
    gD                    &  d Z ddlmZ ddlmZ ddlmZmZmZm	Z	m
Z
mZmZmZmZmZmZmZmZmZmZmZmZmZmZmZmZ  ej        e          Zi dg ddg d	g d
g ddgdg dg dg dg ddg ddg dg dg dg dg dg ddgi dddgdg d g d!d"d#gd$g d%g d&g d'd(g d)d*gd+g d,d-g d.d/gd0g d1d2g d3d4d5d6gd7g d8d9d:gi d;g d<d=d>d?gd@g dAg dBdCgdDg dEdFdGgdHg dIdJdKgdLdMgdNdOgdPdQdRgdSdTgdUdVdWgdXdYdZgd[g d\d]g d^i d_d`gdag dbdcdddegdfdggdhdigdjdkdlgdmg dndog dpdqg drdsg dtdug dvdwg dxdyg dzd{d|gd}d~gddgdddgi ddgddgdg dddgdddgddgdddgdg dddgdddgddgddgddgddgdg dg ddgi ddgddgdddgddgdg ddg dddgddgddgddgddgddgdddgdddgdg dǢddgddgi dg d͢dg dϢddgddgddgddgddgdg ddgddgdddgdg dddgdg dddgddgdddgi dddgddgddgdddgddgddgdg ddd dgdg dddgddgdd	d
gdddgddgddgddgdg di ddgddgdddgddgdd gd!d"gd#d$gd%g d&d'gd(d)gd*d+gd,d-d.gd/g d0d1d2gd3d4gd5d6gd7d8gi d9d:gd;d<gd=d>gd?d@gdAdBgdCg dDdEg dFdGdHgdIdJgdKdLdMgdNdOdPgdQg dRdSg dTdUdVgdWdXdYgdZd[gd\d]gi d^d_gd`dadbgdcdddegdfdgdhgdidjdkgdldmdngdodpgdqdrdsgdtdudvgdwdxgdydzgd{d|gd}d~gdg dddgdddgddgi dg ddgdg dg dddgddgddgdddgdg dddgddgddgddgddgdddgdddgddgi ddgddgdddgdddgdddgddgddgdg ddgddgddgdÐdgdŐdgdǐdȐdgdʐdːdgd͐dΐdgdАdgi dg dӢdg dբd֐dgdؐdgdڐdgdܐdݐdgdߐdgdddgddgddgddgddgddgdg ddddgddgddgi ddgdddgddgddgd ddgdg dddgddd	gd
g dddgddgddgddgddgdddgddgdddgi ddd gd!d"d#gd$d%gd&g d'd(g d)d*d+gd,d-gd.d/gd0d1gd2d3gd4g d5d6d7gd8g d9d:g d;d<d=d>gd?d@dAgdBdCgi dDdEgdFdGgdHdIgdJdKgdLdMgdNdOgdPdQgdRdSgdTdUgdVdWdXgdYdZgd[d\gd]d^gd_d`dagdbdcddgdedfdggdhdigi djdkgdldmgdndodpgdqdrgdsdtgdudvgdwg dxdydzgd{d|gd}d~dgddgddgddgddgddgddgdddgi ddgdg ddddgddgddgddgddgdg ddg dddgdddgddgddgddgddgddgddgi ddgddgdg dg dddgdg dg ddgdg ddg dâdg dŢdƐdgdȐdgdʐdgdg d͢dg dϢZ	  e            s
 e            	 ed.                             dЦ           ed@                             dѦ           edA                             dҦ           edF                             dӦ           edL                             dԦ           edh                             dզ           edy                             d֦           ed                             dצ           ed                             dئ           ed                             d٦           ed                             dڦ           ed                             dۦ           ed                             dܦ           ed%                             dݦ           edU                             dަ           ed^                             dߦ           edw                             d           ed}                             d           ed                             d           ed                             d           ed                             d           ed                             d           ed                             d           ed                             dަ           ed                             d           ed                             d           ed                             d           ed(                             d           ed4                             d           ed8                             d           ed:                             d           edR                             d           ede                             d           ed                             d           ed                             d           ed                             d           n,# e$ r$ ddlm Z  d  e!e           D             ed<   Y nw xY w	  e            s
 e            	 ed.                             d           ed=                             d           ed@                             d           edD                             d           edL                             d           edU                             d           edX                             d           ed_                             d           edh                             d           eds                             d           edy                             d            edz                             d           ed}                             d           ed                             d           ed                             d           ed                             d           ed                             d           ed                             d           ed                             d           ed                             d	           ed         "                    g d
           ed                             d           ed                             d           ed                             d           ed                             d           ed                             d           ed!                             d           ed#                             d           ed1                             d           edN                             d           edQ                             d           edS                             d           edU                             d           edW                             d           ed^                             d           edl                             d           edt                             d           ed                             d           ed                             d           ed                             d           ed                             d           ed                             d           ed                             d            ed                             d!           ed                             d"           ed                             d#           ed                             d$           ed                             d%           ed                              d&           ed                             d'           ed                             d(           ed                             d)           ed                             d*           ed(                             d+           ed<                             d,           ed?                             d-           edR                             d.           ede                             d/           ed                             d0           ed                             d1           ed                             d2           ed                             d3           d4ged5<   n,# e$ r$ dd6lm#Z# d7  e!e#          D             ed8<   Y nw xY w	  e            r
 e            s
 e            	 d9d:ged:<   n,# e$ r$ dd;lm$Z$ d<  e!e$          D             ed=<   Y nw xY w	  e            s
 e            	 edD                             d>           n,# e$ r$ dd?lm%Z% d@  e!e%          D             edA<   Y nw xY w	  e            s
 e            	 ed                             dB           n,# e$ r$ ddClm&Z& dD  e!e&          D             edE<   Y nw xY w	  e            s
 e            	 dFgedG<   dHgedI<   dJgedK<   edB         "                    dLdMg           edS         "                    dNg           ed[         "                    dOg           eda                             dP           edm                             dQ           edo         "                    dRdSg           eds         "                    dTdUg           ed         "                    dVdWg           ed         "                    dXdYg           ed         "                    dZd[g           ed         "                    d\d]g           ed                             d^           ed                             d_           ed                             d`           ed         "                    dag           ed         "                    g db           ed         "                    dcddg           ed         "                    dedfg           ed                             dg           ed         "                    g dh           ed         "                    didjg           ed         "                    dkdlg           ed,         "                    dmg           ed9         "                    dng           ed;         "                    dog           ed=         "                    dpg           ed?         "                    dqdrg           edE         "                    dsg           edQ         "                    dtdug           edS         "                    dvdwg           edZ         "                    dxdyg           edc                             dz           edf                             d{           edi         "                    d|d}g           ed                             d~           ed         "                    ddg           ed         "                    dg           ed         "                    ddg           ed         "                    ddg           ed         "                    ddg           ed                             d           ed         "                    dg           ed                             d           ed         "                    ddg           ed         "                    ddg           ed         "                    dg           ed                             d           ed         "                    ddg           ed         "                    dg           ed         "                    dg           ed!         "                    dg           ed&         "                    dg           ed,         "                    ddg           ed.         "                    dg           ed4                             d           edF         "                    dg           edL                             d           edb                             d           eds                             d           edu         "                    ddg           edw         "                    g d           ed         "                    ddg           ed                             d           ed                             d           ed         "                    ddg           ed                             d           n,# e$ r$ ddlm'Z' d  e!e'          D             ed<   Y nw xY w	  e            s
 e            	 dged<   ed                             d           n,# e$ r$ ddlm(Z( d  e!e(          D             ed<   Y nw xY w	  e            s
 e            	 g ed<   dged<   dged<   g ded<   g ded<   ed          "                    g d           ddged<   g ed<   g ed<   dged<   dged<   ed.         "                    g dŢ           ed0         "                    g dƢ           ed2         "                    g dǢ           ed4         "                    g dȢ           ed7         "                    g dɢ           ed9         "                    g dʢ           ed;         "                    g dˢ           ed=         "                    g d̢           edB         "                    g d͢           edD         "                    g d΢           edF         "                    g dϢ           edL         "                    g dТ           edN         "                    g dѢ           edP         "                    g dҢ           edS         "                    g dӢ           edU         "                    g dԢ           edX         "                    g dբ           ed[         "                    g d֢           ed]         "                    g dע           ed_         "                    g dآ           eda         "                    g d٢           edc         "                    g dڢ           edh         "                    g dۢ           edj         "                    g dܢ           edm         "                    g dݢ           edo         "                    g dޢ           edq         "                    g dߢ           eds         "                    g d           edu         "                    g d           edw         "                    g d           edz         "                    g d           ed}         "                    g d           ed         "                    g d           ed         "                    g d           ed         "                    g d           ed         "                    g d           ed         "                    g d           ed         "                    g d           ed         "                    g d           ed         "                    ddg           ed         "                    g d           ed         "                    g d           ed         "                    g d           ed         "                    g d           ed         "                    g d           ed         "                    g d           ed         "                    g d           ed         "                    g d           ed         "                    g d           ed         "                    g d           ed         "                    g d           ed         "                    g d           ed         "                    g d           ed         "                    g d           ed         "                    g d           ed         "                    g d           ed         "                    g d           ed         "                    g d           ed         "                    g d            ed         "                    g d           ed         "                    g d           ed         "                    ddg           ed         "                    ddg           ed         "                    ddg           ed         "                    g d	           ed         "                    g d
           ed         "                    g d           ed         "                    g d           ed         "                    g d           ed         "                    ddg           ed         "                    g d           ed         "                    g d           ed         "                    g d           ed         "                    g d           ed         "                    ddg           ed         "                    g d           ed         "                    g d           ed         "                    g d           ed         "                    g d           ed         "                    ddg           ed                             d           ed         "                    g d           ed         "                    g d           ed         "                    g d           ed         "                    g d            ed         "                    g d!           ed         "                    g d"           ed         "                    g d#           ed         "                    g d$           ed         "                    g d%           ed         "                    g d&           ed         "                    g d'           ed         "                    d(d)g           ed         "                    g d*           ed         "                    g d+           ed         "                    g d,           ed         "                    g d-           ed         "                    g d.           ed         "                    g d/           ed         "                    g d0           ed         "                    g d1           ed!         "                    g d2           ed#         "                    g d3           ed&         "                    g d4           ed(         "                    g d5           ed*         "                    g d6           ed,         "                    g d7           ed/         "                    g d8           ed3         "                    g d9           ed5         "                    g d:           ed7         "                    g d;           ed9         "                    g d<           ed;         "                    g d=           ed=         "                    g d>           ed?         "                    g d?           edA         "                    g d@           edC         "                    g dA           edE         "                    g dB           edG         "                    g dC           edI         "                    g dD           edK         "                    g dE           edN         "                    g dF           edQ         "                    g dG           edS         "                    g dH           edW         "                    g dI           edZ         "                    g dJ           ed\         "                    g dK           ed^         "                    g dL           ed`         "                    dMdNg           edc         "                    dOdPg           edf         "                    dQdRg           edi         "                    dSdTg           edl         "                    g dU           edo         "                    g dV           edq         "                    g dW           edt         "                    g dX           edw         "                    g dY           edy         "                    g dZ           ed{         "                    g d[           ed}         "                    g d\           ed         "                    g d]           ed         "                    g d^           ed         "                    g d_           ed         "                    g d`           ed         "                    g da           ed         "                    g db           ed         "                    dcddg           ed         "                    g de           ed         "                    g df           ed         "                    g dg           ed         "                    g dh           ed         "                    g di           ed         "                    g dj           ed         "                    g dk           ed         "                    g dl           ed         "                    g dm           ed         "                    g dn           ed         "                    g do           ed         "                    g dp           ed         "                    g dq           ed         "                    g dr           ed         "                    g ds           ed         "                    g dt           ed         "                    g du           ed         "                    g dv           ed         "                    g dw           ed         "                    g dx           ed         "                    g dy           ed         "                    dzd{g           ed         "                    g d|           ed         "                    g d}           ed         "                    g d~           ed         "                    g d           ed         "                    g d           ed         "                    g d           ed         "                    g d           ed         "                    g d           ed         "                    g d           ed         "                    g d           ed         "                    g d           ed         "                    g d           ed         "                    g d           ed         "                    g d           ed         "                    g d           ed         "                    g d           ed         "                    ddg           ed         "                    g d           ed         "                    g d           ed         "                    ddg           ed         "                    g d           ed         "                    g d           ed         "                    g d           ed          "                    g d           ed         "                    g d           ed         "                    g d           ed         "                    g d           ed
         "                    g d           ed         "                    g d           ed         "                    g d           ed         "                    g d           ed         "                    g d           ed         "                    g d           ed         "                    g d           ed         "                    g d           ed         "                    g d           ed         "                    g d           ed!         "                    g d           ed$         "                    g d           ed&         "                    ddg           ed(         "                    g d           ed*         "                    g d           ed,         "                    g d           ed.         "                    g d           ed0         "                    g d           ed2         "                    g d           ed4         "                    g d           ed6         "                    dg           ed8         "                    g d           ed:         "                    g d           ed<         "                    g d           ed?         "                    g d           edB         "                    g d           edD         "                    g d           edF         "                    ddg           edH         "                    g d           edJ         "                    g d           edL         "                    g d           edN         "                    g d           edP         "                    g d           edR         "                    g d           edT         "                    g d           edV         "                    g d           edY         "                    g d           ed[         "                    g d           ed]         "                    dg           ed_         "                    ddg           edb         "                    g dĢ           ede         "                    g dŢ           edh         "                    g dƢ           edj         "                    g dǢ           edl         "                    g dȢ           edn         "                    dg           edq         "                    dʐdg           eds         "                    g d̢           edu         "                    g d͢           edw         "                    g d΢           edy         "                    dϐdg           ed{         "                    dg           ed}         "                    dg           ed         "                    g dӢ           ed         "                    g dԢ           ed         "                    g dբ           ed         "                    g d֢           ed         "                    g dע           ed         "                    dؐdg           ed         "                    dڐdg           ed         "                    g dܢ           ed         "                    g dݢ           ed         "                    g dޢ           ed         "                    g dߢ           ed         "                    g d           ed         "                    g d           ed         "                    g d           ed         "                    g d           ed         "                    g d           ed         "                    g d           ed         "                    g d           ed         "                    g d           ed         "                    g d           ed         "                    g d           ed         "                    g d           ed         "                    g d           ed         "                    ddg           g ded<   g ded<   g ed<   g ed<   dged<   dged<   dged<   n,# e$ r$ ddlm)Z) d  e!e)          D             ed<   Y nw xY w	  e            s
 e            	 g ed<   dged<   d ged<   ed          "                    g d           ddged<   g ed<   g ded<   ed.         "                    g d	           ed7         "                    g d
           ed=         "                    g d           edD         "                    g d           edU         "                    g d           edX         "                    g d           ed[         "                    g d           edh         "                    g d           eds         "                    g d           ed         "                    g d           ed         "                    g d           ed         "                    g d           ed         "                    g d           ed         "                    g d           ed         "                    g d           ed         "                    g d           ed         "                    g d           ed         "                    g d           ed         "                    g d           ed         "                    g d           ed         "                    g d           ed         "                    g d           ed         "                    g d           ed                             d            ed         "                    g d!           ed         "                    g d"           ed         "                    g d#           ed         "                    g d$           ed&         "                    g d%           ed/         "                    g d&           ed5         "                    g d'           ed9         "                    g d(           edN         "                    g d)           edS         "                    g d*           edW         "                    g d+           edl         "                    g d,           edt         "                    g d-           ed}         "                    g d.           ed         "                    g d/           ed         "                    g d0           ed         "                    g d1           ed         "                    g d2           ed         "                    g d3           ed         "                    g d4           ed         "                    g d5           ed         "                    g d6           ed         "                    g d7           ed
         "                    g d8           ed         "                    g d9           ed         "                    g d:           ed         "                    g d;           ed         "                    g d<           ed         "                    g d=           ed         "                    g d>           ed&         "                    d?d@g           ed,         "                    g dA           ed8         "                    g dB           edH         "                    g dC           edJ         "                    g dD           edR         "                    g dE           edV         "                    g dF           ed{         "                    dGg           ed}         "                    dHg           ed         "                    g dI           ed         "                    g dJ           ed         "                    g dK           ed         "                    g dL           ed         "                    g dM           ed         "                    g dN           ed         "                    g dO           ed         "                    g dP           g dQedR<   g edS<   n,# e$ r$ ddTlm*Z* dU  e!e*          D             edV<   Y nw xY w	  e            r( e	            r e            r e            r
 e            s
 e            	 ed                             dW           ed                             dX           ed                             dY           n,# e$ r$ ddZlm+Z+ d[  e!e+          D             ed\<   Y nw xY w	  e            s
 e            	 ed                             d]           ed                             d^           n,# e$ r$ dd_lm,Z, d`  e!e,          D             eda<   Y nw xY w	  e
            s
 e            	 ed          "                    g db           g edc<   ddgede<   ed.         "                    g df           ed7         "                    g dg           ed=         "                    g dh           edB         "                    g di           edD         "                    g dj           edL         "                    g dk           edU         "                    g dl           edX         "                    g dm           ed_         "                    g dn           eds         "                    g do           ed         "                    g dp           ed         "                    g dq           ed         "                    g dr           ed                             ds           ed         "                    g dt           ed         "                    g du           ed&         "                    g dv           ed^         "                    g dw           ed         "                    g dx           edo         "                    g dy           ed}         "                    g dz           ed         "                    g d{           ed         "                    g d|           ed         "                    g d}           ed         "                    g d~           ed         "                    g d           ed         "                    g d           ed         "                    g d           ed         "                    g d           ed         "                    g d           ed         "                    g d           ed6                             d           edR         "                    g d           ed{                             d           ed}         "                    dg           ed         "                    g d           ed         "                    g d           ed         "                    g d           ed         "                    g d           ed         "                    g d           n,# e$ r$ ddlm-Z- d  e!e-          D             ed<   Y nw xY weDr3ddl.m/Z/m0Z0m1Z1m2Z2m3Z3m4Z4m5Z5m6Z6m7Z7m8Z8m9Z9m:Z:m;Z;m<Z<m=Z=m>Z> ddl?m@Z@ ddlAmBZBmCZCmDZDmEZEmFZFmGZGmHZHmIZImJZJmKZKmLZLmMZMmNZNmOZOmPZPmQZQmRZRmSZS ddlTmUZUmVZVmWZWmXZXmYZYmZZZm[Z[m\Z\m]Z]m^Z^m_Z_ ddl`maZa ddlbmcZcmdZd dd!lemfZfmgZgmhZhmiZi ddljmkZk dd'llmmZmmnZnmoZompZpmqZqmrZrmsZsmtZtmuZumvZv ddlwmxZx dd,lymzZzm{Z{m|Z|m}Z}m~Z~mZmZ ddlmZ dd1lmZmZmZmZ dd3lmZmZmZmZ ddlmZmZ dd8lmZmZmZmZmZmZmZmZmZmZmZ ddlmZ dd<lmZmZmZmZmZ ddlmZmZ ddlmZ ddElmZmZmZmZ ddlmZ ddIlmZmZmZ ddlmZ ddlmZ ddlmZ ddlmZmZ ddlmZ ddlmZmZ ddlmZmZ dd\lmZmZmZmZ dd^lmZmZmZmZ ddlmZ ddblmZmZmZmZ ddlmZmZ ddlmZ ddlmZ ddlmZmZ ddnlmZmZmZ ddplmZmZmZmZ ddrlmZmZmZmZ ddtlmZmZmZmZmZ ddvlmZmZmZmZ ddxlmZmZmZmZmZmZ ddl mZmZ ddlmZ ddlmZ ddlmZm	Z	 ddl
mZ ddlmZ ddlmZmZ ddlmZmZ ddlmZ ddlmZmZ ddlmZmZmZ ddlmZ ddlm Z m!Z! ddl"m#Z# ddl$m%Z% ddl&m'Z' ddl(m)Z) ddl*m+Z+ ddl,m-Z- ddl.m/Z/ ddl0m1Z1m2Z2 ddl3m4Z4 ddl5m6Z6m7Z7m8Z8m9Z9 ddl:m;Z;m<Z<m=Z= ddl>m?Z? ddl@mAZA ddlBmCZC ddlDmEZE ddlFmGZG ddlHmIZI ddÐlJmKZKmLZL ddĐlMmNZNmOZO ddǐlPmQZQmRZRmSZS ddŐlTmUZU ddƐlVmWZW dd͐lXmYZYmZZZm[Z[ ddϐl\m]Z]m^Z^m_Z_ ddǐl`maZa ddȐlbmcZc ddɐldmeZe ddʐlfmgZg ddːlhmiZi dd̐ljmkZk dd͐llmmZm ddΐlnmoZompZp ddϐlqmrZrmsZs ddltmuZumvZvmwZwmxZxmyZy ddАlzm{Z{ ddѐl|m}Z} ddҐl~mZmZ ddӐlmZmZ ddԐlmZ ddՐlmZ dd֐lmZmZ ddאlmZ ddؐlmZ ddlmZmZmZmZ ddِlmZmZ ddlmZmZmZmZmZ ddڐlmZ ddېlmZ ddܐlmZmZ ddݐlmZmZ ddސlmZ ddߐlmZ ddlmZ ddlmZmZmZ ddlmZ ddlmZ ddlmZmZ ddlmZ ddlmZ ddlmZ ddlmZ ddlmZ ddlmÐZ ddlĐmŐZ ddlƐmǐZǐmȐZ dd0lɐmʐZʐmːZːm̐Z ddl͐mΐZ ddlϐmАZ ddlѐmҐZ ddlӐmԐZ ddlՐm֐Z ddlאmؐZ ddlِmڐZ ddlېmܐZ ddlݐmސZ ddDlߐmZmZmZmZ ddFlmZmZmZmZ ddlmZ ddlmZ ddlmZmZ ddlmZmZ ddRlmZmZmZmZmZ ddTlmZmZmZmZmZ ddlm Z  ddlmZmZ ddlmZ ddlmZ ddlm	Z	 ddl
mZmZ ddlmZmZ dd lmZmZ ddlmZmZ ddlmZmZ ddlmZ ddlmZmZ ddlmZm Z  ddl!m"Z" ddl#m$Z$ ddl%m&Z& dd	l'm(Z( ddl)m*Z*m+Z+m,Z,m-Z- dd
l.m/Z/ ddl0m1Z1m2Z2 ddl3m4Z4 ddl5m6Z6 ddl7m8Z8m9Z9m:Z: ddl;m<Z< ddl=m>Z> ddl?m@Z@ ddlAmBZBmCZC ddlDmEZEmFZF ddlGmHZH ddlImJZJ ddlKmLZL ddlMmNZN ddlOmPZPmQZQ ddlRmSZSmTZT ddlUmVZV ddlWmXZX ddlYmZZZ ddl[m\Z\m]Z] ddl^m_Z_m`Z` ddlambZbmcZc ddldmeZe dd lfmgZg dd!lhmiZi dd"ljmkZk dd#llmmZm dd$lnmoZo dd%lpmqZq dd&lrmsZsmtZt dd'lumvZvmwZw dd(lxmyZymzZz dd)l{m|Z| ddӐl}m~Z~mZmZmZ ddՐlmZmZmZmZ dd*lmZ dd+lmZ dd,lmZ dd-lmZmZ dd.lmZ dd/lmZmZ dd0lmZ dd1lmZ dd2lmZ dd3lmZ dd4lmZ ddlmZmZmZmZ dd5lmZmZ dd6lmZ dd7lmZ dd8lmZ dd9lmZmZ dd:lmZ dd;lmZ dd<lmZmZ ddlmZmZmZ dd=lmZ dd>lmZmZ ddlmZmZmÐZ dd?lĐmŐZ dd@lƐmǐZ ddAlȐmɐZ ddBlʐmːZ ddCl̐m͐Z ddDlΐmϐZϐmАZ ddElѐmҐZ ddFlӐmԐZԐmՐZ ddGl֐mאZאmؐZ ddHlِmڐZڐmېZ ddIlܐmݐZ dd'lސmߐZߐmZmZmZmZ dd)lmZmZmZ ddJlmZ ddKlmZ ddLlmZ ddMlmZ ddNlmZ dd5lmZmZmZmZ ddOlmZ dd9lmZmZmZ dd;lmZmZm Z mZ ddPlmZmZ ddQlmZmZ ddRlm	Z	 ddSl
mZ ddTlmZ ddUlmZ ddVlmZ ddWlmZ ddXlmZ ddYlmZ ddZlmZ dd[lmZ dd\lmZmZ dd]lm Z  dd^l!m"Z" dd_l#m$Z$ dd`l%m&Z&m'Z' ddal(m)Z)m*Z* ddbl+m,Z,m-Z- ddcl.m/Z/ dddl0m1Z1 ddel2m3Z3 ddfl4m5Z5m6Z6 ddgl7m8Z8 ddhl9m:Z: ddil;m<Z< ddxl=m>Z>m?Z?m@Z@mAZA ddjlBmCZC ddklDmEZE ddllFmGZGmHZH ddmlImJZJ ddnlKmLZL ddolMmNZN ddplOmPZP ddqlQmRZR ddrlSmTZT ddslUmVZVmWZW ddtlXmYZY ddlZm[Z[m\Z\m]Z]m^Z^m_Z_ ddul`maZambZb ddvlcmdZd ddwlemfZf ddxlgmhZh ddylimjZj ddlkmlZlmmZmmnZnmoZo ddlpmqZqmrZrmsZsmtZt ddzlumvZv dd{lwmxZxmyZy dd|lzm{Z{ dd}l|m}Z} dd~l~mZ ddlmZ ddlmZ ddlmZ ddlmZ ddlmZ ddlmZmZmZmZmZmZmZmZmZmZmZmZmZmZmZmZmZmZmZmZmZmZmZmZmZmZmZmZmZmZmZmZmZmZmZ ddlmZ ddlmZ ddlmZmZmZmZmZmZ ddÐlmZmZmZmZmZmZmZ ddŐlmZmÐZÐmĐZĐmŐZŐmƐZ ddlǐmȐZ ddlɐmʐZ ddlːm̐Z ddlm͐Z͐mΐZΐmϐZϐmАZАmѐZѐmҐZҐmӐZӐmԐZԐmՐZՐm֐Z֐mאZאmؐZؐmِZِmڐZmZmېZېmܐZm
Z
mZmݐZݐmސZސmߐZߐmZmZmZmZmZmZmZmZmZmZmZmZmZmZmZmZmZmZmZmZmZmZ ddϐlmZmZmZmZmZmZmZmZmZmZmZ 	  e            s
 e            	 ddlmZ ddlmZ ddlmZ ddlmZ ddlmZ ddlېmZ ddlm Z  ddlmZ ddl"mZ ddl.mZ ddldmZ ddlmZ ddlmZ ddlm	Z	 ddlm
Z
 ddlmZ ddl!mZ ddl'mZ ddl3mZ ddlmZ ddlmZ ddlYmZ ddlmZ ddlmZ ddlmZ ddlƐmZ ddlʐmZ ddlmZ ddlmZ ddlmZ ddlmZ ddlmZ ddl+mZ ddlumZ ddlzm Z  ddl~m!Z! n# e$ r	 ddl"T Y nw xY w	  e            s
 e            	 ddlm#Z# ddlm$Z$ ddlm%Z% ddlm&Z& ddlm'Z' ddlm(Z( ddlm)Z) ddlϐm*Z* ddlېm+Z+ ddlm,Z, ddlm-Z- ddl m.Z. ddlm/Z/ ddlm0Z0 ddlm1Z1 ddlm2Z2 ddl"m3Z3 ddlJm4Z4 ddlMm5Z5 ddlnm6Z6 dd
ltm7Z7m8Z8m9Z9 ddÐl~m:Z: ddĐlm;Z; ddŐlm<Z< ddƐlm=Z= ddǐlm>Z> ddȐlm?Z? ddɐlm@Z@ ddʐl͐mAZA ddːlmBZB dd̐lmCZC dd͐lmDZD ddΐlmEZE ddϐlmFZF ddАlmGZG ddѐlmHZH ddҐlmIZI ddӐl)mJZJ ddԐl3mKZK ddՐlmLZL dd֐lDmMZM ddאlRmNZN ddؐlYmOZO ddِlamPZP ddڐlmQZQ ddېljmRZR ddܐlxmSZS ddݐlmTZT ddސlmUZU ddߐlƐmVZV ddlʐmWZW ddlΐmXZX ddl֐mYZY ddlmZZZ ddlm[Z[ ddlm\Z\ ddlm]Z] ddl+m^Z^ ddlkm_Z_ ddlum`Z` ddlzmaZa ddl~mbZb ddlcmdZd n# e$ r	 ddleT Y nw xY w	  e            r
 e            s
 e            	 ddlfmgZgmfZf n# e$ r	 ddlhT Y nw xY w	  e            s
 e            	 ddlmiZi n# e$ r	 ddljT Y nw xY w	  e            s
 e            	 ddlmkZk n# e$ r	 ddllT Y nw xY w	  e            s
 e            	 ddlmmnZn ddlompZp ddlqmrZr ddlmsZsmtZt ddlmuZu ddlŐmvZv ddlѐmwZw ddlmxZx ddlmyZymzZz ddlm{Z{m|Z| ddlm}Z}m~Z~ ddl
mZmZ ddl&mZmZ ddl(mZmZ ddl*mZ ddl,mZ dd l\mZ ddlbmZ ddblhmZmZmZ ddlqmZmZ ddlzmZmZ ddl|mZ ddhlmZmZmZ ddlmZmZ ddlmZmZ ddlƐmZ ddlՐmZ dd	lאmZ dd
lِmZ ddlېmZmZ ddlmZ ddlmZmZ ddlmZmZ ddlmZmZ ddlmZ ddlmZ ddlmZmZ ddl.mZ ddl0mZmZ ddlAmZ ddlGmZmZ ddlImZmZ ddlKmZmZ ddljmZ ddlumZ ddl}mZ ddlmZmZ ddlmZmZ ddlmZ ddlmZ dd lmZmZ dd!lmZ dd"lmZ dd#lِmZ dd$lސmZ dd%lmZmZ dd&lmZ dd'lmZ dd(lmZ dd)lmÐZ dd*l(mĐZ dd+l9mŐZ dd,l;mƐZƐmǐZ ddl=m?Z?m@Z@mAZA dd-lKmȐZȐmɐZ dd.lSmʐZ dd/lXmːZ dd0lm̐Z̐m͐Z dd1lmΐZ n# e$ r	 ddlT Y nw xY w	  e            s
 e            	 dd2lАmѐZ dd3lKmҐZ n# e$ r	 ddlT Y nw xY w	  e            s
 e            	 dd4lԐmՐZ dd5l֐mאZ ddlؐmِZِmڐZڐmېZېmܐZܐmݐZݐmސZސmߐZߐmZmZmZmZmZmZmZmZ ddlmZmZmZmZmZmZmZmZmZ ddlemZmZmZmZmZmZmZmZmZmZmZmZmZmZm Z mZmZmZmZmZmZmZmZm	Z	m
Z
mZmZmZmZmZmZmZmZmZmZmZmZmZmZmZmZmZmZmZmZmZm Z m!Z!m"Z"m#Z#m$Z$m%Z% dd6l&m'Z'm(Z( dd7l)m*Z* dd8l+m,Z, ddlm-Z-m.Z.m/Z/m0Z0m1Z1m2Z2m3Z3m4Z4m5Z5 ddlm6Z6m7Z7m8Z8m9Z9 ddlm:Z:m;Z;m<Z<m=Z= ddlm>Z>m?Z?m@Z@ dd9lmAZAmBZBmCZCmDZDmEZEmFZFmGZGmHZHmIZImJZJmKZKmLZLmMZMmNZNmOZOmPZPmQZQmRZRmSZSmTZTmUZUmVZVmWZWmXZXmYZYmZZZm[Z[m\Z\m]Z]m^Z^m_Z_m`Z`maZambZbmcZcmdZdmeZemfZfmgZgmhZhmiZimjZjmkZkmlZlmmZmmnZnmoZompZpmqZqmrZrmsZsmtZtmuZumvZvmwZwmxZxmyZymzZzm{Z{m|Z|m}Z}m~Z~mZmZmZmZmZmZmZmZmZmZmZmZmZmZmZmZmZmZmZmZ ddlmZmZmZ ddlmZmZmZmZmZmZ dd:lmZmZmZmZmZmZmZmZ ddlmZmZmZmZmZmZ ddlmZmZmZmZmZmZmZmZmZmZmZ ddlmZmZmZmZ ddlmZmZmZmZmZmZmZmZmZmZ ddlmÐZÐmĐZĐmŐZŐmƐZƐmǐZǐmȐZ ddlmɐZɐmʐZʐmːZːm̐Z̐m͐Z ddlmΐZΐmϐZϐmАZАmѐZ ddlmҐZҐmӐZӐmԐZԐmՐZ ddlm֐Z֐mאZאmؐZؐmِZ ddlŐmڐZڐmېZېmܐZܐmݐZݐmސZސmߐZߐmZ ddlʐmZmZmZmZmZmZmZmZ ddlϐmZmZmZmZmZmZ ddlѐmZmZmZmZmZ ddl֐mZmZmZmZؐmZmZ ddlېmZmZmZmZmZmZmZm Z  ddlݐmZmZmZmZmZmZmZ ddlmZm	Z	m
Z
mZmZ ddlmZmZmZmZ ddlmZmZmZmZmZmZmZ ddlmZmZmZmZmZmZmZ ddlmZmZm Z m!Z!m"Z" ddlm#Z#m$Z$m%Z%m&Z&m'Z'm(Z( ddl m)Z)m*Z*m+Z+ ddlm,Z,m-Z-m.Z. ddlm/Z/m0Z0m1Z1m2Z2 ddlm3Z3m4Z4m5Z5m6Z6m7Z7m8Z8m9Z9m:Z: ddl
m;Z;m<Z<m=Z=m>Z> ddlm?Z?m@Z@mAZAmBZB ddlmCZCmDZDmEZE ddlmFZFmGZGmHZHmIZI ddlmJZJmKZKmLZL dd;lmMZMmNZN ddlmOZOmPZPmQZQmRZRmSZSmTZTmUZUmVZVmWZWmXZXmYZYmZZZm[Z[m\Z\m]Z]m^Z^m_Z_m`Z` ddlmaZambZbmcZc ddlmdZdmeZemfZfmgZgmhZhmiZi ddl"mjZjmkZkmlZlmmZmmnZnmoZompZp ddl$mqZqmrZrmsZsmtZt ddl&muZumvZvmwZw ddl(mxZxmyZymzZzm{Z{m|Z| ddl*m}Z}m~Z~mZ ddl,mZmZmZmZ ddl.mZmZmZmZmZmZmZ ddl0mZmZmZ ddl3mZmZmZ ddl5mZmZmZmZ ddl:mZmZmZ ddl>mZmZmZmZmZmZmZmZ ddl@mZmZmZ ddlBmZmZmZmZ ddlDmZmZmZmZmZmZmZmZmZ dd lFmZmZmZmZ ddlHmZmZmZmZmZmZmZmZmZmZ ddlJmZmZmZmZmZmÐZÐmĐZĐmŐZ dd<lMmƐZƐmǐZ dd=lPmȐZȐmɐZ dd>lVmʐZʐmːZ dd	lXm̐Z̐m͐Z͐mΐZΐmϐZϐmАZАmѐZ dd
l\mҐZҐmӐZӐmԐZԐmՐZ ddl`m֐Z֐mאZאmؐZ ddlbmِZِmڐZڐmېZ ddldmܐZܐmݐZݐmސZސmߐZߐmZmZ dd?lfmZmZ ddlhmZmZmZmZ ddljmZmZmZmZ ddllmZmZmZmZ ddlnmZmZmZmZmZmZmZ dd@lqmZmZ ddltmZmZmZmZmZmZmZ ddlzm Z mZmZmZ ddl|mZmZmZ ddl~mZmZm	Z	m
Z
mZmZmZmZmZmZ ddAlmZmZ ddBlmZ ddlmZmZmZmZmZmZmZmZmZmZ ddlmZmZm Z m!Z!m"Z"m#Z#m$Z$ ddlm%Z%m&Z&m'Z'm(Z(m)Z)m*Z* dd lm+Z+m,Z,m-Z- dd!lm.Z.m/Z/m0Z0m1Z1 dd"lm2Z2m3Z3m4Z4m5Z5m6Z6m7Z7m8Z8m9Z9 dd#lm:Z:m;Z;m<Z<m=Z=m>Z>m?Z?m@Z@ dd$lmAZAmBZBmCZCmDZDmEZEmFZFmGZGmHZHmIZI dd%lmJZJmKZKmLZLmMZMmNZN dd&lmOZOmPZPmQZQ dd'lmRZRmSZSmTZTmUZUmVZVmWZWmXZXmYZYmZZZm[Z[ ddClm\Z\m]Z] dd*lm^Z^m_Z_m`Z`maZambZb dd+lmcZcmdZdmeZemfZfmgZg dd,lmhZhmiZimjZjmkZk dd-lmlZlmmZmmnZnmoZompZp dd.lmqZqmrZrmsZs dd/lmtZtmuZumvZvmwZwmxZxmyZymzZzm{Z{ dd0lm|Z|m}Z}m~Z~mZmZ dd1lmZmZmZmZmZmZmZ dd2lmZmZmZmZmZmZ dd3lmZmZmZ dd4lmZmZmZmZmZ dd5lmZmZmZ dd6lĐmZmZmZ dd7lƐmZmZmZ dd8lɐmZmZmZmZ dd9lϐmZmZmZmZmZ dd:lѐmZmZmZmZ dd;lӐmZmZmZmZmZmZmZ dd<lՐmZmZmZmZ dd=lאmZmZmZmZ dd>lِmZmZmZmZ dd?lېmZmZmZmZmÐZ dd@lݐmĐZĐmŐZŐmƐZ ddAlߐmǐZǐmȐZȐmɐZɐmʐZ ddBlmːZːm̐Z̐m͐Z͐mΐZ ddClmϐZϐmАZАmѐZѐmҐZ ddDlmӐZӐmԐZԐmՐZՐm֐Z ddElmאZאmؐZؐmِZ ddFlmڐZڐmېZېmܐZܐmݐZݐmސZސmߐZ ddGlmZmZmZmZmZ ddHlmZmZmZmZmZ ddIlmZmZmZmZmZ ddJlmZmZmZmZ ddKlmZmZmZmZmZ ddLlmZmZmZmZmZmZ ddDl
mZmZ ddElm Z mZ ddFlmZmZ ddGlmZmZ ddUlmZmZmZm	Z	m
Z
mZmZ ddVlmZmZmZmZ ddWlmZmZmZmZmZmZmZmZmZmZ ddXlmZmZmZmZmZm Z  ddYl!m!Z!m"Z"m#Z# ddZl#m$Z$m%Z%m&Z& dd[l%m'Z'm(Z(m)Z) dd\l'm*Z*m+Z+m,Z,m-Z- dd]l)m.Z.m/Z/m0Z0m1Z1m2Z2 dd^l.m3Z3m4Z4m5Z5 dd_l0m6Z6m7Z7m8Z8m9Z9 dd`l3m:Z:m;Z;m<Z<m=Z=m>Z>m?Z? ddal5m@Z@mAZAmBZBmCZCmDZDmEZEmFZFmGZGmHZHmIZI ddbl7mJZJmKZKmLZL ddHl;mMZMmNZN ddel=mOZOmPZPmQZQmRZRmSZSmTZT ddfl?mUZUmVZVmWZWmXZXmYZYmZZZ ddglAm[Z[m\Z\m]Z]mCZCm^Z^m_Z_ ddhlDm`Z`maZambZbmcZcmdZdmeZemfZfmgZgmhZhmiZi ddilGmjZjmkZkmlZlmmZm ddjlImnZnmoZompZpmqZqmrZr ddklKmsZsmtZtmuZumvZv ddllMmwZwmxZxmyZymzZz ddmlOm{Z{m|Z|m}Z}m~Z~ ddnlRmZmZmZmZmZmZmZ ddolUmZmZmZmZmZmZ ddplWmZmZmZmZmZmZmZ ddqlYmZmZmZmZmZmZmZ ddrl[mZmZmZmZmZ ddsl^mZmZmZmZ ddtlamZmZmZmZmZmZ ddulfmZmZmZmZmZmZ ddvlhmZmZmZmZmZ ddwllmZmZmZmZmZmZmZ ddxlnmZmZmZ ddylpmZmZmZ ddIlrmZmZ dd|lumÐZÐmĐZĐmŐZ dd}lxmƐZƐmǐZǐmȐZȐmɐZɐmʐZʐmːZ dd~l{m̐Z̐m͐Z͐mΐZΐmϐZϐmАZ ddl}mѐZѐmҐZҐmӐZӐmԐZԐmՐZ ddlm֐Z֐mאZאmؐZؐmِZِmڐZ ddlmېZېmܐZܐmݐZ ddlmސZސmߐZߐmZmZmZmZ ddlmZmZmZmZmZmZ ddlmZmZmZmZ ddlmZmZmZ ddlmZmZmZmZmZmZmZmZmZ ddlmZmZmZmZmZ ddlmZ	m 	Z 	m	Z	m	Z	m	Z ddl	m	Z	m	Z	m	Z	m	Z	m	Z ddl	m		Z		m
	Z
	m	Z	m	Z ddl	m	Z	m	Z	m	Z	m	Z ddJl	m	Z	m	Z ddl	m	Z	m	Z	m	Z	m	Z	m	Z ddl	m	Z	m	Z	m	Z ddKl	m	Z	m	Z ddl	m	Z	m	Z	m	Z	m 	Z 	m!	Z!	m"	Z" ddl	m#	Z#	m$	Z$	m%	Z% ddl	m&	Z&	m'	Z'	m(	Z(	m)	Z) ddl	m*	Z*	m+	Z+	m,	Z,	m-	Z-	m.	Z.	m/	Z/ ddl	m0	Z0	m1	Z1	m2	Z2 ddl	m3	Z3	m4	Z4	m5	Z5	m6	Z6	m7	Z7	m8	Z8 ddl	m9	Z9	m:	Z:	m;	Z; ddl	m<	Z<	m=	Z=	m>	Z>	m?	Z? ddlĐ	m@	Z@	mA	ZA	mB	ZB ddlƐ	mC	ZC	mD	ZD	mE	ZE	mF	ZF	mG	ZG	mH	ZH ddlȐ	mI	ZI	mJ	ZJ	mK	ZK ddlʐ	mL	ZL	mM	ZM	mN	ZN	mO	ZO	mP	ZP	mQ	ZQ	mR	ZR	mS	ZS	mT	ZT ddl̐	mU	ZU	mV	ZV	mW	ZW	mX	ZX ddlΐ	mY	ZY	mZ	ZZ	m[	Z[	m\	Z\	m]	Z]	m^	Z^	m_	Z_	m`	Z` ddlѐ	ma	Za	mb	Zb	mc	Zc	md	Zd	me	Ze	mf	Zf	mg	Zg	mh	Zh ddlӐ	mi	Zi	mj	Zj	mk	Zk	ml	Zl	mm	Zm	mn	Zn	mo	Zo	mp	Zp	mq	Zq	mr	Zr ddl֐	ms	Zs	mt	Zt	mu	Zu	mv	Zv	mw	Zw	mx	Zx	my	Zy	mz	Zz	m{	Z{ ddlِ	m|	Z|	m}	Z}	m~	Z~	m	Z	m	Z ddlܐ	m	Z	m	Z	m	Z ddLlސ	m	Z	m	Z ddl	m	Z	m	Z	m	Z	m	Z	m	Z	m	Z	m	Z	m	Z	m	Z	m	Z ddl	m	Z	m	Z	m	Z	m	Z	m	Z	m	Z ddl	m	Z	m	Z	m	Z	m	Z	m	Z ddl	m	Z	m	Z	m	Z ddl	m	Z	m	Z	m	Z	m	Z ddl	m	Z	m	Z	m	Z	m	Z ddl	m	Z	m	Z	m	Z	m	Z	m	Z ddMl	m	Z ddl	m	Z	m	Z	m	Z ddl	m	Z	m	Z	m	Z	m	Z	m	Z	m	Z ddl	m	Z	m	Z	m	Z	m	Z ddl	m	Z	m	Z	m	Z	m	Z	m	Z	m	Z	m	Z ddl	m	Z	m	Z	m	Z	mÐ	ZÐ	mĐ	Z ddl
	mŐ	ZŐ	mƐ	ZƐ	mǐ	Zǐ	mȐ	ZȐ	mɐ	Z ddNl	mʐ	Zʐ	mː	Z ddl	m̐	Z̐	m͐	Z͐	mΐ	Z ddl	mϐ	Zϐ	mА	ZА	mѐ	Zѐ	mҐ	ZҐ	mӐ	Z ddl	mԐ	ZԐ	mՐ	ZՐ	m֐	Z ddl	mא	Zא	mؐ	Zؐ	mِ	Zِ	mڐ	Zڐ	mې	Z ddl	mܐ	Zܐ	mݐ	Zݐ	mސ	Zސ	mߐ	Zߐ	m	Z	m	Z ddl	m	Z	m	Z	m	Z	m	Z	m	Z	m	Z	m	Z	m	Z ddl	m	Z	m	Z	m	Z ddl	m	Z	m	Z	m	Z	m	Z	m	Z	m	Z ddl	m	Z	m	Z	m	Z ddl!	m	Z	m	Z	m	Z ddOl#	m	Z ddPl%	m	Z	m	Z ddĐl(	m	Z	m	Z	m	Z ddŐl+	m	Z
m 
Z 
m
Z
m
Z ddƐl.
m
Z
m
Z
m
Z
m
Z
m
Z
m
Z
m	
Z	 ddǐl0
m

Z

m
Z
m
Z
m
Z
m
Z ddȐl2
m
Z
m
Z
m
Z
m
Z
m
Z
m
Z
m
Z ddQl4
m
Z ddRl7
m
Z
m
Z dd̐l9
m
Z
m
Z
m
Z dd͐l;
m
Z
m
Z
m
Z
m
Z ddΐl=
m 
Z 
m!
Z!
m"
Z"
m#
Z#
m$
Z$
m%
Z%
m&
Z& ddSlB
m'
Z'
m(
Z( ddTlD
m)
Z) ddUlF
m*
Z* ddӐlI
m+
Z+
m,
Z,
m-
Z-
m.
Z.
m/
Z/
m0
Z0
m1
Z1 ddԐlK
m2
Z2
m3
Z3
m4
Z4
m5
Z5 ddՐlM
m6
Z6
m7
Z7
m8
Z8 dd֐lO
m9
Z9
m:
Z:
m;
Z; ddאlQ
m<
Z<
m=
Z=
m>
Z> ddVlS
m?
Z?
m@
Z@ ddWlU
mA
ZA
mB
ZB ddܐlX
mC
ZC
mD
ZD
mE
ZE ddݐlZ
mF
ZF
mG
ZG
mH
ZH
mI
ZI
mJ
ZJ
mK
ZK
mL
ZL
mM
ZM ddސl`
mN
ZN
mO
ZO
mP
ZP
mQ
ZQ
mR
ZR
mS
ZS ddߐlc
mT
ZT
mU
ZU
mV
ZV
mW
ZW
mX
ZX
mY
ZY
mZ
ZZ ddli
m[
Z[
m\
Z\
m]
Z]
m^
Z^
m_
Z_
m`
Z` ddlk
ma
Za
mb
Zb
mc
Zc
md
Zd
me
Ze ddlp
mf
Zf
mg
Zg
mh
Zh
mi
Zi ddlu
mj
Zj
mk
Zk
ml
Zl ddlw
mm
Zm
mn
Zn
mo
Zo
mp
Zp
mq
Zq
mr
Zr
ms
Zs
mt
Zt ddlz
mu
Zu
mv
Zv
mw
Zw
mx
Zx
my
Zy
mz
Zz
m{
Z{
m|
Z| ddl|
m}
Z}
m~
Z~
m
Z
m
Z
m
Z
m
Z
m
Z
m
Z ddl~
m
Z
m
Z
m
Z
m
Z
m
Z
m
Z
m
Z
m
Z
m
Z ddl
m
Z
m
Z
m
Z
m
Z
m
Z
m
Z
m
Z
m
Z ddl
m
Z
m
Z
m
Z ddl
m
Z
m
Z
m
Z
m
Z
m
Z
m
Z
m
Z ddl
m
Z
m
Z
m
Z
m
Z ddXl
m
Z
m
Z dd
l
m
Z
m
Z
m
Z
m
Z
m
Z
m
Z
m
Z
m
Z
m
Z
m
Z
m
Z dd
l
m
Z
m
Z
m
Z ddY
l
m
Z ddZ
l
m
Z dd[
l
m
Z n# e$ r	 dd
lT Y nw xY w	  e            s
 e            	 dd\
l
m
Z dd]
l
m
Z ddle
m
Z
m
Z
mÐ
ZÐ
mĐ
ZĐ
mŐ
ZŐ
mƐ
ZƐ
mǐ
Zǐ
mȐ
ZȐ
mɐ
Zɐ
mʐ
Zʐ
mː
Zː
m̐
Z̐
m͐
Z͐
mΐ
Zΐ
mϐ
Zϐ
mА
Z dd^
lѐ
mҐ
ZҐ
mӐ
Z dd
lԐ
mՐ
ZՐ
m֐
Z֐
mא
Zא
mؐ
Z dd	l
mِ
Zِ
mڐ
Zڐ
mې
Zې
mܐ
Zܐ
mݐ
Zݐ
mސ
Zސ
mߐ
Zߐ
m
Z
m
Z dd_l
m
Z
m
Z
m
Z
m
Z
m
Z
m
Z
m
Z
m
Z
m
Z
m
Z
m
Z
m
Z
m
Z
m
Z
m
Z
m
Z
m
Z
m
Z
m
Z
m
Z
m
Z
m
Z
m
Z
m
Z
m
Z
m
Z
m
Z
m
Z
m
Z
m
Zm Z mZmZmZmZmZmZmZmZm	Z	m
Z
mZmZmZ ddlmZmZmZmZ ddlmZmZmZmZmZmZmZmZmZmZmZ ddlmZmZmZ ddlm Z m!Z!m"Z" ddlŐm#Z#m$Z$m%Z%m&Z&m'Z'm(Z(m)Z) ddlېm*Z*m+Z+m,Z,m-Z-m.Z.m/Z/m0Z0m1Z1 ddlm2Z2m3Z3m4Z4m5Z5 ddlm6Z6m7Z7m8Z8m9Z9m:Z:m;Z;m<Z< ddl
m=Z=m>Z>m?Z? ddlm@Z@mAZAmBZB ddlmCZCmDZDmEZEmFZF ddlmGZGmHZHmIZI ddlmJZJmKZKmLZLmMZM ddlmNZNmOZOmPZPmQZQmRZRmSZS ddl"mTZTmUZUmVZVmWZWmXZXmYZYmZZZ ddl(m[Z[m\Z\m]Z]m^Z^m_Z_ ddl,m`Z`maZambZbmcZc ddlXmdZdmeZemfZfmgZgmhZhmiZi ddlnmjZjmkZkmlZlmmZmmnZnmoZompZpmqZq ddltmrZrmsZsmtZtmuZumvZvmwZw ddl~mxZxmyZymzZzm{Z{m|Z|m}Z}m~Z~mZ dd`lmZ dd!lmZmZmZmZmZ dd"lmZmZmZmZmZmZmZ dd#lmZmZmZmZmZmZmZmZmZ dd$lmZmZmZmZmZmZ dd%lmZmZmZmZmZ dd&lɐmZmZmZmZ dd'lѐmZmZmZ dd(lՐmZmZmZ dd)lmZmZmZmZmZmZmZ dd*lmZmZmZmZmZ dd+lmZmZmZ dd,lmZmZmZmZmZmZmZ dd-lmZmZmÐZÐmĐZĐmŐZ dd.l'mƐZƐmǐZǐmȐZ dd/l3mɐZɐmʐZʐmːZ dd0l=m̐Z̐m͐Z͐mΐZΐmϐZ dd1lDmАZАmѐZѐmҐZҐmӐZӐmԐZԐmՐZՐm֐Z֐mאZאmؐZؐmِZ dd2lKmڐZڐmېZېmܐZܐmݐZ dd3lRmސZސmߐZߐmZmZmZmZmZmZ dd4lYmZmZmZ dd5lxmZmZmZmZmZmZ dd6l{mZmZmZ dd7lmZmZmZ dd8lmZmZmZmZ dd9lȐmZmZmZ dd:lʐmZmZmZmZm Z mZmZmZ dd;l̐mZmZmZ dd<lΐmZmZm	Z	m
Z
mZmZmZmZmZ dd=lѐmZmZmZmZmZmZmZmZmZ dd>l֐mZmZmZmZmZmZmZm Z  ddalސm!Z!m"Z" ddAlm#Z#m$Z$m%Z%m&Z&m'Z' ddBlm(Z(m)Z)m*Z* ddClm+Z+m,Z,m-Z- ddDlm.Z.m/Z/m0Z0m1Z1 ddElm2Z2m3Z3m4Z4m5Z5 ddFlm6Z6m7Z7m8Z8m9Z9m:Z: ddblDm;Z; ddclFm<Z< ddIlKm=Z=m>Z>m?Z? ddJlMm@Z@mAZAmBZB ddKlZmCZCmDZDmEZEmFZF ddLlkmGZGmHZHmIZI ddMlumJZJmKZKmLZL ddNlwmMZMmNZNmOZOmPZPmQZQmRZRmSZSmTZT ddOlzmUZUmVZVmWZWmXZXmYZYmZZZm[Z[m\Z\ ddPl~m]Z]m^Z^m_Z_m`Z`maZambZbmcZcmdZd ddQlemfZfmgZgmhZhmiZi n# e$ r	 ddljT Y nw xY w	  e            r( e	            r e            r e            r
 e            s
 e            	 dddlmkZkmlZlmmZm n# e$ r	 ddlnT Y nw xY w	  e            s
 e            	 ddel^moZompZp n# e$ r	 ddlqT Y nw xY w	  e
            s
 e            	 ddflemrZrmsZsmtZtmuZumvZvmwZwmxZxmyZymzZzm{Z{m|Z|m}Z}m~Z~mZ ddglmZ ddflmZmZmZmZmZmZmZmZ ddglmZmZmZmZmZmZmZmZmZmZmZmZmZmZmZmZmZmZmZmZmZmZmZmZmZmZmZ ddhlmZmZmZmZmZmZmZ ddilmZmZmZmZ ddjlmZmZmZmZmZmZmZmZmZmZ ddklmZmZmZmZmZmZmZmZmZ ddllmÐZÐmĐZĐmŐZ ddmlmƐZƐmǐZǐmȐZ ddnlϐmɐZɐmʐZʐmːZ ddhlm̐Z̐m͐Z͐mΐZΐmϐZϐmАZАmѐZѐmҐZ ddillmӐZӐmԐZԐmՐZ ddqlnm֐Z֐mאZאmؐZؐmِZِmڐZڐmېZېmܐZ ddrl~mݐZݐmސZސmߐZߐmZmZmZmZmZmZ ddjlmZ ddxlmZmZmZ ddtlmZmZmZ ddulmZmZmZ ddvlmZmZmZ ddwlmZmZmZ ddylmZmZmZ ddzl'mZmZmZ dd{l3mZmZmZmZm Z  dd|l=mZmZmZ dd}lYmZmZmZ dd~l{mZmZm	Z	 ddlm
Z
mZmZ ddlȐmZmZmZ ddl̐mZmZmZ ddlΐmZmZmZmZmZmZmZmZ ddlѐmZmZmZmZmZm Z m!Z!m"Z" ddl֐m#Z#m$Z$m%Z%m&Z&m'Z'm(Z(m)Z) ddklm*Z* ddlm+Z+m,Z,m-Z-m.Z. ddllDm/Z/ ddmlFm0Z0 ddlKm1Z1m2Z2m3Z3 ddlZm4Z4m5Z5m6Z6m7Z7 ddnlkm8Z8m9Z9m:Z:m;Z; ddlum<Z<m=Z=m>Z> ddolzm?Z?m@Z@mAZAmBZBmCZCmDZDmEZEmFZF nG# e$ r	 ddlGT Y n:w xY wddplHZH ee eI            dq         eeJdre is          eHjK        e<    e            s. e            s' e
            s eL                    dt           dpS dpS dpS dpS (u  z4.46.0    )TYPE_CHECKING   )dependency_versions_check)OptionalDependencyNotAvailable_LazyModuleis_bitsandbytes_availableis_essentia_availableis_flax_availableis_g2p_en_availableis_keras_nlp_availableis_librosa_availableis_pretty_midi_availableis_scipy_availableis_sentencepiece_availableis_speech_availableis_tensorflow_text_availableis_tf_availableis_timm_availableis_tokenizers_availableis_torch_availableis_torchaudio_availableis_torchvision_availableis_vision_availableloggingagents)Agent	CodeAgentHfApiEngineManagedAgentPipelineTool
ReactAgentReactCodeAgentReactJsonAgentToolToolboxToolCollectionTransformersEnginelaunch_gradio_demo	load_toolstream_to_gradiotoolaudio_utils	benchmarkcommandsconfiguration_utilsPretrainedConfigconvert_graph_to_onnx+convert_slow_tokenizers_checkpoints_to_fast)convert_tf_hub_seq_to_seq_bert_to_pytorchdata)DataProcessorInputExampleInputFeatures%SingleSentenceClassificationProcessorSquadExampleSquadFeaturesSquadV1ProcessorSquadV2Processorglue_compute_metrics!glue_convert_examples_to_featuresglue_output_modesglue_processorsglue_tasks_num_labels"squad_convert_examples_to_featuresxnli_compute_metricsxnli_output_modesxnli_processorsxnli_tasks_num_labelszdata.data_collator)DataCollatorDataCollatorForLanguageModeling*DataCollatorForPermutationLanguageModelingDataCollatorForSeq2SeqDataCollatorForSOP"DataCollatorForTokenClassificationDataCollatorForWholeWordMaskDataCollatorWithFlatteningDataCollatorWithPaddingDefaultDataCollatordefault_data_collatorzdata.metricszdata.processorsdebug_utilsr   dependency_versions_tabledynamic_module_utils!feature_extraction_sequence_utilsSequenceFeatureExtractorfeature_extraction_utilsBatchFeatureFeatureExtractionMixin
file_utils
generation)GenerationConfigTextIteratorStreamerTextStreamerWatermarkingConfighf_argparserHfArgumentParserhyperparameter_searchimage_transformsintegrations)
is_clearml_availableis_comet_availableis_dvclive_availableis_neptune_availableis_optuna_availableis_ray_availableis_ray_tune_availableis_sigopt_availableis_tensorboard_availableis_wandb_availableloss	modelcard	ModelCardmodeling_tf_pytorch_utils)(convert_tf_weight_name_to_pt_weight_name$load_pytorch_checkpoint_in_tf2_modelload_pytorch_model_in_tf2_model!load_pytorch_weights_in_tf2_model$load_tf2_checkpoint_in_pytorch_modelload_tf2_model_in_pytorch_model!load_tf2_weights_in_pytorch_modelmodelszmodels.albertAlbertConfigzmodels.align)AlignConfigAlignProcessorAlignTextConfigAlignVisionConfigzmodels.altclip)AltCLIPConfigAltCLIPProcessorAltCLIPTextConfigAltCLIPVisionConfigz$models.audio_spectrogram_transformer	ASTConfigASTFeatureExtractorzmodels.auto)CONFIG_MAPPINGFEATURE_EXTRACTOR_MAPPINGIMAGE_PROCESSOR_MAPPINGMODEL_NAMES_MAPPINGPROCESSOR_MAPPINGTOKENIZER_MAPPING
AutoConfigAutoFeatureExtractorAutoImageProcessorAutoProcessorAutoTokenizerzmodels.autoformerAutoformerConfigzmodels.bark)BarkCoarseConfig
BarkConfigBarkFineConfigBarkProcessorBarkSemanticConfigzmodels.bart
BartConfigBartTokenizerzmodels.barthezzmodels.bartphozmodels.beit
BeitConfigzmodels.bert)BasicTokenizer
BertConfigBertTokenizerWordpieceTokenizerzmodels.bert_generationBertGenerationConfigzmodels.bert_japanese)BertJapaneseTokenizerCharacterTokenizerMecabTokenizerzmodels.bertweetBertweetTokenizerzmodels.big_birdBigBirdConfigzmodels.bigbird_pegasusBigBirdPegasusConfigzmodels.biogptBioGptConfigBioGptTokenizerz
models.bit	BitConfigzmodels.blenderbotBlenderbotConfigBlenderbotTokenizerzmodels.blenderbot_smallBlenderbotSmallConfigBlenderbotSmallTokenizerzmodels.blip)
BlipConfigBlipProcessorBlipTextConfigBlipVisionConfigzmodels.blip_2)Blip2ConfigBlip2ProcessorBlip2QFormerConfigBlip2VisionConfigzmodels.bloomBloomConfigzmodels.bridgetower)BridgeTowerConfigBridgeTowerProcessorBridgeTowerTextConfigBridgeTowerVisionConfigzmodels.bros
BrosConfigBrosProcessorzmodels.byt5ByT5Tokenizerzmodels.camembertCamembertConfigzmodels.canineCanineConfigCanineTokenizerzmodels.chameleon)ChameleonConfigChameleonProcessorChameleonVQVAEConfigzmodels.chinese_clip)ChineseCLIPConfigChineseCLIPProcessorChineseCLIPTextConfigChineseCLIPVisionConfigzmodels.clap)ClapAudioConfig
ClapConfigClapProcessorClapTextConfigzmodels.clip)
CLIPConfigCLIPProcessorCLIPTextConfigCLIPTokenizerCLIPVisionConfigzmodels.clipseg)CLIPSegConfigCLIPSegProcessorCLIPSegTextConfigCLIPSegVisionConfigzmodels.clvp)
ClvpConfigClvpDecoderConfigClvpEncoderConfigClvpFeatureExtractorClvpProcessorClvpTokenizerzmodels.code_llamazmodels.codegenCodeGenConfigCodeGenTokenizerzmodels.cohereCohereConfigzmodels.conditional_detrConditionalDetrConfigzmodels.convbertConvBertConfigConvBertTokenizerzmodels.convnextConvNextConfigzmodels.convnextv2ConvNextV2Configz
models.cpmzmodels.cpmantCpmAntConfigCpmAntTokenizerzmodels.ctrl
CTRLConfigCTRLTokenizerz
models.cvt	CvtConfigz
models.dac	DacConfigDacFeatureExtractorzmodels.data2vec)Data2VecAudioConfigData2VecTextConfigData2VecVisionConfigzmodels.dbrx
DbrxConfigzmodels.debertaDebertaConfigDebertaTokenizerzmodels.deberta_v2DebertaV2Configzmodels.decision_transformerDecisionTransformerConfigzmodels.deformable_detrDeformableDetrConfigzmodels.deit
DeiTConfigzmodels.deprecatedzmodels.deprecated.bortzmodels.deprecated.deta
DetaConfigz!models.deprecated.efficientformerEfficientFormerConfigzmodels.deprecated.ernie_mErnieMConfigz!models.deprecated.gptsan_japaneseGPTSanJapaneseConfigGPTSanJapaneseTokenizerzmodels.deprecated.graphormerGraphormerConfigzmodels.deprecated.jukebox)JukeboxConfigJukeboxPriorConfigJukeboxTokenizerJukeboxVQVAEConfigzmodels.deprecated.mctct)MCTCTConfigMCTCTFeatureExtractorMCTCTProcessorzmodels.deprecated.mega
MegaConfigzmodels.deprecated.mmbt
MMBTConfigzmodels.deprecated.nat	NatConfigzmodels.deprecated.nezhaNezhaConfigzmodels.deprecated.open_llamaOpenLlamaConfigzmodels.deprecated.qdqbertQDQBertConfigzmodels.deprecated.realmRealmConfigRealmTokenizerzmodels.deprecated.retribertRetriBertConfigRetriBertTokenizerz"models.deprecated.speech_to_text_2)Speech2Text2ConfigSpeech2Text2ProcessorSpeech2Text2Tokenizerzmodels.deprecated.tapexTapexTokenizerz(models.deprecated.trajectory_transformerTrajectoryTransformerConfigzmodels.deprecated.transfo_xl)TransfoXLConfigTransfoXLCorpusTransfoXLTokenizerzmodels.deprecated.tvlt)
TvltConfigTvltFeatureExtractorTvltProcessorzmodels.deprecated.van	VanConfigzmodels.deprecated.vit_hybridViTHybridConfigz models.deprecated.xlm_prophetnetXLMProphetNetConfigzmodels.depth_anythingDepthAnythingConfigzmodels.detr
DetrConfigzmodels.dialogptzmodels.dinatDinatConfigzmodels.dinov2Dinov2Configzmodels.distilbertDistilBertConfigDistilBertTokenizerz
models.ditzmodels.donutDonutProcessorDonutSwinConfigz
models.dpr)	DPRConfigDPRContextEncoderTokenizerDPRQuestionEncoderTokenizerDPRReaderOutputDPRReaderTokenizerz
models.dpt	DPTConfigzmodels.efficientnetEfficientNetConfigzmodels.electraElectraConfigElectraTokenizerzmodels.encodecEncodecConfigEncodecFeatureExtractorzmodels.encoder_decoderEncoderDecoderConfigzmodels.ernieErnieConfigz
models.esm	EsmConfigEsmTokenizerzmodels.falconFalconConfigzmodels.falcon_mambaFalconMambaConfigzmodels.fastspeech2_conformer)FastSpeech2ConformerConfig!FastSpeech2ConformerHifiGanConfigFastSpeech2ConformerTokenizer%FastSpeech2ConformerWithHifiGanConfigzmodels.flaubertFlaubertConfigFlaubertTokenizerzmodels.flava)FlavaConfigFlavaImageCodebookConfigFlavaImageConfigFlavaMultimodalConfigFlavaTextConfigzmodels.fnet
FNetConfigzmodels.focalnetFocalNetConfigzmodels.fsmt
FSMTConfigFSMTTokenizerzmodels.funnelFunnelConfigFunnelTokenizerzmodels.fuyu
FuyuConfigzmodels.gemmaGemmaConfigzmodels.gemma2Gemma2Configz
models.git)	GitConfigGitProcessorGitVisionConfigz
models.glm	GlmConfigzmodels.glpn
GLPNConfigzmodels.gpt2
GPT2ConfigGPT2Tokenizerzmodels.gpt_bigcodeGPTBigCodeConfigzmodels.gpt_neoGPTNeoConfigzmodels.gpt_neoxGPTNeoXConfigzmodels.gpt_neox_japaneseGPTNeoXJapaneseConfigzmodels.gpt_sw3zmodels.gptj
GPTJConfigzmodels.graniteGraniteConfigzmodels.granitemoeGraniteMoeConfigzmodels.grounding_dinoGroundingDinoConfigGroundingDinoProcessorzmodels.groupvit)GroupViTConfigGroupViTTextConfigGroupViTVisionConfigzmodels.herbertHerbertTokenizerzmodels.hieraHieraConfigzmodels.hubertHubertConfigzmodels.ibertIBertConfigzmodels.ideficsIdeficsConfigzmodels.idefics2Idefics2Configzmodels.idefics3Idefics3Configzmodels.imagegptImageGPTConfigzmodels.informerInformerConfigzmodels.instructblip)InstructBlipConfigInstructBlipProcessorInstructBlipQFormerConfigInstructBlipVisionConfigzmodels.instructblipvideo)InstructBlipVideoConfigInstructBlipVideoProcessorInstructBlipVideoQFormerConfigInstructBlipVideoVisionConfigzmodels.jambaJambaConfigzmodels.jetmoeJetMoeConfigzmodels.kosmos2Kosmos2ConfigKosmos2Processorzmodels.layoutlmLayoutLMConfigLayoutLMTokenizerzmodels.layoutlmv2)LayoutLMv2ConfigLayoutLMv2FeatureExtractorLayoutLMv2ImageProcessorLayoutLMv2ProcessorLayoutLMv2Tokenizerzmodels.layoutlmv3)LayoutLMv3ConfigLayoutLMv3FeatureExtractorLayoutLMv3ImageProcessorLayoutLMv3ProcessorLayoutLMv3Tokenizerzmodels.layoutxlmLayoutXLMProcessorz
models.led	LEDConfigLEDTokenizerzmodels.levitLevitConfigzmodels.lilt
LiltConfigzmodels.llamaLlamaConfigzmodels.llavaLlavaConfigLlavaProcessorzmodels.llava_nextLlavaNextConfigLlavaNextProcessorzmodels.llava_next_videoLlavaNextVideoConfigLlavaNextVideoProcessorzmodels.llava_onevisionLlavaOnevisionConfigLlavaOnevisionProcessorzmodels.longformerLongformerConfigLongformerTokenizerzmodels.longt5LongT5Configzmodels.luke
LukeConfigLukeTokenizerzmodels.lxmertLxmertConfigLxmertTokenizerzmodels.m2m_100M2M100Configzmodels.mambaMambaConfigzmodels.mamba2Mamba2Configzmodels.marianMarianConfigzmodels.markuplm)MarkupLMConfigMarkupLMFeatureExtractorMarkupLMProcessorMarkupLMTokenizerzmodels.mask2formerMask2FormerConfigzmodels.maskformerMaskFormerConfigMaskFormerSwinConfigzmodels.mbartMBartConfigzmodels.mbart50zmodels.megatron_bertMegatronBertConfigzmodels.megatron_gpt2zmodels.mgp_str)MgpstrConfigMgpstrProcessorMgpstrTokenizerzmodels.mimi
MimiConfigzmodels.mistralMistralConfigzmodels.mixtralMixtralConfigzmodels.mllamaMllamaConfigMllamaProcessorzmodels.mlukezmodels.mobilebertMobileBertConfigMobileBertTokenizerzmodels.mobilenet_v1MobileNetV1Configzmodels.mobilenet_v2MobileNetV2Configzmodels.mobilevitMobileViTConfigzmodels.mobilevitv2MobileViTV2Configzmodels.moshiMoshiConfigMoshiDepthConfigzmodels.mpnetMPNetConfigMPNetTokenizerz
models.mpt	MptConfigz
models.mra	MraConfigz
models.mt5	MT5Configzmodels.musicgenMusicgenConfigMusicgenDecoderConfigzmodels.musicgen_melodyMusicgenMelodyConfigMusicgenMelodyDecoderConfigz
models.mvp	MvpConfigMvpTokenizerzmodels.myt5MyT5Tokenizerzmodels.nemotronNemotronConfigzmodels.nllbzmodels.nllb_moeNllbMoeConfigzmodels.nougatNougatProcessorzmodels.nystromformerNystromformerConfigzmodels.olmo
OlmoConfigzmodels.olmoeOlmoeConfigzmodels.omdet_turboOmDetTurboConfigOmDetTurboProcessorzmodels.oneformerOneFormerConfigOneFormerProcessorzmodels.openaiOpenAIGPTConfigOpenAIGPTTokenizerz
models.opt	OPTConfigzmodels.owlv2)Owlv2ConfigOwlv2ProcessorOwlv2TextConfigOwlv2VisionConfigzmodels.owlvit)OwlViTConfigOwlViTProcessorOwlViTTextConfigOwlViTVisionConfigzmodels.paligemmaPaliGemmaConfigzmodels.patchtsmixerPatchTSMixerConfigzmodels.patchtstPatchTSTConfigzmodels.pegasusPegasusConfigPegasusTokenizerzmodels.pegasus_xPegasusXConfigzmodels.perceiverPerceiverConfigPerceiverTokenizerzmodels.persimmonPersimmonConfigz
models.phi	PhiConfigzmodels.phi3
Phi3Configzmodels.phimoePhimoeConfigzmodels.phobertPhobertTokenizerzmodels.pix2struct)Pix2StructConfigPix2StructProcessorPix2StructTextConfigPix2StructVisionConfigzmodels.pixtralPixtralProcessorPixtralVisionConfigzmodels.plbartPLBartConfigzmodels.poolformerPoolFormerConfigzmodels.pop2pianoPop2PianoConfigzmodels.prophetnetProphetNetConfigProphetNetTokenizerz
models.pvt	PvtConfigzmodels.pvt_v2PvtV2Configzmodels.qwen2Qwen2ConfigQwen2Tokenizerzmodels.qwen2_audio)Qwen2AudioConfigQwen2AudioEncoderConfigQwen2AudioProcessorzmodels.qwen2_moeQwen2MoeConfigzmodels.qwen2_vlQwen2VLConfigQwen2VLProcessorz
models.rag)	RagConfigRagRetrieverRagTokenizerzmodels.recurrent_gemmaRecurrentGemmaConfigzmodels.reformerReformerConfigzmodels.regnetRegNetConfigzmodels.rembertRemBertConfigzmodels.resnetResNetConfigzmodels.robertaRobertaConfigRobertaTokenizerzmodels.roberta_prelayernormRobertaPreLayerNormConfigzmodels.roc_bertRoCBertConfigRoCBertTokenizerzmodels.roformerRoFormerConfigRoFormerTokenizerzmodels.rt_detrRTDetrConfigRTDetrResNetConfigzmodels.rwkv
RwkvConfigz
models.sam)	SamConfigSamMaskDecoderConfigSamProcessorSamPromptEncoderConfigSamVisionConfigzmodels.seamless_m4t)SeamlessM4TConfigSeamlessM4TFeatureExtractorSeamlessM4TProcessorzmodels.seamless_m4t_v2SeamlessM4Tv2Configzmodels.segformerSegformerConfigzmodels.seggptSegGptConfigz
models.sew	SEWConfigzmodels.sew_d
SEWDConfigzmodels.siglip)SiglipConfigSiglipProcessorSiglipTextConfigSiglipVisionConfigzmodels.speech_encoder_decoderSpeechEncoderDecoderConfigzmodels.speech_to_text)Speech2TextConfigSpeech2TextFeatureExtractorSpeech2TextProcessorzmodels.speecht5)SpeechT5ConfigSpeechT5FeatureExtractorSpeechT5HifiGanConfigSpeechT5Processorzmodels.splinterSplinterConfigSplinterTokenizerzmodels.squeezebertSqueezeBertConfigSqueezeBertTokenizerzmodels.stablelmStableLmConfigzmodels.starcoder2Starcoder2Configzmodels.superpointSuperPointConfigzmodels.swiftformerSwiftFormerConfigzmodels.swin
SwinConfigzmodels.swin2srSwin2SRConfigzmodels.swinv2Swinv2Configzmodels.switch_transformersSwitchTransformersConfigz	models.t5T5Configzmodels.table_transformerTableTransformerConfigzmodels.tapasTapasConfigTapasTokenizerzmodels.time_series_transformerTimeSeriesTransformerConfigzmodels.timesformerTimesformerConfigzmodels.timm_backboneTimmBackboneConfigzmodels.trocrTrOCRConfigTrOCRProcessorz
models.tvp	TvpConfigTvpProcessorzmodels.udop
UdopConfigUdopProcessorzmodels.umt5
UMT5Configzmodels.unispeechUniSpeechConfigzmodels.unispeech_satUniSpeechSatConfigzmodels.univnetUnivNetConfigUnivNetFeatureExtractorzmodels.upernetUperNetConfigzmodels.video_llavaVideoLlavaConfigzmodels.videomaeVideoMAEConfigzmodels.vilt)
ViltConfigViltFeatureExtractorViltImageProcessorViltProcessorzmodels.vipllavaVipLlavaConfigzmodels.vision_encoder_decoderVisionEncoderDecoderConfigzmodels.vision_text_dual_encoderVisionTextDualEncoderConfigVisionTextDualEncoderProcessorzmodels.visual_bertVisualBertConfigz
models.vit	ViTConfigzmodels.vit_maeViTMAEConfigzmodels.vit_msnViTMSNConfigzmodels.vitdetVitDetConfigzmodels.vitmatteVitMatteConfigzmodels.vits
VitsConfigVitsTokenizerzmodels.vivitVivitConfigzmodels.wav2vec2)Wav2Vec2ConfigWav2Vec2CTCTokenizerWav2Vec2FeatureExtractorWav2Vec2ProcessorWav2Vec2Tokenizerzmodels.wav2vec2_bertWav2Vec2BertConfigWav2Vec2BertProcessorzmodels.wav2vec2_conformerWav2Vec2ConformerConfigzmodels.wav2vec2_phonemeWav2Vec2PhonemeCTCTokenizerzmodels.wav2vec2_with_lmWav2Vec2ProcessorWithLMzmodels.wavlmWavLMConfigzmodels.whisper)WhisperConfigWhisperFeatureExtractorWhisperProcessorWhisperTokenizerzmodels.x_clip)XCLIPConfigXCLIPProcessorXCLIPTextConfigXCLIPVisionConfigzmodels.xglm
XGLMConfigz
models.xlm	XLMConfigXLMTokenizerzmodels.xlm_robertaXLMRobertaConfigzmodels.xlm_roberta_xlXLMRobertaXLConfigzmodels.xlnetXLNetConfigzmodels.xmod
XmodConfigzmodels.yolosYolosConfigzmodels.yoso
YosoConfigzmodels.zambaZambaConfigzmodels.zoedepthZoeDepthConfigonnx	pipelines)#AudioClassificationPipeline"AutomaticSpeechRecognitionPipelineCsvPipelineDataFormatDepthEstimationPipeline!DocumentQuestionAnsweringPipelineFeatureExtractionPipelineFillMaskPipelineImageClassificationPipelineImageFeatureExtractionPipelineImageSegmentationPipelineImageToImagePipelineImageToTextPipelineJsonPipelineDataFormatMaskGenerationPipelineNerPipelineObjectDetectionPipelinePipedPipelineDataFormatPipelinePipelineDataFormatQuestionAnsweringPipelineSummarizationPipelineTableQuestionAnsweringPipelineText2TextGenerationPipelineTextClassificationPipelineTextGenerationPipelineTextToAudioPipelineTokenClassificationPipelineTranslationPipelineVideoClassificationPipelineVisualQuestionAnsweringPipeline#ZeroShotAudioClassificationPipelineZeroShotClassificationPipeline#ZeroShotImageClassificationPipelineZeroShotObjectDetectionPipelinepipelineprocessing_utilsProcessorMixin
quantizerstesting_utilstokenization_utilsPreTrainedTokenizertokenization_utils_base)
AddedTokenBatchEncodingCharSpanPreTrainedTokenizerBaseSpecialTokensMixin	TokenSpantrainer_callback)DefaultFlowCallbackEarlyStoppingCallbackPrinterCallbackProgressCallbackTrainerCallbackTrainerControlTrainerStatetrainer_utils)EvalPredictionIntervalStrategySchedulerTypeenable_full_determinismset_seedtraining_argsTrainingArgumentstraining_args_seq2seqSeq2SeqTrainingArgumentstraining_args_tfTFTrainingArgumentsutils),CONFIG_NAMEMODEL_CARD_NAMEPYTORCH_PRETRAINED_BERT_CACHEPYTORCH_TRANSFORMERS_CACHESPIECE_UNDERLINETF2_WEIGHTS_NAMETF_WEIGHTS_NAMETRANSFORMERS_CACHEWEIGHTS_NAME
TensorTypeadd_end_docstringsadd_start_docstringsis_apex_availableis_av_availabler   is_datasets_availableis_faiss_availabler
   r   is_phonemizer_availableis_psutil_availableis_py3nvml_availableis_pyctcdecode_availableis_sacremoses_availableis_safetensors_availabler   r   is_sklearn_availabler   r   r   r   r   r   is_torch_mlu_availableis_torch_musa_availableis_torch_neuroncore_availableis_torch_npu_availableis_torch_tpu_availabler   is_torch_xla_availableis_torch_xpu_availabler   r   zutils.quantization_config)
AqlmConfig	AwqConfigBitNetConfigBitsAndBytesConfigCompressedTensorsConfig
EetqConfigFbgemmFp8Config
GPTQConfig	HqqConfigQuantoConfigTorchAoConfigAlbertTokenizerBarthezTokenizerBartphoTokenizerBertGenerationTokenizerBigBirdTokenizerCamembertTokenizerCodeLlamaTokenizerCpmTokenizerDebertaV2TokenizerErnieMTokenizerXLMProphetNetTokenizerFNetTokenizerGemmaTokenizerGPTSw3TokenizerLayoutXLMTokenizerLlamaTokenizerM2M100TokenizerMarianTokenizerMBartTokenizerMBart50TokenizerMLukeTokenizerMT5TokenizerNllbTokenizerPLBartTokenizerReformerTokenizerRemBertTokenizerSeamlessM4TTokenizerSiglipTokenizerSpeech2TextTokenizerSpeechT5TokenizerT5TokenizerUdopTokenizerXGLMTokenizerXLMRobertaTokenizerXLNetTokenizer)dummy_sentencepiece_objectsc                 <    g | ]}|                     d           |S _
startswith.0names     Q/var/www/html/ai-engine/env/lib/python3.11/site-packages/transformers/__init__.py
<listcomp>r    s:     > > >QTAUAU>> > >    z!utils.dummy_sentencepiece_objectsAlbertTokenizerFastBartTokenizerFastBarthezTokenizerFastBertTokenizerFastBigBirdTokenizerFastBlenderbotTokenizerFastBlenderbotSmallTokenizerFastBloomTokenizerFastCamembertTokenizerFastCLIPTokenizerFastCodeLlamaTokenizerFastCodeGenTokenizerFastCohereTokenizerFastConvBertTokenizerFastCpmTokenizerFastDebertaTokenizerFastDebertaV2TokenizerFastRealmTokenizerFastRetriBertTokenizerFastDistilBertTokenizerFast)DPRContextEncoderTokenizerFastDPRQuestionEncoderTokenizerFastDPRReaderTokenizerFastElectraTokenizerFastFNetTokenizerFastFunnelTokenizerFastGemmaTokenizerFastGPT2TokenizerFastGPTNeoXTokenizerFastGPTNeoXJapaneseTokenizerHerbertTokenizerFastLayoutLMTokenizerFastLayoutLMv2TokenizerFastLayoutLMv3TokenizerFastLayoutXLMTokenizerFastLEDTokenizerFastLlamaTokenizerFastLongformerTokenizerFastLxmertTokenizerFastMarkupLMTokenizerFastMBartTokenizerFastMBart50TokenizerFastMobileBertTokenizerFastMPNetTokenizerFastMT5TokenizerFastMvpTokenizerFastNllbTokenizerFastNougatTokenizerFastOpenAIGPTTokenizerFastPegasusTokenizerFastQwen2TokenizerFastReformerTokenizerFastRemBertTokenizerFastRobertaTokenizerFastRoFormerTokenizerFastSeamlessM4TTokenizerFastSplinterTokenizerFastSqueezeBertTokenizerFastT5TokenizerFastUdopTokenizerFastWhisperTokenizerFastXGLMTokenizerFastXLMRobertaTokenizerFastXLNetTokenizerFastPreTrainedTokenizerFasttokenization_utils_fast)dummy_tokenizers_objectsc                 <    g | ]}|                     d           |S r  r  r  s     r  r  r    9     ; ; ;dooc>R>R;; ; ;r  zutils.dummy_tokenizers_objectsSLOW_TO_FAST_CONVERTERSconvert_slow_tokenizer)*dummy_sentencepiece_and_tokenizers_objectsc                 <    g | ]}|                     d           |S r  r  r  s     r  r  r  f  sD     M M MPTP_P_`cPdPdMM M Mr  z0utils.dummy_sentencepiece_and_tokenizers_objectsTFBertTokenizer)dummy_tensorflow_text_objectsc                 <    g | ]}|                     d           |S r  r  r  s     r  r  r  v  sA     @ @ @4??SVCWCW@@ @ @r  z#utils.dummy_tensorflow_text_objectsTFGPT2Tokenizer)dummy_keras_nlp_objectsc                 <    g | ]}|                     d           |S r  r  r  s     r  r  r    s9     : : :T__S=Q=Q:: : :r  zutils.dummy_keras_nlp_objectsImageProcessingMixinimage_processing_baseBaseImageProcessorimage_processing_utilsImageFeatureExtractionMixinimage_utilsBeitFeatureExtractorBeitImageProcessorBitImageProcessorBlipImageProcessorBridgeTowerImageProcessorChameleonImageProcessorChineseCLIPFeatureExtractorChineseCLIPImageProcessorCLIPFeatureExtractorCLIPImageProcessorConditionalDetrFeatureExtractorConditionalDetrImageProcessorConvNextFeatureExtractorConvNextImageProcessorDeformableDetrFeatureExtractorDeformableDetrImageProcessorDeiTFeatureExtractorDeiTImageProcessorDetaImageProcessorEfficientFormerImageProcessorTvltImageProcessorViTHybridImageProcessor)DetrFeatureExtractorDetrImageProcessorDetrImageProcessorFastDonutFeatureExtractorDonutImageProcessorDPTFeatureExtractorDPTImageProcessorEfficientNetImageProcessor)FlavaFeatureExtractorFlavaImageProcessorFlavaProcessorFuyuImageProcessorFuyuProcessorGLPNFeatureExtractorGLPNImageProcessorGroundingDinoImageProcessorIdeficsImageProcessorIdefics2ImageProcessorIdefics3ImageProcessorImageGPTFeatureExtractorImageGPTImageProcessorInstructBlipVideoImageProcessorro  rp  rt  ru  LevitFeatureExtractorLevitImageProcessorLlavaNextImageProcessorLlavaNextVideoImageProcessorLlavaOnevisionImageProcessorLlavaOnevisionVideoProcessorMask2FormerImageProcessorMaskFormerFeatureExtractorMaskFormerImageProcessorMllamaImageProcessorMobileNetV1FeatureExtractorMobileNetV1ImageProcessorMobileNetV2FeatureExtractorMobileNetV2ImageProcessorMobileViTFeatureExtractorMobileViTImageProcessorNougatImageProcessorOneFormerImageProcessorOwlv2ImageProcessorOwlViTFeatureExtractorOwlViTImageProcessorPerceiverFeatureExtractorPerceiverImageProcessorPix2StructImageProcessorPixtralImageProcessorPoolFormerFeatureExtractorPoolFormerImageProcessorPvtImageProcessorQwen2VLImageProcessorRTDetrImageProcessorSamImageProcessorSegformerFeatureExtractorSegformerImageProcessorSegGptImageProcessorSiglipImageProcessorSuperPointImageProcessorSwin2SRImageProcessorTvpImageProcessorVideoLlavaImageProcessorVideoMAEFeatureExtractorVideoMAEImageProcessor)r:  r;  r<  ViTFeatureExtractorViTImageProcessorVitMatteImageProcessorVivitImageProcessorYolosFeatureExtractorYolosImageProcessorZoeDepthImageProcessor)dummy_vision_objectsc                 <    g | ]}|                     d           |S r  r  r  s     r  r  r    s9     7 7 7$//#:N:N77 7 7r  zutils.dummy_vision_objectsBaseImageProcessorFastimage_processing_utils_fastViTImageProcessorFast)dummy_torchvision_objectsc                 <    g | ]}|                     d           |S r  r  r  s     r  r  r    s9     < < <ts?S?S<< < <r  zutils.dummy_torchvision_objectsactivationsPyTorchBenchmarkzbenchmark.benchmarkPyTorchBenchmarkArgumentszbenchmark.benchmark_args)CacheCacheConfigDynamicCacheEncoderDecoderCacheHQQQuantizedCacheHybridCache
MambaCacheOffloadedCacheOffloadedStaticCacheQuantizedCacheQuantizedCacheConfigQuantoQuantizedCache	SinkCacheSlidingWindowCacheStaticCachecache_utils)	GlueDatasetGlueDataTrainingArgumentsLineByLineTextDatasetLineByLineWithRefDatasetLineByLineWithSOPTextDatasetSquadDatasetSquadDataTrainingArgumentsTextDataset$TextDatasetForNextSentencePredictionzdata.datasets)4#AlternatingCodebooksLogitsProcessorBayesianDetectorConfigBayesianDetectorModel
BeamScorerBeamSearchScorer%ClassifierFreeGuidanceLogitsProcessorConstrainedBeamSearchScorer
ConstraintConstraintListStateDisjunctiveConstraint#EncoderNoRepeatNGramLogitsProcessor'EncoderRepetitionPenaltyLogitsProcessorEosTokenCriteriaEpsilonLogitsWarperEtaLogitsWarperExponentialDecayLengthPenaltyForcedBOSTokenLogitsProcessorForcedEOSTokenLogitsProcessorGenerationMixinHammingDiversityLogitsProcessorInfNanRemoveLogitsProcessorLogitNormalizationLogitsProcessorLogitsProcessorListLogitsWarperMaxLengthCriteriaMaxTimeCriteriaMinLengthLogitsProcessor!MinNewTokensLengthLogitsProcessorMinPLogitsWarperNoBadWordsLogitsProcessorNoRepeatNGramLogitsProcessorPhrasalConstraint PrefixConstrainedLogitsProcessor RepetitionPenaltyLogitsProcessorSequenceBiasLogitsProcessorStoppingCriteriaStoppingCriteriaListStopStringCriteria$SuppressTokensAtBeginLogitsProcessorSuppressTokensLogitsProcessorSynthIDTextWatermarkDetectorSynthIDTextWatermarkingConfig#SynthIDTextWatermarkLogitsProcessorTemperatureLogitsWarperTopKLogitsWarperTopPLogitsWarperTypicalLogitsWarper.UnbatchedClassifierFreeGuidanceLogitsProcessorWatermarkDetectorWatermarkLogitsProcessorWhisperTimeStampLogitsProcessor$TorchExportableModuleWithStaticCacheconvert_and_export_with_cachezintegrations.executorchmodeling_flash_attention_utilsmodeling_outputsROPE_INIT_FUNCTIONSmodeling_rope_utilsPreTrainedModelmodeling_utils)	AlbertForMaskedLMAlbertForMultipleChoiceAlbertForPreTrainingAlbertForQuestionAnsweringAlbertForSequenceClassificationAlbertForTokenClassificationAlbertModelAlbertPreTrainedModelload_tf_weights_in_albert)
AlignModelAlignPreTrainedModelAlignTextModelAlignVisionModel)AltCLIPModelAltCLIPPreTrainedModelAltCLIPTextModelAltCLIPVisionModel)ASTForAudioClassificationASTModelASTPreTrainedModel)R&MODEL_FOR_AUDIO_CLASSIFICATION_MAPPING,MODEL_FOR_AUDIO_FRAME_CLASSIFICATION_MAPPINGMODEL_FOR_AUDIO_XVECTOR_MAPPINGMODEL_FOR_BACKBONE_MAPPING'MODEL_FOR_CAUSAL_IMAGE_MODELING_MAPPINGMODEL_FOR_CAUSAL_LM_MAPPINGMODEL_FOR_CTC_MAPPING"MODEL_FOR_DEPTH_ESTIMATION_MAPPING-MODEL_FOR_DOCUMENT_QUESTION_ANSWERING_MAPPING&MODEL_FOR_IMAGE_CLASSIFICATION_MAPPINGMODEL_FOR_IMAGE_MAPPING$MODEL_FOR_IMAGE_SEGMENTATION_MAPPING$MODEL_FOR_IMAGE_TEXT_TO_TEXT_MAPPING MODEL_FOR_IMAGE_TO_IMAGE_MAPPING'MODEL_FOR_INSTANCE_SEGMENTATION_MAPPING$MODEL_FOR_KEYPOINT_DETECTION_MAPPING'MODEL_FOR_MASKED_IMAGE_MODELING_MAPPINGMODEL_FOR_MASKED_LM_MAPPING!MODEL_FOR_MASK_GENERATION_MAPPING!MODEL_FOR_MULTIPLE_CHOICE_MAPPING*MODEL_FOR_NEXT_SENTENCE_PREDICTION_MAPPING"MODEL_FOR_OBJECT_DETECTION_MAPPINGMODEL_FOR_PRETRAINING_MAPPING$MODEL_FOR_QUESTION_ANSWERING_MAPPING'MODEL_FOR_SEMANTIC_SEGMENTATION_MAPPING&MODEL_FOR_SEQ_TO_SEQ_CAUSAL_LM_MAPPING)MODEL_FOR_SEQUENCE_CLASSIFICATION_MAPPING"MODEL_FOR_SPEECH_SEQ_2_SEQ_MAPPING*MODEL_FOR_TABLE_QUESTION_ANSWERING_MAPPINGMODEL_FOR_TEXT_ENCODING_MAPPING%MODEL_FOR_TEXT_TO_SPECTROGRAM_MAPPING"MODEL_FOR_TEXT_TO_WAVEFORM_MAPPING,MODEL_FOR_TIME_SERIES_CLASSIFICATION_MAPPING(MODEL_FOR_TIME_SERIES_REGRESSION_MAPPING&MODEL_FOR_TOKEN_CLASSIFICATION_MAPPING(MODEL_FOR_UNIVERSAL_SEGMENTATION_MAPPING&MODEL_FOR_VIDEO_CLASSIFICATION_MAPPINGMODEL_FOR_VISION_2_SEQ_MAPPING+MODEL_FOR_VISUAL_QUESTION_ANSWERING_MAPPING0MODEL_FOR_ZERO_SHOT_IMAGE_CLASSIFICATION_MAPPING,MODEL_FOR_ZERO_SHOT_OBJECT_DETECTION_MAPPINGMODEL_MAPPINGMODEL_WITH_LM_HEAD_MAPPINGAutoBackbone	AutoModelAutoModelForAudioClassification$AutoModelForAudioFrameClassificationAutoModelForAudioXVectorAutoModelForCausalLMAutoModelForCTCAutoModelForDepthEstimation%AutoModelForDocumentQuestionAnsweringAutoModelForImageClassificationAutoModelForImageSegmentationAutoModelForImageTextToTextAutoModelForImageToImage AutoModelForInstanceSegmentationAutoModelForKeypointDetectionAutoModelForMaskedImageModelingAutoModelForMaskedLMAutoModelForMaskGenerationAutoModelForMultipleChoice"AutoModelForNextSentencePredictionAutoModelForObjectDetectionAutoModelForPreTrainingAutoModelForQuestionAnswering AutoModelForSemanticSegmentationAutoModelForSeq2SeqLM"AutoModelForSequenceClassificationAutoModelForSpeechSeq2Seq"AutoModelForTableQuestionAnsweringAutoModelForTextEncodingAutoModelForTextToSpectrogramAutoModelForTextToWaveformAutoModelForTokenClassification!AutoModelForUniversalSegmentationAutoModelForVideoClassificationAutoModelForVision2Seq#AutoModelForVisualQuestionAnswering'AutoModelForZeroShotImageClassification#AutoModelForZeroShotObjectDetectionAutoModelWithLMHead)AutoformerForPredictionAutoformerModelAutoformerPreTrainedModel)BarkCausalModelBarkCoarseModelBarkFineModel	BarkModelBarkPreTrainedModelBarkSemanticModel)BartForCausalLMBartForConditionalGenerationBartForQuestionAnsweringBartForSequenceClassification	BartModelBartPretrainedModelBartPreTrainedModelPretrainedBartModel)BeitBackboneBeitForImageClassificationBeitForMaskedImageModelingBeitForSemanticSegmentation	BeitModelBeitPreTrainedModel)BertForMaskedLMBertForMultipleChoiceBertForNextSentencePredictionBertForPreTrainingBertForQuestionAnsweringBertForSequenceClassificationBertForTokenClassificationBertLMHeadModel	BertModelBertPreTrainedModelload_tf_weights_in_bert)BertGenerationDecoderBertGenerationEncoderBertGenerationPreTrainedModel"load_tf_weights_in_bert_generation)
BigBirdForCausalLMBigBirdForMaskedLMBigBirdForMultipleChoiceBigBirdForPreTrainingBigBirdForQuestionAnswering BigBirdForSequenceClassificationBigBirdForTokenClassificationBigBirdModelBigBirdPreTrainedModelload_tf_weights_in_big_bird)BigBirdPegasusForCausalLM&BigBirdPegasusForConditionalGeneration"BigBirdPegasusForQuestionAnswering'BigBirdPegasusForSequenceClassificationBigBirdPegasusModelBigBirdPegasusPreTrainedModel)BioGptForCausalLMBioGptForSequenceClassificationBioGptForTokenClassificationBioGptModelBioGptPreTrainedModel)BitBackboneBitForImageClassificationBitModelBitPreTrainedModel)BlenderbotForCausalLM"BlenderbotForConditionalGenerationBlenderbotModelBlenderbotPreTrainedModel)BlenderbotSmallForCausalLM'BlenderbotSmallForConditionalGenerationBlenderbotSmallModelBlenderbotSmallPreTrainedModel)BlipForConditionalGenerationBlipForImageTextRetrievalBlipForQuestionAnswering	BlipModelBlipPreTrainedModelBlipTextModelBlipVisionModel)Blip2ForConditionalGenerationBlip2ForImageTextRetrieval
Blip2ModelBlip2PreTrainedModelBlip2QFormerModelBlip2TextModelWithProjectionBlip2VisionModelBlip2VisionModelWithProjection)BloomForCausalLMBloomForQuestionAnsweringBloomForSequenceClassificationBloomForTokenClassification
BloomModelBloomPreTrainedModel)!BridgeTowerForContrastiveLearning#BridgeTowerForImageAndTextRetrievalBridgeTowerForMaskedLMBridgeTowerModelBridgeTowerPreTrainedModel)BrosForTokenClassification	BrosModelBrosPreTrainedModelr   !BrosSpadeEEForTokenClassification!BrosSpadeELForTokenClassification)CamembertForCausalLMCamembertForMaskedLMCamembertForMultipleChoiceCamembertForQuestionAnswering"CamembertForSequenceClassificationCamembertForTokenClassificationCamembertModelCamembertPreTrainedModel)CanineForMultipleChoiceCanineForQuestionAnsweringCanineForSequenceClassificationCanineForTokenClassificationCanineModelCaninePreTrainedModelload_tf_weights_in_canine)!ChameleonForConditionalGenerationChameleonModelChameleonPreTrainedModelr   ChameleonVQVAE)ChineseCLIPModelChineseCLIPPreTrainedModelChineseCLIPTextModelChineseCLIPVisionModel)ClapAudioModelClapAudioModelWithProjectionClapFeatureExtractor	ClapModelClapPreTrainedModelClapTextModelClapTextModelWithProjection)CLIPForImageClassification	CLIPModelCLIPPreTrainedModelCLIPTextModelCLIPTextModelWithProjectionCLIPVisionModelCLIPVisionModelWithProjection)CLIPSegForImageSegmentationCLIPSegModelCLIPSegPreTrainedModelCLIPSegTextModelCLIPSegVisionModel)ClvpDecoderClvpEncoderClvpForCausalLM	ClvpModel!ClvpModelForConditionalGenerationClvpPreTrainedModel)CodeGenForCausalLMCodeGenModelCodeGenPreTrainedModel)CohereForCausalLMCohereModelCoherePreTrainedModel)!ConditionalDetrForObjectDetectionConditionalDetrForSegmentationConditionalDetrModelConditionalDetrPreTrainedModel)ConvBertForMaskedLMConvBertForMultipleChoiceConvBertForQuestionAnswering!ConvBertForSequenceClassificationConvBertForTokenClassificationConvBertModelConvBertPreTrainedModelload_tf_weights_in_convbert)ConvNextBackboneConvNextForImageClassificationConvNextModelConvNextPreTrainedModel)ConvNextV2Backbone ConvNextV2ForImageClassificationConvNextV2ModelConvNextV2PreTrainedModel)CpmAntForCausalLMCpmAntModelCpmAntPreTrainedModel)CTRLForSequenceClassificationCTRLLMHeadModel	CTRLModelCTRLPreTrainedModel)CvtForImageClassificationCvtModelCvtPreTrainedModelDacModelDacPreTrainedModel)(Data2VecAudioForAudioFrameClassificationData2VecAudioForCTC&Data2VecAudioForSequenceClassificationData2VecAudioForXVectorData2VecAudioModelData2VecAudioPreTrainedModelData2VecTextForCausalLMData2VecTextForMaskedLMData2VecTextForMultipleChoice Data2VecTextForQuestionAnswering%Data2VecTextForSequenceClassification"Data2VecTextForTokenClassificationData2VecTextModelData2VecTextPreTrainedModel$Data2VecVisionForImageClassification%Data2VecVisionForSemanticSegmentationData2VecVisionModelData2VecVisionPreTrainedModel)DbrxForCausalLM	DbrxModelDbrxPreTrainedModel)DebertaForMaskedLMDebertaForQuestionAnswering DebertaForSequenceClassificationDebertaForTokenClassificationDebertaModelDebertaPreTrainedModel)DebertaV2ForMaskedLMDebertaV2ForMultipleChoiceDebertaV2ForQuestionAnswering"DebertaV2ForSequenceClassificationDebertaV2ForTokenClassificationDebertaV2ModelDebertaV2PreTrainedModel)DecisionTransformerGPT2Model&DecisionTransformerGPT2PreTrainedModelDecisionTransformerModel"DecisionTransformerPreTrainedModel) DeformableDetrForObjectDetectionDeformableDetrModelDeformableDetrPreTrainedModel)DeiTForImageClassification%DeiTForImageClassificationWithTeacherDeiTForMaskedImageModeling	DeiTModelDeiTPreTrainedModel)DetaForObjectDetection	DetaModelDetaPreTrainedModel)%EfficientFormerForImageClassification0EfficientFormerForImageClassificationWithTeacherEfficientFormerModelEfficientFormerPreTrainedModel)ErnieMForInformationExtractionErnieMForMultipleChoiceErnieMForQuestionAnsweringErnieMForSequenceClassificationErnieMForTokenClassificationErnieMModelErnieMPreTrainedModel)&GPTSanJapaneseForConditionalGenerationGPTSanJapaneseModelGPTSanJapanesePreTrainedModel) GraphormerForGraphClassificationGraphormerModelGraphormerPreTrainedModel)JukeboxModelJukeboxPreTrainedModelJukeboxPriorJukeboxVQVAE)MCTCTForCTC
MCTCTModelMCTCTPreTrainedModel)MegaForCausalLMMegaForMaskedLMMegaForMultipleChoiceMegaForQuestionAnsweringMegaForSequenceClassificationMegaForTokenClassification	MegaModelMegaPreTrainedModel)MMBTForClassification	MMBTModelModalEmbeddings)NatBackboneNatForImageClassificationNatModelNatPreTrainedModel)	NezhaForMaskedLMNezhaForMultipleChoiceNezhaForNextSentencePredictionNezhaForPreTrainingNezhaForQuestionAnsweringNezhaForSequenceClassificationNezhaForTokenClassification
NezhaModelNezhaPreTrainedModel)OpenLlamaForCausalLM"OpenLlamaForSequenceClassificationOpenLlamaModelOpenLlamaPreTrainedModel)
QDQBertForMaskedLMQDQBertForMultipleChoice QDQBertForNextSentencePredictionQDQBertForQuestionAnswering QDQBertForSequenceClassificationQDQBertForTokenClassificationQDQBertLMHeadModelQDQBertModelQDQBertPreTrainedModelload_tf_weights_in_qdqbert)RealmEmbedderRealmForOpenQARealmKnowledgeAugEncoderRealmPreTrainedModelRealmReaderRealmRetrieverRealmScorerload_tf_weights_in_realmRetriBertModelRetriBertPreTrainedModelSpeech2Text2ForCausalLMSpeech2Text2PreTrainedModelTrajectoryTransformerModel$TrajectoryTransformerPreTrainedModel)AdaptiveEmbedding"TransfoXLForSequenceClassificationTransfoXLLMHeadModelTransfoXLModelTransfoXLPreTrainedModelload_tf_weights_in_transfo_xl) TvltForAudioVisualClassificationTvltForPreTraining	TvltModelTvltPreTrainedModel)VanForImageClassificationVanModelVanPreTrainedModel)ViTHybridForImageClassificationViTHybridModelViTHybridPreTrainedModel)XLMProphetNetDecoderXLMProphetNetEncoderXLMProphetNetForCausalLM%XLMProphetNetForConditionalGenerationXLMProphetNetModelXLMProphetNetPreTrainedModelDepthAnythingForDepthEstimationDepthAnythingPreTrainedModel)DetrForObjectDetectionDetrForSegmentation	DetrModelDetrPreTrainedModel)DinatBackboneDinatForImageClassification
DinatModelDinatPreTrainedModel)Dinov2BackboneDinov2ForImageClassificationDinov2ModelDinov2PreTrainedModel)DistilBertForMaskedLMDistilBertForMultipleChoiceDistilBertForQuestionAnswering#DistilBertForSequenceClassification DistilBertForTokenClassificationDistilBertModelDistilBertPreTrainedModelDonutSwinModelDonutSwinPreTrainedModel)DPRContextEncoderDPRPretrainedContextEncoderDPRPreTrainedModelDPRPretrainedQuestionEncoderDPRPretrainedReaderDPRQuestionEncoder	DPRReader)DPTForDepthEstimationDPTForSemanticSegmentationDPTModelDPTPreTrainedModel)"EfficientNetForImageClassificationEfficientNetModelEfficientNetPreTrainedModel)
ElectraForCausalLMElectraForMaskedLMElectraForMultipleChoiceElectraForPreTrainingElectraForQuestionAnswering ElectraForSequenceClassificationElectraForTokenClassificationElectraModelElectraPreTrainedModelload_tf_weights_in_electraEncodecModelEncodecPreTrainedModelEncoderDecoderModel)
ErnieForCausalLMErnieForMaskedLMErnieForMultipleChoiceErnieForNextSentencePredictionErnieForPreTrainingErnieForQuestionAnsweringErnieForSequenceClassificationErnieForTokenClassification
ErnieModelErniePreTrainedModel)EsmFoldPreTrainedModelEsmForMaskedLMEsmForProteinFoldingEsmForSequenceClassificationEsmForTokenClassificationEsmModelEsmPreTrainedModel)FalconForCausalLMFalconForQuestionAnsweringFalconForSequenceClassificationFalconForTokenClassificationFalconModelFalconPreTrainedModel)FalconMambaForCausalLMFalconMambaModelFalconMambaPreTrainedModel)FastSpeech2ConformerHifiGanFastSpeech2ConformerModel#FastSpeech2ConformerPreTrainedModelFastSpeech2ConformerWithHifiGan)FlaubertForMultipleChoiceFlaubertForQuestionAnswering"FlaubertForQuestionAnsweringSimple!FlaubertForSequenceClassificationFlaubertForTokenClassificationFlaubertModelFlaubertPreTrainedModelFlaubertWithLMHeadModel)FlavaForPreTrainingFlavaImageCodebookFlavaImageModel
FlavaModelFlavaMultimodalModelFlavaPreTrainedModelFlavaTextModel)	FNetForMaskedLMFNetForMultipleChoiceFNetForNextSentencePredictionFNetForPreTrainingFNetForQuestionAnsweringFNetForSequenceClassificationFNetForTokenClassification	FNetModelFNetPreTrainedModel)FocalNetBackboneFocalNetForImageClassificationFocalNetForMaskedImageModelingFocalNetModelFocalNetPreTrainedModel)FSMTForConditionalGeneration	FSMTModelPretrainedFSMTModel)
FunnelBaseModelFunnelForMaskedLMFunnelForMultipleChoiceFunnelForPreTrainingFunnelForQuestionAnsweringFunnelForSequenceClassificationFunnelForTokenClassificationFunnelModelFunnelPreTrainedModelload_tf_weights_in_funnelFuyuForCausalLMFuyuPreTrainedModel)GemmaForCausalLMGemmaForSequenceClassificationGemmaForTokenClassification
GemmaModelGemmaPreTrainedModel)Gemma2ForCausalLMGemma2ForSequenceClassificationGemma2ForTokenClassificationGemma2ModelGemma2PreTrainedModel)GitForCausalLMGitModelGitPreTrainedModelGitVisionModel)GlmForCausalLMGlmForSequenceClassificationGlmForTokenClassificationGlmModelGlmPreTrainedModel)GLPNForDepthEstimation	GLPNModelGLPNPreTrainedModel)GPT2DoubleHeadsModelGPT2ForQuestionAnsweringGPT2ForSequenceClassificationGPT2ForTokenClassificationGPT2LMHeadModel	GPT2ModelGPT2PreTrainedModelload_tf_weights_in_gpt2)GPTBigCodeForCausalLM#GPTBigCodeForSequenceClassification GPTBigCodeForTokenClassificationGPTBigCodeModelGPTBigCodePreTrainedModel)GPTNeoForCausalLMGPTNeoForQuestionAnsweringGPTNeoForSequenceClassificationGPTNeoForTokenClassificationGPTNeoModelGPTNeoPreTrainedModelload_tf_weights_in_gpt_neo)GPTNeoXForCausalLMGPTNeoXForQuestionAnswering GPTNeoXForSequenceClassificationGPTNeoXForTokenClassificationGPTNeoXModelGPTNeoXPreTrainedModel)GPTNeoXJapaneseForCausalLMGPTNeoXJapaneseModelGPTNeoXJapanesePreTrainedModel)GPTJForCausalLMGPTJForQuestionAnsweringGPTJForSequenceClassification	GPTJModelGPTJPreTrainedModel)GraniteForCausalLMGraniteModelGranitePreTrainedModel)GraniteMoeForCausalLMGraniteMoeModelGraniteMoePreTrainedModel)GroundingDinoForObjectDetectionGroundingDinoModelGroundingDinoPreTrainedModel)GroupViTModelGroupViTPreTrainedModelGroupViTTextModelGroupViTVisionModel)HieraBackboneHieraForImageClassificationHieraForPreTraining
HieraModelHieraPreTrainedModel)HubertForCTCHubertForSequenceClassificationHubertModelHubertPreTrainedModel)IBertForMaskedLMIBertForMultipleChoiceIBertForQuestionAnsweringIBertForSequenceClassificationIBertForTokenClassification
IBertModelIBertPreTrainedModel)IdeficsForVisionText2TextIdeficsModelIdeficsPreTrainedModelIdeficsProcessor) Idefics2ForConditionalGenerationIdefics2ModelIdefics2PreTrainedModelIdefics2Processor) Idefics3ForConditionalGenerationIdefics3ModelIdefics3PreTrainedModelIdefics3Processor)ImageGPTForCausalImageModelingImageGPTForImageClassificationImageGPTModelImageGPTPreTrainedModelload_tf_weights_in_imagegpt)InformerForPredictionInformerModelInformerPreTrainedModel)$InstructBlipForConditionalGenerationInstructBlipPreTrainedModelInstructBlipQFormerModelInstructBlipVisionModel))InstructBlipVideoForConditionalGeneration InstructBlipVideoPreTrainedModelInstructBlipVideoQFormerModelInstructBlipVideoVisionModel)JambaForCausalLMJambaForSequenceClassification
JambaModelJambaPreTrainedModel)JetMoeForCausalLMJetMoeForSequenceClassificationJetMoeModelJetMoePreTrainedModel)Kosmos2ForConditionalGenerationKosmos2ModelKosmos2PreTrainedModel)LayoutLMForMaskedLMLayoutLMForQuestionAnswering!LayoutLMForSequenceClassificationLayoutLMForTokenClassificationLayoutLMModelLayoutLMPreTrainedModel)LayoutLMv2ForQuestionAnswering#LayoutLMv2ForSequenceClassification LayoutLMv2ForTokenClassificationLayoutLMv2ModelLayoutLMv2PreTrainedModel)LayoutLMv3ForQuestionAnswering#LayoutLMv3ForSequenceClassification LayoutLMv3ForTokenClassificationLayoutLMv3ModelLayoutLMv3PreTrainedModel)LEDForConditionalGenerationLEDForQuestionAnsweringLEDForSequenceClassificationLEDModelLEDPreTrainedModel)LevitForImageClassification&LevitForImageClassificationWithTeacher
LevitModelLevitPreTrainedModel)LiltForQuestionAnsweringLiltForSequenceClassificationLiltForTokenClassification	LiltModelLiltPreTrainedModel)LlamaForCausalLMLlamaForQuestionAnsweringLlamaForSequenceClassificationLlamaForTokenClassification
LlamaModelLlamaPreTrainedModelLlavaForConditionalGenerationLlavaPreTrainedModel!LlavaNextForConditionalGenerationLlavaNextPreTrainedModel&LlavaNextVideoForConditionalGenerationLlavaNextVideoPreTrainedModel&LlavaOnevisionForConditionalGenerationLlavaOnevisionPreTrainedModel)LongformerForMaskedLMLongformerForMultipleChoiceLongformerForQuestionAnswering#LongformerForSequenceClassification LongformerForTokenClassificationLongformerModelLongformerPreTrainedModel)LongT5EncoderModelLongT5ForConditionalGenerationLongT5ModelLongT5PreTrainedModel)
LukeForEntityClassificationLukeForEntityPairClassificationLukeForEntitySpanClassificationLukeForMaskedLMLukeForMultipleChoiceLukeForQuestionAnsweringLukeForSequenceClassificationLukeForTokenClassification	LukeModelLukePreTrainedModel)LxmertEncoderLxmertForPreTrainingLxmertForQuestionAnsweringLxmertModelLxmertPreTrainedModelLxmertVisualFeatureEncoder)M2M100ForConditionalGenerationM2M100ModelM2M100PreTrainedModel)MambaForCausalLM
MambaModelMambaPreTrainedModel)Mamba2ForCausalLMMamba2ModelMamba2PreTrainedModel)MarianForCausalLMMarianModelMarianMTModelMarianPreTrainedModel)MarkupLMForQuestionAnswering!MarkupLMForSequenceClassificationMarkupLMForTokenClassificationMarkupLMModelMarkupLMPreTrainedModel)#Mask2FormerForUniversalSegmentationMask2FormerModelMask2FormerPreTrainedModel)!MaskFormerForInstanceSegmentationMaskFormerModelMaskFormerPreTrainedModelMaskFormerSwinBackbone)MBartForCausalLMMBartForConditionalGenerationMBartForQuestionAnsweringMBartForSequenceClassification
MBartModelMBartPreTrainedModel)
MegatronBertForCausalLMMegatronBertForMaskedLMMegatronBertForMultipleChoice%MegatronBertForNextSentencePredictionMegatronBertForPreTraining MegatronBertForQuestionAnswering%MegatronBertForSequenceClassification"MegatronBertForTokenClassificationMegatronBertModelMegatronBertPreTrainedModel)MgpstrForSceneTextRecognitionMgpstrModelMgpstrPreTrainedModel	MimiModelMimiPreTrainedModel)MistralForCausalLMMistralForQuestionAnswering MistralForSequenceClassificationMistralForTokenClassificationMistralModelMistralPreTrainedModel)MixtralForCausalLMMixtralForQuestionAnswering MixtralForSequenceClassificationMixtralForTokenClassificationMixtralModelMixtralPreTrainedModel)MllamaForCausalLMMllamaForConditionalGenerationMllamaPreTrainedModelr  MllamaTextModelMllamaVisionModel)
MobileBertForMaskedLMMobileBertForMultipleChoice#MobileBertForNextSentencePredictionMobileBertForPreTrainingMobileBertForQuestionAnswering#MobileBertForSequenceClassification MobileBertForTokenClassificationMobileBertModelMobileBertPreTrainedModelload_tf_weights_in_mobilebert)!MobileNetV1ForImageClassificationMobileNetV1ModelMobileNetV1PreTrainedModelload_tf_weights_in_mobilenet_v1)!MobileNetV2ForImageClassification"MobileNetV2ForSemanticSegmentationMobileNetV2ModelMobileNetV2PreTrainedModelload_tf_weights_in_mobilenet_v2)MobileViTForImageClassification MobileViTForSemanticSegmentationMobileViTModelMobileViTPreTrainedModel)!MobileViTV2ForImageClassification"MobileViTV2ForSemanticSegmentationMobileViTV2ModelMobileViTV2PreTrainedModel)MoshiForCausalLMMoshiForConditionalGeneration
MoshiModelMoshiPreTrainedModel)MPNetForMaskedLMMPNetForMultipleChoiceMPNetForQuestionAnsweringMPNetForSequenceClassificationMPNetForTokenClassification
MPNetModelMPNetPreTrainedModel)MptForCausalLMMptForQuestionAnsweringMptForSequenceClassificationMptForTokenClassificationMptModelMptPreTrainedModel)MraForMaskedLMMraForMultipleChoiceMraForQuestionAnsweringMraForSequenceClassificationMraForTokenClassificationMraModelMraPreTrainedModel)MT5EncoderModelMT5ForConditionalGenerationMT5ForQuestionAnsweringMT5ForSequenceClassificationMT5ForTokenClassificationMT5ModelMT5PreTrainedModel)MusicgenForCausalLM MusicgenForConditionalGenerationMusicgenModelMusicgenPreTrainedModelMusicgenProcessor)MusicgenMelodyForCausalLM&MusicgenMelodyForConditionalGenerationMusicgenMelodyModelMusicgenMelodyPreTrainedModel)MvpForCausalLMMvpForConditionalGenerationMvpForQuestionAnsweringMvpForSequenceClassificationMvpModelMvpPreTrainedModel)NemotronForCausalLMNemotronForQuestionAnswering!NemotronForSequenceClassificationNemotronForTokenClassificationNemotronModelNemotronPreTrainedModel)NllbMoeForConditionalGenerationNllbMoeModelNllbMoePreTrainedModelNllbMoeSparseMLPNllbMoeTop2Router)NystromformerForMaskedLMNystromformerForMultipleChoice!NystromformerForQuestionAnswering&NystromformerForSequenceClassification#NystromformerForTokenClassificationNystromformerModelNystromformerPreTrainedModel)OlmoForCausalLM	OlmoModelOlmoPreTrainedModel)OlmoeForCausalLM
OlmoeModelOlmoePreTrainedModelOmDetTurboForObjectDetectionOmDetTurboPreTrainedModel)!OneFormerForUniversalSegmentationOneFormerModelOneFormerPreTrainedModel)OpenAIGPTDoubleHeadsModel"OpenAIGPTForSequenceClassificationOpenAIGPTLMHeadModelOpenAIGPTModelOpenAIGPTPreTrainedModelload_tf_weights_in_openai_gpt)OPTForCausalLMOPTForQuestionAnsweringOPTForSequenceClassificationOPTModelOPTPreTrainedModel)Owlv2ForObjectDetection
Owlv2ModelOwlv2PreTrainedModelOwlv2TextModelOwlv2VisionModel)OwlViTForObjectDetectionOwlViTModelOwlViTPreTrainedModelOwlViTTextModelOwlViTVisionModel)!PaliGemmaForConditionalGenerationPaliGemmaPreTrainedModelPaliGemmaProcessor)PatchTSMixerForPredictionPatchTSMixerForPretrainingPatchTSMixerForRegression'PatchTSMixerForTimeSeriesClassificationPatchTSMixerModelPatchTSMixerPreTrainedModel)PatchTSTForClassificationPatchTSTForPredictionPatchTSTForPretrainingPatchTSTForRegressionPatchTSTModelPatchTSTPreTrainedModel)PegasusForCausalLMPegasusForConditionalGenerationPegasusModelPegasusPreTrainedModel) PegasusXForConditionalGenerationPegasusXModelPegasusXPreTrainedModel)	-PerceiverForImageClassificationConvProcessing&PerceiverForImageClassificationFourier&PerceiverForImageClassificationLearnedPerceiverForMaskedLM"PerceiverForMultimodalAutoencodingPerceiverForOpticalFlow"PerceiverForSequenceClassificationPerceiverModelPerceiverPreTrainedModel)PersimmonForCausalLM"PersimmonForSequenceClassificationPersimmonForTokenClassificationPersimmonModelPersimmonPreTrainedModel)PhiForCausalLMPhiForSequenceClassificationPhiForTokenClassificationPhiModelPhiPreTrainedModel)Phi3ForCausalLMPhi3ForSequenceClassificationPhi3ForTokenClassification	Phi3ModelPhi3PreTrainedModel)PhimoeForCausalLMPhimoeForSequenceClassificationPhimoeModelPhimoePreTrainedModel)"Pix2StructForConditionalGenerationPix2StructPreTrainedModelPix2StructTextModelPix2StructVisionModelPixtralPreTrainedModelPixtralVisionModel)PLBartForCausalLMPLBartForConditionalGenerationPLBartForSequenceClassificationPLBartModelPLBartPreTrainedModel) PoolFormerForImageClassificationPoolFormerModelPoolFormerPreTrainedModel!Pop2PianoForConditionalGenerationPop2PianoPreTrainedModel)ProphetNetDecoderProphetNetEncoderProphetNetForCausalLM"ProphetNetForConditionalGenerationProphetNetModelProphetNetPreTrainedModel)PvtForImageClassificationPvtModelPvtPreTrainedModel)PvtV2BackbonePvtV2ForImageClassification
PvtV2ModelPvtV2PreTrainedModel)Qwen2ForCausalLMQwen2ForQuestionAnsweringQwen2ForSequenceClassificationQwen2ForTokenClassification
Qwen2ModelQwen2PreTrainedModel)Qwen2AudioEncoder"Qwen2AudioForConditionalGenerationQwen2AudioPreTrainedModel)Qwen2MoeForCausalLMQwen2MoeForQuestionAnswering!Qwen2MoeForSequenceClassificationQwen2MoeForTokenClassificationQwen2MoeModelQwen2MoePreTrainedModel)Qwen2VLForConditionalGenerationQwen2VLModelQwen2VLPreTrainedModel)RagModelRagPreTrainedModelRagSequenceForGenerationRagTokenForGeneration)RecurrentGemmaForCausalLMRecurrentGemmaModelRecurrentGemmaPreTrainedModel)ReformerForMaskedLMReformerForQuestionAnswering!ReformerForSequenceClassificationReformerModelReformerModelWithLMHeadReformerPreTrainedModel)RegNetForImageClassificationRegNetModelRegNetPreTrainedModel)	RemBertForCausalLMRemBertForMaskedLMRemBertForMultipleChoiceRemBertForQuestionAnswering RemBertForSequenceClassificationRemBertForTokenClassificationRemBertModelRemBertPreTrainedModelload_tf_weights_in_rembert)ResNetBackboneResNetForImageClassificationResNetModelResNetPreTrainedModel)RobertaForCausalLMRobertaForMaskedLMRobertaForMultipleChoiceRobertaForQuestionAnswering RobertaForSequenceClassificationRobertaForTokenClassificationRobertaModelRobertaPreTrainedModel)RobertaPreLayerNormForCausalLMRobertaPreLayerNormForMaskedLM$RobertaPreLayerNormForMultipleChoice'RobertaPreLayerNormForQuestionAnswering,RobertaPreLayerNormForSequenceClassification)RobertaPreLayerNormForTokenClassificationRobertaPreLayerNormModel"RobertaPreLayerNormPreTrainedModel)
RoCBertForCausalLMRoCBertForMaskedLMRoCBertForMultipleChoiceRoCBertForPreTrainingRoCBertForQuestionAnswering RoCBertForSequenceClassificationRoCBertForTokenClassificationRoCBertModelRoCBertPreTrainedModelload_tf_weights_in_roc_bert)	RoFormerForCausalLMRoFormerForMaskedLMRoFormerForMultipleChoiceRoFormerForQuestionAnswering!RoFormerForSequenceClassificationRoFormerForTokenClassificationRoFormerModelRoFormerPreTrainedModelload_tf_weights_in_roformer)RTDetrForObjectDetectionRTDetrModelRTDetrPreTrainedModelRTDetrResNetBackboneRTDetrResNetPreTrainedModel)RwkvForCausalLM	RwkvModelRwkvPreTrainedModelSamModelSamPreTrainedModel)
SeamlessM4TCodeHifiGanSeamlessM4TForSpeechToSpeechSeamlessM4TForSpeechToTextSeamlessM4TForTextToSpeechSeamlessM4TForTextToTextSeamlessM4THifiGanSeamlessM4TModelSeamlessM4TPreTrainedModel-SeamlessM4TTextToUnitForConditionalGenerationSeamlessM4TTextToUnitModel)SeamlessM4Tv2ForSpeechToSpeechSeamlessM4Tv2ForSpeechToTextSeamlessM4Tv2ForTextToSpeechSeamlessM4Tv2ForTextToTextSeamlessM4Tv2ModelSeamlessM4Tv2PreTrainedModel)SegformerDecodeHeadSegformerForImageClassification SegformerForSemanticSegmentationSegformerModelSegformerPreTrainedModel)SegGptForImageSegmentationSegGptModelSegGptPreTrainedModel)	SEWForCTCSEWForSequenceClassificationSEWModelSEWPreTrainedModel)
SEWDForCTCSEWDForSequenceClassification	SEWDModelSEWDPreTrainedModel)SiglipForImageClassificationSiglipModelSiglipPreTrainedModelSiglipTextModelSiglipVisionModelSpeechEncoderDecoderModel)#Speech2TextForConditionalGenerationSpeech2TextModelSpeech2TextPreTrainedModel)SpeechT5ForSpeechToSpeechSpeechT5ForSpeechToTextSpeechT5ForTextToSpeechSpeechT5HifiGanSpeechT5ModelSpeechT5PreTrainedModel)SplinterForPreTrainingSplinterForQuestionAnsweringSplinterModelSplinterPreTrainedModel)SqueezeBertForMaskedLMSqueezeBertForMultipleChoiceSqueezeBertForQuestionAnswering$SqueezeBertForSequenceClassification!SqueezeBertForTokenClassificationSqueezeBertModelSqueezeBertPreTrainedModel)StableLmForCausalLM!StableLmForSequenceClassificationStableLmForTokenClassificationStableLmModelStableLmPreTrainedModel)Starcoder2ForCausalLM#Starcoder2ForSequenceClassification Starcoder2ForTokenClassificationStarcoder2ModelStarcoder2PreTrainedModelSuperPointForKeypointDetectionSuperPointPreTrainedModel)!SwiftFormerForImageClassificationSwiftFormerModelSwiftFormerPreTrainedModel)SwinBackboneSwinForImageClassificationSwinForMaskedImageModeling	SwinModelSwinPreTrainedModel)Swin2SRForImageSuperResolutionSwin2SRModelSwin2SRPreTrainedModel)Swinv2BackboneSwinv2ForImageClassificationSwinv2ForMaskedImageModelingSwinv2ModelSwinv2PreTrainedModel)SwitchTransformersEncoderModel*SwitchTransformersForConditionalGenerationSwitchTransformersModel!SwitchTransformersPreTrainedModelSwitchTransformersSparseMLPSwitchTransformersTop1Router)T5EncoderModelT5ForConditionalGenerationT5ForQuestionAnsweringT5ForSequenceClassificationT5ForTokenClassificationT5ModelT5PreTrainedModelload_tf_weights_in_t5)"TableTransformerForObjectDetectionTableTransformerModelTableTransformerPreTrainedModel)TapasForMaskedLMTapasForQuestionAnsweringTapasForSequenceClassification
TapasModelTapasPreTrainedModelload_tf_weights_in_tapas)"TimeSeriesTransformerForPredictionTimeSeriesTransformerModel$TimeSeriesTransformerPreTrainedModel)!TimesformerForVideoClassificationTimesformerModelTimesformerPreTrainedModelTimmBackboneTrOCRForCausalLMTrOCRPreTrainedModel)TvpForVideoGroundingTvpModelTvpPreTrainedModel)UdopEncoderModelUdopForConditionalGeneration	UdopModelUdopPreTrainedModel)UMT5EncoderModelUMT5ForConditionalGenerationUMT5ForQuestionAnsweringUMT5ForSequenceClassificationUMT5ForTokenClassification	UMT5ModelUMT5PreTrainedModel)UniSpeechForCTCUniSpeechForPreTraining"UniSpeechForSequenceClassificationUniSpeechModelUniSpeechPreTrainedModel)'UniSpeechSatForAudioFrameClassificationUniSpeechSatForCTCUniSpeechSatForPreTraining%UniSpeechSatForSequenceClassificationUniSpeechSatForXVectorUniSpeechSatModelUniSpeechSatPreTrainedModelUnivNetModelUperNetForSemanticSegmentationUperNetPreTrainedModel)"VideoLlavaForConditionalGenerationVideoLlavaPreTrainedModelVideoLlavaProcessor)VideoMAEForPreTrainingVideoMAEForVideoClassificationVideoMAEModelVideoMAEPreTrainedModel)ViltForImageAndTextRetrieval"ViltForImagesAndTextClassificationViltForMaskedLMViltForQuestionAnsweringViltForTokenClassification	ViltModelViltPreTrainedModel VipLlavaForConditionalGenerationVipLlavaPreTrainedModelVisionEncoderDecoderModelVisionTextDualEncoderModel)VisualBertForMultipleChoiceVisualBertForPreTrainingVisualBertForQuestionAnswering$VisualBertForRegionToPhraseAlignmentVisualBertForVisualReasoningVisualBertModelVisualBertPreTrainedModel)ViTForImageClassificationViTForMaskedImageModelingViTModelViTPreTrainedModel)ViTMAEForPreTrainingViTMAEModelViTMAEPreTrainedModel)ViTMSNForImageClassificationViTMSNModelViTMSNPreTrainedModel)VitDetBackboneVitDetModelVitDetPreTrainedModelVitMatteForImageMattingVitMattePreTrainedModel	VitsModelVitsPreTrainedModel)VivitForVideoClassification
VivitModelVivitPreTrainedModel)#Wav2Vec2ForAudioFrameClassificationWav2Vec2ForCTCWav2Vec2ForMaskedLMWav2Vec2ForPreTraining!Wav2Vec2ForSequenceClassificationWav2Vec2ForXVectorWav2Vec2ModelWav2Vec2PreTrainedModel)'Wav2Vec2BertForAudioFrameClassificationWav2Vec2BertForCTC%Wav2Vec2BertForSequenceClassificationWav2Vec2BertForXVectorWav2Vec2BertModelWav2Vec2BertPreTrainedModel),Wav2Vec2ConformerForAudioFrameClassificationWav2Vec2ConformerForCTCWav2Vec2ConformerForPreTraining*Wav2Vec2ConformerForSequenceClassificationWav2Vec2ConformerForXVectorWav2Vec2ConformerModel Wav2Vec2ConformerPreTrainedModel) WavLMForAudioFrameClassificationWavLMForCTCWavLMForSequenceClassificationWavLMForXVector
WavLMModelWavLMPreTrainedModel)WhisperForAudioClassificationWhisperForCausalLMWhisperForConditionalGenerationWhisperModelWhisperPreTrainedModel)
XCLIPModelXCLIPPreTrainedModelXCLIPTextModelXCLIPVisionModel)XGLMForCausalLM	XGLMModelXGLMPreTrainedModel)XLMForMultipleChoiceXLMForQuestionAnsweringXLMForQuestionAnsweringSimpleXLMForSequenceClassificationXLMForTokenClassificationXLMModelXLMPreTrainedModelXLMWithLMHeadModel)XLMRobertaForCausalLMXLMRobertaForMaskedLMXLMRobertaForMultipleChoiceXLMRobertaForQuestionAnswering#XLMRobertaForSequenceClassification XLMRobertaForTokenClassificationXLMRobertaModelXLMRobertaPreTrainedModel)XLMRobertaXLForCausalLMXLMRobertaXLForMaskedLMXLMRobertaXLForMultipleChoice XLMRobertaXLForQuestionAnswering%XLMRobertaXLForSequenceClassification"XLMRobertaXLForTokenClassificationXLMRobertaXLModelXLMRobertaXLPreTrainedModel)	XLNetForMultipleChoiceXLNetForQuestionAnsweringXLNetForQuestionAnsweringSimpleXLNetForSequenceClassificationXLNetForTokenClassificationXLNetLMHeadModel
XLNetModelXLNetPreTrainedModelload_tf_weights_in_xlnet)XmodForCausalLMXmodForMaskedLMXmodForMultipleChoiceXmodForQuestionAnsweringXmodForSequenceClassificationXmodForTokenClassification	XmodModelXmodPreTrainedModel)YolosForObjectDetection
YolosModelYolosPreTrainedModel)YosoForMaskedLMYosoForMultipleChoiceYosoForQuestionAnsweringYosoForSequenceClassificationYosoForTokenClassification	YosoModelYosoPreTrainedModel)ZambaForCausalLMZambaForSequenceClassification
ZambaModelZambaPreTrainedModelZoeDepthForDepthEstimationZoeDepthPreTrainedModel)	AdafactorAdamWget_constant_schedule!get_constant_schedule_with_warmupget_cosine_schedule_with_warmup2get_cosine_with_hard_restarts_schedule_with_warmupget_inverse_sqrt_scheduleget_linear_schedule_with_warmup)get_polynomial_decay_schedule_with_warmupget_schedulerget_wsd_scheduleoptimization)Conv1Dapply_chunking_to_forwardprune_layerpytorch_utils	sagemakertime_series_utilsTrainertrainertorch_distributed_zero_firsttrainer_pt_utilsSeq2SeqTrainertrainer_seq2seq)dummy_pt_objectsc                 <    g | ]}|                     d           |S r  r  r  s     r  r  r    -    2v2v2vDaeapapqtauau2v42v2v2vr  zutils.dummy_pt_objectsactivations_tfTensorFlowBenchmarkArgumentszbenchmark.benchmark_args_tfTensorFlowBenchmarkzbenchmark.benchmark_tf)TFForcedBOSTokenLogitsProcessorTFForcedEOSTokenLogitsProcessorTFForceTokensLogitsProcessorTFGenerationMixinTFLogitsProcessorTFLogitsProcessorListTFLogitsWarperTFMinLengthLogitsProcessorTFNoBadWordsLogitsProcessorTFNoRepeatNGramLogitsProcessor"TFRepetitionPenaltyLogitsProcessor&TFSuppressTokensAtBeginLogitsProcessorTFSuppressTokensLogitsProcessorTFTemperatureLogitsWarperTFTopKLogitsWarperTFTopPLogitsWarperKerasMetricCallbackPushToHubCallbackkeras_callbacksmodeling_tf_outputs)TFPreTrainedModelTFSequenceSummaryTFSharedEmbeddings
shape_listmodeling_tf_utils)	TFAlbertForMaskedLMTFAlbertForMultipleChoiceTFAlbertForPreTrainingTFAlbertForQuestionAnswering!TFAlbertForSequenceClassificationTFAlbertForTokenClassificationTFAlbertMainLayerTFAlbertModelTFAlbertPreTrainedModel),)TF_MODEL_FOR_AUDIO_CLASSIFICATION_MAPPINGTF_MODEL_FOR_CAUSAL_LM_MAPPING0TF_MODEL_FOR_DOCUMENT_QUESTION_ANSWERING_MAPPING)TF_MODEL_FOR_IMAGE_CLASSIFICATION_MAPPING*TF_MODEL_FOR_MASKED_IMAGE_MODELING_MAPPINGTF_MODEL_FOR_MASKED_LM_MAPPING$TF_MODEL_FOR_MASK_GENERATION_MAPPING$TF_MODEL_FOR_MULTIPLE_CHOICE_MAPPING-TF_MODEL_FOR_NEXT_SENTENCE_PREDICTION_MAPPING TF_MODEL_FOR_PRETRAINING_MAPPING'TF_MODEL_FOR_QUESTION_ANSWERING_MAPPING*TF_MODEL_FOR_SEMANTIC_SEGMENTATION_MAPPING)TF_MODEL_FOR_SEQ_TO_SEQ_CAUSAL_LM_MAPPING,TF_MODEL_FOR_SEQUENCE_CLASSIFICATION_MAPPING%TF_MODEL_FOR_SPEECH_SEQ_2_SEQ_MAPPING-TF_MODEL_FOR_TABLE_QUESTION_ANSWERING_MAPPING"TF_MODEL_FOR_TEXT_ENCODING_MAPPING)TF_MODEL_FOR_TOKEN_CLASSIFICATION_MAPPING!TF_MODEL_FOR_VISION_2_SEQ_MAPPING3TF_MODEL_FOR_ZERO_SHOT_IMAGE_CLASSIFICATION_MAPPINGTF_MODEL_MAPPINGTF_MODEL_WITH_LM_HEAD_MAPPINGTFAutoModel!TFAutoModelForAudioClassificationTFAutoModelForCausalLM'TFAutoModelForDocumentQuestionAnswering!TFAutoModelForImageClassification!TFAutoModelForMaskedImageModelingTFAutoModelForMaskedLMTFAutoModelForMaskGenerationTFAutoModelForMultipleChoice$TFAutoModelForNextSentencePredictionTFAutoModelForPreTrainingTFAutoModelForQuestionAnswering"TFAutoModelForSemanticSegmentationTFAutoModelForSeq2SeqLM$TFAutoModelForSequenceClassificationTFAutoModelForSpeechSeq2Seq$TFAutoModelForTableQuestionAnsweringTFAutoModelForTextEncoding!TFAutoModelForTokenClassificationTFAutoModelForVision2Seq)TFAutoModelForZeroShotImageClassificationTFAutoModelWithLMHead)TFBartForConditionalGenerationTFBartForSequenceClassificationTFBartModelTFBartPretrainedModel)TFBertForMaskedLMTFBertForMultipleChoiceTFBertForNextSentencePredictionTFBertForPreTrainingTFBertForQuestionAnsweringTFBertForSequenceClassificationTFBertForTokenClassificationTFBertLMHeadModelTFBertMainLayerTFBertModelTFBertPreTrainedModel)$TFBlenderbotForConditionalGenerationTFBlenderbotModelTFBlenderbotPreTrainedModel))TFBlenderbotSmallForConditionalGenerationTFBlenderbotSmallModel TFBlenderbotSmallPreTrainedModel)TFBlipForConditionalGenerationTFBlipForImageTextRetrievalTFBlipForQuestionAnsweringTFBlipModelTFBlipPreTrainedModelTFBlipTextModelTFBlipVisionModel)TFCamembertForCausalLMTFCamembertForMaskedLMTFCamembertForMultipleChoiceTFCamembertForQuestionAnswering$TFCamembertForSequenceClassification!TFCamembertForTokenClassificationTFCamembertModelTFCamembertPreTrainedModel)TFCLIPModelTFCLIPPreTrainedModelTFCLIPTextModelTFCLIPVisionModel)TFConvBertForMaskedLMTFConvBertForMultipleChoiceTFConvBertForQuestionAnswering#TFConvBertForSequenceClassification TFConvBertForTokenClassificationTFConvBertModelTFConvBertPreTrainedModel) TFConvNextForImageClassificationTFConvNextModelTFConvNextPreTrainedModel)"TFConvNextV2ForImageClassificationTFConvNextV2ModelTFConvNextV2PreTrainedModel)TFCTRLForSequenceClassificationTFCTRLLMHeadModelTFCTRLModelTFCTRLPreTrainedModel)TFCvtForImageClassification
TFCvtModelTFCvtPreTrainedModel)&TFData2VecVisionForImageClassification'TFData2VecVisionForSemanticSegmentationTFData2VecVisionModelTFData2VecVisionPreTrainedModel)TFDebertaForMaskedLMTFDebertaForQuestionAnswering"TFDebertaForSequenceClassificationTFDebertaForTokenClassificationTFDebertaModelTFDebertaPreTrainedModel)TFDebertaV2ForMaskedLMTFDebertaV2ForMultipleChoiceTFDebertaV2ForQuestionAnswering$TFDebertaV2ForSequenceClassification!TFDebertaV2ForTokenClassificationTFDebertaV2ModelTFDebertaV2PreTrainedModel)TFDeiTForImageClassification'TFDeiTForImageClassificationWithTeacherTFDeiTForMaskedImageModelingTFDeiTModelTFDeiTPreTrainedModel)'TFEfficientFormerForImageClassification2TFEfficientFormerForImageClassificationWithTeacherTFEfficientFormerModel TFEfficientFormerPreTrainedModel)TFAdaptiveEmbedding$TFTransfoXLForSequenceClassificationTFTransfoXLLMHeadModelTFTransfoXLMainLayerTFTransfoXLModelTFTransfoXLPreTrainedModel)TFDistilBertForMaskedLMTFDistilBertForMultipleChoice TFDistilBertForQuestionAnswering%TFDistilBertForSequenceClassification"TFDistilBertForTokenClassificationTFDistilBertMainLayerTFDistilBertModelTFDistilBertPreTrainedModel)TFDPRContextEncoderTFDPRPretrainedContextEncoderTFDPRPretrainedQuestionEncoderTFDPRPretrainedReaderTFDPRQuestionEncoderTFDPRReader)TFElectraForMaskedLMTFElectraForMultipleChoiceTFElectraForPreTrainingTFElectraForQuestionAnswering"TFElectraForSequenceClassificationTFElectraForTokenClassificationTFElectraModelTFElectraPreTrainedModelTFEncoderDecoderModel)TFEsmForMaskedLMTFEsmForSequenceClassificationTFEsmForTokenClassification
TFEsmModelTFEsmPreTrainedModel)TFFlaubertForMultipleChoice$TFFlaubertForQuestionAnsweringSimple#TFFlaubertForSequenceClassification TFFlaubertForTokenClassificationTFFlaubertModelTFFlaubertPreTrainedModelTFFlaubertWithLMHeadModel)	TFFunnelBaseModelTFFunnelForMaskedLMTFFunnelForMultipleChoiceTFFunnelForPreTrainingTFFunnelForQuestionAnswering!TFFunnelForSequenceClassificationTFFunnelForTokenClassificationTFFunnelModelTFFunnelPreTrainedModel)TFGPT2DoubleHeadsModelTFGPT2ForSequenceClassificationTFGPT2LMHeadModelTFGPT2MainLayerTFGPT2ModelTFGPT2PreTrainedModel)TFGPTJForCausalLMTFGPTJForQuestionAnsweringTFGPTJForSequenceClassificationTFGPTJModelTFGPTJPreTrainedModel)TFGroupViTModelTFGroupViTPreTrainedModelTFGroupViTTextModelTFGroupViTVisionModel)TFHubertForCTCTFHubertModelTFHubertPreTrainedModel)TFIdeficsForVisionText2TextTFIdeficsModelTFIdeficsPreTrainedModel)TFLayoutLMForMaskedLMTFLayoutLMForQuestionAnswering#TFLayoutLMForSequenceClassification TFLayoutLMForTokenClassificationTFLayoutLMMainLayerTFLayoutLMModelTFLayoutLMPreTrainedModel) TFLayoutLMv3ForQuestionAnswering%TFLayoutLMv3ForSequenceClassification"TFLayoutLMv3ForTokenClassificationTFLayoutLMv3ModelTFLayoutLMv3PreTrainedModel)TFLEDForConditionalGeneration
TFLEDModelTFLEDPreTrainedModel)TFLongformerForMaskedLMTFLongformerForMultipleChoice TFLongformerForQuestionAnswering%TFLongformerForSequenceClassification"TFLongformerForTokenClassificationTFLongformerModelTFLongformerPreTrainedModel)TFLxmertForPreTrainingTFLxmertMainLayerTFLxmertModelTFLxmertPreTrainedModelTFLxmertVisualFeatureEncoder)TFMarianModelTFMarianMTModelTFMarianPreTrainedModel)TFMBartForConditionalGenerationTFMBartModelTFMBartPreTrainedModel)TFMistralForCausalLM"TFMistralForSequenceClassificationTFMistralModelTFMistralPreTrainedModel)
TFMobileBertForMaskedLMTFMobileBertForMultipleChoice%TFMobileBertForNextSentencePredictionTFMobileBertForPreTraining TFMobileBertForQuestionAnswering%TFMobileBertForSequenceClassification"TFMobileBertForTokenClassificationTFMobileBertMainLayerTFMobileBertModelTFMobileBertPreTrainedModel)!TFMobileViTForImageClassification"TFMobileViTForSemanticSegmentationTFMobileViTModelTFMobileViTPreTrainedModel)TFMPNetForMaskedLMTFMPNetForMultipleChoiceTFMPNetForQuestionAnswering TFMPNetForSequenceClassificationTFMPNetForTokenClassificationTFMPNetMainLayerTFMPNetModelTFMPNetPreTrainedModel)TFMT5EncoderModelTFMT5ForConditionalGeneration
TFMT5Model)TFOpenAIGPTDoubleHeadsModel$TFOpenAIGPTForSequenceClassificationTFOpenAIGPTLMHeadModelTFOpenAIGPTMainLayerTFOpenAIGPTModelTFOpenAIGPTPreTrainedModel)TFOPTForCausalLM
TFOPTModelTFOPTPreTrainedModel)!TFPegasusForConditionalGenerationTFPegasusModelTFPegasusPreTrainedModel)
TFRagModelTFRagPreTrainedModelTFRagSequenceForGenerationTFRagTokenForGeneration)TFRegNetForImageClassificationTFRegNetModelTFRegNetPreTrainedModel)TFRemBertForCausalLMTFRemBertForMaskedLMTFRemBertForMultipleChoiceTFRemBertForQuestionAnswering"TFRemBertForSequenceClassificationTFRemBertForTokenClassificationTFRemBertModelTFRemBertPreTrainedModel)TFResNetForImageClassificationTFResNetModelTFResNetPreTrainedModel)	TFRobertaForCausalLMTFRobertaForMaskedLMTFRobertaForMultipleChoiceTFRobertaForQuestionAnswering"TFRobertaForSequenceClassificationTFRobertaForTokenClassificationTFRobertaMainLayerTFRobertaModelTFRobertaPreTrainedModel)	 TFRobertaPreLayerNormForCausalLM TFRobertaPreLayerNormForMaskedLM&TFRobertaPreLayerNormForMultipleChoice)TFRobertaPreLayerNormForQuestionAnswering.TFRobertaPreLayerNormForSequenceClassification+TFRobertaPreLayerNormForTokenClassificationTFRobertaPreLayerNormMainLayerTFRobertaPreLayerNormModel$TFRobertaPreLayerNormPreTrainedModel)TFRoFormerForCausalLMTFRoFormerForMaskedLMTFRoFormerForMultipleChoiceTFRoFormerForQuestionAnswering#TFRoFormerForSequenceClassification TFRoFormerForTokenClassificationTFRoFormerModelTFRoFormerPreTrainedModel
TFSamModelTFSamPreTrainedModel)TFSegformerDecodeHead!TFSegformerForImageClassification"TFSegformerForSemanticSegmentationTFSegformerModelTFSegformerPreTrainedModel)%TFSpeech2TextForConditionalGenerationTFSpeech2TextModelTFSpeech2TextPreTrainedModel)#TFSwiftFormerForImageClassificationTFSwiftFormerModelTFSwiftFormerPreTrainedModel)TFSwinForImageClassificationTFSwinForMaskedImageModelingTFSwinModelTFSwinPreTrainedModel)TFT5EncoderModelTFT5ForConditionalGeneration	TFT5ModelTFT5PreTrainedModel)TFTapasForMaskedLMTFTapasForQuestionAnswering TFTapasForSequenceClassificationTFTapasModelTFTapasPreTrainedModelTFVisionEncoderDecoderModelTFVisionTextDualEncoderModel)TFViTForImageClassification
TFViTModelTFViTPreTrainedModel)TFViTMAEForPreTrainingTFViTMAEModelTFViTMAEPreTrainedModel)TFWav2Vec2ForCTC#TFWav2Vec2ForSequenceClassificationTFWav2Vec2ModelTFWav2Vec2PreTrainedModel)!TFWhisperForConditionalGenerationTFWhisperModelTFWhisperPreTrainedModel)TFXGLMForCausalLMTFXGLMModelTFXGLMPreTrainedModel)TFXLMForMultipleChoiceTFXLMForQuestionAnsweringSimpleTFXLMForSequenceClassificationTFXLMForTokenClassificationTFXLMMainLayer
TFXLMModelTFXLMPreTrainedModelTFXLMWithLMHeadModel)TFXLMRobertaForCausalLMTFXLMRobertaForMaskedLMTFXLMRobertaForMultipleChoice TFXLMRobertaForQuestionAnswering%TFXLMRobertaForSequenceClassification"TFXLMRobertaForTokenClassificationTFXLMRobertaModelTFXLMRobertaPreTrainedModel)TFXLNetForMultipleChoice!TFXLNetForQuestionAnsweringSimple TFXLNetForSequenceClassificationTFXLNetForTokenClassificationTFXLNetLMHeadModelTFXLNetMainLayerTFXLNetModelTFXLNetPreTrainedModel)AdamWeightDecayGradientAccumulatorWarmUpcreate_optimizeroptimization_tftf_utils)dummy_tf_objectsc                 <    g | ]}|                     d           |S r  r  r  s     r  r  r    r	  r  zutils.dummy_tf_objectsPop2PianoFeatureExtractorPop2PianoTokenizerPop2PianoProcessor)Fdummy_essentia_and_librosa_and_pretty_midi_and_scipy_and_torch_objectsc                 <    g | ]}|                     d           |S r  r  r  s     r  r  r    sA     i i is##ii i ir  zLutils.dummy_essentia_and_librosa_and_pretty_midi_and_scipy_and_torch_objectsMusicgenMelodyFeatureExtractorMusicgenMelodyProcessor)dummy_torchaudio_objectsc                 <    g | ]}|                     d           |S r  r  r  s     r  r  r    rK  r  zutils.dummy_torchaudio_objects)!FlaxForcedBOSTokenLogitsProcessor!FlaxForcedEOSTokenLogitsProcessorFlaxForceTokensLogitsProcessorFlaxGenerationMixinFlaxLogitsProcessorFlaxLogitsProcessorListFlaxLogitsWarperFlaxMinLengthLogitsProcessorFlaxTemperatureLogitsWarper(FlaxSuppressTokensAtBeginLogitsProcessor!FlaxSuppressTokensLogitsProcessorFlaxTopKLogitsWarperFlaxTopPLogitsWarper#FlaxWhisperTimeStampLogitsProcessormodeling_flax_outputsFlaxPreTrainedModelmodeling_flax_utils)FlaxAlbertForMaskedLMFlaxAlbertForMultipleChoiceFlaxAlbertForPreTrainingFlaxAlbertForQuestionAnswering#FlaxAlbertForSequenceClassification FlaxAlbertForTokenClassificationFlaxAlbertModelFlaxAlbertPreTrainedModel)+FLAX_MODEL_FOR_AUDIO_CLASSIFICATION_MAPPING FLAX_MODEL_FOR_CAUSAL_LM_MAPPING+FLAX_MODEL_FOR_IMAGE_CLASSIFICATION_MAPPING FLAX_MODEL_FOR_MASKED_LM_MAPPING&FLAX_MODEL_FOR_MULTIPLE_CHOICE_MAPPING/FLAX_MODEL_FOR_NEXT_SENTENCE_PREDICTION_MAPPING"FLAX_MODEL_FOR_PRETRAINING_MAPPING)FLAX_MODEL_FOR_QUESTION_ANSWERING_MAPPING+FLAX_MODEL_FOR_SEQ_TO_SEQ_CAUSAL_LM_MAPPING.FLAX_MODEL_FOR_SEQUENCE_CLASSIFICATION_MAPPING'FLAX_MODEL_FOR_SPEECH_SEQ_2_SEQ_MAPPING+FLAX_MODEL_FOR_TOKEN_CLASSIFICATION_MAPPING#FLAX_MODEL_FOR_VISION_2_SEQ_MAPPINGFLAX_MODEL_MAPPINGFlaxAutoModelFlaxAutoModelForCausalLM#FlaxAutoModelForImageClassificationFlaxAutoModelForMaskedLMFlaxAutoModelForMultipleChoice&FlaxAutoModelForNextSentencePredictionFlaxAutoModelForPreTraining!FlaxAutoModelForQuestionAnsweringFlaxAutoModelForSeq2SeqLM&FlaxAutoModelForSequenceClassificationFlaxAutoModelForSpeechSeq2Seq#FlaxAutoModelForTokenClassificationFlaxAutoModelForVision2Seq)FlaxBartDecoderPreTrainedModelFlaxBartForCausalLM FlaxBartForConditionalGenerationFlaxBartForQuestionAnswering!FlaxBartForSequenceClassificationFlaxBartModelFlaxBartPreTrainedModel)FlaxBeitForImageClassificationFlaxBeitForMaskedImageModelingFlaxBeitModelFlaxBeitPreTrainedModel)
FlaxBertForCausalLMFlaxBertForMaskedLMFlaxBertForMultipleChoice!FlaxBertForNextSentencePredictionFlaxBertForPreTrainingFlaxBertForQuestionAnswering!FlaxBertForSequenceClassificationFlaxBertForTokenClassificationFlaxBertModelFlaxBertPreTrainedModel)	FlaxBigBirdForCausalLMFlaxBigBirdForMaskedLMFlaxBigBirdForMultipleChoiceFlaxBigBirdForPreTrainingFlaxBigBirdForQuestionAnswering$FlaxBigBirdForSequenceClassification!FlaxBigBirdForTokenClassificationFlaxBigBirdModelFlaxBigBirdPreTrainedModel)&FlaxBlenderbotForConditionalGenerationFlaxBlenderbotModelFlaxBlenderbotPreTrainedModel)+FlaxBlenderbotSmallForConditionalGenerationFlaxBlenderbotSmallModel"FlaxBlenderbotSmallPreTrainedModel)FlaxBloomForCausalLMFlaxBloomModelFlaxBloomPreTrainedModel)FlaxCLIPModelFlaxCLIPPreTrainedModelFlaxCLIPTextModelFlaxCLIPTextPreTrainedModelFlaxCLIPTextModelWithProjectionFlaxCLIPVisionModelFlaxCLIPVisionPreTrainedModel)FlaxDinov2Model FlaxDinov2ForImageClassificationFlaxDinov2PreTrainedModel)FlaxDistilBertForMaskedLMFlaxDistilBertForMultipleChoice"FlaxDistilBertForQuestionAnswering'FlaxDistilBertForSequenceClassification$FlaxDistilBertForTokenClassificationFlaxDistilBertModelFlaxDistilBertPreTrainedModel)	FlaxElectraForCausalLMFlaxElectraForMaskedLMFlaxElectraForMultipleChoiceFlaxElectraForPreTrainingFlaxElectraForQuestionAnswering$FlaxElectraForSequenceClassification!FlaxElectraForTokenClassificationFlaxElectraModelFlaxElectraPreTrainedModelFlaxEncoderDecoderModel)FlaxGPT2LMHeadModelFlaxGPT2ModelFlaxGPT2PreTrainedModel)FlaxGPTNeoForCausalLMFlaxGPTNeoModelFlaxGPTNeoPreTrainedModel)FlaxGPTJForCausalLMFlaxGPTJModelFlaxGPTJPreTrainedModel)FlaxLlamaForCausalLMFlaxLlamaModelFlaxLlamaPreTrainedModel)FlaxGemmaForCausalLMFlaxGemmaModelFlaxGemmaPreTrainedModel)"FlaxLongT5ForConditionalGenerationFlaxLongT5ModelFlaxLongT5PreTrainedModel)FlaxMarianModelFlaxMarianMTModelFlaxMarianPreTrainedModel)!FlaxMBartForConditionalGenerationFlaxMBartForQuestionAnswering"FlaxMBartForSequenceClassificationFlaxMBartModelFlaxMBartPreTrainedModel)FlaxMistralForCausalLMFlaxMistralModelFlaxMistralPreTrainedModel)FlaxMT5EncoderModelFlaxMT5ForConditionalGenerationFlaxMT5Model)FlaxOPTForCausalLMFlaxOPTModelFlaxOPTPreTrainedModel)#FlaxPegasusForConditionalGenerationFlaxPegasusModelFlaxPegasusPreTrainedModel) FlaxRegNetForImageClassificationFlaxRegNetModelFlaxRegNetPreTrainedModel) FlaxResNetForImageClassificationFlaxResNetModelFlaxResNetPreTrainedModel)FlaxRobertaForCausalLMFlaxRobertaForMaskedLMFlaxRobertaForMultipleChoiceFlaxRobertaForQuestionAnswering$FlaxRobertaForSequenceClassification!FlaxRobertaForTokenClassificationFlaxRobertaModelFlaxRobertaPreTrainedModel)"FlaxRobertaPreLayerNormForCausalLM"FlaxRobertaPreLayerNormForMaskedLM(FlaxRobertaPreLayerNormForMultipleChoice+FlaxRobertaPreLayerNormForQuestionAnswering0FlaxRobertaPreLayerNormForSequenceClassification-FlaxRobertaPreLayerNormForTokenClassificationFlaxRobertaPreLayerNormModel&FlaxRobertaPreLayerNormPreTrainedModel)FlaxRoFormerForMaskedLMFlaxRoFormerForMultipleChoice FlaxRoFormerForQuestionAnswering%FlaxRoFormerForSequenceClassification"FlaxRoFormerForTokenClassificationFlaxRoFormerModelFlaxRoFormerPreTrainedModelFlaxSpeechEncoderDecoderModel)FlaxT5EncoderModelFlaxT5ForConditionalGenerationFlaxT5ModelFlaxT5PreTrainedModelFlaxVisionEncoderDecoderModelFlaxVisionTextDualEncoderModel)FlaxViTForImageClassificationFlaxViTModelFlaxViTPreTrainedModel)FlaxWav2Vec2ForCTCFlaxWav2Vec2ForPreTrainingFlaxWav2Vec2ModelFlaxWav2Vec2PreTrainedModel)#FlaxWhisperForConditionalGenerationFlaxWhisperModelFlaxWhisperPreTrainedModel!FlaxWhisperForAudioClassification)FlaxXGLMForCausalLMFlaxXGLMModelFlaxXGLMPreTrainedModel)FlaxXLMRobertaForMaskedLMFlaxXLMRobertaForMultipleChoice"FlaxXLMRobertaForQuestionAnswering'FlaxXLMRobertaForSequenceClassification$FlaxXLMRobertaForTokenClassificationFlaxXLMRobertaModelFlaxXLMRobertaForCausalLMFlaxXLMRobertaPreTrainedModel)dummy_flax_objectsc                 <    g | ]}|                     d           |S r  r  r  s     r  r  r    s9     5 5 58L8L55 5 5r  zutils.dummy_flax_objects)r0   )rV   )rX   rY   )ra   )rq   )r{   )r   r   )r   )r   r   )r   )r   )r   )r   )r   )r   r   )r   )r   r   )r   r   )r   )r   r   )r   )r   )r   r   )r   r   )r   )r   )r   r   )r   )r   )r   r   )r   r   )r   )r   r   )r   )r   r   )r   )r   )r   )r   )r   )r   )r   )r   r   )r   )r   )r   )r  )r  )r  )r  )r  r  )r  r  )r  )r  )r  )r  )r  )r  )r  )r  )r  )r  r  )r  r  )r$  )r%  )r&  r'  )r(  r)  )r*  )r+  )r,  r-  )r.  )r/  )r4  r5  )r;  )r<  )r=  r>  )r?  r@  )rA  )rB  )rC  )rG  )rH  )rI  rJ  )rK  )rL  )rM  )rN  )rO  )rP  )rQ  )rR  rS  )rW  )rX  )rY  )rZ  )r[  )r\  )r]  )r^  )r_  )rh  )ri  )rj  rk  )rl  rm  )rx  )ry  rz  )r{  )r|  )r}  )r~  r  )r  r  )r  r  )r  r  )r  r  )r  )r  r  )r  r  )r  )r  )r  )r  )r  )r  r  )r  )r  )r  )r  )r  )r  r  )r  r  )r  )r  )r  )r  )r  r  )r  r  )r  )r  )r  )r  r  )r  r  )r  r  )r  )r  )r  )r  )r  )r  )r  )r  r  )r  r  )r  r  )r  )r  )r  )r  )r  r  )r  )r  r  )r  )r  )r  )r  )r  )r  r  )r  )r  )r  )r  r  )r  )r  )r  r  )r  )r  r  )r  )r  )r  )r  )r  )r  r  )r  )r  r  )r  r  )r  r  )r  )r  )r  )r	  )r
  )r  )r  )r  r  )r  r  )r  )r  )r  )r  )r   )r!  )r"  )r#  )r$  )r%  )r&  r'  )r(  )r)  )r*  )r+  r,  )r-  r.  )r/  r0  )r1  )r2  )r3  )r4  r5  )r6  )r7  )r8  )r=  )r>  )r?  r@  )rA  )rB  )rC  )rD  )rE  )rF  )rG  rH  )rI  )rO  rP  )rQ  )rR  )rS  )rT  )r]  )r^  r_  )r`  )ra  )rb  )rc  )rd  )re  )rf  )rg  )r  )r  )r  )r  )r  ),r  r  r  r  r  r  r  r  r  r  r  r  r  r  r   r  r  r
   r   r  r  r  r  r  r  r   r   r  r   r   r   r   r   r   r  r  r  r  r  r  r  r   r   r   )r  )r  )r  )r  )r  )r  )r  )r  )r  )r  )r  )r  )r  )r  )r  )r  )r  )r  )r  )r  )r  )r  )r  )r  )r  )r  )r  )r  )r  )r  )r  )r  )r  )r  )r  )r  )*)r  )r  )r	  )r
  )r  )r  )r  )r  )r  )r  )r  )r  )r  )r  )r  )r  )r  )r  )r  )r  )r  )r  )r   )r!  )r"  )r#  )r$  )r%  )r&  )r'  )r(  )r)  )r*  )r+  )r,  )r-  )r.  )r/  )r0  )r1  )r2  )r3  )r4  )r5  )r6  )r7  )r8  )r9  )r:  )r;  )r<  )r=  )r>  )r?  )r@  )rA  )rB  )rC  )rD  )rE  )rF  )rG  )rL  rM  )rP  )rS  )rV  )rX  )rZ  )r\  r]  )r^  )r_  )r`  )ra  )rb  rc  )rd  re  )rf  rg  )rh  ri  )rj  rk  )rl  rm  )rn  )ro  )rp  )rq  )ru  rv  )rw  rx  )ry  )r}  r~  )r  r  )r  )r  )r  )r  )r  r  )r  )ro  rp  )rt  ru  )r  r  )r  )r  )r  r  )r  )r  r  )r  )r  r  )r  r  )r  r  )r  )r  )r  )r  r  )r  r  )r  )r  )r  r  )r  )r  )r  )r  )r  r  )r  )r  )r  )r  )r  )r  )r  r  )r  r  )r  )r  )r  r  )r  )r  )r  )r  )r  )r  r  )r  )r  )Rr+  r,  r-  r.  r/  r0  r1  r2  r3  r4  r5  r6  r7  r8  r9  r:  r=  r;  r<  r>  r?  r@  rA  rB  rC  rD  rE  rF  rG  rH  rI  rJ  rK  rL  rM  rN  rO  rP  rQ  rR  rS  rT  rU  rV  rW  rX  rY  rZ  r[  r\  r]  r^  r_  r`  ra  rb  rc  rd  re  rf  rg  rh  ri  rj  rk  rl  rm  rn  ro  rp  rq  rr  rs  rt  ru  rv  rw  rx  ry  rz  r{  r|  )r  r  r  r  r  r  r  r  )r7  r8  )r  r  )r  r  )r  r  )r  r  )r  r  )r  r  )r  )rF  rG  )r  r  )r  r  )r  r  )r  r  )r7  r8  )r  r  )r  r  )r  r  )rn  ro  )r  )r  r  )r  )r  r  )r 	  )r	  r	  )r	  r	  )r	  )r	  )r)	  r*	  )r+	  r,	  )r	  r	  )r	  )r	  )r	  )r	  )r	  )r	  r	  ),r	  r	  r	  r	  r	  r	  r	  r	  r	  r	  r	  r	  r	  r	  r	  r	  r	  r	  r	  r	  r	  r	  r	  r	  r	  r	  r	  r	  r	  r	  r	  r	  r	  r	  r	  r	  r	  r	  r	  r	  r	  r	  r	  r	  )rn
  )r  r  )r)  )r*  )r[  r]  r\  )r`  ra  )rd  re  rf  rg  rh  ri  rj  rk  rm  rn  rl  ro  rp  rq  )rs  )r  r  r  r  r  r  r  )r  r  r  )r  )r  )r"  )r#  )r.  r+  r,  r-  )r8  r2  r3  r4  r5  r6  r7  r9  N__file____version__)module_specextra_objectszNone of PyTorch, TensorFlow >= 2.0, or Flax have been found. Models won't be available and only tokenizers, configuration and file/data utilities can be used.(M  r>  typingr    r   r  r   r   r   r	   r
   r   r   r   r   r   r   r   r   r   r   r   r   r   r   r   r   
get_logger__name__logger_import_structureappendr  dirextendrI  rN  rQ  rT  r  r  r	  rY  r^  rb  r:  r   r   r   r   r   r    r!   r"   r#   r$   r%   r&   r'   r(   r)   r*   r+   r/   r0   r4   r5   r6   r7   r8   r9   r:   r;   r<   r=   r>   r?   r@   rA   rB   rC   rD   rE   rF   data.data_collatorrG   rH   rI   rJ   rK   rL   rM   rN   rO   rP   rQ   rU   rV   rW   rX   rY   r[   r\   r]   r^   r_   r`   ra   rd   re   rf   rg   rh   ri   rj   rk   rl   rm   rn   rp   rq   rr   rs   rt   ru   rv   rw   rx   ry   models.albertr{   models.alignr|   r}   r~   r   models.altclipr   r   r   r   $models.audio_spectrogram_transformerr   r   models.autor   r   r   r   r   r   r   r   r   r   r   models.autoformerr   models.barkr   r   r   r   r   models.bartr   r   models.beitr   models.bertr   r   r   r   models.bert_generationr   models.bert_japaneser   r   r   models.bertweetr   models.big_birdr   models.bigbird_pegasusr   models.biogptr   r   
models.bitr   models.blenderbotr   r   models.blenderbot_smallr   r   models.blipr   r   r   r   models.blip_2r   r   r   r   models.bloomr   models.bridgetowerr   r   r   r   models.brosr   r   models.byt5r   models.camembertr   models.caniner   r   models.chameleonr   r   r   models.chinese_clipr   r   r   r   models.clapr   r   r   r   models.clipr   r   r   r   r   models.clipsegr   r   r   r   models.clvpr   r   r   r   r   r   models.codegenr   r   models.coherer   models.conditional_detrr   models.convbertr   r   models.convnextr   models.convnextv2r   models.cpmantr   r   models.ctrlr   r   
models.cvtr   
models.dacr   r   models.data2vecr   r   r   models.dbrxr   models.debertar   r   models.deberta_v2r   models.decision_transformerr   models.deformable_detrr   models.deitr   models.deprecated.detar   !models.deprecated.efficientformerr   models.deprecated.ernie_mr   !models.deprecated.gptsan_japaneser   r   models.deprecated.graphormerr   models.deprecated.jukeboxr   r   r   r   models.deprecated.mctctr   r   r   models.deprecated.megar   models.deprecated.mmbtr   models.deprecated.natr  models.deprecated.nezhar  models.deprecated.open_llamar  models.deprecated.qdqbertr  models.deprecated.realmr  r  models.deprecated.retribertr  r  "models.deprecated.speech_to_text_2r	  r
  r  models.deprecated.tapexr  (models.deprecated.trajectory_transformerr  models.deprecated.transfo_xlr  r  r  models.deprecated.tvltr  r  r  models.deprecated.vanr  models.deprecated.vit_hybridr   models.deprecated.xlm_prophetnetr  models.depth_anythingr  models.detrr  models.dinatr  models.dinov2r  models.distilbertr  r  models.donutr  r  
models.dprr  r   r!  r"  r#  
models.dptr$  models.efficientnetr%  models.electrar&  r'  models.encodecr(  r)  models.encoder_decoderr*  models.ernier+  
models.esmr,  r-  models.falconr.  models.falcon_mambar/  models.fastspeech2_conformerr0  r1  r2  r3  models.flaubertr4  r5  models.flavar6  r7  r8  r9  r:  models.fnetr;  models.focalnetr<  models.fsmtr=  r>  models.funnelr?  r@  models.fuyurA  models.gemmarB  models.gemma2rC  
models.gitrD  rE  rF  
models.glmrG  models.glpnrH  models.gpt2rI  rJ  models.gpt_bigcoderK  models.gpt_neorL  models.gpt_neoxrM  models.gpt_neox_japaneserN  models.gptjrO  models.graniterP  models.granitemoerQ  models.grounding_dinorR  rS  models.groupvitrT  rU  rV  models.herbertrW  models.hierarX  models.hubertrY  models.ibertrZ  models.ideficsr[  models.idefics2r\  models.idefics3r]  models.imagegptr^  models.informerr_  models.instructblipr`  ra  rb  rc  models.instructblipvideord  re  rf  rg  models.jambarh  models.jetmoeri  models.kosmos2rj  rk  models.layoutlmrl  rm  models.layoutlmv2rn  ro  rp  rq  rr  models.layoutlmv3rs  rt  ru  rv  rw  models.layoutxlmrx  
models.ledry  rz  models.levitr{  models.liltr|  models.llamar}  models.llavar~  r  models.llava_nextr  r  models.llava_next_videor  r  models.llava_onevisionr  r  models.longformerr  r  models.longt5r  models.luker  r  models.lxmertr  r  models.m2m_100r  models.mambar  models.mamba2r  models.marianr  models.markuplmr  r  r  r  models.mask2formerr  models.maskformerr  r  models.mbartr  models.megatron_bertr  models.mgp_strr  r  r  models.mimir  models.mistralr  models.mixtralr  models.mllamar  r  models.mobilebertr  r  models.mobilenet_v1r  models.mobilenet_v2r  models.mobilevitr  models.mobilevitv2r  models.moshir  r  models.mpnetr  r  
models.mptr  
models.mrar  
models.mt5r  models.musicgenr  r  models.musicgen_melodyr  r  
models.mvpr  r  models.myt5r  models.nemotronr  models.nllb_moer  models.nougatr  models.nystromformerr  models.olmor  models.olmoer  models.omdet_turbor  r  models.oneformerr  r  models.openair  r  
models.optr  models.owlv2r  r  r  r  models.owlvitr  r  r  r  models.paligemmar  models.patchtsmixerr  models.patchtstr  models.pegasusr  r  models.pegasus_xr  models.perceiverr  r  models.persimmonr  
models.phir  models.phi3r  models.phimoer  models.phobertr  models.pix2structr  r  r  r  models.pixtralr  r  models.plbartr  models.poolformerr  models.pop2pianor  models.prophetnetr  r  
models.pvtr  models.pvt_v2r  models.qwen2r  r  models.qwen2_audior  r  r  models.qwen2_moer  models.qwen2_vlr  r  
models.ragr  r  r  models.recurrent_gemmar  models.reformerr  models.regnetr  models.rembertr  models.resnetr  models.robertar  r  models.roberta_prelayernormr  models.roc_bertr  r  models.roformerr  r  models.rt_detrr  r  models.rwkvr  
models.samr  r   r  r  r  models.seamless_m4tr  r  r  models.seamless_m4t_v2r  models.segformerr  models.seggptr	  
models.sewr
  models.sew_dr  models.siglipr  r  r  r  models.speech_encoder_decoderr  models.speech_to_textr  r  r  models.speecht5r  r  r  r  models.splinterr  r  models.squeezebertr  r  models.stablelmr  models.starcoder2r  models.superpointr  models.swiftformerr  models.swinr   models.swin2srr!  models.swinv2r"  models.switch_transformersr#  	models.t5r$  models.table_transformerr%  models.tapasr&  r'  models.time_series_transformerr(  models.timesformerr)  models.timm_backboner*  models.trocrr+  r,  
models.tvpr-  r.  models.udopr/  r0  models.umt5r1  models.unispeechr2  models.unispeech_satr3  models.univnetr4  r5  models.upernetr6  models.video_llavar7  models.videomaer8  models.viltr9  r:  r;  r<  models.vipllavar=  models.vision_encoder_decoderr>  models.vision_text_dual_encoderr?  r@  models.visual_bertrA  
models.vitrB  models.vit_maerC  models.vit_msnrD  models.vitdetrE  models.vitmatterF  models.vitsrG  rH  models.vivitrI  models.wav2vec2rJ  rK  rL  rM  rN  models.wav2vec2_bertrO  rP  models.wav2vec2_conformerrQ  models.wav2vec2_phonemerR  models.wav2vec2_with_lmrS  models.wavlmrT  models.whisperrU  rV  rW  rX  models.x_cliprY  rZ  r[  r\  models.xglmr]  
models.xlmr^  r_  models.xlm_robertar`  models.xlm_roberta_xlra  models.xlnetrb  models.xmodrc  models.yolosrd  models.yosore  models.zambarf  models.zoedepthrg  ri  rj  rk  rl  rm  rn  ro  rp  rq  rr  rs  rt  ru  rv  rw  rx  ry  rz  r{  r|  r}  r~  r  r  r  r  r  r  r  r  r  r  r  r  r  r  r  r  r  r  r  r  r  r  r  r  r  r  r  r  r  r  r  r  r  r  r  r  r  r  r  r  r  r  r  r  r  r  r  r  r  r  r  r  r  r  r  r  r  r  r  r  r  r  r  r  r  r  r  r  r  r  r  r  r  r  r  utils.quantization_configr  r  r  r  r  r  r  r  r  r  r  r  models.barthezr  models.bartphor  r  r  r  models.code_llamar  
models.cpmr  r  r  r  r  r  models.gpt_sw3r  r  r  r  r  r  models.mbart50r  models.mluker  r  models.nllbr  r  r  r  r  r  r  r  r  r  r  r  r  !utils.dummy_sentencepiece_objectsr  r  r	  r
  r  r  r  r  r  r  r  r  r  r  r  r  r  r  r  r  r  r  r  r  r  r   r!  r"  r#  r$  r%  r&  r'  r(  r)  r*  r+  r,  r-  r.  r/  r0  r1  r2  r3  r4  r5  r6  r7  r8  r9  r:  r;  r<  r=  r>  r?  r@  rA  rB  rC  rD  rE  rF  rH  rG  utils.dummy_tokenizers_objectsrM  rL  2utils.dummies_sentencepiece_and_tokenizers_objectsrP  #utils.dummy_tensorflow_text_objectsrS  utils.dummy_keras_nlp_objectsrW  rV  rY  rX  r[  rZ  r\  r]  r^  r_  r`  ra  rb  rc  rd  re  rf  rg  rh  ri  rj  rk  rl  rm  rn  ro  rp  rq  rr  rs  rt  ru  rv  rw  rx  ry  rz  r{  r|  r}  r~  r  r  r  r  r  r  r  r  r  r  r  r  r  r  r  r  r  r  r  r  r  r  r  r  r  r  r  r  r  r  r  r  r  r  r  r  r  r  r  r  r  r  r  r  r  r  r  r  r  r  r  r  r  r  r  r  r  utils.dummy_vision_objectsr  r  r  utils.dummy_torchvision_objectsbenchmark.benchmarkr  benchmark.benchmark_argsr  r  r  r  r  r  r  r  r  r  r  r  r  r  r  r  r  data.datasetsr  r  r  r  r  r  r  r  r  r  r  r  r  r  r  r  r  r  r  r  r  r  r  r  r  r  r  r  r  r  r  r  r  r  r  r  r  r  r  r  r  r  r  r  r  r  r   r  r  r  r  r  r  r  r  r	  r
  r  r  r  r  integrations.executorchr  r  r  r  r  r  r  r  r  r  r  r  r  r  r  r   r!  r"  r#  r$  r%  r&  r'  r(  r)  r*  r+  r,  r-  r.  r/  r0  r1  r2  r3  r4  r5  r6  r7  r8  r9  r:  r=  r;  r<  r>  r?  r@  rA  rB  rC  rD  rE  rF  rG  rH  rI  rJ  rK  rL  rM  rN  rO  rP  rQ  rR  rS  rT  rU  rV  rW  rX  rY  rZ  r[  r\  r]  r^  r_  r`  ra  rb  rc  rd  re  rf  rg  rh  ri  rj  rk  rl  rm  rn  ro  rp  rq  rr  rs  rt  ru  rv  rw  rx  ry  rz  r{  r|  r}  r~  r  r  r  r  r  r  r  r  r  r  r  r  r  r  r  r  r  r  r  r  r  r  r  r  r  r  r  r  r  r  r  r  r  r  r  r  r  r  r  r  r  r  r  r  r  r  r  r  r  r  r  r  r  r  r  r  r  r  r  r  r  r  r  r  r  r  r  r  r  r  r  r  r  r  r  r  r  r  r  r  r  r  r  r  r  r  r  r  r  r  r  r  r  r  r  r  r  r  r  r  r  r  r  r  r  r  r  r  r  r  r  r  r  r  r  r  r  r  r  r  r  r  r  r  r  r  r  r  r  r   r  r  r  r  r  r  r  r  r	  r
  r  r  r  r  r  r  r  r  r  r  r  r  r  r  r  r  r  r  r  r  r  r   r!  r"  r#  r$  r%  r&  r'  r(  r)  r*  r+  r,  r-  r.  r/  r0  r1  r2  r3  r4  r5  r6  r7  r8  r9  r:  r;  r<  r=  r>  r?  r@  rA  rB  rC  rD  rE  rF  rG  rH  rI  rJ  rK  rL  rM  rN  rO  rP  rQ  rR  rS  rT  rU  rV  rW  rX  rY  rZ  r[  r\  r]  r^  r_  r`  ra  rb  rc  rd  re  rf  rg  rh  ri  rj  rk  rl  rm  rn  ro  rp  rq  rr  rs  rt  ru  rv  rw  rx  ry  rz  r{  r|  r}  r~  r  r  r  r  r  r  r  r  r  r  r  r  r  r  r  r  r  r  r  r  r  r  r  r  r  r  r  r  r  r  r  r  r  r  r  r  r  r  r  r  r  r  r  r  r  r  r  r  r  r  r  r  r  r  r  r  r  r  r  r  r  r  r  r  r  r  r  r  r  r  r  r  r  r  r  r  r  r  r  r  r  r  r  r  r  r  r  r  r  r  r  r  r  r  r  r  r  r  r  r  r  r  r  r  r  r  r  r  r  r  r  r  r  r  r  r  r  r  r  r  r  r  r  r  r  r  r  r  r  r   r  r  r  r  r  r  r  r  r	  r
  r  r  r  r  r  r  r  r  r  r  r  r  r  r  r  r  r  r  r  r  r  r   r!  r"  r#  r$  r%  r&  r'  r(  r)  r*  r+  r,  r-  r.  r/  r0  r1  r2  r3  r4  r5  r6  r7  r8  r9  r:  r;  r<  r=  r>  r?  r@  rA  rB  rC  rD  rE  rF  rG  rH  rI  rJ  rK  rL  rM  rN  rO  rP  rQ  rR  rS  rT  rU  rV  rW  rX  rY  rZ  r[  r\  r]  r^  r_  r`  ra  rb  rc  rd  re  rf  rg  rh  ri  rj  rk  rl  rm  rn  ro  rp  rq  rr  rs  rt  ru  rv  rw  rx  ry  rz  r{  r|  r}  r~  r  r  r  r  r  r  r  r  r  r  r  r  r  r  r  r  r  r  r  r  r  r  r  r  r  r  r  r  r  r  r  r  r  r  r  r  r  r  r  r  r  r  r  r  r  r  r  r  r  r  r  r  r  r  r  r  r  r  r  r  r  r  r  r  r  r  r  r  r  r  r  r  r  r  r  r  r  r  r  r  r  r  r  r  r  r  r  r  r  r  r  r  r  r  r  r  r  r  r  r  r  r  r  r  r  r  r  r  r  r  r  r  r  r  r  r  r  r  r  r  r  r  r  r  r  r  r  r  r  r   r  r  r  r  r  r  r  r  r	  r
  r  r  r  r  r  r  r  r  r  r  r  r  r  r  r  r  r  r  r  r  r  r   r!  r"  r#  r$  r%  r&  r'  r(  r)  r*  r+  r,  r-  r.  r/  r0  r1  r2  r3  r4  r5  r6  r7  r8  r9  r:  r;  r<  r=  r>  r?  r@  rA  rB  rC  rD  rE  rF  rG  rH  rI  rJ  rK  rL  rM  rN  rO  rP  rQ  rR  rS  rT  rU  rV  rW  rX  rY  rZ  r[  r\  r]  r^  r_  r`  ra  rb  rc  rd  re  rf  rg  rh  ri  rj  rk  rl  rm  rn  ro  rp  rq  rr  rs  rt  ru  rv  rw  rx  ry  rz  r{  r|  r}  r~  r  r  r  r  r  r  r  r  r  r  r  r  r  r  r  r  r  r  r  r  r  r  r  r  r  r  r  r  r  r  r  r  r  r  r  r  r  r  r  r  r  r  r  r  r  r  r  r  r  r  r  r  r  r  r  r  r  r  r  r  r  r  r  r  r  r  r  r  r  r  r  r  r  r  r  r  r  r  r  r  r  r  r  r  r  r  r  r  r  r  r  r  r  r  r  r  r  r  r  r  r  r  r  r  r  r  r  r  r  r  r  r  r  r  r  r  r  r  r  r  r  r  r  r  r  r  r  r  r  r   r  r  r  r  r  r  r  r  r	  r
  r  r  r  r  r  r  r  r  r  r  r  r  r  r  r  r  r  r  r  r  r  r   r!  r"  r#  r$  r%  r&  r'  r(  r)  r*  r+  r,  r-  r.  r/  r0  r1  r2  r3  r4  r5  r6  r7  r8  r9  r:  r;  r<  r=  r>  r?  r@  rA  rB  rC  rD  rE  rF  rG  rH  rI  rJ  rK  rL  rM  rN  rO  rP  rQ  rR  rS  rT  rU  rV  rW  rX  rY  rZ  r[  r\  r]  r^  r_  r`  ra  rb  rc  rd  re  rf  rg  rh  ri  rj  rk  rl  rm  rn  ro  rp  rq  rr  rs  rt  ru  rv  rw  rx  ry  rz  r{  r|  r}  r~  r  r  r  r  r  r  r  r  r  r  r  r  r  r  r  r  r  r  r  r  r  r  r  r  r  r  r  r  r  r  r  r  r  r  r  r  r  r  r  r  r  r  r  r  r  r  r  r  r  r  r  r  r  r  r  r  r  r  r  r  r  r  r  r  r  r  r  r  r  r  r  r  r  r  r  r  r  r  r  r  r  r  r  r  r  r  r  r  r  r  r  r  r  r  r  r  r  r  r  r  r  r  r  r  r  r  r  r  r  r  r  r  r  r  r  r  r  r  r  r  r  r  r  r  r  r  r  r  r  r 	  r	  r	  r	  r	  r	  r	  r	  r	  r		  r
	  r	  r	  r	  r	  r	  r	  r	  r	  r	  r	  r	  r	  r	  r	  r	  r	  r	  r	  r	  r	  r	  r 	  r!	  r"	  r#	  r$	  r%	  r&	  r'	  r(	  r)	  r*	  r+	  r,	  r-	  r.	  r/	  r0	  r1	  r2	  r3	  r4	  r5	  r6	  r7	  r8	  r9	  r:	  r;	  r<	  r=	  r>	  r?	  r@	  rA	  rB	  rC	  rD	  rE	  rF	  rG	  rH	  rI	  rJ	  rK	  rL	  rM	  rN	  rO	  rP	  rQ	  rR	  rS	  rT	  rU	  rV	  rW	  rX	  rY	  rZ	  r[	  r\	  r]	  r^	  r_	  r`	  ra	  rb	  rc	  rd	  re	  rf	  rg	  rh	  ri	  rj	  rk	  rl	  rm	  rn	  ro	  rp	  rq	  rr	  rs	  rt	  ru	  rv	  rw	  rx	  ry	  rz	  r{	  r|	  r}	  r~	  r	  r	  r	  r	  r	  r	  r	  r	  r	  r	  r	  r	  r	  r	  r	  r	  r	  r	  r	  r	  r	  r	  r	  r	  r	  r	  r	  r	  r	  r	  r	  r	  r	  r	  r	  r	  r	  r	  r	  utils.dummy_pt_objectsbenchmark.benchmark_args_tfr	  benchmark.benchmark_tfr	  r	  r	  r	  r	  r	  r	  r	  r	  r	  r	  r	  r	  r	  r	  r	  r	  r	  r	  r	  r	  r	  r	  r	  r	  r	  r	  r	  r	  r	  r	  r	  r	  r	  r	  r	  r	  r	  r	  r	  r	  r	  r	  r	  r	  r	  r	  r	  r	  r	  r	  r	  r	  r	  r	  r	  r	  r	  r	  r	  r	  r	  r	  r	  r	  r	  r	  r	  r	  r	  r	  r	  r	  r	  r	  r	  r	  r	  r	  r	  r	  r	  r 
  r
  r
  r
  r
  r
  r
  r
  r
  r	
  r

  r
  r
  r
  r
  r
  r
  r
  r
  r
  r
  r
  r
  r
  r
  r
  r
  r
  r
  r
  r
  r
  r 
  r!
  r"
  r#
  r$
  r%
  r&
  r'
  r(
  r)
  r*
  r+
  r,
  r-
  r.
  r/
  r0
  r1
  r2
  r3
  r4
  r5
  r6
  r7
  r8
  r9
  r:
  r;
  r<
  r=
  r>
  r?
  r@
  rA
  rB
  rC
  rD
  rE
  rF
  rG
  rH
  rI
  rJ
  rK
  rL
  rM
  rN
  rO
  rP
  rQ
  rR
  rS
  rT
  rU
  rV
  rW
  rX
  rY
  rZ
  r[
  r\
  r]
  r^
  r_
  r`
  ra
  rb
  rc
  rd
  re
  rf
  rg
  rh
  ri
  rj
  rk
  rl
  rm
  rn
  ro
  rp
  rq
  rr
  rs
  rt
  ru
  rv
  rw
  rx
  ry
  rz
  r{
  r|
  r}
  r~
  r
  r
  r
  r
  r
  r
  r
  r
  r
  r
  r
  r
  r
  r
  r
  r
  r
  r
  r
  r
  r
  r
  r
  r
  r
  r
  r
  r
  r
  r
  r
  r
  r
  r
  r
  r
  r
  r
  r
  r
  r
  r
  r
  r
  r
  r
  r
  r
  r
  r
  r
  r
  r
  r
  r
  r
  r
  r
  r
  r
  r
  r
  r
  r
  r
  r
  r
  r
  r
  r
  r
  r
  r
  r
  r
  r
  r
  r
  r
  r
  r
  r
  r
  r
  r
  r
  r
  r
  r
  r
  r
  r
  r
  r
  r
  r
  r
  r
  r
  r
  r
  r
  r
  r
  r
  r
  r
  r
  r
  r
  r
  r
  r
  r
  r
  r
  r
  r
  r
  r
  r
  r
  r
  r
  r
  r
  r
  r
  r
  r   r  r  r  r  r  r  r  r  r	  r
  r  r  r  r  r  r  r  r  r  r  r  r  r  r  r  r  r  r  r  r  r  r   r!  r"  r#  r$  r%  r&  r'  r(  r)  r*  r+  r,  r-  r.  r/  r0  r1  r2  r3  r4  r5  r6  r7  r8  r9  r:  r;  r<  r=  r>  r?  r@  rA  rB  rC  rD  rE  rF  rG  rH  rI  rJ  rK  rL  rM  rN  rO  rP  rQ  rR  rW  rS  rT  rU  rV  utils.dummy_tf_objectsr[  r]  r\  Lutils.dummy_essentia_and_librosa_and_pretty_midi_and_scipy_and_torch_objectsr`  ra  utils.dummy_torchaudio_objectsrd  re  rf  rg  rh  ri  rj  rk  rm  rn  rl  ro  rp  rq  rt  rs  ru  rv  rw  rx  ry  rz  r{  r|  r}  r~  r  r  r  r  r  r  r  r  r  r  r  r  r  r  r  r  r  r  r  r  r  r  r  r  r  r  r  r  r  r  r  r  r  r  r  r  r  r  r  r  r  r  r  r  r  r  r  r  r  r  r  r  r  r  r  r  r  r  r  r  r  r  r  r  r  r  r  r  r  r  r  r  r  r  r  r  r  r  r  r  r  r  r  r  r  r  r  r  r  r  r  r  r  r  r  r  r  r  r  r  r  r  r  r  r  r  r  r  r  r  r  r  r  r  r  r  r  r  r  r  r  r  r  r  r  r  r  r  r  r   r  r  r  r  r  r  r  r  r	  r
  r  r  r  r  r  r  r  r  r  r  r  r  r  r  r  r  r  r  r  r  r  r   r!  r"  r#  r$  r%  r&  r'  r(  r)  r*  r.  r+  r,  r-  r/  r0  r1  r8  r2  r3  r4  r5  r6  r7  r9  utils.dummy_flax_objectssysglobals__spec__moduleswarning_advice r  r  <module>r     s0 *              ( ' ' ' ' '                                             2 
	H	%	%c   c& 2'c( )c* +c, ./-c. R/c0 221c2 03c4    5c\    ]cv Bwcx rycz 2{c|  }c~  c@ BAcB (*D)ECc cD 1I JEcF "GcH    IcT '(UcV RWcX YcZ    [cr Bsct +ucx   " " "ycL bMcN n%OcP    Qc\    ]ch +-icp    qcJ ,-Kc c cL    McZ L/2[c\ b]c^ b_c` L>acb    ccn 56ocp    qcz +,{c| (}c~ 56c@ AcH ;-IcJ KcR " ScZ    [cf    gc c cr ]Osct    uc@ AcH O$IcJ *+KcL McT    Uc^    _cj    kcv    wcD    EcP    Qc` acb ccj n%kcl  78mcn oc c cv ()wcx ,-ycz "{c| }cD EcL ;-McN ; 56OcP    QcZ L>[c\ ]cd +,ecf "$?#@gch 56icj L>kcl mcn bocp |nqc c cr (*A)Bsct  .!1ucv (!*wc~ #%7$8c@	   " " "A	cL	       M	cV	 |nW	cX	 |nY	cZ	 k][	c\	 ]	c^	 #%6$7_	c`	  /!2a	cb	  c	cj	 "$k	cr	 ) + + +s	c|	  01}	c~	 /1N0O	c c c@
 # % % %A
cJ
    K
cT
 k]U
cV
 #%6$7W
cX
 ')>(?Y
cZ
 34[
c\
 L>]
c^
 r_
c`
 ]Oa
cb
 n%c
cd
 e
cl
 "m
cn
 o
cv
    w
cD ;-EcF 01GcH Ic c cP !QcX 56YcZ ]O[c\ ;/]c^ n%_c` /0acb # % % %ccn (*=>ocp    qc~ L>c@ ()AcB CcJ KcR L>ScT ]OUcV n%WcX    Yc c cb ;-ccd L>ecf gcn -.ocp ~&qcr (sct !8 9ucv bwcx L>ycz '{c| ,-}c~  cF    GcP )*QcR ]OScT n%UcV ]OWc c cX 'YcZ ()[c\ ()]c^ ()_c` ()acb    ccn  ! ! !ocz ]O{c| n%}c~ cF GcN    Oc\    ]cj -.kcl ;/mcn ]Oocp L>qc c cr ]Osct uc| }cD ! EcL 57PQMcN OcV n%WcX Yc` ach ~&icj ]Okcl n%mcn n%ocp    qc| ./}c~ cF ]OGc c cH bIcJ 12KcL BMcN    OcX L>YcZ '[c\ ']c^ _cf Bgch icp /0qcr /0sct *+ucv ./wcx yc@ AcH ;-Ic c cJ ;-KcL ;-McN OcV %Wc^ ;/_c` O$acb ()ccd 2ecf (gch '(icj 23kcl L>mcn ]Oocp qcx yc@ AcH ;-Ic c cJ    KcV    Wcb *+ccd 01ecf ()gch icp )*qcr scz *+{c| ;-}c~ L>c@ n%AcB )*CcD    EcP )+@AQcR n%ScT ,-Uc c cV *+WcX Yc` ;-acb m_ccd ecl    mcv )*wcx yc@ ???AcB 56CcD ()EcF n%GcH 'IcJ n%KcL McT "$?#@UcV Wc c c^ _cf ~';<gch L>icj    kcx    ycB 45CcD *+EcF n%GcH ;-IcJ \NKcL    McX $&B%CYcZ    [cd    ecp qcx yc@ ()Ac c cB ,-CcD ,-EcF ./GcH L>IcJ 'KcL n%McN !#=">OcP *QcR !9 :ScT Uc\ %'D&E]c^ ./_c` 12acb ccj kcr scz L>{c c c| *+}c~ 12c@ !AcH 'IcJ -.KcL ()McN    OcZ ()[c\ $&B%C]c^ &%((_cf -.gch ;-icj ~&kcl ~&mcn n%ocp ()qcr sc c cz ]O{c|    }cJ KcR  ";!<ScT  =>UcV  9:WcX ]OYcZ    [cf    gcr L>sct ;/ucv -.wcx 23ycz ]O{c| L>}c~ ]Oc@ L>Ac c cB ]OCcD ()EcF BGcH  $ $ $IcR )*ScT "UcV RWcX 01YcZ       [cj    kc|    }cJ )*KcL 89McN ./OcP  - - -Qcl   " " "mc c L-?%%'' /,,.../ o&--.?@@@&'../ABBB&'../ABBB./667PQQQ'(//0BCCC()001EFFF)*112FGGGl#**>:::)*112FGGG1299:KLLL89@@AYZZZm$++O<<<n%,,-=>>>&'../@AAA()001EFFFn%,,-=>>>&'../@AAAo&--.?@@@n%,,-=>>>&'../ABBBn%,,-=>>>l#**>:::m$++O<<<&'../ABBBo&--.?@@@'(//0CDDD&'../ABBB+,334JKKKo&--.?@@@-.556LMMM'(//0CDDDk"))-888m$++O<<<m$++O<<<*+223HIIIn%,,-=>>>>U &   222222> >899> > >9:::ZOO""$$ /,,.../ o&--.CDDDm$++,?@@@&'../EFFFm$++,?@@@'(//0FGGG)*112KLLL/0778VWWWn%,,-ABBB()001IJJJm$++,?@@@)*112JKKK&'../EFFFo&--.CDDD'(//0GHHHl#**+=>>>&'../EFFF)*112JKKK/0778LMMM34;;<TUUU)*112KLLLl#**	
 	
 	
   &'../EFFFm$++,?@@@o&--.CDDDn%,,-ABBBm$++,?@@@'(//0FGGG01889STTT&'../EFFF'(//0GHHH)*112KLLL)*112KLLL()001IJJJl#**+=>>>n%,,-ABBB)*112KLLLo&--.CDDD'(//0GHHHn%,,-ABBB&'../EFFF)*112KLLLn%,,-ABBBl#**+=>>>l#**+=>>>m$++,?@@@o&--.CDDDo&--.FGGG&'../EFFFn%,,-ABBB'(//0GHHH&'../EFFF&'../EFFF'(//0GHHH+,334NOOO'(//0GHHH*+223MNNNk"))*;<<<m$++,?@@@&'../EFFFm$++,?@@@*+223LMMMn%,,-ABBB4M3N/00Y &   //////; ;566; ; ;6777^&&(( /-D-D-F-F /,,.../ 	" 3.// &   AAAAAAM MGHHM M MHIII
?'')) /,,.../ m$++,=>>>> &   444444@ @:;;@ @ @;<<<
?!!## /,,.../ m$++,=>>>> &   ......: :455: : :5666TJ   /,,.../ 3I1I-.3G2H./(E'Fm$m$++-CEY,Z[[[l#**,?+@AAAm$++-A,BCCC*+223NOOO()001JKKK+,335RTo4pqqqm$++-CEY,Z[[[/077	*,KL   '(//1KMe0fggg./66	)+IJ   m$++-CEY,Z[[[./667KLLL9:AABabbb./667KLLL45<<>W=XYYYm$++,t,t,tuuun%,,.EG\-]^^^l#**,ACV+WXXX+,334PQQQn%,,-o-o-opppm$++-A?,STTTm$++-CEY,Z[[[-.557T6UVVV&'..0G/HIII'(//1I0JKKK'(//1I0JKKK'(//1KMe0fggg0188:[9\]]])*113OQk2lmmm)*113OQk2lmmmn%,,.EG\-]^^^)*112KLLL/0778VWWW./66	')GH   *+223NOOO)*113OQk2lmmmo&--/E.FGGG+,335RTo4pqqq+,335RTo4pqqq()002MOh1ijjjo&--.DEEE()002K1LMMMn%,,-BCCCo&--/GI_.`aaa()002MOh1ijjj)*113M2NOOO&'../FGGG)*113OQk2lmmml#**,?+@AAA'(//1H0IJJJ&'..0F/GHHHl#**,?+@AAA()002MOh1ijjjo&--/E.FGGGo&--.DEEE)*113M2NOOO&'../FGGGl#**+>???*+223MNNN'(//1KMe0fgggm$++,k,k,kllll#**,ACV+WXXX'(//0HIIIn%,,-BCCCn%,,.EG\-]^^^'(//0HIIIIc &   ++++++7 71227 7 72333fD##%% /,,.../ 9Q7Q34l#**+BCCCC &   000000< <677< < <7888L(> /,,.../ (*m$0B/C+,5P4Q01( ( (m$"
* 
* 
*o& l#**5	
 5	
 5	
7 7 7v 	/'4/0
 ;=67,.()0E/F+,+<*=&' o&--
	
 
	
 
	
   n%,,	
 	
 	
   &'..	
 	
 	
   <=DD	
 	
 	
   m$++S	
 S	
 S	
U U Ul )*11	
 	
 	
   m$++	
 	
 	
	 	 	 m$++		
 		
 		
   m$++	
 	
 	
	 	 	 m$++	
 	
 	
   ./66	
 	
 	
   '(//	
 	
 	
   ./66	
 	
 	
	 	 	 o&--	
 	
 	
   l#**	
 	
 	
   )*11	
 	
 	
   /077	
 	
 	
   m$++	
 	
 	

 
 
 o&--		
 		
 		
   n%,,	
 	
 	
	 	 	 *+22	
 	
 	
   m$++	
 	
 	
	 	 	 ()00		
 		
 		
   o&--	
 	
 	

 
 
 ()00	
 	
 	
   +,33	
 	
 	
   m$++	
 	
 	

 
 
 m$++	
 	
 	

 
 
 &'..	
 	
 	
   m$++	
 	
 	
	 	 	 &'..	
 	
 	
   o&--.k.k.klll/077	
 	
 	
   '(//		
 		
 		
   '(//	
 	
 	
   )*11	
 	
 	
   o&--	
 	
 	
   m$++	
 	
 	
   l#**	
 	
 	
   l#** 	
   '(//	
 	
 	
  , m$++	
 	
 	
   &'..	
 	
 	
	 	 	 )*11	
 	
 	

 
 
 34;;	
 	
 	
   ./66	
 	
 	
   m$++	
 	
 	
   ./66	
 	
 	
   9:AA	
 	
 	
   1299	
 	
 	

 
 
 9:AA	
 	
 	
   45<<	
 	
 	
   1299	
 	
 	
   /077	
 	
 	
   ./66		
 		
 		
   ./667p7p7pqqq-.55	
 	
 	
   /077
	
 
	
 
	
   45<<	
 	
 	
   1299	
 	
 	
   /077		
 		
 		
   34;;&	
   :;BB	"$AB   @AHH(2	
   45<<	
 	
 	
	 	 	 ./66	
 	
 	
   -.55	
 	
 	
   45<<	
 	
 	
   89@@	
 	
 	
	 	 	 -.55-*	
   m$++	
 	
 	
   n%,,	
 	
 	
   o&--	
 	
 	
   )*11	
 	
 	

 
 
 n%,,&	
   l#**	
 	
 	

 
 
 l#**	
 	
 	
   +,33	
 	
 	
   &'..	
 	
 	
   &'..$	
   ./667LMMMn%,,	
 	
 	
   l#**	
 	
 	

 
 
 o&--	
 	
 	
	 	 	 +,33	
 	
 	
   45<<	
 	
 	
   '(//		
 		
 		
   n%,,	
 	
 	

 
 
 m$++
	
 
	
 
	
   '(//	
 	
 	
   m$++,p,p,pqqqo&--	
 	
 	
   m$++->@U,VWWWn%,,	
 	
 	
   o&--	
 	
 	
   l#**	
 	
 	
   l#**	
 	
 	
   m$++	
 	
 	
   m$++		
 		
 		
   *+22	
 	
 	
   &'..	
 	
 	

 
 
 '(//	
 	
 	
	 	 	 0188	
 	
 	
   m$++	
 	
 	
   &'..	
 	
 	
   )*11	
 	
 	
   -.55	
 	
 	
   '(//	
 	
 	
   n%,,	
 	
 	
   o&--	
 	
 	
   n%,,	
 	
 	

 
 
 &'..	
 	
 	
   '(//	
 	
 	
   '(//	
 	
 	
   '(//	
 	
 	
   '(//	
 	
 	
   +,33	
 	
 	
   0188	
 	
 	
   n%,,	
 	
 	
   o&--	
 	
 	
   &'..	
 	
 	
   '(//	
 	
 	
	 	 	 )*11	
 	
 	
   )*11	
 	
 	
   l#**	
 	
 	
   n%,,	
 	
 	
   m$++	
 	
 	
   n%,,	
 	
 	
	 	 	 n%,,+"	
   )*11/&	
   /0774+	
   ./664+	
   )*11	
 	
 	

 
 
 o&--	
 	
 	
   m$++	
 	
 	
   o&--	
 	
 	
	 	 	 &'..	
 	
 	
   n%,,	
 	
 	
   o&--	
 	
 	
   o&--VVV   '(//	
 	
 	
   *+22	
 	
 	
   )*11	
 	
 	
   n%,,	
 	
 	
	 	 	 ,-44	
 	
 	
   &'..	
 	
 	
   m$++!	
   &'..	
 	
 	
	 	 	 &'..	
 	
 	
	 	 	 o&--	
 	
 	
	 	 	 )*11	
 	
 	
   +,33	
 	
 	
   +,33	
 	
 	
   ()00	
 	
 	
   *+22	
 	
 	
   n%,,	
 	
 	
   n%,,	
 	
 	

 
 
 l#**	
 	
 	
	 	 	 l#**	
 	
 	

 
 
 l#**	
 	
 	

 
 
 '(//	
 	
 	
   ./66	
 	
 	
   l#**	
 	
 	
	 	 	 '(//	
 	
 	
	 	 	 '(//	
 	
 	
   ,-44	
 	
 	

 
 
 m$++	
 	
 	
   n%,,	
 	
 	
   *+22*'	
   ()00	
 	
 	
   o&--	
 	
 	
	 	 	 l#**	
 	
 	
   n%,,	
 	
 	
   o&--	
 	
 	
   ()00	
 	
 	
   +,33	
 	
 	
	 	 	 '(//	
 	
 	
	 	 	 &'..	
 	
 	
   ()00	
 	
 	
   ()00
	
 
	
 
	
   ()00	
 	
 	
   l#**	
 	
 	
   m$++	
 	
 	
   o&--	
 	
 	
   )*11	
 	
 	
   &'..0HJ^/_```o&--	
 	
 	
   )*11	
 	
 	
   ()00/&	
   )*11	
 	
 	
	 	 	 l#**	
 	
 	
   o&--	
 	
 	
   n%,,	
 	
 	
	 	 	 *+22	
 	
 	
   ()00	
 	
 	
	 	 	 '(//	
 	
 	
   l#**	
 	
 	
   ./66	
 	
 	
   '(//	
 	
 	
	 	 	 o&--	
 	
 	
   &'..
	
 
	
 
	
   o&--	
 	
 	
   &'..		
 		
 		
   34;;		
 		
 		
   '(//	
 	
 	
   '(//
	
 
	
 
	
   &'..	
 	
 	
   m$++	
 	
 	
   l#** 	
   +,33	
 	
 	
   ./66	
 	
 	
	 	 	 ()00	
 	
 	
   o&--	
 	
 	
   l#**	
 	
 	
   n%,,	
 	
 	
   o&--	
 	
 	
   56==?Z>[\\\-.55	
 	
 	
   '(//	
 	
 	
	 	 	 '(//	
 	
 	
   *+22	
 	
 	

 
 
 '(//	
 	
 	
   )*11	
 	
 	
   )*11,'	
   *+22	
 	
 	
   m$++	
 	
 	
   &'..	
 	
 	
   o&--	
 	
 	
   23::	
 	
 	
	 	 	 k"))		
 		
 		
   0188	
 	
 	
   n%,,	
 	
 	
	 	 	 67>>	
 	
 	
   *+22	
 	
 	
   ,-44n5EFFFn%,,"	
   l#**	
 	
 	
   m$++	
 	
 	
   m$++	
 	
 	

 
 
 ()00	
 	
 	
   ,-44	
 	
 	

 
 
 &'..	
  
 &'..,$	
   *+22	
 	
 	
   '(//	
 	
 	
   m$++	
 	
 	

 
 
 '(//.%	
   56==?Z>[\\\78??A]@^___*+22	
 	
 	

 
 
 l#**	
 	
 	
   &'..	
 	
 	
   &'..	
 	
 	
   o&--	
 	
 	
   '(//%%	
   m$++!	
   n%,,	
 	
 	
   '(//		
 		
 		
   ,-44	
 	
 	
	 	 	 1299	
 	
 	

 
 
 n%,,	
 	
 	
	 	 	 &'..	
 	
 	
   o&--	
 	
 	
   m$++	
 	
 	
   l#**		
 		
 		
   *+22		
 		
 		
   -.55		
 		
 		
   n%,,
	
 
	
 
	
   m$++		
 		
 		
   n%,,	
 	
 	
   m$++	
 	
 	

 
 
 n%,,	
 	
 	
   '(//(%	
  ) ) )n%* * *o&
 &(k"-/)*$-;i -K,L(),<+='((SP & w w w''''''2v2vCCHXDYDY2v2v2v.///wXPq
'? /,,.../ +-&'8V7W343H2I./l#**	
 	
 	
  ( -BCV+W'(/1+,. . .)* o&--
	
 
	
 
	
   m$++-	
 -	
 -	
/ / /` m$++	
 	
 	
   m$++	
 	
 	
   )*11	
 	
 	
   /077	
 	
 	
   m$++	
 	
 	

 
 
 ()00		
 		
 		
   m$++	
 	
 	
   '(//	
 	
 	

 
 
 '(//	
 	
 	
   )*11	
 	
 	
   m$++	
 	
 	
   l#**	
 	
 	
   '(//	
 	
 	
   &'..	
 	
 	
	 	 	 )*11	
 	
 	

 
 
 m$++	
 	
 	
   9:AA	
 	
 	
   45<<	
 	
 	
	 	 	 )*11		
 		
 		
   l#**	
 	
 	
	 	 	 &'..		
 		
 		
   ./667NOOOl#**	
 	
 	
   '(//	
 	
 	

 
 
 o&--
	
 
	
 
	
   m$++	
 	
 	
	 	 	 m$++	
 	
 	
   '(//	
 	
 	
   o&--	
 	
 	
   &'..	
 	
 	
   '(//	
 	
 	

 
 
 )*11	
 	
 	
   l#**+r+r+rsss)*11	
 	
 	

 
 
 o&--	
 	
 	
   o&--.m.m.mnnnn%,,UUU   &'..ttt   )*11	
 	
 	
   ()00	
 	
 	
   n%,,		
 		
 		
   l#**+o+o+opppo&--	
 	
 	
	 	 	 l#**	
 	
 	
   &'..	
 	
 	
   l#**	
 	
 	
   o&--	
 	
 	
   &'..		
 		
 		
   o&--	
 	
 	
   &'..
	
 
	
 
	
   34;;
	
 
	
 
	
   '(//		
 		
 		
   l#**"	
   ()00	
 	
 	
   -.55	
 	
 	
   *+22	
 	
 	
   m$++	
 	
 	
   k"))	
 	
 	
   n%,,	
 	
 	
   56==?\>]^^^78??A_@`aaal#**	
 	
 	
   &'..	
 	
 	
   '(//	
 	
 	
   &'..	
 	
 	
   m$++	
 	
 	
   l#**		
 		
 		
   *+22		
 		
 		
   n%,,		
 		
 		
  , , ,'( %'j!!] & w w w''''''2v2vCCHXDYDY2v2v2v.///wbG/!!##/   /   	/
 %$&&/ -,.../& ()001LMMM()001EFFF()001EFFFF & 	 	 	     i iC^__i i ideee	R""$$ /,,.../ ./667WXXX./667PQQQQ &        ; ;566; ; ;6777N /,,.../ l#**	
 	
 	
  $ 24-.0E/F+,o&--		
 		
 		
   m$++	
 	
 	
  D m$++	
 	
 	

 
 
 m$++	
 	
 	
   m$++	
 	
 	
   '(//
	
 
	
 
	
   )*11	
 	
 	
   /077	
 	
 	
   n%,,	
 	
 	
   m$++	
 	
 	

 
 
 o&--	
 	
 	
   )*11	
 	
 	

 
 
 &'..
	
 
	
 
	
   ./667PQQQm$++,o,o,oppp&'..QQQ   m$++,o,o,opppn%,,-s-s-stttn%,,-s-s-sttto&--	
 	
 	
   o&--	
 	
 	
   n%,,	
 	
 	
   &'..	
 	
 	
   l#**+u+u+uvvvl#**	
 	
 	
   &'..	
 	
 	
   o&--	
 	
 	
   o&--	
 	
 	
   &'..		
 		
 		
   34;;		
 		
 		
   '(//	
 	
 	

 
 
 56==>]^^^k"))	
 	
 	
   56==>]^^^78??Aa@bcccl#**+v+v+vwww'(//	
 	
 	
   &'..	
 	
 	
   m$++	
 	
 	
   *+22		
 		
 		
   A
 &   ))))))5 5/005 5 50111^
  IB                                   $ 655555                                       (                          LKKKKK ONNNNNNN eddddddddddd......                        %$$$$$                  ,+++++                                                                         76666666''''''            =<<<<<         
 322222......             &%%%%%                                     *)))))                   +*****                     
                                                                     ,+++++             0/////                    &%%%%%                
 ('''''                       ('''''222222      877777        ?>>>>>                    
 322222222222000000444444      988888                       
 877777              
         
 100000           ;:::::''''''))))))++++++                            &%%%%%                    =<<<<<))))))33333333++++++666666            CBBBBBBB              ('''''//////               ('''''))))))++++++         
 &%%%%%''''''             -,,,,,......      ('''''------333333                
 100000))))))++++++))))))      0///////////////////////                       *)))))++++++                                         54444433333333))))))''''''))))))                                    ,+++++               -,,,,,))))))++++++++++++                        *)))))              
      .-----------                                                 &%%%%%%%%%%%%%%%%%               43333333******//////............      ('''''))))))                      &%%%%%                                 0/////                         &%%%%%''''''++++++000000                   ,+++++                  &%%%%%******99999999         
 100000        BAAAAAAAAA<<<<<<//////++++++------++++++                                  ('''''                      
      211111++++++%%%%%%((((((            JIIIII         
                          0/////333333333333      ('''''------++++++      $#####                       988888               76666666''''''                  .-----444444//////                 JIIIII             &%%%%%,,,,,,,,,,,,++++++//////        *)))))                          EDDDDD@@@@@@))))))                       ('''''33333333           *)))))''''''))))))''''''))))))//////$ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $J 100000 877777                                              100000??????555555- - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -`                         )1))++ 	300222	3
 	322222444444444444CCCCCC555555888888999999,,,,,,999999>>>>>>LLLLLL......000000333333888888000000333333222222000000444444000000,,,,,,......444444222222666666444444======222222??????666666******............;;;;;;0000000M * 9 9 98888889PIE&&(( 	300222	3 	766666222222888888222222999999>>>>>>IIIIII444444<<<<<<222222======888888666666::::::000000888888======??????GGGGGG>>>>>>	
 	
 	
 	
 	
 	
 	
 	
 	
 	

 	988888222222666666444444222222999999FFFFFF888888::::::>>>>>>>>>>>><<<<<<000000444444>>>>>>666666::::::444444888888>>>>>>444444000000000000222222666666999999888888444444::::::888888888888::::::AAAAAA::::::@@@@@@......222222888888222222??????444444DDDDDDDM * 6 6 65555556P	
**,, 	31H1H1J1J 	300222	3
	
 	
 	
 	
 	
 	
 	
 	
 	
 * J J JIIIIIIJ1++-- 	300222	3
 	1000000 * ; ; ;::::::;
1%%'' 	300222	3
 	1000000 * 5 5 54444445
i<""$$ 	300222	3
 	@?????>>>>>><<<<<<IIIIIIII111111333333AAAAAA======	
 	
 	
 	
 	
 	
 	
 	
 	JIIIIIII	
 	
 	
 	
 	
 	
 	
 	
 	VUUUUUUU	
 	
 	
 	
 	
 	
 	
 	
 	JIIIIIII>>>>>>TTTTTT>>>>>>IIIIIIaaaaaaaaaaLLLLLLLLFFFFFFFFCCCCCC	
 	
 	
 	
 	
 	
 	
 	
 	
 	

 	CBBBBBBBIIIIIIIIFFFFFF999999;;;;;;;;;;;;UUUUUUUUMMMMMM	
 	
 	
 	
 	
 	
 	
 	
	
 	
 	
 	
 	
 	
 	
 	
 	MLLLLLLL>>>>>>IIIIIIffffffffAAAAAA	
 	
 	
 	
 	
 	
 	
 	
 	877777	
 	
 	
 	
 	
 	
 	
 	
	
 	
 	
 	
 	
 	
 	
 	
 	YXXXXXXX777777======555555OOOOOOOOXXXXXXXX??????999999	
 	
 	
 	
 	
 	
 	
 	
 	211111::::::888888111111XXXXXXXX777777777777??????999999111111@@@@@@UUUUUUUUXXXXXXXXXXFFFFFFFF;;;;;;555555LLLLLLLL;;;;;;;M * 2 2 21111112P6'')) 	300222	3
 	HGGGGG5555555	 * 7 7 76666667D 4!!## 	300222	3 	:99999GGGGGG	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
"
	
 
	
 
	
 
	
 
	
 
	
 
	
 
	
 
	
 
	
 
	
 
	
 
	
 
	
 
	
 
	
 
	
 
	
 
	
 
	
 
	
 
	
5	
 5	
 5	
 5	
 5	
 5	
 5	
 5	
 5	
 5	
 5	
 5	
 5	
 5	
 5	
 5	
 5	
 5	
 5	
 5	
 5	
 5	
 5	
 5	
 5	
 5	
 5	
 5	
 5	
 5	
 5	
 5	
 5	
 5	
 5	
 5	
 5	
 5	
 5	
 5	
 5	
 5	
 5	
 5	
 5	
 5	
 5	
 5	
 5	
 5	
 5	
 5	
 5	
 5	
 5	
 5	
 5	
 5	
 5	
 5	
 5	
 5	
 5	
 5	
 5	
 5	
 5	
 5	
 5	
 5	
 5	
 5	
 5	
 5	
 5	
 5	
 5	
 5	
 5	
 5	
 5	
 5	
 5	
 5	
 5	
 5	
 5	
 5	
 5	
 5	
 5	
 5	
 5	
 5	
 5	
 5	
 5	
 5	
 5	
 5	
 5	
 5	
 5	
 5	
 5	
 5	
 5	
 5	
l	
 	
 	
 	
 	
 	
 	
 	
 	=<<<<<333333
	
 
	
 
	
 
	
 
	
 
	
 
	
 
	
 
	
 
	
 
	
 
	
 
	
 
	
 
	
 
	
 
	
 
	
 
	
 
	
 
	
 
	
	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
	
 	
 	
 	
 	
 	
 	
 	
 	
 	

S	
 S	
 S	
 S	
 S	
 S	
 S	
 S	
 S	
 S	
 S	
 S	
 S	
 S	
 S	
 S	
 S	
 S	
 S	
 S	
 S	
 S	
 S	
 S	
 S	
 S	
 S	
 S	
 S	
 S	
 S	
 S	
 S	
 S	
 S	
 S	
 S	
 S	
 S	
 S	
 S	
 S	
 S	
 S	
 S	
 S	
 S	
 S	
 S	
 S	
 S	
 S	
 S	
 S	
 S	
 S	
 S	
 S	
 S	
 S	
 S	
 S	
 S	
 S	
 S	
 S	
 S	
 S	
 S	
 S	
 S	
 S	
 S	
 S	
 S	
 S	
 S	
 S	
 S	
 S	
 S	
 S	
 S	
 S	
 S	
 S	
 S	
 S	
 S	
 S	
 S	
 S	
 S	
 S	
 S	
 S	
 S	
 S	
 S	
 S	
 S	
 S	
 S	
 S	
 S	
 S	
 S	
 S	
 S	
 S	
 S	
 S	
 S	
 S	
 S	
 S	
 S	
 S	
 S	
 S	
 S	
 S	
 S	
 S	
 S	
 S	
 S	
 S	
 S	
 S	
 S	
 S	
 S	
 S	
 S	
 S	
 S	
 S	
 S	
 S	
 S	
 S	
 S	
 S	
 S	
 S	
 S	
 S	
 S	
 S	
 S	
 S	
 S	
 S	
 S	
 S	
 S	
 S	
 S	
 S	
 S	
 S	
 S	
 S	
 S	
 S	
 S	
 S	
h	
 	
 	
 	
 	
 	
 	
 	
 	
 	

	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
		
 		
 		
 		
 		
 		
 		
 		
 		
 		
 		
 		
 		
 		
 		
 		
 		
 		
 		
 		
	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
		
 		
 		
 		
 		
 		
 		
 		
 		
 		
 		
 		
 		
 		
 		
 		
 		
 		
 		
 		
	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
		
 		
 		
 		
 		
 		
 		
 		
 		
 		
 		
 		
 		
 		
 		
 		
 		
 		
 		
 		
	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
	
 	
 	
 	
 	
 	
 	
 	
 	
 	

	
 	
 	
 	
 	
 	
 	
 	
 	
 	

	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
		
 		
 		
 		
 		
 		
 		
 		
 		
 		
 		
 		
 		
 		
 		
 		
 		
 		
 		
 		
	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
	
 	
 	
 	
 	
 	
 	
 	
 	
 	

	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
	
 	
 	
 	
 	
 	
 	
 	
 	
 	

	
 	
 	
 	
 	
 	
 	
 	
	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
,	
 	
 	
 	
 	
 	
 	
 	
 	
 	

	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
	
 	
 	
 	
 	
 	
 	
 	
 	
 	

	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
	
 	
 	
 	
 	
 	
 	
 	
 	
 	

	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
	
 	
 	
 	
 	
 	
 	
 	
 	
 	

	
 	
 	
 	
 	
 	
 	
 	
 	
 	

	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
	
 	
 	
 	
 	
 	
 	
 	
 	
 	

		
 		
 		
 		
 		
 		
 		
 		
 		
 		
 		
 		
 		
 		
 		
 		
 		
 		
 		
 		
	
 	
 	
 	
 	
 	
 	
 	
 	
 	

	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	

	
 
	
 
	
 
	
 
	
 
	
 
	
 
	
 
	
 
	
 
	
 
	
 
	
 
	
 
	
 
	
 
	
 
	
 
	
 
	
 
	
 
	
	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
		
 		
 		
 		
 		
 		
 		
 		
 		
 		
 		
 		
 		
 		
 		
 		
 		
 		
 		
 		
	
 	
 	
 	
 	
 	
 	
 	
	
 	
 	
 	
 	
 	
 	
 	
	
 	
 	
 	
 	
 	
 	
 	
	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
	
 	
 	
 	
 	
 	
 	
 	
 	
 	

	
 	
 	
 	
 	
 	
 	
 	
 	
 	

	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
	
 	
 	
 	
 	
 	
 	
 	
	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
	
 	
 	
 	
 	
 	
 	
 	
	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
	
 	
 	
 	
 	
 	
 	
 	
 	
 	

	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
	
 	
 	
 	
 	
 	
 	
 	
 	@?????	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
	
 	
 	
 	
 	
 	
 	
 	
 	
 	

	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
		
 		
 		
 		
 		
 		
 		
 		
 		
 		
 		
 		
 		
 		
 		
 		
 		
 		
 		
 		
	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	

	
 
	
 
	
 
	
 
	
 
	
 
	
 
	
 
	
 
	
 
	
 
	
 
	
 
	
 
	
 
	
 
	
 
	
 
	
 
	
 
	
 
	
	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
	
 	
 	
 	
 	
 	
 	
 	
 	
 	

	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
	
 	
 	
 	
 	
 	
 	
 	
	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
	
 	
 	
 	
 	
 	
 	
 	
 	
 	

		
 		
 		
 		
 		
 		
 		
 		
 		
 		
 		
 		
 		
 		
 		
 		
 		
 		
 		
 		
	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
	
 	
 	
 	
 	
 	
 	
 	
 	
 	

	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
	
 	
 	
 	
 	
 	
 	
 	
 	
 	

	
 	
 	
 	
 	
 	
 	
 	
 	
 	

	
 	
 	
 	
 	
 	
 	
 	
 	
 	

	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
	
 	
 	
 	
 	
 	
 	
 	
 	
 	

	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
	
 	
 	
 	
 	
 	
 	
 	
 	
 	

	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
	
 	
 	
 	
 	
 	
 	
 	
	
 	
 	
 	
 	
 	
 	
 	
	
 	
 	
 	
 	
 	
 	
 	
	
 	
 	
 	
 	
 	
 	
 	
	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
	
 	
 	
 	
 	
 	
 	
 	
 	
 	

	
 	
 	
 	
 	
 	
 	
 	
 	
 	

	
 	
 	
 	
 	
 	
 	
 	
 	
 	

 	hggggggggggg	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
	
 	
 	
 	
 	
 	
 	
 	
 	
 	

	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
	
 	
 	
 	
 	
 	
 	
 	
 	
 	

	
 	
 	
 	
 	
 	
 	
 	
	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
	
 	
 	
 	
 	
 	
 	
 	
 	
 	

	
 	
 	
 	
 	
 	
 	
 	
 	
 	

	
 	
 	
 	
 	
 	
 	
 	
	
 	
 	
 	
 	
 	
 	
 	
 	
 	

	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
	
 	
 	
 	
 	
 	
 	
 	
 	
 	

	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
	
 	
 	
 	
 	
 	
 	
 	
 	
 	


	
 
	
 
	
 
	
 
	
 
	
 
	
 
	
 
	
 
	
 
	
 
	
 
	
 
	
 
	
 
	
 
	
 
	
 
	
 
	
 
	
 
	
	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
	
 	
 	
 	
 	
 	
 	
 	
	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
	
 	
 	
 	
 	
 	
 	
 	
 	
 	

	
 	
 	
 	
 	
 	
 	
 	
	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
	
 	
 	
 	
 	
 	
 	
 	
 	
 	

	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
	
 	
 	
 	
 	
 	
 	
 	
 	
 	

	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
	
 	
 	
 	
 	
 	
 	
 	
 	
 	

	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
	
 	
 	
 	
 	
 	
 	
 	
 	
 	

	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
	
 	
 	
 	
 	
 	
 	
 	
 	
 	


	
 
	
 
	
 
	
 
	
 
	
 
	
 
	
 
	
 
	
 
	
 
	
 
	
 
	
 
	
 
	
 
	
 
	
 
	
 
	
 
	
 
	
	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
		
 		
 		
 		
 		
 		
 		
 		
 		
 		
 		
 		
 		
 		
 		
 		
 		
 		
 		
 		
		
 		
 		
 		
 		
 		
 		
 		
 		
 		
 		
 		
 		
 		
 		
 		
 		
 		
 		
 		
	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	

	
 
	
 
	
 
	
 
	
 
	
 
	
 
	
 
	
 
	
 
	
 
	
 
	
 
	
 
	
 
	
 
	
 
	
 
	
 
	
 
	
 
	
	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
	
 	
 	
 	
 	
 	
 	
 	
 	
 	

	
 	
 	
 	
 	
 	
 	
 	
	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
	
 	
 	
 	
 	
 	
 	
 	
 	
 	

	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	MLLLLL	
 	
 	
 	
 	
 	
 	
 	
 	
 	

	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
	
 	
 	
 	
 	
 	
 	
 	
	
 	
 	
 	
 	
 	
 	
 	
 	
 	

	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
	
 	
 	
 	
 	
 	
 	
 	
 	
 	

	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
		
 		
 		
 		
 		
 		
 		
 		
 		
 		
 		
 		
 		
 		
 		
 		
 		
 		
 		
 		
	
 	
 	
 	
 	
 	
 	
 	
 	
 	

	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
	
 	
 	
 	
 	
 	
 	
 	
 	
 	

	
 	
 	
 	
 	
 	
 	
 	
 	
 	

 	766666	
 	
 	
 	
 	
 	
 	
 	
	
 	
 	
 	
 	
 	
 	
 	
 	
 	

	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	100000	
 	
 	
 	
 	
 	
 	
 	
	
 	
 	
 	
 	
 	
 	
 	
 	
 	

	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
	
 	
 	
 	
 	
 	
 	
 	
 	MLLLLLOOOOOO	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
	
 	
 	
 	
 	
 	
 	
 	
 	
 	

	
 	
 	
 	
 	
 	
 	
 	
 	
 	

	
 	
 	
 	
 	
 	
 	
 	
 	
 	

	
 	
 	
 	
 	
 	
 	
 	
	
 	
 	
 	
 	
 	
 	
 	
	
 	
 	
 	
 	
 	
 	
 	
 	
 	

		
 		
 		
 		
 		
 		
 		
 		
 		
 		
 		
 		
 		
 		
 		
 		
 		
 		
 		
 		
	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
	
 	
 	
 	
 	
 	
 	
 	
 	
 	

		
 		
 		
 		
 		
 		
 		
 		
 		
 		
 		
 		
 		
 		
 		
 		
 		
 		
 		
 		
		
 		
 		
 		
 		
 		
 		
 		
 		
 		
 		
 		
 		
 		
 		
 		
 		
 		
 		
 		
		
 		
 		
 		
 		
 		
 		
 		
 		
 		
 		
 		
 		
 		
 		
 		
 		
 		
 		
 		

	
 
	
 
	
 
	
 
	
 
	
 
	
 
	
 
	
 
	
 
	
 
	
 
	
 
	
 
	
 
	
 
	
 
	
 
	
 
	
 
	
 
	
		
 		
 		
 		
 		
 		
 		
 		
 		
 		
 		
 		
 		
 		
 		
 		
 		
 		
 		
 		
	
 	
 	
 	
 	
 	
 	
 	
 	
 	

	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
	
 	
 	
 	
 	
 	
 	
 	
	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	RQQQQQQQQQ 	%$$$$$BBBBBB3333333C@ * . . .------.H@~
   	300222	3 	NMMMMM 	@?????	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
$ 	LKKKKKKK	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	

	
 
	
 
	
 
	
 
	
 
	
 
	
 
	
 
	
 
	
 
	
 
	
 
	
 
	
 
	
 
	
 
	
 
	
 
	
 
	
 
	
 
	
-	
 -	
 -	
 -	
 -	
 -	
 -	
 -	
 -	
 -	
 -	
 -	
 -	
 -	
 -	
 -	
 -	
 -	
 -	
 -	
 -	
 -	
 -	
 -	
 -	
 -	
 -	
 -	
 -	
 -	
 -	
 -	
 -	
 -	
 -	
 -	
 -	
 -	
 -	
 -	
 -	
 -	
 -	
 -	
 -	
 -	
 -	
 -	
 -	
 -	
 -	
 -	
 -	
 -	
 -	
 -	
 -	
 -	
 -	
 -	
 -	
 -	
 -	
 -	
 -	
 -	
 -	
 -	
 -	
 -	
 -	
 -	
 -	
 -	
 -	
 -	
 -	
 -	
 -	
 -	
 -	
 -	
 -	
 -	
 -	
 -	
 -	
 -	
 -	
 -	
 -	
 -	
\	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
	
 	
 	
 	
 	
 	
 	
 	
 	
 	

	
 	
 	
 	
 	
 	
 	
 	
 	
 	

	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
		
 		
 		
 		
 		
 		
 		
 		
 		
 		
 		
 		
 		
 		
 		
 		
 		
 		
 		
 		
	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
	
 	
 	
 	
 	
 	
 	
 	
 	
 	

	
 	
 	
 	
 	
 	
 	
 	
 	
 	

	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
	
 	
 	
 	
 	
 	
 	
 	
 	
 	

	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
		
 		
 		
 		
 		
 		
 		
 		
 		
 		
 		
 		
 		
 		
 		
 		
 		
 		
 		
 		
	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
		
 		
 		
 		
 		
 		
 		
 		
 		
 		
 		
 		
 		
 		
 		
 		
 		
 		
 		
 		
 	BAAAAA	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	

	
 
	
 
	
 
	
 
	
 
	
 
	
 
	
 
	
 
	
 
	
 
	
 
	
 
	
 
	
 
	
 
	
 
	
 
	
 
	
 
	
 
	
	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
	
 	
 	
 	
 	
 	
 	
 	
 	
 	

	
 	
 	
 	
 	
 	
 	
 	
 	
 	

	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
	
 	
 	
 	
 	
 	
 	
 	
 	
 	

	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
	
 	
 	
 	
 	
 	
 	
 	
 	
 	

	
 	
 	
 	
 	
 	
 	
 	
 	
 	

	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
		
 		
 		
 		
 		
 		
 		
 		
 		
 		
 		
 		
 		
 		
 		
 		
 		
 		
 		
 		
	
 	
 	
 	
 	
 	
 	
 	
 	
 	

	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	SRRRRRRRRR	
 	
 	
 	
 	
 	
 	
 	
 	
 	

	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
	
 	
 	
 	
 	
 	
 	
 	
 	
 	

		
 		
 		
 		
 		
 		
 		
 		
 		
 		
 		
 		
 		
 		
 		
 		
 		
 		
 		
 		
	
 	
 	
 	
 	
 	
 	
 	
 	
 	


	
 
	
 
	
 
	
 
	
 
	
 
	
 
	
 
	
 
	
 
	
 
	
 
	
 
	
 
	
 
	
 
	
 
	
 
	
 
	
 
	
 
	

	
 
	
 
	
 
	
 
	
 
	
 
	
 
	
 
	
 
	
 
	
 
	
 
	
 
	
 
	
 
	
 
	
 
	
 
	
 
	
 
	
 
	
		
 		
 		
 		
 		
 		
 		
 		
 		
 		
 		
 		
 		
 		
 		
 		
 		
 		
 		
 		
	
 	
 	
 	
 	
 	
 	
 	
	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
	
 	
 	
 	
 	
 	
 	
 	
 	
 	

	
 	
 	
 	
 	
 	
 	
 	
 	
 	

	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	ONNNNNQQQQQQ	
 	
 	
 	
 	
 	
 	
 	
 	
 	

	
 	
 	
 	
 	
 	
 	
 	
 	
 	

	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
	
 	
 	
 	
 	
 	
 	
 	
 	
 	

	
 	
 	
 	
 	
 	
 	
 	
 	
 	

		
 		
 		
 		
 		
 		
 		
 		
 		
 		
 		
 		
 		
 		
 		
 		
 		
 		
 		
 		
		
 		
 		
 		
 		
 		
 		
 		
 		
 		
 		
 		
 		
 		
 		
 		
 		
 		
 		
 		
		
 		
 		
 		
 		
 		
 		
 		
 		
 		
 		
 		
 		
 		
 		
 		
 		
 		
 		
 		
	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
m * . . . 	.-----.z
  ""	3%%''	3 #"$$	3 #"$$		3
 )(**	3 10222	3	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 * d d dccccccdd&&(( 	300222	3
 	dcccccccc * 6 6 65555556c
  "" 	300222	3	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
  	=<<<<<		
 		
 		
 		
 		
 		
 		
 		
 		
 		
 		
 		
 		
 		
 		
 		
 		
 		
 		
 		
	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
:	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	

	
 
	
 
	
 
	
 
	
 
	
 
	
 
	
 
	
 
	
 
	
 
	
 
	
 
	
 
	
 
	
 
	
 
	
 
	
 
	
 
	
 
	
	
 	
 	
 	
 	
 	
 	
 	
 	
 	

	
 	
 	
 	
 	
 	
 	
 	
 	
 	

	
 	
 	
 	
 	
 	
 	
 	
 	
 	

	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
	
 	
 	
 	
 	
 	
 	
 	
 	
 	

	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	

	
 
	
 
	
 
	
 
	
 
	
 
	
 
	
 
	
 
	
 
	
 
	
 
	
 
	
 
	
 
	
 
	
 
	
 
	
 
	
 
	
 
	
 	DCCCCC	
 	
 	
 	
 	
 	
 	
 	
 	
 	

	
 	
 	
 	
 	
 	
 	
 	
 	
 	

	
 	
 	
 	
 	
 	
 	
 	
 	
 	

	
 	
 	
 	
 	
 	
 	
 	
 	
 	

	
 	
 	
 	
 	
 	
 	
 	
 	
 	

	
 	
 	
 	
 	
 	
 	
 	
 	
 	

	
 	
 	
 	
 	
 	
 	
 	
 	
 	

	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
	
 	
 	
 	
 	
 	
 	
 	
 	
 	

	
 	
 	
 	
 	
 	
 	
 	
 	
 	

 	YXXXXXXXXX	
 	
 	
 	
 	
 	
 	
 	
 	
 	

	
 	
 	
 	
 	
 	
 	
 	
 	
 	

	
 	
 	
 	
 	
 	
 	
 	
 	
 	

		
 		
 		
 		
 		
 		
 		
 		
 		
 		
 		
 		
 		
 		
 		
 		
 		
 		
 		
 		
		
 		
 		
 		
 		
 		
 		
 		
 		
 		
 		
 		
 		
 		
 		
 		
 		
 		
 		
 		
	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	QPPPPP	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	QPPPPPSSSSSS	
 	
 	
 	
 	
 	
 	
 	
 	
 	

	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
 	
	
 	
 	
 	
 	
 	
 	
 	
 	
 	

		
 		
 		
 		
 		
 		
 		
 		
 		
 		
 		
 		
 		
 		
 		
 		
 		
 		
 		
 		
 		
o * 0 0 0 	0/////0H	 JJJ'K		*$k2  CK  !3!3!5!5 >O>O>Q>Q 
	/         s9  0p &p87p8<AM M&AM5M4AM5M9AN# N#&AOOAOOAP P&AP+P*AP+P/AQ" Q"&ARR
ARRAr r&Ar5r4Ar5r9As4 s4&AttAtt!Cz" z"&C{{
C{{D^= ^=&D_&_%D_&_*<Da? a?&Db(b'Db(b,Dc< c<&Dd%d$Dd%d)Dx. x.&DyyDyy0E* *E87E8<FJ JFJJFJJFK KFKKFKKFK8 K8FLLFLL
FL* L*FL8L7FL8L<FZ ZFZZFZZFZ= Z=F[[
F[[HS2 S2HT S?HT THu> u>HvvHvv<Hw  w Hw.w-Hw.w2Hx xHx$x#Hx$x(II? I?IJJIJ