtHP(H`L Hz fUHAWAVSHIH+HHEH`HŌH9-H0L0LPHLb H5H+-L +HV H5H-L7 +HV H5SHv H5HG H H5|rHf LHKHPI9t HtHP(HP H`0 H+HH;EuLHĸ[A^A_]XHHPI9uHP HtHP(H` H + fUHAWAVATSHIHD+HHEHPHČHLJ-H L L@HL` HW)HDžfDžTƅHH+;W)HDž0H($)Htensors.HH&Hmeric teHH Ho all nuHHH types tHHHns inputHHHConstraiH@.HHHHSC H5H-LHqT H5HB H5XH HV H5HH2 LHt HLMtIHL9t.f.HX@t Hx˛HI9uHLL諛t H薛H@I9t HtHP(HP HP} H+HH;EuLH[A\A^A_]裛ILMuOIH@I9Iut~It HLMtEHL9HX@t Hx軚HI9uHL蠚t H苚H@I9uHP HtHP(HPrL蠗 LUHAWAVSH(H*HHET.t)H*HH;E/HuT.H([A^A_]H=xT.-tW)ƅHDžHr(uint8)HHtensor(uHƅHDžƅH(uint16)HHƅHDžƅH(uint32)HHƅHDžƅH(uint64)HH ƅ) ƅ HDž0Htensor(iH!Dž)nt8)ƅ-HDžHHDž@HDž8ƅ8Hr(int16)H>H9ƅF)PHDž`ƅPHr(int32)HVHQƅ^HDžxHDžpHDžhƅhHr(int64)HnHiƅv)EEHEHfloat16)HEHtensor(fHMEHEHEHEEHr(float)HUHMEHEEH(double)HMHtensor(dHMEHEE HEHEHEHtensor(bHEEHQ.HQ.HQ. 5HQ.HQ.HH H Q.HH'HH=_Q.HH=TQ. HH=AQ.HH=6Q.HH=#Q.HH=Q.͔H H=Q.HH=P.诔H8H=P.HH=P.葔HPH=P.HH=P.sHhH=P.HH=P.UHuH=P.HH=P.:HuH=uP.HH=jP.HuH=ZP.HH=OP.HuH=?P.HH=4P.H'P.EEEEhP8  !-9t HH=H5yO.H*v!H=~O.9H*HH;E>H}ՔE*H}”E!H}诔EH}蜔hHx胔PH`j8HHQ H08HHHIEt\IL=-N.Mt>H)N.L9HX@t Hx蛓HI9uH=M.L=M.耓EEEEhP8 t HH=cM.L H}ɒESH}趒EJH}裒EAH}萒h8HxwP,H`^8 HHE H0,HHHL;fUHAWAVATSHIHD*HHEHPHH{-H L L@HLT HW)HDžfDžTƅHH+/W)HDž0H($)Htensors.HH&Hmeric teHH Ho all nuHHH types tHHHns inputHHHConstraiH@.HHHHS7 H5߷Hy-LHqH H5ԷHB H5XH HV H5HH2 LHt HLMtIHL9t.f.HX@t HxˏHI9uHLL諏t H薏H@I9t HtHP(HP HP}H*HH;EuLH[A\A^A_]裏ILMuOIH@I9Iut~It HLMtEHL9HX@t Hx軎HI9uHL蠎t H苎H@I9uHP HtHP(HPrL蠋 LUHAWAVSHIH*HHEH`H谴HYx-H0L0LPHL9Q H5 Hkw-LJ HE H53Hw-LWHE H55H H5Hg HH5H LHk HPI9t HtHP(HP H`PH*HH;EuLHĸ[A^A_]xHHPI9uHP HtHP(H`H* fUHAVSHIHh*HHEH`HBD$D$$HH L1E1Hy, D$D$$HH `Ld1E1H0 H5PH"v-LH.D H 'U-H0H H8H0HPHH H5H H5H HH5H LH HPH9t HtHP(HP H`H *HH;EuLH[A^]讋I"IHPH9uHP HtHP(H`-L[ UHAVSH1 VHHPHtSH1HPHtCH1HPH(tH@H(u H@ @uu +H@ @u[A^]H1HP(IH1HPHL[A^]܄fff.UHAVSHIH*HHEH`H°D$D$$H8H L1E1H) D$D$$HH LE1H) D$D$$H!H L1E1H4. 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HEu(Eu1Hz!HH;Eu:HHh[A\A]A^A_]H}s -EtH}s -H@!HH;Ett -H}q -H}q - HEt(HEuEuHp - H}os -EtH}`s -Hp - UHAWAVAUATSHMIHIH!HHEЃ/H1+HhHHLHjHpHHL@ED#HCHEHCHELkHHCHCAIGHEIGHEMwIIGIGLHLDHEHMHHLHEHEHMHHHELHEHEƅLLLHHHLVt Hoq -t HZq -H HH!HH;EuEHH[A\A]A^A_]uHH%uHHE1 17Hq -(p -IW)HDž0p -H()Hismatch.HHHtype misHHHication HHHe specifHHHAttributH@&HLn -Hx$IIF IFIF1H5t!H]TLap -IIt Ho -t\Lp -RIL誐t Ho -t Ho -HtIHcLl - fUHAWAVAUATSHhLEAHpIHH!HHEW)EHELq -IIWHxIsDEL}Mu0<DeMIILn -IL}ILeDeLuLLLQp -C7W)EHELpL6q -IIIsDELuMu(4LHHH{n -ILuHH]L}LLLo -C>HuHUHxDLEHEu(Eu1H!HH;Eu:HHh[A\A]A^A_]H}m -EtH}m -H`!HH;Et0n -H}9k -H}0k - HEt(HEuEuHj - H}m -EtH}m -Hj - UHAWAVAUATSHMIHIH!HHEЃ|H1KHhH3HLHH胵LEM4$M|$M9tfDfM.D;u$A\$HHDL,HDL,AD㉝IAM9uHD!HAHEHAHELqHHAHAHHAHEHAHELiHHAHALHLKDHEHMHHLHEHEHMHHHELHEHEƅLLLHHHYLt H*k -t Hk -HۋHϋHx!HH;Eu-HH[A\A]A^A_]u HH1k -(j -IW)HDž0j -H(c})Hismatch.HHHtype misHHHication HHHe specifHHHAttributH@&HLg -HK$IIF IFIF1H5G!H0NL4j -IIt Hi -t^Li -TIL}t Hi -t Hi -HGIH4Lf - f.UHAWAVAUATSHMIIHH!HHEЃH1+HhHkHHLjEIMvL9LDHHt$Hc;}QHDefHHt$H`!胯HH HJ Ph -H@H@HLHHHUf -HI9\E4$ID$HEID$HEMl$I$ID$ID$AIGHEIGHEMgIIGIGLHLDHEHMHHLHEHEHMHHHELHEHEƅLLLgHHHL蹇t Hf -t Hf -H胇HwH !HH;Eu-HH[A\A]A^A_]u HH1f -(qf -IW)HDž0Cf -H( y)Hismatch.HHHtype misHHHication HHHe specifHHHAttributH@&HLc -H$IIF IFIF1H5!HILe -IIt Hle -t^Le -TIL%t H>e -t H)e -HIH܅LJb - fUHGxH]UHAWAVAUATSHLI׉IDU D]DeH>!HHEMIII+H94BHcLH(MED]DU EMDeH(AIOHMIOHMIOIGIIGDHsHuHsHuHsHHCHC0HEH}H8H1H@HEHDž`HDžXHDžPHDžHDžh?DpHEHMHqHxHEHuHEHEHEHEHEDMDeD]DUHcHI}H0EpHXHtfffff.Hb -HHuHHHDžHHtb -0t H@b -H8!HH;EuILHĸ[A\A]A^A_]H}b -pjH}yb -HXHkvb -UHAWAVAUATSPIM>MnLL)HH9sH)LH[A\A]A^A_]>HIM9u>fI}a -AEt.I}a -I}Hu.<fff.AEuAEuI}HtfHa -HHuMeI}IEHta -A$t I}ta -MM9uM~H[A\A]A^A_]ff.UHAWAVSPIHufHCHC1H3_ -IFHCIINHKHIFIFIIvH{3L{@C@ufAHCPHCH1L^ -IF@HHIOHHPIWIH@H@HL{XCXufAHChHC`1Lr^ -IFXHHIOHHPIWIH@H@HAFxCxIFpHCpHH[A^A_]HЇH ЇHЇ@UHAWAVAUATSHxELxIՉuHHE!HHEW)EHEL3b -IIkH]IsDEL}Mu0<DeMIILp_ -IL}ILeDeLuLLL` -C7W)EHELxLa -IIIsDELuMu(4LHHH^ -ILuHH]L}LLLH` 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ffffff.UHAWAVAUATSHMIHIH!HHEЃH1 HhHHLHZI$HEED#HCHEHCHELkHHCHCAIGHEIGHEMwIIGIGLHLDHEHMHHLHEHEHMHHHELHEHEƅLLLHHHLUt H~} +t Hi} +HHH!HH;Eu-HH[A\A]A^A_]u HHD1=o} +(} +IW)HDž0| +H(})Hismatch.HHHtype misHHHication HHHe specifHHHAttributH@&HL.z +Ho$IIF IFIF1H5!HdL| +IIt H| +t\L<| +RILt H{ +t H{ +H苜IHzLx + UHAVSIH1謒HCu#HINu*HH9t2HL5u6HHINtu.HH H9uL9t HL[A^]1INt1H9uH !H!UHAWAVAUATSHhLEAHpIHH!HHEW)EHELR} +IIWHxIsDEL}Mu0<DeMIILz +IL}ILeDeLuLLL{ +C7W)EHELpL| +IIIsDELuMu(4LHHH z +ILuHH]L}LLLd{ +C>HuHUHxDLEHEu(Eu1HJ!HH;Eu:HHh[A\A]A^A_]H}y +EtH}uy +H!HH;Ety +H}v +H}v + HEt(HEuEuHrv + H}y +EtH}y +HPv + UHAWAVAUATSHMIHIHy!HHEЃH1ˏHhHHLHA$EED#HCHEHCHELkHHCHCAIGHEIGHEMwIIGIGLHLPDHEHMHHLHEHEHMHHHELHEHEƅLLLHHH^Lt H?w +t H*w +HHԗH!HH;Eu-HH[A\A]A^A_]u HHE1>0w +(v +IW)HDž0v +H(v)Hismatch.HHHtype misHHHication HHHe specifHHHAttributH@&HLs +H0$IIF IFIF1H5|!H%LIv +IIt Hu +t\Lu +RIL肖t Hu +t Hu +HLIH;Lr + UHAWAVAUATSHhLEAHpIHH!HHEW)EHELw +IIWHxIsDEL}Mu0<DeMIILt +IL}ILeDeLuLLLAv +C7W)EHELpL&w +IIIsDELuMu(4LHHHkt 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f.UHAWAVAUATSHMIIHH!HHEЃH1+HhHkHHLzEIMvL9LDHHt$Hc;}QHDefHHt$H!蓯HH HJ `h +H@H@HLHHHef +HI9\E4$ID$HEID$HEMl$I$ID$ID$AIGHEIGHEMgIIGIGLHLDHEHMHHLHEHEHMHHHELHEHEƅLLLgHHHL蹇t Hf +t Hf +H胇HwHP!HH;Eu-HH[A\A]A^A_]u HH1f +(f +IW)HDž0Sf +H({f)Hismatch.HHHtype misHHHication HHHe specifHHHAttributH@&HLc +HӤ$IIF IFIF1H5!HLe +IIt H|e +t^Le +TIL%t HNe +t H9e +HIH܅LZb + fUHGxH]UHAWAVAUATSHLI׉IDU D]DeHn!HHEMIII+H94BHcLH(MED]DU EMDeH(AIOHMIOHMIOIGIIGDHsHuHsHuHsHHCHC0HEH}H8H1H@HEHDž`HDžXHDžPHDžHDžh?DpHEHMHqHxHEHuHEHEHEHEHEDMDeD]DUHcHI}H0EpHXHtfffff.Hc +HHuHHHDžHHtb +0t H@b +Hh!HH;EuILHĸ[A\A]A^A_]H}b +pjH}b +HXHkvb +UHAWAVAUATSPIM>MnLL)HH9sH)LH[A\A]A^A_]>HIM9u>fI}b +AEt.I}a +I}Hu.<fff.AEuAEuI}HtfHa +HHuMeI}IEHta +A$t I}a +MM9uM~H[A\A]A^A_]ff.UHAWAVSPIHufHCHC1HC_ +IFHCIINHKHIFIFIIvH{3L{@C@ufAHCPHCH1L^ +IF@HHIOHHPIWIH@H@HL{XCXufAHChHC`1L^ +IFXHHIOHHPIWIH@H@HAFxCxIFpHCpHH[A^A_]HHH@UHAWAVAUATSHxELxIՉuHHu!HHEW)EHELCb +IIkH]IsDEL}Mu0<DeMIIL_ +IL}ILeDeLuLLL` +C7W)EHELxLa +IIIsDELuMu(4LHHH^ +ILuHH]L}LLLX` +E MUC>D$L$‰$EHULEH}uHEu(Eu1H'!HH;Eu:HHx[A\A]A^A_]H}a^ +EtH}R^ +H!HH;Et^ +H}[ +H}[ + HEt(HEuEuHO[ + H}] +EtH}] +H-[ + DUHAWAVAUATSHLI׉ID] DeDmHN!HHEMII+H9:BHcLMH(EMD] MEDeH(MDmAIOHMIOHMIOIGIIGDHsHuHsHuHsHHCHC0HEH}H8H1H@HEHDž`HDžXHDžPHDžHDžh?DpHEHMHqHxHEHuHEHEHEHEHEDMDmDeD]HcHI8H0EpHXHtfH[ +HHuHHHDžHHt[ +0t H@[ +HH!HH;EuILHĸ[A\A]A^A_]H}[ +poH}i[ +HXHkv[ +UHAWAVAUATSHxELxIՉuHHſ!HHEW)EHEL] +IIkH]IsDEL}Mu0<DeMIILZ +IL}ILeDeLuLLL%\ +C7W)EHELxL +] +IIIsDELuMu(4LHHHOZ +ILuHH]L}LLL[ +E MUC>D$L$‰$EHULEH}u HEu(Eu1Hw!HH;Eu:HHx[A\A]A^A_]H}Y +EtH}Y +H=!HH;EtY +H}V +H}V + HEt(HEuEuHV + H}LY +EtH}=Y +H}V + DUHAWAVAUATSH8HHH!HHEHHHHAH W)E)EE?H;HHCHH9f.HILH DH H1Hi-8ߝHHHH/H1H1HII/I1LH]HHsHMI9r 1LHIHEJHHHHt7HAL9tH9r1HHL9ueL9qH HuQHAL9tH!L9u?L9qH Hu+ff.IM!HEJHqfpW IMwMoIHEHx WH*HHH WH*XHH؃H Hx5H*Mt9Y.w0MHMJHH*XMuH HrHS1H ^f: -(\H,H HH1H,.HCH9HCH}H]HCHt)I9r1LHI@HMJHt#HI]I!HMJHuff.HEIL}HEJIHt*H@HKHtH9r 1HHH!HHEL8HEHHH;HHuHHHS -LH HS -HHHDžH8H@HDžHHHLHHHPXHt9HH@HVHtH9r 1HHH!LHGHHCHpHHKHhH`HCHCH 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IH5ٴ Hc L H}HMLMAHuLt H#IIF IFIFE1H5#HLͰ :I?I!IXHHrH sf1fHutH^H)f1fofoDfoL o\0od@ffoTPffoD`foLpfHHuHt"HTHoRfofH HuffpNffH~L9tJ HHH9uHUI9HH9t$HOH9t'HHpHH;Qu HH9u HH9uHHCI}0 5@uBHH?y@u7HH?@u,HH?@u!HH?1<11Z1@u HH61(輮 IH5Ե H -H}AHuL5 H#IIF IFIFE1H5#HL莮  (L IH5 Hu[L[H}HMLMmAHuL趫 H7#IIF IFIFE1H5#H L |(ʭ IH5 H H}*AHuLC H#IIF IFIFE1H5#HL蜭 (W IH5& H H}sAHuLЪ HQ#IIF IFIFE1H5#H%L) HEt H}Ĭ Eu"HEt HEuHLŬ H}HH'HEuHHEt H}\ EtsL H菩  0HH}Hu%HH}HtH} H}Hu1HH}Ht#H}HEu HEt H} H$  fff.UHH uH1H9NHD]DUHH=$]UHAWAVAUATSHhMLHHIHxH"!HHEH0L="!I_@HLH !HH@H0HfHnfL诪 LHEEIGHHIhL0HHL謩 L5!!ILHDž HDžHDžHDžDž(LL LLHLxHH٬ LHHH0Lܨ HH諬 LHHqH0L讨 LH1#HHL0HHLt H谩 H萨 H5 !HHm H03 H !HH;EuLHh[A\A]A^A_]跩 HSHeHHHL0HHLt H H H5!HHȧ H0莨 H  @UHAWAVAUATSHhMLHHIHxH !HHEH0L=!I_@HLH%!HH@H0HfHnfLߧ LHEEIGHHIhL0HHLܦ L5!!ILHDž HDžHDžHDžDž(LL- LLHLxHH LHHHH0L/ HHک LHHHH0L LH_ HHL0HHLt Hަ H辥 H5!HH蛥 H0a H*!HH;EuLHh[A\A]A^A_] HSHeHHHL0HHLt H9 H H5 !HH H0輥 HJ  fUH]f.UH] fDUHܥ H $H]fDUHHm$H]UH]f.UH]锥 fDUHAWAVAUATSHHIH!HHEI1LPHx(uH@ H@HtH~$H@HuH~$x(uH@ H}$Dx I1LP(HÃ{(uHC *H&C(H{@HRHC HDx ILPHI1LPHI1LPH(tH@H(uH@ @uH@ @|IHW)EHEEEaxisEHuLHEt H} HEIHW)EEHEHnew_axisHMEHuLHEt H}ţ Ht DE1I1LPx(uH@ H@HtHo|$H@HuH|$x(uH@ L`MtH|$L`MuL%{$AOAD$1AE)ЉEuM99yDEI1LP(HÃ{(uLs ANMnMu[;H$C(H{@HOILs ANMnMuI~@H0OIMn}Mu1fIM Ht'AE;}AEEH9u,\ffffff.I>hNLHOEH9t2HEIU H|H9 )ID$ HcHtCHcEH9H[rH[!HH;EuZHH[A\A]A^A_]@u HH?1@uHH?@uHH?11ѡ ( IH5 HBH}AHuL Hy#IIF IFIFE1H5D#HMLQ  ( IHEHD$HH$H5ʤ HL_ H}HMLMAHuLe H#IIF IFIFE1H5#HL辠 h(y IH5H H5MH}AHuL Hs#IIF IFIFE1H5>#HGLK ( IH5գ HH}ְAHuL H#IIF IFIFE1H5#HL؟ HGHBH=HEu&-HEu"HEuHHEt H}> Et/La Hq  HEu HEt H} - HJ  fUHH H1H9NHD]DUHH#]UHAWAVAUATSHhMLHHIHxH!HHEH0L=!I_@HLH%!HH@H0HfHnfLߝ LHEEIGHHIhL0HHLܜ L%!!ILHDž HDžHDžHDžDž(LL- LLHLxHH LHHH0L HH۟ LHHH0Lޛ H]H谟 LHHvHE0L趛 LH9HHL0HHLt H踜 H蘛 H5!HHu H0; H!HH;EuLHh[A\A]A^A_]远 HSHeHHHL0HHLt H H H5!HHК H0薛 H$  UHAVSHIH8!HHEH`HRH5HAHAD$D$$H H L -1E1HX;D$D$$HX H LA 1E1H?H5] -H1#L"H SH5 H#L>HRH #H0H0HPHHH5 HH5 Hf H H5hHLHzHPH9t HtHP(HP H`_ҁH!HH;EuLH[A^]i I"IHPH9uHP HtHP(H`ҁL  fffff.UHAWAVSH(IH&!HHEH`H@HDž(H5 HL(HcD$D$$H, H $LN 1E1H:9D$D$$Ht H L E1H8D$D$$HH L٥ 1E1Hu=HW)HDž fDžTƅ8HHW)HDž@d H(̪)Hr types.HH-Htensor tHH(H to all HH Hut typesHHHand outpHHHn input HHHConstraiH@5HHHH>H 4#H0H0HPHH| H5 H H5 H^HH5H}LHr߁HPH9tjHtHP(t H$ LMt^HL9tCfffff.HX@t Hx HI9uHHP uLL躖 t H 襖 H`΁H!HH;EuLH([A^A_]Ӗ IugqILMunIIIHPH9tHtHP(uHP t H LMtHHL9tgfffff.HX@t Hx軕 HI9uHL蠕 t H 苕 H`́L迒  LfUHAWAVSH(IH !HHEH`HD$D$$H( H  L+ 1E1H5D$D$$HQ H L0 -1E1H9HW)HDž fDžTƅ4HHW)HDž0} H(E)Hry type.HHHrbitraryHHH be of aHHHnsor canHHHInput teH@&HHHH:H5F -H#L( HKH #H0H0HPHHH5ڬ H H5 Hq HH5MH -LHہHPH9t]HtHP(t H7 LMtQHL9t6HX@t Hx HI9uHHP uLLڒ t H Œ H`ʁH4 -!HH;EuLH([A^A_] ILMu|IuS]IIIHPH9tHtHP(uHP t H LMtHHL9tgfffff.HX@t Hxۑ HI9uHL t H 諑 H`ɁLߎ  LfUHAWAVSH(IH!HHEH`HD$D$$H$ H ! LK 1E1H71D$D$$H]H i LP -1E1H5HW)HDž fDžTƅ0HHW)HDž0蝐 H(e)Hry type.HHHrbitraryHHH be of aHHHnsor canHHHInput teH@&HHHH6H5f -H"#LHHH g#H0H0HPHHH5 HH5 H HH5tHLHׁHPH9t]HtHP(t HW LMtQHL9t6HX@t Hx+ HI9uHHP uLL t H H` ǁHT!HH;EuLH([A^A_] ILMu|IuS]IIIHPH9tHtHP(uHP t H4 LMtHHL9tgfffff.HX@t Hx HI9uHL t H ˍ H`ŁL  LfUHAWAVSH(IH!HHEH`H0~H5: HIAH D$D$$HH LJ 1AH3-D$D$$HH L 1E1H1HW)HDž fDžTƅ,HHW)HDž0虌 H(1()Hnsor typHH Ho any teHHH types tHHHn outputHHHConstraiHf@(e.@*HHHH2H #H0H0HPHHH5п HH53 H HH5HLHӁHPH9teHtHP(t Ho LMtYHL9t>fHX@t Hx; HI9uHHP uLL - t H H`ÁHd!HH;EuLH([A^A_]# IugqILMunIIIHPH9tHtHP(uHP t HD LMtHHL9tgfffff.HX@t Hx HI9uHL t H ۉ H`L  LfUHAWAVSH(IH&!HHEH`H@zD$D$$H H L{ 1E1Hg)D$D$$H H L8 AH()D$D$$H H L 1AH-HW)HDž fDžTƅ(HHW)HDž@苈 H()Hr types.HH-Htensor tHH(H to all HH Hut typesHHHand outpHHHn input HHHConstraiH@5HHHH.HDžH575 HLH H .#H0H0HPHHvH5Z HH5 HX HH5]HwLHlρHPH9tdHtHP(t H LMtXHL9t=HX@t Hx HI9uHHP uLL躆 t H 襆 H`˾H HH;EuLH([A^A_]ӆ IuuIugqILMunIIIHPH9tHtHP(uHP t H LMt:HL9tYHX@t Hx軅 HI9uHL蠅 t H 苅 H`豽L迂  LfUHAWAVSH(IH HHEH`HuD$D$$H H  L+ 1E1H%D$D$$H H } L E1H$D$D$$H H YL E1H$D$D$$H H fLt AH`$D$D$$HH L5 AH!$D$D$$H! H M L 1E1H(HW)HDž fDžTƅ#HHW)HDž@臃 H()Hr types.HH-Htensor tHH(H to all HH Hut typesHHHand outpHHHn input HHHConstraiH@5HHHH)H5 H#LF H:H #H0H0HPHH}H5 HH5 H_ HH5wH~LHsʁHPH9tkHtHP(t H% LMt_HL9tDffffff.HX@t Hx HI9uHHP uLL躁 t H 襁 H`˹H HH;EuLH([A^A_]Ӂ ILMutIuKUIIHPH9tHtHP(uHP t H LMt@HL9tKfDHX@t Hxˀ HI9uHL谀 tH 蛀 LIH`跸L}  ffff.UHAWAVSH(IH HHEH`HpH5`H^E1HD$D$$Hs H L 1E1HD$D$$HiH mLԌ 1E1Hp$HW)HDž fDžTƅHHW)HDž@_ H(Ǒ)Hr types.HH-Htensor tHH(H to all HH Hut typesHHHand outpHHHn input HHHConstraiH@5HHHH%H /#H0H0HPHHwH5| HH5 HY HH5HxLHmƁHPH9teHtHP(t H~ LMtYHL9t>fHX@t Hx} HI9uHHP uLL} t H } H`˵H HH;EuLH([A^A_]} IugqILMunIIIHPH9tHtHP(uHP t H| LMtHHL9tgfffff.HX@t Hx| HI9uHL| t H | H`豴Ly  LfUHAWAVSH(IH HHEH`HlHxHDž(H5) HL(H D$D$$H\ H e L 1E1HD$D$$HJ H #L E1HD$D$$H4H L E1HjD$D$$Hj H LE 1E1HHW)HDž fDžTƅ4yHHW)HDž@z H()Hsor typeHH(H any tenHH Han be ofHHH types cHHHd outputHHHInput anHf@0.HHHH!H5E H]#L H92H -#H0H0HPHHH5{ HH5> H HH5?HLHHPH9t`HtHP(t Hzy LMtTHL9t9@HX@t HxKy HI9uHHP uLLy t H y H`+Ht HH;EuLH([A^A_]3y ILMIIuS]IIIHPH9tHtHP(uHP t HHx LMt<HL9t[fHX@t Hxx HI9uHLx t H w H`Lu  LfUHAWAVSH(IH6 HHEH`HPhD$D$$H - H  L 1E1HwD$D$$H H  LH E1H;D$D$$HH L E1HD$D$$H H I Lڃ 1E1HvHW)HDž fDžTƅHHވW)HDž@ev H(M&)Htensor tHH(H to any HH Hut typesHHHand outpHHHn input HHHConstraiH@0ype.@4HHHHH <#H0H0HPHHH5Q HH5 Hf HH5HLHzHPH9tbHtHP(t H,u LMtVHL9t;fDHX@t Hxt HI9uHHP uLLt t H t H`۬H$ HH;EuLH([A^A_]t IugqILMunIIIHPH9tHtHP(uHP t Ht LMtHHL9tgfffff.HX@t Hxs HI9uHLs t H s H`Lp  LfUHAWAVSH(IH HHEH`HdHDž(H5 H)L(H#D$D$$Ht H } L 1E1HD$D$$Hb H ;L E1HD$D$$HLH L E1HD$D$$H H L] 1E1HHW)HDž fDžTƅ HHڈW)HDž@q H()Hsor typeHH(H any tenHH Han be ofHHH types cHHHd outputHHHInput anHf@0.HHHH3H5] H#L HQ)H "#H0H0HPHHH5 HH5V H HH5#HLHกHPH9thHtHP(t Hp LMt\HL9tAfff.HX@t Hx[p HI9uHHP uLL*p t H p H`;H HH;EuLH([A^A_]Cp ILMu|IuS]IIIHPH9tHtHP(uHP t Hdo LMtHHL9tgfffff.HX@t Hx+o HI9uHLo t H n H`!L/l  LfUHAWAVSH(IHF HHEH`H`_HDž(H5 H=L(HD$D$$H H  Ln{ 1E1HZD$D$$H H NL/ E1HD$D$$H H Lz 1E1HHW)HDž fDžTƅ HHՈW)HDž@m H(l)Htensor tHH(H to any HH Hut typesHHHand outpHHHn input HHHConstraiH@0ype.@4HHHHH5 H,#LJ H$H 9#H0H0HPHHH5; HH5 Hc HH5HLHwHPH9t_HtHP(t H)l LMtSHL9t8HX@t Hxk HI9uHHP uLLk t H k H`ۣH$ HH;EuLH([A^A_]k ILMu|IuS]IIIHPH9tHtHP(uHP t Hk LMtHHL9tgfffff.HX@t Hxj HI9uHLj t H j H`Lg  LfUHAWAVSH(IH HHEH`H[HDž(H5 HL(H#D$D$$Ht H } Lw 1E1H D$D$$Hb H L E1H D$D$$Hz H \Lv 1E1H5HW)HDž fDžTƅH HHYшW)HDž@$i H( )Htensor tHH(H to any HH Hut typesHHHand outpHHHn input HHHConstraiH@0ype.@4HHHHjH5 H#L H H Y#H0H0HPHH!H56 H2H5 H HFH5P"H"LHHPH9t_HtHP(t Hg LMtSHL9t8HX@t Hxg HI9uHHP uLLjg t H Ug H`{H HH;EuLH([A^A_]g ILMu|IuS]IIIHPH9tHtHP(uHP t Hf LMtHHL9tgfffff.HX@t Hxkf HI9uHLPf t H ;f H`aLoc  LfUHAWAVSH(IH HHEH`HVD$D$$HA H dLr 1E1HD$D$$H H Lw AHD$D$$HH !Lcr 1E1H HW)HDž fDžTƅHH#͈W)HDž@d H(Vw)Hr types.HH-Htensor tHH(H to all HH Hut typesHHHand outpHHHn input HHHConstraiH@5HHHH- H #H0H0HPHHH5 HH5r H H+H55HLHHPH9tdHtHP(t Hc LMtXHL9t=HX@t Hx{c HI9uHHP uLLJc t H 5c H`[H HH;EuLH([A^A_]cc IugqILMunIIIHPH9tHtHP(uHP t Hb LMtHHL9tgfffff.HX@t HxKb HI9uHL0b t H b H`ALO_  LfUHAWAVSH(IHf HHEH`HRD$D$$H! H KLn 1E1HD$D$$H H iLxs E1HkD$D$$HH LFn 1E1HHW)HDž fDžTƅHHɈW)HDž@` H(9s)Hr types.HH-Htensor tHH(H to all HH Hut typesHHHand outpHHHn input HHHConstraiH@5HHHHH !#H0H0HPHHH5< HH5U H HH5HLHߧHPH9tgHtHP(t H_ LMt[HL9t@ff.HX@t Hx[_ HI9uHHP uLL*_ t H _ H`;H HH;EuLH([A^A_]C_ IugqILMunIIIHPH9tHtHP(uHP t Hd^ LMtHHL9tgfffff.HX@t Hx+^ HI9uHL^ t H ] H`!L/[  LfUHAWAVSH(IHF HHEH`H`NH58 H[AHOD$D$$Hn H OLzj 1E1HfD$D$$Hfn H LAj 1E1HHW)HDž fDžTƅHHňW)HDž@\ H(4o)Hr types.HH-Htensor tHH(H to all HH Hut typesHHHand outpHHHn input HHHConstraiH@5HHHH H #H0H0HPHHH5h HH5P H H H59HLHڣHPH9tbHtHP(t H[ LMtVHL9t;fDHX@t Hx[[ HI9uHHP uLL*[ t H [ H`;H HH;EuLH([A^A_]C[ IugqILMunIIIHPH9tHtHP(uHP t HdZ LMtHHL9tgfffff.HX@t Hx+Z HI9uHLZ t H Y H`!L/W  LfUHAWAVSHHIHF HHEH`H`JH58 H[AHOW)HDž ƅDžDCRH5, HLHD$D$$HOj H L2f 1E1HD$D$$Hj H Le 1E1HHW)HDžfDžTƅHHW)HDž@X H(j)Hr types.HH-Htensor tHH(H to all HH Hut typesHHHand outpHHHn input HHHConstraiH@5HHHHH Խ#H0H0HPHHH5- HH5 H~ HH5˴HLH蒟HPH9tjHtHP(t HDW LMt^HL9tCfffff.HX@t Hx W HI9uHHP uLLV t HV t H V H`֎H HH;EuLHH[A^A_]V IILMIIIIHPH9tHtHP(uHP t HU LMtCHL9twfHX@t HxU HI9uHLU t H{U t H fU H`茍LR  Lffff.UHAWAVSH(IH HHEH`HED$D$$Hf H <La 1E1HD$D$$H%H &L| -E1HD$D$$He H hLa 1E1H"HW)HDž fDžTƅ5HHFW)HDž@T H(yf)Hr types.HH-Htensor tHH(H to all HH Hut typesHHHand outpHHHn input HHHConstraiH@5HHHHPH5z -HҰ#LHn H #H0H0HPHHH5 HH5s H H,H56HLHHPH9teHtHP(t HR LMtYHL9t>fHX@t Hx{R HI9uHHP uLLJR t H 5R H`[H HH;EuLH([A^A_]cR ILMu|IuS]IIIHPH9tHtHP(uHP t HQ LMtHHL9tgfffff.HX@t HxKQ HI9uHL0Q t H Q H`ALON  LfUHAWAVSHHIHf HHEH`HAHW)ƅHDž HnearestHH5^ HLHD$D$$Ha H Ld] 1E1HPD$D$$HȤ H LPb E1HD$D$$Ha H L\ 1E1HHW)HDžfDžTƅMHH请W)HDž@zO H()Hr types.HH/Hl tensorHH(HY' to alHH Houtput 'HHH'X' and HHHn input HHHConstraiH@7HHHHH ʵ#H0H0HPHHH55 HH5{ Ht -H跿H5'HLH舖HPH9t`HtHP(t H:N LMtTHL9t9@HX@t Hx N HI9uHHP uLLM t HM t H M H`օH HH;EuLHH[A^A_]M IILMIIIIHPH9tHtHP(uHP t HL LMtCHL9twfHX@t HxL HI9uHLL t H{L t H fL H`茄LI  Lffff.UHAWAVSHIH HHEH`H<W)ƅHDž HnearestHH5 HYLHADž @H5m HL H5HDžH5N HLHhW)ƅHDžHhalf_pixHfDželƅH5 HLHW)ƅ$HDžHefer_floHHround_prHfDžorƅH5Q H\LHDžH5d HXLH D$D$$Hs[ H Lq -1E1HDD$D$$HH L-z AHD$D$$H} H L\ AHD$D$$HH L[ AHD$D$$HZ H Lp -1E1HHW)HDžƅfDžT1ƅ -HHW)pHDž@H H(n)pHr types.HH/Hl tensorHH(HY' to alHH Houtput 'HHH'X' and HHHn input HHHConstraiH@7HHHpH%H5cx H#L HCH #H0H0HPHHܼH5ћ HH5Hu H HH5 HݾLHҏHPH9tjHtHP(pt HG LMt^HL9tCfffff.HX@t HxKG HI9uHHP puLLG uTu`ult H F H`HY HH;EuRLHĘ[A^A_]HF tHF tHF uF ILMI!xIxI IIIpuKUIIHPH9tHtHP(puHP pt HE LMtGHL9fHX@t Hx[E HI9uHL@E u=u\uht H E H`6}LDB  HD tLItHD tHD uUHAWAVATSH@IH HHEHPH5D$D$$HvU H L{ -1E1HED$D$$HEU H LB -1E1HIW)HDžfDžVƅHHૈkHH̫HHHH{LMtBHL9t'HX@t Hx[C HI9uHLL;C W)HDžP(C HH(})H5BHvD CBHHHLH -$#H H H(H H@HH|H50 H荸H5o H^H衳H5H}LHrH@H9tjHtHP(t H$B LMt^HL9tCfffff.HX@t HxA HI9uHHP uLLA t HA HPyH HH;EuLH@[A\A^A_]A IILMTILMtSHL9t$HX@t HxA HI9uHLL@ LMuILMHL9@HX@t Hx@ HI9uIIIH@H9tHtHP(uHP t HA@ LMtEHL9tdff.HX@t Hx @ HI9uHL? t H? HPxL=  LfUHAWAVSH(IH& HHEH`H@0H5 H{E1H2D$D$$HzP H L]L 1E1HID$D$$HH Lbf -E1H D$D$$H P H |LK 1E1HHW)HDž fDžTƅ<HH訦W)HDž@s> H(P)Hr types.HH-Htensor tHH(H to all HH Hut typesHHHand outpHHHn input HHHConstraiH@5HHHHH5 e -HT#LHH #H0H0HPHHiH5Op HzH5j HK H莮H5 HjLH_HPH9tgHtHP(t H= LMt[HL9t@ff.HX@t Hx< HI9uHHP uLL< t H < H`tH HH;EuLH([A^A_]< ILMu|IuS]IIIHPH9tHtHP(uHP t H; LMtHHL9tgfffff.HX@t Hx; HI9uHL; t H {; H`sL8  LfUHAWAVAUATSHIH² HHEHPH+HDžH5y HLHD$D$$Hw H L(b -1E1HD$D$$H}H Lj E1HD$D$$Hq H L E1H^D$D$$H^K H rL 1E1HHW)HDžƅfDžT1ƅQHHL(W)HDž09 H(N)Ic types.L`I numericLhI to onlyLpIns inputLxHConstraiH@'HHHHHW)HDžƅfDžT2ƅmHHW)HDž08 H(q)L`LhLpLxIConstraiL0@'HHHH\HW)`HDžpƅ`fDžaT3ƅc6L(HHHRW)0HDž@ 8 H@(E)0Hor type.HHH tensor HHHn to anyHHL0@H`HHH0HH !#H H H@HHiH5z HzH5d HK H莨H5 HjLH_H@H9tgHtHP(0t H@7 LHMt[HPL9t@ff.HX@t Hx6 HI9uHHHP 0uLLP6 `uGuSLMtpHL9tUfHX@t Hxk6 HI9uH2HpN6 tH96 LMuLL6 uIuULMtrHL9tW@HX@t Hx5 HI9uH2H5 tH5 LMuLL5 t Hw5 HPmH HH;EuLH[A\A]A^A_]5 I0ILHM,I.LILMQIILMI`IBTIIIH@H9tHtHP(0uHP 0t H@34 LHMt?HPL9t$HX@t Hx4 HI9uHHLLP3 `uu#LMu/lHp3 tH3 LMt?HL9t$HX@t Hx|3 HI9uHLL\3 uu#LMu/lH03 tH3 LMt?HL9t^DHX@t Hx2 HI9uHL2 t H2 HPjL/  LfUHAVSHIH HHEH`H"#D$D$$HxC H sC LY -1E1HID$D$$HGC H BC L2b 1E1HH5NY -H#LHH5a H#LHH #H0H0HPHHuH5q H膧H5^ HW H蚢H5 HvLHkyHPH9t HtHP(HP H`PiH HH;EuLH[A^]Z1 I"IHPH9uHP HtHP(H`hL.  ffffff.UHAVSHIH HHEH`H2!D$D$$HA H A LW -1E1HYD$D$$HWA H RA LB` 1E1HHDž(H5To HL(HHDž H5o HL H趴H5W -Hh#LHH5_ HV#LĽHH #H0H0HPHH+H5n H<H5\ H -HPH5Z -H,LH!wHPH9t HtHP(HP H`gHO HH;EuLH[A^]/ I,I'I"IHPH9uHP HtHP(H`fL+  ff.UHAWAVSH(IHƥ HHEH`HD$D$$HH L; -1E1HD$D$$H> H L: E1HD$D$$H> H L: E1HD$D$$H> H Lj: 1E1HH5v -H#L -HDHW)HDž fDžTƅ7+HHW)HDž@, H(;?)Hr types.HH-Htensor tHH(H to all HH Hut typesHHHand outpHHHn input HHHConstraiH@5HHHHH ##H0H0HPHHH5G HH5WY Hͤ HH5b -HLHsHPH9tiHtHP(t H+ LMt]HL9tBffff.HX@t Hx[+ HI9uHHP uLL*+ t H + H`;cH HH;EuLH([A^A_]C+ IugqILMunIIIHPH9tHtHP(uHP t Hd* LMtHHL9tgfffff.HX@t Hx+* HI9uHL* t H ) H`!bL/'  LfUHAWAVSH(IHF HHEH`H`D$D$$H: H : L6 1E1HD$D$$H: H : LX; 1E1HHW)HDž fDžTƅɁHH"W)HDž ( H(g)Hr types.HHH tensor HHHn to allHHHConstraiH@HHHHVH #H0H0HPHH/H5h H@H5U H HTH5^ -H0LH%pHPH9t]HtHP(t H' LMtQHL9t6HX@t Hx' HI9uHHP uLLz' t H e' H`_HԞ HH;EuLH([A^A_]' IugqILMunIIIHPH9tHtHP(uHP t H& LMtHHL9tgfffff.HX@t Hx{& HI9uHL`& t H K& H`q^L#  LfUHAWAVSH8IH HHEH`HHDž(H5 HގL(HӪHDž H5 HL H親D$D$$H6 H L2 1E1H}D$D$$Hh H LN7 E1HAD$D$$H?6 H L2 1E1HHW)HDžfDžTƅ #HH܌W)HDž@$ H(o)Hsor typeHH(H any tenHH Han be ofHHH types cHHHd outputHHHInput anHf@0.HHHHH #H0H0HPHH˘H5 HܙH57Q H譜 -HH5 -H̚LHkHPH9tiHtHP(t Hs# LMt]HL9tBffff.HX@t Hx;# HI9uHHP uLL -# t H" H`d HH;EuLH8[A^A_]## IuoyILMuvIIIIHPH9tHtHP(uHP t H<" LMt@HL9t_fDHX@t Hx " HI9uHL! t H! H`ZL  LfUHAWAVSH(IH& HHEH`H@HDž(H5 HL(HcH5 HE1HD$D$$HK2 H L0. 1E1HD$D$$H2 H L- 1E1HD$D$$HK H L2 AHTD$D$$HH Lu2 AHD$D$$H H L62 AHHW)HDž fDžTƅ)HHW)HDž0 H(m)Hor type.HHHany tensHHHn be of HHHInput caH@ HHHH.H #H0H0HPHHH5 HH5sL H H,H56| HLHfHPH9teHtHP(t H LMtYHL9t>fHX@t Hx{ HI9uHHP uLLJ t H 5 H`[VH HH;EuLH([A^A_]c Iu_iILMufIIHPH9tHtHP(uHP t H LMt@HL9tKfDHX@t Hx[ HI9uHL@ tH + LIH`GULU  ffff.UHAWAVSH(IHf HHEH`H HDž(H5FZ H'L(H裡D$D$$H H L) 1E1HzD$D$$H H LK. E1H>D$D$$H>- H ͘L) 1E1HHW)HDž fDžTƅȻHHكW)HDž@ H()Htensor tHH(H to any HH Hut typesHHHand outpHHHn input HHHConstraiH@0ype.@4HHHHH #H0H0HPHHÏH5,W HԐH5/H H襓 HH5w HđLHbHPH9taHtHP(t Hk LMtUHL9t:DHX@t Hx; HI9uHHP uLL - t H  H`RHd HH;EuLH([A^A_]# IugqILMunIIIHPH9tHtHP(uHP t HD LMtHHL9tgfffff.HX@t Hx  HI9uHL t H  H`QL  LfUHAWAVSHHIH& HHEH`H@ W)ƅHDž HconstantHƅH5 HƧLH躨D$D$$H H Ϳ L%% 1E1HD$D$$Hp H L) E1HշD$D$$HH _L$ AH薷D$D$$H( H Lq$ 1E1H HW)HDžfDžTƅ HH1W)HDž@ H(d))Hr types.HH-Htensor tHH(H to all HH Hut typesHHHand outpHHHn input HHHConstraiH@5HHHH;H ̂#H0H0HPHHH5RZ H%H5C H H9H5Cs= HLH -^HPH9tbHtHP(t H LMtVHL9t;fDHX@t Hx HI9uHHP uLLZ t HE t H 0 H`VMH HH;EuLHH[A^A_]^ Iut~ILMu{IIIHPH9tHtHP(uHP t Hr LMtFHL9tzfff.HX@t Hx; HI9uHL  t H  t H  H`LL*  Lffff.UHAWAVSH(IH6 HHEH`HPHDž(H5W H~ L(HsD$D$$H{$ H L^ 1E1HJD$D$$H H GL% AH D$D$$H $ H v L 1E1H肷HW)HDž fDžTƅ蕲HHzW)HDž@q H($)Hr types.HH-Htensor tHH(H to all HH Hut typesHHHand outpHHHn input HHHConstraiH@5HHHH谸H ~#H0H0HPHH艆H5 H蚇H5> HkH讂H5n H芈LHYHPH9tgHtHP(t H1 LMt[HL9t@ff.HX@t Hx HI9uHHP uLL t H  H`HH$ HH;EuLH([A^A_] IugqILMunIIIHPH9tHtHP(uHP t H LMtHHL9tgfffff.HX@t Hx HI9uHL t H  H`GL  LfUH]f.UH]d fDUH\ H ;m#H]fDUHH%m#H]UH]f.UH] fDUHAVSH H~ HHEHW)EHEEfEtoEHu11HrEt H} HHPHtuH1HPHteH1HPH(tDH@H(u H@ @u3u.H@ @t$H1HP(IH1HPHLҁH HH;Eu H [A^]u HEt H} HC  ff.UHH e1H1H9NHD]DUHHl#]UH]f.UH] fDUH H l#H]fDUHHk#H]UH]f.UH]T fDUHAWAVAUATSHIH HHE11LILPHHW)EHEEHallowzerHEfEoIHuLHt -x1H`Et H} W)EHECuHSpHcChH H}1/4HHu -HHAHIHHH}1I1LP(HÃ{(uLc -HC(H{@HIILc AL$ID$HpHu$I|$@HsHpID$I1LPx(uH@ Ha#HPLuLeW)EHEM)tmMMII]HH<k HHEH]LmMIJ4HHH I?t@D)HHHJ!IEnLpID$HHE1Hh1HX<HEMIADIN $HPAt8HIHcQI9{HI JLQ(t"uHY A}(uJN4\LpHY A}(umI} LpHIUHHRL?AE(ILuI] HhHHhIM!&LpZLp?LpAE(I} HN$IE HIUxu HH1Lp`DID$ HtfIcL$;}]QAT$LlKKHuu`A}(tL>AE(JHEIE fDHHH8QHHHILuKKHtHuHXLXtIDfHA}(tLH>AE(JHEI] HhHHhILuHEL)HHI9LXMHPHh@H@HcHH~rHcULEHx 1fHt~(uHF HH9|HfDH9}mHHI4Hs\HH9|"HH`E$(HHhHHA~(tL*=AF(I^ H}Ht H}Ht H}| H~ HH;EuDHĘ[A\A]A^A_]@uHH?<@uHH?`1#1R D(. IHH]H5 - HqHxH AHxL H6#IIF IFIFE1H5"HIL ( IH5y - H{Hx7AHxL H5#IIF IFIFE1H5i"HrILv (4 IH5 - Hf{HxLAHxL H(5#IIF IFIFE1H5"HHL H}   ( IH5 HzHx`AHxL& H4#IIF IFIFE1H5r"H{HL 눿(= IH5 HıHxAHxL H14#IIF IFIFE1H5"HHL  0Hxu5< Hxu%,HxuHHxt H}j EtL H}HtH}HH}HHxtHH}HtHH}HHH}HHH}HuovHH}HuahHEt_H}THH}HuDKHH}H\"HH}HJHH}H8u H}Ht H}c H  ff.UHH 'H1H9NHD]DUHHa#]UHAWAVAUATSHHHIHHxz HHEH0L%#z M|$@LLHx HH@H0HfHnfLC HEEID$HHIhL0LLLF L5y ILHDž HDžHDžHDžDž(LL LLH]uLHz HHH<uLH {HHL0HHLt H Hl H5sx HHI H0 Hx HH;EuLHH[A\A]A^A_] HSHeHHHL0HHLt H HH5w HHH0j H UH]f.UH] fDUH H s_#H]fDUHH]_#H]UH]f.UH]D fDUHAWAVSPII1LP(HÃ{(uHC *HC(H{@H3HC H@ I1LP(HÃ{(u0Ls ANI^HtYHC HtwHcK;}oQSLt|H舁C(H{@rH躬ILs ANI^HuI~@XHHI^HC HuHH;bHHIILPHI1LPHI1LPH(t$fH@H(uH@ @uH@ @I1LPx(u H@ @ucHB#@tVI1LPx(uH@ H@HtH#H@HuH#HcXA~(tL3AF(I^ H[A^A_]@u0HH?@u%HH?@uHH?11`1UHH "H1H9NHD]DUHH\#]UH]f.UH]fDUH|H \#H]fDUHH\#H]UH]f.UH]4fDUHAVSII1LP(HÃ{(uHC *H~C(H{@H&HC H@ I1LP(HÃ{(uLs ANI~t:[A^]H~C(H{@uJH̩ILs ANI~uI~@u3HIF[A^]@u*HH?`@uHH?@uHH?1;11fffff.UHH "H1H9NHD]DUHH[#]UH]f.UH]fDUHH [#H]fDUHH[#H]UH]f.UH]tfDUHAWAVAUATSHhHHr HHE11H"HHPHHMHHEH LcuE1HHPL9HHLPHjHHLPH(t'H@H(uH@ @u2D$H@ @IM9yH1HPx(uH@ H@HtH#H@HuH#Lc`HHW)EHEEEaxisEHuHIEt H}MPEDA9EE9H1HP(IH}u/H1HPHLNH7q HH;E7sDA~(H]uIF /Lt{AF(I~@ -H襦IF ـHD!LpMu'Hx@MHHҥILsMDEM{M~IF HELf.HEHHt$AF;}AFHu'ffffff.I?LH荦HuLeDuE1E1fDH}HHPx(H @#t&LyMt*HxHEA9Gt5=HH LyMuL=#HxHEA9G 1DI9u+IG JDx(uLD` HI9uMfffff.HEHHtIG H|T;HI9uf.EHI9uHxHH;] E1L=M#L%#fffff.H}HHPx(Lt*HAHt.D9hu1HH;]rffff.HH HAHuLD9htϿ(6IH5 H6H}vAHuLH0&#IIF IFIFE1H5"H:L I E1LuHEHHcMH\Mc{(tH,C(Ls Hm HH;EuAHh[A\A]A^A_]@uHH?@uHH? 11(9IH5 HH}YAHuLH3%#IIF IFIFE1H5"H9L (IH5 HH})AHuL?H$#IIF IFIFE1H5"H8LH7HEu 'H'HEuHHEt H}Et$L1HA HEt H}H% ffff.UHH H1H9NHD]DUHHT#]UH]f.UH]fDUH|H T#H]fDUHHT#H]UH]f.UH]4fDUHAWAVAUATSHhIHk HHEILP ~11ffffff.1LHßHILP HH9|ILPHI1LPHI1LPH(u!H@ @dH@H(tOH@ @AI1LPx(H@ HXHuH#D{D}W)EHEEEaxisEIHuLHHxt -x1Et H}D}̉]D9A9y -AD}DHxH@ HcHDx(@ EW)EHEILPHILPHILPH7H}HHuHUH}OH}Ht H}L}H]ILP L)HH9HEHEHUH9HH)HHOH8x1HHY#HXH^RILP HHxXE1ILP HEADžILP H}H Mc1L}Le L(HHEILP 9FLmHEH;ErLLVLHE1HcEH9(IHf6 H$H5 H\L{H}HMLMAHuL8H#IIF IFIFE1H5"H3LHqH)1HHUHPHUHPHUHPHUHP HUHP(HUHP0HUHP8HUH@HuHtHHHUHHuHcEH9E1Lc IILP I9ILLP(IA|$(uMl$ 1LuqAD$(I|$@H褜IMl$ AMIEHHxu"I}@HЛIEHxH9ILLP(IA|$(uMl$ AMIEHuT;LpAD$(I|$@u{H IMl$ AMIEHuI}@uvHCIEHcMH@ H\HEN${(H#C(@uBHH?@u7HH?w@u,HH?@u!HH?|11E11`H}HH}Hke HH;E7@uBHH?@u4HH?7@u)HH?@uHH?B1o111)ILLP(IA}(uMe AL$I|$HudB@L(oAE(I}@IHYIMe AL$I|$Hu I|$@>H芙HI|$H7ILLP(IA}(u$Me AL$ID$HukLfffff.LnAE(I}@H蹙IMe AL$ID$HuI|$@HID$HcMH@ H|"IILP I9Hc HH;E,Hh[A\A]A^A_]ÿ(IH5 H0LRH}HMLM舍AHuLqH#IIF IFIFE1H5"H.L(IH5T HbH}AHuLH#IIF IFIFE1H5J"HS.LW(IHEH+EHHEILP HEH0 H$H5 HDLaH}HMLM;AHuLTH#IIG IGIGE1H5"H-LH`HEt H}CEuHL^H}HHEuHHEt H}EtyLH}HuqxHHEt H}Et\LRHH}Ht4H}H}Hu+2HEtH}HH}Ht H}jH fUHH H1H9NHD]DUHH J#]UH]f.UH]fDUH H I#H]fDUHHI#H]UH]f.UH]fDUHAWAVAUATSHIH"` HHEILPHH*11LXILPHtOI1LPHt?I1LPH(uH@ @tH@H(tu -H@ @u&H_ HH;EH[A\A]A^A_]ILPIILPIILPHr]ILPHtJILP1ۋH(ufH@ @t!H@H(tuH@ @1ILPHrgILPHtTILPE1H(u$f.H@ @H@H(tH@ @E1MMILPHreILPHtRILPH(uH@ @t2H@H(tu!H@ @tILPHKILPHreILPHtRILPH(uH@ @t2H@H(tu!H@ @tILPHAD$HXLH@LH`H+XHHH+@H9I1LPx(H@ HHHHuH #HcAHLXL`Lff HDž0L)HLLMIILH=H IL O<L0LHLH(HMLLHH5HpH Ht#H(ff HDž0LpHxL H(HEH0LXL`HL)LL)H9)(<IH5 HHp蹪AHpLH0#IIF IFIFE1H5"H'L Hh#HHHH)E111HHI9pHPL)HHHs?1LCILPHILPIMF IH?H!HYHHwH sfHnfs1HH^H)fHnfs1fDovfDo vfDovfo%vfo-vfo5vfo=vfo vfofAAATfofAfofAAT A\0foffofAT@A\PfoffofAT`A\pHfHuHt6I|Hfo ufoufofGfH HuH9LMffpHEM)tfILHHH= - LHpHH]H55HHHLHxLY1HxBILH -HHH9uMKHpLHpHxL H(HHH)HL)H9 E1qLAG(I H#IG IIWpu5HHc@uHH?j@uHH?1T113I1LP(IA(uMg AL$I\$Hu\:LaAG(I@uH&IMg AL$I\$Hu I|$@kHWHI\$HC HtHcK;} QSL|HH;赋HHJIHH@ JDH(t6uaHX A(tLAG(I_ IL;@L` A(uI IIWHL'IL;L H(ffEfEE?L)I$II?HI!II9.M%HH11HHPHsHt"LI9r 1LHHLEIHu{HL!LEIHthH8Ht`Ht0HGL9u L9ou1H9r1HHH9u5H?Hu+HGL9t HH!H9uL9u -L9oH?HuHt!MI9r1LHIKHuIM!KHtuHHtmHt/HAL9tH9r1HHL9uML9iH Hu9HAL9tH!L9u(L9iH HuH]HH$IMl$Ml$I$HEHx +ILMKII/6I.IHPH9tHtHP(uHP t Hy +LMt?HL9t$HX@t HxN +HI9uHLL. +uu#LMu/nH +tH +LMtAHL9t`HX@t Hx +HI9uHL +t H  +H`pL  LfUHAWAVAUATSHxIHf!HHEHPH(D$D$$H~TH TL%( 1E1HD$D$$H' +H ]TL +E1HǡD$D$$H]TH _TL +AH舡D$D$$H[(H ULq' 1E1HHW)HDžfDžTƅRHHLxW)HDž +H(l)Ior type.LxI tensor L`In to anyLhIConstraiL0@HHHHPHW)HDžfDžSƅHHDW)HDž / +H(l)LxL`LhL0@HHHH谦H5 +Hr?$LBTHηH @$H H H@HHgtLxH5' HquH5,HBx HpH5IQHavLHF}H@H9t^HtHP(t H LMtRHL9t7fHX@t Hx HI9uHHP uLL uGuSLMtpHL9tUfHX@t Hx{ HI9uH2H^ tHI LMuLL, t H HPlHb!HH;EuLHx[A\A]A^A_]A ILMIILM\IuhrII29I1IH@H9tHtHP(uHP t H LMt?HL9t$HX@t Hx HI9uHLL uu#LMu/qH tH LMtDHL9tcf.HX@t Hx[ HI9uHL@ t H+ HP1jL_  LfUHAWAVAUATSHxIH`!HHEHPHl"D$D$$HNH &NL! 1E1H裛D$D$$H9NH HPL +E1HgD$D$$Hu +H -QLR +1E1HޟHW)HDžfDžSƅ衝HHLxW)HDž H(f)Ior type.LxI tensor L`In to anyLhIConstraiL0@HHHH/HW)HDžfDžTƅbHH#W)HDž  H(e)LxL`LhL0@HHHH菠H5 +Ha9$L!NH譱H ;$H H H@HHFnLxH5Y HPoH5f&H!r HdjH5(KH@pLH%wH@H9t]HtHP(t H LMtQHL9t6HX@t Hx HI9uHHP uLL uGuSLMtpHL9tUfHX@t Hx[ HI9uH2H> tH) LMuLL t H HPeH\!HH;EuLHx[A\A]A^A_]! ILMIILM\IuhrII29I1IH@H9tHtHP(uHP t H LMt?HL9t$HX@t Hx HI9uHLL uu#LMu/qH tHp LMtDHL9tcf.HX@t Hx; HI9uHL t H HPdL?  LfUHAWAVSH(IHvZ!HHEH`HPD$D$$HHH +HL 1E1H臕D$D$$HHH ,JLw +AHHD$D$$HH MKL1 1E1H这HW)HDž fDžSƅ肗HHӒW)HDž H(`)Hor type.HHH tensor HHHn to anyHHHConstraiH@HHHHH5\ +H3$LHH5H &6$H0H0HPHHhH5b HiH5 Hl HdH5E7HjLHqHPH9t\HtHP(t H LMtPHL9t5HX@t Hx[ HI9uHHP uLL* t H  H`aHW!HH;EuLH([A^A_]C ILMu|IuS]IIIHPH9tHtHP(uHP t Hd LMtHHL9tgfffff.HX@t Hx+ HI9uHL t H H``L/  LfUHAWAVSH(IHfV!HHEH`H@D$D$$HCH CL 1E1HwD$D$$Hs H GLg +1E1HHW)HDž fDžSƅ豓HHW)HDž H(\)Hor type.HHH tensor HHHn to anyHHHConstraiH@HHHHFH5 +H80$LGHdH 2$H0H0HPHHdH5= HfH5$Hh H"aH5AXHfLHmHPH9tkHtHP(t H LMt_HL9tDffffff.HX@t Hx{ HI9uHHP uLLJ t H 5 H`;]HS!HH;EuLH([A^A_]c ILMu|IuS]IIIHPH9tHtHP(uHP t H LMtHHL9tgfffff.HX@t HxK HI9uHL0 t H  H`!\LO  LfUHAWAVSHIHR!HHEH`H`D$D$$H H gL 1E1H藍D$D$$H;` H zDL +AHXD$D$$H+H DLA 1E1HϑHW)HDž fDžTƅ"HH㊉W)HDž0 H(&)Hsor typeHH H all tenHHHtypes toHHHn input HHIConstraiL8f@(s.@*HHHHH5X +H ,$LCH1HW)HDžfDžSƅ蔎HH剉W)HDž0 H()Hnsor typHH Ho all teHHH types tHHHn outputHHL8@(es.HHHH"HDžH5 H CLHpHDžH5 HhCLHoH -$H0H0HPHH_H5 H`H5Hc H[H5<HaLHhHPH9t_HtHP(t HY LMtSHL9t8HX@t Hx+ HI9uHHP uLL uGuSLMtpHL9tUfHX@t Hx HI9uH2H tH LMuLLl t H W H`]WHM!HH;EuLHĈ[A^A_] IIIILMILM$fIII5<I4IHPH9tHtHP(uHP t H/ LMt?HL9t$HX@t Hx HI9uHLL uu#LMu/tH tH LMtGHL9tfffff.HX@t Hxk HI9uHLP t H ; H`AULo  LfUHAWAVSHxIHK!HHEH`H H5V H?AHeHDž(H5>@H@@L(HkD$D$$H8H \@L 1E1HiD$D$$H~_H _LT 1E1HHW)HDž fDžSƅ裈HHW)HDž0 H()Hsor typeHH H any tenHHHtypes toHHHn input HHIConstraiL8f@(.HHHH(HW)HDžfDžTƅ[HHW)HDž0 H(_{)Hnsor typHH Ho any teHHH types tHHHn outputHHL8f@(e.@*HHHHVH ($H0H0HPHH/YH5 H@ZH5VH] HTUH56{H0[LHbHPH9t]HtHP(t H LMtQHL9t6HX@t Hx HI9uHHP uLL uGuSLMtpHL9tUfHX@t HxK HI9uH2H. tH LMuLL t H H`PHvG!HH;EuLHx[A^A_] IILMIILM[IhII7>I6IHPH9tHtHP(uHP t H LMt?HL9t$HX@t Hx HI9uHLL uu#LMu/vHj tHU LMtIHL9thffffff.HX@t Hx HI9uHL t H H`NL  LfUH]f.UH] fDUH H $H]fDUHH} $H]UH]f.UH]d fDUHAWAVSH(IHD!HHEIHW)EE +HEEdtypfEeHuLHEt H} Ht{6DAI1LP(HÃ{(u!Ls ANI^HtJ{(uhHC HaC(H{@H(ILs ANI^HuI~@H謎HI^{(tH'aC(H{@uBH]HC HDx HC!HH;EuPH([A^A_]@u-HH?g@u"HH?@uHH?r1?11` ( IH5 H8H}AHuLA H#IIF IFIFE1H5]#H!L  HHEt H}3 Et$LV Hf  HEt H} + HJ  fUHH eH1H9NHD]DUHH5$]UHAWAVAUATSHHHIHHHB!HHEH0L%A!M|$@LLHY@!HH@H0HfHnfL HEEID$HHIhL0LLL L5[A!ILHDž HDžHDžHDžDž(LLG LLH텉LH* HHH̅LH蝋HHL0HHLt H< H H5C@!HH H0 H@!HH;EuLHH[A\A]A^A_]C HSHeHHHL0HHLt H Hw H5?!HHT H0 H  UH]f.UH]D fDUH< H $H]fDUHH$H]UH]f.UH] fDUHAWAVAUATSHXIHu?!HHEIELPHW)EHEH}HEHL HE1L5$L}LeIELHPHLx(LuHH I MHEH;Es HHELL% H]HH]H;]rHMHEH9t'HQH9Lut'Hp@;QuHH9u LuH9IE1LP(HÃ{(u$L{ AOMgMtMA|$(ukM|$ H[C(H{@H$IL{ AOMgMuI@H計IMgA|$(tL![AD$(I|$@HPIM|$ HEAOAG LH IcE1LuIELPL9&IELLPHIELLPf.H@H(uH@ @uH@ @II9rIE1LPx(uH@ L`MtH֘$L`MuL%$AOIHuI@H詄HIL"IrKL5$L%I$IELHPx(LuHH HyHuLL2HH;]rH}Ht H} H@<!HH;EutHX[A\A]A^A_]@u0HH?@u%HH??@uHH?111@u HH?1Lu| (* IH5 H~1L1H}HMAHuL H#IIF IFIFE1H5#HL O( IH5o H0H}AHuL% Hv#IIF IFIFE1H5A#HjL~ (9 IH5 H0H}AHuL H#IIF IFIFE1H5Ν#HL lHiHEu6=HHEt H} Et8L .H3HEt H}n EuH}Ht H}W H  Lu H}HuHH}HuHH}HuHH}HuHH}HuHH}HuHH}HuUHH 5H1H9NHD]DUHH$]UHAWAVAUATSHHHIHH(9!HHEH0L%8!M|$@LLH97!HH@H0HfHnfL HEEID$HHIhL0LLL L5;8!ILHDž HDžHDžHDžDž(LL' LLH|LH + HHH|LH}HHL0HHLt H H H5#7!HH H0 H7!HH;EuLHH[A\A]A^A_]# HSHeHHHL0HHLt Hw HW H5~6!HH4 H0 H  UHAWAVAUATSHXMHHIHH6!HHEH0L5U6!I^@HLH4!HH@H0HfHnfLV LHEEIFHHIhL0HHLS L-5!ILHDž HDžHDžHDžDž(LL LLHJzLHH LHH&zHH0L HHQ LHHyLHHHL0HHLt Hg HG H5n4!HH$ H0 H4!HH;EuLHX[A\A]A^A_]n HSHeHHHL0HHLt H H H53!HH H0E H  ff.UHAWAVAUATSHHHIHH3!HHEH0L%3!M|$@LLH 2!HH@H0HfHnfL HEEID$HHIhL0LLL L5 3!ILHDž HDžHDžHDžDž(LL LLHwLH HHH|wLHM}HHL0HHLt H H H51!HH H0o HX2!HH;EuLHH[A\A]A^A_] HSHeHHHL0HHLt HG H' H5N1!HH H0 HX  UHAWAVAUATSHIIIuMeI)MIIGHH> H?MuI)LHHH9w`II9LBMLEHuI9vK HH50 +H H0!HHH5/!H.!H LEHuIJ<A HHuLEN4ABN|M~HLI LI]M}MuHtHH[A\A]A^A_] H[A\A]A^A_]E11L% IH L  fff.UH]f.UH] fDUH| H s $H]fDUHH] $H]UH]f.UH]4 fDUHAWAVAUATSH8IH/!HHEIE1LPIIELPMHA(uIO HIHtH q$HIHuH $H52$y(HtaDr Dux(uHp HEF EA9IE1LP(HÃ{(u;Lc AL$I\$Htd{(Lc HQ Dr Dux(tHLC(H{@YHwILc AL$I\$HuI|$@NH'yHI\${(tHKC(H{@HvILc AL$Et$ IELPHIE1LPHIE1LPH(tH@H(uH@ @u`WH@ @IIELPH5IELPHIELPH(t$fH@H(uH@ @uH@ @A(uIG H@HtH1$H@HuH$x(uH@ HXHtH݈$HXHuH$AL$I|$Hu I|$@HtHI|$HHEx(uH@ HxHtHu$HxHuH=5$LEHn,!HH;EuZH8[A\A]A^A_]@u0HH?@u%HH?@uHH?1n11 @u HH?21+(Y HH5 H!"H}IAHuH H##HHC HCHCE1H5#H +H+ }( HH5 H"LG"H}HMLM:AHuHS H#HHC HCHCE1H5o#H H  I1IEuI!IEt H}5 Eu +Lp  HN L^  fDUHH UH1H9NHD]DUHHM$]UHAWAVAUATSHHHIHHX*!HHEH0L%*!M|$@LLHi(!HH@H0HfHnfL HEEID$HHIhL0LLL L5k)!ILHDž HDžHDžHDžDž(LLW LLHmLH: HHHmLHsHHL0HHLt HL H, H5S(!HH H0 H(!HH;EuLHH[A\A]A^A_]S HSHeHHHL0HHLt H H H5'!HHd H0* H  UHAWAVAUATSHhMLHHIHxH'!HHEH0L=~'!I_@HLH%!HH@H0HfHnfL LHEEIGHHIhL0HHL| L5&!ILHDž HDžHDžHDžDž(LL LLHskLxHH LHHOkH0L HH{ LHH!kH0L~ LHpHHL0HHLt H H` H5%!HH= H0 H%!HH;EuLHh[A\A]A^A_] HSHeHHHL0HHLt H H軿 H5$!HH蘿 H0^ H  @UH]f.UH] fDUH| H $H]fDUHH$H]UH]f.UH]4 fDUHAWAVSH(HH$!HHEH1HPIMt_H1HP(A~(uIN HqHtH $HqHuH5$H `$!H H;MuHH([A^A_]U (謿 HH5o HH}AHuH% Hv#HHC HCHCE1H5A#HjH~  I&IEuEuL[  H} EtH+ L;  UHH %H1H9NHD]DUHH$]UHAWAVAUATSHHHIHH8#!HHEH0L%"!M|$@LLHI!!HH@H0HfHnfL HEEID$HHIhL0LLL L5K"!ILHDž HDžHDžHDžDž(LL7 LLHfLH HHHfLHlHHL0HHLt H, H H53!!HH H0诼 H!!HH;EuLHH[A\A]A^A_]3 HSHeHHHL0HHLt H臼 Hg H5 !HHD H0 + H蘹  UH]f.UH]4 fDUH, H ##H]fDUHH #H]UH]f.UH] fDUHAWAVSH(HHi !HHEH1HPIMt5H1HP(H = !H H;MuHLH([A^A_]_Qػ (膻 HH5I HH}AHuH HP#HHC HCHCE1H5#HDHX  IIEt H} EtH L$  fff.UHH H1H9NHD]DUHH #]UH]f.UH]鄺 fDUH| H #H]fDUHH#H]UH]f.UH]4 fDUHAVSHH1HQ(IA~(uI^ *L;AF(I~@uPHgHI^ C KH{Ht [A^]$H{@u(HAfHH{[A^]@uHH?@u HH?11ff.UHH H1H9NHD]DUHH-#]UH]f.UH]$ fDUH H #H]fDUHH#H]UH]f.UH]Ը fDUHAWAVAUATSHhIHU!HHEI1LPIM I1LP(HÃ{(u|Lc AL$I\$HI|$@HgHI\${(H:C(H{@gHKeHC A~(t_H x$ZH9C(H{@WHeILc AL$I\$H[{({HC A~(uIN I HH ILPHtJI1LPHt:I1LPH(ufH@ @tH@H(tu +H@ @u#H!HH;EHh[A\A]A^A_]A~(IF LpMuL5aw$EfDeffEHEEEaxisEIHuLHt +x1Et H}賶 De]D9QA9HyADeILPHu{IHffEEHEHkeepdimsHMEHuLHEt H}4 H LHv$LpMILPHHILPHILPH(uH@ @H@H(tH@ @ILPHtp@tjffEHE{H}H轨HuHUHMH}8HEaOAHxI1LP(HÃ{(uL{ AOI_Hu[;H6C(H{@yHMbIL{ AOI_HuI@qHcHI_{(uL{ AOMgMu[;H86C(H{@HjaIL{ AOMgMuI@H`IMgMt]LLHcEIL$ H\C(LxMtH9C(Lk HW!HH;Es AFNM|$1fMH9tJID$ HtIcL$;}QAT$H|I?~_LH#aHIF HtAFHHcH9|u(HC C(H!HH;EWH{ Hs@ H-C(Ho!HH;E@*HH?_HC A~(@HH?@ HH?H}H{HuHUHMH}}H}Ht H}2 LmH}I9}HcEIN HDx(uqL` LeILPx(H@ H@HuH3r$xH}HEH9HHH)HHH1HHHC1^HC A~(^11Hq$H@HqeH}HLHHHHHH H1HUI9( IH5 H Le H}HMLMAHuL脮 H#IIF IFIFE1H5x#HLݰ :I?I!IXHHrH sf1fHutH^H)f1fofoDfoL o\0od@ffoTPffoD`foLpfHHuHt"HTHoRfofH HuffpNffH~L9tJ HHH9uHUI9HH9t$HOH9t'HHpHH;Qu HH9u HH9uHHCI}@ 5@uBHH?y@u7HH?@u,HH?@u!HH?1<11Z1@u HH61(̮ IH5 H: +H}AHuLE H#IIF IFIFE1H5av#HL螮  (\ IH5ֱ H0[LR[H}HMLMmAHuLƫ H#IIF IFIFE1H5u#H L |(ڭ IH5T H H}*AHuLS H#IIF IFIFE1H5ou#HL謭 (g IH5 HK H}sAHuL H1#IIF IFIFE1H5t#H%L9 HEt H}Ԭ Eu"HEt HEuHLլ H}HH'HEuHHEt H}l EtsL菬 H蟩  0HH}Hu%HH}HtH}0 H}Hu1HH}Ht#H}HEu HEt H} H4  fff.UHH H1H9NHD]DUHH#]UHAWAVAUATSHhMLHHIHxH!HHEH0L=!I_@HLH%!HH@H0HfHnfL迪 LHEEIGHHIhL0HHL輩 L5!!ILHDž HDžHDžHDžDž(LL LLHSLxHH LHHSH0L HH軬 LHHaSH0L辨 LH!YHHL0HHLt H H蠨 H5 !HH} H0C H,!HH;EuLHh[A\A]A^A_]ǩ HSHeHHHL0HHLt H H H5" !HHا H0螨 H,  @UHAWAVAUATSHhMLHHIHxHC !HHEH0L= !I_@HLHU !HH@H0HfHnfL LHEEIGHHIhL0HHL L5Q !ILHDž HDžHDžHDžDž(LL= LLHPLxHH LHHPHH0L? HH LHHPHH0L LHOVHHL0HHLt H HΥ H5 +!HH諥 H0q HZ !HH;EuLHh[A\A]A^A_] HSHeHHHL0HHLt HI H) H5P +!HH H0̥ HZ  fUH]f.UH] fDUH H c#H]fDUHHM#H]UH]f.UH]餥 fDUHAWAVAUATSHHIH% +!HHEI1LPHx(uH@ H@HtHe$H@HuHf$x(uH@ He$Dx I1LP(HÃ{(uHC *H&C(H{@HRHC HDx ILPHI1LPHI1LPH(tH@H(uH@ @uH@ @|IHW)EHEEEaxisEHuLHEt H}- HEIHW)EEHEHnew_axisHMEHuLHEt H}գ Ht DE1I1LPx(uH@ H@HtHOd$H@HuHd$x(uH@ L`MtHc$L`MuL%c$AOAD$1AE)ЉEuM99yDEI1LP(HÃ{(uLs ANMnMu[;H$C(H{@HOILs ANMnMuI~@H0OIMn}Mu1fIM Ht'AE;}AEEH9u,\ffffff.I>hNLH PEH9t2HEIU H|H9 )ID$ HcHtCHcEH9H[rH!HH;EuZHH[A\A]A^A_]@u HH?1@uHH?@uHH?11 (菡 IH5R HH}AHuL HY#IIF IFIFE1H5$i#HMLa  ( IHEHD$HH$H5 HLo H}HMLMAHuLu HƷ#IIF IFIFE1H5h#HLΠ h(艠 IH5 HLH}AHuL HS#IIF IFIFE1H5h#HGL[ ( IH5 H~H}ְAHuL菝 H#IIF IFIFE1H5g#HL HGHBH=HEu&-HEu"HEuHHEt H}N Et/Lq H聜  HEu HEt H} HZ  fUHH H1H9NHD]DUHH#]UHAWAVAUATSHhMLHHIHxHC!HHEH0L=!I_@HLHU!HH@H0HfHnfL LHEEIGHHIhL0HHL L%Q!ILHDž HDžHDžHDžDž(LL= LLHFLxHH LHHFH0L HH LHHFH0L H]H LHHfFHE0Lƛ LH)LHHL0HHLt HȜ H訛 H5!HH腛 H0K H4!HH;EuLHh[A\A]A^A_]Ϝ HSHeHHHL0HHLt H# H H5*!HH H0覛 H4  UHAVSHIHh!HHEH`HB‚H5HAHAD$D$$H H L +1E1HX;D$D$$Hh H L_ 1E1H?H5{ +H#LH SH5) H_#LHRH #H0H0HPHHH5 HH5 Hf H H5nhHLHjHPH9t HtHP(HP H`OH HH;EuLH[A^]y I"IHPH9uHP HtHP(H`L&  fffff.UHAWAVSH(IHV HHEH`H0HDž(H5 HL(HcD$D$$Ho, H L^ 1E1H:9D$D$$H H L E1H8D$D$$HH L 1E1Hu=HW)HDž fDžTƅxnHH6W)HDž@t H(<)Hr types.HH-Htensor tHH(H to all HH Hut typesHHHand outpHHHn input HHHConstraiH@5HHHH>H #H0H0HPHH| H5 H H5 H^HH5fH}LHbHPH9tjHtHP(t H4 LMt^HL9tCfffff.HX@t Hx HI9uHHP uLLʖ t H 赖 H`HD HH;EuLH([A^A_] IugqILMunIIIHPH9tHtHP(uHP t H LMtHHL9tgfffff.HX@t Hx˕ HI9uHL谕 t H 蛕 H`Lϒ  LfUHAWAVSH(IH HHEH`HໂD$D$$HL( H L; 1E1H5D$D$$Ho H LN +1E1H9HW)HDž fDžTƅjHH2W)HDž0荔 H()Hry type.HHHrbitraryHHH be of aHHHnsor canHHHInput teH@&HHHH:H5d +H#L HKH #H0H0HPHHH5 H H5 Hq HH5yMH +LHuHPH9t]HtHP(t HG LMtQHL9t6HX@t Hx HI9uHHP uLL t H Ւ H`Hd HH;EuLH([A^A_] ILMu|IuS]IIIHPH9tHtHP(uHP t H$ LMtHHL9tgfffff.HX@t Hx HI9uHLБ t H 軑 H`L  LfUHAWAVSH(IH& HHEH`HD$D$$Hl$ H L[ 1E1H71D$D$$Hq]H $ Ln +1E1H5HW)HDž fDžTƅfHH.W)HDž0譐 H(Ր)Hry type.HHHrbitraryHHH be of aHHHnsor canHHHInput teH@&HHHH6H5 +H#LRHHH G#H0H0HPHHH5 HH5ּ H HH5tHLH HPH9t]HtHP(t Hg LMtQHL9t6HX@t Hx; HI9uHHP uLL + t H H`H HH;EuLH([A^A_]# ILMu|IuS]IIIHPH9tHtHP(uHP t HD LMtHHL9tgfffff.HX@t Hx HI9uHL t H ۍ H`L  LfUHAWAVSH(IHF HHEH`H H5: HAH D$D$$H[H [LZ 1AH3-D$D$$HHH OL 1E1H1HW)HDž fDžTƅbHH*W)HDž0詌 H(#)Hnsor typHH Ho any teHHH types tHHHn outputHHHConstraiHf@(e.@*HHHH2H #H0H0HPHHH5 HH5 H HH5HLH HPH9teHtHP(t H LMtYHL9t>fHX@t HxK HI9uHHP uLL t H  H` H HH;EuLH([A^A_]3 IugqILMunIIIHPH9tHtHP(uHP t HT LMtHHL9tgfffff.HX@t Hx HI9uHL t H H`L  LfUHAWAVSH(IHV HHEH`H0D$D$$H H L 1E1Hg)D$D$$H H LH AH()D$D$$Hb H lL 1AH-HW)HDž fDžTƅ^HH&W)HDž@蛈 H(c)Hr types.HH-Htensor tHH(H to all HH Hut typesHHHand outpHHHn input HHHConstraiH@5HHHH.HDžH5U5 HLH H #H0H0HPHHvH5x HH5 HX HH5`]HwLH\HPH9tdHtHP(t H. LMtXHL9t=HX@t Hx HI9uHHP uLLʆ t H 赆 H`HD HH;EuLH([A^A_] IuuIugqILMunIIIHPH9tHtHP(uHP t H LMt:HL9tYHX@t Hx˅ HI9uHL谅 t H 蛅 H`Lς  LfUHAWAVSH(IH HHEH`HૂD$D$$HL H J L; 1E1H%D$D$$H H 8 L + E1H$D$D$$HB H L E1H$D$D$$HR H !L AH`$D$D$$HH LS AH!$D$D$$H1 H  L 1E1H(HW)HDž fDžTƅYHH!W)HDž@藃 H(_)Hr types.HH-Htensor tHH(H to all HH Hut typesHHHand outpHHHn input HHHConstraiH@5HHHH)H5 H#L H:H #H0H0HPHH}H5 HH5 H_ HH5gwH~LHcHPH9tkHtHP(t H5 LMt_HL9tDffffff.HX@t Hx HI9uHHP uLLʁ t H 赁 H`HD HH;EuLH([A^A_] ILMutIuKUIIHPH9tHtHP(uHP t H LMt@HL9tKfDHX@t Hxۀ HI9uHL tH 諀 LIH`L}  ffff.UHAWAVSH(IH HHEH`HংH5HE1HD$D$$H. H L 1E1HD$D$$H$H (L 1E1Hp$HW)HDž fDžTƅsUHHW)HDž@o H(7)Hr types.HH-Htensor tHH(H to all HH Hut typesHHHand outpHHHn input HHHConstraiH@5HHHH%H #H0H0HPHHwH5 HH5 HY HH5aHxLH]HPH9teHtHP(t H/~ LMtYHL9t>fHX@t Hx} HI9uHHP uLL} t H } H`HD HH;EuLH([A^A_]} IugqILMunIIIHPH9tHtHP(uHP t H} LMtHHL9tgfffff.HX@t Hx| HI9uHL| t H | H`Ly  LfUHAWAVSH(IH HHEH`HࢂHxHDž(H5) HL(H D$D$$H H  L 1E1HD$D$$H H L E1HD$D$$HH pL E1HjD$D$$Hz H jLU 1E1HHW)HDž fDžTƅ4yHHW)HDž@z H(x)Hsor typeHH(H any tenHH Han be ofHHH types cHHHd outputHHHInput anHf@0.HHHH!H5c H=#LV H92H #H0H0HPHHH5 HH5 H HH5?HLHHPH9t`HtHP(t Hy LMtTHL9t9@HX@t Hx[y HI9uHHP uLL*y t H y H`H HH;EuLH([A^A_]Cy ILMIIuS]IIIHPH9tHtHP(uHP t HXx LMt<HL9t[fHX@t Hx+x HI9uHLx t H w H`L/u  LfUHAWAVSH(IHf HHEH`H@D$D$$H + H  L 1E1HwD$D$$H H  LX E1H;D$D$$HH L& E1HD$D$$H H  L 1E1HvHW)HDž fDžTƅyLHHW)HDž@uv H(!)Htensor tHH(H to any HH Hut typesHHHand outpHHHn input HHHConstraiH@0ype.@4HHHHH #H0H0HPHHH5o HH5 Hf HH5nHLHjHPH9tbHtHP(t H<u LMtVHL9t;fDHX@t Hx u HI9uHHP uLLt t H t H`HT HH;EuLH([A^A_]t IugqILMunIIIHPH9tHtHP(uHP t Ht LMtHHL9tgfffff.HX@t Hxs HI9uHLs t H s H`Lp  LfUHAWAVSH(IH HHEH`HHDž(H5 HL(H#D$D$$H/ H 8 L 1E1HD$D$$H H L E1HD$D$$HH L E1HD$D$$H H Lm 1E1HHW)HDž fDžTƅGHH W)HDž@q H()Hsor typeHH(H any tenHH Han be ofHHH types cHHHd outputHHHInput anHf@0.HHHH3H5{ He#Ln HQ)H #H0H0HPHHH5 HH5 H HH5#HLHHPH9thHtHP(t Hp LMt\HL9tAfff.HX@t Hxkp HI9uHHP uLL:p t H %p H`+ށH HH;EuLH([A^A_]Sp ILMu|IuS]IIIHPH9tHtHP(uHP t Hto LMtHHL9tgfffff.HX@t Hx;o HI9uHL o t H o H`݁L?l  LfUHAWAVSH(IHv HHEH`HPHDž(H5 HL(HD$D$$H H  L~{ 1E1HZD$D$$H} H LM E1HD$D$$H. H L { 1E1HHW)HDž fDžTƅCHH W)HDž@m H(<)Htensor tHH(H to any HH Hut typesHHHand outpHHHn input HHHConstraiH@0ype.@4HHHHH5 H #L H$H #H0H0HPHHH5Y HH5 Hc HH5kHLHgHPH9t_HtHP(t H9l LMtSHL9t8HX@t Hx l HI9uHHP uLLk t H k H`فHT HH;EuLH([A^A_]k ILMu|IuS]IIIHPH9tHtHP(uHP t Hk LMtHHL9tgfffff.HX@t Hxj HI9uHLj t H j H`؁Lg  LfUHAWAVSH(IH HHEH`HHDž(H5 HL(H#D$D$$H/ H 8 Lw 1E1H D$D$$H H L E1H D$D$$Hz H Lv 1E1H5HW)HDž fDžTƅ8?HHIW)HDž@4i H()Htensor tHH(H to any HH Hut typesHHHand outpHHHn input HHHConstraiH@0ype.@4HHHHjH5 H#L H H 9#H0H0HPHH!H5T H2H5H H HFH5 "H"LHHPH9t_HtHP(t Hg LMtSHL9t8HX@t Hxg HI9uHHP uLLzg t H eg H`kՁH HH;EuLH([A^A_]g ILMu|IuS]IIIHPH9tHtHP(uHP t Hf LMtHHL9tgfffff.HX@t Hx{f HI9uHL`f t H Kf H`QԁLc  LfUHAWAVSH(IH HHEH`H萌D$D$$H H Lr 1E1HD$D$$Hz H ELw AHD$D$$HH Lsr 1E1H HW)HDž fDžTƅ;HHW)HDž@d H(d)Hr types.HH-Htensor tHH(H to all HH Hut typesHHHand outpHHHn input HHHConstraiH@5HHHH- H #H0H0HPHHH5 HH5- H H+H5HLHHPH9tdHtHP(t Hc LMtXHL9t=HX@t Hxc HI9uHHP uLLZc t H Ec H`KсH HH;EuLH([A^A_]sc IugqILMunIIIHPH9tHtHP(uHP t Hb LMtHHL9tgfffff.HX@t Hx[b HI9uHL@b t H +b H`1ЁL__  LfUHAWAVSH(IH HHEH`HpD$D$$H H Ln 1E1HD$D$$HZ H $Ls E1HkD$D$$HH LVn 1E1HHW)HDž fDžTƅ6HHW)HDž@` H(`)Hr types.HH-Htensor tHH(H to all HH Hut typesHHHand outpHHHn input HHHConstraiH@5HHHHH #H0H0HPHHH5Z HH5 H HH5ӼHLH݁HPH9tgHtHP(t H_ LMt[HL9t@ff.HX@t Hxk_ HI9uHHP uLL:_ t H %_ H`+́H HH;EuLH([A^A_]S_ IugqILMunIIIHPH9tHtHP(uHP t Ht^ LMtHHL9tgfffff.HX@t Hx;^ HI9uHL ^ t H ^ H`́L?[  LfUHAWAVSH(IHv HHEH`HPH5V HAHOD$D$$Hn H +Lj 1E1HfD$D$$Hvn H FLQj 1E1HHW)HDž fDžTƅ2HHW)HDž@\ H(\)Hr types.HH-Htensor tHH(H to all HH Hut typesHHHand outpHHHn input HHHConstraiH@5HHHH H |#H0H0HPHHH5 HH5 H H H5θ9HLHفHPH9tbHtHP(t H[ LMtVHL9t;fDHX@t Hxk[ HI9uHHP uLL:[ t H %[ H`+ɁH HH;EuLH([A^A_]S[ IugqILMunIIIHPH9tHtHP(uHP t HtZ LMtHHL9tgfffff.HX@t Hx;Z HI9uHL Z t H Z H`ȁL?W  LfUHAWAVSHHIHv HHEH`HPH5V HAHOW)HDž ƅDžDCRH5 HLHD$D$$H_j H LBf 1E1HD$D$$H.j H L f 1E1HHW)HDžfDžTƅ.HHW)HDž@X H(\X)Hr types.HH-Htensor tHH(H to all HH Hut typesHHHand outpHHHn input HHHConstraiH@5HHHHH #H0H0HPHHH5K HH5Ä H~ HH5HLHՁHPH9tjHtHP(t HTW LMt^HL9tCfffff.HX@t HxW HI9uHHP uLLV t HV t H V H`āHO HH;EuLHH[A^A_]V IILMIIIIHPH9tHtHP(uHP t HU LMtCHL9twfHX@t HxU HI9uHLU t HU t H vU H`|ÁLR  Lffff.UHAWAVSH(IHֹ HHEH`H{D$D$$H(f H L b 1E1HD$D$$HH L| +E1HD$D$$He H #La 1E1H"HW)HDž fDžTƅ%*HH6W)HDž@!T H(S)Hr types.HH-Htensor tHH(H to all HH Hut typesHHHand outpHHHn input HHHConstraiH@5HHHHPH5z +H#LpHn H #H0H0HPHHH5 HH5. H H,H5HLHЁHPH9teHtHP(t HR LMtYHL9t>fHX@t HxR HI9uHHP uLLZR t H ER H`KHԶ HH;EuLH([A^A_]sR ILMu|IuS]IIIHPH9tHtHP(uHP t HQ LMtHHL9tgfffff.HX@t Hx[Q HI9uHL@Q t H +Q H`1L_N  LfUHAWAVSHHIH HHEH`HpwHW)ƅHDž HnearestHH5 HhLHD$D$$Ha H Lt] 1E1HPD$D$$H H UL`b E1HD$D$$H"a H [L\ 1E1HHW)HDžfDžTƅMHHW)HDž@O H(ry)Hr types.HH/Hl tensorHH(HY' to alHH Houtput 'HHH'X' and HHHn input HHHConstraiH@7HHHHH #H0H0HPHHH5S HH5{ Ht +H跿H5|'HLHx́HPH9t`HtHP(t HJN LMtTHL9t9@HX@t HxN HI9uHHP uLLM t HM t H M H`ƻHO HH;EuLHH[A^A_]M IILMIIIIHPH9tHtHP(uHP t HL LMtCHL9twfHX@t HxL HI9uHLL t HL t H vL H`|LI  Lffff.UHAWAVSHIHְ HHEH`HrW)ƅHDž HnearestHH5a HLHADž @H5 H^L H5HDžH5l H>LHhW)ƅHDžHhalf_pixHfDželƅH52 HLHW)ƅ$HDžHefer_floHHround_prHfDžorƅH5o HLHDžH5 HLH D$D$$H[ H Lq +1E1HDD$D$$HtH qLKz AHD$D$$H H L\ AHD$D$$HmH lL[ AHD$D$$HZ H Lp +1E1HHW)HDžƅfDžT1ƅHH W)pHDž@H H(r)pHr types.HH/Hl tensorHH(HY' to alHH Houtput 'HHH'X' and HHHn input HHHConstraiH@7HHHpH%H5x H#LHCH t#H0H0HPHHܼH5 HH5u H HH5ƤHݾLHŁHPH9tjHtHP(pt HG LMt^HL9tCfffff.HX@t Hx[G HI9uHHP puLL*G uTu`ult H F H`H HH;EuRLHĘ[A^A_]HF tHF tHF uF ILMI!xIxI IIIpuKUIIHPH9tHtHP(puHP pt HE LMtGHL9fHX@t HxkE HI9uHLPE u=u\uht H E H`&LTB  HD tLItHD tHD uUHAWAVATSH@IH4 HHEHPHkD$D$$HU H X L +1E1HED$D$$HUU H L` +1E1HIW)HDžfDžVƅHHkHHHHHH{LMtBHL9t'HX@t HxkC HI9uHLLKC W)HDžP8C HH(o)H5pBHD CBHHHLH #H H #H(H H@HH|H5N H荸H5o H^H衳H5fH}LHbH@H9tjHtHP(t H4B LMt^HL9tCfffff.HX@t HxA HI9uHHP uLLA t HA HP軯HD HH;EuLH@[A\A^A_]A IILMTILMtSHL9t$HX@t Hx&A HI9uHLLA LMuILMHL9@HX@t Hx@ HI9uIIIH@H9tHtHP(uHP t HQ@ LMtEHL9tdff.HX@t Hx@ HI9uHL@ t H? HPL=  LfUHAWAVSH(IHV HHEH`H0fH5 H6E1H2D$D$$HP H LmL 1E1HID$D$$HVH Lf +E1H D$D$$HP H 7LK 1E1HHW)HDž fDžTƅ<HH܈W)HDž@> H(K>)Hr types.HH-Htensor tHH(H to all HH Hut typesHHHand outpHHHn input HHHConstraiH@5HHHHH5>e +H4#LkHH #H0H0HPHHiH5mp HzH5j HK H莮H5S HjLHOHPH9tgHtHP(t H!= LMt[HL9t@ff.HX@t Hx< HI9uHHP uLL< t H < H`諪H4 HH;EuLH([A^A_]< ILMu|IuS]IIIHPH9tHtHP(uHP t H; LMtHHL9tgfffff.HX@t Hx; HI9uHL; t H ; H`葩L8  LfUHAWAVAUATSHIH HHEHPHaHDžH5 HLHD$D$$H2 H LFb +1E1HD$D$$H8H Lj E1HD$D$$Hq H HL + E1H^D$D$$HnK H -L 1E1HHW)HDžƅfDžT1ƅQHH׈L(W)HDž09 H()Ic types.L`I numericLhI to onlyLpIns inputLxHConstraiH@'HHHHHW)HDžƅfDžT2ƅmHHֈW)HDž08 H(A~)L`LhLpLxIConstraiL0@'HHHH\HW)`HDžpƅ`fDžaT3ƅc6L(HHHBֈW)0HDž@ -8 H@()0Hor type.HHH tensor HHHn to anyHHL0@H`HHH0HH #H H H@HHiH5z HzH5d HK H莨H5S HjLHOH@H9tgHtHP(0t H@!7 LHMt[HPL9t@ff.HX@t Hx6 HI9uHHHP 0uLLP6 `uGuSLMtpHL9tUfHX@t Hx{6 HI9uH2Hp^6 tHI6 LMuLL,6 uIuULMtrHL9tW@HX@t Hx5 HI9uH2H5 tH5 LMuLL5 t H5 HP荣H HH;EuLH[A\A]A^A_]5 I0ILHM,I.LILMQIILMI`IBTIIIH@H9tHtHP(0uHP 0t H@C4 LHMt?HPL9t$HX@t Hx4 HI9uHHLLP3 `uu#LMu/lHp3 tH3 LMt?HL9t$HX@t Hx3 HI9uHLLl3 uu#LMu/lH@3 tH+3 LMt?HL9t^DHX@t Hx2 HI9uHL2 t H2 HPѠL/  LfUHAVSHIH8 HHEH`HYD$D$$HC H C LY +1E1HID$D$$HWC H RC LPb 1E1HH5lY +Hjw#LÿHH5b Hhw#LɿHH #H0H0HPHHuH5q H膧H5^ HW H蚢H5_ HvLH[HPH9t HtHP(HP H`@Hɕ HH;EuLH[A^]j1 I"IHPH9uHP HtHP(H`鞁L.  ffffff.UHAVSHIHH HHEH`H"WD$D$$HA H A LW +1E1HYD$D$$HgA H bA L`` 1E1HHDž(H5ro HOL(HHDž H5o HіL H趴H5"W +HHu#LyHH5_ H6u#LHH À#H0H0HPHH+H5n H<H5R\ H +HPH5 +H,LHHPH9t HtHP(HP H`H HH;EuLH[A^] / I,I'I"IHPH9uHP HtHP(H`蕜L+  ff.UHAWAVSH(IH HHEH`HTD$D$$HMH LY +1E1HD$D$$H ? H L: E1HD$D$$H> H L: E1HD$D$$H> H Lz: 1E1HH5 +Hr#LŕHDHW)HDž fDžTƅ7+HHʈW)HDž@, H(,)Hr types.HH-Htensor tHH(H to all HH Hut typesHHHand outpHHHn input HHHConstraiH@5HHHHH ~#H0H0HPHHH5e HH5Y Hͤ HH5Ոb +HLHѩHPH9tiHtHP(t H+ LMt]HL9tBffff.HX@t Hxk+ HI9uHHP uLL:+ t H %+ H`+H HH;EuLH([A^A_]S+ IugqILMunIIIHPH9tHtHP(uHP t Ht* LMtHHL9tgfffff.HX@t Hx;* HI9uHL * t H * H`L?'  LfUHAWAVSH(IHv HHEH`HPPD$D$$H: H : L6 1E1HD$D$$H: H : Lh; 1E1HHW)HDž fDžTƅHHLjW)HDž ( H(eb)Hr types.HHH tensor HHHn to allHHHConstraiH@HHHHVH z#H0H0HPHH/H5h H@H5VU H HTH5 +H0LHHPH9t]HtHP(t H' LMtQHL9t6HX@t Hx' HI9uHHP uLL' t H u' H`{H HH;EuLH([A^A_]' IugqILMunIIIHPH9tHtHP(uHP t H& LMtHHL9tgfffff.HX@t Hx& HI9uHLp& t H [& H`aL#  LfUHAWAVSH8IHƊ HHEH`HLHDž(H5Ӄ HL(HӪHDž H5 HL H親D$D$$H6 H ЎL2 1E1H}D$D$$Hph H L^7 E1HAD$D$$HO6 H ƎL,2 1E1HHW)HDžfDžTƅ #HHˆW)HDž@$ H(Oj)Hsor typeHH(H any tenHH Han be ofHHH types cHHHd outputHHHInput anHf@0.HHHHH v#H0H0HPHH˘H5 HܙH5P H譜 +HH5 +H̚LH象HPH9tiHtHP(t H# LMt]HL9tBffff.HX@t HxK# HI9uHHP uLL# t H# H` H HH;EuLH8[A^A_]3# IuoyILMuvIIIIHPH9tHtHP(uHP t HL" LMt@HL9t_fDHX@t Hx" HI9uHL" t H! H`L  LfUHAWAVSH(IHV HHEH`H0HHDž(H5= HRL(HcH5 HE1HD$D$$H[2 H [L@. 1E1HD$D$$H*2 H NL. 1E1HD$D$$H H ҌL2 AHTD$D$$HH L2 AHD$D$$Hy H ^LF2 AHHW)HDž fDžTƅ)HH꽈W)HDž0 H(ݠ)Hor type.HHHany tensHHHn be of HHHInput caH@ HHHH.H r#H0H0HPHHH5 HH5.L H H,H5{ HLH휁HPH9teHtHP(t H LMtYHL9t>fHX@t Hx HI9uHHP uLLZ t H E H`KHԂ HH;EuLH([A^A_]s Iu_iILMufIIHPH9tHtHP(uHP t H LMt@HL9tKfDHX@t Hxk HI9uHLP tH ; LIH`7Le  ffff.UHAWAVSH(IH HHEH`HpCHDž(H5dZ HL(H裡D$D$$H H L) 1E1HzD$D$$H H ҪL[. 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types.HH-Htensor tHH(H to all HH Hut typesHHHand outpHHHn input HHHConstraiH@5HHHHH Q"H0H0HPHHH5" -HH5 HHH5: HLH蟜HPH9tgHtHP(t HQTLMt[HL9t@ff.HX@t HxTHI9uHHP uLLSt H SH`HDHH;EuLH([A^A_]TIugqILMunIIIHPH9tHtHP(uHP t H$SLMtHHL9tgfffff.HX@t HxRHI9uHLRt H RH`ኀLO LfUHAWAVSH(IHHHEH`H CD$D$$H H 1 L[_1E1HGD$D$$H -H = L`y 1E1HHW)HDž fDžTƅPHH⹇W)HDž0QH(ud)Hry type.HHHrbitraryHHH be of aHHHnsor canHHHInput teH@&HHHHH5vx HZ"LX H& H "H0H0HPHHH5 -j HH5+~ HHH5P HLH赘HPH9t]HtHP(t HgPLMtQHL9t6HX@t Hx;PHI9uHHP uLL -Pt H OH`HdHH;EuLH([A^A_]#PILMu|IuS]IIIHPH9tHtHP(uHP t HDOLMtHHL9tgfffff.HX@t Hx OHI9uHLNt H NH`LL LfUHAWAVSH(IH&HHEH`H@?D$D$$H H Q L{[1E1HgD$D$$H H Lu 1E1HHW)HDž fDžTƅ1LHHW)HDž0MH(`)Hry type.HHHrbitraryHHH be of aHHHnsor canHHHInput teH@&HHHH(H5t H"L HFH "H0H0HPHHH5 -HH5Kz HHH5p HLHՔHPH9t]HtHP(t HLLMtQHL9t6HX@t Hx[LHI9uHHP uLL*Lt H LH`;HHH;EuLH([A^A_]CLILMu|IuS]IIIHPH9tHtHP(uHP t HdKLMtHHL9tgfffff.HX@t Hx+KHI9uHLKt H JH`!L/H LfUHAWAVSH(IHFHHEH`H`;H5 -Hy AHOD$D$$H H LzW1AHcD$D$$H H L>W1E1HHW)HDž fDžTƅ-HHHW)HDž0IH(a)Hnsor typHH Ho any teHHH types tHHHn outputHHHConstraiHf@(e.@*HHHHH "H0H0HPHHH5} -HH5cv H HH5 HLH퐀HPH9teHtHP(t HHLMtYHL9t>fHX@t HxkHHI9uHHP uLL:Ht H %HH`KHHH;EuLH([A^A_]SHIugqILMunIIIHPH9tHtHP(uHP t HtGLMtHHL9tgfffff.HX@t Hx;GHI9uHL Gt H GH`1L?D LfUHAWAVSH(IHVHHEH`Hp7D$D$$HWH E LS1E1HD$D$$H H LrS1AH HW)HDž fDžTƅ^DHH/W)HDž@EH(bX)Hr types.HH-Htensor tHH(H to all HH Hut typesHHHand outpHHHn input HHHConstraiH@5HHHH9HDžH5 -H: LH,H5ٷ -H E1HH o"H0H0HPHHǹH5 -HغH53r H詽 HH5X HȻLH轌HPH9teHtHP(t HoDLMtYHL9t>fHX@t Hx;DHI9uHHP uLL -Dt H CH`|HdHH;EuLH([A^A_]#DIuuILMu|IuS]IIIHPH9tHtHP(uHP t H6CLMt:HL9tYHX@t Hx CHI9uHLBt H BH`{L@ LfUHAWAVSH(IH&HHEH`H@3D$D$$H H L{O1E1HgD$D$$H -H L< -E1H+D$D$$H H L -E1HD$D$$H H LĪ -AHD$D$$H H  L -AHqD$D$$HqRH LLN1E1HHW)HDž fDžTƅ;?HH W)HDž@@H(?S)Hr types.HH-Htensor tHH(H to all HH Hut typesHHHand outpHHHn input HHHConstraiH@5HHHHH5@ -Hx"L H4H "H0H0HPHHʹH5 -H޵H59m H诸 HH5^ HζLHÇHPH9tkHtHP(t Hu?LMt_HL9tDffffff.HX@t Hx;?HI9uHHP uLL -?t H >H`wHdHH;EuLH([A^A_]#?ILMutIuKUIIHPH9tHtHP(uHP t HL>LMt@HL9tKfDHX@t Hx>HI9uHL>tH =LIH`vL; ffff.UHAWAVSH(IH&HHEH`H@.H5 H E1H2D$D$$H H 3 L]J1E1HID$D$$H H L$J1E1HHW)HDž fDžTƅ;HH䤇W)HDž@<H(O)Hr types.HH-Htensor tHH(H to all HH Hut typesHHHand outpHHHn input HHHConstraiH@5HHHHH o"H0H0HPHHǰH5̷ -HرH53i H詴HH5X HȲLH轃HPH9teHtHP(t Ho;LMtYHL9t>fHX@t Hx;;HI9uHHP uLL -;t H :H`sHdHH;EuLH([A^A_]#;IugqILMunIIIHPH9tHtHP(uHP t HD:LMtHHL9tgfffff.HX@t Hx :HI9uHL9t H 9H`rL7 LfUHAWAVSH(IH&HHEH`H@*D$D$$H H L{F1E1HgD$D$$H H L8KE1H+D$D$$H H LFE1HD$D$$HIH 9 LE1E1HfHW)HDž fDžTƅ6HH芠W)HDž@U8H(=)Htensor tHH(H to any HH Hut typesHHHand outpHHHn input HHHConstraiH@0ype.@4HHHHH "H0H0HPHHtH5A -H腭H5d HV H虨H5 HuLHjHPH9tbHtHP(t H7LMtVHL9t;fDHX@t Hx6HI9uHHP uLL6t H 6H`nHHH;EuLH([A^A_]6IugqILMunIIIHPH9tHtHP(uHP t H5LMtHHL9tgfffff.HX@t Hx5HI9uHL5t H 5H`mL2 LfUHAWAVSH(IH֬HHEH`H%HDž(H5 -H L(HD$D$$Hd H m LA1E1HD$D$$HR H + L -E1HD$D$$H< H LAE1HrD$D$$HrEH LMA1E1HHW)HDž fDžTƅ<2HH W)HDž@3H(~)Hsor typeHH(H any tenHH Han be ofHHH types cHHHd outputHHHInput anHf@0.HHHH#H5M -H"L HAH "H0H0HPHHڧH5 -HH5F` H輫 HH5k rH۩LHzHPH9thHtHP(t H2LMt\HL9tAfff.HX@t HxK2HI9uHHP uLL2t H 2H`+jHtHH;EuLH([A^A_]32ILMu|IuS]IIIHPH9tHtHP(uHP t HT1LMtHHL9tgfffff.HX@t Hx1HI9uHL1t H 0H`iL. LfUHAWAVSH(IH6HHEH`HP!HDž(H5 -H- L(HsD$D$$H H L^=1E1HJD$D$$H H > L -E1HD$D$$HAH L<1E1HHW)HDž fDžTƅ-HH詗W)HDž@t/H(\)Htensor tHH(H to any HH Hut typesHHHand outpHHHn input HHHConstraiH@0ype.@4HHHHH5 -H<"L: HH "H0H0HPHHqH5+f -H肤H5[ HS H薟H5 HrLHgvHPH9t_HtHP(t H.LMtSHL9t8HX@t Hx-HI9uHHP uLL-t H -H`eHHH;EuLH([A^A_]-ILMu|IuS]IIIHPH9tHtHP(uHP t H,LMtHHL9tgfffff.HX@t Hx,HI9uHL,t H ,H`dL) LfUHAWAVSH(IH֣HHEH`HHDž(H5 -Hͪ L(HD$D$$Hd H m L81E1HD$D$$HR H L -E1HD$D$$H<H L L81E1H%HW)HDž fDžTƅx)HHIW)HDž@+H()Htensor tHH(H to any HH Hut typesHHHand outpHHHn input HHHConstraiH@0ype.@4HHHHZH5 -H"Lھ HxH "H0H0HPHHH5&c -H"H5}W H H6H5 KHLHrHPH9t_HtHP(t H)LMtSHL9t8HX@t Hx)HI9uHHP uLLZ)t H E)H`kaHHH;EuLH([A^A_]s)ILMu|IuS]IIIHPH9tHtHP(uHP t H(LMtHHL9tgfffff.HX@t Hx[(HI9uHL@(t H +(H`Q`L_% LfUHAWAVSH(IHvHHEH`HH5 Hʨ E1H肦D$D$$H H 6 L41E1HD$D$$H0 H 2 Lt41E1HHW)HDž fDžTƅc%HH4W)HDž@&H(g9)Hr types.HH-Htensor tHH(H to all HH Hut typesHHHand outpHHHn input HHHConstraiH@5HHHH>H ?"H0H0HPHHH5ٜ -H(H5S H H<H5 HLH nHPH9teHtHP(t H%LMtYHL9t>fHX@t Hx%HI9uHHP uLLZ%t H E%H`k]HHH;EuLH([A^A_]s%IugqILMunIIIHPH9tHtHP(uHP t H$LMtHHL9tgfffff.HX@t Hx[$HI9uHL@$t H +$H`Q\L_! LfUHAWAVSH(IHvHHEH`HH5 Hɥ AHD$D$$H H : L01E1HD$D$$H H / Lq01E1H HW)HDž fDžTƅ`!HH1W)HDž@"H(d5)Hr types.HH-Htensor tHH(H to all HH Hut typesHHHand outpHHHn input HHHConstraiH@5HHHH;H "H0H0HPHHH5g -H%H5O H H9H5 HLH -jHPH9tbHtHP(t H!LMtVHL9t;fDHX@t Hx!HI9uHHP uLLZ!t H E!H`kYHHH;EuLH([A^A_]s!IugqILMunIIIHPH9tHtHP(uHP t H LMtHHL9tgfffff.HX@t Hx[ HI9uHL@ t H + H`QXL_ LfUHAWAVSH(IHvHHEH`HH5h -H AHD$D$$H0H  L,1E1H薿D$D$$H0H Lq,1E1H HW)HDž fDžTƅ`HH1W)HDž@H(d1)Hr types.HH-Htensor tHH(H to all HH Hut typesHHHand outpHHHn input HHHConstraiH@5HHHH;H <"H0H0HPHHH5 -H%H5K HH9H5 /HLH -fHPH9tbHtHP(t HLMtVHL9t;fDHX@t HxHI9uHHP uLLZt H EH`kUHHH;EuLH([A^A_]sIugqILMunIIIHPH9tHtHP(uHP t HLMtHHL9tgfffff.HX@t Hx[HI9uHL@t H +H`QTL_ LfUHAWAVSHHIHvHHEH`H H5h -H AHW)HDž ƅDžDCRH5\ H0 LHD$D$$H,H 7 Lb(1E1HND$D$$HN,H  L)(1E1HſHW)HDžfDžTƅHH邇W)HDž@H(-)Hr types.HH-Htensor tHH(H to all HH Hut typesHHHand outpHHHn input HHHConstraiH@5HHHHH t"H0H0HPHH̎H5] -HݏH58G H讒 HH5] H͐LHaHPH9tjHtHP(t HtLMt^HL9tCfffff.HX@t Hx;HI9uHHP uLL -t Ht H H`QHOHH;EuLHH[A^A_]IILMIIIIHPH9tHtHP(uHP t HLMtCHL9twfHX@t HxHI9uHLt Ht H H`OL Lffff.UHAWAVSH(IH֎HHEH`HD$D$$HH(H l L+$1E1HD$D$$HU H V L0> E1H۶D$D$$H'H L#1E1HRHW)HDž fDžTƅHHv~W)HDž@AH(()Hr types.HH-Htensor tHH(H to all HH Hut typesHHHand outpHHHn input HHHConstraiH@5HHHH耼H5< H""L HH _"H0H0HPHH7H5 -HHH5B HH\H5Ȍ H8LH-]HPH9teHtHP(t HLMtYHL9t>fHX@t HxHI9uHHP uLLzt H eH`LHԋHH;EuLH([A^A_]ILMu|IuS]IIIHPH9tHtHP(uHP t HLMtHHL9tgfffff.HX@t Hx{HI9uHL`t H KH`qKL LfUHAWAVSHIHHHEH`HW)ƅHDž HnearestHH5 HI LH1Dž @H5]h -H L H%HDžH5>h -Hs LHXW)ƅHDžHhalf_pixHfDželƅH5g -H LHyW)ƅ$HDžHefer_floHHround_prHfDžorƅH5Ag -HL LH DžH5Tf -HH LHD$D$$Hc"H Л L8 1E1H4D$D$$H H LA -E1HD$D$$Hpe -H c L"E1H輰D$D$$H H L"AH}D$D$$H{!H L7 1E1HHW)HDžƅfDžT1ƅ@HHxW)pHDž@H(dL)pHr types.HH/Hl tensorHH(HY' to alHH Houtput 'HHH'X' and HHHn input HHHConstraiH@7HHHpHH5Y? -H}"L H9H z"H0H0HPHH҃H5b -HH5>< H贇 HH5c @HӅLHVHPH9t`HtHP(pt HzLMtTHL9t9@HX@t HxKHI9uHHP puLLuTu`ult H H`FHYHH;EuRLHĘ[A^A_]H tH tH u ILMI!xIxI IIIpuKUIIHPH9tHtHP(puHP pt H LMtGHL9fHX@t Hx[ HI9uHL@ u=u\uht H  H`6DLD  H tLItH tH uUHAWAVSH(IHHHEH`H D$D$$HxH L[1E1HGD$D$$HGH  L"1E1H辯HW)HDž fDžTƅѪHHrW)HDž@ -H()Hr types.HH-Htensor tHH(H to all HH Hut typesHHHand outpHHHn input HHHConstraiH@5HHHHH E!H0H 'H8H0HPHH~H5kG -HH5#7 H虂 HzH5H ]H踀LHQHPH9teHtHP(t H_ LMtYHL9t>fHX@t Hx+ HI9uHHP uLLt H H` AHTHH;EuLH([A^A_] IugqILMunIIIHPH9tHtHP(uHP t H4LMtHHL9tgfffff.HX@t HxHI9uHLt H H`?L LfUHAWAVSH(IHHHEH`H0D$D$$HH Lk1E1HWD$D$$HWH $ L21E1HΫHW)HDž fDžTƅ!HHnW)HDž@H(%)Hr types.HH-Htensor tHH(H to all HH Hut typesHHHand outpHHHn input HHHConstraiH@5HHHHH U!H0H 7H8H0HPHHzH5{C -H{H533 H~HvH5X} jH|LHMHPH9teHtHP(t HoLMtYHL9t>fHX@t Hx;HI9uHHP uLL -t H H`=Hd|HH;EuLH([A^A_]#IugqILMunIIIHPH9tHtHP(uHP t HDLMtHHL9tgfffff.HX@t Hx HI9uHLt H H`<L LfUHAVSHIH({HHEH`HBD$D$$HH L* 1E1HiD$D$$HgH bLR3 -1E1HH5n* Hq"L( HH53 -Hq"L. HH }"H0H0HPHHwH5B -HxH50 Hw{ HsH5&z HyLHJHPH9t HtHP(HP H`p:HyHH;EuLH[A^]zI"IHPH9uHP HtHP(H`:L' ffffff.UHAWAVSH(IH6yHHEH`HPD$D$$HH L1E1HwD$D$$HuH pLH1E1HHW)HDž fDžTƅAHHiW)HDž H(?)Hr types.HHH tensor HHHn to allHHHConstraiH@HHHHFH {"H0H0HPHHuH5@ -H0vH5- Hy HDqH5w H wLHHHPH9t]HtHP(t HLMtQHL9t6HX@t HxHI9uHHP uLLjt H UH`{7HvHH;EuLH([A^A_]IugqILMunIIIHPH9tHtHP(uHP t HLMtHHL9tgfffff.HX@t HxkHI9uHLPt H ;H`a6Lo LfUHAWAVSH(IHuHHEH`HHDž(H5f; -HG L(HÂD$D$$H H  L -1E1H蚝D$D$$H H 7 LkE1H^D$D$$H^H y L9 -1E1HաHW)HDž fDžTƅ(HHdW)HDž@H()Htensor tHH(H to any HH Hut typesHHHand outpHHHn input HHHConstraiH@0ype.@4HHHH -H x"H0H0HPHHpH5L8 -HqH5O) Ht HmH5ts MHrLHCHPH9taHtHP(t HLMtUHL9t:DHX@t Hx[HI9uHHP uLL*t H H`;3HrHH;EuLH([A^A_]CIugqILMunIIIHPH9tHtHP(uHP t HdLMtHHL9tgfffff.HX@t Hx+HI9uHLt H H`!2L/ LfUHAWAVSHHIHFqHHEH`H`W)ƅHDž HconstantHƅH5? H LHډD$D$$H H LE1E1H1D$D$$H H L E1HD$D$$H: H B LAH趘D$D$$H H ɢ L1E1H-HW)HDžfDžTƅ谝HHQ`W)HDž@H($s)Hric typeHH(Hnly numeHH Hput to oHHH and outHHHns inputHHHConstraiHf@0s.@2HHHHcH s"H0H0HPHH<lH5z; -HMmH5$ Hp HahH5n H=nLH2?HPH9tjHtHP(t HLMt^HL9tCfffff.HX@t HxHI9uHHP uLLzt Het H PH`v.HmHH;EuLHH[A^A_]~Iut~ILMu{IIIHPH9tHtHP(uHP t HLMtFHL9tzfff.HX@t Hx[HI9uHL@t H+t H H`<-LJ Lffff.UHAVSHIHXlHHEH`HrH5j Hj AHasD$D$$HH 7k L 1E1HxD$D$$HxH k La$ -1E1HH5} Hb"L H-H5+$ -H/c"L! H H5 $ -HiH57! HlHdH5\k ! HjLH;H`+HkHH;EuLHİ[A^]HH`+H UHAVSHIHjHHEH`HH5Mi HIi AHqD$D$$H H i L* 1E1HؒD$D$$HH wi L" -1E1HOH5 Hb"LX H荪H5" -HOb"L HkH ,o"H0H0HPHHgH5E" -HhH5p HjH)cH5i _ HiLH9HPH9t HtHP(HP H`)H(iHH;EuLH[A^]I"IHPH9uHP HtHP(H`)L fffff.UHAVSHIHhHHEH`HH5j -Hw E1HoD$D$$H5j H 5j L1AHȐD$D$$H"j H )j L1E1H?H5H`"L H}H5F$ -HNfH5 HiHbaH5g x H>gLH38H`7(HgHH;EuLHİ[A^]AHH`(H f.UHAWAVSH(IH&gHHEH`H@H5 -HL AH/nD$D$$Hh H h LZ1AHCD$D$$Hh H h L1E1H躓HW)HDž fDžTƅ HHVW)HDž0H(A)Hnsor typHH Ho any teHHH types tHHHn outputHHHConstraiHf@(e.@*HHHHH k"H0H0HPHHbH5! -HcH5C HfH^H5he HdLH5HPH9teHtHP(t HLMtYHL9t>fHX@t HxKHI9uHHP uLLt H H`+%HtdHH;EuLH([A^A_]3IugqILMunIIIHPH9tHtHP(uHP t HTLMtHHL9tgfffff.HX@t HxHI9uHLt H H`$L LfUHAVSHIH8cHHEH`HR܀D$D$$HH 'e L1E1HyD$D$$H] -H &~ LTAH:D$D$$H%~ H d L1AH讏H5HH["Lx HH5$ -H} E1HniH5[] -H} E1HPiH5T[ -H`H5 HRcH[H5b HqaLHf2H`j"HaHH;EuLHİ[A^]tHH`7"HE ffff.UHAVSHIHXaHHEH`HrڀH5 } H} AHahW)@ƅ@HDžPHconstantHAƅIH50 HC~ L@HyDž<H5v0 -HE~ L<HsD$D$$Hp| H L -1E1HD$D$$HH L1E1HmH5HY"LCp H諠H5, -H|^H5 HMaHYH5_  -Hl_LHa0@t HP*H`P H_HH;EuLH[A^]ZH@uHH@t HPH`H ff.UHAVSHIH_HHEH`H2؀H57 -H| E1H$fH5qw Hzw E1HfD$D$$Hz H _ L11E1HD$D$$H_ H _ L1E1H蔋H5H^W"Ljn HҞH5 7 -H\H5 Ht_HWH5#^ 9 -H]LH.H`H]HH;EuLHİ[A^]HH`YHg ffffff.UHAVSHIHx]HHEH`HրD$D$$HH j L1E1H蹅D$D$$Hz H z LE1H}D$D$$H -H z LXE1HAD$D$$HAH z L1E1H踉H5HU"Ls HH5$ HU"Lz HԜH b"H0H0HPHHmYH5\ -H~ZH5 HO]HUH5[ p -Hn[LHc,HPH9t HtHP(HP H`HH[HH;EuLH[A^]RIHPH9uHP Ht HP(IH`L UHAVSHIH[HHEH`H2ԀHXH5~y Hy AHbH5y Hy AHaW)@ƅ@HDžPHnearestHAH5ɉ Hy L@HdsD$D$$HH y L1E1H軂D$D$$HH y L1E1H2H5H4S"Ly HpH5k -HAXH5 H[HUSH5Y -H1YLH&*@t HPH`H^YHH;EuLH[A^]HH@t HPH`H fffff.UHAWAVSHHIHXHHEH`HҀH55 -Hx AH_W)ƅHDž HnearestHH5Ň Hy LH`qD$D$$HH Sk L1E1H跀D$D$$HH Cn L1E1H.HW)HDžfDžTƅHHRHW)HDž@H()Hr types.HH-Htensor tHH(H to all HH Hut typesHHHand outpHHHn input HHHConstraiH@5HHHH\H ]"H0H0HPHH5TH5h -HFUH5 HXHZPH5V -H6VLH+'HPH9tcHtHP(t HLMtWHL9t<HX@t HxHI9uHHP uLLzt Het H PH`vHUHH;EuLHH[A^A_]~IILMIIIIHPH9tHtHP(uHP t HLMtCHL9twfHX@t HxKHI9uHL0t Ht H H`,L: Lffff.UHAWAVSHHIHFTHHEH`H`̀W)ƅHDž HnearestHH5F Ht LHlD$D$$HgH f LL1E1H8|D$D$$H0 -H s L8E1H{D$D$$HH i L1E1HsHW)HDžfDžTƅHHCW)HDž@bH()Hr types.HH/Hl tensorHH(HY' to alHH Houtput 'HHH'X' and HHHn input HHHConstraiH@7HHHH衁H Y"H0H0HPHHzOH5d -HPH5 H\S HKH5 R -H{QLHp"HPH9thHtHP(t H"LMt\HL9tAfff.HX@t HxHI9uHHP uLLt Ht H H`HPHH;EuLHH[A^A_]Iut~ILMu{IIIHPH9tHtHP(uHP t HLMtFHL9tzfff.HX@t HxHI9uHLt Hkt H VH`|L Lffff.UHAWAVSHHIHOHHEH`HȀW)ƅHDž HnearestHH5~ Ho LH1hD$D$$HH $b L1E1HwD$D$$H, -H o LE1HLwD$D$$HJH d L'1E1H{HW)HDžfDžTƅHH>W)HDž@H(:)Hr types.HH/Hl tensorHH(HY' to alHH Houtput 'HHH'X' and HHHn input HHHConstraiH@7HHHH|H rU"H0H0HPHHJH5) -HKH56 HN -HFH5[M  HLLHHPH9thHtHP(t HrLMt\HL9tAfff.HX@t Hx;HI9uHHP uLL -t Ht H H` HOLHH;EuLHH[A^A_]Iut~ILMu{IIIHPH9tHtHP(uHP t H"LMtFHL9tzfff.HX@t HxHI9uHLt Ht H H` L Lffff.UHAWAVSH(IHJHHEH`HĀD$D$$Hf H f L;1E1H'sH56g H_l E1HQH5= -Hl AHQH5f Hl AHwQD$D$$HH f L1E1H>wHW)HDž fDžTƅHHb:W)HDž@-H()Hr types.HH-Htensor tHH(H to all HH Hut typesHHHand outpHHHn input HHHConstraiH@5HHHHlxH mQ"H0H0HPHHEFH5i: -HVGH5 H'JHjBH5H HFHLH;HPH9tcHtHP(t HLMtWHL9t<HX@t HxHI9uHHP uLLt H uH`HGHH;EuLH([A^A_]IugqILMunIIIHPH9tHtHP(uHP t HLMtHHL9tgfffff.HX@t HxHI9uHLpt H [H`L LfUHAWAVSH(IHFHHEH`HD$D$$Hab H _b L1E1HnD$D$$Ho9 -H Mb L7 -E1HnD$D$$HWb H )I L7 -E1HonD$D$$Hgb H eb LD7 -AH0nD$D$$HI H 6h L7 -AHmD$D$$HH b L1E1HhrHW)HDž fDžTƅHH5W)HDž@WH()Hr types.HH-Htensor tHH(H to all HH Hut typesHHHand outpHHHn input HHHConstraiH@5HHHHsH55 -H="La H贄H L"H0H0HPHHMAH5q5 -H^BH5 H/E -Hr=H5C HNCLHCHPH9tkHtHP(t HLMt_HL9tDffffff.HX@t HxHI9uHHP uLLt H uH`HBHH;EuLH([A^A_]ILMutIuKUIIHPH9tHtHP(uHP t HLMt@HL9tKfDHX@t HxHI9uHLtH kLIH`L ffff.UHAWAVSH(IHAHHEH`HHDž(H5]w -H{d L(HND$D$$H4] H =m L1E1HiD$D$$H"m H wd L2 -E1H~iD$D$$H F H G LYE1HBiD$D$$HBH G L1E1HmHW)HDž fDžTƅ HH0W)HDž@H()Hsor typeHH(H any tenHH Han be ofHHH types cHHHd outputHHHInput anHf@0.HHHHnH51 -H9"Ls\ HH H"H0H0HPHH<H5S, -H=H5 H@ H8H5;? H>LHHPH9thHtHP(t HRLMt\HL9tAfff.HX@t HxHI9uHHP uLLt H H`HD>HH;EuLH([A^A_]ILMu|IuS]IIIHPH9tHtHP(uHP t H$LMtHHL9tgfffff.HX@t HxHI9uHLt H H`L LfUHAWAVSH(IH=HHEH`H H54 -HH AHDD$D$$HWH H L:1E1H&eD$D$$H&H H L1E1HiHW)HDž fDžTƅHH,W)HDž@H()Hr types.HH-Htensor tHH(H to all HH Hut typesHHHand outpHHHn input HHHConstraiH@5HHHHjH LE"H0H0HPHH8H551 -H9H5 H<H4H55; H:LH HPH9tbHtHP(t HLLMtVHL9t;fDHX@t HxHI9uHHP uLLt H H`HD:HH;EuLH([A^A_]IugqILMunIIIHPH9tHtHP(uHP t H$LMtHHL9tgfffff.HX@t HxHI9uHLt H H`L LfUHAWAVSH(IH9HHEH`H HDž(H5n -H\ L(HCFD$D$$HT H d L.1E1HaD$D$$Hd H \ L) -E1H`D$D$$HH @ L1E1HUeHW)HDž fDžTƅ訾HHy(W)HDž@DH(,p)Htensor tHH(H to any HH Hut typesHHHand outpHHHn input HHHConstraiH@0ype.@4HHHHfH5( -H0"L -T HwH iA"H0H0HPHHA4H5 HR5H5 H#8Hf0H56 o HB6LH7HPH9t_HtHP(t HLMtSHL9t8HX@t Hx軾HI9uHHP uLL芾t H uH`H5HH;EuLH([A^A_]裾ILMu|IuS]IIIHPH9tHtHP(uHP t HĽLMtHHL9tgfffff.HX@t Hx苽HI9uHLpt H [H`L菺 LfUHAWAVSH(IH4HHEH`HH5/Q H>Y E1H;D$D$$HCP H f> L1E1H\D$D$$H`> H b> L1E1H@aHW)HDž fDžTƅ蓺HHd$W)HDž@/H()Hr types.HH-Htensor tHH(H to all HH Hut typesHHHand outpHHHn input HHHConstraiH@5HHHHnbH ="H0H0HPHHG0H5 2 -HX1H5 H)4Hl,H52 HH2LH=HPH9teHtHP(t HLMtYHL9t>fHX@t Hx軺HI9uHHP uLL芺t H uH`H1HH;EuLH([A^A_]裺IugqILMunIIIHPH9tHtHP(uHP t HĹLMtHHL9tgfffff.HX@t Hx苹HI9uHLpt H [H`L菶 LfUHAWAVSH(IH0HHEH`HH5/M HU AH7D$D$$H@L H j; L1E1HXD$D$$HH; H _: L1E1H=]HW)HDž fDžTƅ萶HHa W)HDž@,H()Hr types.HH-Htensor tHH(H to all HH Hut typesHHHand outpHHHn input HHHConstraiH@5HHHHk^H l:"H0H0HPHHD,H5> -HU-H5 H&0Hi(H5. HE.LH:HPH9tbHtHP(t HLMtVHL9t;fDHX@t Hx軶HI9uHHP uLL芶t H uH`H-HH;EuLH([A^A_]裶IugqILMunIIIHPH9tHtHP(uHP t HĵLMtHHL9tgfffff.HX@t Hx苵HI9uHLpt H [H`L菲 LfUHAWAVAUATSHIH,HHEHPH輥HDžH5Yb -HQ LH9D$D$$HWX H AR L1E1HTD$D$$H]S H \S L E1HzTD$D$$H H mT L̉ E1H>TD$D$$H>H RU L 1E1HXHW)HDžƅfDžT1ƅ1YHHL(W)HDž0薳H(.)Ic types.L`I numericLhI to onlyLpIns inputLxHConstraiH@'HHHHYHW)HDžƅfDžT2ƅMXHHW)HDž0蹲H(Q)L`LhLpLxIConstraiL0@'HHHH<YHW)`HDžpƅ`fDžaT3ƅchL(HHH2W)0HDž@ H@(%#)0Hor type.HHH tensor HHHn to anyHHL0@H`HHH0HpXH 4"H H H@HHI&H5 HZ'H5 H+* Hn"H5( HJ(LH?H@H9tgHtHP(0t H@LHMt[HPL9t@ff.HX@t Hx軰HI9uHHHP 0uLLP芰`uGuSLMtpHL9tUfHX@t HxKHI9uH2Hp.tHLMuLLuIuULMtrHL9tW@HX@t Hx軯HI9uH2H螯tH良LMuLLlt HWHP}H&HH;EuLH[A\A]A^A_]聯I0ILHM,I.LILMQIILMI`IBTIIIH@H9tHtHP(0uHP 0t H@LHMt?HPL9t$HX@t HxHI9uHHLLPȭ`uu#LMu/lHp蜭tH臭LMt?HL9t$HX@t Hx\HI9uHLL<uu#LMu/lHtHLMt?HL9t^DHX@t HxˬHI9uHL谬t H蛬HPLϩ LfUHAWAVSHIH#HHEH`HH5Y -HQN E1H*D$D$$H:H O L1E1H LD$D$$H[N H ^N L"E1HKD$D$$HͼH <O L1E1HDPHW)@HDžPfDž@TƅB藩H(HhW)HDž @3H ()Hr types.HH-Htensor tHH(H to all HH Hut typesHHHand outpHHHn input HHHConstraiH@5H@H(HHrQH5H"LpN HbH56 Ha H5 H2# HuH5! HQ!LHFt H L(MtHH0L9t-fHX@t Hx۩HI9uH(LL0軩@t HP覩H`H!HH;EuLH[A^A_]ԩIL(Mu9sI@upzIuIt H 8L(Mt<H0L9t[fHX@t Hx HI9uH(L0@t HPۨH`L LfUHAWAVSH(IH& HHEH`H@D$D$$HH " L{1E1HgHD$D$$H H ! 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H0[A^]M{@uHH?@uHH?1n1HH}Hu*1HH}Hu#HH}HuHH}Ht H}zHw ffff.UHH ŠH1H9NHD]DUHHm"]UH]f.UH]$zfDUHzH S"H]fDUHH="H]UH]f.UH]yfDUHAWAVATSH@HHWHHE1HQEH}1vLuHEHtHcM;} QUL|H}%LH0'IHHPHH1HPHH1HPf.H@H(u H@ @ueu`H@ @tVH1HPx(uH@ H@HtHZ9#H@HuH9#Lc`A(tLAG(Mg HMHtE;}EH}$LHH&1HNHuHH}YHHH;Eu H@[A\A^A_]xHH})Hgu ffffff.UHH UH1H9NHD]DUHH"]UH]f.UH]wfDUHwH s"H]fDUHH]"H]UH]f.UH]twfDUHAWAVSH(HHHHE11HYHHPHH1HPHH1HPH(t#ff.H@H(u H@ @uuzH@ @tpHHPHvaHHPHtNHHPH(t'ffffff.H@H(u H@ @uu +H@ @uHHH;EH([A^A_]H1HPx(uH@ H@HtH6#H@HuHk6#xHHPx(uH@ H@HtHg6#H@HuH'6#xH1HP(IH1HPH EH H;MuHLH([A^A_]ou(uHH5y H H}n>AHuHsHX"HHC HCHCE1H5#="HLH`un(uHH5x H H}fAHuHrH"HHC HCHCE1H5<"HܷHt I1I,IEu IEt H}ytEu +Lq HtLq f.UHH H1H9NHD]DUHHM"]UH]f.UH]tfDUHsH 3"H]fDUHH"H]UH]f.UH]sfDUHAWAVAUATSH8IH5HHE11LBUI1LPII1LP(HEILP IILmILP(IžL>A}(uMu .LAE(I}@WH$ IMu ANI^HLmt#HK HtAC;}:CLHsPI~@H1HI^HK HuHH;HHJ LHILP(IžL=A}(uMu .LAE(I}@HFIMu ANI^HLmt HK Ht>C;}7CIsMI~@HVHI^HK HuHH;HHoIILP(HþL"={(u)Ls ANI^HtRHK HtpC;}iCyHC(H{@HMILs ANI^HuI~@HHI^HK HuHH;HHIHW)EHEEEaxisEHuLHEt H}pHtDAM(IU BH] IM LyM!H]{(ufLs ANI^HHK HC;CHHH;E<Hm0#BH]v HC(H{@3HILs ANI^HqI~@H HI^HK HSHH;|HH!HHH;E]H /#LyMuL=y/#AW!8905AE16@uHH?@uHH?1|1@{(uJLs ANI^HtsHC HHcK;QSHDM9H]fHHC(H{@]HzILs ANI^HuI~@CHHI^HC HoHH;HHM9H]tIO JtHIIcGI9 HbHH;EH8[A\A]A^A_]@uTHH?@uXHH?@uMHH?@uBHH?@uFHH?11L@uCHH?<11w1@u*HH?#1@uHH?1Lm&1Lm1Lm4m(lIH5\p H H}qAHuL[jH"IIF IFIFE1H5w4"HLl HHEt H}MlEt$LplHi HEt H}$lHdi fff.UHH %H1H9NHD]DUHH"]UH]f.UH]kfDUHkH s"H]fDUHH]"H]UH]f.UH]tkfDUHAWAVAUATSHXHHHHE11HMHHPHH1HPHyH1HPH(u#fH@ @OH@H(t:H@ @,HHPHHHPHHHPH(u)ffffff.H@ @H@H(tH@ @H1HPx(H@ H@HuH~*#HELchHHPx(H@ LxMuL=J*#McwW)EHEEHbatch_diHEfEmsEHHuHHt +x1EtH}IiLE EIG J y(HQ HULmL9IA^IDHMAL}IG IN,H1HP(IA|$(uM|$ AOMgMu[?LAD$(I|$@H IM|$ AOMgMuI@uwH@IMgID$ HtIcL$;}QAT$H|II<$LH?HL}L蠦L9ud@uHH?d@uHH?{1K1mH(#H@HH(#LxMHELmA9<A)HL4BHE.@uHH?|@uHH?1f1HEH@ N<0H1HP(IA|$(L}uM|$ AOMgMu_?L+AD$(I|$@yHZIM|$ AOMgMuI@[HIMgID$ HtIcL$;}QAT$H|II<$LHHHuIAH<HH;EuHX[A\A]A^A_]f(fIH5j H$H};AHuLdHU}"IIF IFIFE1H5 ."HIL]fn(fIH5i H H};AHuLcH|"IIF IFIFE1H5-"H٨Le H'HEuHHEt H}veEt$LeHb HEt H}MeHb DUHH EH1H9NHD]DUHH="]UH]f.UH]dfDUHdH #"H]fDUHH "H]UH]f.UH]dfDUHAWAVAUATSHXHH%HHE11H2FHHPHt[H1HPHtKH1HPH(t'ffffff.H@H(u H@ @uu +H@ @u#HHH;EHX[A\A]A^A_]H1HPx(uH@ L`MtHG$#L`MuL%$#Mcl$HHPHtpx`SH}HVHEH+EHKL-H9H1HP(HÃ{(Ls ANIFH1HyHEIIf.HK HtC;}CIuI>LHIuHC(H{@GHILs ANIFHuI~@-HIFEHHHMN4E1HELefIL$ NdHp HtHcH;}QPH\A|$(t%QHEH8$H}HHA|$(u.HELN$La N$0{(tH<C(Lc HEJ J 0u HLIIM9LeHENH}HxH}vaHHH;Eoa@uHH?@uHH?11(9aIH5d HH}YAHuL^Hx"IIF IFIFE1H5("HL an(`IH5Cd HJ H}QAHuLB^Hw"IIF IFIFE1H5^("HL` H'HEuEuH}HukrH}$`EtLG`H}HuJQHHEt H}_Et5L`H(] HH}HuHH}Ht H}_H\ UHH H1H9NHD]DUHH-"]UH]f.UH]d_fDUH\_H "H]fDUHH"H]UH]f.UH]_fDUHAWAVSH(HHHHE11H@HHPHtOH1HPHt?H1HPH(tH@H(u H@ @uu +H@ @uH"HH;EH([A^A_]H1HPx(uH@ H@HtH#H@HuH#x~CH1HP(IH1HPH H H;MuHLH([A^A_]_XH^(]HH5pa H" H}vAHuHo[Ht"HHC HCHCE1H5%"HH] I&IEuEuLZ H}R]EtHu]LZ ffff.UHH H1H9NHD]DUHH-"]UHAVSHIHHHEH`HbH5 H AHaD$D$$HmH L 1E1HxD$D$$HmH L +1E1HH5 Hq"L H-H5I +H"L H H $"H0H0HPHHH5 +HH5ˈ H HH5 YHLHـHPH9t HtHP(HP H`oɀHHH;EuLH[A^][I"IHPH9uHP HtHP(H`ɀLFX fffff.UHAWAVSH(IHvHHEH`HPD$D$$H H , Lg1E1HD$D$$Hߪ +H  LhlE1HKD$D$$H H L6g1E1HHW)HDž fDžTƅ/HHW)HDž@YH(Y)Hr types.HH-Htensor tHH(H to all HH Hut typesHHHand outpHHHn input HHHConstraiH@5HHHHH Ѳ"H0H0HPHHH5` +HH5 H HH5 HLHրHPH9tgHtHP(t HXLMt[HL9t@ff.HX@t HxKXHI9uHHP uLLXt H XH` ƀHHH;EuLH([A^A_]3XIugqILMunIIIHPH9tHtHP(uHP t HTWLMtHHL9tgfffff.HX@t HxWHI9uHLWt H VH`ĀLT LfUHAWAVSH(IHVHHEH`H0}D$D$$H H Lc1E1HgD$D$$H +H LHhE1H+D$D$$H H Lc1E1HHW)HDž fDžTƅSHHW)HDž@UH(iU)Hr types.HH-Htensor tHH(H to all HH Hut typesHHHand outpHHHn input HHHConstraiH@5HHHHH 1"H0H0HPHHH5@ +HH5Ё HHH5 HLHҀHPH9tgHtHP(t HaTLMt[HL9t@ff.HX@t Hx+THI9uHHP uLLSt H SH`HtHH;EuLH([A^A_]TIugqILMunIIIHPH9tHtHP(uHP t H4SLMtHHL9tgfffff.HX@t HxRHI9uHLRt H RH`LO LfUHAWAVSH(IH6HHEH`HyD$D$$H| H Lk_1E1HGD$D$$H +H L~y 1E1HHW)HDž fDžTƅPHHW)HDž0QH(Q)Hry type.HHHrbitraryHHH be of aHHHnsor canHHHInput teH@&HHHHH5x H:"L H& H ǫ"H0H0HPHHH5i HH5} HHH5 HLH΀HPH9t]HtHP(t HwPLMtQHL9t6HX@t HxKPHI9uHHP uLLPt H PH` HHH;EuLH([A^A_]3PILMu|IuS]IIIHPH9tHtHP(uHP t HTOLMtHHL9tgfffff.HX@t HxOHI9uHLOt H NH`LL LfUHAWAVSH(IHVHHEH`H0uD$D$$H H L[1E1HgD$D$$H H T Lu 1E1HHW)HDž fDžTƅ1LHHW)HDž0MH(N)Hry type.HHHrbitraryHHH be of aHHHnsor canHHHInput teH@&HHHH(H5t Hb"L HFH g"H0H0HPHHH5 +HH5z HHH5+ HLHʀHPH9t]HtHP(t HLLMtQHL9t6HX@t HxkLHI9uHHP uLL:Lt H %LH`+HHH;EuLH([A^A_]SLILMu|IuS]IIIHPH9tHtHP(uHP t HtKLMtHHL9tgfffff.HX@t Hx;KHI9uHL Kt H KH`L?H LfUHAWAVSH(IHvHHEH`HPqH5& +H4 AHOD$D$$H H LW1AHcD$D$$Hx H  LNW1E1HHW)HDž fDžTƅ-HHHW)HDž0IH(1)Hnsor typHH Ho any teHHH types tHHHn outputHHHConstraiHf@(e.@*HHHHH "H0H0HPHHH5} +HH5v H HH5C HLHƀHPH9teHtHP(t HHLMtYHL9t>fHX@t Hx{HHI9uHHP uLLJHt H 5HH`;HĬHH;EuLH([A^A_]cHIugqILMunIIIHPH9tHtHP(uHP t HGLMtHHL9tgfffff.HX@t HxKGHI9uHL0Gt H GH`!LOD LfUHAWAVSH(IHHHEH`H`mD$D$$HWH LS1E1HD$D$$Hѕ H ۿ LS1AH HW)HDž fDžTƅ^DHHW)HDž@ +FH(E)Hr types.HH-Htensor tHH(H to all HH Hut typesHHHand outpHHHn input HHHConstraiH@5HHHH9HDžH5 +H LH,H5 +H^ E1HH O"H0H0HPHHǹH5ɵ +HغH5q H詽 HH5 HȻLH€HPH9teHtHP(t HDLMtYHL9t>fHX@t HxKDHI9uHHP uLLDt H DH` HHH;EuLH([A^A_]3DIuuILMu|IuS]IIIHPH9tHtHP(uHP t HFCLMt:HL9tYHX@t HxCHI9uHLCt H BH`L@ LfUHAWAVSH(IHVHHEH`H0iD$D$$H H LO1E1HgD$D$$H +H LZ +E1H+D$D$$H H d L +E1HD$D$$H H q L +AHD$D$$Hټ H ؼ L +AHqD$D$$HRH X L\N1E1HHW)HDž fDžTƅ;?HHއW)HDž@@H(@)Hr types.HH-Htensor tHH(H to all HH Hut typesHHHand outpHHHn input HHHConstraiH@5HHHHH5^ +HX"LQ H4H ՜"H0H0HPHHʹH5 +H޵H5l H诸 HH5 HζLH賽HPH9tkHtHP(t H?LMt_HL9tDffffff.HX@t HxK?HI9uHHP uLL?t H ?H` HHH;EuLH([A^A_]3?ILMutIuKUIIHPH9tHtHP(uHP t H\>LMt@HL9tKfDHX@t Hx+>HI9uHL>tH =LIH`L%; ffff.UHAWAVSH(IHVHHEH`H0dH5k Hi E1H2D$D$$H~ H LmJ1E1HID$D$$Ht H x L4J1E1HHW)HDž fDžTƅ;HHڇW)HDž@<H(<)Hr types.HH-Htensor tHH(H to all HH Hut typesHHHand outpHHHn input HHHConstraiH@5HHHHH O"H0H0HPHHǰH5 +HرH5h H詴HH5 HȲLH譹HPH9teHtHP(t H;LMtYHL9t>fHX@t HxK;HI9uHHP uLL;t H ;H` HHH;EuLH([A^A_]3;IugqILMunIIIHPH9tHtHP(uHP t HT:LMtHHL9tgfffff.HX@t Hx:HI9uHL:t H 9H`L7 LfUHAWAVSH(IHVHHEH`H0`D$D$$H H LF1E1HgD$D$$H H LHKE1H+D$D$$Ht H u LFE1HD$D$$HIH LE1E1HfHW)HDž fDžTƅ6HHzևW)HDž@e8H( )Htensor tHH(H to any HH Hut typesHHHand outpHHHn input HHHConstraiH@0ype.@4HHHHH |"H0H0HPHHtH5_ +H腭H5d HV H虨H5 HuLHZHPH9tbHtHP(t H,7LMtVHL9t;fDHX@t Hx6HI9uHHP uLL6t H 6H`軤HDHH;EuLH([A^A_]6IugqILMunIIIHPH9tHtHP(uHP t H6LMtHHL9tgfffff.HX@t Hx5HI9uHL5t H 5H`衣L2 LfUHAWAVSH(IHHHEH`H[HDž(H5 +HԱ L(HD$D$$H H ( LB1E1HD$D$$H H Lݝ +E1HD$D$$H H x LAE1HrD$D$$HEH r L]A1E1HHW)HDž fDžTƅ<2HHчW)HDž@3H(y)Hsor typeHH(H any tenHH Han be ofHHH types cHHHd outputHHHInput anHf@0.HHHH#H5k +Hu"L^ HAH b"H0H0HPHHڧH5 +HH5` H輫 HH5& rH۩LHHPH9thHtHP(t H2LMt\HL9tAfff.HX@t Hx[2HI9uHHP uLL*2t H 2H`HHH;EuLH([A^A_]C2ILMu|IuS]IIIHPH9tHtHP(uHP t Hd1LMtHHL9tgfffff.HX@t Hx+1HI9uHL1t H 0H`L/. LfUHAWAVSH(IHfHHEH`H@WHDž(H5 +H L(HsD$D$$H H Ln=1E1HJD$D$$Hm H L= +E1HD$D$$HAH z L<1E1HHW)HDž fDžTƅ-HH͇W)HDž@/H(,)Htensor tHH(H to any HH Hut typesHHHand outpHHHn input HHHConstraiH@0ype.@4HHHHH5 +H"L HH y"H0H0HPHHqH5If +H肤H5[ HS H薟H5 HrLHWHPH9t_HtHP(t H).LMtSHL9t8HX@t Hx-HI9uHHP uLL-t H -H`軛HDHH;EuLH([A^A_]-ILMu|IuS]IIIHPH9tHtHP(uHP t H-LMtHHL9tgfffff.HX@t Hx,HI9uHL,t H ,H`衚L) LfUHAWAVSH(IHHHEH`HRHDž(H5 +H L(HD$D$$H H ( L91E1HD$D$$H H r Lݔ +E1HD$D$$H<H  L81E1H%HW)HDž fDžTƅx)HH9ɇW)HDž@$+H()Htensor tHH(H to any HH Hut typesHHHand outpHHHn input HHHConstraiH@0ype.@4HHHHZH5 +H̀"L HxH "H0H0HPHHH5Dc +H"H58W H H6H5] KHLHHPH9t_HtHP(t H)LMtSHL9t8HX@t Hx)HI9uHHP uLLj)t H U)H`[HHH;EuLH([A^A_])ILMu|IuS]IIIHPH9tHtHP(uHP t H(LMtHHL9tgfffff.HX@t Hxk(HI9uHLP(t H ;(H`ALo% LfUHAWAVSH(IHHHEH`HNH5 H E1H肦D$D$$Hκ H L41E1HD$D$$H H L41E1HHW)HDž fDžTƅc%HH$ŇW)HDž@'H(&)Hr types.HH-Htensor tHH(H to all HH Hut typesHHHand outpHHHn input HHHConstraiH@5HHHH>H "H0H0HPHHH5 +H(H5>S H H<H5c HLHHPH9teHtHP(t H%LMtYHL9t>fHX@t Hx%HI9uHHP uLLj%t H U%H`[HHH;EuLH([A^A_]%IugqILMunIIIHPH9tHtHP(uHP t H$LMtHHL9tgfffff.HX@t Hxk$HI9uHLP$t H ;$H`ALo! LfUHAWAVSH(IHHHEH`HJH5 H AHD$D$$H˶ H L01E1HD$D$$Hӥ H L01E1H HW)HDž fDžTƅ`!HH!W)HDž@ #H(")Hr types.HH-Htensor tHH(H to all HH Hut typesHHHand outpHHHn input HHHConstraiH@5HHHH;H "H0H0HPHHH5 +H%H5;O H H9H5` HLHHPH9tbHtHP(t H!LMtVHL9t;fDHX@t Hx!HI9uHHP uLLj!t H U!H`[HHH;EuLH([A^A_]!IugqILMunIIIHPH9tHtHP(uHP t H LMtHHL9tgfffff.HX@t Hxk HI9uHLP t H ; H`ALo LfUHAWAVSH(IHHHEH`HFH5 +HF AHD$D$$H0H : L,1E1H薿D$D$$H0H v L,1E1H HW)HDž fDžTƅ`HH!W)HDž@ H()Hr types.HH-Htensor tHH(H to all HH Hut typesHHHand outpHHHn input HHHConstraiH@5HHHH;H "H0H0HPHHH5 +H%H5;K HH9H5` /HLHHPH9tbHtHP(t HLMtVHL9t;fDHX@t HxHI9uHHP uLLjt H UH`[HHH;EuLH([A^A_]IugqILMunIIIHPH9tHtHP(uHP t HLMtHHL9tgfffff.HX@t HxkHI9uHLPt H ;H`ALo LfUHAWAVSHHIHHHEH`HBH5 +HF AHW)HDž ƅDžDCRH5 H LHD$D$$H,H Lr(1E1HND$D$$H^,H ֞ L9(1E1HſHW)HDžfDžTƅHHٸW)HDž@H()Hr types.HH-Htensor tHH(H to all HH Hut typesHHHand outpHHHn input HHHConstraiH@5HHHHH T{"H0H0HPHH̎H5{ +HݏH5F H讒 HH5 H͐LH貗HPH9tjHtHP(t HLMt^HL9tCfffff.HX@t HxKHI9uHHP uLLt Ht H H`H}HH;EuLHH[A^A_]IILMIIIIHPH9tHtHP(uHP t HLMtCHL9twfHX@t HxHI9uHLt Ht H H`謅L Lffff.UHAWAVSH(IH|HHEH`H=D$D$$HX(H ' L;$1E1HD$D$$H H  LN> E1H۶D$D$$H'H S L#1E1HRHW)HDž fDžTƅHHfW)HDž@QH()Hr types.HH-Htensor tHH(H to all HH Hut typesHHHand outpHHHn input HHHConstraiH@5HHHH耼H5 = Hl"L HH ?w"H0H0HPHH7H5 +HHH5^B HH\H5 H8LHHPH9teHtHP(t HLMtYHL9t>fHX@t HxHI9uHHP uLLt H uH`{HyHH;EuLH([A^A_]ILMu|IuS]IIIHPH9tHtHP(uHP t HLMtHHL9tgfffff.HX@t HxHI9uHLpt H [H`aL LfUHAWAVSHIHwHHEH`H9W)ƅHDž HnearestHH5Q H LH1Dž @H5{h +HN L H%HDžH5\h +H. LHXW)ƅHDžHhalf_pixHfDželƅH5"g +Hɷ LHyW)ƅ$HDžHefer_floHHround_prHfDžorƅH5_g +H LH DžH5rf +H LHD$D$$Hs"H L8 1E1H4D$D$$Hd H a L;A +E1HD$D$$He +H  L#E1H輰D$D$$Hc H b L"AH}D$D$$H!H ĝ L7 1E1HHW)HDžƅfDžT1ƅ@HHW)pHDž@H(9)pHr types.HH/Hl tensorHH(HY' to alHH Houtput 'HHH'X' and HHHn input HHHConstraiH@7HHHpHH5w? +He"L H9H Zq"H0H0HPHH҃H5b +HH5; H贇 HH5 @HӅLH踌HPH9t`HtHP(pt HLMtTHL9t9@HX@t Hx[HI9uHHP puLL*uTu`ult H H`|HrHH;EuRLHĘ[A^A_]H tH tH u ILMI!xIxI IIIpuKUIIHPH9tHtHP(puHP pt H LMtGHL9fHX@t Hxk HI9uHLP u=u\uht H H`&zLT  H tLItH tH uUHAWAVSH(IH6pHHEH`H2D$D$$HH Z Lk1E1HGD$D$$HWH Ϙ L21E1H辯HW)HDž fDžTƅHHҨW)HDž@ +H( +)Hr types.HH-Htensor tHH(H to all HH Hut typesHHHand outpHHHn input HHHConstraiH@5HHHHH %!H0H H8H0HPHH~H5G +HH56 H虂 HzH5 ]H踀LH蝇HPH9teHtHP(t Ho LMtYHL9t>fHX@t Hx; HI9uHHP uLL + t H H`vHmHH;EuLH([A^A_]# IugqILMunIIIHPH9tHtHP(uHP t HDLMtHHL9tgfffff.HX@t Hx HI9uHLt H H`uL LfUHAWAVSH(IHFlHHEH`H .D$D$$HH j L{1E1HWD$D$$HgH ߔ LB1E1HΫHW)HDž fDžTƅ!HH⤇W)HDž@H()Hr types.HH-Htensor tHH(H to all HH Hut typesHHHand outpHHHn input HHHConstraiH@5HHHHH 5!H0H 'H8H0HPHHzH5C +H{H52 H~HvH5} jH|LH譃HPH9teHtHP(t HLMtYHL9t>fHX@t HxKHI9uHHP uLLt H H` sHiHH;EuLH([A^A_]3IugqILMunIIIHPH9tHtHP(uHP t HTLMtHHL9tgfffff.HX@t HxHI9uHLt H H`qL LfUHAVSHIHXhHHEH`H2*D$D$$HH L* 1E1HiD$D$$HwH rLp3 +1E1HH5* HY"L HH5:3 +HY"L HH e"H0H0HPHHwH5B +HxH5/ Hw{ HsH5y HyLH{HPH9t HtHP(HP H``pHfHH;EuLH[A^]I"IHPH9uHP HtHP(H` pL7 ffffff.UHAWAVSH(IHffHHEH`H@(D$D$$HH L1E1HwD$D$$HH LX1E1HHW)HDž fDžTƅAHHW)HDž H(U:)Hr types.HHH tensor HHHn to allHHHConstraiH@HHHHFH c"H0H0HPHHuH5@ +H0vH5F- Hy HDqH5kw H wLH~HPH9t]HtHP(t HLMtQHL9t6HX@t HxHI9uHHP uLLzt H eH`kmHcHH;EuLH([A^A_]IugqILMunIIIHPH9tHtHP(uHP t HLMtHHL9tgfffff.HX@t Hx{HI9uHL`t H KH`QlL LfUHAWAVSH(IHbHHEH`H$HDž(H5; +H L(HÂD$D$$Hϐ H ؠ L +1E1H蚝D$D$$H H L{E1H^D$D$$HnH y LI +1E1HաHW)HDž fDžTƅ(HH隇W)HDž@H(|)Htensor tHH(H to any HH Hut typesHHHand outpHHHn input HHHConstraiH@0ype.@4HHHH +H _"H0H0HPHHpH5j8 +HqH5 +) Ht HmH5/s MHrLHyHPH9taHtHP(t HLMtUHL9t:DHX@t HxkHI9uHHP uLL:t H %H`+iH_HH;EuLH([A^A_]SIugqILMunIIIHPH9tHtHP(uHP t HtLMtHHL9tgfffff.HX@t Hx;HI9uHL t H H`hL? LfUHAWAVSHHIHv^HHEH`HP W)ƅHDž HconstantHƅH5 H LHډD$D$$Hf H LU1E1H1D$D$$HK H g L E1HD$D$$H H LAH趘D$D$$H H L1E1H-HW)HDžfDžTƅ谝HHAW)HDž@,H(`)Hric typeHH(Hnly numeHH Hput to oHHH and outHHHns inputHHHConstraiHf@0s.@2HHHHcH ["H0H0HPHH<lH5; +HMmH5c$ Hp HahH5n H=nLH"uHPH9tjHtHP(t HLMt^HL9tCfffff.HX@t HxHI9uHHP uLLt Hut H `H`fdHZHH;EuLHH[A^A_]Iut~ILMu{IIIHPH9tHtHP(uHP t HLMtFHL9tzfff.HX@t HxkHI9uHLPt H;t H &H`,cLZ Lffff.UHAVSHIHYHHEH`HbH5j Hj AHasD$D$$HH j L 1E1HxD$D$$HH j L$ +1E1HH5 HJ"L H-H5I$ +HK"L܅ H H5*$ +HiH5 HlHdH5k ! HjLHqH`aH>XHH;EuLHİ[A^]HH`aH UHAVSHIHWHHEH`HH5i Hi AHqD$D$$HH Ri LH 1E1HؒD$D$$HH 2i L" +1E1HOH5 HI"L H荪H5" +H/J"L< HkH W"H0H0HPHHgH5c" +HhH5+ HjH)cH5Pi _ HiLHoHPH9t HtHP(HP H`_HXVHH;EuLH[A^]I"IHPH9uHP HtHP(H`x_L fffff.UHAVSHIHUHHEH`HH5 +H2 E1HoD$D$$Hi H i L1AHȐD$D$$Hi H i L1E1H?H5HH"LƂ H}H5d$ +HNfH5d HiHbaH5g x H>gLH#nH`'^HTHH;EuLHİ[A^]QHH`]H" f.UHAWAVSH(IHVTHHEH`H0H5 +H AH/nD$D$$Hkh H kh Lj1AHCD$D$$HXh H _h L.1E1H躓HW)HDž fDžTƅ HHΌW)HDž0H()Hnsor typHH Ho any teHHH types tHHHn outputHHHConstraiHf@(e.@*HHHHH _S"H0H0HPHHbH5! +HcH5 HfH^H5#e HdLHkHPH9teHtHP(t HLMtYHL9t>fHX@t Hx[HI9uHHP uLL*t H H`QHH;EuLH([A^A_]CIugqILMunIIIHPH9tHtHP(uHP t HdLMtHHL9tgfffff.HX@t Hx+HI9uHLt H H`ZL/ LfUHAVSHIHhPHHEH`HBD$D$$HH d L1E1HyD$D$$H^ +H } LdAH:D$D$$H} H ~d L%1AH讏H5H(C"Lx HH5B +H} E1HniH5y] +H} E1HPiH5r[ +H`H5 HRcH[H5a HqaLHVhH`ZXHNHH;EuLHİ[A^]HH`'XHU ffff.UHAVSHIHNHHEH`HbH5| H| AHahW)@ƅ@HDžPHconstantHAƅIH5 H} L@HyDž<H50 +H~ L<HsD$D$$H+| H m L1E1HD$D$$HH Ē L1E1HmH5H@"Lo H諠H5, +H|^H5 HMaHYH5_  +Hl_LHQf@t HP:H`@VHLHH;EuLH[A^]jH@uHH@t HPH`UH ff.UHAVSHIHHLHHEH`H"H58 +H{| E1H$fH5,w H5w E1HfD$D$$HRz H ^ LA1E1HD$D$$H^ H ^ L1E1H蔋H5H>?"L%n HҞH5)7 +H\H5 Ht_HWH5] 9 +H]LHxdH`|THKHH;EuLHİ[A^]HH`ITHw ffffff.UHAVSHIHJHHEH`H D$D$$HH i L1E1H蹅D$D$$Hz H z LE1H}D$D$$H̒ +H z LhE1HAD$D$$HQH vz L,1E1H踉H5Hz="Lr HH5B Hp="LZz HԜH uJ"H0H0HPHHmYH5] +H~ZH5 HO]HUH5[ p +Hn[LHSbHPH9t HtHP(HP H`8RHHHH;EuLH[A^]bIHPH9uHP Ht HP(IH`QL UHAVSHIHHHHHEH`H" +HXH59y H>y AHbH5py Hvy AHaW)@ƅ@HDžPHnearestHAH5 Huy L@HdsD$D$$HH py L1E1H軂D$D$$HH My L1E1H2H5H;"LIy HpH5k +HAXH5W H[HUSH5|Y +H1YLH`@t HPH`PHFHH;EuLH[A^]/HH@t HPH`OH fffff.UHAWAVSHHIHFHHEH`HH5 6 +H|x AH_W)ƅHDž HnearestHH5 Hx LH`qD$D$$HH k L1E1H跀D$D$$HH m L1E1H.HW)HDžfDžTƅHHB~W)HDž@-H()Hr types.HH-Htensor tHH(H to all HH Hut typesHHHand outpHHHn input HHHConstraiH@5HHHH\H E"H0H0HPHH5TH5h +HFUH5\ HXHZPH5V +H6VLH]HPH9tcHtHP(t HLMtWHL9t<HX@t HxHI9uHHP uLLt Hut H `H`fLHBHH;EuLHH[A^A_]IILMIIIIHPH9tHtHP(uHP t HLMtCHL9twfHX@t Hx[HI9uHL@t H+t H H`KLJ Lffff.UHAWAVSHHIHvAHHEH`HPW)ƅHDž HnearestHH5 HPt LHlD$D$$HwH f L\1E1H8|D$D$$H0 +H =s LHE1H{D$D$$H +H Ci L1E1HsHW)HDžfDžTƅHHyW)HDž@rH(Z)Hr types.HH/Hl tensorHH(HY' to alHH Houtput 'HHH'X' and HHHn input HHHConstraiH@7HHHH衁H A"H0H0HPHHzOH5;d +HPH5 H\S HKH5Q +H{QLH`XHPH9thHtHP(t H2LMt\HL9tAfff.HX@t HxHI9uHHP uLLt Ht H H`GH/>HH;EuLHH[A^A_]Iut~ILMu{IIIHPH9tHtHP(uHP t HLMtFHL9tzfff.HX@t HxHI9uHLt H{t H fH`lFL Lffff.UHAWAVSHHIH<HHEH`HW)ƅHDž HnearestHH5Q~ Ho LH1hD$D$$HH a L1E1HwD$D$$H, +H o LE1HLwD$D$$HZH d L71E1H{HW)HDžfDžTƅHHtW)HDž@H()Hr types.HH/Hl tensorHH(HY' to alHH Houtput 'HHH'X' and HHHn input HHHConstraiH@7HHHH|H R="H0H0HPHHJH5) +HKH5 HN +HFH5M  HLLHSHPH9thHtHP(t HLMt\HL9tAfff.HX@t HxKHI9uHHP uLLt Ht H H`BH9HH;EuLHH[A^A_]Iut~ILMu{IIIHPH9tHtHP(uHP t H2LMtFHL9tzfff.HX@t HxHI9uHLt Ht H H`AL Lffff.UHAWAVSH(IH8HHEH`HD$D$$H\f H Zf LK1E1H'sH5f Hl E1HQH5= +Hvl AHQH5ff Hl AHwQD$D$$HH f L1E1H>wHW)HDž fDžTƅHHRpW)HDž@=H()Hr types.HH-Htensor tHH(H to all HH Hut typesHHHand outpHHHn input HHHConstraiH@5HHHHlxH M9"H0H0HPHHEFH5: +HVGH5l H'JHjBH5H HFHLH+OHPH9tcHtHP(t HLMtWHL9t<HX@t HxHI9uHHP uLLt H H`>H5HH;EuLH([A^A_]IugqILMunIIIHPH9tHtHP(uHP t HLMtHHL9tgfffff.HX@t HxHI9uHLt H kH`q=L LfUHAWAVSH(IH3HHEH`HD$D$$Hb H b L 1E1HnD$D$$H9 +H b L7 +E1HnD$D$$Hb H H L7 +E1HonD$D$$H"b H b Lb7 +AH0nD$D$$HYI H g L#7 +AHmD$D$$HH a L1E1HhrHW)HDž fDžTƅHH|kW)HDž@gH(/)Hr types.HH-Htensor tHH(H to all HH Hut typesHHHand outpHHHn input HHHConstraiH@5HHHHsH55 +H%"L` H贄H 4"H0H0HPHHMAH55 +H^BH5t H/E +Hr=H5C HNCLH3JHPH9tkHtHP(t HLMt_HL9tDffffff.HX@t HxHI9uHHP uLLt H H`9H0HH;EuLH([A^A_]ILMutIuKUIIHPH9tHtHP(uHP t HLMt@HL9tKfDHX@t HxHI9uHLtH {LIH`w8L ffff.UHAWAVSH(IH.HHEH`HHDž(H5{w +H6d L(HND$D$$H\ H l L1E1HiD$D$$Hl H 2d L2 +E1H~iD$D$$HE H HG LiE1HBiD$D$$HRH BG L-1E1HmHW)HDž fDžTƅ HHfW)HDž@H(P)Hsor typeHH(H any tenHH Han be ofHHH types cHHHd outputHHHInput anHf@0.HHHHnH5;1 +H "L.\ HH 0"H0H0HPHH<H5q, +H=H5 H@ H8H5> H>LHEHPH9thHtHP(t HbLMt\HL9tAfff.HX@t Hx+HI9uHHP uLLt H H`4Ht+HH;EuLH([A^A_]ILMu|IuS]IIIHPH9tHtHP(uHP t H4LMtHHL9tgfffff.HX@t HxHI9uHLt H H`3L LfUHAWAVSH(IH6*HHEH`HH55 +HG AHDD$D$$HgH G LJ1E1H&eD$D$$H6H H L1E1HiHW)HDž fDžTƅHHbW)HDž@H(d)Hr types.HH-Htensor tHH(H to all HH Hut typesHHHand outpHHHn input HHHConstraiH@5HHHHjH ,-"H0H0HPHH8H5S1 +H9H5 H<H4H5: H:LHAHPH9tbHtHP(t H\LMtVHL9t;fDHX@t Hx+HI9uHHP uLLt H H`0Ht'HH;EuLH([A^A_]IugqILMunIIIHPH9tHtHP(uHP t H4LMtHHL9tgfffff.HX@t HxHI9uHLt H H`/L LfUHAWAVSH(IH6&HHEH`HHDž(H5n +HC\ L(HCFD$D$$HOT H Xd L>1E1HaD$D$$H=d H >\ L * +E1H`D$D$$HH J@ L1E1HUeHW)HDž fDžTƅ訾HHi^W)HDž@TH(j)Htensor tHH(H to any HH Hut typesHHHand outpHHHn input HHHConstraiH@0ype.@4HHHHfH5( +H"LS HwH I)"H0H0HPHHA4H5 HR5H5h H#8Hf0H56 o HB6LH'=HPH9t_HtHP(t HLMtSHL9t8HX@t Hx˾HI9uHHP uLL蚾t H 腾H`,H#HH;EuLH([A^A_]賾ILMu|IuS]IIIHPH9tHtHP(uHP t HԽLMtHHL9tgfffff.HX@t Hx蛽HI9uHL耽t H kH`q+L蟺 LfUHAWAVSH(IH!HHEH`HH5P HX E1H;D$D$$HO H !> L1E1H\D$D$$H> H > L1E1H@aHW)HDž fDžTƅ蓺HHTZW)HDž@?H()Hr types.HH-Htensor tHH(H to all HH Hut typesHHHand outpHHHn input HHHConstraiH@5HHHHnbH %"H0H0HPHHG0H5'2 +HX1H5n H)4Hl,H52 HH2LH-9HPH9teHtHP(t HLMtYHL9t>fHX@t Hx˺HI9uHHP uLL蚺t H 腺H`(HHH;EuLH([A^A_]賺IugqILMunIIIHPH9tHtHP(uHP t HԹLMtHHL9tgfffff.HX@t Hx蛹HI9uHL耹t H kH`q'L蟶 LfUHAWAVSH(IHHHEH`H߀H5L H<U AH7D$D$$HK H %; L1E1HXD$D$$H; H : L1E1H=]HW)HDž fDžTƅ萶HHQVW)HDž@<H()Hr types.HH-Htensor tHH(H to all HH Hut typesHHHand outpHHHn input HHHConstraiH@5HHHHk^H L""H0H0HPHHD,H5> +HU-H5k H&0Hi(H5. HE.LH*5HPH9tbHtHP(t HLMtVHL9t;fDHX@t Hx˶HI9uHHP uLL蚶t H 腶H`$HHH;EuLH([A^A_]賶IugqILMunIIIHPH9tHtHP(uHP t HԵLMtHHL9tgfffff.HX@t Hx蛵HI9uHL耵t H kH`q#L蟲 LfUHAWAVAUATSHIHHHEHPHۀHDžH5wb +HsQ LH9D$D$$HX H Q L&1E1HTD$D$$HS H S L E1HzTD$D$$H H (T L E1H>TD$D$$HNH U L 1E1HXHW)HDžƅfDžT1ƅ1YHHQL(W)HDž0観H()Ic types.L`I numericLhI to onlyLpIns inputLxHConstraiH@'HHHHYHW)HDžƅfDžT2ƅMXHHPW)HDž0ɲH(!)L`LhLpLxIConstraiL0@'HHHH<YHW)`HDžpƅ`fDžaT3ƅchL(HHH"PW)0HDž@ H@()0Hor type.HHH tensor HHHn to anyHHL0@H`HHH0HpXH "H H H@HHI&H5 HZ'H5p H+* Hn"H5( HJ(LH//H@H9tgHtHP(0t H@LHMt[HPL9t@ff.HX@t Hx˰HI9uHHHP 0uLLP蚰`uGuSLMtpHL9tUfHX@t Hx[HI9uH2Hp>tH)LMuLL uIuULMtrHL9tW@HX@t Hx˯HI9uH2H讯tH虯LMuLL|t HgHPmHHH;EuLH[A\A]A^A_]葯I0ILHM,I.LILMQIILMI`IBTIIIH@H9tHtHP(0uHP 0t H@#LHMt?HPL9t$HX@t HxHI9uHHLLPح`uu#LMu/lHp謭tH藭LMt?HL9t$HX@t HxlHI9uHLLLuu#LMu/lH tH LMt?HL9t^DHX@t Hx۬HI9uHLt H諬HPLߩ LfUHAWAVSHIHHHEH`HҀH5Y +H N E1H*D$D$$HJH GO L-1E1H LD$D$$HN H N L@E1HKD$D$$HݼH N L1E1HDPHW)@HDžPfDž@TƅB藩H(HXIW)HDž @CH ( )Hr types.HH-Htensor tHH(H to all HH Hut typesHHHand outpHHHn input HHHConstraiH@5H@H(HHrQH5H"L+N HbH5T Ha H5w H2# HuH5! HQ!LH6(t H L(MtHH0L9t-fHX@t HxHI9uH(LL0˩@t HP趩H`HEHH;EuLH[A^A_]IL(Mu9sI@upzIuIt H HL(Mt<H0L9t[fHX@t HxHI9uH(L0@t HPH`L LfUHAWAVSH(IHV HHEH`H0πD$D$$HH ! L1E1HgHD$D$$H H ! LR1AHLHW)HDž fDžTƅ.HHEW)HDž@ڧH()Hr types.HH-Htensor tHH(H to all HH Hut typesHHHand outpHHHn input HHHConstraiH@5HHHH NHDžH5T +HJ LH+H5 +H9 E1H%H "H0H0HPHHH5 +HH5 HyHH5 $HLH}$HPH9teHtHP(t HOLMtYHL9t>fHX@t HxHI9uHHP uLLt H եH`Hd +HH;EuLH([A^A_]IuuILMu|IuS]IIIHPH9tHtHP(uHP t HLMt:HL9tYHX@t HxHI9uHLФt H 軤H`L LfUHAVSHIH( HHEH`HˀH5; H:H AH#W)ƅHDž HconstantHƅH5J H8 LHk4Dž H54 HbI L H_.D$D$$H6 H K L1E1HCD$D$$HH dM L1E1H HH5mHW!L* HK[H l"H0H0HPHHH5@ HH5 HH H50 HLH HPH9tKHtHP(t H 蜢H`H+HH;Eu LH[A^]HP u転IuISINIu6@IHPH9uHP u HtHP(t H H`L. fDUHAWAVSH(IHfHHEH`H@ȀD$D$$H4 H D L1E1HwAD$D$$HD H / LXE1H;AD$D$$HKH  L&1E1HEHW)HDž fDžTƅHH>W)HDž@豠H(YK)Htensor tHH(H to any HH Hut typesHHHand outpHHHn input HHHConstraiH@0ype.@4HHHHFH "H0H0HPHHH5G HH5 H HH5  HLHHPH9t^HtHP(t HxLMtRHL9t7fHX@t HxKHI9uHHP uLLt H H` HHH;EuLH([A^A_]3IugqILMunIIIHPH9tHtHP(uHP t HTLMtHHL9tgfffff.HX@t HxHI9uHLt H H` L LfUH]f.UH]鴝fDUH謝H !H]fDUHH!H]UH]f.UH]dfDUHAVSH HHHEHW)EHEEfEtoEHu11HEt H}HHPHtuH1HPHteH1HPH(tDH@H(u H@ @u3u.H@ @t$H1HP(IH1HPHLHHH;Eu H [A^]ŜHEt H}SH蓙 ff.UHH H1H9NHD]DUHH!]UHAWAVATSH AIIHHHHEHHxDD0(ěIH5 H[ LLG H}LzHuL4H!IIF IFIF1H5Qc!HzL莛&EHHH;EuHLDH [A\A^A_]fc(IH5ԡ H.[ LjF H}LHuL聘Hұ!IIF IFIF1H5b!HLۚv(虚IH5\ HE LE H}LHuL HZ!IIF IFIF1H5&b!HOLc I@I;I6IEuIEu IEt H}ܙu +L LL fffff.UHAWAVAUATSHXLIHHHHHHEH0L-Mu@LLH,HH@H0HfHnfLƘHEEIEHHIhL0LLLʗL=/ILHDž HDžHDžHDžDž(LHLHHALHHHHHAA$It$IEt$IET$HoAHH謚HHHNALHGHHL0HHLt H辗H螖H5HH{H0AH*HH;EuLHX[A\A]A^A_]ŗHSHeHHHL0HHLt HHH5 HH֕H0蜖H* fUHAWAVAUATSHXLIHHHHJHHEH0L-Mu@LLH\HH@H0HfHnfLHEEIEHHIhL0LLLL=_ILHDž HDžHDžHDžDž(LHKLHH>LHH'HHH>A$It$IEt$IET$H>HHܗHHH~>LHODHHL0HHLt HHΓH5HH諓H0qHZHH;EuLHX[A\A]A^A_]HSHeHHHL0HHLt HIH)H5PHHH0̓HZ fUHAWAVAUATSHXLIHHHHzHHEH0L-%Mu@LLHHH@H0HfHnfL&HEEIEHHIhL0LLL*L=ILHDž HDžHDžHDžDž(LH{LHH!<LHHWHHH;A$It$IEt$IET$H;HH HHH;LHAHHL0HHLt HHH5%HHېH0衑HHH;EuLHX[A\A]A^A_]%HSHeHHHL0HHLt HyHYH5HH6H0H芎 fUH]f.UH]$fDUHH !H]fDUHH!H]UH]f.UH]ԐfDUHAWAVAUATSHIHRHHE11L_rILPHW)EHE@uHPpHc@hH H}1 ϰ4HHu +HHAHIHHH}1ΰI1LP(HÃ{(uLc -HC(H{@H=ILc AL$ID$HpHu$I|$@bH@<HpID$I1LPx(uH@ HP"HXLuLeW)EHEM)tmMMII]HH<HHHEH]LmMIJ4HH%I?t@D)HHHJ!IE>LpID$HPE1Hh1H`HY A}(umI} LpHIUHHLAE(ILuI] HhHHhIM!&LpLLpAE(I} Hwm"IE HIUxu HHk1dfID$ HIcL$;QAT$LlKHHEMIADIN $HXAHIHcQI9IHI JLQ(HY A}(N4HPH;Q9HH:ILuKHWHuH`L`tfKfDHA}(uK/f.Lp2L/AE(JHEI] HhHHhILuHEL)HHI9L`MHXHh@H@HcHH~\HcULEHx 1fHt~(uHF HH9|+fDH9}PHHI4Hs?HH9|HHhHHA~(tL'AF(I^ H}Ht蛋H}Ht H}艋H$HH;EuDHĈ[A\A]A^A_]@uHH?l@uHH?1S1萋D(;IHH]H5 H)7 HxHAHxL裈H!IIF IFIFE1H5R!HL(跊IH51 Hf6 HxdAHxL*H{!IIF IFIFE1H5FR!HoL胊(AIH5 H!6 HxAHxL贇H!IIF IFIFE1H5Q!HL  H} (IH5: H5 Hx-+AHxL3H!IIF IFIFE1H5OQ!HxL茉눿(JIH5Č H|5 HxaAHxL轆H!IIF IFIFE1H5P!HL0HxuCJ Hxu3:Hxu#*H(HxuHxt H}iEtL茈H}HtH}HH}HHt HH}HtvHH}HtzHH}HtlHH}Ht^HH}HtPHH}HtBHH}Ht"HH}HwHH}He衇H}H`H}苇H˄ UHH H1H9NHD]DUHHm!]UHAWAVAUATSHHHIHHHHEH0L%sM|$@LLHHH@H0HfHnfLsHEEID$HHIhL0LLLvL5ILHDž HDžHDžHDžDž(LLLjLLHm/LH誈HHHL/LH5HHL0HHLt H輅H蜄H5HHyH0?H(HH;EuLHH[A\A]A^A_]ÅHSHeHHHL0HHLt HHH5HHԃH0蚄H( UHAWAVAUATSHHHHIHHQHHEH0L-Me@LLHcHH@H0HfHnfLHHEEIEHHIhL0LLHfHHHDž HDžHDžHDžDž(LLRLLH,LL5LLH,HH0L[HH2HHL0LHt H<HH5CHHH0迂HHH;EuHHH[A\A]A^A_]?ILI^IHHL0LHt H蚂HzH5HHWH0L UH]f.UH]DfDUH<H c!H]fDUHHM!H]UH]f.UH]fDUHAWAVAUATSHIHrHHE11LcILPHW)EHE@uHPpHc@hH H}1,4HHu +HHAHIHHH}1I1LP(HÃ{(uLc -HC(H{@H6.ILc AL$ID$HpHu$I|$@bH`-HpID$I1LPx(uH@ H.A"HXLuLeW)EHEM)tmMMII]HH<hHHEH]LmMIJ4HHEI?t@D)HHHJ!IE>LpID$HPE1Hh1H`HY A}(umI} LpHIUHH6L AE(ILuI] HhHHhIM!&LpLɴLpAE(I} H^"IE HIUxu HHk1dfID$ HIcL$;QAT$LlKHHEMIADIN $HXAHIHcQI9IHI JLQ(HY A}(N4HPH;q*HH,ILuKHWHuH`L`tfKfDHA}(uK/f.Lp2LOAE(JHEI] HhHHhILuHEL)HHI9L`MHXHh@H@HcHH~\HcULEHx 1fHt~(uHF HH9|+fDH9}PHHI4Hs?HH9|HHhHHA~(tLGAF(I^ H}Ht|H}Ht H}|HDHH;EuDHĈ[A\A]A^A_]@uHH?l@uHH?1S1|D([|IHH]H5 HI( HxH=AHxLyH!IIF IFIFE1H5C!HL|({IH5Q H' HxVAHxLJyH!IIF IFIFE1H5fC!HL{(a{IH5~ HA' HxAHxLxH%!IIF IFIFE1H5B!HL-{ H}:x (zIH5Z~ H& HxMAHxLSxH!IIF IFIFE1H5oB!HLz눿(jzIH5} H& Hx7RAHxLwH.!IIF IFIFE1H5A!H"L6z0HxuCJ Hxu3:Hxu#*H(HxuHxt H}yEtLyH}HtH}HH}HHv HH}HtvHH}HtzHH}HtlHH}Ht^HH}HtPHH}HtBHH}Ht"HH}HwHH}HexH}H`H}xHu UHH H1H9NHD]DUHH !]UH]f.UH]TxfDUHLxH !H]fDUHH!H]UH]f.UH]xfDUHAWAVSPII1LP(HÃ{(uHC *HC(H{@H$HC H@ I1LP(HÃ{(u0Ls ANI^HtYHC HtwHcK;}oQSLt|H8C(H{@rHj$ILs ANI^HuI~@XH#HI^HC HuHH;#HH$IILPHI1LPHI1LPH(t$fH@H(uH@ @uH@ @I1LPx(u H@ @ucH6"@tVI1LPx(uH@ H@HtH6"H@HuHe6"HcXA~(tLjAF(I^ H[A^A_]@u0HH?@u%HH?@uHH?11`1UHH H1H9NHD]DUHH}!]UH]f.UH]DufDUH<uH c!H]fDUHHM!H]UH]f.UH]tfDUHAVSII1LP(HÃ{(uHC *HC(H{@H!HC H@ I1LP(HÃ{(uLs ANI~t:[A^]HFC(H{@uJH|!ILs ANI~uI~@u3H IF[A^]@u*HH?`@uHH?@uHH?1;11fffff.UHH ţH1H9NHD]DUHH=!]UH]f.UH]sfDUH|sH #!H]fDUHH !H]UH]f.UH]4sfDUHAWAVAUATSHhHHHHE11HTHHPHHMHHEH LcuE1HHPL9HHLPHjHHLPH(t'H@H(uH@ @u2D$H@ @IM9yH1HPx(uH@ H@HtH2"H@HuHn2"Lc`HHW)EHEEEaxisEHuHIEt H}qMPEDA9EE9H1HP(IH}u/H1HPHLkHHH;E7sDA~(H]uIF /L$AF(I~@ +HUIF ـHD!LpMu'Hx@MHHILsMDEM{M~IF HELf.HEHHt$AF;}AFHu'ffffff.I?LHMHuLeDuE1E1fDH}HHPx(H 0"t&LyMt*HxHEA9Gt5=HH LyMuL=d0"HxHEA9G 1DI9u+IG JDx(uLD` HI9uMfffff.HEHHtIG H|HI9uf.EHI9uHxHH;] E1L=/"L%/"fffff.H}HHPx(Lt*HAHt.D9hu1HH;]rffff.HH HAHuLD9htϿ(nIH5pr H H}&xAHuLolH!IIF IFIFE1H56!HLn I E1LuHEHHcMH\Mc{(tH辣C(Ls HHH;EuAHh[A\A]A^A_]@uHH?@uHH? 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HGG(HG,]ÐUHSPHH#H{tH{HtHPH{ HC HHt[]$[]fUHSPHH`#H{tH{HtHPH{ HC HtڙHH[]ҙ@UHAWAVSPIIH{t1zHC Ht"HcK0H~>HcS,HH)IAC0MHcC(HHHOtHC HcK0HH{HS(HQC,~HcHKAHC IH[A^A_]yCH1fff.UHAVSH@HHHHE{0tAHAzLu$LFH5{LGH}HfGH}GC,H{ HC Ht舘H)HH;Eu H@[A^]ИHH}GH褕 fff.UHAWAVSHAIHHHEA0tXHxyH]H(FH5yHIFH5 zH:FH}HFH}GE9w,|fI tE9w,}YHyHxHEH5yHEH5yHEHpH#FHxFEyYHxH@HbEH5xHEH5yHtEH8HEH@IFEw0HHH;EuHĸ[A^A_]@HH@FH HHxEH HH}EH f.UHAWAVSHHAHHHHEEx'{th1H H H;MHH[A^A_]HwL}LFDH5wLgDH}HDH}BE{uC0D)}9A)C0H{HDPHHCD9H hH H;MmK0H MH H;MRHH}DH͒ DUHHGHcO0H)]ffffff.UHHHHwfGҸ OHG HGG(G,]fUHHHHwfGҸ OHG HGG(G,]fUHAVSHH_H{t/{tH{HtHPH{ HC Ht9[A^]鏔S,tH{Hs HPtHcC,HCC,{u[A^]CC,H{ HC Ht9{wIH{ HC HtL:@UH]&fDUHSPHHH[]@UHAVSH{t E1D[A^]ËS,AtH{Hs HPtHcC,HCC,CC,H{ HC HtoDUHAWAVAUATSPIIHS,;S(u=E1{uut3H{Hs HPtqHcC,HCC,HC Lck(Hu*AHC Lck(HuIHIOHC IcHI$A)E.C(C,ADH[A\A]A^A_]CC,H{ HC Ht蘒E1ff.UHAWAVSHAHHHHEExC,;C(uWD9HsL}KLT@H5sLu@H}H@H}PAC,;C(tH[sLxLL@H5tL)@H5sH@HpHk@Hx@C,D9}\HrL@NL?H5sL?H5sH?H8H +@H@@C,D)C,HHH;EuHĸ[A^A_]耑HH}V@HT HH@=@H; HHx$@H" f.UHHcG,HG]fUHAWAVAUATSHAHIH?HHEE9~(~ZIHuHULPtLLeLmDHcUH}A9HۑHcEHA)ILLLPuA~t%1H H H;MH[A\A]A^A_]AV,t"I~Iv HPtbIcF,IFAF,I~HHDPtIcIFIcH>IuD)LPH BH H;MzAFAF,I~ IF H=a3@UHSPHHCHCH@@HC(He messagHH(H for litHH Hg fieldsHHHe missinHHHdeterminHHH(cannot Hf@0e)@2HH[]ÐUHSHxHHMHHEHqH}<W)EHEH56rH}UH5qH}EH5rH}5HH}HPEبt +HuHU HuH} Et H} H5qH}HH}HP8Eبt +HuHU HuH}輋Et H}轍H}Hu"<H}HV<Et H}蕍H}<H'HH;EuHx[]ЍHEu #HEtH}QEuHEt H}3H}l<Hj fUHAWAVSHxIHHHHEHP(HPHHMHEHEHEHEHEHEEEHEHELpLLfH HHLQXHt}uHHP0u +H1H H H;Mu Hx[A^A_]菌UH]fDUHAWAVAUATSHxHIHHHEIP(L{LE{DLEkHOHEHEHEHEHEHEHEEEHEHEIr*Dž|KD/HhH`HEHpKLeLLLŒDž|JD-HhH`HDžpH}uM)L}MIH`LLPXH1Ht"MuILP0u +L1H _H H;MuHx[A\A]A^A_]fUHAWAVATSHIHH!HHELcHP(HRNHEHEHEHEHEHEHEEEHEHEAr'EKD>HpHhHEHxHLeLLL[EJD=HpHhHDžxH}uM)LuMHHhHLPXH1Ht"MuHHP0u +H1H H H;MuHĀ[A\A^A_]蛉ffff.UH]fDUHAWAVSHIHHHHEHPHIIHlHp6HH}HPHpHu7H5<lH6HLR8HhH37Et H}rHp71H H H;MtXdHg$HuHuHuL}fEEHLuHLP`LH}H H H;MuHĈ[A^A_]IHHEt H}҇Hp7H fffff.UHAWAVSHXIHH6HHEL}LnHLSH}t"IH@A| H H H;Mt1H H H;Mu HX[A^A_]~HH}DHR 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HHPHfffff.H;sHH…IL+{D9{Dc\HDDHHHS)ssIcHAA)yʉ!HcHHyDpLHP@y*29@Hffffff.t$ȃtLHH 1ɉKPH[A\A^A_]EuHSHCPE~ HKHHDHff.UHHHqHHEHuHuH TH H;MuH]oUHAWAVAUATSHXIIHHHHEHH$<؃HHcHHuLIM|M'M`LuLmȃr9L}Af.MˀLmIDI?wDL}LlM7Ir7Lfffff.IÀALlHAI?wAALlLuHHH;EMt$M/MM$$r:L}LuAMˀLClIDI?wDLuL}LlLeI?HuȺLLIIM LLpIME1HJHH;EmHQH]HH5QHH}HH}MHHH;EMt$M/MtmE$$r;L}LuA@MˀL#kIDI?wDLuL}LjDeI?HuȺjH]HH;ELHX[A\A]A^A_]HH}Hi @'JUHx HHH]ODx HHH]OHHHxHHHH]OHHHxHHHH]OHHHxHHHH]DGLH#HHHHExHHHH]DGLH*HHHHExHHHH]DGLH1HHHHExHHHH]DGLH8HHHHExHHHH]O xH HH?HHHH]11HH]ÐUHAWAVAUATSHXHXHHEHUL~yHAT IHH_D)M9H}LeI9HEH]LHuIMDmHE;Xu)DsLD -ID$D,ffffff.HEH@D,DsHED0H]I9rH}H_HEI)+E~moHIIMXD)IcIHI]D)MM9Lffff.MI)+EfEHEHHHKHMHEHcLd IcH\HMH9Leff.HHuHHDmHED0D;pu.E~LeLDID$LeF,HED8L9rHEH@F,E~HED8L9r1HL9HEHMHHHH H H;M'MHM$~tLeLHuIMtYDmHED8D;xu+A_LeL ID$LeF,f.HEH@F,A_HEM9rE11M9IDH PH H;MHX[A\A]A^A_]F +ID$D,ffffff.HEH@D,DsHED0H]I9rH}H_HEI)+E~moHIIMXD)IcIHI]D)MM9Lffff.MI)+EfEHEHHHKHMHEHcLd IcH\HMH9Leff.HHuHHDmHED0D;pu.E~LeLDID$LeF,HED8L9rHEH@F,E~HED8L9r1HL9HEHMHHHH H 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MMMMPLHIIJHHIJLMMf.MbM!M9uMMMu@IJ<taLI -MHtnMrMMIIMI9t2AF ;A uLIcv;quC~IH 1@;u+HH9|IMHuN MMMM_1MIEIIJHIEIJLIMM,H[A\A]A^A_]ÿIHH5H说Hz.HHH5,-H=,HIIH L0 UHAVSHH@Hx϶IHC`HH?HH1LHLsh[A^]HL莶Hγ fDUHAVSHH@HxoIHK`LH~Lsh[A^]HL8Hx UHAWAVSPHH@HD{xIHK`AtLH! HH?HHLHHLspH[A^A_]HL豵H fUHAWAVSPHH{(C(HC0C8HC@CHCPHCXC`HChCpHCxǃH3FCC fCHC HCvH{PHpH A0HcQ4HHHcI<H~RLtLHѴH{xHCxHt賴DƃHǃHǃH[A^A_]ÿ蒴IH5'LH+HIH5u*H)L蒴 ILgH{xHCxHuIH{xHCxHt H{hHChHu=H{XHCXHuBH{@HC@HuGH{0HC0HuLL 足H{XHCXHt蠳H{@HC@Ht芳H{0HC0HttL贰 fff.UHAWAVAUATSHAIM}MAE D9MEe EIcH<HEHHHEEIcMeHH}L[HH}LHHHEIEMt L觲M}EuHEIEMtL芲Eu E9u1D9FE9u~EuH[A\A]A^A_]E1E7\IH5L¯H)HIH5?(HP'L\MeHEIEMJQHLH) HH}ӱH ff.UHAWAVSPIIHt蚱IHt'fDL;H{HtwHuLMuI~xIFxHtWI~hIFhHtAI~XIFXHt+I~@IF@HtI~0IF0HHt [A^A_][A^A_]UHAWAVAUATSHhLLxHIH=(HHEЅxLeLWxAIBHH@ AHLfffff.IcAHAD +MHtnMrMMIIMI9t2AF ;A uLIcv;quC~IH 1@;u+HH9|IMHuN MMMM_1MIEIIJHIEIJLIMM,H[A\A]A^A_]ÿIHH5H说HHHH5LH]HIIH L0 UHAVSHH@Hx϶IHC`HH?HH1LHLsh[A^]HL莶Hγ fDUHAVSHH@HxoIHK`LH~Lsh[A^]HL8Hx UHAWAVSPHH@HD{xIHK`AtLH! HH?HHLHHLspH[A^A_]HL豵H fUHAWAVSPHH{(C(HC0C8HC@CHCPHCXC`HChCpHCxǃH3FCC fCHC HCvH{PHpH A0HcQ4HHHcI<H~RLtLHѴH{xHCxHt賴DƃHǃHǃH[A^A_]ÿ蒴IH5'LHHIH5HL蒴 ILgH{xHCxHuIH{xHCxHt H{hHChHu=H{XHCXHuBH{@HC@HuGH{0HC0HuLL 足H{XHCXHt蠳H{@HC@Ht芳H{0HC0HttL贰 fff.UHAWAVAUATSHAIM}MAE D9MEe EIcH<HEHHHEEIcMeHH}L[HH}LHHHEIEMt L觲M}EuHEIEMtL芲Eu E9u1D9FE9u~EuH[A\A]A^A_]E1E7\IH5L¯HHIH5_HpL\MeHEIEMJQHLH) HH}ӱH ff.UHAWAVSPIIHt蚱IHt'fDL;H{HtwHuLMuI~xIFxHtWI~hIFhHtAI~XIFXHt+I~@IF@HtI~0IF0HHt [A^A_][A^A_]UHAWAVAUATSHhLLxHIH]HHEЅxLeLWxAIBHH@ AHLfffff.IcAHAD ML LfMMHt/JM̃ HHHMfff.tsIwHA9G HcI_HcA;s H9tEAI_IcDBHEHcHHDIw7DIu1L3fffff.1LcHLrHC ˀˀnIWJcHHTH1Hc4HA$L"uIcAHA ID OcLD;O IcHAMdHHaHH_ HBuIcAHA ID C E1ɀLvC|HECC\9|C\9 A$L"C ɹLDɀLu"IcADHA ID -DC\HxH讑Ѕ@CE1HLDL!|DLNHHHcX HعHHH@HHLDLHHBHBHIL$HcHHHDCAHs 1MukIPH)1HHH\H\H\H\H\H\H\ H\ H\(H\(H\0H\0H\8H\8HHuMt(IHHHHHHHIuHHBAHJ ICE1ɀLEwDۺHH5v -HH5C4H>HH5{H HLAEHLDEH"HH;EuHh[A\A]A^A_]mHHH> f[UHAWAVAUATSHXH5"HHELLIIHA>IFHHHILfffff.Ml$MAOt!AtIHI}H;yMc$ILZHCӉӀH<AtHI;G $AIMMIH9HI;AI9AӉӀL,$LHLL5MLӺ]HH5 -HH5JA4߃H艧HH5'HkLAӃh[MIMIc HHIIAPHs 1HuwHzL)1fff.HIH\I\H\I\H\I\H\ I\ H\(I\(H\0I\0H\8I\8HHuHt(HH<HIHH9I9HHuMHIAAƇAEHAMIIEMIIFIcHHI9A1H H H;MHX[A\A]A^A_]Ic H MIUHHHDCAHsS1MIIc H-IMHIIEHAHy1MIHH)1fHIH\I\H\I\H\I\H\ I\ H\(I\(H\0I\0H\8I\8HHuMt(IH HIHH -I HIuAƇAMQAU4IIMM ffffff.IHIHIcHINH9tHHHtz9AICHIHӀt у CDH H H;M觥IyL)1HHH\H\H\H\H\H\H\ H\ H\(H\(H\0H\0H\8H\8HHuMt(IH<HHHH9H8HIuIHHHAƇAEHAM%IIEMIHIIIcHIFI9ID$HtދQHHHk UHAWAVAUATSHXIIHHHEA}L2HBHLMt -IL9s4M7IGHLIL9rMgJ#HLH9vdH5HHHH5H 1H H H;MeHX[A\A]A^A_]I}I9t*tH9AEIU AUwLAE EEu AE HHHHH@H覢IAƅMuIM(HMuPAE(AEPHHHmHHHHIMgLIIܹL9Hs LILLLI?LIIOHхH9LnAOt~H9=I}+HMM褡HIc] HعHHH@HoLI@I@XI}趀xOAuHHII_H9s9uHHMMu3fHH)uHHDHHMM8IIAA] I@IHcHHHVHs 1HurHzH)1HHH\H\H\H\H\H\H\ H\ H\(H\(H\0H\0H\8H\8HHuHt(HH<HHHH9H8HHuI@HHAUIIGH9s L$LLLLIHH -IHILLA>-HH5(HmHH5nHljML f.IULcHZHB€ttJcTA;U }IH ŀuIHHAƅRH5~HHH5ن$B4H:H0LMA>tJIFfff.HHHtr1IHIHIcHINH9uAt(MAAu(1Mr1H kH H;M7L)11IH ;H\;H)I 9I\9IH\9HL9H)I\9IL9HH H9uM+IHH4HLH)I4ILH H H;M kHHHt fff.UHAWAVAUATSHHHHHHEЋsH}_IH}Ht-AA9Ev$HcHUHcu9s9t 4HcMEE$L%AIff.Mc/IYHB ʀʀIcLAu>Ht9AU9Uv0LEKct9s9tCDHcEEEB fDwHn9MeHuHc9s 9 NHcE DMκfHH5| -HH5B4HDHH5H&H}EMDHAD9mIcHUHc49s -D9,HcED,EE|u5Ht0AM9Mv'LcHuJc9s9 tBHcE EEBLB:LʀŸwBTAtA9txAfIHcH EI9AHEHtmH}HEHtWHHH;Eu*DHH[A\A]A^A_]AHEHuxHH}HEHu"%HHH}HEHtݙH}HEHu -H  轙H TQQ3QUHAWAVAUATSHMEʼnHIHDuH H HMH0HW) AuEH LDDD1ɃE1EAD4$H0LHMtAuIIGI $IL$H9t1H0H8HH;EuH[A\A]A^A_]HH0Hŕ ffff.UHAWAVAUATSHHIHHHHEЃtGAtAH5H2HH50j H{LEċED<AODžHHH8~,AIHLėHpL赗HHHHKHhH`Ht>}t/H`I;IINHhH`>}uъFt,H`HhM.INI\ H(H9M.INIT H(DEHVXFLpLH,H0@_H8AD$AL0Mff.AEDxA\AA?t$H`LyzHH}A@LcMÀ +DC\HxH讑Ѕ@CE1HLDL!|DLNHHHcX HعHHH@HHLDLHHBHBHIL$HcHHHDCAHs 1MukIPH)1HHH\H\H\H\H\H\H\ H\ H\(H\(H\0H\0H\8H\8HHuMt(IHHHHHHHIuHHBAHJ ICE1ɀLEwDۺHH5& +HH5CTC4H>HH5+TH HLAEHLDEHHH;EuHh[A\A]A^A_]mHHH> f[UHAWAVAUATSHXHUHHELLIIHA>IFHHHILfffff.Ml$MAOt!AtIHI}H;yMc$ILZHCӉӀH<AtHI;G $AIMMIH9HI;AI9AӉӀL,$LHLL5MLӺ]HH5q +HH5*RA4߃H艧HH5RHkLAӃh[MIMIc HHIIAPHs 1HuwHzL)1fff.HIH\I\H\I\H\I\H\ I\ H\(I\(H\0I\0H\8I\8HHuHt(HH<HIHH9I9HHuMHIAAƇAEHAMIIEMIIFIcHHI9A1H H H;MHX[A\A]A^A_]Ic H MIUHHHDCAHsS1MIIc H-IMHIIEHAHy1MIHH)1fHIH\I\H\I\H\I\H\ I\ H\(I\(H\0I\0H\8I\8HHuMt(IH HIHH +I HIuAƇAMQAU4IIMM ffffff.IHIHIcHINH9tHHHtz9AICHIHӀt у CDH H H;M觥IyL)1HHH\H\H\H\H\H\H\ H\ H\(H\(H\0H\0H\8H\8HHuMt(IH<HHHH9H8HIuIHHHAƇAEHAM%IIEMIHIIIcHIFI9ID$HtދQHHHk UHAWAVAUATSHXIIHHHEA}L2HBHLMt +IL9s4M7IGHLIL9rMgJ#HLH9vdH5HHH5CLH 1H H H;MeHX[A\A]A^A_]I}I9t*tH9AEIU AUwLAE EEu AE HHHHH@H覢IAƅMuIM(HMuPAE(AEPHHHmHHHHIMgLIIܹL9Hs LILLLI?LIIOHхH9LnAOt~H9=I}+HMM褡HIc] HعHHH@HoLI@I@XI}趀xOAuHHII_H9s9uHHMMu3fHH)uHHDHHMM8IIAA] I@IHcHHHVHs 1HurHzH)1HHH\H\H\H\H\H\H\ H\ H\(H\(H\0H\0H\8H\8HHuHt(HH<HHHH9H8HHuI@HHAUIIGH9s L$LLLLIHH +IHILLA>-HH5؆HmHH5HHljML f.IULcHZHB€ttJcTA;U }IH ŀuIHHAƅRH5.HHH5$GB4H:H0LMA>tJIFfff.HHHtr1IHIHIcHINH9uAt(MAAu(1Mr1H H H;M7L)11IH ;H\;H)I 9I\9IH\9HL9H)I\9IL9HH H9uM+IHH4HLH)I4ILH H H;M kHHHt fff.UHAWAVAUATSHHHHHHEЋsH}_IH}Ht-AA9Ev$HcHUHcu9s9t 4HcMEE$L%AIff.Mc/IYHB ʀʀIcLAu>Ht9AU9Uv0LEKct9s9tCDHcEEEB fDwHn9MeHuHc9s 9 NHcE DMκfHH5, +HH5IDB4HDHH5DH&H}EMDHAD9mIcHUHc49s +D9,HcED,EE|u5Ht0AM9Mv'LcHuJc9s9 tBHcE EEBLB:LʀŸwBTAtA9txAfIHcH EI9AHEHtmH}HEHtWHHH;Eu*DHH[A\A]A^A_]AHEHuxHH}HEHu"%HHH}HEHtݙH}HEHu +H  轙H TQQ3QUHAWAVAUATSHMEʼnHIHDuH H HMH0HW) AuEH LDDD1ɃE1EAD4$H0LHMtAuIIGI $IL$H9t1H0HXHH;EuH[A\A]A^A_]HH0Hŕ ffff.UHAWAVAUATSHHIHHHHEЃtGAtAH5QH2HH5k0JAH{LEċED<AODžHHH8~,AIHLėHpL赗HHHHKHhH`Ht>}t/H`I;IINHhH`>}uъFt,H`HhM.INI\ H(H9M.INIT H(DEHVXFLpLH,H0@_H8AD$AL0Mff.AEDxA\AA?t$H`LyzHH}A@LcMÀ _uJfffff. tLHH tLHHL9uIL;(91HPE0A0u+1HPIE0A0D?tH`Ly}Ѕ|YD%tO|J8fD DtLHH DtLHHH9uH8|HHHu}LxH0D AAOσHH1HPIAEDxE|D?t9H`LxHH}ЅtA0E1A0u3VfDD@HH0LD A0(D@Dȃ?  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H H;Mt81H  H H;M"H[A\A]A^A_]HHH觎 ffffff.UHAWAVAUATSHHHHHEЀ{t,H{XHHH;EunH[A\A]A^A_]C{t>Lcc,I1IC4HK`HH?H>HHHcHHL9}1H(HH;EtH HcC0HcK4HHcC<HȃH<oH0LckMN4LKIǾLL辑W)PHDž`H}D} H}Dq HcCHL t4HMHt-9Ev(HUHc<u9s9t4HcUEC1HAHXƅpHPHpL }HML L0LHLH(HHcIcHPIHL<{~0HHL1ffffff.0HHcsH9|A0AEABDžDHcɉ<ElE\<HcUEG,AfMcLsHCɀVIc Lu[At=HMHt4D9mv.IcHUHc<u9s +_uF DtLHH DtLHHL9uIEL;(E0A0Pu1H H H;MAEAu1HMugM)1ɿHfDH=XH=`H)H\>HT>H=hH=pH)HT>H>HH I9uMt7HH pH xH)HH|H NH H;Mt81H 7H H;M"H[A\A]A^A_]HHH觎 ffffff.UHAWAVAUATSHHHHHEЀ{t,H{XHHH;EunH[A\A]A^A_]C{t>Lcc,I1IC4HK`HH?H>HHHcHHL9}1HHHH;EtH HcC0HcK4HHcC<HȃH<oH0LckMN4LKIǾLL辑W)PHDž`H}D} H}Dq HcCHL t4HMHt-9Ev(HUHc<u9s9t4HcUEC1HAHXƅpHPHpL }HML L0LHLH(HHcIcHPIHL<{~0HHL1ffffff.0HHcsH9|A0AEABDžDHcɉ<ElE\<HcUEG,AfMcLsHCɀVIc Lu[At=HMHt4D9mv.IcHUHc<u9s D9,4HcED,ECHc<E,ʍQ<E\62CL $ A E1?HMAH/9EA#HuLc}A9B9(DECDDADAHMAH9EAHcHuLc}A9s B9<HcUEAiD@HHDAt.CLCD8kG \E1%L(D;6HHH t=HUHt49Ev/LEMc}A9sB9tA<HcMECH D9HXƅpHPH HpuEAGLPLH(L0CLCD8DD@DD @A ffffff.Hc|3x@8|3yuHHNH~ATփ00uELCDfff.D9Q9|C|CTaaF<zzC9AD@DD @E DHcL;x8L;yuHHWH~At00uELJ9‰|fD9AJ9‰|CDAL D@HMAH9EAHcHuLc}A9s -B9<HcUEAD@HpH5r'HxH5r_C4H螈Hp蔳L0L "<D<HHHcEHHEH9LHL H(1LHH}HEHtUH}HEHt?H}HEHt)H}HEHtHPHt HXLH0HbHH;E1LcL)c`L蹈HCXHPHL)H}HEH,,菈IH5$LHHIH5rHL菈OIH5L赅HHIH52HCLO HL$HLH$ HH}HEHuehHH}HEHtvHHPHuHHHp.HLHH}HEHtZH}HEHuXH}HEHu]H}HEHubHPHt HXLH0H; H}HEHtֆH}HEHtHPHuL;;;UHAWAVATSAIA$Ex7IcHHmIM|$Et$HXID$Et$ [A\A^A_]ÿGHH5H譃HxHHH5*H;HGIHL. 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hP!hl!h!h!h!h!h!h!h!h"h"h"h0"hE"hT"vhc"lht"bh"Xh"Nh"Dh":h"0h"&h"h"h#h#h##h0#h>#hP#h`#hp#OrtGetApiBaseOrtSessionOptionsAppendExecutionProvider_CPU/Users/runner/work/1/s/onnxruntime/core/session/IOBinding.ccBindInputp_providerexecution_mode is not validgraph_optimization_level is not validResult buffer is not large enoughInputT/Users/runner/work/1/s/onnxruntime/core/session/custom_ops.cccommon::Status onnxruntime::CreateCustomRegistry(const std::vector<OrtCustomOpDomain *> &, std::shared_ptr<CustomRegistry> &)type_id_counter == 1There must be one (and only one) dynamic typed input to the custom op. Its type info at runtime will be used to infer the type info of this dynamic typed output which is required for the success of the model loading step. More than one dynamic typed inputs are currently not supported as differing types at runtime means the output type cannot be inferred without which model loading cannot proceed.OutputCreateCustomRegistryonnxruntime::CustomOpKernel::CustomOpKernel(const onnxruntime::OpKernelInfo &, const OrtCustomOp &)Unsupported version '' in custom op 'ComputeAsyncNo requested allocator availableEnv is nullOrtMemoryInfo is nullAllocator with this OrtMemoryInfo is already registered.Received invalid value for arena extend strategy. Valid values can be either 0, 1 or -1.intra-opinter-opMemcpyFromHostXinputYoutputConstrain to any tensor type. If the dtype attribute is not provided this must be a valid output type.MemcpyToHosttensor(uint8)tensor(uint16)tensor(uint32)tensor(uint64)tensor(int8)tensor(int16)tensor(int32)tensor(int64)tensor(bfloat16)tensor(float16)tensor(float)tensor(double)tensor(string)tensor(bool)Input expected to have type but instead is null expected to have tensor typeElement type of input unknownOutput expected to have sequence typeMismatch between source and target type. Source=Trying to register schema with name (domain: version: ) from file line , but it is already registered from file , but its domain is not known by the checker., but its version is not in the inclusive range [] (usually, this means you bumped the operator version but forgot to update the version range in DomainToVersionRange in onnx/defs/schema.h).Schema error: com.microsoftcom.microsoft.nchwc/Users/runner/work/1/s/onnxruntime/core/session/inference_session.ccvoid onnxruntime::InferenceSession::ConstructorCommon(const onnxruntime::SessionOptions &, const onnxruntime::Environment &)status.IsOK()Could not finalize session options while constructing the inference session. Error Message: graph_transformation_mgr_.SetSteps(session_options_.max_num_graph_transformation_steps).IsOK()ConstructorCommonCreating and using per session threadpools since use_per_session_threads_ is true-session--intra-op-inter-opFailed to create the inter-op thread pool for the parallel executor, setting ExecutionMode to SEQUENTIALUsing global/env threadpools since use_per_session_threads_ is falsesession_env.EnvCreatedWithGlobalThreadPools()When the session is not configured to use per session threadpools, the env must be created with the the CreateEnvWithGlobalThreadPools API.onnxruntime::InferenceSession::InferenceSession(const onnxruntime::SessionOptions &, const onnxruntime::Environment &, const std::string &)Given model could not be parsed while creating inference session. Error message: st.IsOK()Could not parse model successfully while constructing the inference sessiononnxruntime::InferenceSession::InferenceSession(const onnxruntime::SessionOptions &, const onnxruntime::Environment &, const void *, int)result~InferenceSessionUnknown error during EndProfiling()Received nullptr for exec providerRegisterExecutionProviderExecution providers must be registered before the session is initialized. Execution providers must be registered before the session is initialized.DmlExecutionProviderHaving memory pattern enabled is not supported while using the DML Execution Provider. So disabling it for this session since it uses the DML Execution Provider.Parallel execution mode does not support the DML Execution Provider. So making the execution mode sequential for this session since it uses the DML Execution Provider.CUDAExecutionProviderParallel execution mode does not support the CUDA Execution Provider. So making the execution mode sequential for this session since it uses the CUDA Execution Provider.TensorrtExecutionProviderAddCustomOpDomainsReceived nullptr for custom registry4SaveToOrtFormatLoadThis session already contains a loaded model.Unknown exception in Load()Encountered unknown exception in Load()ORTModelProto corresponding to the model to be loaded has already been parsed. Invoke Load().ModelProto corresponding to the model to be loaded has not been parsed yet. This API should be called in conjunction with a ctor that takes a model abstraction.TransformGraphCould not find an implementation for the node ( (Node placementsAll nodes have been placed on []., Provider: [: [PartitionOrtFormatModelLoadOrtModelThis session has already been initialized.ORT model verification failed.InferenceSession is null. Invalid ORT format model.Serialized version info is null. Invalid ORT format model.The ORT format model version [] is not supported this build Missing Model. Invalid ORT format model.SessionState is null. Invalid ORT format model.The provided PrePackedWeightsContainer instance to be added to the session is nullInitializeInitializing session.Model was not loadedModel was not loaded.Session has already been initialized.Adding default CPU execution provider.This session will use the allocator registered with the environment.Unable to serialize model as it contains compiled nodes. Please disable any execution providers which generate compiled nodes.Serializing optimized model with Graph Optimization level greater than ORT_ENABLE_EXTENDED and the NchwcTransformer enabled. The generated model may contain hardware specific optimizations, and should only be used in the same environment the model was optimized in.Session successfully initialized.Invalid rank for input: Got: Expected: Please fix either the inputs or the model.Got invalid dimensions for input: for the following indices index: Size mismatch: feed_names has elements, but feeds has elements.Invalid Feed Input Name:Input with name: is not expected to be of type tensor.tensorValidateInputs is not expected to be of type sparse tensor.sparse_tensor is not expected to be of type tensor sequence.seqOutput vector pointer is NULLAt least one output should be requested.Output vector incorrectly sized: output_names.size(): p_fetches->size(): Invalid Output Name:RunSession was not initializedSession not initialized.Running with tag: Encountered unknown exception in Run()GetModelMetadataGetModelInputsGetOverridableInitializersGetModelOutputsNewIOBindingEndProfilingProfiler is disabled.Could not write a profile because no model was loaded.cpugpuUnsupported device specified in the memory arena shrink list: Unsupported device id in the memory arena shrink list: Did not find an arena based allocator registered for device-id combination in the memory arena shrink list: The registered allocator for device-id combination is not an arena based allocator: ShrinkMemoryArenasUnable to shrink arena: error message: const logging::Logger &onnxruntime::InferenceSession::CreateLoggerForRun(const onnxruntime::RunOptions &, std::unique_ptr<logging::Logger> &)run_options.run_log_severity_level >= 0 && run_options.run_log_severity_level <= static_cast<int>(logging::Severity::kFATAL)Invalid run log severity level. Not a valid onnxruntime::logging::Severity value: void onnxruntime::InferenceSession::InitLogger(logging::LoggingManager *)session_options_.session_log_severity_level >= 0 && session_options_.session_log_severity_level <= static_cast<int>(logging::Severity::kFATAL)Invalid session log severity level. Not a valid onnxruntime::logging::Severity value: The only supported values for the environment variable are '0' and '1'. The environment variable contained the value: FinalizeSessionOptionsReading the provided model for the ORT configonnxruntime::common::Status onnxruntime::FinalizeSessionOptions(const onnxruntime::SessionOptions &, const onnx::ModelProto &, bool, onnxruntime::SessionOptions &)is_model_proto_parsedError during EndProfiling(): Provider has already been registered./Users/runner/work/1/s/onnxruntime/core/framework/execution_providers.hAddORTMException during loading: Exception during initialization: Unexpected input data type. Actual: ()) , expected: ())/Users/runner/work/1/s/onnxruntime/core/framework/feeds_fetches_manager.hFeedsFetchesInfoonnxruntime::FeedsFetchesInfo::FeedsFetchesInfo(const std::vector<std::string> &, const std::vector<std::string> &, const onnxruntime::OrtValueNameIdxMap &)Flush-to-zero and denormal-as-zero are onoffwbrbLoad model from failed:Failed to load model because protobuf parsing failed.LoadOrtModelBytes failed. Only / bytes were able to be read._.json%Y-%m-%d_%H-%M-%SThe Model Proto has already been checked for the ORT config json.ort_config/Users/runner/work/1/s/onnxruntime/core/session/inference_session_utils.ccParseOrtConfigJsonInModelProtoFound session/run/environment configuration in the model file to be used while running the modelORT config json from the model: ParseSessionOptionsFromModelProtoDid not find session options in the model file to be used while running the modelsession_optionsintra_op_num_threadsinter_op_num_threadsexecution_modegraph_optimization_levelgraph_optimization_level option in the model file must be an integerenable_profilingIgnoring unsupported session option in ORT config: Json stored in the `ort_config` key cannot be parsed. Error message: SetIntraOpNumThreadsUnsupported value for intra_op_num_threads: Setting intra_op_num_threads to SetInterOpNumThreadsUnsupported value for inter_op_num_threads: Setting inter_op_num_threads to SetExecutionModeUnsupported execution_mode value in ORT config: Setting execution_mode to Sequential modeParallel modeSetGraphOptimizationLevelSetting graph_optimization_level to ORT_DISABLE_ALLSetting graph_optimization_level to ORT_ENABLE_BASICSetting graph_optimization_level to ORT_ENABLE_EXTENDEDSetting graph_optimization_level to ORT_ENABLE_ALLUnsupported graph_optimization_level value in ORT config: SetEnableProfilingUnsupported value for enable_profiling option: Setting enable_profiling to true[json.exception.invalid BOM; must be 0xEF 0xBB 0xBF if givennullinvalid literalinvalid string: missing closing quoteinvalid string: '\u' must be followed by 4 hex digitsinvalid string: surrogate U+DC00..U+DFFF must be followed by U+DC00..U+DFFFinvalid string: surrogate U+DC00..U+DFFF must follow U+D800..U+DBFFinvalid string: forbidden character after backslashinvalid string: control character U+0000 (NUL) must be escaped to \u0000invalid string: control character U+0001 (SOH) must be escaped to \u0001invalid string: control character U+0002 (STX) must be escaped to \u0002invalid string: control character U+0003 (ETX) must be escaped to \u0003invalid string: control character U+0004 (EOT) must be escaped to \u0004invalid string: control character U+0005 (ENQ) must be escaped to \u0005invalid string: control character U+0006 (ACK) must be escaped to \u0006invalid string: control character U+0007 (BEL) must be escaped to \u0007invalid string: control character U+0008 (BS) must be escaped to \u0008 or \binvalid string: control character U+0009 (HT) must be escaped to \u0009 or \tinvalid string: control character U+000A (LF) must be escaped to \u000A or \ninvalid string: control character U+000B (VT) must be escaped to \u000Binvalid string: control character U+000C (FF) must be escaped to \u000C or \finvalid string: control character U+000D (CR) must be escaped to \u000D or \rinvalid string: control character U+000E (SO) must be escaped to \u000Einvalid string: control character U+000F (SI) must be escaped to \u000Finvalid string: control character U+0010 (DLE) must be escaped to \u0010invalid string: control character U+0011 (DC1) must be escaped to \u0011invalid string: control character U+0012 (DC2) must be escaped to \u0012invalid string: control character U+0013 (DC3) must be escaped to \u0013invalid string: control character U+0014 (DC4) must be escaped to \u0014invalid string: control character U+0015 (NAK) must be escaped to \u0015invalid string: control character U+0016 (SYN) must be escaped to \u0016invalid string: control character U+0017 (ETB) must be escaped to \u0017invalid string: control character U+0018 (CAN) must be escaped to \u0018invalid string: control character U+0019 (EM) must be escaped to \u0019invalid string: control character U+001A (SUB) must be escaped to \u001Ainvalid string: control character U+001B (ESC) must be escaped to \u001Binvalid string: control character U+001C (FS) must be escaped to \u001Cinvalid string: control character U+001D (GS) must be escaped to \u001Dinvalid string: control character U+001E (RS) must be escaped to \u001Einvalid string: control character U+001F (US) must be escaped to \u001Finvalid string: ill-formed UTF-8 byteinvalid number; expected digit after '-'invalid number; expected digit after '.'invalid number; expected '+', '-', or digit after exponentinvalid number; expected digit after exponent signnumber overflow parsing 'arrayobjectexcessive object size: cannot use erase() with booleandiscardednumberexcessive array size: <U+%.4X>parse error at line , column while parsing - ; last read: 'unexpected ; expected <uninitialized>true literalfalse literalnull literalstring literalnumber literal'[''{'']''}'':'','<parse error>end of input'[', '{', or a literalunknown tokenkey '' not foundcannot use at() with map::at: key not foundtype must be number, but is tried creating tensor with negative value in shapesize overflownot enough space: expected , got type is not supported in this functionRegisterCustomOpsLibrary: Failed to load libraryRegisterCustomOpsLibrary: Entry point RegisterCustomOps not found in libraryinput name cannot be emptyCPUExecutionProvideroutput name cannot be emptylengths allocation failedstring buffer allocation failedOutput buffer allocation failedinput array doesn't equal tensor sizeelement index is out of boundsshape is invalidoffsets buffer is not equal to tensor sizeoutput buffer is too smallbuffer size is too small for stringinput array is too shortopaque(,)/Users/runner/work/1/s/onnxruntime/core/session/onnxruntime_c_api.ccOrtStatusPtr OrtApis::CreateOpaqueValue(const char *, const char *, const void *, size_t, OrtValue **)ml_type != nullptrSpecified domain and type names combination does not refer to a registered opaque typenon_tensor_base != nullptrOrtStatusPtr OrtApis::GetOpaqueValue(const char *, const char *, const OrtValue *, void *, size_t)this API does not support stringslocation dimensions do not match shape sizeinvalid location rangeROCM execution provider is not enabled.max_memarena_extend_strategyinitial_chunk_size_bytesmax_dead_bytes_per_chunkinitial_growth_chunk_size_bytesInvalid key found: The given version [%u] is not supported, only version 1 to %u is supported in this build. -1.8.0allocator<T>::allocate(size_t n) 'n' exceeds maximum supported sizeORT_LOAD_CONFIG_FROM_MODEL1/Users/runner/work/1/s/include/onnxruntime/core/framework/ml_value.honnxruntime::Tensor *OrtValue::GetMutable()IsTensor()Trying to get a Tensor, but got: const onnxruntime::Tensor &OrtValue::Get() constout of index/Users/runner/work/1/s/onnxruntime/core/common/safeint.hstatic void SafeIntExceptionHandler<onnxruntime::OnnxRuntimeException>::SafeIntOnOverflow()internal errorindex out of rangeconst onnxruntime::TensorSeq &OrtValue::Get() constIsTensorSequence()Trying to get a TensorSeq, but got: Input is not of one of the supported sequence types.Input is not of type sequence or map./Users/runner/work/1/s/include/onnxruntime/core/framework/data_types_internal.hstatic bool onnxruntime::utils::ContainerChecker::IsContainerOfType<std::__1::vector<std::__1::map<std::__1::basic_string<char>, float, std::__1::less<std::__1::basic_string<char> >, std::__1::allocator<std::__1::pair<const std::__1::basic_string<char>, float> > >, std::__1::allocator<std::__1::map<std::__1::basic_string<char>, float, std::__1::less<std::__1::basic_string<char> >, std::__1::allocator<std::__1::pair<const std::__1::basic_string<char>, float> > > > > >::check(const onnxruntime::utils::ContainerChecker::Cont &, size_t) [T = std::__1::vector<std::__1::map<std::__1::basic_string<char>, float, std::__1::less<std::__1::basic_string<char> >, std::__1::allocator<std::__1::pair<const std::__1::basic_string<char>, float> > >, std::__1::allocator<std::__1::map<std::__1::basic_string<char>, float, std::__1::less<std::__1::basic_string<char> >, std::__1::allocator<std::__1::pair<const std::__1::basic_string<char>, float> > > > >]++index < c.size()static bool onnxruntime::utils::ContainerChecker::IsContainerOfType<std::__1::map<std::__1::basic_string<char>, float, std::__1::less<std::__1::basic_string<char> >, std::__1::allocator<std::__1::pair<const std::__1::basic_string<char>, float> > > >::check(const onnxruntime::utils::ContainerChecker::Cont &, size_t) [T = std::__1::map<std::__1::basic_string<char>, float, std::__1::less<std::__1::basic_string<char> >, std::__1::allocator<std::__1::pair<const std::__1::basic_string<char>, float> > >]const T &OrtValue::Get() const [T = std::__1::vector<std::__1::map<std::__1::basic_string<char>, float, std::__1::less<std::__1::basic_string<char> >, std::__1::allocator<std::__1::pair<const std::__1::basic_string<char>, float> > >, std::__1::allocator<std::__1::map<std::__1::basic_string<char>, float, std::__1::less<std::__1::basic_string<char> >, std::__1::allocator<std::__1::pair<const std::__1::basic_string<char>, float> > > > >]onnxruntime::DataTypeImpl::GetType<T>() == type_ != static bool onnxruntime::utils::ContainerChecker::IsContainerOfType<std::__1::vector<std::__1::map<long long, float, std::__1::less<long long>, std::__1::allocator<std::__1::pair<const long long, float> > >, std::__1::allocator<std::__1::map<long long, float, std::__1::less<long long>, std::__1::allocator<std::__1::pair<const long long, float> > > > > >::check(const onnxruntime::utils::ContainerChecker::Cont &, size_t) [T = std::__1::vector<std::__1::map<long long, float, std::__1::less<long long>, std::__1::allocator<std::__1::pair<const long long, float> > >, std::__1::allocator<std::__1::map<long long, float, std::__1::less<long long>, std::__1::allocator<std::__1::pair<const long long, float> > > > >]static bool onnxruntime::utils::ContainerChecker::IsContainerOfType<std::__1::map<long long, float, std::__1::less<long long>, std::__1::allocator<std::__1::pair<const long long, float> > > >::check(const onnxruntime::utils::ContainerChecker::Cont &, size_t) [T = std::__1::map<long long, float, std::__1::less<long long>, std::__1::allocator<std::__1::pair<const long long, float> > >]const T &OrtValue::Get() const [T = std::__1::vector<std::__1::map<long long, float, std::__1::less<long long>, std::__1::allocator<std::__1::pair<const long long, float> > >, std::__1::allocator<std::__1::map<long long, float, std::__1::less<long long>, std::__1::allocator<std::__1::pair<const long long, float> > > > >]/Users/runner/work/1/s/onnxruntime/core/framework/TensorSeq.hconst onnxruntime::Tensor &onnxruntime::TensorSeq::Get(size_t) consti < tensors_.size()Input is not of one of the supported map types.static bool onnxruntime::utils::ContainerChecker::IsContainerOfType<std::__1::map<std::__1::basic_string<char>, std::__1::basic_string<char>, std::__1::less<std::__1::basic_string<char> >, std::__1::allocator<std::__1::pair<const std::__1::basic_string<char>, std::__1::basic_string<char> > > > >::check(const onnxruntime::utils::ContainerChecker::Cont &, size_t) [T = std::__1::map<std::__1::basic_string<char>, std::__1::basic_string<char>, std::__1::less<std::__1::basic_string<char> >, std::__1::allocator<std::__1::pair<const std::__1::basic_string<char>, std::__1::basic_string<char> > > >]Invalid index requested for map type.const T &OrtValue::Get() const [T = std::__1::map<std::__1::basic_string<char>, std::__1::basic_string<char>, std::__1::less<std::__1::basic_string<char> >, std::__1::allocator<std::__1::pair<const std::__1::basic_string<char>, std::__1::basic_string<char> > > >]static bool onnxruntime::utils::ContainerChecker::IsContainerOfType<std::__1::map<std::__1::basic_string<char>, long long, std::__1::less<std::__1::basic_string<char> >, std::__1::allocator<std::__1::pair<const std::__1::basic_string<char>, long long> > > >::check(const onnxruntime::utils::ContainerChecker::Cont &, size_t) [T = std::__1::map<std::__1::basic_string<char>, long long, std::__1::less<std::__1::basic_string<char> >, std::__1::allocator<std::__1::pair<const std::__1::basic_string<char>, long long> > >]const T &OrtValue::Get() const [T = std::__1::map<std::__1::basic_string<char>, long long, std::__1::less<std::__1::basic_string<char> >, std::__1::allocator<std::__1::pair<const std::__1::basic_string<char>, long long> > >]const T &OrtValue::Get() const [T = std::__1::map<std::__1::basic_string<char>, float, std::__1::less<std::__1::basic_string<char> >, std::__1::allocator<std::__1::pair<const std::__1::basic_string<char>, float> > >]static bool onnxruntime::utils::ContainerChecker::IsContainerOfType<std::__1::map<std::__1::basic_string<char>, double, std::__1::less<std::__1::basic_string<char> >, std::__1::allocator<std::__1::pair<const std::__1::basic_string<char>, double> > > >::check(const onnxruntime::utils::ContainerChecker::Cont &, size_t) [T = std::__1::map<std::__1::basic_string<char>, double, std::__1::less<std::__1::basic_string<char> >, std::__1::allocator<std::__1::pair<const std::__1::basic_string<char>, double> > >]const T &OrtValue::Get() const [T = std::__1::map<std::__1::basic_string<char>, double, std::__1::less<std::__1::basic_string<char> >, std::__1::allocator<std::__1::pair<const std::__1::basic_string<char>, double> > >]static bool onnxruntime::utils::ContainerChecker::IsContainerOfType<std::__1::map<long long, std::__1::basic_string<char>, std::__1::less<long long>, std::__1::allocator<std::__1::pair<const long long, std::__1::basic_string<char> > > > >::check(const onnxruntime::utils::ContainerChecker::Cont &, size_t) [T = std::__1::map<long long, std::__1::basic_string<char>, std::__1::less<long long>, std::__1::allocator<std::__1::pair<const long long, std::__1::basic_string<char> > > >]const T &OrtValue::Get() const [T = std::__1::map<long long, std::__1::basic_string<char>, std::__1::less<long long>, std::__1::allocator<std::__1::pair<const long long, std::__1::basic_string<char> > > >]static bool onnxruntime::utils::ContainerChecker::IsContainerOfType<std::__1::map<long long, long long, std::__1::less<long long>, std::__1::allocator<std::__1::pair<const long long, long long> > > >::check(const onnxruntime::utils::ContainerChecker::Cont &, size_t) [T = std::__1::map<long long, long long, std::__1::less<long long>, std::__1::allocator<std::__1::pair<const long long, long long> > >]const T &OrtValue::Get() const [T = std::__1::map<long long, long long, std::__1::less<long long>, std::__1::allocator<std::__1::pair<const long long, long long> > >]const T &OrtValue::Get() const [T = std::__1::map<long long, float, std::__1::less<long long>, std::__1::allocator<std::__1::pair<const long long, float> > >]static bool onnxruntime::utils::ContainerChecker::IsContainerOfType<std::__1::map<long long, double, std::__1::less<long long>, std::__1::allocator<std::__1::pair<const long long, double> > > >::check(const onnxruntime::utils::ContainerChecker::Cont &, size_t) [T = std::__1::map<long long, double, std::__1::less<long long>, std::__1::allocator<std::__1::pair<const long long, double> > >]const T &OrtValue::Get() const [T = std::__1::map<long long, double, std::__1::less<long long>, std::__1::allocator<std::__1::pair<const long long, double> > >]Number of values should be at least 1.For map type num_values MUST be 2Either the key tensor or the value tensor has NumDimensions > 1Key and value tensors have unequal number of elements.Key type is not supported yet.OrtStatus *OrtCreateValueImplMapHelper(const onnxruntime::Tensor &, const onnxruntime::Tensor &, OrtValue **) [KeyType = std::__1::basic_string<char>]value_type != nullptrTensor must always contain primitive types. Found: OrtStatus *OrtCreateMapMLValue(const onnxruntime::Tensor &, const onnxruntime::Tensor &, OrtValue **) [KeyType = std::__1::basic_string<char>, ValueType = std::__1::basic_string<char>]len >= 0 && static_cast<uint64_t>(len) < std::numeric_limits<size_t>::max()OrtStatus *OrtCreateMapMLValue(const onnxruntime::Tensor &, const onnxruntime::Tensor &, OrtValue **) [KeyType = std::__1::basic_string<char>, ValueType = long long]/Users/runner/work/1/s/include/onnxruntime/core/framework/tensor.hconst T *onnxruntime::Tensor::Data() const [T = long long]utils::IsPrimitiveDataType<T>(dtype_)Tensor type mismatch. T !=OrtStatus *OrtCreateMapMLValue(const onnxruntime::Tensor &, const onnxruntime::Tensor &, OrtValue **) [KeyType = std::__1::basic_string<char>, ValueType = float]const T *onnxruntime::Tensor::Data() const [T = float]OrtStatus *OrtCreateMapMLValue(const onnxruntime::Tensor &, const onnxruntime::Tensor &, OrtValue **) [KeyType = std::__1::basic_string<char>, ValueType = double]const T *onnxruntime::Tensor::Data() const [T = double]OrtStatus *OrtCreateValueImplMapHelper(const onnxruntime::Tensor &, const onnxruntime::Tensor &, OrtValue **) [KeyType = long long]OrtStatus *OrtCreateMapMLValue(const onnxruntime::Tensor &, const onnxruntime::Tensor &, OrtValue **) [KeyType = long long, ValueType = std::__1::basic_string<char>]OrtStatus *OrtCreateMapMLValue(const onnxruntime::Tensor &, const onnxruntime::Tensor &, OrtValue **) [KeyType = long long, ValueType = long long]OrtStatus *OrtCreateMapMLValue(const onnxruntime::Tensor &, const onnxruntime::Tensor &, OrtValue **) [KeyType = long long, ValueType = float]OrtStatus *OrtCreateMapMLValue(const onnxruntime::Tensor &, const onnxruntime::Tensor &, OrtValue **) [KeyType = long long, ValueType = double]Each element of the sequence should be either tensor or map.At least one element in the sequence is of a type different from others.Unsupported input typeOrtStatus *OrtCreateValueImplSeqHelper(const OrtValue *const *, size_t, OrtValue **)in[idx]->IsTensor()Expecting all elements to be tensors. Got: Sequences must have tensors of the same data type. There was at least one tensor in the input that was different.Encountered nullptr.const T *onnxruntime::Tensor::Data() const [T = bool]T *onnxruntime::Tensor::MutableData() [T = bool]T *onnxruntime::Tensor::MutableData() [T = float]T *onnxruntime::Tensor::MutableData() [T = double]const T *onnxruntime::Tensor::Data() const [T = onnxruntime::MLFloat16]T *onnxruntime::Tensor::MutableData() [T = onnxruntime::MLFloat16]const T *onnxruntime::Tensor::Data() const [T = onnxruntime::BFloat16]T *onnxruntime::Tensor::MutableData() [T = onnxruntime::BFloat16]const T *onnxruntime::Tensor::Data() const [T = signed char]T *onnxruntime::Tensor::MutableData() [T = signed char]const T *onnxruntime::Tensor::Data() const [T = unsigned char]T *onnxruntime::Tensor::MutableData() [T = unsigned char]const T *onnxruntime::Tensor::Data() const [T = short]T *onnxruntime::Tensor::MutableData() [T = short]const T *onnxruntime::Tensor::Data() const [T = unsigned short]T *onnxruntime::Tensor::MutableData() [T = unsigned short]const T *onnxruntime::Tensor::Data() const [T = int]T *onnxruntime::Tensor::MutableData() [T = int]const T *onnxruntime::Tensor::Data() const [T = unsigned int]T *onnxruntime::Tensor::MutableData() [T = unsigned int]T *onnxruntime::Tensor::MutableData() [T = long long]const T *onnxruntime::Tensor::Data() const [T = unsigned long long]T *onnxruntime::Tensor::MutableData() [T = unsigned long long]void onnxruntime::TensorSeq::SetType(onnxruntime::MLDataType)elem_type_ != nullptr was false. +1.8.1allocator<T>::allocate(size_t n) 'n' exceeds maximum supported sizeORT_LOAD_CONFIG_FROM_MODEL1/Users/runner/work/1/s/include/onnxruntime/core/framework/ml_value.honnxruntime::Tensor *OrtValue::GetMutable()IsTensor()Trying to get a Tensor, but got: const onnxruntime::Tensor &OrtValue::Get() constout of index/Users/runner/work/1/s/onnxruntime/core/common/safeint.hstatic void SafeIntExceptionHandler<onnxruntime::OnnxRuntimeException>::SafeIntOnOverflow()internal errorindex out of rangeconst onnxruntime::TensorSeq &OrtValue::Get() constIsTensorSequence()Trying to get a TensorSeq, but got: Input is not of one of the supported sequence types.Input is not of type sequence or map./Users/runner/work/1/s/include/onnxruntime/core/framework/data_types_internal.hstatic bool onnxruntime::utils::ContainerChecker::IsContainerOfType<std::__1::vector<std::__1::map<std::__1::basic_string<char>, float, std::__1::less<std::__1::basic_string<char> >, std::__1::allocator<std::__1::pair<const std::__1::basic_string<char>, float> > >, std::__1::allocator<std::__1::map<std::__1::basic_string<char>, float, std::__1::less<std::__1::basic_string<char> >, std::__1::allocator<std::__1::pair<const std::__1::basic_string<char>, float> > > > > >::check(const onnxruntime::utils::ContainerChecker::Cont &, size_t) [T = std::__1::vector<std::__1::map<std::__1::basic_string<char>, float, std::__1::less<std::__1::basic_string<char> >, std::__1::allocator<std::__1::pair<const std::__1::basic_string<char>, float> > >, std::__1::allocator<std::__1::map<std::__1::basic_string<char>, float, std::__1::less<std::__1::basic_string<char> >, std::__1::allocator<std::__1::pair<const std::__1::basic_string<char>, float> > > > >]++index < c.size()static bool onnxruntime::utils::ContainerChecker::IsContainerOfType<std::__1::map<std::__1::basic_string<char>, float, std::__1::less<std::__1::basic_string<char> >, std::__1::allocator<std::__1::pair<const std::__1::basic_string<char>, float> > > >::check(const onnxruntime::utils::ContainerChecker::Cont &, size_t) [T = std::__1::map<std::__1::basic_string<char>, float, std::__1::less<std::__1::basic_string<char> >, std::__1::allocator<std::__1::pair<const std::__1::basic_string<char>, float> > >]const T &OrtValue::Get() const [T = std::__1::vector<std::__1::map<std::__1::basic_string<char>, float, std::__1::less<std::__1::basic_string<char> >, std::__1::allocator<std::__1::pair<const std::__1::basic_string<char>, float> > >, std::__1::allocator<std::__1::map<std::__1::basic_string<char>, float, std::__1::less<std::__1::basic_string<char> >, std::__1::allocator<std::__1::pair<const std::__1::basic_string<char>, float> > > > >]onnxruntime::DataTypeImpl::GetType<T>() == type_ != static bool onnxruntime::utils::ContainerChecker::IsContainerOfType<std::__1::vector<std::__1::map<long long, float, std::__1::less<long long>, std::__1::allocator<std::__1::pair<const long long, float> > >, std::__1::allocator<std::__1::map<long long, float, std::__1::less<long long>, std::__1::allocator<std::__1::pair<const long long, float> > > > > >::check(const onnxruntime::utils::ContainerChecker::Cont &, size_t) [T = std::__1::vector<std::__1::map<long long, float, std::__1::less<long long>, std::__1::allocator<std::__1::pair<const long long, float> > >, std::__1::allocator<std::__1::map<long long, float, std::__1::less<long long>, std::__1::allocator<std::__1::pair<const long long, float> > > > >]static bool onnxruntime::utils::ContainerChecker::IsContainerOfType<std::__1::map<long long, float, std::__1::less<long long>, std::__1::allocator<std::__1::pair<const long long, float> > > >::check(const onnxruntime::utils::ContainerChecker::Cont &, size_t) [T = std::__1::map<long long, float, std::__1::less<long long>, std::__1::allocator<std::__1::pair<const long long, float> > >]const T &OrtValue::Get() const [T = std::__1::vector<std::__1::map<long long, float, std::__1::less<long long>, std::__1::allocator<std::__1::pair<const long long, float> > >, std::__1::allocator<std::__1::map<long long, float, std::__1::less<long long>, std::__1::allocator<std::__1::pair<const long long, float> > > > >]/Users/runner/work/1/s/onnxruntime/core/framework/TensorSeq.hconst onnxruntime::Tensor &onnxruntime::TensorSeq::Get(size_t) consti < tensors_.size()Input is not of one of the supported map types.static bool onnxruntime::utils::ContainerChecker::IsContainerOfType<std::__1::map<std::__1::basic_string<char>, std::__1::basic_string<char>, std::__1::less<std::__1::basic_string<char> >, std::__1::allocator<std::__1::pair<const std::__1::basic_string<char>, std::__1::basic_string<char> > > > >::check(const onnxruntime::utils::ContainerChecker::Cont &, size_t) [T = std::__1::map<std::__1::basic_string<char>, std::__1::basic_string<char>, std::__1::less<std::__1::basic_string<char> >, std::__1::allocator<std::__1::pair<const std::__1::basic_string<char>, std::__1::basic_string<char> > > >]Invalid index requested for map type.const T &OrtValue::Get() const [T = std::__1::map<std::__1::basic_string<char>, std::__1::basic_string<char>, std::__1::less<std::__1::basic_string<char> >, std::__1::allocator<std::__1::pair<const std::__1::basic_string<char>, std::__1::basic_string<char> > > >]static bool onnxruntime::utils::ContainerChecker::IsContainerOfType<std::__1::map<std::__1::basic_string<char>, long long, std::__1::less<std::__1::basic_string<char> >, std::__1::allocator<std::__1::pair<const std::__1::basic_string<char>, long long> > > >::check(const onnxruntime::utils::ContainerChecker::Cont &, size_t) [T = std::__1::map<std::__1::basic_string<char>, long long, std::__1::less<std::__1::basic_string<char> >, std::__1::allocator<std::__1::pair<const std::__1::basic_string<char>, long long> > >]const T &OrtValue::Get() const [T = std::__1::map<std::__1::basic_string<char>, long long, std::__1::less<std::__1::basic_string<char> >, std::__1::allocator<std::__1::pair<const std::__1::basic_string<char>, long long> > >]const T &OrtValue::Get() const [T = std::__1::map<std::__1::basic_string<char>, float, std::__1::less<std::__1::basic_string<char> >, std::__1::allocator<std::__1::pair<const std::__1::basic_string<char>, float> > >]static bool onnxruntime::utils::ContainerChecker::IsContainerOfType<std::__1::map<std::__1::basic_string<char>, double, std::__1::less<std::__1::basic_string<char> >, std::__1::allocator<std::__1::pair<const std::__1::basic_string<char>, double> > > >::check(const onnxruntime::utils::ContainerChecker::Cont &, size_t) [T = std::__1::map<std::__1::basic_string<char>, double, std::__1::less<std::__1::basic_string<char> >, std::__1::allocator<std::__1::pair<const std::__1::basic_string<char>, double> > >]const T &OrtValue::Get() const [T = std::__1::map<std::__1::basic_string<char>, double, std::__1::less<std::__1::basic_string<char> >, std::__1::allocator<std::__1::pair<const std::__1::basic_string<char>, double> > >]static bool onnxruntime::utils::ContainerChecker::IsContainerOfType<std::__1::map<long long, std::__1::basic_string<char>, std::__1::less<long long>, std::__1::allocator<std::__1::pair<const long long, std::__1::basic_string<char> > > > >::check(const onnxruntime::utils::ContainerChecker::Cont &, size_t) [T = std::__1::map<long long, std::__1::basic_string<char>, std::__1::less<long long>, std::__1::allocator<std::__1::pair<const long long, std::__1::basic_string<char> > > >]const T &OrtValue::Get() const [T = std::__1::map<long long, std::__1::basic_string<char>, std::__1::less<long long>, std::__1::allocator<std::__1::pair<const long long, std::__1::basic_string<char> > > >]static bool onnxruntime::utils::ContainerChecker::IsContainerOfType<std::__1::map<long long, long long, std::__1::less<long long>, std::__1::allocator<std::__1::pair<const long long, long long> > > >::check(const onnxruntime::utils::ContainerChecker::Cont &, size_t) [T = std::__1::map<long long, long long, std::__1::less<long long>, std::__1::allocator<std::__1::pair<const long long, long long> > >]const T &OrtValue::Get() const [T = std::__1::map<long long, long long, std::__1::less<long long>, std::__1::allocator<std::__1::pair<const long long, long long> > >]const T &OrtValue::Get() const [T = std::__1::map<long long, float, std::__1::less<long long>, std::__1::allocator<std::__1::pair<const long long, float> > >]static bool onnxruntime::utils::ContainerChecker::IsContainerOfType<std::__1::map<long long, double, std::__1::less<long long>, std::__1::allocator<std::__1::pair<const long long, double> > > >::check(const onnxruntime::utils::ContainerChecker::Cont &, size_t) [T = std::__1::map<long long, double, std::__1::less<long long>, std::__1::allocator<std::__1::pair<const long long, double> > >]const T &OrtValue::Get() const [T = std::__1::map<long long, double, std::__1::less<long long>, std::__1::allocator<std::__1::pair<const long long, double> > >]Number of values should be at least 1.For map type num_values MUST be 2Either the key tensor or the value tensor has NumDimensions > 1Key and value tensors have unequal number of elements.Key type is not supported yet.OrtStatus *OrtCreateValueImplMapHelper(const onnxruntime::Tensor &, const onnxruntime::Tensor &, OrtValue **) [KeyType = std::__1::basic_string<char>]value_type != nullptrTensor must always contain primitive types. Found: OrtStatus *OrtCreateMapMLValue(const onnxruntime::Tensor &, const onnxruntime::Tensor &, OrtValue **) [KeyType = std::__1::basic_string<char>, ValueType = std::__1::basic_string<char>]len >= 0 && static_cast<uint64_t>(len) < std::numeric_limits<size_t>::max()OrtStatus *OrtCreateMapMLValue(const onnxruntime::Tensor &, const onnxruntime::Tensor &, OrtValue **) [KeyType = std::__1::basic_string<char>, ValueType = long long]/Users/runner/work/1/s/include/onnxruntime/core/framework/tensor.hconst T *onnxruntime::Tensor::Data() const [T = long long]utils::IsPrimitiveDataType<T>(dtype_)Tensor type mismatch. T !=OrtStatus *OrtCreateMapMLValue(const onnxruntime::Tensor &, const onnxruntime::Tensor &, OrtValue **) [KeyType = std::__1::basic_string<char>, ValueType = float]const T *onnxruntime::Tensor::Data() const [T = float]OrtStatus *OrtCreateMapMLValue(const onnxruntime::Tensor &, const onnxruntime::Tensor &, OrtValue **) [KeyType = std::__1::basic_string<char>, ValueType = double]const T *onnxruntime::Tensor::Data() const [T = double]OrtStatus *OrtCreateValueImplMapHelper(const onnxruntime::Tensor &, const onnxruntime::Tensor &, OrtValue **) [KeyType = long long]OrtStatus *OrtCreateMapMLValue(const onnxruntime::Tensor &, const onnxruntime::Tensor &, OrtValue **) [KeyType = long long, ValueType = std::__1::basic_string<char>]OrtStatus *OrtCreateMapMLValue(const onnxruntime::Tensor &, const onnxruntime::Tensor &, OrtValue **) [KeyType = long long, ValueType = long long]OrtStatus *OrtCreateMapMLValue(const onnxruntime::Tensor &, const onnxruntime::Tensor &, OrtValue **) [KeyType = long long, ValueType = float]OrtStatus *OrtCreateMapMLValue(const onnxruntime::Tensor &, const onnxruntime::Tensor &, OrtValue **) [KeyType = long long, ValueType = double]Each element of the sequence should be either tensor or map.At least one element in the sequence is of a type different from others.Unsupported input typeOrtStatus *OrtCreateValueImplSeqHelper(const OrtValue *const *, size_t, OrtValue **)in[idx]->IsTensor()Expecting all elements to be tensors. Got: Sequences must have tensors of the same data type. There was at least one tensor in the input that was different.Encountered nullptr.const T *onnxruntime::Tensor::Data() const [T = bool]T *onnxruntime::Tensor::MutableData() [T = bool]T *onnxruntime::Tensor::MutableData() [T = float]T *onnxruntime::Tensor::MutableData() [T = double]const T *onnxruntime::Tensor::Data() const [T = onnxruntime::MLFloat16]T *onnxruntime::Tensor::MutableData() [T = onnxruntime::MLFloat16]const T *onnxruntime::Tensor::Data() const [T = onnxruntime::BFloat16]T *onnxruntime::Tensor::MutableData() [T = onnxruntime::BFloat16]const T *onnxruntime::Tensor::Data() const [T = signed char]T *onnxruntime::Tensor::MutableData() [T = signed char]const T *onnxruntime::Tensor::Data() const [T = unsigned char]T *onnxruntime::Tensor::MutableData() [T = unsigned char]const T *onnxruntime::Tensor::Data() const [T = short]T *onnxruntime::Tensor::MutableData() [T = short]const T *onnxruntime::Tensor::Data() const [T = unsigned short]T *onnxruntime::Tensor::MutableData() [T = unsigned short]const T *onnxruntime::Tensor::Data() const [T = int]T *onnxruntime::Tensor::MutableData() [T = int]const T *onnxruntime::Tensor::Data() const [T = unsigned int]T *onnxruntime::Tensor::MutableData() [T = unsigned int]T *onnxruntime::Tensor::MutableData() [T = long long]const T *onnxruntime::Tensor::Data() const [T = unsigned long long]T *onnxruntime::Tensor::MutableData() [T = unsigned long long]void onnxruntime::TensorSeq::SetType(onnxruntime::MLDataType)elem_type_ != nullptr was false. Stacktrace: -:/\T *onnxruntime::Tensor::MutableData() [T = std::__1::basic_string<char>]const T *onnxruntime::Tensor::Data() const [T = std::__1::basic_string<char>]/Users/runner/work/1/s/onnxruntime/core/session/ort_env.ccstatic void OrtEnv::Release(OrtEnv *)env_ptr == p_instance_/Users/runner/work/1/s/onnxruntime/core/optimizer/attention_fusion_helper.hbool onnxruntime::AttentionFusionHelper::CheckSliceParameters(const onnxruntime::Graph &, const onnxruntime::Node &, const std::vector<int> &, const std::vector<int64_t> &, const logging::Logger &)input_indices.size() == expected_values.size() && input_indices.size() > 0CheckSliceParametersSlice does not have enough number of inputsSlice ends is less than INT_MAXSlice parameter is not expected. Input index:Expected value:MatchGemmSubgraphStart MatchGemmSubgraphFaild to match gemm pathInput of reshape_before_gemm is not the input of subgraphOutput edge count not expected for nodes in gemm pathGemm does not have 3 inputsGemm bias is not constantGemm bias shape not expectedCheckSliceParameters return falseconcat first input value is not -1Faild to match concat node for Gather pathsconcat_after_gather does not have expected number of inputs or output edgesconcat_after_gather input 2 does not have expected valueFaild to match gemm gather pathOutput edge count not expected for nodes in gemm gather pathunsqueeze_after_gather axes value not expectedgather axis value not expectedgather input 1 value is not expectedPass MatchGemmSubgraphValidateGemmInitializerStart ValidateGemmInitializerGemm bias is not constant initializerGemm bias shape is not expectedGemm weight is not constant initializerGemm weight shape is not expectedPass ValidateGemmInitializerValidateUnidirMaskunidir mask is not constantunidir mask shape not expectedThis optimizer does not support external data for unidirectional mask right nowMask is neither unidirectional nor all onesExpect mask data type is uint8 or floatMatchUnidirMaskSubgraphStart MatchUnidirMaskSubgraphFaild to match the path (Div-->Where-->Add) for unidirectional maskFaild to match path 1 for unidirectional maskOutput edge count not expected for nodes in path 1 of unidirectional maskDiv and Shape1 does not have edgeCheckSliceParameters returns false for last_sliceCheckSliceParameters returns false for mask_sliceValidateUnidirMask returns false for mask_sliceCheckSliceParameters returns false for slice1Faild to match path 2 for unidirectional maskOutput edge count not expected for unsqueeze2 of unidirectional maskFaild to match path 3 for unidirectional maskOutput edge count not expected for unsqueeze3 of unidirectional maskFaild to match path 4 for unidirectional maskDiv and Shape does not have edgeOutput edge count not expected for squeeze_2/slices2/shape2 of unidirectional maskCheckSliceParameters return false for slice2Pass MatchUnidirMaskSubgraphMatchInputMaskSubgraphStart MatchInputMaskSubgraphFailed to find Softmax nodeOutput edge count not expected for SoftmaxFailed to find path for maskOutput edge count not expected for mask nodesSoftmax attribute axis is expected to be 3mask_unsqueeze_1 axes not matched. Expect: 1mask_unsqueeze_2 axes not matched. Expect: 2mask_sub const input not matchedmask_mul const input not matchedPass MatchInputMaskSubgraphStart MatchInputMaskSubgraphDistilBertFailed to find mask pathwhere const not matched.Failed to find shape pathequal const not matched.Failed to find reshape shape path 1Failed to find reshape shape path 2gather indices not matched.Pass MatchInputMaskSubgraphDistilBertMatchPastSubgraphStart MatchPastSubgraphFailed to find path for past_kFailed to find path for present_kFailed to find path for present_v and past_vFailed to match v_concatpast_k_transpose perm attribute not matchedpresent_k_transpose perm attribute not matchedpresent_k_unsqueeze axes value not expectedpresent_v_unsqueeze axes value not expectedpast_v_gather indices != 1past_k_gather indices != 0past_v_gather and past_k_gather does not have same past inputOutput edge count not expected for nodes in past subgraphPass MatchPastSubgraphCheckDistilBertReshapeShapeCheckNodesInPathVStart CheckNodesInPathVOutput edge count not expected for nodes in path vFailed in match Transpose attribute perm. Expected: 0, 2, 1, 3Failed in match v_transpose attribute perm. Expected: 0, 2, 1, 3hidden_size != num_heads * head_sizev_reshape initializer value is not expectedPass CheckNodesInPathVreshape initializer value is not expectedCheckNodesInPathQStart CheckNodesInPathQq_reshape const not matchedqk_div const not matched.q_transpose perm attribute not matchedPass CheckNodesInPathQCheckNodesInPathKStart CheckNodesInPathKk_transpose perm attribute not matchedk_reshape const not matchedPass CheckNodesInPathKFuseGptAttentionStart FuseGptAttentionFaild to find path to qkv_matmulFaild to find path v to SplitCheckNodesInPathV return falseMatchInputMaskSubgraph returns falseMatchUnidirMaskSubgraph returns NULLFailed to find path for qq and v are not from same Split nodeCheckNodesInPathQ returns falseFailed to find path for kk and v are not from same Split nodeCheckNodesInPathK returns falseMatchPastSubgraph returns falseFused an attention node for GPT./Users/runner/work/1/s/onnxruntime/core/optimizer/attention_fusion.ccshape of layer norm bias tensor not expectedTotal fused Attention node count: FuseSubGraphFaild to find path vOutput edge count not expected for Add or MatMul in path vFailed in match v_matmul and v_add input shapeFailed in match input mask subgraphFuseSubGraphQKFused an attention node.FuseSubGraphQKImplq root should be layer normalizationq_matmul and q_add shape not matchedk root is not layer normk_matmul and k_add shape not matchedFailed to load Q, K and V weights, or data type is not float or float16.Failed to load Q, K and V bias tensors, or data type is not float or float16.Failed to convert mask to int32ConvertMaskToInt32Mask shape is unknown or not 2D, or data type unknownMask data type is not int32 or int64 or float32qkv_weightsqkv_biasFuseSubGraphQKDistilBert/Users/runner/work/1/s/onnxruntime/core/optimizer/bias_dropout_fusion.cc/Users/runner/work/1/s/onnxruntime/core/optimizer/bias_gelu_fusion.cc/Users/runner/work/1/s/onnxruntime/core/optimizer/bias_softmax_fusion.ccfused into softmax(input + bias)/Users/runner/work/1/s/onnxruntime/core/optimizer/common_subexpression_elimination.ccvirtual onnxruntime::common::Status onnxruntime::CommonSubexpressionElimination::ApplyImpl(onnxruntime::Graph &, bool &, int, const logging::Logger &) constrepresentative.output_index != kInvalidOutputIndexNot eliminating output of node ] because it's the graph's output./Users/runner/work/1/s/onnxruntime/core/optimizer/constant_folding.ccCould not find a CPU kernel and hence can't constant fold node 'virtual onnxruntime::common::Status onnxruntime::ConstantFolding::ApplyImpl(onnxruntime::Graph &, bool &, int, const logging::Logger &) constfetches.size() == node->OutputDefs().size()Unsupported output type of . Can't constant fold /Users/runner/work/1/s/onnxruntime/core/optimizer/conv_activation_fusion.ccfused Conv with activation auto onnxruntime::(anonymous namespace)::GetClipConstantMinMax(const onnxruntime::Graph &, const onnxruntime::Node &, float &, float &)::(anonymous class)::operator()(const onnxruntime::Node &, size_t, float &) constUnexpected data type for Clip input of /Users/runner/work/1/s/onnxruntime/core/optimizer/conv_add_fusion.ccvirtual onnxruntime::common::Status onnxruntime::ConvAddFusion::Apply(onnxruntime::Graph &, onnxruntime::Node &, onnxruntime::RewriteRule::RewriteRuleEffect &, const logging::Logger &) constadd_B_tensor_protoConvAddFusion_B_ConvAddFusion_Add_B_/Users/runner/work/1/s/onnxruntime/core/optimizer/conv_bn_fusion.ccvirtual onnxruntime::common::Status onnxruntime::ConvBNFusion::Apply(onnxruntime::Graph &, onnxruntime::Node &, onnxruntime::RewriteRule::RewriteRuleEffect &, const logging::Logger &) constbn_scale_tensor_protobn_B_tensor_protobn_mean_tensor_protobn_var_tensor_protoconv_W_tensor_protoconv_B_tensor_protoConvBnFusion_W_ConvBnFusion_BN_B_/Users/runner/work/1/s/onnxruntime/core/optimizer/initializer.honnxruntime::Initializer::Initializer(const onnx::TensorProto &, const onnxruntime::Path &)size_ == sizeInitializerunsupported data type: ReadExternalRawData() failed: ToProtodata type is not supported/Users/runner/work/1/s/onnxruntime/core/optimizer/conv_mul_fusion.ccvirtual onnxruntime::common::Status onnxruntime::ConvMulFusion::Apply(onnxruntime::Graph &, onnxruntime::Node &, onnxruntime::RewriteRule::RewriteRuleEffect &, const logging::Logger &) constmul_B_tensor_protoConvMulFusion_W_ConvMulFusion_Mul_B_/Users/runner/work/1/s/onnxruntime/core/optimizer/dynamic_quantize_matmul_fusion.cc/Users/runner/work/1/s/onnxruntime/core/optimizer/embed_layer_norm_fusion.ccFuseSubGraphDistilBertWord embedding shape not expected.Failed to match position embedding subgraph.Failed to get position embedding weights.Position embedding shape is not expected.Input id is not valid. Gamma should be of shape (hidden_size). Beta should be of shape (hidden_size). MatchPositionEmbeddingSubgraphsFromGatherOutput edge count not expected for nodes in path1.The first input of Range should be a constant with value 0.The third input of Range should be a constant with value 1.Second input of Gather should be a constant with value 1. Failed to match Shape node. The parent of shape nodes are expected to be input_ids.Optional position subgraph nodes number of outputs unexpected.Optional position subgraph nodes Where node is expected to be the parent of Reshape.Failed to match position subgraph.MatchInputToConcatSubgraphFailed to find path 1 of position shape.Output edge count not expected for nodes in path 1 of position shape.Second input of Gather in path 1 of position shape should be a constant with value 0.Failed to find path 2 of position shape.Output edge count not expected for nodes in path 2 of position shape.Gather node in path 2 is not linked to another subgraph.Second input of Gather in path 2 of position shape should be a constant with value 1.The parent of two shape nodes are expected to be input_ids.two paths share the same shapeCheckInputInput shape is unknown or not 2D, or data type unknownInput data type is not int32 or int64_Int32_CastInput is expected to have dim value in all dimensions.Failed to get initializer tensor.Position embedding shape not matched.Position embedding data type shall be float or float16.Segment id is not valid. Input_ids and segment id should have the same shape. /Users/runner/work/1/s/onnxruntime/core/optimizer/fast_gelu_fusion.cc/Users/runner/work/1/s/onnxruntime/core/optimizer/free_dim_override_transformer.cconnxruntime::FreeDimensionOverrideTransformer::FreeDimensionOverrideTransformer(gsl::span<const FreeDimensionOverride>)Invalid free dimension override.Conflicting free dimension overrides.The model has input '' with a fixed dimension size which does not equal the specified override of /Users/runner/work/1/s/onnxruntime/core/optimizer/gelu_approximation.ccTotal Gelu Approximation (FastGelu) node count: /Users/runner/work/1/s/onnxruntime/core/optimizer/gelu_fusion.cc/Users/runner/work/1/s/onnxruntime/core/optimizer/gemm_activation_fusion.ccfused Gemm _transformed/Users/runner/work/1/s/onnxruntime/core/optimizer/graph_transformer.ccApply/Users/runner/work/1/s/onnxruntime/core/optimizer/graph_transformer_mgr.ccApplyTransformersThis transformer is already registered Level_RuleBasedTransformer/Users/runner/work/1/s/onnxruntime/core/optimizer/graph_transformer_utils.ccstd::vector<std::unique_ptr<RewriteRule> > onnxruntime::optimizer_utils::GenerateRewriteRules(onnxruntime::TransformerLevel, const std::unordered_set<std::string> &)Unsupported levelstd::vector<std::unique_ptr<GraphTransformer> > onnxruntime::optimizer_utils::GenerateTransformers(onnxruntime::TransformerLevel, const onnxruntime::SessionOptions &, const onnxruntime::IExecutionProvider &, const std::unordered_set<std::string> &)Unsupported level YieldOp/Users/runner/work/1/s/onnxruntime/core/optimizer/initializer.ccReadExternalRawDataExternal data type must not be UNDEFINED or STRING.model_path must not be empty. Ensure that a path is provided when the model is created or loaded.TensorProto external data size mismatch. Computed size: /Users/runner/work/1/s/onnxruntime/core/optimizer/insert_cast_transformer.ccvirtual onnxruntime::common::Status onnxruntime::InsertCastTransformer::ApplyImpl(onnxruntime::Graph &, bool &, int, const logging::Logger &) constdtype_attribute->second.has_i()InsertCastTransformer works on the assumption that `dtype` attribute holds an integer./Users/runner/work/1/s/onnxruntime/core/optimizer/layer_norm_fusion.cc/Users/runner/work/1/s/onnxruntime/core/optimizer/matmul_add_fusion.ccfused Matmul and Add /Users/runner/work/1/s/onnxruntime/core/optimizer/matmul_integer_to_float.cc/Users/runner/work/1/s/onnxruntime/core/optimizer/matmul_scale_fusion.cc_FusedMatMulAndScalestd::vector<ScaleMergeInfo> onnxruntime::(anonymous namespace)::GetInputNodeMerges(onnxruntime::Graph &, onnxruntime::Node &, const std::unordered_set<std::string> &)input_node.InputDefs().size() == 2 && scale_and_index.value().second < 2optional<std::pair<float, int> > onnxruntime::(anonymous namespace)::GetScaleFromNode(const onnxruntime::Graph &, const onnxruntime::Node &, const std::unordered_set<std::string> &)div_inputs.size() == 2mul_inputs.size() == 2optional<float> onnxruntime::(anonymous namespace)::GetScalarConstantInitializer(const onnxruntime::Graph &, const onnxruntime::NodeArg &)Constant initializer NodeArg shape should not be null. NodeArg: GetScalarConstantInitializerstd::vector<ScaleMergeInfo> onnxruntime::(anonymous namespace)::GetOutputNodeMerges(onnxruntime::Graph &, onnxruntime::Node &, const std::unordered_set<std::string> &)output_node.OutputDefs().size() == 1/Users/runner/work/1/s/onnxruntime/core/optimizer/matmul_transpose_fusion.ccbool onnxruntime::GetTransposePerms(const onnxruntime::Node &, std::vector<int64_t> &)transpose_node.InputDefs().size() == 1onnxruntime::Node *onnxruntime::ReorderCastAndTranspose(onnxruntime::Graph &, onnxruntime::Node *, std::unordered_map<NodeArg *, size_t> &, std::deque<onnxruntime::NodeIndex> &)cast != nullptrCreated a new Transpose node to interchange Cast and Transpose nodessize_t onnxruntime::UpdateConsumerCount(onnxruntime::Graph &, onnxruntime::NodeArg *, std::unordered_map<NodeArg *, size_t> &)!node_consumers.empty()_nchwc_bn_nchwc/Users/runner/work/1/s/onnxruntime/core/optimizer/nchwc_transformer.cc_nhwc/Users/runner/work/1/s/onnxruntime/core/optimizer/nhwc_transformer.cc/Users/runner/work/1/s/onnxruntime/core/optimizer/optimizer_execution_frame.cconnxruntime::OptimizerExecutionFrame::Info::Info(const std::vector<const Node *> &, const onnxruntime::InitializedTensorSet &, const onnxruntime::Path &, const onnxruntime::IExecutionProvider &)allocator_ptr_InfoQLinear855dd0fa-cd7b-4b10-ae5a-df64cabfe1f835b188f7-c464-43e3-8692-97ac832bb14a/Users/runner/work/1/s/onnxruntime/core/optimizer/qdq_transformer/qdq_propagation.ccvoid onnxruntime::SwapAdjacentNodes(onnxruntime::Graph &, onnxruntime::Node &, onnxruntime::Node &)optimizer_utils::CheckOutputEdges(graph, up_node, 1)up_node should have only one Edge that points to down_node and its output is not graph outputedge_it->GetDstArgIndex() == 0 && edge_it->GetSrcArgIndex() == 0 && edge_it->GetNode().Index() == down_node.Index()up_node should be parent of down_node and NodeArg slots of the edge between up_node and down_node should be (0, 0)./Users/runner/work/1/s/onnxruntime/core/optimizer/qdq_transformer/qdq_s8_to_u8.cc/Users/runner/work/1/s/onnxruntime/core/optimizer/qdq_transformer/qdq_transformer.cc/Users/runner/work/1/s/onnxruntime/core/optimizer/relu_clip_fusion.ccvirtual onnxruntime::common::Status onnxruntime::FuseReluClip::Apply(onnxruntime::Graph &, onnxruntime::Node &, onnxruntime::RewriteRule::RewriteRuleEffect &, const logging::Logger &) constUnexpected data type for Clip 'min' input of FuseReluClip__min_zero_constantonnxruntime::Initializer::Initializer(onnx::TensorProto_DataType, const std::string &, const std::vector<int64_t> &)data type is not supported./Users/runner/work/1/s/onnxruntime/core/optimizer/reshape_fusion.ccFused reshape node: Total fused reshape node count: Fuse_SubgraphCannot replace concat node with initializer:/Users/runner/work/1/s/onnxruntime/core/optimizer/rule_based_graph_transformer.ccApplyRulesOnNode/Users/runner/work/1/s/onnxruntime/core/optimizer/skip_layer_norm_fusion.cc/Users/runner/work/1/s/onnxruntime/core/optimizer/transformer_memcpy.ccApplyImplvoid onnxruntime::TransformerMemcpyImpl::ProcessDefs(onnxruntime::Node &, const onnxruntime::KernelRegistryManager &, onnxruntime::InitializedTensorSet &)Execution type '' doesn't support memcpy bool onnxruntime::TransformerMemcpyImpl::ProcessInitializers(const onnxruntime::KernelRegistryManager &, const onnxruntime::InitializedTensorSet &)/Users/runner/work/1/s/include/onnxruntime/core/optimizer/graph_transformer.hRecurseauto onnxruntime::TransformerMemcpyImpl::ProcessInitializers(const onnxruntime::KernelRegistryManager &, const onnxruntime::InitializedTensorSet &)::(anonymous class)::operator()(const onnxruntime::NodeArg &, size_t) constdup_replacements.find(&arg) == dup_replacements.end()UnsqueezeElimination_/Users/runner/work/1/s/onnxruntime/core/optimizer/unsqueeze_elimination.ccUnsqueezeElimination cannot remove node MIGraphXExecutionProviderROCMExecutionProviderOpenVINOExecutionProviderDnnlExecutionProviderNupharExecutionProviderVitisAIExecutionProviderNnapiExecutionProviderArmNNExecutionProviderACLExecutionProviderRknpuExecutionProviderCeluEluHardSigmoidLeakyReluSoftplusReluSigmoidSoftsignTanhThresholdedReluSeluParametricSoftplusScaledTanhunknown kernel typeonnxruntime::ElementWiseKernel<onnxruntime::functors::Elu<float> >::ElementWiseKernel(const onnxruntime::OpKernelInfo &) [F = onnxruntime::functors::Elu<float>]virtual onnxruntime::common::Status onnxruntime::ElementWiseKernel<onnxruntime::functors::Elu<float> >::Compute(onnxruntime::OpKernelContext *) const [F = onnxruntime::functors::Elu<float>]onnxruntime::ElementWiseKernel<onnxruntime::functors::HardSigmoid<float> >::ElementWiseKernel(const onnxruntime::OpKernelInfo &) [F = onnxruntime::functors::HardSigmoid<float>]virtual onnxruntime::common::Status onnxruntime::ElementWiseKernel<onnxruntime::functors::HardSigmoid<float> >::Compute(onnxruntime::OpKernelContext *) const [F = onnxruntime::functors::HardSigmoid<float>]onnxruntime::ElementWiseKernel<onnxruntime::functors::LeakyRelu<float> >::ElementWiseKernel(const onnxruntime::OpKernelInfo &) [F = onnxruntime::functors::LeakyRelu<float>]virtual onnxruntime::common::Status onnxruntime::ElementWiseKernel<onnxruntime::functors::LeakyRelu<float> >::Compute(onnxruntime::OpKernelContext *) const [F = onnxruntime::functors::LeakyRelu<float>]virtual onnxruntime::common::Status onnxruntime::ElementWiseKernel<onnxruntime::functors::Relu<float> >::Compute(onnxruntime::OpKernelContext *) const [F = onnxruntime::functors::Relu<float>]virtual onnxruntime::common::Status onnxruntime::ElementWiseKernel<onnxruntime::functors::Relu<double> >::Compute(onnxruntime::OpKernelContext *) const [F = onnxruntime::functors::Relu<double>]virtual onnxruntime::common::Status onnxruntime::ElementWiseKernel<onnxruntime::functors::Relu<signed char> >::Compute(onnxruntime::OpKernelContext *) const [F = onnxruntime::functors::Relu<signed char>]virtual onnxruntime::common::Status onnxruntime::ElementWiseKernel<onnxruntime::functors::Relu<int> >::Compute(onnxruntime::OpKernelContext *) const [F = onnxruntime::functors::Relu<int>]onnxruntime::ElementWiseKernel<onnxruntime::functors::Selu<float> >::ElementWiseKernel(const onnxruntime::OpKernelInfo &) [F = onnxruntime::functors::Selu<float>]virtual onnxruntime::common::Status onnxruntime::ElementWiseKernel<onnxruntime::functors::Selu<float> >::Compute(onnxruntime::OpKernelContext *) const [F = onnxruntime::functors::Selu<float>]virtual onnxruntime::common::Status onnxruntime::ElementWiseKernel<onnxruntime::functors::Sigmoid<float> >::Compute(onnxruntime::OpKernelContext *) const [F = onnxruntime::functors::Sigmoid<float>]virtual onnxruntime::common::Status onnxruntime::ElementWiseKernel<onnxruntime::functors::Sigmoid<double> >::Compute(onnxruntime::OpKernelContext *) const [F = onnxruntime::functors::Sigmoid<double>]virtual onnxruntime::common::Status onnxruntime::ElementWiseKernel<onnxruntime::functors::Softplus<float> >::Compute(onnxruntime::OpKernelContext *) const [F = onnxruntime::functors::Softplus<float>]virtual onnxruntime::common::Status onnxruntime::ElementWiseKernel<onnxruntime::functors::Softsign<float> >::Compute(onnxruntime::OpKernelContext *) const [F = onnxruntime::functors::Softsign<float>]virtual onnxruntime::common::Status onnxruntime::ElementWiseKernel<onnxruntime::functors::Tanh<float> >::Compute(onnxruntime::OpKernelContext *) const [F = onnxruntime::functors::Tanh<float>]virtual onnxruntime::common::Status onnxruntime::ElementWiseKernel<onnxruntime::functors::Tanh<double> >::Compute(onnxruntime::OpKernelContext *) const [F = onnxruntime::functors::Tanh<double>]onnxruntime::ElementWiseKernel<onnxruntime::functors::Celu<float> >::ElementWiseKernel(const onnxruntime::OpKernelInfo &) [F = onnxruntime::functors::Celu<float>]virtual onnxruntime::common::Status onnxruntime::ElementWiseKernel<onnxruntime::functors::Celu<float> >::Compute(onnxruntime::OpKernelContext *) const [F = onnxruntime::functors::Celu<float>]onnxruntime::ElementWiseKernel<onnxruntime::functors::ThresholdedRelu<float> >::ElementWiseKernel(const onnxruntime::OpKernelInfo &) [F = onnxruntime::functors::ThresholdedRelu<float>]virtual onnxruntime::common::Status onnxruntime::ElementWiseKernel<onnxruntime::functors::ThresholdedRelu<float> >::Compute(onnxruntime::OpKernelContext *) const [F = onnxruntime::functors::ThresholdedRelu<float>]alphaNo attribute with name:''is defined.Attribute name and type don't match for '/Users/runner/work/1/s/onnxruntime/core/providers/cpu/activation/activations.hInitgamma/Users/runner/work/1/s/onnxruntime/contrib_ops/cpu/activations.hBVIf/Users/runner/work/1/s/onnxruntime/core/providers/cpu/controlflow/if.cconnxruntime::If::Info::Info(const onnxruntime::Node &, const onnxruntime::GraphViewer &)num_subgraph_outputs == static_cast<size_t>(num_outputs)'If' node has outputs which doesn't match the subgraph's outputs.then_branchvoid onnxruntime::If::Init(const onnxruntime::OpKernelInfo &)info.GetAttr<ONNX_NAMESPACE::GraphProto>("then_branch", &proto).IsOK()else_branchinfo.GetAttr<ONNX_NAMESPACE::GraphProto>("else_branch", &proto).IsOK()virtual common::Status onnxruntime::If::SetupSubgraphExecutionInfo(const onnxruntime::SessionState &, const std::string &, const onnxruntime::SessionState &)info == nullptrSetupSubgraphExecutionInfo should only be called once for each subgraph.SetupSubgraphExecutionInfovirtual onnxruntime::common::Status onnxruntime::If::Compute(onnxruntime::OpKernelContext *) constthen_feeds_fetches_manager_ && else_feeds_fetches_manager_CreateFeedsFetchesManager must be called prior to execution of graph.session_stateSubgraph SessionState was not found for '' attribute.ComputeFailed to create output tensor for Executeonnxruntime::TensorSeq *OrtValue::GetMutable()Failed to create output tensor for If output ILoop/Users/runner/work/1/s/onnxruntime/core/providers/cpu/controlflow/loop.cconnxruntime::Loop::Info::Info(const onnxruntime::Node &, const onnxruntime::GraphViewer &)static_cast<size_t>(num_subgraph_inputs) == subgraph_inputs.size()Graph in 'body' attribute of Loop should have inputs. Found:num_subgraph_outputs - 1 == num_outputs'Loop' node has outputs so the subgraph requires but has void onnxruntime::Loop::Init(const onnxruntime::OpKernelInfo &)info.GetAttr<ONNX_NAMESPACE::GraphProto>("body", &proto).IsOK()virtual common::Status onnxruntime::Loop::SetupSubgraphExecutionInfo(const onnxruntime::SessionState &, const std::string &, const onnxruntime::SessionState &)info_ == nullptrvirtual onnxruntime::common::Status onnxruntime::Loop::Compute(onnxruntime::OpKernelContext *) constfeeds_fetches_manager_'Loop' input 'M' should be a scalar tensor. Got shape of 'Loop' input 'cond' should be a scalar tensor. Got shape of Loop subgraph input 0 has unknown shape: Loop subgraph input 1 has unknown shape: void onnxruntime::LoopImpl::SaveOutputsAndUpdateFeeds(const std::vector<OrtValue> &, std::vector<OrtValue> &)last_outputs[j + 1].IsTensor()ConcatenateLoopOutputLoop had zero iterations and the shape of subgraph output was not found. Defaulting to a rank 1 shape of {0}.Inconsistent shape in loop output for output. Expected: Got:auto onnxruntime::LoopImpl::Execute(const onnxruntime::FeedsFetchesManager &)::(anonymous class)::operator()(const OrtValue &, int) const/Users/runner/work/1/s/onnxruntime/core/providers/cpu/controlflow/scan_8.ccvoid onnxruntime::Scan<8>::Init(const onnxruntime::OpKernelInfo &) [OpSet = 8]directionsvirtual onnxruntime::common::Status onnxruntime::Scan<8>::SetupSubgraphExecutionInfo(const onnxruntime::SessionState &, const std::string &, const onnxruntime::SessionState &) [OpSet = 8]virtual onnxruntime::common::Status onnxruntime::Scan<8>::Compute(onnxruntime::OpKernelContext *) const [OpSet = 8]Scan inputs have inconsistent batch size. Previous value was but has batch size of sequence_lens length of did not match batch size of Invalid entries in sequence_lens. Max sequence length was onnxruntime::common::Status onnxruntime::Scan8Impl::CreateLoopStateVariables(std::vector<std::vector<LoopStateVariable> > &)p_mlvalueScan<8> spec does not support transpose of output. This should never be called./Users/runner/work/1/s/onnxruntime/core/framework/ort_value_tensor_slicer.htypename std::enable_if<!std::is_const<reference>::value, reference>::type onnxruntime::OrtValueTensorSlicer<const OrtValue>::Iterator::operator*() [T = const OrtValue]position_ >= 0 && position_ < sequence_length_/Users/runner/work/1/s/onnxruntime/core/providers/cpu/controlflow/scan_9.ccvoid onnxruntime::Scan<9>::Init(const onnxruntime::OpKernelInfo &) [OpSet = 9]num_scan_inputsinfo.GetAttr<int64_t>("num_scan_inputs", &num_scan_inputs_).IsOK()scan_input_directionsscan_output_directionsscan_input_axesgsl::narrow_cast<int64_t>(input_axes_.size()) == num_scan_inputs_Number of entries in 'scan_input_axes' was but expected scan_output_axesgsl::narrow_cast<int64_t>(output_axes_.size()) == num_scan_outputsNumber of entries in 'scan_output_axes' was virtual onnxruntime::common::Status onnxruntime::Scan<9>::SetupSubgraphExecutionInfo(const onnxruntime::SessionState &, const std::string &, const onnxruntime::SessionState &) [OpSet = 9]virtual onnxruntime::common::Status onnxruntime::Scan<9>::Compute(onnxruntime::OpKernelContext *) const [OpSet = 9]feeds_fetches_manager_ && info_Invalid scan input: Expected dimensions or more but input had shape of Scan inputs have inconsistent sequence lengths. Previous value was but input '' dimension has length of Invalid value in scan_input_axes for input of . Input tensor rank was ValidateInputSetupInputsSubgraph in 'body' produces outputs but Scan expects AllocateOutputTensorsCreateLoopStateVariablesonnxruntime::common::Status onnxruntime::ScanImpl::CreateLoopStateVariables(std::vector<LoopStateVariable> &)output_mlvalueOutput OrtValue has not been created for loop state variable output Invalid value in scan_output_axes for output . Output tensor rank was onnxruntime::common::Status onnxruntime::ScanImpl::TransposeOutput()TransposeOutputScanint64_t onnxruntime::HandleNegativeAxis(int64_t, int64_t)axis >= -tensor_rank && axis <= tensor_rank - 1axis is not in valid range [-/Users/runner/work/1/s/onnxruntime/core/providers/cpu/controlflow/scan_utils.hconst OrtValue &onnxruntime::scan::detail::OutputIterator::GetOutput() constfinal_output_mlvalue_/Users/runner/work/1/s/onnxruntime/core/providers/cpu/controlflow/scan_utils.cconnxruntime::scan::detail::Info::Info(const onnxruntime::Node &, const onnxruntime::GraphViewer &, int, bool)num_variadic_inputs == num_subgraph_inputsThe subgraph in 'body' requires inputs but Scan was only given void onnxruntime::scan::detail::ReadDirections(const onnxruntime::OpKernelInfo &, const std::string &, std::vector<int64_t> &, size_t)directions.size() == num_entriesNumber of entries in '' was validInvalid values in ''. 0 == forward. 1 == reverse.Subgraph must have the shape set for all outputs but did not.CreateFeedsFetchesManagerIterateSequencevoid onnxruntime::scan::detail::LoopStateVariable::Next()iteration_num_ < sequence_len_Misuse of LoopStateVariable. Attempt to move beyond end of sequenceFailed to create output tensor for output #AllocateFinalBufferonnxruntime::common::Status onnxruntime::scan::detail::OutputIterator::AllocateFinalOutput(const onnxruntime::TensorShape &)!is_concrete_shape_AllocateFinalOutputOrtValue &onnxruntime::scan::detail::OutputIterator::operator*()cur_iteration_ < num_iterations_is_concrete_shape_Expected AllocateFinalOutput to have been called to before we read the OrtValue from the iterator.onnxruntime::scan::detail::OutputIterator &onnxruntime::scan::detail::OutputIterator::operator++()Expected AllocateFinalOutput to have been called to before we increment the iteratorMismatch between expected shape and shape from first output is not compatible with /Users/runner/work/1/s/onnxruntime/core/providers/cpu/cpu_execution_provider.ccRegisterOnnxOperatorKernelsRegisterOnnxMLOperatorKernelsRegisterCPUKernelsGetKernelRegistryvirtual std::shared_ptr<KernelRegistry> onnxruntime::CPUExecutionProvider::GetKernelRegistry() constCpuConstantOfShape/Users/runner/work/1/s/onnxruntime/core/providers/cpu/generator/constant_of_shape_base.honnxruntime::ConstantOfShapeBase<onnxruntime::TypeList<onnxruntime::MLFloat16, float, double, signed char, short, int, long long, unsigned char, unsigned short, unsigned int, unsigned long long, bool> >::ConstantOfShapeBase(const onnxruntime::OpKernelInfo &) [EnabledOutputTypeList = onnxruntime::TypeList<onnxruntime::MLFloat16, float, double, signed char, short, int, long long, unsigned char, unsigned short, unsigned int, unsigned long long, bool>]t_proto_p->dims_size() == 1t_proto_p->dims()[0] == 1void onnxruntime::ConstantOfShapeBase<onnxruntime::TypeList<onnxruntime::MLFloat16, float, double, signed char, short, int, long long, unsigned char, unsigned short, unsigned int, unsigned long long, bool> >::SetValueFromTensorProto(const onnx::TensorProto &) [EnabledOutputTypeList = onnxruntime::TypeList<onnxruntime::MLFloat16, float, double, signed char, short, int, long long, unsigned char, unsigned short, unsigned int, unsigned long long, bool>]utils::HasDataType(t_proto)ONNX_NAMESPACE::TensorProto::DataType_IsValid(t_proto.data_type())!utils::HasExternalData(t_proto)Tensor proto with external data for value attribute is not supported.SetValueFromTensorProtoUnsupported value attribute datatype: /Users/runner/work/1/s/onnxruntime/core/providers/cpu/generator/constant_of_shape.ccUnsupported output datatype with size: PrepareComputeMust have a valid input shape.RandomNormalRandomUniformRandomNormalLikeRandomUniformLikeMultinomial/Users/runner/work/1/s/onnxruntime/core/providers/cpu/generator/random.ccCould not infer data type from input tensor with data type Empty dimensions for input tensorbatch_size is < 1num_classes is < 1num_samples is < 1Invalid data type of /Users/runner/work/1/s/onnxruntime/core/providers/cpu/generator/random.honnxruntime::RandomNormal::RandomNormal(const onnxruntime::OpKernelInfo &)info.GetAttr<float>("mean", &mean_).IsOK()scaleinfo.GetAttr<float>("scale", &scale_).IsOK()info.GetAttr<int64_t>("dtype", &dtype).IsOK()ONNX_NAMESPACE::TensorProto::DataType_IsValid(dtype_) && dtype_ != ONNX_NAMESPACE::TensorProto::UNDEFINEDInvalid dtype of info.GetAttrs<int64_t>("shape", shape).IsOK()onnxruntime::RandomUniform::RandomUniform(const onnxruntime::OpKernelInfo &)info.GetAttr<float>("high", &high_).IsOK()lowinfo.GetAttr<float>("low", &low_).IsOK()onnxruntime::RandomNormalLike::RandomNormalLike(const onnxruntime::OpKernelInfo &)onnxruntime::RandomUniformLike::RandomUniformLike(const onnxruntime::OpKernelInfo &)sample_sizeonnxruntime::Multinomial::Multinomial(const onnxruntime::OpKernelInfo &)info.GetAttr<int64_t>("sample_size", &num_samples_).IsOK()ONNX_NAMESPACE::TensorProto::DataType_IsValid(output_dtype_) && output_dtype_ != ONNX_NAMESPACE::TensorProto::UNDEFINEDOutput type not supported in this build: MultinomialComputeRangestart in Range operator should be scalar like tensor, yet got shape:limit in Range operator should be scalar like tensor, yet got shape:delta in Range operator should be scalar like tensor, yet got shape:delta in Range operator can not be zero!Clipminmax/Users/runner/work/1/s/onnxruntime/core/providers/cpu/math/clip.honnxruntime::clip_internal::Clip_6Base<float>::Clip_6Base(const onnxruntime::OpKernelInfo &) [T = float]min_ <= max_/Users/runner/work/1/s/onnxruntime/core/providers/cpu/math/clip.ccvoid onnxruntime::Clip::ComputeImpl<float>::operator()(const onnxruntime::Tensor *, const onnxruntime::Tensor *, const onnxruntime::Tensor *, onnxruntime::Tensor *) const [T = float]min->Shape().IsScalar()max->Shape().IsScalar()void onnxruntime::Clip::ComputeImpl<double>::operator()(const onnxruntime::Tensor *, const onnxruntime::Tensor *, const onnxruntime::Tensor *, onnxruntime::Tensor *) const [T = double]void onnxruntime::Clip::ComputeImpl<signed char>::operator()(const onnxruntime::Tensor *, const onnxruntime::Tensor *, const onnxruntime::Tensor *, onnxruntime::Tensor *) const [T = signed char]void onnxruntime::Clip::ComputeImpl<unsigned char>::operator()(const onnxruntime::Tensor *, const onnxruntime::Tensor *, const onnxruntime::Tensor *, onnxruntime::Tensor *) const [T = unsigned char]void onnxruntime::Clip::ComputeImpl<long long>::operator()(const onnxruntime::Tensor *, const onnxruntime::Tensor *, const onnxruntime::Tensor *, onnxruntime::Tensor *) const [T = long long]void onnxruntime::Clip::ComputeImpl<unsigned long long>::operator()(const onnxruntime::Tensor *, const onnxruntime::Tensor *, const onnxruntime::Tensor *, onnxruntime::Tensor *) const [T = unsigned long long]CumSumexclusive/Users/runner/work/1/s/onnxruntime/core/providers/cpu/math/cumsum.ccvirtual onnxruntime::common::Status onnxruntime::CumSum<float>::Compute(onnxruntime::OpKernelContext *) const [T = float]void onnxruntime::WritableSliceIterator<float>::Init(const std::vector<int64_t> &, gsl::span<const int64_t>, gsl::span<const int64_t>) [T = float]dims.size() == starts.size()dims.size()=starts.size()=dims.size() == extents_.size()extents.size()=dims.size() == steps.size()steps.size()=virtual onnxruntime::common::Status onnxruntime::CumSum<double>::Compute(onnxruntime::OpKernelContext *) const [T = double]void onnxruntime::WritableSliceIterator<double>::Init(const std::vector<int64_t> &, gsl::span<const int64_t>, gsl::span<const int64_t>) [T = double]virtual onnxruntime::common::Status onnxruntime::CumSum<int>::Compute(onnxruntime::OpKernelContext *) const [T = int]void onnxruntime::WritableSliceIterator<int>::Init(const std::vector<int64_t> &, gsl::span<const int64_t>, gsl::span<const int64_t>) [T = int]virtual onnxruntime::common::Status onnxruntime::CumSum<long long>::Compute(onnxruntime::OpKernelContext *) const [T = long long]void onnxruntime::WritableSliceIterator<long long>::Init(const std::vector<int64_t> &, gsl::span<const int64_t>, gsl::span<const int64_t>) [T = long long]Det/Users/runner/work/1/s/onnxruntime/core/providers/cpu/math/det.ccvirtual onnxruntime::common::Status onnxruntime::Det<float>::Compute(onnxruntime::OpKernelContext *) const [T = float]X != nullptrInput tensor should have a rank of at least 2Matrix dimensions are not equal. Square matrix is expectedEinsumThere was a problem acquiring temporary memory allocator in Einsum op/Users/runner/work/1/s/onnxruntime/core/providers/cpu/math/einsum.ccDeviceComputeEinsum op: An implementation for the input type is not supported yet/Users/runner/work/1/s/onnxruntime/core/providers/cpu/math/einsum.honnxruntime::Einsum::Einsum(const onnxruntime::OpKernelInfo &)info.GetAttr<std::string>("equation", &equation_).IsOK()->/Users/runner/work/1/s/onnxruntime/core/providers/cpu/math/einsum_utils/einsum_auxiliary_ops.ccstd::unique_ptr<Tensor> onnxruntime::EinsumOp::MatMul(const onnxruntime::Tensor &, const std::vector<int64_t> &, const onnxruntime::Tensor &, const std::vector<int64_t> &, onnxruntime::AllocatorPtr, concurrency::ThreadPool *, void *, const DeviceHelpers::MatMul<T> &) [T = float]input_1.DataType() == input_2.DataType()input_shape_1_override.size() == 3 && input_shape_2_override.size() == 3input_shape_1_override[0] == input_shape_2_override[0]input_shape_1_override[2] == input_shape_2_override[1]Einsum op: Exception during MatMul operation: std::unique_ptr<Tensor> onnxruntime::EinsumOp::MatMul(const onnxruntime::Tensor &, const std::vector<int64_t> &, const onnxruntime::Tensor &, const std::vector<int64_t> &, onnxruntime::AllocatorPtr, concurrency::ThreadPool *, void *, const DeviceHelpers::MatMul<T> &) [T = int]std::unique_ptr<Tensor> onnxruntime::EinsumOp::MatMul(const onnxruntime::Tensor &, const std::vector<int64_t> &, const onnxruntime::Tensor &, const std::vector<int64_t> &, onnxruntime::AllocatorPtr, concurrency::ThreadPool *, void *, const DeviceHelpers::MatMul<T> &) [T = double]std::unique_ptr<Tensor> onnxruntime::EinsumOp::MatMul(const onnxruntime::Tensor &, const std::vector<int64_t> &, const onnxruntime::Tensor &, const std::vector<int64_t> &, onnxruntime::AllocatorPtr, concurrency::ThreadPool *, void *, const DeviceHelpers::MatMul<T> &) [T = long long]onnxruntime::common::Status onnxruntime::EinsumOp::DeviceHelpers::CpuDeviceHelpers::DataCopy(const onnxruntime::Tensor &, onnxruntime::Tensor &, void *)output.SizeInBytes() == input.SizeInBytes()Einsum op: The candidate output does not match the actual output's shapestd::unique_ptr<Tensor> onnxruntime::EinsumOp::DeviceHelpers::CpuDeviceHelpers::Diagonal(const onnxruntime::Tensor &, int64_t, int64_t, onnxruntime::AllocatorPtr, void *)rank >= 2 && dim_1 != dim_2 && input_dims[dim_1] == input_dims[dim_2]Cannot parse the diagonal elements along dims for input shape bool onnxruntime::EinsumOp::IsTransposeRequired(size_t, const std::vector<size_t> &)input_rank == permutation.size()std::unique_ptr<Tensor> onnxruntime::EinsumOp::Transpose(const onnxruntime::Tensor &, const std::vector<int64_t> &, const std::vector<size_t> &, onnxruntime::AllocatorPtr, void *, const DeviceHelpers::Transpose &)Length of permutation must match the rank of the input to be permutatedEinsum op: Transpose failed: std::unique_ptr<Tensor> onnxruntime::EinsumOp::DeviceHelpers::CpuDeviceHelpers::DiagonalInnermostDims(const onnxruntime::Tensor &, bool, onnxruntime::AllocatorPtr)input_dims[rank - 2] == input_dims[rank - 1]The innermost dims should have the same dim value to parse the diagonal elementsEinsum op: Unsupported data type for Diagonal /Users/runner/work/1/s/onnxruntime/core/providers/cpu/math/einsum_utils/einsum_compute_preprocessor.ccNumber of subscripts in the input equation does not match number of input tensorsFound a '.' not part of an ellipsis in input: Einsum subscripts string contains too many subscript labels when compared to the rank of the inputEllipsis must indicate a fixed number of dimensions across all inputsFound '.' not part of an ellipsis in input: The only subscript labels allowed are lower-cased letters (a-z) and upper-cased letters (A-Z)Einsum operands could not be broadcast together. Please check input shapes/equation provided.Input shape of operand is incompatible in the dimension . The shape is: Another operand has a dim value of in the same dimensionEinsum subscripts string contains too many subscript labels when compared to the rank of the input Einsum subscripts does not contain enough subscript labels and there is no ellipsis for input onnxruntime::common::Status onnxruntime::EinsumComputePreprocessor::PostProcessBroadcastedDims()num_broadcasted_indices < num_of_ellipsis_dims_dim_iter == rank...Inputs have ellipses in them but the provided output subscript does not contain an ellipsisFound a '.' not part of an ellipsis in the output subscript providedFound '.' not part of an ellipsis in the output subscript providedRank of the input must match number of subscript labels corresponding to the input/Users/runner/work/1/s/onnxruntime/core/providers/cpu/math/einsum_utils/einsum_typed_compute_processor.ccstd::unique_ptr<Tensor> onnxruntime::EinsumTypedComputeProcessor<float>::PairwiseOperandProcess(const onnxruntime::Tensor &, const onnxruntime::TensorShape &, const onnxruntime::Tensor &, const onnxruntime::TensorShape &, const std::vector<int64_t> &, bool) [T = float]left.Shape().Size() == left_shape_override.Size()The override dims are not compatible with given tensor's shape. Left shape: Left shape override: right.Shape().Size() == right_shape_override.Size()Right shape: Right shape override: left_rank == right_rankRanks of pair-wise operands must be equal. Right shape: left_dim == right_dimEinsum op: Input dimensions must be equal along an axis to be reduced across all inputsvoid onnxruntime::EinsumTypedComputeProcessor<float>::FinalizeOutput(const onnxruntime::Tensor &, const std::vector<int64_t> &) [T = float]candidate_output.Shape().Size() == output_shape.Size()Einsum op: The candidate output cannot be reshaped into the op's outputcandidate_output_dims[iter] == 1Not all dimensions to be reduced have been reduced in the candidate output. Candidate output dims: Einsum op: Could not copy the intermediate output's buffer into the op's output buffer. Error: std::unique_ptr<Tensor> onnxruntime::EinsumTypedComputeProcessor<int>::PairwiseOperandProcess(const onnxruntime::Tensor &, const onnxruntime::TensorShape &, const onnxruntime::Tensor &, const onnxruntime::TensorShape &, const std::vector<int64_t> &, bool) [T = int]void onnxruntime::EinsumTypedComputeProcessor<int>::FinalizeOutput(const onnxruntime::Tensor &, const std::vector<int64_t> &) [T = int]std::unique_ptr<Tensor> onnxruntime::EinsumTypedComputeProcessor<double>::PairwiseOperandProcess(const onnxruntime::Tensor &, const onnxruntime::TensorShape &, const onnxruntime::Tensor &, const onnxruntime::TensorShape &, const std::vector<int64_t> &, bool) [T = double]void onnxruntime::EinsumTypedComputeProcessor<double>::FinalizeOutput(const onnxruntime::Tensor &, const std::vector<int64_t> &) [T = double]std::unique_ptr<Tensor> onnxruntime::EinsumTypedComputeProcessor<long long>::PairwiseOperandProcess(const onnxruntime::Tensor &, const onnxruntime::TensorShape &, const onnxruntime::Tensor &, const onnxruntime::TensorShape &, const std::vector<int64_t> &, bool) [T = long long]void onnxruntime::EinsumTypedComputeProcessor<long long>::FinalizeOutput(const onnxruntime::Tensor &, const std::vector<int64_t> &) [T = long long]SubMulDivAbsNegFloorCeilReciprocalSqrtPowT1ExpLogSumMaxMinLessGreaterEqualLessOrEqualGreaterOrEqualMeanBitShiftErfNotAndOrXorUnsupported X type: /Users/runner/work/1/s/onnxruntime/core/providers/cpu/math/element_wise_ops.ccvirtual onnxruntime::common::Status onnxruntime::Min_6<float>::Compute(onnxruntime::OpKernelContext *) const [T = float]inputCount >= 1Must have 1 or more inputsdata_n.Shape() == shapevirtual onnxruntime::common::Status onnxruntime::Max_6<float>::Compute(onnxruntime::OpKernelContext *) const [T = float]virtual onnxruntime::common::Status onnxruntime::Mean_6<float>::Compute(onnxruntime::OpKernelContext *) const [T = float]data_1.Shape() == shapeSinCosTanAsinAcosAtanSinhCoshAsinhAcoshAtanhPReluExpandMod/Users/runner/work/1/s/onnxruntime/core/providers/cpu/element_wise_ranged_transform.hElementWiseKernelonnxruntime::ElementWiseKernel<onnxruntime::functors::Abs<float> >::ElementWiseKernel(const onnxruntime::OpKernelInfo &) [F = onnxruntime::functors::Abs<float>]virtual onnxruntime::common::Status onnxruntime::ElementWiseKernel<onnxruntime::functors::Abs<float> >::Compute(onnxruntime::OpKernelContext *) const [F = onnxruntime::functors::Abs<float>]input_size < std::numeric_limits<std::ptrdiff_t>::max()onnxruntime::ElementWiseKernel<onnxruntime::functors::Abs<double> >::ElementWiseKernel(const onnxruntime::OpKernelInfo &) [F = onnxruntime::functors::Abs<double>]virtual onnxruntime::common::Status onnxruntime::ElementWiseKernel<onnxruntime::functors::Abs<double> >::Compute(onnxruntime::OpKernelContext *) const [F = onnxruntime::functors::Abs<double>]onnxruntime::ElementWiseKernel<onnxruntime::functors::Abs<signed char> >::ElementWiseKernel(const onnxruntime::OpKernelInfo &) [F = onnxruntime::functors::Abs<signed char>]virtual onnxruntime::common::Status onnxruntime::ElementWiseKernel<onnxruntime::functors::Abs<signed char> >::Compute(onnxruntime::OpKernelContext *) const [F = onnxruntime::functors::Abs<signed char>]onnxruntime::ElementWiseKernel<onnxruntime::functors::Abs<short> >::ElementWiseKernel(const onnxruntime::OpKernelInfo &) [F = onnxruntime::functors::Abs<short>]virtual onnxruntime::common::Status onnxruntime::ElementWiseKernel<onnxruntime::functors::Abs<short> >::Compute(onnxruntime::OpKernelContext *) const [F = onnxruntime::functors::Abs<short>]onnxruntime::ElementWiseKernel<onnxruntime::functors::Abs<int> >::ElementWiseKernel(const onnxruntime::OpKernelInfo &) [F = onnxruntime::functors::Abs<int>]virtual onnxruntime::common::Status onnxruntime::ElementWiseKernel<onnxruntime::functors::Abs<int> >::Compute(onnxruntime::OpKernelContext *) const [F = onnxruntime::functors::Abs<int>]onnxruntime::ElementWiseKernel<onnxruntime::functors::Abs<long long> >::ElementWiseKernel(const onnxruntime::OpKernelInfo &) [F = onnxruntime::functors::Abs<long long>]virtual onnxruntime::common::Status onnxruntime::ElementWiseKernel<onnxruntime::functors::Abs<long long> >::Compute(onnxruntime::OpKernelContext *) const [F = onnxruntime::functors::Abs<long long>]onnxruntime::ElementWiseKernel<onnxruntime::functors::Abs<unsigned char> >::ElementWiseKernel(const onnxruntime::OpKernelInfo &) [F = onnxruntime::functors::Abs<unsigned char>]virtual onnxruntime::common::Status onnxruntime::ElementWiseKernel<onnxruntime::functors::Abs<unsigned char> >::Compute(onnxruntime::OpKernelContext *) const [F = onnxruntime::functors::Abs<unsigned char>]onnxruntime::ElementWiseKernel<onnxruntime::functors::Abs<unsigned short> >::ElementWiseKernel(const onnxruntime::OpKernelInfo &) [F = onnxruntime::functors::Abs<unsigned short>]virtual onnxruntime::common::Status onnxruntime::ElementWiseKernel<onnxruntime::functors::Abs<unsigned short> >::Compute(onnxruntime::OpKernelContext *) const [F = onnxruntime::functors::Abs<unsigned short>]onnxruntime::ElementWiseKernel<onnxruntime::functors::Abs<unsigned int> >::ElementWiseKernel(const onnxruntime::OpKernelInfo &) [F = onnxruntime::functors::Abs<unsigned int>]virtual onnxruntime::common::Status onnxruntime::ElementWiseKernel<onnxruntime::functors::Abs<unsigned int> >::Compute(onnxruntime::OpKernelContext *) const [F = onnxruntime::functors::Abs<unsigned int>]onnxruntime::ElementWiseKernel<onnxruntime::functors::Abs<unsigned long long> >::ElementWiseKernel(const onnxruntime::OpKernelInfo &) [F = onnxruntime::functors::Abs<unsigned long long>]virtual onnxruntime::common::Status onnxruntime::ElementWiseKernel<onnxruntime::functors::Abs<unsigned long long> >::Compute(onnxruntime::OpKernelContext *) const [F = onnxruntime::functors::Abs<unsigned long long>]onnxruntime::ElementWiseKernel<onnxruntime::functors::Neg<float> >::ElementWiseKernel(const onnxruntime::OpKernelInfo &) [F = onnxruntime::functors::Neg<float>]virtual onnxruntime::common::Status onnxruntime::ElementWiseKernel<onnxruntime::functors::Neg<float> >::Compute(onnxruntime::OpKernelContext *) const [F = onnxruntime::functors::Neg<float>]onnxruntime::ElementWiseKernel<onnxruntime::functors::Neg<double> >::ElementWiseKernel(const onnxruntime::OpKernelInfo &) [F = onnxruntime::functors::Neg<double>]virtual onnxruntime::common::Status onnxruntime::ElementWiseKernel<onnxruntime::functors::Neg<double> >::Compute(onnxruntime::OpKernelContext *) const [F = onnxruntime::functors::Neg<double>]onnxruntime::ElementWiseKernel<onnxruntime::functors::Neg<signed char> >::ElementWiseKernel(const onnxruntime::OpKernelInfo &) [F = onnxruntime::functors::Neg<signed char>]virtual onnxruntime::common::Status onnxruntime::ElementWiseKernel<onnxruntime::functors::Neg<signed char> >::Compute(onnxruntime::OpKernelContext *) const [F = onnxruntime::functors::Neg<signed char>]onnxruntime::ElementWiseKernel<onnxruntime::functors::Neg<int> >::ElementWiseKernel(const onnxruntime::OpKernelInfo &) [F = onnxruntime::functors::Neg<int>]virtual onnxruntime::common::Status onnxruntime::ElementWiseKernel<onnxruntime::functors::Neg<int> >::Compute(onnxruntime::OpKernelContext *) const [F = onnxruntime::functors::Neg<int>]onnxruntime::ElementWiseKernel<onnxruntime::functors::Neg<long long> >::ElementWiseKernel(const onnxruntime::OpKernelInfo &) [F = onnxruntime::functors::Neg<long long>]virtual onnxruntime::common::Status onnxruntime::ElementWiseKernel<onnxruntime::functors::Neg<long long> >::Compute(onnxruntime::OpKernelContext *) const [F = onnxruntime::functors::Neg<long long>]onnxruntime::ElementWiseKernel<onnxruntime::functors::Floor<float> >::ElementWiseKernel(const onnxruntime::OpKernelInfo &) [F = onnxruntime::functors::Floor<float>]virtual onnxruntime::common::Status onnxruntime::ElementWiseKernel<onnxruntime::functors::Floor<float> >::Compute(onnxruntime::OpKernelContext *) const [F = onnxruntime::functors::Floor<float>]onnxruntime::ElementWiseKernel<onnxruntime::functors::Ceil<float> >::ElementWiseKernel(const onnxruntime::OpKernelInfo &) [F = onnxruntime::functors::Ceil<float>]virtual onnxruntime::common::Status onnxruntime::ElementWiseKernel<onnxruntime::functors::Ceil<float> >::Compute(onnxruntime::OpKernelContext *) const [F = onnxruntime::functors::Ceil<float>]onnxruntime::ElementWiseKernel<onnxruntime::functors::Reciprocal<float> >::ElementWiseKernel(const onnxruntime::OpKernelInfo &) [F = onnxruntime::functors::Reciprocal<float>]virtual onnxruntime::common::Status onnxruntime::ElementWiseKernel<onnxruntime::functors::Reciprocal<float> >::Compute(onnxruntime::OpKernelContext *) const [F = onnxruntime::functors::Reciprocal<float>]onnxruntime::ElementWiseKernel<onnxruntime::functors::Reciprocal<double> >::ElementWiseKernel(const onnxruntime::OpKernelInfo &) [F = onnxruntime::functors::Reciprocal<double>]virtual onnxruntime::common::Status onnxruntime::ElementWiseKernel<onnxruntime::functors::Reciprocal<double> >::Compute(onnxruntime::OpKernelContext *) const [F = onnxruntime::functors::Reciprocal<double>]onnxruntime::ElementWiseKernel<onnxruntime::functors::Sqrt<float> >::ElementWiseKernel(const onnxruntime::OpKernelInfo &) [F = onnxruntime::functors::Sqrt<float>]virtual onnxruntime::common::Status onnxruntime::ElementWiseKernel<onnxruntime::functors::Sqrt<float> >::Compute(onnxruntime::OpKernelContext *) const [F = onnxruntime::functors::Sqrt<float>]onnxruntime::ElementWiseKernel<onnxruntime::functors::Sqrt<double> >::ElementWiseKernel(const onnxruntime::OpKernelInfo &) [F = onnxruntime::functors::Sqrt<double>]virtual onnxruntime::common::Status onnxruntime::ElementWiseKernel<onnxruntime::functors::Sqrt<double> >::Compute(onnxruntime::OpKernelContext *) const [F = onnxruntime::functors::Sqrt<double>]onnxruntime::ElementWiseKernel<onnxruntime::functors::Exp<float> >::ElementWiseKernel(const onnxruntime::OpKernelInfo &) [F = onnxruntime::functors::Exp<float>]virtual onnxruntime::common::Status onnxruntime::ElementWiseKernel<onnxruntime::functors::Exp<float> >::Compute(onnxruntime::OpKernelContext *) const [F = onnxruntime::functors::Exp<float>]onnxruntime::ElementWiseKernel<onnxruntime::functors::Exp<double> >::ElementWiseKernel(const onnxruntime::OpKernelInfo &) [F = onnxruntime::functors::Exp<double>]virtual onnxruntime::common::Status onnxruntime::ElementWiseKernel<onnxruntime::functors::Exp<double> >::Compute(onnxruntime::OpKernelContext *) const [F = onnxruntime::functors::Exp<double>]onnxruntime::ElementWiseKernel<onnxruntime::functors::Log<float> >::ElementWiseKernel(const onnxruntime::OpKernelInfo &) [F = onnxruntime::functors::Log<float>]virtual onnxruntime::common::Status onnxruntime::ElementWiseKernel<onnxruntime::functors::Log<float> >::Compute(onnxruntime::OpKernelContext *) const [F = onnxruntime::functors::Log<float>]onnxruntime::ElementWiseKernel<onnxruntime::functors::Log<double> >::ElementWiseKernel(const onnxruntime::OpKernelInfo &) [F = onnxruntime::functors::Log<double>]virtual onnxruntime::common::Status onnxruntime::ElementWiseKernel<onnxruntime::functors::Log<double> >::Compute(onnxruntime::OpKernelContext *) const [F = onnxruntime::functors::Log<double>]virtual onnxruntime::common::Status onnxruntime::Sum_6<float>::Compute(onnxruntime::OpKernelContext *) const [T = float]input_count >= 1virtual onnxruntime::common::Status onnxruntime::Sum_6<double>::Compute(onnxruntime::OpKernelContext *) const [T = double]directiononnxruntime::BitShift<unsigned char>::BitShift(const onnxruntime::OpKernelInfo &) [T = unsigned char]LEFTRIGHTInvalid direction value of ''. Valid values are 'LEFT' or 'RIGHT'.auto onnxruntime::BitShift<unsigned char>::Compute(onnxruntime::OpKernelContext *)::(anonymous class)::operator()(onnxruntime::BroadcastHelper &) const [T = unsigned char]cur1 == end1cur_out == end_outonnxruntime::BitShift<unsigned int>::BitShift(const onnxruntime::OpKernelInfo &) [T = unsigned int]auto onnxruntime::BitShift<unsigned int>::Compute(onnxruntime::OpKernelContext *)::(anonymous class)::operator()(onnxruntime::BroadcastHelper &) const [T = unsigned int]onnxruntime::BitShift<unsigned long long>::BitShift(const onnxruntime::OpKernelInfo &) [T = unsigned long long]auto onnxruntime::BitShift<unsigned long long>::Compute(onnxruntime::OpKernelContext *)::(anonymous class)::operator()(onnxruntime::BroadcastHelper &) const [T = unsigned long long]void onnxruntime::UntypedExpand(onnxruntime::OpKernelContext &, const onnxruntime::ProcessBroadcastSpanFuncs &)shape_data_tensor.Shape().GetDims().size() == 1/Users/runner/work/1/s/onnxruntime/core/providers/cpu/math/element_wise_ops.honnxruntime::Broadcaster::Broadcaster(const std::vector<int64_t> &, const std::vector<int64_t> &)largest <= 1Can broadcast 0 by 0 or 1. is invalid.void onnxruntime::BroadcastIterator::Init(ptrdiff_t, ptrdiff_t)axis == 1 || axis == largestAttempting to broadcast an axis by a dimension other than 1. by void onnxruntime::BroadcastIterator::Append(ptrdiff_t, ptrdiff_t)void onnxruntime::ExpandBroadcastLooper(onnxruntime::BroadcastHelper &, const onnxruntime::ProcessBroadcastSpanFuncs &)!helper.HaveTwoTensorInputs()ExpandBroadcastLooper should only have a shape for the second input.void onnxruntime::InputBroadcaster::AdvanceBy(size_t)offset % span_size_ == 0fmodonnxruntime::Mod::Mod(const onnxruntime::OpKernelInfo &)(fmod == 0) || (fmod == 1)onnxruntime::OutputBroadcaster::OutputBroadcaster(size_t, onnxruntime::Tensor &, ptrdiff_t, ptrdiff_t)start_offset >= 0 && real_end >= 0 && start_offset <= real_end && real_end <= lenInvalid start/ending offset [) for tensor of length:start_offset % span_size == 0 && real_end % span_size == 0Broadcast Output range [) are not at boundary of span with size:onnxruntime::TensorAllocator::TensorAllocator(onnxruntime::OpKernelContext &)Unsupported Y type: void onnxruntime::utils::mltype_dispatcher_internal::UnsupportedTypeDefaultPolicy<onnxruntime::common::Status>::operator()(int32_t, Ret &) const [Ret = onnxruntime::common::Status]Unsupported data type: void onnxruntime::mod_internal::CallModImpl<float, void>::operator()(bool, onnxruntime::OpKernelContext *) const [T = float, Enable = void]void onnxruntime::mod_internal::CallModImpl<double, void>::operator()(bool, onnxruntime::OpKernelContext *) const [T = double, Enable = void]void onnxruntime::mod_internal::CallModImpl<onnxruntime::MLFloat16, void>::operator()(bool, onnxruntime::OpKernelContext *) constvoid onnxruntime::utils::mltype_dispatcher_internal::CallableDispatchableHelper::CheckCalledOnce()called_ == 1void onnxruntime::BroadcastLooper(TBroadcastHelper &, const onnxruntime::ProcessBroadcastSpanFuncs &) [TBroadcastHelper = onnxruntime::BroadcastHelper]helper.HaveTwoTensorInputs()GemmtransA/Users/runner/work/1/s/onnxruntime/core/providers/cpu/math/gemm.honnxruntime::Gemm<float>::Gemm(const onnxruntime::OpKernelInfo &) [T = float]info.GetAttr<int64_t>("transA", &temp).IsOK()transBinfo.GetAttr<int64_t>("transB", &temp).IsOK()onnxruntime::Gemm<double>::Gemm(const onnxruntime::OpKernelInfo &) [T = double]/Users/runner/work/1/s/onnxruntime/core/providers/cpu/math/gemm.ccvoid onnxruntime::GemmBroadcastBias(int64_t, int64_t, float, const T *, const onnxruntime::TensorShape *, T *) [T = double]c_shape != nullptr/Users/runner/work/1/s/onnxruntime/core/providers/cpu/math/gemm_helper.honnxruntime::GemmHelper::GemmHelper(const onnxruntime::TensorShape &, bool, const onnxruntime::TensorShape &, bool, const onnxruntime::TensorShape &)left.NumDimensions() == 2 || left.NumDimensions() == 1right.NumDimensions() == 2GEMM: Dimension mismatch, W: K: N:Gemm: Invalid bias shape for broadcastM_ >= 0 && K_ > 0 && N_ >= 0void onnxruntime::GemmBroadcastBias(int64_t, int64_t, float, const T *, const onnxruntime::TensorShape *, T *) [T = float]/Users/runner/work/1/s/onnxruntime/core/providers/cpu/math/hardmax.ccHardmax inputs N, D and N * D must be < . N=, D=HardmaxMatMul/Users/runner/work/1/s/onnxruntime/core/providers/cpu/math/matmul.cc/Users/runner/work/1/s/onnxruntime/core/providers/cpu/math/matmul_helper.hleft_num_dims and right_num_dims must be >= 1MatMul dimension mismatchleft operand cannot broadcast on dim right operand cannot broadcast on dim num_dims_with_pad != num_output_dimsM_ == 1 && N_ == 1 was falsenum_dims_with_pad - 1 != num_output_dimsnum_dims_with_pad - 2 != num_output_dimsMatMulInteger/Users/runner/work/1/s/onnxruntime/core/providers/cpu/math/matmul_integer.ccvirtual onnxruntime::common::Status onnxruntime::MatMulInteger::Compute(onnxruntime::OpKernelContext *) constIsScalarOr1ElementVector(a_zero_point)MatmulInteger : input1 zero point must be a scalar or 1D tensor of size 1IsBQuantParamSupported(b_zero_point->Shape(), b ? b->Shape() : b_shape_)QLinearMatMul/Users/runner/work/1/s/onnxruntime/core/providers/cpu/math/quantize_linear_matmul.ccvirtual onnxruntime::common::Status onnxruntime::QLinearMatMul::Compute(onnxruntime::OpKernelContext *) constIsScalarOr1ElementVector(a_offset)QLinearMatmul : input zero point must be a scalar or 1D tensor of size 1IsBQuantParamSupported(b_offset->Shape(), b ? b->Shape() : b_shape_)QLinearMatmul : weight zero point must be a scalar, 1D tensor of size 1, or last to second dimension is 1IsScalarOr1ElementVector(y_offset)QLinearMatmul : result zero point must be a scalar or 1D tensor of size 1IsScalarOr1ElementVector(a_scale)QLinearMatmul : input scale must be a scalar or 1D tensor of size 1IsBQuantParamSupported(b_scale->Shape(), b ? b->Shape() : b_shape_)QLinearMatmul : weight scale must be a scalar, 1D tensor of size 1, or last to second dimension is 1IsScalarOr1ElementVector(y_scale)QLinearMatmul : result scale must be a scalar or 1D tensor of size 1Per-column quantization parameter of batched matrix should have same dimension as the matrix,and its size by K should be equal to the matrix's size.RoundSignSoftmaxLogSoftmax/Users/runner/work/1/s/onnxruntime/core/providers/cpu/math/softmax.ccComputeImplOpset13SoftmaxCPU inputs N, D and N * D must be < TopK/Users/runner/work/1/s/onnxruntime/core/providers/cpu/math/top_k.ccvoid onnxruntime::TopkOpset9ConstructorCommon(const onnxruntime::OpKernelInfo &, int &, unsigned int &)op_kernel_info.GetAttr<int64_t>("k", &k_temp).IsOK()k_temp > 0op_kernel_info.GetAttr<int64_t>("axis", &axis_temp).IsOK()void onnxruntime::TopkOpset10ConstructorCommon(const onnxruntime::OpKernelInfo &, int &)void onnxruntime::TopkOpset11ConstructorCommon(const onnxruntime::OpKernelInfo &, int &, bool &, bool &)largestop_kernel_info.GetAttr<int64_t>("largest", &largest_temp).IsOK()op_kernel_info.GetAttr<int64_t>("sorted", &sorted_temp).IsOK()input count mismatch, expected 1 input - the tensor to be processedk argument [] should not be greater than specified axis dim value [output count mismatch, expected 2 outputs to be present for TopK operatorinput count mismatch, expected 2 inputs - the tensor to be processed and a tensor containing k valueArrayFeatureExtractorInvalid argument: X input has empty dimensions.Invalid Y argument: num_indices = 0Invalid Y argument: index is out of range: Y[] () >=BinarizerthresholdInput data with index: is NaNCastMapInvalid input type of value: Expected std::map<int64_t, float> or std::map<int64_t, std::string>Unexpected CAST_TO value of cast_to/Users/runner/work/1/s/onnxruntime/core/providers/cpu/ml/cast_map.honnxruntime::ml::CastMap::CastMap(const onnxruntime::OpKernelInfo &)info.GetAttr<std::string>("cast_to", &attr).IsOK()info.GetAttr<std::string>("map_form", &attr).IsOK()max_mapinfo.GetAttr<int64_t>("max_map", &max_map_).IsOK()map_form_ != PACK_MAP::SPARSE || max_map_ > 0TO_FLOATTO_STRINGTO_INT64/Users/runner/work/1/s/onnxruntime/core/providers/cpu/ml/ml_common.honnxruntime::ml::CAST_TO onnxruntime::ml::MakeCast(const std::string &)Invalid CAST_TO value of Expected TO_FLOAT, TO_STRING or TO_INT64DENSESPARSEonnxruntime::ml::PACK_MAP onnxruntime::ml::MakePack(const std::string &)Invalid PACK_MAP value of Expected DENSE or SPARSE/Users/runner/work/1/s/onnxruntime/core/providers/cpu/ml/cast_map.cconnxruntime::common::Status onnxruntime::ml::CastMap::ComputeImpl(onnxruntime::OpKernelContext &, TTo) const [TFrom = float, TTo = float]cur_input == end_input || cur_input->first >= 0Negative index values are not permitted. First entry in map has index value of const T *onnxruntime::OpKernelContext::Input(int) const [T = std::__1::map<long long, float, std::__1::less<long long>, std::__1::allocator<std::__1::pair<const long long, float> > >]onnxruntime::common::Status onnxruntime::ml::CastMap::ComputeImpl(onnxruntime::OpKernelContext &, TTo) const [TFrom = std::__1::basic_string<char>, TTo = float]const T *onnxruntime::OpKernelContext::Input(int) const [T = std::__1::map<long long, std::__1::basic_string<char>, std::__1::less<long long>, std::__1::allocator<std::__1::pair<const long long, std::__1::basic_string<char> > > >]onnxruntime::common::Status onnxruntime::ml::CastMap::ComputeImpl(onnxruntime::OpKernelContext &, TTo) const [TFrom = float, TTo = long long]onnxruntime::common::Status onnxruntime::ml::CastMap::ComputeImpl(onnxruntime::OpKernelContext &, TTo) const [TFrom = std::__1::basic_string<char>, TTo = long long]onnxruntime::common::Status onnxruntime::ml::CastMap::ComputeImpl(onnxruntime::OpKernelContext &, TTo) const [TFrom = float, TTo = std::__1::basic_string<char>]onnxruntime::common::Status onnxruntime::ml::CastMap::ComputeImpl(onnxruntime::OpKernelContext &, TTo) const [TFrom = std::__1::basic_string<char>, TTo = std::__1::basic_string<char>]CategoryMapperInput of string must have output of int64Input of int64 must have output of string cats_strings/Users/runner/work/1/s/onnxruntime/core/providers/cpu/ml/category_mapper.honnxruntime::ml::CategoryMapper::CategoryMapper(const onnxruntime::OpKernelInfo &)info.GetAttrs<std::string>("cats_strings", string_categories).IsOK()cats_int64sinfo.GetAttrs<int64_t>("cats_int64s", int_categories).IsOK()default_stringinfo.GetAttr<std::string>("default_string", &default_string_).IsOK()default_int64info.GetAttr<int64_t>("default_int64", &default_int_).IsOK()num_entries == int_categories.size()DictVectorizerstring_vocabulary/Users/runner/work/1/s/onnxruntime/core/providers/cpu/ml/dictvectorizer.honnxruntime::ml::DictVectorizerOp<std::__1::basic_string<char>, long long>::DictVectorizerOp(const onnxruntime::OpKernelInfo &) [AttrType = std::__1::basic_string<char>, TargetType = long long]info.GetAttrs(std::is_same<AttrType, std::string>::value ? "string_vocabulary" : "int64_vocabulary", vocabulary_).IsOK()const T *onnxruntime::OpKernelContext::Input(int) const [T = std::__1::map<std::__1::basic_string<char>, long long, std::__1::less<std::__1::basic_string<char> >, std::__1::allocator<std::__1::pair<const std::__1::basic_string<char>, long long> > >]onnxruntime::ml::DictVectorizerOp<std::__1::basic_string<char>, float>::DictVectorizerOp(const onnxruntime::OpKernelInfo &) [AttrType = std::__1::basic_string<char>, TargetType = float]const T *onnxruntime::OpKernelContext::Input(int) const [T = std::__1::map<std::__1::basic_string<char>, float, std::__1::less<std::__1::basic_string<char> >, std::__1::allocator<std::__1::pair<const std::__1::basic_string<char>, float> > >]onnxruntime::ml::DictVectorizerOp<std::__1::basic_string<char>, double>::DictVectorizerOp(const onnxruntime::OpKernelInfo &) [AttrType = std::__1::basic_string<char>, TargetType = double]const T *onnxruntime::OpKernelContext::Input(int) const [T = std::__1::map<std::__1::basic_string<char>, double, std::__1::less<std::__1::basic_string<char> >, std::__1::allocator<std::__1::pair<const std::__1::basic_string<char>, double> > >]int64_vocabularyonnxruntime::ml::DictVectorizerOp<long long, std::__1::basic_string<char> >::DictVectorizerOp(const onnxruntime::OpKernelInfo &) [AttrType = long long, TargetType = std::__1::basic_string<char>]onnxruntime::ml::DictVectorizerOp<long long, float>::DictVectorizerOp(const onnxruntime::OpKernelInfo &) [AttrType = long long, TargetType = float]onnxruntime::ml::DictVectorizerOp<long long, double>::DictVectorizerOp(const onnxruntime::OpKernelInfo &) [AttrType = long long, TargetType = double]const T *onnxruntime::OpKernelContext::Input(int) const [T = std::__1::map<long long, double, std::__1::less<long long>, std::__1::allocator<std::__1::pair<const long long, double> > >]FeatureVectorizer/Users/runner/work/1/s/onnxruntime/core/providers/cpu/ml/feature_vectorizer.ccvirtual onnxruntime::common::Status onnxruntime::ml::FeatureVectorizer::Compute(onnxruntime::OpKernelContext *) constinput_count >= 0 && static_cast<size_t>(input_count) == input_dimensions_.size()Number of inputs () does not match number of inputdimensions values (Invalid input type:inputdimensions/Users/runner/work/1/s/onnxruntime/core/providers/cpu/ml/feature_vectorizer.honnxruntime::ml::FeatureVectorizer::FeatureVectorizer(const onnxruntime::OpKernelInfo &)status.IsOK() && !input_dimensions_.empty()Imputerimputed_value_floatsimputed_value_int64sreplaced_value_float/Users/runner/work/1/s/onnxruntime/core/providers/cpu/ml/imputer.cconnxruntime::ml::ImputerOp::ImputerOp(const onnxruntime::OpKernelInfo &)Expected 'replaced_value_float' attribute since 'imputed_value_floats' is specifiedreplaced_value_int64Expected 'replace_value_int64' attribute since 'imputed_values_int64' is specifiedimputed_values_float_.empty() ^ imputed_values_int64_.empty()Must provide imputed_values_float_ or imputed_values_int64_ but not both.virtual common::Status onnxruntime::ml::ImputerOp::Compute(onnxruntime::OpKernelContext *) constInvalid typeEmpty value of imputed values.Empty input dimensions.LabelEncoderInput of tensor(string) must have output of tensor(int64)Input of tensor(int64) must have output of tensor(string)keys_floatsvalues_stringskeys_stringsvalues_floatsdefault_floatkeys_int64svalues_int64sclasses_strings/Users/runner/work/1/s/onnxruntime/core/providers/cpu/ml/label_encoder.honnxruntime::ml::LabelEncoder::LabelEncoder(const onnxruntime::OpKernelInfo &)info.GetAttrs<std::string>("classes_strings", string_classes).IsOK()onnxruntime::ml::LabelEncoder_2<float, std::__1::basic_string<char> >::LabelEncoder_2(const onnxruntime::OpKernelInfo &) [TKey = float, TValue = std::__1::basic_string<char>]info.GetAttrs<TKey>(_key_field_name, keys).IsOK()info.GetAttrs<TValue>(_value_field_name, values).IsOK()num_keys == num_valuesThe attribtues in LabelEncoder (name: ) must have the same length. However, the number of key is and the number of values is onnxruntime::ml::LabelEncoder_2<std::__1::basic_string<char>, float>::LabelEncoder_2(const onnxruntime::OpKernelInfo &) [TKey = std::__1::basic_string<char>, TValue = float]onnxruntime::ml::LabelEncoder_2<long long, float>::LabelEncoder_2(const onnxruntime::OpKernelInfo &) [TKey = long long, TValue = float]onnxruntime::ml::LabelEncoder_2<float, long long>::LabelEncoder_2(const onnxruntime::OpKernelInfo &) [TKey = float, TValue = long long]onnxruntime::ml::LabelEncoder_2<long long, std::__1::basic_string<char> >::LabelEncoder_2(const onnxruntime::OpKernelInfo &) [TKey = long long, TValue = std::__1::basic_string<char>]onnxruntime::ml::LabelEncoder_2<std::__1::basic_string<char>, long long>::LabelEncoder_2(const onnxruntime::OpKernelInfo &) [TKey = std::__1::basic_string<char>, TValue = long long]onnxruntime::ml::LabelEncoder_2<long long, long long>::LabelEncoder_2(const onnxruntime::OpKernelInfo &) [TKey = long long, TValue = long long]LinearClassifiermulti_class/Users/runner/work/1/s/onnxruntime/core/providers/cpu/ml/linearclassifier.cconnxruntime::ml::LinearClassifier::LinearClassifier(const onnxruntime::OpKernelInfo &)void onnxruntime::ml::LinearClassifier::ComputeImpl(const gsl::span<const float>, int64_t, int64_t, int64_t, const std::vector<float> &, const std::vector<float> &, onnxruntime::Tensor &, onnxruntime::Tensor &, onnxruntime::ml::POST_EVAL_TRANSFORM, bool, concurrency::ThreadPool *) constscores_output_data.length() >= scores_output_sizeScores output is incorrect size. Expected: Found:Input shape needs to be at least a single dimension.Unsupported input element type of void onnxruntime::ml::CastInputToFloat(const onnxruntime::Tensor &, gsl::span<float> &) [SrcType = int]shape_size == out.length()void onnxruntime::ml::CastInputToFloat(const onnxruntime::Tensor &, gsl::span<float> &) [SrcType = long long]void onnxruntime::ml::CastInputToFloat(const onnxruntime::Tensor &, gsl::span<float> &) [SrcType = double]LinearRegressorinterceptstargets/Users/runner/work/1/s/onnxruntime/core/providers/cpu/ml/linearregressor.cconnxruntime::ml::LinearRegressor::LinearRegressor(const onnxruntime::OpKernelInfo &)info.GetAttr<int64_t>("targets", &num_targets_).IsOK()Input shape had more than 2 dimension. Dims=Normalizer/Users/runner/work/1/s/onnxruntime/core/providers/cpu/ml/normalizer.honnxruntime::ml::Normalizer::Normalizer(const onnxruntime::OpKernelInfo &)info.GetAttr<std::string>("norm", &norm).IsOK()MAXL1L2onnxruntime::ml::NORMALIZE onnxruntime::ml::MakeNormalize(const std::string &)Invalid normalize value of Rank of input to Normalized must be less than 2. Got Unexpected NORMALIZE value of OneHotEncoderUnknown Category and zeros = 0.zeros/Users/runner/work/1/s/onnxruntime/core/providers/cpu/ml/onehotencoder.cconnxruntime::ml::OneHotEncoderOp<long long>::OneHotEncoderOp(const onnxruntime::OpKernelInfo &) [T = long long]tmp_cats_int64s.empty() || tmp_cats_strings.empty()One and only one of the 'cats_*' attributes must be definednum_categories_ > 0onnxruntime::ml::OneHotEncoderOp<float>::OneHotEncoderOp(const onnxruntime::OpKernelInfo &) [T = float]onnxruntime::ml::OneHotEncoderOp<double>::OneHotEncoderOp(const onnxruntime::OpKernelInfo &) [T = double]onnxruntime::ml::OneHotEncoderOp<std::__1::basic_string<char> >::OneHotEncoderOp(const onnxruntime::OpKernelInfo &) [T = std::__1::basic_string<char>]Scaler/Users/runner/work/1/s/onnxruntime/core/providers/cpu/ml/scaler.cconnxruntime::ml::ScalerOp<float>::ScalerOp(const onnxruntime::OpKernelInfo &) [T = float]!scale_.empty()scale_.size() == offset_.size()Scale size: () != (Invalid argument: input has empty dimensions.Either both scale and offset can be of feature size () or 1onnxruntime::ml::ScalerOp<double>::ScalerOp(const onnxruntime::OpKernelInfo &) [T = double]onnxruntime::ml::ScalerOp<long long>::ScalerOp(const onnxruntime::OpKernelInfo &) [T = long long]onnxruntime::ml::ScalerOp<int>::ScalerOp(const onnxruntime::OpKernelInfo &) [T = int]SVMClassifiervectors_per_classprob_aprob_b/Users/runner/work/1/s/onnxruntime/core/providers/cpu/ml/svmclassifier.cconnxruntime::ml::SVMClassifier::SVMClassifier(const onnxruntime::OpKernelInfo &)proba_.size() == probb_.size()classlabels_intsinfo.GetAttrs<std::string>("classlabels_strings", classlabels_strings_).IsOK() || info.GetAttrs<int64_t>("classlabels_ints", classlabels_ints_).IsOK()classlabels_strings_.size() > 0 || classlabels_ints_.size() > 0coefficients_.size() > 0Unsupported data type of void onnxruntime::ml::batched_update_scores_inplace(gsl::span<T>, int64_t, int64_t, onnxruntime::ml::POST_EVAL_TRANSFORM, int, bool, concurrency::ThreadPool *) [T = float]scores.size() == static_cast<size_t>(expected_num_scores)Unexpected value for 'add_second_class' of SVMRegressorn_supportssupport_vectorspost_transformrho/Users/runner/work/1/s/onnxruntime/core/providers/cpu/ml/svmregressor.cconnxruntime::ml::SVMRegressor<float>::SVMRegressor(const onnxruntime::OpKernelInfo &) [T = float]info.GetAttrs<float>("rho", rho_).IsOK()coefficientsinfo.GetAttrs<float>("coefficients", coefficients_).IsOK()!coefficients_.empty()one_classkernel_typeLINEARkernel_params/Users/runner/work/1/s/onnxruntime/core/providers/cpu/ml/svmclassifier.honnxruntime::ml::SVMCommon::SVMCommon(const onnxruntime::OpKernelInfo &)info.GetAttrs<float>("kernel_params", kernel_params).IsOK()POLYRBFLOGISTICSOFTMAXSOFTMAX_ZEROvirtual onnxruntime::common::Status onnxruntime::ml::SVMRegressor<float>::Compute(onnxruntime::OpKernelContext *) const [T = float]num_features == feature_count_Unexpected mode:TreeEnsembleClassifierclass_idsclass_nodeidsclass_treeidsclass_weightsX dims is empty.computevoid onnxruntime::ml::detail::TreeEnsembleCommonClassifier<float, float>::compute(onnxruntime::OpKernelContext *, const onnxruntime::Tensor *, onnxruntime::Tensor *, onnxruntime::Tensor *) const [ITYPE = float, OTYPE = float]void onnxruntime::ml::detail::TreeAggregatorClassifier<float, float>::FinalizeScores(std::vector<ScoreValue<OTYPE> > &, OTYPE *, int, int64_t *) const [ITYPE = float, OTYPE = float]predictions.size() == 2int64_t onnxruntime::ml::detail::TreeAggregatorClassifier<float, float>::_set_score_binary(int &, const std::vector<ScoreValue<OTYPE> > &) const [ITYPE = float, OTYPE = float]classes.size() == 2 || classes.size() == 1void onnxruntime::ml::detail::TreeEnsembleCommonClassifier<double, float>::compute(onnxruntime::OpKernelContext *, const onnxruntime::Tensor *, onnxruntime::Tensor *, onnxruntime::Tensor *) const [ITYPE = double, OTYPE = float]void onnxruntime::ml::detail::TreeAggregatorClassifier<double, float>::FinalizeScores(std::vector<ScoreValue<OTYPE> > &, OTYPE *, int, int64_t *) const [ITYPE = double, OTYPE = float]int64_t onnxruntime::ml::detail::TreeAggregatorClassifier<double, float>::_set_score_binary(int &, const std::vector<ScoreValue<OTYPE> > &) const [ITYPE = double, OTYPE = float]onnxruntime::ml::detail::TreeEnsembleCommon<long long, float>::TreeEnsembleCommon(int, int, const std::string &, const std::vector<OTYPE> &, int64_t, const std::vector<int64_t> &, const std::vector<int64_t> &, const std::vector<OTYPE> &, const std::vector<int64_t> &, const std::vector<std::string> &, const std::vector<int64_t> &, const std::vector<int64_t> &, const std::vector<int64_t> &, const std::vector<OTYPE> &, const std::string &, const std::vector<int64_t> &, const std::vector<int64_t> &, const std::vector<int64_t> &, const std::vector<OTYPE> &) [ITYPE = long long, OTYPE = float]void onnxruntime::ml::detail::TreeEnsembleCommonClassifier<long long, float>::compute(onnxruntime::OpKernelContext *, const onnxruntime::Tensor *, onnxruntime::Tensor *, onnxruntime::Tensor *) const [ITYPE = long long, OTYPE = float]void onnxruntime::ml::detail::TreeAggregatorSum<long long, float>::ProcessTreeNodePrediction(std::vector<ScoreValue<OTYPE> > &, const TreeNodeElement<OTYPE> &) const [ITYPE = long long, OTYPE = float]void onnxruntime::ml::detail::TreeAggregatorClassifier<long long, float>::FinalizeScores(std::vector<ScoreValue<OTYPE> > &, OTYPE *, int, int64_t *) const [ITYPE = long long, OTYPE = float]int64_t onnxruntime::ml::detail::TreeAggregatorClassifier<long long, float>::_set_score_binary(int &, const std::vector<ScoreValue<OTYPE> > &) const [ITYPE = long long, OTYPE = float]void onnxruntime::ml::detail::TreeAggregatorSum<long long, float>::MergePrediction(std::vector<ScoreValue<OTYPE> > &, const std::vector<ScoreValue<OTYPE> > &) const [ITYPE = long long, OTYPE = float]onnxruntime::ml::detail::TreeEnsembleCommon<int, float>::TreeEnsembleCommon(int, int, const std::string &, const std::vector<OTYPE> &, int64_t, const std::vector<int64_t> &, const std::vector<int64_t> &, const std::vector<OTYPE> &, const std::vector<int64_t> &, const std::vector<std::string> &, const std::vector<int64_t> &, const std::vector<int64_t> &, const std::vector<int64_t> &, const std::vector<OTYPE> &, const std::string &, const std::vector<int64_t> &, const std::vector<int64_t> &, const std::vector<int64_t> &, const std::vector<OTYPE> &) [ITYPE = int, OTYPE = float]void onnxruntime::ml::detail::TreeEnsembleCommonClassifier<int, float>::compute(onnxruntime::OpKernelContext *, const onnxruntime::Tensor *, onnxruntime::Tensor *, onnxruntime::Tensor *) const [ITYPE = int, OTYPE = float]void onnxruntime::ml::detail::TreeAggregatorSum<int, float>::ProcessTreeNodePrediction(std::vector<ScoreValue<OTYPE> > &, const TreeNodeElement<OTYPE> &) const [ITYPE = int, OTYPE = float]void onnxruntime::ml::detail::TreeAggregatorClassifier<int, float>::FinalizeScores(std::vector<ScoreValue<OTYPE> > &, OTYPE *, int, int64_t *) const [ITYPE = int, OTYPE = float]int64_t onnxruntime::ml::detail::TreeAggregatorClassifier<int, float>::_set_score_binary(int &, const std::vector<ScoreValue<OTYPE> > &) const [ITYPE = int, OTYPE = float]void onnxruntime::ml::detail::TreeAggregatorSum<int, float>::MergePrediction(std::vector<ScoreValue<OTYPE> > &, const std::vector<ScoreValue<OTYPE> > &) const [ITYPE = int, OTYPE = float]TreeEnsembleRegressoraggregate_functionSUMbase_valuesn_targetsnodes_falsenodeidsnodes_featureidsnodes_hitratesnodes_missing_value_tracks_truenodes_modesnodes_nodeidsnodes_treeidsnodes_truenodeidsnodes_valuestarget_idstarget_nodeidstarget_treeidstarget_weights/Users/runner/work/1/s/onnxruntime/core/providers/cpu/ml/tree_ensemble_common.honnxruntime::ml::detail::TreeEnsembleCommon<float, float>::TreeEnsembleCommon(int, int, const std::string &, const std::vector<OTYPE> &, int64_t, const std::vector<int64_t> &, const std::vector<int64_t> &, const std::vector<OTYPE> &, const std::vector<int64_t> &, const std::vector<std::string> &, const std::vector<int64_t> &, const std::vector<int64_t> &, const std::vector<int64_t> &, const std::vector<OTYPE> &, const std::string &, const std::vector<int64_t> &, const std::vector<int64_t> &, const std::vector<int64_t> &, const std::vector<OTYPE> &) [ITYPE = float, OTYPE = float]n_targets_or_classes > 0nodes_falsenodeids.size() == nodes_featureids.size()nodes_falsenodeids.size() == nodes_modes.size()nodes_falsenodeids.size() == nodes_nodeids.size()nodes_falsenodeids.size() == nodes_treeids.size()nodes_falsenodeids.size() == nodes_truenodeids.size()nodes_falsenodeids.size() == nodes_values.size()target_class_ids.size() == target_class_nodeids.size()target_class_ids.size() == target_class_treeids.size() in tree is already there.Unable to find node (truenode).One falsenode is pointing either to itself, either to another tree. (falsenode). (weights).AVERAGEMINBRANCH_LEQLEAFBRANCH_LTBRANCH_GTEBRANCH_GTBRANCH_EQvoid onnxruntime::ml::detail::TreeEnsembleCommon<float, float>::compute(onnxruntime::OpKernelContext *, const onnxruntime::Tensor *, onnxruntime::Tensor *, onnxruntime::Tensor *) const [ITYPE = float, OTYPE = float]/Users/runner/work/1/s/onnxruntime/core/providers/cpu/ml/tree_ensemble_aggregator.hvoid onnxruntime::ml::detail::TreeAggregatorSum<float, float>::ProcessTreeNodePrediction(std::vector<ScoreValue<OTYPE> > &, const TreeNodeElement<OTYPE> &) const [ITYPE = float, OTYPE = float]it->i < (int64_t)predictions.size()void onnxruntime::ml::detail::TreeAggregatorAverage<float, float>::FinalizeScores(std::vector<ScoreValue<OTYPE> > &, OTYPE *, int, int64_t *) const [ITYPE = float, OTYPE = float]this->base_values_.size() == predictions.size()void onnxruntime::ml::detail::TreeAggregatorSum<float, float>::MergePrediction(std::vector<ScoreValue<OTYPE> > &, const std::vector<ScoreValue<OTYPE> > &) const [ITYPE = float, OTYPE = float]predictions.size() == predictions2.size()void onnxruntime::ml::detail::TreeAggregator<float, float>::FinalizeScores(std::vector<ScoreValue<OTYPE> > &, OTYPE *, int, int64_t *) const [ITYPE = float, OTYPE = float]predictions.size() == (size_t)n_targets_or_classes_void onnxruntime::ml::detail::TreeAggregatorMin<float, float>::MergePrediction(std::vector<ScoreValue<OTYPE> > &, const std::vector<ScoreValue<OTYPE> > &) const [ITYPE = float, OTYPE = float]void onnxruntime::ml::detail::TreeAggregatorMax<float, float>::MergePrediction(std::vector<ScoreValue<OTYPE> > &, const std::vector<ScoreValue<OTYPE> > &) const [ITYPE = float, OTYPE = float]onnxruntime::ml::detail::TreeEnsembleCommon<double, float>::TreeEnsembleCommon(int, int, const std::string &, const std::vector<OTYPE> &, int64_t, const std::vector<int64_t> &, const std::vector<int64_t> &, const std::vector<OTYPE> &, const std::vector<int64_t> &, const std::vector<std::string> &, const std::vector<int64_t> &, const std::vector<int64_t> &, const std::vector<int64_t> &, const std::vector<OTYPE> &, const std::string &, const std::vector<int64_t> &, const std::vector<int64_t> &, const std::vector<int64_t> &, const std::vector<OTYPE> &) [ITYPE = double, OTYPE = float]void onnxruntime::ml::detail::TreeEnsembleCommon<double, float>::compute(onnxruntime::OpKernelContext *, const onnxruntime::Tensor *, onnxruntime::Tensor *, onnxruntime::Tensor *) const [ITYPE = double, OTYPE = float]void onnxruntime::ml::detail::TreeAggregatorSum<double, float>::ProcessTreeNodePrediction(std::vector<ScoreValue<OTYPE> > &, const TreeNodeElement<OTYPE> &) const [ITYPE = double, OTYPE = float]void onnxruntime::ml::detail::TreeAggregatorAverage<double, float>::FinalizeScores(std::vector<ScoreValue<OTYPE> > &, OTYPE *, int, int64_t *) const [ITYPE = double, OTYPE = float]void onnxruntime::ml::detail::TreeAggregatorSum<double, float>::MergePrediction(std::vector<ScoreValue<OTYPE> > &, const std::vector<ScoreValue<OTYPE> > &) const [ITYPE = double, OTYPE = float]void onnxruntime::ml::detail::TreeAggregator<double, float>::FinalizeScores(std::vector<ScoreValue<OTYPE> > &, OTYPE *, int, int64_t *) const [ITYPE = double, OTYPE = float]void onnxruntime::ml::detail::TreeAggregatorMin<double, float>::MergePrediction(std::vector<ScoreValue<OTYPE> > &, const std::vector<ScoreValue<OTYPE> > &) const [ITYPE = double, OTYPE = float]void onnxruntime::ml::detail::TreeAggregatorMax<double, float>::MergePrediction(std::vector<ScoreValue<OTYPE> > &, const std::vector<ScoreValue<OTYPE> > &) const [ITYPE = double, OTYPE = float]ZipMapclasslabels_int64sclasslabels_strings/Users/runner/work/1/s/onnxruntime/core/providers/cpu/ml/zipmap.cconnxruntime::ml::ZipMapOp::ZipMapOp(const onnxruntime::OpKernelInfo &)classlabels_strings_.empty() ^ classlabels_int64s_.empty()Must provide classlabels_strings or classlabels_int64s but not both.Zipmap does not support empty dim countZipmap only supports 1D or 2D input tensorsInput features_per_batch[] != number of classlabels[T *OrtValue::GetMutable() [T = std::__1::vector<std::__1::map<std::__1::basic_string<char>, float, std::__1::less<std::__1::basic_string<char> >, std::__1::allocator<std::__1::pair<const std::__1::basic_string<char>, float> > >, std::__1::allocator<std::__1::map<std::__1::basic_string<char>, float, std::__1::less<std::__1::basic_string<char> >, std::__1::allocator<std::__1::pair<const std::__1::basic_string<char>, float> > > > >]T *OrtValue::GetMutable() [T = std::__1::vector<std::__1::map<long long, float, std::__1::less<long long>, std::__1::allocator<std::__1::pair<const long long, float> > >, std::__1::allocator<std::__1::map<long long, float, std::__1::less<long long>, std::__1::allocator<std::__1::pair<const long long, float> > > > >]MaxUnpool/Users/runner/work/1/s/onnxruntime/core/providers/cpu/nn/Unpool.ccIndex tensor shape should be same as that of the input data tensor to unpool.Shape must be 1 dimensional as it's tensor data of a shapeoutput_shape is smaller than minimum required. output_shape: inferred output shape:/Users/runner/work/1/s/onnxruntime/core/providers/cpu/nn/unpool.honnxruntime::MaxUnpool::MaxUnpool(const onnxruntime::OpKernelInfo &)info.GetAttrs<int64_t>("kernel_shape", kernel_shape_).IsOK()kernel_shape_[dim] > 0pads_[dim] < kernel_shape_[dim] && pads_[dim + kernel_shape_.size()] < kernel_shape_[dim]strides_.size() == kernel_shape_.size()BatchNormalizationspatial/Users/runner/work/1/s/onnxruntime/core/providers/cpu/nn/batch_norm.honnxruntime::BatchNorm<float>::BatchNorm(const onnxruntime::OpKernelInfo &) [T = float]!is_train_Invalid input X: The rank of input X must be atleast 2. Got rank: Invalid input scale: NumDimensions() != Invalid input scale: 0th dimension != Invalid input scale: dimension != Invalid input B: NumDimensions() != Invalid input B: 0th dimension != Invalid input B: Invalid input mean: NumDimensions() != Invalid input mean: 0th dimension != Invalid input mean: Invalid input var: NumDimensions() != Invalid input var: 0th dimension != Invalid input var: onnxruntime::BatchNorm<double>::BatchNorm(const onnxruntime::OpKernelInfo &) [T = double]/Users/runner/work/1/s/onnxruntime/core/providers/cpu/nn/conv.ccConvX num_dims does not match W num_dims. X: W: Input channels C is not equal to kernel channels * group. C: kernel channels: group: Output channels M is not divisible by group. M: kernel_shape num_dims is not compatible with W num_dims. kernel_shape: kernel_shape is not compatible with W shape.Not enough elements in strides. Expected: Not enough elements in kernel shape. Expected: Not enough elements in dilations. Expected: Not enough elements in pads. Expected: /Users/runner/work/1/s/onnxruntime/core/providers/cpu/nn/conv_attributes.hInferOutputShapeInvalid input shape: /Users/runner/work/1/s/onnxruntime/core/providers/common.hComputePadAndOutputShapeDilation not supported for AutoPadType::SAME_UPPER or AutoPadType::SAME_LOWER.ComputePad: pad type not supported.kernel_shapestridesonnxruntime::ConvAttributes::ConvAttributes(const onnxruntime::OpKernelInfo &)auto_pad == AutoPadType::NOTSETA Conv/ConvTranspose node has both 'auto_pad' and 'pads' attributesdilationsgroupNOTSETVALIDSAME_UPPERSAME_LOWERonnxruntime::AutoPadType onnxruntime::StringToAutoPadType(const std::string &)T3ConvInteger/Users/runner/work/1/s/onnxruntime/core/providers/cpu/nn/conv_integer.ccvirtual onnxruntime::common::Status onnxruntime::ConvInteger::Compute(onnxruntime::OpKernelContext *) constIsScalarOr1ElementVector(X_Zero_Point)IsScalarOr1ElementVector(W_Zero_Point)ConvTranspose/Users/runner/work/1/s/onnxruntime/core/providers/cpu/nn/conv_transpose.ccDoConvTransposeoutput_paddingoutput_shapegroup count is <= 0filter number not equal to input channel number. filter_number: num_input_channels: Input channels is not divisible by group./Users/runner/work/1/s/onnxruntime/core/providers/cpu/nn/conv_transpose_attributes.hvoid onnxruntime::ConvTransposeAttributes::ComputePadsAndOutputShape(onnxruntime::TensorShape, int64_t, const std::vector<int64_t> &, const std::vector<int64_t> &, const std::vector<int64_t> &, const std::vector<int64_t> &, const int64_t, std::vector<int64_t> *, std::vector<int64_t> *) constdim_size > 0void onnxruntime::ConvTransposeAttributes::ComputeTransposePadAndOutputShape(const int64_t, const int64_t, const int64_t, const int64_t, const int64_t, onnxruntime::AutoPadType, int64_t *, int64_t *, int64_t *) const*out_size >= 0/Users/runner/work/1/s/onnxruntime/core/providers/cpu/nn/dropout_op.hvirtual onnxruntime::common::Status onnxruntime::Dropout<float, float>::Compute(onnxruntime::OpKernelContext *) const [T1 = float, T2 = float]!mask || mask->Shape() == X_shapefloat onnxruntime::(anonymous namespace)::GetRatioOrDefault(const onnxruntime::Tensor *) [T2 = float]ratio_tensor->Shape().Size() == 10.0f <= ratio_value && ratio_value < 1.0fvirtual onnxruntime::common::Status onnxruntime::Dropout<float, double>::Compute(onnxruntime::OpKernelContext *) const [T1 = float, T2 = double]float onnxruntime::(anonymous namespace)::GetRatioOrDefault(const onnxruntime::Tensor *) [T2 = double]virtual onnxruntime::common::Status onnxruntime::Dropout<double, float>::Compute(onnxruntime::OpKernelContext *) const [T1 = double, T2 = float]virtual onnxruntime::common::Status onnxruntime::Dropout<double, double>::Compute(onnxruntime::OpKernelContext *) const [T1 = double, T2 = double]Flatten/Users/runner/work/1/s/onnxruntime/core/providers/cpu/nn/flatten.honnxruntime::Flatten::Flatten(const onnxruntime::OpKernelInfo &)virtual onnxruntime::common::Status onnxruntime::Flatten::Compute(onnxruntime::OpKernelContext *) constgsl::narrow_cast<int64_t>(X_shape.NumDimensions()) >= axisInstanceNormalization/Users/runner/work/1/s/onnxruntime/core/providers/cpu/nn/instance_norm.ccepsilon/Users/runner/work/1/s/onnxruntime/core/providers/cpu/nn/instance_norm.honnxruntime::InstanceNorm<float>::InstanceNorm(const onnxruntime::OpKernelInfo &) [T = float]op_kernel_info.GetAttr<float>("epsilon", &epsilon_).IsOK()Invalid input data: number of dimensions is less than 3: Invalid input scale: number of dimensions is not 1: Mismatch between input data and scale: size of scale != input channel count vs. Invalid input B: number of dimensions is not 1: Mismatch between input data and B: size of B != input channel count LpNormalization/Users/runner/work/1/s/onnxruntime/core/providers/cpu/nn/lp_norm.honnxruntime::LpNorm<float>::LpNorm(const onnxruntime::OpKernelInfo &) [T = float]op_kernel_info.GetAttr<int64_t>("axis", &axis_).IsOK()op_kernel_info.GetAttr<int64_t>("p", &p_).IsOK()p_ == 1 || p_ == 2onnxruntime::LpNorm<double>::LpNorm(const onnxruntime::OpKernelInfo &) [T = double]input count mismatch/Users/runner/work/1/s/onnxruntime/core/providers/cpu/nn/lrn.ccvirtual onnxruntime::common::Status onnxruntime::LRN<float>::Compute(onnxruntime::OpKernelContext *) const [T = float]X->Shape().NumDimensions() == 4LRN/Users/runner/work/1/s/onnxruntime/core/providers/cpu/nn/lrn.honnxruntime::LRN<float>::LRN(const onnxruntime::OpKernelInfo &) [T = float]info.GetAttr<int64_t>("size", &size).IsOK()size_ > 0size_ % 2 == 1info.GetAttr<float>("alpha", &alpha_).IsOK()alpha_ > 0.0finfo.GetAttr<float>("beta", &beta_).IsOK()beta_ > 0.0f/Users/runner/work/1/s/onnxruntime/core/providers/cpu/nn/pool.ccInput dimension cannot be less than 3.Unsupported pooling size.kernel_shape num_dims is not compatible with X num_dims.AveragePoolMaxPoolLpPoolGlobalLpPoolGlobalAveragePoolGlobalMaxPool/Users/runner/work/1/s/onnxruntime/core/providers/cpu/nn/pool_attributes.hstd::vector<int64_t> onnxruntime::PoolAttributes::SetOutputSize(const onnxruntime::TensorShape &, int64_t, std::vector<int64_t> *) constinput_shape.Size() > 0 || input_shape[0] == 0Invalid input shape. Only N can be zero. Got:void onnxruntime::PoolAttributes::InferOutputSize(const std::vector<int64_t> &, std::vector<int64_t> *, std::vector<int64_t> *) constinput_dims.size() >= 2void onnxruntime::PoolAttributes::ComputeSizePadDilations(const int64_t, const int64_t, const int64_t, int64_t *, int64_t *, int64_t, int64_t *) constonnxruntime::PoolAttributes::PoolAttributes(const OpNodeProtoHelper<onnxruntime::ProtoHelperNodeContext> &, const std::string &, int)info.GetAttrs<int64_t>("kernel_shape", kernel_shape).IsOK()info.GetAttr<std::string>("auto_pad", &auto_padding).IsOK()ceil_modecount_include_padinfo.GetAttr<int64_t>("count_include_pad", &temp).IsOK()storage_orderinfo.GetAttr("storage_order", &storage_order).IsOK()kernel_shape[dim] > 0pads[dim] < kernel_shape[dim] && pads[dim + kernel_shape.size()] < kernel_shape[dim]strides.size() == kernel_shape.size()dilations.size() == kernel_shape.size()/Users/runner/work/1/s/onnxruntime/core/providers/cpu/nn/pool_base.hvoid onnxruntime::PoolProcessContext::init(const onnxruntime::OpKernelInfo &)info.GetAttr<int64_t>("p", &p_).IsOK()Unsupported pooling size : T4QLinearConv/Users/runner/work/1/s/onnxruntime/core/providers/cpu/nn/qlinearconv.ccvirtual onnxruntime::common::Status onnxruntime::QLinearConv::UseSharedPrePackedBuffers(std::vector<BufferUniquePtr> &, int, bool &)prepacked_buffers[0].get() == nullptrvirtual onnxruntime::common::Status onnxruntime::QLinearConv::Compute(onnxruntime::OpKernelContext *) constIsScalarOr1ElementVector(X_zero_point)QLinearConv : input zero point must be a scalar or 1D tensor of size 1IsScalarOr1ElementVector(Y_zero_point)QLinearConv : result zero point must be a scalar or 1D tensor of size 1IsScalarOr1ElementVector(X_scale)QLinearConv : input scale must be a scalar or 1D tensor of size 1IsScalarOr1ElementVector(Y_scale)QLinearConv : result scale must be a scalar or 1D tensor of size 1channels_lastMaxRoiPool/Users/runner/work/1/s/onnxruntime/core/providers/cpu/nn/roi_pool.ccvirtual onnxruntime::common::Status onnxruntime::RoiPool<float>::Compute(onnxruntime::OpKernelContext *) const [T = float]R->Shape()[1] == 5roi_batch_id >= 0roi_batch_id < batch_sizepooled_shape/Users/runner/work/1/s/onnxruntime/core/providers/cpu/nn/roi_pool.honnxruntime::RoiPool<float>::RoiPool(const onnxruntime::OpKernelInfo &) [T = float]info.GetAttrs<int64_t>("pooled_shape", pooled_shape).IsOK()pooled_shape.size() == 2pooled_height_ > 0pooled_width_ > 0spatial_scaleinfo.GetAttr<float>("spatial_scale", &spatial_scale_).IsOK()spatial_scale_ > 0Shrink/Users/runner/work/1/s/onnxruntime/core/providers/cpu/nn/shrink.honnxruntime::Shrink::Shrink(const onnxruntime::OpKernelInfo &)op_kernel_info.GetAttr<float>("bias", &bias_temp).IsOK()lambdop_kernel_info.GetAttr<float>("lambd", &lambd_temp).IsOK()StringNormalizer/Users/runner/work/1/s/onnxruntime/core/providers/cpu/nn/string_normalizer.cconnxruntime::StringNormalizer::StringNormalizer(const onnxruntime::OpKernelInfo &)LOWERUPPERlocalestopwords!sw.empty()wstr != wconv_errorSingle dimension value must be greater than 0Input dimensions are either[C > 0] or [1][C > 0] allowedInput contains invalid utf8 chars at: auto onnxruntime::string_normalizer::Locale::Locale(const std::string &)::(anonymous class)::operator()() constFailed to construct locale with name::Please, install necessary language-pack-XX and configure localeswstring_convert: from_bytes errorwstring_convert: to_bytes errorTfIdfVectorizer/Users/runner/work/1/s/onnxruntime/core/providers/cpu/nn/tfidfvectorizer.cconnxruntime::TfIdfVectorizer::TfIdfVectorizer(const onnxruntime::OpKernelInfo &)TFIDFTFIDFimpl_->weighting_criteria_ != kNonemode: is unrecognized, acceptable values are TF,IDF,TFIDFmin_gram_lengthimpl_->min_gram_length_ > 0Required min_gram_length must be positive: max_gram_lengthimpl_->max_gram_length_ >= impl_->min_gram_length_min_gram_length >= max_gram_length required: >= max_skip_countimpl_->max_skip_count_ >= 0max_skip_count must be non-negative: ngram_countsstatus.IsOK() && !impl_->ngram_counts_.empty()size_t(impl_->min_gram_length_) <= impl_->ngram_counts_.size()min_gram_length must be inbounds of ngram_counts: <= size_t(impl_->max_gram_length_) <= impl_->ngram_counts_.size()max_gram_length must be inbounds of ngram_counts: ngram_indexesstatus.IsOK() && !impl_->ngram_indexes_.empty()std::all_of(impl_->ngram_indexes_.cbegin(), impl_->ngram_indexes_.cend(), [](int64_t i) { return i >= 0; })weightsimpl_->weights_.size() == impl_->ngram_indexes_.size()Got weights of size: but ngram_indexes size: must be of equal sizepool_strings!pool_strings.empty()pool_int64sstatus.IsOK() && !pool_int64s.empty()end_idx >= start_idx && end_idx <= total_itemsn-gram counts out of bounds for -grams(items % ngram_size == 0)Number of items must compose whole Input shape must have either [C] or [B,C] dimensions with B > 0.size_t onnxruntime::ngram_details::PopulateGrams(ForwardIter, size_t, size_t, size_t, Map &) [K = long long, ForwardIter = const long long *, Map = std::__1::unordered_map<long long, std::__1::unique_ptr<onnxruntime::ngram_details::NgramPart<int64_t>, std::__1::default_delete<onnxruntime::ngram_details::NgramPart<int64_t> > >, std::__1::hash<long long>, std::__1::equal_to<long long>, std::__1::allocator<std::__1::pair<const long long, std::__1::unique_ptr<onnxruntime::ngram_details::NgramPart<int64_t>, std::__1::default_delete<onnxruntime::ngram_details::NgramPart<int64_t> > > > > >]p.first->second->id_ == 0Duplicate ngram detected, size: id: size_t onnxruntime::ngram_details::PopulateGrams(ForwardIter, size_t, size_t, size_t, Map &) [K = std::__1::basic_string<char>, ForwardIter = std::__1::__wrap_iter<std::__1::reference_wrapper<const std::__1::basic_string<char> > *>, Map = std::__1::unordered_map<std::__1::reference_wrapper<const std::__1::basic_string<char> >, std::__1::unique_ptr<onnxruntime::ngram_details::NgramPart<std::string>, std::__1::default_delete<onnxruntime::ngram_details::NgramPart<std::string> > >, std::__1::hash<std::__1::basic_string<char> >, std::__1::equal_to<std::__1::basic_string<char> >, std::__1::allocator<std::__1::pair<const std::__1::reference_wrapper<const std::__1::basic_string<char> >, std::__1::unique_ptr<onnxruntime::ngram_details::NgramPart<std::string>, std::__1::default_delete<onnxruntime::ngram_details::NgramPart<std::string> > > > > >]NonMaxSuppression/Users/runner/work/1/s/onnxruntime/core/providers/cpu/object_detection/non_max_suppression.ccstatic onnxruntime::common::Status onnxruntime::NonMaxSuppressionBase::PrepareCompute(onnxruntime::OpKernelContext *, onnxruntime::PrepareContext &)boxes_tensorscores_tensorboxes must be a 3D tensor.scores must be a 3D tensor.boxes and scores should have same num_batches.boxes and scores should have same spatial_dimension.The most inner dimension in boxes must have 4 data.GetThresholdsFromInputsiou_threshold must be in range [0, 1].virtual onnxruntime::common::Status onnxruntime::NonMaxSuppression::Compute(onnxruntime::OpKernelContext *) constoutput != nullptrcenter_point_box/Users/runner/work/1/s/onnxruntime/core/providers/cpu/object_detection/non_max_suppression.honnxruntime::NonMaxSuppressionBase::NonMaxSuppressionBase(const onnxruntime::OpKernelInfo &)0 == center_point_box_ || 1 == center_point_box_RoiAlignNull input X ptrNull rois_ptrNull batch_indices_ptrNumber of dimensions for batch indices should be exactly 1Number of dimensions for rois should be exactly Second dimension for rois should be exactly First dimension (num_rois) of batch_indices and rois don't matchavg/Users/runner/work/1/s/onnxruntime/core/providers/cpu/object_detection/roialign.honnxruntime::RoiAlignBase::RoiAlignBase(const onnxruntime::OpKernelInfo &)Invalid mode of value specified. It should be either avg or maxoutput_heightoutput_widthsampling_ratiosampling_ratio_ >= 0Sampling ratio should be >=0, but it was ReduceL1ReduceL2ReduceLogSumReduceLogSumExpReduceMaxReduceMeanReduceMinReduceProdReduceSumReduceSumSquareArgMaxArgMin/Users/runner/work/1/s/onnxruntime/core/providers/cpu/reduction/reduction_ops.ccvoid onnxruntime::ResultsNoTransposePrepareForReduce::ValidateNotEmpty()last_loop_red_size > 0last_loop_size > 0projected_index.size() > 0void onnxruntime::ValidateNoTransposeReduce(int64_t)count == 1void onnxruntime::ValidateCommonFastReduce(const onnxruntime::Tensor *)keepdims/Users/runner/work/1/s/onnxruntime/core/providers/cpu/reduction/reduction_ops.honnxruntime::ReduceKernelBase<false>::ReduceKernelBase(const onnxruntime::OpKernelInfo &, optional<int64_t>) [allow_multi_axes = false]info.GetAttr("keepdims", &keepdims).IsOK()noop_with_empty_axesselect_last_indexvoid onnxruntime::ValidateFastReduceKR(const std::vector<int64_t> &, const onnxruntime::Tensor &)fast_shape.size() == 2fast_shape[0] == output.Shape().Size()void onnxruntime::ValidateFastReduceRK(const std::vector<int64_t> &, const onnxruntime::Tensor &)fast_shape[1] == output.Shape().Size()void onnxruntime::ValidateFastReduceKRK(const std::vector<int64_t> &, const onnxruntime::Tensor &)fast_shape.size() == 3fast_shape[0] * fast_shape[2] == output.Shape().Size()void onnxruntime::ValidateMustBeOverloaded()void onnxruntime::ValidateKeepDims(const onnxruntime::TensorShape &, int64_t)Can't reduce on dim with value of 0 if 'keepdims' is false. Invalid output shape would be produced. input_shape:onnxruntime::ReduceKernelBase<true>::ReduceKernelBase(const onnxruntime::OpKernelInfo &, optional<int64_t>) [allow_multi_axes = true]GRU/Users/runner/work/1/s/onnxruntime/core/providers/cpu/rnn/deep_cpu_gru.ccvirtual onnxruntime::common::Status onnxruntime::DeepCpuGruOp::Compute(onnxruntime::OpKernelContext *) constInvalid data type for GRU operator of /Users/runner/work/1/s/onnxruntime/core/providers/cpu/rnn/deep_cpu_gru.honnxruntime::DeepCpuGruOp::DeepCpuGruOp(const onnxruntime::OpKernelInfo &)info.GetAttr("direction", &direction).IsOK()linear_before_resetinfo.GetAttr("linear_before_reset", &int64_value).IsOK()hidden_sizeinfo.GetAttr("hidden_size", &int64_value).IsOK() && int64_value > 0activationsactivation_alphaactivation_betaclip_ > 0.fsigmoidtanhactivation_func_names.size() == static_cast<size_t>(num_directions_) * 2layoutlayout_ == 0Batchwise recurrent operations (layout == 1) are not supported. If you need support create a github issue with justification.forwardreversebidirectional/Users/runner/work/1/s/onnxruntime/core/providers/cpu/rnn/rnn_helpers.honnxruntime::rnn::detail::Direction onnxruntime::rnn::detail::MakeDirection(const std::string &)Invalid 'direction' argument of ''. Must be one of 'forward', 'reverse', or 'bidirectional'.ComputeImplgsl::span<const T> onnxruntime::Tensor::DataAsSpan() const [T = float]gsl::span<const T> onnxruntime::Tensor::DataAsSpan() const [T = int]gsl::span<T> onnxruntime::Tensor::MutableDataAsSpan() [T = float]void onnxruntime::rnn::detail::ComputeGemm(const int, const int, const int, const float, TSpanAIter, TSpanAIter, const int, TSpanBIter, TSpanBIter, const int, const float, TSpanCIter, TSpanCIter, const int, concurrency::ThreadPool *) [TSpanAIter = const float *, TSpanBIter = const float *, TSpanCIter = float *]lda >= K && ldb >= K && ldc >= NA + (M * lda - (lda - K)) <= A_endB + (N * ldb - (ldb - K)) <= B_endC + (M * ldc - (ldc - N)) <= C_endconst T *onnxruntime::rnn::detail::SafeRawConstPointer(typename gsl::span<T>::const_iterator, typename gsl::span<T>::const_iterator, size_t) [T = float]cur + size <= endT *onnxruntime::rnn::detail::SafeRawPointer(typename gsl::span<T>, size_t, size_t) [T = float]offset + size <= size_t(span.size())T *onnxruntime::rnn::detail::SafeRawPointer(typename gsl::span<T>::iterator, typename gsl::span<T>::iterator, size_t) [T = float]void onnxruntime::rnn::detail::ComputeGemm(const int, const int, const int, const float, TSpanAIter, TSpanAIter, const int, TSpanBIter, TSpanBIter, const int, const float, TSpanCIter, TSpanCIter, const int, concurrency::ThreadPool *) [TSpanAIter = float *, TSpanBIter = const float *, TSpanCIter = float *]LSTM/Users/runner/work/1/s/onnxruntime/core/providers/cpu/rnn/deep_cpu_lstm.ccPrePackvirtual onnxruntime::common::Status onnxruntime::DeepCpuLstmOp::Compute(onnxruntime::OpKernelContext *) constInvalid data type for LSTM operator of /Users/runner/work/1/s/onnxruntime/core/providers/cpu/rnn/lstm_base.honnxruntime::LSTMBase::LSTMBase(const onnxruntime::OpKernelInfo &)input_forgetactivation_func_names.size() == static_cast<size_t>(num_directions_) * 3/Users/runner/work/1/s/onnxruntime/core/providers/cpu/rnn/lstm_base.ccRNN/Users/runner/work/1/s/onnxruntime/core/providers/cpu/rnn/rnn.ccAffine/Users/runner/work/1/s/onnxruntime/core/providers/cpu/rnn/rnn.honnxruntime::RNN<float>::RNN(const onnxruntime::OpKernelInfo &) [T = float]info.GetAttr("direction", &direction_).IsOK()allowed_directions.find(direction_) != allowed_directions.end()info.GetAttrs("activations", activations_).IsOK()info.GetAttr("hidden_size", &hidden_size_).IsOK()activations_.size() == static_cast<size_t>(num_directions)allowed_activations.find(activations_[direction]) != allowed_activations.end()RNN op: Invalid activation attribute - Input X must have 3 dimensions only. Actual:Input W must have shape {*}. Actual:Input R must have shape {Input B must have shape {Input sequence_lens must have shape {Invalid value/s in sequence_lens. All values must be > 0 and < seq_length. seq_length=Input initial_h must have shape {affinereluleakyreluthresholdedreluscaledtanhhardsigmoidelusoftsignsoftplus/Users/runner/work/1/s/onnxruntime/core/providers/cpu/rnn/rnn_helpers.ccstd::string onnxruntime::rnn::detail::NormalizeActivationArgumentAndGetAlphaBetaCount(const std::string &, std::vector<float>::const_iterator &, const std::vector<float>::const_iterator &, std::vector<float>::const_iterator &, const std::vector<float>::const_iterator &, float &, float &)Expecting activation to be one of Affine, Relu, LeakyRelu, ThresholdedRelu, Tanh, ScaledTanh, Sigmoid, HardSigmoid, Elu, Softsign, Softplus. Got void onnxruntime::rnn::detail::ComputeGemm(const int, const int, const int, const float, const float *, const float *, const GemmWeights<float> &, const float, float *, float *, const int, uint8_t *, int32_t *, concurrency::ThreadPool *)A + (M * K) <= A_endvoid onnxruntime::rnn::detail::ComputeGemm(const int, const int, const int, const float, const float *, const float *, const GemmWeights<uint8_t> &, const float, float *, float *, const int, uint8_t *, int32_t *, concurrency::ThreadPool *)weights.quant_para_alpha == 1.0f && (beta == 0.0f || beta == 1.0f)Quantized GEMM only support alpha equal to 1.0f and beta equal to 0.0f or 1.0fonnxruntime::rnn::detail::deepcpu::ActivationFuncPtr onnxruntime::rnn::detail::deepcpu::ActivationFuncByName(const std::string &)Invalid activation function of onnxruntime::rnn::detail::deepcpu::LstmMergeGatesFuncPtr onnxruntime::rnn::detail::deepcpu::LstmMergeGatesFuncByName(const std::string &)Invalid LSTM merge activation function of onnxruntime::rnn::detail::deepcpu::GruResetGateFuncPtr onnxruntime::rnn::detail::deepcpu::GruResetGateFuncByName(const std::string &)Invalid GRU reset gate activation function: onnxruntime::rnn::detail::deepcpu::GruOutputGateFuncPtr onnxruntime::rnn::detail::deepcpu::GruOutputGateFuncByName(const std::string &)Invalid GRU hidden gate activation function: rows[const T *onnxruntime::rnn::detail::SafeRawConstPointer(gsl::span<T>, size_t, size_t) [T = const float]const T *onnxruntime::rnn::detail::SafeRawConstPointer(gsl::span<T>, size_t, size_t) [T = float]ConcatFromSequence/Users/runner/work/1/s/onnxruntime/core/providers/cpu/sequence/concat_from_sequence.ccvirtual onnxruntime::common::Status onnxruntime::ConcatFromSequence::Compute(onnxruntime::OpKernelContext *) constSSequenceLength/Users/runner/work/1/s/onnxruntime/core/providers/cpu/sequence/sequence_ops.ccvirtual onnxruntime::common::Status onnxruntime::SequenceLength::Compute(onnxruntime::OpKernelContext *) constY != nullptrSequenceAtvirtual onnxruntime::common::Status onnxruntime::SequenceAt::Compute(onnxruntime::OpKernelContext *) constI != nullptrInvalid sequence index () specified for sequence of size (SequenceEmptyvirtual onnxruntime::common::Status onnxruntime::SequenceEmpty::Compute(onnxruntime::OpKernelContext *) constUnsupported 'dtype' value: SequenceInsertCreateCopyAndAppendCpuTensorvirtual onnxruntime::common::Status onnxruntime::SequenceInsert::Compute(onnxruntime::OpKernelContext *) constS != nullptrData type of the input tensor MUST be same as that of the input sequence. Sequence data type (), input tensor data type (SequenceErasevirtual onnxruntime::common::Status onnxruntime::SequenceErase::Compute(onnxruntime::OpKernelContext *) constSequenceConstructvirtual onnxruntime::common::Status onnxruntime::SequenceConstruct::Compute(onnxruntime::OpKernelContext *) constnum_inputs >= 1Violation of the requirment that all input tensors must have the same data type.SplitToSequenceSplitToSequence operator does not support split_size_sum () != split_dim_size (int64_t onnxruntime::GetSeqIdx(const onnxruntime::Tensor &)onnxruntime::common::Status onnxruntime::SplitToSequence::ComputeImpl(onnxruntime::OpKernelContext &, const onnxruntime::Tensor &, const onnxruntime::Tensor *) const [T = float]split_scalar > 0std::all_of(split_sizes.cbegin(), split_sizes.cend(), [](int64_t value) { return value >= 0; })int64_t onnxruntime::GetScalarSplitInput(const onnxruntime::Tensor &)Invalid data type for split tensor void onnxruntime::GetSplitSizesInput(const onnxruntime::Tensor &, std::vector<int64_t> &)onnxruntime::common::Status onnxruntime::SplitToSequence::ComputeImpl(onnxruntime::OpKernelContext &, const onnxruntime::Tensor &, const onnxruntime::Tensor *) const [T = double]onnxruntime::common::Status onnxruntime::SplitToSequence::ComputeImpl(onnxruntime::OpKernelContext &, const onnxruntime::Tensor &, const onnxruntime::Tensor *) const [T = int]onnxruntime::common::Status onnxruntime::SplitToSequence::ComputeImpl(onnxruntime::OpKernelContext &, const onnxruntime::Tensor &, const onnxruntime::Tensor *) const [T = long long]onnxruntime::common::Status onnxruntime::SplitToSequence::ComputeImpl(onnxruntime::OpKernelContext &, const onnxruntime::Tensor &, const onnxruntime::Tensor *) const [T = std::__1::basic_string<char>]T2Cast/Users/runner/work/1/s/onnxruntime/core/providers/cpu/tensor/cast_op.cconnxruntime::(anonymous namespace)::Cast::Cast(const onnxruntime::OpKernelInfo &)NaN-INFINF%.8gtypename std::enable_if<std::is_floating_point<SrcType>::value, void>::type onnxruntime::(anonymous namespace)::CastToString(const SrcType &, std::string &) [SrcType = float]snprintf_result > 0snprintf() failed with return value: snprintf_result > 0 && gsl::narrow_cast<size_t>(snprintf_result) == buffer_span.size() - 1typename std::enable_if<std::is_floating_point<SrcType>::value, void>::type onnxruntime::(anonymous namespace)::CastToString(const SrcType &, std::string &) [SrcType = double]Compress/Users/runner/work/1/s/onnxruntime/core/providers/cpu/tensor/compress.ccvirtual onnxruntime::common::Status onnxruntime::Compress::Compute(onnxruntime::OpKernelContext *) constaxes_right_stride >= 0 && static_cast<uint64_t>(axes_right_stride) < std::numeric_limits<size_t>::max()Concat/Users/runner/work/1/s/onnxruntime/core/providers/cpu/tensor/concat.ccPrepareForComputeCannot concatenate scalarsonnxruntime::common::Status onnxruntime::ConcatBase::PrepareForCompute(onnxruntime::OpKernelContext *, const std::vector<const Tensor *> &, onnxruntime::Prepare &) constinputs_n_rank == inputs_0_rankRanks of input data are different, cannot concatenate them. expected rank: got: Non concat axis dimensions must match: Axis has mismatched dimensions of Data type mismatch/Users/runner/work/1/s/onnxruntime/core/providers/cpu/tensor/concatbase.honnxruntime::ConcatBase::ConcatBase(const onnxruntime::OpKernelInfo &, bool)DynamicQuantizeLinear/Users/runner/work/1/s/onnxruntime/core/providers/cpu/tensor/dynamicquantizelinear.ccvirtual onnxruntime::common::Status onnxruntime::DynamicQuantizeLinear<unsigned char>::Compute(onnxruntime::OpKernelContext *) const [T = unsigned char]x_ptr != nullptrEyeLikedtypeGather/Users/runner/work/1/s/onnxruntime/core/providers/cpu/tensor/gather.cc/Users/runner/work/1/s/onnxruntime/core/providers/cpu/tensor/gatherbase.honnxruntime::GatherBase::GatherBase(const onnxruntime::OpKernelInfo &)info.GetAttr<int64_t>("axis", &axis_).IsOK()indices element out of data bounds, idx= must be within the inclusive range [GatherElementsGatherElements op: Rank of input 'data' needs to be equal to rank of input 'indices'GatherElements op: 'indices' shape should have values within bounds of 'data' shape. Invalid value in indices shape is: GatherElements op: Data type of input 'data' should match the data type of the output/Users/runner/work/1/s/onnxruntime/core/providers/cpu/tensor/gather_elements.honnxruntime::GatherElements::GatherElements(const onnxruntime::OpKernelInfo &)/Users/runner/work/1/s/onnxruntime/core/providers/cpu/tensor/gather_elements.ccauto onnxruntime::core_impl(const onnxruntime::Tensor *, const onnxruntime::Tensor *, onnxruntime::Tensor *, int64_t, concurrency::ThreadPool *)::(anonymous class)::operator()(ptrdiff_t) constGatherElements op: Value in indices must be within bounds [ , ]. Actual value is invalid index found, index = GatherND/Users/runner/work/1/s/onnxruntime/core/providers/cpu/tensor/gather_nd.ccvirtual onnxruntime::common::Status onnxruntime::GatherND::Compute(onnxruntime::OpKernelContext *) constinput_tensor != nullptr && indices_tensor != nullptrlast dimension of indices must not be larger than rank of input tensorbatch_dimsDropoutIdentity/Users/runner/work/1/s/onnxruntime/core/providers/cpu/tensor/identity_op.hvirtual onnxruntime::common::Status onnxruntime::IdentityOp<true>::Compute(onnxruntime::OpKernelContext *) const [is_dropout = true]const T *onnxruntime::OpKernelContext::Input(int) const [T = onnxruntime::TensorSeq]virtual onnxruntime::common::Status onnxruntime::IdentityOp<false>::Compute(onnxruntime::OpKernelContext *) const [is_dropout = false]IsInfdetect_positive/Users/runner/work/1/s/onnxruntime/core/providers/cpu/tensor/isinf.cconnxruntime::IsInf::IsInf(const onnxruntime::OpKernelInfo &)detect_negativeIsNaNNull input ptrMeanVarianceNormalizationInput is expected to have four dimensions corresponding to [N,C,H,W]NonZero/Users/runner/work/1/s/onnxruntime/core/providers/cpu/tensor/nonzero_op.ccvirtual onnxruntime::common::Status onnxruntime::NonZero<bool>::Compute(onnxruntime::OpKernelContext *) const [T = bool]virtual onnxruntime::common::Status onnxruntime::NonZero<unsigned char>::Compute(onnxruntime::OpKernelContext *) const [T = unsigned char]virtual onnxruntime::common::Status onnxruntime::NonZero<int>::Compute(onnxruntime::OpKernelContext *) const [T = int]virtual onnxruntime::common::Status onnxruntime::NonZero<long long>::Compute(onnxruntime::OpKernelContext *) const [T = long long]virtual onnxruntime::common::Status onnxruntime::NonZero<float>::Compute(onnxruntime::OpKernelContext *) const [T = float]OneHotInvalid argument for depth; it's not a scalar.Invalid argument for values; either it's rank is more than 1 or it has more than 2 elements/Users/runner/work/1/s/onnxruntime/core/providers/cpu/tensor/onehot.ccDepth is negative.PadCannot use 'reflect' mode to pad dimension with a value of 0. Input shape:Unexpected mode of /Users/runner/work/1/s/onnxruntime/core/providers/cpu/tensor/pad.ccvirtual onnxruntime::common::Status onnxruntime::Pad::Compute(onnxruntime::OpKernelContext *) constpads_tensor.IsDataType<int64_t>()pads_tensor_dims.size() == 1 || (pads_tensor_dims.size() == 2 && pads_tensor_dims[0] == 1)Pads tensor should be a 1D tensor of shape [2 * input_rank] or a 2D tensor of shape [1, 2 * input_rank]pads_size == 2 * data_rankPads tensor size should be equal to twice the input dimension count value_tensor->DataType() == data_type && value_tensor->Shape().Size() == 1Value tensor should be a 1D tensor of size 1 with the same type as that of the input tensorUnsupported input data type of valueconstantreflectedge/Users/runner/work/1/s/onnxruntime/core/providers/cpu/tensor/padbase.honnxruntime::PadBase::PadBase(const onnxruntime::OpKernelInfo &)onnxruntime::PadValue onnxruntime::PadValueFromFloat(float, onnxruntime::MLDataType)onnxruntime::common::Status onnxruntime::PadImpl(onnxruntime::OpKernelContext *, const std::vector<int64_t> &, const std::vector<int64_t> &, const onnxruntime::Mode &, T) [T = unsigned int]data_rank > 0data_rank * 2 == pads.size()PadInputWithDimValueOfZero/Users/runner/work/1/s/onnxruntime/core/providers/cpu/tensor/utils.honnxruntime::SliceSkips::SliceSkips(const onnxruntime::TensorShape &, gsl::span<const int64_t>, gsl::span<const int64_t>)dims.size() == extents.size() && dims.size() >= steps.size()void onnxruntime::SliceIteratorBase::Init(const std::vector<int64_t> &, gsl::span<const int64_t>, gsl::span<const int64_t>)dims.size() == starts.size() && dims.size() == extents_.size() && dims.size() >= steps.size()onnxruntime::common::Status onnxruntime::PadImpl(onnxruntime::OpKernelContext *, const std::vector<int64_t> &, const std::vector<int64_t> &, const onnxruntime::Mode &, T) [T = unsigned long long]onnxruntime::common::Status onnxruntime::PadImpl(onnxruntime::OpKernelContext *, const std::vector<int64_t> &, const std::vector<int64_t> &, const onnxruntime::Mode &, T) [T = unsigned char]DequantizeLinearQuantizeLinear/Users/runner/work/1/s/onnxruntime/core/providers/cpu/tensor/quantize_linear.ccvoid onnxruntime::PrepareForQDQ(const onnxruntime::TensorShape &, const onnxruntime::Tensor &, const onnxruntime::Tensor *, int64_t, int64_t &, int64_t &, int64_t &)zero_point_ptr == nullptr || IsScalarOr1ElementVector(zero_point_ptr)scale.Shape().NumDimensions() == 1 && scale.Shape()[0] == broadcast_dimscale must be 1D tensor with size zero_point_ptr == nullptr || (zero_point_ptr->Shape().NumDimensions() == 1 && zero_point_ptr->Shape()[0] == broadcast_dim)x_zero_point must be null or 1D tensor with size virtual onnxruntime::common::Status onnxruntime::DequantizeLinear<int>::Compute(onnxruntime::OpKernelContext *) const [T = int]zero_point == nullptr || std::all_of(zero_point, zero_point + x_zero_point->Shape().Size(), [](int32_t zp) { return zp == 0; })DequantizeLinear with type int32 should have no zero point or all zero points should be 0Reshapeshape/Users/runner/work/1/s/onnxruntime/core/providers/cpu/tensor/reshape.honnxruntime::Reshape_1::Reshape_1(const onnxruntime::OpKernelInfo &)/Users/runner/work/1/s/onnxruntime/core/providers/cpu/tensor/reshape_helper.honnxruntime::ReshapeHelper::ReshapeHelper(const onnxruntime::TensorShape &, std::vector<int64_t> &, bool)requested_shape[i] >= -1A dimension cannot be less than -1, got !allow_zeroThe input tensor cannot be reshaped to the requested shape. Input shape:, requested shape:unknown_dim == -1i < input_shape.NumDimensions()The dimension with value zero exceeds the dimension size of the input tensor.size != 0 && (input_shape.Size() % size) == 0gsl::narrow_cast<int64_t>(input_shape.Size()) == sizeallowzerovirtual onnxruntime::common::Status onnxruntime::Reshape::Compute(onnxruntime::OpKernelContext *) constshapeTensor->Shape().NumDimensions() == 1Resize/Users/runner/work/1/s/onnxruntime/core/providers/cpu/tensor/upsample.honnxruntime::UpsampleBase::UpsampleBase(const onnxruntime::OpKernelInfo &)info.GetAttr<std::string>("mode", &mode).IsOK()scalesinfo.GetAttrs<float>("scales", scales_).IsOK()extrapolation_valuecoordinate_transformation_modehalf_pixelasymmetricUpsampleBase`tf_half_pixel_for_nn` is deprecated since opset 13, yet this opset model uses the deprecated attributenearest_moderound_prefer_floorcubic_coeff_aexclude_outsideexclude_outside can be set to 1 only when mode is CUBIC. Current mode is set to nearestlinearcubiconnxruntime::UpsampleMode onnxruntime::UpsampleBase::StringToUpsampleMode(const std::string &)mode attribute is . It can only be (default) or or void onnxruntime::UpsampleBase::ScalesValidation(const std::vector<float> &, const onnxruntime::UpsampleMode) constscale >= 1scale > 0scales.size() == 2 || (scales.size() == 4 && scales[0] == 1 && scales[1] == 1) || scales.size() == 3 || (scales.size() == 5 && scales[0] == 1 && scales[1] == 1)'Linear' mode only support 2-D inputs or 3-D inputs ('Bilinear', 'Trilinear') or 4-D inputs or 5-D inputs with the corresponding outermost 2 scale values being 1 in the Resize operatorUpsample operatorscales.size() == 2 || (scales.size() == 4 && scales[0] == 1 && scales[1] == 1)'Cubic' mode only support 2-D inputs ('Bicubic') or 4-D inputs with the corresponding outermost 2 scale values being 1 in the pytorch_half_pixeltf_half_pixel_for_nnalign_cornerstf_crop_and_resizeonnxruntime::ResizeCoordinateTransformationMode onnxruntime::UpsampleBase::StringToCoordinateTransformationMode(const std::string &)coordinate_transform_mode:[] is not supportted!round_prefer_ceilfloorceilonnxruntime::ResizeNearestMode onnxruntime::UpsampleBase::StringToNearestMode(const std::string &)nearest_mode:[] is not supported!void onnxruntime::UpsampleBase::ParseScalesData(const onnxruntime::Tensor *, std::vector<float> &) constscales_size > 0ReverseSequencesequence_lens shape must be {batch_size}. Got:. batch_size=/Users/runner/work/1/s/onnxruntime/core/providers/cpu/tensor/reverse_sequence.ccvirtual onnxruntime::common::Status onnxruntime::ReverseSequenceOp::Compute(onnxruntime::OpKernelContext *) constUnknown tensor type of batch_axis/Users/runner/work/1/s/onnxruntime/core/providers/cpu/tensor/reverse_sequence.honnxruntime::ReverseSequenceOp::ReverseSequenceOp(const onnxruntime::OpKernelInfo &)info.GetAttr<int64_t>("batch_axis", &batch_axis).IsOK()time_axisinfo.GetAttr<int64_t>("time_axis", &time_axis).IsOK()batch_axis < 2Invalid batch_axis of . Must be 0 or 1time_axis < 2Invalid time_axis of batch_axis != time_axistime_axis and batch_axis must have different values but both are Invalid sequence length: . Value must be in range [0,gsl::span<const T> onnxruntime::Tensor::DataAsSpan() const [T = bool]gsl::span<T> onnxruntime::Tensor::MutableDataAsSpan() [T = bool]gsl::span<const T> onnxruntime::Tensor::DataAsSpan() const [T = double]gsl::span<T> onnxruntime::Tensor::MutableDataAsSpan() [T = double]gsl::span<const T> onnxruntime::Tensor::DataAsSpan() const [T = unsigned char]gsl::span<T> onnxruntime::Tensor::MutableDataAsSpan() [T = unsigned char]gsl::span<const T> onnxruntime::Tensor::DataAsSpan() const [T = unsigned short]gsl::span<T> onnxruntime::Tensor::MutableDataAsSpan() [T = unsigned short]gsl::span<const T> onnxruntime::Tensor::DataAsSpan() const [T = short]gsl::span<T> onnxruntime::Tensor::MutableDataAsSpan() [T = short]gsl::span<T> onnxruntime::Tensor::MutableDataAsSpan() [T = int]gsl::span<const T> onnxruntime::Tensor::DataAsSpan() const [T = unsigned int]gsl::span<T> onnxruntime::Tensor::MutableDataAsSpan() [T = unsigned int]gsl::span<const T> onnxruntime::Tensor::DataAsSpan() const [T = unsigned long long]gsl::span<T> onnxruntime::Tensor::MutableDataAsSpan() [T = unsigned long long]gsl::span<const T> onnxruntime::Tensor::DataAsSpan() const [T = onnxruntime::MLFloat16]gsl::span<T> onnxruntime::Tensor::MutableDataAsSpan() [T = onnxruntime::MLFloat16]gsl::span<const T> onnxruntime::Tensor::DataAsSpan() const [T = onnxruntime::BFloat16]gsl::span<T> onnxruntime::Tensor::MutableDataAsSpan() [T = onnxruntime::BFloat16]ScatterScatterElements/Users/runner/work/1/s/onnxruntime/core/providers/cpu/tensor/scatter.cconnxruntime::Scatter<onnxruntime::TypeList<float, double, long long, unsigned long long, int, unsigned int, short, unsigned short, signed char, unsigned char, onnxruntime::MLFloat16, onnxruntime::BFloat16, bool, std::__1::basic_string<char> > >::Scatter(const onnxruntime::OpKernelInfo &) [EnabledDataTypes = onnxruntime::TypeList<float, double, long long, unsigned long long, int, unsigned int, short, unsigned short, signed char, unsigned char, onnxruntime::MLFloat16, onnxruntime::BFloat16, bool, std::__1::basic_string<char> >]Indices vs updates dimensions differs at position= vs Indices must have the same rank as Input. Indices rank=. Input rank=Indices dim= at pos= is greater than input dim=ScatterNDinput tensor and indices tensor must has rank larger than 0. input shape: , indices shape: updates tensor should have shape equal to indices.shape[:-1] + data.shape[indices.shape[-1]:]. updates shape: , data shape: /Users/runner/work/1/s/onnxruntime/core/providers/cpu/tensor/scatter_nd.ccinvalid indice found, indice = SizeSliceTind'axes' has an axis outside of the tensor dimension count'axes' has duplicates'step' value cannot be 0/Users/runner/work/1/s/onnxruntime/core/providers/cpu/tensor/slice.ccFillVectorsFromInputStarts must be a 1-D arrayEnds must be a 1-D arrayStarts and ends shape mismatchStarts and axes shape mismatchStarts and steps shape mismatchData type for starts and ends inputs' is not supported in this build. Got starts/Users/runner/work/1/s/onnxruntime/core/providers/cpu/tensor/slice.honnxruntime::SliceBase::SliceBase(const onnxruntime::OpKernelInfo &, bool)has_starts && has_ends && attr_starts_.size() == attr_ends_.size()!has_axes || attr_axes_.size() == attr_starts_.size()Invalid axes attribute, axes attribute (if present) should have the same size as starts/ends attributesauto onnxruntime::SliceImpl(onnxruntime::OpKernelContext *, const onnxruntime::Tensor &, SliceOp::PrepareForComputeMetadata &)::(anonymous class)::operator()(SliceIterator<T> &) constoutput == output_endvoid *onnxruntime::SliceIteratorBase::CopyInnermostAxisNonSolitaryInnerStep(void *)Unexpected element size of SpaceToDepthDepthToSpace/Users/runner/work/1/s/onnxruntime/core/providers/cpu/tensor/space_depth_ops.ccvirtual onnxruntime::common::Status onnxruntime::SpaceToDepth<float>::Compute(onnxruntime::OpKernelContext *) const [T = float]input_shape.NumDimensions() == 4input_height % this->blocksize_ == 0input_width % this->blocksize_ == 0virtual onnxruntime::common::Status onnxruntime::DepthToSpace<float>::Compute(onnxruntime::OpKernelContext *) const [T = float]input.Shape().NumDimensions() == 4input_depth % (blocksize_ * blocksize_) == 0blocksize/Users/runner/work/1/s/onnxruntime/core/providers/cpu/tensor/space_depth_ops.honnxruntime::SpaceDepthBase::SpaceDepthBase(const onnxruntime::OpKernelInfo &)info.GetAttr("blocksize", &blocksize_).IsOK()CRDDCRonnxruntime::DepthToSpace<float>::DepthToSpace(const onnxruntime::OpKernelInfo &) [T = float]SplitInput cannot be split evenly on selected axis. Input shape= Axis= NumOutputs=Cannot split using values in 'split' attribute. Axis= Input shape= Num entries in 'split' (must equal number of outputs) was Sum of sizes in 'split' (must equal size of selected axis) was /Users/runner/work/1/s/onnxruntime/core/providers/cpu/tensor/split.ccvirtual onnxruntime::common::Status onnxruntime::Split::Compute(onnxruntime::OpKernelContext *) constSplit operator does not support yetsplit/Users/runner/work/1/s/onnxruntime/core/providers/cpu/tensor/split.honnxruntime::SplitBase::SplitBase(const onnxruntime::OpKernelInfo &)std::all_of(split_sizes_.cbegin(), split_sizes_.cend(), [](int64_t value) { return value >= 0; })onnxruntime::common::Status onnxruntime::Split::ComputeImpl(onnxruntime::OpKernelContext &, const onnxruntime::Tensor &) const [T = float]split_tensor->Shape().NumDimensions() == 1onnxruntime::common::Status onnxruntime::Split::ComputeImpl(onnxruntime::OpKernelContext &, const onnxruntime::Tensor &) const [T = int]onnxruntime::common::Status onnxruntime::Split::ComputeImpl(onnxruntime::OpKernelContext &, const onnxruntime::Tensor &) const [T = long long]onnxruntime::common::Status onnxruntime::Split::ComputeImpl(onnxruntime::OpKernelContext &, const onnxruntime::Tensor &) const [T = unsigned char]onnxruntime::common::Status onnxruntime::Split::ComputeImpl(onnxruntime::OpKernelContext &, const onnxruntime::Tensor &) const [T = std::__1::basic_string<char>]Squeeze/Users/runner/work/1/s/onnxruntime/core/providers/cpu/tensor/squeeze.hvirtual onnxruntime::common::Status onnxruntime::Squeeze::Compute(onnxruntime::OpKernelContext *) constaxes_tensor != nullptraxes_tensor->Shape().NumDimensions() == 1static std::vector<int64_t> onnxruntime::SqueezeBase::ComputeOutputShape(const onnxruntime::TensorShape &, const std::vector<int64_t> &)input_shape[i] == 1Dimension of input must be 1 instead of . shape=TileInput count of Tile OP mismatch, the first one is emptyInput count of Tile OP mismatch, the second one is emptythe tensor to be tiled using Tile OP must be atleast 1 dimensional'repeat' input tensor must be 1 dimensional'repeat' input tensor must have the same length as the 'input' tensor/Users/runner/work/1/s/onnxruntime/core/providers/cpu/tensor/tile.ccvirtual onnxruntime::common::Status onnxruntime::Tile::Compute(onnxruntime::OpKernelContext *) const!input_tensor.IsDataType<std::string>()Tile doesn't have an implementation yet for the type: Transpose of element size not supported in this build. Size=Mismatched data types between input and output Tensors. /Users/runner/work/1/s/onnxruntime/core/providers/cpu/tensor/transpose.ccvirtual onnxruntime::common::Status onnxruntime::Transpose::Compute(onnxruntime::OpKernelContext *) constinput_tensor_ptr != nullptrTransposevoid onnxruntime::DoTransposeEltWise(int64_t, const std::vector<int64_t> &, size_t, const std::vector<size_t> &, const std::string *, std::string *)num_axes > 0(local_source >= source) && (local_source < source + num_blocks)void onnxruntime::IncrementIndexAndComputeOffsetSetup(onnxruntime::MultiIndex &, size_t, const std::vector<int64_t> &, const std::vector<size_t> &, size_t)naxes > 0Method IncrementIndexAndComputeOffset assumes this value is strictly positive.void onnxruntime::DoTransposeImpl(int64_t, const std::vector<int64_t> &, size_t, size_t, const std::vector<size_t> &, const std::string *, std::string *)(local_source >= source) && (local_source < source + num_blocks * num_elts_in_block)void onnxruntime::DoTransposeImpl(int64_t, const std::vector<int64_t> &, size_t, size_t, const std::vector<size_t> &, const uint8_t *, uint8_t *, size_t)(local_source >= source) && (local_source < source + num_blocks * blocksize)[ perm: does not align with rank of input data: /Users/runner/work/1/s/onnxruntime/core/providers/cpu/tensor/transpose.honnxruntime::TransposeBase::TransposeBase(const onnxruntime::OpKernelInfo &)v >= 0 && static_cast<uint64_t>(v) <= std::numeric_limits<size_t>::max()Attribute perm of Transpose has an invalid value. Value is outside range. is repeated.bool onnxruntime::TypedDoTransposeEltWise(int64_t, const std::vector<int64_t> &, size_t, const std::vector<size_t> &, const uint8_t *, uint8_t *) [T = unsigned long long](local_source >= source) && (local_source < source + sizeof(T) * num_blocks)bool onnxruntime::TypedDoTransposeEltWise(int64_t, const std::vector<int64_t> &, size_t, const std::vector<size_t> &, const uint8_t *, uint8_t *) [T = unsigned int]bool onnxruntime::TypedDoTransposeEltWise(int64_t, const std::vector<int64_t> &, size_t, const std::vector<size_t> &, const uint8_t *, uint8_t *) [T = unsigned short]bool onnxruntime::TypedDoTransposeEltWise(int64_t, const std::vector<int64_t> &, size_t, const std::vector<size_t> &, const uint8_t *, uint8_t *) [T = unsigned char]Trilu/Users/runner/work/1/s/onnxruntime/core/providers/cpu/tensor/trilu.ccvirtual onnxruntime::common::Status onnxruntime::Trilu::Compute(onnxruntime::OpKernelContext *) constIsScalarOr1ElementVector(k)upper/Users/runner/work/1/s/onnxruntime/core/providers/cpu/tensor/trilu.honnxruntime::Trilu::Trilu(const onnxruntime::OpKernelInfo &)info.GetAttr<int64_t>("upper", &temp).IsOK()UniqueUnsupported tensor type of sortedgsl::span<T> onnxruntime::Tensor::MutableDataAsSpan() [T = long long]gsl::span<const T> onnxruntime::Tensor::DataAsSpan() const [T = signed char]gsl::span<T> onnxruntime::Tensor::MutableDataAsSpan() [T = signed char]gsl::span<const T> onnxruntime::Tensor::DataAsSpan() const [T = std::__1::basic_string<char>]gsl::span<T> onnxruntime::Tensor::MutableDataAsSpan() [T = std::__1::basic_string<char>]Unsqueeze/Users/runner/work/1/s/onnxruntime/core/providers/cpu/tensor/unsqueeze.cconnxruntime::common::Status onnxruntime::UnsqueezeBase::PrepareCompute(onnxruntime::OpKernelContext *, onnxruntime::UnsqueezeBase::Prepare &) constaxes_tensor->Shape().NumDimensions() == 0 || axes_tensor->Shape().NumDimensions() == 1'axes' has an out of range axis'axes' has a duplicate axisnullptr != p.output_tensor/Users/runner/work/1/s/onnxruntime/core/providers/cpu/tensor/unsqueeze.honnxruntime::UnsqueezeBase::UnsqueezeBase(const onnxruntime::OpKernelInfo &)info.GetAttrs("axes", axes_).IsOK()Upsample/Users/runner/work/1/s/onnxruntime/core/providers/cpu/tensor/upsample.ccvirtual onnxruntime::common::Status onnxruntime::Upsample<float>::Compute(onnxruntime::OpKernelContext *) const [T = float]roi_input_idx_ > 0sizes == nullptrsizes != nullptr && sizes->Shape().Size() != 0X->Shape().GetDims().size() == output_dims.size()Resize: input tensor's rank does not match the output tensor's rank.onnxruntime::common::Status onnxruntime::Upsample<float>::BaseCompute(onnxruntime::OpKernelContext *, const std::vector<float> &, const std::vector<float> &, const std::vector<int64_t> &) const [T = float]output_dims.size() == dims.size()Resize: input tensor's dimension does not match the scales.Upsample: input tensor's dimension does not match the scales.Resize: size of roi array should be 2 * N where N is the rank of input tensor X.BaseComputeResize: unexpected modeUpsample: unexpected modeResize: input/output value is nullptrUpsample: input/output value is nullptrResize: input/output value's dimension mismatchUpsample: input/output value's dimension mismatchResize: input shape needs to be at least a single dimensionUpsample: input shape needs to be at least a single dimension.void onnxruntime::UpsampleBase::ParseScalesDataFromOutputSize(const std::vector<int64_t> &, const std::vector<int64_t> &, std::vector<float> &) constoutput_dims[i] == 0Input dim is zero but required output dim is non-zero. Cannot scale 0 by any factor to generate a non-zero value. Dimension: Input dim value: Output dim value: virtual onnxruntime::common::Status onnxruntime::Upsample<int>::Compute(onnxruntime::OpKernelContext *) const [T = int]onnxruntime::common::Status onnxruntime::Upsample<int>::BaseCompute(onnxruntime::OpKernelContext *, const std::vector<float> &, const std::vector<float> &, const std::vector<int64_t> &) const [T = int]virtual onnxruntime::common::Status onnxruntime::Upsample<unsigned char>::Compute(onnxruntime::OpKernelContext *) const [T = unsigned char]onnxruntime::common::Status onnxruntime::Upsample<unsigned char>::BaseCompute(onnxruntime::OpKernelContext *, const std::vector<float> &, const std::vector<float> &, const std::vector<int64_t> &) const [T = unsigned char]WhereGeluonnxruntime::ElementWiseKernel<onnxruntime::functors::ParametricSoftplus<float> >::ElementWiseKernel(const onnxruntime::OpKernelInfo &) [F = onnxruntime::functors::ParametricSoftplus<float>]virtual onnxruntime::common::Status onnxruntime::ElementWiseKernel<onnxruntime::functors::ParametricSoftplus<float> >::Compute(onnxruntime::OpKernelContext *) const [F = onnxruntime::functors::ParametricSoftplus<float>]onnxruntime::ElementWiseKernel<onnxruntime::functors::ScaledTanh<float> >::ElementWiseKernel(const onnxruntime::OpKernelInfo &) [F = onnxruntime::functors::ScaledTanh<float>]virtual onnxruntime::common::Status onnxruntime::ElementWiseKernel<onnxruntime::functors::ScaledTanh<float> >::Compute(onnxruntime::OpKernelContext *) const [F = onnxruntime::functors::ScaledTanh<float>]/Users/runner/work/1/s/onnxruntime/contrib_ops/cpu/attnlstm/bahdanau_attention.cconnxruntime::contrib::BahdanauAttention<float>::BahdanauAttention(onnxruntime::AllocatorPtr, const logging::Logger &, int, int, int, int, int, bool, concurrency::ThreadPool *) [T = float]!normalize_virtual void onnxruntime::contrib::BahdanauAttention<float>::PrepareMemory(const gsl::span<const T> &, const gsl::span<const int> &) [T = float]mem_steps <= max_memory_steps_ && mem_steps > 0Real memory steps is not in (0, AttnLSTM/Users/runner/work/1/s/onnxruntime/contrib_ops/cpu/attnlstm/deep_cpu_attn_lstm.ccvirtual onnxruntime::common::Status onnxruntime::contrib::DeepCpuAttnLstmOp::Compute(onnxruntime::OpKernelContext *) constAttention mechanism memory shape error! Expected: {}, actural: Attention mechanism memory sequence lengths must have shape {Attention mechanism memory sequence lengths value must in (0, ], while found!Attention memory layer weight shape error! Expected:{, am_attn_size}, Got:Attention query layer weight shape error! Expected:{}, Got: Attention v weight shape error! Expected:{}. Got: Attention layer weight shape error! Expected: {, aw_attn_size}. Got:Input initial_c must have shape {Input P must have shape {/Users/runner/work/1/s/onnxruntime/contrib_ops/cpu/attnlstm/deep_cpu_attn_lstm.honnxruntime::contrib::DeepCpuAttnLstmOp::DeepCpuAttnLstmOp(const onnxruntime::OpKernelInfo &)static_cast<int>(activation_func_names.size()) == num_directions_ * 3 [seqno= row[AttentionInput 'input' is expected to have 3 dimensions, got Input 'weights' is expected to have 2 dimensions, got Input 1 dimension 0 should have same length as dimension 2 of input 0Input 'bias' is expected to have 1 dimension, got Input 'bias' dimension 0 should have same length as dimension 1 of input 'weights'Input 'past' is expected to have 5 dimension, got Inputs 'past' dimension 1 shall have same length as dimension 0 of input 0Inputs 'past' dimension 2 shall have length of num_headsInputs 'past' dimension 2 shall have length of Inputs 'mask_index' with 1D data shall have length of batch_size or 2 * batch_sizeInputs 'mask_index' with 2D data shall have shape batch_size x (past_sequence_length + sequence_length)Inputs 'mask_index' with 3D data shall have shape batch_size x sequence_length x (past_sequence_length + sequence_length)Inputs 'mask_index' with 4D data shall have shape batch_size x 1 x max_sequence_length x max_sequence_length)Inputs 'mask_index' with 4D data shall have is_unidirectional_ set to falseInput 'mask_index' is expected to have 1, 2, 3 or 4 dimensions, got /Users/runner/work/1/s/onnxruntime/contrib_ops/cpu/bert/attention.cconnxruntime::Tensor *onnxruntime::contrib::AttentionBase::GetPresent(onnxruntime::OpKernelContext *, const onnxruntime::Tensor *, int, int, int, int &) constExpect to have present state output when past state input is givennum_heads/Users/runner/work/1/s/onnxruntime/contrib_ops/cpu/bert/attention_base.honnxruntime::contrib::AttentionBase::AttentionBase(const onnxruntime::OpKernelInfo &)info.GetAttr("num_heads", &num_heads).IsOK() && num_heads > 0unidirectional/Users/runner/work/1/s/onnxruntime/contrib_ops/cpu/bert/attention_cpu_base.hApplyAttention/Users/runner/work/1/s/onnxruntime/contrib_ops/cpu/bert/bias_gelu.ccvirtual onnxruntime::common::Status onnxruntime::contrib::BiasGelu<float, false>::Compute(onnxruntime::OpKernelContext *) const [T = float, use_approximation = false]use_approximationBiasGeluInput 0 is expected to have 1 or more dimensions, got Input 1 is expected to have 1 dimensions, got Input 1 dimension 0 should have same length as the last dimension of input 0EmbedLayerNormalization/Users/runner/work/1/s/onnxruntime/contrib_ops/cpu/bert/embed_layer_norm.cconnxruntime::contrib::EmbedLayerNorm<float>::EmbedLayerNorm(const onnxruntime::OpKernelInfo &) [T = float]input_ids is expected to have 2 dimensions, got word_embedding is expected to have 2 dimensions, got position_embedding is expected to have 2 dimensions, got segment_embedding is expected to have 2 dimensions, got word_embedding and position_embedding shall have same dimension 1beta is expected to have 1 dimensions, got beta is expected to have size of gamma is expected to have 1 dimensions, got gamma is expected to have size of FastGeluCDistmetric/Users/runner/work/1/s/onnxruntime/contrib_ops/cpu/cdist.honnxruntime::contrib::CDist<float>::CDist(const onnxruntime::OpKernelInfo &) [T = float]info.GetAttr<std::string>("metric", &metric).IsOK()sqeuclideaneuclideanThe first input of CDist kernel has wrong shape: The second input of CDist kernel has wrong shape: Input shape dimensions mismatch:onnxruntime::contrib::CDist<double>::CDist(const onnxruntime::OpKernelInfo &) [T = double]ConvTransposeWithDynamicPads/Users/runner/work/1/s/onnxruntime/contrib_ops/cpu/cpu_contrib_kernels.ccRegisterNchwcKernelsRegisterQuantizationKernelsRegisterCpuContribKernelsCropborder/Users/runner/work/1/s/onnxruntime/contrib_ops/cpu/crop.hAttribute border needs to be specified with four border elements, got Input is expected to have four dimensions corresponding to [N,C,H,W], got input dimensions insteadInput's height () needs to be greater than or equal to the topBorder () + bottomBorder (Input's width () needs to be greater than or equal to the leftBorder () + rightBorder () + scale_[0] () + scale_[1] (CropAndResizebilinear/Users/runner/work/1/s/onnxruntime/contrib_ops/cpu/crop_and_resize.honnxruntime::contrib::CropAndResize<float>::CropAndResize(const onnxruntime::OpKernelInfo &) [T = float] specified. It should be either bilinear or nearestNull crop_size_ptrNumber of dimensions for crop size should be exactly 1/Users/runner/work/1/s/onnxruntime/contrib_ops/cpu/element_wise_ops.honnxruntime::contrib::Affine<float>::Affine(const onnxruntime::OpKernelInfo &) [T = float]info.GetAttr("alpha", &alpha_).IsOK()info.GetAttr("beta", &beta_).IsOK()onnxruntime::contrib::Scale<float>::Scale(const onnxruntime::OpKernelInfo &) [T = float]info.GetAttr("scale", &scale_).IsOK()axisExpandDims/Users/runner/work/1/s/onnxruntime/contrib_ops/cpu/expand_dims.hvirtual onnxruntime::common::Status onnxruntime::contrib::ExpandDims::Compute(onnxruntime::OpKernelContext *) constaxis_tensor->Shape().IsScalar()axis <= X_NumDims && axis >= -X_NumDimsAxis must be within range [ Axis is unimplemented activation: activation_params count mismatchFusedConv/Users/runner/work/1/s/onnxruntime/contrib_ops/cpu/fused_conv.cconnxruntime::contrib::FusedConvFloat::FusedConvFloat(const onnxruntime::OpKernelInfo &)FusedGemmactivationactivation_/Users/runner/work/1/s/onnxruntime/contrib_ops/cpu/fused_gemm.cconnxruntime::contrib::FusedGemm<float>::FusedGemm(const onnxruntime::OpKernelInfo &) [T = float]TransposeMatMulFusedMatMul/Users/runner/work/1/s/onnxruntime/contrib_ops/cpu/image_scaler.honnxruntime::contrib::ImageScaler<float>::ImageScaler(const onnxruntime::OpKernelInfo &) [T = float]info.GetAttrs<float>("bias", bias_).IsOK()Bias size () does not match the number of channels (InverseLayerNormalizationSimplifiedLayerNormalization/Users/runner/work/1/s/onnxruntime/contrib_ops/cpu/layer_norm.cconnxruntime::contrib::LayerNorm<float, false>::LayerNorm(const onnxruntime::OpKernelInfo &) [T = float, simplified = false]op_kernel_info.GetAttr("axis", &axis_).IsOK()onnxruntime::contrib::LayerNorm<float, true>::LayerNorm(const onnxruntime::OpKernelInfo &) [T = float, simplified = true]onnxruntime::contrib::LayerNorm<double, false>::LayerNorm(const onnxruntime::OpKernelInfo &) [T = double, simplified = false]onnxruntime::contrib::LayerNorm<double, true>::LayerNorm(const onnxruntime::OpKernelInfo &) [T = double, simplified = true]MatMulInteger16/Users/runner/work/1/s/onnxruntime/contrib_ops/cpu/matmul_integer16.ccvirtual onnxruntime::common::Status onnxruntime::contrib::MatMulInteger16<short, short, int>::Compute(onnxruntime::OpKernelContext *) const [T1 = short, T2 = short, T3 = int]A != nullptr && B != nullptrMaxpoolWithMask/Users/runner/work/1/s/onnxruntime/contrib_ops/cpu/maxpool_with_mask.hacross_channels/Users/runner/work/1/s/onnxruntime/core/providers/cpu/tensor/mean_variance_normalization.honnxruntime::MeanVarianceNormalization_0<float>::MeanVarianceNormalization_0(const onnxruntime::OpKernelInfo &, bool) [T = float]info.GetAttr<int64_t>("across_channels", &across_channels_).IsOK()normalize_varianceinfo.GetAttr<int64_t>("normalize_variance", &normalize_variance_).IsOK()MurmurHash3/Users/runner/work/1/s/onnxruntime/contrib_ops/cpu/murmur_hash3.ccvirtual onnxruntime::common::Status onnxruntime::contrib::MurmurHash3::Compute(onnxruntime::OpKernelContext *) constkeyssizeof(uint32_t) == output_element_bytesinput_num_bytes % 4 == 0/Users/runner/work/1/s/onnxruntime/contrib_ops/cpu/nchwc_ops.ccvirtual onnxruntime::common::Status onnxruntime::contrib::ReorderInput::Compute(onnxruntime::OpKernelContext *) constX_rank == 4(channels % 4) == 0virtual onnxruntime::common::Status onnxruntime::contrib::ReorderOutput::Compute(onnxruntime::OpKernelContext *) constchannels_ <= X_shape[1]virtual onnxruntime::common::Status onnxruntime::contrib::NchwcConv::Compute(onnxruntime::OpKernelContext *) constX_shape.NumDimensions() == 4(static_cast<size_t>(X_shape[1]) < nchwc_block_size) || ((X_shape[1] % nchwc_block_size) == 0)Unsupported convolution size.output and sum shape must matchonnxruntime::common::Status onnxruntime::contrib::NchwcPoolBase::NchwcPool(onnxruntime::OpKernelContext *, MLAS_POOLING_KIND) const(X_shape[1] % MlasNchwcGetBlockSize()) == 0virtual onnxruntime::common::Status onnxruntime::contrib::NchwcUpsample::Compute(onnxruntime::OpKernelContext *) constX_shape.size() == 4ReorderInputReorderOutput/Users/runner/work/1/s/onnxruntime/contrib_ops/cpu/nchwc_ops.honnxruntime::contrib::ReorderInput::ReorderInput(const onnxruntime::OpKernelInfo &)info.GetAttr<int64_t>("channels_last", &channels_last_).IsOK()onnxruntime::contrib::ReorderOutput::ReorderOutput(const onnxruntime::OpKernelInfo &)info.GetAttr<int64_t>("channels", &channels_).IsOK()channels_ > 0invalid channel countonnxruntime::contrib::NchwcConv::NchwcConv(const onnxruntime::OpKernelInfo &)GetFusedActivationAttr(info, activation_).IsOK()onnxruntime::contrib::NchwcPoolBase::NchwcPoolBase(const onnxruntime::OpKernelInfo &)pool_attrs_.kernel_shape.size() == 2onnxruntime::contrib::NchwcUpsample::NchwcUpsample(const onnxruntime::OpKernelInfo &)info.GetAttrs<int64_t>("scales", scales_).IsOK()scales_.size() == 4scales_[0] == 1 && scales_[1] == 1 && scales_[2] >= 1 && scales_[3] >= 1info.GetAttr<std::string>("coordinate_transformation_mode", &transformation_mode).IsOK()Unsupported transformation mode '' for NCHWc Upsampletransformation_mode_ == TransformationMode::ASYMMETRICUnsupported mode 'QLinearAddQLinearMul/Users/runner/work/1/s/onnxruntime/contrib_ops/cpu/qlinear_binary_op.ccvoid onnxruntime::contrib::(anonymous namespace)::QLinearImpl(onnxruntime::OpKernelContext &, double, const onnxruntime::ProcessBroadcastSpanFuncs &) [T = signed char]IsScalarOr1ElementVector(tensor_a_scale)MatmulInteger : input1 A_scale must be a scalar or 1D tensor of size 1tensor_a_zero_point == nullptr || IsScalarOr1ElementVector(tensor_a_zero_point)MatmulInteger : input1 A_zero_point must be a scalar or 1D tensor of size 1 if givenIsScalarOr1ElementVector(tensor_b_scale)MatmulInteger : input1 B_scale must be a scalar or 1D tensor of size 1tensor_b_zero_point == nullptr || IsScalarOr1ElementVector(tensor_b_zero_point)MatmulInteger : input1 B_zero_point must be a scalar or 1D tensor of size 1 if givenIsScalarOr1ElementVector(tensor_c_scale)MatmulInteger : input1 C_scale must be a scalar or 1D tensor of size 1tensor_c_zero_point == nullptr || IsScalarOr1ElementVector(tensor_c_zero_point)MatmulInteger : input1 C_zero_point must be a scalar or 1D tensor of size 1 if givenvoid onnxruntime::BroadcastLooper(TBroadcastHelper &, const onnxruntime::ProcessBroadcastSpanFuncs &) [TBroadcastHelper = onnxruntime::contrib::(anonymous namespace)::QLinearBroadcastHelper]void onnxruntime::contrib::(anonymous namespace)::QLinearImpl(onnxruntime::OpKernelContext &, double, const onnxruntime::ProcessBroadcastSpanFuncs &) [T = unsigned char]/Users/runner/work/1/s/onnxruntime/contrib_ops/cpu/qlinear_concat.cconnxruntime::contrib::QLinearConcat::QLinearConcat(const onnxruntime::OpKernelInfo &)input_def_count >= 8 && (input_def_count - 2) % 3 == 0At least two inputs are needed, and each input must be (tensor, scale, zero_point) tuple!tensor_x_scale->IsDataType<float>()Input scale is not float for input def @tensor_x_zero_point->GetElementType() == tensor_y_zero_point->GetElementType()Wrong input type encountered for zero point input def @virtual onnxruntime::common::Status onnxruntime::contrib::QLinearConcat::Compute(onnxruntime::OpKernelContext *) constinput_count_x3 >= 6 && input_count_x3 % 3 == 0Input scale is not float for quantized input @Wrong input type encountered for zero point of quantized input @QLinearConcat/Users/runner/work/1/s/onnxruntime/contrib_ops/cpu/qlinear_global_average_pool.ccvirtual onnxruntime::common::Status onnxruntime::contrib::QLinearGlobalAveragePool::Compute(onnxruntime::OpKernelContext *) constIsScalarOr1ElementVector(tensor_x_zero_point)IsScalarOr1ElementVector(tensor_y_zero_point)QLinearGlobalAveragePoolQLinearLeakyReluQLinearSigmoid/Users/runner/work/1/s/onnxruntime/contrib_ops/cpu/qlinear_lookup_table.ccvoid onnxruntime::contrib::QlinearBuildLookupTable(uint8_t *, const onnxruntime::Tensor *, const onnxruntime::Tensor *, const onnxruntime::Tensor *, const onnxruntime::Tensor *, const onnxruntime::contrib::LookupTableArrayTransformer &) [T = unsigned char]QlinearBuildLookupTable : input X_scale must be a scalar or 1D tensor of size 1QlinearBuildLookupTable : input X_zero_point must be a scalar or 1D tensor of size 1QlinearBuildLookupTable : input Y_scale must be a scalar or 1D tensor of size 1QlinearBuildLookupTable : input Y_zero_point must be a scalar or 1D tensor of size 1void onnxruntime::contrib::QlinearBuildLookupTable(uint8_t *, const onnxruntime::Tensor *, const onnxruntime::Tensor *, const onnxruntime::Tensor *, const onnxruntime::Tensor *, const onnxruntime::contrib::LookupTableArrayTransformer &) [T = signed char]/Users/runner/work/1/s/onnxruntime/contrib_ops/cpu/qlinear_pool.ccvirtual onnxruntime::common::Status onnxruntime::contrib::QLinearAveragePool::Compute(onnxruntime::OpKernelContext *) constIsScalarOr1ElementVector(tensor_x_scale)tensor_x_zero_point == nullptr || IsScalarOr1ElementVector(tensor_x_zero_point)input x_zero_point must be a scalar or 1D tensor of size 1 if givenIsScalarOr1ElementVector(tensor_y_scale)tensor_y_zero_point == nullptr || IsScalarOr1ElementVector(tensor_y_zero_point)input y_zero_point must be a scalar or 1D tensor of size 1 if givenUnsupported 'dtype' in QLinear Pooling:QLinear Pooling unsupported pooling size!QLinearAveragePoolQAttention/Users/runner/work/1/s/onnxruntime/contrib_ops/cpu/quantization/attention_quant.ccinput scale must be a scalar or 1D tensor of size 1input zero point must be a scalar or 1D tensor of size 1./Users/runner/work/1/s/onnxruntime/contrib_ops/cpu/quantization/dynamic_quantize_lstm.ccW_zero_point must have shape {} for per-tensor/layer quantization or shape {, 4*} for per-channel quantization. Actual:R_zero_pointW_scaleR_scaleDynamicQuantizeLSTM : Weight zero point must be zeroWeight point must be constantRecurrentDynamicQuantizeLSTM/Users/runner/work/1/s/onnxruntime/contrib_ops/cpu/quantization/dynamic_quantize_matmul.ccComputeCommononnxruntime::common::Status onnxruntime::contrib::MatMulIntegerToFloatBase::ComputeCommon(onnxruntime::OpKernelContext *, const uint8_t *, const onnxruntime::TensorShape &, float, uint8_t, const onnxruntime::Tensor *, const onnxruntime::Tensor *, const onnxruntime::Tensor *, const onnxruntime::Tensor *) constIsBQuantParamSupported(b_zp_tensor->Shape(), b_tensor ? b_tensor->Shape() : b_shape_)virtual onnxruntime::common::Status onnxruntime::contrib::MatMulIntegerToFloat::Compute(onnxruntime::OpKernelContext *) constIsScalarOr1ElementVector(a_zero_point_tensor)MatMulIntegerToFloat : input a zero point must be a scalar or 1D tensor of size 1. Per-Channel is not supported yet.DynamicQuantizeMatMulMatMulIntegerToFloat/Users/runner/work/1/s/onnxruntime/contrib_ops/cpu/quantization/nhwc_max_pool.ccvirtual onnxruntime::common::Status onnxruntime::contrib::NhwcMaxPool::Compute(onnxruntime::OpKernelContext *) constinput_shape.Size() > 0 || N == 0NhwcMaxPoolSampleOpSkipLayerNormalization/Users/runner/work/1/s/onnxruntime/contrib_ops/cpu/skip_layer_norm.cconnxruntime::contrib::SkipLayerNorm<float>::SkipLayerNorm(const onnxruntime::OpKernelInfo &) [T = float]epsilon_ >= 0input is expected to have 3 dimensions, got gamma is expected to have 1 dimension, got beta is expected to have 1 dimension, got bias is expected to have 1 dimension, got onnxruntime::contrib::SkipLayerNorm<double>::SkipLayerNorm(const onnxruntime::OpKernelInfo &) [T = double]Tokenizer/Users/runner/work/1/s/onnxruntime/contrib_ops/cpu/tokenizer.cconnxruntime::contrib::Tokenizer::Tokenizer(const onnxruntime::OpKernelInfo &)pad_valuemincharnummincharnum_ > 0separatorsEither one of the separators OR tokenexp attributes required but none is set!tokenexp.empty()!separators.empty()!char_tokenezation_ || mincharnum_ < 2Can not digest separators: Can not digest tokenexp: Input string contains invalid utf8 chars: Match contains invalid utf8 chars: tensor(string) expected as inputInput dimensions are either [C] or [N][C] allowedConv filter size does not match embedding_size attribute. embedding_size attribute: conv filter size: Conv kernal size 1 does not match conv_window_size attribute . conv_window_size attribute: conv kernal size 1: Char embedding size does not match char_embedding_size attribute. char_embedding_size attribute: Char embedding size: Char embedding size does not match conv kernal size 2. Conv kernal size 2 : /Users/runner/work/1/s/onnxruntime/contrib_ops/cpu/word_conv_embedding.ccWordConvEmbeddingembedding_sizeconv_window_sizechar_embedding_size/Users/runner/work/1/s/onnxruntime/core/util/math_cpu.ccGemv found an unexpected CBLAS_TRANSPOSE input ofvoid onnxruntime::math::Gemv(CBLAS_TRANSPOSE, int, int, float, const T *, const T *, float, T *, Provider *) [T = double, Provider = onnxruntime::CPUMathUtil]bool onnxruntime::math::NextPosition(int64_t, const int64_t *, int64_t *)dims[d_i] < d_maxReceived null OrtThreadingOptionsReceived invalid value for allow_spinning. Valid values are 0 or 1/Users/runner/work/1/s/onnxruntime/core/framework/allocation_planner.cc[CreatePlanCan not find the node onnxruntime::common::Status onnxruntime::PlannerImpl::ComputeUseCounts()p_kernel_defShould not have entry in kernel create info with nullptr for kernel_defCan not find the execution provider ComputeUseCountsallocatoronnxruntime::OrtValueIndex onnxruntime::PlannerImpl::Index(const onnxruntime::OrtValueName &)void onnxruntime::PlannerImpl::ProcessDef(onnxruntime::OrtValueIndex, const onnxruntime::NodeArg *)id >= 0 && static_cast<size_t>(id) < ort_value_info_.size()int &onnxruntime::PlannerImpl::UseCount(onnxruntime::OrtValueIndex)n >= 0 && static_cast<size_t>(n) < ort_value_info_.size()const onnxruntime::KernelCreateInfo &onnxruntime::GetKernelCreateInfo(const std::unordered_map<NodeIndex, gsl::not_null<const KernelCreateInfo *> > &, onnxruntime::NodeIndex)entry != kernel_create_info_map.cend()SessionState should have saved the KernelCreateInfo prior to this running. NodeIndex:onnxruntime::AllocPlanPerValue &onnxruntime::PlannerImpl::AllocPlan(onnxruntime::OrtValueIndex)n >= 0 && static_cast<size_t>(n) < plan_.allocation_plan.size()ComputeReusePlanonnxruntime::common::Status onnxruntime::PlannerImpl::ComputeReusePlan()!IsNonTensor(*node_output)GeneratePlanForWeightsOrtMemoryInfo onnxruntime::PlannerImpl::GetLocationForNodeInput(size_t, const onnxruntime::Node &)void onnxruntime::PlannerImpl::Reuse(onnxruntime::OrtValueIndex, onnxruntime::OrtValueIndex, onnxruntime::AllocKind)reused != reused_for/Users/runner/work/1/s/onnxruntime/core/framework/sequential_execution_plan.hvoid onnxruntime::AllocPlanPerValue::ProgramCounter::AddStart(size_t)starts_.size() == ends_.size()starts_.empty() || start > ends_.back()static size_t onnxruntime::PlannerImpl::GetElementSize(const onnx::DataType &)nullptr != tensor_type_baseonnxruntime::OrtValueIndex &onnxruntime::PlannerImpl::Buffer(onnxruntime::OrtValueIndex)void onnxruntime::AllocPlanPerValue::ProgramCounter::AddEnd(size_t)starts_.size() == ends_.size() + 1end >= starts_.back()void onnxruntime::PlannerImpl::GenerateDeallocationPlan()AllocPlan(ml_value_idx).program_counter.Ends().back() == program_countervoid onnxruntime::PlannerImpl::VerifyMemoryTimeSchedule()entry.program_counter.HasValidEntries()Invalid program_counter entries at index CudaCudaPinnedSpecified device is not supported./Users/runner/work/1/s/onnxruntime/core/framework/allocator.ccoperator()/Users/runner/work/1/s/include/onnxruntime/core/common/logging/logging.hstatic const onnxruntime::logging::Logger &onnxruntime::logging::LoggingManager::DefaultLogger()OrtMemoryInfo:[name: id: OrtMemType: OrtAllocatorType:]Device:[DeviceType: MemoryType: DeviceId:/Users/runner/work/1/s/onnxruntime/core/framework/allocatormgr.ccCreateAllocatorReceived invalid value of arena_extend_strategy void onnxruntime::AllocatorManager::InsertAllocator(onnxruntime::AllocatorPtr)/Users/runner/work/1/s/onnxruntime/core/framework/bfc_arena.ccBFCArenaCreating BFCArena for with following configs: initial_chunk_size_bytes: max_dead_bytes_per_chunk: initial_growth_chunk_size_bytes: memory limit: arena_extend_strategy: Creating bins of max chunk size onnxruntime::BFCArena::BFCArena(std::unique_ptr<IAllocator>, size_t, onnxruntime::ArenaExtendStrategy, int, int, int)BinForSize(bin_size) == BinFromIndex(b)BinForSize(bin_size + 255) == BinFromIndex(b)BinForSize(bin_size * 2 - 1) == BinFromIndex(b)BinForSize(bin_size * 2) != BinFromIndex(b)BFCArena::Chunk *onnxruntime::BFCArena::ChunkFromHandle(onnxruntime::BFCArena::ChunkHandle)h < chunks_.size()Available memory of is smaller than requested bytes of Failed to allocate memory for requested buffer of size ExtendExtended allocation by bytes.Total allocated bytes: Allocated memory at ReserveReserving memory in BFCArena for size: virtual void *onnxruntime::BFCArena::Reserve(size_t)reserved_chunks_.find(ptr) == reserved_chunks_.end()h != kInvalidChunkHandleAllocateRawInternaltried to allocate 0 bytesExtending BFCArena for . bin_num: (requested) num_bytes: (actual) rounded_bytes:Failed to find a free memory block despite calling Extend. rounded_bytes=BFC Arena ran out of memory trying to allocate . Current allocation summary follows.void *onnxruntime::BFCArena::AllocateRawInternal(size_t, bool)void *onnxruntime::BFCArena::FindChunkPtr(onnxruntime::BFCArena::BinNum, size_t, size_t)!chunk->in_use()void onnxruntime::BFCArena::SplitChunk(BFCArena::ChunkHandle, size_t)!c->in_use() && (c->bin_num == kInvalidBinNum) BFC Arena shrunk by bytes. The total allocated bytes is now void onnxruntime::BFCArena::DeallocateRawInternal(void *)void onnxruntime::BFCArena::Merge(BFCArena::ChunkHandle, BFCArena::ChunkHandle)!c1->in_use() && !c2->in_use()c2->prev == h1void onnxruntime::BFCArena::InsertFreeChunkIntoBin(BFCArena::ChunkHandle)void onnxruntime::BFCArena::RemoveFreeChunkIterFromBin(BFCArena::Bin::FreeChunkSet *, const BFCArena::Bin::FreeChunkSet::iterator &)!c->in_use() && (c->bin_num != kInvalidBinNum)void onnxruntime::BFCArena::RemoveFreeChunkFromBin(BFCArena::ChunkHandle)BinFromIndex(c->bin_num)->free_chunks.erase(h) > 0void onnxruntime::BFCArena::FreeAndMaybeCoalesce(BFCArena::ChunkHandle)c->in_use() && (c->bin_num == kInvalidBinNum)std::array<BFCArena::BinDebugInfo, BFCArena::kNumBins> onnxruntime::BFCArena::get_bin_debug_info()bin->free_chunks.count(h) == 1c->bin_num == bin_numDumpMemoryLogAllocator:Bin size: Chunks in_use/total (if not zero). Allocated bytes in_use/total. Requested bytes.void onnxruntime::BFCArena::DumpMemoryLog(size_t)b->free_chunks.size() == bin_info.total_chunks_in_bin - bin_info.total_chunks_in_use: Chunks . Bytes . Requested Diff between in-use and requested bytes is Bin for bytes has max bytes of , Chunk State: Overall chunks summary: Chunk Free at of size Summary of in-use chunks by size: chunks of size . Total Sum Total of in-use chunks: Stats: -auto onnxruntime::BFCArena::Extend(size_t)::(anonymous class)::operator()(const size_t) constIncorrect arena extend strategy./Users/runner/work/1/s/onnxruntime/core/framework/bfc_arena.honnxruntime::BFCArena::AllocationRegion::AllocationRegion(void *, size_t, int64_t)0 == memory_size % kMinAllocationSizeRegionForCould not find Region for int onnxruntime::BFCArena::AllocationRegion::IndexFor(const void *) constp_int >= base_intp_int < base_int + memory_size_void onnxruntime::BFCArena::RegionManager::RemoveAllocationRegion(void *)entry != regions_.end()Could not find Region for: Size: | Requested Size: | in_use: , prev: , next: Limit: InUse: TotalAllocated: MaxInUse: NumAllocs: NumReserves: NumArenaExtensions: NumArenaShrinkages: MaxAllocSize: /Users/runner/work/1/s/onnxruntime/core/framework/config_options.ccAddConfigEntryConfig with key [] already exists with value []. It will be overwritten/Users/runner/work/1/s/onnxruntime/core/framework/data_transfer.ccvirtual common::Status onnxruntime::CPUDataTransfer::CopyTensor(const onnxruntime::Tensor &, onnxruntime::Tensor &, int) constsrc.SizeInBytes() == dst.SizeInBytes()data_transfer registered is nullptr.Tensor size mismatchThere's no data transfer registered for copying tensors from to /Users/runner/work/1/s/onnxruntime/core/framework/data_transfer_manager.ccCopyTensors/Users/runner/work/1/s/onnxruntime/core/framework/data_types.ccbool onnxruntime::data_types_internal::IsCompatible(const onnx::TypeProto_Map &, const onnx::TypeProto_Map &)bool onnxruntime::data_types_internal::IsCompatible(const onnx::TypeProto_Sequence &, const onnx::TypeProto_Sequence &)virtual bool onnxruntime::TensorTypeBase::IsCompatible(const onnx::TypeProto &) constthisProto->value_case() == TypeProto::ValueCase::kTensorTypeutils::HasElemType(thisProto->tensor_type())virtual bool onnxruntime::SparseTensorTypeBase::IsCompatible(const onnx::TypeProto &) constthisProto->value_case() == TypeProto::ValueCase::kSparseTensorTypeutils::HasElemType(thisProto->sparse_tensor_type())virtual bool onnxruntime::SequenceTensorTypeBase::IsCompatible(const onnx::TypeProto &) constthisProto->value_case() == TypeProto::ValueCase::kSequenceTypeutils::HasElemType(thisProto->sequence_type())bool onnxruntime::NonTensorTypeBase::IsMapCompatible(const onnx::TypeProto &) constthisProto->value_case() == TypeProto::ValueCase::kMapTypeutils::HasKeyType(thisProto->map_type())bool onnxruntime::NonTensorTypeBase::IsSequenceCompatible(const onnx::TypeProto &) constvirtual void onnxruntime::NonTensorTypeBase::FromDataContainer(const void *, size_t, OrtValue &) constNot implementedvirtual void onnxruntime::NonTensorTypeBase::ToDataContainer(const OrtValue &, size_t, void *) const(null)floatbooldoublestringint8uint8int16uint16int32uint32int64uint64float16bfloat16tensor type MLDataType for: is not currently registered or supportedonnxruntime::utils::ContainerChecker::ContainerChecker(onnxruntime::MLDataType)void onnxruntime::data_types_internal::DataTypeRegistry::RegisterDataType(onnxruntime::MLDataType)proto != nullptrp.secondWe do not expect duplicate registration of types for: GetElementType is not implemented/Users/runner/work/1/s/include/onnxruntime/core/framework/data_types.hstatic void onnxruntime::data_types_internal::SetMapTypes<std::__1::basic_string<char>, std::__1::basic_string<char> >::Set(onnx::TypeProto &) [K = std::__1::basic_string<char>, V = std::__1::basic_string<char>]value_proto != nullptr expected to be a registered ONNX typestatic void onnxruntime::data_types_internal::SetMapTypes<std::__1::basic_string<char>, long long>::Set(onnx::TypeProto &) [K = std::__1::basic_string<char>, V = long long]static void onnxruntime::data_types_internal::SetMapTypes<std::__1::basic_string<char>, float>::Set(onnx::TypeProto &) [K = std::__1::basic_string<char>, V = float]static void onnxruntime::data_types_internal::SetMapTypes<std::__1::basic_string<char>, double>::Set(onnx::TypeProto &) [K = std::__1::basic_string<char>, V = double]static void onnxruntime::data_types_internal::SetMapTypes<long long, std::__1::basic_string<char> >::Set(onnx::TypeProto &) [K = long long, V = std::__1::basic_string<char>]static void onnxruntime::data_types_internal::SetMapTypes<long long, long long>::Set(onnx::TypeProto &) [K = long long, V = long long]static void onnxruntime::data_types_internal::SetMapTypes<long long, float>::Set(onnx::TypeProto &) [K = long long, V = float]static void onnxruntime::data_types_internal::SetMapTypes<long long, double>::Set(onnx::TypeProto &) [K = long long, V = double]static void onnxruntime::data_types_internal::SetSequenceType<float>::Set(onnx::TypeProto &) [T = float]elem_proto != nullptrstatic void onnxruntime::data_types_internal::SetSequenceType<double>::Set(onnx::TypeProto &) [T = double]static void onnxruntime::data_types_internal::SetSequenceType<signed char>::Set(onnx::TypeProto &) [T = signed char]static void onnxruntime::data_types_internal::SetSequenceType<unsigned char>::Set(onnx::TypeProto &) [T = unsigned char]static void onnxruntime::data_types_internal::SetSequenceType<short>::Set(onnx::TypeProto &) [T = short]static void onnxruntime::data_types_internal::SetSequenceType<unsigned short>::Set(onnx::TypeProto &) [T = unsigned short]static void onnxruntime::data_types_internal::SetSequenceType<int>::Set(onnx::TypeProto &) [T = int]static void onnxruntime::data_types_internal::SetSequenceType<unsigned int>::Set(onnx::TypeProto &) [T = unsigned int]static void onnxruntime::data_types_internal::SetSequenceType<long long>::Set(onnx::TypeProto &) [T = long long]static void onnxruntime::data_types_internal::SetSequenceType<unsigned long long>::Set(onnx::TypeProto &) [T = unsigned long long]static void onnxruntime::data_types_internal::SetSequenceType<bool>::Set(onnx::TypeProto &) [T = bool]static void onnxruntime::data_types_internal::SetSequenceType<std::__1::basic_string<char> >::Set(onnx::TypeProto &) [T = std::__1::basic_string<char>]static void onnxruntime::data_types_internal::SetSequenceType<onnxruntime::MLFloat16>::Set(onnx::TypeProto &) [T = onnxruntime::MLFloat16]static void onnxruntime::data_types_internal::SetSequenceType<onnxruntime::BFloat16>::Set(onnx::TypeProto &) [T = onnxruntime::BFloat16]static void onnxruntime::data_types_internal::SetSequenceType<std::__1::map<std::__1::basic_string<char>, float, std::__1::less<std::__1::basic_string<char> >, std::__1::allocator<std::__1::pair<const std::__1::basic_string<char>, float> > > >::Set(onnx::TypeProto &) [T = std::__1::map<std::__1::basic_string<char>, float, std::__1::less<std::__1::basic_string<char> >, std::__1::allocator<std::__1::pair<const std::__1::basic_string<char>, float> > >]static void onnxruntime::data_types_internal::SetSequenceType<std::__1::map<long long, float, std::__1::less<long long>, std::__1::allocator<std::__1::pair<const long long, float> > > >::Set(onnx::TypeProto &) [T = std::__1::map<long long, float, std::__1::less<long long>, std::__1::allocator<std::__1::pair<const long long, float> > >]/Users/runner/work/1/s/onnxruntime/core/framework/endian_utils.ccCopyLittleEndiansource and destination buffer size mismatch/Users/runner/work/1/s/onnxruntime/core/framework/ex_lib_loader.cc~ExLibLoaderUnloading DSO Failed to unload DSO: A dso with name has already been loaded.LoadExternalLibCaught exception while destructing CustomOpsLoader with message: Caught exception while loading custom ops with message: /Users/runner/work/1/s/onnxruntime/core/framework/execution_frame.cconnxruntime::IExecutionFrame::IExecutionFrame(const onnxruntime::OrtValueNameIdxMap &, const onnxruntime::NodeIndexInfo &, const std::vector<int> &)node_index_info_.GetMaxMLValueIdx() == ort_value_idx_map.MaxIdx()node_index_info and ort_value_idx_map are out of sync and cannot be usedonnxruntime::common::Status onnxruntime::IExecutionFrame::GetOrCreateNodeOutputMLValue(const int, int, const onnxruntime::TensorShape *, OrtValue *&, const onnxruntime::Node &, size_t)shape && tensor.Shape() == *shapeOrtValue shape verification failed. Current shape: Requested shape:invalid index void onnxruntime::IExecutionFrame::Init(const std::vector<int> &, const std::vector<OrtValue> &, const std::unordered_map<int, OrtValue> &, const std::vector<OrtValue> &)feeds.size() == feed_mlvalue_idxs.size()fetches.empty() || fetches.size() == fetch_mlvalue_idxs_.size()Fetches vector passed to GetOutputs contains entries which doesn't match the number of fetches the frame was initialized with of onnxruntime::ExecutionFrame::ExecutionFrame(const std::vector<int> &, const std::vector<OrtValue> &, const std::vector<int> &, const std::vector<OrtValue> &, const std::unordered_map<size_t, IExecutor::CustomAllocator> &, const onnxruntime::SessionState &)buffers_.find(location) == buffers_.end()static_activation_memory_sizes_in_byte_.find(location.name) == static_activation_memory_sizes_in_byte_.end()Memory type should only appear once.ExecutionFrameAllocation of memory pattern buffer for returned nullptrTrying to allocate memory for unused optional inputs/outputsTensor shape cannot contain any negative valueonnxruntime::common::Status onnxruntime::ExecutionFrame::AllocateMLValueTensorSelfOwnBufferHelper(OrtValue &, int, onnxruntime::MLDataType, const OrtMemoryInfo &, const onnxruntime::TensorShape &, bool)ort_value.Fence() == nullptrAllocateMLValueTensorSelfOwnBufferHelperFor ort_value with index: , block in memory pattern size is: but the actually size is: , fall back to default allocation behaviorShape mismatch attempting to re-use buffer. . Validate usage of dim_value (values should be > 0) and dim_param (all values with the same string should equate to the same size) in shapes in the model.AllocateMLValueTensorPreAllocateBufferonnxruntime::common::Status onnxruntime::ExecutionFrame::AllocateAsPerAllocationPlan(OrtValue &, int, const onnxruntime::TensorShape *, size_t)ort_value_index >= 0 && static_cast<size_t>(ort_value_index) < alloc_plan.size()Tried to allocate without valid type information, ort_value index=We don't expect custom allocators for non-tensor types, so a shape is mandatory here.AllocateAsPerAllocationPlanInvalid allocation kind: VerifyOutputSizesExpected shape from model of does not match actual shape of for output ReleaseMLValueImplconst onnxruntime::AllocPlanPerValue &onnxruntime::ExecutionFrame::GetAllocationPlan(int)ort_value_idx >= 0 && static_cast<size_t>(ort_value_idx) < alloc_plan.size()TraceAllocateTraceAllocation for ort_value_idx= size= failed: void onnxruntime::ExecutionFrame::TraceFree(int)TraceFreeTraceFree for ort_value_idx=Memory pattern planner is not enabled on this execution framework./Users/runner/work/1/s/onnxruntime/core/framework/execution_frame.hconst OrtValue &onnxruntime::IExecutionFrame::GetMLValue(int) constort_value_index >= 0 && static_cast<size_t>(ort_value_index) < all_values_size_int onnxruntime::NodeIndexInfo::GetMLValueIndex(int) constoffset >= 0 && static_cast<size_t>(offset) < node_values_size_ failed. Error:onnxruntime::common::Status onnxruntime::AllocateSparseTensor(OrtValue &, const onnxruntime::DataTypeImpl &, onnxruntime::AllocatorPtr, const onnxruntime::TensorShape &, size_t, bool, const onnxruntime::SessionState &)mlvalue.Fence() == nullptr/Users/runner/work/1/s/onnxruntime/core/framework/execution_provider.ccvoid onnxruntime::IExecutionProvider::InsertAllocator(onnxruntime::AllocatorPtr)TryInsertAllocatorduplicated allocator: IExecutionProvider::Compile with fused Node is not implemented by IExecutionProvider::Compile with fused Node and dll path is not implemented by IExecutionProvider::Compile with FusedNodeAndGraph is not implemented by virtual int onnxruntime::IExecutionProvider::GenerateMetaDefId(const onnxruntime::GraphViewer &, uint64_t &) constmetadef_id_generator_IExecutionProvider constructor must be called with true for use_metadef_id_creator/Users/runner/work/1/s/onnxruntime/core/framework/fallback_cpu_capability.ccstd::unordered_set<NodeIndex> onnxruntime::GetCpuPreferredNodes(const onnxruntime::GraphViewer &, const std::string &, const std::vector<const KernelRegistry *> &, const std::vector<NodeIndex> &)kernel_info != nullptrGetCpuPreferredNodesORT optimization- Force fallback to CPU execution for node: because the CPU execution path is deemed faster than overhead involved with execution on other EPs capable of executing this nodeForEachWithIndexCandidate for fallback CPU execution: /Users/runner/work/1/s/onnxruntime/core/framework/feeds_fetches_manager.ccMapNamesToMLValueIdxsError mapping feeds: Error mapping output names: void onnxruntime::FeedsFetchesManager::SetDeviceCopyChecks(onnxruntime::DeviceCopyCheck, onnxruntime::DeviceCopyCheck)input_copy_needed != DeviceCopyCheck::Unknown && output_copy_needed != DeviceCopyCheck::Unknownstatic void SafeIntExceptionHandler<onnxruntime::OnnxRuntimeException>::SafeIntOnDivZero()func info for node: already exist.Can't use func with null ptr not found./Users/runner/work/1/s/onnxruntime/core/framework/fuse_nodes_funcs.ccGetFuncs/Users/runner/work/1/s/onnxruntime/core/framework/graph_partitioner.ccPartitionOnnxFormatModelNo provider specified.Partitiononnxruntime::common::Status onnxruntime::GraphPartitioner::Partition(onnxruntime::Graph &, bool, onnxruntime::FuncManager &, onnxruntime::GraphPartitioner::Mode, std::unordered_map<std::string, uint64_t> *) constcompiled_kernel_hashes != nullptrPartitionOnnxFormatModelImplonnxruntime::common::Status onnxruntime::PartitionOnnxFormatModelImpl(onnxruntime::Graph &, bool, onnxruntime::FuncManager &, onnxruntime::KernelRegistryManager &, onnxruntime::KernelRegistry &, onnxruntime::IExecutionProvider &, GraphPartitioner::Mode, int &)fusion_style == IExecutionProvider::FusionStyle::FunctionMust use Function based fusion when exporting compiled nodes to dll. did not return correct number of compiled functionsonnxruntime::Node *onnxruntime::PlaceNode(onnxruntime::Graph &, const onnxruntime::IndexedSubGraph &, const onnxruntime::KernelRegistryManager &, const std::string &, IExecutionProvider::FusionStyle, GraphPartitioner::Mode, int &)1 == capability.nodes.size()/Users/runner/work/1/s/onnxruntime/core/framework/func_kernel.honnxruntime::FunctionKernel::FunctionKernel(const onnxruntime::OpKernelInfo &)compute_info_->create_state_func(&context, &func_state_) == 0InlineNodesPartitionOrtFormatModelImplEP: has Compile error: single_node_compute_func should have 1 elementsonnxruntime::common::Status onnxruntime::PartitionOrtFormatModelImpl(onnxruntime::Graph &, onnxruntime::FuncManager &, onnxruntime::KernelRegistryManager &, onnxruntime::KernelRegistry &, onnxruntime::IExecutionProvider &, std::unordered_map<std::string, uint64_t> &, int &)Existing entry in compiled kernel hashes for . Execution Provider must generate unique names across the entire model./Users/runner/work/1/s/onnxruntime/core/framework/kernel_def_builder.cconnxruntime::KernelDefBuilder &onnxruntime::KernelDefBuilder::VariadicAlias(int, int)input_offset >= 0 && output_offset >= 0Op with name ( and type ( Version mismatch. node_version: kernel start version: kernel_end_version: Found kernel for Op with name ( in the supported version range (node_version: However the types are incompatible. This op has been implemented only for the following types (), but the node in the model has the following type (/Users/runner/work/1/s/onnxruntime/core/framework/kernel_registry.ccTryCreateKernel kernel not found in No matching hash for kernel is not supported in Encountered following errors: (Kernel not foundkernel def can't be NULLFailed to add kernel for : Conflicting with a registered kernel with op versions.void onnxruntime::(anonymous namespace)::TraverseFormalParametersWithTypeProto(const onnxruntime::Node &, ParamFilterFn, TraverseFn) [ParamFilterFn = (lambda at /Users/runner/work/1/s/onnxruntime/core/framework/kernel_registry.cc:75:11), TraverseFn = (lambda at /Users/runner/work/1/s/onnxruntime/core/framework/kernel_registry.cc:76:11)]len <= op_schema.inputs().size()void onnxruntime::(anonymous namespace)::TraverseFormalParametersWithTypeProto(const onnxruntime::Node &, ParamFilterFn, TraverseFn) [ParamFilterFn = (lambda at /Users/runner/work/1/s/onnxruntime/core/framework/kernel_registry.cc:100:9), TraverseFn = (lambda at /Users/runner/work/1/s/onnxruntime/core/framework/kernel_registry.cc:103:9)]found duplicated provider in KernelRegistryManager (node ). /Users/runner/work/1/s/onnxruntime/core/framework/mldata_type_utils.cconnxruntime::MLDataType onnxruntime::utils::GetMLDataType(const onnxruntime::NodeArg &)nullptr != type_proto/Users/runner/work/1/s/onnxruntime/core/framework/node_index_info.ccauto onnxruntime::NodeIndexInfo::Init(const onnxruntime::ConstGraphNodes &, onnxruntime::NodeIndex, const onnxruntime::OrtValueNameIdxMap &)::(anonymous class)::operator()(const onnxruntime::NodeArg &, bool) constauto onnxruntime::NodeIndexInfo::Init(const onnxruntime::ValidNodes<const std::__1::vector<const onnxruntime::Node *, std::__1::allocator<const onnxruntime::Node *> > > &, onnxruntime::NodeIndex, const onnxruntime::OrtValueNameIdxMap &)::(anonymous class)::operator()(const onnxruntime::NodeArg &, bool) consttype_proto is not of type map!type_proto is not of type sequence!OrtValue is TensorSequence type but has no element Tensor DataType.Tensor types should have been handled alreadynot implemented is not supportedconst onnxruntime::SparseTensor &OrtValue::Get() constIsSparseTensor()Trying to get a SparseTensor, but got: /Users/runner/work/1/s/onnxruntime/core/framework/op_kernel.cconnxruntime::OpKernelContext::OpKernelContext(onnxruntime::IExecutionFrame *, const onnxruntime::OpKernel *, concurrency::ThreadPool *, const logging::Logger &)frame != nullptrkernel != nullptrOrtValue *onnxruntime::OpKernelContext::OutputMLValue(int, const onnxruntime::TensorShape &, size_t)int onnxruntime::OpKernelContext::NumVariadicInputs(size_t) constarg_num < arg_counts.size()Invalid arg_num of . Num args is TempSpace allocator not foundOrtValue *onnxruntime::OpKernelContext::GetOrCreateOutputMLValue(int)/Users/runner/work/1/s/onnxruntime/core/framework/node_index_info.hint onnxruntime::NodeIndexInfo::GetNodeOffset(onnxruntime::NodeIndex) constnode_offsets_index < node_offsets_size_/Users/runner/work/1/s/onnxruntime/core/framework/op_kernel_info.ccconst OrtMemoryInfo &onnxruntime::OpKernelInfo::GetMemoryInfo(int, OrtMemType) constNo attribute with name: is defined.Requested attribute: is expected to have type: but is of type: Attibute name and type don't matchNo attribute with this name is defined.Attribute: expected to be of type: /Users/runner/work/1/s/onnxruntime/core/framework/mem_pattern_planner.hvoid onnxruntime::MemPatternPlanner::TraceAllocation(int, size_t)!using_counters_current <= buffer_size_/Users/runner/work/1/s/onnxruntime/core/framework/ort_value_tensor_slicer.ccstatic OrtValueTensorSlicer<T> onnxruntime::OrtValueTensorSlicer<OrtValue>::Create(T &, int64_t, int64_t) [T = OrtValue]ort_value.IsTensor()Can't slice a non-tensor OrtValue. Type was ort_value.IsAllocated()gsl::narrow_cast<int64_t>(tensor_shape.NumDimensions()) >= slice_dimensionInsufficient dimensions to slice on . Shape:dim0_offset < dim0_sizeInvalid dim0_offset of . Dimension 0 is onnxruntime::OrtValueTensorSlicer<OrtValue>::Iterator::Iterator(T &, size_t, size_t, int64_t, onnxruntime::OrtValueTensorSlicer::Iterator::Direction) [T = OrtValue]typename std::enable_if<!std::is_const<reference>::value, reference>::type onnxruntime::OrtValueTensorSlicer<OrtValue>::Iterator::operator*() [T = OrtValue]static OrtValueTensorSlicer<T> onnxruntime::OrtValueTensorSlicer<const OrtValue>::Create(T &, int64_t, int64_t) [T = const OrtValue]onnxruntime::OrtValueTensorSlicer<const OrtValue>::Iterator::Iterator(T &, size_t, size_t, int64_t, onnxruntime::OrtValueTensorSlicer::Iterator::Direction) [T = const OrtValue]Multiple errors were found./Users/runner/work/1/s/onnxruntime/core/framework/parallel_executor.ccRunNodeAsyncBegin executionExiting due to terminate flag being set to true.onnxruntime::common::Status onnxruntime::ParallelExecutor::RunNodeAsync(size_t, const onnxruntime::SessionState &, const logging::Logger &)Got nullptr from GetKernel for node: _fence_beforeNon-zero status code returned while running node. Name:'' Status Message: _kernel_time_fence_after/Users/runner/work/1/s/onnxruntime/core/framework/op_kernel_context_internal.honnxruntime::OpKernelContextInternal::OpKernelContextInternal(const onnxruntime::SessionState &, onnxruntime::IExecutionFrame &, const onnxruntime::OpKernel &, const logging::Logger &, const bool &)entry != nullptrAll implicit inputs should have OrtValue instances by now. does not.Exception running nodes starting at '. Unknown exception was caught by catch-all handler./Users/runner/work/1/s/onnxruntime/core/framework/prepacked_weights.ccuint64_t onnxruntime::PrePackedWeights::GetHash() constbuffers_.size() == buffer_sizes_.size()/Users/runner/work/1/s/onnxruntime/core/framework/prepacked_weights_container.cconnxruntime::AllocatorPtr onnxruntime::PrepackedWeightsContainer::GetOrCreateAllocator(const std::string &)Unsupported device allocator in the context of pre-packed weights caching: libonnxruntime_providers_cuda.dyliblibonnxruntime_providers_dnnl.dyliblibonnxruntime_providers_openvino.dyliblibonnxruntime_providers_tensorrt.dylib/Users/runner/work/1/s/onnxruntime/core/framework/provider_bridge_ort.ccGetProviderInfo_CUDAGetProviderInfo_CUDA called, returning nullptrProviderInfo_CUDA *onnxruntime::GetProviderInfo_CUDA()SessionOptionsAppendExecutionProvider_Tensorrt: Failed to load shared librarySessionOptionsAppendExecutionProvider_OpenVINO: Failed to load shared libraryCUDA execution provider is not enabled.OrtSessionOptionsAppendExecutionProvider_Cuda: Failed to load shared libraryEnsureGetunordered_map::at: key not found/Users/runner/work/1/s/include/onnxruntime/core/framework/op_kernel_context.hconst T *onnxruntime::OpKernelContext::Input(int) const [T = onnxruntime::Tensor]Missing Input: const T &onnxruntime::OpKernelContext::RequiredInput(int) const [T = onnxruntime::Tensor]input_ptrRequired input at index is not present.onnxruntime::Tensor *onnxruntime::OpKernelContext::Output(int)p_ml_valueonnxruntime::Tensor &onnxruntime::OpKernelContext::RequiredOutput(int, const onnxruntime::TensorShape &)output_ptrRequired output at index gsl::span<const T> onnxruntime::Tensor::DataAsSpan() const [T = long long]void *onnxruntime::Tensor::MutableDataRaw(onnxruntime::MLDataType)type == dtype_Tensor type mismatch.const void *onnxruntime::Tensor::DataRaw(onnxruntime::MLDataType) constvoid onnxruntime::Tensor::Reshape(const onnxruntime::TensorShape &)shape_.Size() == new_shape.Size()Tensor size () != new size (/Users/runner/work/1/s/onnxruntime/core/framework/sequential_executor.cc[Memory] ExecutionFrame statically allocates [Memory] ExecutionFrame dynamically allocates ReleaseNodeMLValues/Users/runner/work/1/s/onnxruntime/core/framework/session_state.ccSetupAllocatorsAllocator already registered for . Ignoring allocator from CreateGraphInfoSaveMLValueNameIndexMappingDone saving OrtValue mappings.PopulateKernelCreateInfoconst onnxruntime::KernelCreateInfo &onnxruntime::SessionState::GetNodeKernelCreateInfo(onnxruntime::NodeIndex) constentry != kernel_create_info_map_.cend()duplicated ort_value index:. Do you have duplicated calls to SessionState::AddInitializedTensor function?Using an input in multiple nodes on different devices is not supported currently. Input: is used by node ) and node Failed to find input name in the mapping: void onnxruntime::SessionState::AddOutputNameToNodeInfoMapping(const std::string &, const onnxruntime::SessionState::NodeInfo &)output_names_to_nodeinfo.empty()Only one node should produce an output. Existing entry for void onnxruntime::SessionState::AddSubgraphSessionState(onnxruntime::NodeIndex, const std::string &, std::unique_ptr<SessionState>)existing_entries.find(attribute_name) == existing_entries.cend()Entry exists in node for attribute const onnxruntime::NodeIndexInfo &onnxruntime::SessionState::GetNodeIndexInfo() constnode_index_info_SetGraphAndCreateKernels must be called prior to GetExecutionInfo.void onnxruntime::SessionState::UpdateToBeExecutedNodes(const std::vector<int> &)onnxruntime::common::Status onnxruntime::SessionState::CreateSubgraphSessionState()subgraphMain Graph instance should have populated all subgraphs when being resolved.CreateSubgraphSessionStateKernel create info is null. Invalid ORT format model.Kernel create info node indices are null. Invalid ORT format model.Kernel create info hashes are null. Invalid ORT format model.Size mismatch for kernel create info node indexes and hashes. Invalid ORT format model.Can't find node with index . Invalid ORT format model.Unable to find compiled kernel hash for node ''.SessionState for subgraphs is null. Invalid ORT format model.Subgraph SessionState entry for is missing. Invalid ORT format model.Subgraph SessionState for is null. Invalid ORT format model.FinalizeSessionStateFinalizeSessionStateImplonnxruntime::common::Status onnxruntime::SessionState::FinalizeSessionStateImpl(const std::basic_string<PATH_CHAR_TYPE> &, onnxruntime::KernelRegistryManager &, const onnxruntime::Node *, const onnxruntime::SessionOptions &, bool, std::unordered_map<std::string, size_t> &)entry != node_to_subgraph_ss.second.cend()Missing session state for subgraph. Node:'' OpType: Index: Attribute:p_op_kernelauto onnxruntime::SessionState::PrepackConstantInitializedTensors(std::unordered_map<std::string, size_t> &, const std::unordered_map<std::string, const OrtValue *> &)::(anonymous class)::operator()(bool) constallocator_for_caching.get() != nullptrweights_to_be_filled_in.buffers_.size() > 0The kernel corresponding to the node doesn't have an implementation that can cache computed pre-packed weights!op_type.empty()Using cached version of pre-packed weight for constant initializer: used in the node: which is of op type: Unable to write the provided PrePackedWeights instance into the containerCould not find OrtValue with name ''+KernelUseSharedPrePackedBuffers doesn't have an implementation that can consume provided pre-packed weightsCould not find OrtValue with idx 'GetSubGraphSessionStatesOrtFormat/Users/runner/work/1/s/onnxruntime/core/framework/session_state_utils.ccSaveInitializedTensorsSaving initialized tensors.common::Status onnxruntime::session_state_utils::SaveInitializedTensors(const onnxruntime::Env &, const std::basic_string<PATH_CHAR_TYPE> &, const onnxruntime::GraphViewer &, const onnxruntime::AllocatorPtr &, const onnxruntime::OrtValueNameIdxMap &, const std::vector<OrtValueIndex> &, onnxruntime::ITensorAllocator &, const std::function<Status (int, const OrtValue &, const OrtCallback &, bool)> &, const logging::Logger &, const onnxruntime::DataTransferManager &, const onnxruntime::ExecutionPlanBase &, const onnxruntime::SessionOptions &)ort_value_name_idx_map.MaxIdx() > -1entry != initialized_tensors_to_allocate.end() && entry->second->data_type() != ONNX_NAMESPACE::TensorProto_DataType_STRING[Memory] SessionStateInitializer statically allocates bytes for Using user supplied initializer with name (Deserialize tensor failed.Done saving initialized tensorsSaveInputOutputNamesToNodeMappingSubgraph input with name is not used by any node.Cannot use user supplied initializer with name: () because the ORT planned memory location device ) is different from what is supplied (DeserializeTensorProto() takes either pre-allocated buffer or an allocator!Internal error. The preallocated buffer is too small. Requires DeserializeTensorProtoFailed to copy tensor to /Users/runner/work/1/s/onnxruntime/core/framework/tensor.cconnxruntime::Tensor::Tensor(onnxruntime::MLDataType, const onnxruntime::TensorShape &, void *, const OrtMemoryInfo &, ptrdiff_t)p_type != nullptronnxruntime::Tensor::Tensor(onnxruntime::MLDataType, const onnxruntime::TensorShape &, std::shared_ptr<IAllocator>)onnxruntime::Tensor::Tensor(onnxruntime::MLDataType, const onnxruntime::TensorShape &, void *, std::shared_ptr<IAllocator>, ptrdiff_t)size_t onnxruntime::Tensor::SizeInBytes() constvoid onnxruntime::Tensor::Init(onnxruntime::MLDataType, const onnxruntime::TensorShape &, void *, onnxruntime::AllocatorPtr, ptrdiff_t)dtype_ != nullptrTensor is expected to contain one of the primitive data types. Got: /Users/runner/work/1/s/onnxruntime/core/framework/tensor_allocator_with_mem_pattern.hFinalizePlanFailed to get allocator for location: duplicated locationMem pattern for initializer is not foundWeight buffer for initializer '' is not foundGet preallocated buffer for initializer '' failedTracemodel format error! Need a value for the external data infoparsing checksum/Users/runner/work/1/s/onnxruntime/core/framework/tensor_shape.ccint64_t onnxruntime::TensorShape::SizeToDimension(size_t) constdimension <= num_dimsInvalid dimension of for SizeFromDimension. Tensor has dimensions.int64_t onnxruntime::TensorShape::SizeFromDimension(size_t) constonnxruntime::TensorShape onnxruntime::TensorShape::Slice(size_t, size_t) constdimstart <= dimend && dimend <= size(){}/Users/runner/work/1/s/onnxruntime/core/framework/tensor_type_and_shape.ccOrtStatusPtr OrtApis::GetTensorTypeAndShape(const OrtValue *, OrtTensorTypeAndShapeInfo **)type != nullptrInvalid TensorProtocorrupted protobuf data: tensor shape size() does not match the data size() in protoUnpackTensor: the pre-allocate size does not match the size in protodata overflowTensorProtoToTensor() tensor shape mismatch!TensorProto type can not be writen into Tensor type /Users/runner/work/1/s/onnxruntime/core/framework/tensorprotoutils.ccTensorProtoToTensorstring tensor can not have raw datatensor can't contain negative dimsInitialized tensor with unexpected type: TensorProtoToMLValue() must take a pre-allocated MemBuffer!string tensor can not use pre-allocated bufferThe preallocated buffer is too small. Requires , Got ConstantNodeProtoToTensorProtocommon::Status onnxruntime::utils::ConstantNodeProtoToTensorProto(const onnx::NodeProto &, const onnxruntime::Path &, onnx::TensorProto &)Unsupported attribute value type of in 'Constant' node 'SparseTensorProtoToDenseTensorProto BUG! Report to onnxruntime team. element_size of: is not supported. type: common::Status onnxruntime::utils::DenseTensorToSparseTensorProto(const onnx::TensorProto &, const onnxruntime::Path &, onnx::SparseTensorProto &)HasDataType(dense_proto)DenseTensorToSparseTensorProto data_type: UnpackInitializerDataUnsupported type: UnpackTensorWithExternalDataImplnullptr == p_dataGetExternalDataInfoTensor does not have external data to read from.External data type cannot be UNDEFINED or STRING.TensorProto external data size mismatch. Computed size: , external_data.length: GetFileContentUnsupported sparse tensor data type of ReadExternalDataForTensorUnpackTensor: the pre-allocated size does not match the raw data size, expected CopySparseDataIndicies expected to be INT64Sparse Indicies raw data size does not match expected.Invalid SparseTensor indices. Should either have raw or int64 dataonnxruntime::common::Status onnxruntime::utils::CopySparseData(size_t, const onnx::TensorProto &, gsl::span<const int64_t>, std::function<void (size_t, size_t)>) [T = unsigned char]rank == dims.size() && rank > 0cur_index == &*indices_data.cend()Invalid SparseTensor indices. Should be rank 0 or 1. Got:onnxruntime::common::Status onnxruntime::utils::CopySparseData(size_t, const onnx::TensorProto &, gsl::span<const int64_t>, std::function<void (size_t, size_t)>) [T = unsigned short]onnxruntime::common::Status onnxruntime::utils::CopySparseData(size_t, const onnx::TensorProto &, gsl::span<const int64_t>, std::function<void (size_t, size_t)>) [T = unsigned int]onnxruntime::common::Status onnxruntime::utils::CopySparseData(size_t, const onnx::TensorProto &, gsl::span<const int64_t>, std::function<void (size_t, size_t)>) [T = unsigned long long]CoreMLExecutionProviderInternalTestingExecutionProvider/Users/runner/work/1/s/onnxruntime/core/framework/utils.ccconst OrtMemoryInfo &onnxruntime::utils::FindMemoryInfoForValue(const onnxruntime::SessionState &, const std::string &)exec_plan_ptrInitializeFeedFetchCopyInfoCopyOneInputAcrossDevicesExecuteGraphFindMemoryInfoForValueconst OrtMemoryInfo &onnxruntime::utils::FindMemoryInfoForValue(const onnxruntime::OrtValueNameIdxMap &, const onnxruntime::SequentialExecutionPlan &, const std::string &)CalculateStaticCopyInfoForFeedsbool onnxruntime::utils::FinalizeCopyInfoForFeeds(const std::vector<OrtDevice> &, std::vector<MLValueCopyInfo> &)feed_locations.size() == copy_info.size()bool onnxruntime::utils::FinalizeCopyInfoForFetches(const std::vector<const OrtMemoryInfo *> &, std::vector<MLValueCopyInfo> &)fetch_alloc_info.size() == copy_info.size()CalculateStaticCopyInfoForFeedonnxruntime::common::Status onnxruntime::utils::BatchOrCopyMLValue(const onnxruntime::SessionState &, const onnxruntime::MLValueCopyInfo &, const OrtValue &, OrtValue &, std::vector<IDataTransfer::SrcDstPair> *)allocator != nullptrFailed to find allocator for device BatchOrCopyMLValueExecuteGraphImplOnly one thread was configured for parallel execution. Hence will use sequential execution.common::Status onnxruntime::utils::CopyInputsAcrossDevices(const onnxruntime::SessionState &, const std::vector<OrtValue> &, std::vector<OrtValue> &, const std::vector<MLValueCopyInfo> &)copy_info.size() == num_feedsCopyInputsAcrossDevicesCopyOutputsAcrossDevicesNumber of neurons in the hidden layer.Constrain seq_lens to integral tensors.The input sequences packed (and potentially padded) into one 3-D tensor with the shape of `[seq_length, batch_size, input_size]`Optional tensor specifying lengths of the sequences in a batch. If not specified - assumed all sequences in the batch to have length `seq_length`. It has shape `[batch_size]` QWThe weight tensor of the query layer in the attention mechanism. Should be of shape `[num_directions, am_query_depth(hidden_size of lstm), am_attn_size]` MWThe weight tensor of the memory layer in the attention mechanism. Should be of shape `[num_directions, memory_depth, am_attn_size]` The attention_v tensor in the attention mechanism. Should be of shape `[num_directions, am_attn_size]` The sequence of the memory (input) for attention mechanism. Should be of `[batch_size, max_memory_step, memory_depth]` memory_seq_lensThe sequence length of the input memory for the attention mechanism. Should be of `[batch_size]` AWThe weights of attention layer in the attention wrapper. If exists, should be of shape `[num_directions, memory_depth+hidden_size, aw_attn_size]. Please note that attention mechanism context depth is also memory_depth in the attention mechanism.` A tensor that concats all the intermediate output values of the hidden. It has shape `[seq_length, num_directions, batch_size, hidden_size]`The last output value of the hidden. It has shape `[num_directions, batch_size, hidden_size]`. 'pads' input must be a 1D (shape: [2 * n_input_dims]) tensor of type int64Pads has incorrect number of valuesInput tensors of wrong rank (0).Incompatible dimensions for matrix multiplicationInputs 0 shall be 3 dimensionsInvalid bias shapeInputs 4 shall be 5 dimensions/Users/runner/work/1/s/onnxruntime/core/graph/contrib_ops/contrib_defs.ccNumber of attention headsWhether every token can only attend to previous tokens. Default value is 0.3D input tensor with shape (batch_size, sequence_length, input_hidden_size)weight2D input tensor with shape (input_hidden_size, 3 * hidden_size), where hidden_size = num_heads * head_sizebias1D input tensor with shape (3 * hidden_size)mask_indexAttention mask with shape (batch_size, 1, max_sequence_length, max_sequence_length), (batch_size, past_sequence_length + sequence_length)or (batch_size, sequence_length, past_sequence_length + sequence_length), or index with shape (batch_size) or (2 * batch_size).Mpastpast state for key and value with shape (2, batch_size, num_heads, past_sequence_length, head_size).3D output tensor with shape (batch_size, append_length, hidden_size)presentpresent state for key and value with shape (2, batch_size, num_heads, past_sequence_length + sequence_length, head_size)Constrain input and output types to float tensors.Constrain mask index to integer types2D input tensor with shape (input_hidden_size, 3 * hidden_size), hidden_size = num_heads * head_sizeinput_scalescale of quantized input tensor. It's a scalar, which means a per-tensor/layer quantization.weight_scalescale of weight scale. It's a scalar or a 1D tensor, which means a per-tensor/per-column quantization.Its size should be 3 * hidden_size if it is per-column quantizationAttention mask index with shape (batch_size)input_zero_pointzero point of quantized input tensor.It's a scalar, which means a per-tensor/layer quantization.weight_zero_pointzero point of quantized weight tensor. It's a scalar or a 1D tensor, which means a per-tensor/per-column quantization.Its size should be 3 * hidden_size if it is per-column quantization3D output tensor with shape (batch_size, sequence_length, hidden_size)Constrain input and output types to int8 tensors.windowOne sided attention windows length W, or half of total window length3D input tensor with shape (batch_size, sequence_length, hidden_size), hidden_size = num_heads * head_size2D input tensor with shape (hidden_size, 3 * hidden_size)maskAttention mask with shape (batch_size, sequence_length)global_weightglobal_biasglobalGlobal attention flags with shape (batch_size, sequence_length)GConstrain to integer typesThe epsilon value to use to avoid division by zero.input_ids2D words IDs with shape (batch_size, sequence_length)segment_ids2D segment IDs with shape (batch_size, sequence_length)word_embedding2D with shape (,hidden_size)position_embedding2D with shape (, hidden_size)segment_embedding1D gamma tensor for layer normalization with shape (hidden_size)beta1D beta tensor for layer normalization with shape (hidden_size)2D attention mask with shape (batch_size, sequence_length)1D mask_index tensor with shape (batch_size)Constrain input and output integer tensors typesConstrain input and output float tensors types.input tensorbias tensoroutput tensorConstrain input and output types to float or half tensors.3D input tensor with shape (batch_size, sequence_length, hidden_size)skip3D skip tensor with shape (batch_size, sequence_length, hidden_size)1D input tensor with shape (hidden_size)1D skip tensor with shape (hidden_size1D bias tensor with shape (hidden_sizemeanSaved mean used during training to speed up gradient computationUinv_std_varSaved inverse standard variance used during training to speed up gradient computation.Constrain mean and inv_std_var to float tensors.Value of alphaValue of beta1D input tensor1D output tensorBias applied to each channel, same size as C.The scale to apply.Input tensor of shape [N,C,H,W]Result, has same shape and type as inputA 1-D values of (leftBorder, topBorder, rightBorder, bottomBorder).A 1-D values of (height, width).Result, has same type as input, with H and W dimensions reduced.Threshold valueInput tensorOutput tensordataTensor of data to extract slices from.1-D tensor of starting indices of corresponding axis in `axes`ends1-D tensor of ending indices (exclusive) of corresponding axis in axesaxes1-D tensor of axes that `starts` and `ends` apply to.Sliced data tensor.Constrain indices to integer typesThe shape of filled tensorThe filled tensorinput_as_shapeextra_shapeInput data to be scaledOutput data after scalingdrop_statesBool to determine if hidden state is zeroes or passed along for timesteps past the given sequence_length.hidden_prevThe previous GRU hidden state.gatesUnactivated gate outputs from forget, update, and output gates, pre-activation.seq_lengthsArray of sequence lengths. len(seq_lengths) should equal batch size N.The timestep for this operation.hiddenThe new GRU hidden state calculated by this op.If 1, mean and variance are computed across channels. Default is 0.If 0, normalize the mean only. Default is 1.Scaling valueThe scaled hyperbolic tangent values of the input tensor computed element-wiseauto_padpadsConstrain input0 and output types to float tensorssignal_ndimnormalizedonesidedAinput_0input_1CWPadsConstrain input and output types to float tensorsactivation_paramsZInput tensor A. The shape of A should be (M, K) if transA is 0, or (K, M) if transA is non-zero.Input tensor B. The shape of B should be (K, N) if transB is 0, or (N, K) if transB is non-zero.Input tensor C. The shape of C should be unidirectional broadcastable to (M, N).Output tensor of shape (M, N).Constrain input and output types to float/int tensors.Whether A should be transposedWhether B should be transposedScalar multiplier for the product of input tensors A * B.Scalar multiplier for input tensor C.activation_gammaSpecified axis to insert a dimensionStrings to tokenizeTokenized stringsInput/Output is a string tensormarkBoolean whether to mark the beginning/end character with start of text character (0x02)/end of text character (0x03).The string used to pad output tensors when the tokens extracted doesn't match the maximum number of tokens found. If start/end markers are needed, padding will appear outside the markers.tokenexpAn optional string. Token's regular expression in basic POSIX format (pubs.opengroup.org/onlinepubs/9699919799/basedefs/V1_chap09.html#tag_09_03). If set, tokenizer may produce tokens matching the specified pattern. Note that one and only of 'tokenexp' and 'separators' should be set.an optional list of strings attribute that contains a list of separators - regular expressions to match separators Two consecutive segments in X connected by a separator would be divided into two tokens. For example, if the input is "Hello World!" and this attribute contains only one space character, the corresponding output would be ["Hello", "World!"]. To achieve character-level tokenization, one should set the 'separators' to [""], which contains an empty string.Minimum number of characters allowed in the output. For example, if mincharnum is 2, tokens such as "A" and "B" would be ignoredN-dimensional matrix AN-dimensional matrix BMatrix multiply results from A * BConstrain input A data types as 16-bit integer tensorConstrain input B data types as 16-bit integer tensorConstrain output Y data types as 32-bit integer tensor.T3 must be tensor(uint32) when both T1 and T2 are tensor(uint16),or must be tensor(int32) when either T1 or T2 is tensor(int16).Scalar multiplier for the product of the input tensors.Whether A should be transposed on the last two dimensions before doing multiplicationWhether B should be transposed on the last two dimensions before doing multiplicationMatrix multiply resultsAn input tensor to hash.32-bit hash value.Constrain input type to unsigned or signed 32-bit integer tensor, or string tensor. It should be utf-8 encoded if using unicode.Constrain output type to unsigned and signed 32-bit integer tensor.seedSeed for the hashing algorithm, unsigned 32-bit integer, default to 0.positiveIf value is 1, output type is uint32_t, else int32_t. Default value is 1.Tensor of rank r >= 1.indicesTensor of rank q >= 1.Tensor of rank q-1+r-indices[-1].Constrain indice type to int32 or int64Integer representing the embedding vector size for each word.If not provide, use the fileter size of conv weightThis operator applies convolution to word from left to right with window equal to conv_window_size and stride to 1.Take word 'example' for example, with conv_window_size equal to 2, conv is applied to [ex],[xa], [am], [mp]...If not provide, use the first dimension of conv kernal shape.Integer representing the embedding vector size for each char.If not provide, use the char embedding size of embedding vector.SequenceSpecify batchs of sequence words to embeddingSpecify weights of convSpecify bias of convSpecify embedding vector of charConstrain to tensor(int32).Constrain to tensor(float).modeThree modes: `constant`(default) - pads with a given constant value, `reflect` - pads with the reflection of the vector mirrored on the first and last values of the vector along each axis, `edge` - pads with the edge values of arrayInput tensor.Tensor of integers indicating the number of padding elements to add or remove (if negative) at the beginning and end of each axis. For 2D input tensor, it is the number of pixels. `pads` should be a 1D tensor of shape [2 * input_rank] or a 2D tensor of shape [1, 2 * input_rank]. `pads` format (1D example) should be as follow [x1_begin, x2_begin,...,x1_end, x2_end,...], where xi_begin is the number of pixels added at the beginning of axis `i` and xi_end, the number of pixels added at the end of axis `i`.(Optional) A scalar or rank 1 tensor containing a single value to be filled if the mode chosen is `constant` (by default it is 0.0).Tensor after padding.xA 1-D input tensor that is to be processed.A 1-D tensor of the same type as 'x' containing all the unique values in 'x' sorted in the same order that they occur in the input 'x'idxA 1-D INT64 tensor of the same size as 'x' containing the indices for each value in 'x' in the output 'uniques'countsA 1-D INT64 tensor containing the the count of each element of 'uniques' in the input 'x'Input can be of any tensor type.The distance metric to use. If a string, the distance function can be "braycurtis", "canberra", "chebyshev", "cityblock", "correlation", "cosine", "dice", "euclidean", "hamming", "jaccard", "jensenshannon", "kulsinski", "mahalanobis", "matching", "minkowski", "rogerstanimoto", "russellrao", "seuclidean", "sokalmichener", "sokalsneath", "sqeuclidean", "wminkowski", "yule".2D matrix with shape (M,N)2D matrix with shape (K,N)A 2D Matrix that represents the distance between each pair of the two collections of inputs.Constrains input to only numeric types.The pooling method. Two modes are supported: 'bilinear' and 'nearest'. Default is 'bilinear'.Value used for extrapolation, when applicable. Default is 0.0f. Input data tensor from the previous operator; 4-D feature map of shape (N, C, H, W), where N is the batch size, C is the number of channels, and H and W are the height and the width of the data.roisRoIs (Regions of Interest) to pool over; rois is 2-D input of shape (num_rois, 4) given as [[y1, x1, y2, x2], ...]. The RoIs' coordinates are normalized in the coordinate system of the input image. Each coordinate set has a 1:1 correspondence with the 'batch_indices' input.batch_indices1-D tensor of shape (num_rois,) with each element denoting the index of the corresponding image in the batch.crop_size1-D tensor of 2 elements: [crop_height, crop_width]. All cropped image patches are resized to this size. Both crop_height and crop_width need to be positive.RoI pooled output, 4-D tensor of shape (num_rois, C, crop_height, crop_width). The r-th batch element Y[r-1] is a pooled feature map corresponding to the r-th RoI X[r-1].Constrain types to float tensors.Constrain types to int tensors.The first normalization dimension: normalization will be performed along dimensions axis : rank(inputs).stash_typetype used for stash mean/inv_std_varInput data tensor from the previous layer.Scale tensor.Bias tensor.Output data tensor.InvStdDevSaved inverse standard deviation used during training to speed up gradient computation.Constrain input types and output Y type to float tensors.Type of Mean and InvStdDev tensors.Constrain input and output types (except mean and inv_std_var) to float tensors.Constrain mean and inv_std_var to be float tensors.The input data as Tensor.The output.The normal input data.The bias input data that is a 1D tensor.Input tensor. Every matrix in the batch must be invertible.Output tensor of the same type and shape as the input tensor.The embedding matrix of size N x M. 'N' is equal to the maximum possible index + 1, and 'M' is equal to the embedding sizeLong tensor containing the indices to extract from embedding matrix.padding_idxA 0-D scalar tensor. If specified, the entries at `padding_idx` do not contribute to the gradient; therefore, the embedding vector at `padding_idx` is not updated during training, i.e. it remains as a fixed pad.scale_grad_by_freqA 0-D bool tensor. If given, this will scale gradients by the inverse of frequency of the indices (words) in the mini-batch. Default is ``False``Output tensor of the same type as the input tensor. Shape of the output is * x M, where '*' is the shape of input indices, and 'M' is the embedding size.Constrain input and output types to all numeric tensors.Boolean. Indicates whether upper or lower part of matrix is retained. Default is true.Input tensor of rank 2 or higher.kA 0-D tensor containing a single value corresponding to the number diagonals above or the main diagonal to exclude or include.Default value is 0 if it's not specified.Constrain input and output types to all numeric tensors and bool tensors.softmax_axisapply softmax to elements for dimensions softmax_axis or higherbroadcast_axisbroadcast bias across input for dimensions broadcast_axis to softmax_axis-1The bias (or mask) as Tensor.(Optional) Seed to the random generator, if not specified we will auto generate one.The bias input, a vector with the same shape as last dim of dataresidualThe residual input, must have the same shape as dataratioThe ratio of random dropout, with value in [0, 1). If this input was not set, or if it was set to 0, the output would be a simple copy of the input. If it's non-zero, output will be a random dropout of input, which is typically the case during training.training_modeIf set to true then it indicates dropout is being used for training. It is an optional value hence unless specified explicitly, it is false. If it is false, ratio is ignored and the operation mimics inference mode where nothing will be dropped from the input data and if mask is requested as output it will contain all ones.The output mask of dropout.Constrain input 'ratio' types to float tensors.Constrain output 'mask' types to boolean tensors.isinf_onlyIf true, check only for Inf, -Inf.isnan_onlyIf true, check only for NaN.Constrain the output to a boolean tensor.Input tensors to check.The output scalar. Its value is true if all input tensors are finite. Otherwise, the output value would be false.Incompatible dimensionsInputs 0 shall be 2 dimensionsword_embedding should have 2 dimensions and dimension size is known.X_biasNegative values are not allowed in a shape specificationAttribute should specify a shapeInput's shape must be 4-D'Border' attribute must be present and must contain exactly 4 values - (left_border, top_border, right_border, bottom_border)'Scale' must contain exactly 2 values - (height, width)) needs to be greater than or equal to the top_border () + bottom_border () needs to be greater than or equal to the left_border () + right_border () + scale[0] () + scale[1] (First input does not have rank 2Second input does not have rank 2Input axis is invalid: inputs are expected to have tensor type and output type should not be null.both data and indices tensor need to have rank larger than zero.last dimension of indices must not be larger and rank of data tensor'pads' input must be a 1D (shape: [input_rank]) or 2D tensor (shape: [1, input_rank]) of type int64first input tensor has wrong dimensionrois input tensor has wrong dimensionbatch_indices shape input tensor has wrong dimensioncrop_size shape input tensor has wrong dimensionInput rank must be >= 2.The inner-most 2 dimensions must have the same size (mat_w: != mat_h: expected to have rank > but has rank Dimension mismatch in unification between auto onnxruntime::contrib::RegisterContribSchemas()::(anonymous class)::operator()(onnx::InferenceContext &) const!(isinf_only && isnan_only)Both attributes isinf_only and isnan_only cannot be set. Unset both to check for both conditions./Users/runner/work/1/s/onnxruntime/core/graph/contrib_ops/nchwc_schema_defs.ccchannelstensor rank too smallinvalid scales dimensioninvalid scales value/Users/runner/work/1/s/onnxruntime/core/graph/contrib_ops/nhwc_schema_defs.ccInput data tensor from the previous operator; According to channels_last, dimensions for image case are (N x C x H x W), or (N x H x W x C) where N is the batch size, C is the number of channels, and H and W are the height and the width of the data. For non image case, the dimensions are in the form of (N x C x D1 x D2 ... Dn), or (N x D1 X D2 ... Dn x C) where N is the batch size.Scale of quantized input 'X'. It must be a scalar.Zero point tensor for input 'X'. It must be a scalar.Scale of quantized output 'Y'. It must be a scalar.Zero point tensor for output 'Y'. It must be a scalar.Output data tensor from pooling across the input tensor. The output tensor has the same rank as the input. with the N and C value keep it value, while the otherdimensions are all 1.Constrain input and output types to singed/unsigned int8 tensors.Works on NHWC layout or not? Default not.Input scale. It's a scalar, which means a per-tensor/layer quantization.Input zero point. Default value is 0 if it's not specified. It's a scalar, which means a per-tensor/layer quantization.Output zero point. Default value is 0 if it's not specified. It's a scalar, which means a per-tensor/layer quantization.Constrain input and output types to 8 bit tensors.Output tensor must have at least 2 dimensionsInput data type does not match the expected data typeInput data type does not match the expected data type. Current data type is Scale and Zero-point must be a scalarScale and Zero-point must be of rank 1Scale and Zero-point must be of rank 1 and the number of elements should be equal to the number of rows of the corresponding input./Users/runner/work/1/s/onnxruntime/core/graph/contrib_ops/quantization_defs.ccThe axis along which same quantization parameters are applied. It's optional.If it's not specified, it means per-tensor quantization and input 'x_scale' and 'x_zero_point' must be scalars.If it's specified, it means per 'axis' quantization and input 'x_scale' and 'x_zero_point' must be 1-D tensors.Scale for doing quantization to get 'y'. It could be a scalar or a 1-D tensor,which means a per-tensor or per-axis quantization. If it's a 1-D tensor, its number of elements should be equal to the dimension value of 'axis' dimension of input 'x'.Zero point for doing quantization to get 'y'. It could be a scalar or a 1-D tensor, which means a per-tensoror per-axis quantization. If it's a 1-D tensor, its number of elements should be equal to the dimension value of 'axis' dimension of input 'x'.Constrain 'x', 'y_scale' to float tensors.Constrain 'y_zero_point' and 'y' to 8-bit integer tensors.N-D quantized Input tensor to be de-quantized.Scale for input 'x'. It could be a scalar or a 1-D tensor, which means a per-tensor or per-axis quantization.If it's a 1-D tensor, its number of elements should be equal to the dimension value of 'axis' dimension of input 'x'.Zero point for input 'x'. It could be a scalar or a 1-D tensor, which means a per-tensor or per-axis quantization.If it's a 1-D tensor, its number of elements should be equal to the dimension value of 'axis' dimension of input 'x'.Constrain 'x' and 'x_zero_point' to 8-bit integer tensors.Constrain 'y', 'x_scale' to float tensors.Constrain output data type to 32-bit integer tensor.T2 must be tensor(uint32) when T1 is tensor(uint8),or must be tensor(int32) when T1 is tensor(int8).A_zero_pointInput A zero point. Default value is 0 if it's not specified. It's a scalar, which means a per-tensor/layer quantization.B_zero_pointInput B zero point. Default value is 0 if it's not specified. It's a scalar, which means a per-tensor/layer quantization.Constrain output to 32 bit tensorConstrain input types to 8 bit signed and unsigned tensors.Constrain output types to 32 bit tensors.Scale of quantized input 'B'. It could be a scalar or a 1-D tensor, which means a per-tensor or per-column quantization. If it's a 1-D tensor, its number of elements should be equal to the number of columns of input 'B'.1D input tensor, whose dimension is same as B's last dimensionConstrain input A, b_scale and output Y data type as float tensor.Scale of quantized input 'A'. It could be a scalar or a 1-D tensor, which means a per-tensor or per-column quantization. If it's a 1-D tensor, its number of elements should be equal to the number of columns of input 'A'.Zero point tensor for input 'A'. It's optional and default value is 0. It could be a scalar or a 1-D tensor, which means a per-tensor or per-column quantization. If it's a 1-D tensor, its number of elements should be equal to the number of columns of input 'A'.Constrain input a_scale, b_scale and output Y data type as float tensor.additionC = (A_scale * (A - A_zero_point) + B_scale * (B - B_zero_point))/C_scale + C_zero_pointmultiplicationC = ((A - A_zero_point) * (B - B_zero_point)) * (A_scale * B_scale)/C_scale + C_zero_pointdata_scaledata_zero_pointreduced_scalereduced_zero_pointX_scaleInput X's scale. It's a scalar, which means a per-tensor/layer quantization.X_zero_pointInput X's zero point. Default value is 0 if it's not specified. It's a scalar, which means a per-tensor/layer quantization.Y_scaleOutput Y's scale. It's a scalar, which means a per-tensor/layer quantization.Y_zero_pointOutput Y's zero point. Default value is 0 if it's not specified. It's a scalar, which means a per-tensor/layer quantization.The weight tensor for the gates. Concatenation of `W[iofc]` and `WB[iofc]` (if bidirectional) along dimension 0. The tensor has shape `[num_directions, input_size, 4*hidden_size]`.The recurrence weight tensor. Concatenation of `R[iofc]` and `RB[iofc]` (if bidirectional) along dimension 0. This tensor has shape `[num_directions, hidden_size, 4*hidden_size]`.W's scale. Its size is [num_directions] for per-tensor/layer quantization, or [num_directions, 4*hidden_size] for per-channel quantization on the axis input_size.W's zero point. Its size is [num_directions] for per-tensor/layer quantization, or [num_directions, 4*hidden_size] for per-channel quantization on the axis input_size.R's scale. Its size is [num_directions] for per-tensor/layer quantization, or [num_directions, 4*hidden_size] for per-channel quantization on the axis input_size.R's zero point. Its size is [num_directions] for per-tensor/layer quantization, or [num_directions, 4*hidden_size] for per-channel quantization on the axis input_size.Constrain weights types to 8 bit tensors.Y's scale.Y's zero point.T8List of tensors/scale/zero_point for concatenationTVConstrain input and output types to 8 bit signed and unsigned tensors.Constrain scale types to any float tensor type.Sequence of (Tensor, Scale, ZeroPoint) tuples. The type is sequence of (T8, TF, T8). +:/\T *onnxruntime::Tensor::MutableData() [T = std::__1::basic_string<char>]const T *onnxruntime::Tensor::Data() const [T = std::__1::basic_string<char>]/Users/runner/work/1/s/onnxruntime/core/session/ort_env.ccstatic void OrtEnv::Release(OrtEnv *)env_ptr == p_instance_/Users/runner/work/1/s/onnxruntime/core/optimizer/attention_fusion_helper.hbool onnxruntime::AttentionFusionHelper::CheckSliceParameters(const onnxruntime::Graph &, const onnxruntime::Node &, const std::vector<int> &, const std::vector<int64_t> &, const logging::Logger &)input_indices.size() == expected_values.size() && input_indices.size() > 0CheckSliceParametersSlice does not have enough number of inputsSlice ends is less than INT_MAXSlice parameter is not expected. Input index:Expected value:MatchGemmSubgraphStart MatchGemmSubgraphFaild to match gemm pathInput of reshape_before_gemm is not the input of subgraphOutput edge count not expected for nodes in gemm pathGemm does not have 3 inputsGemm bias is not constantGemm bias shape not expectedCheckSliceParameters return falseconcat first input value is not -1Faild to match concat node for Gather pathsconcat_after_gather does not have expected number of inputs or output edgesconcat_after_gather input 2 does not have expected valueFaild to match gemm gather pathOutput edge count not expected for nodes in gemm gather pathunsqueeze_after_gather axes value not expectedgather axis value not expectedgather input 1 value is not expectedPass MatchGemmSubgraphValidateGemmInitializerStart ValidateGemmInitializerGemm bias is not constant initializerGemm bias shape is not expectedGemm weight is not constant initializerGemm weight shape is not expectedPass ValidateGemmInitializerValidateUnidirMaskunidir mask is not constantunidir mask shape not expectedThis optimizer does not support external data for unidirectional mask right nowMask is neither unidirectional nor all onesExpect mask data type is uint8 or floatMatchUnidirMaskSubgraphStart MatchUnidirMaskSubgraphFaild to match the path (Div-->Where-->Add) for unidirectional maskFaild to match path 1 for unidirectional maskOutput edge count not expected for nodes in path 1 of unidirectional maskDiv and Shape1 does not have edgeCheckSliceParameters returns false for last_sliceCheckSliceParameters returns false for mask_sliceValidateUnidirMask returns false for mask_sliceCheckSliceParameters returns false for slice1Faild to match path 2 for unidirectional maskOutput edge count not expected for unsqueeze2 of unidirectional maskFaild to match path 3 for unidirectional maskOutput edge count not expected for unsqueeze3 of unidirectional maskFaild to match path 4 for unidirectional maskDiv and Shape does not have edgeOutput edge count not expected for squeeze_2/slices2/shape2 of unidirectional maskCheckSliceParameters return false for slice2Pass MatchUnidirMaskSubgraphMatchInputMaskSubgraphStart MatchInputMaskSubgraphFailed to find Softmax nodeOutput edge count not expected for SoftmaxFailed to find path for maskOutput edge count not expected for mask nodesSoftmax attribute axis is expected to be 3mask_unsqueeze_1 axes not matched. Expect: 1mask_unsqueeze_2 axes not matched. Expect: 2mask_sub const input not matchedmask_mul const input not matchedPass MatchInputMaskSubgraphStart MatchInputMaskSubgraphDistilBertFailed to find mask pathwhere const not matched.Failed to find shape pathequal const not matched.Failed to find reshape shape path 1Failed to find reshape shape path 2gather indices not matched.Pass MatchInputMaskSubgraphDistilBertMatchPastSubgraphStart MatchPastSubgraphFailed to find path for past_kFailed to find path for present_kFailed to find path for present_v and past_vFailed to match v_concatpast_k_transpose perm attribute not matchedpresent_k_transpose perm attribute not matchedpresent_k_unsqueeze axes value not expectedpresent_v_unsqueeze axes value not expectedpast_v_gather indices != 1past_k_gather indices != 0past_v_gather and past_k_gather does not have same past inputOutput edge count not expected for nodes in past subgraphPass MatchPastSubgraphCheckDistilBertReshapeShapeCheckNodesInPathVStart CheckNodesInPathVOutput edge count not expected for nodes in path vFailed in match Transpose attribute perm. Expected: 0, 2, 1, 3Failed in match v_transpose attribute perm. Expected: 0, 2, 1, 3hidden_size != num_heads * head_sizev_reshape initializer value is not expectedPass CheckNodesInPathVreshape initializer value is not expectedCheckNodesInPathQStart CheckNodesInPathQq_reshape const not matchedqk_div const not matched.q_transpose perm attribute not matchedPass CheckNodesInPathQCheckNodesInPathKStart CheckNodesInPathKk_transpose perm attribute not matchedk_reshape const not matchedPass CheckNodesInPathKFuseGptAttentionStart FuseGptAttentionFaild to find path to qkv_matmulFaild to find path v to SplitCheckNodesInPathV return falseMatchInputMaskSubgraph returns falseMatchUnidirMaskSubgraph returns NULLFailed to find path for qq and v are not from same Split nodeCheckNodesInPathQ returns falseFailed to find path for kk and v are not from same Split nodeCheckNodesInPathK returns falseMatchPastSubgraph returns falseFused an attention node for GPT./Users/runner/work/1/s/onnxruntime/core/optimizer/attention_fusion.ccshape of layer norm bias tensor not expectedTotal fused Attention node count: FuseSubGraphFaild to find path vOutput edge count not expected for Add or MatMul in path vFailed in match v_matmul and v_add input shapeFailed in match input mask subgraphFuseSubGraphQKFused an attention node.FuseSubGraphQKImplq root should be layer normalizationq_matmul and q_add shape not matchedk root is not layer normk_matmul and k_add shape not matchedFailed to load Q, K and V weights, or data type is not float or float16.Failed to load Q, K and V bias tensors, or data type is not float or float16.Failed to convert mask to int32ConvertMaskToInt32Mask shape is unknown or not 2D, or data type unknownMask data type is not int32 or int64 or float32qkv_weightsqkv_biasFuseSubGraphQKDistilBert/Users/runner/work/1/s/onnxruntime/core/optimizer/bias_dropout_fusion.cc/Users/runner/work/1/s/onnxruntime/core/optimizer/bias_gelu_fusion.cc/Users/runner/work/1/s/onnxruntime/core/optimizer/bias_softmax_fusion.ccfused into softmax(input + bias)/Users/runner/work/1/s/onnxruntime/core/optimizer/common_subexpression_elimination.ccvirtual onnxruntime::common::Status onnxruntime::CommonSubexpressionElimination::ApplyImpl(onnxruntime::Graph &, bool &, int, const logging::Logger &) constrepresentative.output_index != kInvalidOutputIndexNot eliminating output of node ] because it's the graph's output./Users/runner/work/1/s/onnxruntime/core/optimizer/constant_folding.ccCould not find a CPU kernel and hence can't constant fold node 'virtual onnxruntime::common::Status onnxruntime::ConstantFolding::ApplyImpl(onnxruntime::Graph &, bool &, int, const logging::Logger &) constfetches.size() == node->OutputDefs().size()Unsupported output type of . Can't constant fold /Users/runner/work/1/s/onnxruntime/core/optimizer/conv_activation_fusion.ccfused Conv with activation auto onnxruntime::(anonymous namespace)::GetClipConstantMinMax(const onnxruntime::Graph &, const onnxruntime::Node &, float &, float &)::(anonymous class)::operator()(const onnxruntime::Node &, size_t, float &) constUnexpected data type for Clip input of /Users/runner/work/1/s/onnxruntime/core/optimizer/conv_add_fusion.ccvirtual onnxruntime::common::Status onnxruntime::ConvAddFusion::Apply(onnxruntime::Graph &, onnxruntime::Node &, onnxruntime::RewriteRule::RewriteRuleEffect &, const logging::Logger &) constadd_B_tensor_protoConvAddFusion_B_ConvAddFusion_Add_B_/Users/runner/work/1/s/onnxruntime/core/optimizer/conv_bn_fusion.ccvirtual onnxruntime::common::Status onnxruntime::ConvBNFusion::Apply(onnxruntime::Graph &, onnxruntime::Node &, onnxruntime::RewriteRule::RewriteRuleEffect &, const logging::Logger &) constbn_scale_tensor_protobn_B_tensor_protobn_mean_tensor_protobn_var_tensor_protoconv_W_tensor_protoconv_B_tensor_protoConvBnFusion_W_ConvBnFusion_BN_B_/Users/runner/work/1/s/onnxruntime/core/optimizer/initializer.honnxruntime::Initializer::Initializer(const onnx::TensorProto &, const onnxruntime::Path &)size_ == sizeInitializerunsupported data type: ReadExternalRawData() failed: ToProtodata type is not supported/Users/runner/work/1/s/onnxruntime/core/optimizer/conv_mul_fusion.ccvirtual onnxruntime::common::Status onnxruntime::ConvMulFusion::Apply(onnxruntime::Graph &, onnxruntime::Node &, onnxruntime::RewriteRule::RewriteRuleEffect &, const logging::Logger &) constmul_B_tensor_protoConvMulFusion_W_ConvMulFusion_Mul_B_/Users/runner/work/1/s/onnxruntime/core/optimizer/dynamic_quantize_matmul_fusion.cc/Users/runner/work/1/s/onnxruntime/core/optimizer/embed_layer_norm_fusion.ccFuseSubGraphDistilBertWord embedding shape not expected.Failed to match position embedding subgraph.Failed to get position embedding weights.Position embedding shape is not expected.Input id is not valid. Gamma should be of shape (hidden_size). Beta should be of shape (hidden_size). MatchPositionEmbeddingSubgraphsFromGatherOutput edge count not expected for nodes in path1.The first input of Range should be a constant with value 0.The third input of Range should be a constant with value 1.Second input of Gather should be a constant with value 1. Failed to match Shape node. The parent of shape nodes are expected to be input_ids.Optional position subgraph nodes number of outputs unexpected.Optional position subgraph nodes Where node is expected to be the parent of Reshape.Failed to match position subgraph.MatchInputToConcatSubgraphFailed to find path 1 of position shape.Output edge count not expected for nodes in path 1 of position shape.Second input of Gather in path 1 of position shape should be a constant with value 0.Failed to find path 2 of position shape.Output edge count not expected for nodes in path 2 of position shape.Gather node in path 2 is not linked to another subgraph.Second input of Gather in path 2 of position shape should be a constant with value 1.The parent of two shape nodes are expected to be input_ids.two paths share the same shapeCheckInputInput shape is unknown or not 2D, or data type unknownInput data type is not int32 or int64_Int32_CastInput is expected to have dim value in all dimensions.Failed to get initializer tensor.Position embedding shape not matched.Position embedding data type shall be float or float16.Segment id is not valid. Input_ids and segment id should have the same shape. /Users/runner/work/1/s/onnxruntime/core/optimizer/fast_gelu_fusion.cc/Users/runner/work/1/s/onnxruntime/core/optimizer/free_dim_override_transformer.cconnxruntime::FreeDimensionOverrideTransformer::FreeDimensionOverrideTransformer(gsl::span<const FreeDimensionOverride>)Invalid free dimension override.Conflicting free dimension overrides.The model has input '' with a fixed dimension size which does not equal the specified override of /Users/runner/work/1/s/onnxruntime/core/optimizer/gelu_approximation.ccTotal Gelu Approximation (FastGelu) node count: /Users/runner/work/1/s/onnxruntime/core/optimizer/gelu_fusion.cc/Users/runner/work/1/s/onnxruntime/core/optimizer/gemm_activation_fusion.ccfused Gemm _transformed/Users/runner/work/1/s/onnxruntime/core/optimizer/graph_transformer.ccApply/Users/runner/work/1/s/onnxruntime/core/optimizer/graph_transformer_mgr.ccApplyTransformersThis transformer is already registered Level_RuleBasedTransformer/Users/runner/work/1/s/onnxruntime/core/optimizer/graph_transformer_utils.ccstd::vector<std::unique_ptr<RewriteRule> > onnxruntime::optimizer_utils::GenerateRewriteRules(onnxruntime::TransformerLevel, const std::unordered_set<std::string> &)Unsupported levelstd::vector<std::unique_ptr<GraphTransformer> > onnxruntime::optimizer_utils::GenerateTransformers(onnxruntime::TransformerLevel, const onnxruntime::SessionOptions &, const onnxruntime::IExecutionProvider &, const std::unordered_set<std::string> &)Unsupported level YieldOp/Users/runner/work/1/s/onnxruntime/core/optimizer/initializer.ccReadExternalRawDataExternal data type must not be UNDEFINED or STRING.model_path must not be empty. Ensure that a path is provided when the model is created or loaded.TensorProto external data size mismatch. Computed size: InsertedCast_/Users/runner/work/1/s/onnxruntime/core/optimizer/insert_cast_transformer.ccvirtual onnxruntime::common::Status onnxruntime::InsertCastTransformer::ApplyImpl(onnxruntime::Graph &, bool &, int, const logging::Logger &) constdtype_attribute->second.has_i()InsertCastTransformer works on the assumption that `dtype` attribute holds an integer./Users/runner/work/1/s/onnxruntime/core/optimizer/layer_norm_fusion.cc/Users/runner/work/1/s/onnxruntime/core/optimizer/matmul_add_fusion.ccfused Matmul and Add /Users/runner/work/1/s/onnxruntime/core/optimizer/matmul_integer_to_float.cc/Users/runner/work/1/s/onnxruntime/core/optimizer/matmul_scale_fusion.cc_FusedMatMulAndScalestd::vector<ScaleMergeInfo> onnxruntime::(anonymous namespace)::GetInputNodeMerges(onnxruntime::Graph &, onnxruntime::Node &, const std::unordered_set<std::string> &)input_node.InputDefs().size() == 2 && scale_and_index.value().second < 2optional<std::pair<float, int> > onnxruntime::(anonymous namespace)::GetScaleFromNode(const onnxruntime::Graph &, const onnxruntime::Node &, const std::unordered_set<std::string> &)div_inputs.size() == 2mul_inputs.size() == 2optional<float> onnxruntime::(anonymous namespace)::GetScalarConstantInitializer(const onnxruntime::Graph &, const onnxruntime::NodeArg &)Constant initializer NodeArg shape should not be null. NodeArg: GetScalarConstantInitializerstd::vector<ScaleMergeInfo> onnxruntime::(anonymous namespace)::GetOutputNodeMerges(onnxruntime::Graph &, onnxruntime::Node &, const std::unordered_set<std::string> &)output_node.OutputDefs().size() == 1/Users/runner/work/1/s/onnxruntime/core/optimizer/matmul_transpose_fusion.ccbool onnxruntime::GetTransposePerms(const onnxruntime::Node &, std::vector<int64_t> &)transpose_node.InputDefs().size() == 1onnxruntime::Node *onnxruntime::ReorderCastAndTranspose(onnxruntime::Graph &, onnxruntime::Node *, std::unordered_map<NodeArg *, size_t> &, std::deque<onnxruntime::NodeIndex> &)cast != nullptrCreated a new Transpose node to interchange Cast and Transpose nodessize_t onnxruntime::UpdateConsumerCount(onnxruntime::Graph &, onnxruntime::NodeArg *, std::unordered_map<NodeArg *, size_t> &)!node_consumers.empty()_nchwc_bn_nchwc/Users/runner/work/1/s/onnxruntime/core/optimizer/nchwc_transformer.cc_nhwc/Users/runner/work/1/s/onnxruntime/core/optimizer/nhwc_transformer.cc/Users/runner/work/1/s/onnxruntime/core/optimizer/optimizer_execution_frame.cconnxruntime::OptimizerExecutionFrame::Info::Info(const std::vector<const Node *> &, const onnxruntime::InitializedTensorSet &, const onnxruntime::Path &, const onnxruntime::IExecutionProvider &)allocator_ptr_InfoQLinear855dd0fa-cd7b-4b10-ae5a-df64cabfe1f835b188f7-c464-43e3-8692-97ac832bb14a/Users/runner/work/1/s/onnxruntime/core/optimizer/qdq_transformer/qdq_propagation.ccvoid onnxruntime::SwapAdjacentNodes(onnxruntime::Graph &, onnxruntime::Node &, onnxruntime::Node &)optimizer_utils::CheckOutputEdges(graph, up_node, 1)up_node should have only one Edge that points to down_node and its output is not graph outputedge_it->GetDstArgIndex() == 0 && edge_it->GetSrcArgIndex() == 0 && edge_it->GetNode().Index() == down_node.Index()up_node should be parent of down_node and NodeArg slots of the edge between up_node and down_node should be (0, 0)./Users/runner/work/1/s/onnxruntime/core/optimizer/qdq_transformer/qdq_s8_to_u8.cc/Users/runner/work/1/s/onnxruntime/core/optimizer/qdq_transformer/qdq_transformer.cc/Users/runner/work/1/s/onnxruntime/core/optimizer/relu_clip_fusion.ccvirtual onnxruntime::common::Status onnxruntime::FuseReluClip::Apply(onnxruntime::Graph &, onnxruntime::Node &, onnxruntime::RewriteRule::RewriteRuleEffect &, const logging::Logger &) constUnexpected data type for Clip 'min' input of FuseReluClip__min_zero_constantonnxruntime::Initializer::Initializer(onnx::TensorProto_DataType, const std::string &, const std::vector<int64_t> &)data type is not supported./Users/runner/work/1/s/onnxruntime/core/optimizer/reshape_fusion.ccFused reshape node: Total fused reshape node count: Fuse_SubgraphCannot replace concat node with initializer:/Users/runner/work/1/s/onnxruntime/core/optimizer/rule_based_graph_transformer.ccApplyRulesOnNode/Users/runner/work/1/s/onnxruntime/core/optimizer/skip_layer_norm_fusion.cc/Users/runner/work/1/s/onnxruntime/core/optimizer/transformer_memcpy.ccApplyImplvoid onnxruntime::TransformerMemcpyImpl::ProcessDefs(onnxruntime::Node &, const onnxruntime::KernelRegistryManager &, onnxruntime::InitializedTensorSet &)Execution type '' doesn't support memcpy bool onnxruntime::TransformerMemcpyImpl::ProcessInitializers(const onnxruntime::KernelRegistryManager &, const onnxruntime::InitializedTensorSet &)/Users/runner/work/1/s/include/onnxruntime/core/optimizer/graph_transformer.hRecurseauto onnxruntime::TransformerMemcpyImpl::ProcessInitializers(const onnxruntime::KernelRegistryManager &, const onnxruntime::InitializedTensorSet &)::(anonymous class)::operator()(const onnxruntime::NodeArg &, size_t) constdup_replacements.find(&arg) == dup_replacements.end()UnsqueezeElimination_/Users/runner/work/1/s/onnxruntime/core/optimizer/unsqueeze_elimination.ccUnsqueezeElimination cannot remove node MIGraphXExecutionProviderROCMExecutionProviderOpenVINOExecutionProviderDnnlExecutionProviderNupharExecutionProviderVitisAIExecutionProviderNnapiExecutionProviderArmNNExecutionProviderACLExecutionProviderRknpuExecutionProviderCeluEluHardSigmoidLeakyReluSoftplusReluSigmoidSoftsignTanhThresholdedReluSeluParametricSoftplusScaledTanhunknown kernel typeonnxruntime::ElementWiseKernel<onnxruntime::functors::Elu<float> >::ElementWiseKernel(const onnxruntime::OpKernelInfo &) [F = onnxruntime::functors::Elu<float>]virtual onnxruntime::common::Status onnxruntime::ElementWiseKernel<onnxruntime::functors::Elu<float> >::Compute(onnxruntime::OpKernelContext *) const [F = onnxruntime::functors::Elu<float>]onnxruntime::ElementWiseKernel<onnxruntime::functors::HardSigmoid<float> >::ElementWiseKernel(const onnxruntime::OpKernelInfo &) [F = onnxruntime::functors::HardSigmoid<float>]virtual onnxruntime::common::Status onnxruntime::ElementWiseKernel<onnxruntime::functors::HardSigmoid<float> >::Compute(onnxruntime::OpKernelContext *) const [F = onnxruntime::functors::HardSigmoid<float>]onnxruntime::ElementWiseKernel<onnxruntime::functors::LeakyRelu<float> >::ElementWiseKernel(const onnxruntime::OpKernelInfo &) [F = onnxruntime::functors::LeakyRelu<float>]virtual onnxruntime::common::Status onnxruntime::ElementWiseKernel<onnxruntime::functors::LeakyRelu<float> >::Compute(onnxruntime::OpKernelContext *) const [F = onnxruntime::functors::LeakyRelu<float>]virtual onnxruntime::common::Status onnxruntime::ElementWiseKernel<onnxruntime::functors::Relu<float> >::Compute(onnxruntime::OpKernelContext *) const [F = onnxruntime::functors::Relu<float>]virtual onnxruntime::common::Status onnxruntime::ElementWiseKernel<onnxruntime::functors::Relu<double> >::Compute(onnxruntime::OpKernelContext *) const [F = onnxruntime::functors::Relu<double>]virtual onnxruntime::common::Status onnxruntime::ElementWiseKernel<onnxruntime::functors::Relu<signed char> >::Compute(onnxruntime::OpKernelContext *) const [F = onnxruntime::functors::Relu<signed char>]virtual onnxruntime::common::Status onnxruntime::ElementWiseKernel<onnxruntime::functors::Relu<int> >::Compute(onnxruntime::OpKernelContext *) const [F = onnxruntime::functors::Relu<int>]onnxruntime::ElementWiseKernel<onnxruntime::functors::Selu<float> >::ElementWiseKernel(const onnxruntime::OpKernelInfo &) [F = onnxruntime::functors::Selu<float>]virtual onnxruntime::common::Status onnxruntime::ElementWiseKernel<onnxruntime::functors::Selu<float> >::Compute(onnxruntime::OpKernelContext *) const [F = onnxruntime::functors::Selu<float>]virtual onnxruntime::common::Status onnxruntime::ElementWiseKernel<onnxruntime::functors::Sigmoid<float> >::Compute(onnxruntime::OpKernelContext *) const [F = onnxruntime::functors::Sigmoid<float>]virtual onnxruntime::common::Status onnxruntime::ElementWiseKernel<onnxruntime::functors::Sigmoid<double> >::Compute(onnxruntime::OpKernelContext *) const [F = onnxruntime::functors::Sigmoid<double>]virtual onnxruntime::common::Status onnxruntime::ElementWiseKernel<onnxruntime::functors::Softplus<float> >::Compute(onnxruntime::OpKernelContext *) const [F = onnxruntime::functors::Softplus<float>]virtual onnxruntime::common::Status onnxruntime::ElementWiseKernel<onnxruntime::functors::Softsign<float> >::Compute(onnxruntime::OpKernelContext *) const [F = onnxruntime::functors::Softsign<float>]virtual onnxruntime::common::Status onnxruntime::ElementWiseKernel<onnxruntime::functors::Tanh<float> >::Compute(onnxruntime::OpKernelContext *) const [F = onnxruntime::functors::Tanh<float>]virtual onnxruntime::common::Status onnxruntime::ElementWiseKernel<onnxruntime::functors::Tanh<double> >::Compute(onnxruntime::OpKernelContext *) const [F = onnxruntime::functors::Tanh<double>]onnxruntime::ElementWiseKernel<onnxruntime::functors::Celu<float> >::ElementWiseKernel(const onnxruntime::OpKernelInfo &) [F = onnxruntime::functors::Celu<float>]virtual onnxruntime::common::Status onnxruntime::ElementWiseKernel<onnxruntime::functors::Celu<float> >::Compute(onnxruntime::OpKernelContext *) const [F = onnxruntime::functors::Celu<float>]onnxruntime::ElementWiseKernel<onnxruntime::functors::ThresholdedRelu<float> >::ElementWiseKernel(const onnxruntime::OpKernelInfo &) [F = onnxruntime::functors::ThresholdedRelu<float>]virtual onnxruntime::common::Status onnxruntime::ElementWiseKernel<onnxruntime::functors::ThresholdedRelu<float> >::Compute(onnxruntime::OpKernelContext *) const [F = onnxruntime::functors::ThresholdedRelu<float>]alphaNo attribute with name:''is defined.Attribute name and type don't match for '/Users/runner/work/1/s/onnxruntime/core/providers/cpu/activation/activations.hInitgamma/Users/runner/work/1/s/onnxruntime/contrib_ops/cpu/activations.hBVIf/Users/runner/work/1/s/onnxruntime/core/providers/cpu/controlflow/if.cconnxruntime::If::Info::Info(const onnxruntime::Node &, const onnxruntime::GraphViewer &)num_subgraph_outputs == static_cast<size_t>(num_outputs)'If' node has outputs which doesn't match the subgraph's outputs.then_branchvoid onnxruntime::If::Init(const onnxruntime::OpKernelInfo &)info.GetAttr<ONNX_NAMESPACE::GraphProto>("then_branch", &proto).IsOK()else_branchinfo.GetAttr<ONNX_NAMESPACE::GraphProto>("else_branch", &proto).IsOK()virtual common::Status onnxruntime::If::SetupSubgraphExecutionInfo(const onnxruntime::SessionState &, const std::string &, const onnxruntime::SessionState &)info == nullptrSetupSubgraphExecutionInfo should only be called once for each subgraph.SetupSubgraphExecutionInfovirtual onnxruntime::common::Status onnxruntime::If::Compute(onnxruntime::OpKernelContext *) constthen_feeds_fetches_manager_ && else_feeds_fetches_manager_CreateFeedsFetchesManager must be called prior to execution of graph.session_stateSubgraph SessionState was not found for '' attribute.ComputeFailed to create output tensor for Executeonnxruntime::TensorSeq *OrtValue::GetMutable()Failed to create output tensor for If output ILoop/Users/runner/work/1/s/onnxruntime/core/providers/cpu/controlflow/loop.cconnxruntime::Loop::Info::Info(const onnxruntime::Node &, const onnxruntime::GraphViewer &)static_cast<size_t>(num_subgraph_inputs) == subgraph_inputs.size()Graph in 'body' attribute of Loop should have inputs. Found:num_subgraph_outputs - 1 == num_outputs'Loop' node has outputs so the subgraph requires but has void onnxruntime::Loop::Init(const onnxruntime::OpKernelInfo &)info.GetAttr<ONNX_NAMESPACE::GraphProto>("body", &proto).IsOK()virtual common::Status onnxruntime::Loop::SetupSubgraphExecutionInfo(const onnxruntime::SessionState &, const std::string &, const onnxruntime::SessionState &)info_ == nullptrvirtual onnxruntime::common::Status onnxruntime::Loop::Compute(onnxruntime::OpKernelContext *) constfeeds_fetches_manager_'Loop' input 'M' should be a scalar tensor. Got shape of 'Loop' input 'cond' should be a scalar tensor. Got shape of Loop subgraph input 0 has unknown shape: Loop subgraph input 1 has unknown shape: void onnxruntime::LoopImpl::SaveOutputsAndUpdateFeeds(const std::vector<OrtValue> &, std::vector<OrtValue> &)last_outputs[j + 1].IsTensor()ConcatenateLoopOutputLoop had zero iterations and the shape of subgraph output was not found. Defaulting to a rank 1 shape of {0}.Inconsistent shape in loop output for output. Expected: Got:auto onnxruntime::LoopImpl::Execute(const onnxruntime::FeedsFetchesManager &)::(anonymous class)::operator()(const OrtValue &, int) const/Users/runner/work/1/s/onnxruntime/core/providers/cpu/controlflow/scan_8.ccvoid onnxruntime::Scan<8>::Init(const onnxruntime::OpKernelInfo &) [OpSet = 8]directionsvirtual onnxruntime::common::Status onnxruntime::Scan<8>::SetupSubgraphExecutionInfo(const onnxruntime::SessionState &, const std::string &, const onnxruntime::SessionState &) [OpSet = 8]virtual onnxruntime::common::Status onnxruntime::Scan<8>::Compute(onnxruntime::OpKernelContext *) const [OpSet = 8]Scan inputs have inconsistent batch size. Previous value was but has batch size of sequence_lens length of did not match batch size of Invalid entries in sequence_lens. Max sequence length was onnxruntime::common::Status onnxruntime::Scan8Impl::CreateLoopStateVariables(std::vector<std::vector<LoopStateVariable> > &)p_mlvalueScan<8> spec does not support transpose of output. This should never be called./Users/runner/work/1/s/onnxruntime/core/framework/ort_value_tensor_slicer.htypename std::enable_if<!std::is_const<reference>::value, reference>::type onnxruntime::OrtValueTensorSlicer<const OrtValue>::Iterator::operator*() [T = const OrtValue]position_ >= 0 && position_ < sequence_length_/Users/runner/work/1/s/onnxruntime/core/providers/cpu/controlflow/scan_9.ccvoid onnxruntime::Scan<9>::Init(const onnxruntime::OpKernelInfo &) [OpSet = 9]num_scan_inputsinfo.GetAttr<int64_t>("num_scan_inputs", &num_scan_inputs_).IsOK()scan_input_directionsscan_output_directionsscan_input_axesgsl::narrow_cast<int64_t>(input_axes_.size()) == num_scan_inputs_Number of entries in 'scan_input_axes' was but expected scan_output_axesgsl::narrow_cast<int64_t>(output_axes_.size()) == num_scan_outputsNumber of entries in 'scan_output_axes' was virtual onnxruntime::common::Status onnxruntime::Scan<9>::SetupSubgraphExecutionInfo(const onnxruntime::SessionState &, const std::string &, const onnxruntime::SessionState &) [OpSet = 9]virtual onnxruntime::common::Status onnxruntime::Scan<9>::Compute(onnxruntime::OpKernelContext *) const [OpSet = 9]feeds_fetches_manager_ && info_Invalid scan input: Expected dimensions or more but input had shape of Scan inputs have inconsistent sequence lengths. Previous value was but input '' dimension has length of Invalid value in scan_input_axes for input of . Input tensor rank was ValidateInputSetupInputsSubgraph in 'body' produces outputs but Scan expects AllocateOutputTensorsCreateLoopStateVariablesonnxruntime::common::Status onnxruntime::ScanImpl::CreateLoopStateVariables(std::vector<LoopStateVariable> &)output_mlvalueOutput OrtValue has not been created for loop state variable output Invalid value in scan_output_axes for output . Output tensor rank was onnxruntime::common::Status onnxruntime::ScanImpl::TransposeOutput()TransposeOutputScanint64_t onnxruntime::HandleNegativeAxis(int64_t, int64_t)axis >= -tensor_rank && axis <= tensor_rank - 1axis is not in valid range [-/Users/runner/work/1/s/onnxruntime/core/providers/cpu/controlflow/scan_utils.hconst OrtValue &onnxruntime::scan::detail::OutputIterator::GetOutput() constfinal_output_mlvalue_/Users/runner/work/1/s/onnxruntime/core/providers/cpu/controlflow/scan_utils.cconnxruntime::scan::detail::Info::Info(const onnxruntime::Node &, const onnxruntime::GraphViewer &, int, bool)num_variadic_inputs == num_subgraph_inputsThe subgraph in 'body' requires inputs but Scan was only given void onnxruntime::scan::detail::ReadDirections(const onnxruntime::OpKernelInfo &, const std::string &, std::vector<int64_t> &, size_t)directions.size() == num_entriesNumber of entries in '' was validInvalid values in ''. 0 == forward. 1 == reverse.Subgraph must have the shape set for all outputs but did not.CreateFeedsFetchesManagerIterateSequencevoid onnxruntime::scan::detail::LoopStateVariable::Next()iteration_num_ < sequence_len_Misuse of LoopStateVariable. Attempt to move beyond end of sequenceFailed to create output tensor for output #AllocateFinalBufferonnxruntime::common::Status onnxruntime::scan::detail::OutputIterator::AllocateFinalOutput(const onnxruntime::TensorShape &)!is_concrete_shape_AllocateFinalOutputOrtValue &onnxruntime::scan::detail::OutputIterator::operator*()cur_iteration_ < num_iterations_is_concrete_shape_Expected AllocateFinalOutput to have been called to before we read the OrtValue from the iterator.onnxruntime::scan::detail::OutputIterator &onnxruntime::scan::detail::OutputIterator::operator++()Expected AllocateFinalOutput to have been called to before we increment the iteratorMismatch between expected shape and shape from first output is not compatible with /Users/runner/work/1/s/onnxruntime/core/providers/cpu/cpu_execution_provider.ccRegisterOnnxOperatorKernelsRegisterOnnxMLOperatorKernelsRegisterCPUKernelsGetKernelRegistryvirtual std::shared_ptr<KernelRegistry> onnxruntime::CPUExecutionProvider::GetKernelRegistry() constCpuConstantOfShape/Users/runner/work/1/s/onnxruntime/core/providers/cpu/generator/constant_of_shape_base.honnxruntime::ConstantOfShapeBase<onnxruntime::TypeList<long long, onnxruntime::MLFloat16, float, double, signed char, short, int, unsigned char, unsigned short, unsigned int, unsigned long long, bool> >::ConstantOfShapeBase(const onnxruntime::OpKernelInfo &) [EnabledOutputTypeList = onnxruntime::TypeList<long long, onnxruntime::MLFloat16, float, double, signed char, short, int, unsigned char, unsigned short, unsigned int, unsigned long long, bool>]t_proto_p->dims_size() == 1t_proto_p->dims()[0] == 1void onnxruntime::ConstantOfShapeBase<onnxruntime::TypeList<long long, onnxruntime::MLFloat16, float, double, signed char, short, int, unsigned char, unsigned short, unsigned int, unsigned long long, bool> >::SetValueFromTensorProto(const onnx::TensorProto &) [EnabledOutputTypeList = onnxruntime::TypeList<long long, onnxruntime::MLFloat16, float, double, signed char, short, int, unsigned char, unsigned short, unsigned int, unsigned long long, bool>]utils::HasDataType(t_proto)ONNX_NAMESPACE::TensorProto::DataType_IsValid(t_proto.data_type())!utils::HasExternalData(t_proto)Tensor proto with external data for value attribute is not supported.SetValueFromTensorProtoUnsupported value attribute datatype: /Users/runner/work/1/s/onnxruntime/core/providers/cpu/generator/constant_of_shape.ccUnsupported output datatype with size: PrepareComputeMust have a valid input shape.RandomNormalRandomUniformRandomNormalLikeRandomUniformLikeMultinomial/Users/runner/work/1/s/onnxruntime/core/providers/cpu/generator/random.ccCould not infer data type from input tensor with data type Empty dimensions for input tensorbatch_size is < 1num_classes is < 1num_samples is < 1Invalid data type of /Users/runner/work/1/s/onnxruntime/core/providers/cpu/generator/random.honnxruntime::RandomNormal::RandomNormal(const onnxruntime::OpKernelInfo &)info.GetAttr<float>("mean", &mean_).IsOK()scaleinfo.GetAttr<float>("scale", &scale_).IsOK()info.GetAttr<int64_t>("dtype", &dtype).IsOK()ONNX_NAMESPACE::TensorProto::DataType_IsValid(dtype_) && dtype_ != ONNX_NAMESPACE::TensorProto::UNDEFINEDInvalid dtype of info.GetAttrs<int64_t>("shape", shape).IsOK()onnxruntime::RandomUniform::RandomUniform(const onnxruntime::OpKernelInfo &)info.GetAttr<float>("high", &high_).IsOK()lowinfo.GetAttr<float>("low", &low_).IsOK()onnxruntime::RandomNormalLike::RandomNormalLike(const onnxruntime::OpKernelInfo &)onnxruntime::RandomUniformLike::RandomUniformLike(const onnxruntime::OpKernelInfo &)sample_sizeonnxruntime::Multinomial::Multinomial(const onnxruntime::OpKernelInfo &)info.GetAttr<int64_t>("sample_size", &num_samples_).IsOK()ONNX_NAMESPACE::TensorProto::DataType_IsValid(output_dtype_) && output_dtype_ != ONNX_NAMESPACE::TensorProto::UNDEFINEDOutput type not supported in this build: MultinomialComputeRangestart in Range operator should be scalar like tensor, yet got shape:limit in Range operator should be scalar like tensor, yet got shape:delta in Range operator should be scalar like tensor, yet got shape:delta in Range operator can not be zero!Clipminmax/Users/runner/work/1/s/onnxruntime/core/providers/cpu/math/clip.honnxruntime::clip_internal::Clip_6Base<float>::Clip_6Base(const onnxruntime::OpKernelInfo &) [T = float]min_ <= max_/Users/runner/work/1/s/onnxruntime/core/providers/cpu/math/clip.ccvoid onnxruntime::Clip::ComputeImpl<float>::operator()(const onnxruntime::Tensor *, const onnxruntime::Tensor *, const onnxruntime::Tensor *, onnxruntime::Tensor *) const [T = float]min->Shape().IsScalar()max->Shape().IsScalar()void onnxruntime::Clip::ComputeImpl<double>::operator()(const onnxruntime::Tensor *, const onnxruntime::Tensor *, const onnxruntime::Tensor *, onnxruntime::Tensor *) const [T = double]void onnxruntime::Clip::ComputeImpl<signed char>::operator()(const onnxruntime::Tensor *, const onnxruntime::Tensor *, const onnxruntime::Tensor *, onnxruntime::Tensor *) const [T = signed char]void onnxruntime::Clip::ComputeImpl<unsigned char>::operator()(const onnxruntime::Tensor *, const onnxruntime::Tensor *, const onnxruntime::Tensor *, onnxruntime::Tensor *) const [T = unsigned char]void onnxruntime::Clip::ComputeImpl<long long>::operator()(const onnxruntime::Tensor *, const onnxruntime::Tensor *, const onnxruntime::Tensor *, onnxruntime::Tensor *) const [T = long long]void onnxruntime::Clip::ComputeImpl<unsigned long long>::operator()(const onnxruntime::Tensor *, const onnxruntime::Tensor *, const onnxruntime::Tensor *, onnxruntime::Tensor *) const [T = unsigned long long]CumSumexclusive/Users/runner/work/1/s/onnxruntime/core/providers/cpu/math/cumsum.ccvirtual onnxruntime::common::Status onnxruntime::CumSum<float>::Compute(onnxruntime::OpKernelContext *) const [T = float]void onnxruntime::WritableSliceIterator<float>::Init(const std::vector<int64_t> &, gsl::span<const int64_t>, gsl::span<const int64_t>) [T = float]dims.size() == starts.size()dims.size()=starts.size()=dims.size() == extents_.size()extents.size()=dims.size() == steps.size()steps.size()=virtual onnxruntime::common::Status onnxruntime::CumSum<double>::Compute(onnxruntime::OpKernelContext *) const [T = double]void onnxruntime::WritableSliceIterator<double>::Init(const std::vector<int64_t> &, gsl::span<const int64_t>, gsl::span<const int64_t>) [T = double]virtual onnxruntime::common::Status onnxruntime::CumSum<int>::Compute(onnxruntime::OpKernelContext *) const [T = int]void onnxruntime::WritableSliceIterator<int>::Init(const std::vector<int64_t> &, gsl::span<const int64_t>, gsl::span<const int64_t>) [T = int]virtual onnxruntime::common::Status onnxruntime::CumSum<long long>::Compute(onnxruntime::OpKernelContext *) const [T = long long]void onnxruntime::WritableSliceIterator<long long>::Init(const std::vector<int64_t> &, gsl::span<const int64_t>, gsl::span<const int64_t>) [T = long long]Det/Users/runner/work/1/s/onnxruntime/core/providers/cpu/math/det.ccvirtual onnxruntime::common::Status onnxruntime::Det<float>::Compute(onnxruntime::OpKernelContext *) const [T = float]X != nullptrInput tensor should have a rank of at least 2Matrix dimensions are not equal. Square matrix is expectedEinsumThere was a problem acquiring temporary memory allocator in Einsum op/Users/runner/work/1/s/onnxruntime/core/providers/cpu/math/einsum.ccDeviceComputeEinsum op: An implementation for the input type is not supported yet/Users/runner/work/1/s/onnxruntime/core/providers/cpu/math/einsum.honnxruntime::Einsum::Einsum(const onnxruntime::OpKernelInfo &)info.GetAttr<std::string>("equation", &equation_).IsOK()->/Users/runner/work/1/s/onnxruntime/core/providers/cpu/math/einsum_utils/einsum_auxiliary_ops.ccstd::unique_ptr<Tensor> onnxruntime::EinsumOp::MatMul(const onnxruntime::Tensor &, const std::vector<int64_t> &, const onnxruntime::Tensor &, const std::vector<int64_t> &, onnxruntime::AllocatorPtr, concurrency::ThreadPool *, void *, const DeviceHelpers::MatMul<T> &) [T = float]input_1.DataType() == input_2.DataType()input_shape_1_override.size() == 3 && input_shape_2_override.size() == 3input_shape_1_override[0] == input_shape_2_override[0]input_shape_1_override[2] == input_shape_2_override[1]Einsum op: Exception during MatMul operation: std::unique_ptr<Tensor> onnxruntime::EinsumOp::MatMul(const onnxruntime::Tensor &, const std::vector<int64_t> &, const onnxruntime::Tensor &, const std::vector<int64_t> &, onnxruntime::AllocatorPtr, concurrency::ThreadPool *, void *, const DeviceHelpers::MatMul<T> &) [T = int]std::unique_ptr<Tensor> onnxruntime::EinsumOp::MatMul(const onnxruntime::Tensor &, const std::vector<int64_t> &, const onnxruntime::Tensor &, const std::vector<int64_t> &, onnxruntime::AllocatorPtr, concurrency::ThreadPool *, void *, const DeviceHelpers::MatMul<T> &) [T = double]std::unique_ptr<Tensor> onnxruntime::EinsumOp::MatMul(const onnxruntime::Tensor &, const std::vector<int64_t> &, const onnxruntime::Tensor &, const std::vector<int64_t> &, onnxruntime::AllocatorPtr, concurrency::ThreadPool *, void *, const DeviceHelpers::MatMul<T> &) [T = long long]onnxruntime::common::Status onnxruntime::EinsumOp::DeviceHelpers::CpuDeviceHelpers::DataCopy(const onnxruntime::Tensor &, onnxruntime::Tensor &, void *)output.SizeInBytes() == input.SizeInBytes()Einsum op: The candidate output does not match the actual output's shapestd::unique_ptr<Tensor> onnxruntime::EinsumOp::DeviceHelpers::CpuDeviceHelpers::Diagonal(const onnxruntime::Tensor &, int64_t, int64_t, onnxruntime::AllocatorPtr, void *)rank >= 2 && dim_1 != dim_2 && input_dims[dim_1] == input_dims[dim_2]Cannot parse the diagonal elements along dims for input shape bool onnxruntime::EinsumOp::IsTransposeRequired(size_t, const std::vector<size_t> &)input_rank == permutation.size()std::unique_ptr<Tensor> onnxruntime::EinsumOp::Transpose(const onnxruntime::Tensor &, const std::vector<int64_t> &, const std::vector<size_t> &, onnxruntime::AllocatorPtr, void *, const DeviceHelpers::Transpose &)Length of permutation must match the rank of the input to be permutatedEinsum op: Transpose failed: std::unique_ptr<Tensor> onnxruntime::EinsumOp::DeviceHelpers::CpuDeviceHelpers::DiagonalInnermostDims(const onnxruntime::Tensor &, bool, onnxruntime::AllocatorPtr)input_dims[rank - 2] == input_dims[rank - 1]The innermost dims should have the same dim value to parse the diagonal elementsEinsum op: Unsupported data type for Diagonal /Users/runner/work/1/s/onnxruntime/core/providers/cpu/math/einsum_utils/einsum_compute_preprocessor.ccNumber of subscripts in the input equation does not match number of input tensorsFound a '.' not part of an ellipsis in input: Einsum subscripts string contains too many subscript labels when compared to the rank of the inputEllipsis must indicate a fixed number of dimensions across all inputsFound '.' not part of an ellipsis in input: The only subscript labels allowed are lower-cased letters (a-z) and upper-cased letters (A-Z)Einsum operands could not be broadcast together. Please check input shapes/equation provided.Input shape of operand is incompatible in the dimension . The shape is: Another operand has a dim value of in the same dimensionEinsum subscripts string contains too many subscript labels when compared to the rank of the input Einsum subscripts does not contain enough subscript labels and there is no ellipsis for input onnxruntime::common::Status onnxruntime::EinsumComputePreprocessor::PostProcessBroadcastedDims()num_broadcasted_indices < num_of_ellipsis_dims_dim_iter == rank...Inputs have ellipses in them but the provided output subscript does not contain an ellipsisFound a '.' not part of an ellipsis in the output subscript providedFound '.' not part of an ellipsis in the output subscript providedRank of the input must match number of subscript labels corresponding to the input/Users/runner/work/1/s/onnxruntime/core/providers/cpu/math/einsum_utils/einsum_typed_compute_processor.ccstd::unique_ptr<Tensor> onnxruntime::EinsumTypedComputeProcessor<float>::PairwiseOperandProcess(const onnxruntime::Tensor &, const onnxruntime::TensorShape &, const onnxruntime::Tensor &, const onnxruntime::TensorShape &, const std::vector<int64_t> &, bool) [T = float]left.Shape().Size() == left_shape_override.Size()The override dims are not compatible with given tensor's shape. Left shape: Left shape override: right.Shape().Size() == right_shape_override.Size()Right shape: Right shape override: left_rank == right_rankRanks of pair-wise operands must be equal. Right shape: left_dim == right_dimEinsum op: Input dimensions must be equal along an axis to be reduced across all inputsvoid onnxruntime::EinsumTypedComputeProcessor<float>::FinalizeOutput(const onnxruntime::Tensor &, const std::vector<int64_t> &) [T = float]candidate_output.Shape().Size() == output_shape.Size()Einsum op: The candidate output cannot be reshaped into the op's outputcandidate_output_dims[iter] == 1Not all dimensions to be reduced have been reduced in the candidate output. Candidate output dims: Einsum op: Could not copy the intermediate output's buffer into the op's output buffer. Error: std::unique_ptr<Tensor> onnxruntime::EinsumTypedComputeProcessor<int>::PairwiseOperandProcess(const onnxruntime::Tensor &, const onnxruntime::TensorShape &, const onnxruntime::Tensor &, const onnxruntime::TensorShape &, const std::vector<int64_t> &, bool) [T = int]void onnxruntime::EinsumTypedComputeProcessor<int>::FinalizeOutput(const onnxruntime::Tensor &, const std::vector<int64_t> &) [T = int]std::unique_ptr<Tensor> onnxruntime::EinsumTypedComputeProcessor<double>::PairwiseOperandProcess(const onnxruntime::Tensor &, const onnxruntime::TensorShape &, const onnxruntime::Tensor &, const onnxruntime::TensorShape &, const std::vector<int64_t> &, bool) [T = double]void onnxruntime::EinsumTypedComputeProcessor<double>::FinalizeOutput(const onnxruntime::Tensor &, const std::vector<int64_t> &) [T = double]std::unique_ptr<Tensor> onnxruntime::EinsumTypedComputeProcessor<long long>::PairwiseOperandProcess(const onnxruntime::Tensor &, const onnxruntime::TensorShape &, const onnxruntime::Tensor &, const onnxruntime::TensorShape &, const std::vector<int64_t> &, bool) [T = long long]void onnxruntime::EinsumTypedComputeProcessor<long long>::FinalizeOutput(const onnxruntime::Tensor &, const std::vector<int64_t> &) [T = long long]SubMulDivAbsNegFloorCeilReciprocalSqrtPowT1ExpLogSumMaxMinLessGreaterEqualLessOrEqualGreaterOrEqualMeanBitShiftErfNotAndOrXorUnsupported X type: /Users/runner/work/1/s/onnxruntime/core/providers/cpu/math/element_wise_ops.ccvirtual onnxruntime::common::Status onnxruntime::Min_6<float>::Compute(onnxruntime::OpKernelContext *) const [T = float]inputCount >= 1Must have 1 or more inputsdata_n.Shape() == shapevirtual onnxruntime::common::Status onnxruntime::Max_6<float>::Compute(onnxruntime::OpKernelContext *) const [T = float]virtual onnxruntime::common::Status onnxruntime::Mean_6<float>::Compute(onnxruntime::OpKernelContext *) const [T = float]data_1.Shape() == shapeSinCosTanAsinAcosAtanSinhCoshAsinhAcoshAtanhPReluExpandMod/Users/runner/work/1/s/onnxruntime/core/providers/cpu/element_wise_ranged_transform.hElementWiseKernelonnxruntime::ElementWiseKernel<onnxruntime::functors::Abs<float> >::ElementWiseKernel(const onnxruntime::OpKernelInfo &) [F = onnxruntime::functors::Abs<float>]virtual onnxruntime::common::Status onnxruntime::ElementWiseKernel<onnxruntime::functors::Abs<float> >::Compute(onnxruntime::OpKernelContext *) const [F = onnxruntime::functors::Abs<float>]input_size < std::numeric_limits<std::ptrdiff_t>::max()onnxruntime::ElementWiseKernel<onnxruntime::functors::Abs<double> >::ElementWiseKernel(const onnxruntime::OpKernelInfo &) [F = onnxruntime::functors::Abs<double>]virtual onnxruntime::common::Status onnxruntime::ElementWiseKernel<onnxruntime::functors::Abs<double> >::Compute(onnxruntime::OpKernelContext *) const [F = onnxruntime::functors::Abs<double>]onnxruntime::ElementWiseKernel<onnxruntime::functors::Abs<signed char> >::ElementWiseKernel(const onnxruntime::OpKernelInfo &) [F = onnxruntime::functors::Abs<signed char>]virtual onnxruntime::common::Status onnxruntime::ElementWiseKernel<onnxruntime::functors::Abs<signed char> >::Compute(onnxruntime::OpKernelContext *) const [F = onnxruntime::functors::Abs<signed char>]onnxruntime::ElementWiseKernel<onnxruntime::functors::Abs<short> >::ElementWiseKernel(const onnxruntime::OpKernelInfo &) [F = onnxruntime::functors::Abs<short>]virtual onnxruntime::common::Status onnxruntime::ElementWiseKernel<onnxruntime::functors::Abs<short> >::Compute(onnxruntime::OpKernelContext *) const [F = onnxruntime::functors::Abs<short>]onnxruntime::ElementWiseKernel<onnxruntime::functors::Abs<int> >::ElementWiseKernel(const onnxruntime::OpKernelInfo &) [F = onnxruntime::functors::Abs<int>]virtual onnxruntime::common::Status onnxruntime::ElementWiseKernel<onnxruntime::functors::Abs<int> >::Compute(onnxruntime::OpKernelContext *) const [F = onnxruntime::functors::Abs<int>]onnxruntime::ElementWiseKernel<onnxruntime::functors::Abs<long long> >::ElementWiseKernel(const onnxruntime::OpKernelInfo &) [F = onnxruntime::functors::Abs<long long>]virtual onnxruntime::common::Status onnxruntime::ElementWiseKernel<onnxruntime::functors::Abs<long long> >::Compute(onnxruntime::OpKernelContext *) const [F = onnxruntime::functors::Abs<long long>]onnxruntime::ElementWiseKernel<onnxruntime::functors::Abs<unsigned char> >::ElementWiseKernel(const onnxruntime::OpKernelInfo &) [F = onnxruntime::functors::Abs<unsigned char>]virtual onnxruntime::common::Status onnxruntime::ElementWiseKernel<onnxruntime::functors::Abs<unsigned char> >::Compute(onnxruntime::OpKernelContext *) const [F = onnxruntime::functors::Abs<unsigned char>]onnxruntime::ElementWiseKernel<onnxruntime::functors::Abs<unsigned short> >::ElementWiseKernel(const onnxruntime::OpKernelInfo &) [F = onnxruntime::functors::Abs<unsigned short>]virtual onnxruntime::common::Status onnxruntime::ElementWiseKernel<onnxruntime::functors::Abs<unsigned short> >::Compute(onnxruntime::OpKernelContext *) const [F = onnxruntime::functors::Abs<unsigned short>]onnxruntime::ElementWiseKernel<onnxruntime::functors::Abs<unsigned int> >::ElementWiseKernel(const onnxruntime::OpKernelInfo &) [F = onnxruntime::functors::Abs<unsigned int>]virtual onnxruntime::common::Status onnxruntime::ElementWiseKernel<onnxruntime::functors::Abs<unsigned int> >::Compute(onnxruntime::OpKernelContext *) const [F = onnxruntime::functors::Abs<unsigned int>]onnxruntime::ElementWiseKernel<onnxruntime::functors::Abs<unsigned long long> >::ElementWiseKernel(const onnxruntime::OpKernelInfo &) [F = onnxruntime::functors::Abs<unsigned long long>]virtual onnxruntime::common::Status onnxruntime::ElementWiseKernel<onnxruntime::functors::Abs<unsigned long long> >::Compute(onnxruntime::OpKernelContext *) const [F = onnxruntime::functors::Abs<unsigned long long>]onnxruntime::ElementWiseKernel<onnxruntime::functors::Neg<float> >::ElementWiseKernel(const onnxruntime::OpKernelInfo &) [F = onnxruntime::functors::Neg<float>]virtual onnxruntime::common::Status onnxruntime::ElementWiseKernel<onnxruntime::functors::Neg<float> >::Compute(onnxruntime::OpKernelContext *) const [F = onnxruntime::functors::Neg<float>]onnxruntime::ElementWiseKernel<onnxruntime::functors::Neg<double> >::ElementWiseKernel(const onnxruntime::OpKernelInfo &) [F = onnxruntime::functors::Neg<double>]virtual onnxruntime::common::Status onnxruntime::ElementWiseKernel<onnxruntime::functors::Neg<double> >::Compute(onnxruntime::OpKernelContext *) const [F = onnxruntime::functors::Neg<double>]onnxruntime::ElementWiseKernel<onnxruntime::functors::Neg<signed char> >::ElementWiseKernel(const onnxruntime::OpKernelInfo &) [F = onnxruntime::functors::Neg<signed char>]virtual onnxruntime::common::Status onnxruntime::ElementWiseKernel<onnxruntime::functors::Neg<signed char> >::Compute(onnxruntime::OpKernelContext *) const [F = onnxruntime::functors::Neg<signed char>]onnxruntime::ElementWiseKernel<onnxruntime::functors::Neg<int> >::ElementWiseKernel(const onnxruntime::OpKernelInfo &) [F = onnxruntime::functors::Neg<int>]virtual onnxruntime::common::Status onnxruntime::ElementWiseKernel<onnxruntime::functors::Neg<int> >::Compute(onnxruntime::OpKernelContext *) const [F = onnxruntime::functors::Neg<int>]onnxruntime::ElementWiseKernel<onnxruntime::functors::Neg<long long> >::ElementWiseKernel(const onnxruntime::OpKernelInfo &) [F = onnxruntime::functors::Neg<long long>]virtual onnxruntime::common::Status onnxruntime::ElementWiseKernel<onnxruntime::functors::Neg<long long> >::Compute(onnxruntime::OpKernelContext *) const [F = onnxruntime::functors::Neg<long long>]onnxruntime::ElementWiseKernel<onnxruntime::functors::Floor<float> >::ElementWiseKernel(const onnxruntime::OpKernelInfo &) [F = onnxruntime::functors::Floor<float>]virtual onnxruntime::common::Status onnxruntime::ElementWiseKernel<onnxruntime::functors::Floor<float> >::Compute(onnxruntime::OpKernelContext *) const [F = onnxruntime::functors::Floor<float>]onnxruntime::ElementWiseKernel<onnxruntime::functors::Ceil<float> >::ElementWiseKernel(const onnxruntime::OpKernelInfo &) [F = onnxruntime::functors::Ceil<float>]virtual onnxruntime::common::Status onnxruntime::ElementWiseKernel<onnxruntime::functors::Ceil<float> >::Compute(onnxruntime::OpKernelContext *) const [F = onnxruntime::functors::Ceil<float>]onnxruntime::ElementWiseKernel<onnxruntime::functors::Reciprocal<float> >::ElementWiseKernel(const onnxruntime::OpKernelInfo &) [F = onnxruntime::functors::Reciprocal<float>]virtual onnxruntime::common::Status onnxruntime::ElementWiseKernel<onnxruntime::functors::Reciprocal<float> >::Compute(onnxruntime::OpKernelContext *) const [F = onnxruntime::functors::Reciprocal<float>]onnxruntime::ElementWiseKernel<onnxruntime::functors::Reciprocal<double> >::ElementWiseKernel(const onnxruntime::OpKernelInfo &) [F = onnxruntime::functors::Reciprocal<double>]virtual onnxruntime::common::Status onnxruntime::ElementWiseKernel<onnxruntime::functors::Reciprocal<double> >::Compute(onnxruntime::OpKernelContext *) const [F = onnxruntime::functors::Reciprocal<double>]onnxruntime::ElementWiseKernel<onnxruntime::functors::Sqrt<float> >::ElementWiseKernel(const onnxruntime::OpKernelInfo &) [F = onnxruntime::functors::Sqrt<float>]virtual onnxruntime::common::Status onnxruntime::ElementWiseKernel<onnxruntime::functors::Sqrt<float> >::Compute(onnxruntime::OpKernelContext *) const [F = onnxruntime::functors::Sqrt<float>]onnxruntime::ElementWiseKernel<onnxruntime::functors::Sqrt<double> >::ElementWiseKernel(const onnxruntime::OpKernelInfo &) [F = onnxruntime::functors::Sqrt<double>]virtual onnxruntime::common::Status onnxruntime::ElementWiseKernel<onnxruntime::functors::Sqrt<double> >::Compute(onnxruntime::OpKernelContext *) const [F = onnxruntime::functors::Sqrt<double>]onnxruntime::ElementWiseKernel<onnxruntime::functors::Exp<float> >::ElementWiseKernel(const onnxruntime::OpKernelInfo &) [F = onnxruntime::functors::Exp<float>]virtual onnxruntime::common::Status onnxruntime::ElementWiseKernel<onnxruntime::functors::Exp<float> >::Compute(onnxruntime::OpKernelContext *) const [F = onnxruntime::functors::Exp<float>]onnxruntime::ElementWiseKernel<onnxruntime::functors::Exp<double> >::ElementWiseKernel(const onnxruntime::OpKernelInfo &) [F = onnxruntime::functors::Exp<double>]virtual onnxruntime::common::Status onnxruntime::ElementWiseKernel<onnxruntime::functors::Exp<double> >::Compute(onnxruntime::OpKernelContext *) const [F = onnxruntime::functors::Exp<double>]onnxruntime::ElementWiseKernel<onnxruntime::functors::Log<float> >::ElementWiseKernel(const onnxruntime::OpKernelInfo &) [F = onnxruntime::functors::Log<float>]virtual onnxruntime::common::Status onnxruntime::ElementWiseKernel<onnxruntime::functors::Log<float> >::Compute(onnxruntime::OpKernelContext *) const [F = onnxruntime::functors::Log<float>]onnxruntime::ElementWiseKernel<onnxruntime::functors::Log<double> >::ElementWiseKernel(const onnxruntime::OpKernelInfo &) [F = onnxruntime::functors::Log<double>]virtual onnxruntime::common::Status onnxruntime::ElementWiseKernel<onnxruntime::functors::Log<double> >::Compute(onnxruntime::OpKernelContext *) const [F = onnxruntime::functors::Log<double>]virtual onnxruntime::common::Status onnxruntime::Sum_6<float>::Compute(onnxruntime::OpKernelContext *) const [T = float]input_count >= 1virtual onnxruntime::common::Status onnxruntime::Sum_6<double>::Compute(onnxruntime::OpKernelContext *) const [T = double]directiononnxruntime::BitShift<unsigned char>::BitShift(const onnxruntime::OpKernelInfo &) [T = unsigned char]LEFTRIGHTInvalid direction value of ''. Valid values are 'LEFT' or 'RIGHT'.auto onnxruntime::BitShift<unsigned char>::Compute(onnxruntime::OpKernelContext *)::(anonymous class)::operator()(onnxruntime::BroadcastHelper &) const [T = unsigned char]cur1 == end1cur_out == end_outonnxruntime::BitShift<unsigned int>::BitShift(const onnxruntime::OpKernelInfo &) [T = unsigned int]auto onnxruntime::BitShift<unsigned int>::Compute(onnxruntime::OpKernelContext *)::(anonymous class)::operator()(onnxruntime::BroadcastHelper &) const [T = unsigned int]onnxruntime::BitShift<unsigned long long>::BitShift(const onnxruntime::OpKernelInfo &) [T = unsigned long long]auto onnxruntime::BitShift<unsigned long long>::Compute(onnxruntime::OpKernelContext *)::(anonymous class)::operator()(onnxruntime::BroadcastHelper &) const [T = unsigned long long]void onnxruntime::UntypedExpand(onnxruntime::OpKernelContext &, const onnxruntime::ProcessBroadcastSpanFuncs &)shape_data_tensor.Shape().GetDims().size() == 1/Users/runner/work/1/s/onnxruntime/core/providers/cpu/math/element_wise_ops.honnxruntime::Broadcaster::Broadcaster(const std::vector<int64_t> &, const std::vector<int64_t> &)largest <= 1Can broadcast 0 by 0 or 1. is invalid.void onnxruntime::BroadcastIterator::Init(ptrdiff_t, ptrdiff_t)axis == 1 || axis == largestAttempting to broadcast an axis by a dimension other than 1. by void onnxruntime::BroadcastIterator::Append(ptrdiff_t, ptrdiff_t)void onnxruntime::ExpandBroadcastLooper(onnxruntime::BroadcastHelper &, const onnxruntime::ProcessBroadcastSpanFuncs &)!helper.HaveTwoTensorInputs()ExpandBroadcastLooper should only have a shape for the second input.void onnxruntime::InputBroadcaster::AdvanceBy(size_t)offset % span_size_ == 0fmodonnxruntime::Mod::Mod(const onnxruntime::OpKernelInfo &)(fmod == 0) || (fmod == 1)onnxruntime::OutputBroadcaster::OutputBroadcaster(size_t, onnxruntime::Tensor &, ptrdiff_t, ptrdiff_t)start_offset >= 0 && real_end >= 0 && start_offset <= real_end && real_end <= lenInvalid start/ending offset [) for tensor of length:start_offset % span_size == 0 && real_end % span_size == 0Broadcast Output range [) are not at boundary of span with size:onnxruntime::TensorAllocator::TensorAllocator(onnxruntime::OpKernelContext &)Unsupported Y type: void onnxruntime::utils::mltype_dispatcher_internal::UnsupportedTypeDefaultPolicy<onnxruntime::common::Status>::operator()(int32_t, Ret &) const [Ret = onnxruntime::common::Status]Unsupported data type: void onnxruntime::mod_internal::CallModImpl<float, void>::operator()(bool, onnxruntime::OpKernelContext *) const [T = float, Enable = void]void onnxruntime::mod_internal::CallModImpl<double, void>::operator()(bool, onnxruntime::OpKernelContext *) const [T = double, Enable = void]void onnxruntime::mod_internal::CallModImpl<onnxruntime::MLFloat16, void>::operator()(bool, onnxruntime::OpKernelContext *) constvoid onnxruntime::utils::mltype_dispatcher_internal::CallableDispatchableHelper::CheckCalledOnce()called_ == 1void onnxruntime::BroadcastLooper(TBroadcastHelper &, const onnxruntime::ProcessBroadcastSpanFuncs &) [TBroadcastHelper = onnxruntime::BroadcastHelper]helper.HaveTwoTensorInputs()GemmtransA/Users/runner/work/1/s/onnxruntime/core/providers/cpu/math/gemm.honnxruntime::Gemm<float>::Gemm(const onnxruntime::OpKernelInfo &) [T = float]info.GetAttr<int64_t>("transA", &temp).IsOK()transBinfo.GetAttr<int64_t>("transB", &temp).IsOK()onnxruntime::Gemm<double>::Gemm(const onnxruntime::OpKernelInfo &) [T = double]/Users/runner/work/1/s/onnxruntime/core/providers/cpu/math/gemm.ccvoid onnxruntime::GemmBroadcastBias(int64_t, int64_t, float, const T *, const onnxruntime::TensorShape *, T *) [T = double]c_shape != nullptr/Users/runner/work/1/s/onnxruntime/core/providers/cpu/math/gemm_helper.honnxruntime::GemmHelper::GemmHelper(const onnxruntime::TensorShape &, bool, const onnxruntime::TensorShape &, bool, const onnxruntime::TensorShape &)left.NumDimensions() == 2 || left.NumDimensions() == 1right.NumDimensions() == 2GEMM: Dimension mismatch, W: K: N:Gemm: Invalid bias shape for broadcastM_ >= 0 && K_ > 0 && N_ >= 0void onnxruntime::GemmBroadcastBias(int64_t, int64_t, float, const T *, const onnxruntime::TensorShape *, T *) [T = float]/Users/runner/work/1/s/onnxruntime/core/providers/cpu/math/hardmax.ccHardmax inputs N, D and N * D must be < . N=, D=HardmaxMatMul/Users/runner/work/1/s/onnxruntime/core/providers/cpu/math/matmul.cc/Users/runner/work/1/s/onnxruntime/core/providers/cpu/math/matmul_helper.hleft_num_dims and right_num_dims must be >= 1MatMul dimension mismatchleft operand cannot broadcast on dim right operand cannot broadcast on dim num_dims_with_pad != num_output_dimsM_ == 1 && N_ == 1 was falsenum_dims_with_pad - 1 != num_output_dimsnum_dims_with_pad - 2 != num_output_dimsMatMulInteger/Users/runner/work/1/s/onnxruntime/core/providers/cpu/math/matmul_integer.ccvirtual onnxruntime::common::Status onnxruntime::MatMulInteger::Compute(onnxruntime::OpKernelContext *) constIsScalarOr1ElementVector(a_zero_point)MatmulInteger : input1 zero point must be a scalar or 1D tensor of size 1IsBQuantParamSupported(b_zero_point->Shape(), b ? b->Shape() : b_shape_)QLinearMatMul/Users/runner/work/1/s/onnxruntime/core/providers/cpu/math/quantize_linear_matmul.ccvirtual onnxruntime::common::Status onnxruntime::QLinearMatMul::Compute(onnxruntime::OpKernelContext *) constIsScalarOr1ElementVector(a_offset)QLinearMatmul : input zero point must be a scalar or 1D tensor of size 1IsBQuantParamSupported(b_offset->Shape(), b ? b->Shape() : b_shape_)QLinearMatmul : weight zero point must be a scalar, 1D tensor of size 1, or last to second dimension is 1IsScalarOr1ElementVector(y_offset)QLinearMatmul : result zero point must be a scalar or 1D tensor of size 1IsScalarOr1ElementVector(a_scale)QLinearMatmul : input scale must be a scalar or 1D tensor of size 1IsBQuantParamSupported(b_scale->Shape(), b ? b->Shape() : b_shape_)QLinearMatmul : weight scale must be a scalar, 1D tensor of size 1, or last to second dimension is 1IsScalarOr1ElementVector(y_scale)QLinearMatmul : result scale must be a scalar or 1D tensor of size 1Per-column quantization parameter of batched matrix should have same dimension as the matrix,and its size by K should be equal to the matrix's size.RoundSignSoftmaxLogSoftmax/Users/runner/work/1/s/onnxruntime/core/providers/cpu/math/softmax.ccComputeImplOpset13SoftmaxCPU inputs N, D and N * D must be < TopK/Users/runner/work/1/s/onnxruntime/core/providers/cpu/math/top_k.ccvoid onnxruntime::TopkOpset9ConstructorCommon(const onnxruntime::OpKernelInfo &, int &, unsigned int &)op_kernel_info.GetAttr<int64_t>("k", &k_temp).IsOK()k_temp > 0op_kernel_info.GetAttr<int64_t>("axis", &axis_temp).IsOK()void onnxruntime::TopkOpset10ConstructorCommon(const onnxruntime::OpKernelInfo &, int &)void onnxruntime::TopkOpset11ConstructorCommon(const onnxruntime::OpKernelInfo &, int &, bool &, bool &)largestop_kernel_info.GetAttr<int64_t>("largest", &largest_temp).IsOK()op_kernel_info.GetAttr<int64_t>("sorted", &sorted_temp).IsOK()input count mismatch, expected 1 input - the tensor to be processedk argument [] should not be greater than specified axis dim value [output count mismatch, expected 2 outputs to be present for TopK operatorinput count mismatch, expected 2 inputs - the tensor to be processed and a tensor containing k valueArrayFeatureExtractorInvalid argument: X input has empty dimensions.Invalid Y argument: num_indices = 0Invalid Y argument: index is out of range: Y[] () >=BinarizerthresholdInput data with index: is NaNCastMapInvalid input type of value: Expected std::map<int64_t, float> or std::map<int64_t, std::string>Unexpected CAST_TO value of cast_to/Users/runner/work/1/s/onnxruntime/core/providers/cpu/ml/cast_map.honnxruntime::ml::CastMap::CastMap(const onnxruntime::OpKernelInfo &)info.GetAttr<std::string>("cast_to", &attr).IsOK()info.GetAttr<std::string>("map_form", &attr).IsOK()max_mapinfo.GetAttr<int64_t>("max_map", &max_map_).IsOK()map_form_ != PACK_MAP::SPARSE || max_map_ > 0TO_FLOATTO_STRINGTO_INT64/Users/runner/work/1/s/onnxruntime/core/providers/cpu/ml/ml_common.honnxruntime::ml::CAST_TO onnxruntime::ml::MakeCast(const std::string &)Invalid CAST_TO value of Expected TO_FLOAT, TO_STRING or TO_INT64DENSESPARSEonnxruntime::ml::PACK_MAP onnxruntime::ml::MakePack(const std::string &)Invalid PACK_MAP value of Expected DENSE or SPARSE/Users/runner/work/1/s/onnxruntime/core/providers/cpu/ml/cast_map.cconnxruntime::common::Status onnxruntime::ml::CastMap::ComputeImpl(onnxruntime::OpKernelContext &, TTo) const [TFrom = float, TTo = float]cur_input == end_input || cur_input->first >= 0Negative index values are not permitted. First entry in map has index value of const T *onnxruntime::OpKernelContext::Input(int) const [T = std::__1::map<long long, float, std::__1::less<long long>, std::__1::allocator<std::__1::pair<const long long, float> > >]onnxruntime::common::Status onnxruntime::ml::CastMap::ComputeImpl(onnxruntime::OpKernelContext &, TTo) const [TFrom = std::__1::basic_string<char>, TTo = float]const T *onnxruntime::OpKernelContext::Input(int) const [T = std::__1::map<long long, std::__1::basic_string<char>, std::__1::less<long long>, std::__1::allocator<std::__1::pair<const long long, std::__1::basic_string<char> > > >]onnxruntime::common::Status onnxruntime::ml::CastMap::ComputeImpl(onnxruntime::OpKernelContext &, TTo) const [TFrom = float, TTo = long long]onnxruntime::common::Status onnxruntime::ml::CastMap::ComputeImpl(onnxruntime::OpKernelContext &, TTo) const [TFrom = std::__1::basic_string<char>, TTo = long long]onnxruntime::common::Status onnxruntime::ml::CastMap::ComputeImpl(onnxruntime::OpKernelContext &, TTo) const [TFrom = float, TTo = std::__1::basic_string<char>]onnxruntime::common::Status onnxruntime::ml::CastMap::ComputeImpl(onnxruntime::OpKernelContext &, TTo) const [TFrom = std::__1::basic_string<char>, TTo = std::__1::basic_string<char>]CategoryMapperInput of string must have output of int64Input of int64 must have output of string cats_strings/Users/runner/work/1/s/onnxruntime/core/providers/cpu/ml/category_mapper.honnxruntime::ml::CategoryMapper::CategoryMapper(const onnxruntime::OpKernelInfo &)info.GetAttrs<std::string>("cats_strings", string_categories).IsOK()cats_int64sinfo.GetAttrs<int64_t>("cats_int64s", int_categories).IsOK()default_stringinfo.GetAttr<std::string>("default_string", &default_string_).IsOK()default_int64info.GetAttr<int64_t>("default_int64", &default_int_).IsOK()num_entries == int_categories.size()DictVectorizerstring_vocabulary/Users/runner/work/1/s/onnxruntime/core/providers/cpu/ml/dictvectorizer.honnxruntime::ml::DictVectorizerOp<std::__1::basic_string<char>, long long>::DictVectorizerOp(const onnxruntime::OpKernelInfo &) [AttrType = std::__1::basic_string<char>, TargetType = long long]info.GetAttrs(std::is_same<AttrType, std::string>::value ? "string_vocabulary" : "int64_vocabulary", vocabulary_).IsOK()const T *onnxruntime::OpKernelContext::Input(int) const [T = std::__1::map<std::__1::basic_string<char>, long long, std::__1::less<std::__1::basic_string<char> >, std::__1::allocator<std::__1::pair<const std::__1::basic_string<char>, long long> > >]onnxruntime::ml::DictVectorizerOp<std::__1::basic_string<char>, float>::DictVectorizerOp(const onnxruntime::OpKernelInfo &) [AttrType = std::__1::basic_string<char>, TargetType = float]const T *onnxruntime::OpKernelContext::Input(int) const [T = std::__1::map<std::__1::basic_string<char>, float, std::__1::less<std::__1::basic_string<char> >, std::__1::allocator<std::__1::pair<const std::__1::basic_string<char>, float> > >]onnxruntime::ml::DictVectorizerOp<std::__1::basic_string<char>, double>::DictVectorizerOp(const onnxruntime::OpKernelInfo &) [AttrType = std::__1::basic_string<char>, TargetType = double]const T *onnxruntime::OpKernelContext::Input(int) const [T = std::__1::map<std::__1::basic_string<char>, double, std::__1::less<std::__1::basic_string<char> >, std::__1::allocator<std::__1::pair<const std::__1::basic_string<char>, double> > >]int64_vocabularyonnxruntime::ml::DictVectorizerOp<long long, std::__1::basic_string<char> >::DictVectorizerOp(const onnxruntime::OpKernelInfo &) [AttrType = long long, TargetType = std::__1::basic_string<char>]onnxruntime::ml::DictVectorizerOp<long long, float>::DictVectorizerOp(const onnxruntime::OpKernelInfo &) [AttrType = long long, TargetType = float]onnxruntime::ml::DictVectorizerOp<long long, double>::DictVectorizerOp(const onnxruntime::OpKernelInfo &) [AttrType = long long, TargetType = double]const T *onnxruntime::OpKernelContext::Input(int) const [T = std::__1::map<long long, double, std::__1::less<long long>, std::__1::allocator<std::__1::pair<const long long, double> > >]FeatureVectorizer/Users/runner/work/1/s/onnxruntime/core/providers/cpu/ml/feature_vectorizer.ccvirtual onnxruntime::common::Status onnxruntime::ml::FeatureVectorizer::Compute(onnxruntime::OpKernelContext *) constinput_count >= 0 && static_cast<size_t>(input_count) == input_dimensions_.size()Number of inputs () does not match number of inputdimensions values (Invalid input type:inputdimensions/Users/runner/work/1/s/onnxruntime/core/providers/cpu/ml/feature_vectorizer.honnxruntime::ml::FeatureVectorizer::FeatureVectorizer(const onnxruntime::OpKernelInfo &)status.IsOK() && !input_dimensions_.empty()Imputerimputed_value_floatsimputed_value_int64sreplaced_value_float/Users/runner/work/1/s/onnxruntime/core/providers/cpu/ml/imputer.cconnxruntime::ml::ImputerOp::ImputerOp(const onnxruntime::OpKernelInfo &)Expected 'replaced_value_float' attribute since 'imputed_value_floats' is specifiedreplaced_value_int64Expected 'replace_value_int64' attribute since 'imputed_values_int64' is specifiedimputed_values_float_.empty() ^ imputed_values_int64_.empty()Must provide imputed_values_float_ or imputed_values_int64_ but not both.virtual common::Status onnxruntime::ml::ImputerOp::Compute(onnxruntime::OpKernelContext *) constInvalid typeEmpty value of imputed values.Empty input dimensions.LabelEncoderInput of tensor(string) must have output of tensor(int64)Input of tensor(int64) must have output of tensor(string)keys_floatsvalues_stringskeys_stringsvalues_floatsdefault_floatkeys_int64svalues_int64sclasses_strings/Users/runner/work/1/s/onnxruntime/core/providers/cpu/ml/label_encoder.honnxruntime::ml::LabelEncoder::LabelEncoder(const onnxruntime::OpKernelInfo &)info.GetAttrs<std::string>("classes_strings", string_classes).IsOK()onnxruntime::ml::LabelEncoder_2<float, std::__1::basic_string<char> >::LabelEncoder_2(const onnxruntime::OpKernelInfo &) [TKey = float, TValue = std::__1::basic_string<char>]info.GetAttrs<TKey>(_key_field_name, keys).IsOK()info.GetAttrs<TValue>(_value_field_name, values).IsOK()num_keys == num_valuesThe attribtues in LabelEncoder (name: ) must have the same length. However, the number of key is and the number of values is onnxruntime::ml::LabelEncoder_2<std::__1::basic_string<char>, float>::LabelEncoder_2(const onnxruntime::OpKernelInfo &) [TKey = std::__1::basic_string<char>, TValue = float]onnxruntime::ml::LabelEncoder_2<long long, float>::LabelEncoder_2(const onnxruntime::OpKernelInfo &) [TKey = long long, TValue = float]onnxruntime::ml::LabelEncoder_2<float, long long>::LabelEncoder_2(const onnxruntime::OpKernelInfo &) [TKey = float, TValue = long long]onnxruntime::ml::LabelEncoder_2<long long, std::__1::basic_string<char> >::LabelEncoder_2(const onnxruntime::OpKernelInfo &) [TKey = long long, TValue = std::__1::basic_string<char>]onnxruntime::ml::LabelEncoder_2<std::__1::basic_string<char>, long long>::LabelEncoder_2(const onnxruntime::OpKernelInfo &) [TKey = std::__1::basic_string<char>, TValue = long long]onnxruntime::ml::LabelEncoder_2<long long, long long>::LabelEncoder_2(const onnxruntime::OpKernelInfo &) [TKey = long long, TValue = long long]LinearClassifiermulti_class/Users/runner/work/1/s/onnxruntime/core/providers/cpu/ml/linearclassifier.cconnxruntime::ml::LinearClassifier::LinearClassifier(const onnxruntime::OpKernelInfo &)void onnxruntime::ml::LinearClassifier::ComputeImpl(const gsl::span<const float>, int64_t, int64_t, int64_t, const std::vector<float> &, const std::vector<float> &, onnxruntime::Tensor &, onnxruntime::Tensor &, onnxruntime::ml::POST_EVAL_TRANSFORM, bool, concurrency::ThreadPool *) constscores_output_data.length() >= scores_output_sizeScores output is incorrect size. Expected: Found:Input shape needs to be at least a single dimension.Unsupported input element type of void onnxruntime::ml::CastInputToFloat(const onnxruntime::Tensor &, gsl::span<float> &) [SrcType = int]shape_size == out.length()void onnxruntime::ml::CastInputToFloat(const onnxruntime::Tensor &, gsl::span<float> &) [SrcType = long long]void onnxruntime::ml::CastInputToFloat(const onnxruntime::Tensor &, gsl::span<float> &) [SrcType = double]LinearRegressorinterceptstargets/Users/runner/work/1/s/onnxruntime/core/providers/cpu/ml/linearregressor.cconnxruntime::ml::LinearRegressor::LinearRegressor(const onnxruntime::OpKernelInfo &)info.GetAttr<int64_t>("targets", &num_targets_).IsOK()Input shape had more than 2 dimension. Dims=Normalizer/Users/runner/work/1/s/onnxruntime/core/providers/cpu/ml/normalizer.honnxruntime::ml::Normalizer::Normalizer(const onnxruntime::OpKernelInfo &)info.GetAttr<std::string>("norm", &norm).IsOK()MAXL1L2onnxruntime::ml::NORMALIZE onnxruntime::ml::MakeNormalize(const std::string &)Invalid normalize value of Rank of input to Normalized must be less than 2. Got Unexpected NORMALIZE value of OneHotEncoderUnknown Category and zeros = 0.zeros/Users/runner/work/1/s/onnxruntime/core/providers/cpu/ml/onehotencoder.cconnxruntime::ml::OneHotEncoderOp<long long>::OneHotEncoderOp(const onnxruntime::OpKernelInfo &) [T = long long]tmp_cats_int64s.empty() || tmp_cats_strings.empty()One and only one of the 'cats_*' attributes must be definednum_categories_ > 0onnxruntime::ml::OneHotEncoderOp<float>::OneHotEncoderOp(const onnxruntime::OpKernelInfo &) [T = float]onnxruntime::ml::OneHotEncoderOp<double>::OneHotEncoderOp(const onnxruntime::OpKernelInfo &) [T = double]onnxruntime::ml::OneHotEncoderOp<std::__1::basic_string<char> >::OneHotEncoderOp(const onnxruntime::OpKernelInfo &) [T = std::__1::basic_string<char>]Scaler/Users/runner/work/1/s/onnxruntime/core/providers/cpu/ml/scaler.cconnxruntime::ml::ScalerOp<float>::ScalerOp(const onnxruntime::OpKernelInfo &) [T = float]!scale_.empty()scale_.size() == offset_.size()Scale size: () != (Invalid argument: input has empty dimensions.Either both scale and offset can be of feature size () or 1onnxruntime::ml::ScalerOp<double>::ScalerOp(const onnxruntime::OpKernelInfo &) [T = double]onnxruntime::ml::ScalerOp<long long>::ScalerOp(const onnxruntime::OpKernelInfo &) [T = long long]onnxruntime::ml::ScalerOp<int>::ScalerOp(const onnxruntime::OpKernelInfo &) [T = int]SVMClassifiervectors_per_classprob_aprob_b/Users/runner/work/1/s/onnxruntime/core/providers/cpu/ml/svmclassifier.cconnxruntime::ml::SVMClassifier::SVMClassifier(const onnxruntime::OpKernelInfo &)proba_.size() == probb_.size()classlabels_intsinfo.GetAttrs<std::string>("classlabels_strings", classlabels_strings_).IsOK() || info.GetAttrs<int64_t>("classlabels_ints", classlabels_ints_).IsOK()classlabels_strings_.size() > 0 || classlabels_ints_.size() > 0coefficients_.size() > 0Unsupported data type of void onnxruntime::ml::batched_update_scores_inplace(gsl::span<T>, int64_t, int64_t, onnxruntime::ml::POST_EVAL_TRANSFORM, int, bool, concurrency::ThreadPool *) [T = float]scores.size() == static_cast<size_t>(expected_num_scores)Unexpected value for 'add_second_class' of SVMRegressorn_supportssupport_vectorspost_transformrho/Users/runner/work/1/s/onnxruntime/core/providers/cpu/ml/svmregressor.cconnxruntime::ml::SVMRegressor<float>::SVMRegressor(const onnxruntime::OpKernelInfo &) [T = float]info.GetAttrs<float>("rho", rho_).IsOK()coefficientsinfo.GetAttrs<float>("coefficients", coefficients_).IsOK()!coefficients_.empty()one_classkernel_typeLINEARkernel_params/Users/runner/work/1/s/onnxruntime/core/providers/cpu/ml/svmclassifier.honnxruntime::ml::SVMCommon::SVMCommon(const onnxruntime::OpKernelInfo &)info.GetAttrs<float>("kernel_params", kernel_params).IsOK()POLYRBFLOGISTICSOFTMAXSOFTMAX_ZEROvirtual onnxruntime::common::Status onnxruntime::ml::SVMRegressor<float>::Compute(onnxruntime::OpKernelContext *) const [T = float]num_features == feature_count_Unexpected mode:TreeEnsembleClassifierclass_idsclass_nodeidsclass_treeidsclass_weightsX dims is empty.computevoid onnxruntime::ml::detail::TreeEnsembleCommonClassifier<float, float>::compute(onnxruntime::OpKernelContext *, const onnxruntime::Tensor *, onnxruntime::Tensor *, onnxruntime::Tensor *) const [ITYPE = float, OTYPE = float]void onnxruntime::ml::detail::TreeAggregatorClassifier<float, float>::FinalizeScores(std::vector<ScoreValue<OTYPE> > &, OTYPE *, int, int64_t *) const [ITYPE = float, OTYPE = float]predictions.size() == 2int64_t onnxruntime::ml::detail::TreeAggregatorClassifier<float, float>::_set_score_binary(int &, const std::vector<ScoreValue<OTYPE> > &) const [ITYPE = float, OTYPE = float]classes.size() == 2 || classes.size() == 1void onnxruntime::ml::detail::TreeEnsembleCommonClassifier<double, float>::compute(onnxruntime::OpKernelContext *, const onnxruntime::Tensor *, onnxruntime::Tensor *, onnxruntime::Tensor *) const [ITYPE = double, OTYPE = float]void onnxruntime::ml::detail::TreeAggregatorClassifier<double, float>::FinalizeScores(std::vector<ScoreValue<OTYPE> > &, OTYPE *, int, int64_t *) const [ITYPE = double, OTYPE = float]int64_t onnxruntime::ml::detail::TreeAggregatorClassifier<double, float>::_set_score_binary(int &, const std::vector<ScoreValue<OTYPE> > &) const [ITYPE = double, OTYPE = float]onnxruntime::ml::detail::TreeEnsembleCommon<long long, float>::TreeEnsembleCommon(int, int, const std::string &, const std::vector<OTYPE> &, int64_t, const std::vector<int64_t> &, const std::vector<int64_t> &, const std::vector<OTYPE> &, const std::vector<int64_t> &, const std::vector<std::string> &, const std::vector<int64_t> &, const std::vector<int64_t> &, const std::vector<int64_t> &, const std::vector<OTYPE> &, const std::string &, const std::vector<int64_t> &, const std::vector<int64_t> &, const std::vector<int64_t> &, const std::vector<OTYPE> &) [ITYPE = long long, OTYPE = float]void onnxruntime::ml::detail::TreeEnsembleCommonClassifier<long long, float>::compute(onnxruntime::OpKernelContext *, const onnxruntime::Tensor *, onnxruntime::Tensor *, onnxruntime::Tensor *) const [ITYPE = long long, OTYPE = float]void onnxruntime::ml::detail::TreeAggregatorSum<long long, float>::ProcessTreeNodePrediction(std::vector<ScoreValue<OTYPE> > &, const TreeNodeElement<OTYPE> &) const [ITYPE = long long, OTYPE = float]void onnxruntime::ml::detail::TreeAggregatorClassifier<long long, float>::FinalizeScores(std::vector<ScoreValue<OTYPE> > &, OTYPE *, int, int64_t *) const [ITYPE = long long, OTYPE = float]int64_t onnxruntime::ml::detail::TreeAggregatorClassifier<long long, float>::_set_score_binary(int &, const std::vector<ScoreValue<OTYPE> > &) const [ITYPE = long long, OTYPE = float]void onnxruntime::ml::detail::TreeAggregatorSum<long long, float>::MergePrediction(std::vector<ScoreValue<OTYPE> > &, const std::vector<ScoreValue<OTYPE> > &) const [ITYPE = long long, OTYPE = float]onnxruntime::ml::detail::TreeEnsembleCommon<int, float>::TreeEnsembleCommon(int, int, const std::string &, const std::vector<OTYPE> &, int64_t, const std::vector<int64_t> &, const std::vector<int64_t> &, const std::vector<OTYPE> &, const std::vector<int64_t> &, const std::vector<std::string> &, const std::vector<int64_t> &, const std::vector<int64_t> &, const std::vector<int64_t> &, const std::vector<OTYPE> &, const std::string &, const std::vector<int64_t> &, const std::vector<int64_t> &, const std::vector<int64_t> &, const std::vector<OTYPE> &) [ITYPE = int, OTYPE = float]void onnxruntime::ml::detail::TreeEnsembleCommonClassifier<int, float>::compute(onnxruntime::OpKernelContext *, const onnxruntime::Tensor *, onnxruntime::Tensor *, onnxruntime::Tensor *) const [ITYPE = int, OTYPE = float]void onnxruntime::ml::detail::TreeAggregatorSum<int, float>::ProcessTreeNodePrediction(std::vector<ScoreValue<OTYPE> > &, const TreeNodeElement<OTYPE> &) const [ITYPE = int, OTYPE = float]void onnxruntime::ml::detail::TreeAggregatorClassifier<int, float>::FinalizeScores(std::vector<ScoreValue<OTYPE> > &, OTYPE *, int, int64_t *) const [ITYPE = int, OTYPE = float]int64_t onnxruntime::ml::detail::TreeAggregatorClassifier<int, float>::_set_score_binary(int &, const std::vector<ScoreValue<OTYPE> > &) const [ITYPE = int, OTYPE = float]void onnxruntime::ml::detail::TreeAggregatorSum<int, float>::MergePrediction(std::vector<ScoreValue<OTYPE> > &, const std::vector<ScoreValue<OTYPE> > &) const [ITYPE = int, OTYPE = float]TreeEnsembleRegressoraggregate_functionSUMbase_valuesn_targetsnodes_falsenodeidsnodes_featureidsnodes_hitratesnodes_missing_value_tracks_truenodes_modesnodes_nodeidsnodes_treeidsnodes_truenodeidsnodes_valuestarget_idstarget_nodeidstarget_treeidstarget_weights/Users/runner/work/1/s/onnxruntime/core/providers/cpu/ml/tree_ensemble_common.honnxruntime::ml::detail::TreeEnsembleCommon<float, float>::TreeEnsembleCommon(int, int, const std::string &, const std::vector<OTYPE> &, int64_t, const std::vector<int64_t> &, const std::vector<int64_t> &, const std::vector<OTYPE> &, const std::vector<int64_t> &, const std::vector<std::string> &, const std::vector<int64_t> &, const std::vector<int64_t> &, const std::vector<int64_t> &, const std::vector<OTYPE> &, const std::string &, const std::vector<int64_t> &, const std::vector<int64_t> &, const std::vector<int64_t> &, const std::vector<OTYPE> &) [ITYPE = float, OTYPE = float]n_targets_or_classes > 0nodes_falsenodeids.size() == nodes_featureids.size()nodes_falsenodeids.size() == nodes_modes.size()nodes_falsenodeids.size() == nodes_nodeids.size()nodes_falsenodeids.size() == nodes_treeids.size()nodes_falsenodeids.size() == nodes_truenodeids.size()nodes_falsenodeids.size() == nodes_values.size()target_class_ids.size() == target_class_nodeids.size()target_class_ids.size() == target_class_treeids.size() in tree is already there.Unable to find node (truenode).One falsenode is pointing either to itself, either to another tree. (falsenode). (weights).AVERAGEMINBRANCH_LEQLEAFBRANCH_LTBRANCH_GTEBRANCH_GTBRANCH_EQvoid onnxruntime::ml::detail::TreeEnsembleCommon<float, float>::compute(onnxruntime::OpKernelContext *, const onnxruntime::Tensor *, onnxruntime::Tensor *, onnxruntime::Tensor *) const [ITYPE = float, OTYPE = float]/Users/runner/work/1/s/onnxruntime/core/providers/cpu/ml/tree_ensemble_aggregator.hvoid onnxruntime::ml::detail::TreeAggregatorSum<float, float>::ProcessTreeNodePrediction(std::vector<ScoreValue<OTYPE> > &, const TreeNodeElement<OTYPE> &) const [ITYPE = float, OTYPE = float]it->i < (int64_t)predictions.size()void onnxruntime::ml::detail::TreeAggregatorAverage<float, float>::FinalizeScores(std::vector<ScoreValue<OTYPE> > &, OTYPE *, int, int64_t *) const [ITYPE = float, OTYPE = float]this->base_values_.size() == predictions.size()void onnxruntime::ml::detail::TreeAggregatorSum<float, float>::MergePrediction(std::vector<ScoreValue<OTYPE> > &, const std::vector<ScoreValue<OTYPE> > &) const [ITYPE = float, OTYPE = float]predictions.size() == predictions2.size()void onnxruntime::ml::detail::TreeAggregator<float, float>::FinalizeScores(std::vector<ScoreValue<OTYPE> > &, OTYPE *, int, int64_t *) const [ITYPE = float, OTYPE = float]predictions.size() == (size_t)n_targets_or_classes_void onnxruntime::ml::detail::TreeAggregatorMin<float, float>::MergePrediction(std::vector<ScoreValue<OTYPE> > &, const std::vector<ScoreValue<OTYPE> > &) const [ITYPE = float, OTYPE = float]void onnxruntime::ml::detail::TreeAggregatorMax<float, float>::MergePrediction(std::vector<ScoreValue<OTYPE> > &, const std::vector<ScoreValue<OTYPE> > &) const [ITYPE = float, OTYPE = float]onnxruntime::ml::detail::TreeEnsembleCommon<double, float>::TreeEnsembleCommon(int, int, const std::string &, const std::vector<OTYPE> &, int64_t, const std::vector<int64_t> &, const std::vector<int64_t> &, const std::vector<OTYPE> &, const std::vector<int64_t> &, const std::vector<std::string> &, const std::vector<int64_t> &, const std::vector<int64_t> &, const std::vector<int64_t> &, const std::vector<OTYPE> &, const std::string &, const std::vector<int64_t> &, const std::vector<int64_t> &, const std::vector<int64_t> &, const std::vector<OTYPE> &) [ITYPE = double, OTYPE = float]void onnxruntime::ml::detail::TreeEnsembleCommon<double, float>::compute(onnxruntime::OpKernelContext *, const onnxruntime::Tensor *, onnxruntime::Tensor *, onnxruntime::Tensor *) const [ITYPE = double, OTYPE = float]void onnxruntime::ml::detail::TreeAggregatorSum<double, float>::ProcessTreeNodePrediction(std::vector<ScoreValue<OTYPE> > &, const TreeNodeElement<OTYPE> &) const [ITYPE = double, OTYPE = float]void onnxruntime::ml::detail::TreeAggregatorAverage<double, float>::FinalizeScores(std::vector<ScoreValue<OTYPE> > &, OTYPE *, int, int64_t *) const [ITYPE = double, OTYPE = float]void onnxruntime::ml::detail::TreeAggregatorSum<double, float>::MergePrediction(std::vector<ScoreValue<OTYPE> > &, const std::vector<ScoreValue<OTYPE> > &) const [ITYPE = double, OTYPE = float]void onnxruntime::ml::detail::TreeAggregator<double, float>::FinalizeScores(std::vector<ScoreValue<OTYPE> > &, OTYPE *, int, int64_t *) const [ITYPE = double, OTYPE = float]void onnxruntime::ml::detail::TreeAggregatorMin<double, float>::MergePrediction(std::vector<ScoreValue<OTYPE> > &, const std::vector<ScoreValue<OTYPE> > &) const [ITYPE = double, OTYPE = float]void onnxruntime::ml::detail::TreeAggregatorMax<double, float>::MergePrediction(std::vector<ScoreValue<OTYPE> > &, const std::vector<ScoreValue<OTYPE> > &) const [ITYPE = double, OTYPE = float]ZipMapclasslabels_int64sclasslabels_strings/Users/runner/work/1/s/onnxruntime/core/providers/cpu/ml/zipmap.cconnxruntime::ml::ZipMapOp::ZipMapOp(const onnxruntime::OpKernelInfo &)classlabels_strings_.empty() ^ classlabels_int64s_.empty()Must provide classlabels_strings or classlabels_int64s but not both.Zipmap does not support empty dim countZipmap only supports 1D or 2D input tensorsInput features_per_batch[] != number of classlabels[T *OrtValue::GetMutable() [T = std::__1::vector<std::__1::map<std::__1::basic_string<char>, float, std::__1::less<std::__1::basic_string<char> >, std::__1::allocator<std::__1::pair<const std::__1::basic_string<char>, float> > >, std::__1::allocator<std::__1::map<std::__1::basic_string<char>, float, std::__1::less<std::__1::basic_string<char> >, std::__1::allocator<std::__1::pair<const std::__1::basic_string<char>, float> > > > >]T *OrtValue::GetMutable() [T = std::__1::vector<std::__1::map<long long, float, std::__1::less<long long>, std::__1::allocator<std::__1::pair<const long long, float> > >, std::__1::allocator<std::__1::map<long long, float, std::__1::less<long long>, std::__1::allocator<std::__1::pair<const long long, float> > > > >]MaxUnpool/Users/runner/work/1/s/onnxruntime/core/providers/cpu/nn/Unpool.ccIndex tensor shape should be same as that of the input data tensor to unpool.Shape must be 1 dimensional as it's tensor data of a shapeoutput_shape is smaller than minimum required. output_shape: inferred output shape:/Users/runner/work/1/s/onnxruntime/core/providers/cpu/nn/unpool.honnxruntime::MaxUnpool::MaxUnpool(const onnxruntime::OpKernelInfo &)info.GetAttrs<int64_t>("kernel_shape", kernel_shape_).IsOK()kernel_shape_[dim] > 0pads_[dim] < kernel_shape_[dim] && pads_[dim + kernel_shape_.size()] < kernel_shape_[dim]strides_.size() == kernel_shape_.size()BatchNormalizationspatial/Users/runner/work/1/s/onnxruntime/core/providers/cpu/nn/batch_norm.honnxruntime::BatchNorm<float>::BatchNorm(const onnxruntime::OpKernelInfo &) [T = float]!is_train_Invalid input X: The rank of input X must be atleast 2. Got rank: Invalid input scale: NumDimensions() != Invalid input scale: 0th dimension != Invalid input scale: dimension != Invalid input B: NumDimensions() != Invalid input B: 0th dimension != Invalid input B: Invalid input mean: NumDimensions() != Invalid input mean: 0th dimension != Invalid input mean: Invalid input var: NumDimensions() != Invalid input var: 0th dimension != Invalid input var: onnxruntime::BatchNorm<double>::BatchNorm(const onnxruntime::OpKernelInfo &) [T = double]/Users/runner/work/1/s/onnxruntime/core/providers/cpu/nn/conv.ccConvX num_dims does not match W num_dims. X: W: Input channels C is not equal to kernel channels * group. C: kernel channels: group: Output channels M is not divisible by group. M: kernel_shape num_dims is not compatible with W num_dims. kernel_shape: kernel_shape is not compatible with W shape.Not enough elements in strides. Expected: Not enough elements in kernel shape. Expected: Not enough elements in dilations. Expected: Not enough elements in pads. Expected: /Users/runner/work/1/s/onnxruntime/core/providers/cpu/nn/conv_attributes.hInferOutputShapeInvalid input shape: /Users/runner/work/1/s/onnxruntime/core/providers/common.hComputePadAndOutputShapeDilation not supported for AutoPadType::SAME_UPPER or AutoPadType::SAME_LOWER.ComputePad: pad type not supported.kernel_shapestridesonnxruntime::ConvAttributes::ConvAttributes(const onnxruntime::OpKernelInfo &)auto_pad == AutoPadType::NOTSETA Conv/ConvTranspose node has both 'auto_pad' and 'pads' attributesdilationsgroupNOTSETVALIDSAME_UPPERSAME_LOWERonnxruntime::AutoPadType onnxruntime::StringToAutoPadType(const std::string &)T3ConvInteger/Users/runner/work/1/s/onnxruntime/core/providers/cpu/nn/conv_integer.ccvirtual onnxruntime::common::Status onnxruntime::ConvInteger::Compute(onnxruntime::OpKernelContext *) constIsScalarOr1ElementVector(X_Zero_Point)IsScalarOr1ElementVector(W_Zero_Point)ConvTranspose/Users/runner/work/1/s/onnxruntime/core/providers/cpu/nn/conv_transpose.ccDoConvTransposeoutput_paddingoutput_shapegroup count is <= 0filter number not equal to input channel number. filter_number: num_input_channels: Input channels is not divisible by group./Users/runner/work/1/s/onnxruntime/core/providers/cpu/nn/conv_transpose_attributes.hvoid onnxruntime::ConvTransposeAttributes::ComputePadsAndOutputShape(onnxruntime::TensorShape, int64_t, const std::vector<int64_t> &, const std::vector<int64_t> &, const std::vector<int64_t> &, const std::vector<int64_t> &, const int64_t, std::vector<int64_t> *, std::vector<int64_t> *) constdim_size > 0void onnxruntime::ConvTransposeAttributes::ComputeTransposePadAndOutputShape(const int64_t, const int64_t, const int64_t, const int64_t, const int64_t, onnxruntime::AutoPadType, int64_t *, int64_t *, int64_t *) const*out_size >= 0/Users/runner/work/1/s/onnxruntime/core/providers/cpu/nn/dropout_op.hvirtual onnxruntime::common::Status onnxruntime::Dropout<float, float>::Compute(onnxruntime::OpKernelContext *) const [T1 = float, T2 = float]!mask || mask->Shape() == X_shapefloat onnxruntime::(anonymous namespace)::GetRatioOrDefault(const onnxruntime::Tensor *) [T2 = float]ratio_tensor->Shape().Size() == 10.0f <= ratio_value && ratio_value < 1.0fvirtual onnxruntime::common::Status onnxruntime::Dropout<float, double>::Compute(onnxruntime::OpKernelContext *) const [T1 = float, T2 = double]float onnxruntime::(anonymous namespace)::GetRatioOrDefault(const onnxruntime::Tensor *) [T2 = double]virtual onnxruntime::common::Status onnxruntime::Dropout<double, float>::Compute(onnxruntime::OpKernelContext *) const [T1 = double, T2 = float]virtual onnxruntime::common::Status onnxruntime::Dropout<double, double>::Compute(onnxruntime::OpKernelContext *) const [T1 = double, T2 = double]Flatten/Users/runner/work/1/s/onnxruntime/core/providers/cpu/nn/flatten.honnxruntime::Flatten::Flatten(const onnxruntime::OpKernelInfo &)virtual onnxruntime::common::Status onnxruntime::Flatten::Compute(onnxruntime::OpKernelContext *) constgsl::narrow_cast<int64_t>(X_shape.NumDimensions()) >= axisInstanceNormalization/Users/runner/work/1/s/onnxruntime/core/providers/cpu/nn/instance_norm.ccepsilon/Users/runner/work/1/s/onnxruntime/core/providers/cpu/nn/instance_norm.honnxruntime::InstanceNorm<float>::InstanceNorm(const onnxruntime::OpKernelInfo &) [T = float]op_kernel_info.GetAttr<float>("epsilon", &epsilon_).IsOK()Invalid input data: number of dimensions is less than 3: Invalid input scale: number of dimensions is not 1: Mismatch between input data and scale: size of scale != input channel count vs. Invalid input B: number of dimensions is not 1: Mismatch between input data and B: size of B != input channel count LpNormalization/Users/runner/work/1/s/onnxruntime/core/providers/cpu/nn/lp_norm.honnxruntime::LpNorm<float>::LpNorm(const onnxruntime::OpKernelInfo &) [T = float]op_kernel_info.GetAttr<int64_t>("axis", &axis_).IsOK()op_kernel_info.GetAttr<int64_t>("p", &p_).IsOK()p_ == 1 || p_ == 2onnxruntime::LpNorm<double>::LpNorm(const onnxruntime::OpKernelInfo &) [T = double]input count mismatch/Users/runner/work/1/s/onnxruntime/core/providers/cpu/nn/lrn.ccvirtual onnxruntime::common::Status onnxruntime::LRN<float>::Compute(onnxruntime::OpKernelContext *) const [T = float]X->Shape().NumDimensions() == 4LRN/Users/runner/work/1/s/onnxruntime/core/providers/cpu/nn/lrn.honnxruntime::LRN<float>::LRN(const onnxruntime::OpKernelInfo &) [T = float]info.GetAttr<int64_t>("size", &size).IsOK()size_ > 0size_ % 2 == 1info.GetAttr<float>("alpha", &alpha_).IsOK()alpha_ > 0.0finfo.GetAttr<float>("beta", &beta_).IsOK()beta_ > 0.0f/Users/runner/work/1/s/onnxruntime/core/providers/cpu/nn/pool.ccInput dimension cannot be less than 3.Unsupported pooling size.kernel_shape num_dims is not compatible with X num_dims.AveragePoolMaxPoolLpPoolGlobalLpPoolGlobalAveragePoolGlobalMaxPool/Users/runner/work/1/s/onnxruntime/core/providers/cpu/nn/pool_attributes.hstd::vector<int64_t> onnxruntime::PoolAttributes::SetOutputSize(const onnxruntime::TensorShape &, int64_t, std::vector<int64_t> *) constinput_shape.Size() > 0 || input_shape[0] == 0Invalid input shape. Only N can be zero. Got:void onnxruntime::PoolAttributes::InferOutputSize(const std::vector<int64_t> &, std::vector<int64_t> *, std::vector<int64_t> *) constinput_dims.size() >= 2void onnxruntime::PoolAttributes::ComputeSizePadDilations(const int64_t, const int64_t, const int64_t, int64_t *, int64_t *, int64_t, int64_t *) constonnxruntime::PoolAttributes::PoolAttributes(const OpNodeProtoHelper<onnxruntime::ProtoHelperNodeContext> &, const std::string &, int)info.GetAttrs<int64_t>("kernel_shape", kernel_shape).IsOK()info.GetAttr<std::string>("auto_pad", &auto_padding).IsOK()ceil_modecount_include_padinfo.GetAttr<int64_t>("count_include_pad", &temp).IsOK()storage_orderinfo.GetAttr("storage_order", &storage_order).IsOK()kernel_shape[dim] > 0pads[dim] < kernel_shape[dim] && pads[dim + kernel_shape.size()] < kernel_shape[dim]strides.size() == kernel_shape.size()dilations.size() == kernel_shape.size()/Users/runner/work/1/s/onnxruntime/core/providers/cpu/nn/pool_base.hvoid onnxruntime::PoolProcessContext::init(const onnxruntime::OpKernelInfo &)info.GetAttr<int64_t>("p", &p_).IsOK()Unsupported pooling size : T4QLinearConv/Users/runner/work/1/s/onnxruntime/core/providers/cpu/nn/qlinearconv.ccvirtual onnxruntime::common::Status onnxruntime::QLinearConv::UseSharedPrePackedBuffers(std::vector<BufferUniquePtr> &, int, bool &)prepacked_buffers[0].get() == nullptrvirtual onnxruntime::common::Status onnxruntime::QLinearConv::Compute(onnxruntime::OpKernelContext *) constIsScalarOr1ElementVector(X_zero_point)QLinearConv : input zero point must be a scalar or 1D tensor of size 1IsScalarOr1ElementVector(Y_zero_point)QLinearConv : result zero point must be a scalar or 1D tensor of size 1IsScalarOr1ElementVector(X_scale)QLinearConv : input scale must be a scalar or 1D tensor of size 1IsScalarOr1ElementVector(Y_scale)QLinearConv : result scale must be a scalar or 1D tensor of size 1channels_lastMaxRoiPool/Users/runner/work/1/s/onnxruntime/core/providers/cpu/nn/roi_pool.ccvirtual onnxruntime::common::Status onnxruntime::RoiPool<float>::Compute(onnxruntime::OpKernelContext *) const [T = float]R->Shape()[1] == 5roi_batch_id >= 0roi_batch_id < batch_sizepooled_shape/Users/runner/work/1/s/onnxruntime/core/providers/cpu/nn/roi_pool.honnxruntime::RoiPool<float>::RoiPool(const onnxruntime::OpKernelInfo &) [T = float]info.GetAttrs<int64_t>("pooled_shape", pooled_shape).IsOK()pooled_shape.size() == 2pooled_height_ > 0pooled_width_ > 0spatial_scaleinfo.GetAttr<float>("spatial_scale", &spatial_scale_).IsOK()spatial_scale_ > 0Shrink/Users/runner/work/1/s/onnxruntime/core/providers/cpu/nn/shrink.honnxruntime::Shrink::Shrink(const onnxruntime::OpKernelInfo &)op_kernel_info.GetAttr<float>("bias", &bias_temp).IsOK()lambdop_kernel_info.GetAttr<float>("lambd", &lambd_temp).IsOK()StringNormalizer/Users/runner/work/1/s/onnxruntime/core/providers/cpu/nn/string_normalizer.cconnxruntime::StringNormalizer::StringNormalizer(const onnxruntime::OpKernelInfo &)LOWERUPPERlocalestopwords!sw.empty()wstr != wconv_errorSingle dimension value must be greater than 0Input dimensions are either[C > 0] or [1][C > 0] allowedInput contains invalid utf8 chars at: auto onnxruntime::string_normalizer::Locale::Locale(const std::string &)::(anonymous class)::operator()() constFailed to construct locale with name::Please, install necessary language-pack-XX and configure localeswstring_convert: from_bytes errorwstring_convert: to_bytes errorTfIdfVectorizer/Users/runner/work/1/s/onnxruntime/core/providers/cpu/nn/tfidfvectorizer.cconnxruntime::TfIdfVectorizer::TfIdfVectorizer(const onnxruntime::OpKernelInfo &)TFIDFTFIDFimpl_->weighting_criteria_ != kNonemode: is unrecognized, acceptable values are TF,IDF,TFIDFmin_gram_lengthimpl_->min_gram_length_ > 0Required min_gram_length must be positive: max_gram_lengthimpl_->max_gram_length_ >= impl_->min_gram_length_min_gram_length >= max_gram_length required: >= max_skip_countimpl_->max_skip_count_ >= 0max_skip_count must be non-negative: ngram_countsstatus.IsOK() && !impl_->ngram_counts_.empty()size_t(impl_->min_gram_length_) <= impl_->ngram_counts_.size()min_gram_length must be inbounds of ngram_counts: <= size_t(impl_->max_gram_length_) <= impl_->ngram_counts_.size()max_gram_length must be inbounds of ngram_counts: ngram_indexesstatus.IsOK() && !impl_->ngram_indexes_.empty()std::all_of(impl_->ngram_indexes_.cbegin(), impl_->ngram_indexes_.cend(), [](int64_t i) { return i >= 0; })weightsimpl_->weights_.size() == impl_->ngram_indexes_.size()Got weights of size: but ngram_indexes size: must be of equal sizepool_strings!pool_strings.empty()pool_int64sstatus.IsOK() && !pool_int64s.empty()end_idx >= start_idx && end_idx <= total_itemsn-gram counts out of bounds for -grams(items % ngram_size == 0)Number of items must compose whole Input shape must have either [C] or [B,C] dimensions with B > 0.size_t onnxruntime::ngram_details::PopulateGrams(ForwardIter, size_t, size_t, size_t, Map &) [K = long long, ForwardIter = const long long *, Map = std::__1::unordered_map<long long, std::__1::unique_ptr<onnxruntime::ngram_details::NgramPart<int64_t>, std::__1::default_delete<onnxruntime::ngram_details::NgramPart<int64_t> > >, std::__1::hash<long long>, std::__1::equal_to<long long>, std::__1::allocator<std::__1::pair<const long long, std::__1::unique_ptr<onnxruntime::ngram_details::NgramPart<int64_t>, std::__1::default_delete<onnxruntime::ngram_details::NgramPart<int64_t> > > > > >]p.first->second->id_ == 0Duplicate ngram detected, size: id: size_t onnxruntime::ngram_details::PopulateGrams(ForwardIter, size_t, size_t, size_t, Map &) [K = std::__1::basic_string<char>, ForwardIter = std::__1::__wrap_iter<std::__1::reference_wrapper<const std::__1::basic_string<char> > *>, Map = std::__1::unordered_map<std::__1::reference_wrapper<const std::__1::basic_string<char> >, std::__1::unique_ptr<onnxruntime::ngram_details::NgramPart<std::string>, std::__1::default_delete<onnxruntime::ngram_details::NgramPart<std::string> > >, std::__1::hash<std::__1::basic_string<char> >, std::__1::equal_to<std::__1::basic_string<char> >, std::__1::allocator<std::__1::pair<const std::__1::reference_wrapper<const std::__1::basic_string<char> >, std::__1::unique_ptr<onnxruntime::ngram_details::NgramPart<std::string>, std::__1::default_delete<onnxruntime::ngram_details::NgramPart<std::string> > > > > >]NonMaxSuppression/Users/runner/work/1/s/onnxruntime/core/providers/cpu/object_detection/non_max_suppression.ccstatic onnxruntime::common::Status onnxruntime::NonMaxSuppressionBase::PrepareCompute(onnxruntime::OpKernelContext *, onnxruntime::PrepareContext &)boxes_tensorscores_tensorboxes must be a 3D tensor.scores must be a 3D tensor.boxes and scores should have same num_batches.boxes and scores should have same spatial_dimension.The most inner dimension in boxes must have 4 data.GetThresholdsFromInputsiou_threshold must be in range [0, 1].virtual onnxruntime::common::Status onnxruntime::NonMaxSuppression::Compute(onnxruntime::OpKernelContext *) constoutput != nullptrcenter_point_box/Users/runner/work/1/s/onnxruntime/core/providers/cpu/object_detection/non_max_suppression.honnxruntime::NonMaxSuppressionBase::NonMaxSuppressionBase(const onnxruntime::OpKernelInfo &)0 == center_point_box_ || 1 == center_point_box_RoiAlignNull input X ptrNull rois_ptrNull batch_indices_ptrNumber of dimensions for batch indices should be exactly 1Number of dimensions for rois should be exactly Second dimension for rois should be exactly First dimension (num_rois) of batch_indices and rois don't matchavg/Users/runner/work/1/s/onnxruntime/core/providers/cpu/object_detection/roialign.honnxruntime::RoiAlignBase::RoiAlignBase(const onnxruntime::OpKernelInfo &)Invalid mode of value specified. It should be either avg or maxoutput_heightoutput_widthsampling_ratiosampling_ratio_ >= 0Sampling ratio should be >=0, but it was ReduceL1ReduceL2ReduceLogSumReduceLogSumExpReduceMaxReduceMeanReduceMinReduceProdReduceSumReduceSumSquareArgMaxArgMin/Users/runner/work/1/s/onnxruntime/core/providers/cpu/reduction/reduction_ops.ccvoid onnxruntime::ResultsNoTransposePrepareForReduce::ValidateNotEmpty()last_loop_red_size > 0last_loop_size > 0projected_index.size() > 0void onnxruntime::ValidateNoTransposeReduce(int64_t)count == 1void onnxruntime::ValidateCommonFastReduce(const onnxruntime::Tensor *)keepdims/Users/runner/work/1/s/onnxruntime/core/providers/cpu/reduction/reduction_ops.honnxruntime::ReduceKernelBase<false>::ReduceKernelBase(const onnxruntime::OpKernelInfo &, optional<int64_t>) [allow_multi_axes = false]info.GetAttr("keepdims", &keepdims).IsOK()noop_with_empty_axesselect_last_indexvoid onnxruntime::ValidateFastReduceKR(const std::vector<int64_t> &, const onnxruntime::Tensor &)fast_shape.size() == 2fast_shape[0] == output.Shape().Size()void onnxruntime::ValidateFastReduceRK(const std::vector<int64_t> &, const onnxruntime::Tensor &)fast_shape[1] == output.Shape().Size()void onnxruntime::ValidateFastReduceKRK(const std::vector<int64_t> &, const onnxruntime::Tensor &)fast_shape.size() == 3fast_shape[0] * fast_shape[2] == output.Shape().Size()void onnxruntime::ValidateMustBeOverloaded()void onnxruntime::ValidateKeepDims(const onnxruntime::TensorShape &, int64_t)Can't reduce on dim with value of 0 if 'keepdims' is false. Invalid output shape would be produced. input_shape:onnxruntime::ReduceKernelBase<true>::ReduceKernelBase(const onnxruntime::OpKernelInfo &, optional<int64_t>) [allow_multi_axes = true]GRU/Users/runner/work/1/s/onnxruntime/core/providers/cpu/rnn/deep_cpu_gru.ccvirtual onnxruntime::common::Status onnxruntime::DeepCpuGruOp::Compute(onnxruntime::OpKernelContext *) constInvalid data type for GRU operator of /Users/runner/work/1/s/onnxruntime/core/providers/cpu/rnn/deep_cpu_gru.honnxruntime::DeepCpuGruOp::DeepCpuGruOp(const onnxruntime::OpKernelInfo &)info.GetAttr("direction", &direction).IsOK()linear_before_resetinfo.GetAttr("linear_before_reset", &int64_value).IsOK()hidden_sizeinfo.GetAttr("hidden_size", &int64_value).IsOK() && int64_value > 0activationsactivation_alphaactivation_betaclip_ > 0.fsigmoidtanhactivation_func_names.size() == static_cast<size_t>(num_directions_) * 2layoutlayout_ == 0Batchwise recurrent operations (layout == 1) are not supported. If you need support create a github issue with justification.forwardreversebidirectional/Users/runner/work/1/s/onnxruntime/core/providers/cpu/rnn/rnn_helpers.honnxruntime::rnn::detail::Direction onnxruntime::rnn::detail::MakeDirection(const std::string &)Invalid 'direction' argument of ''. Must be one of 'forward', 'reverse', or 'bidirectional'.ComputeImplgsl::span<const T> onnxruntime::Tensor::DataAsSpan() const [T = float]gsl::span<const T> onnxruntime::Tensor::DataAsSpan() const [T = int]gsl::span<T> onnxruntime::Tensor::MutableDataAsSpan() [T = float]void onnxruntime::rnn::detail::ComputeGemm(const int, const int, const int, const float, TSpanAIter, TSpanAIter, const int, TSpanBIter, TSpanBIter, const int, const float, TSpanCIter, TSpanCIter, const int, concurrency::ThreadPool *) [TSpanAIter = const float *, TSpanBIter = const float *, TSpanCIter = float *]lda >= K && ldb >= K && ldc >= NA + (M * lda - (lda - K)) <= A_endB + (N * ldb - (ldb - K)) <= B_endC + (M * ldc - (ldc - N)) <= C_endconst T *onnxruntime::rnn::detail::SafeRawConstPointer(typename gsl::span<T>::const_iterator, typename gsl::span<T>::const_iterator, size_t) [T = float]cur + size <= endT *onnxruntime::rnn::detail::SafeRawPointer(typename gsl::span<T>, size_t, size_t) [T = float]offset + size <= size_t(span.size())T *onnxruntime::rnn::detail::SafeRawPointer(typename gsl::span<T>::iterator, typename gsl::span<T>::iterator, size_t) [T = float]void onnxruntime::rnn::detail::ComputeGemm(const int, const int, const int, const float, TSpanAIter, TSpanAIter, const int, TSpanBIter, TSpanBIter, const int, const float, TSpanCIter, TSpanCIter, const int, concurrency::ThreadPool *) [TSpanAIter = float *, TSpanBIter = const float *, TSpanCIter = float *]LSTM/Users/runner/work/1/s/onnxruntime/core/providers/cpu/rnn/deep_cpu_lstm.ccPrePackvirtual onnxruntime::common::Status onnxruntime::DeepCpuLstmOp::Compute(onnxruntime::OpKernelContext *) constInvalid data type for LSTM operator of /Users/runner/work/1/s/onnxruntime/core/providers/cpu/rnn/lstm_base.honnxruntime::LSTMBase::LSTMBase(const onnxruntime::OpKernelInfo &)input_forgetactivation_func_names.size() == static_cast<size_t>(num_directions_) * 3/Users/runner/work/1/s/onnxruntime/core/providers/cpu/rnn/lstm_base.ccRNN/Users/runner/work/1/s/onnxruntime/core/providers/cpu/rnn/rnn.ccAffine/Users/runner/work/1/s/onnxruntime/core/providers/cpu/rnn/rnn.honnxruntime::RNN<float>::RNN(const onnxruntime::OpKernelInfo &) [T = float]info.GetAttr("direction", &direction_).IsOK()allowed_directions.find(direction_) != allowed_directions.end()info.GetAttrs("activations", activations_).IsOK()info.GetAttr("hidden_size", &hidden_size_).IsOK()activations_.size() == static_cast<size_t>(num_directions)allowed_activations.find(activations_[direction]) != allowed_activations.end()RNN op: Invalid activation attribute - Input X must have 3 dimensions only. Actual:Input W must have shape {*}. Actual:Input R must have shape {Input B must have shape {Input sequence_lens must have shape {Invalid value/s in sequence_lens. All values must be > 0 and < seq_length. seq_length=Input initial_h must have shape {affinereluleakyreluthresholdedreluscaledtanhhardsigmoidelusoftsignsoftplus/Users/runner/work/1/s/onnxruntime/core/providers/cpu/rnn/rnn_helpers.ccstd::string onnxruntime::rnn::detail::NormalizeActivationArgumentAndGetAlphaBetaCount(const std::string &, std::vector<float>::const_iterator &, const std::vector<float>::const_iterator &, std::vector<float>::const_iterator &, const std::vector<float>::const_iterator &, float &, float &)Expecting activation to be one of Affine, Relu, LeakyRelu, ThresholdedRelu, Tanh, ScaledTanh, Sigmoid, HardSigmoid, Elu, Softsign, Softplus. Got void onnxruntime::rnn::detail::ComputeGemm(const int, const int, const int, const float, const float *, const float *, const GemmWeights<float> &, const float, float *, float *, const int, uint8_t *, int32_t *, concurrency::ThreadPool *)A + (M * K) <= A_endvoid onnxruntime::rnn::detail::ComputeGemm(const int, const int, const int, const float, const float *, const float *, const GemmWeights<uint8_t> &, const float, float *, float *, const int, uint8_t *, int32_t *, concurrency::ThreadPool *)weights.quant_para_alpha == 1.0f && (beta == 0.0f || beta == 1.0f)Quantized GEMM only support alpha equal to 1.0f and beta equal to 0.0f or 1.0fonnxruntime::rnn::detail::deepcpu::ActivationFuncPtr onnxruntime::rnn::detail::deepcpu::ActivationFuncByName(const std::string &)Invalid activation function of onnxruntime::rnn::detail::deepcpu::LstmMergeGatesFuncPtr onnxruntime::rnn::detail::deepcpu::LstmMergeGatesFuncByName(const std::string &)Invalid LSTM merge activation function of onnxruntime::rnn::detail::deepcpu::GruResetGateFuncPtr onnxruntime::rnn::detail::deepcpu::GruResetGateFuncByName(const std::string &)Invalid GRU reset gate activation function: onnxruntime::rnn::detail::deepcpu::GruOutputGateFuncPtr onnxruntime::rnn::detail::deepcpu::GruOutputGateFuncByName(const std::string &)Invalid GRU hidden gate activation function: rows[const T *onnxruntime::rnn::detail::SafeRawConstPointer(gsl::span<T>, size_t, size_t) [T = const float]const T *onnxruntime::rnn::detail::SafeRawConstPointer(gsl::span<T>, size_t, size_t) [T = float]ConcatFromSequence/Users/runner/work/1/s/onnxruntime/core/providers/cpu/sequence/concat_from_sequence.ccvirtual onnxruntime::common::Status onnxruntime::ConcatFromSequence::Compute(onnxruntime::OpKernelContext *) constSSequenceLength/Users/runner/work/1/s/onnxruntime/core/providers/cpu/sequence/sequence_ops.ccvirtual onnxruntime::common::Status onnxruntime::SequenceLength::Compute(onnxruntime::OpKernelContext *) constY != nullptrSequenceAtvirtual onnxruntime::common::Status onnxruntime::SequenceAt::Compute(onnxruntime::OpKernelContext *) constI != nullptrInvalid sequence index () specified for sequence of size (SequenceEmptyvirtual onnxruntime::common::Status onnxruntime::SequenceEmpty::Compute(onnxruntime::OpKernelContext *) constUnsupported 'dtype' value: SequenceInsertCreateCopyAndAppendCpuTensorvirtual onnxruntime::common::Status onnxruntime::SequenceInsert::Compute(onnxruntime::OpKernelContext *) constS != nullptrData type of the input tensor MUST be same as that of the input sequence. Sequence data type (), input tensor data type (SequenceErasevirtual onnxruntime::common::Status onnxruntime::SequenceErase::Compute(onnxruntime::OpKernelContext *) constSequenceConstructvirtual onnxruntime::common::Status onnxruntime::SequenceConstruct::Compute(onnxruntime::OpKernelContext *) constnum_inputs >= 1Violation of the requirment that all input tensors must have the same data type.SplitToSequenceSplitToSequence operator does not support split_size_sum () != split_dim_size (int64_t onnxruntime::GetSeqIdx(const onnxruntime::Tensor &)onnxruntime::common::Status onnxruntime::SplitToSequence::ComputeImpl(onnxruntime::OpKernelContext &, const onnxruntime::Tensor &, const onnxruntime::Tensor *) const [T = float]split_scalar > 0std::all_of(split_sizes.cbegin(), split_sizes.cend(), [](int64_t value) { return value >= 0; })int64_t onnxruntime::GetScalarSplitInput(const onnxruntime::Tensor &)Invalid data type for split tensor void onnxruntime::GetSplitSizesInput(const onnxruntime::Tensor &, std::vector<int64_t> &)onnxruntime::common::Status onnxruntime::SplitToSequence::ComputeImpl(onnxruntime::OpKernelContext &, const onnxruntime::Tensor &, const onnxruntime::Tensor *) const [T = double]onnxruntime::common::Status onnxruntime::SplitToSequence::ComputeImpl(onnxruntime::OpKernelContext &, const onnxruntime::Tensor &, const onnxruntime::Tensor *) const [T = int]onnxruntime::common::Status onnxruntime::SplitToSequence::ComputeImpl(onnxruntime::OpKernelContext &, const onnxruntime::Tensor &, const onnxruntime::Tensor *) const [T = long long]onnxruntime::common::Status onnxruntime::SplitToSequence::ComputeImpl(onnxruntime::OpKernelContext &, const onnxruntime::Tensor &, const onnxruntime::Tensor *) const [T = std::__1::basic_string<char>]T2Cast/Users/runner/work/1/s/onnxruntime/core/providers/cpu/tensor/cast_op.cconnxruntime::(anonymous namespace)::Cast::Cast(const onnxruntime::OpKernelInfo &)NaN-INFINF%.8gtypename std::enable_if<std::is_floating_point<SrcType>::value, void>::type onnxruntime::(anonymous namespace)::CastToString(const SrcType &, std::string &) [SrcType = float]snprintf_result > 0snprintf() failed with return value: snprintf_result > 0 && gsl::narrow_cast<size_t>(snprintf_result) == buffer_span.size() - 1typename std::enable_if<std::is_floating_point<SrcType>::value, void>::type onnxruntime::(anonymous namespace)::CastToString(const SrcType &, std::string &) [SrcType = double]Compress/Users/runner/work/1/s/onnxruntime/core/providers/cpu/tensor/compress.ccvirtual onnxruntime::common::Status onnxruntime::Compress::Compute(onnxruntime::OpKernelContext *) constaxes_right_stride >= 0 && static_cast<uint64_t>(axes_right_stride) < std::numeric_limits<size_t>::max()Concat/Users/runner/work/1/s/onnxruntime/core/providers/cpu/tensor/concat.ccPrepareForComputeCannot concatenate scalarsonnxruntime::common::Status onnxruntime::ConcatBase::PrepareForCompute(onnxruntime::OpKernelContext *, const std::vector<const Tensor *> &, onnxruntime::Prepare &) constinputs_n_rank == inputs_0_rankRanks of input data are different, cannot concatenate them. expected rank: got: Non concat axis dimensions must match: Axis has mismatched dimensions of Data type mismatch/Users/runner/work/1/s/onnxruntime/core/providers/cpu/tensor/concatbase.honnxruntime::ConcatBase::ConcatBase(const onnxruntime::OpKernelInfo &, bool)DynamicQuantizeLinear/Users/runner/work/1/s/onnxruntime/core/providers/cpu/tensor/dynamicquantizelinear.ccvirtual onnxruntime::common::Status onnxruntime::DynamicQuantizeLinear<unsigned char>::Compute(onnxruntime::OpKernelContext *) const [T = unsigned char]x_ptr != nullptrEyeLikedtypeGather/Users/runner/work/1/s/onnxruntime/core/providers/cpu/tensor/gather.cc/Users/runner/work/1/s/onnxruntime/core/providers/cpu/tensor/gatherbase.honnxruntime::GatherBase::GatherBase(const onnxruntime::OpKernelInfo &)info.GetAttr<int64_t>("axis", &axis_).IsOK()indices element out of data bounds, idx= must be within the inclusive range [GatherElementsGatherElements op: Rank of input 'data' needs to be equal to rank of input 'indices'GatherElements op: 'indices' shape should have values within bounds of 'data' shape. Invalid value in indices shape is: GatherElements op: Data type of input 'data' should match the data type of the output/Users/runner/work/1/s/onnxruntime/core/providers/cpu/tensor/gather_elements.honnxruntime::GatherElements::GatherElements(const onnxruntime::OpKernelInfo &)/Users/runner/work/1/s/onnxruntime/core/providers/cpu/tensor/gather_elements.ccauto onnxruntime::core_impl(const onnxruntime::Tensor *, const onnxruntime::Tensor *, onnxruntime::Tensor *, int64_t, concurrency::ThreadPool *)::(anonymous class)::operator()(ptrdiff_t) constGatherElements op: Value in indices must be within bounds [ , ]. Actual value is invalid index found, index = GatherND/Users/runner/work/1/s/onnxruntime/core/providers/cpu/tensor/gather_nd.ccvirtual onnxruntime::common::Status onnxruntime::GatherND::Compute(onnxruntime::OpKernelContext *) constinput_tensor != nullptr && indices_tensor != nullptrlast dimension of indices must not be larger than rank of input tensorbatch_dimsDropoutIdentity/Users/runner/work/1/s/onnxruntime/core/providers/cpu/tensor/identity_op.hvirtual onnxruntime::common::Status onnxruntime::IdentityOp<true>::Compute(onnxruntime::OpKernelContext *) const [is_dropout = true]const T *onnxruntime::OpKernelContext::Input(int) const [T = onnxruntime::TensorSeq]virtual onnxruntime::common::Status onnxruntime::IdentityOp<false>::Compute(onnxruntime::OpKernelContext *) const [is_dropout = false]IsInfdetect_positive/Users/runner/work/1/s/onnxruntime/core/providers/cpu/tensor/isinf.cconnxruntime::IsInf::IsInf(const onnxruntime::OpKernelInfo &)detect_negativeIsNaNNull input ptrMeanVarianceNormalizationInput is expected to have four dimensions corresponding to [N,C,H,W]NonZero/Users/runner/work/1/s/onnxruntime/core/providers/cpu/tensor/nonzero_op.ccvirtual onnxruntime::common::Status onnxruntime::NonZero<bool>::Compute(onnxruntime::OpKernelContext *) const [T = bool]virtual onnxruntime::common::Status onnxruntime::NonZero<unsigned char>::Compute(onnxruntime::OpKernelContext *) const [T = unsigned char]virtual onnxruntime::common::Status onnxruntime::NonZero<int>::Compute(onnxruntime::OpKernelContext *) const [T = int]virtual onnxruntime::common::Status onnxruntime::NonZero<long long>::Compute(onnxruntime::OpKernelContext *) const [T = long long]virtual onnxruntime::common::Status onnxruntime::NonZero<float>::Compute(onnxruntime::OpKernelContext *) const [T = float]OneHotInvalid argument for depth; it's not a scalar.Invalid argument for values; either it's rank is more than 1 or it has more than 2 elements/Users/runner/work/1/s/onnxruntime/core/providers/cpu/tensor/onehot.ccDepth is negative.PadCannot use 'reflect' mode to pad dimension with a value of 0. Input shape:Unexpected mode of /Users/runner/work/1/s/onnxruntime/core/providers/cpu/tensor/pad.ccvirtual onnxruntime::common::Status onnxruntime::Pad::Compute(onnxruntime::OpKernelContext *) constpads_tensor.IsDataType<int64_t>()pads_tensor_dims.size() == 1 || (pads_tensor_dims.size() == 2 && pads_tensor_dims[0] == 1)Pads tensor should be a 1D tensor of shape [2 * input_rank] or a 2D tensor of shape [1, 2 * input_rank]pads_size == 2 * data_rankPads tensor size should be equal to twice the input dimension count value_tensor->DataType() == data_type && value_tensor->Shape().Size() == 1Value tensor should be a 1D tensor of size 1 with the same type as that of the input tensorUnsupported input data type of valueconstantreflectedge/Users/runner/work/1/s/onnxruntime/core/providers/cpu/tensor/padbase.honnxruntime::PadBase::PadBase(const onnxruntime::OpKernelInfo &)onnxruntime::PadValue onnxruntime::PadValueFromFloat(float, onnxruntime::MLDataType)onnxruntime::common::Status onnxruntime::PadImpl(onnxruntime::OpKernelContext *, const std::vector<int64_t> &, const std::vector<int64_t> &, const onnxruntime::Mode &, T) [T = unsigned int]data_rank > 0data_rank * 2 == pads.size()PadInputWithDimValueOfZero/Users/runner/work/1/s/onnxruntime/core/providers/cpu/tensor/utils.honnxruntime::SliceSkips::SliceSkips(const onnxruntime::TensorShape &, gsl::span<const int64_t>, gsl::span<const int64_t>)dims.size() == extents.size() && dims.size() >= steps.size()void onnxruntime::SliceIteratorBase::Init(const std::vector<int64_t> &, gsl::span<const int64_t>, gsl::span<const int64_t>)dims.size() == starts.size() && dims.size() == extents_.size() && dims.size() >= steps.size()onnxruntime::common::Status onnxruntime::PadImpl(onnxruntime::OpKernelContext *, const std::vector<int64_t> &, const std::vector<int64_t> &, const onnxruntime::Mode &, T) [T = unsigned long long]onnxruntime::common::Status onnxruntime::PadImpl(onnxruntime::OpKernelContext *, const std::vector<int64_t> &, const std::vector<int64_t> &, const onnxruntime::Mode &, T) [T = unsigned char]DequantizeLinearQuantizeLinear/Users/runner/work/1/s/onnxruntime/core/providers/cpu/tensor/quantize_linear.ccvoid onnxruntime::PrepareForQDQ(const onnxruntime::TensorShape &, const onnxruntime::Tensor &, const onnxruntime::Tensor *, int64_t, int64_t &, int64_t &, int64_t &)zero_point_ptr == nullptr || IsScalarOr1ElementVector(zero_point_ptr)scale.Shape().NumDimensions() == 1 && scale.Shape()[0] == broadcast_dimscale must be 1D tensor with size zero_point_ptr == nullptr || (zero_point_ptr->Shape().NumDimensions() == 1 && zero_point_ptr->Shape()[0] == broadcast_dim)x_zero_point must be null or 1D tensor with size virtual onnxruntime::common::Status onnxruntime::DequantizeLinear<int>::Compute(onnxruntime::OpKernelContext *) const [T = int]zero_point == nullptr || std::all_of(zero_point, zero_point + x_zero_point->Shape().Size(), [](int32_t zp) { return zp == 0; })DequantizeLinear with type int32 should have no zero point or all zero points should be 0Reshapeshape/Users/runner/work/1/s/onnxruntime/core/providers/cpu/tensor/reshape.honnxruntime::Reshape_1::Reshape_1(const onnxruntime::OpKernelInfo &)/Users/runner/work/1/s/onnxruntime/core/providers/cpu/tensor/reshape_helper.honnxruntime::ReshapeHelper::ReshapeHelper(const onnxruntime::TensorShape &, std::vector<int64_t> &, bool)requested_shape[i] >= -1A dimension cannot be less than -1, got !allow_zeroThe input tensor cannot be reshaped to the requested shape. Input shape:, requested shape:unknown_dim == -1i < input_shape.NumDimensions()The dimension with value zero exceeds the dimension size of the input tensor.size != 0 && (input_shape.Size() % size) == 0gsl::narrow_cast<int64_t>(input_shape.Size()) == sizeallowzerovirtual onnxruntime::common::Status onnxruntime::Reshape::Compute(onnxruntime::OpKernelContext *) constshapeTensor->Shape().NumDimensions() == 1Resize/Users/runner/work/1/s/onnxruntime/core/providers/cpu/tensor/upsample.honnxruntime::UpsampleBase::UpsampleBase(const onnxruntime::OpKernelInfo &)info.GetAttr<std::string>("mode", &mode).IsOK()scalesinfo.GetAttrs<float>("scales", scales_).IsOK()extrapolation_valuecoordinate_transformation_modehalf_pixelasymmetricUpsampleBase`tf_half_pixel_for_nn` is deprecated since opset 13, yet this opset model uses the deprecated attributenearest_moderound_prefer_floorcubic_coeff_aexclude_outsideexclude_outside can be set to 1 only when mode is CUBIC. Current mode is set to nearestlinearcubiconnxruntime::UpsampleMode onnxruntime::UpsampleBase::StringToUpsampleMode(const std::string &)mode attribute is . It can only be (default) or or void onnxruntime::UpsampleBase::ScalesValidation(const std::vector<float> &, const onnxruntime::UpsampleMode) constscale >= 1scale > 0scales.size() == 2 || (scales.size() == 4 && scales[0] == 1 && scales[1] == 1) || scales.size() == 3 || (scales.size() == 5 && scales[0] == 1 && scales[1] == 1)'Linear' mode only support 2-D inputs or 3-D inputs ('Bilinear', 'Trilinear') or 4-D inputs or 5-D inputs with the corresponding outermost 2 scale values being 1 in the Resize operatorUpsample operatorscales.size() == 2 || (scales.size() == 4 && scales[0] == 1 && scales[1] == 1)'Cubic' mode only support 2-D inputs ('Bicubic') or 4-D inputs with the corresponding outermost 2 scale values being 1 in the pytorch_half_pixeltf_half_pixel_for_nnalign_cornerstf_crop_and_resizeonnxruntime::ResizeCoordinateTransformationMode onnxruntime::UpsampleBase::StringToCoordinateTransformationMode(const std::string &)coordinate_transform_mode:[] is not supportted!round_prefer_ceilfloorceilonnxruntime::ResizeNearestMode onnxruntime::UpsampleBase::StringToNearestMode(const std::string &)nearest_mode:[] is not supported!void onnxruntime::UpsampleBase::ParseScalesData(const onnxruntime::Tensor *, std::vector<float> &) constscales_size > 0ReverseSequencesequence_lens shape must be {batch_size}. Got:. batch_size=/Users/runner/work/1/s/onnxruntime/core/providers/cpu/tensor/reverse_sequence.ccvirtual onnxruntime::common::Status onnxruntime::ReverseSequenceOp::Compute(onnxruntime::OpKernelContext *) constUnknown tensor type of batch_axis/Users/runner/work/1/s/onnxruntime/core/providers/cpu/tensor/reverse_sequence.honnxruntime::ReverseSequenceOp::ReverseSequenceOp(const onnxruntime::OpKernelInfo &)info.GetAttr<int64_t>("batch_axis", &batch_axis).IsOK()time_axisinfo.GetAttr<int64_t>("time_axis", &time_axis).IsOK()batch_axis < 2Invalid batch_axis of . Must be 0 or 1time_axis < 2Invalid time_axis of batch_axis != time_axistime_axis and batch_axis must have different values but both are Invalid sequence length: . Value must be in range [0,gsl::span<const T> onnxruntime::Tensor::DataAsSpan() const [T = bool]gsl::span<T> onnxruntime::Tensor::MutableDataAsSpan() [T = bool]gsl::span<const T> onnxruntime::Tensor::DataAsSpan() const [T = double]gsl::span<T> onnxruntime::Tensor::MutableDataAsSpan() [T = double]gsl::span<const T> onnxruntime::Tensor::DataAsSpan() const [T = unsigned char]gsl::span<T> onnxruntime::Tensor::MutableDataAsSpan() [T = unsigned char]gsl::span<const T> onnxruntime::Tensor::DataAsSpan() const [T = unsigned short]gsl::span<T> onnxruntime::Tensor::MutableDataAsSpan() [T = unsigned short]gsl::span<const T> onnxruntime::Tensor::DataAsSpan() const [T = short]gsl::span<T> onnxruntime::Tensor::MutableDataAsSpan() [T = short]gsl::span<T> onnxruntime::Tensor::MutableDataAsSpan() [T = int]gsl::span<const T> onnxruntime::Tensor::DataAsSpan() const [T = unsigned int]gsl::span<T> onnxruntime::Tensor::MutableDataAsSpan() [T = unsigned int]gsl::span<const T> onnxruntime::Tensor::DataAsSpan() const [T = unsigned long long]gsl::span<T> onnxruntime::Tensor::MutableDataAsSpan() [T = unsigned long long]gsl::span<const T> onnxruntime::Tensor::DataAsSpan() const [T = onnxruntime::MLFloat16]gsl::span<T> onnxruntime::Tensor::MutableDataAsSpan() [T = onnxruntime::MLFloat16]gsl::span<const T> onnxruntime::Tensor::DataAsSpan() const [T = onnxruntime::BFloat16]gsl::span<T> onnxruntime::Tensor::MutableDataAsSpan() [T = onnxruntime::BFloat16]ScatterScatterElements/Users/runner/work/1/s/onnxruntime/core/providers/cpu/tensor/scatter.cconnxruntime::Scatter<onnxruntime::TypeList<float, double, long long, unsigned long long, int, unsigned int, short, unsigned short, signed char, unsigned char, onnxruntime::MLFloat16, onnxruntime::BFloat16, bool, std::__1::basic_string<char> > >::Scatter(const onnxruntime::OpKernelInfo &) [EnabledDataTypes = onnxruntime::TypeList<float, double, long long, unsigned long long, int, unsigned int, short, unsigned short, signed char, unsigned char, onnxruntime::MLFloat16, onnxruntime::BFloat16, bool, std::__1::basic_string<char> >]Indices vs updates dimensions differs at position= vs Indices must have the same rank as Input. Indices rank=. Input rank=Indices dim= at pos= is greater than input dim=ScatterNDinput tensor and indices tensor must has rank larger than 0. input shape: , indices shape: updates tensor should have shape equal to indices.shape[:-1] + data.shape[indices.shape[-1]:]. updates shape: , data shape: /Users/runner/work/1/s/onnxruntime/core/providers/cpu/tensor/scatter_nd.ccinvalid indice found, indice = SizeSliceTind'axes' has an axis outside of the tensor dimension count'axes' has duplicates'step' value cannot be 0/Users/runner/work/1/s/onnxruntime/core/providers/cpu/tensor/slice.ccFillVectorsFromInputStarts must be a 1-D arrayEnds must be a 1-D arrayStarts and ends shape mismatchStarts and axes shape mismatchStarts and steps shape mismatchData type for starts and ends inputs' is not supported in this build. Got starts/Users/runner/work/1/s/onnxruntime/core/providers/cpu/tensor/slice.honnxruntime::SliceBase::SliceBase(const onnxruntime::OpKernelInfo &, bool)has_starts && has_ends && attr_starts_.size() == attr_ends_.size()!has_axes || attr_axes_.size() == attr_starts_.size()Invalid axes attribute, axes attribute (if present) should have the same size as starts/ends attributesauto onnxruntime::SliceImpl(onnxruntime::OpKernelContext *, const onnxruntime::Tensor &, SliceOp::PrepareForComputeMetadata &)::(anonymous class)::operator()(SliceIterator<T> &) constoutput == output_endvoid *onnxruntime::SliceIteratorBase::CopyInnermostAxisNonSolitaryInnerStep(void *)Unexpected element size of SpaceToDepthDepthToSpace/Users/runner/work/1/s/onnxruntime/core/providers/cpu/tensor/space_depth_ops.ccvirtual onnxruntime::common::Status onnxruntime::SpaceToDepth<float>::Compute(onnxruntime::OpKernelContext *) const [T = float]input_shape.NumDimensions() == 4input_height % this->blocksize_ == 0input_width % this->blocksize_ == 0virtual onnxruntime::common::Status onnxruntime::DepthToSpace<float>::Compute(onnxruntime::OpKernelContext *) const [T = float]input.Shape().NumDimensions() == 4input_depth % (blocksize_ * blocksize_) == 0blocksize/Users/runner/work/1/s/onnxruntime/core/providers/cpu/tensor/space_depth_ops.honnxruntime::SpaceDepthBase::SpaceDepthBase(const onnxruntime::OpKernelInfo &)info.GetAttr("blocksize", &blocksize_).IsOK()CRDDCRonnxruntime::DepthToSpace<float>::DepthToSpace(const onnxruntime::OpKernelInfo &) [T = float]SplitInput cannot be split evenly on selected axis. Input shape= Axis= NumOutputs=Cannot split using values in 'split' attribute. Axis= Input shape= Num entries in 'split' (must equal number of outputs) was Sum of sizes in 'split' (must equal size of selected axis) was /Users/runner/work/1/s/onnxruntime/core/providers/cpu/tensor/split.ccvirtual onnxruntime::common::Status onnxruntime::Split::Compute(onnxruntime::OpKernelContext *) constSplit operator does not support yetsplit/Users/runner/work/1/s/onnxruntime/core/providers/cpu/tensor/split.honnxruntime::SplitBase::SplitBase(const onnxruntime::OpKernelInfo &)std::all_of(split_sizes_.cbegin(), split_sizes_.cend(), [](int64_t value) { return value >= 0; })onnxruntime::common::Status onnxruntime::Split::ComputeImpl(onnxruntime::OpKernelContext &, const onnxruntime::Tensor &) const [T = float]split_tensor->Shape().NumDimensions() == 1onnxruntime::common::Status onnxruntime::Split::ComputeImpl(onnxruntime::OpKernelContext &, const onnxruntime::Tensor &) const [T = int]onnxruntime::common::Status onnxruntime::Split::ComputeImpl(onnxruntime::OpKernelContext &, const onnxruntime::Tensor &) const [T = long long]onnxruntime::common::Status onnxruntime::Split::ComputeImpl(onnxruntime::OpKernelContext &, const onnxruntime::Tensor &) const [T = unsigned char]onnxruntime::common::Status onnxruntime::Split::ComputeImpl(onnxruntime::OpKernelContext &, const onnxruntime::Tensor &) const [T = std::__1::basic_string<char>]Squeeze/Users/runner/work/1/s/onnxruntime/core/providers/cpu/tensor/squeeze.hvirtual onnxruntime::common::Status onnxruntime::Squeeze::Compute(onnxruntime::OpKernelContext *) constaxes_tensor != nullptraxes_tensor->Shape().NumDimensions() == 1static std::vector<int64_t> onnxruntime::SqueezeBase::ComputeOutputShape(const onnxruntime::TensorShape &, const std::vector<int64_t> &)input_shape[i] == 1Dimension of input must be 1 instead of . shape=TileInput count of Tile OP mismatch, the first one is emptyInput count of Tile OP mismatch, the second one is emptythe tensor to be tiled using Tile OP must be atleast 1 dimensional'repeat' input tensor must be 1 dimensional'repeat' input tensor must have the same length as the 'input' tensor/Users/runner/work/1/s/onnxruntime/core/providers/cpu/tensor/tile.ccvirtual onnxruntime::common::Status onnxruntime::Tile::Compute(onnxruntime::OpKernelContext *) const!input_tensor.IsDataType<std::string>()Tile doesn't have an implementation yet for the type: Transpose of element size not supported in this build. Size=Mismatched data types between input and output Tensors. /Users/runner/work/1/s/onnxruntime/core/providers/cpu/tensor/transpose.ccvirtual onnxruntime::common::Status onnxruntime::Transpose::Compute(onnxruntime::OpKernelContext *) constinput_tensor_ptr != nullptrTransposevoid onnxruntime::DoTransposeEltWise(int64_t, const std::vector<int64_t> &, size_t, const std::vector<size_t> &, const std::string *, std::string *)num_axes > 0(local_source >= source) && (local_source < source + num_blocks)void onnxruntime::IncrementIndexAndComputeOffsetSetup(onnxruntime::MultiIndex &, size_t, const std::vector<int64_t> &, const std::vector<size_t> &, size_t)naxes > 0Method IncrementIndexAndComputeOffset assumes this value is strictly positive.void onnxruntime::DoTransposeImpl(int64_t, const std::vector<int64_t> &, size_t, size_t, const std::vector<size_t> &, const std::string *, std::string *)(local_source >= source) && (local_source < source + num_blocks * num_elts_in_block)void onnxruntime::DoTransposeImpl(int64_t, const std::vector<int64_t> &, size_t, size_t, const std::vector<size_t> &, const uint8_t *, uint8_t *, size_t)(local_source >= source) && (local_source < source + num_blocks * blocksize)[ perm: does not align with rank of input data: /Users/runner/work/1/s/onnxruntime/core/providers/cpu/tensor/transpose.honnxruntime::TransposeBase::TransposeBase(const onnxruntime::OpKernelInfo &)v >= 0 && static_cast<uint64_t>(v) <= std::numeric_limits<size_t>::max()Attribute perm of Transpose has an invalid value. Value is outside range. is repeated.bool onnxruntime::TypedDoTransposeEltWise(int64_t, const std::vector<int64_t> &, size_t, const std::vector<size_t> &, const uint8_t *, uint8_t *) [T = unsigned long long](local_source >= source) && (local_source < source + sizeof(T) * num_blocks)bool onnxruntime::TypedDoTransposeEltWise(int64_t, const std::vector<int64_t> &, size_t, const std::vector<size_t> &, const uint8_t *, uint8_t *) [T = unsigned int]bool onnxruntime::TypedDoTransposeEltWise(int64_t, const std::vector<int64_t> &, size_t, const std::vector<size_t> &, const uint8_t *, uint8_t *) [T = unsigned short]bool onnxruntime::TypedDoTransposeEltWise(int64_t, const std::vector<int64_t> &, size_t, const std::vector<size_t> &, const uint8_t *, uint8_t *) [T = unsigned char]Trilu/Users/runner/work/1/s/onnxruntime/core/providers/cpu/tensor/trilu.ccvirtual onnxruntime::common::Status onnxruntime::Trilu::Compute(onnxruntime::OpKernelContext *) constIsScalarOr1ElementVector(k)upper/Users/runner/work/1/s/onnxruntime/core/providers/cpu/tensor/trilu.honnxruntime::Trilu::Trilu(const onnxruntime::OpKernelInfo &)info.GetAttr<int64_t>("upper", &temp).IsOK()UniqueUnsupported tensor type of sortedgsl::span<T> onnxruntime::Tensor::MutableDataAsSpan() [T = long long]gsl::span<const T> onnxruntime::Tensor::DataAsSpan() const [T = signed char]gsl::span<T> onnxruntime::Tensor::MutableDataAsSpan() [T = signed char]gsl::span<const T> onnxruntime::Tensor::DataAsSpan() const [T = std::__1::basic_string<char>]gsl::span<T> onnxruntime::Tensor::MutableDataAsSpan() [T = std::__1::basic_string<char>]Unsqueeze/Users/runner/work/1/s/onnxruntime/core/providers/cpu/tensor/unsqueeze.cconnxruntime::common::Status onnxruntime::UnsqueezeBase::PrepareCompute(onnxruntime::OpKernelContext *, onnxruntime::UnsqueezeBase::Prepare &) constaxes_tensor->Shape().NumDimensions() == 0 || axes_tensor->Shape().NumDimensions() == 1'axes' has an out of range axis'axes' has a duplicate axisnullptr != p.output_tensor/Users/runner/work/1/s/onnxruntime/core/providers/cpu/tensor/unsqueeze.honnxruntime::UnsqueezeBase::UnsqueezeBase(const onnxruntime::OpKernelInfo &)info.GetAttrs("axes", axes_).IsOK()Upsample/Users/runner/work/1/s/onnxruntime/core/providers/cpu/tensor/upsample.ccvirtual onnxruntime::common::Status onnxruntime::Upsample<float>::Compute(onnxruntime::OpKernelContext *) const [T = float]roi_input_idx_ > 0sizes == nullptrsizes != nullptr && sizes->Shape().Size() != 0X->Shape().GetDims().size() == output_dims.size()Resize: input tensor's rank does not match the output tensor's rank.onnxruntime::common::Status onnxruntime::Upsample<float>::BaseCompute(onnxruntime::OpKernelContext *, const std::vector<float> &, const std::vector<float> &, const std::vector<int64_t> &) const [T = float]output_dims.size() == dims.size()Resize: input tensor's dimension does not match the scales.Upsample: input tensor's dimension does not match the scales.Resize: size of roi array should be 2 * N where N is the rank of input tensor X.BaseComputeResize: unexpected modeUpsample: unexpected modeResize: input/output value is nullptrUpsample: input/output value is nullptrResize: input/output value's dimension mismatchUpsample: input/output value's dimension mismatchResize: input shape needs to be at least a single dimensionUpsample: input shape needs to be at least a single dimension.void onnxruntime::UpsampleBase::ParseScalesDataFromOutputSize(const std::vector<int64_t> &, const std::vector<int64_t> &, std::vector<float> &) constoutput_dims[i] == 0Input dim is zero but required output dim is non-zero. Cannot scale 0 by any factor to generate a non-zero value. Dimension: Input dim value: Output dim value: virtual onnxruntime::common::Status onnxruntime::Upsample<int>::Compute(onnxruntime::OpKernelContext *) const [T = int]onnxruntime::common::Status onnxruntime::Upsample<int>::BaseCompute(onnxruntime::OpKernelContext *, const std::vector<float> &, const std::vector<float> &, const std::vector<int64_t> &) const [T = int]virtual onnxruntime::common::Status onnxruntime::Upsample<unsigned char>::Compute(onnxruntime::OpKernelContext *) const [T = unsigned char]onnxruntime::common::Status onnxruntime::Upsample<unsigned char>::BaseCompute(onnxruntime::OpKernelContext *, const std::vector<float> &, const std::vector<float> &, const std::vector<int64_t> &) const [T = unsigned char]WhereGeluonnxruntime::ElementWiseKernel<onnxruntime::functors::ParametricSoftplus<float> >::ElementWiseKernel(const onnxruntime::OpKernelInfo &) [F = onnxruntime::functors::ParametricSoftplus<float>]virtual onnxruntime::common::Status onnxruntime::ElementWiseKernel<onnxruntime::functors::ParametricSoftplus<float> >::Compute(onnxruntime::OpKernelContext *) const [F = onnxruntime::functors::ParametricSoftplus<float>]onnxruntime::ElementWiseKernel<onnxruntime::functors::ScaledTanh<float> >::ElementWiseKernel(const onnxruntime::OpKernelInfo &) [F = onnxruntime::functors::ScaledTanh<float>]virtual onnxruntime::common::Status onnxruntime::ElementWiseKernel<onnxruntime::functors::ScaledTanh<float> >::Compute(onnxruntime::OpKernelContext *) const [F = onnxruntime::functors::ScaledTanh<float>]/Users/runner/work/1/s/onnxruntime/contrib_ops/cpu/attnlstm/bahdanau_attention.cconnxruntime::contrib::BahdanauAttention<float>::BahdanauAttention(onnxruntime::AllocatorPtr, const logging::Logger &, int, int, int, int, int, bool, concurrency::ThreadPool *) [T = float]!normalize_virtual void onnxruntime::contrib::BahdanauAttention<float>::PrepareMemory(const gsl::span<const T> &, const gsl::span<const int> &) [T = float]mem_steps <= max_memory_steps_ && mem_steps > 0Real memory steps is not in (0, AttnLSTM/Users/runner/work/1/s/onnxruntime/contrib_ops/cpu/attnlstm/deep_cpu_attn_lstm.ccvirtual onnxruntime::common::Status onnxruntime::contrib::DeepCpuAttnLstmOp::Compute(onnxruntime::OpKernelContext *) constAttention mechanism memory shape error! Expected: {}, actural: Attention mechanism memory sequence lengths must have shape {Attention mechanism memory sequence lengths value must in (0, ], while found!Attention memory layer weight shape error! Expected:{, am_attn_size}, Got:Attention query layer weight shape error! Expected:{}, Got: Attention v weight shape error! Expected:{}. Got: Attention layer weight shape error! Expected: {, aw_attn_size}. Got:Input initial_c must have shape {Input P must have shape {/Users/runner/work/1/s/onnxruntime/contrib_ops/cpu/attnlstm/deep_cpu_attn_lstm.honnxruntime::contrib::DeepCpuAttnLstmOp::DeepCpuAttnLstmOp(const onnxruntime::OpKernelInfo &)static_cast<int>(activation_func_names.size()) == num_directions_ * 3 [seqno= row[AttentionInput 'input' is expected to have 3 dimensions, got Input 'weights' is expected to have 2 dimensions, got Input 1 dimension 0 should have same length as dimension 2 of input 0Input 'bias' is expected to have 1 dimension, got Input 'bias' dimension 0 should have same length as dimension 1 of input 'weights'Input 'past' is expected to have 5 dimension, got Inputs 'past' dimension 1 shall have same length as dimension 0 of input 0Inputs 'past' dimension 2 shall have length of num_headsInputs 'past' dimension 2 shall have length of Inputs 'mask_index' with 1D data shall have length of batch_size or 2 * batch_sizeInputs 'mask_index' with 2D data shall have shape batch_size x (past_sequence_length + sequence_length)Inputs 'mask_index' with 3D data shall have shape batch_size x sequence_length x (past_sequence_length + sequence_length)Inputs 'mask_index' with 4D data shall have shape batch_size x 1 x max_sequence_length x max_sequence_length)Inputs 'mask_index' with 4D data shall have is_unidirectional_ set to falseInput 'mask_index' is expected to have 1, 2, 3 or 4 dimensions, got /Users/runner/work/1/s/onnxruntime/contrib_ops/cpu/bert/attention.cconnxruntime::Tensor *onnxruntime::contrib::AttentionBase::GetPresent(onnxruntime::OpKernelContext *, const onnxruntime::Tensor *, int, int, int, int &) constExpect to have present state output when past state input is givennum_heads/Users/runner/work/1/s/onnxruntime/contrib_ops/cpu/bert/attention_base.honnxruntime::contrib::AttentionBase::AttentionBase(const onnxruntime::OpKernelInfo &)info.GetAttr("num_heads", &num_heads).IsOK() && num_heads > 0unidirectional/Users/runner/work/1/s/onnxruntime/contrib_ops/cpu/bert/attention_cpu_base.hApplyAttention/Users/runner/work/1/s/onnxruntime/contrib_ops/cpu/bert/bias_gelu.ccvirtual onnxruntime::common::Status onnxruntime::contrib::BiasGelu<float, false>::Compute(onnxruntime::OpKernelContext *) const [T = float, use_approximation = false]use_approximationBiasGeluInput 0 is expected to have 1 or more dimensions, got Input 1 is expected to have 1 dimensions, got Input 1 dimension 0 should have same length as the last dimension of input 0EmbedLayerNormalization/Users/runner/work/1/s/onnxruntime/contrib_ops/cpu/bert/embed_layer_norm.cconnxruntime::contrib::EmbedLayerNorm<float>::EmbedLayerNorm(const onnxruntime::OpKernelInfo &) [T = float]input_ids is expected to have 2 dimensions, got word_embedding is expected to have 2 dimensions, got position_embedding is expected to have 2 dimensions, got segment_embedding is expected to have 2 dimensions, got word_embedding and position_embedding shall have same dimension 1beta is expected to have 1 dimensions, got beta is expected to have size of gamma is expected to have 1 dimensions, got gamma is expected to have size of FastGeluCDistmetric/Users/runner/work/1/s/onnxruntime/contrib_ops/cpu/cdist.honnxruntime::contrib::CDist<float>::CDist(const onnxruntime::OpKernelInfo &) [T = float]info.GetAttr<std::string>("metric", &metric).IsOK()sqeuclideaneuclideanThe first input of CDist kernel has wrong shape: The second input of CDist kernel has wrong shape: Input shape dimensions mismatch:onnxruntime::contrib::CDist<double>::CDist(const onnxruntime::OpKernelInfo &) [T = double]ConvTransposeWithDynamicPads/Users/runner/work/1/s/onnxruntime/contrib_ops/cpu/cpu_contrib_kernels.ccRegisterNchwcKernelsRegisterQuantizationKernelsRegisterCpuContribKernelsCropborder/Users/runner/work/1/s/onnxruntime/contrib_ops/cpu/crop.hAttribute border needs to be specified with four border elements, got Input is expected to have four dimensions corresponding to [N,C,H,W], got input dimensions insteadInput's height () needs to be greater than or equal to the topBorder () + bottomBorder (Input's width () needs to be greater than or equal to the leftBorder () + rightBorder () + scale_[0] () + scale_[1] (CropAndResizebilinear/Users/runner/work/1/s/onnxruntime/contrib_ops/cpu/crop_and_resize.honnxruntime::contrib::CropAndResize<float>::CropAndResize(const onnxruntime::OpKernelInfo &) [T = float] specified. It should be either bilinear or nearestNull crop_size_ptrNumber of dimensions for crop size should be exactly 1/Users/runner/work/1/s/onnxruntime/contrib_ops/cpu/element_wise_ops.honnxruntime::contrib::Affine<float>::Affine(const onnxruntime::OpKernelInfo &) [T = float]info.GetAttr("alpha", &alpha_).IsOK()info.GetAttr("beta", &beta_).IsOK()onnxruntime::contrib::Scale<float>::Scale(const onnxruntime::OpKernelInfo &) [T = float]info.GetAttr("scale", &scale_).IsOK()axisExpandDims/Users/runner/work/1/s/onnxruntime/contrib_ops/cpu/expand_dims.hvirtual onnxruntime::common::Status onnxruntime::contrib::ExpandDims::Compute(onnxruntime::OpKernelContext *) constaxis_tensor->Shape().IsScalar()axis <= X_NumDims && axis >= -X_NumDimsAxis must be within range [ Axis is unimplemented activation: activation_params count mismatchFusedConv/Users/runner/work/1/s/onnxruntime/contrib_ops/cpu/fused_conv.cconnxruntime::contrib::FusedConvFloat::FusedConvFloat(const onnxruntime::OpKernelInfo &)FusedGemmactivationactivation_/Users/runner/work/1/s/onnxruntime/contrib_ops/cpu/fused_gemm.cconnxruntime::contrib::FusedGemm<float>::FusedGemm(const onnxruntime::OpKernelInfo &) [T = float]TransposeMatMulFusedMatMul/Users/runner/work/1/s/onnxruntime/contrib_ops/cpu/image_scaler.honnxruntime::contrib::ImageScaler<float>::ImageScaler(const onnxruntime::OpKernelInfo &) [T = float]info.GetAttrs<float>("bias", bias_).IsOK()Bias size () does not match the number of channels (InverseLayerNormalizationSimplifiedLayerNormalization/Users/runner/work/1/s/onnxruntime/contrib_ops/cpu/layer_norm.cconnxruntime::contrib::LayerNorm<float, false>::LayerNorm(const onnxruntime::OpKernelInfo &) [T = float, simplified = false]op_kernel_info.GetAttr("axis", &axis_).IsOK()onnxruntime::contrib::LayerNorm<float, true>::LayerNorm(const onnxruntime::OpKernelInfo &) [T = float, simplified = true]onnxruntime::contrib::LayerNorm<double, false>::LayerNorm(const onnxruntime::OpKernelInfo &) [T = double, simplified = false]onnxruntime::contrib::LayerNorm<double, true>::LayerNorm(const onnxruntime::OpKernelInfo &) [T = double, simplified = true]MatMulInteger16/Users/runner/work/1/s/onnxruntime/contrib_ops/cpu/matmul_integer16.ccvirtual onnxruntime::common::Status onnxruntime::contrib::MatMulInteger16<short, short, int>::Compute(onnxruntime::OpKernelContext *) const [T1 = short, T2 = short, T3 = int]A != nullptr && B != nullptrMaxpoolWithMask/Users/runner/work/1/s/onnxruntime/contrib_ops/cpu/maxpool_with_mask.hacross_channels/Users/runner/work/1/s/onnxruntime/core/providers/cpu/tensor/mean_variance_normalization.honnxruntime::MeanVarianceNormalization_0<float>::MeanVarianceNormalization_0(const onnxruntime::OpKernelInfo &, bool) [T = float]info.GetAttr<int64_t>("across_channels", &across_channels_).IsOK()normalize_varianceinfo.GetAttr<int64_t>("normalize_variance", &normalize_variance_).IsOK()MurmurHash3/Users/runner/work/1/s/onnxruntime/contrib_ops/cpu/murmur_hash3.ccvirtual onnxruntime::common::Status onnxruntime::contrib::MurmurHash3::Compute(onnxruntime::OpKernelContext *) constkeyssizeof(uint32_t) == output_element_bytesinput_num_bytes % 4 == 0/Users/runner/work/1/s/onnxruntime/contrib_ops/cpu/nchwc_ops.ccvirtual onnxruntime::common::Status onnxruntime::contrib::ReorderInput::Compute(onnxruntime::OpKernelContext *) constX_rank == 4(channels % 4) == 0virtual onnxruntime::common::Status onnxruntime::contrib::ReorderOutput::Compute(onnxruntime::OpKernelContext *) constchannels_ <= X_shape[1]virtual onnxruntime::common::Status onnxruntime::contrib::NchwcConv::Compute(onnxruntime::OpKernelContext *) constX_shape.NumDimensions() == 4(static_cast<size_t>(X_shape[1]) < nchwc_block_size) || ((X_shape[1] % nchwc_block_size) == 0)Unsupported convolution size.output and sum shape must matchonnxruntime::common::Status onnxruntime::contrib::NchwcPoolBase::NchwcPool(onnxruntime::OpKernelContext *, MLAS_POOLING_KIND) const(X_shape[1] % MlasNchwcGetBlockSize()) == 0virtual onnxruntime::common::Status onnxruntime::contrib::NchwcUpsample::Compute(onnxruntime::OpKernelContext *) constX_shape.size() == 4ReorderInputReorderOutput/Users/runner/work/1/s/onnxruntime/contrib_ops/cpu/nchwc_ops.honnxruntime::contrib::ReorderInput::ReorderInput(const onnxruntime::OpKernelInfo &)info.GetAttr<int64_t>("channels_last", &channels_last_).IsOK()onnxruntime::contrib::ReorderOutput::ReorderOutput(const onnxruntime::OpKernelInfo &)info.GetAttr<int64_t>("channels", &channels_).IsOK()channels_ > 0invalid channel countonnxruntime::contrib::NchwcConv::NchwcConv(const onnxruntime::OpKernelInfo &)GetFusedActivationAttr(info, activation_).IsOK()onnxruntime::contrib::NchwcPoolBase::NchwcPoolBase(const onnxruntime::OpKernelInfo &)pool_attrs_.kernel_shape.size() == 2onnxruntime::contrib::NchwcUpsample::NchwcUpsample(const onnxruntime::OpKernelInfo &)info.GetAttrs<int64_t>("scales", scales_).IsOK()scales_.size() == 4scales_[0] == 1 && scales_[1] == 1 && scales_[2] >= 1 && scales_[3] >= 1info.GetAttr<std::string>("coordinate_transformation_mode", &transformation_mode).IsOK()Unsupported transformation mode '' for NCHWc Upsampletransformation_mode_ == TransformationMode::ASYMMETRICUnsupported mode 'QLinearAddQLinearMul/Users/runner/work/1/s/onnxruntime/contrib_ops/cpu/qlinear_binary_op.ccvoid onnxruntime::contrib::(anonymous namespace)::QLinearImpl(onnxruntime::OpKernelContext &, double, const onnxruntime::ProcessBroadcastSpanFuncs &) [T = signed char]IsScalarOr1ElementVector(tensor_a_scale)MatmulInteger : input1 A_scale must be a scalar or 1D tensor of size 1tensor_a_zero_point == nullptr || IsScalarOr1ElementVector(tensor_a_zero_point)MatmulInteger : input1 A_zero_point must be a scalar or 1D tensor of size 1 if givenIsScalarOr1ElementVector(tensor_b_scale)MatmulInteger : input1 B_scale must be a scalar or 1D tensor of size 1tensor_b_zero_point == nullptr || IsScalarOr1ElementVector(tensor_b_zero_point)MatmulInteger : input1 B_zero_point must be a scalar or 1D tensor of size 1 if givenIsScalarOr1ElementVector(tensor_c_scale)MatmulInteger : input1 C_scale must be a scalar or 1D tensor of size 1tensor_c_zero_point == nullptr || IsScalarOr1ElementVector(tensor_c_zero_point)MatmulInteger : input1 C_zero_point must be a scalar or 1D tensor of size 1 if givenvoid onnxruntime::BroadcastLooper(TBroadcastHelper &, const onnxruntime::ProcessBroadcastSpanFuncs &) [TBroadcastHelper = onnxruntime::contrib::(anonymous namespace)::QLinearBroadcastHelper]void onnxruntime::contrib::(anonymous namespace)::QLinearImpl(onnxruntime::OpKernelContext &, double, const onnxruntime::ProcessBroadcastSpanFuncs &) [T = unsigned char]/Users/runner/work/1/s/onnxruntime/contrib_ops/cpu/qlinear_concat.cconnxruntime::contrib::QLinearConcat::QLinearConcat(const onnxruntime::OpKernelInfo &)input_def_count >= 8 && (input_def_count - 2) % 3 == 0At least two inputs are needed, and each input must be (tensor, scale, zero_point) tuple!tensor_x_scale->IsDataType<float>()Input scale is not float for input def @tensor_x_zero_point->GetElementType() == tensor_y_zero_point->GetElementType()Wrong input type encountered for zero point input def @virtual onnxruntime::common::Status onnxruntime::contrib::QLinearConcat::Compute(onnxruntime::OpKernelContext *) constinput_count_x3 >= 6 && input_count_x3 % 3 == 0Input scale is not float for quantized input @Wrong input type encountered for zero point of quantized input @QLinearConcat/Users/runner/work/1/s/onnxruntime/contrib_ops/cpu/qlinear_global_average_pool.ccvirtual onnxruntime::common::Status onnxruntime::contrib::QLinearGlobalAveragePool::Compute(onnxruntime::OpKernelContext *) constIsScalarOr1ElementVector(tensor_x_zero_point)IsScalarOr1ElementVector(tensor_y_zero_point)QLinearGlobalAveragePoolQLinearLeakyReluQLinearSigmoid/Users/runner/work/1/s/onnxruntime/contrib_ops/cpu/qlinear_lookup_table.ccvoid onnxruntime::contrib::QlinearBuildLookupTable(uint8_t *, const onnxruntime::Tensor *, const onnxruntime::Tensor *, const onnxruntime::Tensor *, const onnxruntime::Tensor *, const onnxruntime::contrib::LookupTableArrayTransformer &) [T = unsigned char]QlinearBuildLookupTable : input X_scale must be a scalar or 1D tensor of size 1QlinearBuildLookupTable : input X_zero_point must be a scalar or 1D tensor of size 1QlinearBuildLookupTable : input Y_scale must be a scalar or 1D tensor of size 1QlinearBuildLookupTable : input Y_zero_point must be a scalar or 1D tensor of size 1void onnxruntime::contrib::QlinearBuildLookupTable(uint8_t *, const onnxruntime::Tensor *, const onnxruntime::Tensor *, const onnxruntime::Tensor *, const onnxruntime::Tensor *, const onnxruntime::contrib::LookupTableArrayTransformer &) [T = signed char]/Users/runner/work/1/s/onnxruntime/contrib_ops/cpu/qlinear_pool.ccvirtual onnxruntime::common::Status onnxruntime::contrib::QLinearAveragePool::Compute(onnxruntime::OpKernelContext *) constIsScalarOr1ElementVector(tensor_x_scale)tensor_x_zero_point == nullptr || IsScalarOr1ElementVector(tensor_x_zero_point)input x_zero_point must be a scalar or 1D tensor of size 1 if givenIsScalarOr1ElementVector(tensor_y_scale)tensor_y_zero_point == nullptr || IsScalarOr1ElementVector(tensor_y_zero_point)input y_zero_point must be a scalar or 1D tensor of size 1 if givenUnsupported 'dtype' in QLinear Pooling:QLinear Pooling unsupported pooling size!QLinearAveragePoolQAttention/Users/runner/work/1/s/onnxruntime/contrib_ops/cpu/quantization/attention_quant.ccinput scale must be a scalar or 1D tensor of size 1input zero point must be a scalar or 1D tensor of size 1./Users/runner/work/1/s/onnxruntime/contrib_ops/cpu/quantization/dynamic_quantize_lstm.ccW_zero_point must have shape {} for per-tensor/layer quantization or shape {, 4*} for per-channel quantization. Actual:R_zero_pointW_scaleR_scaleDynamicQuantizeLSTM : Weight zero point must be zeroWeight point must be constantRecurrentDynamicQuantizeLSTM/Users/runner/work/1/s/onnxruntime/contrib_ops/cpu/quantization/dynamic_quantize_matmul.ccComputeCommononnxruntime::common::Status onnxruntime::contrib::MatMulIntegerToFloatBase::ComputeCommon(onnxruntime::OpKernelContext *, const uint8_t *, const onnxruntime::TensorShape &, float, uint8_t, const onnxruntime::Tensor *, const onnxruntime::Tensor *, const onnxruntime::Tensor *, const onnxruntime::Tensor *) constIsBQuantParamSupported(b_zp_tensor->Shape(), b_tensor ? b_tensor->Shape() : b_shape_)virtual onnxruntime::common::Status onnxruntime::contrib::MatMulIntegerToFloat::Compute(onnxruntime::OpKernelContext *) constIsScalarOr1ElementVector(a_zero_point_tensor)MatMulIntegerToFloat : input a zero point must be a scalar or 1D tensor of size 1. Per-Channel is not supported yet.DynamicQuantizeMatMulMatMulIntegerToFloat/Users/runner/work/1/s/onnxruntime/contrib_ops/cpu/quantization/nhwc_max_pool.ccvirtual onnxruntime::common::Status onnxruntime::contrib::NhwcMaxPool::Compute(onnxruntime::OpKernelContext *) constinput_shape.Size() > 0 || N == 0NhwcMaxPoolSampleOpSkipLayerNormalization/Users/runner/work/1/s/onnxruntime/contrib_ops/cpu/skip_layer_norm.cconnxruntime::contrib::SkipLayerNorm<float>::SkipLayerNorm(const onnxruntime::OpKernelInfo &) [T = float]epsilon_ >= 0input is expected to have 3 dimensions, got gamma is expected to have 1 dimension, got beta is expected to have 1 dimension, got bias is expected to have 1 dimension, got onnxruntime::contrib::SkipLayerNorm<double>::SkipLayerNorm(const onnxruntime::OpKernelInfo &) [T = double]Tokenizer/Users/runner/work/1/s/onnxruntime/contrib_ops/cpu/tokenizer.cconnxruntime::contrib::Tokenizer::Tokenizer(const onnxruntime::OpKernelInfo &)pad_valuemincharnummincharnum_ > 0separatorsEither one of the separators OR tokenexp attributes required but none is set!tokenexp.empty()!separators.empty()!char_tokenezation_ || mincharnum_ < 2Can not digest separators: Can not digest tokenexp: Input string contains invalid utf8 chars: Match contains invalid utf8 chars: tensor(string) expected as inputInput dimensions are either [C] or [N][C] allowedConv filter size does not match embedding_size attribute. embedding_size attribute: conv filter size: Conv kernal size 1 does not match conv_window_size attribute . conv_window_size attribute: conv kernal size 1: Char embedding size does not match char_embedding_size attribute. char_embedding_size attribute: Char embedding size: Char embedding size does not match conv kernal size 2. Conv kernal size 2 : /Users/runner/work/1/s/onnxruntime/contrib_ops/cpu/word_conv_embedding.ccWordConvEmbeddingembedding_sizeconv_window_sizechar_embedding_size/Users/runner/work/1/s/onnxruntime/core/util/math_cpu.ccGemv found an unexpected CBLAS_TRANSPOSE input ofvoid onnxruntime::math::Gemv(CBLAS_TRANSPOSE, int, int, float, const T *, const T *, float, T *, Provider *) [T = double, Provider = onnxruntime::CPUMathUtil]bool onnxruntime::math::NextPosition(int64_t, const int64_t *, int64_t *)dims[d_i] < d_maxReceived null OrtThreadingOptionsReceived invalid value for allow_spinning. Valid values are 0 or 1/Users/runner/work/1/s/onnxruntime/core/framework/allocation_planner.cc[CreatePlanCan not find the node onnxruntime::common::Status onnxruntime::PlannerImpl::ComputeUseCounts()p_kernel_defShould not have entry in kernel create info with nullptr for kernel_defCan not find the execution provider ComputeUseCountsallocatoronnxruntime::OrtValueIndex onnxruntime::PlannerImpl::Index(const onnxruntime::OrtValueName &)void onnxruntime::PlannerImpl::ProcessDef(onnxruntime::OrtValueIndex, const onnxruntime::NodeArg *)id >= 0 && static_cast<size_t>(id) < ort_value_info_.size()int &onnxruntime::PlannerImpl::UseCount(onnxruntime::OrtValueIndex)n >= 0 && static_cast<size_t>(n) < ort_value_info_.size()const onnxruntime::KernelCreateInfo &onnxruntime::GetKernelCreateInfo(const std::unordered_map<NodeIndex, gsl::not_null<const KernelCreateInfo *> > &, onnxruntime::NodeIndex)entry != kernel_create_info_map.cend()SessionState should have saved the KernelCreateInfo prior to this running. NodeIndex:onnxruntime::AllocPlanPerValue &onnxruntime::PlannerImpl::AllocPlan(onnxruntime::OrtValueIndex)n >= 0 && static_cast<size_t>(n) < plan_.allocation_plan.size()ComputeReusePlanonnxruntime::common::Status onnxruntime::PlannerImpl::ComputeReusePlan()!IsNonTensor(*node_output)GeneratePlanForWeightsOrtMemoryInfo onnxruntime::PlannerImpl::GetLocationForNodeInput(size_t, const onnxruntime::Node &)void onnxruntime::PlannerImpl::Reuse(onnxruntime::OrtValueIndex, onnxruntime::OrtValueIndex, onnxruntime::AllocKind)reused != reused_for/Users/runner/work/1/s/onnxruntime/core/framework/sequential_execution_plan.hvoid onnxruntime::AllocPlanPerValue::ProgramCounter::AddStart(size_t)starts_.size() == ends_.size()starts_.empty() || start > ends_.back()static size_t onnxruntime::PlannerImpl::GetElementSize(const onnx::DataType &)nullptr != tensor_type_baseonnxruntime::OrtValueIndex &onnxruntime::PlannerImpl::Buffer(onnxruntime::OrtValueIndex)void onnxruntime::AllocPlanPerValue::ProgramCounter::AddEnd(size_t)starts_.size() == ends_.size() + 1end >= starts_.back()void onnxruntime::PlannerImpl::GenerateDeallocationPlan()AllocPlan(ml_value_idx).program_counter.Ends().back() == program_countervoid onnxruntime::PlannerImpl::VerifyMemoryTimeSchedule()entry.program_counter.HasValidEntries()Invalid program_counter entries at index CudaCudaPinnedSpecified device is not supported./Users/runner/work/1/s/onnxruntime/core/framework/allocator.ccoperator()/Users/runner/work/1/s/include/onnxruntime/core/common/logging/logging.hstatic const onnxruntime::logging::Logger &onnxruntime::logging::LoggingManager::DefaultLogger()OrtMemoryInfo:[name: id: OrtMemType: OrtAllocatorType:]Device:[DeviceType: MemoryType: DeviceId:/Users/runner/work/1/s/onnxruntime/core/framework/allocatormgr.ccCreateAllocatorReceived invalid value of arena_extend_strategy void onnxruntime::AllocatorManager::InsertAllocator(onnxruntime::AllocatorPtr)/Users/runner/work/1/s/onnxruntime/core/framework/bfc_arena.ccBFCArenaCreating BFCArena for with following configs: initial_chunk_size_bytes: max_dead_bytes_per_chunk: initial_growth_chunk_size_bytes: memory limit: arena_extend_strategy: Creating bins of max chunk size onnxruntime::BFCArena::BFCArena(std::unique_ptr<IAllocator>, size_t, onnxruntime::ArenaExtendStrategy, int, int, int)BinForSize(bin_size) == BinFromIndex(b)BinForSize(bin_size + 255) == BinFromIndex(b)BinForSize(bin_size * 2 - 1) == BinFromIndex(b)BinForSize(bin_size * 2) != BinFromIndex(b)BFCArena::Chunk *onnxruntime::BFCArena::ChunkFromHandle(onnxruntime::BFCArena::ChunkHandle)h < chunks_.size()Available memory of is smaller than requested bytes of Failed to allocate memory for requested buffer of size ExtendExtended allocation by bytes.Total allocated bytes: Allocated memory at ReserveReserving memory in BFCArena for size: virtual void *onnxruntime::BFCArena::Reserve(size_t)reserved_chunks_.find(ptr) == reserved_chunks_.end()h != kInvalidChunkHandleAllocateRawInternaltried to allocate 0 bytesExtending BFCArena for . bin_num: (requested) num_bytes: (actual) rounded_bytes:Failed to find a free memory block despite calling Extend. rounded_bytes=BFC Arena ran out of memory trying to allocate . Current allocation summary follows.void *onnxruntime::BFCArena::AllocateRawInternal(size_t, bool)void *onnxruntime::BFCArena::FindChunkPtr(onnxruntime::BFCArena::BinNum, size_t, size_t)!chunk->in_use()void onnxruntime::BFCArena::SplitChunk(BFCArena::ChunkHandle, size_t)!c->in_use() && (c->bin_num == kInvalidBinNum) BFC Arena shrunk by bytes. The total allocated bytes is now void onnxruntime::BFCArena::DeallocateRawInternal(void *)void onnxruntime::BFCArena::Merge(BFCArena::ChunkHandle, BFCArena::ChunkHandle)!c1->in_use() && !c2->in_use()c2->prev == h1void onnxruntime::BFCArena::InsertFreeChunkIntoBin(BFCArena::ChunkHandle)void onnxruntime::BFCArena::RemoveFreeChunkIterFromBin(BFCArena::Bin::FreeChunkSet *, const BFCArena::Bin::FreeChunkSet::iterator &)!c->in_use() && (c->bin_num != kInvalidBinNum)void onnxruntime::BFCArena::RemoveFreeChunkFromBin(BFCArena::ChunkHandle)BinFromIndex(c->bin_num)->free_chunks.erase(h) > 0void onnxruntime::BFCArena::FreeAndMaybeCoalesce(BFCArena::ChunkHandle)c->in_use() && (c->bin_num == kInvalidBinNum)std::array<BFCArena::BinDebugInfo, BFCArena::kNumBins> onnxruntime::BFCArena::get_bin_debug_info()bin->free_chunks.count(h) == 1c->bin_num == bin_numDumpMemoryLogAllocator:Bin size: Chunks in_use/total (if not zero). Allocated bytes in_use/total. Requested bytes.void onnxruntime::BFCArena::DumpMemoryLog(size_t)b->free_chunks.size() == bin_info.total_chunks_in_bin - bin_info.total_chunks_in_use: Chunks . Bytes . Requested Diff between in-use and requested bytes is Bin for bytes has max bytes of , Chunk State: Overall chunks summary: Chunk Free at of size Summary of in-use chunks by size: chunks of size . Total Sum Total of in-use chunks: Stats: +auto onnxruntime::BFCArena::Extend(size_t)::(anonymous class)::operator()(const size_t) constIncorrect arena extend strategy./Users/runner/work/1/s/onnxruntime/core/framework/bfc_arena.honnxruntime::BFCArena::AllocationRegion::AllocationRegion(void *, size_t, int64_t)0 == memory_size % kMinAllocationSizeRegionForCould not find Region for int onnxruntime::BFCArena::AllocationRegion::IndexFor(const void *) constp_int >= base_intp_int < base_int + memory_size_void onnxruntime::BFCArena::RegionManager::RemoveAllocationRegion(void *)entry != regions_.end()Could not find Region for: Size: | Requested Size: | in_use: , prev: , next: Limit: InUse: TotalAllocated: MaxInUse: NumAllocs: NumReserves: NumArenaExtensions: NumArenaShrinkages: MaxAllocSize: /Users/runner/work/1/s/onnxruntime/core/framework/config_options.ccAddConfigEntryConfig with key [] already exists with value []. It will be overwritten/Users/runner/work/1/s/onnxruntime/core/framework/data_transfer.ccvirtual common::Status onnxruntime::CPUDataTransfer::CopyTensor(const onnxruntime::Tensor &, onnxruntime::Tensor &, int) constsrc.SizeInBytes() == dst.SizeInBytes()data_transfer registered is nullptr.Tensor size mismatchThere's no data transfer registered for copying tensors from to /Users/runner/work/1/s/onnxruntime/core/framework/data_transfer_manager.ccCopyTensors/Users/runner/work/1/s/onnxruntime/core/framework/data_types.ccbool onnxruntime::data_types_internal::IsCompatible(const onnx::TypeProto_Map &, const onnx::TypeProto_Map &)bool onnxruntime::data_types_internal::IsCompatible(const onnx::TypeProto_Sequence &, const onnx::TypeProto_Sequence &)virtual bool onnxruntime::TensorTypeBase::IsCompatible(const onnx::TypeProto &) constthisProto->value_case() == TypeProto::ValueCase::kTensorTypeutils::HasElemType(thisProto->tensor_type())virtual bool onnxruntime::SparseTensorTypeBase::IsCompatible(const onnx::TypeProto &) constthisProto->value_case() == TypeProto::ValueCase::kSparseTensorTypeutils::HasElemType(thisProto->sparse_tensor_type())virtual bool onnxruntime::SequenceTensorTypeBase::IsCompatible(const onnx::TypeProto &) constthisProto->value_case() == TypeProto::ValueCase::kSequenceTypeutils::HasElemType(thisProto->sequence_type())bool onnxruntime::NonTensorTypeBase::IsMapCompatible(const onnx::TypeProto &) constthisProto->value_case() == TypeProto::ValueCase::kMapTypeutils::HasKeyType(thisProto->map_type())bool onnxruntime::NonTensorTypeBase::IsSequenceCompatible(const onnx::TypeProto &) constvirtual void onnxruntime::NonTensorTypeBase::FromDataContainer(const void *, size_t, OrtValue &) constNot implementedvirtual void onnxruntime::NonTensorTypeBase::ToDataContainer(const OrtValue &, size_t, void *) const(null)floatbooldoublestringint8uint8int16uint16int32uint32int64uint64float16bfloat16tensor type MLDataType for: is not currently registered or supportedonnxruntime::utils::ContainerChecker::ContainerChecker(onnxruntime::MLDataType)void onnxruntime::data_types_internal::DataTypeRegistry::RegisterDataType(onnxruntime::MLDataType)proto != nullptrp.secondWe do not expect duplicate registration of types for: GetElementType is not implemented/Users/runner/work/1/s/include/onnxruntime/core/framework/data_types.hstatic void onnxruntime::data_types_internal::SetMapTypes<std::__1::basic_string<char>, std::__1::basic_string<char> >::Set(onnx::TypeProto &) [K = std::__1::basic_string<char>, V = std::__1::basic_string<char>]value_proto != nullptr expected to be a registered ONNX typestatic void onnxruntime::data_types_internal::SetMapTypes<std::__1::basic_string<char>, long long>::Set(onnx::TypeProto &) [K = std::__1::basic_string<char>, V = long long]static void onnxruntime::data_types_internal::SetMapTypes<std::__1::basic_string<char>, float>::Set(onnx::TypeProto &) [K = std::__1::basic_string<char>, V = float]static void onnxruntime::data_types_internal::SetMapTypes<std::__1::basic_string<char>, double>::Set(onnx::TypeProto &) [K = std::__1::basic_string<char>, V = double]static void onnxruntime::data_types_internal::SetMapTypes<long long, std::__1::basic_string<char> >::Set(onnx::TypeProto &) [K = long long, V = std::__1::basic_string<char>]static void onnxruntime::data_types_internal::SetMapTypes<long long, long long>::Set(onnx::TypeProto &) [K = long long, V = long long]static void onnxruntime::data_types_internal::SetMapTypes<long long, float>::Set(onnx::TypeProto &) [K = long long, V = float]static void onnxruntime::data_types_internal::SetMapTypes<long long, double>::Set(onnx::TypeProto &) [K = long long, V = double]static void onnxruntime::data_types_internal::SetSequenceType<float>::Set(onnx::TypeProto &) [T = float]elem_proto != nullptrstatic void onnxruntime::data_types_internal::SetSequenceType<double>::Set(onnx::TypeProto &) [T = double]static void onnxruntime::data_types_internal::SetSequenceType<signed char>::Set(onnx::TypeProto &) [T = signed char]static void onnxruntime::data_types_internal::SetSequenceType<unsigned char>::Set(onnx::TypeProto &) [T = unsigned char]static void onnxruntime::data_types_internal::SetSequenceType<short>::Set(onnx::TypeProto &) [T = short]static void onnxruntime::data_types_internal::SetSequenceType<unsigned short>::Set(onnx::TypeProto &) [T = unsigned short]static void onnxruntime::data_types_internal::SetSequenceType<int>::Set(onnx::TypeProto &) [T = int]static void onnxruntime::data_types_internal::SetSequenceType<unsigned int>::Set(onnx::TypeProto &) [T = unsigned int]static void onnxruntime::data_types_internal::SetSequenceType<long long>::Set(onnx::TypeProto &) [T = long long]static void onnxruntime::data_types_internal::SetSequenceType<unsigned long long>::Set(onnx::TypeProto &) [T = unsigned long long]static void onnxruntime::data_types_internal::SetSequenceType<bool>::Set(onnx::TypeProto &) [T = bool]static void onnxruntime::data_types_internal::SetSequenceType<std::__1::basic_string<char> >::Set(onnx::TypeProto &) [T = std::__1::basic_string<char>]static void onnxruntime::data_types_internal::SetSequenceType<onnxruntime::MLFloat16>::Set(onnx::TypeProto &) [T = onnxruntime::MLFloat16]static void onnxruntime::data_types_internal::SetSequenceType<onnxruntime::BFloat16>::Set(onnx::TypeProto &) [T = onnxruntime::BFloat16]static void onnxruntime::data_types_internal::SetSequenceType<std::__1::map<std::__1::basic_string<char>, float, std::__1::less<std::__1::basic_string<char> >, std::__1::allocator<std::__1::pair<const std::__1::basic_string<char>, float> > > >::Set(onnx::TypeProto &) [T = std::__1::map<std::__1::basic_string<char>, float, std::__1::less<std::__1::basic_string<char> >, std::__1::allocator<std::__1::pair<const std::__1::basic_string<char>, float> > >]static void onnxruntime::data_types_internal::SetSequenceType<std::__1::map<long long, float, std::__1::less<long long>, std::__1::allocator<std::__1::pair<const long long, float> > > >::Set(onnx::TypeProto &) [T = std::__1::map<long long, float, std::__1::less<long long>, std::__1::allocator<std::__1::pair<const long long, float> > >]/Users/runner/work/1/s/onnxruntime/core/framework/endian_utils.ccCopyLittleEndiansource and destination buffer size mismatch/Users/runner/work/1/s/onnxruntime/core/framework/ex_lib_loader.cc~ExLibLoaderUnloading DSO Failed to unload DSO: A dso with name has already been loaded.LoadExternalLibCaught exception while destructing CustomOpsLoader with message: Caught exception while loading custom ops with message: /Users/runner/work/1/s/onnxruntime/core/framework/execution_frame.cconnxruntime::IExecutionFrame::IExecutionFrame(const onnxruntime::OrtValueNameIdxMap &, const onnxruntime::NodeIndexInfo &, const std::vector<int> &)node_index_info_.GetMaxMLValueIdx() == ort_value_idx_map.MaxIdx()node_index_info and ort_value_idx_map are out of sync and cannot be usedonnxruntime::common::Status onnxruntime::IExecutionFrame::GetOrCreateNodeOutputMLValue(const int, int, const onnxruntime::TensorShape *, OrtValue *&, const onnxruntime::Node &, size_t)shape && tensor.Shape() == *shapeOrtValue shape verification failed. Current shape: Requested shape:invalid index void onnxruntime::IExecutionFrame::Init(const std::vector<int> &, const std::vector<OrtValue> &, const std::unordered_map<int, OrtValue> &, const std::vector<OrtValue> &)feeds.size() == feed_mlvalue_idxs.size()fetches.empty() || fetches.size() == fetch_mlvalue_idxs_.size()Fetches vector passed to GetOutputs contains entries which doesn't match the number of fetches the frame was initialized with of onnxruntime::ExecutionFrame::ExecutionFrame(const std::vector<int> &, const std::vector<OrtValue> &, const std::vector<int> &, const std::vector<OrtValue> &, const std::unordered_map<size_t, IExecutor::CustomAllocator> &, const onnxruntime::SessionState &)buffers_.find(location) == buffers_.end()static_activation_memory_sizes_in_byte_.find(location.name) == static_activation_memory_sizes_in_byte_.end()Memory type should only appear once.ExecutionFrameAllocation of memory pattern buffer for returned nullptrTrying to allocate memory for unused optional inputs/outputsTensor shape cannot contain any negative valueonnxruntime::common::Status onnxruntime::ExecutionFrame::AllocateMLValueTensorSelfOwnBufferHelper(OrtValue &, int, onnxruntime::MLDataType, const OrtMemoryInfo &, const onnxruntime::TensorShape &, bool)ort_value.Fence() == nullptrAllocateMLValueTensorSelfOwnBufferHelperFor ort_value with index: , block in memory pattern size is: but the actually size is: , fall back to default allocation behaviorShape mismatch attempting to re-use buffer. . Validate usage of dim_value (values should be > 0) and dim_param (all values with the same string should equate to the same size) in shapes in the model.AllocateMLValueTensorPreAllocateBufferonnxruntime::common::Status onnxruntime::ExecutionFrame::AllocateAsPerAllocationPlan(OrtValue &, int, const onnxruntime::TensorShape *, size_t)ort_value_index >= 0 && static_cast<size_t>(ort_value_index) < alloc_plan.size()Tried to allocate without valid type information, ort_value index=We don't expect custom allocators for non-tensor types, so a shape is mandatory here.AllocateAsPerAllocationPlanInvalid allocation kind: VerifyOutputSizesExpected shape from model of does not match actual shape of for output ReleaseMLValueImplconst onnxruntime::AllocPlanPerValue &onnxruntime::ExecutionFrame::GetAllocationPlan(int)ort_value_idx >= 0 && static_cast<size_t>(ort_value_idx) < alloc_plan.size()TraceAllocateTraceAllocation for ort_value_idx= size= failed: void onnxruntime::ExecutionFrame::TraceFree(int)TraceFreeTraceFree for ort_value_idx=Memory pattern planner is not enabled on this execution framework./Users/runner/work/1/s/onnxruntime/core/framework/execution_frame.hconst OrtValue &onnxruntime::IExecutionFrame::GetMLValue(int) constort_value_index >= 0 && static_cast<size_t>(ort_value_index) < all_values_size_int onnxruntime::NodeIndexInfo::GetMLValueIndex(int) constoffset >= 0 && static_cast<size_t>(offset) < node_values_size_ failed. Error:onnxruntime::common::Status onnxruntime::AllocateSparseTensor(OrtValue &, const onnxruntime::DataTypeImpl &, onnxruntime::AllocatorPtr, const onnxruntime::TensorShape &, size_t, bool, const onnxruntime::SessionState &)mlvalue.Fence() == nullptr/Users/runner/work/1/s/onnxruntime/core/framework/execution_provider.ccvoid onnxruntime::IExecutionProvider::InsertAllocator(onnxruntime::AllocatorPtr)TryInsertAllocatorduplicated allocator: IExecutionProvider::Compile with fused Node is not implemented by IExecutionProvider::Compile with fused Node and dll path is not implemented by IExecutionProvider::Compile with FusedNodeAndGraph is not implemented by virtual int onnxruntime::IExecutionProvider::GenerateMetaDefId(const onnxruntime::GraphViewer &, uint64_t &) constmetadef_id_generator_IExecutionProvider constructor must be called with true for use_metadef_id_creator/Users/runner/work/1/s/onnxruntime/core/framework/fallback_cpu_capability.ccstd::unordered_set<NodeIndex> onnxruntime::GetCpuPreferredNodes(const onnxruntime::GraphViewer &, const std::string &, const std::vector<const KernelRegistry *> &, const std::vector<NodeIndex> &)kernel_info != nullptrGetCpuPreferredNodesORT optimization- Force fallback to CPU execution for node: because the CPU execution path is deemed faster than overhead involved with execution on other EPs capable of executing this nodeForEachWithIndexCandidate for fallback CPU execution: /Users/runner/work/1/s/onnxruntime/core/framework/feeds_fetches_manager.ccMapNamesToMLValueIdxsError mapping feeds: Error mapping output names: void onnxruntime::FeedsFetchesManager::SetDeviceCopyChecks(onnxruntime::DeviceCopyCheck, onnxruntime::DeviceCopyCheck)input_copy_needed != DeviceCopyCheck::Unknown && output_copy_needed != DeviceCopyCheck::Unknownstatic void SafeIntExceptionHandler<onnxruntime::OnnxRuntimeException>::SafeIntOnDivZero()func info for node: already exist.Can't use func with null ptr not found./Users/runner/work/1/s/onnxruntime/core/framework/fuse_nodes_funcs.ccGetFuncs/Users/runner/work/1/s/onnxruntime/core/framework/graph_partitioner.ccPartitionOnnxFormatModelNo provider specified.Partitiononnxruntime::common::Status onnxruntime::GraphPartitioner::Partition(onnxruntime::Graph &, bool, onnxruntime::FuncManager &, onnxruntime::GraphPartitioner::Mode, std::unordered_map<std::string, uint64_t> *) constcompiled_kernel_hashes != nullptrPartitionOnnxFormatModelImplonnxruntime::common::Status onnxruntime::PartitionOnnxFormatModelImpl(onnxruntime::Graph &, bool, onnxruntime::FuncManager &, onnxruntime::KernelRegistryManager &, onnxruntime::KernelRegistry &, onnxruntime::IExecutionProvider &, GraphPartitioner::Mode, int &)fusion_style == IExecutionProvider::FusionStyle::FunctionMust use Function based fusion when exporting compiled nodes to dll. did not return correct number of compiled functionsonnxruntime::Node *onnxruntime::PlaceNode(onnxruntime::Graph &, const onnxruntime::IndexedSubGraph &, const onnxruntime::KernelRegistryManager &, const std::string &, IExecutionProvider::FusionStyle, GraphPartitioner::Mode, int &)1 == capability.nodes.size()/Users/runner/work/1/s/onnxruntime/core/framework/func_kernel.honnxruntime::FunctionKernel::FunctionKernel(const onnxruntime::OpKernelInfo &)compute_info_->create_state_func(&context, &func_state_) == 0InlineNodesPartitionOrtFormatModelImplEP: has Compile error: single_node_compute_func should have 1 elementsonnxruntime::common::Status onnxruntime::PartitionOrtFormatModelImpl(onnxruntime::Graph &, onnxruntime::FuncManager &, onnxruntime::KernelRegistryManager &, onnxruntime::KernelRegistry &, onnxruntime::IExecutionProvider &, std::unordered_map<std::string, uint64_t> &, int &)Existing entry in compiled kernel hashes for . Execution Provider must generate unique names across the entire model./Users/runner/work/1/s/onnxruntime/core/framework/kernel_def_builder.cconnxruntime::KernelDefBuilder &onnxruntime::KernelDefBuilder::VariadicAlias(int, int)input_offset >= 0 && output_offset >= 0Op with name ( and type ( Version mismatch. node_version: kernel start version: kernel_end_version: Found kernel for Op with name ( in the supported version range (node_version: However the types are incompatible. This op has been implemented only for the following types (), but the node in the model has the following type (/Users/runner/work/1/s/onnxruntime/core/framework/kernel_registry.ccTryCreateKernel kernel not found in No matching hash for kernel is not supported in Encountered following errors: (Kernel not foundkernel def can't be NULLFailed to add kernel for : Conflicting with a registered kernel with op versions.void onnxruntime::(anonymous namespace)::TraverseFormalParametersWithTypeProto(const onnxruntime::Node &, ParamFilterFn, TraverseFn) [ParamFilterFn = (lambda at /Users/runner/work/1/s/onnxruntime/core/framework/kernel_registry.cc:75:11), TraverseFn = (lambda at /Users/runner/work/1/s/onnxruntime/core/framework/kernel_registry.cc:76:11)]len <= op_schema.inputs().size()void onnxruntime::(anonymous namespace)::TraverseFormalParametersWithTypeProto(const onnxruntime::Node &, ParamFilterFn, TraverseFn) [ParamFilterFn = (lambda at /Users/runner/work/1/s/onnxruntime/core/framework/kernel_registry.cc:100:9), TraverseFn = (lambda at /Users/runner/work/1/s/onnxruntime/core/framework/kernel_registry.cc:103:9)]found duplicated provider in KernelRegistryManager (node ). /Users/runner/work/1/s/onnxruntime/core/framework/mldata_type_utils.cconnxruntime::MLDataType onnxruntime::utils::GetMLDataType(const onnxruntime::NodeArg &)nullptr != type_proto/Users/runner/work/1/s/onnxruntime/core/framework/node_index_info.ccauto onnxruntime::NodeIndexInfo::Init(const onnxruntime::ConstGraphNodes &, onnxruntime::NodeIndex, const onnxruntime::OrtValueNameIdxMap &)::(anonymous class)::operator()(const onnxruntime::NodeArg &, bool) constauto onnxruntime::NodeIndexInfo::Init(const onnxruntime::ValidNodes<const std::__1::vector<const onnxruntime::Node *, std::__1::allocator<const onnxruntime::Node *> > > &, onnxruntime::NodeIndex, const onnxruntime::OrtValueNameIdxMap &)::(anonymous class)::operator()(const onnxruntime::NodeArg &, bool) consttype_proto is not of type map!type_proto is not of type sequence!OrtValue is TensorSequence type but has no element Tensor DataType.Tensor types should have been handled alreadynot implemented is not supportedconst onnxruntime::SparseTensor &OrtValue::Get() constIsSparseTensor()Trying to get a SparseTensor, but got: /Users/runner/work/1/s/onnxruntime/core/framework/op_kernel.cconnxruntime::OpKernelContext::OpKernelContext(onnxruntime::IExecutionFrame *, const onnxruntime::OpKernel *, concurrency::ThreadPool *, const logging::Logger &)frame != nullptrkernel != nullptrOrtValue *onnxruntime::OpKernelContext::OutputMLValue(int, const onnxruntime::TensorShape &, size_t)int onnxruntime::OpKernelContext::NumVariadicInputs(size_t) constarg_num < arg_counts.size()Invalid arg_num of . Num args is TempSpace allocator not foundOrtValue *onnxruntime::OpKernelContext::GetOrCreateOutputMLValue(int)/Users/runner/work/1/s/onnxruntime/core/framework/node_index_info.hint onnxruntime::NodeIndexInfo::GetNodeOffset(onnxruntime::NodeIndex) constnode_offsets_index < node_offsets_size_/Users/runner/work/1/s/onnxruntime/core/framework/op_kernel_info.ccconst OrtMemoryInfo &onnxruntime::OpKernelInfo::GetMemoryInfo(int, OrtMemType) constNo attribute with name: is defined.Requested attribute: is expected to have type: but is of type: Attibute name and type don't matchNo attribute with this name is defined.Attribute: expected to be of type: /Users/runner/work/1/s/onnxruntime/core/framework/mem_pattern_planner.hvoid onnxruntime::MemPatternPlanner::TraceAllocation(int, size_t)!using_counters_current <= buffer_size_/Users/runner/work/1/s/onnxruntime/core/framework/ort_value_tensor_slicer.ccstatic OrtValueTensorSlicer<T> onnxruntime::OrtValueTensorSlicer<OrtValue>::Create(T &, int64_t, int64_t) [T = OrtValue]ort_value.IsTensor()Can't slice a non-tensor OrtValue. Type was ort_value.IsAllocated()gsl::narrow_cast<int64_t>(tensor_shape.NumDimensions()) >= slice_dimensionInsufficient dimensions to slice on . Shape:dim0_offset < dim0_sizeInvalid dim0_offset of . Dimension 0 is onnxruntime::OrtValueTensorSlicer<OrtValue>::Iterator::Iterator(T &, size_t, size_t, int64_t, onnxruntime::OrtValueTensorSlicer::Iterator::Direction) [T = OrtValue]typename std::enable_if<!std::is_const<reference>::value, reference>::type onnxruntime::OrtValueTensorSlicer<OrtValue>::Iterator::operator*() [T = OrtValue]static OrtValueTensorSlicer<T> onnxruntime::OrtValueTensorSlicer<const OrtValue>::Create(T &, int64_t, int64_t) [T = const OrtValue]onnxruntime::OrtValueTensorSlicer<const OrtValue>::Iterator::Iterator(T &, size_t, size_t, int64_t, onnxruntime::OrtValueTensorSlicer::Iterator::Direction) [T = const OrtValue]Multiple errors were found./Users/runner/work/1/s/onnxruntime/core/framework/parallel_executor.ccRunNodeAsyncBegin executionExiting due to terminate flag being set to true.onnxruntime::common::Status onnxruntime::ParallelExecutor::RunNodeAsync(size_t, const onnxruntime::SessionState &, const logging::Logger &)Got nullptr from GetKernel for node: _fence_beforeNon-zero status code returned while running node. Name:'' Status Message: _kernel_time_fence_after/Users/runner/work/1/s/onnxruntime/core/framework/op_kernel_context_internal.honnxruntime::OpKernelContextInternal::OpKernelContextInternal(const onnxruntime::SessionState &, onnxruntime::IExecutionFrame &, const onnxruntime::OpKernel &, const logging::Logger &, const bool &)entry != nullptrAll implicit inputs should have OrtValue instances by now. does not.Exception running nodes starting at '. Unknown exception was caught by catch-all handler./Users/runner/work/1/s/onnxruntime/core/framework/prepacked_weights.ccuint64_t onnxruntime::PrePackedWeights::GetHash() constbuffers_.size() == buffer_sizes_.size()/Users/runner/work/1/s/onnxruntime/core/framework/prepacked_weights_container.cconnxruntime::AllocatorPtr onnxruntime::PrepackedWeightsContainer::GetOrCreateAllocator(const std::string &)Unsupported device allocator in the context of pre-packed weights caching: libonnxruntime_providers_cuda.dyliblibonnxruntime_providers_dnnl.dyliblibonnxruntime_providers_openvino.dyliblibonnxruntime_providers_tensorrt.dylib/Users/runner/work/1/s/onnxruntime/core/framework/provider_bridge_ort.ccSessionOptionsAppendExecutionProvider_Tensorrt: Failed to load shared librarySessionOptionsAppendExecutionProvider_OpenVINO: Failed to load shared libraryCUDA execution provider is either not enabled or not available.OrtSessionOptionsAppendExecutionProvider_Cuda: Failed to load shared libraryEnsureGetunordered_map::at: key not found/Users/runner/work/1/s/include/onnxruntime/core/framework/op_kernel_context.hconst T *onnxruntime::OpKernelContext::Input(int) const [T = onnxruntime::Tensor]Missing Input: const T &onnxruntime::OpKernelContext::RequiredInput(int) const [T = onnxruntime::Tensor]input_ptrRequired input at index is not present.onnxruntime::Tensor *onnxruntime::OpKernelContext::Output(int)p_ml_valueonnxruntime::Tensor &onnxruntime::OpKernelContext::RequiredOutput(int, const onnxruntime::TensorShape &)output_ptrRequired output at index gsl::span<const T> onnxruntime::Tensor::DataAsSpan() const [T = long long]void *onnxruntime::Tensor::MutableDataRaw(onnxruntime::MLDataType)type == dtype_Tensor type mismatch.const void *onnxruntime::Tensor::DataRaw(onnxruntime::MLDataType) constvoid onnxruntime::Tensor::Reshape(const onnxruntime::TensorShape &)shape_.Size() == new_shape.Size()Tensor size () != new size (/Users/runner/work/1/s/onnxruntime/core/framework/sequential_executor.cc[Memory] ExecutionFrame statically allocates [Memory] ExecutionFrame dynamically allocates ReleaseNodeMLValues/Users/runner/work/1/s/onnxruntime/core/framework/session_state.ccSetupAllocatorsAllocator already registered for . Ignoring allocator from CreateGraphInfoSaveMLValueNameIndexMappingDone saving OrtValue mappings.PopulateKernelCreateInfoconst onnxruntime::KernelCreateInfo &onnxruntime::SessionState::GetNodeKernelCreateInfo(onnxruntime::NodeIndex) constentry != kernel_create_info_map_.cend()duplicated ort_value index:. Do you have duplicated calls to SessionState::AddInitializedTensor function?Using an input in multiple nodes on different devices is not supported currently. Input: is used by node ) and node Failed to find input name in the mapping: void onnxruntime::SessionState::AddOutputNameToNodeInfoMapping(const std::string &, const onnxruntime::SessionState::NodeInfo &)output_names_to_nodeinfo.empty()Only one node should produce an output. Existing entry for void onnxruntime::SessionState::AddSubgraphSessionState(onnxruntime::NodeIndex, const std::string &, std::unique_ptr<SessionState>)existing_entries.find(attribute_name) == existing_entries.cend()Entry exists in node for attribute const onnxruntime::NodeIndexInfo &onnxruntime::SessionState::GetNodeIndexInfo() constnode_index_info_SetGraphAndCreateKernels must be called prior to GetExecutionInfo.void onnxruntime::SessionState::UpdateToBeExecutedNodes(const std::vector<int> &)onnxruntime::common::Status onnxruntime::SessionState::CreateSubgraphSessionState()subgraphMain Graph instance should have populated all subgraphs when being resolved.CreateSubgraphSessionStateKernel create info is null. Invalid ORT format model.Kernel create info node indices are null. Invalid ORT format model.Kernel create info hashes are null. Invalid ORT format model.Size mismatch for kernel create info node indexes and hashes. Invalid ORT format model.Can't find node with index . Invalid ORT format model.Unable to find compiled kernel hash for node ''.SessionState for subgraphs is null. Invalid ORT format model.Subgraph SessionState entry for is missing. Invalid ORT format model.Subgraph SessionState for is null. Invalid ORT format model.FinalizeSessionStateFinalizeSessionStateImplonnxruntime::common::Status onnxruntime::SessionState::FinalizeSessionStateImpl(const std::basic_string<PATH_CHAR_TYPE> &, onnxruntime::KernelRegistryManager &, const onnxruntime::Node *, const onnxruntime::SessionOptions &, bool, std::unordered_map<std::string, size_t> &)entry != node_to_subgraph_ss.second.cend()Missing session state for subgraph. Node:'' OpType: Index: Attribute:p_op_kernelauto onnxruntime::SessionState::PrepackConstantInitializedTensors(std::unordered_map<std::string, size_t> &, const std::unordered_map<std::string, const OrtValue *> &)::(anonymous class)::operator()(bool) constallocator_for_caching.get() != nullptrweights_to_be_filled_in.buffers_.size() > 0The kernel corresponding to the node doesn't have an implementation that can cache computed pre-packed weights!op_type.empty()Using cached version of pre-packed weight for constant initializer: used in the node: which is of op type: Unable to write the provided PrePackedWeights instance into the containerCould not find OrtValue with name ''+KernelUseSharedPrePackedBuffers doesn't have an implementation that can consume provided pre-packed weightsCould not find OrtValue with idx 'GetSubGraphSessionStatesOrtFormat/Users/runner/work/1/s/onnxruntime/core/framework/session_state_utils.ccSaveInitializedTensorsSaving initialized tensors.common::Status onnxruntime::session_state_utils::SaveInitializedTensors(const onnxruntime::Env &, const std::basic_string<PATH_CHAR_TYPE> &, const onnxruntime::GraphViewer &, const onnxruntime::AllocatorPtr &, const onnxruntime::OrtValueNameIdxMap &, const std::vector<OrtValueIndex> &, onnxruntime::ITensorAllocator &, const std::function<Status (int, const OrtValue &, const OrtCallback &, bool)> &, const logging::Logger &, const onnxruntime::DataTransferManager &, const onnxruntime::ExecutionPlanBase &, const onnxruntime::SessionOptions &)ort_value_name_idx_map.MaxIdx() > -1entry != initialized_tensors_to_allocate.end() && entry->second->data_type() != ONNX_NAMESPACE::TensorProto_DataType_STRING[Memory] SessionStateInitializer statically allocates bytes for Using user supplied initializer with name (Deserialize tensor failed.Done saving initialized tensorsSaveInputOutputNamesToNodeMappingSubgraph input with name is not used by any node.Cannot use user supplied initializer with name: () because the ORT planned memory location device ) is different from what is supplied (DeserializeTensorProto() takes either pre-allocated buffer or an allocator!Internal error. The preallocated buffer is too small. Requires DeserializeTensorProtoFailed to copy tensor to /Users/runner/work/1/s/onnxruntime/core/framework/tensor.cconnxruntime::Tensor::Tensor(onnxruntime::MLDataType, const onnxruntime::TensorShape &, void *, const OrtMemoryInfo &, ptrdiff_t)p_type != nullptronnxruntime::Tensor::Tensor(onnxruntime::MLDataType, const onnxruntime::TensorShape &, std::shared_ptr<IAllocator>)onnxruntime::Tensor::Tensor(onnxruntime::MLDataType, const onnxruntime::TensorShape &, void *, std::shared_ptr<IAllocator>, ptrdiff_t)size_t onnxruntime::Tensor::SizeInBytes() constvoid onnxruntime::Tensor::Init(onnxruntime::MLDataType, const onnxruntime::TensorShape &, void *, onnxruntime::AllocatorPtr, ptrdiff_t)dtype_ != nullptrTensor is expected to contain one of the primitive data types. Got: /Users/runner/work/1/s/onnxruntime/core/framework/tensor_allocator_with_mem_pattern.hFinalizePlanFailed to get allocator for location: duplicated locationMem pattern for initializer is not foundWeight buffer for initializer '' is not foundGet preallocated buffer for initializer '' failedTracemodel format error! Need a value for the external data infoparsing checksum/Users/runner/work/1/s/onnxruntime/core/framework/tensor_shape.ccint64_t onnxruntime::TensorShape::SizeToDimension(size_t) constdimension <= num_dimsInvalid dimension of for SizeFromDimension. Tensor has dimensions.int64_t onnxruntime::TensorShape::SizeFromDimension(size_t) constonnxruntime::TensorShape onnxruntime::TensorShape::Slice(size_t, size_t) constdimstart <= dimend && dimend <= size(){}/Users/runner/work/1/s/onnxruntime/core/framework/tensor_type_and_shape.ccOrtStatusPtr OrtApis::GetTensorTypeAndShape(const OrtValue *, OrtTensorTypeAndShapeInfo **)type != nullptrInvalid TensorProtocorrupted protobuf data: tensor shape size() does not match the data size() in protoUnpackTensor: the pre-allocate size does not match the size in protodata overflowTensorProtoToTensor() tensor shape mismatch!TensorProto type can not be writen into Tensor type /Users/runner/work/1/s/onnxruntime/core/framework/tensorprotoutils.ccTensorProtoToTensorstring tensor can not have raw datatensor can't contain negative dimsInitialized tensor with unexpected type: TensorProtoToMLValue() must take a pre-allocated MemBuffer!string tensor can not use pre-allocated bufferThe preallocated buffer is too small. Requires , Got ConstantNodeProtoToTensorProtocommon::Status onnxruntime::utils::ConstantNodeProtoToTensorProto(const onnx::NodeProto &, const onnxruntime::Path &, onnx::TensorProto &)Unsupported attribute value type of in 'Constant' node 'SparseTensorProtoToDenseTensorProto BUG! Report to onnxruntime team. element_size of: is not supported. type: common::Status onnxruntime::utils::DenseTensorToSparseTensorProto(const onnx::TensorProto &, const onnxruntime::Path &, onnx::SparseTensorProto &)HasDataType(dense_proto)DenseTensorToSparseTensorProto data_type: UnpackInitializerDataUnsupported type: UnpackTensorWithExternalDataImplnullptr == p_dataGetExternalDataInfoTensor does not have external data to read from.External data type cannot be UNDEFINED or STRING.TensorProto external data size mismatch. Computed size: , external_data.length: GetFileContentUnsupported sparse tensor data type of ReadExternalDataForTensorUnpackTensor: the pre-allocated size does not match the raw data size, expected CopySparseDataIndicies expected to be INT64Sparse Indicies raw data size does not match expected.Invalid SparseTensor indices. Should either have raw or int64 dataonnxruntime::common::Status onnxruntime::utils::CopySparseData(size_t, const onnx::TensorProto &, gsl::span<const int64_t>, std::function<void (size_t, size_t)>) [T = unsigned char]rank == dims.size() && rank > 0cur_index == &*indices_data.cend()Invalid SparseTensor indices. Should be rank 0 or 1. Got:onnxruntime::common::Status onnxruntime::utils::CopySparseData(size_t, const onnx::TensorProto &, gsl::span<const int64_t>, std::function<void (size_t, size_t)>) [T = unsigned short]onnxruntime::common::Status onnxruntime::utils::CopySparseData(size_t, const onnx::TensorProto &, gsl::span<const int64_t>, std::function<void (size_t, size_t)>) [T = unsigned int]onnxruntime::common::Status onnxruntime::utils::CopySparseData(size_t, const onnx::TensorProto &, gsl::span<const int64_t>, std::function<void (size_t, size_t)>) [T = unsigned long long]CoreMLExecutionProviderInternalTestingExecutionProvider/Users/runner/work/1/s/onnxruntime/core/framework/utils.ccconst OrtMemoryInfo &onnxruntime::utils::FindMemoryInfoForValue(const onnxruntime::SessionState &, const std::string &)exec_plan_ptrInitializeFeedFetchCopyInfoCopyOneInputAcrossDevicesExecuteGraphFindMemoryInfoForValueconst OrtMemoryInfo &onnxruntime::utils::FindMemoryInfoForValue(const onnxruntime::OrtValueNameIdxMap &, const onnxruntime::SequentialExecutionPlan &, const std::string &)CalculateStaticCopyInfoForFeedsbool onnxruntime::utils::FinalizeCopyInfoForFeeds(const std::vector<OrtDevice> &, std::vector<MLValueCopyInfo> &)feed_locations.size() == copy_info.size()bool onnxruntime::utils::FinalizeCopyInfoForFetches(const std::vector<const OrtMemoryInfo *> &, std::vector<MLValueCopyInfo> &)fetch_alloc_info.size() == copy_info.size()CalculateStaticCopyInfoForFeedonnxruntime::common::Status onnxruntime::utils::BatchOrCopyMLValue(const onnxruntime::SessionState &, const onnxruntime::MLValueCopyInfo &, const OrtValue &, OrtValue &, std::vector<IDataTransfer::SrcDstPair> *)allocator != nullptrFailed to find allocator for device BatchOrCopyMLValueExecuteGraphImplOnly one thread was configured for parallel execution. Hence will use sequential execution.common::Status onnxruntime::utils::CopyInputsAcrossDevices(const onnxruntime::SessionState &, const std::vector<OrtValue> &, std::vector<OrtValue> &, const std::vector<MLValueCopyInfo> &)copy_info.size() == num_feedsCopyInputsAcrossDevicesCopyOutputsAcrossDevicesNumber of neurons in the hidden layer.Constrain seq_lens to integral tensors.The input sequences packed (and potentially padded) into one 3-D tensor with the shape of `[seq_length, batch_size, input_size]`Optional tensor specifying lengths of the sequences in a batch. If not specified - assumed all sequences in the batch to have length `seq_length`. It has shape `[batch_size]` QWThe weight tensor of the query layer in the attention mechanism. Should be of shape `[num_directions, am_query_depth(hidden_size of lstm), am_attn_size]` MWThe weight tensor of the memory layer in the attention mechanism. Should be of shape `[num_directions, memory_depth, am_attn_size]` The attention_v tensor in the attention mechanism. Should be of shape `[num_directions, am_attn_size]` The sequence of the memory (input) for attention mechanism. Should be of `[batch_size, max_memory_step, memory_depth]` memory_seq_lensThe sequence length of the input memory for the attention mechanism. Should be of `[batch_size]` AWThe weights of attention layer in the attention wrapper. If exists, should be of shape `[num_directions, memory_depth+hidden_size, aw_attn_size]. Please note that attention mechanism context depth is also memory_depth in the attention mechanism.` A tensor that concats all the intermediate output values of the hidden. It has shape `[seq_length, num_directions, batch_size, hidden_size]`The last output value of the hidden. It has shape `[num_directions, batch_size, hidden_size]`. 'pads' input must be a 1D (shape: [2 * n_input_dims]) tensor of type int64Pads has incorrect number of valuesInput tensors of wrong rank (0).Incompatible dimensions for matrix multiplicationInputs 0 shall be 3 dimensionsInvalid bias shapeInputs 4 shall be 5 dimensions/Users/runner/work/1/s/onnxruntime/core/graph/contrib_ops/contrib_defs.ccNumber of attention headsWhether every token can only attend to previous tokens. Default value is 0.3D input tensor with shape (batch_size, sequence_length, input_hidden_size)weight2D input tensor with shape (input_hidden_size, 3 * hidden_size), where hidden_size = num_heads * head_sizebias1D input tensor with shape (3 * hidden_size)mask_indexAttention mask with shape (batch_size, 1, max_sequence_length, max_sequence_length), (batch_size, past_sequence_length + sequence_length)or (batch_size, sequence_length, past_sequence_length + sequence_length), or index with shape (batch_size) or (2 * batch_size).Mpastpast state for key and value with shape (2, batch_size, num_heads, past_sequence_length, head_size).3D output tensor with shape (batch_size, append_length, hidden_size)presentpresent state for key and value with shape (2, batch_size, num_heads, past_sequence_length + sequence_length, head_size)Constrain input and output types to float tensors.Constrain mask index to integer types2D input tensor with shape (input_hidden_size, 3 * hidden_size), hidden_size = num_heads * head_sizeinput_scalescale of quantized input tensor. It's a scalar, which means a per-tensor/layer quantization.weight_scalescale of weight scale. It's a scalar or a 1D tensor, which means a per-tensor/per-column quantization.Its size should be 3 * hidden_size if it is per-column quantizationAttention mask index with shape (batch_size)input_zero_pointzero point of quantized input tensor.It's a scalar, which means a per-tensor/layer quantization.weight_zero_pointzero point of quantized weight tensor. It's a scalar or a 1D tensor, which means a per-tensor/per-column quantization.Its size should be 3 * hidden_size if it is per-column quantization3D output tensor with shape (batch_size, sequence_length, hidden_size)Constrain input and output types to int8 tensors.windowOne sided attention windows length W, or half of total window length3D input tensor with shape (batch_size, sequence_length, hidden_size), hidden_size = num_heads * head_size2D input tensor with shape (hidden_size, 3 * hidden_size)maskAttention mask with shape (batch_size, sequence_length)global_weightglobal_biasglobalGlobal attention flags with shape (batch_size, sequence_length)GConstrain to integer typesThe epsilon value to use to avoid division by zero.input_ids2D words IDs with shape (batch_size, sequence_length)segment_ids2D segment IDs with shape (batch_size, sequence_length)word_embedding2D with shape (,hidden_size)position_embedding2D with shape (, hidden_size)segment_embedding1D gamma tensor for layer normalization with shape (hidden_size)beta1D beta tensor for layer normalization with shape (hidden_size)2D attention mask with shape (batch_size, sequence_length)1D mask_index tensor with shape (batch_size)Constrain input and output integer tensors typesConstrain input and output float tensors types.input tensorbias tensoroutput tensorConstrain input and output types to float or half tensors.3D input tensor with shape (batch_size, sequence_length, hidden_size)skip3D skip tensor with shape (batch_size, sequence_length, hidden_size)1D input tensor with shape (hidden_size)1D skip tensor with shape (hidden_size1D bias tensor with shape (hidden_sizemeanSaved mean used during training to speed up gradient computationUinv_std_varSaved inverse standard variance used during training to speed up gradient computation.Constrain mean and inv_std_var to float tensors.Value of alphaValue of beta1D input tensor1D output tensorBias applied to each channel, same size as C.The scale to apply.Input tensor of shape [N,C,H,W]Result, has same shape and type as inputA 1-D values of (leftBorder, topBorder, rightBorder, bottomBorder).A 1-D values of (height, width).Result, has same type as input, with H and W dimensions reduced.Threshold valueInput tensorOutput tensordataTensor of data to extract slices from.1-D tensor of starting indices of corresponding axis in `axes`ends1-D tensor of ending indices (exclusive) of corresponding axis in axesaxes1-D tensor of axes that `starts` and `ends` apply to.Sliced data tensor.Constrain indices to integer typesThe shape of filled tensorThe filled tensorinput_as_shapeextra_shapeInput data to be scaledOutput data after scalingdrop_statesBool to determine if hidden state is zeroes or passed along for timesteps past the given sequence_length.hidden_prevThe previous GRU hidden state.gatesUnactivated gate outputs from forget, update, and output gates, pre-activation.seq_lengthsArray of sequence lengths. len(seq_lengths) should equal batch size N.The timestep for this operation.hiddenThe new GRU hidden state calculated by this op.If 1, mean and variance are computed across channels. Default is 0.If 0, normalize the mean only. Default is 1.Scaling valueThe scaled hyperbolic tangent values of the input tensor computed element-wiseauto_padpadsConstrain input0 and output types to float tensorssignal_ndimnormalizedonesidedAinput_0input_1CWPadsConstrain input and output types to float tensorsactivation_paramsZInput tensor A. The shape of A should be (M, K) if transA is 0, or (K, M) if transA is non-zero.Input tensor B. The shape of B should be (K, N) if transB is 0, or (N, K) if transB is non-zero.Input tensor C. The shape of C should be unidirectional broadcastable to (M, N).Output tensor of shape (M, N).Constrain input and output types to float/int tensors.Whether A should be transposedWhether B should be transposedScalar multiplier for the product of input tensors A * B.Scalar multiplier for input tensor C.activation_gammaSpecified axis to insert a dimensionStrings to tokenizeTokenized stringsInput/Output is a string tensormarkBoolean whether to mark the beginning/end character with start of text character (0x02)/end of text character (0x03).The string used to pad output tensors when the tokens extracted doesn't match the maximum number of tokens found. If start/end markers are needed, padding will appear outside the markers.tokenexpAn optional string. Token's regular expression in basic POSIX format (pubs.opengroup.org/onlinepubs/9699919799/basedefs/V1_chap09.html#tag_09_03). If set, tokenizer may produce tokens matching the specified pattern. Note that one and only of 'tokenexp' and 'separators' should be set.an optional list of strings attribute that contains a list of separators - regular expressions to match separators Two consecutive segments in X connected by a separator would be divided into two tokens. For example, if the input is "Hello World!" and this attribute contains only one space character, the corresponding output would be ["Hello", "World!"]. To achieve character-level tokenization, one should set the 'separators' to [""], which contains an empty string.Minimum number of characters allowed in the output. For example, if mincharnum is 2, tokens such as "A" and "B" would be ignoredN-dimensional matrix AN-dimensional matrix BMatrix multiply results from A * BConstrain input A data types as 16-bit integer tensorConstrain input B data types as 16-bit integer tensorConstrain output Y data types as 32-bit integer tensor.T3 must be tensor(uint32) when both T1 and T2 are tensor(uint16),or must be tensor(int32) when either T1 or T2 is tensor(int16).Scalar multiplier for the product of the input tensors.Whether A should be transposed on the last two dimensions before doing multiplicationWhether B should be transposed on the last two dimensions before doing multiplicationMatrix multiply resultsAn input tensor to hash.32-bit hash value.Constrain input type to unsigned or signed 32-bit integer tensor, or string tensor. It should be utf-8 encoded if using unicode.Constrain output type to unsigned and signed 32-bit integer tensor.seedSeed for the hashing algorithm, unsigned 32-bit integer, default to 0.positiveIf value is 1, output type is uint32_t, else int32_t. Default value is 1.Tensor of rank r >= 1.indicesTensor of rank q >= 1.Tensor of rank q-1+r-indices[-1].Constrain indice type to int32 or int64Integer representing the embedding vector size for each word.If not provide, use the fileter size of conv weightThis operator applies convolution to word from left to right with window equal to conv_window_size and stride to 1.Take word 'example' for example, with conv_window_size equal to 2, conv is applied to [ex],[xa], [am], [mp]...If not provide, use the first dimension of conv kernal shape.Integer representing the embedding vector size for each char.If not provide, use the char embedding size of embedding vector.SequenceSpecify batchs of sequence words to embeddingSpecify weights of convSpecify bias of convSpecify embedding vector of charConstrain to tensor(int32).Constrain to tensor(float).modeThree modes: `constant`(default) - pads with a given constant value, `reflect` - pads with the reflection of the vector mirrored on the first and last values of the vector along each axis, `edge` - pads with the edge values of arrayInput tensor.Tensor of integers indicating the number of padding elements to add or remove (if negative) at the beginning and end of each axis. For 2D input tensor, it is the number of pixels. `pads` should be a 1D tensor of shape [2 * input_rank] or a 2D tensor of shape [1, 2 * input_rank]. `pads` format (1D example) should be as follow [x1_begin, x2_begin,...,x1_end, x2_end,...], where xi_begin is the number of pixels added at the beginning of axis `i` and xi_end, the number of pixels added at the end of axis `i`.(Optional) A scalar or rank 1 tensor containing a single value to be filled if the mode chosen is `constant` (by default it is 0.0).Tensor after padding.xA 1-D input tensor that is to be processed.A 1-D tensor of the same type as 'x' containing all the unique values in 'x' sorted in the same order that they occur in the input 'x'idxA 1-D INT64 tensor of the same size as 'x' containing the indices for each value in 'x' in the output 'uniques'countsA 1-D INT64 tensor containing the the count of each element of 'uniques' in the input 'x'Input can be of any tensor type.The distance metric to use. If a string, the distance function can be "braycurtis", "canberra", "chebyshev", "cityblock", "correlation", "cosine", "dice", "euclidean", "hamming", "jaccard", "jensenshannon", "kulsinski", "mahalanobis", "matching", "minkowski", "rogerstanimoto", "russellrao", "seuclidean", "sokalmichener", "sokalsneath", "sqeuclidean", "wminkowski", "yule".2D matrix with shape (M,N)2D matrix with shape (K,N)A 2D Matrix that represents the distance between each pair of the two collections of inputs.Constrains input to only numeric types.The pooling method. Two modes are supported: 'bilinear' and 'nearest'. Default is 'bilinear'.Value used for extrapolation, when applicable. Default is 0.0f. Input data tensor from the previous operator; 4-D feature map of shape (N, C, H, W), where N is the batch size, C is the number of channels, and H and W are the height and the width of the data.roisRoIs (Regions of Interest) to pool over; rois is 2-D input of shape (num_rois, 4) given as [[y1, x1, y2, x2], ...]. The RoIs' coordinates are normalized in the coordinate system of the input image. Each coordinate set has a 1:1 correspondence with the 'batch_indices' input.batch_indices1-D tensor of shape (num_rois,) with each element denoting the index of the corresponding image in the batch.crop_size1-D tensor of 2 elements: [crop_height, crop_width]. All cropped image patches are resized to this size. Both crop_height and crop_width need to be positive.RoI pooled output, 4-D tensor of shape (num_rois, C, crop_height, crop_width). The r-th batch element Y[r-1] is a pooled feature map corresponding to the r-th RoI X[r-1].Constrain types to float tensors.Constrain types to int tensors.The first normalization dimension: normalization will be performed along dimensions axis : rank(inputs).stash_typetype used for stash mean/inv_std_varInput data tensor from the previous layer.Scale tensor.Bias tensor.Output data tensor.InvStdDevSaved inverse standard deviation used during training to speed up gradient computation.Constrain input types and output Y type to float tensors.Type of Mean and InvStdDev tensors.Constrain input and output types (except mean and inv_std_var) to float tensors.Constrain mean and inv_std_var to be float tensors.The input data as Tensor.The output.The normal input data.The bias input data that is a 1D tensor.Input tensor. Every matrix in the batch must be invertible.Output tensor of the same type and shape as the input tensor.The embedding matrix of size N x M. 'N' is equal to the maximum possible index + 1, and 'M' is equal to the embedding sizeLong tensor containing the indices to extract from embedding matrix.padding_idxA 0-D scalar tensor. If specified, the entries at `padding_idx` do not contribute to the gradient; therefore, the embedding vector at `padding_idx` is not updated during training, i.e. it remains as a fixed pad.scale_grad_by_freqA 0-D bool tensor. If given, this will scale gradients by the inverse of frequency of the indices (words) in the mini-batch. Default is ``False``Output tensor of the same type as the input tensor. Shape of the output is * x M, where '*' is the shape of input indices, and 'M' is the embedding size.Constrain input and output types to all numeric tensors.Boolean. Indicates whether upper or lower part of matrix is retained. Default is true.Input tensor of rank 2 or higher.kA 0-D tensor containing a single value corresponding to the number diagonals above or the main diagonal to exclude or include.Default value is 0 if it's not specified.Constrain input and output types to all numeric tensors and bool tensors.softmax_axisapply softmax to elements for dimensions softmax_axis or higherbroadcast_axisbroadcast bias across input for dimensions broadcast_axis to softmax_axis-1The bias (or mask) as Tensor.(Optional) Seed to the random generator, if not specified we will auto generate one.The bias input, a vector with the same shape as last dim of dataresidualThe residual input, must have the same shape as dataratioThe ratio of random dropout, with value in [0, 1). If this input was not set, or if it was set to 0, the output would be a simple copy of the input. If it's non-zero, output will be a random dropout of input, which is typically the case during training.training_modeIf set to true then it indicates dropout is being used for training. It is an optional value hence unless specified explicitly, it is false. If it is false, ratio is ignored and the operation mimics inference mode where nothing will be dropped from the input data and if mask is requested as output it will contain all ones.The output mask of dropout.Constrain input 'ratio' types to float tensors.Constrain output 'mask' types to boolean tensors.isinf_onlyIf true, check only for Inf, -Inf.isnan_onlyIf true, check only for NaN.Constrain the output to a boolean tensor.Input tensors to check.The output scalar. Its value is true if all input tensors are finite. Otherwise, the output value would be false.Incompatible dimensionsInputs 0 shall be 2 dimensionsword_embedding should have 2 dimensions and dimension size is known.X_biasNegative values are not allowed in a shape specificationAttribute should specify a shapeInput's shape must be 4-D'Border' attribute must be present and must contain exactly 4 values - (left_border, top_border, right_border, bottom_border)'Scale' must contain exactly 2 values - (height, width)) needs to be greater than or equal to the top_border () + bottom_border () needs to be greater than or equal to the left_border () + right_border () + scale[0] () + scale[1] (First input does not have rank 2Second input does not have rank 2Input axis is invalid: inputs are expected to have tensor type and output type should not be null.both data and indices tensor need to have rank larger than zero.last dimension of indices must not be larger and rank of data tensor'pads' input must be a 1D (shape: [input_rank]) or 2D tensor (shape: [1, input_rank]) of type int64first input tensor has wrong dimensionrois input tensor has wrong dimensionbatch_indices shape input tensor has wrong dimensioncrop_size shape input tensor has wrong dimensionInput rank must be >= 2.The inner-most 2 dimensions must have the same size (mat_w: != mat_h: expected to have rank > but has rank Dimension mismatch in unification between auto onnxruntime::contrib::RegisterContribSchemas()::(anonymous class)::operator()(onnx::InferenceContext &) const!(isinf_only && isnan_only)Both attributes isinf_only and isnan_only cannot be set. Unset both to check for both conditions./Users/runner/work/1/s/onnxruntime/core/graph/contrib_ops/nchwc_schema_defs.ccchannelstensor rank too smallinvalid scales dimensioninvalid scales value/Users/runner/work/1/s/onnxruntime/core/graph/contrib_ops/nhwc_schema_defs.ccInput data tensor from the previous operator; According to channels_last, dimensions for image case are (N x C x H x W), or (N x H x W x C) where N is the batch size, C is the number of channels, and H and W are the height and the width of the data. For non image case, the dimensions are in the form of (N x C x D1 x D2 ... Dn), or (N x D1 X D2 ... Dn x C) where N is the batch size.Scale of quantized input 'X'. It must be a scalar.Zero point tensor for input 'X'. It must be a scalar.Scale of quantized output 'Y'. It must be a scalar.Zero point tensor for output 'Y'. It must be a scalar.Output data tensor from pooling across the input tensor. The output tensor has the same rank as the input. with the N and C value keep it value, while the otherdimensions are all 1.Constrain input and output types to singed/unsigned int8 tensors.Works on NHWC layout or not? Default not.Input scale. It's a scalar, which means a per-tensor/layer quantization.Input zero point. Default value is 0 if it's not specified. It's a scalar, which means a per-tensor/layer quantization.Output zero point. Default value is 0 if it's not specified. It's a scalar, which means a per-tensor/layer quantization.Constrain input and output types to 8 bit tensors.Output tensor must have at least 2 dimensionsInput data type does not match the expected data typeInput data type does not match the expected data type. Current data type is Scale and Zero-point must be a scalarScale and Zero-point must be of rank 1Scale and Zero-point must be of rank 1 and the number of elements should be equal to the number of rows of the corresponding input./Users/runner/work/1/s/onnxruntime/core/graph/contrib_ops/quantization_defs.ccThe axis along which same quantization parameters are applied. It's optional.If it's not specified, it means per-tensor quantization and input 'x_scale' and 'x_zero_point' must be scalars.If it's specified, it means per 'axis' quantization and input 'x_scale' and 'x_zero_point' must be 1-D tensors.Scale for doing quantization to get 'y'. It could be a scalar or a 1-D tensor,which means a per-tensor or per-axis quantization. If it's a 1-D tensor, its number of elements should be equal to the dimension value of 'axis' dimension of input 'x'.Zero point for doing quantization to get 'y'. It could be a scalar or a 1-D tensor, which means a per-tensoror per-axis quantization. If it's a 1-D tensor, its number of elements should be equal to the dimension value of 'axis' dimension of input 'x'.Constrain 'x', 'y_scale' to float tensors.Constrain 'y_zero_point' and 'y' to 8-bit integer tensors.N-D quantized Input tensor to be de-quantized.Scale for input 'x'. It could be a scalar or a 1-D tensor, which means a per-tensor or per-axis quantization.If it's a 1-D tensor, its number of elements should be equal to the dimension value of 'axis' dimension of input 'x'.Zero point for input 'x'. It could be a scalar or a 1-D tensor, which means a per-tensor or per-axis quantization.If it's a 1-D tensor, its number of elements should be equal to the dimension value of 'axis' dimension of input 'x'.Constrain 'x' and 'x_zero_point' to 8-bit integer tensors.Constrain 'y', 'x_scale' to float tensors.Constrain output data type to 32-bit integer tensor.T2 must be tensor(uint32) when T1 is tensor(uint8),or must be tensor(int32) when T1 is tensor(int8).A_zero_pointInput A zero point. Default value is 0 if it's not specified. It's a scalar, which means a per-tensor/layer quantization.B_zero_pointInput B zero point. Default value is 0 if it's not specified. It's a scalar, which means a per-tensor/layer quantization.Constrain output to 32 bit tensorConstrain input types to 8 bit signed and unsigned tensors.Constrain output types to 32 bit tensors.Scale of quantized input 'B'. It could be a scalar or a 1-D tensor, which means a per-tensor or per-column quantization. If it's a 1-D tensor, its number of elements should be equal to the number of columns of input 'B'.1D input tensor, whose dimension is same as B's last dimensionConstrain input A, b_scale and output Y data type as float tensor.Scale of quantized input 'A'. It could be a scalar or a 1-D tensor, which means a per-tensor or per-column quantization. If it's a 1-D tensor, its number of elements should be equal to the number of columns of input 'A'.Zero point tensor for input 'A'. It's optional and default value is 0. It could be a scalar or a 1-D tensor, which means a per-tensor or per-column quantization. If it's a 1-D tensor, its number of elements should be equal to the number of columns of input 'A'.Constrain input a_scale, b_scale and output Y data type as float tensor.additionC = (A_scale * (A - A_zero_point) + B_scale * (B - B_zero_point))/C_scale + C_zero_pointmultiplicationC = ((A - A_zero_point) * (B - B_zero_point)) * (A_scale * B_scale)/C_scale + C_zero_pointdata_scaledata_zero_pointreduced_scalereduced_zero_pointX_scaleInput X's scale. It's a scalar, which means a per-tensor/layer quantization.X_zero_pointInput X's zero point. Default value is 0 if it's not specified. It's a scalar, which means a per-tensor/layer quantization.Y_scaleOutput Y's scale. It's a scalar, which means a per-tensor/layer quantization.Y_zero_pointOutput Y's zero point. Default value is 0 if it's not specified. It's a scalar, which means a per-tensor/layer quantization.The weight tensor for the gates. Concatenation of `W[iofc]` and `WB[iofc]` (if bidirectional) along dimension 0. The tensor has shape `[num_directions, input_size, 4*hidden_size]`.The recurrence weight tensor. Concatenation of `R[iofc]` and `RB[iofc]` (if bidirectional) along dimension 0. This tensor has shape `[num_directions, hidden_size, 4*hidden_size]`.W's scale. Its size is [num_directions] for per-tensor/layer quantization, or [num_directions, 4*hidden_size] for per-channel quantization on the axis input_size.W's zero point. Its size is [num_directions] for per-tensor/layer quantization, or [num_directions, 4*hidden_size] for per-channel quantization on the axis input_size.R's scale. Its size is [num_directions] for per-tensor/layer quantization, or [num_directions, 4*hidden_size] for per-channel quantization on the axis input_size.R's zero point. Its size is [num_directions] for per-tensor/layer quantization, or [num_directions, 4*hidden_size] for per-channel quantization on the axis input_size.Constrain weights types to 8 bit tensors.Y's scale.Y's zero point.T8List of tensors/scale/zero_point for concatenationTVConstrain input and output types to 8 bit signed and unsigned tensors.Constrain scale types to any float tensor type.Sequence of (Tensor, Scale, ZeroPoint) tuples. The type is sequence of (T8, TF, T8). Performs element-wise binary {name} on 8 bit data types (with Numpy-style broadcasting support). {additionalDocumentation} {additionalDocumentation}A_scaleInput A's scale. It's a scalar, which means a per-tensor/layer quantization.B_scaleInput B's scale. It's a scalar, which means a per-tensor/layer quantization.C_scaleC_zero_pointaxis must be in [-rank, rank)Constrain input and output types.Tensor(scalar, or dims=[1]). First entry in the range.Tensor(scalar, or dims=[1]). Upper limit of sequence, exclusive.Tensor(scalar, or dims=[1]). Number that increments start. Defaults to 1.1-D Tensor of the range.Unsupported type:Can not get shape initializer data!Unsupported non-raw-data data type!inout/Users/runner/work/1/s/onnxruntime/core/graph/function.cconnxruntime::FunctionImpl::FunctionImpl(const onnxruntime::Graph &, const onnxruntime::IndexedSubGraph &, const logging::Logger &)_dummyonnxruntime::FunctionImpl::FunctionImpl(const onnxruntime::Graph &, const onnxruntime::NodeIndex &, const onnx::FunctionProto &, const logging::Logger &)Resolve subgraph failed:std::unique_ptr<onnx::OpSchema> onnxruntime::CreateSchema(const onnxruntime::Graph &, const onnxruntime::IndexedSubGraph &)input_arg->Type() != nullptrstd::unordered_map<std::string, int> onnxruntime::CreateOpsetImportsForFunction(const onnx::FunctionProto &, const std::unordered_map<std::string, int> &)(result.first->second == opset_version)ONNX model does not support multiple opset versions for a domain. Model imports opset version for domain and function is trying to import opset version for the same domainvoid onnxruntime::update_subgraphs_within_function_body(onnx::GraphProto &, const onnxruntime::Graph &, const onnx::NodeProto &, const std::unordered_map<std::string, int> &, const std::unordered_map<std::string, int> &)A node with a function body within a subgraph within another function body is currently not supported in ORT/Users/runner/work/1/s/onnxruntime/core/graph/function_impl.hvirtual const onnxruntime::Graph &onnxruntime::ViewerFunctionImpl::Body() constType mismatch. Current= Input=Tensor element type mismatch. /Users/runner/work/1/s/onnxruntime/core/graph/graph.ccUpdateTypeAndShapeSparseTensor element type mismatch. Serialization of fused function body is not currently supported, Node [] op_type [] does not have the graph for key LoadFromOrtFormatfbs_attr cannot be nullSerialization error. Graph attribute was serialized without Graph instanceNode::LoadFromOrtFormat, input_arg_counts is missingLoadEdgesFromOrtFormatinput index: is not the same as this node's index:ai.onnxThis is an invalid model. The sum of input arg count is not equal to size of input defs in node (onnxruntime::Graph::Graph(const onnxruntime::Model &, onnx::GraphProto *, const std::unordered_map<std::string, int> &, onnxruntime::Version, onnxruntime::IOnnxRuntimeOpSchemaCollectionPtr, onnxruntime::Graph *, const onnxruntime::Node *, const logging::Logger &)graph_proto != nullptrConstantDuplicate constant node sparse initializer name: '' Model is invalid.utils::HasName(sparse_tensor)Duplicate sparse_tensor_initializer: 'GraphDuplicate initializer (dense, sparse or ConstantNode): '' the model will use the latest encountered initializer. Please, fix your model.Initializer appears in graph inputs and will not be treated as constant value/weight. This may prevent some of the graph optimizations, like const folding. Move it out of graph inputs if there is no need to override it, by either re-generating the model with latest exporter/converter or with the tool onnxruntime/tools/python/remove_initializer_from_input.py.void onnxruntime::Graph::InitializeStateFromModelFileGraphProto()graph_inputs_excluding_initializers_.empty() && graph_inputs_including_initializers_.empty() && value_info_.empty() && graph_outputs_.empty()node_argGraph ctor should have created NodeArg for initializer. Missing:This is an invalid model. Graph output () does not exist in the graph.This is an invalid model. Error: two nodes with same node name ().This is an invalid model. Error: Duplicate definition of name (SetOuterScopeNodeArgsvoid onnxruntime::Graph::AddEdge(onnxruntime::NodeIndex, onnxruntime::NodeIndex, int, int)void onnxruntime::Graph::RemoveEdge(onnxruntime::NodeIndex, onnxruntime::NodeIndex, int, int)BuildConnectionsThis is an invalid model. At top level graph without matching NodeArg that subgraph consumes. Name= Graph may not conform to the ONNX spec and contain initializers that are not graph inputs.This is an invalid model. Failed to find NodeArg in all parent graphs. Name=Invalid model. Node input '' is not a graph input, initializer, or output of a previous node.void onnxruntime::Graph::KahnsTopologicalSort(const std::function<void (const Node *)> &, const std::function<bool (const Node *, const Node *)> &) constSome nodes are not included in the topological sort, graph have a cycle.This is an invalid model. Error: the graph is not acyclic.Size mismatch validating subgraph inputs. Got inputs but subgraph has inputs and requires inputs. Either provide all subgraph inputs, or just the required inputs.Node:InferAndVerifySubgraphTypesonnxruntime::common::Status onnxruntime::Graph::UpdateShapeInference(onnxruntime::Node &)node.GetAttributeNameToMutableSubgraphMap().empty()UpdateTypeShapeInference is not intended to be used with control flow nodes containing subgraphsThis is an invalid model. Node () input arg () does not have type information set by parent node.This is an invalid model. Type Error: Type '' of input parameter () of operator () in node () is invalid.Type Error: Type parameter () of Optype () bound to different types ( and in node (InferAndVerifyTypeMatchNode () output arg () type inference failedType Error: Type () of output arg () of node () does not match expected type (This is an invalid model. Model input () does not have type information.Type Error: Data in initializer '' has element type but usage of initializer in graph expects Type Error: Shape of initializer does not match. VerifyNodeAndOpMatchFatal error: is not a registered function/op) attribute () is required but not specified.Error: Duplicate definition-site for (InitInputsInitializersOutputsPerformTypeAndShapeInferencingForThisAndAllSubgraphsResolveonnxruntime::common::Status onnxruntime::Graph::Resolve(const onnxruntime::Graph::ResolveOptions &)outer_scope_node_args_consumed.empty()Shouldn't be possible to have NodeArgs that haven't been handled already.void onnxruntime::Graph::AddInitializedTensor(const onnx::TensorProto &)existing->second == &tensorAddInitializedTensor already has tensor with name but different TensorProto.void onnxruntime::Graph::RemoveInitializedTensor(const std::string &)sparse_tensor_names_.count(tensor_name) == 0!found_token_NoOpbool onnxruntime::Graph::RemoveNode(onnxruntime::NodeIndex)node->GetOutputEdgesCount() == 0Can't remove node as it still has output edges.onnx::GraphProto onnxruntime::Graph::ToGraphProto() constlocationoffsetlengthvoid onnxruntime::Graph::ToGraphProtoInternal(onnx::GraphProto &) constOuter scope node arg name ''was added but does not exist. CleanUnusedInitializersRemoving initializer ''. It is not used by any node and should be removed from the model.'. It is no longer used by any node. must be either specified in graph inputs or graph initializers.gsl::not_null<Node *> onnxruntime::Graph::AllocateNode()nodes_.size() < static_cast<unsigned int>(std::numeric_limits<int>::max())onnxruntime::Node &onnxruntime::Graph::CreateFusedSubGraphNode(const onnxruntime::IndexedSubGraph &, const std::string &)nullptr != func_meta_defvoid onnxruntime::Graph::FinalizeFuseSubGraph(const onnxruntime::IndexedSubGraph &, onnxruntime::Node &)dst_implicit_input_idx < (int)node->ImplicitInputDefs().size()Node 's number of inputs is different from function body graph's number of input.onnxruntime::common::Status onnxruntime::Graph::InlineFunction(onnxruntime::Node &)node.MutableOutputDefs().size() == subgraph.GetOutputs().size()'s number of outputs is different from function body graph's number of outputs.InlineFunctionvoid onnxruntime::Graph::SetInputs(const std::vector<const NodeArg *> &)input->Exists() : : Initializer tensor is missing. Invalid ORT format model.Duplicate initializer (dense or ConstantNode): 'Sparse Initializer tensor is missing. Invalid ORT format model.NodeArg is missing. Invalid ORT format model.Node is missing. Invalid ORT format model.Node index is out of rangeNodeEdge is missing. Invalid ORT format model.MergeShapeInfoError merging shape info for output. '' source: target:. Falling back to lenient merge.[ShapeInferenceError] Mismatch between number of source and target dimensions. Source= Target=Can't merge shape info. Both source and target dimension have values but they differ. Source= Dimension=Output:fbs_node_arg_names cannot be nullnode_arg_name cannot be nullLoadNodeArgsFromOrtFormat: Node [], could not find NodeArg ALLOW_RELEASED_ONNX_OPSET_ONLY/Users/runner/work/1/s/onnxruntime/core/graph/model_load_utils.hbool onnxruntime::model_load_utils::IsAllowReleasedONNXOpsetsOnlySet() are '0' and '1'. The environment variable contained the value: ai.onnx.mlai.onnx.training/Users/runner/work/1/s/include/onnxruntime/core/graph/graph.honnxruntime::Node *onnxruntime::Graph::NodeAtIndexImpl(onnxruntime::NodeIndex) constnode_index < nodes_.size()Validating no unexpected access using an invalid node_index. Got: Max:[TypeInferenceError] No Graph instance was found for attribute in node Graph attribute inferencing failed: ) Op () This is an invalid model. Error in Node:NodeArg Name is missing. Invalid ORT format model./Users/runner/work/1/s/include/onnxruntime/core/common/const_pointer_container.hconst onnxruntime::ConstPointerContainer::T *onnxruntime::ConstPointerContainer<std::__1::vector<onnxruntime::NodeArg *, std::__1::allocator<onnxruntime::NodeArg *> > >::at(size_t) const [Container = std::__1::vector<onnxruntime::NodeArg *, std::__1::allocator<onnxruntime::NodeArg *> >]index < data_.size()/Users/runner/work/1/s/onnxruntime/core/graph/graph_flatbuffers_utils.ccSaveInitializerOrtFormatSaveSparseInitializerOrtFormatSaveAttributeOrtFormatGraph attribute value was null. Invalid ORT format model.SaveAttributeOrtFormat: Unsupported attribute type: LoadInitializerOrtFormatMissing dimensions for initializer. Invalid ORT format model.Missing string data for initializer. Invalid ORT format model.Missing raw data for initializer. Invalid ORT format model.LoadSparseInitializerOrtFormatMissing values for sparse initializer. Invalid ORT format model.Missing name for SparseTensor initializer. Invalid ORT format model.Missing indicies for sparse initializer: Invalid ORT format model.Missing dims for sparse initializer: LoadAttributeOrtFormatNull string attribute. Invalid ORT format model.Null tensor attribute. Invalid ORT format model.Null graph attribute. Invalid ORT format model.Empty graph proto from deserialization of ORT format modelNull floats attribute. Invalid ORT format model.Null ints attribute. Invalid ORT format model.Null strings attribute. Invalid ORT format model.Null string in strings attribute. Invalid ORT format model.Null tensors attribute. Invalid ORT format model.Null tensor in tensors attribute. Invalid ORT format model.UNDEFINEDFLOATINTSTRINGTENSORGRAPHFLOATSINTSSTRINGSTENSORSGRAPHSSPARSE_TENSORSPARSE_TENSORS/Users/runner/work/1/s/onnxruntime/core/graph/graph_utils.ccint onnxruntime::graph_utils::GetIndexFromName(const onnxruntime::Node &, const std::string &, bool)itr != node_args.end()Attempting to get index by a name which does not exist:for node: const std::string &onnxruntime::graph_utils::GetNodeInputName(const onnxruntime::Node &, int)index >= 0 && static_cast<size_t>(index) < inputs.size()const std::string &onnxruntime::graph_utils::GetNodeOutputName(const onnxruntime::Node &, int)index >= 0 && static_cast<size_t>(index) < outputs.size()bool onnxruntime::graph_utils::RemoveNode(onnxruntime::Graph &, onnxruntime::Node &)Should be unreachable if CanRemoveNodeAndMergeEdges is in sync with the logic here.onnxruntime::NodeArg &onnxruntime::graph_utils::AddInitializer(onnxruntime::Graph &, const onnx::TensorProto &)!graph.GetInitializedTensor(new_initializer.name(), existing)Initializer with same name exists. Name:void onnxruntime::graph_utils::ReplaceNodeInput(onnxruntime::Node &, int, onnxruntime::NodeArg &)Invalid input index for node . Index: ExplicitInputs: ImplicitInputs:void onnxruntime::graph_utils::AddNodeInput(onnxruntime::Node &, int, onnxruntime::NodeArg &)num_explicit_inputs == static_cast<size_t>(target_input_idx)FindPathFailed since multiple edges matched:CanUpdateImplicitInputNameInSubgraphs Implicit input name cannot be safely updated to in one of the subgraphs.bool onnxruntime::graph_utils::RemoveNodeWithSingleNodeInSingleUsedOutput(onnxruntime::Graph &, onnxruntime::Node &)std::all_of(output_edges.cbegin(), output_edges.cend(), [&src_idx](const GraphEdge& edge) { return edge.src_arg_index == src_idx; })void onnxruntime::graph_utils::UpdateImplicitInputNameInSubgraph(onnxruntime::Node &, const std::string &, const std::string &)std::count_if(subgraph_node.InputEdgesBegin(), subgraph_node.InputEdgesEnd(), [input_slot_index](const Node::EdgeEnd& entry) { return entry.GetDstArgIndex() == input_slot_index; }) == 0/Users/runner/work/1/s/onnxruntime/core/graph/graph_viewer.cconnxruntime::GraphViewer::GraphViewer(const onnxruntime::Graph &, const onnxruntime::IndexedSubGraph *)graph_->GetNode(idx) != nullptrnodeargMismatch between Graph and IndexedSubGraph. Input not found:Mismatch between Graph and IndexedSubGraph. Output not found:nodeMismatch between Graph and IndexedSubGraph. Node not found: const std::vector<NodeIndex> &onnxruntime::GraphViewer::GetNodesInTopologicalOrder(onnxruntime::ExecutionOrder) constconst std::vector<NodeIndex> &onnxruntime::GraphViewer::GetRootNodes() constfilter_info_ == nullptrShape/Users/runner/work/1/s/onnxruntime/core/graph/model.cconnxruntime::Model::Model(onnx::ModelProto &&, const onnxruntime::PathString &, const onnxruntime::IOnnxRuntimeOpSchemaRegistryList *, const logging::Logger &)Missing opset in the model. All ModelProtos MUST have at least one entry that specifies which version of the ONNX OperatorSet is being imported.ModelONNX Runtime only *guarantees* support for models stamped with opset version 7 or above for opset domain 'ai.onnx'. Please upgrade your model to opset 7 or higher. For now, this opset model may run depending upon legacy support of some older opset version operators.No graph was found in the protobuf.Protobuf parsing failed.<p_fd> less than 0.<p_fd> is less than 0.SaveProtobuf serialization failed.Graph is null. Invalid ORT format model.void onnxruntime::model_load_utils::ValidateOpsetForDomain(const std::unordered_map<std::string, int> &, const logging::Logger &, bool, const std::string &, int)ONNX Runtime only *guarantees* support for models stamped with official released onnx opset versions. Opset is under development and support for this is limited. The operator schemas and or other functionality may change before next ONNX release and in this case ONNX Runtime will not guarantee backward compatibility. Current official support for domain is till opset ValidateOpsetForDomain is under development and support for this is limited. The operator schemas and or other functionality could possibly change before next ONNX release and in this case ONNX Runtime will not guarantee backward compatibility. Current official support for domain Failed to load model with error: Load model failed. File doesn't exist failedsystem error number SaveModelDomain already set in registry/Users/runner/work/1/s/onnxruntime/core/graph/schema_registry.ccRegisterOpSetRegisterOpSchemaInternal, but it its domain is notknown by the checker., but it its version is higherthan the operator set version onnxruntime/Users/runner/work/1/s/onnxruntime/core/common/logging/logging.cconnxruntime::logging::LoggingManager::LoggingManager(std::unique_ptr<ISink>, onnxruntime::logging::Severity, bool, const onnxruntime::logging::LoggingManager::InstanceType, const std::string *, int)default_logger_id must be provided if instance_type is InstanceType::DefaultOnly one instance of LoggingManager created with InstanceType::Default can exist at any point in time.void onnxruntime::logging::LoggingManager::CreateDefaultLogger(const std::string &) [VIWEFampm is not a valid date is not a valid year is not a valid day/Users/runner/work/1/s/onnxruntime/core/common/path.ccParsestatic onnxruntime::Path onnxruntime::Path::Parse(const onnxruntime::PathString &)..ParsePathRootFailed to parse path root: /Users/runner/work/1/s/onnxruntime/core/common/profiler.cc::onnxruntime::TimePoint onnxruntime::profiling::Profiler::StartTime() constvoid onnxruntime::profiling::Profiler::Initialize(const logging::Logger *)session_logger != nullptrEndTimeAndRecordEventMaximum number of events reached, could not record profile event.Writing profiler data to file [ {"cat" : "","pid" :"tid" :"dur" :"ts" :"ph" : "X","name" :""args" : {" : " : "} @@ -10623,21 +10562,21 @@ if coordinate_transformation_mode is "tf_half_pixel_for_nn", <br/> x_original = (x_resized + 0.5) / scale, <br/> if coordinate_transformation_mode is "tf_crop_and_resize", <br/> x_original = length_resized > 1 ? start_x * (length_original - 1) + x_resized * (end_x - start_x) * (length_original - 1) / (length_resized - 1) : 0.5 * (start_x + end_x) * (length_original - 1).Value of attribute not specified should be of integer type and specify a type. does not specify a valid type.Target shape may not have multiple -1 dimensionsInvalid position of 0Invalid dimension value: Invalid Target shape product of 0Dimension could not be inferred: incompatible shapesRequired attribute axis is missingaxis must be in [-rank, rank-1].All inputs to Concat must have same rankInvalid value of attribute 'axis'. Rank= Value=Mismatch between number of splits () and outputs (Mismatch between the sum of 'split' () and the split dimension of the input (The input is not evenly splittableSlice op must have either three, four or five inputs.Incorrect or missing input value for starts and endsInput axes has incorrect lengthInput steps has incorrect lengthInput axes has invalid data'step' cannot be 0Only supports `int32_t` or `int64_t` inputs for starts/ends/axes/stepsInvalid attribute perm {}, input shape = {data tensor must have rank >= 1axis must be in [-r, r-1]'axes' attribute must not contain any duplicatesvalues in 'axes' are beyond the bounds of the computed output shapeBlocksize must be positiveInput tensor must be 4-dimensional'Repeats' input must be 1D tensor of type int64'Repeats' input has incorrect number of values. The number of values in 'repeats' must be equal to the number of input dimensions.Both `data` and `indices` input tensors in GatherND op need to have rank larger than 0.Last dimension of `indices` input tensor in GatherND op must not be larger than the rank of `data` tensor'pads' input must be a 1D (shape: [2 * input_rank]) tensor of type int64rank must be greater than axisRanks inferred () is not equal to the existing rank value (Number of elements of attribute 'scales' must be same as rank of input 'X'Attribute 'scales' must have floats type.Attribute 'scales' is required.Incorrect or missing attribute value for starts and endsAttribute axes has incorrect lengthOneHot node must have three inputs.Input 'depth' must be a scalar or rank 1 tensor.Input 'depth' must have exactly one element.Input 'values' must be rank 1 tensor.Input 'values' must have exactly two elements.Indices tensor must have rank >= 1'axis' must be in [-rank(indices)-1, rank(indices)]Attribute value for pads is requiredAttribute pads has incorrect lengthDimension value inferred () is not equal to the existing dim value (Number of elements of input 'sizes' must be same as rank of input 'X'Input 'sizes' must have int64 element type.Number of elements of input 'scales' must be same as rank of input 'X'Input 'scales' must have float element type.Data to be selectedThe indices, based on 0 as the first index of any dimension.Selected output data as an arrayThe input must be a tensor of a numeric type or string. The output will be of the same tensor type./Users/runner/work/1/s/cmake/external/onnx/onnx/defs/traditionalml/defs.ccData to be binarizedBinarized output dataThe input must be a tensor of a numeric type. The output will be of the same tensor type.Values greater than this are mapped to 1, others to 0.The input map that is to be cast to a tensorA tensor representing the same data as the input map, ordered by their keysmap(int64, string)map(int64, float)The input must be an integer map to either string or float.The output is a 1-D tensor of string, float, or integer.A string indicating the desired element type of the output tensor, one of 'TO_FLOAT', 'TO_STRING', 'TO_INT64'.map_formIndicates whether to only output as many values as are in the input (dense), or position the input based on using the key of the map as the index of the output (sparse).<br>One of 'DENSE', 'SPARSE'.If the value of map_form is 'SPARSE,' this attribute indicates the total length of the output tensor.Input dataOutput data. If strings are input, the output values are integers, and vice versa.The input must be a tensor of strings or integers, either [N,C] or [C].The output is a tensor of strings or integers. Its shape will be the same as the input shape.The strings of the map. This sequence must be the same length as the 'cats_int64s' sequenceThe integers of the map. This sequence must be the same length as the 'cats_strings' sequence.A string to use when an input integer value is not found in the map.<br>One and only one of the 'default_*' attributes must be defined.An integer to use when an input string value is not found in the map.<br>One and only one of the 'default_*' attributes must be defined.A dictionary.A 1-D tensor holding values from the input dictionary.map(string, int64)map(int64, double)map(string, float)map(string, double)The input must be a map from strings or integers to either strings or a numeric type. The key and value types cannot be the same.The output will be a tensor of the value type of the input map. It's shape will be [1,C], where C is the length of the input dictionary.A string vocabulary array.<br>One and only one of the vocabularies must be defined.An integer vocabulary array.<br>One and only one of the vocabularies must be defined.An ordered collection of tensors, all with the same element type.The output array, elements ordered as the inputs.The input type must be a tensor of a numeric type.The size of each input in the input listData to be processed.Imputed output dataThe input type must be a tensor of a numeric type, either [N,C] or [C]. The output type will be of the same tensor type and shape.Value(s) to change toA value that needs replacing.Value(s) to change to.Input data. It can be either tensor or scalar.Output data.The input type is a tensor of any shape.Output type is determined by the specified 'values_*' attribute.A list of strings. One and only one of 'keys_*'s should be set.A list of ints.A list of floats.A list of strings. One and only one of 'value_*'s should be set.A string.An integer.A float.Data to be classified.Classification outputs (one class per example).Classification scores ([N,E] - one score for each class and exampleThe input must be a tensor of a numeric type, and of of shape [N,C] or [C]. In the latter case, it will be treated as [1,C]The output will be a tensor of strings or integers.A collection of weights of the model(s).A collection of intercepts.Indicates whether to do OvR or multinomial (0=OvR is the default).Class labels when using string labels. One and only one 'classlabels' attribute must be defined.Class labels when using integer labels. One and only one 'classlabels' attribute must be defined.Indicates the transform to apply to the scores vector.<br>One of 'NONE,' 'SOFTMAX,' 'LOGISTIC,' 'SOFTMAX_ZERO,' or 'PROBIT'Data to be regressed.Regression outputs (one per target, per example).The input must be a tensor of a numeric type.Indicates the transform to apply to the regression output vector.<br>One of 'NONE,' 'SOFTMAX,' 'LOGISTIC,' 'SOFTMAX_ZERO,' or 'PROBIT'Weights of the model(s).Weights of the intercepts, if used.The total number of regression targets, 1 if not defined.Data to be encoded, a tensor of shape [N,C] or [C]Encoded output datanormOne of 'MAX,' 'L1,' 'L2'Data to be encoded.Encoded output data, having one more dimension than X.List of categories, ints.<br>One and only one of the 'cats_*' attributes must be defined.List of categories, strings.<br>One and only one of the 'cats_*' attributes must be defined.If true and category is not present, will return all zeros; if false and a category if not found, the operator will fail.Data to be scaled.Scaled output data.First, offset by this.<br>Can be length of features in an [N,F] tensor or length 1, in which case it applies to all features, regardless of dimension count.Second, multiply by this.<br>Can be length of features in an [N,F] tensor or length 1, in which case it applies to all features, regardless of dimension count.<br>Must be same length as 'offset'Class scores (one per class per example), if prob_a and prob_b are provided they are probabilities for each class, otherwise they are raw scores.The input must be a tensor of a numeric type, either [C] or [N,C].The output type will be a tensor of strings or integers, depending on which of the the classlabels_* attributes is used. Its size will match the bactch size of the input.The kernel type, one of 'LINEAR,' 'POLY,' 'RBF,' 'SIGMOID'.List of 3 elements containing gamma, coef0, and degree, in that order. Zero if unused for the kernel.First set of probability coefficients.Second set of probability coefficients. This array must be same size as prob_a.<br>If these are provided then output Z are probability estimates, otherwise they are raw scores.Indicates the transform to apply to the score. <br>One of 'NONE,' 'SOFTMAX,' 'LOGISTIC,' 'SOFTMAX_ZERO,' or 'PROBIT'Class labels if using string labels.<br>One and only one of the 'classlabels_*' attributes must be defined.Class labels if using integer labels.<br>One and only one of the 'classlabels_*' attributes must be defined.Regression outputs (one score per target per example).The input type must be a tensor of a numeric type, either [C] or [N,C].Chosen support vectorsFlag indicating whether the regression is a one-class SVM or not.Support vector coefficients.The number of support vectors.Indicates the transform to apply to the score. <br>One of 'NONE,' 'SOFTMAX,' 'LOGISTIC,' 'SOFTMAX_ZERO,' or 'PROBIT.'Input of shape [N,F]N, Top class for each pointThe class score for each class, for each point, a tensor of shape [N,E].The output type will be a tensor of strings or integers, depending on which of the the classlabels_* attributes is used.Tree id for each node.Node id for each node. Ids may restart at zero for each tree, but it not required to.Feature id for each node.Thresholds to do the splitting on for each node.Popularity of each node, used for performance and may be omitted.The node kind, that is, the comparison to make at the node. There is no comparison to make at a leaf node.<br>One of 'BRANCH_LEQ', 'BRANCH_LT', 'BRANCH_GTE', 'BRANCH_GT', 'BRANCH_EQ', 'BRANCH_NEQ', 'LEAF'Child node if expression is true.Child node if expression is false.For each node, define what to do in the presence of a missing value: if a value is missing (NaN), use the 'true' or 'false' branch based on the value in this array.<br>This attribute may be left undefined, and the defalt value is false (0) for all nodes.The id of the tree that this node is in.node id that this weight is for.The index of the class list that each weight is for.The weight for the class in class_id.Indicates the transform to apply to the score. <br> One of 'NONE,' 'SOFTMAX,' 'LOGISTIC,' 'SOFTMAX_ZERO,' or 'PROBIT.'Base values for classification, added to final class score; the size must be the same as the classes or can be left unassigned (assumed 0)N classesNode id for each node. Node ids must restart at zero for each tree and increase sequentially.Child node if expression is trueChild node if expression is falseFor each node, define what to do in the presence of a NaN: use the 'true' (if the attribute value is 1) or 'false' (if the attribute value is 0) branch based on the value in this array.<br>This attribute may be left undefined and the defalt value is false (0) for all nodes.The id of the tree that each node is in.The node id of each weightThe index of the target that each weight is forThe weight for each targetThe total number of targets.Defines how to aggregate leaf values within a target. <br>One of 'AVERAGE,' 'SUM,' 'MIN,' 'MAX.'The input valuesThe output mapseq(map(string, float))seq(map(int64, float))The output will be a sequence of string or integer maps to float.The keys when using string keys.<br>One and only one of the 'classlabels_*' attributes must be defined.The keys when using int keys.<br>One and only one of the 'classlabels_*' attributes must be defined.Label encoder has only one input.Label encoder has only one output.Only one of keys_*'s can be set in label encoder.Input type is not string tensor but key_strings is setInput type is not int64 tensor but keys_int64s is setInput type is not float tensor but keys_floats is setOnly one of values_*'s can be set in label encoder.Input's shape should be 1D or 2DInput data.The input type must be a tensor of integers or strings, of any shape.The output type will be a tensor of strings or integers, and will have the same shape as the input.A list of labels./Users/runner/work/1/s/cmake/external/onnx/onnx/defs/traditionalml/old.ccInferred elem type differs from existing elem type: () vs (Inferred shape and existing shape differ in rank: (Inferred shape and existing shape differ in dimension : (type case mismatch. existing= inferred=type case unsupported. existing=Graph has inputs but were provided, node name: (op_type:Warning: Shape inference does not support models with experimental operators: Warning: Unsupported operator . No schema registered for this operator.ONNX models don't support multiple opset version imports for a domain. Function input is out of boundsGraphProto attribute inferencing is not enabled in this InferenceContextImpl instance. does not contain a graph.output /Users/runner/work/1/s/cmake/external/protobuf/src/google/protobuf/arena.ccCHECK failed: (min_bytes) <= (std::numeric_limits<size_t>::max() - SerialArena::kBlockHeaderSize): /Users/runner/work/1/s/cmake/external/protobuf/src/google/protobuf/io/zero_copy_stream.ccThis ZeroCopyOutputStream doesn't support aliasing. Reaching here usually means a ZeroCopyOutputStream implementation bug./Users/runner/work/1/s/cmake/external/protobuf/src/google/protobuf/io/zero_copy_stream_impl.ccclose() failed: CHECK failed: !is_closed_: /Users/runner/work/1/s/cmake/external/protobuf/src/google/protobuf/io/zero_copy_stream_impl_lite.ccCHECK failed: (count) >= (0): CHECK failed: backup_bytes_ == 0 && buffer_.get() != NULL: BackUp() can only be called after Next().CHECK failed: (count) <= (buffer_used_): Can't back up over more bytes than were returned by the last call to Next(). Parameter to BackUp() can't be negative.CHECK failed: (backup_bytes_) == (0): CHECK failed: (buffer_used_) == (buffer_size_): /Users/runner/work/1/s/cmake/external/protobuf/src/google/protobuf/message_lite.ccparse exceeded maximum protobuf size of 2GB: Can't message of type "" because it is missing required fields: /Users/runner/work/1/s/cmake/external/protobuf/src/google/protobuf/parse_context.hCan't happenINFOWARNINGERRORFATAL[libprotobuf %s %s:%d] %s -%lu\x%02xtyfalse/Users/runner/work/1/s/cmake/external/re2/re2/bitstate.ccGrowStack() failed: njob_ = job_.size() = Unexpected opcode: arg Bad arg in kInstAltMatch: Bad arg in kInstCapture: /Users/runner/work/1/s/cmake/external/re2/re2/compile.ccshould never happenCompiler::Copy called!No ranges in char classMissing case in Compiler: |/Users/runner/work/1/s/cmake/external/re2/re2/dfa.ccDeadState in RunStateOnByteNULL state in RunStateOnByteUnexpected special state in RunStateOnByteStateSaver failed to restore state.context does not contain textFailed to analyze start state.RunStateOnByteUnlocked failed after ResetCacheRunStateOnByteUnlocked failed after Reset/Users/runner/work/1/s/cmake/external/re2/re2/nfa.ccunhandled in AddToThreadqUnhandled in stepBad args: nsubmatch=Unexpected opcode in short circuit: in ComputeFirstByte/Users/runner/work/1/s/cmake/external/re2/re2/onepass.ccCannot use SearchOnePass for unanchored matches.unhandled opcode: /Users/runner/work/1/s/cmake/external/re2/re2/parse.ccRepetitionWalker::ShortVisit calledConcat of unknown round: RE2: unexpected op: Bad call to ParseState::ParsePerlFlagsAddFoldedRange recurses too much.AnyBad hex digit \d\D\s\S\w\W[:alnum:][:^alnum:][:alpha:][:^alpha:][:ascii:][:^ascii:][:blank:][:^blank:][:cntrl:][:^cntrl:][:digit:][:^digit:][:graph:][:^graph:][:lower:][:^lower:][:print:][:^print:][:punct:][:^punct:][:space:][:^space:][:upper:][:^upper:][:word:][:^word:][:xdigit:][:^xdigit:]/Users/runner/work/1/s/cmake/external/re2/re2/re2.ccUnknown encoding Error parsing '': Error compiling 'Invalid RE2: RE2: invalid startpos, endpos pair. [startpos: endpos: text size: DFA out of memory: size bytemap range list count SearchDFA inconsistencySearchOnePass inconsistencySearchBitState inconsistencySearchNFA inconsistencyError reverse compiling '/Users/runner/work/1/s/cmake/external/re2/re2/regexp.ccRegexp not destroyed.Bad reference count Unexpected op in Regexp::Equal: no errorunexpected errorinvalid escape sequenceinvalid character classinvalid character class rangemissing ]missing )trailing \no argument for repetition operatorinvalid repetition sizebad repetition operatorinvalid perl operatorinvalid UTF-8invalid named capture groupNumCapturesWalker::ShortVisit called/Users/runner/work/1/s/cmake/external/re2/re2/walker-inl.hStack not empty.Walk NULL/Users/runner/work/1/s/cmake/external/re2/re2/simplify.ccCase not handled in ComputeSimple: CoalesceWalker::ShortVisit calledDoCoalesce failed: r1->op() is DoCoalesce failed: r2->op() is SimplifyWalker::ShortVisit calledSimplify case not handled: Malformed repeat [truncated](?:/Users/runner/work/1/s/cmake/external/re2/re2/tostring.cckRegexpCapture cap() == 0?P<>[^\x00-\x{10ffff}](?:)Bad final char: ?{%d,}{%d}{%d,%d}\C^$(?-m:^)(?-m:$)\z\b\B(?HaveMatch:%d)(){}[]*+?|.^$\[]^-\\\r\t\n\f\x{%x}AdlamAhomAnatolian_HieroglyphsArabicArmenianAvestanBalineseBamumBassa_VahBatakBengaliBhaiksukiBopomofoBrahmiBrailleBugineseBuhidCanadian_AboriginalCarianCaucasian_AlbanianCcCfChakmaChamCherokeeCoCommonCopticCsCuneiformCypriotCyrillicDeseretDevanagariDograDuployanEgyptian_HieroglyphsElbasanEthiopicGeorgianGlagoliticGothicGranthaGreekGujaratiGunjala_GondiGurmukhiHanHangulHanifi_RohingyaHanunooHatranHebrewHiraganaImperial_AramaicInheritedInscriptional_PahlaviInscriptional_ParthianJavaneseKaithiKannadaKatakanaKayah_LiKharoshthiKhmerKhojkiKhudawadiLLaoLatinLepchaLimbuLinear_ALinear_BLisuLlLmLoLtLuLycianLydianMahajaniMakasarMalayalamMandaicManichaeanMarchenMasaram_GondiMcMeMedefaidrinMeetei_MayekMende_KikakuiMeroitic_CursiveMeroitic_HieroglyphsMiaoMnModiMongolianMroMultaniMyanmarNNabataeanNdNew_Tai_LueNewaNkoNlNoNushuOghamOl_ChikiOld_HungarianOld_ItalicOld_North_ArabianOld_PermicOld_PersianOld_SogdianOld_South_ArabianOld_TurkicOriyaOsageOsmanyaPahawh_HmongPalmyrenePau_Cin_HauPcPdPePfPhags_PaPhoenicianPiPoPsPsalter_PahlaviRejangRunicSamaritanSaurashtraScSharadaShavianSiddhamSignWritingSinhalaSkSmSoSogdianSora_SompengSoyomboSundaneseSyloti_NagriSyriacTagalogTagbanwaTai_LeTai_ThamTai_VietTakriTamilTangutTeluguThaanaThaiTibetanTifinaghTirhutaUgariticVaiWarang_CitiYiZanabazar_SquareZlZpZsmu held in reader and writer mode simultaneously on entry to nsync_cv_wait_with_deadline() +%lu\x%02xtyfalse/Users/runner/work/1/s/cmake/external/re2/re2/bitstate.ccGrowStack() failed: njob_ = job_.size() = Unexpected opcode: arg Bad arg in kInstAltMatch: Bad arg in kInstCapture: /Users/runner/work/1/s/cmake/external/re2/re2/compile.ccshould never happenCompiler::Copy called!No ranges in char classMissing case in Compiler: |/Users/runner/work/1/s/cmake/external/re2/re2/dfa.ccDeadState in RunStateOnByteNULL state in RunStateOnByteUnexpected special state in RunStateOnByteStateSaver failed to restore state.context does not contain textFailed to analyze start state.RunStateOnByteUnlocked failed after ResetCacheRunStateOnByteUnlocked failed after Reset/Users/runner/work/1/s/cmake/external/re2/re2/nfa.ccunhandled in AddToThreadqUnhandled in stepBad args: nsubmatch=Unexpected opcode in short circuit: in ComputeFirstByte/Users/runner/work/1/s/cmake/external/re2/re2/onepass.ccCannot use SearchOnePass for unanchored matches.unhandled opcode: /Users/runner/work/1/s/cmake/external/re2/re2/parse.ccRepetitionWalker::ShortVisit calledConcat of unknown round: RE2: unexpected op: Bad call to ParseState::ParsePerlFlagsAddFoldedRange recurses too much.AnyBad hex digit \d\D\s\S\w\W[:alnum:][:^alnum:][:alpha:][:^alpha:][:ascii:][:^ascii:][:blank:][:^blank:][:cntrl:][:^cntrl:][:digit:][:^digit:][:graph:][:^graph:][:lower:][:^lower:][:print:][:^print:][:punct:][:^punct:][:space:][:^space:][:upper:][:^upper:][:word:][:^word:][:xdigit:][:^xdigit:]/Users/runner/work/1/s/cmake/external/re2/re2/re2.ccUnknown encoding Error parsing '': Error compiling 'Invalid RE2: RE2: invalid startpos, endpos pair. [startpos: endpos: text size: DFA out of memory: size bytemap range list count SearchDFA inconsistencySearchOnePass inconsistencySearchBitState inconsistencySearchNFA inconsistencyError reverse compiling '/Users/runner/work/1/s/cmake/external/re2/re2/regexp.ccRegexp not destroyed.Bad reference count Unexpected op in Regexp::Equal: no errorunexpected errorinvalid escape sequenceinvalid character classinvalid character class rangemissing ]missing )trailing \no argument for repetition operatorinvalid repetition sizebad repetition operatorinvalid perl operatorinvalid UTF-8invalid named capture groupNumCapturesWalker::ShortVisit called/Users/runner/work/1/s/cmake/external/re2/re2/walker-inl.hStack not empty.Walk NULL/Users/runner/work/1/s/cmake/external/re2/re2/simplify.ccCase not handled in ComputeSimple: CoalesceWalker::ShortVisit calledDoCoalesce failed: r1->op() is DoCoalesce failed: r2->op() is SimplifyWalker::ShortVisit calledSimplify case not handled: Malformed repeat [truncated](?:/Users/runner/work/1/s/cmake/external/re2/re2/tostring.cckRegexpCapture cap() == 0?P<>[^\x00-\x{10ffff}](?:)Bad final char: ?{%d,}{%d}{%d,%d}\C^$(?-m:^)(?-m:$)\z\b\B(?HaveMatch:%d)(){}[]*+?|.^$\[]^-\\\r\t\n\f\x{%x}AdlamAhomAnatolian_HieroglyphsArabicArmenianAvestanBalineseBamumBassa_VahBatakBengaliBhaiksukiBopomofoBrahmiBrailleBugineseBuhidCanadian_AboriginalCarianCaucasian_AlbanianCcCfChakmaChamCherokeeCoCommonCopticCsCuneiformCypriotCyrillicDeseretDevanagariDograDuployanEgyptian_HieroglyphsElbasanEthiopicGeorgianGlagoliticGothicGranthaGreekGujaratiGunjala_GondiGurmukhiHanHangulHanifi_RohingyaHanunooHatranHebrewHiraganaImperial_AramaicInheritedInscriptional_PahlaviInscriptional_ParthianJavaneseKaithiKannadaKatakanaKayah_LiKharoshthiKhmerKhojkiKhudawadiLLaoLatinLepchaLimbuLinear_ALinear_BLisuLlLmLoLtLuLycianLydianMahajaniMakasarMalayalamMandaicManichaeanMarchenMasaram_GondiMcMeMedefaidrinMeetei_MayekMende_KikakuiMeroitic_CursiveMeroitic_HieroglyphsMiaoMnModiMongolianMroMultaniMyanmarNNabataeanNdNew_Tai_LueNewaNkoNlNoNushuOghamOl_ChikiOld_HungarianOld_ItalicOld_North_ArabianOld_PermicOld_PersianOld_SogdianOld_South_ArabianOld_TurkicOriyaOsageOsmanyaPahawh_HmongPalmyrenePau_Cin_HauPcPdPePfPhags_PaPhoenicianPiPoPsPsalter_PahlaviRejangRunicSamaritanSaurashtraScSharadaShavianSiddhamSignWritingSinhalaSkSmSoSogdianSora_SompengSoyomboSundaneseSyloti_NagriSyriacTagalogTagbanwaTai_LeTai_ThamTai_VietTakriTamilTangutTeluguThaanaThaiTibetanTifinaghTirhutaUgariticVaiWarang_CitiYiZanabazar_SquareZlZpZsmu held in reader and writer mode simultaneously on entry to nsync_cv_wait_with_deadline() mu not held on entry to nsync_cv_wait_with_deadline() checking a waiter condition while unlocked attempt to nsync_mu_unlock() an nsync_mu held in read mode attempt to nsync_mu_unlock() an nsync_mu not held in write mode attempt to nsync_mu_runlock() an nsync_mu held in write mode attempt to nsync_mu_runlock() an nsync_mu not held in read mode nsync_mu not held in some mode when calling nsync_mu_wait_with_deadline() nsync_mu_wait woke but condition not true panic: unique_lock::lock: references null mutexunique_lock::lock: already lockedunique_lock::unlock: not locked}uWWxl8.l l(1 =F R})'OUA - 3o8(`g}}{{[ ! iq.,",}}{{   IAs j~ u*5_ jIAs j~ u*5_ j8 C]; GzLwրNv X+ clM XրNv X+ clM X 3 3 '$3{D_րN ''d ;1 '}u * + 3o8(`g}}hdi[ ! iq.,",}}hh   IAs j~ u*5_ jIAs j~ u*5_ j8 C]; GzLwրNv X+ clM XրNv X+ clM X 3 3 '$3{D_րN ''d ;1 '}u * ! w/ ;a }u * ! w/ ;a ߇\\dY\e<} G EsavA teT? Y<2D 4f?kE `+ D64j?? X <  @@ -10647,17 +10586,17 @@ ,^  > 4I  ?E P -} C&   YZ"g* 7z(7% v8]&5Uh] n   &% 3$6\Z )'ppxIAC O IAC O )'9)'9b)'^^ GhF R})'9)' #55E] P\8K@IN0"Nf%Q% K #pN88 O_ÀA""3DiI4= [w])'94""3J;yIAOM ofRn)'9ÀA== QdlրNoaY/Q9 qnNi I)':,#hh Dt= # ? -YQ!Q H K4BB Wom&)'##;95'c}tl€4$3< -F`j},l,>)'v5g; +YQ!Q H K4BB Wom&)'##;95'c}Y€4$3< +F`j}Y,>)'v5g;  y >  M - 4l PO - 1h Pyp   2 $ -Q     [ lx }0jꀀhMjCJ!'V:V*v ')' + 1h Pyp   2 $ -Q     [ lx }WꀀhMjCJ!'V:V*v ')' C&4"+G0)?450(p:&&"KG"G"DGPxx\"&Gm"pG"k"Guit450(p:450(p:450(p:450(p:450(p:4&F=4LG/Q'/Qd { yG [ g$$@Th u  M 9  W$X W    I  ]  X ? -3o r $  o  P  =  Mb 8  !!0&}cIAC NO 7 AIAC O )'rr Q)'9)'9)'gL[րNK a @ YvNcVF R}^^f  k  !Uv~  k # /񃀀VV^>E q +3o r $  o  P  =  Mb 8  !!0&}PIAC NO 7 AIAC O )'rr Q)'9)'9)'gL[րNK a @ YvNcVF R}^^f  k  !Uv~  k # /񃀀VV^>E q 2J\ `{ 0J O _MEM>>>>]e>>>/|7>ud}j20-G_]h][BnJE ] @t(@>d&&99 j&C+n @@ -11208,11 +11147,11 @@ & A5 0 R /      -3I 3>q k }#F  ( /2w # ŁJY) H!p+ + 1!YY8 .  a}][Zk{Kmm !  +3I 3>q k }#F  ( /2w # ŁJY) H!p+ + 1!YY8 .  a}\][Zk{Kmm !   s"v o %% | +%W%# 6"n f  M~ @@ -11235,11 +11174,11 @@  g q G  -U}t #'JX[[ +U} #'JX[[ u+fb#f}O} $ "5 B'i )u>D ÀAV {;QWW vt `mu#t<j[. iVF A  h   N   / O >mn<T|-IAC 6O 9)'Lct/"HHQy!oQM>! RQ< IhOHgUP tyb*  n  a 0l @@ -11249,13 +11188,13 @@ #K . && N(6 (Z  " H #"]#Gu# C R-:)W z#Lk!mJSy.   aKWI5h! $ $ $ $!!($!#$!!# -" #m" f#"$N#$$''$wg%'4&'S&!a'& D','''''}})' 6)'88@fƁ)D~N A %y; X[|΂]{F6Yx.wK#^ua7A`#NBgNf$)0MPꀀhQQUo~CyyQ 'qKj!qZ +" #m" f#"$N#$$''$wg%'4&'S&!a'& D','''''}})' 6)'88@fƁ)D~N A %y; X[|΂]{F6Yx.wK#^ua7A`#NBgNf$)0MPꀀhQQUo~CyyQ 'qKj!qZ nq3 1b=!Cd2w -?x_ 2  F :b & -#:05})'9e ?X tB     /M5 {\kꀀh7" x&]P2][  " /Ln V09)'9@@o!myq|@@!}@@!}@@o!myq|AAI]!'Sje #NS3rucN@ L)'<<oK9}u&   8#E+HWMꀀh+ A`38 X[pp   #e(ꀀhk t $ +?x_ 2  F :b & -#:05}@)'9e ?X tB     /M5 {\kꀀh7" x&]P2][  " /Ln V09)'9@@o!myq|@@!}@@!}@@o!myq|AAI]!'Sje #NS3rucN@ L)'<<oK9}u&   8#E+HWMꀀh+ A`38 X[pp   #e(ꀀhk t $ .B0D8 d_: 2 W <K [W )'BO XրNK a @ YvNcV)'9րNjj& K'$,gF R}IAC PO 9 C)'9)'94{   :IA 0 D f>SF44 Jo~. &1LGPրNSS%  -<.)'P)'9)'PF R}h ddlxTK [W IAII \ lրNZ3 !74qq;j'--0o)'Q UU 9~ 1 f  <K [W ÀAGGi)'9ll bvU-+s / Tc4s53I[)Pdu4e'.AyZq[ku m5eY]"IA3aPS)'  @@ -11264,19 +11203,19 @@ ! $ C     -   4}4d- _ڈ&!5"!"$`+a/^+ +   4}4d- _ڈ&!5"!"$`+a/^+ 6*b+V+eN+F+F*7>*t"1* *<N*Unb+$(&)u nb+ $' &~) vb+ $6&+ &( yb+. $%R # vb+6 $%Z && b+$N&:&(b+$&C%(b+$&&'b+$`$#b+$%#B@'%1%x"f&%"# "?b+^$$#b+$$A#P)((T'q "%P%! !# !] ! !) ! ! ~!-' i!a d!O!m  !  !  ! !! -Ɂ3"<6#Y)`s)2;0}xƁ$j&~A[`'}=Vu$h.# B_N::w  44(yQ41D 9UJA `SJ <J`++ 4PSt B 'H  qoZU @0 +K j    +Ɂ3"<6#Y)`s)2;0}Ɓ$j&~A[`'}=Vu$h.# B_N::w  44(yQ41D 9UJA `SJ <J`++ 4PSt B 'H  qoZU @0 +K j     /  P   @@ -11292,45 +11231,45 @@ %)*#=4Wf L54O^x D-)'xx}y4wK:`":84wK:`":84rK4_424wK:`":8Naa UqbYqo04wK:`":8N44s  4)'PÀAoV[)'`)'`)'S)'`][hh s' e  NTH { i)'`4< sF i#Z4 %)*#=4gg -)/ÀA*d8*ob@N<#_)_UA5S-)!+}}DUA4R,) *}}XUA4P*)(}}UA5T.)",}}<UA, 2RW(}}PUA, 2RW(}}p {% dd o4   c n8 { V!  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G P ] N L !8 +0 ]   &B Qi]  @@ -13474,21 +13416,17 @@ uK\SD][ ~= &j62h/4 3 uK\SD][ z= &f22d/4 3 uK\SD][ z= &f22d/4 3 uK\SD][ z= &f22d/4 3 uK\SD][ z= &f22d/4 3 -uK\SD][ z= &f22d/[a]/' 1CY[]QI' AE9Wm))'e)'e4||'',@lVi{"<1"mV<>z@&H!op-2)B}H -/ CV -Zt ^#1cS ^\\}P - -)'xx}uu8 $D# +uK\SD][ z= &f22d/[a]/' 1CY[]QI' AE9Wm))'e)'e4||'',@lVi{"<1"mV<>z@&H!op-2)B} / CV +Zt ^#1cS ^\\} )'xx}uu8 $D# | /2, $A z< SeH &`2r)'c/PÀAoo {#/ÀAii u#/ o ,Eb WI ] r&" H U a#S K    #/ CR ^#/  -X…,afTs $  = 0H,tT .,=C 2  B" d| "t r  `  | L 0X n Q z &3  :\ " .. |!>]q 4M Z &$72ki&} -)'  )'94C O +X…,afTs $  = 0H,tT .,=C 2  B" d| "t r  `  | L 0X n Q z &3  :\ " .. |!>]q 4M Z &$72ki&} )'  )'94C O  %  h  /  # 8\  : -, ] r    >v T o|   & M 2  ÀA %# @@ -13538,12 +13476,12 @@ ÀA++.O #A9][QQs uIIOmZOa8DL*ZZ f w M   b n) v&)'9F R}4((:}u ) OBW"*)'SSf4 > 1 $_} u& s^M qOf`[v4Z')'PF R}F R})'9ÀAgg s#/ A  ^ kg t)  5   6 P  f    ~iwKiw Q ~    I  5  -@  V p      ~)'4N [&@/6c-nN [&@/6c-n4]] n xUA -0B~G(ov}}   74GG X -bUA 0A}F(nu}} X  5ÀAOOh "[124;o 9{& 2A /wjer' uGg^Z ec)' 9(&  #C +0B~G(ov}}h  74GG X +bUA 0A}F(nu}} (  5ÀAOOh "[124;o 9{& 2A /wjer' uGg^Z ec)' 9(&  #C 3 #P3N &4~F6|nN[ f2!F /ÀAW0!QD /ÀA _&D2gBN Y&>-6a+nÀAgg s#/րN I&0H`^,':][tt  :S+h_ })'y)'yIAqb i(eրN   րN  @@ -13559,12 +13497,11 @@ %v{րNAA/k's/ww!|! 4-]i"v &!#% Vi%5AP &Fhw   c%J |  "+ W  / u " ![@ )o z "Mvw"eP0;X%&rB/1j~ b-lgg% &j -BZp, ` P&,OBB4 E@} )'zzuoo  ?<+ 7&9 `)'9)'P7 nd \&$JR>* n(Ufd?} h?? ^{  NJÀA &W2   I" <#*;VQdIAC !O 7)'++^:9h  bD D=@fzF R})'9)'9F R}FF '9HlZjy!ny  9u &N -@X}nƁ OZ`(`'F!b8 bz t Oj[! gA .+}} \ [! gA .+}}| [! gA .+}} t UA@Gfk(}}  UA C"Gin(}}X ij 2A2A2A)'++YD*)' +BZp, ` P&,OBB4 E@} )'zzuoo  ?<+ 7&9 `)'9)'P7 nd \&$JR>* n(Ufd?} h?? ^{  NJÀA &W2   I" <#*;VQdIAC !O 7)'++^:9h  bD D=@fzF R})'9)'9F R}FF '9HlZjy!ny  9Ɓ OZ`(`'F!b8 bz t Oj[! gA .+}}P [! gA .+}}ܦ H [! gA .+}}h Ԧ UA,U4G{(}} | UA .X7G~(}} $ 2A2A2A)'++YD*)' ,! )' ,! )' ,! )' ''# t0 l:B'# t0 l:B'# t0 @@ -13574,21 +13511,21 @@ 7)'SSf})'--`<9րN] i[ krT^>f"IA.. ; fH})' 9(&IA.. ; fH})' 7A  )'QQc)'++YD*2A)'Qh ddlqNK [W )'9IAII \ lF R}րNC O  -[PP^  z) *2F R})'922s:Z #.c[53Cv{} ÀAcc o&2 Ngg s#j +[PP^  z) *2F R})'922s:Z #.c[53Cv{}d ÀAcc o&2 Ngg s#j Y$3W!ÀAcc o&2 ÀA}} D&)2L'ÀAjj &v& 2. hhTL D8<T 4gv#ÀAjj &v& 2.  %# ??  Si3-|.H3.UA -(}}P  5 @] **!! *I) *j4!434Zd5}b5f5x~5333vj41M2+12]22%1y212F5 3 HF5  +(}}   5 @] **!! *I) *j4!434Zd5}b5f5x~5333vj41M2+12]22%1y212F5 3 HF5  1 3 1 3 /- /o ^/~ T/ ./ /s / . .?H. . -%~+0y+p2"21B13N1x""1p0 S0j1131L"1}/"/t+_+3J+[% +e1W*%*|-&<=y&+ &J)d) 3+`3d 2x )((|(!.((R({\' (!(!'" -)W"")"2""y2#E2,#4#2#4$2$"P1%813%3%1%3%& && '&}Т [][- %5 HWMg XR z +)W"")"2""y2#E2,#4#2#4$2$"P1%813%3%1%3%& && '&}0 [][- %5 HWMg XR z P E ) u|  z +o R e Z @ HS =  2 %   Y    4==Zi''66 *AZm6? * @@ -13626,13 +13563,13 @@ KÀA&&DaS][>>TB[N`vI\%Z ~ I3> I* GP?S *%WfC N#q^ gj  )[!GU1 C vD    * w4O H[>HF"ÀA++ 7&2ÀA;; G&2 ][\d7 # xC3v?N? gv Q%)'== vHJUA -fy(}}|t t UA %(}}$t t UA- 3SX(}}s 8t )'\\ e][ G8U9< GE/N b= p9W b`/Nb m29 /8 V ` q  7 # +fy(}}f Hg UA %(}}f f UA- 3SX(}},f f )'\\ e][ G8U9< GE/N b= p9W b`/Nb m29 /8 V ` q  7 # _3 #& -4Ia_9u>+is}}xq q UA ^(\(}} q q UA *;PU(}}}p 4q )' H][Fvc4Bhc4 &)'>4 &)'>)'HH]D)'HH]D)'CCXh)'CCXh4 &)'DDYD4 &)' >4 &)'>4 &)'GG\D4 &4 &4S T^I TR!4P \#z H9(bFDU`& F17h!d +4Ia_9u>+is}}c Dd UA ^(\(}}c c UA *;PU(}}}(c c )' H][Fvc4Bhc4 &)'>4 &)'>)'HH]D)'HH]D)'CCXh)'CCXh4 &)'DDYD4 &)' >4 &)'>4 &)'GG\D4 &4 &4S T^I TR!4P \#z H9(bFDU`& F17h!d 4!b.Ulj 4)]K)Y { W   ! !X  U  @@ -13730,11 +13667,11 @@ *)4 3|3PS2g=2r 2Eb)Z) * R)G)8 *D +)} * ) * 3] 3 (@ 1 N0 $0 / / \1 "o1 T1 1 "1 T$1.. |. <.&)( $1)4<(F_)x(v((((R)H.o,W,! +-+l +0}/ A/7.< /."-D/}.,.1+0+pS0-O- -,+{ ,,eR+g-n+T-j-,,-8 +QM+1-- ,+5 *n * -'*"-)H"g(b"# (#&'$2 '$ ($ x($ v($ % &%&g&s%:%%1E #W= J-w>4 =w)'''M8*րN!! *#;3F R}F R}k $ Bo  rIF R})' x)'9F R}@ -J)'nÀACC`f l(fs4<<B^R2+]G<9L&I"*LL$n52Q%}{%}Duuy *`, I}; qa"?Ɓ +J)'nÀACC`f l(fs4<<B^R2+]G<9L&I"*LL$n52Q%}{%}uuy *`, I}; qa"?Ɓ  $ ^^  C @@ -13787,15 +13724,15 @@ 0 /ÀA<YwM][yy [#@ /03c-!NN((L*J*% %#j## %f|% g%R%~ $$#g #"k" %f" " !Z ! ! !| ! !- g   g  8E"q>"Z Ac#( !(3(H#e#('Y '' - 'Mq' &&?&k "R&Zy(Il'c@" #+G#u" PvR F2 }lIAC O ÀAd7.M1&ou8W"+o[@d"" q" + 'Mq' &&?&k "R&Zy(Il'c@" #+G#u" PvR F2 }IAC O ÀAd7.M1&ou8W"+o[@d"" q" "! !$ r$# # # # # c#># o#m# Y#V"^ -"h "G"F "9#9 "1# /# "#| # YX v ! !o[!8!   S 2 B [T   }ÀApp |#/        +"h "G"F "9#9 "1# /# "#| # YX v ! !o[!8!   S 2 B [T   }ÀApp |#/         `  ف z   V t  h  ~    _ Up 9x M]0$` p ~ e   @@ -13874,21 +13811,21 @@ G ?    $ 0 & e r *    WIAC O IA00^bEGV9Tl -v 0N,z #aG)!> ^m s}}}ǁoo `  e1CtP [+ ?}|{{ J pCP =?lpanszx?}{OO ny XCm}X{4nn Uy3q!uLL P`# !  +v 0N,z #aG)!> ^m s}}pǁoo `  e1CtP [+ ?}4o{{ J pCP =?lpanszx?}\nOO ny XCm}m4nn Uy3q!uLL P`# !  N__e}V`I/ `g|"K!Rs\RDn )'9ƁFF 3 PH    :Sv % )'OIA..DIAC O )'t ÀA((FJÄ́+DS 2 K$ .   T?$  ~ )D0x p 0u) $ ) k  f 7 ! X  -F  K p ?1C uG1 ?n}uրN!! [L &W$ { sQ- (9[L &W$ { sQ- (9uz DVy  k' y-Vq9 DBn)'(nF R})'9F R} + -k)'9)'9)'!9)'!9 !'#Iۂa   4 v# +F  K p ?1C uG1 ?n}xgրN!! [L &W$ { sQ- (9[L &W$ { sQ- (9uz DVy  k' y-Vq9 DBn)'(nF R})'9F R} + -k)'9)'9)'!9)'!9 !'#Iۂa   4 v# h}V Q# v-#n8AN` 1l# C-;  .[ [# ~#v8PN"' V bF4@@ V _]5-Mz++_`#=!Avz{z)'66:@uTT E*7EG 3S%5GXN[[ p y-U)'LL lt'H T-/    V2 < | !,    4 @@ -13908,11 +13845,11 @@ i d&Nf{| v&0 /G_]U)'66qEBNm|~₀7b p y2 t `Z y ',Sa l, L W,    a$`u}M.C) 4,` , &Kq   ꀀhKK VV#ycXvI TRL4pp)'44Gc)'// i:DÀA 4PfÀAll }uO_ FV / -94#3:8}M$ H-#( U1,41XE!:e][:}+4s53I[-Ga~[-E: GQc!4~~!Ikhhj  b+ZORj J}#. V:5][fat-&f<i)']]p)'zzÀA?? Jx\)'99lH9ÀA\\kz;ÀA  p , ; n J ;)']]p4/D `!Hf@!"7|-}N..ALRo.񃀀v]Y"nKK[s%'0^sj'O 0 {  4 qf 2 '';}/xXs{D "" R  f@[)'9)'O[a]/' 1CY[al>6.@&RhLL,{Go1,j`G),bGF f,ZGQ-JF,G',RVG,JG%7,BfGz,:Go54d_/i4d_/i4d_/i4d_/i4d_/i4d_/i4A</qF!o7MZ+bOJWoF J 24F }J 1F~ AJ 2Fv J P2FD Ja 2GF< JL /# Jm   J  +94#3:8},@$ H-#( U1,41XE!:e][:}+4s53I[-Ga~[-E: GQc!4~~!Ikhhj  b+ZORj J}#. V:5][fat-&f<i)']]p)'zzÀA?? Jx\)'99lH9ÀA\\kz;ÀA  p , ; n J ;)']]p4/D `!Hf@!"7|-}N..ALRo.񃀀v]Y"nKK[s%'0^sj'O 0 {  4 qf 2 '';}/xXs{D "" R  f@[)'9)'O[a]/' 1CY[al>6.@&RhLL,{Go1,j`G),bGF f,ZGQ-JF,G',RVG,JG%7,BfGz,:Go54d_/i4d_/i4d_/i4d_/i4d_/i4d_/i4A</qF!o7MZ+bOJWoF J 24F }J 1F~ AJ 2Fv J P2FD Ja 2GF< JL /# Jm   J  - Jw  ' J @@ -13926,11 +13863,11 @@ I   2 I {   I   3 I~ | v4d_/i4d_/i4y)$(`.!4y)$(`.!4y)$(`.!ц``,G!PV =  N  - I     mIJ0B-XnJN:L/~J' hJu)@pJ_hzZUI@/;2J*|' %*JtIy V! -%m}-N20}$.    X sH030, _G $G 2M`q \GA &m  GN  G4d_/i4|(4d_/i4y)$(`.!IAC O 4d_/i4/5+4y)$(`.!4y72+o<%J)'ww)'22t:O)'22u:P)'22J|H)'22J|H4AAg)'66(^P4hh-F=ᅀii Yr =qyZ7FM !Tz7F 9  ] l  *k. +%m}-N20}     X sH030, _G $G 2M`q \GA &m  GN  G4d_/i4|(4d_/i4y)$(`.!IAC O 4d_/i4/5+4y)$(`.!4y72+o<%J)'ww)'22t:O)'22u:P)'22J|H)'22J|H4AAg)'66(^P4hh-F=ᅀii Yr =qyZ7FM !Tz7F 9  ] l  *k. jm> j     +m4   3 o < N $ [ p)) o.h*Y5(I (JI  T/nIGB)'9)'9u= +4gO/N '/YN16G$}1G 6G }Gj׃DD& l { '  R> ; W 0 <U } u  K N  i j Y B -@ MS  S j{ S c` /d IV  /T ' IF p @@ -14468,11 +14405,11 @@ p?$+?D6Lu t V} T   2 w #0   +e  `U X !y      (!In Im } NJ(#1  I ^ -+-JJve q~ c] h6SC 38}{ēxՂcc  ++-JJve q~ c] h6SC 38}{$؅Ղcc  9 'O< + tp X   @@ -14533,13 +14470,13 @@ N11onnxruntime25QDQPropagationTransformerE   N11onnxruntime20QDQS8ToU8TransformerENSt3__110__function6__funcIZN11onnxruntime42Register_MaxPool_qdq_QDQMaxPoolTransformerEvE3$_0NS_9allocatorIS3_EEFNS_10unique_ptrINS2_22QDQOperatorTransformerENS_14default_deleteIS7_EEEERNS2_4NodeERNS2_5GraphEEEEN11onnxruntime21QDQMaxPoolTransformerEN11onnxruntime20QDQSimpleTransformerE ZN11onnxruntime42Register_MaxPool_qdq_QDQMaxPoolTransformerEvE3$_0NSt3__110__function6__funcIZN11onnxruntime41Register_Reshape_qdq_QDQSimpleTransformerEvE3$_1NS_9allocatorIS3_EEFNS_10unique_ptrINS2_22QDQOperatorTransformerENS_14default_deleteIS7_EEEERNS2_4NodeERNS2_5GraphEEEEZN11onnxruntime41Register_Reshape_qdq_QDQSimpleTransformerEvE3$_1NSt3__110__function6__funcIZN11onnxruntime40Register_Gather_qdq_QDQSimpleTransformerEvE3$_2NS_9allocatorIS3_EEFNS_10unique_ptrINS2_22QDQOperatorTransformerENS_14default_deleteIS7_EEEERNS2_4NodeERNS2_5GraphEEEEZN11onnxruntime40Register_Gather_qdq_QDQSimpleTransformerEvE3$_2NSt3__110__function6__funcIZN11onnxruntime43Register_Transpose_qdq_QDQSimpleTransformerEvE3$_3NS_9allocatorIS3_EEFNS_10unique_ptrINS2_22QDQOperatorTransformerENS_14default_deleteIS7_EEEERNS2_4NodeERNS2_5GraphEEEEZN11onnxruntime43Register_Transpose_qdq_QDQSimpleTransformerEvE3$_3N11onnxruntime14QDQTransformerE  N11onnxruntime15ReluQuantFusionE  N11onnxruntime12FuseReluClipE  N11onnxruntime13ReshapeFusionEN11onnxruntime25RuleBasedGraphTransformerE N11onnxruntime18ShapeToInitializerE̼+N11onnxruntime19SkipLayerNormFusionE  - 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MlasConvPostProcessFloatGetFunctionEntryByNameKOrtP_ZMlas+GetApiBaseSessionOptionsAppendExecutionProvider_CPUVTNWN11onnxruntime11concurrency10ThreadPool15ParallelSection24current_parallel_sectionESIVN4onnxGemSgemmCoPoolReduceMaximumF32KernelAvx ErfKernelFma3mvU8S8KernelAvxDoubleKernelFloatKernelU8 SseAvxFma3SseAvxFma3TransposePackB16x4KernelM1SseAvxnvmpute NchwDepthwiseFloatKernelPointwiseFloatKernelFloatKernelcFloatKernelSseAvxFma3SseAvxFma3SseAvxFma3SseAvxFma3SseFilterFma3FilterAvx 1Output12Output13Output14Output1źƺǺɺMaximumFloatKernelAverageSseAvx ˺ExcludePadFloatKernelIncludePadFloatKernelSseAvx ̺SseAvx κϺ512F512FAvxTransposeBAvx512F512F໻512F512F1Output 2Output +@__ZNSt3__113basic_ostreamIcNS_11char_traitsIcEEElsEjq @__ZNSt3__113basic_ostreamIcNS_11char_traitsIcEEElsElq @__ZNSt3__113basic_ostreamIcNS_11char_traitsIcEEElsEmq @__ZNSt3__113basic_ostreamIcNS_11char_traitsIcEEElsEsq @__ZNSt3__113basic_ostreamIcNS_11char_traitsIcEEElsEtq 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MlasConvPostProcessFloatGetFunctionEntryByNameKOrtP_ZMlas=GetApiBaseSessionOptionsAppendExecutionProvider_CPUVTNWN11onnxruntime11concurrency10ThreadPool15ParallelSection24current_parallel_sectionESIVN4onnxŬGemSgemmCoPoolReduceMaximumF32KernelAvx ErfKernelFma3mvU8S8KernelAvxDoubleKernelFloatKernelU8 SseAvxFma3ЕSseAvxFma3TransposePackB16x4KernelM1SseAvxnvmpute NchwDepthwiseFloatKernelPointwiseFloatKernelFloatKernelcFloatKernelSseAvxFma3SseAvxFma3SseAvxFma3ӹSseAvxFma3չSseFilterFma3FilterAvx 1Output12Output13Output14Output1MaximumFloatKernelAverageSseAvx ExcludePadFloatKernelIncludePadFloatKernelSseAvx SseAvx 512F512FAvxTransposeBAvx঺ૺЭ512F512F512F512F1Output 2Output 3Output 4Output 1 2 3 -߻Filter 512FFilter1Output 2Output +℻Filter 512FFilter1Output 2Output 3Output -4Output 1 2 3 ߻߻߻1 +4Output 1 2 3 ℻ꅻꅻ1 2 3 -1 +ц1 2 3 -1 -2 3 1 +ц1 +2 3 ω1 2 -3 1 2 3 1 2 3 512F512F512FS Log ExpF32KernelTanhF32KernelFma3oftmaxOutputF32KernelAvx umExpF32KernelSoftmaxOutputF32KernelAvx isticF32KernelFma3S8 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ntime21BuildKernelCreateInfoINS_53kCpuExecutionProvider_Less_kOnnxDomain_ver9_12_doubleEEENS_16KernelCreateInfoEv__ZN11onnxruntime21BuildKernelCreateInfoINS_54kCpuExecutionProvider_Less_kOnnxDomain_ver9_12_int32_tEEENS_16KernelCreateInfoEv__ZN11onnxruntime21BuildKernelCreateInfoINS_54kCpuExecutionProvider_Less_kOnnxDomain_ver9_12_int64_tEEENS_16KernelCreateInfoEv__ZN11onnxruntime21BuildKernelCreateInfoINS_50kCpuExecutionProvider_Less_kOnnxDomain_ver13_floatEEENS_16KernelCreateInfoEv__ZN11onnxruntime21BuildKernelCreateInfoINS_51kCpuExecutionProvider_Less_kOnnxDomain_ver13_doubleEEENS_16KernelCreateInfoEv__ZN11onnxruntime21BuildKernelCreateInfoINS_52kCpuExecutionProvider_Less_kOnnxDomain_ver13_int32_tEEENS_16KernelCreateInfoEv__ZN11onnxruntime21BuildKernelCreateInfoINS_52kCpuExecutionProvider_Less_kOnnxDomain_ver13_int64_tEEENS_16KernelCreateInfoEv__ZN11onnxruntime21BuildKernelCreateInfoINS_54kCpuExecutionProvider_Greater_kOnnxDomain_ver7_8_floatEEENS_16KernelCreateInfoEv__ZN11onnxruntime21BuildKernelCreateInfoINS_55kCpuExecutionProvider_Greater_kOnnxDomain_ver7_8_doubleEEENS_16KernelCreateInfoEv__ZN11onnxruntime21BuildKernelCreateInfoINS_55kCpuExecutionProvider_Greater_kOnnxDomain_ver9_12_floatEEENS_16KernelCreateInfoEv__ZN11onnxruntime21BuildKernelCreateInfoINS_56kCpuExecutionProvider_Greater_kOnnxDomain_ver9_12_doubleEEENS_16KernelCreateInfoEv__ZN11onnxruntime21BuildKernelCreateInfoINS_57kCpuExecutionProvider_Greater_kOnnxDomain_ver9_12_int32_tEEENS_16KernelCreateInfoEv__ZN11onnxruntime21BuildKernelCreateInfoINS_57kCpuExecutionProvider_Greater_kOnnxDomain_ver9_12_int64_tEEENS_16KernelCreateInfoEv__ZN11onnxruntime21BuildKernelCreateInfoINS_53kCpuExecutionProvider_Greater_kOnnxDomain_ver13_floatEEENS_16KernelCreateInfoEv__ZN11onnxruntime21BuildKernelCreateInfoINS_54kCpuExecutionProvider_Greater_kOnnxDomain_ver13_doubleEEENS_16KernelCreateInfoEv__ZN11onnxruntime21BuildKernelCreateInfoINS_55kCpuExecutionProvider_Greater_kOnnxDomain_ver13_int32_tEEENS_16KernelCreateInfoEv__ZN11onnxruntime21BuildKernelCreateInfoINS_55kCpuExecutionProvider_Greater_kOnnxDomain_ver13_int64_tEEENS_16KernelCreateInfoEv__ZN11onnxruntime21BuildKernelCreateInfoINS_52kCpuExecutionProvider_Equal_kOnnxDomain_ver7_10_boolEEENS_16KernelCreateInfoEv__ZN11onnxruntime21BuildKernelCreateInfoINS_55kCpuExecutionProvider_Equal_kOnnxDomain_ver7_10_int32_tEEENS_16KernelCreateInfoEv__ZN11onnxruntime21BuildKernelCreateInfoINS_55kCpuExecutionProvider_Equal_kOnnxDomain_ver7_10_int64_tEEENS_16KernelCreateInfoEv__ZN11onnxruntime21BuildKernelCreateInfoINS_53kCpuExecutionProvider_Equal_kOnnxDomain_ver7_10_floatEEENS_16KernelCreateInfoEv__ZN11onnxruntime21BuildKernelCreateInfoINS_54kCpuExecutionProvider_Equal_kOnnxDomain_ver7_10_doubleEEENS_16KernelCreateInfoEv__ZN11onnxruntime21BuildKernelCreateInfoINS_53kCpuExecutionProvider_Equal_kOnnxDomain_ver11_12_boolEEENS_16KernelCreateInfoEv__ZN11onnxruntime21BuildKernelCreateInfoINS_56kCpuExecutionProvider_Equal_kOnnxDomain_ver11_12_int32_tEEENS_16KernelCreateInfoEv__ZN11onnxruntime21BuildKernelCreateInfoINS_56kCpuExecutionProvider_Equal_kOnnxDomain_ver11_12_int64_tEEENS_16KernelCreateInfoEv__ZN11onnxruntime21BuildKernelCreateInfoINS_54kCpuExecutionProvider_Equal_kOnnxDomain_ver11_12_floatEEENS_16KernelCreateInfoEv__ZN11onnxruntime21BuildKernelCreateInfoINS_55kCpuExecutionProvider_Equal_kOnnxDomain_ver11_12_doubleEEENS_16KernelCreateInfoEv__ZN11onnxruntime21BuildKernelCreateInfoINS_50kCpuExecutionProvider_Equal_kOnnxDomain_ver13_boolEEENS_16KernelCreateInfoEv__ZN11onnxruntime21BuildKernelCreateInfoINS_53kCpuExecutionProvider_Equal_kOnnxDomain_ver13_int32_tEEENS_16KernelCreateInfoEv__ZN11onnxruntime21BuildKernelCreateInfoINS_53kCpuExecutionProvider_Equal_kOnnxDomain_ver13_int64_tEEENS_16KernelCreateInfoEv__ZN11onnxruntime21BuildKernelCreateInfoINS_51kCpuExecutionProvider_Equal_kOnnxDomain_ver13_floatEEENS_16KernelCreateInfoEv__ZN11onnxruntime21BuildKernelCreateInfoINS_52kCpuExecutionProvider_Equal_kOnnxDomain_ver13_doubleEEENS_16KernelCreateInfoEv__ZN11onnxruntime21BuildKernelCreateInfoINS_57kCpuExecutionProvider_LessOrEqual_kOnnxDomain_ver12_floatEEENS_16KernelCreateInfoEv__ZN11onnxruntime21BuildKernelCreateInfoINS_58kCpuExecutionProvider_LessOrEqual_kOnnxDomain_ver12_doubleEEENS_16KernelCreateInfoEv__ZN11onnxruntime21BuildKernelCreateInfoINS_59kCpuExecutionProvider_LessOrEqual_kOnnxDomain_ver12_int32_tEEENS_16KernelCreateInfoEv__ZN11onnxruntime21BuildKernelCreateInfoINS_59kCpuExecutionProvider_LessOrEqual_kOnnxDomain_ver12_int64_tEEENS_16KernelCreateInfoEv__ZN11onnxruntime21BuildKernelCreateInfoINS_60kCpuExecutionProvider_GreaterOrEqual_kOnnxDomain_ver12_floatEEENS_16KernelCreateInfoEv__ZN11onnxruntime21BuildKernelCreateInfoINS_61kCpuExecutionProvider_GreaterOrEqual_kOnnxDomain_ver12_doubleEEENS_16KernelCreateInfoEv__ZN11onnxruntime21BuildKernelCreateInfoINS_62kCpuExecutionProvider_GreaterOrEqual_kOnnxDomain_ver12_int32_tEEENS_16KernelCreateInfoEv__ZN11onnxruntime21BuildKernelCreateInfoINS_62kCpuExecutionProvider_G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ED1Ev__ZN11onnxruntime4LessIxED0Ev__ZNK11onnxruntime4LessIxE7ComputeEPNS_15OpKernelContextE__ZZNK11onnxruntime4LessIxE7ComputeEPNS_15OpKernelContextEENUlRNS_15BroadcastHelperEE_8__invokeES5___ZZNK11onnxruntime4LessIxE7ComputeEPNS_15OpKernelContextEENUlRNS_15BroadcastHelperEE0_8__invokeES5___ZZNK11onnxruntime4LessIxE7ComputeEPNS_15OpKernelContextEENUlRNS_15BroadcastHelperEE1_8__invokeES5___ZZN11onnxruntime21BuildKernelCreateInfoINS_50kCpuExecutionProvider_Less_kOnnxDomain_ver13_floatEEENS_16KernelCreateInfoEvEN5$_1218__invokeERKNS_12OpKernelInfoE__ZZN11onnxruntime21BuildKernelCreateInfoINS_51kCpuExecutionProvider_Less_kOnnxDomain_ver13_doubleEEENS_16KernelCreateInfoEvEN5$_1228__invokeERKNS_12OpKernelInfoE__ZZN11onnxruntime21BuildKernelCreateInfoINS_52kCpuExecutionProvider_Less_kOnnxDomain_ver13_int32_tEEENS_16KernelCreateInfoEvEN5$_1238__invokeERKNS_12OpKernelInfoE__ZZN11onnxruntime21BuildKernelCreateInfoINS_52kCpuExecutionProvider_Less_kOnnxDomain_ver13_int64_tEEENS_16KernelCreateInfoEvEN5$_1248__invokeERKNS_12OpKernelInfoE__ZZN11onnxruntime21BuildKernelCreateInfoINS_54kCpuExecutionProvider_Greater_kOnnxDomain_ver7_8_floatEEENS_16KernelCreateInfoEvEN5$_1258__invokeERKNS_12OpKernelInfoE__ZN11onnxruntime7GreaterIfED1Ev__ZN11onnxruntime7GreaterIfED0Ev__ZNK11onnxruntime7GreaterIfE7ComputeEPNS_15OpKernelContextE__ZZNK11onnxruntime7GreaterIfE7ComputeEPNS_15OpKernelContextEENUlRNS_15BroadcastHelperEE_8__invokeES5___ZZNK11onnxruntime7GreaterIfE7ComputeEPNS_15OpKernelContextEENUlRNS_15BroadcastHelperEE0_8__invokeES5___ZZNK11onnxruntime7GreaterIfE7ComputeEPNS_15OpKernelContextEENUlRNS_15BroadcastHelperEE1_8__invokeES5___ZZN11onnxruntime21BuildKernelCreateInfoINS_55kCpuExecutionProvider_Greater_kOnnxDomain_ver7_8_doubleEEENS_16KernelCreateInfoEvEN5$_1268__invokeERKNS_12OpKernelInfoE__ZN11onnxruntime7GreaterIdED1Ev__ZN11onnxruntime7GreaterIdED0Ev__ZNK11onnxruntime7GreaterIdE7ComputeEPNS_15OpKernelContextE__ZZNK11onnxruntime7GreaterIdE7ComputeEPNS_15OpKernelContextEENUlRNS_15BroadcastHelperEE_8__invokeES5___ZZNK11onnxruntime7GreaterIdE7ComputeEPNS_15OpKernelContextEENUlRNS_15BroadcastHelperEE0_8__invokeES5___ZZNK11onnxruntime7GreaterIdE7ComputeEPNS_15OpKernelContextEENUlRNS_15BroadcastHelperEE1_8__invokeES5___ZZN11onnxruntime21BuildKernelCreateInfoINS_55kCpuExecutionProvider_Greater_kOnnxDomain_ver9_12_floatEEENS_16KernelCreateInfoEvEN5$_1278__invokeERKNS_12OpKernelInfoE__ZZN11onnxruntime21BuildKernelCreateInfoINS_56kCpuExecutionProvider_Greater_kOnnxDomain_ver9_12_doubleEEENS_16KernelCreateInfoEvEN5$_1288__invokeERKNS_12OpKernelInfoE__ZZN11onnxruntime21BuildKernelCreateInfoINS_57kCpuExecutionProvider_Greater_kOnnxDomain_ver9_12_int32_tEEENS_16KernelCreateInfoEvEN5$_1298__invokeERKNS_12OpKernelInfoE__ZN11onnxruntime7GreaterIiED1Ev__ZN11onnxruntime7GreaterIiED0Ev__ZNK11onnxruntime7GreaterIiE7ComputeEPNS_15OpKernelContextE__ZZNK11onnxruntime7GreaterIiE7ComputeEPNS_15OpKernelContextEENUlRNS_15BroadcastHelperEE_8__invokeES5___ZZNK11onnxruntime7GreaterIiE7ComputeEPNS_15OpKernelContextEENUlRNS_15BroadcastHelperEE0_8__invokeES5___ZZNK11onnxruntime7GreaterIiE7ComputeEPNS_15OpKernelContextEENUlRNS_15BroadcastHelperEE1_8__invokeES5___ZZN11onnxruntime21BuildKernelCreateInfoINS_57kCpuExecutionProvider_Greater_kOnnxDomain_ver9_12_int64_tEEENS_16KernelCreateInfoEvEN5$_1308__invokeERKNS_12OpKernelInfoE__ZN11onnxruntime7GreaterIxED1Ev__ZN11onnxruntime7GreaterIxED0Ev__ZNK11onnxruntime7GreaterIxE7ComputeEPNS_15OpKernelContextE__ZZNK11onnxruntime7GreaterIxE7ComputeEPNS_15OpKernelContextEENUlRNS_15BroadcastHelperEE_8__invokeES5___ZZNK11onnxruntime7GreaterIxE7ComputeEPNS_15OpKernelContextEENUlRNS_15BroadcastHelperEE0_8__invokeES5___ZZNK11onnxruntime7GreaterIxE7ComputeEPNS_15OpKernelContextEENUlRNS_15BroadcastHelperEE1_8__invokeES5___ZZN11onnxruntime21BuildKernelCreateInfoINS_53kCpuExecutionProvider_Greater_kOnnxDomain_ver13_floatEEENS_16KernelCreateInfoEvEN5$_1318__invokeERKNS_12OpKernelInfoE__ZZN11onnxruntime21BuildKernelCreateInfoINS_54kCpuExecutionProvider_Greater_kOnnxDomain_ver13_doubleEEENS_16KernelCreateInfoEvEN5$_1328__invokeERKNS_12OpKernelInfoE__ZZN11onnxruntime21BuildKernelCreateInfoINS_55kCpuExecutionProvider_Greater_kOnnxDomain_ver13_int32_tEEENS_16KernelCreateInfoEvEN5$_1338__invokeERKNS_12OpKernelInfoE__ZZN11onnxruntime21BuildKernelCreateInfoINS_55kCpuExecutionProvider_Greater_kOnnxDomain_ver13_int64_tEEENS_16KernelCreateInfoEvEN5$_1348__invokeERKNS_12OpKernelInfoE__ZZN11onnxruntime21BuildKernelCreateInfoINS_52kCpuExecutionProvider_Equal_kOnnxDomain_ver7_10_boolEEENS_16KernelCreateInfoEvEN5$_1358__invokeERKNS_12OpKernelInfoE__ZN11onnxruntime5EqualIbED1Ev__ZN11onnxruntime5EqualIbED0Ev__ZNK11onnxruntime5EqualIbE7ComputeEPNS_15OpKernelContextE__ZZNK11onnxruntime5EqualIbE7ComputeEPNS_15OpKernelContextEENUlRNS_15BroadcastHelperEE_8__invokeES5___ZZNK11onnxruntime5EqualIbE7ComputeEPNS_15OpKernelContextEENUlRNS_15BroadcastHelperEE0_8__invokeES5___ZZNK11onnxruntime5EqualIbE7ComputeEPNS_15OpKernelContextEENUlRNS_15BroadcastHelperEE1_8_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NUlRNS_15BroadcastHelperEE_8__invokeES5___ZZNK11onnxruntime11LessOrEqualIdE7ComputeEPNS_15OpKernelContextEENUlRNS_15BroadcastHelperEE0_8__invokeES5___ZZNK11onnxruntime11LessOrEqualIdE7ComputeEPNS_15OpKernelContextEENUlRNS_15BroadcastHelperEE1_8__invokeES5___ZZN11onnxruntime21BuildKernelCreateInfoINS_59kCpuExecutionProvider_LessOrEqual_kOnnxDomain_ver12_int32_tEEENS_16KernelCreateInfoEvEN5$_1528__invokeERKNS_12OpKernelInfoE__ZN11onnxruntime11LessOrEqualIiED1Ev__ZN11onnxruntime11LessOrEqualIiED0Ev__ZNK11onnxruntime11LessOrEqualIiE7ComputeEPNS_15OpKernelContextE__ZZNK11onnxruntime11LessOrEqualIiE7ComputeEPNS_15OpKernelContextEENUlRNS_15BroadcastHelperEE_8__invokeES5___ZZNK11onnxruntime11LessOrEqualIiE7ComputeEPNS_15OpKernelContextEENUlRNS_15BroadcastHelperEE0_8__invokeES5___ZZNK11onnxruntime11LessOrEqualIiE7ComputeEPNS_15OpKernelContextEENUlRNS_15BroadcastHelperEE1_8__invokeES5___ZZN11onnxruntime21BuildKernelCreateInfoINS_59kCpuExecutionProvider_LessOrEqual_kOnnxDomain_ver12_int64_tEEENS_16KernelCreateInfoEvEN5$_1538__invokeERKNS_12OpKernelInfoE__ZN11onnxruntime11LessOrEqualIxED1Ev__ZN11onnxruntime11LessOrEqualIxED0Ev__ZNK11onnxruntime11LessOrEqualIxE7ComputeEPNS_15OpKernelContextE__ZZNK11onnxruntime11LessOrEqualIxE7ComputeEPNS_15OpKernelContextEENUlRNS_15BroadcastHelperEE_8__invokeES5___ZZNK11onnxruntime11LessOrEqualIxE7ComputeEPNS_15OpKernelContextEENUlRNS_15BroadcastHelperEE0_8__invokeES5___ZZNK11onnxruntime11LessOrEqualIxE7ComputeEPNS_15OpKernelContextEENUlRNS_15BroadcastHelperEE1_8__invokeES5___ZZN11onnxruntime21BuildKernelCreateInfoINS_60kCpuExecutionProvider_GreaterOrEqual_kOnnxDomain_ver12_floatEEENS_16KernelCreateInfoEvEN5$_1548__invokeERKNS_12OpKernelInfoE__ZN11onnxruntime14GreaterOrEqualIfED1Ev__ZN11onnxruntime14GreaterOrEqualIfED0Ev__ZNK11onnxruntime14GreaterOrEqualIfE7ComputeEPNS_15OpKernelContextE__ZZNK11onnxruntime14GreaterOrEqualIfE7ComputeEPNS_15OpKernelContextEENUlRNS_15BroadcastHelperEE_8__invokeES5___ZZNK11onnxruntime14GreaterOrEqualIfE7ComputeEPNS_15OpKernelContextEENUlRNS_15BroadcastHelperEE0_8__invokeES5___ZZNK11onnxruntime14GreaterOrEqualIfE7ComputeEPNS_15OpKernelContextEENUlRNS_15BroadcastHelperEE1_8__invokeES5___ZZN11onnxruntime21BuildKernelCreateInfoINS_61kCpuExecutionProvider_GreaterOrEqual_kOnnxDomain_ver12_doubleEEENS_16KernelCreateInfoEvEN5$_1558__invokeERKNS_12OpKernelInfoE__ZN11onnxruntime14GreaterOrEqualIdED1Ev__ZN11onnxruntime14GreaterOrEqualIdED0Ev__ZNK11onnxruntime14GreaterOrEqualIdE7ComputeEPNS_15OpKernelContextE__ZZNK11onnxruntime14GreaterOrEqualIdE7ComputeEPNS_15OpKernelContextEENUlRNS_15BroadcastHelperEE_8__invokeES5___ZZNK11onnxruntime14GreaterOrEqualIdE7ComputeEPNS_15OpKernelContextEENUlRNS_15BroadcastHelperEE0_8__invokeES5___ZZNK11onnxruntime14GreaterOrEqualIdE7ComputeEPNS_15OpKernelContextEENUlRNS_15BroadcastHelperEE1_8__invokeES5___ZZN11onnxruntime21BuildKernelCreateInfoINS_62kCpuExecutionProvider_GreaterOrEqual_kOnnxDomain_ver12_int32_tEEENS_16KernelCreateInfoEvEN5$_1568__invokeERKNS_12OpKernelInfoE__ZN11onnxruntime14GreaterOrEqualIiED1Ev__ZN11onnxruntime14GreaterOrEqualIiED0Ev__ZNK11onnxruntime14GreaterOrEqualIiE7ComputeEPNS_15OpKernelContextE__ZZNK11onnxruntime14GreaterOrEqualIiE7ComputeEPNS_15OpKernelContextEENUlRNS_15BroadcastHelperEE_8__invokeES5___ZZNK11onnxruntime14GreaterOrEqualIiE7ComputeEPNS_15OpKernelContextEENUlRNS_15BroadcastHelperEE0_8__invokeES5___ZZNK11onnxruntime14GreaterOrEqualIiE7ComputeEPNS_15OpKernelContextEENUlRNS_15BroadcastHelperEE1_8__invokeES5___ZZN11onnxruntime21BuildKernelCreateInfoINS_62kCpuExecutionProvider_GreaterOrEqual_kOnnxDomain_ver12_int64_tEEENS_16KernelCreateInfoEvEN5$_1578__invokeERKNS_12OpKernelInfoE__ZN11onnxruntime14GreaterOrEqualIxED1Ev__ZN11onnxruntime14GreaterOrEqualIxED0Ev__ZNK11onnxruntime14GreaterOrEqualIxE7ComputeEPNS_15OpKernelContextE__ZZNK11onnxruntime14GreaterOrEqualIxE7ComputeEPNS_15OpKernelContextEENUlRNS_15BroadcastHelperEE_8__invokeES5___ZZNK11onnxruntime14GreaterOrEqualIxE7ComputeEPNS_15OpKernelContextEENUlRNS_15BroadcastHelperEE0_8__invokeES5___ZZNK11onnxruntime14GreaterOrEqualIxE7ComputeEPNS_15OpKernelContextEENUlRNS_15BroadcastHelperEE1_8__invokeES5___ZZN11onnxruntime21BuildKernelCreateInfoINS_51kCpuExecutionProvider_Mean_kOnnxDomain_ver6_7_floatEEENS_16KernelCreateInfoEvEN5$_1588__invokeERKNS_12OpKernelInfoE__ZN11onnxruntime6Mean_6IfED1Ev__ZN11onnxruntime6Mean_6IfED0Ev__ZZN11onnxruntime21BuildKernelCreateInfoINS_52kCpuExecutionProvider_Mean_kOnnxDomain_ver8_12_floatEEENS_16KernelCreateInfoEvEN5$_1598__invokeERKNS_12OpKernelInfoE__ZN11onnxruntime6Mean_8IfED1Ev__ZN11onnxruntime6Mean_8IfED0Ev__ZZN11onnxruntime21BuildKernelCreateInfoINS_50kCpuExecutionProvider_Mean_kOnnxDomain_ver13_floatEEENS_16KernelCreateInfoEvEN5$_1608__invokeERKNS_12OpKernelInfoE__ZZN11onnxruntime21BuildKernelCreateInfoINS_56kCpuExecutionProvider_BitShift_kOnnxDomain_ver11_uint8_tEEENS_16KernelCreateInfoEvEN5$_1618__invokeERKNS_12OpKernelInfoE__ZN11onnxruntime8BitShiftIhEC2ERKNS_12OpKernelInfoE__ZN11onnxruntime8BitShiftIhED1Ev__ZN11onn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Filter2.LNchw.2.1.ProcessNextRow.LNchw.2.1.ProcessNextColumn.LNchw.2.1.SkipOverPadding.LNchw.2.1.HandlePostProcessingMlasConvNchwFloatSingleFma3Filter3.LNchw.3.1.ProcessNextRow.LNchw.3.1.ProcessNextColumn.LNchw.3.1.SkipOverPadding.LNchw.3.1.HandlePostProcessingMlasConvNchwFloatSingleFma3Filter4.LNchw.4.1.ProcessNextRow.LNchw.4.1.ProcessNextColumn.LNchw.4.1.SkipOverPadding.LNchw.4.1.HandlePostProcessing.LNchwc.4.ProcessOutputCount.LNchwc.4.ProcessNextOutputCountBy3.LNchwc.4.3.ProcessNextRow.LNchwc.4.3.ProcessNextColumn.LNchwc.4.3.SkipOverPadding.LNchwc.4.3.HandlePostProcessing.LNchwc.4.ProcessRemainingOutputCount.LNchwc.4.2.ProcessNextRow.LNchwc.4.2.ProcessNextColumn.LNchwc.4.2.SkipOverPadding.LNchwc.4.2.HandlePostProcessing.LNchwc.4.ProcessOutputCountRightPadAndRemaining.LNchwc.ProcessFilterCount3.LNchwc.3.ProcessOutputCount.LNchwc.3.ProcessNextOutputCountBy3.LNchwc.3.3.ProcessNextRow.LNchwc.3.3.ProcessNextColumn.LNchwc.3.3.SkipOverPadding.LNchwc.3.3.HandlePostProcessing.LNchwc.3.ProcessRemainingOutputCount.LNchwc.3.2.ProcessNextRow.LNchwc.3.2.ProcessNextColumn.LNchwc.3.2.SkipOverPadding.LNchwc.3.2.HandlePostProcessing.LNchwc.3.ProcessOutputCountRightPadAndRemaining.LNchwc.ProcessFilterCountLessThan3.LNchwc.2.ProcessOutputCount.LNchwc.2.ProcessNextOutputCountBy3.LNchwc.2.3.ProcessNextRow.LNchwc.2.3.ProcessNextColumn.LNchwc.2.3.SkipOverPadding.LNchwc.2.3.HandlePostProcessing.LNchwc.2.ProcessRemainingOutputCount.LNchwc.2.2.ProcessNextRow.LNchwc.2.2.ProcessNextColumn.LNchwc.2.2.SkipOverPadding.LNchwc.2.2.HandlePostProcessing.LNchwc.2.ProcessOutputCountRightPadAndRemaining.LNchwc.ProcessFilterCount1.LNchwc.1.ProcessOutputCount.LNchwc.1.ProcessNextOutputCountBy3.LNchwc.1.3.ProcessNextRow.LNchwc.1.3.ProcessNextColumn.LNchwc.1.3.SkipOverPadding.LNchwc.1.3.HandlePostProcessing.LNchwc.1.ProcessRemainingOutputCount.LNchwc.1.2.ProcessNextRow.LNchwc.1.2.ProcessNextColumn.LNchwc.1.2.SkipOverPadding.LNchwc.1.2.HandlePostProcessing.LNchwc.1.ProcessOutputCountRightPadAndRemaining.LNchwc.ExitKernelMlasConvNchwcFloatSingleFma3Filter1.LNchwc.1.1.ProcessNextRow.LNchwc.1.1.ProcessNextColumn.LNchwc.1.1.SkipOverPadding.LNchwc.1.1.HandlePostProcessingMlasConvNchwcFloatSingleFma3Filter2.LNchwc.2.1.ProcessNextRow.LNchwc.2.1.ProcessNextColumn.LNchwc.2.1.SkipOverPadding.LNchwc.2.1.HandlePostProcessingMlasConvNchwcFloatSingleFma3Filter3.LNchwc.3.1.ProcessNextRow.LNchwc.3.1.ProcessNextColumn.LNchwc.3.1.SkipOverPadding.LNchwc.3.1.HandlePostProcessingMlasConvNchwcFloatSingleFma3Filter4.LNchwc.4.1.ProcessNextRow.LNchwc.4.1.ProcessNextColumn.LNchwc.4.1.SkipOverPadding.LNchwc.4.1.HandlePostProcessing.LDepthwise.1.ProcessOutputCount.LDepthwise.1.ProcessNextOutputCountBy3.LDepthwise.1.3.ProcessNextRow.LDepthwise.1.3.ProcessNextColumn.LDepthwise.1.3.SkipOverPadding.LDepthwise.1.3.HandlePostProcessing.LDepthwise.1.ProcessRemainingOutputCount.LDepthwise.1.2.ProcessNextRow.LDepthwise.1.2.ProcessNextColumn.LDepthwise.1.2.SkipOverPadding.LDepthwise.1.2.HandlePostProcessing.LDepthwise.1.ProcessOutputCountRightPadAndRemaining.LDepthwise.ExitKernelMlasConvDepthwiseFloatSingleFma3Filter1.LDepthwise.1.1.ProcessNextRow.LDepthwise.1.1.ProcessNextColumn.LDepthwise.1.1.SkipOverPadding.LDepthwise.1.1.HandlePostProcessing.LPointwise.4.ProcessNextOutputCountBy3.LPointwise.4.3.ProcessNextInputBlock.LPointwise.4.ProcessRemainingOutputCount.LPointwise.4.2.ProcessNextInputBlock.LPointwise.4.ProcessRemainingOutputCount1.LPointwise.4.1.ProcessNextInputBlock.LPointwise.ProcessFilterCount3.LPointwise.3.ProcessNextOutputCountBy3.LPointwise.3.3.ProcessNextInputBlock.LPointwise.3.ProcessRemainingOutputCount.LPointwise.3.2.ProcessNextInputBlock.LPointwise.3.ProcessRemainingOutputCount1.LPointwise.3.1.ProcessNextInputBlock.LPointwise.ProcessFilterCountLessThan3.LPointwise.2.ProcessNextOutputCountBy3.LPointwise.2.3.ProcessNextInputBlock.LPointwise.2.ProcessRemainingOutputCount.LPointwise.2.2.ProcessNextInputBlock.LPointwise.2.ProcessRemainingOutputCount1.LPointwise.2.1.ProcessNextInputBlock.LPointwise.ProcessFilterCount1.LPointwise.1.ProcessNextOutputCountBy3.LPointwise.1.3.ProcessNextInputBlock.LPointwise.1.ProcessRemainingOutputCount.LPointwise.1.2.ProcessNextInputBlock.LPointwise.1.ProcessRemainingOutputCount1.LPointwise.1.1.ProcessNextInputBlock.LPointwise.ExitKernel.LComputeExp.ComputeExpBy8Loop.LComputeExp.ProcessRemainingCount.LComputeExp.ExitKernel.LComputeSumExp.ComputeExpBy24Loop.LComputeSumExp.SkipStoreResultsBy24.LComputeSumExp.ProcessRemainingCount.LComputeSumExp.ComputeExpBy8Loop.LComputeSumExp.LoadPartialVector.LComputeSumExp.ProcessSingleVector.LComputeSumExp.SkipStoreResultsBy8.LComputeSumExp.StorePartialVector.LComputeSumExp.ReduceAccumulator.LComputeLogisticBy8Loop.LProcessRemainingCount.LExitKernel.LComputeTanhBy8Loop.LProcessRemainingCount.LExitKernel.LComputeErf4x8Loop.BiggerNumbers.LErfProcessRemainingCount.LErfProcess1x8.BiggerNumbersRemaining.LErfBatchExp_MlasQLinearAddS8KernelAvx2_MlasQLinearAddU8KernelAvx2__Z27MlasConvDepthwiseKernelAvx2IaEvPKPKhhP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ocessRemainingCountN2101.LComputeBlockBy4Loop2223.LProcessRemainingBlocks2223.LComputeBlockBy1Loop2223.LOutputBlock2223.LProcessCountM3.LProcessNextColumnLoop2xN2301.LComputeBlockBy4Loop2315.LProcessRemainingBlocks2315.LComputeBlockBy1Loop2315.LOutputBlock2315.LMultiplyAlpha2xNBlock2301.LStore2xNBlock2301.LOutput1xNBlock2301.LOutput1xNBlockWithMask2301.LMultiplyAlpha1xNBlockWithMask2301.LStore1xNBlockWithMask2301.LProcessRemainingCountN2301.LComputeBlockBy4Loop2655.LProcessRemainingBlocks2655.LComputeBlockBy1Loop2655.LOutputBlock2655.LProcessCountM5.LProcessNextColumnLoop2xN2743.LComputeBlockBy4Loop2757.LProcessRemainingBlocks2757.LComputeBlockBy1Loop2757.LOutputBlock2757.LMultiplyAlpha2xNBlock2743.LStore2xNBlock2743.LOutput1xNBlock2743.LOutput1xNBlockWithMask2743.LMultiplyAlpha1xNBlockWithMask2743.LStore1xNBlockWithMask2743.LProcessRemainingCountN2743.LComputeBlockBy4Loop3139.LProcessRemainingBlocks3139.LComputeBlockBy1Loop3139.LOutputBlock3139.LNchw.4.ProcessOutputCount.LNchw.4.ProcessNextOutputCountBy6.LNchw.4.6.ProcessNextRow.LNchw.4.6.ProcessNextColumn.LNchw.4.6.SkipOverPadding.LNchw.4.6.HandlePostProcessing.LNchw.4.ProcessRemainingOutputCount.LNchw.4.3.ProcessNextRow.LNchw.4.3.ProcessNextColumn.LNchw.4.3.SkipOverPadding.LNchw.4.3.HandlePostProcessing.LNchw.4.ProcessRemainingOutputCountLessThan3.LNchw.4.2.ProcessNextRow.LNchw.4.2.ProcessNextColumn.LNchw.4.2.SkipOverPadding.LNchw.4.2.HandlePostProcessing.LNchw.4.ProcessOutputCountRightPadAndRemaining.LNchw.ProcessFilterCount3.LNchw.3.ProcessOutputCount.LNchw.3.ProcessNextOutputCountBy6.LNchw.3.6.ProcessNextRow.LNchw.3.6.ProcessNextColumn.LNchw.3.6.SkipOverPadding.LNchw.3.6.HandlePostProcessing.LNchw.3.ProcessRemainingOutputCount.LNchw.3.3.ProcessNextRow.LNchw.3.3.ProcessNextColumn.LNchw.3.3.SkipOverPadding.LNchw.3.3.HandlePostProcessing.LNchw.3.ProcessRemainingOutputCountLessThan3.LNchw.3.2.ProcessNextRow.LNchw.3.2.ProcessNextColumn.LNchw.3.2.SkipOverPadding.LNchw.3.2.HandlePostProcessing.LNchw.3.ProcessOutputCountRightPadAndRemaining.LNchw.ProcessFilterCountLessThan3.LNchw.2.ProcessOutputCount.LNchw.2.ProcessNextOutputCountBy6.LNchw.2.6.ProcessNextRow.LNchw.2.6.ProcessNextColumn.LNchw.2.6.SkipOverPadding.LNchw.2.6.HandlePostProcessing.LNchw.2.ProcessRemainingOutputCount.LNchw.2.3.ProcessNextRow.LNchw.2.3.ProcessNextColumn.LNchw.2.3.SkipOverPadding.LNchw.2.3.HandlePostProcessing.LNchw.2.ProcessRemainingOutputCountLessThan3.LNchw.2.2.ProcessNextRow.LNchw.2.2.ProcessNextColumn.LNchw.2.2.SkipOverPadding.LNchw.2.2.HandlePostProcessing.LNchw.2.ProcessOutputCountRightPadAndRemaining.LNchw.ProcessFilterCount1.LNchw.1.ProcessOutputCount.LNchw.1.ProcessNextOutputCountBy6.LNchw.1.6.ProcessNextRow.LNchw.1.6.ProcessNextColumn.LNchw.1.6.SkipOverPadding.LNchw.1.6.HandlePostProcessing.LNchw.1.ProcessRemainingOutputCount.LNchw.1.3.ProcessNextRow.LNchw.1.3.ProcessNextColumn.LNchw.1.3.SkipOverPadding.LNchw.1.3.HandlePostProcessing.LNchw.1.ProcessRemainingOutputCountLessThan3.LNchw.1.2.ProcessNextRow.LNchw.1.2.ProcessNextColumn.LNchw.1.2.SkipOverPadding.LNchw.1.2.HandlePostProcessing.LNchw.1.ProcessOutputCountRightPadAndRemaining.LNchw.ExitKernelMlasConvNchwFloatSingleAvx512FFilter1.LNchw.1.1.ProcessNextRow.LNchw.1.1.ProcessNextColumn.LNchw.1.1.SkipOverPadding.LNchw.1.1.HandlePostProcessingMlasConvNchwFloatSingleAvx512FFilter2.LNchw.2.1.ProcessNextRow.LNchw.2.1.ProcessNextColumn.LNchw.2.1.SkipOverPadding.LNchw.2.1.HandlePostProcessingMlasConvNchwFloatSingleAvx512FFilter3.LNchw.3.1.ProcessNextRow.LNchw.3.1.ProcessNextColumn.LNchw.3.1.SkipOverPadding.LNchw.3.1.HandlePostProcessingMlasConvNchwFloatSingleAvx512FFilter4.LNchw.4.1.ProcessNextRow.LNchw.4.1.ProcessNextColumn.LNchw.4.1.SkipOverPadding.LNchw.4.1.HandlePostProcessing.LNchwc.4.ProcessOutputCount.LNchwc.4.ProcessNextOutputCountBy6.LNchwc.4.6.ProcessNextRow.LNchwc.4.6.ProcessNextColumn.LNchwc.4.6.SkipOverPadding.LNchwc.4.6.HandlePostProcessing.LNchwc.4.ProcessRemainingOutputCount.LNchwc.4.3.ProcessNextRow.LNchwc.4.3.ProcessNextColumn.LNchwc.4.3.SkipOverPadding.LNchwc.4.3.HandlePostProcessing.LNchwc.4.ProcessRemainingOutputCountLessThan3.LNchwc.4.2.ProcessNextRow.LNchwc.4.2.ProcessNextColumn.LNchwc.4.2.SkipOverPadding.LNchwc.4.2.HandlePostProcessing.LNchwc.4.ProcessOutputCountRightPadAndRemaining.LNchwc.ProcessFilterCount3.LNchwc.3.ProcessOutputCount.LNchwc.3.ProcessNextOutputCountBy6.LNchwc.3.6.ProcessNextRow.LNchwc.3.6.ProcessNextColumn.LNchwc.3.6.SkipOverPadding.LNchwc.3.6.HandlePostProcessing.LNchwc.3.ProcessRemainingOutputCount.LNchwc.3.3.ProcessNextRow.LNchwc.3.3.ProcessNextColumn.LNchwc.3.3.SkipOverPadding.LNchwc.3.3.HandlePostProcessing.LNchwc.3.ProcessRemainingOutputCountLessThan3.LNchwc.3.2.ProcessNextRow.LNchwc.3.2.ProcessNextColumn.LNchwc.3.2.SkipOverPadding.LNchwc.3.2.HandlePostProcessing.LNchwc.3.ProcessOutputCountRightPadAndRemaining.LNchwc.ProcessFilterCountLessThan3.LNchwc.2.ProcessOutputCount.LNchwc.2.ProcessNextOutputCountBy6.LNchwc.2.6.ProcessNextRow.LNchwc.2.6.ProcessNextColumn.LNchwc.2.6.SkipOverPa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ntime21BuildKernelCreateInfoINS_54kCpuExecutionProvider_Less_kOnnxDomain_ver9_12_int64_tEEENS_16KernelCreateInfoEvEN5$_1208__invokeERKNS_12OpKernelInfoE__ZN11onnxruntime4LessIxED1Ev__ZN11onnxruntime4LessIxED0Ev__ZNK11onnxruntime4LessIxE7ComputeEPNS_15OpKernelContextE__ZZNK11onnxruntime4LessIxE7ComputeEPNS_15OpKernelContextEENUlRNS_15BroadcastHelperEE_8__invokeES5___ZZNK11onnxruntime4LessIxE7ComputeEPNS_15OpKernelContextEENUlRNS_15BroadcastHelperEE0_8__invokeES5___ZZNK11onnxruntime4LessIxE7ComputeEPNS_15OpKernelContextEENUlRNS_15BroadcastHelperEE1_8__invokeES5___ZZN11onnxruntime21BuildKernelCreateInfoINS_50kCpuExecutionProvider_Less_kOnnxDomain_ver13_floatEEENS_16KernelCreateInfoEvEN5$_1218__invokeERKNS_12OpKernelInfoE__ZZN11onnxruntime21BuildKernelCreateInfoINS_51kCpuExecutionProvider_Less_kOnnxDomain_ver13_doubleEEENS_16KernelCreateInfoEvEN5$_1228__invokeERKNS_12OpKernelInfoE__ZZN11onnxruntime21BuildKernelCreateInfoINS_52kCpuExecutionProvider_Less_kOnnxDomain_ver13_int32_tEEENS_16KernelCreateInfoEvEN5$_1238__invokeERKNS_12OpKernelInfoE__ZZN11onnxruntime21BuildKernelCreateInfoINS_52kCpuExecutionProvider_Less_kOnnxDomain_ver13_int64_tEEENS_16KernelCreateInfoEvEN5$_1248__invokeERKNS_12OpKernelInfoE__ZZN11onnxruntime21BuildKernelCreateInfoINS_54kCpuExecutionProvider_Greater_kOnnxDomain_ver7_8_floatEEENS_16KernelCreateInfoEvEN5$_1258__invokeERKNS_12OpKernelInfoE__ZN11onnxruntime7GreaterIfED1Ev__ZN11onnxruntime7GreaterIfED0Ev__ZNK11onnxruntime7GreaterIfE7ComputeEPNS_15OpKernelContextE__ZZNK11onnxruntime7GreaterIfE7ComputeEPNS_15OpKernelContextEENUlRNS_15BroadcastHelperEE_8__invokeES5___ZZNK11onnxruntime7GreaterIfE7ComputeEPNS_15OpKernelContextEENUlRNS_15BroadcastHelperEE0_8__invokeES5___ZZNK11onnxruntime7GreaterIfE7ComputeEPNS_15OpKernelContextEENUlRNS_15BroadcastHelperEE1_8__invokeES5___ZZN11onnxruntime21BuildKernelCreateInfoINS_55kCpuExecutionProvider_Greater_kOnnxDomain_ver7_8_doubleEEENS_16KernelCreateInfoEvEN5$_1268__invokeERKNS_12OpKernelInfoE__ZN11onnxruntime7GreaterIdED1Ev__ZN11onnxruntime7GreaterIdED0Ev__ZNK11onnxruntime7GreaterIdE7ComputeEPNS_15OpKernelContextE__ZZNK11onnxruntime7GreaterIdE7ComputeEPNS_15OpKernelContextEENUlRNS_15BroadcastHelperEE_8__invokeES5___ZZNK11onnxruntime7GreaterIdE7ComputeEPNS_15OpKernelContextEENUlRNS_15BroadcastHelperEE0_8__invokeES5___ZZNK11onnxruntime7GreaterIdE7ComputeEPNS_15OpKernelContextEENUlRNS_15BroadcastHelperEE1_8__invokeES5___ZZN11onnxruntime21BuildKernelCreateInfoINS_55kCpuExecutionProvider_Greater_kOnnxDomain_ver9_12_floatEEENS_16KernelCreateInfoEvEN5$_1278__invokeERKNS_12OpKernelInfoE__ZZN11onnxruntime21BuildKernelCreateInfoINS_56kCpuExecutionProvider_Greater_kOnnxDomain_ver9_12_doubleEEENS_16KernelCreateInfoEvEN5$_1288__invokeERKNS_12OpKernelInfoE__ZZN11onnxruntime21BuildKernelCreateInfoINS_57kCpuExecutionProvider_Greater_kOnnxDomain_ver9_12_int32_tEEENS_16KernelCreateInfoEvEN5$_1298__invokeERKNS_12OpKernelInfoE__ZN11onnxruntime7GreaterIiED1Ev__ZN11onnxruntime7GreaterIiED0Ev__ZNK11onnxruntime7GreaterIiE7ComputeEPNS_15OpKernelContextE__ZZNK11onnxruntime7GreaterIiE7ComputeEPNS_15OpKernelContextEENUlRNS_15BroadcastHelperEE_8__invokeES5___ZZNK11onnxruntime7GreaterIiE7ComputeEPNS_15OpKernelContextEENUlRNS_15BroadcastHelperEE0_8__invokeES5___ZZNK11onnxruntime7GreaterIiE7ComputeEPNS_15OpKernelContextEENUlRNS_15BroadcastHelperEE1_8__invokeES5___ZZN11onnxruntime21BuildKernelCreateInfoINS_57kCpuExecutionProvider_Greater_kOnnxDomain_ver9_12_int64_tEEENS_16KernelCreateInfoEvEN5$_1308__invokeERKNS_12OpKernelInfoE__ZN11onnxruntime7GreaterIxED1Ev__ZN11onnxruntime7GreaterIxED0Ev__ZNK11onnxruntime7GreaterIxE7ComputeEPNS_15OpKernelContextE__ZZNK11onnxruntime7GreaterIxE7ComputeEPNS_15OpKernelContextEENUlRNS_15BroadcastHelperEE_8__invokeES5___ZZNK11onnxruntime7GreaterIxE7ComputeEPNS_15OpKernelContextEENUlRNS_15BroadcastHelperEE0_8__invokeES5___ZZNK11onnxruntime7GreaterIxE7ComputeEPNS_15OpKernelContextEENUlRNS_15BroadcastHelperEE1_8__invokeES5___ZZN11onnxruntime21BuildKernelCreateInfoINS_53kCpuExecutionProvider_Greater_kOnnxDomain_ver13_floatEEENS_16KernelCreateInfoEvEN5$_1318__invokeERKNS_12OpKernelInfoE__ZZN11onnxruntime21BuildKernelCreateInfoINS_54kCpuExecutionProvider_Greater_kOnnxDomain_ver13_doubleEEENS_16KernelCreateInfoEvEN5$_1328__invokeERKNS_12OpKernelInfoE__ZZN11onnxruntime21BuildKernelCreateInfoINS_55kCpuExecutionProvider_Greater_kOnnxDomain_ver13_int32_tEEENS_16KernelCreateInfoEvEN5$_1338__invokeERKNS_12OpKernelInfoE__ZZN11onnxruntime21BuildKernelCreateInfoINS_55kCpuExecutionProvider_Greater_kOnnxDomain_ver13_int64_tEEENS_16KernelCreateInfoEvEN5$_1348__invokeERKNS_12OpKernelInfoE__ZZN11onnxruntime21BuildKernelCreateInfoINS_52kCpuExecutionProvider_Equal_kOnnxDomain_ver7_10_boolEEENS_16KernelCreateInfoEvEN5$_1358__invokeERKNS_12OpKernelInfoE__ZN11onnxruntime5EqualIbED1Ev__ZN11onnxruntime5EqualIbED0Ev__ZNK11onnxruntime5EqualIbE7ComputeEPNS_15OpKernelContextE__ZZNK11onnxruntime5EqualIbE7ComputeEPNS_15OpKernelContextEENUlRNS_15BroadcastHelperEE_8__invokeES5___ZZNK11onnxruntime5EqualIbE7ComputeEPNS_15OpKernelContextEENUlRNS_15BroadcastHelperEE0_8__invokeES5___ZZNK11onnxruntime5EqualIbE7ComputeEPNS_15OpKernelContextEENUlRNS_15BroadcastHelperEE1_8__invokeES5___ZZN11onnxruntime21BuildKernelCreateInfoINS_55kCpuExecutionProvider_Equal_kOnnxDomain_ver7_10_int32_tEEENS_16KernelCreateInfoEvEN5$_1368__invokeERKNS_12OpKernelInfoE__ZN11onnxruntime5EqualIiED1Ev__ZN11onnxruntime5EqualIiED0Ev__ZNK11onnxruntime5EqualIiE7ComputeEPNS_15OpKernelContextE__ZZNK11onnxruntime5EqualIiE7ComputeEPNS_15OpKernelContextEENUlRNS_15BroadcastHelperEE_8__invokeES5___ZZNK11onnxruntime5EqualIiE7ComputeEPNS_15OpKernelContextEENUlRNS_15BroadcastHelperEE0_8__invokeES5___ZZNK11onnxruntime5EqualIiE7ComputeEPNS_15OpKernelContextEENUlRNS_15BroadcastHelperEE1_8__invokeES5___ZZN11onnxruntime21BuildKernelCreateInfoINS_55kCpuExecutionProvider_Equal_kOnnxDomain_ver7_10_int64_tEEENS_16KernelCreateInfoEvEN5$_1378__invokeERKNS_12OpKernelInfoE__ZN11onnxruntime5EqualIxED1Ev__ZN11onnxruntime5EqualIxED0Ev__ZNK11onnxruntime5EqualIxE7ComputeEPNS_15OpKernelContextE__ZZNK11onnxruntime5EqualIxE7ComputeEPNS_15OpKernelContextEENUlRNS_15BroadcastHelperEE_8__invokeES5___ZZNK11onnxruntime5EqualIxE7ComputeEPNS_15OpKernelContextEENUlRNS_15BroadcastHelperEE0_8__invokeES5___ZZNK11onnxruntime5EqualIxE7ComputeEPNS_15OpKernelContextEENUlRNS_15BroadcastHelperEE1_8__invokeES5___ZZN11onnxruntime21BuildKernelCreateInfoINS_53kCpuExecutionProvider_Equal_kOnnxDomain_ver7_10_floatEEENS_16KernelCreateInfoEvEN5$_1388__invokeERKNS_12OpKernelInfoE__ZN11onnxruntime5EqualIfED1Ev__ZN11onnxruntime5EqualIfED0Ev__ZNK11onnxruntime5EqualIfE7ComputeEPNS_15OpKernelContextE__ZZNK11onnxruntime5EqualIfE7ComputeEPNS_15OpKernelContextEENUlRNS_15BroadcastHelperEE_8__invokeES5___ZZNK11onnxruntime5EqualIfE7ComputeEPNS_15OpKernelContextEENUlRNS_15BroadcastHelperEE0_8__invokeES5___ZZNK11onnxruntime5EqualIfE7ComputeEPNS_15OpKernelContextEENUlRNS_15BroadcastHelperEE1_8__invokeES5___ZZN11onnxruntime21BuildKernelCreateInfoINS_54kCpuExecutionProvider_Equal_kOnnxDomain_ver7_10_doubleEEENS_16KernelCreateInfoEvEN5$_1398__invokeERKNS_12OpKernelInfoE__ZN11onnxruntime5EqualIdED1Ev__ZN11onnxruntime5EqualIdED0Ev__ZNK11onnxruntime5EqualIdE7ComputeEPNS_15OpKernelContextE__ZZNK11onnxruntime5EqualIdE7ComputeEPNS_15OpKernelContextEENUlRNS_15BroadcastHelperEE_8__invokeES5___ZZNK11onnxruntime5EqualIdE7ComputeEPNS_15OpKernelContextEENUlRNS_15BroadcastHelperEE0_8__invokeES5___ZZNK11onnxruntime5EqualIdE7ComputeEPNS_15OpKernelContextEENUlRNS_15BroadcastHelperEE1_8__invokeES5___ZZN11onnxruntime21BuildKernelCreateInfoINS_53kCpuExecutionProvider_Equal_kOnnxDomain_ver11_12_boolEEENS_16KernelCreateInfoEvEN5$_1408__invokeERKNS_12OpKernelInfoE__ZZN11onnxruntime21BuildKernelCreateInfoINS_56kCpuExecutionProvider_Equal_kOnnxDomain_ver11_12_int32_tEEENS_16KernelCreateInfoEvEN5$_1418__invokeERKNS_12OpKernelInfoE__ZZN11onnxruntime21BuildKernelCreateInfoINS_56kCpuExecutionProvider_Equal_kOnnxDomain_ver11_12_int64_tEEENS_16KernelCreateInfoEvEN5$_1428__invokeERKNS_12OpKernelInfoE__ZZN11onnxruntime21BuildKernelCreateInfoINS_54kCpuExecutionProvider_Equal_kOnnxDomain_ver11_12_floatEEENS_16KernelCreateInfoEvEN5$_1438__invokeERKNS_12OpKernelInfoE__ZZN11onnxruntime21BuildKernelCreateInfoINS_55kCpuExecutionProvider_Equal_kOnnxDomain_ver11_12_doubleEEENS_16KernelCreateInfoEvEN5$_1448__invokeERKNS_12OpKernelInfoE__ZZN11onnxruntime21BuildKernelCreateInfoINS_50kCpuExecutionProvider_Equal_kOnnxDomain_ver13_boolEEENS_16KernelCreateInfoEvEN5$_1458__invokeERKNS_12OpKernelInfoE__ZZN11onnxruntime21BuildKernelCreateInfoINS_53kCpuExecutionProvider_Equal_kOnnxDomain_ver13_int32_tEEENS_16KernelCreateInfoEvEN5$_1468__invokeERKNS_12OpKernelInfoE__ZZN11onnxruntime21BuildKernelCreateInfoINS_53kCpuExecutionProvider_Equal_kOnnxDomain_ver13_int64_tEEENS_16KernelCreateInfoEvEN5$_1478__invokeERKNS_12OpKernelInfoE__ZZN11onnxruntime21BuildKernelCreateInfoINS_51kCpuExecutionProvider_Equal_kOnnxDomain_ver13_floatEEENS_16KernelCreateInfoEvEN5$_1488__invokeERKNS_12OpKernelInfoE__ZZN11onnxruntime21BuildKernelCreateInfoINS_52kCpuExecutionProvider_Equal_kOnnxDomain_ver13_doubleEEENS_16KernelCreateInfoEvEN5$_1498__invokeERKNS_12OpKernelInfoE__ZZN11onnxruntime21BuildKernelCreateInfoINS_57kCpuExecutionProvider_LessOrEqual_kOnnxDomain_ver12_floatEEENS_16KernelCreateInfoEvEN5$_1508__invokeERKNS_12OpKernelInfoE__ZN11onnxruntime11LessOrEqualIfED1Ev__ZN11onnxruntime11LessOrEqualIfED0Ev__ZNK11onnxruntime11LessOrEqualIfE7ComputeEPNS_15OpKernelContextE__ZZNK11onnxruntime11LessOrEqualIfE7ComputeEPNS_15OpKernelContextEENUlRNS_15BroadcastHelperEE_8__invokeES5___ZZNK11onnxruntime11LessOrEqualIfE7ComputeEPNS_15OpKernelContextEENUlRNS_15BroadcastHelperEE0_8__invokeES5___ZZNK11onnxruntime11LessOrEqualIfE7ComputeEPNS_15OpKernelContextEENUlRNS_15BroadcastHelperEE1_8__invokeES5___ZZN11onnxruntime21BuildKernelCreateInfoINS_58kCpuExecutionProvider_LessOrEqual_kOnnxDomain_ver12_doubleEEENS_16KernelCreateInfoEvEN5$_1518__invokeERKNS_12OpKernelInfoE__ZN11onnxruntime11LessOrEqualIdED1Ev__ZN11onnxruntime11LessOrEqualIdED0Ev__ZNK11onnxruntime11LessOrEqualIdE7ComputeEPNS_15OpKernelContextE__ZZNK11onnxruntime11LessOrEqualIdE7ComputeEPNS_15OpKernelContextEENUlRNS_15BroadcastHelperEE_8__invokeES5___ZZNK11onnxruntime11LessOrEqualIdE7ComputeEPNS_15OpKernelContextEENUlRNS_15BroadcastHelperEE0_8__invokeES5___ZZNK11onnxruntime11LessOrEqualIdE7ComputeEPNS_15OpKernelContextEENUlRNS_15BroadcastHelperEE1_8__invokeES5___ZZN11onnxruntime21BuildKernelCreateInfoINS_59kCpuExecutionProvider_LessOrEqual_kOnnxDomain_ver12_int32_tEEENS_16KernelCreateInfoEvEN5$_1528__invokeERKNS_12OpKernelInfoE__ZN11onnxruntime11LessOrEqualIiED1Ev__ZN11onnxruntime11LessOrEqualIiED0Ev__ZNK11onnxruntime11LessOrEqualIiE7ComputeEPNS_15OpKernelContextE__ZZNK11onnxruntime11LessOrEqualIiE7ComputeEPNS_15OpKernelContextEENUlRNS_15BroadcastHelperEE_8__invokeES5___ZZNK11onnxruntime11LessOrEqualIiE7ComputeEPNS_15OpKernelContextEENUlRNS_15BroadcastHelperEE0_8__invokeES5___ZZNK11onnxruntime11LessOrEqualIiE7ComputeEPNS_15OpKernelContextEENUlRNS_15BroadcastHelperEE1_8__invokeES5___ZZN11onnxruntime21BuildKernelCreateInfoINS_59kCpuExecutionProvider_LessOrEqual_kOnnxDomain_ver12_int64_tEEENS_16KernelCreateInfoEvEN5$_1538__invokeERKNS_12OpKernelInfoE__ZN11onnxruntime11LessOrEqualIxED1Ev__ZN11onnxruntime11LessOrEqualIxED0Ev__ZNK11onnxruntime11LessOrEqualIxE7ComputeEPNS_15OpKernelContextE__ZZNK11onnxruntime11LessOrEqualIxE7ComputeEPNS_15OpKernelContextEENUlRNS_15BroadcastHelperEE_8__invokeES5___ZZNK11onnxruntime11LessOrEqualIxE7ComputeEPNS_15OpKernelContextEENUlRNS_15BroadcastHelperEE0_8__invokeES5___ZZNK11onnxruntime11LessOrEqualIxE7ComputeEPNS_15OpKernelContextEENUlRNS_15BroadcastHelperEE1_8__invokeES5___ZZN11onnxruntime21BuildKernelCreateInfoINS_60kCpuExecutionProvider_GreaterOrEqual_kOnnxDomain_ver12_floatEEENS_16KernelCreateInfoEvEN5$_1548__invokeERKNS_12OpKernelInfoE__ZN11onnxruntime14GreaterOrEqualIfED1Ev__ZN11onnxruntime14GreaterOrEqualIfED0Ev__ZNK11onnxruntime14GreaterOrEqualIfE7ComputeEPNS_15OpKernelContextE__ZZNK11onnxruntime14GreaterOrEqualIfE7ComputeEPNS_15OpKernelContextEENUlRNS_15BroadcastHelperEE_8__invokeES5___ZZNK11onnxruntime14GreaterOrEqualIfE7ComputeEPNS_15OpKernelContextEENUlRNS_15BroadcastHelperEE0_8__invokeES5___ZZNK11onnxruntime14GreaterOrEqualIfE7ComputeEPNS_15OpKernelContextEENUlRNS_15BroadcastHelperEE1_8__invokeES5___ZZN11onnxruntime21BuildKernelCreateInfoINS_61kCpuExecutionProvider_GreaterOrEqual_kOnnxDomain_ver12_doubleEEENS_16KernelCreateInfoEvEN5$_1558__invokeERKNS_12OpKernelInfoE__ZN11onnxruntime14GreaterOrEqualIdED1Ev__ZN11onnxruntime14GreaterOrEqualIdED0Ev__ZNK11onnxruntime14GreaterOrEqualIdE7ComputeEPNS_15OpKernelContextE__ZZNK11onnxruntime14GreaterOrEqualIdE7ComputeEPNS_15OpKernelContextEENUlRNS_15BroadcastHelperEE_8__invokeES5___ZZNK11onnxruntime14GreaterOrEqualIdE7ComputeEPNS_15OpKernelContextEENUlRNS_15BroadcastHelperEE0_8__invokeES5___ZZNK11onnxruntime14GreaterOrEqualIdE7ComputeEPNS_15OpKernelContextEENUlRNS_15BroadcastHelperEE1_8__invokeES5___ZZN11onnxruntime21BuildKernelCreateInfoINS_62kCpuExecutionProvider_GreaterOrEqual_kOnnxDomain_ver12_int32_tEEENS_16KernelCreateInfoEvEN5$_1568__invokeERKNS_12OpKernelInfoE__ZN11onnxruntime14GreaterOrEqualIiED1Ev__ZN11onnxruntime14GreaterOrEqualIiED0Ev__ZNK11onnxruntime14GreaterOrEqualIiE7ComputeEPNS_15OpKernelContextE__ZZNK11onnxruntime14GreaterOrEqualIiE7ComputeEPNS_15OpKernelContextEENUlRNS_15BroadcastHelperEE_8__invokeES5___ZZNK11onnxruntime14GreaterOrEqualIiE7ComputeEPNS_15OpKernelContextEENUlRNS_15BroadcastHelperEE0_8__invokeES5___ZZNK11onnxruntime14GreaterOrEqualIiE7ComputeEPNS_15OpKernelContextEENUlRNS_15BroadcastHelperEE1_8__invokeES5___ZZN11onnxruntime21BuildKernelCreateInfoINS_62kCpuExecutionProvider_GreaterOrEqual_kOnnxDomain_ver12_int64_tEEENS_16KernelCreateInfoEvEN5$_1578__invokeERKNS_12OpKernelInfoE__ZN11onnxruntime14GreaterOrEqualIxED1Ev__ZN11onnxruntime14GreaterOrEqualIxED0Ev__ZNK11onnxruntime14GreaterOrEqualIxE7ComputeEPNS_15OpKernelContextE__ZZNK11onnxruntime14GreaterOrEqualIxE7ComputeEPNS_15OpKernelContextEENUlRNS_15BroadcastHelperEE_8__invokeES5___ZZNK11onnxruntime14GreaterOrEqualIxE7ComputeEPNS_15OpKernelContextEENUlRNS_15BroadcastHelperEE0_8__invokeES5___ZZNK11onnxruntime14GreaterOrEqualIxE7ComputeEPNS_15OpKernelContextEENUlRNS_15BroadcastHelperEE1_8__invokeES5___ZZN11onnxruntime21BuildKernelCreateInfoINS_51kCpuExecutionProvider_Mean_kOnnxDomain_ver6_7_floatEEENS_16KernelCreateInfoEvEN5$_1588__invokeERKNS_12OpKernelInfoE__ZN11onnxruntime6Mean_6IfED1Ev__ZN11onnxruntime6Mean_6IfED0Ev__ZZN11onnxruntime21BuildKernelCreateInfoINS_52kCpuExecutionProvider_Mean_kOnnxDomain_ver8_12_floatEEENS_16KernelCreateInfoEvEN5$_1598__invokeERKNS_12OpKernelInfoE__ZN11onnxruntime6Mean_8IfED1Ev__ZN11onnxruntime6Mean_8IfED0Ev__ZZN11onnxruntime21BuildKernelCreateInfoINS_50kCpuExecutionProvider_Mean_kOnnxDomain_ver13_floatEEENS_16KernelCreateInfoEvEN5$_1608__invokeERKNS_12OpKernelInfoE__ZZN11onnxruntime21BuildKernelCreateInfoINS_56kCpuExecutionProvider_BitShift_kOnnxDomain_ver11_uint8_tEEENS_16KernelCreateInfoEvEN5$_1618__invokeERKNS_12OpKernelInfoE__ZN11onnxruntime8BitShiftIhEC2ERKNS_12OpKernelInfoE__ZN11onnxruntime8BitShiftIhED1Ev__ZN11onnxruntime8BitShiftIhED0Ev__ZNK11onnxruntime8BitShiftIhE7ComputeEPNS_15OpKernelContextE__ZZNK11onnxruntime8BitShiftIhE7ComputeEPNS_15OpKernelContextEENUlRNS_15BroadcastHelperEE_8__invokeES5___ZZNK11onnxruntime8BitShiftIhE7ComputeEPNS_15OpKernelContextEENUlRNS_15BroadcastHelperEE0_8__invokeES5___ZZNK11onnxruntime8BitShiftIhE7ComputeEPNS_15OpKernelContextEENUlRNS_15BroadcastHelperEE1_8__invokeES5___ZZNK11onnxruntime8BitShiftIhE7ComputeEPNS_15OpKernelContextEENKUlRNS_15BroadcastHelperEE1_clES5___ZZN11onnxruntime21BuildKernelCreateInfoINS_57kCpuExecutionProvider_BitShift_kOnnxDomain_ver11_uint32_tEEENS_16KernelCreateInfoEvEN5$_1628__invokeERKNS_12OpKernelInfoE__ZN11onnxruntime8BitShiftIjEC2ERKNS_12OpKernelInfoE__ZN11onnxruntime8BitShiftIjED1Ev__ZN11onnxruntime8BitShiftIjED0Ev__ZNK11onnxruntime8BitShiftIjE7ComputeEPNS_15OpKernelContextE__ZZNK11onnxruntime8BitShiftIjE7ComputeEPNS_15OpKernelContextEENUlRNS_15BroadcastHelperEE_8__invokeES5___ZZNK11onnxruntime8BitShiftIjE7ComputeEPNS_15OpKernelContextEENUlRNS_15BroadcastHelperEE0_8__invokeES5___ZZNK11onnxruntime8BitShiftIjE7ComputeEPNS_15OpKernelContextEENUlRNS_15BroadcastHelperEE1_8__invokeES5___ZZNK11onnxruntime8BitShiftIjE7ComputeEPNS_15OpKernelContextEENKUlRNS_15BroadcastHelperEE1_clES5___ZZN11onnxruntime21BuildKernelCreateInfoINS_57kCpuExecutionProvider_BitShift_kOnnxDomain_ver11_uint64_tEEENS_16KernelCreateInfoEvEN5$_1638__invokeERKNS_12OpKernelInfoE__ZN11onnxruntime8BitShiftIyEC2ERKNS_12OpKernelInfoE__ZN11onnxruntime8BitShiftIyED1Ev__ZN11onnxruntime8BitShiftIyED0Ev__ZNK11onnxruntime8BitShiftIyE7ComputeEPNS_15OpKernelContextE__ZZNK11onnxruntime8BitShiftIyE7ComputeEPNS_15OpKernelContextEENUlRNS_15BroadcastHelperEE_8__invokeES5___ZZNK11onnxruntime8BitShiftIyE7ComputeEPNS_15OpKernelContextEENUlRNS_15BroadcastHelperEE0_8__invokeES5___ZZNK11onnxruntime8BitShiftIyE7ComputeEPNS_15OpKernelContextEENUlRNS_15BroadcastHelperEE1_8__invokeES5___ZZNK11onnxruntime8BitShiftIyE7ComputeEPNS_15OpKernelContextEENKUlRNS_15BroadcastHelperEE1_clES5___ZZN11onnxruntime21BuildKernelCreateInfoINS_51kCpuExecutionProvider_Erf_kOnnxDomain_ver9_12_floatEEENS_16KernelCreateInfoEvEN5$_1648__invokeERKNS_12OpKernelInfoE__ZN11onnxruntime3ErfIfED1Ev__ZN11onnxruntime3ErfIfED0Ev__ZZN11onnxruntime21BuildKernelCreateInfoINS_49kCpuExecutionProvider_Erf_kOnnxDomain_ver13_floatEEENS_16KernelCreateInfoEvEN5$_1658__invokeERKNS_12OpKernelInfoE__ZZN11onnxruntime21BuildKernelCreateInfoINS_42kCpuExecutionProvider_Not_kOnnxDomain_ver1EEENS_16KernelCreateInfoEvEN5$_1668__invokeERKNS_12OpKernelInfoE__ZZN11onnxruntime21BuildKernelCreateInfoINS_42kCpuExecutionProvider_And_kOnnxDomain_ver7EEENS_16KernelCreateInfoEvEN5$_1678__invokeERKNS_12OpKernelInfoE__ZZN11onnxruntime21BuildKernelCreateInfoINS_41kCpuExecutionProvider_Or_kOnnxDomain_ver7EEENS_16KernelCreateInfoEvEN5$_1688__invokeERKNS_12OpKernelInfoE__ZZN11onnxruntime21BuildKernelCreateInfoINS_42kCpuExecutionProvider_Xor_kOnnxDomain_ver7EEENS_16KernelCreateInfoEvEN5$_1698__invokeERKNS_12OpKernelInfoE__ZZNK11onnxruntime3And7ComputeEPNS_15OpKernelContextEEN5$_1708__invokeERNS_15BroadcastHelperE__ZZNK11onnxruntime3And7ComputeEPNS_15OpKernelContextEEN5$_1718__invokeERNS_15BroadcastHelperE__ZZNK11onnxruntime3And7ComputeEPNS_15OpKernelContextEEN5$_1728__invokeERNS_15BroadcastHelperE__ZZNK11onnxruntime2Or7ComputeEPNS_15OpKernelContextEEN5$_1738__invokeERNS_15BroadcastHelperE__ZZNK11onnxruntime2Or7ComputeEPNS_15OpKernelContextEEN5$_1748__invokeERNS_15BroadcastHelperE__ZZNK11onnxruntime2Or7ComputeEPNS_15OpKernelContextEEN5$_1758__invokeERNS_15BroadcastHelperE__ZZNK11onnxruntime3Xor7ComputeEPNS_15OpKernelContextEEN5$_1768__invokeERNS_15BroadcastHelperE__ZZNK11onnxruntime3Xor7ComputeEPNS_15OpKernelContextEEN5$_1778__invokeERNS_15BroadcastHelperE__ZZNK11onnxruntime3Xor7ComputeEPNS_15OpKernelContextEEN5$_1788__invokeERNS_15BroadcastHelperE__ZZNK11onnxruntime6Mean_8IfE7ComputeEPNS_15OpKernelContextEEN5$_1808__invokeERNS_15BroadcastHelperE__ZZNK11onnxruntime6Mean_8IfE7ComputeEPNS_15OpKernelContextEEN5$_1818__invokeERNS_15BroadcastHelperE__ZZNK11onnxruntime6Mean_8IfE7ComputeEPNS_15OpKernelContextEEN5$_1828__invokeERNS_15BroadcastHelperE__ZZNK11onnxruntime6Mean_8IfE7ComputeEPNS_15OpKernelContextEEN5$_1798__invokeERKNS_15TensorAllocatorERKNS_11TensorShapeE__ZZN11onnxruntime21BuildKernelCreateInfoINS_48kCpuExecutionProvider_Sin_kOnnxDomain_ver7_floatEEENS_16KernelCreateInfoEvEN5$_1838__invokeERKNS_12OpKernelInfoE__ZN11onnxruntime3SinIfED1Ev__ZN11onnxruntime3SinIfED0Ev__ZNK11onnxruntime3SinIfE7ComputeEPNS_15OpKernelContextE__ZN5Eigen8internal13psincos_floatILb1EDv4_fEET0_RKS3___ZZN11onnxruntime21BuildKernelCreateInfoINS_49kCpuExecutionProvider_Sin_kOnnxDomain_ver7_doubleEEENS_16KernelCreateInfoEvEN5$_1848__invokeERKNS_12OpKernelInfoE__ZN11onnxruntime3SinIdED1Ev__ZN11onnxruntime3SinIdED0Ev__ZNK11onnxruntime3SinIdE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Block1523.LProcessCountM5.LProcessNextColumnLoop2xN1934.LComputeBlockBy4Loop1936.LProcessRemainingBlocks1936.LComputeBlockBy1Loop1936.LOutputBlock1936.LMultiplyAlpha2xNBlock1934.LStore2xNBlock1934.LProcessRemainingCountN1934.LComputeBlockBy4Loop2193.LProcessRemainingBlocks2193.LComputeBlockBy1Loop2193.LOutputBlock2193.LMultiplyAlpha1xNBlock1934.LStore1xNBlock1934.LOutputMasked2xNBlock1934.LMultiplyAlphaMasked2xNBlock1934.LStoreMasked2xNBlock1934.LOutputMasked1xNBlock1934.LMultiplyAlphaMasked1xNBlock1934.LStoreMasked1xNBlock1934.LNchw.4.ProcessOutputCount.LNchw.4.ProcessNextOutputCountBy3.LNchw.4.3.ProcessNextRow.LNchw.4.3.ProcessNextColumn.LNchw.4.3.SkipOverPadding.LNchw.4.3.HandlePostProcessing.LNchw.4.ProcessRemainingOutputCount.LNchw.4.2.ProcessNextRow.LNchw.4.2.ProcessNextColumn.LNchw.4.2.SkipOverPadding.LNchw.4.2.HandlePostProcessing.LNchw.4.ProcessOutputCountRightPadAndRemaining.LNchw.ProcessFilterCount3.LNchw.3.ProcessOutputCount.LNchw.3.ProcessNextOutputCountBy3.LNchw.3.3.ProcessNextRow.LNchw.3.3.ProcessNextColumn.LNchw.3.3.SkipOverPadding.LNchw.3.3.HandlePostProcessing.LNchw.3.ProcessRemainingOutputCount.LNchw.3.2.ProcessNextRow.LNchw.3.2.ProcessNextColumn.LNchw.3.2.SkipOverPadding.LNchw.3.2.HandlePostProcessing.LNchw.3.ProcessOutputCountRightPadAndRemaining.LNchw.ProcessFilterCountLessThan3.LNchw.2.ProcessOutputCount.LNchw.2.ProcessNextOutputCountBy3.LNchw.2.3.ProcessNextRow.LNchw.2.3.ProcessNextColumn.LNchw.2.3.SkipOverPadding.LNchw.2.3.HandlePostProcessing.LNchw.2.ProcessRemainingOutputCount.LNchw.2.2.ProcessNextRow.LNchw.2.2.ProcessNextColumn.LNchw.2.2.SkipOverPadding.LNchw.2.2.HandlePostProcessing.LNchw.2.ProcessOutputCountRightPadAndRemaining.LNchw.ProcessFilterCount1.LNchw.1.ProcessOutputCount.LNchw.1.ProcessNextOutputCountBy3.LNchw.1.3.ProcessNextRow.LNchw.1.3.ProcessNextColumn.LNchw.1.3.SkipOverPadding.LNchw.1.3.HandlePostProcessing.LNchw.1.ProcessRemainingOutputCount.LNchw.1.2.ProcessNextRow.LNchw.1.2.ProcessNextColumn.LNchw.1.2.SkipOverPadding.LNchw.1.2.HandlePostProcessing.LNchw.1.ProcessOutputCountRightPadAndRemaining.LNchw.ExitKernelMlasConvNchwFloatSingleFma3Filter1.LNchw.1.1.ProcessNextRow.LNchw.1.1.ProcessNextColumn.LNchw.1.1.SkipOverPadding.LNchw.1.1.HandlePostProcessingMlasConvNchwFloatSingleFma3Filter2.LNchw.2.1.ProcessNextRow.LNchw.2.1.ProcessNextColumn.LNchw.2.1.SkipOverPadding.LNchw.2.1.HandlePostProcessingMlasConvNchwFloatSingleFma3Filter3.LNchw.3.1.ProcessNextRow.LNchw.3.1.ProcessNextColumn.LNchw.3.1.SkipOverPadding.LNchw.3.1.HandlePostProcessingMlasConvNchwFloatSingleFma3Filter4.LNchw.4.1.ProcessNextRow.LNchw.4.1.ProcessNextColumn.LNchw.4.1.SkipOverPadding.LNchw.4.1.HandlePostProcessing.LNchwc.4.ProcessOutputCount.LNchwc.4.ProcessNextOutputCountBy3.LNchwc.4.3.ProcessNextRow.LNchwc.4.3.ProcessNextColumn.LNchwc.4.3.SkipOverPadding.LNchwc.4.3.HandlePostProcessing.LNchwc.4.ProcessRemainingOutputCount.LNchwc.4.2.ProcessNextRow.LNchwc.4.2.ProcessNextColumn.LNchwc.4.2.SkipOverPadding.LNchwc.4.2.HandlePostProcessing.LNchwc.4.ProcessOutputCountRightPadAndRemaining.LNchwc.ProcessFilterCount3.LNchwc.3.ProcessOutputCount.LNchwc.3.ProcessNextOutputCountBy3.LNchwc.3.3.ProcessNextRow.LNchwc.3.3.ProcessNextColumn.LNchwc.3.3.SkipOverPadding.LNchwc.3.3.HandlePostProcessing.LNchwc.3.ProcessRemainingOutputCount.LNchwc.3.2.ProcessNextRow.LNchwc.3.2.ProcessNextColumn.LNchwc.3.2.SkipOverPadding.LNchwc.3.2.HandlePostProcessing.LNchwc.3.ProcessOutputCountRightPadAndRemaining.LNchwc.ProcessFilterCountLessThan3.LNchwc.2.ProcessOutputCount.LNchwc.2.ProcessNextOutputCountBy3.LNchwc.2.3.ProcessNextRow.LNchwc.2.3.ProcessNextColumn.LNchwc.2.3.SkipOverPadding.LNchwc.2.3.HandlePostProcessing.LNchwc.2.ProcessRemainingOutputCount.LNchwc.2.2.ProcessNextRow.LNchwc.2.2.ProcessNextColumn.LNchwc.2.2.SkipOverPadding.LNchwc.2.2.HandlePostProcessing.LNchwc.2.ProcessOutputCountRightPadAndRemaining.LNchwc.ProcessFilterCount1.LNchwc.1.ProcessOutputCount.LNchwc.1.ProcessNextOutputCountBy3.LNchwc.1.3.ProcessNextRow.LNchwc.1.3.ProcessNextColumn.LNchwc.1.3.SkipOverPadding.LNchwc.1.3.HandlePostProcessing.LNchwc.1.ProcessRemainingOutputCount.LNchwc.1.2.ProcessNextRow.LNchwc.1.2.ProcessNextColumn.LNchwc.1.2.SkipOverPadding.LNchwc.1.2.HandlePostProcessing.LNchwc.1.ProcessOutputCountRightPadAndRemaining.LNchwc.ExitKernelMlasConvNchwcFloatSingleFma3Filter1.LNchwc.1.1.ProcessNextRow.LNchwc.1.1.ProcessNextColumn.LNchwc.1.1.SkipOverPadding.LNchwc.1.1.HandlePostProcessingMlasConvNchwcFloatSingleFma3Filter2.LNchwc.2.1.ProcessNextRow.LNchwc.2.1.ProcessNextColumn.LNchwc.2.1.SkipOverPadding.LNchwc.2.1.HandlePostProcessingMlasConvNchwcFloatSingleFma3Filter3.LNchwc.3.1.ProcessNextRow.LNchwc.3.1.ProcessNextColumn.LNchwc.3.1.SkipOverPadding.LNchwc.3.1.HandlePostProcessingMlasConvNchwcFloatSingleFma3Filter4.LNchwc.4.1.ProcessNextRow.LNchwc.4.1.ProcessNextColumn.LNchwc.4.1.SkipOverPadding.LNchwc.4.1.HandlePostProcessing.LDepthwise.1.ProcessOutputCount.LDepthwise.1.ProcessNextOutputCountBy3.LDepthwise.1.3.ProcessNextRow.LDepthwise.1.3.ProcessN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