vendor/libxgboost.arm64.dylib in xgb-0.5.2 vs vendor/libxgboost.arm64.dylib in xgb-0.5.3
- old
+ new
@@ -1,351 +1,472 @@
- ` x __TEXT __text __TEXT H v H __stubs __TEXT __stub_helper __TEXT
- __gcc_except_tab__TEXT ` ` __const __TEXT p p __cstring __TEXT x$
x$ __unwind_info __TEXT p~ 8 __DATA_CONST __got __DATA_CONST __mod_init_func __DATA_CONST __const __DATA_CONST Џ Џ x __DATA @ @ @ @ __la_symbol_ptr __DATA @ @ V __thread_vars __DATA K P K __data __DATA HM HM __thread_ptrs __DATA U p U __thread_bss __DATA hV
- __bss __DATA ` __common __DATA u H __LINKEDIT
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+ x __TEXT __text __TEXT |6 _ |6 __stubs __TEXT D T D __stub_helper __TEXT
+ __gcc_except_tab__TEXT T L T __const __TEXT __cstring __TEXT X X __unwind_info __TEXT X X 8 __DATA_CONST __got __DATA_CONST __mod_init_func __DATA_CONST __const __DATA_CONST __DATA @ @ @ __la_symbol_ptr __DATA @ 8 @ c __thread_vars __DATA 8L 8L __data __DATA N 0 N __thread_ptrs __DATA 0W 0W __thread_data __DATA W $ W __thread_bss __DATA W M __bss __DATA __common __DATA H __LINKEDIT
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+ ` V C P 9( @ 7 @i h 6@"@sC"h R 9R2 C /@)@ R ? h ( R 9 R =<H@o0 @<Ё< 9`" 979(7\ I^vX)@? T{HOGWF_EC_@9(6 @O 9 6! 9 797 @9H6 96 9H6 96 9H6 96 @ _WO{ vX i@ a |
+ ՈEvX a > $ HBvXA o< =R" {COBWA_Ĩ_ ^9h 6@
vX! VT O{C R~ 2o
a vX uX ? { B HBvXA {_W O
{ o = # 9<<<<O g# % 97 97/@` 3 :{NOMWL_G@2 9h6;@./@ 9h 6G@&# # ] Cog_WO{ AvX@RI'oP 9:@S 7Q@S
+9 R o < < < < < < < VvXB 9( @ 7Ռ-) @Ռ-i h 6@XsX" R 9 R2 @)@ o ? H3R(ӧrh ( R 9 RҶ ig =< o @ (R̥r 9"s8(79h7R o 98@S 9a@c
+9 R o < < < < < < <B µ 9( @i7
+ X96S@ @i h 6@XsX" R 9R2 @)@ o ? h ( R 9 R| @h<op @ =<< = 9"шs8h797(R9 oXS
RSy R^ 9 o = y uXhC 9 @ T
+ ` d 9( @7<͍Rr X896S@4 @<͍Rri h 6@+XsX"h R 9R2 8@)@ R ? Rh ( R 9 R `h<h oP <A < =@ =" d9"s879H7HR9lRSy ( oXS 9 R 9 o = yhC 9 @
+ ` V 9( @i7
+ Xյ96S@ѵ @i h 6@ʵXsX"h R 9R2 @)@ R ? h ( R 9 R ]g<op @<< 9"Ǵs879H7 R9-Rr KR(ͭr3
+9 R 9 o = yhC 9 @
+ ` V 9( @i7
+ Xz96S@v @i h 6@oXsX"h R 9R2 |@)@A R ? Rh ( R 9
+R] `<g=<np C @ A 9"hs8(79h7hR9-Rh,rs
+HnP @S 9 R< 9 o = yhC 9 @
+ ` V D 9( @i7
+ X96S@ @i h 6@XsX"h R 9R2 j ( R" 9:Rs8nP @ Rx R9#y HnXG #" R R; `dh<nP D
C$= BA @ =" 9 9h797s879(7R9np =+=9 Rƴ o < < < < < < <B ճ 9( @i7 ;@96G@s8h6X9(6S@ @i h 6@XsX" R 9R2 @)@ o ? Rh ( R 9 R Հ g=<n @ =<< = 9"ёs8(79h7HR9,RSy <YmXS 9 Rf o < < < < < < <B u 9( @i7
+ XK96S@G @i h 6@@XsX" R 9R2 M@)@ o ? Rh ( R 9 R. Հg=<nP @ 9"=s879H7(R9hPm0 @S ( RSy R o < < < < < < <B " 9( @i7
+ X96S@ @i h 6@XsX" R 9R2 @)@ o ? h ( R 9 Rܳ=<n0 @ 9"s879(7(R9nP =+=
Rcy Ró 9 o = yhC 9 @
+ ` V ˲ 9( @i7
+ X9(6S@ @ h 6@(͍Rr XsX h R 9R2 j ( R" 9 Rs8R(Lr
RCx R4 R9RȌr 39#" R+ R 9H.R rs R yB R! Ri/ =<Hn @ =<< = 9"cv97 9(79h7s8797Rɺl0 9(@S (a@c
+9 RE o < < < < < < <B T 9( @7) /@* 9(6;@&96G@"s86X 9h6S@ @i h 6@XsX" R 9R2 @)@ o ? h ( R 9 R Հ'h<HnP 9@B 8 @A= =" 9 s879H7(R9(np @S RSy R߲ o < < < < < < <B 9( @i7
+ XIJ96S@ @i h 6@XsX" R 9R2 @%@. o ? Rh ( R 9 R f<n0 @<< 9"Ѵs879H7RInp 9(@S (q@s
+9 R 9 o = yhC 9 @
+ ` V 9( @i7
+ Xg96S@c @ h 6@\(͍Rr XsX h R 9R2 fj ( R" 9 Rs8R(ͬrRHr3s8 RRnp 9(@G (a@[9#" R R4; @h<nP D C!= (= A
B @ mR.r " 96 9h797s879(7R9np =+=9 R o < < < < < < <B 9( @i7 ;@96G@s8h6X9(6S@ @i h 6@۱XsX" R 9R2 @%@. o ? Rh ( R 9 Rȱ=<Ȣn @ =<< = 9"հs879H7(R9Hnp =+=
Rcy R o < < < < < < <B 9( @i7
+ X96S@ @i h 6@XsX" R 9R2 @%@. o ? Rh ( R 9 Rr Հf<Hn0 @= =ȮRͥr 9"}s879(7R9n0 =+=9 RT o < < < < < < <B c 9( @i7
+ X99(6S@5 @i h 6@.XsX" R 9R2 ;@%@. o ? Rh ( R 9 R ՠf<nP @ =<< = 9"'s8(79h7HR9nRSynP @S 9 R o < < < < < < <B 9( @i7
+ X96S@ݰ @i h 6@ְXsX" R 9R2 @%@. o ? QRrh ( R 9 R° Հf<Ȉn0 @= =Rͥr0 9"ͯs8H797R9(R(r nP @S 9 R o < < < < < < <B 9( @i7
+ X96S@ @i h 6@{XsX" R 9 R2 @)@ o ? Rh ( R 9
+Ri=<np C @ A 9"vs8H797(R9nP @S RSy RL 4 o < < < < < < ,uXB Y 9( @i7I
+ X/96S@+ @ h 6@$H荭,
XsX R 9 R2 ,( R9" 9 R g<wn @ (Rͥr 9"!s8H797R9R(̬r Hvn0 @S 9 R 4 o < < < < < <B 9( @i7I
+ Xگ96S@֯ @ h 6@ϯH荭,
XsX R 9 R2 ( R9" 9 R ՠg<nnP @ =@ = 9"ˮs8797R9(͍Rnr mnp =+=9 R o < < < < < < < < ըuXA 9( @i7
+ X9H6S@| @I h 6@uXsX" 9
+R2 mA( R 9 Rh =<Hfn @ h,R.r 9"vs8H797 RTS Dfdn =< @ = = \ 9 RF o < < < < < < < < V uXB Q 9( @i7)
+ X'96S@# @ h 6@ hH. XsX R 9
R2 %s88)( R 9 $R G @g<\n Ղ#Rr9"#97s879(7R cn0 9(@S (q@s
+9 R o < < < < < < < <B 9( @7 G@ήs8h6Xʮ9(6S@Ʈ @ h 6@hH. XsX R 9R2 Rs8H[n0 =<@S8ŭ( R 9 RG cf<Ynp @A 9"#97s8797R9XnP =+=9 R o < < < < < < < < utXB 9( @7 G@js86Xf9H6S@b @ h 6@[ҨN XsX R 9R2 d@%@n o ? H3(4 ( R 9 RB f<Onp @ =B = 9"Ns8h797 R,S hNn0 =< @ = = \ 9 R 9 o = yhC 9 @
+ ` V ( 9( @i7
+ X96S@ @ h 6@(͍Rr XsX h R 9R2 @)@ R ? h ( R 9 R߭ ՠg<(En0 A @ = = @9"s8(79h7(R9hEnP =+= Rcy R o < < < < < < < <B Ϭ 9( @i7)
+ X96S@ @ h 6@ҨN XsX R 9R2 @%@n o ? 4 ( R 9 R zg<<n <D <BC= A@ =" 9s8(79h7R9 @?n+=9 R^ o < < < < < < < tXA k 9( @i7i
+ XA96S@= @) h 6@6(͍҈,R y MlX&
+9HR 9R2 =@)@ R ? Rh ( R 9 (R `ng<6n0 b'R 9"-s8 79H 7HR9,RSyS 9 Rs8-RMrCxc8os8H
79
-7(R9S ( RSy Rs8)R rCx+s8@797R9S c
-9 Rs8,Rr( RCx+s879H7R9S S
-9h Rs8R( r*s8797Z IwsX)@? T{TOSWR_QgPoOC_֠X96S@X96S@X9h6S@X96S@X9h6S@ުE 9H6 96 96 9h6 9h
6} 9 6w 9H 6 9 6 9( 6 9
-6 { 9 6~ v 9H 6y q 96t l 96o g 9h6j 0 9H6D 96@ Y X 96[ S 96V 9h6/@s 96) B A 96D < 96? 7 9h6: 9H797s879(7H ;@N96 9H6 96G@Bs86 96 9h6
- 96
9(6 s8h6X%9(6S@! 9(6 96 9(6 96 9(6 96 9(6 96 9(6 96 9(6 96 9(6 96 9(6 96 9(6 96 9(6 96 9(6 96 9(6 96 9(6 96 9(6 96{ Al Տ ՈBsXA {_O{C HsXA 4@` `: ՈsXA h h~9(7h 9h7h97{AO¨_`&@h 96`@h96`@{AO¨_O{C H
sXA 4@` `: o Ո sXA h h~9(7h 9h7h97{AO¨a`&@_h 96`@[h96`@W{AO¨Sg_WO{ @9 4 0@( ?@ TF{VOUWT_SgRKS{VOUWT_SgR_ c ! rX a G W,sXb G (sXC oR j c bRH A
-]@9K @ q!Hj Ղ RHC^@9* @_ qbH=l "RH R B9 R ߧ rXA Rs rX
_9 6@֨y 7 4 b G C 9h 63@ƨR ըrX! c g_WO{ 2@@^!@ R j T7 7 R8 1 T @ q"ɚ@ T@^jh8H6 @^ Ra @^ @ 2Y@ ^ )@9?j! T )sX*a ) A sXA 9h 6@f hrX! <{DOCWB_AgŨ_c ! rX a G ! WsXb G ȧ sXC oR j c RH A
-]@9K @ q!GjP RGC^@9* @_ qbGRh ՂRG^@9 .@? qAbGR 9 " RG R A9 R ՈrXA Rs brX E
_9 6@y 7 4 b G C 9h 63@ڧf (rX! c 4 sX a S TA rXA 9h 6@H (rX! _WO{0@( ; !@@ TB~h ; T : { њZ8[8 k TZ8[8 kA T#Z8[8 k
- T3Z8[8 kA
- TCZ8[8 k TSZ8[8 kA TcZ8[8 k TsZ8[8 kA TZ8\8 k TZ8\8 kA TZ8#\8 k TZ83\8 kA TZ8C\8 k TZ8S\8 kA TZ8c\8 k TZ8s\8 kA T[8\8 k T[8\8 kA T#[8\8 k T3[8\8 kA TC[8\8 k TS[8\8 kA Tc[8\8 k Ts[8\8 k R (rX a T? UA rXA 9h 6+@ HrX! KZ` [` {WOVWU_T_֠#ƥ ! HrX a ? B (rXA 9h 6+@s ՈrX! Z` ئ[` Ԧɣ Cog_WO{ ! rX a K # ՚rXHc I K : rXhC o<<R 2@ !@@ TB~ T9 @%@ # ?@` ]@Hc IK iC '9h 67@x rX! ҥN{XOWWV_UgToSC_# 0 @` \Hc IK iC '9h 67@Sߥ rX! %; g_WO{ o c ! rX a G rXc G rX(C oR b 6 `b 2 A9 .C? qAbc E"@9( 4R 9c " REk bRE@!@c ? k c BRE ?w h 9h 6@= @
- ="`"c G )C 9h 63@٥e rX! c 3{VOUWT_SgR_ c G )C 9h 63@F (rX! c h~9H7h 97h97h^97 `&@h 96`@h96`@h^9H6`@ _WO{C F@ TB~ T{ @%@# ?@` m{EODWC_B_# 0 @` ^S C_WO{R3 93 " R E&@ TR T? 9? " REF@@ T@!T@ TR; 9; " RD(R7 97 " RD{DOCWB_AC_ `Tg_WO{ @9H 4$F)h({VOUWT_SgR_ c ! irX a G Ӥ rXb G z rXC oR ! j c bRD A
-]@9K @ q!D j Ղ RDC^@9* @_ qbD!k "RD RӤ >9 R HdrXA RSs "@rXޤ
_9 6@y 7 4 b G C 9h 63@$ ^rX! c n Cg_WO{ rX@ c 2@j(h^@9 j@? qH c @ AkP BR^9mk R4Dgp բR0D@ ]@9* 1@_ qa(DVg B R$D W;@ ^9h 6@JH@i^@9* k@_ qi T[ ՉrX)@? T{XOWWV_UgTC_֛ ! ՈNrX a K # rXb K rXC o<<R g0 RC @ !_@9 /@? qAbCAk " RC_9h 6@ R =9 R ݢ IrXA h RA9s բ%rX
- ! _9 6@Уy 7
- 9 4 _9h 6@ţb K C '9h 67@H hCrX! ? qa T ! =rX a K z # w{rXb K ! wrXC o<<R i RZC A
-]@9K @ q!QCiP RMCC^@9* @_ qbECg ՂRACh^@9 j.@? qAb:CR 9 " R5C Rm 9=5 R K Ո7rXA h R's brXxW ? q T[ ! h1rX a K # nrXb K xkrXC o<<R g0 RBA^@9* @_ qbBg0 "RBh^@9 j.@? qAbBR 9 " RB R <5 R ը,rXA h R! s ՂrX!
+ . _9 6@u 7 4
/ 2 _9 6@ڢu 7 U 4 b K C '9h 67@ʢV (%rX! $آ# b K C '9h 67@A Ո"rX! â 9@ h^9h 6`@ CWO{0@3hh | ͡]8 3k Th~Hө]8?(k! Th~Pө#]8?(k T3]8 aSkA Th`өC]8?(k ThhөS]8?(kA Tc]8]8 k Ts]8]8 k R ըTrX a T? UA hQrXA 9h 6+@Y rX! /{TOSWRC_ ՈPrX a ? B hMrXA 9h 6+@9š rX! o% g_WO{0@ hh A9A9 4<@ a ( 4 T@@ a T ! H rX a O + HrXb O XErXC oR i RA@\Ag0 RAȎA^@9* @_ qbA!g0 RA>@IRC 9C " RAB@B RC 9C " RAHRC 9C " RA@9* A_ qa Ag B RAD^@9* @_ qbA Rġ C ;9 RC hrXA Rr BqXϡ
4@@ a
T ! qX a O k + 9rXb O 6rXC oR i RLA@~g0 RFAȎA^@9* @_ qb=Ai ՂR9AB@ϠHRC 9C " R2A@9* A_ qa *Af B R&AD^@9* @_ qb A RV C ";9 RC 4 ըqXA R!r ՂqXar T{WOVWU_TgS_ ! qX a O + W+rXb O 'rXC oR i R@@pog0 R@ȎA^@9* @_ qb@!og0 ՂR@>@]HRC 9C " R@@9* A_ qa @f B R@D^@9* @_ qb@ R C :9 RC hqXA Rr BqX 1 , 97Y 5 96
- 9H6 @ 6 b O C 9h 6;@" ըqX! l og_WO{ # ! (qX a ? L ոrXc ? :rXYC oRs 2@jh@%@# ?2:c ? IC 9h 6+@Mٟ ՈqX! # #{VOUWT_SgRoQ_ c ? 9h 6+@/ qX! # g_WO{ o c ! qX a G rXc G rX(C oR b `b A9 .C? qAbc ?"@9( 4R 9c " R?k bR?@!@c ? k c BR? 9w h 9h 6@ɟ= @
- ="`"c G )C 9h 63@E qX! c {VOUWT_SgR_ c G )C 9h 63@& (qX! c ph~9H7h 97h97h^97~ `&@h 96`@h96`@|h^9H6`@xm 4@ @%@@ ( @^( )R Ԟ m( R y_ < ( R9_#mO{ \9 @ q4# 2 N g !` T @ q T@ TS h N{COB#Am_ RK <g0 Մ AqX «qX_ R? AqX ªqXU B WO{C hqX@ ( R )
+7(R9S ( RSy Rs8)R rCx\s8@797R9S c
+9 Rs8,Rr( RCxGs879H7R9S S
+9h Rs8R( r5s8797Z tX)@? T{TOSWR_QgPoOC_֠X96S@X96S@X9h6S@X96S@X9h6S@ 9H6 96 96 9h6 9h
6} 9 6w 9H 6 9 6 9( 6 9
+6 { 9 6~ v 9H 6y q 96t l 96o g 9h6j 0 9H6D 96@ Y X 96[ S 96V 9h6/@ 96) B A 96D < 96? 7 9h6: 9H797s879(7ר ;@96 9H6 96G@s86 96 9h6
+ 96
9(6 s8h6Xϫ9(6S@˫ 9(6 96 9(6 96 9(6 96 9(6 96 9(6 96 9(6 96 9(6 96 9(6 96 9(6 96 9(6 96 9(6 96 9(6 96 9(6 96 9(6 96{ l 6 tXA {_O{C HtXA 4@` `: A ՈtXA h h~9(7h 9h7h97{AO¨_`&@1h 96`@-h96`@){AO¨_O{C HtXA 4@` `: ՈtXA h h~9(7h 9h7h97{AO¨ `&@ h 96`@h96`@{AO¨g_WO{ @9 4 0@( ?@ TF{VOUWT_SgR<{VOUWT_SgR_ c ! ltX a G תtXb G L XtXC oR AkP c bR# A
+]@9K @ q!#!kP Ղ R#C^@9* @_ qb#i0 "R# R I9 R htXA R-u bCtX
_9 6@y 7 4 b G C 9h 63@p ըbtX! c ĩCA g_WO{ 2@{@^!@ R j T7 7 R8 k 1 T @ q"ɚ@ T@^jh8H6 @^ R @^ @ 2 @ ^ )@9?j! T թtX*a ) A ՈtXA 9h 6@ hVtX! F{DOCWB_AgŨ_c ! PtX a G ȩ tXb G l XtXC oR kP c R" A
+]@9K @ q!"!k R"C^@9* @_ qb"ymP ՂR"^@9 .@? qAb"R 9 " R" R ]9 R ՈJtXA Ru %tXʩE
_9 6@y 7 4 b G C 9h 63@
+ (EtX! c بW ՈtX a S TA H|tXA 9h 6@f (AtX! 97 Cog_WO{ ! :tX a K # xtXHc I K {utXhC o<<R 2@ !@@ TB~ ) T9 @!@ # ?@`
Hc IK iC '9h 67@ 4tX! UԨ{XOWWV_UgToSC_# @` Hc IK iC '9h 67@ܨb /tX! . g_WO{ o c ! (tX a G ftXc G - yctX(C oR b `b A9 .C? qAbc y!"@9( 4R 9c " Rq!awip bRm!@ @c ? vip c BRb! %w h 9h 6@r= @
+ ="`"c G )C 9h 63@b tX! c 5{VOUWT_SgR_ c G )C 9h 63@Cɧ tX! c h~9H7h 97h97h^97 `&@-h 96`@)h96`@%h^9H6`@! _WO{C F@ TB~ T @!@# ?@` {EODWC_B_# @` C_WO{R3 93 " R &@ TR T? 9? " R F@0@ T@!T@ TR; 9; " R (R7 97 " R {DOCWB_AC_ `Tg_WO{ @9H 4$F)h({VOUWT_SgR_ c ! tX a G Y @tXb G x=tXC oR akP c bRS A
+]@9K @ q!J AkP Ղ RF C^@9* @_ qb> Ri0 "R: R\
9 R 7 (sXA Rt ՂsXg
_9 6@1y 7 4G b G C 9h 63@! sX! c u g_WO{ # 2@j(h^@9 j@? qH [? T ## %@H # +Fip R(# %!l R }mP բR @ ]@9* 1@_ qa rhP B R # `@ T ^9h 6@ѦϦ [i^@9* k@_ qi T{WOVWU_TgS_ ! ըsX a K # շ&tXb K + 8#tXC o<<R !tm R [# # @9 @? qAbp 8ip " Rl 9h 6@ R # (
9 R# e sXA h Rat BsX ! 9 6@[y 7
+ 9 4q 9h 6@Pb K C '9h 67@Gͥ ՈsX! ? qa TH ! sX a K # tXb K XtXC o<<R dkP R A
+]@9K @ q! dk R C^@9* @_ qb a mP ՂR h^@9 j.@? qAb R# 9# " R R # 5 R# Ѥ hsXA h Rt ¬sXW ? q T ! HsX a K # W tXb K @ tXC o<<R Um R A^@9* @_ qb !Tm "R h^@9 j.@? qAb R# 9# " R} R # = 5 R# z ՈsXA h Rt sX
+ . 9 6@tu 7 4
/ 2 9 6@cu 7 U 4y b K C '9h 67@S٤ sX! &a" b K C '9h 67@>Ĥ hsX! L
# @ h^9h 6`@)' 5g_WO{0@ hh A9A9 4<@ a ( 4 T@@ a T ! ȲsX a O ؤ + sXb O | XsXC oR !DkP R @Ll R ȎA^@9* @_ qb al R >@9RC 9C " R B@2 RC 9C " R HRC 9C " R @9* A_ qa .hP B R D^@9* @_ qb R C X 9 RC sXA Raot BsXŤ
4@@ a
T ! ՈsX a O ^ + sXb O sXC oR 4kP RX @ңAl RR ȎA^@9* @_ qbI 2kP ՂRE B@HRC 9C " R> @9* A_ qa 6 hP B R2 D^@9* @_ qb* RL C
+9 RC ' (sXA Rat ՂwsXWr T{WOVWU_TgS_ ! HsX a O + WsXb O sXC oR &kP R @`l R ȎA^@9* @_ qb al ՂR >@MHRC 9C " R @9* A_ qa hP B R D^@9* @_ qb Rڣ C x
+9 RC sXA RaSt BisX 1 , 97Y 5 96
+ 9H6 @ 6 b O C 9h 6;@ (sX! _] og_WO{ # ! ըsX a ? ? ոsXc ? :sXYC oRs 2@jh@!@# ? c ? IC 9h 6+@Cɢ }sX! # {VOUWT_SgRoQ_ c ? 9h 6+@% HysX! # y g_WO{ o c ! ՈrsX a G ֢ sXc G z sX(C oR b `b A9 .C? qAbc "@9( 4R 9c " Rhp bR@ @c ? ahp c BR r w h 9h 6@= @
+ ="`"ڡc G )C 9h 63@5 ՈjsX! c {VOUWT_SgR_ c G )C 9h 63@ ըfsX! c ch~9H7h 97h97h^97Y `&@zh 96`@vh96`@rh^9H6`@nH 4@ @!@@ ( @^( )R ġ m( R y_ < ( R9_#mO{ \9 @ q4# 2 Ny g !` T @ q T@ TS h N{COB#Am_ RA l XsX BSsXU R5 WsX BRsXK 8 WO{ ( R )
@9_ q T !ʚ T
- @8_ qiT _ T_ T R ( R *@8J2_q T K @8k2qA T K-@8k2q T K=@8k2q! T KM@8k2q# T K]@8k2qa# T Km@8k2q# T
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- K5@8k2q
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+ @8_ qiT _ T_ T R ( R *@8J2_q T K @8k2qA T K-@8k2q T K=@8k2q T KM@8k2q T K]@8k2q# T Km@8k2qa# T
+|@8J2_q T R ) R I R
+ K5@8k2q T l @82q Tl @82qa TH@9 qA T4 @9 Q?% qT y)Q }q) ZzT)R 9 q T
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+ RMRN}
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- @c? q`T*2_q T)2?qS i @a q a `
+ @c? q`T*2_q T)2?qS i @a q a
+ R Acbc!b (` *2_qT
- @8_ q+ R_ q4@9+ Q% q T RLRk} i) + Q @8- Q) qCTq TLHR S t g6 n 4 a )2?qs a )2?qq T Ձd\ a ן Ad\ a W_ q qT&R ! q# Tn 2 g!b ! Q qTk 5
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+ @8_ q+ R_ q4@9+ Q% q T RLRk} i) + Q @8- Q) qCTq TvHR S t gx n 4 a )2?qs a )2?qq T e\ a ן e\ a W_ q qT&R ! q Tn 2 g!b ! Q qTk 5
+S i q gg ` B n K4d !b k qT R1# e@ /l ՂR, )$l R!j "R@ ]@9* 1@_ qaAgP B RajP bR `@ 5 ^9h 6@ѠϠ S j g{COBWA_֩ R R B@ @ { R hesXA ALt բ#sXϠog_WO{ @ x" (\@9 *,@? qzU T@ < (@9 )@ q;v3v @ qr` 4 7 _ T(@ 6@ qa 4@7@@
+ @ @@u R] @ l ~
+ h@@ h @ `@/h
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- (hJ x 0 șqXA h o`<`<Rh w9 sqXA h {DOCWB_AgŨ_ Ո]qX! ey O{C )@d ? T`" {AO¨_? T {AO¨_ @@`4 {AO¨_@t _Cog_WO{ ՈqX@ Ո1qX8 6R@R")
@ ! q(@ %{@ R9hύR(rc R y=<#@G # @ R9hόR-r (Rr3_9x# @ " T \ T9Y
(C | HA# W k98c ~@ R_9i/Rlr Ry<<@w R@R%
+ ! R{FOEWD_CgBoA_ 6 O{ esX@ ? T @ Th@@ T ` : h@ T @
@ ?ր@ @@ ?h@ + @)
@ ?`@ @@ ?ֈ@h @
@ ?ր@ @@ ?֟ `@ @
@ ?`@ @@ ? @
@ ?@@ ?s @ թ[sX)@? T{COB_C_֟{ R؟ȇv {_(v ( __ǟg_WO{h @9 q &R ը sXA P ըsX a 9FsX8 | h"(c h
+ (hJ x ! AsXA h o`<`<Rh w9 hsXA h {DOCWB_AgŨ_ (sX! Y{U O{C )@e ? T`" {AO¨_? T {AO¨_ @@`4 {AO¨_`v _Cog_WO{ HsX@ ըrX8 6R@R")
@ ! q(@ {@ R9hύR(rc R y=<#@G # @ R9hόR-r (Rr3_9x#r @ " T \ T9Y
(C | HA# W k98c ~@ R_9i/Rlr Ry<<@w R@R%
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- T{XOWWV_UgToSC_@ 96{@9h6o@_9(6c@96W@96K@?9h6?@9(63@_96@96@} 9h6@y qX4 Rx qX
-d <(jp @ R 9 9 @2qXB o qXě* qXrN 96K@N
- 4 R$ 4 RU R% 5 R4 R! : +@#197 9(79h7_97979(7?9h797_9h 6@' R9h 6@"u R 9 6@ t 7 4|8 7r87 AT
- ^
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-R ՁhqX ՠYbj0 < A
@ (͍R謯r@ 9 ՀqXB `pX pX 9h 6@ _WO{C ըpX8H 6R@R") @# u
- `qX# - 9h 6@g{EODWC_B_ pX4
-Ra ]qX Ob(j0 < A
@ (͍R謯r@ 9 qXB U ՠpXg pX\ 9h 6@8- W O {
C H[qX@ pX8
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- 4 49h 63@t9h 6'@pe K@k?9H6?@g963@c96'@__97#m_WO{ (P@RH )@ pX8 6# NF Ճ<qX# 9h 6@8{FOEWD_C#Bm_ ՀpXO4
-R1 A9qX dHj0 < C @ A 9 pXB & @pX8 ՠpX- 9h 6@ _WO{C 5qX@ (P@RH )
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- T{^O]W\_[oZ_c@96W@_96@96'@9H63@}?96?@y `pX`4 Rx !qX c(}j0 < =<< = x 9 @pXB o `pX pXz`4 !pXR){j (\ 9(@( (a@(` ?8 9 @pXB W ՠpXi ՠpX] 4 RP @c -4 RM 4 RR 4 RU RR 5 R4 RR O@C_97979H7?979797 9H797 96@ R 7. @ 9H6@96@?96@ 96@9H6@ 96{@96o@ 97 R 4@c _9797_9h 6@9h 6'@ݖu R9h 63@ؖ?9 6?@Ԗt 7% 4|c8 7r87 AT ^Ėr8H6 ] T c@96W@_9H7 ?9h 6?@ og_WO{ hpX@(P@RH )@ 1 T ըupX8 6@ @C ?cR9h(LO 9= <3@c 3 D9 4@
@ ? @@Z )pX)@? T{[OZWY_XgWoV ?9 9~@c R9R
- yhoR.r ;9< <'@{ ' R@R(# @ @ @ ??9hR̬r y9 = <@ R@R(# @@ @# ? R9chOR(r+ Rr3 9< <@ ! 7 ccB ՠpX ;@_9(79h797?979(79h7 97979(79h7?9797#=K@h
- `=Z ՉpX)@? T{[OZWY_XgWoV_@ȕ96@ĕ96@?9h6@9(6s@96g@ 96[@9h6O@9(6@96@?96 @9h6+@ `VpX4 R աpX @bCjP < =<Ѐ< = t 9 ՀvpXB `SpX RpXL 5 R4 R-
- 4 R 4 RU R! > ;@]_9h79797?9(79h797 979( 79h 6@S R9h 6@Nu R?9h 6 @I9 6+@Et 7 4|c8 7r87 AT
- ^5r8H6 ]0 T# @)96@%9h6@!?9(6@ 96s@96g@ 9h6[@9(6O@
97WO{ HpXA ipX (a ( ( )pX (A Ȏ9h 6`6@z (ipX! fĔ{BOAWè_WO{ |pXA )pX (a ( ( pX (A Ȏ9h 6`6@ĔP cpX! <{BOAWèWO {
- ըpX@ h8pX8 pX 6@h@ @ R R ? R9hύR荬rK Rhr?9=< @; c ! c ##) c @c w9797_9(7` A9 /C? q AbD4 9h 6@n] IpX)@?! T{JOIWH_3@a9h6'@]_9(6@Y -pXu4 յ+pXR^ 9hύ荬lO " 9 ՠNpXB Q (pX ՖpX Հ*pX^ 9h6@ @c #9 797_9H7
3@$9H6'@ _9 6@ ] 9 9_O{ hB @# # R R ?@9 @? qAb39 7{COB_@{COB_ 9h 6@ og_WO{C ȑpX@@` T |@pX T Bh^@9
- k2@_ qy
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A@_ aTZ IpX)@?! T{YOXWW_VgUoT_ְ h^9h6 c D*@ h^97. Ԩ^9h 6@20h^96`@,! ԉoO{C ypX@ $@(CiU} # C f`@( AiP C R(!Bi C R2aip bR2@ ]@9* 1@_ qa2A+e B R2ip բR2C )@ ^9h 6@@i@
+ ! ? qH @ ʞ R 9hύR譯r 9=< @ #! ' #wb #w#wB#w 5sX#+@#09h7 9797_9(79h797?979(7_9h797 97Z 4sX)@?
+ T{XOWWV_UgToSC_@ 96{@9h6o@_9(6c@96W@96K@?9h6?@9(63@|_96@x96@t 9h6@p @rX4 Ro A*sX `?e <rlp @ R 9 9 rXbB f @rXx rXiN 96K@E
+ 4 R$ 4 RU R% 5 R4 R! : +@#k097 9(79h7_97979(7?9h797_9h 6@ R9h 6@u R 9 6@t 7 4|8 7r87 AT
+ ^r8H6 ] Tך @ 9(6{@96o@_96c@9h6W@9(6K@?96?@963@ܝ_9h7_WO{C (rX8 6R@R") @@% 0 # sX# 9h 6@{EODWC_B_ rXʝ4
+R sX Հc`l0 < A
@ (͍R謯r@ 9 rXbB ՀrX rX 9h 6@] _WO{C ȜrX8H 6R@R") @# C sX# 9h 6@^{EODWC_B_ rXv4
+RX !sX cVl0 < A
@ (͍R謯r@ 9 ՠrXbB L rX^ rXS 9h 6@/ W O {
C ըsX@ (rX8
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+ 4 49h 63@k9h 6'@gA K@b?9H6?@^963@Z96'@V_97#m_WO{ (P@RH )@ xrX8 6# N rX# e 9h 6@/{FOEWD_C#Bm_ ՠtrXF4
+R( աrX Pe(5l0 < C @ A 9 rXbB `qrX/ prX$ 9h 6@ ژ _WO{C (P@RH )
@y@~
+ @$@(CiU} T q T * Ie Պ +ih8J @ @ @# ? @ @# ?<@h
+ `={EODWC_B_@ @# ?@ @# ?# skp
R# (lp "R# %
+ # k o_W O { hrX@ h^rX8h 6 (^rX8h# 6G 4!R qT R9hR(Lr hRy{9<<G@ G ; R9hύR(r Ry=<;@ ; R@R") @# R?9hR,r;ȬR{y9<</@ / ȢD9 4~@j@( @ R9hoRͮr ȮRHr2 9=< @k c ! c 7t @rX c 6 R R 9 9 R9cC(Rhr2 hoR.r 9=<#@ # C! K Ccct CtC tCt ՠrXCӗO@C-_9h79797?9(79h797 979(7 9h7 5- @̚96@Ț9h6@Ě?9(6@96@96@ 9h6{@9(6o@ 96@V 4@c ,_979H7_979797?9H7[ ՉrX)@?a
+ T{^O]W\_[oZ_c@96W@_96@96'@9H63@}?96?@y ՠ=rX`4 Rx աrX Հd(l0 < =<< = x 9 [rXbB o ՠ:rX `:rXz`4 աrXR) l (\ 9(@( (a@(` ?8 9 XrXbB W 7rXi 6rX] 4 RP @c p,4 RM 4 RR 4 RU RR 5 R4 RR O@C^,_97979H7?979797 9H797 96@ R 7. @ 9H6@96@?96@ 96@9H6@ 96{@96o@ 97 R 4@c ",_9797_9h 6@9h 6'@ݙu R9h 63@ؙ?9 6?@ԙt 7% 4|c8 7r87 AT ^ęr8H6 ] T c@96W@_9H7 ?9h 6?@ og_WO{ rX@(P@RH )@ 1 T ը rX8 6@ @C ?cR9h(LO 9= <3@c 3 D9 4@
@ ? @@Z թrX)@? T{[OZWY_XgWoV ?9 9~@c R9R
+ yhoR.r ;9< <'@{ ' R@R(# @ @ @ ??9hR̬r y9 = <@ R@R(# @@ @# ? R9chOR(r+ Rr3 9< <@ ! 7 cc%r rrBr wrX;@-+_9(79h797?979(79h7 97979(79h7?9797#=K@h
+ `=Z zrX)@? T{[OZWY_XgWoV_@Ș96@Ę96@?9h6@9(6s@96g@ 96[@9h6O@9(6@96@?96 @9h6+@ `qX4 R jrX @ckP < =<Ѐ< = t 9 @ rXbB `qX qXL 5 R4 R-
+ 4 R 4 RU R! > ;@*_9h79797?9(79h797 979( 79h 6@S R9h 6@Nu R?9h 6 @I9 6+@Et 7 4|c8 7r87 AT
+ ^5r8H6 ]0 T @)96@%9h6@!?9(6@ 96s@96g@ 9h6[@9(6O@
97WO{ *rXA թPrX (a ( ( iMrX (A Ȏ9h 6`6@t rX! `{BOAWè_WO{ $rXA iKrX (a ( ( )HrX (A Ȏ9h 6`6@ėJ ը rX! 6{BOAWèWO {
+ (UrX@ hqX8 UMrX 6@h@ @ R R ? R9hύR荬rK Rhr?9=< @; c ! c ##p c r@c )9797_9(7` A9 /C? q AbZ 9h 6@n] LrX)@?! T{JOIWH_3@a9h6'@]_9(6@Y qXu4 յqXR^ 9hύ荬lO " 9 `qXbB Q h@rX @rX ՀqX^ 9h6@ @c f)9 797_9H7
3@$9H6'@ _9 6@ ] 9 9_O{ hB @# # R R ?@9 @? qAb9 7{COB_@{COB_ 9h 6@ɓ og_WO{ @ T)Bh^@9
+ k2@_ qw*_@9K ,@ q: * T C c qX @ # ajp BR# aj R}k0 R @ ]@9* 1@_ qalfP B R# * @ ^9h 6@@(_9(7 @ @(_9(6@ C
+]@9K @ q#@ @
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+@_ aT\@9 bT _ ] 4 JTT T{GOFWE_DgCoB_ h^96 # ͽ @ h^97 Ԩ^9h 6@97h^96`@3
AO{ $@(CiU} i T 3 C c # @ # MjkP RJ# Gaj Rlkp bR @ ]@9* 1@_ qaWfP B Rjkp բR# ~ @ 4 ^9h 6@ @i@
R %
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- T c ! pX a G X]pXc G 0 YpX(C oR g c B Rj2@ ajiP բ Rd2@!ci B R^2 e, R _9h 6@c G )C 9h 63@v ըpX! c БL {VOUWT_SgR_ a _9H6@[ c G )C 9h 63@Kב HpX! c !7 og_WO{CC [pX@(P@RH )
@K 4!R89 qT R 9hR(Lr hRky9#=<K@o K A{@ R9hύR(r Ry<<?@ ? @$@(CiU} T P @ b& T \ " TC9 C͑ (C | hA+ ݒ_k98 R9X(Rr3 hόR-r _9=<3@ 3 R_9hoRͭrCRy 9~@R@R" @ R 9hR̬rsRy9<<'@ ' R@R" @ v R^ 9hOR(r Rr39h# = =@ R@R"
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@K 4!RȔ9 qT R 9hR(Lr hRky9#=<K@o K }A{@ R9hύR(r Ry<<?@ ? @$@(CiU} TX ږ @ b& T \ " TC9 CZ (C |y hA+ g_k98 R9X(Rr3 hόR-r _9=<3@ 3 R_9hoRͭrCRy 9f~@R@R" @ % R 9hR̬rsRy9<<'@ ' R@R" @ v R^ 9hOR(r Rr39h# = =@ R@R"
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- 4|8 7r87 ATI ^Ir8H6 ]D T? @?96@;?9h6@79(6@396@/ 96@+9h6@'_9(6@#96@ 96@?9h6@9(6s@96g@ 96[@ 9h7 _9h 6C@ #m_WO{ N pX oX# 34a _G a ȢG b h pXB oR # A @^ )R N9)b ɢB G 9h 63@J (oX! # 6{VOUWT_S#Rm_ b ɢB G 9h 63@- HoX! # s oO{C pX@ $@(CiU} # C \@( ariP C Rl$Ah C RB/sip bR>/@ ]@9* 1@_ qa6/ad B R2/!rip բR./C a&@ ^9h 6@TR@i@ yh] ioX)@? T{UOToS_֬ C E&@@ m}0 Ԙ_5{ R7(s {_(s ( __&g_WO{h @9 q &R oXA P ȪoX a oX8 ގ h"(c h
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- 4 R, 4 Ru R- 4 RU R) 5 R4 R) B ;@T97_9(79h797?979( 79h 7 9 79 7_9(
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B = @
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C hoX@ h+oX8
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B A
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@# ? 9#9C R_9R
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+ 4|8 7r87 ATI ^ٓr8H6 ]ԓ T? @ϓ96@˓?9h6@Ǔ9(6@Ó96@ 96@9h6@_9(6@96@96@?9h6@9(6s@96g@ 96[@9h7 _9h 6C@m #m_WO{ N VqX ՈqX# 34a _G a MȢG b qXB oR # A @^ )R NÒb ɢB G 9h 63@NԒ }qX! # !{VOUWT_S#Rm_ b ɢB G 9h 63@1 zqX! # O{ $@(CiU} i T 3 C c # @ # ?! kP բR<# 9fj R A
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+ 4 R, 4 Ru R- 4 RU R) 5 R4 R) B ;@)#97_9(79h797?979( 79h 7 9 79 7_9(
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+ ^r8H6 ] T @_9(6@96@96@?9h6@9(6s@96g@ 96[@9h6O@_9(6C@97#m_WO{ (P@RH )@ A% ( (pX8( 60 # K gqX# i 9h 6@_{FOEWD_C#Bm_ ՠpXv4 RX աdqX Հc <hj G C
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- ^r8H6 ] T [@96O@97og_WO{ ըoX@ nX8 6# q(R9 hX' R yYc 9 4fP ?k88 1 T hp c p9 qTR?9h/ȍ? 9<@<@S R@R") @@? 1 T @ ? @ ? R9#ԂRhr2 hύR荬r 9=@< @k ! ##s s s `nX , @ _97979(7?9h79797_9(79h7Z ՉnX)@? T{SORWQ_PgOoN_c@ 9h6W@9(6K@?96?@963@9h6'@_9(6@96@ ~nX 4 R nX `~hp < = @ = ` 9 ՠnXB چ {nX8/ {nXV 4 R @ _9(79h797?979(79h7_9h 6@ R9 6@t 77 4H R c@96W@96K@?9h6?@9(63@96'@_97 9h 6@( R|#8 7r87 AT
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+ ^Jr8H6 ]E T [@>96O@:97og_WO{ hpX@ (OpX8 6# q(R9 )jX' R yYc 9 4gP ?k88 1 T #jp c 9 qTR?9h/ȍ? 9<@<@S R@R") @@? 1 T @ ? @ ? R9#ԂRhr2 hύR荬r 9=@< @k ! ##c c c pX @ _97979(7?9h79797_9(79h7Z IpX)@? T{SORWQ_PgOoN_c@9h6W@9(6K@?96?@963@9h6'@~_9(6@z96@v 9pX 4 Ru ՁpX ՠajp < = @ = ` 9 ՠZpXBB l 6pX~8 @5pXrV 4 R @ _9(79h797?979(79h7_9h 6@; R9 6@6t 77 4H R c@/96W@+96K@'?9h6?@#9(63@ 96'@_97 9h 6@( R|#8 7r87 AT
+ ^r8H6 ] T؆ og_WO{CC ըpX@(P@RH )
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+y)) Toyi/4@yiiV@) ?h T) R )Pi I R Ri yt} C9i+@J
+ TC b T(h 7D @)yt
@JJC!
-i TM b T
h+ @h? h@yy8 bs9`h3@ytp 6hR@G q T q T a&@ `c @ q@ T qa Ta&@6 u a&@ l a&@ f R[ #c'@ AQP cR`UP cRpkaQp ՂRlk'@ ]@9* 1@_ qadk!>L B R`kcb'@ ^9h 6@ a&@/ 1 R[ #c'@ QP cBRf`NP cR<k!Q R8k'@ ]@9* 1@_ qa0k7L B R,kc_b'@ ^9h 6@RPa&@ Y ~WX)@?A T{^O]W\_[gZoY#Xm_֤ c;b'@@ ž c4b'@` c+b'@@ ~*_WO {
- R zAz {qb F`@t ` j\ @@ ?֎r @)@ ? u@ R t 4 hLWXA F @) @ ?s@ R JWX HWXA F @) @ ?s@ R ՉFWX)A `Fh @ @ ?{JOIWH_G_ wj\ @@ ? _WO {
- R zAz
-qb `@t ` Jj\ @@ ? r @)@ ? u@ R t 4 >WXA F @) @ ?s@ Ru թ;WX Ո:WXA F @) @ ?s@ Rc )8WX)A `Fh @ @ ?{JOIWH_G_ j\ @@ ?>3 H@. ! e T R_D@9 4pAh d tA% { {&og_WO{C @hR 9 ըQX (LR(rs 9 @W xR @ @9 @ q9?/ 53u H@ q ` 47 ?/ HTu H@ q ` 4 7 ?/ T@ : ab j@R 9(LR(rC HQp ==96 R @ ق @9 @_ q8 S 3t (@_ q ` 47 S HTt (@_ q ` 4 7 S T@ aB {YOXWW_VgUoT_ ? q! T RB@ 4 R ՀvJ<Q @ A = =
R@9 D9 c R# R+AQP RMi!Q Ղ
-RIiAQ0 բ
-REiaQp բ
-RAiQ0 Ղ
-R=iQP "R9iQ ՂR5i 9h 6@]# hA8 4 W
CF^ R( Rh 9@S @ T T8 7 шr8(6 ^5 шr8h6]0@ ,@S @ T T8 7 шr8(6 ^ шr8h6]@ (j + - @` @ @ T87 Ѩr8H7!T ^ Ѩr86]T@ 9h 6@ =( WO{ C ` #jhR 9(LR(rs ըPX 9`@ @
@ ? R #" ) R)@ @ i q T9 @@ ? 9h 6@եW ըB ' # A 3@cB # R 9(LR(rC _Qp ==9`@ @
@ ? R # " ) R)`@t @ i q T9 @@ ? 9h 6@sB # A @b{IOHWG_ e a 9h 6@[B # 9h 6@RHW A ' # A
@b? Mp _O{C RK
AVX VXa O) { Kp hWXA {_!@@ @$@ R O{C @%{AO¨_WO{ aV@`F@` `J
-`:@@ `.@` `2 `"@` `& t@t h@ T T^ `@ t {BOAWè_g_WO{ @) @ i
- T c ! HVX a G WXc G L YVX(C oR a$N c B Rg@
PP բ Rg@P B Rzg a R _9h 6@c G )C 9h 63@ (VX! c h {VOUWT_SgR_ } _9H6@w c G )C 9h 63@g ȸVX! c =S g_WO{ @) @ `
- T c ! VX a G xVXc G VX(C oR N c B Rf@OP բ Rf@AO B Rf ` R . _9h 6@c G )C 9h 63@ ȬVX! c a {VOUWT_SgR_ _9H6@ c G )C 9h 63@h hVX! c 6 _WO{ @I)CkU)} ? TIUl@ C} ( TJ JCkUJ} K1 _ 1 T }ӫ R" J} a =
+i T b T
h+ @h? h@yy8 bs9`h3@yt 6hR@K q T q T a&@ `c @ q@ T q Ta&@
+ a&@ ~ a&@ x RC q! T+ 5 RK qa T+ f C#-+@( C'a&RP R@'='!P R>)Rp ՂR>+@ ]@9* 1@_ qa>ULP B R>x+@+ 6 ^9h 6@ + a&@: 4 C#+@( # ' RP BR '#'AP R>#R R>+@ ]@9* 1@_ qa>NLP B R>#A+@+ 6 ^9h 6@ + a&@ {LOKWJ_IgHoG#FmC_ #!+@+ +@+ v
+ #+@+ @ ~] ԑ_WO {
+ Rz zAz gb `@t ` b `\ @@ ?ְr @)@ ? u@ RX t 4 WXA F @) @ ?s@ RH ՉWX hWXA F @) @ ?s@ R6 WX)A `Fh @ @ ?{JOIWH_G_ W`\ @@ ? _WO {
+ R zAz fb `@t ` 3 *`\ @@ ??r @)@ ? u@ R t 4 ՈWXA F @) @ ?s@ R )WX WXA F @) @ ?s@ R թWX)A `Fh @ @ ?{JOIWH_G_ _\ @@ ?z D@9 4pA R$ R tA R$ R_D@9 4pAh tA@ v_p { m {Cog_WO{ @FhR 9~Q0 @ (LR(rs 9 @W xR @ @9 @ q9?/ 53u H@ q L` 47 ?/ HTu H@ q ?` 4 7 ?/ T@t V ab _YU Z T T8 7 r8(6 ^& r8h6]!Y @R 9(LR(rC Qp ==96 R @ ق @9 @_ q8 S 3t (@_ q ` 47 S HTt (@_ q ` 4 7 S T@ aB 2 XS X T T8 7 шr8(6 ^ шr8h6]X{\O[WZ_YgXoWC_ ? q T R;@ 4 R ՠJ<Q @ A = =
R@9 D9 c "R# RQP R<Q Ղ
+R<Q0 բ
+R|<!Qp բ
+Rx<aQ0 Ղ
+Rt<QP "Rp<Q ՂRl< 9h 6@~# hA8 4
EC ` R( Rh 9@S @ T T8 7 шr8(6 ^W шr8h6]R@ N@S @ T T8 7 шr8(6 ^< шr8h6]7@ 3Jk + - @` *@ @ T87 Ѩr8H7!T ^ Ѩr86]T@ 9h 6@ WO{ C ` #)`hR 9(LR(rsMQ0 @ 9`@ @
@ ? R #" ) R)@ @ i q T9 @@ ? 9h 6@]X ըB ' # A 3@*B # 0 R 9(LR(rC Qp ==9`@ @
@ ? R # ջ" ) R)`@t @ i q T9 @@ ? 9h 6@B # A @s*{IOHWG_ 9h 6@}B # 9h 6@tHSX A ' # A
@P*F N0 _O{C Rm
A^WX XWX q0 { KP 1 WXA {_!@@ @$@ R O{C @It{AO¨_WO{ aV@YT`F@` `J ,`:@@ )`.@` `2 %`"@` `& !t@t h@ T T^ `@ t
{BOAWè_g_WO{C # ! PWX a ? ؎WXc ? l YWX(C oRs N # B R:@6awP բ R:@0pPP B R: R v( c ? )C 9h 6+@D hLWX! # {UOTWS_RgQ_ c ? )C 9h 6+@" (HWX! # om _WO{ @I)CkU)} ? TIUl@ C} ( TJ JCkUJ} K1 _ 1 T }k R" J} a =
@ = ka Ja !T h R )} =
-@K @<)a aTt&@"_ Tu^ v
- {COBWA_Ĩt{COBWA_Ĩ_8)g_WO{ @? T
-@Hz8 "!Ki T A Jy, z_ 1 !
- f@( @? T:FW}Es7@@ T zz(%ȚIj@H( h @ L @*CJ}
+@K @<)a aTt&@"_ T9u^ v
+ {COBWA_Ĩ4{COBWA_Ĩ_g_WO{ @? T
+@Hz8 "!Ki T A Jy, z_ 1 !
+ f@( @? T:FW}s7@@ T zz(%ȚIj@H( h @ L @*CJ}
7 R= <= @
- Ⴠ<v 8 4 4RK 3
- K!ך H%Ț j@Hh F} R@@ T (%Țijt( 4RK 3
- K!ך H%Ț j@H(h F}t@ T (%Țijt((hj4{FOEWD_CgB_ @@ og_WO{CC hVX@] h@ 4 ]
##Cc# "q R* R@ @ !@ ?G ! ) R) R VXA | |7 R #|c{ 6{ @ 6 6 3 + h'@(CW #C'@ APP B R[ZO R1eKP R-e'@ ]@9* 1@_ qa%eAvK B R!eT\'@ _9h 6@G E +@H @( +@ B T i@*yv5yhX @@
!@' W #r#@ PP RZO RdAK0 ՂRd#@ ]@9* 1@_ qadnK B Rd\#@ _9h 6@ '@bT@
@j2@IyiS@Jit8G@I ji)8jB@+Ck}"ɚLik)Ii+ '@ џ T 5}h@
!@ T @@
!@' W #q#@ PP RYazO RdK0 ՂRd#@ ]@9* 1@_ qadcK B Rd[#@ _9h 6@ '@ T +@T@b _ 3@s h" h@ @ ?2;@s h" h@ @ ?&C@s h" h@ @ ?Z )VX)@? TC{EODWC_BgAoƨ_ ӣVX`@Kp O `@ ] 3VX`@VPP *
S['@ H[#@ ^9h 6@;93@t " @ @ ?;@t " @ @ ?C@t " @ @ ?
- r#og_WO{CC VX@`\ S h@ 4 4\ J ##Cc# A R8* R@ @ !@ ?G ! ) R) R ՈVXA | |7 R `zcy 6(z D @ s s p + h'@(CW #C'@ PP B RXTO Rnc!yKP Rjc'@ ]@9* 1@_ qabc=K B R^cZ'@ _9h 6@ +@H @( +@ B T i@*yv5yhX @@
!@' W #Ep#@ PP RVXaLO R,cqK0 ՂR(c#@ ]@9* 1@_ qa c5K B R cOZ#@ _9h 6@B @'@bT@
S@G@ @l2@yk,ytxK Ly+xlB@mCӭ}"˚im+i- '@ џ T 5}h@
!@ T @@
!@' W #o#@ APP RXBO RbgK0 ՂRb#@ ]@9* 1@_ qabA+K B RbY#@ _9h 6@ '@ T +@T@ 3@s h" h@ @ ?o;@s h" h@ @ ?cC@s h" h@ @ ?WZ lVX)@? TC{EODWC_BgAoƨ_ skVX`@hKp lO T`@F iVX`@H PP *
Y'@ Y#@ ^9h 6@xv3@t " @ @ ?;@t " @ @ ?C@t " @ @ ?G ԯ!og_WO{CC ը]VX@ \ Ր h@ 4 A ԓ\ ##Cc# B Ru* R@ @ !@ ?G ! ) R) R (KVXA | |7 R xc5x 6ex @ + h'@(CW #C8'@ PP B RVA O Ra@KP Ra'@ ]@9* 1@_ qaaK B RaX'@ _9h 6@ +@H @( +@ B T i@*yv5yhX @@
!@' W #n#@ AzPP RVO Ria9K0 ՂRea#@ ]@9* 1@_ qa]aAJ B RYaX#@ _9h 6@ }'@bT@
S@G@ @l2@yk,ytK Ly+lB@mCӭ}"˚im+i- '@ џ T 5}h@
!@ T @@
!@' W #/n#@ oPP R@V O Ra!/K0 ՂRa#@ ]@9* 1@_ qa
-aJ B Ra9X#@ _9h 6@, *'@ T +@T@ܿ ٿ 3@s h" h@ @ ?;@s h" h@ @ ?C@s h" h@ @ ?Z i4VX)@? TC{EODWC_BgAoƨ_ 3VX`@^Kp A4O Ց`@E s1VX`@OP *
W'@ W#@ ^9h 6@3@t " @ @ ?D;@t " @ @ ?8C@t " @ @ ?, og_WO{C ը%VX@K # 'H)? T )? T)C) ) ? T@@ Q@ @ !@ ?#G# ! ) R) R\ VXA | 7 R | @ vCxv 6v ľ @ ' @(%@(CO #cz#@ cJPP բ#RUcN R_ KP R_#@ ]@9* 1@_ qa_J B R_cW#@ H_9h 6@@ '@( '@ b T@ @)@)
6%@# @)@*ys9yh\@H O cl @ c!BPP բ$RTcN R_aK0 ՂR_ @ ]@9* 1@_ qa_!J B R_cV @ H_9h 6@@#@T@
>@yj k
KC@J}ӭiji-82@kijC@ij &@y+ijk i* #@ !
-BT
- zv
+ Ⴠ<v 8 4 4RK 3
+ K!ך H%Ț j@Hh F} R@@ T (%Țijt( 4RK 3
+ K!ך H%Ț j@H(h F}4@ T (%Țijt((hj4{FOEWD_CgB_d @@ q o g
+_ W O
{ @/ 4|@Oc'
+ @P@ @ !@ ?#G ! ) R) Rr _WXA | 7 R | @ #i# i 6#i @ @I)@I )C T @H ?@ i!!kQP " Rf! c! P R9a&Lp R 9@ ]@9* 1@_ qa9KP B R 9 @ _9h 6@
@( @ B
T @)@*yv9yhXU @ @
!@ ? T @T1 c >@H c !!aQP R!c !P R8a LP ՂR8@ ]@9* 1@_ qa8KP B R8c N@ _9h 6@ @bTx
+ @j2@Iyi7@Jit8/@I ji)8jB@+Ck}"ɚLik)Ii+ @ џ T @T @(@PM 1#@s h" h@ @ ? +@s h" h@ @ ??@s h" h@ @ ?{NOMWL_KgJoI__ ,
+ @ c @ ^9h 6@FD#@t " @ @ ?Ͼ+@t " @ @ ?þ?@t " @ @ ? .o g
+_ W O
{ @/ 4|@Oc' @P@ @ !@ ?#G ! ) R) R 0WXA | 7 R | @ #h# 0h 6#Wh _ @ @I)@I )C T @H =@ !<QP " R O R7aKp R7@ ]@9* 1@_ qa7kKP B R7 &@ _9h 6@ @( @ B
T @)@*yv9yhXU @ @
!@ ? T @T1 c ?=@H c !2QP R c O RH7aKP ՂRD7@ ]@9* 1@_ qa<7aKP B R87c @ _9h 6@G E@bT7@/@8
+ @l2@yk,ytxK Ly+xlB@mCӭ}"˚im+i- @ џ T @T @(@ؼռ 1#@s h" h@ @ ?+@s h" h@ @ ??@s h" h@ @ ?{NOMWL_KgJoI_ ,
+ j@ c ]@ ^9h 6@ν̽#@t " @ @ ?W+@t " @ @ ?K?@t " @ @ ?? Զo g
+_ W O
{ @/ 4|@Oc' @P@ @ !@ ?#G ! ) R) R WXA | 7 R | @ #g# f 6#f @ @I)@I )C T @H <@ y !
QP " Rv s O R 6aKp R 6@ ]@9* 1@_ qa6<KP B R6 @ _9h 6@ @( @ B
T @)@*yv9yhXU @ @
!@ ? T @T1 c ;@H c ) !QP R& c # O R5aKP ՂR5@ ]@9* 1@_ qa52KP B R5c ^@ _9h 6@ϼ ͼ@bT7@/@8
+ @l2@yk,ytK Ly+lB@mCӭ}"˚im+i- @ џ T @T @(@`] 1#@s h" h@ @ ?-+@s h" h@ @ ?!?@s h" h@ @ ?{NOMWL_KgJoI_o ,
+ @ c @ ^9h 6@VT#@t " @ @ ?+@t " @ @ ?ӻ?@t " @ @ ?ǻ
+ >o g
+_ W O
{ 9# Ezy)? T )? T)C) ) ? T@@ Q@ @ !@ ?F ! ) R) R ըVXA | 7 R | @ cec#7e 6c^e f @ # @I)@I )C T #@H : @H PP Ղ#R }O R4!Kp R4 @ ]@9* 1@_ qa4A KP B R4 , @ H_9h 6@@ #@ #@ T#A;@@
!@ 3 J@KysYyi|@I ? T @T1 F:@ PP Ղ$R sO RO4AKP ՂRK4@ ]@9* 1@_ qaC4aKP B R?4 @ H_9h 6@@NL @T@
>@yj k
KYJ}ӭiji-82@kijYij &@y+ijk i* @ !
+T zv
@@yj2@yj-5>@yjk
K+i,82@jyjj
-B@LCӌ}"ʚmil*ji, @?< 3/@s h" h@ @ ?7@s h" h@ @ ??@s h" h@ @ ?C@` G VZ I VX)@? T{EODWC_BgAoƨ_ UX`@)Kp ! O `@6 SUX`@ȱOP F , B
c,V#@ c!V @ ^9h 6@/@t " @ @ ?7@t " @ @ ??@t " @ @ ?C@` G G og_WO{C UX@K # 1'H)? T )? T)C) ) ? T@@ Q@ @ !@ ?#G# ! ) R) R (UXA | 7 R | @ ;uCt 6u @ N N K ' @(%@(CO #cՋ#@ c!PP բ#RrScN RH^aJP RD^#@ ]@9* 1@_ qa<^!J B R8^ckU#@ H_9h 6@@^\ '@h '@
T@ @)@)
6%@# @)@*ys9yh\@H O c k @ c
PP բ$R-ScAN R^J0 ՂR] @ ]@9* 1@_ qa]J B R]c&U @ H_9h 6@@#@T@
C@
- >@ymkK}/imy/x &@y++imk +i- #@ ! T|
- zv
@@ym2@ym5>@ymk
KKy,xk B@mCӭ}"˚im+i- @ 9/@s h" h@ @ ?p7@s h" h@ @ ?d?@s h" h@ @ ?XC@` G Z iUX)@? T{EODWC_BgAoƨ_ UX`@Jp AN Q`@C sUX`@}OP F , B
cT#@ cT @ ^9h 6@us/@t " @ @ ?7@t " @ @ ??@t " @ @ ?C@` G K@ Ԩ og_WO{C (UX@K # 'H)? T )? T)C) ) ? T@@ Q@ @ !@ ?#G# ! ) R) R HUXA | 7 R | @ sC4s 6ds @ ' @(%@(CO #c6#@ cAOP բ#RQc|N R\JP R\#@ ]@9* 1@_ qa\AeJ B R\cS#@ H_9h 6@@ '@h '@
T@ @)@)
6%@# @)@*ys9yh\@H O c}i @ cOP բ$RQcasN Rd\J0 ՂR`\ @ ]@9* 1@_ qaX\\J B RT\cS @ H_9h 6@@zx#@T@
C@
- >@ymkK}/imy/ &@y++imk +i- #@ ! T|
- zv
@@ym2@ym5>@ymk
KKy,k B@mCӭ}"˚im+i- @ 9/@s h" h@ @ ?ѻ7@s h" h@ @ ?Ż?@s h" h@ @ ?C@` G Z ՉUX)@? T{EODWC_BgAoƨ_ 3UX`@(Jp aN ղ`@f ՓUX`@JOP F , B
cR#@ cR @ ^9h 6@ֻԻ/@t " @ @ ?e7@t " @ @ ?Y?@t " @ @ ?MC@` G g_WO{ @h
+B@LCӌ}"ʚmil*ji, @T #@@ù +@s h" h@ @ ?3@s h" h@ @ ?;@s h" h@ @ ?xY` ݺ{NOMWL_KgJoI_κ H . D
+ M @ @@ ^9h 6@+@t " @ @ ?:3@t " @ @ ?.;@t " @ @ ?"Y` a ԕo g
+_ W O
{ 9# xy)? T )? T)C) ) ? T@@ Q@ @ !@ ?F ! ) R) RX ՈVXA | 7 R | @ ccc#c 6cc @ # @I)@I )C T #@H 8 @ NPP Ղ#RK HHO R2cKp R2 @ ]@9* 1@_ qa2!JP B R2 @ H_9h 6@@ #@ #@ T#A;@@
!@ 3 J@KysYyi|@I < ? T @T1 8@ PP Ղ$R >O R2!ZKP ՂR2@ ]@9* 1@_ qa2AJP B R2 4@ H_9h 6@@ @T@
Y
+ >@ymkK}/imy/x &@y++imk +i- @ ! T
+ zv
@@ym2@ym5>@ymk
KKy,xk B@mCӭ}"˚im+i- @bT #@@ +@s h" h@ @ ?3@s h" h@ @ ?;@s h" h@ @ ?ոY` :{NOMWL_KgJoI_+ H . D
+ @ @ ^9h 6@ +@t " @ @ ?3@t " @ @ ?;@t " @ @ ?Y` o g
+_ W O
{ 9# vy)? T )? T)C) ) ? T@@ Q@ @ !@ ?F ! ) R) R (hVXA | 7 R | @ cAbc#a 6cb @ I I F # @I)@I )C T #@H I7 @ asPP Ղ#R !O RR1.Kp RN1 @ ]@9* 1@_ qaF1JP B RB1 @ H_9h 6@@QO #@ #@ T#A;@@
!@ 3 J@KysYyi|@I < ? T @T1 6@ \iPP Ղ$RY VA
+O R1%KP ՂR0@ ]@9* 1@_ qa0JP B R0 @ H_9h 6@@ @T@
Y
+ >@ymkK}/imy/ &@y++imk +i- @ ! T
+ zv
@@ym2@ym5>@ymk
KKy,k B@mCӭ}"˚im+i- @bT #@@}z +@s h" h@ @ ?J3@s h" h@ @ ?>;@s h" h@ @ ?2Y` {NOMWL_KgJoI_ֈ H . D
+ @ @ ^9h 6@ki+@t " @ @ ?3@t " @ @ ?;@t " @ @ ?ܶY` A Og_WO{ @h
@ ? Tt@ ˸B *~Ӫ
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+ TwZ y
+ {DOCWB_AgŨ{DOCWB_AgŨ_O{C@? T ( F } h&@ *CJ}
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-UXA F @ @ ?`F @ @ ?`b6` `3`2x`BF` `F`6F` `:Ӹ`*F` `.ϸt&F&T b @ T @@ @@ ?ր@` uFU vF T TԂ_B є" (@ @ ?C`F u`F` ``E` ``.SX`E @@ ?`E` `t,`,`,ߵ`E` `t~Et hE T T^ s`~E tm`jE` `nit^Et hbE T T^ [`^E tbU`JE` `NQ`>E` `BMt2E u6E T ` T^` ? Ѡ] :`2Et66`&E` `*2`E` ` .`"@` `& *` a@ibt@t " @ @ ?{COBWA_Ĩ__WO{ HTXA F @ @ ?`F @ @ ?`b6` `3`2w`BF` `F`6F` `:`*F` `.t&F&T b @ T @@ @@ ?ր@` ۷ٷuFU vF T TԂ_B є" (@ @ ?a`F u`F` ``E` ``.qW`E @@ ?`E` `t,`, `,`E` `t~Et hE T T^ `~E t`jE` `nt^Et hbE T T^ y`^E tbs`JE` `No`>E` `Bkt2E u6E T ` T^` ] Ѡ] X`2Et6T`&E` `*P`E` ` L`"@` `& H` a@at@t " @ @ ?ֶ{COBWA_Ĩ_O{C X@` `^ +t"`b`B~`:@` `> `@` ` `@` ` `@` ` {AO¨__WO{ @c ! @` T)Hp T @@ c B @ @
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R y6 # &D (n/X$ 9h 6@ ¿8 6 R 9-RH̬r
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- q ( b " Y
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- 6 CiU} ( R# c /@( N*P R ' R'O*0 R'/@ ]@9* 1@_ qa'# B R'N*0 R' /@ ^9h 6@ @R 'X)? a T a R V @ T a cA R /X Ո /XA .X! ` c Z V )CjU)}
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- ^9h 6@ L /@ ^9h 6@ Q . L ~ ?9h 6 @p 9h 6@l hb ik I.X)A / 7 9h 6W@` ը.X! c 6 @ @ @ Ta 8i 6 ^L !T@ F @ @ @ Ta 8i 6 ^; !T@ 5 @ @ @ Ta 8i 6 ^* !T@ $ k@ @H_9h 6@@ !@@(_9h 6 @ Cog_WO{ 9 VU~ RxU R
- w! @^ @9 j Tu@ T b h j@
+ =h" = 0XBB 31: 4
+ab? hB o =( tRHUrh =?@ `0XBB ̌ ߌ 9h 6@ CWO{ \@9
+ @_ q+ Tþ%P RZ @ 4h^@9i@K q+ Tk {0X8 6 0X #+P RB 4h^@9i@J _ q( % Tc+P $R2 5 + BR +p RH h^@9
+ i@_ q+ T+p R 4h^@9i@K q+ T+0 R 4h^@9i@J _ q( ! T#+0 R 5 d+ "Ra ^a+P bR h^@9 j@? qH ! T#+P R؊ 5 GA+ "RD Aa+p "R c 9+ բR6c 3 +0 _@9 /@? qAb_9h 6@ c o {DOCWBC_ ՠe0X Փ0X45 A h `d0X V ްݰܰ۰ڰ M հ H _9 6@ c = ð {C 9 R R R {A _og_WO{ @ . T \ T?9Z
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+ oJ R r qB Rr J Rr F ՠ$<~ V 5 A # R R @!@ ?֎ 9 @ b T \ Tc 9V
+ U Rފ - s8(5 չVA
+ oJ R rˊ C@9 q8B Rr J Rr@ F $<~ V h5 A R~ @!@ ?J A+
R + R~ : B | hA# _k68 c ] 9h 6@| ^R s8V q" 9@ q # @ 9h 63@a a +@ 9h 6@Y sZ8 Y q( <RW Y q"# RV 7RK @8 9H797?97s8h 6Y7 a Xl s8h 6V/ {VOUWT_SgRoQ_W@$ 96K@ ?96?@ s86 c ? 9h6@ 8 4 2 " ( 9h 63@ a +@/ 9(6@ 2 k
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+c _ B Tc o =c Rg @^ @9 j Teag+p Rb_k+p բR $P B RAl+0 bRl+0 R A ќ/@^c 0X @ @AR ? ͇ c0 @^ @9 j T.`+p BR+(g+P "R $P B R ae+0 bR g+ BR A O e @o ?9797hb ik / 7 96W@̇ { @ɇ 9h6@Ň CjU)}
+ ) R a T/ / D c р /@ W+p R ( R A`+p R /@ ]@9* 1@_ qa A$P B R~ W+P Rz /@/ 5 ^9h 6@ @4 T Ta 8i6 ^y Uu W WS W T Ta 8i6 ^c W_ XS Y T Ta 8i6 ^P XL {EODWC_BgAoƨ_/ * , " ) 3 5 /@/ 5 ^9h 6@& j /@/ ^9h 6@ n [ i z hb ig B 9h 6S@ (/X! cX ׆ R . ѽ w s մ/X 7+0X?9h 6 @ 9h 6@܆ hb ik B / 7 9h 6W@҆ X " c
+ U V @ Ta 8i 6 ^ !TU W W @ Ta 8i 6 ^ !TW X Y @ Ta 8i 6 ^ !TX k@ @H_9h 6@@ !@@(_9h 6 @ e Cog_WO{ 9 VU~ RxU R
+ @^ @9 j Tu@ Tx b h j@
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+ T# @Ta 8i6 ^ 0X a S? TA Ո0XA 9h 6+@ h/X! > ۅ s8h 6Y {XOWWV_UgToSC_ 9 u u@ h@ @ Ta 8i 6 ^ׅ !T`@u х
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+AT? u h 97 @a&@ T^9h7 @ q# 52 h @a&@ BT RL ^96h @ @# 5 # ` 4@^@9 I 6h @k @
+ _ qk k J 6@ h& AT Iˈ& j* R{COBWA_WO{ $E Tu h 97 @a&@ T^9h7 @ q# 5/ h @a&@ BT R ^96h @ @# 5 # 4@^@9 I 6h @k @
+ _ qk k J 6@ h&*ˈ* i* R{COBWA_ @@@ O{C (/XA @@9( 4h 9h7h97{AO¨_`@F h 96`@ h96`@ {AO¨_O{C (/XA @@9( 4h 9h7h97{AO¨ `@& h 96`@ h96`@ {AO¨~ O{ a 5_ q` T# *P R# a*p RRA$P B RN# h@ @ ?{BOA _ # 3 g@! R O{ # *P B R# |*p R)# Ǫ{BOA _ # F_WO{ X @9 @7
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Rh"(Rh*) Rj RyHJ } h K k)Qkz*) J _
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@ ?ր@C + @
@ ? R # C Ո-XA @ `@t @@ ?# q C +@ T @@ @@ ?C ! @ T @@ @@ ?֨\ I&.X)@? T{IOHWG_F_ R a&$0 V -X B-X 8 # 6
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+h@lFӌ})ilk!@(y+H h hb ? q T) R hr 8h 6# BA%P "R?# <! %p R!#P B R# h@h 4` tr ¿8h 6# )!%P բR&# #%p R#P B R# j¿8 7tC m hr 8h6hr h@ 4h rc@9 4 @| c 9t 4`W a c@9h 4 @r {COB_ Rc@95A%P R^ # : # 5 c@9h 4 @U | O{C @ C {AO¨v O{ @ {BOA _# %P bR# % Re#P B Ra% BR]# `@{BOA _ # E| yO{
+ @ "c E~ @ c <~ {COB_C c 2~ C A C .~ q TS # u %P Ղ>Rr# o h@ @ ? # B # : 2 c ~ { og_WO{ @ Th t@@t h@ Tu@ T(C
+ ? HA˕XC T t@h in@x"A
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+ )( H R_ O{C {AO¨ s s o !@@ @$@ R g_WO{C( @@3 R ? Ҡ YaRڹr(P ( !P (0 h@@3 R ?@ @ kTh@@# R ?` R RB RR ] @} Sh 4" {EODWC_BgA_ Mo ӗCWO{ (@ ` Tc C 3 ~@ C !(P ՂRC a[& R(P բR@ ]@9* 1@_ qa!P B R|C @ ^9h 6@r r @ T< @ Tc C 3 F@ C !(P բRC aT& RTA( bRP@ ]@9* 1@_ qaH!P B RDC @ 5 ^9h 6@Sr Qr h" h T @T h" i Tc y(P Rvc s( բR !P B R c " TIaRڹr T
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HHH[ / #- N4dmlc2io14InputSplitBaseE NSt3__111__end_stateIcEE NSt3__16__nodeIcEE NSt3__120__shared_ptr_pointerIPNS_13__empty_stateIcEENS_14default_deleteIS2_EENS_9allocatorIS2_EEEE NSt3__114default_deleteINS_13__empty_stateIcEEEE NSt3__113__empty_stateIcEE NSt3__116__owns_one_stateIcEE NSt3__115__has_one_stateIcEE NSt3__110__l_anchorIcEE NSt3__110__r_anchorIcEE NSt3__115__word_boundaryIcNS_12regex_traitsIcEEEE NSt3__111__lookaheadIcNS_12regex_traitsIcEEEE NSt3__123__match_any_but_newlineIcEE NSt3__118__match_char_icaseIcNS_12regex_traitsIcEEEE NSt3__120__match_char_collateIcNS_12regex_traitsIcEEEE NSt3__112__match_charIcEE NSt3__116__back_ref_icaseIcNS_12regex_traitsIcEEEE NSt3__118__back_ref_collateIcNS_12regex_traitsIcEEEE NSt3__110__back_refIcEE NSt3__120__bracket_expressionIcNS_12regex_traitsIcEEEE NSt3__128__begin_marked_subexpressionIcEE NSt3__126__end_marked_subexpressionIcEE NSt3__16__loopIcEE NSt3__117__owns_two_statesIcEE NSt3__117__repeat_one_loopIcEE NSt3__111__alternateIcEE NSt3__121__empty_non_own_stateIcEE NSt3__111__match_anyIcEE N4dmlc2io10FileSystemE N4dmlc2io15LocalFileSystemE N4dmlc2io10FileStreamE XGBoost distributed mode detected, will split data among workers /Users/runner/work/ml-builds/ml-builds/xgboost/src/c_api/c_api.cc DMatrix/Booster has not been intialized or has already been disposed. Check failed: p_m : Check failed: m Current DMatrix type does not support set data. static_cast<std::shared_ptr<DMatrix>*>(handle) ->get() ->Info() .group_ptr_.size() == 0U slice does not support group structure binary saving only supported by SimpleDMatrix Check failed: type >= 1 && type <= 4 XGDMatrixSetGroup is deprecated, use `XGDMatrixSetUIntInfo` instead. group cache_id == 0 Cache ID is not supported yet Check failed: p_predt json str.size() > 2 str[0] == '{' r w Check failed: p_out text /Users/runner/work/ml-builds/ml-builds/xgboost/src/c_api/../data/adapter.h Check failed: at_first_ Cannot reset IteratorAdapter Check failed: columns_ == data::kAdapterUnknownSize || columns_ == batch.columns Number of columns between batches changed from allocator<T>::allocate(size_t n) 'n' exceeds maximum supported size /Users/runner/work/ml-builds/ml-builds/xgboost/src/c_api/../common/common.h XGBoost version not compiled with GPU support. /Users/runner/work/ml-builds/ml-builds/xgboost/src/c_api/../data/proxy_dmatrix.h Slicing DMatrix is not supported for Proxy DMatrix. Not implemented. write position exceed fixed buffer size /Users/runner/work/ml-builds/ml-builds/xgboost/rabit/include/rabit/internal/utils.h fid == static_cast<int>(names_.size()) i q int float unknown feature type, use i for indicator and q for quantity NaN 0E0 ;unknown;unknown;0;0;; /Users/runner/work/ml-builds/ml-builds/xgboost/src/common/hist_util.cc sibling.size() == size parent.size() == size cut.Values().size() > 0U curent_bin_size == kUint32BinsTypeSize /Users/runner/work/ml-builds/ml-builds/xgboost/src/common/hist_util.h bins_type_size == kUint32BinsTypeSize /Users/runner/work/ml-builds/ml-builds/xgboost/src/common/column_matrix.h sizeof(BinIdxType) == bins_type_size_ /Users/runner/work/ml-builds/ml-builds/xgboost/include/xgboost/data.h Check failed: impl_ != nullptr batch_size < offset_vec.size() ibegin + inst.size() == iend Check failed: false /Users/runner/work/ml-builds/ml-builds/xgboost/src/common/host_device_vector.cc Size() == other.Size() Size() == other.size() /Users/runner/work/ml-builds/ml-builds/xgboost/src/common/io.cc pointer_ <= buffer_.size() Check failed: out file:// :// Opening failed: /Users/runner/work/ml-builds/ml-builds/xgboost/src/common/io.h Not implemented rb /Users/runner/work/ml-builds/ml-builds/xgboost/src/common/json.cc \\ \" \b \f \n \r \t \u%04x String Number Object Array Boolean Integer Object of type can not be indexed by Integer. can not be indexed by string. Please try obtaining std::string first. Unknown construct , around character position: , " " \0 " Unknown escape null Expecting null value "null" ch != -1 cursor_.Pos(): , raw_str_.size(): Expecting digit beg <= size_ Expecting: " ", got: " EOF" \0" HostSketchContainer /Users/runner/work/ml-builds/ml-builds/xgboost/src/common/quantile.cc columns_size_.size() != 0 count <= total_entries PushRowPage sketches_.size() == info.num_col_ worker_segments.size() >= 1 AllReduce num_cuts.size() == 0 n_columns == sketches_.size() Number of columns differs across workers Check failed: reduced[i].data Check failed: a.data Check failed: a.data && reduced[fid].data cuts->cut_values_.HostVector().size() <= std::numeric_limits<uint32_t>::max() cut_size > cuts->cut_ptrs_.HostVector().back() /Users/runner/work/ml-builds/ml-builds/xgboost/src/common/quantile.h invalid init parameter Check failed: nlevel <= std::max(static_cast<size_t>(1), static_cast<size_t>(limit_size * eps)) base_rowid < group_ptr.back() Row: is not found in any group. mingap= , maxgap= , wgap= Check failed: size <= sa.size + sb.size bug in combine src.size == 0 this->size == 0 (index_ + n) <= span_->size() index_ < span_->size() index_ != span_->size() Check failed: worker_feature.data() (_idx) < (size()) /Users/runner/work/ml-builds/ml-builds/xgboost/src/common/random.cc features.size() > 0 /Users/runner/work/ml-builds/ml-builds/xgboost/src/common/random.h array.size() == weights.size() aft_loss_distribution normal extreme Choice of distribution for the noise term in Accelerated Failure Time model aft_loss_distribution_scale Scaling factor used to scale the distribution in Accelerated Failure Time model but value=' for Parameter exceed bound [ should be greater equal to map::at: key not found )
- Out of range value for , value=' pos <= value.length() Some trailing characters could not be parsed: ' Out of range value /Users/runner/work/ml-builds/ml-builds/xgboost/dmlc-core/include/dmlc/./strtonum.h statistic count elapsed /Users/runner/work/ml-builds/ml-builds/xgboost/src/common/timer.cc Timer for did not get stopped properly. s, calls @ us ======== Monitor: ======== From rank: version /Users/runner/work/ml-builds/ml-builds/xgboost/src/common/version.cc Invaid version format in loaded JSON object: Incorrect version format found in binary file. Binary file from XGBoost < 1.0.0 is no longer supported. Please generate it again. fi->Read(&read[0], verstr.size()) == verstr.size() Check failed: fi->Read(&major) Check failed: fi->Read(&minor) Check failed: fi->Read(&patch) . num_row num_col num_nonzero labels group_ptr weights base_margin labels_lower_bound labels_upper_bound feature_names feature_types /Users/runner/work/ml-builds/ml-builds/xgboost/src/data/data.cc field_cnt == kNumField Wrong number of fields categorical All feature_types must be one of {int, float, i, q, categorical}. major == 1 Binary DMatrix generated by XGBoost: is no longer supported. Please process and save your data in current version: again. Check failed: fi->Read(&num_field) MetaInfo: invalid format num_field >= expected MetaInfo: insufficient number of fields (expected at least fields, but the binary file only contains fields.) MetaInfo: the given binary file contains extra fields which will be ignored. this->base_margin_.Size() % this->num_row_ == 0 Incorrect size of base margin vector. label Unknown data type weight Check failed: valid Weights must be positive values. label_lower_bound label_upper_bound feature_weights Feature weight must be greater than 0. Unknown key for MetaInfo: Unknown float field name: Unknown uint32 field name: Unknown data type for getting meta info. size == this->num_col_ Length of must be equal to number of columns. feature_type feature_name Unknown feature info name: Unknown feature info: this->num_col_ == that.num_col_ Number of columns must be consistent across batches. that.group_ptr_.size() != 0 group_ptr_.size() == weights_.Size() + 1 Size of weights must equal to number of groups when ranking group is used. group_ptr_.back() == num_row_ Invalid group structure. Number of rows obtained from groups doesn't equal to actual number of rows given by data. weights_.Size() == num_row_ Size of weights must equal to number of rows. labels_.Size() == num_row_ Size of labels must equal to number of rows. labels_lower_bound_.Size() == num_row_ Size of label_lower_bound must equal to number of rows. feature_weigths.Size() == num_col_ Size of feature_weights must equal to number of columns. labels_upper_bound_.Size() == num_row_ Size of label_upper_bound must equal to number of rows. num_nonzero_ <= num_col_ * num_row_ base_margin_.Size() % num_row_ == 0 Size of base margin must be a multiple of number of rows. cache_file.find('#') == std::string::npos Only one `#` is allowed in file path for cache file specification. .r - XGBOOST_TEST_NPART Load part of data parts auto matrix with entries loaded from csv libsvm No format parameter is provided in input uri, but found file extension: . Consider providing a uri parameter: filename?format= No format parameter is provided in input uri. Choosing default parser in dmlc-core. Consider providing a uri parameter like: filename?format=csv Encountered parser error:
- .group groups are loaded from .base_margin base_margin are loaded from .weight weights are loaded from self_offset.size() == other_offset.size() self_data.size(): other_data.size(): beg <= data.size() ptr < offset.size() /Users/runner/work/ml-builds/ml-builds/xgboost/src/data/../common/common.h float32 float64 bool8 int32 int8 int16 int64 /Users/runner/work/ml-builds/ml-builds/xgboost/src/data/../data/adapter.h Unknown data table type. Check failed: v.DeviceIdx() == GenericParameter::kCpuId || device == GenericParameter::kCpuId || v.DeviceIdx() == device Data is resided on a different device than `gpu_id`. Device that data is on: `gpu_id` for XGBoost: MetaInfo: Invalid format. Check failed: strm->Read(&name) name == expected_name Expected field: , got: Check failed: strm->Read(&type_val) Check failed: type == expected_type Expected field of type: got field type: Check failed: strm->Read(&is_scalar) Check failed: is_scalar Expected field to be a scalar; got a vector Check failed: strm->Read(field) Check failed: !is_scalar to be a vector; got a scalar Check failed: strm->Read(&shape.first) Check failed: strm->Read(&shape.second) shape.second == 1 Number of columns is expected to be 1. /Users/runner/work/ml-builds/ml-builds/xgboost/src/data/./sparse_page_source.h Couldn't remove external memory cache file ; you may want to remove it manually .row.page page->Size() == 0 Check failed: qids.empty() || qids.size() == info.num_row_ SparsePageSource Finished writing to cache_shards.size() != 0U .fmt- raw Cache file exists already; Is there another DMatrix with the same cache prefix? It can be caused by previously used DMatrix that hasn't been collected by language environment garbage collector. Otherwise please remove it manually. /Users/runner/work/ml-builds/ml-builds/xgboost/src/data/sparse_page_writer.h name_shards.size() == format_shards.size() thread constructor failed SparsePageWriter Finished writing to Unknown format type info.name_shards.size() != 0U Check failed: finfo->Read(&tmagic) tmagic == kMagic invalid format, magic number mismatch Check failed: fi->Read(&format) Invalid page format /Users/runner/work/ml-builds/ml-builds/xgboost/dmlc-core/include/dmlc/threadediter.h Check failed: !producer_sig_processed_.load(std::memory_order_acquire) unique_lock::unlock: not locked Check failed: producer_sig_.load(std::memory_order_acquire) == kProduce Make sure you call BeforeFirst not inconcurrent with Next! Check failed: produce_end_.load(std::memory_order_acquire) Check failed: out_data_ != NULL Calling Value at beginning or end? Check failed: producer_sig_.load(std::memory_order_acquire) == kDestroy Check failed: cell != __null || produce_end_.load(std::memory_order_acquire) Check failed: producer_sig_.load(std::memory_order_acquire) != kDestroy No thread Check failed: mutex_.try_lock() Multiple threads attempting to use prefetcher key >= builder_base_row_offset /Users/runner/work/ml-builds/ml-builds/xgboost/src/data/ellpack_page.cc Internal Error: XGBoost is not compiled with CUDA but EllpackPage is required .ellpack.page /Users/runner/work/ml-builds/ml-builds/xgboost/src/data/ellpack_page_source.cc Internal Error: XGBoost is not compiled with CUDA but EllpackPageSource is required /Users/runner/work/ml-builds/ml-builds/xgboost/src/data/simple_dmatrix.cc Check failed: (std::is_same<AdapterT, CSCAdapter>::value) Expecting CSCAdapter Check failed: param != BatchParam{} Batch parameter is not initialized. param.gpu_id >= 0 param.max_bin >= 2 Check failed: in_stream->Read(&tmagic) invalid input file format /Users/runner/work/ml-builds/ml-builds/xgboost/src/data/./simple_batch_iterator.h Check failed: page_ != nullptr /Users/runner/work/ml-builds/ml-builds/xgboost/src/data/sparse_page_dmatrix.cc /Users/runner/work/ml-builds/ml-builds/xgboost/src/data/sparse_page_source.h Check failed: source_ != nullptr .col.page Writing to in MB/s, written CSCPageSource: Finished writing to Check failed: *out_page == nullptr Check failed: qrecycle_.Pop(out_page) .sorted.col.page SortedCSCPageSource: Finished writing to /Users/runner/work/ml-builds/ml-builds/xgboost/src/data/./sparse_page_dmatrix.h Slicing DMatrix is not supported for external memory. Raw binary data format. /Users/runner/work/ml-builds/ml-builds/xgboost/src/data/sparse_page_raw_format.cc page->offset.Size() != 0U Invalid SparsePage file fi->Read(dmlc::BeginPtr(data_vec), (page->data).Size() * sizeof(Entry)) == (page->data).Size() * sizeof(Entry) fid + 1 < disk_offset_.size() disk_offset_[fid] > curr_offset fi->Read(dmlc::BeginPtr(data_vec) + offset_vec[i], size_to_read * sizeof(Entry)) == size_to_read * sizeof(Entry) Check failed: page.offset.Size() != 0 && offset_vec[0] == 0 offset_vec.back() == page.data.Size() /Users/runner/work/ml-builds/ml-builds/xgboost/src/data/sparse_page_source.cc offset + n_rows + 1 <= in_offset.size() h_offset.size() > 0 n_entries == in_offset.at(offset + n_rows) - in_offset.at(offset) out->Size() != 0 GBLinearTrainParam gblinear Linear booster, implement generalized linear model. updater shotgun Update algorithm for linear model. One of shotgun/coord_descent tolerance Stop if largest weight update is smaller than this number. max_row_perbatch Maximum rows per batch. /Users/runner/work/ml-builds/ml-builds/xgboost/dmlc-core/include/dmlc/parameter.h /Users/runner/work/ml-builds/ml-builds/xgboost/src/gbm/gblinear.cc get<String>(in["name"]) == "gblinear" model gpu_coord_descent Cannot find argument ' /Users/runner/work/ml-builds/ml-builds/xgboost/src/gbm/../common/common.h /Users/runner/work/ml-builds/ml-builds/xgboost/src/gbm/gblinear_model.h fi->Read(¶m_, sizeof(param_)) == sizeof(param_) /Users/runner/work/ml-builds/ml-builds/xgboost/include/xgboost/gbm.h Slice is not supported by current booster. DoBoost PredictBatch ntree_limit == 0U GBLinear::Predict ntrees is only valid for gbtree predictor PredictBatchInternal base_margin.size() == nsize * ngroup Inplace predict is not supported by current booster. gblinear does not support prediction of leaf index GBLinear::PredictContribution: ntrees is only valid for gbtree predictor { "bias": [ , ], "weight": [ ] } bias:
+)>Cg 3 /7: #'7+/;3 ! HHH[ / #- N4dmlc2io14InputSplitBaseE NSt3__111__end_stateIcEE NSt3__16__nodeIcEE NSt3__120__shared_ptr_pointerIPNS_13__empty_stateIcEENS_14default_deleteIS2_EENS_9allocatorIS2_EEEE NSt3__114default_deleteINS_13__empty_stateIcEEEE NSt3__113__empty_stateIcEE NSt3__116__owns_one_stateIcEE NSt3__115__has_one_stateIcEE NSt3__110__l_anchorIcEE NSt3__110__r_anchorIcEE NSt3__115__word_boundaryIcNS_12regex_traitsIcEEEE NSt3__111__lookaheadIcNS_12regex_traitsIcEEEE NSt3__123__match_any_but_newlineIcEE NSt3__118__match_char_icaseIcNS_12regex_traitsIcEEEE NSt3__120__match_char_collateIcNS_12regex_traitsIcEEEE NSt3__112__match_charIcEE NSt3__116__back_ref_icaseIcNS_12regex_traitsIcEEEE NSt3__118__back_ref_collateIcNS_12regex_traitsIcEEEE NSt3__110__back_refIcEE NSt3__120__bracket_expressionIcNS_12regex_traitsIcEEEE NSt3__128__begin_marked_subexpressionIcEE NSt3__126__end_marked_subexpressionIcEE NSt3__16__loopIcEE NSt3__117__owns_two_statesIcEE NSt3__117__repeat_one_loopIcEE NSt3__111__alternateIcEE NSt3__121__empty_non_own_stateIcEE NSt3__111__match_anyIcEE N4dmlc2io10FileSystemE N4dmlc2io15LocalFileSystemE N4dmlc2io10FileStreamE /Users/runner/work/ml-builds/ml-builds/xgboost/src/c_api/c_api.cc Check failed: ec == std::errc() : Unknown global parameters: { } Check failed: e XGBoost distributed mode detected, will split data among workers DMatrix/Booster has not been intialized or has already been disposed. Check failed: p_m Check failed: m Current DMatrix type does not support set data. nthread static_cast<std::shared_ptr<DMatrix>*>(handle) ->get() ->Info() .group_ptr_.size() == 0U slice does not support group structure binary saving only supported by SimpleDMatrix Check failed: type >= 1 && type <= 4 XGDMatrixSetGroup is deprecated, use `XGDMatrixSetUIntInfo` instead. group Booster has not been intialized or has already been disposed. DMatrix has not been intialized or has already been disposed. iteration_begin iteration_end strict_shape json str.size() > 2 str[0] == '{' r w Check failed: p_out text feature_name feature_type Unknown field for Booster feature info: allocator<T>::allocate(size_t n) 'n' exceeds maximum supported size /Users/runner/work/ml-builds/ml-builds/xgboost/src/c_api/../data/adapter.h Check failed: at_first_ Cannot reset IteratorAdapter Check failed: columns_ == data::kAdapterUnknownSize || columns_ == batch.columns Number of columns between batches changed from /Users/runner/work/ml-builds/ml-builds/xgboost/src/c_api/../common/common.h XGBoost version not compiled with GPU support. /Users/runner/work/ml-builds/ml-builds/xgboost/src/c_api/../data/proxy_dmatrix.h Slicing DMatrix is not supported for Proxy DMatrix. Not implemented. /Users/runner/work/ml-builds/ml-builds/xgboost/src/c_api/../data/array_interface.h get<Array const>(jinterface).size() == 1 Column: typestr n_bits == num_rows Shape of bit mask doesn't match data shape. XGBoost doesn't support internal broadcasting. Check failed: array.find("mask") == array.cend() Masked array is not yet supported. stream version Missing `version' field for array interface Missing `typestr' field for array interface typestr.size() == 3 typestr.front() != '>' shape Missing `shape' field for array interface Missing `data' field for array interface Only version <= 3 of `__cuda_array_interface__' are supported. `typestr' should be of format <endian><type><size of type in bytes>. Big endian is not supported. is not supported. Bit field Boolean Integer Unsigned integer Floating point Complex floating point Timedelta Object String Unicode Other Invalid type code: in `typestr' of input array.
+Please verify the `__cuda_array_interface__' of your input data complies to: https://docs.scipy.org/doc/numpy/reference/arrays.interface.html
+Or open an issue. j_shape.size() == 2 Only 1-D and 2-D arrays are supported. shape.first * shape.second == 0 Empty data with non-zero shape. Empty data passed in. j_shape.size() == 1 type_length == 1 mask with bitfield type should be of 1 byte per bitfield. mask with integer type should be of 1 byte per integer. mask must be of integer type or bit field type. strides strides.size() == 1 get<Integer>(strides.at(0)) == type_length Memory should be contigious. j_strides.size() <= 2 Check failed: valid Invalid strides in array. Only dimensional array is valid. Check failed: num_rows == 1 || num_cols == 1 Array should be a vector instead of matrix. missing /Users/runner/work/ml-builds/ml-builds/xgboost/src/c_api/c_api_utils.h Invalid missing value: gblinear dart gbtree gbtree_train_param num_parallel_tree Unknown booster: chunksize == groups Unknown prediction type: std::accumulate(shape.cbegin(), shape.cend(), 1, std::multiplies<>{}) == chunksize * rows write position exceed fixed buffer size /Users/runner/work/ml-builds/ml-builds/xgboost/rabit/include/rabit/internal/utils.h read can not have position excceed buffer length fid == static_cast<int>(names_.size()) i q int float unknown feature type, use i for indicator and q for quantity Cannot find argument ' get<Integer const>(config["cache_id"]) == 0 Cache ID is not supported yet Check failed: p_predt NaN 0E0 ;unknown;unknown;0;0;; /Users/runner/work/ml-builds/ml-builds/xgboost/src/common/hist_util.cc sibling.size() == size parent.size() == size cut.Values().size() > 0U curent_bin_size == kUint32BinsTypeSize /Users/runner/work/ml-builds/ml-builds/xgboost/src/common/hist_util.h bins_type_size == kUint32BinsTypeSize /Users/runner/work/ml-builds/ml-builds/xgboost/src/common/column_matrix.h sizeof(BinIdxType) == bins_type_size_ /Users/runner/work/ml-builds/ml-builds/xgboost/include/xgboost/data.h Check failed: impl_ != nullptr batch_size < offset_vec.size() ibegin + inst.size() == iend Check failed: false /Users/runner/work/ml-builds/ml-builds/xgboost/src/common/host_device_vector.cc Size() == other.Size() Size() == other.size() /Users/runner/work/ml-builds/ml-builds/xgboost/src/common/io.cc pointer_ <= buffer_.size() Check failed: out file:// :// Opening failed: /Users/runner/work/ml-builds/ml-builds/xgboost/src/common/io.h Not implemented rb /Users/runner/work/ml-builds/ml-builds/xgboost/src/common/json.cc \\ \" \b \f \n \r \t \u%04x Number Array Object of type can not be indexed by Integer. can not be indexed by string. Please try obtaining std::string first. Unknown construct , around character position: , " " \0 Unknown escape null Expecting null value "null" ch != -1 cursor_.Pos(): raw_str_.size(): Expecting digit beg <= size_ Expecting: " ", got: " EOF" \0" HostSketchContainer /Users/runner/work/ml-builds/ml-builds/xgboost/src/common/quantile.cc columns_size_.size() != 0 count <= total_entries PushRowPage sketches_.size() == info.num_col_ worker_segments.size() >= 1 AllReduce num_cuts.size() == 0 n_columns == sketches_.size() Number of columns differs across workers Check failed: reduced[i].data Check failed: a.data Check failed: a.data && reduced[fid].data cuts->cut_values_.HostVector().size() <= std::numeric_limits<uint32_t>::max() cut_size > cuts->cut_ptrs_.HostVector().back() /Users/runner/work/ml-builds/ml-builds/xgboost/src/common/quantile.h invalid init parameter Check failed: nlevel <= std::max(static_cast<size_t>(1), static_cast<size_t>(limit_size * eps)) base_rowid < group_ptr.back() Row: is not found in any group. mingap= , maxgap= , wgap= Check failed: size <= sa.size + sb.size bug in combine src.size == 0 this->size == 0 Check failed: worker_feature.data() /Users/runner/work/ml-builds/ml-builds/xgboost/src/common/random.cc features.size() > 0 /Users/runner/work/ml-builds/ml-builds/xgboost/src/common/random.h array.size() == weights.size() aft_loss_distribution normal extreme Choice of distribution for the noise term in Accelerated Failure Time model aft_loss_distribution_scale Scaling factor used to scale the distribution in Accelerated Failure Time model optional, default= , required Invalid Input: ' ' is not presented /Users/runner/work/ml-builds/ml-builds/xgboost/dmlc-core/include/dmlc/./parameter.h has already been registered in Enum ( exisit! Enums: ), statistic count elapsed /Users/runner/work/ml-builds/ml-builds/xgboost/src/common/timer.cc Timer for did not get stopped properly. s, calls @ us ======== Monitor: ======== From rank: /Users/runner/work/ml-builds/ml-builds/xgboost/src/common/version.cc Invaid version format in loaded JSON object: Incorrect version format found in binary file. Binary file from XGBoost < 1.0.0 is no longer supported. Please generate it again. fi->Read(&read[0], verstr.size()) == verstr.size() Check failed: fi->Read(&major) Check failed: fi->Read(&minor) Check failed: fi->Read(&patch) . /Users/runner/work/ml-builds/ml-builds/xgboost/src/data/data.cc Input data contains `inf` or `nan` num_row num_col num_nonzero labels group_ptr weights base_margin labels_lower_bound labels_upper_bound field_cnt == kNumField Wrong number of fields categorical All feature_types must be one of {int, float, i, q, categorical}. major == 1 Binary DMatrix generated by XGBoost: is no longer supported. Please process and save your data in current version: again. Check failed: fi->Read(&num_field) MetaInfo: invalid format num_field >= expected MetaInfo: insufficient number of fields (expected at least fields, but the binary file only contains fields.) MetaInfo: the given binary file contains extra fields which will be ignored. this->base_margin_.Size() % this->num_row_ == 0 Incorrect size of base margin vector. label Unknown data type weight Weights must be positive values. qid Check failed: non_dec `qid` must be sorted in non-decreasing order along with data. label_lower_bound label_upper_bound feature_weights Feature weight must be greater than 0. Unknown key for MetaInfo: Unknown float field name: Unknown uint32 field name: Unknown data type for getting meta info. size == this->num_col_ Length of must be equal to number of columns. Unknown feature info name: Unknown feature info: this->num_col_ == that.num_col_ Number of columns must be consistent across batches. that.group_ptr_.size() != 0 group_ptr_.size() == weights_.Size() + 1 Size of weights must equal to number of groups when ranking group is used. group_ptr_.back() == num_row_ Invalid group structure. Number of rows obtained from groups doesn't equal to actual number of rows given by data. weights_.Size() == num_row_ Size of weights must equal to number of rows. labels_.Size() == num_row_ Size of labels must equal to number of rows. labels_lower_bound_.Size() == num_row_ Size of label_lower_bound must equal to number of rows. feature_weigths.Size() == num_col_ Size of feature_weights must equal to number of columns. labels_upper_bound_.Size() == num_row_ Size of label_upper_bound must equal to number of rows. num_nonzero_ <= num_col_ * num_row_ base_margin_.Size() % num_row_ == 0 Size of base margin must be a multiple of number of rows. cache_file.find('#') == std::string::npos Only one `#` is allowed in file path for cache file specification. .r - XGBOOST_TEST_NPART Load part of data parts auto matrix with entries loaded from csv libsvm No format parameter is provided in input uri, but found file extension: . Consider providing a uri parameter: filename?format= No format parameter is provided in input uri. Choosing default parser in dmlc-core. Consider providing a uri parameter like: filename?format=csv Encountered parser error:
+ .group groups are loaded from .base_margin base_margin are loaded from .weight weights are loaded from self_offset.size() == other_offset.size() self_data.size(): other_data.size(): beg <= data.size() ptr < offset.size() /Users/runner/work/ml-builds/ml-builds/xgboost/src/data/../common/common.h float32 float64 bool8 int32 int8 int16 int64 /Users/runner/work/ml-builds/ml-builds/xgboost/src/data/../data/adapter.h Unknown data table type. Check failed: v.DeviceIdx() == GenericParameter::kCpuId || device == GenericParameter::kCpuId || v.DeviceIdx() == device Data is resided on a different device than `gpu_id`. Device that data is on: `gpu_id` for XGBoost: MetaInfo: Invalid format. Check failed: strm->Read(&name) name == expected_name Expected field: , got: Check failed: strm->Read(&type_val) Check failed: type == expected_type Expected field of type: got field type: Check failed: strm->Read(&is_scalar) Check failed: is_scalar Expected field to be a scalar; got a vector Check failed: strm->Read(field) Check failed: !is_scalar to be a vector; got a scalar Check failed: strm->Read(&shape.first) Check failed: strm->Read(&shape.second) shape.second == 1 Number of columns is expected to be 1. /Users/runner/work/ml-builds/ml-builds/xgboost/src/data/./sparse_page_source.h Couldn't remove external memory cache file ; you may want to remove it manually .row.page page->Size() == 0 Check failed: qids.empty() || qids.size() == info.num_row_ SparsePageSource Finished writing to cache_shards.size() != 0U .fmt- raw Cache file exists already; Is there another DMatrix with the same cache prefix? It can be caused by previously used DMatrix that hasn't been collected by language environment garbage collector. Otherwise please remove it manually. /Users/runner/work/ml-builds/ml-builds/xgboost/src/data/sparse_page_writer.h name_shards.size() == format_shards.size() thread constructor failed SparsePageWriter Finished writing to Unknown format type info.name_shards.size() != 0U Check failed: finfo->Read(&tmagic) tmagic == kMagic invalid format, magic number mismatch Check failed: fi->Read(&format) Invalid page format /Users/runner/work/ml-builds/ml-builds/xgboost/dmlc-core/include/dmlc/threadediter.h Check failed: !producer_sig_processed_.load(std::memory_order_acquire) unique_lock::unlock: not locked Check failed: producer_sig_.load(std::memory_order_acquire) == kProduce Make sure you call BeforeFirst not inconcurrent with Next! Check failed: produce_end_.load(std::memory_order_acquire) Check failed: out_data_ != NULL Calling Value at beginning or end? Check failed: producer_sig_.load(std::memory_order_acquire) == kDestroy Check failed: cell != __null || produce_end_.load(std::memory_order_acquire) Check failed: producer_sig_.load(std::memory_order_acquire) != kDestroy No thread Check failed: mutex_.try_lock() Multiple threads attempting to use prefetcher key >= builder_base_row_offset /Users/runner/work/ml-builds/ml-builds/xgboost/src/data/ellpack_page.cc Internal Error: XGBoost is not compiled with CUDA but EllpackPage is required .ellpack.page /Users/runner/work/ml-builds/ml-builds/xgboost/src/data/ellpack_page_source.cc Internal Error: XGBoost is not compiled with CUDA but EllpackPageSource is required /Users/runner/work/ml-builds/ml-builds/xgboost/src/data/simple_dmatrix.cc Check failed: (std::is_same<AdapterT, CSCAdapter>::value) Expecting CSCAdapter Check failed: param != BatchParam{} Batch parameter is not initialized. param.gpu_id >= 0 param.max_bin >= 2 Check failed: in_stream->Read(&tmagic) invalid input file format /Users/runner/work/ml-builds/ml-builds/xgboost/src/data/./simple_batch_iterator.h Check failed: page_ != nullptr /Users/runner/work/ml-builds/ml-builds/xgboost/src/data/sparse_page_dmatrix.cc /Users/runner/work/ml-builds/ml-builds/xgboost/src/data/sparse_page_source.h Check failed: source_ != nullptr .col.page Writing to in MB/s, written CSCPageSource: Finished writing to Check failed: *out_page == nullptr Check failed: qrecycle_.Pop(out_page) .sorted.col.page SortedCSCPageSource: Finished writing to /Users/runner/work/ml-builds/ml-builds/xgboost/src/data/./sparse_page_dmatrix.h Slicing DMatrix is not supported for external memory. Raw binary data format. /Users/runner/work/ml-builds/ml-builds/xgboost/src/data/sparse_page_raw_format.cc page->offset.Size() != 0U Invalid SparsePage file fi->Read(dmlc::BeginPtr(data_vec), (page->data).Size() * sizeof(Entry)) == (page->data).Size() * sizeof(Entry) fid + 1 < disk_offset_.size() disk_offset_[fid] > curr_offset fi->Read(dmlc::BeginPtr(data_vec) + offset_vec[i], size_to_read * sizeof(Entry)) == size_to_read * sizeof(Entry) Check failed: page.offset.Size() != 0 && offset_vec[0] == 0 offset_vec.back() == page.data.Size() /Users/runner/work/ml-builds/ml-builds/xgboost/src/data/sparse_page_source.cc offset + n_rows + 1 <= in_offset.size() h_offset.size() > 0 n_entries == in_offset.at(offset + n_rows) - in_offset.at(offset) out->Size() != 0 /Users/runner/work/ml-builds/ml-builds/xgboost/src/gbm/gblinear.cc layer_begin == 0 Linear booster does not support prediction range. layer_end == 0 GBLinearTrainParam Linear booster, implement generalized linear model. updater shotgun Update algorithm for linear model. One of shotgun/coord_descent tolerance Stop if largest weight update is smaller than this number. max_row_perbatch Maximum rows per batch. /Users/runner/work/ml-builds/ml-builds/xgboost/dmlc-core/include/dmlc/parameter.h get<String>(in["name"]) == "gblinear" model gpu_coord_descent /Users/runner/work/ml-builds/ml-builds/xgboost/src/gbm/../common/common.h /Users/runner/work/ml-builds/ml-builds/xgboost/src/gbm/gblinear_model.h fi->Read(¶m_, sizeof(param_)) == sizeof(param_) /Users/runner/work/ml-builds/ml-builds/xgboost/include/xgboost/gbm.h Slice is not supported by current booster. DoBoost PredictBatch PredictBatchInternal base_margin.size() == nsize * ngroup Inplace predict is not supported by current booster. gblinear does not support prediction of leaf index { "bias": [ , ], "weight": [ ] } bias:
weight:
gblinear_train_param Check failed: this->updater_ DeprecatedGBLinearModelParam /Users/runner/work/ml-builds/ml-builds/xgboost/src/gbm/gbm.cc Unknown gbm type cpu_predictor GBTree /Users/runner/work/ml-builds/ml-builds/xgboost/src/gbm/gbtree.cc DANGER AHEAD: You have manually specified `updater` parameter. The `tree_method` parameter will be ignored. Incorrect sequence of updaters will produce undefined behavior. For common uses, we recommend using `tree_method` parameter instead. Check failed: this->configured_ Check failed: tparam_.GetInitialised() Using updaters: Tree method is automatically selected to be 'approx' for distributed training. Tree method is automatically set to 'approx' since external-memory data matrix is used. Tree method is automatically selected to be 'approx' for faster speed. To use old behavior (exact greedy algorithm on single machine), set tree_method to 'exact'. Using tree method: grow_histmaker,prune grow_colmaker,prune Tree method is selected to be 'hist', which uses a single updater grow_quantile_histmaker. grow_quantile_histmaker grow_gpu_hist Unknown tree_method ( ) detected BoostNewTrees ngroup != 0 in_gpair->Size() % ngroup == 0U must have exactly ngroup * nrow gpairs ups.size() == updaters_.size() Internal Error: mismatched updater sequence.
- Specified updaters: Actual updaters: Check failed: !updaters_.front()->CanModifyTree() Updater: ` ` can not be used to create new trees. Set `process_type` to `update` if you want to update existing trees. Check failed: up->CanModifyTree() can not be used to modify existing trees. Set `process_type` to `default` if you want to build new trees. model_.trees.size() < model_.trees_to_update.size() No more tree left for updating. For updating existing trees, boosting rounds can not exceed previous training rounds gpair->Size() == p_fmat->Info().num_row_ Mismatching size between number of rows from input data and size of gradient vector. CommitModel get<String>(in["name"]) == "gbtree" gbtree_train_param Loading from a raw memory buffer on CPU only machine. Changing predictor to auto. predictor tree_method Loading from a raw memory buffer on CPU only machine. Changing tree_method to hist. specified_updater default process_type Check failed: configured_ Check failed: p_gbtree layer_end >= layer_begin step >= 1 Check failed: this->model_.trees_to_update.empty() Check failed: cpu_predictor_ Data is on CUDA device, but XGBoost is not compiled with CUDA support. GBTreeModelParam GBTreeTrainParam DartTrainParam Tree booster, gradient boosted trees. dart Tree booster, dart. XGBoost version not compiled with OneAPI support. /Users/runner/work/ml-builds/ml-builds/xgboost/src/gbm/gbtree.h tree_begin < tree_end in_it < tree_end num_trees Number of features used for training and prediction. size_leaf_vector Reserved option for vector tree. num_parallel_tree Number of parallel trees constructed during each iteration. This option is used to support boosted random forest. updater_seq Tree updater sequence. update Whether to run the normal boosting process that creates new trees, or to update the trees in an existing model. gpu_predictor oneapi_predictor Predictor algorithm type approx exact Choice of tree construction method. has not been registered in sample_type Different types of sampling algorithm. normalize_type forest Different types of normalization algorithm. rate_drop Fraction of trees to drop during the dropout. Whether at least one tree should always be dropped during the dropout. skip_drop Probability of skipping the dropout during a boosting iteration. learning_rate Learning rate(step size) of update. eta false 1 0 get<String>(in["name"]) == "dart" weight_drop Check failed: p_dart Check failed: p_dart->weight_drop_.empty() out_preds.size() == n num_group == model_.learner_model_param->num_output_group model_.param.size_leaf_vector == 0 size_leaf_vector is enforced to 0 so far preds.size() == p_fmat->Info().num_row_ * num_group dart_train_param drop trees, weight = /Users/runner/work/ml-builds/ml-builds/xgboost/src/gbm/gbtree_model.cc param.num_trees == static_cast<int32_t>(trees.size()) fi->Read(¶m, sizeof(param)) == sizeof(param) GBTree: invalid model file fi->Read(dmlc::BeginPtr(tree_info), sizeof(int32_t) * param.num_trees) == sizeof(int32_t) * param.num_trees param.num_trees == static_cast<int>(trees.size()) gbtree_model_param trees tree_info LearnerModelParamLegacy LearnerTrainParam GenericParameter gpu_id eval_metric num_round CONFIG-offset: Learner /Users/runner/work/ml-builds/ml-builds/xgboost/src/learner.cc Check failed: IsA<Object>(in) learner learner_model_param objective gradient_booster booster attributes [ ]
+ Specified updaters: Actual updaters: Check failed: !updaters_.front()->CanModifyTree() Updater: ` ` can not be used to create new trees. Set `process_type` to `update` if you want to update existing trees. Check failed: up->CanModifyTree() can not be used to modify existing trees. Set `process_type` to `default` if you want to build new trees. model_.trees.size() < model_.trees_to_update.size() No more tree left for updating. For updating existing trees, boosting rounds can not exceed previous training rounds gpair->Size() == p_fmat->Info().num_row_ Mismatching size between number of rows from input data and size of gradient vector. CommitModel get<String>(in["name"]) == "gbtree" Loading from a raw memory buffer on CPU only machine. Changing predictor to auto. predictor tree_method Loading from a raw memory buffer on CPU only machine. Changing tree_method to hist. specified_updater default process_type Check failed: configured_ Check failed: p_gbtree layer_end > layer_begin step >= 1 Check failed: this->model_.trees_to_update.empty() out_preds->version == 0 Check failed: cpu_predictor_ Data is on CUDA device, but XGBoost is not compiled with CUDA support. GBTreeModelParam GBTreeTrainParam DartTrainParam Tree booster, gradient boosted trees. Tree booster, dart. /Users/runner/work/ml-builds/ml-builds/xgboost/src/gbm/gbtree.h tree_begin <= tree_end XGBoost version not compiled with OneAPI support. tparam_.num_parallel_tree != 0 model_.learner_model_param->num_output_group != 0 Unsupported data type for inplace predict. Check failed: success tree_begin == 0 Predict leaf supports only iteration end: (0, n_iteration), use model slicing instead. Predict contribution supports only iteration end: (0, n_iteration), using model slicing instead. Predict interaction contribution supports only iteration end: (0, n_iteration), using model slicing instead. in_it < tree_end num_trees Number of features used for training and prediction. Reserved option for vector tree. Number of parallel trees constructed during each iteration. This option is used to support boosted random forest. updater_seq Tree updater sequence. update Whether to run the normal boosting process that creates new trees, or to update the trees in an existing model. gpu_predictor oneapi_predictor Predictor algorithm type approx exact Choice of tree construction method. has not been registered in sample_type uniform Different types of sampling algorithm. normalize_type forest Different types of normalization algorithm. rate_drop Fraction of trees to drop during the dropout. Whether at least one tree should always be dropped during the dropout. skip_drop Probability of skipping the dropout during a boosting iteration. true get<String>(in["name"]) == "dart" weight_drop Check failed: p_dart Check failed: p_dart->weight_drop_.empty() Check failed: predictor i >= p_out_preds->version p_out_preds->predictions.Size() == predts.predictions.Size() predts.predictions.Size() == out_preds->predictions.Size() dart_train_param drop trees, weight = /Users/runner/work/ml-builds/ml-builds/xgboost/src/gbm/gbtree_model.cc param.num_trees == static_cast<int32_t>(trees.size()) fi->Read(¶m, sizeof(param)) == sizeof(param) GBTree: invalid model file fi->Read(dmlc::BeginPtr(tree_info), sizeof(int32_t) * param.num_trees) == sizeof(int32_t) * param.num_trees param.num_trees == static_cast<int>(trees.size()) gbtree_model_param trees tree_info GlobalConfiguration verbosity Flag to print out detailed breakdown of runtime. use_rmm Whether to use RAPIDS Memory Manager to allocate GPU memory in XGBoost LearnerModelParamLegacy LearnerTrainParam GenericParameter gpu_id eval_metric num_round CONFIG-offset: Learner /Users/runner/work/ml-builds/ml-builds/xgboost/src/learner.cc Check failed: IsA<Object>(in) learner learner_model_param objective gradient_booster booster attributes feature_names feature_types [ ]
Stack trace:
- [bt] ( _Z %zu /Users/runner/work/ml-builds/ml-builds/xgboost/include/xgboost/json.h Invalid cast, from to num_feature num_class base_score __ ', Possible Arguments:
+ [bt] ( _Z %zu /Users/runner/work/ml-builds/ml-builds/xgboost/include/xgboost/json.h Invalid cast, from to num_class base_score __ ', Possible Arguments:
----------------
: Check failed: !this->need_configuration_ Call Configure before saving model. Check failed: ret.ec == std::errc() Configure /Users/runner/work/ml-builds/ml-builds/xgboost/include/xgboost/generic_parameters.h
-n_gpus: n_gpus Check failed: matrix.first Check failed: !matrix.second.ref.expired() num_col <= static_cast<uint64_t>(std::numeric_limits<unsigned>::max()) Unfortunately, XGBoost does not support data matrices with features or greater mparam_.num_feature != 0 0 feature is supplied. Are you using raw Booster interface? ( multi:softprob num_output_group multi:softmax count:poisson 0.7 _param verbosity
-Parameters: { } might not be used.
+n_gpus: n_gpus Check failed: matrix.first Check failed: !matrix.second.ref.expired() num_col <= static_cast<uint64_t>(std::numeric_limits<unsigned>::max()) Unfortunately, XGBoost does not support data matrices with features or greater mparam_.num_feature != 0 0 feature is supplied. Are you using raw Booster interface? ( multi:softprob num_output_group multi:softmax max_delta_step count:poisson 0.7 _param Invalid parameter " " contains whitespace.
+Parameters: { " ", } might not be used.
This may not be accurate due to some parameters are only used in language bindings but
passed down to XGBoost core. Or some parameters are not used but slip through this
verification. Please open an issue if you find above cases.
- UpdateOneIter PredictRaw GetGradient Check failed: tparam_.dsplit != DataSplitMode::kAuto Precondition violated; dsplit cannot be 'auto' in distributed mode Column-wise data split is currently not supported. learner_model_param_.num_feature == p_fmat->Info().num_col_ Number of columns does not match number of features in booster. learner_model_param_.num_feature >= p_fmat->Info().num_col_ Empty dataset at worker: Check failed: gbm_ != nullptr Predict must happen after Load or configuration BoostOneIter EvalOneIter binary:logistic error logloss merror Starting in XGBoost 1.3.0, the default evaluation metric used with the objective ' ' was changed from ' ' to ' '. Explicitly set eval_metric if you'd like to restore the old behavior. multiple_predictions <= 1 Perform one kind of prediction at a time. value margin Unsupported prediction type: bs64 header != "bs64" Base64 format is no longer supported in brick. binf fp.Read(&header[0], 4) == 4U fi->Read(&mparam_, sizeof(mparam_)) == sizeof(mparam_) BoostLearner: wrong model format Check failed: fi->Read(&tparam_.objective) Check failed: fi->Read(&tparam_.booster) SAVED_PARAM_ count_poisson_max_delta_step multi: metrics Loading model from XGBoost < 1.0.0, consider saving it again for improved compatibility ; begin_layer >= 0 learner_train_param generic_param Model Config read can not have position excceed buffer length fp.Read(&header[0], header.size()) == serialisation_header_.size() Check failed: header == serialisation_header_
+ UpdateOneIter PredictRaw GetGradient Check failed: tparam_.dsplit != DataSplitMode::kAuto Precondition violated; dsplit cannot be 'auto' in distributed mode Column-wise data split is currently not supported. learner_model_param_.num_feature == p_fmat->Info().num_col_ Number of columns does not match number of features in booster. learner_model_param_.num_feature >= p_fmat->Info().num_col_ Empty dataset at worker: Check failed: gbm_ != nullptr Predict must happen after Load or configuration BoostOneIter EvalOneIter binary:logistic error logloss 1.3.0 binary:logitraw auc 1.4.0 merror Starting in XGBoost , the default evaluation metric used with the objective ' ' was changed from ' ' to ' '. Explicitly set eval_metric if you'd like to restore the old behavior. multiple_predictions <= 1 Perform one kind of prediction at a time. Unsupported prediction type: bs64 header != "bs64" Base64 format is no longer supported in brick. binf fp.Read(&header[0], 4) == 4U fi->Read(&mparam_, sizeof(mparam_)) == sizeof(mparam_) BoostLearner: wrong model format Check failed: fi->Read(&tparam_.objective) Check failed: fi->Read(&tparam_.booster) SAVED_PARAM_ count_poisson_max_delta_step multi: metrics Loading model from XGBoost < 1.0.0, consider saving it again for improved compatibility ; begin_layer >= 0 learner_train_param generic_param Model Config fp.Read(&header[0], header.size()) == serialisation_header_.size() Check failed: header == serialisation_header_
If you are loading a serialized model (like pickle in Python) generated by older
XGBoost, please export the model by calling `Booster.save_model` from that version
first, then load it back in current version. There's a simple script for helping
the process. See:
@@ -9658,21 +10328,21 @@
https://xgboost.readthedocs.io/en/latest/tutorials/saving_model.html
for reference to the script, and more details about differences between saving model and
serializing.
- fp.Read(&sz, sizeof(sz)) == sizeof(sz) sz > 0 Global bias of the model. Number of features in training data, this parameter will be automatically detected by learner. Number of class option for multi-class classifier. By default equals 0 and corresponds to binary classifier. Invalid Parameter format for expect Required parameter of Invalid NAN literal value should be smaller equal to key int (non-negative) ', valid values are: optional, default= dsplit col row Data split mode for distributed training. disable_default_eval_metric Flag to disable default metric. Set to >0 to disable gbtree Gradient booster used for training. reg:squarederror Objective function used for obtaining gradient. Enum exisit! Enums: ), true Random number seed during training. random_state seed_per_iteration Seed PRNG determnisticly via iterator number, this option will be switched on automatically on distributed mode. nthread Number of threads to use. n_jobs The primary GPU device ordinal. fail_on_invalid_gpu_id Fail with error when gpu_id is invalid. gpu_page_size GPU page size when running in external memory mode. enable_experimental_json_serialization Enable using JSON for memory serialization (Python Pickle, rabit checkpoints etc.). validate_parameters Enable checking whether parameters are used or not.
+ fp.Read(&sz, sizeof(sz)) == sizeof(sz) sz > 0 Global bias of the model. Number of features in training data, this parameter will be automatically detected by learner. Number of class option for multi-class classifier. By default equals 0 and corresponds to binary classifier. Invalid Parameter format for expect Required parameter of No conversion could be performed *p == ')' Invalid NAN literal value should be smaller equal to int (non-negative) ', valid values are: enum_back_map_.count(value) != 0U Value not found in enum declared dsplit col row Data split mode for distributed training. disable_default_eval_metric Flag to disable default metric. Set to >0 to disable Gradient booster used for training. reg:squarederror Objective function used for obtaining gradient. )
+ false Random number seed during training. random_state seed_per_iteration Seed PRNG determnisticly via iterator number, this option will be switched on automatically on distributed mode. Number of threads to use. n_jobs The primary GPU device ordinal. fail_on_invalid_gpu_id Fail with error when gpu_id is invalid. gpu_page_size GPU page size when running in external memory mode. validate_parameters Enable checking whether parameters are used or not.
Deprecated. Single process multi-GPU training is no longer supported.
Please switch to distributed training with one process per GPU.
- This can be done using Dask or Spark. See documentation for details. /Users/runner/work/ml-builds/ml-builds/xgboost/src/linear/linear_updater.cc Unknown linear updater LinearTrainParam Learning rate of each update. L2 regularization on weights. L1 regularization on weights. feature_selector cyclic shuffle thrifty greedy random Feature selection or ordering method. alpha CoordinateParam coord_descent Update linear model according to coordinate descent algorithm. top_k The number of top features to select in 'thrifty' feature_selector. The value of zero means using all the features. linear_train_param coordinate_param CoordinateUpdater /Users/runner/work/ml-builds/ml-builds/xgboost/src/linear/coordinate_common.h unknown coordinate selector: UpdateFeature Update linear model according to shotgun coordinate descent algorithm. /Users/runner/work/ml-builds/ml-builds/xgboost/src/linear/updater_shotgun.cc Unsupported feature selector for shotgun updater.
- Supported options are: {cyclic, shuffle} ConsoleLoggerParam WARNING: DEBUG: INFO: Flag to print out detailed breakdown of runtime. debug_verbose rmse Rooted mean square error. rmsle Rooted mean square log error. mae Mean absolute error. mape Mean absolute percentage error. mphe Mean Pseudo Huber error. Negative loglikelihood for logistic regression. poisson-nloglik Negative loglikelihood for poisson regression. gamma-deviance Residual deviance for gamma regression. gamma-nloglik Negative log-likelihood for gamma regression. Binary classification error. tweedie-nloglik tweedie-nloglik@rho for tweedie regression. /Users/runner/work/ml-builds/ml-builds/xgboost/src/metric/elementwise_metric.cu preds.Size() == info.labels_.Size() label and prediction size not match, hint: use merror or mlogloss for multi-class classification %f sscanf(param, "%f", &threshold_) == 1 unable to parse the threshold value for the error metric Check failed: param != nullptr tweedie-nloglik must be in format tweedie-nloglik@rho Check failed: rho_ < 2 && rho_ >= 1 tweedie variance power must be in interval [1, 2) tweedie-nloglik@ /Users/runner/work/ml-builds/ml-builds/xgboost/src/metric/metric.cc Unknown metric function Cannot find a GPU metric builder for metric . Resorting to the CPU builder Multiclass classification error. mlogloss Multiclass negative loglikelihood. /Users/runner/work/ml-builds/ml-builds/xgboost/src/metric/multiclass_metric.cu preds.Size() == 0 Check failed: preds.Size() % info.labels_.Size() == 0 label and prediction size not match nclass >= 1U mlogloss and merror are only used for multi-class classification, use logloss for binary classification Check failed: label_error >= 0 && label_error < static_cast<int32_t>(n_class) MultiClassEvaluation: label must be in [0, num_class), num_class= but found in label ams AMS metric for higgs. auc Area under curve for both classification and rank. aucpr Area under PR curve for both classification and rank. pre precision@k for rank. ndcg ndcg@k for rank. map map@k for rank. cox-nloglik Negative log partial likelihood of Cox proportioanl hazards model. /Users/runner/work/ml-builds/ml-builds/xgboost/src/metric/rank_metric.cc AMS must be in format ams@k ams@ Check failed: !distributed metric AMS do not support distributed evaluation best-ams-ratio= info.labels_.Size() != 0U label set cannot be empty label size predict size not match gptr.back() == info.labels_.Size() EvalAuc: group structure must match number of prediction dat[1] > 0.0f AUC: the dataset only contains pos or neg samples EvalAucPR: group structure must match number of prediction Check failed: !auc_error AUC-PR: error in calculation AUC-PR: the dataset only contains pos or neg samples dat[0] <= dat[1] AUC-PR: AUC > 1.0 %u[-]? gptr.size() != 0U must specify group when constructing rank file gptr.back() == preds.Size() EvalRank: group structure must match number of prediction Cox metric does not support distributed evaluation aft-nloglik Negative log likelihood of Accelerated Failure Time model. interval-regression-accuracy aft_loss_param /Users/runner/work/ml-builds/ml-builds/xgboost/src/metric/survival_metric.cu Unknown probability distribution preds.Size() == info.labels_lower_bound_.Size() preds.Size() == info.labels_upper_bound_.Size() ndata == labels_upper_bound.Size() Check failed: metric_ AFT metric must be configured first, with distribution type and scale survival:aft AFT loss function /Users/runner/work/ml-builds/ml-builds/xgboost/src/objective/aft_obj.cu info.labels_lower_bound_.Size() == ndata info.labels_upper_bound_.Size() == ndata info.weights_.Size() == ndata Number of weights should be equal to number of data points. Unrecognized distribution /Users/runner/work/ml-builds/ml-builds/xgboost/src/objective/../common/transform.h Not part of device code. WITH_CUDA: binary:hinge Hinge loss. Expects labels to be in [0,1f] /Users/runner/work/ml-builds/ml-builds/xgboost/src/objective/hinge.cu labels are not correctly provided preds.size= , label.size= SoftmaxMultiClassParam Softmax for multi-class classification, output class index. Softmax for multi-class classification, output probability distribution. Number of output class in the multi-class classification. softmax_multiclass_param /Users/runner/work/ml-builds/ml-builds/xgboost/src/objective/multiclass_obj.cu Check failed: preds.Size() == (static_cast<size_t>(param_.num_class) * info.labels_.Size()) SoftmaxMultiClassObj: label size and pred size does not match.
- label.Size() * num_class: num_class: preds.Size(): SoftmaxMultiClassObj: label must be in [0, num_class). span_ == rhs.span_ Objective candidate: /Users/runner/work/ml-builds/ml-builds/xgboost/src/objective/objective.cc Unknown objective function: ` `
- LambdaRankParam Pairwise rank objective. LambdaRank with NDCG as objective. LambdaRank with MAP as objective. rank:pairwise rank:ndcg rank:map num_pairsample Number of pair generated for each instance. fix_list_weight Normalize the weight of each list by this value, if equals 0, no effect will happen lambda_rank_param /Users/runner/work/ml-builds/ml-builds/xgboost/src/objective/rank_obj.cu Check failed: gptr.size() != 0 && gptr.back() == info.labels_.Size() group structure not consistent with #rows group ponter size: labels size: group pointer back: Computing gradients on CPU. RegLossParam Regression with squared error. Regression with root mean squared logarithmic error. Logistic regression for probability regression task. Regression Pseudo Huber error. Logistic regression for binary classification task. Logistic regression for classification, output score before logistic transformation. reg:linear PoissonRegressionParam Possion regression for count data. survival:cox Cox regression for censored survival data (negative labels are considered censored). reg:gamma Gamma regression for severity data. TweedieRegressionParam reg:tweedie Tweedie regression for insurance data. reg:squaredlogerror reg:logistic reg:pseudohubererror binary:logitraw scale_pos_weight Scale the weight of positive examples by this factor reg_loss_param /Users/runner/work/ml-builds/ml-builds/xgboost/src/objective/regression_obj.cu Loss: label must be greater than -1 for rmsle so that log(label + 1) can be valid. label must be in [0,1] for logistic regression /Users/runner/work/ml-builds/ml-builds/xgboost/src/objective/./regression_loss.h Check failed: base_score > 0.0f && base_score < 1.0f base_score must be in (0,1) for logistic loss, got: reg:linear is now deprecated in favor of reg:squarederror. Maximum delta step we allow each weight estimation to be. This parameter is required for possion regression. poisson_regression_param PoissonRegression: label must be nonnegative Check failed: last_abs_y <= abs_y CoxRegression: labels must be in sorted order, MetaInfo::LabelArgsort failed! GammaRegression: label must be nonnegative tweedie_variance_power Tweedie variance power. Must be between in range [1, 2). tweedie_regression_param TweedieRegression: label must be nonnegative Make predictions using CPU. /Users/runner/work/ml-builds/ml-builds/xgboost/src/predictor/cpu_predictor.cc tree_begin == 0 predts->version >= tree_begin predts->version == 0 output_groups != 0 ntree_limit != 0 beg_version <= end_version delta <= model.trees.size() Check failed: out_preds->Size() == output_groups * dmat->Info().num_row_ || out_preds->Size() == dmat->Info().num_row_ model.learner_model_param->num_output_group != 0 out_preds->Size() == n Ignoring the base margin, since it has incorrect length. The base margin must be an array of length [num_class] * [number of data points], i.e. * = . [number of data points], i.e. Instead, all data points will use base_score = out_preds->size() == p_fmat->Info().num_row_ * model.learner_model_param->num_output_group model.param.size_leaf_vector == 0 Data type is not supported by CPU Predictor. m->NumColumns() == model.learner_model_param->num_feature Number of columns in data must equal to trained model. /Users/runner/work/ml-builds/ml-builds/xgboost/dmlc-core/include/dmlc/any.h Check failed: type_ != nullptr The any container is empty requested= Check failed: *(type_->ptype_info) == typeid(T) The stored type mismatch stored= ncolumns != 0 /Users/runner/work/ml-builds/ml-builds/xgboost/src/predictor/predictor.cc Check failed: container_.find(m) != container_.cend() Check failed: container_.at(m).ref.lock() [Internal error]: DMatrix: has expired. Unknown predictor type unordered_map::at: key not found /Users/runner/work/ml-builds/ml-builds/xgboost/src/tree/constraints.cc Failed to parse feature interaction constraint:
- newsize != 0 /Users/runner/work/ml-builds/ml-builds/xgboost/src/tree/param.cc std::floor(d) == d Found floating point number in interaction constraints Unknown value type for interaction constraint: TreeParam TrainParam /Users/runner/work/ml-builds/ml-builds/xgboost/src/tree/tree_model.cc Unknown Model Builder: Dump text representation of tree Dump json representation of tree GraphvizParam dot Dump graphviz representation of tree Check failed: node.IsLeaf() Check failed: fi->Read(¶m, sizeof(TreeParam)) == sizeof(TreeParam) param.num_nodes != 0 fi->Read(dmlc::BeginPtr(nodes_), sizeof(Node) * nodes_.size()) == sizeof(Node) * nodes_.size() fi->Read(dmlc::BeginPtr(stats_), sizeof(RTreeNodeStat) * stats_.size()) == sizeof(RTreeNodeStat) * stats_.size() static_cast<int>(deleted_nodes_.size()) == param.num_deleted param.num_nodes == static_cast<int>(nodes_.size()) param.num_nodes == static_cast<int>(stats_.size()) param.deprecated_num_roots == 1 categories_segments categories_sizes categories_nodes categories j_end - j_begin != 0 std::numeric_limits<bst_cat_t>::min() != max_cat this->split_types_.size() == param.num_nodes this->GetSplitCategoriesPtr().size() == param.num_nodes tree_param n_nodes != 0 loss_changes loss_changes.size() == n_nodes sum_hessian sum_hessian.size() == n_nodes base_weights base_weights.size() == n_nodes left_children lefts.size() == n_nodes right_children rights.size() == n_nodes parents parents.size() == n_nodes split_indices indices.size() == n_nodes split_conditions conds.size() == n_nodes default_left default_left.size() == n_nodes split_type n_nodes == split_categories_segments_.size() parent != RegTree::kInvalidNodeId static_cast<bst_node_t>(deleted_nodes_.size()) == param.num_deleted this->split_categories_segments_.size() == param.num_nodes num_nodes get<String>(out["tree_param"]["num_nodes"]) == std::to_string(param.num_nodes) this->node_mean_values_.size() > 0U unique_path[i].pweight == 0 Unique path must have zero weight : %02d:%02d:%02d ) DMLC_LOG_STACK_TRACE_DEPTH /Users/runner/work/ml-builds/ml-builds/xgboost/include/xgboost/tree_model.h param.num_nodes < std::numeric_limits<int>::max() number of nodes in the tree exceed 2^31 vs. [xgboost] Condition %s failed.
- (pos_v.int_pos) < (bits_.size()) Number of features used in tree construction. num_deleted Size of leaf vector, reserved for vector tree optional, default= , required is not presented Invalid Input: ' ' /Users/runner/work/ml-builds/ml-builds/xgboost/dmlc-core/include/dmlc/./parameter.h enum_back_map_.count(value) != 0U Value not found in enum declared has already been registered in min_split_loss Minimum loss reduction required to make a further partition. max_depth Maximum depth of the tree; 0 indicates no limit; a limit is required for depthwise policy max_leaves Maximum number of leaves; 0 indicates no limit. max_bin if using histogram-based algorithm, maximum number of bins per feature grow_policy depthwise lossguide Tree growing policy. 0: favor splitting at nodes closest to the node, i.e. grow depth-wise. 1: favor splitting at nodes with highest loss change. (cf. LightGBM) min_child_weight Minimum sum of instance weight(hessian) needed in a child. reg_lambda L2 regularization on leaf weight reg_alpha L1 regularization on leaf weight default_direction learn right Default direction choice when encountering a missing value max_delta_step Maximum delta step we allow each tree's weight estimate to be. If the value is set to 0, it means there is no constraint subsample Row subsample ratio of training instance. sampling_method uniform gradient_based Sampling method. 0: select random training instances uniformly. 1: select random training instances with higher probability when the gradient and hessian are larger. (cf. CatBoost) colsample_bynode Subsample ratio of columns, resample on each node (split). colsample_bylevel Subsample ratio of columns, resample on each level. colsample_bytree Subsample ratio of columns, resample on each tree construction. sketch_eps EXP Param: Sketch accuracy of approximate algorithm. sketch_ratio EXP Param: Sketch accuracy related parameter of approximate algorithm. cache_opt EXP Param: Cache aware optimization. refresh_leaf Whether the refresh updater needs to update leaf values. monotone_constraints Constraint of variable monotonicity interaction_constraints Constraints for interaction representing permitted interactions.The constraints must be specified in the form of a nest list,e.g. [[0, 1], [2, 3, 4]], where each inner list is a group ofindices of features that are allowed to interact with each other.See tutorial for more information split_evaluator elastic_net,monotonic The criteria to use for ranking splits sparse_threshold percentage threshold for treating a feature as sparse enable_feature_grouping if >0, enable feature grouping to ameliorate work imbalance among worker threads max_conflict_rate when grouping features, how many "conflicts" to allow.conflict is when an instance has nonzero values for two or more features.default is 0, meaning features should be strictly complementary. max_search_group when grouping features, how much effort to expend to prevent singleton groups. We'll try to insert each feature into existing groups before creating a new group for that feature; to save time, only up to (max_search_group) of existing groups will be considered. If set to zero, ALL existing groups will be examined. lambda gamma No conversion could be performed *p == ')' ( Alias {nid}:[{fname}] yes={yes},no={no} {nid} {fname} {yes} pos != std::string::npos /Users/runner/work/ml-builds/ml-builds/xgboost/include/xgboost/feature_map.h idx < names_.size() FeatureMap feature index exceed bound {tabs}{nid}:[{fname}<{cond}] yes={left},no={right},missing={missing} {tabs} {cond} {left} {right} {missing} ,gain={loss_chg},cover={sum_hess} {loss_chg} {sum_hess} {tabs}{nid}:[f{fname}<{cond}] yes={left},no={right},missing={missing} Unknown feature map type. {tabs}{nid}:leaf={leaf}{stats} ,cover={cover} {leaf} {stats} {cover} {parent}{stat}
+ This can be done using Dask or Spark. See documentation for details. /Users/runner/work/ml-builds/ml-builds/xgboost/src/linear/linear_updater.cc Unknown linear updater LinearTrainParam Learning rate of each update. reg_lambda L2 regularization on weights. reg_alpha L1 regularization on weights. feature_selector cyclic shuffle thrifty greedy random Feature selection or ordering method. lambda CoordinateParam coord_descent Update linear model according to coordinate descent algorithm. top_k The number of top features to select in 'thrifty' feature_selector. The value of zero means using all the features. linear_train_param coordinate_param CoordinateUpdater /Users/runner/work/ml-builds/ml-builds/xgboost/src/linear/coordinate_common.h unknown coordinate selector: UpdateFeature Update linear model according to shotgun coordinate descent algorithm. /Users/runner/work/ml-builds/ml-builds/xgboost/src/linear/updater_shotgun.cc Unsupported feature selector for shotgun updater.
+ Supported options are: {cyclic, shuffle} WARNING: DEBUG: INFO: /Users/runner/work/ml-builds/ml-builds/xgboost/src/metric/auc.cc Check failed: !labels.empty() labels.size() == predts.size() n_classes != 0 auc <= 1.0f info.group_ptr_.size() >= 2 Receiver Operating Characteristic Area Under the Curve. /Users/runner/work/ml-builds/ml-builds/xgboost/src/metric/auc.h Invalid group with less than 3 samples is found on worker . Calculating AUC value requires at least 2 pairs of samples. /Users/runner/work/ml-builds/ml-builds/xgboost/src/metric/../common/common.h info.weights_.Size() == info.group_ptr_.size() - 1 info.group_ptr_.back() == info.labels_.Size() auc <= 1 Total AUC across groups: , valid groups: Dataset contains only positive or negative samples. rmse Rooted mean square error. rmsle Rooted mean square log error. mae Mean absolute error. mape Mean absolute percentage error. mphe Mean Pseudo Huber error. Negative loglikelihood for logistic regression. poisson-nloglik Negative loglikelihood for poisson regression. gamma-deviance Residual deviance for gamma regression. gamma-nloglik Negative log-likelihood for gamma regression. Binary classification error. tweedie-nloglik tweedie-nloglik@rho for tweedie regression. /Users/runner/work/ml-builds/ml-builds/xgboost/src/metric/elementwise_metric.cu preds.Size() == info.labels_.Size() label and prediction size not match, hint: use merror or mlogloss for multi-class classification %f sscanf(param, "%f", &threshold_) == 1 unable to parse the threshold value for the error metric Check failed: param != nullptr tweedie-nloglik must be in format tweedie-nloglik@rho Check failed: rho_ < 2 && rho_ >= 1 tweedie variance power must be in interval [1, 2) tweedie-nloglik@ /Users/runner/work/ml-builds/ml-builds/xgboost/src/metric/metric.cc Unknown metric function Cannot find a GPU metric builder for metric . Resorting to the CPU builder Multiclass classification error. mlogloss Multiclass negative loglikelihood. /Users/runner/work/ml-builds/ml-builds/xgboost/src/metric/multiclass_metric.cu preds.Size() == 0 Check failed: preds.Size() % info.labels_.Size() == 0 label and prediction size not match nclass >= 1U mlogloss and merror are only used for multi-class classification, use logloss for binary classification Check failed: label_error >= 0 && label_error < static_cast<int32_t>(n_class) MultiClassEvaluation: label must be in [0, num_class), num_class= but found in label ams AMS metric for higgs. aucpr Area under PR curve for both classification and rank. pre precision@k for rank. ndcg ndcg@k for rank. map map@k for rank. cox-nloglik Negative log partial likelihood of Cox proportioanl hazards model. /Users/runner/work/ml-builds/ml-builds/xgboost/src/metric/rank_metric.cc AMS must be in format ams@k ams@ Check failed: !distributed metric AMS do not support distributed evaluation best-ams-ratio= info.labels_.Size() != 0U label set cannot be empty label size predict size not match gptr.back() == info.labels_.Size() EvalAucPR: group structure must match number of prediction dat[1] > 0.0f AUC-PR: the dataset only contains pos or neg samples dat[0] <= dat[1] AUC-PR: AUC > 1.0 Check failed: !auc_error AUC-PR: error in calculation %u[-]? gptr.size() != 0U must specify group when constructing rank file gptr.back() == preds.Size() EvalRank: group structure must match number of prediction Cox metric does not support distributed evaluation aft-nloglik Negative log likelihood of Accelerated Failure Time model. interval-regression-accuracy aft_loss_param /Users/runner/work/ml-builds/ml-builds/xgboost/src/metric/survival_metric.cu Unknown probability distribution preds.Size() == info.labels_lower_bound_.Size() preds.Size() == info.labels_upper_bound_.Size() ndata == labels_upper_bound.Size() Check failed: metric_ AFT metric must be configured first, with distribution type and scale survival:aft AFT loss function /Users/runner/work/ml-builds/ml-builds/xgboost/src/objective/aft_obj.cu info.labels_lower_bound_.Size() == ndata info.labels_upper_bound_.Size() == ndata info.weights_.Size() == ndata Number of weights should be equal to number of data points. Unrecognized distribution /Users/runner/work/ml-builds/ml-builds/xgboost/src/objective/../common/transform.h Not part of device code. WITH_CUDA: binary:hinge Hinge loss. Expects labels to be in [0,1f] /Users/runner/work/ml-builds/ml-builds/xgboost/src/objective/hinge.cu labels are not correctly provided preds.size= , label.size= SoftmaxMultiClassParam Softmax for multi-class classification, output class index. Softmax for multi-class classification, output probability distribution. Number of output class in the multi-class classification. softmax_multiclass_param /Users/runner/work/ml-builds/ml-builds/xgboost/src/objective/multiclass_obj.cu Check failed: preds.Size() == (static_cast<size_t>(param_.num_class) * info.labels_.Size()) SoftmaxMultiClassObj: label size and pred size does not match.
+ label.Size() * num_class: num_class: preds.Size(): SoftmaxMultiClassObj: label must be in [0, num_class). Objective candidate: /Users/runner/work/ml-builds/ml-builds/xgboost/src/objective/objective.cc Unknown objective function: ` `
+ LambdaRankParam Pairwise rank objective. LambdaRank with NDCG as objective. LambdaRank with MAP as objective. rank:pairwise rank:ndcg rank:map num_pairsample Number of pair generated for each instance. fix_list_weight Normalize the weight of each list by this value, if equals 0, no effect will happen lambda_rank_param /Users/runner/work/ml-builds/ml-builds/xgboost/src/objective/rank_obj.cu Check failed: gptr.size() != 0 && gptr.back() == info.labels_.Size() group structure not consistent with #rows group ponter size: labels size: group pointer back: Computing gradients on CPU. RegLossParam Regression with squared error. Regression with root mean squared logarithmic error. Logistic regression for probability regression task. Regression Pseudo Huber error. Logistic regression for binary classification task. Logistic regression for classification, output score before logistic transformation. reg:linear PoissonRegressionParam Possion regression for count data. survival:cox Cox regression for censored survival data (negative labels are considered censored). reg:gamma Gamma regression for severity data. TweedieRegressionParam reg:tweedie Tweedie regression for insurance data. reg:squaredlogerror reg:logistic reg:pseudohubererror scale_pos_weight Scale the weight of positive examples by this factor reg_loss_param /Users/runner/work/ml-builds/ml-builds/xgboost/src/objective/regression_obj.cu Loss: label must be greater than -1 for rmsle so that log(label + 1) can be valid. label must be in [0,1] for logistic regression /Users/runner/work/ml-builds/ml-builds/xgboost/src/objective/./regression_loss.h Check failed: base_score > 0.0f && base_score < 1.0f base_score must be in (0,1) for logistic loss, got: reg:linear is now deprecated in favor of reg:squarederror. Maximum delta step we allow each weight estimation to be. This parameter is required for possion regression. poisson_regression_param PoissonRegression: label must be nonnegative Check failed: last_abs_y <= abs_y CoxRegression: labels must be in sorted order, MetaInfo::LabelArgsort failed! GammaRegression: label must be positive. tweedie_variance_power Tweedie variance power. Must be between in range [1, 2). tweedie_regression_param TweedieRegression: label must be nonnegative Make predictions using CPU. /Users/runner/work/ml-builds/ml-builds/xgboost/src/predictor/cpu_predictor.cc model.learner_model_param->num_output_group != 0 out_preds->Size() == n Ignoring the base margin, since it has incorrect length. The base margin must be an array of length [num_class] * [number of data points], i.e. * = . [number of data points], i.e. Instead, all data points will use base_score = out_preds->size() == p_fmat->Info().num_row_ * model.learner_model_param->num_output_group model.param.size_leaf_vector == 0 size_leaf_vector is enforced to 0 so far m->NumColumns() == model.learner_model_param->num_feature Number of columns in data must equal to trained model. /Users/runner/work/ml-builds/ml-builds/xgboost/dmlc-core/include/dmlc/any.h Check failed: type_ != nullptr The any container is empty requested= Check failed: *(type_->ptype_info) == typeid(T) The stored type mismatch stored= ncolumns != 0 /Users/runner/work/ml-builds/ml-builds/xgboost/src/predictor/predictor.cc Check failed: container_.find(m) != container_.cend() Check failed: container_.at(m).ref.lock() [Internal error]: DMatrix: has expired. Unknown predictor type unordered_map::at: key not found /Users/runner/work/ml-builds/ml-builds/xgboost/src/tree/constraints.cc Failed to parse feature interaction constraint:
+ newsize != 0 /Users/runner/work/ml-builds/ml-builds/xgboost/src/tree/param.cc std::floor(d) == d Found floating point number in interaction constraints Unknown value type for interaction constraint: TreeParam TrainParam /Users/runner/work/ml-builds/ml-builds/xgboost/src/tree/tree_model.cc Unknown Model Builder: Dump text representation of tree Dump json representation of tree GraphvizParam dot Dump graphviz representation of tree Check failed: node.IsLeaf() Check failed: fi->Read(¶m, sizeof(TreeParam)) == sizeof(TreeParam) param.num_nodes != 0 fi->Read(dmlc::BeginPtr(nodes_), sizeof(Node) * nodes_.size()) == sizeof(Node) * nodes_.size() fi->Read(dmlc::BeginPtr(stats_), sizeof(RTreeNodeStat) * stats_.size()) == sizeof(RTreeNodeStat) * stats_.size() static_cast<int>(deleted_nodes_.size()) == param.num_deleted param.num_nodes == static_cast<int>(nodes_.size()) param.num_nodes == static_cast<int>(stats_.size()) param.deprecated_num_roots == 1 categories_segments categories_sizes categories_nodes categories j_end - j_begin != 0 std::numeric_limits<bst_cat_t>::min() != max_cat this->split_types_.size() == param.num_nodes this->GetSplitCategoriesPtr().size() == param.num_nodes tree_param n_nodes != 0 loss_changes loss_changes.size() == n_nodes sum_hessian sum_hessian.size() == n_nodes base_weights base_weights.size() == n_nodes left_children lefts.size() == n_nodes right_children rights.size() == n_nodes parents parents.size() == n_nodes split_indices indices.size() == n_nodes split_conditions conds.size() == n_nodes default_left default_left.size() == n_nodes split_type n_nodes == split_categories_segments_.size() static_cast<bst_node_t>(deleted_nodes_.size()) == param.num_deleted this->split_categories_segments_.size() == param.num_nodes num_nodes get<String>(out["tree_param"]["num_nodes"]) == std::to_string(param.num_nodes) this->node_mean_values_.size() > 0U unique_path[i].pweight == 0 Unique path must have zero weight : %02d:%02d:%02d ) DMLC_LOG_STACK_TRACE_DEPTH /Users/runner/work/ml-builds/ml-builds/xgboost/include/xgboost/tree_model.h param.num_nodes < std::numeric_limits<int>::max() number of nodes in the tree exceed 2^31 vs. num_feature Number of features used in tree construction. num_deleted size_leaf_vector Size of leaf vector, reserved for vector tree but value=' , for Parameter exceed bound [ should be greater equal to optional, default= map::at: key not found key learning_rate Learning rate(step size) of update. min_split_loss Minimum loss reduction required to make a further partition. max_depth Maximum depth of the tree; 0 indicates no limit; a limit is required for depthwise policy max_leaves Maximum number of leaves; 0 indicates no limit. max_bin if using histogram-based algorithm, maximum number of bins per feature grow_policy depthwise lossguide Tree growing policy. 0: favor splitting at nodes closest to the node, i.e. grow depth-wise. 1: favor splitting at nodes with highest loss change. (cf. LightGBM) min_child_weight Minimum sum of instance weight(hessian) needed in a child. L2 regularization on leaf weight L1 regularization on leaf weight default_direction learn right Default direction choice when encountering a missing value Maximum delta step we allow each tree's weight estimate to be. If the value is set to 0, it means there is no constraint subsample Row subsample ratio of training instance. sampling_method gradient_based Sampling method. 0: select random training instances uniformly. 1: select random training instances with higher probability when the gradient and hessian are larger. (cf. CatBoost) colsample_bynode Subsample ratio of columns, resample on each node (split). colsample_bylevel Subsample ratio of columns, resample on each level. colsample_bytree Subsample ratio of columns, resample on each tree construction. sketch_eps EXP Param: Sketch accuracy of approximate algorithm. sketch_ratio EXP Param: Sketch accuracy related parameter of approximate algorithm. cache_opt EXP Param: Cache aware optimization. refresh_leaf Whether the refresh updater needs to update leaf values. monotone_constraints Constraint of variable monotonicity interaction_constraints Constraints for interaction representing permitted interactions.The constraints must be specified in the form of a nest list,e.g. [[0, 1], [2, 3, 4]], where each inner list is a group ofindices of features that are allowed to interact with each other.See tutorial for more information split_evaluator elastic_net,monotonic The criteria to use for ranking splits sparse_threshold percentage threshold for treating a feature as sparse enable_feature_grouping if >0, enable feature grouping to ameliorate work imbalance among worker threads max_conflict_rate when grouping features, how many "conflicts" to allow.conflict is when an instance has nonzero values for two or more features.default is 0, meaning features should be strictly complementary. max_search_group when grouping features, how much effort to expend to prevent singleton groups. We'll try to insert each feature into existing groups before creating a new group for that feature; to save time, only up to (max_search_group) of existing groups will be considered. If set to zero, ALL existing groups will be examined. alpha gamma eta Out of range value for , value=' pos <= value.length() Some trailing characters could not be parsed: ' Out of range value /Users/runner/work/ml-builds/ml-builds/xgboost/dmlc-core/include/dmlc/./strtonum.h 1 0 Alias {nid}:[{fname}] yes={yes},no={no} {nid} {fname} {yes} pos != std::string::npos /Users/runner/work/ml-builds/ml-builds/xgboost/include/xgboost/feature_map.h idx < names_.size() FeatureMap feature index exceed bound {tabs}{nid}:[{fname}<{cond}] yes={left},no={right},missing={missing} {tabs} {cond} {left} {right} {missing} ,gain={loss_chg},cover={sum_hess} {loss_chg} {sum_hess} {tabs}{nid}:[f{fname}<{cond}] yes={left},no={right},missing={missing} Unknown feature map type. {tabs}{nid}:leaf={leaf}{stats} ,cover={cover} {leaf} {stats} {cover} {parent}{stat}
{left}
-{right} {stat} {nodes} "nodeid": {nid}, "depth": {depth}, "split": "{fname}", "yes": {yes}, "no": {no} {depth} "nodeid": {nid}, "depth": {depth}, "split": "{fname}", "split_condition": {cond}, "yes": {left}, "no": {right}, "missing": {missing} , "gain": {loss_chg}, "cover": {sum_hess} "nodeid": {nid}, "depth": {depth}, "split": {fname}, "split_condition": {cond}, "yes": {left}, "no": {right}, "missing": {missing} {{properties} {stat}, "children": [{left}, {right}
+{right} {stat} {nodes} "nodeid": {nid}, "depth": {depth}, "split": "{fname}", "yes": {yes}, "no": {no} {depth} "nodeid": {nid}, "depth": {depth}, "split": "{fname}", "split_condition": {cond}, "yes": {left}, "no": {right}, "missing": {missing} , "gain": {loss_chg}, "cover": {sum_hess} {{properties} {stat}, "children": [{left}, {right}
{indent}]} {properties} { "nodeid": {nid}, "leaf": {leaf} {stat}} , "cover": {sum_hess} {newline}{indent}{nodes} {newline} yes_color #0000FF Edge color when meets the node condition. #FF0000 Edge color when doesn't meet the node condition. rankdir Passed to graphiz via graph_attr. condition_node_params Conditional node configuration leaf_node_params Leaf node configuration graph_attrs Any other extra attributes for graphviz `graph_attr`. Failed to parse graphviz parameters:
With error:
" graph [ {key}="{value}" ]
{key} {value} The following parameters for graphviz are not recognized:
/Users/runner/work/ml-builds/ml-builds/xgboost/dmlc-core/include/dmlc/./json.h ch == '{' Error at , Expect '{' but get ' Line , around ^` ` ch == ',' , JSON object expect '}' or ',' ' ch == ':' , Expect ':' but get ' ch == '\"' , Expect '"' but get '
\ unknown string escape \ , Expect '"' but reach end of line {nid} [ label="{fname}{<}{cond}" {params}]
@@ -9681,1720 +10351,1617 @@
{leaf-value} {parent}
{left}
{right} digraph {
graph [ rankdir={rankdir} ]
{graph_attrs}
-{nodes}} {rankdir} {graph_attrs} (_count == dynamic_extent) ? (_offset <= size()) : (_offset + _count <= size()) _ptr || _count == 0 /Users/runner/work/ml-builds/ml-builds/xgboost/src/tree/tree_updater.cc Unknown tree updater ColMakerTrainParam grow_colmaker Grow tree with parallelization over columns. opt_dense_col EXP Param: speed optimization for dense column. train_param colmaker_train_param /Users/runner/work/ml-builds/ml-builds/xgboost/src/tree/updater_colmaker.cc Updater `grow_colmaker` or `exact` tree method doesn't support distributed training. /Users/runner/work/ml-builds/ml-builds/xgboost/src/tree/param.h Max leaves and max depth cannot both be unconstrained. this->max_depth <= 31 max_depth can not be greater than 31 as that might generate 2 ** 32 - 1 nodes. Check failed: param_.cache_opt Support for `cache_opt' is removed in 1.0.0 fmat.Info().num_row_ == position_.size() param_.sampling_method == TrainParam::kUniform Only uniform sampling is supported, gradient-based sampling is only support by GPU Hist. ridx < position_.size() ridx exceed bound ridx= pos= /Users/runner/work/ml-builds/ml-builds/xgboost/src/tree/../common/transform.h !common::CheckNAN(mid) grow_local_histmaker Tree constructor that uses approximate histogram construction. grow_histmaker Tree constructor that uses approximate global of histogram construction. /Users/runner/work/ml-builds/ml-builds/xgboost/src/tree/../common/quantile.h fi.Read(&this->size, sizeof(this->size)) == sizeof(this->size) fi.Read(this->data, this->size * sizeof(Entry)) == this->size * sizeof(Entry) check quantile stats, nbig= , n= srcsize= , maxsize= , range= , chunk= Check failed: nbig < n quantile: too many large chunk ] rmin= , rmax= , wmin= , v= /Users/runner/work/ml-builds/ml-builds/xgboost/src/tree/updater_histmaker.cc Check failed: param_.max_depth > 0 max_depth must be larger than 0 /Users/runner/work/ml-builds/ml-builds/xgboost/src/tree/./updater_basemaker-inl.h node2workindex_[nid] == static_cast<int>(wid) summary_array_.size() == sketchs_.size() offset == -2 this->wspace_.rptr.size() == (fset.size() + 1) * this->qexpand_.size() + 1 fid * 2 + 1 < fminmax_.size() FeatHelper fid exceed query bound ret > 0U Check failed: tree[nid].IsLeaf() sketch->temp.size < max_size invalid maximum size max_size= , stemp.size INFO: rmax= , sum_total= , naxt_goal= , size= sketch->temp.size <= max_size Finalize: invalid maximum size, max_size= , stemp.size= fid * 2 < fminmax_.size() fv= , hist.size= hist[ ]= , hist.last= istart != hist.size this->qexpand_.size() == 1U this->wspace_.rptr.back() == this->wspace_.cut.size() prune Pruner that prune the tree according to statistics. TreePruner PrunerUpdate /Users/runner/work/ml-builds/ml-builds/xgboost/src/tree/updater_prune.cc tree pruning end, extra nodes, pruned nodes, max_depth= Check failed: !tree[pid].IsLeaf() Check failed: nodes_[nodes_[rid].LeftChild() ].IsLeaf() Check failed: nodes_[nodes_[rid].RightChild()].IsLeaf() nid >= 1 Quantile::Builder Update SubtractionTrick UpdatePredictionCache /Users/runner/work/ml-builds/ml-builds/xgboost/src/tree/updater_quantile_hist.cc out_preds.size() > 0U Check failed: (param_.max_depth > 0 || param_.max_leaves > 0) max_depth or max_leaves cannot be both 0 (unlimited); at least one should be a positive quantity. max_depth cannot be 0 (unlimited) when grow_policy is depthwise. min_nbins_per_feature > 0U EvaluateSplits ApplySplit (*p_tree)[nid].LeftChild() + 1 == (*p_tree)[nid].RightChild() upper_bound < static_cast<uint32_t>(std::numeric_limits<int32_t>::max()) InitNewNode BuildLocalHistograms SplitSiblings BuildNodeStats ExpandWithLossGuide CPUHistMakerTrainParam GmatInitialization grow_fast_histmaker (Deprecated, use grow_quantile_histmaker instead.) Grow tree using quantized histogram. Grow tree using quantized histogram. /Users/runner/work/ml-builds/ml-builds/xgboost/src/tree/../common/row_set.h elem_of_each_node_.size() == 0U Check failed: e.begin != nullptr n_left + n_right == e.Size() begin + n_left <= e.end begin + n_left + n_right == e.end /Users/runner/work/ml-builds/ml-builds/xgboost/src/tree/../common/column_matrix.h gmat.cut.Ptrs()[fid + 1] - gmat.cut.Ptrs()[fid] <= max_val gmat_bin_size == kUint32BinsTypeSize bins_type_size_ == kUint32BinsTypeSize cpu_hist_train_param /Users/runner/work/ml-builds/ml-builds/xgboost/src/tree/./updater_quantile_hist.h Attempted to load internal configuration for a model file that was generated by a previous version of XGBoost. A likely cause for this warning is that the model was saved with saveRDS() in R or pickle.dump() in Python. We strongly ADVISE AGAINST using saveRDS() or pickle.dump() so that the model remains accessible in current and upcoming XGBoost releases. Please use xgb.save() instead to preserve models for the long term. For more details and explanation, see https://xgboost.readthedocs.io/en/latest/tutorials/saving_model.html single_precision_histogram Use single precision to build histograms. SyncHistograms SyncHistogramsAllreduce /Users/runner/work/ml-builds/ml-builds/xgboost/src/tree/../common/threading_utils.h begin < end /Users/runner/work/ml-builds/ml-builds/xgboost/src/tree/../common/hist_util.h end > begin nid < nodes_ i < first_dimension_.size() i < ranges_.size() AddHistRows row_ptr_[nid] == kMax Check failed: (*p_last_tree_)[nid].IsLeaf() id != kMax cut_ptr[fid] <= static_cast<uint32_t>(std::numeric_limits<int32_t>::max()) cut_ptr[fid + 1] <= static_cast<uint32_t>(std::numeric_limits<int32_t>::max()) local_block_ptr != (BlockInfo*)nullptr nodes == targeted_hists.size() tid < nthreads_ data_ || size_ == 0 grow_fast_histmaker is deprecated, use grow_quantile_histmaker instead. QuantileHistMaker refresh Refresher that refreshes the weight and statistics according to data. /Users/runner/work/ml-builds/ml-builds/xgboost/src/tree/updater_refresh.cc batch.Size() < std::numeric_limits<unsigned>::max() Syncher that synchronize the tree in all distributed nodes. NULL worker rabit_reduce_buffer 256MB DMLC_TASK_ID DMLC_ROLE DMLC_NUM_ATTEMPT DMLC_TRACKER_URI DMLC_TRACKER_PORT DMLC_WORKER_CONNECT_RETRY %[^=]=%s mapred_tip_id mapreduce_task_id hadoop_mode is set but cannot find mapred_task_id rabit_task_id rabit_hadoop_mode mapred_task_id %d rabit_num_trial mapred_map_tasks mapreduce_job_maps hadoop_mode is set but cannot find mapred_map_tasks rabit_world_size /Users/runner/work/ml-builds/ml-builds/xgboost/rabit/src/allreduce_base.cc Rabit Module currently only work with dmlc worker can only call Init once start Failed to shutdown due to %s print rabit_tracker_uri rabit_tracker_port rabit_tree_reduce_minsize rabit_reduce_ring_mincount rabit_reduce_ring_mincount should be greater than 0 rabit_bootstrap_cache rabit_debug rabit_timeout rabit_timeout_sec rabit_timeout_sec should be non negative second rabit_enable_tcp_no_delay Connect to (failed): [ ]
- Connect Retry connect to ip(retry time ): [ ReConnectLink failure 1 ReConnectLink failure 2 sync::Invalid tracker message, init failure ReConnectLink failure 3 task connected to the tracker ReConnectLink failure 4 must keep rank to same if the node already have one tracker got overwhelemed and not able to assign correct rank got new rank ReConnectLink fail to bind the ports specified ReConnectLink failure 5 ReConnectLink failure 6 ReConnectLink failure 7 ReConnectLink failure 8 ReConnectLink failure 9 ReConnectLink failure 10 ReConnectLink failure 12 ReConnectLink failure 13 ReConnectLink failure, link rank inconsistent Override a link that is active ReConnectLink failure 14 ReConnectLink failure 15 ReConnectLink: bad socket tcp no delay is not implemented on non unix platforms cannot find parent in the link cannot find prev ring in the link cannot find next ring in the link failed in ReconnectLink buffer size inconsistent must assign buffer_size Allreduce: size check Allreduce: boundary error Broadcast: root should be smaller than world size need to assume rank structure write ptr boundary check [%d] read_ptr boundary check fail to get host name Socket::Close double close the socket or close without create error during send SendStr %lu%c invalid format for %s invalid format for %s,shhould be {integer}{unit}, unit can be {B, KB, MB, GB} Create cannot obtain address of %s Does not support IPv6 Socket %s Error:%s SendAll RecvAll 0.0.0.0 TryBindHost GetSockError error during send RecvStr Accept SetNonBlock-1 SetNonBlock-2 SetKeepAlive too large type_nbytes=%lu, buffer_size=%lu /Users/runner/work/ml-builds/ml-builds/xgboost/rabit/include/rabit/internal/socket.h Poll timeout Poll ReadToRingBuffer: buffer not allocated ReadToRingBuffer: max_size_read check Allreduce: boundary check AllgatherRing failed Allreduce failed Broadcast failed unknown enum_op unknown data_type Failed to initialize RABIT. Failed to shutdown RABIT worker. Read pickle string not implemented DataType does not support bitwise or operation the rabit has not been initialized cannot initialize reduce handle twice must intialize handle to call AllReduce LibSVMParserParam LibFMParserParam CSVParserParam libfm format File format indexing_mode If >0, treat all feature indices as 1-based. If =0, treat all feature indices as 0-based. If <0, use heuristic to automatically detect mode of indexing. See https://en.wikipedia.org/wiki/Array_data_type#Index_origin for more details on indexing modes. If >0, treat all field and feature indices as 1-based. If =0, treat all field and feature indices as 0-based. If <0, use heuristic to automatically detect mode of indexing. See https://en.wikipedia.org/wiki/Array_data_type#Index_origin for more details on indexing modes. File format. label_column Column index (0-based) that will put into label. delimiter Delimiter used in the csv file. weight_column Column index that will put into instance weights. /Users/runner/work/ml-builds/ml-builds/xgboost/dmlc-core/src/data/disk_row_iter.h Check failed: TryLoadCache() failed to build cache file /Users/runner/work/ml-builds/ml-builds/xgboost/dmlc-core/src/data/./row_block.h Check failed: fi->Read(&label) Bad RowBlock format Check failed: fi->Read(&weight) Check failed: fi->Read(&qid) Check failed: fi->Read(&field) Check failed: fi->Read(&index) Check failed: fi->Read(&value) Check failed: fi->Read(&max_field, sizeof(IndexType)) Check failed: fi->Read(&max_index, sizeof(IndexType)) MB read, MB/sec finish reading at %g MB/sec batch.field[i] <= std::numeric_limits<IndexType>::max() field exceed numeric bound of current type batch.index[i] <= std::numeric_limits<IndexType>::max() index exceed numeric bound of current type label.size() + 1 == offset.size() offset.back() == index.size() Check failed: offset.back() == value.size() || value.size() == 0 /Users/runner/work/ml-builds/ml-builds/xgboost/dmlc-core/src/data/basic_row_iter.h finish reading at /Users/runner/work/ml-builds/ml-builds/xgboost/dmlc-core/src/data.cc Unknown data type /Users/runner/work/ml-builds/ml-builds/xgboost/dmlc-core/src/data/./libsvm_parser.h param_.format == "libsvm" /Users/runner/work/ml-builds/ml-builds/xgboost/dmlc-core/src/data/./text_parser.h chunk.size != 0U qid: Check failed: out->label.size() + 1 == out->offset.size() Check failed: base <= 10 && base >= 2 sign == true /Users/runner/work/ml-builds/ml-builds/xgboost/dmlc-core/src/data/parser.h cannot call ParseNext /Users/runner/work/ml-builds/ml-builds/xgboost/dmlc-core/src/data/libfm_parser.h param_.format == "libfm" Check failed: out->field.size() == out->index.size() /Users/runner/work/ml-builds/ml-builds/xgboost/dmlc-core/src/data/csv_parser.h param_.format == "csv" Check failed: param_.label_column != param_.weight_column || param_.label_column < 0 Must have distinct columns for labels and instance weights Delimiter ' ' is not found in the line. Expected ' ' as the delimiter to separate fields. Check failed: out->weight.size() == 0 || out->weight.size() + 1 == out->offset.size() hdfs:// viewfs:// /Users/runner/work/ml-builds/ml-builds/xgboost/dmlc-core/src/io.cc Please compile with DMLC_USE_HDFS=1 to use hdfs s3:// http:// https:// Please compile with DMLC_USE_S3=1 to use S3 azure:// Please compile with DMLC_USE_AZURE=1 to use Azure unknown filesystem protocol stdin Check failed: part < nsplit invalid input parameter for InputSplit::Create indexed_recordio need to pass index file to use IndexedRecordIO recordio unknown input split type .split .part /Users/runner/work/ml-builds/ml-builds/xgboost/dmlc-core/src/io/uri_spec.h name_cache.size() == 1U only one `#` is allowed in file path for cachefile specification Check failed: std::getline(is, kv.first, '=') Invalid uri argument format for key in arg Check failed: std::getline(is, kv.second) for value in arg name_args.size() == 1U /Users/runner/work/ml-builds/ml-builds/xgboost/dmlc-core/src/io/single_file_split.h Check failed: fp_ != NULL SingleFileSplit: fail to open Check failed: part_index == 0 && num_parts == 1 InputSplit do not support write /Users/runner/work/ml-builds/ml-builds/xgboost/dmlc-core/src/io/cached_input_split.h Check failed: nread == sizeof(size) has invalid cache file format Check failed: fi_->Read(p->begin, size) == size BeforeFirst is not supported Check failed: this->InitCachedIter() Failed to initialize CachedIter ResetPartition is not supported in CachedInputSplit /Users/runner/work/ml-builds/ml-builds/xgboost/dmlc-core/src/io/line_split.cc Check failed: begin != end /Users/runner/work/ml-builds/ml-builds/xgboost/dmlc-core/src/io/recordio_split.cc Check failed: fi->Read(&lrec, sizeof(lrec)) != 0 invalid record io format (reinterpret_cast<size_t>(begin) & 3UL) == 0U (reinterpret_cast<size_t>(end) & 3UL) == 0U Check failed: p >= pbegin + 2 Check failed: chunk->begin + 2 * sizeof(uint32_t) <= chunk->end Invalid RecordIO Format (reinterpret_cast<size_t>(chunk->begin) & 3UL) == 0U (reinterpret_cast<size_t>(chunk->end) & 3UL) == 0U Check failed: chunk->begin <= chunk->end Check failed: cflag == 1U Check failed: p[0] == RecordIOWriter::kMagic /Users/runner/work/ml-builds/ml-builds/xgboost/dmlc-core/src/io/indexed_recordio_split.cc expanded_list.size() == 1ul IndexedRecordIOSplitter does not support multiple index files /Users/runner/work/ml-builds/ml-builds/xgboost/dmlc-core/src/io/input_split_base.cc Check failed: files_[i].size % align_bytes == 0 file do not align by bytes Check failed: offset_end_ >file_offset_[file_ptr_end_] Check failed: file_ptr_end_ < files_.size() bad regex This could due to compiler version, g++-4.9 is needed files_.size() != 0U Cannot find any files that matches the URI pattern curr= ,begin= ,end= ,fileptr= ,fileoffset= offset[ file offset not calculated correctly C /Users/runner/work/ml-builds/ml-builds/xgboost/dmlc-core/src/io/filesys.cc Check failed: !IsSymlink(info.path.name) Symlink not supported in TemporaryDirectory Couldn't remove file Successfully deleted temporary directory ~TemporaryDirectory(): Could not remove temporary directory /Users/runner/work/ml-builds/ml-builds/xgboost/dmlc-core/include/dmlc/filesystem.h lstat(path.c_str(), &sb) == 0 dmlc::TemporaryDirectory::IsSymlink(): Unable to read file attributes /Users/runner/work/ml-builds/ml-builds/xgboost/dmlc-core/src/io/local_filesys.cc LocalFileSystem.GetPathInfo: detected symlink error: LocalFileSystem.GetPathInfo: LocalFileSystem.ListDirectory .. stdout wb Check failed: allow_null LocalFileSystem::Open " ": Check failed: std::fwrite(ptr, 1, size, fp_) == size FileStream.Write incomplete Check failed: !std::fseek(fp_, static_cast<long>(pos), SEEK_SET) % T T T T T T T T T T T T T T T T T T T H `@ d pN U
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RK ;St16initializer_listIS3_E ; S4_ ;NSt3__16vectorIS3_NS5_9allocatorIS3_EEEE ; ExtendERKS4_ <ResizeEmS3_ < HostCanWriteEv <DeviceAccessEv < C =D >aSEOS1_ ?1 @8HostSpanEv B4 C6 D 2E =1E > mii >St16initializer_listIiEi >RKNSt3__16vectorIiNS2_9allocatorIiEEEEi >OS1_ ? mii >St16initializer_listIiEi >RKNSt3__16vectorIiNS2_9allocatorIiEEEEi >OS1_ ? 2Ev ?1Ev ? 5EmptyEv ?4SizeEv ?9 ?1 @8HostSpanEv B ̀ DeviceIdxEv @SetDeviceEi D 0 @3DevicePointerEv B1HostPointerEv B DeviceSpanEv @HostVectorEv B 5Const A0 A8ConstDevicePointerEv B3 B6ConstHostPointerEv B1Host B2 D4DeviceCanWriteEv D DeviceSpanEv AHostVectorEv B DeviceSpanEv AHostVectorEv B Device BConstHostSpanEv B PointerEv BCanReadEv D ā ܁ PointerEv CCanReadEv D FillEi CCopyE C RK CSt16initializer_listIiE D S1_ DNSt3__16vectorIiNS2_9allocatorIiEEEE D̂ ą ExtendERKS1_ DResizeEmi E HostCanWriteEv DDeviceAccessEv DȌ Ќ ، C ED GaSEOS1_ G1 H8HostSpanEv J4 K6 L 2E E1E F mhi FSt16initializer_listIhEi FRKNSt3__16vectorIhNS2_9allocatorIhEEEEi GOS1_ Gč mhi FSt16initializer_listIhEi FRKNSt3__16vectorIhNS2_9allocatorIhEEEEi GOS1_ G 2Ev G1Ev G ܕ ȗ 5EmptyEv G4SizeEv G9 G1 H8HostSpanEv JИ DeviceIdxEv HSetDeviceEi M 0 H3DevicePointerEv J1HostPointerEv J DeviceSpanEv HHostVectorEv J 5Const I0 I8ConstDevicePointerEv J3 J6ConstHostPointerEv K1Host K2 L4DeviceCanWriteEv M DeviceSpanEv IHostVectorEv K DeviceSpanEv JHostVectorEv J Device JConstHostSpanEv J PointerEv JCanReadEv L ԙ PointerEv KCanReadEv L FillEh KCopyE K RK KSt16initializer_listIhE L S1_ LNSt3__16vectorIhNS2_9allocatorIhEEEE LК ExtendERKS1_ LResizeEmh M HostCanWriteEv LDeviceAccessEv M C MD OaSEOS2_ O1 P8HostSpanEv S4 S6 T 2E M1E N mS1_i NSt16initializer_listIS1_Ei ORKNSt3__16vectorIS1_NS3_9allocatorIS1_EEEEi OOS2_ O mS1_i OSt16initializer_listIS1_Ei ORKNSt3__16vectorIS1_NS3_9allocatorIS1_EEEEi OOS2_ O ة 2Ev O1Ev OĮ ̯ 5EmptyEv P4SizeEv P9 P1 Q8HostSpanEv S DeviceIdxEv PSetDeviceEi U 0 P3DevicePointerEv R1HostPointerEv R DeviceSpanEv QHostVectorEv S 5Const Q0 R8ConstDevicePointerEv R3 R6ConstHostPointerEv S1Host S2 T4DeviceCanWriteEv U DeviceSpanEv RHostVectorEv S DeviceSpanEv RHostVectorEv S Ȳ Device RConstHostSpanEv S PointerEv RCanReadEv Uв ز PointerEv SCanReadEv Tij FillES1_ SCopyE Sг RK TSt16initializer_listIS1_E T S2_ TNSt3__16vectorIS1_NS3_9allocatorIS1_EEEE T Թ ExtendERKS2_ TResizeEmS1_ U HostCanWriteEv UDeviceAccessEv U Ŀ ȿ C UD WaSEOS2_ X1 X8HostSpanEv [4 [6 \ 2E U1E V mS1_i VSt16initializer_listIS1_Ei WRKNSt3__16vectorIS1_NS3_9allocatorIS1_EEEEi WOS2_ W mS1_i WSt16initializer_listIS1_Ei WRKNSt3__16vectorIS1_NS3_9allocatorIS1_EEEEi WOS2_ W 2Ev W1Ev W 5EmptyEv X4SizeEv X9 X1 Y8HostSpanEv [ DeviceIdxEv XSetDeviceEi ] 0 Y3DevicePointerEv Z1HostPointerEv [ DeviceSpanEv YHostVectorEv [ 5Const Z0 Z8ConstDevicePointerEv Z3 Z6ConstHostPointerEv [1Host [2 ]4DeviceCanWriteEv ] DeviceSpanEv ZHostVectorEv [ DeviceSpanEv ZHostVectorEv [ Device [ConstHostSpanEv [ PointerEv [CanReadEv ] PointerEv [CanReadEv ] FillES1_ \CopyE \ RK \St16initializer_listIS1_E \ S2_ \NSt3__16vectorIS1_NS3_9allocatorIS1_EEEE \ ExtendERKS2_ ]ResizeEmS1_ ] HostCanWriteEv ]DeviceAccessEv ] C ^D _aSEOS1_ `1 `8HostSpanEv c4 d6 e 2E ^1E _ myi ^St16initializer_listIyEi _RKNSt3__16vectorIyNS2_9allocatorIyEEEEi _OS1_ ` myi _St16initializer_listIyEi _RKNSt3__16vectorIyNS2_9allocatorIyEEEEi _OS1_ ` 2Ev `1Ev ` 5EmptyEv `4SizeEv `9 `1 a8HostSpanEv c DeviceIdxEv `SetDeviceEi e 0 a3DevicePointerEv b1HostPointerEv c DeviceSpanEv aHostVectorEv c 5Const b0 b8ConstDevicePointerEv c3 c6ConstHostPointerEv c1Host c2 e4DeviceCanWriteEv e DeviceSpanEv bHostVectorEv c DeviceSpanEv bHostVectorEv c Device cConstHostSpanEv c PointerEv cCanReadEv e PointerEv dCanReadEv e FillEy dCopyE d RK dSt16initializer_listIyE e S1_ dNSt3__16vectorIyNS2_9allocatorIyEEEE e ExtendERKS1_ eResizeEmy e HostCanWriteEv eDeviceAccessEv e C fD haSEOS1_ h1 i8HostSpanEv k4 l6 m 2E f1E g mji gSt16initializer_listIjEi gRKNSt3__16vectorIjNS2_9allocatorIjEEEEi gOS1_ h mji gSt16initializer_listIjEi gRKNSt3__16vectorIjNS2_9allocatorIjEEEEi hOS1_ h 2Ev h1Ev h 5EmptyEv h4SizeEv h9 h1 i8HostSpanEv k DeviceIdxEv iSetDeviceEi n 0 i3DevicePointerEv k1HostPointerEv k DeviceSpanEv iHostVectorEv k 5Const j0 j8ConstDevicePointerEv k3 k6ConstHostPointerEv k1Host l2 m4DeviceCanWriteEv m DeviceSpanEv jHostVectorEv l DeviceSpanEv kHostVectorEv k Device kConstHostSpanEv k PointerEv kCanReadEv m PointerEv lCanReadEv m FillEj lCopyE l RK lSt16initializer_listIjE m S1_ mNSt3__16vectorIjNS2_9allocatorIjEEEE m
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- mS2_i pSt16initializer_listIS2_Ei pRKNSt3__16vectorIS2_NS4_9allocatorIS2_EEEEi pOS3_ p
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- Json SparsePage ExtendPathEPNS_11PathElementEjffi UnwindPathEPNS_11PathElementEjj Writer Object String Number ͏Reader 4SaveENS_4JsonE 5VisitEPKNS_ 9JsonArrayE 1 Ă8JsonNullE 0Json 1Json ObjectE NumberE StringE IntegerE BooleanE ش غ DummyJsonObjectEv LoadFeatureTypeERKNSt3__16vectorINS0_12basic_stringIcNS0_11char_traitsIcEENS0_9allocatorIcEEEENS5_IS7_EEEEPNS1_INS_11FeatureTypeENS5_ISC_EEEE ٺGradientBooster6CreateERKNSt3__112basic_stringIcNS1_11char_traitsIcEENS1_9allocatorIcEEEEPKNS_16GenericParameterEPKNS_17LearnerModelParamE C ixE aSERKNS_5ValueE 4SaveEPNS_10JsonWriterE 2EO dž1EO ׇ S0_ чNSt3__13mapINS1_12basic_stringIcNS1_11char_traitsIcEENS1_9allocatorIcEEEENS_4JsonENS1_4lessIS8_EENS6_INS1_4pairIKS8_S9_EEEEEE S0_ NSt3__13mapINS1_12basic_stringIcNS1_11char_traitsIcEENS1_9allocatorIcEEEENS_4JsonENS1_4lessIS8_EENS6_INS1_4pairIKS8_S9_EEEEEE RKNSt3__112basic_stringIcNS1_11char_traitsIcEENS1_9allocatorIcEEEE i Ɖ Json SparsePage12GetTransposeEi ObjecteqERKNS_5ValueE StringeqERKNS_5ValueE NumbereqERKNS_5ValueE ݐReader5ErrorENSt3__112basic_stringIcNS1_11char_traitsIcEENS1_9allocatorIcEEEE ixE ۋaSERKNS_5ValueE 4SaveEPNS_10JsonWriterE RKNSt3__112basic_stringIcNS1_11char_traitsIcEENS1_9allocatorIcEEEE i JsonArray GPUMetric15CreateGPUMetricERKNSt3__112basic_stringIcNS1_11char_traitsIcEENS1_9allocatorIcEEEEPKNS_16GenericParameterE predictor Predictor TreeParam11__MANAGER__Ev C ixE aSERKNS_5ValueE 4SaveEPNS_10JsonWriterE Ǐ 2EOS0_ ֎1EOS0_ RKNSt3__112basic_stringIcNS1_11char_traitsIcEENS1_9allocatorIcEEEE i ixE aSERKNS_5ValueE 4SaveEPNS_10JsonWriterE RKNSt3__112basic_stringIcNS1_11char_traitsIcEENS1_9allocatorIcEEEE ѐi א Ѝ Json EllpackPage ȽObjFunction6CreateERKNSt3__112basic_stringIcNS1_11char_traitsIcEENS1_9allocatorIcEEEEPKNS_16GenericParameterE TreeUpdater6CreateERKNSt3__112basic_stringIcNS1_11char_traitsIcEENS1_9allocatorIcEEEEPKNS_16GenericParameterE LearnerImpl14kRandSeedMagicE Integer Boolean Η ixE ٓaSERKNS_5ValueE 4SaveEPNS_10JsonWriterE RKNSt3__112basic_stringIcNS1_11char_traitsIcEENS1_9allocatorIcEEEE i Json ҔEllpackPage4SizeEv IntegereqERKNS_5ValueE BooleaneqERKNS_5ValueE ޘ JsonNull ParseStrERKNSt3__112basic_stringIcNS0_11char_traitsIcEENS0_9allocatorIcEEEE MetaInfo ixE aSERKNS_5ValueE 4SaveEPNS_10JsonWriterE ȗ RKNSt3__112basic_stringIcNS1_11char_traitsIcEENS1_9allocatorIcEEEE i ԡ JsonNulleqERKNS_5ValueE MetaInfo Ӹ ixE aSERKNS_5ValueE 4SaveEPNS_10JsonWriterE RKNSt3__112basic_stringIcNS1_11char_traitsIcEENS1_9allocatorIcEEEE Ҙi ؘ Ĵ 5ParseEv 1 4LoadEv 9ParseNullEv 0 ۙ1Parse 2ParseBooleanEv ٚ3kMaxNumLengthE SkipSpacesEv ParseArrayEv ǚ StringEv ObjectEv ͚NumberEv Ӛ
Json data tree 4 aSERKS0_ LoadE DumpES0_PNSt3__112basic_stringIcNS1_11char_traitsIcEENS1_9allocatorIcEEEE NS_10StringViewE PNS_10JsonReaderE
C 1 Ȟ9AllReduceEPNSt3__16vectorINS0_22QuantileSketchTemplateIffNS0_9WQSummaryIffEEE16SummaryContainerENS2_9allocatorIS8_EEEEPNS3_IiNS9_IiEEEE 8MakeCutsEPNS0_13HistogramCutsE 2ENSt3__16vectorImNS2_9allocatorImEEEEib 1ENSt3__16vectorImNS2_9allocatorImEEEEib
4CalcColumnSizeERKNS_10SparsePageEjm 1 6GatherSketchInfoERKNSt3__16vectorINS0_22QuantileSketchTemplateIffNS0_9WQSummaryIffEEE16SummaryContainerENS2_9allocatorIS8_EEEEPNS3_ImNS9_ImEEEESG_PNS3_INS6_5EntryENS9_ISH_EEEE
LoadBalanceERKNS_10SparsePageEjm PushRowPageERKNS_10SparsePageERKNS_8MetaInfoE
2 ѡ1 6engine 5c_api9All op7ReducerINS0_ 4SerializeReducerFuncImplIN7xgboost6common22QuantileSketchTemplateIffNS2_10WXQSummaryIffEEE16SummaryContainerEEEvPKvPviRKN3MPI8DatatypeE 2SerializeReduceClosureIN7xgboost6common22QuantileSketchTemplateIffNS2_10WXQSummaryIffEEE16SummaryContainerEE6InvokeEPv 3 5BitORE SumE M mEEvPKvPviRKN3MPI8DatatypeE fEEvPKvPviRKN3MPI8DatatypeE dEEvPKvPviRKN3MPI8DatatypeE cEEvPKvPviRKN3MPI8DatatypeE hEEvPKvPviRKN3MPI8DatatypeE iEEvPKvPviRKN3MPI8DatatypeE jEEvPKvPviRKN3MPI8DatatypeE lEEvPKvPviRKN3MPI8DatatypeE axE inE mEEvPKvPviRKN3MPI8DatatypeE yEEvPKvPviRKN3MPI8DatatypeE ½jEEvPKvPviRKN3MPI8DatatypeE fEEvPKvPviRKN3MPI8DatatypeE cEEvPKvPviRKN3MPI8DatatypeE hEEvPKvPviRKN3MPI8DatatypeE iEEvPKvPviRKN3MPI8DatatypeE lEEvPKvPviRKN3MPI8DatatypeE dEEvPKvPviRKN3MPI8DatatypeE 5StartERKNSt3__112basic_stringIcNS2_11char_traitsIcEENS2_9allocatorIcEEEE 4StopERKNSt3__112basic_stringIcNS2_11char_traitsIcEENS2_9allocatorIcEEEE 21CollectFromOtherRanksEv 15PrintStatisticsERKNSt3__13mapINS2_12basic_stringIcNS2_11char_traitsIcEENS2_9allocatorIcEEEENS2_4pairImmEENS2_4lessIS9_EENS7_INSA_IKS9_SB_EEEEEE 5PrintEv « ؈ Version DMatrix ѯLearner RegTree 4 6StringERKNSt3__15tupleIJiiiEEE ح8kInvalidE LoadE S RKNS_4JsonE PN4dmlc6StreamE a elfEv ̭ veEPN meERKNSt3__15tupleIJiiiEEE ޭ S_4JsonE ƭ4dmlc6StreamE ҭ 7xgboost S_16ParserFactoryRegI 4data19SparsePageFormatRegINS1_ ˮ1 9MetricRegEE3GetEv 1 7CSCPageEEEE3GetEv 0SparsePageEEEE3GetEv 3SortedCSCPageEEEE3GetEv ů1EllpackPageEEEE3GetEv ˯ 6CreateI D 4LoadERKNSt3__112basic_stringIcNS1_11char_traitsIcEENS1_9allocatorIcEEEEbbS9_m PvS2_FvS2_EFiS2_EEEPS0_T_T0_PT1_PT2_fii NS_4data1 2DenseAdapterEEEPS0_PT_fiRKNSt3__112basic_stringIcNS7_11char_traitsIcEENS7_9allocatorIcEEEEm 0CS 6DataTableAdapterEEEPS0_PT_fiRKNSt3__112basic_stringIcNS7_11char_traitsIcEENS7_9allocatorIcEEEEm 1FileAdapterEEEPS0_PT_fiRKNSt3__112basic_stringIcNS7_11char_traitsIcEENS7_9allocatorIcEEEEm 5IteratorAdapterIPvFiS4_PFiS4_15XGBoostBatchCSRES4_ES5_EEEEPS0_PT_fiRKNSt3__112basic_stringIcNSD_11char_traitsIcEENSD_9allocatorIcEEEEm RAdapterEEEPS0_PT_fiRKNSt3__112basic_stringIcNS7_11char_traitsIcEENS7_9allocatorIcEEEEm CAdapterEEEPS0_PT_fiRKNSt3__112basic_stringIcNS7_11char_traitsIcEENS7_9allocatorIcEEEEm Ԁ 4Push 7PushCSCERKS0_ INS_4data ERKS0_ 1 21DataTableAdapterBatchEEEyRKT_fi 7DenseAdapterBatchEEEyRKT_fi 5CS 6FileAdapterBatchEEEyRKT_fi RAdapterBatchEEEyRKT_fi CAdapterBatchEEEyRKT_fi 5ClearEv 1 ߺ7SetInfoEPKc 6ExtendERKS0_b 9kNumFieldE 1 ¹5SliceENS_6common4SpanIKiLm18446744073709551615EEE 7GetInfoEPKcPyNS_8DataTypeEPPKv 8ValidateEi 0SaveBinaryEPN4dmlc6StreamE Ӻ4GetFeatureInfoEPKcPNSt3__16vectorINS3_12basic_stringIcNS3_11char_traitsIcEENS3_9allocatorIcEEEENS8_ISA_EEEE 0LoadBinaryEPN4dmlc6StreamE 4SetFeatureInfoEPKcPS2_y PKvNS_8DataTypeEm RKNSt3__112basic_stringIcNS3_11char_traitsIcEENS3_9allocatorIcEEEE ȫ DMatrix14GetThreadLocalEv Learner19AllowLazyCheckPointEv RegTree 2Ev 1Ev 0Ev Խ C D 12SetBaseRowIdEm 2E 1E v PNS_7DMatrixERKNS_10BatchParamE ־ v оPNS_7DMatrixERKNS_10BatchParamE ܾ 2Ev 1Ev Ģ ܣ 1 49__dmlc_registry_file_tag_sparse_page_raw_format__Ev 8DataPool 7 3SimpleDMatrix EllpackPageSourceC SparsePageDMatrix 2EPNS_7DMatrixERKNSt3__112basic_stringIcNS4_11char_traitsIcEENS4_9allocatorIcEEEERKNS_10BatchParamE 1EPNS_7DMatrixERKNSt3__112basic_stringIcNS4_11char_traitsIcEENS4_9allocatorIcEEEERKNS_10BatchParamE C 4InfoEv 5SliceENS_6common4SpanIKiLm18446744073709551615EEE 1 22GetSortedColumnBatchesEv 2 1 INS0_1 EPN4dmlc6StreamE 2DenseAdapterEEEPT_fi 0CS 6DataTableAdapterEEEPT_fi 1FileAdapterEEEPT_fi 5IteratorAdapterIPvFiS4_PFiS4_15XGBoostBatchCSRES4_ES5_EEEEPT_fi INS0_1 EPN4dmlc6StreamE 2DenseAdapterEEEPT_fi 0CS 6DataTableAdapterEEEPT_fi 1FileAdapterEEEPT_fi 5IteratorAdapterIPvFiS4_PFiS4_15XGBoostBatchCSRES4_ES5_EEEEPT_fi RAdapterEEEPT_fi CAdapterEEEPT_fi RAdapterEEEPT_fi CAdapterEEEPT_fi data tree17QuantileHistMaker7BuilderI 1 8DataPool5SliceENSt3__110shared_ptrINS_10SparsePageEEEmmm 3SimpleDMatrix4InfoEv 7SparsePageDMatrix4InfoEv 3GetRowBatchesEv 6GetColumnBatchesEv 7GetEllpackBatchesERKNS_10BatchParamE 5SaveToLocalFileERKNSt3__112basic_stringIcNS2_11char_traitsIcEENS2_9allocatorIcEEEE ā ̘ 4InfoEv 1 22GetSortedColumnBatchesEv 3GetRowBatchesEv 6GetColumnBatchesEv 7GetEllpackBatchesERKNS_10BatchParamE 14SplitWritePageEv 8FinalizeEv ܇ gbm obj 2FeatureInteractionConstraintHost 3 1 28DeprecatedGBLinearModelParam11__MANAGER__Ev 6GBTree 5__dmlc_registry_file_tag_gblinear__Ev 3__dmlc_registry_file_tag_gbtree__Ev Đ 8GBLinearTrainParam11__MANAGER__Ev 3GBLinearModel9LoadModelERKNS_4JsonE 6GBTree 4DartTrainParam11__MANAGER__Ev 1GBTreeModel ̐ 1 6GBTree 3GBLinearModel9SaveModelEPNS_4JsonE 1GBTreeModel 8GradientBoosterRegEE3GetEv 6LinearUpdaterRegEE3GetEv 2 4 0TreeGenRegEE3GetEv 9 1 2 7DoBoostEPNS_7DMatrixEPNS_16HostDeviceVectorINS_6detail20GradientPairInternalIfEEEEPNS_20PredictionCacheEntryE ConfigureERKNSt3__16vectorINS2_4pairINS2_12basic_stringIcNS2_11char_traitsIcEENS2_9allocatorIcEEEESA_EENS8_ISB_EEEE LoadModelERKNS_4JsonE 7ConfigureUpdatersEv 1 3BoostNewTreesEPNS_16HostDeviceVectorINS_6detail20GradientPairInternalIfEEEEPNS_7DMatrixEiPNSt3__16vectorINSA_10unique_ptrINS_7RegTreeENSA_14default_deleteISD_EEEENSA_9allocatorISG_EEEE 0LoadConfigERKNS_4JsonE 2PredictBatchEPNS_7DMatrixEPNS_20PredictionCacheEntryEbj InitUpdaterERKNSt3__16vectorINS2_4pairINS2_12basic_stringIcNS2_11char_traitsIcEENS2_9allocatorIcEEEESA_EENS8_ISB_EEEE CommitModelEONSt3__16vectorINS3_INS2_10unique_ptrINS_7RegTreeENS2_14default_deleteIS5_EEEENS2_9allocatorIS8_EEEENS9_ISB_EEEEPNS_7DMatrixEPNS_20PredictionCacheEntryE 2ConfigureWithKnownDataERKNSt3__16vectorINS2_4pairINS2_12basic_stringIcNS2_11char_traitsIcEENS2_9allocatorIcEEEESA_EENS8_ISB_EEEEPNS_7DMatrixE 6PerformTreeMethodHeuristicEPNS_7DMatrixE ԃ! Đ! ! ! hn SN VN IN ̄ 8_N 16_N7xgboost7LearnerD 7xgboost K7xgboost3gbm6GBTree10SaveConfigEPNS_4JsonE 3gbm6GBTree10LoadConfigERKNS_4JsonE 7LearnerD ! 1 9SaveModelEPNS_4JsonE 5SliceEiiiPNS_15GradientBoosterEPb 0SaveConfigEPNS_4JsonE 2GetPredictorEPKNS_16HostDeviceVectorIfEEPNS_7DMatrixE ! ! ! ! ! " " ModelParam11__MANAGER__Ev TrainParam11__MANAGER__Ev ̌" " ܐ" 4SaveEPN4dmlc6StreamE 9SaveModelEPNS_4JsonE % 4LoadEPN4dmlc6StreamE 9LoadModelERKNS_4JsonE Ȕ% ؝% ȶ% % D 6CreateERKNSt3__16vectorINS1_10shared_ptrINS_7DMatrixEEENS1_9allocatorIS5_EEEE 2Ev 1Ev 0Ev % % 1Ev 0Ev % 1Ev 0Ev % % % % ModelParamC TrainParam11__MANAGER__Ev 2ERKNS_23LearnerModelParamLegacyEf 1ERKNS_23LearnerModelParamLegacyEf % % 3LearnerModelParamLegacy11__MANAGER__Ev 6ParseInteractionConstraintERKNSt3__112basic_stringIcNS0_11char_traitsIcEENS0_9allocatorIcEEEEPNS0_6vectorINS9_IjNS4_IjEEEENS4_ISB_EEEE 0LearnerConfiguration11kEvalMetricE ʹ % % 1 6kCpuIdE 1__MANAGER__Ev 4ConfigureGpuIdEb 2kDefaultSeedE % % % ) ܶ+ LinearUpdater6CreateERKNSt3__112basic_stringIcNS1_11char_traitsIcEENS1_9allocatorIcEEEEPKNS_16GenericParameterE ConsoleLogger Tr GraphvizParam11__MANAGER__Ev + 1 4 6LinearTrainParam11__MANAGER__Ev 5CoordinateParam11__MANAGER__Ev + + 5__dmlc_registry_file_tag_updater_coordinate__Ev 2__dmlc_registry_file_tag_updater_shotgun__Ev + Ќ- 6CustomLogMessage3LogERKNSt3__112basic_stringIcNS1_11char_traitsIcEENS1_9allocatorIcEEEE 2 0 8TemporaryDirectory15RecursiveDeleteERKNSt3__112basic_stringIcNS1_11char_traitsIcEENS1_9allocatorIcEEEE - D 9 1 C 6param_E ٴ 2Ev 1Ev - ShouldLogENS0_12LogVerbosityE ConfigureERKNSt3__16vectorINS1_4pairINS1_12basic_stringIcNS1_11char_traitsIcEENS1_9allocatorIcEEEES9_EENS7_ISA_EEEE - - ackerLoggerD eeGenerator 2Ev 1Ev - - - - 6DefaultVerbosityEv 5GlobalVerbosityEv 7global_verbosity_E Ӵ - - 2E 1E NS0_12LogVerbosityE RKNSt3__112basic_stringIcNS1_11char_traitsIcEENS1_9allocatorIcEEEEiNS0_12LogVerbosityE - NS0_12LogVerbosityE RKNSt3__112basic_stringIcNS1_11char_traitsIcEENS1_9allocatorIcEEEEiNS0_12LogVerbosityE - - - 4 3 2 ߴ 5__ 4__dmlc_registry_file_tag_multiclass_metric__Ev 2__dmlc_registry_file_tag_survival_metric__Ev dmlc_registry_file_tag_elementwise_metric__Ev make_MetricReg_IntervalRegressionAccuracy__E ۸ - - / / / MetricGPURegEE3GetEv PredictorRegEE3GetEv / / 8__dmlc_registry_file_tag_rank_metric__Ev 5__make_MetricReg_PossionNegLoglik__E 2__make_MetricReg_GammaDeviance__E 1__make_MetricReg_ 3__make_MetricReg_TweedieNLogLik__E / 2 3 41__dmlc_registry_file_tag_ 22 1 9ListEntry7CmpPredERKS1_S3_ 4__dmlc_registry_file_tag_aft_obj__Ev 6__dmlc_registry_file_tag_hinge_obj__Ev 5__dmlc_registry_file_tag_rank_obj__Ev М3 4 multiclass_obj__Ev regression_obj__Ev 4 SoftmaxMultiClassParam11__MANAGER__Ev PoissonRegressionParam11__MANAGER__Ev TweedieRegressionParam11__MANAGER__Ev 4 ObjFunctionRegEE3GetEv TreeUpdaterRegEE3GetEv 5 5 5 5LambdaRankParam11__MANAGER__Ev 2RegLossParam11__MANAGER__Ev 5 5 Ē7 ̒7 7 7 40__dmlc_registry_file_tag_cpu_predictor__Ev 9PredValueERKNS_6common4SpanIKNS_5EntryELm18446744073709551615EEERKNSt3__16vectorINS8_10unique_ptrINS_7RegTreeENS8_14default_deleteISB_EEEENS8_9allocatorISE_EEEERKNS9_IiNSF_IiEEEEiPNSB_4FVecEjj : : < 19ClearExpiredEntriesEv 5 9ContainerEv ĭ< CacheENSt3__110shared_ptrINS_7DMatrixEEEi EntryEPNS_7DMatrixE < < ܻ< 9ConfigureERKNSt3__16vectorINS1_4pairINS1_12basic_stringIcNS1_11char_traitsIcEENS1_9allocatorIcEEEES9_EENS7_ISA_EEEE 6CreateERKNSt3__112basic_stringIcNS1_11char_traitsIcEENS1_9allocatorIcEEEEPKNS_16GenericParameterE < < 9 5ResetEv ConfigureERKNS_4tree10TrainParamEj SplitImplEijii < < < = = Ԧ= 1 4 22CPUHistMakerTrainParam11__MANAGER__Ev 39__dmlc_registry_file_tag_updater_sync__Ev 0TrainParam11__MANAGER__Ev 8ColMakerTrainParam11__MANAGER__Ev 7QuantileHistMaker = = 6CreateERKNSt3__112basic_stringIcNS1_11char_traitsIcEENS1_9allocatorIcEEEERKNS_10FeatureMapEb 5MatchERKNSt3__112basic_stringIcNS1_11char_traitsIcEENS1_9allocatorIcEEEERKNS1_3mapIS7_S7_NS1_4lessIS7_EENS5_INS1_4pairIS8_S7_EEEEEE = = 9 5EqualERKS0_ ߀1 4SaveEPN4dmlc6StreamE 2 Ń8TreeShapERKNS0_4FVecEPfjjPNS_11PathElementEffiijf DumpModelERKNS_10FeatureMapEbNSt3__112basic_stringIcNS4_11char_traitsIcEENS4_9allocatorIcEEEE ـSaveModelEPNS_4JsonE ӄ = = 2GetNumLeavesEv 6GetNumSplitNodesEv = = 1 4LoadEPN4dmlc6StreamE 20LoadCategoricalSplitERKNS_4JsonE 9LoadModelERKNS_4JsonE ̈́5kRootE 0ExpandNodeEijfbfffffffi Ă7 ʂ8FillNodeMeanValuesEv ل = ExpandCategoricalEijNS_6common4SpanIjLm18446744073709551615EEEbfffffff FillNodeMeanValueEi ߄ = = = = 0SaveCategoricalSplitEPNS_4JsonE DŽ8CalculateContributionsApproxERKNS0_4FVecEPf 2CalculateContributionsERKNS0_4FVecEPfij > > > ? ? д? ? ? ? ? ? A D D 3__dmlc_registry_file_tag_updater_colmaker__Ev 4__dmlc_registry_file_tag_updater_histmaker__Ev 0__dmlc_registry_file_tag_updater_prune__Ev 8__dmlc_registry_file_tag_updater_quantile_hist__Ev 2__dmlc_registry_file_tag_updater_refresh__Ev D D G 5ReducerSafeImplIN7xgboost ֈ2InvokeLambdaEPv 6ReducerAlignImplIN7xgboost6detail20GradientPairInternalIfEEXadL_ZNS4_6ReduceERS4_RKS4_EEEEvPKvPviRKN3MPI8DatatypeE 4tree9GradStatsEXadL_ZNS3_6ReduceERS3_RKS3_EEEEvPKvPviRKN3MPI8DatatypeE 6detail20GradientPairInternalIdEEXadL_ZNS4_6ReduceERS4_RKS4_EEEEvPKvPviRKN3MPI8DatatypeE G G H I I J 7BuilderI 9ConfigureERKNSt3__16vectorINS2_4pairINS2_12basic_stringIcNS2_11char_traitsIcEENS2_9allocatorIcEEEESA_EENS8_ISB_EEEE 6UpdateEPNS_16HostDeviceVectorINS_6detail20GradientPairInternalIfEEEEPNS_7DMatrixERKNSt3__16vectorIPNS_7RegTreeENSA_9allocatorISD_EEEE 21UpdatePredictionCacheEPKNS_7DMatrixEPNS_16HostDeviceVectorIfEE fE dE C 6UpdateERKNS_6common16GHistIndexMatrixERKNS4_21GHistIndexBlockMatrixERKNS4_12ColumnMatrixEPNS_16HostDeviceVectorINS_6detail20GradientPairInternalIfEEEEPNS_7DMatrixEPNS_7RegTreeE 8InitDataERKNS_6common16GHistIndexMatrixERKNSt3__16vectorINS_6detail20GradientPairInternalIfEENS8_9allocatorISC_EEEERKNS_7DMatrixERKNS_7RegTreeE 1 9 2 2ERKNS0_10TrainParamENSt3__110unique_ptrINS_11TreeUpdaterENS7_14default_deleteIS9_EEEENS_32FeatureInteractionConstraintHostEPKNS_7DMatrixE 1ERKNS0_10TrainParamENSt3__110unique_ptrINS_11TreeUpdaterENS7_14default_deleteIS9_EEEENS_32FeatureInteractionConstraintHostEPKNS_7DMatrixE J J J J 9 6S 1 2InitSamplingERKNSt3__16vectorINS_6detail20GradientPairInternalIfEENS4_9allocatorIS8_EEEERKNS_7DMatrixEPNS5_ImNS9_ImEEEE 4 0ApplySplitENSt3__16vectorINS3_11ExpandEntryENS4_9allocatorIS6_EEEERKNS_6common16GHistIndexMatrixERKNSA_12ColumnMatrixERKNSA_14HistCollectionIfEEPNS_7RegTreeE 7AddSplitsToRowSetERKNSt3__16vectorINS3_11ExpandEntryENS4_9allocatorIS6_EEEEPNS_7RegTreeE 3SplitSiblingsERKNSt3__16vectorINS3_11ExpandEntryENS4_9allocatorIS6_EEEEPS9_SC_PNS_7RegTreeE Ш5 ExpandWith SetHistSynchronizerEPNS0_16HistSynchronizerIfEE FindSplitConditionsERKNSt3__16vectorINS3_11ExpandEntryENS4_9allocatorIS6_EEEERKNS_7RegTreeERKNS_6common16GHistIndexMatrixEPNS5_IiNS7_IiEEEE LossGuideERKNS_6common16GHistIndexMatrixERKNS4_21GHistIndexBlockMatrixERKNS4_12ColumnMatrixEPNS_7DMatrixEPNS_7RegTreeERKNSt3__16vectorINS_6detail20GradientPairInternalIfEENSI_9allocatorISM_EEEE DepthWiseERKNS_6common16GHistIndexMatrixERKNS4_21GHistIndexBlockMatrixERKNS4_12ColumnMatrixEPNS_7DMatrixEPNS_7RegTreeERKNSt3__16vectorINS_6detail20GradientPairInternalIfEENSI_9allocatorISM_EEEE J J BuildHistERKNSt3__16vectorINS_6detail20GradientPairInternalIfEENS4_9allocatorIS8_EEEENS_6common16RowSetCollection4ElemERKNSE_16GHistIndexMatrixERKNSE_21GHistIndexBlockMatrixENSE_4SpanIS8_Lm18446744073709551615EEE LossGuideENS3_11ExpandEntryES4_ J ubtractionTrickENS_6common4SpanINS_6detail20GradientPairInternalIfEELm18446744073709551615EEES9_S9_ etHistRowsAdderEPNS0_13HistRowsAdderIfEE J 1UpdatePredictionCacheEPKNS_7DMatrixEPNS_16HostDeviceVectorIfEE 6SplitContainsMissingValuesENS0_9GradStatsERKNS1_9NodeEntryE ʨ0BuildLocalHistogramsERKNS_6common16GHistIndexMatrixERKNS4_21GHistIndexBlockMatrixEPNS_7RegTreeERKNSt3__16vectorINS_6detail20GradientPairInternalIfEENSD_9allocatorISH_EEEE ֨2EvaluateAndApplySplitsERKNS_6common16GHistIndexMatrixERKNS4_12ColumnMatrixEPNS_7RegTreeEPiiPjPNSt3__16vectorINS3_11ExpandEntryENSF_9allocatorISH_EEEE 4BuildHistogramsLossGuideENS3_11ExpandEntryERKNS_6common16GHistIndexMatrixERKNS5_21GHistIndexBlockMatrixEPNS_7RegTreeERKNSt3__16vectorINS_6detail20GradientPairInternalIfEENSE_9allocatorISI_EEEE J J J ExpandEntryC InitNewNodeEiRKNS_6common16GHistIndexMatrixERKNSt3__16vectorINS_6detail20GradientPairInternalIfEENS8_9allocatorISC_EEEERKNS_7DMatrixERKNS_7RegTreeE Ĩ 2Eiiifj 1Eiiifj K K fE11ExpandEntry7IsValidERKNS0_10TrainParamEi dE11ExpandEntry7IsValidERKNS0_10TrainParamEi K K K EvaluateSplitsERKNSt3__16vectorINS3_11ExpandEntryENS4_9allocatorIS6_EEEERKNS_6common16GHistIndexMatrixERKNSC_14HistCollectionIfEERKNS_7RegTreeE BuildNodeStatsERKNS_6common16GHistIndexMatrixEPNS_7DMatrixEPNS_7RegTreeERKNSt3__16vectorINS_6detail20GradientPairInternalIfEENSC_9allocatorISG_EEEE ܨK K K йK K K K K K K K AddSplitsToTreeERKNS_6common16GHistIndexMatrixEPNS_7RegTreeEPiiPjPNSt3__16vectorINS3_11ExpandEntryENSC_9allocatorISE_EEEESI_ PartitionKernelI K C 6UpdateERKNS_6common16GHistIndexMatrixERKNS4_21GHistIndexBlockMatrixERKNS4_12ColumnMatrixEPNS_16HostDeviceVectorINS_6detail20GradientPairInternalIfEEEEPNS_7DMatrixEPNS_7RegTreeE 8InitDataERKNS_6common16GHistIndexMatrixERKNSt3__16vectorINS_6detail20GradientPairInternalIfEENS8_9allocatorISC_EEEERKNS_7DMatrixERKNS_7RegTreeE 1 9 2 2ERKNS0_10TrainParamENSt3__110unique_ptrINS_11TreeUpdaterENS7_14default_deleteIS9_EEEENS_32FeatureInteractionConstraintHostEPKNS_7DMatrixE 1ERKNS0_10TrainParamENSt3__110unique_ptrINS_11TreeUpdaterENS7_14default_deleteIS9_EEEENS_32FeatureInteractionConstraintHostEPKNS_7DMatrixE L L L ĝL 9 6S 1 2InitSamplingERKNSt3__16vectorINS_6detail20GradientPairInternalIfEENS4_9allocatorIS8_EEEERKNS_7DMatrixEPNS5_ImNS9_ImEEEE 4 0ApplySplitENSt3__16vectorINS3_11ExpandEntryENS4_9allocatorIS6_EEEERKNS_6common16GHistIndexMatrixERKNSA_12ColumnMatrixERKNSA_14HistCollectionIdEEPNS_7RegTreeE 7AddSplitsToRowSetERKNSt3__16vectorINS3_11ExpandEntryENS4_9allocatorIS6_EEEEPNS_7RegTreeE 3SplitSiblingsERKNSt3__16vectorINS3_11ExpandEntryENS4_9allocatorIS6_EEEEPS9_SC_PNS_7RegTreeE 5 ExpandWith SetHistSynchronizerEPNS0_16HistSynchronizerIdEE FindSplitConditionsERKNSt3__16vectorINS3_11ExpandEntryENS4_9allocatorIS6_EEEERKNS_7RegTreeERKNS_6common16GHistIndexMatrixEPNS5_IiNS7_IiEEEE LossGuideERKNS_6common16GHistIndexMatrixERKNS4_21GHistIndexBlockMatrixERKNS4_12ColumnMatrixEPNS_7DMatrixEPNS_7RegTreeERKNSt3__16vectorINS_6detail20GradientPairInternalIfEENSI_9allocatorISM_EEEE DepthWiseERKNS_6common16GHistIndexMatrixERKNS4_21GHistIndexBlockMatrixERKNS4_12ColumnMatrixEPNS_7DMatrixEPNS_7RegTreeERKNSt3__16vectorINS_6detail20GradientPairInternalIfEENSI_9allocatorISM_EEEE L L BuildHistERKNSt3__16vectorINS_6detail20GradientPairInternalIfEENS4_9allocatorIS8_EEEENS_6common16RowSetCollection4ElemERKNSE_16GHistIndexMatrixERKNSE_21GHistIndexBlockMatrixENSE_4SpanINS7_IdEELm18446744073709551615EEE LossGuideENS3_11ExpandEntryES4_ L ubtractionTrickENS_6common4SpanINS_6detail20GradientPairInternalIdEELm18446744073709551615EEES9_S9_ etHistRowsAdderEPNS0_13HistRowsAdderIdEE L 1UpdatePredictionCacheEPKNS_7DMatrixEPNS_16HostDeviceVectorIfEE 6SplitContainsMissingValuesENS0_9GradStatsERKNS1_9NodeEntryE 0BuildLocalHistogramsERKNS_6common16GHistIndexMatrixERKNS4_21GHistIndexBlockMatrixEPNS_7RegTreeERKNSt3__16vectorINS_6detail20GradientPairInternalIfEENSD_9allocatorISH_EEEE 2EvaluateAndApplySplitsERKNS_6common16GHistIndexMatrixERKNS4_12ColumnMatrixEPNS_7RegTreeEPiiPjPNSt3__16vectorINS3_11ExpandEntryENSF_9allocatorISH_EEEE 4BuildHistogramsLossGuideENS3_11ExpandEntryERKNS_6common16GHistIndexMatrixERKNS5_21GHistIndexBlockMatrixEPNS_7RegTreeERKNSt3__16vectorINS_6detail20GradientPairInternalIfEENSE_9allocatorISI_EEEE L L L ExpandEntryC InitNewNodeEiRKNS_6common16GHistIndexMatrixERKNSt3__16vectorINS_6detail20GradientPairInternalIfEENS8_9allocatorISC_EEEERKNS_7DMatrixERKNS_7RegTreeE 2Eiiifj 1Eiiifj L L L L L EvaluateSplitsERKNSt3__16vectorINS3_11ExpandEntryENS4_9allocatorIS6_EEEERKNS_6common16GHistIndexMatrixERKNSC_14HistCollectionIdEERKNS_7RegTreeE BuildNodeStatsERKNS_6common16GHistIndexMatrixEPNS_7DMatrixEPNS_7RegTreeERKNSt3__16vectorINS_6detail20GradientPairInternalIfEENSC_9allocatorISG_EEEE L L M M M M M M M ԬM M AddSplitsToTreeERKNS_6common16GHistIndexMatrixEPNS_7RegTreeEPiiPjPNSt3__16vectorINS3_11ExpandEntryENSC_9allocatorISE_EEEESI_ PartitionKernelI M hEEvmmNS_6common7Range1dEiRKNS5_12ColumnMatrixERKNS_7RegTreeE tEEvmmNS_6common7Range1dEiRKNS5_12ColumnMatrixERKNS_7RegTreeE jEEvmmNS_6common7Range1dEiRKNS5_12ColumnMatrixERKNS_7RegTreeE M M M hEEvmmNS_6common7Range1dEiRKNS5_12ColumnMatrixERKNS_7RegTreeE tEEvmmNS_6common7Range1dEiRKNS5_12ColumnMatrixERKNS_7RegTreeE jEEvmmNS_6common7Range1dEiRKNS5_12ColumnMatrixERKNS_7RegTreeE N N N N N N N N Q Q R S 1 4InitEiPPc 8FinalizeEv 9 3AllreduceBase 0Allreduce_EPvmmPFvPKvS1_iRKN3MPI8DatatypeEENS0_3mpi8DataTypeENSA_6OpTypeEPFvS1_ES1_ 2ReduceHandle C 4InitEiPPc 1 8S 20TryReduceScatterRingEPvmmPFvPKvS2_iRKN3MPI8DatatypeEE 2Ev 1Ev S S S 4ReConnectLinksEPKc 2Tr 6TryAll S hutdownEv etParamEPKcS3_ S S ackerPrintERKNSt3__112basic_stringIcNS2_11char_traitsIcEENS2_9allocatorIcEEEE y T T AllreduceEPvmmPFvPKvS2_iRKN3MPI8DatatypeEE BroadcastEPvmi T reduce gatherRingEPvmmmm RingEPvmmPFvPKvS2_iRKN3MPI8DatatypeEE TreeEPvmmPFvPKvS2_iRKN3MPI8DatatypeEE ЧT T T T T reduceEPvmNS_6engine3mpi8DataTypeENS3_6OpTypeEPFvS1_ES1_ gatherEPvmmmmi U U I Finalize Get TrackerPrint Broadcast All L CheckPoint VersionNumber nit sDistributed U U R WorldSize ProcessorName ingPrevRank ank U U U U U U ؓU gather reduce U U oadCheckPoint inkTag НU U ܢU U U U تU U U cEEvPKvPviRKN3MPI8DatatypeE hEEvPKvPviRKN3MPI8DatatypeE iEEvPKvPviRKN3MPI8DatatypeE jEEvPKvPviRKN3MPI8DatatypeE lEEvPKvPviRKN3MPI8DatatypeE mEEvPKvPviRKN3MPI8DatatypeE fEEvPKvPviRKN3MPI8DatatypeE dEEvPKvPviRKN3MPI8DatatypeE U U U ȸU кU U U U U U U U U cEEvPKvPviRKN3MPI8DatatypeE hEEvPKvPviRKN3MPI8DatatypeE iEEvPKvPviRKN3MPI8DatatypeE jEEvPKvPviRKN3MPI8DatatypeE lEEvPKvPviRKN3MPI8DatatypeE mEEvPKvPviRKN3MPI8DatatypeE U U U U U U U U GetEngineEv AllgatherEPvmmmm U U U C D 8TypeSizeERKN3MPI8DatatypeE 4InitEPFvPKvPviRKN3MPI8DatatypeEEm 9AllreduceEPvmmPFvS2_ES2_ 2Ev 1Ev U U 2Ev 1Ev U U U U U 7 6LibFMParserParam11__MANAGER__Ev 4CSVParserParam11__MANAGER__Ev 8CreateLibSVMParserI 5CreateCSVParserI LibSVMParserParam11__MANAGER__Ev CreateLibFMParserI U U U RowBlockIterI ThreadedIterINS_2io14InputSplitBase5ChunkEE14NotImplementedEv j y fE6CreateEPKcjjS3_ iE6CreateEPKcjjS3_ xE6CreateEPKcjjS3_ U fE6CreateEPKcjjS3_ iE6CreateEPKcjjS3_ xE6CreateEPKcjjS3_ U U U U U ParserI Stream6CreateEPKcS2_b j y fE6CreateEPKcjjS3_ iE6CreateEPKcjjS3_ xE6CreateEPKcjjS3_ U fE6CreateEPKcjjS3_ iE6CreateEPKcjjS3_ xE6CreateEPKcjjS3_ V V V V ĵV j y fEEE3GetEv iEEE3GetEv xEEE3GetEv V V V fEEE3GetEv iEEE3GetEv xEEE3GetEv V V V jfEEPNS_6ParserIT_fEERKNSt3__112basic_stringIcNS6_11char_traitsIcEENS6_9allocatorIcEEEERKNS6_3mapISC_SC_NS6_4lessISC_EENSA_INS6_4pairISD_SC_EEEEEEjj yfEEPNS_6ParserIT_fEERKNSt3__112basic_stringIcNS6_11char_traitsIcEENS6_9allocatorIcEEEERKNS6_3mapISC_SC_NS6_4lessISC_EENSA_INS6_4pairISD_SC_EEEEEEjj V V jfEEPNS_6ParserIT_fEERKNSt3__112basic_stringIcNS6_11char_traitsIcEENS6_9allocatorIcEEEERKNS6_3mapISC_SC_NS6_4lessISC_EENSA_INS6_4pairISD_SC_EEEEEEjj yfEEPNS_6ParserIT_fEERKNSt3__112basic_stringIcNS6_11char_traitsIcEENS6_9allocatorIcEEEERKNS6_3mapISC_SC_NS6_4lessISC_EENSA_INS6_4pairISD_SC_EEEEEEjj V V j y fEEPNS_6ParserIT_T0_EERKNSt3__112basic_stringIcNS7_11char_traitsIcEENS7_9allocatorIcEEEERKNS7_3mapISD_SD_NS7_4lessISD_EENSB_INS7_4pairISE_SD_EEEEEEjj iEEPNS_6ParserIT_T0_EERKNSt3__112basic_stringIcNS7_11char_traitsIcEENS7_9allocatorIcEEEERKNS7_3mapISD_SD_NS7_4lessISD_EENSB_INS7_4pairISE_SD_EEEEEEjj xEEPNS_6ParserIT_T0_EERKNSt3__112basic_stringIcNS7_11char_traitsIcEENS7_9allocatorIcEEEERKNS7_3mapISD_SD_NS7_4lessISD_EENSB_INS7_4pairISE_SD_EEEEEEjj V 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+{nodes}} {rankdir} {graph_attrs} /Users/runner/work/ml-builds/ml-builds/xgboost/src/tree/tree_updater.cc Unknown tree updater ColMakerTrainParam grow_colmaker Grow tree with parallelization over columns. opt_dense_col EXP Param: speed optimization for dense column. train_param colmaker_train_param /Users/runner/work/ml-builds/ml-builds/xgboost/src/tree/updater_colmaker.cc Updater `grow_colmaker` or `exact` tree method doesn't support distributed training. /Users/runner/work/ml-builds/ml-builds/xgboost/src/tree/param.h Max leaves and max depth cannot both be unconstrained. this->max_depth <= 31 max_depth can not be greater than 31 as that might generate 2 ** 32 - 1 nodes. Check failed: param_.cache_opt Support for `cache_opt' is removed in 1.0.0 fmat.Info().num_row_ == position_.size() param_.sampling_method == TrainParam::kUniform Only uniform sampling is supported, gradient-based sampling is only support by GPU Hist. ridx < position_.size() ridx exceed bound ridx= pos= /Users/runner/work/ml-builds/ml-builds/xgboost/src/tree/../common/transform.h grow_local_histmaker Tree constructor that uses approximate histogram construction. grow_histmaker Tree constructor that uses approximate global of histogram construction. /Users/runner/work/ml-builds/ml-builds/xgboost/src/tree/../common/quantile.h fi.Read(&this->size, sizeof(this->size)) == sizeof(this->size) fi.Read(this->data, this->size * sizeof(Entry)) == this->size * sizeof(Entry) check quantile stats, nbig= , n= srcsize= , maxsize= , range= , chunk= Check failed: nbig < n quantile: too many large chunk ] rmin= , rmax= , wmin= , v= /Users/runner/work/ml-builds/ml-builds/xgboost/src/tree/updater_histmaker.cc Check failed: param_.max_depth > 0 max_depth must be larger than 0 /Users/runner/work/ml-builds/ml-builds/xgboost/src/tree/./updater_basemaker-inl.h node2workindex_[nid] == static_cast<int>(wid) summary_array_.size() == sketchs_.size() offset == -2 this->wspace_.rptr.size() == (fset.size() + 1) * this->qexpand_.size() + 1 fid * 2 + 1 < fminmax_.size() FeatHelper fid exceed query bound ret > 0U Check failed: tree[nid].IsLeaf() sketch->temp.size < max_size invalid maximum size max_size= , stemp.size INFO: rmax= , sum_total= , naxt_goal= , size= sketch->temp.size <= max_size Finalize: invalid maximum size, max_size= , stemp.size= fid * 2 < fminmax_.size() fv= , hist.size= hist[ ]= , hist.last= istart != hist.size this->qexpand_.size() == 1U this->wspace_.rptr.back() == this->wspace_.cut.size() prune Pruner that prune the tree according to statistics. TreePruner PrunerUpdate /Users/runner/work/ml-builds/ml-builds/xgboost/src/tree/updater_prune.cc tree pruning end, extra nodes, pruned nodes, max_depth= Check failed: !tree[pid].IsLeaf() Check failed: nodes_[nodes_[rid].LeftChild() ].IsLeaf() Check failed: nodes_[nodes_[rid].RightChild()].IsLeaf() nid >= 1 Quantile::Builder Update SubtractionTrick UpdatePredictionCache /Users/runner/work/ml-builds/ml-builds/xgboost/src/tree/updater_quantile_hist.cc out_preds.size() > 0U Check failed: (param_.max_depth > 0 || param_.max_leaves > 0) max_depth or max_leaves cannot be both 0 (unlimited); at least one should be a positive quantity. max_depth cannot be 0 (unlimited) when grow_policy is depthwise. row_indices.size() + unused_rows_.size() == info.num_row_ min_nbins_per_feature > 0U EvaluateSplits ApplySplit (*p_tree)[nid].LeftChild() + 1 == (*p_tree)[nid].RightChild() upper_bound < static_cast<uint32_t>(std::numeric_limits<int32_t>::max()) InitNewNode BuildLocalHistograms SplitSiblings BuildNodeStats ExpandWithLossGuide CPUHistMakerTrainParam GmatInitialization grow_fast_histmaker (Deprecated, use grow_quantile_histmaker instead.) Grow tree using quantized histogram. Grow tree using quantized histogram. /Users/runner/work/ml-builds/ml-builds/xgboost/src/tree/../common/row_set.h elem_of_each_node_.size() == 0U Check failed: e.begin != nullptr n_left + n_right == e.Size() begin + n_left <= e.end begin + n_left + n_right == e.end /Users/runner/work/ml-builds/ml-builds/xgboost/src/tree/../common/column_matrix.h gmat.cut.Ptrs()[fid + 1] - gmat.cut.Ptrs()[fid] <= max_val gmat_bin_size == kUint32BinsTypeSize bins_type_size_ == kUint32BinsTypeSize cpu_hist_train_param /Users/runner/work/ml-builds/ml-builds/xgboost/src/tree/./updater_quantile_hist.h Attempted to load internal configuration for a model file that was generated by a previous version of XGBoost. A likely cause for this warning is that the model was saved with saveRDS() in R or pickle.dump() in Python. We strongly ADVISE AGAINST using saveRDS() or pickle.dump() so that the model remains accessible in current and upcoming XGBoost releases. Please use xgb.save() instead to preserve models for the long term. For more details and explanation, see https://xgboost.readthedocs.io/en/latest/tutorials/saving_model.html single_precision_histogram Use single precision to build histograms. SyncHistograms SyncHistogramsAllreduce /Users/runner/work/ml-builds/ml-builds/xgboost/src/tree/../common/threading_utils.h begin < end /Users/runner/work/ml-builds/ml-builds/xgboost/src/tree/../common/hist_util.h end > begin nid < nodes_ i < first_dimension_.size() i < ranges_.size() AddHistRows row_ptr_[nid] == kMax Check failed: (*p_last_tree_)[nid].IsLeaf() id != kMax cut_ptr[fid] <= static_cast<uint32_t>(std::numeric_limits<int32_t>::max()) cut_ptr[fid + 1] <= static_cast<uint32_t>(std::numeric_limits<int32_t>::max()) nodes == targeted_hists.size() tid < nthreads_ grow_fast_histmaker is deprecated, use grow_quantile_histmaker instead. QuantileHistMaker refresh Refresher that refreshes the weight and statistics according to data. /Users/runner/work/ml-builds/ml-builds/xgboost/src/tree/updater_refresh.cc batch.Size() < std::numeric_limits<unsigned>::max() Syncher that synchronize the tree in all distributed nodes. NULL worker rabit_reduce_buffer 256MB DMLC_TASK_ID DMLC_ROLE DMLC_NUM_ATTEMPT DMLC_TRACKER_URI DMLC_TRACKER_PORT DMLC_WORKER_CONNECT_RETRY %[^=]=%s mapred_tip_id mapreduce_task_id hadoop_mode is set but cannot find mapred_task_id rabit_task_id rabit_hadoop_mode mapred_task_id %d rabit_num_trial mapred_map_tasks mapreduce_job_maps hadoop_mode is set but cannot find mapred_map_tasks rabit_world_size /Users/runner/work/ml-builds/ml-builds/xgboost/rabit/src/allreduce_base.cc Rabit Module currently only work with dmlc worker can only call Init once start Failed to shutdown due to %s print rabit_tracker_uri rabit_tracker_port rabit_tree_reduce_minsize rabit_reduce_ring_mincount rabit_reduce_ring_mincount should be greater than 0 rabit_bootstrap_cache rabit_debug rabit_timeout rabit_timeout_sec rabit_timeout_sec should be non negative second rabit_enable_tcp_no_delay Connect to (failed): [ ]
+ Connect Retry connect to ip(retry time ): [ ReConnectLink failure 1 ReConnectLink failure 2 sync::Invalid tracker message, init failure ReConnectLink failure 3 task connected to the tracker ReConnectLink failure 4 must keep rank to same if the node already have one tracker got overwhelemed and not able to assign correct rank got new rank ReConnectLink fail to bind the ports specified ReConnectLink failure 5 ReConnectLink failure 6 ReConnectLink failure 7 ReConnectLink failure 8 ReConnectLink failure 9 ReConnectLink failure 10 ReConnectLink failure 12 ReConnectLink failure 13 ReConnectLink failure, link rank inconsistent Override a link that is active ReConnectLink failure 14 ReConnectLink failure 15 ReConnectLink: bad socket tcp no delay is not implemented on non unix platforms cannot find parent in the link cannot find prev ring in the link cannot find next ring in the link failed in ReconnectLink buffer size inconsistent must assign buffer_size Allreduce: size check Allreduce: boundary error Broadcast: root should be smaller than world size need to assume rank structure write ptr boundary check [%d] read_ptr boundary check fail to get host name Socket::Close double close the socket or close without create error during send SendStr %lu%c invalid format for %s invalid format for %s,shhould be {integer}{unit}, unit can be {B, KB, MB, GB} Create cannot obtain address of %s Does not support IPv6 Socket %s Error:%s SendAll RecvAll 0.0.0.0 TryBindHost GetSockError error during send RecvStr Accept SetNonBlock-1 SetNonBlock-2 SetKeepAlive too large type_nbytes=%lu, buffer_size=%lu /Users/runner/work/ml-builds/ml-builds/xgboost/rabit/include/rabit/internal/socket.h Poll timeout Poll ReadToRingBuffer: buffer not allocated ReadToRingBuffer: max_size_read check Allreduce: boundary check AllgatherRing failed Allreduce failed Broadcast failed unknown enum_op unknown data_type Failed to initialize RABIT. Failed to shutdown RABIT worker. Read pickle string not implemented DataType does not support bitwise or operation the rabit has not been initialized cannot initialize reduce handle twice must intialize handle to call AllReduce LibSVMParserParam LibFMParserParam CSVParserParam libfm format File format indexing_mode If >0, treat all feature indices as 1-based. If =0, treat all feature indices as 0-based. If <0, use heuristic to automatically detect mode of indexing. See https://en.wikipedia.org/wiki/Array_data_type#Index_origin for more details on indexing modes. If >0, treat all field and feature indices as 1-based. If =0, treat all field and feature indices as 0-based. If <0, use heuristic to automatically detect mode of indexing. See https://en.wikipedia.org/wiki/Array_data_type#Index_origin for more details on indexing modes. File format. label_column Column index (0-based) that will put into label. delimiter Delimiter used in the csv file. weight_column Column index that will put into instance weights. /Users/runner/work/ml-builds/ml-builds/xgboost/dmlc-core/src/data/disk_row_iter.h Check failed: TryLoadCache() failed to build cache file /Users/runner/work/ml-builds/ml-builds/xgboost/dmlc-core/src/data/./row_block.h Check failed: fi->Read(&label) Bad RowBlock format Check failed: fi->Read(&weight) Check failed: fi->Read(&qid) Check failed: fi->Read(&field) Check failed: fi->Read(&index) Check failed: fi->Read(&value) Check failed: fi->Read(&max_field, sizeof(IndexType)) Check failed: fi->Read(&max_index, sizeof(IndexType)) MB read, MB/sec finish reading at %g MB/sec label.size() + 1 == offset.size() offset.back() == index.size() Check failed: offset.back() == value.size() || value.size() == 0 /Users/runner/work/ml-builds/ml-builds/xgboost/dmlc-core/src/data/basic_row_iter.h finish reading at /Users/runner/work/ml-builds/ml-builds/xgboost/dmlc-core/src/data.cc Unknown data type /Users/runner/work/ml-builds/ml-builds/xgboost/dmlc-core/src/data/./libsvm_parser.h param_.format == "libsvm" /Users/runner/work/ml-builds/ml-builds/xgboost/dmlc-core/src/data/./text_parser.h chunk.size != 0U qid: Check failed: out->label.size() + 1 == out->offset.size() Check failed: base <= 10 && base >= 2 sign == true /Users/runner/work/ml-builds/ml-builds/xgboost/dmlc-core/src/data/parser.h cannot call ParseNext /Users/runner/work/ml-builds/ml-builds/xgboost/dmlc-core/src/data/libfm_parser.h param_.format == "libfm" Check failed: out->field.size() == out->index.size() /Users/runner/work/ml-builds/ml-builds/xgboost/dmlc-core/src/data/csv_parser.h param_.format == "csv" Check failed: param_.label_column != param_.weight_column || param_.label_column < 0 Must have distinct columns for labels and instance weights Delimiter ' ' is not found in the line. Expected ' ' as the delimiter to separate fields. Check failed: out->weight.size() == 0 || out->weight.size() + 1 == out->offset.size() hdfs:// viewfs:// /Users/runner/work/ml-builds/ml-builds/xgboost/dmlc-core/src/io.cc Please compile with DMLC_USE_HDFS=1 to use hdfs s3:// http:// https:// Please compile with DMLC_USE_S3=1 to use S3 azure:// Please compile with DMLC_USE_AZURE=1 to use Azure unknown filesystem protocol stdin Check failed: part < nsplit invalid input parameter for InputSplit::Create indexed_recordio need to pass index file to use IndexedRecordIO recordio unknown input split type .split .part /Users/runner/work/ml-builds/ml-builds/xgboost/dmlc-core/src/io/uri_spec.h name_cache.size() == 1U only one `#` is allowed in file path for cachefile specification Check failed: std::getline(is, kv.first, '=') Invalid uri argument format for key in arg Check failed: std::getline(is, kv.second) for value in arg name_args.size() == 1U /Users/runner/work/ml-builds/ml-builds/xgboost/dmlc-core/src/io/single_file_split.h Check failed: fp_ != NULL SingleFileSplit: fail to open Check failed: part_index == 0 && num_parts == 1 InputSplit do not support write /Users/runner/work/ml-builds/ml-builds/xgboost/dmlc-core/src/io/cached_input_split.h Check failed: nread == sizeof(size) has invalid cache file format Check failed: fi_->Read(p->begin, size) == size BeforeFirst is not supported Check failed: this->InitCachedIter() Failed to initialize CachedIter ResetPartition is not supported in CachedInputSplit /Users/runner/work/ml-builds/ml-builds/xgboost/dmlc-core/src/io/line_split.cc Check failed: begin != end /Users/runner/work/ml-builds/ml-builds/xgboost/dmlc-core/src/io/recordio_split.cc Check failed: fi->Read(&lrec, sizeof(lrec)) != 0 invalid record io format (reinterpret_cast<size_t>(begin) & 3UL) == 0U (reinterpret_cast<size_t>(end) & 3UL) == 0U Check failed: p >= pbegin + 2 Check failed: chunk->begin + 2 * sizeof(uint32_t) <= chunk->end Invalid RecordIO Format (reinterpret_cast<size_t>(chunk->begin) & 3UL) == 0U (reinterpret_cast<size_t>(chunk->end) & 3UL) == 0U Check failed: chunk->begin <= chunk->end Check failed: cflag == 1U Check failed: p[0] == RecordIOWriter::kMagic /Users/runner/work/ml-builds/ml-builds/xgboost/dmlc-core/src/io/indexed_recordio_split.cc expanded_list.size() == 1ul IndexedRecordIOSplitter does not support multiple index files /Users/runner/work/ml-builds/ml-builds/xgboost/dmlc-core/src/io/input_split_base.cc Check failed: files_[i].size % align_bytes == 0 file do not align by bytes Check failed: offset_end_ >file_offset_[file_ptr_end_] Check failed: file_ptr_end_ < files_.size() bad regex This could due to compiler version, g++-4.9 is needed files_.size() != 0U Cannot find any files that matches the URI pattern curr= ,begin= ,end= ,fileptr= ,fileoffset= offset[ file offset not calculated correctly C /Users/runner/work/ml-builds/ml-builds/xgboost/dmlc-core/src/io/filesys.cc Check failed: !IsSymlink(info.path.name) Symlink not supported in TemporaryDirectory Couldn't remove file Successfully deleted temporary directory ~TemporaryDirectory(): Could not remove temporary directory /Users/runner/work/ml-builds/ml-builds/xgboost/dmlc-core/include/dmlc/filesystem.h lstat(path.c_str(), &sb) == 0 dmlc::TemporaryDirectory::IsSymlink(): Unable to read file attributes /Users/runner/work/ml-builds/ml-builds/xgboost/dmlc-core/src/io/local_filesys.cc LocalFileSystem.GetPathInfo: detected symlink error: LocalFileSystem.GetPathInfo: LocalFileSystem.ListDirectory .. stdout wb Check failed: allow_null LocalFileSystem::Open " ": Check failed: std::fwrite(ptr, 1, size, fp_) == size FileStream.Write incomplete Check failed: !std::fseek(fp_, static_cast<long>(pos), SEEK_SET) % T T T T T T T T T T T T T T T T T T T |6 D w D T `u d # L t l7 E D (7 T @ d C J L (P , 0T U W t Y \ x ] _ , b xd h i <l n | p Ts L w y ` | ~ l l ܿ $ ` l p l l P \ L 8 | T 4 H ` X T X h H ` \ x 0 , @ | p P 0 D H
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@__ZNSt3__114basic_iostreamIcNS_11char_traitsIcEEED2Ev r@__ZNSt3__115__get_classnameEPKcb r@__ZNSt3__115__thread_structC1Ev r@__ZNSt3__115__thread_structD1Ev r@__ZNSt3__115basic_streambufIcNS_11char_traitsIcEEEC2Ev r@__ZNSt3__115basic_streambufIcNS_11char_traitsIcEEED2Ev r@__ZNSt3__118condition_variable10notify_allEv r@__ZNSt3__118condition_variable10notify_oneEv r@__ZNSt3__118condition_variable4waitERNS_11unique_lockINS_5mutexEEE r@__ZNSt3__118condition_variableD1Ev r@__ZNSt3__119__shared_weak_count14__release_weakEv r@__ZNSt3__119__shared_weak_count4lockEv r@__ZNSt3__119__shared_weak_countD2Ev r@__ZNSt3__119__thread_local_dataEv r@__ZNSt3__120__get_collation_nameEPKc r@__ZNSt3__120__throw_system_errorEiPKc r@__ZNSt3__14stoiERKNS_12basic_stringIcNS_11char_traitsIcEENS_9allocatorIcEEEEPmi r@__ZNSt3__15mutex4lockEv r@__ZNSt3__15mutex6unlockEv r@__ZNSt3__15mutex8try_lockEv r@__ZNSt3__15mutexD1Ev r@__ZNSt3__16__sortIRNS_6__lessIiiEEPiEEvT0_S5_T_ r@__ZNSt3__16__sortIRNS_6__lessIjjEEPjEEvT0_S5_T_ r@__ZNSt3__16__sortIRNS_6__lessImmEEPmEEvT0_S5_T_ r@__ZNSt3__16chrono12steady_clock3nowEv r@__ZNSt3__16localeC1ERKS0_ r@__ZNSt3__16localeC1Ev r@__ZNSt3__16localeD1Ev r@__ZNSt3__16thread4joinEv r@__ZNSt3__16threadD1Ev r@__ZNSt3__18ios_base33__set_badbit_and_consider_rethrowEv r@__ZNSt3__18ios_base4initEPv r@__ZNSt3__18ios_base5clearEj r@__ZNSt3__19basic_iosIcNS_11char_traitsIcEEED2Ev r@__ZNSt3__19to_stringEi r@__ZNSt3__19to_stringEj r@__ZNSt3__19to_stringEm r@__ZNSt3__19to_stringEx r@__ZNSt3__1plIcNS_11char_traitsIcEENS_9allocatorIcEEEENS_12basic_stringIT_T0_T1_EEPKS6_RKS9_ r@__ZNSt8bad_castC1Ev r@__ZNSt9exceptionD2Ev r@__ZSt17current_exceptionv r@__ZSt17rethrow_exceptionSt13exception_ptr r@__ZSt9terminatev r@___cxa_allocate_exception r@___cxa_atexit r@___cxa_begin_catch r@___cxa_demangle r@___cxa_end_catch r@___cxa_free_exception r@___cxa_guard_abort r@___cxa_guard_acquire r@___cxa_guard_release r@___cxa_rethrow r@___cxa_throw r@___dynamic_cast r@___error r@___kmpc_barrier r@___kmpc_dispatch_init_4u r@___kmpc_dispatch_next_4u r@___kmpc_end_reduce_nowait r@___kmpc_end_serialized_parallel r@___kmpc_end_single r@___kmpc_for_static_fini r@___kmpc_for_static_init_4 r@___kmpc_for_static_init_4u r@___kmpc_for_static_init_8 r@___kmpc_for_static_init_8u r@___kmpc_fork_call r@___kmpc_global_thread_num r@___kmpc_push_num_threads r@___kmpc_reduce_nowait r@___kmpc_serialized_parallel r@___kmpc_single r@___maskrune r@___stack_chk_fail r@___tolower r@__tlv_atexit r@_accept r@_atof r@_atoi r@_atoll r@_backtrace r@_backtrace_symbols r@_bind r@_bzero r@_close r@_closedir r@_connect r@_erf r@_exp r@_expf r@_fclose r@_fcntl r@_feof r@_fflush r@_fileno r@_fopen r@_fopen$DARWIN_EXTSN r@_fread r@_free r@_freeaddrinfo r@_fseek r@_fseeko r@_fstat r@_ftell r@_ftello r@_fwrite r@_getaddrinfo r@_getenv r@_gethostname r@_getsockopt r@_lgammaf r@_listen r@_localtime_r r@_log r@_log1pf r@_log2 r@_log2f r@_logf r@_lstat r@_malloc r@_memchr r@_memcmp r@_memcpy r@_memmove r@_memset r@_nan r@_omp_get_max_threads r@_omp_get_num_procs r@_omp_get_num_threads r@_omp_get_thread_num r@_omp_in_parallel r@_omp_set_num_threads r@_opendir r@_poll r@_pthread_create r@_pthread_setspecific r@_readdir r@_recv r@_remove r@_rmdir r@_send r@_setsockopt r@_sleep r@_snprintf r@_socket r@_sscanf r@_stat r@_strcasecmp r@_strchr r@_strcmp r@_strcpy r@_strerror r@_strlen r@_strncmp r@_strrchr r@_strstr r@_strtof r@_strtoimax r@_strtoll r@_time r@_vsnprintf _ XG ?_Z Rabit .gomp_critical_user_.reduction.var B ]D ProxyDMatrixCreate oost RegisterLogCallback SetGlobalConfig Get Version er l m n GlobalConfig LastError Matrix eviceQuantileDMatrix CreateFrom S Free Get Num File D ArrayInterface CS Mat ataIter T Columns SetDataCuda CreateFromCallback ArrayInterface Columnar Կ R CEx Ex _omp liceDMatrix aveBinary et Ex FloatInfo InfoFromInterface UIntInfo StrFeatureInfo DenseInfo Group StrFeatureInfo FloatInfo UIntInfo Row Col ܦ
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+ Ex WithFeatures WithFeatures Ģ آ Names ZN N 18XGBAPISetLastErrorPKc T StrsRNSt3__113basic_istreamIcNS_11char_traitsIcEEEERNS_6vectorIiNS_9allocatorIiEEEE ɅG 7xgboost 4dmlc K7xgboost 4data15IteratorAdapterIPvFiS2_PFiS2_15XGBoostBatchCSRES2_ES3_E4NextEvENUlS2_S3_E_8__invokeES2_S3_ 1 20ArrayInterfaceErrors9DimensionEiE3str 9LogCallbackRegistryC1EvENUlPKcE_8__invokeES2_ 3 7GraphvizGenerator ͽԢ 4dmlc 7xgboost K -5rabit 3any11TypeOnStackINSt3__110shared_ptrIN7xgboost4data1 8RegistryIN ˯1 4data1 6 2io 2ArrayAdapterEEEE 5CSRArrayAdapterEEEE 7destroyEPNS0_4DataE 16create_from_dataEPNS0_4DataERKS9_ 7destroyEPNS0_4DataE 16create_from_dataEPNS0_4DataERKS9_
+6 1 )9 8 4 lsERNSt3__113basic_ostreamIcNS0_11char_traitsIcEEEENS_10StringViewE 7 5Entry8CmpValueERKS0_S2_ 3 2 detail1 common linear metric Metric6CreateERKNSt3__112basic_stringIcNS1_11char_traitsIcEENS1_9allocatorIcEEEEPKNS_16GenericParameterE 6 9ToCharsUnsignedImplEPcS1_y 7FromCharFloatImplEPKciPf 4RyuPowLogUtils1 ToCharsFloatImplEfPc ItoaUnsignedImplEPcjy 1 21 8 5Index1 (7Monitor 2G 4AllVisibleGPUsEv 3 5 6 '8LoadSequentialFileENSt3__112basic_stringIcNS1_11char_traitsIcEENS1_9allocatorIcEEEEb 9HostSketchContainer 1AddCutPointERKNS0_22QuantileSketchTemplateIffNS0_9WQSummaryIffEEE16SummaryContainerEiPNS0_13HistogramCutsE lobalRandomEv HistBuilderI ̗ InitilizeHistByZeroesI GHistIndexBlockMatrix4InitERKNS0_16GHistIndexMatrixERKNS0_12ColumnMatrixERKNS_4tree10TrainParamE ( fEEvNS0_4SpanINS_6detail20GradientPairInternalIT_EELm18446744073709551615EEEmm dEEvNS0_4SpanINS_6detail20GradientPairInternalIT_EELm18446744073709551615EEEmm ԗ IncrementHistI HistogramCutsC (ColumnSampler9ColSampleENSt3__110shared_ptrINS_16HostDeviceVectorIjEEEEf fEEvNS0_4SpanINS_6detail20GradientPairInternalIT_EELm18446744073709551615EEES7_mm dEEvNS0_4SpanINS_6detail20GradientPairInternalIT_EELm18446744073709551615EEES7_mm Й CopyHistI AFTParam11__MANAGER__Ev Prefetch15kNoPrefetchSizeE Ƈ fEEvNS0_4SpanINS_6detail20GradientPairInternalIT_EELm18446744073709551615EEES7_mm dEEvNS0_4SpanINS_6detail20GradientPairInternalIT_EELm18446744073709551615EEES7_mm SubtractionHistI FixedSizeStream Հ fEEvNS0_4SpanINS_6detail20GradientPairInternalIT_EELm18446744073709551615EEES7_S7_mm dEEvNS0_4SpanINS_6detail20GradientPairInternalIT_EELm18446744073709551615EEES7_S7_mm ĝ fE dE ! 9BuildHistERKNSt3__16vectorINS_6detail20GradientPairInternalIfEENS3_9allocatorIS7_EEEENS0_16RowSetCollection4ElemERKNS0_16GHistIndexMatrixENS0_4SpanIS7_Lm18446744073709551615EEEb !1 # 9BuildHistERKNSt3__16vectorINS_6detail20GradientPairInternalIfEENS3_9allocatorIS7_EEEENS0_16RowSetCollection4ElemERKNS0_16GHistIndexMatrixENS0_4SpanINS6_IdEELm18446744073709551615EEEb #1 % 4BuildBlockHistERKNSt3__16vectorINS_6detail20GradientPairInternalIfEENS3_9allocatorIS7_EEEENS0_16RowSetCollection4ElemERKNS0_21GHistIndexBlockMatrixENS0_4SpanIS7_Lm18446744073709551615EEE %6SubtractionTrickENS0_4SpanINS_6detail20GradientPairInternalIfEELm18446744073709551615EEES7_S7_ '̯ 4BuildBlockHistERKNSt3__16vectorINS_6detail20GradientPairInternalIfEENS3_9allocatorIS7_EEEENS0_16RowSetCollection4ElemERKNS0_21GHistIndexBlockMatrixENS0_4SpanINS6_IdEELm18446744073709551615EEE '6SubtractionTrickENS0_4SpanINS_6detail20GradientPairInternalIdEELm18446744073709551615EEES7_S7_ ' GHistIndexMatrix (PeekableInStream 11ResizeIndexEmb (4InitEPNS_7DMatrixEi ( 2Ev (1Ev ( 7GetValueFromUint8EPvm )8GetValueFromUint ) 16EPvm )32EPvm ) 6 *0 5 1 В9 7Learner 3 4UnwoundPathSumEPKNS_11PathElementEjj HostDeviceVectorI *GenericParameter fE *NS_ 4iE >hE FyE _jE gmE x C +D ,aSEOS1_ -1 /8HostSpanEv 24 36 3 2E +1E , mfi ,St16initializer_listIfEi ,RKNSt3__16vectorIfNS2_9allocatorIfEEEEi ,OS1_ -ԗ mfi ,St16initializer_listIfEi ,RKNSt3__16vectorIfNS2_9allocatorIfEEEEi ,OS1_ - 2Ev -1Ev - 7xgboost -5rabit6engine13AllreduceBase14ConnectTrackerEv 1 .5Value7TypeStrEv 9JsonArrayeqERKNS_5ValueE 8 6common7Monitor ݫ7 4 3gbm 6HostDeviceVectorI .0 1 fE /NS_ 8iE @hE IyE ajE jmE z 5EmptyEv /4SizeEv /9 /1 08HostSpanEv 2 DeviceIdxEv /SetDeviceEi 4 0 03DevicePointerEv 11HostPointerEv 2 DeviceSpanEv 0HostVectorEv 2 5Const 10 18ConstDevicePointerEv 13 16ConstHostPointerEv 21Host 22 44DeviceCanWriteEv 4 DeviceSpanEv 1HostVectorEv 2 DeviceSpanEv 1HostVectorEv 2 Device 2ConstHostSpanEv 2 PointerEv 2CanReadEv 4 Ȣ Ԣ ܢ PointerEv 2CanReadEv 4 FillEf 3CopyE 3̣ RK 3St16initializer_listIfE 3 S1_ 3NSt3__16vectorIfNS2_9allocatorIfEEEE 3 ExtendERKS1_ 4ResizeEmf 4 HostCanWriteEv 4DeviceAccessEv 4 6detail20GradientPairInternalIfEEE 511FeatureTypeEE N5EntryEE W7RegTree7SegmentEE o C 5D 7aSEOS4_ 81 98HostSpanEv <4 <6 = 2E 61E 6 mS3_i 6St16initializer_listIS3_Ei 7RKNSt3__16vectorIS3_NS5_9allocatorIS3_EEEEi 7OS4_ 7 mS3_i 7St16initializer_listIS3_Ei 7RKNSt3__16vectorIS3_NS5_9allocatorIS3_EEEEi 7OS4_ 7 2Ev 71Ev 7 ط 6detail20GradientPairInternalIfEEE 811FeatureTypeEE Q5EntryEE Y7RegTree7SegmentEE r 5EmptyEv 94SizeEv 99 91 :8HostSpanEv < ȹ DeviceIdxEv 9SetDeviceEi >ܹ 0 93DevicePointerEv ;1HostPointerEv < DeviceSpanEv :HostVectorEv < 5Const :0 ;8ConstDevicePointerEv ;3 ;6ConstHostPointerEv <1Host <2 >4DeviceCanWriteEv > DeviceSpanEv ;HostVectorEv < DeviceSpanEv ;HostVectorEv < Device ;ConstHostSpanEv < PointerEv <CanReadEv > غ PointerEv <CanReadEv = FillES3_ <CopyE < RK =St16initializer_listIS3_E = S4_ =NSt3__16vectorIS3_NS5_9allocatorIS3_EEEE =Ȼ ̾ ExtendERKS4_ =ResizeEmS3_ > HostCanWriteEv >DeviceAccessEv > C >D @aSEOS1_ @1 A8HostSpanEv D4 D6 E 2E ?1E ? mii ?St16initializer_listIiEi @RKNSt3__16vectorIiNS2_9allocatorIiEEEEi @OS1_ @ mii @St16initializer_listIiEi @RKNSt3__16vectorIiNS2_9allocatorIiEEEEi @OS1_ @ 2Ev @1Ev @ 5EmptyEv A4SizeEv A9 A1 B8HostSpanEv D DeviceIdxEv ASetDeviceEi F 0 B3DevicePointerEv C1HostPointerEv D DeviceSpanEv BHostVectorEv D 5Const C0 C8ConstDevicePointerEv C3 C6ConstHostPointerEv D1Host D2 F4DeviceCanWriteEv F DeviceSpanEv CHostVectorEv D DeviceSpanEv CHostVectorEv D Device DConstHostSpanEv D PointerEv DCanReadEv F PointerEv DCanReadEv F FillEi ECopyE E RK ESt16initializer_listIiE E S1_ ENSt3__16vectorIiNS2_9allocatorIiEEEE E ExtendERKS1_ FResizeEmi F HostCanWriteEv FDeviceAccessEv F C GD HaSEOS1_ I1 I8HostSpanEv L4 M6 M 2E G1E G mhi GSt16initializer_listIhEi HRKNSt3__16vectorIhNS2_9allocatorIhEEEEi HOS1_ H mhi HSt16initializer_listIhEi HRKNSt3__16vectorIhNS2_9allocatorIhEEEEi HOS1_ I 2Ev H1Ev H 5EmptyEv I4SizeEv I9 I1 J8HostSpanEv L DeviceIdxEv ISetDeviceEi N 0 J3DevicePointerEv K1HostPointerEv L DeviceSpanEv JHostVectorEv L 5Const K0 K8ConstDevicePointerEv K3 K6ConstHostPointerEv L1Host L2 N4DeviceCanWriteEv N DeviceSpanEv KHostVectorEv L DeviceSpanEv KHostVectorEv L Device LConstHostSpanEv L PointerEv LCanReadEv N PointerEv LCanReadEv N FillEh MCopyE M RK MSt16initializer_listIhE M S1_ MNSt3__16vectorIhNS2_9allocatorIhEEEE M ExtendERKS1_ NResizeEmh N HostCanWriteEv NDeviceAccessEv N C OD QaSEOS2_ Q1 R8HostSpanEv T4 U6 V 2E O1E P mS1_i PSt16initializer_listIS1_Ei PRKNSt3__16vectorIS1_NS3_9allocatorIS1_EEEEi POS2_ Q mS1_i PSt16initializer_listIS1_Ei PRKNSt3__16vectorIS1_NS3_9allocatorIS1_EEEEi POS2_ Q 2Ev Q1Ev Q 5EmptyEv Q4SizeEv Q9 Q1 R8HostSpanEv T DeviceIdxEv RSetDeviceEi W 0 R3DevicePointerEv T1HostPointerEv T DeviceSpanEv RHostVectorEv T 5Const S0 S8ConstDevicePointerEv T3 T6ConstHostPointerEv T1Host U2 V4DeviceCanWriteEv W DeviceSpanEv SHostVectorEv T DeviceSpanEv THostVectorEv T Device TConstHostSpanEv T PointerEv TCanReadEv V Ȅ Ԅ ܄ PointerEv UCanReadEv V FillES1_ UCopyE U RK USt16initializer_listIS1_E V S2_ VNSt3__16vectorIS1_NS3_9allocatorIS1_EEEE V ExtendERKS2_ VResizeEmS1_ W̎ HostCanWriteEv VDeviceAccessEv W ȑ Б ԑ C WD YaSEOS2_ Y1 Z8HostSpanEv ]4 ]6 ^ 2E W1E X mS1_i XSt16initializer_listIS1_Ei YRKNSt3__16vectorIS1_NS3_9allocatorIS1_EEEEi YOS2_ Y mS1_i YSt16initializer_listIS1_Ei YRKNSt3__16vectorIS1_NS3_9allocatorIS1_EEEEi YOS2_ YЕ ؘ ܘ ؚ 2Ev Y1Ev Yܚ 5EmptyEv Z4SizeEv Z9 Z1 [8HostSpanEv ] DeviceIdxEv ZSetDeviceEi _ 0 Z3DevicePointerEv \1HostPointerEv \ DeviceSpanEv [HostVectorEv ]Ğ 5Const [0 \8ConstDevicePointerEv \3 \6ConstHostPointerEv ]1Host ]2 ^4DeviceCanWriteEv _ DeviceSpanEv \HostVectorEv ]̞ DeviceSpanEv \HostVectorEv ]Ԟ ܞ Device \ConstHostSpanEv ] PointerEv \CanReadEv _ ؟ PointerEv ]CanReadEv ^ FillES1_ ]CopyE ] RK ^St16initializer_listIS1_E ^ S2_ ^NSt3__16vectorIS1_NS3_9allocatorIS1_EEEE ^ ExtendERKS2_ ^ResizeEmS1_ _ HostCanWriteEv _DeviceAccessEv _Ȫ Ъ ت C _D aaSEOS1_ a1 b8HostSpanEv e4 e6 f 2E _1E ` myi `St16initializer_listIyEi aRKNSt3__16vectorIyNS2_9allocatorIyEEEEi aOS1_ aī myi aSt16initializer_listIyEi aRKNSt3__16vectorIyNS2_9allocatorIyEEEEi aOS1_ aĭ į 2Ev a1Ev a Գ 5EmptyEv b4SizeEv b9 b1 c8HostSpanEv eȶ ܶ DeviceIdxEv bSetDeviceEi g 0 b3DevicePointerEv d1HostPointerEv e DeviceSpanEv cHostVectorEv e 5Const d0 d8ConstDevicePointerEv d3 d6ConstHostPointerEv e1Host e2 g4DeviceCanWriteEv g DeviceSpanEv dHostVectorEv e DeviceSpanEv dHostVectorEv e Device dConstHostSpanEv e PointerEv eCanReadEv g Է PointerEv eCanReadEv g FillEy eCopyE f RK fSt16initializer_listIyE f S1_ fNSt3__16vectorIyNS2_9allocatorIyEEEE fܸ ExtendERKS1_ gResizeEmy g HostCanWriteEv gDeviceAccessEv g C hD iaSEOS1_ j1 j8HostSpanEv m4 m6 n 2E h1E h mji hSt16initializer_listIjEi iRKNSt3__16vectorIjNS2_9allocatorIjEEEEi iOS1_ i mji iSt16initializer_listIjEi iRKNSt3__16vectorIjNS2_9allocatorIjEEEEi iOS1_ i 2Ev i1Ev i 5EmptyEv j4SizeEv j9 j1 k8HostSpanEv m DeviceIdxEv jSetDeviceEi o 0 k3DevicePointerEv l1HostPointerEv m DeviceSpanEv kHostVectorEv m 5Const l0 l8ConstDevicePointerEv l3 l6ConstHostPointerEv m1Host m2 o4DeviceCanWriteEv o DeviceSpanEv lHostVectorEv m DeviceSpanEv lHostVectorEv m Device mConstHostSpanEv m PointerEv mCanReadEv o PointerEv mCanReadEv o FillEj nCopyE n RK nSt16initializer_listIjE n S1_ nNSt3__16vectorIjNS2_9allocatorIjEEEE n ExtendERKS1_ oResizeEmj o HostCanWriteEv oDeviceAccessEv o C pD qaSEOS3_ r1 s8HostSpanEv u4 v6 w 2E p1E q mS2_i pSt16initializer_listIS2_Ei qRKNSt3__16vectorIS2_NS4_9allocatorIS2_EEEEi qOS3_ r mS2_i qSt16initializer_listIS2_Ei qRKNSt3__16vectorIS2_NS4_9allocatorIS2_EEEEi qOS3_ r 2Ev r1Ev r 5EmptyEv r4SizeEv r9 r1 s8HostSpanEv u DeviceIdxEv sSetDeviceEi x 0 s3DevicePointerEv u1HostPointerEv u DeviceSpanEv sHostVectorEv u 5Const t0 t8ConstDevicePointerEv u3 u6ConstHostPointerEv u1Host u2 w4DeviceCanWriteEv w DeviceSpanEv tHostVectorEv u DeviceSpanEv tHostVectorEv u Device uConstHostSpanEv u PointerEv uCanReadEv w PointerEv vCanReadEv w FillES2_ vCopyE v RK vSt16initializer_listIS2_E w S3_ wNSt3__16vectorIS2_NS4_9allocatorIS2_EEEE w ExtendERKS3_ wResizeEmS2_ x HostCanWriteEv wDeviceAccessEv x C xD zaSEOS1_ z1 {8HostSpanEv }4 ~6 2E x1E y mmi ySt16initializer_listImEi zRKNSt3__16vectorImNS2_9allocatorImEEEEi zOS1_ z mmi ySt16initializer_listImEi zRKNSt3__16vectorImNS2_9allocatorImEEEEi zOS1_ z 2Ev z1Ev z 5EmptyEv z4SizeEv z9 z1 {8HostSpanEv } DeviceIdxEv {SetDeviceEi 0 {3DevicePointerEv }1HostPointerEv } DeviceSpanEv {HostVectorEv } 5Const |0 |8ConstDevicePointerEv }3 }6ConstHostPointerEv ~1Host ~2 4DeviceCanWriteEv DeviceSpanEv |HostVectorEv ~ DeviceSpanEv }HostVectorEv ~ Device }ConstHostSpanEv ~ PointerEv }CanReadEv
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Json SparsePage ExtendPathEPNS_11PathElementEjffi UnwindPathEPNS_11PathElementEjj Writer ЃObject ܇String Number Reader њ 4SaveENS_4JsonE 5VisitEPKNS_
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Ԋ DummyJsonObjectEv ևLoadFeatureTypeERKNSt3__16vectorINS0_12basic_stringIcNS0_11char_traitsIcEENS0_9allocatorIcEEEENS5_IS7_EEEEPNS1_INS_11FeatureTypeENS5_ISC_EEEE GradientBooster6CreateERKNSt3__112basic_stringIcNS1_11char_traitsIcEENS1_9allocatorIcEEEEPKNS_16GenericParameterEPKNS_17LearnerModelParamE C ixE ԊaSERKNS_5ValueE 4SaveEPNS_10JsonWriterE 2EO 1EO S0_ NSt3__13mapINS1_12basic_stringIcNS1_11char_traitsIcEENS1_9allocatorIcEEEENS_4JsonENS1_4lessIS8_EENS6_INS1_4pairIKS8_S9_EEEEEE Ȋ S0_ NSt3__13mapINS1_12basic_stringIcNS1_11char_traitsIcEENS1_9allocatorIcEEEENS_4JsonENS1_4lessIS8_EENS6_INS1_4pairIKS8_S9_EEEEEE Ί RKNSt3__112basic_stringIcNS1_11char_traitsIcEENS1_9allocatorIcEEEE i đ Json ՋSparsePage12GetTransposeEi ObjecteqERKNS_5ValueE StringeqERKNS_5ValueE NumbereqERKNS_5ValueE Reader5ErrorENSt3__112basic_stringIcNS1_11char_traitsIcEENS1_9allocatorIcEEEE Ȗ ixE aSERKNS_5ValueE 4SaveEPNS_10JsonWriterE RKNSt3__112basic_stringIcNS1_11char_traitsIcEENS1_9allocatorIcEEEE i JsonArray GPUMetric15CreateGPUMetricERKNSt3__112basic_stringIcNS1_11char_traitsIcEENS1_9allocatorIcEEEEPKNS_16GenericParameterE predictor Predictor TreeParam11__MANAGER__Ev Յ C ixE ÐaSERKNS_5ValueE 4SaveEPNS_10JsonWriterE 2EOS0_ 1EOS0_ RKNSt3__112basic_stringIcNS1_11char_traitsIcEENS1_9allocatorIcEEEE i ixE aSERKNS_5ValueE Ē4SaveEPNS_10JsonWriterE ʒ RKNSt3__112basic_stringIcNS1_11char_traitsIcEENS1_9allocatorIcEEEE i ܻ Json EllpackPage ObjFunction6CreateERKNSt3__112basic_stringIcNS1_11char_traitsIcEENS1_9allocatorIcEEEEPKNS_16GenericParameterE TreeUpdater6CreateERKNSt3__112basic_stringIcNS1_11char_traitsIcEENS1_9allocatorIcEEEEPKNS_16GenericParameterE ǏLearnerImpl14kRandSeedMagicE Integer Boolean ixE aSERKNS_5ValueE 4SaveEPNS_10JsonWriterE RKNSt3__112basic_stringIcNS1_11char_traitsIcEENS1_9allocatorIcEEEE i Json EllpackPage4SizeEv IntegereqERKNS_5ValueE BooleaneqERKNS_5ValueE JsonNull ParseStrERKNSt3__112basic_stringIcNS0_11char_traitsIcEENS0_9allocatorIcEEEE MetaInfo ixE aSERKNS_5ValueE 4SaveEPNS_10JsonWriterE RKNSt3__112basic_stringIcNS1_11char_traitsIcEENS1_9allocatorIcEEEE i JsonNulleqERKNS_5ValueE MetaInfo ixE aSERKNS_5ValueE Ś4SaveEPNS_10JsonWriterE ˚ RKNSt3__112basic_stringIcNS1_11char_traitsIcEENS1_9allocatorIcEEEE i 5ParseEv 1 4LoadEv 9ParseNullEv 0 1Parse 2ParseBooleanEv 3kMaxNumLengthE SkipSpacesEv ޛParseArrayEv StringEv ObjectEv NumberEv з Json ڜdata tree ۅ 4 aSERKS0_ LoadE ŝDumpES0_PNSt3__112basic_stringIcNS1_11char_traitsIcEENS1_9allocatorIcEEEE NS_10StringViewE PNS_10JsonReaderE м Ŀ C ɟ1 9AllReduceEPNSt3__16vectorINS0_22QuantileSketchTemplateIffNS0_9WQSummaryIffEEE16SummaryContainerENS2_9allocatorIS8_EEEEPNS3_IiNS9_IiEEEE 8MakeCutsEPNS0_13HistogramCutsE 2ENSt3__16vectorImNS2_9allocatorImEEEEib 1ENSt3__16vectorImNS2_9allocatorImEEEEib 4CalcColumnSizeERKNS_10SparsePageEjm 1 6GatherSketchInfoERKNSt3__16vectorINS0_22QuantileSketchTemplateIffNS0_9WQSummaryIffEEE16SummaryContainerENS2_9allocatorIS8_EEEEPNS3_ImNS9_ImEEEESG_PNS3_INS6_5EntryENS9_ISH_EEEE LoadBalanceERKNS_10SparsePageEjm PushRowPageERKNS_10SparsePageERKNS_8MetaInfoE 2 1 ݑ6engine 5c_api9All op7ReducerINS0_ ԥ4SerializeReducerFuncImplIN7xgboost6common22QuantileSketchTemplateIffNS2_10WXQSummaryIffEEE16SummaryContainerEEEvPKvPviRKN3MPI8DatatypeE 2SerializeReduceClosureIN7xgboost6common22QuantileSketchTemplateIffNS2_10WXQSummaryIffEEE16SummaryContainerEE6InvokeEPv 3 5BitORE SumE M mEEvPKvPviRKN3MPI8DatatypeE fEEvPKvPviRKN3MPI8DatatypeE dEEvPKvPviRKN3MPI8DatatypeE cEEvPKvPviRKN3MPI8DatatypeE hEEvPKvPviRKN3MPI8DatatypeE iEEvPKvPviRKN3MPI8DatatypeE jEEvPKvPviRKN3MPI8DatatypeE lEEvPKvPviRKN3MPI8DatatypeE О axE inE mEEvPKvPviRKN3MPI8DatatypeE yEEvPKvPviRKN3MPI8DatatypeE jEEvPKvPviRKN3MPI8DatatypeE fEEvPKvPviRKN3MPI8DatatypeE ÔcEEvPKvPviRKN3MPI8DatatypeE hEEvPKvPviRKN3MPI8DatatypeE iEEvPKvPviRKN3MPI8DatatypeE lEEvPKvPviRKN3MPI8DatatypeE dEEvPKvPviRKN3MPI8DatatypeE Ĥ 5StartERKNSt3__112basic_stringIcNS2_11char_traitsIcEENS2_9allocatorIcEEEE ѫ4StopERKNSt3__112basic_stringIcNS2_11char_traitsIcEENS2_9allocatorIcEEEE 21CollectFromOtherRanksEv 15PrintStatisticsERKNSt3__13mapINS2_12basic_stringIcNS2_11char_traitsIcEENS2_9allocatorIcEEEENS2_4pairImmEENS2_4lessIS9_EENS7_INSA_IKS9_SB_EEEEEE 5PrintEv Version ݭDMatrix Learner RegTree ϋ 4 6StringERKNSt3__15tupleIJiiiEEE 8kInvalidE LoadE S ծ RKNS_4JsonE ɮPN4dmlc6StreamE Ϯ a elfEv veEPN meERKNSt3__15tupleIJiiiEEE ů S_4JsonE 4dmlc6StreamE 7xgboost S_16ParserFactoryRegI 4data19SparsePageFormatRegINS1_ 1 9MetricRegEE3GetEv 1 ϰ7CSCPageEEEE3GetEv 0SparsePageEEEE3GetEv 3SortedCSCPageEEEE3GetEv 1EllpackPageEEEE3GetEv 6CreateI D ֿ4LoadERKNSt3__112basic_stringIcNS1_11char_traitsIcEENS1_9allocatorIcEEEEbbS9_m PvS2_FvS2_EFiS2_EEEPS0_T_T0_PT1_PT2_fii ײNS_4data1 ݲ 2DenseAdapterEEEPS0_PT_fiRKNSt3__112basic_stringIcNS7_11char_traitsIcEENS7_9allocatorIcEEEEm 0CS 6DataTableAdapterEEEPS0_PT_fiRKNSt3__112basic_stringIcNS7_11char_traitsIcEENS7_9allocatorIcEEEEm ض1FileAdapterEEEPS0_PT_fiRKNSt3__112basic_stringIcNS7_11char_traitsIcEENS7_9allocatorIcEEEEm 5 RAdapterEEEPS0_PT_fiRKNSt3__112basic_stringIcNS7_11char_traitsIcEENS7_9allocatorIcEEEEm ̶CAdapterEEEPS0_PT_fiRKNSt3__112basic_stringIcNS7_11char_traitsIcEENS7_9allocatorIcEEEEm Ҷ CSRArrayAdapterEEEPS0_PT_fiRKNSt3__112basic_stringIcNS7_11char_traitsIcEENS7_9allocatorIcEEEEm ҸIteratorAdapterIPvFiS4_PFiS4_15XGBoostBatchCSRES4_ES5_EEEEPS0_PT_fiRKNSt3__112basic_stringIcNSD_11char_traitsIcEENSD_9allocatorIcEEEEm ظ 4Push 7PushCSCERKS0_ INS_4data ERKS0_ 1 21DataTableAdapterBatchEEEyRKT_fi Һ 7DenseAdapterBatchEEEyRKT_fi 5CS 6FileAdapterBatchEEEyRKT_fi غ RAdapterBatchEEEyRKT_fi ƺCAdapterBatchEEEyRKT_fi ̺ 5ClearEv 1 7SetInfoEPKc 6ExtendERKS0_b 9kNumFieldE 1 5SliceENS_6common4SpanIKiLm18446744073709551615EEE 7GetInfoEPKcPyNS_8DataTypeEPPKv 8ValidateEi 0SaveBinaryEPN4dmlc6StreamE 4GetFeatureInfoEPKcPNSt3__16vectorINS3_12basic_stringIcNS3_11char_traitsIcEENS3_9allocatorIcEEEENS8_ISA_EEEE 0LoadBinaryEPN4dmlc6StreamE 4SetFeatureInfoEPKcPS2_y Ă PKvNS_8DataTypeEm ھRKNSt3__112basic_stringIcNS3_11char_traitsIcEENS3_9allocatorIcEEEE ܭ DMatrix14GetThreadLocalEv пLearner19AllowLazyCheckPointEv RegTree 2Ev 1Ev 0Ev ̤ C D 12SetBaseRowIdEm 2E 1E v PNS_7DMatrixERKNS_10BatchParamE v PNS_7DMatrixERKNS_10BatchParamE 2Ev 1Ev 1 49__dmlc_registry_file_tag_sparse_page_raw_format__Ev 8DataPool 7 3SimpleDMatrix EllpackPageSourceC SparsePageDMatrix 2EPNS_7DMatrixERKNSt3__112basic_stringIcNS4_11char_traitsIcEENS4_9allocatorIcEEEERKNS_10BatchParamE 1EPNS_7DMatrixERKNSt3__112basic_stringIcNS4_11char_traitsIcEENS4_9allocatorIcEEEERKNS_10BatchParamE C 4InfoEv 5SliceENS_6common4SpanIKiLm18446744073709551615EEE 1 22GetSortedColumnBatchesEv 2 1 INS0_1 EPN4dmlc6StreamE 2DenseAdapterEEEPT_fi 0CS 5 6DataTableAdapterEEEPT_fi 1FileAdapterEEEPT_fi INS0_1 EPN4dmlc6StreamE 2DenseAdapterEEEPT_fi 0CS 5 6DataTableAdapterEEEPT_fi 1FileAdapterEEEPT_fi RAdapterEEEPT_fi CAdapterEEEPT_fi RAdapterEEEPT_fi CAdapterEEEPT_fi CSRArrayAdapterEEEPT_fi IteratorAdapterIPvFiS4_PFiS4_15XGBoostBatchCSRES4_ES5_EEEEPT_fi CSRArrayAdapterEEEPT_fi IteratorAdapterIPvFiS4_PFiS4_15XGBoostBatchCSRES4_ES5_EEEEPT_fi data tree17QuantileHistMaker7BuilderI 1 8DataPool5SliceENSt3__110shared_ptrINS_10SparsePageEEEmmm 3SimpleDMatrix4InfoEv 7SparsePageDMatrix4InfoEv 3GetRowBatchesEv 6GetColumnBatchesEv 7GetEllpackBatchesERKNS_10BatchParamE 5SaveToLocalFileERKNSt3__112basic_stringIcNS2_11char_traitsIcEENS2_9allocatorIcEEEE ȸ 4InfoEv 1 22GetSortedColumnBatchesEv 3GetRowBatchesEv 6GetColumnBatchesEv 7GetEllpackBatchesERKNS_10BatchParamE ؙ 14SplitWritePageEv 8FinalizeEv ̮ ܽ gbm obj 2FeatureInteractionConstraintHost 3 1 2 6GBTree 5__dmlc_registry_file_tag_gblinear__Ev 3__dmlc_registry_file_tag_gbtree__Ev 6 8GBLinearTrainParam11__MANAGER__Ev 3GBLinearModel9LoadModelERKNS_4JsonE 7GPUDartPredictIncENS_6common4SpanIfLm18446744073709551615EEES3_fmjj 4DartTrainParam11__MANAGER__Ev 1GBTreeModel LinearCheckLayerEjj GBTree 1 6GBTree 3GBLinearModel9SaveModelEPNS_4JsonE 1GBTreeModel " " 8DeprecatedGBLinearModelParam11__MANAGER__Ev 4GPUDartInplacePredictIncENS_6common4SpanIfLm18446744073709551615EEES3_fmfjj " 8GradientBoosterRegEE3GetEv 6LinearUpdaterRegEE3GetEv 2 4 0TreeGenRegEE3GetEv " " " 9 1 2 7DoBoostEPNS_7DMatrixEPNS_16HostDeviceVectorINS_6detail20GradientPairInternalIfEEEEPNS_20PredictionCacheEntryE ConfigureERKNSt3__16vectorINS2_4pairINS2_12basic_stringIcNS2_11char_traitsIcEENS2_9allocatorIcEEEESA_EENS8_ISB_EEEE LoadModelERKNS_4JsonE " 7ConfigureUpdatersEv 1 3BoostNewTreesEPNS_16HostDeviceVectorINS_6detail20GradientPairInternalIfEEEEPNS_7DMatrixEiPNSt3__16vectorINSA_10unique_ptrINS_7RegTreeENSA_14default_deleteISD_EEEENSA_9allocatorISG_EEEE 0LoadConfigERKNS_4JsonE 2PredictBatchEPNS_7DMatrixEPNS_20PredictionCacheEntryEbjj " InitUpdaterERKNSt3__16vectorINS2_4pairINS2_12basic_stringIcNS2_11char_traitsIcEENS2_9allocatorIcEEEESA_EENS8_ISB_EEEE CommitModelEONSt3__16vectorINS3_INS2_10unique_ptrINS_7RegTreeENS2_14default_deleteIS5_EEEENS2_9allocatorIS8_EEEENS9_ISB_EEEEPNS_7DMatrixEPNS_20PredictionCacheEntryE " 2ConfigureWithKnownDataERKNSt3__16vectorINS2_4pairINS2_12basic_stringIcNS2_11char_traitsIcEENS2_9allocatorIcEEEESA_EENS8_ISB_EEEEPNS_7DMatrixE 6PerformTreeMethodHeuristicEPNS_7DMatrixE " # # # # # hn SN ̇VN IN ؏ 8_N 16_N7xgboost7LearnerD 7xgboost K7xgboost3gbm6GBTree10SaveConfigEPNS_4JsonE 3gbm6GBTree10LoadConfigERKNS_4JsonE 7LearnerD # 1 9SaveModelEPNS_4JsonE 5SliceEiiiPNS_15GradientBoosterEPb 0SaveConfigEPNS_4JsonE 2GetPredictorEPKNS_16HostDeviceVectorIfEEPNS_7DMatrixE # # # # # ܉$ $ $ $ ModelParam11__MANAGER__Ev TrainParam11__MANAGER__Ev ̝$ $ ܡ$ 4SaveEPN4dmlc6StreamE 9SaveModelEPNS_4JsonE ' 4LoadEPN4dmlc6StreamE 9LoadModelERKNS_4JsonE ' ' ' GlobalConfiguration11__MANAGER__Ev PredictionContainer ' ' D 6CreateERKNSt3__16vectorINS1_10shared_ptrINS_7DMatrixEEENS1_9allocatorIS5_EEEE 2Ev 1Ev 0Ev ' ' 1Ev 0Ev ' 1Ev 0Ev ' ' ' ' ModelParamC TrainParam11__MANAGER__Ev 2ERKNS_23LearnerModelParamLegacyEf 1ERKNS_23LearnerModelParamLegacyEf ' ' 3LearnerModelParamLegacy11__MANAGER__Ev 6ParseInteractionConstraintERKNSt3__112basic_stringIcNS0_11char_traitsIcEENS0_9allocatorIcEEEEPNS0_6vectorINS9_IjNS4_IjEEEENS4_ISB_EEEE υ0LearnerConfiguration11kEvalMetricE ' ' 1 6kCpuIdE 1__MANAGER__Ev 4ConfigureGpuIdEb 2kDefaultSeedE ' ' ' + - LinearUpdater6CreateERKNSt3__112basic_stringIcNS1_11char_traitsIcEENS1_9allocatorIcEEEEPKNS_16GenericParameterE ConsoleLogger Tr GraphvizParam11__MANAGER__Ev - 1 4 6LinearTrainParam11__MANAGER__Ev 5CoordinateParam11__MANAGER__Ev - - 5__dmlc_registry_file_tag_updater_coordinate__Ev 2__dmlc_registry_file_tag_updater_shotgun__Ev - / 6CustomLogMessage3LogERKNSt3__112basic_stringIcNS1_11char_traitsIcEENS1_9allocatorIcEEEE 2 0 8TemporaryDirectory15RecursiveDeleteERKNSt3__112basic_stringIcNS1_11char_traitsIcEENS1_9allocatorIcEEEE / D 9 1 C 2Ev 1Ev / ShouldLogENS0_12LogVerbosityE ConfigureERKNSt3__16vectorINS1_4pairINS1_12basic_stringIcNS1_11char_traitsIcEENS1_9allocatorIcEEEES9_EENS7_ISA_EEEE / / ackerLoggerD eeGenerator 2Ev 1Ev / / / 6DefaultVerbosityEv 5GlobalVerbosityEv / / 2E 1E NS0_12LogVerbosityE RKNSt3__112basic_stringIcNS1_11char_traitsIcEENS1_9allocatorIcEEEEiNS0_12LogVerbosityE / NS0_12LogVerbosityE RKNSt3__112basic_stringIcNS1_11char_traitsIcEENS1_9allocatorIcEEEEiNS0_12LogVerbosityE / / / 9BinaryAUCERKNSt3__16vectorIfNS1_9allocatorIfEEEES7_S7_ 1 4 3 2 / 3 5GroupRankingAUCENS_6common4SpanIKfLm18446744073709551615EEES4_f 0RankingAUCERKNSt3__16vectorIfNS1_9allocatorIfEEEERKNS_8MetaInfoE 2GPUBinaryAUCENS_6common4SpanIKfLm18446744073709551615EEERKNS_8MetaInfoEiPNSt3__110shared_ptrINS0_14DeviceAUCCacheEEE 9GPUMultiClassAUCOVRENS_6common4SpanIKfLm18446744073709551615EEERKNS_8MetaInfoEiPNSt3__110shared_ptrINS0_14DeviceAUCCacheEEE MultiClassOVRERKNSt3__16vectorIfNS1_9allocatorIfEEEERKNS_8MetaInfoE GPURankingAUCENS_6common4SpanIKfLm18446744073709551615EEERKNS_8MetaInfoEiPNSt3__110shared_ptrINS0_14DeviceAUCCacheEEE / / / 0 0 0 5__ 4__dmlc_registry_file_tag_multiclass_metric__Ev 2__dmlc_registry_file_tag_survival_metric__Ev dmlc_registry_file_tag_elementwise_metric__Ev make_MetricReg_IntervalRegressionAccuracy__E 0 0 2 2 ܣ2 MetricGPURegEE3GetEv PredictorRegEE3GetEv 2 2 8__dmlc_registry_file_tag_rank_metric__Ev 2__make_MetricReg_ 5__make_MetricReg_PossionNegLoglik__E 1__make_MetricReg_ 3__make_MetricReg_TweedieNLogLik__E 2 4 3 41__dmlc_registry_file_tag_ 22 1 9ListEntry7CmpPredERKS1_S3_ 4__dmlc_registry_file_tag_aft_obj__Ev 6__dmlc_registry_file_tag_hinge_obj__Ev 5__dmlc_registry_file_tag_rank_obj__Ev 5 6 multiclass_obj__Ev regression_obj__Ev 6 SoftmaxMultiClassParam11__MANAGER__Ev PoissonRegressionParam11__MANAGER__Ev TweedieRegressionParam11__MANAGER__Ev 6 ObjFunctionRegEE3GetEv TreeUpdaterRegEE3GetEv 7 7 7 5LambdaRankParam11__MANAGER__Ev 2RegLossParam11__MANAGER__Ev 7 8 9 9 9 9 40__dmlc_registry_file_tag_cpu_predictor__Ev ܁9PredValueERKNS_6common4SpanIKNS_5EntryELm18446744073709551615EEERKNSt3__16vectorINS8_10unique_ptrINS_7RegTreeENS8_14default_deleteISB_EEEENS8_9allocatorISE_EEEERKNS9_IiNSF_IiEEEEiPNSB_4FVecEjj = = ? 19ClearExpiredEntriesEv 5 9ContainerEv ? CacheENSt3__110shared_ptrINS_7DMatrixEEEi EntryEPNS_7DMatrixE ? ? ? 9ConfigureERKNSt3__16vectorINS1_4pairINS1_12basic_stringIcNS1_11char_traitsIcEENS1_9allocatorIcEEEES9_EENS7_ISA_EEEE ބ6CreateERKNSt3__112basic_stringIcNS1_11char_traitsIcEENS1_9allocatorIcEEEEPKNS_16GenericParameterE ? ? 9 5ResetEv ConfigureERKNS_4tree10TrainParamEj SplitImplEijii Å ? ? @ @ @ @ 1 4 ͏22CPUHistMakerTrainParam11__MANAGER__Ev 39__dmlc_registry_file_tag_updater_sync__Ev 0TrainParam11__MANAGER__Ev 8ColMakerTrainParam11__MANAGER__Ev ё7QuantileHistMaker Ք @ @ 6CreateERKNSt3__112basic_stringIcNS1_11char_traitsIcEENS1_9allocatorIcEEEERKNS_10FeatureMapEb 5MatchERKNSt3__112basic_stringIcNS1_11char_traitsIcEENS1_9allocatorIcEEEERKNS1_3mapIS7_S7_NS1_4lessIS7_EENS5_INS1_4pairIS8_S7_EEEEEE @ @ 9 5EqualERKS0_ 1 4SaveEPN4dmlc6StreamE 2 8TreeShapERKNS0_4FVecEPfjjPNS_11PathElementEffiijf DumpModelERKNS_10FeatureMapEbNSt3__112basic_stringIcNS4_11char_traitsIcEENS4_9allocatorIcEEEE SaveModelEPNS_4JsonE @ @ 2GetNumLeavesEv Ë6GetNumSplitNodesEv ɋ @ @ 1 4LoadEPN4dmlc6StreamE 20LoadCategoricalSplitERKNS_4JsonE 9LoadModelERKNS_4JsonE 5kRootE 0ExpandNodeEijfbfffffffi 7 8FillNodeMeanValuesEv A ExpandCategoricalEijNS_6common4SpanIjLm18446744073709551615EEEbfffffff ߍFillNodeMeanValueEi A A A A 0SaveCategoricalSplitEPNS_4JsonE 8CalculateContributionsApproxERKNS0_4FVecEPf 2CalculateContributionsERKNS0_4FVecEPfij A A B B B B B B B B B E G G 3__dmlc_registry_file_tag_updater_colmaker__Ev ˑ4__dmlc_registry_file_tag_updater_histmaker__Ev ב0__dmlc_registry_file_tag_updater_prune__Ev ϔ8__dmlc_registry_file_tag_updater_quantile_hist__Ev 2__dmlc_registry_file_tag_updater_refresh__Ev G G J 5ReducerSafeImplIN7xgboost 2InvokeLambdaEPv ɔ6ReducerAlignImplIN7xgboost6detail20GradientPairInternalIfEEXadL_ZNS4_6ReduceERS4_RKS4_EEEEvPKvPviRKN3MPI8DatatypeE 4tree9GradStatsEXadL_ZNS3_6ReduceERS3_RKS3_EEEEvPKvPviRKN3MPI8DatatypeE 6detail20GradientPairInternalIdEEXadL_ZNS4_6ReduceERS4_RKS4_EEEEvPKvPviRKN3MPI8DatatypeE J J L L L ܨM 7BuilderI 9ConfigureERKNSt3__16vectorINS2_4pairINS2_12basic_stringIcNS2_11char_traitsIcEENS2_9allocatorIcEEEESA_EENS8_ISB_EEEE 6UpdateEPNS_16HostDeviceVectorINS_6detail20GradientPairInternalIfEEEEPNS_7DMatrixERKNSt3__16vectorIPNS_7RegTreeENSA_9allocatorISD_EEEE 21UpdatePredictionCacheEPKNS_7DMatrixEPNS_16HostDeviceVectorIfEE 31UpdatePredictionCacheMulticlassEPKNS_7DMatrixEPNS_16HostDeviceVectorIfEEii fE dE C 6UpdateERKNS_6common16GHistIndexMatrixERKNS4_21GHistIndexBlockMatrixERKNS4_12ColumnMatrixEPNS_16HostDeviceVectorINS_6detail20GradientPairInternalIfEEEEPNS_7DMatrixEPNS_7RegTreeE 8InitDataERKNS_6common16GHistIndexMatrixERKNSt3__16vectorINS_6detail20GradientPairInternalIfEENS8_9allocatorISC_EEEERKNS_7DMatrixERKNS_7RegTreeE 1 9 2 2ERKNS0_10TrainParamENSt3__110unique_ptrINS_11TreeUpdaterENS7_14default_deleteIS9_EEEENS_32FeatureInteractionConstraintHostEPKNS_7DMatrixE 1ERKNS0_10TrainParamENSt3__110unique_ptrINS_11TreeUpdaterENS7_14default_deleteIS9_EEEENS_32FeatureInteractionConstraintHostEPKNS_7DMatrixE M M M M 9 6S 1 î2InitSamplingERKNSt3__16vectorINS_6detail20GradientPairInternalIfEENS4_9allocatorIS8_EEEERKNS_7DMatrixEPNS5_ImNS9_ImEEEE 4 0ApplySplitENSt3__16vectorINS3_11ExpandEntryENS4_9allocatorIS6_EEEERKNS_6common16GHistIndexMatrixERKNSA_12ColumnMatrixERKNSA_14HistCollectionIfEEPNS_7RegTreeE 7AddSplitsToRowSetERKNSt3__16vectorINS3_11ExpandEntryENS4_9allocatorIS6_EEEEPNS_7RegTreeE ³3SplitSiblingsERKNSt3__16vectorINS3_11ExpandEntryENS4_9allocatorIS6_EEEEPS9_SC_PNS_7RegTreeE Գ5 ExpandWith SetHistSynchronizerEPNS0_16HistSynchronizerIfEE FindSplitConditionsERKNSt3__16vectorINS3_11ExpandEntryENS4_9allocatorIS6_EEEERKNS_7RegTreeERKNS_6common16GHistIndexMatrixEPNS5_IiNS7_IiEEEE LossGuideERKNS_6common16GHistIndexMatrixERKNS4_21GHistIndexBlockMatrixERKNS4_12ColumnMatrixEPNS_7DMatrixEPNS_7RegTreeERKNSt3__16vectorINS_6detail20GradientPairInternalIfEENSI_9allocatorISM_EEEE DepthWiseERKNS_6common16GHistIndexMatrixERKNS4_21GHistIndexBlockMatrixERKNS4_12ColumnMatrixEPNS_7DMatrixEPNS_7RegTreeERKNSt3__16vectorINS_6detail20GradientPairInternalIfEENSI_9allocatorISM_EEEE N N BuildHistERKNSt3__16vectorINS_6detail20GradientPairInternalIfEENS4_9allocatorIS8_EEEENS_6common16RowSetCollection4ElemERKNSE_16GHistIndexMatrixERKNSE_21GHistIndexBlockMatrixENSE_4SpanIS8_Lm18446744073709551615EEE LossGuideENS3_11ExpandEntryES4_ ̣N ubtractionTrickENS_6common4SpanINS_6detail20GradientPairInternalIfEELm18446744073709551615EEES9_S9_ etHistRowsAdderEPNS0_13HistRowsAdderIfEE N 1UpdatePredictionCacheEPKNS_7DMatrixEPNS_16HostDeviceVectorIfEEii 6SplitContainsMissingValuesENS0_9GradStatsERKNS1_9NodeEntryE γ0BuildLocalHistogramsERKNS_6common16GHistIndexMatrixERKNS4_21GHistIndexBlockMatrixEPNS_7RegTreeERKNSt3__16vectorINS_6detail20GradientPairInternalIfEENSD_9allocatorISH_EEEE ڳ2EvaluateAndApplySplitsERKNS_6common16GHistIndexMatrixERKNS4_12ColumnMatrixEPNS_7RegTreeEPiiPjPNSt3__16vectorINS3_11ExpandEntryENSF_9allocatorISH_EEEE 4BuildHistogramsLossGuideENS3_11ExpandEntryERKNS_6common16GHistIndexMatrixERKNS5_21GHistIndexBlockMatrixEPNS_7RegTreeERKNSt3__16vectorINS_6detail20GradientPairInternalIfEENSE_9allocatorISI_EEEE N N N ExpandEntryC InitNewNodeEiRKNS_6common16GHistIndexMatrixERKNSt3__16vectorINS_6detail20GradientPairInternalIfEENS8_9allocatorISC_EEEERKNS_7DMatrixERKNS_7RegTreeE ȳ 2Eiiifj 1Eiiifj N ķN fE11ExpandEntry7IsValidERKNS0_10TrainParamEi dE11ExpandEntry7IsValidERKNS0_10TrainParamEi طN N N EvaluateSplitsERKNSt3__16vectorINS3_11ExpandEntryENS4_9allocatorIS6_EEEERKNS_6common16GHistIndexMatrixERKNSC_14HistCollectionIfEERKNS_7RegTreeE BuildNodeStatsERKNS_6common16GHistIndexMatrixEPNS_7DMatrixEPNS_7RegTreeERKNSt3__16vectorINS_6detail20GradientPairInternalIfEENSC_9allocatorISG_EEEE N N N N O O O ܞO O ȧO O AddSplitsToTreeERKNS_6common16GHistIndexMatrixEPNS_7RegTreeEPiiPjPNSt3__16vectorINS3_11ExpandEntryENSC_9allocatorISE_EEEESI_ PartitionKernelI O C 6UpdateERKNS_6common16GHistIndexMatrixERKNS4_21GHistIndexBlockMatrixERKNS4_12ColumnMatrixEPNS_16HostDeviceVectorINS_6detail20GradientPairInternalIfEEEEPNS_7DMatrixEPNS_7RegTreeE 8InitDataERKNS_6common16GHistIndexMatrixERKNSt3__16vectorINS_6detail20GradientPairInternalIfEENS8_9allocatorISC_EEEERKNS_7DMatrixERKNS_7RegTreeE 1 9 2 2ERKNS0_10TrainParamENSt3__110unique_ptrINS_11TreeUpdaterENS7_14default_deleteIS9_EEEENS_32FeatureInteractionConstraintHostEPKNS_7DMatrixE 1ERKNS0_10TrainParamENSt3__110unique_ptrINS_11TreeUpdaterENS7_14default_deleteIS9_EEEENS_32FeatureInteractionConstraintHostEPKNS_7DMatrixE O O O O 9 6S 1 2InitSamplingERKNSt3__16vectorINS_6detail20GradientPairInternalIfEENS4_9allocatorIS8_EEEERKNS_7DMatrixEPNS5_ImNS9_ImEEEE 4 0ApplySplitENSt3__16vectorINS3_11ExpandEntryENS4_9allocatorIS6_EEEERKNS_6common16GHistIndexMatrixERKNSA_12ColumnMatrixERKNSA_14HistCollectionIdEEPNS_7RegTreeE 7AddSplitsToRowSetERKNSt3__16vectorINS3_11ExpandEntryENS4_9allocatorIS6_EEEEPNS_7RegTreeE 3SplitSiblingsERKNSt3__16vectorINS3_11ExpandEntryENS4_9allocatorIS6_EEEEPS9_SC_PNS_7RegTreeE 5 ExpandWith SetHistSynchronizerEPNS0_16HistSynchronizerIdEE FindSplitConditionsERKNSt3__16vectorINS3_11ExpandEntryENS4_9allocatorIS6_EEEERKNS_7RegTreeERKNS_6common16GHistIndexMatrixEPNS5_IiNS7_IiEEEE LossGuideERKNS_6common16GHistIndexMatrixERKNS4_21GHistIndexBlockMatrixERKNS4_12ColumnMatrixEPNS_7DMatrixEPNS_7RegTreeERKNSt3__16vectorINS_6detail20GradientPairInternalIfEENSI_9allocatorISM_EEEE DepthWiseERKNS_6common16GHistIndexMatrixERKNS4_21GHistIndexBlockMatrixERKNS4_12ColumnMatrixEPNS_7DMatrixEPNS_7RegTreeERKNSt3__16vectorINS_6detail20GradientPairInternalIfEENSI_9allocatorISM_EEEE ܁P P BuildHistERKNSt3__16vectorINS_6detail20GradientPairInternalIfEENS4_9allocatorIS8_EEEENS_6common16RowSetCollection4ElemERKNSE_16GHistIndexMatrixERKNSE_21GHistIndexBlockMatrixENSE_4SpanINS7_IdEELm18446744073709551615EEE LossGuideENS3_11ExpandEntryES4_ ĞP ubtractionTrickENS_6common4SpanINS_6detail20GradientPairInternalIdEELm18446744073709551615EEES9_S9_ etHistRowsAdderEPNS0_13HistRowsAdderIdEE ܟP 1UpdatePredictionCacheEPKNS_7DMatrixEPNS_16HostDeviceVectorIfEEii 6SplitContainsMissingValuesENS0_9GradStatsERKNS1_9NodeEntryE 0BuildLocalHistogramsERKNS_6common16GHistIndexMatrixERKNS4_21GHistIndexBlockMatrixEPNS_7RegTreeERKNSt3__16vectorINS_6detail20GradientPairInternalIfEENSD_9allocatorISH_EEEE 2EvaluateAndApplySplitsERKNS_6common16GHistIndexMatrixERKNS4_12ColumnMatrixEPNS_7RegTreeEPiiPjPNSt3__16vectorINS3_11ExpandEntryENSF_9allocatorISH_EEEE 4BuildHistogramsLossGuideENS3_11ExpandEntryERKNS_6common16GHistIndexMatrixERKNS5_21GHistIndexBlockMatrixEPNS_7RegTreeERKNSt3__16vectorINS_6detail20GradientPairInternalIfEENSE_9allocatorISI_EEEE P P P ExpandEntryC InitNewNodeEiRKNS_6common16GHistIndexMatrixERKNSt3__16vectorINS_6detail20GradientPairInternalIfEENS8_9allocatorISC_EEEERKNS_7DMatrixERKNS_7RegTreeE 2Eiiifj 1Eiiifj P P вP P P EvaluateSplitsERKNSt3__16vectorINS3_11ExpandEntryENS4_9allocatorIS6_EEEERKNS_6common16GHistIndexMatrixERKNSC_14HistCollectionIdEERKNS_7RegTreeE BuildNodeStatsERKNS_6common16GHistIndexMatrixEPNS_7DMatrixEPNS_7RegTreeERKNSt3__16vectorINS_6detail20GradientPairInternalIfEENSC_9allocatorISG_EEEE P P P P P P P Q ȋQ Q Q AddSplitsToTreeERKNS_6common16GHistIndexMatrixEPNS_7RegTreeEPiiPjPNSt3__16vectorINS3_11ExpandEntryENSC_9allocatorISE_EEEESI_ PartitionKernelI Q hEEvmmNS_6common7Range1dEiRKNS5_12ColumnMatrixERKNS_7RegTreeE tEEvmmNS_6common7Range1dEiRKNS5_12ColumnMatrixERKNS_7RegTreeE jEEvmmNS_6common7Range1dEiRKNS5_12ColumnMatrixERKNS_7RegTreeE Q Q Q hEEvmmNS_6common7Range1dEiRKNS5_12ColumnMatrixERKNS_7RegTreeE tEEvmmNS_6common7Range1dEiRKNS5_12ColumnMatrixERKNS_7RegTreeE jEEvmmNS_6common7Range1dEiRKNS5_12ColumnMatrixERKNS_7RegTreeE Q Q Q Q Q Q ̃R R R T U V V 1 4InitEiPPc 8FinalizeEv 9 3AllreduceBase 0Allreduce_EPvmmPFvPKvS1_iRKN3MPI8DatatypeEENS0_3mpi8DataTypeENSA_6OpTypeEPFvS1_ES1_ 2ReduceHandle C 4InitEiPPc 1 8S 20TryReduceScatterRingEPvmmPFvPKvS2_iRKN3MPI8DatatypeEE 2Ev 1Ev V W W 4ReConnectLinksEPKc 2Tr 6TryAll ԞW hutdownEv etParamEPKcS3_ W W ackerPrintERKNSt3__112basic_stringIcNS2_11char_traitsIcEENS2_9allocatorIcEEEE y W W AllreduceEPvmmPFvPKvS2_iRKN3MPI8DatatypeEE BroadcastEPvmi X reduce gatherRingEPvmmmm RingEPvmmPFvPKvS2_iRKN3MPI8DatatypeEE TreeEPvmmPFvPKvS2_iRKN3MPI8DatatypeEE X ЅX X X ̼X reduceEPvmNS_6engine3mpi8DataTypeENS3_6OpTypeEPFvS1_ES1_ gatherEPvmmmmi X X I Finalize Get TrackerPrint Broadcast All L CheckPoint VersionNumber nit sDistributed X X R WorldSize ProcessorName ingPrevRank ank X X X X X X X gather reduce X X oadCheckPoint inkTag X X X X Y Y ؆Y Y Y cEEvPKvPviRKN3MPI8DatatypeE hEEvPKvPviRKN3MPI8DatatypeE iEEvPKvPviRKN3MPI8DatatypeE jEEvPKvPviRKN3MPI8DatatypeE lEEvPKvPviRKN3MPI8DatatypeE mEEvPKvPviRKN3MPI8DatatypeE fEEvPKvPviRKN3MPI8DatatypeE dEEvPKvPviRKN3MPI8DatatypeE Y Y Y ȔY ЖY Y Y Y Y Y Y آY Y cEEvPKvPviRKN3MPI8DatatypeE hEEvPKvPviRKN3MPI8DatatypeE iEEvPKvPviRKN3MPI8DatatypeE jEEvPKvPviRKN3MPI8DatatypeE lEEvPKvPviRKN3MPI8DatatypeE mEEvPKvPviRKN3MPI8DatatypeE Y Y Y ԨY Y Y Y ܮY GetEngineEv AllgatherEPvmmmm Y Y ijY C D 8TypeSizeERKN3MPI8DatatypeE 4InitEPFvPKvPviRKN3MPI8DatatypeEEm 9AllreduceEPvmmPFvS2_ES2_ 2Ev 1Ev Y Y 2Ev 1Ev Y ĴY ȴY дY Y 7 6LibFMParserParam11__MANAGER__Ev 4CSVParserParam11__MANAGER__Ev 8CreateLibSVMParserI 5CreateCSVParserI LibSVMParserParam11__MANAGER__Ev CreateLibFMParserI ضY Y Y RowBlockIterI ThreadedIterINS_2io14InputSplitBase5ChunkEE14NotImplementedEv j y fE6CreateEPKcjjS3_ iE6CreateEPKcjjS3_ xE6CreateEPKcjjS3_ Y fE6CreateEPKcjjS3_ iE6CreateEPKcjjS3_ xE6CreateEPKcjjS3_ Y Y Y Y Y ParserI Stream6CreateEPKcS2_b j y fE6CreateEPKcjjS3_ iE6CreateEPKcjjS3_ xE6CreateEPKcjjS3_ Y fE6CreateEPKcjjS3_ iE6CreateEPKcjjS3_ xE6CreateEPKcjjS3_ Y Y Y Z Z j y fEEE3GetEv iEEE3GetEv xEEE3GetEv ԚZ Z Z fEEE3GetEv iEEE3GetEv xEEE3GetEv Z Z Z jfEEPNS_6ParserIT_fEERKNSt3__112basic_stringIcNS6_11char_traitsIcEENS6_9allocatorIcEEEERKNS6_3mapISC_SC_NS6_4lessISC_EENSA_INS6_4pairISD_SC_EEEEEEjj yfEEPNS_6ParserIT_fEERKNSt3__112basic_stringIcNS6_11char_traitsIcEENS6_9allocatorIcEEEERKNS6_3mapISC_SC_NS6_4lessISC_EENSA_INS6_4pairISD_SC_EEEEEEjj Z İZ jfEEPNS_6ParserIT_fEERKNSt3__112basic_stringIcNS6_11char_traitsIcEENS6_9allocatorIcEEEERKNS6_3mapISC_SC_NS6_4lessISC_EENSA_INS6_4pairISD_SC_EEEEEEjj yfEEPNS_6ParserIT_fEERKNSt3__112basic_stringIcNS6_11char_traitsIcEENS6_9allocatorIcEEEERKNS6_3mapISC_SC_NS6_4lessISC_EENSA_INS6_4pairISD_SC_EEEEEEjj Z Z j y fEEPNS_6ParserIT_T0_EERKNSt3__112basic_stringIcNS7_11char_traitsIcEENS7_9allocatorIcEEEERKNS7_3mapISD_SD_NS7_4lessISD_EENSB_INS7_4pairISE_SD_EEEEEEjj iEEPNS_6ParserIT_T0_EERKNSt3__112basic_stringIcNS7_11char_traitsIcEENS7_9allocatorIcEEEERKNS7_3mapISD_SD_NS7_4lessISD_EENSB_INS7_4pairISE_SD_EEEEEEjj xEEPNS_6ParserIT_T0_EERKNSt3__112basic_stringIcNS7_11char_traitsIcEENS7_9allocatorIcEEEERKNS7_3mapISD_SD_NS7_4lessISD_EENSB_INS7_4pairISE_SD_EEEEEEjj Z fEEPNS_6ParserIT_T0_EERKNSt3__112basic_stringIcNS7_11char_traitsIcEENS7_9allocatorIcEEEERKNS7_3mapISD_SD_NS7_4lessISD_EENSB_INS7_4pairISE_SD_EEEEEEjj iEEPNS_6ParserIT_T0_EERKNSt3__112basic_stringIcNS7_11char_traitsIcEENS7_9allocatorIcEEEERKNS7_3mapISD_SD_NS7_4lessISD_EENSB_INS7_4pairISE_SD_EEEEEEjj xEEPNS_6ParserIT_T0_EERKNSt3__112basic_stringIcNS7_11char_traitsIcEENS7_9allocatorIcEEEERKNS7_3mapISD_SD_NS7_4lessISD_EENSB_INS7_4pairISE_SD_EEEEEEjj Z Z Z Z Z 1 23IndexedRecordIOSplitter 0FileSystem 2LineSplitter1 6RecordIOSplitter1 4InputSplitBase 5LocalFileSystem 11GetInstanceERKNS0_3URIE 22ListDirectoryRecursiveERKNS0_3URIEPNSt3__16vectorINS0_8FileInfoENS5_9allocatorIS7_EEEE e InputSplit6CreateEPKc SeekStream13CreateForReadEPKcb jjS2_ S2_jjS2_bimb e e e e ğg 5SeekRecordBeginEPNS_6StreamE 9FindLastRecordBeginEPKcS3_ 7ExtractNextRecordEPNS_10InputSplit4BlobEPNS0_14InputSplitBase5ChunkE g g g 5SeekRecordBeginEPNS_6StreamE 9FindLastRecordBeginEPKcS3_ 7ExtractNextRecordEPNS_10InputSplit4BlobEPNS0_14InputSplitBase5ChunkE g ԯg g 1 9 4ResetPartitionEjj 3ReadIndexFileEPNS0_10FileSystemERKNSt3__112basic_stringIcNS4_11char_traitsIcEENS4_9allocatorIcEEEE 5SeekRecordBeginEPNS_6StreamE 9FindLastRecordBeginEPKcS3_ 7ExtractNextRecordEPNS_10InputSplit4BlobEPNS0_14InputSplitBase5ChunkE 1 g g g g g ReadChunkEPvPm Next g ChunkEPNS_10InputSplit4BlobE BatchEPNS_10InputSplit4BlobEm g NextBatchExEPNS0_14InputSplitBase5ChunkEm ڀBeforeFirstEv g g g 4 1 D 8StripEndENSt3__112basic_stringIcNS2_11char_traitsIcEENS2_9allocatorIcEEEEc 9ReadChunkEPvPm 5Chunk InitEPNS0_10FileSystemEPKcmb ReadEPvm g 7InitInputFileInfoERKNSt3__112basic_stringIcNS2_11char_traitsIcEENS2_9allocatorIcEEEEb 4ResetPartitionEjj 1BeforeFirstEv 3ConvertToURIsERKNSt3__112basic_stringIcNS2_11char_traitsIcEENS2_9allocatorIcEEEE 6ExtractNextChunkEPNS_10InputSplit4BlobEPNS1_5ChunkE g h h 2Ev ׄ1Ev ݄0Ev ̋h ԍh ؍h ܍h h h h 4LoadEPS1_m 6AppendEPS1_m h h h k Эk 1 4OpenERKNS0_3URIEPKcb 1 3ListDirectoryERKNS0_3URIEPNSt3__16vectorINS0_8FileInfoENS5_9allocatorIS7_EEEE GetPathInfoERKNS0_3URIE OpenForReadERKNS0_3URIEb k k k k 8kFloatPow5InvSplitE 5kFloatPow5SplitE v v v 7xgboost 5rabit6engine13AllreduceBaseE 4dmlc2io 6common1 1 9 щ8JsonNullE 7 Ŋ4 3gbm ϋ 6PeekableInStreamE 5FixedSizeStreamE v v v 0Json 1Json StringE ˉObjectE NumberE ReaderE WriterE v JsonArrayE PredictorE мv v v IntegerE BooleanE v v v v v v v DMatrixE LearnerE RegTreeE v data1 tree17QuantileHistMaker Č 3SimpleDMatrixE Ë7SparsePageDMatrixE ɋ v v 1 6GBTreeE 3GBLinearModelE 1GBTreeModelE v v v v v v v w w w E ،7BuilderI ތ w fEE dEE w w w 1 23IndexedRecordIOSplitterE 2LineSplitterE 6RecordIOSplitterE 4InputSplitBaseE 0FileSystemE 5LocalFileSystemE x x ܜx x x x 7xgboost 5rabit6engine13AllreduceBaseE 4dmlc2io 6common1 1 9 ב8JsonNullE ʓ7 4 Ҕ3gbm 5FixedSizeStreamE ̏6PeekableInStreamE ҏ ~ ~ 7xgboost 5rabit6engine13AllreduceBaseE 4dmlc2io љ 6common1 ː1 9 Ԓ8JsonNullE Г7 4 3gbm ͖ 6PeekableInStreamE 5FixedSizeStreamE ~ ~ 0Json 1Json ObjectE ёStringE NumberE ReaderE WriterE ~ JsonArrayE PredictorE ~ ~ 0Json 1Json StringE ΒObjectE NumberE ReaderE WriterE ~ JsonArrayE PredictorE ~ ~ ~ ~ IntegerE BooleanE ֓ ~ IntegerE ēBooleanE ܓ ~ ~ ~ ~ ~ ~ ~ ~ ~ DMatrixE LearnerE RegTreeE ~ DMatrixE ̔LearnerE RegTreeE ~ data1 tree17QuantileHistMaker ȗ 3SimpleDMatrixE 7SparsePageDMatrixE ~ data1 Еtree17QuantileHistMaker 3SimpleDMatrixE 7SparsePageDMatrixE ~ ~ ~ 1 6GBTreeE 3GBLinearModelE ǖ1GBTreeModelE ~ 1 6GBTreeE 3GBLinearModelE 1GBTreeModelE ~ ~ ~ ~ 7BuilderI ܗE fEE dEE E 7BuilderI fEE dEE 1 23IndexedRecordIOSplitterE 2LineSplitterE ʙ6RecordIOSplitterE 4InputSplitBaseE 0FileSystemE 5LocalFileSystemE 1 23IndexedRecordIOSplitterE 2LineSplitterE ٚ6RecordIOSplitterE 4InputSplitBaseE 0FileSystemE 5LocalFileSystemE Ѐ Ѐ р р Ҁ Ҁ Ԁ 1 3any8TypeInfoINSt3__110shared_ptrIN7xgboost4data1 2io15LocalFileSystem11GetInstanceEvE8instance 5LogMessageFatal5Entry11ThreadLocalEvE6result ܜ6ThreadLocalStoreI VZN RZN7xgboost13TextGenerator9BuildTreeERKNS_7RegTreeEE13kTreeTemplate_ 4dmlc ؝7xgboost ©K7xgboost 1 Ş3any8TypeInfoINSt3__110shared_ptrIN7xgboost4data1 Ϫ2io15LocalFileSystem11GetInstanceEvE8instance 5LogMessageFatal5Entry11ThreadLocalEvE6result 6ThreadLocalStoreI ϡИ N 16XGBAPIErrorEntryE3GetEvE4inst 7xgboost St3__13mapIPKN7xgboost7 5rabit6engine16ThreadLocalEntryEE3GetEvE4inst 19 22XGBAPIThreadLocalEntryEE3GetEvE4inst 6common22RandomThreadLocalEntryEE3GetEvE4inst LogCallbackRegistryEE3GetEvE4inst ȡGlobalConfigurationEE3GetEvE4inst ޣ蘁 N 16XGBAPIErrorEntryE3GetEvE4inst 7xgboost ӢSt3__13mapIPKN7xgboost7 5rabit6engine16ThreadLocalEntryEE3GetEvE4inst 19LogCallbackRegistryEE3GetEvE4inst ף22XGBAPIThreadLocalEntryEE3GetEvE4inst 6common22RandomThreadLocalEntryEE3GetEvE4inst ș DMatrixENS3_22XGBAPIThreadLocalEntryENS1_4lessIS6_EENS1_9allocatorINS1_4pairIKS6_S7_EEEEEEE3GetEvE4inst LearnerENS3_ DMatrixENS3_22XGBAPIThreadLocalEntryENS1_4lessIS6_EENS1_9allocatorINS1_4pairIKS6_S7_EEEEEEE3GetEvE4inst LearnerENS3_ ؚۧ 19PredictionContainerENS1_4lessIS6_EENS1_9allocatorINS1_4pairIKS6_S7_EEEEEEE3GetEvE4inst ԧ22XGBAPIThreadLocalEntryENS1_4lessIS6_EENS1_9allocatorINS1_4pairIKS6_S7_EEEEEEE3GetEvE4inst 19PredictionContainerENS1_4lessIS6_EENS1_9allocatorINS1_4pairIKS6_S7_EEEEEEE3GetEvE4inst 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__ZN4dmlc4data14TextParserBaseIyfE8FillDataEPNSt3__16vectorINS0_17RowBlockContainerIyfEENS3_9allocatorIS6_EEEE.cold.1 __ZN4dmlc4data14TextParserBaseIyfE8FillDataEPNSt3__16vectorINS0_17RowBlockContainerIyfEENS3_9allocatorIS6_EEEE.cold.2 __ZN4dmlc4data14ThreadedParserIyfEC2EPNS0_10ParserImplIyfEE.cold.1 __ZN4dmlc4data14ThreadedParserIyfEC2EPNS0_10ParserImplIyfEE.cold.2 __ZN4dmlc4data14ThreadedParserIyfEC2EPNS0_10ParserImplIyfEE.cold.3 __ZNSt3__16threadC2IRZN4dmlc12ThreadedIterINS_6vectorINS2_4data17RowBlockContainerIyfEENS_9allocatorIS7_EEEEE4InitENS_8functionIFbPPSA_EEENSC_IFvvEEEEUlvE_JEvEEOT_DpOT0_.cold.1 __ZNSt3__16threadC2IRZN4dmlc12ThreadedIterINS_6vectorINS2_4data17RowBlockContainerIyfEENS_9allocatorIS7_EEEEE4InitENS_8functionIFbPPSA_EEENSC_IFvvEEEEUlvE_JEvEEOT_DpOT0_.cold.2 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__ZN4dmlc4data14TextParserBaseIyiE8FillDataEPNSt3__16vectorINS0_17RowBlockContainerIyiEENS3_9allocatorIS6_EEEE.cold.2 __ZN4dmlc4data14TextParserBaseIjxEC2EPNS_10InputSplitEi.cold.1 __ZN4dmlc4data14TextParserBaseIjxED2Ev.cold.1 __ZN4dmlc4data14TextParserBaseIjxE8FillDataEPNSt3__16vectorINS0_17RowBlockContainerIjxEENS3_9allocatorIS6_EEEE.cold.1 __ZN4dmlc4data14TextParserBaseIjxE8FillDataEPNSt3__16vectorINS0_17RowBlockContainerIjxEENS3_9allocatorIS6_EEEE.cold.2 __ZN4dmlc4data14TextParserBaseIyxEC2EPNS_10InputSplitEi.cold.1 __ZN4dmlc4data14TextParserBaseIyxED2Ev.cold.1 __ZN4dmlc4data14TextParserBaseIyxE8FillDataEPNSt3__16vectorINS0_17RowBlockContainerIyxEENS3_9allocatorIS6_EEEE.cold.1 __ZN4dmlc4data14TextParserBaseIyxE8FillDataEPNSt3__16vectorINS0_17RowBlockContainerIyxEENS3_9allocatorIS6_EEEE.cold.2 __ZN4dmlc6Stream6CreateEPKcS2_b.cold.1 __ZN4dmlc10SeekStream13CreateForReadEPKcb.cold.1 __ZN4dmlc2io18ThreadedInputSplitC2EPNS0_14InputSplitBaseEm.cold.1 __ZN4dmlc2io18ThreadedInputSplitC2EPNS0_14InputSplitBaseEm.cold.2 __ZNSt3__16threadC2IRZN4dmlc12ThreadedIterINS2_2io14InputSplitBase5ChunkEE4InitENS_8functionIFbPPS6_EEENS8_IFvvEEEEUlvE_JEvEEOT_DpOT0_.cold.1 __ZNSt3__16threadC2IRZN4dmlc12ThreadedIterINS2_2io14InputSplitBase5ChunkEE4InitENS_8functionIFbPPS6_EEENS8_IFvvEEEEUlvE_JEvEEOT_DpOT0_.cold.2 __ZNSt3__1L14__thread_proxyINS_5tupleIJNS_10unique_ptrINS_15__thread_structENS_14default_deleteIS3_EEEEZN4dmlc12ThreadedIterINS7_2io14InputSplitBase5ChunkEE4InitENS_8functionIFbPPSB_EEENSD_IFvvEEEEUlvE_EEEEEPvSM_.cold.1 __ZN4dmlc12ThreadedIterINS_2io14InputSplitBase5ChunkEED2Ev.cold.1 __ZN4dmlc2io16CachedInputSplit14InitCachedIterEv.cold.1 __ZN4dmlc2io16CachedInputSplit14InitCachedIterEv.cold.2 __ZN4dmlc2io16CachedInputSplit15InitPreprocIterEv.cold.1 __ZN4dmlc2io16CachedInputSplit15InitPreprocIterEv.cold.2 __ZN4dmlc2io23IndexedRecordIOSplitter13ReadIndexFileEPNS0_10FileSystemERKNSt3__112basic_stringIcNS4_11char_traitsIcEENS4_9allocatorIcEEEE.cold.1 __ZN4dmlc2io14InputSplitBase17InitInputFileInfoERKNSt3__112basic_stringIcNS2_11char_traitsIcEENS2_9allocatorIcEEEEb.cold.1 __ZN4dmlc2io14InputSplitBase17InitInputFileInfoERKNSt3__112basic_stringIcNS2_11char_traitsIcEENS2_9allocatorIcEEEEb.cold.2 __ZN4dmlc5SplitERKNSt3__112basic_stringIcNS0_11char_traitsIcEENS0_9allocatorIcEEEEc.cold.1 __ZNSt3__111basic_regexIcNS_12regex_traitsIcEEE21__start_matching_listEb.cold.1 __ZNSt3__111basic_regexIcNS_12regex_traitsIcEEE21__start_matching_listEb.cold.2 __ZN4dmlc18TemporaryDirectory9IsSymlinkERKNSt3__112basic_stringIcNS1_11char_traitsIcEENS1_9allocatorIcEEEE.cold.1 GCC_except_table4 GCC_except_table5 GCC_except_table7 GCC_except_table8 GCC_except_table9 GCC_except_table10 GCC_except_table11 GCC_except_table12 GCC_except_table13 GCC_except_table15 GCC_except_table17 GCC_except_table19 GCC_except_table20 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__ZN7xgboost6common11ParallelForImZNKS0_9TransformILb0EE9EvaluatorIZNS_3obj10RegLossObjINS5_16PseudoHuberErrorEE13PredTransformEPNS_16HostDeviceVectorIfEEEUlmNS0_4SpanIfLm18446744073709551615EEEE_E9LaunchCPUIJSA_EEEvSE_DpPT_EUlmE_EEvT_mT0_ _.omp_outlined..124 __ZN4dmlc12OMPException3RunIZNK7xgboost6common9TransformILb0EE9EvaluatorIZNS2_3obj10RegLossObjINS7_16PseudoHuberErrorEE13PredTransformEPNS2_16HostDeviceVectorIfEEEUlmNS3_4SpanIfLm18446744073709551615EEEE_E9LaunchCPUIJSC_EEEvSG_DpPT_EUlmE_JmEEEvT_DpT0_ __ZNSt3__110__function6__funcIN7xgboost3obj3$_4ENS_9allocatorIS4_EEFPNS2_11ObjFunctionEvEED1Ev __ZNSt3__110__function6__funcIN7xgboost3obj3$_4ENS_9allocatorIS4_EEFPNS2_11ObjFunctionEvEED0Ev __ZNKSt3__110__function6__funcIN7xgboost3obj3$_4ENS_9allocatorIS4_EEFPNS2_11ObjFunctionEvEE7__cloneEv __ZNKSt3__110__function6__funcIN7xgboost3obj3$_4ENS_9allocatorIS4_EEFPNS2_11ObjFunctionEvEE7__cloneEPNS0_6__baseIS9_EE 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__ZNK7xgboost6common9TransformILb0EE9EvaluatorIZNS_3obj10RegLossObjINS4_11LogisticRawEE11GetGradientERKNS_16HostDeviceVectorIfEERKNS_8MetaInfoEiPNS8_INS_6detail20GradientPairInternalIfEEEEEUlmNS0_4SpanIfLm18446744073709551615EEENSK_ISH_Lm18446744073709551615EEENSK_IKfLm18446744073709551615EEESO_SO_E_E10LaunchCUDAILPv0EJS9_SI_SA_SA_SA_EEEvSP_DpPT0_ __ZN7xgboost6common11ParallelForImZNKS0_9TransformILb0EE9EvaluatorIZNS_3obj10RegLossObjINS5_11LogisticRawEE11GetGradientERKNS_16HostDeviceVectorIfEERKNS_8MetaInfoEiPNS9_INS_6detail20GradientPairInternalIfEEEEEUlmNS0_4SpanIfLm18446744073709551615EEENSL_ISI_Lm18446744073709551615EEENSL_IKfLm18446744073709551615EEESP_SP_E_E9LaunchCPUIJSA_SJ_SB_SB_SB_EEEvSQ_DpPT_EUlmE_EEvT_mT0_ _.omp_outlined..128 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__ZNSt3__16threadC2IRZN4dmlc12ThreadedIterINS2_4data17RowBlockContainerIyiEEE4InitENS_8functionIFbPPS6_EEENS8_IFvvEEEEUlvE_JEvEEOT_DpOT0_.cold.2 __ZNSt3__1L14__thread_proxyINS_5tupleIJNS_10unique_ptrINS_15__thread_structENS_14default_deleteIS3_EEEEZN4dmlc12ThreadedIterINS7_4data17RowBlockContainerIyiEEE4InitENS_8functionIFbPPSB_EEENSD_IFvvEEEEUlvE_EEEEEPvSM_.cold.1 __ZN4dmlc12ThreadedIterINS_4data17RowBlockContainerIyiEEED2Ev.cold.1 __ZN4dmlc4data11DiskRowIterIjxE12TryLoadCacheEv.cold.1 __ZN4dmlc4data11DiskRowIterIjxE12TryLoadCacheEv.cold.2 __ZNSt3__16threadC2IRZN4dmlc12ThreadedIterINS2_4data17RowBlockContainerIjxEEE4InitENS_8functionIFbPPS6_EEENS8_IFvvEEEEUlvE_JEvEEOT_DpOT0_.cold.1 __ZNSt3__16threadC2IRZN4dmlc12ThreadedIterINS2_4data17RowBlockContainerIjxEEE4InitENS_8functionIFbPPS6_EEENS8_IFvvEEEEUlvE_JEvEEOT_DpOT0_.cold.2 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__ZNSt3__16threadC2IRZN4dmlc12ThreadedIterINS_6vectorINS2_4data17RowBlockContainerIyfEENS_9allocatorIS7_EEEEE4InitENS_8functionIFbPPSA_EEENSC_IFvvEEEEUlvE_JEvEEOT_DpOT0_.cold.1 __ZNSt3__16threadC2IRZN4dmlc12ThreadedIterINS_6vectorINS2_4data17RowBlockContainerIyfEENS_9allocatorIS7_EEEEE4InitENS_8functionIFbPPSA_EEENSC_IFvvEEEEUlvE_JEvEEOT_DpOT0_.cold.2 __ZNSt3__1L14__thread_proxyINS_5tupleIJNS_10unique_ptrINS_15__thread_structENS_14default_deleteIS3_EEEEZN4dmlc12ThreadedIterINS_6vectorINS7_4data17RowBlockContainerIyfEENS_9allocatorISC_EEEEE4InitENS_8functionIFbPPSF_EEENSH_IFvvEEEEUlvE_EEEEEPvSQ_.cold.1 __ZN4dmlc12ThreadedIterINSt3__16vectorINS_4data17RowBlockContainerIyfEENS1_9allocatorIS5_EEEEED2Ev.cold.1 __ZN4dmlc4data14TextParserBaseIjiEC2EPNS_10InputSplitEi.cold.1 __ZN4dmlc4data14TextParserBaseIjiED2Ev.cold.1 __ZN4dmlc4data14TextParserBaseIjiE8FillDataEPNSt3__16vectorINS0_17RowBlockContainerIjiEENS3_9allocatorIS6_EEEE.cold.1 __ZN4dmlc4data14TextParserBaseIjiE8FillDataEPNSt3__16vectorINS0_17RowBlockContainerIjiEENS3_9allocatorIS6_EEEE.cold.2 __ZN4dmlc4data14TextParserBaseIyiEC2EPNS_10InputSplitEi.cold.1 __ZN4dmlc4data14TextParserBaseIyiED2Ev.cold.1 __ZN4dmlc4data14TextParserBaseIyiE8FillDataEPNSt3__16vectorINS0_17RowBlockContainerIyiEENS3_9allocatorIS6_EEEE.cold.1 __ZN4dmlc4data14TextParserBaseIyiE8FillDataEPNSt3__16vectorINS0_17RowBlockContainerIyiEENS3_9allocatorIS6_EEEE.cold.2 __ZN4dmlc4data14TextParserBaseIjxEC2EPNS_10InputSplitEi.cold.1 __ZN4dmlc4data14TextParserBaseIjxED2Ev.cold.1 __ZN4dmlc4data14TextParserBaseIjxE8FillDataEPNSt3__16vectorINS0_17RowBlockContainerIjxEENS3_9allocatorIS6_EEEE.cold.1 __ZN4dmlc4data14TextParserBaseIjxE8FillDataEPNSt3__16vectorINS0_17RowBlockContainerIjxEENS3_9allocatorIS6_EEEE.cold.2 __ZN4dmlc4data14TextParserBaseIyxEC2EPNS_10InputSplitEi.cold.1 __ZN4dmlc4data14TextParserBaseIyxED2Ev.cold.1 __ZN4dmlc4data14TextParserBaseIyxE8FillDataEPNSt3__16vectorINS0_17RowBlockContainerIyxEENS3_9allocatorIS6_EEEE.cold.1 __ZN4dmlc4data14TextParserBaseIyxE8FillDataEPNSt3__16vectorINS0_17RowBlockContainerIyxEENS3_9allocatorIS6_EEEE.cold.2 __ZN4dmlc6Stream6CreateEPKcS2_b.cold.1 __ZN4dmlc10SeekStream13CreateForReadEPKcb.cold.1 __ZN4dmlc2io18ThreadedInputSplitC2EPNS0_14InputSplitBaseEm.cold.1 __ZN4dmlc2io18ThreadedInputSplitC2EPNS0_14InputSplitBaseEm.cold.2 __ZNSt3__16threadC2IRZN4dmlc12ThreadedIterINS2_2io14InputSplitBase5ChunkEE4InitENS_8functionIFbPPS6_EEENS8_IFvvEEEEUlvE_JEvEEOT_DpOT0_.cold.1 __ZNSt3__16threadC2IRZN4dmlc12ThreadedIterINS2_2io14InputSplitBase5ChunkEE4InitENS_8functionIFbPPS6_EEENS8_IFvvEEEEUlvE_JEvEEOT_DpOT0_.cold.2 __ZNSt3__1L14__thread_proxyINS_5tupleIJNS_10unique_ptrINS_15__thread_structENS_14default_deleteIS3_EEEEZN4dmlc12ThreadedIterINS7_2io14InputSplitBase5ChunkEE4InitENS_8functionIFbPPSB_EEENSD_IFvvEEEEUlvE_EEEEEPvSM_.cold.1 __ZN4dmlc12ThreadedIterINS_2io14InputSplitBase5ChunkEED2Ev.cold.1 __ZN4dmlc2io16CachedInputSplit14InitCachedIterEv.cold.1 __ZN4dmlc2io16CachedInputSplit14InitCachedIterEv.cold.2 __ZN4dmlc2io16CachedInputSplit15InitPreprocIterEv.cold.1 __ZN4dmlc2io16CachedInputSplit15InitPreprocIterEv.cold.2 __ZN4dmlc2io23IndexedRecordIOSplitter13ReadIndexFileEPNS0_10FileSystemERKNSt3__112basic_stringIcNS4_11char_traitsIcEENS4_9allocatorIcEEEE.cold.1 __ZN4dmlc2io14InputSplitBase17InitInputFileInfoERKNSt3__112basic_stringIcNS2_11char_traitsIcEENS2_9allocatorIcEEEEb.cold.1 __ZN4dmlc2io14InputSplitBase17InitInputFileInfoERKNSt3__112basic_stringIcNS2_11char_traitsIcEENS2_9allocatorIcEEEEb.cold.2 __ZN4dmlc5SplitERKNSt3__112basic_stringIcNS0_11char_traitsIcEENS0_9allocatorIcEEEEc.cold.1 __ZNSt3__111basic_regexIcNS_12regex_traitsIcEEE21__start_matching_listEb.cold.1 __ZNSt3__111basic_regexIcNS_12regex_traitsIcEEE21__start_matching_listEb.cold.2 __ZN4dmlc18TemporaryDirectory9IsSymlinkERKNSt3__112basic_stringIcNS1_11char_traitsIcEENS1_9allocatorIcEEEE.cold.1 GCC_except_table4 GCC_except_table6 GCC_except_table8 GCC_except_table9 GCC_except_table10 GCC_except_table11 GCC_except_table13 GCC_except_table14 GCC_except_table15 GCC_except_table16 GCC_except_table17 GCC_except_table18 GCC_except_table19 GCC_except_table20 GCC_except_table22 GCC_except_table23 GCC_except_table25 GCC_except_table27 GCC_except_table29 GCC_except_table30 GCC_except_table33 GCC_except_table34 GCC_except_table35 GCC_except_table36 GCC_except_table37 GCC_except_table38 GCC_except_table39 GCC_except_table40 GCC_except_table41 GCC_except_table42 GCC_except_table43 GCC_except_table44 GCC_except_table45 GCC_except_table46 GCC_except_table47 GCC_except_table49 GCC_except_table50 GCC_except_table51 GCC_except_table52 GCC_except_table53 GCC_except_table54 GCC_except_table55 GCC_except_table56 GCC_except_table57 GCC_except_table58 GCC_except_table59 GCC_except_table60 GCC_except_table61 GCC_except_table62 GCC_except_table63 GCC_except_table64 GCC_except_table65 GCC_except_table66 GCC_except_table67 GCC_except_table68 GCC_except_table69 GCC_except_table70 GCC_except_table71 GCC_except_table72 GCC_except_table74 GCC_except_table76 GCC_except_table77 GCC_except_table78 GCC_except_table79 GCC_except_table80 GCC_except_table81 GCC_except_table82 GCC_except_table83 GCC_except_table84 GCC_except_table86 GCC_except_table88 GCC_except_table89 GCC_except_table90 GCC_except_table91 GCC_except_table92 GCC_except_table93 GCC_except_table94 GCC_except_table97 GCC_except_table98 GCC_except_table110 GCC_except_table112 GCC_except_table113 GCC_except_table114 GCC_except_table115 GCC_except_table116 GCC_except_table127 GCC_except_table131 GCC_except_table132 GCC_except_table141 GCC_except_table142 GCC_except_table143 GCC_except_table144 GCC_except_table145 GCC_except_table146 GCC_except_table147 GCC_except_table150 GCC_except_table176 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